i 

Responses to Significant Comments on the 

2012 Proposed Rule on the 

National Ambient Air Quality Standards 

for Particulate Matter 

(June 29, 2012; 77 FR 38890) 

Docket Number EPA-HQ-OAR-2007-0492

U.S. Environmental Protection Agency 

December 2012 

 
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ii 

Table of Contents 

I. INTRODUCTION ............................................................................................................................................ I-1

II. RESPONSES TO SIGNIFICANT COMMENTS ON PROPOSED PRIMARY PM2.5 STANDARDS ... II-1

A. GENERAL COMMENTS ON PROPOSED PRIMARY PM2.5 STANDARDS ............................................................ II‐1

B. SPECIFIC COMMENTS ON PROPOSED PRIMARY PM2.5 STANDARDS.............................................................. II‐1

1. Need to Revise Current Standards ............................................................................................................. II-1

2. Indicator .................................................................................................................................................. II-44

3. Averaging Time ........................................................................................................................................ II-46

4. Form ........................................................................................................................................................ II-47

5. Level ........................................................................................................................................................ II-52

C. SPECIFIC COMMENTS ON THE QUANTITATIVE HEALTH RISK ASSESSMENT............................................... II‐90

D. SPECIFIC COMMENTS RELATED TO DATA HANDLING (APPENDIX N)........................................................ II‐99

1. Identifying PM2.5 data “appropriate” for NAAQS comparisons ............................................................. II-99

2. Procedures for combining data for design value computations ............................................................ II-100

3. ADDITIONAL PM2.5 DATA SUBSTITUTION TESTS ...................................................................................... II‐101

4. SEASONAL SAMPLING SPECIAL 98TH PERCENTILE CONCENTRATION IDENTIFICATION PROCEDURE........... II‐103

E. SPECIFIC COMMENTS RELATED TO THE AQI FOR PM2.5 .......................................................................... II‐104

III. RESPONSES TO SIGNIFICANT COMMENTS ON PRIMARY PM10 STANDARD ....................... III-1

F. COMMENTS FROM GROUPS SUPPORTING RETENTION OF THE PRIMARY PM10 STANDARD ......................... III‐1

G. COMMENTS FROM GROUPS SUPPORTING REVISION OF THE PRIMARY PM10 STANDARD ............................ III‐4

IV. RESPONSES TO SIGNIFICANT COMMENTS ON SECONDARY PM STANDARDS ................. IV-1

A. GENERAL COMMENTS ON PROPOSED SECONDARY PM STANDARDS ......................................................... IV‐1

B. SPECIFIC COMMENTS ON PROPOSED SECONDARY PM STANDARD TO PROTECT VISIBILITY ...................... IV‐1

1. Indicator ................................................................................................................................................... IV-2

2. Averaging Time ....................................................................................................................................... IV-12

3. Form ....................................................................................................................................................... IV-18

4. Level ....................................................................................................................................................... IV-19

5. Specific Comments on Visibility Preference Studies ............................................................................... IV-28

6. Need for a Distinct Secondary Standard ................................................................................................ IV-43

7. Specific Comments on Surrogacy Analysis ............................................................................................. IV-47

8. Legal Issues ............................................................................................................................................ IV-49

9. Other Issues ............................................................................................................................................ IV-56

C. SPECIFIC COMMENTS ON PROPOSED SECONDARY PM STANDARDS FOR NON-VISIBILITY WELFARE EFFECTS

IV‐59

V. RESPONSES TO SIGNIFICANT COMMENTS ON AMENDMENTS TO AMBIENT MONITORING 

AND REPORTING REQUIREMENTS ............................................................................................................... V-1

A. COMMENTS ON GENERAL ISSUES FOR REFERENCE, EQUIVALENT, OR APPROVED REGIONAL METHODS .... V‐1

B. COMMENTS ON USE OF CSN AND IMPROVE METHODS TO PROVIDE SPECIATION DATA USED IN THE 

PROPOSED NEW SECONDARY PM2.5 VISIBILITY INDEX NAAQS................................................................... V‐3

C. COMMENTS ON THE TERMINOLOGY CHANGES............................................................................................ V‐5

D. COMMENTS ON REVOKING USE OF POPULATION-ORIENTED AS A CONDITION FOR COMPARABILITY OF PM2.5

MONITORING SITES TO THE NAAQS .......................................................................................................... V‐5

E. COMMENTS ON APPLICABILITY OF MICRO- AND MIDDLE SCALE MONITORING SITES TO THE ANNUAL PM2.5

NAAQS.................................................................................................................................................... V‐11

F. COMMENTS ON THE ADDITION OF PM2.5 MONITORS TO THE NEAR-ROAD MONITORING STATIONS. ............ V‐16

G. COMMENTS ON REVOKING PM10-2.5SPECIATION REQUIREMENTS AT NCORE SITES.................................. V‐47

H. COMMENTS ON THE NETWORK DESIGN FOR THE PROPOSED SECONDARY PM2.5 VISIBILITY INDEX............. V‐47

I. COMMENTS ON THE USE OF PM2.5 CONTINUOUS FEMS AT SLAMS.......................................................... V‐50

J. COMMENTS ON WEIGHT OF EVIDENCE APPROACH IN THE REVISIONS TO THE QUALITY ASSURANCE 

REQUIREMENTS FOR SLAMS, SPMS, AND PSD. ...................................................................................... V‐53
iii 

K. COMMENTS ON QUALITY ASSURANCE REQUIREMENTS FOR THE CHEMICAL SPECIATION NETWORK. ...... V‐55

L. COMMENTS ON WAIVER FOR WIDER SPACING OF COLLOCATED MONITORS ............................................ V‐55

M. ADDITIONAL QA RELATED COMMENTS NOT SPECIFICALLY RELATED TO PROPOSED CHANGES TO APPENDIX 

A............................................................................................................................................................... V‐55

N. COMMENTS ON PROBE AND MONITORING PATH SITING CRITERIA ........................................................... V‐56

O. COMMENTS ON THE ANNUAL MONITORING NETWORK PLAN AND PERIODIC ASSESSMENT ...................... V‐58

P. COMMENTS ON OPERATING SCHEDULES................................................................................................... V‐59

Q. COMMENTS ON DATA REPORTING AND CERTIFICATION FOR CSN AND IMPROVE DATA........................ V‐60

R. COMMENTS ON THE REQUIREMENTS FOR ARCHIVING FILTERS................................................................. V‐62

S. FUNDING AND RESOURCES ISSUES ASSOCIATED WITH AMBIENT AIR MONITORING REQUIREMENTS........ V‐62

VI. RESPONSES TO SIGNIFICANT COMMENTS ON IMPLEMENTATION ..................................... VI-1

A. SPECIFIC COMMENTS RELATED TO DESIGNATION OF AREAS..................................................................... VI‐1

B. SPECIFIC COMMENTS RELATED TO SECTION 110(A)(2) INFRASTRUCTURE SIP REQUIREMENTS ................ VI‐6

C. SPECIFIC COMMENTS RELATED TO IMPLEMENTING THE PROPOSED REVISED PRIMARY ANNUAL PM2.5

NAAQS IN NONATTAINMENT AREAS........................................................................................................ VI‐9

D. SPECIFIC COMMENTS ON PREVENTION OF SIGNIFICANT DETERIORATION AND NONATTAINMENT NEW 

SOURCE REVIEW...................................................................................................................................... VI‐11

E. NONATTAINMENT NEW SOURCE REVIEW ................................................................................................ VI‐25

F. OTHER NSR IMPLEMENTATION COMMENTS ............................................................................................ VI‐25

G. SPECIFIC COMMENTS RELATED TO TRANSPORTATION CONFORMITY ...................................................... VI‐27

H. SPECIFIC COMMENTS RELATED TO EXCEPTIONAL EVENTS...................................................................... VI‐29

VII. RESPONSES TO SIGNIFICANT COMMENTS ON LEGAL, ADMINISTRATIVE, PROCEDURAL, 

OR MISPLACED COMMENTS ....................................................................................................................... VII-1

A. LEGAL ISSUES ........................................................................................................................................... VII‐1

B. ADMINISTRATIVE/PROCEDURAL ISSUES ................................................................................................... VII‐4

C. MISPLACED COMMENTS ........................................................................................................................... VII‐6

REFERENCES 

APPENDIX A: Provisional Science Assessment 
iv 

List of Acronyms 

The following acronyms have been used for the sake of brevity in this document: 

AAM Alliance of Automobile Manufacturers 

AAMMS Ambient Air Monitoring and Methods Subcommittee 

AASHTO American Association of State Highway and Transportation Officials 

ACC American Chemistry Council 

ACS American Cancer Society 

AFBF American Farm Bureau Federation 

AFPM American Fuel & Petroleum Manufacturers 

AHA American Heart Association 

ALA American Lung Association 

AMC Appalachian Mountain Club 

APHEA Air Pollution and Health: A European Approach 

APHENA Air Pollution and Health: A European and North American Approach 

API American Petroleum Institute 

AQCD Air Quality Criteria Document 

AQI Air Quality Index 

AQMD Air Quality Management District 

AQS Air Quality System 

ARMs Approved Regional Methods 

ARS Air Resource Specialists 

ATS American Thoracic Society 

BC British Columbia 

CAA Clean Air Act 

CAPs Concentrated ambient particles 

CASAC Clean Air Scientific Advisory Committee 

CBD Center for Biological Diversity 

CBSA Core Based Statistical Area 

CDC Centers for Disease Control 

CF Cystic fibrosis 

CFR Code of Federal Regulations 

CHPAC Children’s Health Protection Advisory Committee 

CI Confidence intervals 

CPC Coarse Particulate Matter Coalition 

CPL Candidate Protection Level 

C-R Concentration-response 

CRA Charles River Associates 

CSA Combined Statistical Area 

CSN Chemical Speciation Network 

CVD Cardiovascular disease 

DC District of Columbia 

DEC Department of Environmental Conservation 

DEQ Department of Environmental Quality 

DOH Department of Health 
v 

DOI U.S. Department of the Interior 

DPHE Department of Public Health and Environment 

df Degrees of freedom 

dv Deciview 

DV Design value 

EC Elemental carbon 

ED Emergency department 

EPA U.S. Environmental Protection Agency 

EPRI Electric Power Research Institute 

FEM Federal Equivalent Method 

FEV1 Forced expiratory volume in one second, volume of air exhaled in first 

second of exhalation 

FR Federal Register 

FRM Federal Reference Method 

GMA Georgia Mining Association 

IARC International Agency Research on Cancer 

IMPROVE Interagency Monitoring of Protected Visual Environment 

IHD Ischemic heart disease 

ISA Integrated Science Assessment 

ISEE International Society for Environmental Epidemiology 

IUGR Intrauterine growth retardation 

Km Kilometer 

LML Lowest measured level 

μg Microgram 

μm micrometer, micron 

μg/m3

 microgram per cubic meter 

MCAPS Medicare Air Pollution Study 

Mm-1 Inverse megameters, 1/(million meters) 

MSA Metropolitan Statistical Area 

NAAQS National ambient air quality standards 

NACAA National Association of Clean Air Agencies 

NAM National Association of Manufacturers 

NCBA National Cattlemen’s Beef Association 

NCore National Core Monitoring Network 

NEDA/CAP National Environmental Development Association/Clean Air Project 

NESCAUM Northeast States Coordinated Air Use Management 

NMA National Mining Association 

NMMAPS National Morbidity, Mortality, and Air Pollution Study 

NO2 Nitrogen dioxide 

NPCA National Parks Conservation Association 

NSSGA National Stone, Sand, & Gravel Association 

NTAA National Tribal Air Association 

O3 Ozone 

OC Organic carbon 

OM Organic mass 

PA Policy Assessment 
vi 

PACF Partial autocorrelation function 

PM Particulate matter 

PM2.5 In general terms, particulate matter with an aerodynamic diameter less 

than or equal to a nominal 2.5 μm; a measurement of fine particles 

PM10 In general terms, particulate matter with an aerodynamic diameter less 

than or equal to a nominal 10 μm; a measurement of thoracic particles 

(i.e., that subset of inhalable particles thought small enough to penetrate 

beyond the larynx into the thoracic region of the respiratory system 

PM10-2.5 In general terms, particulate matter with an aerodynamic diameter less 

than or equal to a nominal 10 μm and greater than a nominal 2.5 μm; a 

measurement of thoracic coarse particles or the coarse fraction of PM10 

PRB Policy-relevant background 

PSR Physicians for Social Responsibility 

QA Quality assurance 

RA Risk Assessment 

REA Risk and Exposure Assessment 

RH Relative humidity 

RR Relative risk 

RTC Responses to Comments 

SANDWICH Sulfate, Adjusted Nitrate, Derived Water, Inferred Carbonaceous mass 

approacH 

SD Standard deviation 

SES Socioeconomic status 

SHS Secondhand smoke 

SIP State Implementation Plan 

SLAMS State and local air monitoring stations 

SO2 Sulfur dioxide 

TCEQ Texas Commission on Environmental Quality 

TSP Total suspended particulate 

UARG Utility Air Regulatory Group 

UFPs Ultrafine particles 

UFVA Urban Focused Visibility Assessment 

VAQ Visual air quality 

WESTAR Western States Air Resources Council 

WHI Women’s Health Initiative 

WHO World Health Organization 

 
vii 

Frequently Cited Documents 

The following documents are frequently cited throughout the EPA’s response to comments 

Integrated Science Assessment (ISA) 

Integrated Science Assessment for Particulate Matter: Final Report. National Center for 

Environmental Assessment-RTP Division, Office of Research and Development, 

Research Triangle Park, NC. EPA/600/R-08/139F. December 2009. Available: 

http://www.epa.gov/ttn/naaqs/standards/pm/s_pm_2007_isa.html. 

Risk Assessment (RA)

Quantitative Health Risk Assessment for Particulate Matter – Final Report. Office of Air 

Quality Planning and Standards, U.S. Environmental Protection Agency, Research 

Triangle Park, NC. EPA-452/R-10-005. June 2010. Available: 

http://www.epa.gov/ttn/naaqs/standards/pm/s_pm_2007_risk.html. 

Urban-Focused Visibility Assessment (UFVA)

Particulate Matter Urban-Focused Visibility Assessment – Final Report. Office of Air 

Quality Planning and Standards, U.S. Environmental Protection Agency, Research 

Triangle Park, NC. EPA-452/R-10-004. July 2010. Available: 

http://www.epa.gov/ttn/naaqs/standards/pm/s_pm_2007_risk.html. 

Policy Assessment (PA) 

Policy Assessment for the Review of the Particulate Matter National Ambient Air Quality 

Standards. Office of Air Quality Planning and Standards, U.S. Environmental Protection 

Agency, Research Triangle Park, NC. EPA 452/R-11-003. April 2011. Available: 

http://www.epa.gov/ttn/naaqs/standards/pm/s_pm_2007_pa.html. 

Proposal 

National Ambient Air Quality Standards for Particulate Matter: Proposed Rule. 77 FR 

38890, June 29, 2012 

Preamble to the final rule 

Preamble to the Final Rule on the Review of the National Ambient Air Quality Standards 

for Particulate Matter; signed December 14, 2012
 

I-1 

I. INTRODUCTION 

This document, together with the preamble to the final rule on the review of the national ambient 

air quality standards (NAAQS) for particulate matter (PM), presents the responses of the Environmental 

Protection Agency (EPA) to the more than 230,000 public comments received on the 2012 PM NAAQS 

proposal notice (77 FR 38890, June 29, 2012). The EPA has addressed all significant issues raised in the 

public comments. 

Due to the large number of comments that addressed similar issues, as well as the volume of the 

comments received, this response-to-comments document does not generally cross-reference each 

response to the commenter(s) who raised the particular issue involved, although commenters are 

identified in some cases where they provided particularly detailed comments that were used by the EPA 

to frame the overall response on an issue. 

The responses presented in this document are intended to augment the responses to comments 

that appear in the preamble to the final rule or to address comments not discussed in that preamble. 

Although portions of the preamble to the final rule are paraphrased in this document where useful to add 

clarity to responses, the preamble itself remains the definitive statement of the rationale for the revisions 

to the standards adopted in the final rule. 

In many instances, particular responses presented in this document include cross references to 

responses on related issues that are located either in the preamble to the PM NAAQS final rule, or in this 

Response to Comments (RTC) document. All issues on which the Administrator is taking final action in 

the PM NAAQS final rule are addressed in the PM NAAQS rulemaking record. 

Accordingly, this RTC document, together with the preamble to the PM NAAQS final rule and 

the information contained in the Integrated Science Assessment (ISA, U.S. EPA, 2009a), Risk and 

Exposure Assessments (REAs, U.S. EPA, 2010a; U.S. EPA, 2010b) and the Policy Assessment (PA, 

U.S. EPA, 2011a), should be considered collectively as the EPA’s response to all of the significant 

comments submitted on the EPA’s 2012 PM NAAQS proposed rule. This document incorporates 

directly or by reference the significant public comments addressed in the preamble to the PM NAAQS 

final rule as well as other significant public comments that were submitted on the proposed rule. 

Consistent with the final decisions presented in the notice of final rulemaking, comments on the 

primary standards for fine particles and for thoracic coarse particles are addressed separately in this 

document in sections II and III, respectively. Comments on secondary standards for fine and coarse 

particles are addressed below in section IV. Comments on related monitoring and implementation issues 

are addressed below in sections V and VI, respectively. Section VII includes responses to legal, 

administrative, procedural, or misplaced comments. 

In the PM NAAQS proposal, the EPA recognized that there were a number of new scientific 

studies on the health effects of PM that had been published recently and, therefore, were not included in 

the ISA (77 FR at 383899, June 29, 2012). The EPA committed to conduct a review and assessment of 

any significant “new” studies, including studies submitted during the public comment period. The 

purpose of this review was to ensure that the Administrator was fully aware of the new science before 

making a final decision on whether to revise the current PM NAAQS. The EPA screened and surveyed 

the recent literature, including studies submitted during the public comment period, and conducted a 

provisional assessment that places the results of those studies of potentially greatest policy relevance in 

the context of the findings of the ISA. This provisional assessment, entitled Provisional Assessment of 

Recent Studies on Health Effects of Particulate Matter Exposure (US EPA, 2012a), is included as 
 

I-2 

Appendix A of this document. This RTC document is part of the basis for the EPA’s responses to 

specific public comments on the “new” science. 
II-1 

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

STANDARDS 

A. General Comments on Proposed Primary PM2.5 Standards 

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

general in nature, basically expressing one of two substantively different views: (1) support for 

revisions to the primary standards to be more public health-protective or (2) opposition to any 

revision of the current PM2.5 standards. Many of these commenters simply expressed their views 

without stating any rationale, while others gave general reasons for their views but without 

reference to the factual evidence or rationale presented in the proposal notice as a basis for the 

Agency’s proposed decision. The preamble to the final rule in its entirety presents the Agency’s 

response to these very general views. 

Specific public comments on a range of issues related to the proposed primary PM2.5

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

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

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

III.E.4.c of the preamble discuss significant comments addressing the four basic elements of the 

standard: indicator, averaging time, form, and level, respectively. Significant comments on the 

revised Air Quality Index (AQI) for PM2.5 are discussed in section V of the preamble. Significant 

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

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

raised in the public comments on these issues. 

B. Specific Comments on Proposed Primary PM2.5 Standards 

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

to revise the level and form of the primary annual PM2.5 standard in conjunction with retaining 

the current 24-hour standard. Below, the EPA provides more detailed responses to the full range 

of significant issues raised in these comments. 

1. Need to Revise Current Standards 

This section responds to more detailed comments that either support or oppose any 

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

discussed in section III.D.2 of the preamble to the final rule and discussed more fully below. 

Significant comments on specific long- and short-term exposure studies that relate to 

consideration of the appropriate level of the annual and 24-hour PM2.5 standards are addressed in 

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

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

sections III.E.4.c of the preamble to the final rule, the EPA provides the following responses to 

specific issues related to the need to revise the fine particle standards. 

a. Support for Revising the Current Standards 

Many public commenters asserted that the current PM2.5 standards are insufficient to 
II-2 

protect public health with an adequate margin of safety and that revisions to the standards are 

therefore appropriate within the meaning of section 109 (d) of the Act, indeed necessitated. 

Among those calling for revisions to the current standards were the Children’s Health Protection 

Advisory Committee (CHPAC); major medical and public health groups including the American 

Heart Association (AHA), American Lung Association (ALA), American Public Health 

Association (APHA), American Thoracic Society (ATS); the Physicians for Social 

Responsibility (PSR); the International Society for Environmental Epidemiology (ISEE); major 

environmental groups such as the Clean Air Council, Clean Air Task Force, Earthjustice, 

Environmental Defense Fund (EDF), National Resources Defense Council (NRDC), and Sierra 

Club; many environmental justice organizations as well as medical doctors, academic 

researchers, health professionals, and many private citizens. 

All of these medical and public health commenters stated that the current PM2.5 standards 

need to be revised, and that even more protective standards than those proposed by the EPA are 

needed to adequately protect public health, particularly for at-risk populations. Many 

environmental justice organizations and individual commenters also expressed such views. 

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

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

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

current PM2.5 standards, as did five state attorneys general (Schneiderman et al., 2012) and the 

National Tribal Air Association (NTAA). 

(1) Comment: In general, all of these commenters agreed on the importance of results from 

the large body of scientific studies and technical analyses presented and discussed in the 

Integrated Science Assessment (ISA), the Risk Assessment (RA), and the Policy 

Assessment (PA) and on the need to revise the PM2.5 standards as articulated in section 

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

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

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

protection for at-risk populations. These commenters generally concluded that the body 

of evidence assessed in the ISA was stronger and more compelling than in the last 

review. In addition, these commenters generally placed much weight on the Clean Air 

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

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

increased public health protection. In arguing for more health protective standards, these 

commenters expressed the following specific views:

 Multiple, multi-city studies show clear evidence of premature mortality, 

cardiovascular and respiratory harm, as well as reproductive and developmental 

effects at ambient concentrations “far below the level of the current standard” (ALA, 

et al., 2012, p. 39). Specific studies cited by commenters included: 

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

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

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

2004) studies. 
II-3 

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

study of premature mortality in older adults (Eftim et al., 2008) and the 

Women’s Health Initiative (WHI) study of cardiovascular morbidity and 

mortality effects in women (Miller et al., 2007) providing stronger evidence of 

mortality and morbidity effects associated with long-term PM2.5 exposures at 

lower concentrations than had previously been observed, including studies of 

effects in at-risk populations. 

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

mortality and morbidity effects at concentrations below the level of the 

current 24-hour PM2.5 standard. Specifically, these commenters made note of 

multi-city studies of premature mortality (Zanobetti and Schwartz, 2009) and 

increased hospitalizations for cardiovascular and respiratory-related effects in 

older adults (Bell et al., 2008). 

 Single-city short-term PM2.5 studies “provide valuable information regarding impacts 

on susceptible populations and on health risk in areas with high peak to mean 

concentration ratios” (ALA, et al., 2012, p. 65). 

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

review, in better understanding mechanisms by which PM2.5 may be causing the 

observed health effects, and in improving our understanding of at-risk populations. 

 The EPA’s quantitative risk assessment concluded that the risks estimated to remain 

when the current standards are met are large and important from a public health 

perspective and warrant increased protection. 

 PM2.5-related risks are likely larger than those estimated in the RA, in part because 

the EPA focused on limited study areas and health endpoints. Some commenters cited 

to a recent study based on 2005 air quality data. In this study, the EPA staff published 

estimates that “peg the annual toll from PM2.5 at 130,000 premature deaths each 

year”1

 (ALA et al., p. 5). Furthermore, “this analysis estimated a staggering 1.1 

million life years lost among people over age 65, accounting for 7 percent of life 

years lost in 2005 in this population of elderly Americans. Looking at it another way, 

this translates into an average shortened lifespan of 8.5 months per individual 

affected. Further, the analysis estimated 1,800 deaths among babies and infants 

attributable to PM air pollution.” Id.

 The EPA’s distributional statistical analysis of population-level data (i.e., health event 

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

statistical metric (e.g., mean) to consider in reaching decisions on the appropriate 

annual standard level. 

Response: The EPA generally agrees with these commenters’ conclusion regarding the 

need to revise the current suite of PM2.5 standards. The scientific evidence noted by these 

 

1

 Fann et al., 2012 
II-4 

commenters was generally the same as that assessed in the ISA and the PA, and the EPA 

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

standards, taken together, are not requisite to protect public health with an adequate 

margin of safety, and they need to be revised to provide increased protection. For reasons 

discussed in section III.E.4.c of the preamble to the final rule and in section II.B.5 below, 

however, the EPA disagrees with aspects of these commenters’ views on the level of 

protection that is appropriate. 

In addition, with regard to progress made to better understand mechanisms by which 

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

discussed the current scientific information related to potential modes of action (Chapter 

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

11 to 12). 

(2) Comment: With regard to the scope of the literature reviewed for PM2.5-related health 

effects, some commenters asserted that the EPA inappropriately narrowed the scope of 

the review by excluding a number of categories of relevant studies, specifically related to 

studies of diesel pollution and traffic-related pollution (ALA, et al., 2012, p. 17). These 

commenters argued that, based upon the exclusion of these types of studies, the ISA 

“came to the erroneous conclusion that the causal relationship between PM and cancer is 

merely suggestive. This conclusion does not square with the International Agency 

Research on Cancer (IARC) finding that diesel emissions are a known human carcinogen 

nor with the conclusions of the extended analyses of the [Harvard] Six Cities and ACS 

cohort studies that report positive and statistically significant associations between PM2.5

and lung cancer.” Id. 

Response: The EPA disagrees with these commenters’ views that diesel exhaust studies 

were excluded from the ISA and were not considered when making the causality 

determination for cancer, mutagenicity, and genotoxicity. As discussed in section 7.5 of 

the ISA, diesel exhaust studies were integrated within the broader body of scientific 

evidence that was considered in reaching the causality determination for these health 

endpoints. Additionally, as discussed in section 1.5.3 of the ISA, the evidence from diesel 

exhaust studies was also considered as part of the collective evidence evaluated when 

making determinations for other, noncancer health outcomes (e.g., cardiovascular and 

respiratory effects). Specifically, when evaluating this evidence, the ISA focused on 

understanding the effects of diesel exhaust particles. It is important to recognize that the 

ISA focused on diesel exhaust studies that evaluated exposures that were relevant to 

ambient concentrations, i.e., “within one or two orders of magnitude of ambient PM 

concentrations” (U.S. EPA, 2009a, section 1.3). The causal determination for cancer, 

mutagenicity, and genotoxicity presented in the ISA represents an integration of 

experimental and observational evidence of exposures to ambient PM concentrations. 

The EPA fully considered the findings of studies that assessed these and other health 

effects associated with exposure to diesel particles in reaching causality determinations 

regarding health outcomes associated with PM2.5 exposures. 
II-5 

In developing the second draft ISA, the EPA reexamined the controlled human exposure 

and toxicological studies of fresh diesel and gasoline exhaust. This information, in 

addition to other considerations, supported a change in the causal determinations for 

ultrafine particles. Specifically, in reevaluating the causal determinations for short-term 

ultrafine particle exposures and cardiovascular and respiratory effects, the EPA changed 

the classification from “inadequate” to “suggestive” for both categories of health 

outcomes (Vandenberg, 2009, p. 3). CASAC agreed with the EPA’s rationale for revising 

these causal determinations (Samet, 2009f, pp. 2 and 10). 

With regard to traffic studies, the EPA disagrees with the commenters’ views that traffic 

studies that focused on exposure indicators such as distance to roadways should have 

been included in the ISA. These studies were excluded from consideration because they 

did not measure ambient concentrations of specific air pollutants, including PM2.5, but 

instead were studies evaluating exposure to the undifferentiated “traffic related air 

pollution” mixture (ALA et al., 2012, p.17) (U.S. EPA, 2009a, section 1.3). As a result, 

these studies do not add to the collective body of evidence on the relationship between 

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

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

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

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

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

standard was established, substantial new information regarding adverse health effects at 

lower concentrations supports setting a more protective standard (ALA et al, 2012, p. 23). 

Other commenters argued that revising the primary PM2.5 standards would be more 

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

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

1).

Response: In considering these comments, the EPA notes that the Administrator’s 

decision on setting an appropriate annual standard level is constrained by the provision of 

the CAA that requires that the primary NAAQS be requisite to protect public health with 

an adequate margin of safety. This requires that her judgment is to be based on an 

interpretation of the evidence that neither overstates nor understates the strength and 

limitations of the evidence, or the appropriate inferences to be drawn from the evidence. 

This is not the same legal framework that governs the standards set by the State of 

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

the WHO. For example, the California statute does not refer to setting a standard that is 

‘‘requisite’’ to protect, as that term is used in the CAA, and California, unlike EPA, may 

take economic impacts into consideration in setting air quality standards. In addition, as 

with the WHO guidelines, the standards appear to be more in the nature of goals as 

compared to binding requirements that must be met. 

As discussed in section III.E.4.d of the preamble for the final rule, the Administrator has 

considered the epidemiological and other scientific evidence, estimates of risk reductions 

associated with just meeting alternative standards, air quality analyses, related limitations 

and uncertainties, the advice of CASAC, and the extensive public comments on the 
II-6 

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

annual PM2.5 standard level, consistent with the requirements of the CAA. 

(4) Comment: Some of these commenters also identified “new” studies that were not 

included in the ISA as providing further support for the need to revise the PM2.5

standards. 

Response: In the proposal, the EPA recognized that there were a number of new scientific 

studies on the health effects of PM that had been published since the mid-2009 cutoff 

date for inclusion in the ISA (77 FR 38899). As discussed in section II.B.3 of the 

preamble to the final rule, the EPA conducted a provisional assessment of “new” science 

published since the close of the ISA including studies submitted to the EPA during the 

public comment period. The purpose of the provisional science assessment was to ensure 

that the Administrator was fully aware of the “new” science that has developed since 

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

NAAQS. 

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

limited to studies submitted during the public comment period, and conducted a 

provisional assessment (U.S. EPA, 2012b) that places the results of those studies of 

potentially greatest policy relevance in the context of the findings of the ISA (U.S. EPA, 

2009a). This provisional assessment, including a summary of the key conclusions is 

included in Appendix A to this RTC document. 

The provisional assessment found that the “new” studies expand the scientific 

information considered in the ISA and provide important insights on the relationship 

between PM exposure and health effects. The provisional assessment also found that 

“new” studies generally strengthen the evidence that long- and short-term exposures to 

fine particles are associated with a wide range of health effects (i.e. the strongest 

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

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

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

studies continue to link various health effects with a range of fine particle sources and 

components, the provisional assessment found that the results reported in “new” studies 

do not materially change any of the broad scientific conclusions regarding the health 

effects of PM exposure made in the ISA. 

As further noted in section II.B.3 of the preamble to the final rule, as in prior NAAQS 

reviews, the EPA is basing its decision in this review on studies and related information 

included in the ISA, RA, and PA, which have undergone CASAC and public review. The 

studies assessed in the ISA, and the integration of the scientific evidence presented in that 

document, have undergone extensive critical review by the EPA, CASAC, and the public 

during the development of the ISA. The rigor of that review makes these studies, and 

their integrative assessment, the most reliable source of scientific information on which 

to base decisions on the NAAQS. NAAQS decisions can have profound impacts on 

public health and welfare, and NAAQS decisions are based on studies that have been 

rigorously assessed in an integrative manner not only by the EPA but also by the 
II-7 

statutorily-mandated independent advisory committee, CASAC, and have been subjected 

as well to the public review that accompanies this process. As described above, the 

provisional assessment did not and could not provide that kind of in-depth critical review. 

This decision is consistent with the EPA’s practice in prior NAAQS reviews. Since the 

1970 amendments, the EPA has taken the view that NAAQS decisions are to be based on 

scientific studies and related information that have been assessed as a part of the pertinent 

air quality criteria. See e.g., 36 FR 8186 (April 30, 1971) (the EPA based original 

NAAQS for six pollutants on scientific studies discussed in air quality criteria documents 

and limited consideration of comments to those concerning validity of scientific basis); 

38 FR 25678, 25679 to 25680 (September 14, 1973) (the EPA revised air quality criteria 

for sulfur oxides to provide basis for reevaluation of secondary NAAQS). This 

longstanding interpretation was strengthened by new legislative requirements enacted in 

1977, which added section 109(d)(2) of the CAA concerning CASAC review of air 

quality criteria. The EPA has consistently followed this approach. 52 FR 24634, 24637 

(July 1, 1987) (after review by CASAC, the EPA issued a post-proposal addendum to the 

PM Air Quality Criteria Document (AQCD), to address certain new scientific studies not 

included in the 1982 AQCD); 61 FR 25566, 25568 (May 22, 1996) (after review by 

CASAC, the EPA issued a post-proposal supplement to the 1982 AQCD to address 

certain new health studies not included in the 1982AQCD or 1986 Addendum). The EPA 

reaffirmed this approach in its decision not to revise the ozone NAAQS in 1993, as well 

as in its final decision on the PM NAAQS in the 1997 and 2006 reviews. 58 FR 13008, 

13013 - 13014 (March 9, 1993) (ozone review); 62 FR 38652, 38662 (July 18, 1997) and 

71 FR 61141, 61148 -61149 (October 17, 2006) (PM reviews) (The EPA conducted a 

provisional assessment but based the final PM decisions on studies and related 

information included in the air quality criteria that had been reviewed by CASAC). 

As discussed in the EPA's 1993 decision not to revise the NAAQS for ozone, “new” 

studies may sometimes be of such significance that it is appropriate to delay a decision on 

revision of NAAQS and to supplement the pertinent air quality criteria so the “new” 

studies can be taken into account (58 FR at 13013 to 13014, March 9, 1993). In this 2012 

review of the PM NAAQS, the provisional assessment of recent studies concludes that, 

taken in context, the “new” information and findings do not materially change any of the 

broad scientific conclusions regarding the health effects of PM exposure made in the ISA 

(U.S. EPA, 2012b). For this reason, reopening the air quality criteria review would not be 

warranted even if there were time to do so under the court order governing the schedule 

for this rulemaking. Accordingly, the EPA is basing the final decisions in this review on 

the studies and related information included in the PM air quality criteria that have 

undergone CASAC and public review. The EPA will consider the “new” published 

studies for purposes of decision making in the next periodic review of the PM NAAQS, 

which will provide the opportunity to fully assess them through a more rigorous review 

process involving the EPA, CASAC, and the public. 

(5) Comment: Some commenters encouraged the EPA to consider emerging evidence for a 

broader range of health outcomes. For example, one commenter urged the EPA “to 

exercise a high level of vigilance in order to identify and act on additional peer-reviewed 
II-8 

studies that may strengthen a putative link between PM and diabetes and 

neurodegenerative diseases” (PSR, 2012, p. 7).

Response: The EPA agrees that additional research could expand our understanding of a 

broader range of health outcomes (e.g., central nervous system effects) and potential 

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

future health-related research, model development, and data collection activities that 

could provide important evidence for informing future PM NAAQS reviews (U.S. EPA, 

2011a, section 2.5). The EPA will consider all policy-relevant studies published in the 

peer-review literature, including “new” studies published since the close of the ISA in its 

next PM NAAQS review. 

b. Support for Retaining the Current Standards 

Another group of commenters opposed revising the current PM2.5 standards. These views 

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

representing a group of electric generating companies and organizations and several national 

trade associations; the American Petroleum Institute (API) representing more than 500 oil and 

natural gas companies; the National Association of Manufacturers (NAM), the American 

Chemistry Council (ACC), the American Fuel & Petroleum Manufacturers (AFPM), the Alliance 

of Automobile Manufacturers, and other manufacturing associations; the Electric Power 

Research Institute (EPRI); and the Texas Commission on Environmental Quality (Texas CEQ). 

These commenters generally mentioned many of the same studies that were cited by the 

commenters who supported revising the standards, as well as other studies, but highlighted 

different aspects of these studies in reaching substantially different conclusions about their 

strength and the extent to which progress has been made in reducing uncertainties in the 

evidence since the last review. Furthermore, they asserted that the evidence that has become 

available since the last review does not establish a more certain risk or a risk of effects that are 

significantly different in character to those that provided a basis for the current standards, nor 

does the evidence demonstrate that the risk to public health upon attainment of the current 

standards would be greater than was understood when the EPA established the current standards 

in 2006. 

These commenters generally expressed the view that the current standards provide the 

requisite degree of public health protection. In supporting their view, these commenters generally 

argued that the EPA’s conclusions are inconsistent with the current state of the science and 

questioned the underlying scientific evidence including the causal determinations reached in the 

ISA. More specifically, this group of commenters argued that: 

 the EPA did not apply its framework for causal determination consistently across 

studies or health outcomes and, in the process, the EPA relied on a selective group of 

long- and short-term exposure studies to reach conclusions regarding causality 

 toxicological and controlled human exposure studies do not provide supportive 

evidence that the health effects observed in epidemiological studies are biologically 

plausible 

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

NAAQS review completed in2006 
II-9 

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

current annual PM2.5 standard 

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

health risks associated with exposure to PM2.5 

These comments and other similar comments are addressed below. 

(1) Comment: Multiple commenters asserted that the EPA did not apply its framework for 

causal determinations consistently across studies or health outcomes (API, 2012, 

Attachment 1, p. 30).2

 These commenters further contended that the EPA relied on a 

selective group of long- and short-term PM2.5 exposure studies when making causality 

determinations in the ISA (ACC, 2012, Attachment A, pp. 1 to 2; API, 2012, pp. 18 to 

20; API, 2012, Attachment 1, p. 30; NAM et al., 2012, pp. 22 to 25; Texas CEQ, 2012, 

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

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

Response: The EPA disagrees with these commenters’ assertion that the EPA did not 

consistently apply the causality framework. The EPA’s evaluation of the scientific 

evidence and its application of the causal framework used in the current PM NAAQS 

review was the subject of exhaustive and detailed review by CASAC and the public. 

Prior to finalizing the ISA, two drafts were released for CASAC and public review to 

evaluate the scientific integrity of the documents. Evidence related to the substantive 

issues raised by CASAC and public commenters with regard to the content of the first 

and second draft ISAs were discussed at length during these public CASAC meetings and 

considered in developing the final ISA. CASAC supported the development of the EPA’s 

causality framework and its use in the current PM NAAQS review and concluded:

The five-level classification of strength of evidence for causal inference has been 

systematically applied; this approach has provided transparency and a clear 

statement of the level of confidence with regard to causation, and we recommend 

its continued use in future Integrated Science Assessments (Samet 2009f, p. 1).

The EPA disagrees with these commenters’ views on assessing the health effects 

evidence and on their conclusions regarding the causality determinations reached in the 

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

studies that reported results with statistical significance without regard to other 

considerations that are important in a comprehensive evaluation of the evidence. 

Specifically, the EPA recognizes the distinction between evaluation of the relative 

scientific quality of individual study results, and the evaluation of the pattern of results 

within the broader body of scientific evidence and considered both in reaching causality 

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

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

 

2

 The EPA notes that the same concerns about the causal determinations presented in the ISA were raised in 

comments to CASAC on the first and second draft ISAs (e.g., UARG, 2009; API, 2009; ACC, 2012, Appendix B). 

CASAC, therefore, had the opportunity to consider these comments as it reached consensus conclusions that the 

EPA had consistently and appropriately applied the causality framework, as well as its consensus agreement on the 

causality determinations themselves. 
II-10 

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

EPA, 2009a, section 1.5.3). 

Statistical significance is an indicator of the precision of a study’s results, which is 

influenced by a variety of factors including, but not limited to, the size of the study, 

exposure and measurement error, and statistical model specifications. Statistical 

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

determined with epidemiological studies. The EPA can reasonably look to other indicia 

of reliability such as the consistency and coherence of a body of studies as well as other 

confirming data to justify reliance on the results of a body of epidemiological studies, 

even if individual studies may lack statistical significance. American Trucking 

Association v. EPA, 283 F. 3d 355, 371 (D.C. Cir. 2002). As a result, in developing an 

integrated assessment of the health effects evidence for PM, the EPA has emphasized the 

importance of examining the pattern of results across various studies and their coherence 

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

study reliability. 

It has been clearly articulated throughout the epidemiological and causal inference 

literature that it is important not to focus on results of statistical tests to the exclusion of 

other information. For example, Rothman (1998) stated: “Many data analysts appear to 

remain oblivious to the qualitative nature of significance testing [and that]... statistical 

significance is itself only a dichotomous indicator. As it has only two values, significant 

or not significant.” As a result, Rothman recommended that P-values be omitted as long 

as point and interval estimates are available. 

The concepts underlying the EPA’s approach to evaluating statistical associations 

reported for the health effects on PM2.5 have been discussed in numerous publications, 

including a report by the U.S. Surgeon General on the health consequences of smoking 

(Centers for Disease Control and Prevention, 2004). This report cautions against overreliance on statistical significance in evaluating the overall evidence for an exposureresponse relationship: 

Hill made a point of commenting on the value, or lack thereof, of statistical testing in the 

determination of cause: “No formal tests of significance can answer those [causal] 

questions. Such tests can, and should, remind us of the effects the play of chance can 

create, and they will instruct us in the likely magnitude of those effects. Beyond that, they 

contribute nothing to the ‘proof’ of our hypothesis” (Hill 1965, p. 299). 

Hill’s warning was in some ways prescient, as the reliance on statistically significant 

testing as a substitute for judgment in a causal inference remains today (Savitz et al., 

1994; Holman et al., 2001; Poole 2001). To understand the basis for this warning, it is 

critical to recognize the difference between inductive inferences about the truth of 

underlying hypotheses, and deductive statistical calculations that are relevant to those 

inferences, but that are not inductive statements themselves. The latter include p values, 

confidence intervals, and hypothesis tests (Greenland 1998; Goodman 1999). The 

dominant approach to statistical inference today, which employs those statistical 

measures, obscures this important distinction between deductive and inductive inferences 
II-11 

(Royall 1997), and has produced the mistaken view that inferences flow directly and 

inevitably from data. There is no mathematical formula that can transform data into a 

probabilistic statement about the truth of an association without introducing some formal 

quantification of external knowledge, such as in Bayesian approaches to inference 

(Goodman 1993; Howson and Urbach, 1993). Significance testing and the 

complementary estimation of confidence intervals remain useful for characterizing the 

role of chance in producing the association in hand (CDC, 2003, pp. 23 to 24). 

Accordingly, the statistical significance of findings from an individual study has played 

an important role in the EPA’s evaluation of the study’s results and overall the EPA has 

placed greater emphasis on studies reporting statistically significant results in making 

determinations as to the elements of the standard. In particular, as noted in section 

III.E.4.b.i of the preamble to the final rule, the EPA identified long- and short-term 

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

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

for which the evidence supported a causal or likely causal association. Figure 4 in the 

preamble to the final rule (also Figure 4 in the proposal, 77 FR 38933) represents the 

subset of multi-city studies included in Figures 1 through 3 of the preamble to the final 

rule (also Figures 1 through 3 in the proposal, 77 FR 38929 to 38931) that provided 

evidence of positive and generally statistically significant effects associated in whole, or 

in part, with more recent air quality data, generally representing health effects associated 

with lower PM2.5 concentrations than had previously been considered in the last review. 

The EPA notes that many of these studies evaluated multiple health endpoints, and not all 

of the effects evaluated provided evidence of positive and statistically significant effects. 

For purposes of informing the Administrator’s decision on the appropriate standard 

levels, the Agency considers the full body of scientific evidence and focuses on those 

aspects of the key studies that provided evidence of positive and generally statistically 

significant effects.. 

However, in the broader evaluation of the evidence from many epidemiological studies, 

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

emphasized the pattern of results across epidemiological studies for drawing conclusions 

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

are coherent across the scientific disciplines. Thus, in making causality determinations, 

the EPA did not limit its focus or consideration to just studies that reported positive 

associations or where the results were statistically significant. 

As discussed in section III.D.2 of the preamble to the final rule, the EPA notes that the 

final causality determinations presented in the ISA reflected CASAC’s recommendations 

on the second draft ISA (Samet, 2009f, pp. 2 to 3). Specifically, CASAC supported the 

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

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

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

causality classification for PM2.5 and total mortality to “causal” for both the short- and 

long-term timeframes. Id. With regard to mortality, the “EPA carefully reevaluated the 

body of evidence, including the collective evidence for biological plausibility for 

mortality effects, and determined that a causal relationship exists for short- and long-term 
II-12 

exposure to PM2.5 and mortality, consistent with the CASAC comments” (Jackson, 2012). 

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

reexamined the controlled human exposure and toxicological studies of fresh diesel and 

gasoline exhaust This information, in addition to other considerations, supported a 

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

the causal determinations for short-term ultrafine particle exposures and cardiovascular 

and respiratory effects, the EPA changed the classification from “inadequate” to 

“suggestive” for both categories of health outcomes (Vandenberg, 2009, p. 3). CASAC 

agreed with the EPA’s rationale for revising these causal determinations (Samet, 2009f, 

p. 10). 

(2) Comment: Some commenters asserted that the EPA inappropriately used the Hill criteria 

by failing to consider the limitations of studies with weak associations, thereby 

overstating the consistency of the observed associations (API, 2012, Attachment 1, pp. 30 

to 35). Specifically, these commenters argued that risk estimates greater than 3 to 4 

reflect strong associations supportive of a causal link, while smaller risk estimates (i.e., 

1.5 to 3) are considered to be weak and require other lines of evidence to demonstrate 

causality. Additionally, these commenters believed that the EPA downplayed null or 

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

concentrations above and below the level of the current annual standard (e.g., Id.; NAM 

et al., 2012, p. 9).

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

uncertainties and limitations of all studies during its evaluation of the scientific literature 

(U.S. EPA, 2009a, pp. 1 to 14). This collective body of evidence, including known 

uncertainties and limitations of the studies evaluated, were considered by the EPA (and 

reviewed by the CASAC) during the process of forming causality determinations as 

discussed in Chapters 6 and 7 of the ISA. For example, the EPA concluded that “a causal 

relationship exists between short-term PM2.5 exposure and cardiovascular effects”; 

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

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

6.2.12.1). Therefore, the commenters have mischaracterized the EPA’s process. The 

limitations of the studies, and their uncertainties, were noted and considered by the EPA. 

The EPA also disagrees with the commenters’ assertion that the magnitude of the 

association must be large to support a determination of causality. As discussed in the 

ISA, the strength of the observed association is an important aspect to aid in judging 

causality and “while large effects support causality, modest effects therefore do not 

preclude it” (U.S. EPA, 2009a, Table 1-2, section 1.5.4).3

 The weight of evidence 

approach used by the EPA encompasses a multitude of factors of which the magnitude of 

the association is only one component (U.S. EPA, 2009a, Table 1-3). An evaluation of 

the association across multiple investigators and locations supports the “reproducibility of 

findings [which] constitutes one of the strongest arguments for causality” (U.S. EPA, 

2009a, Table 1-2). Even though the risk estimates for air pollution studies may be 

 

3

 For example, environmental tobacco smoke (second-hand smoke) causes lung cancer in humans, even though the 

magnitude of the association is small (U.S. EPA, 1992). 
II-13 

modest, the associations are consistent across hundreds of studies as demonstrated 

throughout the ISA (U.S. EPA, 2009a, Figures 2-1, 6-27, and 7-7). Furthermore, the 

causality determinations rely on different lines of evidence, by integrating evidence 

across disciplines, including animal toxicological studies and controlled human exposure 

studies. 

The EPA recognizes that the population potentially affected by PM2.5 is considerable, 

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

populations (e.g., children, older adults, persons with underlying cardiovascular or 

respiratory disease). While individual effect estimates from epidemiological studies may 

be modest in size, the public health impact of the mortality and morbidity associations 

can be quite large given that exposure to airborne PM2.5 is ubiquitous. Indeed, with the 

large population exposed, exposure to a pollutant causally associated at a population level 

with mortality and serious illness has significant public health consequences, virtually 

regardless of the relative risk. Taken together, this information indicates that exposure to 

ambient PM2.5 concentrations has substantial public health impacts. 

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

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

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

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

between long-term PM2.5 exposure and mortality. Overall, across these studies there was 

evidence of consistent positive associations in different cohorts. That evidence in 

combination with the biological plausibility provided by experimental studies evaluated 

in sections 7.1 and 7.2 of the ISA supported that a causal relationship exists between 

long-term PM2.5 exposure and mortality, which is consistent with CASAC advice (Samet, 

2009f, pp. 2 to 3). 

(3) Comment: Some commenters argued that in some cases, the EPA used the same study 

and the same underlying database to conclude that there was a causal association between 

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

the EPA attributes the cause of the mortality effects observed to whichever criteria 

pollutant it is reviewing at the time” (API, 2012, pp. 14 to 16).

Response: The EPA strongly disagrees that the Agency “attributes the cause of mortality 

effects observed to whichever criteria pollutant it is reviewing at the time.” The EPA 

consistently recognizes that other pollutants are also associated with health outcomes, as 

is reflected in the fact that the EPA has established NAAQS to limit emissions of the 

particulate criteria pollutants as well as other gaseous criteria pollutants. Epidemiological 

studies often examine the association between short- and long-term exposures to multiple 

air pollutants and mortality within a common dataset in an attempt to identify the air 

pollutant(s) of the complex mixture most strongly associated with mortality. It is 

important to recognize that more than one pollutant can have effects on the same system; 

in fact, it is not reasonable to assume that effects can be attributed to only one pollutant 

and to exclude effects of all other pollutants. 

The EPA carefully considers evidence from experimental studies providing information 
II-14 

on mode(s) of action in evaluating the overall weight of the scientific evidence to develop 

causal judgments. In evaluating these studies, the EPA employs specific study selection 

criteria to identify those studies most relevant to the review of the NAAQS. In its 

assessment of the health evidence regarding PM2.5, the EPA has carefully evaluated the 

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

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

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

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

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

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

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

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

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

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

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

sections 2.3.1.1 and 2.3.1.2). This was the first time that the Agency concluded that a 

causal relationship exists between short-or long-term exposure to a criteria pollutant and 

mortality. 

Additionally, while the EPA has evaluated the studies used to inform the causality 

determination for PM2.5 in ISAs for other criteria air pollutants, the Agency has done so 

in the context of examining the collective body of evidence for each of the respective 

criteria air pollutants. Therefore, the EPA disagrees with the commenter that the 

underlying database used in the PM ISA was also used in concluding a causal 

relationship exists between mortality and other criteria pollutants. As discussed in the 

recently-completed ISAs for nitrogen oxides, sulfur oxides and carbon monoxide, the 

EPA did not conclude that a causal relationship exists with mortality and these criteria 

pollutants due to either short- or long-term exposures (U.S. EPA, 2008e, 2008f, 2010k). 

(4) Comment: A number of commenters questioned the underlying scientific basis used in 

the ISA to conclude that a causal relationship exists between long-term PM2.5 exposure 

and mortality. Specifically, commenters asserted that evidence from two studies, Janes et 

al. (2007) and Greven et al. (2011), indicated that the association between long-term 

PM2.5 exposures and mortality is subject to unmeasured confounding. The commenters 

further asserted that these studies therefore indicated that unmeasured confounding is 

inherent in all long-term exposure studies of mortality (UARG, 2012, pp. 10 to 11, 

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

Attachment 7, pp 3 to 10; ACC, 2012, p. 18 to 21; AFPM, 2012, p. 8; TCEQ, 2012, p. 4; 

EPRI, 2012, p. 3). In addition, all of the authors of the Janes et al. (2007) and Greven et 

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

Greven) submitted a joint comment to the public docket in order to clarify specific points 

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

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

2009a, p. 7-88) and evaluated the study by Greven et al. (2011) (an extension of the study 

by Janes et al. (2007) incorporating three additional years of data) in the Provisional 
II-15 

Science Assessment (U.S. EPA, 2012b). In the EPA’s evaluation of the relationship 

between long-term exposure to PM2.5 and mortality, the Janes et al. (2007) study was 

included in the body of evidence that supported the determination that a causal 

relationship existed (U.S. EPA, 2009a, section 7.6.5.1). For the reasons discussed below, 

the EPA does not agree with the commenters’ views that these two studies call into 

question the scientific merit or the consistency of the results of long-term exposure 

studies of mortality that contribute to this body of evidence. 

Both studies used nationwide Medicare mortality data to examine the association 

between monthly averages of PM2.5 over the preceding 12 months and monthly mortality 

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

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

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

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

national average trend in monthly PM2.5 concentrations averaged over the previous 12 

months and the national average trend in monthly mortality rates and (2) “local” trends, 

defined as county-specific deviations in monthly PM2.5 concentrations and monthly 

mortality rates from national trends. 

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

et al. (2007) and Greven et al. (2011).4 Both Janes et al. (2007) and Greven et al. (2011) 

observed positive and statistically significant associations between long-term exposure to 

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

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

set when estimating the national effect, focusing instead on both chronic (yearly) and 

sub-chronic (monthly) temporal differences in the data (Dominici et al. 2012). Janes et al. 

(2007) (Table 1) highlighted that over 90 percent of the variance in the data set used for 

the analyses conducted by both Janes et al. (2007) and Greven et al. (2011) was 

attributable to spatial variability, which the authors chose to discard. The focus of the 

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

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

association between the national average trend in monthly PM2.5 concentrations averaged 

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

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

county-specific deviations in monthly PM2.5 concentrations and monthly mortality rates 

from national trends. These two components combined comprised less than 10 percent of 

the variance in the data set. The authors included a focus on the space-by-time 

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

an attempt to identify, absent confounding, if PM2.5 was associated with mortality at this 

unique exposure window. Thus, the national effects reported in these studies are not 

directly comparable to other cohort studies investigating the relationship between longterm exposure to PM2.5 and mortality, which make use of spatial variability in air 

 

4 In its evaluation of Janes et al. (2007) in the ISA, the EPA did not identify limitations in the statistical methods 

used per se (U.S. EPA, 2009a, p. 7-88) and included the results of the national-scale analyses in that study in the 

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

exposure and mortality. 
II-16 

pollution and mortality data. 5 Indeed, the study authors noted expressly that “when one 

considers that this wealth of [spatial] information is not accounted for in that study, it is 

not as surprising that we see vastly different estimates of the PM2.5/mortality relationship 

than in other studies that do exploit that variability” (Dominici et al. 2012, p. 2). 

For the local analyses, both Janes et al. (2007) and Greven et al. (2011) observed 

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

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

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

were estimating “associations between temporal changes in exposure and outcomes 

within counties relative to the national trend.” However, a limitation of the analysis 

conducted by Janes et al. (2007) [and subsequently by Greven et al. (2011)], and 

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

PM2.5 concentrations to examine associations at the local scale. This is a limitation 

because such an exposure assignment approach does not provide enough exposure 

contrast to observe temporal changes in mortality. The ISA (U.S. EPA, 2009a, p. 7-88) 

recognized comments made by Pope and Burnett (2007) that pointed out that the 

conclusions of Janes et al (2007) “are overstated. . . their analysis tells us little or nothing 

about unmeasured confounding in those and related studies because the methodology of 

Janes et al largely excludes the sources of variability that are exploited in those other 

studies. By using monthly mortality counts and lagged 12-month average pollution 

concentrations, the authors eliminate the opportunity to exploit short-term or day-to-day 

variability.” 

Furthermore, the EPA disagrees with commenters that Janes et al. (2007) and Greven et 

al. (2011) provide evidence that other studies of long-term exposure to PM2.5 and 

mortality are affected by unmeasured confounding. As noted above, the design of the 

studies conducted by Janes et al (2007) and Greven et al (2011) are fundamentally 

different than those used in other studies of long-term exposure to PM2.5 and mortality, 

including the ACS cohort and the Harvard Six Cities study. Studies, such as the ACS and 

Harvard Six Cities studies, used the spatial variation between cities to measure the effect 

of long-term (annual) exposures to PM2.5 on mortality risk, and did not conduct any 

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

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

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

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

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

therefore control for confounders would be based on including variables that vary over 

time rather than over space. As a result, any evidence of potential confounding of the 

PM2.5-mortality risk relationship derived from Janes et al. (2007) and Greven et al. (2011) 

 

5

 Though not directly comparable, the effect estimates for mortality reported by Janes et al. (2007) and Greven et al. 

(2011) were coincidentally similar in magnitude to those previously reported in other long-term cohort studies. It is 

important to note that previous cohort studies focused on identifying spatial differences in PM2.5 concentrations 

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

concentrations. In fact, Greven et al. (2011) stated, “We do not focus here on a third type [of statistical approach] 

used in cohort studies, measuring the association between average PM2.5 levels and average age-adjusted mortality 

rates across cities (purely spatial or cross-sectional association).” 
II-17 

cannot be extrapolated to draw conclusions related to potential spatial confounding in 

studies based on the spatial variation in PM2.5 concentrations. 

As detailed in the ISA (U.S. EPA, 2009a, section 7.6), and recognized by the authors of 

Janes et al. (2007) and Greven et al. (2011), the cohort studies that informed the causality 

determination for long-term PM2.5 exposure and mortality “have developed approaches to 

adjust for measured and unmeasured confounders” (Dominici et al. 2012). These 

approaches were specifically designed to adjust for spatial confounding. The hypothesis 

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

differences in the local and national effects indicate unmeasured temporal confounding in 

either the local or national effect estimate. This hypothesis was specific to these two 

studies that examined temporal variability in exposure to air pollution and did not include 

known potential confounders at either the national or local scale as covariates in the 

statistical model. The authors acknowledged that the interpretation of either the national 

or local estimates needs to occur with an appreciation of the potential confounding effects 

of national and local scale covariates that were omitted from the model (Dominici et al., 

2012). It is important to recognize that because Janes et al. (2007) and Greven et al. 

(2011) focused on variations in PM2.5 over time and not space, the results from these two 

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

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

authors of Janes et al. (2007) and Greven et al. (2011) recognized “it is entirely possible 

that these papers are looking for an association at a timescale for which no association 

truly exists” (Dominici et al. 2012, p.3). 

Specific comments by UARG (UARG, 2012, Attachment A, pp. 19 to 23) stated that 

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

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

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

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

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

studies of mortality rely on even more aggregate timescales that are multi-year averages. 

The EPA agrees that many of the long-term cohort studies rely on timescales that are 

aggregated beyond monthly averages (as was done by Janes et al., 2007) in multi-city 

studies where spatial variability in exposure is being examined. However, Janes et al. 

(2007) discounted all of the spatial variability in their analyses. Thus, the EPA agrees 

with the criticism by Pope and Burnett (2007) that when looking within a single city or 

geographic area, as Janes et al. (2007) did in their “local” analysis, there was not enough 

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

level. 

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

use of county-level fixed effects eliminated the source of long-term average spatial 

variability. As stated by the commenters, “To estimate the new model developed by Janes 

 

6

 Further, the EPA notes that Janes et al. (2007) and Greven et al. (2011) provide no information relevant to 

examining confounding in studies of short-term exposure to PM2.5. 
II-18 

et al. (2007a), they must use other sources of variation: they must use temporal and 

spatial-temporal variation” (UARG, 2012, Attachment A, p. 21). While this may be true, 

as mentioned above, the Medicare mortality dataset used by the authors does not have 

adequate temporal resolution to look at spatial-temporal variation in the “local” analyses 

conducted by Janes et al (2007) and reanalyzed by Greven et al. (2011). As noted by 

Janes et al. (2007) (See Table 1), and discussed by Dominci et al. (2012) only 5 percent 

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

component. Therefore, although Janes et al. (2007) and Greven et al. (2011) attempt to 

use temporal and spatial-temporal variation in the data set to examine associations 

between PM2.5 exposure and mortality as stated by the commenters, there is not enough 

temporal variability to identify associations using this approach. 

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

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

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

The commenters stated that “[a]ll researchers are limited by the data available to them, 

and Janes et al. (2007a) used only three years in their analysis because that is all the data 

they had available” (UARG, 2012, Attachment A, p. 21). While the EPA acknowledges 

that the researchers may be limited by the data available to them, scientists must decide 

whether those limitations enable them to answer the scientific question that they are 

posing. Because the Medicare mortality was aggregated at the monthly level, it could 

take decades and decades of data to provide the appropriate exposure contrast to conduct 

these analyses. 

There were also specific comments suggesting that the study by Greven et al. (2011) 

substantiated the results of Janes et al. (2007). Specifically, the commenters stated that 

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

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

confounders, and investigated trends at the regional level (UARG, 2012, Attachment A, 

p. 22). While these may be improvements upon the original study by Janes et al. (2007), 

Greven et al. (2011), like Janes et al. (2007), eliminated all of the spatial variation in their 

data set. Therefore, the results in Greven et al. (2011) similar to Janes et al. (2007), are 

not comparable to, nor would they invalidate, the results of cohort studies investigating 

the relationship between long-term exposure to PM2.5 and mortality (Dominici et al. 

2012, p. 1.). 

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

exposure to PM2.5 and mortality characterized in the ISA are inconsistent and discordant, 

indicating significant confounding (API, 2012, Attachment 7, pp. 2 to 10). This 

commenter pointed to the study by Greven et al. (2011) as an example of a study that 

avoids such potential confounding. The EPA disagrees with this comment. As 

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

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

positive relative risks (U.S. EPA 2009a, Figures 7.6 and 7.7). The EPA does not interpret 

these results as being “inconsistent and discordant”. 

This commenter also suggested that the data used by Greven et al. (2011) were “superior 
II-19 

or comparable to data used in other studies of PM2.5 and mortality” ((API, 2012, 

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

data from more locations than other researchers. Specifically, this commenter pointed out 

that Greven et al. (2011) included data from 814 ZIP code areas while Pope et al. (2009) 

focused on 211 county units. The EPA acknowledges that Greven et al. (2011) used a 

more spatially resolved data set (i.e., ZIP codes instead of counties), but points out that 

the study by Greven et al. (2011) includes data from just 113 counties, compared to the 

211 counties included in Pope et al. (2009). Furthermore, while this enhanced spatial 

resolution may help to reduce exposure measurement error, the focus on the study by 

Greven et al. (2011) was on temporal variability in exposure, and in this case does not 

provide additional exposure contrast. We consequently do not accept the conclusion that 

the data set in Greven (2011) was superior to that in other studies. 

In addition, the commenter cited the use of monthly average mortality data as a strength 

of the study by Geven et al. (2011), when, in fact, for a study focusing on temporal 

variability in exposure, daily average mortality would be preferable. The EPA thus 

considers the use of monthly-average mortality data in the study as a limitation, not 

strength. Finally, the commenter acknowledged that the study by Greven et al. (2011) did 

not include any individual-level covariates, but had to rely on county- and month-level 

information for potential confounders, including smoking whereas other cohort studies 

have used individual-level data (e.g., the ACS cohort (Pope et al., 2002)). For these 

reasons, the EPA disagrees with the commenters’ views that the study by Greven et al. 

(2011) is superior to other cohort studies of long-term exposure to PM2.5 and mortality. 

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

(2007) and Greven et al. (2011); however, the EPA disagrees that the results of these 

studies are comparable to the results of other cohort studies of long-term exposure to 

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

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

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

chose to eliminate the spatial variability in the air pollution and mortality data. Thus, the 

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

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

concentrations and mortality) because the authors only use temporal variability measured 

on a monthly scale. Nor can the results of these studies be directly compared to cohort 

studies of long-term exposure to PM 2.5 and mortality (which rely on the spatial 

variability of air pollution concentrations and mortality) because their analyses include a 

fixed effect for county in the regression model which eliminates spatial variability when 

estimating the national effect. Additionally, Janes et al. (2007) and Greven et al. (2011) 

use a different time scale in their analyses compared to the timescales used in other 

cohort studies. Janes et al. (2007) and Greven et al. (2011) examined whether an 

association exists at a sub-chronic (i.e., monthly) time scale. Thus, the results of the study 

by Janes et al. (2007) are included in the ISA and contributed to the body of evidence for 

an association between long-term PM2.5 exposures and mortality, but are not directly 

comparable to other cohort studies that rely on a different timescale and focus on spatial 

variability. 
II-20 

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

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

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

large body of evidence, the EPA concluded that a causal relationship exists between longterm exposure to PM2.5 and mortality (U.S. EPA, section 7.6.5.1). The results presented 

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

studies of long-term exposure to PM2.5 and mortality. Therefore, the EPA concludes that 

these studies do not invalidate the large body of epidemiological evidence that supports 

the EPA’s determination that a causal relationship exists between long-term PM2.5

exposure and mortality. 7

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

the adequacy of the current PM NAAQS because “of the untestable assumptions on 

which much of air pollution epidemiology, along with EPA’s proposed NAAQS 

revisions, are built” (ACC, 2012, pp. 20 to 21). These commenters made this claim based 

on a recent publication by Moore et al. (2012), which they asserted demonstrates that 

“most, if not all, results from epidemiologic studies of air pollution – requires reliance on 

untestable and possible invalid assumptions, and that the alternative analyses designed to 

meet such assumptions can produce different (e.g., null instead of positive) results” 

(ACC, 2012, p. 20). 

Response: The EPA disagrees with the commenters’ views that the results of the recently 

published Moore et al. (2012) study bring into question the epidemiological evidence 

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

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

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

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

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

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

examined heat as a potential confounder of the O3-asthma hospital admission 

relationship. For PM, temperature is also a known potential confounder, but a number of 

studies have demonstrated that alternative approaches to controlling for the potential 

confounding effects of weather do not influence PM risk estimates (e.g., Welty and Zeger 

(2005), as discussed on p. 6-163 and 6-164, U.S. EPA, 2009a). Therefore, the study by 

Moore et al. (2012) does not inform the relationship between PM2.5 exposure and health 

effects. 

(6) Comment: With regard to toxicological and controlled human exposure studies, some 

commenters argued that the available evidence does not provide coherence or biological 

plausibility for health effects observed in epidemiological studies (API, 2012, pp. 21 to 

22, Attachment 1, pp. 25 to 29; AAM, 2012, pp. 15 to 16; Texas CEQ, 2012, p. 3). With 

regard to the issue of mechanisms, these commenters noted that although the EPA 

recognizes that new evidence is now available on potential mechanisms and plausible 

biological pathways, the evidence provided by toxicological and controlled human 

 

7

 We note that the EPA’s conclusion with regard to interpretation of the results from Janes (2007) and Greven 

(2012) is supported by the study authors’ conclusion that “[o]ur results do not invalidate previous epidemiologic 

studies” (Dominici (2012) p. 1 (emphasis original)). 
II-21 

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

concentrations could produce the mortality and morbidity effects observed in 

epidemiological studies. More specifically, for example, some of these commenters 

stated that: 

A review of the Integrated Science Assessment, however, suggests that the 

experimental evidence is inconsistent and not coherent with findings in 

epidemiology studies. Specifically, the findings of mild and reversible effects in 

most experimental studies conducted at elevated exposures are not consistent with 

the more serious associations described in epidemiology studies (e.g., hospital 

admissions and mortality). Also, both animal studies and controlled human 

exposure studies have identified no effect levels for acute and chronic exposure to 

PM and PM constituents at concentrations considerably above ambient levels. 

The EPA should consider the experimental findings in light of these higher 

exposure levels and what the relevance may be for ambient exposures (API, 2012, 

Attachment 1, p. 25).

Response: The EPA notes that in the review completed in 1997, the Agency considered 

the lack of demonstrated biological mechanisms for the varying effects observed in 

epidemiological studies to be an important caution in its integrated assessment of the 

health evidence upon which the standards were based (71 FR 61157, October 17, 2006). 

In the review completed in 2006, the EPA recognized the findings from additional 

research that indicated that different health responses were linked with different particle 

characteristics and that both individual components and complex particle mixtures 

appeared to be responsible for many biologic responses relevant to fine particle 

exposures. Id. Since that review, there has been a great deal of research directed toward 

advancing our understanding of biological mechanisms. While this research has not 

resolved all questions, and further research is warranted (U.S. EPA, 2011a, section 2.5), it 

has provided important insights as discussed in section III.B.1 of the proposal (77 FR at 

38906 to 38909) and discussed more fully in the ISA (U.S. EPA, 2009a, chapter 5). 

As noted in the proposal, toxicological studies provide evidence to support the biological 

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

PM2.5 exposures observed in epidemiological studies (77 FR 38906) and provide 

supportive mechanistic evidence that the cardiovascular morbidity effects observed in 

long-term exposure epidemiological studies are coherent with studies of cardiovascularrelated mortality (77 FR 38907). The ISA concluded that the new evidence available in 

this review “greatly expands” upon the evidence available in the last review “particularly 

in providing greater understanding of the underlying mechanisms for PM2.5 induced 

cardiovascular and respiratory effects for both short- and long-term exposures” (U.S. 

EPA, 2009a, p. 2-17). The mechanistic evidence now available, taken together with 

newly available epidemiological evidence, increases the Agency’s confidence that a 

causal relationship exists between long- and short-term exposure to PM2.5 and 

cardiovascular effects and mortality. In addition, CASAC supported the ISA approach 

and characterization of potential mechanisms or modes of action (Samet, 2009e, pp. 7 to 

8; Samet, 2009f, p. 11), as well as the findings of a causal relationship at the population 
II-22 

level between exposure to PM2.5 and mortality and cardiovascular effects (Samet, 2009f, 

pp. 2 to 3). 

Additionally, the EPA disagrees with commenters that the mild and reversible effects 

observed in controlled human exposure studies are inconsistent with the more serious 

effects observed in epidemiological studies. Ethical considerations regarding the types of 

studies that can be performed with human subjects limit the effects that can be evaluated 

to those that are transient, reversible, and of limited short-term consequence. The 

relatively small number of subjects recruited for controlled exposure studies should also 

be expected to have less variability in health status and risk factors than occurring in the 

general population.8 Consequently, the severity of health effects observed in controlled 

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

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

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

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

expected in a more diverse population, specifically, in at-risk populations. Put another 

way, there are serious public health risks from exposure of large populations of people 

including those with pre-existing illnesses, to ambient concentrations of PM2.5, but these 

are not the same as the very small risks that individuals who do not have such conditions 

face when participating in a controlled human exposure study. 

It should also be noted that there is a small body of toxicological evidence demonstrating 

mortality in rodents exposed to PM2.5 (e.g., Killingsworth et al. 1997). Overall, it is not 

surprising that lethality is not induced in more toxicological research, as these types of 

studies do not readily lend themselves to this endpoint. Epidemiological studies have 

observed associations between PM2.5 and mortality in communities with populations in 

the range of many thousands to millions of people. Clearly, it is not feasible to expose 

hundreds (if not thousands) of animals to PM2.5 (potentially over many years) in a 

laboratory setting to induce enough lethalities to distinguish between natural deaths and 

those attributable to PM2.5. Furthermore, the heterogeneous human populations sampled 

in epidemiological studies are comprised of individuals with different physical, genetic, 

health, and socioeconomic backgrounds which may impact the outcome. However, in 

toxicological studies, the rodent groups most frequently evaluated are typically inbred, 

such that inter-individual variability is minimized. Thus, if the rodent strain used is quite 

robust, PM2.5-induced effects may not be observed at low exposure concentrations. 

 

8

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

individual with a significant risk factor for experiencing adverse effects from such exposure. Thus, the EPA 

excludes a priori the following categories of persons: those with a history of angina, cardiac arrhythmias, and 

ischemic myocardial infarction or coronary bypass surgery; those with a cardiac pacemaker; those with uncontrolled 

hypertension (greater than 150 systolic and 90 diastolic); those with neurogenetive diseases; those with a history of 

bleeding diathesis; those taking beta-blockers; those using oral anticoagulants; those who are pregnant, attempting to 

become pregnant, or breastfeeding; those who have experienced a respiratory infection within four weeks of 

exposure; those experiencing eye or abdominal surgery within six weeks of exposure; those with active allergies; 

those with a history of chronic illnesses such as diabetes, cancer, rheumatologic diseases, immunodeficiency state, 

known cardiovascular disease, or chronic respiratory diseases; smokers. The EPA “Application for Independent 

Review Board Approval of Human Subjects Research: Cardiopulmonary Effects of healthy Older GSTM1 Null and 

Sufficient individuals to Concentrated Ambient Air Particles (CAPTAIN),” Nov. 9, 2011, p. 9.
II-23 

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

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

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

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

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

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

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

misclassification. 

Response: The EPA carefully evaluated “the body of evidence, including the collective 

evidence for biological plausibility for mortality effects, and determined that a causal 

relationship exists for ...long-term exposure to PM2.5 and mortality, consistent with 

CASAC comments” (Jackson, 2012). This evaluation of the evidence included review of 

the potential limitations mentioned by commenters. Furthermore, CASAC supported the 

EPA’s evaluation of the scientific evidence and the application of the causal framework 

in making a causal determination for mortality attributed to long-term PM exposures 

(Samet, 2009f, pp. 2 to 3). Below, the EPA responds to each of the specific limitations 

noted by commenters: 

(a) With respect to biological plausibility, some commenters argued that the estimated 

associations between ambient PM and mortality are stronger than those for long-term 

heavy cigarette smoking, thereby defying biological plausibility (ACC, 2012, pp. 6 to 7). 

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

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

was not raised during the CASAC and public review of the drafts of the ISA. In order to 

address the comments submitted, the EPA conducted a provisional review of the “new” 

literature published since the close of the ISA including studies cited by commenters, and 

identified several relevant studies that compared and evaluated effect estimates 

determined for relationships between specific health outcomes and ambient particulate 

matter and active smoking (Pope et al. 2009; Pope et al. 2011). These authors analyzed 

data from the ACS cohort in order to evaluate the shape of the exposure-response 

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

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

studies, the authors evaluated three sources of exposure to PM2.5: active smoking, passive 

smoking, and ambient air pollution. 

For lung cancer mortality, the authors observed “a monotonic, nearly linear exposure 

response relationship with fairly constant marginal increases in RR [relative risk] with 

increasing exposure” across the full range of observed exposures (Pope et al. 2011). 

When the authors evaluated CVD mortality, they observed “an exposure-response 

relationship that is substantially non-linear, that is, much steeper at the very low levels of 

exposure compared with higher levels of exposure” (Pope et al. 2011). In fact, the study 

authors noted that “For lung cancer mortality, the RRs steadily increase to nearly 40 at 

the highest increment of cigarette smoking (>42 cigarettes per day), whereas for CVD 

mortality, the RRs level off at approximately 2.0-2.5” (Pope et al. 2011, Figure 1).
II-24 

Figure 1. Adjusted RRs [with 95% confidence intervals (CIs)] of lung cancer mortality (A) and IHD, cardcardiopulmonary mortality (B) plotted over estimated daily exposure of PM2.5 (milligrams) and incremensmoking relative to never smokers (cigarettes/day). Diamonds represent comparative mortality risk estim

for PM2.5 from air pollution from the comparative studies (Dockery et al. 1993; Laden et al. 2006; Miller 

1995, 2002, 2004). Stars represent comparable pooled RR estimates (with 95% CIs) associated with SHS comparative studies (Teo et al. 2006; U.S. Department of Health and Human Services 2006). The dotted 

nonlinear power function fit through the origin and the estimates (including active smoking, SHS, ambien

doses from different increments of active smoking are dramatically larger than estimated doses from ambtherefore, associations at lower exposure levels (due to ambient air pollution and SHS) are shown as insetscale. Source: Pope et al. 2011.
II-25 

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

PM2.5 and CVD mortality at low PM2.5 concentrations, which flattens out at higher PM2.5

concentrations (i.e., those associated with passive and active cigarette smoking), it is 

biologically plausible that the risk estimates for CVD mortality due to exposure to 

ambient concentrations of PM2.5 would be similar to risk estimates for CVD mortality 

due to active cigarette smoking. These results are consistent with the results observed in 

epidemiological studies of long-term exposure to PM2.5 and mortality, and with the 

conclusions drawn in the ISA. For example, Dockery et al. (1993) found essentially the 

same risk estimates for CVD mortality associated with both ambient PM2.5 concentrations 

and active cigarette smoking in an area with relatively high levels of ambient PM2.5

concentration. Thus, contrary to views expressed by commenters, the EPA concludes that 

the scientific evidence provides biologically plausibility for the mortality effects observed 

in epidemiological studies of ambient PM. 

(b) With regard to estimating PM2.5 exposure for periods when data are not available, as 

discussed in section III.E.4.c.i of the preamble to the final rule and in section II.B.5.a.i 

below, both in the last review and the current review, the EPA has assessed studies that 

used different air quality periods for estimating long-term exposure and tested 

associations with mortality for the different exposure periods (U.S. EPA, 2004, section 

8.2.3.5; U.S. EPA 2009a, section 7.6.4). In this review, the ISA discussed studies 

available since the last review that have assessed the relationship between long-term 

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

exposure to PM2.5 and death (U.S. EPA, 2009a, section 7.6.4). 

Notably, in a recent analysis of the extended Harvard Six Cities Study, Schwartz et al. 

(2008) used model averaging (i.e., multiple models were averaged and weighted by 

probability of accuracy) to assess exposure periods prospectively. The exposure periods 

were estimated across a range of unconstrained distributed lag models (i.e., same year, 

one year prior, two years prior to death). In comparing lags, the authors reported that the 

effects of changes in exposure to PM2.5 on mortality were strongest within a two-year 

period prior to death (U.S. EPA, 2009a, p. 7-92, Figure 7-9). Similarly, a large multi-city 

study of the elderly found that the mortality risk associated with long-term exposure to 

PM10 reported cumulative effects that extended over the years that deaths were observed 

in the study population (i.e., the follow-up period) and for the three-year period prior to 

death (Zanobetti et al., 2008). 

Further, in a study of two locations that experienced an abrupt decline in PM2.5

concentrations (i.e., Utah Steel Strike, coal ban in Ireland), Röösli et al. (2005) reported 

that approximately 75 percent of health benefits were observed in the first 5 years (U.S. 

EPA, 2009a, Table 7-9). Schwartz et al. (2008) and Puett et al. (2008) found, in a 

comparison of exposure periods ranging from 1 month to 48 months prior to death that 

exposure to PM10 24 months prior to death exhibited the strongest association, and the 

weakest association was reported for exposure in the time period of 1 month prior to 

death. 

Collectively, the EPA notes that the available evidence for determining the window over 

which the mortality effects of long-term PM exposures occur, as discussed above and in 
II-26 

section III.E.4.c.i of the preamble to the final rule and in section II.B.5.a.i below, 

suggests that a latency period of up to five years would account for the majority of 

deaths, with the strongest association observed in the two years prior to death. Further, 

the EPA recognizes that there is no discernible population-level threshold below which 

effects would not occur, such that health effects may occur over the full range of 

concentrations observed in the epidemiological studies, including the lower 

concentrations in the latter years. (U.S. EPA, 2009a, section 2.4.2.3). In light of this 

evidence and these considerations, the EPA concludes that it is appropriate to consider air 

quality concentrations that are contemporaneous with the collection of health event data 

(i.e., collected over the same time period) as being causally associated with at least some 

proportion of the deaths assessed in a long-term exposure study. 

In addition, the EPA acknowledges that the appropriate exposure period for mortality 

effects observed in long-term exposure studies may extend up to a few years prior to the 

years in which health event data were collected. Such an extended exposure window 

would likely more fully capture the PM2.5-related deaths in such studies. To explore how 

much higher the long-term mean PM2.5 concentrations would likely have been had air 

quality data prior to the follow-up years of the studies been included, the EPA conducted 

a sensitivity analysis of long-term mean PM2.5 concentrations (Schmidt, 2012a), 

particularly, considering studies that only included deaths from a relatively recent followup period. As examples of such studies, this analysis considered the Eftim et al. (2008) 

study of mortality in the ACS sites and the Harvard Six Cities sites, as well as sites in the 

eastern region in the Zeger et al. (2008) study. Using data from the EPA’s AQS database, 

the analysis added the two years of air quality data just prior to the follow-up period in 

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

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

for each study. As discussed in Schmidt (2012a), in each case the long-term mean PM2.5

concentration averaged over the extended exposure period was less than 0.4 μg/m3 higher 

than the long-term mean PM2.5 concentration averaged over the follow-up period. The 

EPA finds it reasonable to conclude that such a relatively small difference in long-term 

mean PM2.5 concentrations would likely apply for other long-term exposure studies that 

used similarly recent follow-up periods as well (e.g., Goss et al., 2004; Lipfert et al., 

2006a). Furthermore, the EPA finds that this sensitivity analysis illustrates that, even 

when considering a somewhat longer exposure window, including the years the health 

event data were collected plus the two previous years, health effects are occurring at 

concentrations below the current level of the annual standard (i.e., below 15 μg/m3

). 

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

section II.5.a.i below, the EPA notes that the relevant exposure period for the short-term 

exposure studies is the period contemporaneous with the collection of health event data, 

and that this exposure period is not subject to the uncertainties related to the long-term 

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

long-term mean concentrations evaluated in key short-term exposure studies in revising 

the level of the annual standard. 

(c) The EPA has long recognized that exposure error is an important issue for 

interpretation of epidemiological studies and that assessment of air pollution exposure 
II-27 

using community average concentrations may lead to exposure misclassification or 

exposure measurement error. To investigate this issue, several analyses using ACS data 

focused on neighborhood-to-neighborhood differences in urban air pollutants (Jerrett et 

al. 2005; Krewski et al. 2009a) (U.S. EPA, 2009a, section 7.6.3). These analyses used 

spatial interpolation and land use regression methods to assign exposure to study subjects 

living in Los Angeles, CA, resulting in improved exposure assessment compared to the 

full cohort of the ACS study. Statistically significant associations between PM2.5 and 

mortality from all causes and cardiopulmonary diseases were reported with the 

magnitude of the relative risks being greater in the analyses with the improved exposure 

assessment compared to the relative risks reported for the full ACS cohort. This provides 

evidence that reducing exposure error can result in stronger associations between PM2.5

and mortality than generally observed in studies having less well-characterized exposure. 

(8) Comment: Some commenters contended that the associations observed in long-term 

exposure studies were due to exposures that occurred many years earlier when PM2.5

concentrations were much higher and therefore are “misattributing those risks to more 

recent, lower PM2.5 levels” (UARG, Attachment 1, pp. 14 to 15; Southern Company, 

2012 p. 2; AAM, 2012, pp. 14 to 15). Additionally, these commenters asserted that 

mortality due to long-term exposure is the result of cumulative exposure over a lifetime, 

which led to the development of chronic conditions that ultimately contributed to death. 

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

between PM2.5-associated effects due to past and recent long-term exposures, and in 

identifying the relevant latency period for long-term exposure to PM and resultant health 

effects (U.S. EPA, 2009a; 77 FR 38941/1). While the EPA acknowledges that there 

remain important uncertainties related to characterizing the most relevant exposure 

periods in long-term exposure studies, the EPA notes that there are a number of studies 

that help inform the Agency’s consideration of this issue. 

Both in the last review and the current review, the EPA has assessed studies that used 

different air quality periods for estimating long-term exposure and tested associations 

with mortality for the different exposure periods (U.S. EPA, 2004, Section 8.2.3.5; U.S. 

EPA 2009a, section 7.6.4). In this review, the ISA discussed studies available since the 

last review that have assessed the relationship between long-term exposure to PM2.5 and 

mortality in exploring the issue of the latency period between exposure to PM2.5 and 

death (U.S. EPA, 2009a, Section 7.6.4). 

Notably, in a recent analyses of the Harvard Six Cities Study, Schwartz et al. (2008) used 

model averaging (i.e., multiple models were averaged and weighted by probability of 

accuracy) to assess exposure periods prospectively (77 FR 38907/1-2). The exposure 

periods were estimated across a range of unconstrained distributed lag models (i.e., same 

year, one year prior, two years prior to death). In comparing lags, the authors reported the 

effects of changes in exposure to PM2.5 on mortality were strongest within a two year 

period prior to death (U.S. EPA, 2009a, p. 7-92, Figure 7-9). Similarly, a large multi-city 

study of the elderly found that the mortality risk associated with long-term exposure to 

PM10 reported cumulative effects that extended over the years that deaths were observed 

in the study population (i.e., the follow-up period) and for the 3-year period prior to death 
II-28 

(Zanobetti et al., 2008). 

Further, in a study of two locations that experienced an abrupt decline in PM2.5

concentrations (i.e., Utah Steel Strike, coal ban in Ireland), Röösli et al. (2005) reported 

that approximately 75 percent of health benefits were observed in the first 5 years (U.S. 

EPA, 2009a, Table 7-9). Furthermore, Schwartz et al. (2008) and Puett et al. (2008) 

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

death that exposure to PM10 24 months prior to death exhibited the strongest association, 

and the weakest association was reported for exposure in the time period of 1 month prior 

to death. 

Overall, the EPA notes that the available evidence for determining the window over 

which the mortality effects of long-term pollution exposures occur suggests that a latency 

period of up to five years would account for the majority of deaths, with the strongest 

association observed in the two years prior to death. Further, the EPA recognizes that 

there is no discernible threshold below which effects would not occur, such that health 

effects may occur over the full range of concentrations observed in epidemiological 

studies, including the lower concentrations in the latter years. In light of this evidence and 

these considerations, the EPA concludes that it is appropriate to consider air quality 

concentrations that are contemporaneous with the collection of health event data as 

evidence to be used in determining causality. The EPA acknowledges that exposure 

windows that extend up to a few years prior to the follow-up period in which health event 

data were collected would likely more fully capture the PM-related deaths in such 

studies. 

To explore how much higher the long-term mean PM2.5 concentrations would likely have 

been had air quality data prior to the follow-up years of the studies been included, the 

EPA conducted a sensitivity analysis of PM2.5 concentrations (Schmidt, 2012), 

particularly, considering studies that only included deaths from a relatively recent followup period. As examples of such studies, this analysis considered the Eftim et al. (2008) 

study of mortality in both the ACS sites and the Harvard Six Cities sites, as well as sites 

in the eastern region in the Zeger et al. (2008) study. Using data from the EPA’s AQS 

database, the analysis added the two years of air quality data just prior to the follow-up 

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

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

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

mean PM2.5 concentration averaged over the extended exposure period was no more than 

0.4 μg/m3 higher than the long-term mean PM2.5 concentration averaged over the followup period. The EPA finds it reasonable to conclude that such a relatively small difference 

in long-term mean PM2.5 concentrations would likely apply for other long-term exposure 

studies that used similarly recent follow-up periods as well (e.g., Goss et al., 2004; 

Lipfert et al., 2006a).

Based on the above considerations, the EPA concludes that it is appropriate to consider 

the available air quality information from the long-term exposure studies, while taking 

into account the uncertainty in the relevant long-term exposure period when weighing the 

information from the long-term exposure studies in the context of the broader array of 
II-29 

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

PM2.5 standard. Furthermore, as noted in the preamble and in the response to the previous 

comment (Comment (7)), the relevant exposure period for the short-term exposure 

studies is the period contemporaneous with the collection of health event data, and that 

this exposure period is not subject to the uncertainties related to the long-term exposure 

studies. In this review, the EPA accordingly gave special consideration to the long-term 

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

annual standard. These comments are addressed further in section III.E.4.c.i of the 

preamble to the final rule and in section II.B.5.a.i below. 

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

exposure studies of mortality. For example, one group of commenters (NAM et al., 2012, 

pp. 23 to 24) asserted there were serious weaknesses in the long-term exposure studies 

considered by the EPA (e.g., Harvard Six Cities Study, Laden et al., 2006). Specifically, 

NAM et al. asserted that the Harvard Six Cities Study did not account for increasing age 

of the cohort, and that there were discrepancies in the results of the study. Another 

commenter (EPRI, 2012, p. 3) asserted that the EPA mischaracterized the results of the 

Veterans Cohort Study (Lipfert et al., 2006). 

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

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

estimating the association between decreased PM2.5 concentrations and decreased 

mortality observed by Laden et al. (2006). The average age of the cohort at enrollment 

was 50 years (range 25 to - 74 years) and the first follow-up period consisted of the 15 

years following enrollment (including 104,243 person-years of follow up and 1,364 

deaths). An additional follow-up period (16 to 24 years after enrollment) included an 

additional 54,735 person-years of follow-up and 1,368 deaths. The overall death rate for 

the first follow-up period was 13.1 deaths per 1,000 years of follow-up; it was 25.0 in the 

second follow-up period “reflecting the aging of this cohort” (Laden et al. 2006, p. 668). 

To account for this, Laden et al. (2006) controlled for baseline individual risk factors and 

potential confounders, including age. The authors stratified study subjects “by sex and 1-

yr age groups, such that each sex/age group had its own baseline hazard.” Id. The authors 

found that the associations between PM2.5 and mortality were comparable for both 

follow-up periods (Laden et al. 2006, p. 669). Additionally, NAM et al. asserted that 

there were discrepancies in results among the six cities in the study that lead to 

considerable uncertainty. The EPA acknowledges that there was variability in the results 

for the individual cities in the Harvard Six Cities Study (in fact the objective of the study 

was to look at the variability between cities), but disagrees that such variability 

contributes to uncertainty. In fact, variability in the PM2.5 concentrations among the cities 

is necessary in long-term cohort studies, such as the Harvard Six Cities Study, which rely 

on spatial variability for exposure contrast (see also response to Comment (4), above). 

Laden et al. (2006) recognized that there is variability in the association between the 

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

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

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

data in Figures 1 and 4 (77 FR 38929) of the proposal were attributed to the wrong 
II-30 

Lipfert et al. study published in 2006. The air quality data reported in Figure 1 of the 

proposal incorrectly identified the long-term mean PM2.5 concentration for Lipfert et al 

(2006a – labeled Lipfert et al. (2006) in Figure 1) as 14.3 μg/m3, which was instead the 

long-term mean PM2.5 concentration reported for Lipfert et al. (2006b). This mistake was 

also made in the Figure 2-2 of the ISA (U.S. EPA, 2009a, p. 2-15). The EPA notes that 

footnote a for Figure 4 of Lipfert et al. (2006a) identified that the mortality risks for 

PM2.5 were based on one year of air quality data (1999), although the study did not report 

the long-term mean PM2.5 concentration for that year. Rather, in Table 1 of Lipfert et al. 

(2006a), the study authors reported long-term mean PM2.5 concentrations of 14.3 μg/m3

for the years 1989 to 1996 and 14.6 μg/m3

 for the years 1997 to 2001. Based on this 

information, the EPA concludes that 14.3 μg/m3 is a reasonable approximation for the 

long-term mean PM2.5 concentration in Lipfert et al. (2006) even though this value was 

not specifically reported in that study. 

The EPA disagrees that the proposal mischaracterized the results of the Lipfert et al. 

(2006) study. The effect estimate for Lipfert et al., (2006a) was positive and statistically 

significant in a single pollutant model, and remained positive (though no longer 

statistically significant) in a two-pollutant model that included traffic density, as well as 

in a three-pollutant model that included traffic density and PM10-2.5. The EPA also 

acknowledges that this effect estimate represents an association for which the deaths 

occurred before PM2.5 measurements were collected, but disagrees with comments that it 

is inappropriate to consider this study as part of the body of evidence that informed the 

EPA’s causal determinations. Although the comments are unpersuasive that this study 

should be invalidated for purposes of assessing causality, the EPA notes that 

consideration of this study played no part in actually determining any of the elements of 

the revised annual PM2.5 standard. 

(10) Comment: Some commenters contended that PM2.5 risk estimates are highly sensitive to 

the approach used to control for temporal trends (API, 2012, Attachment 1pp. 11 to 12; 

AAM, 2012, pp. 6 to 10). Specifically, the results of the Air Pollution and Health: A 

European and North American Approach (APHENA) study provided evidence of no 

effect of short-term PM exposure on mortality and morbidity because the “overall pattern 

[of effects] is not what one would expect if PM health effects associations have a real 

physiological basis” (AAM, 2012, pp. 6 to 10). AAM stated that this conclusion was 

supported by the lack of consistent statistically significant associations across all models 

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

selection of degrees of freedom to control for temporal trends was further demonstrated 

in Dominici et al. (2007) and Ostro et al. (2006). 

Response: The EPA disagrees with the commenters’ view that the results from 

Katsouyanni et al. (2009), Dominici et al. (2007), and Ostro et al. (2006) demonstrate the 

sensitivity of PM2.5 risk estimates to the method used to control for temporal trends and 

bring into question the association between short-term PM2.5 exposures and mortality and 

hospital admissions. Additionally, these commenters have focused solely on the statistical 

significance of risk estimates and not on the pattern of associations across studies as is 

discussed more fully in response to Comment (1) above. 
II-31 

The APHENA study combined data from existing multi-city study databases from the 

U.S. (the National Morbidity, Mortality, and Air Pollution Study [NMMAPS]), Europe 

(Air Pollution and Health: A European Approach [APHEA]), and Canada to “develop 

more reliable estimates of the potential acute effects of air pollution on human health 

[and] provide a common basis for [the] comparison of risks across geographic areas” 

(Katsouyanni et al., 2009). In an attempt to address both of these issues the investigators 

conducted extensive sensitivity analyses to evaluate the robustness of the results to 

different model specifications (e.g., penalized splines vs. natural splines) and the extent 

of smoothing to control for temporal trends. In models where an appropriate number of 

degrees of freedom (df) to control for temporal trends were employed risk estimates were 

robust across the different model specifications. The trend analyses consisted of 

subjecting the models to varying extent of smoothing selected either a priori (i.e., 3 

df/year, 8 df/year, and 12 df/year), which was selected through exploratory analyses 

using between 2 and 20 df, or by using the absolute sum of the residuals of the partial 

autocorrelation function (PACF). Although the investigators did not identify the model 

they deemed to be the most appropriate for comparing the results across study locations, 

they did specify that “overall effect estimates (i.e., estimates pooled over several cities) 

tended to stabilize at high degrees of freedom” (Katsouyanni et al., 2009). 

The results of the APHENA study are consistent with those reported by both Dominici et 

al. (2007) and Ostro et al. (2006), which as part of their studies conducted sensitivity 

analyses to examine the influence of increasing the degrees of freedom per year to control 

for temporal trends on the PM2.5-mortality association. In both cases the authors found 

evidence that as the degrees of freedom per year increases a point is reached where risk 

estimates tend to stabilize, which for both of these studies was approximately 7 degrees 

of freedom or more per year. 

It should be noted that even the commenters acknowledged that “[i]n most cases, the 

results and conclusions from these updated analyses were not significantly altered, but 

effect estimates were lower” (API, 2012, Attachment 1, p 12). The EPA, therefore, 

disagrees with the commenters that the lack of consistent statistically significant results 

across all models supports the lack of an association between short-term PM exposure on 

hospital admissions and mortality. The inconsistency in the results across some of the 

models (i.e., for APHENA those that controlled for temporal trends using 3 df/year or 

PACF compared to those that employed 8 or 12 df/year, while for Dominici et al. (2007) 

and Ostro et al. (2006) those less than 7 df/year) is due to inadequate control for temporal 

trends. Additionally, the EPA disagrees with these commenters sole reliance on statistical 

significance when evaluating the results of these studies. As stated in the response to 

Comment (1) above, focusing solely on statistically significance is inappropriate when 

evaluating a body of studies. 

(11) Comment: Multiple commenters (ACC, 2012, pp. 14 to 18; AAM, 2012, pp. 6 to 10) 

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

studies that examined associations with morbidity and mortality outcomes. Specifically, 

these commenters questioned: (a) interpretation of results from copollutant models; (b) 

lag selection; (c) the derivation of national risk estimates from multicity studies; and (d) 

the ignoring of evidence indicating a reduction in PM-mortality risk over time. 
II-32 

Response: Overall, the EPA disagrees with each of the points raised by the commenters 

and provides detailed responses to each below: 

(a) Interpretation of results from copollutant models 

The commenters questioned the EPA’s interpretation of results from the copollutants 

models examined in Burnett et al. (2004) as well as all studies that examined copollutants 

models based on Ito et al. (2007), which stated that the use of multipollutant models “are 

a cautionary exercise, and throw into question the now commonplace practice of using 

multipollutant models in health effects analysis.” The EPA disagrees with the 

commenters’ interpretation of the results from Burnett et al. (2004). The main copollutant 

analyses conducted over the entire study duration used PM2.5 data that were not collected 

every day. As a result, when including PM2.5 in copollutant analyses with other pollutants 

that are measured on a daily basis, the overall sample size is reduced, which reduces the 

precision of resulting effect estimates. Burnett et al. (2004) performed a sensitivity 

analysis that further illustrates this point. When limiting the dataset to days in which daily 

PM2.5 concentrations were available, the PM2.5 association remained robust after 

adjustment for NO2, while the NO2 association was attenuated. Overall, this result brings 

into question the results from copollutants analyses including PM2.5 that is collected 

every third or every sixth day when other pollutants are collected more frequently. 

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

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

(2007) cautioned against including all pollutants in one model, which, as they 

demonstrated can result in “the pollutant that varies least like all the rest of the pollutants, 

and is least affected by concurvity in such a multi-pollutant model” being the pollutant 

that looks to be causing the effect. The EPA has emphasized evaluation of models 

including no more than two pollutants because models that included multiple pollutants 

are difficult to interpret due to the potential multicollinearity between pollutants. (e.g., 

U.S. EPA, 2004, sections 8.4.3.2 and 8.4.3.3). 

(b) Lag selection 

With regard to the lags selected in certain mortality studies (i.e., Franklin et al. 2007), 

commenters questioned the selection of lag days a priori and not through the use of 

model fit criteria (ACC, 2012, pp. 14 to 18). As demonstrated in the ISA, studies that 

examined the association between short-term PM2.5 exposure and mortality “were 

consistently observed at lag 1 and lag 0-1, which have been confirmed through extensive 

analysis of PM10-mortality studies” (U.S. EPA, 2009a, p. 6-200). Therefore, the lag days 

selected by Franklin et al. (2007) a priori (i.e., lag 0-1) were consistent with the large 

body of evidence that has demonstrated associations between short-term PM exposure 

and mortality. 

(c) Derivation of national risk estimates from multicity studies 

Some commenters questioned the derivation of national risk estimates from multi-city 

studies. Specifically, these commenters questioned the approach employed by study 
II-33 

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

the community-level data (ACC, 2012, pp. 14 to 18). The EPA disagrees with these 

commenters understanding of the approach used to calculate national risk estimates in 

multicity studies. Multi-city studies, in fact, do use the entirety of the dataset to calculate 

national risk estimates. By calculating city-specific risk estimates and then utilizing either 

a meta-regression or a second stage Bayesian Hierarchical model, investigators use the 

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

studies are not excluding any community-level data, but instead are using the totality of 

data to provide information that is needed to calculate a national risk estimate. 

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

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

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

et al. (2007) to support their argument (e.g., ACC, 2012, pp. 14 to 18, NAM et al., 2012, 

p. 9). At first glance, the results of Dominici et al. (2007) would seem to indicate that 

PM-mortality risk estimates have declined over time due to the observed decline in the 

slope for all-cause and cardiorespiratory mortality. However, this analysis was motivated 

by accountability research and instead of measuring the impact of a sudden change in air 

quality, this study attempted to measure the impact of policy interventions. As such, “a 

flaw in the use of the time-series study design for this type of analysis is that it adjusts for 

long-term trends, and, therefore, does not estimate the change in mortality in response to 

the gradual change in PM10” (U.S. EPA, 2009a, p. 6-163). Therefore, the EPA disagrees 

with the commenters. Although this analysis may indicate a slight reduction in PMmortality risk estimates over time “the analytic approach used in the study does not allow 

for a systematic analysis of the effect of air pollution policies on the risk of mortality” 

(U.S. EPA, 2009a, p. 6-163). 

(12) Comment: In asserting that the uncertainties in the underlying health science are as great 

or greater than in the last review and therefore do not support revision to the standards at 

this time, multiple commenters (e.g., API, 2012, pp. 1, 17 to 20, and Attachment 1, pp. 9 

to 24, Attachment 7, p. 9, Attachment 9; ACC, 2012, pp. 2 to 7, 14 to 18; NAM et al., 

2012, pp. 9, 23; AAM, 2012, pp. 5 to 15; AFPM, 2012, p. 3; Southern Company, 2012, 

pp. 2 to 3; EPRI, 2012, pp. 1 to 4; Texas CEQ, 2012, pp. 1 to 4; AFPM et al., 201, p. 32) 

discussed a number of issues related to: (a) copollutant confounding; (b) 

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

measurement error; (e) model specification; (f) the shape of the concentration-response 

(C-R) function; and (g) understanding the relative toxicity of components within the 

mixture of fine particles. 

Response: The EPA believes that the overall uncertainty about possible health risks 

associated with both long- and short-term PM2.5 exposure has diminished since the last 

review. The EPA disagrees with commenters’ views that the remaining uncertainties in 

the scientific evidence are too great to support revising the current PM2.5 NAAQS. The 

EPA has carefully considered the uncertainties highlighted by commenters in its 

evaluation of the scientific evidence as discussed in section III. D.2 of the preamble to the 

final rule and below: 
II-34 

(a) Copollutant confounding 

Some commenters asserted that the EPA has not adequately interpreted the results from 

studies that examined the effect of copollutants on the relationship between long- and 

short-term PM2.5 exposures and mortality and morbidity outcomes (e.g., NAM et al., 

2012, p. 23, ACC 2012, pp. 14 to 18). These commenters contended that the EPA has 

inappropriately concluded that PM2.5-related mortality and morbidity associations are 

generally robust to confounding. The commenters stated that statistically significant 

PM2.5 associations in single-pollutant models in epidemiological studies do not remain 

statistically significant in copollutant models. 

The EPA recognizes where PM2.5 and other pollutants are highly correlated, it can be 

difficult to distinguish effects of the various pollutants in copollutant models. The loss of 

statistical significance or the reduction in the magnitude of the effect estimate when a 

copollutant model is used may be the result of factors other than confounding. These 

changes do not prove either the existence or absence of confounding. These impacts must 

be evaluated in a broader context that considers the entire body of evidence. The broader 

examination of this issue in the ISA included a focus on evaluating the stability of the 

size of the effect estimates in epidemiological studies conducted by a number of research 

groups using single- and co-pollutant models (U.S. EPA, 2009a, sections 6.2.10.9, 

6.3.8.5, and 6.5, Figures 6-5, 6-9, and 6-15). This examination found that, for most 

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

copollutant models, although the ISA recognized that in some cases, the PM2.5 effect 

estimates were markedly reduced in size and lost statistical significance. 

In questioning the influence of co-pollutants on associations observed in short-term PM 

exposure and mortality studies, commenters highlighted the lack of control for 

copollutants in Dominici et al. (2003, 2007) and Franklin et al. (2007). The EPA 

recognized that a limitation of the multi-city studies that examined the association 

between short-term PM2.5 exposure and mortality evaluated in the ISA was the relative 

lack of copollutant analyses. This limitation was mentioned when evaluating the 

collective evidence and forming the causality determination for mortality. In Chapter 2 of 

the ISA (U.S. EPA, 2009a, p. 2-11), the EPA stated, “Although recently evaluated U.S.-

based multi-city studies did not analyze potential confounding of PM2.5 risk estimates by 

gaseous pollutants, evidence from the limited number of single-city studies evaluated in 

the 2004 PM AQCD (U.S. EPA, 2004) suggest that gaseous copollutants do not confound 

the PM2.5-mortality association. This is further supported by studies that examined the 

PM10-mortality relationship”, which were discussed in section 6.5.2.1 of the ISA (U.S. 

EPA, 2009a). 

These commenters also questioned the lack of copollutant analyses in long-term exposure 

and mortality studies. The EPA recognizes that a limited number of studies investigating 

the association between long-term exposure to PM2.5 and mortality have included 

copollutant models. As discussed in the previous review, the analysis of multiple 

pollutants from the ACS cohort observed increases in two-pollutant models that 

incorporated CO, NO2, and ozone, and were reduced only for models that incorporated 

SO2 (Krewski et al. 2000). The 2004 AQCD recognized, however, that SO2 is a precursor 
II-35 

for fine particle sulfates, which complicates the interpretation of copollutant model 

results. In a follow-up study of the ACS cohort restricted to just Los Angeles, CA (Jerrett 

et al. 2005), the authors observed that O3 “did not confound the relationship between 

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

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

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

PM2.5 did not change when NO2 was included in co-pollutants models. The results of 

these studies provide confidence that more recent reports with updated datasets are 

showing independent effects of PM2.5. 

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

inherent in assessing the issue of copollutant confounding. As discussed in the proposal 

(77 FR 38907, 38909, and 38910) and more fully in the ISA (USEPA, 2009a, sections 

6.2, 6.3, and 6.5), although copollutant models may be useful tools for assessing whether 

gaseous copollutants may be potential confounders, such models alone cannot determine 

whether copollutants are in fact confounders. The EPA believes that observing robust 

effect estimates after examination of copollutant models provides greater confidence in 

the observed associations between short- and long-term exposures to PM2.5 and mortality 

and morbidity, while recognizing that potential confounding by copollutants remains a 

very challenging issue to address, even with well-designed studies. Interpretation of the 

results of copollutant models is complicated by correlations that often exist among air 

pollutants, by the fact that some pollutants play a role in the atmospheric reactions that 

form other pollutants such as secondary fine particles, and by the statistical power of the 

studies in question inherent in the study methodology. For example, as discussed in 

response to Comment (12)(a) above, the every-third or sixth-day sampling schedule often 

employed for PM2.5 compared to daily measurements of gaseous copollutants drastically 

reduces the overall sample size to assess the effect of copollutants on the PM2.5-morbidity 

or mortality relationship, such that the reduced sample size can lead to less precise effect 

estimates (e.g., wider confidence intervals, as demonstrated in Burnett et al. (2004)). 

The EPA recognizes that when PM2.5 is correlated with gaseous pollutants it can be 

difficult to identify the effect of individual pollutants in the ambient mixture (77 FR 

38910). However, based on the available evidence, the EPA concludes epidemiological 

studies continue to support the conclusion that PM2.5 associations with mortality and 

morbidity outcomes are robust to the inclusion of gaseous copollutants in statistical 

models. The EPA evaluated the potential confounding effects of gaseous copollutants 

and, although it is recognized that uncertainties and limitations still remain, the Agency 

concluded the collective body of scientific evidence is “stronger and more consistent than 

in previous reviews providing a strong basis for decision making in this review" (77 FR 

38910/1). 

(b) Ecological/contextual confounding 

Some commenters contended that both short- and long-term PM2.5 exposure studies of 

mortality did not appropriately control for ecological or contextual confounders (ACC, 

2012, p. 3; API, 2012, Attachment 1, p. 14; NAM et al., 2012, p. 23). 
II-36 

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

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

evaluated (e.g., mortality or hospital admissions or emergency department visits). The 

confounders that fit these criteria for short-term exposure studies are related to weather 

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

specifically time-series studies, evaluated in the ISA all included weather covariates in 

their models to account for their potential confounding effects (U.S. EPA, 2009a, Chapter 

6). 

With regard to long-term exposure studies, a number of multilevel cohort studies (Naess 

et al. 2007; Jerrett et al. 2003; Jerrett et al. 2005) have evaluated individual-level and 

contextual, or ecologic-level variables as potential confounders. As reported in Jerrett et 

al. (2005), “Contextual effects occur when individual differences in health outcomes are 

associated with the grouped variables that represent the social, economic, and 

environmental settings where the individuals live, work, or spend time (e.g., poverty or 

crime rate in a neighborhood). These contextual effects often operate independently from 

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

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

the association between long-term exposure to PM2.5 and mortality, but that an 

independent effect of PM2.5 on mortality remains. For example, Jerrett et al. (2005) found 

that for PM2.5 (controlling for age, sex, and race), the relative risk was 1.24 (95% CI 1.11, 

1.37) for a 10 μg/m3

 exposure contrast. In a parsimonious model that controlled for 44 

different individual covariates and ecological confounder variables that both reduced the 

pollution coefficient and had associations with mortality, the relative risk was 1.11 (95% 

CI 0.99, 1.25) for the same exposure contrast. The EPA believes that the results of these 

studies provide confidence that more recent reports with updated datasets are showing 

independent effects of PM2.5. 

Additionally, commenters contended that non-traditional confounders have not been 

accounted for in epidemiological studies of short- and long-term exposure to air 

pollution, which could confound the associations observed (API, 2012, Attachment 1, p. 

14). These confounders include physical and psychological population stress factors. The 

EPA disagrees with these commenters because: (1) there is very limited evidence of 

stress affecting the air pollution-health effect relationship upon which to base the 

commenters assertion; (2) in order for stress to be a true confounder it would need to vary 

temporally (for short-term exposure studies) and spatially (for long-term exposure 

studies) with both air pollution concentrations and the health effect of interest, which has 

not been demonstrated; and (3) rather than stress acting as a true confounder, more than 

likely stress is on the causal pathway to the health effects that have been observed to be 

associated with air pollution. The EPA acknowledges that stress may contribute bias to 

epidemiological studies; however, stress more than likely would influence the magnitude 

of individual effect estimates in a single-city or multi-city study and not the trends of 

positive associations observed across studies conducted in multiple locations. 

(c) Heterogeneity in risk estimates 

Some commenters argued that the heterogeneity in risk estimates observed in multi-city 
II-37 

epidemiological studies and the lack of statistical significance in many regional or 

seasonal estimates highlights a potential bias associated with combined multi-city 

epidemiological study results (e.g., API, 2012, Attachment 1, pp. 15 to 19). Additionally, 

these commenters contended that the wide range of individual city results in these multicity studies, specifically NMMAPS, demonstrated a biologically implausible wide range 

of associations (e.g, AAM, 2012, pp. 6 to 10). One commenter asserted, “there is 

overwhelming epidemiologic evidence, dating back to 2000, which shows clear and large 

geographic variation in PM2.5 mortality risk across the United States. The PM2.5 mortality 

risk is much stronger in the eastern portion of the US than in the western portion of the 

U.S. and there is no PM2.5 mortality risk in California” (Enstrom, 2012, p. 1). Other 

commenters further argued that more refined intra-urban exposure estimates conducted 

for two of the largest cities included in the ACS study, Los Angeles and New York City, 

based on land-use regression models and/or kreiging methods (Krewski et al., 2009a) 

“underscore the importance of considering city-specific health estimates, which may 

account for heterogeneity in PM2.5 concentrations or other differences among cities, 

rather than relying on pooled nationwide results from multi-city studies” (API, 2012, 

Attachment 1, p. 17). 

With respect to understanding the nature and magnitude of PM2.5-related risks, the EPA 

agrees that epidemiological studies evaluating health effects associated with long- and 

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

effect estimates across geographic regions of the U.S. (U.S. EPA, 2009a, sections 

6.2.12.1, 6.3.8.1, 6.5.2, and 7.6.1; U.S. EPA, 2011a, p. 2-25). For example, when 

focusing on short-term PM2.5 exposure, the ISA found that multi-city studies that 

examined associations with mortality and cardiovascular and respiratory hospital 

admissions and emergency department visits demonstrated greater cardiovascular effects 

in the eastern versus the western U.S. (Dominici, et al., 2006a; Bell et al., 2008; Franklin 

et al. (2007, 2008)). However, the rationale that heterogeneity in risk estimates presents a 

potential bias as posed by the commenters is simplistic and does not account for a 

number of factors that have been shown to influence city-specific risk estimates in 

epidemiologic studies. As discussed in the ISA, the EPA recognizes that there are 

compositional differences in PM2.5 across the country and that the county-level air quality 

data used in epidemiological studies may result in exposure error, which could in part 

account for variability in city-specific risk estimates (U.S. EPA, 2009a, section 2.3.2). 

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

association between long-term exposure to PM2.5 and mortality. Krewski et al. (2009a) 

conducted subset analyses of the ACS cohort in Los Angeles, CA and New York City, 

NY, and observed a relative risk in Los Angeles that was greater in magnitude than what 

was observed in the full ACS cohort, while the relative risk in New York City was less 

than what was observed in the full ACS cohort. These observations are likely due to the 

greater spatial heterogeneity in PM2.5 concentrations observed in Los Angeles, and the 

overall spatial homogeneity of PM2.5 concentrations in New York City. 

In another retrospective cohort, Zeger et al. (2008) observed associations between longterm exposure to PM2.5 and mortality for the eastern and central ZIP codes that were 

similar to those reported in the ACS and Harvard Six Cities studies, though no 
II-38 

association was observed in the western region. The lack of the association in the western 

region is “largely because the Los Angeles basin counties (California) have higher PM 

levels than other West Coast urban centers, but not higher adjusted mortality rates” 

(Zeger et al. 2008). The ISA also evaluated studies that provided some evidence for 

seasonal differences in PM2.5 risk estimates, specifically in the northeast. The ISA found 

evidence indicating that individuals may be at greater risk of dying from higher 

exposures to PM2.5 in the warmer months, and at greater risk of PM2.5 associated 

hospitalization for cardiovascular and respiratory diseases during colder months of the 

year. The limited influence of seasonality on PM risk estimates in other regions of the 

U.S. may be due to a number of factors including varying PM composition by season, 

exposure misclassification due to regional tendencies to spend more or less time outdoors 

and air conditioning usage, and the prevalence of infectious diseases during the winter 

months (U.S. EPA, 2009a, p. 3-182). 

Overall, the EPA recognizes that uncertainties still remain regarding various factors that 

contribute to heterogeneity observed in epidemiological studies (77 FR 38909/3). 

Nonetheless, the EPA recognizes that this heterogeneity could be attributed, at least in 

part, to differences in PM2.5 composition across the U.S., as well as to exposure 

differences that vary regionally such as personal activity patterns, microenvironmental 

characteristics, and the spatial variability of PM2.5 concentrations in urban areas (U.S. 

EPA, 2009a, section 2.3.2; 77 FR 38910). 

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

city-specific speciated PM2.5 data does not allow conclusions to be drawn that specifically 

differentiate effects of PM in different locations (U.S. EPA, 2011a, p. 2-25). 

Furthermore, as discussed in section III.E.1 of the preamble to the final rule, the ISA 

concluded, “that many constituents of PM2.5 can be linked with multiple health effects, 

and the evidence is not yet sufficient to allow differentiation of those constituents or 

sources that are more closely related to specific health outcomes” (U.S. EPA, 2009a, p. 2-

17). CASAC thoroughly reviewed the EPA’s presentation of the scientific evidence 

indicating heterogeneity in PM2.5 effect estimates in epidemiological studies and 

concurred with the overall conclusions presented in the ISA. 

(d) Exposure measurement error 

Industry commenters argued that the EPA did not adequately consider exposure 

measurement error, which they asserted is an important source of bias in epidemiological 

studies that can bias effect estimates in either direction (e.g., API, 2012, Attachment 1, 

pp. 19 to 20). 

The EPA agrees that exposure measurement error is an important source of uncertainty, 

and that the variability in risk estimates observed in multi-city studies could be attributed, 

in part, to exposure error due to measurement-related issues (77 FR 38910). However, the 

Agency disagrees with the commenters’ assertion that exposure measurement error was 

not adequately considered by EPA in this review. The ISA included an extensive 

discussion that addresses issues of exposure measurement error (U.S. EPA, 2009a, 

sections 2.3.2 and 3.8.6). Exposure measurement error may lead to bias in effect 
II-39 

estimates in epidemiological studies. A number of studies evaluated in the last review 

(U.S. EPA, 2004, section 8.4.5) and in the current review (U.S. EPA, 2009a, section 

3.8.6) have discussed the direction and magnitude of bias resulting from specified 

patterns of exposure measurement error (Armstrong 1998; Thomas et al. 1993; Carroll et 

al. 1995) and have generally concluded “classical” (i.e., random, within-person) exposure 

measurement error can bias effect estimates towards the null. Therefore, consistent with 

conclusions reached in the last review, the ISA concluded “in most circumstances, 

exposure error tends to bias a health effect estimate downward” (U.S. EPA, 2009a, 

sections 2.3.2 and 3.8.6). Thus, the EPA has both considered and accounted for the 

possibility of exposure measurement error, and the possible bias would make it more 

difficult to detect true associations, not less difficult. 

Additionally a commenter specifically questioned the influence of exposure measurement 

error on the results from epidemiological analyses by referencing a study conducted by 

Sarnat et al. (2009) (API, 2012, Attachment 1, p. 19). This commenter stated: 

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

of PM2.5 in certain parts of the country), averaged over time, varied by individual, 

city and season, and this variability can lead to CRFs that do not represent the true 

relationship between exposure and outcome. These factors may bias the results of 

an epidemiology analysis in either direction and are particularly relevant for longterm studies (for which these factors likely vary over time). 

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

Sarnat et al. (2009) describes variability in the use of home ventilation (i.e., air 

conditioning) as a key factor contributing to both the bias and the variability in personal 

exposure. Air conditioning usage varies by individuals and between cities. Use of air 

conditioning results in the introduction of less outdoor air to the indoors, resulting in the 

central-site monitoring value overestimating exposure. In an epidemiological analysis, 

this condition causes the effect estimate to be biased towards the null, with some 

variability. Given the limiting condition that the maximum indoor concentration of 

ambient PM is that of the outdoors, the exposure error would not be expected to bias the 

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

bias can go in either direction. 

