From: "Frey, Nathan J." <Nathan_J._Frey@omb.eop.gov>

To: Lydia Wegman/RTP/USEPA/US@EPA, "Mancini, Dominic J."

<Dominic_J._Mancini@omb.eop.gov> Cc: Michael Ling/RTP/USEPA/US@EPA, Anna Wood/RTP/USEPA/US@EPA, Joseph

- J

Dougherty/DC/USEPA/US@EPA, "Lee, Amanda I." <Amanda_I._Lee@omb.eop.gov> Date: 12/14/2012 08:06 AM Subject: Summary of Interagency Comments Under EOs 12866 and 13563
-- PM NAAQs Final Rule RIA
Attached please find a summary of interagency comments under EOs 12866 and 13563 regarding the PM NAAQs final rule preamble and RIA. In these files, previous EPA edits were accepted and anything additional should show in tracked changes. Please let me know if you have any questions or if you would like to discuss further.

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- 2 E.O. 12866_PM NAAQS_2060 - AO47_FRN_ RIA_Chap5 _20121120 .dox

CHAPTER 5 HUMAN HEALTH BENEFIT S ANALYSIS APPROACH AND RESULTS 5.1 Synopsis This chapter present s the estimated human health benefits for the revised National Ambient Air Quality Standards (NAAQS) for particulate matter (PM) . In this chapter , we quantify the health

- related benefits of the fine particulate matter ( PM 2.5 )

- related air quality improvements resulting from the illustrative emission control scenarios that reduce emissions of directly emitted particles and precursor pollutants including SO 2 and NO x to reach alternative PM 2.5 NAAQS levels in 2020

. 1
T hese benefits are relative to a n analytical baseline reflecting nationwide attainment of the current primary PM 2.5 standards (i.e., annual standard of 15 μg/m 3 and 24

- hour standard of 35 μg/m 3 ) that includes promulgated national regulations and illustrative emission controls to simulate attainment with 15/35 as well as a NO x emission adjustment to reflect expected reductions in mobile NO x emissions between 2020 and 2025

. W e project PM 2.5 levels in certain areas that would exceed the revised annual standard of 12 μg/m 3 as well as alternative annual standards of 13 and 11 μg/m 3 after simulate d attainment with 15/35 in the analytical baseline

. Table 5

- 1 summarizes the total monetized benefits of the revised and alternative PM 2.5 standards in 2020. These estimates reflect the sum of the economic value of estimated PM 2.5 mortality impacts identified and the value of all morbidity impacts. The estimated benefits for the revised and alternative standards are in addition to the substantial benefits estimated for several recent implementation rules (U.S. EPA, 2009a, 2011c, 20 11d, 2011e). Rules such as the Mercury and Air Toxics Standard (MATS) and other emission reductions will have substantially reduced ambient PM 2.5 concentrations by 2020 in the East, such that no additional controls would be needed in the East for the revis ed annual standard of 12 μg/m 3 . Thus, all of the estimated benefits occur in California because this is the only state that needs additional air quality improvement beyond the analytical baseline after accounting

1 The estimates in this chapter reflect incremental emissions reductions from an analytical baseline that gives an adjustment to the San Joaquin and South Coast areas in California for NOx emissions reductions expected to occur between 2020 and 2025, when those areas are expected to demonstrate attainment with the revised standards . Full benefits of the revised standards in those two areas will not be realized until 2025.

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- 3 for air quality improvements from recent ru les. This fact does, however, introduce some added uncertainty, as discussed below. Also of interest, is that the estimated benefits for the revised NAAQS are about double what was predicted in the proposal due to a combination of updates to the analytic baseline (updated emissions inventories and ambient air quality data

– as discussed in Chapter xx)

, changes in the emissions reductions approach (as disussed in Chapter xx), and changes in this chapter, the most significant of which are xxxx. EPA believes that all of these improvements lead to a more refined estimate.

Table 5 - 1. Estimated Monetized Benefits of the of Revised and Alternative Annual PM 2.5 Standards in 2020 Incremental to the Analytical Baseline ( billions of 2010$ ) a

Benefits Estimate 13 μg/m 3 12 μg/m 3 11 μg/m 3 Economic value of avoided PM 2.5 - related morbidities and premature deaths using PM 2.5 mortality estimate from Krewski et al. (2009) 3% discount rate $1.3 + B $ 4.0 +B $13 + B 7% discount rate $1.2 + B $3. 6 +B $12 + B Economic value of avoided PM 2.5 - related morbidities and premature deaths using PM 2.5 mortality estimate from Lepeule et al. (2012) 3% discount rate $2.9 + B $ 9.1 +B $ 29 + B 7% discount rate $2.6 + B $ 8.2 +B $ 26 + B

a Rounded to two significant figures. Avoided premature deaths account for over 98 % of monetized benefits here , which are discount ed over the SAB

- recommended 20

- year segmented lag. It was not all possible to quantify all benefits due to data limitations in this analysis. “ B ” is the sum of all unquanti fied health benefits and welfare co

benefits

. As we describe in detail below, we estimate PM

- related health impacts using concentration

- response relationships drawn from the epidemiological literature. In general, we are more confident in the magnitude of the risks we estimate from simulated PM 2.5 concentrations that coincide with the bulk of the observed PM concentrations in the epidemiological studies that are used in th e benefits estimates

. Likewise, we are less confiden t in the risk we estimate from sim ulated PM 2.5 concentrations that fall below the bulk of the observed data in these studies. As noted in the preamble to the rule, the range from the 25 th to 10 th percentiles of the air quality data in the epidemiology studies is a reasonable range below wh ich we start to have appreciably less confidence in the magnitude of the associations observed in the epidemiological studies. M ost of the estimated avoided premature deaths

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- 4 occur at or above the lowest measured PM 2.5 concentration in the two studies that are used to estimate mortality benefits. In addition to PM 2.5 benefits, implementation of emissions controls to reach some of the alternative PM 2.5 standards would reduce other ambient pollutants , such as SO 2 , NO 2 , and ozone . However, because the method used in this analysis to simulate attainment does not account for changes in ambient concentrations of other pollutants , we were not able to quantify the co - benefits of reduced exposure to other pollutants

. In addition, due to data and m ethodology limitations, we were unable to estimate additional health benefits associated with exposure to PM 2.5 or the additional co - benefits from improvements in welfare effects (i.e., non - health effects) associated with emission reductions to attain the primary standard , such as visibility

. We describe the unquantified health benefits in this chapter and the unquantified welfare co - benefits in Chapter 6

. 5.2 Overview This chapter contains a subset of the estimated health benefits of the revised and alternative PM 2.5 standards in 2020 that the EPA was able to quantify, given the available resources and methods . The analysis in this chapter aims to characterize the benefits of the air quality changes resulting from the implementation of new PM standard s by answering two key questions: 1. What are the health effects of changes in ambient particulate matter (PM 2.5 ) resulting from reductions in directly emitted PM 2.5 and precursors due to the attainment of a new PM 2.5 standard ? 2. What is the economic value of these effects? In this analysis , we consider an array of health impacts attributable to changes in PM 2.5 . The Integrated Science Assessment for Particulate Matter (“PM ISA”) (U.S. EPA, 2009b ) identif ies the human health effects associated with ambi ent particles , which include premature mortality and a variety of morbidity effects associated with acute and chronic exposures. Table 5

- 2 summarizes human health categories contained within the core benefits estimate as well as those categories that were unquantified due to limited data or resources. It is important to emphasize that the list of unquantified benefit categories is not exhaustive, nor is quantification of each effect complete. To ident ify human health benefits that we could quantify with confidence we selected endpoints that were classified as causal or likely causal in the PM ISA ,

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- 5 and we excluded effects not identified as having at least a causal, likely causal, or suggestive relations hip with the affected pollutants in the most recent comprehensive scientific assessment, such as an Integrated Science Assessment (ISA). This decision does not imply that additional relationships between these and other human health and environmental co

- be nefits and the affected pollutants do not exist. Due to this decision criterion, we excluded some effects that were identified in previous lists of unquantified benefits in other RIAs (e.g., UVb exposure). The benefits analysis in this chapter relies on an array of data inputs

— including air quality modeling, health impact functions and valuation estimates among others

— which are themselves subject to uncertainty and may also in turn contribute to the overall uncertainty in this analysis. We employ several te chniques to characterize this uncertainty, which are described in detail in section 5.4.

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- 6 Table 5
- 2 . Human Health Effects of Pollutants Potentially Affected by Strategies to Attain

the Primary PM 2.5 Standards

Benefits Category Specific Effect Effect Has Been Quantified Effect Has

Been Monetized More Information Improved Human Health Reduced incidence of premature mortality from exposure to PM 2.5 Adult premature mortality based on cohort

study estimates and expert elicitation estimates (age >25 or age > 30)   Section 5.6

Infant mortality (age <1)   Section 5.6 Non

- fatal heart attacks (age > 18)   Section 5.6 Hospital admissions

— respiratory (all ages)   Section 5.6 Hospital admissions

— cardiovascular (age >20)   Section 5.6 Emergency department visits for asthma (all ages)   Section 5.6 Acute bronchitis (age 8

– 12)   Section 5.6 Lower respiratory symptoms (age 7

– 14)   Section 5.6 Upper respiratory symptoms (asthmatics age 9
– 11)   Section 5.6
Asthma exacerbation (asthmatics age 6

– 18)   Section 5.6 Lost work days (age 18

– 65)   Section 5.6 Minor restricted

- activity days (age 18

– 65)   Section 5.6 Chronic Bronchitis (age >26)

— a

— a Section 5.6 Emergency department visits for cardiovascular effects (all ages) — a

— a Section 5.6 Strokes and cerebrovascular disease (age 50

– 79) — a

— a Section 5.6 Other cardiovascular effects (e.g., other ages)

— — PM ISA b Other respiratory effects (e.g., pulmonary function, non

- asthma ER visits, non

- bronchitis chronic diseases, other ages and populations) — — PM ISA b

Reproductive and developmental effects (e.g., low birth weight, pre

- term births, etc.) — — PM ISA b,c
Cancer, mutagenicity, and genotoxicity effects

— — PM ISA b,c (continued)

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- 7 Table 5
- 2. Human Health Effects of Pollutants Potentially Affected by Strategies to Attain

the Primary PM 2.5 Standards (continued)

Benefits Category Specific Effect Effect Has Been Quantified Effect Has

Been Monetized More Information Reduced incidence of mortality from exposure to ozone Premature mortality based on short

- term

study estimates (all ages) — — Ozone CD, Draft Ozone ISA d Premature mortality based on long

- term study estimates (age 30

– 99) — — Ozone CD, Draft Ozone ISA d Hospital admissions

— respiratory causes (age > 65) — — Ozone CD, Draft ISA d Hospital admissions

— respiratory causes (age <2) — — Ozone CD, Draft ISA d Emergency department visits for asthma (all ages) — — Ozone CD, Draft ISA d Minor restricted

- activity days (age 18

– 65)

— — Ozone CD, Draft ISA d School absence days (age 5

– 17)

— — Ozone CD, Draft ISA d Decreased outdoor worker productivity (age 18
– 65) — — Ozone CD, Draft ISA d Other respiratory effects (e.g., premature aging of lungs) — — Ozone CD, Draft ISA b Cardiovascular and nervous system effects

— — Ozone CD, Draft ISA c Reproductive and developmental effects

— — Ozone CD, Draft ISA c Reduced incidence of morbidity from exposure to NO 2 Asthma hospital admissions (all ages)

— — NO 2 ISA d

Chronic lung disease hospital admissions (age > 65) — — NO 2 ISA d
Respiratory emergency department visits (all ages) — — NO 2 ISA d
Asthma exacerbation (asthmatics age 4

– 18)

— — NO 2 ISA d Acute respiratory symptoms (age 7

– 14)

— — NO 2 ISA d Premature mortality

— — NO 2 ISA b,c

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- 8 Other respiratory effects (e.g., airway hyperresponsiveness and inflammation, lung function, other ages and populations) — — NO 2 ISA b,c
(continued)

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- 9 Table 5
- 2. Human Health Effects of Pollutants Potentially Affected by Strategies to Attain

the Primary PM 2.5 Standards (continued)

Benefits Category Specific Effect Effect Has Been Quantified Effect Has

Been Monetized More Information Reduced incidence of morbidity from exposure to SO 2 Respiratory hospital admissions (age > 65)

— — SO 2 ISA d

Asthma emergency department visits (all ages) — — SO 2 ISA d
Asthma exacerbation (asthmatics age 4

– 12)

— — SO 2 ISA d Acute respiratory symptoms (age 7

– 14)

— — SO 2 ISA d Premature mortality

— — SO 2 ISA b,c Other respiratory effects (e.g., airway hyperresponsiveness and inflammation, lung function, other ages and populations) — — SO 2 ISA b,c

Reduced incidence of morbidity from exposure to methylmercury (through role of sulfate in methylation) Neurologic effects

— IQ loss

— — IRIS; NRC, 2000 d

Other neurologic effects (e.g., developmental delays, memory, behavior) — — IRIS; NRC, 2000 b

Cardiovascular effects

— — IRIS; NRC, 2000 b,c Genotoxic, immunologic, and other toxic effects — — IRIS; NRC, 2000 b,c

a We quantify these benefits in a sensitivity analysis, but not in the core analysis. b We assess these benefits qualitatively because we do not have sufficient confidence in available data or methods.
c We assess these benefits qualitatively because current evidence is only suggestive of causality or there are other s ignificant concerns over the strength of the association. d We assess these benefits qualitative ly due to time and resource limitations for this analysis. As described in Chapter 1 of this RIA, there are important differences worth noting in the design and analytical objectives of NAAQS RIAs compared to RIAs for implementation rules, such as the recent MATS rule (U.S. EPA, 2011d). The NAAQS RIAs illustrate the potential costs and benefits of attaining a revised air quality standard nationwide based on an ar ray of emission reduction strategies for different sources including known and unknown controls, incremental to implementation of existing regulations and controls needed to attain the current standards. In short, NAAQS RIAs hypothesize, but do not predict , the emission reduction strategies that States may choose to enact when implementing a revised NAAQS. The setting of a NAAQS does not directly result in costs or benefits, and as such, NAAQS RIAs are

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- 10 merely illustrative and the estimated costs and benefit s are not intended to be added to the costs and benefits of other regulations that result in specific costs of control and emission reductions. By contrast, the emission reductions from implementation rules are generally for specific, well

- characterized so urces, such as the recent MATS rule addressing emissions from coal and oil

- fired electricity generating units (U.S. EPA, 2011d). In general, the EPA is more confident in the magnitude and location of the emission reductions for implementation rules. As such, emission reductions achieved under promulgated implementation rules such as MATS have been reflected in the baseline of this NAAQS analysis. Subs equent implementation rules will be reflected in the baseline for the next PM NAAQS review. For this reason, the benefits estimated provided in this RIA and all other NAAQS RIAs should not be added to the benefits estimated for implementation rules. 5.3 Update d Methodology Presented in this RIA The benefits analysis presented in this chapter incorporates an array of policy and technical changes that the Agency has adopted since the previous review of the PM 2.5 standards in 2006, and since publication of the proposal RIA for this rulemaking . Below we note the aspects of this analysis that differ from the proposal RIA (U.S. EPA, 2012 a ) : 1. Incorporation of the newest Harvard Six Cities mortality study . In 2012 , Lepeule et al. published an extended analysis of t he Six Cities cohort. Compared to the study it replaces ( Laden et al. , 200 6 ), this new analysis follows the cohort for a longer time and includes more years of PM 2.5 monitoring data . The all

- cause PM 2.5 mortality risk coefficient drawn from Lepeule et al. (2012 ) is roughly similar to the Laden et al. (200 6 ) risk coefficient applied in the EPA’s recent analyses of long

- term PM 2.5 mortality and has narrower confidence intervals

. 2. Updated demographic data

. We updated the population demographic data in BenMAP to reflect the 2010 Census and future projections based on economic forecasting models developed by Woods and Poole, Inc. (Woods and Poole, 2012). These data replace the earlier demographic projection data from Woods and Poole (2007). 3. Incorporation of new morbidity studies . Since the publication of the PM ISA (U.S. EPA, 2009 ) the epidemiological literature has produced several new studies examining the association between short

- term PM 2.5 exposure and re spiratory and cardiovascular hospitalizations, respiratory and cardiovascular emergency department visits , and stroke . Upon careful evaluation of this new literature identified in the Provisional Science Assessment for Particulate Matter (“Provisional

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- 11 Asse ssment”) (U.S. EPA, 2012b) we added several new studies to our health impact assessment. 4. Updated the survival rates for non

- fatal acute myocardial infarctions

. Based on recent data from Agency for Healthcare Research and Quality ’ s Healthcare Utilization Project National Inpatient Sample database ( AHRQ , 2009) , we identified death rates for adults hospitalized with acute myocardial infarction stratified by age. These rates replace the survival rates from Rosamond et al. (1999). 5
. Expanded uncertainty assessment
. We clarified the comprehensive assessment of the various uncertain parameters and assumptions within the benefits analysis and expanded the evaluation of air quality benchmarks (previously the LML analysis)

. Although the list above identifies t he major changes implemented since the proposal RIA , the EPA has also updated several additional components of the benefits analysis since the 2006 PM NAAQS RIA (U.S. EPA, 2006 a ). In the Portland Cement NESHAP proposal RIA (U.S. EPA, 2009 a ), the Agency no longer assumed a concentration threshold in the concentration

response function for PM 2.5 - related health effects and began using the benefits derived from the two major cohort studies of PM 2.5 and mortality as the core benefits estimates , while still inclu ding a range of sensitivity estimates based on the EPA ’ s PM 2.5 mortality expert elicitation

. In the NO 2 NAAQS proposal RIA (U.S. EPA, 2009a ), we revised the estimate used for the value

of

- a - statistical life to be consistent with Agency guidance

. In the proposed CSAPR (previously the “ Transport Rule ” ) (U.S. EPA, 2010g) , we incorporated the “ lowest measured level ” assessment to help characterize uncertainty in estimates of benefits of reductions in PM 2.5 at lower baseline concentrations of PM 2.5 . In the fi nal CSAPR (U.S. EPA, 2011c ), we updated the baseline incidence rates for hospital admissions and emergency department visits and asthma prevalence rates. We direct the reader to each of these RIAs for more information on these changes. In the proposal RIA for this NAAQS review (U.S. EPA, 2012 a ) , we updated the American Cancer Society cohort study to Krewski et al. (2009), updated health endpoints in the core and sensitivity analyses, incorporated new morbidity studies, updated the median wage data in the cost
- of

- illness studies, and expan ded the uncertainty assessment.

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- 12 5.4 Human Health Benefits Analysis Methods We follow a “ damage

- function ” approach in calculating total benefits of the modeled changes in environmental quality. 2 This approach estimates changes in individual health endpoints (specific effects that can be associated with changes in air quality) and assigns values to those changes assuming independence of the values for those individual endpoints

. Total benefits are calculated simply as the sum of the values for all non

- overlapping health endpoints. The “ damage

- function ” approach is the standard method for assessing costs and benefits of environmental quality programs and has been used in several recent published analyses (Levy et al., 2009; Fann et al

. , 201 2 a ; Tagaris et al., 2009)

. To assess economic value in a damage

- function framework, the changes in environmental quality must be translated into effects on people or on the things that people value. In some cases, the changes in environmental quality can be directly valued, as is the case for changes in visibility. In other cases, such as for changes in ozone and PM, a impact analysis must first be conducted to convert air quality changes into effects that can be assigned dollar values. For the purposes of this RIA, the health impacts analysis (HIA) is limited to those health effects that are directly linked to ambient levels of air pollution and specifically to those linked to PM 2.5 . We note at the outset that the EPA rarely has the time or res ources to perform extensive new research to measure directly either the health outcomes or their values for regulatory analyses. Thus, similar to Kunzli et al. (2000) and other , more recent health impact analyses, our estimates are based on the best availa ble methods of benefits transfer. Benefits transfer is the science and art of adapting primary research from similar contexts to obtain the most accurate measure of benefits for the environmental quality change under analysis. Adjustments are made for the level of environmental quality change, the socio

- demographic and economic characteristics of the affected population, and other factors to improve the accuracy and robustness of benefits estimates. 5.4.1 Health Impact Assessment The health impact assessment (HIA ) quantifies the changes in the incidence of adverse health impacts resulting from changes in human exposure to PM 2.5 and ozone air quality. HIAs

2 The damage function approach is a more comprehensive method of estimating total benefits than the hedonic price approach applied to housing prices, which require s homebuyers to be knowledgeable of the full magnitude of health risks associated with their home purchase. See discussion of hedonic studies in Chapter 6.

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- 13 are a well

- established approach for estimating the retrospective or prospective change in adverse health impac ts expected to result from population

- level changes in exposure to pollutants (Levy et al. , 2009). PC

- based tools such as the environmental Ben efits M apping and A nalysis P rogram (BenMAP) can systematize health impact analyses by applying a database of key input parameters, including health impact functions and population projections

— provided that key input data are available, including air quality estimates and risk coefficients (Abt Associates, 2010) . Analysts have applied the HIA approach to estimate huma n health impacts resulting from hypothetical changes in pollutant levels (Hubbell et al. , 2005; Tagaris et al. , 2009; Fann et al. , 201 2 a ) . The EPA and others have relied upon this method to predict future changes in health impacts expected to result from the implementation of regulations affecting air quality ( e.g., U.S. EPA, 201 1d ). For this assessment, the HIA is limited to those health effects th at are directly linked to ambient PM 2.5 concentrations. There may be other indirect health impacts associated with implementing emissions controls, such as occupational health exposures. The HIA approach used in this analysis involves three basic steps: (1 ) utilizing projections of PM 2.5 air quality 3 and estimating the change in the spatial distribution of the ambient air quality; (2) determining the subsequent change in population

- level exposure; (3) calculating health impacts by applying concentration

- res ponse relationships drawn from the epidemiological literature (Hubbell et al. , 2009) to this change in population exposure. A typical health impact function might look as follows: (5

. 1) where y 0 is the baseline incidence rate for the health endpoint being quantified (for example, a health impact function quantifying changes in mortality would use the baseline, or background, mortality rate for the given population of interest); Pop is the populati on affected by the change in air quality; x is the change in air quality; and β is the effect coefficient drawn from the epidemiological study. Figure 5

- 1 provides a simplified overview of this approach.

3 Projections of ambient PM 2.5 concentrations for this analysis were generated using the Community M ultiscale Air Quality model (CMAQ). See Chapter 3 of this RIA for more information on the air quality modeling.

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- 14 Figure 5 - 1. Illustration of BenMAP Approach

Baseline Air Quality Post
- Policy Scenario Air Quality

Incremental Air Quality Improvement

PM 2.5 Reduction

Population Ages 30
- 99 Background Incidence Rate Effect

Estimate Mortality

Reduction

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- 15 5.4.2 Economic Valuation of Health Impacts After quantifying the change in adverse health impacts, the final step is to estimate the economic value of these avoided impacts. The appropriate economic value for a change in a health effect depends on whether the health effect is viewed ex ante (before the effect has occurred) or ex post (after the effect has occurred). Reductions in ambient concentrations of air pollution generally lower the risk of future adverse health effects by a small amount for a large population. The appropriate economic measure is therefore ex ante willingness to p ay (WTP) for changes in risk. E pidemiological studies generally provide estimates of the relative risks of a particular health effect for a given increment of air pollution (often per 10 μg/m 3 for PM 2.5 )

. These relativ e risks can be used to develop risk coefficients that relate a unit reduction in PM 2.5 to change s in the incidence of a health effect. In order to value these changes in incidence, WTP for changes in risk need to be converted into WTP per statistical incid ence. This measure is calculated by dividing individual WTP for a risk reduction by the related observed change in risk. For example, suppose a measure is able to reduce the risk of premature mortality from 2 in 10,000 to 1 in 10,000 (a reduction of 1 in 1 0,000). If individual WTP for this risk reduction is $100, then the WTP for an avoided statistical premature mortality amounts to $1 million ($100/0.0001 change in risk). Using this approach, the size of the affected population is automatically taken into account by the number of incidences predicted by epidemiological studies applied to the relevant population. The same type of calculation can produce values for statistical incidences of other health endpoints. For some health effects, such as hospital adm issions, WTP estimates are generally not available. In these cases, we use the cost of treating or mitigating the effect. For example, for the valuation of hospital admissions we use the avoided medical costs as an estimate of the value of avoiding the hea lth effects causing the admission. These cost

- of

- illness (COI) estimates generally (although not necessarily in every case) understate the true value of reductions in risk of a health effect. They tend to reflect the direct expenditures related to treatment but not the value of avoided pain and suffering from the health effect. We use the BenMAP model version 4.0.5 2 (Abt Associates, 2010 ) to estimate the health impacts and monetized health benefits for the proposed standard

. Figure 5

- 2 shows the dat a inputs and outputs for the BenMAP model.

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- 16 Figure 5 - 2. Data Inputs and Outputs for the BenMAP Model

5.5 Uncertainty Characterization In any complex analysis using estimated parameters and inputs from numerous models, there are likely to be many sources of uncertaint y . T his analysis is no exception. As outlined both in this and preceding chapters, this analysis includes many data sources as inputs, including emission inventories, air quality data from models (with their associated parameters and inputs), population data, population estimates, health effect estimates from epidemiology studies, economic data for monetizing benefits, and assumptions regarding the future state of the world (i.e., regulations, technology, and human behavior). Each of these inputs may be u ncertain and would affect the benefits estimate. When the uncertainties from each stage of the analysis are compounded, even small uncertainties can have large effects on the total quantified benefits. After reviewing the EPA ’ s approach, the National Resea rch Council (NRC) (2002, 2008) , which is part of the National Academies of Science, concluded that the EPA ’ s general

Modeled Baseline and Post
- Control Ambient PM 2.5

PM 2.5 Health Functions

Economic Valuation Functions 2020 Population Projections

PM 2.5 Incremental Air Quality Change

PM 2.5 - Related Health Impacts Woods & Poole Population Projections

Background Incidence and Prevalence Rates

Monetized PM 2.5 - related Benefits Blue identifies a user
- selected input within the BenMAP model Green identifies a data input generated outside of the BenMAP model Census Population Data

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- 17 methodology for calculating the benefits of reducing air pollution is reasonable and informative in spite of inherent uncertainties. The NR C also highlighted the need to conduct rigorous quantitative analyses of uncertainty and to present benefits estimates to decision makers in ways that foster an appropriate appreciation of their inherent uncertainty. Since the publication of these reports, the EPA has continued work to improve the characterization of uncertainty in both health incidence and benefits estimates. In response to these recommendations, we have expanded our previous analyses to incorporate additional quantitative and qualitative characterizations of uncertainty. Although we have not yet been able to make as much progress towards a full, probabilistic uncertainty assessment as envisioned by the NAS as we had hoped, we have added a number of additional quantitative and qualitative a nalyses to highlight the impact that uncertain assumptions may have on the benefits estimates. In addition, for some inputs into the benefits analysis, such as the air quality data, it is difficult to address uncertainty probabilistically due to the comple xity of the underlying air quality models and emission inputs. Therefore, we decline to make up alternative assumptions simply for the purpose of probabilistic uncertainty characterization when there is no scientific literature to support alternate assumpt ions. To characterize uncertainty and variability, we follow an approach that combines elements from two recent analyses by the EPA (U.S. EPA, 2010b; 2011a), and uses a tiered approach developed by the World Health Organization (WHO) for characterizing unc ertainty (WHO, 2008). We present this tiered assessment as well as an assessment of the potential impact and magnitude of each aspect of uncertainty In Appendix 5c

. D ata limitations prevent us from treating each source of uncertainty quantitatively and from reaching a full

- probabilistic simulation of our results , but we were able to consider the influence of uncertainty in the risk coefficients and economic valuation functions by incorporating six quantitative analyses described in more detail below : 1. A Monte Carlo assessment that accounts for random sampling error and between study variability in the epidemiological and economic valuation studies; 2. A concentration benchmark assessment that characterizes the distribution of avoided PM 2.5 - related deat hs relative to specific concentrations in the long

- term epidemiological studies used to estimate PM 2.5 - related mortality; 3. The quantification of PM

- related mortality using alternative PM 2.5 mortality effect estimates drawn from two long

- term cohort studies and an expert elicitation ;

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- 18 4. S ensitivity analys e s of several aspects of PM

- related benefits ; 5. Distributional analyses of PM 2.5 - related benefits by locati on, race, income, and education; and 6. An analysis of the influence of various parameters on total monetized benefits

. 5.5.1 Monte Carlo A ssessment Similar to other recent RIAs, we used Monte Carlo methods for characterizing random sampling error associated with the concentration response functions from epidemiological studies and random effects modeling to characterize both sampling error and variabi lity across the economic valuation functions. The Monte Carlo simulation in the BenMAP software random ly samples from a distribution of incidence and valuation estimates to characterize the effects of uncertainty on output variables. Specifically, we used Monte Carlo methods to generate confidence intervals around the estimated health impact and monetized benefits. The reported standard errors in the epidemiological studies determined the distributions for individual effect estimates for endpoints estimated using a single study. For endpoints estimated using a pooled estimate of multiple studies, the confidence intervals reflect both the standard errors and the variance across studies . The confidence intervals around the monetized benefits incorporate the ep idemiology standard errors as well as the distribution of the valuation function. These confidence intervals do not reflect other sources of uncertainty inherent within the estimates, such as baseline incidence rates, populations exposed and transferabilit y of the effect estimate to diverse locations. As a result, the reported confidence intervals and range of estimates give an incomplete picture about the overall uncertainty in the benefits estimates. 5.5.2 Concentration Benchmark Analysis for PM 2.5 We include a concentration benchmark assessment, which identifies the baseline (i.e. , pre - rule) annual mean PM 2.5 levels at which populations are exposed and specific concentrations in the two long

- term cohort stud ies we use to quantify mortality impacts. This analysis characterize s avoided PM 2.5 - related deaths relative to the 10 th and 25 th percentiles of the air quality data used the Krewski et al. (2009) study as well as the lowest measured level (LML) of the Krewski et al. (2009) and Lepeule et al. (20) studi es.

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- 19 5.5.3 Alternative Conce ntration - Response Functions for PM 2.5 – Related Mortality We assign the greatest economic value to the reduction in PM 2.5 related mortality risk

. Therefore, it is particularly important to attempt to characterize the uncertainties associated with reductions in premature mortality. To better understand the concentration

- response relationship between PM 2.5 exposure and premature mortality, the EPA conducted an expert elicitation in 2006 (Roman et al., 2008; IEc, 2006). 4 In general, th e results of the expert elicitation support the conclusion that the benefits of PM 2.5 control are very likely to be substantial. Alternative concentration

- response functions are useful for assessing uncertainty beyond random statistical error, including un certainty in the functional form of the model or alternative study design. Thus, we include the expert elicitation results as well as standard errors approaches to provide insights into the likelihood of different outcomes and about the state of knowledge regarding the benefits estimates. In this analysis, we present the results derived from the expert elicitation as indicative of the uncertainty associated with a major component of the health impact functions, and we provide the independent estimates deriv ed from each of the twelve experts to better characterize the degree of variability in the expert responses. In previous RIAs, the EPA presented benefits estimates using concentration response functions derived from the PM 2.5 Expert Elicitation (Roman et a l., 2008) as a range from the lowest expert value (Expert K) to the highest expert value (Expert E). However, this approach did not indicate the agency ’ s judgment on what the best estimate of PM 2.5 benefits may be ; as well , and the EPA ’ s independent Science Advisory Board (SAB) recommended refinements to the raised concerns about this way EPA present at ed ion the results of the elicitation (U.S. EPA

SAB, 2008). Therefore, we began to present the cohort

- based studies (Krewski et al., 2009; Laden et al., 2 006) 5 as our core estimates in the proposal RIA for the Portland Cement NESHAP (U.S. EPA, 2009 a ). Using alternate relationships between PM 2.5 and premature mortality supplied by experts, higher and lower benefits estimates are plausible, but most of the ex pert
based estimates of the mean PM 2.5 effect on mortality fall between the two epidemiology

based estimates (Roman et al., 2008)

. In addition to these studies, we have included a

4 Expert elicitation is a formal, highly structured and well documented process whereby expert judgments, usually of multiple experts, are obtai ned (Ayyub, 2002). 5 We have since updated the the Harvard Six Cities cohort study from Laden et al. (2006) to use the most recent follow

- up publication of this cohort (Lepeule et al, 2012).

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- 20 discussion or other recent multi

- state cohort studies conducted in North America, but we have not estimated benefits using the effect coefficients from these studies. Please note that the benefits estimates results presented are not the direct results from the studies or expert elicitation; rather, the estimates are based in pa rt on the effect coefficients provided in those studies or by experts

. In addition, the experts provided distributions around their mean PM 2.5 effect estimates, which provides more information regarding the overall range of uncertainty , and this overall ra nge is larger than the range of the mean effect estimates from each of the experts. Even these multiple characterizations with confidence intervals omit the contribution to overall uncertainty from uncertainty in air quality changes, baseline incidence rat es, and populations exposed. Furthermore, the approach presented here does not yet include methods for addressing correlation between input parameters and the identification of reasonable upper and lower bounds for input distributions characterizing uncertainty in additional model elements. As a result, the reported confidence intervals and range of estimates give an incomplete picture about the overall uncertainty in the estimates. This information should be interpreted within the context of the larg er uncertainty surrounding the entire analysis. 5.5.4 Sensitivity Analyses For some aspects of uncertainty, we have sufficient data to conduct sensitivity analyses. In this analysis, we performed five such analyses for the revised standard level . In particular, we: 1. Assessed the sensitivity of the economic value of reductions in the risk of PM 2.5 -

related death according to differing assumptions regarding the lag between PM 2.5 exposure and premature death. The timing of such premature deaths affects the magnitud e of the discounted PM 2.5 - related mortality benefits

. I n this sensitivity assessment , we consider 6 alternative cessation lags. 2. Characterized the sensitivity of the economic value of the health endpoints valued using willingness

- to
- pay estimates to a higher and a lower assumption regarding income elasticity. As we discuss below, economic theory argues that individual willingness to pay increases as personal income grows. The relationship between growth in personal income and willingness

- to
- pay to red uce mortality and morbidity risk is characterized by the income growth factor. 3. Summarize d the avoided cases of certain health endpoints for which we either lacked an appropriate economic value (cardiovascular hospital admissions and

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- 21 stroke) or in which we no longer had sufficient confidence to retain in our primary benefits estimate (chronic bronchitis). 4. Assessed the sensitivity of the benefits results to the new population data from the 2010 C ensus . 5. Assessed the sensitivity of the benefits results to an analysis year of 2025. 5.5.5 Distributional Assessment In an Appendix to the proposal RIA , we characterize d the distribution of PM 2.5 - related benefits based on the geographic distribution of race and education in areas where the illustrative emission reduction strategies would reduce PM 2.5 concentrations

. In that assessment , we aim ed to answer two key questions: 1. What wa s the estimated distribution of PM 2.5 - related mortality risk based on the race a nd education characteristics o f the population living within areas projected to exceed alternative combinations of the proposed primary PM 2.5 standards ? 2. How would air quality improvements within these counties change the distribution of risk among populations of different races and educational attainment ? 6
Th at assessment wa s generally consistent with the distributional assessments performed in support of MATS ( U.S. EPA, 2011 c ), with one key difference. The e nvironmental j ustice analyses accompanying the MATS RIA applied CMAQ

- mo deled PM 2.5 predictions that represent the change in air quality after the implementation of each rule. By contrast, the proposal RIA aim ed to illustrate the potential benefits and costs of attaining alternative primary PM 2.5 standards ; the states will ultimately implement attainment strategies, which may differ greatly from the least

- cost strategy the EPA modeled here. Alternative emission reduction strategies
— particularly those that maximize benefits to human health and provide a more equitable distribution of risk

— are also available to the states, though not modeled here (Fann et al. , 2012b). Due in part to time constraints, the EPA did not perform such an analysis for the final RIA, and instead refers readers to the Appendix noted ab ove.

6 In this analysis we assess the change in risk among populations of different race and educational attainment. As we discuss further in the methodology, we consider this last variable because of the availability of education

modified PM 2.5 mortality risk estimates.

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- 22 5.5.6 Influence Analysis — Quantitative Assessment of Uncertainty In the past few years, the EPA has initiated several projects to improve the characterization of uncertainty for benefits analysis. In particular, the EPA recently completed the first phase of a quantitative uncertainty analysis of benefits, hereafter referred to as the

“ Influence Analysis ” (Mansfield et al., 2009). The Influence Analysis diagramed the uncertain components of each step within the benefits analysis process, identified plausible r anges for a sensitivity analysis, and assessed the sensitivity to total benefits to changes in each component. Although this analysis does not quite fulfill the goal of a full probabilistic assessment, it accomplished the necessary first steps and identified the challenges to accomplishing that goal. Below are some of the preliminary observations from the first phase of th e project.

 The components that contribute the most to uncertainty of the monetized benefits and mortality incidence (in order of importance) are the value

- of

- a - statistical

- life ( VSL ) , the concentration

- response ( C

- R ) function for mortality, and change in P M 2.5 concentration.

 The components that contribute the least to uncertainty of the monetized benefits and mortality incidence are population, morbidity valuation, and income elasticity.

 The choice of a C

- R function for mortality affects the mortality incid ence and monetized benefits more than other sources of uncertainty within each C

- R function.

 Alternative cessation lag structures for mortality have a moderate effect on the monetized benefits.

 Because the health impact function is essentially linear, the key components show the same sensitivity across all mortality C

- R functions even if the midpoints differ significantly from one expert to another. 5.5.7 Qualitative Assessment of Uncertainty and Other Analysis Limitations Although we strive to incorporate as man y quantitative assessments of uncertainty as possible , there are several aspects we are only able to address qualitatively. These aspects are important factors to consider when evaluating the relative benefits of the emission reduction strategies for the r evised and alternative annual standards:
T he total monetized benefits presented in this chapter are based on our interpretation of the best available scientific literature and methods and supported by the EPA ’ s independent

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- 23 SAB (Health Effects Subcommittee) ( SAB

- HES ) (U.S. EPA

- SAB, 2010 a ) and the National Academies of Science ( NAS ) (NRC, 2002). The benefits estimates are subject to a number of assumptions and uncertainties. For example, the key assumptions underlying the estimates for premature mortality, w hich account for over 9 8 % of the total monetized benefits in this analysis , include the following: 1. We assume that all fine particles, regardless of their chemical composition, are equally potent in causing premature mortality. This is an important assu mption, because PM 2.5 varies considerably in composition across sources, but the scientific evidence is not yet sufficient to allow differentiation of effect estimates by particle type. The PM ISA, which was twice reviewed by Clean Air Scientific Advisory Committee (SAB

- CASAC ) , concluded that “many constituents of PM 2.5 can be linked with multiple health effects, and the evidence is not yet sufficient to allow differentiation of those constituents or sources that are more closely related to specific outcome s” (U.S. EPA, 2009b). These uncertainties are likely to be magnified in the current analysis to the extent that the emissions controls are less diverse when focusing on one small region of the country rather than EPA’s more typical NAAQS RIA’s that cover a broader geography with more diverse emissions sources and the application of a more diverse set of controls. 2. We assume that health impact functions based on national studies are representative of the experience in California. EPA has considered the cohort studies conducted in California specifically in addition to the national risk coefficients we use as our core estimates. Although we have not calculated the benefits results using these cohort studies, we provided the risk coefficients from these Ca lifornia cohorts to show how much the monetized benefits could have changed if we used these cohort studies. Most of the California cohort studies report central effect estimates similar to the (nation

- wide) all

- cause mortality risk estimate we applied fro m Krewski et al. (2009) and Lepeule et al. (2012) albeit with wider confidence intervals. Three cohort studies conducted in California indicate statistically significant higher risks than the risk estimates we applied from Lepeule et al. (2012), and four s tudies showed insignificant results. 3. We assume that the health impact function for fine particles is log

- linear without a threshold in this analysis. Thus, the estimates include health benefits from reducing fine particles in areas with varied concentrations of PM 2.5 , including both areas that do not meet the fine particle standard and those areas that are in attainment, down to the lowest modeled concentrations. 3. We assume that there is a “ cessation ” lag between the change in PM exposures and the total realization of changes in mortality effects. Specifically, we assume that

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- 24 some of the incidences of premature mortality related to PM 2.5 exposures occur in a distributed fashion over the 20 years following exposure based on the advice of the SA B

- HES (U.S. EPA

- SAB, 2004c), which affects the valuation of mortality benefits at different discount rates. 4
. To characterize the uncertainty in the relationship between PM 2.5 and premature mortality (which account for over 98 % of total monetized benefits in this analysis ), we include a set of twelve estimates based on results of the expert elicitation study in addition to our core estimates. Even these multiple characterizations omit the uncertainty in air quality estimates, baseline incidence rates, popu lations exposed and transferability of the effect estimate to diverse locations. As a result, the reported confidence intervals and range of estimates give an incomplete picture about the overall uncertainty in the PM 2.5 estimates. This information should be interpreted within the context of the larger uncertainty surrounding the entire analysis. As previously described, we strive to monetize as many of the benefits anticipated from the revised and alternative standards as possible given data and resource l imitations , but the monetized benefits estimated in this RIA inevitably only reflect a portion of the benefits. Specifically, only certain benefits attributable to the health impacts associated with exposure to ambient fine particles have been monetized in this analysis. Data and m ethodological limitations prevented the EPA from quantifying or monetizing the benefits from several important he alth benefit categories from emission reduction strategies to reach the revised annual standard in this RIA , including potential co - benefits from reducing ozone exposure , NO 2 exposure, SO 2 exposure, and methylmercury exposure (see section 5.6.5 for more in formation)

. If we could fully monetize all of the benefit categories, the total monetized benefits would exceed the costs by an even greater margin than we currently estimate

. To more fully address all these uncertainties including those we cannot quantify , we apply a four

- tiered approach using the WHO uncertainty framework (WHO, 2008) , which provides a means for systematically linking the characterization of uncertainty to the sophistication of the underlying risk assessment . The EPA has applied similar approaches in analyses (U.S. EPA, 2010b, 2011a). Using this framework, we summarize the key uncertainties in the health benefits analysis, including our assessment of the direction of potential bias, magnitude of impact on the monetize d benefits, degree of confidence in our analytical approach, and our ability to assess the source of uncertainty. More information on this approach and the uncertainty characterization are available in Appendix 5 B
.

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- 25 5.6 Benefits Analysis Data Inputs In Figure 5

- 2, we summarized the key data inputs to the health impact and economic valuation estimate. Below we summarize the data sources for each of these inputs, including demographic projections, incidence and prevalence rates, effect coefficients, and economic valuation. We indicate where we have updated key data inputs since the benefits analysis conducted for the MATS RIA (U.S. EPA, 2011d ) and the proposal RIA (U.S. EPA, 2012 a )

. 5.6.1 Demographic D ata Quantified and monetized human health impacts depend on the demog raphic characteristics of the population, including age, location, and income. We use population projections based on economic forecasting models developed by Woods and P oole, Inc

. (Woods and Poole, 2012 ). The Woods and Poole (WP) database contains county

- level projections of population by age, sex, and race out to 2040, relativ e to a baseline using the 2010 C ensus data; the proposal RIA incorporated WP projections relative to a baseline using 2000 C ensus da ta. An analysis exploring the sensitivity of population and health impact estimates to this update can be found in Appendix 5 .A
. Projections in each county are determined simultaneously with every other county in the United States to take into account patt erns of economic growth and migration. The sum of growth in county

- level populations is constrained to equal a previously determined national population growth, based on Bureau of Census estimates (Hollman et al., 2000). According to WP, linking county

- lev el growth projections together and constraining to a national

- level total growth avoids potential errors introduced by forecasting each county independently. County projections are developed in a four

- stage process:

 First, national

- level variables such as income, employment, and populations are forecasted.

 Second, employment projections are made for 17 9 economic areas defined by the Bureau of Economic Analysis (U.S. BEA, 2004 ) , using an “ export
- base ” approach, which relies on linking industrial

- sector produ ction of non

- locally consumed production items, such as outputs from mining, agriculture, and manufacturing with the national economy. The export

- based approach requires estimation of demand equations or calculation of historical growth rates for output an d employment by sector.

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- 26  Third, population is projected for each economic area based on net migration rates derived from employment opportunities and following a cohort

- component method based on fertility and mortality in each area.

 Fourth, employment and p opulation projections are repeated for counties, using the economic region totals as bounds. The age, sex, and race distributions for each region or county are determined by aging the population by single year of age by sex and race for each year through 2 0 4 0 based on historical rates of mortality, fertility, and migration. 5.6.2 Baseline Incidence and Prevalence Estimates Epidemiological studies of the association between pollution levels and adverse health effects generally provide a direct estimate of the relationship of air quality changes to the relative risk of a health effect, rather than estimating the absolute numbe r of avoided cases. For example, a typical result might be that a 10 μg/m 3 decrease in daily PM 2.5 levels might be associated with a decrease in hospital admissions of 3 % . The baseline incidence of the health effect is necessary to convert this relative ch ange into a number of cases. A baseline incidence rate is the estimate of the number of cases of the health effect per year in the assessment location, as it corresponds to baseline pollutant levels in that location. To derive the total baseline incidence per year, this rate must be multiplied by the corresponding population number. For example, if the baseline incidence rate is the number of cases per year per million people, that number must be multiplied by the millions of people in the total population. Table 5

- 3 summarizes the sources of baseline incidence rates and provides average incidence rates for the endpoints included in the analysis. For both baseline incidence and prevalence data, we used age

- specific rates where available. We applied concentra tion

response functions to individual age groups and then summed over the relevant age range to provide an estimate of total population benefits. In most cases, we used a single national incidence rate, due to a lack of more spatially disaggregated data. W henever possible, the national rates used are national averages, because these data are most applicable to a national assessment of benefits. For some studies, however, the only available incidence information comes from the studies themselves; in these ca ses, incidence in the study population is assumed to represent typical incidence at the national level. County, state and regional incidence rates are available for hospital admissions, and county

- level data are available for premature mortality.

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- 27 We proje cted mortality rates such that future mortality rates are consistent with our projections of population growth (Abt Associates, 2012 ). To perform this calculation, we began first with an average of 2004

– 2006 cause - specific mortality rates. Using Census Bureau projected national

- level annual mortality rates stratified by age range, we projected these mortality rates to 2050 in 5

- year increments (Abt Associates, 2012; U.S. Bureau of the Census 2002). The baseline incidence rates for hospital admissions and emergency department visits reflect the revised rates first applied in the CSAPR RIA (U.S. EPA, 2011c). In addition, we have revised the baseline incidence rates for acute myocardial infarction. These revised rates are more recent (AHRQ, 2007), which prov ides a better representation of the rates at which populations of different ages, and in different locations, visit the hospital and emergency department for air pollution

- related illnesses. Also, the new baseline incidence rates are more spatially refined . For many locations within the U.S., these data are resolved at the county

- or state
- level, providing a better characterization of the geographic distribution of hospital and emergency department visits than the previous national rates. Lastly, these rate s reflect unscheduled hospital admissions only, which represents a conservative assumption that most air pollution

- related visits are likely to be unscheduled. If air pollution

- related hospital admissions are scheduled, this assumption would underestimate these benefits. For the set of endpoints affecting the asthmatic population, in addition to baseline incidence rates, prevalence rates of asthma in the population are needed to define the applicable population. Table 5

- 4 lists the prevalence rates used to determine the applicable population for asthma symptoms. Note that these reflect current asthma prevalence and assume no change in prevalence rates in future years. We updated these rates in the CSAPR RIA (U.S. EPA, 2011c).

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- 28 Table 5
- 3 . Baseline Incidence Rates and Population Prevalence Rates for Use in Impact

Functions, General Population

Endpoint Parameter Rates Value Source Mortality Daily or annual mortality rate

projected to 202 0 a Age

- , cause - , and county

specific rate CDC WONDER (2004

– 2006) U.S. Census bureau, 2000 Hospitalizations Daily hospitalization rate Age

- , region

- , state
- , county
- and cause

- specific rate 2007 HCUP data files b

ER Visits Daily ER visit rate for asthma and

cardiovascular events Age

- , region

- , state
- , county
- and cause - specific rate 2007 HCUP data files b

Cerebrovascular events Incidence of new cerebrovascular

events among populations 50

– 79 0.001575I Table 3 of Miller et al. (2007) Chronic Bronchitis c Annual prevalence rate per

person Aged 18

– 44 Aged 45

– 64 Aged 65 and older 0.0315 0.0549 0.0563 American Lung Association

(2010a, Table 4).

Annual incidence rate per person 0.00378 Abbey et al. (1993, Table 3) Nonfatal Myocardial Infarction (heart attacks) Daily nonfatal myocardial

infarction incidence rate per person, 18+ Age

- , region

- , state
- , and county
- specific rate 2007 HCUP data files ; b adjusted by 0.93 for probability of surviving after 28 days (Rosamond et al., 1999) Asthma Exacerbations Incidence among asthmatic

African

- American children daily wheeze daily cough daily shortness of breath 0.173 0.145 0.074 Ostro et al. (2001)

Acute Bronchitis Annual bronchitis incidence rate,

children 0.043 American Lung Association (2002c, Table 11) Lower Respiratory Symptoms Daily lower respiratory symptom

incidence among children d 0.0012 Schwartz et al. (1994, Table 2) Upper Respiratory Symptoms Daily upper respiratory symptom

incidence among asthmatic 0.3419 Pope et al. (1991, Table 2)

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- 29 children (continued)

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- 30 Table 5
- 3. Baseline Incidence Rates and Population Prevalence Rates for Use in Impact

Functions, General Population (continued)

Endpoint Parameter Rates Value Source Work Loss Days Daily WLD incidence rate per

person (18

– 65) Aged 18

– 24 Aged 25

– 44 Aged 45

– 64 0.00540 0.00678 0.00492 1996 HIS (Adams,

Hendershot, and Marano, 1999, Table 41); U.S. Census Bureau (2000)

School Loss Days Rate per person per year,

assuming 180 school days per year 9.9 National Center for Education Statistics (1996) and 1996 HIS (Adams et al., 1999, Table 47); Minor Restricted

Activity Days Daily MRAD incidence rate per

person 0.02137 Ostro and Rothschild (1989, p. 243)

a Mortality rates are only available at 5

- year increments. b Healthcare Cost and Utilization Program (HCUP) database contains individual level, state and regional

- level hospital and emergency department discharges for a variety of ICD codes (AHRQ, 2007).
c Assessed in sensitivity analysis only. The rate numbers may be slightly different from those in Table 4 because we received more current estim ates from ALA. d Lower respiratory symptoms are defined as two or more of the following: cough, chest pain, phlegm, and wheeze. Table 5
- 4 . Asthma Prevalence Rates

Population Group Asthma Prevalence Rates Value Source All Ages 0.0780 American Lung Association (2010b, Table 7) < 18 0.0941 5
– 17 0.1070 18
– 44 0.0719 45
– 64 0.0745 65+ 0.0716 African American, 5

– 17 0.1776 American Lung Association (2010b, Table 9) African American, <18 0.1553 American Lung Association a

a Calculated by ALA for U.S. EPA, based on NHIS data (CDC, 2008).

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- 31 5.6.3 Effect Coefficients The first step in selecting effect coefficients is to identify the health endpoints to be quantified. We base our selection of health endpoints on consistency with the EPA ’ s Integrated Science A ssessments (which replace previous Criteria Documents), with input and advice from the SAB

- HES, a scientific review panel specifically established to provide advice on the use of the scientific literature in developing benefits analyses for the EPA’s Repor t to Congress on The Benefits and Costs of the Clean Air Act 1990 to 2020 (U.S. EPA, 2011a)

. In addition , we have included more recent epidemiology studies from the PM ISA (U.S. EPA, 2009 b ) and the Provisional Assessment (U.S. EPA, 2012 b )

. 7 I n general, we follow a weight of evidence approach, based on the biological plausibility of effects, availability of concentration

- response functions from well conducted peer

- reviewed epidemiological studies, cohesiveness of results across studies, and a f ocus on endpoints reflecting public health impacts (like hospital admissions) rather than physiological responses (such as changes in clinical measures like Forced Expiratory Volume [ FEV1 ] ). There are several types of data that can support the determinatio n of types and magnitude of health effects associated with air pollution exposures. These sources of data include toxicological studies (including animal and cellular studies), human clinical trials, and observational epidemiology studies. All of these dat a sources provide important contributions to the weight of evidence surrounding a particular health impact. However, only epidemiology studies provide direct concentration

- response relationships that can be used to evaluate population

- level impacts of redu ctions in ambient pollution levels in a health impact assessment. For the data

- derived estimates, we relied on the published scientific literature to ascertain the relationship between PM 2.5 and adverse human health effects. We evaluated epidemiological st udies using the selection criteria summarized in Table 5

- 5 . These criteria include consideration of whether the study was peer

- reviewed, the match between the pollutant studied and the pollutant of interest, the study design and location, and characteristi cs of the study population, among other considerations. In general, the use of concentration

- response functions from more than a single study can provide a more

7 T he peer

- reviewed studies in the Provisional Assessm ent have not yet undergone external review by the SAB . The new studies from the PM ISA and Provisional Assessment for health endpoints not previously quantified in EPA’s RIAs are presented in a sensitivity analysis in Appendix 5B, but these new endpoints h ave not been incorporated into the core benefits analysis.

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- 32 representative distribution of the effect estimate . However, there are often differences between studies examining the same endpoint, making it difficult to pool the results in a consistent manner. For example, studies may examine different pollutants or different age Table 5
- 5 . Criteria Used When Select ing C - R Functions Consideration Comments Peer

- Reviewed Research Peer

- reviewed research is preferred to research that has not undergone the peer

- review process. Study Type Among studies that consider chronic exposure (e.g., over a year or longer), prospective cohort studies are preferred over ecological studies because they control for important individual

- level confounding variables that cannot be controlled for in ecologic al studies. Study Period Studies examining a relatively longer period of time (and therefore having more data) are preferred, because they have greater statistical power to detect effects. Studies that are more recent are also preferred because of possib le changes in pollution mixes, medical care, and lifestyle over time. However, when there are only a few studies available, studies from all years will be included. Population Attributes The most technically appropriate measures of benefits would be based on impact functions that cover the entire sensitive population but allow for heterogeneity across age or other relevant demographic factors. In the absence of effect estimates specific to age, sex, preexisting condition status, or other relevant factors, it may be appropriate to select effect estimates that cover the broadest population to match with the desired outcome of the analysis, which is total national

- level health impacts. When available, multi

- city studies are preferred to single city studies bec ause they provide a more generalizable representation of the concentration

- response function. Study Size Studies examining a relatively large sample are preferred because they generally have more power to detect small magnitude effects. A large sample can be obtained in several ways, including through a large population or through repeated observations on a smaller population (e.g., through a symptom diary recorded for a panel of asthmatic children). Study Location U.S. studies are more desirable than non - U.S. studies because of potential differences in pollution characteristics, exposure patterns, medical care system, population behavior, and lifestyle. National estimates are most appropriate when benefits are nationally distributed; the impact of reg ional differences may be important when benefits only accrue to a single area. Pollutants Included in Model When modeling the effects of ozone and PM (or other pollutant combinations) jointly, it is important to use properly specified impact functions tha t include both pollutants. Using single

- pollutant models in cases where both pollutants are expected to affect a health outcome can lead to double

- counting when pollutants are correlated. Measure of PM For this analysis, impact functions based on PM 2.5 are preferred to PM 10 because of the focus on reducing emissions of PM 2.5 precursors, and because air quality modeling was conducted for this size fraction of PM. Where PM 2.5 functions are not available, PM 10 functions are used as surrogates, recognizing that there will be potential downward (upward) biases if the fine fraction of PM 10 is more (less) toxic than the coarse fraction.

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- 33 Economically Valuable Health Effects Some health effects, such as forced expiratory volume and other technical measurements of lung function, are difficult to value in monetary terms. These health effects are not quantified in this analysis. Non

- overlapping Endpoints Although the benefits associated with each individual health endpoint may be analyzed separately, care must be exercised in selecting health endpoints to include in the overall benefits analysis because of the possibility of double

- counting of benefits. groups. For this reason, we consider very carefully the set of studies available examining each endpoint and select a consistent subset that provides a good balance of population coverage and match with the pollutant of interest. In many cases, either because of a lack of multiple studies, consistency problems, or clear superiority in the quality or comprehensive ness of one study over others, a single published study is selected as the basis of the effect estimate. When several effect estimates for a pollutant and a given health endpoint have been selected, they are quantitatively combined or pooled to derive a m ore robust estimate of the relationship. The BenMAP Manual Technical Appendices provides details of the procedures used to combine multiple impact functions ( Abt Associates, 2012 ). In general, we used fixed or random effects models to pool estimates from d ifferent single city studies of the same endpoint. Fixed effects pooling simply weights each study’s estimate by the inverse variance, giving more weight to studies with greater statistical power (lower variance). Random effects pooling accounts for both w ithin

- study variance and between

- study variability, due, for example, to differences in population susceptibility. We used the fixed effects model as our null hypothesis and then determined whether the data suggest that we should reject this null hypothesi s, in which case we would use the random effects model. 8 Pooled impact functions are used to estimate hospital admissions and asthma exacerbations. When combining evidence across multi

- city studies (e.g., cardiovascular hospital admission studies), we use equal weights pooling. The effect estimates drawn from each multi

- city study are themselves pooled across a large number of urban areas. For this reason, we elected to give each study an equal weight rather than weighting by the inverse of the variance re ported in each study. For more details on methods used to pool incidence estimates, see the BenMAP Manual Appendices ( Abt Associates, 2012 ).

8 EPA recently changed the algorithm BenMAP uses to calculate study variance, which is used in the pooling process. Prior versions of the model calculated population variance, while the version use d here calculated sample variance. This change did not affect the selection of random or fixed effects for the pooled incidence estimates between the proposal and final RIA.

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- 34 Effect estimates selected for a given health endpoint were applied consistently across all locations nationwide. Th is applies to both impact functions defined by a single effect estimate and those defined by a pooling of multiple effect estimates. Although the effect estimate may, in fact, vary from one location to another (e.g., because of differences in population su sceptibilities or differences in the composition of PM), location

- specific effect estimates are generally not available. The specific studies from which effect estimates for the core analysis are drawn are included in Table 5

- 6. We highlight in blue those studies that have been added since the benefits analysis conducted for the MATS RIA (U.S. EPA, 2011d), and we highlight those studies in red that have been added since the proposal RIA (U.S. EPA, 2012a). In all cases where effect estimates are drawn direct ly from epidemiological studies, standard errors are used as a partial representation of the uncertainty in the size of the effect estimate. Table 5

- 7 summarizes those health endpoints and studies we have included as in sensitivity analyses. Table 5
- 6 . Health Endpoints and Epidemiological Studies Used to Quantify Health Impacts

in the Core Analysis a

Endpoint Study Study Population Risk Estimate (95 th Percentile Confidence Interval) a Premature Mortality Premature mortality

— cohort study, all

- cause Krewski et al. (2009) >29 years >24 years RR = 1.06 (1.04

– 1.06) per

10 μg/m 3 Lepeule et al. (2012) RR = 1. 14 (1.07

– 1. 22 ) per 10 μg/m 3 Premature mortality, total exposures PM 2.5 Expert Elicitation (Roman et al.,

2008) >24 years Varies by expert
Premature mortality

— all

- cause Woodruff et al. (1997) Infant (<1 year) OR = 1.04 (1.02

– 1.07) per 10 μg/m 3 Chronic Illness Nonfatal heart attacks Peters et al. (2001) Adults (>18 years) OR = 1.62 (1.13

– 2.34) per

20 μg/m 3 Pooled estimate: Pope et al. (2006) β = 0.00481 (0.00199) Sullivan et al. (2005) β = 0.00198 (0.00224) Nonfatal heart attacks (cont’d) Zanobetti et al. (2009) β = 0.00225 (0.000591) Zanobetti and Schwartz (2006) β = 0.0053 (0.00221) Hospital Admissions Respiratory Zanobetti et al. (2009)

— ICD 460

- 519 (All respiratory) >64 years β=0.00207 (0.00446) Kloog et al. (2012)

— ICD 460

- 519 (All Respiratory β=0.0007 (0.000961) Moolgavkar (2000)

— ICD 490
– 496 18
– 64 years 1.02 (1.01

– 1.03) per Formatted: Spanish (International Sort)

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- 35 (Chronic lung disease) 36 μg/m 3 Babin et al. (2007)

— ICD 493 (asthma) <19 β=0.002 (0.004337) Sheppard (2003)

— ICD 493 (asthma) < 18 RR = 1.04 (1.01

– 1.06) per 11.8 μg/m 3 (continued)

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- 36 Table 5
- 6. Health Endpoints and Epidemiological Studies Used to Quantify Health Impacts

in the Core Analysis a (continued)

Endpoint Study Study Population Risk Estimate

(95th Percentile Confidence Interval) a Cardiovascular Pooled estimate:

Zanobetti et al. (2009)

— ICD 390

- 459 (all cardiovascular) >64 years β=0.00189 (0.000283) Peng et al. (2009)

— ICD 426

- 427; 428; 430

- 438; 410

- 414; 429; 440

- 449 (Cardio

- , cerebro

- and peripheral vascular disease) β=0.00068 (0.000214) Peng et al. (2008)

— ICD 426

- 427; 428; 430

- 438; 410

- 414; 429; 440

- 449 (Cardio

- , cerebro

- and peripheral vascular disease) β=0.00071 (0.00013) Bell et al. (2008)

— ICD 426

- 427; 428; 430

- 438; 410

- 414; 429; 440

- 449 (Cardio

- , cerebro

- and peripheral vascular disease) β=0.0008 (0.000107) Moolgavkar (2000)

— ICD 390
– 429 (all cardiovascular) 20
– 64 years RR=1.04 (t statistic: 4.1) per 10 μg/m 3 Asthma

- related ER visits Pooled estimate:

Mar et al. (2010) All ages RR = 1.04 (1.01

– 1.07) per 7 μg/m 3 Slaughter et al. (2005) RR = 1.03 (0.98

– 1.09) per 10 μg/m 3 Glad et al. (2012) β=0.00392 (0.002843) Other Health Endpoints Acute bronchitis Dockery et al. (1996) 8
– 12 years OR = 1.50 (0.91

– 2.47) per 14.9 μg/m 3 Asthma exacerbations Pooled estimate: Ostro et al. (2001) (cough, wheeze and shortness of breath) b 6
– 18 years b OR = 1.03 (0.98

– 1.07) OR = 1.06 (1.01

– 1.11) OR = 1.08 (1.00

– 1.17) per 30 μg/m 3 Mar et al. (2004) (cough, shortness of breath) RR = 1.21 (1

– 1.47) per RR = 1.13 (0.86

– 1.48) per 10 μg/m 3 Work loss days Ostro (1987) 18
– 65 years β=0.0046 (0.00036) Acute respiratory symptoms Ostro and Rothschild (1989) (Minor restricted

activity days) 18
– 65 years β=0.00220 (0.000658) Upper respiratory symptoms Pope et al. (1991) Asthmatics, 9

– 11 years 1.003 (1

– 1.006) per

10 μg/m 3 Lower respiratory symptoms Schwartz and Neas (2000) 7
– 14 years OR = 1.11 (1.58

– 1.58) per 15 μg/m 3

a Studies highlighted in blue represent updates incorporated since the RIA for MATS (U.S. EPA, 2011d). Studies highlighted in red represent update s incorporated since the proposal RIA (U.S. EPA, 2012a). Formatted: Spanish (International Sort)

Formatted: Spanish (International Sort)

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- 37 b The original study populations were 8 to 13 for the O stro et al. (2001) study and 7 to 12 for the Mar et al. (2004) study. Based on advice from the SAB

- HES, we extended the applied population to 6

- 18, reflecting the common biological basis for the effect in children in the broader age group. See: U.S. EPA

- SA B (2004) and NRC (2002).

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- 38 Table 5
- 7 . Health Endpoints and Epidemiological Studies Used to Quantify Health Impacts

in the Sensitivity Analysis a Endpoint Study Study Population Chronic Illness Chronic bronchitis Abbey et al. (1995) >26 years Stroke Miller et al. (2007) 50
– 79 years Hospital Admissions Cardiovascular ED Visits Metzger et al. (2004) 0
– 99 Tolbert et al. (2007) 0
– 99 Mathes et al. (2011) 40
– 99

a Studies highlighted in blue represent updates incorporated since the RIA for MATS (U.S. EPA, 2011d). Studies highlighted in red represent updated incorporated since the proposal RIA (U.S. EPA, 2012a). 5.6.3.1 PM 2.5 Premature Mortality Effect Coefficients Core Mortality Effect Coefficients for Adults . A substantial body of published scientific lite rature documents the association between elevated PM 2.5 concentrations and increased premature mortality (U.S. EPA, 2009b). This body of literature reflects thousands of epidemiology, toxicology, and clinical studies. The PM ISA completed as part of the th is review of the PM standards, which was twice reviewed by the SAB

- CASAC (U.S. EPA

- SAB, 2009b, 2009c), concluded that there is a causal relationship between mortality and both long

- term and short

- term exposure to PM 2.5 based on the entire body of scientifi c evidence (U.S. EPA, 2009b). The size of the mortality effect estimates from epidemiological studies, the serious nature of the effect itself, and the high monetary value ascribed to prolonging life make mortality risk reduction the most significant healt h endpoint quantified in this analysis. Researchers have found statistically significant associations between PM 2.5 and premature mortality using different types of study designs. Time

- series methods have been used to relate short

- term (often day

- to
- day) changes in PM 2.5 concentrations and changes in daily mortality rates up to several days after a period of elevated PM 2.5 concentrations. Cohort methods have been used to examine the potential relationship between community

- level PM 2.5 exposures over multiple years (i.e., long

- term exposures) and community

- level annual mortality rates that have been adjusted for individual level risk factors. When choosing between using short

- term studies or cohort studies for estimating mortality benefi ts, cohort analyses are thought to capture more of the public health impact of exposure to air pollution over time because they account for the effects of long

- term exposures as well as some fraction of short

-

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- 39 term exposures (Kunzli et al., 2001; NRC, 2002) . The NRC stated that “ it is essential to use the cohort studies in benefits analysis to capture all important effects from air pollution exposure ” (NRC, 2002, p. 108). The NRC further notes that “ the overall effect estimates may be a combination of effect s from long

- term exposure plus some fraction from short

- term exposure. The amount of overlap is unknown ” (NRC, 2002, p. 108

- 9). To avoid double counting, we focus on applying the risk coefficients from the long

- term cohort studies in estimating the mortali ty impacts of reductions in PM 2.5 . Over the last two decades, several studies using “ prospective cohort ” designs have been published that are consistent with the earlier body of literature. Two prospective cohort studies, often referred to as the Harvard “ Six Cities Study ” (Dockery et al., 1993; Laden et al., 2006; Lepeule et al., 2012) and the “ American Cancer Society ” or “ ACS study ” (Pope et al., 1995; Pope et al., 2002; Pope et al., 2004; Krewski et al., 2009), provide the most extensive analyses of ambi ent PM 2.5 concentrations and mortality. These studies have found consistent relationships between fine particle indicators and premature mortality across multiple locations in the United States. The credibility of these two studies is further enhanced by t he fact that the initial published studies (Pope et al., 1995; Dockery et al., 1993) were subject to extensive reexamination and reanalysis by an independent team of scientific experts commissioned by the Health Effect Institute (HEI) and by a Special Pane l of the HEI Health Review Committee (Krewski et al., 2000). Publication of studies confirming and extending the findings of the 1993 Six Cities Study and the 1995 ACS study using more recent air quality and a longer follow

- up period for the ACS cohort pro vides additional validation of the findings of these original studies (Pope et al., 2002, 2004; Laden et al., 2006; Krewski et al., 2009; Lepeule et al., 2012). The SAB

HES also supported using these two cohorts for analyses of the benef its of PM reduction s, and concluded, “ the selection of these cohort studies as the underlying basis for PM mortality benefit estimates to be a good choice. These are widely cited, well studied and extensively reviewed data sets ” (U.S. EPA

- SAB, 2010a). As both the ACS and Six Cities studies have inherent strengths and weaknesses, we present benefits estimates using relative risk estimates from the most recent extended reanalysis of these cohorts (Krewski et al., 2009; Lepeule et al., 2012). Presenting results using both ACS an d Six Cities is consistent with other recent RIAs (e.g., U.S. EPA, 2006a, 2010c, 2011c, 2011d). The PM ISA concludes that the ACS and Six Cities cohorts provide the strongest evidence of the association between long

- term PM 2.5 exposure and premature mortal ity with support from a number of additional cohort studies (described below).

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- 40 The extended analyses of the ACS cohort data (Krewski et al., 2009) provides additional refinements to the analysis of PM

- related mortality by (a) extending the follow

- up period by 2 years to the year 2000, for a total of 18 years; (b) incorporating almost double the number of urban areas (c) addressing confounding by spatial autocorrelation by incorporating ecological, or community

- level, co

- variates; (d) performing an extensive spatial analysis using land use regression modeling in two large urban areas. These enhancements make this analysis well

suited for the assessment of mortality risk from long

- term PM 2.5 exposures for the EPA ’s benefits analyses. In 2009, the SAB

- HES agai n reviewed the choice of mortality risk coefficients for benefits analysis, concluding that “ [t]he Krewski et al. (2009) findings, while informative, have not yet undergone the same degree of peer review as have the aforementioned studies. Thus, the SAB

HES recommends that EPA not use the Krewski et al. (2009) findings for generating the Primary Estimate ” (U.S. EPA

- SAB, 2010a). Since this time, the Krewski et al. (2009) has undergone additional peer review, which we believe strengthens the support for inc luding this study in this RIA. For example, the PM ISA (U.S. EPA, 2009b) included this study among the key mortality studies. In addition, the risk assessment supporting the PM NAAQS (U.S. EPA, 2010b) utilized risk coefficients drawn from the Krewski et al . (2009) study, the most recent reanalysis of the ACS cohort data. The risk assessment cited a number of advantages that informed the selection of the Krewski et al. (2009) study as the source of the core effect estimates, including the extended period of observation, the rigorous examination of model forms and effect estimates, the coverage for ecological variables, and the large dataset with over 1.2 million individuals and 156 MSAs (U.S. EPA, 2010b). The SAB

- CASAC also provided extensive peer review of t he risk assessment and supported the use of effect estimates from this study (U.S. EPA

- SAB, 2009a, 2010b, c). Consistent with the Quantitative Health Risk Assessment for Particulate Matter (U.S. EPA, 2010b) which was reviewed by the SAB

- CASAC (U.S. EPA

- SA B, 2009), we use the all

- cause mortality risk estimate based on the random

- effects Cox proportional hazard model that incorporates 44 individual and 7 ecological covariates (RR=1.06, 95% confidence intervals 1.04

– 1.08 per 10μg/m 3 increase in PM 2.5 ). The re lative risk estimate (1.06 per 10μg/m 3 increase in PM 2.5 ) is identical to the risk estimate drawn from the earlier Pope et al. (2002) study, though the confidence interval around the Krewski et al. (2009) risk estimate is tighter.

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- 41 In the most recent Six Ci ties study, which was published after the last SAB

- HES review, Lepeule et al. (2012) evaluated the sensitivity of previous Six Cities results to model specifications, lower exposures, and averaging time using eleven additional years of cohort follow

- up tha t incorporated recent lower exposures. The authors found significant associations between PM 2.5 exposure and increased risk of all

- cause, cardiovascular and lung cancer mortality. The authors also concluded that the concentration

- response relationship was linear down to PM 2.5 concentrations of 8 μg/m 3 , and that mortality rate ratios for PM 2.5 fluctuated over time, but without clear trends, despite a substantial drop in the sulfate fraction. We use the all

- cause mortality risk estimate based on a Cox proportional hazard model that incorporates 3 individual covariates. (RR=1.14, 95% confidence intervals 1.07

– 1.22 per 10 μg/m 3 increase in PM 2.5 ). The relative risk estimate is slightly smaller th an the risk estimate drawn from Laden et al

. (2006), with relatively smaller confidence intervals. Implicit in the calculation of PM 2.5 - related premature mortality impacts are several key assumptions, which are described in further detail later in this cha pter. First, we assume that there is a “ cessation ” lag in time between the reduction in PM exposure and the full reduction in mortality risk that affects the timing (and thus discounted monetary valuation) of the resulting premature deaths (see section 5.6 .6.1). Second, following conclusions of the PM ISA, we assume that all fine particles are equally potent in causing premature mortality (see section 5.7.2). Third, following conclusions of the PM ISA, we assume that the health impact function for fine part icles is linear within the range of ambient concentrations affected by these standards (see section 5.7.4). Alternate Mortality Effect Coefficients for Adults. In addition to the ACS and Six Cities cohorts, several recent cohort studies conducted in North America provide evidence for the relationship between long

- term exposure to PM 2.5 and the risk of premature death. Many of these additional cohort studies are described in the PM ISA (U.S. EPA, 2009) and the Provisional Assessment (U.S. EPA, 2012 b ) (and th us not summarized here). 9 , 10 Table 5

- 8 provides the effect

9 It is important to note that the newer studies in the Provisional Assessment are published in peer

- reviewed journals and meet our study selection criteria, but they have not been assessed in the context of an Integrated Science Assessment nor gone through review by the SAB. In addition, only the ACS and H6C cohort studies have bee n recommended by the SAB as appropriate for benefits analysis of national rulemakings. 10 In this chapter, we only describe multi

- state cohort studies. There are additional cohort studies that we have not included in this list, including cohort studies that focus on single cities (e.g., Gan et al., 2012) and cohort studies focusing on methods development. In Appendix 5A, we provide additional information regarding cohort studies in California, which is the only state for which we identified single state coho rts.

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- 42 estimates from each of these cohort studies for all

- cause, cardiovascular, cardiopulmonary, and ischemic heart disease (IHD) mortality as well as the lowest measured air quality level (LML) and mean concentration in the study. We also draw upon the results of the 2006 expert elicitation sponsored by the EPA (Roman et al., 2008; IEc, 2006) to demonstrate the sensitivity of the benefits estimates to 12 expert
- defined concentration

- response functions. The PM 2.5 expert elicitation and the derivation of effect estimates from the expert elicitation results are described in detail in the 2006 PM 2.5 NAAQS RIA (U.S. EPA, 2006a), the elicitation summary report (IEc, 2006) and Roman et al. (2008), and so we sum marize here the key attributes of this study relative to the interpretation of the estimates of PM

- related mortality reported here. We describe also how the epidemiological literature has evolved since the expert elicitation was conducted in 2005 and 2006. Table 5
- 8. Summary of Effect estimates from Associated With Change in Long
- Term

Exposure to PM 2.5 in Recent Cohort Studies in North America

Study Cohort (age) LML (μg/m 3 ) Mean

(μg/m 3 ) Hazard Ratios per 10 μg/m 3 Change in PM 2.5 (95 th percentile confidence intervals) All Causes Cardiovascular Cardiopulmonary IHD Pope et al. (2002) ACS

(age >30) 7.5 18.2 1.06 (1.02

– 1.11) 1.12

(1.08

– 1.15) 1.09

(1.03

– 1.16) N/A
Laden et al. (2006) Six Cities

(age > 25) 10 16.4 1.16 (1.07

– 1.26) 1.28

(1.13

– 1.44) N/A N/A Lipfert et al. (2006) a Veterans

(age 39

– 63) <14.1 14.3 1.15 (1.05

– 1.25) N/A N/A N/A
Miller et al. (2007) b WHI

(age 50

– 79) 3.4 13.5 N/A 1.76 (1.25

– 2.47) N/A 2.21 (1.17

– 4.16) Eftim et al. (2008) Medicare (age

> 65) 6 13.6 1.21 (1.15

– 1.27) N/A N/A N/A Zeger et al. (2008) c Medicare (age

> 65) <9.8 13.2 1.068 (1.049

– 1.087) N/A N/A N/A
Krewski et al. (2009) d ACS

(age >30) 5.8 14 1.06 (1.04

– 1.08) N/A 1.13 (1.10

– 1.16) 1.24

(1.19

– 1.29) Puett et al. (2009) b NHS

(age 30

– 55) 5.8 13.9 1.26 (1.02

– 1.54) N/A N/A 2.02 (1.07

– 3.78) Crouse et al. (2011) d,e Canadian

census 1.9 8.7 1.06 (1.01

– 1.10) N/A N/A N/A
Puett et al. (2011) f Health

Professionals (age 40

– 75) <14.4 17.8 0.86 (0.70

– 1.00) 1.02

(0.84

– 1.23) N/A N/A Formatted: Spanish (International Sort)

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- 43 Lepeule et al. (2012) d Six Cities

(age > 25) 8 15.9 1.14 (1.07

– 1.22) 1.26

(1.14

– 1.40) N/A N/A

a Low socio

- economic status ( SES ) men only. Used traffic proximity as a surrogate of exposure. b Women only.
c Reflects risks in the Eastern U.S. Risks in the Central U.S. were higher, but the authors found no association in the Western U.S. d Random effects Cox model with individual and ecologic covariates.
e Canadian population. f Men with high socioeconomic status only. The primary goal of the 2006 study was to elicit from a sample of health experts probabilistic distributions describing uncertainty in estimates of the reduction in mortality among the adult U.S. population resulting from reductions in ambient annual average PM 2.5 levels. These distributions were obtained through a form al interview protocol using methods designed to elicit subjective expert judgments. These experts were selected through a peer

nomination process and included experts in epidemiology, toxicology, and medicine. The elicitation interview consisted of a proto col of carefully structured questions, both qualitative and quantitative, about the nature of the PM 2.5 - mortality relationship designed to build twelve individual distributions for the coefficient (or slope) of the C

- R function relating changes in annual a verage PM 2.5 exposures to annual, adult all

- cause mortality. The elicitation also provided useful information regarding uncertainty characterization in the PM 2.5 - mortality relationship. Specifically, during their interviews, the experts highlighted several uncertainties inherent within the epidemiology literature, such as causality, concentration thresholds, effect modification, the role of short

- and long

- term exposures, potential confounding, and exposure misclassification. In Appendix 5c, we evaluate eac h of these uncertainties in the context of this health impact assessment. For several of these uncertainties, such as causality, we are able to use the expert

- derived functions to quantify the impacts of applying different assumptions. The elicitation rece ived favorable peer review in 2006 (Mansfield and Patil, 2006). Prior to providing a quantitative estimate of the risk of premature death associated with long

- term PM 2.5 exposure, the experts answered a series of “ conditioning questions. ” One such question asked the experts to identify which epidemiological studies they found most informative. The “ ideal study attributes ” 11 according to the experts included:

11 These criteria are substantively similar to EPA’s study selection criteria identified in Table 5

- 5 of this chapter.

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- 44  Geographic representation of the entire U.S. (e.g., monitoring sites across the country)

 Collection of information on individual risk factors and residential information both at the beginning and throughout the follow

- up period

 Large sample size that is representative of the general U.S. population

 Collection of genetic information from cohort members to identify and assess potential effect modifiers

 Monitoring of individual exposures (e.g., with a personal monitor)

 Collection of data on levels of several co

- pollutants (not only those that are monitored for compliance purposes

 Accurate characterization of outcome (i.e., cause of death)

 Follow

- up for a long period of time, up to a lifetime

 Prospective study design Although no single epidemiological study completely satisfies each of these criteria, the experts determined that the ACS and Six Cities cohort s tudies best satisfy a majority of these ideal attributes. To varying degrees the studies examining these two cohorts: are geographically representative; have collected information on individual risk factors; include a large sample size; have collected data on co - pollutants in the case of the ACS study; have accurately characterized the health outcome; include a long (and growing) follow

- up period; and, are prospective in nature. The experts also noted a series of limitations in these two cohort studies. In the case of the Six Cities study (Laden et al., 2006), the experts identified the “ small sample size, limited number of cities, and concerns about representativeness of the six cities for the U.S. as a whole ” as weaknesses. When considering the ACS study ( Pope et al., 2002), the experts indicated that the “ method of recruitment for the study, which resulted in a group with higher income, more education, and a greater proportion of whites than is representative of the general U.S. population ” represented a s hortcoming. Several experts also argued that because the ACS study relied upon “ ...whatever monitors were available to the study...a single monitor represent[ed] exposure for an entire metropolitan area...whereas [the Six Cities study] often had exposures assign ed at the county level. ” Despite these limitations, the experts considered the Pope et al. (2002) extended analysis of the ACS cohort and the Laden et al.

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- 45 (2006) extended analysis of the Six Cities cohort to be particularly influential in their opinions (s ee Exhibit 3

- 3 of the elicitation summary report [ IEc, 2006 ] ). Since the completion of the EPA ’ s expert elicitation in 2006, additional epidemiology literature has become available, including 9 new multi

- state cohort studies shown in Table 5

- 8. This newer literature addresses some of the weaknesses identified in the prior literature. For example, in an attempt to improve its characterization of population exposure the most recent extended analysis of the ACS cohort Krewski et al. (2009) incorporates two ca se studies that employ more spatially resolved estimates of population exposure. In light of the availability of this newer literature, we have updated the presentation of results in the RIA. Specifically, we focus the core analysis on results derived fro m the two most recent studies of the ACS and Six Cities cohorts (Krewski et al. , 2009; Lepeule et al. , 2012). Because the other multi

- state cohorts generally have limited geography and age/gender representativeness, these limitations preclude us from using these studies in our core benefits results, and we instead present the risk coefficients from these o ther multi

- state cohorts in Table 5

- 8. In addition, we now present the full distribution s of the expert

- derived results in a probabilistic graphic (rather than cascading the expert

- derived results throughout the results tables as done in prior RIAs). We do not combine the expert results in order to preserve the breadth and diversity of opinion on the expert panel (Roman et. al., 2006). This presentation of the expert

- derived results is generally consistent with SAB advice (U.S. EPA

- SAB, 2008), which recomme nded that the EPA empha si ze that “scientific differences existed only with respect to the magnitude of the effect of PM 2.5 on mortality, not whether such an effect existed ” and that the expert elicitation “supports the conclusion that the benefits of PM 2. 5 control are very likely to be substantial”. Although it is possible that the newer literature could revise the experts’ quantitative responses if elicited again, we believe that these general conclusions are unlikely to change. Mortality Effect Coefficie nts for Infants In addition to the adult mortality studies described above, several studies show an association between PM exposure and premature mortality in children under 5 years of age. 12 The PM ISA states that less evidence is available regarding the p otential impact of PM 2.5

12 For the purposes of this analysis, we only calculate benefits for infants age 0

– 1, not all children under 5 years old.

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- 46 exposure on infant mortality than on adult mortality and the results of studies in several countries include a range of findings with some finding significant associations. Specifically, the PM ISA concluded that evidence exists for a stronger effect at the post

- neonatal period and for respiratory

- related mortality, although this trend is not consistent across all studies. In addition, compared to avoided premature deaths estimated for adult mortality, avoided premature deaths for infants are significantly smaller because the number of infants in the population is much smaller than the number of adults and the epidemiology studies on infant mortality provide smaller risk coefficients associated with exposure to PM 2.5 . In 2004, the SAB

- HES noted the release of the WHO Global Burden of Disease Study focusing on ambient air, which cites several recently published time

- series studies relating daily PM exposure to mortality in children (U.S. EPA

- SAB, 2004a). The SAB

- HES also cites the st udy by Belanger et al. (2003) as corroborating findings linking PM exposure to increased respiratory inflammation and infections in children. A study by Chay and Greenstone (2003) found that reductions in TSP caused by the recession of 1981

– 1982 were stati stically associated with reductions in infant mortality at the county level. With regard to the cohort study conducted by Woodruff et al. (1997), the SAB

- HES notes several strengths of the study, including the use of a larger cohort drawn from a large numb er of metropolitan areas and efforts to control for a variety of individual risk factors in infants (e.g., maternal educational level, maternal ethnicity, parental marital status, and maternal smoking status). Based on these findings, the SAB

- HES recommend ed that the EPA incorporate infant mortality into the primary benefits estimate and that infant mortality be evaluated using an impact function developed from the Woodruff et al. (1997) study (U.S. EPA

- SAB, 2004a). In 2010, the SAB

- HES again noted the incr easing body of literature relating infant mortality and PM exposure and supported the inclusion of infant mortality in the monetized benefits (U.S. EPA

- SAB, 2010a). The SAB

- HES generally supported the approach of estimating infant mortality based on Woodru ff et al. (1997) and noted that a more recent study by Woodruff et al. (2006) continued to find associations between PM 2.5 and infant mortality in California

. The SAB

- HES also noted, “when PM 10 results are scaled to estimate PM 2.5 impacts, the results yield similar risk estimates.” Consistent with the Costs and Benefits of the Clean Air Act (U.S. EPA, 2011a) , we continue to rely on the earlier 1997 study in part due to the national

– scale of the earlier study

.

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- 47 5.6.3.2 Nonfatal Acute Myocardial Infarction s (AMI) (Heart Attacks) Nonfatal heart attacks have been linked with short

- term exposures to PM 2.5 in the United States (Mustafić et al., 2012; Peters et al., 2001; Sullivan et al., 2005; Pope et al., 2006; Zanobetti and Schwartz, 2006; Zanobetti et al., 2 009) and other countries (Poloniecki et al., 1997; Barnett et al., 2006; Peters et al., 2005). In previous health impact assessments, we have relied upon a study by Peters et al. (2001) as the basis for the impact function estimating the relationship betwe en PM 2.5 and nonfatal heart attacks. The Peters et al. (2001) study exhibits a number of strengths. In particular, it includes a robust characterization of populations experiencing acute myocardial infarctions (AMIs). The researchers interviewed patients w ithin 4 days of their AMI events and, for inclusion in the study, patients were required to meet a series of criteria including minimum kinase levels, an identifiable onset of pain or other symptoms and the ability to indicate the time, place and other cha racteristics of their AMI pain in an interview. Since the publication of Peters et al. (2001), a number of other single and multi

- city studies have appeared in the literature. These studies include Sullivan et al. (2005), which considered the risk of PM 2.5 - related hospitalization for AMIs in King County, WA; Pope et al. (2006), based in Wasatch Range, UT; Zanobetti and Schwartz (2006), based in Boston , MA ; and, Zanobetti et al. (2009), a multi

- city study of 26 U.S. communities. Each of these single and mult i

- city studies, with the exception of Pope et al. (2006), measure AMIs using hospital discharge rates. Conversely, the Pope et al. (2006) study is based on a large registry with angiographically characterized patients

— arguably a more precise indicator of A MI. Because the Pope et al. (2006) study reflected both myocardial infarctions and unstable angina, this produces a more comprehensive estimate of acute ischemic heart disease events than the other studies. However, unlike the Peters study (Peters et al., 2006), Pope and colleagues did not measure the time of symptom onset, and PM 2.5 data were not measured on an hourly basis. As a means of recognizing the strengths of the Peters study while also incorporating the newer evidence found in the four single and multi

- city studies, we present a range of AMI estimates. The upper end of the range is calculated using the Peters study while the lower end of the range is the result of an equal

- weights pooling of these four newer studies. It is important to note that when calculating the incidence of nonfatal AMI , the fraction of fatal heart attacks is subtracted to ensure that there is no double

- counting with premature mortality estimates. Specifically, we apply an adjustment factor in the concentration

- response funct ion to reflect the probability of surviving a heart attack. B ased on recent data from the Agency for

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- 48 Healthcare Research and Quality ’ s Healthcare Utilization Project National Inpatient Sample database (AHRQ, 2009), we identified death rates for adults hosp italized with acute myocardial infarction stratified by age (e.g., 1.85 2 % for age s 18
– 44, 2.8 188 % for age s 45
– 64, and 7.43 39 % for age s 65+). These rates show a clear downward trend over time between 1994 and 2009 for the average adult and thus replace the 7% survival rate previously applied across all age groups from Rosamond et al. (1999). 5.6. 3

. 3 Hospital Admissions and Emergency Department Visits Because of the availability of detailed hospital admission and discharge records, there is an extensive body of literature examining the relationship between hospital admissions and air pollution. For this reason , we pool together the incidence estimates using several different studies for many of the hospital admission endpoints. In addition, some studies have examined the relationship between air pollution and emergency department visits. Since most emergency department visits do not result in an admission to the hospital ( i.e., most people going to the emergency department are treated and return home), we trea t hospital admissions and emergency department visits separately, taking account of the fraction of emergency department visits that are admitted to the hospital. Specifically, within the baseline incidence rates, we parse out the scheduled hospital visits from unscheduled ones as well as the hospital visits that originated in the emergency department

. The two main groups of hospital admissions estimated in this analysis are respiratory admissions and cardiovascular admissions. There is not much evidence li nking PM 2.5 with other types of hospital admissions. Both asthma

- and cardiovascular

- related visits have been linked to PM 2.5 in the United States , though as we note below, we are able to assign an economic value to asthma

- related events only. To estimate the effects of PM 2.5 air pollution reductions on asthma

- related ER visits, we use the effect estimate from a study of children 18 and under by Mar et al. (2010) , Slaughter et al. ( 2005 ) , and Glad et al. (2012)

. The first two studies examine d p opulations 0 to 9 9 in Washington State , while Glad et al. examined populations 0

- 99 in Pittsburgh, PA . Mar and colleagues perform their study in Tacoma, while Slaughter and colleagues base their study in Spokane. We apply random/fixed effects pooling to co mbine evidence across these two studies. To estimate avoided incidences of cardiovascular hospital admissions associated with PM 2.5 , we used studies by Moolgavkar (2000), Zanobetti et al. (2009), Peng et al. (2008, 2009) and Bell et al., (2008). Only Moolg avkar (2000) provided a separate effect estimate for adults 20

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- 49 to 64, while the remainder estimate risk among adults over 64. 13 Total cardiovascular hospital admissions are thus the sum of the pooled estimate for adults over 65 and the single study estimate for adults 20 to 64. Cardiovascular hospital admissions include admissions for myocardial infarctions. To avoid double

- counting benefits from reductions in myocardial infarctions when applying the impact function for c ardiovascular hospital admissions, we first adjusted the baseline cardiovascular hospital admissions to remove admissions for myocardial infarctions. We applied equal weights pooling to the multi

- city studies assessing risk among adults over 64 because the se studies already incorporated pooling across the city

- level estimates. One potential limitation of our approach is that while the Zanobetti et al

. (2009) study assesses all cardiovascular risk, Bell et al. (2008) , and Peng et al., (2008, 2009) studies es timate a subset of cardiovascular hospitalizations as well as certain cerebro

- and peripheral

vascular diseases. To address the potential for the pooling of these four studies to produce a biased estimate, we match the pooled risk estimate with a baseline incidence rate that excludes cerebro

- and peripheral

- vascular disease. An alternative approach would be to use the Zanobetti et al. (2009) study alone, though this would prevent us from drawing upon the strengths of the three multi

- city studies.
To estimat e avoided incidences of respiratory hospital admissions associated with PM 2.5 , we used a number of studies examining total respiratory hospital admissions as well as asthma and chronic lung disease. We estimated impacts among three age groups: adults over 65, adults 18 to 6 4 and children 0 to 1 7. For adults over 65, the multi

- city stud ies by Zanobetti et al. (2009) and Kloog et al. (2012) provide effect coefficients for total respiratory hospital admissions (defined as ICD codes 460

– 519). We pool these two studies using equal weights. Moolgavkar et al. ( 2003 ) examines PM 2.5 and chronic lung disease hospital admissions (less asthma) in Los Angeles, CA among adults 18 to 6 4. For children 0 to 18, we pool two studies using random/fixed effects. The first is Babin et al. (2007) which assessed PM 2.5 and asthma hospital admissions in Washington, DC among children 1 to 1 8; we adjusted the age range for this study to apply to children 0 to 1 8. The second is Sheppard et al. (2003) which assessed PM 2.5 and asthma ho spitalizations in Seattle, Washington , among children 0 to 1 8.

13 Note that the Moolgavkar (2000) study has not been updated to reflect the more stringent GAM convergence criteria. However, given that no other estimates are available for this age group, we chose to use the existing study. Given the very small (<5 % ) difference in the effect estimates for people 65 and older with cardiovascular hospital admissions between the original and reanalyzed results, we do not expect this choice to introduce much bias. For a discussion of the GAM convergence criteria, and how it affected the size of effect coefficients reported by time series epidemiological studies using NMMAPS data, see: http://www.healtheffects.org/Pubs/st

timeseries.htm

.

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- 50 5.6

. 3

. 4 Acute Health Events and School/Work Loss Days In addition to mortality, chronic illness, and hospital admissions, a number of acute health effects not requiring hospitalization are asso ciated with exposure to PM 2.5 . The sources for the effect estimates used to quantify these effects are described below. Approximately 4 % of U.S. children between the ages of 5 and 17 experience episodes of acute bronchitis annually ( ALA , 2002). Acute bronchitis is characterized by coughing, chest discomfort, slight fever, and extreme tiredness, lasting for a number of days. According to the MedlinePlus medical encyclopedia, 14 with the exception of cough, most acute bronchitis symptoms abate within 7 to 10 days. Incidence of episodes of acute bronchitis in children between the ages of 5 and 17 were estimated using an effect estimate developed from Dockery et al. (1996). Health effects from air pollution can also result in missed days of work (either from personal symptoms or from caring for a sick family member). Days of work lost due to PM 2.5 were estimated using an effect estimate developed from Ostro (1987). Children may also be absent from school because of respiratory or other diseases caused by expos ure to air pollution , but we have not quantified these effects for this rule

. We estimate three types of acute respiratory symptoms: lower respiratory symptoms, upper respiratory symptoms, and minor restricted activity days (MRAD). Incidences of lower resp iratory symptoms (e.g., wheezing, deep cough) in children aged 7 to 14 were estimated using an effect estimate from Schwartz and Neas (2000). Incidences of upper respiratory symptoms in asthmatic children aged 9 to 11 are estimated using an effect estimate developed from Pope et al. (1991). Because asthmatics have greater sensitivity to stimuli (including air pollution), children with asthma can be more susceptible to a variety of upper respiratory symptoms (e.g., runny or stuffy nose; wet cough; and burnin g, aching, or red eyes). Research on the effects of air pollution on upper respiratory symptoms has thus focused on effects in asthmatics. Minor restricted activity days (MRAD) result when individuals reduce most usual daily activities and replace them wi th less strenuous activities or rest, yet not to the point of missing work or school. For example, a mechanic who would usually be doing physical work most of the day will instead spend the day at a desk doing paper and phone work because of difficulty

14 See http://www.nlm.nih.gov/medlineplus/ency/article/ 001087.htm , accessed April 2012

.

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- 51 bre athing or chest pain. The effect of PM 2.5 on MRAD was estimated using an effect estimate derived from Ostro and Rothschild (1989). More recently published literature examining the relationship between short

- term PM 2.5 exposure and acute respiratory symptom s was available in the PM ISA (U.S. EPA, 2009) , but proved to be unsuitable for use in this benefits analysis. In particular, the best available study ( Patel et al., 2010) specified a population aged 13

– 20, which overlaps with the population in which we asses asthma exacerbation. As we describe in detail below, to avoid the chance of double

- counting impacts, we do not estimate changes in acute respiratory symptoms and asthma exacerbation among populations of the same age. For this RIA , we have followed th e SAB

- HES recommendations regarding asthma exacerbations in developing the core estimate (U.S. EPA

- SAB, 2004 a )

. Although certain studies of acute respiratory events characterize these impacts among only asthmatic populations, others consider the full popul ation, including both asthmatics and non

- asthmatics. For this reason, incidence estimates derived from studies focused only on asthmatics cannot be added to estimates from studies that consider the full population

— to do so would double

- count impacts. To prevent such double

- counting, we estimat ed the exacerbation of asthma among children and excluded adults from the calculation. Asthma exacerbations occurring in adults are assumed to be captured in the general population endpoints such as work loss days and MRADs. Finally, note also the important distinction between the exacerbation of asthma among asthmatic populations, and the onset of asthma among populations not previously suffering from asthma; in this RIA , we quantify the exacerbation of asthma amo ng asthmatic populations and not the onset of new cases of asthma. To characterize asthma exacerbations in children, we selected two studies (Ostro et al., 2001; Mar et al., 2004) that followed panels of asthmatic children. Ostro et al. (2001) followed a g roup of 138 African

- American children in Los Angeles for 13 weeks, recording daily occurrences of respiratory symptoms associated with asthma exacerbations (e.g., shortness of breath, wheeze, and cough). This study found a statistically significant associa tion between PM 2.5 , measured as a 12

- hour average, and the daily prevalence of shortness of breath and wheeze endpoints. Although the association was not statistically significant for cough, the results were still positive and close to significance; conseq uently, we decided to include this endpoint, along with shortness of breath and wheeze, in generating incidence estimates (see below).

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- 52 Mar et al. (2004) studied the effects of various size fractions of particulate matter on respiratory symptoms of adults and children with asthma, monitored over many months. The study was conducted in Spokane, Washington, a semiarid city with diverse sources of particulate matter. Data on respiratory symptoms and medication use were record ed daily by the study ’ s subjects, while air pollution data was collected by the local air agency and Washington State University. Subjects in the study consisted of 16 adults

— the majority of whom participated for over a year

— and nine children, all of whom were studied for over eight months. Among the children, the authors found a strong association between cough symptoms and several metrics of particulate matter, including PM 2.5 . However, the authors found no association between respiratory symptoms and PM of any metric in adults. Mar et al. therefore concluded that the discrepancy in results between children and adults was due either to the way in which air quality was monitored, or a greater sensitivity of children than adults to increased levels of PM air pollution. We employed the following pooling approach in combining estimates generated using effect estimates from the two studies to produce a single asthma exacerbation incidence estimate. First, we used random/fixed effects pooling to combine the Ostro and Mar estimates for shortness of breath and cough. Next, we pooled the Ostro estimate of wheeze with the pooled cough and shortness of breath estimates to derive an overall estimate of asthma exacerbation. 5.6

. 3 .5 Effect Coefficients Selected for the Se nsitivity Analyses Chronic Bronchitis. Chronic bronchitis is characterized by mucus in the lungs and a persistent wet cough for at least 3 months a year for several years in a row. C hronic bronchitis affects an estimated 5 % of the U.S. population ( ALA , 1999). A limited number of studies have estimated the impact of air pollution on new incidences of chronic bronchitis. Schwartz (1993) and Abbey et al. (1995) provide evidence that long

- term PM 2.5 exposure gives rise to the development of chronic bronchiti s in adults in the United States; these remain the two most recent studies observing a relationship between long

- term exposure to PM 2.5 and the onset of chronic bronchitis in the U.S . The absence of newer studies finding a relationship between long

term PM 2.5 exposure and chronic bronchitis argues for moving this endpoint from the core benefits analysis to a sensitivity analysis

. In their review of the scientific literature on chronic obstructive pulmonary disease (COPD), which includes chronic bronchitis a nd emphysema, the

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- 53 American Thoracic Society concluded that air pollution is “ associated with COPD, but sufficient criteria for causation were not met ” (Eisner et al., 2010). Stroke . The PM ISA (U.S. EPA, 2009) includes several new studies that have examined the relationship between PM 2.5 exposure and cerebrovascular events ( U.S. EPA, 2009). Time

series studies have generally been inconsistent with several studies showing positive associations (Dominici et al. , 2006 ; Metzger et al. , 2004 ; Lippman et a l. , 2000 ; Lisabeth et al. , 2008). Several other studies have demonstrated null or negative associations (Anderson et al. , 2001 ; Barnett et al. , 2006 ; Peel et al. , 2007). In general, these studies examined cerebrovascular disease as a group, though a few st udies partition ischemic and hemorrhagic strokes separately (Lisabeth et al. , 2008). A key limitation of these time

- series studies is that they use hospital discharge rates as the diagnosis and relatively short lags (0

– 2 days)

— this is problematic, as discharge rates are an imperfect diagnosis and strokes may occur several days before admission to the hospital. Longer

- term prospective cohort studies of PM 2.5 and stroke include Miller et al. (2007)

. Miller et al. (2007) est imated the change in risk among post

- menopausal women enrolled in the Women ’ s Health Initiative ( U.S. EPA, 2009 b ). After adjusting for age, race, smoking status, educational level, household income, body

- mass index, diabetes, hypertension, and hypercholest erolemia, hazard ratios were estimated for the first cardiovascular event. Because this study considers first

- time cardiovascular events, a key challenge to incorporating this study into the core health impact assessment is match ing the baseline incidence rate correctly , and we have approximated this information using the data in the study

. In addition, Wellenius et al. ( 2012 ) examined the association of PM 2.5 with neurologist confirmed ischemic stroke in Boston adults in a time

- stratified case

- crossover study. A key feature of this study is that it included the time of stroke symptom onset for most patients. Similar to the challenge with Miller et al. (2007), we do not have baseline incidence rates, and we do not have suff icient data from the study to approximate it. Three factors argue for treating this endpoint in the sensitivity analysis: (1) the epidemiological literature examining PM

- related cerebrovascular events is still evolving; (2) there are special uncertainties associated with quantifying this endpoint; (3) we have not yet identified an appropriate method for estimating the economic value of this endpoint.

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- 54 Cardiovascular Emergency Department Visits. A large number of recent U.S.

- based studies provide support for an association between short

- term increases in PM 2.5 and increased risk of ED visits for ischemic heart diseases ( U.S. EPA, 2009 b ). Both Metzger et al. (2004) and Tolbert et al. (2007) published interim results from the Study of Particles and Health in Atlanta (SOPHIA), finding a relationship between PM 2.5 exposure and cardiovascular emergency department visits. These cardiovascular emergency department visits are distinct from cardiovascular hospital admissions and non

- fatal heart attacks. To ensure no double

- counting, we excluded ICD

- 9

- 411 (ischemic heart disease) from the baseline incidence rates for cardiovascular emergency department visits. Mathes et al. (2011) find relationships between PM 2.5 levels and cardiovascular emergency department visits in New York City. The principal challenge to incorporating these studies is the absence of readily

- available economic valuation estimates for cardiovascular emergency department visits. Until we develop an approach for estimating the economic value of this endpoint, we will quantify these ED visits in a sensitivity analysis only

. 5.6.4 Unquantified Human Health Benefits
T he illustrative emission reduction strategies to reach the revised and alternative annual standards described in Chapter 4 would reduce emissions of directly emit ted particles, as well as SO 2 , and NO x for an alternative standard for 11 μg/m 3

. The extent to which down wind exposure to secondary pollutants ozone , SO 2 , NOx , and /or methyl mercury would actually be reduced would depend on the specific control strategy that States would use to reduce PM 2.5 in a given area as well as local geographic and meteorological conditions

. Although we have quantified many of the health benefits associated with reducing exposure to PM 2.5 , as shown in Table 5

- 2, we are unable to qua ntify the health benefits associated with reducing the potential for ozone exposure, SO 2 exposure, NO 2 exposure or contamination of local water bodies with mercury methylmercury exposure due to the absence of air quality modeling data for these pollutants in this analysis . Although we applied the rollback method to simulate the impact of attaining the revised and alternative annual standards on ambient levels of PM 2.5 , this method does not simulate how the illustrative emission reductions would affect ambi ent levels of ozone, SO 2 , or NO 2 . Furthermore, the air quality modeling conducted for this analysis did not assess mercury, so we are unable to estimate mercury deposition associated with the illustrative controls or subsequent bioaccumulation and exposure

. Below we provide a qualitative description of these health benefits. In general, previous analyses have shown that

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- 55 the monetized value of these additional health benefits is much smaller than PM 2.5 - related benefits (U.S. EPA, 2010a, 2010 c, 2010 d). Reducing NO x emissions also reduce s ozone concentrations in most areas. Reducing ambient ozone concentrations is associated with significant human health benefits, including mortality and respiratory morbidity (U.S. EPA, 2008a, 2010d ). Epidemiological researchers have associated ozone exposure with adverse health effects in numerous toxicological, clinical and epidemiological studies (U.S. EPA, 2006b ). When adequate data and resources are available, the EPA generally quantifies several h ealth effects associated with exposure to ozone (e.g., U.S. EPA, 2008a, 2010d , 2011a , 2011c ). These health effects include respiratory morbidity such as asthma attacks, hospital and emergency department visits, school loss days, as well as premature mortal ity. T he scientific literature suggests that exposure to ozone is also associated with chronic respiratory damage and premature aging of the lungs , but the EPA has not quantified these effects in benefits analyses previously

. Following an extensive evaluation of health evidence from epidemiologic and laboratory studies, the Integrated Science Assessment for Sulfur Dioxide

— Health Criteria (SO 2 ISA) concluded that there is a causal relationship between respiratory health effects and short

- term exposure to SO 2 (U.S. EPA, 2008 c ). The immediate effect of SO 2 on the respiratory system in humans is bronchoconstriction. Asthmatics are more sensitive to the effects of SO 2 likely resulting from preexisting inflammation associated with this disease. A clear concentration

response relationship has been demonstrated in laboratory studies following exposures to SO 2 at concentrations between 20 and 100 ppb, both in terms of increasing severity of effect and percentage of asthmatics adversely affected. Based on ou r review of this information, we identified four short

- term morbidity endpoints that the SO 2 ISA identified as a “ causal relationship ” : asthma exacerbation, respiratory

- related emergency department visits, and respiratory

- related hospitalizations. The diff ering evidence and associated strength of the evidence for these different effects is described in detail in the SO 2 ISA. The SO 2 ISA also concluded that the relationship between short

- term SO 2 exposure and premature mortality was

“ suggestive of a causal r elationship ” because it is difficult to attribute the mortality risk effects to SO 2 alone. Although the SO 2 ISA stated that studies are generally consistent in reporting a relationship between SO 2 exposure and mortality, there was a lack of robustness of t he observed associations to adjustment for pollutants. We did not quantify these benefits due to data constraints.

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- 56 Epidemiological researchers have associated NO 2 exposure with adverse health effects in numerous toxicological, clinical and epidemiological studies, as described in the Integrated Science Assessment for Oxides of Nitrogen

— Health Criteria (NO 2 ISA) (U.S. EPA, 2008b ). The NO 2 ISA provides a comprehensive review of the current evidence of health and environmental effects of NO 2 . The NO 2 ISA concluded that the evidence “ is sufficient to infer a likely causal relationship between short

- term NO 2 exposure and adverse effects on the respiratory system

. ” These epidemiologic and experimental studies encompass a number of endpoints including emer gency d epartment visits and hospitalizations, respiratory symptoms, airway hyperresponsiveness, airway inflammation, and lung function. Effect estimates from epidemiologic studies conducted in the United States and Canada generally indicate a 2

– 2 0% increas e in risks for ED visits and hospital admissions and higher risks for respiratory symptoms. The NO 2 ISA concluded that the relationship between short

- term NO 2 exposure and premature mortality was “ suggestive but not sufficient to infer a causal relationshi p ” because it is difficult to attribute the mortality risk effects to NO 2 alone. Although the NO 2 ISA stated that studies consistently reported a relationship between NO 2 exposure and mortality, the effect was generally smaller than that for other pollutan ts such as PM. We did not quantify these benefits due to data constraints. 5.6.5 Economic Valuation Estimates Reductions in ambient concentrations of air pollution generally lower the risk of future adverse health effects for a large population. Therefore, the a ppropriate economic measure is WTP for changes in risk of a health effect rather than WTP for a health effect that would occur with certainty (Freeman, 1993). Epidemiological studies generally provide estimates of the relative risks of a particular health effect that is avoided because of a reduction in air pollution. We converted those changes in risk to units of avoided statistical incidence for ease of presentation. We calculated the value of avoided statistical incidences by dividing individual WTP for a risk reduction by the related observed change in risk. WTP estimates generally are not available for some health effects, such as hospital admissions. In these cases, we instead used the cost of treating or mitigating the effect to estimate the economic value . COI estimates generally ( al though not necessarily in all cases) understate the true value o f reducing the risk of a health effect, because they reflect the direct expenditures related to treatment, but not the value of avoided pain and suffering (Harrington and Portney, 1987; Berger, 1987).

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- 57 We provide unit values for health endpoints (along wit h information on the distribution of the unit value) in Table 5

- 9 . All values are in constant year 2006 dollars, adjusted for growth in real income for WTP estimates out to 2020 using projections provided by Standard and Poor ’ s , which is discussed in furth er detail in Section 5.6.8. Economic theory argues that WTP for most goods (such as environmental protection) will increase if real income increases. Several of the valuation studies used in this analysis were conducted in the late 1980s and early 1990s , a nd we are in the process of reviewing the literature to update these unit values . The discussion below provides additional details on valuing specific PM 2.5 - related related endpoints. 5.6.6.1 Mortality Valuation Following the advice of the SAB’s Environmental Economics Advisory Committee (SAB

EEAC) , the EPA currently uses the value of statistical life (VSL) approach in calculating the core estimate of mortality benefits, because we believe this calculation provides the most reasonable single estim ate of an individual’s willingness to trade off money for reductions in mortality risk (U.S. EPA

- SAB, 2000). The VSL approach is a summary measure for the value of small changes in mortality risk experienced by a large number of people. For a period of tim e (2004

– 2008), the Office of Air and Radiation (OAR) valued mortality risk reductions using a VSL estimate derived from a limited analysis of some of the available studies. OAR arrived at a VSL using a range of $1 million to $10 million (2000$) consistent with two meta

- analyses of the wage - risk literature. The $1 million value represented the lower end of the interquartile range from the Mrozek and Taylor (2002) meta

- analysis of 33 studies. The $10 million value represented the upper end of the interquartil e range from the Viscusi and Aldy (2003) meta

analysis of 43 studies. The mean estimate of $5.5 million (2000$) was also consistent with the mean VSL of $5.4 million estimated in the Kochi et al. (2006) meta

- analysis. However, the Agency neither changed it s official guidance on the use of VSL in rule

- makings nor subjected the interim estimate to a scientific peer

- review process through SAB or other peer

- review group.*** E.O. 12866 Review
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### Table 5
- 9 . Unit Values for Economic Valuation of Health Endpoints ( 2010$ ) a

Health Endpoint Central Estimate of Value Per Statistical Incidence Derivation of Distributions of Estimates 1990 Income Level 2020 Income Level Premature Mortality (Value of a Statistical Life) $ 8 , 0 00 ,000 $ 9 , 6 00 ,000 The EPA currently recommends a central VSL of $ 4
. 8m ( 1990 $ , 1990 income ) based on a Weibull distribution fitted to 26 published VSL estimates (5 contingent valuation and 21 labor market studies). The underlying studies, the distribution parameters, and other useful information are available in Appendix B of the EPA ’ s Guidelin es for Preparing Economic Analyses (U.S. EPA, 2010 e ). Nonfatal Myocardial Infarction (heart attack) 3% discount rat e Age 0
– 24 Age 25
– 44 Age 45
– 54 Age 55
– 64 Age 65 and over
7% discount rate Age 0
– 24 Age 25
– 44 Age 45
– 54 Age 55
– 6 4 Age 65 and over $ 98 ,000 $ 110 ,000 $ 120 ,000 $ 200 ,000 $ 98 ,000
$ 97 ,000 $ 110 ,000 $ 110 ,000 $ 190 ,000 $ 97 ,000 $98,000 $110,000 $120,000 $200,000 $98,000
$97,000 $110,000 $110,000 $190,000 $97,000 No distributional information available. Age

- specific cost

- of

- illness

values reflect lost earnings and direct medical costs over a 5

- year period following a nonfatal MI. Lost earnings estimates are based on Cropper and Krupnick (1990). Direct medical costs are based on simple average of estimates from Russell et al. (1998) and Wittels et al. (1990). Lost earnings: Cropper and Krupnick (1990). Present discounted value of 5 years of lost earnings in 2000$ : age of onset: at 3% at 7% 25
– 44 $ 9,000 $ 8,000 45
– 54 $ 13,000 $12,000 55
– 65 $ 77,000 $69,000 Direct medical expenses (2000$) : An average of: 1. Wittels et al. (1990) ($ 100 , 000
— no discounting) 2. Russell et al. (1998), 5

- year period ($22, 000 at 3% discount rate; $21, 000 at 7% discount rate) (continued)*** E.O. 12866 Review
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### Table 5
- 9 . Unit Values for Economic Valuation of Health Endpoints ( 20 10$ ) a 

### (continued)

Health Endpoint Central Estimate of Value Per Statistical Incidence Derivation of Distributions of Estimates 2000 Income Level 2020 Income Level Hospital Admissions Chronic Lung Disease (18

– 64) $21,000 $21,000 No distributional information available. The COI estimates (lost earnings plus direct medical costs) are based on ICD

- 9 code

- level information (e.g., average hospital care costs, average length of hospital stay, and weighted share of total chronic lung illnesses) reported i n Agency for Healthcare Research and Quality (2007) (www.ahrq.gov). Asthma Admissions (0

– 64) $ 16 ,000 $ 16 ,000 No distributional information available. The COI estimates (lost earnings plus direct medical costs) are based on ICD

- 9 code

- level information (e.g., average hospital care costs, average length of hospital stay, and weighted share of total asthma category illnesses) reported in Agency for Healthcare Research and Quality (200 7 ) (www.ahrq.gov). All Cardiovascular Age 18
– 64 Age 65
– 99 $ 42 ,000 $ 41 ,000 $ 42 ,000 $ 41 ,000 No distributional information available. The COI estimates (lost

earnings plus direct medical costs) are based on ICD

- 9 code

- level information (e.g., average hospital care costs, average length of hospital stay, and weighted share of total cardiovascular category illnesses) reported in Agency for Healthcare Research and Quality (200 7 ) (www.ahrq.gov). All respiratory (ages 65+) $ 36 ,000 $ 36 ,0 00 No distributions available. The COI point estimates (lost earnings plus direct medical costs ) are based on ICD

- 9 code level information (e.g., average hospital care costs, average length of hospital stay, and weighted share of total respiratory category illnesses) reported in Agency for Healthcare Research and Quality, 200 7 (www.ahrq.gov). Emergency Department Visits for Asthma $ 430 $ 430 No distributional information available. Simple average of two unit COI values (2000$) : (1) $ 310 , from Smith et al. (1997) and (2) $260, from Stanford et al. (1999). (continued)*** E.O. 12866 Review
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### Table 5
- 9 . Unit Values for Economic Valuation of Health Endpoints ( 2010$ ) a 

### (continued)

Health Endpoint Central Estimate of Value Per Statistical Incidence Derivation of Distributions of Estimates 2000 Income Level 2020 Income Level Respiratory Ailments Not Requiring Hospitalization Upper Respiratory Symptoms (URS) $ 31 $ 33 Combinations of the three symptoms for which WTP estimates are available that closely match those listed by Pope et al. result in seven different “ symptom clusters, ” each describing a “ type ” of URS. A dollar value was derived for each type of URS, using mid

- range estimates of WTP (IEc, 1994) to avoid each symptom in the cluster and assuming additivity of WTPs. In the absence of information surrounding the frequency with which each of the seve n types of URS occurs within the URS symptom complex, we assumed a uniform distribution between $9.2 and $43 (2000$)

. Lower Respiratory Symptoms (LRS) $ 20 $ 21 Combinations of the four symptoms for which WTP estimates are available that closely match those listed by Schwartz et al. result in 11 different “ symptom clusters, ” each describing a “ type ” of LRS. A dollar value was derived for each type of LRS, using mi d

- range estimates of WTP (IEc, 1994) to avoid each symptom in the cluster and assuming additivity of WTPs. The dollar value for LRS is the average of the dollar values for the 11 different types of LRS. In the absence of information surrounding the frequen cy with which each of the 11 types of LRS occurs within the LRS symptom complex, we assumed a uniform distribution between $6.9 and $ 25 (2000$)

. Asthma Exacerbations $ 54 $ 58 Asthma exacerbations are valued at $45 per incidence, based on the mean of averag e WTP estimates for the four severity definitions of a
“ bad asthma day, ” described in Rowe and Chestnut (1986). This study surveyed asthmatics to estimate WTP for avoidance of a “ bad asthma day, ” as defined by the subjects. For purposes of valuation, an as thma exacerbation is assumed to be equivalent to a day in which asthma is moderate or worse as reported in the Rowe and Chestnut (1986) study. The value is assumed have a uniform distribution between $16 and $7 1 (2000$)

. (continued)*** E.O. 12866 Review
- Draft
- Do Not Cite, Quote, or Release During Review ***

5 - 61 

### Table 5
- 9 . Unit Values for Economic Valuation of Health Endpoints ( 2010$ ) a 

### (continued)

Health Endpoint Central Estimate of Value Per Statistical Incidence Derivation of Distributions of Estimates 2000 Income Level 2020 Income Level Respiratory Ailments Not Requiring Hospitalization (continued) Acute Bronchitis $ 450 $ 480 Assumes a 6

- day episode, with the distribution of the daily value specified as uniform with the low and high values based on those recommended for related respiratory symptoms in Neumann et al. (1994) . The low daily estimate of $10 is the sum of the mid

- range values recommended by IEc (1994) for two symptoms believed to be associated with acute bronchitis: coughing and chest tightness. The high daily estimate was taken to be twice the value of a minor respiratory restricted

- activity day, or $110 (2000$)

. Work Loss Days (WLDs) Variable (U.S. median = $ 1 5 0 ) Variable (U.S. median = $ 1 5 0 ) No distribution available. Point estimate is based on county

- specific median annual wages divided by 52 and then by 5

— to get median daily wage. U.S. Year 2000 Census, compiled by Geolytics, Inc. (Geolytics, 2002) Minor Restricted Activity Days (MRADs) $ 64 $ 68 Median WTP estimate to avoid one MRAD from Tolley et al. (1986). Distribution is assumed to be triangular with a minimum of $22 and a maximum of $83, with a most likely value of $52 (2000$) . Range is based on assumption that value should exceed WTP fo r a single mild symptom (the highest estimate for a single symptom

— for eye irritation
— is $16.00) and be less than that for a WLD. The triangular distribution acknowledges that the actual value is likely to be closer to the point estimate than either extrem e.

a All estimates are rounded to two significant digits. Unrounded estimates in 2000$ are available in the Ap pendi x J of the BenMAP user manual ( Abt Associates, 2012 )

.

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Page 62 of 423 During this time, the Agency continued work to update its guidance on valuing mortality risk reductions, including commissioning a report from meta

- analytic experts to evaluate methodological questions raised by the EPA and the SAB on combining estimates from the various data sources. In addition, the Agency consulted several times with the SAB

- EEAC on the issue. With input from the meta

- analytic experts, the SAB

EEAC advised the Agency to update its guidance using speci fic, appropriate meta

analytic techniques to combine estimates from unique data sources and different studies, including those using different methodologies (i.e., wage

- risk and stated preference) (U.S. EPA

- SAB, 2007). Until updated guidance is available, the Agency determined that a single, peer

reviewed estimate applied consistently best reflects the SAB

- EEAC advice it has received. Therefore, the Agency has decided to apply the VSL that was vetted and endorsed by the SAB in the Guidelines for Preparing E conomic Analyses (U.S. EPA, 2000) 15 while the Agency continues its efforts to update its guidance on this issue. This approach calculates a mean value across VSL estimates derived from 26 labor market and contingent valuation studies published between 1974 and 1991. The mean VSL across these studies is $4.8 million (1990$) or $6.3 million (2000$). 16 The Agency is committed to using scientifically sound, appropriately reviewed evidence in valuing mortality risk reductions and has made significant progress in r esponding to the SAB

EEAC ’ s specific recommendations. In the process, the Agency has identified a number of important issues to be considered in updating its mortality risk valuation estimates. These are detailed in a white paper on “ Valuing Mortality Risk Reductions in Environmental Policy, ” which recently underwent review by the SAB

- EEAC . A meeting with the SAB on this paper was held on March 14, 2011 and formal recommendations were transmitted on July 29, 2011 (U.S. EPA

- SAB, 2011). Draft guidance respond ing to SAB recommendations will be developed shortly. The economics literature concerning the appropriate method for valuing reductions in premature mortality risk is still developing. The adoption of a value for the

15 In the updated Guidelines for Preparing Economic Analyses (U.S. EPA, 2010e), EPA retained the VSL endorsed by the SAB with the understanding that further updates to the mor tality risk valuation guidance would be forthcoming in the near future. 16 In this analysis, we adjust the VSL to account for a different currency year ( 2010$ ) and to account for income growth to 2020 . After applying these adjustments to the $6.3 million v alue, the VSL is $8. 9 M.

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Page 63 of 423 projected reduction in the risk of prem ature mortality is the subject of continuing discussion within the economics and public policy analysis community. The EPA strives to use the best economic science in its analyses. Given the mixed theoretical finding and empirical evidence regarding adjust ments to VSL for risk and population characteristics (e.g., Smith et al., 2004; Alberini et al., 2004; Aldy and Viscusi, 2008) , we use a single VSL for all reductions in mortality risk. Although there are several differences between the labor market studie s the EPA uses to derive a VSL estimate and the PM 2.5 air pollution context addressed here, those differences in the affected populations and the nature of the risks imply both upward and downward adjustments. Table 5

- 1 0 lists some of these differences and the expected effect on the VSL estimate for air pollution

- related mortality. In the absence of a comprehensive and balanced set of adjustment factors, the EPA believes it is reasonable to continue to use the $4.8 million (1990$) value adjusted for inflati on and income growth over time while acknowledging the significant limitations and uncertainties in the available literature. Table 5
- 1 0 . Influence of Applied VSL Attributes on the Size of the Economic Benefits

of Reductions in the Risk of Premature Death (U.S. EPA, 2006a)
Attribute Expected Direction of Bias Age Uncertain, perhaps overestimate Life Expectancy/Health Status Uncertain, perhaps overestimate Attitudes Toward Risk Underestimate Income Uncertain Voluntary vs. Involuntary Uncertain, perhaps underestimate Catastrophic vs. Protracted Death Uncertain, perhaps underestimate
The SAB

- EEAC has reviewed many potential VSL adjustments and the state of the economics literature. The SAB

- EEAC advised the EPA to “continue to use a wage

- risk

based VSL as its primary estimate, including appropriate sensitivity analyses to reflect the uncertainty of these estimates,” and that “the only risk characteristic for which adjustments to the VSL can be made is the timing of the risk” (U.S. EPA

- SAB, 2000). In

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Page 64 of 423 develo ping our core estimate of the benefits of premature mortality reductions, we have followed this advice. For premature mortality, we assume that there is a “cessation” lag between PM exposures and the total realization of changes in health effects. We assu med for this analysis that some of the incidences of premature mortality related to PM 2.5 exposures occur in a distributed fashion over the 20 years following exposure and discounted over the period between exposure and premature mortality. Although the st ructure of the lag is uncertain, the EPA follows the advice of the SAB

- HES to assume a segmented lag structure characterized by 30% of mortality reductions in the first year, 50% over years 2 to 5, and 20% over the years 6 to 20 after the reduction in PM 2. 5 (U.S. EPA

- SAB, 2004c). Additional cessation lag structures are described and assessed in Appendix 5.A of this RIA. To take this into account in the valuation of reductions in premature mortality, we discount the value of premature mortality occurring in future years using rates of 3% and 7%. 17 Changes in the cessation lag assumptions do not change the total number of estimated deaths but rather the timing of those deaths. As such, the monetized benefits using a 7% discount rate are only approximately 10% l ess than the monetized benefits using a 3% discount rate. Further discussion of this topic appears in the EPA ’s Guidelines for Preparing Economic Analyses (U.S. EPA, 2010e). Uncertainties Specific to Premature Mortality Valuation . The economic benefits associated with reductions in the risk of premature mortality are the largest category of monetized benefits in this RIA . In addition, in prior analyses, the EPA has identified valuation of mortality

- related benefits as the largest co ntributor to the range of uncertainty in monetized benefits (Mansfield et al., 2009). 18 Because of the uncertainty in estimates of the value of reducing premature mortality risk, it is important to adequately characterize and understand the various types of economic approaches

17 The choice of a discount rate, and its associated conceptual basis, is a topic of ongoing discussion within the federal government. To comply with Circular A

- 4, EPA provides monetized benefits using discount rates of 3% and 7% (O MB, 2003). A 3% discount reflects reliance on a “ social rate of time preference ” discounting concept. A 7% rate is consistent with an “ opportunity cost of capital ” concept to reflect the time value of resources directed to meet regulatory requirements. 18 This conclusion was based on an assessment of uncertainty based on statistical error in epidemiological effect estimates and economic valuation estimates. Additional sources of model error such as those examined in the PM 2.5 mortality expert elicitation (R oman et al., 2008) may result in different conclusions about the relative contribution of sources of uncertainty.

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Page 65 of 423 available for valuing reductions in mortality risk. Such an assessment also requires an understanding of how alternative valuation approaches reflect that some individuals may be more susceptible to air pollution

- induced mortality or r eflect differences in the nature of the risk presented by air pollution relative to the risks studied in the relevant economics literature. The health science literature on air pollution indicates that several human characteristics affect the degree to whi ch mortality risk affects an individual. For example, some age groups appear to be more susceptible to air pollution than others (e.g., the elderly and children). Health status prior to exposure also affects susceptibility. An ideal benefits estimate of mo rtality risk reduction would reflect these human characteristics, in addition to an individual ’ s WTP to improve one ’ s own chances of survival plus WTP to improve other individuals ’ survival rates. The ideal measure would also take into account the specific nature of the risk reduction commodity that is provided to individuals, as well as the context in which risk is reduced. To measure this value, it is important to assess how reductions in air pollution reduce the risk of dying from the time that reduction s take effect onward and how individuals value these changes. Each individual ’ s survival curve, or the probability of surviving beyond a given age, should shift as a result of an environmental quality improvement. For example, changing the current probabil ity of survival for an individual also shifts future probabilities of that individual ’ s survival. This probability shift will differ across individuals because survival curves depend on such characteristics as age, health state, and the current age to whic h the individual is likely to survive. Although a survival curve approach provides a theoretically preferred method for valuing the benefits of reduced risk of premature mortality associated with reducing air pollution, the approach requires a great deal o f data to implement. The economic valuation literature does not yet include good estimates of the value of this risk reduction commodity. As a result, in this study we value reductions in premature mortality risk using the VSL approach.

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Page 66 of 423 Other uncertainties specific to premature mortality valuation include the following:

 Across

- study variation: There is considerable uncertainty as to whether the available literature on VSL provides adequate estimates of the VSL for risk reductions from air pollution reductio n. Although there is considerable variation in the analytical designs and data used in the existing literature, the majority of the studies involve the value of risks to a middle

- aged working population. Most of the studies examine differences in wages of risky occupations, using a hedonic wage approach. Certain characteristics of both the population affected and the mortality risk facing that population are believed to affect the average WTP to reduce the risk. The appropriateness of a distribution of WTP based on the current VSL literature for valuing the mortality

- related benefits of reductions in air pollution concentrations therefore depends not only on the quality of the studies (i.e., how well they measure what they are trying to measure), but also on the extent to which the risks being valued are similar and the extent to which the subjects in the studies are similar to the population affected by changes in pollution concentrations.

 Level of risk reduction: The transferability of estimates of the VSL from the wage - risk studies to the context of the PM NAAQS analysis rests on the assumption that, within a reasonable range, WTP for reductions in mortality risk is linear in risk reduction. For example, suppose a study provides a result that the average WT P for a reduction in mortality risk of 1/100,000 is $50, but that the actual mortality risk reduction resulting from a given pollutant reduction is 1/10,000. If WTP for reductions in mortality risk is linear in risk reduction, then a WTP of $50 for a reduc tion of 1/100,000 implies a WTP of $500 for a risk reduction of 1/10,000 (which is 10 times the risk reduction valued in the study). Under the assumption of linearity, the estimate of the VSL does not depend on the particular amount of risk reduction being valued. This assumption has been shown to be reasonable provided the change in the risk being valued is within the range of risks evaluated in the underlying studies (Rowlatt et al., 1998).

 Voluntariness of risks evaluated: Although job

- related mortality risks may differ in several ways from air pollution

- related mortality risks, the most important difference may be that job

- related risks are incurred voluntarily, or generally assumed to be, whereas air pollution

- related risks are incurred involuntarily. S ome evidence suggests that people will pay more to reduce involuntarily incurred risks than risks incurred voluntarily (e.g., Lichtenstein and Slovic, 2006) . If this is the case, WTP estimates based on wage

- risk

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Page 67 of 423 studies may understate WTP to reduce involun tarily incurred air pollution

related mortality risks.

 Sudden versus protracted death: A final important difference related to the nature of the risk may be that some workplace mortality risks tend to involve sudden, catastrophic events, whereas air pollut ion

- related risks tend to involve longer periods of disease and suffering prior to death. Some evidence suggests that WTP to avoid a risk of a protracted death involving prolonged suffering and loss of dignity and personal control is greater than the WTP t o avoid a risk (of identical magnitude) of sudden death (e.g., Tsuge et al., 2005; Alberini and Scasny, 2011) . To the extent that the mortality risks addressed in this assessment are associated with longer periods of illness or greater pain and suffering t han are the risks addressed in the valuation literature, the WTP measurements employed in the present analysis would reflect a downward bias.

 Self

- selection and skill in avoiding risk: Recent research (Shogren and Stamland, 2002) suggests that VSL estimates based on hedonic wage studies may overstate the average value of a risk reduction. This is based on the fact that the risk

- wage trade

- off revealed in hedonic studies reflects the preferences of the marginal worker (i.e., that worker who demands t he highest compensation for his risk reduction for a given job). This worker must have either a higher workplace risk than the average worker in a given occupation, a lower risk tolerance than the average worker in that occupation, or both. Conversely, the marginal worker should have a higher risk tolerance than workers employed in less

- risky sectors. However, the risk estimate used in hedonic studies is generally based on average risk, so the VSL may be biased, in an ambiguous direction, because the wage d ifferential and risk measures do not match.

 Baseline risk and age: Recent research (Smith, Pattanayak, and Van Houtven, 2006) finds that because individuals reevaluate their baseline risk of death as they age, the marginal value of risk reductions does not decline with age as predicted by some lifetime consumption models. This research supports findings in recent stated preference studies that suggest only small reductions in the value of mortality risk reductions with increasing age (e.g., Alberini et al., 2004)

. 5.6.6.2 Nonfatal Myocardial Infarctions Valuation We were not able to identify a suitable WTP value for reductions in the risk of nonfatal heart attacks. Instead, we use a COI unit value with two components: the direct

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Page 68 of 423 medical costs and the opportu nity cost (lost earnings) associated with the illness event. Because the costs associated with a myocardial infarction extend beyond the initial event itself, we consider costs incurred over several years. Using age

- specific annual lost earnings estimated by Cropper and Krupnick (1990) and a 3% discount rate, we estimated a rounded present discounted value in lost earnings (in 2000$) over 5 years due to a myocardial infarction of $8,800 for someone between the ages of 25 and 44, $13,000 for someone between the ages of 45 and 54, and $75,000 for someone between the ages of 55 and 65. The rounded corresponding age

- specific estimates of lost earnings (in 2000$) using a 7% discount rate are $7,900, $12,000, and $67,000, respectively. Cropper and Krupnick (1990) do not provide lost earnings estimates for populations under 25 or over 65. As such, we do not include lost earnings in the cost estimates for these age groups. We found three possible sources in the literature of estimates of the direct medical costs of m yocardial infarction, which provide significantly different values (see Table 5

- 1 1 ):

 Wittels et al. (1990) estimated expected total medical costs of myocardial infarction over 5 years to be $51,000 (rounded in 1986$) for people who were admitted to the hos pital and survived hospitalization. (There does not appear to be any discounting used.) This estimated cost is based on a medical cost model, which incorporated therapeutic options, projected outcomes, and prices (using “ knowledgeable cardiologists ” as consultants). The model used medical data and medical decision algorithms to estimate the probabilities of certain events and/or medical procedures being used. The authors note that the average length of hospitalization for acute myocardial infarction has decreased over time (from an average of 12.9 days in 1980 to an average of 11 days in 1983). Wittels et al. used 10 days as the average in their study. It is unclear how much further the length of stay for myocardial infarction may have decreased from 1983 to the present. The average length of stay for ICD code 410 (myocardial infarction) in the year

- 2000 Agency for Healthcare Research and Quality (AHRQ) HCUP database is 5.5 days ( AHRQ , 2000) . However, this may include patients who died in the hospital (not included among our nonfatal myocardial infarction cases), and whose length of stay was therefore substantially shorter than it would be if they had not died.

 Eisenstein et al. (2001) estimated 10

- year costs of $45,000 in rounded 1997$ (using a 3% disc ount rate) for myocardial infarction patients, using statistical

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Page 69 of 423 prediction (regression) models to estimate inpatient costs. Only inpatient costs (physician fees and hospital costs) were included. Table 5
- 11. Alternative Direct Medical Cost of Illness Esti mates for Nonfatal Heart

Attacks a
Study Direct Medical Costs (2010$) Over an x - Year Period, for x = Wittels et al. (1990) $1 6 0,000 b 5 Russell et al. (1998) $3 3 ,000 c 5 Average (5

- year) costs $ 98 ,000 5 Eisenstein et al. (2001) $ 7 4,000 c 10

a All estimates rounded to two significant digits. Unrounded estimates in 2000$ are available in appendix J of the BenMAP user manual ( Abt Associates, 2012 ). b Wittels et al. (1990) did not appear to discount costs incurred in future years.
c Using a 3% discount rate. Discounted values as reported in the study. As noted above, the estimates from these three studies are substantially different, and we have not adequately resolved the sources of differences in the estimates. Because the wage

- related opportunity cos t estimates from Cropper and Krupnick (1990) cover a 5

- year period, we used estimates for medical costs that similarly cover a 5

- year period (i.e., estimates from Wittels et al. (1990) and Russell et al. (1998). We used a simple average of the two 5

- year e stimates, or rounded to $ 85 ,000, and added it to the 5

- year opportunity cost estimate. The resulting estimates are given in Table 5

- 1 2

. Table 5
- 1 2 . Estimated Costs Over a 5
- Year Period of a Nonfatal Myocardial Infarction

(in 2010$ ) a
Age Group Opportunity Cost Medical Cost b Total Cost 0
– 24 $0 $ 98 ,000 $ 98 ,000 25
– 44 $1 2 ,000 c $ 98 ,000 $ 110 ,000 45
– 54 $ 17 ,000 c $ 98 ,000 $1 20 ,000 55
– 65 $ 100 ,000 c $ 98 ,000 $ 200 ,000 > 65 $0 $ 98 ,000 $ 98 ,000

a All estimates rounded to two significant digits , so estimates may not sum across columns . Unrounded estimates in 2000$ are available in appendix J of the BenMAP user manual ( Abt Associates, 2012 ).

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Page 70 of 423 b An average of the 5

- year costs estimated by Wittels et al. (1990) and Russell et al. (1998).
c From Cropper and Krupnick (1990), using a 3% discount rate for illustration

. 5.6.6 Hospital Admissions and Emergency Department Valuation In the absence of estimates of societal WTP to avoid hospital visits/admissions for specific illnesses, we derive COI estimates for use in the benefits analys is. The International Classification of Diseases (WHO, 1977) code

- specific COI estimates used in this analysis consist of estimated hospital charges and the estimated opportunity cost of time spent in the hospital (based on the average length of a hospital stay for the illness). We based all estimates of hospital charges and length of stays on statistics provided by the Agency for Healthcare Research and Quality ’ s Healthcare Utilization Project National Inpatient Sample (NIS) database ( AHRQ , 2007). We estim ated the opportunity cost of a day spent in the hospital as the value of the lost daily wage, regardless of whether the hospitalized individual is in the workforce. To estimate the lost daily wage, we divided the median weekly wage reported by the 2007 Ame rican Community Survey (ACS) by five and deflated the result to year 2010$ using the CPI

- U “ all items ” ( Abt Associates, 2012 ). The resulting national average lost daily wage is $1 48 . The total cost

- of

- illness estimate for an ICD code

- specific hospital stay lasting n days, then, was the mean hospital charge plus $1 48 multiplied by n. In general, the mean length of stay has decreased since the 2000 database used in previous version of BenMAP while the mean hospital charge has increased. We provide the rounded unit values in 2 01 0$ for the COI functions used in this analysis in Table 5

- 1 3

. Table 5
- 1 3 . Unit Values for Hospital Admissions

End Point ICD Codes Age Range Mean Hospital Charge (20 1 0$) Mean

Length of Stay (days) Total Cost of

Illness (unit value in 20 1 0$) min. max. HA, Chronic Lung Disease 490
– 496 18 64 $19,000 3.9 $21,000 HA, Asthma 493 0 64 $14,000 3.0 $16,000 HA, All Cardiovascular 390
– 429 18 64 $ 40 ,000 4.1 $ 42 ,000 HA, All Cardiovascular 390
– 429 65 99 $ 37 ,000 4.9 $ 41 ,000 HA, All Respiratory 460
– 519 65 99 $ 3 1,000 6.1 $ 36 ,000

* All estimates rounded to two significant digits. Unrounded estimates in 2000$ are available in Appendix J of the BenMAP user manual ( Abt Associates, 2012 ).