(e) Model specification 

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

appropriate statistical model for epidemiologic studies of air pollution involves several 

choices that involve much ambiguity, scant biological evidence, and a profound impact 

on analytic results, given that many estimated associations are weak” (ACC, 2012, p. 5) 

For short-term exposure studies, the EPA recognizes, as summarized in the HEI review 

panel commentary that selecting a level of control to adjust for time-varying factors, such 

as temperature, in time-series epidemiologic studies involves a trade-off (HEI, 2003). For 

example, if the model does not sufficiently adjust for the relationship between the health 

outcome and temperature, some effects of temperature could be falsely ascribed to the 

pollution variable. Conversely, if an overly aggressive approach is used to control for 
II-40 

temperature, the result would possibly underestimate the pollution-related effect and 

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

236; HEI, 2003, p. 266). The selection of approaches to address such variables depends in 

part on prior knowledge and judgments made by the investigators, for example, about 

weather patterns in the study area and expected relationships between weather and other 

time-varying factors and health outcomes considered in the study. As demonstrated in 

section 6.5 of the ISA, the EPA thoroughly considered each of these issues and the 

overall effect of different model specifications on the association between short-term 

PM2.5 exposure and mortality. Regardless of the model employed, consistent positive 

associations were observed across studies that controlled for the potential confounding 

effects of time and weather using different approaches (e.g., U.S. EPA 2009a, Figure 6-

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

considered the influence of model specification in the examination of long-term PM2.5

exposure studies. For example, in section 7.6, Figures 7-6 and 7-7, the ISA summarized 

the collective evidence that evaluated the association between long-term PM2.5 exposure 

and mortality. Regardless of the model used, these studies collectively found evidence of 

consistent positive associations between long-term PM2.5 exposure and mortality. 

The EPA, therefore, disagrees with commenters that model specification was not 

considered when evaluating the epidemiologic evidence used to form causality 

determinations. The EPA specifically points out that the process of assessing the 

scientific quality and relevance of epidemiologic studies includes examining “important 

methodological issues (e.g., lag or time period between exposure and effects, model 

specifications, thresholds, mortality displacement) related to interpretation of the health 

evidence (U.S. EPA, 2009a, p. 1-9).” Consistent with the conclusions of the 2004 PM 

AQCD, the EPA recognizes that there is still no clear consensus at this time as to what 

constitutes appropriate control of weather and temporal trends in short-term exposure 

studies, and that no single statistical modeling approach is likely to be most appropriate 

in all cases (U.S. EPA, 2004, p. 8-238). However, the EPA believes that the available 

evidence interpreted in light of these remaining uncertainties does provide increased 

confidence relative to the last review in the reported associations between short- and 

long-term PM2.5 exposures and mortality and morbidity effects, alone and in combination 

with other pollutants.

(f) Shape of the concentration-response relationship 

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

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

that there is a threshold in the PM-health effect relationship and that the log-linear model 

is not biologically plausible (API, 2012 pp. 17 to 20; API, 2012, Attachment 9; ACC, 

2012, Appendix A, pp. 7 to 8). The EPA disagrees with this assertion due to the number 

of studies evaluated in the ISA that continue to demonstrate a no-threshold log-linear 

model most adequately represents the PM concentration-response relationship (U.S. EPA, 

2009a, section 2.4.3). While recognizing that uncertainties remain, the EPA believes that 

our understanding of this issue for both long-and short-term exposure studies has 

advanced since the last review. As discussed in the ISA, both long- and short-term 

exposure studies have employed a variety of statistical approaches to examine the shape 
II-41 

of the concentration-response function and whether a threshold exists. While the EPA 

recognizes that there likely are individual biologic thresholds for specific health 

responses, the ISA concluded the overall evidence from existing epidemiological studies 

does not support the existence of thresholds at the population level, for effects associated 

with either long- or short-term PM exposures within the ranges of air quality observed in 

these studies (U.S. EPA, 2009a, section 2.4.3). While epidemiological analyses have not 

identified a population threshold in the range of air quality concentrations evaluated in 

these studies, the EPA recognizes that it is possible that such thresholds exist towards the 

lower end of these ranges (or below these ranges). This would be a concentration far 

lower than the level of the revised annual standard. The ISA concluded that this evidence 

collectively supported the conclusion that a no-threshold, log-linear model is most 

appropriate (U.S. EPA, 2009a, sections 6.2.10.10, 6.5.2.7, and 7.6.4). CASAC likewise 

advised that “[a]lthough there is increasing uncertainty at lower levels, there is no 

evidence of a threshold (Samet, 2010d, p. ii). 

The EPA recognizes that some short-term exposure studies have examined the PM C-R 

relationship in individual cities or on a city-to-city basis and observed heterogeneity in 

the shape of the C-R curve across cities. As discussed in (b) above, these findings are a 

source of uncertainty that the EPA agrees requires further investigation. Nonetheless, the 

ISA concluded that “the studies evaluated further support the use of a no-threshold, loglinear model, but additional issues such as the influence of heterogeneity in estimates 

between cities and the effects of seasonal and regional differences in PM on the 

concentration-response-relationship still require further investigation” (U.S. EPA, 2009a, 

p. 2-25). 

(g) Relative toxicity of components 

Some commenters highlighted uncertainties in understanding the role of individual 

constituents within the mix of fine particles. These commenters asserted that a massbased standard may not be appropriate due to the growing body of evidence indicating 

that certain PM2.5 components may be more closely related to specific health outcomes 

(e.g., elemental carbon (EC) and organic carbon (OC)) (EPRI, 2012, p. 2). 

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

particles, as a general matter, the EPA recognizes that although new research directed 

toward this question has been conducted since the last review, important questions 

remain and the issue remains an important element in the Agency’s ongoing research 

program. At the time of the last review, the Agency determined that it was appropriate to 

continue to control fine particles as a group, as opposed to singling out any particular 

component or class of fine particles (71 FR 61162 to 61164, October 17, 2006). This 

distinction was based largely on epidemiological evidence of health effects using various 

indicators of fine particles in a large number of areas that had significant contributions of 

differing components or sources of fine particles, together with some limited 

experimental studies that provided some evidence suggestive of health effects associated 

with high concentrations of numerous fine particle components. 

In this review, as discussed in the proposal (77 FR 38922 to 38923) and in section III.E.1 
II-42 

preamble to the final rule, while most epidemiological studies continue to be indexed by 

PM2.5 mass, several recent epidemiological studies included in the ISA have used PM2.5

speciation data to evaluate health effects associated with fine particle exposures. In the 

ISA, the EPA thoroughly evaluated the scientific evidence that examined the effect of 

different PM2.5 components and sources on a variety of health outcomes (U.S. EPA, 

2009a, section 6.6) and observed that the available information continues to suggest that 

many different chemical components of fine particles and a variety of different types of 

source categories are all associated with, and probably contribute to, effects associated 

with PM2.5. The ISA concluded that the current body of scientific evidence indicated that 

“many constituents of PM can be linked with differing health effects and the evidence is 

not yet sufficient to allow differentiation of those constituents or sources that are more 

closely related to specific health outcomes” (U.S. EPA, 2009a, p. 2-26 and 6-212). 

Furthermore, the PA concluded that the evidence is not sufficient to support eliminating 

any component or group of components associated with any specific source categories 

from the mix of fine particles included in the PM2.5 indicator (U.S. EPA, 2009a, p. 2-56). 

CASAC agreed that it was reasonable to retain PM2.5 as an indicator for fine particles in 

this review as “[t]here was insufficient peer-reviewed literature to support any other 

indicator at this time” (Samet, 2010c, p. 12). 

This information is relevant to the Agency’s decision to retain PM2.5 as the indicator for 

fine particles as discussed in section III.E.1 of the preamble for the final rule. The EPA 

also believes that it is relevant to the Agency’s conclusion as to whether revision of the 

suite of primary PM2.5 standards is appropriate. While there remain uncertainties about 

the role and relative toxicity of various components of fine PM, the current evidence 

continues to support the view that fine particles should be addressed as a group for 

purposes of public health protection and that “many constituents of PM can be linked 

with differencing health effects and the evidence is not yet sufficient to allow 

differentiation of those constituents or sources that are more closely related to specific 

health outcomes” such that it is inappropriate to remove any constituent of PM2.5 from the 

standard (U.S. EPA, 2009a, 2-17; U.S. EPA, 2011a, p. 2-25). 

In summary, in considering the above issues related to uncertainties in the underlying 

health science, on balance, the EPA believes that the available evidence interpreted in 

light of these remaining uncertainties does provide increased confidence relative to the 

last review in the reported associations between long- and short- term PM2.5 exposures 

and mortality and morbidity effects, alone and in combination with other pollutants, and 

supports stronger inferences as to the causal nature of the associations. The EPA also 

believes that this increased confidence, when taken in context of the entire body of 

available health effects evidence and in light of the evidence from epidemiological 

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

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

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

increased public health protection from exposure to all types of PM2.5. 

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

justify lowering the current annual PM2.5 standard, some commenters argued that, “if the 

current primary PM2.5 annual standard of 15 μg/m3

 was considered to be adequately 
II-43 

protective of public health in 2006, given relative risk estimates that EPA was using at 

that time, then that standard would surely still be adequately protective of the public 

health if relative risk estimates remain at the same level (or lower)” (UARG, 2012, 

Attachment 1, p. 24). These commenters compared risk coefficients used for mortality in 

the EPA’s risk assessment done in the last review with those from the Agency’s core risk 

assessment done as part of this review, and they concluded that “the entire range of the 

core relative risk for long-term mortality is lower now than it was in the prior review” 

(UARG, 2012, Attachment 1, p. 24). These commenters used this conclusion as the basis 

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

Response: The EPA believes that this claim is fundamentally flawed. In comparing the 

scientific understanding of the risk presented by exposure to PM2.5 between the last and 

current reviews, one must examine not only the quantitative estimate of risk from those 

exposures (e.g., the numbers of premature deaths or increased hospital admissions at 

various concentrations), but also the degree of confidence that the Agency has that the 

observed health effects are causally linked to PM2.5 exposure at those concentrations. As 

documented in the ISA and in the recommendations and conclusions of CASAC, the EPA 

recognizes significant advances in our understanding of the health effects of PM2.5, based 

on evidence that is stronger than in the last review. As a result of these advances, the 

EPA is now more certain that fine particles, alone or in combination with other 

pollutants, present a significant risk to public health at concentrations allowed by the 

current primary PM2.5 standards. From this more comprehensive perspective, since the 

risks presented by PM2.5 are more certain, similar or even somewhat lower relative risk 

estimates would not be a basis to conclude that no revision to the suite of PM2.5 standards 

is “requisite” to protect public health with an adequate margin of safety. The comment 

also ignores that the relative risk estimate is only one factor considered by the 

Administrator. Most obviously, it ignores that epidemiological studies since the last 

review indicate associations between PM2.5 and mortality and morbidity in areas meeting 

the current annual standard. 

In any case, the commenters’ reliance on the flawed 2006 review is badly misplaced. As 

discussed in section III.A.2 of the preamble to the final rule, the D.C. Circuit remanded 

Administrator Johnson’s 2006 decision to retain the primary annual PM2.5 standard 

because the Agency failed to adequately explain why the annual standard provided the 

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

protection for at-risk populations. The EPA, in fact, knows of no legitimate explanation. 

The 2006 standard was also at sharp odds with CASAC advice and recommendations as 

to the requisite level of protection (Henderson, 2006a,b). The judgment of the thenAdministrator that the 2006 primary annual PM2.5 standard was requisite to protect public 

health with an adequate margin of safety is thus not precedential and is an inappropriate 

benchmark for the comparison drawn in the comments. 

(14) Comment: One group of commenters who argued that a revised annual standard was not 

necessary to protect the public health asserted that the proposed standard was “far more 

stringent that the standards in other industrialized countries” (NAM et al., 2012, p.5). 

These commenters cited to standards set by the European Union and Japan Ministry of 

the Environment. Id. 
II-44 

Response: In considering these comments, as discussed in Comment (3) in section 

II.B.1.a above, the EPA notes that the Administrator’s decision on setting an appropriate 

annual standard level is constrained by the provision of the CAA that requires that the 

primary NAAQS be requisite to protect public health with an adequate margin of safety. 

This requires that her judgment is to be based on an interpretation of the evidence that 

neither overstates nor understates the strength and limitations of the evidence, or the 

appropriate inferences to be drawn from the evidence. This is not the same legal 

framework that governs the standards set by the European Union or Japan. 

As discussed in section III.E.4.d of the preamble for the final rule, the Administrator has 

considered the epidemiological and other scientific evidence, estimates of risk reductions 

associated with just meeting alternative standards, air quality analyses, related limitations 

and uncertainties, the advice of CASAC, and the extensive public comments on the 

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

PM2.5 standard levels, consistent with the requirements of the CAA. 

(15) Comment: Some of these commenters also identified “new” as well as older studies that 

had been included in prior reviews as providing additional evidence that the causality 

determinations presented in the ISA did not consider the totality of the scientific 

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

inappropriate.

Response: As discussed in section II.B.3 of the preamble to the final rule and in section 

II.B.1.a above, the EPA notes that, as in past NAAQS reviews, the Agency is basing the 

final decisions in this review on the studies and related information included in the PM 

ISA that have undergone CASAC and public review, and will consider newly published 

studies for purposes of decision making in the next PM NAAQS review. Nonetheless, in 

provisionally evaluating commenters’ arguments, the EPA notes that its provisional 

assessment of “new” science found that such studies did not materially change the 

conclusions reached in the ISA (U.S. EPA, 2012b).

2. Indicator 

The EPA received comparatively few public comments on issues related to the indicator 

for fine particles. No public comments were submitted regarding the use of a different size cut 

for fine particles. Public comments from all major public and private sector groups received on 

the proposal were generally in favor of the EPA’s proposal to retain PM2.5 as the indicator for 

fine particles. In addition to the responses contained in section III.E.1 of the preamble to the final 

rule, the EPA provides the following responses to specific issues related to the indicator for fine 

particles. 

(1) Comment: Some commenters emphasized the need to conduct additional research to 

more fully understand the effect of specific PM2.5 components and/or sources on public 

health. These commenters expressed views about the importance of evaluating health 

effect associations with various fine particle components and types of source categories 

as a basis for focusing ongoing and future research to reduce uncertainties in this area and 

for considering whether alternative indicator(s) may be appropriate to consider in future 
II-45 

PM NAAQS reviews for standards intended to protect against the array of health effects 

that have been associated with fine particles as indexed by PM2.5. For example, the PSR 

encouraged more research and monitoring related to PM2.5 components and noted the 

importance of components associated with coal combustion (PSR, 2012, pp. 5 to 6). 

EPRI asserted that “new” studies support focusing on elemental carbon (EC) and organic 

carbon (OC) and encouraged the EPA to seriously consider the mass-based approach 

(EPRI, 2012, p. 2). Likewise, Georgia Mining Association (GMA) supported additional 

monitoring and research efforts related to PM2.5 composition and specifically encouraged 

the evaluation of using particle number (e.g., particle count) (GMA, 2012, pp. 2 to 3). 

ALA et al. argued that causal conclusions of an European expert elicitation workshop 

(Knol et al., 2009) are stronger than the causal determinations reached in the ISA for 

ultrafine particles. These commenters suggested that “action is needed to establish 

ambient air quality standards for ultrafines in the next review cycle” (ALA et al., 2012, p. 

21). One group of commenter stated “Further delay in moving the process forward of 

acquiring the necessary data and beginning the long process of establishing and 

implementing a standard for ultrafine particles/nano particles represents an unacceptable 

health risk to the nation” (Sammons, et al., 2012, p. 6).

Response: The Administrator agrees with these commenters that the results of additional 

research and monitoring efforts will be helpful for informing future PM NAAQS reviews. 

Section 2.5 of the PA highlighted areas for future health-related research, model 

development, and data collection activities and recognized that “these efforts, if 

undertaken, could provide important evidence for information future PM NAAQS 

reviews, and, in particular, consideration of possible alternative indicators, averaging 

times, and/or levels” (U.S. EPA, 2011a, p. 2-106). The EPA recognizes that information 

from such studies could also help inform the development of strategies that emphasize 

control of specific types of emission sources so as to address particles of greatest concern 

to public health. 

These views are consistent with comments offered by CASAC. In general, “CASAC 

urges the Agency to reinvigorate research that might lead to new indicators that my be 

more directly linked to the health ad welfare effects associated with ambient 

concentrations of PM. CASAC also suggests the ongoing collection of more 

comprehensive PM monitoring data, including expanding the range of sizes to provide 

information in the ultrafine particle range, and adding measurements of numbers, 

chemistry, species, and related emissions characteristics of particles” (Samet, 2010d, p. 

iii). More specifically, CASAC asserted that “PM2.5 has been a useful surrogate index 

since it was adopted in the 1997 PM NAAQS promulgation, but may become an 

increasingly inadequate index of health risk as the mass concentration limits are 

reduced...While research evidence on PM and health has evolved, we urge the Agency to 

undertake additional efforts to leverage the gains made thus far. Now is the time to look 

ahead to future review cycles and reinvigorate support for the development of evidence 

that might lead to newer indicators that may correlate better with the health effects 

associated with ambient air concentrations of particulate matter (PM) and for more 

comprehensive PM monitoring data, including expanding the range of sizes, and adding 

measurements of numbers, chemistry, species, and related emissions characteristics of 

particles. There is an inherent feedback in the cycle from research to policy formulation 
II-46 

whereby researchers use the monitoring data that are gathered primarily for regulatory 

purposes with available indicators, and, in turn, expand the scientific basis for regulation. 

If EPA initiates efforts with air pollution research and monitoring communities now to 

create a more robust monitoring platform for research, the Agency will be better 

positioned to make an evidence-based transition to the ‘next generation’ of indicators of 

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

See also response to Comment (12)(g) in section II.B.1.b above. 

3. Averaging Time 

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

standards. One specific significant comment is addressed below. 

(1) Comment: As discussed in section III.E.2 of the preamble to the final rule, the EPA 

received no significant comments on the appropriateness of either the 24-hour or annual 

averaging times for the PM2.5 primary standards. However, one group representing 

several States (i.e., NESCAUM, 2012) suggested consideration of a rolling 24-hour 

average, rather than a midnight-to-midnight 24-hour average, for the 24-hour PM2.5

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

hour average, rather than the current midnight-to-midnight average, “would be 

particularly helpful in providing better public health protection in areas where there is the 

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

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

increase public health protection against exposures to PM2.5. As discussed in the 

preamble to the final rule (section III.E.4.c.ii), the Administrator has judged it appropriate 

to achieve such an increase in public health protection by lowering the level of the annual 

PM2.5 standard and retaining the current 24-hour PM2.5 standard. These judgments reflect 

in large part the Administrator’s consideration of ambient PM2.5 concentrations in the 

locations where long-term and short-term PM2.5 health studies have been conducted. The 

PM2.5 concentrations reported in these study locations are based on midnight-to-midnight 

sampling. 

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

commenters, would alter the PM2.5 concentrations reported and, thus, would alter the 

degree of health protection provided by the 24-hour standard. As discussed in section 

II.A of the preamble to the final rule, the CAA charges the Administrator with setting 

NAAQS that are “requisite” (i.e., neither more nor less stringent than necessary) to 

protect public health with an adequate margin of safety. In setting such standards, the 

Administrator must weigh the available scientific evidence and information, including 

associated uncertainties and limitations. In reaching her proposed decisions on the PM2.5

standards that would provide “requisite” protection, the Administrator carefully 

considered the available scientific evidence and risk information, making public health 

policy judgments that, in her view, neither overstated nor understated the strengths and 

limitations of that evidence and information. Commenters have not provided new 

information or analyses to support the appropriateness of the changes in public health 
II-47 

protection that could result from their recommended alterations in the sampling time 

period. 

4. Form 

The EPA received a number of public comments on the appropriate forms for the PM2.5

standards, primarily related to the spatial averaging provisions within the form of the annual 

standard. Few public commenters commented specifically on the form of the 24-hour standard. 

None of the public commenters raised objections to continuing the use of a concentration-based 

form for the 24-hour standard. 

Incorporating responses contained in sections III.E.3.a and III.E.3.b of the preamble to 

the final rule, the EPA provides the following responses to specific comments related to the form 

of (a) the annual PM2.5 standard and (b) the 24-hour PM2.5 standard. 

a. Annual Standard 

(1) Comment: Of the commenters noted in section III.D.2 of the preamble to the final rule 

and in section II.B.1.a above who supported a more stringent annual PM2.5 standard, 

those who commented on the form of the annual PM2.5 standard supported the EPA’s 

proposal to eliminate the spatial averaging provisions. These commenters contended that 

the EPA’s analyses of the potential impacts of spatial averaging, discussed in section 

III.E.3.a of the preamble to the final rule, demonstrated that the current form results in 

uneven public health protection leading to disproportionate impacts on at-risk 

populations. Specifically, the ALA and other environmental and public health 

commenters contended that “spatial averaging allows exposure of people to unhealthy 

levels of pollution at specific locales even within an area meeting the standard” (ALA et 

al., 2012, p. 23). These commenters particularly focused on the importance for lowincome and minority populations of eliminating the spatial averaging provisions. They 

concluded that spatial averaging “is an environmental justice concern because poor 

people are more likely to live near roads, depots, factories, ports, and other pollution 

sources.” Id. p. 24. ALA et al. further asserted that “in order for EPA to meet its 

Environmental Justice and Clean Air Act requirements dictating that all Americans be 

protected from environmental health concerns, spatial averaging must be removed” Id. p. 

25.

Other commenters (e.g., AAM, 2012; Dow, 2012) also supported the elimination of 

spatial averaging in order to “avoid potential disproportionate impacts on at-risk 

populations” and to maximize “the benefits to public health of reducing the annual PM2.5

standard.” However, these groups expressed concern that the elimination of spatial 

averaging, in combination with the requirement for near road monitors (as discussed in 

section VIII.B.3.b.i of the proposal), would effectively and inappropriately increase the 

stringency of the annual PM2.5 standard. 

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

spatial averaging. For example, the Class of ’85 RRG emphasized concerns about 

increasing the stringency of the standard while providing few health benefits if spatial 
II-48 

averaging is eliminated, particularly in combination with the requirement for near-road 

monitors. These commenters contended that “[b]ecause EPA proposes to use the readings 

from the highest single worst case monitor (rather than the average of all community area 

monitors), and since roadway monitoring locations will likely be worst case monitors, the 

proposed NAAQS will become more stringent without targeting the PM2.5 species most 

harmful to human health” (Class of ’85 RRG, 2012, p. 6). Other commenters argued that 

“unless the Agency adjusts the level of the NAAQS to account for the difference in 

concentrations at the community-based monitors used to set the standard and those at 

near-roach monitors, use of the latter to judge compliance with the NAAQS would be 

unreasonable” (API, 2012, p. 58). 

Several commenters also maintained that because spatial averaging is consistent with 

how air quality data are considered in the underlying epidemiological studies, such 

averaging should not be eliminated. Specifically, commenters including NAM et al., 

AFPM, API, and ACC pointed out that PM2.5 epidemiological studies use spatially 

averaged multi-monitor concentrations, rather than the single highest monitor, when 

evaluating health effects. Therefore, these commenters contended that allowing spatial 

averaging would make the PM2.5 standard more consistent with the approaches used in 

the epidemiological studies upon which the standard is based. One commenter argued 

that averaging measurements across multiple monitors in an area “would almost certainly 

also have included monitors in areas in which minorities and low-income individuals 

reside. Therefore, their potentially higher exposures would have been addressed in the 

epidemiological studies” (API, 2012, pp. 24 to 25). Thus, this commenter asserted that 

elimination of spatial averaging is not warranted. 

In addition, some commenters contended that the EPA failed to consider whether 

modifying, rather than eliminating, the constraints on spatial averaging would have been 

sufficient to protect public health. If so, these commenters argued that “elimination of 

spatial averaging would go beyond what is requisite to protect the public health” (NAM 

et al., 2012, p. 20). 

Response: In considering the public comments on the form of the annual standard, the 

EPA recognizes a number of commenters agreed with the basis for the EPA’s proposal to 

eliminate spatial averaging. While other commenters expressed disagreement or concern 

with the proposed decision to eliminate the spatial averaging provisions, the Agency 

notes that these commenters did not challenge the analyses or considerations that 

provided the fundamental basis for the Administrator’s proposed decision. These 

unchallenged analyses indicate that public health would not be protected with an 

adequate margin of safety in all locations, as required by law, if disproportionately higher 

exposure concentrations in at-risk populations such as low income communities as well 

as minority communities were averaged together with lower concentrations measured at 

other sites in a large urban area. Moreover, the Agency’s concern over possible 

disproportionate PM2.5-related health impacts in at-risk populations extends to 

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

populations that live near major roadways. 

Rather than addressing these analyses specifically, these commenters generally raised 
II-49 

concerns that eliminating the option for spatial averaging would increase the stringency 

of the standard, especially in light of additional monitoring sites in near-road 

environments as discussed in section VIII.B.3.b.1 of the preamble for the final rule. 

The EPA does not agree with the comment that siting some monitors in near roadway 

environments makes the standard more stringent or impermissibly more stringent. As 

discussed in section VIII.B.3.b.i of the preamble to the final rule, a significant fraction of 

the population lives in proximity to major roads, and these exposures occur in locations 

that represent ambient air. Monitoring in such areas does not make the standard more 

stringent than warranted, but rather affords the intended protection to the exposed 

populations, among them at-risk populations, exposed to fine particles in these areas. 

Thus, in cases where monitors in near roadway environments are deemed to be 

representative of area-wide air quality they would be compared to the annual standard (as 

discussed more fully in section VIII of the preamble to the final rule). The 24-hour and 

annual NAAQS are designed to protect the public with an adequate margin of safety, and 

this siting provision is fully consistent with providing the protection the standard is 

designed to provide and does not make the standard more stringent or more stringent than 

necessary. 

Monitors that are representative of area-wide air quality may be compared to the annual 

standard. This is consistent with the use of monitoring data in the epidemiological studies 

that provide the primary basis for determining the level of the annual standard. In 

addition, the EPA notes that the annual standard is designed to protect against both longand short-term exposures through controlling the broad distribution of air quality across 

an area over time.9

 It is fully consistent with the protection the standard is designed to 

provide for near road monitors to be compared to the annual standard if the monitor is 

representative of area-wide air quality. This does not make the standard either more 

stringent or impermissibly more stringent. 

The EPA notes that CASAC agreed that it was “reasonable” for the EPA to eliminate the 

spatial averaging provisions (Samet, 2010d, p. 2). Further, in CASAC’s comments on the 

first draft PA, it noted, “Given mounting evidence showing that persons with lower SES 

levels are a susceptible group for PM-related health risks, CASAC recommends that the 

provisions that allow for spatial averaging across monitors be eliminated for the reasons 

cited in the (first draft) Policy Assessment” (Samet, 2010c, p. 13). In its review of the 

second draft PA, CASAC recognized that “although much of the epidemiological 

research has been conducted using community-wide averages, several key studies 

reference the nearest measurement site, so that some risk estimates are not necessarily 

biased by the averaging process. Further, the number of such studies is likely to expand 

in the future” (Samet, 2010d, pp. 1 to 2). 

In considering CASAC advice and public comments, the EPA notes that the stringency or 

level of protection provided by each NAAQS is not based solely on the form of the 

standard; rather, the four elements of the standard that together serve to define each 

 

9

 This is in contrast to the 24-hour standard which is designed to provide supplemental protection, addressing peak 

exposures that might not otherwise be addressed by the annual standard. Consistent with this, monitors are not 

required to be representative of area-wide air quality to be compared to the 24-hour standard. 
II-50 

standard (i.e., indicator, averaging time, form, and level) must be considered collectively 

in evaluating the protection afforded by each standard, including the protection afforded 

to at-risk populations. Therefore, the EPA considers it appropriate to discuss these 

comments collectively with other issues related to the appropriate level for the annual 

standard as discussed in section III.E.4.c-d of the preamble and in section II.B.5.c below. 

The EPA notes further that this issue is similar to the issue of whether to base compliance 

with the standard on use of a maximum monitor or composite monitors. As explained in 

responses addressing that parallel issue, the EPA’s analysis of nationwide air quality 

patterns indicates that in many instances there is no difference at all, or minor difference, 

between maximum monitor results and those from composite monitors (Frank, 2012a.). 

Further, there were only a few other areas in which the maximum monitor mean 

concentration was appreciably higher than the composite monitor mean concentration, 

such as areas in which some monitors may be separately impacted by local sources. 

There were only 10 such areas in the country in which the maximum monitor mean 

concentration was between 2 to 6 μg/m3 higher than the composite monitor concentration 

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

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

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

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

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

with key underlying epidemiologic studies. 

Based on the analyses done to inform consideration of the form of the standard (Schmidt, 

2011, Analysis A), as well as the nationwide analysis of composite and maximum 

monitor values just discussed, the EPA concludes that spatial averaging (or a composite 

monitor approach) does not provide a margin of safety for the at-risk populations that live 

around the monitor measuring the highest concentration, such as in those few areas in 

which the maximum monitor concentration is appreciably higher than the composite 

monitor concentration. Thus, the comment that eliminating spatial averaging makes the 

standard more stringent misstates the issue. The proper question is what level of 

protection is requisite with an adequate margin of safety. If the standard needs to be made 

more stringent to provide such protection, then such stringency is not only permissible 

but required (or “appropriate” in the words of section 109 (d)). Diluting the needed 

protection by averaging monitoring results can demonstrably result in potentially 

disproportionate impacts on at-risk populations and so would fail to carry out the core 

statutory requirement to provide requisite protection to public health with an adequate 

margin of safety.10 

(2) Comment: One commenter argued that the rationale to support elimination of spatial 

averaging to potentially avoid disproportionate impacts on at-risk populations is flawed 

because the “evidence for greater susceptibility from PM exposures in these populations 

 

10 As noted in section II.A of the preamble to the final rule, the legislative history of section 109 indicates that a 

primary standard is to be set at “the maximum permissible ambient air level . . . which will protect the health of any 

[sensitive] group of the population,” and that for this purpose “reference should be made to a representative sample 

of persons comprising the sensitive group rather than to a single person in such a group.” S. Rep. No. 91-1196, 91st 

Cong., 2d Sess. 10 (1970). 
II-51 

is weak” (API, 2012, Attachment 1, pp. ES-2). Furthermore, this commenter asserted that 

the “evidence presented in the ISA and summarized in the PA and Proposed Rule in 

support of increased susceptibility to PM among children, older adults, those with preexisting heart and lung diseases, and those of lower SES is limited and inconsistent. This 

evidence does not add to the understanding or identification of susceptible populations, 

and it should not be used to support changes to the form of the annual PM2.5 standard” 

(API, 2012, Attachment 1, p. 47). 

Response: The EPA strongly disagrees with the commenter’s conclusion regarding the 

evidence for populations at increased risk for PM-related health effects. Chapter 8 of the 

ISA discusses the available evidence regarding at-risk populations, and why children, 

older adults, those with pre-existing heat and lung diseases, and those of lower SES are 

legitimately regarded as at-risk. For example, “[o]lder adults represent a potentially 

susceptible population due to the higher prevalence of pre-existing cardiovascular and 

respiratory diseases found in this age range compared to younger age groups.” (U.S. 

EPA, 2009 a, p. 8-3). Results of epidemiological and toxicological studies support this 

conclusion, and indicate as well increased susceptibility of older adults to all-cause 

mortality from short-term exposure, and increased susceptibility to respiratory morbidity 

and mortality. Id. at pp. 8-4 to 5. Children have generally been considered more 

susceptible to PM exposure due to factors such as more time spent outdoors, greater 

activity levels, exposures resulting in higher doses per body weight and long surface area, 

and the possibility of irreversible effects on the developing respiratory system. Id. p. 8-5. 

Two drafts of the ISA drawing these conclusions with regard to at-risk populations were 

reviewed by CASAC and by the public, and these same comments were before CASAC 

as part of that public comment process. CASAC found the “organization and 

presentation” of the evidence for at-risk populations presented in the ISA to be 

“complete, clear, and well-organized” (Samet, 2009f, p. 12). Furthermore, CASAC found 

that the “data presented fully justifies consideration of lower socioeconomic status (SES) 

people as a susceptible group” (Samet, 2010c. p. 11). Indeed, as noted above, one of the 

reasons CASAC supported eliminating spatial averaging from the form of the annual 

standard was due to the “mounting evidence showing that persons with lower SES levels 

are a susceptible group for PM-related health risks” (Samet, 2010c, p. 13). 

(3) Comment: Some commenters asserted that elimination of spatial averaging from the form 

of the annual standard “does not excuse EPA’s obligation under the CAA to set standards 

that explicitly incorporate a margin of safety” (ALA et al., 2012, p. 25). 

Response: The EPA agrees with the commenters that setting a standard that provides 

protection with an adequate margin of safety is not limited to considering the protection 

afforded by the form of the standard alone. As noted in section III.E.3.i of the preamble 

to the final rule, the EPA notes that the stringency or level of protection provided by each 

NAAQS is not based solely on the form of the standard, rather, the four elements of the 

of the standard that together serve to define each standard (i.e., indicator, averaging time, 

form, and level) must be considered collectively in evaluating the protection afforded by 

each standard. As discussed in section III.E.4, the EPA Administrator’s conclusions on 

the appropriate indicator, averaging time, form, and level are considered together in 
II-52 

reaching her final decision on the appropriate annual standard that will provide requisite 

public health protection with an adequate margin of safety. 

b. 24-Hour Standard 

(1) Comment: Many of the individuals and groups who supported a more stringent 24-hour 

PM2.5 standard noted in section III.D.2 of the preamble to the final rule and in section 

II.B.1.a above, however, recommended a more restrictive concentration-based percentile 

form, specifically a 99th percentile form. The limited number of these commenters who 

provided a specific rationale for this recommendation generally expressed their concern 

that the 98th percentile form could allow too many days where concentrations exceeded 

the level of the standard, and thus fail to adequately protect public health. Other public 

commenters representing state and local air agencies and industry groups generally 

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

expressed the overall view that the current 24-hour PM2.5 standard, including the form of 

the current standard, should be retained.

Response: The EPA notes that the viewpoints represented in this review are similar to 

comments submitted in the last review and through various NAAQS reviews. The EPA 

recognizes that the selection of the appropriate form includes maintaining adequate 

protection against peak 24-hour values while also providing a stable target for risk 

management programs, which serves to provide for the most effective public health 

protection in the long run.11

As discussed in section III.E.3.b of the preamble to the final rule, the PA considered air 

quality data reported in 2000 to 2008 to update our understanding of the ratio between 

peak-to-mean PM2.5 concentrations. This analysis provided evidence that the 98th

percentile value was a more stable metric than the 99th percentile (U.S. EPA, 2011a, 

Figure 2-2, p. 2-62).. In retaining the 98th percentile form, the Administrator focused on 

the relative stability of the 98th percentile form as a basis for her decision, while 

recognizing that the degree of public health protection likely to be afforded by a standard 

is a result of the combination of the form and level of the standard. 

5. Level 

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

basically expressed one of two substantively different views. As explained in section III.D.2 of 

the preamble to the final rule and in sections II.A and II.B.1 above, one group of commenters 

generally opposed any change to the current primary PM2.5 standards and more specifically 

disagreed with the basis for the EPA’s proposal to revise the annual standard level. Another 

group of commenters supported revising the current suite of primary PM2.5 standards to provide 

increased public health protection. Some commenters in this second group argued that both the 

 

11 As noted in section III.E.3.b of the preamble to the final rule, it is legitimate for the EPA to consider promotion of 

overall effectiveness of risk management programs designed to attain the NAAQS, including their overall stability, 

in setting a standard that is requisite to protect the public health. The context for the court’s discussion in ATA III is 

identical to that here; whether to adopt a 98th percentile form for a 24-hour standard intended to provide 

supplemental protection for a generally controlling annual standard. 
II-53 

annual and 24-hour standard levels should be lowered while other commenters in this group 

agreed with the EPA’s proposal to retain the level of the 24-hour standard in conjunction with 

revising the level of the annual standard. 

Many of these commenters simply expressed their views without stating any rationale, 

while others gave general reasons for their views but without reference to the factual evidence or 

rationale presented in the proposal notice as a basis for the Agency’s proposed decision 

regarding the levels of the primary PM2.5 standards. A number of commenters, including many 

environmental and public health organizations as well as state and local air agencies and health 

departments and tribes, who supported the revising the standard levels generally placed great 

weight on the recommendations of CASAC. Sections III.D.2 and III.E.4.c of the preamble to the 

final rule present the Agency’s response to these very general views. In addition to the discussion 

contained in those sections, the EPA provides the following responses to specific issues related 

to the levels for the primary PM2.5 standards. This includes comments on the general approach 

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

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

a. Annual Standard 

i. Support for Retaining the Current Level 

The group of commenters opposed to any change to the current suite of primary PM2.5

standards generally raised questions regarding the underlying scientific evidence, including the 

causal determinations reached in the ISA, and focused strongly on the uncertainties they saw in 

the scientific evidence as a basis for their conclusion that no changes to the current standard 

levels were warranted. In commenting on the proposed standard levels, these commenters 

typically relied on the arguments summarized and addressed in section III.D.2 of the preamble to 

the final rule and in section II.B.1.b above as to why they believed it was inappropriate for the 

EPA to make any revisions to the suite of primary PM2.5 standards. That is, they asserted that the 

EPA’s causal determinations were not adequately supported by the underlying scientific 

information; the biological plausibility of health effects observed in epidemiological studies has 

not been demonstrated in controlled human exposure and toxicological studies; uncertainties in 

the underlying health science are as great or greater than in 2006; there is no evidence of greater 

risk since the last review to justify tightening the current annual PM2.5 standard; and “new” 

studies not included in the Integrated Science Assessment continue to increase uncertainty about 

possible health risks associated with exposure to PM2.5. 

With regard to the level of the annual standard, these commenters strongly disagreed with 

the Agency’s proposed decision to revise the level to within a range of 12 to 13 μg/m3

 and 

argued that the current standard level of 15 μg/m3 should be retained. For example, UARG, API, 

and other commenters in this group raised a number of issues that they asserted called into 

question the EPA’s interpretation of the epidemiological evidence to support revising the annual 

standard level. These commenters raised specific questions related to the general approach used 

by the EPA to translate the air quality and other information from specific epidemiological 

studies into standard levels which are discussed in section III.E.4.c.i of the preamble to the final 

rule, including: 
II-54 

 the EPA’s approach for using composite monitor air quality distributions reported in 

epidemiological studies to select a standard level that would be compared to measurements at 

the monitor recording the highest value in an area to determine compliance with the standard; 

 the appropriate exposure period for effects observed in long-term exposure mortality studies; 

and 

 the use of the EPA’s analysis of distributions of underlying population-level data (i.e., health 

event and study population data) for those epidemiological studies for which such 

information was available. 

These commenters also raised questions regarding the EPA’s consideration of specific 

scientific evidence as a basis for setting a standard level, including: 

 evidence of respiratory morbidity effects in long-term exposure studies and 

 more limited evidence of health effects which have been categorized in the ISA as suggestive 

of a causal relationship (i.e., developmental and reproductive outcomes) 

These comments and other comments are discussed below. 

(1) Comment: Some commenters in this group argued that one reason why they believe there 

is no basis for setting a standard level below 15 μg/m3 is that the air quality metric from 

epidemiological studies that the EPA relied on in the proposal is not the same metric that 

will be compared to the level of the standard to determine compliance with the standard. 

That is, commenters noted that the long-term mean PM2.5 concentrations that the EPA 

considered, shown in Figure 4 of the preamble to the final rule, are composite monitor

mean concentrations (i.e., concentrations averaged across multiple monitors within areas 

with more than one monitor), whereas the PM2.5 concentrations that will be compared to 

the level of the standard are maximum monitor concentrations (i.e., the concentration 

measured by the monitor within an area reporting the highest concentration). This 

comment was presented most specifically in UARG’s comments (UARG, 2012, 

Attachment 1, pp. 2 to 6), which raised two overarching issues as discussed below. 

First, the commenter noted that the EPA’s approach of considering composite monitor 

mean PM2.5 concentrations in selecting a standard level, and then comparing the 

maximum monitor mean PM2.5 concentration in each area to the standard level when the 

standard is implemented, was characterized in the proposal as inherently having the 

potential to build in a margin of safety (UARG, 2012, Attachment 1, p. 4, citing 77 FR 

38905). The commenter asserted that the Administrator is ignoring this distinction 

between composite and maximum monitor concentrations, and that this approach creates 

an unwarranted case for lowering the standard level, since in the commenter’s view, it 

would result in a margin of safety that would be arbitrary, not based on evidence, and 

unquantified (UARG, 2012, Attachment 1, p. 4). In support of this view, the commenter 

asserted that there is a significant difference between composite monitor mean PM2.5

concentrations and maximum monitor mean PM2.5 concentrations. The commenter 

asserted that the maximum monitor value will always be higher than the composite 

monitor value (except in areas that contain only a single monitor), such that when an area 
II-55 

just attains the NAAQS, that area’s composite monitor long-term mean PM2.5

concentration will be lower than the level of the standard (UARG, 2012, Attachment 1, p. 

3). 

Second, the commenter asserted that a more “reasoned and consistent approach would be 

to decide on a mean composite monitor PM2.5 level that should be achieved and then 

identify the maximum monitor level that would result in that composite value” (UARG, 

2012, Attachment 1, p. 4). The commenter conducted an analysis of maximum monitor 

versus composite monitor annual mean PM2.5 concentrations using monitoring data12

from 2006 to 2008 and presented results averaged across areas within two groups (i.e., 

those with design values13 above the current standard level and those with design values 

just below the current standard level) to illustrate their suggested alternative approach. 

The commenter interpreted this analysis as showing that the composite monitor long-term 

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

Figure 4 (of the preamble to the final rule) that the commenter considered to be an 

appropriate focus for this analysis would be achieved across the U.S. if the current annual 

NAAQS of 15 μg/m3 is retained and attained. The commenter considered the subset of 

epidemiological studies that included only long-term exposures studies of effects for 

which the evidence is categorized as causal or likely causal, but did not consider shortterm exposure studies. On this basis, the commenter asserted that attaining the current 

annual PM2.5 standard would result in composite monitor long-term mean concentrations 

in all areas that would be generally within or below the range of the composite monitor 

long-term mean concentrations from such studies and, as a result, there is no reason to 

lower the level of the current annual NAAQS. 

Response: In considering the first issue related to the EPA’s approach, the EPA notes that 

in proposing to revise both the form and level of the annual standard, the Administrator 

clearly took into account the distinction between the composite monitor long-term mean 

PM2.5 concentrations from the epidemiological studies, considered as a basis for selecting 

an annual standard level, and maximum monitor long-term mean PM2.5 concentrations. In 

deciding to focus on the composite monitor long-term mean concentrations in selecting 

the standard level, and on the maximum monitor concentrations in selecting the form of 

the standard (i.e., consistent with proposing to eliminate the option for spatial averaging 

across monitors within an area when implementing the standard14), the Administrator 

reasonably considered the distinction between these metrics in a manner that was 

consistent with advice from CASAC (Samet et al., 2010d, pp. 2 to 3). 

As noted in section III.A.3 of the preamble to the final rule, the EPA recognizes that a 

statistical metric (e.g., the mean of a distribution) based on maximum monitor 

concentrations may be identical to or above the same statistical metric based on 

composite monitor concentrations. More specifically, many areas have only one monitor, 

 

12 The commenter indicated that this analysis was based on monitoring data for every core based statistical area 

(CBSA) in the EPA’s Air Quality System (AQS) database. 13 The design value is the air quality statistic that is compared to the level of the NAAQS to determine the attainment 

status of a given area. 14 As discussed in section III.E.3.a of the preamble to the final rule and in response to comment (1) in section 

II.B.4.a above. 
II-56 

in which case the composite and maximum monitor concentrations are identical. Based 

on the most recent data from the EPA’s AQS from 2009 to 2011 in the 331 CBSAs in 

which valid PM2.5 data are available, as discussed in Frank (2012a, Table 5), there were 

208 such areas (with design values ranging up to about 15 μg/m3

). Frank (2012a) also 

observed that other areas have multiple monitors with composite and maximum monitor 

mean PM2.5 concentrations that were the same or relatively close, with 57 areas in which 

the maximum monitor mean concentration was no more than 0.5 μg/m3

 higher than the 

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

0.6 and 2 μg/m3

. Further, there were only a few other areas in which the maximum 

monitor mean concentration was appreciably higher than the composite monitor mean 

concentration, such as areas in which some monitors may be separately impacted by local 

sources. There were only 10 such areas in the country in which the maximum monitor 

mean concentration was between 2 to 6 μg/m3

 higher than the composite monitor 

concentration (Frank, 2012a, Table 4).15 Thus, the EPA does not agree that there is a 

significant difference between composite monitor mean PM2.5 concentrations and 

maximum monitor mean PM2.5 concentrations in the large majority of areas across the 

country. 

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

III.E.3.a of the preamble to the final rule, the EPA noted that when an annual PM2.5

standard was first set in 1997, the form of the standard included the option for averaging 

across measurements at appropriate monitoring sites within an area, generally consistent 

with the composite monitor approach used in epidemiological studies, with some 

constraints intended to ensure that spatial averaging would not result in inequities in the 

level of protection for communities within large metropolitan areas. In the last review the 

EPA tightened the constraints on spatial averaging, and in this review has eliminated the 

option altogether, on the basis of analyses in each review that showed that such 

constraints may be inadequate to avoid substantially greater exposures for people living 

in locations around the monitors recording the highest PM2.5 concentrations in some 

areas, potentially resulting in disproportionate impacts on at-risk populations such as 

persons with lower SES levels. In light of these analyses, and consistent with the 

Administrator’s decision to revise the form of the annual PM2.5 standard by eliminating 

the option for spatial averaging, the EPA continues to conclude that a standard level 

based on consideration of long-term mean concentrations from composite monitors, and 

applied at each monitor within an area including the monitor measuring the highest 

concentration, is the appropriate approach to use in setting a standard that will protect 

public health, including the health of at-risk populations, with an adequate margin of 

safety, as required by the CAA. 

The EPA acknowledges that at proposal, the Agency characterized the approach of using 

maximum monitor concentrations to determine compliance with the standard, while 

selecting the standard level based on consideration of composite monitor concentrations, 

as one that inherently had the potential to build in a margin of safety (77 FR 38905), and 

 

15 The average difference between the maximum and composite design value among the 123 CBSAs with two or 

more monitors is 0.8 μg/m3 and the median difference is 0.6 μg/m3. The 25th and 75th percentiles are 0.3 and 1.0 

μg/m3

, respectively (Frank, 2012a, p. 4). 
II-57 

CASAC reiterated that view in supporting the EPA’s approach (Samet, 2010d, p. 3). 

Nonetheless, in light of the analysis discussed above, the EPA more specifically 

recognizes that this approach does not build in any margin of safety in the large number 

of areas across the country with only one monitor. Further, based on the analyses done to 

inform consideration of the form of the standard (Schmidt, 2011, Analysis A), the EPA 

concludes that this approach does not provide a margin of safety for the at-risk 

populations that live around the monitor measuring the highest concentration, such as in 

those few areas in which the maximum monitor concentration is appreciably higher than 

the composite monitor concentration. Rather, this approach properly treats those at-risk 

populations the same way it does the broader populations that live in areas with only one 

monitor, by providing the same degree of protection for those at-risk populations that 

would otherwise be disproportionately impacted as it does for the broader populations in 

other areas. Moreover, while the EPA recognizes that this approach can result in some 

additional margin of safety for the subset of areas with multiple monitors in which at-risk 

populations may not be disproportionately represented in areas around the maximum 

monitor, which may be the case in areas with relatively small differences between the 

maximum and composite monitor concentrations, the EPA notes that this margin would 

be relatively small in such areas. 

Based on the above considerations, the EPA does not agree that the Agency’s approach 

of using maximum monitor concentrations to determine compliance with the standard, 

while selecting the standard level based on consideration of composite monitor 

concentrations, creates an unwarranted case for lowering the standard level based on a 

margin of safety that would be arbitrary, not based on evidence, or lacking quantification. 

The EPA recognizes that setting a standard to protect public health, including the health 

of at-risk populations, with an adequate margin of safety, depends upon selecting a 

standard level sufficiently below where the EPA has found the strongest evidence of 

health effects so as to provide such protection, and that the EPA’s approach regarding 

consideration of composite and maximum monitor concentrations is intended to, and 

does, serve to address this requirement as part of and not separate from the selection of an 

appropriate standard level and form based on the health effects evidence. 

In considering the second issue related to the commenter’s suggested alternative 

approach, the EPA strongly disagrees with the commenter’s view that a more “reasoned 

and consistent approach would be to decide on a mean composite monitor PM2.5 level 

that should be achieved and then identify the maximum monitor level that would result in 

that composite value” (UARG, 2012, Attachment 1, p. 4). As discussed above, the EPA 

notes that for areas with only one monitor, or with multiple monitors that measure 

concentrations that are very close in magnitude, the maximum monitor level that would 

limit the composite monitor PM2.5 level to be no greater than the level that should be 

achieved to protect public health with an adequate margin of safety, would essentially be 

the same as that composite monitor level. Further, as discussed above, even for areas in 

which the maximum monitor concentration is appreciably higher than other monitor 

concentrations within the same area, public health would not be protected with an 

adequate margin of safety if the disproportionately higher exposures of at-risk, 

susceptible populations around the monitor measuring the highest concentration were in 

essence averaged away with measurements from monitors in other locations within large 
II-58 

urban areas. Further, the commenter’s suggested approach would be based on annual 

average PM2.5 concentrations that have been measured over some past time period. Such 

an approach would reflect the air quality that existed in the past, but it would not 

necessarily provide appropriate constraints on the range of concentrations that would be 

allowed by such a standard in the future, when relationships between maximum and 

composite monitor concentrations in areas across the country may be different. For these 

reasons, the EPA fundamentally rejects the commenter’s suggested approach because it 

results in a standard that demonstrably would not protect public health, including 

providing protection for at-risk populations, with an adequate margin of safety in areas 

across the country. 

More specifically, in further considering the commenter’s analysis of design values based 

on maximum versus composite monitor annual mean PM2.5 concentrations using 

monitoring data from 2006 to 2008 which they assert supports retaining the current 

standard level of 15 μg/m3

, the EPA finds flaws with the numerical results and the scope 

of the analysis, as well as flaws in the commenter’s translation of the analysis results into 

the basis for selecting an annual standard level. 

In considering the commenter’s analysis, the EPA notes that the analysis compared 

maximum versus composite monitor annual mean PM2.5 concentrations, averaged over 3 

years, for two groups of areas: (1) areas with design values that exceed the current annual 

standard level (i.e., greater than 15.0 μg/m3

) and (2) areas with design values that are just 

attaining the current annual standard (i.e., between 14.5 and 15.0 μg/m3

).16 The 

commenter indicated that they used the full body of PM2.5 monitoring data from the 

EPA’s AQS database (UARG, 2012, Attachment 1, p. 4). In attempting to reproduce the 

commenter’s results, the EPA repeated the calculations using only valid air quality data 

(i.e., data that meet data completeness and monitor siting criteria) from the AQS database 

for the same time period (Frank, 2012a).17 Based on this corrected analysis, the EPA 

finds that the composite monitor concentrations averaged across the areas within each 

group are somewhat higher than those calculated by the commenter, and the average 

differences between the maximum and composite monitor concentrations are somewhat 

smaller (Frank, 2012a, Table 3).18 Notably, the difference between the maximum and 

composite monitor average concentrations for the second group of areas is substantially 

 

16For the first group of areas (which included 33 areas), this analysis calculated an average across the areas of 

maximum monitor annual mean PM2.5 concentrations, averaged over 3 years, of 17.2 μg/m3

 compared to an average 

of composite monitor concentrations of 14.3 μg/m3

. For the second group of areas (which included 11 areas), this 

analysis calculated an average across the areas of maximum monitor annual mean concentrations, averaged over 3 

years, of 14.8 μg/m3

 compared to an average of composite monitor concentrations of 13.6 μg/m3 (UARG, 2012, 

Attachment 1, Table 1). 

17 The EPA notes that the Frank (2012a) analysis is similar to an earlier EPA staff analysis (Hassett-Sipple et al., 

2010), which used air quality data from the EPA’s AQS database to compare maximum versus composite monitor 

long-term mean PM2.5 concentrations across the study areas in six selected multi-city epidemiological studies. 18 The EPA’s analysis was intended to repeat the commenter’s analysis, but using only valid air quality data (from 

2006 to 2008). For the first group of areas (which included 21 areas with valid data), the EPA’s analysis calculated 

an average across the areas of maximum monitor annual mean concentrations, averaged of 3 years, of 16.8 μg/m3

compared to an average of composite monitor concentrations of 14.8 μg/m3

. For the second group of areas (which 

included 10 areas with valid data), the EPA’s analysis calculated an average across the areas of maximum monitor 

annual mean concentrations, averaged over 3 years, of 14.8 μg/m3

 compared to an average of composite monitor 

concentrations of 14.2 μg/m3

 (Frank, 2012a, Table 3).
II-59 

reduced in the corrected analysis, such that the difference (averaged across the 10 areas 

with valid data in the second group) is approximately 0.5 μg/m3

, not 1.2 μg/m3 as in the 

commenter’s analysis. In addition, the commenter’s analysis compared the average of 

the composite monitors to the average of the maximum monitors for each subset of areas. 

This comparison of averages across all the areas in each subset masks the fact that the 

large majority of areas across the country have only one monitor, with the composite 

monitor and maximum monitor values the same for such areas, and many other areas 

have a maximum monitor value that is close to the composite monitor value. As 

discussed above, these circumstances have a major impact on the protection that would 

be achieved by the approach suggested by the commenter. 

With regard to the scope of the commenter’s analysis, the EPA finds that by limiting the 

scope to a small subset of areas with design values above or just below the current annual 

standard level of 15 μg/m3, the analysis ignores the large number of areas across the 

country with lower design values that are relevant to consider in light of the 

epidemiological evidence of serious health effects at concentrations lower than 15 μg/m3

, 

well below the level of the current standard. 

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

commenter’s translation is premised on the view that the “natural focal point” for setting 

an annual PM2.5 standard level should be somewhere within the range of the long-term 

mean PM2.5 concentrations from the subset of epidemiological studies that included only 

long-term exposure studies of effects for which the evidence is categorized as causal or 

likely causal, but not for effects categorized as suggestive of causality, nor did it include 

short-term exposure studies (which are included in Figure 4 of the preamble to the final 

rule). Ignoring effects for which evidence of causality is suggestive is not consistent with 

setting a standard that would provide sufficient protection from the serious health effects 

reported even in the limited subset of studies considered by the commenter, much less 

protecting public health with an adequate margin of safety. Moreover, as discussed 

below, the EPA does not agree with the commenter’s view as to the appropriate focal 

point for selecting the level of an annual PM2.5 standard, or with the limited set of studies 

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

standard. 

Regarding an appropriate focal point for selecting the level of the annual standard, as 

discussed in the proposal and as advised by CASAC, the EPA has focused on PM2.5

concentrations somewhat below the lowest long-term mean concentrations from each of 

the key studies of both long- and short-term exposures of effects for which the evidence 

is causal or likely causal, as considered by the EPA (i.e., the first two sets of studies 

shown in Figure 4 of the preamble to the final rule and in the proposal, 77 FR 38933). If 

the level of the annual standard was set just somewhere within the range of the long-term 

mean concentrations from the various long-term exposure studies, then one or more of 

the studies would have a long-term mean concentration below the selected level of the 

standard. Absent some reason to ignore or discount these studies, which the commenter 

does not provide (and of which the EPA is unaware), setting such a standard would allow 

that level of air quality, where the evidence of health effects is strongest, and its 

associated risk of PM2.5-related mortality and/or morbidity effects to continue. Selecting 
II-60 

such a standard level could not be considered sufficient to protect the public health with 

an adequate margin of safety. 

Further, focusing on just the long-term mean PM2.5 concentrations in the key 

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

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

concentrations represent the part of the air quality distribution where the data in any 

given study are most concentrated and, thus, where the confidence in the magnitude and 

significance of an association in such study is strongest. However, the evidence of an 

association with adverse health effects in the studies is not limited to the PM2.5

concentrations just at and around the long-term mean, but rather extends more broadly to 

a lower part of the distribution, recognizing that no discernible population-level threshold 

for any such effects can be identified based on the available evidence. This broader 

region of the distribution of PM2.5 concentrations should be considered to the extent 

relevant information is available, recognizing that the degree of confidence in the 

association identified in a study would become lower as one moves below concentrations 

at and around the long-term mean concentration in any given study. The commenter’s 

approach ignores this fundamental consideration. 

Regarding the set of studies that is appropriate to inform the selection of the level of the 

annual PM2.5 standard, the EPA finds that limiting consideration only to the long-term 

exposure studies, as this commenter suggests, would be tantamount to ignoring the shortterm exposure studies,19 which provide some of the strongest evidence from the entire 

body of epidemiological studies. Thus, selecting an annual standard level using the 

limited set of studies suggested by the commenter would fail to provide a degree of 

protection that would be sufficient to protect public health with an adequate margin of 

safety. 

For all the reasons discussed above, the EPA finds the commenter’s concerns with the 

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

selecting the level of the annual PM2.5 standard to be without merit. Further, the EPA 

finds no support in the commenter’s analysis for their suggested alternative approach. 

(2) Comment: With respect to the appropriate exposure period for mortality effects observed 

in long-term exposure studies, some commenters in this group generally expressed views 

consistent with comments from UARG that argued that these studies “are most likely 

detecting health risk from earlier, higher PM2.5 levels and misattributing those risks to 

 

19 The commenter suggests that the EPA should not place significant reliance on the long-term mean concentrations 

from short-term exposure studies because “]the short‐term studies did not use the annual average of PM2.5 to develop 

their associations; they used the daily 24‐hour averages of PM2.5. Thus, short‐term studies do not provide a natural 

indicator for the appropriate level of an annual standard....” (UARG, 2012, Attachment 1, p. 3). The EPA finds this 

argument unpersuasive. Quite simply, effects were observed in these studies with an air quality distribution that can 

meaningfully be characterized by these long-term mean concentrations. Indeed, in remanding the 2006 standard, the 

D.C. Circuit discussed at length the interrelationship of the long- and short-term standards and studies, and 

remanded the 2006 standard to the EPA, in part, because the EPA had either ignored these relationships or had failed 

to provide an adequate explanation for disregarding them. American Farm Bureau Federation v. EPA. 559 F. 3d at 

522-24. 
II-61 

more recent, lower PM2.5 levels” (UARG, 2012, Attachment 1, p 7). Further, this 

commenter asserted that “there is no knowledge or evidence indicating whether 

premature deaths are the result of PM2.5 exposures in the most recent year; or due to 

physical damages incurred from PM2.5 exposures much earlier in life (with the impact on 

lifespan only emerging later in life); or due to total accumulated PM2.5 exposure over 

many years.” Id. In addition, the commenter asserted that the long-term exposure studies 

of mortality are central to the EPA’s basis for proposing to set a lower annual standard 

level, since most of the estimated benefits associated with a lower annual PM2.5 standard 

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

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

between PM2.5-associated effects due to past and recent long-term exposures, and in 

identifying the relevant latency period for long-term exposure to PM and resultant health 

effects (U.S. EPA, 2009a, section 7.6.4; 77 FR 38941/1). While the EPA has 

acknowledged that there remain important uncertainties related to characterizing the most 

relevant exposure periods in long-term exposure studies, the assertion that there is “no 

knowledge or evidence” that helps to inform this issue is not correct, as discussed below. 

Both in the last review and in the current review, the EPA has assessed studies that used 

different air quality periods for estimating long-term exposure and tested associations 

with mortality for the different exposure periods (U.S. EPA, 2004, section 8.2.3.5; U.S. 

EPA 2009a, section 7.6.4). In this review, the ISA discussed studies available since the 

last review that have assessed the relationship between long-term exposure to PM2.5 and 

mortality to explore the issue of the latency period between exposure to PM2.5 and death 

(U.S. EPA, 2009a, section 7.6.4). 

Notably, in a recent analysis of the extended Harvard Six Cities Study, Schwartz et al. 

(2008) used model averaging (i.e., multiple models were averaged and weighted by 

probability of accuracy) to assess exposure periods prospectively (77 FR 38907/1-2). The 

exposure periods were estimated across a range of unconstrained distributed lag models 

(i.e., same year, one year prior, two years prior to death). In comparing lags, the authors 

reported that the effects of changes in exposure to PM2.5 on mortality were strongest 

within a 2-year period prior to death (U.S. EPA, 2009a, p. 7-92, Figure 7-9). Similarly, a 

large multi-city study of the elderly found that the mortality risk associated with longterm exposure to PM10 reported cumulative effects that extended over the years that 

deaths were observed in the study population (i.e., the follow-up period) and for the 3-

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

Further, in a study of two locations that experienced an abrupt decline in PM2.5

concentrations (i.e., Utah Steel Strike, coal ban in Ireland), Röösli et al. (2005) reported 

that approximately 75 percent of health benefits were observed in the first 5 years (U.S. 

EPA, 2009a, Table 7-9). Schwartz et al. (2008) and Puett et al. (2008) found, in a 

comparison of exposure periods ranging from 1 month to 48 months prior to death, that 

exposure to PM10 24 months prior to death exhibited the strongest association, and the 

weakest association was reported for exposure in the time period of 1 month prior to 

death. 
II-62 

Overall, the EPA notes that the available evidence for determining the exposure period 

that is causally related to the mortality effects of long-term PM2.5 exposures, as discussed 

above, cannot specifically disentangle the effects observed in long-term exposure studies 

associated with more recent air quality measurements from effects that may have been 

associated with earlier, and most likely higher, PM2.5 exposures. While the evidence 

suggests that a latency period of up to five years would account for the majority of 

deaths, it does not provide a basis for concluding that it is solely recent PM2.5

concentrations that account for the mortality risk observed in such studies. Nonetheless, 

the more recent air quality data does well at explaining the relationships observed 

between long-term exposures to PM2.5 and mortality, with the strongest association 

observed in the two years prior to death. Further, the EPA recognizes that there is no 

discernible population-level threshold below which effects would not occur, such that it 

is reasonable to consider that health effects may occur over the full range of 

concentrations observed in the epidemiological studies, including the lower 

concentrations in the latter years. In light of this evidence and these considerations, the 

EPA concludes that it is appropriate to consider air quality concentrations that are 

generally contemporaneous with the collection of health event data (i.e., collected over 

the same time period) as being causally associated with at least some proportion of the 

deaths assessed in a long-term exposure study. This would include long-term mean PM2.5

concentrations from most of the key long-term exposure studies of effects with causal or 

likely causal evidence shown in Figure 4 of the preamble to the final rule, which reported 

long-term mean PM2.5 concentrations ranging from 13.6 μg/m3 to 14.3 μg/m3. These 

studies include studies of mortality by Eftim et al. (2008), which separately analyzed the 

ACS and Harvard Six City sites, Zeger et al. (2008), and Lipfert et al. (2006a), as well as 

studies of morbidity endpoints by Goss et al. (2004), McConnell et al. (2003) and 

Gauderman et al. (2004), and Dockery et al. (1996) and Razienne et al. (1996). The EPA 

acknowledges that uncertainty in the relevant exposure period is most notable in two 

other long-term exposure studies of mortality. The Miller et al. (2007) reported a longterm mean PM2.5 concentration for a 1-year exposure period that post-dated the follow-up 

period in which health event data were collected by two years. Also, the Krewski et al. 

(2009a) study reported a long-term mean PM2.5 concentration for an exposure period that 

included only the last two years of the 18-year follow-up period. Based on these 

considerations, the EPA does not now consider it appropriate to put weight on the 

reported long-term mean concentrations from these two studies for the purpose of 

translating the information from the long-term mortality studies into a basis for selecting 

the level of the annual PM2.5 standard.20

In addition, the EPA acknowledges that exposure periods that extend at least a couple 

years prior to the follow-up period in which health event data were collected would likely 

more fully capture the PM-related deaths in such studies. To explore how much higher 

the long-term mean PM2.5 concentrations would likely have been had air quality data 

prior to the follow-up years of the studies been included, the EPA conducted a sensitivity 

analysis of long-term mean PM2.5 concentrations (Schmidt, 2012a) particularly 

 

20 Nonetheless, the EPA notes that the Krewski et al. (2009) and Miller et al. (2007) studies provide strong evidence 

of mortality and cardiovascular-related effects associated with long-term PM2.5 exposures to inform causality 

determinations reached in the ISA (U.S. EPA, 2009a, sections 7.2.11 and 7.6). 
II-63 

considering studies that only included deaths from a relatively recent follow-up period. 

As examples of such studies, this analysis considered the Eftim et al. (2008) study of 

mortality in the ACS sites and the Harvard Six Cities sites, as well as sites in the eastern 

region in the Zeger et al. (2008) study. Using data from the EPA’s AQS database, the 

analysis added the two years of air quality data just prior to the follow-up period in each 

study, which was 2000 to 2002 in Eftim et al. (2008) and 2000 to 2005 in Zeger et al. 

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

for each study. As discussed in Schmidt (2012a), in each case the long-term mean PM2.5

concentration averaged over the extended exposure period was no more than 0.4 μg/m3

higher than the long-term mean PM2.5 concentration averaged over the follow-up period. 

The EPA finds it reasonable to conclude that such a relatively small difference in longterm mean PM2.5 concentrations would likely apply for other long-term exposure studies 

that used similarly recent follow-up periods as well (e.g., Goss et al., 2004; Lipfert et al., 

2006).

Based on the above considerations, the EPA concludes that it is appropriate to consider 

the available air quality information from the long-term exposure studies, while taking 

into account the uncertainties in the relevant long-term exposure periods in weighing the 

information from these studies. The EPA recognizes that considering such information in 

selecting an appropriate annual standard level has the potential to build in some margin of 

safety. The EPA further concludes that it is appropriate to consider the air quality 

information from the set of long-term exposure studies discussed above in the context of 

the broader array of epidemiological studies that inform the EPA’s consideration of the 

level of the annual PM2.5 standard. 

The EPA also notes that while the long-term exposure studies are an important 

component of the epidemiological evidence that informs the Agency’s consideration of 

the level of the annual standard, they do not provide the only relevant information, nor 

are they the set of studies for which the relevant long-term mean PM2.5 concentrations are 

the lowest. As discussed in the proposal, the EPA also considers the long-term mean 

PM2.5 concentrations from the short-term mortality and morbidity studies as providing 

important information in considering the level of the annual standard. As discussed 

above, a large proportion of the aggregate risk associated with short-term exposures 

results from the large number of days during which the 24-hour average concentrations 

are in the low- to mid-range of the concentrations observed in the studies. Thus, setting 

the level of the annual standard based on long-term mean concentrations, as well as the 

distribution of concentrations below the mean, in the short-term exposure studies is the 

most effective and efficient way to reduce total PM2.5-related risk from the broad array of 

mortality and morbidity effects associated with short-term exposures. 

Further, the EPA notes that the relevant exposure period for the short-term exposure 

studies is the period contemporaneous with the collection of health event data, and that 

this exposure period is not subject to the uncertainties discussed above related to the 

long-term exposure studies. Recognizing that the long-term mean PM2.5 concentrations 

from several of the multi-city short-term exposure studies shown in Figure 4 of the 

preamble to the final rule are below the long-term mean PM2.5 concentrations from the 
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long-term exposure studies (with the exception of Miller et al., 2007).21 It is reasonable 

that in selecting the level of the annual standard primary consideration should be given to 

the information from this set of short-term exposure studies. There is no reasonable basis 

to discount the long-term mean concentrations of the short-term exposure studies for 

purposes of setting the level of the annual standard. Thus, the commenter is incorrect in 

asserting that the long-term exposure studies, not the short-term exposure studies, would 

be central in the Administrator’s decision on the level of the annual standard. The 

standard is ultimately intended to protect not just against the single type of effect that 

contributes the most to quantitative estimates of risk to public health, but rather to the 

broad array of effects, including mortality and morbidity effects from long- and shortterm exposures across the range of at-risk populations impacted by PM2.5-related effects. 

(3) Comment: With regard to the EPA’s analysis of distributions of underlying populationlevel data (i.e., health event and study population data) and corresponding air quality data 

from each study area in certain key multi-city epidemiological studies (Rajan et al., 

2011), some commenters in this group raised a number of issues related to this analysis 

(e.g., McClellan, 2012; API, 2012, Attachment 1, pp. 5 to 6). Some commenters noted 

the limited number of studies for which health event and study population data were 

available, and questioned whether these distributions would apply to other studies. 

Commenters expressed concerns that this analysis had not been formally reviewed by 

CASAC and was not published in the peer-review literature. One commenter asserted 

that the data sets the EPA used in the distributional analysis were “not available to other 

scientists for critical independent analysis and interpretation” (McClellan, 2012, p. 2). 

Based on such concerns, some commenters asserted that the EPA should not consider this 

information as a basis for selecting a standard level. 

Response: As an initial matter, as discussed in section III.E.4.b of the preamble to the 

final rule and in previous responses in this document, the EPA agrees with CASAC’s 

advice that it is appropriate to consider additional data beyond the mean PM2.5

concentrations in key multi-city studies to help inform selection of the level of the annual 

PM2.5 standard. As both the EPA and CASAC recognize, in the absence of a discernible 

threshold, health effects may occur over the full range of concentrations observed in the 

epidemiological studies. Nonetheless, the EPA recognizes that confidence in the 

magnitude and significance of an association is highest at and around the long-term mean 

PM2.5 concentrations reported in the studies and the degree of confidence becomes lower 

at lower concentrations within any given study. Following CASAC’s advice (Samet, 

2010d, p.2), the EPA used additional population-level and air quality data made available 

by study authors to conduct an analysis of the distributions of such data, to help inform 

consideration of how the degree of confidence in the magnitude and significance of 

observed associations varies across the range of long-term mean PM2.5 concentrations in 

study areas within key multi-city epidemiological studies. In the EPA’s view, such 

consideration is important in selecting a level for an annual standard that will protect 

public health with an adequate margin of safety. 

 

21 As noted in sections III.E.4.c.i and III.E.4.d of the preamble to the final rule, the EPA is not placing weight on the 

reported long-term mean concentrations from the Miller et al. (2007) study for the purpose of translating the 

information from the long-term mortality studies into a basis for selecting the level of the annual PM2.5 standard. 
II-65 

With regard to the number of multi-city studies for which an analysis of the distributions 

of population-level data across the study areas and the corresponding annual mean PM2.5

concentrations was done, the EPA noted at proposal that data for such an analysis were 

made available from study authors for four studies, including two long-term exposure 

studies and two short-term exposure studies.22 The EPA recognized that access to health 

event data can be restricted due to confidentiality issues, such that it is not reasonable to 

expect that such information could be made available from all studies. In considering the 

information from these four studies, the EPA has further taken into consideration 

uncertainties discussed in response to the above comment related to the appropriate 

exposure period for long-term exposure studies. Based on these considerations, as noted 

above, the EPA concludes that such uncertainties are an important factor in evaluating the 

usefulness of the air quality information from the two long-term exposure studies in this 

analysis (Krewski et al., 2009a; Miller et al., 2007) and that it would not be appropriate to 

place weight on the distributional analysis of health event and air quality data from these 

two studies specifically for the purpose of translating the information from the long-term 

mortality studies into a basis for selecting the level of the annual PM2.5 standard. Such 

uncertainties are not relevant to the short-term exposure studies, and thus, the Agency 

focuses on the two short-term exposure studies in this analysis (Bell et al., 2008; 

Zanobetti and Schwartz, (2009). 

In focusing on these two short-term exposure studies, the EPA first notes that these 

studies are key multi-city studies that reported positive and statistically significant 

associations between mortality and cardiovascular-related hospital admissions across a 

large number of areas throughout the U.S. (112 U.S. cities in Zanobetti and Schwartz, 

2009; 202 U.S. counties in Bell et al., 2008) using relatively recent air quality and health 

event data (i.e., 1999 through 2005 in both studies). The EPA considers these two studies 

to comprise a modest but important data set to use for this distributional analysis in this 

review to help inform consideration of how much below the long-term mean PM2.5

concentrations in key multi-city long- and short-term exposure studies the annual PM2.5

standard level should be set. While the EPA acknowledges that having such data 

available from more studies would have been useful, the Agency finds the information 

from this limited set of studies to be useful for consideration in selecting an annual 

standard level, consistent with CASAC advice to consider such information. 

The results of this distributional analysis are shown in Figure 5 below (adapted from 

Figure 3 in Rajan et al., 2011). For each study, this figure shows the cumulative 

frequency of the number of health events in each study area and the corresponding longterm mean PM2.5 concentrations in each area. Consistent with CASAC advice (Samet, 

2010d, p.2), such an analysis helps to inform the EPA’s understanding of the long-term 

mean PM2.5 concentrations that were most influential in generating the health effect 

estimates in individual studies. In particular, the EPA recognizes that there is 

significantly greater confidence in the magnitude and significance of observed 

associations in that part of the air quality distribution corresponding to where the bulk of 

 

22 Health event data and study population data were available from two short-term exposure studies (Bell et al. 2008; 

Zanobetti and Schwartz, 2009) and one long-term exposure study (Krewski et al., 2009). Only study population data 

were available from another long-term exposure study (Miller et al., 2007). 
II-66 

the health events evaluated in each study have been observed. With regard to the part of 

the distribution in which confidence in the magnitude and significance of associations 

observed may become appreciably lower, the EPA considers PM2.5 concentrations 

between the 25th and 10th percentiles of the distribution of health events in these studies 

to be a reasonable range for providing a general frame of reference for that part of the 

distribution in which confidence in the magnitude and significance of the association may 

be appreciably lower than confidence at and around the long-term mean concentration. 

As highlighted in Figure 5, the long-term mean PM2.5 concentrations corresponding with 

study areas contributing to the 25th and 10th percentiles of the distribution of deaths and 

cardiovascular-related hospitalizations in the two short-term exposure studies were 12.5 

μg/m3

 and 10.3 μg/m3, respectively, for Zanobetti and Schwartz (2009), and 11.5 μg/m3

and 9.8 μg/m3

, respectively, for Bell et al. (2008). The EPA also recognizes, however, 

that there is no clear dividing line or single percentile within a given distribution 

(including both above and below the 25th percentile) provided by the scientific evidence 

that is most appropriate or ‘correct’ to use to characterize where the degree of confidence 

in the associations warrants setting the annual standard level. The decision as to the 

appropriate standard level below the long-term mean concentrations of the key studies is 

largely a public health policy judgment to be made by the Administrator, taking into 

account all of the evidence and its related uncertainties, as discussed in section III.E.4.d 

of the preamble to the final rule. 

In response to concerns that this analysis was not reviewed by CASAC nor published in 

the peer-reviewed literature, the EPA notes that this analysis was conducted to directly 

respond to advice from CASAC, as discussed in section III.E.4.b.1 of the preamble to the 
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final rule, in conjunction with their review of the PA. The EPA notes that the same type 

of distributional analysis was presented in the second draft PA based on air quality data, 

as well as on population-weighted air quality data, rather than on health event or study 

population data. In considering that distributional information, CASAC urged that the 

EPA redo the analysis using health event or study population data, which is exactly what 

the EPA did and presented in the final PA. The EPA provided CASAC with the final PA 

and communicated how the final staff conclusions reflected consideration of its advice 

and that those staff conclusions were based in part on the specific distributional analysis 

that CASAC had urged the EPA to conduct (Wegman, 2011, Attachment p. 2). CASAC 

did not choose to provide any additional comments or advice after receiving the final PA. 

The EPA considers this distributional analysis to be the product of the peer review 

conducted by CASAC of the PA, and thus does not agree with commenters’ 

characterization that the analysis lacked appropriate peer review. The EPA’s final 

analysis was based on the comments provided by CASAC, the peer review committee 

established pursuant to the CAA, on the draft analysis, such that the final analysis stems 

directly from CASAC’s advice and the EPA’s response to its comments. 

With regard to the availability of the underlying data sets, the EPA disagrees with the 

commenters’ assertion that these data are not publically available. As noted in the EPA 

staff technical memorandum, the underlying data sets provided by study authors are 

available in the rulemaking docket (Rajan et al., 2011, pp. 2 to 3). 

Based on the above considerations, the EPA continues to conclude that its analysis of 

distributions of health event and air quality data from two key multi-city epidemiological 

studies provides important information related to understanding the associations between 

health events observed in each city (e.g., deaths, hospitalizations) and the corresponding 

long-term mean PM2.5 concentrations observed in the studies. While recognizing that this 

is a relatively modest data set, the EPA further concludes that such information can 

appropriately help to inform the selection of the level of an annual standard that will 

protect public health with an adequate margin of safety from these types of health effects 

which are causally related to long- and short-term exposures to PM2.5.

(4) Comment: Some commenters in this group asserted there were limitations in the longterm exposure studies of morbidity, including studies evaluating respiratory effects in 

children. For example, one commenter (UARG, 2012, p. 12, Attachment 1, pp. 14 to 16) 

asserted there were serious limitations in the long-term exposure studies of respiratory 

morbidity in each of the studies considered by the EPA (including McConnell et al., 

2003; Gauderman et al., 2004; Dockery et al., 1996; Raizenne et al., 1996; and Goss et 

al., 2004) and argued that this evidence provides only a “weak association” with PM2.5

exposures. This commenter asserted that many of these long-term exposure studies 

evaluating respiratory effects were considered at the time the EPA reaffirmed the current 

annual standard level of 15 μg/m3 in 2006, that the Administrator in the last review 

determined that the information they provided “was too limited to serve as the basis for 

setting a level of a national standard,” and that they should be given little weight in 

setting the level of the annual standard in this review (UARG, 2012, Attachment 1, p. 

14). 
II-68 

More specifically, this commenter asserted that the McConnell et al. (2003) and 

Gauderman et al. (2004) studies reported mixed results for associations with PM2.5 and 

stronger associations with NO2 (API, 2012, Attachment 1, pp. 14 to 15). Similarly, this 

commenter argued that the Dockery et al. (1996) and Raizenne et al. (1996) studies 

showed stronger associations with acidity than with fine particles (measured as PM2.1). 

Id. pp. 15 to 16. With regard to the cystic fibrosis study, this commenter noted that the 

association between pulmonary exacerbations and PM2.5 in this study was no longer 

statistically significant when the model adjusted for each individual’s baseline lung 

function. The commenters referred to the data on lung function as an “important 

explanatory variable,” and suggested that the EPA should rely on results from the model 

that included individual baseline lung function information. Id. p. 16. 

Response: For the reasons discussed in section III.E.4.c.i of the preamble for the final 

rule, the response in section II.B.1.b above, and the further response below, the EPA 

disagrees with the commenters’ interpretation of these studies. 

As an initial matter, the EPA notes that three of these studies (McConnell et al., 2003; 

Dockery et al., 1996; Raizenne et al., 1996) as well as the initial studies from the 

Southern California Children’s Health Study (Peters et al., 1999; McConnell et al., 1999’ 

Gauderman et al., 2000, 2002; Avol et al., 2001) were discussed and considered in the 

2004 Air Quality Criteria Document (U.S. EPA, 2004) and, thus, considered within the 

air quality criteria supporting the EPA’s final decisions in the review completed in 2006. 

Two additional studies (Gauderman et al., 2004; Goss et al., 2004) were discussed and 

considered in the provisional science assessment conducted for the last review (U.S. 

EPA, 2006a). All of these studies were considered in the ISA that informs the current 

review (U.S. EPA, 2009a). 

With regard to the Southern California Children’s Health Study, extended analyses 

considered in the ISA provided evidence that clinically important deficits in lung 

function23 associated with long-term exposure to PM2.5 persist into early adulthood (U.S. 

EPA, 2009a, p. 7-27; Gauderman et al., 2004). These effects remained positive in 

copollutant models.24 Additional analyses of the Southern California Children’s Health 

Study cohort reported an association between long-term PM2.5 exposure and bronchitic 

symptoms (U.S. EPA, 2009a, p. 7-23 to 7-24; McConnell et al., 2003, long-term mean 

concentration of 13.8 μg/m3

) that remained positive in co-pollutant models, with the 

PM2.5 effect estimates increasing in magnitude in some models and decreasing in others, 

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

asthma incidence (U.S. EPA, 2009a, 7-24; Islam et al., 2007). The outcomes observed in 

the more recent reports from the Southern California Children’s Health Study, including 

 

23 Clinical significance was defined as an FEV1 below 80 percent of the predicted value, a criterion commonly used 

in clinical settings to identify persons at increased risk for adverse respiratory conditions (U.S. EPA, 2009a, p. 7-29 

to 7-30). The primary NAAQS for sulfur dioxide (SO2) also included this interpretation for FEV1 (75 FR 35525, 

June 22, 2010). 

24 Gauderman et al. (2004) clearly stated throughout their analysis that NO2 was one component of a highly 

correlated mixture that contains PM2.5. Gauderman et al. (2004) did not present the results from copollutants models 

but stated “two-pollutant models for any pair of pollutants did not provide a significantly better fit to the data than 

the corresponding single-pollutant models.” 
II-69 

evaluation of a broader range of endpoints and longer follow-up periods, were larger in 

magnitude and more precise than reported in the initial version of the study. Supporting 

these results were new longitudinal cohort studies conducted by other researchers in 

varying locations using different methods (U.S. EPA, 2009a, section 7.3.9.1). The EPA, 

therefore, disagrees with the commenters that the studies by McConnell et al. (2003) and 

Gauderman et al. (2004) are flawed and should not be used in the PM NAAQS review 

process. 

The 24-City study25 by Dockery et al. (1996) (long-term mean concentration of 14.5 

μg/m3

) was considered in the current as well as two previous reviews (U.S. EPA, 2009a; 

U.S. EPA, 2004; U.S. EPA, 1996). This study observed that PM, specifically “particle 

strong acidity” and sulfate particles (indicators of fine particles), were associated with 

reports of bronchitis in the previous year. Similarly, the magnitude of the associations 

between bronchitis and PM10 and PM2.1 were similar to those for acidic aerosols and 

sulfate particles, though the confidence intervals for the PM10 and PM2.1 associations 

were slightly wider and the associations were not statistically significant. Acid aerosols, 

sulfate, and fine particles are formed in secondary reactions of the emissions from 

incomplete combustion and these pollutants have similar regional and temporal 

distributions. As noted by the study authors, “the strong correlations of several pollutants 

in this study, especially particle strong acidity with sulfate (r=0.90) and PM2.1 (r=0.82), 

make it difficult to distinguish the agent of interest” (Dockery et al., 1996, p. 505). 

Overall, Dockery et al. (1996) (and, similarly, Raizenne et al., 1996) observed similar 

associations between respiratory health effects and acid aerosols, sulfate, PM10 and PM2.1

concentrations. The commenters noted that the associations with particle acidity were 

sensitive to the inclusion of the six Canadian sites. The EPA notes that none of these 

Canadian cities were in the “sulfate belt” where particle strong acidity was highest. Thus, 

the change in the effect estimate when the six Canadian cities were excluded from the 

analysis is likely due to the lower prevalence of bronchitis and the lower concentrations 

of acid aerosols in these cities, and not due to some difference in susceptibility to 

bronchitis between the U.S. and Canadian populations that is not due to air pollution, as 

suggested by the commenters (UARG, 2012, Attachment 1, p. 15). In fact, contrary to the 

statements made by the commenters, the authors did not observe any subgroups that 

appeared to be markedly more susceptible to the risk of bronchitis. 

The Goss et al. (2004) study considered a U.S. cohort of cystic fibrosis patients and 

provided evidence of association between long-term PM2.5 exposures and exacerbations 

of respiratory symptoms resulting in hospital admissions or use of home intravenous 

antibiotics (U.S. EPA, 2009a, p. 7-25; long-term mean concentration of 13.7 μg/m3). The 

commenters noted that the association between pulmonary exacerbations and PM2.5 in 

this study was no longer statistically significant when the model adjusted for each 

individual’s baseline lung function. The commenters referred to the data on lung function 

as an “important explanatory variable,” and suggested that the EPA should rely on results 

from the model that included individual baseline lung function information. The EPA 

 

25 The 24-City study conducted by Dockery et al. (1996) included 18 sites in the U.S. and 6 sites in Canada. The 

Raizenne et al. (1996) study considered 22 of these 24 study areas. Athens, OH and South Brunswick, NJ were not 

included in this study. 
II-70 

disagrees with the commenters’ interpretation of this study. The Agency concludes it is 

unlikely that lung function is a potential confounder or an important explanatory variable 

in this study. In fact, the authors noted that “it is more likely that lung function decline 

may be intimately associated with chronic exposure to air pollutants and may be part of 

the causal pathway in worsening prognosis in CF [cystic fibrosis]; in support of this 

explanation, we found both cross-sectional and longitudinal strong inverse relationships 

between FEV1 and PM levels” (Goss et al., 2004, p. 819). The EPA notes that adjusting 

for a variable that is on the causal pathway can lead to overadjustment bias, which is 

likely to attenuate the association (Schisterman et al. 2009); this is likely what was 

observed by the authors. Thus, the EPA continues to believe it is appropriate to focus on 

the results reported in Goss et al. (2004) that did not include individual baseline lung 

function in the model. 

In addition, the EPA disagrees with commenters’ reliance solely on statistical 

significance when interpreting the study results from individual study results and the 

collective evidence across studies. As discussed in section III.D.2 of the preamble to the 

final rule and in the response in section II.B.1.b above, statistical significance of 

individual study findings has played an important role in the EPA’s evaluation of the 

study’s results and the EPA has placed greater emphasis on studies reporting statistically 

significant results. However, in the broader evaluation of the evidence from many 

epidemiological studies, and subsequently during the process of forming causality 

determinations in the Integrated Science Assessment by integrating evidence from across 

epidemiological, controlled human exposure, and toxicological studies, the EPA has 

emphasized the pattern of results across epidemiological studies and whether the effects 

observed were coherent across the scientific disciplines for drawing conclusions on the 

relationship between PM2.5 and different health outcomes. The EPA notes further that the 

D.C. Circuit has held that the EPA can look to other indicia of reliability such as the 

consistency and coherence of a body of studies as well as other confirming data to justify 

reliance on the results of a body of epidemiological studies, even if individual studies 

may lack statistical significance. American Trucking Association v. EPA, 283 F. 3d at 371 

(in the context of discussing whether study results were confounded by co-pollutants). 

As noted in section III.B.1.a of the proposal, with regard to respiratory effects, the 

Integrated Science Assessment concluded that extended analyses of studies available in 

the last review as well as new epidemiological studies conducted in the U.S. and abroad 

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

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

available in this review was from epidemiological studies that evaluated decrements in 

lung function growth in children and increased respiratory symptoms and disease 

incidence in adults (U.S. EPA, 2009a, sections 2.3.1.2, 7.3.1.1, and 7.3.2.1). 

In considering the collective evidence from epidemiological, toxicological, and 

controlled human exposure studies, including the studies discussed above, the EPA 

recognizes that the Integrated Science Assessment concluded that a causal relationship is 

likely to exist between long-term PM2.5 exposures and respiratory effects (U.S. EPA, 

2009a, p. 2-12, pp. 7-42 to 7-43). CASAC concurred with this causality determination 

(Samet, 2009f, p.9). 
II-71 

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

as it did in the review completed in 2006 is significantly mistaken. Most obviously, the 

EPA’s final decision in the last review was held to be deficient by the D.C. Circuit in 

remanding the 2006 primary annual PM2.5 standard. As discussed in section III.A.2 of the 

preamble to the final rule, the D.C. Circuit specifically held that the EPA did not provide 

a reasonable explanation of why certain morbidity studies, including an earlier study 

from the Southern California Children’s Health Study (Gauderman et al., 2000, long-term 

mean PM2.5 concentration approximately 15 μg/m3

) and the 24-Cities Study (Raizenne et 

al., 1996, long-term mean concentrations approximately 14.5 μg/m3

) did not warrant a 

more stringent annual PM2.5 standard when the long-term mean PM2.5 concentrations 

reported in those studies were at or lower than the level of the annual standard. American 

Farm Bureau Federation v. EPA. 559 F. 3d at 525. Indeed, the court found that, viewed 

together, the Gauderman et al. (2000) and Raizenne et al., (1996) studies “are related and 

together indicate a significant public health risk...On this record, therefore, it appears the 

EPA too hastily discounted the Gauderman and 24-Cities studies as lacking in 

significance.” Id. 

In this review, the EPA recognizes a significant amount of evidence beyond these two 

studies that expands our understanding of respiratory effects associated with long-term 

PM2.5 exposures. This body of scientific evidence includes an extended and new analyses 

from the Southern California Children’s Health Study (Gauderman et al., 2004; Islam et 

al., 2007; Stanojevic et al., 2008) as well as additional studies that examined these health 

effects (Kim et al., 2004; Goss et al., 2004). Thus, even more so than in the last review, 

the evidence indicates a “significant public health risk” to children from long-term PM2.5

exposures at concentrations below the level of the current annual standard. A standard 

that does not reflect appropriate consideration of this evidence would not be requisite to 

protect public health with an adequate margin of safety. 

(5) Comment: With regard to the use of studies of health effects for which the EPA finds the 

evidence to be “suggestive” of a causal relationship, some commenters argued that such 

studies “do not merit any weight in the setting of the annual NAAQS” (e.g., UARG, 

2012, Appendix 1, p. 3). One commenter asserted that the proposed use of evidence that 

is only suggestive of a causal relationship to support revision to the primary annual PM2.5

standard is inconsistent with the EPA use of such evidence to retain the primary 24-hour 

PM10 standard and “represents a significant departure from the Agency’s precedent and is 

not justified” (AFPM, 2012, p. 2). 

Response: The EPA disagrees with the commenter’s view that studies of health effects 

for which the evidence is suggestive of a causal relationship, rather than studies of health 

effects for which the evidence supports a causal or likely causal relationship, merit no 

weight at all in setting the NAAQS. To place no weight at all on such evidence would in 

essence treat such evidence as though it had been categorized as “not likely to be a causal 

relationship.” To do so would ignore the important distinctions in the nature of the 

evidence supporting these different causality determinations in the ISA. It would also 

ignore the CAA requirement that primary standards are to be set to provide protection 

with an adequate margin of safety, including providing protection for at-risk populations. 

Thus, ignoring this information in making decisions on the appropriate standard level 
II-72 

would not be appropriate.26 Nonetheless, in considering studies of health effects for 

which the evidence is suggestive of a causal relationship, the EPA does believe that it is 

appropriate to place less weight on such studies than on studies of health effects for 

which there is evidence of a causal or likely causal relationship. 

The EPA also disagrees with the commenters’ assertion that the EPA’s bases for final 

decision on the primary PM2.5 and PM10 standards are inconsistent. As discussed in 

sections III.E.4.d and IV. G of the preamble to the final rule, in each case the EPA has 

considered the relevant available scientific evidence and the uncertainties and limitations 

associated with that evidence to reach final decisions on the appropriate primary PM2.5

and PM10 standards. 

(6) Comment: Some commenters questioned the long-term mean PM2.5 concentration 

reported in the final PA and used in Figure 4 of the proposal for the Miller et al. (2007) 

study (e.g., API, 2012, Attachment 1, p. 8; UARG, 2012, Attachment 1, pp. 2 to 3, fn 3, 

p. 12). 

Response: The EPA recognizes that the study authors originally reported a long-term 

mean PM2.5 concentration of 13.5 μg/m3

 (Miller et al., 2007, Table 2). This concentration 

was presented in the ISA (US EPA, 2009a) and discussed in the second draft PA (US 

EPA, 2010f). In response to a request from the EPA for additional information on the air 

quality data used in selected epidemiological studies (Hassett-Sipple and Stanek, 2009), 

study investigators provided updated air quality data for the study period. The updated 

long-term mean PM2.5 concentration provided by the study authors was 12.9 μg/m3

(personal communication from Cynthia Curl, 2009; Stanek et al., 2010). The final PA 

noted that this updated long-term mean concentration matched the composite monitor 

approach annual mean calculated by the EPA (Hassett-Sipple et al., 2010, Attachment A, 

p. 6) for the year of air quality data (i.e., 2000) considered by the study investigators 

(U.S. EPA, 2011a, p. 2-32, fn 24). The EPA staff concluded it was most appropriate to 

include the updated air quality data in the final PA (Id.). Thus, the long-term mean PM2.5

concentration for Miller et al. (2007) discussed in the proposal and presented in Figures 1 

and 4 of the proposal was reported as 12.9 μg/m3

. The PA noted that in comparison to 

other long-term exposure studies, the Miller et al. (2007) study was more limited in that it 

was based on only one year of air quality data (U.S. EPA, 2011a, p. 2-82). The proposal 

further noted that the air quality data considered were extrapolated from that one single 

year of air quality data (2000) to the whole study, and that the air quality data post-dated 

the years of health events considered (i.e., 1994 to 1998) (77 FR 38918, fn 62). 

For the reasons discussed in section III.E.4.c.i of the preamble to the final rule, the EPA 

does not now consider it appropriate to put weight on the reported long-term mean 

concentration from the Miller et al. (2007) study (either the original value reported in the 

published study nor the updated value provided by the study authors) for the purpose of 

 

26 As discussed in section II.A of the preamble to the final rule, the requirement that primary standards provide an 

adequate margin of safety was intended to address uncertainties associated with inconclusive scientific and technical 

information available at the time of standard setting. It was also intended to provide a reasonable degree of 

protection against hazards that research has not yet identified. This certainly encompasses consideration of effects 

for which there is evidence suggestive of a causal relationship. 
II-73 

translating the epidemiological information from the long-term exposure studies into a 

basis for selecting the level of the annual PM2.5 standard. Nonetheless, the EPA notes that 

the Miller et al. (2007) study provides strong evidence of cardiovascular-related effects 

associated with long-term PM2.5 exposures to inform causality determinations reached in 

the ISA (U.S. EPA, 2009a, sections 7.2.11 and 7.6). 

(7) Comment: Some commenters who supported retaining current annual standard level 

argued there is no basis for the EPA to select a level lower than 13 μg/m3

 (e.g., NAM et 

al., 2012, pp. 26 to 27; Class of ’85, 2012, p. 2; Dow, 2012, pp 1 to 3).

Response: The EPA disagrees with the commenters’ views that there is no basis to select 

a level below 13 μg/m3

. As discussed in section III.E.4.d of the preamble for the final 

rule, in light of the entire body of scientific evidence and technical analyses considered, 

the EPA Administrator judges that an annual standard level set above 12 would not be 

sufficient to protect public health with an adequate margin of safety from the serious 

health effects associated with long- and short-term PM2.5 exposures. 

(8) Comment: In raising objections to the requirement for near-road PM2.5 monitoring, one 

industry group (AFPM, 2012) compared the consideration of PM gradients around 

roadways in the current review to the consideration of NO2 gradients discussed in the 

most recent revision of the primary NO2 NAAQS (75 FR 6474, February 9, 2010). 

Specifically, in discussing the EPA’s decision to set a new 1-hour NO2 standard at a level 

of 100 parts per billion, these commenters stated the following: 

In taking this action, EPA noted that NO2 concentrations could be expected to vary, and 

therefore, the differences between near-roadway monitors and area-wide concentrations 

that had been used to measure compliance with the pre-existing NO2 annual standard 

could result in a variable level of the standard (i.e., between 50 ppb and 75 ppb based on 

whether concentrations near roadways were 100% or 30% higher than at other monitors). 

Yet, in this proposed rule, EPA does not offer any comparable analysis with respect to 

the relative stringency of a PM2.5 annual or 24-hour NAAQS as implemented through a 

network of new roadside monitors. 

Response: As explained in section III.E.4.c.i of the preamble to the final rule and in 

response to Comment (1) above, it is appropriate to compare the PM2.5 concentrations 

from a maximum area-wide monitor to the level of the annual PM2.5 standard. 

Consequently, the approach adopted in this rulemaking for the PM2.5 standard is 

consistent with the ultimate thrust of the approach in the NO2 NAAQS: providing a level 

of protection in an area with a maximum monitor affords requisite protection across the 

entire area. However, given differences in the bodies of available scientific evidence for 

NO2 and PM2.5, it is appropriate that the EPA employed different types of analyses in the 

two reviews to achieve this ultimate result. In the case of NO2, the scientific evidence that 

formed the basis for the final decision on the level of the revised standard included both 

epidemiological studies, reporting associations between respiratory endpoints and areawide NO2 concentrations, and controlled human exposure studies, reporting respiratory 

effects following short-term exposures to NO2 concentrations at or above 100 ppb. In 

considering this evidence, the Administrator set a new 1-hour standard with a level of 
II-74 

100 ppb. 

In setting this new standard, information on the NO2 gradients around roadways was used 

to consider the relationships between area-wide NO2 concentrations and potential 

exposure concentrations. Specifically, because the revised NO2 standard was intended to 

reflect the maximum allowable NO2 concentration in an area, the Administrator 

concluded that this standard would limit exposures to NO2 concentrations reported in 

controlled human exposure studies to result in respiratory effects. In reaching this 

conclusion, the Administrator noted that the highest NO2 exposure concentrations in 

urban areas could occur around major roadways. In addition, given the available evidence 

for NO2 concentration gradients around roadways, she concluded that the new standard 

would maintain area-wide NO2 concentrations (away from major roads) well below those 

in locations where key U.S. epidemiological studies had reported associations with 

adverse respiratory effects (75 FR 6501, February 9, 2010). 

In the current review of the PM NAAQS the scientific evidence forming the basis for 

final decisions on the PM2.5 standards includes epidemiological studies reporting 

associations between area-wide PM2.5 concentrations and a number of adverse health 

outcomes (i.e., including mortality and a variety of cardiovascular and respiratory 

effects). While controlled human exposure studies of PM2.5 provide coherence and 

biological plausibility for the effects observed in epidemiological studies, because of the 

exposure concentrations and durations evaluated they do not provide an appropriate basis 

to inform decisions on the levels of the 24-hour or annual standards. In light of this 

fundamental difference in the bodies of evidence available for NO2 and PM2.5, the 

approach to considering NO2 roadway concentration gradients adopted in the most recent 

review of the primary NO2 NAAQS would not similarly inform the Administrator’s 

decisions in the current review of the PM NAAQS.27 Therefore, the same approach would 

not be warranted in the two reviews. 

(9) Comment: One group of commenters asserted that “the supplemental 24-hour standard 

adds to the margin of safety that protects children and other sensitive subpopulations” 

(NAM et al., 2012, p. 9). These commenters argued that when the 24-hour standard is 

“controlling” the long-term mean PM2.5 concentrations were reduced well below the 

existing or proposed annual standard level. Thus, these commenters expressed the view 

that “the existing annual standard, when considered along-side the 24-hour standard, is 

not only requisite to protect the public health, but also ensures an adequate margin of 

safety for sensitive subpopulations” Id. 

Response: The EPA agrees with the first point raised by the commenters; that is, the 

24-hour standard provides supplemental protection beyond the protection provided by the 

annual standard. The EPA recognizes that the protection afforded by the two standards 

working together meets the CAA requirement to set primary standards that provide 

 

27 See also comments of UARG at 55 n. 73 drawing this same distinction (“The fact that the level of the PM2.5

NAAQS is derived solely from epidemiological studies distinguishes it from the NO2 NAAQS for which, as EPA 

notes, 77 Fed. Reg. at 39010/2-3, it recently adopted near-road monitoring requirements. That standard was based, 

in significant part, on controlled human exposure studies in which actual NO2 exposures were measured that could 

reasonably be compared to concentrations measured near roads. 75 Fed. Reg. at 6500/1-01/2.”). 
II-75 

requisite public health protection with an adequate margin of safety, including providing 

protection for at-risk populations. 

With regard to the second point raised by these commenters, the EPA disagrees with the 

commenters’ view that if the 24-hour standard is “controlling,” the long-term mean PM2.5

concentrations would be reduced well below the existing or proposed annual standard 

level. This comment would only be true if the 24-hour standard level was substantially 

lowered. As illustrated in Figure 2-10 of the PA, based on 2007 to 2009 air quality data, 

many counties across the country would likely meet the current 24-hour PM2.5 standard 

of 35 μg/m3

 but not the current or alternative annual standard, i.e., the lower right 

quadrant of the figure characterizing counties where the annual standard would be the 

controlling standard (U.S. EPA, 2011a, p. 2-90). 

Furthermore, the EPA recognized in the section III.A.3 of the proposal that there are 

various ways to combine the annual and 24-hour standards to achieve an appropriate 

degree of protection. The extent to which these two standards are interrelated in any 

given area depends in large part on the relative levels of the standards, the peak-to mean 

ratios that characterize air quality patterns in an area, and whether changes in air quality 

designed to meet a given suite of standards are likely to be of a more regional or more 

localized nature (77 FR 38902), While the EPA recognized that changes designed to meet 

a 24-hour standard would result not only in fewer and lower peak 24-hour concentrations 

(especially when coupled with a high percentile-based form, such as the 98th percentile) 

but also in lower annual mean concentrations, the EPA also noted that changes in PM2.5

air quality designed to meet an annual standard would likely result not only in lower 

annual average PM2.5 concentrations but also in fewer and lower peak 24-hour PM2.5

concentrations. As discussed in section III.E.4.d of the preamble to the final rule, based 

on the evidence and quantitative risk assessment, the EPA concludes that it is appropriate 

to setting an annual standard that is generally controlling, which will lower the broad 

distribution of 24-hour average concentrations in a area as well as the annual average 

concentration, so as to provide protection from both long- and short-term PM2.5

exposures, with the 24-hour standard providing supplemental protection. The EPA 

concludes this approach will reduce aggregate risks associated with both long- and shortterm exposures more consistently than a generally controlling 24-hour standard and is the 

most effective and efficient way to reduce total PM2.5-related population risk and so 

provide appropriate protection. 

(10) Comment: One commenter argued that “data from the available epidemiological studies 

suggest that effects of chronic PM exposure are reversible and that even small reductions 

in PM levels decrease cardiovascular mortality within a time frame as short as a few 

years (Dow, 2012, pp. 2 to 3). 

Response: The EPA disagrees that all effects of chronic PM exposure are reversible. The 

ISA concluded that there is a causal relationship between long-term PM2.5 exposure and 

mortality (U.S. EPA, 2009a, sections 2.3.1 and 7.6), obviously an irreversible effect. 

Furthermore, with regard to morbidity effects, extended analyses of the Southern 

California Children’s Health Study provide evidence that clinically important deficits in 
II-76 

lung function associated with children’s long-term exposure to PM2.5 persisted into early 

adulthood (77 FR 38907; U.S. EPA, 2009a, p. 7-27; Gauderman et al., 2004). 

The EPA agrees with the commenter’s assertion that improvements in community health 

related to reducing PM2.5 concentrations do not require a long latency period. As noted in 

the proposal (77 FR 38907), the strength of the causal relationship between long-term 

PM2.5 exposure and mortality also builds upon new studies providing evidence of 

improvement in community health following reductions in ambient fine particles. Pope et 

al. (2009) documented the population health benefits of reducing ambient air pollution by 

correlating past reductions in ambient PM2.5 concentrations with increased life 

expectancy. These investigators reported that reductions in ambient fine particles during 

the 1980s and 1990s account for as much as 15 percent of the overall improvement in life 

expectancy in 51 U.S. metropolitan areas, with the fine particle reductions reported to be 

associated with an estimated increase in mean life expectancy of approximately 5 to 9 

months (U.S. EPA, 2009a, p. 7–95; Pope et al., 2009). An extended analysis of the 

Harvard Six Cities study found that as cities cleaned up their air, locations with the 

largest reductions in PM2.5 saw the largest improvements in reduced mortality rates, 

while those with the smallest decreases in PM2.5 concentrations saw the smallest 

improvements (Laden et al., 2006). Another extended follow-up to the Harvard Six Cities 

study investigated the delay between changes in ambient PM2.5 concentrations and 

changes in mortality (Schwartz et al., 2008) and reported that the effects of changes in 

PM2.5 were seen within the 2 years prior to death (U.S. EPA, 2009a, p. 7–92; Figure 7–9). 

Looking more broadly across studies, the ISA concluded, “Generally, these results 

indicate a developing coherence of the air pollution mortality literature, suggesting that 

the health benefits form reducing air pollution do not require a long latency period and 

would be expected within a few years of intervention” (U.S. EPA, 2009a, p. 7-95).

(11) Comment: One commenter recognized the need to protect human health and supported 

the EPA’s effort to set a primary annual PM2.5 standard that protects human health with 

an adequate margin, as required by the CAA. However, this commenter asserted that the 

“EPA should consider the impact of using background levels in establishing the standard. 

If the annual PM standard is set close to or below background level, it would be 

impossible for nonattainment ares to attain the standard (AASHTO, 2012, p.2). This 

commenter recommended that “the standard be set at a level that is realistic and 

attainable since the standard will lose its meaning as background levels are approached.” 

Id. 

Response: The EPA notes that the PM2.5 standard levels established in the final rule (i.e., 

an annual standard level of 12 μg/m3 and a 24-hour standard level of 35 μg/m3) are well 

above the policy-relevant background concentrations considered in the ISA (U.S. EPA, 

2009a, sections 3.6, 3.7 and 3.9.1.7). Therefore, the concern raised by the commenter 

remains simply an academic one. 

(12) Comment: Some of these commenters also identified “new” studies as providing 

additional evidence to support their views that the annual standard level does not need to 

be revised.
II-77 

Response: As discussed in section II.B.3 of the preamble to the final rule and in section 

II.B.1.a above, the EPA notes that, as in past NAAQS reviews, the Agency is basing the 

final decisions in this review on the studies and related information included in the PM 

ISA that have undergone CASAC and public review, and will consider newly published 

studies for purposes of decision making in the next PM NAAQS review. Nonetheless, in 

provisionally evaluating commenters’ arguments, the EPA notes that its provisional 

assessment of “new” science found that such studies did not materially change the 

conclusions reached in the ISA (U.S. EPA, 2012b).

ii. Support for Revising the Current Level 

A second group of commenters supported revising the suite of primary PM2.5 standards to 

provide increased public health protection. These commenters found the available scientific 

information and technical analyses to be stronger and more compelling than in the last review. 

These commenters generally placed substantial weight on CASAC advice and on the EPA staff 

analyses presented in the final PA. While generally supporting the EPA’s proposal to lower the 

level of the annual standard, many commenters in this group disagreed that a level within the 

EPA’s proposed range (i.e., 12 to 13 μg/m3

) was adequately protective and supported a level of 

11 μg/m3 or below. 

In general, these commenters expressed the view that given the strength of the available 

scientific evidence, the serious nature of the health effects associated with PM2.5 exposures, the 

large size of the at-risk populations, the risks associated with long- and short-term PM2.5

exposures, and the important uncertainties inherently present in the evidence, the EPA should 

follow a highly precautionary policy response by selecting an annual standard level that 

incorporates a large margin of safety. 

More specifically, these commenters offered a range of comments related to the general 

approach used by the EPA to select standard levels, including: (1) the EPA’s approach for setting 

a generally controlling annual standard; (2) the importance of the greatly expanded and stronger 

overall scientific data base; (3) consideration of the distributional statistical analysis conducted 

by the EPA and other approaches for translating the air quality information from specific 

epidemiological studies into standard levels; and (4) the significance of the PM2.5-related public 

health impacts, especially potential impacts on at-risk populations, including children, in 

reaching judgments on setting standards that provide protection with an adequate margin of 

safety. These comments are discussed in turn below. 

(1) Comment: Some of these commenters disagreed with the EPA’s approach for setting a 

“generally controlling” annual standard in conjunction with a 24-hour standard providing 

supplemental protection particularly for areas with high peak-to-mean ratios. These 

commenters argued this approach would lead to “regional inequities” as demonstrated in 

the EPA’s analyses contained in Appendix C of the PA (ALA et al., pp. 26 to 27). 

Specifically, these commenters argued: 

There is no basis in the CAA for such a determination. The CAA requires only 

that the NAAQS achieve public health protection with an adequate margin of 

safety. It is well-documented that both long- and short-term exposures to PM2.5
II-78 

have serious and sometimes irreversible health impacts. There is no health 

protection reason to argue that one standard should be “controlling” as a matter of 

policy without regard to the health consequences of such a policy. To adopt such 

a policy ignores the obligation to provide equal protection under the law to all 

Americans because it would result in uneven protection from air pollution in 

different localities and regions of the country (ALA et al., 2012, p. 26). 

Response: The EPA believes these commenters misunderstood the basis for the EPA’s 

policy goal of setting a “generally controlling” annual standard. This approach relates 

exclusively to setting standards that will provide requisite protection against effects 

associated with both long- and short-term PM2.5 exposures. It does so by lowering the 

overall air quality distributions across an area, recognizing that changes in PM2.5 air 

quality designed to meet an annual standard would likely result not only in lower annual 

mean PM2.5 concentrations but also in fewer and lower peak 24-hour PM2.5

concentrations. As discussed in section III.A.3 in the proposal and in the preamble to the 

final rule, the EPA recognizes that there are various ways to combine the two primary 

PM2.5 standards to achieve an appropriate degree of public health protection. 

Furthermore, the extent to which these two standards are interrelated in any given area 

depends in large part on the relative levels of the standards, the peak-to-mean ratios that 

characterize air quality patterns in an area, and whether changes in air quality designed to 

meet a given suite of standards are likely to be of a more regional or more localized 

nature. 

In focusing on an approach of setting a generally controlling annual standard, the EPA’s 

intent is in fact to avoid the potential “regional inequities” that are of concern to these 

commenters. The EPA judges that the most appropriate way to set standards that provide 

more consistent public health protection is by using the approach of setting a generally 

controlling annual standard. This judgment builds upon information presented in the PA 

as discussed in section III.A.3 of the preamble to the final rule. More specifically, the PA 

recognized that the short-term exposure studies primarily evaluated daily variations in 

health effects with monitor(s) that measured the variation in daily PM2.5 concentrations 

over the course of several years. The strength of the associations observed in these 

epidemiological studies was demonstrably in the numerous “typical” days within the air 

quality distribution, not in the peak days (U.S. EPA, 2011a, p. 2-9). In addition, the 

quantitative risk assessments conducted for this and previous reviews demonstrated the 

same point: that is, much, if not most, of the aggregate risk associated with short-term 

PM2.5 exposures results from the large number of days during which the 24-hour average 

concentrations are in the low-to mid-range, below the peak 24-hour concentrations (U.S. 

EPA, 2011a, section 2.2.2; U.S. EPA, 2010a, section 3.1.2.2). In addition, there was no 

evidence suggesting that risks associated with long-term exposures were likely to be 

disproportionately driven by peak 24-hour concentrations.28 See also American Trucking 

Association v. EPA, 283 F. 3d at 373 (rejecting arguments to lower the level of the daily 

PM2.5 standard when there is persuasive evidence that the main risk from exposure comes 

 

28 In confirmation, a number of studies have presented analyses excluding higher PM concentration days and 

reported a limited effect on the magnitude of the effect estimates or statistical significance of the association (e.g., 

Dominici, 2006b; Schwartz et al., 1996; Pope and Dockery, 1992). 
II-79 

from the entire air quality distribution rather than from peak days, and the annual 

standard will lower that distribution). 

For these reasons, the PA concluded that strategies that focused primarily on reducing 

peak days were less likely to achieve reductions in the PM2.5 concentrations that were 

most strongly associated with the observed health effects. Furthermore, the PA concluded 

that an approach that focused on reducing peak exposures would most likely result in 

more uneven public health protection across the U.S. by either providing inadequate 

protection in some areas or overprotecting in other areas (U.S. EPA, 2011a, p. 2-9; U.S. 

EPA, 2010a, section 5.2.3). This is because reductions based on control of peak days are 

less likely to control the bulk of the air quality distribution. As noted above, this would 

create the very inequity of results the commenters seek to avoid. 

As a result, the EPA believes an approach that focuses on a generally controlling annual 

standard would likely reduce aggregate risks associated with both long- and short-term 

exposures more consistently than a generally controlling 24-hour standard and, therefore, 

would be the most effective and efficient way to reduce total PM2-5-related population 

risk. The CASAC agreed with this approach and considered it was “appropriate to return 

to the strategy used in 1997 that considers the annual and the short-term standards 

together, with the annual standard as the controlling standard, and the short-term standard 

supplementing the protection afforded by the annual standard” (Samet, 2010d, p. 1). The 

EPA thus disagrees with the comments that this approach will result in the concerns 

raised by the commenters; rather the EPA concludes that this approach will help to 

address these concerns. 

(2) Comment: Many of these commenters asserted that the currently available scientific 

information is greatly expanded and stronger compared to the last review. Some of these 

commenters highlighted the availability of multiple, multi-city long- and short-term 

exposure studies providing “repeated, consistent evidence of effects below the current 

annual standard level” (ALA et al., 2012, pp. 39 to 49) and, more specifically, 

“significant evidence of harm with strong confidence well below EPA’s proposed annual 

standard range of 12-13 μg/m3

” (AHA et al., 2012, pp. 10 to 12).

Response: The EPA recognizes that in setting standards that are requisite to protect 

public health with an adequate margin of safety, the Administrator must weigh the 

various types of available scientific information in reaching public health policy 

judgments that neither overstate nor understate the strength and limitations of this 

information or the appropriate inferences to be drawn from the available science. 

In general, the EPA agrees with these commenters’ views that the currently available 

scientific evidence is stronger “because of its breadth and the substantiation of previously 

observed health effects” (77 FR 38906/2) and provides “greater confidence in the 

reported associations than in the last review” (77 FR 38940/1). The EPA also agrees with 

the commenters’ position that it is appropriate to consider the regions within the broader 

air quality distributions where we have the strongest confidence in the associations 

reported in epidemiological studies in setting the level of the annual standard. However, 

as discussed in section III.E.4.d of the preamble to the final rule, in weighing the 

available evidence and technical analyses, as well as the associated uncertainties and 
II-80 

limitations in that information, the EPA disagrees with the commenters’ views regarding 

the extent to which the available scientific information provides support for considering 

an annual standard level below the proposed range (i.e., below 12 to 13 μg/m3

). In 

particular, the EPA disagrees with the degree to which these commenters place more 

weight on the relatively more uncertain evidence that is suggestive of a causal 

relationship (e.g., low birth weight). Consistent with CASAC advice (Samet, 2010d, p. 

1), the Agency concludes it is appropriate and reasonable to place the greatest emphasis 

on health effects for which the ISA concluded there is evidence of a causal or likely 

causal relationship and to place less weight on the health effects that provide evidence 

that is only suggestive of a causal relationship. 

(3) Comment: With regard to using the air quality information from epidemiological studies 

to inform decisions on standard levels, commenters in this group generally supported the 

EPA’s efforts to explore different statistical metrics from epidemiological studies to 

inform the Administrator’s decisions. These commenters argued that by considering 

different analytic measures -- either concentrations one standard deviation below the 

long-term means reported in the epidemiological studies or the EPA’s distributional 

statistical analysis of population-level data that extends the approach used in previous PM 

NAAQS reviews to consider information beyond a single statistical metric -- “the annual 

standard must be significantly lower than EPA has proposed” (ALA et al., 2012, pp. 50 to 

61). Furthermore, with regard to characterizing the PM2.5 air quality at which associations 

have been observed, some of these commenters highlighted CASAC’s recommendation 

that “[f]urther consideration should be given to using the 10th percentile as a level for 

assessing various scenarios of levels for the PM NAAQS” (Samet, 2010c, p. 11) (ALA et 

al., 2012, p. 55). Other commenters urged that the EPA extend the distributional analysis 

to include additional studies. For example, CHPAC urged the EPA to also conduct 

distributional analysis for children’s health studies to better inform standards that would 

protect both children and adults from adverse health outcomes (CHPAC, 2012, p. 3). 

Response: The EPA agrees with these commenters’ views that it is appropriate to take 

into account different statistical metrics from epidemiological studies to inform the 

decisions on standard levels that are appropriate to consider in setting a standard that will 

protect public health with an adequate margin of safety. In the development of the PA, 

the EPA staff explored various approaches for using information from epidemiological 

studies in setting the standards. The general approach used in the final PA, discussed in 

sections III.A.3 and III.E.4.a of the preamble to the final rule, reflects consideration of 

CASAC advice (Samet, 2010c,d) and public comments on multiple drafts of the PA. 