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Page 71 of 423 To value asthma emergency department visits, we used a simple average of two estimates from the health economics literature. The first estimate comes from Smith et al. (1997), who reported approximately 1.2 million asthma

- related emergency department visit s in 1987, at a total cost of $186 million (1987$). The average cost per visit that year was $155; in 2010$ , that cost was $4 64 (using the CPI

- U for medical care to adjust to 2010$ ). The second estimate comes from Stanford et al. (1999), who reported the cost of an average asthma

- related emergency department visit at $335, based on 1996

– 1997 data. A simple average of the two estimates yields a unit value of $3 8 8. 5.6.7 Minor Restricted Activity Days Valuation No studies are reported to have estimated WTP to avoi d a minor restricted activity day. However, Neumann et al. (1994) derived an estimate of willingness to pay to avoid a minor respiratory restricted activity day, using estimates from Tolley et al. (1986) of WTP for avoiding a combination of coughing, throa t congestion and sinusitis. This estimate of WTP to avoid a minor respiratory restricted activity day is $38 (1990$), or about $6 8 ( 2010$ ). Although Ostro and Rothschild (1989) statistically linked ozone and minor restricted activity days, it is likely tha t most MRADs associated with ozone and PM 2.5 exposure are, in fact, minor respiratory restricted activity days. For the purpose of valuing this health endpoint, we used the estimate of mean WTP to avoid a minor respiratory restricted activity day. 5.6.8 Growth i n WTP Reflecting National Income Growth Over Time Our analysis accounts for expected growth in real income over time. This is a distinct concept from inflation and currency year. Economic theory argues that WTP for most goods (such as environmental protect ion) will increase if real incomes increase. There is substantial empirical evidence that the income elasticity 19 of WTP for health risk reductions is positive, although there is uncertainty about its exact value. Thus, as real income increases, the WTP for environmental improvements also increases. Although many analyses assume that the income elasticity of WTP is unit elastic (i.e., a 10% higher real income level implies a 10% higher WTP to reduce risk changes), empirical evidence suggests that income elas ticity is substantially less than one and thus

19 Income elasticity is a common economic measure equal to the percentage change in WTP for a 1% change in income.

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Page 72 of 423 relatively inelastic. As real income rises, the WTP value also rises but at a slower rate than real income. The effects of real income changes on WTP estimates can influence benefits estimates in two different ways: through real (national average) income growth between the year a WTP study was conducted and the year for which benefits are estimated, and through differences in income between study populations and the affected populations at a particular time. Th e SAB

- EEAC advised the EPA to adjust WTP for increases in real income over time but not to adjust WTP to account for cross

sectional income differences “ because of the sensitivity of making such distinctions, and because of insufficient evidence available at present ” (U.S. EPA

- SAB, 2000). An advisory by another committee associated with the SAB, the Advisory Council on Clean Air Compliance Analysis (SAB

- Council ) , has provided conflicting advice. While agreeing with

“ the general principle that the willingnes s to pay to reduce mortality risks is likely to increase with growth in real income ” and that “ [t]he same increase should be assumed for the WTP for serious nonfatal health effects, ” they note that “ given the limitations and uncertainties in the available empirical evidence, the Council does not support the use of the proposed adjustments for aggregate income growth as part of the primary analysis ” (U.S. EPA

- SAB, 2004b). Until these conflicting advisories have been reconciled, the EPA will continue to adjus t valuation estimates to reflect income growth using the methods described below, while providing sensitivity analyses for alternative income growth adjustment factors. Based on a review of the available income elasticity literature, we adjusted the valuat ion of human health benefits upward to account for projected growth in real U.S. income. Faced with a dearth of estimates of income elasticities derived from time

- series studies, we applied estimates derived from cross

- sectional studies in our analysis. Details of the procedure can be found in Kleckner and Neumann (1999). We note that the literature has evolved since the publication of this memo and that an array of newer studies identifying potentially suitable income elasticity estimates are available ( IE c , 2012). The EPA anticipates seeking an SAB review of these studies, and its approach to adjusting WTP estimates to account for changes in personal income, in 2013. As such, these newer studies have not yet been incorporated into the benefits analysis. An

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Page 73 of 423 abbreviated description of the procedure we used to account for WTP for real income growth between 1990 and 2020 is presented below. Reported income elasticities suggest that the severity of a health effect is a primary determinant of the strength of the relationship between changes in real income and WTP. As such, we use different elasticity estimates to adjust the WTP for minor health effects, severe and chronic health effects, and premature mortality. Note that because of the variety of empirical so urces used in deriving the income elasticities, there may appear to be inconsistencies in the magnitudes of the income elasticities relative to the severity of the effects ( a priori one might expect that more severe outcomes would show less income elastici ty of WTP). We have not imposed any additional restrictions on the empirical estimates of income elasticity. One explanation for the seeming inconsistency is the difference in timing of conditions. WTP for minor illnesses is often expressed as a short term payment to avoid a single episode. WTP for major illnesses and mortality risk reductions are based on longer term measures of payment (such as wages or annual income). Economic theory suggests that relationships become more elastic as the length of time g rows, reflecting the ability to adjust spending over a longer time period. Based on this theory, it would be expected that WTP for reducing long term risks would be more elastic than WTP for reducing short term risks. The relative magnitude of the income e lasticity of WTP for visibility compared with those for health effects suggests that visibility is not as much of a necessity as health, thus, WTP is more elastic with respect to income. The elasticity values used to adjust estimates of benefits in 2020 ar e presented in Table 5

- 1 4
. 20 Table 5
- 1 4 . Elasticity Values Used to Account for Projected Real Income Growth a

Benefit Category Central Elasticity Estimate Minor Health Effect 0.14 Severe and Chronic Health Effects 0.45 Premature Mortality 0.40

a Derivation of estimates can be found in Kleckner and Neumann (1999). COI estimates are not adjusted for income growth

.

20 We expect that the WTP for improved visibility in Class 1 areas would also increase with growth in real income (see Chapter 6)

.

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Page 74 of 423 In addition to elasticity estimates, projections of real gross domestic product (GDP) and populations from 1990 to 2020 are needed to adj ust benefits to reflect real per capita income growth. For consistency with the emissions and benefits modeling, we used national population estimates for the years 1990 to 1999 based on U.S. Census Bureau estimates (Hollman, Mulder, and Kallan, 2000). The se population estimates are based on application of a cohort

- component model applied to 1990 U.S. Census data projections (U.S. Bureau of Census, 2000). For the years between 2000 and 2020 , we applied growth rates based on the U.S. Census Bureau projection s to the U.S. Census estimate of national population in 2000. We used projections of real GDP provided in Kleckner and Neumann (1999) for the years 1990 to 2010. 21 We used projections of real GDP (in chained 1996 dollars) provided by Standard and Poor ’ s (20 00) for the years 2010 to 2020

. 22 Using the method outlined in Kleckner and Neumann (1999) and the population and income data described above, we calculated WTP adjustment factors for each of the elasticity estimates listed in Table 5

- 1 5
. Benefits for each of the categories (minor health effects, severe and chronic health effects, premature mortality, and visibility) are adjusted by multiplying the unadjusted benefits by the appropriate adjustment factor. For premature mortality, we applied the income adjust ment factor specific to the analysis year, but we do not adjust for income growth over the 20

- year cessation lag. Our approach could underestimate the benefits for the later years of the lag. There is some uncertainty regarding the total costs of illness in the future. Specifically, the nature of medical treatment is changing, including a shift towards more outpatient treatment. Although we adjust the COI estimates for inflation, we do not have data to project COI estimates for the cost of treatment in the future or income growth over time, which leads to an inherent though unavoidable inconsistency between COI

- and WTP

- based estimates This approach may underpredict benefits in

21 U.S. Bureau of Economic Analysis, Table 2A

— Real Gross Domestic Product (1997) and U.S. Bureau of Economic Analysis, The Economic and Budget Outlook: An Update , Table 4

— Economic Projections for Calendar Years 1997 Through 2007 (1997) . Note that projections for 2007 to 2010 are based on average GDP growth rates between 1999 and 2007. 22 In previous analyses, we used the Standard and Poor ’ s projections of GDP directly. This led to an apparent discontinuity in the adjustment factors between 2010 and 2011. We refined the method by applying the relative growth rates for GDP derived from the Standard and Poor ’ s projections to the 2010 projected GDP based on the Bu reau of Economic Analysis projections.

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Page 75 of 423 future years because it is likely that increases in real U.S. income would also result in increased COI (due, for example, to increases in wages paid to medical workers) and increased cost of work loss days and lost worker productivity (reflecting that if worker incomes are higher, the losses resulting from reduced worker production w ould also be higher). In addition, cost

- of

- illness estimates do not include sequelae costs or pain and suffering, the value of which would likely increase in the future. To the extent that costs would be expected to increase over time, this increase may be partially offset by advancement in medical technology that improves the effectiveness of treatment at lower costs. For these reasons, we believe that the cost

- of

- illness estimates in this RIA may underestimate ( on net ) the total economic value of avoided health impacts. Table 5
- 1 5 . Adjustment Factors Used to Account for Projected Real Income Growth a Benefit Category 2020 Minor Health Effect 1.07 Severe and Chronic Health Effects 1.22 Premature Mortality 1.20

a Based on elasticity values reported in Table 5

- 3, U.S. Census population projections, and projections of real GDP per capita. 5.7 Benefits Results 5.7.1 Benefits of the Revised and Alternative Annual Primary PM 2.5 Standard

s Applying the impact and valuation functions described previously in this chapter to the estimated changes in PM 2.5 yields estimates of the changes in physical damages (e.g., premature mortalities, cases of acute bronchitis and hospital admissions) and the associated monetary values for those changes. Not all known PM health effects could be quantified or monetized. The monetized value of these unquantified effects is represented by adding an unknown “ B ” to the aggregate total. The estimate of total monetized health benefits is thus equal to the subset of monetized PM

- related health b enefits plus B, the sum of the non

- monetized health benefits and welfare co - benefits; this B represents both uncertainty and a bias in this analysis, as it reflects those benefits categories that we are unable to monetize in this analysis. Table 5

- 16 shows the population

- weighted air quality change for the alternative standards averaged across the continental U.S. Tables 5

- 17 through 5

- 2 2 present the

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Page 76 of 423 benefits results for the annual PM 2.5 standards. These benefits are relative to a 2020 analytical baseline reflecting attainment nationwide of the current primary PM 2.5 standards (i.e., 15/35) that includes promulgated national regulations and illustrative emission controls to simulate attainment with 15/35 as well as a n adjustment to NO x emission s to reflect e xpected reductions in mobile NO x emissions between 2020 and 2025. 23 Figure 5

- 3 graphicall y display s the total monetized benefits of the revised annual primary standard of 12 μg/m 3 , using alternative concentration

- response functions at discount rates of 3% and 7%. Figure 5

- 4 graphically displays the cumulative distribution of total monetized benefits using the 2 epidemiology

- derived and the 12 expert

- derived relationships between PM 2.5 and mortality f or the revised standard , which provides the full range of uncertainty within and across the expert

- derived relationships

. Table 5
- 16 . Population
- Weighted Air Quality Change for the Revised and Alternative

Annual Primary PM 2.5 Standards Relative to Analytical Baseline
Standard Population
- Weighted Air Quality Change 13 μg/m 3 0. 014 μg/m 3 12 μg/m 3 0. 04 3 μg/m 3 11 μg/m 3 0. 207 μg/m 3

23 The estimates in this chapter reflect incremental emissions reductions from an analytical baseline that gives “an adjustment” to the San Joaquin and South Coast areas in California for NOx emissions reductions expec ted to occur between 2020 and 2025, when those areas are expected to demonstrate attainment with the revised standards. Full benefits of the revised standards in those two areas will not be realized until 2025.

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Page 77 of 423 Table 5
- 1 7 . Emission Reductions in Illustrative Emission Reduction Strategies for the

Revised and Alternative Annual Primary PM 2.5 Standard s , by Pollutant and Region in 2020 (tons) a

13 μg/m 3 12 μg/m 3 11 μg/m 3 Directly emitted PM 2.5 East 0 0 8, 200 West 0 0 160 CA 730 4,000 10, 600 SO 2 East 0 0 21,000 West 0 0 43 CA 0 0 0 NOx East 0 0 9 West 0 0 0 CA 0 0 0

a See Chapter 4 for more information on the illustrative emission reduction strategies. The emissions in this table reflect both known and unknown controls.

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Page 78 of 423 Table 5
- 1 8 . Estimated number of Avoided PM 2.5 Health Impacts for the Revised and

Alternative Annual Primary PM 2.5 Standards (Incremental to the Analytical Baseline ) a

Health Effect Revised and Alterative Annual Standards (95 th percentile confidence interval) 13 μg/m 3 12 μg/m 3 11 μg/m 3 Avoided Mortality Krewski et al. (2009) (adult mortality age 30+) 140 460 1,500 (100

-- 190) (320

-- 590) (1,000

-- 1,900) Laden et al. (2006) (adult mortality age 25+) 330 1,000 3,300 (180

-- 480) (560

-- 1,500) (1,800

-- 4,800) Woodruff et al. (1997) (infant mortality) 0 1 4 (0

-- 1) (1

-- 2) (2

-- 6) Avoided Morbidity Non

- fatal heart attacks Peters et al. (2001) (age >18) 160 480 1,600 (49

-- 260) (150

-- 800) (480

-- 2,600) Pooled estimate of 4 studies (age >18) 17 52 170 (8

-- 41) (24

-- 130) (78

-- 410) Hospital admissions

— respiratory (all ages) b 31 110 380 (

- 9

-- 58) (

- 30

-- 200) (

- 100

-- 720) Hospital admissions

— cardiovascular (age > 18) 43 140 480 (20

-- 76) (66

-- 240) (230

-- 0,840) Emergency department visits for asthma (age < 18) b 67 230 810 (

- 22

-- 140) (

- 74

-- 470) (

- 260

-- 1,600) Acute bronchitis (ages 8

– 12) b 280 870 2,700 (

- 36

-- 580) (

- 110

-- 1,800) (

- 350

-- 5,500) Lower respiratory symptoms (ages 7

– 14) 3,500 11,000 34,000 (1500

-- 5500) (4,900

-- 17,000) (15,000

-- 53,000) Upper respiratory symptoms (asthmatics ages 9

– 11) 5,100 16,000 49,000 (1300

-- 8900) (4,100

-- 28,000) (12,000

-- 86,000) Asthma exacerbation (asthmatics ages 6

– 18) 13,000 40,000 120,000 (270

-- 81000) (850

-- 250,000) (2,600

-- 770,000) Lost work days (ages 18

– 65) 22,000 71,000 230,000 (19000

-- 25000) (61,000

-- 81,000) (190,000

-- 260,000) Minor restricted

- activity days (ages 18

– 65) 130,000 420,000 1,300,000 (110,000

-- 150,000) (350,000

-- 490,000) (1,100,000

-- 1,600,000)
a All incidence estimates are rounded to whole numbers with a maximum of two significant digits. These estimates reflect incremental emissions reductions from an analytical baseline that gives “an adjustment” to the San Joaquin and South Coast areas in California for NOx emissions reductions expected to occur between 2020 and 2025, when those areas ar e expected to demonstrate attainment with the revised standards. Full benefits of the revised standards in those two areas will not be realized until 2025. Additional health endpoints , such as cardiovascular emergency department visits, are only

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Page 79 of 423 quantified in a sensitivity analysis in Table 5.A

- 6 because we do not yet have a valuation estimate for this endpoint. b The negative estimates at the 5 th percentile confidence estimates for these morbidity endpoints reflect the statistical power of the study used to calculate these health impacts. These results do not suggest that reducing air pollution results in additional health impacts.

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Page 80 of 423 Table 5
- 1 9 . Monetized PM 2.5 Health Benefits for the Revised and Alternative Annual

Primary PM 2.5 Standards (Incremental to Ana lytical Baseline ) (Millions of 2006$, 3% discount rate ) a

Health Effect Revised and Annual Standards (95 th percentile confidence interval) 13 μg/m 3 12 μg/m 3 11 μg/m 3 Avoided Mortality b Krewski et al. (2009) (adult mortality age 30+) $1,300 $4,000 $13,000 ($120

-- $3,500) ($370

-- $11,000) ($1,200

-- $35,000) Laden et al. (2006) (adult mortality age 25+) $2,900 $9,000 $29,000 ($250

-- $8,100) ($800

-- $26,000) ($2,600

-- $82,000) Woodruff et al. (1997) (infant mortality) $3.4 $11 $35 ($0.29

-- $10) ($0.91

-- $32) ($3.0

-- $100) Avoided Morbidity Non

- fatal heart attacks Peters et al. (2001) (age >18) $18 $55 $180 ($3.0

-- $46) ($9.1

-- $140) ($31

-- $460) Pooled estimate of 4 studies (age >18) $2.0 $6.0 $20.0 ($0.43

-- $6.8) ($1.3

-- $21) ($4.4

-- $68) Hospital admissions

— respiratory (all ages) c $0.86 $3.0 $11 (

- $0.22

-- $1.6) (

- $0.8

-- $5.5) (

- $2.7

-- $20) Hospital admissions

— cardiovascular (age > 18) $1.70 $5.3 $18 ($0.85

-- $2.8) ($2.7

-- $9.2) ($10

-- $32) Emergency department visits for asthma (age < 18) $0.03 $0.10 $0.34 (

- $0.0052

-- $0.061) (

- $0.018

-- $0.21) (

- $0.063

-- $0.73) Acute bronchitis (ages 8

– 12) c $0.13 $0.42 $1.30 (

- $0.0060

-- $0.37) (

- $0.019

-- $1.2) (

- $0.059

-- $3.5) Lower respiratory symptoms (ages 7

– 14) $0.08 $0.24 $0.71 ($0.025

-- $0.10) ($0.078

-- $0.47) ($0.24

-- $1.4) Upper respiratory symptoms (asthmatics ages 9

– 11) $0.17 $0.54 $1.6 ($0.038

-- $0.42) ($0.12

-- $1.30) ($0.36

-- $4.0) Asthma exacerbation (asthmatics ages 6

– 18) $0.7 $2.30 $7.0 ($0.027

-- $5.2) ($0.085

-- $16) ($0.26

-- $49) Lost work days (ages 18

– 65) $3.3 $11 $35 ($2.90

-- $3.70) ($9.4

-- $12) ($30

-- $39) Minor restricted

- activity days (ages 18

– 65) $8.8 $29 $91 ($4.70

-- $13) ($15

-- $43) ($48

-- $140)

a All estimates are rounded to two significant digits. Estimates do not include unquantified health benefits noted in Table 5

- 2 or Section 5.6.5 or welfare co

- benefits noted in Chapter 6. These estimates reflect incremental emissions reductions from an analy tical baseline that gives “an adjustment” to the San Joaquin and South Coast areas in California for NOx emissions reductions expected to occur between 2020 and 2025, when those areas are expected to demonstrate attainment with the revised standards. Full benefits of the revised standards in those two areas will not be realized until 2025. b The reduction in premature fatalities each year accounts for over 98% of total monetized benefits in this analysis. Mortality risk valuation assumes discounting over the SAB

- recommended 20

- year segmented lag structure.

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Page 81 of 423 c The negative estimates at the 5 th percentile confidence estimates for this morbidity endpoint reflects the statistical power of the study used to calculate these health impacts. These results do not su ggest that reducing air pollution results in additional health impacts.

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Page 82 of 423 Table 5
- 20 . Monetized PM 2.5 Health Benefits for the Revised and Alternative Annual

Primary PM 2.5 Standards (Incremental to Analytical Baseline ) (Millions of 2006$, 7% discount rate ) a

Health Effect Revised and Alterative Annual Standards (95 th percentile confidence interval) 13 μg/m 3 12 μg/m 3 11 μg/m 3 Avoided Mortality b Krewski et al. (2009) (adult mortality age 30+) $1,100 $3,600 $11,000 ($110

-- $3,100) ($330

-- $9,800) ($1,100

-- $31,000) Laden et al. (2006) (adult mortality age 25+) $2,600 $8,100 $26,000 ($230

-- $7,300) ($720

-- $23,000) ($2,300

-- $74,000) Woodruff et al. (1997) (infant mortality) $3.4 $11 $35 ($0.29

-- $100) ($0.91

-- $32) ($3.0

-- $100) Avoided Morbidity Non

- fatal heart attacks Peters et al. (2001) (age >18) $18 $54 $180 ($2.8

-- $46) ($8.4

-- $140) ($28

-- $450) Pooled estimate of 4 studies (age >18) $1.9 $5.9 $20 ($0.40

-- $6.7) ($1.2

-- $20) ($4.1

-- $67) Hospital admissions

— respiratory (all ages) c $0.86 $3.0 $11 (

- $0.22

-- $1.6) (

- $0.8

-- $5.5) (

- $2.7

-- $20) Hospital admissions

— cardiovascular (age > 18) $1.70 $5.3 $18 ($0.85

-- $2.8) ($2.7

-- $9.2) ($10

-- $32) Emergency department visits for asthma (age < 18) $0.03 $0.10 $0.34 (

- $0.0052

-- $0.061) (

- $0.018

-- $0.21) (

- $0.063

-- $0.73) Acute bronchitis (ages 8

– 12) c $0.13 $0.42 $1.3 (

- $0.0060

-- $0.37) (

- $0.019

-- $1.2) (

- $0.059

-- $3.5) Lower respiratory symptoms (ages 7

– 14) $0.08 $0.24 $0.71 ($0.025

-- $0.10) ($0.078

-- $0.47) ($0.24

-- $1.4) Upper respiratory symptoms (asthmatics ages 9

– 11) $0.17 $0.54 $1.6 ($0.038

-- $0.42) ($0.12

-- $1.30) ($0.36

-- $4.0) Asthma exacerbation (asthmatics ages 6

– 18) $0.7 $2.30 $7.0 ($0.027

-- $5.2) ($0.085

-- $16) ($0.26

-- $49) Lost work days (ages 18

– 65) $3.3 $11 $35 ($2.90

-- $3.70) ($9.4

-- $12) ($30

-- $39) Minor restricted

- activity days (ages 18

– 65) $8.8 $29 $91 ($4.70

-- $13) ($15

-- $43) ($48

-- $140)

a All estimates are rounded to two significant digits. Estimates do not include unquantified health benefits noted in Table 5

- 2 or Section 5.6.5 or welfare co

- benefits noted in Chapter 6. These estimates reflect incremental emissions reductions from an analy tical baseline that gives “an adjustment” to the San Joaquin and South Coast areas in California for NOx emissions reductions expected to occur between 2020 and 2025, when those areas are expected to demonstrate attainment with the revised standards. Full benefits of the revised standards in those two areas will not be realized until 2025. b The reduction in premature fatalities each year accounts for over 98% of total monetized benefits in this analysis. Mortality risk valuation assumes discounting over th e SAB

- recommended 20

- year segmented lag structure.

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Page 83 of 423 c The negative estimates at the 5 th percentile confidence estimates for this morbidity endpoint reflects the statistical power of the study used to calculate these health impacts. These results do not sugg est that reducing air pollution results in additional health impacts. Table 5 - 2 1 . Total Estimated Monetized Benefits of the for Revised and Alternative

Annual Primary PM 2.5 Standards (Incremental to the Analytical Baseline ) ( b illions of 2006$) a ,b

Benefits Estimate 13 μg/m 3 12 μg/m 3 11 μg/m Economic value of avoided PM 2.5 - related morbidities and premature deaths using PM 2.5 mortality estimate from Krewski et al. (2009) 3% discount rate $ 1.3 + B $ 4.0 +B $ 13 + B 7% discount rate $ 1.2 + B $ 3. 6 +B $ 12 + B Economic value of avoided PM 2.5 - related morbidities and premature deaths using PM 2.5 mortality estimate from Lepeule et al. (20 12 ) 3% discount rate $ 2.9 + B $ 9.1 +B $ 29 + B 7% discount rate $ 2.6 + B $ 8. 2 +B $ 26 + B

a Rounded to two significant figures. The reduction in premature fatalities each year accounts for over 98% of total monetized benefits in this analysis. Mortality risk valuation assumes discounting over the SAB

- recommended 20

- year segmented lag structure. N ot all possible benefits are quantified and monetized in this analysis. B is the sum of all unquantified health and welfare co

- benefits . Data limitations prevented us from quantifying these endpoints, and as such, these benefits are inherently more uncerta in than those benefits that we were able to quantify. b These estimates reflect incremental emissions reductions from an analytical baseline that gives “an adjustment” to the San Joaquin and South Coast areas in California for NOx emissions reductions expected to occur between 2020 and 2025, when those areas are expected to demonstrate attainment with the revised standards. Full benefits of the revised standards in those two areas will not be realized until 2025. Table 5
- 2 2 . Regional Breakdown of Moneti zed Benefits Results

Region Revised and Alterative Annual Standards

13 μg/m 3 12 μg/m 3 11 μg/m 3 East a 0% 0% 23 % California b 100 % 100 % 77 % Rest of West 0% 0% <1%

a Includes Texas and those states to the north and east. Several recent rules such as MATS and CSAPR will have substantially reduced PM 2.5 levels by 2020 in the East, thus few additional control s would be needed to reach 12 μg/m 3

.

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Page 84 of 423 b For 12 and 13 μg/m 3 , all of the benefits occur in California because this highly populated area is where the most air quality improvement beyond the analytical baseline is needed to reach these levels. These estimates reflect incremental emissions reductions from an analytical baseline t hat gives “an adjustment” to the San Joaquin and South Coast areas in California for NOx emissions reductions expected to occur between 2020 and 2025, when those areas are expected to demonstrate attainment with the revised standards. Full benefits of the revised standards in those two areas will not be realized until 2025.

Figure 5 - 3. Estimated PM 2.5 - Related Premature Mortalities Avoided According to Epidemiology or Expert
- Derived PM 2.5 Mortality Risk Estimate for 12 μg/m 3 in 2020 a

a These estimates reflect incremental emissions reductions from an analytical baseline that gives “an adjustment” to the San Joaquin and South Coast areas in California for NOx emissions reductions expected to occur between 2020 and 2025, when those areas a re expected to demonstrate attainment with the revised standards. Full benefits of the revised standards in those two areas will not be realized until 2025.

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Page 85 of 423 Figure 5 - 4. Total Monetized Benefits Using 2 Epidemiology
- Derived and 12
- Expert Derived Relations hips Between PM 2.5 and Premature Mortality for 12 μg/m 3 in 2020 a

a These estimates reflect incremental emissions reductions from an analytical baseline that gives “an adjustment” to the San Joaquin and South Coast areas in California for NOx emissions reductions expected to occur between 2020 and 2025, when those areas are expected to demonstrate attainment with the revised standards. Full benefits of the revised standards in those two areas will not be realized until 2025. 5.7.2 Uncertainty in Benefits Resul ts Mortality benefits account for 98% of total monetized benefits, in part because we are unable to quantify most of the non

- health benefits. The next largest benefit is for reductions in chronic illness (nonfatal heart attacks), although this value is mor e than an order of magnitude lower than for premature mortality. Hospital admissions for respiratory and cardiovascular causes, MRADs and work loss days account for the majority of the remaining benefits. The remaining categories each account for a small p ercentage of total benefit; however, they represent a large number of avoided incidences affecting many individuals. A comparison of the incidence table to the

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Page 86 of 423 monetary benefits table reveals that there is not always a close correspondence between the numb er of incidences avoided for a given endpoint and the monetary value associated with that endpoint. For example, we estimate almost 1 , 00 0 times more work loss days would be avoided than premature mortalities, yet work loss days account for only a very smal l fraction of total monetized benefits. This reflects the fact that many of the less severe health effects, while more common, are valued at a lower level than the more severe health effects. Also, some effects, such as hospital admissions, are valued usin g a proxy measure of WTP. As such, the true value of these effects may be higher than that reported in the tables above.
PM 2.5 mortality benefits represent a substantial proportion of total monetized benefits (over 98% in this analysis), and these estimate s have the following key assumptions and uncertainties.

1. We assume that all fine particles, regardless of their chemical composition, are equally potent in causing premature mortality. This is an important assumption, because PM 2.5 produced varies considera bly in composition across sources, but the scientific evidence is not yet sufficient to allow differential effects estimates by particle type. The PM ISA, which was twice reviewed by SAB

- CASAC, concluded that “many constituents of PM 2.5 can be linked with multiple health effects, and the evidence is not yet sufficient to allow differentiation of those constituents or sources that are more closely related to specific outcomes” (U.S. EPA, 2009b). 2. We assume that the health impact function for fine particles is log

- linear without a threshold in this analysis. Thus, the estimates include health benefits from reducing fine particles in areas with varied concentrations of PM 2.5 , including both areas that do not meet the fine particle standard and those areas that a re in attainment, down to the lowest modeled concentrations. 3. We assume that there is a “cessation” lag between the change in PM exposures and the total realization of changes in mortality effects. Specifically, we assume that some of the incidences of prem ature mortality related to PM 2.5 exposures occur in a distributed fashion over the 20 years following exposure based on the advice of the SAB

- HES (U.S. EPA

- SAB, 2004c), which affects the valuation of mortality benefits at different discount rates.

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Page 87 of 423 Given t hat reductions in premature mortality dominate the size of the overall monetized benefits, more focus on uncertainty in mortality

- related benefits gives us greater confidence in our uncertainty characterization surrounding total benefits. 5.7.3 Estimated Life Ye ars Gained and Reduction in the Percentage of Deaths Attributable to PM 2.5 In their 2008 review of the EPA ’ s approach to estimating ozone

- related mortality benefits, NRC indicated, “ EPA should consider placing greater emphasis on reporting decreases in age

- specific death rates in the relevant population and develop models for consistent calculation of changes in life expectancy and changes in number of deaths at all ages ” (NRC, 2008). In addition, NRC noted in an earlier report that “ [f]rom a public

health perspective, life

- years lost might be more relevant than annual number of mortality cases ” (NRC, 2002). This advice is consistent with that of the SAB

- HES, which agreed that “ ...the interpretation of mortality risk results is enhanced if estimates of lost li fe

- years can be made ” ( U.S. EPA

- SAB , 2004 a). To address these recommendations, we use simplifying assumptions to estimate the number of life years that might be gained. We also estimate the reduction in the percentage of deaths attributed to PM 2.5 resultin g from the illustrative emission reduction strategies to reach the revised annual primary standard . The EPA included similar estimates of life years gained in a previous assessment of PM 2.5 benefits (U.S. EPA, 2006a, 2011a), the latter of which was peer reviewed by the SAB

- HES (U.S. EPA

- SAB, 2010a). Changes in life years and changes in life expectancy at birth are frequently conflated, thus it is important to distinguish these two very diffe rent metrics at the outset. Life expectancy varies by age. CDC defines life expectancy as the “ average number of years of life remaining for persons who have attained a given age ” (CDC, 2011). In other words, changes in life expectancy refer to an average change for the entire population, and refer to the future. Over the past 50 years, average life expectancy at birth in the U.S. has increased by 8.4 years (CDC, 2001). For example, life expectancy at birth was estimated in 2007 to be 77.9 years for an aver age person born in the U.S., but for people surviving to age 60, estimated life expectancy is 82.5 years (i.e., 4.6 years more than life expectancy at birth) (CDC, 2011). Life years, on the other hand, measure the amount of time that an individual loses if they die before the age of their life expectancy. Life years refer to individuals, and refer to the past, e.g., when the

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Page 88 of 423 individual has already died. If a 60

- year old individual dies, we estimate that this individual would lose about 22.5 years of life (i .e., the average population life expectancy for an individual of this age minus this person ’ s age at death). 5.7.3.1 Estimated Life Years Gained For estimating the potential life years gained by reducing exposure to PM 2.5 in the U.S. adult population, we u se the same general approach as Hubbell (2006) and Fann et al. (2012a). We have not estimated the change in average life expectancy at birth in this RIA. Hubbell (2006) estimated that reducing exposure to PM 2.5 from air pollution regulations may result in an average gain of 15 years of life for those adults prematurely dying from PM 2.5 exposure. In contrast, Pope et al. (2009) estimated changes in average life expectancy at birth over a twenty year period, suggesting that reducing exposure to air pollution may increase average life expectancy at birth by approximately 7 months, which was 15% of the overall increase in life expectancy at birth from 1980 through 2000. These results are not necessarily inconsistent because they are reporting different metrics. Because life expectancy is an average of the entire population (including both those whose deaths would likely be attributed to PM exposure as well as those whose deaths would not), average life expectancy changes associated with PM exposure would be expec ted to always be significantly smaller than the average number of life years lost by an individual who is projected to die prematurely from PM exposure. To estimate the potential distribution of life years gained for population subgroups defined by the age range at which their reduction in PM 2.5 exposure is modeled to occur we use standard life tables available from the CDC (2003) and the following formula: (5

. 2) where LE i is the average remaining life expectancy for age interval i, M i is the estimated change in number of deaths in age interval i, and n is the number of age intervals. To get M i (the estimate the number of avoided premature deaths attributed to changes in PM 2.5 exposure in 2020), we use a health impact function that incorporates risk coefficients estimated for the adult population in the U.S. and age

- specific mortality

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Page 89 of 423 rates. That is, we use risk coefficients that do not vary by age, but use baseline mortal ity rates that do. Because mortality rates for younger populations are much lower than mortality rates for older populations, most but not all, of the avoided deaths tend to be in older populations. Table 5

- 2 3 summarizes the modeled number of life years ga ined by reducing PM 2.5 exposure to 12 μg/m 3 in 2020. We then calculated the average number of life years gained per avoided premature mort ality. Figure 5

- 5 shows the potential life years gained as a result of meeting a primary standard of 12 μg/m 3 in 2020, partitioned by the age when exposure reduction occurred, not necessarily age at death. By comparing the projected age distribution of the avoided premature deaths with the age distribution of life years gained, we observed that about half of the deaths o ccur in populations age 75

– 99, but half of the life years would occur in populations younger than 65. This is because the younger populations have the potential to lose more life years per death than older populations based on changes in PM 2.5 exposure in 2020. W e estimate that the average individual who would otherwise have died prematurely from PM exposure would gain 16 additional years of life. However, this approach does not account for whether or not people who are older are more likely to be susceptible to the health effects of PM or whether that susceptibility was in and of itself cause d by PM exposure (for a more complete discussion of this issue, see Kunzli et al., 2001).

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Page 90 of 423 Table 5
- 2 3 . Sum of Life Years Gained by Age Range Attributed to t he Revised Annual

Primary PM 2.5 Standard of 12 μg/m 3 in 2020 a,b

Age Range b Krewski et al. (2009) Risk Coefficient c Lepeule et al. (20 12 ) Risk Coefficient 25
– 29
— 610 30
– 34 210 470 35
– 44 550 1,200 45
– 54 1,000 2,300 55
– 64 1,600 3,500 65
– 74 1,700 3,900 75
– 84 1,300 2,900 85
– 99 560 1,300 Total life years gained 7,000 16,000 Average life years gained per individual 15.0 16.0

a Estimates rounded to two significant figures. b Because we assume that there is a “ cessation ” lag between PM exposures and the reduction in the risk of premature death, there is uncertainty regarding the specific ages that people die relative to the change in exposure.
c The youngest age in the population cohort of this study is 30.

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Page 91 of 423 Figure 5 - 5 . Estimated Life Years Gained as a Result of the Revised Annual Primary PM 2.5 Standard of 12 μg/m 3 in 2020, Partitioned by the Age When Exposure Reduction Occurred, Not Necessarily Age at Death a

a As shown in these charts, slightly more than half of the avoided premature deaths occur in populations age 75
– 99, but slightly more than half of the avoided life years occur in populations age <65 due to the fact that the younger populations would lose more life years per death than older populations. Results would be similar for other standard levels on a percent age basis. Because we assume that there is a
“ cessation ” lag between PM exposures and the reduction in the risk of premature death, there is uncertainty regarding the specific ages that people die relative to the change in exposure. b The youngest age in t he population cohort of this study used to estimate PM 2.5 mortality incidence is 30.

5.7.3.2 Percent of PM

- related Mortality Reduced To estimate the percentage of all

- cause mortality attributed to reduced PM 2.5 exposure in 2020 as a result of the illustra tive emission reduction strategies, we use M i from the equation above, dividing the number of excess deaths estimated for each alternative standard by the total number of deaths in each county. Table 5

- 2 4 shows the reduction in all

- cause mortality attributed to reducing PM 2.5 exposure to the revised annual standard of 12 μg/m 3 in 2020. Figure 5

- 6 shows the percentage of avoided premature deaths attributed to meeting the revised primary annual standard of 1 2 μg/m 3 in 2020, partitioned by the age when exposure reduction occurred, not necessarily age at death. Age 30 - 34 Age 35 - 44
Age 45 - 54

Age 55 - 64 Age 65 - 74 Age 75 - 84 Age

85 - 99 Age 25 - 29 Age 30 - 34
Age 35 - 44
Age 45 - 54

Age 55 - 64 Age 65 - 74 Age 75 - 84 Age 85 - 99

Calculated using Lepeule et al. (2012) risk coefficient Calculated using Krewski et al. (2009) risk coefficient b

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Page 92 of 423 Table 5
- 2 4 . Estimated Reduction in the Percentage of All
- Cause Mortality Attributed

to the Revised Annual Primary PM 2.5 Standard of 12 μg/m 3 in 2020 a,b
Age Range b Krewski et al. (2009) Risk Coefficient c Laden et al. (2006) Risk Coefficient 25
– 29
— 0.80% 30
– 34 0.35% 0.78% 35
– 44 0.32% 0.73% 45
– 54 0.32% 0.73% 55
– 64 0.33% 0.73% 65
– 74 0.33% 0.73% 75
– 84 0.32% 0.73% 85
– 99 0.29% 0.65%

a Rounded to two significant figures. Results would be similar for other standard levels on a percentage basis. These estimates reflect incremental emissions reductions from an analytical baseline that gives “an adjustment” to the San Joaquin and South Coast areas in Calif ornia for NOx emissions reductions expected to occur between 2020 and 2025, when those areas are expected to demonstrate attainment with the revised standards. Full benefits of the revised standards in those two areas will not be realized until 2025. b Bec ause we assume that there is a “ cessation ” lag between PM exposures and the reduction in the risk of premature death, there is uncertainty regarding the specific ages that people die relative to the change in exposure.
c The youngest age in the population cohort of this study is 30. The relative distributions of the potential number of life years gained (Figure 5

- 5) and the estimated avoided mortalities (Figure 5

- 6) would be similar across alternative annual standards. Because reduction in PM exposure is no t associated with an immediate improvement in chronic health conditions, we assume that there is a “cessation” lag between PM exposures and the reduction in the risk of premature death. There is uncertainty regarding the specific ages at which people “avoi d” death relative to the change in exposure. While the structure of the lag is uncertain, some studies suggest that most of the premature deaths are avoided within the first 3 years after the change in exposure, while others are unable to identify conclusi vely a critical window of exposure (U.S. EPA, 2004c; Schwartz, 2008; Krewski et al. 2009). These studies did not examine whether the cessation lag was modified by either age at the time when exposure is reduced or the extent of cumulative lifetime exposure

.

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Page 93 of 423 Figure 5 - 6 . Estimate of Avoided Premature Deaths Attributed to the Revised Annual Primary PM 2.5 Standard of 12 μg/m 3 in 2020 , Partitioned by the Age When Exposure Reduction Occurred, Not Necessarily Age at Death a

a As shown in these charts, slightly more than half of the avoided premature deaths occur in populations age 75

- 99, but slightly more than half of the avoided life years occur in populations age <65 due to the fact that the younger populations would lose mor e life years per death than older populations. Results would be similar for other standard levels on a percentage basis. Because we assume that there is a
“ cessation ” lag between PM exposures and the reduction in the risk of premature death, there is uncer tainty regarding the specific ages that people die relative to the change in exposure. b The youngest age in the population cohort of this study is 30. 5.7.4 Evaluation of Mortality Impacts Relative to Various Concentration Benchmarks In this analysis, we estimate the number of avoided PM 2.5 - related deaths occurring due to PM 2.5 reductions down to various PM 2.5 concentration benchmarks, including the Lowest Measured Level (LML) of each long

- term PM 2.5 mortality study. This analysis is one of several sensiti vities that the EPA has historically performed that characterize the uncertainty associated with the PM

- mortality relationship and the economic value of reducing the risk of premature death (Roman et al., 2008; U.S. EPA, 2006a, 2011a; Mansfield, 2009).
Our review of the current body of scientific literature indicates that a log

- linear no - threshold model provides the best estimate of PM

- related long

- term mortality. The Age 30 - 34 Age 35 - 44 Age 45 - 54

Age 55 - 64

Age 65 - 74 Age 75 - 84 Age 85 - 99 Age 25 - 29 Age

30 - 34 Age 35 - 44 Age 45 - 54 Age 55 - 64

Age 65 - 74 Age 75 - 84 Age 85 - 99

Calculated using Krewski et al. (2009) risk coefficient b Calculated using Lepeule et al. (2012) risk coefficient

.

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Page 94 of 423 PM ISA (U.S. EPA, 2009b), which was twice reviewed by the EPA ’ s Clean Air Scientific Advis ory Committee (U.S. EPA

- SAB, 2009a, 2009b), concluded that the evidence supports the use of a no

- threshold log

- linear model while also recognizing potential uncertainty about the exact shape of the concentration

- response function. 24 Consistent with this fin ding, we estimate benefits associated with the full range of PM 2.5 exposure in conjunction with sensitivity analyses to recognize the potential uncertainty at lower concentrations. Specifically, we incorporated a LML assessment, a method the EPA has employed in several recent RIAs (U.S. EPA, 2010g, 2011c, 2011d). In addition, we have incorporated an assessment using specific concentration benchmarks identified in the EPA ’ s Policy Assessment for Particulate Matter (U.S. EPA, 2011b). These two appr oaches summarize the distribution of avoided PM 2.5 - related mortality impacts relative to baseline (i.e., pre

- rule) annual mean PM 2.5 levels. The LML approach compares the percentage of avoided premature deaths estimated to occur above and below the minimum observed air quality level of each long

- term cohort study we use to quantify PM. In the air quality benchmark approach, we summari ze the impacts occurring at different points in the distribution of the air quality data used in these same epidemiology stud ies.
O ur confidence in the estimated number of premature deaths avoided (but not in the existence of a causal relationship between PM and premature mortality) diminishes as we estimate these impacts in locations where PM 2.5 levels are below the LML. This i nterpretation is consistent with the Policy Assessment (U.S. EPA, 2011b) and advice from SAB

- CASAC during their peer review (U.S. EPA

- SAB, 2010d). As noted in the preamble to the final rule, the Policy Assessment (U.S. EPA, 2011b) concludes that the range from the 25 th to the 10 th percentile is a reasonable range of the air quality distribution below which we start to have appreciably less confidence in the magnitude of the associations observed in the epidemiological studies. In general, we are more confident in the magnitude of the risks we estimate from simulated PM 2.5 concentrations that coincide with the bulk of the observed PM concentrations in the epidemiological studies at are used to estimate the benefits. Likewise, we are less

24 F or a summary of the scientific review stat ements regarding the lack of a threshold in the PM 2.5 - mortality relationship, see the Technical Support Document (TSD) entitled Summary of Expert Opinions on the Existence of a Threshold in the Concentration

- Response Function for PM 2.5 - related Mortality (U.S. EPA, 2010f).

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Page 95 of 423 confident in th e risk we estimate from simulated PM 2.5 concentrations that fall below the bulk of the observed data in these studies. However, there are uncertainties inherent in identifying any particular point at which our confidence in reported associations becomes ap preciably less , and the scientific evidence provides no clear dividing line

. For these reasons, we consider the LML as well as one standard deviation below the mean 25 air quality levels when characterizing the distribution of mortality impacts. It is impor tant to emphasize that “ less confidence ” does not mean “ no confidence .” In addition, while we may have less confidence in the magnitude of the risk, we still have high confidence that PM 2.5 is causally associated with risk at those lower air quality concen trations. To clarify this concept, Figure 5

- 7 graphically displays the spectrum of confidence using illustrative concentration benchmarks from the major epidemiology studies cited in this chapter.

25 A range of one standard deviation around the mean represents approximately 68 percent of normally distributed data, and, below the mean falls between the 25 th and 10 th percentiles.

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Page 96 of 423 Figure 5 - 7 . Relationship between the Size of the PM Mortality Estimates and the PM 2.5 Concentration Observed in the Epidemiology Study Although these types of concentration benchmark analyses (e.g., LML , one standard deviation below the mean , etc. ) provide some insight into the level of uncertainty in the e stimated PM 2.5 mortality benefits, the EPA does not view these concentration benchmarks as a concentration threshold below which we would not quantify health benefits of air quality improvements Rather, the core benefits estimates reported in this RIA (i.e ., those based on Krewski et al. (2009) and Lepeule et al. (2012)) are the best measures because they reflect the full range of modeled air quality concentrations associated with the emission reduction strategies. In reviewing the Policy Assessment , SAB

- CASAC confirmed that “ [a]lthough there is increasing uncertainty at lower levels, there is no evidence of a threshold (i.e., a level below which there is no risk for adverse health effects) ” (U.S. EPA

- SAB, 2010d). In addition, in reviewing the Costs and Be nefits of the Clean Air Act (U.S. EPA, 2011a), the SAB

- HES noted that “ [t]his [no

- threshold] decision is supported by the data, which are quite consistent in showing effects down to the lowest measured levels. Analyses of cohorts using data from more recen t years, during which time PM concentrations have fallen, continue to report strong associations with mortality ” (U.S. EPA

- SAB, 2010a). Therefore,

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Page 97 of 423 the best estimate of benefits includes estimates below and above these concentration benchmarks but uncertain ty is higher in the magnitude of health benefits estimated at lower concentrations, with the lowest confidence below the LML. Estimated health impacts reflecting air quality improvements below and above these concentration benchmarks are appropriately incl uded in the total benefits estimate. In other words, our higher confidence in the estimated benefits above these concentration benchmarks should not imply an absence of confidence in the benefits estimated below these concentration benchmarks.
We estimate that most of the avoided PM

- related impacts we estimate in this analysis occur among populations exposed at or above the LML of the Lepeule et al. (2012) study, while a majority of the impacts occur at or above the LML of the Krewski et al. (2009) study. W e show the estimated reduction in incidence of premature mortality above and below the LML or air quality benchmarks of these studies in Tables 5

- 2 5 , and we graphically display the distribution of PM 2.5 - related mortality impacts for the selected standard i n Figures 5

- 8 and 5

- 9

. When interpreting these LML and air quality benchmarks results, it is important to understand that the avoided PM 2.5 deaths are estimated to occur from PM 2.5 reductions in the baseline air quality simulation, which assumes that 15/3 5 is already met. When simulating attainment with revised and alternative standards, we “roll back” the design value at each monitor exceeding the standard alternative to equal that standard and use an air quality interpolation technique to simulate the ch ange in PM levels surrounding that monitor. This technique tends to simulate the greatest air quality changes nearest the monitor. We estimate benefits using modeled air quality data with 12 km grid cells, which is important because the grid cells are ofte n substantially smaller than counties and PM 2.5 concentrations vary spatially within a county. Therefore, there may be a small number of grid cells with concentrations slightly greater than 15 μg/m 3 in the gridded baseline even though all monitors could me et an annual standard of 15 μg/m 3 . In addition, some grid cells in a county can be below the level of a standard even though the highest monitor value is above that standard. Thus, emission reductions can lead to benefits in grid cells that are below a standard even within a county with a monitor that exceeds that standard. Furthermore , our approach to simulating attainment can lead to benefits in counties that are below alternative

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Page 98 of 423 standard. Emission reduction strategies designed to reduce PM 2.5 concent rations at a given monitor will frequently improve air quality in neighboring counties. In order to make a direct comparison between the benefits and costs of these emission reduction strategies, it is appropriate to include all the benefits occurring as a result of the emission reduction strategies applied regardless of where they occur. Therefore , it is not appropriate to estimate the fraction of benefits that occur only in counties that exceed the alternative standards because it would omit benefits attr ibutable to emission reductions in exceeding counties . Figure 5

- 10 provides an illustration of this concept. Table 5
- 2 5 . Estimated Reduction in Incidence of Adult Premature Mortality Occurring

Above and Below Various Concentration Benchmarks in the Underly ing Epidemiology Studies a

Revised and Alternative Standard Level Epidemiology Study Total Reduced Mortality Incidence Allocation of Reduced Mortality Incidence

Below 1 S td . D ev . B elow AQ M ean At or Above

1 S td . D ev . B elow AQ M ean Below

LML At or Above LML 13 μg/m 3 Krewski et al. (2009) 140 79 66 6 140 (54%) (46%) (4%) (96%) Lepeule et al. (2012) 330 N/A N/A 130 200 (38%) (62%) 12 μg/m 3 Krewski et al. (2009) 460 200 260 14 440 (43%) (57%) (3%) (97%) Lepeule et al. (2012) 1,000 N/A N/A 310 720 (30%) (70%) 11 μg/m 3 Krewski et al. (2009) 1,500 690 770 27 1,400 (47%) (53%) (2%) (98%) Lepeule et al. (2012) 3,300 N/A N/A 1,000 2,300 (31%) (69%)

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Page 9 9 of 423 a Mortality incidence estimates are rounded to whole numbers and two significant digits, so estimates may not sum across columns. One standard deviation below the mean is equivalent to the middle of the range between the 10 th and 25 th percentile. For Krewski , the LML is 5.8 μg/m 3 and one standard deviation below the mean is 11.0 μg/m 3 . For Lepeule et al., the LML is 8 μg/m 3 and we do not have the data for one standard deviation below the mean. I t is important to emphasize that although we have lower levels of confidence in levels below the LML for each study, the scientific evidence does not support the existence of a level below which health effects from exposure to PM 2.5 do not occur.

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Page 100 of 423 While the LML of each study is important to consider when characterizing and interpreting the overall level of PM 2.5 - related benefits, as discussed earlier in this chapter, the EPA believes that both of the cohort

- based mortality estimates are suitable for use in air pollution health impact analyses. When estimating PM

- related premature deaths avoided using risk coefficients drawn from the Lepeule et al. (2012) analysis of the Harvard Six Cities and the Krewski et al. (2009) analysis of the ACS cohorts there are innumerable other attributes that may affect the size of the report ed effect estimates

— including differences in population demographics, the size of the cohort, activity patterns and particle composition among others. The LML assessment presented here provides a limited representation of one key difference between the two studies.

Of total PM 2.5 - Related deaths avoided for 12 μg/m 3 : 97 % occur among populations exposed to PM 2.5 levels at or above the LML of the Krewski et al. (2009) study. 70 % occur among populations exposed to PM 2.5 levels at or above the LML of the Lepeule et al. (2012) study. Figure 5 - 8 . Number of Premature PM 2.5 - related Deaths Avoided for the Revised Annual Primary PM 2.5 Standard of 12 μg/m 3 in 2020 According to the Baseline Level of PM 2.5 and the Lowest Measured Air Quality Levels of Each Mortality Study

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Page 101 of 423 Of total PM 2.5 - Related deaths avoided for 12 μg/m 3 : 97 % occur among populations exposed to PM 2.5 levels at or above the LML of the Krewski et al. (2009) study. 70 % occur among populations exposed to PM 2.5 levels at or above the LML of th e Lepeule et al. (2012) study. Figure 5 - 9 . Number of Premature PM 2.5 - related Deaths Avoided for the Revised Annual Primary PM 2.5 Standard of 12 μg/m 3 in 2020 According to the Baseline Level of PM 2.5 and the Lowest Measured Air Quality Levels of Each Mortality Study

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Page 102 of 423 As this illustration shows, because 12km grid cells are much smaller than counties and because PM 2.5 concentrations vary within a county, there can be modeled grid cells with PM 2.5 concentrations below an standard level even when the c ounty exceeds that level. Because we model benefits using grid cells , this is a key reason why the LML graphs show benefits at levels below the alternative standards. In addition, emission reductions in an exceeding county can have benefits in a neigh boring county that does not exceed. Figure 5 - 10. Illustration of Relative Size of County with Exceeding Monitor and Modeled Grid Cells

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Page 103 of 423 5.7.5 Additional Sensitivity Analys e s The details of these sensitivity analyses are provided in A ppendix 5 .A , and summarized here. The use of an alternate lag structure would change the PM 2.5 - related mortality benefits discounted at 3% discounted by between 10% and

– 27%; when discounted at 7%, these benefits change by between 22% and −52%. When applying higher and low er income growth adjustments, the monetary value of PM 2.5 - related premature mortality changes between 33% and −14%; the value of acute endpoints changes between 8% and −4%. Using the updated population projection data , the rounded estimates of total moneti zed benefits increases by 4. 4 % for 12 μg/m 3 . These sensitivity analysis results would be similar on a percentage basis for the alternative annual standards. 5.8 Discussion Th e analysis in this Chapter demonstrates the potential for significant health benefits of the illustrative emission controls applied to simulate attainment with the revised annual primary PM 2.5 standard. We estimate that by 2020 the emissions reductions to reach the revised annual primary standard would have reduced the number of PM 2.5 - related premature mortalities and produce substantial non

- mortality benefits. This rule promises to yield significant welfare impacts as well (see Chapter 6) , though the quantification of those endpoints is absent in this RIA. Even considering the quantif ied and unquantified uncertainties identified in this chapter, we believe that the implementing the revised annual PM 2.5 standard of 12 μg/m 3 would have substantial public health benefits that outweigh the costs (see Chapter 7)

. Inherent in any complex RIA such as this one are multiple sources of uncertainty. Some of these we characterized through our quantification of statistical error in the concentration response relationships and our use of the expert elicitation

- derived PM 2.5 mortality functions. Others, including the projection of atmospheric conditions and source - level emissions, the projection of baseline morbidity rates, incomes and technological development are unquantified. When evaluated within the context of these uncer tainties, the health impact and monetized benefits estimates in this RIA can provide useful information regarding the public health benefits associated with the revised PM NAAQS.

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Page 104 of 423 There are important differences worth noting in the design and analytical obj ectives of NAAQS RIAs compared to RIAs for implementation rules, such as the recent MATS rule (U.S. EPA, 2011d). The NAAQS RIAs illustrate the potential costs and benefits of a revised air quality standard nationwide based on an array of emission reduction strategies for different sources , incremental to implementation of existing regulations and controls needed to attain the current standards . In short, NAAQS RIAs hypothesize, but do not predict, the emission reduction strategies that States may choose to enact when implementing a revised NAAQS. The setting of a NAAQS does not directly result in costs or benefits, and as such, NAAQS RIAs are merely illustrative and are not intended to be added to the costs and benefits of other regulations that result in sp ecific costs of control and emission reductions. By contrast, the emission reductions from implementation rules are generally for specific, well

- characterized sources, such as the recent MATS rule (U.S. EPA, 2011d). In general, the EPA is more confident in the magnitude and location of the emission reductions for implementation rules. As such, emission reductions achieved under promulgated implementation rules such as MATS have been reflected in the baseline of this NAAQS analysis. S ubsequent implementation rules will be reflected in the baseline for the next PM NAAQS review. For this reason, the benefits estimated provided in this RIA and all other NAAQS RIAs should not be added to the benefits estimated for implementation rules. In setting the NAAQS, the EPA considers that PM 2.5 concentrations vary over space and time. While the standard is designed to limit concentrations at the highest monitor in an area, it is understood that emission controls put in place to meet the standard of the highest monitor wil l simultaneously result in lower PM 2.5 concentrations throughout the entire area. In fact, the Quantitative R isk and E xposure A ssessment for Particulate Matter (U.S. EPA, 2010b) shows how different standard levels would affect the entire distribution of PM 2.5 concentrations, and thus people ’ s exposures and risk, across urban areas. For this reason, it is inappropriate to use the NAAQS level as a bright line for health effects. The NAAQS are not set at levels that eliminate the risk of air pollution completely

. Instead, the Administrator sets the NAAQS at a level requisite to protect public health with an adequate margin of safety, taking into consideration effects on susceptible populations based on the scientific literature

. The risk analysis prepared in

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Page 105 of 423 support of this PM NAAQS reported risks below these levels, while acknowledging that the confidence in those effect estimates is higher at levels closer to the standard (U.S. EPA, 2010 b ). While benefits occurring below the standard may be somewhat more uncertain than those occurring above the standard, the EPA considers these to be legitimate components of the total benefits estimate

. Though there are greater uncertainties at lower PM 2.5 concentrations, there is no evidence of a threshold in PM 2.5 - related health effects in the epidemiology literature. G iven that the epidemiological literature in most cases has not provided estimates based on threshold models, there would be additional uncertainties imposed by assuming thresholds or other non

- linear concentration

- response functions for the purposes of benefits analysis. The estimated benefits for the revised and alternative annual standards are in addition to the substantial benefits estimated for several recent implementation rules (U.S. EPA, 2009a, 2011c, 2011d, 2011e). Rules such as the Mercury and Air Toxics Standard (MATS) and other emission reductions will have substantially reduced ambient PM 2.5 concentrations by 2020 in the East, such that no additional c ontrols would be needed to reach 12 μg/m 3 in the East beyond the analytical baseline

. These rules that have already been promulgated have tremendous combined benefits that explain why the number of avoided premature deaths associated with this NAAQS revisi on are smaller than were estimated in the previous PM NAAQS RIA (U.S. EPA, 2006a) for the year 2020 and even smaller than the mortality risks estimated for the current year in the PM REA (U.S. EPA, 2010b) . In addition, because our analytical baseline exclu des benefits associated with attaining the current annual an d daily standards as well as the mobile NOx emissions anticipated by 2025, including th e benefits associated with those air quality improvements would result in higher benefits than we have estima ted here.
F or the revised annual standard of 12 μg/m 3 , all of the estimated benefits occur in California because this is the only state that needs additional air quality improvement beyond the analytical baseline after accounting for the air quality improvements from recent rules. Because all of the monetized human health benefits are projected to occur in California, we have consider ed the cohort studies conducted in California specifically in addition to the national risk coefficients we use as our core estimates . Although we have not calculated the benefits results using these cohort studies, we provided the risk coefficients from these California cohorts to show how much the monetized benefits

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Page 106 of 423 c ould have changed if we used these cohort s tudies . Mos t of the California cohort studies report central effect estimates similar to the (nation

- wide) all

- cause mortality risk estimate we applied from Krewski et al. (2009) and Lepeule et al. (20 12 ) albeit with wider confidence intervals. Three cohort studies c onducted in California indicate statistically significant higher risks than the risk estimates we applied from Lepeule et al. (2012) , and four studies showed insignificant results. 5.9 References Abbey, David E et al. 1995. “ Chronic Respiratory Symptoms Associ ated with Estimated Long

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- term inhalable particles and other air pollutants related to mortality in nonsmokers. ” American Journal of Respiratory and Critical Care Medicine 159(2):373

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. BenMAP User ’ s Manual Appendices . Prepared for U.S. Environmental Protection Agency Office of Air Quality Planning and Standards. Research Triangle Park, NC. September. Available on the Internet at <http://www.epa.gov/air/benmap/m odels/BenMAPAppendicesOct2012.pdf>. Abt Associates, Inc. 2010. Environmental Benefits and Mapping Program (Version 4.0)

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Page 107 of 423 Agency for Healthcare Research and Quality (AHRQ). 2009. HCUPnet, Healthcare Cost and Utilization Project. Rockville, MD. Available on the Internet at <http://hcupnet.ahrq.gov>. American Lung Associat ion (ALA) . 1999. Chronic Bronchitis . Available on the Internet at <http://www.lungusa.org/diseases/lungchronic.html>. Alberini A, Cropper M, Krupnick A, Simon NB. 2004. “Does the value of a statistical life vary with age and health status? Evidence from the US and Canada.” Journal of Environmental Economics and Management 48(1): 769

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Page 108 of 423 Babin, S. M., H. S. Burkom, et al. 2007. “ Pediatric patient asthma

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E.O . 12866_PM NAAQS_2060 - AO47_FRN_RIA_Executive Summary_20121120 . dox

EXECUTIVE SUMMARY 5.10 ES.1 Overview Based on its review of the air quality criteria and the national ambient air quality standards (NAAQS) for particulate matter (PM), the U.S. Environmental Protection Agency ( EPA ) is making revisions to the primary standards for PM to provide requisite prot ection of public health and welfare. The EPA is revis ing the primary annual (health

based) standard , retaining the primary 24

- hour standard, and retaining the secondary (welfare

- based) NAAQS for fine particles (generally referring to particles less than or equal to 2.5 micrometers [ μm ] in diameter

— PM 2.5 )

. T he EPA is retain ing the current primary and secondary 24

- hour PM 10 standards. As has traditionally been done in NAAQS rulemaking s , the EPA has conducted a Regulatory Impact Analysis (RIA) to provide the public with illustrative estimates of the potential costs and health and welfare benefits of attaining the revised annual standard along with two alternat ive standards. In NAAQS rule making s , the RIA is prepared for

### Summary of Interagency Working Comments on Draft Language under

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Page 127 of 423 informational purposes only, and the decisions related to the setting of the PM NAAQS standards are not in any way based on consideration of the information or analyses in the RIA. The RIA fulfills the requirements of Execu tive Order s 12866 and 13563 and guidelines of the Office of Management and Budget ’ s ( OMB ) Circular A

- 4
. 26 The control strategies presented in this RIA are illustrative and represent one set of control strategies states might choose to implement in order to meet the final standards. As a result, b enefit and cost estimates provided in th is RIA are not additive to benefits and costs f rom other regulations as each regulation is based on a different set of analytical assumptions and policy decisions

. T he costs a nd benefits identified in this RIA will not be realized until specific controls are mandated by future State Implementation Plans ( SIPs ) or other federal regulations

. 5.11 ES.2 Existing and Revised PM Air Quality Standards T wo primary PM 2.5 standards provide public health protection from effects associated with fine particle exposures : the annual standard and the 24

- hour standard

. The current annual standard is set at a level of 15.0 μg/m 3 , based on the 3

- year average of annual arithmetic mean PM 2.5 concentrat ions. The current 24

- hour standard is set at a level of 35 μg/m 3 , based on the 3

- year average of the 98 th percentile of 24

- hour PM 2.5 concentration. In the RIA , the current primary PM 2.5 standard s , including both annual and 24

- hour standard s are denoted as 15/ 35 μg/m 3

. Attainment of the 24

- hour standard is analyzed only in developing the scenario of attainment with the existing standards of 15/35 μg/m 3

. All other scenarios evaluate additional emissions reductions needed to attain alternative annual standards only

. In th is PM NAAQS review, the EPA has revis ed and lowered the level of the primary annual PM 2.5 standard to 12 μ g/m 3 in conjunction with retaining the level of the 24

- hour standard at 35 μg/m 3 and th is standard is denoted as 12 μg/m 3

. In addition to t he revised annual standard of 12 μg/m 3 , the RIA also analyzes the benefits and costs of incremental control strategies for two alternative annual standards of 13 μg/m 3 and 11 μg/m 3

.

26 U.S. Office of Management and Budget. Circular A

- 4, September 17, 2003. Available at http://www.whitehouse.gov/omb/circulars/a004/a

- 4.pdf.

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Page 128 of 423 Currently, t he existing secondary (welfare

- based) PM 2.5 standards are identical in all respects to the primary standards. In this PM NAAQS review , the EPA i s retaining the current suite of secondary standards for 24

- hour and annual PM 2.5 . Thus, while the new primary annual standard will be revised to 12 μg/m 3 , t he secondary annual standard will remain at 15 μ g/m 3

. Non

- visibility welfare effects are addressed by this suite of secondary standards, and PM

- related visibility impairment is addressed by the secondary 24

- hour PM 2.5 standard , which EPA is leaving unchanged at 35 μ g/m 3

. The secondary standards will thus remain at 15/35 μg/m 3

. W ith regard to the primary and secondary standards for particles less than or equal to 10 μm in diameter (PM 10 ), the EPA is retain ing the current primary and secondary 24

- hour PM 10 standards , which are both set at a level of 150 μg/m 3 , not to be exceeded more than once per year on average over 3 years ( U.S. EPA, 1997) 27

. Since the benefit

- cost analysis of the alternative PM 10 standards was conducted when the standard was promulgated in 19 9 7 , this RIA does not repeat that analysis here. 5.11.1 ES.2.1 Establishing A ttainment with the C urrent 15/35 μg/m 3 PM 2.5 S tandards The RIA is intended to evaluate the costs and benefits of reaching attainment with the alternative PM 2.5 standards. In order to develop and evaluate control strategies for attaining a more stringent primary standard, it is important to first estimate PM 2.5 levels in 2020 for attainment with the current NAAQS standards (15/35 μg/m 3 ) and projections of future air quality reflecting on

- the

- books Federal regulations, enforcement actions, state regulations, and population and economic growth. Estimating the 2020 levels after attainment of the current standards is traditionally known as the baseline, or more specifically for this analysis the attainment baseline. Establishing this baseline typically allows us to estimate the incremental costs and bene fits of attaining any alternative primary standard. EPA anticipates attainment with 15/35 μg/m 3 in all but two areas in California, not expected to attain the current standard until 2025. While establishing the attainment of 15/35 μg/m 3 is an important step in getting to the analytical baseline for evaluating costs and benefits of alternative

27 U.S. Environmental Protection Agency. 1997. Regulatory Impact Analyses for the Parti culate Matter and Ozone National Ambient Air Quality Standards and Proposed Regional Haze Rule. Available at: http://www.epa.gov/ttn/oarpg/naaqsfin/ria.html

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Page 129 of 423 an nual PM standards , evaluating the revised and alternative standards in these two areas in 2020 is not appropriate

. The attainment baseline includes reductions already achieved as a result of national regulations and reductions expected prior to 2020 from r ecently promulgated national regulations , referred to as the base case. In addition, the attainment baseline refers to the reductions from additional controls which the EPA estimates are needed to attain the current standard (15/35 μg/m 3 ). Reductions achieved as a result of state and local agency regulations and voluntary programs are reflected to the extent that they are represented in emission inventory information submitted to the U.S. EPA by state and local agencies. Below is a list of some of the major national rules reflected in the base case. Refer to Chapter 3, Section 3.2. 1.4 for a more detailed discussion of the rules reflected in the 2020 base case emissions inventory

.

 Light

- Duty Vehicle Tier 2 Rule (U.S. EPA, 1999)

 Heavy Duty Diesel Rule (U. S. EPA, 2000)

 Clean Air Nonroad Diesel Rule (U.S. EPA, 2004)

 Regional Haze Regulations and Guidelines for Best Available Retrofit Technology Determinations (U.S. EPA, 2005b)

 NO x Emission Standard for New Commercial Aircraft Engines (U.S. EPA, 2005)

 Emissions Standards for Locomotives and Marine Compression

- Ignition Engines (U.S. EPA, 2008)

 Control of Emissions for Nonroad Spark Ignition Engines and Equipment (U.S. EPA, 2008)

 C3 Oceangoing Vessels (U.S. EPA, 2010)

 Hospital/Medical/Infectious Waste Inc inerators: New Source Performance Standards and Emission Guidelines: Final Rule Amendments (U.S. EPA, 2009)

 Reciprocating Internal Combustion Engines (RICE) NESHAPs (U.S. EPA, 2010)

 Mercury and Air Toxics Standards (U.S. EPA, 2011)

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Page 130 of 423  Cross

- State Air Pollutio n Rule (U.S. EPA, 2011) 28 The attainment baseline for this analysis does not assume emissions controls that might be implemented to meet the other NAAQS for O 3 , NO x , or SO 2 . To the extent that some of the estimated emissions reductions needed to meet the re vised annual PM standard are also needed to meet the current standards for O 3 , NO x , or SO 2 , the costs and benefits of meeting the revised PM annual PM standard will be overstated. W e did not conduct this analysis incremental to controls applied as part of previous NAAQS analyses (e.g., O 3 , NO x , or SO 2 ) because the data and modeling on which these previous analyses were based are now considered outdated and are not compatible with the current PM 2.5 NAAQS analysis. In addition, all control strategies analyzed in all NAAQS RIAs are hypothetical. Th e analysis present ed here is just one scenario that states may employ but does not prescribe how attainment must be achieved. 5.11.2 ES.2. 2 Establishing the Analytical Basel ine for Evaluation of Alternative Standards The goa l of this RIA is to provide the best estimates of the costs and benefits of an illustrative attainment strategy to meet the revised annual standard of 12 μg/m 3 , as well as two alternative standards of 13 μg/m 3 and 11 μg/m 3 , incremental to meeting the current standards of 15/35 μg/m 3 , reflecting emissions projected to include the impact of economic growth and implementation of state and federal emissions controls. Most areas of the U.S. will be required to demonstrate attainment with the new standard by 2020. As a result, for these areas, the correct baseline for estimating the incremental emissions reductions that would be needed to attain the more protective standard is a baseline with emissions projected to 2020 and adjusted to reflect the additional emissions reductions that would be needed to attain the current 15/35 μg/m 3 standards. For two areas in Southern California (South Coast and San Joaquin), the degree of projected non

- attainment with the annual 12 μg/m 3 standard is such that those counties are not exp ected to be able to demonstrate attainment of the new standard by 2020. Instead, those two areas are likely to qualify for an extension of their attainment date of up to five year s . If the areas are granted an attainment date extension, they will have unti l 2025 to demonstrate attainment of the revised annual standard of 12 μg/m 3

. As a

28 See Chapter 3, Section 3.2.1.4 for a discussion of the role CSAPR plays in the PM 2.5 RIA and the reasons w e believe CSAPR remains an appropriate proxy for this analysis

.

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Page 131 of 423 result, for these two areas, the correct baseline for estimating the incremental emission reductions needed to attain the more protective standard is a baseline with emissions projected to 2025 adjusted to reflect the additional emissions reductions needed to attain the current 15/35 μg/m 3 standards. This difference in attainment year is important because between 2020 and 2025, emissions from mobile sources in California are ex pected to be reduced due to continued fleet turnover from older, higher emitting vehicles to newer, lower emitting vehicles. These reductions in emissions will occur as a result of previous state rules for which costs and benefits have already been counted , and thus will not be costs and benefits attributable to meeting the revised annual standard of 12 μg/m 3 29

. For the purposes of this analysis, we have constructed a n analytical baseline which reflects attainment of 15/35 μg/m 3 in 2020 for all areas except S outh Coast and San Joaquin. Th is analytical baseline is modified in those two areas to reflect an

“ adjustment ” for the reductions in NOx emissions that those areas are expected to see between 2020 and 2025. These reductions in NOx are not attributable to attainment of the current or revised PM standards, but rather reflect the impacts of other programs. These NOx emissions changes will affect baseline PM concentrations, but will not affect costs or benefits of attaining the revised or alternative standards

. Since the RIA for the proposed rule, the EPA has made a number of technical improvements to its estimate of the analytic baseline, including x, y, and z, which jointly result in xxxxx

..... 5.11.3 ES.2. 3 Emission Reduction Estimates by Alternative Standards (2020) Emission reductions were calculated for the revised annual standard of ( 12 μg/m 3 ) and two alternative annual standards (13 μg/m 3 and 11 μg/m 3 ) from a baseline of attaining the current standard s of 15/35 μg/m 3 for all areas of the U.S. except the South Coast a nd San Joaquin areas of California, where the baseline is adjusted to reflect NOx emissions reductions expected to occur between 2020 and 2025 . Emission reductions were calculated for the known control strategy analysis and the cost analysis for emission r eductions needed beyond known controls (“extrapolated” costs) for each

29 See Chapter 3, Section 3.2.1.4 for a listing of the EPA and California rules reflected in the 15/35 analysis.

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Page 132 of 423 alternative standard being analyzed. The EPA estimates the national

- scale emission reductions for revised annual standard of 12 μg/m 3 and two alternative annual standards ( 13 μg/m 3 and 11 μg/m 3 ) as shown in Table ES

- 1. Due to the rules listed above and other emissions reductions should have substantially reduced ambient PM2.5 concentrations by 2020 in the East, no additional controls are anticipated to be needed outside of California (assum ing no the absence of new sources). Specifically, our analysis estimates that in 2020 only xx counties, all in California, will be out of attainment with the revised annual standard of 12ug/m3. Emissions reductions are needed in more locations for the al ternative standard of 11ug/m3

. See table xxx below

. Since the RIA for the proposed rule, the EPA has made a number of technical improvements to its estimates of needed reductions, which jointly result in ..... Table ES - 1. Emission Reduction Estimates by Standard in 2020 (annual tons/year) a

Alternative Annual Standard s ( μg/m 3 ) PM 2.5 SO 2 NO x 13 730

- - 12 4,000

- - 11 19,000 21,000 9

a Estimates are rounded to two significant figures. 5.11.4 Table 5
- 17. Emission Reductions in Illustrative Emission Reduction Strategies for the

Revised and Alternative Annual Primary PM 2.5 Standards, by Pollutant and Region in 2020 (tons) a

13 μg/m 3 12 μg/m 3 11 μg/m 3 Directly emitted PM 2.5 East 0 0 8,200 West 0 0 160 CA 730 4,000 10,600 SO 2 Comment [A1]: Please insert table 5

- 17

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Page 133 of 423 East 0 0 21,000 West 0 0 43 CA 0 0 0 NOx East 0 0 9 West 0 0 0 CA 0 0 0
5.11.5 a See Chapter 4 for more information on the illustrative emission reduction strategies. The emissions in this table reflect both known and unknown controls. 5.11.6 ES.2. 4 Health and Welfare Co - Benefits The EPA estimated impacts on human health (e.g., mortality and morbidity effects) under full attainment of the three alternative annual PM 2.5 standards. We considered an array of health impacts attributable to changes in PM 2.5 exposure and estimated these benefits using the BenMAP model (Abt Associates, 2012), which has been used in many recent RIAs ( e.g., U.S. EPA, 2006, 2011a, 2011b), and The Benefits and Costs of the Clean Air Act 1990 to 2020 (U.S. EPA, 2011c). As noted above, because California is th e only state that needs additional air quality improvement beyond the analytic baseline after accounting expected air quality improvements expected from recent rules, all of the benefits associated with the revised standard of 12ug/m3 occur in California. Since the proposed rule, t he EPA has incorporated an array of policy and technical updates to the benefits analysis approach applied in this RIA, including incorporation of the most recent follow

- up to the Harvard Six Cities cohort study ( Lepeule et al., 2012 ), more recent demographic data projections, additional hospitalization and emergency department visit studies, and an expanded uncertainty assessment. Each of these updates is fully described in the health benefits chapter (Chapter 5)

. Of most signif icance updating population estimates by using the 2010 census rather than the 2000 census, updating the VSL from xxxx dollars to xxxx dollars

. The combination of the changes and the changes already discussed to the analytic baseline and the emissions cont rol strategies has lead to an almost doubling of the size of the estimated benefits between the proposal for this rule and this final analysis.

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Page 134 of 423 The monetized benefits estimated in the core analysis include avoided premature deaths (derived from effect coe fficients in two cohort studies [ Krewski et al. (2009) and Lepeule et al. (2012) ] for adults and one for infants Woodruff et al. (1997) ) as well as avoided morbidity effects for ten non

- fatal endpoints ranging in severity from lower respiratory symptoms to heart attacks. Even though the primary standards are designed to protect against adverse effects to human health, the emission reductions will have welfare co

- benefits in addition to the direct human health benefits. The term welfare co

- benefits covers both environmental and societal benefits of reducing pollution, such as reductions in visibility impairment, materials damage, and ecosystem damage. Despite our attempts to quantify and monetize as many of the benefits as possibl e, the welfare co - benefits associated with meeting the alternative standards are not quantified or monetized in this analysis. Unquantified health benefits are discussed in Chapter 5, and unquantified welfare co - benefits are discussed in Chapter 6.
It is important to note that estimates of the health benefits from reduced PM 2.5 exposure reported here contain uncertainty, which are described in detail in Chapter 5 and Appendix 5b. Below are two key assumptions in the benefits analysis:
1. We assume that all fi ne particles, regardless of their chemical composition, are equally potent in causing premature mortality. This is an important assumption, because PM 2.5 varies considerably in composition across sources, but the scientific evidence is not yet sufficient t o allow differentiation of effect estimates by particle type. The PM ISA, which was twice reviewed by CASAC, concluded that “many constituents of PM 2.5 can be linked with multiple health effects, and the evidence is not yet sufficient to allow differentiat ion of those constituents or sources that are more closely related to specific outcomes” (U.S. EPA, 2009). These uncertainties are likely to be magnified in the current analysis to the extent that the emissions controls are less diverse when focusing on o ne small region of the country rather than EPA’s more typical NAAQS RIA’s that cover a broader geography with more diverse emissions sources and the application of a more diverse set of controls.

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Page 135 of 423 2. We assume that health impact functions based on national s tudies are

representative of the experience in California

. EPA has considered the cohort studies conducted in California specifically in addition to the national risk coefficients we use as our core estimates. Although we have not calculated the benefits results using these cohort studies, we provided the risk coefficients from these California cohorts to show how much the monetized benefits could have changed if we used these cohort studies. Most of the California cohort studies report central effect esti mates similar to the (nation

wide) all

- cause mortality risk estimate we applied from Krewski et al. (2009) and Lepeule et al. (2012) albeit with wider confidence intervals. Three cohort studies conducted in California indicate statistically significant hig her risks than the risk estimates we applied from Lepeule et al. (2012), and four studies showed insignificant results.
3. We assume that the health impact function for fine particles is log

- linear without a threshold in this analysis. Thus, the estimates include health benefits from reducing fine particles in areas with varied concentrations of PM 2.5, including both areas that do not meet the fine particle standard and those areas that are in attainment, down to the lowest modeled concentrations. In genera l, we are more confident in the magnitude of the risks we estimate from simulated PM 2.5 concentrations that coincide with the bulk of the observed PM concentrations in the epidemiological studies at are used to estimate the benefits. Likewise, we are less confident in the risk we estimate from simulated PM 2.5 concentrations that fall below the bulk of the observed data in these studies. As noted in the preamble to the rule, the range from the 25 th to 10 th percentiles of the air quality data in the epidemiol ogy studies is a reasonable range below which we start to have appreciably less confidence in the magnitude of the associations observed in the epidemiological studies. C oncentration benchmark analyses (e.g., 25 th percentile, 10 th percentile, one standard deviation below the mean 30 , and lowest measured level ( LML ) ) provide some insight into the level of uncertainty in the estimated PM 2.5 mortality benefits

. Most of the estimated avoided premature deaths for this rulemaking occur at or above the lowest measured PM 2.5 concentration in the two studies that are used to estimate mortality benefits. T here are uncertainties inherent in identifying any particular point at which our confidence in reported associations becomes appreciably

30 A range of one standard deviation around the mean represents approximately 68 percent of normally distributed data, and, below the mean falls between the 25 th and 10 th percentiles.

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Page 136 of 423 less , and the scientific evidence provides no clear dividing line

. However , the EPA does not view these concentration benchmarks as a concentration threshold below which we would not quantify health benefits of air quality improvements. Rather, t he core benefits estimates reporte d in this RIA (i.e., those based on Krewski et al. (2 009) and Lepeule et al. (2012)) are the best measures because they reflect the full range of modeled air quality concentrations associated with the emission reduction strategies and because t he current b ody of scientific literature indicates that a no

- threshold model provides the best estimate of PM

- related long

- term mortality. It is important to emphasize that “less confidence” does not mean “no confidence.” The estimated benefits reflect illustrative c ontrol measures and emission reductions to lower PM 2.5 concentrations at monitors projected to exceed the revised and alternative annual standards. The result is that air quality is expected to improve in counties that exceed these standards as well as sur rounding areas that do not exceed the alternative standards. In order to make a direct comparison between the benefits and costs of the emission reduction strategies, it is appropriate to include all the benefits occurring as a result of the emission reduc tion strategies applied regardless of where they occur. Therefore, it is not appropriate to estimate the fraction of benefits that occur only in the counties that exceed the standards because it would omit benefits attributable to emission reduction in exc eeding counties. In addition, we estimate benefits using modeled air quality data with 12km grid cells, which is important because the grid cells are often substantially smaller than counties and PM 2.5 concentrations can vary spatially within a county. Som e grid cells in a county can be below the level of the alternative standard even though the highest monitor exceeds the alternative standard. Thus, emission reductions can lead to benefits in grid cells that are below the alternative standards within an ex ceeding county. 5.11.7 ES.2. 5 Cost Analysis Approach The EPA estimated total costs under partial and full attainment of the alternative PM 2.5 standards. The engineering costs generally include the costs of purchasing, installing, and operating the referenced control technologies. The technologies and control strategies selected for analysis are illustrative of one way in which nonattainment are as could meet a revised standard. There are numerous ways to construct and evaluate potential control programs that would bring areas into

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Page 137 of 423 attainment with alternative standards, and the EPA anticipates that state and local governments will consider program s that are best suited for local conditions. The partial attainment cost analysis reflects the costs associated with app lying known controls

. Costs for full attainment include estimates for the engineering costs of the additional tons of emissions reductio ns that are needed beyond identified controls, referred to as extrapolated costs. By definition, no cost data currently exist s for the additional emissions reductions needed beyond known controls. W e e mploy two methodologies for estimating the costs of un i dentified future controls : a fixed

- cost methodology and a hybrid methodology ; b oth approaches assume that innovative strategies and new control options make possible the emissions reductions needed for attainment by 2020. T he two approaches , however, impli citly reflect different assumptions about technological progress and innovation in emissions reductions strategies. The fixed

- cost methodology uses a $15,000/ton estimate for each ton of PM 2.5 reduced, and t he hybrid methodology generates a total annual cost curve for PM 2.5 for unknown future controls that might be applied in order to move toward 2020 attainment. The hybrid methodology has the advantage of incorporating information about how significant the needed reductions from unspecified control technologies are relative to the known control measures and matching that information with expected increasing per

- ton cost for applying unknown controls. Employing the fixed

- cost methodology, approximately 90% of total costs for attai ning the revised annual standard of 12 μg/m 3 are from unspecified control technologies . Employing the hybrid methodology, approximately 97% of total costs for attaining the revised annual standard of 12 μg/m 3 are from unspecified control technologies

. The EPA recognizes that the extrapolated portion of the engineering cost estimates reflects substantial uncertainty about which sectors and which technologies might become available for cost
- effective application in the future.
T he engineering cost estimates are limited in their scope. Our analysis focuses on the emissions reductions needed for attainment of the revised and alternative standards . Also, t he amendments to the ambient air monitoring regulations will revise the network design requirements for PM 2. 5 monitoring sites, resulting in moving 21 monitors to established near

- road monitoring stations by January 1, 2015. The incremental cost associated with moving these 21 monitors is a one

- time cost of

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Page 138 of 423 $28,570. Lastly, EPA understands that some states will incur costs designing State Implementation Plans (SIPs) and implementing new control strategies to meet the revised standard. However, EPA does not know what specific actions states will take to design their SIPs to meet the revised standards ; therefore we do not include estimated costs that government agencies may incur for managing the requirement , implementing these (or other) control strategies, or for offering incentives that may be necessary to encourage the implementation of specific technologies, especially for technologies that are not necessarily market driven. 5.11.8 5.11.9 ES.2. 6 Comparison of Benefits and Costs The EPA’s illustrative analysis has estimated the health and welfare benefits and costs associated with the revised annual PM NAAQS. The results for 2020 suggest there will be significant health and welfare benefits and these benefits will outweigh the costs associated with the illustrative control strategies in 2020. In the analysis , we estimate the net benefits of the revised annual PM 2.5 standar d of 12 μg/m 3 and al ternative annual standards of 13 μg/m 3 and 11 μg/m 3 , incremental to the 2020 analytical baseline. For the revised annual standard of 12 μg/m 3 , net benefits are estimated to be $ 4.0 billion to $ 8. 8 billion at a 3% discount rate and $ 3. 6 billi on to $ 7. 9 billion at a 7% discount rate in 2020 (20 10 dollars )

. For an alternative annual standard of 13 μg/m 3 , net benefits are estimated to be $ 1.3 b illion to $2 .8 b illion at the 3% discount rate and $ 1.1 b illion to $2 .5 b illion at the 7% discount r ate. N et benefits of an alternative annual PM 2.5 standard of 11 μg/m 3 are estimated to be $ 13 billion to $ 2 7 bill i on at a 3% discount rate and $ 11 billion to $ 25 billion at a 7% discount rate in 2020

. For the revised annual s tandard of 12 μg/m 3 , the EPA estimates that the benefits of full attainment exceed the costs of full attainment by 10 to 150 times at a 7% discount rate. For the alternative annual standard of 13 μg/m 3 , the EPA estimates that the benefits of full attainment exceed the costs o f full attainment by 11 to 245 times at a 7% discount rate. For the alternative annual standard s of 11 μg/m 3 , the EPA estimates that the benefits of full attainment exceed the costs of full attainment by 7 to 83 times at a 7% discount rate.

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Page 139 of 423 Figure ES

- 1 reflects the range of costs based of the calculation of costs using the fixed costs approach and the hybrid costs approach. Additionally, we see the difference in the calculation of benefits based on using various studies. Table ES
- 2. Total Monetized Benef its, Total Co sts, and Net Benefits in 20 20 (m illions

of 20 10 $)
— Full Attainment a

Alternative Annual Standard ( μg/m 3 ) Total Costs b Monetized Benefits d Net Benefits

3% Discount Rate c 7% Discount

Rate 3% Discount

Rate 7% Discount

Rate 3% Discount

Rate b 7% Discount

Rate 13 $11 to $100 $11 to $100 $1,300 to $2,900 $1,200 to

$2,600 $1,300 to

$2,800 $1,100 to

$2,500 12 $53 to $350 $53 to 350 $4,000 to $9,100 $3,600 to

$8,200 $4,000 to

$8,800 $3,600 to

$7,900 11 $ 320 to

$1,700 $320 to

$1,700 $13,000 to

$29,000 $12,000 to

$26,000 $13,000 to

$27,000 $11,000 to

$25,000

a These estimates reflect incremental emissions reductions from an analytical baseline that gives an
“ adjustment ” to the San Joaquin and South Coast areas in California for NOx emissions reductions expected to occur between 2020 and 2025, when those areas are expected to demonstrate attainment with the revised standards. Full benefits of the revised standards in those two areas will not be realized unt il 2025. b The two cost estimates do not represent lower and upper bound estimates, but represent estimates generated by two different methodologies. The lower estimate is generated using the fixed

- cost methodology, which assumes that technological change and innovation will result in the availability of additional controls by 2020 that are similar in cost to the higher end of the cost range for current, known controls. The higher estimate is generated using the hybrid methodology, which assumes that whil e additional controls may become available by 2020, they become available at an increasing cost and the increasing cost varies by geographic area and by degree of difficulty associated with obtaining the needed emissions reductions.
c Due to data limitat ions, we were unable to discount compliance costs for all sectors at 3%. See Chapter 7, Section 7.2.2 for additional details on the data limitations. As a result, the net benefit calculations at 3% were computed by subtracting the costs at 7% from the mone tized benefits at 3%. d The reduction in premature deaths each year accounts for over 90% of total monetized benefits. Mortality risk valuation assumes discounting over the SAB

- recommended 20

- year segmented lag structure. Not all possible benefits or disbe nefits are quantified and monetized in this analysis. B is the sum of all unquantified benefits. Data limitations prevented us from quantifying these endpoints, and as such, these benefits are inherently more uncertain than those benefits that we were able to quantify. The range of benefits reflects the range of the central estimates from two mortality cohort studies (i.e., Krewski et al. (2009) to Lepeule et al. (2012)).

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Page 140 of 423 Figure ES - 1. Monetized Benefit to Cost Comparison for 12 μg/m 3 in 2020 (7% Discount Rate)

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Page 141 of 423 T able ES
- 3 . Estimated Number of Avoided PM 2.5 Health Impacts for Standard

Alternatives — Full Attainment in 2020 a

Health Effect Alternative Annual Standards 13 μg/m 3 12 μg/m 3 11 μg/m 3 Adult Mortality Krewski et al. (2009) (adult) 140 460 1,500 Lepeule et al. (2012) (adult) 330 1,000 3,300 Woodruff et al. (1997) (infant) 0 1 4 Non

- Fatal Heart Attacks (age >18) Peters et al. (2001) 160 480 1,600 Pooled estimate of 4 studies 17 52 170 Hospital admissions

— respiratory (all ages) 31 110 380 Hospital admissions

— cardiovascular (age > 18) 43 140 480 Emergency department visits for asthma (age < 18) 67 230 810 Acute bronchitis (age 8

– 12) 280 870 2,700 Lower respiratory symptoms (age 7

– 14) 3,500 11,000 34,000 Upper respiratory symptoms (asthmatics age 9

– 11) 5,100 16,000 49,000 Asthma exacerbation (age 6

– 18) 13,000 40,000 120,000 Lost work days (age 18

– 65) 22,000 71,000 230,000 Minor restricted

- activity days (age 18

– 65) 130,000 420,000 1,300,000

a Incidence estimates are rounded to whole numbers with no more than two significant figures. 5.12 ES. 3 Discussion and Conclusions An extensive body of scientific evidence documented in the Integrated Science Assessment for Particulate Matter (PM ISA) indicates that PM 2.5 can penetrate deep into the lungs and cause serious health effects, including premature death and other non

fatal illnesses (U.S. EPA, 2009). As described in the preamble to the rule , the revisions to the standards are based on an integrative assessment of an extensive body of new scientific evidence (U.S. EPA, 2009). Health studies published since the PM ISA (e.g., Pope et al. [2009]) confirm that recent levels of PM 2.5 have had a significant impact on

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Page 142 of 423 public health. Based on the air quality analysis in this RIA, the EPA projects that nearly all counties with PM 2.5 monitors in the U.S. would meet an annual standard of 12 μg/m 3 without additional federal, state, or local PM control programs. This demonstrates the substantial pr ogress that the U.S. has made in reducing air pollution emissions over the last several decades. Regulations such as the EPA’s recent Mercury a nd Air Toxics Standards (MATS) and other federal programs such as diesel standards will provide substantial impro vements in regional concentrations of PM 2.5 . Our analysis shows a few areas would still need additional emissions reductions to address local sources of air pollution, including ports and uncontrolled industrial emissions. For this reason, we have designed the RIA analysis to focus on local controls in these few areas. We estimate that these additional local controls would yield benefits well in excess of costs. The setting of a NAAQS does not compel specific pollution reductions, and as such does not direc tly result in costs or benefits. For this reason, NAAQS RIAs are merely illustrative. The NAAQS RIAs illustrate the potential costs and benefits of additional steps States could take to attain a revised air quality standard nationwide beyond rules already on the books. We base our illustrative estimates on an array of emission control strategies for different sources. T he costs and benefits identified in this RIA will not be realized until specific controls are mandated by State Implementation Plans (SIPs) or other federal regulations. In short, NAAQS RIAs hypothesize, but do not prescribe, the control strategies that States may choose to enact when implementing a revised NAAQS. It is important to emphasize that the EPA does not “double count” the costs or t he benefits of our rules. E mission reductions achieved under rules that require specific actions from sources

— such as MATS

— are in the baseline of this NAAQS analysis, as are emission reductions needed to meet the current NAAQS. For this reason, the cost an d benefits estimates provided in this RIA and all other NAAQS RIAs should not be added to the estimates for implementation rules. In calculating the costs, EPA assume d the application of a significant number of un identified future controls that would make possible the additional emission s reductions needed for attainment in 2020. EPA used two methodologies

– the fixed

- cost and hybrid methodologies

-- for estimating the costs of un identified future controls , and b oth approaches assume that innovative strategies and new control options make

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Page 143 of 423 possible the emissions reductions needed for attainment by 2020. Estimates generated by the two approaches do not represent lower and upper bound estimates, but simply represent estimates generated by two different methodologies. The fixed

- cost methodology implicitly assumes that technological change and innovation will result in the availability of additional controls by 2020 that are similar in cost to the higher end of the cost range for current controls. The hybrid methodology implicitly assumes that while additional controls become available by 2020, they become available at an increasing cost and the increasing cost varies by geographic area and by degree of difficulty associ ated with obtaining the needed emissions reductions.
F or the revised annual standard of 12 μg/m 3 , the total cost estimates are comprised of between 90 and 97 percent extrapolated cost estimates , and the estimated total cost using the hybrid methodology is roughly 6.5 times more than the estimated total cost using the fixed

- cost methodology. Because the hybrid methodology reflects increasing marginal costs in areas needing a higher ratio of emission s reductions from unknown to known controls, it could be mo re representative of total costs. In an effort to consider the potential fitness of the e xtrapolated cost estimates, we reviewed the South Coast Air Quality Management District’s (SCAQMD) 2012 Air Quality Management Plan (AQMP) , and we located data on rece nt emission reduction credit (ERC) transaction s in both the SCAQMD and San Joaquin Valley Air Pollution Control District (SJV APCD). While this information provides context for the extrapolated cost estimates, the current relationship between available con trols and costs to reduce emissions may or may not be applicable in 2020 because of changes in innovation and advances in technology. The SCAQMD’s 2012 AQMP includes information on control measures to meet the current 24

- hour standard of 35 μg/m 3 , including further PM 2.5 controls for under

fired charbroilers at a cost per ton reduced of $15,000. This control cost matches the parameter used in the fixed

- cost methodology, as well as the initial value used for the hybrid methodology and is supportive o f our selection of that value. In addition, the California Air Resources Board’s 2009 and 2010 Emission Reduction Offset Transaction Costs, Summary Report included PM 10 ERC prices in both the SCAQMD and the SJV APCD. To some degree, ERC transaction prices reflect a choice between installing a more stringent control or purchasing ERCs. Between 2009 and 2010 PM 10 ERC prices in SJV

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Page 144 of 423 APCD ranged from $40,000 per ton per year (tpy) to $70,000/tpy, and PM 10 ERC prices in the SCAQMD ranged from $575,000/tpy to more than $1.9 million/tpy. These prices reflect both marginal costs that are higher than the fixed

- cost estimates and marginal costs that are not inconsistent with the higher cost estimates generated using the hybrid methodology. For further discussion of the total cost estimates, refer to Section 7.2.4 in Chapter 7 of this RIA. Furthermore, the monetized benefits estimates presented in this RIA are not intended to capture the full burden of PM to public health , but rather represent the incremental benefits ex pected upon attaining the revised annual primary standard of 12 μg/m 3

. In comparison , modeling by Fann et al. (2012) estimated that 2005 levels of air pollution were responsible for between 130,000 and 320,000 PM 2.5 - related deaths, or between 6.1% and 15% of total deaths from all causes in the continental United States. The monetized benefits associated with attaining the proposed range of standards appear modest when viewed within the context of the potential overall public health burden of PM 2.5 and ozone air pollution estimated by Fann et al. (2012), but this is primarily because regulations already on the books will make great strides toward reducing future levels of PM. One important distinction between the total public health burden estimated for 2005 air pollution levels and the estimated benefits in this RIA is that ambient levels of PM 2.5 will have improved substantially by 2020 , due to major emissions reductions resulting from implementation of Federal regulations

. For example, we estimate that SO 2 emissions (an important PM 2.5 precursor) in the U.S. would fall from 14 million tons in 2005 to less than 5 million tons by 2020 (a reduction of 66%). For this reason, States will only need to achieve small air quality improvements to reach the proposed PM standards. As shown in the recent RIA for MATS (U.S. EPA, 2011b), implementing other federal and state air quality actions will address a substantial fraction of the total public health burden of PM 2.5 and ozone air pollution. The NAAQS are not set at lev els that eliminate the risk of air pollution. Instead, the Administrator sets the NAAQS at a level requisite to protect public health with an adequate margin of safety, taking into consideration effects on susceptible populations based on the scientific li terature. The risk analysis prepared in support of this PM NAAQS reported risks below these levels, while acknowledging that the confidence in those effect estimates is higher at levels closer to the standard (U.S. EPA, 2010). While

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Page 145 of 423 benefits occurring belo w the standard are assumed to be more uncertain than those occurring above the standard, the EPA considers these to be legitimate components of the total benefits estimate. Though there are greater uncertainties at lower PM 2.5 concentrations, there is no e vidence of a population

- level threshold in PM 2.5 - related health effects in the epidemiology literature. Lastly, EPA recognizes that there are uncertainties in both the cost and benefit estimates provided in this RIA. T he EPA was unable to monetize fully a ll of the benefits associated with reaching these standards in this RIA, including other health effects of PM, visibility effects, ecosystem effects, and climate effects. If the EPA were able to monetize all of the benefits, the benefits would exceed the e stimated costs by an even greater margin.

5.13 ES. 4 Caveats and Limitations EPA acknowledges several important limitations of th is analysis. These include: 5.13.1 ES. 4 . 1 Benefits Caveats

 PM 2.5 mortality benefits represent a substantial proportion of tota l monetized benefits (over 98 %)

. To characterize the uncertainty in the relationship between PM 2.5 and premature mortality, we include a set of twelve estimates of the concentration

- response function based on results of the PM 2.5 mortality expert elicitati on study in addition to our core estimates. Even these multiple characterizations omit the uncertainty in air quality estimates, baseline incidence rates, populations exposed , chemical composition, transferability of the effect estimate to diverse location s , and additional uncertainty around the mean estimates expressed by the experts

. As a result, the reported confidence intervals and range of estimates give an incomplete picture about the overall uncertainty in the PM 2.5 estimates. This information should be interpreted within the context of the larger uncertainty surrounding the entire analysis.

 Most of the estimated avoided premature deaths occur at or above the lowest measured PM 2.5 concentration in the two studies used to estimate mortality benefits. I n general, we have greater confidence in risk estimates

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Page 146 of 423 based on PM 2.5 concentrations where the bulk of the health and air quality data reside and somewhat less confidence where data density is lower.

 We a naly zed full attainment in 2020 , and projecting key variables introduces uncertainty. Inherent in any analysis of future regulatory programs are uncertainties in projecting atmospheric conditions and source

- level emissions, as well as population, health baselines, incomes, technology, and other factors.

 Th ere are uncertainties related to the health impact functions used in the analysis. These include within

- study variability; pooling across stud ies ; the application of C

- R functions nationwide and for all particle species; extrapolation of impact functions a cross population s ; and various uncertainties in the C

- R function, including causality and shape of the function at low concentrations. Therefore, benefits may be under

- or over estimates.

 T his analysis omits certain unquantified effects due to lack of data , time , and resources. These unquantified endpoints include other health and ecosystem effects. The EPA will continue to evaluate new methods and models and select those most appropriate for estimating the benefits of reductions in air pollution.

 Full bene fits of the revised standards in San Joaquin and South Coast will not be realized until 2025 when those areas are expected to demonstrate attainment with the revised standards. If we were to estimate the monetized benefits for 2025, those benefits would be higher due to population growth, aging of the population, and income growth over time. 5.13.2 ES. 4 . 2 Control Strategy and Cost Analysis Caveats and Limitations

 The control technologies applied as part of the illustrative control strategies represent technologies that are available currently and may not reflect emerging devices that may be available in future years to aid in attainment of the revised standard. In addition the emission reductions calculated from the known controls (control efficiencies) assume that the control devices are properly installed and maintained. There is also variability in scale of application that is difficult to reflect for small area sources of emissions.

 The illustrative control strategy analysis estimates only one potential pathway to attainment. The control strategies are not recommendations for how the revised PM 2.5 standard should be implemented, and states will make

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Page 147 of 423 all final decisions regarding implementation strategies for the revised NAAQS.

 The application of known controls is based upon source information obtained from the emissions inventory. To the extent the inventory is lacking data on baseline controls from State Implementation Plans (SIPs), we may analyze control options that are currently in place.

 The future year emis sions used as a basis for developing the control strategies in this RIA have implicit assumptions regarding e missions growth and control , which differ by sector. For some emission sectors these future year emissions may not reflect new sources locating in thes e areas .

 For two areas in California (South Coast Air Quality Management District and San Joaquin Valley Air Pollution Control District ) the degree of projected nonattainment with the revised annual standard of 12 μg/m 3 is such that th ese areas are not expected to be able to demonstrate attainment with the new standard by 2020. These areas may qualify for up to a five

- year extension of their attainment date and are likely to have until 2025 to demonstrate attainment with the revised annual stand ard

.

 The control technologies applied do not reflect potential effects of technological change that may be available in future years and the effects of “learning by doing” are not accounted for in the emissions reduction estimates. In our analysis , we do not have the necessary data for cumulative output, fuel sales, or emission reductions for all sectors included in order to properly generate control costs that reflect learning curve impacts. We believe the effect of including these impacts would be to low er our estimates of costs for our control strategies in 2020.

 In addition to the application of known controls, EPA assume s the application of un identified future controls that make possible the additional emission reductions needed for attainment in 2020. By definition, no cost data currently exist s for unidentified future technologies or innovative strategies and the cost estimat es for un identified future controls reflect some uncertainty

.

 Because we obtain control cost data from many sources, we are not always able to obtain consistent data across original data sources. If disaggregated control cost data is unavailable (i.e., where capital, equipment life value, and O&M costs are not separated out), EPA typically assumes that the estimated control costs a re annualized using a 7% discount rate. When disaggregated control cost data is available (i.e., where capital, equipment life value, and

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Page 148 of 423 O&M costs are explicit) we can recalculate costs using a 3% discount rate. In general, we have some disaggregated data available for non

- EGU point source controls and we do not have any disaggregated control cost data for area source controls. In this analysis, for the revised annual standard of 12 μg/m 3 and the alternative standard of 13 μg/m 3 we did not have any disaggregated known control cost data, and as such we were not able to recalculate known control costs using a 3% discount rate.

 EPA understands that some states will incur costs designing SIPs and implementing new control strategies to meet the revised annual standard. However, EPA does not know what specific actions states will take to design their SIPs to meet the revised standards ; therefore we do not present estimated costs that government agencies may incur for managing the requi rement , implementing these (or other) control strategies, or for offering incentives that may be necessary to encourage the implementation of specific technologies, especially for technologies that are not necessarily market driven. 5.13.3 ES. 5 References Abt Ass ociates, Inc. 2012. BenMAP User ’ s Manual Appendices

. Prepared for U.S. Environmental Protection Agency Office of Air Quality Planning and Standards. Research Triangle Park, NC. September. Fann, N., A. Lamson, K. Wesson, D. Risley, S.C. Anenberg, and B.J. Hubbell. 2012. “Estimating the National Public Health Burden Associated with Exposure to Ambient PM 2.5 and Ozone. Risk Analysis.” Risk Analysis 32(1): 81

- 95. Krewski, D., R.T. Burnett, M.S. Goldbert, K. Hoover, J. Siemiatycki, M. Jerrett, M. Abrahamowicz, and W.H. White. 2000. “ Reanalysis of the Harvard Six Cities Study and the American Cancer Society Study of Particulate Air Pollution and Mortality. ” Special Report to the Health Effects Institute. Cambridge MA. July. Lepeule J, Laden F, Dockery D, Schwartz J 2012. “ Chronic Exposure to Fine Particles and Mortality: An Extended Follow

- Up of the Harvard Six Cities Study from 1974 to 2009. ” Environ Health Perspect. In press. http://dx.doi.org/10.1289/ehp.1104660 Pope, CA III, E Majid, D Dockery. 2009. “ Fine Particle Air Pollution and Life Expectancy in the United States. ” New England Journal of Medicine 360: 376
– 3 86. U.S. Environmental Protection Agency. 1997. Regulatory I mpact Analyses for the Particulate Matter and Ozone National Ambient Air Quality Standards and Proposed Regional Haze Rule. Available at: http://www.epa.gov/ttn/oarpg/naaqsfin/ria.html

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Page 149 of 423 U.S. Envir onmental Protection Agency (U.S. EPA). 2004. Final Regulatory Analysis: Control of Emissions from Nonroad Diesel Engines. EPA420

- R

- 04

- 007. Available on the Internet at http://www.epa.gov/otaq/documents/nonroad

diesel/420r04007.pdf

. U.S. Environmental Protection Agency ( U.S. EPA ). November 17, 2005a. Federal Register

. Vol. 70, No. 221. “ Control of Air Pollution From Aircraft and Aircraft Engines; Emission Standards and Test Procedures. ” 40 CFR Part 87. Available on the Internet at < http://www.epa.gov/fedrgstr/EPA

- AIR/2005/November/Day

17/a22704.pdf > . U.S. Environmental Protection Agency ( U.S. EPA ). 2005b

. Regulatory Impact Analysis for the Final Clean Air Visibility Rule o r the Guidelines for Best Available Retrofit Technology (BART) Determinations Under the Regional Haze Regulations

. EPA

452/R

- 05

- 004. Available on the Internet at < http://www.epa.go v/oar/visibility/pdfs/bart_ria_2005_6_15.pdf >. U.S. Environmental Protection Agency (U.S. EPA). 2006. Regulatory Impact Analysis, 2006 National Ambient Air Quality Standards for Particulate Matter, Chapter 5

. Office of Air Quality Planning and Standards, Research Triangle Park, NC. October. Available on the Internet at <http://www.epa.gov/ttn/ecas/regdata/RIAs/Chapter%205

— Benefits.pdf>. U.S. Environmental Protection Agency (U.S. EPA). 2009. Integrated Science Assessment for Particulate Matter (Final Report )

. EPA

- 600

- R

- 08

- 139F. National Center for Environmental Assessment

— RTP Division. December. Available on the Internet at <http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=216546>. U.S. Environmental Protection Agency (U.S. EPA). 2011 a . Regulatory Impact Analysis for the Federal Implementation Plans to Reduce Interstate Transport of Fine Particulate Matter and Ozone in 27 States; Correction of SIP Approvals for 22 States

. June . Available on the Internet at < http://www.epa.gov/airtransport/pdfs/FinalRIA.pdf >. U.S. Environmental Protection Agency (U.S. EPA). 2011 b

. Regulatory Impact Analysis for the Final Mercury and Air Toxics Standards. EPA

- 452/R

- 11

- 011

. December

. Available on the Internet at < http://www.epa.gov/ttn/ecas/regdata/RIAs/matsriafinal.pdf >. U.S. Environmental Protection Agency (U.S. EPA). 2011 c . The Benefits and Costs of the Clean Air Act 1990 to 2020: EPA Report to Congress . Office of Air and Radiation, Office of Policy, Washington, DC. March. Available on the Internet at < http://www.epa.gov/oar /sect812/feb11/fullreport.pdf >.

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Page 150 of 423 U.S. Environmental Protection Agency (U.S. EPA). 2011 d

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

452/D

- 11

- 003. April. Available on the Internet at < http://www.epa.gov/ttnnaaqs/standards/pm/s_pm_2007_pa.html > . Woodruff, T.J., J. Grillo, and K.C. Schoendorf. 1997. “ The Relationship Between Selected of postneonatal infant mortality and particulat e air pollution in the United States. ” Environmental Health Perspectives . Vol. 105 (6): 608

- 612.

I. Rationale for Final Decisions on the Primary PM 2.5 Standards This section presents the Administrator’s final decision regarding the need to revise the current primary PM 2.5 standards and, more specifically, regarding revisions to the level and form of the existing primary annual PM 2.5 standard in conjunction with retaining the existing primary 24

- hour PM 2.5 standard. As discussed more fully below, the rationale for the final decision is based on a thorough review, in the Integrated Science Assessment, of the latest scientific information, published through mid

- 2009, on human health effects associated with long

- and short

- term exposures to fine particles in the ambient air. Th e final decisions also take into account: (1) staff assessments of the most policy

- relevant information presented and assessed in the Integrated Science Assessment and staff analyses of air quality and human risks presented in the Risk Assessment and the P olicy Assessment, upon which staff conclusions regarding appropriate considerations in this review are based; (2) CASAC advice and recommendations, as reflected in discussions of drafts of the Integrated Science Assessment, Risk Assessment, and Policy Asse ssment at public meetings, in separate

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Page 151 of 423 written comments, and in CASAC’s letters to the Administrator; (3) the multiple rounds of public comments received during the development of these documents, both in connection with CASAC meetings and separately; and (4) extensive public comments received on the proposal. In developing this final rule, the Administrator recognizes that the CAA requires her to reach a public health policy judgment as to what standards would be requisite

-- neither more nor less stringe nt than necessary

-- to protect public health with an adequate margin of safety, based on scientific evidence and technical assessments that have inherent uncertainties and limitations. This judgment requires making reasoned decisions as to what weight to place on various types of evidence and assessments, and on the related uncertainties and limitations. Thus, in selecting the final standards, the Administrator is seeking not only to prevent fine particle concentrations that have been demonstrated to be ha rmful but also to prevent lower fine particle concentrations that may pose an unacceptable risk of harm, even if the risk is not precisely identified as to nature or degree. As discussed below, as well as in more detail in the proposal, a substantial

amou nt of new research has been conducted since the close of the science assessment in the last review of the PM 2.5 NAAQS ( U.S. EPA, 2004), with important new information coming from epidemiological studies, in particular. This body of evidence includes hundre ds of new epidemiological studies conducted in many countries around the world. In its assessment of the evidence judged to be most relevant to making decisions

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Page 152 of 423 on elements of the primary PM 2.5 standards, the EPA has placed greater weight on U.S. and Canad ian studies using PM 2.5 measurements, since studies conducted in other countries may reflect different demographic and air pollution characteristics. 31 The newly available research studies as well as the earlier body of scientific evidence presented and as sessed in the Integrated Science Assessment have undergone intensive scrutiny through multiple layers of peer review and opportunities for public review and comment. In developing this final rule, the EPA has drawn upon an integrative synthesis of the enti re body of evidence concerning exposure to ambient fine particles and a broad range of health endpoints ( U.S. EPA, 2009a, Chapters 2, 4, 5, 6, 7, and 8) focusing on those health endpoints for which the Integrated Science Assessment concludes that there is a causal or likely causal relationship with long

- or short

- term PM 2.5 exposures. The EPA has also considered health endpoints for which the Integrated Science Assessment concludes there is evidence suggestive of a causal relationship with long

- term PM 2.5 e xposures. The EPA has also drawn upon a quantitative risk assessment based upon the scientific evidence described and assessed in the Integrated Science Assessment. These analyses, discussed in the Risk Assessment ( U.S. EPA, 2010a) and Policy Assessment ( U.S. EPA, 2011a, chapter 2), have also undergone intensive scrutiny through multiple layers of peer review and multiple opportunities for public review and comment.

31 Nonetheless, the Administrator recognizes the importance of all studies, including international studies, in the Integrated Science Assessment’s considerations of the weight of the evidence that informs causality determinations.

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Page 153 of 423 Although important uncertainties remain in the qualitative and quantitative characterizati ons of health effects attributable to ambient fine particles, progress has been made in addressing these uncertainties in this review . The EPA ’s review of this information has been extensive and deliberate. This intensive evaluation of the scientific evide nce and quantitative assessments has provided a comprehensive and adequate basis for regulatory decision making at this time. This section describes the integrative synthesis of the evidence and technical information contained in the Integrated Science As sessment , the Risk Assessment , and the Policy Assessment with regard to the current and alternative standards. The EPA notes that the final decision for retaining or revising the current primary PM 2.5 standards is a public health policy judgment made by th e Administrator. The Administrator’s final decision draws upon scientific information and analyses related to health effects and risks; judgments about uncertainties that are inherent in the scientific evidence and analyses; CASAC advice; and comments rece ived in response to the proposal. In presenting the rationale for the final decisions on the primary PM 2.5 standards, this section begins with a summary of the approaches used in setting the initial primary
PM 2.5 NAAQS in 1997 and in reviewing and revising those standards in 2006 (section III.A.1). The D.C. Circuit Court of Appeals remand of the primary annual PM 2.5 standard in 2009 is discussed in section III.A.2. Taking into consideration this history, section
I II.A.3 describes the EPA’s general approach used in the current review for considering

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Page 154 of 423 the need to retain or revise the current suite of fine particle standards, taking into account public comment on the proposed approach. The scientific evidence and quantitative risk assessment were presented in

s ections III.B and III.C of the proposal, respectively (77 FR 38906 to 38917, June 29, 2012) and are outlined in sections III.B and III.C below. Subsequent sections of this preamble provide a more complete discussion of the Administrator’s rationale, in lig ht of key issues raised in public comments, for concluding that it is appropriate to revise the suite of current primary PM 2.5 standards (section III.D), as well as a more complete discussion of the Administrator’s rationale for retaining or revising the s pecific elements of the primary PM 2.5 standards, namely the indicator (section III.E.1); averaging time (section III.E.2); form (section III.E.3); and level (section III.E.4). A summary of the final decisions to revise the suite of primary PM 2.5 standards is presented in section III.F.
A. Background There are currently two primary PM 2.5 standards providing public health protection from effects associated with fine particle exposures. The annual standard is set at a level of 15.0 μg/m 3 , based on the 3

- year average of annual arithmetic mean
PM 2.5 concentrations from single or multiple monitors sited to represent community

wide air quality. The 24

- hour standard is set at a level of 35 μg/m 3 , based on the 3

- year average of the 98 th percentile of 24

- hour PM 2.5 c oncentrations at each population

oriented monitor within an area.

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Page 155 of 423 The past and current approaches for reviewing the primary PM 2.5 standards described below are all based most fundamentally on using information from epidemiological studies to inform the se lection of PM 2.5 standards that, in the Administrator’s judgment, protect public health with an adequate margin of safety. Such information can be in the form of air quality distributions over which health effect associations have been observed in scientif ic studies or in the form of concentration

response functions that support quantitative risk assessment. However, evidence

- and risk

- based approaches using information from epidemiological studies to inform decisions on PM 2.5 standards are complicated by t he recognition that no population threshold, below which it can be concluded with confidence that PM 2.5 - related effects do not occur, can be discerned from the available evidence. 32 As a result, any general approach to reaching decisions on what standards a re appropriate necessarily requires judgments about how to translate the information available from the epidemiological studies into a basis for appropriate standards. This includes consideration of how to weigh the uncertainties in the reported associatio ns across the distributions of PM 2.5 concentrations in the studies and the uncertainties in quantitative estimates of risk, in the context of the entire body of evidence before the Agency. Such approaches are consistent with setting standards that are neit her more nor less stringent than necessary, recognizing that a zero

- risk standard is not required by the CAA.

32 The term "evidence

- based" approach or consideration generally refers to using the information in the scientific evidence to inform judgments on the need to retain or revise the NAAQS. The term "risk

- based" generally refers to using the quantitative inform ation in the Risk Assessment to inform such judgments.

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Page 156 of 423 1. General Approach Used in Previous Reviews The general approach used to translate scientific information into standards in the previous PM NAAQS r eviews focused on consideration of alternative standard levels that were somewhat below the long

- term mean PM 2.5 concentrations reported in key epidemiological studies ( U.S. EPA, 2011a, section 2.1.1). This approach recognized that the strongest evidence o f PM 2.5 - related associations occurs where the bulk of the data exists, which is over a range of concentrations around the long

- term (i.e., annual) mean. In setting primary PM 2.5 annual and 24

- hour standards for the first time in 1997, the Agency relied pr imarily on an evidence

- based approach that focused on epidemiological evidence, especially from short

- term exposure studies of fine particles judged to be the strongest evidence at that time ( U.S. EPA, 2011a, section 2.1.1.1). The EPA selected a level for the annual standard that was at or below the long

- term mean PM 2.5 concentrations in studies providing evidence of associations with short

- term PM 2.5 exposures, placing greatest weight on those short

- term exposure studies that reported clearly statistically significant associations with mortality and morbidity effects. Further consideration of long

- term mean PM 2.5 concentrations associated with mortality and respiratory effects in children did not provide a basis for establishing a lower annual standard leve l. The EPA did not place much weight on quantitative risk estimates from the very limited risk assessment conducted, but did conclude that the risk assessment results confirmed the general conclusions drawn from the epidemiological evidence that

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Page 157 of 423 a serious public health problem was associated with ambient PM levels allowed under the then current PM 10 standards (62 FR 38665/1, July 18, 1997). The EPA considered the epidemiological evidence and data on air quality relationships to set an annual PM 2.5 standard that was intended to be the “generally controlling” standard; i.e., the primary means of lowering both long

- and short

- term ambient concentrations of PM 2.5 . 33 In conjunction with the annual standard, the EPA also established a 24

- hour PM 2.5 standa rd to provide supplemental protection against days with high peak concentrations, localized “hotspots,” and risks arising from seasonal emissions that might not be well controlled by an annual standard (62 FR 38669/3). In 2006, the EPA used a different ev idence

- based approach to assess the appropriateness of the levels of the 24

- hour and annual PM 2.5 standards ( U.S. EPA, 2011a, section 2.1.1.2). Based on an expanded body of epidemiological evidence that was stronger and more robust than that available in t he 1997 review, including additional studies of both short

- and long

- term exposures, the EPA decided that using evidence of effects associated with periods of exposure that were most closely matched

33 In so doing, the EPA noted that because an annual standard would focus control programs on annual average PM 2.5 concentrations, it would not only control long

term exposure levels, but would also gen erally control the overall distribution of 24

- hour exposure levels, resulting in fewer and lower 24

- hour peak concentrations. Alternatively, a 24

- hour standard that focused controls on peak concentrations could also result in lower annual average concentra tions. Thus, the EPA recognized that either standard could provide some degree of protection from both short

- and long

term exposures, with the other standard serving to address situations where the daily peaks and annual averages are not consistently corr elated (62 FR 38669, July 18, 1997). In the circumstances presented in that review, the EPA determined that it was appropriate to focus on the annual standard as the standard best suited to control both annual and daily air quality distributions (62 FR 386 70).

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Page 158 of 423 to the averaging time of each standard was the most appro priate public health policy approach for evaluating the scientific evidence to inform selecting the level of each standard. Thus, the EPA relied upon evidence from the short

- term exposure studies as the principal basis for revising the level of the 24

- hour PM 2.5 standard from 65 to 35 μg/m 3 to protect against effects associated with short

- term exposures. The EPA relied upon evidence from long

- term exposure studies as the principal basis for retaining the level of the annual PM 2.5 standard at 15 μg/m 3 to pro tect against effects associated with long

- term exposures. This approach essentially took the view that short

- term studies were not appropriate to inform decisions relating to the level of the annual standard, and long

- term studies were not appropriate to i nform decisions relating to the level of the 24

- hour standard. With respect to quantitative risk

- based considerations, the EPA determined that the estimates of risks likely to remain upon attainment of the 1997 suite of PM 2.5 standards were indicative of r isks that could be reasonably judged important from a public health perspective and, thus, supported revision of the standards. However, the EPA judged that the quantitative risk assessment had important limitations and did not provide an appropriate basis for selecting the levels of the revised standards in 2006 (71 FR 61174/1

- 2, October 17, 2006).
2. Remand of Primary Annual PM 2.5 Standard As noted above in section II.B.2, several parties filed petitions for review in the U.S. Court of Appeals for the Distr ict of Columbia Circuit following promulgation of the revised PM NAAQS in 2006. These petitions challenged several aspects of the final rule

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Page 159 of 423 including the level of the primary PM 2.5 annual standard. The primary 24

- hour PM 2.5 standard was not challenged by any of the litigants and, thus, was not considered in the court’s review and decision. On judicial review, the D.C. Circuit remanded the primary annual PM 2.5 NAAQS to the EPA on grounds that the Agency failed to adequately e xplain why the annual standard provided the requisite protection from both short

- and long

- term exposures to fine particles including protection for at

- risk populations. American Farm Bureau Federation v. EPA , 559 F. 3d 512 (D.C. Cir. 2009). With respect t o human health protection from short

- term PM 2.5 exposures, the court considered the different approaches used by the EPA in the 1997 and 2006 PM NAAQS decisions, as summarized in section III.A.1 above. The court found that the EPA failed to adequately expl ain why a primary 24

- hour PM 2.5 standard by itself would provide the protection needed from short

- term exposures and remanded the primary annual PM 2.5 standard to the EPA “for further consideration of whether it is set at a level requisite to protect the p ublic health while providing an adequate margin of safety from the risk of short

- term exposures to
PM 2.5 .” American Farm Bureau Federation v. EPA , 559 F. 3d at 520

- 24. With respect to protection from long

- term exposure to fine particles, the court found t hat the EPA failed to adequately explain how the primary annual PM 2.5 standard provided an adequate margin of safety for children and other at

- risk populations. The court found that the EPA did not provide a reasonable explanation of why certain morbidity studies, including a study of children in Southern California showing lung

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Page 160 of 423 damage associated with long

- term PM 2.5 exposure (Gauderman et.al, 2000) and a multi

city study (24

- Cities Study) evaluating decreased lung function in children associated with long

- term PM 2.5 exposures (Raizenne et al., 1996), did not warrant a more stringent annual PM 2.5 standard. Id. at 522

- 23. Specifically, the court found that: EPA was unreasonably confident that, even though it relied solely upon long

term mortality studies, the revised standard would provide an adequate margin of safety with respect to morbidity among children. Notably absent from the final rule, moreover, is any indication of how the standard will adequately reduce risk to the elderly or to those with certain h eart or lung diseases despite (a) the EPA’s determination in its proposed rule that those subpopulations are at greater risk from exposure to fine particles and (b) the evidence in the record supporting that determination. Id. at 525. In addition, the cour t held that the EPA had not adequately explained its decision to base the level of the annual standard essentially exclusively on the results of long

term studies and the 24

- hour standard level essentially exclusively on the results of short

- term studies. See 559 F. 3d at 522 (“[e]ven if the long

- term studies available today are useful for setting an annual standard,..., it is not clear why the EPA no longer believes it useful to look as well to short

- term studies in order to design the suite of standards tha t will most effectively reduce the risks associated with short

- term exposure”); see also I d. at 523

- 24 (holding that the EPA had not adequately explained why a standard based on levels in short

- term exposure studies alone provided appropriate protection fr om health effects associated with short

- term PM 2.5 exposures given the stated need to lower the entire air quality distribution, and not just peak concentrations, in order to control against short

- term effects).

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Page 161 of 423 In remanding the primary annual PM 2.5 stand ard for reconsideration, the court did not vacate the standard, Id

. at 530, so the standard remains in effect and is therefore the standard considered by the EPA in this review.
3. General Approach Used in the Policy Assessment for the Current Review This review is based on an assessment of a much expanded body of scientific evidence, more extensive air quality data and analyses, and a more comprehensive quantitative risk assessment relative to the information available in past reviews, as presented an d assessed in the Integrated Science Assessment and Risk Assessment and discussed in the Policy Assessment . As a result, the EPA’s general approach to reaching conclusions about the adequacy of the current suite of PM 2.5 standards and potential alternative standards that are appropriate to consider was broader and more integrative than in past reviews. Our general approach also reflected consideration of the issues raised by the court in its remand of the primary annual PM 2.5 standard as discussed in sectio n III.A.2 above , since decisions made in this review, and the rationales for those decisions, will comprise the Agency’s response to the remand. The EPA’s general approach took into account both evidence

- based and risk

based considerations and the uncertai nties related to both types of information, as well as advice from CASAC (Samet, 2010c,d) and public comments on the first and second draft Policy Assessments ( U.S. EPA, 2010c,f). In so doing, the EPA staff developed a final Policy Assessment ( U.S. EPA, 20 11a) which provided as broad an array of policy options as was supported by the available information, recognizing that the selection of a

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Page 162 of 423 specific approach to reaching final decisions on the primary PM 2.5 standards will reflect the judgments of the Admini strator as to what weight to place on the various approaches and types of information available in the current review. The Policy Assessment concluded it was most appropriate to consider the protection against PM 2.5 - related mortality and morbidity effects, associated with both long

- and short

- term exposures, afforded by the annual and 24

- hour standards taken together, as was done in the 1997 review, rather than to consider each standard separately, as was done in the 2006 review ( U.S. EPA, 2011a, section 2. 1.3). 34 As the EPA recognized in 1997, there are various ways to combine two standards to achieve an appropriate degree of public health protection. The extent to which these two standards are interrelated in any given area depends in large part on the rela tive 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 consid ering the combined effect of annual and 24

- hour standards, the Policy Assessment recognized that changes in PM 2.5 air quality designed to meet an annual

34 By utilizing this approach, the Agency also is responsive to the remand of the 2006 standard. As noted in section III.A.2, the D.C. Circuit, in remanding the 2006 primary annual PM 2.5 standard, concluded that the Administrator had failed to adequate ly explain why an annual standard was sufficiently protective in the absence of consideration of the long

- term mean PM 2.5 concentrations in short

- term exposure studies as well, and likewise had failed to explain why a 24

- hour standard was sufficiently prot ective in the absence of consideration of the effect of an annual standard on reducing the overall distribution of 24

- hour average PM 2.5 concentrations. 559 F. 3d at 520

- 24.

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Page 16 3 of 423 standard would likely result not only in lower annual average PM 2.5 concentrations but also in fewer an d lower peak 24

- hour PM 2.5 concentrations. The Policy Assessment also recognized that changes designed to meet a 24

- hour standard would result not only in fewer and lower peak 24

- hour PM 2.5 concentrations but also in lower annual average
PM 2.5 concentratio ns. Thus, either standard could be viewed as providing protection from effects associated with both short

- and long

- term exposures, with the other standard serving to address situations where the daily peak and annual average
concentrations are not consist ently correlated. In considering the currently available evidence, the Policy Assessment recognized that the short

- term exposure studies were primarily drawn from epidemiological studies that associated variations in area

- wide health effects with monitor( s) that measured the variation in daily PM 2.5 concentrations over the course of several years. The strength of the associations in these data was demonstrably in the numerous “typical” days within the air quality distribution, not in the peak days. See als o 71 FR 61168, October 17, 2006 and American Farm Bureau Federation v EPA , 559 F. 3d at 523, 524 (making the same point). The quantitative risk assessments conducted for this and previous reviews demonstrated the same point ; that is, much, if not most of t he 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, 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

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Page 164 of 423 long

- term exposures were likely to be disproportionately driven by peak 24

- hour concentrations. 35 For these reasons, the Policy Assessment concluded that strategie s that focused primarily on reducing peak days were less likely to achieve reductions in the PM 2.5 concentrations that were most strongly associated with the observed health effects. Furthermore, the Policy Assessment concluded that a policy 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, as discussed above, reductions based on control of peak days are less likely to control the bulk of the air quality distribution. The Policy Assessment concluded that a policy goal of setting a “generally controlling” annual stand ard that will lower a wide range of ambient 24

- hour PM 2.5 concentrations, as opposed to focusing on control of peak 24

- hour PM 2.5 concentrations, was the most effective and efficient way to reduce total population risk and so provide appropriate protection . This approach, in contrast to one focusing on a generally controlling 24

- hour standard, would likely reduce aggregate risks associated with both long

- and short

- term exposures with more consistency and would likely avoid setting national standards that c ould result in relatively uneven protection across the

35 In confirmation, a number of studies have presented analyses excluding higher P M 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).

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Page 165 of 423 country, due to setting standards that are either more or less stringent than necessary in different geographical areas (U.S. EPA, 2011a, p. 2

- 9)

. The Policy Assessment also concluded that an annual st andard intended to serve as the primary means for providing protection from effects associated with both long

and short

- term PM 2.5 exposures cannot be expected to offer sufficient protection against the effects of all short

- term PM 2.5 exposures. As a result, in conjunction with a generally controlling annual standard, the Policy Assessment concluded it was appropriate to consider setting a 24

- hour standard to provide supplemental protection, particularly for areas with high peak

- to
- mea n ratios possibly associated with strong local or seasonal sources, or PM 2.5 - related effects that may be associated with shorter

- than

daily exposure periods ( U.S. EPA, 2011a, p. 2

- 10). The Policy Assessment ’s consideration of the protection afforded by the current and alternative suites of standards focused on PM 2.5 - related health effects associated with long

- term exposures for which the magnitude of quantitative estimates of risks to public health generated in the risk assessment was appreciably larger in terms of overall incidence and percent of total mortality or morbidity effects than for short

- term PM 2.5 - related effects. Nonetheless, the EPA also considered health effects and estimated risks associated with short

- term exposures. In both cases, the Polic y Assessment placed greatest weight on health effects that had been judged in the Integrated Science Assessment to have a causal or likely causal relationship with PM 2.5 exposures, while also considering health effects judged to be suggestive of a causal

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Page 166 of 423 r elationship or evidence that focused on specific at

- risk populations. The Policy
Assessment placed relatively greater weight on statistically significant associations that yielded relatively more precise effect estimates and that were judged to be robust t o confounding by other air pollutants. In the case of short

- term exposure studies, the Policy Assessment placed greatest weight on evidence from large multi

- city studies, while also considering associations in single

- city studies. In translating informati on from epidemiological studies into the basis for reaching staff conclusions on the adequacy of the current suite of standards, the Policy
Assessment considered a number of factors. As an initial matter, the Policy Assessment considered the extent to whic h the currently available evidence and related uncertainties strengthens or calls into question conclusions from the last review regarding associations between fine particle exposures and health effects. The Policy
Assessment also considered evidence of he alth effects in at

- risk populations and the potential impacts on such populations. Further, the Policy Assessment explored the extent to which PM 2.5 - related health effects had been observed in areas where air quality distributions extend to lower concentra tions than previously reported or in areas that would likely have met the current suite of standards. In translating information from epidemiological studies into the basis for reaching staff conclusions on standard levels for consideration ( U.S. EPA, 201 1a, sections 2.1.3 and 2.3.4), the Policy Assessment first recognized the absence of discernible thresholds in the concentration

- response functions from long

- and short

-

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Page 167 of 423 term PM 2.5 exposure studies ( U.S. EPA, 2011a, section 2.4.3). 36 In the absence of any di scernible thresholds, the Agency’s general approach for identifying appropriate standard levels for consideration involved characterizing the range of PM 2.5 concentrations over which we have the most confidence in the associations reported in epidemiologic al studies. In so doing, the Policy Assessment recognized that there is no single factor or criterion that comprises the “correct” approach, but rather there are various approaches that are reasonable to consider for characterizing the confidence in the as sociations and the limitations and uncertainties in the evidence. Identifying the implications of various approaches for reaching conclusions on the range of alternative standard levels that is appropriate to consider can help inform the final decisions to either retain or revise the standards. Today’s final decisions also take into account public health policy judgments as to the degree of health protection that is to be achieved. In reaching staff conclusions on the range of annual standard levels that w as appropriate to consider, the Policy Assessment focused on identifying an annual

36 The epidemiological studies evaluated in the Integrated Science Assessment that examined the shape of concentration

- response relationships and the potential presence of a threshold focused on cardiovascular

- related hospital admissions and emergency department visits associated with short

- term PM 10 e xposures and premature mortality associated with long

- term PM 2.5 exposure (U.S. EPA, 2009a, sections 6.5, 6.2.10.10 and 7.6). Overall, the Integrated Science Assessment concluded that the studies evaluated support the use of a no

- threshold, log

- linear mode l but recognized that “additional issues such as the influence of heterogeneity in estimates between cities, and the effect of seasonal and regional differences in PM on the concentration

- response relationship still require further investigation” (U.S. EPA , 2009a, section 2.4.3).

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Page 168 of 423 standard that provided requisite protection from effects associated with both long

- and short

- term exposures. In so doing, the Policy Assessment explored different approache s for characterizing the range of PM 2.5 concentrations over which our confidence in the nature of the associations for both long

- and short

- term exposures is greatest, as well as the extent to which our confidence is reduced at lower PM 2.5 concentrations. First, the Policy Assessment recognized that the approach that most directly addressed this issue considered studies that analyzed confidence intervals around
concentration

- response relationships and in particular, analyses that averaged across multiple concentration

- response models rather than considering a single concentration

response model. 37 The Policy Assessment explored the extent to which such analyses had been published for studies of health effects associated with long

- or short

- term PM 2.5 exposu res. Such analyses could potentially be used to characterize a concentration below which uncertainty in a concentration

- response relationship substantially increases or is judged to be indicative of an unacceptable degree of uncertainty about the existence of a continuing concentration

- response relationship. The Policy Assessment concluded that identifying this area of uncertainty in the concentration

- response relationship could be used to inform identification of alternative standard levels that are approp riate to consider.

37 This is distinct from confidence intervals around concentration

- response relationships that are related to the magnitude of effect estimates generated at specific PM 2.5 concentrations (i.e., point

- wise confidence intervals) and t hat are relevant to the precision of the effect estimate across the air quality distribution, rather than to our confidence in the existence of a continuing concentration

- response relationship across the entire air quality distribution on which a reported association was based.

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Page 169 of 423 Further, the Policy Assessment explored other approaches that considered different statistical metrics from epidemiological studies. The Policy Assessment first took into account the general approach used in previous PM reviews which fo cused on consideration of alternative standard levels that were somewhat below the long

- term mean PM 2.5 concentrations reported in epidemiological studies using air quality distributions based on composite monitor concentrations. 38 This approach recognized that the strongest evidence of PM 2.5 - related associations occurs at concentrations around the long

- term (i.e., annual) mean. In using this approach, the Policy Assessment placed greatest weight on those long

- and short

- term exposure studies that reported

s tatistically significant associations with mortality and morbidity effects. In extending this approach, the Policy Assessment also considered information beyond a single statistical metric of PM 2.5 concentrations (i.e., the mean) to the extent such information was available. Pursuant to an express comment from CASAC (Samet 2010d, p. 2), the Policy Assessment utilized distributional statistics (i.e., statistical characterization of an entire distribu tion of data) to identify the broader range of PM 2.5 concentrations that had the most influence on the calculation of relative risk estimates

38 Using the term “composite monitor” does not imply that the EPA can identify one monitor that represents the air quality evaluated in a specific study area. Rather, the composite monitor concentration represents the average concent ration across monitors within each area with more than one monitor included in a given study as typically reported in epidemiological studies. For multi

- city studies, this metric reflects concentrations averaged across multiple monitors or from single moni tors within each area and then averaged across study areas for an overall study mean PM 2.5 concentration. This is consistent with the epidemiological evidence considered in other NAAQS reviews.

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Page 170 of 423 in both long

- and short

- term exposure epidemiological studies. Thus, the Policy
Assessment considered the part of the distribution of PM 2.5 concentrations in which the data analyzed in the study (i.e., air quality and population

- level data, as discussed below) w ere most concentrated, specifically, the range of PM 2.5 concentrations around the long

- term mean over which our confidence in the magnitude and significance of associations observed in the epidemiological studies was greatest. The Policy
Assessment then focused on the lower part of th e distribution to characterize where the data became appreciably more sparse an d, thus, where our understanding of the magnitude and significance of the associations correspondingly became more uncertain. The Policy Assessment recognized there was no single percentile value within a given distribution that was most appropriate or “co rrect” to use to characterize where our confidence in the associations becomes appreciably lower. The Policy Assessment concluded that the range from the 25 th to 10 th percentiles is a reasonable range to consider as a region where we had appreciably less c onfidence in the associations observed in epidemiological studies. 39

39 In the PM NAAQS review completed in 2006, the Staff Paper si milarly recognized that the evidence of an association in any epidemiological study is “strongest at and around the long

- term average where the data in the study are most concentrated. For example, the interquartile range of long

- term average concentration s within a study [with a lower bound of the 25 th percentile] or a range within one standard deviation around the study mean, may reasonably be used to characterize the range over which the evidence of association is strongest” (U.S. EPA, 2005, p. 5

- 22). A range of one standard deviation around the mean represents approximately 68 percent of normally distributed data, and below the mean falls between the 25 th and 10 th percentiles.

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Page 171 of 423 In considering distributional statistics from epidemiological studies, the final Policy Assessment focused on two types of population

- level metrics that CASAC advised were most useful to consider in identifying the PM 2.5 concentrations most influential in generating the health effect estimates reported in the epidemiological studies. 40 Consistent with CASAC advice, the most relevant information was the distribution of health events (e.g., d eaths, hospitalizations) occurring within a study population in relation to the distribution of PM 2.5 concentrations. However, in recognizing that access to health event data can be restricted, the Policy Assessment also considered the number of study part icipants within each study area as an appropriate surrogate for health event data. The Policy Assessment recognize d that an approach considering analyses of confidence intervals around concentration

- response functions wa s intrinsically related
to an approach that consider ed different distributional statistics. Both of these approaches could be employed to understand the broader distribution of PM 2.5 concentrations which correspond to the health events reported in epidemiological

40 The second draft Policy Assessment focused on the distributions of ambient P M 2.5 concentrations and associated population data across areas included in several multi

city studies for which such data were available in seeking to identify the most influential range of concentrations (U.S. EPA, 2010f, section 2.3.4.1). In its review of the second draft Policy Assessment, CASAC advised that it “would be preferable to have information on the concentrations that were most influential in generating the health effect estimates in individual studies” (Samet, 2010d, p.2). Therefore, in the f inal Policy Assessment, the EPA considered population

- level data (i.e., area

- specific health event data and study area population data) along with corresponding PM 2.5 concentrations to generate a cumulative distribution of the population

- level data relativ e to long

- term mean PM 2.5 concentrations to determine the most influential part of the air quality distribution (U.S. EPA, 2011a, Figure 2

- 7 and associated text).