With regard to using the distributional statistical analysis to characterize the confidence 

in the associations, the EPA emphasizes that there is no clear dividing line provided by 

the scientific evidence, and that choosing how far below the long-term mean 

concentrations from the epidemiological studies is appropriate to identify a standard level 

that will provide protection for the public health with an adequate margin of safety is 

largely a public health policy judgment. In this review, the EPA considers the region 

from approximately the 25th to 10th percentiles to be a reasonable range for providing a 

general frame of reference as to the part of the distribution over which our confidence in 

the magnitude and significance of the associations observed in epidemiological studies is 
II-81 

appreciably lower. Based on these considerations, the EPA concludes that it is not 

appropriate to place as much confidence in the magnitude and significance of the 

associations over the lower percentiles of the distributions in each study as at and around 

the long-term mean concentrations. Thus, the EPA disagrees with the commenters’ views 

that this analysis compels placing more emphasis on the lower part of this range in 

selecting a level for an annual standard that will protect public health with an adequate 

margin of safety. The EPA recognizes that this information comes primarily from two 

short-term exposure studies, a relatively modest data set. In light of the limited nature of 

this information, and in recognition of more general uncertainties inherent in the 

epidemiological evidence, the Administrator deems it reasonable not to place more 

emphasis on concentrations in the lower part of this range, as discussed in section 

III.E.4.d of the preamble to the final rule. 

With regard to the scope of the distributional statistical analysis, the EPA requested 

additional population-level data from the study authors for a group of six multi-city 

studies for which previous air quality analyses had been conducted (Hassett-Sipple et al., 

2010; Schmidt et al., 2010, Analysis 2). These six studies were originally selected 

because they considered multiple locations representing varying geographic regions 

across multiple years. Thus, these studies provided evidence on the influence of different 

particle mixtures on health effects associated with long- and short-term PM2.5 exposures. 

In addition, these multi-city studies considered relatively more recent health events and 

air quality conditions (1999 to 2005). As discussed in section III.E.4.b.i of the preamble 

to the final rule, the EPA received and analyzed population-level data for four of the six 

studies (Rajan et al., 2011). Three of these four studies (Krewski et al., 2009a; Bell et al., 

2008; Zanobetti and Schwartz, 2009) served as the basis for the C-R functions used to 

develop the core risk estimates (U.S. EPA, 2010a, section 3.3.3). While the EPA agrees 

that it would be useful to have such data from more studies, the Agency believes that the 

additional data that was requested and received from study authors provide useful 

information to help inform the Administrator’s selection of the annual standard level. 

(4) Comment: Many commenters in this group highlighted PM2.5-related impacts on at-risk 

populations, including potential impacts on children, older adults, persons with preexisting heart and lung disease, and low-income populations, to support their views that 

the annual standard should be revised to a level of 11 μg/m3

 or lower (e.g., CHPAC, 

2012; AHA et al., 2012; ALA, 2012, pp. 29 to 38; Rom et al., 2012; Air Alliance 

Houston, et al., 2012, p. 1; PSR, pp. 2 and 4). These commenters urged the EPA to adopt 

a policy approach that placed less weight on the remaining uncertainties and limitations 

in the evidence and placed more emphasis on margin of safety considerations, including 

providing protection against effects for which there is more limited scientific evidence. 

For example, CHPAC urged the EPA “to place the same weight on studies examining 

impacts on children’s health as that of adult studies. ... The fact that there may be 

stronger evidence from adult studies does not mean that standards based on adult studies 

will be protective for children and consequently will meet the standard requisite to 

protect public health with an adequate margin of safety” (CHPAC, 2012 p. 3). 

Furthermore, with regard to the EPA’s approach for weighing uncertainties, some of 

these commenters stated that “we find no justification in the preamble for an annual 

standard level as high as 13 μg/m3

, other than the vague assertion that uncertainties 
II-82 

increase at lower concentrations. Further, the final proposal completely failed to address 

the Policy Assessment recommendations that if 13 μg/m3

 was proposed, the 24-hour 

standard should be strengthened as well” (ALA et al., p. 7).

Response: The EPA has carefully evaluated and considered evidence of effects in at-risk 

populations. With regard to effects classified as having evidence of a causal or likely 

causal relationship with long- or short-term PM2.5 exposures (i.e., premature mortality, 

cardiovascular effects, and respiratory effects), the Agency takes note that it considered 

the full range of studies evaluating these effects, including studies of at-risk populations, 

to inform its review of the primary PM2.5 standards. Specific multi-city studies 

summarized in Figures 1, 2, and 3 in the preamble for the final rule highlight evidence of 

effects observed in two different lifestages – children and older adults – that have been 

identified as at-risk populations. Thus, the EPA places as much weight on studies that 

explored effects in children for which the evidence is causal or likely causal in nature as 

on studies of such effects in adults, including older adults. As discussed above in 

responses to commenters supporting the retention of the current standards, in setting the 

standard, the EPA has focused on considering PM2.5 concentrations somewhat below the 

lowest long-term mean concentrations from each of the key studies of both long- and 

short-term exposures of effects for which the evidence supports a causal or likely causal 

relationship (i.e., the first two sets of studies shown in Figure 4 of the preamble to the 

final rule). The EPA has thus considered the available evidence of effects in children as 

well as other at-risk populations, given that those commenters urging the EPA to discount 

or disregard those studies provided no legitimate reason to do so. With respect to the 

EPA’s consideration of more limited studies providing evidence suggestive of a causal 

relationship (e.g., developmental and reproductive effects), as noted above in responding 

to comments from the first group of commenters, the Agency is placing some weight on 

this body of evidence in setting standards that provide protection for at-risk populations,. 

However, the Agency does not agree that the same weight must be placed on this 

information as on the body of scientific information for which there is evidence of a 

causal or likely causal relationship. To do so here would ignore the difference in the 

breadth and strength of the evidence supporting the different causality determinations 

reached in the ISA. 

With regard to weighing the uncertainties and limitations remaining in the evidence and 

technical analyses, as discussed in section II.A of the preamble to the final rule, the EPA 

recognizes that in setting a primary NAAQS that provides an adequate margin of safety, 

the Administrator must consider a number of factors including the nature and severity of 

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

degree of the uncertainties that remain. As discussed in section III.E.4.d of the preamble 

to the final rule, the Agency agrees with these commenters that, in weighing the available 

evidence and technical analyses including the uncertainties and limitations in this 

scientific information, there is no legitimate justification for setting a primary PM2.5

annual standard level as high as 13 μg/m3 (in conjunction with retaining the 24-hour 

standard at the current level). 

(5) Comment: Some commenters urged the EPA “to select a standard based on science, not 

politics” (ALA et al., 2012, p. 6). More specficially, these commenters asserted “last 
II-83 

minute changes to the proposed level (following interagency review) were not 

accompanied by substantive changes in the text to the proposal. In fact, we find no 

justification in the preamble for an annual standard as high as 13 μg/m3

, other than the 

vague assertion that uncertainties increase at lower concentrations. Further the final 

proposal completely failed to address the Policy Assessment recommendations that if 13 

μg/m3

 was proposed, then the 24-hour standard should be strengthened as well. The 

apparent last minute and unsupported insertion of a less protective annual standard to the 

proposal appears to be political interference, not scientific consideration” (ALA et al., 

2012, p. 7). 

Response: As stated in the previous response, the EPA agrees that the evidence in the 

record of this review does not support an annual standard at the level of 13 μg/m3 (unless 

the 24-hour standard level was to be lowered substantially).

(6) Comment: Some commenters argued that the EPA “committed a serious procedural error 

in not explicitly soliciting comment on retaining the current [annual] PM2.5 NAAQS” 

(API, 2012, p. 9). 

Response: The commenter suggested (without providing any specific argument) that the 

EPA somehow prejudged the outcome of the rulemaking , or otherwise committed 

procedural error, by not proposing to retain the 2006 NAAQS. This is incorrect. First, the 

EPA provided far more process through this review than the amount required by law. 

Commenters had multiple opportunities to review and comment on all of the critical 

documents underlying the review (notably the ISA, the RA, and the PA), as well as on all 

of the critical scientific and policy issues, assumptions, and factual data informing the 

review as discussed in the proposal (77 FR 38890). Given that the basic question being 

addressed throughout this proceeding is whether or not it is appropriate to revise the 2006 

standard (CAA section 109 (d)), that issue was necessarily before the public for comment 

(as evidenced by all the comments urging retention of the standard, among other indicia 

of proper notice). Nor does the EPA’s proposal indicate a pre-judgment of the outcome of 

the review. Rather, the proposal reflected the EPA’s consideration of the body of 

scientific data and analysis comprising the record for this review. 

The EPA strongly disagrees that the currently available scientific evidence and technical 

information supports consideration for retaining the annual standard level at 15 μg/m3

.

and consequently did not propose to do so. As discussed in section III.D.3. of the 

preamble for the final rule, having carefully considered CASAC advice and the public 

comments on the proposal as discussed in section III.D.2 preamble to the final rule and in 

section II.B.1 above, the EPA believes the fundamental scientific conclusions on the 

effects of PM2.5 reached in the ISA, and discussed in the PA, are valid. The Agency 

believes that since the last review the overall uncertainty about the public health risks 

associated with both long- and short-term exposure to PM2.5 has been diminished to an 

important degree. The remaining uncertainties in the available evidence do not diminish 

confidence in the associations between exposure to fine particles and mortality and 

serious morbidity effects. Based on the Agency’s increased confidence in the association 

between exposure to PM2.5 and serious public health effects, combined with evidence of 

such an association in areas that would meet the current standards , the Administrator 
II-84 

agrees with CASAC that revision of the current suite of PM2.5 standards to provide 

increased public health protection is necessary. Based on these considerations discussed 

in section III.D.3 of the preamble to the final rule, the Administrator concludes that the 

current suite of primary PM2.5 standards is not sufficient, and thus not requisite, to protect 

public health with an adequate margin of safety, and that revision is needed to increase 

public health protection. Furthermore, as discussed in section III.E.4.e of the proposal, 

the Administrator provisionally concluded that the available scientific information 

supported consideration of an annual standard level no higher that 13 μg/m3

. In 

considering public comments on the proposal as discussed in sections III.E.4.c.i and 

III.E.4.d of the preamble for the final rule and above, the Agency concludes there is no 

scientific basis for considering retaining the annual standard level at 15 μg/m3 (absent a 

substantially lower level of the daily standard). 

(7) Comment: Some of these commenters also identified “new” studies as providing 

additional evidence to support their views that the annual standard level needs to be 

lowered.

Response: As discussed in section II.B.3 of the preamble to the final rule and in section 

II.B.1.a above, the EPA notes that, as in past NAAQS reviews, the Agency is basing the 

final decisions in this review on the studies and related information included in the PM 

ISA that have undergone CASAC and public review, and will consider newly published 

studies for purposes of decision making in the next PM NAAQS review. Nonetheless, in 

provisionally evaluating commenters’ arguments, the EPA notes that its provisional 

assessment of “new” science found that such studies did not materially change the 

conclusions reached in the ISA (U.S. EPA, 2012b). 

b. 24-Hour Standard 

With respect to the level of the 24-hour standard, the EPA received comments on the 

proposal from two distinct groups of commenters. One group that included virtually all 

commenters representing industry associations, businesses, and many States agreed with the 

Agency’s proposed decision to retain the level of the 24-hour PM2.5 standard. The other group of 

commenters included many medical groups, numerous physicians and academic researchers, 

many public health organizations, some State and local agencies, five state attorneys general, and 

a large number of individual commenters. These commenters disagreed with the Agency’s 

proposed decision and argued that EPA should lower the level of the 24-hour standard to 30 or 

25 μg/m3

. Comments from these groups on the level of the 24-hour PM2.5 standard are addressed 

in section III.E.4.c.ii in the preamble for the final rule and below.

i. Support for Retaining the Current Level 

Of the public commenters who addressed the level of the 24-hour PM2.5 standard, all 

industry commenters and most State and local commenters supported the proposed decision to 

retain the current level of 35 g/m3

. In many cases, these groups agreed with the rationale 

supporting the Administrator’s proposed decision to retain the current 24-hour PM2.5 standard, 

including her emphasis on the annual standard as the generally controlling standard with the 24-

hour standard providing supplementary protection, and her conclusion that multi-city, short-term 
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exposure studies provide the strongest data set for informing decisions on the appropriate 24-

hour standard level. Many of these commenters agreed with the Administrator’s view that the 

single-city, short-term studies provided a much more limited data set (e.g., limited statistical 

power, limited exposure data) and more equivocal results (e.g., mixed results within the same 

study area), making them an unsuitable basis for setting the level of the 24-hour standard. 

(1) Comment: While these commenters agreed with the EPA’s proposed decision to retain 

the current 24-hour PM2.5 standard, some did not agree with the EPA’s approach to 

considering the evidence from short-term multi-city studies. For example, a commenter 

representing UARG pointed out that the 98th percentile concentrations reported in the 

proposal for multi-city studies reflect the averages of 98th percentile concentrations across 

the cities included in those studies (UARG, 2012; Attachment 1; p. 25). This commenter 

contended that such averaged 98th percentile PM2.5 concentrations do not provide 

information that can appropriately inform a decision on the adequacy of the public health 

protection provided by the current or alternative 24-hour standards.

Response: While the EPA agrees that there is uncertainty in linking effects reported in 

multi-city studies to specific air quality concentrations (U.S. EPA, 2011a, section 

2.3.4.1), the EPA disagrees with this commenter’s view that such uncertainty precludes 

the use of averaged 98th percentile PM2.5 concentrations to inform a decision on the 

appropriateness of the protection provided by the 24-hour PM2.5 standard. In particular, 

the EPA notes that averaged 98th percentile concentrations do provide information on the 

extent to which study cities contributing to reported associations would likely have met 

or violated the current 24-hour PM2.5 standard during the study period. As evidence of 

this, the EPA notes the three multi-city studies specifically highlighted by this commenter 

as having averaged 98th percentile 24-hour PM2.5 concentrations below 35 g/m3

(Dominici et al., 2006a; Bell et al., 2008; Zanobetti and Schwartz, 2009). Based on the 

98th percentiles of 24-hour PM2.5 concentrations in the individual cities evaluated in these 

studies, the EPA notes that the majority of these study cities would likely have met the 

current standard during the study periods (Hassett-Sipple et al., 2010). Therefore, 

regardless of whether the averaged 98th percentile concentrations or the 98th percentile 

concentrations in each city are considered, these studies provide evidence for associations 

between short-term PM2.5 and mortality or morbidity across a large number of U.S. cities, 

the majority of which would likely have met the current 24-hour PM2.5 standard during 

study periods. In their review of the PA, CASAC endorsed the conclusions drawn from 

analyses of averaged 98th percentile 24-hour PM2.5 concentrations (Samet, 2010d) and the 

EPA continues to conclude that this type of information can appropriately inform the 

Administrator’s decision on the current 24-hour PM2.5 standard.29 

(2) Comment: One commenter questioned whether the 24-hour standard would offer any 

additional protection beyond the protection provided by the annual standard. This 

 

29This is not to say that the EPA’s decision on whether to revise the 24-hour PM2.5 standard should be based on or 

only be informed by considerations of whether studies reported associations with mortality or morbidity in areas 

with averaged 98th percentile PM2.5 concentrations less than 35 mg/m3

. As discussed in section III.E.4.d of the 

preamble to the final rule, in reaching a decision in the final notice on the most appropriate approach to strengthen 

the suite of PM2.5 standards, the Administrator considers the degree of public health protection provided by the 

combination of the annual and 24-hour standards together. 
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commenter argued that EPA has not provided any evidence that the 24-hour standard is 

necessary to protect public health and asserted that the EPA should better explain why the 

existing 24-hour standard is not more stringent than necessary (API, 2012, p. 9). More 

specifically, based on statements in the PA (quoting “there is no evidence suggesting that 

risks associated with long-term exposures are likely to be disproportionately driven by 

peak 24-hour concentrations” and citing to several studies that evaluated the effect on the 

magnitude and statistical significance of the association between PM2.5 health impacts 

with and without high PM concentrations days, finding very little difference, U.S. EPA, 

2011a, p. 2-9), this commenter asserted “If the annual standard is protective of effects 

from both short- and long-term exposures, and no additional effects are observed with 

peak events, this indicates that there is likely no additional benefit to having the 24-hour 

standard. Retaining the 24-hour standard, therefore, would be an additional level of 

protection, or ‘margin of safety’” (API, 2012, Attachment 1, p.2). 

Response: The EPA disagrees with the commenter’s contention that evidence has not 

been provided to support the appropriateness of the retaining the current 24-hour standard 

in conjunction with revising the annual standard. The EPA has carefully considered the 

degree of public health protection provided by the annual and 24-hour PM2.5 standards 

working together. As highlighted by commenters and as discussed in section III.E.4.d of 

the preamble to the final rule, based on the evidence and quantitative risk assessment, the 

EPA concludes that it is appropriate to set an annual standard with a level of 12 μg/m3 to 

provide protection from both long- and short-term PM2.5 exposures. In conjunction with 

the revised annual standard, the EPA concludes it is also appropriate to retain the current 

24-hour standard in order to provide supplemental protection in areas with high peak-tomean ratios of PM2.5 concentrations, possibly associated with strong local or seasonal 

sources, and against PM2.5-related effects that may be associated with shorter-than daily 

exposure periods. 

As discussed in more detail in section III.E.4.a of the preamble to the final rule, in 

reaching this conclusion the EPA notes that multi-city studies provide clear evidence for 

positive and statistically significant associations with short-term PM2.5 concentrations in 

locations with averaged (i.e., averaged across study cities) 98th percentile 24-hour 

concentrations from 45.8 to 34.2 μg/m3 (Burnett et al., 2004; Zanobetti and Schwartz, 

2009; Bell et al., 2008; Dominici et al., 2006a, Burnett and Goldberg, 2003; Franklin et 

al., 2008). In many locations, the revised annual PM2.5 standard is expected to protect 

against the effects reported in these studies. However, some areas of the United States, 

particularly in the northwest, could experience 98th percentile 24-hour PM2.5

concentrations above 35 mg/m3 while annual PM2.5 concentrations remain below 12 

g/m3 (U.S. EPA, 2011, Figure 2-10). In such locations, the current 24-hour standard is 

necessary to provide protection against effects that have been associated with short-term 

PM2.5 exposures. Without the 24-hour standard in place, short-term PM2.5 concentrations 

in some locations could be allowed to exceed those that have clearly been associated with 

mortality and morbidity. Therefore, the EPA disagrees with commenters who call into 

question support for the conclusion that the 24-hour standard provides appropriate 

supplementary protection against effects that have been associated with fine particle 

exposures. 
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ii. Support for Revising the Current Level 

Another group of commenters argued that the 24-hour standard level should be lowered. 

Many of these commenters supported setting the level of the 24-hour PM2.5 standard at either 25 

or 30 g/m3. 

(1) Comment: In support of their position, the ALA et al., AHA et al., five state Attorneys 

General, and a number of additional groups pointed to 98th percentile PM2.5

concentrations in locations of multi-city and single-city epidemiological studies. For 

example, the ALA and others pointed to multi-city studies by Dominici et al. (2006a), 

Zanobetti and Schwartz (2009), Burnett et al. (2000), and Bell et al. (2008) as providing 

evidence for associations with mortality and morbidity in study locations with averaged 

(i.e., averaged across cities) 98th percentile 24-hour PM2.5 concentrations below 35 

g/m3

. These commenters also pointed to several single-city and panel studies reporting 

associations between short-term PM2.5 and mortality or morbidity in locations with 

relatively low 24-hour PM2.5 concentrations. Because some of these multi- and single-city 

studies have reported associations with health effects in locations with 98th percentile 

PM2.5 concentrations below 35 g/m3

, commenters maintained that the current 24-hour 

PM2.5 standard (i.e., with its level of 35 g/m3) does not provide an appropriate degree of 

protection in all areas. 

In further support of their position that the level of the current 24-hour standard should be 

lowered, these commenters pointed out the variability across the U.S. in ratios of 24-hour 

to annual PM2.5 concentrations. They noted that some locations, including parts of the 

northwestern U.S., experience relatively low annual PM2.5 concentrations but can 

experience relatively high 24-hour concentrations at certain times of the year. In order to 

provide protection against effects associated with short-term PM2.5 exposures, especially 

in locations with high ratios of 24-hour to annual PM2.5 concentrations, these commenters 

advocated setting a lower level for the 24-hour standard. 

Response: The EPA agrees with these commenters that it is appropriate to maintain a 

24-hour PM2.5 standard in order to supplement the protection provided by the revised 

annual standard, particularly in locations with relatively high ratios of 24-hour to annual 

PM2.5 concentrations. However, in highlighting 98th percentile PM2.5 concentrations in 

study locations without also considering the impact of a revised annual standard on shortterm concentrations, these commenters ignore the fact that many areas would be expected 

to experience decreasing short- and long-term PM2.5 concentrations in response to a 

revised annual standard. See American Trucking Association v. EPA, 283 F. 3d at 373 

(rejecting argument to lower the level of the 24-hour PM2.5 standard since the argument 

had failed to account for the reductions in the entire air quality distribution resulting from 

the implementation of the annual standard). 

In considering the specific multi-city studies highlighted by public commenters who 

advocated a more stringent 24-hour standard, the EPA notes that such studies have 

reported consistently positive and statistically significant associations with short-term 

PM2.5 exposures in locations with averaged 98th percentile PM2.5 concentrations ranging 

from 45.8 to 34.2 μg/m3

 and long-term mean PM2.5 concentrations ranging from 13.4 to 
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12.8 (Burnett and Goldberg, 2003; Burnett et al., 2004; Dominici et al., 2006a; Bell et al., 

2008; Franklin et al., 2008; Zanobetti and Schwartz, 2009).30 The EPA notes that to the 

extent air quality distributions are reduced to meet the current 24-hour standard with its 

level of 35 g/m3 and/or the revised annual standard with its level of 12 g/m3, additional 

protection would be anticipated against the effects reported in these short-term, multi-city 

studies. Put another way, to attain an annual standard with a level below the long-term 

means in the locations of these short-term studies (as EPA is adopting in the final rule), 

the overall air quality distributions in the majority of study cities will necessarily be 

reduced, resulting in lower daily PM2.5 ambient concentrations. We therefore expect that 

the revised annual standard will result in 98th percentile PM2.5 concentrations in these 

cities that are lower than those measured in the studies, and that the overall distributions 

of PM2.5 concentrations will be lower than those reported to be associated with health 

effects. Thus, even for effects reported in multi-city studies with averaged 98th percentile 

concentrations below 35 μg/m3

, additional protection from the risks associated with 

short-term exposures is anticipated from the revised annual standard, without revising the 

24-hour standard, because long-term average PM2.5 concentrations in multi-city study 

locations were above the level of the revised annual standard (i.e., 12 μg/m3).31 As 

discussed above, reducing the annual standard is the most efficient way to reduce the 

risks from short-term exposures identified in these studies, as the bulk of the risk comes 

from the large number of days across the bulk of the air quality distribution, not the 

relatively small number of days with peak concentrations. See American Trucking 

Association, 283 F. 3d at 372 (endorsing this reasoning). 

In considering the single-city studies highlighted by public commenters who advocated a 

more stringent 24-hour standard, the EPA first notes that, overall, these single-city 

studies reported mixed results. Specifically, some studies reported positive and 

statistically significant associations with PM2.5, some studies reported positive but nonsignificant associations, and several studies reported negative associations or a mix of 

positive and negative associations with PM2.5. In light of these inconsistent results, the 

proposal noted that the overall body of evidence from single-city studies is mixed, 

particularly in locations with 98th percentiles of 24-hour concentrations below 35 μg/m3. 

Therefore, although some single-city studies reported effects at appreciably lower PM2.5

concentrations than short-term multi-city studies, the uncertainties and limitations 

 

30Commenters also highlighted associations with short-term PM2.5 concentrations reported in sub-analyses restricted 

to days with 24-hour concentrations at or below 35 g/m3

 (Dominici, 2006b). These sub-analyses were not included 

in the original publication by Dominici et al. (2006a). Authors provided results of sub-analyses for the 

Administrator’s consideration in a letter to the docket following publication of the proposed rule in January 2006 

(personal communication with Dr. Francesca Dominici, 2006b). As noted in section III.A.3 of the preamble to the 

final rule and to the proposal, these sub-analyses are part of the basis for the conclusion that there is no evidence 

suggesting that risks associated with long-term exposures are likely to be disproportionately driven by peak 24-hour 

concentrations. Because the sub-analyses did not present long-term average PM2.5 concentrations, it is not clear 

whether they reflected PM2.5 air quality that would have been allowed by the revised annual PM2.5 standard being 

established in this notice. 

31It is also the case that additional protection is anticipated in locations with 98th percentile 24-hour PM2.5

concentrations above 35 μg/m3

, even if long-term concentrations are below 12 μg/m3. As noted in the proposal (77 

FR 38938) and in the PA (U.S. EPA, 2011, Figure 2-10), as well as by a number of the commenters (e.g., ALA et 

al., 2012, p. 26), parts of the northwestern U.S. are more likely than other parts of the country to violate the 24-hour 

standard and meet the revised annual standard. 
II-89 

associated with the single-city studies were noted to be greater. In light of these greater 

uncertainties and limitations, the Administrator concluded in the proposal that she had 

less confidence in using these studies as a basis for setting the level of the standard (77 

FR 38943). 

Given the considerations and conclusions noted above, in the proposal the Administrator 

concluded that the short-term multi-city studies provide the strongest evidence to inform 

decisions on the level of the 24-hour standard. Further, she viewed single-city, short-term 

exposure studies as a much more limited data set providing mixed results, and she had 

less confidence in using these studies as a basis for setting the level of a 24-hour standard 

(77 FR 38942). In highlighting specific single-city studies, public health, environmental, 

and State and local commenters appear to have selectively focused on studies reporting 

associations with PM2.5 and to have overlooked studies that reported more equivocal 

results (e.g., Ostro et al., 2003; Rabinovitch et al., 2004; Slaughter et al., 2005; 

Villeneuve et al., 2006) (U.S. EPA, 2011, Figure 2-9). As such, these commenters have 

not presented new information that causes the EPA to reconsider its decision to 

emphasize multi-city studies over single-city studies when identifying the appropriate 

level of the 24-hour PM2.5 standard. 

In further considering the single-city studies highlighted by public commenters, the EPA 

notes that some commenters advocating for a lower level for the 24-hour PM2.5 standard 

also discussed short-term studies that have been published since the close of the ISA. 

These recent studies were conducted in single cities or in small panels of volunteers. As 

in prior NAAQS reviews and as discussed in more detail in section II.B.3 of the preamble 

to the final rule and in section II.B.1.a above, the EPA is basing its decisions in this 

review on studies and related information assessed in the ISA. The studies assessed in the 

ISA, and the conclusions based on those studies, have undergone extensive critical 

review by the EPA, CASAC, and the public. The rigor of that review makes the studies 

assessed in the ISA, and the conclusions based on those studies, the most reliable source 

of scientific information on which to base decisions on the NAAQS. 

(2) Comment: Some public health, medical, and environmental commenters also criticized 

the EPA’s interpretation of PM2.5 risk results. These commenters presented risk estimates 

for combinations of annual and 24-hour standards using more recent air quality data than 

that used in the EPA’s RA (U.S. EPA, 2010a). Based on these additional risk analyses, 

the ALA and other commenters contended that public health benefits could continue to 

increase as annual and 24-hour standard levels decrease below 13 g/m3

 and 35 g/m3, 

respectively. 

Response: The EPA agrees with these commenters that important public health benefits 

are expected as a result of revising the level of the annual standard to 12 g/m3

, as is 

done in the final rule, rather than 13 g/m3. The Agency also acknowledges that 

estimated PM2.5-associated health risks continue to decrease with annual standard levels 

below 12 g/m3 and/or with 24-hour standard levels below 35 g/m3. However, the EPA 

disagrees with the commenters’ views regarding the extent to which risk estimates 

support setting standard levels below 12 μg/m3 (annual standard) and 35 g/m3 (24-hour 
II-90 

standard).32 

The CAA charges the Administrator with setting NAAQS that are “requisite” (i.e., 

neither more nor less stringent than necessary) to protect public health with an adequate 

margin of safety. In setting such standards the Administrator must weigh the available 

scientific evidence and information, including associated uncertainties and limitations. As 

described above, in reaching her proposed decisions on the PM2.5 standards that would 

provide “requisite” protection, the Administrator carefully considered the available 

scientific evidence and risk information, making public health policy judgments that, in 

her view, neither overstated nor understated the strengths and limitations of that evidence 

and information. In contrast, as discussed more fully above, public health, medical, and 

environmental commenters who recommended levels below 35 g/m3 for the 24-hour 

PM2.5 standard have not provided new information or analyses to suggest that such 

standard levels are appropriate, given the uncertainties and limitations in the available 

health evidence, particularly uncertainties in studies conducted in locations with 98th

percentile 24-hour PM2.5 concentrations below 35 g/m3

 and long-term average 

concentrations below 12 g/m3

. 

C. Specific Comments on the Quantitative Health Risk Assessment 

This section responds to more detailed comments regarding the quantitative health risk 

assessment conducted for PM2.5 (RA, US EPA, 2010a). .

(1) Comment: Some commenters argued that the quantitative health risk assessment 

conducted for PM2.5 was too limited since it “focused on only 15 urban study areas to 

represent the continental U.S. and only examined a fraction of the available combinations 

of annual and daily standards” (ALA et al., 2012, p. 73). These commenters noted that 

the RA indicated the quantitative risk analyses likely underestimated PM2.5-related 

mortality (U.S. EPA, 2010a, p. 5-16) and argued that “the measurements of risk should 

be treated conservatively” (ALA, et al., 2012, p. 73). These commenters also noted that 

significant additional risk reduction is associated with combinations of annual and 24-

hour standards lower than those considered by the EPA (ALA et al., 2012, pp. 73 to76).

Response: The RA used a case study approach wherein distinct sets of risk estimates 

were generated for each of 15 urban study areas. The case study approach was selected in 

order to make use of site-specific data in modeling PM2.5-related risk, thereby generating 

risk estimates with higher overall confidence. Furthermore, the case study approach was 

intended to provide coverage for the range of PM-related health effects likely to be 

experienced by urban residents across the U. S. and was not intended to provide a 

comprehensive picture of total risk for the U.S. population. 

With regard to the scope of the quantitative risk analysis, as stated in the proposal, “The 

selection of urban study areas was based on a number of criteria including: (1) 

consideration of urban study areas evaluated in the last PM risk assessment; (2) 

consideration of locations evaluated in key epidemiological studies; (3) preference for 

 

32This section focuses on the 24-hour standard. Section III.E.4.c.i of the preamble to the final rule and section 

II.B.5.a.i above also discuss these commenters’ recommendations within the context of the annual PM2.5 standard. 
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locations with relatively elevated annual and/or 24-hour PM2.5 monitored concentrations; 

and (4) preference for including locations from different regions across the country, 

reflecting potential differences in PM2.5 sources, composition, and potentially other 

factors which might impact PM2.5 -related risk” (77 FR 38912; see also U.S. EPA, 2010a, 

section 3.3.2). Based on the results of several analyses examining the representativeness 

of these 15 urban study areas in the broader national context (U.S. EPA, 2010a, section 

4.4), the RA concluded that these study areas were generally representative of urban 

areas in the U.S. likely to experience relatively elevated levels of risk related to ambient 

PM2.5 exposure with the potential for better characterization at the higher end of that 

distribution (U.S. EPA, 2011a, p. 2–42; U.S. EPA, 2010a, section 4.4, Figure 4–17). 

The CASAC's in their letter response on the 1st draft RA supported the choice of cities 

stating that, "The Risk Assessment understandably focuses on risk in the urban study 

areas, where the population is concentrated; and there appears to be an appropriate 

selection of cities, using defined criteria." (Samet 2010a, p. 10). 

With respect to the selection of various combinations of alternative annual and 24-hour 

standard levels modeled in the RA, as noted in section 2.3.4.2 of the PA, the quantitative 

risk assessment initially included analyses of alternative annual standard levels of 14, 13, 

and 12 μg/m3

 paired with either the current 24-hour standard level of 35 μg/m3 or with 

alternative 24-hour standard levels of 30 and 25 μg/m3. The specific combinations of 

alternative standard levels assessed in the quantitative risk assessment included: (a) 

alternative suites of standards focusing on alternative annual standard levels in 

conjunction with the current 24-hour standard including combinations denoted by 14/35, 

13/25, and 12/35and (b) alternative suites of standards reflecting combinations of 

alternative annual and 24-hour standard levels including combinations denoted by 13/30 

and 12/25. This set of alternative annual and 24-hour standard levels was chosen prior to 

completion of the first draft RA (U.S. EPA, 2009e) and reflected consideration for 

evidence related to potential PM2.5-related health effects as presented in the second draft 

ISA (U.S. EPA, 2009b). The range of alternative standard levels discussed in the PA (i.e., 

annual standard levels within a range of 13 to 11 μg/m3 and 24-hour standard levels 

within a range of 35 to 30 μg/m3

), reflected consideration of evidence as presented in the 

final ISA and consequently differed somewhat from the set of alternative standard levels 

originally selected for modeling in the quantitative risk assessment. In addition, 

subsequent to the release of the second draft RA (U.S. EPA, 2010d), the Agency 

expanded the range of alternative annual standard levels evaluated in the final RA to 

include an alternative annual standard level of 10 μg/m3

 and developed risk estimates for 

two additional combinations of alternative standards – 10/35 and 10/25 (U.S. EPA, 

2010a, Appendix J). 

While the EPA agrees with the commenters that the combinations of alternative standard 

levels modeled in the RA were only a “fraction” of possible combinations that one might 

model, the EPA selection of alternative standard levels to model followed a deliberative 

and transparent process. Modifications in the alternative standard levels considered in the 

first and second draft RAs and the final RA reflected changes made in the ISA, RA, and 

PA based on CASAC and public comments on multiple draft assessment documents and 

the EPA’s staff’s expert judgment regarding the confidence associated with modeling 

different combinations of alternative standard levels. The EPA believes that the 
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uncertainties associated with the risk estimates increase when simulating increasingly 

lower alternative standard levels. For example, in simulating an alternative annual 

standard level of 10 μg/m3

, the Agency noted increased uncertainty associated with risk 

estimates generated for this lower alternative standard level and for, that reason, these 

risk estimates were deemphasized in the final RA (U.S. EPA, 2010a, Appendix J). The 

EPA’s decision to limit the range of alternative standard levels considered to 

combinations with increased confidence is consistent with advice provided by CASAC. 

More specifically, CASAC recommended that the “...EPA develop and apply specific 

criteria for determining the lower-bound exposure concentrations to be considered in the 

risk assessment. Mounting uncertainty at lower concentrations would be one such 

reasonable basis. Other relevant considerations include the range of concentrations at 

which the epidemiological studies have been carried out and the need for consideration of 

the degree of protection afforded to susceptible populations under various scenarios” 

(Samet 2010a, p. 2). The EPA readily acknowledges that additional risk reductions would 

be expected as one simulates progressively lower alternative standard levels as suggested 

by the commenters. However, the Agency also recognizes that the uncertainties 

associated with these lower alternative standard levels would also be increased resulting 

in more uncertain basis for informing the Agency’s decisionmaking. 

With regard to the comment that the RA likely underestimates risk and that for this 

reason, the risk estimates should be treated conservatively by the EPA when considering 

them in the context of the PM NAAQS review, the EPA generally agrees with the 

commenters’ views. As noted in the proposal, the RA concluded, “it is unlikely that the 

estimated risks are over-stated, particularly for premature mortality related to long-term 

PM2.5 exposures” (77 FR 38917/2). When model uncertainty associated with 

specification of the effect estimates for long-term exposure-related mortality was 

considered, the RA noted the potential that the risk estimates may have been under-stated 

(U.S. EPA, 2010a. section 4.3.2). This point is clearly made in the RA as noted above 

and is further reiterated when summarizing the risk estimates in the PA (U.S. EPA, 

2011a, section 2.2.2, p. 2-40). In addition, the EPA recognizes that the RA estimated 

risks for selective health outcomes (i.e., mortality, cardiovascular- and respiratory-related 

hospital admissions, asthma-related emergency department visits). As summarized in 

section III.B of the preamble to the final rule and discussed in more detail in section 

III.B.1 of the proposal and section 2.2.1 of the PA, the Agency recognizes that the 

currently available scientific information includes evidence for a broader range of health 

endpoints and at-risk populations beyond those considered in the quantitative risk 

assessment (U.S. EPA, 2011a, p. 2-47). Thus, for the reasons discussed above, the EPA 

agrees with the comment that the risk estimates are most likely underestimated and 

should be treated conservatively. 

(2) Comment: Some public health, medical, and environmental commenters also criticized 

the EPA’s interpretation of the PM2.5 risk results. These commenters summarized an 

expanded analysis of alternative PM2.5 standard levels (McCubbin, 2011) that they argued 

documented the need for more protective standards (ALA et al., 2012, p. 73; PSR, 2012, 

p.5; CLF, 2012, p.3). Specifically, they asserted that the McCubbin et al. (2011) 

demonstrated that (a) the EPA evaluated compliance with the PM2.5 standard for each 

year separately, while the McCubbin analysis used an innovative approach that 
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considered three years in evaluating compliance , and (b) risks can be generated using 

more recent air quality data than that used in the EPA’s RA (U.S. EPA, 2010a) (Id.; ALA 

et al., 2012, pp. 73. 

Response: The commenters’ assertion that the EPA evaluated compliance with each 

simulation year separately is incorrect. In the RA, the EPA considered three years of 

monitoring data in constructing the design values for each monitor within an urban study 

area. The design values were used as the basis for establishing the magnitude of rollback 

to simulate both the current and alternative standards. While the rollback of each monitor 

(or of the composite monitor depending on the adjustment method) was completed 

separately for each simulation year, the design values themselves were based on three 

years of data (U.S. EPA, 2010a, section 3.2.3). 

The commenters stated that the alternative risk assessment (McCubbin, 2011) included 

more recent ambient PM2.5 data than the RA. The EPA agrees with this comment. The 

McCubbin (2011) analysis used air quality data from 2007 to 2009. The RA, completed 

in 2010 considered air quality data from 2005 to 2007. The EPA observes that the RA 

utilized the most recent PM2.5 monitoring data available at the time of the analysis. It is 

always the case with regulatory risk assessments that they reflect the use of input data 

available at the time of their completion and that often, portions of that input data could 

be updated if the RA is repeated at a future point in time. 

(3) Comment: One group of commenters asserted that there was no evidence for a threshold, 

which, in the commenters’ views, argued against constraining simulation of risk to only 

extend down to the lowest measured level (LML) as was done in the RA (ALA et al., 

2012, pp., 76 to 77). 

Response: The Agency agrees that there is no evidence for a threshold for effects related 

to endpoints modeled in the RA, as supported by conclusions reached in the ISA (U.S. 

EPA, 2009a, section 2.4.3). However, application of the LML in the RA does not reflect 

modeling of a threshold for long-term exposure-related mortality. Rather it reflects 

consideration for where we have greater overall confidence in the risk estimates 

generated within the range of ambient PM2.5 data reflected in the epidemiological study 

underlying the effect estimates used in modeling risk. Specifically, as discussed in section 

5.1.6 of the RA, the EPA has relatively high confidence when we estimate risks 

associated with PM2.5 concentrations within one standard deviation (SD) of the mean 

PM2.5 concentrations reported in the epidemiological study underlying the effect 

estimates used to develop the C-R functions used in the risk assessment. However, as 

simulated annual average PM2.5 concentrations extend below this range, our confidence 

in the risk estimates decreases, with our confidence being significantly reduced when 

composite monitor annual average values reach or extend below the LML associated with 

the epidemiological study. Consequently, application of the LML allows us to focus risk 

on that portion of the PM range where we have relatively higher confidence and is not 

meant to imply that there is no risk below the LML (U.S. EPA, 2010a, section 4.3.1.2). 

(4) Comment: Some commenters cited to the results of an expert elicitation sponsored by the 

EPA providing “credence” to the EPA’s use of both the Laden et al. (2006) and Krewski 
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et al. (2009a) studies in the RA (ALA et al., 2012, p. 20). 

Response: With regard to Laden et al. (2006), the RA stated, "The Laden et al. (2006) 

study (which focused on the Harvard Six Cities dataset) was not selected because it used 

visibility data to estimate ambient PM2.5 levels." (U.S. EPA, 2010a, p. 3-38). In addition, 

the EPA recognizes that the Laden et al., 2006 study utilized data from six urban study 

areas, only one of which (St. Louis) was reflected in the set of urban study areas modeled 

in the RA. By contrast, the Krewski et al. (2009a) study included a substantially larger 

number of urban study areas (116 including all study areas modeled in the RA). That 

means that the effect estimates based on Krewski et al. (2009a) are likely to be more 

representative of the set of urban study areas modeled in the RA than are effect estimates 

based on Laden et al. (2006). While the smaller number of cities reflected in Laden et al. 

(2006) may not compromise the study in terms of informing consideration for uncertainty 

related to specification of effect estimates (as reflected in the Expert Elicitation 

referenced by the commenter, Roman et al., 2008.), the smaller number of cities in the 

Laden et al., (2006) study can substantially increase uncertainty associated with using 

that study’s effect estimates in risk assessments when those assessments focus on cities 

not reflected in the Laden et al., 2006 study, as noted here. The EPA did include Laden et 

al., (2006)-based mortality estimates as part of the national scale analysis in order to look 

at uncertainty related to model specification in modeling national-scale risk (U.S. EPA, 

2010a, Appendix G). In that case, matching urban study areas was not as critical since a 

single national-level effect estimate was used to generate a national-scale estimate of risk. 

(1) Comment: Some commenters argued that the RA is “compromised by the EPA’s 

willingness to overlook a large amount of uncertainty in the epidemiologic studies on 

which it relied in the ISA and on which it based the QHRA [Quantitative Health Risk 

Assessment]. Because it is based on a series of critical assumptions, and the uncertainty 

associated with those assumptions is not fully quantified, the QHRA cannot serve the 

functions for which it is intended: to quantify the risk to public health remaining at the 

level of the current standard or at the alternative levels” considered in the proposal (API, 

2012, p. 23, Attachment 1, p. 36). These commenters argued that the “RA results do not 

warrant being used as evidence for long-term PM health risks below current PM 

standards, and they should not be used to guide decisions regarding the PM standards” 

(API, 2012, Attachment 1, p. 36). In asserting that the uncertainties in the quantitative 

risk assessment have not been appropriately considered and, thus, this assessment does 

not support revision to the standards at this time, the commenters raised a number of 

detailed technical comments related to key modeling elements of the RA including: (a) 

the use of a no-threshold, log-linear model to support estimating risk down to LML and 

policy relevant background (PRB); (b) uncertainty related to model specification 

(selection of C-R functions), (c) failure to sufficiently consider sources of heterogeneity 

impacting risk estimates; (d) treatment of measurement error and potential direction of 

associated bias in the effect estimates; and (e) representation of the confidence associated 

with the risk assessment results.

Response: In presenting response to these comments, the EPA first addresses each of the 

detailed technical comments. Then, the EPA addresses the broader criticism made by this 

commenter that asserted the Agency overlooked important sources of uncertainty 
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associated with the risk assessment, thereby compromising the ability of the risk 

assessment to be used to support the PM NAAQS review. 

(a) Modeling risk down to LML and PRB 

The commenter disagreed with the EPA’s use of a no-threshold, log-linear model to 

support modeling risk down to either the LML or PRB, depending on the health endpoint 

(API, 2012, Attachment 1, p. 36). 

Comments related to the shape of the C-R relationship, specifically issues related to 

whether there is a threshold in the PM2.5-health effect relationship are addressed in 

section II. B.1.b, Comment (12)(f) above. Based on the ISA conclusion, and CASAC’s 

consensus recommendation, that the overall evidence from existing epidemiological 

studies does not support the existence of thresholds at the population level for effects 

associated with either long- or short-term PM2.5 exposures within the ranges of air quality 

observed in these studies (U.S. EPA, 2009a, section 2.4.3; Samet 2010d, p. ii), risk 

estimates were generated without consideration for a threshold. However, in order to 

focus the risk assessment on a range of PM where there is greater overall confidence (i.e., 

the range of ambient PM concentrations reflected in the epidemiological study(s) 

underlying the effect estimates used in the risk assessment), the EPA modeled risk for 

long-term exposure-related mortality down to the lowest measured level (LML) 

associated with the Krewski et al., 2009a study which provided effect estimates for this 

endpoint. Short-term exposure-related morbidity and mortality endpoints were modeled 

down to P RB since the 24-hour PM metrics reflected in those epidemiological studies 

typically have LML values below PRB (U.S. EPA, 2010a, section 3.1.1). The RA 

included a sensitivity analysis for long-term mortality comparing modeling of risk down 

to LML with risk modeled down to PRB. Not surprisingly, this sensitivity analysis 

showed that modeling risk down to PRB resulted in notably greater estimates for total 

risk (U.S. EPA, 2010a, section 4.3.1.1). The CASAC also supported this approach, 

stating that “[t]here was support [from CASAC members] for modeling risk for long-term 

PM2.5 exposures to the lowest measured level (LML). For short-term risk estimates, the 

EPA’s approach is appropriate, since as the document points out, the LMLs (which are 

daily) are below the PRB” (Samet, 2009c, p.2). 

(b) Uncertainty related to model specification (selection of C-R functions) 

One commenter argued that the EPA only considered a small fraction of overall 

uncertainty in the epidemiological studies and C-R functions from those studies, 

specifically reflected in the considering the confidence intervals (CIs) associated with the 

effect estimates (API, 2012, Attachment 1, p. 36). This commenter asserted that 

consideration of C-R function CI’s does not capture significant model uncertainty. 

Specifically, this commenter pointed to variation in the risk estimates resulting from 

consideration of different C-R functions in the RA sensitivity analysis. This commenter 

used these arguments to support its views that the analysis results were not "robust" to 

model specification as stated by the EPA (API, 2012, Attachment 1, p. 39). They also 

asserted that the EPA communicated with the study authors associated with Krewski et 

al., 2009a and that, while these authors suggested that the EPA use a random effects 
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model, the EPA elected to use the fixed-effects Cox model instead (API, 2012, 

Attachment 1, p. 38). 

Finally, the commenter asserted that the EPA did not consider multi-pollutant models in 

the RA and relied only on single-pollutant models (particularly for LT mortality) (API, 

2012, Attachment 1, p. 36). This commenter pointed out that an earlier study (Krewski et 

al., 2000) provided evidence of copollutant effects (API, 2012, Attachment 1, p. 38) and 

the commenter recognized that the EPA addressed the issue of copollutants in a 

sensitivity analysis. However, the commenter asserted that the EPA discounted its 

sensitivity analysis of copollutants because control for SO2 may capture a portion of the 

PM2.5 effect. The commenter agreed that this may be true for some regions of the 

country, but not for regions where SO2 is not a major portion of PM2.5. The commenter 

concluded by observing that single- pollutant models may over-estimate risk by including 

the impacts of other copollutants in the PM2.5 signal. 

The EPA disagrees that the RA did not consider the full range of uncertainty associated 

with the C-R functions and only considered uncertainty captured by CIs (i.e., statistical 

fit). As noted by the commenter, the EPA included a sensitivity analysis in the RA which 

specifically examined the issue of model uncertainty by considering a range of different 

C-R function model specifications (U.S. EPA, 2010a, section 4.3.2). The results of that 

sensitivity analysis suggested that, in the case of long-term exposure-related mortality, 

consideration of model uncertainty could result in risk estimates that are from 2-3 times 

higher than risk estimates generated for the core analysis. As discussed in section 5.1.5 of 

the RA, because the Krewski et al. (2009a) study does not provide coverage for lower 

SES individuals who were identified in the ISA as an at-risk population, there is a likely 

low-bias in the effect estimates associated with this study (with the results of the 

sensitivity analysis supporting this observation). Therefore, while the EPA agrees that 

model uncertainty does impact the core risk estimates, in contrast to the commenters’ 

views, the Agency believes the direction of the bias in the Krewski et al. (2009a) models 

is likely downwards which means that it is unlikely that the EPA has over-estimated risk 

using those models. This was an important observation when discussing the overall 

confidence in the risk estimates within the policy context and was highlighted in the PA 

(U.S. EPA, 2011a, section 2.2.2). 

Regarding the Krewski et al., 2009a study authors’ advice to the EPA on model selection 

related to long-term exposure-related mortality, the EPA recognizes that in their 

communication, the study authors stated that they had “refrained from expressing a 

preference among the results for their use in quantitative risk assessment,” preferring to 

“explore several plausible statistical models that we have fit to the available data.” 

(Krewski, 2009b). The EPA considered this input along with the authors’ 

recommendation that a random effects model be used. In addition, the EPA staff 

considered the results of an analysis presented in the study examining the importance of 

exposure time windows in deriving C-R functions. This analysis suggested that models 

developed using both exposure time windows considered in the analysis (1979-1983 and 

1999-2000) were equally effective at representing the relationship between PM2.5

exposure and long-term exposure-related mortality (U.S. EPA, 2010a, section 3.3.3) . 

Therefore, the EPA concluded that C-R functions used in the core analysis should include 
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functions fitted to both exposure time windows. However, the study does not provide 

random effects models with ecological covariates for both exposure time windows (this 

form of model is only provided with a fit to the latter exposure window). Therefore, for 

the core analysis, the EPA reasonably decided to use the Cox proportional hazard model, 

since effect estimates for both exposure time windows were provided for this model. 

However, had random effects models been provided for the separate exposure windows, 

then those would have been considered for the core analysis. It is important to note that 

the EPA did include the random effects referenced by the Krewski et al. (2009a) authors 

as part of the sensitivity analysis completed for the risk assessment, and, as noted above, 

this sensitivity analysis suggested greater risk than estimated in the EPA’s core analysis. 

The issue of copollutant confounding was addressed previously in section II.B.1.b, 

Comment (12)(a) and points made in that response are applicable here. With specific 

regard to the risk assessment, the EPA also notes that the Krewsi et al. (2009a) study 

was selected by the EPA as the basis for the core set of risk estimates over other studies, 

including those using multi-pollutant models, because it has a number of advantages 

(e.g., extended air quality analysis which increases the power of the study and allows the 

study authors to examine the important issue of exposure time windows, rigorous 

examination of a range of model forms and effect estimates, coverage for a range of 

ecological variables, relatively large overall dataset with over 1.2 million individuals and 

156 MSAs) (U.S. EPA, 2010a, section 3.3.3). While the Krewski et al. (2009a) analysis 

did not provide copollutants models, given the overall conclusion regarding the 

robustness of single-pollutant models (as noted in the comment-response referenced 

above - see section II.B.1.b, comment 13.a ), The EPA concluded that these other 

strengths of the study design argued for the use of this study as the basis for the core set 

of risk estimates for long-term exposure-related mortality. In their comments on the first 

draft RA, CASAC supported the use of the Krewski et al. (2009a) study as the basis for 

modeling long-term exposure-related mortality, although they requested that the EPA 

provide an expanded discussion of our rationale for focusing on this study (Samet 2009c). 

The EPA provided that expanded discussion in the final RA (U.S. EPA, 2010a, section 

3.3.3), which was also reviewed by CASAC. 

(c) Failure to sufficiently consider sources of heterogeneity impacting risk estimates. 

The commenter makes several points regarding heterogeneity including: (a) Bayes 

shrunken estimates for ST mortality are likely to mask some of the heterogeneity and can 

result in overly tight SDs for those effect estimates (API, 2012 Attachment 1, p. 38), (b) 

seasonality has been shown to impact both long-term and short-term exposure related risk 

and this source of heterogeneity is not captured in the RA (API, 2012, Attachment 1, p. 

40, 41), (c) regional effect estimates for ST morbidity (as used by the EPA) only capture 

a portion of variability in the response and do not fully capture spatial and seasonal 

heterogeneity (API, 2012, Attachment 1, p. 40), and (d) long-term mortality risk 

estimates are based on nationwide CRFs that do not reflect heterogeneity across regions 

(API, 2012, Attachment 1, p. 42). 

Regarding the use of Bayes shrunken estimates; rather than masking heterogeneity, the 

use of Bayes shrunken estimates has the advantage of correcting for uncertainty-induced 
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heterogeneity. Specifically, city-specific effect estimates are shrunken towards the 

national effect estimates based on consideration of variance in those city-specific effect 

estimates. In those cases where a city-specific effect estimate has a relatively large 

confidence interval (reflecting uncertainty in specification of that effect estimates and not 

necessarily true heterogeneity), then that effect estimate will be shrunken towards the 

national mean, in order to incorporate information from the higher confidence national 

effect estimate. By using city-specific Bayes shrunken estimates, instead of a single 

national-level effect estimate, the EPA did reflect consideration for heterogeneity in the 

PM2.5 effect across cities in modeling short-term exposure-related mortality. 

The EPA addressed comments regarding potential heterogeneity in effect estimates 

related to seasonality in a previous comment (section II.B.1.b, comment 13c). There the 

EPA notes that the importance of seasonality as a factor influencing effect estimates 

varies regionally across the country, but does not have a systematic impact on those 

estimates, reflecting the complexity of this issue. The EPA also points out that for this 

reason heterogeneity related to seasonality is an area that could benefit from additional 

research. 

In response to the comment regarding use of regional effect estimates in modeling ST 

morbidity, the EPA notes that Table 3-6 of the RA (U.S. EPA, 2010a) addresses 

qualitative uncertainty associated with the use of regional effect estimates in modeling 

this category of endpoints (specifically, use of the Bell et al. (2008) study for 

cardiovascular and respiratory hospital admissions). In Table 3-6, the EPA acknowledges 

that these regional effect estimates are in some cases non-statistically significant, but also 

notes that this study benefits from larger sample sizes compared to city-specific models. 

In addition, the EPA reiterates that a lack of statistical significance does not demonstrate 

a lack of causal association between exposure and response. See, e.g. section II.B.5. a. i. 

Comment (4). 

The comment regarding regionality and the modeling of long-term exposure-related 

mortality has been addressed in a previous comment (see section II.B.1.b, Comment 

12.c). As noted there, the PA recognizes that the current epidemiological evidence and 

the limited amount of city-specific speciated PM2.5 data does not allow conclusions to be 

drawn that specifically differentiate effects of PM in different locations (U.S. EPA, 

2011a, p. 2-25). 

(d) Treatment of measurement error and potential direction of associated bias 

The commenters argued that uncertainty related to variation in PM and its components 

(measurement error) has a greater impact on risk estimates than the EPA acknowledges. 

They argue that measurement error can influence results in either direction and not 

mainly lower as asserted by the EPA. (API, 2012, Attachment 1, p. 42). 

The EPA disagrees with the commenter that measurement error has not been adequately 

considered in the RA. This issue was addressed in an earlier comment response (see 

section II.B.1.b, Comment 12.d). In that earlier response, the EPA also notes that the ISA 

concluded “in most circumstances, exposure error tends to bias a health effect estimate 
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downward” (U.S. EPA, 2009a, sections 2.3.2 and 3.8.6). Thus, the EPA has both 

considered and accounted for the possibility of exposure measurement error, including 

possible bias associated with measurement error which can make it more difficult to 

detect true associations. 

(e) Stratification of risk assessments to consider different regions of confidence 

Commenters asserted that the EPA did not stratify risk estimates to consider those 

estimates above and below various levels of interest (e.g., LML with estimates falling 

below the LML having lower confidence). (API, 2012 Attachment 1, p. 42). 

The EPA disagrees with the comment that the EPA did not stratify risk estimates to 

consider estimates above and below various levels of interest (e.g., LML, PRB etc). In 

Figures 2-11 and 2-12 in the PA (U.S. EPA, 2011a), the EPA presents percentile risk 

reductions for long-term and short-term exposure-related mortality, respectively, 

including stratification of those risk reductions into regions of varying confidence. In the 

case of long-term exposure-related mortality, these regions include differentiation based 

on risk estimates falling above and below the LML referenced by the commenter. 

D. Specific Comments Related to Data Handling (Appendix N) 

The EPA is revising the PM2.5 NAAQS data handling rules codified in 40 CFR Part 50, 

appendix N. The EPA is modifying appendix N to conform to the revised PM2.5 standards; most 

notably, the EPA is amending the appendix N procedures by removing the option for spatial 

averaging. In addition to making changes to appendix N that correspond to the changes in the 

annual standard form and the revised primary annual standard level, the EPA is also finalizing 

additional proposed revisions to the appendix in order to codify existing practices currently 

included in guidance documents or implemented as the EPA standard operating procedures; 

better align appendix N language and requirements with proposed changes in PM2.5 ambient 

monitoring and reporting requirements; provide greater clarity and transparency in the 

provisions; and enhance consistency with data handling protocols utilized for other pollutants. 

The EPA received a few substantive comments related to data handling for the primary 

PM2.5 NAAQS. Most comments corresponded to specific revisions to appendix N, some 

addressed issues on which the EPA explicitly solicited feedback at proposal. All substantive 

comments are addressed below. Comments are grouped into four issue categories regarding the 

EPA final decision to: (1) codify proposed changes for identifying PM2.5 data “appropriate” for 

NAAQS comparisons; (2) codify proposed modifications to the procedures for combining data 

for design value computations; (3) incorporate additional PM2.5 data substitution tests; and (4) 

eliminate the special seasonal sampling 98th percentile concentration identification procedure, as 

proposed. 

1. Identifying PM2.5 data “appropriate” for NAAQS comparisons 

This topic concerns “equivalency” issues associated with measurements from certain 

continuous PM2.5 Federal Equivalent Method (FEM) monitors for the calculation of PM2.5 design 

values. As discussed in section VII.A.3 of the preamble to the final rule, “With regards to 

clarification of which monitoring data are appropriate for comparison to the PM2.5 NAAQS, the 
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EPA proposal acknowledged important data quality concerns associated with the PM2.5

measurements collected by continuous PM2.5 FEMs and referenced a subsequent preamble 

proposal section that discussed the issue in more depth and put forward a solution to mitigate the 

data quality concerns.” 

(1) Comment: The EPA received numerous comments expressing concerns regarding the use 

of measurement data provided by certain continuous PM2.5 FEMs for NAAQS 

comparisons. 

Response: As explained in section VIII of the preamble to the final rule, the EPA is 

revising the monitoring regulations in conjunction with the revisions to the PM2.5

standards to include language allowing monitoring agencies to identify PM2.5 FEMs that 

are not providing data sufficiently comparable to the PM2.5 Federal Reference Method 

(FRM) and, with the EPA approval, to allow such data to be excluded from comparisons 

with the PM2.5 NAAQS. The EPA is modifying Sections 1 and 2 of appendix N to 

comport with these revisions. 

2. Procedures for combining data for design value computations 

This topic concerns the procedures for combining monitored data from collocated 

instruments into a single “combined site” data record. The EPA proposed a minor modification 

to these procedures for the unique situation in which a monitoring agency identifies a PM2.5

FRM (that operates on a non-daily schedule) as the site’s primary monitor instead of a collocated 

continuous PM2.5 FEM instrument (that provides a measured value for every day). This minor 

modification, which affects few sites, and the impetus for making it are described in detail in 

section VII.A.3 of the proposal (77 FR 39001). No significant comments were received on the 

proposed minor modification noted above, and thus, for the reasons stated in the preamble to the 

proposed rule, it was included in the revised appendix N. 

In the same section of the proposal that described the minor modification (VII.A.3), the 

EPA explicitly solicited comment on the more general issue of whether “non-primary” (i.e., 

collocated) FEM data should ever be combined with the primary data as part of the comparison 

to the NAAQS for PM2.5. Numerous comments were received regarding that issue. Most 

substantive comments noted that due to comparability issues between certain FEMs and FRMs, it 

was not always prudent to combine the two data types for NAAQS comparison purposes (or 

even to use an FEM sited without a collocated FRM with that intention). These particular types 

of comments are addressed above (in the first comment response), as well as in expanded detail 

in section V below.. 

One commenter questioned a different aspect of the issue of FEM and FRM 

comparability and combination of the two data types. This comment, described below, 

questioned why the EPA had implemented different daily data completeness criteria for the two 

types of data. 

(1) Comment: The EPA received a comment questioning the differences in the data handling 

rules for continuous and filter-based data. Specifically, the commenter questioned why 

continuous (FEM) data required 75 percent completeness (i.e., 18 or more hours) for a 
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valid daily average, while filter-based (FRM) measurements required 23 to 25 hours (95 

percent to 105 percent) for a valid daily value. The commenter suggested that the EPA 

define consistent data handling procedures for continuous and filter-based PM2.5 (and 

PM10 data). 

Response: The EPA did not specifically propose, nor did we seek comment on this issue 

and we are not reopening or otherwise reconsidering the matter in this rulemaking. 

Nonetheless, the EPA notes that the rules for meeting a valid sample with an FRM, which 

have been in place since 1997, are based in part on the desire to obtain valid 

measurements of 24-hour periods, with some flexibility provided if a sample runs less 

than the minimum number of hours for a valid sample (i.e., a minimum 23 hours). The 

Agency also notes that continuous PM2.5 methods, which typically report concentrations 

on an hourly basis and include additional diagnostic data which support data validity 

judgments, provide a basis for determining data completeness and validity hour by hour 

in a manner that is not feasible for 24-hour, filter-based methods. 

3. Additional PM2.5 data substitution tests

With regard to assessments of data completeness, the EPA proposed two additional data 

substitution tests33 in appendix N for validating annual and 24-hour PM2.5 design values 

otherwise deemed incomplete (via the 75 percent and 11 creditable sample minimum quarterly 

data completeness requirements). The EPA proposed to add these tests in order to codify existing 

practices currently included in guidance documents (U.S. EPA, 1999) and implemented as the 

EPA standard operating procedures. Further, the EPA sought to make the data handling 

procedures for PM2.5 more consistent with the procedures used for other NAAQS. While the 

need for data substitution will lessen as more continuous PM2.5 monitors continue to be deployed 

in PM2.5 networks, the EPA believes that these substitution procedures are important to ensure 

that available data, if incomplete, can be confidently used to make comparisons to the NAAQS.

As noted in the EPA proposal, data substitution tests are diagnostic in nature (i.e., they are only 

used in an illustrative manner to show that the determination of NAAQS status based on 

incomplete data is reasonable). 

Previously, section 4.1(c) of appendix N specified only one data substitution test for 

validating an otherwise incomplete design value. That diagnostic test only applied to the primary 

and secondary annual PM2.5 standard, and only applied in instances of a violation. This data 

substitution test is referred to as the “minimum quarterly value” test and is used to determine if 

the NAAQS is not met (i.e., is violated). The EPA proposed two additional data substitution tests 

to allow comparisons to the primary and secondary annual and 24-hour PM2.5 standards to 

determine whether the NAAQS are met. One of these proposed tests uses collocated PM10 data to 

fill in “slightly incomplete”34 data records, and the other uses quarter-specific maximum values 

to fill in “slightly incomplete” data records. These two data substitution tests are referred to as 

the “collocated PM10 test” and the “maximum quarterly value test,” respectively. Both tests are 

designed to confirm that the PM2.5 design value is less than the level of the NAAQS. 

 

33 Data substitution tests are supplemental data completeness assessments that use estimates of 24-hour average 

concentrations to fill in for missing data (i.e., “data substitution”). 

34 Slightly incomplete is defined as less than 75 percent but at least 50 percent quarterly data capture. 
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As codified in section 4 of the revised appendix N, data are substituted for missing data 

to produce a “test design value” which is compared to the level of the NAAQS. If the test design 

value passes the diagnostic test, the “incomplete” design value (without the data substitutions) is 

then considered a valid design value. If an “incomplete” design value does not pass any 

stipulated data substitution test, then the original design value is still considered incomplete (and 

not valid for NAAQS comparisons). 

The EPA received several comments on the proposed addition of the two data 

substitution tests to determine that the NAAQS were met. The majority of comments generally 

supported the addition of data substitution tests. However, two commenters questioned the 

general philosophy of all appendix N data substitution tests (i.e., the existing “over NAAQS” test 

and the two proposed “under NAAQS” tests) by suggesting that there were more appropriate 

techniques for filling in for missing data that would result in better estimates of true design value 

level. Another commenter questioned, and argued against, the use of collocated PM10 data in 

PM2.5 data substitution tests. 

(1) Comment: One commenter questioned, and argued against, the use of collocated PM10

data in PM2.5 data substitution tests. 

Response: At the time of proposal, the EPA believed that PM10 data would be appropriate 

for a PM2.5 data substitution test. However, after consideration of public comments and 

additional air quality analyses, the EPA has decided that substitution of PM10 data is 

largely redundant with the maximum quarterly value test and, thus, as discussed in 

section VII.A.4 of the preamble to the final rule, the EPA decided to not include the PM10

substitution test in appendix N. 

More specifically, the EPA analyzed the most recent three years of PM2.5 and PM10 data 

(2009 to 2011) and assessed the separate benefit of the PM10 substitution routine 

compared to the maximum quarterly value test (Schmidt, 2012b). In this assessment of 

2009 to 2011 PM2.5 design values which did not meet the nominal data completeness 

requirements, the EPA found that collocated PM10 test was almost entirely redundant and 

infrequently utilized after use of the maximum quarterly value test. For the annual PM2.5

NAAQS, the maximum quarter value test in 100 cases resulted in a test design value 

(TDVmax) less than or equal to 12.0 μg/m3

. There were only two additional cases (i.e., 2 

percent) when TDVmax was greater than 12.0 μg/m3

 but the TDV associated with the 

collocated PM10 test was less than 12.0 μg/m3. Similarly for the 24-hour NAAQS, the 

maximum quarter value test in 116 cases resulted in a test design value (TDVmax) less 

than or equal to 35 μg/m3 and again only 2 additional sites (less than 2 percent) passed 

the collocated PM10 test but not the maximum quarterly value test. Furthermore, the 

maximum quarterly value tests allowed the annual and 24-hour design value to be 

validated approximately 5 times more often than through the use of the collocated PM10

test. Accordingly, the EPA has decided to not include the collocated PM10 data 

substitution tests in appendix N, and thereby further simplify the data handling 

procedures for making comparisons to the annual and 24-hour PM2.5 NAAQS. 

Furthermore, the two tests that are now codified in the revised appendix N (the retained 

minimum quarterly value test and the added maximum quarterly value test) are consistent 

with the data substitution tests recently codified for lead, SO2, and NO2. 
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(2) Comment: Some commenters questioned the general philosophy of all appendix N data 

substitution tests (i.e., the existing “minimum quarterly value” test and the two proposed 

tests) and suggested that there were more appropriate techniques for filling in for missing 

data that would result in better estimates of true design value levels. Their suggestions 

included the use of collocated PM2.5 concentrations produced by non-reference or nonequivalent monitors and use of data provided by nearby monitors. 

Response: While acknowledging that other techniques to account for missing data may 

exist, the EPA believes that the data substitution tests provided in the finalized appendix 

N are all appropriate for this purpose, simple to understand and implement, and have 

been tested over time as the standard operating procedures for making NAAQS 

compliance assessments. The EPA is finalizing very conservative approaches to data 

substitution consistent with the intended purpose of verifying that the NAAQS standards 

are either met or not met. Finally, the EPA points out that the test design values derived 

from the data substitution tests are diagnostic in nature; that is; they are only used in an 

illustrative manner to show that the NAAQS status based on incomplete data is 

reasonable. The test design values are not used as the best estimators of the design value 

concentrations (i.e., not used as quantitative replacements for actual design values).35

While the EPA does not agree with the commenter that information from nearby 

monitors or other sources of information would be appropriate for making comparisons 

with the NAAQS, the use of supplemental information can be used for other purposes, 

such as to assist with the implementation of the NAAQS.

4. Seasonal sampling special 98th percentile concentration identification procedure

As stated in section VII.A.4 of the preamble of the final rule, “With regard to identifying 

annual 98th percentile concentrations for comparison to the primary and secondary 24-hour PM2.5

standards, the EPA suggested in the proposal to simplify the procedures used with an approved 

seasonal sampling schedule. Specifically, the EPA proposed to eliminate the use of a special 

formula for calculating annual 98th percentile concentrations with a seasonal sampling schedule 

and thereby proposed to use only one method for calculating annual 98th percentile 

concentrations for all sites (77 FR 39002).” 

The proposal explained that with an approved seasonal sampling schedule, a site is 

typically required to sample during periods of the year when the highest concentrations are 

expected to occur, but less frequently during periods of the year when lower concentrations are 

expected to occur (77 FR 39002). This type of sampling schedule generally leads to an 

unbalanced data record; that is, a data record with proportionally more ambient measurements 

(with respect to the total number of days in the sampling period) in the “high” season and 

proportionally fewer ambient measurements in the “low” season. 

In the proposal, the EPA noted that there were, at that time, very few PM2.5 FRM 

monitors that actually operated on an approved seasonal sampling schedule (only 15 sites out of 

 

35 Appendix N states that when the data substitution tests are satisfied, then the NAAQS design values derived from 

reported PM2.5 data which otherwise would be considered to be incomplete shall be considered valid for 

comparisons to the PM2.5 NAAQS. 
II-104 

approximately 1,000 total sites in 2010) and that almost half of those sites had a collocated PM2.5

FEM monitor (77 FR 39002). The proposal stated that for the 3-year period 2008 to 2010, the 

annual 98th percentile concentrations calculated with the special formula at those 15 sites were 

approximately five percent lower than if the regular procedure was used. Updating these results 

to 2009 to 2011, the EPA shows that among 919 sites there were only 12 (1.3 percent) that still 

operated on an approved seasonal sampling schedule as of the end of 2011; five of the 12 

seasonal sampling sites had a collocated continuous FEM monitor; and for the 12 sites, the 2011 

annual 98th percentile concentrations calculated with the seasonal sampling formula were 1.7 

μg/m3

 (4.5 percent) lower on average than if the standard data handling procedures were used. 

The corresponding median values were 0.1 μg/m3

 (0.8 percent) lower. Both statistics show that 

the change in design values using the seasonal sampling formula was very small (Schmidt, 

2012c). 

The EPA only received a few substantive comments on the Agency’s proposed 

elimination of the special “seasonal sampling” 98th percentile concentration identification 

procedure. All commenters voiced some measure of support for the elimination of the special 

formula. No commenter explicitly opposed the elimination of the formula, however, one 

commenter suggested that the EPA compare results from the special formula (for the sites that 

currently use it) to corresponding results from the “regular” formula to understand the extent, if 

any, the new method introduces bias in the PM2.5 design value. 

(1) Comment: The EPA should compare the seasonal formula with the simplified “regular” 

formula to understand the extent, if any, to which the new method introduces bias in the 

PM2.5 design value at those sites that are currently using it. 

Response: In section VII.A.4 of the preamble to the final rule, the EPA presents the potential bias 

between the ‘regular approach’ and the ‘special formula’ for use with a seasonal sampling 

schedule for estimating calculating annual 98th percentile concentrations for the primary 24-hour 

PM2.5 standard for the 12 sites that operated an approved seasonal sampling schedule in 2011. 

For these locations, the annual 98th percentile concentrations in 2011 calculated with the special 

formula were 1.9 μg/m3

 (5.3 percent) lower on average than if the regular procedure was used; 

the 2009 to 2011 design values were 1.8 μg/m3

 (5.4 percent) lower on average than if the regular 

procedure was used. Moreover, there are no instances in the 2009 to 2011 timeframe (i.e., 0 out 

of 12 monitoring sites) in which the seasonal-formula 24-hour design value meets the NAAQS 

but the corresponding regular-formula design value does not meet the NAAQS 

E. Specific Comments Related to the AQI for PM2.5

The final rule for PM revises 40 CFR 58.50 Index Reporting, and Appendix G to 40 CFR 

58.50, with respect to specifying population of a metropolitan statistical area for purposes of 

index reporting, and specific breakpoints for the AQI sub-index for PM2.5. Incorporating 

responses contained in section V of the preamble to the final rule, the EPA provides the 

following responses to specific comments related to the AQI sub-index for PM2.5. 

(1) Comment: With respect to an AQI value of 100, which is the basis for advisories to 

individuals in sensitive groups, in the proposal the EPA described two general 

approaches that could be used to select the associated PM2.5 level. By far the most 
II-105 

common approach, which has been used with all of the other sub-indices, is to set an AQI 

value of 100 at the same level as the short-term standard. In the proposal, the EPA 

recognized that some state and local air quality agencies have expressed a strong 

preference that the Agency set an AQI value of 100 equal to any short-term standard (77 

FR 38964). These agencies typically expressed the view that this linkage is useful for the 

purpose of communicating with the public about the standard, as well as providing 

consistent messages about the health impacts associated with daily air quality. The EPA 

proposed to use this approach to set the AQI value of 100 at 35 μg/m3, 24-hour average, 

consistent with the proposed decision to retain the current 24-hour PM2.5 standard (Id.). 

An alternative approach discussed in the proposal (77 FR 38964), was to directly evaluate 

the health effects evidence to select the level for an AQI value of 100. This was the 

approach used in the 1999 rulemaking to set the AQI value of 100 at a level of 40 μg/m3

, 

24-hour average, when the 24-hour standard level was 65 μg/m3. This alternative 

approach was used in the case of the PM2.5 sub-index, because the annual and 24-hour 

PM2.5 standards set in 1997 were designed to work together, and the intended degree of 

health protection against short-term risks was not defined by the 24-hour standard alone, 

but rather by the combination of the two standards working in concert. Indeed, at that 

time, the 24-hour standard was set to provide supplemental protection relative to the 

principal protection provided by the annual standard. In the proposal, the EPA solicited 

comment on this alternative approach in recognition that, as proposed, the 24-hour PM2.5

standard is intended to continue to provide supplemental protection against effects 

associated with short-term exposures of PM2.5 by working in conjunction with the annual 

standard to reduce 24-hour exposures to PM2.5. The EPA recognized that in the past, 

some state and local air quality agencies have expressed support for this alternative 

approach. Using this alternative approach could have resulted in consideration of a lower 

level for an AQI value of 100, based on the discussion of the health information 

pertaining to the level of the 24-hour standard in section III.E.4 of the proposal. The EPA 

encouraged state and local air quality agencies to comment on both the approach and the 

level at which to set an AQI value of 100 together with any supporting rationale. 

Of the state or local agencies, or their organizations (e.g., NACAA), that commented on 

the proposed changes to the AQI, only one organization, NESCAUM, expressed some 

support for this approach. In its comments, NESCAUM expressed support for a 24-hour 

standard set at 30 μg/m3

, 24 hour average. NESCAUM also expressed the view that EPA 

should carefully consider how to set the breakpoint for an AQI value of 100. NESCAUM 

expressed the view that if the EPA were to keep the 24-hour PM2.5 standard at 35 ug/m3

, 

the annual standard would be controlling, and a 24-hour breakpoint at that level (35 

ug/m3

) would not be very effective for the purposes of public health messaging. 

However, other agencies, such as the Georgia DNR and Indiana DEM, expressed the 

view that linkage between the short-term standard and the AQI of 100 is useful for the 

purpose of communicating with the public about the standard as well as providing 

consistent messages about the health impacts associated with the daily air quality. 

A comment signed by five physicians (Sammons et al., 2012, p.2) expressed the view that 

based on the body of evidence of morbidity effects, if the current 24-hour standard is 
II-106 

retained, then the calculation of the AQI should be adjusted so that AQI value of 100 

occurs at a PM2.5 concentration less than or equal to 30 μg/m3

. 

Response: Based on these comments, the EPA sees no basis for deviating from the 

approach it proposed. Thus, as discussed in section V of the preamble to the final rule, 

the EPA is taking final action to set an AQI value of 100 at 35 μg/m3

, 24-hour average, 

consistent with the final decision on the 24-hour PM2.5 standard level as summarized in 

section III.F of the preamble to the final rule. 

(2) Comment: One set of commenters (e.g., API and UARG), expressed the view that 

changes to the AQI are not appropriate (API, 2012, pp. 45 to 46; UARG, 2012, pp. 42 to 

43). They noted that air quality is getting better, and in fact is better than when EPA 

established the AQI. These commenters stated that the proposed changes to the annual 

standard and the AQI would mean that the public would hear less often that air quality is 

good, and thereby would receive apparently inconsistent or misleading messages that air 

quality is worse. 

Response: The AQI has been revised several times in conjunction with revisions to the 

standards. State and local air quality agencies and organizations are proficient at 

communicating with the public about the reasons for changes to the AQI. Therefore, the 

EPA strongly disagrees with these commenters that the public will receive inconsistent or 

misleading messages. Recognizing the importance of the AQI as a communication tool 

that allows the public to take exposure reduction measures when air quality may pose 

health risks, the EPA agrees with state and local air quality agencies and organizations 

that favored revising the AQI at the same time as the primary standard. Indeed, failure to 

conform the AQI to the NAAQS could be a derogation of EPA’s duty to utilize “a 

uniform air quality index” to communicate information to the public, and to “provid[e] 

for ... reporting of air quality based upon such uniform air quality index”. CAA section 

319 (a)(1) and (3). 

(3) Comment: A few state and local air quality agencies and organizations (e.g., 

Pennsylvania DEP, South Coast AQMD, and NACAA) recommended against using nearroadway PM2.5 monitors for AQI reporting. In support of this comment, they expressed 

the following views: (1) that near-roadway monitors are source-oriented; (2) that nearroadway monitors represent micro-scale conditions; and (3) the agencies do not have 

experience using such monitors for AQI reporting. Additionally, one state agency, the 

New York DEC/DOH, commented that such reporting may be possible in the future with 

experience.

Response: The EPA disagrees with these comments. These monitors will be located at 

existing near-road stations that have been sited in locations that meet the EPA’s 

definition of ambient air and also comply with applicable 40 CFR part 58 monitoring 

requirements for operating networks to meet multiple objectives including providing air 

quality data to the public in a timely manner. As discussed in section VIII.B.3.b.i of the 

preamble to the final rule, the EPA believes that these monitors will be representative of 

area-wide PM2.5 concentrations indicative of many such locations throughout a 

metropolitan area given the ubiquitous nature of roadway emissions in major urban areas. 
II-107 

Although the stations may be representative of somewhat elevated concentrations, they 

are appropriate for characterizing exposure in typical portions of major urban areas as 

they provide information about PM2.5 concentrations in areas where millions of people 

work, live and go to school. Accordingly, the EPA believes that such data from these 

near-road monitors are appropriate to use for reporting daily air quality information to the 

public through the AQI. The EPA is committed to helping air agencies develop 

appropriate ways to make use of the PM2.5 measurements from these near-roadway 

monitors for AQI reporting purposes. 

 
III-1 

III.RESPONSES TO SIGNIFICANT COMMENTS ON PRIMARY PM10 STANDARD 

Section IV.F of the preamble to the final rule discusses a number of significant public 

comments on the primary PM10 standard. This section incorporates that discussion from the 

preamble, as well as discussion of additional public comments on the primary PM10 standard. 

F. Comments from Groups Supporting Retention of the Primary PM10 Standard 

(1) Comment: Although industry commenters generally agreed with the Administrator’s 

proposed decision to retain the current primary PM10 standard, some also contended that 

the current standard is “excessively precautionary” (NMA and NCBA, 2012, p. 4) and a 

few expressed support for a less stringent standard for coarse particles that are comprised 

largely of crustal material. For example, the Coarse Particulate Matter Coalition (CPMC) 

(2012) and several other industry commenters recommended that the final decision allow 

application of a 98th percentile form for the current standard (i.e. with its level of 150 

ug/m3) in cases where coarse particles consist primarily of crustal material. Such an 

approach would allow more yearly exceedances of the existing standard level than are 

allowed with the current one-expected-exceedance form. These industry commenters 

contended that a 98th percentile form applied in this way would provide appropriate 

regulatory relief for areas where the evidence for coarse particle-related health effects is 

relatively uncertain. 

Response: In reaching her conclusion that the current primary PM10 standard is requisite 

to protect public health with an adequate margin of safety, the Administrator considered 

the degree of public health protection provided by the current standard as a whole, 

including all elements of that standard (i.e., indicator, averaging time, form, level). As 

discussed above and in the following section, this conclusion reflects the Administrator’s 

judgments that (1) the current standard appropriately provides some measure of 

protection against exposures to all thoracic coarse particles, regardless of their location, 

source of origin, or composition and (2) the current standard appropriately allows lower 

ambient concentrations of PM10-2.5 in urban areas, where the evidence is strongest that 

thoracic coarse particles are linked to mortality and morbidity, and higher concentrations 

in non-urban areas, where the public health concerns are less certain. 

Because the considerations that led to these judgments, and to the conclusion that the 

current primary PM10 standard is requisite to protect public health, took into account the 

degree of public health protection provided by the standard as a whole, it would not be 

appropriate to consider revising one element of the standard (e.g., the form, as suggested 

by commenters in this case) without considering the extent to which the other elements of 

the standard should also be revised. The change in form requested by industry 

commenters, without also lowering the level of the standard, would markedly reduce the 
III-2 

public health protection provided against exposures to thoracic coarse particles.36

However, industry commenters have not presented new evidence or analyses to support 

their conclusion that an appropriate degree of public health protection could be achieved 

by allowing the use of an alternative form (i.e., 98th percentile) for some coarse particles, 

while retaining the other elements of the current standard. Nor have these commenters 

presented new evidence or analyses challenging the basis for the conclusion in the 

proposal that the varying amounts of coarse particles allowed in urban versus non-urban 

areas under the current 24-hour PM10 standard, based on the varying levels of PM2.5

present, appropriately reflect the differences in the strength of evidence regarding coarse 

particle effects in urban and non-urban areas. In light of this, EPA does not believe that a 

reduction in public health protection, such as that requested by industry commenters, is 

warranted. 

In further considering these comments, it is to be remembered that epidemiologic studies 

have not demonstrated that coarse particles of non-urban origin do not cause health 

effects, and commenters have not provided additional evidence on this point. While there 

are fewer studies of non-urban coarse particles than of urban coarse particles, several 

studies have reported positive and statistically significant associations between coarse 

particles of crustal, non-urban origin and mortality or morbidity (Ostro et al., 2003; Bell 

et al., 2008; Chan et al., 2008; Middleton et al., 2008; Perez et al., 2008). These studies 

formed part of the basis for the PM Integrated Science Assessment conclusion that 

“recent studies have suggested that PM (both PM2.5 and PM10-2.5) from crustal, soil or 

road dust sources or PM tracers linked to these sources are associated with cardiovascular 

effects” (U.S. EPA, 2009a, p. 2-26). Moreover, crustal coarse particles may be 

contaminated with toxic trace elements and other components from previously deposited 

fine PM from ubiquitous sources such as mobile source engine exhaust, as well as by 

toxic metals from smelters or other industrial activities, animal waste, or pesticides (U.S. 

EPA, 2004, p. 8-344). In the proposal, the Administrator acknowledged the potential for 

this type of contamination to increase the toxicity of coarse particles of crustal, non-urban 

origin (77 FR 38960; see also 71 FR 61190). 

In suggesting a change in the form of the current standard, industry commenters also did 

not address the manifold difficulties noted above, and in the last review, associated with 

developing an indicator that could reliably identify ambient mixes dominated by 

particular types of sources of coarse particles. See above and 71 FR 61193. Yet such an 

 

36Based on regression analyses presented in the PA (U.S. EPA, 2011a, Figures 3-7 and 3-8), 

PM10 one-expected-exceedance concentration-equivalent design values were between 

approximately 175 and 300 g/m3

 at monitoring locations recording 3-year averages of 98th

percentile 24-hour PM10 concentrations around 150 g/m3 (i.e., the level of the current standard). 

This suggests that, depending on the location, a 24-hour PM10 standard with a 98th percentile 

form in conjunction with the current level (i.e., as recommended by these commenters) could be 

“generally equivalent” to a 24-hour PM10 standard with a one-expected-exceedance form and a 

level as high as approximately 300 g/m3

. Based on this analysis, a 24-hour PM10 standard with 

a 98th percentile form and a level of 150 g/m3

 would be markedly less health protective than the 

current standard. 
III-3 

indicator would be a prerequisite of the type of standard these commenters request. 

For all of the reasons discussed above, the EPA does not agree with industry commenters 

who recommended allowing the application of a 98th percentile form for the current 

standard in cases where coarse particles consist primarily of crustal material. 

(2) Comment: Some industry commenters contended that the uncertainties and limitations 

that precluded a quantitative risk assessment also preclude revising the PM10 standard. 

Response: Although the EPA agrees that there are important uncertainties and limitations 

in the extent to which the quantitative relationships between ambient PM10-2.5 and health 

outcomes can be characterized in risk models, the Agency does not agree that such 

limitations alone preclude the option of revising a NAAQS. As noted above, the lack of a 

quantitative PM10-2.5 risk assessment in the current review adds uncertainty to conclusions 

about the extent to which revision of the current PM10 standard would be expected to 

improve the protection of public health, beyond the protection provided by the current 

standard. However, the EPA does not agree that such uncertainties necessarily preclude 

revision of a NAAQS. Indeed, with respect to thoracic coarse particles, the D.C. Circuit 

noted that “[a]lthough the evidence of danger from coarse PM is, as the EPA recognizes, 

‘inconclusive’, the agency need not wait for conclusive findings before regulating a 

pollutant it reasonably believes may pose a significant risk to public health.” 559 F. 3d at 

533. Thus, the Administrator’s conclusion that the current 24-hour PM10 standard 

provides requisite protection of public health relies on her consideration of the broad 

body of evidence, rather than solely on the uncertainties that led to the decision not to 

conduct a quantitative assessment of PM10-2.5 health risks. 

(3) Comment: Some industry commenters argued that the EPA did not adequately consider 

exposure measurement error, which they asserted is an important source of bias in 

epidemiological studies that can bias effect estimates in either direction (e.g., NMA and 

NCBA, 2012). 

The EPA has recognized that exposure measurement error is an important source of 

uncertainty, and that the variability in risk estimates observed in multi-city studies could 

be attributed, in part, to exposure error due to measurement-related issues (77 FR 38910). 

However, the Agency disagrees with the commenters’ assertion that exposure 

measurement error was not adequately considered in this review. The Integrated Science 

Assessment included an extensive discussion that addresses issues of exposure 

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

error may lead to bias in effect estimates in epidemiological studies. A number of studies 

evaluated in the last review (U.S. EPA, 2004, section 8.4.5) and in the current review 

(U.S. EPA, 2009a, section 3.8.6) have discussed the direction and magnitude of bias 

resulting from specified patterns of exposure measurement error (Armstrong 1998; 

Thomas et al. 1993; Carroll et al. 1995) and have generally concluded “classical” (i.e., 

random, within-person) exposure measurement error can bias effect estimates towards the 

null. Therefore, consistent with conclusions reached in the last review, the Integrated 

Science Assessment concluded “in most circumstances, exposure error tends to bias a 

health effect estimate downward” (U.S. EPA, 2009a, sections 2.3.2 and 3.8.6). Thus, the 
III-4 

EPA has both considered and accounted for the possibility of exposure measurement 

error, and the possible bias would make it more difficult to detect true associations, not 

less difficult. 

(4) Comment: The CPMC (2012) commented that EPA should retain the current PM10

standard. In support of their comments, the CPMC submitted analyses of PM10 air quality 

characterizing the potential implications of a revised PM10 standard. Many of these 

analyses were originally submitted to EPA in July 2011. The CPMC analyses were also 

cited by other industry commenters (e.g., NMA and NCBA, 2012) who supported the 

proposed decision to retain the current PM10 standard. 

Response: As discussed above and in the preamble, the Administrator’s decision to retain 

the current PM10 standard is consistent with the overall position expressed by the CPMC 

and by other industry groups. However, the EPA does not agree with all aspects of the 

analyses supporting this CPMC position. The EPA has previously responded to these 

analyses in a letter to the CPMC (Wayland, 2011). 

G. Comments from Groups Supporting Revision of the Primary PM10 Standard 

(1) Comment: Commenters representing a number of environmental groups and medical 

organizations disagreed with the Administrator’s proposal to retain the current primary PM10

standard. These commenters generally requested that the EPA revise the PM10 standard to 

increase public health protection, consistent with the recommendations from CASAC. 

Response: As discussed above and in the proposal, in reaching provisional conclusions in the 

proposal regarding the current standard, the Administrator carefully considered CASAC’s 

advice and recommendations. She specifically noted that in making its recommendation 

on the current PM10 standard, CASAC did not discuss its approach to considering the 

important uncertainties and limitations in the health evidence, and did not discuss how 

these uncertainties and limitations were reflected in its recommendations. Such 

uncertainties and limitations contributed to the conclusions in the Integrated Science 

Assessment that the PM10-2.5 evidence is only suggestive of a causal relationship, a 

conclusion that CASAC endorsed (Samet, 2009e,f). These commenters also did not 

address the important uncertainties in the epidemiologic studies on which their comments 

are based. Given the importance of these uncertainties and limitations to the 

interpretation of the evidence, as reflected in the weight of evidence conclusions in the 

Integrated Science Assessment and as discussed in the proposal, the Administrator judges 

that it is appropriate to consider and account for them when drawing conclusions about 

the implications of individual PM10-2.5 health studies for the current standard. 

Commenters have not provided new information that would change the Administrator’s 

views on the evidence and uncertainties. 

(2) Comment: In recommending that the PM10 standard be revised, some commenters 

supported their conclusions by referencing studies that evaluated PM10, rather than 

PM10-2.5. These commenters contended that “[t]he most relevant studies to the setting of 

a PM10 standard are the thousands of studies that have reported adverse effects associated 

with PM10 pollution” (ALA et al., 2012). 
III-5 

Response: As discussed in the Policy Assessment, the proposal, and the preamble to the 

final rule, since the establishment of the primary PM2.5 standards, the purpose of the 

primary PM10 standard has been to protect against health effects associated with 

exposures to PM10-2.5. PM10 is the indicator, not the target pollutant. With regard to the 

appropriateness of considering PM10 health studies for the purpose of reaching 

conclusions on a standard meant to protect against exposures to PM10-2.5, the proposal 

noted that PM10 includes both fine and coarse particles, even in locations with the highest 

concentrations of PM10-2.5. Therefore, the extent to which PM10 effect estimates reflect 

associations with PM10-2.5 versus PM2.5 can be highly uncertain and it is often unclear 

how PM10 health studies should be interpreted when considering a standard meant to 

protect against exposures to PM10-2.5. Given this uncertainty and the availability of a 

number of PM10-2.5 health studies in this review, the Integrated Science Assessment 

considered PM10-2.5 studies, but not PM10 studies, when drawing weight-of-evidence 

conclusions regarding the coarse fraction.37 In light of the uncertainty in ascribing PM10-

related health effects to the coarse or fine fractions, indicating that the best evidence for 

effects associated with exposures to PM10-2.5 comes from studies evaluating PM10-2.5

itself, and given CASAC’s support for the approach adopted in the Integrated Science 

Assessment, which draws weight-of-evidence conclusions for PM2.5 and PM10-2.5 but not 

for PM10 (Samet, 2009f), the EPA continues to conclude that it is appropriate to focus on 

PM10-2.5 health studies when considering the degree of public health protection provided 

by the current primary PM10 standard, a standard intended exclusively to provide 

protection against exposures to PM10-2.5. 

(3) Comment: Two State commenters (New York DOH/DEC, 2012) expressed the view that 

the PM10 standard should be tightened if the level of the PM2.5 standard is tightened. 

These commenters contended that “In order to maintain adequate protection against 

exposure to coarse particles in urban settings, the PM10 standard would need to be 

lowered to ensure that coarse particle levels do not rise as PM2.5 levels decline.” 

Response: While it is possible that the relationships between PM2.5 and PM10-2.5

concentrations and/or composition will change in some locations in the future, it is not 

possible at this time to precisely predict the nature of such potential future changes, or to 

account for them in the standard. For example, changes in ambient PM2.5 concentrations 

could alter not only the allowable coarse particle concentrations under the PM10 standard 

in some locations, but also the extent to which thoracic coarse particles are contaminated 

with specific fine particle components (section IV.G of final rule). Alterations in coarse 

particle composition could impact the toxicity of ambient thoracic coarse particles, 

potentially altering the health effects that result following coarse particle exposures 

and/or altering the coarse particle exposure concentrations resulting in such health 

 

37Although EPA relied in the 1997 review on evidence from PM10 studies, EPA did so out of 

necessity (i.e., there were as yet no reliable studies measuring PM10-2.5). In the 2006 review, EPA 

placed primary reliance on epidemiologic studies measuring or estimating PM10-2.5, although 

there were comparatively few such studies. In this review, a larger body of PM10-2.5 studies are 

available. EPA regards these studies as the evidence to be given principal weight in reviewing 

the adequacy of the PM10 standard. 
III-6 

effects. Based on the available health evidence, it is unclear the extent to which such 

future potential changes in PM concentrations and/or composition could support revisions 

to the PM NAAQS. 

Future scientific studies will evaluate PM10-2.5 health effects as fine particle 

concentrations and/or coarse particle composition change. The issue of whether the 

existing PM10 standard remains requisite to protect public health with an adequate margin 

of safety will need to be revisited in future reviews of the PM NAAQS, in light of new 

evidence and air quality information reflecting any future changes in particle 

concentrations and/or composition. 

(4) Comment: Some environmental and public health groups disagreed with the weight-ofevidence conclusions for coarse particles. Specifically, the ALA et al. (2012) contended 

that “EPA should re-evaluate this conclusion and consider separately a classification of 

PM10 effects on mortality as likely causal, in light of evidence.” 

Response: As discussed in the preamble to the final rule (section IV.F), the EPA 

disagrees with these commenters regarding the extent to which it is appropriate to rely on 

PM10 studies when considering a standard meant to protect the public health against 

exposures to PM10-2.5. In addition, the EPA disagrees that it is appropriate to draw 

separate weight-of-evidence conclusions for PM10. When this issue was presented to 

CASAC during the development of the Integrated Science Assessment, they made the 

following recommendation (Samet, 2009e, p. 3): 

Revisions are needed to remove the impression that PM10 is a separate 

pollutant from PM2.5 and PM10-2.5. The [draft] ISA handles PM10, PM2.5, 

and PM10-2.5, as if they were separate entities, even though the latter two 

are components of PM10. The CASAC cautions against this approach and 

notes that PM10 is a mixture that contains varying proportions of particles 

in the smaller and larger size ranges. 

In light of this advice, the final Integrated Science Assessment did not draw separate 

weight-of-evidence conclusions for PM10. Public commenters have not presented new 

information that would justify going against CASAC’s recommendation on this issue. 

(5) Comment: Environmental and public health groups also commented on the 

appropriateness of setting standards based on evidence that has been judged to be 

“suggestive of a causal relationship,” as is the case for PM10-2.5. Specifically, the ALA et 

al. (ALA et al., 2012) stated that “EPA must set standards that protect against effects that 

are deemed suggestive by the evidence.” 

Response: The EPA agrees with these commenters that the available evidence supports 

the appropriateness of setting a standard to protect public health against exposures to all thoracic 

coarse particles. However, although the commenters are correct that EPA may establish 

standards to guard against threats which are uncertain, or even which research has not yet 

identified, it is also the case that EPA may evaluate the strength of the evidence, and a standard 

may legitimately be more or less stringent in order to reflect the strength of that evidence. 
III-7 

Therefore, in deciding whether it is appropriate to revise the PM10 standard, it is reasonable for 

EPA to account for the uncertainties inherent in the evidence, which underlie the determination 

that the evidence is “suggestive of a causal relationship.” As discussed extensively in the 

preamble to the final rule (section IV.G), the Administrator concludes that the current PM10

standard is requisite to protect public health with an adequate margin of safety against effects 

associated with exposures to thoracic coarse particles. 

. 
IV-1 

IV. RESPONSES TO SIGNIFICANT COMMENTS ON SECONDARY PM 

STANDARDS 

A. General Comments on Proposed Secondary PM Standards 

A number of comments on the proposed secondary standards for PM were general in 

nature, basically expressing one of three views: (1) support for setting a distinct secondary 

standard to protect from visibility impairment; (2) opposition to setting a distinct secondary 

standard to protect from visibility impairment; or (3) support for revising the secondary 

standards to be equivalent in all respects to the proposed primary standards, including the revised 

primary annual standard. Many of these commenters simply expressed their views without 

stating any rationale, while others gave general reasons for their views but without reference to 

the factual evidence or rationale presented in the proposal notice as a basis for the Agency’s 

proposed decision. In general, the large majority of comments focused on the proposal to set a 

distinct standard to protect against visibility impairment. Relatively few commenters addressed 

the proposal to retain the existing secondary standards for non-visibility welfare effects. 

The preamble to the final rule presents the Agency’s full response to these views, 

expressly identifying: (1) the strengths and limitations of the scientific evidence regarding PMrelated visibility impairment; (2) the need for and appropriateness of a secondary standard to 

protect from visibility impairment; (3) the appropriate indicator, averaging time, form and level 

for a standard designed to protect against PM-related visibility impairment; (4) the scientific 

evidence regarding non-visibility welfare effects and the appropriate standards to protect against 

those effects; and 5) the advice of CASAC regarding the secondary standard for PM. See 

sections VI.A, VI.B, and VI.C of the preamble to the final rule for a discussion of these topics.

B. Specific Comments on Proposed Secondary PM Standard to Protect Visibility 

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

to set a distinct secondary standard for protection from visibility impairment. Many of these 

comments addressed specific elements of the proposed distinct secondary PM2.5 standard, 

including indicator, averaging time, form, and level. Other comments focused on the strength of 

currently available evidence—particularly the visibility preference studies—as a basis for setting 

a distinct secondary standard. In addition, some commenters questioned whether a distinct 

secondary standard was needed in light of the protection already afforded by the existing 

secondary standards for PM, while others raised legal issues or other challenges, such as issues 

related to the Regional Haze Program, data handling, or monitoring. Responses to key issues 

raised on these topics are generally summarized in section VI.C.1 of the preamble. Below, the 

EPA provides more detailed responses to the full range of significant issues raised in these 

comments. 

It is important to note that because the Administrator’s final decision regarding the 

secondary PM standards differs from what was proposed, a number of issues raised by 

commenters are now moot. Specifically, since the Administrator is retaining the current suite of 

secondary PM standards generally, while revising only the form of the secondary annual PM2.5

standard to remove the option for spatial averaging consistent with this change to the primary 

annual PM2.5 standard, and is not establishing a distinct secondary standard for protection from 
IV-2 

visibility impairment, concerns expressed by commenters about various aspects of the proposal, 

such as the overlap with the Regional Haze Program, the data handling requirements, and 

monitoring requirements, are no longer pertinent. Though the EPA has summarized many of 

these issues below, it does not respond to them in detail since they pertained to specific aspects 

of the proposal that were not adopted in the final rule. 

1. Indicator 

In the current review of the secondary PM2.5 standards, the EPA considered what type of 

indicator it would be appropriate to adopt for a distinct secondary standard designed to protect 

from visibility impairment. While agreeing with CASAC that a directly measured PM light 

extinction indicator would provide the most direct link between PM in the ambient air and PMrelated light extinction, the Administrator concluded this was not an appropriate option in this 

review due to technical limitations, and instead proposed to adopt a new calculated PM2.5 light 

extinction indicator, similar to that used in the Regional Haze Program (i.e., using an IMPROVE 

algorithm as translated into the deciview scale). This kind of indicator, referred to as a PM2.5

visibility index, would directly incorporate the effects of differences in PM2.5 composition and 

relative humidity on visibility. 

A large number of public comments on the secondary PM standards addressed the 

suitability of utilizing a calculated light extinction indicator for the distinct secondary standard as 

proposed. Some commenters supported the proposal to adopt a calculated light extinction 

indicator, while others advocated relying on direct measurements instead. Commenters from 

both groups expressed concern over specific elements of the proposed calculated PM2.5 visibility 

index. In particular, commenters expressed differing views on which IMPROVE algorithm 

should be utilized; whether it is appropriate to exclude coarse particles from the indicator; and 

whether the proposed protocols for incorporating data on relative humidity and PM2.5 species are 

appropriate. In addition, some commenters expressed concern about the omission of other 

contributors to visibility impairment from the visibility index. The EPA has addressed these 

comments in section VI.C.1.b of the proposal, and provides additional details in response to 

specific issues, below. 

a. Comments Supporting Directly Measured Light Extinction Indicator 

(1) Comment: The majority of commenters noted the uncertainties associated with relying on 

a calculated indicator and argued that it was inappropriate to rely on a calculated light 

extinction indicator rather than direct measurements. A number of these commenters 

advocated postponing setting a distinct secondary standard until an approach based on 

direct light extinction measurements can be adopted. 

Response: The EPA generally agrees with commenters that an indicator based on directly 

measured light extinction would provide the most direct link between PM in the ambient 

air and PM-related light extinction. However, as noted at the time of proposal and in 

accordance with the advice of CASAC, the EPA has concluded that this is not an 

appropriate option in this review because a suitable specification of currently available 

equipment or performance-based verification procedures could not be developed in the 

time frame of this review. 
IV-3 

In evaluating whether direct measurement of light extinction was appropriate to consider 

in the context of this PM review, the EPA produced a White Paper on Particulate Matter 

(PM) Light Extinction Measurements (U.S. EPA, 2010g) and solicited comment on the 

White Paper from the Ambient Air Monitoring and Methods Subcommittee (AAMMS) 

of CASAC. In its review of the White Paper (Russell and Samet, 2010a), the CASAC 

AAMMS commented on the capabilities of currently available instruments, and 

expressed optimism regarding the near-term development of even better instruments for 

such measurement than are now commercially available. The CASAC AAMMS advised 

against choosing any currently available commercial instrument as the basis for an FRM, 

or even selecting a general measurement approach as an FRM, because to do so could 

discourage development of other potentially superior approaches. Instead, the CASAC 

AAMMS recommended that EPA develop performance-based approval criteria for direct 

measurement methods in order to put all approaches on a level playing field. Such criteria 

would necessarily include procedures and pass/fail requirements for demonstrating that 

the performance criteria have been met, both in the laboratory and during field tests. At 

the present time of this review, the EPA has not undertaken to develop and test such 

performance-based approval criteria. The EPA anticipates that if an effort were begun it 

would take at least several years before such criteria would be ready for proposed 

regulatory use as an FRM. 

Since the available evidence demonstrates that a strong correspondence exists between 

calculated PM2.5 light extinction and PM-related visibility impairment, the EPA does not 

believe it would be appropriate to postpone setting a distinct secondary standard until an 

approach based on direct light extinction measurements could be adopted. Furthermore, 

the EPA notes CASAC’s conclusion that the proposed calculated PM2.5 light extinction 

indicator based on the original IMPROVE algorithm “appears to be a reasonable 

approach for estimating hourly light extinction” (Samet, 2010d, p. 11) and “its reliance 

on procedures that have already been implemented in the CSN and routinely collected 

continuous PM2.5 data suggest that it could be implemented much sooner than a directly 

measured indicator” (Samet, 2010d, p. iii). 

(2) Comment: Some commenters argued that the proposed calculated light extinction 

indictor is ill suited for a bright line standard because the method uses average humidity 

and a reconstructed visibility measurement calculated from PM2.5 speciation filter 

analysis, rather than measuring what is actually observed by individuals. 

Response: The available evidence demonstrates that a strong correspondence exists 

between calculated PM2.5 light extinction and PM-related visibility impairment. Thus, the 

EPA concludes that in the absence of reliable direct measurements of visibility 

impairment in urban areas, it is appropriate to rely on a calculated light-extinction 

indicator. The EPA notes that CASAC concluded that relying on a calculated PM2.5 light 

extinction indicator based on PM2.5 chemical speciation and relative humidity data 

represented a reasonable approach. The inputs that are necessary include measurements 

that are available through existing monitoring networks and established protocols. 

(3) Comment: Many commenters stated that relying on direct light extinction measurements 

would enable a standard to be based on a shorter averaging time, either 1-hour or sub-
IV-4 

daily (4 to 6 hours), consistent with the more instantaneous nature of perceptions of 

visual air quality and the advice of CASAC in this review. 

Response: The EPA agrees with commenters that there would be a number of advantages 

to direct measurements of light extinction for use in a secondary standard relative to 

estimates of PM2.5 light extinction calculated using PM2.5 mass and speciation data. These 

include greater accuracy of direct measurements with shorter averaging times and overall 

greater simplicity when compared to the need for measurements of multiple parameters to 

calculate PM light extinction. However, as noted above, the EPA has concluded, in 

accordance with the advice of CASAC, that direct measurement is not an appropriate 

option in this review because a suitable specification of currently available equipment or 

performance-based verification procedures could not be developed in the time frame of 

this review. Furthermore, the available evidence demonstrates that a strong 

correspondence exists between calculated PM2.5 light extinction and PM-related visibility 

impairment. Thus, the EPA concludes that in the absence of reliable direct measurements 

of visibility impairment in urban areas, it is appropriate to rely on a calculated lightextinction indicator. 

(4) Comment: Numerous commenters supported developing a pilot study to field test and 

evaluate direct measurement instrumentation in several areas around the country, as 

recommended by CASAC AAMMS. These commenters recommended collocating pilot 

direct measurement instruments with other existing monitors and cameras such as 

CAMNET, the National Weather Service’s Automated Surface Observing System 

monitors, and continuous PM2.5 and filter-based PM2.5 speciation monitors. Such a pilot 

field-study program using candidate instruments would allow for near real-time 

measurements of light extinction and would enable comparisons between existing 

monitors and alternative approaches. 

Response: The EPA agrees with these commenters that, resources permitting, it would be 

useful to establish such a pilot program to inform future reviews of the PM NAAQS. 

However, in the current review, the Agency continues to agree with CASAC that relying 

on a calculated PM2.5 light extinction indicator based on PM2.5 chemical speciation and 

relative humidity data represents a reasonable approach at this time. The inputs that are 

necessary include measurements that are available through existing monitoring networks 

and established protocols. 

b. Comments Supporting Calculated Light Extinction Indicator 

(1) Comment: Recognizing the limitations on applying direct measurements at present, 

commenters supporting the proposal to set a distinct standard argued that relying on 

“calculated light extinction is a reasonable first approach” (DOI, p. 2). These commenters 

pointed to the advice of CASAC, which had acknowledged that it was not possible for the 

EPA to develop an FRM for direct measurement of light extinction within the time frame 

of this review and had concluded that relying on a calculated PM2.5 light extinction 

indicator represented a reasonable approach that could be implemented sooner than a 

directly measured indicator. These commenters generally supported the proposal to adopt 

a calculated PM2.5 light extinction indicator, at least as an interim approach. 
IV-5 

Response: The EPA agrees with commenters who stated that relying on calculated PM2.5

light extinction would be a reasonable approach at this time. The EPA notes that this 

conclusion is consistent with the advice of CASAC, which advised the EPA not to choose 

any currently available commercial instrument, or even a general measurement approach 

for direct light extinction measurement at this time because to do so could discourage 

development of other potentially superior approaches. Given the limitations in current 

direct measurement options, the EPA continues to conclude that it is appropriate to rely 

on a calculated PM2.5 light extinction approach for purposes of a PM2.5 visibility index at 

this time. 

c. Comments on Specific Aspects of Calculated Light Extinction Indicator 

(1) Comment: A number of commenters expressed concern over the proposal to use the 

original IMPROVE algorithm as the basis for the calculated light extinction indicator. 

These commenters noted that the original IMPROVE algorithm has been shown to have 

consistent biases at both low and high levels of light extinction. In particular, these 

commenters expressed concern with the algorithm’s bias at higher levels of light 

extinction, which they pointed out were the conditions that might be encountered on 

hazier days in urban areas. In general, these commenters endorsed using the revised 

IMPROVE algorithm as a basis for a calculated light extinction indicator. 

Response: The EPA agrees that the revised algorithm was developed to correct known 

biases in the estimated extinction in remote areas under the original IMPROVE algorithm 

under very low and very high light extinction conditions, with further modifications and 

additions to better account for differences in particle composition and aging in remote 

areas. However, the EPA does not believe that these same modifications and additions 

would necessarily be appropriate for calculating light extinction in urban areas. In 

general, the EPA considers the original algorithm to be suitable for purposes of 

calculating urban light-extinction, although the Agency believes some adjustments to this 

algorithm may be appropriate for urban environments, as discussed in the preamble to the 

final rule. 

There are several reasons why the EPA considers the original IMPROVE algorithm better 

suited to urban environments than the revised algorithm. First, the EPA considers that the 

multiplier of 1.8 used to convert OC to OM in the revised IMPROVE algorithm is too 

high for urban environments. This is discussed further in response to specific comments 

on the OC multiplier, below. Second, the EPA does not believe that it would be 

appropriate to include a term for hygroscopic sea salt for urban light extinction. Unlike in 

some remote coastal locations, sea salt is not major contributor to light extinction in 

urban areas. Pitchford (2010) estimated that in most instances, the contribution of sea salt 

to PM2.5 light extinction is well below 5% for PM2.5 light extinction greater than 24 dv. 

Moreover, urban sources of salt include sanding of roads during the winter and those reentrained particles are mostly in the coarse size range. 

Third, the EPA does not consider the revised algorithm’s differentiation between 

different size modes of sulfate, nitrate, and organic mass appropriate for urban areas. Like 

in remote areas, small and large size modes of sulfate, nitrate and organic mass would 
IV-6 

exist in the urban environment. However, the apportionment of the total fine particle 

concentration of each of the three PM2.5 components into the concentrations of the small 

and large size fractions in urban areas would likely need a different approach than that 

used for remote areas. This is because of the closer proximity of urban sources to their 

emissions. This is a particular concern not only for organic mass, which as explained 

previously has a large contribution from nearby urban emission sources, but also for 

PM2.5 nitrate whose concentrations are also higher in urban areas compared to the 

surrounding regions. Thus, a higher portion of the total urban concentration may be in the 

small mode compared to remote areas and thus a different apportionment algorithm 

would be needed. 

Finally, the EPA does not consider it necessary to employ site-specific Rayleigh light 

scattering terms in place of a universal Rayleigh light scattering value for purposes of 

calculating light extinction in urban areas for purposes of calculating the 90th percentile 

values. The site-specific Rayleigh value is most important to accurately estimate 

extinction in remote areas, particularly for the average of the 20% best visibility days, an 

essential metric for the regional haze program. In most other instances, the Raleigh light 

scattering term has relatively little impact. For example, Pitchford (2010) estimated that 

the difference between the approach employed by the EPA in the UFVA and Policy 

Assessment to define the 20 to 30 dv range of candidate protection levels and an 

approach utilizing site-specific Rayleigh light scattering terms was less than 0.1 dv for 

light extinction around 30 dv. 

For all of these reasons, the EPA considers the original IMPROVE algorithm better 

suited to the task of calculating urban light extinction than the revised IMPROVE 

algorithm. However, the EPA does consider it appropriate to make certain adjustments to 

the original algorithm for purposes of calculating urban light extinction. As discussed 

below, the EPA believes it is appropriate to use a 1.6 multiplier to convert OC to OM in 

urban areas, and to exclude the term for coarse particles from the IMPROVE equation. 

(2) Comment: Some commenters supported use of the revised IMPROVE algorithm. These 

commenters noted that the revised equation has been through a peer review which 

confirmed that it is based on the best science and corrects the biases inherent in the 

original algorithm. Commenters also noted that this revised algorithm has been widely 

incorporated into Regional Haze plans, and urged the EPA to use this same equation in 

the visibility index for the sake of consistency: “EPA approved this approach for regional 

haze and does not dispute its greater accuracy. Therefore, a national secondary ambient 

air quality standard based on criteria that accurately reflect the latest scientific knowledge 

logically should not revert to the original IMPROVE algorithm” (Oklahoma DEQ, p. 2). 

Other states agreed, arguing that “Utilizing alternate forms of the equation will lead to 

inconsistency in how agencies and regulated sources evaluate visibility impacts and add 

an additional layer to source, SIP, and Regional Haze analysis” (Arizona DEQ, p. 3). 

These states urged the EPA to adopt the revised improve algorithm to maintain 

consistency between programs. 

Response: The EPA agrees with commenters that the revised algorithm represents the 

best science for estimating visibility impairment from aerosol components in remote 
IV-7 

areas. The EPA does not agree that this approach is necessarily a better approach for 

estimating visibility impairment in urban areas. Considering the nature of urban PM 

composition, EPA concludes that it is appropriate to use the original IMPROVE 

algorithm (with the adjustments discussed in response to the previous comment, above) 

to relate urban PM to light extinction in urban areas. 

The revised algorithm was designed to separately account for extinction and water uptake 

from freshly emitted versus aged aerosols and also to account for hygroscopic sea salt 

which was not considered in the original algorithm. The new formula includes an 

adjustment for the calculation of OM as 1.8*OC to account for the more aged and 

oxygenated organic aerosol that is found in remote areas which may also result from 

different emission sources. 

The EPA does not believe that these same modifications and additions would necessarily 

be appropriate for calculating light extinction in urban areas. The composition of, and the 

mix of emission sources contributing to, PM2.5 in urban areas is different than in remote 

areas. Thus, the urban PM2.5 would have different light extinction properties. In 

particular, urban organic mass results from local and regional sources and thus has a 

different ratio of fresh to aged emissions and a different mass to organic carbon ratio than 

rural areas. The approach used by the revised algorithm to partition OM into small and 

large particles may not be appropriate for the urban mixture where a higher percentage of 

smaller particles are likely from the fresher nearby urban emissions. In addition, the 1.8 

OC to OM multiplier in the revised improve algorithm is likely too high for urban OC. 

The revised algorithm was developed for use in remote areas and was evaluated with 

concurrently available light scattering measurements at 21 remote locations. The revised 

algorithm is largely untested in urban areas and in fact, the PM2.5 portion of the algorithm 

may overestimate urban extinction because of the contributions from organic mass. For 

all of these reasons, the EPA has concluded that it would not be appropriate to use the 

revised IMPROVE algorithm for purposes of calculating light extinction in urban areas. 

(3) Comment: Some commenters noted that both the original and the revised IMPROVE 

algorithms were designed in support of the Regional Haze Program which is focused on 

largely rural Class I areas, and that neither algorithm is necessarily suitable for urban 

areas. Noting that the EPA has not thoroughly evaluated the applicability of either 

IMPROVE algorithm in urban areas, these commenters urged additional research to 

evaluate the suitability of either algorithm (or an alternative approach) in urban areas. 

Response: EPA agrees with commenters that neither the original nor the revised 

IMPROVE algorithms have been evaluated in urban areas. Based on the advice of 

CASAC (Samet, 2010b), EPA concluded that it was unnecessary to develop a new urbanoptimized algorithm to assess the relationship between urban PM to PM light extinction. 

(4) Comment: Some commenters stated that they believed the 1.4 multiplier used to convert 

organic carbon (OC) to organic mass (OM) in the original IMPROVE algorithm was too 

low, and that it would be more appropriate to use a higher multiplier, such as the 1.8 

multiplier that has been adopted as part of the revised IMPROVE algorithm. 
IV-8 

Response: The EPA is aware that there has been considerable debate within the research 

community about the appropriate multiplier to use to best represent urban environments. 

In general, the EPA agrees with commenters that a multiplier of 1.4 is likely too low, and 

that a somewhat higher value would be appropriate. However, the EPA also believes that 

it would be inappropriate to use a multiplier as high as 1.8 to convert OC to OM in urban 

areas. As noted by commenters, the organic mass contribution to visibility impairment 

can be large, and generally OM is significantly larger in urban areas compared to 

surrounding rural areas. Because a large portion of the organic component of urban PM 

results from nearby emissions sources, the total OM mass is generally closer to the 

measured OC from which it is derived. This means it is appropriate to use a smaller 

multiplier to convert OC to OM in urban areas as compared to the value of 1.8 used in the 

revised algorithm, which is tailored to remote areas. The CASAC noted that urban OM 

includes fresh emissions and the EPA concluded in the Visibility Assessment that “the 

original version is considered more representative of urban situations when emissions are 

still fresh rather than aged as at remote IMPROVE sites” (U.S. EPA, 2010b, p. 3-19). 

Although the revised algorithm represents the best science of estimating extinction in 

remote areas with its aged aerosol, the commenters did not address how the EPA should 

modify the revised algorithm to best represent the more complex and different urban 

aerosol, particularly for OM. 

As discussed in Appendix F of the Policy Assessment (U.S. EPA, 2011a), the EPA used 

the SANDWICH mass closure approach (Frank, 2006) in the Urban Focused Visibility 

Assessment (U.S. EPA, 2010b) for purposes of calculating maximum daylight hourly 

PM2.5 light extinction and evaluated which multiplier would produce 24-hour results most 

similar to the SANDWICH approach using 24-hour PM2.5 organic carbon derived from 

the new Chemical Speciation Network (CSN) carbon monitoring protocol established in 

2007. Analyses presented in Appendix F of the Policy Assessment indicate that a 

multiplier of 1.6 is most appropriate for purposes of comparing the hourly PM2.5 light 

extinction with calculated 24-hour extinction (see Appendix F, section F.6 for a full 

explanation). The EPA also considers this higher multiplier to be a better approach for 

urban CSN monitoring sites where the new measurements of organic carbon tend to be 

lower than those produced by the older NIOSH-type monitoring protocol (Malm, 2011). 