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Page 172 of 423 studies. In applying t hese approaches, the Policy Assessment, consistent with CASAC advice (Samet, 2010d, p.3), considered PM 2.5 concentrations from long

- and short

- term PM 2.5 exposure studies using composite monitor distributions. In reaching staff conclusions on alternative standard levels that were appropriate to consider, the Policy Assessment also included a broader consideration of the uncertainties and limitations of the current scientific evidence. Most notably, these uncertainties are related to the heterogeneity obser ved in the epidemiological studies in the eastern versus western parts of the U.S., the relative toxicity of PM 2.5 components, and the potential role of co

- pollutants ( U.S. EPA, 2011a, pp. 2

- 25 to 2

- 26). The limitations and uncertainties associated with th e currently available scientific evidence, including the availability of fewer studies toward the lower range of alternative annual standard levels being considered in this proposal, are summarized in section III.B below and further discussed in section II I.B.2 of the propos al

. The Policy Assessment recognized that the level of protection afforded by the NAAQS relies both on the level and the form of the standard. The Policy Assessment concluded that a policy approach that used data based on composite monit or distributions to identify alternative standard levels, and then compared those levels to concentrations at maximum monitors to determine whether an area meets a given standard, inherently has the potential to build in some margin of safety ( U.S. EPA,

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Page 173 of 423 20 11a, p. 2

- 14). 41 This conclusion was consistent with CASAC’s comments on the second draft Policy Assessment , in which CASAC expressed its preference for focusing on an approach using composite monitor distributions “because of its stability, and for the add itional margin of safety it provides” when “compared to the maximum monitor perspective” (Samet, et al., 2010d, pp. 2 to 3). In reaching staff conclusions on alternative 24

- hour standard levels that are appropriate to consider for setting a 24

- hour standa rd intended to supplement the protection afforded by a generally controlling annual standard, the Policy Assessment considered currently available short

- term PM 2.5 exposure studies. The evidence from these studies informed our understanding of the protecti on afforded by the suite of standards against effects associated with short

- term exposures. In considering the short

- term exposure studies, the Policy Assessment evaluated both the distributions of
24

- hour PM 2.5 concentrations, with a focus on the 98 th per centile concentrations (to the extent such data were available) to match the form of the current 24

- hour PM 2.5

41 Statistical metrics (e.g., means) based on composite monitor distributions may be identical to or below the same statistical metrics based on maximum monitor distributions. For example, some areas may have only one monitor, in which case the composite and maximum monitor distributions will be identical in those areas. Other areas may have multip le monitors that may be very close to the monitor measuring the highest concentrations, in which case the composite and maximum monitor distributions could be similar in those areas. As noted in Hassett

- Sipple et al. (2010), for studies involving a large n umber of areas, the composite and maximum concentrations are generally within 5 percent of each other (77 FR 38905, fn. 30). Still other areas may have multiple monitors that may be separately impacted by local sources in which case the composite and maxim um monitor distributions could be quite different (U.S. EPA, 2011a, p. 2

- 14). See further discussion of this issue in section III.E.4.c.i below.

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Page 174 of 423 standard, as well as the long

- term mean PM 2.5 concentrations reported in these studies. In addition to considering the epidemiological evidence, the Policy Assessment also considered air quality information based on county

- level 24

- hour and annual design values 42 to understand the policy implications of the alternative standard levels supported by the underlying science. In particular, the Policy Assessment considered the extent to which different combinations of alternative annual and 24

- hour standards would support the policy goal of focusing on a ge nerally controlling annual standard in conjunction with a 24

- hour standard that would provide supplemental protection. In so doing, the Policy Assessment discussed the roles that each standard might be expected to play in the protection afforded by alterna tive suites of standards. Beyond these evidence

- based considerations, the Policy Assessment also considered the quantitative risk estimates and the key observations presented in the Risk Assessment. This assessment included an evaluation of 15 urban case s tudy areas and estimated risk associated with a number of health endpoints associated with long

and short

- term PM 2.5 exposures ( U.S. EPA, 2010a). As part of the risk

- based considerations, the Policy Assessment considered estimates of the magnitude of PM 2. 5 - related risks associated with recent air quality levels and air quality simulated to just meet the current and alternative suites of standards using alternative simulation approaches. The Policy Assessment also characterized the risk reductions, relative to the risks remaining upon just meeting the current standards, associated with just meeting

42 Design values are the metrics (i.e., statistics) that are compared to the NAAQS levels to determine complianc e.

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Page 175 of 423 alternative suites of standards. In so doing, the Policy Assessment recognized the uncertainties inherent in such risk estimates, and took such uncertainties into account by considering the sensitivity of the “core” risk estimates to alternative assumptions and methods likely to have substantial impact on the estimates. In addition, the Policy
Assessment considered additional analyses characterizing the representat iveness of the urban study areas within a broader national context to understand the roles that the annual and 24

- hour standards may play in affording protection against effects related to both long

- and short

- term PM 2.5 exposures. Based on the approach di scussed above, the Policy Assessment reached conclusions related to the primary PM 2.5 standards that reflected an understanding of both evidence

- based and risk

- based considerations to inform two overarching questions related to: (1) the adequacy of the cur rent suite of PM 2.5 standards and (2) revisions to the standards that were appropriate to consider in this review to protect against health effects associated with both long

- and short

- term exposures to fine particles. When evaluating the health protection afforded by the current or any alternative suites of standards considered, the Policy Assessment took into account the four basic elements of the NAAQS: the indicator, averaging time, form, and level. The general approach for reviewing the primary PM 2.5 s tandards described above provided a comprehensive basis that helped to inform the Administrator’s judgments in reaching her proposed and final decisions to revise the current suite of primary fine

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Page 176 of 423 particle NAAQS and in responding to the remand of the 2006 primary annual PM 2.5 standard.
B. Overview of Health Effects Evidence This section outlines the key information presented in section III.B of the proposal (77 FR 38906 to 38911, June 29, 2012) and discussed more fully in the Integrated Science Assessment (Cha pters 2, 4, 5, 6, 7, and 8) and the Policy Assessment (Chapter 2) related to health effects associated with fine particle exposures. Section III.B. of the proposal discusses available information on the health effects associated with exposures to PM 2.5 , in cluding the nature of such health effects (section III.B.1) and associated limitations and uncertainties (section III.B.2), at

- risk populations (section III.B.3), and potential PM 2.5 - related impacts on public health (section III.B.4). As was true in the la st two reviews, evidence from epidemiologic al , controlled human exposure and animal toxicological studies played a key role in the Integrated Science Assessment ’s evaluation of the scientific evidence. The 2006 PM NAAQS review concluded that there was “st rong epidemiological evidence” for linking long

- term PM 2.5 exposures with cardiovascular

- related and lung cancer mortality and respiratory

- related morbidity and for linking short

- term PM 2.5 exposures with cardiovascular

- related and respiratory

- related mort ality and morbidity ( U.S. EPA, 2004, p. 9

- 46; U.S. EPA, 2005, p. 5

- 4). Overall, the evidence from epidemiological, toxicological, and controlled human exposure studies supported “likely causal associations” between PM 2.5 and both mortality and morbidity fr om

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Page 177 of 423 cardiovascular and respiratory diseases, based on “an assessment of strength, robustness, and consistency in results” ( U.S. EPA, 2004, p. 9

- 48). 43 In this review, based on the expanded body of evidence, the EPA finds that: (1) In looking across the extensive new scientific evidence available in this review, our overall understanding of health effects associated with fine particle exposures has been greatly expanded. The currently available evidence is largely consistent with evi dence available in the last review and substantially strengthens what is known about the effects associated with fine particle exposures. (2) A number of large multi

- city epidemiological studies have been conducted throughout the U.S., including extended anal yses of long

- term exposure studies that were important to inform decision

- making in the last review. The body of currently available scientific evidence has also been expanded greatly by the publication of a number of new multi

- city, time

- series studies th at have used uniform methodologies to investigate the effects of short

- term PM 2.5 exposures on public health. This body of evidence provides a more expansive data base and considers multiple locations representing varying regions and seasons that provide e vidence of the influence of different air pollution mixes on PM 2.5 - associated health effects. These studies provide more precise estimates of the magnitude of effects associated with short

- term PM 2.5 exposure than most smaller

- scale single

- city studies tha t were more commonly available in the last review. These studies have reported consistent increases in morbidity and/or premature mortality related to ambient PM 2.5 concentrations, with the strongest evidence reported for cardiovascular

- related effects. (3) In addition, the findings of new toxicological and controlled human exposure studies greatly expand and provide stronger support for a number of potential biologic al mechanisms or pathways for cardiovascular and respiratory effects associated with long

- and short

- term PM exposures. These studies provide

43 The term “likely causal association” was used in the 2004 Criteria Document to summarize the strength of the available evidence available in the last review for PM 2.5 . However, this terminology was not based on a formal framework for evaluating eviden ce for inferring causation. Since the last review, the EPA has developed a more formal framework for reaching causal determinations with standardized language to express evaluation of the evidence (U.S. EPA, 2009a, section 1.5).

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Page 178 of 423 coherence and biological plausibility for the effects observed in epidemiological studies. (4) Using a more formal framework for reaching causal determinations than used in prior reviews , 44 the EPA concludes that a causal relationship exists between both long

- and short

- term exposures to PM 2.5 and premature mortality and cardiovascular effects and a likely causal relationship exists between long

- and short

- term PM 2.5 exposures and respiratory effects. Further, there is evidence suggestive of a causal relationship between long

- term PM 2.5 exposures and other health effects, including developmental and reproductive effects (e.g., low birth weight, infant mortality) and carcinogenic, mutagenic, and genotoxic effects (e.g ., lung cancer mortality). 45 (5) The newly available evidence significantly strengthens the link between long

and short

- term exposure to PM 2.5 and premature mortality, while providing indications that the magnitude of the PM 2.5 - mortality association with long

- term exposures may be larger than previously estimated. The strongest evidence comes from recent studies investigating long

- term exposure to PM 2.5 and cardiovascular

- related mortality. The evidence supporting a causal relationship between long

- term PM 2.5 exposure and mortality also includes consideration of new studies that demonstrated an improvement in community health following reductions in ambient fine particles.

44 The causal framework draw s upon the assessment and integration of evidence from across epidemiological, controlled human exposure, and toxicological studies, and the related uncertainties that ultimately influence our understanding of the evidence. This framework employs a five

- le vel hierarchy that classifies the overall weight of evidence and causality using the following categorizations: causal relationship, likely to be causal relationship, suggestive of a causal relationship, inadequate to infer a causal relationship, and not l ikely to be a causal relationship (U.S. EPA, 2009a, Table 1

- 3). The development of the causal framework reflects considerable input from CASAC and the public, with CASAC concluding that, “The five

- level classification of strength of evidence for causal inf erence has been systemically applied [for PM]; 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 ISAs” (Samet, 2009f, p. 1). 45 These causal infere nces are based not only on the more expansive epidemiological evidence available in this review but also reflect consideration of important progress that has been made to advance our understanding of a number of potential biologic modes of action or pathwa ys for PM

- related cardiovascular and respiratory effects (U.S. EPA, 2009a, chapter 5).

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Page 179 of 423 (6) Several new studies have examined the association between cardiovascular effects and long

- term PM 2.5 exposures in multi

- city studies conducted in the U.S. and Europe. While studies were not available in the last review with regard to long

- term exposure and cardiovascular

- related morbidity, recent studies have provided new evidence linking long

- term exposure to PM 2.5 with an array of cardiovascular effects such as heart attacks, congestive heart failure, stroke, and mortality. This evidence is coherent with studies of short

- term exposure to PM 2.5 that have observed associations with a continuum of effects ranging from subtle changes in indicators of cardiovascular health to serious clinical events, such as increased hospitalizations and emergency department visits due to cardiovascular disease and cardiovascular mortality. (7) Extended analyses of st udies available in the last review as well as new epidemiological studies conducted in the U.S. and abroad provide stronger evidence of respiratory

- related morbidity effects associated with long

- term PM 2.5 exposure. The strongest evidence for respiratory

- r elated effects is from studies that evaluated decrements in lung function growth, increased respiratory symptoms, and asthma development. The strongest evidence from short

- term PM 2.5 exposure studies has been observed for increased respiratory

- related emer gency department visits and hospital admissions for chronic obstructive pulmonary disease (COPD) and respiratory infections. (8) The body of scientific evidence is somewhat expanded from the 2006 review but is still limited with respect to associations between long

- term PM 2.5 exposures and developmental and reproductive effects as well as cancer, mutagenic, and genotoxic effects. The strongest evidence for an association between PM 2.5 and developmental and reproductive effects comes from epidemiological studies of low birth weight and infant mortality, especially due to respiratory causes during the post

- neonatal period (i.e., 1 month

- 12 months of age). With regard to cancer effects, “[m]ultiple epidemiologic studies have shown a consistent positive asso ciation between PM 2.5 and lung cancer mortality, but studies have generally not reported associations between PM 2.5 and lung cancer incidence” (U.S. EPA 2009a p. 2

- 13 )

. (9) Efforts to evaluate the relationships between PM composition and health effects contin ue to evolve. While many constituents of PM 2.5 can be linked with differing health effects, the evidence is not yet sufficient to allow differentiation of those constituents or sources that may be more closely related to specific health outcomes nor to exclude any individual component or group of comp onents associated with any source categories from the fine particle mixture of concern.

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Page 180 of 423 (10) Specific groups within the general population are at increased risk for experiencing adverse health effects related to PM exposures . The currently available evidence ex pands our understanding of previously identified at

- risk populations (i.e., children, older adults, and individuals with pre

- existing heart and lung disease) and supports the identification of additional at

- risk populations (e.g., persons with lower socioe conomic status, genetic differences). Evidence for PM

- related effects in these at

- risk populations has expanded and is stronger than previously observed. There is emerging, though still limited, evidence for additional potentially at

- risk populations, such as those with diabetes, people who are obese, pregnant women, and the developing fetus. (11) The population potentially affected by PM 2.5 is large. In addition, large subgroups of the U.S. population have been identified as at

- risk populations. While individua l effect estimates from epidemiological studies may be small in size, the public health impact of the mortality and morbidity associations can be quite large given the extent of exposure. Taken together, this suggests that exposure to ambient PM 2.5 concent rations can have substantial public health impacts. (12) While the currently available scientific evidence is stronger and more consistent than in previous reviews, providing a strong basis for decision making in this review, the EPA recognizes that important uncertainties and limitations in the health effects evidence remain. Epidemiological studies evaluating health effects associated with long

- and short

- term PM 2.5 exposures have reported heterogeneity in responses between cities and geographic regions withi n the U.S. This heterogeneity may be attributed, in part, to differences in the fine particle composition or related to exposure measurement error, which can introduce bias and increased uncertainty in associated health effect estimates. Variability in the associations observed across PM 2.5 epidemiological studies may be due in part to exposure error related to measurement

- related issues, the use of central fixed

- site monitors to represent population exposure to PM 2.5 , models used in lieu of or to supplemen t ambient measurements, and our limited understanding of factors that may influence exposures (e.g., topography, the built environment, weather, source characteristics, ventilation usage, personal activity patterns, photochemistry). In addition, where PM 2. 5 and other pollutants (e.g., ozone, nitrogen dioxide, and carbon monoxide) are correlated, it can be difficult to distinguish the effects of the various pollutants in the ambient mixture (i.e., co

- pollutant confounding). 46

46 A copollutant meets the criteria for potential confounding in PM

- health associations if: (1) it is a potential risk factor for the health effect under study; (2) it is correlated

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Page 181 of 423 While uncertainties and limitati ons still remain in the available health effects evidence, the Administrator judges the currently available scientific data base to be stronger and more consistent than in previous reviews providing a strong basis for decision making in this review.
C. Overv iew of Quantitative Characterization of Health Risks In addition to a comprehensive evaluation of the health effects evidence available in this review, the EPA conducted an expanded quantitative risk assessment for selected health endpoints to provide addi tional information and insights to inform decisions on the primary PM 2.5 NAAQS. 47 As discussed in section III.C of the proposal, the approach used to develop quantitative risk estimates associated with PM 2.5 exposures was built on the approach used and less ons learned in the last review and focused on improving the characterization of the overall confidence in the risk estimates, including related uncertainties, by incorporating a number of enhancements, in terms of both the methods and data used in the anal yses. The goals of this quantitative risk assessment were largely the same as those articulated in the risk assessment conducted for the last review. These goals included: (1) to provide estimates of the potential magnitude of premature mortality and/or
with PM; and (3) it does not act as an intermediate step in the pathway between PM exposure and the health effect under study (U.S. EPA, 2004, p. 8

- 10). 47 The quantitative risk assessment conducted for this review is more fully described and presented in the Risk Assessment (U.S. EPA, 2010a) and summarized in detail in the Policy Assessment (U.S. EPA, 2011a, sections 2.2.2. and 2.3.4.2). The scope and metho dology for this risk assessment were developed over the last few years with considerable input from CASAC and the public as described in section II.B.3 above

.

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Page 182 of 423 s elected morbidity effects in the population associated with recent ambient levels of
PM 2.5 and with simulating just meeting the current and alternative suites of PM 2.5 standards in 15 selected urban study areas , 48 including, where data were available, consideration of impacts on at

- risk populations; (2) to develop a better understanding of the influence of various inputs and assumptions on the risk estimates to more clearly differentiate among alternative suites of standards; and (3) to gain insights into the distribution of risks and patterns of risk reductions and the variability and uncertainties in those risk estimates. In addition, the quantitative risk assessment included nationwide estimates of the potential magnitude of premature mortality associated with long

- term exposure to recent ambient PM 2.5 concentrations to more broadly characterize this risk on a national scale and to support the interpretation of the more detailed risk estimates generated for select ed urban study areas. The expanded and updated risk assessment conducted in this review included estimates of risk for: (1) all

- cause, ischemic heart disease

- related, cardiopulmonary

related, and lung cancer

- related mortality associated with long

- term PM 2 .5 exposure; (2)

48 The Risk Assessment concluded that these 15 urban study areas were generally representative of urban areas in the U.S. likely to experience relatively elevated levels of risk related to ambient PM 2.5 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 representativeness analysis also showed that the 15 urban study areas do not capture areas with the highest baseline morality risks or the oldest populations (both of which can result in higher PM 2.5 - related mortality estimates). Howeve r, some of the areas with the highest values for these attributes had relatively low PM 2.5 concentrations (e.g., urban areas in Florida) and, consequently, the Risk Assessment concluded failure to include these areas in the set of urban study areas was unl ikely to exclude high PM 2.5 - risk locations (U.S. EPA, 2010a, section 4.4.1).

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Page 183 of 423 non - accidental, cardiovascular

- related, and respiratory

- related mortality associated with short

- term PM 2.5 exposure; and (3) cardiovascular

- related and respiratory

- related hospital admissions and asthma

- related emergency department visits associated with short

- term PM 2.5 exposure. 49
The Risk Assessment included a core set of risk estimates supplemented by an alternative set of risk results generated using single

- factor and multi

- factor sensitivity analyses. The core set of risk estimates wa s developed using the combination of modeling elements and input data sets identified in the Risk Assessment as having higher confidence relative to inputs used in the sensitivity analyses. The results of the sensitivity analyses provided information to ev aluate and rank the potential impacts of key sources of uncertainty on the core risk estimates. In addition, the sensitivity analyses represented a set of reasonable alternatives to the core set of risk estimates that fell within an overall set of plausibl e risk estimates surrounding the core estimates. The EPA recognized that there were many sources of variability and uncertainty inherent in the inputs to its quantitative risk assessment. 50 The design of the risk assessment included a number of elements to address these issues in order to increase the overall confidence in the risk estimates generated for the 15 urban study areas,

49 The evidence available for these selected health effect endpoints generally focused on the entire population, although some information was available to support analyses that co nsidered differences in estimated risk for at

- risk populations including older adults and persons with pre

- existing cardiovascular and respiratory diseases. 50 Variability refers to the heterogeneity of a variable of interest within a population or across d ifferent populations. Uncertainty refers to the lack of knowledge regarding the actual values of inputs to an analysis (U.S. EPA, 2010a, p. 3

- 63).

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Page 184 of 423 including using guidance from the World Health Organization (WHO, 2008) as a framework for characterizing uncertainty in the ana lyses. 51 With respect to the sources of variability, the Risk Assessment considered those that contributed to differences in risk across urban study areas, but did not directly affect the degree of risk reduction associated with the simulation of just meet ing current or alternative standard levels (e.g., differences in baseline incidence rates, demographics and population behavior). The Risk Assessment also focused on factors that not only introduced variability into risk estimates across study areas, but a lso played an important role in determining the magnitude of risk reductions upon simulation of just meeting current or alternative standard levels (e.g., peak

- to
- mean ratios of ambient PM 2.5 concentrations within individual urban study areas and the
natur e of the rollback approach used to simulate just meeting the current or alternative standards). Key sources of potential variability that were likely to affect population risks included the following : (1) intra

- urban variability in ambient PM 2.5 concentrat ions, including PM 2.5 composition; (2) variability in the patterns of reductions in PM 2.5 concentrations associated with different rollback approaches when simulating just meeting the current or alternative standards; co

- pollutant exposures; (3) factors re lated to demographic and socioeconomic status; (4) behavioral differences across urban study areas (e.g., time spent outdoors); (5) baseline incidence rates; and (6) longer

- term

51 The extent to which key sources of potential variability were (or were not) fully captured in the design o f the risk assessment are discussed in section 3.5.2 of the Risk Assessment (U.S. EPA, 2010a, pp. 3

- 67 to 3

- 69).

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Page 185 of 423 temporal variability in ambient PM 2.5 concentrations reflecting meteorological trends as well as future changes in the mix of PM 2.5 sources, including changes in air quality related to future regulatory actions. With regard to uncertainties, single and multi

- factor sensitivity analyses were combined with a qualitative analysis to a ssess the impact of potential sources of uncertainty on the core risk estimates. Key sources of uncertainty included: (1) characterizing intra

- urban population exposure in the context of epidemiolog ical studies linking PM 2.5 to specific health effects; (2) statistical fit of the concentration

- response functions for short

- term exposure
- related health endpoints; (3) shape of the
concentration

- response functions; (4) specifying the appropriate lag structure for short

term exposure studies; (5) transferability of concentration

- response functions from study locations to urban study area locations for long

- term exposure
- related health endpoints; (6) use of single

- city versus multi

- city studies in the derivation of concentration

- response functions; (7) impact of hi storical air quality on estimates of health risk associate with long

- term PM 2.5 exposures; and (8) potential variation in effect estimates reflecting compositional differences in PM 2.5 . Beyond characterizing uncertainty and variability, a number of design elements were included in the risk assessment to increase the overall confidence in the risk estimates generated for the 15 urban study areas ( U.S. EPA, 2011a, pp. 2

- 38 to 2

- 41). These elements included: (1) use of a deliberative process for specifying com ponents of the risk model that reflects consideration of the latest research on PM 2.5 exposure and

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Page 186 of 423 risk ( U.S. EPA, 2010a, section 5.1.1); (2) integration of key sources of variability into the design as well as the interpretation of risk estimates (U.S.EPA, 2010a, section 5.1.2); (3) assessment of the degree to which the urban study areas are representative of ar eas in the U.S. experiencing higher PM 2.5 - related risk (U.S.EPA, 2010a, section 5.1.3); and (4) identification and assessment of important sources of uncertainty and the impact of these uncertainties on the core risk estimates (U.S.EPA, 2010a, section 5.1. 4). Further, additional analyses examined potential bias and overall confidence in the risk estimates. Greater confidence is associated with risk estimates based on simulated annual mean
PM 2.5 concentrations that are within the region of the air quality di stribution used in deriving the concentration

- response functions where the bulk of the data reside (e.g., within one standard deviation around the long

- term mean PM 2.5 concentration) ( U.S. EPA, 2011a, p. 2

- 38). Key observations and insights from the PM 2.5 risk assessment, together with important caveats and limitations , were discussed in section III.C.3 of the proposal. In general, in considering the set of quantitative risk estimates and related uncertainties and limitations related to long

- and short

- term PM 2.5 exposure together with consideration of the health endpoints which could not be quantified, the Policy Assessment concluded this information provided strong evidence that risks estimated to remain upon simulating just meeting the current suite of PM 2.5 standards are important from a public health perspective, both in terms of severity and magnitude of effects. Patterns of increasing estimated risk reductions were generally observed as either the

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Page 187 of 423 annual or 24

- hour standard level, or both, were reduced over the ranges considered in the Risk Assessment. The magnitude of both long

- and short

- term exposure
- related risk estimated to remain upon just meeting the current suite of standards as well as alternative standard levels w as strongly associated with th e simulated change in annual mean PM 2.5 concentrations. Although long

- and short

- term exposure
- related mortality rates have similar patterns in terms of the subset of urban study areas experiencing risk reductions for the current suite of standard levels, the magnitude of risk remaining is higher for long

- term exposure
- related mortality and substantially lower for short

- term exposure
related mortality. Short

- term exposure
- related morbidity risk estimates w ere greater for cardiovascular

- related than respirat ory - related events and emergency department visits for asthma

- related events were significant: Furthermore, most of the aggregate risk associated with short

- term exposures was not primarily driven by the small number of days with PM 2.5 concentrations in th e upper tail of the air quality distribution, but rather by the large number of days with PM 2.5 concentrations at and around the mean of the distribution, that is, the 24

- hour average concentrations that are in the low

- to mid

range, well below the peak 24

- hour concentrations (U.S. EPA, 2011a, p. 2

- 3)

. With regard to characterizing estimates of PM 2.5 - related risk associated with simulation of alternative standards, the Policy Assessment recognized that greater overall confidence was associated with estimates of risk reduction than for estimates of absolute risk remaining ( U.S. EPA, 2011a, p. 2

- 94). Furthermore, the Policy Assessment

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Page 188 of 423 recognized that estimates of absolute risk remaining for each of the alternative standard levels considered, particularly in the context of long

- term exposure
- related mortality, may be underestimated 52 . In addition, the Policy Assessment observed that in considering the overall confidence associated with the quantitative analyses, the Risk Assessment recognized that: (1) substantial variability existed in the magnitude of risk remaining across urban study areas and (2) in general, higher confidence was associated with risk estimates based on PM 2.5 concentrations near the mean PM 2.5 concentrations in the underlying epidemiological stu dies providing the concentration

- response functions (e. g. , within one standard deviation of the mean PM 2.5 concentration reported). Furthermore, although the Risk Assessment estimated that the alternative
24

- hour standard levels considered (when controllin g) would result in additional estimated risk reductions beyond those estimated for alternative annual standard levels alone, these additional estimated reductions were highly variable. Conversely, the Risk Assessment recognized that alternative annual stan dard levels, when controlling, resulted in more consistent risk reductions across urban study areas, thereby potentially

52 Based on the consideration of both the qualitative and quantitative assessments of uncertainty, the Risk Assessment concluded that it is unli kely that the estimated risks are over - stated, particularly for premature mortality related to long

- term PM 2.5 exposures. In fact, the Policy Assessment and the Risk Assessment concluded that the core risk estimates for this category of health effects may well be biased low based on consideration of alternative model specifications evaluated in the sensitivity analyses (U.S. EPA, 2011a, p. 2

- 41; U.S. EPA, 2010a, p. 5

- 16; Figures 4

- 7 and 4

- 8). In addition, the Policy Assessment recognized that the currently available scientific information included evidence for a broader range of health endpoints and at

- risk populations beyond those included in the quantitative risk assessment, including decrements in lung function growth and respiratory symptoms in children as well as reproductive and developmental effects (U.S. EPA, 2011a, section 2.2.1).

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Page 189 of 423 providing a more consistent degree of public health protection ( U.S. EPA, 2010a, p. 5

- 17).
D. Conclusions on the Adequacy of the Current P rimary PM 2.5 Standards
1. Introduction The initial issue to be addressed in the current review of the primary PM 2.5 standards is whether, in view of the advances in scientific knowledge and other information reflected in the Integrated Science Assessment, the Risk Assessment, and the Policy Assessment, the existing standards should be retained or revised. In considering the adequacy of the current suite of PM 2.5 standards, the Administrator has considered the large body of evidence presented and assessed in the Integrated Science
Assessment ( U.S. EPA, 2009a), the quantitative assessment of risks, staff conclusions and associated rationales presented in the Policy Assessment , views expressed by CASAC, and public comments. The Administrator has taken into acco unt both evidence

and risk

- based considerations 53 in developing final conclusions on the adequacy of the current primary PM 2.5 standards.

53 Evidence

- based considerations include the assessment of epidemiological, toxicological, and controlled human exposure studies evaluating long

- or short

- term exposures to PM 2.5 , with supporting evidence related to dosimetry and potential pathways/modes of action, as well as the integration of evidence across each of these disciplines, as assessed in the Integrated Science Assessment (U.S. EPA, 2009a) and focus on the policy

- relevant considerations as discussed in section III.B above and in the Policy Assessment (U.S. EPA, 2011a, section 2.2.1). Risk

- based considerations draw from the results of the quantitative analyses presented in the Risk Assessment (U.S. EPA, 2010a) and focus on the policy

- relevant considerations as discussed in section III.C above and in the Policy Assessment (U.S. EPA, 2011a, section 2.2.2).

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Page 190 of 423 a. Evidence

- and Risk

- based Considerations in the Policy Assessment In considering the available epidemiologic al evid ence in this review, the Policy Assessment took a broader approach than was used in the last review. This approach reflected the more extensive and stronger body of evidence available since the last review on health effects related to both long

- and short

- term exposure to PM 2.5 . As discussed in section III.A.3 above, this broader approach focused on setting the annual standard as the “generally controlling” standard for lowering both short

- and long

- term
PM 2.5 concentrations and so providing requisite prote ction to public health . In conjunction with such an annual standard, this approach focused on setting the 24

- hour standard to provide supplemental protection against days with high peak PM 2.5 concentrations. In addressing the question whether the evidence now available in this review supports consideration of standards that are more protective than the current PM 2.5 standards, the Policy Assessment considered whether : (1) statistically significant health effects associations with long

- or short

- term exposur es to fine particles occur in areas that would likely have met the current PM 2.5 standards [ see American Trucking
Ass ociatio n , 283 F. 3d at 369, 376 (revision of level of PM NAAQS justified when health effects are observed in areas meeting the existing st andard) ] , and (2) associations with long

- term exposures to fine particles extend down to lower air quality concentrations than had previously been observed. With regard to associations observed in long

- term PM 2.5 exposure studies, the Policy Assessment rec ognized that extended follow

- up

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Page 191 of 423 analyses of the ACS and Harvard Six Cities studies provided consistent and stronger evidence of an association with mortality at lower air quality distributions than had previously been observed ( U.S. EPA, 2011a, pp. 2

- 31 to 2

- 32). The original and reanalysis of the ACS study reported positive and statistically significant effects associated with a long

- term mean PM 2.5 concentration of 18.2 μg/m 3 across 50 metropolitan areas for 1979 to 1983 (Pope et al., 1995; Krewski et al. , 2000). 54 In extended analyses, positive and statistically significant effects of approximately similar magnitude were associated with declining PM 2.5 concentrations, from an aggregate long

- term mean in 58 metropolitan areas of 21.2 μg/m 3 in the original monitoring period (1979 to 1983) to 14.0 μg/m 3 for 116 metropolitan areas in the most recent years evaluated (1999

- 2000), with an overall average across the two study periods in 51 metropolitan areas of 17.7 μg/m 3 (Pope et al., 2002; Krews ki et al., 2009). With regard to the Harvard Six Cities Study, the original and reanalysis reported positive and statistically significant effects associated with a long

- term mean PM 2.5 concentration of 18.0 μg/m 3 for 1980 to 1985 (Dockery et al., 1993; Kr ewski et al., 2000). In an extended follow

- up of this study, the aggregate long

- term mean concentration across all years evaluated was 16.4 μg/m 3 for
1980 to 1988 55 (Laden et al., 2006). In an additional analysis of the extended follow

- up of the Harvard Six Cities study, investigators reported that the concentration

- response

54 The study periods referred to in the Policy Assessment (U.S. EPA, 2011a) and in this final rule reflect the yea rs of air quality data that were included in the analyses, whereas the study periods identified in the Integrated Science Assessment (U.S. EPA, 2009a) reflect the years of health event data that were included. 55 Aggregate mean concentration provided by stu dy author (personal communication from Dr. Francine Laden, 2009).

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Page 192 of 423 relationship was linear and “clearly continuing below the level” of the current annual standard ( U.S. EPA, 2009a, p. 7

- 92; Schwartz et al., 2008). Cohort studies conducted since the las t review provided additional evidence of mortality associated with air quality distributions that are generally lower than those reported in the ACS and Harvard Six Cities studies, with effect estimates that were similar or, in some studies, significantly greater in magnitude than in the ACS and Harvard Six Cities studies (see also, section III.D.1.a of the proposal, 77 FR 38918 to 28919; U.S. EPA, 2011a, pp. 2

- 32 to 2

- 33). The Women’s Health Initiative (WHI) study reported positive and most often statistic ally significant associations between long

- term PM 2.5 exposure and cardiovascular

- related mortality as well as morbidity effects, with much larger relative risk estimates for mortality than in the ACS and Harvard Six Cities studies, at an aggregate long

- te rm mean PM 2.5 concentration of 12.9 μg/m 3 for 2000 (Miller et al., 2007). 56 Using the Medicare cohort, Eftim et al. (2008) reported somewhat higher effect estimates than in the ACS and Harvard Six Cities studies with aggregate long

- term mean concentrations of 13.6 μg/m 3 and 14.1 μg/m 3 , respectively, for 2000 to 2002. Zeger et al. (2008) reported associations between long

- term PM 2.5 exposure and mortality for the eastern region of the U.S. at an aggregated long

- term PM 2.5 median concentration

56 The Policy Assessment 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 dat a (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 con sidered (i.e., 1994 to 1998) (77 FR 38918, fn 62).

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Page 193 of 423 of 14.0 μg/m 3 , although no association was reported for the western region with an aggregate long

- term PM 2.5 median concentration of 13.1 μg/m 3 ( U.S. EPA, 2009a, p. 7

- 88). 57 Premature mortality in children reported in a national infant mortality study as well as mortalit y in a cystic fibrosis cohort including both children and adults reported positive but statistically nonsignificant effects associated with long

- term aggregate mean concentrations of 14.8 μg/m 3 and 13.7 μg/m 3 , respectively (Woodruff et al., 2008;
Goss et a l., 2004). With respect to respiratory morbidity effects associated with long

- term PM 2.5 exposure, the across

- city mean of 2

- week average PM 2.5 concentrations reported in the initial Southern California Children’s Health Study was approximately 15.1 μg/m 3 (Peters et al., 1999). These results were found to be consistent with results of cross

- sectional analyses of the 24

- Cities Study (Dockery et al., 1996; Raizenne et al., 1996), which reported a long

- term cross
- city mean PM 2.5 concentration of 14.5 μg/m 3

. 58 I n this review, extended analyses o f the Southern California Children’s Health Study provide stronger evidence of PM 2.5 - related respiratory effects, at lower air quality

57 Zeger et al. (2008) also reported positive and statistically significant effects for the central region, with an aggregate long

- term mean PM 2.5 concentration of 10.7 μg/m 3

. However, in contrast to the ea stern and western risk estimates, the central risk estimate increased with adjustment for COPD (used as a proxy for smoking status). Due to the potential for confounding bias influencing the risk estimate for the central region, the Policy Assessment did n ot focus on the results reported in the central region to inform the adequacy of the current suite of standards or alternative annual standard levels (U.S. EPA, 2011a, p. 2

- 32). 58 See American Farm Bureau Federation v. EPA , 559 F. 3d at 525 (noting the imp ortance of these studies, as well as EPA’s failure to properly take them into account).

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Page 194 of 423 concentrations than had previously been reported, with a four

- year aggregate mean concentration of 13.8 μg/m 3 across the 12 study communities (McConnell et al., 2003; Gauderman et al., 2004, U.S. EPA, 2009a, Figure 7

- 4). In also considering health effects for which the Integrated Science Assessment concluded evidence was suggestive of a causal relationship, the Policy Assessment noted a limited number of birth outcome studies that reported positive and statistically significant effects related to aggregate long

- term mean PM 2.5 concentrations down to approximately 12 μg/m 3 ( U.S. EPA, 201 1a, p. 2

- 33). Collectively, the Policy Assessment concluded that currently available evidence provided support for associations between long

- term PM 2.5 exposure and mortality and morbidity effects that extend to distributions of PM 2.5 concentrations that a re lower than those that had previously been associated with such effects, with aggregate long

term mean PM 2.5 concentrations extending to well below the level of the current annual standard. The Policy Assessment also considered the long

- term mean PM 2.5 c oncentrations in short

- term exposure studies in assessing the appropriateness of the level of the current annual standard. See American Farm Bureau Federation v. EPA , 559 F. 3d at 522,
523

- 24 (remanding 2006 standard because the EPA had not adequately expl ained its choice not to consider long

- term means of short

- term exposure studies in assessing adequacy of primary annual PM 2.5 standard). In light of the mixed findings reported in single

- city, short

- term exposure studies, the Policy Assessment placed compa ratively

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Page 195 of 423 greater weight on the results from multi

- city studies in considering the adequacy of the current suite of standards ( U.S. EPA, 2011a, pp. 2

- 34 to 2

- 35). With regard to associations reported in short

- term PM 2.5 exposure studies, the Policy Assessm ent recognized that long

- term mean concentrations reported in new multi

- city U.S. and Canadian studies provided evidence of associations between short

term PM 2.5 exposure and mortality at similar air quality distributions t o those that had previously been observed in an 8

- cities Canadian study (Burnett and Goldberg, 2003; aggregate long

- term mean PM 2.5 concentration of 13.3 μg/m 3 ). In a multi

- city time

series analysis of 112 U.S. cities, Zanobetti and Schwartz (2009) reported a positive and statistically si gnificant association with all

- cause, cardiovascular

- related (e.g., heart attacks, stroke), and respiratory

- related mortality and short

- term PM 2.5 exposure, in which the aggregate long

- term mean PM 2.5 concentration was 13.2 μg/m 3 ( U.S. EPA, 2009a, Figure 6

- 24). Furthermore, city

- specific effect estimates indicated the association between short

- term exposure to PM 2.5 and total mortality and cardiovascular

- and respiratory

- related mortality was consistently positive for an overwhelming majority (99 percent) o f the 112 cities across a wide range of air quality concentrations (long

- term mean concentrations ranging from 6.6 μg/m 3 to 24.7 μg/m 3 ; U.S. EPA, 2009a, Figure 6

- 24, p. 6

- 178 to 179). The EPA staff noted that for all

- cause mortality, city

- specific effect

e stimates were statistically significant for 55 percent of the 112 cities, with long

- term city

- mean PM 2.5 concentrations ranging from 7.8 μg/m 3 to 18.7 μg/m 3 and 24

- hour

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Page 196 of 423 PM 2.5 city

- mean 98 th percentile concentrations ranging from 18.4 to 64.9 μg/m 3 (personal communication with Dr. Antonella Zanobetti, 2009). 59 With regard to cardiovascular and respiratory morbidity effects, in the first analysis of the Medicare cohort conducted by Dominici et al. (2006a) across 204 U.S. counties, investigators repor ted a statistically significant association with hospitalizations for cardiovascular and respiratory diseases and short

- term PM 2.5 exposure, in which the aggregate long

- term mean PM 2.5 concentration was 13.4 μg/m 3

. Furthermore, a sub

- analysis restricted to days with 24

- hour average concentrations of
PM 2.5 at or below 35 μg/m 3 indicated that, in spite of a reduced statistical power from a smaller number of study days, statistically significant associations were still observed between short

- term exposure to P M 2.5 and hospital admissions for cardiovascular and respiratory diseases (Dominici, 2006b). 60 In an extended analysis of this cohort, Bell et al (2008) reported a positive and statistically significant increase in cardiovascular hospitalizations associated with short

- term PM 2.5 exposure, in which the aggregate long

term mean PM 2.5 concentration was 12.9 μg/m 3 . These results, along with the observation that approximately 50 percent of the 204 county

- specific mean 98 th

59 Single

- city Bayes

- adjusted effect estimates for the 112 cities analyzed in Zanobetti and Schwartz (2009) were provided by the study authors (personal communication wi th Dr. Antonella Zanobetti, 2009; see also U.S. EPA, 2009a, Figure 6

- 24). 60 This sub

- analysis was not included in the original publication (Dominici et al., 2006a). The study authors provided sub

- analysis results for the Administrator’s consideration as 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, this study is part of the basis for the conclusion that there is no evidence suggesti ng that risks associated with long

- term exposures are likely to be disproportionately driven by peak 24

- hour concentrations.

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Page 197 of 423 percentile PM 2.5 concentrations in the st udy aggregated across all years were below the
24

- hour standard of 35 μg/m 3 , not only indicated that effects are occurring in areas that would meet the current standards but also suggested that the overall health effects observed across the U.S. are not pr imarily driven by the higher end of the PM 2.5 air quality distribution (Bell, 2009a, personal communication from Dr. Michelle Bell regarding air quality data for Bell et al., 2008 and Dominici et al., 2006a). Collectively, the Policy Assessment concluded that the findings from short

- term
PM 2.5 exposure studies provided evidence of PM 2.5 - associated health effects occurring in areas that would likely have met the current suite of PM 2.5 standards ( U.S. EPA, 2011a, p. 2

- 35). These findings were further bolster ed by evidence of statistically significant
PM 2.5 - related health effects occurring in analyses restricted to days in which 24

- hour average PM 2.5 concentrations were below 35 μg/m 3 (Dominici, 2006b). In evaluating the currently available scientific evidenc e, as summarized in section III.B of the proposal, the Policy Assessment first concluded that there was stronger and more consistent and coherent support for associations between long

- and short

- term
PM 2.5 exposures and a broad range of health outcomes tha n was available in the last review, providing the basis for fine particle standards at least as protective as the
current PM 2.5 standards ( U.S. EPA, 2011a, p. 2

- 26). Having reached this initial conclusion, the Policy Assessment addressed the question of whether the available evidence supported consideration of standards that were more protective than the current standards. In so doing, the Policy Assessment considered whether there was now

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Page 198 of 423 evidence that health effect associations have been observed in areas that likely met the current suite of PM 2.5 standards. As discussed above, long

- and short

- term PM 2.5 exposure studies provided evidence of ass ociations with mortality and cardiovascular and respiratory effects both at lower ambient PM 2.5 concentrations than had been observed in the previous review and at concentrations allowed by the current standards ( U.S. EPA, 2011a, p. 2

- 35). In reviewing th is information, the Policy Assessment recognized that important limitations and uncertainties associated with this expanded body of scientific evidence, as discussed in section III.B.2 of the proposal, needed to be carefully considered in determining the w eight to be placed on the body of studies available in this review. Taking these limitations and uncertainties into consideration, the Policy Assessment concluded that the currently available evidence clearly calls into question whether the current suite o f primary PM 2.5 standards protects public health with an adequate margin of safety from effects associated with long

- and short

- term exposures. Furthermore, the Policy Assessment concluded this evidence provides strong support for considering fine particle standards that would afford increased protection beyond that afforded by the current standards ( U.S. EPA, 2011a, p. 2

- 35).

In addition to evidence

- based consideration, the Policy Assessment also considered the extent to which health risks estimated to occ ur upon simulating just meeting the current PM 2.5 standards may be judged to be important from a public health perspective, taking into account key uncertainties associated with the

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Page 199 of 423 quantitative health risk estimates. In so doing, the Policy Assessment fir st noted that the quantitative risk assessment addresses: (1) the core PM 2.5 - related risk estimates; (2) the related uncertainty and sensitivity analyses, including additional sets of reasonable risk estimates generated to supplement the core analysis; (3) an assessment of the representativeness of the urban study areas within a national context; 61 and (4) consideration of patterns in design values and air quality monitoring data to inform interpretation of the risk estimates, as discussed in section III.C a bove. In considering the health risks estimated to remain upon simulation of just meeting the current suite of standards and considering both the qualitative and quantitative assessment of uncertainty completed as part of the assessment, the Policy
Assess ment concluded these risks are important from a public health standpoint and provided strong support for consideration of alternative standards that would provide increased protection beyond that afforded by the current PM 2.5 ( U.S. EPA, 2011a, pp. 2

- 47 to 2

- 48). This conclusion reflected consideration of both the severity and the magnitude of the effects. For example, the Risk Assessment indicated the possibility that premature deaths related to ischemic heart disease associated with long

- term PM 2.5 exposur e alone would likely be on the order of thousands of deaths per year in the 15

61 Based on analyses of the representativeness of the 15 urban study areas in the broader national context, the Policy Assessment co ncludes that these study areas are generally representative of urban areas in the U.S. likely to experience relatively elevated levels of risk related to ambient PM 2.5 exposures (U.S. EPA, 2011a, p. 2

- 42).

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Page 200 of 423 urban study areas upon simulating just meeting the current standards 62 ( U.S. EPA, 2011a, pp. 2

- 46 to 2

- 47). Moreover, additional risks were anticipated for premature mortality re lated to cardiopulmonary effects and lung cancer associated with long

- term PM 2.5 exposure as well as mortality and cardiovascular

- and respiratory

- related morbidity effects (e.g., hospital admissions, emergency department visits) associated with short

- term PM 2.5 exposures. Based on the consideration of both qualitative and quantitative assessments of uncertainty completed as part of the quantitative risk assessment, the Risk Assessment concluded that it was unlikely that the estimated risks

are over - stated, particularly for mortality related to long

- term PM 2.5 exposure, and may well be biased low based on consideration of alternative model specifications evaluated in the sensitivity analyses ( U.S. EPA, 2010a, p. 5

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

- 41). Furthermore, the currently available scientific information summarized in section III.B of the proposal provided evidence for a broader range of health endpoints and at

- risk populations beyond those included in the quantitative risk assessment ( U.S. EPA, 2011a, p. 2

- 47 ).

b. CASAC Advice The CASAC, based on its review of drafts of the Integrated Science Assessment, the Risk Assessment, and the Policy Assessment, provided an array of advice both with regard to interpreting the scientific evidence and quantitative risk ass essment, as well as

62 Premature mortality for all causes attributed t o PM 2.5 exposure was estimated to be on the order of tens of thousands of deaths per year on a national scale based on 2005 air quality data (U.S. EPA, 2010a, Appendix G, Table G

- 1).

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Page 201 of 423 with regard to consideration of the adequacy of the current PM 2.5 standards (Samet, 2009a b,c,d,e,f; Samet 2010a,b,c,d). With regard to the adequacy of the current standards, CASAC concluded that the “currently available information cle arly calls into question the adequacy of the current standards” (Samet, 2010d, p. i) and that the current standards are “not protective” (Samet, 2010d, p. 1). Further, in commenting on the first draft Policy Assessment, CASAC noted: With regard to the inte gration of evidence

- based and risk

- based considerations, CASAC concurs with EPA’s conclusion that the new data strengthens the evidence available on associations previously considered in the last round of the assessment of the PM 2.5 standard. CASAC also ag rees that there are significant public health consequences at the current levels of the standard that justify consideration of lowering the PM 2.5 NAAQS further (Samet, 2010c, p.12).

c. Administrator's Proposed Conclusions Concerning the Adequacy of the Current Primary PM 2.5 Standards At the time of the proposal, in considering the body of scientific evidence, the Administrator concluded there was stronger and more consistent and coheren t support for associations between long

- and short

- term PM 2.5 exposure and a broader range of health outcomes than was available in the last review, providing the basis for fine particle standards at least as protective as th e current PM 2.5 standards. In p articular, the Administrator recognized in section III.D.4 of the proposal that the Integrated Science
Assessment concluded that the results of epidemiological and experimental studies form a plausible and coherent data set that supports a causal relations hip between long

- and short

- term PM 2.5 exposures and mortality and cardiovascular effects and a likely causal relationship between long

- and short

- term PM 2.5 exposures and respiratory

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Page 202 of 423 effects. Furthermore, the Administrator reflected that effects had been observed at lower ambient PM 2.5 concentrations than what had been observed in the last review, including at ambient PM 2.5 concentrations in areas that likely met the current PM 2.5 NAAQS. With regard to the results of the quantitative risk assessment, the Administrator note d that the Risk Assessment conclude d that the risks estimated to remain upon simulation of just meeting the current standards we re important from a public health standpoint in terms of both the severity and magnitude of the effects. At the time of the proposal, in considering whether the current suite of PM 2.5 standards should be revised to provide requisite public health protection, the Administrator carefully co nsidered the staff conclusions and rationales presented in the Policy Assessment, the advice and recommendations from CASAC, and public comments to date on this issue. In so doing, the Administrator placed primary consideration on the evidence obtained fro m the epidemiological studies and provisionally found the evidence of serious health effects reported in long

- and short

- term exposure studies conducted in areas that would have met the current standards to be compelling, especially in light of the extent to which such studies are part of an overall pattern of positive and frequently statistically significant associations across a broad range of studies that collectively represent a strong and robust body of evidence. As discussed in the Integrated Science Assessment and Policy Assessment, the Administrator recognized that much progress has been made since the last review in addressing some of the key uncertainties that were important considerations in

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Page 203 of 423 establishing the current suite of PM 2.5 standards. For example, progress made since the last review provides increased confidence in the long

- and short

- term exposure studies as a basis for considering whether any revision of the annual standard is appropriate and increased confidence in the short

- term exposur e studies as a basis for considering whether any revision of the 24

- hour standard is appropriate. 63 Based on her consideration of these conclusions, as well as consideration of CASAC’s conclusion that the evidence and risk assessment clearly call ed into qu estion the adequacy of the public health protection provided by the current PM 2.5 NAAQS and public comments on the proposal, the Administrator provisionally concluded that the current primary PM 2.5 standards, taken together, we re not requisite to protect p ublic health with an adequate margin of safety and that revision wa s needed to provide increased public health protection. The Administrator provisionally concluded that the scientific evidence and information on risk provide d strong support for considerat ion of alternative standards that would provide increased public health protection beyond that afforded by the current PM 2.5 standards.
2. Comments on the Need for Revision This section addresses general comments based on relevant facts that either support or oppose any change to the current suite of primary PM 2.5 standards.

63 The EPA notes that this increased confidence in the long

- and short

- term associations generally reflects less uncertainty as to the likely causal nature of such associations, but does not address directly the question of the extent to which such associati ons remain toward the lower end of the range of ambient PM 2.5 concentrations. This question is central to the Agency’s evaluation of the relevant evidence to determine appropriate standards levels, as discussed below in section III.E.4.

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Page 204 of 423 Comments on specific long

- and short

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

- hour standards are addressed in section III.E.4 below . Many public comments asserted that the current
PM 2.5 standards are insufficient to protect public health with an adequate margin of safety and that revisions to the standards are therefore appropriate, indeed necessitated. Among those calling for revisi ons 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); major environmental groups such as the Clean Air Council, Clean Air Task Force, Earthjustice, Environmental Defense Fund (EDF), National Resources Defense Council (NRDC), an d Sierra Club; many environmental justice organizations as well as medical doctors, academic researchers, health professionals, and many private citizens. For example, the American Heart Association and other major national public health and medical organi zations stated that, “[o]ur organizations are keenly aware of the public health and medical threats from particulate matter” and called on the EPA to “significantly strengthen” both the annual and 24

- hour
PM 2.5 standards “to help us protect the health of o ur patients and our nation” (AHA et al., 2012, pp 1 and 13). AHA et al. and ALA et al., as well as a group of more than 350

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Page 205 of 423 physicians, environmental health researchers, and public health and medical professionals articulated similar comments on the availa ble evidence: Ample scientific evidence supports adopting tighter standards to protect the health of people who are most susceptible to the serious health effects of these pollutants. More than 10,000 peer

- reviewed scientific studies have been published si nce 1997 when EPA adopted the current annual standard. These studies validate and extend earlier epidemiologic research linking both acute and chronic fine particle pollution with serious morbidity and mortality. The newer research has also expanded our un derstanding of the range of health outcomes associated with PM and has identified adverse respiratory and cardiovascular health effects at lower exposure levels than previously reported. As discussed and interpreted in the EPA’s 2009 Integrated Science Ass essment for Particulate Matter, the new evidence reinforces already strong existing studies and supports the conclusion that PM 2.5 is causally associated with numerous adverse health effects in humans at exposure levels far below the current standard. Such a conclusion demands prompt action to protect human health. (AHA et al., 2012, pp. 1 to 2; ALA et al., pp. 4 to 5; similar comment submitted by Rom et al., 2012, p. 1). All of these medical and public health commenters stated that the current PM 2.5 standa rds 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 exp ressed 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 PM 2.5 standards supported revisi on of

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Page 206 of 423 the suite of current PM 2.5 standards, as did five s tate a ttorneys g eneral (Schneiderman et al., 2012) and the National Tribal Air Association (NTAA). These commenters based their views chiefly on the body of evidence and technical analyses presented and discussed in the Integrated Science Assessment, the Risk Assessment, and the Policy Assessment finding the available scientific information to be stronger and more compelling than in the last review. These commenters generally placed much weight on CASAC’s recommendation to revise the PM 2.5 standards to provide increased public health protection and on the EPA staff conclusions presented in the final Policy Assessment. Some of these commenters specifically mentioned extended analyses of seminal long

- term exposure studies

- the ACS (Krewski et al., 2009), Harvard Six Cities (Laden et al., 2006), and Southern California Children’s Health (Gauderman et al., 2004) studies. These commenters also highlighted the availability of additional long

- term exposure studies in this review, specifically a study of premature mortality in older adults (Eftim et al., 2008) and the WHI study of cardiovascular morbidity and mortality effects in women (Miller et al., 2007) providing stronger evidence of mortality and morbid ity effects associated with long

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

- risk populations. For example, some commenters asserted: Evidence during the last review showed clearly that the annual average standard needed to be much lower than the standard of 15 μg/m 3 that was first set in 1997. The evidence has only grown since then. Multiple, multi

- city studies over

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Page 207 of 423 long periods of time have shown clear evidence of premature death, card iovascular and respiratory harm as well as reproductive and developmental harm at contemporary concentrations far below the level of the current (annual) standard (ALA et al., 2012, p. 39; AHA et al., 2012, p. 10). These commenters also highlighted the av ailability of a number of short

- term PM 2.5 exposure studies as providing evidence of mortality and morbidity effects at
concentration s below the level of the current 24

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

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

related effects in older adults (Bell et al., 2008). These commenters also asserted the importance of many of the single

- city studies, argu ing that these 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). Collectively, considering the multi

- and single

- city shor t
- term exposure studies, these commenters asserted “the record clearly supports a more stringent 24

- hour standard of 25 μg/m 3 to provide uniform protection in all regions of the country particularly from short

- term spikes in pollution and from the sub

- dail y exposures that trigger heart attacks and strokes” (ALA et al., 2012, p. 62). A group of more than 350 physicians, environmental health researchers, and public health and medical professionals argued, “[s]tudies of short

- term exposure demonstrate that PM 2 .5 air pollution increases the risk of hospital admissions for heart and lung problems even when you exclude days with pollution concentrations at or above the current daily standard of 35 μg/m 3 . Daily

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Page 208 of 423 concentrations must be capped at lower levels to prote ct against peak exposure days that occur due to local and seasonal sources of emissions” (Rom et al., 2012, p. 2). In addition, many of these commenters generally concluded that progress had been made in reducing many of the uncertainties identified in the last review, in better understanding mechanisms by which PM 2.5 may be causing the observed health effects, and in improving our understanding of at

- risk populations. Further, a number of commenters argued that by making the standards more protective, the PM 2.5 NAAQS would be more consistent with other existing standards (e.g., California's annual average standard of 12 μg/m 3 ) (CARB, 2012; CA OEHHA, 2012). Other commenters argued that revising the primary PM 2.5 standards would be more consistent with the

re commendations of the World Health Organization (WHO) and/or Canada (e.g., ALA et al., 2012, p. 62; ISEE, 2012, p. 2 ; MOE

- Ontario, 2012, p. 1).
With regard to the scope of the literature reviewed for PM 2.5 - related health effects, some commenters asserted that the EPA inappropriately narrowed the scope of the review by excluding a number of categories of relevant studies, specifically related to studies of diesel pollution and traffic

- related pollution (ALA, et al., 2012, p. 17). These commenters argued that, based upon the exclusion of these types of studies, the Integrated Science Assessment “came to the erroneous conclusion that the causal relationship between PM and cancer is merely suggestive. This concl usion 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

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Page 209 of 423 analyses of the [Harvard] Six Cities and ACS cohort studies that report positi ve and statistically significant associations between PM 2.5 and lung cancer.” Id. Some of these commenters also noted the results of the EPA’s quantitative risk assessment, concluding that it showed that the risks estimated to remain when the
current stan dards are met are large and important from a public health perspective and warrant increased protection. For example, ALA et al., noted that the Risk Assessment indicated the quantitative risk analyses likely underestimated PM 2.5 - related mortality ( U.S. EP A, 2010a, p. 5

- 16) and argued that “the measurements of risk should be treated conservatively” (ALA, et al., 2012, p. 73). These commenters also summarized an expanded analysis of alternative PM 2.5 standard levels that they argued documented the need for m ore protective standards (McCubbin, 2011).
In general, all of these commenters agreed on the importance of results from the large body of scientific studies reviewed in the Integrated Science Assessment and on the need to revise the suite of PM 2.5 standar ds as articulated in the EPA’s proposal, while generally differing with 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. The EPA g enerally agrees with these commenters’ conclusion regarding the need to revise the current suite of PM 2.5 standards. The scientific evidence noted by these commenters was generally the same as that assessed in the Integrated Science Assessment and the Poli cy Assessment, and the EPA agrees that this evidence provides a

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Page 210 of 423 strong basis for concluding that the current PM 2.5 standards, taken together, are not requisite to protect public health with an adequate margin of safety, and they need to be revised to provi de increased protection. For reasons discussed in section III.E.4.c below, however, the EPA disagrees with aspects of these commenters’ views on the level of protection that is appropriate

. T he EPA disagrees with these commenters’ views that diesel exhaust studies were excluded from the Integrated Science Assessment and were not considered when making the causality determination for cancer, mutagenicity, and genotoxicity. As discussed in s ecti on 7.5 of the Integrated Science Assessment, 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 Integrated Science Assessment, 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 eff ects). 64 Specifically, when evaluating this evidence , the focus was on understanding the effects of diesel exhaust particles.

64 In developing the second draft Integrated Science Assessment, 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 determinati ons 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 categ ories of health outcomes (Vandenberg, 2009, p. 3). CASAC agreed with the EPA’s rationale for revising these causal determinations (Samet, 2009f, p. 10).

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Page 211 of 423 It is important to recognize that the Integrated Science Assessment focused on experimental studies of diesel exhaust that evaluat ed 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 Integ rated Science Assessment represents an integration of experimental and observational evidence of exposures to ambient PM concentrations. T he EPA fully considered the findings of studies that assessed the se and other health effects associated with exposure to diesel particles in reaching causality determinations regarding health outcomes associated with PM 2.5 exposures. Furthermore, CASAC supported the EPA’s change to the causal determination for cancer and long

- term PM 2.5 concentrations from “inadequate” to “suggestive” (Samet, 2009f, p. 2). 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 Integrated Science Asses sment. These studies were excluded from consideration because they did not measure ambient concentrations of specific air pollutants, including PM 2.5 , but instead we re 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 PM 2.5 and health effects.

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Page 212 of 423 Some o f these commenters also identified “new” studies that were not included in the Integrated Science Assessment as providing further support for the need to revise the primary PM 2.5 standards. As discussed in section II.B.3 above , the EPA notes that, as in pa st NAAQS reviews, the Agency 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 and will consider the “new” studies for purposes of decisio n making in the next PM NAAQS review. Nonetheless, in provisionally evaluating commenters’ arguments (see Response to Comments document), the EPA notes that its provisional assessment of “new” science found that such studies did not materially change the c onclusions in the Integrated Science Assessment (U.S. EPA, 2012b)

. Another group of commenters opposed revising the current PM 2.5 standards. These views were most extensively presented in comments from the Utility Air Regulatory Group (UARG), representing a group of electric generating companies and 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 Americ an Chemistry Council (ACC), the American Fuel & Petroleum Manufacturers (AFPM), the Alliance of Automobile Manufacturers (AAM) , and other manufacturing associations; the Electric Power Research Institute (EPRI); and the Texas Commission on Environmental Qu ality (T exas 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

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Page 213 of 423 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 stan dards 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 Integrated Science Assessment. More
sp ecifically, this group of commenters argued that: (1) 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 stud ies to reach conclusions regarding causality; (2) toxicological and controlled human exposure studies do not provide supportive evidence that the health effects observed in epidemiological studies are biologically plausible; (3) uncertainties in the underl ying health science are as great or greater than in 2006; ( 4 ) there is no evidence of greater risk since the last review to justify tightening the current annual PM 2.5 standard; and ( 5 )

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Page 214 of 423 “new” studies not included in the Integrated Science Assessment contin ue to increase uncertainty about possible health risks associated with exposure to PM 2.5 . These comments are discussed in turn below. (l) Some of these commenters asserted that the EPA did not apply its framework for causal determinations consistently acro ss studies or health outcomes ( ACC, 2012, Attachment A, pp. 1 to 2; API, 2012, Attachment 1, p. 30; NAM et al., 2012, pp. 22 to 25; Texas CEQ, 2012, pp 2 to 3 ). 65 These commenters argued that the EPA downplayed epidemiological studies with null or inconsist ent results, inappropriately used the Hill criteria when evaluating the epidemiologic al evidence, and used the same study and the same underlying database to conclude that there was a causal association between mortality and multiple criteria pollutants

. T he EPA disagrees with these commenters’ views. First, the EPA recognizes that the 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 CAS AC and the public. As summarized in section II.B.3 above, p rior to finalizing the Integrated Science Assessment, 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

65 The EPA notes that the same concerns about the causal determinations presented in the Integrated Scie nce Assessment were raised in comments to CASAC on the draft Integrated Science Assessments (e.g., UARG, 2009; API, 2009; ACC, 2012, Appendix B). CASAC, therefore, had the opportunity to consider these comments in reaching consensus conclusions on this iss ue.

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Page 215 of 423 and second draft Integrated Science Assessments were discussed at length during these public CASAC meetings and considered in developing the final Integrated Science
Asse ssment. 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). These commenters asserted that during the application of the causal framework the EPA inappropriately relied on a selective group of long

- and short

- term exposure studies in reaching causal inferences (API, 2012, pp 12 to 17; ACC, 2012, Attachment A, pp 1 to 2; NAM et al., 2012, pp. 22 to 25; Texas CEQ, 2012, pp 2 to 3). Additionally, these commenters expressed the view that the EPA focused on a subset of epidemiological studies that reported positive and statistically significan t results while ignoring other studies, especially those that reported no statistically significan t associations, those that reported potential thresholds, or those that highlighted uncertainties and limitations in study design or results. Furthermore, some of these commenters argued that epidemiological studies are observational in nature and cannot provide evidence of a causal association. The EPA disagrees with these commenters’ views on assessing the health effects evidence and on the conclusions regardi ng the causal ity determinations reached in the Integrated Science Assessment

. In conducting a comprehensive evaluation of the

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Page 216 of 423 evidence in the Integrated Science Assessment, the EPA recognized the distinction between the evaluation of the relative scientifi c 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. The more detailed characterizations of individual studies included a n assessment of the quality of the study based on specific criteria as described in the Integrated Science Assessment ( U.S. EPA, 2009a, section 1.5.3). In developing an integrated assessment of the health effects evidence for PM, the EPA emphasized the im portance of examining the pattern of results across various studies and did not focus solely on statistical significance 66 as a criterion of study strength. This approach is consistent with views clearly articulated throughout the epidemiological and causal inference literature, specifically, that it is important not to focus on results of statistical tests to the exclusion of other information. 67 The concepts underlying the EPA’s approach to evaluating statistical associations have been discussed

66 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. S tudies typically calculate “p

- values” to determine whether the study results are statistically significant or whether the study results are likely to occur simply by chance. In general practice, effects are considered statistically significant if p values are less than 0.05. 67 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 value s, significant or not significant ....Nevertheless, p

- values still confound effect size with study size, the two components of estimation that we believe need to be reported separately.” As a result, Rothman recommended that p

- values be omitted as long as po int and interval estimates are available.

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Page 217 of 423 in numerous publications, including a report by the U.S. Surgeon General on the health consequences of smoking (Centers for Disease Control and Prevention, 2004). This report cautions against over

- reliance on statistical significance in evaluating the overall evidenc e for an exposure

- response relationship. Criteria characterized by Hill (1965) also addressed the value, or lack thereof, of statistical tests in the determination of

cause: No formal tests of significance can answer those [causal] questions. Such tests c an, 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). The statistical signifi cance 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 evidenc e from many epidemiological studies, and subsequently during the process of forming causality determinations in integrating evidence 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 PM 2.5 and different health outcomes. Thus, the EPA did not limit its focus or consideratio n to just studies that reported positive associations or where the results were statistically significant. In addition, some commenters asserted that the EPA inappropriately used the Hill criteria by failing to consider the limitations of studies with wea k associations,

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Page 218 of 423 thereby overstating the consistency of the observed associations (API, 2012, Attachment 1, pp

. 30 to 35). 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. As discussed in section 1.5.3 of the Integrated Science Assessment, the EPA thoroughly considered the limitations of all studies durin g its evaluation of the scientific literature (U.S. EPA,, 2009a, p. 1

- 14). This collective body of evidence, including known uncertainties and limitations of the studies evaluated, were considered during the process of forming causality determinations as d iscussed in chapters 6 and 7 of the Integrated Science Assessment. For example, the EPA concluded that “a causal relationship exists between short

- term PM 2.5 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

. , in

s ection 6.2.12.1 ). Therefore, t he EPA disagrees with these commenters’ views that the Hill criteria were inappropriately used in that the limitations of studies were not considered. 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 Integrated Science Assessment, the strength of the observed association is an important aspect to aid in judging causality and “while large effects support causality,

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Page 219 of 423 modest effects therefore do not preclude it” ( U.S. EPA, 2009a, Table 1

- 2, section 1.5.4). 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 investigato rs and locations supports the “reproducibility of findings [which] constitutes one of the strongest arguments for causality” ( U.S. EPA, 2009a, Table 1

- 2). Even though the risk estimates for air pollution studies may be modest, the associations are consiste nt across hundreds of studies as demonstrated in the Integrated Science Assessment. Furthermore, the causality determinations rely on different lines of evidence, by integrating evidence across disciplines, including animal toxicological studies and contro lled human exposure studies. Furthermore, as summarized in section III.B above and discussed more fully in section III.B.3 of the proposal , the EPA recognizes that the population potentially affected by PM 2.5 is considerable, including large subgroups of t he 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 pub lic health impact of the mortality and morbidity associations can be quite large given that air pollution 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, th is information

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Page 220 of 423 indicates that exposure to ambient PM 2.5 concentrations has substantial public health impacts. In addition, these commenters be lieved that the EPA downplayed null or inconsistent findings in numerous long

- term mortality studies with reported PM 2.5 concentrations above and below the level of the current annual standard. The EPA disagrees that studies with null or inconsistent findi ngs were not accurately presented and considered in the Integrated Science Assessment. For example, as discussed throughout section 7.6 and depicted in Figures 7

- 6 and 7

- 7 of the Integrated Science Assessment, the EPA presented the collective evidence from all studies that examined the association between long

- term PM 2.5 exposure and mortality. Overall, across these studies there was evidence of consistent positive associations in different cohorts. That evidence, in combination with the biological plausibi lity provided by experimental and toxicological studies evaluated in sections 7.1 and 7.2 of the Integrated Science Assessment, supported a causal relationship exists between long

- term PM 2.5 exposure and mortality

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

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Page 221 of 423 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 regulations to limit emissions of particulate criteria pollutants as well as other gaseou s criteria pollutants. Epidemiologic al studies often examine the association between short

- and long

- term exposures to multiple air pollutants and mortality within a common dataset in an attempt to identify the air pollutant(s) of the complex mixture most strongly associated with mortality. In evaluating these studies , the EPA employs specific study selection criteria to identify those studies most relevant to the review of the NAAQS. In its assessment of the health evidence regarding PM 2.5 , the EPA has car efully evaluated the potential for confounding, effect measure modification , and the role of PM 2.5 as a component of a complex mixture of air pollutants ( U.S. EPA, 2009, p. 1

- 9). The EPA use d a rigorous weight of evidence approach to inform causality that evaluate d consistency across studies within a discipline, evidence for coherence across disciplines, and biological plausibility. Additionally, during this process, the EPA assesse d the limitations of each study in the context of the collective body of evi dence. It wa s the collective evidence, not one individual study that ultimately determine d whether a causal relationship exists between a pollutant and health outcome. In the Integrated Science
Assessment , the combination of epidemiologic al and experimental evidence formed the basis for the Agency concluding for the first time that a causal relationship exists

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Page 222 of 423 between short

- or long

- term exposure to a criteria pollutant and mortality ( U.S. EPA, 2009, s ection s 2.3.1.1 and 2.3.1.2). Additiona lly, while the EPA has evaluated some of the studies used to inform the causality determination for PM in the Integrated Science Assessments for other criteria air pollutants, the Agency has done so in the context of examining the collective body of eviden ce for each of the respective criteria air pollutants. As such, the body of evidence to inform causality has varied from pollutant to pollutant resulting in the association between each criteria air pollutant and mortality being classified at a different l evel of the five

- level hierarchy used to inform causation ( e.g., U.S. EPA, 2008 e , U.S. EPA, 2008 f , U.S. EPA, 2010 k ). The EPA notes that the final causality determinations presented in the Integrated Science Assessment reflected CASAC’s recommendations on the second draft Integrated Science Assessment (Samet, 2009f, pp. 2 to 3). Specifically, CASAC supported the EPA’s changes (in the second versus first draft Integrated Science Assessment) from “likely causal” to “causal” for long

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

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

- and long

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

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Page 223 of 423 exists for short

- and long

- term exposure to PM 2.5 and m ortality, consistent with the CASAC comments” (Jackson, 2012). (2) With regard to toxicological and controlled human exposure studies, these commenters argued that the available evidence does not provide coherence or biological plausibility for health eff ects observed in epidemiological studies (API, 2012, pp. 21 to 22, Attachment 1, pp. 25 to 29; AAM, 2012, pp. 15 to 16; T exas CEQ, 2012, p. 3). With regard to the issue of mechanisms, these commenters noted that although the EPA recognizes that new evidenc e is now available on potential mechanisms and plausible biological pathways, the evidence provided by toxicological and controlled human exposure studies still does not resolve all questions about how PM 2.5 at ambient concentrations could produce the mort ality and morbidity effects observed in epidemiological studies. More specifically, for example, some of these commenters argued that: A review of the Integrated Science Assessment, however, suggests that the experimental evidence is inconsistent and not c oherent 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. EPA shou ld 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). The EPA notes that in the review completed in 1997 , the Agency considered the lack of demon strated biologic al mechanisms for the varying effects observed in

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Page 224 of 423 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 a ppeared to be responsible for many biologic responses relevant to fine particle exposures. Id. Since that review, there has been a great deal of research directed toward advancing our understanding of biologic mechanisms. While this research has not resolv ed 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 Integrated Science Assessment ( U.S. EPA, 2009a, C hapter 5). As noted in the proposal, toxicological studies provide evidence to support the biologic al plausibility of cardiovascular and respiratory effects associated with long

- and short

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

- term exposure epidemiological studies are coherent with studies of cardiovascular

- related mortality (77 FR 38907). The Integrated Sci ence Assessment concluded that t he new evidence available in this review “greatly expands” upon the evidence available in the last review “particularly in providing greater understanding of the underlying mechanisms for PM 2.5 induced cardiovascular and res piratory effects for

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Page 225 of 423 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 PM 2.5 and cardiovascular effects and mortality. 68 In addition, CASAC supported the Integrated Science Assessment approach and characterization of potential mechanisms or modes of action (Samet, 2009e, pp. 7 to 8; Sam et, 2009f, p. 11), as well as the findings of a causal relationship at the population level between exposure to PM 2.5 and mortality and cardiovascular effects (Samet, 2009f, pp. 2 to 3). 69 Additionally, the EPA disagrees with commenters that the mild and r eversible effects observed in controlled human exposure studies are inconsistent with the more serious effects observed in epidemiologic al studies. Ethical considerations regarding the types of studies that can be performed with human subjects generally li mit 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

68 See American Trucking Ass ociation v. EPA, 175 F. 3d 1027, 1055

- 56 (D.C. Cir. 1999) rev erse d in part and affirmed in part sub nom , Whitman v. American Trucking Assn’s, 531 U.S. 457 (2001) holding that the EPA co uld establish NAAQS without identifying a biological mechanism (“ To begin with, the statute itself requires no such proof. The Administrator may regulate air pollutants "emissions of which, in his judgment, cause or contribute to air pollution which may re asonably be anticipated to endanger public health or welfare ." ( emphasis added by the court). Moreover, this court has never required the type of explanation petitioners seek from EPA. In fact, we have expressly held that EPA's decision to adopt and set ai r quality standards need only be based on ‘reasonable extrapolations from some reliable evidence’.... Indeed, were we to accept petitioners' view, EPA (or any agency for that matter) would be powerless to act whenever it first recognizes clear trends of mort ality or morbidity in areas dominated by a particular pathogen.”).

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Page 226 of 423 studies should also be expected to have less variability in heal th status and risk factors than occurring in the general population. 70 Consequently, the severity of health effects observed in controlled human exposure studies evaluating the effects of PM should be expected to be less than observed in epidemiologic studi es. Nonetheless, that effects are observed in relatively healthy individuals participating in controlled exposure studies serves as an indicator that PM is initiating health responses and that more severe responses may reasonably be expected in a more dive rse population. It should also be noted that there is a small body of toxicological evidence demonstrating mortality in rodents exposed to PM (e.g., Killingsworth et al. 1997; Godleski et al. 1996). Overall it is not surprising that lethality is not induced in more toxicological research, as these types of studies do not readily lend themselves to this endpoint. Epidemiologic al studies have observed associations between PM and

70 For example, the EPA excludes from its controlled human exposure studies involving exposure to PM 2.5 any individual with a significant risk factor for experiencing adverse effects from s uch 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 h ypertension (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 diabet es, 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 Ol der GSTM1 Null and Sufficient individuals to Concentrated Ambient Air Particles (CAPTAIN)”, Nov. 9, 2011, p. 9.

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Page 22 7 of 423 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 ambient PM (potentially over many years) in a laboratory setting to induce enough lethalities to distinguish between natural deaths and those attributable to PM. 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 are typically inbred, such that inter

- individual variability is minimized. Thus, if the rodent strain used is quite robust, PM

- induced effects may not be observed at low exposure concentrations. (3) 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, commenters in this group variously discussed a number of issues related to: (a) confounding, (b) heterogenei ty in risk estimates, (c) exposure measurement error, (d) model specification , (e) the concentration

- response relationship, and ( f ) understanding the relative toxicity of components within the mixture of fine particles. Each of these issues is addressed be low and some are discussed in more detail in the Response to Comments document

. In summary, these commenters concluded that the substantial uncertainties present in the last review have not been resolved and/or that the uncertainty about the possible heal th risks associated with PM 2.5 exposure has not diminished. As discussed

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Page 228 of 423 below, the EPA believes that the overall uncertainty about possible health risks associated with both long

- and short

- term PM 2.5 exposure has diminished to an important degree since t he last review. While the EPA agrees that important uncertainties remain, and that future research directed toward addressing these uncertainties is warranted, the EPA disagrees with commenters’ views that the remaining uncertainties in the scientific evid ence are too great to warrant revising the
current PM 2.5 NAAQS. ( a ) Confounding Some commenters have criticized the EPA for not adequately addressing the issue of confounding in both long

- and short

- term exposure studies of mortality and morbidity. This includes confounding due to copollutants, as well as unmeasured confounding. 71 With regard to copollutant confounding, these commenters asserted that the EPA has not adequately interpreted the results from studies that examined the effect of copollutants o n the relationship between long

- and short

- term PM 2.5 exposures and mortality and morbidity outcomes. These commenters contend that the EPA has

71 The Integrated Science Assessment defines confounding as “a confusion of effects. Specifically, the apparent effect of the exposure of interest is distorted because the effect of an extraneous factor is mistaken for or mixed with the actual exposure effec t (which may be null) (Rothman and Greenland, 1998)” (U.S. EPA, 2009a, p. 1

- 16). Epidemiological analyses attempt to adjust or control for these characteristics (i.e., potential confounders) that differ between exposed and non

- exposed individuals (U.S. EPA , 2009a, section 1.5.3). Not all risk factors can be controlled for within a study design/model and are termed “unmeasured confounders.” An unmeasured confounder is a confounder that has not previously been measured and therefore is not included in the stu dy design/model.

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Page 229 of 423 inappropriately concluded that PM 2.5 - related mortality and morbidity associations are generally robust to confou nding. The commenters stated that statistically significant
PM 2.5 associations in single

- pollutant models in epidemiologic al studies do not remain statistically significant in copollutant models. The loss of statistical significance or the reduction in th e magnitude of the effect estimate when a co

- pollutant 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 c onsiders the entire body of evidence. The broader examination of this issue in the Integrated Science Assessment included a focus on evaluating the stability of the size of the effect estimates in epidemiological studies conducted by a number of research g roups using single

- and copollutant 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 c opollutant models, although the Integrated Science Assessment recognized that in some cases, the
PM 2.5 effect estimates were markedly reduced in size and lost statistical significance. Additionally, the EPA notes that these comments do not adequately refle ct 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 Integrated Science Assessment ( U.S. EPA, 2009a, sections 6.2, 6.3, and 6.5), although copollut ant models may be useful tools for assessing whether gaseous copollutants may be potential

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Page 230 of 423 confounders, such models alone cannot determine whether copollutants are in fact confounders. Interpretation of the results of copollutant models is complicated by

c orrelations 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 th e study methodology. For example, the every

- third or sixth

- day sampling schedule often employed for PM 2.5 measurements compared to daily measurements of gaseous copollutants drastically reduces the overall sample size to assess the effect of copollutants o n the PM 2.5 - morbidity or mortality relationship, such that the reduced sample size can lead to less precise effect estimates (e.g., wider confidence intervals). The EPA recognizes that when PM 2.5 is correlated with gaseous pollutants it can be difficult to identify the effect of individual pollutants in the ambient mixture (77 FR 38910). However, based on the available evidence, the EPA concludes epidemiological studies continue to support the conclusion that PM 2.5 associations with mortality and morbidity outcomes are robust to the inclusion of gaseous copollutants in statistical models. The EPA evaluated the potential confounding effects of gaseous copollutants and, although it is recognized that uncertainties and limitations still remain, the Agency concl uded 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).

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Page 231 of 423 Several commenters offered detailed comments on the long

- term PM 2.5 exp osure studies arguing that associations from mortality studies are subjected to unmeasured confounding and as a result are not appropriately characterized as providing evidence of a causal relationship between long

- term PM 2.5 exposure and mortality (e.g., UARG, 2012, pp. 10 to 11, Attachment A, pp. 17 to 23; API, 2012, pp. 13 to 14, Attachment 1, pp. 11 to 14, Attachment 7, pp. 2

- 10; ACC, 2012, p. 18 to 21; AFPM, 2012, p. 8; Texas CEQ, 2012, p. 4). Specifically, commenters cited two studies (i.e., Janes
et al. , 2007 and Greven et al. , 2011) that used a new type of statistical analysis to examine associations between annual (long

- term) and monthly (sub

- chronic) PM 2.5 exposure and mortality. The commenters interpreted the results of these analyses as evidence of unmeasured confounding in the long

- term PM 2.5 exposure - mortality relationship. These commenters interpreted these studies as raising fundamental questions rega rding the EPA’s determination that a causal relationship exists between long

- term PM 2.5 exposure and mortality. In addition to the commenters mentioned above, all of the authors of the publications by Janes et al. (2007) and Greven et al. (2011) (i.e., Fra ncesca Dominici, Scott Zeger, Holly Janes, and Sonja Greven) submitted a joint comment to the public docket in order to clarify specific points regarding these two studies (Dominici et al., 2012). The first study, Janes et al. ( 2007 ) , was evaluated in the Integrated Science Assessment (U.S. EPA, 2009a, p. 7

- 88). The second study, Greven et al. (2011), an extension of the Janes et al. (2007) study adding three more years of data, is a “new”

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Page 232 of 423 study discussed in the Provisional Science Assessment (U.S. EPA, 201 2). Both studies used nationwide Medicare mortality data to examine the association between monthly average PM 2.5 concentrations over the preceding 12 months and monthly mortality rates in 113 U.S. counties and examined whether community

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

- specific deviations in monthly PM 2.5 concentrations and

m onthly 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). 72 Both Janes et al. (2007) and Greven et al. (2011) observed positive and statisti cally significant associations between long

- term exposure to PM 2.5 and mortality in their national analyses. However, Janes et al. (2007) and Greven et al. (2011) 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

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

- 88) and included the results of the national

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

- term PM 2.5 exposure and mortality

.

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Page 233 of 423 al. 2012). Janes et al. (2007) (Table 1) highlight ed that over 90 percent of the variance in the data set use d for the analyses conducted by both Janes et al. (2007) and Greven et al. (2011) was attributable to spatial variability, which the authors chose to discard. As noted above, the focus of the analyses by Janes et al. (2007) and Greven et al. (2011)

was on two components: (1) a temporal or time component, i.e., the “national” trends analysis, which examined the association between the national average trend in monthly PM 2.5 concentrations averaged over the previous 12 months and the national average trend in monthly mortality rates and (2) a space

- by

- time component, i.e., the “local” trends analysis, which examined county
- specific deviations in monthly PM 2.5 concentrations and monthly mortality rates from national trends. These two components combined compris ed less than 10 percent of the variance in the data set. The authors included a focus on the space

- by

- time component, which represented approximately 5 percent of the variance in the data set, in an attempt to identify, absent confounding, if PM 2.5 was associated with mortality at this unique exposure window. Thus, these studies are not directly comparable to other cohort studies investigating the relationship between long

- term exposure to PM 2.5 and mortality, which make use of spatial variability i n air pollution and mortality data. 73 This point was highlighted by the

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

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Page 234 of 423 study authors who stated that “when one considers that this wealth of information is not accounted for in [Janes 2007], it is not as surprising that... vastly different estimates of the P M 2.5 /mortality relationship [were observed] than in other studies that do exploit that variability” (Dominici et al., 2012, p. 2 ). The EPA notes that the results of the local trends analyses conducted by Janes et al. (2007) and Greven et al. (2011) are li mited by the monthly timescale used in these analyses. This view is consistent with comments on the Janes et al. (2007) study articulated in Pope and Burnett (2007), 74 which noted that an important limitation of the local scale analysis conducted by Janes e t al. (2007) and subsequently by Greven et al. (2011) was the subchronic exposure window considered in these analyses. Both studies used annual average PM 2.5 concentrations to characterize long

- term national trends which was consistent with exposure window s considered in other studies of long

- term exposure to PM 2.5 and mortality. 75 However, the local scale analyses used monthly average PM 2.5 concentrations to characterize county

- specific deviations from national trends (the local scale). The use of monthly a verage data likely does not provide enough exposure contrast to observe temporal changes in mortality at the local scale. It also

the asso ciation between average PM 2.5 levels and average age

- adjusted mortality rates across cities (purely spatial or cross

- sectional association).” 74 S ome commenters argued that there were flaws in the criticisms offered by Pope and Burnett (2007) on the paper b y Janes et al. (2007) (UARG, 2012, Attachment A, pp. 19 to 23). The EPA responds to each of these specific comments in the Response to Comments document. 75 As noted above, however, Janes et al. (2007) and Greven et al. (2011) focus ed on temporal variabilit y and other studies of long

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

.

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Page 235 of 423 represents a different exposure window than considered in the large body of evidence of health effects related to short

- term ( from less than one day to up to several days) and chronic (one or more years) measures of PM 2.5 . Furthermore, the EPA disagrees with commenters that studies by Janes et al. (2007) and Greven et al. (2011) provide evidence that other studies of long

- term

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

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

- term (annual) exposures to PM 2.5 on mortality ri sk, and did not conduct any analyses relying on the temporal variation in PM 2.5 . The opposite is true of the Janes et al. (2007) and Greven et al. (2011) studies which first removed the spatial variability in PM 2.5 and then examined the temporal variation at both the national and local scale to measure the effects of temporal differences in PM 2.5 on mortality risk. Janes et al. (2007) and Greven et al. (2011) focus on changes in PM 2.5 concentrations over time and , therefore , control for confounders would be based on including variables that vary over time rather than over space. As a result, any evidence of potential confounding of the PM 2.5 - mortality risk relationship derived from Janes et al. (2007) and Greven et al. (2011) cannot be extrapolated to draw c onclusions related

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Page 236 of 423 to potential spatial confounding in studies based on the spatial variation in PM 2.5 concentrations. As detailed in the Integrated Science Assessment (U.S. EPA, 2009a, section 7.6) , and recognized by the authors of Janes et al. (2007) an d Greven et al. (2011), the cohort studies that informed the causality determination for long

- term PM 2.5 exposure and mortality “have developed approaches to adjust for measured and unmeasured confounders” (Dominici et al., 2012, p. 2). These approaches were specifically designed to adjust for spatial confounding. The hypothesis that the authors of Janes et al. (2007) and Greven et al. (2011) chose to examine was that differences in the local and national effects indicated unmeasured temporal confounding in either the local or national effect estimate. This hypothesis was specific to these two studies that ex amined temporal variability in exposure to air pollution and did not include known potential confounders at either the national or local scale as time

- varying covariates in the statistical model. The authors acknowledge d that the interpretation of either t he 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) focus ed on variations in PM 2.5 over time and not space, the results from these two studies do not provide any indication that other studies of long

- term exposure to

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Page 237 of 423 PM 2.5 and mortality exhibit spatial confounding, or that PM 2.5 does not cause mortality. 76 The authors of Janes et al. (2007) and Greven et al. (2011) recognized that “it is entirely possible that these papers are looking for an association at a timescale for which no association truly exists” (Dominici et al.,. 20 12, p. 3). Furthermore, as highlighted in the Integrated Science Assessment and discussed by Pope and Burnett (2007), the conclusions of Janes et al. (2007) “are overstated. . . [T]heir analysis tells us little or nothing about unmeasured confounding in th ose 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 elimi nate the opportunity to exploit short

- term or day

- to
- day variability.” In conclusion, the EPA interprets the results of the analyses conducted by Janes et al. (2007) and Greven et al. (2011) as being consistent with prior knowledge of examining associations with long

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

- term average PM 2.5 concentrations. For the reasons presented above and discussed in more detail in the Response to Comments document, the Agency disagrees with the commenters’ a ssumption that the results of Janes et al. (2007) and Greven et al. (2011) indicate unmeasured confounding in the results of other cohort studies of long

- term exposure to PM 2.5 and mortality . Therefore, the EPA concludes that these studies do not

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

- term exposure to PM 2.5 .

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Page 238 of 423 invalidat e the large body of epidemiological evidence that supports the EPA’s determination that a causal relationship exists between long

- term PM 2.5 exposure and mortality. 77 ( b ) Heterogeneity in Risk Estimates
Some commenters argued that the heterogeneity in risk estimates observed in multi

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

- city epide miological study results (e.g., API, 2012, Attachment 1, pp. 15 to 19). These commenters further argued that more refined intra

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

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

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

- city studies” (API, 2012, Attachment 1, p. 17). With respect to understanding the nature and magnitude of PM 2.5 - related risks, the EPA agrees that epidemiological studies evaluating health effects associate d with long

- and short

- term PM 2.5 exposures have reported heterogeneity in responses between cities and effect estimates across geographic regions of the U.S. ( U.S. EPA,

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

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Page 239 of 423 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

ex ample, when focusing on short

- term PM 2.5 exposure, the Integrated Science Assessment 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., 2006; Bell et al., 2008; Franklin et al. (2007, 2008)). In addition, the Integrated Science Assessment evaluated studies that provided some evidence for seasonal dif ferences in PM 2.5 risk estimates, specifically in the northeast. The I ntegrated S cience A ssessment found evidence indicating that individuals may be at greater risk of dying from higher exposures to PM 2.5 in the warmer months, and at greater risk of PM 2.5 associated hospitalization for cardiovascular and respiratory diseases during colder months of the year. The limited influence of seasonality on PM risk estimates in other regions of the U.S. may be due to a number of factors including varying PM compositi on 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 took note in the proposal 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, t o differences in PM 2.5 composition across the U.S., as well as to exposure differences that vary regionally such as personal activity patterns,

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Page 240 of 423 microenvironmental characteristics, and the spatial variability of PM 2.5 concentrations in urban areas ( U.S. EPA , 2009a, section 2.3.2; 77 FR 38910). As recognized in the Policy Assessment, the current epidemiological evidence and the limited amount of city

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

- 25). Furthermore, the Integrated Science Assessment concluded “that many constituents of PM 2.5 can be linked with multiple health effects, and the evidence is not yet sufficient to allow differentiation of those constituents or sources that are more closely 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 PM 2.5 effect estimates in epidem iological studies and concurred with the overall conclusions presented in the Integrated Science Assessment. (c) Exposure Measurement Error Some 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 vari ability 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

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Page 241 of 423 measurement error was not a dequately 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 e stimates 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 pat terns 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, consisten t 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) (emphasis added). 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. ( d ) Model Specification Commenters contend ed 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 es timated associations are weak” (ACC, 2012, p. 5) For short

- term exposure studies , the EPA recognizes, as summarized in the

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Page 242 of 423 HEI review panel commentary that selecting a level of control to adjust for time

- varying factors, such as temperature, in time

- series epidemiologic al 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 variab le. Conversely, if an overly aggressive approach is used to control for temperature, the result would possibly underestimate the pollution

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

- 236; HEI, 2003, p. 266). The selection of approaches to address such variables depends in part on prior knowledge and judgments made by the investigators, for example, about weather patterns in the study area and expected relationships between weather and other tim e - varying factors and health outcomes considered in the study. As demonstrated in s ection 6.5 of the Integrated Science Assessment, the EPA thoroughly considered each of these issues and the overall effect of different model specifications on the associati on between short

- term PM 2.5 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 (U

. S

. E PA 2009, Figure 6

- 27). The EPA also considered the influence of model specification in the examination of long

- term PM 2.5 exposure studies. For example, in s ection 7.6 of the Integrated Science Assessment , Figures 7

- 6 and 7

- 7 summarize the collective evide nce that evaluated the association between long

- term PM 2.5 exposure and mortality. Regardless of the model used, these studies collectively

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Page 243 of 423 found evidence of consistent positive associations between long

- term PM 2.5 exposure and mortality. The EPA, therefo re, disagrees with commenters that model specification was not considered when evaluating the epidemiologic al evidence used to form causality determinations. The EPA specifically points out that the process of assessing the scientific quality and relevance of epidemiologic al 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, 20 09, p. 1

- 9).” Consistent with the conclusions of the 2004 PM A ir Q uality C riteria D ocument , 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 expos ure studies, and that no single statistical modeling approach is likely to be most appropriate in all cases ( U.S. EPA, 2004, p. 8

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

- and long

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

- response Relationship Additio nally, commenters questioned the interpretation of the shape of the
concentration

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

- health effect relationship and that the

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Page 244 of 423 log

- linear model is not biologically plausible (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 Integrated Science Assessment that continue to support the use of a no

- threshold, log

- linear model to most appropriately represent the PM concentration

- response relationship ( U.S. EPA, 2009a, section 2.4.3). W hile recognizing that uncertainties rem ain, 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 Integrated Science Assessment, both long

- and short

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

response function and whether a threshold exists. While the EPA recognizes that there likely are individual biologic al thresholds for specific health responses, the Integrated Science A ssessment concluded the overall evidence from existing epidemiological studies do es not support the existence of thresholds at the population level, for effects associated with either long

- term or short

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

. 78 The Integrated Science Assessment 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).

78 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 suc h thresholds exist towards the lower end of these ranges (or below these ranges).

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Page 245 of 423 The EPA recognizes that some short

- term exposure studies have examined the
PM 2.5 concen tration

- response relationship in individual cities or on a city

- to
- city basis and observed heterogeneity in the shape of the concentration

- response curve across cities. As discussed in (b) above, these findings are a source of uncertainty that the EPA
agre es requires further investigation. Nonetheless, the Integrated Science Assessment concluded that “the studies evaluated further support the use of a no

- threshold, log

linear model, but additional issues such as the influence of heterogeneity in estimates b etween 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). (f) Relative Toxicity of PM 2.5 Components Some commenters highlighted un certainties in understanding the role of individual constituents with in the mix of fine particles. These commenters asserted that

a mass - based standard may not be appropriate due to the growing body of evidence indicating that certain PM 2.5 components may be more closely related to specific health outcomes (e.g., EC and OC) (EPRI, 2012, p. 2). With regard to questions about the role of individual constituents within the mix of fine particle s , as a general matter, the EPA recognizes that although new resear ch 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

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Page 246 of 423 app ropriate 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 eff ects 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 he alth 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 below, while most epidemiological studies continue to be indexed by PM 2.5 mass, several recent epidemiological studies included in the Integrated Science Assessment have used PM 2.5 speciation data to evaluate health effects associated with fine particle exposures. In the Integrated Science Assessment, the EPA thoroughly evaluat ed the scientific evidence that examined the effect of different PM 2.5 components and sources on a variety of health outcomes ( U.S. EPA, 2009a, section 6.6) and observed that the available information continues to suggest that many different chemical compo nents of fine particles and a variety of different types of source categories are all associated with, and probably contribute to, effects associated with PM 2.5 . The Integrated Science Assessment concluded that the current body of scientific evidence indic ated 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,

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Page 247 of 423 the Policy Assessment 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 PM 2. 5 indicator ( U.S. EPA, 2009a, p. 2

- 56). CASAC agreed that it was reasonable to retain PM 2.5 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 PM 2.5 as the indicator for fine particles as discussed in section III.E.1 below. The EPA also believes that it is relevant to the Agency’s conclusion as to whether revision of the suit e of primary PM 2.5 standards is appropriate. While there remain uncertainties about the role and relative toxicity of various components of fine PM, the current evidence continues to support the view that fine particles should be addressed as a group for p urposes of public health protection. 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
PM 2.5 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

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Page 248 of 423 evidence from epidemiological studies of associations observed i n areas meeting the current primary PM 2.5 standards, specifically in areas meeting the current primary annual PM 2.5 standard, adds support to its conclusion that the current suite of PM 2.5 standards needs to be revised to provide increased public health pr otection. (4) In asserting that there is no evidence of greater risk since the 2006 review to justify lowering the current annual PM 2.5 standard, some commenters argued that, “if the current primary PM 2.5 annual standard of 15 μg/m 3 was considered to be adequately protective of public health in 2006, given relative risk estimates that EPA was using at that time, then that standard would surely still be adequately protective of the public health if relative risk estimates remain at th e 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, a nd 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 reas on to revise the current annual PM 2.5 standard. The EPA believes that this claim is fundamentally flawed. In comparing the scientific understanding of the risk presented by exposure to PM 2.5 between the last and current reviews, one must examine not only t he 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

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Page 249 of 423 observed health effects are causally li nked to PM 2.5 exposure at those concentrations. As documented in the Integrated Science Assessment and in the recommendations and conclusions of CASAC, the EPA recognizes significant advances in our understanding of the health effects of PM 2.5 , based on ev idence 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 cur rent primary PM 2.5 standards. From this more comprehensive perspective, since the risks presented by PM 2.5 are more certain, similar or even somewhat lower relative risk estimates would not be a basis to conclude that no revision to the suite of PM 2.5 stan dards is “requisite” to protect public health with an adequate margin of safety. This also ignores that the relative risk estimate is only one factor considered by the Administrator, e.g. it ignores that epidemiological studies since the last review indica te associations between PM 2.5 and mor t ality and morbidity in areas meeting the current annual standard. In any case, the commenters’ reliance on the flawed 2006 review is misplaced. As discussed in section III.A.2 above, the D.C. Circuit remanded Administr ator Johnson’s 2006 decision to retain the primary annual PM 2.5 standard because the Agency failed to adequately explain why the annual standard provided the requisite protection from both short

- and long

- term exposure to fine particles including protectio n for at

- risk populations. The 2006 standard was also at sharp odds with CASAC advice and recommendations as to the requisite level of protection (Henderson, 2006a,b). In other

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Page 250 of 423 words, the 2006 primary annual PM 2. 5 standard is not an appropriate benchmark for comparison. (5) Some of these commenters also identified “new” as well as older studies that had been included in prior reviews as prov iding additional evidence that the causality determinations presented in the Integrated Science Assessment did not consider the totality of the scientific literature , further supporting the ir view that a revision of the
PM 2.5 is unwarranted. As discussed i n section II.B.3 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 I ntegrated S cience A ssessment that have undergone CASAC and public review, and will consider newly published studies for purposes of decision making in the next PM NAAQS review. In provisionally evaluating commenters’ arguments (see Response to Comments document), the EPA notes that its provisional assessment of “new” science fou nd that such studies did not materially change the conclusions reached in the Integrated S cience Assessment (U.S. EPA, 2012b)

. 3. Administrator’s Final Conclusions Concerning the Adequacy of the Current Primary PM 2.5 Standards Having carefully considered the public comments, as discussed above, the Administrator believes the fundamental scientific conclusions on the effects of PM 2.5 reached in the Integrated Science Assessment, and discussed in the Policy Assessment, are valid. In considering whether the suit e of primary PM 2.5 standards should be revised, the Administrator places primary consideration on the evidence obtained from the epidemiological studies. The Administrator believes that this literature, combined with

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Page 251 of 423 the other scientific evidence discussed in the I ntegrated S cience A ssessment , collectively represents a strong and generally robust body of evidence of serious health effects associated with both long

- and short

- term exposures to PM 2.5 . As discussed in the Integrated Science Assessment and Policy Assessment, the EPA believes that much progress has been made since the last review in reducing some of the major uncertainties that were important considerations in establishing the current suite of
PM 2.5 standards. In that context, the Administrat or finds the evidence of serious health effects reported in exposure studies conducted in areas with long

- term mean concentration s ranging from approximately at or above the level of the annual standard to long

- term mean concentration s significantly below the level of the annual standard to be compelling, especially in light of the extent to which such studies are part of an overall pattern of positive and frequently statistically significant associations across a broad range of studies. The information in the quantitative risk assessment lends support to this conclusion.
There has been extensive critical review of this body of evidence, the quantitative risk assessment, and related uncertainties, including review by CASAC and the public. The public comments on the basis for the EPA’s proposed decision to revise the suite of primary PM 2.5 standards have identified a number of issues about which different parties disagree including issues for which additional research is warranted. Having weighed all comments and the advice of CASAC, the Administrator believes that since the last review the overall uncertainty about the public health risks associated

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Page 252 of 423 with both long

- and short

- term exposure to PM 2.5 has been diminished to an important degree. The remaining uncer tainties in the available evidence do not diminish confidence in the associations between exposure to fine particles and mortality and serious morbidity effects. Based on her increased confidence in the association between exposure to PM 2.5 and serious pub lic health effects, combined with evidence of such an association in areas that would meet the current standards, the Administrator agrees with CASAC that revision of the current suite of PM 2.5 standards to provide increased public health protection is nec essary. Based on these considerations, the Administrator concludes that the current suite of primary PM 2.5 standards is not sufficient, and thus not requisite, to protect public health with an adequate margin of safety, and that revision is needed to incre ase public health protection.
It is important to note that this conclusion, and the reasoning on which it is based, do not resolve the question of what specific revisions are appropriate. That requires looking specifically at the current 24

- hour and annua l PM 2.5 standards, including their indicator, averaging times, forms, and levels, and evaluating the scientific evidence and other information relevant to determining the appropriate revision of the suite of standards.

E. Conclusions on the Elements of the Pr imary Fine Particle Standards
1. Indicator

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Page 253 of 423 In initially setting standards for fine particles in 1997, the EPA concluded it was appropriate to control fine particles as a group, rather than singling out any particular component or class of fine particles. The EPA noted that community health studies had found significant associations between various indicators of fine particles, and that health effects in a large number of areas had significant mass contributions of differing components or sources of fine partic les. In addition, a number of toxicological and controlled human exposure studies had reported health effects associations with high concentrations of numerous fine particle components. It was also not possible to rule out any component within the mix of f ine particles as not contributing to the fine particle effects found in the epidemiologic studies (62 FR 38667, July 18, 1977). In establishing a size

- based indicator in 1977 to distinguish fine particles from particles in the coarse mode, the EPA noted th at the available epidemiological studies of fine particles were based largely on PM 2.5 and also considered monitoring technology that was generally available. The selection of a 2.5 μm size cut reflected the regulatory importance of defining an indicator t hat would more completely capture fine particles under all conditions likely to be encountered across the U.S., especially when fine particle concentrations and humidity are likely to be high, while recognizing that some small coarse particles would also b e captured by current methods to monitor PM 2.5 (62 FR 38666 to 38668, July 18, 1997). In the last review, based on the same considerations, the EPA again recognized that the available information supported retaining the PM 2.5 indicator and remained too lim ited to support a distinct standard for any specific PM 2.5

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Page 254 of 423 component or group of components associated with any source categories of fine particles (71 FR 61162 to 61164, October 17, 2006). In this current review, the same considerations continue to apply for selection of an appropriate indicator for fine particles. As an initial matter, the Policy Assessment recognizes that the available epidemiological studies linking mortality and morbidity effects with long

- and short

- term exposures to fine particles co ntinue to be largely indexed by PM 2.5 . For the same reasons discussed in the last two reviews, the Policy Assessment concluded that it was appropriate to consider retaining a PM 2.5 indicator to provide protection from effects associated with long

- and shor t
- term fine particle exposures ( U.S. EPA, 2011, p. 2

- 50). The Policy Assessment also considered the expanded body of evidence available in this review to consider whether there was sufficient evidence to support a separate standard for ultrafine particles 79 or whether there was sufficient evidence to establish distinct standards focused on regulating specific PM 2.5 components or a group of components associated with any source categories of fine particles ( U.S. EPA, 2011a, section 2.3.1). A number of studies available in this review have evaluated potential health effects associated with short

- term exposures to ultrafine particles. As noted in the Integrated Science Assessment, the enormous number and larger, collective surface

79 Ultrafine particles, generally including particles with a mobility diameter less than or equal to 0.1 μm, are emitted directly to the atmosphere or are formed by nucleation of gaseous constituents in the atmosphere (U.S. EPA, 2009a, p. 3

- 3).

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Page 255 of 423 area of ultrafine particles are important considerations for focusing on this particle size fraction in assessing potential public health impacts ( U.S. EPA, 2009a, p. 6

- 83). Per unit mass, ultrafine particles may have more opportunity to interact with cell surfaces due to their greater surface area and their greater particle number compared with larger particles ( U.S. EPA, 2009a, p. 5

- 3). Greater surface area also increases the potential for soluble components (e.g., transition metals, organics) to adsorb to ultrafine particles and poten tially cross cell membranes and epithelial barriers ( U.S. EPA, 2009a, p. 6

- 83). In addition, evidence available in this review suggests that the ability of particles to enhance allergic sensitization is associated more strongly with particle number and surface area than with particle mass ( U.S. EPA, 2009a, p. 6

- 127). New evidence, primarily from controlled human exposure and toxicological studies, expands our understanding of cardiovascular and respiratory effects related to short

- term ultrafine particle exposures. However, the Policy Assessment concluded that
t his evidence was still very limited and largely focused on exposure to diesel exhaust, for which the Integrated Science Assessment concluded it was unclear whether the effects observed are due to ultrafine particles, larger particles within the PM 2.5 mixtu re, or the gaseous components of diesel exhaust ( U.S. EPA, 2009a, p. 2

- 22). In addition, the Integrated Science Assessment noted uncertainties associated with the controlled human exposure studies using concentrated ambient particle systems which have been shown to modify the composition of ultrafine particles ( U.S. EPA, 2009a, p. 2

- 22, see also section 1.5.3).

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Page 256 of 423 The Policy Assessment recognized that there are relatively few epidemiological studies that have examined potential cardiovascular and respiratory effects associated with short

- term exposures to ultrafine particles ( U.S. EPA, 2011a, p. 2

- 51). These studies have reported inconsistent and mixed results ( U.S. EPA, 2009a, section 2.3.5). Collectively, in considering the body of scientific evidence availa ble in this review, the Integrated Science Assessment concluded that the currently available evidence was suggestive of a causal relationship between short

- term exposures to ultrafine particles and cardiovascular and respiratory effects. Furthermore, the
I ntegrated Science Assessment concluded that evidence was inadequate to infer a causal relationship between short

- term exposure to ultrafine particles and mortality as well as long

- term exposure to ultrafine particles and all outcomes evaluated ( U.S. EPA,
2 009a, sections 2.3.5, 6.2.12.3, 6.3.10.3, 6.5.3.3, 7.2.11.3, 7.3.9, 7.4.3.3, 7.5.4.3, and 7.6.5.3; Table 2

- 6). With respect to our understanding of ambient ultrafine particle concentrations, at present, there is no national network of ultrafine particle s amplers; thus, only episodic and/or site

- specific data sets exist ( U.S. EPA, 2009a, p. 2

- 2). Therefore, the Policy Assessment recognized a national characterization of concentrations, temporal and spatial patterns, and trends was not possible at this time, and the availability of ambient ultrafine measurements to support health studies was extremely limited ( U.S. EPA, 2011a, p. 2

- 51). In general, measurements of ultrafine particles are highly dependent on monitor location and, therefore, more subject to exp osure error than

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Page 257 of 423 accumulation mode particles ( U.S. EPA, 2009a, p. 2

- 22). Furthermore, the number of ultrafine particles generally decreases sharply downwind from sources, as ultrafine particles may grow into the accumulation mode by coagulation or condensa tion ( U.S. EPA, 2009a, p. 3

- 89). Limited studies of ambient ultrafine particle measurements have suggested that these particles exhibit a high degree of spatial and temporal heterogeneity driven primarily by differences in nearby source characteristics ( U. S. EPA, 2009a, p. 3

- 84). Internal combustion engines and, therefore, roadways are a notable source of ultrafine particles, so concentrations of these particles near roadways are generally expected to be elevated ( U.S. EPA, 2009a, p. 2

- 3). Concentrations of ultrafine particles have been reported to drop off much more quickly with distance from roadways than fine particles ( U.S. EPA, 2009a, p. 3

- 84). In considering both the currently available health effects evidence and the air quality data, the Policy Asses sment concluded that this information was still too limited to provide support for consideration of a distinct PM standard for ultrafine particles ( U.S. EPA, 2011a, p. 2

- 52). In addressing the issue of particle composition, the Integrated Science
Assessmen t concluded that, “[f]rom a mechanistic perspective, it is highly plausible that the chemical composition of PM would be a better predictor of health effects than particle size” ( U.S. EPA, 2009a, p. 6

- 202). Heterogeneity of ambient concentrations of
PM 2.5 constituents (e.g., elemental carbon, organic carbon, sulfates, nitrates) observed in different geographical regions as well as regional heterogeneity in PM 2.5 - related

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Page 258 of 423 health effects reported in a number of epidemiological studies are consistent with this hypothesis ( U.S. EPA, 2009a, section 6.6). With respect to the availability of ambient measurement data for fine particle components in this review, the Policy Assessment noted that there were now more extensive ambient PM 2.5 speciation measurement data a vailable through the Chemical Speciation Network (CSN) than in previous reviews ( U.S. EPA, 2011a, section 1.3.2 and Appendix B, section B.1.3). The Integrated Science Assessment observed that data from the CSN provided further evidence of spatial and seaso nal variation in both PM 2.5 mass and composition among cities and geographic regions ( U.S. EPA, 2009a, pp. 3

- 50 to 3

- 60; Figures 3

- 12 to 3

- 18; Figure 3

- 47). Some of this variation may be related to regional differences in meteorology, sources, and topograp hy ( U.S. EPA, 2009a, p. 2

- 3).
The currently available epidemiological, toxicological, and controlled human exposure studies evaluated in the Integrated Science Assessment on the health effects associated with ambient PM 2.5 constituents and categories of f ine particle sources used a variety of quantitative methods applied to a broad set of PM 2.5 constituents, rather than selecting a few constituents a priori ( U.S. EPA, 2009a, p. 2

- 26). Epidemiological studies have used measured ambient PM 2.5 speciation data , including monitoring data from the CSN, while all of the controlled human exposure and most of the toxicological studies have used concentrated ambient particles and analyzed the constituents therein

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Page 259 of 423 ( U.S. EPA, 2009a, p. 6

- 203). 80 The CSN provides PM 2.5 s peciation measurements generally on a one

- in

- three or one

- in

- six day sampling schedule and, thus, do es not capture data every day at most sites. 81 The Policy Assessment recognized that several new multi

- city studies evaluating short

- term exposures to fine particle constituents are now available. These studies continued to show an association between mortality and cardiovascular and/or respiratory morbidity effects and short

- term exposures to various PM 2.5 components including nickel, vanadium, elemental car bon, organic carbon, nitrates, and sulfates ( U.S. EPA, 2011a, section 2.3.1; U.S. EPA, 2009a, sections 6.5.2.5 and 6.6). Limited evidence is available to evaluate the health effects associated with long

term exposures to PM 2.5 components ( U.S. EPA, 2009a, section 7.6.2). The Policy Assessment noted the most significant new evidence was provided by a study that evaluated multiple PM 2.5 components and an indicator of traffic density in an

80 Most studies considered between 7 to 20 ambient PM 2.5 constituents, with elemental carbon, organic carbon, sulfates, nitrates, and metals most commonly measured. Many of the studies gr ouped the constituents with various factorization or source apportionment techniques to examine the relationship between the grouped constituents and various health effects. However, not all studies labeled the constituent groupings according to their pres umed source and a small number of controlled human exposure and toxicological studies did not use any constituent grouping. These differences across studies substantially limit any integrative interpretation of these studies (U.S. EPA, 2009a, p. 6

- 203). 81 To expand our understanding of the role of specific PM 2.5 components and sources with respect to the observed health effects, researchers have expressed a strong interest in having access to PM 2.5 speciation measurements collected more frequently (U.S. EP A, 2011a, p. 2

- 53, including footnote 47).

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Page 260 of 423 assessment of health effects related to long

- term exposure to PM 2.5 (L ipfert et al., 2006). Using health data from a cohort of U.S. military veterans and PM 2.5 measurement data from the CSN, Lipfert et al. (2006) reported positive associations between mortality and long

- term exposures to nitrates, elemental carbon, nickel, and vanadium as well as traffic density and peak ozone concentrations ( U.S. EPA, 2011a, p. 2

- 54; U.S. EPA, 2009a, pp. 7

- 89 to 7

- 90). With respect to source categories of fine particles potentially associated with a range of health endpoints, the Integrate d Science Assessment reported that the currently available evidence suggests associations between cardiovascular effects and a number of specific PM 2.5 – related source categories, including oil combustion, wood or biomass burning, motor vehicle emissions, and crustal or road dust sources ( U.S. EPA, 2009a, section 6.6; Table 6

- 18). In addition, a few studies have evaluated associations between PM 2.5 - related source categories and mortality. For example, o ne stud y reported an association between mo rtality and a PM 2.5 coal combustion factor (Laden et al., 2000), while other studies linked mortality to a secondary sulfate long

- range transport PM 2.5 source (Ito et al., 2006; Mar et al., 2006) ( U.S. EPA, 2009a, section 6.6.2.1). Other studies have looke d different components of particulate matter. There was less consistency in associations observed between selected sources of fine particles and respiratory health endpoints , which may be partially due to the fact that fewer studies have evaluated r espiratory

- related outcomes and measures. However, there was some evidence for PM 2.5 - related associations with secondary sulfate and

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Page 261 of 423 decrements in lung function in asthmatic and healthy adults ( U.S. EPA, 2009a, p. 6

- 211; Gong et al., 2005; Lanki et al., 20 06). A couple of studies have observed an association between r espiratory e ndpoints in asthmatics and surrogates for the crustal/soil/road dust and traffic sources of PM ( U.S. EPA, 200 9a, p. 6

- 205; Gent et al., 2009; Penttinen et al., 2006). Recent studies have shown that source apportionment methods have the potential to add useful insights into which sources and/or PM constituents may contribute to different health effects. Of partic ular interest are several epidemiological studies that compared source apportionment methods and reported consistent results across research groups ( U.S. EPA, 2009a, p. 6

- 211; Hopke et al., 2006; Ito et al., 2006; Mar et al., 2006; Thurston et al., 2005). These studies reported associations between total mortality and secondary sulfate in two cities for two different lag times. The sulfate effect was stronger for total mortality in Washington D.C. and for cardiovascular

- related

mor t ality in Phoenix ( U.S. EP A, 2009a, p. 6

- 204). These studies also found some evidence for associations with mortality and a number of source categories (e.g., biomass/wood combustion, traffic, copper smelter, coal combustion, sea salt) at various lag times ( U.S. EPA, 2009a, p. 6

- 20 4). Sarnat et al. (2008) compared three different source apportionment methods and reported consistent associations between emergency department visits for cardiovascular diseases with mobile sources and biomass combustion as well as increased respiratory

- related emergency department visits associated with secondary sulfate ( U.S. EPA, 2009a, pp. 6

- 204 and 6

- 211).

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Page 262 of 423 Collectively, in considering the currently available evidence for health effects associated with specific PM 2.5 components or groups of components associated with any source categories of fine particles as presented in the Integrated Science Assessment, the Policy Assessment concluded that additional information available in this review continues to provide evidence that many different constituents of the fine particle mixture as well as groups of components associated with specific source categories of fine particles are linked to adverse health effects ( U.S. EPA, 2011a, p. 2

- 55). However, as noted in the Integrated Science Assessment, while “[t]her e is some evidence for trends and patterns that link particular ambient PM constituents or sources with specific health outcomes...there is insufficient evidence to determine whether these patterns are consistent or robust” ( U.S. EPA, 2009a, p. 6

- 210). Asses sing this information, the Integrated Science Assessment concluded that “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, pp. 2

- 26 and 6

- 212). Therefore, the Policy Assessment concluded that the currently available evidence is not sufficient to support consideration of a separate indicator for a specific PM 2.5 component or group of components associated with any source category of fine particles. Furthermore, the Policy Assessment concluded that the evidence is not sufficient to support eliminating any component or group of components associated with any source categories of fine particles from the mix of fine par ticles included in the PM 2.5 indicator ( U.S. EPA, 2011a, p. 2

- 56).

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Page 263 of 423 The CASAC agreed with the EPA staff conclusions presented in the Policy
Assessmen t and concluded that it is appropriate to consider retaining PM 2.5 as the indicator for fine particles and further asserted, “There [is] insufficient peer

- reviewed literature to support any other indicator at this time” (Samet, 2010c, p. 12). CASAC expressed a strong desire for the EPA to “look ahead to future review cycles and reinvigorate support for the deve lopment of evidence that might lead to newer indicators that may correlate better with the health effects associated with ambient air concentrations of PM ...” (Samet, 2010c, p 2). Consistent with the staff conclusions presented in the Policy Assessment and CASAC advice, the Administrator proposed to retain PM 2.5 as the indicator for fine particles. Further, the Administrator provisionally concluded that currently available scientific information does not provide a sufficient basis for supplementing mass

- bas ed, primary fine particle standards with standards using a separate indicator for ultrafine particles or a separate indicator for a specific PM 2.5 component or group of components associated with any source categories of fine particles. In addition, the Ad ministrator also provisionally concluded that the currently available scientific information did not provide a sufficient basis for eliminating any individual component or group of components associated with any source categories from the mix of fine parti cles included in the PM 2.5 mass - based indicator.

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Page 264 of 423 The EPA received comparatively few public comments on issues related to the indicator for fine particles. 82 Some commenters emphasized the need to conduct additional research to more fully understand the eff ect of specific PM 2.5 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 on going and future research to reduce uncertainties in this area and for considering whether alternative indicator(s) may be appropriate to consider in future PM NAAQS reviews for standards intended to protect against the array of health effects that have be en associated with fine particles as indexed by PM 2.5 . For example, the PSR encouraged more research and monitoring related to PM 2.5 components and noted the importance of components associated with coal combustion (PSR, 2012, pp. 5 to 6). EPRI asserted th at “new” studies support focusing on EC and OC and encouraged the EPA to seriously consider the mass

- based approach (EPRI, 2012, p. 2). Likewise, Georgia Mining Association supported additional monitoring and research efforts related to PM 2.5 composition a nd specifically encouraged the evaluation of using particle number (e.g., particle count) (GMA, 2012, pp. 2 to 3). The Administrator agrees with CASAC as well as these commenters that the results of additional research and monitoring efforts will be helpf ul for informing future PM NAAQS reviews. Information from such studies could also help inform the

82 No public comments were submitted regarding the use of a different size cut for fine particles.

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Page 265 of 423 development of strategies that emphasize control of specific types of emission sources so as to address particles of greatest concern to public health. Howev er, based upon the scientific information considered in the Integrated Science Assessment as well as the public comments summarized above, the Administrator continues to take note there is evidence that many different constituents of the fine particle mixt ure as well as groups of components associated with specific sources of fine particles are linked to adverse health effects. Furthermore, she recognizes that the evidence is not yet sufficient to differentiate those constituents or sources that are most cl osely related to specific health outcomes nor to exclude any PM 2.5 components or sources of fine particles from the mix of particles included in the PM 2.5 indicator.
Having considered the public comments on this issue, the Administrator concurs with the P olicy Assessment conclusions and CASAC recommendations and concludes that it is appropriate to retain PM 2.5 as the indicator for fine particles.
2. Averaging Time In 1997, the EPA initially set both an annual standard, to provide protection from health effects associated with both long

- and short

- term exposures to PM 2.5 , and a 24

- hour standard to supplement the protection afforded by the annual standard (62 FR 38667 to 38668, July, 18, 1997). In the last review, the EPA retained both annual and 24

- hour a veraging times (71 FR 61164, October 17, 2006). These decisions were based, in part, on evidence of health effects related to both long

- term (from a year to several years) and short

- term (from less than one day to up to several days) measures of PM 2.5 .

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Page 266 of 423 The overwhelming majority of studies conducted since the last review continue to utilize annual (or multi

- year) and 24

- hour averaging times, reflecting the averaging times of the current PM 2.5 standards. These studies continue to provide evidence that health effects are associated with annual and 24

- hour averaging times. Therefore, the Policy Assessment concluded it is appropriate to retain the current annual and 24

- hour averaging times to provide protection from effects associated with both long

- and short

te rm PM 2.5 exposures ( U.S. EPA, 2011a, p. 2

- 57).
In considering whether the information available in this review supports consideration of different averaging times for PM 2.5 standards specifically with regard to considering a standard with an averaging time less than 24 hours to address health effects associated with sub

- daily PM 2.5 exposures, the Policy Assessment noted there continues to be a growing body of studies that provide additional evidence of effects associated with exposure periods less than 24

- h ours ( U.S. EPA, 2011a, p. 2

- 57). Relative to information available in the last review, recent studies provide additional evidence for cardiovascular effects associated with sub

- daily (e.g., one to several hours) exposure to PM, especially effects related t o cardiac ischemia, vasomotor function, and more subtle changes in markers of systemic inflammation, hemostasis, thrombosis and coagulation ( U.S. EPA, 2009a, section 6.2). Because these studies have used different indicators (e.g., PM 2.5 , PM 10 , PM 10

- 2.5 , u ltrafine particles), averaging times (e.g., 1, 2, and 4 hours), and health outcomes, it is difficult to draw conclusions about cardiovascular effects associated specifically with sub

- daily exposures to PM 2.5 .

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Page 267 of 423 With regard to respiratory effects associated with sub

- daily PM 2.5 exposures, the currently available evidence was much sparser than for cardiovascular effects and continues to be very limited. The Integrated Science Assessment concluded that for several studies of hospital admissions or medical visit s for respiratory diseases, the strongest associations were observed with 24

- hour average or longer exposures, not with less than 24

- hour exposures ( U.S. EPA, 2009a, section 6.3).
Collectively, the Policy Assessment concluded that this information, when

v iewed as a whole, is too unclear, with respect to the indicator, averaging time and health outcome, to serve as a basis for consideration of establishing a primary PM 2.5 standard with an averaging time shorter than 24

- hours at this time ( U.S. EPA, 2011a, p

. 2

- 57).
With regard to health effects associated with PM 2.5 exposure across varying seasons in this review, Bell et al. (2008) reported higher PM 2.5 risk estimates for hospitalization for cardiovascular and respiratory diseases in the winter compared to other seasons. In comparison to the winter season, smaller statistically significant associations were also reported between PM 2.5 and cardiovascular morbidity for spring and autumn, and a positive, but statistically non

- significant association was observed for the summer months. In the case of mortality, Zanobetti and Schwartz (2009) reported a
4

- fold higher effect estimate for PM 2.5 - associated mortali ty for the spring as compared to the winter. Taken together, these results provided emerging but limited evidence

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Page 268 of 423 that individuals may be at greater risk of dying from higher exposures to PM 2.5 in the warmer months and may be at greater risk of PM 2.5 - assoc iated hospitalization for cardiovascular and respiratory diseases during colder months of the year ( U.S. EPA, 2011a, p. 2

- 58). Overall, the Policy Assessment observed that there are few studies presently available to deduce a general pattern in PM 2.5 - rela ted risk across seasons. In addition, these studies utilized 24

- hour exposure periods within each season to assess the
PM 2.5 - associated health effects and do not provide information on health effects associated with a season

- long exposure to PM 2.5 . Due to these limitations in the currently available evidence, the Policy Assessment concluded that there was no basis to consider a seasonal averaging time separate from a 24

- hour averaging time.
Based on the above considerations, the Policy Assessment concluded that the currently available information provided strong support for consideration of retaining the current annual and 24

- hour averaging times but does not provide support for considering alternative averaging times ( U.S. EPA, 2011a, p. 2

- 58). In addition, CASAC considered it appropriate to retain the current annual and 24

- hour averaging times for the primary PM 2.5 standards (Samet, 2010c, pp. 2 to 3). At the time of the proposal, the Administrator concurred with the staff conclusions and CASAC advice and p roposed that the averaging times for the primary PM 2.5 standards should continue to include annual and 24

- hour averages to protect against health effects associated with long

- and short

term exposures. Furthermore, the Administrator provisionally concluded , consistent

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Page 269 of 423 with conclusions reached in the Policy Assessment and by CASAC, that the currently available information was too limited to support consideration of alternative averaging times to establish a national standard with a shorter

- than 24

- hour avera ging time or with a seasonal averaging time. The EPA received no significant public comments on the issue of averaging time for the PM 2.5 primary standards. The Administrator concurs with recommendations made by CASAC and the staff conclusions presented i n the Policy Assessment and concludes, as proposed, that it is appropriate to retain the current annual and 24

- hour averaging times for the primary PM 2.5 standards to protect against health effects associated with long

- and short

- term exposure periods.
3. For m The “form” of a standard defines the air quality statistic that is to be compared to the level of the standard in determining whether an area attains the standard. In this review, the EPA considers whether currently available information supports retaini ng or revising the forms for the annual or 24

- hour PM 2.5 standards.

a. Annual Standard In 1997, the EPA established the form of the annual PM 2.5 standard as an annual arithmetic mean, averaged over 3 years, from single or multiple community

- oriented monitors . This form was intended to represent a relatively stable measure of air quality and to characterize longer

- term area
- wide PM 2.5 concentrations, in conjunction with a
24

- hour standard designed to provide adequate protection against localized peak or

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Page 270 of 423 season al PM 2.5 concentrations. The level of the standard was to be compared to measurements made at each community

- oriented monitoring site, or, if specific criteria were met, measurements from multiple community

- oriented monitoring sites could be averaged (i.e. , spatial averaging) 83 (62 FR 38671 to 38672, July 18, 1997). The constraints were intended to ensure that spatial averaging would not result in inequities in the level of protection provided by the standard (62 FR 38672, July 18, 1997). This approach was

c onsistent with the epidemiological studies on which the PM 2.5 standard was primarily based, in which air quality data were generally averaged across multiple monitors in an area or were taken from a single monitor that was selected to represent community

w ide exposures.
In the last review, the EPA tightened the criteria for use of spatial averaging to
pr ovide increased protection for vulnerable populations exposed to PM 2.5 . 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 percent ages of minority populations (71 FR 61166/2, October 17, 2006; U.S. EPA, 2005, section 5.3.6.1).
In this review, as outlined in section III.B above and discussed more fully in section III.B.3 of the proposal, there now exist more health data such that the

83 Spatial averaging as part of the form of the annual PM 2.5 standard is unique to this standard and is not used wi th other PM standards nor with other NAAQS.

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Page 271 of 423 Integrated Science Assessment has identified persons from lower socioeconomic strata
as an at
- risk population ( U.S. EPA, 2009a, section 8.1.7; U.S. EPA, 2011a, section 2.2.1). Moreover, there now exist more years of PM 2.5 air quality data than were availab le in the last review. Consideration in the Policy Assessment of the spatial variability across urban areas that was revealed by this expanded data base has raised questions as to whether an annual standard that allows for spatial averaging, even within sp ecified constraints as narrowed in 2006 (71 FR 61165 to 61167, October 17, 2006) , would provide appropriate public health protection. In considering the potential for disproportionate impacts on at

- risk populations, the Policy Assessment considered an update of an air quality analysis conducted for the last review ( U.S. EPA, 2011a, pp. 2

- 59 to 60; Schmidt, 2011, Analysis A). This analysis focused on determining whether the spatial averaging provisions, as modified in 2006, could introduce inequities in protection for at

- risk populations exposed to PM 2.5 . Specifically, the Policy Assessment considered whether persons of lower socioeconomic
status , minority groups, or different age groups (i.e., children or older adults) are more likely than the genera l population to live in areas in which the monitors recording the highest air quality values in an area are located. Data used in this analysis included demographic parameters measured at the Census Block or Census Block Group level, including percent mino rity population, percent minority subgroup population, percent of persons living below the poverty level, percent of persons 18 years of age or older, and percent of persons 65 years of age and older. In each candidate geographic area,

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Page 272 of 423 data from the Census Block(s) or Census Block Group(s) surrounding the location of the monitoring site (as delineated by radii buffers of 0.5, 1.0, 2.0, and 3.0 miles) in which the highest air quality value was monitored were compared to the average of monitored values in the area. This analysis looked beyond areas that would meet the current spatial averaging criteria and considered all urban areas (i.e., Core Based Statistical Areas or CBSAs) with at least two valid annual desig n value monitors (Schmidt, 2011 , Analysis A). R ecognizing the limitations of such cross

- sectional analyses, the Policy Assessment observed that the highest concentrations in an area tend to be measured at monitors located in areas where the surrounding populations are more likely to live below the pove rty line and to have higher percentage of minorities ( U.S. EPA, 2011a, p.
2

- 60). Based upon the analysis described above, the Policy Assessment concluded that the existing constraints on spatial averaging, as modified in 2006, may be inadequate to avoid s ubstantially greater exposures in some areas, potentially resulting in disproportionate impacts on at

- risk populations of persons with lower SES levels as well as minorities. Therefore, the Policy Assessment concluded that it was appropriate to consider re vising the form of the annual PM 2.5 standard such that it did not allow for the use of spatial averaging across monitors. In doing so, the level of the annual PM 2.5 standard would be compared to measurements made at the monitoring site that

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Page 273 of 423 represents area
- wide air quality recording the highest PM 2.5 concentrations 84 ( U.S. EPA, 2011a, p. 2

- 60). The CASAC agreed with staff conclusions 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 Policy Assessment, 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 m onitors be eliminated for the reasons cited in the (first draft) Policy Assessment” (Samet, 2010c, p. 13). In its review of the second draft Policy Assessment, CASAC recognized “although much of the epidemiological research has been conducted using communi ty
- 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)

. Only two areas in the country used the initial spatial averaging provisions for demonstrating attainment with the primary annual PM 2.5 standard set in 1997 ( 70 FR 19847, April 14, 2005; U.S. EPA, 2006c ). Since these provisions were tightened in 2006 ,
no area has used spatial averaging to demonstrate attainment. No areas in the country

84 As discussed in section VIII.B.1 below, the EPA is revising several terms associated with PM 2.5 monitor placement. Specifically, the EPA is revoking the term “community

oriented” and replacing it with the term “area

- wide” monitoring.

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Page 274 of 423 are currently using the spatial averaging provisions to demonstrate attainment with the current primary annual PM 2.5 standard. In considering the Policy Assessment’s conclus ions based on the results of the analysis discussed above and concern over the evidence of potential disproportionate impacts on at

- risk populations as well as CASAC advice, the Administrator proposed to revise the form of the annual PM 2.5 standard to elim inate the use of spatial averaging. Thus, the Administrator proposed revising the form of the annual PM 2.5 standard to compare the level of the standard with measurements from each “appropriate” monitor
in an area 85 with no allowance for spatial averaging. Thus, for an area with multiple monitors, the appropriate reporting monitor with the highest design value would determine the attainment status for that area. Of the commenters noted in section III.D.2 above who supported a more stringent annual PM 2.5 stan dard, those who commented on the form of the annual PM 2.5 standard supported the EPA’s proposal to eliminat e the spatial averaging provisions. These commenters contended that the EPA ’s analyses of the potential impacts of spatial averaging, discussed above and in the proposal (77 FR 38924) , demonstrate d 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 pe ople to

85 As discussed in section VIII.B.2.b below, the EPA concludes that PM 2.5 monitoring sites at micro

- and middle

- scale locations should be comparable to the annual standard unless the monitoring site has been approved by the Regional Administrator as a “relatively unique micro

- scale, or localized hot

- spot, or unique middle

- scale site.”

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Page 275 of 423 unhealthy levels of pollution at specific locales even within an area meeting the standard” (ALA et al., 2012, p. 23 ). These commenters particularly focused on the importance for low

- income and minority populations of eliminating the spatial
averag ing 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. Other commenters (e.g., AAM , 2012 ; Dow , 20 12 ) also supported the elimination of spatial averaging in order to “avoid potential disproportionate impacts on at

- risk populations” and to maximize “the benefits to public health of reducing the annual
PM 2.5 standard.” However, these groups expressed con c ern 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 PM 2.5 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 a veraging 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
communit y area monitors), and since roadway monitoring locations will likely be worst

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Page 276 of 423 case monitors, the proposed NAAQS will become more stringent without targeting the
PM 2.5 species most harmful to human health” (Class of ’85 RRG, 2012, p. 6). Several commenters also ma intained 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, and ACC pointed o ut that PM 2.5 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 PM 2.5 st andard more consistent with the approaches used in the epidemiological studies upon which the standard is based. In addition, some
commenters also contended that the EPA failed to consider whether modifying, rather than eliminating, the constraints on spat ial averaging would have been sufficient to protect the public health. If so, th ese commenter s argued that “elimination of spatial averaging would go beyond what is requisite to protect the public health” (NAM et al., 2012, p. 20)

. 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
A gency notes that these comment er s did not challenge the analyses or considerations that provided the fundamental basis for the Administrator’s propos ed decision

. Rather,

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Page 277 of 423 these commenters generally raised 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 below).
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 below, a significant fraction of the population lives in proximit y 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

- ris k populations, exposed to fine particles in these areas. Thus, the EPA has made a determination that monitors representative of area

- wide air quality may be compared to the annual standard. The 24

- hour and annual NAAQS are designed to protect the public wi th 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 representat ive 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 not es that the annual standard is designed to protect against both long

and short

- term exposures through controlling the broad distribution of air quality across

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Page 278 of 423 an area over time. 86 It is fully consistent with the protection the standard is designed to provi de 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. In further considering these comments, the EPA notes that the stringency or level of protection provided by each NAAQS is not based solely on the form of the standard; rather, the four elements of the standard that together serve to define each standard (i.e., indicator, averaging time, form, and leve l) must be considered collectively in evaluating the protection afforded by each standard. Therefore, the EPA considers these comments

are also appropriate to discuss collectively with other issues related to the appropriate level for annual standard, and are discussed below in section s III.E.4.c

- d. In reaching a final decision on the form of the annual standard, the Administrator considers the available analyses, CASAC advice, and public comments on form as discussed above . She also considers related issu es in the public comments on the level of the annual standard as discussed in section III.E.4.c below . She notes that even when the annual PM 2.5 standard was first set in 1997, the spatial averaging provisions included constraints intended to ensure that i nequities in the level of protection would not result. These constraints on spatial averaging were tightened in the last review, based on an analysis showing the potential for spatial averaging to allow higher PM 2.5 concentrations in locations where subgro ups within the general population

86 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 comp ared to the 24

- hour standard.

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Page 279 of 423 we re potentially disproportionately exposed and hence, at disproportionate risk (e.g., low income and minority communities). The Administrator notes that in proposing to eliminate spatial averaging altogether in this review, she has relied on further analyses in the current review (Schmidt, 2011 , Analysis A ). As discussed above and in the proposal (77 FR 38924) , these analyses showed that the current constraints on spatial averaging may be inadequate in some a reas to avoid substantially greater exposures for people living near monitors recording the highest PM 2.5 concentrations. Such exposures could result in disproportionate impacts to at
- risk populations, including low

- income populations as well as minority g roups. On this basis, t he Administrator concludes 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 inc ome communities as well as minority communities were averaged together with lower concentrations measured at other sites in a large urban area. See ALA v. EPA , 134 F. 3d 388, 389 (D.C. Cir., 1998) (“this court has held that ‘NAAQS must protect not only

ave rage healthy individuals, but also sensitive citizens such as children,’ and ‘if a pollutant adversely affects the health of these sensitive individuals, EPA must strengthen the entire national standard’”) and Coalition of Battery Recyclers Association

v. EPA, 604 F 3d. 613, 617 (D.C. Cir., 2010) (“Petitioners’ assertion that the revised lead NAAQS is overprotective because it is more stringent than necessary to protect the entire population of young U.S. children ignores that the Clean Air Act allows prote ction

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Page 280 of 423 of sensitive subpopulations.”) In reaching this conclusion, the Administrator further notes that her concern over possible disproportionate PM 2.5 - related health impacts in
at
- risk populations extends to populations living near important sources of PM 2.5 , including the large populations that live near major roadways. 87 In light of all of the above considerations, including consideration of available analyses, CASAC advice, and public comments, the Administrator concludes that the current form of the an nual PM 2.5 standard should be revised to eliminate spatial averaging provisions. Thus, the level of the revised annual PM 2.5 standard established with this notice will be compared with measurements from each appropriate monitor in an area, with no allowanc e for spatial averaging. The Administrator’s conclusions with regard to the appropriate level of the annual PM 2.5 standard to set in conjunction with this form are discussed below in section III.E.4.d. b. 24

- Hour Standard In 1997, the EPA established the form of the 24

- hour PM 2.5 standard as the 98 th percentile of 24

- hour concentrations at each population

- oriented monitor within an area, averaged over three years (62 FR at 38671 to 38674, July 18, 1997). The Agency selected the 98 th percentile as an appropriate balance between adequately limiting the occurrence of peak concentrations and providing increased stability which, when averaged over 3 years, facilitated effective health protection through the development of more stable impl ementation programs. By basing the form of the standard on

87 Section VIII.B.3.b.i below discusses public comments specifically related to the proposed requirement for near

- road monitors.

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Page 281 of 423 concentrations measured at population

- oriented monitoring sites, the EPA intended to provide protection for people residing in or near localized areas of elevated concentrations. In the last review , in conjunction with lowering the level of the 24

- hour standard, the EPA retained this form based in part on a comparison with the 99 th percentile form. 88
In revisiting the stability of a 98 th versus 99 th percentile form for a 24

- hour standard intended to provide supplemental protection for a generally controlling annual standard, an analysis presented in the Policy Assessment considered air quality data reported in 2000 to 2008 to update our understanding of the ratio between peak

- to
mean PM 2.5 concentrat ions. This analysis provided evidence that the 98 th percentile value was a more stable metric than the 99 th percentile ( U.S. EPA, 2011a, Figure 2

- 2, p.
2

- 62). At the time of the proposal, the Agency recognized that the selection of the appropriate form of the 24

- hour standard includes maintaining adequate protection against peak 24

- hour concentrations while also providing a stable target for risk management programs, which serves to provide for the most effective public health

88 In reaching this final decision, the EPA recognized a technical problem associated with a potent ial bias in the method used to calculate the 98 th percentile concentration for this form. The EPA adjusted the sampling frequency requirement in order to reduce this bias. Accordingly, the Agency modified the final monitoring requirements such that areas t hat are within 5 percent of the standards are required to increase the sampling frequency to every day (71 FR 61164 to 61165, October 17, 2006).

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Page 282 of 423 protection in the long run. 89 As in previous reviews, the EPA recognized that a concentration

- based form, compared to an exceedance

- based form, was more reflective of the health risks posed by elevated pollutant concentrations because such a form gives proportionally greater weight to days when concentrations are well above the level of the standard than to days when the concentrations are just above the level of the standard. Further, the Agency provisionally concluded that a concentration

- based form, when averaged over three years, pr ovided an appropriate balance between limiting peak pollutant concentrations and providing a stable regulatory target, thus facilitating the development of more stable implementation programs. In considering the information provided in the Policy Assessment and 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 the level of the standard, the Administrator proposed to retain the 98 th percentile form of the 24

- hou r standard. The Administrator provisionally concluded that the 98 th percentile form represents an appropriate balance between adequately limiting the occurrence of peak concentrations and providing increased stability relative to an alternative 99 th percen tile form. 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. Many of the individuals and groups

89 See ATA III , 283 F.3d at 374

- 376 which concludes that it is legitimate for the EPA to consider overall stabil ity of the standard and its resulting promotion of overall effectiveness of NAAQS control programs in setting a standard that is requisite to protect the public health.

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Page 283 of 423 w ho supported a more stringent 24

- hour PM 2.5 standard noted in section III.D.2 above, however, recommended a more restrictive concentration

- based percentile form, specifically a 99 th percentile form. The limited number of these commenters who provided a spe cific rationale for this recommendation generally expressed their concern that the 98 th percentile form could allow too many days where concentrations exceeded the level of the standard, and thus fail to adequately protect public health. Other public

comme nters representing s tate and local air agencies and industry groups generally supported retaining the current 98 th percentile form. In most cases, these groups expressed the overall view that the current 24

- hour PM 2.5 standard, including the form of the cu rrent standard, should be retained. 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. 90 Nothing in the commenters’ views has p rovided a reason to change the Administrator’s previous conclusion regarding the appropriate balance represented in the proposed form of the 24

- hour PM 2.5 standard. Therefore, the

90 As just noted above, it is legitimate for the EPA to consider promotion of overall e ffectiveness 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; whe ther to adopt a 98 th percentile form for a 24

- hour standard intended to provide supplemental protection for a generally controlling annual standard.