A multiplier of 1.6 is now used to calculate OM from OC measurements at CSN sites. 

In light of all of these considerations, in particular the analyses the EPA conducted for 

Appendix F of the Policy Assessment and the fact that the monitoring method for organic 

carbon has recently changed in the CSN network, the EPA judges that a multiplier of 1.6 

for urban areas would be most appropriate for purposes of calculating PM2.5 light 

extinction in urban areas. The implications of this shift to a 1.6 multiplier for OC in urban 

areas for decisions about averaging time, level, and need for a distinct secondary standard 

are discussed in the preamble to the final rule in sections VI.C.1.c, VI.C.1.e, and VI.C.1.f, 

respectively. 

(5) Comment: A number of commenters argued that exclusion of coarse PM from the 

calculated light extinction indicator was inappropriate. These commenters noted that 

coarse particulate matter is an important contributor to visibility impairment in many 

areas, particularly in the western U.S., and that the levels of “acceptable” visual air 
IV-9 

quality derived from the visibility preference studies reflected total light extinction due to 

the full mix of particles (including coarse PM) in ambient air. 

Response: The EPA does not agree with commenters who suggested that coarse particles 

should be included in the calculated light extinction indicator. As noted in the proposal, 

PM2.5 is the component of PM responsible for most of the visibility impairment in most 

urban areas. Currently available data suggest that PM10-2.5 is a minor contributor to 

visibility impairment most of the time, although at some locations (U.S. EPA, 2010b, 

Figure 3-13 for Phoenix) PM10-2.5 can be a major contributor to urban visibility effects. 

While it is reasonable to assume that other urban areas in the desert southwestern region 

of the country may have conditions similar to the conditions shown for Phoenix, in fact 

few urban areas conduct continuous PM10-2.5 monitoring. This significantly increases the 

difficulty of assessing the role of coarse particles in urban visibility impairment. For 

example, among the 15 urban areas assessed in this review, only four areas had 

collocated continuous PM10 data allowing calculation of hourly PM10-2.5 data for 2005 to 

2007. In addition, PM10-2.5 is generally less homogenous in urban areas than PM2.5 in that 

coarse particle concentrations exhibit greater temporal variability and a steeper gradient 

across urban areas than fine particles (U.S. EPA, 2009a, p. 3-72). This makes it more 

challenging to select sites that would adequately represent urban visibility conditions. 

Thus, while it would be possible to include a PM10-2.5 light extinction term in a calculated 

light extinction indicator, as was done in the Visibility Assessment, there is insufficient 

information available at this time to assess the impact and effectiveness of such a 

refinement in providing public welfare protection in areas across the country (U.S. EPA, 

2011a, pp. 4-41 to 4-42). 

In addition, the EPA notes CASAC’s advice that it would be appropriate to focus on 

PM2.5 light extinction for purposes of setting a standard to protect visibility. In its 

comments on the EPA’s White Paper on Particulate Matter (PM) Light Extinction 

Measurements (U.S. EPA, 2010g), the Ambient Air Monitoring and Methods 

Subcommittee (AAMMS) of CASAC made the recommendation that consideration of 

direct measurement should be limited to PM2.5 light extinction as this can be 

accomplished by a number of commercially available instruments and because PM2.5 is 

generally responsible for most of the PM visibility impairment in urban areas. The 

CASAC AAMMS indicated that it is technically more challenging at this time to 

accurately measure the PM10-2.5 component of light extinction (Russell and Samet, 

2010a). 

In light of the limited role of PM10-2.5 in light extinction in most urban areas, and the 

greater uncertainty and variability involved in the role of coarse particle in visibility 

impairment, the EPA has concluded that it is not appropriate to set a standard based on a 

calculated light extinction indicator that includes coarse particles at this time, and that it 

would be appropriate to base a calculated indicator on PM2.5 light extinction. 

(6) Comment: Some commenters objecting to the exclusion of coarse particles from the 

proposed light extinction indicator argued that the EPA had not provided “compelling 

reasons” for not including coarse particles. For example, North Carolina DENR stated 

while the coarse particle fraction might contribute only a small amount toward visibility 
IV-10 

impairment, it should still be included because “nothing presented in the proposed rule 

would support not including the coarse particle fraction. Where coarse particle data are 

not available, the EPA should develop a method to estimate the coarse particle fraction 

for use in the equation” (p. 4). However, other commenters, agreed with the EPA’s 

proposal to exclude coarse particles from the calculated light extinction indicator. 

Response: As noted above, in light of the limited role of PM10-2.5 in light extinction in 

most urban areas, and the greater uncertainty and variability involved in the role of coarse 

particle in visibility impairment, the EPA continues to conclude that it is not appropriate 

to set a standard based on a calculated light extinction indicator that includes coarse 

particles at this time, and the calculated indicator should be based on PM2.5 light 

extinction. The EPA notes that this conclusion was supported by the advice of CASAC. 

(7) Comment: A few commenters noted that due to the exclusion of coarse particles, a 

“deciview” calculated for purposes of the proposed PM2.5 visibility index is inconsistent 

with the unit as conventionally defined under the Regional Haze Program. 

Response: A deciview is a unit of measure of visibility derived from calculated light 

extinction measurements. A one dv change is approximately a 10% change in the aerosol 

based extinction. As used by EPA in the PM2.5 visibility index, however, a one dv change 

is approximately a 10% change in the PM2.5 aerosol based extinction coefficient. 

Typically, coarse particles contribute a very small amount of the total light extinction and 

resulting deciviews. For example, when the PM2.5 aerosol components result in 30 dv of 

light extinction, even an additional 10 μg/m3

 (the median value for the U.S., see Schmidt 

et al., 2010b) of coarse particles would only increase the visibility index by 0.2 dv. Thus, 

the EPA concludes that the exclusion of coarse particles does not have a substantial 

impact on visibility index values in urban areas and that it is appropriate to exclude 

coarse particles from the indicator for the reasons discussed above. 

(8) Comment: Some commenters questioned why the EPA was proposing to rely on monthly 

average relative humidity [f(RH)] values when hourly humidity data are widely available, 

particularly in urban areas. One commenter argued that the EPA’s proposed approach 

involves “guessing relative humidity” rather than relying on accurate, readily available 

measurements (Oklahoma DEQ, p. 1). The commenter stated that since relative humidity 

is highly variable and weather dependent, the proposed approach “effectively undermines 

the capacity of the prescribed monitoring regime to identify periods when PM2.5

adversely affects visibility.” Other commenters supported this view, noting that relative 

humidity can vary substantially even within a 24-hour period, and that light extinction 

can be very sensitive to these changes. These commenters recommended that hourly or 

daily humidity measurements should be utilized in place of the proposed monthly average 

f(RH) values. 

Response: The EPA disagrees that concurrent (hourly) humidity measurements should be 

used. The use of longer-term averages for each monitoring site adequately captures the 

seasonal variability of relative humidity and its effects of visibility impairment, and this 

approach focuses more on the underlying aerosol contributions to visibility impairment 

and less on the day-to-day variations in humidity. This provides a more stable indicator 
IV-11 

for comparison to the NAAQS and one that is more directly related to the underlying 

emissions that contribute to visibility impairment. Moreover, the EPA disagrees with 

commenters that using monthly average relative humidity undermines the proposed 

monitoring regime, noting that the Agency’s conclusion that a 24-hour averaging time 

would be appropriate for a visibility index standard diminishes the importance of having 

hourly humidity data. Longer-term average humidity data are better matched to 24-hour 

averaging times, which effectively smooth out the influence of peak hourly values 

regardless of whether hourly data are available. Therefore, the EPA continues to believe 

that it is appropriate to use f(RH) values for purposes of calculating a 24-hour PM2.5

visibility index. Moreover, the EPA disagrees that this approach involves “guessing 

relative humidity” since the f(RH) values are based on 10 years of climatological data for 

each location. 

(9) Comment: Some commenters recommended that the EPA should utilize a 90 percent 

relative humidity screen rather than 95 percent cap for purposes of eliminating periods in 

which visibility impairment is due to rain or fog. These commenters claimed that under a 

95 percent cap, both the average f(RH) values and the PM2.5 visibility index values could 

be inflated in locations frequently affected by fog and/or precipitation. These commenters 

preferred the approach of excluding hours with relative humidity above 90 percent on the 

grounds that this approach would eliminate foggy/rainy hours irrespective of the 

frequency of occurrence. 

Response: The EPA believes that relying on monthly average relative humidity values 

based on 10 years of climatological data would appropriately reduce the effect of fog and 

precipitation. Although the approach of using a 95 percent humidity cap, as in the 

Regional Haze Program, includes some hours with relative humidity between 90-95 

percent, the general approach of using a longer-term average for each monitoring site 

effectively eliminates the effect of very high humidity conditions on visibility at those 

locations. In essence, the adoption of monthly average f(RH) values mitigates (i.e., 

smoothes out) the peak humidity values, and capping remaining hours at 95 percent 

relative humidity further reduces the influence of fog or precipitation events (even if 

those conditions occur frequently). Therefore, the EPA disagrees with commenters that it 

would be more appropriate to use a 90 percent relative humidity screen. 

(10) Comment: One commenter stated that utilizing only one sampling point for purposes of 

calculating the light extinction indicator would not be appropriate because it would not 

represent visibility across the airshed. The commenter stated that the unit of deciviews as 

used in the Regional Haze Program was “primarily developed for areas with a long site 

path to encompass a large sample size” (Clark County, Nevada, Department of Air 

Quality, p. 2). The commenter urged the EPA to consider requiring the use of additional 

sampling points for purposes of calculating light extinction in urban areas. 

Response: EPA agrees that PM2.5 is more spatially homogeneous in remote areas than in 

urban areas. For this reason, the visibility impairment estimated from aerosol 

concentrations at individual urban locations may not be representative of a nearby long 

urban site path. Thus urban visibility measured at the maximum concentration location in 

an urban area, especially at locations with a small scale of spatial representativeness for 
IV-12 

one or more PM chemical components could provide even more protection against 

visibility impairment than the location which is more typical of urban-wide PM2.5

concentrations. 

(11) Comment: A number of commenters criticized other specific aspects of the proposed 

visibility index, especially with regard to the inclusion, exclusion, or construction of 

specific terms in the IMPROVE equation. In many instances, these commenters argued 

that the proposed indicator was inappropriate for specific local environments due to 

unique or atypical conditions influencing aerosol composition or relative humidity. These 

commenters generally stated that it was inappropriate to adopt a single indicator for 

application nationwide, or that some change in the indicator was necessary to 

accommodate local conditions. Some commenters offered specific recommendations 

about ways to improve the proposed calculated PM2.5 light extinction indicator to account 

for specific, local influences or to accommodate other perceived weaknesses of the 

proposed indicator, such as those discussed above. Other commenters urged the EPA to 

conduct more research on the factors influencing light extinction in specific 

environments, and to consider developing a revised indicator in conjunction with a pilot 

monitoring program. Some of these commenters stated that the proposed standard was 

simply too complicated, and failed to capture the full suite of necessary components. 

Response: The EPA disagrees with these commenters, noting that the proposed calculated 

light extinction indicator is expressly designed to account for differences in humidity and 

PM2.5 composition among various regions. Furthermore, the EPA notes that both the 

original and revised IMPROVE algorithms are routinely used to calculate PM-related 

light extinction on a 24-hour basis in Federal Class I areas under the Regional Haze 

Program, despite variability in aerosol composition and humidity among these locations. 

Therefore, the EPA continues to conclude that a similar approach is appropriate for a 

standard to protect against PM2.5-related visibility impairment. However, as discussed in 

section VI.C.1.e of the preamble to the final rule and section IV.B.4, below, regarding 

comments on level, the EPA agrees with commenters who emphasize the high degree of 

variability in visibility conditions and the potential variability in visibility preferences 

across different parts of the country. In light of the associated uncertainty, the 

Administrator has judged it appropriate to establish a target level of protection at the 

upper end of the range of levels considered (30 dv), recognizing that no one level will be 

"correct" for every area in the country. The EPA considers that a standard set at this level 

appropriately accommodates the variability among local environments and the resulting 

uncertainty that concerns these commenters. In addition, the EPA notes that in light of the 

Agency’s decision not to establish a distinct secondary standard for protection from 

visibility impairment at this time, these concerns are generally moot at this time. 

2. Averaging Time 

a. Comments Supporting 24-Hour Averaging Time 

(1) Comment: Among commenters supporting the proposed distinct secondary standard for 

protection from visibility impairment, many commenters recognized the limitations on 

monitoring methods and currently available data that led to the EPA’s proposal to adopt a 
IV-13 

standard based on a 24-hour averaging time. Most of these commenters acknowledged 

that the lack of reliable hourly speciation data means that a 24-hour averaging time is the 

only workable approach for a standard based on calculated light extinction. Commenters 

advocating a distinct secondary standard therefore generally supported the proposal to 

adopt a 24-hour averaging time, at least as an interim approach until a directly measured 

light extinction indicator could be adopted in the future.

Response: As discussed in section VI.C.1.c of the preamble, the EPA agrees with these 

commenters that a 24-hour averaging time would be the most appropriate for purposes of 

a distinct secondary standard based on a calculated light extinction indicator. 

(2) Comment: A few industry commenters argued that since a visibility index standard would 

be based on data from the IMPROVE and CSN monitors, which operate on a 24-hour 

basis with 1-in-3 (or 1-in-6) day sampling, “it is imperative that EPA retain a 24-hour 

averaging time if a secondary visibility standard is promulgated” (API, Attachment 3, p. 

9). 

Response: As discussed in section VI.C.1.c of the preamble, the EPA agrees with these 

commenters that a 24-hour averaging time would be the most appropriate for purposes of 

a standard based on a calculated light extinction indicator. 

(3) Comment: A number of commenters supported a 24-hour averaging time due to the 

limitations that would be associated with using a shorter (sub-daily) averaging time. For 

example, New York DOH/DEC agreed with the EPA that it would not be appropriate to 

utilize the PM2.5 FEM monitors for purposes of calculating a short-term light extinction 

value at this time. Arizona DEQ stated that it “does not support a sub-daily visibility 

standard with the proposed monitoring method. This approach would necessarily rely on 

temporal distribution estimates derived from nearby or on-site hourly PM measurements 

and extrapolation of 24-hour composite speciated samples. ADEQ believes this method 

would prove to be overly complex with seasonal variation of species and too inconsistent 

to utilize for a NAAQS secondary standard” (Arizona DEQ, p. 3; see also Minnesota, 

NY). 

Response: As discussed in section VI.C.1.c of the preamble, the EPA agrees with these 

commenters that a 24-hour averaging time would be the most appropriate for purposes of 

a standard based on a calculated light extinction indicator. 

b. Comments Supporting Sub-daily (1-, 4-, or 6-hour) Averaging Time 

(1) Comment: A number of commenters expressed the view that an hourly or sub-daily 

averaging time would be the most appropriate approach, as supported by CASAC and the 

EPA’s staff analyses in this review. These comments also generally stressed the 

desirability of adopting a directly measured light extinction indicator that could be 

measured on an hourly or sub-daily time scale. Some commenters noted that a standard 

based on a 4-6 hour averaging time would better capture peak daily light extinction while 

allowing stable signal quality; others urged the EPA to adopt a 1-hour averaging time in 

conjunction with direct measurements. 
IV-14 

Response: In response to comments supporting a 1-hour or sub-daily (4- to 6- hour) 

averaging time in conjunction with a direct light extinction measurements, the EPA notes 

that, as discussed above in the response to comments on indicator, the Agency has 

concluded that a directly measured light extinction indicator is not an appropriate option 

in this review, independent of the decision on averaging time. Having reached the 

conclusion that a calculated PM2.5 light extinction indicator would be most appropriate, 

the EPA next considered what averaging time would be most desirable for such an 

indicator. As noted in the proposal, the EPA has recognized that hourly or sub-daily (4- 

to 6-hour) averaging times, within daylight hours and excluding hours with high relative 

humidity, are more directly related than a 24-hour averaging time to the short-term nature 

of the perception of PM-related visibility impairment and the relevant exposure periods 

for segments of the viewing public. Thus, the Agency agrees with commenters’ general 

point that, as a starting premise, a sub-daily averaging time would generally be 

preferable. 

However, as discussed in section VI.B.1.c of the preamble to the final rule, important 

data quality uncertainties have recently been identified in association with currently 

available instruments that would be used to provide the hourly PM2.5 mass measurements 

that would be needed in conjunction with an averaging time shorter than 24 hours. As a 

result, at this time the Agency has strong technical reservations about a secondary 

standard that would be defined in terms of a sub-daily averaging time. The data quality 

issues which have been identified, including short-term variability in hourly data from 

currently available continuous monitoring methods, effectively preclude adoption of a 1-

hour averaging time in this review, given the sensitivity of a 1-hour averaging time to 

these data quality limitations. Even with regard to multi-hour averaging times, the EPA 

continues to conclude that the data quality concerns preclude adoption of a sub-daily 

averaging time. 

(2) Comment: Commenters pointed to significant limitations associated with using a 24-hour 

averaging time, including the uncertainties in translating hourly or sub-daily visibility 

index values into 24-hour equivalent values. Some commenters criticized the analysis 

presented in the Policy Assessment comparing the 24-hour calculated light extinction 

values to the maximum daylight 4-hour calculated light extinction values. These 

commenters stated that the scatter plots and regressions presented in the Policy 

Assessment indicate there is considerable variation in the 24-hour vs. 4-hour relationship, 

and interpreted this to mean that 24-hour light extinction values are a poor surrogate for 

4-hour values. For example, one consultant cited by several industry commenters noted 

that the correlation coefficient between the 24-hour and 4-hour values was as low as r2

 = 

0.42 in Houston, and stated that the EPA was being overly “optimistic” in concluding that 

city-specific and pooled r2

 values in the range of 0.6 to 0.8 showed good correlation 

(UARG, Attachment 2, p. 27). 

Response: Analyses conducted for the Policy Assessment indicate that PM2.5 light 

extinction calculated on a 24-hour average basis would be a reasonable and appropriate 

surrogate for PM2.5 light extinction calculated on a 4-hour basis. The scatter plots 

comparing 24-hour and 4-hour calculated PM2.5 light extinction in the Policy Assessment 

(U.S. EPA, 2011a, Figures G-4 and G-5) do show some scatter around the regression line 
IV-15 

for each city. This was to be expected, since the calculated 4-hour light extinction 

includes day-specific and hour-specific influences that are not captured by the simpler 

24-hour approach. Overall, however, in the EPA’s view, both the city-specific and pooled 

15-city 24-hour vs. 4-hour comparisons show strong correlation between the two 

averaging times. Moreover, the 90th percentile design values calculated for 4-hour vs. 

24-hour light extinction are much more closely correlated than are the values for 

individual days in particular urban areas calculated using these two approaches. Thus, 

while the EPA agrees with commenters who pointed out the relatively low correlation 

between 4- and 24-hour values in cities such as Houston, the Agency points out that the 

correlations of 90th percentile values are much higher, particularly when one considers 

the average values across urban areas. In general, the 90th percentile values line up better 

and demonstrate closer to a one-to-one relationship. 

The EPA has conducted a reanalysis (Frank et al., 2012b) of the relationships between 

estimated 24-hour and 4-hour visibility impairment based on the variety of metrics 

discussed in Appendix G of the Policy Assessment that further supports this finding. The 

reanalysis more appropriately considered the uncertainty of the calculated 4-hour values. 

It also considered the effect of changing the OC to OM multiplier used in urban areas 

from 1.4 to 1.6. The revised analysis shows that the 24-hour values are generally closer to 

the 4-hour values than originally estimated, particularly with regard to the 90th percentile 

values or the average of the 15 city-specific values. 

Since conclusions in the proposal about the relationship between 4-hour and 24-hour 

values were drawn not just on the basis of the city specific results but also on the more 

robust 90th percentile values, the EPA disagrees with commenters who state that the 

Agency was overly optimistic in considering 24-hour values an appropriate surrogate for 

4-hour values. Also, it is appropriate to focus on the 90th percentile design value 

comparison since the design values would determine attainment status and the degree of 

improvement in air quality that could be expected in areas instituting controls to meet the 

standard. Therefore, the EPA does not agree with commenters who state that a 24-hour 

averaging time cannot serve as an appropriate surrogate for sub-daily periods of visibility 

impairment. On the contrary, the EPA continues to conclude, on the basis of this analysis, 

that PM2.5 light extinction calculated on a 24-hour basis is a reasonable and appropriate 

surrogate for sub-daily PM2.5 light extinction calculated on a 4-hour basis. 

(3) Comment: Some commenters emphasized the poor fit of a 24-hour averaging time with 

the near instantaneous judgments about visibility impairment reflected in the visibility 

preference studies. Some of these commenters objected to a 24-hour averaging time as 

unsupported by the record in this review: “Because the science the Administrator relies 

on for the other elements of the proposed visibility standard is tied to short-term 

exposures to visibility impairment, the EPA has no basis for promulgating a standard that 

uses a 24-hour averaging time” (API, p. 43). These commenters claimed that while the 

EPA may not have the information or infrastructure in place to allow the Agency to set a 

standard based on a 1-hour or other sub-daily averaging time, this does not justify 

moving to a 24-hour averaging time. 

Response: The EPA has recognized that hourly or sub-daily (4- to 6-hour) averaging 
IV-16 

times, within daylight hours and excluding hours with high relative humidity, are more 

directly related than a 24-hour averaging time to the short-term nature of the perception 

of PM-related visibility impairment and the relevant exposure periods for segments of the 

viewing public. However, as discussed in section VI.B.1.c of the preamble to the final 

rule, important data quality uncertainties have recently been identified in association with 

currently available instruments that would be used to provide the hourly PM2.5 mass 

measurements that would be needed in conjunction with an averaging time shorter than 

24 hours. As a result, the EPA determined it would not be appropriate at this time to 

adopt a standard defined in terms of a sub-daily averaging time. 

Instead, the EPA considered using PM2.5 light extinction calculated on a 24-hour basis to 

reduce the various data quality concerns on relying on continuous PM2.5 monitoring data. 

However, the Policy Assessment recognized that 24 hours is far longer than the hourly or 

multi-hour time periods that might reasonably characterize the visibility effects 

experienced by various segments of the population, including both those who do and do 

not have access to visibility conditions often or continuously throughout the day. Thus, 

the EPA stated in section VI.D.2.ii of the proposal that consideration of a 24-hour 

averaging time would depend upon the extent to which PM-related light extinction 

calculated on a 24-hour average basis would be a reasonable and appropriate surrogate

for PM-related light extinction calculated on a sub-daily basis. Analyses conducted for 

the Policy Assessment did indicate that PM2.5 light extinction calculated on a 24-hour 

average basis would be a reasonable and appropriate surrogate for PM2.5 light extinction 

calculated on a 4-hour basis, supporting the EPA’s decision to consider this longer 

averaging time appropriate. 

(4) Comment: Some commenters expressed concern over potential bias and greater 

uncertainty introduced by the inclusion of nighttime hours, noting that because relative 

humidity tends to be higher at night, inclusion of these hours could cause areas to “record 

NAAQS exceedances that have no corresponding visibility impairment value” (UARG, p. 

36). 

Response: The Policy Assessment recognized that since a 24-hour averaging time 

combines daytime and nighttime periods, the public preference studies do not directly 

provide a basis for identifying an appropriate level of protection, in terms of 24-hour 

average light extinction, based on judgments of acceptable daytime visual air quality 

obtained in those studies. The EPA’s consideration of a 24-hour averaging time therefore 

also depended upon developing an approach to translate the candidate levels of protection 

derived from the public preference studies, which the Policy Assessment interpreted on 

an hourly or multi-hourly basis, to a candidate level of protection defined in terms of a 

24-hour average calculated light extinction. The EPA’s analyses comparing 24-hour and 

4-hour averaging times showed good correlation between 24-hour and 4-hour average 

PM2.5 light extinction, as discussed further in section IV.2.e regarding comments on level, 

below, and in section VI.C.1.e of the preamble. This supported the Agency’s conclusion 

that PM2.5 light extinction calculated on a 24-hour average basis would be a reasonable 

and appropriate surrogate for PM2.5 light extinction calculated on a 4-hour basis. 

(5) Comment: Commenters also noted that there is greater hourly variation in PM 
IV-17 

concentrations and resulting visibility conditions in urban areas than in Class I areas; 

thus, while the Regional Haze Program uses 24-hour IMPROVE data, the commenters 

stated that a shorter averaging time is needed for an urban-focused PM2.5 standard to 

protect visibility. 

Response: As discussed in section VI.B.1.c of the preamble to the final rule, the EPA has 

recognized that hourly or sub-daily (4- to 6-hour) averaging times, within daylight hours 

and excluding hours with high relative humidity, are more directly related than a 24-hour 

averaging time to the short-term nature of the perception of PM-related visibility 

impairment and the relevant exposure periods for segments of the viewing public. 

However, analyses of air quality in 15 urban areas conducted for the Policy Assessment 

indicated that PM2.5 light extinction calculated on a 24-hour average basis would be a 

reasonable and appropriate surrogate for PM2.5 light extinction calculated on a 4-hour 

basis. Thus, the EPA concludes that a 24-hour averaging time would be appropriate for a 

standard based on a calculated light extinction indicator. 

(6) Comment: Some commenters expressed concern with the proposal to calculate the 

visibility index over 24-hours, noting that this would introduce additional uncertainty in 

the light extinction calculations: “The NCDAQ understands the Administrator's dilemma 

with the uncertainty that can be introduced using instrumentation that people do not have 

confidence in, namely some of the recently approved Federal Equivalent Methods 

(FEMs). At the same time the NCDAQ currently uses continuous monitors that are not 

Federal Reference Methods (FRMs) or FEMs to comply with meeting air quality 

reporting requirements. The data from these monitors are adjusted seasonally using an 

equation derived at each specific location so that they match the FRM data. Is the 

uncertainty that would occur using continuous particle monitors adjusted to match the 

FRM really greater than the uncertainty that occurs from using 24 hour speciation data?” 

(NC DENR, p. 4-5). 

Response: PM2.5 FEMs are designed and tested by manufacturers and approved by EPA 

according to their ability to reproduce 24-hr mass based PM2.5 concentrations as 

measured by the PM2.5 FRM. When these continuous measurements are used as part of 

the air quality index to publicly report PM2.5 concentrations, they are adjusted by State 

and local air pollution agencies to better predict 24-hour values. Such adjustments are 

sometimes performed on a seasonal basis. However, the PM2.5 FEM is not necessarily 

designed nor is it tested to produce precise 1-hr values. In fact, some of the potential 

uncertainty in 1-hour values is removed through the process of averaging multiple hours. 

Moreover, the composition of PM2.5 can change from hour to hour and the estimated 

extinction depends on the change in composition as well as the change in hourly PM2.5

mass concentration. However, hourly speciation and optical measurements which 

separately estimate the extinction contributions from scattering and absorbing PM2.5 

aerosols are not widely deployed in urban monitoring networks. Therefore, as part of the 

urban visibility assessment, EPA estimated the change in composition using modeling 

data to help estimate the change in extinction resulting from the different scattering and 

absorbing components of PM2.5 . For those complex calculations, the EPA also assumed 

that the composition did not change from day to day. Although precise measurements of 

hourly PM2.5 would be helpful, EPA does not believe that they are available. Also, use of 
IV-18 

existing hourly PM2.5 measurements in combination with all of the other stated factors 

introduced significant uncertainty into this analysis in the urban visibility assessment. For 

these reasons, EPA has more confidence in the visibility impairment derived from 24-hr 

speciation measurements than from the 1-hr PM2.5 mass concentrations produced by 

PM2.5 FEMs combined with assumed hour to hour changes in PM2.5 composition. 

3. Form 

a. Comments on 90th Percentile 

(1) Comment: One commenter stated that it was inappropriate to use a 90th percentile form, 

noting that this would result in the exclusion of a minimum of 36 days of data annually. 

The commenter expressed particular concern that this proposed approach, in combination 

with a 24-hour standard based on an unadjusted CPL, would not capture the worst 

visibility impairment and that this would undermine “the intent of setting a meaningful 

secondary visibility standard” (AMC, et al., p. 2). 

Response: The EPA disagrees that a 90th percentile form would exclude too many days to 

offer meaningful protection against visibility impairment. The EPA notes that there is a 

significant lack of information on, and a high degree of uncertainty regarding, the impact 

on public welfare of the number of days with visibility impairment over the course of a 

year. For example, the visibility preference studies used to derive the range of CPLs 

considered in this review offered no information regarding the frequency of time that 

visibility levels should be below those values. Based on this limitation, the EPA 

concluded in the Policy Assessment that it would not be appropriate to consider 

eliminating all exposures above the level of the standard and that it was reasonable to 

consider allowing some number of days with reduced visibility. Recognizing that the 

Regional Haze Program focuses attention on the 20 percent worst visibility days (i.e., 

those at or above the 80th percentile of visibility impairment), the EPA continues to 

believe, as noted in the proposal, that a percentile well above the 80th percentile would 

be appropriate to increase the likelihood that all days in this range would be improved by 

control strategies intended to help areas attain the standard. Focusing on the 90th 

percentile, which represents the median of the distribution of the 20 percent worst 

visibility days, could be reasonably expected to lead to improvements in visual air quality 

on the 20 percent most impaired days. Thus, the EPA has made a reasoned judgment 

based on a full consideration of the upper end of the distribution of visibility impairment 

conditions, in light of the significant uncertainty discussed above and continues to 

conclude that it is appropriate to focus on the 90th percentile of visibility impairment 

values. 

(2) Comment: Another commenter argued that the EPA had provided no scientific basis for 

why the 90th percentile form was suitable, and claimed that the Agency was making “a 

somewhat arbitrary judgment that people’s welfare would be affected only if adverse 

urban visibility were to occur more than 10 percent of the time” (API, Attachment 2, p. 

4). 
IV-19 

Response: EPA notes that there is a significant lack of information on, and a high degree 

of uncertainty regarding, the impact on public welfare of the number of days with 

visibility impairment over the course of a year. For example, the visibility preference 

studies used to derive the range of CPLs considered in this review offered no information 

regarding the frequency of time that visibility levels should be below those values. Based 

on this limitation, the EPA concluded in the Policy Assessment that it would not be 

appropriate to consider eliminating all exposures above the level of the standard and that 

it was reasonable to consider allowing some number of days with reduced visibility. 

Recognizing that the Regional Haze Program focuses attention on the 20 percent worst 

visibility days (i.e., those at or above the 80th percentile of visibility impairment), the 

EPA continues to believe, as noted in the proposal, that a percentile well above the 80th 

percentile would be appropriate to increase the likelihood that all days in this range 

would be improved by control strategies intended to help areas attain the standard. 

Focusing on the 90th percentile, which represents the median of the distribution of the 20 

percent worst visibility days, could be reasonably expected to lead to improvements in 

visual air quality on the 20 percent most impaired days. Thus, the EPA did not arbitrarily 

pick the 90th percentile, but has made a reasoned judgment based on a full consideration 

of the upper end of the distribution of visibility impairment conditions, in light of the 

significant uncertainty as discussed above, and continues to conclude that it is appropriate 

to focus on the 90th percentile of visibility impairment values. 

b. Comments on 3-year Average 

(1) Comment: A few commenters argued that averaging over only 3 years would not provide 

a stable assessment of visual air quality in the West because this time period is 

insufficient to properly account for western drought and fire cycles. These commenters 

pointed to the approach in the Regional Haze Program of averaging visibility impairment 

over 5 years, and noted that even within this longer time period data can be significantly 

influenced by high emissions during significant fire years. 

Response: The EPA disagrees that it would be appropriate to average the 90th percentile 

values over periods longer than 3 years. The EPA recognizes that a multi-year percentile 

form offers greater stability to the air quality management process by reducing the 

possibility that statistically unusual indicator values will lead to transient violations of the 

standard. Utilizing a 3-year average form provides stability from the occasional effects of 

inter-annual meteorological variability that can result in unusually high pollution levels 

for a particular year. The Agency has adopted this approach in other NAAQS, including 

the current 24-hour PM2.5 NAAQS, which has a 98th percentile form averaged over 3 

years. However, adopting a multi-year averaging period longer than 3 years would 

increase even more the number of days with visibility impairment above the target level 

of protection and would therefore reduce the protectiveness of the standard. Based on this 

the EPA does not believe it would be appropriate to average 90th percentile values over a 

period as long as five years. 

4. Level 

The EPA received relatively few comments endorsing a specific level for a distinct 
IV-20 

secondary standard to address visibility impairment. In general, commenters who opposed 

setting a distinct secondary standard at this time did not address the question of what level would 

be appropriate if the EPA were to set a distinct secondary standard to address visibility 

impairment; similarly, commenters who supported adopting a distinct secondary standard at this 

time generally did not recommend a specific level. However, a few commenters did provide 

comments in support of a specific level or range of levels, with some commenters advocating 

standards at the upper end of the range of proposed levels (i.e., 30 dv), while others supported 

levels below the lower end of the proposed range (i.e., below 28 dv). These comments reflected 

consideration of the results of the public preference studies as well as analyses conducted in the 

Visibility Assessment and the Policy Assessment. Comments addressing the appropriateness of 

specific levels are discussed in this section. In addition, the EPA received a large number of 

comments addressing the information available from the public preference studies with regard to 

the acceptability of various levels of visual air quality. These comments, which are discussed in 

section IV.5, below, address the EPA’s use of visibility preference studies as the basis for the 

selection of a range of appropriate levels for the Administrator to consider. 

a. Comments Supporting a Level of 30 dv or higher 

(1) Comment: Several industry commenters submitted an analysis which they argued 

indicated that the proposed level of 28 or 30 dv did not reflect the substantial difference 

in visibility preferences between the East and the West reflected in the preference studies 

(UARG, Attachment 2, p. 11), and that it did not reflect the full range of preferences (i.e., 

potential 50 percent acceptability levels) likely to exist nationwide (UARG, Attachment 

2, p. 19). These commenters further objected to the EPA’s proposal for a level of 28 or 30 

dv on the grounds that the EPA had inaccurately adjusted 4-hour values into 24-hour 

values. Based on the analysis, the commenters concluded that “a range of adjusted values 

from 28 to 32 dv is needed” to account for the majority of the spread between the 4-hour 

vs. 24-hour equivalent values at the upper end of the distribution of values. 

Response: While acknowledging the uncertainties and limitations associated with the 

visibility preference studies as discussed above, the EPA continues to conclude, as did 

CASAC, that the preference studies are appropriate to use as the basis for selecting a 

target level of protection from visibility impairment. However, the EPA agrees with 

commenters who emphasize the high degree of variability in visibility conditions and the 

potential variability in visibility preferences across different parts of the country. As 

discussed in the preamble, the information supports the view that variability in the results 

of the studies is likely based on variability in the content of the view at issue in the study, 

as compared to variability in people’s preferences. In addition, the EPA has concluded 

that in light of the significant uncertainties, it is appropriate to place less weight on the 

results of western visibility preference studies and that the CPL value (30 dv) that is 

based on the eastern preference study results is likely to be more representative of urban 

areas that do not have associated mountains or other valued objects visible in the distant 

background. In light of the associated uncertainty, as noted in the proposal, the 

Administrator judged it appropriate to establish a target level of protection equivalent to 

the upper end of the range of Candidate Protection Levels (CPLs) identified in the Policy 

Assessment and generally supported by CASAC. Thus, the EPA considered the issues 

raised by commenters, and the EPA proposed to set a 24-hour visibility index standard 
IV-21 

that would provide protection equivalent to the protection afforded by a 4-hour standard 

set at a level of 30 dv. In light of the comments received on the proposal, in particular 

comments emphasizing the uncertainty and variability in the results of the public 

preference studies, the EPA continues to conclude that this approach is warranted, and 

that it is appropriate to set a target level of protection equivalent to the protection that 

would be afforded by a 4-hour, 30 dv visibility index standard. 

In adjusting 4-hour values for purposes of defining an appropriate level for a 24-hour 

standard, the EPA noted that there were multiple approaches for estimating generally 

equivalent levels on a city-specific or national basis, and that both of the two preferred 

approaches identified in the Policy Assessment generated a range of city-specific 

estimates of generally equivalent 24-hour levels that encompassed the range of levels 

considered appropriate for 4-hour CPLs, including the CPL of 30 dv at the upper end of 

that range. This led to the conclusion that it would be appropriate to use an unadjusted 4-

hour CPL for purposes of establishing a target level of protection for a 24-hour standard. 

The EPA disagrees with commenters who argued that the EPA’s approach for translating 

4-hour CPLs into equivalent 24-hour values was inappropriate. The EPA has conducted a 

reanalysis (Frank et al., 2012b) of the relationships between estimated 24-hour and 4-

hour visibility impairment based on the variety of metrics discussed in Appendix G of the 

Policy Assessment. The reanalysis has more appropriately considered the uncertainty of 

the calculated 4-hour values. The revised analysis shows that, for all cases considered, the 

24-hour equivalent level is even closer to the 4-hour values than originally estimated, 

demonstrating that the EPA’s approach to translating of 4-hour CPLs into equivalent 24-

hour values was appropriate. 

(2) Comment: A number of commenters questioned whether the proposed range of levels 

was appropriate. One industry commenter claimed that the EPA had not explicitly 

justified why a standard within the proposed range was requisite, stating that “EPA 

makes no attempt to explain how the proposed level of the standard is neither lower nor 

higher than necessary to protect public welfare” (NSSGA, p. 15). Noting perceived 

problems with the proposed range of levels, a few commenters noted that if the EPA were 

to set a distinct secondary standard, the level should be set no lower than 30 dv, “to 

account for inconsistent value judgments, a great deal of spatial and temporal variability, 

and a very high level of uncertainty” (TX CEQ, p. 7). 

Response: While acknowledging the uncertainties and limitations associated with the 

visibility preference studies as discussed above, the EPA continues to conclude, as did 

CASAC, that the preference studies are appropriate to use as the basis for selecting a 

target level of protection from visibility impairment. After considering the alternative 

levels proposed for a 24-hour standard, either 28 dv or 30 dv, the EPA has concluded that 

the current substantial degrees of variability and uncertainty inherent in the public 

preference studies should be reflected in a higher target protection level than would be 

appropriate if the underlying information were more consistent and certain. In addition, 

the EPA has concluded that in light of the significant uncertainties, it is appropriate to 

place less weight on the results of western visibility preference studies and that the CPL 

value (30 dv) that is based on the eastern preference study results is likely to be more 

representative of urban areas that do not have associated mountains or other valued 
IV-22 

objects visible in the distant background. In light of all the information available in this 

review, therefore, the Administrator has concluded that the protection provided by a 

standard defined in terms of a PM2.5 visibility index (based on speciated PM2.5 mass 

concentrations and relative humidity data to calculate PM2.5 light extinction), a 24-hour 

averaging time, and a 90th percentile form, averaged over 3 years, set at a level of 30 dv, 

would be requisite to protect public welfare with regard to visual air quality. 

(3) Comment: Many commenters also expressed concern over what they perceived to be the 

high degree of uncertainty associated with the proposed distinct secondary standard for 

visibility. For example, Nevada DEP stated “the EPA’s own analysis regarding the 

secondary visibility standard highlights several areas of high uncertainty, which preclude 

a reasonable conclusion that the proposed visibility rule is sufficient, but not overly so, to 

protect public welfare. Therefore, it is inappropriate to pursue a fatally flawed standard” 

(p. 9). 

Response: While acknowledging the uncertainties and limitations associated with the 

information available in this review, the EPA continues to conclude, as did CASAC, that 

this information provides a sufficient basis for selecting a target level of protection for 

visibility in this review. Thus the EPA disagrees with commenters who stated that the 

uncertainties were so great as to preclude establishing a standard at this time. Rather, the 

EPA has concluded that the current substantial degrees of variability and uncertainty 

should be reflected in a higher target protection level than would be appropriate if the 

underlying information were more consistent and certain. In considering the two 

alternative levels (28 or 30 dv) proposed for a distinct secondary standard to protect 

visibility, therefore, the EPA has elected to set a target level of protection at the higher of 

the two levels proposed (30 dv). 

(4) Comment: The states of Arizona and Colorado submitted comments arguing that the 

visibility preference studies conducted in Phoenix and Denver, respectively, were 

designed to address a specific local problem and that the results of these studies were not 

an appropriate basis for selecting the level of a national standard. For example, Arizona 

DEQ noted: 

The cited studies were conducted considering total light extinction; including 

extinction resulting from particulate matter and Rayleigh scattering. Visibility 

impairment due to coarse particulate matter can be an important contributor in 

Arizona, specifically in the Phoenix area where ongoing measurements have been 

made. Therefore, ADEQ believes that the proposed levels of the secondary 

visibility standard are inconsistent with applicable urban studies. (Arizona DEQ, 

p. 2) 

Similarly, the Colorado Department of Public Health and the Environment noted that the 

Denver visibility standard was designed to address “brown clouds”, i.e., strong inversions 

that occur in the Denver metropolitan area, and that this standard “is based on a specific 

view of Denver” associated with particular sight paths and direct measurement methods. 

The commenter stated that this standard “is applicable only to this location,” and that 

these limitations make it potentially unsuitable for application as “a national secondary 
IV-23 

standard, particularly a proposed standard that does not use a direct measurement 

method” (Colorado DPHE, p. 2). 

Response: In the preamble to the final rule, the EPA noted several reasons for caution in 

interpreting the results of the Denver and Phoenix preference studies. Noting both that the 

scenic vistas available on a daily basis in many urban areas across the country generally 

do not have the inherent visual interest or the distance between viewer and object of 

greatest intrinsic value as in the Denver and Phoenix preference studies, and the caution 

expressed by Colorado and Arizona about using the results of the Denver and Phoenix 

preference studies, which were aimed at addressing specific local visibility problems, to 

inform the choice of level for a national standard, the EPA concluded that it is 

appropriate, especially in light of the significant uncertainties, to place less weight on the 

western preference results. The EPA concluded that the high CPL value (30 dv) that is 

based on the eastern preference results is likely to be more representative of urban areas 

that do not have associated mountains or other valued objects visible in the distant 

background. These areas would include the middle of the country and many areas in the 

eastern U.S., as well as some western areas. In reaching this conclusion, the EPA 

recognized that no one level would be "correct" for every urban area in the country, and 

that the development of local programs, such as those in Denver and Phoenix, can 

continue to be an effective and appropriate approach to provide additional protection, 

beyond that afforded by a national standard, for unique scenic resources in and around 

certain urban areas that are particularly highly valued by people living in those areas. 

In regard to the commenter’s concern about contributions from coarse particles and 

Rayleigh scattering, the EPA further notes that participants in the Phoenix and other 

studies were not asked to break out their preferences based on how much of the haze was 

caused by contributions from coarse particles, Rayleigh scattering or fine particles. 

Instead, Phoenix study participants were simply asked to identify levels of visual air 

quality that they would consider “unreasonable or objectionable,” no matter what the 

source. Based on this information, Phoenix was able to come up with a target level of 

VAQ, even though pollutant mixes vary temporally and spatially, even within the 

Phoenix urban area. Since the goal of the secondary PM 2.5 NAAQS is to provide a 

uniform national level of public welfare protection from PM 2.5 related visibility 

impairment, the form of the EPA’s proposed secondary standard was selected to allow 

each area to achieve that level of protection in a way that addresses its own unique mix of 

contributing pollutants. Therefore, the EPA disagrees with the commenter that it is 

inappropriate to use the results of the Phoenix study to inform a range of candidate 

protection levels for consideration by the Administrator in selecting a national level of 

visibility protection. Instead, the EPA believe the Phoenix results form an important data 

point that shed light on public preferences for visibility in western areas with urban 

scenes that include distant mountains. 

b. Comments Supporting a Level below 30 dv 

(1) Comment: Some commenters stated that the proposed range of levels from 28-30 dv was 

insufficiently protective based on a 24-hour averaging time, and recommended a lower 

level for the visibility index standard. These commenters expressed the view that the 
IV-24 

proposed levels of 28 or 30 dv represented neither adequate surrogates for equivalent 4-

hour values, as the EPA claimed, nor sufficiently protective levels based on recent air 

quality data. Several commenters stated that the EPA’s own analyses suggested that a 

standard set at a level of 28 or 30 dv was insufficiently protective based on a 24-hour 

averaging time. One commenter emphasized that the Policy Assessment had indicated a 

level between 25-28 dv was appropriate for a standard calculated on a 24-hour average, 

and encouraged the EPA to adopt a standard level of 25 dv. 

Response: The EPA disagrees with commenters who argue that the currently available 

evidence is sufficient to justify establishing a target level of protection at 25 dv or below. 

The EPA recognizes that 25 dv represents the middle of the range of 50 percent 

acceptability levels from the 4 cities studied, and represents the 50 percent acceptability 

level from the Phoenix study, which the Agency has acknowledged as the best of the four 

studies in terms of having the least noise in the preference study results and the most 

representative selection of participants. The EPA also notes the caveats discussed in the 

proposal regarding whether it would be appropriate to interpret results from the western 

studies as generally representative of a broader range of scenic vistas in urban areas 

across the country. The Policy Assessment noted significant differences in the 

characteristics of the urban scenes used in each study, with western urban visibility 

preference study scenes including mountains in the background and objects at greater 

distances, while scenes in the eastern study did not. Since objects at a greater distance 

have a greater sensitivity to perceived visibility changes as light extinction changes 

compared to otherwise similar scenes with objects at a shorter range, this likely explains 

part of the difference between the results of the eastern study and results of the western 

studies. 

In the proposal, the EPA noted that the scenic vistas available on a daily basis in many 

urban areas across the country generally do not have the inherent visual interest or the 

distance between viewer and object of greatest intrinsic value as in the Denver and 

Phoenix preference studies. Also, the Agency takes note of the caution expressed by 

Colorado and Arizona about using the results of the Denver and Phoenix preference 

studies, which were aimed at addressing specific local visibility problems, to inform the 

choice of level for a national standard. Therefore, the Agency considers it reasonable to 

conclude, especially in light of the significant uncertainties, that it is appropriate to place 

less weight on the western preference results and that the high CPL value (30 dv) that is 

based on the eastern preference results is likely to be more representative of urban areas 

that do not have associated mountains or other valued objects visible in the distant 

background. These areas would include the middle of the country and many areas in the 

eastern U.S., as well as some western areas. As a result, the EPA concludes that it is more 

appropriate to establish a target level of protection at the upper end of the range of 24-

hour CPLs considered, recognizing that no one level will be "correct" for every urban 

area in the country. 

(2) Comment: Several environmental groups provided comments stating that a 24-hour 

average would underestimate a 4-hour value by 13-42 percent and certain areas of the 

country—particularly the Northeast—would be affected disproportionately. These 

commenters suggested that a 24-hour PM2.5 visibility index standard should be set at a 
IV-25 

level of 18.6-20 dv. 

Response: The EPA disagrees with these commenters that the EPA’s approach for 

translating 4-hour CPLs into equivalent 24-hour values was inappropriate. The EPA has 

conducted a reanalysis (Frank et al., 2012b) of the relationships between estimated 24-

hour and 4-hour visibility impairment based on the variety of metrics discussed in 

Appendix G of the Policy Assessment. The reanalysis has more appropriately considered 

the uncertainty of the calculated 24-hour and 4-hour values. The analysis in Appendix G 

of the Policy Assessment used the 4-hour light extinction value treated as the independent 

(x-axis) variable in an ordinary least squares regression. The EPA now concludes that this 

regression approach was not the most appropriate approach because that variable has 

error and in fact may be more uncertain than the calculated 24-hour extinction values. 

The Frank et al. (2012b) reanalysis uses an orthogonal regression instead of ordinary least 

squares regression and results in slopes closer to the 1:1 line for all the results, 

particularly for Dallas, TX. Furthermore, consistent with the EPA’s conclusion that a 

higher multiplier for converting OC to OM would be appropriate (see section VI.C.1.b.ii 

above), the reanalysis substitutes a 1.6 multiplier for converting OC to OM in the 

calculation of 24-hour values instead of the value of 1.4 that was used in calculating 24-

hour values for Appendix G. The higher multiplier is more consistent with the 

SANDWICH approach used to calculate the 4-hour values found in Appendix G. See 

Frank et al. (2012b) for a more detailed explanation. 

The revised analysis shows that the 24-hour equivalent level is generally closer to the 4-

hour value at the upper end of the range of CPLs than originally estimated, as can be seen 

in the results for Approaches B, C, and D presented in Frank et al., 2012b.38 For example, 

the reanalysis indicates that Approach B (annual 90th percentile design values regression) 

yields an adjusted 24-hour CPL of 29 dv as generally being equivalent to a 4-hour CPL of 

30 dv. In contrast, in Appendix G of the Policy Assessment, a 24-hour adjusted CPL of 

28 dv was estimated to be equivalent to a 4-hour value of 30 dv under Approach B. 

Similarly, Approach C (all-days city-specific regression) yields a 24-hour equivalent CPL 

of 29 dv averaged across cities and a range of city-specific values from 25-36 dv in the 

reanalysis, whereas in Appendix G of the Policy Assessment, under Approach C, a 24-

hour adjusted CPL of 27 dv was estimated to be equivalent to a 4-hour CPL of 30 dv 

when averaged across cities, and city-specific values were estimated to range from 24-30 

dv. In the reanalysis, Approach D (all days pooled regression) generated results of 28 dv 

for the 24-hour CPL equivalent to a 4-hour value of 30 dv as compared to a value of 27 

dv in the original analysis described in Appendix G. 

As can be seen in the tables presented in Frank et al. (2012b), not only are the 90th

percentile and pooled average values closer to the 4-hour CPL of 30 dv in the reanalysis, 

the range of city-specific results shows a wider spread that clearly encompasses the 

unadjusted 4-hour value of 30 dv near the midpoint of the city-specific range. This 

provides support for concluding that the EPA’s approach to translating of 4-hour CPLs 

into equivalent 24-hour values was appropriate, and that it is appropriate to use 

 

38 Approach E as presented in the Policy Assessment is based on the median values for each city; these results are 

not affected by the regression analyses. Therefore, Approach E was not included in the reanalysis, and the results 

remain unchanged from those reported in the corrected Table G-6 as reported in Frank, et al., 2012b. 
IV-26 

unadjusted 4-hour values for purposes of selecting a level for a standard based on a 24-

hour averaging time. 

(3) Comment: The Department of the Interior pointed to recent air quality data indicating that 

visibility on the 20% worst days in several large metropolitan areas, including 

Birmingham, Fresno, New York City, Phoenix, and Washington, DC was below 29 dv. 

While noting that these calculations were based on IMPROVE calculations which include 

contributions from coarse PM mass, DOI expressed the view that the proposed level of 

28 to 30 dv would not provide adequate visibility protection compared to the current 24-

hour PM2.5 standard of 35 μg/m3

 and recommended that the standard be set at a level of 

25 dv consistent with the results of the Phoenix visibility preference study. 

Response: The EPA notes that the purpose of establishing NAAQS is to ensure adequate 

protection of public welfare from a national perspective, not to mandate continuous 

improvements in areas that may already be relatively clean. In fact, the evidence from the 

IMPROVE program cited by commenters indicating that many urban areas have total 24-

hour PM-related light extinction below 29 dv on the 20 percent worst visibility days 

suggests that many areas have relatively good visual air quality already. Furthermore, the 

development of local programs, such as those in Denver and Phoenix, can continue to be 

an effective and appropriate approach to provide additional protection, beyond that 

afforded by a national standard, for unique scenic resources in and around certain urban 

areas that are particularly highly valued by people living in those areas.

(4) Comment: One group of commenters suggested that a 24-hour PM2.5 Visibility Index 

standard of 28-30 dv would be equivalent to higher 4-hour values than suggested by the 

EPA in Appendix G of the Policy Assessment, and that individual areas such as Dallas, 

TX would have equivalent 4-hour values as much as 9 dv higher . They asserted that 

further insight into the differences in protectiveness of an unadjusted 24-hour standard 

could be found by examining Table G-5 in Appendix G of the Policy Assessment, which 

indicates that only 1 of 15 cities would exceed a 24-hour, 3-year 90th percentile standard 

at 30 dv . but that 5 of the cities would exceed 30 dv if light extinction were based on 

daily maximum daylight light extinction measured over 4 hours. (AMC, et al.) 

Response: The EPA disagrees with these commenters that 24-hour light extinction in the 

range of 28-30 dv would be equivalent to 4-hour values as high as those presented by the 

commenters. The EPA has conducted a reanalysis (Frank et al., 2012b) of the 

relationships between estimated 24-hour and 4-hour visibility impairment based on the 

variety of metrics discussed in Appendix G of the Policy Assessment. The reanalysis has 

more appropriately considered the uncertainty of the calculated 24-hour and 4-hour 

values. The analysis in Appendix G of the Policy Assessment used the 4-hour light 

extinction value treated as the independent (x-axis) variable in an ordinary least squares 

regression. The EPA now concludes that this regression approach was not the most 

appropriate approach because that variable has error and in fact may be more uncertain 

than the calculated 24-hour extinction values. The Frank et al. (2012b) reanalysis uses an 

orthogonal regression instead of ordinary least squares regression and results in slopes 

closer to the 1:1 line for all the results, particularly for Dallas, TX. Furthermore, 

consistent with the EPA’s conclusion that a higher multiplier for converting OC to OM 
IV-27 

would be appropriate (see section VI.C.1.b.ii above), the reanalysis substitutes a 1.6 

multiplier for converting OC to OM in the calculation of 24-hour values instead of the 

value of 1.4 that was used in calculating 24-hour values for Appendix G. The higher 

multiplier is more consistent with the SANDWICH approach used to calculate the 4-hour 

values found in Appendix G. See Frank et al. (2012b) for a more detailed explanation. 

Table 4 of the revised analysis shows that at the upper end of the range of levels 

considered (i.e., 30 dv) the 24-hour equivalent level for each city is generally closer to the 

4-hour value of 30 dv. Moreover, the EPA notes that with OLS regression, the same 

regression equation (Y = b0 + b1X) should not be reversed—i.e. the same equation should 

not be used to estimate X from Y (Frank et al. 2012b). Thus the predicted 4-hour values 

constructed by the commenters are flawed because they used the regression equations 

presented by EPA in Appendix G of the Policy Assessment. 

(5) Comment: One group of commenters suggested that, on the basis of estimated 4-hour 

average visibility data presented by EPA in Appendix H of the Policy Assessment, 

shifting to a 24-hour averaging time for a standard set a level of 28 dv would 

substantially reduce the protectiveness of the standard. The commenters claimed that this 

reduction in protection would particularly affect the Northeast, where 50% fewer counties 

would exceed a design value of 28 deciviews based on a 24-hour average as compared to 

a 4 hour daily maximum approach. According to the commenters, this indicates that a 24-

hour standard in the range of 28-30 deciviews would be weaker than a 4-hour standard 

set at the same level and that certain areas of the country would be affected 

disproportionately. (AMC, et al.) 

Response: The EPA notes that the illustrative 4-hour and 24-hr results presented in 

Tables H-1 and H-2 of the Policy Assessment were based on a two different methods. 

The 4-hr results were based on a method which used 2007-2009 monthly average

speciation measurements in combination with hourly PM2.5 data, used a 1.6 multiplier to 

estimate organic mass from PM2.5 OC and only included counties with at least 2500 hours 

of PM2.5 data. The 24-hr results were based on the method described in Appendix G 

which used daily speciation measurements and a 1.4 multiplier to estimate organic mass 

from PM2.5 OC. A different data selection criterion was used for these 24-hr speciation 

measurement data. Thus the number of included counties is different, and more 

importantly, the presented illustrative data are not directly comparable. 

Although the 24-hr results presented in Table H-2, as well as the 4-hr results presented in 

Table H-1, suggest that several Northeastern counties would exceed a visibility standard 

of 28-30 dv (even though they do not exceed the existing suite of secondary PM2.5

standards, 15 ug/m3 annual and 35 ug/m3 24-hour), that comparison was based on 2007-

2009 data. Since that time, the composition of PM2.5 has significantly changed in the 

eastern U.S. due to massive reductions in SO2 emissions and concomitant changes in 

PM2.5 sulfate. As shown in Kelly 2012a and Kelly 2012b, all of the Northeastern counties 

would meet a 30 dv visibility index NAAQS, using 2008-10 data and using 2009-2011 

data. 
IV-28 

5. Specific Comments on Visibility Preference Studies 

The evidence relied upon by the Administrator in determining an appropriate degree of 

public welfare protection from visibility impairment is predominately derived from a small 

number of urban-focused visibility preference studies. As a result, many comments were 

received on the adequacy and appropriateness of this limited dataset serving as a basis for the 

Administrator’s judgments regarding what is requisite national protection for visibility 

impairment. Both CASAC and the EPA staff, as well as a few commenters, concluded that while 

limited, these studies did form a sufficient basis on which the Administrator could make a 

decision. A majority of commenters, however, expressed the view that the existing preference 

studies provide an insufficient basis for selection by the Administrator of an appropriate level of 

public welfare visibility protection for a national standard. These commenters highlighted a 

number of limitations and uncertainties associated with these studies as support for this view. 

Many of the important and fundamental comments are also discussed in the final rule, with 

further details provided below. As in the final rule, this section organizes and discusses the 

preference study comments under four broad topic areas, including: (a) limitations and 

uncertainties associated with the visibility preference studies; (b) preference study methods and 

design; (c) use of preference study results for determining adversity; (d) the appropriateness of 

using regionally varying preference study results to select a single level for a national standard. 

a. Comments on Preference Study Limitations and Uncertainties 

A large and diverse number of limitations and uncertainties associated with the visibility 

preference studies has been identified and discussed in the public comments. Many of these same 

limitations and uncertainties were also identified and discussed by the EPA in the various 

documents developed throughout this review such as the Integrated Science Assessment, 

Visibility Assessment, and Policy Assessment, as well as in the proposed rule (see section VI.b.2 

beginning at 77 FR 38973, 38990) and in the final rule (section VI.C.1.e.i). 

(1) Comment: Most commenters expressed concern over the small number of preference 

studies that are available in this review. In particular some note that these preference 

studies cover just four locations, only three of which occur in the U.S., that the two 

studies conducted in Washington, DC were pilot studies, not full preference studies, 

and/or that three of the preference studies were conducted in the West, while only one 

was conducted in the East, thus providing only limited geographic coverage. Typically 

these same commenters also noted the small number of survey participants, which totaled 

852 across the four urban areas, which they assert are too few and unrepresentative 

nationally. These commenters thus concluded that there is insufficient information, both 

geographically and demographically, upon which to select a national level of a visibility 

index for purposes of visibility protection. 

Response: The EPA notes that it is well aware of the limited nature of the information, 

which it has described in great detail in the Integrated Science Assessment, Visibility 

Assessment, and Policy Assessment, as well as in section VI.B.2 of the proposed rule 

(i.e., beginning at 77 FR 38973, 38990). The EPA further notes however that limited 

information does not preclude the Administrator from making judgments based on the 

best available science, taking into account the existing uncertainties and limitations 
IV-29 

associated with that available science. Thus, in reaching judgments based on the science, 

the Administrator appropriately weighs the associated uncertainties. The CASAC 

supported this view and concluded that the available information provided a sufficient 

basis on which the Administrator could form a judgment about requisite PM-related 

public welfare visibility protection. Specifically, CASAC stated “[t]he 20-30 deciview 

range of levels chosen by EPA staff as ‘Candidate Protection Levels’ is adequately 

supported by the evidence presented” (Samet, 2010b, p. iii). As discussed in the proposed 

rule (77 FR 38990), the Administrator recognized and explicitly took into account the 

uncertainties and limitations in the science in determining an appropriate degree of 

protection when she proposed a level at the upper end of the recommended range. 

(2) Comment: Some commenters also made the point that the EPA relied on much of this 

same evidence to reach the conclusion in 2006 that the information was too limited to 

allow selection of a national standard. For example, API stated: 

[T]he bulk of the VAQ preference studies were available during the previous PM 

NAAQS review and were considered by the Agency in its establishment of the 

2006 PM secondary NAAQS.... The Proposed Rule does not mention this fact 

and does not explain why many of these same studies now compel EPA to 

propose this new secondary NAAQS....The Proposed Rule notes in passing that, 

since the last review of the PM NAAQS, ‘limited information that has become 

available regarding the characterization of public preferences in urban areas has 

provided some new perspectives on the usefulness of this information in 

informing the selection of target levels of urban visibility protection.’ 77 Fed. 

Reg. at 38969/2. It is a serious oversight that the Proposed Rule makes no attempt 

to explain what that information is or how it affects the interpretation of the VAQ 

preference studies. This ‘limited information’ is an apparent reference to 

information provided by Dr. Anne Smith. (API, p. 37) 

Response: The EPA disagrees with these commenters. First, the EPA disagrees that it 

failed to distinguish between studies that were available in the previous review (see 

discussion in section VI.A.1 of the proposal which specifically identifies the studies from 

Denver, Phoenix and British Columbia (77 FR 38967/2) as being considered in the last 

review). The EPA further disagrees with the implication that it is being circumspect about 

identifying the “limited information that has become available regarding the 

characterization of public preferences in urban areas.” Beginning in section VI.A.3 of the 

proposed rule (77 FR 38969), the EPA was clear about what information, both 

preexisting and new, it relied upon in this review to inform its views and provide the 

basis for its proposal. In section VI.B.2 of the proposed rule, the EPA elaborates on the 

specific tools, methods and data which are considered in relation to the public preference 

studies, including the new information available since the last review. 

In addition to the substantial PM urban air quality information and analyses new to this 

review, there are three other sources of information that have specifically “provided some 

new perspectives on the usefulness of” the preference studies “in informing the selection 

of target levels of urban visibility protection”(77 FR 38969), They include: (1) results 

from additional urban visibility preference study experiments conducted for Washington, 
IV-30 

DC by Smith and Howell (2009) which added to the preference data for that location, and 

shed light on the role of location in preference responses (77 FR 38974, 38976); (2) a 

review and reanalysis (Stratus Consulting, 2009) of the urban visibility public preference 

studies from the four urban areas, including the newly available Smith and Howell (2009) 

experiments which examined the similarities and differences between the studies and 

evaluated the potential significance of those differences on the study results (77 FR 

38893, 389975-76); and (3) additional analyses, including most importantly a logit 

analysis (Deck and Lawson, 2010, as discussed in Chapter 2 and Appendix J of the 

Visibility Assessment), which was requested and reviewed by CASAC, which showed 

that each city’s responses represented unique and statistically different curves (77 FR 

38975-76). 

Taken together, these sources contributed to the EPA’s current knowledge and 

understanding of each survey study’s results, the appropriateness of comparing each 

study’s results to the others, and the key uncertainties relevant to data interpretation. In 

addition, in the last review the decision to not adopt a distinct secondary standard was 

remanded as contrary to law and failing to provide a reasoned explanation for the 

decision. As such it is not appropriate for purposes of comparison with the 

Administrator's judgment and reasoning in this review. 

(3) Comment: Other commenters stated support for using the preference studies, concluding 

they provide an adequate basis, in spite of their limited nature. In particular, AMC et al. 

state: 

We believe that these studies provide sufficient results to inform setting a national 

visibility standard. While the number of studies is small, they do incorporate 

spatial variation and, in the case of Denver and Phoenix, varied populations.... 

EPA should have confidence, rather than uncertainty, in the fact that these studies 

used different methods and respondents and yield a range of 20 – 24 dv, with one 

outlier of 29. (pp. 6-7) 

Response: The EPA agrees that these studies provide a sufficient basis to inform the 

Administrator’s judgments regarding an appropriate level of protection from PM-related 

visibility impairment but she recognized that these studies, which are the only studies 

before her, are a limited source of information (see also response to (1) above). However, 

the EPA does not agree that the Washington, D.C. results represent an outlier, and thus 

the EPA believes these results are appropriately included in the range identified for the 

Administrator to consider. 

(4) Comment: A number of other technical features of the studies were identified by 

commenters which they assert limit the usefulness of these studies in representing real 

world urban views and in eliciting appropriate preferences for urban visibility. For 

example, some commenters state that the assumption of light extinction at 550 nm is 

unsupported, technically flawed and invalid for a number of reasons, including that it 

does not account for the mix of pollutants, which varies substantially within and between 

urban areas, or how changes in that mix affect light extinction at different wavelengths of 

light, and it misses the role of sky discoloration from NO2 and carbonaceous particles 
IV-31 

(i.e., Brown Cloud phenomenon) which can be significant in urban areas and influence 

human perception of urban visibility impairment. Other commenters note that pollutant 

concentrations in urban areas are not uniform in all directions over the length of a line of 

sight and that visibility depends upon the site-path integrated concentration of fine PM. 

Studies which used photographic data capture the integrated site path. They further state 

that momentary glances at 2-dimentional pictures cannot represent the actual way that 

visibility is perceived outdoors. 

Response: First, the EPA disagrees that its choice of measuring light extinction at 550 nm 

wavelength is ‘unsupported, technically flawed and invalid’. The EPA’s Integrated 

Science Assessment makes clear that 550 nm represents the “most sensitive portion of the 

spectrum for human vision” and has thus traditionally “been used to characterize light 

extinction and its components” (U.S. EPA, 2009a, p. 9-2). The ISA further states that 

“the convention for visibility monitoring purposes is to make measurement at or near 550 

nm, which is the wavelength of maximum eye response” (U.S. EPA, 2009a, p. 9-8). The 

EPA therefore concludes that it remains logical to select a wavelength of light that is 

most relevant to human observers when evaluating impacts to the public welfare. 

Regarding the comment that 550 nm misses the impacts of NO2 on sky discoloration, the 

EPA notes that this PM NAAQS review is intended to only address visibility impairment 

caused by particles present in the ambient air. Thus, while it is true that sky discoloration 

from NO2 results from its ability to absorb more light in the short wavelength blue 

portion of the spectrum giving a yellow or brown appearance to the pollution layer or 

plume, improvement in the Brown Cloud Phenomenon is not the goal of this NAAQS 

review and would be expected to occur only indirectly from a secondary PM2.5 NAAQS 

for visibility in as much as PM2.5 controls also reduced co-emitted NO2. The EPA further 

notes, however, that not every urban or other area suffers from the Brown Cloud 

Phenomenon. At background concentrations NO2 absorption is generally less than five 

percent of the light scattering by clean air (Rayleigh scattering), making it imperceptible” 

(U.S. EPA, 2009a, p. 9-5) Regarding the comment that measuring light extinction using 

550 nm “does not account for the mix of pollutants, which varies substantially within and 

between urban areas”, the EPA disagrees, noting that the IMPROVE algorithm used to 

calculate light extinction was designed to specifically take into account the variability in 

the mix of pollutants from place to place and to measure the “photopic-weighted 

absorption efficiency at the 550 nm wavelength” in its calculations of PM-related light 

extinction. Thus, given the above, the EPA believes it is still appropriate to use the 550 

nm wavelength in order to measure the maximum impact of ambient PM on light 

extinction that is perceptible to the human observer. 

Second, with respect to the other technical issues raised above, the EPA agrees that 

photographic and WinHaze images cannot duplicate the outdoor, three dimensional 

viewing environment. This limitation of the preference study design does introduce some 

degree of uncertainty into the results. However, the EPA does not believe that this 

uncertainty significantly limits the usefulness of the results. People take pictures of 

aesthetically pleasing vistas so that they can look at them repeatedly, even though they 

are not exact replicas of their initial outdoor viewing experience. This shows that they 

appreciate the photographic view of the scene, commensurate with their appreciation with 

the scene itself. Thus, the EPA believes photos or digital images can be useful surrogates 
IV-32 

for the purpose of eliciting public preferences. Regarding the commenters other concern 

that pollutant concentrations in urban areas are not uniform in all directions over the 

length of a line of sight and that visibility depends upon the site-path integrated 

concentration of fine PM, the EPA notes that both the photos used in two of the 

preference study areas (Denver and British Columbia) and the WinHaze images used in 

two others (Phoenix and Washington, DC) depict visibility impairment over an integrated 

sight path. The difference between the two methods is that a photo can capture the nonuniformity across the sight path while the WinHaze views present a uniform haze 

integrated across the sight path. Photos of the Denver scene therefore would also have 

included any layered haze known as the brown cloud that was present at the time that fell 

within the integrated site path. Despite these variables, the ordering of the results of these 

studies appear to be explainable based predominantly on scene characteristics – i.e. 

people found impairment of the views with the most sensitive scene characteristics 

(Denver and Phoenix) more unacceptable at lower deciview values than those with less 

sensitive scenes (British Columbia and Washington, DC) regardless of the image 

depiction methods used. Thus, the EPA concludes that the concerns over study methods 

and designs identified by commenters are not substantial, and that the preference study 

results are still sufficiently informative to allow selection of candidate protection levels. 

b. Comments on Preference Study Methods and Design 

(1) Comment: Many commenters asserted that the methodologies used in the preference 

studies are fundamentally flawed. Most of these same commenters also pointed to an 

assessment of the preference study methodology conducted by Smith and Howell (2009) 

of Charles River Associates (CRA) as the basis for their views. These commenters 

criticized the EPA for not acknowledging that (in their view) the Smith and Howell 

results undermined the validity of the earlier preference studies. For example: 

Smith and Howell (2009) show that VAQ preference study outcomes are 

malleable and depend entirely on the design of the study. Accordingly, such 

studies do not identify any meaningful threshold of acceptable visibility 

conditions. Despite Smith and Howell’s conclusions, EPA continues to assert that 

the VAQ preference studies can be used to identify minimally acceptable 

visibility conditions even though the Agency has never provided any valid 

scientific basis for discounting the Smith and Howell (2009) results. (API, p. 38) 

Well-controlled preference studies discussed by Anne Smith of Charles River 

Associates at the March 2010 CASAC meeting demonstrated that the judgment of 

panel members was affected by the order in which photographs were presented 

and tendency to identify the middle of the range of visibility degredation as a 

threshold of acceptability. This points to a potential flaw in these studies and that 

artifacts caused by these tendencies may have influenced study results. 

Dismissing these inherent flaws in the existing preference studies and then using 

these studies to set a secondary NAAQS is arbitrary and capricious. (API, 

attachment 14, p. 12) 

EPA also fails to acknowledge that the only study conducted since the last review 
IV-33 

rebuts the validity of the VAQ preference studies previously conducted. (UARG, 

Attachment 2. p. 28) 

Response: As noted above, the EPA is aware of the issues raised regarding the 

uncertainties and limitations associated with the preference studies, including those 

associated with study methods and design and specifically solicited comment on how 

these uncertainties and limitations should be considered (see 77 FR 38990). However, as 

is explained in the following discussion, the EPA disagrees that the analysis by Smith and 

Howell (2009) supports the commenters’ conclusion that the preference study 

methodologies and design were fundamentally flawed, however the EPA notes that their 

experiments do identify areas where additional research would be useful to further inform 

our limited understanding of public preferences in urban areas. Though still limited, the 

EPA views the Smith and Howell (2009) experiments as increasing the EPA’s knowledge 

and understanding of the findings of the 2001 Washington, DC focus group pilot study 

(Abt, 2001) in several important ways. Smith and Howell (2009) conducted a series of 

three sets of experiments based on the 2001 Washington, DC, focus group pilot study. 

The first set of experiments (Test 1) was designed to replicate the 2001 focus group to 

explore whether the 2001 study findings could be reproduced. Tests 2 and 3 varied the 

range and distribution of visibility conditions to examine whether such changes would 

affect the results. As explained below, the EPA asserts that some aspects of the approach 

used by Smith and Howell (2009) in Tests 2 and 3 are flawed. 

It is important to note as an initial matter, that while Smith and Howell (2009) claims to 

have replicated the Abt 2001 protocol, there were three distinct differences in the 

methods used by Smith and Howell (2009) and the methods used in the Washington, DC 

2001 pilot study. First, the images of alternative levels of visibility degradation in 

Washington, DC were prepared and presented differently. While both studies used the 

same original photograph of Washington, DC, the 2001 images showing different levels 

of visibility degredation were prepared by John Molenar of Air Resource Specialists, Inc. 

(ARS) using the mainframe computer version of WinHaze available at that time. The 

2009 Smith and Howell experiments, on the other hand, used images prepared in a more 

simple manner using the MS-Windows©-based version of WinHaze (Ver. 2.9.0) available 

by that time from ARS. 

Second, the 2001 pilot study used high quality photographic transparencies (“color 

slides”) prepared by ARS, which were presented on a large format, high quality 

projection screen. The entire group of participants was seated at the viewing angle and 

distance from the projection screen in a darkened room to provide the optimal viewing 

conditions recommended by John Molenar. The 2009 study used images presented to 

individuals on a large desktop computer monitor. 

Third, the method used to recruit participants differed between the 2001 and 2009 

studies. While a group of only 9 people can never be a statistically valid representative 

set of any population, the 2001 focus group participants were recruited by a professional 

focus group facilitation firm to reflect aspects of the demographic distribution of the 

Washington, DC metropolitan area adult population. The recruitment screening method 

was designed to obtain 9 adults resembling major aspects of the demographic gender, 
IV-34 

age, residence and income distribution of the Washington, DC area. At least two of the 

2001 participants were in each of the following groups: a) Income: at least two people 

with household incomes under $25k, two with incomes between $25k and $60k, and two 

with incomes above $60k; b) Age: at least two between the ages 18 and 25, two between 

26 and 55, and two over 56; c) Race/Ethnicity: at least two African Americans and two 

Hispanics; d) Residence location: at least two living in each of Washington, DC, 

Maryland and Virginia. In contrast, the Smith and Howell (2009) study did not use a 

structured recruitments process. Due to the schedule of the Smith and Howell (2009) 

study, all study participants were employees of CRA, Inc. (where both Smith and Howell 

are also employed). One variant of Test 1 was conducted with participants who work at 

the CRA Washington, DC office (and who presumably live in the Washington, DC area). 

The other variant of Test 1 was conducted with participants from the CRA Houston office 

(and likely live in the Houston area). The same set of images of Washington, DC was 

shown to both the CRA Washington and Houston participants. 

In spite of these differences in study methods, the Test 1 results (Smith and Howell, 

2009, p.11) found a “...remarkable degree of replication, given the differences in the 

samples, and the relatively small sample size of the Abt pilot (nine people).” 

Furthermore, the preferences for Washington, DC visibility provided by the Houston 

participants were effectively the same as both the preferences of the CRA Washington 

office participants and the Abt 2001 participants. 

The EPA identified a number of important implications from the similarity between the 

Test 1 (2009) and 2001 study results. 

1. The change in the presentation methods (i.e., from slide projection to computer 

monitor, and mainframe WinHaze images versus the simpler Windows WinHaze 

method) shows no evidence of impacting reported preferences. 

2. The replicability of the 50% acceptable criteria results supports a hypothesis that 

the 2001 results, although based on a small sample of 9, were consistent with the 

preferences from a larger sample of the general Washington, DC population. 

3. The similarity of the Test 1 Houston results to both the Test 1 Washington results 

and the 2001 Washington study suggest that an individual’s preferences for 

visibility in one location (i.e., Washington, DC) may not depend on whether they 

live in that location or in another. 

As a result of the similarity between the results of these two DC studies and the above 

implications, the EPA concluded that the Test 1 experiment could legitimately be 

combined with the 2001 study to effectively more than triple the responses to the original 

Washington, DC urban visibility preference study, thus increasing the available 

information from 9 (in the 2001 study) to 31 (with the addition of both the Washington, 

DC and Houston CRA participants). Smith and Howell’s Test 1 thus instigated a shift in 

the EPA’s thinking regarding the usefulness of the available Washington, DC preference 

study data. 
IV-35 

The Smith and Howell (2009) Tests 2 and 3 also provided important information relevant 

to understanding the results of visibility preference studies. In Test 2 and 3 the range and 

distribution of visibility conditions shown to participants were substantially different than 

the range and distribution shown in Test 1 and the 2001 Washington, DC study. Test 2 

removed from the range of Test 1 slides those that showed the 11 worst visibility 

conditions (all images above 27.1 dv). Test 3 changed the visibility conditions presented 

in two ways: first, the number of clean or cleaner images were reduced substantially, 

dropping all images in the lower third of the distribution, and adding two new images of 

substantially worse visibility (42 and 45 dv), which were substantially above the previous 

worst scene shown (38.3 dv). 

Smith and Howell (2009) found that changing the range of visibility images shown has a 

pronounced impact on the resulting 50% acceptability level. They concluded that this is 

an indication that preferences obtained using the general PS method are not stable, and 

therefore not an accurate representation of the populations pre-existing (or “true”) 

preferences for visibility. 

While the Smith and Howell (2009) results suggest such a hypothesis, the Test 2 and Test 

3 results also are consistent with a very different effect in visibility preference survey 

results. The range of visibility conditions shown in Test 1 and the original 2001 

Washington, DC study were selected by EPA to present a good representation of the 

distribution of visibility conditions expected to occur in Washington, DC with thencurrent EPA air quality regulations. In other words, the original range and distribution of 

visibility conditions shown to the participants were near to current conditions, and 

reflected the “policy relevant” range of expected conditions. This fundamental approach 

was used in all the existing studies (i.e. Denver, Phoenix, and British Columbia); the 

range of visibility conditions reflects current real world conditions. While the participants 

were not informed that the images they were being shown were essentially then-current 

conditions, the range of images would have been consistent with the participants own 

experiences. 

When the range of images presented was substantially different, as in Tests 2 and 3, the 

participants would very likely recognize that the conditions did not depict the real range 

of conditions. This creates a disconnect between the participants’ own experiences and 

expectations and the hypothetical scenario being presented to them through the use of the 

altered ranges. This creates a form of the well known “scenario rejection bias” that has 

been observed in many types of stated preference studies. Current methods of stated 

preference research on a range of environmental issues find it is very important to present 

as realistic and believable a description as possible of the real world conditions matching 

to participants’ personal experience and knowledge in order to produce robust, stable and 

reproducible results. The effect Smith and Howell (2009) see in their Test 2 and Test 3 

methods are likely to be due to just such a scenario rejection biasing influence. 

Thus, on the basis of the above discussion, the EPA disagrees that the findings of Tests 2 

and 3 in Smith and Howell (2009) make the case that the methodology used in the 

preference studies is fundamentally flawed and therefore disagrees with commenter 

views that the EPA’s use of these studies is somehow inappropriate, scientifically 
IV-36 

unsound, or arbitrary and capricious. 

(2) Comment: Many commenters also asserted that preference study participants were not 

given guidance on how to interpret the concept of “acceptable urban visibility”. This lack 

of guidance was considered a detriment by commenters because in their view it renders 

the responses subjective. 

Response: EPA notes that while the overall method used in all the preference studies is 

consistent (based on the method and elicitation protocol developed by Ely et al., 1991 in 

the Denver study), each study developed a specific protocol (including the specific 

language on both background information and the wording of the key questions) for 

conducting that study’s survey. The Denver and Phoenix studies each gave the survey 

participants specific guidance on interpreting “acceptability”. 

The Denver study framed the question in the explicit context of setting an urban visibility 

standard for Denver, and instructed the participants that they were being asked to identify 

the VAQ that in their opinion should violate an urban visibility standard, and that 

“...standard violations should be VAQ that is unreasonable/objectionable, and 

unacceptable visually. Participants were asked to discern ‘how much haze was too much’, 

not to indicate standard violations based on whether haze was detectable unless any 

amount of haze was more than they could accept” (Ely et al., 2001, p. 6-7). 

The Phoenix study instructions to participants defined acceptable (or unacceptable) as 

“Consider ‘unacceptable’ as visual air quality that is unreasonable or objectionable 

visibility. Please do not mark a slide ‘unacceptable’ just because you can see some haze, 

unless you believe that any amount of haze is more than you would tolerate.” 

The British Columbia study (Pryor et al., 1996) followed the survey protocol in the 

Denver survey closely, and gave similar guidance to the participants on the meaning of 

“acceptability” in a standard setting context. 

The Washington, DC (2001) study was a focus group designed to investigate a series of 

issues involved with conducting group interview type surveys about preferences for 

urban visibility. A key feature of the 2001 focus group script was to deliberately not give 

the participants guidance on how to interpret “acceptable” or “unacceptable” before 

rating the series of Winhaze images. After the series questions involving rating the 

images, the focus group moderator lead a discussion about how the participants 

interpreted the term “acceptable”, and what issues and information they considered in 

forming their responses. The 2009 series of Washington, DC urban visibility preference 

experiments followed a similar procedure, although apparently conducted a more 

abbreviated focus group follow-on discussion. 

Thus, the EPA believes that study participants were given sufficient direction and context 

so that they could understand the nature of the questions being posed and were all on 

equal footing in developing subjective judgments regarding “acceptable” and 

“unacceptable” visual air quality. Since the goal of these studies was to elicit personal 

preferences, which by very nature are subjective, the EPA does not view the subjectivity 
IV-37 

of the responses as a weakness of the study design or protocols. 

c. Comments on Preference Study Results and Adversity 

A number of comments were received regarding the EPA’s use of preference study 

results to make the determination that adverse PM2.5-related visibility effects on the public 

welfare are occurring. Some of these commenters questioned whether the EPA had made the 

case that unacceptable levels of visual air quality based on preference study results alone can be 

equated with an adverse public welfare effect. Other commenters questioned the EPA’s selection 

of the 50% acceptability criterion as the appropriate benchmark for determining adversity. 

(1) Comment: Several commenters asserted that the EPA had not made a sufficient case for 

the occurrence of adverse public welfare effects in association with ambient levels of 

PM2.5: 

Thus, EPA seemingly was building the foundation for a determination of what 

constitutes an adverse effect on visibility in the context of public welfare. 

However ... EPA subsequently veered toward an oversimplified focus on public 

acceptance of visibility conditions.... EPA’s discussion of visibility in the Policy 

Assessment and its proposed rule in the Federal Register focuses entirely on 

“acceptable” and “unacceptable” visual air quality and make no mention of an 

“adverse effect” in the context of visibility. EPA’s reliance on only 3 urban 

preference studies represents a paucity of data and a wholesale abandonment of 

any effort to seek a scientifically measurable adverse effect. (Kennecott Utah 

Copper LLC, p. 26) 

These commenters suggested that unless preference study information is linked to 

personal comfort and well-being or other associated welfare effects, it cannot form the 

basis of a determination of adversity. 

Response: The EPA first notes that the definition of effects on welfare included in section 

302(h) of the CAA identifies both visibility and the broader category of effects on 

personal comfort and well-being as effects on welfare. In setting a secondary standard to 

address visibility impairment, the EPA considers the effect on the public from 

impairment of visibility as a separate and distinct welfare effect in its own right. The EPA 

is not required to translate this into terms of personal comfort and well-being, as visibility 

impairment is designated explicitly by Congress as an effect on welfare. While there may 

be a large degree of overlap among these different welfare effects, the EPA properly 

focuses on evaluating all of the information before the Agency on the effect visibility 

impairment has on the public, whether or not this impairment would also be categorized 

as having an adverse effect on personal comfort and well-being. It is in the context of all 

of this information that the EPA makes the judgment as to the appropriate degree of 

protection from known and anticipated adverse effects on the public from visibility 

impairment. The EPA recognizes that there is uncertainty about the degree of adversity to 

the public welfare associated with PM-related visibility impairment. However a 

secondary standard is designed to provide protection from "known or anticipated" 

adverse effects, and a bright line determination of adversity is not required in judging the 
IV-38 

requisite degree of protection under section 109(b)(2). Furthermore, the EPA disagrees 

that it has abandoned its consideration of visibility-related impacts on the welfare effect 

of personal comfort and well-being, as is made clear in the following quote: 

Research has demonstrated that people are emotionally affected by low visual air quality, 

that perception of pollution is correlated with stress, annoyance, and symptoms of 

depression, and that visual air quality is deeply intertwined with a ‘‘sense of place,’’ 

affecting people’s sense of the desirability of a neighborhood (U.S. EPA, 2009a, section 

9.2.4). Though it is not known to what extent these emotional effects are linked to 

different periods of exposure to poor visual air quality, providing additional protection 

against short-term exposures to levels of visual air quality considered unacceptable by 

subjects in the context of the preference studies would be expected to provide some 

degree of protection against the risk of loss in the public’s ‘‘sense of well-being.’’ (77 

FR 38973/1, emphasis added) 

The approach taken to address such qualitative, but policy-relevant, information in this 

review is the same as in other NAAQS reviews. The review is initiated with a 

comprehensive assessment of all possible public health and welfare effects associated 

with PM in the Integrated Science Assessment. Then policy-relevant effects for which 

there is sufficient quantitative information to allow a determination of the change in risks 

associated with incremental changes in air quality are assessed (in this review, in the 

Visibility Assessment) and used to provide a quantitative basis to inform the selection of 

an appropriate range of levels for further consideration in the Policy Assessment. In the 

Policy Assessment, the EPA considers all important policy-relevant evidence and 

information, both quantitative and qualitative, in making recommendations regarding the 

range of policy options appropriate for the Administrator to consider. It is in the context 

of all of this information that the Administrator makes her final judgment as to the 

appropriate degree of protection from known and anticipated adverse effects on the 

public from visibility impairment.. 

(2) Comment: Another issue raised in the comments regarding adversity is the EPA’s 

decision to use the 50 percent acceptability criterion from the public preference studies in 

determining candidate protection levels of visibility impairment for the selection of a 

national level of visibility protection. For example, AMC et al. recommended “a 75% 

acceptability criterion as a target that is in line with protecting the broader public from 

the negative effects of visibility impairment” (AMC, et al., p. 9). 

Response: In the Visibility Assessment, the EPA noted that the use of the 50 percent 

acceptance level for urban visibility was first presented in Ely et al. (1991) (U.S. EPA, 

2010b, p. 2-5). Ely discussed the use of the 50 percent acceptability criterion as a 

reasonable basis for setting a standard to protect visibility in urban areas. 

The standard was determined based on a 50% acceptability criterion, that is, the 

standard was set at the level of extinction that would divide the slides into two 

groups: those judged acceptable and those judged unacceptable by a majority of 

the people in the study. The criterion is politically reasonable because it defines 

the point where a majority of the study participants begin to judge slides as 
IV-39 

representing unacceptable visibility. It is also consistent with psychological 

scaling theory which indicates that a “true score” exceeds a standard when more 

than 50% of the “observed scores” exceed that standard. (Ely et al., 1991, p. 11) 

As Ely described, the 50 percent acceptability criterion and the preference study 

conducted by Ely were used as the basis for setting the level of the Denver Visibility 

Standard in 1990. That same criterion was judged appropriate and selected for use in the 

Phoenix preference study (BBC research, 2003) and was also used as the basis for setting 

the level of the Phoenix Visibility Standard in 2003. Most recently, the 50 percent 

acceptability criterion has been recommended by the British Columbia Visibility 

Coordinating Committee as the basis for the visibility standard currently under 

consideration by British Columbia, Canada. Furthermore, CASAC supported this 

approach, while recognizing the uncertainty associated with this issue. Specifically, 

CASAC agreed that “the 50th percentile for the acceptability criteria is logical, given the 

noted similarities in methodologies employed in the 4 study areas. ... In terms of 

choosing a specific percentile from the preference studies, we note that there may not be 

a “preferred” one, but in assessing preference studies to propose a PM secondary 

NAAQS, the 50th percentile is sufficient, as it is the basis for existing visibility indexes 

used in the Denver/Colorado Front Range and Phoenix metropolitan areas” (Samet, 

2009c, pp. 8-9). Therefore, after considering the information that served as the original 

basis for its selection as described in Ely et al., 1991, and given its acceptance and use in 

existing visibility programs, the EPA continues to conclude, consistent with the advice of 

CASAC, that it is reasonable to use the 50 percent acceptability criterion in determining 

target levels of protection from visibility impairment. 

d. Comments on Using Preference Studies as Basis for Nationally Uniform Standard 

A number of commenters raised concerns regarding the bases for and implications of the 

differences observed in the preference study results, concluding that these results were due to 

regionally varying factors and thus could not be used to set a national standard. 

(1) Comment: Some commenters asserted that because the confidence intervals around the 

four 50 percent acceptability levels do not overlap at all, and because there are variations 

in preference study designs and inherent differences in the visual setting among cities and 

panels, the four preference curves and their associated 50 percent dv values are cityspecific and statistically different. The commenters concluded, therefore, that it was 

inappropriate to aggregate the 50th percentile dv values from multiple studies and that 

they should instead be evaluated individually. Similarly, other commenters expressed the 

related view that the preference study results cannot be used to set a national standard for 

visibility impairment because the results show that visibility preferences vary regionally 

and/or locally for a variety of reasons. For example: 

The ‘one-size-fits-all’ approach...is not viable because it does not account for 

regional and city-specific factors that have been made evident in the disparity of 

preference study data.... It is well known, for example, that the level of light 

extinction to which people in different areas of the country are accustomed, as 

well as the urban setting, are the primary factors that affect a person’s visual 
IV-40 

perception of an urban vista. Thus, the degree to which extinction threshold can 

be related to human welfare is inevitably regionally-dependent. (API, Attachment 

2, p. 4) 

[T]he proposed method falls short because it is not temporally or geographically 

representative enough to have any meaning.... The uncertainty evidenced in these 

studies and the non-uniformity between the western and eastern vistas makes it 

impossible at this time to set an acceptable light extinction value that would 

appropriately address visibility concerns in non-Class I areas. (New York 

DOH/DEC, pp. 5-6) 

These commenters suggest that the basis for the differences in preference study results 

include regionally varying preferences for acceptable visual air quality and/or regionally 

varying factors, such as relative humidity and other differences between Eastern and 

Western areas. These commenters asserted that it would be more appropriate to develop 

distinct visibility standards at the state or local level, since it is not possible to select a 

single level for a national standard to protect visibility across the United States that 

provides the appropriate degree of protection in locations with distinct characteristics, 

including areas which lack “important visibility vistas” that might not need standards at 

all, since flat areas without significant terrain have a limited maximum visual range. 

(NEDA/CAP, p. 3) 

Response: The EPA agrees that the preference curves and the 50 percent dv levels are 

separate and distinct data points representing four different VAQ preference curves for 

four unique urban scenes. However, the EPA does not consider the fact that the four 

curves are distinct as a weakness of the approach or a reason that the results cannot be 

compared. In addition, the EPA does not agree that the study results necessarily support a 

conclusion that preferences are regionally dependent. In particular, the EPA notes that the 

results of Smith and Howell (2009) which show that participants in Houston and 

Washington, DC did not have significantly different views on acceptable air quality in 

Washington, DC, provide limited support for the conclusion that people’s preferences 

differ less because of where they live and more because of the scene they are viewing. 

The existing literature indicates that people’s preferences for VAQ depend in large part 

on the characteristics and sensitivity of the scene being viewed. The EPA also 

understands that there is a wide variety or range of urban scenes within the United States. 

These sensitive urban scenes include those with natural vistas such as the Rocky 

Mountains in Colorado as well as those with iconic man-made urban structures like the 

Washington Monument. The EPA believes that the scenes presented in the four urban 

areas include important types of sensitive valued urban scenes and therefore, when 

considered together, can inform the selection of acceptable urban VAQ at the national 

scale, taking into account the variation across the country evidenced in the studies. 

In response to the comments that there are factors that vary regionally that are important 

to take into account when setting a national standard for visibility protection, the EPA 

agrees, and notes that it has clearly taken these into account. Section VI.A of the 

preamble to the final rule regarding the history of the secondary PM NAAQS review 
IV-41 

discusses the evolution of the EPA’s understanding regarding the regional differences in 

PM concentrations, relative humidity and other factors. As a result, the current review has 

gone to great lengths to address these factors, leading to the EPA’s proposal to use the 

IMPROVE algorithm to calculate light extinction in order to take into account the 

varying effects of relative humidity and speciated PM. While this approach does not 

result in a uniform level of ambient PM2.5, it does ensure a nationally uniform level of 

visibility protection. The EPA refers the reader to other sections of the final rule, 

including sections VI.B.1.a, VI.B.1.c, VI.C.1.b and VI.C.1.f, and other sections of the 

Response to Comments document for a more detailed response as to how it is taking 

these variables into account. 

(2) Comment: The Arizona DEQ stated that it was inappropriate to use the Phoenix study for 

purposes of establishing a level for a national standard: 

The proposed secondary visibility standard does not integrate our measurement 

method or mirror our index scale, essentially making the program incomparable 

with the proposed standard. Four urban visibility studies were cited in the 

proposed rule as a consideration in developing the level of the secondary PM2.5

standard. The recommended level for the proposed standard, 28 or 30 deciviews, 

and corresponding calculation method excludes extinction by coarse particulate 

matter and Rayleigh scattering. The cited studies were conducted considering 

total light extinction; including extinction resulting from particulate matter and 

Rayleigh scattering. Visibility impairment due to coarse particulate matter can be 

an important contributor in Arizona, specifically in the Phoenix area where 

ongoing measurements have been made. Therefore, ADEQ believes that the 

proposed levels of the secondary visibility standard are inconsistent with 

applicable urban studies. (Arizona DEQ, p. 2) 

Response: The EPA understands that each of the four preference study areas has a 

different mix of pollutants and that across the studies a variety of methods for measuring 

and linking ambient PM concentrations to images (either photos or WinHaze) of differing 

haze levels at a given urban scene were employed. However, as discussed above section 

IV.B.5.a, the EPA conducted a detailed assessment (77 FR 38893, 77 FR 38974-75) of 

the differences and similarities that existed between the four studies and concluded that it 

was still appropriate to compare them and consider their results together. The CASAC 

also reached the same conclusion (Samet, 2010b, iii). In regard to the commenter’s 

concern about contributions from coarse particles and Rayleigh, the EPA further notes 

that participants in the Phoenix and other studies were not asked to break out their 

preferences based on how much of the haze was caused by contributions from coarse 

particles, Rayleigh scattering or fine particles. Instead, as discussed above in section 

IV.B.5.b, Phoenix study participants were simply asked to identify levels of visual air 

quality that they would consider “unreasonable or objectionable”, no matter what the 

source. Based on this information, Phoenix was able to come up with a target level of 

VAQ, even though pollutant mixes vary temporally and spatially, even within the 

Phoenix urban area. Since the goal of the secondary PM2.5 NAAQS is to provide a 

uniform national level of public welfare protection from PM2.5 related visibility 

impairment, the form of the EPA’s proposed secondary standard was selected to allow 
IV-42 

each area to achieve that level of protection in a way that addresses its own unique mix of 

contributing pollutants. Therefore, the EPA disagrees with the commenter that it is 

inappropriate to use the results of the Phoenix study to inform a range of candidate 

protection levels for consideration by the Administrator in selecting a national level of 

visibility protection. Instead, the EPA believe the Phoenix results form an important data 

point that shed light on public preferences for visibility in western areas with urban 

scenes that include distant mountains. 

(3) Comment: Similar to comment (2) above, Colorado DPHE expressed concern with the 

EPA’s use of the Denver study results in a national context. In particular the commenter 

states: 

The proposed secondary visibility standard relies in part on the Denver urban 

visibility standard as supporting justification for establishing a new secondary 

standard. However, the Denver visibility standard was originally developed in 

1989 in response to a bipartisan directive from the legislature to meet a statutory 

deadline of January 1990 for a standard based solely on aesthetics. The Denver 

visibility standard, set at about 20 deciviews (32 miles or 0.076/km), was based 

on a survey of 214 Denver citizens that evaluated 25 slides of the ‘Brown Cloud’, 

a publically understood name for the strong inversions that occur in the Denver 

metropolitan area. These slides were specifically referenced to data obtained 

using a transmissometer. Thus, this standard is based on a specific view of Denver 

and specific transmissometer location and path and is applicable only to this 

location. This constitutes a limitation with its applicability to a national secondary 

standard, particularly a proposed standard that does not use a direct measurement 

method. ... Visibility from year to year is highly variable.... [A]dditional studies 

are necessary to establish a secondary NAAQS standard, or what might ultimately 

become multiple standards, across the United States” (Colorado DPHE, p. 2-3).

Response: The Colorado comment raises some of the same concerns as the Arizona 

comment and the EPA refers the reader to its response to comment (2) above. In addition, 

this commenter states that the visibility standard is “based solely on aesthetics”. This is 

not a significant difference with the proposed secondary visibility PM NAAQS. While 

qualitative information was also available regarding personal comfort and well being, the 

proposed range of levels considered by the Administrator was derived from the 

quantitative information regarding public preferences for the aesthetic quality of the 

urban view. This commenter also points out that the slides presented to the study 

participants included images of the Brown Cloud that occurs under conditions of a strong 

inversion. The EPA notes that while this condition does not happen everywhere, there are 

other urban areas that experience it and therefore preference information that takes such a 

phenomenon into account provides useful information for the Administrator to consider. 

The commenter further notes that “this standard is based on a specific view of Denver 

and specific transmissometer location and path and is applicable only to this location.” In 

spite of this, however, the EPA observes that Denver still went ahead and established a 

standard that applies to the entire metropolitan area, even though there are many other 

views and paths that could be evaluated. Likewise, the EPA believes it is possible to 

select a national level of visibility protection based on a variety of disparate data points 
IV-43 

for urban visibility preferences, because when taken together, they provide useful 

information regarding the range of scene and site characteristics that can influence public 

perception of acceptable VAQ. While the EPA agrees that additional studies would be 

helpful and provide more useful data points to consider, it does not agree that they are 

necessary to establish a secondary standard.

6. Need for a Distinct Secondary Standard 

a. Comments Supporting a Distinct Secondary Standard 

(1) Comment: Some tribal commenters who supported the proposal to set a distinct standard 

to protect visibility expressed concern about the urban focus of the proposed secondary 

standard for visibility, and urged the EPA to focus on visibility protection in rural areas 

as well. Specifically, they urged the EPA to conduct additional preference studies in rural 

areas, and to expand monitoring in Tribal regions to obtain more information on visibility 

impairment in rural locations. 

Response: The EPA agrees with these commenters that it is important to provide 

protection against PM-related visibility impairment in both urban and rural areas, and that 

it would helpful to have additional preference study data from more locations, including 

rural locations. However, with regard to the commenters’ assertion that the proposed 

secondary standard for visibility would neglect rural areas, the EPA disagrees. The EPA 

has considered both urban and rural areas, and has focused on urban-related visibility 

impairment for a reason. CAA section 109(b) requires the Agency to establish national 

standards to protect the public welfare, which means that the NAAQS are designed to 

protect against adverse impacts in both urban and rural areas. In the case of visibility, the 

EPA has also recognized that the Regional Haze Program under sections 169A and 169B 

of the CAA specifically targets visibility protection in Federal Class I areas, most of 

which are in remote (rural) areas. The goal of the Regional Haze Program is to address all 

man-made impairment of visibility, and the program specifically targets the widespread, 

regionally uniform type of haze caused by a multitude of sources. Over time, the 

Regional Haze Program will provide a level of protection of visual air quality in Class I 

areas that extends far beyond the level of protection envisioned for a secondary NAAQS 

under section 109(b). The EPA notes that any national ambient air quality standard for 

visibility would be designed to work in conjunction with the Regional Haze Program as a 

means of achieving appropriate levels of protection against PM-related visibility 

impairment in all areas of the country, including urban, non-urban, and Federal Class I 

areas. While the Regional Haze Program is focused on improving visibility in Federal 

Class I areas and a secondary visibility index NAAQS would focus on protecting visual 

air quality principally in urban areas, both programs could be expected to provide 

benefits in surrounding areas. Thus, in considering a distinct standard to protect visibility 

impairment under the NAAQS program, the EPA focused particular attention on areas 

not already covered by the Regional Haze Program. This led to a focus on urban air 

quality as a means of ensuring adequate protection of visibility in all locations (i.e. as a 

supplement to the protection already afforded by the Regional Haze Program). 
IV-44 

b. Comments Opposing a Distinct Secondary Standard 

(1) Comment: A number of commenters opposed setting a distinct secondary standard to 

protect visibility on the grounds that existing regulatory mechanisms are adequate to 

protect urban visibility. According to these commenters, the combination of urbanoriented PM control programs and long-term regional haze strategies will effectively 

protect visibility and urban visibility will improve over time without a separate visibility 

NAAQS. These commenters urged the EPA to wait for implementation of the Regional 

Haze Program to achieve visibility improvements and then re-assess whether a secondary 

standard for visibility is warranted. 

Response: While the EPA has determined that a distinct secondary standard to protect 

against visibility impairment is not needed at this time, this decision was based on the 

degree of protection afforded by the existing secondary PM2.5 standards, particularly the 

secondary 24-hour PM2.5 standard of 35 μg/m3. The Regional Haze Program has more 

ambitious goals to be implemented over a longer time period (i.e., to eliminate all manmade impairment in visibility by 2064), and is focused primarily on remote (Federal 

Class I) areas. Therefore, it would not be appropriate to rely solely on that program to 

protect visibility in all areas across the country as required by CAA section 109(b) or to 

wait for the Regional Haze Program to be implemented before evaluating what additional 

protection might be needed for non-Federal Class I areas. The EPA continues to 

emphasize that the secondary PM NAAQS is designed to work in concert with the 

Regional Haze Program to afford the requisite degree of visibility protection in all areas. 

(2) Comment: Some commenters urged the EPA to delay setting a distinct secondary 

standard for visibility pending the establishment of a pilot program to gather additional 

data. For example, NY State Departments of Health and Environmental Conservation 

stated that while they support the promulgation of a secondary standard to protect 

visibility, they “have serious concerns with the proposed method as it fails to be 

temporally and geographically representative of real-world visibility. EPA should 

establish a pilot measurement development program to identify methods that would more 

accurately measure and report real-time visibility conditions to the public” (New York 

DOH/DEC, p. 2). 

Response: While acknowledging the uncertainties and limitations associated with the 

information available in this review, the EPA continues to conclude, as did CASAC, that 

this information provides a sufficient basis for selecting a target level of protection for 

visibility in this review. Thus, the EPA disagrees with these commenters that the 

uncertainties are so significant as to preclude establishing a standard at this time.

(3) Comment: Numerous commenters questioned whether a distinct secondary standard for 

visibility is necessary in light of the EPA’s own analysis as presented in Kelly et al. 

(2012a) which indicated that a 24-hour mass-based PM2.5 standard of 35 μg/m3

 would 

protect against visibility impacts exceeding the range of levels considered in the proposal 

(28-30 dv). Many commenters pointed to this analysis in support of their argument that a 

visibility index standard in the range proposed (28-30 dv) would provide no additional 

protection beyond that afforded by the existing secondary 24-hour PM2.5 NAAQS, and 
IV-45 

therefore no distinct secondary standard to protect visibility was necessary. These 

commenters advocated retaining the current 24-hour PM2.5 mass-based standard to 

protect against visibility effects. “Since the 24-hour PM2.5 standard already protects the 

welfare the 24-hour PM2.5 visibility standard is designed to protect, the new standard is 

duplicative and unnecessary” (South Dakota DENR, p. 2). Michigan DEQ agreed, stating 

it believed “that the visibility index is an unnecessary standard and that the 24-hour 

PM2.5standard should be used as a surrogate for evaluating visibility” (Michigan DEQ, p. 

2). 

Response: The EPA agrees with commenters that Kelly et al. (2012a) indicates that the 

existing 24-hour PM2.5 standard provides at least the target level of protection for visual 

air quality defined by a visibility index set at 30 dv, averaged over 24-hours, with a 90th

percentile, 3-year average form, which the EPA judges appropriate. While the Kelly et al. 

(2012a) analysis was conducted in support of proposed implementation requirements for 

a distinct secondary standard (specifically, the modeling demonstrations that would be 

required under the PSD program), the second prong of the analysis suggested that the 24-

hour PM2.5 standard of 35 μg/m3

 would be controlling relative to a standard based on a 

visibility index set at 30 dv. Kelly et al. (2012a) concluded that the “overall, design 

values based on 2008-2010 data suggest that counties that attain 24-hour PM2.5 NAAQS 

level of 35 μg/m3 would attain the proposed secondary PM2.5 visibility index NAAQS 

level of 30 dv” (pp. 17-18). 

Importantly, the analysis performed by Kelly et al. (2012a) provides an area-by-area 

comparison of the relative degree of protectiveness of the existing secondary 24-hour 

PM2.5 standard and the proposed distinct standard for visibility. This analysis confirms 

that for each area examined, it is highly likely that a standard of 35 μg/m3 would provide 

as much or greater protection than a standard based on a visibility index set at 30 dv. 

Based on 2008-2010 data, it appears that there are no areas that would have exceeded a 

30 dv, 24-hour visibility index standard that would not also have exceeded a 24-hour 

PM2.5 standard of 35 μg/m3. Stated another way, all areas that met the 24-hour PM2.5

standard of 35 μg/m3

 would have had visual air quality at least as good as 30 dv (24-hour 

average, based on 90th percentile form averaged over 3 years). The Kelly analysis also 

shows that for some areas, particularly in the West, areas that would have met a 24-hour 

PM2.5 standard of 35 μg/m3

 would have had visual air quality better than 30 dv for the 

PM2.5 visibility index standard, and that at sites that violated both the 24-hour level and 

the secondary visibility index 30 dv level, the visibility index level of 30 dv would likely 

be attained if PM2.5 concentrations were reduced such that the 24-hour PM2.5 level of 35 

μg/m3 was attained. 

Moreover, the EPA has conducted a reanalysis (Kelly et al., 2012b) that confirms the 

results of the original Kelly et al. (2012a) memo. This reanalysis updates the area-by-area 

analysis in Kelly et al. (2012a) in three respects. First, noting that the original Kelly et al. 

(2012a) analysis used a 1.4 multiplier to convert OC to OM at those monitors not using 

the new CSN monitoring protocol, the EPA recalculated the visibility index design values 

for 2008-2010 using a higher multiplier for converting OC to OM at monitors not already 

using the new CSN monitoring protocol SANDWICH approach, consistent with the 

Agency’s view that it is more appropriate to use a multiplier of 1.6 at such monitors as 
IV-46 

compared to 1.4, as described in section VI.C.1.a.ii of the preamble to the final rule and 

discussed in response to comments on indicator in section IV.B.1, above. The 

recomputed visibility design index values for 2008-2010 show the same overall 

relationship to 24-hour PM2.5 design values as presented in Kelly et al., 2012a. 

Second, the EPA repeated the calculations comparing visibility index design values with 

24-hour PM2.5 design values using 2009-2011 data, the most recent three years of air 

quality information currently available. Third, the EPA modified the area-by-area 

evaluation to ensure consistency with the data completeness criteria of 40 CFR part 50, 

Appendix N, including the removal of data approved by EPA as exceptional events, for 

the current 24–hour PM2.5 standard and the proposed visibility index standard. 

The results of this reanalysis, as presented in Kelly et al. (2012b), show a similar pattern 

to that described in the original Kelly memo. Specifically, the analysis indicates that there 

were no areas with visibility impairment above 30 dv that did not also exceed the 

secondary 24-hour PM2.5 standard of 35 μg/m3. The updated memo concludes that the 

results for 2009-2011 corroborate the findings for 2008-2010. 

Based on these analyses (Kelly et al., 2012a; 2012b), the EPA concluded with a high 

degree of confidence that having air quality that meets the 24-hour PM2.5 standard of 35 

μg/m3

 would be sufficient to ensure areas would not exceed 30 dv. 

However, the EPA also recognizes that it is important to evaluate whether such a 

standard would be over-protective (i.e. more stringent than necessary to protect public 

welfare). The analyses presented in Kelly et al. (2012a; 2012b) indicates that the 24-hour 

PM2.5 standard of 35 μg/m3

 would achieve more than the target level of protection of 

visual air quality (30 dv) in some areas. That is, when meeting a mass-based standard of 

35 μg/m3, some areas would have levels of PM-related visibility impairment far below 30 

dv. Thus, when considered by itself and without consideration of the secondary standards 

adopted for purposes of non-visibility welfare effects, the 24-hour PM2.5 standard of 35 

μg/m3 would be over-protective of visibility in some areas. However, it is important to 

note that as long as the current secondary 24-hour PM2.5 standard of 35 μg/m3

 remains in 

effect, this overprotection for visibility would occur, regardless of whether a distinct 

secondary standard based on a visibility index set at 30 dv were adopted. These issues are 

discussed more fully in section VI.D of the preamble which outlines the Administrator’s 

final conclusions on the secondary PM standards. 

(4) Comment: A number of commenters noted that the proposed secondary standard for 

visibility would not offer significant additional protection beyond the primary standard 

and yet would place an additional burden on states charged with monitoring and 

complying with the standard. These commenters objected to the additional resource 

burden associated with implementing a standard which had, in their view, no practical 

effect: “If the 24-hour PM2.5 mass standard has the same effect as the visibility standard, 

crafting complex regulations to implement another standard seems redundant” (South 

Carolina DHEC, p. 3). Other commenters agreed: “A PM2.5-related Visibility Index 

appears redundant since the benefits achieved from the current primary and secondary 

annual and 24-hour PM2.5 standards already provide reductions that would improve 
IV-47 

visibility. Establishing a new PM2.5 secondary standard for visibility would be an 

additional complication and burden to the states that is not warranted” (Indiana DEM, p. 

5). Similarly, Florida DEP argued that “While urban visibility is indeed a welfare issue, 

the standard as proposed would require unwarranted resource efforts to verify, validate 

and calculate the visibility parameters, complete the designation process, and revise the 

State Implementation Plan (SIP). These efforts would be fruitless in 49 states where the 

standard is either currently met or will be met without additional regulation. It is 

inappropriate to promulgate a national standard to affect the air quality in three counties 

of one state (i.e., California)” (Florida DEP, p. 1). 

Response: The EPA disagrees with commenters who stated that implementation 

concerns, in particular the additional resource burden associated with implementing a 

distinct secondary standard, should alter the Agency’s decision making with regard to a 

standard to protect visibility. The EPA may not take the costs of implementation into 

account in setting or revising the NAAQS. The EPA’s decision not to establish a distinct 

secondary standard to protect against PM-related visibility impairment is based entirely 

on the degree of protection that would be afforded by such a standard if adopted with the 

indicator, averaging time, form and level judged appropriate by the Administrator, as 

compared to the degree of protection afforded by the existing secondary 24-hour PM2.5

standard. 

7. Specific Comments on Surrogacy Analysis 

(1) Comment: Several commenters submitted additional analyses supporting their position 

that a 35 μg/m3

 24-hour PM2.5 standard would provide at least equivalent protection to a 

distinct 24-hour visibility standard within the range of levels proposed (API, Attachment 

2, p. 8 and Attachment 3, p. 1). 

Response: The EPA agrees with commenters that Kelly et al. (2012a) indicates that the 

existing 24-hour PM2.5 standard provides at least an equivalent measure of protection a 

distinct 24-hour visibility index set at 30 dv with a 90th percentile, 3-year average form, 

which the EPA judges appropriate. Importantly, the analysis performed by Kelly et al. 

(2012a) provides an area-by-area comparison of the relative degree of protectiveness of 

the existing secondary 24-hour PM2.5 standard and the proposed distinct standard for 

visibility. The Kelly analysis also confirms that for each area examined, it is highly likely 

that a standard of 35 μg/m3

 would provide as much or greater protection than a standard 

based on a visibility index set at 30 dv. The EPA acknowledges that the conclusions from 

the additional analyses submitted by the commenters are supportive of the Agency’s 

decisions to retain the current suite of secondary PM standards and to not establish a 

distinct secondary standard for protection from visibility impairment. However, the EPA 

did not rely upon these additional analyses from the commenters to inform its decisions. 

Rather, the agency based its conclusions on the analysis performed by Kelly et al. 

(2012a).

(2) Comment: Three environmental commenters (Appalachian Mountain Club, National 

Parks Conservation Association, and Earthjustice) made several comments that 

questioned the technical analysis of the Kelly et al. memo (2012a) that provided the 
IV-48 

justification of the surrogacy policy, specifically the area by area evaluation where EPA 

compares the design values of various areas to see if areas that attain the mass-based 

standard are also likely to attain the distinct secondary standard to protect against 

visibility impairment. These commenters claimed that “the analysis actually reaffirms 

that the mass-based standard is not a reasonable predictor, but EPA sweeps these 

concerns away with generalized and conclusory claims. Figure 6 in the memo by Kelly, 

et al., shows again that the correlation between meeting the 24-hour mass standard and 

meeting the visibility standard varies significantly from region to region.” The 

commenters also stated that “Even more important than the fact that there is no regional 

consistency in the correlation between the mass and visibility standards is the fact that 

any linear relationship does not extend to zero.” (AMC, et al., p. 11) 

Response: As shown in Figure 6 of Kelly, et al. (2012a), the differences in 24-hr PM2.5

and visibility index design values across different regions of the country do not detract 

from the EPA’s analysis as the commenters suggest. While distinct regions of the country 

have distinct relationships between the 24-hr PM2.5 design value and the secondary 

visibility index design value, the relationship in all regions is such that an area that meets 

the secondary 24-hr PM2.5 standard would also attain the proposed visibility index 

standard level of 30 dv, and all areas except the Industrial Midwest would attain the 

proposed level of 28 dv. It is also not possible to examine the relationship for design 

values near zero since such levels do not occur in the ambient atmosphere. However, this 

situation does not limit our analysis which focuses on the potential impact of sources on 

design values under realistic atmospheric conditions.

(3) Comment: These environmental commenters claim that the plot in Figure 6 of Kelly, et 

al. (2012a) “suggests that an area can be closer to a violation of the visibility standard 

even when further from a violation of the mass standard. This is demonstrated by the fact 

that it is more likely to find an area violating a visibility standard of 28 dv and still 

meeting the mass-based standard of 35 μg/m3

 than the other way around (i.e., violating 

the mass standard but meeting the visibility standard).” (AMC, et al., p. 11) 

Response: The EPA does not believe that comparing the closeness of the site-specific 

design values to each standard level is a valid way to examine the relationships between 

design values. Instead, the trend in the data shown in Figure 6 of Kelly et al. (2012a) 

from the lowest design values to the highest design values should be considered for each 

region since that trend is the best guide to the likely relationship between ambient mass 

concentrations and visibility index values in these regions. Trends in Figure 6 indicate 

that design values in each region would follow a path where exceedance of the 30 dv 

visibility index level would not occur without the secondary 24-hr PM2.5 standard level of 

35 μg/m3 also being exceeded. Moreover, the commenters are inappropriately comparing 

design values across different regions in the statement about areas being more likely to 

violate a visibility index level of 28 dv while meeting the secondary 24-hr PM2.5 standard 

level of 35 μg/m3 than the other way around. 

(4) Comment: These commenters took issue with the EPA’s suggestion that the regional 

differences will be minimized over time because federal control measures will reduce 

sulfate levels in the Midwest. The commenters argued that the EPA had made an 
IV-49 

unreasonable claim that in a few years the correlation between attaining the two standards 

would get “better” so it is acceptable to allow the surrogacy approach now. The 

commenters further stated that the EPA does not provide details on the time horizon or 

magnitude of such improvement. As a result, the commenters concluded that unless and 

until there is a change in this correlation, there is not reasonable basis for allowing the 

proposed surrogacy approach. 

Response: The discussion of federal control measures was not related to minimizing 

regional differences between 24-hr PM2.5 design values and visibility index design 

values. Instead, the control measures were mentioned to indicate that the few observed 

cases in the Industrial Midwest where the proposed visibility index level of 28 dv is 

exceeded in current air quality data while the 24-hr standard level is attained would be 

less likely to occur in the future due to ongoing control programs. However, the results of 

the analysis of 2008-2010 data presented in Kelly et al. 2012a (and the results of the 

reanalysis using updated 2009-2011 air quality data presented in Kelly et al. 2012b) 

indicate that, in all regions of the U.S., an area that met the 24-hr PM2.5 standard would 

also have attained the proposed visibility index standard level of 30 dv and thus support 

the use of the surrogacy approach. 

(5) Comment: The commenters also added a footnote stating that “As with other EPA 

regulatory decisions that have relied on EPA’s Cross-State Air Pollution Rule, the D.C. 

Circuit’s recent vacature of the rule undermines EPA’s argument. See EMA Homer City 

Generation v, EPA, 2012 WL 3570721, (D.C. Cir. Aug. 21, 2012). Unless and until the 

court’s vacature is reversed, EPA has no basis for claiming that the rule will change the 

current mix of air pollutants.” (AMC, et al., p. 11) 

Response: The EPA’s analysis and discussion as presented in Kelly et al. (2012a) does 

not rely on the Cross-State Air Pollution Rule, nor are the conclusions drawn by the EPA 

with regard to the results presented in this analysis dependent on implementation of the 

Cross-State Air Pollution Rule. 