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Page 284 of 423 Administrator concurs with staff conclusions presented in the Policy Assessm ent and CASAC recommendations and concludes that it is appropriate to retain the 98 th percentile form for the 24

- hour PM 2.5 standard.
4. Level In the last review, the EPA selected levels for the annual and the 24

- hour PM 2.5 standards using evidence of effects associated with periods of exposure that were most closely matched to the averaging time of each standard. Thus, as discussed in section III.A.1, the EPA relied upon evidence from long

- term exposure studies as the principal basis for selecting the level o f the annual PM 2.5 standard that would protect against effects associated with long

- term exposures. The EPA relied upon evidence from the short

- term exposure studies as the principal basis for selecting the level of the 24

- hour
PM 2.5 standard that would pr otect against effects associated with short

- term exposures. As summarized in section III.A.2 above, the 2006 decision to retain the level of the annual PM 2.5 standard at 15 μg/m 3 91 was challenged and on judicial review, the D.C. Circuit remanded the primar y annual PM 2.5 standard to the EPA, finding that EPA’s explanation for its approach to setting the level of the annual standard was inadequate.

a. General Approach for Considering Standard Levels

91 Throughout this section, the annual standard levels are denoted as integer values for simplicity, althoug h, as noted above in section II.B.1, Table 1, the annual standard level is defined to one decimal place, such that the current annual standard level is 15.0 μg/m 3 . Alternative annual standard levels discussed in this section are similarly defined to one de cimal place.

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Page 285 of 423 Building upon the lessons learned in the previous PM NAAQS rev iews, in considering alternative standard levels supported by the currently available scientific information, the Policy Assessment used an approach that integrated evidence

- based and risk

- based considerations, took into account CASAC advice, and considere d the issues raised by the court in remanding the primary annual PM 2.5 standard. Following the general approach outlined in section III.A.3 above, for the reasons discussed below, the Policy Assessment concluded it was appropriate to consider the protectio n afforded by the annual and 24

- hour standards taken together against mortality and morbidity effects associated with both long

- and short

- term PM 2.5 exposures. This was consistent with the approach taken in the review completed in 1997 rather than conside ring each standard separately, as was done in the review completed in 2006. Beyond looking directly at the relevant epidemiologic evidence, the Policy Assessment considered the extent to which specific alternative PM 2.5 standard levels were likely to redu ce the nature and magnitude of both long

- term exposure
- related mortality risk and short

- term exposure
- related mortality and morbidity risk ( U.S. EPA, 2011a, section 2.3.4.2; U.S.EPA, 2010a, section 4.2.2). As noted in section III.C.3 above, patterns of inc reasing estimated risk reductions were generally observed as either the annual or 24

- hour standard, or both, were reduced below the level of the current standards ( U.S. 2011a, Figures 2

- 11 and 2

- 12; U.S. EPA, 2010a, sections 4.2.2, 5.2.2, and 5.2.3).

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Page 286 of 423 Based on the quantitative risk assessment, the Policy Assessment observed, as discussed in section III.A.3, that analyses conducted for this and previous reviews demonstrated that much, if not most, of the aggregate risk associated with short

- term
exposure s 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, p. 2

- 9). Furthermore, as discussed in section III.C above and in section III.C.3 of the proposal, the Risk Assessment observed that alternative annual standard levels, when controlling, resulted in more consistent risk reductions across urban study areas, thereby potentially providing a more consistent degree of public health protection ( U.S. EPA, 2010a, pp. 5

- 15 to 5

- 16). In contrast, the Risk Assessment noted that the results of simulating alternative suites of PM 2.5 standards including different combinations of alternative annual and 24

- hour standard levels suggested that an alternativ e 24

- hour standard level can produce additional estimated risk reductions beyond that provided by an alternative annual standard alone. However, the degree of estimated risk reduction provided by alternative 24

- hour standard levels was highly variable, in part due to the choice of rollback approached used ( U.S. EPA, 2010a, p. 5

- 17). Based on its review of the second draft Policy Assessment, CASAC agreed with the EPA staff’s general approach for translating the available epidemiological evidence, risk infor mation, and air quality information into the basis for reaching conclusions on alternative standards for consideration. Furthermore, CASAC agreed “that it is

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Page 287 of 423 appropriate to return to the strategy used in 1997 that considers the annual and the short

- term st andards together, with the annual standard as the controlling standard, and the short

- term standard supplementing the protection afforded by the annual standard” and “considers it appropriate to place the greatest emphasis” on health effects judged to have evidence supportive of a causal or likely causal relationship as presented in the Integrated Science Assessment (Samet, 2010d, p. 1). Therefore, the Policy Assessment concluded, consistent with specific CASAC advice, that it was appropriate to set a “gen erally controlling” annual standard that will lower a wide range of ambient 24

- hour concentrations. The Policy Assessment concluded this approach would likely reduce aggregate risks associated with both long

and short

- term exposures with more consistency than a generally controlling 24

- hour standard and would be the most effective and efficient way to reduce total
PM 2.5 - related population risk and so provide appropriate protection. The staff believed this approach, in contrast to one focusing on a generall y controlling 24

- hour standard, would likely reduce aggregate risks associated with both long

- and short

- term exposures with more consistency and would likely avoid setting national standards that could result in relatively uneven protection across the cou ntry due to setting standards that were either more or less stringent than necessary in different geographical areas. The Policy Assessment recognized that an annual standard intended to serve as the primary means for providing protection against effects associated with both long

and short

- term PM 2.5 exposures cannot be expected to offer an adequate margin of

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Page 288 of 423 safety against the effects of all short

- term PM 2.5 exposures. As a result, in conjunction with a generally controlling annual standard, the Policy A ssessment concluded it was appropriate to consider setting a 24

- hour standard to provide supplemental protection, particularly for areas with high peak

- to
- mean ratios possibly associated with strong local or seasonal sources, or PM 2.5 - related effects that may be associated with shorter

- than

daily exposure periods. At the time of the proposal, the Administrator agreed with the approach discussed in the Policy Assessment as summarized in section III.A.3 above, and supported by CASAC, of considering the protec tion afforded by the annual and 24

- hour standards taken together for mortality and morbidity effects associated with both long

and short

- term exposures to PM 2.5 . Furthermore, based on the evidence and quantitative risk assessment, the Administrator provis ionally concluded it was appropriate to set a “generally controlling” annual standard that will lower a wide range of ambient 24

- hour concentrations, with a 24

- hour standard focused on providing supplemental protection, particularly for areas with high pea k

- to
- mean ratios possibly associated with strong local or seasonal sources, or PM 2.5 - related effects that may be associated with shorter

- than daily exposure periods. The Administrator provisionally concluded this approach would likely reduce aggregate risk s associated with both long

and short

- term exposures more consistently than a generally controlling 24

- hour standard and would be the most effective and efficient way to reduce total PM 2

- 5 - related population risk.

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Page 289 of 423 The Administrator is mindful that conside ring what standards are requisite to protect public health with an adequate margin of safety requires pub lic health policy judgments that neither overstate nor understate the strength and limitations of the evidence or the appropriate inferences to be draw n from the evidence. At the time of the proposal, in considering how to translate the available information into appropriate standard levels, the Administrator weighed the available scientific information and associated uncertainties and limitations. For t he purpose of determining what standard levels were appropriate to propose, the Administrator recognized, as did the EPA staff in the Policy Assessment, that there was no single factor or criterion that comprised the “correct” approach to weighing the vari ous types of available evidence and information, but rather there were various approaches that were appropriate to consider. The Administrator further recognized that different evaluations of the evidence and other information before the Administrator coul d reflect placing different weight on the relative strengths and limitations of the scientific information, and different judgments could be made as to how such information should appropriately be used in making public health policy decisions on standard l evels. This recognition led the Administrator to consider various approaches to weighing the evidence so as to identify appropriate standard levels to propose. In so doing, the Administrator encouraged extensive public comment on alternative approaches to weighing the evidence and other information so as to inform her public health policy judgments before reaching final decisions on appropriate standard levels.

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Page 290 of 423 b. Proposed Decisions on Standard Levels
i. Consideration of the Alternative Standard Levels in the Pol icy Assessment In recognizing the absence of a discernible population threshold below which effects would not occur, the Policy Assessment’s general approach for identifying alternative annual standard levels that were appropriate to consider focused on characterizing the part of the distribution of PM 2.5 concentrations in which we had the
most c onfidence in the associations reported in the epidemiological studies and conversely where our confidence in the association became appreciably lower. The most direct approach to address this issue, consistent with CASAC advice (Samet, 2010c, p.10), was to consider epidemiological studies reporting confidence intervals around
concentration

- response relationships ( U.S. EPA, 2011a, p. 2

- 63). Based on a thorough search of the available evidence, the Policy Assessment identified only one study (Schwartz et al., 2008) that conducted a multi

- model analysis to characterize confidence intervals around the estimated concentration

- response relationship. The Policy Assessment concluded that this single relevant analysis was too limited to serve as the principal basis f or identifying alternative standard levels in this review ( U.S. EPA, 2011a, p. 2

- 70). The Policy Assessment explored other approaches that considered different heuristic approaches to characterizing the part of the distribut ions of long

- term mean PM 2.5 concentrations that were most influential in generating health effect estimates in long

- and short

- term epidemiological studies, and placed greatest weight on those

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Page 29 1 of 423 studies that reported positive and statistically significant a ssociations ( U.S. EPA, 2011a, p. 2

- 63). First, as discussed in section III.A.3 above, the Policy Assessment considered the statistical metric used in previous reviews. This approach recognized our assumption that the strongest evidence of associations occu rs at concentrations around the long

term mean concentration. Thus, in earlier reviews, the EPA focused on identifying standard levels that were somewhat below the long

- term mean concentrations reported in PM 2.5 e pidemiological studies. The long

- term mean concentrations represented air quality data typically used in epidemiological analyses and provided a direct link between PM 2.5 concentrations and the observed health effects. Further, these data were available for all long

- an d short

- term exposure studies analyzed and, therefore, represented the data set available for the broadest set of epidemiological studies. However, consistent with CASAC’s comments on the second draft Policy
Assessment 92 (Samet, 2010d, p. 2), in preparing the final Policy Assessment, the EPA staff explored ways to take into account additional information from epidemiological studies, when available (Rajan et al., 2011). These analyses focused on evaluating different statistical metrics, beyond the long

- term mean concentration, to characterize the part of the distribution of PM 2.5 concentrations in which staff continued to have confidence in the associations observed in epidemiological studies and below which

92 While CASAC expressed the view that it would be most desirable to have information on concentration

- response relationships, they recognized that it would also be “preferable to have information on the concentrations that were most influentia l in generating the health effect estimates in individual studies” (Samet, 2010d, p. 2).

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Page 292 of 423 there was a comparative lack of data such that the staff’s confidence in the relationship was appreciably less. This would also be the part of the distribution of PM 2.5 concentrations which had the most influence on generating the health effect estimates reported in epidemiological studies. As discussed i n section III.A.3 above, the Policy Assessment recognized there was no one percentile value within a given distribution that was the most appropriate or “correct” way to characterize where our confidence in the associations becomes appreciably lower. The P olicy Assessment concluded that focusing on concentrations within the lower quartile of a distribution, such as the range from the 25 th to the 10 th percentile, was reasonable to consider as a region within which we begin to have appreciably less confidence in the associations observed in epidemiological studies. 93 In the EPA staff’s view, considering lower PM 2.5 concentrations, down to the lowest concentration observed in a study, would be a highly uncertain basis for selecting alternative standard levels ( U .S. EPA, 2009a, p. 2

- 71).

93 In the last review, staff believed it was appropriate to consider a level for an annual PM 2.5 standard that was somewhat below the averages of the long

- term concent rations across the cities in each of the key long

- term exposures studies, recognizing that the evidence of an association in any such study was strongest at and around the long

- term average where the data in the study are most concentrated. For example, th e interquartile range of long

- term average concentrations within a study and a range within one standard deviation around the study mean were considered reasonable approaches for characterizing the range over which the evidence of association is strongest (U.S. EPA, 2005, pp. 5

- 22 to 5

- 23). In this review, the Policy Assessment noted the interrelatedness of the distributional statistics and a range of one standard deviation around the mean which contains approximately 68 percent of normally distributed data , in that one standard deviation below the mean falls between the 25 th and 10 th percentiles (U.S. EPA, 2011a, p. 2

- 71).

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Page 293 of 423 As outlined in section III.A.3 above, the Policy Assessment recognized that there were two types of population

- level information to consider in identifying the range of
PM 2.5 concentrations which have the most influence on generat ing the health effect estimates reported in epidemiological studies. The most relevant information to consider was the number of health events (e.g., deaths, hospitalizations) occurring within a study population in relation to the distribution of PM 2.5 con centrations likely experienced by study participants. However, in recognizing that access to health event data may be restricted, and consistent with advice from CASAC (Samet 2010d, p.2), EPA staff also considered the number of participants within each stu dy area, in relation to the distribution of PM 2.5 concentrations (i.e., study population data), as a surrogate for health event data. In applying this approach, the Policy Assessment focused on identifying the part of the distribution of PM 2.5 concentrati ons which had the most influence on generating health effect estimates in epidemiological studies, as discussed in section III.A.3 above. As discussed below, in working with study investigators, the EPA staff was able to obtain health event data for three large multi

- city studies (Krewski et al., 2009; Zanobetti and Schwartz, 2009; Bell et al., 2008) and population data for the same three studies and one additional long

- term exposure study (Miller et al., 2007) , as documented in a staff memorandum (Rajan et al., 2011). 94 For the three studies for which both health event

94 The distributional statistical analysis of population

- level data built upon an earlier analysis that evaluated the distributions of a ir quality and associated population data

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Page 294 of 423 and study population data were available, the EPA staff analyzed the reliability of using study population data as a surrogate for health event data. Based on these analyses, the EPA staff rec ognized that the 10 th and 25 th percentiles of the health event and study population distributions are nearly identical and concluded that the distribution of population data can be a useful surrogate for event data, providing support for consideration of t he study population data for Miller et al. (2007), for which health event data were not available (Rajan et al., 2011, Analysis 1 and Analysis 2, in particular, Table 1 and Figures 1 and 2). With regard to the long

- term mean PM 2.5 concentrations which are relevant to the first approach, Figures 1 through 3 ( U.S. EPA, 2011a, Figures 2

- 4, 2

- 5, 2

- 6, and 2

- 8) summarize data available for multi

- city, long

- and short

- term exposure studies that evaluated endpoints classified in the Integrated Science Assessment as having evidence of a causal or likely causal relationship or evidence suggestive of a causal relationship, showing the studies with long

- term mean PM 2.5 concentrations below 17 μg/m 3

. 95 As discussed in more detail in section III.E.4.b of the proposal, Figu res 1 and 3 summarize the health outcomes evaluated, relative risk estimates, air quality data, and geographic scope for long

- and short

- term exposure studies, respectively, that evaluated mortality (evidence of a causal relationship); cardiovascular effec ts (evidence of a causal
for three long

- term exposure studies and three short

- term exposure studies (Schmidt et al., 2010, Analysis 2). 95 Additional studies presented and assessed in the Integrated Science Assessment report effects at higher long

- term mean PM 2.5 concentrations (e.g., U.S. EPA, 2009a, Figures 2

- 1, 2

- 2, 7

- 6, and 7

- 7).

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Page 295 of 423 relationship); and respiratory effects (evidence of a likely causal relationship) in the general population, as well as in older adults, an at

- risk population. Figure 2 provides this same summary information for long

- term exposure studies that evaluated respiratory effects (evidence of a likely causal relationship) in children, an at

- risk population, as well as developmental effects (evidence suggestive of a causal relationship).

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Page 296 of 423 Figure 1. Summary of Effect Estimates (per 10 μg/m 3 

### ) and Air Quality Distributions for Multi
- City, Long - term PM 2.5 

### Exp osure Studies of the General Population and Older Adults 96 , 97 , 98

96 

### The air quality data for the Miller et al. (2007) study is discussed more fully in the Response to Comments document. 97 

### The Goss et al. (2004) study patients over the age of 6 years enrolled in the Cystic Fibrosis Foundation National Patient Reg istry in 1999 and 2000. The average age of the study participants w as 18.4 (SD 10). 98 The air quality data reported in Figure 1 of the proposal incorrectly identified the long

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

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

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

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

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

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

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Page 297 of 423 Source: U.S. EPA, 2011a, Figure 2

- 4

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Page 298 of 423 Figure 2. Summary of Effect Estimates (per 10 μg/m 3 

### ) and Air Quality Distributions for Multi
- City, Long - term PM 2.5 

### Exposure Studies of Children

Source: U.S. EPA, 2011a, Figure 2

- 5

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Page 299 of 423 Figure 3. Summary of Effect Estimates (per 10 μg/m 3 

### ) and Air Quality Distributions for Multi
- City, Short
- term PM 2.5 

### Exposure Studies of the General Population and Older Adults

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Page 300 of 423

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Page 301 of 423 Source: U.S. EPA, 2011a, Figure 2

- 6

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Page 302 of 423 With regard to consideration of additional information from epidemiological studies which was relevant to the second approach, the EPA staff compiled a summary of the range of PM 2.5 concentrations corresponding with the 25 th to 10 th percentiles of health event or study population data from the four multi

- city studies, for which distributional statistics are available 99 ( U.S. EPA, 2011a, Figure 2

- 7; Rajan et al., 2011, Table 1). By considering this approach, one could focus on the rang e of
PM 2.5 concentrations below the long

- term mean ambient concentrations over which we continue to have confidence in the associations observed in epidemiological studies (e.g., above the 25 th percentile) where commensurate public health protection could be obtained for PM 2.5 - related effects and, conversely, identify the range in the distribution below which our confidence in the associations is appreciably less, to identify alternative annual standard levels. The mean PM 2.5 concentrations associated with the studies summarized in Figures 1, 2, and 3 and with the distributional statistics analyses (Rajan et al., 2011) are based on concentrations averaged across ambient monitors within each area included in a given study and then averaged across study

areas to calculate an overall study mean concentration, as discussed above. Figure 4, discussed in more detail in section III.E.4.a of the proposal, summarizes statistical metrics for those key studies 100 included
in

99 The EPA staff obtained health event data (e.g., number of deaths, hospitalizations) occurring in a study population for three multi

- city studies (Krewski et al., 2009; Zanobetti and Schwartz, 2009 ; Bell et al., 2008) and study population data were obtained for the same three studies and one additional study (Miller et al., 2007) (U.S. EPA, 2011a, p.2

- 71). If health event or study population data were available for additional studies, the EPA could employ distributional statistics to identify the broader range of PM 2.5 concentrations that were most influential in generating health effect estimates in those studies. 100 Long

- and short

- term exposure studies considered “key” studies for consideration ar e summarized in Figure 4 and include those studies observing effects for which the evidence supported a causal or

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likely causal association. This figure represents the subset of multi

- city studies included in Figures 1 through 3 that provided evidence of p ositive and generally statistically significant effects associated in whole or in part with more recent air quality data, generally representing health effects associated

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Page 304 of 423 Figure 4. Translating Epidemiol ogical Evidence from Multi
- City Exposure Studies into an Annual PM 2.5 

### Standard 101

101 

### The air quality data for the Miller et a l. (2007) study is discussed more fully in the Response to Comments document.

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Page 305 of 423

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Page 306 of 423 Source: U.S. EPA, 2011a, Figure 2

-

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5

- 307 Figures 1, 2, and 3 that provide evidence of positive and generally statistically significant PM 2.5 - related effects, which are relevant to the two approaches for translating epidemiological evidence into potential standard levels as discussed above. The top of Figure 4 includes information for long

- term exposure studies evaluating health outcomes classi fied as having evidence of a cau s al or likely cau s al relationship with PM 2.5 exposures (long

- term mean PM 2.5 concentrations indicated by diamond symbols). The middle of Figure 4 includes information for short

- term exposure studies evaluating health outcome s classified as having evidence of a

cau s al or likely cau s al relationship with PM 2.5 exposures (long

- term mean PM 2.5 concentrations indicated by triangle symbols). The bottom of Figure 4 includes information for long

- term exposures studies evaluating healt h outcomes classified as having evidence suggestive of a causal relationship (long

- term mean PM 2.5 concentrations indicated by square symbols). Figure 4 also summarizes the range of PM 2.5 concentrations corresponding with the 25 th (indicated by solid circl es) to 10 th (indicated by open circles) percentiles of the health event or study population data from the four multi

- city studies (highlighted in bold text) for which distributional statistics are available. In considering the evidence, the Policy Assessme nt recognized that NAAQS are standards set so as to provide requisite protection, neither more nor less stringent than necessary to protect public health, with an adequate margin of safety. This judgment, ultimately made by the Administrator, involves weig hing the strength of the evidence and the inherent uncertainties and limitations of that evidence. Therefore, depending on the weight

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- 308 placed on different aspects of the evidence and inherent uncertainties, consideration of different alternative standard le vels could be supported. Given the currently available evidence discussed in more detail in section III.E.4.b of the proposal and considering the various approaches discussed above, the Policy Assessment concluded it was appropriate to focus on an annual standard level within a range of about 12 to 11 μg/m 3 ( U.S. EPA, 2011a, pp. 2

- 82, 2

- 101, and 2

- 106). As illustrated in Figure 4, the Policy Assessment recognized that a standard level of 12 μg/m 3 , at the upper end of this range, was somewhat below the long

- term mean PM 2.5 concentrations reported in all the multi

- city, long

and short

- term exposure studies that provided evidence of positive and statistically significant associations with health effects classified as having evidence of a causal or likely caus al relationship, including premature mortality and hospitalizations and emergency department visits for cardiovascular and respiratory effects as well as respiratory effects in children. Further, a level of 12 μg/m 3 would reflect consideration of additiona l population

- level information from such epidemiological studies in that it generally corresponded with approximately the 25 th percentile of the available distributions of health events data in the studies for which population

- level information was availab le. In addition, a level of 12 μg/m 3 would reflect some consideration of studies that provided more limited evidence of reproductive and developmental effects, which were suggestive of a causal relationship, in that it was about at the same level as the lo west long

- term mean PM 2.5 concentrations reported in such studies (see Figure 4).

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- 309 Alternatively the Policy Assessment recognized that an annual standard level of 11 μg/m 3 , at the lower end of this range, was well below the lowest long

- term mean PM 2.5 concentrations reported in all multi

- city long

- and short

- term exposure studies that provide evidence of positive and statistically significant associations with health effects classified as having evidence of a causal or likely causal relationship. A lev el of 11 μg/m 3 would reflect placing more weight on the distributions of health event and population data, in that this level was within the range of PM 2.5 concentrations corresponding to the 25 th and 10 th percentiles of all the available distributions of such data. In addition, a level of 11 μg/m 3 was somewhat below the lowest long

- term mean PM 2.5 concentrations reported in reproductive and developmental effects studies that are suggestive of a causal relationship. Thus, a level of 11 μg/m 3 would reflect a n approach to translating the available evidence that places relatively more emphasis on margin of safety considerations and less certain causal relationships than would a standard set at a higher level. Such a policy approach would tend to weigh uncertain ties in the evidence in such a way as to avoid potentially underestimating PM 2.5 - related risks to public health. Further, recognizing the uncertainties inherent in identifying any particular point at which our confidence in reported associations becomes ap preciably less, the Policy Assessment concluded that the available evidence did not provide a sufficient basis to consider alternative annual standard levels below 11 μg/m 3 ( U.S. EPA, 2011a, p. 2

- 81). The Policy Assessment also considered the extent to wh ich the available evidence provided a basis for considering alternative annual standard levels above 12 μg/m 3 . As discussed below, the Policy Assessment concluded that it could be reasonable to consider a

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- 310 standard level up to 13 μg/m 3 based on a policy app roach that weighed uncertainties in the evidence in such a way as to avoid potentially overestimating PM 2.5 - related risks to public health, especially to the extent that primary emphasis was placed on long

- term exposure studies as a basis for an annual sta ndard level. A level of 13 μg/m 3 was somewhat below the long

- term mean PM 2.5 concentrations reported in all but one of the long

- term exposure studies providing evidence of positive and statistically significant associations with PM 2.5 - related health effect s classified as having a causal or likely causal relationship. As shown in Figure 4, the one long

- term exposure study with a long

- term mean PM 2.5 concentration just below 13 μg/m 3 was the Miller et al., ( 2007) study . However, as noted in section III.D.1.a of the proposal and discussed in more detail in the Response to Comments document , the Policy Assessment observed that in comparison to other long

- term exposure studies, the Miller et al. study was more limited in that it was based on only one year of air quality data and the one year was after the health outcomes were reported ( U.S. EPA, 2011a, pp. 2

- 81 to 2

- 82). Thus, to the extent that less weight was placed on the Miller et al. study than on other long

- term exposure studies with more robust air quality data, a level of 13 μg/m 3 could be considered as being protective of long

- term exposure related effects classified as having a causal or likely causal relationship. In also considering short

- term exposure studies, however, the Policy Assessment noted that a level of 13 μg/m 3 was below the long

- term mean PM 2.5 concentrations reported in most but not all such studies . In particular , two studies

-- Burnett et al. (2004) and Bell et al. (2008)

-- reported long

- term mean PM 2.5 concentration s of 12.8 and 12.9 μg/ m 3 , respectively. In considering these studies, the Policy Assessment found no basis to conclude that these two

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- 311 studies were any more limited or uncertain than the other short

- term exposure studies shown in Figures 3 and 4 ( U.S. EPA, 2011a, p. 2

- 82). On this basis, as discussed below, the Policy Assessment concluded that consideration of an annual standard level of 13 μg/m 3 would have implications for the degree of protection that would need to be provided by the 24

- hour standard , in order that the suite of PM 2.5 standards, taken together, would provide appropriate protection from effects on public health related to short

- term exposure to PM 2.5 ( U.S. EPA, 2011a, p. 2

- 82). The Policy Assessment also noted that a standard level of 1 3 μg/m 3 would reflect a judgment that the uncertainties in the epidemiological evidence as summarized in section III.B above and discussed in more detail in section III.B.2 of the proposal, including uncertainties related to the heterogeneity observed in t he epidemiological studies in the eastern versus western parts of the U.S., the relative toxicity of PM 2.5 components, and the potential role of

co - pollutants, are too great to warrant placing any weight on the distributions of health event and population data that extend down below the long

- term mean concentrations into the lower quartile of the data. This level would also reflect a judgment that the evidence from reproductive and developmental effects studies that is suggestive of a causal relationship wa s too uncertain to support consideration of any lower level. Beyond evidence

- based considerations, the Policy Assessment also considered the extent to which the quantitative risk assessment supported consideration of these alternative standard levels or pr ovided support for lower levels. In considering simulations of just meeting alternative annual standard levels within the range of 13 to 11 μg/m 3 (in conjunction with the

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- 312 current 24

- hour standard level of 35 μg/m 3 ), the Policy Assessment concluded that imp ortant public health improvements are associated with risk reductions estimated for standard levels of 13 and 12 μg/m 3 and noted that the level of 11 μg/m 3 was not included in the quantitative risk assessment. The Policy Assessment noted that the overall c onfidence in the quantitative risk estimates varied for the different alternative standard levels evaluated and was stronger for the higher levels and substantially lower for the lowest level evaluated (i.e., 10 μg/m 3 ). Based on the above considerations, t he Policy Assessment concluded that the quantitative risk assessment provided support for considering alternative annual standard levels within a range of 13 to 11 μg/m 3 , but did not provide strong support for considering lower alternative standard levels ( U.S. EPA, 2011a, pp. 2

- 102 to 2

- 103). Taken together, the Policy Assessment concluded that consideration of alternative annual standard levels in the range of 13 to 11 μg/m 3 may be appropriate. Furthermore, the Policy Assessment concluded that the current ly available evidence most strongly supported consideration of an alternative annual standard level in the range of 12 to 11 μg/m 3 ( U.S. EPA, 2011a, p. 2

- 82). The Policy Assessment concluded that an alternative level within the range of 12 to 11 μg/m 3 woul d more fully take into consideration the available information from all long

and short

- term PM 2.5 exposure studies, including studies of at

- risk populations, than would a higher level. This range also reflected placing weight on information from studies t hat helped to characterize the range of PM 2.5 concentrations over which we continue to have confidence in the associations observed in epidemiological studies, as well as the extent to which our confidence in the associations was appreciably less at lower concentrations.

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- 313 As recognized in sections III.A.3 and III.E.4.a above, an annual standard intended to serve as the primary means for providing protection from effects associated with both long

and short

- term PM 2.5 exposures is not expected to provide app ropriate protection against the effects of all short

- term PM 2.5 exposures (unless established at a level so low as to undoubtedly provide more protection than necessary for long

- term exposures). Of particular concern are areas with high peak

- to
- mean ratios possibly associated with strong local or seasonal sources,
or PM 2.5 - related effects that may be associated with shorter

- than

- daily exposure periods. As a result, the Policy Assessment concluded that it was appropriate to consider alternative 24

- hour
PM 2.5 standard levels that would supplement the protection provided by an annual standard. As outlined in section III.A.3 above, the Policy Assessment considered the available evidence from short

- term PM 2.5 exposure studies, as well as the uncertainties and li mitations in that evidence, to assess the degree to which alternative annual and 24

- hour PM 2.5 standards can be expected to reduce the estimated risks attributed to short

- term fine particle exposures. In considering the available epidemiological evidence, the Policy Assessment took into account information from multi

- city studies as well as single

- city studies. The Policy Assessment considered the distributions of 24

- hour PM 2.5 concentrations reported in short

- term exposure studies, focusing on the 98 th per centile concentrations to match the form of the 24

- hour standard as discussed in section III.E.3.b above. In recognizing that the annual and 24

- hour standards work together to provide protection from effects associated with short

- term PM 2.5 exposures, the Policy Assessment also considered information on the long

- term mean PM 2.5 concentrations from these studies.

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- 314 In addition to considering the epidemiological evidence, the Policy Assessment considered air quality information, specifically peak

- to
- mean ratio s using county

- level 24

- hour and annual design values, to characterize air quality patterns in areas possibly associated with strong local or seasonal sources. These patterns helped in understanding the extent to which different combinations of annual and 24

- hour standards would be consistent with the policy goal of setting a generally controlling annual standard with a 24

- hour standard that provides supplemental protection especially for areas with high peak

- to
- mean ratios ( U.S. EPA, 2011a, p.
2

- 14).
In considering the information provided by the short

- term exposure studies, the Policy Assessment recognized that to the extent these studies were conducted in areas that likely did not meet one or both of the current standards, such studies did not help info rm the characterization of the potential public health improvements of alternative standards set at lower levels. Therefore, in considering the short

- term exposure studies to inform staff conclusions regarding levels of the 24

- hour standard that are approp riate to consider, the Policy Assessment placed greatest weight on studies conducted in areas that likely met both the current annual and 24

- hour standards. With regard to multi

- city studies that evaluated effects associated with short

- term PM 2.5 exposures , as summarized in Figure 3 above and discussed in more detail in section III.E.4.c of the proposal, the Policy Assessment noted that, to the extent air quality distributions were reduced to reflect just meeting the current 24

- hour standard, additional pro tection would be anticipated for the effects observed in the three multi

- city studies with 98 th percentile values

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- 315 greater than 35 μg/m 3 (Burnett et al., 2004; Burnett and Goldberg, 2003; Franklin et al., 2008). In the three additional studies with 98 th per centile values below 35 μg/m 3 , specifically 98 th percentile concentrations of 34.2, 34.3, and 34.8 μg/m 3 , the Policy Assessment noted that these studies reported long

- term mean PM 2.5 concentrations of 12.9, 13.2, and 13.4 μg/m 3 , respectively (Bell et al., 2008; Zanobetti and Schwartz, 2009; Dominici et al., 2006a). To the extent that consideration was given to revising the level of the annual standard, as discussed in section III.E.4.b of the proposal, the Policy Assessment reco gnized that potential changes associated with meeting such an alternative annual standard would result in lowering risks associated with both long

- and short

- term PM 2.5 exposures. Consequently, in considering a 24

- hour standard that would operate in conjun ction with an annual standard to provide appropriate public health protection, the Policy Assessment noted that to the extent that the level of the annual standard was revised to within a range of 13 to 11 μg/m 3 , in particular in the range of 12 to 11 μg/ m 3 , additional protection would be provided for the long

- term effects observed in these multi

- city studies ( U.S. EPA, 2011a, p. 2

- 84). Based on this information, the Policy Assessment concluded that the multi

- city, short

term exposure studies generally pro vided support for retaining the 24

- hour standard level at 35 μg/m 3 so long as the standard is in conjunction with an annual standard level revised to within a range of 12 to 11 μg/m 3 ( U.S. EPA, 2011a, p. 2

- 84). Alternatively, in conjunction with an annual standard level of 13 μg/m 3 , the Policy Assessment concluded that the multi

- city studies provided limited support for revising the 24

- hour standard level somewhat below 35 μg/m 3 , such as down to 30 μg/m 3 , based on one study (Bell et al., 2008) that reported positive and

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- 316 statistically significant effects with an overall 98 th percentile value below the level of the
current 24

- hour standard and an overall long

- term mean concentration slightly less than 13 μg/m 3 (Figure 3; U.S. EPA, 2011a, p. 2

- 84). In reachin g staff conclusions regarding alternative 24

- hour standard levels that were appropriate to consider, the Policy Assessment also took into account relevant information from single

- city studies that evaluated effects associated with short

- term PM 2.5 exposure s. The Policy Assessment recognized that these studies may provide additional insights regarding impacts on at

- risk populations and/or on areas with isolated peak concentrations. As discussed in more detail in section III.E.4.c of the proposal, although a number of single

- city studies reported effects at appreciably lower PM 2.5 concentrations than multi

- city short

- term exposure studies, the uncertainties and limitations associated with the single

- city studies were considerably greater than those associated with the multi

- city studies and, thus, the Policy Assessment concluded there was less confidence in using these studies as a basis for setting the level of a standard. Therefore, the Policy Assessment concluded that the multi

- city short

- term exposure stud ies provided the strongest evidence to inform decisions on the level of the 24

- hour standard, and the single

- city studies did not warrant consideration of 24

- hour standard levels different from those supported by the multi

- city studies ( U.S. EPA, 2011a, p. 2

- 88). In addition to considering the epidemiological evidence, the Policy Assessment took into account air quality information based on county

- level 24

- hour and annual design values to understand the public health implications of the alternative standar d levels supported by the

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- 317 currently available scientific evidence, as discussed in section III.E.4.b above. Consistent with the general approach discussed in section III.A.3 above, the Policy Assessment considered the extent to which different combinations of alternative annual and 24

- hour standard levels based on the evidence would support the policy goal of lowering annual and 24

- hour air quality distributions by using the annual standard to be the “generally controlling” standard in conjunction with set ting the 24

- hour standard to provide supplemental protection ( U.S. EPA, 2011a, pp 2

- 88 to 2

- 91, Figure 2

- 10). Using information on the relationship of the 24

- hour and annual design values, the Policy Assessment examined the implications of three alternati ve suites of PM 2.5 standards identified as appropriate to consider based on the currently available scientific evidence, as discussed above. The Policy Assessment concluded that an alternative suite of PM 2.5 standards that would include an annual standard level of 11 or 12 μg/m 3 and a 24

- hour standard with a level of 35 μg/m 3 (i.e., 11/35 or 12/35) would result in the annual standard being the generally controlling standard in most areas although the 24

- hour standard would continue to be the generally contr olling standard in the Northwest ( U.S. EPA, 2011a, pp. 2

- 89 to 2

- 91 and Figure 2

- 10). These Northwest counties generally represented areas where the annual mean PM 2.5 concentrations have historically been low but where relatively high 24

- hour concentration s occur, often related to seasonal wood smoke emissions. Alternatively, combining an alternative annual standard of 13 μg/m 3 with a 24

- hour standard of 30 μg/m 3 would result in many more areas across the country in which the 24

- hour standard would likely b ecome the controlling standard (the standard driving air quality distributions lower) than if an alternative annual

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- 318 standard of 12 or 11 μg/m 3 were paired with the current level of the 24

- hour standard (i.e., 35 μg/m 3 ). The Policy Assessment concluded tha t consideration of retaining the 24

- hour standard level at 35 μg/m 3 would reflect placing greatest weight on evidence from multi

- city studies that reported positive and statistically significant associations with health effects classified as having

a causa l or likely causal relationship. In conjunction with lowering the annual standard level, especially within a range of 12 to 11 μg/m 3 , this alternative recognized additional public health protection against effects associated with short

- term PM 2.5 exposures which would be provided by lowering the annual standard such that revision to the 24

- hour standard would not be warranted ( U.S. EPA, 2011a, p. 2

- 91). Beyond evidence

- based considerations, the Policy Assessment also considered the extent to which the quan titative risk assessment supported consideration of retaining the
current 24

- hour standard level or provided support for lower standard levels. In considering simulations of just meeting the current 24

- hour standard level of 35 μg/m 3 or alternative levels of 30 or 25 μg/m 3 (in conjunction with alternative annual standard levels within a range of 13 to 11 μg/m 3 ), the Policy Assessment noted that the overall confidence in the quantitative risk estimates varied for the different standard levels evaluated and was stronger for the higher levels and substantially lower for the lowest level evaluated (i.e., 25 μg/m 3 ). Based on this information, the Policy Assessment concluded that the quantitative risk assessment provided support for consider ing a 24

- hour standard level of 35 or 30 μg/m 3 (in conjunction with an

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- 319 alternative standard level within a range of 13 to 11 μg/m 3 ) but did not provide strong support for considering lower alternative 24

- hour standard levels ( U.S. EPA, 2011a, pp. 2

- 102 to 2

- 103). Taken together, the Policy Assessment concluded that while it was appropriate to consider an alternative 24

- hour standard level within a range of 35 to 30 μg/m 3 , the currently available evidence most strongly supported consideration for retaining t he current 24

- hour standard level at 35 μg/m 3 in conjunction with lowering the level of the annual standard within a range of 12 to 11 μg/m 3 ( U.S. EPA, 2011a, p. 2

- 92).
ii. CASAC Advice Based on its review of the second draft Policy Assessment, CASAC agreed wi th the general approach for translating the available epidemiological evidence, risk information, and air quality information into the basis for reaching conclusions on alternative standards for consideration. Furthermore, CASAC agreed “that it is appropri ate 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” and “considers it appropriate to place the greatest emphasis” on health effects judged to have evidence supportive of a causal or likely causal relationship as presented in the Integrated Science Assessment (Samet, 2010d, p. 1). CASAC concluded that the range of levels presented in the second draft Policy Assessment (i.e., alternative annual standard levels within a range of 13 to 11 μg/m 3 and alternative 24

- hour standard levels within a range of 35 to 30 μg/m 3 ) “are supported by the epidemiological and toxico logical evidence, as well as by the risk and air quality information

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- 320 compiled” in the Integrated Science Assessment, Risk Assessment, and second draft Policy Assessment. CASAC further noted that “[a]lthough there is increasing uncertainty at lower levels, there is no evidence of a threshold (i.e., a level below which there is no risk for adverse health effects)” (Samet, 2010d, p. ii). Although CASAC supported the alternative standard level ranges presented in the second draft Policy Assessment, it did not express support for any specific levels or combinations of standards. Rather, CASAC encouraged the EPA to develop a clearer rationale in the final Policy Assessment for staff conclusions regarding annual and 24

- hour standards that were appropriate to consi der, including consideration of the combination of these standards supported by the available information (Samet, 2010d, p. ii). Specifically, in commenting on a distributional statistical analysis of air quality and associated population data presented in the second draft Policy Assessment, CASAC encouraged staff to focus on information related to the concentrations that were most influential in generating the health effect estimates in individual studies to inform alternative standard levels. CASAC urged that the EPA redo that analysis using health event or study population data (Samet, 2010d, p. 2). CASAC also commented that the approach presented in the second draft Policy Assessment to identify alternative 24

- hour standard levels which focused on peak

- t o - mean ratios was not relevant for informing the actual level (Samet 2010d, p. 4). Further, they expressed the concern that the combinations of annual and 24

- hour standard levels discussed in the second draft Policy Assessment (i.e., in the range of 13 to 11 μg/m 3 for the annual standard, in conjunction with retaining the current 24

- hour
PM 2.5 standard level of 35 μg/m 3 ; alternatively, revising the level of the 24

- hour standard to 30

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- 321 μg/m 3 in conjunction with an annual standard level of 11 μg/m 3 ) “may not b e adequately inclusive” and “[i]t was not clear why, for example a daily standard of 30 μg/m 3 should only be considered in combination with an annual level of 11 μg/m 3 ” (Samet, 2010d, p. ii). CASAC encouraged the EPA to more clearly explain its rationale f or identifying the 24

- hour/annual combinations that are appropriate for consideration (Samet 2010d, p. ii). In considering CASAC’s advice as well as public comment on the second draft Policy Assessment, the EPA staff conducted additional analyses and modi fied their conclusions regarding alternative standard levels that were appropriate to consider. The staff conclusions in the final Policy Assessment ( U.S. EPA, 2011a, section 2.3.4.4) differed somewhat from the alternative standard levels discussed in the second draft Policy Assessment ( U.S. EPA, 2010f, section 2.3.4.3), upon which CASAC based its advice. Changes made in the final Policy Assessment were primarily focused on improving and clarifying the approach for translating the epidemiological evidence i nto a basis for staff conclusions on the broadest range of alternative standard levels supported by the available scientific information and more clearly articulating the rationale for the staff’s conclusions (Wegman, 2011, pp. 1 to 2). Consistent with CAS AC’s advice to consider more information from epidemiological studies, as discussed in section III.E.4.b.1 above, the EPA analyzed additional population

- level data obtained from several study authors (Rajan et al., 2011). In transmitting the final Policy A ssessment to CASAC, the Agency notified CASAC that the final staff conclusions reflected consideration of CASAC’s 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, p.2). Thus, CASAC had an opportunity to

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- 322 comment on the final Policy Assessment, but chose not to provide any additional comments or advice after receiving it.
iii. Administrator’s Proposed Decisions on the Primary PM 2.5 Standard Levels In reachin g her conclusions regarding appropriate alternative standard levels to consider, the Administrator considered the epidemiological and other scientific evidence, estimates of risk reductions associated with just meeting alternative annual and/or 24

- hour
sta ndards, air quality analyses, related limitations and uncertainties, staff conclusions as presented in the Policy Assessment, and the advice of CASAC. As an initial matter, the Administrator agreed with the general approach discussed in the Policy Assessme nt as summarized in sections III.A.3 and III.E.4.a above, and supported by CASAC, of considering the protection afforded by the annual and 24

- hour standards taken together for mortality and morbidity effects associated with both long

- and short

- term exposu res to PM 2.5 ( 77 FR 38939 )

. Furthermore, based on the evidence and quantitative risk assessment, the Administrator provisionally concluded it is appropriate to set a “generally controlling” annual standard that will lower a wide range of ambient 24

- hour co ncentrations, with a 24

- hour standard focused on providing supplemental protection, particularly for areas with high peak

- to
- mean ratios possibly associated with strong local or seasonal sources, or PM 2.5 - related effects that may be associated with shorter

- than daily exposure periods. The Administrator provisionally concluded this approach would likely reduce aggregate risks associated with both long

- and short

- term exposures more consistently than a generally controlling 24

- hour standard and would be the

m ost effective and efficient way to reduce total PM 2

- 5 - related population risk. Id.

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- 323 In reaching decisions on alternative standard levels to propose, the Administrator judged that it was most appropriate to examine where the evidence of associations observed in the epidemiological studies was strongest and, conversely, where she had appreciably less confidence in the associations observed in the epidemiological studies. Based on the characterization and assessment of the epidemiological and other studies pres ented and assessed in the Integrated Science Assessment and the Policy Assessment, the Administrator recognized the substantial increase in the number and diversity of studies available in this review including extended analyses of the seminal studies of l ong - term PM 2.5 exposures (i.e., ACS and Harvard Six Cities studies) as well as important new long

- term exposure studies (as summarized in Figures 1 and 2). Collectively, the Administrator noted that these studies, along with evidence available in the last review, provid ed consistent and stronger evidence of an association with premature mortality, with the strongest evidence related to cardiovascular

related mortality, at lower ambient concentrations than previously observed. The Administrator also recognized the availab ility of stronger evidence of morbidity effects associated with long

term PM 2.5 exposures, including evidence of cardiovascular effects from the WHI study and respiratory effects, including decreased lung function growth, from the extended analyses for the Southern California Children’s Health Study. Furthermore, the Administrator recognized new U.S. multi

- city studies that greatly expanded and reinforced our understanding of mortality and morbidity effects associated with short

- term PM 2.5 exposures, provid ing stronger evidence of associations at ambient concentrations similar to those previously observed (as summarized in Figure 3). Id. at 38939

- 40.

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- 324 The newly available scientific evidence built upon the previous scientific data base to provide evidence of g enerally robust associations and to provide a basis for greater confidence in the reported associations than in the last review. The Administrator recognized that the weight of evidence, as evaluated in the Integrated Science Assessment, was strongest for health endpoints classified as having evidence of a causal relationship. These relationships included those between long

- and short

- term PM 2.5 exposures and mortality and cardiovascular effects. She recognized that the weight of evidence was also strong fo r health endpoints classified as having evidence of a likely causal relationship, which included those between long

- and short

term PM 2.5 exposures and respiratory effects. In addition, the Administrator made note of the much more limited evidence for heal th endpoints classified as having evidence suggestive of a causal relationship, including developmental, reproductive and carcinogenic effects. Id . at 38940. Based on information discussed and presented in the Integrated Science Assessment, the Administrat or recognized that health effects may occur over the full range of concentrations observed in the long

- and short

- term epidemiological studies and that no discernible threshold for any effects can be identified based on the currently available evidence ( U. S. EPA, 2009a, section 2.4.3). She also recognized, in taking note of CASAC advice and the distributional statistics analysis discussed in section III.E.4.b.i above and in the Policy Assessment, that there was significantly greater confidence in observed a ssociations over certain parts of the air quality distributions in the studies, and conversely, that there was

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- 325 significantly diminished confidence in ascribing effects to concentrations toward the lower part of the distributions. Consistent with the genera l approach summarized in section III.A.3 above, and supported by CASAC as discussed in section III.E.4.a above, the Administrator generally agreed that it was appropriate to consider a level for an annual standard that was somewhat below the long

- term mean PM 2.5 concentrations reported in long

- and short

- term exposure studies. In recognizing that the evidence of an association in any such study was strongest at and around the long

- term average where the data in the study are most concentrated, she understoo d that this approach did not provide a bright line for reaching decisions about appropriate standard levels. The Administrator noted that long

- term mean PM 2.5 concentrations were available for each study considered and, therefore, represented the most robu st data set to inform her decisions on appropriate annual standard levels. She also noted that the overall study mean
PM 2.5 concentrations were generally calculated based on monitored concentrations averaged across monitors in each study area with multiple monitors, referred to as a composite monitor concentration, in contrast to the highest concentration monitored in each study area, referred to as a maximum monitor concentration, which are used to determine whether an area meets a given standard. In consi dering such long

- term mean concentrations, the Administrator understood that it was appropriate to consider the weight of evidence for the health endpoints evaluated in such studies in giving weight to this information. Id

. Based on the information summari zed in Figure 4 above and presented in more detail in the Policy Assessment ( U.S. EPA, 2011a, chapter 2) for effects classified in the Integrated

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- 326 Science Assessment as having a causal or likely causal relationship with PM 2.5 exposures, the Administrator ob served an overall pattern of statistically significant associations reported in studies of long

- term PM 2.5 exposures with long

- term mean concentrations ranging from somewhat above the current standard level of 15 μg/m 3 down to the lowest mean concentration in such studies of 12.9 μg/m 3 (in Miller et al., 2007). 102 She observed a similar pattern of statistically significant associations in studies of short

- term PM 2.5 exposures with long

- term mean concentrations ranging from around 15 μg/m 3 down to 12.8 μg/m 3 ( in Burnett et al., 2004). With regard to effects classified as providing evidence suggestive of a causal relationship, the Administrator observed a small number of long

- term exposure studies related to developmental and reproductive effects that reported s tatistically significant associations with overall study mean PM 2.5 concentrations down to 11.9 μg/m 3 (in Bell et al., 2007). 103 Id. The Administrator also considered additional information from epidemiological studies, consistent with CASAC advice, to take into account the broader distribution of PM 2.5 concentrations and the degree of confidence in the observed associations over the broader air

102 The EPA notes that the Miller et al., (2007) study provides strong evidence of cardiovascular related effects associated with long

- term PM 2.5 exposures. At the time of the prop osal, the EPA recognized the limited nature of the air quality data considered in this study (77 FR 38918, fn. 62). The EPA has reviewed those limitations, in conjunction with consideration of public comments received on the proposal as discussed in sectio n III.E.4.c, in conjunction with reaching a final decision on the level of the annual standard. 103 With respect to suggestive evidence related to cancer, mutagenic, and genotoxic effects, the PM 2.5 concentrations reported in studies generally included ambi ent concentrations that are equal to or greater than ambient concentrations observed in studies that reported mortality and cardiovascular and respiratory effects (U.S. EPA, 2009a, section 7.5), such that in selecting alternative standard levels that provi de protection from mortality and cardiovascular and respiratory effects, it is reasonable to anticipate that protection will also be provided for carcinogenic effects.

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- 327 quality distribution. In considering this additional information, she understood that the Policy Assessment present ed information on the 25 th and 10 th percentiles of the distributions of PM 2.5 concentrations available from four multi

- city studies to provide a general frame of reference as to the part of the distribution in which the data become appreciably more sparse and, thus, where her confidence in the associations observed in epidemiological studies would become appreciably less. As summarized in Figure 4 above, the Administrator took note of additional population

level data that were available for four studies (K rewski et al., 2009; Miller et al., 2007; Bell et al., 2008; Zanobetti and Schwartz, 2009), each of which reported statistically significant associations with health endpoints classified as having evidence of a causal relationship. In considering the long

- term PM 2.5 concentrations associated with the 25 th percentile values of the population

- level data for these four studies, she observed that these values ranged from somewhat above to somewhat below 12 μg/m 3 . The Administrator recognized that three of these four studies represented some of the strongest evidence available within the overall body of scientific evidence and noted that three of these studies (Krewski et al., 2009; Bell et al., 2008; Zanobetti and Schwartz, 2009) were used as the basis for conce ntration

- response functions used in the quantitative risk assessment ( U.S. EPA, 2010a, section 3.3.3). In considering this information, the Administrator noted that CASAC advised that information about the long

- term PM 2.5 concentrations that were most influential in generating the health effect estimates in epidemiological studies can help to inform selection of an appropriate annual standard level. However, t he Administrator also recognized that additional

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- 328 population

- leve l data were available for only these four studies and, therefore, she believed that these studies comprised a more limited data set than one based on long

- term mean PM 2.5 concentrations for which data were available for all studies considered, as discussed above. The Administrator recognized, as summarized in section III.B.2 above, that important uncertainties remain in the evidence and information considered in this review of the primary fine particle standards. These uncertainties are generally related t o understanding the relative toxicity of the different components in the fine particle mixture, the role of PM 2.5 in the complex ambient mixture, exposure measurement errors inherent in epidemiological studies based on concentrations measured at fixed monitor sites, and the nature, magnitude, and confidence in estimated risks related to increasingly lower ambient PM 2 .5 concentrations. Furthermore, the Administrator noted that epidemiological studies have reported heterogeneity in responses both within and between cities and geographic regions across the U.S. She recognized that this heterogeneity may be attributed, in part, to differences in fine particle composition in different regions and cities. The Administrator also recognized that
t here are additional limitations associated with evidence for reproductive and developmental effects, identified as being suggestive of a causal relationship with long

- term PM 2.5 exposures, including: the limited number of studies evaluating such effects; uncertainties related to identifying the relevant exposure time periods of concern; and limited toxicological evidence providing litt le information on the mode of action(s) or biological plausibility for an association between long

- term PM 2.5 exposures and adverse birth outcomes. Id . at 38941.

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- 329 The Administrator was mindful that considering what standards were requisite to protect public health with an adequate margin of safety required public health policy judgments that neither overstated nor understated the strength and limitations of the evidence or the appr opriate inferences to be drawn from the evidence. In considering how to transl ate the available information into appropriate standard levels, the Administrator weighed the available scientific information and associated uncertainties and limitations. For the purpose of determining what standard levels were appropriate to propose, th e Administrator recognized, as did EPA staff in the Policy Assessment, that there was no single factor or criterion that comprised the sole “correct” approach to weighing the various types of available evidence and information, but rather there were variou s approaches that are appropriate to consider. The Administrator further recognized that different evaluations of the evidence and other information before the Administrator could reflect placing different weight on the relative strengths and limitations o f the scientific information, and different judgments could be made as to how such information should appropriately be used in making public health policy decisions on standard levels. This recognition led the Administrator to consider various approaches t o weighing the evidence so as to identify appropriate standard levels to propose. In so doing, the Administrator encouraged extensive public comment on alternative approaches to weighing the evidence and other information so as to inform her public health policy judgments before reaching final decisions on appropriate standard levels. In considering the available information, the Administrator noted the advice of CASAC that the currently available scientific information, including epidemiological and toxic ological

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- 330 evidence as well as risk and air quality information, provided support for considering an annual standard level within a range of 13 to 11 μg/m 3 and a 24

- hour standard level within a range of 35 to 30 μg/m 3 . In addition, the Administrator recogniz ed that the Policy Assessment concluded that the available evidence and risk

- based information support consideration of annual standard levels in the range of 13 to 11 μg/m 3 , and that the Policy Assessment also concluded that the evidence most strongly sup ported consideration of an annual standard level in the range of 12 to 11 μg/m 3 . In considering how the annual and 24

- hour standards work together to provide appropriate public health protection, the Administrator observed that CASAC did not
express suppor t for any specific levels or combinations of standards within these ranges . Nor did CASAC choose to comment on additional information and analyses presented in the final Policy Assessment prepared in response to CASAC’s recommendations on the second draft Policy Assessment (Wegman, 2011)

. In considering the extent to which the currently available evidence and information provided support for specific standard levels within the ranges identified by CASAC and the Policy Assessment as appropriate for consider ation, the Administrator initially considered standard levels within the range of 13 to 11 μg/m 3 for the annual standard. In so doing, the Administrator first considered the long

- term mean PM 2.5 concentrations reported in studies of effects classified as having evidence of a causal or likely causal relationship, as summarized in Figure 4 above and discussed more broadly above. She noted that a level at the upper end of this range would be below most but not all the overall study mean concentrations from th e multi

- city studies of long

- and short

- term exposures, whereas somewhat lower levels within

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- 331 this range would be below all such overall study mean concentrations. In considering the appropriate weight to place on this information, the Administrator again n oted that the evidence of an association in any such study was strongest at and around the long

- term average where the data in the study are most concentrated, and that long

- term mean PM 2.5 concentrations were available for each study considered and, there fore, represented the most robust data set to inform her decisions on appropriate annual standard levels. Further, she was mindful that this approach did not provide a bright line for reaching decisions about appropriate standard levels. Id. In considering the long

- term mean PM 2.5 concentrations reported in studies of effects classified as having evidence suggestive of a causal relationship, as summarized in Figure 4 for reproductive and developmental effects, the Administrator noted that a level at the upp er end of this range would be below the overall study mean concentration in one of the three studies, while levels in the mid

- to lower part of this range would be below the overall study mean concentrations in two or three of these studies. In considering the appropriate weight to place on this information, the Administrator noted the very limited nature of this evidence of such effects and the additional uncertainties in these epidemiological studies relative to the studies that provide evidence of causal or likely causal relationships. The Administrator also considered the distributional analyses of population

- level information that were available from four of the epidemiological studies that provide evidence of effects identified as having a causal relat ionship with long

- or short

- term PM 2.5 concentrations for annual standard levels within the same range of 13 to 11 μg/m 3 . In so doing,

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- 332 the Administrator first noted that a level in the mid

- part of this range generally corresponds with approximately the 25 t h percentile of the distributions of health events data available in three of these studies. The Administrator also noted that standard levels toward the upper part of this range would reflect placing substantially less weight on this information, whereas standard levels toward the lower part of this range would reflect placing substantially more weight on this information. In considering this information, the Administrator noted that there was no bright line that delineates the part of the distribution of PM 2.5 concentrations within which the data become appreciably more sparse and, thus, where her confidence in the associations observed in epidemiological studies became appreciably less. In considering mean PM 2.5 concentrations and distributional analyses from the various sets of epidemiological studies noted above, the Administrator was mindful, as noted above, that such studies typically report concentrations based on composite monitor distributions, in which concentrations may be averaged across multiple ambient monitors that may be present within each area included in a given study. Thus, a policy approach that used data based on composite monitors to identify potential alternative standard levels would inherently build in a margin of safety of some degr ee relative to an alternative standard level based on measurements at the monitor within an area that records the highest concentration, or the maximum monitor, since once a standard was set, concentrations at appropriate maximum monitors within an area we re generally used to determine whether an area meets a given standard.

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- 333 The Administrator also recognized that judgments about the appropriate weight to place on any of the factors discussed above should reflect consideration not only of the relative streng th of the evidence but also on the important uncertainties that remained in the evidence and information being considered in this review. The Administrator noted that the extent to which these uncertainties influenced judgments about appropriate annual sta ndard levels within the range of 13 to 11 μg/m 3 would likely be greater for standard levels in the lower part of this range which would necessarily be based on fewer available studies than would higher levels within this range. Based on the above considera tions, the Administrator concluded that it was appropriate to propose to set a level for the primary annual PM 2.5 standard within the range of 12 to 13 μg/m 3 . The Administrator provisionally concluded that a standard set within this range would reflect alt ernative approaches to appropriately placing the most weight on the strongest available evidence, while placing less weight on much more limited evidence and on more uncertain analyses of information available from a relatively small number of studies. Fur ther, she provisionally concluded that a standard level within this range would reflect alternative approaches to appropriately providing an adequate margin of safety for the populations at risk for the serious health effects classified as having evidence of a causal or likely causal relationship, depending in part on the emphasis placed on margin of safety considerations. The Administrator recognized that setting an annual standard level at the lower end of this range would reflect an approach that placed more emphasis on the entire body of the evidence, including the analysis of the distribution of air quality concentrations most influential in

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- 334 generating health effect estimates in the studies, and on margin of safety considerations, than would setting a l evel at the upper end of the range. Conversely, an approach that would support a level at the upper end of this range would generally support a view that the uncertainties remaining in the evidence are such that the evidence does not warrant setting a lower annual standard level. Id . at 38942

. At the time of the proposal, while the Administrator recognized that CASAC advised, and the Policy Assessment concluded, that the available scientific information provided support for considering a range that extended down to 11 μg/m 3 , she concluded that proposing such an extended range would reflect a public health policy approach that placed more weight on relatively limited evidence and more uncertain information and analyses than she considered appropriate at this time. Nonetheless, the Administrator solicited comment on a level down to 11 μg/m 3 as well as on appr oaches for translating scientific evidence and rationales that would support such a level. Such an approach might reflect a view that the uncertainties associated with the available scientific information warrant a highly precautionary public health policy response that would incorporate a large margin of safety. The Administrator recognized that potential air quality changes associated with meeting an annual standard set at a level within the range of 12 to 13 μg/m 3 will result in lowering risks associated with both long

- and short

- term PM 2.5 exposures. However, the Administrator recognized that such an annual standard intended to serve as the primary means for providing protection from effects associated with both long

- and short

- term PM 2.5 exposures would not by itself be expected to offer requisite protection with an adequate margin of safety against the

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- 335 effects of all short

- term PM 2.5 exposures. As a result, in conjunction with proposing an annual standard level in the range of 12 to 13 μg/m 3 , the Admini strator provisionally concluded that it was appropriate to continue to provide supplemental protection by means of a 24

- hour standard set at the appropriate level, particularly for areas with high peak

- to
- mean ratios possibly associated with strong local o r seasonal sources, or for PM 2.5 - related effects that may be associated with shorter

- than

- daily exposure periods. Based on the approach discussed in section III.A.3 above, at the time of the proposal the Administrator relied upon evidence from the short

- t erm exposure studies as the principal basis for selecting the level of the 24

- hour standard. In considering these studies as a basis for the level of a 24

- hour standard, and having selected a 98 th percentile form for the standard, the Administrator agreed with the focus in the Polic y Assessment of looking at the 98 th percentile values, as well as at the long

- term mean PM 2.5 concentrations in these studies. In considering the information provided by the short

- term exposure studies, the Administrator recogniz ed that to the extent these studies were conducted in areas that likely did not meet one or both of the current standards, such studies did not help inform the characterization of the potential public health improvements of alternative standards set at low er levels. By reducing the PM 2.5 concentrations in such areas to just meet the current standards, the Administrator anticipated that additional public health protection would occur. Therefore, the Administrator focused on studies that reported positive and statistically significant associations in areas that would likely have met both the current 24

- hour and annual standards. She also considered whether or not these studies were conducted in areas that

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- 336 would likely have met an annual standard level of 12 to 13 μg/m 3 to inform her decision regarding an appropriate 24

- hour standard level. As discussed in section III.E.4.a, consistent with the Policy Assessment, the Administrator concluded that multi

- city, short

- term exposure studies provided the strongest data set for informing her decisions on appropriate 24

- hour standard levels. The Administrator viewed the single

- city, short

- term exposure studies as a much more limited data set providing mixed results and, therefore, she had less confidence in using those st udies as a basis for setting the level of a 24

- hour standard. With regard to the limited number of single

- city studies that reported positive and statistically significant associations for a range of health endpoints related to short

- term PM 2.5 concentrati ons in areas that would likely have met the current suite of PM 2.5 standards, the Administrator recognized that many of those studies had significant limitations (e.g., limited statistical power, limited exposure data) or equivocal results (mixed results w ithin the same study area) that made them unsuitable to form the basis for setting the level of a 24

- hour standard. With regard to multi

- city studies that evaluated effects associated with short

- term PM 2.5 exposures, the Administrator observed an overall pattern of positive and statistically significant associations in studies with 98 th percentile values averaged across study areas in the range of 45.8 to 34.2 μg/m 3 (Burnett et al., 2004; Zanobetti and Schwartz, 2009; Bell et al., 2008; Dominici et al., 20 06a, Burnett and Goldberg, 2003; Franklin et al., 2008). The Administrator noted that, to the extent air quality distributions were reduced to reflect just meeting the
current 24

- hour standard, additional protection would be anticipated for the effects obs erved in the three multi

- city studies with 98 th percentile values greater than 35 μg/m 3 (Burnett et al.,

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- 337 2004; Burnett and Goldberg, 2003; Franklin et al., 2008). In the three additional studies with
98 th percentile values below 35 μg/m 3 , specifically 98 th percentile concentrations of 34.2, 34.3, and 34.8 μg/m 3 , the Administrator noted that these studies reported long

- term mean PM 2.5 concentrations of 12.9, 13.2, and 13.4 μg/m 3 , respectively (Bell et al., 2008; Zanobetti and Schwartz, 2009; Dominici et al., 2006a). In proposing to revise the level of the annual standard to within the range of 12 to 13 μg/m 3 , as discussed above, the Administrator recognized that additional protection would be provided for the short

- term effects observed in these multi

- city st udies in conjunction with an annual standard level of 12 μg/m 3 , and in two of these three studies in conjunction with an annual standard level of 13 μg/m 3 . She noted that the study

- wide mean concentrations were based on averaging across monitors within stu dy areas and that compliance with the standard would be based on concentrations measured at the monitor reporting the highest concentration within each area. The Administrator believed it would be reasonable to conclude that revision to the 24

- hour standar d would not be appropriate in conjunction with an annual standard within this range. Based on the above considerations related to the epidemiological evidence, the Administrator provisionally concluded that it was appropriate to retain the level of the 24

- hour standard at 35 μg/m 3 , in conjunction with a revised annual standard level in the proposed range of 12 to 13 μg/m 3

. In addition to considering the epidemiological evidence, the Administrator also took into account air quality information based on count y - level 24

- hour and annual design values to understand the public health implications of retaining the 24

- hour standard level at 35 μg/m 3 in

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- 338 conjunction with an annual standard level within the proposed range of 12 to 13 μg/m 3 . She considered whether these suites of standards would meet a public health policy goal which included setting the annual standard to be the “generally controlling” standard in conjunction with setting the 24

- hour standard to provide supplemental protection to the extent that additio nal protection is warranted. As discussed above, the Administrator provisionally concluded that this approach was the most effective and efficient way to reduce total population risk associated with both long

- and short

- term PM 2.5 exposures, resulting in m ore uniform protection across the U.S. than the alternative of setting the 24

- hour standard to be the controlling standard. In considering the air quality information, the Administrator first recognized that there was no annual standard within the propose d range of levels, when combined with a 24

- hour standard at the proposed level of 35 μg/m 3 , for which the annual standard would be the generally controlling standard in all areas of the country. She further observed that such a suite of PM 2.5 standards wit h an annual standard level of 12 μg/m 3 would result in the annual standard as the generally controlling standard in most regions across the country, except for certain areas in the Northwest, where the annual mean PM 2.5 concentrations have historically bee n low but where relatively high 24

- hour concentrations occur, often related to seasonal wood smoke emissions ( U.S. EPA, 2011a, pp. 2

- 89 to 2

- 91, Figure 2

- 10). Although not explicitly delineated on Figure 2

- 10 in the Policy Assessment, an annual standard of 13 μg/m 3 would be somewhat less likely to be the generally controlling standard in some regions of the U.S. outside the Northwest in conjunction with a 24

- hour standard level of 35 μg/m 3

.

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- 3 39 Taking the above considerations into account, the Administrator pro posed to revise the level of the primary annual PM 2.5 standard from 15.0 μg/m 3 to within the range of 12.0 to 13.0 μg/m 3 and to retain the 24

- hour standard level at 35 μg/m 3 . In the Administrator’s judgment, such a suite of primary PM 2.5 standards and the rationale supporting such levels could reasonably be judged to reflect alternative approaches to the appropriate consideration of the strength of the available evidence and other information and their associated uncertainties and the advice of CASAC. The A dministrator recognized that the final suite of standards selected from within the proposed range of annual standard levels, or the broader range of annual standard levels on which public comment was solicited, must be clearly responsive to the issues rais ed by the D.C. Circuit’s remand of the 2006 primary annual PM 2.5 standard. Furthermore, at the time of the proposal, she recognized that the final suite of standards will reflect her ultimate judgment in the final rulemaking as to the suite of primary PM 2. 5 standards that would be requisite to protect the public health with an adequate margin of safety from effects associated with fine particle exposures. The final judgment to be made by the Administrator will appropriately consider the requirement for a st andard that is neither more nor less stringent than necessary and will recognize that the CAA does not require that primary standards be set at a zero

- risk level, but rather at a level that reduces risk sufficiently so as to protect public health with an

a dequate margin of safety. At the time of the proposal, having reached her provisional judgment to propose revising the annual standard level from 15.0 to within a range of 12.0 to 13.0 μg/m 3 and to

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- 340 propose retaining the 24

- hour standard level at 35 μg/m 3 , the Administrator solicited public comment on this range of levels and on approaches to considering the available evidence and information that would support the choice of levels within this range. The Administrator also solicited public comment on alter native annual standard levels down to 11 μg/m 3 and on the combination of annual and 24

- hour standards that commenters may believe is appropriate, along with the approaches and rationales used to support such levels. In addition, given the importance the ev idence from epidemiologic studies played in considering the appropriate annual and 24

- hour levels, the Administrator solicited public comment on issues related to translating epidemiological evidence into standards, including approaches for addressing the uncertainties and limitations associated with this evidence.

c. Comments on Standard Levels This section addresses comments that relate to consideration of the appropriate levels of the primary annual and 24

- hour PM 2.5 standards , including c omments on the general approach used by the EPA to translate the available scientific information into standard levels and how specific PM 2.5 exposure studies should be considered as a basis for the standard level s. These comments on standard levels expand upon the more general comments that either support ed or oppose d any change to the current suite of primary PM 2.5 standards , which are addressed above in section III.D.2. 104 As explained there, one group of commenters generally opposed any change to the current primary PM 2 .5 standards and more specifically disagreed with the basis for the EPA’s proposal to revise the annual standard level. Another group of

104 Specific comments on the forms of the annual and 24

- hour standards are addressed in se ction III.E.3.a and III.E.3.b, respectively.