8. Legal Issues 

Some commenters argued that the entire approach proposed by the EPA is inconsistent 

with the requirements of CAA section 109(b). They pointed to a number of different aspects of 

the proposal which in their view made it incompatible with the CAA. For example, UARG 

stated: 

In the past, EPA has always used a measure of PM mass as the indicator for both primary 

and secondary PM NAAQS. Such a standard is, as a general matter, consistent with the 

directive in the CAA that the NAAQS “specify a level of air quality” and targets for 

control the listed criteria air pollutant. CAA § 109(b)(2). The standard contained in 

EPA’s proposed rule does neither of these things. Instead, it would (1) regulate relative 

humidity, which is not a criteria pollutant; (2) fail to “specify a level of air quality” as 

required by section 109(b)(2) of the CAA; and (3) result in a standard necessitating 

nationally variable PM concentrations instead of a standard establishing a nationally 

uniform, minimally acceptable PM concentration. (UARG, p. 22-23) 
IV-50 

Other commenters raised similar or related issues, arguing that the EPA improperly set a 

visibility standard, and not a PM2.5 standard, and that NAAQS can only be set in terms of a level 

or concentration of the air pollutant. Commenters also argued that an endangerment finding and 

air quality criteria would be needed before the EPA could set a standard based on PM 

components. Each of these comments is discussed below. 

As a general matter, it should be noted that the EPA disagrees with the points raised by 

these commenters. While the EPA is not adopting the proposed secondary standard, this decision 

is not based on concern over the EPA’s authority to adopt a secondary standard such as the one 

proposed. 

(1) Comment: Some commenters argued that the proposed standard is unlawful because it is 

“not a PM2.5 standard at all, but rather a visibility standard, and visibility is neither an air 

pollutant nor a criteria pollutant for which a NAAQS may be promulgated” 

(NMA/NCBA, p. 21). According to these commenters, the CAA requires that NAAQS be 

established as limits on the concentration of an air pollutant in ambient air, not limits on 

the “identifiable effects” caused by that air pollutant. These commenters claimed that 

reduced visibility due to light extinction is not an air pollutant but instead is an effect, 

noting that “the Act’s definition of ‘air pollutant’ speaks in terms of specific substances 

or matter in the ambient air” (National Stone Sand and Gravel Association, p. 8). The 

commenters pointed to the use of the term “air pollutant” in sections 109(a)(1)(A) and 

(b)(2) as support for their argument, as these provisions refer to setting standards for the 

“air pollutant” to address the effects associated with the presence of the air pollutant in 

the ambient air. They likewise pointed to section 108(a)(2)’s reference to the presence of 

the air pollutant in the ambient air. Since reduced visibility is not an air pollutant, they 

argue the EPA cannot set a NAAQS that is a standard for visibility. They argue that the 

proposed secondary standard it is not a PM2.5 standard as it does not limit the 

concentration of PM2.5 or any other fraction of particulate matter in the ambient air and 

therefore is not an “ambient air quality standard” for any pollutant. 

Response: The EPA disagrees with these commenters. The proposed distinct secondary 

standard was a standard for PM2.5, and was not a “visibility standard.” The proposed 

secondary standard was based on the mass concentration of PM2.5 in the ambient air. The 

standard was defined in terms of calculated PM2.5 light extinction, which is based on the 

measurement of the mass concentration of ambient PM2.5 over a 24-hour period. Under 

the proposed approach, the measured mass concentration would be adjusted based on 

information on the speciated mass components of the PM2.5 and the relative humidity, 

resulting in a calculated visibility index. The level of the visibility index, combined with 

the form of the standard and averaging time, would identify whether a level of ambient 

mass concentration of PM2.5 achieved the standard or not. Given any specific mass 

concentration of ambient PM2.5, combined with information on speciation and relative 

humidity, it could be determined whether the specific mass concentration of ambient 

PM2.5 achieved the NAAQS. Hence, the proposed secondary NAAQS clearly specified 

acceptable levels of ambient mass concentration of PM2.5. 

The combination of indicator, averaging time, form, and level of the proposed NAAQS is 

designed to provide the appropriate degree of protection from visibility impairment 
IV-51 

caused by ambient levels of PM2.5. It does this by calculating the light extinction 

associated with ambient concentrations of PM2.5 and specifying the level of acceptable 

PM2.5 mass concentration in terms of this calculation. However this does not change the 

fact that the standard is for the air pollutant PM2.5, and defines acceptable ambient levels 

of this air pollutant. It does not transform the standard into a “visibility standard” and not 

a standard for PM2.5. 

(2) Comment: One commenter argued that the EPA is required to “specify a level of air 

quality” under section 109(b)(2), which Congress intended as an acceptable concentration 

level of the air pollutant in the ambient air, noting that specification of acceptable 

visibility conditions is not the same as an acceptable air pollution concentration level. 

Citing American Farm Bureau v. EPA, 559 F.3d at 516, one commenter claimed that the 

court had affirmed that “the NAAQS—whether primary or secondary—is a mass-based 

standard” (Nevada DEP, p. 5). Commenters also refer to the legislative history of the 

1970 amendments, referring to NAAQS as setting the “maximum permissible ambient air 

level” for an air pollutant. The commenters argue that the proposed secondary standard is 

improper because it would not limit the concentration of PM2.5 or any fraction of PM in 

ambient air, but would improperly set a limit on visibility effects. 

Response: The EPA disagrees with these commenters. The text of sections 108 and 109 

does not support the limited interpretation commenters suggest. Instead, these provisions 

provide the EPA with significant discretion in determining the metric for air quality that 

is appropriate to achieve the required degree of protection of public welfare. The 

commenters’ interpretation would improperly limit this discretion, interfering with 

achieving the goals of section 109(b). 

The term “concentration” typically means some measure of relative content, including 

relative measures such as mass per unit of volume or parts per million. The EPA has 

often used such metrics to define the NAAQS, largely because the scientific evidence of 

health or welfare effects supporting the NAAQS typically use such metrics in air 

pollution studies. For example, the current secondary standards for PM are defined in 

terms of the concentration of PM2.5 and PM10 in the ambient air, measured as the dried 

mass of the particulate matter per unit of air. However section 109(b) does not require 

that a NAAQS be defined this way. 

Sections 109(a) and (b) both use the general term “air quality” when discussing the 

EPA’s obligation to set NAAQS. The NAAQS are clearly national ambient “air quality” 

standards under section 109(b), which specifies that the primary NAAQS “shall be 

ambient air quality standards” and the secondary NAAQS “shall specify a level of air 

quality.” Both the primary and secondary NAAQS are to be based on the “air quality 

criteria,” which are to accurately reflect the latest scientific knowledge on the effects on 

public health and welfare associated with “the presence of such air pollutant in the 

ambient air, in varying quantities.” Section 109(b), 108(a)(2). Congress spoke in broad 

terms, tasking the EPA with assessing the latest scientific knowledge about the public 

health and welfare associated with the presence of the pollutant in the air, without 

limiting this to consideration of only those effects associated with one or more measures 

of concentration of the air pollutant. Congress referred to any and all effects associated 
IV-52 

with the presence of the pollutant in the ambient air, not just the effects associated with 

the concentration of the pollutant in the ambient air. Based on this knowledge, the EPA is 

required to set standards for the quality of the air that will provide the appropriate degree 

of protection from these health and welfare effects, without limitation on how to measure 

or define air quality. While concentration in the air has typically been an appropriate way 

to set a standard to achieve these requirements, the more general terms used in section 

108(a) and 109(b) do not limit the EPA to using concentration as the only way to measure 

air quality for purposes of setting a NAAQS. The EPA is charged with setting air quality 

standards, and has the discretion under section 109(b) to choose the metric for defining 

air quality that is appropriate to address the health or welfare effect at issue. 

Congress did refer to “concentration” in certain situations. In section 109(c) Congress 

required the EPA to set a primary NAAQS for NO2 concentration over 3 hours. This 

addressed Congress’ concern over whether the then current NO2 standard, which used 

concentration as a metric, provided adequate protection. Congress also called on CASAC 

to advise the Administrator on the relative contribution to “air pollution concentrations” 

of natural and anthropogenic sources, under section 109(d)(2)(C)(iii). This information is 

in addition to the advice CASAC is required to provide concerning appropriate revisions 

to the “air quality criteria” and to the NAAQS under section 109(d)(2)(B). While these 

provisions refer to ambient concentrations of pollutants, this reflects the EPA’s standard 

practice to date in setting NAAQS, and none of them change or limit the range of 

discretion provided under section 109(b) in setting NAAQS. They do not change the fact 

that the EPA is to set “air quality” standards, and is not limited to “air concentration” 

standards. The reference in the legislative history to a maximum permissible ambient air 

level for the pollutant also does not limit the EPA to a level of air pollutant concentration, 

as compared to a different metric for specifying the level of air quality, if that is judged to 

be appropriate. 

(3) Comment: Some commenters argued that the proposed standard improperly regulates 

relative humidity because it is included in the calculation to determine the value of the 

visibility index. According to these commenters, the CAA allows the EPA to control 

criteria air pollutants through the NAAQS program, but not other various substances. The 

commenters stated that the EPA recognized this in the last review, treating humidity as a 

confounding factor and considering addressing it by measuring PM2.5 mass-based 

concentration over the midday hours, when humidity would have the least effect. This 

would target the effects caused by PM, and not by humidity. Referring to American Farm 

Bureau v. EPA, 559 F.3d 512, 528 (D.C.Cir. 2009) and 77 Fed. Reg. at 38979 n.153. 

UARG contested the proposed calculated visibility index as it does not approach relative 

humidity as a confounding factor but instead “embraces it and treats it as if it were a PM 

effect” (UARG, p. 24). 

Response: Contrary to the claims of these commenters, the use of calculated PM2.5 light 

extinction does not regulate relative humidity. The proposed secondary standard would 

define acceptable levels of ambient PM2.5, not acceptable levels of relative humidity. In 

addition, section 108 explicitly requires that the air quality criteria include information on 

the atmospheric conditions that can alter the effects of the air pollutant on public health 

or welfare, and relative humidity certainly has this kind of impact. Section 109(b) 
IV-53 

requires that the standard be based on the air quality criteria, indicating that this 

information can and should be taken into account in setting the standard. Including 

relative humidity as an adjustment factor in the calculation of PM2.5 light extinction is a 

reasonable and straightforward way to use the scientific information in the air quality 

criteria in establishing a standard to provide protection from visibility impairment. 

The EPA disagrees with commenters that the EPA’s treatment of humidity in this review 

is inconsistent with its handling of this issue in the previous review. In the last review, the 

EPA considered a distinct PM2.5 mass-based secondary standard. In that context, limiting 

the measurement of PM2.5 mass concentration to the mid-day hours when relative 

humidity had the least impact would promote the correlation between measured PM2.5

mass concentration and light extinction, which would promote achievement of a 

relatively consistent degree of visibility protection across the country. However in this 

rulemaking the proposed calculated PM2.5 light extinction standard achieves a consistent 

degree of visibility protection by directly accounting for humidity, in a scientifically 

defensible manner. The goal has not changed – achieving the desired degree of protection 

across the country. What has changed is that calculated PM2.5 light extinction is a more 

direct and scientifically appropriate way to achieve that result. 

Finally, it should be made clear that water is not a separate compound from PM2.5 that 

confounds the impact PM2.5 has on light extinction. As described in the Integrated 

Science Assessment, “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” (U.S. EPA, 2009a, p. 1-4). “Particles composed of water 

soluble inorganic salts (i.e., ammoniated sulfate, ammonium nitrate, sodium chloride, 

etc.) are hygroscopic in that they absorb water as a function of relative humidity to form a 

liquid solution droplet. Aside from the chemical consequences of this water growth, the 

droplets become larger when relative humidity increases, resulting in increased light 

scattering. Hence, the same PM dry concentration produces more haze” (U.S. EPA, 

2009a, p. 9-6). Thus water is not a compound that is separate and apart from the particle 

that acts as an extraneous confounding factor. The effect of relative humidity occurs after 

the water becomes part of the particle. Certain water soluble salts absorb water and the 

resulting particle is larger in size and scatters more light, increasing the visibility impact 

of the particle. But the particle is still a PM2.5 particle. The fact that the PM NAAQS 

traditionally uses a measurement of the dried mass of the particles as the metric for the 

standard does not change the fact that the particles in the air include liquid droplets and 

particles that have increased in size because of absorption of water. These ambient PM2.5

particles are what are in the air and impacting visibility, not just the dried mass of PM2.5

that is measured in the laboratory and is currently used as the indicator for the PM 

NAAQS. Thus, the commenters improperly claimed that the proposed secondary standard 

regulates water or relative humidity, and not PM2.5, when in fact the proposed secondary 

standard accounts in a scientific manner for the fact that some PM2.5 particles are larger 

in size and have a greater impact on light extinction when the relative humidity increases. 

(4) Comment: The commenters also stated that the use of a calculated visibility index, and 

the failure to exclude the effects of humidity, would result in acceptable PM 

concentrations that vary across the nation. These commenters claimed that such a 
IV-54 

standard is inconsistent with the requirements of the CAA because the proposed approach 

fails to establish a nationally uniform PM concentration standard. For example, API 

argued that the proposed visibility index approach is “essentially specifying levels—not a 

level—of air quality” (API, p. 29). UARG agreed, and stated that the Act “requires that 

criteria pollutant concentrations throughout the nation reach, at the least, a single, 

specified ambient concentration level” (UARG, p. 25, emphasis in original). The 

commenters argue that a PM2.5 visibility index standard cannot provide equal protection 

nationwide due to geographic variation in key factors such as relative humidity that affect 

level of particles allowed in different areas. The commenters noted that establishing a 

single national level for the PM2.5 visibility index would necessarily result in unequal 

acceptable PM2.5 levels in different areas of the country, with lowest allowable PM2.5

levels in urban areas in the Southeast and highest allowable levels in the arid West. 

UARG recognized that under section 108 the air quality criteria are to “address those 

variable factors (including atmospheric conditions) which of themselves or in 

combination with other factors may alter the effects on public health or welfare of such 

air pollutant,” but stated that while section 108 “allows” this, it has no bearing on this 

issue. Instead, the commenter stated that the EPA may take such information into account 

in setting a permissible concentration of the pollutant that is uniform and national 

(UARG, p. 25). 

Response: The EPA disagrees with commenters that section 109(b) requires that the 

NAAQS set a single, specified ambient concentration that is nationally uniform across 

the country. As discussed above, the text of section 109(b) does not specify this limitation 

of a single national acceptable concentration. Instead the secondary NAAQS is to specify 

a level of air quality that achieves the appropriate degree of protection. The proposed 

secondary standard would do just that – specify a level of air quality, defined in terms of 

calculated PM2.5 light extinction, that would achieve the desired degree of protection. The 

fact that this results in varying allowable levels of PM2.5 mass concentrations is not 

inconsistent with the Act. The D.C. Circuit recently approved such a result. In the last 

review of the PM10 primary NAAQS, the court approved the EPA’s choice of an 

indicator that was designed to allow varying levels of acceptable coarse PM. The court 

stated that: 

The industry petitioners next argue that the 150 μg/m3 standard for PM10 will result in 

arbitrarily varying levels of coarse PM, and that the agency should instead have used a 

PM10-2.5 indicator. The EPA does not dispute that using the PM10 indicator will result in 

coarse PM levels that vary within the limit of 150 μg/m3. As the EPA explains: “Because 

the PM10 indicator includes both coarse PM (PM10-2.5) and fine PM (PM2.5), the 

concentration of PM10-2.5 allowed by a PM10 standard set at a single level declines as the 

concentration of PM2.5 increases. Thus, the level of coarse particles allowed varies 

depending on the level of fine particles present.” Id. at 61,195. 

Although the EPA acknowledges that a PM10 indicator will result in varying coarse PM 

levels, it does not agree that the variance will be arbitrary. The EPA agrees with the 

industry petitioners that protection from coarse particles should be targeted at urban 

areas, where coarse particles have been shown to pose the greatest danger. Id. at 61,194. 

But the agency argues that targeting of urban areas is effectively accomplished by using 
IV-55 

an indicator that permits the varying levels that the industry petitioners challenge. ... Id. 

at 61,195-96 (citations omitted). In other words: “The varying levels of coarse particles 

allowed by a PM10 indicator will therefore target protection in urban and industrial areas 

where the evidence of adverse health effects associated with exposure to coarse particles 

is strongest.” Id. 

The EPA also offers a further rationale for tying the stringency of coarse PM regulation 

to increases in the level of PM2.5. ... EPA argues that it is “logical to allow lower levels 

of coarse particles when fine particle concentrations are high. . . . [I]nclusion of PM2.5 in 

the PM10 indicator for purposes of coarse particle protection would appropriately reflect 

the contribution that contaminants emitted in fine particle form can make to the overall 

health risk posed by coarse particles.” Id. 

In sum, we find that the EPA has provided a reasonable explanation for its decision[ ] ... 

to utilize a standard that allows targeted variance in coarse PM levels in an inverse 

relationship to the amount of fine PM in the air. American Farm Bureau v. EPA, 559 F.3d 

512, 534-5 (D.C.Cir. 2009). 

A similar result applies here. Under the proposed secondary standard there would be a 

single level of air quality specified for the NAAQS. The standard would apply across the 

nation; it would not be a regional standard. The proposed standard would be the same 

standard everywhere—the acceptable level of mass concentration of PM2.5 would be 

defined the same way across the nation, using the same method of calculating the 

allowable concentration of PM2.5. The same degree of protection from visibility 

impairment would apply across the country. While the allowable amount of PM2.5 could 

vary, this would be a reasoned way to achieve the desired degree of protection from 

visibility impairment. The requirements of section 109(b) would be satisfied. 

(5) Comment: Some commenters opposed to the proposed distinct secondary standard argued 

that in order to base a standard on measured levels of several speciated substances, the 

EPA must first make an endangerment finding and issue air quality criteria for each of 

the speciated substances included in the calculation of PM2.5 light extinction. According 

to these commenters, “EPA cannot use NAAQS to indirectly regulate multiple substances 

which are not criteria pollutants under the guise of establishing a visibility standard” 

(NMA/NCBA, p. 21). Noting that air quality criteria for particulate matter were issued in 

1969, NMA/NCBA argued that the 1969 Criteria Document “did not establish air quality 

criteria for individual constituents that occur in particle form, instead it established 

criteria for particulate matter as a whole” (p. 27). In light of the fact that criteria have 

never been issued for “individual speciated components of particulate matter,” these 

commenters argued, “if EPA wishes to promulgate a rule such as its secondary visibility 

NAAQS, it first must make a finding that the speciated components listed in Appendix N 

endanger public health or welfare and then issue an air quality criteria document for those 

components” (NMA/NCBA, p. 29). According to these commenters, the approach the 

EPA adopted in promulgating a NAAQS for lead supports this view: 

When EPA promulgated a NAAQS for lead, an individual substance in particle 

form, it did not assert that an endangerment finding or criteria document for lead 
IV-56 

was unnecessary because lead was already covered by the PM Criteria Document. 

Instead, EPA complied with the Section 108 and 109 NAAQS prerequisites for 

lead, just as it must do for Appendix N substances if it intends to promulgate a 

NAAQS for those substances. ... [In 1976], EPA listed lead as an air pollutant 

that adversely affected public health or welfare, issued an air quality criteria 

document for lead, and promulgated a NAAQS for lead. 43 Fed. Reg. 46246 (Oct. 

5, 1976). (NMA/NCBA, p. 29) 

Response: The EPA strongly disagrees with commenters the Agency would need to issue 

a separate endangerment finding and establish air quality criteria for each of the speciated 

substances included in the calculation of PM2.5 light extinction prior to setting a distinct 

secondary standard based on a PM2.5 visibility index, as proposed. The proposed standard 

would set an allowable limit on ambient concentrations of PM2.5. Information on both the 

speciated components of PM2.5 and the relative humidity affect how much light extinction 

is associated with any specific level of PM2.5, but the standard would be for PM2.5. The 

D.C. Circuit has made it clear that PM2.5, just like PM10 and TSP before that, is an 

appropriate subset of PM for the EPA to focus on in setting the NAAQS based on the 

scientific evidence before the EPA. This focus of the NAAQS does not make the subset a 

new pollutant that requires listing and new air quality criteria under section 108 before 

setting a NAAQS. American Trucking Association et al. v. EPA, 175 F.3d 1027, 1055 

(D.C.Cir. 1999). Commenters’ interpretation would apply to PM2.5 as well as to 

components of PM2.5, and is inconsistent with the ATA decision. In addition, it is clear 

that the current air quality criteria do address the scientific basis for calculating PM2.5

light extinction as the EPA proposed (U.S. EPA, 2009a, pp. 9-5 to 9-8). 

(6) Comment: UARG argued that the EPA has in the past recognized that the secondary 

NAAQS is an inappropriate vehicle for regulating PM-related visibility, referring to 62 

Fed. Reg. at 38680, including fn 49. UARG claimed the same situation continues, and the 

EPA has not provided a valid basis for changing this conclusion. 

Response: UARG mischaracterized the EPA’s past decision-making. In past reviews the 

EPA has been clear that the EPA should take into account the existence of the visibility 

program under section 169A, the regional haze program, when considering a secondary 

NAAQS and should not treat the secondary NAAQS as the sole mechanism to address 

visibility impairment across the country. That is the approach the EPA has taken in this 

and prior reviews. See 77 FR at 38990. 

9. Other Issues 

(1) Comment: A large number of commenters expressed confusion and concern over 

differences between the proposed visibility index standard and the Regional Haze 

Program. This included commenters who supported setting a distinct secondary standard 

to protect visibility as well as those opposed to setting such a standard. Many of these 

comments focused on concerns relating to implementation challenges that might be 

caused by overlap between the programs. These concerns included: 

 Visibility impairment would be assessed differently under the two approaches due to 

differences in the way light extinction is calculated, including different IMPROVE 
IV-57 

equations and differences in the inclusion and weighting of specific species and 

components. This would mean having two different regimes for managing visibility 

impairment in the exact same location. 

 Since data from the IMPROVE monitoring network would inform nonattainment 

designations, as well as an area’s obligations under the Regional Haze Program, there 

could be considerable confusion over how to draw nonattainment boundaries and 

what requirements would affect large sources in rural areas. 

 There would be a large resource burden associated with maintaining two different 

programs aimed at protecting visibility in the same geographic area. 

Response: Though the EPA’s decision not to establish a distinct secondary standard for 

protection from visibility impairment at this time renders these comments moot, the EPA 

disagrees with commenters in principle that implementing two programs for visibility 

protection simultaneously would be overly burdensome. Since the same data can be used 

to calculate both visibility impairment under the Regional Haze approach and the 

proposed visibility index, the additional calculation burden for state and local agencies 

would be light. Also, to the extent that there is any difference in terms of the emissions 

control obligations the two different programs would impose upon state and local areas, 

this is likely appropriate given the extent and nature of visibility impairment in those 

areas. The EPA notes that in general, there is likely to be substantial overlap in the 

control strategies a state or local area would pursue under either program. 

(2) Comment: Noting concerns about overlap with the Regional Haze Program, some 

commenters argued that a visibility NAAQS should not apply to rural areas. The 

Department of the Interior requested that the EPA clearly define the geographic area to 

which the visibility index standard would be applicable, and suggested that Class I and 

Class II areas should generally be excluded from the standard. 

Response: The EPA disagrees with these commenters that it would be appropriate to 

exclude some areas from coverage under a secondary NAAQS to protect visibility. CAA 

section 109(b) requires the Agency to establish national standards to protect the public 

welfare, and that the specific requirements laid out in the proposal for the distinct 

secondary standard would ensure that the protection it afforded would be appropriately 

targeted toward urban areas so that it could work in conjunction with—not be in conflict 

with—the Regional Haze Program under sections 169A and 169B of the CAA. While it 

is true that the Regional Haze Program under sections 169A and 169B of the CAA also 

targets visibility protection (focusing on Federal Class I areas), the EPA notes that areas 

affected by both programs would find substantial complementarities among the controls 

necessary to meet the requirements associated with each program. 

Comment: A number of commenters questioned the need for a distinct secondary 

standard to protect visibility, arguing that the existing primary PM standards combined 

with the Regional Haze Program ensured adequate protection of visibility, even in urban 

areas. 

Response: The EPA notes that the objectives of the Regional Haze program are distinct 
IV-58 

from the objectives of the proposed secondary standard. While the Regional Haze 

program is designed to eliminate man-made impairment of visibility in Federal Class I 

areas over the course of several decades, a distinct secondary standard for PM-related 

visibility impairment would be focused on providing a nationally applicable level of 

protection for all areas, particularly urban areas which do not receive targeted protection 

under the Regional Haze Program. Moreover, the metric used to assess visibility 

impairment differs between the two programs precisely because each program is aimed at 

a different aspect of the problem. Recognizing the importance of fresh emissions for 

urban visibility, the Visibility Assessment focused on visibility impairment as measured 

by the original IMPROVE equation because “the original version is considered more 

representative of urban situations when emissions are still fresh rather than aged as at 

remote IMPROVE sites” (U.S. EPA, 2010b, p. 3-19). The Regional Haze Program, on 

the other hand, has shifted to a revised IMPROVE algorithm more suited to remote 

locations. While this difference is discussed in more detail with regard to comments on 

indicator, above, and in section VI.C.1.b of the preamble, the result is that each program 

would appropriately measure those aspects of visibility impairment most closely related 

to the problem the program is trying to prevent. 

Thus, the EPA disagrees with commenters who stated that a distinct standard to address 

visibility impairment as proposed would inherently conflict with the Regional Haze 

Program or that it would be appropriate to draw geographical distinctions that would 

explicitly exclude some areas (e.g., Class I areas) from the NAAQS. The EPA notes that 

the CAA requires that NAAQS be national in scope, and that the specific requirements 

laid out in the proposal for the distinct secondary standard would ensure that the 

protection it afforded would be appropriately targeted toward urban areas so that it could 

work in conjunction with—not be in conflict with—the Regional Haze Program under 

sections 169A and 169B of the CAA. 

(3) Comment: The EPA received numerous comments on data handling related to the 

proposed secondary standard for PM-related visibility impairment, including 

minimum number of PM-component measurement days, treatment of missing data, 

rounding or truncation protocols and assignment of relative humidity weighting factors to 

monitored locations. 

Response: In light of the Agency’s decision not to establish a distinct secondary standard 

to address visibility impairment at this time, these concerns are moot. 

(4) Comment: The EPA received numerous comments on monitoring related to the proposed 

secondary standard for PM-related visibility impairment, including the use of IMPROVE 

and CSN methods, the designation of these methods as Federal Reference or Federal 

Equivalent Methods (FRM/FEM), preference of alternative methods such as a direct 

measurement of light extinction, network design, data reporting, data validation, and 

reporting requirements for IMPROVE and CSN data. 

Response: For the reasons stated in section VI of the preamble to the final rule, EPA is 

not establishing a distinct secondary PM2.5 NAAQS. Consequently, the final rule does not 

include requirements for monitoring to support such a standard and these concerns are 
IV-59 

moot. 

C. Specific Comments on Proposed Secondary PM Standards for Non-Visibility 

Welfare Effects 

Relatively few commenters addressed the proposal to retain the existing suite of 

secondary PM standards to address non-visibility welfare effects. Those who did comment either 

raised concerns on the proposal to retain the current secondary annual standard, or raised 

concerns about whether the existing secondary standards offered sufficient protection against 

impacts on climate. 

(1) Comment: Some commenters opposed the proposal to retain the current secondary annual 

PM2.5 standard of 15 μg/m3 in light of the proposal to revise the primary annual PM2.5

standard to a level between 12-13 μg/m3. Expressing concern over the implications of 

this decision for the air quality planning obligations of states, these commenters argued 

that the EPA should revise the secondary PM2.5 standards to be equivalent in all respects 

to the primary PM2.5 standards. For example, the American Association of State Highway 

and Transportation Officials (AASHTO) supported “retaining secondary standards that 

are consistent with the primary standards in order to reduce the complexity of the 

transportation and air quality planning processes, as well as the transportation conformity 

process” (AASHTO, p. 3). Thus, if the EPA were to adopt a lower level for the primary 

annual PM2.5 standard, the commenters recommended that the EPA adopt this same lower 

level for the primary secondary PM2.5 standard as well. 

Response: As discussed in sections VI.B.2 and VI.C.2 of the preamble on non-visibility 

welfare effects, the EPA lacks an appropriate scientific basis for revising the level of the 

secondary annual PM2.5 standard. There is an absence of information that would support 

any different secondary standards for PM at this time. Comments related to the 

implementation challenges associated with distinct primary and secondary standards are 

not relevant to the Administrator’s final decisions regarding what standards are requisite 

to protect the public welfare. Therefore, the EPA continues to conclude that it would be 

appropriate to retain the current suite of secondary PM standards to address non-visibility 

welfare effects, as proposed. 

(2) Comment: With regard to the impacts of particulate matter on climate, one commenter 

cited a number of recent studies that considered mobile source black carbon emissions 

and associated climate impacts, and urged the EPA to protect the public welfare by 

setting “higher standards for gasoline quality” (Urban Air Initiative, p. 4). This 

commenter did not advocate specific secondary NAAQS to address climate impacts of 

PM. 

Response: The commenters concerns are not relevant to this rulemaking, which is 

limited to determining the secondary NAAQS for PM under section 109(b) of the Act. 

(3) Comment: The Center for Biological Diversity urged the EPA to “set a separate limit for 

black carbon within the overall PM2.5 standard” to ensure that public welfare is fully 

protected “from the serious climate impacts of black carbon” (Center for Biological 
IV-60 

Diversity, p. 2). This commenter argued that “[p]recaution is required for secondary 

NAAQS,” citing American Trucking Associations, Inc. v. EPA, 283 F.3d 355, 369 (D.C. 

Cir. 2002): 

[N]othing in the Clean Air Act requires EPA to wait until it has perfect 

information before adopting a protective secondary NAAQS. Rather, the Act 

mandates promulgation of secondary standards requisite to protect public welfare 

from any “anticipated adverse effects associated with” regulated pollutants, 42 

U.S.C. § 7409(b)(2) (emphasis added), suggesting that EPA must act as soon as it 

has enough information (even if crude) to “anticipate[]” such effects[.] 

The commenter stressed the growing scientific evidence regarding the impacts of black 

carbon on climate, and argued that the EPA’s proposal ignores important research studies 

published within the last five years which provide improved estimates of the radiative 

forcing associated with black carbon, and the effects of black carbon on snow and ice, the 

Arctic climate, water availability and climate “tipping points.” The commenter also noted 

that reductions in cooling aerosol species, particularly sulfate, due to pollution control 

programs are leading to an “unmasking” of the true extent of warming due to the 

accumulation of greenhouse gases in the atmosphere. The commenter argued that this 

unmasking effect can be offset by ensuring “that sufficient black carbon reductions 

accompany reductions in overall aerosol pollution” (Center for Biological Diversity, p. 

10). 

Response: The EPA agrees with the commenters’ assertion that the scientific information 

about the impacts of aerosol species on climate is developing rapidly, and that 

understanding of the magnitude of aerosol effects on climate and the contribution of 

individual aerosol components to those effects has improved substantially over the past 

decade. The EPA also agrees that certain species, in particular black carbon, play a 

significant role in multiple aspects of climate. The Policy Assessment recognized that 

“Aerosols can impact glaciers, snowpack, regional water supplies, precipitation and 

climate patterns,” and may contribute to the melting of ice and snow, a decrease in 

surface albedo, and climate impacts in the Arctic and other locations (U.S. EPA, 2011a, 

p. 5-9). The contribution of black carbon to these effects is discussed in detail in the 

EPA’s recent Report to Congress on Black Carbon (U.S. EPA, 2012c). In particular, 

black carbon plays an important role in heating the lower atmosphere by absorbing 

incoming solar radiation and outgoing terrestrial radiation, i.e. via “direct” radiative 

forcing. 

However, the EPA disagrees that there is sufficient information available at this time to 

establish a NAAQS to protect against the climate impacts associated with current ambient 

concentrations of black carbon or other PM constituents. While the Integrated Science 

Assessment concluded that “a causal relationship exists between PM and effects on 

climate, including both direct effects on radiative forcing and indirect effects that involve 

cloud feedbacks that influence precipitation formation and cloud lifetime” (U.S. EPA, 

2009a, section 9.3.10), it also identified substantial remaining uncertainties with regard to 

the contribution of individual aerosol species to these climate effects. The contribution of 

individual aerosol components to total aerosol direct radiative forcing is more uncertain 
IV-61 

than the global average (U.S. EPA, 2009a, section 9.3.6.6), and the indirect effects of 

aerosols and aerosol components remain highly uncertain, in particular with regard to 

their complex interactions with clouds. 

The EPA notes the substantial remaining uncertainties and gaps with regard to the 

climate impacts of PM components, including black carbon. These include the 

uncertainties associated with the spatial and temporal heterogeneity of PM components 

that contribute to climate forcing; the uncertainties associated with measurement of 

aerosol components; the inadequate consideration of aerosol impacts in climate 

modeling; and the currently insufficient data on local and regional microclimate 

variations and the heterogeneity of cloud formations. As a result, the EPA continues to 

conclude that it is not currently feasible to conduct a quantitative analysis for the purpose 

of informing revisions of the current secondary PM standards based on climate, and that 

there is insufficient information at this time to base a national ambient standard on 

climate impacts associated with current ambient concentrations of PM or any of its 

constituents. 

(4) Comment: The Center for Biological Diversity also argued that the EPA did not consider 

the negative impacts of climate change on public health adequately in the proposal. 

Response: Given the large remaining uncertainties about the impact of aerosols on 

climate, there is even greater uncertainty with regard to how aerosol-induced climate 

change will affect public health. At this time, it is not possible to estimate the extent to 

which aerosols in general, let alone particular aerosol components, contribute to the 

occurrence or exacerbation of adverse health outcomes due to climate change. The EPA 

therefore disagrees with the Center for Biological Diversity’s claim that the EPA should 

pursue black carbon reductions for purposes of reducing the impacts of climate change on 

public health. 

(5) Comment: The Center for Biological Diversity stated that the EPA had an obligation to 

address the impacts of black carbon in the PM NAAQS, despite the remaining 

uncertainties. The commenter pointed to the U.S. EPA’s report to Congress on Black 

Carbon (U.S. EPA, 2012X), stating that the “report shows that EPA is aware of the 

climate science and public health information that point to the importance of addressing 

black carbon pollution. EPA must use this information in its relevant decisionmaking” (p. 

13). 

Response: As noted above, the EPA disagrees that there is sufficient information 

available at this time to establish a NAAQS to protect against the climate impacts 

associated with current ambient concentrations of black carbon or other PM constituents. 

While the Integrated Science Assessment concluded that “a causal relationship exists 

between PM and effects on climate, including both direct effects on radiative forcing and 

indirect effects that involve cloud feedbacks that influence precipitation formation and 

cloud lifetime” (U.S. EPA, 2009a, section 9.3.10), it also identified substantial remaining 

uncertainties with regard to the contribution of individual aerosol species to these climate 

effects. The contribution of individual aerosol components to total aerosol direct radiative 

forcing is more uncertain than the global average (U.S. EPA, 2009a, section 9.3.6.6), and 
IV-62 

the indirect effects of aerosols and aerosol components remain highly uncertain, in 

particular with regard to their complex interactions with clouds. The EPA’s Report to 

Congress on Black Carbon provides an extensive discussion of these uncertainties. 

(6) Comment: The Center for Biological Diversity challenged the uncertainties cited by EPA 

with regard to the climate impacts of aerosols generally, arguing that they “do not apply 

to the regulation of black carbon” (p. 14). Specifically, the commenter stated that “there 

are significant anthropogenic sources of black carbon that contribute a large proportion of 

total black carbon emissions”; that “there is enough information related to black carbon’s 

impact to know that global temperatures will rise due to black carbon emissions”; that 

spatial and temporal heterogeneity in black carbon emissions do not matter for estimating 

likely climate effects; that “[b]lack carbon’s negative climate impacts do not depend upon 

details of cloud interactions with aerosols”; and that the EPA does not need to be able to 

quantify the health or climate benefits precisely to know that it is appropriate to control 

black carbon as a specific component of PM under the CAA (Center for Biological 

Diversity, pp. 14-15). 

Response: The EPA disagrees with the commenter’s assertion that the uncertainties about 

the role of aerosols in climate do not apply to black carbon. The Integrated Science 

Assessment identified substantial remaining uncertainties with regard to the contribution 

of individual aerosol species to climate effects. The contribution of individual aerosol 

components to total aerosol direct radiative forcing is more uncertain than the global 

average (U.S. EPA, 2009a, section 9.3.6.6), and the indirect effects of aerosols and 

aerosol components remain highly uncertain, in particular with regard to their complex 

interactions with clouds. Thus, the uncertainty about black carbon’s effects remains 

significant, just as for other aerosol species. 

The EPA disagrees that “black carbon’s negative climate impacts do not depend upon 

details of cloud interactions with aerosols” and that the uncertainties associated with 

climate impacts of aerosols generally do not apply to black carbon. In fact, the EPA has 

pointed to cloud interactions as the area of greatest uncertainty with regard to black 

carbon: recognizing that black carbon affects cloud reflectivity (albedo), lifetime, and 

stability as well as precipitation, the Report to Congress on Black Carbon noted that “few 

quantitative estimates of these effects are available, and significant uncertainty remains. 

Due to all of the remaining gaps in scientific knowledge, it is difficult to place 

quantitative bounds on the forcing attributable to [black carbon] impacts on clouds at 

present” (U.S. EPA, 2012c, p. 4). The Report acknowledged that “most estimates of the 

forcing from aerosol indirect effects are based on all aerosol species (e.g. total PM) and 

are not estimated for individual species (e.g., BC alone)” (U.S. EPA, 2012c, p. 40). The 

Report concluded that it remains unclear the extent to which black carbon contributes to 

the overall aerosol indirect effect, and did not assign any central estimate or even a range 

of possible values to the role of black carbon in the overall aerosol indirect effect. With 

regard to black carbon’s net contribution to climate, therefore, the Report concluded: 

The direct and snow/ice albedo effects of BC are widely understood to lead to 

climate warming. However, the globally averaged net climate effect of BC also 

includes the effects associated with cloud interactions, which are not well 
IV-63 

quantified and may cause either warming or cooling. Therefore, though most 

estimates indicate that BC has a net warming influence, a net cooling effect 

cannot be ruled out. It is also important to note that the net radiative effect of all 

aerosols combined (including sulfates, nitrates, BC and OC) is widely understood 

to be negative (cooling) on a global average basis. (U.S. EPA, 2012c, p. 3) 

The Report to Congress on Black Carbon also stressed the importance of considering coemitted PM species, such as SO2 and NOx, in evaluating the benefits of black carbon 

mitigation options. Noting that many of these co-emitted particles and gases have a 

cooling influence on climate, the Report noted the difficulty of estimating the net effect 

of various mitigation measures on net radiative forcing or other climate variables. The 

EPA concluded that the location and timing of emissions reductions would be critically 

important for achieving climate benefits, and that “more research is needed on the 

benefits of individual control measures in specific locations to support policy decisions 

made at the national level” (U.S. EPA, 2012c, p. 140). Thus, the EPA disagrees with the 

Center for Biological Diversity’s claim that spatial and temporal heterogeneity in black 

carbon emissions do not matter for estimating likely climate effects, and continues to 

believe that being able to quantify the climate impacts of various aerosol species, alone 

and in combination, is essential for informing any possible revisions to the current 

secondary PM standards based on climate. 

(7) Comment: The commenter noted that the United States participates in a number of 

international forums that have recognized the need to take action on black carbon, and 

argued that the U.S. has “an obligation under the Gothenburg Protocol to address black 

carbon pollution” (Center for Biological Diversity, p. 13). 

Response: In May, new provisions pertaining to particulate matter were added to the 

Gothenburg Protocol under the Convention on Long-Range Transboundary Air Pollution. 

Amongst other things, these provisions encourage parties to develop national inventories 

and projections for black carbon, and to “give priority” to black carbon when 

implementing measures to control PM. However, the EPA notes that the U.S. has not yet 

ratified the PM amendments to the Gothenburg Protocol, and furthermore, these 

amendments do not require action specifically to reduce black carbon, but rather 

encourage countries to take such actions voluntarily within the context of their broader 

PM reduction strategies. Thus the EPA disagrees with the commenter that the U.S. has an 

“obligation” to reduce black carbon under the Gothenburg Protocol, or that it has 

“agree[d] to choose mitigation options for particulate matter that focus on black carbon 

reductions” under the Protocol (Center for Biological Diversity, p. 13). 

(8) Comment: The Center for Biological Diversity concluded that the current size-based PM 

mass standard “is insufficient to fully protect health and welfare,” and that the EPA was 

obligated to establish a specific limit on black carbon as a component of PM. The 

commenter argued that “Black carbon must be regulated separately and in addition to 

PM2.5 because absent separate standards sulfates and nitrates may be more likely to be 

mitigated than the black carbon component of PM” (Center for Biological Diversity, p. 

17). To support this point, the commenter cited the conclusion in the Policy Assessment 

that: 
IV-64 

The current standards that are defined in terms of aggregate size mass cannot be 

expected to appropriately target controls on components of fine and coarse 

particles that are related to climate forcing effects. Thus, the current mass-based 

PM2.5 and PM10 secondary standards are not an appropriate or effective means of 

focusing protection against PM-associated climate effects due to these differences 

in components. (U.S. EPA, 2011a, p. 5-11). 

The commenter also noted that existing regulations on diesel engines, which are the 

largest source of black carbon in the United States, do not affect existing engines and 

vehicles, and stated that “The NAAQS program is one of the few opportunities to reduce 

black carbon from existing engines, industrial and biofuel sources within the United 

States and rapidly reduce emissions from this pollutant” (Center for Biological Diversity, 

p. 18). 

Response: While the EPA agrees with the commenter that a large percentage of black 

carbon emissions come from anthropogenic sources, including diesel engines and 

vehicles, the EPA notes that existing regulations on mobile diesel engines are already 

reducing these emissions substantially. Between 1990 and 2005, new engine 

requirements resulted in a 32 percent reduction in black carbon emissions from mobile 

sources, and a further 86 percent reduction from 2005 levels is projected to occur by 2030 

as vehicles and engines meeting existing regulations are phased into the fleet (U.S. EPA, 

2012c, p. 175). Long-term historic data indicate that there has been a dramatic overall 

decline in black carbon emissions over the past century, due to changes in fuel use, more 

efficient combustion practices, and implementation of PM controls. 

Therefore, the EPA disagrees with the Center for Biological Diversity’s claim that a 

distinct black carbon NAAQS is necessary to achieve reductions in black carbon 

emissions. Clearly, U.S. emissions of black carbon are already declining substantially, 

suggesting that the existing mass-based PM standards, though not targeting black carbon 

specifically, have been effective in achieving black carbon emissions reductions in 

practice. As acknowledged in the Report to Congress on Black Carbon, “While [black 

carbon] is not the direct target of existing programs, it has been reduced through controls 

aimed at reducing ambient PM2.5 concentrations and/or direct particle emissions” (U.S. 

EPA, 2012c, p. 161). The EPA has acknowledged the need to encourage PM mitigation 

strategies that focus on reducing directly emitted PM2.5 for purposes of reducing black 

carbon, and this is reflected in its general support for the revised language in the 

Gothenburg Protocol, as discussed above. 

 
V-1 

V. RESPONSES TO SIGNIFICANT COMMENTS ON AMENDMENTS TO AMBIENT 

MONITORING AND REPORTING REQUIREMENTS 

A. Comments on General Issues for Reference, Equivalent, or Approved Regional 

Methods 

(1) Comment: One commenter supported the proposed administrative change to 40 CFR Part 

53.9 – Conditions of Designation. 

Response: The comment in support of the proposal is acknowledged and EPA is adopting 

the proposed approached in the final rule. 

(2) Comment: One commenter stated that the approach of requiring PM2.5 FEMs to meet the 

data objectives necessary for method designation for a period of at least one year will not 

be effective since the data objectives used in the FEM evaluation protocols do not match 

the required routine operating schedules for monitoring agencies. The FRMs used by 

monitoring agencies are operated from midnight to midnight while the vendors used midmorning to mid-morning for the FEM evaluation protocols. This difference creates a bias 

because the routine midnight-to-midnight agency samples will retain a smaller portion of 

volatile PM than the vendor-operated FRMs. The vendors also were required to operate 

and average the results from triplicate FRMs and triplicate candidate FEMs. These 

averaged results are more stable and consistent than individual FRM and FEM data. 

Response: The EPA’s intention in making this administrative change to 40 CFR Part 53.9 

– Conditions of Designation is to link this long-standing requirement to the appropriate 

performance criteria as is done for all other Federal equivalent methods. The EPA agrees 

that there are differences in the way the testing and routine operation of these methods 

are conducted. However, despite these differences, and as explained in the preamble to 

the final rule, a number of PM2.5 continuous FEMs monitors are achieving acceptable 

data comparability. To the extent that this change encourages a closer relationship 

between instrument companies and monitoring agencies, especially during the first 12 

months of operation, EPA believes such a relationship will lead to mutual responsibility 

in striving to meet the appropriate performance criteria. Also, EPA did not propose any 

changes to the testing criteria. 

(3) Comment: One commenter stated that the monitoring methods proposed to support the 

proposed new secondary PM2.5 visibility index NAAQS do not address an estimate of 

measurement accuracy. 

Response: For the reasons stated in section VI of the preamble to the final rule, EPA is 

not adopting the proposed secondary PM2.5 visibility index NAAQS. Consequently, the 

final monitoring rule does not include requirements on the use of CSN or IMPROVE 

measurements. 

(4) Comment: A few commenters stated that the EPA does not adequately recognize the 

potential for intrusion of coarse particle mass into fine particle measurements. The 

commenters noted that the potential for coarse particle intrusion is significant in the arid 

West, where PM concentrations of crustal origin may account for an appreciable portion 
V-2 

of the total ambient mass concentration. 

Response: The Agency has long recognized that ambient fine and coarse modes vary 

appreciably with regard to origin, particle size, chemical composition, and potential 

adverse health effects associated with their exposure. As discussed in the Air Quality 

Criteria for Particulate Matter (October 2004), intermodal minimums between fine and 

coarse particle ambient size distribution modes typically range between 1 and 3 μm. 

Based on recommendations by both Agency staff and the CASAC, 2.5 μm was selected 

as the most appropriate size indicator in this intermodal size range when setting the fine 

particle standard for the 1997 PM NAAQS. The decision regarding whether to maintain 

the 2.5 um size cut for ambient PM2.5 samplers was also considered during the review of 

the 2006 PM NAAQS, and it has again been considered during this review (see 

discussion at Section III.E.1 in the preamble to this final rule). In each instance, selection 

of PM2.5 as the most appropriate indicator of fine particle exposure has been 

overwhelmingly supported by subsequent Agency reviews, CASAC peer-reviews, and 

Integrated Science Assessments. 

When selecting the most appropriate size indicator for the fine particle standard within 

the 1 and 3 μm size range, the Agency recognized that there is no unambiguous definition 

of a size cut that would provide for complete separation of overlapping fine and coarse 

ambient particle modes under all circumstances. While there is generally very little 

particle mass in the intermodal size range in most monitoring situations, the fine mode 

can extend up to and above 2.5 μm in situations of high ambient relative humidity. 

Conversely, the coarse mode can extend down to approximately 1 micrometer in 

situations characterized by high coarse mode concentrations in conjunction with high 

wind speeds. Ultimately, the selection of PM2.5 as the most appropriate size indicator for 

assessing exposure to fine particles has been based on ensuring that ambient 

measurements completely captured the aerosol component of greatest health concern. As 

a result, it was deemed by the Agency and CASAC to be more important to collect fine 

particles more completely under all sampling conditions than to exclude coarse-mode 

particles which may inadvertently intrude into fine particle measurements. In addition, 

there is currently insufficient epidemiological and toxicological evidence to conclude that 

crustal particulate matter is totally benign with respect to potential adverse health effects 

associated with its exposure. 

The EPA notes that in order to provide a distinct measurement separation between 

particles above and below 2.5 μm aerodynamic diameter, the FRM for the PM2.5 NAAQS 

employs use of a single-stage inertial separator which provides very sharp fractionation 

characteristics. The FRM’s development and subsequent promulgation of equivalent 

method specifications includes provisions to ensure that the fractionation characteristics 

of PM2.5 NAAQS monitors do not appreciably degrade as a function of aerosol loading. 

In conjunction with the inherently very sharp fractionation characteristics of the inertial 

separator itself, these provisions are designed to ensure that the intrusion of ambient 

coarse particles into fine particle measurements does not significantly positively bias fine 

particle concentrations in the presence of high concentrations of ambient crustal 

components. 
V-3 

B. Comments on use of CSN and IMPROVE methods to provide speciation data used in 

the proposed new secondary PM2.5 visibility index NAAQS. 

(1) Comment: One commenter was supportive of using the IMPROVE monitors in urban 

areas. 

Response: For the reasons stated in section VI of the preamble to the final rule, EPA is 

not adopting the proposed secondary PM2.5 visibility index NAAQS. Consequently, the 

final monitoring rule does not include requirements on the use of CSN or IMPROVE 

measurements. 

(2) Comment: Regarding the use of IMPROVE and CSN samplers for use in the visibility 

index, several commenters do not support the use of methods that have not been 

designated as FEM or FRM in comparison to the NAAQS as this is inconsistent with all 

other NAAQS. 

Response: For the reasons stated in section VI of the preamble to the final rule, EPA is 

not adopting the proposed secondary PM2.5 visibility index NAAQS. Consequently, the 

final monitoring rule does not include requirements on the use of CSN or IMPROVE 

measurements. 

(3) Comment: Several commenters preferred a direct measurement of light extinction. For 

example, use of optical instrumentation such as nephelometers and aethalometers. 

Response: For the reasons stated in section VI of the preamble to the final rule, the EPA 

is not adopting the proposed secondary PM2.5 visibility index NAAQS. Consequently, 

the final monitoring rule does not include requirements on the use methods to support 

such a standard. 

(4) Comment: One commenter recommended that EPA needs to begin the process of 

developing a Federal Reference Method that directly measures light-extinction. 

Response: The EPA can consider the development of a light extinction method for an 

FRM as part of an overall strategy on methods development; however, even if the EPA 

decides to pursue such a direct measurement method as an FRM, which would have to be 

considered with other method development priorities, the timing of developing such a 

method is expected to take several years to complete the needed laboratory and field 

studies prior to a future proposal. 

(5) Comment: Several commenters recommend the EPA develop a pilot urban visibility 

network program that would field test and evaluate the most promising methods of direct 

measurement under varying field conditions. 

Response: The EPA can consider such a pilot program; however, since a pilot program is 

inherently not a national deployment, there is no need to direct any requirements for such 

a program in the final rule. 
V-4 

(6) Comment: One commenter stated that the EPA should establish a pilot measurement 

program to identify methods that would more accurately measure and report real-time 

visibility conditions to the public. 

Response: he EPA can consider such a pilot program; however, since a pilot program is 

inherently not a national deployment, there is no need to direct any requirements for such 

a program in the final rule. 

(7) Comment: Several commenters stated that the IMPROVE monitoring network is not 

suitable for supporting a visibility standard that is intended to be primarily a program for 

urban areas. 

Response: For the reasons stated in section VI of the preamble to the final rule, the EPA 

is not adopting the proposed secondary PM2.5 visibility index NAAQS. Consequently, the 

final rule does not include requirements for monitoring sites to support such a standard. 

(8) Comment: One commenter asked for clarification on how total PM2.5 mass concentrations 

from IMPROVE and CSN samplers might be used for comparison to the primary PM2.5

NAAQS. 

Response: It was never the EPA’s intention that the PM2.5 mass concentrations from 

IMPROVE and CSN samplers would be used for comparison to the primary PM2.5

NAAQS. Had we finalized use of the IMPROVE and CSN samplers for use with the 

proposed PM2.5 visibility index NAAQS, which as described in section VI of the 

preamble to the final rule, we are not doing, we would have clarified this issue in the 

preamble. 

(9) Comment: One commenter stated that in addition to reconstructing visibility from 

speciated PM2.5, states should also have the ability to use direct measurements located at 

airports (AWOS/ASOS), or from nephalometer, telephotometers, and/or 

transmissometers. 

Response: For the reasons stated in section VI of the preamble to the final rule, the EPA 

is not adopting the proposed secondary PM2.5 visibility index NAAQS. Consequently, the 

final rule does not include requirements for monitoring sites to support such a standard. 

(10) Comment: One commenter stated that they do not believe that at this time the PM2.5 

continuous FEMs can be utilized for the purpose of calculating a short-term light 

extinction value for comparison to a standard. 

Response: The EPA would have only needed the PM2.5 continuous FEMs for use in a 

short-term light extinction calculation had it finalized a secondary PM2.5 visibility index 

NAAQS with a sub-daily averaging time. For the reasons stated in section VI of the 

preamble to the final rule, the EPA is not adopting the proposed secondary PM2.5

visibility index NAAQS, nor is the short-term secondary PM2.5 visibility index NAAQS it 

took comment on being finalized; consequently, the final rule does not include 

requirements for monitoring methods to support such a standard. 
V-5 

C. Comments on the Terminology Changes 

(1) Comment: One commenter supports removing of the term ‘community-oriented’ and 

‘community monitoring zone’. 

Response: The comment in support of the proposal is acknowledged and EPA is adopting 

the proposed approach in the final rule. 

D. Comments on Revoking Use of Population-Oriented as a Condition for Comparability 

of PM2.5 Monitoring Sites to the NAAQS 

(1) Comment: One commenter supports revoking the term “population-oriented” so that data 

comparable to the PM2.5 NAAQS are consistent with other NAAQS. 

Response: The comment in support of the proposal is acknowledged and EPA is adopting 

the proposed approach in the final rule. 

(2) Comment: One commenter stated that they are concerned that revoking the populationoriented requirement may result in monitoring at locations that are not appropriate for 

comparison with either the annual standard or the 24-hour standard. 

Response: The EPA believes that for PM, as with all other criteria pollutants, all sites that 

meet the definition of ambient air are appropriate for comparison to the NAAQS. 

However, the EPA provides additional criteria described in §58.30 on those sites that 

may be eligible only for comparison to the annual PM2.5 NAAQS. Although the EPA is 

removing from this provision the requirement that sites be “population-oriented” to be 

compared to the annual PM2.5 NAAQS, all monitoring sites must still be representative of 

area-wide locations to make this comparison. Thus, these sites will represent locations 

where there is population exposure. Therefore, the EPA disagrees that revoking the 

requirement for sites to be population oriented may result in monitoring at locations that 

are not appropriate for comparison with either the annual or 24-hour standards. oreover, 

this amendment will not alter the current PM2.5 monitoring network, since (based on data 

in the Air Quality System (AQS) database) there are no current PM2.5 monitoring sites 

that have affirmatively been categorized as “non population oriented” using the current 

regulations. 

(3) Comment: One commenter stated that EPA’s definition of ambient air is specified in 40 

CFR 50.1—‘‘Ambient air means that portion of the atmosphere, external to buildings, to 

which the general public has access.’’ While this is an appropriate definition of ambient 

air, monitoring for compliance with any given air quality standard should be carried out 

at locations where there are people actually exposed for time periods that correspond 

approximately to the averaging time of that NAAQS. Thus, for comparison with the 

annual PM2.5 standard, the population-oriented definition is appropriate since it involves 

locations where a substantial number of people spend a significant fraction of the day. 

Without a requirement to site monitors in this manner, monitoring from locations that 

have little or no population exposure could be used for comparison with the PM2.5
V-6 

NAAQS. For example, in the proposal the Agency indicates: 

Area-wide means all monitors sited at neighborhood, urban, and regional 

scales, as well as those monitors sited at either micro- or middle-scale that are 

representative of many such locations in the same CBSA. 

The key issue with this approach is that there may be many similar micro-scale locations 

in a metropolitan area but none of them may have actual human exposures relevant to the 

averaging time of the NAAQS. 

The proposed rule indicated: 

In reviewing the impact that this proposed change might have on the nation’s PM2.5

monitoring network, the EPA notes that there are no remaining sites operating 

affirmatively as ‘‘non-population-oriented.’’ 

While this may be true, the proposed rule also requires the addition of a substantial 

number of near-road monitoring sites the location of which is still to be decided. The 

Agency provides no examples of cases where the current definitions have resulted in any 

ambiguity with regard to monitoring locations. Therefore, the commenter does not 

support the EPA proposal to revoke the requirement that PM2.5 monitoring sites be 

‘‘population-oriented’’ for comparison to the NAAQS. 

Response: The EPA believes that the location of any site meeting the definition of 

ambient air, which represents a location where the public is (or may be) exposed, will 

represent current or potential population exposure and is an acceptable location for 

comparison to PM2.5 NAAQS, as is the case with all other criteria pollutants. 

Additionally, for comparison to the annual PM2.5 NAAQS, monitoring sites are also to 

represent area-wide air quality; therefore, even if a monitor was located in a location at a 

small scale where no one was actually exposed on a given day, there is still the potential 

for someone to be exposed there and that site is intended to represent many such other 

locations in the same area, where the public is (or may be) exposed. For example, 

undeveloped or lightly utilized areas that border industrial sources or exist along 

roadways may at one time have little or no population exposure, however, if subsequent 

housing, commercial, or recreational development occurs than population exposure will 

occur. Basing monitoring decisions on the ambient air definition provides states with the 

flexibility to place monitors in these areas before as well as after such development. With 

regard to the comment that “....monitoring for compliance with any given air quality 

standard should be carried out at locations where there are people actually exposed for 

time periods that correspond approximately to the averaging time of that NAAQS”, the 

EPA notes that no such requirements exist in the monitoring regulations. While the 

consideration of NAAQS averaging time may be one factor on which to base the siting of 

monitors, monitoring agencies need flexibility in designing their networks to ensure 

characterization of locations to which the general public has access as well as to support 

the specific objectives described in Appendix D of Part 58, section 1.1. Regarding the 

commenter’s point that we have not provided any “...examples of cases where the 

current definitions have resulted in any ambiguity with regard to monitoring locations”, 
V-7 

the EPA points out that such cases do exist, including the use by stakeholders of 

dispersion modeling to support NAAQS attainment planning, associated SIP 

development, and the calculation of transportation conformity budgets, and that these 

examples typically apply as often to locations that are unmonitored as well as locations 

that are monitored. The EPA contends that the monitoring rules need to be clear as to the 

requirements to monitor and that the removal of the “population oriented” phrase that has 

only applied to PM2.5 sites will provide needed clarity for monitoring agencies that plan 

and operate ambient networks as well as those stakeholders that base implementation 

strategies, in part, on PM2.5 monitoring requirements. 

(4) Comment: One commenter stated that the EPA proposes to revoke the Part 58 

requirement that placement of PM2.5 monitor placements be “population oriented,” 

because the Agency argues that this requirement is “inconsistent” with the regulatory 

definition of “ambient air” at 40 CFR 50.1.10 Id. 39011. The commenter believes this 

change of historical practice is unreasonable, particularly since the agency has trumpeted 

that the value of the proposed rulemaking is for promulgation of a suite of urban PM2.5

NAAQS. First, we submit that the EPA conflated the issue of the definition of “ambient 

air” with the placement of monitors. The definition of “ambient air” is relevant to 

placement of stationary source monitors and compliance, not to the placement of roadside monitors. Further the definition of “ambient air” is quite flexible as evidenced by 30 

years of NSR determinations. Second, what the EPA seems to desire is the ability to 

reorient the placement of monitors from urban areas to: (1) roads where they can “piggy 

back” on the recently installed NO2 NAAQS monitors; and (2) establish a new 

monitoring network in rural areas; and (3) to potential hotspots in rural areas caused by 

energy exploration. These plans, discussed at length in the proposed notice of 

rulemaking, certainly do not jive with the objective of this rulemaking – a suite of urban 

PM2.5 NAAQS to compliment the regional haze regulations already in place. For this 

reason, the proposed changes to Part 58 and the change of the focus of the existing focus 

of the Part 58 monitoring requirements from “population centers” to rural areas is not 

supportable at all based on the record of decision and we oppose it on that grounds. 

Response: The EPA disagrees with several of the commenter’s assertions. First, EPA 

disagrees that revoking the requirement for monitors to be “population-oriented’ is 

unreasonable. As explained in the preamble, the NAAQS provide protection for the 

public health and welfare in areas where the public can be exposed (necessarily including 

rural and urban areas). For all other criteria pollutants, monitoring requirements allow the 

comparability of monitors in any location representative of ambient air to the NAAQS 

without further restriction. In the case of PM2.5 however, the historic rules contained an 

additional restriction requiring monitors to be in population oriented locations to be 

comparable to the PM2.5 NAAQS. The term “population oriented” has lacked a 

quantitative definition (e.g., the interpretation of “substantial numbers” used as part of the 

part 58.1 definition of “Population-Oriented Monitoring”), therefore monitoring agencies 

and those stakeholders who based implementation strategies and decisions on monitoring 

regulations have been uncertain about what locations are or are not appropriate for PM2.5

monitoring. The EPA believes that the continued use of the population oriented 

restriction on NAAQS comparability represents an unwise limitation on the flexibility of 
V-8 

monitoring agencies to revise their PM2.5 networks to account for anticipated changes in 

demographics or development as well as a contradiction with the inherent applicability of 

the NAAQS in ambient air locations where the public has access (e.g., in any location 

outside the perimeter of a industrial facility). Consistent with the long-standing practice 

of monitoring agencies in locating ambient monitors, we also note that, based on 

supporting data in the AQS, all currently existing PM2.5 monitors are located in areas that 

are representative of population exposures. There are no PM2.5 monitors currently 

operating as “non-population oriented”. The EPA does not believe that removing the 

restriction for monitors to be population oriented will result in monitors that are not 

representative of population exposures. Regarding the comment that “the definition of 

ambient air is relevant to placement of stationary source monitors and compliance, not to 

the placement of road-side monitors”, the EPA disagrees that “ambient air” is not 

relevant to road-side monitors. The EPA points out that a significant fraction of the 

population lives, works, plays, and goes to school near major roads and that these 

exposures occur in locations that represent ambient air. As noted in the preamble, one 

referenced study (http://www.census.gov/housing/ahs/data/ahs2009.html) identified that 

45 million Americans live within 300 feet of a major roadway or other major mobile 

source. The survey provides an estimate of the county’s numerous housing units in the 

U.S. that are located with 300 feet of a highway with four or more lanes, or a railroad, or 

an airport. 

Regarding the comment “what EPA seems to desire is the ability to reorient the 

placement of monitors from urban areas to: (1) roads where they can “piggy back” on the 

recently installed NO2 NAAQS monitors; and (2) establish a new monitoring network in 

rural areas; and (3) to potential hotspots in rural areas caused by energy exploration”, we 

point out that the requirement is to site PM2.5 near-road monitors in urban areas with 

populations of 1 millions persons or more; therefore, these monitoring locations are still 

representative of those urban areas and the populations that live, work, play, and go to 

school near these major roads. Regarding the comment that the EPA is to “establish a 

new monitoring network in rural areas” the EPA disagrees as we did not propose, nor are 

we finalizing any changes to monitoring requirements in rural areas. Regarding the 

comment to reorient the placement of monitors from urban areas to “potential hotspots in 

rural areas caused by energy exploration”, we again note that there was no such proposal 

nor are we finalizing any such language. The commenter’s obscure reference to Regional 

Haze suggests the commenter was referring to the proposed secondary standard for 

visibility, which the EPA is not adopting in the final rule. 

(5) Comment: One commenter stated that removing the requirement for population oriented 

combined with other proposed monitoring changes creates a situation where any monitor, 

anywhere, measuring only very localized air quality of a small areas, could be compared 

to the NAAQS. 

Response: As explained in the preamble, the NAAQS provide protection for the public 

health and welfare in areas where the public can be exposed. For all other criteria 

pollutants, monitoring requirements allow the comparability of monitors in any location 

representative of ambient air to the NAAQS without further restriction, even if such 

locations characterize very localized air quality. In the case of PM2.5 however, the 
V-9 

additional restriction of requiring monitors to be in population oriented locations to be 

NAAQS comparable has existed. The term “population oriented” has lacked a 

quantitative definition (e.g., the interpretation of “substantial numbers” used as part of the 

part 58.1 definition of “Population-Oriented Monitoring”), therefore monitoring agencies 

and those stakeholders who based implementation strategies and decisions on monitoring 

regulations have been uncertain about what locations are or are not appropriate for PM2.5

monitoring for purposes of NAAQS comparability. The EPA believes that the continued 

use of the population oriented restriction on NAAQS comparability represents an unwise 

limitation on the flexibility of monitoring agencies to revise their PM2.5 networks to 

account for anticipated changes in demographics or development as well as a 

contradiction with the inherent applicability of the NAAQS in ambient air locations 

where the public has access (e.g., in any location outside the perimeter of a industrial 

facility). Moreover, all PM2.5 monitoring sites must still be representative of area-wide 

locations to make the comparison to the annual NAAQS. Thus, these sites still represent 

locations where there is population exposure. Consistent with the long-standing practice 

of monitoring agencies in locating ambient monitors, we also note that all currently 

existing PM2.5 monitors are located in areas that are representative of population 

exposures based on supporting data in the AQS. There are no PM2.5 monitors currently 

operating as “non-population oriented” and the EPA does not believe that removing the 

restriction for monitor to be population oriented will result in monitors that are not 

representative of population exposures. 

(6) Comment: One commenter (EEI) stated that purportedly to address “ambiguity,” the 

EPA is proposing to remove existing requirements regarding PM2.5 NAAQS that require 

monitors to be “population-oriented.” The EPA additionally claims it must now align a 

15-year old regulatory requirement (for population-orientation) with an even older 

regulatory definition of ambient air. The EPA offers no analytical support or logical 

rationale for this proposal and the EPA should not finalize the proposed changes. The 

EPA states that eliminating the requirement does not change the requirements for the 

design of PM2.5 networks. But this perspective ignores other changes that the EPA is 

proposing to make with regard to PM2.5 monitoring. As referenced above, the EPA is 

proposing to allow monitors that measure air quality representative of very small areas to 

be compared to the NAAQS. By additionally proposing to eliminate the requirement that 

such monitors be population-oriented, the EPA is not conforming its monitoring 

requirements to the definition of “ambient air” (which includes the specification that such 

air be that to which the general public has access). Instead, removing any requirement for 

population orientation combined with other proposed monitoring changes results in the 

prospect that any monitor, anywhere, measuring any very localized air quality of any size 

could be comparable to the NAAQS, and possibly drive the characterization of the air 

quality status of a much broader geographic area. This is inconsistent both with the 

definition of ambient air and with the CAA’s requirement that NAAQS be protective of 

“public health.” On a fundamental level, it appears fully consistent with the primary 

NAAQS process contained in CAA sections 107-109 and completely logical to maintain 

a population-orientation as a criterion for monitors for primary, health-based NAAQS. 

This is certainly the perspective that EPA adopted from the very first staff paper for the 

PM2.5 NAAQS in 1997. As noted at that time, “all concentration-response functions used 

in these analyses are based on findings from human epidemiological studies, which rely 
V-10 

on fixed-site, population-oriented, ambient monitors as a surrogate for actual integrated 

PM exposures. Measurements of daily variations of ambient PM concentrations . . . have 

a plausible linkage to the daily variations of exposure from ambient sources for the 

populations represented by ambient monitoring stations. . .” These conditions have not 

changed in the years since 1997 and thus support retention of the current requirement. 

Response: The EPA’s disagrees with a number of the commenter’s statements. With 

regard to the comment that “EPA is not conforming its monitoring requirements to the 

definition of ambient air (which includes the specification that such air be that to which 

the general public has access)”, we note that the NAAQS provide protection for the 

public health and welfare in areas where the public can be exposed. For all other criteria 

pollutants, monitoring requirements allow the comparability of monitors in any location 

representative of ambient air to the NAAQS without further restriction. The EPA 

believes that the continued use of the population oriented restriction on PM2.5 NAAQS 

comparability represents an unwise limitation on the flexibility of monitoring agencies to 

revise their PM2.5 networks to account for anticipated changes in demographics or 

development as well as a clear contradiction with the inherent applicability of the 

NAAQS in ambient air locations where the public has access (e.g., in any location 

outside the perimeter of a industrial facility). Moreover, all monitoring sites must still be 

representative of area-wide locations to be used for comparison with the annual PM2.5

NAAQS. Thus, these sites still represent locations where there is population exposure. 

This change thus, results in monitoring requirements that are completely consistent both 

with the definition of ambient air and with the CAA’s requirement that NAAQS be 

protective of “public health.” From an operational standpoint, we have noted that from a 

sample of over 900 operating monitoring stations in the country, and none of the 

currently operated monitors have been determined to not be “population-oriented” based 

on data in AQS, therefore the practical implications of this revision on the operating 

monitoring network are inconsequential. 

With regard to the comment that “As noted at that time, “*all concentration-response 

functions used in these analyses are based on findings from human epidemiological 

studies, which rely on fixed-site, population-oriented, ambient monitors as a surrogate for 

actual integrated PM exposures. Measurements of daily variations of ambient PM 

concentrations . . . have a plausible linkage to the daily variations of exposure from 

ambient sources for the populations represented by ambient monitoring stations. . .” 

These conditions have not changed in the years since 1997 and thus support retention of 

the current requirement”. The commenter cites language from the EPA’s initial 

promulgation of the “population oriented” provision (40 CFR Part 58 App. D section 

2.8.1.2.3 (1997)), and suggests that a “population oriented” provision is required to be 

consistent with the form of the annual standard and the epidemiologic information on 

which the standard is based. However, as explained in section III.E.4 to the preamble to 

the final rule, it is appropriate in this review to eliminate the spatial averaging option 

from the form of the annual standard, and appropriate to compare the PM2.5

concentrations from a maximum monitor to the level of the PM2.5 standard. 

Consequently, the commenter’s premise that the “population oriented” phrase is 

necessary to be consistent with the form and general structure of the annual PM2.5

NAAQS is misplaced. 
V-11 

The requirement that a near-road monitor represent area-wide air quality (as defined) 

assures that the commenter’s example of “any monitor, anywhere, measuring very 

localized air quality” being used for comparison with the annual PM2.5 NAAQS will not 

occur. This is because area-wide air quality is representative of those population 

exposures where large numbers of people live, work, play, and go to school. Moreover, 

the commenter’s concern that air quality measured at a micro-scale (or other small- scale) 

could characterize air quality in a much broader area is not appropriately raised here. 

Issues as to attainment or non-attainment area boundaries are determined as part of the 

section 107 designation process. 

(7) Comment: Commenters (ALA et al., 2012) stated, “We especially welcome EPA’s 

proposal to abandon and revoke regulatory language in Part 58 that effectively prevented 

the implementation of the PM2.5 NAAQS to protect populations exposed to incremental 

concentrations near transportation facilities. These include the current prohibitions 

against comparison of micro- and middle-scale monitors with the annual NAAQS, and 

the requirement that only “population-oriented” monitors be compared with the 24-hour 

NAAQS. For the reasons discussed below, we believe these policies impose limitations 

on the applicability of the NAAQS that are inconsistent with the text, purpose and intent 

of the Clean Air Act, and must be revoked. 

Response: As noted in the preamble and elsewhere in this RTC, we are finalizing the 

removal of the population-oriented language from the applicable PM2.5 monitoring 

regulatory text. 

(8) Comment: One commenter (AASHTO, 2012) stated that “CASAC strongly recommends 

that key population-oriented monitors be maintained, particularly those that have been 

used in past health-focused and accountability studies.” It was also stated that “AASHTO 

is concerned that this proposal will deemphasize the need for area-wide and 

neighborhood scale PM2.5 monitors in these areas.” 

Response: The EPA notes that the removal of the population oriented language from the 

applicable PM2.5 regulatory text in no way affects the current or future distribution of 

PM2.5 monitors in terms of the objectives of supporting population exposure. From a 

sample of over 900 operating monitoring stations in the country, none of the currently 

operated monitors have been determined to not be “population-oriented” based on data in 

AQS. As noted in the preamble, neighborhood scale monitoring sites remain the 

backbone of the PM2.5 monitoring network and the EPA anticipates they will continue to 

represent over two thirds of the operating network following the deployment of the nearroad monitors. Maintaining the area-wide and largely neighborhood scale design value 

sites is critical to the long-standing goal of using data to support a variety of monitoring 

objectives. 

E. Comments on Applicability of Micro- and Middle Scale Monitoring Sites to the Annual 

PM2.5 NAAQS 
V-12 

(1) Comment: One commenter stated that the EPA should remove the restriction that the 

annual PM2.5 standard applies only at “area-wide” sites. The proposed rule requires 

agencies to exclude sites that are relatively unique middle scale or micro-scale from 

comparison to the annual NAAQS. This construction is problematic and will be difficult 

for agencies to implement. 

Response: The requirement that monitors represent area-wide air quality to be 

comparable to the annual PM2.5 NAAQS is longstanding and the EPA did not propose to 

eliminate it or solicit comment on that issue. While the EPA understands that there may 

be some challenges in determining the differences between micro-scale and middle scale 

sites that meet the definition of “area-wide”, such challenges have always been in place 

since the requirements for comparability to the PM2.5 NAAQS were first promulgated in 

1997. The EPA will work with monitoring agencies through the annual network plan 

approval process to address such issues. 

(2) Comment: Several commenters suggested that the EPA should revise the network design 

requirement to reflect the importance of area-wide representative data to meet national 

and state monitoring objectives and remove the presumption that micro- and middle-scale 

sites are representative of many such locations. 

Response: The EPA fully supports, and is maintaining, the network design criteria 

focusing on “area-wide” representative data. Current regulatory language in section 58.30 

addressed the NAAQS applicability issue that where micro- and middle-scale sites are 

representative of many such locations throughout an area, they likewise represent “areawide” air quality. Similarly, regulatory language in Appendix D, section 4.7.1(b) states 

that (for PM2.5), “The required monitoring stations or sites must be sited to represent 

area-wide air quality.” The final rule provides that the air agency recommend whether the 

site is or is not “area-wide” in the Annual Monitoring Network Plan. Such a 

recommendation is still subject to approval by the Regional Administrator. 

(3) Comment: One commenter stated that EPA should explicitly state that near-road data are 

considered unique unless otherwise specified by the Regional Administrator. 

Response: EPA has clarified language to note that we do not presume that any near-road 

monitoring site will be considered unique or not unique; rather it provides that the air 

agency recommend the status of such sites in the Annual Monitoring Network Plan. 

Such a recommendation is still subject to approval by the Regional Administrator. We 

disagree that all near-road locations are unique, as these sites can reflect many such 

locations throughout a metropolitan area. In the preamble, EPA provided examples of 

near-road sites that could be considered unique; these included sites located in proximity 

to a unique source like a tunnel entrance, nearby major point source, or other relatively 

unique microscale hot spot. EPA expects that near-road stations placed in other 

representative locations will reflect area-wide air quality. 
V-13 

(4) Comment: One commenter stated that changing the scale of monitoring site locations that 

can provide data for use in NAAQS attainment determinations has implications that 

impact monitoring objectives. 

Response: The EPA disagrees that changing the scale of monitoring site locations that 

can provide data for use in NAAQS attainment determinations is problematic or has 

negative implications for monitoring objectives. Locations that are at micro- and middlescale have always been used for comparison to the 24-hour NAAQS, and where these 

locations represent many such locations in the same area, they have always been 

appropriate to be compared to the annual NAAQS. As stated in the preamble to the final 

rule, EPA believes that multiple objectives can be supported with the addition of the 

near-road monitoring stations, so while EPA agrees there are implications, on balance 

EPA believes the changes will result in a better network. 

(5) Comment: One commenter stated that the alternative proposal under consideration, 

permitting micro- and middle-scale sites to be classified as area-wide, would diminish 

our ability to track future public health progress at the neighborhood scale. 

Response: EPA disagrees that allowing micro- and middle-scale sites to be classified as 

area-wide, diminishes the ability to track future public health progress at the 

neighborhood scale. Individual sites will be still be labeled with a given spatial scale 

(e.g., neighborhood scale) allowing stakeholders to understand the nature and general 

representativeness of a given site. However, to ensure neighborhood scale sites remain 

an important part of the PM2.5 network, EPA has addressed this issue in the final rule by 

clarifying language in Appendix D, section 4.7.1(b)(1) to state that “At least one 

monitoring station is to be sited at neighborhood or larger scale in an area of expected 

maximum concentration.” 

(6) Comment: Several commenters recommend a positive determination that a PM2.5 monitor 

represents area-wide air quality, and thus eligible for comparison to the PM2.5 NAAQS, 

which should be proposed in Annual Network Plan submittals, with subsequent 

concurrence and approval by the Regional Administrator. Representation of area-wide air 

quality should not be “presumed” as proposed in section 58.30(a)(2). 

Response: The EPA has clarified language to note that we do not presume that any site 

will be considered unique or not unique; rather it provides that the air agency recommend 

the status of such sites in the Annual Monitoring Network Plan. Such a recommendation 

is still subject to approval by the Regional Administrator. Sites that are approved per 

section 58.30 as representing area-wide conditions will be eligible for comparison to the 

PM2.5 annual NAAQS. 

(7) Comment: One commenter (AFPM) stated that contrary to the EPA’s assertions in the 

proposed rule, the proposed changes to allow micro- and middle-scale monitors to be 

compared to the NAAQS and the revoking of the “population-oriented” condition for 

monitoring locations (discussed below) do not promote consistency with EPA’s existing 

regulatory definition for “ambient air.” As noted by EPA, the regulatory definition of 
V-14 

“ambient air” specifically references the portion of outside air to which the general public 

has access. In implementing this regulatory definition, EPA has exempted areas where a 

source owns or controls the property involved and where public access has been 

precluded. The Agency has consistently relied on documents describing the definition of 

ambient air with regard to not including areas “to which public access is precluded by a 

fence or other physical barrier.” Thus, EPA has never interpreted ambient air to be “any 

potential location” outside of a building and proposing to allow “any” PM2.5 monitor to 

be compared to the NAAQS is clearly and directly inconsistent with this long-standing 

regulatory interpretation. Rather than promote consistency, the change would have the 

opposite effect given the expansive interpretation of “any” within the CAA. Therefore, 

EPA should retain the current requirements restricting the use of micro- and middle-scale 

monitors and additionally consider revising the regulations to remove the ability of a 

Regional Administrator to determine monitor comparability. These changes would better 

promote the goal of national uniformity by making it clear that monitors would not be 

subject to highly localized conditions (perhaps measuring highly transient air quality in 

areas measuring no more than a few square meters) or subject to the individual (and 

perhaps inconsistent) preferences of different Regional Administrators 

Response: With regard to the comment that the proposed change to allow micro- and 

middle-scale monitors to be compared to the NAAQS does not promote consistency with 

the EPA’s existing regulatory definition for “ambient air”, the EPA disagrees. Micro- and 

middle-scale are already comparable to the NAAQS for all other pollutants, and even for 

PM2.5, all operating micro- and middle scale sites are comparable to at least the 24-hour 

NAAQS. The EPA believes that its long-standing definition of ambient air is well suited 

to provide for the consistency needed in ensuring monitors are appropriately sited for 

comparison to the NAAQS. The EPA disagrees that this change would lead to an 

expansive interpretation for “any” within the CAA, rather as we have stated, it will 

promote consistency across all pollutants in determining their applicability to the 

NAAQS. Moreover, all PM2.5 monitoring sites must also be representative of area-wide 

locations to make the comparison to the annual NAAQS. Thus, these sites will represent 

locations where there is population exposure. Consistent with the long-standing practice 

of monitoring agencies in locating ambient monitors, we also note that all currently 

existing PM2.5 monitors are located in areas that are representative of population 

exposures based on supporting data in the AQS. 

The EPA does not believe it is necessary to remove the ability of Regional 

Administrators to determine monitor comparability. The EPA Regional Offices are the 

most familiar with their individual State networks and possible changes to them. We do 

not believe that removing the Regional Administrator from the process of approving 

micro- or middle-scale sites from comparison to the annual NAAQS, will promote 

consistency. Rather we believe that information provided by monitoring agencies in their 

annual monitoring network plans will be sufficient to consistently apply 

recommendations and support determinations by the EPA Regional Administrator as to 

whether micro- or middle-scale sites are to be considered” area-wide. With regard to the 

comment “that monitors may be established in areas subject to highly localized 

conditions (perhaps measuring highly transient air quality in areas measuring no more 
V-15 

than a few square meters)”, EPA believes this to be an unrealistic observation for PM2.5

based on the secondary nature of fine particle formation that provides for a more 

homogenous concentration distribution as compared with pollutants dominated by 

primary emissions such as CO or PM10. 

(8) Comment: One commenter (EEI, 2012) stated that EPA is proposing to change the 

current presumption that micro- and middle-scale monitors are unique and therefore are 

only comparable to the annual PM2.5 NAAQS if approved by an EPA Regional 

Administrator. EPA claims that its intent in amending the current regulations is solely for 

consistency and predictability in the interpretation of monitoring requirements. Micro 

scale monitors are defined as applying to “concentrations in air volumes associated with 

air dimensions ranging from several meters up to about 100 meters” (emphasis added). 

Middle scale monitors are defined as “typical of areas up to several city blocks in size 

with dimensions ranging from about 100 meters to 0.5 kilometers” (emphasis added). 

When these vague regulatory definitions are combined with EPA’s proposal to allow 

“any” micro- or middle-scale monitor to be comparable to the NAAQS, the result is a 

“standardless” standard. Under the EPA’s proposed rule, the placement of a monitor may 

literally occur anywhere and hence the regulations provide for an arbitrary and capricious 

designation of nonattainment areas. The EPA provides no analytical support in the record 

for this fundamental change in position. In place of current restrictions, the EPA states 

that “any potential location for a PM2.5 monitoring site would be eligible for comparison 

to the annual NAAQS.” Rather than promote consistency, the change would have the 

opposite effect given the expansive interpretation of “any” within the CAA. The EPA 

should retain the current requirement and consider revising the current regulations to 

remove the ability of a Regional Administrator to determine monitor comparability. 

These changes would better promote the goal of national uniformity by making it clear 

that monitors would not be subject to highly localized conditions (perhaps down to the 

transient air quality in an area measuring no more than a few meters wide) or subject to 

the preferences on an individual Regional Administrator. 

Response: The EPA disagrees with the commenter for several reasons. The EPA asserts 

that it has always been true that the placement of a monitor may potentially occur 

anywhere. However, the EPA’s long-standing practice does not allow a monitor to be 

compared to a NAAQS unless it represents ambient air. Even under current rules, when a 

monitor is placed in an environment that represents ambient air, regardless of the scale of 

representation or whether it represents area-wide air quality it is eligible for comparison 

to the 24-hour PM2.5 NAAQS. When a monitor – at any scale – represents area-wide air 

quality it is also eligible for comparison to the annual NAAQS. None of these criteria 

have changed, other than saying “area-wide” instead of “community-wide”, which terms 

are synonymous. With regard to the comment that “Under EPA’s proposed rule, the 

placement of a monitor may literally occur anywhere and hence the regulations provide 

for an arbitrary and capricious designation of nonattainment areas”, the EPA notes that 

such issues can appropriately be handled with the designations process, when states have 

the opportunity to address the interpretation of ambient air data and make 

recommendations on the size of the nonattainment areas based on their interpretation of 

ambient monitoring data. 
V-16 

(9) Comment: Commenters (ALA et al., 2012) stated, “We especially welcome EPA’s 

proposal to abandon and revoke regulatory language in Part 58 that effectively prevented 

the implementation of the PM2.5 NAAQS to protect populations exposed to incremental 

concentrations near transportation facilities. These include the current prohibitions 

against comparison of micro- and middle-scale monitors with the annual NAAQS, and 

the requirement that only “population-oriented” monitors be compared with the 24-hour 

NAAQS. For the reasons discussed below, we believe these policies impose limitations 

on the applicability of the NAAQS that are inconsistent with the text, purpose and intent 

of the Clean Air Act, and must be revoked.

Response: The EPA disagrees that a prohibition has existed against the comparison of 

micro- and middle-scale monitors with the annual NAAQS. Current regulatory language 

in section 58.30 addresses the NAAQS applicability issue that where micro- and middlescale sites are representative of many such locations throughout an area, they likewise 

represent “area-wide” air quality and are eligible for comparison to the annual NAAQS. 

This flexibility and inclusion in the annual monitoring network plan process has been a 

long-standing practice that is not changed in this rulemaking. The EPA also disagrees that 

monitors placed near transportation facilities would ever have been discounted in a 

manner suggested by the commenters. As long as such monitors were located in ambient 

air, they would have been comparable to the 24-hour NAAQS. Any such monitors that 

were approved as area-wide monitors would also have been comparable to the annual 

NAAQS. 

(10) Comment: One commenter (CLF) stated that they support EPA’s plans to allow air 

quality measured at micro- and middle-scale sites near roadways to be compared to the 

annual standard. 

Response: EPA notes that current regulatory language in section 58.30 addresses the 

NAAQS applicability issue that where micro- and middle-scale sites are representative of 

many such locations throughout an area, they likewise represent “area-wide” air quality 

and are eligible for comparison to the annual NAAQS. This eligibility for comparison to 

the annual NAAQS has been a long-standing practice that is not changed in this 

rulemaking. 

F. Comments on the addition of PM2.5 monitors to the near-road monitoring stations. 

(1) Comment: One commenter strenuously objected to the PM2.5 roadway network concept. 

The concerns expressed included access, safety, and other logistical problems involving 

roadside monitoring. 

Response: As stated in section VIII of the final rule, the addition of PM2.5 monitors to the 

near-road environment is part of a multipollutant design at monitoring stations that are 

already required and being implemented as part of the required NO2 monitoring network. 

The issues referenced by the commenter have already been addressed in a Technical 

Assistance Document that has been provided to monitoring agencies. Therefore, EPA 

anticipates any issues on siting of the stations will already be resolved by the time the 
V-17 

PM2.5 monitors are required to be operating. To the extent that significant problems do 

arise with siting a near-road PM2.5 monitor, EPA has existing authority to address such 

situations on a case-by-case basis, or could undertake changes to the rule as necessary. 

(2) Comment: One commenter stated that a near-road monitor may result in it being the 

controlling monitor for an area, where the components of PM2.5 have not been fully 

identified, and that this is a national issue where more research is needed. 

Response: As stated in section VIII of the final rule, the addition of PM2.5 monitors to the 

near-road environment is to support a number of monitoring objectives. Specifically on 

the use of data for comparison to the PM2.5 NAAQS, the EPA points out that people 

spend a substantial amount of time in these environments, resulting in a significant 

potential for exposure to pollutants. The agency believes near-road monitoring is 

important to ensure that public health is protected with an adequate margin of safety. 

EPA agrees that more information is needed on the components of PM2.5 near roads, and 

supports the use of supplemental measurements (e,g., aethalometers for black carbon) to 

contribute to this body of information. 

(3) Comment: One commenter stated that they would support PM2.5 near-roadway monitors 

if these monitors were used for research data collection purposes and not as a controlling 

monitor. 

Response: As stated in section VIII of the final rule, the addition of PM2.5 monitors to the 

near-road environment is to support a number of monitoring objectives. Specifically on 

the use of data for comparison to the PM2.5 NAAQS, the EPA points out that these 

monitors will be sited at existing near-road stations. Accordingly, data from these nearroad monitors will be compared to the PM2.5 24-hour NAAQS and where determined to 

be an area-wide monitoring location they will also be compared to PM2.5 annual NAAQS. 

The comparison of these sites to the PM2.5 NAAQS is appropriate as these sites will 

represent ambient air. The EPA also agrees that more information is needed on many 

aspects of PM2.5 levels near roads, and supports the use of supplemental measurements 

(e,g., aethalometers for black carbon, ultrafine particles) to contribute to research on this 

topic. 

(4) Comment: Several commenters stated that while the requirement for near-road PM2.5

monitoring can be met by collocation at a near-road NO2 station, the requirement could 

also be met by locating a PM2.5 monitor at a different near-road location where PM2.5

concentrations are expected to be high. 

Response: The EPA discusses this issue in section VIII.B.3.b.i of the preamble to the 

final rule. The EPA concludes that there are sufficient existing authorities to address this 

issue on a case-by-case basis if necessary, e.g., where a near-road site is not area-wide, 

and that no additional regulatory language is needed. 
V-18 

(5) Comment: One commenter stated that if additional measurements at near-road monitoring 

stations are believed to offer increased knowledge of the near-road environment, EPA 

should implement a national level program to address the data need. 

Response: The EPA can consider such a program in future planning. In at least one 

example, EPA’s Office of Research and Development is partnering with a state 

monitoring agency to support the deployment of additional monitors at a required nearroad station. 

(6) Comment: Several commenters recommended the near-road PM2.5 network should be 

smaller and more specifically designed to capture the data needed to characterize the 

near-source exposures and correlate them to key source variables that extrapolate to other 

locations. 

Response: The EPA considered comments on the size of the network in finalizing the 

requirements for the final rule. Rationale for the size of the network is explained in 

section VIII.B.3.b.i of the preamble to the final rule. As noted in the previous response, 

the EPA continues to pursue additional information on near-road environments. 

(7) Comment: Several commenters recommended that the expected maximum concentration 

PM2.5 monitoring sites be neighborhood scale and that the maximum concentration site 

not be subject to relocation on a year-to-year basis. 

Response: The EPA agrees with the commenters and has adjusted the requirements 

accordingly. See section VIII.B.3.b.i of the preamble to the final rule for a more detailed 

explanation of this issue. Specifically, EPA has addressed this issue in the final rule by 

clarifying language in Appendix D, section 4.7.1(b)(1) to state that “At least one 

monitoring station is to be sited at neighborhood or larger scale in an area of expected 

maximum concentration.” 

(8) Comment: Several commenters recommended that we can improve the efficiency and 

effectiveness of the PM2.5 network and reduce implementation costs by a combination of 

phasing, timing, and focusing the scope of the near road monitoring portion of the 

network by: refocusing the near-road network to provide better characterization of mobile 

source emissions at a more limited number of sites including the correlation of emissions 

to key variables such as traffic, volume, fleet composition, and prevailing winds; initiate 

deployment of the near-road network in MSAs with populations greater than 2.5 million; 

and commence deployment of near-road PM2.5 monitors one year after implementation of 

near road NO2 monitors. 

Response: These issues are addressed in section VIII.B.3.b.i of the preamble to the final 

rule. 

(9) Comment: One commenter stated that they understand the need to develop better 

characterization of near-road exposures to PM2.5. 
V-19 

Response: The comment in support of the proposal is acknowledged. 

(10) Comment: One commenter stated that for those CBSAs with just one required monitor, 

that monitor should be at a neighborhood scale. 

Response: The EPA agrees with the commenters and has adjusted the requirements 

accordingly. See section VIII.B.3.b.i of the preamble to the final rule for a more detailed 

explanation of this issue. Specifically, the EPA has addressed this issue in the final rule 

by clarifying language in Appendix D, section 4.7.1(b)(1) to state that “At least one 

monitoring station is to be sited at neighborhood or larger scale in an area of expected 

maximum concentration.” 

(11) Comment: One commenter stated the monitoring networks resources should be used to 

support a developed NAAQS, not to support exploratory research. Until such time the 

EPA can clarify the connection between near-roadway emissions concentrations and 

population exposure, we believe that participation in this research should be voluntary 

rather than mandated by code. 

Response: As explained in the preamble to the final rule, the EPA points out that a 

significant fraction of the population lives, works, plays, and goes to school near major 

roads and that these exposures occur in locations that represent ambient air for which the 

agency has a responsibility to ensure the public is protected with an adequate margin of 

safety, including through the requirement for a minimum number of ambient monitors for 

the NAAQS. Indeed, one study identified that 45 million Americans live within 300 feet 

of a highway with four or more lanes, a railroad, or an airport, and given the relative 

ubiquity of roads, EPA anticipates that those are predominantly near-road exposures. See 

study of the American Housing Survey, which is available on the web at: 

http://www.census.gov/housing/ahs/data/ahs2009.html. 

(12) Comment: Two commenters stated that any near-roadway monitor should be classified 

as representative of micro-scale conditions and thus exempt from comparison to the 

NAAQS. 

Response: There is no exemption from comparability to the NAAQS based solely on the 

scale of representation. There are requirements for comparability to the annual PM2.5

NAAQS based on whether a site is approved in an annual monitoring network plan as 

area-wide or not. Near road monitors will be evaluated by monitoring agencies and the 

EPA to determine whether they meet the criteria to be classified as “area-wide” or not. 

However, all sites representative of ambient air are at a minimum compared to the 24-

hour PM2.5 NAAQS. Where an existing near-road site is not classified as area-wide for 

PM2.5, EPA will work with monitoring agencies to determine whether it is appropriate to 

locate the monitor at a different location, such as a near-road site that is area-wide for 

PM2.5. 

(13) Comment: One commenter stated that agencies need the maximum amount of time 

possible to comply with the new near-road monitoring requirements; however, they do 
V-20 

believe they can comply with the proposed requirement for PM2.5 monitors at near-road 

stations by January 1, 2015. 

Response: As explained in section VIII.B.3.b.i of the preamble to the final rule, the EPA 

is finalizing a phased in approach for deployment of the required near-road PM2.5

monitors. 

(14) Comment: One commenter supports the proposal to allow research at selected near-road 

monitoring stations, so long as this remains voluntary. 

Response: The comment in support of the proposal is acknowledged and the EPA is 

adopting the proposed approach in the final rule. 

(15) Comment: One commenter stated with regard to the EPA’s proposal to relocate PM2.5

monitors to meet the near-roadway environment, the EPA rarely allows a state to simply 

shut down a monitoring station and relocate it. Also, that the assumption that states will 

have extra PM2.5 monitors to relocate to near-roadway sites is simply untenable and 

unrealistic. 

Response: The EPA appreciates the concern regarding the challenges of relocating a site, 

including getting approval from EPA Regional Offices. As explained in section 

VIII.B.3.b.i of the preamble to the final rule, the EPA will work with monitoring agencies 

in the phased implementation to address which monitors will be most appropriate for 

relocating. Also, as explained in the preamble, the EPA is aware that every existing 

PM2.5 monitor has value to someone or some data user and that relocating these sites will 

result in the loss of that data; however, the EPA maintains that on balance, the siting of 

the monitors in the near-road environment will provide for a better overall network 

design to address a number of monitoring objectives. 

(16) Comment: The EPA has not provided any information showing the near-roadway data 

would have any meaning with respect to measurement of population exposures. The 

proposed near-road monitoring network is more appropriately addressed in a research 

venue until such time that the EPA can adequately demonstrate that near-roadway 

environment has a direct nexus to a population exposure. 

Response: As explained in section VIII.B.3.(b) i of the preamble to the final rule and in 

response to Comment (11) above, people spend a substantial amount of time in proximity 

to major roadways and EPA believes near-road monitoring is important to ensure that 

public health is protected with an adequate margin of safety. 

(17) Comment: The PM near-road monitors appear to be an EPA-mandated, state-operated 

research project. These monitors do not capture broadly representative ambient air, thus 

they are likely to provide a comparison to the NAAQS not foreseen by the Clean Air Act. 

Response: As explained in, section VIII of the preamble to the final rule and this 

response to comments, there are large numbers of people (in the tens of millions) that 
V-21 

live, work, play, and go to school in close in proximity to major roadways. These 

exposures occur in locations that represent ambient air for which the agency has a 

responsibility to ensure the public is protected with an adequate margin of safety. 

Comparison of monitoring results from such areas to the NAAQS is therefore 

appropriate. The EPA disagrees that the data produced from PM2.5 near-road monitors 

compared to the NAAQS will result in something unforeseen by the Clean Air Act. 

(18) Comment: One commenter disagrees with the placement of (PM2.5) monitors used to 

represent long-term public exposure at near-road sites because the data are not 

representative enough to compare to a national standard. 

Response: The EPA disagrees that the near-road PM2.5 data are not representative 

enough to compare to a national standard. The purpose of a national ambient air quality 

standard is not to achieve an average ambient air quality, with some areas above or below 

the standard, but to establish a level of air quality that all areas achieve. Likewise the 

purpose of a monitoring network design plan, given necessarily limited resources, is 

generally to locate monitors in areas that pose a risk of exceeding the standard, subject to 

decisions about the appropriate spatial scale or, as here, area-wide monitoring. If the 

comment is suggesting that the data should not be comparable to the annual NAAQS 

even where there is an “area-wide” monitor, the EPA rejects that argument for the 

reasons explained elsewhere in this document and the preamble. Moreover, if the 

premise of the comment is that more polluted populated areas are by definition 

unrepresentative, the EPA rejects that premise, and further rejects the comment that siting 

some monitors in near roadway environments makes the standard more stringent or 

impermissibly more stringent. As discussed in section VIII.B.3.b.i of the preamble to the 

final rule, a significant fraction of the population lives in proximity to major roads, and 

these exposures occur in locations that represent ambient air. Monitoring in such areas 

does not make the standard more stringent than warranted, but rather affords the intended 

protection to the exposed populations, among them at-risk populations, exposed to fine 

particles in these areas. Thus, in cases where monitors in near roadway environments are 

deemed to be representative of area-wide air quality they would be compared to the 

annual standard. The 24-hour and annual NAAQS are designed to protect the public with 

an adequate margin of safety, and this siting provision is fully consistent with providing 

the protection the standard is designed to provide and does not make the standard more 

stringent or more stringent than necessary. 

Monitors that are representative of area-wide air quality may be compared to the annual 

standard. This is consistent with the use of monitoring data in the epidemiological studies 

that provide the primary basis for determining the level of the annual standard. In 

addition, the EPA notes that the annual standard is designed to protect against both longand short-term exposures through controlling the broad distribution of air quality across 

an area over time.39 It is fully consistent with the protection the standard is designed to 

provide for near road monitors to be compared to the annual standard if the monitor is 

 

39 This is in contrast to the 24-hour standard which is designed to provide supplemental protection, addressing peak 

exposures that might not otherwise be addressed by the annual standard. Consistent with this, monitors are not 

required to be representative of area-wide air quality to be compared to the 24-hour standard. 
V-22 

representative of area-wide air quality. This does not make the standard either more 

stringent or impermissibly more stringent. Furthermore, as the agency explained in the 

discussion of the form of the annual standard, higher measuring monitors are often 

located in areas where there are higher numbers of at-risk populations. These areas 

require requisite protection with an adequate margin of safety, and placing monitors in 

such areas and comparing results from such monitors to the PM2.5 NAAQS is part of that 

process of affording requisite protection with an adequate margin of safety. 

(19) Comment: A single monitoring station near a heavily travelled roadway is not adequate 

to describe the gradient of PM components with increasing distance from the roadway. 

Response: The EPA is not attempting to address the question of PM components in the 

near-road environment, other than as explained in the proposal, those monitoring 

agencies that voluntarily deploy additional instrumentation in the near-road environment. 

Additionally, the EPA is not attempting to describe the gradient with a single monitoring 

station. As described in the preamble to the final rule, the network design is intended to 

provide for representative near-road monitoring stations that are collocated with NO2 and 

CO. Thus, while a gradient of the PM2.5 concentrations from representative near-road 

stations to neighborhood scale stations may be possible, if such neighborhood scale 

monitoring sites are located in the same general vicinity, it is not the EPA’s goal to have 

these gradients determined for every area. 

(20) Comment: One commenter states that near-road monitoring sites should be considered 

micro-scale sites due to the lack of experience with these monitoring sites, data, and 

experimental nature of near-road monitoring. Only when we have a better understanding 

of their relationship to population exposure should these sites be considered for 

comparison to the NAAQS. 

Response: The relative experience of monitoring has nothing to do with the scale of 

representation of a monitoring station or its applicability to the NAAQS. Rather the 

variability of that data at the location where it is monitored compared to the variability 

of that pollutant in the surrounding area is what defines its scale of representation. As 

explained in the section VIII of the preamble to the final rule and in earlier responses in 

this document, there are large numbers of people (in the tens of millions) that live, 

work, play, and go to school in close proximity to major roadways. These exposures 

occur in locations that represent ambient air and the EPA believes near road monitoring 

is important to ensure the public is protected with an adequate margin of safety. 

(21) Comment: The continued collection of data from the neighborhood scale monitors is 

absolutely necessary because they represent typical worst-case air quality for each Core 

Based Statistical Area. 

Response: The EPA generally agrees with the need for continued collection of 

neighborhood scale data. This comment is addressed in more detail in section 

VIII.B.3.b.i of the preamble to the final rule for a more detailed explanation of this issue. 

Specifically, EPA has addressed this issue in the final rule by clarifying language in 
V-23 

Appendix D, section 4.7.1(b)(1) to state that “At least one monitoring station is to be 

sited at neighborhood or larger scale in an area of expected maximum concentration.” 

(22) Comment: One commenter disagreed with the proposal to add a near-road component to 

the compliance monitoring network. The micro-scale nature of these sites precludes the 

data from being used for all of the monitoring objectives except source characterization. 

Response: The EPA notes that near-road monitors must represent “area-wide” air quality 

to be comparable to the annual NAAQS, and that we have a process for determining 

whether sites at smaller scales (i.e., micro- or middle-scale) represent “area-wide” air 

quality. The EPA disagrees with the commenter that the micro-scale nature of the nearroad sites precludes their use for all monitoring objectives, except source 

characterization. These sites in combination with the neighborhood scale sites in the 

same CBSA will support a number of monitoring objectives as explained in section 

VIII.B.3.b.i of the preamble to the final rule. 

(23) Comment: One commenter stated that the proposal would remove the population 

exposure objective from sites used in NAAQS determinations and permit micro- and 

middle-scale sites to be classified as area-wide. Micro- and middle-scale data are not 

applicable for CBSA-wide exposures and can’t be used for many of the monitoring 

objectives including health studies, pollution trends analysis, or State Implementation 

Plan (SIP) development and control strategy development where necessary. 

Response: As explained in the preamble, the PM2.5 monitors at near-road monitoring 

stations will in fact support a number of monitoring objectives, including all of the 

monitoring objectives, where necessary, that the commenter lists (i.e., health studies, 

pollution trends analysis, or State Implementation Plan (SIP) development and control 

strategy development where necessary) in the comment. The EPA disagrees that we are 

removing population exposure from sites used in NAAQS determinations. The near-road 

monitoring stations, when determined to be representative of many such locations 

throughout an area, are considered to represent “area-wide’ air quality and as such are 

representative of those population exposures where large numbers of people live, work, 

play, and go to school. 

(24) Comment: One commenter states that the inclusion of PM2.5 measurements near 

roadways is consistent with CASAC’s recommendations to develop the near roadway 

network with a multipollutant focus and to include PM2.5 on the list of pollutants that 

should be measured. 

Response: The comment in support of the proposal is acknowledged and the EPA is 

adopting the proposed approach in the final rule. 

(25) Comment: Several comments stated that the deployment of new near-roadway 

monitoring should not come at the expense of existing PM2.5 network objectives, 

including neighborhood scale population exposure, AQI reporting, environmental justice, 

transport, and background. 
V-24 

Response: As explained in the preamble to the final rule, the PM2.5 monitors at near-road 

monitoring stations will support a number of monitoring objectives, including several of 

the monitoring objectives that the commenter lists in the comment. Also, as explained in 

the preamble, the EPA is aware that every existing PM2.5 monitor has value to someone 

or some data user and that relocating these sites will result in the loss of that data; 

however, the EPA maintains that on balance, the siting of the monitors in the near-road 

environment will provide for a better overall network design to address monitoring 

objectives. 

(26) Comment: One commenter stated that for CBSAs with populations greater than 1 million, 

the proposed rule would require that one site be collocated with a near roadway NO2 site, 

which has no corresponding requirement to be an area-wide monitor. 

Response: The assignment of whether a monitor represents area-wide air quality is by a 

combination of the pollutant and the location of the station and not just the location of the 

station itself. The EPA anticipates that PM2.5 monitoring located at near-road monitoring 

stations will often be representative of area-wide air quality, and will consider requests 

for limited deviations from the requirements of Appendix D, as necessary and 

appropriate, where an existing near-road site is not classified as “area-wide” for PM2.5. 

Also, although the EPA does not require the NO2 near-road sites to be area wide, we do 

explain the in the Near-road NO2 Monitoring Technical Assistance Document (TAD) that 

higher weight should be placed on sites that are most influenced by typical roadway 

activity rather than those that are heavily influenced by unique sources or features. 

(27) Comment: One commenter stated that they understand and agree with the objective to 

maximize resources by collocating near road monitors, as well as the desire for 

comprehensive, multi-pollutant data a single location. 

Response: The comment in support of the proposal is acknowledged and the EPA is 

adopting the proposed approach in the final rule. 

(28) Comment: One commenter provided recommendations on new language for cases where 

a third PM2.5 SLAMS monitor is required in a CBSA. The recommendation stated “For 

areas with additional required SLAMS, a monitor should be installed to provide 

additional information necessary for one of the following objectives: source 

characterization, health studies, selection of control strategies or SIP implementation”. 

Response: The EPA believes the existing language is sufficient to encompass the 

recommendations in the comment. 

(29) Comment: One commenter stated that the proposed near-roadway monitoring to measure 

particulate matter from transportation sources is only warranted with a species-based 

standard. The commenters also states that many recognized medical experts have long 

believed that transportation related PM2.5 is a major contributor to human health impacts. 

So from that standpoint, the EPA’s proposal to add PM2.5 ambient air monitor to roadway 
V-25 

locations might be a positive step , but only if the agency is proposing a speciated PM2.5

standard. 

Response: The EPA has addressed the issue of considering a species based standard in 

section III.E.1 of the preamble to the final rule. As stated there, the Administrator 

concluded, consistent with CASAC advice, that the currently available scientific 

information did not provide a sufficient basis for either targeting or eliminating any 

individual component or group of components associated with any source categories 

from the mix of fine particles included in the PM2.5 mass-based indicator. Consequently, 

although EPA agrees with the comment that adding PM2.5 monitoring roadway is a 

positive step, and accordingly has finalized a requirement for monitoring for PM2.5 mass 

at a modest number of locations, the EPA disagrees that a consequence of such a 

monitoring approach must be a speciated indicator for the standard. 

(30) Comment: One commenter provided a detailed follow-up comment on the EPAs 

proposal to revise the form of the annual PM2.5 standard to base the standard on the 

highest community-oriented monitor in an area and to eliminate spatial averaging. The 

commenter stated that, according to the EPA, for an area with multiple monitors, the 

appropriate reporting monitor with the highest design value would determine the 

attainment status for that area. The commenter does not support this approach as it is not 

consistent with monitoring results from health study analyses. Furthermore, the 

commenter is very skeptical of this approach given the EPA’s intent to locate more 

monitors along roadways in major urban areas without the requisite knowledge of what 

the PM2.5 readings might be from these monitors. 

Response: The EPA has addressed the issue of eliminating spatial averaging in section 

III.E.3.a of the preamble to the final rule. Regarding the comment that this approach is 

not consistent with the monitoring results from health study analyses, the EPA considered 

this issue in the form of the standard which is also described in section III.E.3.a of the 

preamble to the final rule. As explained in section II.E.c.i.1 of the preamble to the final 

rule, it is appropriate to compare the PM2.5 concentrations from a maximum area-wide 

monitor to the level of the annual PM2.5 standard. Regarding the commenter’s statement 

on having the requisite knowledge of what the PM2.5 readings might be from these 

monitors, the EPA has considered the available information40 and the need to protect the 

public health with an adequate margin of safety in deciding to move forward with this 

requirement. 

(31) Comment: One commenter stated the net effect of relocating the 52 monitors (the 

monitors to be located in the near-road environment) will be to overestimate the ambient 

air concentration of PM2.5. These roadside monitors would be measuring PM2.5 in a worst 

case scenario that would not be representative of ambient air. 

Response: The EPA does not believe it will overestimate ambient air concentrations of 

PM2.5 in the near road environment for the following reasons. First, when monitoring is 

 

40 In the preamble to the final rule we cite multiple studies (Ntziachristos et al., 2007; Ross et al., 2007; Yanosky et 

al., 2009; Zwack et al., 2011) that are relevant to informing what the PM2.5 readings may be. 
V-26 

performed, it is an actual measurement and does not constitute an estimate of conditions 

present at that location. Second, the EPA in almost all cases purposely requires air 

agencies to site ambient air monitoring in areas that represent maximum concentrations, 

particularly to meet objectives such as assessing NAAQS compliance. EPA does this to 

focus monitoring resources where they are most worthwhile to assess compliance with 

the NAAQS and protection of public health and welfare. For example, our monitoring 

requirements are typically stated to site monitors “in area of expected maximum 

concentration”. This is described repeatedly throughout Appendix D to Part 58. Third, 

EPA’s long-standing practice is to locate monitors that meet the definition of ambient air. 

In the final rule EPA is requiring PM2.5 sites in near-road environments to be collocated 

with NO2. EPA notes that near-road monitors that are not “area-wide” will not be 

eligible for comparison to the annual NAAQS, but EPA believes that monitors 

comparable to the NAAQS will be representative of ambient air and representative of 

actual exposures in the near-road environment. 

(32) Comment: One commenter stated that the EPA needs to consider modifications to the 

monitoring system for PM2.5 emissions beyond the roadside monitors before 

implementing any revisions to the PM2.5 standard and making nonattainment 

designations. The existing PM2.5 monitoring network is not sufficient to predict ambient 

air concentrations reliably for all facility locations. For example, many monitors are 

located in areas expected to yield the highest PM2.5 emissions. This high sampling bias is 

not representative of the true ambient air concentrations and will result in an 

unrealistically high number of nonattainment areas. For example, the ambient air levels 

for one foundry located in a rural setting are determined from a PM2.5 emissions monitor 

that is located in a more urban area located 60 miles away. Consequently, the foundry 

may be subject unnecessarily to restrictions on modernization and expansion based on a 

nonattainment designation from biased and unrepresentative PM2.5 emissions monitoring 

data. 

Response: The network design criteria for ambient air monitoring of PM2.5 does not 

specifically require source oriented monitoring stations; rather the network design is 

primarily focusing on characterizing area-wide air quality which represent many such 

locations within urban areas. The EPA purposely requires monitoring sites in the area of 

expected maximum concentration where it also represents area-wide air quality. The EPA 

does not believe it is necessary to address source oriented monitoring for facilities, for 

which there are no specific requirements, prior to implementing PM2.5 monitoring in 

near-road environments. Any such discussion would necessarily be premature, absent the 

specific facts and regulatory context. The EPA notes that areas are designated 

nonattainment based on a determination that the area either violates or contributes to a 

violation of the NAAQS, and States are only required to implement those control 

measures that will attain the NAAQS as expeditiously as practicable. Issues as to the 

proper extent of the nonattainment area or control strategy may be considered as those 

issues arise, but EPA does not believe that avoiding a determination of nonattainment is a 

reason to change the monitoring network design requirements. 
V-27 

We note further, however, that the final rule expressly provides that PM2.5 measurement 

data from monitors that are not representative of area-wide air quality but rather of 

relatively unique micro-scale, or localized hotspot, or relatively unique middle-scale 

impact sites are not eligible for comparison to the annual PM2.5 NAAQS. The rule gives 

the specific example of “a micro- or middle-scale PM2.5 monitoring site ... adjacent to a 

unique dominating local PM2.5 source” being eligible only for comparison to the 24-hour 

PM2.5 NAAQS. Additionally, the majority of the PM2.5 monitoring network consists of 

monitors that represent neighborhood scale or areas up to several kilometers across. 

Accordingly, the EPA believes that the revised PM2.5 network will continue to 

appropriately characterize concentrations in a wide variety of settings. 

(33) Comment: Several commenters summarized a series of concerns regarding the EPA’s 

proposal to end spatial averaging, to establish a new requirement for roadside monitoring, 

allow comparison of micro- and middle-scale monitors to the PM2.5 NAAQS and revoke 

the long-standing requirement that PM2.5 monitors used for comparison to the 24-Hour 

PM2.5 NAAQS be “population-oriented”. The commenters generally object to these 

changes and request that EPA not act to finalize any of the new requirements. One of the 

rationales provided was that EPA has not provided sufficient rationale in the proposed 

rule for the changes, and the combined effect of all the changes would be to substantially 

revise the stringency of either the existing PM NAAQS (if retained) or any newly revised 

NAAQS. 

Response: These comments are addressed in section III and section VIII of the preamble 

to the final rule. 

(34) Comment: One commenter stated that although the EPA indicates that the new near-road 

micro-scale monitoring for PM2.5 promotes efficiency, the EPA has apparently not 

considered in any substantial fashion the differences between NO2 and PM2.5 formation in 

such an environment. Instead, the EPA’s roadside monitoring plan is inherently and 

irretrievably arbitrary: The EPA essentially admits that the only reason that PM2.5

monitors will be placed in such locations is that the EPA previously required such a new 

monitoring network for an entirely different pollutant. 

Response: EPA disagrees that it has not considered the differences between NO2 and 

PM2.5. As stated in section VIII.B.3.b.i of the preamble, the EPA is requiring the addition 

of PM2.5 monitors at near-road stations to support a number of monitoring objectives. 

Therefore, we reject the comment that the only reason we are placing PM2.5 monitors in 

near-road environments is that we already have a monitoring network there for another 

pollutant (i.e., NO2). Regarding the comment that we have apparently not considered, in 

any substantial fashion, the difference between NO2 and PM2.5 formation in such an 

environment, the EPA believes that the characterization of representative maximum 

PM2.5 concentrations due to on-road mobile sources and the appropriate location of such 

PM2.5 monitors will be the same approximate locations that are the focus of the near-road 

NO2 network. This is due to the fact that PM2.5, like NOX, is disproportionately 

influenced by heavy duty (HD) vehicles which are predominantly diesel fueled, when 

compared to light duty (LD) vehicles which are primarily gasoline fueled. Specifically, 
V-28 

for both PM2.5 and NOx, HD vehicles emit more of these two pollutants and their 

precursors on a per vehicle basis than LD vehicles. The EPA recognized this fact in the 

near-road NO2 network by requiring states to consider the fleet mix of candidate road 

segments where near-road monitoring might occur. In the design of the NO2 near-road 

network where the PM2.5 monitors will be installed, states were instructed to place a 

higher priority on those highly trafficked roads which have more diesel fueled vehicles 

using a metric called the fleet equivalent average annual daily traffic. 41 As such, the 

Agency believes it is appropriate that required near-road PM2.5 monitors would be located 

with near-road NO2 monitors as they are similarly influenced not only by fleet mix but 

also by total traffic count, congestion patterns, roadway design, terrain, and meteorology. 

In addition, as discussed in section VIII of the preamble, where an air agency believes a 

different location is a more appropriate site for a near-road PM2.5 monitor, the EPA can 

use its discretion in approving a deviation from the PM2.5 monitoring requirements under 

existing authority in the network design criteria. A deviation would be appropriate for 

consideration where, for example, a state provides quantitative evidence demonstrating 

that peak ambient PM2.5 concentrations would occur in a near-road location which meets 

siting criteria but is not a near-road NO2 monitoring site. Such deviations may be 

approved by the Regional Administrator as described in section 4.7.1 of Appendix D to 

part 58. 

(35) Comment: One commenter stated that in the final rule for the NO2 NAAQS, the near 

road monitoring requirement was justified by the EPA explicitly on the basis of the 

averaging time and level of the standard (e.g., the EPA finalized a new 1-hour standard at 

a level of 100 parts per billion (“ppb”)). In taking this action, the EPA noted that NO2

concentrations could be expected to vary, and therefore, the differences between nearroadway monitors and area-wide concentrations that had been used to measure 

compliance with the pre-existing NO2 annual standard could result in a variable level of 

the standard (i.e., between 50 ppb and 75 ppb based on whether concentrations near 

roadways were 100% or 30% higher than at other monitors). Yet, in this proposed rule, 

the EPA does not offer any comparable analysis with respect to the relative stringency of 

a PM2.5 annual or 24-hour NAAQS as implemented through a network of new roadside 

monitors. 

This lack of information is even more notable since the EPA is proposing that the probe 

and siting criteria for near-road PM2.5 monitoring follow the same probe and siting 

criteria for the NO2 near-roadway monitoring sites. These criteria require monitors “as 

near as practicable” to the outside nearest edge of traffic lanes, but no greater than 50 

meters from the edge of a road. AFPM provided comments to the EPA in 2009 regarding 

the severe limitations and qualifications that are associated with such monitors. To briefly 

reiterate and as reflected in the NO2 NAAQS ISA and REA, such monitors suffer from 

issues involving accuracy and the relationship between area-wide monitoring data and 

roadside emissions is highly variable. In addition, there is increased potential for errors 

associated with monitor placement. 

 

41 See the Near-road NO2 Monitoring Technical Assistance Document at: 

http://www.epa.gov/ttn/amtic/files/nearroad/NearRoadTAD.pdf
V-29 

Response: As explained in section III.E.c.i.1 of the preamble to the final rule, it is 

appropriate to compare the PM2.5 concentrations from a maximum area-wide monitor to 

the level of the annual PM2.5 standard. Consequently, the approach adopted in this 

rulemaking for the PM2.5 standard is consistent with the ultimate thrust of the approach in 

the NO2 NAAQS: providing a level of protection in an area with a maximum monitor 

affords requisite protection across the entire area. However, given differences in the 

bodies of available scientific evidence for NO2 and PM2.5, it is appropriate that EPA 

employed different types of analyses in the two reviews to achieve this ultimate result. In 

the case of NO2 the scientific evidence that formed the basis for the final decision on the 

level of the revised standard included both epidemiological studies, reporting associations 

between respiratory endpoints and area-wide NO2 concentrations, and controlled human 

exposure studies, reporting respiratory effects following short-term exposures to NO2

concentrations at or above 100 ppb. In considering this evidence, the Administrator set a 

new 1-hour standard with a level of 100 ppb. 

In setting this new standard, information on the NO2 gradients around roadways was used 

to consider the relationships between area-wide NO2 concentrations and potential 

exposure concentrations. Specifically, because the revised NO2 standard was intended to 

reflect the maximum allowable NO2 concentration in an area, the Administrator 

concluded that this standard would limit exposures to NO2 concentrations reported in 

controlled human exposure studies to result in respiratory effects. In reaching this 

conclusion, the Administrator noted that the highest NO2 exposure concentrations in 

urban areas could occur around major roadways. In addition, given the available evidence 

for NO2 concentration gradients around roadways, she concluded that the new standard 

would maintain area-wide NO2 concentrations (away from major roads) well below those 

in locations where key U.S. epidemiological studies had reported associations with 

adverse respiratory effects (75 FR 6501). 

In the current review of the PM NAAQS the scientific evidence forming the basis for 

final decisions on the PM2.5 standards includes epidemiological studies reporting 

associations between area-wide PM2.5 concentrations and a number of adverse health 

outcomes (i.e., including mortality and a variety of cardiovascular and respiratory 

effects). While controlled human exposure studies of PM2.5 provide coherence and 

biological plausibility for the effects observed in epidemiological studies, because of the 

exposure concentrations and durations evaluated they do not provide an appropriate basis 

to inform decisions on the levels of the 24-hour or annual standards. In light of this 

fundamental difference in the bodies of evidence available for NO2 and PM2.5, the 

approach to considering NO2 roadway concentration gradients adopted in the most recent 

review of the primary NO2 NAAQS would not similarly inform the Administrator’s 

decisions in the current review of the PM NAAQS. 42 Therefore, the same approach 

would not be warranted in the two reviews. 

 

42 See also comments of UARG at 55 n. 73 drawing this same distinction (“The fact that the level of the PM2.5

NAAQS is derived solely from epidemiological studies distinguishes it from the NO2 NAAQS for which, as the 

EPA notes, 77 Fed. Reg. at 39010/2-3, it recently adopted near-road monitoring requirements. That standard was 

based, in significant part, on controlled human exposure studies in which actual NO2 exposures were measured that 
V-30 

The EPA’s discusses the specifics of siting within the near-road environment in section 

VIII.B.5.a of the preamble to the final rule. 

(36) Comment: One commenter stated that the EPA provides little if any technical support for 

this proposal. Two documents are mentioned in the preamble: the “Near-road Monitoring 

Pilot Studies Objectives and Approach” and the “Review of the Near-Road Document – 

Outline.” But these documents either do not specifically address near-road PM2.5

monitors or merely mention the issues involved with identifying monitor locations. 

Therefore, the EPA’s proposed monitoring plan is wholly unsupported in the preamble 

and the docket for this rulemaking. 

Response: The EPA believes that the documents cited in combination with the rationale 

in the preamble do support the decision to add PM2.5 near-roadway monitoring. While 

these documents were created prior to the proposal to add PM2.5 monitors to near-road 

environments, for reasons already explained above in this response to comment section, 

we believe there are a number of reasons that support siting PM2.5 and NO2 monitors at 

the same near-road monitoring station, related both to technical issues such as vehicle 

mix as well as support for monitoring objectives. 

(37) Comment: One commenter stated that compounding the issue of near road monitoring is 

EPA’s proposal to change the current regulatory presumption that micro- and middlescale monitors are not comparable to the annual PM2.5 NAAQS (unless specifically 

approved for such use by an EPA Regional Administrator) and to additionally strike other 

existing regulatory language that limits the use of such monitors. EPA should abandon 

these proposals. Instead, the EPA should consider removing the current role of the 

Regional Administrator in order to promote national consistency in NAAQS monitoring 

and to specifically disallow utilization of microscale monitors except for special purpose 

monitoring and for the purpose of conducting research. 

Under current regulations, micro scale monitors are defined as applying to 

“concentrations in air volumes associated with air dimensions ranging from several 

meters up to about 100 meters.” Thus, such monitors may comply with regulatory 

requirements yet be placed in varying locations, including at sites which are very close to 

emissions which could heavily influence monitoring results. The scale of “several 

meters” effectively provides no restriction at all on where monitors could be placed. 

When combined with EPA representation that “any potential location for a PM2.5

monitoring site . . . would be eligible for comparison to the annual NAAQS”, the result is 

that nonattainment areas could be considered to exist literally anywhere, including 

extremely small areas within a urban (or rural) area and/or where public access is 

prohibited. 

Contrary to the EPA’s assertions in the proposed rule, the proposed changes to allow 

micro- and middle-scale monitors to be compared to the NAAQS and the revoking of the 

 

could reasonably be compared to concentrations measured near roads. 75 Fed. Reg. at 6500/1-01/2.”). 
V-31 

“population-oriented” condition for monitoring locations (discussed below) do not 

promote consistency with the EPA’s existing regulatory definition for “ambient air.” As 

noted by the EPA, the regulatory definition of “ambient air” specifically references the 

portion of outside air to which the general public has access. In implementing this 

regulatory definition, the EPA has exempted areas where a source owns or controls the 

property involved and where public access has been precluded. The Agency has 

consistently relied on documents describing the definition of ambient air with regard to 

not including areas “to which public access is precluded by a fence or other physical 

barrier.” Thus, EPA has never interpreted ambient air to be “any potential location” 

outside of a building and proposing to allow “any” PM2.5 monitor to be compared to the 

NAAQS is clearly and directly inconsistent with this long-standing regulatory 

interpretation. It is also contrary to original distinctions Congress made between ambient 

air and other air quality issues. In the 1970 Clean Air Act, Congress distinguished 

between ambient air issues where emissions emanated from diverse stationary and 

moving sources, and other pollution agents that were “generally confined, at least for 

detection purposes, to the area of the emission source.” 

Finally, as noted above with reference to roadside monitoring, the EPA provides no 

documentation for this proposal in the preamble or, as of this date, the docket. Rather 

than promote consistency, the change would have the opposite effect given the expansive 

interpretation of “any” within the CAA. Therefore, the EPA should retain the current 

requirements restricting the use of micro- and middle-scale monitors and additionally 

consider revising the regulations to remove the ability of a Regional Administrator to 

determine monitor comparability. These changes would better promote the goal of 

national uniformity by making it clear that monitors would not be subject to highly 

localized conditions (perhaps measuring highly transient air quality in areas measuring no 

more than a few square meters) or subject to the individual (and perhaps inconsistent) 

preferences of different Regional Administrators. 

Response: The EPA utilizes the Regional Administrators in the approval of annual 

monitoring network plans and in many other areas applicable to network design and 

probe and siting criteria. We believe that the annual monitoring network plans, which are 

described in §58.10, provide an appropriate place for monitoring agencies to describe 

their networks, since the public has an opportunity to provide input on plans where there 

are changes. The EPA Regional Offices are the most familiar with their individual State 

networks and possible changes to them and there is routine coordination across the EPA 

Regional Offices on technical and policy issues. Therefore, we do not believe that 

removing the Regional Administrator from the process of approving micro- or middlescale sites from comparison to the annual NAAQS, will promote consistency. 

Regarding the comment, “Thus, EPA has never interpreted ambient air to be “any 

potential location” outside of a building and proposing to allow “any” PM2.5 monitor to 

be compared to the NAAQS is clearly and directly inconsistent with this long-standing 

regulatory interpretation”. The EPA disagrees that we are intending ambient air to be 

“any potential location outside of a building”. We will continue to use our long standing 

definition of “ambient air” which is specified in 40 CFR 50.1 – our definition is: – 
V-32 

“Ambient air means that portion of the atmosphere, external to buildings, to which the 

general public has access”. If a monitoring station does not meet this definition, 

monitoring results from the station could not be compared to the PM2.5 NAAQS. 

Consequently, the rule does not authorize comparison with the annual PM2.5 NAAQS 

with monitoring data from sites to which the public lacks access. Moreover, the final rule 

provides that to be compared to the annual PM2.5 NAAQS, measurement data must come 

from monitors that are representative of area-wide air quality. Section 58.1. Area-wide 

“means all monitors sited at neighborhood, urban, and regional scales, as well as those 

monitors sited at either micro- or middle-scale that are representative of many such 

locations in the same CBSA.” Id. So in addition to representing areas in which there is 

public exposure, sites must be representative of many similar locations in an area for 

comparison with the annual PM2.5 NAAQS. 

(38) Comment: One commenter stated that the proposed near-roadway monitoring to measure 

particulate matter from transportation sources is only warranted with a species-based 

standard. The commenters also states that many recognized medical experts have long 

believed that transportation related PM2.5 is a major contributor to human health impacts. 

So from that standpoint, the EPA’s proposal to add PM2.5 ambient air monitor to roadway 

locations might be a positive step , but only if the agency is proposing a speciated PM2.5

standard. 

Response: The EPA has addressed the issue of considering a species based standard in 

section 3E.1 of the preamble to the final rule. 

(39) Comment: One commenter provide a detailed follow-up comment on the EPA’s proposal 

to revise the form of the annual PM2.5 standard to base the standard on the highest 

community-oriented monitor in an area and to eliminate spatial averaging. The 

commenter stated that, according to the EPA, for an area with multiple monitors, the 

appropriate reporting monitor with the highest design value would determine the 

attainment status for that area. The commenter does not support this approach as it is not 

consistent with monitoring results from health study analyses. Furthermore, the 

commenter is very skeptical of this approach given the EPA’s intent to locate more 

monitors along roadways in major urban areas without the requisite knowledge of what 

the PM2.5 readings might be from these monitors. 

Response: The EPA has addressed the issue of eliminating spatial averaging in the 

preamble to the final rule. Regarding the commenter’s statement on having the requisite 

knowledge of what the PM2.5 readings might be from these monitors, EPA believes it has 

sufficient information to move forward with this requirement. In the preamble to the 

final rule we cite multiple studies (Ntziachristos et al., 2007; Ross et al., 2007; Yanosky 

et al., 2008; Zwack et al., 2011) that are relevant to informing what the PM2.5 readings 

may be. 

(40) Comment: One commenter stated that the EPA is proposing to remove existing 

requirements regarding PM2.5 NAAQS that require monitors to be “population-oriented” 

but provides exceedingly thin and conflicting rationale for the proposed change. On one 
V-33 

hand, the EPA proposes to eliminate this requirement since it claims it will have no 

impact. In the same breath, however, the EPA provides a justification for the proposal 

based on ambiguity in “applying modeling across an area.” The illogic of these two 

statements is apparent. If a provision has no impact, it can hardly create ambiguity. 

Outside of this observation, AFPM believes that population-oriented requirements fulfill 

an important purpose in the implementation of NAAQS. Indeed, such requirements are 

aligned with the focus of primary NAAQS as standards intended to protect public health. 

Maintaining this current regulatory requirement is also consistent with the 

epidemiological data upon which the 1997 PM2.5 NAAQS was established and on which 

this proposed rule still relies. Epidemiological studies, at their heart, are designed to 

probe relationships between human exposures and varying levels of an air pollutant. Such 

studies explicitly rely on existing air quality data in order to assess long-term and shortterm associations, and this relationship has been noted since the initial staff review of 

scientific information that was used to finalize a fine particulate standard. The EPA 

should recognize this association and abandon its proposal to revoke this long-standing – 

and logical – requirement. 

Response: In section VIII.B.2 of the preamble to the final rule and in this Response to 

Comments, the EPA explains that removing “population-oriented” does not have a 

practical impact on siting of monitors, but eliminates ambiguity and confusion that has 

arisen in other, related NAAQS-regulatory contexts, such as dispersion modeling for 

attainment planning and SIP development. 

The EPA believes that the location of any site meeting the definition of ambient air, 

which represents a location where the public is (or may be) exposed, will represent 

current or potential population exposure and is an acceptable location for comparison to 

PM2.5 NAAQS, as is the case with all other criteria pollutants. Additionally, for 

comparison to the annual PM2.5 NAAQS, monitoring sites are also to represent area-wide 

air quality; therefore, even if a monitor was located in a location at a small scale where no 

one was actually exposed on a given day, and this site was determined to be an area-wide 

site, there is still the potential for someone to be exposed there and that site is intended to 

represent many such other locations in the same area, where the public is (or may be) 

exposed. 

On the comment of maintaining this current regulatory requirement for consistency with 

the epidemiological data upon which the 1997 PM2.5 NAAQS was established and on 

which this proposed rule still relies, as explained in section II.E.c.i.1 of the preamble to 

the final rule, it is appropriate to compare the PM2.5 concentrations from a maximum 

area-wide monitor to the level of the annual PM2.5. Moreover, EPA anticipates that 

monitoring agencies will continue to site monitors that represent population exposure, 

particularly in light of the requirement to site monitors in ambient air, and the “areawide” requirement for comparability to the annual NAAQS. EPA also points out that it is 

maintaining the overwhelming majority of the network at existing locations and that this 

data will continue to be available to support epidemiological studies for comparison to 

the NAAQS and other objectives. The addition of near-road PM2.5 monitoring data will 
V-34 

add value to the ambient air network as it will provide for data in near-road environments 

where millions of people are exposed43 and for which we have very little data. 

(41) Comment: One commenter stated that they have no problem with monitoring anywhere 

in the near-road environment for research purposes, but they are concerned that any PM2.5

monitoring that is to be used to compare with the annual standard for attainment purposes 

must be population-oriented. 

Response: This comment is addressed in the preamble to the final rule. As discussed 

there and elsewhere in this Response to Comments, a significant fraction of the 

population lives in proximity to major roads, and these exposures occur in locations that 

represent ambient air. Monitoring in such areas does not make the standard more 

stringent than warranted, but rather affords the intended protection to the exposed 

populations, among them at-risk populations, exposed to fine particles in these areas. 

Thus, in cases where monitors in near roadway environments are deemed to be 

representative of area-wide air quality they would be compared to the annual standard. 

However, the EPA has limited the comparability of monitors that are not “area-wide” for 

purposes of comparison with the annual PM2.5 NAAQS. 

(42) Comment: One commenter stated several issues with the way the EPA proposes to 

implement the near-road requirement. The commenter is concerned that the elimination 

of spatial averaging and the definition of population-oriented when combined with the 

requirement to co-locate PM2.5 monitors with near-road NO2 and CO monitors will result 

in collection of data in locations that are representative of no-one’s annual average or 24-

hour average PM2.5 exposure. This could result in a major tightening of the standard, with 

significant unintended consequences for industry and economic development. Entire 

metropolitan areas could be placed in non-attainment based on measurements made 

where no-one is actually exposed. 

The commenter is concerned that the decision to co-locate with NO2 monitors was based 

on convenience and the intent of the NO2 near-road monitoring is to find the highest 

micro-scale concentrations within a few meters of the most heavily travelled segments of 

the most heavily travelled expressways, a unique situation. 

The proposed rule defends the decision to piggy-back the PM monitoring with the 

planned NO2 monitoring because considerable thought and review has gone into that 

network design. However, the final guidelines for monitor placement do not require 

population exposure at the monitoring site. The final Technical Assistance Document 

notes “It is important to recall that the objective is to monitor in locations that are as near 

as practicable to roads where peak, ground-level NO2 concentrations are expected to 

occur.” Once candidate sites are identified based on traffic counts and other factors, the 

potential for population exposure can be considered as noted in the TAD. However, the 

 

43 One study identified that 45 million Americans live within 300 feet of a major roadway or other source of mobile 

emissions. The commenters’ information is based on the American Housing Survey, which is available on the web 

at: http://www.census.gov/housing/ahs/data/ahs2009.html. The survey provides an estimate of the county’s housing 

units in the U.S. that are located with 300 feet of a highway with four or more lanes, or a railroad, or an airport. 
V-35 

discussion of population exposure suggests that it is near-by population rather than actual 

population exposure at the monitoring site that is the relevant consideration. Once a site 

has been selected and approved, the TAD indicates that the information for the site in the 

EPA’s Air Quality System identify the site as “source-oriented” and include the 

horizontal distance from the probe to the nearest edge of the target road. The TAD also 

discusses the fact that the probe may be located in the right-of-way (ROW) of a limited 

access expressway. Thus, the location of NO2 and any co-located PM2.5 monitors will be 

source-oriented and not population-oriented. This would be a major change from prior 

practice and is not justified. Near-road monitor results should not be used to compare to 

the annual or 24-hour PM2.5 standard unless it can be shown that it is from a populationoriented site consistent with the definition in 40 CFR 58.1. Although the EPA proposes to 

allow the Regional Administrator to give a waiver for “unique” micro-scale sites, the 

Agency should not allow consideration of source-oriented sites in the first place. 

Response: The commenter raises several points to address, a number of which are 

discussed in the preamble to the final rule in section III.E.3.a on the form of the annual 

PM2.5 NAAQS or in section VIII.B.3.b.i on the addition of a near-road component to the 

PM2.5 monitoring network. For example, section III.E.c.i.1 of the preamble to the final 

rule explains why it is appropriate to compare the PM2.5 concentrations from a maximum 

area-wide monitor to the level of the annual PM2.5. 

The comment suggests that the decision to co-locate with NO2 monitors was based on 

convenience. The EPA does believe that there are some benefits to local monitoring 

agencies in reduced resource needs from siting the PM2.5 monitors in the near-road 

environment with other measurements; however, the most important reason we are 

requiring these monitors be located at multi-pollutant near-road station is to support 

multiple monitoring objectives. As stated in section VIII.B.3.b.i of the preamble: “a 

number of key monitoring objectives will be supported, including collection of NAAQS 

comparable data in the near-road environment, support for long-term health studies 

investigating adverse effects on people, providing a better understanding of pollutant 

gradients impacting neighborhoods that parallel major roads, availability of data to 

validate performance of models simulating near-road dispersion, characterization of areas 

with potentially elevated concentrations and/or poor air quality, implementation of a 

multi-pollutant paradigm as stated in the NO2 NAAQS proposed rule (74 FR 34442, July 

15, 2009), and monitoring goals consistent with existing objectives noted in the specific 

design criteria for PM2.5 described in appendix D, 4.7.1(b) to 40 CFR part 58”. 

The comment further suggests that the intent of the NO2 near-road monitoring is to find 

the highest micro-scale concentrations within a few meters of the most heavily travelled 

segments of the most heavily travelled expressways, a unique situation, and that the 

monitors “will be source-oriented and not population-oriented. This would be a major 

change from prior practice and is not justified.” The EPA notes that the substantive 

criteria for which monitors are eligible to be compared to the PM2.5 NAAQS monitors are 

not changing-- near road monitors have always been eligible for comparison to the 24 

hour standard, and will continue to be eligible for comparison to the annual standard only 

if they are found to be “area-wide” (i.e., to represent many such locations in the area). 
V-36 

The EPA disagrees that siting monitors in the area of expected maximum concentration is 

a unique situation. Such cases of seeking the highest concentrations of a pollutant have 

been a long-standing goal in the network design of every criteria pollutant as described in 

appendix D to Part 58 in order to provide the greatest degree of protection for public 

health and welfare without requiring an overly burdensome monitoring network. The 

EPA maintains that the near-road environments are locations where there is a significant 

potential for population exposure to PM2.5 and it is important to locate monitors to 

measure that exposure. To the extent these sites are “unique” they would not be 

comparable to the annual PM2.5 NAAQS. 

Regarding the comment that the near-road monitor results should not be used to compare 

to the annual or 24-hour PM2.5 standard unless it can be shown that it is from a 

population-oriented site consistent with the definition in 40 CFR 58.1. For the reasons 

explained in section VIII.B.2.a of the preamble to the final rule, the EPA will no longer 

be using “population-oriented” as a condition for comparability to the PM2.5 NAAQS. 

The EPA disagrees that we should not allow consideration of source-oriented sites in the 

first place. There is no exemption from the NAAQS for violations caused by sources. 

Indeed, for some NAAQS, such as Pb, most of the monitoring network may be sourceoriented but that does not mean that the data is not comparable to the NAAQS. Moreover, 

source oriented and population-oriented are not mutually exclusive. So there is no basis, 

even if we were keeping a requirement for population oriented (which we are not), to 

exclude source oriented sites. However, the EPA is requiring that all monitors must be at 

least “area-wide” to be compared to the annual NAAQS. 

(43) Comment: One commenter is also concerned that EPA is overestimating the gradients in 

PM2.5 near the road. The four references provided in the proposed rule do not make a 

sufficient case to add near-road PM2.5 monitoring. The Zwack et al. (2011) study involves 

the impact in street canyons in mid-town Manhattan and concludes that PM2.5 is elevated 

by from 5 to 8 % over background. Although the Zwack et al. study is useful, it does not 

apply to the multi-lane expressway case that is at issue in the proposed rule. The Ross et 

al. (2007) and Yanosky et al. (2008) references are to studies that used land-use 

regression to estimate PM2.5 exposures and do not include any data on actual roadway 

impacts. The Ntziachristos et al. (2007) study evaluated the composition near the road 

with a site 1 mile downwind and did not evaluate the gradient near the roadway. In 

contrast to these studies, Karner et al. (2010) synthesized the results of 41 studies 

evaluating the shape and rate of decay curves of pollutants near roadways. The review 

included 16 studies with PM2.5 measured at various distances from the roadway. Karner 

et al. report, in contrast with other pollutants, PM2.5 shows little or no gradient with 

distance from the road. Since the Karner et al. review analyzed real-world data from a 

variety of roadway situations, the commenter urges the Agency to re-visit its concern 

over PM2.5 gradients near roadways and the need for near-road monitoring. Karner et al. 

show that near-road exposures to PM2.5 are not substantially elevated compared to 

community-wide exposures. 

Response: The EPA has reviewed the Karner paper and believes that the results presented 

are consistent with the results from Zwack, which support our position that there are 
V-37 

gradients in near-road environments. The EPA also believes the other papers cited in the 

preamble (Ross, Yanosky, and Ntziachristos) are useful to support its position that there 

are elevated levels of PM2.5 in near-road environments. The information presented in 

Karner states that PM2.5 concentration levels in near-road environments have a 22% 

decrease between the edge-of-road concentration and the farthest downwind measured 

value, which was identified at a distance of 986 meters. Therefore, the EPA disagrees 

with the commenters point that current information establishes there are little or no 

gradients with distance from road. The EPA maintains its position that these gradients 

exist and there is a need for near-road monitoring for the reasons explained in the section 

VIII.B.3.b.i of the preamble to the final rule. However, the EPA agrees that there are 

uncertainties over the extent of the gradient and it may be modest. To the extent there is 

a smaller than expected gradient, the information will still be useful to support 

monitoring objectives, and the fears of several commenters that near road monitoring is 

unrepresentative of wider air quality will be dispelled. 

(44) Comment: One commenter stated that along with the small gradient near roadways, there 

is also evidence that drivers and passengers in vehicles experience lower PM2.5 exposures 

due to deposition losses in the vehicle air handling system. For example, Riedeker et al., 

200359 report in-vehicle PM2.5 was 24% lower than ambient and roadside levels, in a 

study of the occupational exposure of North Carolina State troopers during their normal 

work shifts, probably due to deposition associated with the recirculating air. Similarly, 

Rodes et al., 199860 in a study of thirty-two, 2-hour commuting trips in Los Angeles and 

Sacramento, CA in the fall of 1997 reported that particle concentrations were 

significantly higher outside the vehicles than inside, with inside levels often less than 

roadside levels, presumably due to losses in the vehicles ventilation system. Thus, there is 

also evidence that in-vehicle exposures to PM2.5 are not elevated compared to 

community-wide exposures. 

Response: As stated in the section VIII.B.3.1 of the preamble to the final rule, we are 

requiring PM2.5 monitors in the near-road environment to support a number of objectives. 

However, we did not state that we are attempting to characterize the actual on-road 

concentrations; rather, we are attempting to understand, among other objectives, the 

health impacts of near-road PM2.5 exposures. Therefore, while the on-road exposure is 

still a relevant consideration, since these are locations where the public is exposed, it was 

not the sole basis for the proposed network design requirements for PM2.5 monitors in 

near-road environments, and the possibility that there is a gradient of exposure for people 

inside moving cars as compared to outside, while useful to understand, is not a reason to 

forego near road monitoring. Therefore, we maintain our position that there are gradients 

in the near-road environment and that we have a responsibility to monitor the exposure of 

the public in these areas. 

(45) Comment: One commenter stated that basing attainment designations on each area's 

single worst-case monitor, instead of using the current practice of area-wide averaging 

produces non-representative sampling results. Compounding this proposed approach is 

EPA's intent to require placement of monitors near heavily traveled roadways. These two 
V-38 

elements of the proposed monitoring scheme will significantly and improperly skew 

results in many areas.

Response: The first part of this comment has to do with EPA’s decision to revoke spatial 

averaging and use the highest-reading area-wide monitor in each area for purposes of 

comparing to the annual NAAQS. This comment is addressed in the section III.E.3.a of 

the preamble to final rule, but EPA notes briefly that no area is currently using spatial 

averaging. The second part of the comment connects the requirement to place monitors 

near-heavily travelled roads with the commenters point on producing non-representative 

sampling results. The EPA disagrees with the commenters point on producing nonrepresentative sampling results. The EPA’s network design requirements for PM2.5 

include a provision to locate sites at area-wide locations, thus these locations are in fact 

representative of many such locations throughout the same area. In addition, as discussed 

elsewhere, EPA believe that monitors should generally be located in areas of expected 

maximum concentration so that the NAAQS can be attained and provide requisite 

protection throughout the country. 

(46) Comment: Several commenters stated that EPA had not demonstrated the need to add a 

requirement for near-road monitoring of PM2.5. The primary purpose of these monitor 

appears to be research. 

Response: The EPA addressed the objectives of the near-road PM2.5 monitors in section 

VIII of the preamble to the final rule. The EPA believes these objectives provide 

sufficient rationale to add the requirement for the near-road PM2.5 monitors. The EPA 

agrees that one of the purposes for these monitors is research; however, the EPA 

disagrees that this is the primary purpose. 

(47) Comment: One commenter (for API) stated that placing PM2.5 monitors near roadways 

rather than at population-oriented locations will likely measure locally unique 

concentrations of primary particulate associated directly with diesel exhaust, tire and 

brake wear and roadway dust. These observations will likely have limited geographical 

representativeness, and should be interpreted with caution. Monitors should not be moved 

near roadways if these measurements do not represent the broader area. 

Response: The EPA notes that near road monitors will be characterized by monitoring 

agencies, subject to Regional Administrator approval, as to whether they are “area-wide” 

(i.e., whether they represent many such locations within an area). To the extent that 

concentrations of primary particulate are captured during the monitoring of PM2.5 in any 

near-road environment that is determined to be an area-wide location, such monitoring is 

representative of many locations throughout the area and therefore is not unique. 

(48) Comment: One commenter stated that they view near-road or source-oriented monitoring 

as failing to represent population exposures (unless people are sitting in lawn chairs by 

roads for extended periods of time) or visibility concerns under the proposed primary and 

secondary PM2.5 NAAQS. The newly installed NO2 monitoring network is devised to 

address NO2 emission from mobile sources and address curbside health concerns since 
V-39 

NO2 is radicalized quickly in the atmosphere. The height and distance of such stations 

from roads, seems particularly unsuited for PM2.5 formation in urban areas, although we 

fully appreciate why the EPA would like to take advantage of these stations because of 

the cost of a new monitoring network. We think the EPA should re-examine these plans. 

Instead, the EPA should utilize existing monitors for these purposes, and importantly, 

that will require much more extensive changes to Part 58 regulations that exceed the 

proposed changes in this rulemaking. Among these are changes that allow for existing 

monitors to be relocated. 

Response: Regarding the comment that views near-road or source-oriented monitoring as 

failing to represent population exposures, the EPA disagrees. As explained in section 

VIII.B.3.b.i of the preamble to the final rule and this response to comments, there are 

large numbers of people (in the tens of millions) that live, work, play, and go to school in 

close in proximity to major roadways. These exposures occur in locations that represent 

ambient air for which the agency has a responsibility to ensure the public is protected 

with an adequate margin of safety. Comparison of monitoring results from such areas to 

the NAAQS is therefore appropriate. 

The height and distance of the PM2.5 monitors is addressed in section VIII.B.5.a, while 

the rationale of why PM2.5 is collocated with NO2 at near-roadway station is addressed in 

VIII.B.3.b.i. As we explain in the preamble, we believe that the characterization of 

representative maximum PM2.5 concentrations due to on-road mobile sources with PM2.5

monitors will be at the same approximate locations that are the focus of the near-road 

NO2 network. This is due to the fact that PM2.5, like NOX, is disproportionately 

influenced by heavy duty (HD) vehicles which are predominantly diesel fueled, when 

compared to light duty (LD) vehicles which are primarily gasoline fueled. Specifically, 

for both PM2.5 and NOx, HD vehicles emit more of these two pollutants and their 

precursors on a per vehicle basis than LD vehicles. The EPA recognized this fact in the 

near-road NO2 network by requiring states to consider the fleet mix of candidate road 

segments where near-road monitoring might occur. In the design of the NO2 near-road 

network where the PM2.5 monitors will be installed, states were instructed to place a 

higher priority on those highly trafficked roads which have more diesel fueled vehicles 

using a metric called the fleet equivalent average annual daily traffic. As such, the 

Agency believes it is appropriate that required near-road PM2.5 monitors would be located 

with near-road NO2 monitors as they are similarly influenced not only by fleet mix but 

also by total traffic count, congestion patterns, roadway design, terrain, and meteorology. 

As discussed in section VIII of the preamble, if States can demonstrate that a different 

monitor location is more appropriate, e.g., through a quantitative demonstration that peak 

ambient PM2.5 concentrations would occur in a near-road location which meets siting 

criteria but is not a near-road NO2 monitoring site, then the EPA Regional Administrator 

may use its existing discretion to approve a deviation from the PM2.5 monitoring 

requirements. 

(49) Comment: One commenter (H&W) stated they believe an emphasis on near-road 

monitors could skew monitored PM2.5 emissions results away from a representative 

dataset compatible with measuring NAAQS attainment. NAAQS have traditionally 
V-40 

assessed air quality health impacts across general areas. The EPA admits near-road 

monitors will result in an undefined "bump" in monitored PM2.5. See 77 Fed Reg. at 

39007. In this way, requiring near-road monitors may morph what are now area-wide air 

quality assessments into a hot-spot analysis predicated solely on, in EPA's terminology, 

"bump" PM2.5 levels. The proposed PM Rule's near-road monitor requirements should not 

have the normative effect of forcing vast geographic swaths to lower emissions simply 

because of limited non-representative monitoring data. Instead, EPA should eschew plans 

that will undermine the representative quality of air quality monitoring data and require 

broad PM2.5 emissions reductions in order to achieve attainment at discrete locations 

where no population is likely to be exposed for the averaging periods (24-hour and 

annual) of the NAAQS. For this reason, the commenter urges the EPA to reexamine the 

proposed PM Rule's near-road monitoring requirements. 

Response: As discussed elsewhere, the EPA generally tries to place NAAQS monitors in 

areas of expected maximum concentration, in order to make the most efficient use of 

limited monitoring resources while protecting public health and welfare. As explained in, 

section VIII.B.3.b.i of the preamble to the final rule and this response to comments, there 

are large numbers of people (in the tens of millions) that live, work, play, and go to 

school in close in proximity to major roadways and the EPA believes it is important to 

monitor their exposure to PM2.5 in the near-road environment. EPA notes that the criteria 

for which monitors are comparable to the NAAQS are not substantively changing, as 

monitors will still be required to be “area-wide” to be comparable to the NAAQS and 

EPA does not believe that removal of the “population oriented” requirement will 

substantively affect which monitors are comparable (particularly in light of the area-wide 

requirement). 

To the extent the commenter is concerned about the “effect of forcing vast geographic 

swaths to lower emissions simply because of limited non-representative monitoring 

data,” the EPA notes that issues as to the proper extent of the nonattainment area or 

control strategy may be considered as those issues arise, but the agency does not agree 

that avoiding a determination of nonattainment is a reason to change the monitoring 

network design requirements. 

(50) Comment: One commenter stated that the EPA proposes to determine compliance with 

the proposed PM2.5 standard based solely on measurements acquired from PM2.5 monitors 

that are placed in close proximity to major roads in each air quality area. Importantly, 

data from other existing PM2.5 monitors will not be used to calculate the spatial average 

for the air quality area. This method of compliance demonstration will bias the results 

toward non-attainment since "near road" monitors will likely record higher PM2.5

readings than other monitors. For example, assume that the EPA revises the PM2.5

standard from 15 μg/m3 to 12.8 μg/m3 and that the concentration of PM2.5 based on the 

average of existing community monitors for the air quality area is 12.5 μg/m3

. It would 

appear that the area is in attainment. However, if the averaged data from the existing 

network of community-based monitors is ignored and, instead, a single "near road" 

monitor - due to its location - records PM2.5 at a level that is as little as 5 percent higher 

than the network monitors' spatial average, the air quality area is classified as non-
V-41 

attainment with the revised (hypothetical) standard of 12.8 μg/m3 (i.e., 12.5 μg/m3x 

105% = 13.1 μg/m3

). The Clean Air Act requires that PM2.5 sources within nonattainment areas either install additional control technologies or restrict growth in order to 

remedy the non-attainment condition. Non-attainment designation will have a direct 

economic impact on the vitality if not the viability of business located in or around the 

non-attainment area. By instituting a technically flawed policy of using only near-road 

monitors to determine attainment status for an air region, the EPA is unnecessarily 

increasing the cost of doing business by creating an artificial air quality concern.

Response: The EPA disagrees that it will solely use near-road monitors to determine the 

attainment status for an area. The EPA’s network design criteria include multiple 

requirements for PM2.5 monitors, including a requirement to monitor in an area-wide 

location of expected maximum concentration. All eligible monitors in accordance with 

Appendix N to Part 50 and Part 58 will be used in comparison to the NAAQS. The EPA 

disagrees that the addition of PM2.5 monitors will bias the results toward non-attainment 

since "near road" monitors will likely record higher PM2.5 readings than other monitors. 

The addition of the near-road monitors will lead to an appropriate level of protection, 

with an adequate margin of safety, for those populations that live, work, play, and go to 

school near major roadways. The rationale for the appropriate level and form of the 

PM2.5 NAAQS, including a discussion on eliminating spatial averaging is described in 

section III.E.3 and section III.E.4 of the preamble to the final rule. While the EPA does 

not dispute the calculations provided in the example of the comment, the EPA points out 

that this example fails to recognize constraints on the use of spatial averaging from the 

2006 NAAQS that are intended to ensure that spatial averaging does not adversely affect 

disadvantaged populations. In the 2006 PM NAAQS final rule, the EPA tightened the 

criteria for use of spatial averaging to provide increased protection for vulnerable 

populations exposed to PM2.5. This change was based in part on an analysis of the 

potential for disproportionate impacts on potentially at-risk populations, which found that 

the highest concentrations in an area tend to be measured at monitors located in areas 

where the surrounding population is more likely to have lower education and income 

levels and higher percentages of minority populations (71 FR 61166/2, October 17, 2006; 

U.S. EPA, 2005, section 5.3.6.1). Since those changes, no area has used spatial 

averaging, and no other NAAQS uses spatial averaging. 

(51) Comment: One commenter stated that EPA should not finalize the proposed changes to 

PM2.5 monitoring, which would substantially increase the stringency of the PM2.5 Primary 

NAAQS, even absent the proposed tightening of the level of the annual standard. 

Response: As described in section III.E.3.a of the preamble to the final rule, EPA took 

the addition of near-road monitoring into consideration in setting the form of the 

NAAQS. The EPA disagrees that the proposed changes to PM2.5 monitoring would 

substantially increase the stringency of the PM2.5 Primary NAAQS. A significant fraction 

of the population lives in proximity to major roads. These exposures occur in locations 

that represent ambient air for which the agency has a responsibility to ensure the public is 

protected with an adequate margin of safety. Ignoring monitoring results from such areas 

(or not monitoring at all) would abdicate this responsibility. Put another way, monitoring 
V-42 

in such areas does not make the standard stricter, but rather affords requisite protection to 

the populations, among them at-risk populations, exposed to fine particulate in these 

areas. Thus, the EPA has made a determination to protect all area-wide locations, 

including those locations with populations living near major roads that are representative 

of many such locations throughout an area. As discussed above, the EPA concludes that 

the requirement to locate monitors to represent ambient air, along with other siting 

requirements, will ensure that monitors represent PM2.5 concentrations in areas of 

potential public exposure. 

(52) Comment: One commenter stated that the EPA is proposing to require that 52 near-road 

PM2.5 monitors be placed in locations around the country, collocated with NO2 monitors. 

The EPA states that placing PM2.5 monitors in such locations will be the “most efficient 

and beneficial approach” to deploying this network. Given that the EPA performed no 

analysis of the differences between near-road monitoring for NO2 and PM2.5, this 

requirement is arbitrary and capricious to the extent that it would form the basis for any 

designation of PM2.5 nonattainment areas. While there may indeed be economies in 

placing such monitors at existing sites, any monitor so co-located is not rationally related 

to or comparable to the NAAQS. Further, as discussed later, it appears that the proposed 

roadside monitors would increase the stringency of the standard and lead to designation 

of additional nonattainment areas. 

Response: The EPA disagrees that the requirement to establish and use data from PM2.5

monitors in near-road environments for the NAAQS is arbitrary and capricious. As 

explained in the section VIII.B.3.b.i of the preamble to the final rule, there are gradients 

in near-roadway PM2.5 that are most likely to be associated with heavily travelled roads 

(particularly those with significant heavy-duty diesel activity, which is also associated 

with increased NO2 concentrations), and that the largest numbers of impacted populations 

are located in the largest CBSAs in the country (Ntziachristos et al., 2007; Ross et al., 

2007; Yanosky et al., 2008; Zwack et al., 2011). There are a number of reasons 

identified in the preamble and this Response to Comments that support siting PM2.5 and 

NO2 monitors at the same near-road monitoring station, related both to technical issues 

such as vehicle mix as well as support for monitoring objectives. Further, a significant 

fraction of the population lives in proximity to major roads44. These exposures occur in 

locations that represent ambient air for which the agency has determined is important to 

monitor to protect public health and welfare. As discussed elsewhere, the EPA disagrees 

that monitoring in these areas increases the stringency of the standard, or that the 

possibility of additional nonattainment areas is a reason not to monitor in these areas. 

(53) Comment: One commenter provided comments on the EPA’s use of two documents as 

supportive of the new near-road monitoring requirement, i.e., the “Near-road Monitoring 

Pilot Studies Objectives and Approach” and the “Review of the Near-Road Document – 

Outline.” These documents are wholly inadequate to support the proposed monitoring 

 

44 One study identified that 45 million Americans live within 300 feet of a major roadway or other source of mobile 

emissions. The commenters information is based on the American Housing Survey, which is available on the web at: 

http://www.census.gov/housing/ahs/data/ahs2009.html. The survey provides an estimate of the county’s housing 

units in the U.S. that are located with 300 feet of a highway with four or more lanes, or a railroad, or an airport. 
V-43 

requirements. The first document does not specifically address near-road PM2.5 monitors, 

but is centered on newly promulgated NO2 NAAQS; the second document is a 1-page 

outline which addresses the identification of locations and parameters for maximum 

concentrations of several pollutants, not the establishment of monitoring requirements 

themselves. Instead, the entire basis of the EPA’s proposed near-road PM2.5 monitoring 

network appears to be a suggestion by CASAC that such measurements might be useful. 

This is an insufficient informational basis and justification for rulemaking. 

Response: With regard to the documents cited and their applicability to support the nearroad requirement, the EPA is not exclusively relying on these documents to support its 

position to add PM2.5 monitors to the near road environment, rather these documents 

provide useful technical information that can be gleaned as monitoring agencies consider 

the addition of PM2.5 to the near-road stations. We also explain in preamble section 

VIII.B.3.b.i of the final rule that the characterization of representative maximum PM2.5

concentrations due to on-road mobile sources and the appropriate location of such PM2.5

monitors will be the same approximate locations that are the focus of the near-road NO2

network. This is due to the fact that PM2.5, like NOX, is disproportionately influenced by 

heavy duty (HD) vehicles which are predominantly diesel fueled, when compared to light 

duty (LD) vehicles which are primarily gasoline fueled. Specifically, for both PM2.5 and 

NOx, HD vehicles emit more of these two pollutants and their precursors on a per vehicle 

basis than LD vehicles. The EPA recognized this fact in the near-road NO2 network by 

requiring states to consider the fleet mix of candidate road segments where near-road 

monitoring might occur. In the design of the NO2 near-road network where the PM2.5

monitors will be installed, states were instructed to place a higher priority on those highly 

trafficked roads which have more diesel fueled vehicles using a metric called the fleet 

equivalent average annual daily traffic. 45 As such, the Agency believes it is appropriate 

that required near-road PM2.5 monitors would be located with near-road NO2 monitors as 

they are similarly influenced not only by fleet mix but also by total traffic count, 

congestion patterns, roadway design, terrain, and meteorology. 

The EPA disagrees with the statement that the entire basis of the EPA’s proposed nearroad PM2.5 monitoring network appears to be a suggestion by CASAC that such 

measurements might be useful and that this is an insufficient informational basis and 

justification for rulemaking. While the EPA did consider CASAC’s advice, it also 

considered a number of other factors such as explained in section VIII.B.3.b.i of the 

preamble to the final rule. For example, the EPA also considered the significant fraction 

of the population that lives in proximity to major roads. These exposures occur in 

locations that represent ambient air for which the agency has a responsibility to ensure 

the public is protected with an adequate margin of safety. 

(54) Comment: Several commenters (AEP) stated that EPA has not demonstrated the need to 

add a requirement for near-road monitoring of PM2.5. 

 

45 See the Near-road NO2 Monitoring Technical Assistance Document at: 

http://www.epa.gov/ttn/amtic/files/nearroad/NearRoadTAD.pdf
V-44 

Response: The EPA believes that for the reasons stated in section VIII of the preamble to 

the final rule, there are sufficient reasons to add a requirement for near-road monitoring 

of PM2.5. 

(55) Comment: One commenter (AGC) stated that they oppose EPA’s addition of near-road 

monitoring as it would measure mobile-source emissions instead of ambient air quality. 

Response: Any monitoring station sited in an area representing ambient air is by 

definition measuring ambient air. Since PM2.5 monitors are to be sited at near-road 

monitoring stations that are in the ambient air, they are measuring ambient air quality. 

(56) Comment: One commenter (AGC) stated monitoring sites should reflect ambient air 

conditions to which a significant portion of the public is exposed – not conditions specific 

to one location. Emissions are naturally going to be higher in some area of a county and 

lower in others. 

Response: As explained in section VIII.B.3.b.i, a significant fraction of the population 

lives in proximity to major roads. These exposures occur in locations that represent 

ambient air which the agency has determined is important to monitor because of the 

potential for population exposure to pollutants at levels exceeding the NAAQS. 

Although it may be true that emissions will often be higher in one area than another, the 

EPA generally sites monitors in areas of expected maximum concentrations to protect 

public health and welfare. The EPA notes, however that for the reasons explained in the 

preamble, monitors must be at least “area-wide” to be comparable to the annual PM2.5

NAAQS. 

(57) Comment: One comment letter representing 48 organizations provided strong support for 

the addition of the near road monitors. The comment letter stated that monitors with the 

highest measured concentrations of fine particulate matter tend to be located in areas 

where the population is more likely to be lower-income, have lower education levels, and 

minority. Furthermore, lower socioeconomic populations may be more vulnerable to fine 

particulate matter because of proximity to roadways and industry, higher rates of preexisting diseases, less access to health care, and nutritional deficiencies. At the same 

time, rural areas are at high risk because of significant gaps in air monitoring. Further, 

numerous scientific studies have now identified increased health risks in association with 

traffic-generated air pollution, including fine particulate matter. With more than 45 

million Americans living less than 300 feet from a highway, there is growing concern 

about the health impacts of living near heavily traveled roads. One of the most significant 

aspects of the EPA proposal relates to the proposed extension of the fine particle 

monitoring network to the near road environment. Motor vehicle traffic is a major and 

undisputed source of emissions of ultrafine, fine and coarse particles. In order to protect 

all citizens’ right to a safe and healthy air supply, as mandated by the Clean Air Act, it is 

imperative that our nation’s air pollution air quality monitoring network require 

measurement of particulate concentrations near highways and other significant sources of 

particulate pollution. This protection is long overdue and it is critical that that these 
V-45 

monitored concentrations, or the modeled equivalent, be considered in the designation of 

nonattainment areas and the development of associated air pollution control programs. 

Response: The comment in support of requiring the addition of PM2.5 monitors to the 

near-road environment is acknowledged. 

(58) Comment: One comment letter representing five organizations stated that they welcome 

and support EPA’s proposal to monitor the concentrations of PM2.5 that occur in near-road 

communities where millions of Americans are exposed to emissions from major highways, 

truck terminals and facilities that attract concentrations of motor vehicles. This NAAQS 

proposal seeks to begin for the first time the implementation of the PM2.5 NAAQS within the 

zone where emissions of fine particles from existing transportation facilities that attract large 

concentrations of mobile sources adversely affect concentrations of PM2.5.

Response: The comment in support of requiring the addition of PM2.5 monitors to the 

near-road environment is acknowledged. 

(59) Comment: One commenter stated they were pleased to see that the Agency plans to 

increase near-roadway monitoring to provide new information on population exposures to 

mobile sources of PM.

Response: The comment in support of requiring the addition of PM2.5 monitors to the 

near-road environment is acknowledged. 

(60) Comment: One comment letter representing 48 organizations (different than the 

commenters cited above) stated that they support the addition of PM2.5 roadway monitors, 

(as) an efficient implementation process specifically for communities that are already in 

non-attainment and significant environmental justice considerations, as well as consider 

in this and future assessments the research studies that describe the disproportionate 

health impacts on low income, communities of color. 

The letter also stated that they applaud the EPA for realizing the importance monitoring 

for co-pollutants, as well proposing additional PM2.5 monitors near highways, traffic 

corridors, especially near residential areas. Additional monitoring will provide a better 

opportunity for us to understand the health impacts of exposures, especially in core based 

statistical areas with one million persons or greater. With approximately 45% of the 

urban population living near major roads, and ethnic minorities and lower-income 

populations being more likely to live near sources of PM2.5, adding to the current national 

monitoring network will help researchers to better understand the exposure variation near 

roadways and other hotspots where exposure disparities exist. 

The comment letter also recommends that if at all possible, adding PM10-2.5 monitors to 

this network would be extremely helpful, since there are limited PM10 data in the near 

road environment. As noted by the CASAC and others, there is an obvious data gap to 

support future regulatory reviews and better understand how PM10 emissions are 

contributing to the existing public health burden. The comment letter states that they 
V-46 

support the addition of PM2.5 near-road monitors to the existing network, and, where 

possible, adding in PM10-2.5 monitors. 

Response: The comment in support of requiring the siting of PM2.5 monitors in the nearroad environment is acknowledged. 

With regard to the recommendation to add PM10-2.5 measurements to the roadway 

environment, where possible, as explained in section VIII.B.3.b.i of the preamble to the 

proposal, the EPA supports the measurement of other pollutants in the near-road 

environment. Such additional measurement are not required, but encouraged to support 

enhancing knowledge of exposures in the near-road environment. 

(61) Comment: One commenter offered some support for the addition of PM2.5 monitors to 

the near-road environments stating that they agree with the EPA that “...such near-road 

sites could provide valuable understanding of emissions “such as BC, ultrafine particles, 

and particle size distribution.”” However, the commenter also expressed concern as they 

state that “Once again, the EPA unfortunately displays its misguided bias prioritizing 

diesel over gasoline emissions. “The EPA believes that there are gradients in nearroadway PM2.5 that are most likely to be associated with heavily travelled roads, 

particularly those with significant heavy duty diesel activity.” The commenter later goes 

on to state that they are “...confident that these monitors will provide further 

reinforcement for what is already known about particle-borne toxics in our largest cities.” 

Response: The commenter appears to be generally supportive of pursuing 

characterization of the near-road environment; however, they have a specific concern 

regarding our placement of monitors in that we incorporate diesel as a factor in the 

identification of the road segment to use, which is tied siting of NO2 monitors. 

We do believe that the characterization of representative maximum PM2.5 concentrations 

due to on-road mobile sources and the appropriate location of such PM2.5 monitors will 

be the same approximate locations that are the focus of the near-road NO2 network. This 

is due to the fact that PM2.5, like NOX, is disproportionately influenced by heavy duty 

(HD) vehicles which are predominantly diesel fueled, when compared to light duty (LD) 

vehicles which are primarily gasoline fueled. Specifically, for both PM2.5 and NOx, HD 

vehicles emit more of these two pollutants and their precursors on a per vehicle basis than 

LD vehicles. The EPA recognized this fact in the near-road NO2 network by requiring 

states to consider the fleet mix of candidate road segments where near-road monitoring 

might occur. In the design of the NO2 near-road network where the PM2.5 monitors will 

be installed, states were instructed to place a higher priority on those highly trafficked 

roads which have more diesel fueled vehicles using a metric called the fleet equivalent 

average annual daily traffic. As such, the Agency believes it is appropriate that required 

near-road PM2.5 monitors would be located with near-road NO2 monitors as they are 

similarly influenced not only by fleet mix but also by total traffic count, congestion 

patterns, roadway design, terrain, and meteorology. 
V-47 

G. Comments on Revoking PM10-2.5 Speciation Requirements at NCore Sites 

(1) Comment: Several commenters support revoking the requirements for PM10-2.5 speciation 

at NCore stations. 

Response: The comment in support of the proposal is acknowledged and EPA is adopting 

the proposed approached in the final rule. 

(2) Comment: One commenter stated that with regard to the EPA’s proposal to revoke the 

requirement for PM10-2.5 speciation monitoring as part of the current suite of NCore 

monitoring requirements, that dropping this requirement may seem reasonable from a 

compliance perspective, it is problematic from the research perspective and needlessly 

delays improved understanding gained from the speciated data collected. 

Response: This comment is addressed in section VIII.B.3.c of the preamble to the final 

rule. 

(3) Comment: One comment letter representing five organizations stated that they strongly 

oppose EPA’s proposal to rescind the speciation requirements for PM10 monitoring. They 

find no legal, practical, or scientific justification for eliminating requirements for better 

characterization of coarse particle concentrations.

Response: This comment is addressed in section VIII.B.3.c of the preamble to the final 

rule. 

H. Comments on the network design for the proposed secondary PM2.5 visibility index. 

(1) Comment: One commenter stated that the scope of the speciation monitors should be 

limited to “urban areas” only and should not include IMPROVE monitoring sites, which 

are already evaluated as part of the Regional Haze program. 

Response: For the reasons stated in section VI of the preamble to the final rule, EPA is 

not adopting the proposed secondary PM2.5 visibility index NAAQS. Consequently, the 

final rule does not include requirements on the use of CSN or IMPROVE stations. 

(2) Comment: One commenter recommends that the EPA clarify that PM2.5 chemical species 

measurements be only required in urban areas, primarily utilizing the CSN network. 

Also, to the extent that an individual monitoring agency may not have appropriate CSN 

measurements, and wishes to use IMPROVE instead, the agency should have that 

flexibility. 

Response: For the reasons stated in section VI of the preamble to the final rule, EPA is 

not adopting the proposed secondary PM2.5 visibility index NAAQS. Consequently, the 

final rule does not include requirements on the use of CSN or IMPROVE stations. 
V-48 

(3) Comment: Two commenters stated that use of data from IMPROVE sites could be 

problematic as those sites are not always operated by state, local, or tribal air monitoring 

agencies. One of these commenters would prefer to only use data that they collect, 

analyze, quality assure, report, and certify. 

Response: For the reasons stated in section VI of the preamble to the final rule, EPA is 

not adopting the proposed secondary PM2.5 visibility index NAAQS. Consequently, the 

final rule does not include requirements on the use of CSN or IMPROVE stations. 

(4) Comment: One commenter stated that with regard to using deciviews that this metric was 

primarily developed for areas with a long site path to encompass a large sample size. The 

approach used for the proposed visibility standard is only one sampling point, which may 

not be representative for estimating visibility of an entire airshed. Additional sampling 

points should be considered. 

Response: For the reasons stated in section VI of the preamble to the final rule, the EPA 

is not adopting the proposed secondary PM2.5 visibility index NAAQS. Consequently, 

the final rule does not include requirements for monitoring sites to support such a 

standard. 

(5) Comment: One commenter stated the many of the urban speciation sites were originally 

located close to industrial facilities to ascertain their unique characteristics and influence 

upon air quality. These sites represent impacts in only a very small urban area and thus 

do not necessarily represent areas large enough to comprise “vistas”. 

Response: For the reasons stated in section VI of the preamble to the final rule, the EPA 

is not adopting the proposed secondary PM2.5 visibility index NAAQS. Consequently, 

the final rule does not include requirements for monitoring sites to support such a 

standard. 

(6) Comment: One commenter supported the minimum network design where only certain 

cities over 1 million in population would be required to have CSN stations to support the 

proposed visibility index. The commenter stated that they agree with the EPA’s approach 

in not having every city in the state over 1 million in population have to perform CSN 

measurements as their own analyses shows that their two major cities, which have longstanding CSN stations (Raleigh and Charlotte, NC), both have deciview calculations that 

are the same at 24 deciviews as calculated by the EPA for years 2008 – 2010. 

Response: For the reasons stated in section VI of the preamble to the final rule, the EPA 

is not adopting the proposed secondary PM2.5 visibility index NAAQS. Consequently, 

the final rule does not include requirements for monitoring sites to support such a 

standard. 

(7) Comment: One commenter identified that their monitoring program had two speciation 

sites in urban areas that are not near the population threshold proposed for the urban 

visibility standard (i.e., CBSAs greater than 1,000,000 in population). 
V-49 

Response: For the reasons stated in section VI of the preamble to the final rule, the EPA 

is not adopting the proposed secondary PM2.5 visibility index NAAQS. Consequently, 

the final rule does not include requirements for monitoring sites to support such a 

standard. However, to clarify, the proposed network requirements for CSN (or 

IMPROVE) were intended as minimum network requirements and not as criteria for 

comparability to the NAAQS. 

(8) Comment: One commenter stated that the EPA’s proposal of the visibility standard 

indicates that both urban and rural monitors are subject to the visibility standard; 

however, the commenter believes that rural monitoring should be excluded for use in 

determining attainment of the visibility index NAAQS. 

Response: For the reasons stated in section VI of the preamble to the final rule, the EPA 

is not adopting the proposed secondary PM2.5 visibility index NAAQS. Consequently, the 

final rule does not include requirements for monitoring sites to support such a standard. 

(9) Comment: One commenter stated lacking any empirical support for its intended use of 

the existing monitoring network, if the EPA finalizes a secondary PM2.5 visibility 

NAAQS, the EPA should at minimum adopt the approach it took in 1997 when it first 

established a PM2.5 standard. In specific, President Clinton directed the EPA to only 

address decisions regarding attainment and nonattainment areas when a well designed 

PM2.5 monitoring network was in place. The 1997 NAAQS implementation strategy 

stated that, “[b]ecause the EPA is establishing standards for a new indicator for PM (i.e., 

PM2.5) it is critical to develop the best information possible before attainment and 

nonattainment designation decisions are made.”47 The policy directed that 

“unclassifiable” designations be issued until there was a robust network specifically 

designed to address the new PM indicator. 

Response: For the reasons stated in section VI of the preamble to the final rule, EPA is 

not adopting the proposed secondary PM2.5 visibility index NAAQS. Consequently, the 

final monitoring rule does not include requirements on the use of CSN or IMPROVE 

measurements. 

(10) Comment: One commenter (NEDA/CAP) stated EPA’s proposal for the secondary 

visibility standard is technically flawed. EPA addressed visibility at a single point 

measurement rather than an integrated sight path average PM2.5 concentration. 

Response: For the reasons stated in section VI of the preamble to the final rule, EPA is 

not adopting the proposed secondary PM2.5 visibility index NAAQS. Consequently, the 

final monitoring rule does not include requirements on the use of CSN or IMPROVE 

measurements, or their siting to support such a standard. 
V-50 

I. Comments on the use of PM2.5 Continuous FEMs at SLAMS 

(1) Comment: Several commenters were supportive of the proposal allowing identification of 

PM2.5 continuous FEMs that should not be used for comparison to the PM2.5 NAAQS 

through an evaluation in the annual monitoring network plan. 

Response: The comment in support of the proposal is acknowledged and the EPA is 

adopting the proposed approach in the final rule. 

(2) Comment: One of the commenters supportive of the proposal allowing identification of 

PM2.5 continuous FEMs that should not be used for comparison to the PM2.5 NAAQS 

stated that such an approach would encourage continued use and improvements of these 

methods. 

Response: The comment in support of the proposal is acknowledged and the EPA is 

adopting the proposed approached in the final rule. 

(3) Comment: Of the many commenters that were supportive of the proposal allowing 

identification of PM2.5 continuous FEMs that should not be used for comparison to the 

PM2.5 NAAQS through an evaluation in the annual monitoring network plan, several of 

these commenters also recommended that monitoring agencies be allowed to identify and 

recommend exclusion of FEM continuous data both prospectively and retrospectively. 

Response: The EPA has addressed this issue in section VIII.B.3.ii of the preamble of the 

final rule. 

(4) Comment: One commenter did not support the proposal to allow data comparability 

assessments between continuous FEMs and FRM monitors that are not located at the 

same site. 

Response: The EPA’s intention in allowing the grouping of sites for purposes of 

allowing identification of PM2.5 continuous FEMs that should not be used for comparison 

to the PM2.5 NAAQS through an evaluation in the annual monitoring network plan is to 

provide for flexibility so that monitoring agencies do not have to collocate every PM2.5

continuous FEM with an FRM to assess that FEM’s suitability for NAAQS use. The EPA 

wishes to recognize the reality that not every continuous FEM is collocated with an FRM. 

However the final approach does not in any way restrict collocating sites. Each agency 

can decide for itself if it chooses to collocate more than the minimally required number of 

sites. 

(5) Comment: One commenter stated that reasonable minimum requirements for 

demonstration and assessment of FEM performance must be clearly stated, not only in a 

preamble, and consistently applied across all regions. As described in the preamble, the 

determination, demonstration, and decisions involved in the assessment of non-equivalent 

FEM data could easily become a significant burden for monitoring organizations that 

have relied on the equivalency designation to design and implement a monitoring 
V-51 

strategy. The EPA must develop a more representative and reliable protocol to designate 

approved monitoring methods. 

Response: In the preamble section VIII to the final rule, the EPA provides some 

additional information for monitoring agencies on how to address this issue. The EPA 

shares the concern on assessments becoming a significant burden to monitoring agencies 

and will work to minimize this burden wherever possible. EPA also points out that such 

an assessment is not required; however, the EPA has developed an automated tool to 

assist monitoring agencies when performing assessments. See: 

http://www.epa.gov/airquality/airdata/ad_rep_frmvfem.html. 

(6) Comment: One commenter stated that the recent availability of the “PM2.5 Continuous 

Monitor Comparability Assessment” web-based tool is a valuable addition, and provides 

States with a uniform approach to FEM data quality assessment. 

Response: The comment in support of this tool is acknowledged. 

(7) Comment: One commenter stated that due to lack of experience, data, and the 

experimental nature of near-roadway monitoring, PM2.5 FEMs should not be used for 

determining compliance with the NAAQS. 

Response: As explained in the preamble to the proposal, the EPA has conducted an 

assessment of the comparability of PM2.5 FEMs and found that in many cases the data are 

meeting the performance criteria used to approve theses methods when compared to 

collocated FRMs. Since the monitoring agencies are achieving the desired comparability 

with these continuous FEMs – at least in some cases, the EPA is supportive of their 

continued use, including for comparison to the NAAQS. The EPA has provided a process 

for identifying data from continuous FEMS that is not suitable for comparison to the 

NAAQS, and will continue to consider issues related to the performance of the 

continuous FEMs in the future. 

(8) Comment: One commenter does not support the use of PM2.5 continuous FEMs for 

comparison to the NAAQS at near-roadway sites until problems with FEMs have been 

adequately addressed. 

Response: As explained in the preamble to the proposal, the EPA has conducted an 

assessment of the comparability of PM2.5 FEMs and found that in many cases the data are 

meeting the performance criteria used to approve these methods when compared to 

collocated FRMs. Since the monitoring agencies are achieving the desired comparability 

with these continuous FEMs, the EPA is supportive of their continued use, including for 

comparison to the NAAQS. However, as explained in the preamble, there is a process for 

identifying data from continuous FEMs not suitable for comparison to the NAAQS, and it 

remains the monitoring agencies choice to use a FRM, filter-based FEM, or continuous 

FEM at near-road monitoring stations or other SLAMS. So even if the commenter 

disagrees with the EPA’s position, it can still choose the method that they are most 
V-52 

comfortable with so long as it is an approved FEM; FRM; or ARM, if one of those 

methods were to become available at a later time. 

(9) Comment: One commenter stated that the EPA should develop sample language for 

inclusion in individual agencies’ PM2.5 Quality Assurance Project Plans (QAPPs) 

regarding criteria for FEM data exclusion. 

Response: The EPA intends to work with monitoring agency stakeholder groups to 

develop such language. The sample language may be documented in one or more 

locations; for example, a location such as the Quality Assurance Handbook for Air 

Pollution Measurement Systems – Volume II, EPA-454/B-08-003, December 2008. 

(10) Comment: Several commenters stated that the EPA should provide an acceptable range 

for each instrument parameter (for the continuous FEMs) that is associated with the 

ambient concentration data. Over the last several years, the EPA has provided minimal 

guidance on how to determine when the FEM instruments are satisfactorily performing. 

Response: The EPA will work with monitoring agencies and instrument companies on 

updating the acceptable ranges for instrument parameters so that they can be incorporated 

in monitoring agency SOPs and quality assurance projects plans, where applicable. The 

EPA has developed draft SOPs for three of the more commonly used continuous FEMs. 

These SOPs were developed in cooperation with several monitoring agencies and they 

are available on the web at: http://www.epa.gov/ttn/amtic/contmont.html. The EPA 

anticipates it will update these SOPs to accommodate the latest information on acceptable 

ranges for each instrument parameter. 

(11) Comment: One commenter stated that PM2.5 monitoring methods are widely believed to 

be suspect. The EPA should revisit the adequacy of those methodologies before reducing 

the PM2.5 standard. EPA's supporting materials for the FRM for PM2.5 monitoring set 

forth in Appendix L to 40 CFR Part 50 indicate that reductions in the standard could 

exacerbate the limitations of the method, i.e. limiting the method's effectiveness in 

defining meaningful differences in PM2.5 concentrations. The commenter understands 

that ongoing implementation of FEM monitoring (alternative methodologies) indicates 

inconsistent degrees to which a given equivalent method is comparable to the FRM, 

varying from site-to-site. The inconsistencies may suggest that the "equivalent" methods 

are producing more accurate data than the FRM. Further, the EPA research as to the 

reliability and accuracy of the FRM for PM2.5 is necessary before reducing the standard.

Response: As stated in the preamble to the final rule, the EPA believes that progress is 

being made to implement well performing PM2.5 continuous FEMs across the nation. 

However, in recognition that some monitoring agencies are not achieving the expected 

data comparability, and as explained in section VIII of the final rule, the EPA has 

finalized a process by which monitoring agencies can identify and exclude PM2.5

continuous FEM data, where comparability results are not met, from comparison to the 

NAAQS. The EPA believes that the combination of using the FRMs, filter-based FEMs, 

and well performing continuous FEMs across the network provides more than a sufficient 
V-53 

number of monitoring options to support the revised PM2.5 standard. As stated in the 

preamble, the EPA intends to continue working with monitoring agencies and instrument 

manufacturers to document best practices on these methods to improve the comparability 

and consistency of resulting data, wherever possible. 

(12) Comment: One commenter stated that until it is demonstrated that virtually all of the 

continuous FEMs reliably replicate FRM PM2.5 concentrations throughout the U.S. and 

all times of the year, the FEMs should not be used to provide primary data for 

comparison to NAAQS unless a state provides evidence of the equivalence of FEMs in 

comparison with the FRM for a specific area. 

Response: As described in section VIII of the preamble to the final rule, the EPA 

finalized an approach to allow monitoring agencies to specify their intention to use or not 

use data from continuous PM2.5 FEMs that are eligible for comparison to the NAAQS as 

part of their annual monitoring network plan due to the applicable EPA Regional Office 

by July 1 each year. The EPA believes this provision ensures monitoring agencies will 

only use PM2.5 continuous FEM data where an appropriate level of comparability with 

collocated FRMs has been determined. First, despite some differences between the 

instrument company field testing of the continuous FEMs with collocated FRMs and the 

monitoring agency operation of these methods (e.g., averaging of three FRMs and three 

candidate continuous FEMs in the instrument company tests; operation of the FRMs from 

morning to morning periods, rather than midnight to midnight as is the case in routine 

monitoring programs) these methods were approved as they met performance criteria in 

each of the field locations where they were tested. These field tests included multiple 

locations around the country with specifications on winter and summer seasons, 

depending on location. Second, as stated in the preamble there are likely multiple 

reasons why some of the PM2.5 continuous FEMs are not meeting the expected 

performance criteria. Some of these reasons such as differences in installation, operator 

training, and development and use of Standard Operating Procedures (SOPs) are likely to 

affect data comparability on an agency by agency basis. Therefore, the EPA believes this 

approach appropriately allows a method working in one or more monitoring programs 

with acceptable comparability to be used in comparison to the NAAQS. 

J. Comments on Weight of Evidence Approach in the Revisions to the Quality Assurance 

Requirements for SLAMS, SPMs, and PSD. 

(1) Comment: The large majority of comments were in favor of the weight of evidence 

approach for determining whether the quality of data is appropriate for regulatory 

decision-making purposes. Some that supported the approach also provided a word of 

caution that there needs to be a minimum set of requirements for data collection and 

reporting in order for data to be used for attainment/non-attainment decisions. 

Response: The EPA agrees with the commenter’s point that data should be subject to a 

minimum set of requirements for data collection, reporting, and quality. While the EPA 

considers the Appendix A requirements the minimum for reporting, it is not the only data 

that the EPA and the monitoring organizations use to judge quality. Therefore if an 

Appendix A requirement for some reason is not complete it should not be the sole reason 
V-54 

to declare the data invalid or unusable. The comment in support of the proposal is 

acknowledged and the EPA is adopting the proposed approached in the final rule.

(2) Comment: One commenter felt that the paragraph, as written, undermines the importance 

of the quality control/quality assurance system dictated in Part 58 and also said that 

while a common sense approach to the assessment of quality data is important, minimum 

requirements are necessary to ensure scientifically-defensible data is being used in 

decision making. 

Response: The EPA agrees with the commenter’s point that data should be subject to a 

minimum set of requirements for data collection, reporting, and quality. In developing the 

weight of evidence approach EPA is not attempting to diminish the requirements of 

Appendix A but rather ensuring that other elements of a quality system that monitoring 

organizations implement and are documented in their QAPP can also be used when 

judging whether data are valid for a particular monitoring objective. After considering the 

support for this change, EPA will adopt the proposed weight of evidence approach in the 

final rule.

(3) Comment: One commenter who felt that the approach may be appropriate suggested that 

the language of the proposal was vague and may weaken the ability of air monitoring 

agencies to validate their own data and instead allows EPA to make decisions regarding 

data validity. 

Response: The EPA agrees that the monitoring organizations know more about their data 

and that these organizations are responsible for certifying the data as valid. In the 

majority of cases when the quality of ambient air data is called into question, the EPA 

Regions and monitoring organizations work together and reach consensus on data 

usability. However, since the EPA is responsible for making final NAAQS decisions, in 

rare cases it may ultimately have to make a validity decision that the monitoring 

organization may not agree with. After considering the support for this change, the EPA 

will adopt the proposed weight of evidence approach in the final rule.

(4) Comment: A few commenters, although supporting the weight of evidence approach, 

also commented that Appendix A minimum requirements should not only apply to all air 

quality data collected by state, local, and tribal agencies, but also to “secondary” data 

collected by other monitoring efforts. 

Response: The EPA believes that the term secondary data is used to represent 

information that may have been originally intended for one monitoring objective but is 

now being used for a “secondary” objective. The EPA assumes this term is used to either 

represent the Chemical Speciation and IMPROVE Network data being used in the light 

extinction calculation for the proposed secondary visibility index NAAQS standard, or 

for criteria pollutant data collected by entities other than the state, local or tribal 

monitoring organizations. The EPA agrees with the comments that the Appendix A 

requirements must apply to the CSN and IMPROVE data and included the term “PM2.5

CSN” to refer to both networks. Based on the assessment of the CSN and IMPROVE data 

against the PM2.5 DQOs (10% precision and + 10% bias) it appeared that the PM2.5 DQOs 

were being met under the current CSN and IMPROVE quality systems (QAPPs and 
V-55 

SOPs). However, since the EPA is not adopting the proposed secondary PM2.5 visibility 

index NAAQS, the EPA will not include these QA requirements into Appendix A since 

the networks will not produce data related to NAAQS decisions. 

K. Comments on Quality Assurance Requirements for the Chemical Speciation Network. 

There were no comments on the proposed addition of collocation and flow rate 

requirements in Appendix A for the chemical speciation network (CSN). However, since for the 

reasons stated in section VI of the preamble to the final rule, the EPA is not adopting the 

proposed secondary PM2.5 visibility index NAAQS, we will not include any PM2.5 secondary 

standard QA requirements related to the Chemical Speciation Network or IMPROVE Network 

into Appendix A.

L. Comments on Waiver for Wider Spacing of Collocated Monitors 

(1) Comment: All comments received supported the proposed requirement allowing up to 10 

meter horizontal spacing for sites at a neighborhood or larger scale of representation. 

During stakeholder presentations of the proposal, the EPA received verbal comments that 

monitoring organizations were also having difficulties meeting the 1 meter vertical limit 

since PM2.5 FEMs are often housed in shelters with inlets extending through shelter roofs 

while the collocated FRM monitors are placed outside usually on low platforms. 

Response: The comments in support of the proposal are acknowledged and the EPA is 

adopting the proposed approach in the final rule. Based on discussion with EPA’s Office 

of Research and Development, the agency will amend the Appendix A requirements to 

allow for a 1-3 meter vertical spacing which may be approved by the Regional 

Administrator for sites at a neighborhood or larger scale of representation. In addition, 

the language will be amended to allow for waiver approvals during annual network plan 

approval processes. 

M. Additional QA Related Comments not Specifically Related to Proposed Changes to 

Appendix A 

(1) Comment: The EPA received a comment that another part of the rule appeared to 

encourage the use of collocated FEM samplers in an official reporting capacity where 

they have been held back or used sparingly up to now due to concerns regarding 

operational confidence. The commenter was suggesting this reference was intended to 

allow primary FRM monitors to be collocated with FEM monitors for QA purposes 

which would require a regulatory change to the current QA requirements. 

Response: The verbiage described by the commenter referred to allowing FEM 

collocated data from a site that has an FRM as the primary monitor to replace the FRM 

data (if a scheduled sample was invalidated or not collected) or augment data (filling in 

for unscheduled samples). The FRMs collocated with continuous FEMs in this context 

were not meant to count towards meeting the QA collocation requirements and EPA does 

not intend to change the current PM2.5 QA collocation requirements. 
V-56 

(2) Comment: A commenter had concerns that the reporting of IMPROVE data for 

comparison to a secondary PM2.5 visibility index standard could prove problematic as 

those sites are not always operated by state, local, or tribal air monitoring agencies. They 

felt that the regulation should outline some data quality and certification responsibilities 

to the appropriate state, local, or tribal air monitoring agencies. 

Response: The EPA acknowledges this comment; however, since the EPA is not adopting 

the proposed secondary PM2.5 visibility index NAAQS, the EPA will not include any 

PM2.5 secondary standard QA requirements related to the Chemical Speciation Network 

or IMPROVE Network into Appendix A. 

(3) Comment: Commenters recommended that the EPA develop explicit guidance regarding 

the methodology and criteria for assessing validity of air quality data from secondary 

sources. Such data evaluations should be included as part of the five year Network 

Assessment. 

Response: The EPA acknowledges this comment. However, since the EPA is not 

adopting the proposed secondary PM2.5 visibility index NAAQS, the EPA will not 

include any PM2.5 secondary standard QA requirements related to the Chemical 

Speciation Network or IMPROVE Network into Appendix A.

(4) Comment: Commenter felt that EPA should clarify the use of the term "PM2.5 CSN" in 

40 CFR part 58 Appendix A. "CSN" is used several times throughout the proposal to 

denote a network separate from the IMPROVE network. The definition in Appendix A 

should clearly state if it includes IMPROVE monitors.

Response: The EPA acknowledges this comment. However, since the EPA is not 

adopting the proposed secondary PM2.5 visibility index NAAQS, the EPA will not 

include any PM2.5 secondary standard QA requirements related to the Chemical 

Speciation Network or IMPROVE Network into Appendix A since the networks will not 

produce data related to NAAQS decisions. 

N. Comments on Probe and Monitoring Path Siting Criteria 

(1) Comment: One commenter supports making the Appendix E siting criteria for near-road 

PM2.5 monitoring the same as the Appendix E siting criteria for near road monitoring of 

nitrogen dioxide and carbon monoxide. 

Response: The comment in support of the proposal is acknowledged and the EPA is 

generally adopting this approach, except as explained in the preamble to the final rule, we 

are also including a provision for separation distances from horizontal and vertical 

distances that is consistent with the existing PM criteria (i.e., greater than 2 meters). For 

gas monitoring the separation distances from horizontal and vertical distances is greater 

than 1 meter. 
V-57 

(2) Comment: Two commenters support the proposal to extend the existing probe and 

monitoring path siting criteria described in Appendix E to 40 CFR Part 58 for PM2.5 

FRMs and FEMs to the CSN and IMPROVE measurements. 

Response: For the reasons stated in section VI of the preamble to the final rule, the EPA 

is not adopting the proposed secondary PM2.5 visibility index NAAQS. Consequently, 

the final rule does not include requirements on the use of CSN or IMPROVE 

measurements. 

(3) Comment: One commenter suggested allowing the same 10 meter collocation waiver 

provision proposed for the PM2.5 NAAQS to also apply to CSN monitors. 

Response: For the reasons stated in section VI of the preamble to the final rule, the EPA 

is not adopting the proposed secondary PM2.5 visibility index NAAQS. Consequently, 

the final rule does not include requirements on the use of CSN or IMPROVE 

measurements. 

(4) Comment: The PM2.5 monitor should have the same height and distance from the road 

requirements as NO2, but the distance to the nearest vertical wall or obstruction should be 

increased to match the requirements for current micro- and middle-scale installations. It 

is not advisable to install a PM2.5 monitor adjacent to a wall or other obstruction that 

would disrupt the normal upwind-to-downwind flow across the roadway. 

Response: As explained in the preamble to the final rule, the EPA did not propose to 

change the existing requirements regarding placement near walls or obstructions. As 

such, even though a PM2.5 monitor may be collocated with an NO2 monitor at a near-road 

location, the individual siting requirements regarding placement near walls or 

obstructions for each pollutant still apply. 

(5) Comment: One commenter stated that the required near-road measurements of PM2.5

must be suitably distant from traffic so as not to be influenced by traffic wake effects that 

make the measurements unrepresentative of ambient air. For at-grade roadways, the 

turbulent wakes caused by traffic and wind blowing across a busy road result in eddies 

that disturb the air flow and trap pollutants. This phenomenon, similar in some respects to 

building-wake cavity effects, causes recirculation and high concentrations can occur if 

emissions are trapped within this zone. Population exposure near roadways generally 

occurs outside of this zone. If a monitor were to be placed in this recirculation zone, it 

could misrepresent concentrations in ambient air by for areas not immediately close to 

roadways. The general rule of thumb is that this turbulent zone could extend 5 to 10 times 

the vehicle height from the road, which for a box trailer would correspond to about 15 to 

30 m. For an elevated roadway or complex interchange with complex structures, the 

required offset distance could be greater. 

Response: The EPA is finalizing its proposal on the siting of the PM2.5 monitors in the 

near-road environment, which is the same as the NO2 siting, which states to be as near as 

practicable to the road but no more than 50 meters away. While EPA is finalizing these 
V-58 

siting criteria, it did consider the optimum distance that sites should be located at in the 

Near-Road NO2 Monitoring Technical Assistance Document (TAD) EPA-454/B-12-002, 

June 2012. In this document, we recommend that the ideal distance is within 20 meters 

the road. In providing this additional guidance we cite Baldauf et al. (2009) in the TAD, 

which notes that a distance of 10 to20 meters should be considered for near-roadway 

monitoring. The referenced paper states that this is partly to avoid being in the wake 

zone as described by the commenter. Now that we are finalizing requirements for siting 

of PM2.5 monitors in the near-road environment and we want these measurements to be 

collocated with the near –road NO2 monitors, it is appropriate to use the same additional 

guidance from the Near-Road NO2 Monitoring TAD when considering the optimum 

location of the monitor for PM2.5. Therefore, and as stated in the TAD, the EPA strongly 

encourages state and local agencies to place near-road NO2 monitor probes, and now 

PM2.5 inlets within 20 meters from target road segments whenever possible. To avoid 

being in the wake zone as described by Baldauf et al. (2009), monitoring agencies should 

also consider, but are not required, to site inlets at least 10 meters from the road, if 

possible. While the commenter’s distance is a little different as its based on an example 

of a box trailer (15 to 30 meters), we believe this approach adequately addresses this 

issue, taking into consideration the need to address other issues related to monitoring 

objectives for near road sites. 

O. Comments on the Annual Monitoring Network Plan and Periodic Assessment 

(1) Comment: One commenter requested that the EPA clarify the requirements for 

assessments and identify differences between the network assessments and the network 

plan requirements. 

Response: The requirements for annual monitoring network plans and five year 

assessments are detailed in §58.10. Essentially, a five year assessment is intended to be a 

comprehensive assessment while an annual monitoring network plan is intended to be the 

year to year changes that are being implemented as a result of that comprehensive 

assessment as well as any other changes that are needed. 

(2) Comment: One commenter recommends that an evaluation of the requirements for the 

Five Year Monitoring Network Assessment should be reevaluated in light of the 

frequency with which NAAQS standards are revised. The commenter recommends that 

this evaluation be conducted by one or more of the National Association of Clean Air 

Agencies (NACAA)/EPA stakeholder groups. 

Response: The comment in support of a reevaluation of the requirements for the Five 

Year Monitoring Network Assessment, conducted by one or more of the National 

Association of Clean Air Agencies (NACAA)/EPA stakeholder groups is noted. 

(3) Comment: One commenter stated that the tools available (for the five year assessments) 

are inadequate for the objective assessment needed for urbanized areas, and assessment 

of inter- and intrastate scales needed by monitoring agencies. Also, that the monitoring 
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and supporting data does not, and typically will not, have the spatial resolution to allow 

adequate network assessment at the most useful scales, the urban area, or MSA. 

Response: This comment is addressed in section VIII.B.6.a of the preamble to the final 

rule. 

(4) Comment: One commenter stated that EPA must take the experience gained by the states 

and local monitoring organizations in the development of these first assessment 

documents to immediately start development of new and refined tools and state-specific 

data hinted at in the Monitoring Assessment Guidance. Many monitoring organizations 

could greatly benefit from accessible tools that can be used to refine and improve MSA 

and state scale monitoring networks. 

Response: This comment is addressed in section VIII.B.6.a of the preamble to the final 

rule. 

(5) Comment: One commenter strongly recommended that EPA provide guidance to States 

at least one year prior to the due dates for the 5-year assessments. 

Response: As stated in section VIII.B.6.a of the preamble to the final rule, the EPA will 

work with States to support tools and guidance on the five year assessments. 

(6) Comment: One commenter stated that any requirements for the State agencies should be 

met with commensurate requirements for the EPA Region to review and respond to the 

assessment. 

Response: The 5-year network assessments are required to be submitted along with 

annual monitoring network plans during the years when the assessments are due (e.g., 

2010, 2015, etc.). During the initial assessment conducted in 2010, many EPA regions 

did include the network assessment as part of the overall dialogue with the submitting 

agency. The EPA will consider ways to improve the process and the text of part 58 in a 

possible future rule making on monitoring. 

(7) Comment: One commenter stated that it would be more efficient to make a periodic 

monitoring network assessment an activity conducted by regional planning organizations 

(RPOs) with commensurate funding going to the RPO as LADCO did for Region V states 

for the 2010 assessment. 

Response: The coordination of five-year assessments by or through a regional planning 

organization is an appropriate way to perform these required assessments. 

P. Comments on Operating Schedules 

(1) Comment: One commenter stated that they generally agree that every day sampling is 

appropriate for sites whose design values are within 5% of the NAAQS. However, for 

sites with design values greater than 5% above the NAAQS, reduced sampling frequency 
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should be allowed only if the sites has a collocated continuous PM2.5 monitor that is 

suitable for Air Quality Index (AQI) reporting required by 40 CFR Part 58, Appendix G. 

Response: The comment in support of the proposal is acknowledged and EPA is adopting 

the proposed approached in the final rule. Regarding the recommendation on sites with 

design values greater than 5% above the NAAQS, where reduced sampling frequency 

should be allowed only if the site has a collocated continuous PM2.5 monitor that is 

suitable for AQI reporting required by 40 CFR Part 58, Appendix G, the EPA believes 

the existing monitoring rules are already largely supportive of operating PM2.5 continuous 

methods at SLAMS. For example, at least one-half (round-up) the minimum required 

sites according to Table D-5 of appendix D to part 58 are to have a PM2.5 continuous 

monitor operating at the sites. This requirement ensures that there is at least one PM2.5

continuous monitor operating in each CBSA required to monitor for PM2.5. 

(2) Comment: One commenter supports that it is reasonable for each agency to determine 

the applicability of the requirement for daily sampling once a year when updating the 

annual monitoring network plan. 

Response: The comment in support of the proposal is acknowledged and the EPA is 

adopting the proposed approached in the final rule. 

(3) Comment: One commenter recommended retaining the current sample frequencies for 

PM measurements. 

Response: The EPA believes the proposed changes will provide flexibility and 

predictability regarding how sample frequency changes are addressed, which will be of 

benefit to monitoring agencies as they operate their PM2.5 monitoring programs. 

Accordingly, the EPA is finalizing the changes to the sample frequency requirements for 

PM2.5 as proposed. 

Q. Comments on Data Reporting and Certification for CSN and IMPROVE data 

(1) Comment: One commenter identified that an appropriate and efficient approach for 

implementing the visibility standard would be to require urban areas with only 

IMPROVE monitors to add one CSN monitor to the urban area and align NAAQS and 

CSN data reporting and certification requirements to meet the May 1 data certification 

deadline cited in 40 CFR 58.15. 

Response: For the reasons stated in section VI of the preamble to the final rule, the EPA 

is not adopting the proposed secondary PM2.5 visibility index NAAQS. Consequently, 

the final rule does not include requirements on the use of CSN or IMPROVE 

measurements. 

(2) Comment: One commenter recommended that the EPA work with the IMPROVE 

program to reduce the lead time for data submittal and certification in the EPA’s Air 
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Quality System (AQS) and align the IMPROVE quality assurance protocol with the CSN 

and SLAMS networks. 

Response: For the reasons stated in section VI of the preamble to the final rule, the EPA 

is not adopting the proposed secondary PM2.5 visibility index NAAQS. Consequently, 

the final rule does not include requirements on the use of CSN or IMPROVE 

measurements. 

(3) Comment: One commenter recommended that data from IMPROVE be submitted to 

AQS no more than 6 months after they are collected. 

Response: For the reasons stated in section VI of the preamble to the final rule, the EPA 

is not adopting the proposed secondary PM2.5 visibility index NAAQS. Consequently, 

the final rule does not include requirements on the use of CSN or IMPROVE 

measurements. 

(4) Comment: One commenter recommended that data from IMPROVE and CSN be placed 

on a separate certification schedule where data for an entire year is certified by August 1 

of the following year. 

Response: For the reasons stated in section VI of the preamble to the final rule, the EPA 

is not adopting the proposed secondary PM2.5 visibility index NAAQS. Consequently, 

the final rule does not include requirements on the use of CSN or IMPROVE 

measurements. 

(5) Comment: One commenter stated that the proposed delay in data certification could pose 

problems with the states’ ability to meet mandated due dates to provide technical 

justification for excluding data due to exceptional events. 

Response: For the reasons stated in section VI of the preamble to the final rule, the EPA 

is not adopting the proposed secondary PM2.5 visibility index NAAQS. Consequently, 

the final rule does not include requirements on the use of CSN or IMPROVE 

measurements or changes to the data certification of this data. 

(6) Comment: One commenter stated the certification data should be extended to six months 

from the end of the quarter in which the data were collected to provide sufficient time for 

lead, CSN and IMPROVE data certification. 

Response: For the reasons stated in section VI of the preamble to the final rule, 

the EPA is not adopting the proposed secondary PM2.5 visibility index NAAQS. 

Consequently, the final rule does not include requirements on the use of CSN or 

IMPROVE measurements or changes to the data certification of this data. 
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R. Comments on the Requirements for Archiving Filters 

(1) Comment: Several commenters support the proposal to extend the filter archival 

requirements from one to five years, with cold storage during the first year. 

Response: The comments in support of the proposal are acknowledged and the EPA is 

adopting the proposed approached in the final rule. 

(2) Comment: One commenter suggested that the EPA study the effectiveness of long term 

cold storage looking specifically at repeatability of gravimetric measurements. 

Response: Such studies already exist. Also, the EPA has existing guidance on the storage 

of filters and may, at its discretion, update that guidance in light of the changes to filter 

storage requirements. 

(3) Comment: One commenter stated that they do not have the space to store four years of 

samples in either cold or ambient storage and believes this proposed requirement would 

be burdensome even if the samples dot not need to be stored cold. 

Response: This comment is addressed in section VIII of the preamble of the final rule. 

(4) Comment: One commenter questioned the value of filter retention beyond one year if 

they are not refrigerated. Critical information may be lost once filters go to room 

temperature. Perhaps 2-year cold storage retention with a 5-year total is more 

appropriate. 

Response: The EPA believes, that at a minimum, analyses for elements can be conducted 

very successfully for several years after sample collection and that these analyses can be 

performed with filters that have either have or have not been refrigerated. Other 

analyses, such as for nitrate and sulfate ions, provide better results when refrigerated and 

their long term usefulness is not expected to be as good compared to elemental analysis. 

S. Funding and Resources Issues associated with Ambient Air Monitoring Requirements 

The EPA received numerous comments on funding and resources associated with the 

implementation and operation of ambient air monitors that are described in the proposed 

amendments to the ambient monitoring requirements. We understand that monitoring agencies 

desire full funding when revisions to monitoring requirements require the purchase of new 

equipment and installation of new sites, relocation of existing monitors, and increase burdens for 

staff and operational budgets. The EPA understands these concerns. The EPA has historically 

funded part of the cost to State, local, and Tribal governments of installation and operation of 

monitors to meet Federal monitoring requirements. Sections 103 and 105 of the CAA allow the 

EPA to provide grant funding for programs for preventing and controlling air pollution and for 

some research and development efforts respectively. However, the CAA requirements from 

which this final rule derives are not contingent on the EPA providing funding to States to assist 

in meeting those requirements. Accordingly, the comments regarding funding are not directly 
V-63 

relevant to the content of this final rule. Nevertheless, the EPA recognizes that resources always 

have been and will remain a practical consideration for establishing and operating monitoring 

programs. The EPA will continue to work with States in this regard, in particular as the EPA 

determines how to allocate enacted funding among States and among types of monitoring so as 

to achieve the best possible environmental outcomes. 

(1) Comment: One commenter representing many air agencies across the country stated that 

the monitoring requirements must be fully funded, including staffing as well as operation 

and maintenance costs. New monitoring mandates must be supported by appropriate 

increases in federal funding. State and local agencies need additional, adequate federal 

funding in order to move forward with new monitoring requirements and continue to 

operate and maintain existing monitoring networks, which are crucial to the protection of 

public health and the environment. Implementing a multipollutant near roadway 

monitoring network requires the purchase of new equipment and installation of new sites, 

relocation of monitors, and additional staff, operation and maintenance costs, and must be 

fully funded under Clean Air Act section 103. 

Response: Information on how the EPA addresses funding for monitoring is described 

above. 

(2) Comment: One commenter representing a number of air agencies stated that the EPA is 

proposing new requirements for ambient air monitoring. The commenter believes the 

costs of these requirements have been significantly underestimated, in large part because 

of the proposed network design and underlying assumptions for the near‐road monitors. 

The commenter offer specific comments on the proposal that they believe will both 

reduce the costs and enhance the effectiveness of the network; we urge the EPA to 

incorporate these changes. Even with the changes, however, we believe there will be 

substantial monitoring costs, both for installation and ongoing operation/maintenance of 

the stations, as well as in data handling and network review. The commenter stated that 

their members do not have the financial resources to absorb these new costs and they 

believe the EPA must provide full funding for any new monitoring requirements that are 

established. 

Response: The EPA believes that there will be minimal cost in relocating PM2.5 monitors 

required to be implemented according to the schedule described in section VIII of the 

preamble to the final rule. The EPA considered the commenter’s suggestions on the 

proposal that they believe will both reduce the costs and enhance the effectiveness of the 

network and, as described in Section VIII.B.3.b.i of the preamble to the final rule, the 

EPA is providing for a phased deployment of the near-road monitors. Regarding the 

comment that there will be substantial monitoring costs, the EPA believes these costs 

should not be new costs since we are emphasizing moving monitors, rather than adding 

new ones. 

(3) Comment: One commenter representing several State air agencies stated that while their 

States are not opposed to adding PM2.5 monitoring to the near-road network, as the EPA 

proposes, there is no funding for this new network objective. 
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Response: As described in Section VIII.B.3.b.i of the preamble to the final rule, the EPA 

noted that a number of air agencies stated concerns that the near-road monitors are 

challenging to site and that there is additional cost in operating these monitors, the EPA 

maintains that the major challenges in siting would already be accomplished by 

implementing the required NO2 monitoring stations in near-road environments since the 

EPA fully expects that the PM2.5 monitors will be placed at the NO2 near roadway 

stations and has revised the PM2.5 monitoring requirements consistent with that 

expectation. The EPA also points out that the requirements for the minimum number of 

PM2.5 monitors is unchanged and that in most cases the addition of near-road PM2.5

monitors can be accomplished by relocating an existing monitor, with no net increase in 

monitors. Thus, while we are requiring a new component of the PM2.5 monitoring 

network, the overall size of the network is expected to remain about the same, and we 

expect that air agencies can meet this requirement by relocating existing lower-priority 

monitors. Additional information on how monitoring is funded is described above.

(4) Comment: One commenter stated that they continue to stress that monitoring 

requirements must be fully funded, including staffing as well as operation and 

maintenance costs. New monitoring mandates must be supported by increases in federal 

funding necessary to establish this new or expanded network based on revisions to the 

federal air quality standards. State agencies need additional, adequate federal funding in 

order to move forward with new monitoring requirements and continue to operate and 

maintain existing monitoring networks, which are crucial to the protection of public 

health and the environment. Implementing a new, multi-pollutant near roadway 

monitoring network requires the purchase of new equipment and installation of new sites, 

and additional staff and operation and maintenance costs at a time when state agencies 

are already struggling with budget and staffing shortfalls. New federal funding is 

necessary in order to implement these new requirements, and should be provided under 

Section 103 of the Clean Air Act (Act), rather than Section 105 of the Act which requires 

a state match for federal funding. 

Response: Information on how the EPA addresses funding for monitoring is described 

above. 

(5) Comment: One commenter stated that the addition or relocation of monitors can increase 

staffing, operation and maintenance costs for states and local agencies. U.S. EPA must 

support new monitoring mandates by providing appropriate increases in federal funding 

to ensure states and local agencies can move forward with new monitoring requirements 

and continue to operate and maintain existing monitoring networks, which are crucial to 

the protection of public health and the environment. 

Response: Information on how the EPA addresses funding for monitoring is described 

above. 

(6) Comment: One commenter stated that it is also important to note that the relocation of 

existing monitors will result in additional costs to states and these costs must be fully 

funded. For those agencies that may not be able to relocate existing monitors – because 
V-65 

they are needed to provide neighborhood scale data for a CBSA, for attainment planning 

or model confirmation, to address specific community-based air quality concerns, or 

because they are part of ongoing research efforts – full funding for the purchase, 

installation, and operation and maintenance of an additional monitor must be provided. 

We believe EPA has significantly underestimated the initial cost of the proposed 

monitoring requirements, as well as the costs of ongoing network operation. 

Response: Information on how the EPA addresses funding for monitoring is described 

above. The EPA disagrees we have significantly underestimated the initial cost of the 

proposed monitoring requirements, as well as the costs of ongoing network operation, but 

even if the costs were somewhat higher, the EPA would still judge the monitoring 

requirements as necessary and appropriate under the Clean Air Act. As explained in 

Section VIII.B.3.b.i of the preamble to the final rule, the EPA noted that a number of air 

agencies stated concerns that the near-road monitors are challenging to site and that there 

is additional cost in operating these monitors, the EPA maintains that the major 

challenges in siting would already be accomplished by implementing the required NO2

monitoring stations in near-road environments since the EPA fully expects that the PM2.5

monitors will be placed at the NO2 near roadway stations and has revised the PM2.5

monitoring requirements consistent with that expectation. The EPA also points out that 

the requirements for the minimum number of PM2.5 monitors is unchanged and that in 

most cases the addition of near-road PM2.5 monitors can be accomplished by relocating 

an existing monitor, with no net increase in monitors. Thus, while we are requiring a new 

component of the PM2.5 monitoring network, the overall size of the network is expected 

to remain about the same, and we expect that air agencies can meet this requirement by 

relocating existing lower-priority monitors, which generally requires fewer resources than 

operating new monitors. Additional information on how monitoring is funded is 

described above. 

(7) Comment: One commenter requests that the EPA provide states with additional funding 

necessary to implement the revised PM2.5 standards, including additional ambient air 

monitoring equipment. 

Response: Information on how the EPA addresses funding for monitoring is 

described above.

(8) Comment: One commenter stated that if the EPA is going to require PM2.5 monitoring at 

the near-road sites, additional funding must be provided. The EPA assumes that states 

can relocate existing monitors and thus incur no additional costs. This typically will not 

be the case as the PM2.5 monitors decommissioned probably will not be in the same 

locales where near-road monitoring is being conducted. Therefore, it cannot be assumed 

that current staffing levels are adequate for the near-road PM2.5 monitoring. Second, if a 

decision is made by a monitoring agency to shift from the FRM to other particulate 

monitoring methodologies, such as the FEM or aethalometry as allowed in the proposed 

rule, additional funding for new monitors will be needed. Third, the placement of 

additional monitors at some near-road sites may require that more safety barriers or 
V-66 

mitigation measures be installed. Hence, moving monitors cannot be assumed to be a 

zero-sum game. 

Response: Information on how the EPA addresses funding for monitoring is described 

above. With regard to the comment that a decommissioned monitor may not be in the 

same locale as where the near-road monitoring is being conducted, the EPA points out 

that there will already be other measurements at the near-road stations and therefore the 

addition of PM2.5 to this station will result in some efficiency for the operator responsible 

for the near-road station. In most cases the EPA expects that the relocation of a monitor 

will be from within the same CBSA. If there are cases where this cannot be 

accomplished and there are reasons why the relocated PM2.5 monitors cannot be 

supported, the EPA will work with agencies on a case by case basis to addresses such 

issues. 

(9) Comment: One commenter stated that they continue to stress that all monitoring 

requirements must be fully funded, including staffing as well as operation and 

maintenance costs. Relocation of existing monitors does result in additional costs to state 

and local agencies, as it requires the use of additional staff time and resources. New 

monitoring mandates must be supported by appropriate increases in federal funding. The 

commenter stated they need additional funding in order to move forward with new 

monitoring requirements and continue to operate and maintain existing monitoring 

networks, which are crucial to the protection of public health and the environment. New 

federal funding is needed to implement these new requirements, and should be provided 

under Clean Air Act § 103. 

Response: Information on how the EPA addresses funding for monitoring is described 

above. With regard to the comment that” Relocation of existing monitors does result in 

additional costs to state and local agencies”; the EPA believes that such costs will be 

minimal, or at least will be the most cost-effective means of providing necessary 

monitoring, and can be managed within the timeframe of the requirement to implement 

the near-road monitors described in section VIIIB.3.b.i of the preamble to the final rule. 

(10) Comment: One commenter stated that they do not support an expanded network to 

monitor specifically for a secondary visibility standard. States do not have the resources 

to add additional monitors for a secondary standard. 

Response: As described in Section VI of the preamble to the final rule, the EPA is not 

finalizing a secondary NAAQS using a visibility index and therefore is not finalizing the 

monitoring changes that would have been necessary to support it. 

(11) Comment: One commenter stated that they support the integration of multi-pollutant 

monitoring at NO2 near-road monitoring stations so long as federal funding is provided 

for the deployment of the monitors. 

Response: Information on how the EPA addresses funding for monitoring is described 

above.
V-67 

(12) Comment: One commenter stated that the U.S. EPA needs to provide funding for all new 

required monitors, including capital costs and operations and maintenance costs. State 

and local agencies are facing an extraordinary shortage of resources. The commenter also 

stated that they are committed to protecting air quality and public health but we must also 

be careful stewards of the public's money. In the current economic environment, state and 

local agencies are unable to develop the additional resources needed to meet the proposed 

new monitoring requirements. The regulation should be written so that new monitoring is 

not required unless the U.S. EPA has the ability to fund the initiative. 

Response: Information on how the EPA addresses funding for monitoring is 

described above.

(13) Comment: One commenter stated that they do not have a PM2.5 monitor available for 

relocation to a near-road site. Therefore, they will have to purchase a new FEM for this 

monitoring at a cost of $25,000 to $30,000. In circumstances such as this, the EPA must 

provide full funding for the purchase, installation, and operation and maintenance of a 

new PM2.5 monitor for the required roadway location. 

Response: Information on how the EPA addresses funding for monitoring is described 

above.

(14) Comment: One commenter stated that the U.S. EPA must provide supplemental funding 

that does not require matching to support purchasing, installing, operating, and 

maintaining additional fine particulate matter (PM2.5) monitors at near-road monitoring 

sites as currently proposed. If an existing monitor is relocated to a near-roadway site, 

supplemental funding should be made available to support the breakdown, relocation, and 

installation of the monitor. 

Response: Information on how the EPA addresses funding for monitoring is described 

above.

(15) Comment: One commenter stated that the regulation should be written so that new 

monitoring is not required unless the U.S. EPA has the ability to fund the initiative. 

Response: Information on how the EPA addresses funding for monitoring is described 

above. 

(16) Comment: In providing comments on the proposal to require near-roadway monitors, 

one commenter stated that most of these laudatory objectives are not directly tied to the 

implementation of the new or proposed PM2.5 NAAQS, but instead involve support for 

research. At a time when budgets for NAAQS-compliance monitoring are seriously 

limited, it does not make sense to devote those limited funds to monitoring for research 

purposes. 

Response: As stated in section VIII.B.3.b.i, the EPA believes the addition of PM2.5

monitors to the near-road environment will support a number of objectives and is 
V-68 

important for the protection of public health. Information on how the EPA addresses 

funding for monitoring is described above.

(17) Comment: Multiple commenters stated that the EPA has not demonstrated the need to 

add a requirement for near-road monitoring of PM2.5. The primary purpose of these 

monitors appears to be research. At a time when state monitoring budgets are reportedly 

inadequate to provide monitors to ascertain compliance with the 1-hour SO2 NAAQS that 

the EPA adopted in 2010, funding should not be diverted to fund new PM2.5 monitoring 

sites. 

Response: As stated in section VIII.B.3.b.i, the EPA believes the addition of PM2.5

monitors to the near-road environment will support a number of objectives and is 

important for the protection of public health. Information on how the EPA addresses

funding for monitoring is described above. 
VI-1 

VI. RESPONSES TO SIGNIFICANT COMMENTS ON IMPLEMENTATION 

The EPA received comments on a range of implementation topics discussed in section IX 

of the proposal, including initial area designations, section 110(a)(2) infrastructure State 

Implementation Plan (SIP) requirements, nonattainment area SIPs, New Source Review (NSR) 

and Prevention of Significant Deterioration (PSD) program requirements (including the specific 

proposed changes to the PSD regulations to provide a transition into meeting new requirements 

associated with the revised PM NAAQS), and the transportation conformity program. Our 

responses to specific comments relevant to this final rule are presented below. Because the EPA 

is not finalizing a new secondary PM2.5 NAAQS in this rulemaking, we are not addressing 

comments related to implementation of a distinct new secondary PM2.5 NAAQS.

A. Specific Comments Related to Designation of Areas 

This section responds to comments supporting and opposing the proposed schedules for 

initial area designations, recommending classification schemes, and discussing various technical 

and policy aspects of the area designations process. The responses to some of these comments 

are also discussed in section IX.A of the preamble to the final rule. The EPA received numerous 

comments on these issues from states, state organizations, local air pollution control agencies, 

regional organizations, industry, environmental organizations, and health-related organizations. 

(1) Comment: Most commenters expressed support for a standard 2-year schedule for initial 

area designations for the primary annual PM2.5 NAAQS. 

Response: Under section 107(d)(1) of the CAA, the EPA is required to designate areas no 

later than 2 years following promulgation of a new or revised NAAQS, or by December 

2014 based on promulgating the PM NAAQS on December 14, 2012. Also under the 

schedule in section 107(d)(1) and confirmed in the final PM NAAQS action, state 

Governors and tribes, if they choose, are required to submit their initial designation 

recommendations for the revised primary annual PM2.5 NAAQS to the EPA no later than 

1 year following promulgation of the revised NAAQS (i.e., by December 13, 2013). If 

the EPA intends to make any modifications to a state’s or tribe’s recommendations, 

including modifications to area boundaries, the EPA is required to notify the state or tribe 

no later than 120 days prior to finalizing the designation; this would be no later than 

August 14, 2014. States and tribes will then have an opportunity to demonstrate why the 

EPA's intended modification is inappropriate before the EPA makes the final designation 

decisions by December 12, 2014. 

(2) Comment: Several commenters encouraged the EPA either to consider additional time 

(up to 1 year) for initial area designations (or not to designate areas) associated with the 

proposed secondary PM visibility index standard due to the lag in obtaining data from 

speciation monitoring networks, the variability in monitored relative humidity data, and 

the “unique” nature of the proposed secondary standard. Another commenter suggested 

that, rather than waiting for data from newly established monitors, designations for the 

secondary standard should be made based on the existing PM2.5 monitoring network. 
VI-2 

Response: For the reasons stated in section VI.D.2 of the preamble to the final rule, the 

Administrator has decided not to establish the proposed distinct secondary standard to 

address visibility impairment. Therefore, the EPA will not promulgate initial area 

designations for a secondary PM visibility index standard. 

(3) Comment: Several commenters asked the EPA to clarify whether data from the proposed 

new near-road monitors will be used, if available, for initial area designations. Others 

expressed concern that data from violating near-road monitors not be used when 

designating areas as these monitors are not representative of surrounding communities 

and should not drive the designations process for an entire urban area. Many of these 

same commenters asked the EPA to clarify how near-road data might be used in future 

designations processes. 

Response: The EPA does not believe that data from the new near-road monitors will be 

available for the EPA to consider within the timeframe for initial area designations 

provided by the CAA. Section 107(d)(1) of the CAA requires the EPA to designate areas 

no later than 2 years following promulgation of a new or revised NAAQS, or by 

December 2014. (The CAA provides the Agency an additional third year from 

promulgation should there be insufficient information on which to make compliance 

determinations.46) For initial area designations for the primary annual PM2.5 NAAQS, the 

EPA relies exclusively on monitoring data to identify areas to be designated 

nonattainment due to violations of the standards and then uses monitoring data and other 

information to identify areas contributing to violations in those areas. See Catawba 

County v. EPA, 571 F.3d 12-13 (D.C. Cir. 2009). As indicated in the preamble to both the 

proposed and final PM NAAQS, the initial set of near-road PM2.5 monitors will be fully 

deployed by January 2015 with the requisite 3 years of air quality data available in 

2018.47 The EPA intends to proceed with initial area designations for the revised primary 

annual PM2.5 NAAQS using 3 years of consecutive air quality data from the existing, 

area-wide FRM/FEM/ARM PM2.5 monitoring sites to complete designations by 

December 2014.48 Consistent with previous area designations processes used in 

informing boundary decisions, the EPA would then analyze a variety of area-specific 

 

46While the EPA intends to make every effort to designate areas for the primary annual PM2.5 NAAQS on a 2-year 

schedule, the EPA recognizes that new information may later arise that justifies the need for additional time, up to 1 

additional year is available based on insufficiency of data, to complete the process. Any subsequent change to the 

designations schedule would be announced. 

47The remainder of the near-road monitors in CBSAs with populations between 1 million but less than 2.5 million 

will be deployed by January 1, 2017. 

48The EPA notes that once the EPA has promulgated initial designations for a new or revised NAAQS, section 

107(d)(3) of the Clean Air Act provides a separate process for redesignating areas based upon subsequent air 

quality-related considerations. We believe that this process is the appropriate process for addressing monitoring 

information that was not available in sufficient time to be considered during the designation process. As noted by the 

Court in Catawba v. EPA, 571 F.3d 52, “Congress imposed deadlines on EPA and thus clearly envisioned an end to 

the designation process.” It is important that states can rely on the completed designations and to move forward with 

the associated required implementation planning. 
VI-3 

information49 in determining which nearby areas contribute to a violation. 

Although we do not anticipate that data from the new near-road monitors will be 

available for initial designations, the EPA would consider near-road data meeting the 

EPA’s completeness, quality assurance, and NAAQS comparability criteria in future 

designations processes (e.g., a designations process associated with a future revision to 

the NAAQS) or in potential redesignation processes under section 107(d)(3). The EPA 

believes that data from all near-road sites are comparable to the primary 24-hour PM2.5

NAAQS and that data from near-road sites approved as area-wide sites would be 

comparable to the annual PM2.5 standard. As explained in sections III.E.3.a and 

VIII.B.3.b.i of the final rule preamble, a significant fraction of the nation’s population 

lives near major roads. The EPA has a responsibility to protect air quality and public 

health in all locations that meet EPA’s definition of ambient air, including those areas 

with populations living near major roads. As noted in the previously mentioned preamble 

sections, air agencies and the EPA will use the annual monitoring network plan described 

in 40 CFR 58.10 to identify and approve sites that are suitable and sites that are not 

suitable for comparison to the annual PM2.5 NAAQS. 

(4) Comment: One commenter suggested that the EPA conduct dispersion modeling around 

transportation facilities in accordance with the EPA’s transportation conformity hotspot 

modeling guidance and use concentrations to determine attainment status for the 

designations process. This same commenter also supported using modeling for 

unmonitored areas, e.g., communities near roadways. 

Response: As previously indicated, for the primary annual PM2.5 NAAQS, the EPA relies 

on monitoring data to identify areas to be designated nonattainment due to violations of 

the standards and does not intend to conduct or use dispersion modeling around 

transportation facilities or in unmonitored areas to determine whether an area is violating 

the standard for purposes of establishing nonattainment areas, as this is not required by 

the statute. See Catawba County v. EPA, 571 F.3d 12-13 (D.C. Cir. 2009). The EPA 

intends to address the factor analysis and boundary setting process in the designation 

guidance to the states and tribes, expected to be available shortly after promulgation of 

the PM NAAQS. 

 

(5) Comment: Several commenters emphasized the need for the EPA to provide timely 

guidance and technical information for area designations. Commenters similarly 

encouraged the EPA to consult with potentially affected areas during the area 

designations process. 

Response: As discussed in the preamble, the EPA intends to provide designation 

guidance and technical information shortly after the NAAQS are promulgated. In 

 

49The EPA has used area-specific information to support boundary determinations by evaluating factors such as air 

quality data, emissions and emissions-related data, meteorology, geography/topography, and existing jurisdictional 

boundaries. This may include, as appropriate, information from non-FRM/FEM/ARM monitors and air quality 

modeling, where available, to help define an appropriate boundary for areas contributing to FRM/FEM/ARM-based 

monitored violations. 
VI-4 

addition, the EPA plans to offer assistance to states and tribes throughout the designations 

process on technical and policy issues. 

 

(6) Comment: One commenter suggested that the EPA use the designation categories 

outlined in the Clean Air Act (i.e., nonattainment, attainment, or unclassifiable) as 

opposed to the EPA’s practice of using “unclassifiable/attainment” when designating 

areas that meet the NAAQS. The commenter noted that the “unclassifiable/attainment” 

designation is unclear to the public. Another commenter presented an additional 

designation category approach and asked the EPA to consider using “unclassifiable” or 

“transitional” when designating nonattainment areas that the EPA projects could reach 

attainment within 5 to 10 years based on federal measures. The commenter notes that 

with this approach the “EPA could take the pragmatic step of avoiding the imposition of 

costly and unnecessary stationary source controls while assuring continued progress 

toward meeting the tighter standard. Such a designation would recognize the strong role 

of [sic] federal measures provide in helping areas to attain the standard and would set the 

precedent of avoiding unnecessary and redundant costs where feasible.” 

Response: As previously discussed, the EPA intends to provide designation guidance and 

technical information shortly after the NAAQS are promulgated. The EPA expects this 

guidance to include the intended designation categories for area designations for the 

revised primary annual PM2.5 NAAQS. 

(7) Comment: Several commenters supported the EPA’s proposed approach to use 3 

consecutive years of monitored ambient air quality data to determine violations of the 

standard rather than modeling for initial area designations. One commenter urged the 

EPA to determine and clearly define the “contribution” to nonattainment. 

Response: As indicated in both the proposed and final PM NAAQS actions, the EPA 

intends to proceed with initial area designations for the revised primary annual PM2.5

NAAQS using 3 years of consecutive air quality data from the existing, area-wide 

FRM/FEM/ARM PM2.5 monitoring sites to complete designations by December 2014. 

Consistent with previous area designations processes used in informing boundary 

decisions, the EPA would then use area-specific factor analyses in determining which 

nearby areas contribute to a violation. These supporting analyses may include 

information from non-FRM/FEM/ARM monitors and air quality modeling, where 

available, to help define an appropriate boundary for areas contributing to 

FRM/FEM/ARM-based monitored violations. Shortly after the NAAQS are promulgated, 

the EPA intends to further clarify in designations guidance and technical information the 

use of monitoring data, factor analyses, and “contribution.” 

(8) Comment: Several commenters submitted remarks related to establishing boundaries for 

PM nonattainment areas. A few commenters asserted that a Metropolitan Statistical Area 

(MSA), either a Core-Based Statistical Area (CBSA) or Combined Statistical Area 

(CSA), is too large an area to use in establishing presumptive boundaries for 

nonattainment areas and prefer starting at the county boundary. 
VI-5 

Response: The EPA did not address the issue of appropriate boundaries for nonattainment 

areas in the PM NAAQS rule. The EPA will evaluate nonattainment area boundary 

recommendations from states and tribes and assess appropriate area boundaries during 

the designations process. Under the CAA, the EPA must designate as nonattainment any 

area that is violating the NAAQS or that is contributing to a nearby violation. 

(9) Comment: Multiple commenters noted that the regulatory burden associated with the 

EPA’s process of designating nonattainment areas will cause affected areas economic 

harm. 

Response: The EPA’s Regulatory Impact Analysis (RIA) provides illustrative estimates 

of the potential costs and health and welfare benefits of attaining several alternative PM2.5

standards based on one possible set of selected control strategies for reducing direct PM 

and PM precursor emissions. 

 

As previously discussed, the EPA intends to provide designation guidance and technical 

information shortly after the NAAQS are promulgated. Additionally, the EPA will be 

developing a PM NAAQS implementation rule, which the EPA intends to finalize around 

the time the initial area designations decisions are promulgated in December 2014. This 

implementation rule will address the control obligations for areas designated 

nonattainment and strive to identify, with appropriate stakeholder input, approaches that 

provide flexibility and opportunity for efficiency to the extent such approaches are 

consistent with the CAA and will not jeopardize expeditious attainment of the public 

health and welfare goals of the CAA. Finally, to the extent the CAA does not mandate 

specific control measures, states may consider economic concerns in development of 

their SIPs to address air quality. 

(10) Comment: One commenter noted that “[i]n preparing new designations, EPA must 

consider needed redesignations under the 24-hour standard, even if EPA decides to retain 

the current standard unchanged. To ignore evidence of violations of the 24-hour standard 

would be arbitrary and capricious and contrary to the health protection goals of the 

statute. Designations must be accurate to avoid irrational outcomes, for example, around 

the proper permitting program for new and modified sources. EPA reasonably proposes 

to apply the nonattainment permitting programs in areas violating either the 24-hour or 

annual primary standards, but this approach, if the 24-hour designations are not revisited, 

would not guard against the situation where an area is designated attainment for both the 

annual and 24-hour standard even though it is violating the 24-hour standard. This would 

create the untenable situation wherein new sources in the area, governed by the PSD 

program, would be required to show that they will not cause or contribute to a violation 

of a NAAQS that the area is in fact already violating. New 2009-2011 data... identify 

areas that don’t attain current standard yet are officially in attainment.” 

Response: Section 107(d)(1) of the CAA requires the EPA to designate areas no later 

than 2 years following promulgation of a new or revised NAAQS. In the EPA’s final 

rule, the EPA revised the primary annual PM2.5 standard, strengthening it from 15 μg/m3

to 12 μg/m3

; retained the existing 24-hour PM2.5 standard at 35 μg/m3; retained the 
VI-6 

existing 24-hour PM10 (coarse particle) standard at 150 μg/m3; and retained the current 

suite of secondary PM standards. Under section 107(d)(1), the EPA is required to 

designate areas only for the revised primary annual PM2.5 standard. The CAA does not 

require the EPA to designate areas when it retains a standard in every aspect (level, form, 

averaging time and indicator). Therefore, the EPA does not intend to designate areas for 

the retained standards when we designate areas for the revised primary annual PM2.5

standard. Section 107(d)(3) of the CAA provides a separate process for redesignating 

areas and provides the EPA with discretion regarding timing for 

designations/redesignations under section 107(d)(3). The EPA will work with states to 

achieve attainment in the most effective manner, whether this is accomplished through 

section 107(d)(3) or other approaches. 

B. Specific Comments Related to Section 110(a)(2) Infrastructure SIP Requirements 

 In the proposal, the EPA invited preliminary comment on all aspects of infrastructure 

SIPs for the Agency to consider in developing future guidance. As stated in section IX.B of the 

preamble to the final rule, the EPA is currently developing a guidance document on CAA section 

110 infrastructure SIP requirements that will address most infrastructure SIP elements and will 

aim to help states develop SIP submissions for all NAAQS, including the revised PM2.5 NAAQS, 

and the EPA is considering comments received as it develops this guidance. The EPA also may 

issue supplemental infrastructure SIP guidance specific to the revised PM2.5 NAAQS in the 

future if needed. 

 In addition to seeking comment on all aspects of infrastructure SIPs, the EPA sought 

comment specifically on the timing of infrastructure SIP submittals, particularly in light of the 

proposed new secondary standard. The EPA received comments both recommending and 

opposing granting states additional time to submit SIPs for any revised secondary standard, but 

because the Agency is not revising the secondary NAAQS in this rule, the issue of whether or 

not to allow states extra time to submit infrastructure SIPs for the secondary NAAQS is now 

moot. 

(1) Comment: Some commenters emphasized the need for infrastructure guidance no later 

than one year after promulgation of the revised standards. The commenters also stated 

that the EPA's infrastructure guidance should include detailed guidance on how states 

should address the interstate transport obligations in CAA section 110(a)(2)(D), arguing 

that the guidance for the 2006 PM NAAQS indicated that technical analysis would be 

required, but it did not specify how the analysis should be conducted or how the EPA 

would evaluate the analysis. The commenters noted that the issue is further complicated 

by the status of the Clean Air Interstate Rule (CAIR) and the Cross State Air Pollution 

Rule (CSAPR or the “Transport Rule”). 

A few commenters argued that the EPA should not issue guidance on CAA section 110 

infrastructure SIP requirements for a revised PM2.5 NAAQS, claiming that the 

requirements are already stated in the CAA and that EPA guidance would be 

“inappropriately prescriptive.” One of these commenters felt “the EPA should not attempt 

to supplant the states’ and districts’ discretion in applying the basic infrastructure 
VI-7 

requirements. If the EPA determines in the future that nonattainment areas cannot attain 

because of emissions outside of the area in question, out of State, or outside the United 

States, then the EPA can employ any of its statutory powers to address the situation.” 

Response: The EPA believes that issuing non-binding infrastructure SIP guidance is 

appropriate and that it is beneficial to states by helping them to develop plans in a 

nationally consistent manner. The EPA also understands commenters’ concerns about the 

need for timely guidance and intends to issue, in the very near future, a guidance 

document on section 110 infrastructure SIP requirements, which will aim to help states 

develop SIP submissions for all NAAQS, including the revised PM2.5 NAAQS. We 

intend to address most infrastructure SIP requirements in this guidance including the 

interstate transport requirements contained in CAA sections 110(a)(2)(D)(i)(II) and 

110(a)(2)(D)(ii). In addition, the EPA may issue supplemental infrastructure SIP 

guidance specific to the revised PM2.5 NAAQS if needed. 

The EPA does not intend to address in the upcoming infrastructure SIP guidance 

document the interstate transport requirements contained in CAA section 

110(a)(2)(D)(i)(I) – i.e., the requirements related to emissions from one State that 

significantly contribute to nonattainment or interfere with maintenance of the NAAQS in 

another state. The U.S. Court of Appeals for the D.C. Circuit recently issued an opinion 

in EME Homer City Generation v. EPA, 696 F.3d 7 (D.C. Cir.) that is relevant to this 

provision. Among other things the court concluded that “a SIP cannot be deemed to lack 

a required submission or be deemed deficient for failing to implement the good neighbor 

obligation [its obligation under 110(a)(2)(D)i)(I)50] until after EPA has defined the State's 

good neighbor obligation." EME Homer City Generation v. EPA, 696 F.3d 7, 31 (D.C. 

Cir 2012). This decision is not yet final as the mandate in EME Homer has not been 

issued and the EPA has petitioned for rehearing en banc in that case. In the meantime, the 

EPA intends to act in accordance with the holdings in the EME Homer opinion. Unless 

the EME Homer decision is altered, states will not be required to submit SIP revisions 

addressing the requirements in CAA section 110(a)(2)(D)(i)(I) until the EPA further 

defines state obligations pursuant to that section. 

(2) Comment: Some commenters stated that the EPA should allow states the full 3-year 

statutory time period for submitting primary NAAQS infrastructure SIPs. Another 

commenter argued that the submittal deadline for section 110(a)(2)(D) SIPs for interstate 

transport should not be governed by the 3-year submission deadline for infrastructure 

SIPs. 

Response: As noted in section IX.B of the preamble to the final rule, while the CAA 

allows the EPA to set a shorter time than 3 years from the date of promulgation of a 

NAAQS for submission of infrastructure SIPs, the EPA does not currently intend to do 

so. With respect to the second comment, the EPA is without authority to alter, in this rule, 

the SIP submission deadline established in the statute. The EPA has historically 

interpreted section 110(a)(1) of the CAA as establishing the required submittal date for 

 

50 The Court refers to section 110(a)(2)(D)(i)(I) as the “good neighbor provision" and obligations under that 

provision as a state's “good neighbor obligation." EME Homer City, 696 F.3d at 13. 
VI-8 

110(a)(2)(D) interstate transport SIPs, including the provisions in section 

110(a)(2)(D)(i)(I) regarding significant contribution to nonattainment and interference 

with maintenance. However, as noted above, the D.C. Circuit's recent opinion in EME 

Homer, 696 F.3d at 31, concluded that a SIP cannot be deemed to lack a required 

submission under section 110(a)(2)(D)(i)(I) until after the EPA has defined the state's 

good neighbor obligation. Although this decision is not yet final as the mandate in EME 

Homer has not been issued and the EPA has petitioned for rehearing en banc in that case, 

in the meantime EPA intends to act in accordance with the holdings in the EME Homer

opinion. Nothing in the EME Homer opinion, however, affects the state’s obligation to 

submit SIPs addressing the requirements of CAA sections 110(a)(2)(D)(i)(II) and 

110(a)(2)(D)(ii) by the deadline established in CAA section 110(a)(1). 

(3) Comment: Some commenters suggested that the EPA should not require anything more 

than a "traditional infrastructure SIP" to satisfy CAA section 110 requirements for the 

PM2.5 NAAQS, stating that "the EPA has indicated that it will call for only the traditional 

elements of infrastructure SIPs and will not purport to require specific emission control 

strategies as part of infrastructure SIPs." 

Response: The EPA agrees with these commenters and does not intend to require in 

PM2.5 infrastructure SIP submittals any specific emission control strategies for the 

purpose of attaining the standard. Such strategies will be required in nonattainment area 

plans. 

(4) Comment: One commenter supported the EPA’s approach to allow states to make a 

certification that their current infrastructure SIPs are sufficient to implement the revised 

NAAQS. Another group of commenters cautioned that a streamlined certification option 

"may not be available to States that last updated their infrastructure SIPs before the 

applicability of requirements governing condensable particulate emissions and PSD 

permitting elements specific to PM2.5," and further stated that the EPA should identify in 

any future guidance changes in requirements that have become effective since the last 

round of infrastructure SIPs. 

Response: The EPA notes that states may be able to certify that for selected infrastructure 

SIP elements, existing state regulations are sufficient for meeting the new infrastructure 

SIP obligations associated with the revised PM2.5 NAAQS. A SIP submittal in the form 

of a certification should provide citations to the relevant provision already approved by 

the EPA that meet the particular infrastructure SIP element requirements, but it would not 

have to include a paper copy of those provisions. Like any other SIP submittal, such a 

certification should be made and submitted to the EPA only after the state has provided 

reasonable notice and opportunity for public hearing, as required in CAA section 110. 

The EPA agrees that for infrastructure SIPs to be approvable for the revised PM2.5

NAAQS, SIP submissions need to address all infrastructure-related requirements that 

have become applicable since the PM2.5 NAAQS were revised in 2006. The EPA’s 

forthcoming guidance on infrastructure SIPs for all NAAQS, including the revised PM2.5

NAAQS, will include discussion of these requirements. 
VI-9 

C. Specific Comments Related to Implementing the Proposed Revised Primary Annual 

PM2.5 NAAQS in Nonattainment Areas 

As explained in section IX of the preambles to the proposed and final rules, the EPA will 

be undertaking a separate effort to develop and finalize an implementation rule for the revised 

PM2.5 NAAQS through a formal notice-and-comment rulemaking process. To help inform that 

effort, in the PM NAAQS proposal we sought preliminary input from stakeholders on 

implementation issues to update or address in a future implementation rule proposal. The EPA 

received a number of comments related to a variety of implementation issues either specifically 

raised in the proposal or in addition to those raised in the proposal. Topics raised by commenters 

included, but were not limited to, monitoring requirements, treatment of PM2.5 precursors, 

requirements for Reasonable Further Progress (RFP) and Reasonable Available Control 

Technology/Reasonable Available Control Measures (RACT/RACM), and NAAQS 

implementation burden. We are not taking any final actions with regard to these or other 

implementation issues in this final rule. 

We will provide a separate comment period for the submission of comments on the future 

implementation rule proposal. At that time, parties who submitted preliminary implementationrelated comments as part of this rulemaking (to revise the PM NAAQS) may choose to resubmit 

their comments for formal consideration as part of the PM2.5 NAAQS implementation 

rulemaking. Comments received on the PM NAAQS proposed rule will not be considered to be 

comments “submitted in advance” on any future implementation rule proposal. 

1. Transition Period 

The EPA sought preliminary comment in the proposal on the potential concept of a 

transition period during which any changes in monitoring requirements would not affect 

attainment plans and maintenance plans for the 1997 and 2006 PM2.5 NAAQS. The EPA 

received comments in support of and in opposition to such a concept. 

(1) Comment: In support of a transition period for 1997 and 2006 PM2.5 SIPs, one 

commenter argued that attainment demonstrations and redesignation requests for existing 

standards should not be impacted by the revised standards and requirements. Other 

commenters specified that the EPA should provide a 3-year transition period for updating 

attainment plans or maintenance plans for the 1997 and 2006 PM2.5 NAAQS as they may 

relate to any new monitoring requirements. Another commenter stated that EPA will need 

to address outstanding "transition period" issues resulting from changes in the monitoring 

regulations, especially with respect to the effect of this information on designations and 

the collection of pre-and post-construction monitoring for projects. The same commenter 

noted that states should not be obligated to change their SIPs as part of the transition to 

the revised standards in the absence of a SIP call. 

In objecting to the concept of a transition period described in the proposal, a group of 

commenters argued that the EPA cannot ignore valid data if it raises questions about 

assumptions or conclusions of SIPs for the 1997 or 2006 PM2.5 standards. The 

commenters insisted that the CAA “places upon EPA an affirmative duty to ensure that 
VI-10 

SIP revisions will not interfere with any applicable requirement concerning attainment,” 

and that the “EPA should be clear that agencies must consider available data and 

determine, on a case-by-case basis, whether it is relevant and significant to the planning 

decision being made.” 

Response: As explained in section IX.C of the preamble to the final rule, in consideration 

of comments received and upon further analysis of the potential effect of monitoring 

requirement changes, we believe that it will not be necessary to provide for a transition 

period in any future implementation rule because the changes in monitoring requirements 

included in this final PM NAAQS rule would not automatically affect attainment plans 

and maintenance plans for the 1997 or 2006 PM2.5 NAAQS. Specifically, there are 

currently approximately ten PM2.5 air quality monitors that have been identified as not 

comparable to the annual standard as part of the annual state monitoring plan revision 

process. If a state chooses to revise the status of one of these monitors in order to make it 

comparable to the annual standard because it is determined to be representative of many 

other similar locations, it would propose a change in status for that monitor in the next 

revision of the state PM2.5 monitoring plan (state revisions are due in June of each year). 

The EPA would then review and take action on the state's proposed change. The EPA 

believes that the monitoring plan revision process provides adequate procedural steps for 

identifying which monitors are to be comparable to the annual PM2.5 standard. For this 

reason, we believe that there is no need to include any "transition period" in a future rule. 

2. Timing and Development Process for Implementation Rule and Tools 

 The EPA received several comments that raised concerns about the timing of an 

implementation rule or guidance and compliance tools for the revised PM2.5 NAAQS, as well as 

about the development process for an implementation rule. While many of these comments were 

not relevant to the PM NAAQS review itself, we addressed some of these comments in section 

IX.C of the preamble to the final rule, where we reiterated our intentions to develop a separate 

implementation rule through a formal notice-and-comment rulemaking process. 

(1) Comment: Several commenters communicated a need for the EPA to issue an 

implementation rule, either in proposed or final form, simultaneous with the final PM 

NAAQS rule. Some of these commenters insisted that implementation requirements 

should be specified at the time a NAAQS is promulgated, while others stated that the 

EPA should issue the implementation guidance prior to making the new NAAQS 

effective and no later than the date the areas are initially designated. Several state 

commenters noted that a lack of timely implementation guidance can prevent them from 

meeting their own state obligations. Another commenter asked for the EPA to commit to 

firm deadlines rather than target dates for the proposed and finalized implementation rule 

and revised monitoring regulations. The commenter was specifically concerned about 

timely guidance for reasonably available control technology (RACT) and reasonably 

available control measures (RACM) and infrastructure guidance to align with the timing 

of states’ SIP development process. 

Response: As noted in the preamble to the final rule, the EPA acknowledges states’ need 
VI-11 

for timely guidance on how to implement the revised NAAQS. However, due to the 

number of unique and complex issues associated with the PM NAAQS proposal and 

uncertainty about the outcome of the final NAAQS, at this time the EPA is not able to 

propose an implementation rule or finalize any aspect of the implementation program 

beyond a limited set of PSD permitting issues. The EPA intends to address state 

implementation planning issues and requirements through a formal notice-and-comment 

rulemaking process and to finalize a PM2.5 NAAQS implementation rule around the time 

the initial area designations process is finalized. We believe this schedule for proposing 

and finalizing such a rule is timely. With respect to infrastructure guidance, the EPA 

intends to issue, in the very near future, a guidance document on section 110 

infrastructure SIP requirements, which will aim to help states develop SIP submissions 

for all NAAQS, including the revised PM2.5 NAAQS. 

(2) Comment: Several commenters stated that it is critical that the EPA not promulgate 

NAAQS prior to the development of tools and techniques suitable for states and regulated 

entities to use for implementation. 

Response: The EPA notes that fine particle standards have been implemented by states 

and regulated entities for a number of years already and there are a number of technical 

tools in place already to facilitate the implementation of a newly revised PM2.5 standard. 

These tools (such as air quality models, emission factors, and emission inventories) 

continue to be updated and refined over time. 

(3) Comment: A few commenters urged the EPA to consult with stakeholders, particularly 

with states and local agencies, prior to developing any rules or guidance for the revised 

NAAQS and throughout the process. 

Response: As stated in the preamble to the final rule, the EPA agrees that it is beneficial 

to engage with air agencies early in the rule development process. We have initiated such 

discussions to help inform the development of an upcoming proposed implementation 

rule, and expect to have additional such discussions during 2013. 

D. Specific Comments on Prevention of Significant Deterioration and Nonattainment 

New Source Review 

This section responds to comments received on the PSD and Nonattainment NSR 

(NNSR) programs and potential impacts associated with the revised PM NAAQS. Several of 

these comments are addressed in detail in section IX.D of the preamble to the final rule, and in 

those cases, the reader is referred to the appropriate subsection(s) of the preamble for the EPA’s 

responses. Responses to comments not specifically addressed in the preamble to the final rule are 

provided below. 

As a general matter, we note that, with the exception of the PSD grandfathering 

provisions, the EPA is not taking final action to address NSR implementation in this NAAQS 

package. Nevertheless, we did receive several comments raising NSR implementation issues, 

some of which argued that particular issues may be of greater concern under the revised 
VI-12 

NAAQS. Some comments further suggested changes to NSR policy or rules—beyond the 

grandfathering provision—to alleviate these concerns. This section provides responses to those 

issues by describing, as appropriate, current and future EPA efforts to facilitate NSR 

implementation for the PM2.5 NAAQS. The responses generally indicate that the EPA is 

committed to working with air agencies and other stakeholders to address these issues in the 

appropriate forum (which could include rulemaking, guidance, or case-by-case determinations). 

Thus, again with the exception of grandfathering, our responses here do not reflect final 

decisions by the agency on these issues but instead are provided for informational purposes only. 

In addition, we note that while the particular implementation issues raised or the burden 

associated with them will receive further consideration by the Agency as noted above, they are 

not relevant to the decisions made on revisions to the NAAQS, including establishing the level of 

the standard. 

1. Prevention of Significant Deterioration 

a. Transition Provision (Grandfathering) 

(1) Comment: 

 The majority of commenters, including all industry and state agency representatives, 

supported the EPA’s proposed grandfathering provision based on the purpose and 

rationale described in the preamble to the proposal. These commenters agreed that 

grandfathering certain pending PSD permit applications was reasonable to balance the 

CAA objectives to protect the NAAQS on one hand, and to avoid delays in 

processing PSD permit application on the other. They also agreed grandfathering 

provides a reasonable transition into the PSD requirements associated with the 

revised NAAQS. Industry commenters also indicated that such a provision was 

important to economic growth and recovery, and was consistent with the purposes of 

the PSD program, i.e., to ensure that economic growth will occur in a manner 

consistent with preservation of air quality. Several state commenters pointed out that 

finalizing the revised PM2.5 NAAQS without a grandfathering provision would result 

in a significant additional resource burden on both permit applicants and air agencies, 

which would have to reopen pending permit applications that have reached advanced 

stages in processing to address the revised standard. The commenters further noted 

that there would likely be little if any environmental benefit afforded by such a 

process. One state agency commenter performed a preliminary review of recent PSD 

permitting actions and determined that in all cases, the proposed primary annual 

PM2.5 standard would not have led to tighter permit restrictions or reduced emissions, 

and that a re-noticing of the preliminary permit decisions would accomplish nothing 

more than to change the margins of compliance. In other words, re-noticing would 

have led to project delays with no reduction in PM2.5 impacts. 

 Four environmental group commenters (one representing a coalition of a health 

advocacy group and several environmental groups) opposed the proposed 

grandfathering provision based either on concerns about further delay in 

implementation of the revised PM NAAQS or on a position that the proposed 

grandfathering provision exceeds the EPA’s statutory authority and is unlawful. 

Commenters challenging EPA’s legal authority to implement the proposed 
VI-13 

grandfathering provision contended that CAA sections 165 and 301 do not confer any 

authority on the EPA to grandfather PSD permit applications. The commenters 

asserted that CAA section 165(a) forecloses the EPA’s proposed approach, 

specifically citing CAA section 165(a)(3)(B) which provides that no major emitting 

facility “may be constructed” unless the facility’s owner or operator demonstrates 

emissions from the facility will not cause or contribute to the violation of “any . . . 

national ambient air quality standard in any air quality control region.” These 

commenters further claimed that because Congress limited the applicability of the 

new PSD requirements in several ways, including specific grandfathering relief for 

sources constructed before the enactment of the 1977 Amendments to the CAA, the 

EPA is not authorized to waive otherwise applicable statutory requirements (citing 

Andrus v. Glover Constr. Co., 446 U.S 608, 116-17 (1980)). A subset of these same 

commenters also stated that the EPA’s proposed grandfathering approach undermines 

the policy choices made by Congress in adopting the PSD program that 1) it is 

preferable to prevent air pollution from becoming a problem in the first place, and 2) 

controls should be installed when new sources are being constructed rather than as 

retrofits on existing sources. 

One commenter asserted that there is no conflict between CAA sections 165(a) and 

165(c) as the EPA had implied; therefore, there is no need for the EPA to invoke the 

regulatory authority of CAA section 301. This commenter also concluded that the 

EPA’s rationale of balancing of economic growth and the protection of air quality 

pursuant to CAA section 160(3) was unlawful, and that the EPA had not adequately 

explained the considerations it sought to balance and how the proposal would achieve 

its goals. The same commenter questioned the EPA’s authority to leverage principles 

of equity and fairness in proposing the grandfathering provision. The commenter also 

objected to the EPA’s rationale for choosing the public notice date of a draft permit as 

the milestone triggering the grandfathering provision, stating that the approach was 

contrary to statute because it would deprive interested persons of their statutory right 

to comment on elements of the application related to the current NAAQS. 

 Regarding the need for a sunset clause for the grandfathering provision, the majority 

of commenters supported, as proposed, not including such a clause, and no 

commenters specifically recommended that a sunset clause be established. 

Commenters pointed out that permit applicants and reviewing authorities already 

have strong incentives to issue final permits in a timely manner following the public 

notice stage, and that a sunset clause would not add any meaningful incentive to 

expedite the permitting process, rather potentially causing additional delays. One 

commenter stated that permitting authorities have ample discretion, which they 

routinely use, to refuse to issue a draft permit if additional information is requested 

during a comment period or the agency itself wants additional information following 

publication of a draft permit or preliminary determination. The same commenter 

indicated that permitting authorities also have sufficient discretion to reopen permit 

proceedings if they consider information in an application to be stale. 
VI-14 

 Several of the commenters supporting the proposed grandfathering provision in 

general recommended that the EPA establish the grandfathering milestone as the date 

that a complete permit application is submitted (or that a submitted permit application 

is deemed complete by the reviewing agency) rather than the publication date of 

public notice for a draft permit or preliminary determination as proposed. These 

commenters pointed out the significant level of effort, resources and time involved in 

preparing all of the information necessary for a complete permit application, 

including a BACT analysis, air quality analysis, additional impacts analyses, and a 

Class I area impact analysis. They claimed that it would be unfair to establish a 

grandfathering milestone past the complete application date because the processes 

and timeframes involved in generating the draft permit or preliminary determination 

materials and publishing the public notice are largely out of the control of the permit 

applicant and vary from agency to agency. They further stated that requiring 

reevaluation of a proposed project to assess impacts with respect to the revised 

NAAQS after a permit application has been deemed complete would result in 

significant additional cost and delay. Several such commenters cited prior EPA 

grandfathering provisions that relied upon that milestone, including the 1987 PM10

NAAQS (52 FR 24672, July 1, 1987) and the 1988 NO2 increments (53 FR 40656, 

October 17, 1998), and contended that the EPA had not justified the use of an 

alternative date for purposes of the proposed revisions to the PM2.5 NAAQS. Some 

state commenters also indicated that the proposed draft permit public notice date 

milestone could result in additional resource burden on the agency to expedite 

completion of draft permit packages and process public notices. Other state 

commenters supported the EPA’s proposed draft permit or preliminary determination 

public notice date as the appropriate grandfathering eligibility milestone, indicating 

that this approach would provide states and industry certainty on the NAAQS 

demonstration required during the PM2.5 NAAQS transition period. 

 A few industry commenters suggested, as an alternative to the proposed approach, 

that the EPA should effectively grandfather PSD permit actions from meeting 

requirements associated with the revised PM NAAQS by extending the effective date 

of the NAAQS by one year. 

Response: The EPA has provided detailed responses to these comments in section 

IX.D.1.a.ii of the final rule preamble. 

(2) Comment: One local government and one industry commenter suggested that the EPA 

should extend grandfathering to non-PSD permits, e.g., minor source permits and 

synthetic minor permits. 

Response: The commenters did not demonstrate the need for grandfathering of minor 

NSR permits nor did they provide any other supporting rationale for such grandfathering. 

The EPA did not propose, and is not finalizing, any grandfathering provisions for minor 

NSR permit applications. 
VI-15 

(3) Comment: One state agency commenter suggested that the grandfathering provision be 

consistent with the EGU GHG NSPS rule. 

Response: The proposed EGU GHG NSPS (“Standards of Performance for Greenhouse 

Gas Emissions for New Stationary Sources: Electric Utility Generating Units,” 77 FR 

22392, April 13, 2012) proposed requirements for any electricity generating unit (EGU) 

that meets the definition of an “affected facility.” Under CAA section 111(a)(2), any 

source that is covered by a proposed NSPS and that commences construction after the 

date of the proposal must meet the requirements of the NSPS that EPA finalizes. 

However, in this proposal, EPA made clear that certain types of sources would not be 

treated as “affected facilit[ies],” including “transitional sources.” A “transitional source” 

was defined as, in general, an EGU that had received a complete PSD permit prior to 

April 13, 2012, and that commences construction within 12 months after the April 13, 

2012, date of the proposal. Therefore, under this proposal, a source that qualifies as a 

“transitional source” would not be subject to the requirements of the NSPS when the rule 

is finalized. Although the comment is not specific, apparently it is this “transitional 

source” provision that the comment considers to be the grandfathering provision. 

As stated in Section IX.D.1.a.i of the preamble to the final rule, longstanding EPA policy 

interprets the CAA and EPA regulations at 40 CFR 52.21(k)(1) and 51.166(k)(1) to 

generally require that PSD permit applications include a demonstration that new major 

stationary sources and major modifications will not cause or contribute to a violation of 

any NAAQS that is in effect as of the date the PSD permit is issued (Page, 2010a; Seitz, 

1997). Accordingly, a source that has received a final PSD permit prior to the effective 

date of the final NAAQS would not be required to meet any new requirements associated 

with the revised standards regardless of the scope of the grandfathering provision 

finalized in this rule. In this sense, this longstanding EPA policy already is consistent 

with the proposed “transitional source” provision because under the latter, sources with 

PSD permits prior to the date of proposal (and that commence construction within one 

year after proposal) would not be subject to the final NSPS requirements. Accordingly, 

there is no need to make the grandfathering provision in this rule consistent with the 

“transitional source” provision in the proposed EGU GHG NSPS. 

b. Surrogacy Approach for Proposed Secondary Visibility Index NAAQS 

The EPA received a large number of comments on the proposed implementation of a 

surrogacy approach for addressing PSD requirements associated with the proposed distinct 

secondary visibility index NAAQS. As described in section VI of the final rule, the EPA is not 

finalizing a distinct secondary visibility index standard at this time and therefore the proposed 

surrogacy approach for implementing such a standard under the PSD program is unnecessary. 

Accordingly, the EPA is not responding to comments on the proposed surrogacy approach for 

the proposed secondary visibility index NAAQS here. Comments received on the proposed 

surrogacy approach and associated technical memorandum that are relevant to the EPA’s final 

decision not to establish a distinct secondary visibility NAAQS at this time are addressed in 

section VI.D.2 of the final rule preamble and section IV of this response to comments document. 
VI-16 

c. Modeling Tools and Guidance Applicable to the Revised Primary Annual PM2.5 NAAQS 

(1) Comment: Several industry commenters identified a generally common suite of issues 

and limitations associated with currently available modeling tools and guidance for 

performing required PSD air quality impact analyses for PM2.5 (i.e., the requirement that 

PSD permit applicants demonstrate that source emissions will not cause or contribute to a 

violation of the PM2.5 NAAQS). These commenters stated that the current regulatory air 

quality model, AERMOD, is unable to predict the impact of a single source on ambient 

PM2.5 concentrations, including secondary particle formation from PM2.5 precursors. 

They further stated that the EPA has yet to provide adequate guidance on how applicants 

are to address the PSD air quality demonstration requirements for the current PM2.5

NAAQS. Many of these commenters also contended that current modeling tools and 

guidance result in over-predictions and/or overly conservative estimates of impacts, and 

that this, in combination with lower NAAQS levels, would result in project delays and 

adverse impacts on the economy. Commenters speaking to the same issue referred to a 

“narrow window” for source-related impacts under the proposed revised PM2.5 NAAQS. 

Many of these commenters indicated that the EPA should resolve the identified PM2.5

modeling issues prior to finalizing the PM2.5 NAAQS, and do so through notice-andcomment rulemaking. One industry commenter stated the EPA should not require point 

source modeling of PM2.5 until the Agency has an effective modeling tool available. 

Response: To address PSD air quality demonstration requirements for current PM2.5

NAAQS, EPA issued, on March 23, 2010, a guidance memorandum entitled “Model 

Procedures for Demonstrating Compliance with PM2.5 NAAQS” (Page, 2010b) that 

recommended certain interim procedures to address compliance with the PM2.5 NAAQS 

and acknowledged that there are technical complications associated with the ability of 

existing models to estimate the impacts of secondarily formed PM2.5 in the atmosphere 

resulting from emissions of PM2.5 precursors. The EPA is currently preparing draft PM2.5

permit modeling guidance that recommends appropriate technical approaches for 

conducting a PM2.5 NAAQS compliance demonstration that includes the use of the 

AERMOD modeling system to account for impacts of directly emitted PM2.5 and a more 

adequate accounting for contributions from secondary formation of ambient PM2.5

concentrations resulting from a proposed new or modified source’s precursor emissions. 

This draft PM2.5 permit modeling guidance is necessary to inform case-by-case 

determination of appropriate methods as sources should now conduct a PM2.5-based 

analysis under NSR and PSD to demonstrate compliance with the PM2.5 NAAQS rather 

than relying upon a PM10-based analysis in accordance with past EPA guidance. (76 FR 

28646, 28648, 28659 (May 18, 2011); Page, 2010b). The EPA expects that technical 

issues related to the PSD compliance demonstration will be resolved during the 

consultation process with the EPA’s regional offices pursuant to section 5.2.2.1.c so that 

the most appropriate analytical techniques can be used on a case-by-case basis to address 

the impacts of individual sources on secondary PM2.5 formation. 

The EPA has provided presentations regarding the draft guidance at the 10th Conference 

on Air Quality Models in March 2012 and at the Regional/State/Local Modelers 

Workshop in May 2012 which are available at: 
VI-17 

http://www.epa.gov/ttn/scram/conferenceindex.htm. The EPA intends to provide this 

draft guidance for public review and comment soon after final rule signature, no later 

than end of calendar year, with the intent of issuing final guidance in Spring 2013. This 

guidance extends the guidance from the previous March 23, 2010 memo and takes into 

account specific recommendations from the NACAA PM2.5 Modeling Implementation 

Workgroup, public comments received from the 10th Modeling Conference, and our caseby-case involvement with recent applicant-submitted PM2.5 compliance demonstrations. 

(2) Comment: One industry trade association commenter provided detailed comments on 

implementation issues for PM2.5 modeling including a review of existing models, 

including AERMOD and CALPUFF, and pointed out specific characteristics and 

limitations associated with those models. In summary, the commenter stated that there 

was a critical need for EPA modeling tools to evaluate secondary PM2.5 impacts, and that 

the EPA should develop a research plan, including funding requirements, for addressing 

model development. The commenter also stated that the “EPA cannot proceed with 

modeling implementation of the PM2.5 NAAQS until field studies with speciated PM2.5

observations focused upon a single source are available and used in evaluation of new 

state-of-the-science models.” 

Response: The EPA acknowledges the need to conduct a thorough review and evaluation 

of existing and developing models and modeling techniques to address the complexities 

of accounting for PM2.5 impacts from single sources. As part of the 10th Modeling 

Conference in March 2012, the EPA dedicated a session to this issue of emerging models 

and techniques with detailed presentations on the current state of the science which 

included model evaluations with available field study data (see presentations at 

http://www.epa.gov/ttn/scram/10thmodconfpres.htm). The EPA sponsored a similar 

session at the 11th Annual CMAS Conference in October 2012 where additional model 

developments and evaluations were presented (See presentations from afternoon of 

October 16th at: http://www.cmascenter.org/conference/2012/agenda.cfm). The EPA will 

continue engaging with the modeling community on the evaluation of current models and 

modeling techniques as part of its commitment to engage in rulemaking to update 

Appendix W and, as appropriate, incorporate new analytical techniques or models for 

secondary PM2.5 impacts from single sources. 

In terms of current compliance demonstrations under PM2.5 NAAQS, as noted in the 

previous comment response, the EPA is preparing draft PM2.5 permit modeling guidance 

that will provide recommendations on appropriate technical approaches for conducting a 

PM2.5 NAAQS compliance demonstration for a proposed new major stationary source or 

major modifications. This draft PM2.5 permit modeling guidance is necessary to inform 

case-by-case determination of appropriate methods as sources should now conduct a 

PM2.5-based analysis under NSR and PSD to demonstrate compliance with the PM2.5 

NAAQS rather than relying upon a PM10-based analysis in accordance with past EPA 

guidance. (76 FR 28646, 28648, 28659 (May 18, 2011); Page, 2010b). The EPA expects 

that technical issues related to the PSD compliance demonstration will be resolved during 

the consultation process with the EPA’s regional offices pursuant to section 5.2.2.1.c so 

that the most appropriate analytical techniques can be used on a case-by-case basis to 
VI-18 

address the impacts of individual sources on secondary PM2.5 formation. 

(3) Comment: One industry commenter made several specific suggestions to improve model 

accuracy. The commenter suggested that model inputs should be adjusted by: 1) not 

assuming simultaneous maximum allowable emissions when a reasonable worst case 

actual emissions scenario is available, and 2) eliminating the inputs for non-stack sources 

(e.g., haul roads, pits, roof monitors) until adequate studies of source-specific test data is 

conducted to establish a discount factor to offset over-prediction bias in the model results. 

The commenter suggested that model outputs should be refined by 1) eliminating 

downwash assumptions during low wind speed events that are contrary to the observed 

plume rise under these meteorological conditions, and 2) foregoing the modeling of 

secondary formation of PM2.5 until there is a clear understanding of when and where it 

will affect ambient air quality. The commenter also stated that the EPA should 

“encourage the use of available monitored data to ’ground truth’ the air model results 

and, where appropriate, use the monitor data to establish calibration factors for adjusting 

the model results.” 

Response: The EPA will be addressing the commenter suggestions as part of its response 

to comments from the at the 10th Conference on Air Quality Models and, as appropriate, 

will consider updates to current modeling requirements for PSD compliance 

demonstrations as part of future rulemaking to revise EPA’s Guideline on Air Quality 

Models (published as Appendix W of 40 CFR Part 51). 

(4) Comment: One industry coalition commenter suggested that the EPA’s pending revised 

PM2.5 modeling guidance be co-proposed as a draft for public comment with the final PM 

NAAQS rulemaking. This commenter also suggested that until the new guidance can be 

finalized, the final rule should indicate that “the 2010 Guidance be used judiciously for 

general directions and that air quality planning and permitting authorities can deviate 

from the 2010 guidance based on their professional judgment.”. The commenter 

requested that the EPA remind air agencies in the final PM NAAQS rulemaking that 

“Section 10 of Appendix W allows for the placement of post-construction monitors in 

lieu of modeling to collect emissions information where modeling suggests future 

nonattainment issues, particularly in view of the inadequacy of current PM2.5 modeling 

techniques and the stringency of the current and the proposed new PM2.5 NAAQS.” 

Response: As noted in previous comment response, the EPA is currently preparing draft 

PM2.5 permit modeling guidance that recommends appropriate technical approaches for 

conducting a PM2.5 NAAQS compliance demonstration. This draft PM2.5 permit 

modeling guidance is necessary to inform case-by-case determination of appropriate 

methods as sources should now conduct a PM2.5-based analysis under NSR and PSD to 

demonstrate compliance with the PM2.5 NAAQS rather than relying upon a PM10-based 

analysis in accordance with past EPA guidance. (76 FR 28646, 28648, 28659 (May 18, 

2011); Page, 2010b). The EPA expects that technical issues related to the PSD 

compliance demonstration will be resolved during the consultation process with the 

EPA’s regional offices pursuant to section 5.2.2.1.c so that the most appropriate 

analytical techniques can be used on a case-by-case basis to address the impacts of 
VI-19 

individual sources on secondary PM2.5 formation. 

EPA will continue to remind air agencies of the applicability of Section 10 of Appendix 

W that allows for monitoring in lieu of modeling to demonstrate compliance under PSD 

for those situations where it has been determined in consultation with the appropriate 

reviewing authority that the modeling techniques are not appropriate for use. It is 

important to note that the commenter mischaracterizes this guidance as “placement of 

post-construction monitors” conceivably in the case of a new source, but the applicability 

of Section 10 is only in the case of an existing source, where monitoring data could be 

used in a NAAQS assessment following the recommendations in that guidance. 

(5) Comment: One state agency commenter raised a concern that the EPA appeared to be 

planning to make substantive changes to the PSD modeling requirements through 

guidance instead of through rulemaking, without the opportunity for public comment. 

The commenter further stated that any substantive changes to PM2.5 modeling, including 

any substantive changes to how secondary formation of PM2.5 is handled for PSD 

purposes, should be done thorough public notice and comment rulemaking (referring to 

40 CFR 52.21, 51.166 and Appendix W). 

Response: The EPA is currently preparing draft PM2.5 permit modeling guidance that 

recommends appropriate technical approaches for conducting a PM2.5 NAAQS 

compliance demonstration that includes the use of the AERMOD modeling system to 

account for impacts of directly emitted PM2.5 and a more adequate accounting for 

contributions from secondary formation of ambient PM2.5 concentrations resulting from a 

proposed new or modified source’s precursor emissions. This draft PM2.5 permit 

modeling guidance is necessary to inform case-by-case determination of appropriate 

methods as sources should now conduct a PM2.5-based analysis under NSR and PSD to 

demonstrate compliance with the PM2.5 NAAQS rather than relying upon a PM10-based 

analysis in accordance with past EPA guidance. (76 FR 28646, 28648, 28659 (May 18, 

2011); Page, 2010b). The EPA expects that technical issues related to the PSD 

compliance demonstration will be resolved during the consultation process with the 

EPA’s regional offices pursuant to section 5.2.2.1.c so that the most appropriate 

analytical techniques can be used on a case-by-case basis to address the impacts of 

individual sources on secondary PM2.5 formation. This guidance extends the previous 

March 23, 2010, memo and takes into account specific recommendations from the 

NACAA PM2.5 Modeling Implementation Workgroup, public comments received from 

the 10th Modeling Conference, and our case-by-case involvement with recent applicant 

submitted PM2.5 compliance demonstrations. The EPA intends to provide this draft 

guidance for public review and comment soon after final rule signature, no later than the 

end of calendar year 2012, with the intent of issuing final guidance in Spring 2013. 

(6) Comment: Three industry commenters, in support of their position that current PM 

models over-predict impacts, cited the adoption of section 234 of the CAA and the EPA’s 

recognition of these concerns in communications with Wyoming in which the EPA 

allowed some areas to demonstrate PM10 NAAQS compliance by us of extensive 

monitoring rather than inaccurate fugitive dust models (citing Proposed Approval of 
VI-20 

Wyoming SIP, 57 FR 38641, 38646-48, August 26, 1992). These commenters also stated 

that modeling tools and guidance should be developed through an open process with peer 

review opportunities to improve the data relied upon in regulatory decisions. Two of 

these commenters encouraged the EPA adopting modeling changes consistent with the 

NMA’s comments regarding the 10th Modeling conference (NMA, 2012). One state 

agency commenter indicated that the agency did not require short-term fugitive PM 

modeling, and that that approach was affirmed in Sierra Club v. Wyo. Dept. of Envl. 

Quality, 2011 WY42, 251 P.3d 310 (Wyo. 2011). The same commenter referenced that the 

AERMOD Implementation Guide acknowledges that the model has shortcomings and 

may overestimate area source concentrations. 

Response: The EPA will be addressing the commenters’ suggestions as part of its 

response to comments from the 10th Conference on Air Quality Models and, as 

appropriate, will consider updates to current modeling requirements for PSD compliance 

demonstrations as part of future rulemaking to revise the EPA’s Guideline on Air Quality 

Models (published as Appendix W of 40 CFR Part 51). 

(7) Comment: One industry coalition commenter identified that current modeling tools are 

not appropriate to address fugitive PM emissions, and that industry has already provided 

the EPA with a short-term fix to this problem called an “emissions pre-processing step.” 

As described, the pre-processing step reduces emission factors for fugitive emissions 

sources to account for inadequacies in the model. The commenter stated that EPA is 

already using a pre-processing step in regional modeling, and recommended that the EPA 

extend the approach to point-source modeling, indicating that this approach would 

improve PM modeling and reduce some implementation burden. The commenter also 

stated that it would be willing to “bring resources to the table to help EPA find a longterm solution and verify that solutions effectiveness.” 

Response: The EPA will be addressing the commenters’ suggestions as part of its 

response to comments from the 10th Conference on Air Quality Models and, as 

appropriate, will consider updates to current modeling requirements for PSD compliance 

demonstrations as part of future rulemaking to revise the EPA’s Guideline on Air Quality 

Models (published as Appendix W of 40 CFR Part 51). 

d. PSD Screening Tools: Significant Emissions Rates, Significant Impact Levels, and 

Significant Monitoring Concentration 

(1) Comment: The EPA received several comments from industry and state agencies 

regarding the existing PSD screening tools and the potential need to adjust associated 

values based on the revised primary annual PM2.5 NAAQS. The majority of these 

commenters supported retaining the existing SERs, SILs and SMC for PM2.5 (and PM2.5

precursors in the case of the SERs), indicating that there was no compelling technical 

reason for revision based on the proposed revision to the primary PM2.5 NAAQS. One 

industry commenter indicated that there might be a need to revise the annual PM2.5 SILs 

based on the approach used in establishing the current value. However, this commenter 

and others recommended that any revisions to the PSD screening levels for PM2.5 be 
VI-21 

accomplished through a separate notice-and-comment rulemaking. Several state 

commenters that supported retention of the current PM2.5 SILs also urged the EPA to 

provide guidance on the use of those existing SILs. 

Response: As described in section IX.D.1.c of the final rule preamble, the EPA did not 

propose to make and is not finalizing any changes to the existing PM2.5 SERs, SILs and 

SMC as part of the final rule. The EPA intends to consider the need for any future 

changes to these values in light of today’s revision of the primary annual PM2.5 NAAQS 

and considering public comments received. The EPA will address any changes to the 

PM2.5 SERs, SILs and SMC in a subsequent PSD implementation rulemaking if deemed 

necessary or appropriate. The EPA will determine the need for, and develop such 

rulemaking expeditiously, and any such forthcoming rulemaking will provide an 

additional opportunity for public comment on specific proposed revisions to the PSD 

screening tool values for PM2.5. Until any rulemaking to amend existing regulations is 

completed, permitting decisions should continue to be based on the SERs for PM2.5 (and 

its precursors) and the SILs and SMC for PM2.5 in existing regulations. 

(2) Comment: One set of collaborative comments from health and environmental advocacy 

groups stated that the EPA’s proposal to leave in place the PSD screening tools adopted 

with the previous PM NAAQS had no rational basis and was contrary to statutory 

requirements. Referring the SILs and SMCs, these commenters contended that the EPA 

has no legal authority to create such de minimis exemptions in the PSD program and that 

even if EPA could adopt such exemptions, to leave in place exemptions based on PM 

NAAQS promulgated at higher levels has no technical basis. The commenters further 

stated that the EPA has offered no evidence that sources with impacts below the proposed 

SILs or SMCs will never cause or contribute to violations of NAAQS or increments, or 

that the gain from regulating such sources would be trivial, and that the EPA’s proposal 

to leave the preexisting exemptions in place is unreasonable given that the analysis 

supporting those exemptions was tied to a specific standards that EPA has now found 

inadequate to protect public health and welfare. Further, the commenters contended that a 

single national number that defines “trivial” impact for all attainment areas is 

fundamentally flawed, given that even a very small impact can be of great significance in 

an area that is very close to exceeding an increment or a NAAQS. Finally, these 

commenters stated that the EPA must reassess its SERs, because the SERs cannot be 

disconnected from the level of the NAAQS and the EPA must provide a rational basis for 

concluding that the existing SERs continue to be appropriate. One additional set of 

collaborative comments from academic researchers also supported reconsideration, and 

possible lowering of the PSD screening levels, citing, in the context of the SERs, the fact 

that there is no safe threshold and a linear dose response curve for PM2.5. These same 

commuters recommended that the EPA consider screening levels for other indicators, 

including ultra fine and nano PM and that those indicators be established based on 

particle number instead of mass to account for surface area and volume. 

Response: As described in section IX.D.1.c of the final rule preamble and in the response 

to comment VI.C.1.d. (1) above, the EPA did not propose to make and is not finalizing 

any changes to the existing PM2.5 SERs, SILs and SMC as part of the final rule. The EPA 
VI-22 

intends to consider the need for any future changes to these values in light of today’s 

revision of the primary annual PM2.5 NAAQS and considering public comments received. 

The EPA will address any changes to the PM2.5 SERs, SILs and SMC in a subsequent 

PSD implementation rulemaking if deemed necessary or appropriate. The EPA will 

determine the need for, and develop such rulemaking expeditiously, and any such 

forthcoming rulemaking will provide an additional opportunity for public comment on 

specific proposed revisions to the PSD screening tool values for PM2.5. 

The commenters’ claims that the de minimis nature of the SILs and SMCs are 

unsubstantiated and that the EPA has no statutory authority to establish SILs and SMC 

for PM2.5 are the subject of current litigation in Sierra Club v. EPA, No. 10-1413 (D.C. 

Cir. filed Dec. 17, 2010). The EPA’s argument in support of the existing PSD screening 

tools is contained in a brief filed in that case, which is included in the docket for the final 

rule. Id., Brief of Respondent at 26-56 (June 26, 2012). 

e. PSD Increments 

(1) Comment: The EPA received few comments on whether there was any need or 

justification to revise the existing PSD increments for PM2.5. Industry and state agency 

commenters generally supported retaining the existing increments. One industry 

commenter indicated that there may be a need to reevaluate the annual PM2.5 increment. 

Commenters again recommended that any revisions to the PSD increments for PM2.5 be 

accomplished through a separate notice-and-comment rulemaking. 

Response: As described in section IX.D.1.d of the final rule preamble, the EPA did not 

propose to make and is not finalizing any changes to the existing PSD increments for 

PM2.5 as part of the final rule. The EPA will consider whether it is appropriate to propose 

any revised PSD increments for PM2.5 in the future. Any such forthcoming rulemaking 

will provide an additional opportunity for public comment on specific proposed revisions 

to the PSD increments for PM2.5. Until any rulemaking to amend existing regulations is 

completed, permitting decisions should continue to be based on the PSD increments for 

PM2.5 in existing regulations. 

f. Other PSD Transition Issues 

(1) Comment: Several industry commenters expressed concern that a permitting problem 

would result from the fact that, upon promulgation of the revised PM2.5 NAAQS, ambient 

air quality monitoring data would show that for some areas, PM2.5 concentrations exceed 

the revised NAAQS, although those areas would not be formally designated as 

“nonattainment” until a later date pursuant to the designations process provided by the 

CAA. The commenters noted that sources locating in such areas would be required to 

obtain a PSD permit in order to construct or modify, but could not do so because the 

requirement that the new or modified source must demonstrate that it will not cause or 

contribute to a NAAQS violation, even though the area would technically already be in 

nonattainment. The commenters further noted that once the nonattainment designation is 

made, section 173 of the CAA provides a nonattainment area permit program that 

specifies conditions under which a permit will be issued, including obtaining offsetting 
VI-23 

reductions in emissions rather than demonstrating through modeling or other analysis that 

the source will not cause or contribute to a violation of the NAAQS as required in PSD. 

Thus, the commenters urged the EPA to offer an interim approach that would avoid the 

imposition of an effective construction ban on such areas until such time as the 

nonattainment area designations and the nonattainment NSR offset requirements are in 

place instead of the PSD requirements. Some of the commenters specifically requested 

that the EPA provide either a surrogacy approach based on showing compliance with the 

pre-existing annual PM2.5 NAAQS or a PSD offset approach to avoid a construction 

moratorium in such areas. 

Response: The EPA has provided a detailed response to these comments in section 

IX.D.1.e of the final rule preamble. 

(2) Comment: One state agency commenter objected to the EPA’s policy that the state must 

implement a permitting requirement that has not yet been adopted into the SIP, stating 

that the EPA should not burden SIP-approved states with the requirement to immediately 

develop permitting procedures to demonstrate compliance with a new NAAQS. The 

commenter recommended that the EPA promulgate in rule a phase-in period that would 

require the demonstration after implementation guidance and tools (including singlesource models) are available. 

Response: As stated in section IX.D.1.a.i of the preamble to the final rule, longstanding 

EPA policy interprets the CAA and EPA regulations at 40 CFR 52.21(k)(1) and 

51.166(k)(1) to generally require that PSD permit applications include a demonstration 

that new major stationary sources and major modifications will not cause or contribute to 

a violation of any NAAQS that is in effect as of the date the PSD permit is issued (Page, 

2010a; Seitz, 1997). As described in section IX.D.1.a.iii of the preamble to the final rule, 

the EPA is finalizing a grandfathering provision under the PSD regulations that is 

designed to help provide a workable transition to implementing the revised PM2.5

NAAQS under the PSD permitting program. The CAA does not authorize the type of 

additional phase-in period recommended by the commenter. Furthermore, the commenter 

did not provide any substantive supporting basis for the need for such a phase-in period. 

The final rule establishes a revised level of the primary annual PM2.5 NAAQS. Permitting 

procedures and tools should already be in place for the previously existing primary 

annual PM2.5 NAAQS, and these same procedures and tools are applicable to the revised 

standard. Response to comments on modeling tools and guidance are provided in section 

VI.C.1.c of this document. 

(3) Comment: One industry coalition commenter, in support of a general comment that NSR 

solutions are needed to resolve the difficulty in obtaining NSR permits for PM2.5

emissions, provided some specific suggestions. They suggested that the EPA should 

explore the voluntary use of PM2.5 “offsets” as an alternative to air quality demonstration 

requirements under the current regulations. They asked that the EPA explore whether 

offsets can be utilized in attainment or unclassified areas to reduce the burden of ambient 

air impact analyses. They also requested that the EPA “address the ability for source 

operators in attainment areas to buy NOX or SO2 credits from cap-and-trade participants 
VI-24 

in affected states/regions in addition to traditional offsets representing sources that are 

deactivated at the time a new ‘source’ starts up.” They suggested another potential 

mechanism which was to “‘tier’ requirements post construction to levels of actual 

emissions from a new project.” Finally, the commenter requested that the EPA “affirm in 

the final rulemaking the use of the existing provisions in Appendix W and Section 10 for 

the use of ‘post-construction’ monitoring where models may predict certain future air 

quality impacts from a project.” 

Response: The commenter presented several alternative means of addressing the alleged 

problem of obtaining a PSD permit where a source’s modeled impact would show the 

source would cause or contribute to a violation of the PM2.5 NAAQS. With regard to the 

commenter’s recommendation that the EPA explore the voluntary use of PM2.5 offsets as 

an alternative to an air quality demonstration under the current PSD regulations, we point 

the commenter to our response to comment f.1, above, which is contained in section 

IX.D.1.e of the final rule preamble. In brief, we believe that the offsets option is already 

available to proposed new major stationary sources and major modifications whose 

emissions are shown to cause or contribute to violation of any NAAQS. 

The commenter’s second recommended alternative is to allow a source to “buy NOX or 

SO2 credits from cap and trade participants in affected states/regions.” The EPA places 

the same criteria on offsets obtained for PSD purposes as are required under the Act for 

nonattainment areas. Accordingly, any emissions reduction, in order to be creditable as 

an emissions offset, must be surplus, permanent, quantifiable and federally enforceable. 

To the extent that credits purchased from a cap and trade participant meet the required 

creditability criteria, then we believe they may be considered for use as emissions offsets 

(see, e.g., Rothblatt, 2007). An additional consideration that will need to be made with 

regard to any credit used for PSD offsetting purposes is the location of the offset relative 

to the proposed emissions increase. That is, an appropriate emissions offset must be 

shown to affect the same area as the new emissions so as to provide effective 

compensation for the adverse impact of the new emissions. See 40 CFR 51.165(b)(3) 

(“sufficient emissions reductions to, at a minimum, compensate for its adverse ambient 

impact where the source would otherwise cause or contribute to a violation of any 

[NAAQS]”). 

Thirdly, the commenter recommended that the EPA “tier requirements post construction 

to levels of actual emissions from a new project.” Unfortunately, it is not clear what the 

commenter meant by “tiering” the requirements, or how using the project’s postconstruction actual emissions would address a potential NAAQS violation. Thus, we are 

unable to respond to this particular comment as presented. 

Finally, the commenter recommended that the EPA use the existing provisions in section 

10 of Appendix W (Guideline on Air Quality Models) to allow post-construction 

monitoring “where models may predict certain future air quality impacts from a project.” 

As indicated in the response to comment c.4 of this section, the EPA will continue to 

remind air agencies of the applicability of Section 10 of Appendix W that allows for 

monitoring in lieu of modeling to demonstrate compliance under PSD for existing 
VI-25 

sources in situations where it has been determined in consultation with the appropriate 

reviewing authority that the modeling techniques are not appropriate for use. 

(4) Comment: One industry trade association commenter, stated that EPA should prepare for 

NSR/PSD implementation to avoid a practical “permitting moratorium” in areas where 

existing air quality is such that PSD air quality analyses must be performed to 

demonstrate compliance with the NAAQS, but cannot in practice because current air 

quality is: (1) currently monitored at a level greater the new NAAQS level before model 

results are considered; or (2) currently monitored at a level in the range of 10-12 μg/m3

(or 13 μg/m3

) and would have such a small margin available that a major source or major 

modification could not practically model a small enough impact attributable to the source 

that, when added to the background, could demonstrate compliance with the NAAQS. 

The commenter stated that in many areas, based on the EPA’s 2009-2011 Design Values, 

modeling of new source growth can be anticipated to be very challenging. 

Response: As we indicated in the responses above (f.1 and f.3), we believe that adequate 

policy exists to enable states to issue permits to proposed new and modified sources that 

model violations of the NAAQS, as long as those sources provide sufficient 

compensation for their modeled adverse impacts. Accordingly, it is not appropriate to 

conclude that sources proposing to construct or modify in areas already showing 

exceedances of the annual PM2.5 NAAQS or experiencing levels near the NAAQS face 

an automatic “permitting moratorium.” 

E. Nonattainment New Source Review 

(1) Comment: Several industry commenters recommended that the EPA establish a 

grandfathering provision for NNSR as was proposed under the PSD program. A subset of 

these commenters recommended that grandfathering be accomplished by establishing an 

effective date for designations 1 year after initial publication in the Federal Register. 

Response: The EPA has provided detailed responses to these comments in section IX.D.2 

of the final rule preamble. 

(2) Comment: A few industry and state agency commenters addressed the issue of potential 

dual review (applying NNSR and PSD simultaneously) based on distinct designations for 

separate averaging times of the PM2.5 NAAQS. These commenters generally agreed with 

the EPA’s conclusion that it was reasonable to apply only the NNSR permitting 

requirements to such situations and not PSD. 

Response: The EPA has provided detailed responses to these comments in section IX.D.2 

of the final rule preamble. 

F. Other NSR Implementation Comments 

(1) Comment: One industry coalition commenter and one industry trade association 

commenter identified issues related to in-stack PM2.5 test methods. These commenters 

stated that available test methods for PM2.5 from wet stacks overestimate emissions and 

therefore will subject more sources to NSR/PSD. One of the commenters indicated that 

the EPA had committed to study this issue further when it finalized revisions to 
VI-26 

Reference Method 202 for condensable particulate, and the other that API and the 

National Council for Air and Stream Improvement, Inc. (NCASI) are working with the 

EPA to develop a validation test plan for candidate methods, but that this process will 

take time. 

Response: The EPA recognizes the need to develop a method which quantifies PM2.5

emissions in a wet stack environment. Since the proposal of Method 201A, the EPA has 

been engaged in the development of this capability. In addition, the EPA has been 

following the efforts of a contractor retained by API to develop this capability but with a 

somewhat different approach. While these efforts are promising, the EPA is several years 

from having a validated test method which all stakeholders are confident is reliable and 

capable of being performed by most stack test consultants. 

(2) Comment: One industry association and one state agency commented on the lack of 

accurate emissions information and technical guidance concerning PM2.5. The industry 

association commenter cited deficiencies in EPA’s AP-42, including the fact that most 

emission factors are for total PM, the limited data on particle size distribution, the lack of 

data on condensable PM, and the low quality rating of available emission factors. The 

state agency commenter stated that the lack of reliable emission factors and data on the 

condensable portion of PM2.5 makes it difficult for air agencies and/or sources to fairly 

and effectively implement the standards, and that this would be exacerbated by lowering 

the standards. 

Response: The EPA recognizes that many of the emissions factors in AP-42 are outdated 

and/or deficient for many source categories. This situation has arisen due to the inability 

to obtain and process source test information in an efficient and cost effective way to 

develop new and revised emissions factors. As a result the EPA is updating the way that 

stack test reports are documented and processed to develop emissions factors. In 2004, 

the EPA developed the Electronic Reporting Tool (ERT) for documenting stack tests. 

The ERT revises the paper method of documenting the requisite information so that the 

remainder of the emissions factor development does not require the level of resources 

required with paper test reports. Since the development of the ERT, the EPA has required 

sources to use this tool to report the results of stack test data required for regulatory 

development efforts. In addition, the EPA has promulgated several rules for specific 

source categories that require sources to submit stack test reports t using the ERT. On 

January 1, 2012, the EPA activated the Central Data Exchange (CDX) portal for 

submitting stack test reports. The EPA will be developing a data system to replace the 

existing WebFIRE which will use test data submitted with the ERT through the CDX to 

update existing emissions factors or to develop new emissions factors. To the extent that 

sources submit their stack test data to the EPA with the ERT, updated emissions factors 

will be made available for use by regulated sources’ air agencies. 

(3) Comment: One industry coalition commenter suggested that a transition period may be 

needed for pre- and post-construction monitoring of PM2.5 under the PSD program to 

address changes in the monitoring regulations. 
VI-27 

Response: The EPA does not anticipate that the changes to the monitoring regulations 

contained in the final NAAQS rule would affect pre- or post-construction monitoring 

under the PSD program that may be in progress or pending at the time the changes 

become effective. Therefore, the EPA does not believe that a regulatory transition period 

is necessary. In the unlikely event that case-specific PSD pre- and/or post-construction 

monitoring may be affected by the monitoring regulation changes contained in the final 

rule, the EPA and permitting authorities may have the discretion to mitigate such impacts 

by providing a transition period or mechanism tailored to the specific permit action to 

avoid unreasonable delays and additional burden. 

G. Specific Comments Related to Transportation Conformity 

(1) Comment: One commenter was pleased to see that, if the proposed changes to the PM2.5

monitoring regulations concerning replacing the term “community oriented” with “areawide” and revoking the requirement that monitoring sites be population oriented are 

finalized, the EPA would update its guidance on conducting quantitative PM2.5 hot-spot 

analyses for transportation conformity purposes. The commenter stated that to avoid 

confusion the guidance will need to be revised expeditiously. 

Response: The changes to the monitoring regulations are designed to align different 

elements of those regulations for consistency. The EPA intends to quickly revise its 

guidance entitled, “Transportation Conformity Guidance for Quantitative Hot-spot 

Analyses in PM2.5 and PM10 Nonattainment and Maintenance Areas”51 to address 

these revisions to the monitoring regulations. The preamble to the final PM NAAQS rule 

describes how the EPA intends to address the overall transition from the current 

monitoring regulations to the revised monitoring regulations. The EPA intends the 

current PM Hot-spot Guidance to continue to apply to any quantitative PM2.5 hot-spot 

analysis that was begun before the effective date of today’s revisions to the monitoring 

regulations. Revised guidance would apply to any quantitative PM2.5 hot-spot analysis 

begun after the effective date of the revised monitoring regulations. Nonattainment and 

maintenance areas are encouraged to use their interagency consultation processes to 

determine whether an analysis for a given project was started before the effective date of 

the revised monitoring regulations. 

(2) Comment: Two commenters raised issues related to having one or more separate 

secondary NAAQS for PM2.5 making transportation and air quality planning and 

transportation conformity more complex and costly by requiring that conformity be 

demonstrated by comparing future emissions to multiple sets of PM2.5 motor vehicle 

emissions budgets. The commenters were also concerned that the EPA will not be able to 

completely revoke the 1997 annual PM2.5 NAAQS as has been the practice as the ozone 

NAAQS has been revised meaning that areas will have to continue to demonstrate 

conformity to the 1997 annual PM2.5 NAAQS. One commenter notes that revoking the 

previous less stringent NAAQS conserves resources because the areas no longer have to 

demonstrate conformity for the earlier NAAQS after it is revoked. 

 

51 Hereafter, referred to as “PM Hot-spot Guidance” in this document. EPA420­B­10­040, December 2010. U.S.

EPA (2010j). See www.epa.gov/otaq/stateresources/transconf/policy.htm#project.
VI-28 

Response: As discussed in the final rule the EPA retained the 1997 annual secondary 

PM2.5 NAAQS of 15.0 ug/m3

, and did not finalize the proposed visibility-related standard 

because we determined that retaining the current 24-hour PM2.5 NAAQS provides 

visibility protection equivalent to the proposed visibility-related secondary NAAQS. The 

EPA will work with areas through the conformity rule’s interagency consultation process 

to determine efficient ways to fulfill conformity requirements for each of the PM2.5

NAAQS that apply in each area in order to minimize the impact on the area’s resources. 

The comment on revocation is beyond the scope of the current final rule. The potential 

revocation of the 1997 annual PM2.5 NAAQS will be addressed in the planned 

implementation rule for the 2012 annual PM2.5 NAAQS. 

(3) Comment: In order to reduce the possibility of diverting transportation funds from 

addressing regional air quality which benefits the population of the entire nonattainment 

area to addressing near road or hot-spot problems, the EPA should work closely with 

transportation professionals when developing implementation policies for these types of 

issues. 

Response: The EPA will work with a wide range of stakeholders as it develops SIP 

requirements for implementing the PM2.5 NAAQS through a future rulemaking. 

(4) Comment: Given the potential implications for transportation planning and transportation 

projects the EPA should consult with transportation agencies on changes to 

implementation and designation requirements, transportation conformity requirements 

including hot-spot requirements, and monitoring requirements. 

Response: The EPA will work with a wide range of stakeholders as it develops SIP 

requirements for implementing the PM2.5 NAAQS in a future rulemaking. The EPA will 

also update existing transportation conformity or issue new guidance as needed, as the 

Agency has historically done for conformity transitions to new NAAQS. 

(5) Comment: Adding additional requirements on top of requirements that have not yet been 

fully implemented could result in transportation projects that had been in compliance 

with the Clean Air Act being determined to be out of compliance which would expose 

them to litigation. 

Response: It is not clear what the commenter is referring to, since the comment provides 

no information regarding which specific “additional requirements” it is referring to, or 

how transportation projects could be determined to be out of compliance with the CAA. 

Therefore, we are unable to respond to this comment. 

(6) Comment: The commenter seeks assurance that PM2.5 nonattainment areas will be 

eligible to receive Congestion Mitigation and Air Quality Improvement (CMAQ) funds 

even though they will not be classified. 

Response: PM2.5 nonattainment and maintenance areas are eligible to receive CMAQ 
VI-29 

funds from the Federal Highway Administration. On July 6, 2012, the President signed 

the Moving Ahead for Progress in the 21st Century Act (MAP-21) into law. MAP-21 

authorizes transportation funding through the end of federal fiscal year 2014 and amends 

the federal transportation law. Under MAP-21, a State with PM2.5 areas must use a 

portion of its funds to address PM2.5-related emissions in such areas; eligible projects to 

mitigate PM2.5 include diesel retrofits. MAP-21 also retains the direction to states and 

metropolitan planning organizations to give priority to funding projects in PM2.5

nonattainment or maintenance areas that are proven to reduce PM2.5, including diesel 

retrofits. 

H. Specific Comments Related to Exceptional Events 

Comments related to exceptional events focused on the schedule for data flagging and 

documentation submittal for the primary standard and the schedule for data flagging and 

documentation submittal for the secondary standard to address the “unique” components of the 

secondary standard. Each of these is addressed below. The responses to these comments are also 

discussed in section VII.B of the preamble to the final rule. 

(1) Comment: The majority of commenters supported the schedule by which agencies must 

flag ambient air data that they believe have been affected by exceptional events, submit 

initial descriptions of those events, and submit detailed justification to support the 

exclusion of those data from EPA-monitoring-based determinations of nonattainment 

with the primary annual PM2.5 NAAQS. A few commenters suggested schedule 

extensions for one of two reasons: the potential resource burden associated with 

preparing and submitting multiple wildfire exceptional event demonstrations for events in 

the unusually active wildfire years of 2010 to 2012 and data reporting lags and “unique” 

monitoring elements associated with the secondary standard. 

Response: The EPA is finalizing the exceptional events schedule as proposed and as 

supported by multiple commenters. For air quality data collected in 2010 and 2011, the 

EPA is extending to July 1, 2013, the otherwise applicable generic deadlines of July 1, 

2011 and July 1, 2012, respectively, for flagging data and providing an initial description 

of an event (40 CFR 50.14(c)(2)(iii)). The EPA is retaining the existing generic deadline 

in the Exceptional Events Rule of July 1, 2013, for flagging data and providing an initial 

description of events occurring in 2012. Similarly, the EPA is revising to December 12, 

2013, the deadline for submitting documentation to support exceptional events occurring 

in 2010 through 2012 and potentially influencing compliance with the revised primary 

annual PM2.5 NAAQS. If an air agency intends the EPA to consider in the revised 

primary annual PM2.5 designations decisions whether PM2.5 data collected during 2013 

influence compliance with the primary annual PM2.5 NAAQS, then the air agency must 

flag these data by the generic Exceptional Event Rule deadline of July 1, 2014. The EPA 

is finalizing August 1, 2014, as the deadline for submitting documentation to justify 

PM2.5-related exceptional events occurring in 2013 and potentially influencing 

compliance with the revised primary annual PM2.5 NAAQS. The EPA believes these 

revisions/extensions will provide adequate time for air agencies to review potential PM2.5

exceptional events influencing compliance with the revised primary annual PM2.5
VI-30 

NAAQS, to notify the EPA by flagging the relevant data and providing an initial 

description in AQS, and to submit documentation to support claims for exceptional 

events. These schedule revisions will also allow the EPA to fully consider and act on the 

submitted information during the initial area designations process for the revised primary 

annual PM2.5 NAAQS. 

The EPA acknowledges commenter concerns that numerous wildfires occurred between 

2010 and 2012 and that air agencies may determine that these wildfires influenced 

ambient air quality concentrations potentially affecting compliance with the revised 

primary annual PM2.5 NAAQS. The EPA further acknowledges that air agencies may 

submit detailed exceptional events documentation associated with multiple wildfires. 

Although some commenters noted that 1 year to provide documentation of these potential 

exceptional events may not be sufficient, the EPA believes that the promulgated 

schedules provide sufficient time for air agencies to submit information related to the 

annual standard and for the EPA to fully consider and act on the submitted information 

during the initial area designations process. The EPA recently released draft exceptional 

events guidance that clarifies key provisions of the 2007 Exceptional Events Rule, 

provides examples of best practices, and streamlines the documentation development 

process. The guidance provides approaches that are broadly applicable to all 

event/pollutant combinations and would apply to many PM events, including wildfire/PM 

combinations. Additionally, the EPA has posted several concurred upon wildfire/PM 

exceptional event demonstration packages on its website at 

http://www.epa.gov/ttn/analysis/exevents.htm. Considered together, the EPA believes 

this guidance will help air agencies submit information in a timely manner.52 The EPA 

notes that under the promulgated schedule, except for events that occur in December 

2012, air agencies will have more than 1 year to provide documentation for these 

potential events. The EPA intends to work with potentially affected areas to identify, 

screen and prioritize events potentially influencing compliance with the primary annual 

PM2.5 NAAQS and associated area designations. 

For the reasons stated in section VI.D.2 of the preamble to the final rule, the 

Administrator has decided not to establish the proposed distinct secondary standard to 

address visibility impairment. Therefore, the EPA will not promulgate initial area 

designations for a secondary PM visibility index standard and, as a result, has not 

promulgated exceptional event schedule revisions for events that might influence 

compliance with the secondary standard. 

(2) Comment: Several commenters asked that the EPA clarify the preamble language and the 

associated promulgated exceptional events schedule to specifically identify the NAAQS 

to which the exceptional event schedule revisions apply. 

Response: In response to comment, the EPA clarified that the preamble language and the 

associated promulgated exceptional events schedules apply only to the NAAQS that the 

 

52U.S. EPA (2012e). Draft Guidance to Implement Requirements for the Treatment of Air 

Quality Monitoring Data Influenced by Exceptional Events, U.S. Environmental Protection 

Agency. June 2012. Available: http://www.epa.gov/ttn/analysis/exevents.htm. 
VI-31 

EPA is newly promulgating or revising in this action, that is, the revised primary annual 

PM2.5 NAAQS. The promulgated exceptional event schedule revisions do not apply to the 

retained PM standards (i.e., secondary PM standards, primary 24-hour PM10, primary 24-

hour PM2.5). Further, the revised/extended exceptional event schedules apply only to 

those data the EPA will use to establish initial area designations for the revised primary 

annual PM2.5 NAAQS. 
VII-1 

VII. RESPONSES TO SIGNIFICANT COMMENTS ON LEGAL, ADMINISTRATIVE, 

PROCEDURAL, OR MISPLACED COMMENTS 

A number of comments were received that addressed a wide range of issues including 

legal, administrative, and procedural issues. Many legal issues are addressed generally 

throughout the preamble to the final rule. Specific legal issues are more fully addressed in 

section VII.A as well as in the previous RTC sections above. Comments related to the Statutory 

and Executive Orders are addressed generally in section X of the preamble to the final rule and 

discussed more fully in section VII.B below. In addition, a number of comments were submitted 

related to issues that are not germane to the review of the NAAQS. Such comments have been 

categorized as “misplaced” comments and are discussed in section VII.C below. 

A. Legal Issues 

A number of commenters submitted comments addressing specific legal issues. These 

issues are generally discussed throughout the preamble to the final rule and more specifically 

below. A number of legal issues specifically addressing comments related to the secondary 

standards are addressed in section VI.C.1.g of the preamble to the final rule and in section IV.B.8 

above. 

(1) Comment: One commenter asserted that the EPA has failed to “review and consider the 

latest science in an unbiased, factual manner...raising the potential that its decision to 

propose a lower standard violates the Clean Air Act” (ACC, 2012, p.2). This commenter 

further argued that the proposal “presents inadequate justification for revising the level 

and form of the primary annual PM2.5 standard and the EPA has “failed to address the 

2009 D.C. Circuit remand” Id. 

Response: The EPA strongly disagrees with this comment. The final decisions discussed 

in the preamble to the final rule reflect decisions based on air quality criteria representing 

“”the latest scientific knowledge” within the meaning of section 108 (a) (2) of the Act. 

The CASAC reviewed this enormous body of material and found it a sufficient basis for 

agency action with respect to review of the PM standards, including the primary fine 

particle standards. Moreover, the EPA is addressing the remand of the 2006 standards by 

the D.C. Circuit by revising the primary and secondary standards for PM2.5 in a manner 

consistent with the court’s opinion and mandate.

(2) Comment: A group of commenters argued that the “EPA’s failure to seek comment on 

the existing primary annual standard inappropriately prejudges the outcome, leads to 

inherently biased rulemaking and is contrary to law” (e.g., NAM, 2012, p. 6).

Response: The commenter suggests that the EPA somehow prejudged the outcome of the 

rulemaking , or otherwise committed procedural error, by not proposing to retain the 

2006 NAAQS. This is in error. First, the EPA provided far more process through this 

review than the amount required by law. Commenters had multiple opportunities to 

review and comment on multiple drafts of all of the critical documents underlying the 

review (notably the ISA, the REAs, and the PA), as well as on all of the critical scientific 

and policy issues, assumptions, and factual data informing the review. Given that the 
VII-2 

basic question being addressed throughout this proceeding is whether or not it is 

appropriate to revise the 2006 standard (CAA section 109 (d)), that issue was necessarily 

before the public for comment (as evidenced by all the comments urging retention of the 

standard, among other indicia of proper notice). Nor does the EPA’s proposal indicate a 

pre-judgment of the outcome of the review. Rather, the proposal reflected the EPA’s 

consideration of the body of scientific data and analysis comprising the record for this 

review. 

The EPA strongly disagrees that the currently available scientific evidence and technical 

information supports consideration for retaining the annual standard level at 15 μg/m3 and 

consequently did not propose to do so (just as the EPA did not propose to make the 

standard less stringent). As discussed in section III.D.3. of the preamble for the final rule, 

having carefully considered CASAC advice and the public comments on the proposal as 

discussed in section III.D.2 of the preamble to the final rule and in section II.B.1 above, 

the EPA believes the fundamental scientific conclusions on the effects of PM2.5 reached 

in the ISA, and discussed in the PA, are valid. The Agency believes that since the last 

review the overall uncertainty about the public health risks associated with both long- and 

short-term exposure to PM2.5 has been diminished to an important degree. The remaining 

uncertainties in the available evidence do not diminish confidence in the associations 

between exposure to fine particles and mortality and serious morbidity effects. Based on 

the Agency’s increased confidence in the association between exposure to PM2.5 and 

serious public health effects, combined with evidence of such an association in areas that 

would meet the current standards , the Administrator agrees with CASAC that revision of 

the current suite of PM2.5 standards to provide increased public health protection is 

necessary. Based on these considerations as discussed in section III.D.3 of the preamble 

to the final rule, the Administrator concludes that the current suite of primary PM2.5

standards is not sufficient, and thus not requisite, to protect public health with an 

adequate margin of safety, and that revision is needed to increase public health 

protection. Furthermore, as discussed in section III.E.4.e of the proposal, the 

Administrator provisionally concluded that the available scientific information supported 

consideration of an annual standard level no higher that 13 μg/m3

. In considering public 

comments on the proposal as discussed in sections III.E.4.c.i and III.E.4.d of the 

preamble for the final rule and in section II.B.5.a above, the Agency concludes there is no 

scientific basis for considering retaining the annual standard level at 15 μg/m3 (absent a 

drastically lower level of the 24-hour standard). These conclusions represent reasoned 

consideration of the body of evidence comprising the record for this proceeding, not 

impermissible bias. 

(3) Comment: One group of commenters argued that the EPA is not bound by the CASAC 

recommended range or any other CASAC recommendations (e.g., NAM, 2012, p. 10).

Response: The EPA agrees that the Agency is not bound by the CASAC recommended 

range or any other CASAC recommendations, however, the Agency believes it needs to 

give careful consideration to CASAC’s advice and recommendations, and has done so 

here. The EPA is also clearly required to explain the reasons for any significant 

differences in approach. CAA section 307 (d) (3). The EPA’s deviation from CASAC 

advice and recommendations, and its failure to adequately explain those deviations, was 
VII-3 

one of the reasons for the remand of the 2006 primary annual PM2.5standard. See

American Farm Bureau Federation v. EPA, 559 F. 3d at 521. 

The EPA has carefully considered CASAC’s advice and recommendations in this review, 

understanding that CASAC’s views are not binding on the agency. Under sections 108 

and 109 of the CAA, the Administrator is required to make decisions in reviewing the 

NAAQS using her own “judgment” in determining what standard is “requisite” in light of 

all of the evidence, and is not required to accept or follow CASAC’s recommendations 

on what revisions are appropriate. The merits of the Administrator’s decision is not 

determined solely based on whether she did or did not agree with CASAC, but based on a 

review of the record as a whole, including any explanation the Administrator provides for 

accepting or rejecting a recommendation from CASAC. The EPA has provided such 

explanations here as discussed in the preamble to the final rule, both where the 

Administrator’s actions are consistent with CASAC’s advice (e.g., final decisions on the 

primary PM2.5 standards) and where in her judgment a different course of action than 

recommended by CASAC was appropriate (e.g., final decision on the primary PM10

standard). 

(4) Comment: A group of commenters argued that “issuing a revised lower PM NAAQS that 

is both complicated and legally infirm will produce regulatory delay and uncertainty that 

could result in adverse rather than beneficial health impacts (NAM, 2012, p. 26). These 

commenters further noted the delay in the EPA’s response to the 2009 remand of the 

2006 PM NAAQS and argued that “issuing a final rule that promotes regulatory and legal 

uncertainty may delay or even foreclose investments that could reduce overall PM 

emissions from the manufacturing sector.” Id. 

Response: The EPA does not believe the revised standards are legally infirm. Moreover, 

the remand of the 2006 primary annual standard for PM2.5 was due to the EPA’s inability 

to adequately explain why that standard was not more stringent, not less stringent as this 

commenter would prefer. 

(5) Comment: Many commenters asserted that the standards must protect at-risk populations 

– children, older adults, persons with pre-existing heart and respiratory disease, and 

persons with an adequate margin of safety (e.g., CHPAC, 2012; ALA et al., 2012, pp. 29 

to 38).

Response: The EPA agrees with this comment and has carefully considered effects on atrisk populations in considering whether and how to revise the PM2.5 NAAQS. As noted in 

section II.A of the preamble to the final rule, the CAA requires the EPA Administrator to 

establish primary standards that provide an adequate margin of safety. The legislative 

history of section 109 of the CAA 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). The 

CAA does not require the Administrator to establish a primary NAAQS at a zero-risk 

level or at background concentration levels, see Lead Industries v. EPA, 647 F.2d at 1156 
VII-4 

n.51, but rather at a level that reduces risk sufficiently so as to protect public health with 

an adequate margin of safety. In the Administrator’s judgment, the final decisions 

articulated in the final rule represent primary PM standards that are sufficient but not 

more protective than necessary to protect the public health, including at-risk populations, 

with an adequate margin of safety from effects associated with PM exposures. 

(6) Comment: Some commenters argued that the EPA must adopt a precautionary approach 

to the standard setting, and set standards in a manner that deals with uncertainty not by 

ignoring effects but rather by protecting against adverse health effects (e.g., ALA et al., 

2012, pp. 9 to 10). In support of this argument, these commenters specifically cited Ethyl 

Corp v. EPA, 541 F. 2d at 15, H. Rep No. 294, 95th Cong, 1st Sess. At 49 to 51 (1977) 

(explaining amendments designed inter alia “[t]o emphasize the preventive or 

precautionary nature of the act, i.e., to assure that regulatory action can effectively 

prevent harm before it occurs”), and American Trucking Association v. EPA, 283 F. 3d at 

355, 369 (“the Act requires EPA to promulgate protective primary NAAQS even 

where... the pollutant’s risks cannot be quantified or ‘precisely identified as to nature or 

degree’”). 

Response: The EPA agrees generally with this comment, but notes further that a general 

invocation of precautionary principles does not determine where in the range of 

reasonable values the EPA could establish the level of a standard. Section III.E.4.d to the 

preamble to the final rule explains in detail why it is appropriate to revise the annual 

standard level to 12.0 μg/m3

 in conjunction with retaining the 24-hour standard level at 

35 μg/m3. The EPA notes further that this choice is consistent with case law in the D.C. 

Circuit (not cited by the commenter) that the Administrator is to carefully examine all of 

the relevant studies in the record, but need not base the level of the standard on either the 

highest or lowest value in these studies. Rather, an informed judgment is called for. API 

v. EPA, 665 F. 2d at 1187; NRDC v. EPA, 902 F. 2d 962, 970. Section III.E.4.d to the 

preamble to the final rule states the basis for the Administrator’s exercise of informed 

judgment here in setting the levels of the primary annual and 24-hour PM2.5 standards. 

B. Administrative/Procedural Issues 

Several comments addressed administrative and procedural issues related ot he review of 

the PM NAAQS. These comments are addressed below. 

(1) Comment: Several commenters argued that the timeline for issuing the final rule will 

likely mean that the EPA will not have time to adequately review and respond to 

comments filed on the proposal (ACC, 2012, p. 2, NAM, 2012, pp. 5 and 15 to 17; Dow, 

2012, p. 1; US. Chamber of Commerce, 2012. pp. 2 to 5). 

Response: Although the EPA sought to justify a longer schedule in the scheduling 

litigation leading up to the District Court issuing a preliminary injunction and lodging the 

governing consent decree, the EPA believes that it has adequately considered and 

responded to all of the substantive public comments. The EPA also notes that it provided 

multiple opportunities to review and comment on all of the critical documents underlying 

the review (notably multiple drafts of the ISA, the RA, the UFVA, and the PA), as well 
VII-5 

as on all of the critical scientific and policy issues, assumptions, and factual data 

informing the review. In addition to affording multiple opportunities for public comment, 

review of those comments gave the EPA opportunity to consider commenters’ views 

throughout the process of reviewing the standards. Consequently, the EPA was already 

informed of many of the key points raised in the comments to the proposal in advance of 

the proposal. The EPA notes further that the time between proposal and final rule, 

although relatively brief, is not significantly different from that of other NAAQS reviews, 

including the 2006 PM NAAQS (proposed in January 2006 and signed in September 

2006 – eight months versus six months here). 

(2) Comment: Further, some of these commenters asserted that in following the current 

schedule for completing the final rule (i.e., signature by December 14, 2012), the Agency 

will not have the results of the EPA Inspector General’s investigation of CASAC’s role in 

reviewing the EPA”s PM NAAQS recommendations to inform its final decisions (NAM, 

2012, pp. 5 and 17 to 18). 

Response: As stated in an earlier response in this RTC section, the decision on whether to 

revise a NAAQS is the EPA’s alone. By statute, that decision is informed by CASAC’s 

advice and recommendations, but not determined by it. Moreover, the EPA is fully 

capable of assessing the scientific merit of CASAC’s advice and recommendations. 

Review of the EPA’s decision rests on the administrative record, not on some possibly 

forthcoming report by a non-scientific entity not involved in the review proceeding. Thus, 

EPA does not see that this comment has merit. 

(3) Comment: One commenter asserted “it is farcical that EPA claims the proposed rule does 

not have Tribal implications as specified by Executive Order (EO) 13175” (NTAA, 2012, 

p. 4). Further this commenter argued that the EPA did not conduct meaningful 

consultation with Tribes in accordance with EO 13175. Id.

Response: The EPA disagrees with this comment. As summarized in section X.F of the 

preamble to the final rule, this rule concerns the establishment of national standards to 

address the health and welfare effects of particulate matter. Historically, the EPA’s 

definition of “tribal implications” has been limited to situations in which it can be shown 

that a rule has impacts on the tribes’ ability to govern or implications for tribal 

sovereignty. Based on this historic definition, this action does not have Tribal 

implications, as specified in Executive Order 13175 (65 FR 67249, November 9, 2000), 

i.e. because it does not have a substantial direct effect on one or more Indian tribes, since 

tribes are not obligated to adopt or implement any NAAQS. Nevertheless, the Agency 

was aware that many tribes would be interest in this rule and we undertook a number of 

outreach activities to inform tribes about the PM NAAQS review and offered two 

consultations with tribes. 

Although Executive Order 13175 does not apply to this rule, the EPA undertook a 

consultation process including: prior to proposal on March 29,2012 we sent letters to 

tribal leadership inviting consultation on the rule and then sent a second round of letters 

offering consultation after the proposal was issued on June 29, 2012. No tribe requested a 

formal consultation with the EPA. We conducted outreach and information calls to tribal 
VII-6 

environmental staff on May 9, 2012; June 15, 2012; and August 1, 2012. The EPA also 

participated on the National Tribal Air Association (NTAA) call on June 28, 2012. 

As a result, we received comments from the NTAA, the Southern Ute Mountain Ute 

Tribe, and the Navajo Nation EPA. In general, these tribal organizations were supportive 

of the EPA’s proposal. 

C. Misplaced Comments 

Some comments received on the proposed PM NAAQS addressed issues that are not 

relevant for consideration in the review of the NAAQS. These comments and other “misplaced 

comments are discussed more fully below. 

(1) Comment: One group of commenters argued that the EPA should ensure that its final rule 

“does not impose unnecessary costs on the regulated community” (NAM, 2012, p. 29). 

Another commenter asserted that the EPA should consider the broader regulatory burden 

that is being imposed through application of multiple PM standards which collectively 

serve to address many of the same health effects – in addition implementing revised 

primary NO2 and SO2 standards (AFPM, 2012, p. 23).

Response: The EPA strongly disagrees with this comment. As discussed in section II.A 

of the preamble to the final rule, in setting NAAQS, the 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). Likewise, “[a]ttainability and 

technological feasibility are not relevant considerations in the promulgation of national 

ambient air quality standards.” American Petroleum Institute v. Costle, 665 F. 2d at 1185. 

(2) Comment: Some commenters provided comments related to the EPA’s Regulatory 

Impact Analysis (RIA) for the proposal which was issued in June 2012.

Response: As discussed in section II.A of the preamble to the final rule, because the costs 

of implementation cannot be considered in setting or revising the NAAQS, the results of 

the RIA were not considered in the EPA’s decisions on the PM standards. Comments on 

the RIA for the proposal were considered, as appropriate, in developing the RIA for the 

final rule.

(3) Comment: The EPA received several comments critical of the development process and 

timing of a revised PM NAAQS implementation rule. One commenter stated that the 

EPA should not finalize the proposed revisions without considering and responding to 

comments regarding implementation issues, particularly with respect to the secondary 

standard. Another commenter stated that the EPA needs to be clear what issues are going 

to be final in this (PM NAAQS) rulemaking versus a future implementation rulemaking. 

Another commenter interpreted EPA's request for comment on the NAAQS as 

purposefully seeking more information about how to implement the standard, which they 

claimed was problematic due to limited implementation guidance or rulemaking to 

comment on prior to finalization of the NAAQS. 

Response: These comments reflect a possible misunderstanding of the scope of the PM 
VII-7 

NAAQS rulemaking with respect to implementation issues. As explained in Section IX of 

the preamble to the final rule, the EPA will be undertaking a separate effort to develop an 

implementation rule for the revised NAAQS through a formal notice-and-comment 

rulemaking, which we intend to finalize around the time the initial area designations 

process is completed. The EPA will seek input from a wide range of stakeholders and the 

public throughout the implementation rulemaking process. To the extent the EPA sought 

comment on any state implementation planning issues as part of the PM NAAQS 

proposal, the Agency stated that we would take under consideration comments received 

as we developed a separate future implementation rule proposal. (Note, however, that 

certain PSD issues are specifically addressed in the final PM NAAQS rulemaking; issues 

related to implementing a secondary standard are not relevant as the Agency is not 

finalizing the proposed secondary standard relating to visibility in this final rule.) 

We will provide a separate comment period for the submission of comments on any 

future implementation rule proposal. At that time, parties who submitted preliminary 

implementation-related comments as part of this rulemaking (to revise the PM NAAQS) 

may choose to resubmit their comments for consideration as part of the PM2.5 NAAQS 

implementation rulemaking. Comments received on the PM NAAQS proposed rule will 

not be considered to be comments “submitted in advance” on any future implementation 

rule proposal. 

(4) Comment: One commenter suggested that the EPA should, through the appropriations 

process, request adequate funds for air agencies to implement any revised or new 

NAAQS. 

Response: This comment is on EPA’s budget request and is not relevant to the PM 

NAAQS rulemaking. 

(5) Comment: The commenter asserts that complying with transportation conformity 

requirements will delay transportation projects that are intended to address traffic 

congestion. 

Response: This comment is outside the scope of this rulemaking. In addition, we do not 

understand the basis of the commenter’s claim that complying with transportation 

conformity requirements results in the delay of projects designed to address traffic 

congestion. Areas are successfully implementing conformity requirements for the current 

suite of transportation–related NAAQS (ozone, PM2.5, PM10, carbon monoxide and 

nitrogen dioxide) including meeting relevant deadlines. All areas that were designated 

nonattainment for the 1997 and 2006 PM2.5 NAAQS successfully complied with the 

requirement to demonstrate conformity within one-year of the effective date of their 

nonattainment designation. The conformity rule also exempts certain congestion-related 

projects from conformity requirements, including traffic signal synchronization projects 

(40 CFR 93.128) and certain intersection and interchange projects (40 CFR 93.127). If 

the commenter is concerned that project-level conformity requirements could delay 

congestion relief projects, the commenter should be aware that a hot-spot analysis is only 

required if the project is determined through interagency consultation to be a project of 

air quality concern. 
VII-8 

(6) Comment: One commenter opines that the transportation conformity process needs to be 

examined. The commenter supplies examples of several concerns that they have with 

transportation conformity implementation. The other commenter opines that due to 

transportation conformity requirements transportation projects can only proceed in 

nonattainment and maintenance areas if they do not result in increased emissions. 

Response: These comments address requirements of the existing conformity rule and are 

not relevant to the PM NAAQS rulemaking.
R-1 

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R-17 

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59b22!OpenDocument

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APPENDIX A: Provisional Science Assessment 
i

December 2012

EPA/600/R-12/056F

Provisional Assessment of Recent

Studies on Health Effects of

Particulate Matter Exposure

National Center for Environmental Assessment RTP Division

Office of Research and Development

U.S. Environmental Protection Agency

Research Triangle Park, NC 27711
ii

DISCLAIMER

This document has been reviewed in accordance with U.S. Environmental Protection Agency

policy and approved for publication. Mention of trade names or commercial products does not

constitute endorsement or recommendation for use.
iii

Table of Contents

List of Tables ............................................................................................................................................... iv

List of Figures............................................................................................................................................... v

Authors, Contributors, Reviewers................................................................................................................ vi

Executive Summary ...................................................................................................................................viii

1. INTRODUCTION AND METHODOLOGY....................................................................................... 1

2. OVERVIEW OF RECENT HEALTH STUDIES RESULTS .............................................................. 2

2.1. Epidemiologic Studies of Long-Term Exposure........................................................................... 3

2.1.1. Mortality ............................................................................................................................... 4

2.1.2. Morbidity – Cardiovascular Effects.................................................................................... 12

2.1.3. Morbidity – Respiratory Effects ......................................................................................... 14

2.1.4. Morbidity – Reproductive and Developmental Effects....................................................... 16

2.2. Epidemiologic Studies of Short-Term Exposure ........................................................................ 16

2.2.1. Mortality ............................................................................................................................. 17

2.2.2. Morbidity ............................................................................................................................ 21

2.3. Health Effects Related to Sources or Components of PM .......................................................... 30

2.3.1. Epidemiologic Studies Using Source Apportionment ........................................................ 30

2.3.2. Epidemiologic Studies on Effects of Fine PM Components and Sources .......................... 31

2.3.3. Toxicology Studies – Source Apportionment and Fine PM Components.......................... 35

3. SUMMARY AND CONCLUSIONS ................................................................................................. 40

APPENDIX A. Studies Included in the PM Provisional Science Assessment ........................................... 42

References .............................................................................................................. 57
iv

List of Tables

Table 2.1. Causal Determinations for Short-and Long-Term Exposure to PM2.5......................................... 3

Table 2.2.Association between mortality outcomes and PM2.5 components using a 30-km buffer

(n=43,220) (adapted from Ostro et al. (2011))............................................................................................ 34

Table 2.3. CAPs Sources and Associated Endpoints ................................................................................. 36

Table A.1. Characterization of Studies of Long-term Exposure to PM2.5 and Mortality ......................... 42

Table A.2. Characterization of Studies of Long-term Exposure to PM10-2.5 and Mortality .................... 43

Table A.3. Characterization of Studies of Long-term Exposure to PM2.5 and Cardiovascular Effects.... 44

Table A.4. Characterization of Studies of Long-term Exposure to PM2.5 and Respiratory Effects.......... 45

Table A.5. Characterization of Studies of Long-term Exposure to PM2.5 and Reproductive and

Developmental Effects................................................................................................................................ 47

Table A.6. Characterization of U.S. and Canadian Studies of Short-Term Exposure to PM2.5 and

Mortality .................................................................................................................................................... 49

Table A.7. Characterization of U.S. and Canadian Studies of Short-Term Exposure to PM2.5 and

Respiratory Hospital Admissions and Emergency Department Visits........................................................ 50

Table A.8. Characterization of U.S. and Canadian Studies of Short-Term Exposure to PM10-2.5 and

Respiratory Hospital Admissions and Emergency Department Visits........................................................ 53

Table A.9. Characterization of U.S. and Canadian Studies of Short-Term Exposure to PM2.5 and

Cardiovascular Hospital Admissions and Emergency Department Visits.................................................. 53

Table A.10. Characterization of U.S. and Canadian Studies of Short-Term Exposure to PM2.5 and

Out of Hospital Cardiac Arrests.................................................................................................................. 56

Table A.11. Characterization of U.S. and Canadian Studies of Short-Term Exposure to PM2.5 and

Time of Stroke Symptom Onset ................................................................................................................. 56
v

List of Figures

Figure 2.1. All-cause mortality risk estimates, long-term exposure to PM2.5 in recent cohort studies. ....... 6

Figure 2.2. Cardiovascular mortality risk estimates, long-term exposure to PM2.5 in recent cohort

studies ........................................................................................................................................................... 7

Figure 2.3. Respiratory mortality risk estimates, long-term exposure to PM2.5 in recent cohort

studies.. ......................................................................................................................................................... 8

Figure 2.4. Percent increase in non-accidental and cause-specific mortality for a 10 μg/m3 increase in

24-h average PM2.5 concentrations in single-pollutant models from U.S. and Canadian studies............... 20

Figure 2.5. % Increase in respiratory-related hospital admissions and ED visits for a 10 μg/m3

increase in 24-h average PM2.5 concentrations in single-pollutant models from U.S. and Canadian

studies ......................................................................................................................................................... 25

Figure 2.6. Percent increase in cardiovascular-related hospital admissions and ED visits for a 10

μg/m3 increase in 24-h average PM2.5 concentrations in single-pollutant models from U.S. and

Canadian studies. ........................................................................................................................................ 29
vi

Authors, Contributors, Reviewers

Executive Direction

Dr. John Vandenberg (Director) – National Center for Environmental Assessment-RTP Division,

U.S. Environmental Protection Agency, Research Triangle Park, NC

Ms. Debra Walsh (Deputy Director) – National Center for Environmental Assessment-RTP

Division, U.S. Environmental Protection Agency, Research Triangle Park, NC

Dr. Mary Ross (Branch Chief) – National Center for Environmental Assessment, U.S.

Environmental Protection Agency, Research Triangle Park, NC

Principal Authors

Mr. Jason Sacks (Team Lead) – National Center for Environmental Assessment, U.S.

Environmental Protection Agency, Research Triangle Park, NC

Dr. Ellen Kirrane – National Center for Environmental Assessment, U.S. Environmental

Protection Agency, Research Triangle Park, NC

Dr. Thomas Luben – National Center for Environmental Assessment, U.S. Environmental

Protection Agency, Research Triangle Park, NC

Dr. Elizabeth Oesterling Owens – National Center for Environmental Assessment, U.S.

Environmental Protection Agency, Research Triangle Park, NC

Contributors

Ms. Laura Datko-Williams – Oak Ridge Institute for Science and Education Research Fellow,

National Center for Environmental Assessment, U.S. Environmental Protection Agency,

Research Triangle Park, NC

Reviewers

Dr. Dan Costa, Air, Climate, and Energy Research Program, Office of Research and

Development, U.S. Environmental Protection Agency, Research Triangle Park, NC

Dr. Aimen Farraj, National Health and Environmental Effects Research Laboratory, U.S.

Environmental Protection Agency, Research Triangle Park, NC

Dr. Ian Gilmour, National Health and Environmental Effects Research Laboratory, U.S.

Environmental Protection Agency, Research Triangle Park, NC

Ms. Beth Hassett-Sipple, Office of Air Quality Planning and Standards, U.S. Environmental

Protection Agency, Research Triangle Park, NC.
vii

Dr. Karen Martin, Office of Air Quality Planning and Standards, U.S. Environmental Protection

Agency, Research Triangle Park, NC.

Dr. Lucas Neas, National Health and Environmental Effects Research Laboratory, U.S.

Environmental Protection Agency, Research Triangle Park, NC

Mr. Steven Silverman, Office of General Council, U.S. Environmental Protection Agency,

Washington, D.C.

Dr. Lindsay Wichers Stanek, National Exposure Research Laboratory, U.S. Environmental

Protection Agency, Research Triangle Park, NC
viii

Executive Summary

In the proposed rule on the National Ambient Air Quality Standards for particulate matter

(PM), EPA committed to conduct a review and assessment of the numerous studies relevant to

assessing the health effects of PM that were published too recently to be included in the 2009

PM Integrated Science Assessment (ISA). This report presents the findings of EPA’s survey and

provisional assessment of such studies. EPA has screened and surveyed the recent literature and

developed a provisional assessment that places those studies of potentially greatest relevance to

the current PM NAAQS review in the context of the findings of the 2009 PM ISA. The focus is

on: (a) epidemiologic studies that used PM2.5 (i.e., fine PM) or PM10-2.5 (i.e., coarse PM) and were

conducted in the U.S. or Canada, and (b) toxicological or epidemiologic studies that compared

effects of PM from different sources, PM components, or size fractions. The provisional

assessment is not intended to critically review individual studies or integrate the scientific

findings to draw causal conclusions as is done for an ISA.

This survey and assessment finds that that the new studies expand the scientific

information and provide important insights on the relationships between PM exposure and health

effects of PM. However, the new information and findings do not materially change any of the

broad scientific conclusions regarding the health effects of PM exposure made in the 2009 PM

ISA. In brief, this report finds the following:

• Recent epidemiologic studies, most of which are extensions of earlier work, continue to

support the conclusions of the 2009 PM ISA for long-term exposure to PM2.5 and

mortality, cardiovascular effects, respiratory effects, and reproductive and

developmental effects. Notably, updated findings from the Harvard Six Cities and

American Cancer Society cohorts continue to observe an association between long-term

PM2.5 exposure and mortality, which supports the findings from previous studies

conducted in these cohorts. Additionally, a new Canadian multicity study observed

associations with mortality at long-term mean PM2.5 concentrations below those reported

in the PM ISA. Recent cause-specific mortality studies also provide more evidence for

cardiovascular mortality associations, especially in women, and additional evidence for

respiratory mortality including lung cancer. Studies of cardiovascular effects provide

evidence of myocardial infarction, hypertension, diabetes, and stroke, especially among

women, which is consistent with the conclusions of the 2009 PM ISA. Recent studies

continue to demonstrate associations with respiratory morbidity including respiratory

symptoms and hospital admissions, as well as incident asthma among children.

Reproductive and developmental effects studies continue to provide evidence for

associations between long-term exposure to PM2.5 and reduced birth weight.

• Recent epidemiologic studies have also continued to report associations between shortterm exposure to PM2.5 and mortality and morbidity health endpoints, which further

support the causality determinations presented in the 2009 PM ISA. These include multi-
ix

and single-city analyses that demonstrate consistent positive associations across all

respiratory and cardiovascular hospital admissions and emergency department visits as

well as cause-specific outcomes, particularly asthma. Although limited to single-city

studies, recent studies continue to demonstrate associations between short-term fine PM

exposures and nonaccidental and cardiovascular mortality. Additionally, new evidence

for stroke which focuses on assigning exposure from the time of stroke onset, instead of

entry to the hospital, provides new information regarding an uncertainty recognized in

the PM ISA.

• New toxicological and epidemiologic studies have continued to link health outcomes

with a range of PM2.5 sources and components. Several new epidemiologic analyses

continue to demonstrate health effects attributed to multiple sources and PM components

including combustion activities (e.g., motor vehicle emissions, coal combustion, oil

burning, power plants, and wood smoke/vegetative burning), crustal sources, and

secondary sulfate. Toxicological studies examined various source categories and found

that no source consistently showed the strongest association with cardiovascular health

effects. Additionally, an examination of a number of PM2.5 components found

associations with various components and both cardiovascular and respiratory endpoints.

• Only a few recent epidemiologic studies have examined health effects of short- and

long-term exposures to coarse particles (PM10-2.5). A short-term exposure and

respiratory emergency department visits (ED) visits study found a positive and

significant association with pediatric asthma ED visits in Atlanta, GA. One long-term

exposure and mortality study did not find any evidence of an association with all-cause

mortality though there was a positive but not statistically significant association with

coronary heart disease (CHD) mortality.
1

1. INTRODUCTION AND METHODOLOGY

EPA is currently in the final stages of the review of the National Ambient Air Quality Standards

(NAAQS) for particulate matter (PM). As described in more detail in the Federal Register Notice

of EPA’s proposed rule on the PM NAAQS (77 FR 38890), EPA has prepared the Integrated

Science Assessment for Particulate Matter (hereafter 2009 PM ISA) which reviewed,

summarized, and integrated the latest scientific knowledge useful in indicating the kind and

extent of all identifiable effects on public health or welfare that may be expected from the

presence of PM in the ambient air in varying quantities, as required by section 108 of the Clean

Air Act (CAA) (U.S. EPA, 2009). As noted in the PM proposal,1 EPA is aware that numerous

studies potentially relevant to assessing the health effects of ambient PM have been published

recently that were not included in the 2009 PM ISA (U.S. EPA, 2009). The proposal notice also

indicates the Agency’s intent to conduct a review and assessment of these new studies before a

final decision is made on the PM NAAQS. The purpose of this report is to present the findings of

EPA’s survey and provisional assessment of potentially relevant recent studies on the health

effects of PM exposure. This provisional assessment will inform a decision by the EPA

Administrator to proceed with final rulemaking or to revise the ISA to include the new studies. 

This provisional assessment is focused on those studies most important to the major conclusions

presented in the 2009 PM ISA and most relevant to the considerations of the current review of

the PM NAAQS. EPA, therefore, identified potentially relevant studies by applying the

following selection criteria to those studies published through August 2012: (1) epidemiologic

studies that used PM2.5 (i.e., fine PM) or PM10-2.5 (i.e., coarse PM) and were conducted in the U.S.

or Canada, and (2) toxicological or epidemiologic studies that compared effects of PM from

different sources, PM components, or size fractions. In addition, we considered studies identified

by public comments submitted to the docket of the proposed rule. Studies that met these criteria

were evaluated by EPA staff and their key findings were summarized. This preliminary

assessment was then developed to place those new studies of potentially greatest relevance in the

context of the findings of the 2009 PM ISA including a judgment as to whether the new studies

materially change the major conclusions of the 2009 PM ISA. The provisional assessment

presented here does not attempt to critically review individual studies or to provide the kind of

full integration found in a typical ISA. 

The literature search and submissions from public commenters found that more than 1,500

studies have been published since the ISA closed on the health effects of particulate matter.

 1 As stated in the PM NAAQS proposal: “The EPA is aware that a number of new scientific studies on the health 

effects of PM have been published since the mid-2009 cutoff date for inclusion in the Integrated Science 

Assessment. As in the last PM NAAQS review, the EPA intends to conduct a provisional review and assessment of 

any significant new studies published since the close of the Integrated Science Assessment, including studies that 

may be submitted during the public comment period on this proposed rule in order to ensure that, before making a 

final decision, the Administrator is fully aware of the new science that has developed since 2009. In this provisional 

assessment, the EPA will examine these new studies in light of the literature evaluated in the Integrated Science 

Assessment. This provisional assessment and a summary of the key conclusions will be placed in the rulemaking

docket.” (77 FR 38899)
2

Application of the selection criteria resulted in a list of over 100 studies that are summarized in

the main body of this report. Additional details of the air quality distributions observed in these

studies can be found in the annex to this report. The most significant studies are discussed in the

assessment, and where feasible, quantitative results are compared to those from the 2009 PM

ISA. A comprehensive list of studies identified as being potentially relevant through the survey

effort, including those studies not discussed in detail in this report can be found here:

http://hero.epa.gov/pm . Studies not discussed in detail include controlled human exposure

studies, and toxicological studies that examined health effects attributed to specific PM size

fractions, as well as studies that focused on ultrafine particles.

The overview in the main body of this report is organized into three main sections:

(1) epidemiologic studies on effects associated with long-term exposure to PM, focusing on

U.S. and Canadian studies with measurements of PM2.5 or PM10-2.5; (2) epidemiologic studies on

effects associated with short-term PM exposure, again focusing on U.S. and Canadian studies

with measurements of PM2.5 or PM10-2.5; and (3) toxicological and epidemiologic studies that

have evaluated health effects with exposure to PM components and PM from different sources.

This last section includes results of studies that assessed the effects of 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 components. Most studies have

focused on components or sources of PM2.5, but information related to sources of PM10-2.5 was

also included to the extent available. Unless otherwise noted, the majority of new studies

included in this assessment did not examine the robustness of single-pollutant results in

copollutants models.

2. OVERVIEW OF RECENT HEALTH STUDIES RESULTS

As stated in the 2009 PM ISA, EPA integrated the scientific evidence from toxicological,

controlled human exposure, and epidemiologic studies in combination with evidence from

atmospheric chemistry and exposure assessment studies and developed causal determinations for 

health outcomes categories (e.g., respiratory effects, cardiovascular effects, mortality, etc.) for

different exposure durations (i.e., short- or long-term) and PM size fractions. Causal judgments

drawn for short- and long-term exposure to PM2.5 and short-term exposure to PM10-2.5 are

included in Table 2.1.
3

Table 2.1. Causal Determinations for Short-and Long-Term Exposure to PM2.5

Long-term Exposure to PM2.5

Size Fraction Outcome Causality Determination

PM2.5

Cardiovascular Effects Causal

Respiratory Effects Likely to be causal

Mortality Causal

Reproductive and Developmental Suggestive

Cancer, Mutagenicity, and Genotoxicity Suggestive

Short-term Exposure to PM2.5

Size Fraction Outcome Causality Determination

PM2.5

Cardiovascular Effects Causal

Respiratory Effects Likely to be causal

Mortality Causal

Short-term Exposure to PM10-2.5

Size Fraction Outcome Causality Determination

PM10-2.5

Cardiovascular Effects Suggestive

Respiratory Effects Suggestive

Mortality Suggestive

The following sections of this document summarize the scientific evidence published since the

completion of the 2009 PM ISA for each of the health outcome categories presented in Table 2.1.

2.1. Epidemiologic Studies of Long-Term Exposure

The majority of the epidemiologic evidence evaluated in the 2009 PM ISA (U.S. EPA, 2009)

focused on health effects of PM2.5 exposure, with very limited evidence for health effects of

long-term exposure to PM10-2.5. These studies demonstrated consistent positive associations

between long-term PM2.5 exposures and a variety of health effects (Chapter 7, (U.S. EPA, 2009)).

Sections 2.1.1 - 2.1.4 highlight results from epidemiologic studies of mortality, cardiovascular

effects, respiratory effects, and reproductive and developmental effects, respectively, published

since the completion of the 2009 PM ISA (U.S. EPA, 2009) because these were the health

outcomes specifically taken into consideration in developing the proposed rule (77 FR 38890).

Tables A.1 through A.5 (Appendix A) summarize the recent epidemiologic studies that evaluated
4

relationships between health effects and long-term exposure to PM2.5 and PM10-2.5. The

discussions below emphasize results of studies conducted in the U.S. and Canada.

2.1.1. Mortality

Long-term exposure to PM2.5

Summary of 2009 PM ISA Conclusions

The 2009 PM ISA synthesized the epidemiologic literature characterizing the association

between long-term exposure to PM2.5 and increased risk of mortality and concluded that “a

causal relationship exists between long-term exposure to PM2.5 and mortality” (See Section 7.6

of the 2009 PM ISA). Long-term mean

2 PM2.5 concentrations ranged from 13.2 to 32.0 μg/m3

during the study periods in the areas in which these studies, comprising the entire body of

evidence reviewed in the 2009 ISA, were conducted. When evaluating cause-specific mortality,

the strongest evidence contributing to this causal determination was observed for associations

between PM2.5 and cardiovascular mortality. Positive associations were also reported between

PM2.5 and lung cancer mortality. Both the Harvard Six Cities (Laden et al., 2006; Dockery et al., 

1993) and the American Cancer Society (ACS) (Krewski, 2009; Pope III et al., 2004; Pope et al., 

2002) studies continued to provide strong evidence for the associations between long-term

exposure to PM2.5 and cardiopulmonary disease (CPD) and ischemic heart disease (IHD)

mortality. Additional evidence from a study that used the Women’s Health Initiative (WHI)

cohort (Miller et al., 2007) found a particularly strong association between long-term exposure to

PM2.5 and cardiovascular disease (CVD) mortality in post-menopausal women. 

Recent Mortality Studies

Since the completion of the 2009 PM ISA (U.S. EPA, 2009), a number of studies have been

published that examined the association between long-term exposure to PM2.5 and all-cause

mortality (See Figure 2.1) and cause-specific mortality (See Figures 2.2 and 2.3), including

updated results for both the Harvard Six Cities and ACS cohorts. Lepeule et al. (2012) extended

the analysis of the Harvard Six Cities cohort using 11 additional years of follow-up and PM2.5

monitoring data and explored a variety of issues that might affect the size and timing of the

mortality effect. Generally, the authors observed results similar to those reported by Laden et al.

(2006) for all-cause and cardiovascular mortality, though the central estimate was slightly

diminished and had slightly narrower confidence intervals (all-cause mortality: RR=1.14 [95%

CI: 1.07, 1.22]3 for Lepeule et al. (2012) versus RR=1.16 [95% CI: 1.07, 1.26] for Laden et al.

(2006); cardiovascular mortality: RR=1.26 [95% CI: 1.14, 1.40] for Lepeule et al. (2012) versus

RR=1.28 [95% CI: 1.13, 1.44] for Laden et al.(2006). The authors applied both spline and linear

 2 For long-term exposure studies, the long-term mean PM2.5 concentration refers to the average PM2.5 concentrations 

reported across the entire study duration, which could equate to the monthly or annual PM2.5 concentration averaged 

over many years.

3 All effect estimates for associations between long-term exposure to PM2.5 and mortality are presented for a 10

μg/m3 increase in PM2.5 concentration.
5

models to investigate the concentration-response relationship, and observed that for all-cause

mortality, the model fit was better without the spline, indicating a no threshold, linear

relationship with PM2.5 down to the lowest observed concentration (i.e., 8 μg/m3

). Jerrett et al.

(2009a) reanalyzed data from the ACS cohort, including data from 86 metropolitan statistical

areas (MSAs) across the U.S with monitoring data for PM2.5. The authors observed an

association between PM2.5 and all-cause mortality in single pollutant models (RR 1.048 [95% CI:

1.024, 1.071]) that increased in magnitude in a copollutant model adjusting for ozone (O3)

concentration (RR 1.080 [95% CI: 1.048, 1.113]). The associations were stronger when limited

to mortality due to cardiovascular disease (CPD mortality: RR 1.129 [95% CI: 1.094, 1.071];

CVD mortality: RR 1.150 [95% CI: 1.111, 1.191]; IHD mortality: RR 1.211 [95% CI: 1.156,

1.268]); these associations also became stronger in copollutant models adjusting for O3

concentration. No statistically significant association was observed between PM2.5 and

respiratory mortality in this re-analysis of the ACS cohort. In another analysis among the ACS

cohort, McKean-Cowdin et al. (2009) examined the association between long-term exposure to

PM2.5 and brain cancer mortality. The authors observed no associations with brain cancer

mortality.
6

Figure 2.1. All-cause mortality risk estimates, long-term exposure to PM2.5 in recent cohort studies. Red text and triangles represent

new studies published since the completion of the 2009 PM ISA.

Study

McDonnell et al. (2000)

Enstrom (2005)

Jerrett et al. (2005)

Krewski et al. (2009)

Puett et al. (2011)

Ostro et al. (2009)

Laden et al. (2006)

Lepeule et al. (2012)

Lipsett et al. (2011)

Jerrett et al. (2009)

Lipfert et al. (2006)

Eftim et al. (2008)

Hart et al. (2010)

Krewski et al. (2009)

Goss et al. (2004)

Puett et al. (2009)

Zeger et al. (2008)

Krewski et al. (2009)

Crouse et al. (2012)

Cohort

AHSMOG

CA Cancer Prevention

ACS-LA

ACS Reanalysis II - LA

Health Prof

CA Teachers

Harvard 6-Cities

Harvard 6-Cities

CA Teachers

ACS

Veterans Cohort

Medicare Cohort

US Trucking

ACS Reanalysis II

U.S. Cystic Fibrosis

Nurses Health

MCAPS

ACS Reanalysis II - NYC

Canadian National

Years

1973-1977

1973-1982

1983-2002

1973-2002

1982-2000

1982-2000

1986-2002

2002-2007

1974-1998

1974-2009

1999-2005

1982-2000

1989-1996

1997-2001

2000-2002

1985-2000

1982-2000

1999-2000

1992-2002

2000-2005

1982-2000

1991-2001

Mean

32

23.4

---

---

21

21

17.8

17

16.4

15.9

15.6

14.3

14.3

14.3

13.6

14.1

14.1

14.0

13.7

13.9

13.2

---

9.4

8.9

8.7

Notes

Males

Men

Women

Women

ACS Sites

6-Cities sites

Men

Women

65+, Eastern

65-74, Eastern

75-84, Eastern

85+, Eastern

65+, Central

65-74, Central

75-84, Central

85+, Central

65+, Western

65-74, Western

75-84, Western

85+, Western

11 cities; remote sensing

11 cities; monitoring data

Nationwide; remote sensing

►

All Cause

0.6 0.7 0.8 0.9 1 1.1 1.2 1.3 1.4 1.5 1.6

Effect Estimate
7

Figure 2.2. Cardiovascular mortality risk estimates, long-term exposure to PM2.5 in recent cohort studies. Red text and triangles

represent new studies published since the completion of the 2009 PM ISA. * As discussed in Federal Register Notice of EPA’s

proposed rule on the PM NAAQS (77 FR at 38929 and 38934 n. 82). CV = cardiovascular disease, CHD = coronary heart disease,

IHD = ischemic heart disease, CPD = cardiopulmonary disease.

Study

Pope et al. (2004)

Laden et al. (2006)

Lepeule et al. (2012)

Lipsett et al. (2011)

Jerrett et al. (2009)

Hart et al. (2010)

Miller et al. (2007)

Crouse et al. (2012)

Chen et al. (2005)

Puett et al. (2011)

Puett et al. (2009)

Gan et al. (2011)

Jerrett et al. (2005)

Krewski et al. (2009)

Pope et al. (2004)

Ostro et al. (2009)

Lipsett et al. (2011)

Jerrett et al. (2009)

Hart et al. (2010)

Krewski et al. (2009)

Crouse et al. (2012)

McDonnell et al. (2000)

Jerrett et al. (2005)

Krewski et al. (2009)

Ostro et al. (2009)

Jerrett et al. (2009)

Krewski et al. (2009)

Cause

CV

CHD

IHD

CPD

Cohort

ACS

Harvard 6-Cities

Harvard 6-Cities

CA Teachers

ACS

US Trucking

WHI

Canadian National

AHSMOG

Health Prof

Nurses Health

Vancouver, BC

ACS-LA

ACS Reanalysis II

ACS

CA Teachers

CA Teachers

ACS

US Trucking

ACS Reanalysis II

Canadian National

AHSMOG

ACS-LA

ACS Reanalysis II 

CA Teachers

ACS

ACS Reanalysis II

Years

1982-2000

1974-1998

1974-2009

1999-2005

1982-2000

1985-2000

1994-1998

1991-2001

1973-1998

1986-2002

1992-2002

1999-2002

1982-2000

1982-2000

1982-2000

2002-2007

1995-2005

1982-2000

1985-2000

1982-2000

1991-2001

1973-1977

1982-2000

1982-2000

2002-2007

1982-2000

1982-2000

Mean

17.1

16

15.9

15.6

14.3

14.1

13.5 (12.9)*

8.7

29

17.8

13.9

4.08

21

21

17.1

17

15.6

14.3

14.1

14.02

---

8.7

32

21

21

17

14.3

14.02

---

Notes

Women

Men

Females

Females

Males

Men

Women

Women

Women

Men

Nationwide

NYC

Males

Women

Nationwide

NYC

►

►

0.5 1 1.5 2 2.5

Effect Estimate
8

Figure 2.3. Respiratory mortality risk estimates, long-term exposure to PM2.5 in recent cohort studies. Red text and triangles represent

new studies published since the completion of the 2009 PM ISA.

Respiratory

Lung Cancer

Study

Laden et al. (2006)

Lipsett et al. (2011)

Jerret et al. (2009)

Hart et al. (2010)

McDonnell et al. (2000)

Jerrett et al. (2005)

Krewski et al. (2009)

Laden et al. (2006)

Lipsett et al. (2011)

Lepeule et al. (2012)

Hart et al. (2010)

Krewski et al. (2009)

Krewski et al. (2009)

Cohort

Harvard 6-Cities

CA Teachers

ACS

US Trucking

AHSMOG

ACS-LA

ACS Reanalysis II 

Harvard 6-Cities

CA Teachers

Harvard 6-Cities

US Trucking

ACS Reanalysis II

ACS Reanalysis II

Years

1974-1998

1999-2005

1982-2000

1985-2010

1973-1977

1982-2000

1982-2000

1974-1998

1999-2005

1974-2009

1985-2000

1982-2000

1982-2000

Mean

16

15.6

14.3

14.1

32

21

21

16

15.6

15.9

14.1

14.02

---

Notes

Women

Men

Males

LA

Women

Men

Nationwide

NYC

0.5 1 1.5 2 2.5

Effect Estimate
9

In an update to a study by Janes et al. (2007), Greven et al. (2011) used data from a nationwide

Medicare mortality cohort to develop a statistical approach for estimating the associations

between monthly mean PM2.5 concentrations averaged over the preceding 12 months and

monthly mortality rates among subjects living within ZIP codes with a geographic centroid

within a six mile radius of one of 814 monitoring stations from 2000 to 2006. The study authors

decomposed the association between PM2.5 and mortality into two components: (1) the

association between the “national” trend in the monthly PM2.5 concentrations averaged over the

previous 12 months and the national average trend in monthly mortality rates (purely temporal

association); and (2) the association between the “local” trend in the deviation in the

community-specific trend from the national average trend of monthly averages of PM2.5 and the

deviation of the community-specific trends from the national average trend of mortality rates

(residual spatio-temporal association). The authors posit that this second component provides

evidence as to whether locations having steeper declines in PM2.5 also have steeper declines in

mortality relative to the national trend. The authors conclude that differences in effect estimates

at these two spatiotemporal scales raise concerns about confounding bias in these analyses, with

the association for the national trend more likely to be confounded than the association for the

local trend. The authors observed no evidence for a “local” effect, but did observe evidence for a

“national” effect. Similar to the study by Janes et al. (2007), Greven et al. (2011) eliminate all of

the spatial variation in air pollution and mortality in their data set when estimating the “national”

effect, focusing instead on sub-chronic (monthly) temporal differences in the data. As noted by

the authors, this eliminates 90% of the variance in the data set used for these analyses that is

attributable to spatial variability (Janes et al. (2007), Table 1). Only 5% of the variance in the

data set used in these analyses is attributable to the space by time component, which was the

focus of the papers by Janes et al. (2007) and Greven et al. (2011). Thus, while the results of the

papers themselves provide evidence for an association between exposure to PM2.5 and mortality,

it is not possible to directly compare the results of these studies to the results of other cohort

studies investigating the relationship between long-term exposure to PM2.5 and mortality, which

make use of spatial variability in air pollution and mortality data. As noted by Pope and Burnett

(2007) and highlighted in the 2009 PM ISA (Section 7.6.1, (U.S. EPA, 2009)), the conclusions of

Janes et al. (2007) “largely excludes the sources of variability that are exploited in those other

[cohort] studies.” These comments are also applicable to the study by Greven et al. (2011).

Crouse et al. (2012) conducted a nationwide study of the relationship between long-term

exposure and PM2.5 in Canada and provide new evidence for a positive association at relatively

low concentrations of PM2.5. The authors investigated the association between long-term

exposure to ambient PM2.5 and non-accidental mortality. The level of ambient PM2.5 to which the

study population was exposed was estimated from satellite observations and assigned to the

cohort of 2.1 million Canadian adults that completed detailed census data in 1991. The study

included deaths between 1991 and 2001. The authors observed a hazard ratio (HR) of 1.15 (95%

CI: 1.13, 1.16) for non-accidental mortality. Using spatial random-effects models, the HR was

slightly diminished (1.10 [95% CI: 1.05, 1.15]). The strongest association was observed for
10

deaths due to ischemic heart disease (HR: 1.31 [95% CI: 1.27, 1.35]). Using spatial randomeffects models did not substantially change the association (HR: 1.30 [95% CI: 1.18, 1.43]). The

associations between PM2.5 and deaths due to CVD and circulatory diseases were similar in

magnitude to that observed for non-accidental mortality. There was a weaker association with

mortality due to cerebrovascular disease (CBD) (HR: 1.04 [95%CI; 0.99, 1.10]). Sensitivity

analyses including 11 Canadian cities with ground-based PM2.5 measurements produced similar

associations to those observed in the full cohort that utilized satellite observations to estimate

PM2.5 exposure (See Figure 2.1).

A number of studies have looked at the association between long-term exposure to ambient

PM2.5 and all-cause mortality among different occupational cohorts. Hart et al. (2010) examined

the association between residential exposure to PM2.5 and mortality among men in the U.S.

trucking industry. The authors observed a 10% (95% CI: 2.5, 18) increase in all-cause mortality. 

This association was stronger when the cohort was restricted to truck drivers that maintained

local routes, and long haul drivers were excluded (15% increase [95% CI: 5.0, 26.6] for all-cause

mortality; 59.7% increase [95% CI: 18.7, 114.9%] for respiratory mortality). The associations for

other causes of death (i.e., lung cancer, CVD, IHD, chronic obstructive pulmonary disease

[COPD]) were generally positive, but were not statistically significant. Puett et al. (2009)

examined the relationship of long-term PM2.5 exposures with all-cause mortality among women

from the Nurses’ Health Study. The authors found an increased risk of all-cause mortality (HR

1.26 [95% CI: 1.02, 1.54]) and coronary heart disease (CHD) mortality (HR 2.02, 95% CI: 1.07,

3.78) associated with long-term exposure to PM2.5. More recently, Puett et al. (2011) used the

same spatiotemporal exposure estimation models to characterize the association between longterm exposure to PM2.5 and mortality among male subjects in the Health Professionals Follow-up

Study. In this cohort, long-term exposure to PM2.5 was not associated with all-cause or CHD

mortality. Ostro et al. (2010) examined the association between long-term exposures to PM2.5 and

all-cause, CPD, IHD and pulmonary disease mortality among the subjects from the California

Teachers Study. No associations were observed between all-cause mortality and PM2.5. There

was a positive association between long-term exposure to PM2.5 and CPD mortality (HR: 1.19

[95% CI: 1.05, 1.37]) and IHD mortality (HR: 1.56 [95% CI: 1.24, 1.94]). In a follow-up study,

Lipsett et al. (2011) examined the associations between long-term exposure to PM2.5 and allcause and cause-specific mortality among the subjects in the California Teachers Study. The

authors did not observe an association between long-term exposure to PM2.5 and all-cause

mortality in this cohort, but observed an association with IHD mortality (HR 1.20 [95% CI: 1.02,

1.41]). They also observed positive associations for respiratory mortality and CBD mortality,

though these associations were not statistically significant.

In a single-city study conducted in Toronto, Ontario, Canada, Jerrett et al (2009b) examined the

association between long-term exposure to PM2.5 and all-cause mortality among subjects from a

respiratory clinic. The authors observed positive, though not statistically significant associations

with all-cause, circulatory or respiratory mortality. A limited number of deaths in the cohort and

low variability in PM2.5 concentrations (limiting the exposure contrast) led the authors to
11

conclude that “no definitive conclusions [could] be drawn about these associations with PM2.5”. 

In a single-city study conducted in Vancouver, British Columbia, Canada, Gan et al. (2011)

conducted a population-based cohort study to evaluate the association between traffic-related

pollutants and risk of mortality due to CHD. Land-use regression models were used to estimate

exposure over a 5 year period (1994-1998) and the cohort was followed up for 4 years (1999-

2002). Exposure to PM2.5 was weakly associated with CHD mortality.

Recent studies that examined the association between long-term PM2.5 exposure and mortality

further support the conclusions of the 2009 PM ISA. The strongest evidence for mortality was

from the Harvard Six Cities (Laden et al., 2006; Dockery et al., 1993) and American Cancer

Society cohorts (Krewski, 2009; Pope III et al., 2004; Pope et al., 2002), which was supported by

a number of other cohort studies. Updated results from the Harvard Six Cities (Lepeule et al., 

2012) and American Cancer Society (Jerrett et al., 2009a) cohorts support the findings of the

2009 PM ISA, while a new Canadian multicity study (Crouse et al., 2012) observed associations

below those reported in the PM ISA (i.e., < 10 μg/m3

). In the 2009 PM ISA, for cause-specific

mortality, the strongest evidence was for cardiovascular-related mortality, particularly among

post-menopausal women (Miller et al., 2007). Respiratory-related mortality was also observed,

particularly for lung cancer mortality (Naess et al., 2007). Recent studies provide more evidence

for strong associations with cardiovascular-related mortality among women (Lipsett et al., 2011; 

Puett et al., 2009) and additional evidence for respiratory mortality including lung cancer

mortality (Lepeule et al., 2012).

Long-term exposure to PM10-2.5

Summary of 2009 PM ISA Conclusions

The 2009 PM ISA synthesized the epidemiologic literature characterizing the association

between long-term exposure to PM10-2.5 and increased risk of mortality and concluded that the

evidence was too limited to adequately characterize the associations for PM10-2.5. The findings

from the AHSMOG (Chen et al., 2005) and Veterans (Lipfert et al., 2006) cohort studies

provided limited evidence for associations between long-term exposure to PM10-2.5 and mortality

in areas with mean concentrations in the range of 16 to 25 μg/m3

. Overall, the evidence was

determined to be inadequate to determine if a causal relationship exists between long-term

exposure to PM10-2.5 and mortality (See Section 7.6 of the 2009 PM ISA). Recent studies

published since the completion of the 2009 PM ISA are characterized in Table A.1.

Recent Mortality Studies

Since the completion of the 2009 PM ISA, Puett et al. (2009) examined the relationship of longterm exposure to PM10-2.5 with all-cause and CHD mortality among women from the Nurses’

Health Study. The authors did not find an association between PM10-2.5 and the risk of all-cause

mortality (HR 1.03 [95% CI: 0.89, 1.18]). The association between PM10-2.5 and CHD mortality

was positive, but not statistically significant (HR: 1.14 [95% CI: 0.73, 1.77]). More recently,

Puett et al. (2011) used the same spatiotemporal exposure estimation models to characterize the
12

association between PM10-2.5 and mortality among male subjects in the Health Professionals

Follow-up Study. In this cohort, long-term exposure to PM10-2.5 was not associated with all-cause

or CHD mortality.

In summary, two new studies (Puett et al., 2011; Puett et al., 2009) evaluated the association

between long-term exposure to PM10-2.5 and mortality. The long-term mean PM10-2.5

concentrations reported in these studies were lower than those reported in the 2009 PM ISA (7.7

and 10.1μg/m3

, respectively). These studies do not provide any additional evidence for an

association between long-term exposure to PM10-2.5 and mortality that would be sufficient to

materially change conclusions made in the 2009 PM ISA.

2.1.2. Morbidity – Cardiovascular Effects

Summary of 2009 PM ISA Conclusions

The 2009 PM ISA concluded that “the evidence from epidemiologic and toxicological studies is

sufficient to conclude that a causal relationship exists between long-term exposures to PM2.5 and

cardiovascular effects.” The strongest evidence was provided by large, multicity, U.S.-based

studies of cardiovascular mortality (See Section 7.2.10 of the 2009 PM ISA) with supporting

evidence from a U.S.-based epidemiologic study (Miller et al. (2007)) that reported associations

between PM2.5 and incident stroke and myocardial infarction (MI) among post-menopausal

women at mean PM2.5 concentrations of 13.5 μg/m3

.

4

Recent Cardiovascular Morbidity Studies

Several new studies of long-term exposure to PM2.5 and cardiovascular disease were conducted

since the completion of the 2009 PM ISA. In a study of male subjects enrolled in the Health

Professionals Follow-Up Study, Puett et al. (2011) used spatiotemporal models to estimate

exposure to PM2.5 by combining data from available air monitoring networks with geographic

information system (GIS) derived variables such as distance to roadway and elevation. The

authors reported no association between long-term PM2.5 and total CVD or ischemic stroke;

however, in fully adjusted models (i.e. adjusted for covariates including body mass index (BMI),

hypertension, hypercholesterolemia, diabetes, family history of MI, smoking physical activity,

diet) elevated HRs for non-fatal MI and hemorrhagic stroke were observed (HR: 1.16 [95% CI:

0.81, 1.64] and 1.69 [95%CI: 0.59, 3.71])

5

. Associations of PM2.5 with all-cause mortality and

fatal CHD were not observed in this all male cohort. A cross-sectional study of male and female

patients attending a pulmonary clinic after reporting respiratory complaints reported no

associations of long-term PM2.5 exposure with prevalent IHD, although an association with

nitrogen dioxide (NO2) was reported (Beckerman et al., 2012). Interactions among exposures,

risk factors and potential confounders were tested and no statistically significant effect modifiers

 4 Listed as 12.9 μg/m3 for the reasons stated in Federal Register Notice of EPA’s proposed rule on the PM NAAQS

(77 FR 38934 n. 82). 5 All effect estimates for associations between long-term exposure to PM2.5 and cardiovascular morbidity are

presented for a 10 μg/m3 increase in PM2.5 concentration.
13

were identified. A study using satellite derived aerosol optical depth (AOD) measurements to

predict PM2.5 concentrations, reported a 3.12% (95% CI: 0.30, 4.29) increase in cardiovascular

hospital admission among older adults for an increase in long-term PM2.5 exposure (Kloog et al., 

2012a). A similar increase in risk was reported for stroke hospital admissions (3.49 [95% CI:

0.09, 5.18]).

The stronger evidence linking long-term PM2.5 exposure with cardiovascular disease was

apparent in studies of women as originally demonstrated in the 2009 PM ISA. In a study of

female teachers residing in California, Lipsett et al. (2011) used concentration data from 1999-

2000 and applied inverse distance weighted interpolation techniques to develop monthly PM2.5

concentration surfaces from ambient monitor data. This study reported an increased risk for

incident stroke (HR: 1.15 95% CI 1.00-1.33), which was highest among post-menopausal

women, but no association between PM2.5 and incident MI (HR: 0.99 95% CI 0.84-1.15). This

study supports the findings of Miller et al. (2007) linking incident stroke to long-term PM2.5

exposure among post-menopausal women; however, they also reported an association with

incident MI. Coogan et al. (2012) followed African American women who ranged in age from 21

to 69 years at enrollment in the Black Women’s Health Study for 10 years to investigate incident

hypertension and diabetes in association with long-term exposure to PM2.5. PM2.5 concentrations

were spatially interpolated using monitoring data from state and local stations in the Los Angeles

basin for the year 2000. This study reported an increased risk of incident hypertension (IRR: 1.48

95%CI: 0.95-2.31) . This risk was attenuated, but remained positive in a copollutant model

containing NO2 (IRR: 1.32 95%CI: 0.84-2.05).

Several studies have been published from the Multi-Ethnic Study of Atherosclerosis (MESA)

that was designed to inform on mechanistic pathways by which PM2.5 exposure may act on the

cardiovascular system. Long-term PM2.5 exposure was associated with increased prevalent QT

prolongation (OR: 1.6 95% CI: 1.2-2.2) and intraventricular conduction delay (OR: 1.7 95% CI

1.0-2.6) (Van Hee et al., 2011). In addition, both long- and short-term PM2.5 exposure was

associated with a narrowing of retinal vessel diameter (Adar et al., 2010). Reductions in flowmediated dilation have been observed in association with short-term exposures to PM2.5 (See

Section 6.2.4 of the PM ISA); however, O’Neill et al. (2011) found no association of long-term

PM2.5 exposure with chronic arterial stiffness. 

Generally, the results of recent studies are consistent with the evidence for an association

between long-term exposure to PM2.5 and cardiovascular morbidity characterized in the 2009 PM

ISA. Findings on incident stroke reported by Miller et al (2007) in a cohort of post-menopausal

women are supported by a new study of female teachers (Lipsett et al., 2011), while a recent

study of black women reports an association between PM2.5 and incident hypertension (Coogan 

et al., 2012) at long-term mean PM2.5 concentrations ranging from 15.6 – 21.5 μg/m3 (Table

A.3).
14

2.1.3. Morbidity – Respiratory Effects

Summary of 2009 PM ISA Conclusions

The epidemiologic evidence reviewed in the 2009 PM ISA demonstrated associations between

long-term exposure to PM2.5 and decrements in lung function growth, increased respiratory

symptoms, and asthma development in study locations with mean PM2.5 concentrations ranging

from 13.8 to 30 μg/m3 during the study periods (See Sections 7.3.1.1 and 7.3.2.1 of the 2009 PM

ISA). These studies contributed to a body of evidence that was sufficient to conclude that “a

causal relationship is likely to exist between long-term exposures to PM2.5 and respiratory

effects.”

Recent Respiratory Morbidity Studies

Since the completion of the 2009 PM ISA, a number of studies have been published that examine

the association between long-term exposure to PM2.5 and respiratory outcomes (Table A.4). 

These recent studies are consistent with the associations observed for respiratory outcomes

reported in the 2009 PM ISA and provide additional evidence for associations between long-term

exposure to PM2.5 and respiratory symptoms and asthma development. For example, in a recent

prospective community intervention study in Libby, MT (Noonan et al., 2012) ambient PM2.5

concentrations decreased by 26.7% over four winters following the replacement of over 1,100

wood stoves in the community with new lower emission wood stoves or other heating sources. 

This decrease in PM2.5 concentrations was associated with decreases in reported wheeze and

respiratory infections (including colds, bronchitis, influenza and throat infection) among school

children. These results suggest that beneficial health impacts are associated with decreases in

ambient PM2.5 concentrations. 

A number of other studies evaluated the association between long-term exposure to PM2.5 and

respiratory symptoms. Several nationwide U.S. studies that used data from the National Health

Interview Survey reported associations between long-term exposure to PM2.5 and respiratory

symptoms among children (including respiratory allergy/hay fever (Parker et al., 2009), and

respiratory allergy and frequent ear infections (Bhattacharyya and Shapiro, 2010) and adults

(including asthma among African-Americans (Nachman and Parker, 2012); sinusitis (Nachman 

and Parker, 2012; Bhattacharyya, 2009); and hay fever (Bhattacharyya, 2009). Meng et al.

(2010) examined long-term exposure to PM2.5 in the San Joaquin Valley of California and

weekly asthma symptoms among participants with physician-diagnosed asthma. They observed

associations between annual average concentrations of PM2.5 and frequent asthma symptoms. In

a study conducted in New York City, Patel et al. (2009) examined long-term exposure to PM2.5

and respiratory symptoms in children through 24 months of age. Long-term exposure to PM2.5

was not associated with wheeze or cough in this study, though several PM2.5 constituents were

associated with wheeze and/or cough (see Section 2.4.2 for results on PM2.5 constituents).

A substantial body of evidence exists that has evaluated short-term exposure to PM2.5 and

emergency department visits and hospitalizations for respiratory causes (See Section 2.2.2.1). 
15

Several recent studies have evaluated the association between long-term exposure to PM2.5 and

respiratory hospitalizations. Karr et al. (2009a; 2009b) examined exposure to PM2.5 averaged

over an infant’s lifetime (0-12 months) and did not observe an association between PM2.5 and

bronchiolitis hospitalizations in the Puget Sound Region of Washington (Karr et al., 2009a) or in

the Georgia Air Basin of British Columbia, Canada (Karr et al., 2009b). Kloog et al. (2012a)

investigated hospital admissions for all respiratory causes among residents of New England 65

years of age and older. The authors observed a 4.22% (95% CI 1.06, 4.75)6 increase in

respiratory hospital admissions associated with long-term PM2.5 concentrations. Similarly,

Neupane et al. (2010) restricted their analyses of pneumonia hospitalizations to those 65 years of

age and older and found that long-term exposure to PM2.5 was associated with hospitalization for

community-acquired pneumonia (OR 13.64, 95% CI: 1.79, 101.01). Meng et al. (2010)

examined long-term exposure to PM2.5 in the San Joaquin Valley of California and asthmarelated emergency department visits or hospitalizations (analyzed together) among participants

with physician-diagnosed asthma. They observed associations between annual average

concentrations of PM2.5 and emergency department visits and hospitalizations.

The 2009 PM ISA identified a number of prospective cohort studies that provided evidence of an

association between long-term exposure to PM2.5 and the development of asthma. Recent studies

contribute to this weight of evidence, reporting results that are consistent with those summarized

in the 2009 PM ISA. Akinbami et al. (2010) conducted a nationwide U.S. study with data on

children (ages 3-17 years) from the National Health Interview Survey and observed a positive

association between county-wide annual average PM2.5 concentration and current asthma (OR

1.43, 95% CI: 0.98, 2.10 comparing highest quartile of exposure to lowest) and/or a recent

asthma attack (OR 1.30, 95% CI: 0.89, 1.90 comparing highest quartile of exposure to lowest). 

Two studies examining the relationship between long-term exposure to PM2.5 and incident

asthma were conducted in British Columbia, Canada. Carlsten et al. (2011) evaluated birth year

exposure to PM2.5 and physician-diagnosed asthma at age 7 and observed an association with an

increased risk of incident asthma. Similarly, Clark et al. (2010) assigned exposure based on

average PM2.5 concentration during the first week of life and the association with incident asthma

between ages 3 and 4. The authors did not observe an association between PM2.5 and incident

asthma. McConnell et al. (2010) characterized the relationship between childhood incident

asthma and long-term exposure to PM2.5 among the Southern California Children’s Health Study

participants. In this cohort, asthma-free kindergarten and first-grade children were followed up

for three years and the authors observed a positive association (HR 1.34, 95% CI: 0.95, 1.90),

though this association was diminished when the authors adjusted for traffic related pollution

concentrations measured near the child’s home and school.

In summary, the results of recent studies generally continue to demonstrate an association

between long-term exposure to PM2.5 and respiratory morbidity. Recent epidemiologic studies

 6 All effect estimates for associations between long-term exposure to PM2.5 and respiratory morbidity are presented

for a 10 μg/m3 increase in PM2.5 concentration.
16

reported associations with respiratory symptoms and respiratory hospitalizations. New findings

on incident asthma among children are consistently positive, though not statistically significant.

These recent studies demonstrate associations at long-term mean PM2.5 concentrations ranging

from 9.7 to 27 μg/m3 (Table A.4).

2.1.4. Morbidity – Reproductive and Developmental Effects

Summary of 2009 PM ISA Conclusions

The 2009 PM ISA synthesized the epidemiologic literature characterizing the association

between long-term exposure to PM2.5 and increased risk of reproductive and developmental

effects and concluded that the evidence was suggestive of a causal relationship between longterm exposure to PM2.5 and reproductive and developmental outcomes (See Section 7.4 of the

2009 PM ISA). The strongest evidence was for reduced birth weight and infant mortality,

especially due to respiratory causes during the post-neonatal period. The mean PM2.5

concentrations during the study periods ranged from 5.3 – 27.4 μg/m3

, with effects becoming

more precise and consistently positive in locations with mean PM2.5 concentrations of 15 μg/m3

and above. The epidemiologic literature did not consistently report associations between longterm exposure to PM2.5 and preterm birth, growth restriction, birth defects or decreased sperm

quality. 

Recent Reproductive and Developmental Outcome Studies

Since the completion of the 2009 PM ISA, a number of studies have been published that examine

the association between long-term exposure to PM2.5 and reproductive and developmental

outcomes (Table A.5). These recent studies are consistent with the associations observed for

reproductive and developmental outcomes reported in the 2009 PM ISA, within similar

concentrations (long-term mean PM2.5 concentrations ranging from 11.0 – 19.8 μg/m3

), and

provide additional evidence for associations between long-term exposure to PM2.5 and reduced

birth weight (Ghosh et al., 2012; Kloog et al., 2012b; Kumar, 2012; Darrow et al., 2011b; Bell et 

al., 2010; Morello-Frosch et al., 2010; Salihu et al., In Press). Recent evidence remains

inconsistent for the association between exposure to PM2.5 and preterm birth, with some studies

providing evidence for an association (Chang et al., 2012b; Wu et al., 2009), while others did not

(Rudra et al., 2011; Darrow et al., 2009). 

2.2. Epidemiologic Studies of Short-Term Exposure

The 2009 PM ISA included the results of many new epidemiologic studies reporting associations

between short-term exposure to PM and a range of health outcomes. The epidemiologic evidence

evaluated in the ISA contributed to the determination that there is sufficient evidence to conclude

that “a causal relationship exists” between short-term PM2.5 exposure and cardiovascular effects

and mortality, and a “likely to be causal relationship exists” between short-term PM2.5 exposure

and respiratory effects (Chapter 2, 2009 PM ISA). Additionally, the epidemiologic evidence
17

contributed to a “suggestive” causal determination for short-term PM10-2.5 exposure and

cardiovascular and respiratory effects, and mortality (Chapter 2, 2009 PM ISA).

Sections 2.2.1 and 2.2.2 highlight results from recent epidemiologic studies. Tables A.6 through

A.11 (Appendix A) summarize results of recent epidemiologic studies that evaluated

relationships between health effects and short-term exposure to PM2.5 and PM10-2.5.

The 2009 PM ISA included a particular focus on results of multicity studies due to their

evaluation of a wide range of PM exposures and large numbers of observations, which lead to

generally more precise effects estimates than most smaller scale studies of single cities. The

multicity studies also allowed investigation of homogeneity or heterogeneity of PM health

relationships, evaluation of confounding by co-pollutants across communities with different air

pollution mixtures, and assessment of potential effect modifiers. Since the completion of the

2009 PM ISA, numerous multicity analyses have been published that evaluate morbidity

outcomes.

2.2.1. Mortality

Summary of 2009 PM ISA Conclusions

Overall, in the evaluation of multi- and single-city studies in the 2009 PM ISA and in the 2004

PM Air Quality Criteria Document (AQCD) (U.S. EPA, 2004) consistent positive associations

were observed at mean 24-h average7 PM2.5 concentrations above 12.8 μg/m3

. This collective

evidence contributed to the conclusion that “a causal relationship exists between short-term

PM2.5 exposure and mortality.” Building on the evidence presented in the 2004 PM AQCD (U.S. 

EPA, 2004), multi- and single-city studies evaluated in the 2009 PM ISA reported consistent

positive associations between short-term PM10-2.5 exposure and mortality (Section 6.5.2.3, 2009

PM ISA).

Recent Mortality Studies

Several recent studies evaluated the effects of short-term exposure to PM2.5 on mortality in single

city analyses. No new multi-city studies have been published. Additionally, no new studies have

been published that examined associations between short-term PM10-2.5 exposure and mortality in

the U.S. or Canada.

New studies have continued to report associations between PM2.5 and mortality that are

consistent with the conclusions of the 2009 PM ISA as shown in Figure 2.4. Two of these studies

were conducted in New York City. Ito et al. (2011a) examined the relationship between shortterm exposure to PM2.5 and PM components and cardiovascular disease (CVD) mortality for the

population ≥ 40 years old in New York City for the years 2000-2006. PM2.5 was associated with

CVD mortality at lag 1 in the all-year and cold season (October-March) analyses, but the

strongest association with CVD mortality was observed during the warm season (April-

 7 For short-term exposure studies the mean 24-h avg PM2.5 concentration refers to the mean of all daily 24-h avg 

PM2.5 concentrations over the course of the study duration.
18

September) at lag 0 and 1. Also in New York City, Chang et al. (2012a) used a novel approach to

examine the relationship between short-term exposure to PM2.5 concentrations and

cardiorespiratory mortality. The authors used a spatio-temporal deterministic model that was

bias-corrected with monitoring data to predict daily PM2.5 concentrations. The authors developed

a statistical model to consider personal exposure to PM2.5 from outdoor sources to improve

exposure assessment. Using data from 2001-2005, positive associations were observed for those

greater than 65 years old. The model that accounted for personal exposure found a higher risk of

mortality (2.32% [95% CI: 0.68, 3.94] at lag 1)8 compared to a model that used only PM2.5

concentrations (1.13% [95% CI: 0.27, 2.00]) suggesting that risk estimates derived using ambient

concentrations as a proxy for exposure are biased towards the null. 

Additional single-city analyses were conducted in Seattle, Detroit, and Atlanta. Zhou et al.

(2011) conducted a study using daily PM2.5 data collected in Seattle and Detroit to examine the

effect of short-term PM2.5 exposure on all-cause, cardiovascular, and respiratory mortality for the

years 2002-2004. In a distributed lag model of 0-2 days, a strong association was observed

between PM2.5 and all-cause and cardiovascular mortality, with some evidence of an association

with respiratory mortality in Detroit during the warm season (April-September) (quantitative

results not presented). There was no evidence of an association with PM2.5 and any mortality

outcome in Seattle in the warm season. In the cold season (October-March), the strongest

associations were for all-cause and cardiovascular mortality in Seattle, while there was no

evidence of an association between PM2.5 and any mortality outcome in Detroit. Interestingly the

magnitude of the cardiovascular mortality association in Seattle in the cold season is larger than

that in Detroit in the warm season even though mean PM2.5 concentrations are lower, 11.4 μg/m3

and 14.9 μg/m3, respectively. Klemm et al. (2011) conducted an extended analysis of two

previously published studies (Klemm et al., 2004; Klemm and Mason, 2000) that examined the

effect of air pollution on mortality in Atlanta, GA. This analysis included an additional 7.5 years

of data and expanded the study location to include two additional counties. Focusing on deaths in

individuals 65 years of age and older, the authors found a positive association between shortterm PM2.5 exposure and nonaccidental (0.78% [95% CI: -0.43, 2.0]; lag 0-1 for a 10 μg/m3

increase in 24-h avg PM2.5 concentrations) and cardiovascular mortality (0.83% [95% CI: -1.1,

2.8]), but no evidence of an association with respiratory mortality (-0.86% [95% CI: -4.4, 2.8]).

In summary, multi- and single-city studies evaluated in the 2009 PM ISA provided evidence of

consistent positive associations between short-term PM2.5 exposure and nonaccidental,

cardiovascular, and respiratory mortality. Relatively few mortality studies have been published

in the U.S. and Canada since the completion of the 2009 PM ISA and they are limited to singlecity studies. These studies continue to demonstrate evidence of positive associations between

short-term PM2.5 exposures and mortality in the same range of concentrations as those studies

 8 All effect estimates for associations between short-term exposure to PM2.5 and mortality are presented for a 10

μg/m3 increase in PM2.5 concentration.
19

included in the 2009 PM ISA (i.e., mean 24-h avg concentrations of 12.8 μg/m3 and above in the

multi-city studies).
20

Figure 2.4. Percent increase in non-accidental and cause-specific mortality for a 10 μg/m3 increase in 24-h average PM2.5

concentrations in single-pollutant models from U.S. and Canadian studies. Red text and triangles represent recent studies published

since the completion of the 2009 PM ISA. Results presented from single-pollutant models for purposes of comparing results across

studies that included different mixes of copollutants. 

Study

Tsai et al. (2000)

Moolgavkar (2003)

Ostro et al. (2006)

Klemm et al. (2004)

Ito (2003)

Klemm et al. (2011)

Franklin et al. (2007)

Franklin et al. (2008)

Klemm and Mason (2003)

Fairley (2003)

Burnett and Goldberg (2003)

Zanobetti and Schwartz (2009)

Burnett et al. (2004)

Slaughter et al. (2005)

Villeneuve et al. (2003)

Chock et al. (2000)

Dominici et al. (2007a)

Tsai et al. (2000)

Dominici et al. (2007)

Chang et al. (2012)

Ostro et al. (1995)

Moolgavkar (2003)

Ostro et al. (2006)

Ostro et al. (2007)

Ito (2003)

Lipfert et al. (2000)

Klemm et al. (2011)

Holloman et al. (2004)

Franklin et al. (2007)

Franklin et al. (2008)

Klemm and Mason (2003)

Ito et al. (2011) 

Zanobetti and Schwartz (2009)

Mar et al. (2003)

Fairley (2003) 

Wilson et al. (2007)

Villeneuve et al. (2003)

Ostro et al. (1995)

Moolgavkar (2003)

Ostro et al. (2006)

Ito (2003)

Klemm et al. (2011)

Franklin et al. (2007)

Franklin et al. (2008)

Klemm and Mason (2003)

Zanobetti and Schwartz (2009)

Fairley (2003)

Villeneuve et al. (2003)

Nonaccidental

Cardio-respiratory

Cardiovascular

Respiratory

Location

Newark, NJ

Camden, NJ

Elizabeth, NJ

Los Angeles, CA

9 California counties Atlanta, GA

Detroit, MI

Atlanta, GA

27 U.S. cities

25 U.S. cities

6 U.S. Cities Santa Clara County, CA 8 Canadian Cities

112 U.S. cities 12 Canadian cities Spokane, WA

Vancouver, CAN

Pittsburgh, PA

Pittsburgh, PA

100 U.S. cities

Newark, NJ

Camden, NJ

Elizabeth, NJ

100 U.S. cities

New York, NY

Southern California

Los Angeles, CA

9 California counties

9 California counties Detroit, MI

Philadelphia, PA Atlanta, GA

7 NC counties

27 U.S. cities

25 U.S. cities

6 U.S. Cities

New York, NY

112 U.S. cities

Phoenix, AZ

Santa Clara County, CA Phoenix, AZ

Vancouver, CAN

Southern California

Los Angeles, CA

9 California counties Detroit, MI

Atlanta, GA

27 U.S. cities

25 U.S. cities

6 U.S. Cities

112 U.S. cities Santa Clara County, CA Vancouver, CAN

Age

All 

All 

All 

All 

All

65+

All 

65+

All 

All 

All 

All 

All 

All

All

All

65+

< 75

75+

All 

All 

All 

All 

All

65+

All

All

All

All 

All

All

65+

> 16

All 

All 

All

40+

All

All

All

> 25

65+

All

All

All

All

65+

All 

All 

All

All

All

65+

Lag

0

0

0

1

0-1

0-1

3

0-1

1

0-1

0-1

0

1

0-1

1

1

0

0

0

1

0

0

0

1

1

0

1

0-1

3

1

1

0-1

0

1

0-1

0-1

1

0-1

1

0

0-5

0

0

1

0-1

0

0-1

0-1

1-2

0-1

0-1

0

0 ►

◄ ►

Mean

42.1

39.9

37.1

22.0*

19.9

19.6

18.0

17.0

15.6

14.8

14.7

13.6

13.3

13.2

12.8

10.8

7.9

---

---

---

42.1

39.9

37.1

--- 13.3-17.5

32.5

22.0*

19.9

18.4

18.0

17.3

17.0

~15.6

15.6

14.8

14.7

14.4

13.2

13.0

13.0

13.0

7.9

32.5

22.0*

19.9

18.0

17.0

15.6

14.8

14.7

13.2

13.0

7.9

98th

---

---

---

---

---

---

---

45.8

43.0

---

59.0

38.9

34.3

38.0

29.6

---

---

---

---

---

---

---

---

---

---

---

---

---

---

---

---

---

45.8

43.0

---

---

34.3

---

25-88 31.6

---

---

---

---

---

---

45.8

43.0

---

34.3

---

---

| | |

-5.0 -3.0 -1.0 1.0 3.0 5.0 7.0 9.0 11.0 13.0 15.0

% Increase
21

2.2.2. Morbidity

2.2.2.1. Associations between Short-Term Exposures to PM and Respiratory

Morbidity

Summary of 2009 PM ISA Conclusions

The association between short-term PM2.5 exposure and respiratory-related emergency

department (ED) visits, hospital admissions, and physician visits was evaluated in Section 6.3.8

of the 2009 PM ISA (U.S. EPA, 2009). The numerous multi- and single-city studies evaluated

reported consistent positive associations with respiratory ED visits and hospital admissions for

COPD, asthma, and respiratory infection in study areas with mean 24-h average PM2.5

concentrations ranging from 6.1 – 22 μg/m3

. However, associations for asthma were imprecise

and not consistently positive when limiting analyses to children. The evidence from respiratoryrelated emergency department (ED) visits, hospital admissions, and physician visits studies

contributed to the conclusion that a “causal relationship is likely to exist between short-term

exposures to PM2.5 and respiratory effects.”

Additional epidemiologic studies evaluated in the 2009 PM ISA examined associations between

short-term PM10-2.5 exposure and respiratory hospital admissions and ED visits. This limited

number of studies demonstrated consistent positive associations with respiratory-related hospital

admissions and ED visits with the strongest evidence in children. The evidence from these

studies in combination with the evidence from toxicological and controlled human exposure

studies led to the conclusion that the collective evidence across disciplines “is suggestive of a

causal relationship between short-term exposures to PM10-2.5 and respiratory effects.”

Recent Respiratory Hospital Admission Studies

Within this section, respiratory-related hospital admissions and ED visit studies are discussed

separately. This is because ED visits for respiratory-related outcomes often represent less

serious, but more common health effects. Additionally, only a small percentage of respiratoryrelated ED visits result in a hospital admission. Therefore, it is important to discuss the evidence

for each respiratory-related health outcome separately.

Respiratory-related Hospital Admissions

A number of studies published since the completion of the 2009 PM ISA conducted multicity or

multi-location analyses to examine the association between short-term PM2.5 exposures and

respiratory hospital admissions. Figure 2.5 summarizes the evidence from single-pollutant

models from studies evaluated in the 2009 PM ISA as well as recent studies published since its

completion. Bell et al. (2012) represented a consolidated and more detailed account of a number

of previous publications, of which most were discussed in the 2009 PM ISA (Bell et al., 2009a; 

Bell et al., 2009b; Bell et al., 2008; Bell et al., 2007). In an all-year analysis of 187 U.S. counties,

short-term exposure to PM2.5 was positively associated with respiratory hospital admissions in

individuals 65 years of age and older across lags of 0 to 2 days, with the strongest association at
22

lag 2 (0.41% [95% CI: 0.09, 0.74])9. In seasonal analyses, the association at lag 2 was

consistently positive across seasons, but the strongest association was at lag 0 (1.05% [95% CI:

0.29, 1.82]) in the winter season with the largest magnitude of an effect in the Northeast region.

Of note the Northeast region comprised 53% of all counties included in the analysis. In an

additional analysis using this data (Bell et al., 2009a), there was no evidence of a reduction in the

association between PM2.5 and respiratory hospital admissions when accounting for air

conditioning use. In a multi-city study conducted in the New England region of the U.S., Kloog

et al. (2012a) examined associations between short-term PM2.5 exposure and respiratory hospital

admissions in individuals 65 years of age and older. To estimate exposure the authors developed

a novel prediction model that combined land use regression with physical measurements from

satellite aerosol optical depth. The authors observed a 0.70% (95% CI: 0.35, 1.05) increase in

respiratory hospital admissions for lags days 0-1. The results obtained using the novel approach

presented (i.e., 0.70% increase in respiratory hospital admissions) were consistent with the

percent increase in respiratory hospital admissions observed in a traditional time-series analysis

(i.e., 1.51%).

In addition to the multicity studies presented above, a few single city studies were conducted in

the U.S. that examined asthma and acute bronchitis. Silverman and Ito (2010) conducted a study

to evaluate the effect of short-term PM2.5 and O3 exposure on asthma hospital admissions, both

general and those that required a stay in the intensive care unit (ICU) in New York City.

Analyses focused on four age groups (i.e., <6, 6-18, 19-49, and 50+) and were limited to the

warm season (April-August). Positive associations were observed for each age group and for all

ages combined when considering general asthma hospital admissions, with the strongest

association for the age group 6-18 (15.5% [95% CI: 9.1, 22.0] at lag 0-1). When limiting the

analysis to ICU asthma admissions, again the strongest association was for the age group 6-18

(21.1% [95% CI: 8.3, 35.5]). The observed associations remained robust in copollutant models

with O3. The authors also examined the shape of the concentration-response (C-R) relationship

using linear, smooth functions, which allowed for a possible nonlinear relationship. This analysis

found evidence that the linear fit is a reasonable approximation of the relationship between shortterm PM2.5 concentrations and asthma hospital admissions. Grineski et al. (2011) primarily

focused on examining the effect of dust and low wind events on asthma and acute bronchitis

hospital admissions in El Paso, TX; however, since daily PM2.5 data were available the authors

also examined associations between short-term PM2.5 exposures and each respiratory health

effect. The authors found that PM2.5 was positively, but weakly associated with asthma

(OR=1.02 [95% CI: 0.96, 1.09]) and acute bronchitis (OR=1.01 [95% CI: 0.92, 1.12]) hospital

admissions.

 9 All effect estimates for associations between short-term exposure to PM2.5 and morbidity are presented for a 10

μg/m3 increase in PM2.5 concentration.
23

Recent Respiratory-related ED Visits Studies

Of the recent studies identified that focused on short-term exposures to PM2.5 and respiratoryrelated ED visits the majority consisted of single-city studies. However, a couple large, multicity studies were conducted in the U.S. and Canada. Zanobetti et al. (2009) examined the

association between short-term PM2.5 exposure and respiratory ED visits in individuals 65 years

of age and older in 26 U.S. communities. In an all-year analysis, PM2.5 was strongly associated

with respiratory ED visits (2.1 [95% CI: 1.2, 3.0] at lag 0-1), while in seasonal analyses positive

associations were observed across seasons with the strongest association in the spring (4.3%

[95% CI: 2.2, 6.5]). Stieb at al. (2009) conducted a study in 7 Canadian cities to examine the

effect of air pollution on ED visits for multiple respiratory-related health outcomes including

asthma, COPD, and respiratory infection. The authors found no evidence of an association

between short-term PM2.5 exposure and COPD ED visits at any of the single-day lags examined.

In all-year analyses, positive associations were observed for asthma with the magnitude of the

association decreasing as lag day increased (i.e., the strongest association was observed at lag 0,

2.1% [95% CI: -3.0, 7.5]). However, in a warm season analysis (April-September), the

magnitude of the association between PM2.5 and asthma was nearly 4 times higher (9.3% [95%

CI: 6.3, 12.5]).

A couple of single city studies were also conducted that examined all respiratory, multiple

respiratory effects, or asthma ED visits. Darrow et al. (2011a) examined the association between

short-term air pollution exposure and respiratory ED visits in Atlanta using various exposure

metrics (i.e., 1-h max, 24-h avg, Commute (0700-1000, 1600-1900 hours), Day-time (0800-1900

hours), and Night-time (2400-0600 hours). PM2.5 (lag 1) was positively associated with

respiratory ED visits across exposure metrics, with the magnitude ranging from 0.2% to 0.4%. 

Kim et al. (2011) examined the associations between short-term PM2.5 exposure and hospital

admissions in Denver, CO. The authors found no evidence of an association with all respiratory

(-0.44% [95% CI: -5.6, 5.4]), COPD or pneumonia hospital admissions (quantitative results only

presented for all respiratory). However, there was evidence of a delayed effect of PM2.5 on

asthma hospital admissions with effects not occurring until approximately lag day 4.

A number of studies focused on ED visits and hospital admissions for asthma. Strickland et al.

(2010)conducted an analysis in Atlanta using the same air quality data as Darrow et al. (2011a)

to examine the association between air pollution and pediatric (ages 5-17) asthma ED visits.

PM2.5 was strongly associated with pediatric asthma ED visits in both all-year (2.2% [95% CI:

0.2, 4.2] at lag 0-2) and warm season (4.7% [95% CI: 1.7, 7.6]) analyses. The magnitude of the

association was robust to the inclusion of O3 in the model. An examination of the C-R

relationship through a quintile analysis and a loess C-R analysis using lag 0-2 day PM2.5

concentrations found evidence of increased risk of pediatric asthma ED visits down to relatively

low ambient concentrations (i.e., mean 24-h avg concentrations < 14 μg/m3). In Tacoma, WA,

Mar et al. (2010) also examined the association between short-term PM2.5 exposure and asthma

ED visits. Individual lag days of 0 to 5 days were examined with the strongest association
24

occurring at lag 2 (5.7% [95% CI: 1.4, 10.1]). Li et al. (2011) examined the C-R relationship

between short-term PM2.5 exposures and asthma ED visits in children 2 to 18 years of age in

Detroit. Associations were examined in both a time-series and time-stratified case-crossover

study design assuming: (1) no deviation from linearity and (2) a change in linearity at 12 μg/m3.

In the analyses assuming linearity, similar effect estimates were observed in both models for a 0-

4 day lag, (time series: RR=1.03 [95% CI: 1.00, 1.07]; case-crossover: OR=1.04 [95% CI: 1.01,

1.07]). In the models assuming a deviation from linearity at 12 μg/m3, the authors reported

slightly larger effect estimates, compared to the linear model, for asthma ED visits in the timeseries (RR=1.07 [95% CI: 1.03, 1.11]; lag 0-4) and case-crossover analyses (OR=1.06 [95% CI:

1.03, 1.09]; lag 0-4), respectively. Glad et al. (2012) conducted a study in Pittsburgh, PA that

found PM2.5 to be positively associated with asthma ED visits in analyses of all ages and ages 18

to 64 for single lag days and the average of 0-5 days (i.e., all ages: OR=1.04 [95% CI: 0.98, 1.10]

and 18 to 64: OR=1.053 [95% CI: 0.99, 1.12] at lag 0-5). Additionally, when stratifying by race

there was some evidence for larger effects in African Americans compared to Caucasian

Americans.
25

Figure 2.5. Percent (%) Increase in respiratory-related hospital admissions and ED visits for a 10 μg/m3 increase in 24-h average

PM2.5 concentrations in single-pollutant models from U.S. and Canadian studies. Red text and triangles represent recent studies

published since the completion of the 2009 PM ISA. * ED visit studies. ** Median concentration.

Study

Ostro et al. (2009)

Peel et al. (2005)

Tolbert et al. (2007)

Darrow et al. (2011)*

Zanobetti et al. (2009)

Bell et al. (2008)

Slaughter et al. (2005)

Kloog et al. (2012)

Kim et al. (2012)

Fung et al. (2006)

Chen et al. (2005)

Peel et al. (2005)*

Ito et al. (2007)*

Sheppard et al. (2003)

Strickland et al. (2010)*

NYS DOH (2006)*

NYS DOH (2006)*

Li et al. (2011)*

Glad et al. (2012)*

Silverman and Ito (2010)

Grineski et al. (2011)

Mar et al. (2010)*

Slaughter et al. (2005)*

Stieb et al. (2009)*

Chimonas & Gessner (2006)

Grineski et al. (2011)

Peel et al. (2005)*

Lin et al. (2005)

Dominici et al. (2006)

Stieb et al. (2009)*

Chimonas & Gessner (2006)

Location

6 CA Counties

Atlanta, GA

Atlanta, GA

Atlanta, GA

26 U.S. communities

202 U.S. counties

Spokane

New England

Denver, CO

Vancouver

Vancouver

Atlanta, GA

New York, NY

Seattle, WA

Atlanta, GA

Bronx, NY

Manhattan, NY

Detroit, MI

Pittsburgh, PA

New York, NY

El Paso, TX

Tacoma, WA

Spokane, WA

7 Canadian cities

Anchorage, AK

El Paso, TX

Atlanta, GA

Ontario, CAN

204 U.S. counties

7 Canadian cities

Anchorage, AK

Age

0-19

All

All

All

65+

65+

All

65+

All

65+

65+

All

All

All

5-17

All

All

2-18

All

All

1+

All

All

All

0-19

1+

All

< 15

65+

All

0-19

Lag

3

0-2 

0-2

1

0-1

2

1

0-1

0-14 DL

0-2

0-2 

0-2

0-1

0

0-2

0-4

0-4

0-4

0-5

0-1

0-3

2

1

0

0

0-3

0-3

0-3

2

0

0

►

◄

◄

All Respiratory

Asthma

Bronchitis

Respiratory Infection

Mean

19.4

19.2

17.1

16.0

15.3

12.9

10.8

9.6

8.0

7.7

7.7

19.2

---

16.7

16.4

15.0

15.0

15.0

13.3

13.0**

12.8

12.3

10.8

6.7-9.8

6.1

12.8

19.2

9.6

13.3

6.7-9.8

6.1

98th

---

---

---

---

---

34.2

29.6

---

---

---

---

---

---

46.6

---

---

---

---

---

---

---

---

29.6

---

---

---

---

---

34.8

---

---

-15.0 -10.0 -5.0 0.0 5.0 10.0 15.0 20.0

% Increase
26

The 2009 PM ISA evaluated a number of multi- and single-city studies that found consistent

positive associations with all and cause-specific respiratory hospital admissions and ED visits,

specifically COPD and respiratory infections in study areas with mean 24-h PM2.5 concentrations

ranging from 6.1 – 22.0 μg/m3

. Additionally, there was evidence for asthma hospital admissions

and ED visits, but the effects were not consistent in children. Recent multi- and single-city

studies have continued to demonstrate consistent positive associations for all respiratory-related

hospital admissions and ED visits, and provide additional evidence for increases in asthma

hospital admissions and ED visits. The associations observed in the new studies occur in

locations with mean concentrations similar (i.e., mean 24-h avg concentrations ranging from 6.7

– 16.4 μg/m3

) to those studies included in the 2009 PM ISA.

The 2009 PM ISA also found evidence that associations between short-term PM10-2.5 exposures

and respiratory-related hospital admissions and ED visits were strongest among children. A

recent study by Strickland et al. (2010) that examined the association between short-term PM10-

2.5 exposure and pediatric asthma ED visits in Atlanta, GA further supports this conclusion.

Positive associations were observed in both all-year (5.8% [95% CI: 1.9, 9.9] at lag 0-2) and

seasonal analyses, with the strongest association in the cold season (7.0% [95% CI: 1.7, 12.7]).

An examination of the C-R relationship in both quintile and smooth estimates of the

concentration-response provided evidence of associations at relatively low ambient

concentrations for all pollutants, including PM10-2.5 (i.e., mean 24-h avg concentrations < ~12

μg/m3

)..

2.2.2.2. Associations between Short-Term Exposures to PM and

Cardiovascular Morbidity

Summary of 2009 PM ISA Conclusions

The associations between short-term PM2.5 exposure and cardiovascular-related hospital

admissions and ED visits was evaluated in Section 6.2.10 of the 2009 PM ISA (U.S. EPA, 2009).

Epidemiologic studies that examined the effect of PM2.5 on cardiovascular ED visits and hospital

admissions reported consistent positive associations (predominantly for IHD and congestive

heart failure [CHF]) in study areas with mean 24-h average concentrations ranging from 7.0 – 18

μg/m3

. This evidence contributed to the conclusion that “a causal relationship exists between

short-term PM2.5 exposure and cardiovascular effects.”

Epidemiologic studies of the association of short-term PM10-2.5 exposure with cardiovascular

hospital admissions and ED visits were also evaluated in the 2009 PM ISA, and the evidence

from these studies contributed to the conclusion that the evidence “is suggestive of a causal

relationship between short-term exposures to PM10-2.5 and cardiovascular effects.

Recent Cardiovascular-related Hospital Admissions/ED Visits Studies

Recent multi-city and multi-location studies, as well as single-city studies, add to the collective

body of evidence that examined associations between short-term PM2.5 exposure and

cardiovascular-related hospital admissions and ED visits evaluated in the 2009 PM ISA. Figure
27

2.6 summarizes the results from single-pollutant models from studies evaluated in the 2009 PM

ISA as well as recent studies published since its completion. No new studies have been published

that examined the association between short-term PM10-2.5 exposure and cardiovascular hospital

admissions or ED visits in the U.S. or Canada.

In a recent Health Effects Institute (HEI) report, Bell et al. (2012) compiled findings from

several multicity analyses of Medicare data (older adults, ≥ 65 years of age) for 204 counties

across the U.S. (some analyses included fewer counties). Although additional detail is provided

in the HEI report, these analyses were largely included in the 2009 PM ISA (Bell et al., 2008; 

Dominici et al., 2006). In an analysis using the same data, Bell et al. (Bell et al., 2009a) found a

higher prevalence of central air conditioning was associated with a decrease in the risk of PM2.5 -

associated hospitalization for cardiovascular disease.

Recent studies are consistent with the evidence assessed in the 2009 PM ISA. In a time-series

analysis of Medicare records for older adults ≥65 years of age in 26 US communities for 2000-

2003, Zanobetti et al. (2009) reported increases in hospital admissions for all CVD (1.89%

95%CI: 1.34 to 2.45), MI (2.25% 95%CI: 1.10 to 3.42) and CHF (1.85% 95%CI: 1.19 to 2.51;

lag 0-1). Although the largest excess risks were observed in the spring, statistically significant

excess risks were also observed in the winter. In a time-series analysis of hospital admissions in

seven Canadian cities, a 17% (95%CI: 0 to 37%) increase in hospital admissions for heart failure

was observed at lag 0 (Stieb et al., 2009). Weak, nonsignificant associations were observed

between PM2.5 and dysrhythmia and MI hospitalizations.

In a study of emergency hospitalizations among New York City residents ≥ 40 years of age, Ito

et al. (2011a) reported an excess risk of 1.0% (95% CI: 0.40, 1.6, lag 0). The excess risk was

stronger in the cold season (1.1% [95% CI 0.2 to 2.0]). These results were not sensitive to the

choice of method used to control temperature. Using a subset of these emergency hospitalization

data, Mathes et al. (2011) defined two cardiovascular syndromes from a database containing text

descriptions of the chief complaint reported by the patient upon admission to the hospital. This

study reported that PM2.5 was associated with both cardiac and more general cardiovascular

syndromes. In case-crossover analysis of cardiovascular disease admissions across New York

state from 2001 to 2005, Haley et al. (2009) found a 3.9% increase in heart failure admissions

per 10 μg/m3 increase in PM2.5 (lag 0-2). A case-crossover study of atrial fibrillation

hospitalizations between 1993 and 2008 in Utah (Wasatch Front) reported consistently positive,

but non-significant, associations across all lags examined in the study (lag 0 through 21 day

moving average) (quantitative results not provided) (Bunch et al., 2011). Finally, a 1.03% (95%

CI: 0.69, 1.34) increase in cardiovascular admissions was reported in a time-series study of

hospitalizations across New England among older adults (65 years) with predicted PM2.5

concentrations using satellite-derived AOD measurements (Kloog et al., 2012b).
28

Acute Stroke

Wellenius et al. (2012) examined the association of PM2.5 with neurologist-confirmed ischemic

stroke in predominately white female patients admitted to the Beth Israel Deaconess Medical

Center (BIDMC) in Boston from 1999 to 2008. Time of stroke symptom onset (exact or

estimated) was available for most patients included in the study. The OR of stroke onset was

1.30 (95% CI: 1.08 to 1.58) per 10 μg/m3 increase in PM2.5 in the previous 24 hours. Authors

report a 34% (95% CI: 13 to 58) higher risk of ischemic stroke during the previous 24 hours in

an analysis comparing moderate PM2.5 exposure (≥15 μg/m3

) to good (<15 μg/m3) exposure, as

defined by EPA’s Air Quality Index (AQI). These results were confirmed in an additional

analysis conducted by Mostofsky et al. (2012) using a subset of the data (i.e., 2003-2008) used

by Wellenius et al. (2012). Mostofsky et al. (2012) found a 22.7% (95% CI: 3.1, 47.0) increase in

ischemic stroke onset for an increase in PM2.5 over the previous 24 hours.

Out of Hospital Cardiac Arrests

The small number of studies of out-of-hospital cardiac arrest included in the 2009 PM ISA

reported mixed results. A recent time series analysis of cardiac arrests in New York City reported

an increased risk of 1.06 (95%CI 1.02, 1.10, lag 0-1) per 10 μg/m3 increase in PM2.5 (Silverman 

et al., 2010). Case cross-over analysis of the same data produced a result that was similar in

magnitude but did not reach statistical significance. The association with cardiac arrest was

stronger in the warm season (1.09 95% CI: 1.03-1.15) compared to the cold season (1.01 95% CI

0.95 to 1.07).

In summary, the 2009 PM ISA found consistent positive associations between short-term PM2.5

exposures and all and cause-specific cardiovascular hospital admissions and ED visits,

specifically IHD and CHF in study areas with mean 24-h PM2.5 concentrations ranging from 7.0

– 18.0 μg/m3. New multi- and single-city studies further support associations with all

cardiovascular hospital admissions and ED visits at mean 24-h PM2.5 concentrations ranging

from 6.7 – 15.3 μg/m3. Additional support for associations between short-term PM2.5 exposures

and cardiovascular effects comes from a new study of stroke onset (Wellenius et al. (2012)).
29

Figure 2.6. Percent increase in cardiovascular-related hospital admissions and ED visits for a 10 μg/m3 increase in 24-h average PM2.5

concentrations in single-pollutant models from U.S. and Canadian studies. Red text and triangles represent recent studies published

since the completion of the 2009 PM ISA. * ED visit studies. ** Median concentration. a = study only presented mean age of

participants.

Study

Metzger et al. (2004)

Tolbert et al. (2007)

Zanobetti et al. (2009)*

Ito et al. (2011)

Bell et al. (2008)

Slaughter et al. (2005)

Kloog et al. (2012)

Kim et al. (2012)

Burnett et al. (1999)

Ito (2003)

Metzger et al. (2004)

Dominici et al. (2006)

Pope et al. (2006)

Zanobetti et al. (2009)*

Sullivan et al. (2005)

Peters et al. (2001)

Zanobetti & Schwartz (2005)

Stieb et al. (2009)*

Burnett et al. (1999)

Ito (2003)

Metzger et al. (2004)*

Symons et al. (2006)

Zanobetti et al. (2009)*

Dominici et al. (2006)

Haley et al. (2009)

Pope et al. (2008)

Stieb et al. (2009)*

Metzger et al. (2004)*

Dominici et al. (2006)

Kloog et al. (2012)

Szyszkowicz et al. (2012)*

All CVD

IHD

MI

CHF

CBVD

Hypertension

Location

Atlanta, GA

Atlanta, GA

26 U.S. Communities

New York, NY

202 U.S. Counties

Spokane, WA

New England

Denver, CO

Toronto, CAN

Detroit, MI

Atlanta, GA

204 U.S. Counties

Utah Valley, UT

26 U.S. Communities

King County, WA

Boston, MA

Boston, MA

7 Canadian cities

Toronto, CAN

Detroit, MI

Atlanta, GA

Baltimore, MD

26 U.S. Communities

204 U.S. Counties

New York State

Utah

7 Canadian cities

Atlanta, GA

204 U.S. Counties

New England

Edmonton, CAN

Age

All

All

65+

40+

65+

All

65+

All

All

65+

All

65+

All

65+

21-98

61.6a

65+

All

All

65+

All

All

65+

65+

All

All

All

All

65+

65+

All

Lag

0-2

0-2

0-1

0

0

1

0-1

0-2 DL

0-1

1

0-3

0-2 DL

0

0-1

24 h

24 h

0

0

0-2

1

0-2

2

0-1

0

0-2

0-13 DL

0

0-2

0

0-1

0-3

◄

◄

►

Mean

17.8

17.1

15.3

14.4

12.9

10.8

9.6

8.0

18.0

18.0

17.8

13.3

10.1-11.3

15.3

12.8

12.1

11.1**

6.7-9.8

18.0

18.0

17.8

16.0

15.3

13.3

11.1-15.5

10.8

6.7-9.8

17.8

13.3

9.6

8.5

98th

---

---

---

---

34.2

29.6

---

---

---

---

---

34.8

---

---

---

28.2

---

---

---

---

---

---

---

34.8

---

44.5

---

---

34.8

---

---

-4.0 -2.0 0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 16.0 18.0 20.0 22.0 24.0 26.0 28.0 30.0 32.0

% Increase
30

2.3. Health Effects Related to Sources or Components of PM

Summary of 2009 PM ISA Conclusions

The 2009 PM ISA evaluated epidemiologic, toxicological, and controlled human exposure

studies that examined health effects associated with ambient PM components and sources. These

studies used a variety of quantitative methods and examined a broad set of PM components

(Section 6.6), and found evidence of health effects from sources and components associated with

a number of combustion activities (e.g., motor vehicle emissions, coal combustion, oil burning,

power plants, and wood smoke/vegetative burning), crustal sources, and secondary sulfate. As a

result, the ISA concluded that “the evidence is not yet sufficient to allow differentiation of those

components or sources that are more closely related to specific health outcomes.” These

conclusions are consistent with those presented in the 2004 PM AQCD where the studies

evaluated found evidence of health effects attributed to a number of source types, including

motor vehicle emissions, coal combustion, oil burning, and vegetative burning.

Recent Studies of Health Effects Related to Sources or Components of PM

Recent studies have continued to examine whether specific PM components or sources are more

closely related to specific health outcomes. For the purposes of this provisional assessment of

new literature published since the release of the 2009 PM ISA, emphasis has been placed on

studies that investigated the health effects related to PM sources or comparisons of various PM

components. To highlight the scientific content of the recent literature while focusing on key PM

study categories, this section focuses on results of studies that evaluated the effects of a range of

sources or components. Thus, the discussion includes: (1) recent epidemiologic studies using

source apportionment; (2) epidemiologic evidence on effects with PM components; and (3)

results of new toxicological studies using source apportionment with exposures to concentrated

ambient particles (CAPs) to provide insight into potential effects related to PM from different

sources, and comparative toxicology studies using fine PM components. In addition, numerous

epidemiologic and/or toxicology studies have reported effects of several ultrafine PM as

discussed in the 2009 PM ISA. Specific findings for ultrafine PM are not discussed in detail;

instead, the available new studies are included in the reference list: http://hero.epa.gov/pm .

2.3.1. Epidemiologic Studies Using Source Apportionment

Lall et al. (2011) examined the association between source-specific daily PM2.5 mass and

component data and hospital admissions in New York City for the years 2001-2002. The use of

daily data allowed for the examination of both single-day lags and a distributed lag. Source

categories identified through positive matrix factorization included long-range transported

sulfates, traffic, residual oil, steel metal works dust, and soil. In single-day lag models, total

respiratory hospital admissions were positively associated with residual oil at lag 2, but the

strongest associations were with steel metal works dust at lag 0 and 3. For cardiovascular

hospital admissions the strongest associations were observed with traffic at lag 0 and residual oil

at lag 3. When examining associations between cause-specific cardiovascular and the traffic
31

source category, the strongest associations were observed at lag 0 for total cardiovascular, heart

failure, and stroke. For associations between cause-specific respiratory hospital admissions and

the steel source category, pneumonia was associated with steel metal works dust at lag 3, while

asthma was observed to have the largest magnitude of an association across all lags. The

distributed lag model demonstrated a stronger association between traffic and cardiovascular

hospital admissions and steel metal works dust and respiratory hospital admissions than the

single-day lag models, indicating that single-day lags may underestimate the magnitude of

associations. Finally, a sensitivity analysis using key tracers of each source (i.e., elemental

carbon for traffic and manganese for steel metal works) found similar patterns of associations as

the source-specific analyses.

2.3.2. Epidemiologic Studies on Effects of Fine PM Components and Sources

In addition to examining the association between short-term PM2.5 exposures and mortality or

hospital admissions and ED visits a number of studies also attempted to identify if an individual

PM component or group of PM components could explain the observed association. The

following section describes the results from these studies some of which have been

aforementioned.

Short-term exposure to PM2.5 components and sources and mortality

In addition to examining the association between short-term exposure to PM2.5 and mortality, a

few single-city studies also examined the effect of individual PM2.5 components on mortality. Ito

et al. (2011a) focused on key PM components (i.e., elemental carbon [EC], organic carbon [OC],

sulfate [SO4], nickel [Ni], vanadium [V], zinc [Zn], silicon [Si], selenium [Se], sodium [Na], and

bromine [Br]) identified in previous source apportionment studies conducted in NYC. In all-year

analyses, the strongest associations were observed at lag 1 for EC, OC, SO4, Si, Se, and Br. In

the warm season, strong associations were observed for secondary aerosols including OC and

SO4, Se, which is associated with transported coal emissions, EC, and Br. In the cold season, the

components associated with residual oil burning, Ni, V, and Zn, all showed a similar pattern of

associations, with the strongest effects at lag 3. Overall, the components representing regional

transport showed a seasonal pattern of associations similar to those found with PM2.5 mass, while

associations were found throughout the year with EC and NO2. 

Zhou et al. (2011) examined the association between PM components with all-cause,

cardiovascular, and respiratory mortality in seasonal analyses in Seattle and Detroit. The

components selected for analysis represent the major emissions sources of the two cities: soil

(aluminium [Al] and Si), smelter effluents (iron [Fe] and Zn), residual oil burning (Ni and V),

coal burning (sulfur [S]), traffic (EC), sea salt (Na), and wood burning (potassium [K]). Daily

component data was available in both cities, which allowed for the examination of a 0-2 day

distributed lag. In Detroit, S was associated with all-cause and cardiovascular mortality and S

and Ni were moderately associated with respiratory mortality in the warm season. No

components were positively associated with any mortality outcome in the cold season in Detroit.
32

In Seattle, in the warm season no component was significantly associated with any mortality

outcome, but Fe, K, and EC were positively associated with respiratory mortality. In the cold

season, Al, K, Si, Zn, and EC were strongly associated with all-cause mortality, with the same

components, minus Al, strongly associated with cardiovascular mortality. No components were

associated with respiratory mortality in Seattle in the cold season. Overall, in Detroit the

components associated with mortality are indicative of coal burning while in Seattle the

components associated with mortality represent cold-season traffic and combustion sources, such

as residual oil and wood burning.

In the study conducted by Klemm et al. (2011) in Atlanta, daily concentrations of the PM

components EC, OC, nitrate [NO3], and SO4 were also available for the entire study duration.

The authors found that EC, OC, and NO3 were positively associated with nonaccidental mortality

at lag 0-1 in individuals 65 years of age and older, with the strongest association for NO3. In

analyses of cause-specific mortality, a similar pattern of associations was observed for

cardiovascular and respiratory mortality. SO4 was not found to be associated with any of the

mortality outcomes examined.

Respiratory-related Hospital Admissions and ED Visits

Recent multicity studies were identified that examined the effect of PM components on the

relationship between short-term PM exposure and respiratory-related ED visits and hospital

admissions. Zanobetti et al. (2009) conducted a second-stage analysis, using the same

methodology as Franklin et al. (2008) (2009 PM ISA; p. 6-193-195) and examined whether

season and community-specific long-term mean seasonal concentration ratios of PM components

to PM2.5 total mass modified the association between short-term PM2.5 concentrations and

respiratory ED visits. Of the components examined only Na+ and Ni were found to modify the

association between PM2.5 and respiratory ED visits. Using a different approach, Levy et al.

(2012) attempted to identify if some PM components are more toxic than others by focusing on

the four components that dominate PM2.5 mass and are highly correlated with PM2.5 (i.e., EC,

OC, SO4, and NO3). In a time-series analysis using Medicare data from 119 U.S. counties the

authors examined the association between each component and respiratory hospital admissions

across the U.S. and regionally (i.e., East and West). Of the components examined, only EC and

OC were positively associated with respiratory hospital admissions.

A few single-city studies were also identified that examined associations between respiratoryrelated ED visits and hospital admissions and individual PM components. Strickland et al. (2010)

focused on the PM components SO4, EC, OC, and water-soluble metals. For each component

positive associations were observed with pediatric asthma ED visits in all-year analyses. The

strongest associations were observed in the warm season with the magnitude being similar across

components. In addition, analyses including copollutant adjustment were conducted using warm

season data. Risk estimates for PM2.5, EC, and SO4 were attenuated, but remained positive when

including O3 in the model. In LOESS C-R analyses, there was evidence of a positive C-R

relationship for each component. Kim et al. (2011) examined the lag structure of associations
33

between the PM components EC, OC, SO4, and NO3 and respiratory hospital admissions. The

authors focused on these components because they comprise the majority of PM2.5 mass in

Denver. Consistent with the PM2.5 results, there was no evidence of an association with COPD or

pneumonia and any of the components. For both all respiratory and asthma hospital admissions

there was evidence of greater effects with EC and OC compared to SO4 and NO3, and additional

evidence for delayed effects occurring 2 to 5 days after exposure.

Cardiovascular-related Hospital Admissions and ED Visits

The 2009 PM ISA included multicity analyses of the effect of PM2.5 components on

cardiovascular hospital admissions that reported associations between oil combustion and trafficrelated PM2.5 and CVD hospitalizations.

Two recent studies investigated the association of PM2.5 components with cardiovascular

hospital admissions. Using Medicare data from 26 US communities, Zanobetti et al. (2009)

examined the modification of the associations of PM2.5 with CVD, MI and CHF hospital

admissions by season- and community-specific PM2.5 composition. Authors estimated the

relative contribution of specific components (EC, OC, SO4, NO3, Na, Ni, V, Zn, Si, Se, Br) by

computing concentration ratios (i.e. component species as a proportion of PM2.5 mass). In the

second stage of a hierarchical model, season- and community-specific estimates of the

association between PM2.5 and CVD hospitalizations were regressed on the concentration ratios.

The association of PM2.5 with all CVD hospitalizations was significantly modified when the

proportion of Br, Na+

, Ni, V and Al in PM2.5 was high. The association of PM2.5 with all MI

hospitalizations was significantly modified when the proportion of arsenic [As], chromium [Cr],

manganese [Mn], OC, Ni, K and Na+ was high. Additional increases in CVD hospitalizations per

interquartile range (IQR) increase in the proportion of the component ranged from 0.53% to

0.9% (larger, less precise increases were reported for MI). None of the components significantly

modified the association of PM2.5 with CHF admissions (i.e. p-value > 0.05). Ito et al. (2011b)

conducted a time series analysis of the lag structure and seasonal patterns in the association

between emergency hospitalization for CVD and PM2.5 chemical components. Same day

concentration of most components examined was associated with CVD hospitalizations (EC,

OC, SO4, NO3, Na, Ni, V, Zn, Se, and Br). The association and lag structure of EC with CVD

hospitalization was constant across season; associations of OC, SO4, Ni, Zn, Si, Se and Br with

CVD hospitalizations were strongest in the cold season. 

An additional study (Mostofsky et al., 2012) examined different approaches to modeling the

association between PM components and health outcomes using ischemic stroke onset as an

example. The authors used three different models that included parameters for the following: (1)

component concentration, (2) component concentration adjusted for total PM2.5 mass, which

accounts for total PM2.5 mass, and (3) component residuals, which eliminates confounding by

total PM2.5 mass. In model 1, positive associations were observed for a number of components

including Al, calcium [Ca], Br, lead [Pb], Se, titanium [Ti], and Fe with the strongest

associations for V, S, Ni, and black carbon [BC]. Models 2 and 3 resulted in relatively few
34

components with positive associations, but the pattern of associations across pollutants was

consistent between the two models with the strongest associations for V, Ni, and BC.

Long-term exposure to PM2.5 components and mortality

Ostro et al. (2010) also examined the association between long-term exposures to PM2.5

components (i.e., EC, OC, SO4, NO3, Fe, K, Si, Zn) and all-cause mortality among the subjects

from the California Teachers Study. No associations were observed between all-cause mortality

and any PM2.5 component. In analyses of cause-specific mortality, Ostro et al. (2010) observed

an association between long-term exposure to several PM2.5 components and mortality from

CPD, IHD and pulmonary disease. The authors observed positive associations of CPD and IHD

mortality with each of the measured components, and between pulmonary mortality and SO4 and

NO3. Of the components analyzed, there were positive associations with nitrate, sulfate and

silicon for CPD mortality and all of the components were associated with mortality from IHD

(See Table 2.2). 

Table 2.2.Association between mortality outcomes and PM2.5 components using a 30-km buffer

(n=43,220) (adapted from Ostro et al. (2011))

Component (IQR, μg/m3) All-Cause* CPD* IHD* Pulmonary*

EC (0.65) 1.02 (0.93, 1.12) 1.07 (0.94, 1.22) 1.46 (1.17, 1.83) 0.88 (0.68, 1.15)

OC (0.84) 1.00 (0.95, 1.04) 1.04 (0.98, 1.11) 1.13 (1.01, 1.25) 0.95 (0.84, 1.06)

SO4 (2.2) 1.06 (0.97, 1.16) 1.14 (1.01, 1.29) 1.48 (1.20, 1.82) 1.04 (0.82, 1.31)

NO3 (3.2) 1.03 (0.98, 1.09) 1.11 (1.03, 1.19) 1.27 (1.12, 1.43) 1.04 (0.90, 1.20)

Fe (0.13) 1.01 (0.93, 1.11) 1.05 (0.93, 1.19) 1.39 (1.13, 1.72) 0.88 (0.69, 1.13)

K (0.07) 1.01 (0.94, 1.08) 1.06 (0.97, 1.17) 1.27 (1.07, 1.49) 0.90 (0.74, 1.09)

Si (0.03) 1.02 (0.99, 1.06) 1.05 (1.00, 1.10) 1.11 (1.02, 1.20) 0.98 (0.89, 1.08)

Zn (0.01) 1.03 (0.96, 1.11) 1.09 (0.98, 1.20) 1.33 (1.12, 1.58) 0.97 (0.79, 1.18)

*Hazard ratio and 95% confidence interval for an increase in PM2.5 components equal to the interquartile range 

(IQR)

Long-term exposure to PM2.5 components and sources and morbidity

In a study conducted in New York City, Patel et al. (2009) examined long-term exposure to

PM2.5 components (Ni, V, Zn, EC) and respiratory symptoms in children through 24 months of

age. Positive associations were observed between Ni and wheeze, but not cough. No other

associations were observed between the other metals or EC and either wheeze or cough. PM2.5

mass was not associated with wheeze and/or cough (see Section 2.1.3 for results on PM2.5 mass).

Several recent studies have examined the association between exposure to PM2.5 components and

sources and birth outcomes, including birth weight and preterm birth. Studies examining birth

weight and PM2.5 components and sources found the strongest associations with metals/oil

combustion (Bell et al., 2012; Darrow et al., 2011b; Bell et al., 2010) and elemental
35

carbon/motor vehicles (Wilhelm et al., 2012; Darrow et al., 2011b; Bell et al., 2010). Similarly,

when evaluating PM2.5 components and preterm birth, the associations with metals, EC, OC and

ammonium nitrate were strongest (Wilhelm et al., 2011; Darrow et al., 2009). Several PM2.5

sources were associated with preterm birth, including biomass burning and diesel traffic

(Wilhelm et al., 2011). 

2.3.3. Toxicology Studies – Source Apportionment and Fine PM Components

The 2009 PM ISA examined health effects associated with exposure to ambient PM components

and sources in animals. In vivo and in vitro studies reported a variety of sources and components

were linked with cardiopulmonary effects; however, there was insufficient evidence overall to

determine which sources or components were most closely related to the observed effects. Since

the completion of the 2009 PM ISA, a small number of animal toxicology studies have continued

to assess the role of PM sources and components on effects observed after exposure to PM2.5.

2.3.3.1. Toxicology Studies Comparing Ambient Fine PM Sources and

Components

Toxicology studies employing CAPs offer a relevant surrogate for atmospheric PM. Table 2.3

shows the endpoints that were associated with various source categories from rodents exposed to

CAPs from four locations. These three studies compare electrocardiogram (ECG) responses

during CAPs inhalation to PM2.5 components associated with source factors (Kamal et al., 2011; 

Rohr et al., 2011; Chen et al., 2010).

Chen et al. (2010) compared subchronic CAPs inhalation exposures from two locations in New

York, Sterling Forest (SF; undeveloped woodland park) and Manhattan in male hyperlipidemic

mice. Using Manhattan CAPs (mean CAPs concentration, 122.9 ± 81.1 μg/m3), heart rate (HR)

decreased with increased current day CAPs mass at all lags and several measures of heart rate

variability (HRV) increased with increased CAPs mass (i.e., standard deviation of the normal-tonormal intervals, SDNN; root mean square of the standard deviation of the normal-to-normal

intervals, rMSSD; and frequency domain indices, high-frequency, HF, low-frequency, LF, and

LF/HF ratio). Using SF CAPs (mean CAPs concentration, 133.3 ± 110.5 μg/m3

), CAPs mass was

positively associated with HR, whereas HRV decreased with increased CAPs. Using Manhattan

CAPs, ECG changes were associated with components related to residual oil combustion > longrange transport > traffic > iron/steel > incineration > soil. Using SF CAPs, ECG changes were

associated with long-range transport > Ni refinery > soil > residual oil combustion/traffic. Chen

et al. (2010) also performed single-element analysis and note that EC did not account for the

acute ECG changes associated with PM2.5 and that Ni may have an effect in Manhattan but not

SF.

Rohr et al. (2011) reported altered ECG responses in spontaneously hypertensive rats following

CAPs inhalation exposures from Detroit, Michigan over 13 consecutive days in both the summer

and winter. Source factors were identified using positive matrix factorization. In summer (time

weighted average CAPs concentration, 518 μg/m3), decreased HRV (SDNN) was associated with
36

cement/lime, iron/steel, and gasoline/diesel factors, and less so with sludge incineration. In

winter (time weighted average CAPs concentration, 357 μg/m3); decreased HR was associated

with sludge incineration, cement/lime, and coal/secondary sulfate factors.

Kamal et al. (2011) also identified source factors (via positive matrix factorization) associated

with ECG alterations in hypertensive rats exposed for 13 days to CAPs (from Steubenville, OH;

mean CAPs concentration 406 ± 266 μg/m3). Statistically significant associations were found

between acute cardiac responses and PM components linked with incineration, metal processing,

mobile sources, and iron/steel production. The strength of the association with each source was

dependent upon wind direction; however, incineration was consistently found to be associated

with changes in HR and HRV. Several individual CAPs components were also associated with

cardiovascular responses, S, SO2, Pb, and oxides of nitrogen (NOx).

Table 2.3. CAPs Sources and Associated Endpoints

Source Category

Elemental

Loading

Endpoint

Affected Location

Exposure

Duration References

Metal processing V, Cr, Ti,

Mo, La, Ce

↑ HR

↓ SDNN

Steubenville, OH 13 days (s) Kamal et al. (2011)

Incineration

(including sludge)

Zn, Cd ↓ HR

↓ SDNN

Steubenville, OH 13 days (s) Kamal et al. (2011)

Zn, Ba, Mn,

Sr, Sb

↓ HR (w)

↓ SDNN (s)

Detroit, MI 13 days (s &

w)

Rohr et al. (2011)

Zn, Pb, Cu,

Fe

ECG alterations Manhattan, NY 6 months Chen et al. (2010)

Pb Pb, Cu ↓ HR Detroit, MI 13 days (s &

w)

Rohr et al. (2011)

Iron/Steel

manufacturing

Fe, Mn, Cu,

EC, Pb

↓ HR

↑ rMSSD

Steubenville, OH 13 days (s) Kamal et al. (2011)

Mn, Fe ECG alterations Manhattan, NY 6 months Chen et al. (2010)

Fe, Mn, Cu ↑ rMSSD (w)

↓ SDNN (s)

Detroit, MI 13 days (s &

w)

Rohr et al. (2011)

Mobile/Traffic Fe, Sb, As,

K, CO

↓ SDNN

↑ rMSSD

Steubenville, OH 13 days (s) Kamal et al. (2011)

Fe, Ti, Zn ↓ SDNN (s)

↑ rMSSD (w)

Detroit, MI 13 days (s &

w)

Rohr et al. (2011)

EC, NO2, Si,

Fe, Cu

ECG alterations Manhattan, NY 6 months Chen et al. (2010)

Coal and Secondary

Sulfate

S, Se, Al, V,

P

↓ HR

↑ rMSSD

Steubenville, OH 13 days (s) Kamal et al. (2011)

S, Se ↓ HR (w)

↑ rMSSD (w)

Detroit, MI 13 days (s &

w)

Rohr et al. (2011)

Oil refinery La, Ce ↑ HR (w) Detroit, MI 13 days (s &

w)

Rohr et al. (2011)

Cement/lime

processing

Ca, Sr, Mg ↓ HR (w)

↓ SDNN (s)

Detroit, MI 13 days (s &

w)

Rohr et al. (2011)
37

Source Category

Elemental

Loading

Endpoint

Affected Location

Exposure

Duration References

Residual oil

combustion

V, Ni, EC,

Fe

ECG alterations Manhattan, NY 6 months Chen et al. (2010)

Ni-refinery Cr, Ni ECG alterations Sterling Forest,

NY

6 months Chen et al. (2010)

Soil Al, Si, Ca,

Fe

ECG alterations Sterling Forest,

NY

Manhattan, NY

6 months Chen et al. (2010)

Long range

transport

S, Se, Br ECG alterations Sterling Forest,

NY

Manhattan, NY

6 months Chen et al. (2010)

(w) winter season, (s) summer season, HR: heart rate, SDNN: standard deviation of the normal-to-normal intervals, rMSSD: root 

mean square of the standard deviation of the normal-to-normal intervals, Mo: molybdenum, La: lanthanum, Ce: cerium, Cd: 

cadmium, Ba: barium, Sr: strontium, Sb: antimony, Cu: copper, CO: carbon monoxide, P: phosphorus

Other studies have used regression and correlation approaches to estimate the relationship

between various PM components and sources with health effects. Happo et al. (2010b)

intratracheally instilled mice (10 mg/kg) with size-segregated ambient PM samples collected in

six European cities over various seasons: Duisberg autumn, Prague winter, Amsterdam winter,

Helsinki spring, Barcelona spring, Athens summer. PM exposure (PM10-2.5 and PM2.5-0.2 )

increased bronchoalveolar lavage fluid (BALF) total cell number and BALF protein

concentration. No formal source apportionment was conducted, but oxidized organic compounds

(e.g., dicarboxylic acids), transition metals (e.g., Fe and Cr), and source tracers for fuel oil

combustion (i.e., Ni and V) were the most strongly correlated components of PM2.5-0.2

contributing to the inflammatory response (i.e., BALF total cell number). These studies

measured response to PM10-2.5 and PM2.5-0.2 PM samples, and generally report stronger

inflammatory responses (e.g., BALF cytokines, cell number, and total protein) after exposure to

coarse PM compared to fine. Source tracers for soil (K+

, magnesium [Mg2+], Cu, manganese

[Mn], Fe) and sea spray (Na+

, chlorine [Cl-], and NO3

-

) found in PM10-2.5 were the most strongly

correlated with inflammatory response.

A few studies discuss how seasonal variation in PM components may affect PM-induced health

effects. Happo et al. (2010a) intratracheally instilled mice (10 mg/kg) with size-fractionated

ambient PM collected in Helsinki in the winter, spring, summer, and autumn. PM collected in the

spring produced the highest relative inflammatory activity (i.e., total cell number, total protein,

tissue necrosis factor alpha [TNF-α], interleukin-6 [IL-6], and keratinocyte-derived chemokine in

BALF) when dose was adjusted to the PM per cubic meter of urban air, whereas the PM

collected in the autumn produced the highest inflammation per equal mass dose. This difference

was influenced by a greater PM mass concentration in urban air in the springtime. The overall

inflammatory activity of PM decreased with particle size, such that PM10-2.5 and PM2.5-1 had a

higher potency than PM1-0.2 and PM0.2. Components of road dust (Ca2+, Fe, Mn, and Al) and

trace metals (presumed to be the result of non-exhaust PM from traffic; Cu, Chromium [Cr],

cobalt [Co]) were consistently correlated with BALF inflammatory response in PM2.5-1.

Resuspension of road dust was also strongly correlated with inflammatory responses to PM10-2.5.
38

Farina et al. (2011) treated mice (100 μg, intratracheal aerosolization) with size-fractionated

ambient PM collected from Milano, Italy in summer and winter. A stronger inflammatory

activity was generally observed after administration of summer PM10 and PM2.5 than winter PM.

PM10 exposure resulted in a higher TNF-α concentration (in BALF) compared to PM2.5, and this

was attributed to the greater endotoxin concentration and bacteria content of PM10.

Additional studies assessed the differential responses of PM collected at different distances from

a highway. Cho et al. (2009) found similar composition in size-fractionated ambient PM

collected near (20 m) and far (275 m) from a road in Raleigh, NC; however, PM collected nearroad was enriched with metals and a greater concentration of endotoxin. Coarse PM samples, but

not fine PM samples, produced pulmonary inflammation (i.e., BALF, macrophage inflammatory

protein 2 [MIP-2], TNF-α, IL-6) in exposed mice (25 and 100 μg) irrespective of distance

collected from the road. Zhang et al. (2011) reported greater increases in protein and lactate

dehydrogenase [LDH] in BALF after instillation (7.5 mg/kg) of PM2.5 collected near traffic

compared to far from traffic in Beijing, China. Chemical analysis of the near-traffic PM revealed

higher concentrations of polycyclic aromatic hydrocarbons [PAHs] and heavy metal elements

(arsenic [As], Cd, Zn, S), but no statistical correlations were computed between these

components and the health effects observed.

A number of studies have attempted to disentangle the role of PM and gaseous components in

the health effects associated with ambient air pollution exposure by removing PM from the

mixture using a high efficiency particle filter. A few recent studies report cardiovascular,

respiratory, and reproductive effects after exposure to unfiltered (the whole mixture), but not

filtered Sao Paulo urban air (20 m from road) (Pires et al., 2011; Matsumoto et al., 2010; 

Akinaga et al., 2009). These studies suggest that PM but not the gaseous components of the

urban air play a role in these responses.

2.3.3.2. Toxicology Studies Comparing Source-Derived PM and Components

A number of studies attempted to characterize effects from ambient PM sources by exposing

animals in the laboratory to PM derived from potential ambient sources (e.g., coal combustion,

diesel).

A series of studies evaluated the health effects resulting from various coal-fired power plant

emissions scenarios (Diaz et al., 2011; Godleski et al., 2011a; Godleski et al., 2011c; Godleski et 

al., 2011b; Lemos et al., 2011; Wellenius et al., 2011). Stack emissions were collected from three

coal-fired power plants and various atmospheric transformations (e.g., oxidation, reaction with αpinene, neutralization) were simulated to investigate the toxicity of primary and photochemically

aged (secondary) particles. Particle mass concentrations varied from 43.8 to 257.1 μg/m3 (Kang 

et al., 2011). Rats were exposed to these simulated emissions scenarios for 6 hours and

demonstrated (1) increased BALF total cells, macrophages, and neutrophils (Godleski et al., 

2011a); (2) moderately increased heart and lung reactive oxygen species (measured by in vivo

chemiluminescence) (Lemos et al., 2011), 3) increased premature ventricular beat frequency, but
39

no change in heart rate, HRV, or ECG intervals (Wellenius et al., 2011); and 4) breathing pattern

changes (Diaz et al., 2011). Overall, specific PM components did not predict respiratory or

cardiovascular effects observed after PM exposure as well as simulated atmospheric

transformation scenarios.

Additionally, a few studies assessed respiratory, cardiovascular, and systemic effects following

exposure to filtered and unfiltered simulated downwind coal combustion emissions (Barrett et 

al., 2011; Mauderly et al., 2011). Barrett et al. (2011) reported different respiratory effects after

exposure to filtered and unfiltered emissions. Mauderly et al. (2011) found 17 out of 270 speciesgender-time-outcome comparisons were affected by whole emissions and that PM participated in

only 3 responses (liver weight, serum K+, and MIP-2). The authors concluded that PM

contributed to a few of the effects but that the pollutants responsible for the effects observed

were not able to be identified.

Studies have also evaluated the role of PM in engine emissions on the progression of health

effects. Tzamkiozis et al. (2010) instilled mice with PM collected from a gasoline Euro 3 car, a

diesel Euro 2 car, and a diesel Euro 4 car (with a diesel particle filter). Significant pulmonary

inflammation (i.e., BALF polymorphonuclear leukocytes (PMN) number) and injury (i.e., BALF

protein concentration) occurred 24 hours after treatment. The strongest associations with these

effects were observed for the PM components, P, Mn, Fe, Pb, reactive oxygen species (ROS),

benz(a)anthracene, chrysene, and medium and heavy PAHs. A strong association was also

observed between pulmonary injury and S.

A number of studies evaluated the impact of inhaled diesel exhaust on the cardiovascular system

with and without filtration (Gordon et al., 2012; Lamb et al., 2012; Seilkop et al., 2012; Campen 

et al., 2010). Different cardiovascular effects were reported after filtration of diesel exhaust by

Gordon et al. (2012) and Lamb et al. (2012). Campen et al. (2010) found that filtration of PM

from diesel exhaust did not alter the vascular responses observed. Seilkop et al. (2012) ranked

components of diesel or gasoline exhaust, wood smoke, or simulated “downwind” coal emissions

by their ability to induce pro-atherosclerotic responses in the aorta of mice that inhaled these

pollutant mixtures 6 hours/day for 50 days. Filtration of PM did not have a large effect on the

responses measured. Gases (i.e., SO2, ammonia (NH3), NO2, CO)) were found to be most highly

predictive of the response indicators. These studies using filtration of PM from whole mixtures did not

consistently identify whether PM or gases from whole air pollution mixtures led to the cardiovascular,

respiratory, or reproductive effects observed.

Summary

The few epidemiologic studies that have been conducted since the completion of the 2009 PM

ISA continue to report health effects with a number of sources and components. Toxicological

studies have attempted to identify whether particular sources or components are responsible for

the health effects observed by comparing the health effects, primarily cardiopulmonary effects,

observed in response to exposures to ambient fine PM sources and components and sourcederived PM and components. However, the toxicology studies did not find consistent evidence
40

that one source or component is most closely related to a specific health effect. Collectively these

studies continue to report that a variety of sources and components are linked with

cardiopulmonary effects and mortality; however, there is still insufficient evidence to determine

which sources or components are most closely related to the observed effects.

3. SUMMARY AND CONCLUSIONS

The new studies published since the completion of the 2009 PM ISA provide additional evidence

indicating a relationship between exposure to ambient PM and health effects. The new studies

provide important insights on the health effects of PM exposure, with the results continuing to

support a relationship between PM exposure and health effects at ambient concentrations similar

or lower than those observed in previous studies. Overall: (a) the new studies generally

strengthen the evidence that acute and chronic exposures to fine PM; (b) although limited in

number, coarse PM studies provide evidence of an association with short-exposures and pediatric

asthma ED visits, but no association between long-term exposure and mortality; (c) some of the

new epidemiologic studies report effects in areas with long-term mean or mean 24-h avg PM2.5

concentrations lower than that reported in the 2009 PM ISA; and (d) new toxicology and

epidemiologic studies continue to link various health outcomes with a range of fine PM sources

and components. In conclusion, the results of the new studies identified and described in this

provisional assessment does not materially change any of the broad scientific conclusions

regarding the health effects of PM exposure made in the 2009 PM ISA.

In summary, this provisional assessment found:

Long-term PM Exposure

• Mortality: Generally, the results of recent studies are consistent with the evidence for an

association between long-term exposure to PM2.5 and mortality (i.e., all-cause and

cardiovascular) within the range of long-term mean PM2.5 concentrations characterized in the

2009 PM ISA (i.e., 13.2 – 32.0 μg/m3

), with one new Canadian multi-city study showing

associations at concentrations below 10 μg/m3. New studies provide additional evidence for

respiratory mortality, including lung cancer. Two recent studies that examined associations

between long-term PM10-2.5 exposure and mortality do not observe an association in either

men or women.

• Cardiovascular morbidity: Recent studies continue to demonstrate the strongest

cardiovascular effects in women, specifically for stroke, incident MI, and incident

hypertension at long-term mean PM2.5 concentrations ranging from 9.7 – 21.5 μg/m3.

• Respiratory morbidity: Recent studies provide additional evidence for respiratory

symptoms and incident asthma, as well as respiratory hospitalizations at long-term mean

PM2.5 concentrations ranging from 9.7 – 27.0 μg/m3,

which is consistent with the conclusions

of the 2009 PM ISA.
41

• Reproductive and Developmental Outcomes: Recent studies continue to provide evidence

for developmental outcomes, specifically reductions in birth weight, at long-term mean PM2.5

concentrations ranging from 11.0 – 19.8 μg/m3

, which further support the conclusions of the

2009 PM ISA. 

Short-Term PM Exposure

• Mortality: The limited number of mortality studies conducted in the U.S. and Canada

further support the conclusions of the 2009 PM ISA and continue to demonstrate associations

between short-term PM2.5 exposure and mortality at mean 24-h average concentrations

greater than 12.8 μg/m3. Since the completion of the 2009 PM ISA no new studies have been

conducted that examined associations between short-term exposure to PM10-2.5 and mortality.

• Respiratory hospital admissions/ED visits: New multi-city and single-city studies

demonstrate consistent positive associations for all respiratory-related hospital

admissions/ED visits, and provide additional evidence for increases in asthma hospital

admissions/ED visits in areas with mean 24-h average PM2.5 concentrations ranging from 6.7

– 22.0 μg/m3, which further supports the conclusions of the 2009 PM ISA. One new study

was identified that examined the association between short-term PM10-2.5 exposure and

respiratory-related ED visits, and provided evidence of increases in pediatric asthma ED

visits.

• Cardiovascular hospital admissions/ED visits: New studies focusing primarily on all

cardiovascular hospital admissions/ED visits continue to demonstrate consistent positive

associations in areas with mean 24-h average PM2.5 concentrations ranging from 6.7 – 15.3

μg/m3. Additionally, there is new evidence for potential associations with hypertension ED

visits, and a new study demonstrating an association with stroke onset.

Health Effects Related to Sources or Components of PM

• Consistent with those studies evaluated in the 2009 PM ISA, new studies continue to

demonstrate cardiovascular and mortality effects with sources and components related to a

number of combustion activities (e.g., motor vehicle emissions, coal combustion, oil burning,

power plants, and wood smoke/vegetative burning), crustal sources, and secondary sulfate.

Additional new studies also add to the limited number of studies that have examined

associations between sources and components and respiratory and birth outcome effects, as

well as, long-term exposure and mortality. Overall, new studies support the conclusions of

the 2009 PM ISA that many PM components can be linked with differing health effects and

the evidence is not yet sufficient to allow differentiation of those components or sources that

are more closely related to specific health outcomes.
42

APPENDIX A. Studies Included in the PM Provisional Science Assessment

Table A.1. Characterization of Studies of Long-term Exposure to PM2.5 and Mortality

Author

Years

of

Study Location Outcome Population

Size

Fraction

Long-term

Mean

Concentration

(μg/m3)

Upper

Percentile

Concentrations

(μg/m3)

Crouse

et al.

(2012)

1991-

2001

Canada

(nationwide

)

All-Cause,

CVD, IHD

Mortality

Nonimmigrant

Canadian

adults

PM2.5 8.7 Max: 19.2

Gan et

al.

(2011)

AQ:

1994-

1998;

Death

s:

1999-

2002

Vancouver,

BC 

Canada

CHD Mortality Adults (45-85)

without known

CHD at

baseline PM2.5 4.08 Max: 10.24

Greven

et al.

(2011)

2000-

2006

U.S.

(nationwide

)

All-Cause Medicare

recipients

(65+ yrs)

PM2.5 13.0 75th: 14.7

Hart et

al.

(2010)

AQ:

2000

Death

s:

1985-

2000

U.S.

(nationwide)

All-Cause,

Lung Cancer,

CVD Disease,

IHD,

Respiratory

Disease,

COPD Mortality

Adult males

from 4 U.S.

trucking

companies PM2.5 14.1 NR

Jerrett

et al.

(2009b)

1992-

2002

Toronto,

Canada

All-Cause,

Circulatory

Mortality

Adults from

respiratory

clinic

PM2.5 8.71 75th: 8.83

Jerrett

et al.

(2009a)

AQ:

1999-

2000

Death

s:

1982-

2000

U.S.

(nationwide; 86

MSAs)

All-Cause,

Cardiopulmona

ry, CVD, IHD,

Respiratory

Adults

PM2.5 14.3 NR

Lepeule

et al.

(2012)

1974-

2009

U.S (6

cities in

East and

Midwest)

All Cause, CVD

and Lung

Cancer

Mortality

Adults

PM2.5

15.9 (six

cities

combined);

means for

individual

cities ranged

from 11.4-

23.6

NR

Lipsett

et al.

(2011)

AQ:

1999-

2005;

Death

s:

1995-

2005

California All-Cause,

CVD,

Respiratory,

Lung Cancer,

IHD, CBD

Adults

(Female

teachers)

PM2.5 15.64 Max: 28.35
43

Author

Years

of

Study Location Outcome Population

Size

Fraction

Long-term

Mean

Concentration

(μg/m3)

Upper

Percentile

Concentrations

(μg/m3)

McKean

-

Cowden

et al.

(2009)

AQ:

1979-

1983;

1999-

2000;

Death

s:

1982-

2000

U.S.

(nationwide)

Brain Cancer

Mortality

Adults

PM2.5

1979-1983:

21.1

1999-2000:

14.0

Avg: 17.7

Max:

1979-1983:

30.0

1999-2000:

22.2

Avg: 23.6

Ostro et

al.

(2010)

AQ:

2002-

2007

California All-Cause,

CPD, IHD

Mortality

Adults

(Female

teachers)

PM2.5 and

componen

ts (EC,

OC, SO4,

NO3, Fe,

K, Si, Zn)

17.0 Max: 34.7

Puett et

al.

(2009)

1992-

2002

U.S. (East

and

Midwest)

All Cause and

CHD Mortality

Adults

(Female

Nurses)

PM2.5 13.9

75th: 15.6

Max: 27.6

Puett et

al.

(2011)

1986-

2002

U.S. (East

and

Midwest)

All Cause and

CHD Mortality

Adults (Male

Health

Professionals)

PM2.5

17.8 (at

baseline) NR

CVD: Cardiovascular Disease, CHD: Coronary Heart Disease; IHD: Ischemic Heart Disease; COPD: Chronic Obstructive Pulmonary 

Disease; CBD: Cerebrovascular Disease; NR: Not reported

Table A.2. Characterization of Studies of Long-term Exposure to PM10-2.5 and Mortality

Author

Years

of

Study Location Outcome Population

Size

Fraction

Long-term Mean

Concentration

(μg/m3

)

Upper Percentile

Concentrations

(μg/m3)

Puett et

al.

(2009)

1992-

2002

U.S. (East

and

Midwest)

All-Cause

and CHD

Mortality

Adults

(Female

Nurses)

PM10-2.5 7.7

75th: 9.2

Max: 26.9

Puett et

al.

(2011)

1986-

2002

U.S. (East

and

Midwest)

All-Cause

and CHD

Mortality

Adults (Male

Health

Professionals)

PM10-2.5 10.1 (at baseline) NR

CHD: Coronary Heart Disease; NR: Not reported
44

Table A.3. Characterization of Studies of Long-term Exposure to PM2.5 and Cardiovascular

Effects

Author

Study

Years Location Outcome Population

Size

Fraction

Long-term

Mean

Concentration

(μg/m3)

Upper

Percentile

Concentrations

(μg/m3)

Puett et al.

(2011)

1989 -

2003

Northeast and

Midwest,

U.S.*

All-cause

Mortality,

Nonfatal MI,

fatal CHD,

and

Hemorrhagic

and Ischemic

Stroke

Health

Professionals

Follow-Up

Study

men, 40-75

yrs of age

PM2.5,

PM10-2.5

Predicted

PM2.5 = 17.8

± 3.4

Predicted

PM10-2.5 =

10.1 ± 3.3

Interquartile

range (IQR):

PM2.5: 4.3

PM10-2.5: 4.3

Lipsett et

al. (2011)

1995-

2000

California All Cause

Mortality,

CVD

mortality, IHD

mortality,

cerebrovascular

disease

mortality, MI

incidence,

stroke

incidence

California

Teachers

Study

N=124,614

women, 20-

>80 yrs 15.64 Max: 28.35

Coogan et

al. (2012)

1995-

2005

Los

Angeles,

CA

Hypertension

and Diabetes

Mellitus

(incidence)

Black

Women’s

Health Study

N=4204

(hypertension)

N-3236

(diabetes)

disease free 

at baseline

PM2.5 20.7 75th: 21.6

Beckerman

et al.

(2012)

1992-

1999

Toronto,

Ontario

IHD

(prevalence)

N=2360

pulmonary

clinic patients

PM2.5

50th

percentile:

8.71

75th: 8.83

Adar et al.

(2010)

2002-

2003

6 US

Cities**

Retinal

Microvasculat

ure

MESA,

N=4,607

46-87 years ,

no clinical

cardiovascular

disease at

baseline

PM2.5 16 (±3)

75th: 17.2

personal PM

prediction;

17.2; nearest

monitor PM17.3

Max: personal

PM prediction26.3; nearest

monitor PM25.4
45

Author

Study

Years Location Outcome Population

Size

Fraction

Long-term

Mean

Concentration

(μg/m3)

Upper

Percentile

Concentrations

(μg/m3)

O'Neill et

al. (2011)

2000-

2002

6 US

Cites**

Arterial

Stiffness

MESA

N=3,996

men and

women, 44-84

yrs

PM2.5

Imputed 20 yr

avg: 21.47 ±

5.00

16.80 ± 3.90

(2005)

Van Hee et

al. (2011)

Jul

2000-

Aug

2002

6 US

Cites**

Ventricular

Conduction

and

Repolarization

Abnormalities

MESA

N=4,783

45 to 84 yrs

PM2.5

Kloog et al.

(2012a)

2000-

2006

New

England

Hospital

Admissions

≥65 years PM2.5

(predicted) 9.65 17.79

Table A.4. Characterization of Studies of Long-term Exposure to PM2.5 and Respiratory Effects

Author

Years

of

Study Location Outcome Population

Size

Fraction

Long-term

Mean

Concentration

(μg/m3)

Upper

Percentile

Concentrations

(μg/m3)

Noonan et al.

(2012)

2003-

2009

Libby, MT Respiratory

infections

(including

bronchitis)

PM2.5 19.0-27.0 NR

Bhattacharyya

(2009)

1997-

2006

US

(Nationwide)

Hay Fever and

Sinusitis

National

Health

Interview

Survey

respondents

PM2.5 13.4-11.6 NR

Bhattacharyya 

and Shapiro

(2010)

1997-

2006

US

(Nationwide)

Ear Infections National

Health

Interview

Survey

respondents

PM2.5 13.4-11.6 NR

Patel et al.

(2009)

1998-

2006

NYC, NY Wheeze and

Cough

Participants in

Columbia

Center for

Children’s

Environmental

Health birth

cohort

PM2.5 13.0 Max: 38.4
46

Author

Years

of

Study Location Outcome Population

Size

Fraction

Long-term

Mean

Concentration

(μg/m3)

Upper

Percentile

Concentrations

(μg/m3)

Parker et al.

(2009)

1999-

2005

US

(Nationwide)

Respiratory

Allergies

Children

(ages 3-17) in

National

Health

Interview

Survey

PM2.5 13.1 75th: 15.2

Nachman and

Parker (2012)

2002-

2005

US

(Nationwide)

Asthma,

sinusitis,

chronic

bronchitis

National

Health

Interview

Survey

respondents

PM2.5 12.1

75th: 14.4

Max: 27.5

Karr et al.

(2009a)

1997-

2003

Puget

Sound

Region,

WA

Bronchiolitis

hospital

admission

Washington

State Birth

Events

Registry

Database

PM2.5 12.0

75th: 14.0

Max: 36.9

Karr et al.

(2009b)

1999-

2003

Georgia Air

Basin of

BC,

Canada

Inpatient or

outpatient

bronciolitis

Infants born

between

1999-2002 PM2.5 5.8 Max: 12.0

Kloog et al.

(2012a)

2000-

2006

New

England

Respiratory

hospital

admission

Residents ≥65

years PM2.5 9.7

75th: 10.1

Max: 17.8

Neupane et al.

(2010)

2003-

2005

Hamilton,

ON,

Canada

Pneumonia

hospital

admissions

Residents ≥65

years PM2.5 10.7

75th: 113

95th: 12.4

Max: 13.0

Meng et al.

(2010)

2000-

2001

San

Joaquin

Valley, CA

Asthma

Symptons;

Asthma ED

visits or

hospitalizations

San Joaquin

Valley

residents

participating

in 2001

California

Health

Interview

Survey)

PM2.5 21.4 75th: 23.5

Akinbami et al.

(2010)

2001-

2004

US

(Nationwide)

Asthma

prevalence

Children

(ages 3-17) in

National

Health

Interview

Survey

PM2.5 13.3 75th: 15.7

Carlsten et al.

(2011)

1995-

2003

Vancouver,

BC,

Canada

Incident

Asthma

Birth cohort

born in 1995 PM2.5 5.6 NR
47

Author

Years

of

Study Location Outcome Population

Size

Fraction

Long-term

Mean

Concentration

(μg/m3)

Upper

Percentile

Concentrations

(μg/m3)

Clark et al.

(2010)

1999-

2004

Southwestern

BC,

Canada

Incident

Asthma

Children born

in 1999 and

2000 and

followed up to

3-4 yrs

PM2.5 5.6 75th: 6.1

McConnell et

al. (2010)

2002-

2006

Southern

California

Incident

Asthma

Kindergarten

and First

grade children

in Southern

California

Children’s

Health Study

PM2.5 13.9 Max: 17.4

Table A.5. Characterization of Studies of Long-term Exposure to PM2.5 and Reproductive and

Developmental Effects

Author

Years

of

Study Location Outcome Population

Size

Fraction

Long-term

Mean

Concentration

(μg/m3

)

Upper

Percentile

Concentrations

(μg/m3)

Lee et al.

(2011)

1997-

2001

PA C-reactive

protein

Healthy

women PM2.5 16.4

75th: 18.7

95th: 26.2

100th: 40.8

Legro et

al.

(2010)

2000-

2007

Northeastern

US

In Vitro

Fertilization

(IVF)

success

Women

undergoing

IVF PM2.5 14.0-14.5 NR

VinikoorImler et

al.

(2012)

2000-

2003

NC Gestational

Hypertension

All births in

NC PM2.5 14.5 75th: 15.7

Rich et

al.

(2009)

1999-

2003

NJ Fetal Growth All births in

NJ PM2.5 13.8 NR

Chang et

al.

(2012b)

2001-

2005

NC Pre-term

birth (PTB)

All births in

NC PM2.5 13.0-15.3 NR

Darrow

et al.

(2009)

1994-

2004

Atlanta, GA PTB All births in

Atlanta (5

counties)

PM2.5 16.5 Max: 34.1

Rudra et

al.

(2011)

1996-

2006

Western WA PTB Healthy

Women PM2.5 10.0

75th: 12.7

100th: 17.2

Wilhelm

et al.

(2011)

2004-

2006

Los Angeles,

CA

PTB All births in

LA county PM2.5 18.0 NR
48

Author

Years

of

Study Location Outcome Population

Size

Fraction

Long-term

Mean

Concentration

(μg/m3)

Upper

Percentile

Concentrations

(μg/m3)

Marshall

et al.

(2010)

1998-

2003

NJ Birth Defects 

(Oral Clefts)

All births in

NJ PM2.5 13.4 NR

Bell et al.

(2012)

2000-

2004

CT and MA birth weight

(BW)

All births

from 5

counties

PM2.5 14.0 75th: 16.0

Bell et al.

(2010)

2000-

2004

CT and MA BW All births

from 5

counties

PM2.5 14.0 NR

Darrow

et al.

(2011b)

1994-

2004

Atlanta, GA BW All births in

Atlanta (5

counties)

PM2.5 16.5 NR

Ghosh et

al.

(2012)

1995-

2006

Los Angeles,

CA

BW All births in

LA county PM2.5 19.8 NR

Kloog et

al.

(2012b)

2000-

2008

MA BW, PTB All births in

MA PM2.5 9.6 75th: 11.6

Kumar

(2012)

2000-

2004

Chicago, IL BW All births

from

Chicago

MSA

PM2.5 18.0 NR

MorelloFrosch et

al.

(2010)

1996-

2006

CA BW All births in

CA PM2.5 16.7 75th: 21.0

Salihu et

al. (In 

Press)

2000-

2007

Tampa, FL BW, PTB Women

participating

in Health

Start

Project

PM2.5 11.0 Max: 23.2

Wilhelm

et al.

(2012)

2004-

2006

Los Angeles,

CA

BW All births in

LA county PM2.5 17.9 NR

Faiz et

al.

(2012)

1998-

2004

NJ Stillbirth All births in

NJ PM2.5 14.0 NR
49

Table A.6. Characterization of U.S. and Canadian Studies of Short-Term Exposure to PM2.5 and

Mortality

Author Years Location Mortality Population

Size

Fraction

Mean 24-h avg

Concentration

(μg/m3)

Upper

Percentile

Concentrations

(μg/m3)

Ito et al.

(2011a)

2000-

2006

New

York, NY

Cardiovascular ≥ 40 PM2.5, PM

components

(EC, OC,

SO4, Ni, V,

Zn, Si, Se,

Na, Br, NO3)

PM2.5

All-Year: 14.4

Warm (AprilSeptember):

14.8

Cold (OctoberMarch): 14.1

NR

Zhou et

al.

(2011)

2000-

2004

Detroit,

MI

Seattle,

WA

Non-accidental,

Cardiovascular,

Respiratory

All PM2.5, PM

components

(Al, Fe, K,

Na, Ni, S, Si,

V, Zn, EC)

Detroit

All-Year

(Median): 13.2

Warm (AprilSeptember)

(Mean):15.3

Cold (OctoberMarch) (Mean):

14.9

Seattle

All-Year

(Median): 7.9

Warm (AprilSeptember)

(Mean): 8.0

Cold (OctoberMarch) (Mean):

11.4

Detroit

Max: 65.8

Seattle

Max: 41.3

Chang

et al.

(2012a)

2001-

2005

New

York, NY

Cardiovascular,

Respiratory

≥ 65 PM2.5 Spring (MarchMay): 14.3

Summer (JuneAugust): 17.5

Fall

(SeptemberNovember):

13.3

Winter

(DecemberFebruary): 15.4

NR

Klemm

et al.

(2011)

1998-

2007

Atlanta,

GA (4

counties)

Non-accidental,

Cardiovascular,

Respiratory

≥ 65 PM2.5, PM

components

(EC, OC,

NO3, SO4)

17.0 75th: 21.6

Max: 72.9
50

Table A.7. Characterization of U.S. and Canadian Studies of Short-Term Exposure to PM2.5 and

Respiratory Hospital Admissions and Emergency Department Visits

Author Years Location

Hospital

Admission/

ED Visit

PopulationSize

Fraction

Mean 24-h

avg Concentration

(μg/m3)

Upper

Percentile

Concentrations

(μg/m3)

Bell et al.

(2012)

2000-

2005

187 U.S.

counties

Hospital

admissions:

All

respiratory

≥ 65

PM2.5, PM

components

All-Year: 14.0

Summer: 16.2

Winter: 13.9

Max:

All Year: 26.0

Summer: 28.5

Winter: 32.8

Zanobetti

et al.

(2009)

2000-

2003

26 U.S.

communities

ED Visits:

All

respiratory

≥ 65 PM2.5, PM

components

(As, Al, Br,

Cr, Fe, Pb,

Mn, Ni, K,

Si, V, Zn,

NO3, SO4,

NH4, Na+

,

EC, OC)

15.3

PM2.5 Max 

Spring: 24

(Riverside, CA)

PM2.5Max

Winter: 29.9 

(Fresno, CA)

Stieb et

al. (2009)

1992-

2003

7 Canadian

cities

ED Visits:

Asthma

COPD

Respiratory

Infection

All

PM2.5

Montreal

(1/97-12/02):

8.6

Ottawa (4/92-

12/00): 6.7

Edmonton

(4/92-3/02):

8.5

Halifax (1/99-

12/02): 9.8

Toronto (4/99-

6/03): 9.1

Vancouver

(1/99-2/03):

6.8

75th:

Montreal: 10.9

Ottawa: 8.7

Edmonton: 10.9

Halifax: 11.3

Toronto: 11.9

Vancouver: 8.5

Levy et

al. (2012)

2000-

2008

119 U.S.

counties

Hospital

Admissions:

All

respiratory

≥ 65 PM

components

(EC, OC,

SO4, NO3)

--- ---
51

Darrow et 

al. 

(2011a)

1993-

2004 

(PM2.5

collecte

d from 

8/1/98-

12/31/0

4)

Atlanta, GA ED Visits:

All 

respiratory

All

PM2.5

1-h max: 29

24-h avg: 16

Commute: 17

Day-time: 15

Night-time: 17

1-h max:

75th: 36

Max: 188

24-h avg:

75th: 21

Max: 72

Commute:

75th: 21

Max: 76

Day-time:

75th: 19

Max: 71

Night-time:

75th: 14

Max: 88

Strickland 

et al. 

(2010)

1993-

2004

(PM2.5

collecte

d from 

8/1/98-

12/31/0

4)

Atlanta, GA ED Visits:

Asthma

5-17

PM2.5, PM 

components 

(SO4, EC, 

OC, watersoluble 

metals)

PM2.5

All-Year: 16.4

Warm (MayOctober): 18.4

Cold 

(NovemberApril): 14.3

PM10-2.5

All-Year: 9.0

Warm: 9.7

Cold: 8.3

NR

Kim et al. 

(2011)

2003-

2007

Denver, CO Hospital 

Admissions:

All 

respiratory

COPD

Asthma

Pneumonia

All

PM2.5, PM 

components 

(EC, OC, 

SO4, NO3)

8.0 59.4

Mar et al. 

(2010)

1998-

2002

Tacoma, WA ED Visits:

Asthma

All PM2.5 12.3 NR

Kloog et 

al. 

(2012a)

2000-

2006

New England Hospital 

Admissions:

All 

respiratory

≥ 65

PM2.5 9.6 Max: 72.6

Li et al. 

(2011)

2004-

2006

Detroit, MI ED Visits:

Asthma

2-18

PM2.5 15.0

75th: 18.5

Max: 69.0

Glad et 

al. (2012)

2002-

2005

Pittsburgh, 

PA

ED Visits:

Asthma

All

PM2.5 13.3 Max: 55.0
52

Grineski 

et al. 

(2011)

2000-

2003

El Paso, TX Hospital 

Admissions:

Asthma

Acute 

bronchitis

≥ 1

PM2.5 12.8

75th: 15.6

95th: 26.6

Max: 119.1
53

Table A.8. Characterization of U.S. and Canadian Studies of Short-Term Exposure to PM10-2.5 and Respiratory Hospital Admissions

and Emergency Department Visits

Table A.9. Characterization of U.S. and Canadian Studies of Short-Term Exposure to PM2.5 and Cardiovascular Hospital Admissions

and Emergency Department Visits

Author

Study

Years Location Outcome Population Size Fraction

Mean 24-h avg

Concentration

(μg/m3)

Upper Percentile

Concentrations (μg/m3)

Zanobetti et al.

(2009)

2000-2003 USA (26

communities)

ED Visits:

MI, CHF

Older

adults ≥ 65

yrs

PM2.5

PM2.5

components:

As, Al, Br, Cr,

Fe, Pb, Mn, Ni,

K, Si, V, Zn,

NO3, SO4,

NH4, Na+, EC,

OC

15.3

PM2.5 Max Spring: 24

(Riverside, CA)

PM2.5Max Winter: 29.9 

(Fresno, CA)

Stieb et al.

(2009)

1990’s-early

2000’s

(depending

on city)

Candada (7

Cities)

ED

Visits:Angina/MI,

Heart Failure,

Dysrhythmia

PM2.5

City-specific means (range):

6.7-9.8

City Specific 75th

Percentiles:

8.5-11.9

Author Years Location

Hospital

Admissions/

ED Visit Population

Size

Fraction

Mean 24-h avg

Concentration

(μg/m3

)

Upper Percentile

Concentrations (μg/m3)

Strickland et al.

(2010)

1993-2004

(PM2.5 collected from

8/1/98-12/31/04)

Atlanta,

GA

ED Visits:

Asthma

5-17 PM10-2.5

PM10-2.5

All-Year: 9.0

Warm: 9.7

Cold: 8.3

NR
54

Author

Study

Years Location Outcome Population Size Fraction

Mean 24-h avg

Concentration

(μg/m3)

Upper Percentile

Concentrations (μg/m3)

Ito et al.

(2011a)

2000-2006 New York,

NY

ED Visits: CVD ≥40 yrs

PM2.5

PM2.5

components:

EC, OC, SO4,

NO3, Na+, Ni,

V, Zn, Si, Se,

Br

All year/Warm/Cold:

14.44/14.79/ 14.09

1.13/ 1.03/1.24

4.3/4.51/4.08

4.14/ 4.81/3.42

2.12/1.52/ 2.78

0.14/ 0.14/ 0.15

0.0171/0.0111/ 0.0236

0.0066/ 0.0054/0.0080

0.0300/ 0.0216/ 0.0389

0.0769/ 0.0886/ 0.0643

0.0013/0.0011/ 0.0015

0.0036/0.0031/0.0040

Not presented

(Note: SD provided so

we could compute)

Mathes et al.

(2011)

2000-2002 New York,

NY

ED Visits: CVD ≥40 yrs

PM2.5 --- ---

Szyszkowicz

et al. (2012)

Apr 1992-

Mar 2002

Canada

(Edmonton)

ED Visits: 

Hypertension

N=5,365 PM2.5 8.575th percentile: 10.9

Max: 1.3.1

Haley et al.

(2009)

2001-2005 New York

State

ED Visits

Discharges

from all

NYS

hospitals

PM2.5 NR NR

Bunch et al.

(2011)

1993-1998 Wasatch

Front, Utah

Hospital

Admissions

All

PM2.5

City specific means (range):

9.3-11.1

City specific max:

9.3-11.1

Kloog et al.

(2012a)

New England Hospital

Admissions

≥65 PM2.5

(predicted) 9.6 72.59
55

Author

Study

Years Location Outcome Population Size Fraction

Mean 24-h avg

Concentration

(μg/m3)

Upper Percentile

Concentrations (μg/m3)

Kim et al.

(2011)

2003-2007 Denver Hospital

Admissions

All PM2.5

EC

OC

Sulfate

Nitrate

7.98

0.47

3.09

1.08

1.03

59.41

3.02

10.28

14.32

19.72
56

Table A.10. Characterization of U.S. and Canadian Studies of Short-Term Exposure to PM2.5

and Out of Hospital Cardiac Arrests

Author

Study

Years Location Outcome Population

Size

Fraction

Mean 24-h

avg

Concentration

(μg/m3)

Upper Percentile

Concentrations

(μg/m3)

Silverman

et al.

(2010)

2002-

2006

USA

(New

York

City)

Out-ofhospital

cardiac

arrests

N=8,216

<40 to ≥ 70

yrs

PM2.5

Median:

All year = 12

Apr-Sept = 12

Oct-Mar = 12

Upper (95%):

All year = 30

Apr-Sept = 31

Oct-Mar = 28

Table A.11. Characterization of U.S. and Canadian Studies of Short-Term Exposure to PM2.5

and Time of Stroke Symptom Onset

Author

Study

Years Location Outcome Population

Size

Fraction

Mean 24-h

avg

Concentration

(μg/m3)

Upper Percentile

Concentrations

(μg/m3)

Wellenius

et al.

(2012)

1999-

2008

Boston,

MA

Time of

Symptom

Onset

(Ischemic

Stroke)

Patients

admitted to

BIDMC PM2.5 NR NR

BIDMC= Beth Israel Deaconess Medical Center
57

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