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- 341 commenters supported revising the current suite of primary PM 2.5 standards to provide increased public health protectio n. Some commenters in this second group argued that both the annual and 24

- hour standard levels should be lowered while other commenters in this group agreed with the EPA’s proposal to retain the level of the 24

- hour standard in conjunction with revising t he level of the annual standard. 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 was adequately protective and supported a level o f 11 μg/m 3
or below.
i. Annual Standard Level The group of commenters opposed to any change to the current suite of primary PM 2.5 standards generally raised questions regarding the underlying scientific evidence, including the causal determinations reached in the Integrated Science Assessment, and focused strongly on the uncertainties they saw in the scientific evidence as a basis f or 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 above in section III.D.2 as to why they believed i t was inappropriate for the EPA to make any revisions to the suite of primary PM 2.5 standards. That is, they asserted that the EPA’s causal determinations were not adequately supported by the underlying scientific information; the biological plausibility o f health effects observed in epidemiologic al studi es 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

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- 342 risk since the last review to justify tightening the current annual PM 2.5 standard; and “new” studies not included in the Integrated Science Assessment continue to increase uncertainty about possible health risks associated with exposure to PM 2.5 . With regard to the level of the annual standard, these commenters strongly disagreed with the Agency’s proposed decision to revise the level to within a range of 12 to 13 μg/m 3 and argued that the current standard level of 15 μg/m 3 should be retained

. For example, UAR G, 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, including : (1) 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; (2) the appropriate exposure period for effects observed in long

- t erm exposure mortality studies; and (3) the use of the EPA’s analysis of distribution s 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 : (4) evidence of respiratory morbidity effects in long

- te rm exposure studies and (5) more limited evidence of health effects which have been categorized in the Integrated Science Assessment as suggestive of a causal

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- 343 relationship (i.e., developmental and reproductive outcomes ). These comments are discussed in tur n below. (1) Some commenters in this group argued that one reason why they believe there is no basis for setting a standard level below 15 μg/m 3 is that the air quality metric from epidemiological studies that the EPA relied on in the proposal is not the s ame metric that will be compared to the level of the standard to determine compliance with the standard. That is, commenters noted that the long

- term mean PM 2.5 concentrations that the EPA considered, shown in Figure 4 above, are composite monitor mean con centrations (i.e., concentrations averaged across multiple monitors within areas with more than one monitor), whereas the
PM 2.5 concentrations that will be compared to the level of the standard are maximum monitor concentrations (i.e., the concentration me asured 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 PM 2.5 concentrations in selecting a standard level, and then comparing the maximum monitor mean PM 2.5 concentration in each area to the standard level when the standard is implemented, was characterized in the proposal as inherently having the potential to build in a margin of safety (UARG, 2012, Attachment 1, p. 4, citing 77 FR 38905). The 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

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- 344 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, A ttachment 1, p. 4). In support of this view, the commenter asserted that there is a significant difference between composite monitor mean PM 2.5 concentrations and maximum monitor mean PM 2.5 concentrations. The commenter asserted that the maximum monitor va lue will always be higher than the composite monitor value (except in areas that contain only a single monitor), such that when an area just attains the NAAQS, that area’s composite monitor long

- term mean
PM 2.5 concentration will be lower than the level of the standard (UARG, 2012, Attachment 1, p. 3). Second, the commenter asserted that a more “reasoned and consistent approach would be to decide on a mean composite monitor PM 2.5 level that should be achieved and then identify the maximum monitor level that would result in that composite value” (UARG, 2012, Attachment 1, p. 4). The commenter conducted an analysis of maximum monitor versus composite monitor annual mean PM 2.5 concentrations using monitoring data 105 from 2006 to 2008 and presented results average d across areas within two groups (i.e., those with design values 106 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 analys is as showing that the composite monitor long

- term mean PM 2.5 concentrations from the subset of the epidemiological studies shown in Figure 4 (of the proposal and above) that

105 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. 106 The design value is the air quality statis tic that is compared to the level of the NAAQS to determine the attainment status of a given area.

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- 345 the commenter considered to be an appropriate focus for this analysis would be achieved across the U.S. if the current annual NAAQS of 15 μg/m 3 is retained and attained

. The commenter considered the subset of epidemiological studies that included only long

- term exposures studies of effects for which the evidence is categorized as causal or likely causal, but did not consider short

- term exposure studies. On this basis, the commenter asserted that attaining the current annual PM 2.5 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

- ter m mean concentrations from such studies and, as a result, there is no reason to lower the level of the current annual NAAQS. In considering the first issue related to the EPA’s approach, the EPA notes that in proposing to revise both the form and level of the annual standard, the Administrator clearly took into account the distinction between the composite monitor long

- term mean PM 2.5 concentrations from the epidemiological studies, considered as a basis for selecting an annual standard level, and maximum m onitor long

- term mean PM 2.5 concentrations. In deciding to focus on the composite monitor long

- term mean concentrations in selecting the standard level, and on the maximum monitor concentrations in selecting the form of the standard (i.e., consistent with proposing to eliminate the option for spatial averaging across monitors within an area when implementing the standard 107 ), the Administrator reasonably considered the distinction between these metrics in a manner that was consistent with advice from CASAC (S amet et al., 2010d, pp. 2 to 3).

107 As discussed above in section III.E.3.a.

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- 346 As noted above in section III.A.3, 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 co mposite monitor concentrations. More specifically, many areas have only one monitor, in which case the composite and maximum monitor concentrations are identical. Based on the most recent data from the EPA’s AQS from 2009 to 2011 in the 331 CBSAs in which valid PM 2.5 data are available, as discussed in Frank (2012a, Table 5), there were 20 8 such areas (with design values ranging up to about 15 μg/m 3 ). Frank (2012a) also observed that other areas have multiple monitors with composite and
maximum monitor mean PM 2.5 concentrations that were the same or relatively close, with 5 7 areas in which the maximum monitor mean concentration was no more than 0.5 μg/m 3 higher than the composite monitor mean concentration and 56 areas in which the difference was between 0.6 and 2 μg/m 3 . Further, there were only a few other areas in which the maximum monitor mean concentration was appreciably higher than the composite monitor mean concentration, such as areas in which some monitors may be separately impacted by local

sources. There were only 10 such areas in the country in which the maximum monitor mean concentration was between 2 to 6 μg/m 3 higher than the composite monitor concentration (Frank, 2012a, Table 4). 108 Thus, the EPA does not agree that there is a significant differ ence between composite monitor mean PM 2.5 concentrations and maximum monitor mean PM 2.5 concentrations in the large majority of areas across the country.

108 The average difference between the maximum and composite design value among the 123 CBSAs with two or more monitors is 0.8 μg/m 3 and the median difference is 0.6 μg/m 3 . The 25 th and 75 th percentiles are 0.3 and 1.0 μg/m 3 , respectively (Frank, 2012a, p. 4)

.

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- 347 In proposing to revise the form of the annual PM 2.5 standard, as discussed above in section III.E.3.a, the EPA noted that when an annual PM 2.5 standard was first set in 1997, the form of the standard included the option for averaging across measurements at appropriate monitoring sites within an area, generally consistent with 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 constraint s 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 PM 2.5 concentrations in some areas, potentially resulting in disproportionate impacts on at

- risk populations of persons with lower SES levels as well as minorities . In light of these analyses, and consistent with the Administ rator’s decision to revise the form of the annual PM 2.5 standard by eliminating the option for spatial averaging, the EPA continues to conclude that a standard level based on consideration of long

- term mean concentrations from composite monitors, and appli ed 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 s afety, 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 comp osite monitor concentrations, as one that

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- 348 inherently had the potential to build in a margin of safety (77 FR 38905), and CASAC reiterated that view in supporting the EPA’s approach (Samet, 2010d, p. 3). Nonetheless, in light of the discussion above, the EP A 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 concentratio n 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 protect ion for those at

- risk populations that would otherwise be disproportionately impacted as it does for the broader populations in other areas, While the EPA recognizes that this approach can result in some additional 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, th e 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

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- 349 would be arbitrary, not based on evidence, or lack quantification. The EPA recognizes that setting a standard to protect public health, including the health of at

- risk populations, with an adequate margin of safety, depends upon selecting a standard level sufficiently below where the EPA has found the strongest evidence of health effects s o 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 appropriat e standard level 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 PM 2.5 level that should be achieved and then identify the maximum monitor level that would result in that composite value” (UARG, 2012, Attachment 1, p. 4). As discussed above, the EPA notes 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 PM 2.5 level to be no greater than the level that should be achieved to protect public health w ith 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

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- 350 essence averaged away with measuremen ts from monitors in other locations within large urban areas. Further, the commenter’s suggested approach would be based on annual average
PM 2.5 concentrations that have been measured over some past time period. Such an approach would reflect the air quali ty 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 area s across the country may be different. For these reasons, the EPA fundamentally rejects the commenter’s suggested approach because it would result in a standard that is inconsistent with EPA’s reasons for concluding that a standard of 15ug/m3 does 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 maxim um versus composite monitor annual mean PM 2.5 concentrations using monitoring data from 2006 to 2008 which they assert supports retaining the current standard level of 15 μg/m 3 , the EPA finds flaws with the numerical results and the scope of the 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 PM 2.5 concentrations, averaged over 3 years, for two groups of areas: (1) areas with design values that exceed the current annual standard level (i.e., greater than 15.0 μg/m 3 ) and (2) areas with design values that are just attaining the

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- 351 current annual stand ard (i.e., between 14.5 and 15.0 μg/m 3 ). 109 The commenter indicated that they used the full body of PM 2.5 monitoring data from the EPA’s AQS database (UARG, 2012, Attachment 1, p. 4), In attempting to reproduce the commenter’s results, the EPA repeated the

c alculations 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). 110 Based on this corrected analysis, the EPA finds that the composite monitor co ncentrations 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). 111 Notably , the difference between the maximum and composite monitor average concentrations for the second group of areas is substantially reduced in the corrected analysis, such that the difference (averaged

109 For the first group of areas (which included 33 areas), this analysis calculated an average across the areas of maximum monitor annual mean PM 2.5 concentrations, averaged over 3 years, of 17.2 μg/m 3 compared to an average of composite monitor concentra tions of 14.3 μg/m 3 . 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/m 3 compared to an average of composite monit or concentrations of 13.6 μg/m 3 (UARG, 2012, Attachment 1, Table 1). 110 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 EPA’s AQS database to compare m aximum versus composite monitor long

- term mean PM 2.5 concentrations across the study areas in six selected multi

- city epidemiological studies. 111 The EPA’s analysis was intended to repeat the commenter’s analysis, but using only valid air quality data (from 2006 to 2008). For the first group of areas (which included 21 areas with valid data), the EPA’s analysis calculated an average across the areas of maximum monitor annual mean concentrations, averaged of 3 years, of 16.8 μg/m 3 compared to an average of co mposite monitor concentrations of 14.8 μg/m 3 . 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 μ g/m 3 compared to an average of composite monitor concentrations of 14.2 μg/m 3 (Frank, 2012a, Table 3).

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- 352 across the 10 areas with valid data in the second group) is approximately 0.5 μg/m 3 , not 1.2 μg/m 3 as in the commenter’s analysis. In addition, the commenter’s analysis compared the average of the composite monitors to the average of the maximum monitors for each subset of areas. This comparison of averages acro ss 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 th at by limiting the scope to a small subset of areas with design values above or just below the current annual standard level of 15 μg/m 3 , the analysis ignores the large number of areas across the country with lower design values that are relevant to consid er in light of the epidemiological evidence of serious health effects at lower concentrations, well below the level of the current standard. In translating the analysis results into the basis for selecting an annual standard level, the commenter’s translat ion is premised on the view that the “natural focal point” for setting an annual PM 2.5 standard level should be somewhere within the range of the long

- term mean
PM 2.5 concentrations from the subset of epidemiological studies that included only long

- term

ex posure 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 proposal notice an d above). Such a view is not

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- 353 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, including protecting public health with an adequate margin of safety. As discussed below, the EPA does not agree with the commenter’s view as to the appropriate focal point for selecting the level of an annual PM 2.5 standard, or with the limited set of studies considered by the commenter as a basis for selecting the level of the annual PM 2.5 standard. Regarding an appropriate focal point for selecting the level of the annual standard, as discussed in the proposal and as advised by CASAC, the EPA has focused on PM 2.5 concentrations somewhat below the lowest long

- term mean concentrations from each of the key studies of both long

- and short

- term exposures of effects for which the evidence is causal or likely causal, as considered by the EPA (i.e., the first two sets of studies shown in Figure 4). 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 stud ie s would have a long

- term mean concentration below the selec ted level o f 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 PM 2.5 - related mortality and /or morbidity effects to continue. Selecting 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 lon g - term mean PM 2.5 concentrations in the key epidemiological studies

– even the lowest long

- term mean concentration from the set of key

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- 354 studies

-- is not appropriate. Concentrations at and around the long

- term mean concentration s represent the part of the a ir quality distribution where the data in any given study are most concentrated and, thus, where the confidence in the magnitude and significance of an
associati on in such study is strongest. However , the evidence of an association with adverse health effects in the studies is not limited to the PM 2.5 concentrations just at and around the long

- term mean, but rather extends more broadly to a lower part of the distribution, recognizing that no discernible population

- level threshold for any such effects can be identified based on the available evidence . This broader region of the distribution of PM 2.5 concentrations should be considered to the extent relevant information is available , recognizing that the d egree 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 PM 2.5 standard, the EPA finds that limiting consideration only to the long

- term
exposure studies, as this commenter suggests, would be tantamount to ignoring the shor t
- term
exposure studies , 112 which provide some of the strongest evidence from the entire body of

112 The commenter suggests that the EPA should not place significant reliance on the long

- term mean concentrations from short

- term exposure studies because “[T]he short

‐ term studies did not use the annual average of PM 2.5 to develop their associations; they used the daily 24
‐ hour averages of PM 2.5 . Thus, short

‐ term studies do not provide a natural indicator for the appropriate level of an annual standard....” (UARG, 2012, Attachment 1, p. 3). The EPA finds this argument unpersuasive. Quite simply, effects were observed in these studies with an air quality distribution that can meaningfully be characterized by these long

- term mean concentrations. Indeed, in rema nding the 2006 standard, the D.C. Circuit discussed at length the interrelationship of the long

- and short

- term standards and studies, and remanded the

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- 355 ep idemiological studies. Thus, s e lecting a n annual standard level using the limited set of studies suggested by the commenter would fail to provide a degree of p rotection 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 PM 2.5 concentrat ions in selecting the level of the annual PM 2.5 standard to be without merit. Further, the EPA finds no support in the commenter’s analysis for their suggested alternative approach. (2) With respect to the appropriate exposure period for mortality effects observed in long

- term exposure studies, some commenters in this group generally expressed views consistent with comments from UARG that argued that these studies “are most likely detecting health risk from earlier, higher PM 2.5 levels and misattributing th ose risks to more recent, lower
PM 2.5 levels” (UARG, 2012, Attachment 1, p 7). Further, this commenter asserted that “there is no knowledge or evidence indicating whether premature deaths are the result of PM 2.5 exposures in the most recent year; or due to physical damages incurred from PM 2.5 exposures much earlier in life (with the impact on lifespan only emerging later in life); or due to total accumulated PM 2.5 exposure over many years.” Id . Further, the commenter asserted that the long

- term exposure stu dies 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

2006 standard to the EPA, in part, for ignoring those relationships without adequate explanation. Americ an Farm Bureau Federation v. EPA. 559 F. 3d at 522

- 24.

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- 356 annual PM 2.5 standard are based on reductions in mortality related to long

- term exposures to
P M 2.5 . As an initial matter, the EPA has recognized t he challenge in distinguishing between
PM 2.5 - associated effects due to past and recent long

- term exposures , and in identif ying 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 k nowledge 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 a ssociations 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 Integrate d Science Assessment discussed studies available since the last review that have assessed the relat ionship between long

- term exposure to PM 2.5 and mortality to explore the issue of the latency period between exposure to PM 2.5 and death ( U.S. EPA, 2009 a , s ection 7.6.4 ). Notably, i n a recent analys i s 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 un constrained distributed lag models (i.e., same ye ar, one year prior, two years prior to death ). In comparing lags , the authors reported that the effects of

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- 357 changes in exposure to PM 2.5 on mortality we re strongest within a 2

- year period prior to death ( U.S. EPA, 2009a, p. 7

- 92, Figure 7

- 9 )

. Similarly, a large multi

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

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

- up period) and for the 3

- year period prior to death (Zanobetti et al., 2008). Further, i n a study of two locations that experienced an abrupt decline in PM 2.5 concentrations (i.e. , Utah Steel Strike, coal ban in Ireland), Röösl i 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 PM 10 24 months prior to death exhibited the strongest association, and the weakest association was reported for exposure in the time period of 1 month prior to death. Overall, the EPA notes that the available eviden ce for determining the exposure period that is causally related to the mortality effects of long

- term PM 2.5 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, PM 2.5 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 bas is for concluding that it is solely recent PM 2.5 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 PM 2.5 and mortality,

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- 358 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 ex posure study. This would include long

- term mean PM 2.5 concentrations from most of the key long

- term exposure studies of effects with causal or likely causal evidence shown in Figure 4 above, which reported long

- term mean PM 2.5 concentrations ranging from 1 3.6 μg/m 3 to 14.3 μg/m 3

. These studies include studies of mortality by Eftim et al. (2008), which separately analyzed the ACS and Harvard Six City sites, Zeger et al. (2008), and Lipfert et al. (2006), as well as studies of morbidity endpoints by Goss et a l. (2004), McConnell et al. (2003) and Gauderman et al. (2004), and Dockery et al. (1996) and Razienne et al. (1996). The EPA acknowledges that uncertainty in the relevant exposure period is most notable in two other long

- term exposure studies of mortality . The Miller et al. (2007) reported a long

- term mean PM 2.5 concentration for a 1

- year exposure period that post

- dated the follow

- up period in which health event data were collected by two years. Also, the Krewski et al. (2009) study reported a long

- term me an PM 2.5 concentration for an exposure period that included only the last two years of the 18

- year

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- 359 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 fro m these two studies for the purpose of translating the information from the long

- term mortality studies into a basis for selecting the level of the annual PM 2.5 standard. 113 In addition, the EPA acknowledges that exposure periods that extend at least a coupl e years prior to the follow

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

- related deaths in such studies. To explore how much higher the long

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

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

- term mean PM 2.5 concentrations (Schmidt, 2012 a ) particularly considering studies that only included 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 w ell 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 PM 2.5 concentration for each study. As discussed in Schmidt (2012 a ), in each case the long

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

- term mean PM 2.5 concentration averaged over the follow

- up period. The

113 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 PM 2.5 exp osures to inform causality determinations reached in the Integrated Science Assessment (U.S. EPA, 2009a, sections 7.2.11 and 7.6).

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- 360 EPA finds it reasonable to conclude that such a relatively small difference in long

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

- term exposure studies that used similarly recent follow

- up periods as well (e.g., Goss et al., 2004; Lipfert et al., 2006). Based on the above considerations, the EPA concludes that it is appropriate to consider the available air quality in formation 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 appro priate 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 broa der array of epidemiological studies that inform the EPA’s consideration of the level of the annual PM 2.5 standard. The EPA also notes that while the long

- term exposure studies are an important component of the epidemiological evidence that informs the Age ncy’s consideration of the level of the annual standard, they do not provide the only relevant information, nor are they the set of studies for which the relevant long

- term mean PM 2.5 concentrations are the lowest. As discussed in the proposal, the EPA als o considers the long

- term mean PM 2.5 concentrations from the short

- term mortality and morbidity studies as providing important information in considering the level of the annual standard. As discussed above, a large proportion of the aggregate risk associa ted 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

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- 361 concentrations observed in the studies. Thus, setting the level of the annual standard based on long

- ter m mean concentrations, as well as the distribution of concentrations below the mean, in the short

- term exposure studies is the most effective and efficient way to reduce total PM 2.5 - related risk from the broad array of mortality and morbidity effects assoc iated 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 uncert ainties discussed above related to the long

- term exposure studies. Recognizing that the long

- term mean PM 2.5 concentrations from several of the multi

- city short

- term exposure studies shown in Figure 4 are below the long

- term mean
PM 2.5 concentrations from the long

- term exposure studies (with the exception of Miller et al., 2007). 114 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

114 As noted above, the EPA is not placing weight on the reported long

- term mean concentrations from the Miller et al. (2007) s tudy for the purpose of translating the information from the long

- term mortality studies into a basis for selecting the level of the annual PM 2.5 standard.

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- 362 contributes the most to quantitative estimates of r isk to public health, but rather to the broad array of effects, including mortality and morbidity effects from long

- and short

- term exposures across the range of at

- risk populations impacted by PM 2.5 - related effects. (3) With regard to the EPA’s analysis of distribution s of underlying population

- level data (i.e., health event and study population data) and corresponding air quality data from each study area in certain key multi

- city epidemiological studies (Rajan et al., 2011), some commenters in this grou p raised a number of issues related to this analysis (API, 2012, Attachment 1 pp. 5 to 6; McClennan, 2012, p p.2 to 4 ) . 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. Based on such concerns, some commenters asserted that th e EPA should not consider this information as a basis for selecting a standard level. As an initial matter, as discussed in section III.E.4.b above, the EPA agrees with CASAC’s advice that it is appropriate to consider additional data beyond the mean PM 2.5 concentrations in key multi

- city studies to help inform selection of the level of the annual PM 2.5 standard. As both the EPA and CASAC recognize, in the absence of a discernible threshold, health effects may occur over the full range of concentrations obs erved 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 PM 2.5 concentrations reported in the studies and the degree of confidence becomes lower at lower concentrations within any given

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- 363 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 da ta, 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 PM 2.5 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. With regard to the number of multi

- city studies for which an analysis of the distributions of populat ion

- level data across the study areas and the corresponding annual mean PM 2.5 concentrations was done, the EPA noted at proposal that data for such an analysis were made available from study authors for four studies, including two long

- term exposure studie s and two short

- term exposure studies. 115 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 conside ring 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., 2009; Miller et al.,

115 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 anothe r long

- term exposure study (Miller et al., 2007).

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- 364 2007) and that it wou ld 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 PM 2.5 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 focusin g on these two short

- term exposure studies, the EPA first notes that these studies are key multi

- city studies that reported positive and statistically significant associations between mortality and cardiovascular

- related hospital admissions across a large number of areas throughout the U.S. (112 U.S. cities in Zanobetti and Schwartz, 2009; 202 U.S. counties in Bell et al., 2008) using relatively recent air quality and health event data (i.e., 1999 through 2005 in both studies). The EPA considers this to be a modest but important data set to use for this distributional analysis to help inform consideration of how much below the long

- term mean PM 2.5 concentrations in key multi

- city long

- and short

- term exposure studies the annual
PM 2.5 standard level should be set. While the EPA acknowledges that having such data available from more studies would have been useful, the Agency finds the information from this limited set of studies to be an important consideration in selecting an annual standard level, consistent with CASAC advice to consider such information. In considering t he results of this distributional analysis , as discussed more fully in the Response to Comments document, the EPA considers PM 2.5 concentrations between the 25 th
and 10 th percentiles of the di stribution of health events to be a reasonable range for providing a

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- 365 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

aroun d the long

- term mean concentration

. For the two short

- term exposure studies included in this analysis, the EPA notes that the PM 2.5 concentrations corresponding to the 25 th percentiles of the distributions of health events were 12.5 μg/m 3 and 11.5 μg/m 3 , respectively, for Zanobetti and Schwartz (2009) and for Bell et al. (2008) , with the 10 th percentiles being lower by approximately 2 μg/m 3 in each study (Rajan et al., 2011, Table 1)

. In considering this information, t he EPA recognizes, however, that there is no clear dividing line or single percentile within a given distribution (including both above and below the 25 th 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 below. 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 w as conducted to directly respond to advice from CASA C , as discussed in section III.E.4.b.1 above, in conjunction with their review of the Policy Assessment. The EPA notes that the same type of distributional analysis was presented in the second draft Polic y Assessment based on air quality data, as well as population

- weighted air quality data, rather than health event or study population data. In

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- 366 considering that distributional information, CASAC urged that the EPA redo the analysis using health event or stu dy population data, which is exactly what the EPA did and presented in the final Policy Assessment. The EPA provided CASAC with the final Policy Assessment and communicated how the final staff conclusions reflected consideration of its advice and that thos e 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 Policy Asses sment. The EPA considers this distributional analysis to be the product of the peer review conducted by CASAC of the Policy Assessment, and thus does not agree with commenters’ characterization that the analysis lacked appropriate peer review. The EPA’s fi nal analysis was based on the comments provided by CASAC, the pe e r 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. 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 he alth events observed in each city (e.g., deaths, hospitalizations) and the corresponding long

term mean PM 2.5 concentrations observed in the studies. While recognizing that this is a relatively modest data set, the EPA further concludes that such informati on can appropriately help to inform the selection of the level of an annual standard that will protect public health

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- 367 with an adequate margin of safety from these types of health effects which are causally related to long

- and short

- term exposures to PM 2.5 . (4) Some commenters in this group asserted there were limitations in the long

- term exposure studies of morbidity, including studies evaluating respiratory effects in children. For example, one commenter (UARG, 2012, p. 12, Attachment 1, pp. 14 to 16) asse rted 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 PM 2.5 exposures. This commenter asserted that many of these long

- term exposure studies evaluating respiratory effects were considered at the time the EPA reaffirmed the curren t annual standard level of 15 μg/m 3 in 2006, that the Administrator in the last review determined that the information they provided “was too limited to serve as the basis for setting a level of a national standard,” and that they should be given little we ight in setting the level of the annual standard in this review (UARG, 2012, Attachment 1, p. 14). More specifically, this commenter asserted that the McConnell et al. (2003) and Gauderman et al. (2004) stud ies reported mixed results for associations with PM 2.5 and stronger associations with NO 2 (API, 2012, Attachment 1, pp. 14 to 15). Similarly, this commenter argued that the Dockery et al. (1 996) and Raizenne et al. (1996) studies show ed stronger associations with acidity than with fine particles (measur ed as PM 2.1 ). Id. pp. 15 to 16. With regard to the cystic fibrosis study, this commenter noted that the association between pulmonary

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- 368 exacerbations and PM 2.5 in this study was no longer statistically significant when the model adjusted for each individual ’s baseline lung function. The commenters referred to the data on lung function as an “important explanatory variable,” and suggested that the EPA should rely on results from the model that included individual baseline lung function information. Id . p. 16. For the reasons discussed below and in more detail in the Response to Comments document,
t he 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 compl eted 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). The EPA concluded that “new” studies considered in the pro visional assessment completed in 2006 did not materially change any of the broad scientific conclusions regarding the health effects of PM exposure made in the Criteria Document (71 FR 61148 to 61149, October 17, 2006). All of these studies were considered in the Integrated Science Assessment that informs the current review ( U.S. EPA, 2009a). With regard to the Southern California Children’s Health Study, extended analyses considered in the Integrated Science Assessment provided evidence that clinically im portant

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- 369 deficits in lung function 116 associated with long

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

- 27; Gauderman et al., 2004). These effects remained positive in copollutant models. 117 Additional analyses of the Southern Cali fornia Children’s Health Study cohort reported an association between long

- term PM 2.5 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/m 3 ) that remained positive in co

- pollu tant models, with the PM 2.5 effect estimates increasing in magnitude in some models and decreasing in others, and a strong modifying effect of PM 2.5 on the association between lung function and asthma incidence ( U.S. EPA, 2009 a , 7

- 24; Islam et al., 2007). T he outcomes observed in the more recent reports from the Southern California Children’s Health Study, including evaluation of a broader range of endpoints and longer follow

- up periods, were larger in magnitude and more precise than reported in the initial version of the study . Supporting these results were new longitudinal cohort studies conducted by 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.

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

- 29 to 7

- 30). The primary NAAQS for sulfur dioxide (SO 2 ) also included this interpretation for FEV 1 (75 FR 35525, June 22, 2010). 117 Gauderman et al. (2004) clearly stated throughout their analysis that NO 2 was one component of a highly correlated mixture that contains PM 2.5 . 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 th e data than the corresponding single

- pollutant models.”

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- 370 The 24

- City study 118 by Dockery et al. (1996) (long

- term mean concentration of 14.5 μg/m 3 ) was considered in the current as well as two previous reviews ( U.S. EPA, 2009a; U.S. EPA, 2004; U.S. EPA, 1996). This study observed that PM, specifically “particle strong acidity” and sulfate particles (indicators of fine particles), were associated with reports of bronchitis in the previous year. Similarly, the magnitude of the associations between bronchitis and PM 10 and PM 2.1 were similar to those for acidi c aerosols and sulfate particles, though the confidence intervals for the PM 10 and PM 2.1 associations were slightly wider and the associ ations 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 PM 2.1 (r=0.82), make it difficult to di stinguish the agent of interest ” (Dockery et al., 1996, p. 505). Overall, Dockery et al. (1996) (and, similarly, Raizenne et al., 1996) observed similar associations between respiratory health effects and acid aerosols , sulfate, PM 10 and PM 2.1 concentrations. The commenters noted that the associations with particle acidity were
sensitive to the inclusion of the six Canadian sites. The EPA notes that none of these Canadian cities were in the “sulfate belt” where particle strong acidity was highest. Thus, the change in the effect estimate when the six Canadian cities were excluded from the a nalysis is likely due to the lower prevalence of bronchitis and the lower concentrations of acid aerosols in these cities,

118 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.

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- 371 and not due to some difference in susceptibility to bronchitis between the U.S. and Canadian populations that is not due to air pollu tion, 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 PM 2.5 exposures and exacerbations of respiratory symptoms resulting in hospital admissions or use of home intravenous antibioti cs ( U.S. EPA, 2009a, p. 7

- 25; long

- term mean concentration of 13.7 μg/m 3 ). The commenters noted that the association between pulmonary exacerbations and PM 2.5 in this study was no longer statistically significant when the model adjusted for each individual ’s baseline lung function. The commenters referred to the data on lung function as an “important explanatory variable,” and suggested that the EPA should rely on results from the model that included individual baseline lung function information. The EPA di sagrees 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 fun ction 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
i nverse relationships between FEV 1 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,

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- 372 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 disagree s 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 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 epidemiologic al 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 p attern of results across epidemiological studies and whether the effects observed were coherent across the scientific disciplines for drawing conclusions on the relationship between PM 2.5 and different health
outcomes. 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 PM 2.5 exposure (77 FR 38918). The strongest evidence for respiratory

- related effects available in this review

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- 373 was from epidemiological studies that evaluated decrements in lung function growth in chil dren 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 PM 2.5 exposures and respiratory effects ( U.S. EPA, 2009a, p. 2

- 12, pp. 7

- 42
to 7

- 43). CASAC con curred with this causality determination (Samet, 2009f, p.9). The commenter’s assertion that the EPA should adhere to its assessment of these studies as it did in the review completed in 2006 is significantly mistaken. Most obviously, the EPA’s final decis ion in the last review was held to be deficient by the D.C. Circuit in remanding the 2006 primary annual PM 2.5 standard. As discussed in section III.A.2 above, 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 PM 2.5 concentration approximately 15 μg/m 3 ) and the 24

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

- term mean co ncentrations approximately 14.5 μg/m 3 ) did not warrant a more stringent annual PM 2.5 standard when the long

- term mean PM 2.5 concentrations reported in those studies were at or lower than the level of the annual 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

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- 374 appears the EPA too hast ily 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

- ter m PM 2.5 exposures. This body of scientific evidence includes an extended and new analyses from the Southern California Children’s Health Study (Gauderman et al., 2004; Islam et al., 2007; Stanojevic et al., 2008) as well as additional studies that examined these health effects (Kim et al., 2004; Goss et al., 2004). Thus, even more so than in the last review, the evidence indicates a “significant public health risk” to children from long

- term PM 2.5 exposures at concentrations below the level of the current a nnual 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) With regard to the use of studies of health effects for which the EPA finds t he 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). 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

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- 375 would ignore the important distinctions in the nature of the evidence supporting these different causality det erminations in the Integrated Science Assessment. It would also ignore the CAA requirement that primary standards are to be set to provide protection with an adequate margin of safety, including providing protection for at

- risk populations. Thus, ignoring this information in making decisions on the appropriate standard level would not be appropriate. 119 Nonetheless, in considering studies of health effects for which the evidence is suggestive of a causal relationship, the EPA does believe that it is appropria te 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. A second group of commenters supported revising the suite of primary PM 2.5 standards to provide increased publi c 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

an alyses presented in the final Policy Assessment, which concluded that the evidence most strongly supported an annual standard level within a range of 11 to 12 μg/m 3 ( U.S. EPA, 2011a, p. 2

- 206). While some of these commenters felt that the level should be s et within the

119 As discussed in section II.A above, the requirement that primary standards provide an adequate margin of safety was intended to address uncertainties associated with inconclusive scientific and technical i nformation available at the time of standard setting. I 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 sug gestive of a causal relationship.

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- 376 proposed range (12 to 13 μg/m 3 ), most of these commenters advocated a level of 11 μg/m 3

. 120 For example, ALA et al., asserted: The EPA’s proposed PM 2.5 standards, while a step in the right direction are insufficient to protect public health, including the health of susceptible populations, with an adequate margin of safety as required by the Clean Air Act...we will discuss the enormous gap in public heal th protection afforded by an annual standard of 13 μg/m 3 , at the upper end of the proposed range, compared to the more protective 11 μg/m 3 , as advocated by our organizations (ALA et al., 2012, p. 6). In general, these commenters expressed the view that gi ven the strength of the available scientific evidence, the serious nature of the health effects associated with PM 2.5 exposures, the large size of the at

- risk populations, the risks associated with long

- and short

term PM 2.5 exposures, and the important un certainties 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) cons ideration 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 PM 2.5 - related public heal th impacts, especially potential impacts on at

- risk populations, including

120 As discussed in section III.E.4.c.ii, many of these commenters also supported lowering the level of the primary 24

- hour PM 2.5 standard.

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- 377 children, in reaching judgments on setting standards that provide protection with an adequate margin of safety. These comments are discussed in turn below. (1) Some of these comment ers 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 Policy Assessment (ALA et al., pp. 26 to 27). Specifically, these commenters argued: There is no basis in the Clean Air Act for such a determination. The Clean Air Act requires only that the NAAQS achieve public health protection with an adequate margin of safety. It is well

- documented that both long

- and short

- term exposures to PM 2.5 have serious and sometimes irreversible health impacts. There is no h ealth protection reason to argue tha t 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 Amer icans because it would result in uneven protection from air pollution in different localities and regions of the country (ALA et al., 2012, p. 26). 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 PM 2.5 exposures. It does so by lowering the overall air quality distributi ons across an area, recognizing that changes in PM 2.5 air quality designed to meet an annual standard would likely result not only in lower annual mean PM 2.5 concentrations but also in fewer and lower peak 24

- hour PM 2.5 concentrations. As discussed in sect ion III.A.3 in the proposal and above, the EPA recognizes that there are various ways to combine the two primary PM 2.5 standards to

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- 378 achieve an appropriate degree of public health protection. Furthermore, the extent to which these two standards are interrel ated 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 a n approach of setting a generally controlling annual standard, the EPA’s
intent is in fact to avoid the potential “regional inequities” that are of concern to the commenters. The EPA judges tha t 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 Policy Assessment as discu ssed in section III.A.3 above. More specifically, the Policy Assessment recognized that the short

- term exposure studies primarily evaluated daily variations in health effects with monitor(s) that measured the variation in daily PM 2.5 concentrations over th e 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 quan titative risk assessments conducted for this and previous reviews demonstrated the same point, that is, much, if not most , of the aggregate risk associated with short

- term PM 2.5 exposures results from the large number of days during which the 24

- hour avera ge 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,

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- 379 there was no evidence suggesting that risks associated with long

- term exposures were likel y to be disproportionately driven by peak 24

- hour concentrations. 121 For these reasons, the Policy Assessment concluded that strategies that focused primarily on reducing peak days were less likely to achieve reductions in the PM 2.5 concentrations that were most strongly associated with the observed health effects. Furthermore, the Policy Assessment concluded that a n approach that focused on reducing peak exposures would most likely result in more uneven public health protection acro ss 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 a result, the EPA believes a n approach that focuses on a generally controlling annual standard would likely reduce aggregate risks associated with both long

- and short

- term exposures more consistently than a generally cont rolling 24

- hour standard and, therefore, would be the most effective and efficient way to reduce total PM 2

- 5 - related population risk. The CASAC agreed with this approach and considered it was “appropriate to return to the strategy used in 1997 that conside rs 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). For the reasons discussed above, the EPA disagrees with the comments that this approach will result in the concerns

121 In confirmation, a number of studies have presented analyses excluding higher PM c oncentration 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).

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- 380 raised by the commenters; rather the EPA concludes that this approach will help to address these concerns. (2) Many of these commenters asserted that the currently available sci entific 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/m 3 ” (AHA et al., 2012, pp. 10 to 12). The EPA reco gnizes 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 overs tate 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 i n

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- 381 section III.E.4.d below, in weighing the available evidence and technical analyses, as well as the associated uncertainties and limitations in that information, the EPA disagrees with the commenters’ views regarding the extent to which the available scie ntific information provides support for considering an annual standard level below the proposed range (i.e., below 12 to 13 μg/m 3 ). In particular, the EPA disagrees with the degree to which these commenters place more weight on the relatively more uncertai n 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 Integra ted Science Assessment 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) With regard to us ing the air quality i nformation 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. Th ese 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 d istributional statistical analysis of population

- level dat a 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 t o characterizing the
PM 2.5 air quality at which associations have been observed, some of these commenters

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- 382 highlighted CASAC’s recommendation that “[f]urther consideration should be given to using the
10 th percentile as a level for assessing various scenari os 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 f or children’s health studies to better inform standards that would protect both children and adults from adverse health outcomes (CHPAC, 2012, p. 3) The EPA agrees with these commenters’ views that it is appropriate to take into account different statistic al 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 Policy Assessment, the EP A staff explored various approaches for us ing information from epidemiological studies in setting the standards. The general approach used in the final Policy Assessment, discussed in sections III.A.3 and III.E.4.a above, reflects consideration of CASAC ad vice (Samet, 2010c, d) and public comments on multiple drafts of the Policy Assessment

. With regard to using the distributional statistical analysis to characterize the confidence in the associations , the EPA emphasizes that there is no clear dividing line provided by the scientific evidence, and that choosing how far below the long

- term mean concentrations from the epidemiological studies is appropriate to identify a standard level that will provide protection for the public health with an adequate margin of safety is largely a public health policy judgment. The EPA considers the region from approximately the 25 th to 10 th percentiles to be a reasonable range for providing a general frame of reference as to the part of the

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- 383 distribution over which our confide nce in the magnitude and significance of the associations observed in epidemiological studies is appreciably lower. Based on these considerations, t he
EPA concludes that it is not appropriate to place as much confidence in the magnitude and significance of the assoc i ation s 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 thi s 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 discus sed below in section III.E.4.d. 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 provid ed evidence on the influence of different particle mixtures on health effects associated with long

- and short

- term PM 2.5 exposures. In addition, these multi

- city studies considered relatively more recent health events and air quality conditions (1999 to 20 05). As discussed in section III.E.4.b.i above, the EPA received and analyzed population

- level data for

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- 384 four of the six studies (Rajan et al., 2011). T hree of these four studies (Krewski et al., 2009; Bell et al., 2008; Zanobetti and Schwartz, 2009) served as the basis for the concentration

- response 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) Many commenters in this group highlighted PM 2.5 - related impacts on at

- risk populations, including potential impacts on children, older adults, persons with pre

- existing heart and lung disease, and low

- income populations, to support their views that the annual standard should be revised to a level of 11 μg/m 3 or lower (CHPAC, 2012; AHA et al., 2012; AL A, 2012, pp. 29 to 38; Rom et al., 2012; Air Alliance Houston, et al, 2012). 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 stu dies. ... 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 o f 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/m 3 , other than the

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- 385 vague a ssertion that uncertainties increase at lower concentrations. Further, the final proposal completely failed to address the Policy Assessment recommendations that if 13 μg/m 3 was proposed, the 24

- hour standard should be strengthened as well” (ALA et al., p. 7). The EPA has carefully evaluated and considered evidence of effects in at

- risk populations. With regard to effects classified as having evidence of a causal or likely causal relationship with long

- or short

- term PM 2.5 exposures (i.e., premature mortali ty, cardiovascular effects, and respiratory effects), the Agency takes note that it considered the full range of studies evaluating these effects, including studies of at

- risk populations, to inform its review of the primary PM 2.5 standards. Specific multi

- city studies summarized in Figures 1, 2, and 3 above 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 exp lored 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 sett ing the standard, the EPA has focused on considering PM 2.5 concentrations somewhat below the lowest long

- term mean concentrations from each of the key studies of both long

- and short

- term exposures of effects for which the evidence supports a causal or lik ely causal relationship (i.e., the first two sets of studies shown in Figure 4). Absent some reason to ignore or discount these studies, which the commenter does not provide (and of which the EPA is unaware) , the EPA considers the available evidence of eff ects in children as well as other at

- risk populations.

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- 386 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 co mments from the first group of commenters, the Agency agrees that it is important to place some weight on this body of evidence in setting standards that provide protection for at

- risk populations, as required by the CAA. 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 would ignore the difference in the breadth and strength of the evidence suppor ting the different causality determinations reached in the Integrated Science Assessment. With regard to weighing the uncertainties and limitations remaining in the evidence and technical analyses, as discussed in section II.A above, the EPA recognizes th at 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 de gree of the uncertainties that remain. As discussed in section III.E.4.d below, the Agency agrees with these commenters that, in weighing the available evidence and technical analyses including the uncertainties and limitations in this scientific informati on, there is no justification for setting a primary PM 2.5 annual standard level as high as 13 μg/m 3

. Finally, some commenters in both groups also identified “new” studies that were not included in the Integrated Science Assessment as providing further support for their views on the level of the annual standard. As discussed in section II.B.3 above, the EPA completed a

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- 387 provisional review and assessment of “new” studies published since the close of the Integrated Science Assessment, including “new” studie s submitted by commenters (U.S. EPA, 2012a). The provisional assessment found that the “new” studies expand the scientific information considered in the Integrated Science Assessment and provide important insights on the relationship between PM 2.5 exposure and health effects of PM (U.S. EPA, 2012b) . However, the EPA notes that the provisional assessment found that the “new” science did not materially change the conclusions reached in the Integrated Science Assessment. The EPA notes that, as in past NAAQS re views, the Agency is basing the final decisions in this review on the studies and related information included in the Integrated Science Assessment that have undergone CASAC and public review, and will consider newly published studies for purposes of decis ion making in the next PM NAAQS review.
ii. 24

- Hour Standard Level 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 represe nting industry associations , businesses , and many States agreed with the Agency’s proposed decision to retain the level of the 24

- hour PM 2.5 standard. The other group of 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

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- 388 25 μg/m 3 . Comments from these groups on the level of the 24

- hour PM 2.5 standard are

a ddressed below and in the Response to Comments Document

. As noted above, o f the public commenters who addressed the level of the 24

- hour PM 2.5 stan dard, all industry commenters and most State and l ocal commenters supported the proposed decision to retain the current level of 35 g/m 3 . In many cases, these groups agreed with the rationale supporting the Administrator’s proposed decision to retain the current 24

- hour PM 2.5 standard, including her emphasis on the annual standard as the generally controlling standard with the 24

- hour standard providing supplementary protection, and her conclusion that multi

- city, short

- term exposure studies provide the st rongest 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 leve l of the 24

- hour standard. While these commenters agreed with the EPA’s proposed decision to retain the current
24

- hour PM 2.5 standard, some did not agree with the EPA’s approach to considering the evidence from short

- term multi

- city studies. For example, a commenter representing UARG pointed out that the 98 th percentile concentrations reported in the proposal for multi

- city studies reflect the averages of 98 th percentile concentrations across the cities included in those studies (UARG, 2012; Attachment 1; p. 25). This commenter contended that such averaged 98 th percentile PM 2.5 concentrations do not provide information that can appropriately inform a

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- 389 decision on the adequacy of the public health protection provided by the current or alternative
24

- hour sta ndards. While the EPA agrees that there is uncertainty in linking effects reported in multi

- city studies to specific air quality concentrations (U.S. EPA, 2011, section 2.3.4.1), the EPA disagrees with this commenter’s view that such uncertainty preclude s the use of averaged 98 th percentile
PM 2.5 concentrations to inform a decision on the appropriateness of the protection provided by the 24

- hour PM 2.5 standard. In particular, the EPA notes that averaged 98 th percentile concentrations do provide informatio n on the extent to which study cities contributing to reported associations would likely have met or violated the current 24

- hour PM 2.5 standard during the study period. As evidence of this, the EPA notes the three multi

- city studies specifically highlight ed by this commenter as having averaged 98 th percentile 24

- hour PM 2.5 concentrations below 35 g/m 3 (Dominici et al., 2006; Bell et al., 2008; Zanobetti and Schwartz, 2009). Based on the 98 th percentiles of 24

- hour PM 2.5 concentrations in the individual ci ties evaluated in these studies, the EPA notes that the majority of these study cities would likely have met the current standard during the study periods (Hassett

- Sipple et al., 2010). Therefore, regardless of whether the averaged 98 th percentile concentr ations or the 98 th percentile concentrations in each city are considered, these studies provide evidence for associations between short

- term PM 2.5 and mortality or morbidity across a large number of U.S. cities, the majority of which would likely have met the current 24

- hour PM 2.5 standard during study periods. In their review of the PM Policy Assessment, CASAC endorsed the conclusions drawn from analyses of averaged 98 th percentile 24

- hour PM 2.5 concentrations, and the EPA continues

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- 390 to conclude that this t ype of information can appropriately inform the Administrator’s decision on the current 24

- hour PM 2.5 standard. 122
A nother 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 PM 2.5 standard at either 25 or 30 g/m 3 . In support of their position, the ALA et. al. , AHA et al., five state Attorneys General, and a number of additional groups pointed to 98 th percentile PM 2.5 concentrations in locations of multi

- c ity and single

- city epidemiological studies. For example, the ALA and others pointed to multi

- city studies by Dominici et al. (2006), Zanobetti and Schwartz (2009), Burnett et al. (2000), and Bell et al. (2008) as providing evidence for associations with m ortality and morbidity in study locations with averaged (i.e., averaged across cities) 98 th percentile 24

- hour PM 2.5 concentrations below 35 g/m 3 . These commenters also pointed to several single

- city and panel studies reporting associations between short

- term
PM 2.5 and mortality or morbidity in locations with relatively low 24

- hour PM 2.5 concentrations.
Because some of these multi

- and single

- city studies have reported associations with health effects in locations with 98 th percentile PM 2.5 concentrations below 35 g/m 3 , commenters maintained that the current 24

- hour PM 2.5 standard (i.e., with its level of 35 g/m 3 ) does not provide an appropriate degree of protection in all areas.

122 This is not to say that the EPA’s decision on w hether to revise the 24

- hour PM 2.5 standard should be based on or only be informed by considerations of whether studies reported associations with mortality or morbidity in areas with averaged 98 th percentile PM 2.5 concentrations less than 35 mg/m 3 . As dis cussed below, in reaching a decision in this final notice on the most appropriate approach to strengthen the suite of PM 2.5 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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- 391 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 PM 2.5 concentrations. They noted that some locations, including parts of the northwestern U.S., e xperience relatively low annual PM 2.5 concentrations but can experience relatively high 24

- hour concentrations at certain times of the year. In order to provide protection against effects associated with short

- term PM 2.5 exposures, especially in locations with high ratios of 24

- hour to annual PM 2.5 concentrations, these commenters advocated setting a lower level for the 24

- hour standard. The EPA agrees with these commenters that it is appropriate to maintain a 24

- hour
PM 2.5 standard in order to supplement the protection provided by the revised annual standard, particularly in locations with relatively high ratios of 24

- hour to annual PM 2.5 concentrations. However, in highlighting 98 th percentile PM 2.5 concentrations in study locations without also consideri ng the impact of a revised annual standard on short

- term concentrations, these commenters ignore the fact that many areas would be expected to experience decreasing short

- and long

- term PM 2.5 concentrations in response to a revised annual standard.
In con sidering the specific multi

- city studies highlighted by public commenters who advocated a more stringen t 24

- hour standard, the EPA notes that such studies have reported consistently positive and statistically significant associations with short

- term PM 2.5 exposures in locations with averaged 98 th percentile PM 2.5 concentrations ranging from 45.8 to 34.2 μg/m 3 and long

- term mean PM 2.5 concentrations rang ing from 13.4 to 12.9 (Burnett and Goldberg, 2003; Burnett et al., 2004; Dominici et al., 2006 a ; Bell et al., 2008; Franklin et al., 2008;

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- 392 Zanobetti and Schwartz, 2009). 123 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/m 3 and/or the revised annual standard with its level of 12 g/m 3 , additional protection would be anticipated against the effects reported in these short

- term , multi

- city studies. Put another way, to attain an annual standard with a level below the long

- term means in the locations of these short

- term studies (as E PA is adopting here), the overall air quality distributions in the majority of study cities will necessarily be reduced, resulting in lower daily PM 2.5 ambient concentrations. We therefore expect that the revised annual standard will result in 98 th percentile PM 2.5 concentrations in these cities that are lower than those measured in the studies, and that the overall distributions of PM 2.5 concentrations will be lower than those reported to be associated with health effects. Thus, even for effects re ported in multi

- city studies with averaged 98 th percentile concentrations below 35 μ g/m 3 , additional protection from the risks associated with short

- term exposures is anticipated from the revised annual standard, without revising the 24

- hour standard, beca use long

- term average PM 2.5 concentrations in multi

- city study locations

123 Commenters also highlighted associations with short

- term PM 2.5 concentrations reported in sub

- analyses restricted to days with 24

- 3 (Dominici, 2006b). These sub

- analyses were not included in the original publication by Dominici et al. (2006a). Authors provided results of sub

- analyses for the Administrator’s consideration in a letter to the docket following publication of the proposed rule in January 2006 (personal communication with Dr. Francesca Dominici, 2006b). As noted in section III.A.3, 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 concen trations. Because the sub

- analyses did not present long

- term average PM 2.5 concentrations, it is not clear whether they reflected PM 2.5 air quality that would have been allowed by the revised annual PM 2.5 standard being established in this notice.

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- 393 were above the level of the revised annual standard (i.e., 12 μ g/m 3 ). 124 As discussed above, reducing the annual standard is the most efficient way to reduce the risks from short

- term

e xposures 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. In considering the single

- city studies hig hlighted by public commenters who advocated a more stringen t 24

- hour standard, the EPA first notes that, overall, these single

- city studies reported mixed results. Specifically, some studies reported positive and statistically significant associations with PM 2.5 , some studies reported positive but non

- significant associations, and several studies reported negative associations or a mix of positive and negative associations with PM 2.5 . In light of these inconsistent results, the proposal noted that the overa ll body of evidence from single

- city studies is mixed, particularly in locations with 98 th percentile s of 24

- hour concentrations below 35 μg/m 3 . Therefore, a lthough some single

- city studies report ed effects at appreciably lower PM 2.5 concentrations than short

- term multi

- city studies, the uncertainties and limitations associated with the single

- city studies were noted to be greater . In light of these greater uncertainties and limitations, the Administrator concluded in the proposal that she had less confid ence in using these studies as a basis for setting the level of the standard (77 FR 38943).

124 It is also the case that additional protection is anticipated in locations with 98 th percentile 24

- hour PM 2.5 concentrations above 35 μg/m 3 , even if long

- term concentrations are below 12 μg/m 3 . As noted in the proposal and in the Policy Assessment (U.S. EPA, 2011, Figure 2

- 10), 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.

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- 394 Given the considerations and conclusions noted above, in the proposal the Administrator concluded that the short

- term multi

- city studies provide the strongest evid ence to inform decisions on the level of the 24

- hour stan dard. F urther , she viewed single

- city, short

term exposure studies as a much more limited data set providing mixed results, and she had less confidence in using these studies as a basis for setting t he level of a 24

- hour standard (77 FR 38942)

. . In highlighting specific single

- city studies, public health, environmental, and State and local commenters appear to have selectively focused on studies reporting associations with
PM 2.5 and to have overlooked studies that reported more equivocal results (e.g., Ostro et al., 2003; Rabinovitch et al., 2004; Slaughter et al., 2005; Villeneuve et al., 2006) (U.S. EPA, 2011, Figure 2

- 9). As such, these commenters have not presented new information that causes the
E PA to reconsider its decision to emphasize multi

- city studies over single

- city studies when identifying the appropriate level of the 24

- hour PM 2.5 standard. In further considering the single

- city studies highlighted by public commenters, the EPA notes that some commenters advocating for a lower level for the 24

- hour PM 2.5 standard also discussed short

- term studies that have been published since the close of the Integrated Science Assessment. These recent studies were conducted in single cities or in small p anels of volunteers. As in prior NAAQS reviews and as discussed above in more detail (section II.B.3) , the EPA is basing its decisions in this review on studies and related information assessed in the Integrated Science Assessment. The studies assessed in the Integrated Science Assessment, 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 Integrated

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- 395 Science Assessment, and the con clusions based on those studies, the most reliable source of scientific information on which to base decisions on the NAAQS. However, as discussed above (section II.B.3) , the EPA recognizes that ‘‘new studies” may sometimes be of such significance that it is appropriate to delay a decision on revision of a NAAQS and to supplement the pertinent air quality criteria so the studies can be taken into account. In the present case, the EPA’s provisional consideration of ‘‘new studies” concludes that, taken in context, the “new” information and findings do not materially change any of the broad scientific conclusions made in the air quality criteria regarding the health effects of PM 2.5 ( U.S. EPA , 2012a). 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 completing this review . Accordingly, the EPA is basing its final decisio ns in this review on the studies and related information included in the PM Integrated Science Assessment (i.e., the air quality criteria) that has undergone CASAC and public review. The EPA will consider the “new studies” in the next periodic review of th e PM NAAQS, which will provide an opportunity to fully assess these studies through a more rigorous review process involving the EPA, CASAC, and the public.

Some p ublic health, medical , and env ironmental commenters also criticized the EPA’s interpretation of PM 2.5 risk results. These commenters presented risk estimates for combinations of annual and 24

- hour standards using more recent air quality data than that used in the EPA’s Risk Assessment (U.S. EPA, 2010a). Based on these additional risk analyses, th e ALA and other commenters contended that public health benefits could continue to

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- 396 increase as annual and 24

- hour standard levels decrease below 13 g/m 3 and 35 g/m 3 , respectively

. The EPA agrees with commenters that important public health benefits are expected as a result of revising the level of the annual standard to 12 g/m 3 , as is done in this notice, rather than 13 g/m 3 . The Agency also acknowledges that estimated PM 2.5 - assoc iated health risks continue to decrease with annual standard levels below 12 g/m 3 and/or with 24

- hour standard levels below 35 g/m 3 . However, the EPA disagrees with the commenters’ views regarding the extent to which risk estimates support setting standa rd levels below 12 μg/m 3 (annual standard) and 35 g/m 3 (24

- hour standard). 125 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 PM 2.5 standards that would provide “requisite” protection , the Administrator carefully considered the available scientific evidence and risk information , making public health policy judgments that , in her view, neither overstate d nor understate d the streng ths and limitations of that evidence and information. In contrast, a s discussed more fully above , public health, medical, and environmental commenters who recommended levels below 35 g/m 3 for the 24

- hour PM 2.5 standard have not provided new

125 This section focus es on the 24

- hour standard. Section III.E.4.c.i above also discusses these commenters’ recommendations within the context of the annual PM 2.5 standard.

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- 397 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 98 th percentile 24

- hour PM 2.5 concentrations below 3 5 g/m 3 and long

- term average concentrations below 12 g/m 3

. d. Administrator’s Final Conclusions on the Primary PM 2.5 Standard Levels In reaching her conclusions regarding appropriate standard levels, the Administrator has considered the epidemiological and other scientific evidence, estimates of risk reductions associated with just meeting alternative annual and/or 24

- hour standards, air quality analyses, related limitations and uncertainties, the advice of CASAC, and extensive public comments on the propos al. After careful consideration of all of these, the Administrator has decided to revise the level of the primary annual PM 2.5 standard from 15.0 μg/m 3 to 12.0 μg/m 3 and to retain the level of the primary 24

- hour standard at 35 μg/m 3

. As an initial matter, the Administrator agrees with the approach supported by CASAC and discussed in the Policy Assessment as summarized in sections III.A.3 and III.E.4.a above, of considering the annual and 24

- hour standards together in determining the protection afforded
aga inst mortality and morbidity effects associated with both long

- and short

- term exposures to
PM 2.5 . This approach is consistent with the approach taken in the review completed in 1997, in contrast to the approach used in the review completed in 2006 where e ach standard was considered independently of the other (i.e., only data from long

- term exposure studies were

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- 398 used to inform the level of the annual standard and only data from short

- term exposure studies were used to inform the level of the 24

- hour standar d). 126 Based on the evidence and quantitative risk assessment, the Administrator concludes that it is appropriate to set an annual standard that is generally controlling, which will lower the broad distribution of 24

- hour average concentrations in an area a s well as the annual average concentration, so as to provide protection from both long

- and short

- term PM 2.5 exposures. In conjunction with this, it is appropriate to set a 24

- hour standard focused on providing supplemental protection, particularly for are as with high peak

- to
- mean ratios of 24

- hour concentrations, possibly associated with strong local or seasonal sources, and for PM 2.5 - related effects that may be associated with shorter

- than daily exposure periods. The Administrator concludes this approach will reduce aggregate risks associated with both long

- and short

- term exposures more consistently than a generally controlling 24

- hour standard and is the most effective and efficient way to reduce total PM 2

- 5 - related population risk and to protect public health with an adequate margin of safety

. In selecting the level of the annual PM 2.5 standard, b ased on the characterization and assessment of the epidemiological and other studies presented and assessed in the Integrated Science Assessment and the Policy Assessment, the Administrator recognizes the substantial increase in the number and diversity of studies available in this review . This expanded body of evidence includes extended analyses of the seminal studies of long

- term PM 2.5 exposures (i.e., ACS and Harvard Six Cities studies) as well as important new long

- term exposure studies (as

126 See 71 FR 61148 and 61168, October 17, 2006.

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- 399 summarized in Figures 1 and 2). Collectively, the Administrator notes that these studies, along with evidence available in the last review, provide consistent and stronger evidence than previously observed of an association between long

- term PM 2.5 exposures and premature mortality in areas with lower long

- term ambient concentrations than previously observed, with the strongest evidence related to cardiovascular

- related mort ality. The Administrator also recognizes the availability of stronger evidence of morbidity effects associated with long

- term PM 2.5 exposures, including evidence of respiratory effects such as decreased lung function growth, from the extended analyses for the Southern California Children’s Health Study and evidence of cardiovascular effects from the WHI study. Furthermore, the Administrator recognizes new U.S. multi

- city studies that greatly expand and reinforce our understanding of mortality and morbidity effects associated with short

- term PM 2.5 exposures, providing stronger evidence of associations in areas with ambient concentrations similar to those previously observed in short

- term exposure studies considered in the previous review (as summarized in Fig ure 3). The Administrator recognizes the strength of the scientific evidence for evaluating health effects associated with fine particles, noting that the newly available scientific evidence builds upon the previous scientific data base to provide evidenc e of generally robust associations and a basis for greater confidence in the reported associations than in the last review. She notes the conclusion of the Integrated Science Assessment that this body of evidence supports a causal relationship between long

- and short

- term PM 2.5 exposures and mortality and cardiovascular effects and a likely causal relationship between long

- and short

-

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- 400 term PM 2.5 exposures and respiratory effects. In addition, the Administrator notes additional, but more limited evidence, for a broader range of health endpoints including evidence suggestive of a causal relationship for developmental and reproductive effects as well as for carcinogenic effects. Based on information discussed and presented in the Integrated Science Assessment,
t he Administrator recognizes that health effects may occur over the full range of concentrations observed in the epidemiological studies of both long

- term and short

- term exposures, since no discernible population

- level threshold for any such effects can be identified based on the currently available evidence (U.S. EPA, 2009a, section 2.4.3). To inform her decisions on an appropriate level for the annual standard that will protect public health with an adequate margin of safety, in the absence of any discerni ble population

- level thresholds, the Administrator judges that it is appropriate to consider the relative degree of confidence in the magnitude and significance of the associations observed in epidemiological stud ies across the range of long

- term PM 2.5 con centrations in such studies . Further, she recognizes, in taking note of CASAC advice and the distributional statistics analysis discussed in the Policy Assessment and in section III.E.4.a above, that there is significantly greater confidence in the magnitu de and significance of observed associations for the part of the air quality distribution corresponding to where the bulk of the health events evaluated in each study have been observed , generally at and around the long

- term mean concentrations . Conversely , she also recognizes that there is significantly diminished confidence in the magnitude and significance of observed associations in the low er part of the air quality distribution corresponding to where a relatively small

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- 401 proportion of the health events w ere observed. F urther, the Administrator recognizes that the long

- term mean concentrations, or any other specific point in the air quality distribution of each study, do not represent a “bright line” at and above which effects have been observed and below which effects have not been observed.
I n considering the long

- term mean concentrations reported in epidemiological studies, the Administrator recognizes that in selecting a level of the annual standard that will protect public health with an adequate margin of safety , it is not sufficient to focus on a concentration generally somewhere within the range of long

- term mean concentrations from the key long

term and short

- term exposure studies that reported lower concentrations than had been observed in ear lier reviews. These key studies provide information for various types of serious health endpoints (including mortality and morbidity effects), different study populations (which may include at

- risk populations such as children and older adults), and differ ent air quality distributions that are specific to each study. A level somewhere within the range of long

- term mean concentrations of the full set of key studies would be higher than the long

- term mean of at least one of the studies being considered and th erefore would not provide a sufficient degree of protection against the health effects observed in that study. Absent some reasoned basis to place less weight on the evidence in the epidemiological study with the lowest long

term mean concentration among t hese key studies, this approach would not be consistent with the requirement to set a standard that will protect public health with an adequate margin of safety. 127 Thus, the Administrator recognizes it is important to protect against the serious

127 See American Farm Bureau Federation v. EPA , 559 F. 3d 512, 525

- 26 (D.C. Cir. 2009).

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- 402 effects obs erved in each of these studies so as to protect public health with an adequate margin of safety . In so doing, she looks to identify the study with the lowest long

- term mean concentration within the full set of key studies to help inform her decision of the appropriate standard level which will provide protection for the broad array of health outcomes observed in all of the studies, including effects observed in at

- risk populations. Further, consistent with the general approach summarized in section III.E.4. a above and supported by CASAC as discussed in section III.E.4.b.ii above, the Administrator recognizes that it is appropriate to consider a level for an annual standard that is not just at but rather is somewhat below the long

- term mean PM 2.5 concentratio ns reported in each of the key long

and short

- term exposure studies. In so doing, she focuses especially on multi

- city studies that evaluated health endpoints for which the associations are causal or likely causal (i.e., mortality and cardiovascular and r espiratory effects associated with both long

- and short

- term PM 2.5 exposures). As discussed above, the importance of considering a level somewhat below the lowest long

- term mean concentrations in this set of key studies is to establish a standard that woul d be protective against the observed effects in all of the studies, and that takes into account the relative degree of confidence in the magnitude and significance of observed associations across the air quality distributions in these studies. The Adminis trator recognizes that there is no clear way to identify how much below the long

- term mean concentrations of key studies to set a standard that would provide requisite protection with an adequate margin of safety. She therefore must use her judgment to wei gh the available scientific and technical information, and associated uncertainties, to reach a final

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- 403 decision on the appropriate standard level. In considering the information in Figures 1

- 4 for effects classified as having evidence of a causal or likel y causal relationship with long

- or short

term PM 2.5 exposures, she observes a cluster of short

- term exposure studies with long

- term mean concentrations within a range of 13.4 μg/m 3 down to 12.8 μg/m 3 (Dominici et al., 2006; Burnett and Goldberg, 2003; Zano betti and Schwartz, 2009; Bell et al., 2008; Burnett et al., 2004). She also observes a cluster of long

- term exposure studies with long

- term mean concentrations within a range of 14.5 μg/m 3 to 13.6 μg/m 3 (Dockery et al., 1996; Lipfert et al., 2006; Zeger e t al., 2008; McConnell et al., 2003; Goss et al., 2004; Eftim et al., 2008). For the reasons discussed in response to public comments in section III.E.4.c above, the Administrator is less influenced by the long

- term mean PM 2.5 concentrations from the Mille r et al. (2007) and Krewski et al. (2009) studies with reported long

- term mean PM 2.5 concentrations of 12.9 and 14.0 μg/m 3 , respectively. In each case, the most relevant exposure periods would likely have had higher mean PM 2.5 concentrations than those rep orted in the studies. 128 Thus, the Administrator considers the long

- term mean PM 2.5 concentrations from these two studies to be a highly uncertain basis for informing her selection of the annual standard level. 129 To help guide her judgment of the appropriate level below the long

- term mean concentrations in the epidemiological studies at which to set the standard, the Administrator

128 In the case of Miller et al. (2007), the mean concentration is based on a single year of air quality data which post

- dated by two years the period for which the health events data were collected. In the case of Krewski et a l. (2009),the air quality data were based on the last two years of the 18

- year period for which the health event data were collected. 129 Nonetheless, as noted above, the EPA notes that the Krewski et al. (2009) and Miller et al. (2007) studies provide stro ng evidence of mortality and cardiovascular

- related effects associated with long

- term PM 2.5 exposures to inform causality determinations reached in the Integrated Science Assessment (U.S. EPA, 2009a, sections 7.2.11 and 7.6).

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- 404 considered additional information from epidemiological studies concerning the broader distribution of PM 2.5 concentrations which c orrespond to the health events observed in these studies (e.g., deaths, hospitalizations). The Administrator observes that the development and use of this information in considering standard levels is consistent with CASAC’s advice, as discussed in section III.E.4.b.ii above, to focus on understanding the concentrations that were most influential in generating the health effect estimates in individual studies (Samet, 2010d, p. 2). In considering this additional population

- level information, the Administrat or recognizes that, in general, the confidence in the magnitude and significance of an association identified in a study is strongest at and around the long

- term mean concentration for the air quality distribution, as this represents the part of the distri bution in which the data in any given study are generally most concentrated. She also recognizes that the degree of confidence decreases as one moves towards the lower part of the distribution. Consistent with the approach used in the Policy Assessment, th e Administrator believes that the range from approximately the 25 th
to 10 th percentiles is a reasonable range for providing a general frame of reference as to the part of the distribution in which her confidence in the associations observed in epidemiologi cal studies is appreciably lower. However, as noted above, it is important to emphasize that there is no clear dividing line or single percentile within a given distribution provided by the scientific evidence that is most appropriate or ‘correct’ to use to characterize where the degree of confidence in the associations warrants setting the annual standard level. The decision of the appropriate standard level below the long

- term mean concentrations of the key studies , which

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- 405 in conjunction with the other el ements of the standard would protect public health with an adequate margin of safety, is largely a public health policy judgment, taking into account all of the evidence and its related uncertainties. As discussed in section III.E.4.b, the Administrator t akes note of additional population

level data that were made available to the EPA by study authors. 130 In considering this information, the Administrator particularly focuses on the analysis of the distributions of the health event data for each area within these studies and the corresponding air quality data for the two short

- term exposure studies (Zanobetti and Schwartz, 2009; Bell et al., 2008). These short

- term exposure studies evaluate the relationship between daily changes (one or more days) in PM 2.5 co ncentrations and daily changes in health events (e.g., deaths, hospitalizations), such that the air quality concentrations that comprise the most relevant exposure periods in these studies are contemporaneous with the health event data. In addition, these studies considered more recent air quality data, representing generally lower PM 2.5 concentrations, in a large number of study areas across the U.S. Thus, such studies provide the most useful evidence for an analysis evaluating the distribution of health e vent data and the corresponding long

- term mean PM 2.5 concentrations across the areas included in each multi

- city study.

130 As summarized in section II I.E.4.a, population

- level data were provided to the EPA for four studies. These four studies represent some of the strongest evidence showing associations between health effects and PM 2.5 within the overall body of scientific evidence and include three stu dies (Krewski et al., 2009; Bell et al., 2008; and Zanobetti and Schwartz, 2009) that were used as the basis for concentration

- response functions in the quantitative risk assessment (U.S. EPA, 2010a, section 3.3.3). T he Administrator recognizes that the ad ditional population

- level data available for these four multi

- city studies represents a more limited data set compared to the set of long

- term mean PM 2.5 concentrations which were available in the published literature for all studies considered in the Inte grated Science Assessment.

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- 406 The Administrator also considered the additional population

- level data that were made available to EPA for two long

- term exposure studi es (Krewski et al., 2009; Miller et al., 2007). She re cognizes that in long

- term exposure studies investigators follow a specific group of study participants (i.e., cohort) over time and across urban study areas, and evaluate how PM 2.5 concentrations avera ged over a period of years are associated with specific health endpoints (e.g., deaths) across cities. As discussed in response to public comments in section III.E.4.c, disentangling the effects observed in long

- term exposure studies associated with more r ecent air quality measurements from effects that may have been associated with earlier, and most likely higher, PM 2.5 exposures introduces some uncertainty with regard to understanding the appropriate exposure window associated with the observed effects. T his is in contrast to the short

- term exposure studies where the relevant exposure period is contemporaneous to the period for which the health data were collected. In light of these considerations, as noted above, the Administrator considers the analysis o f air quality concentrations that correspond to the distribution of population

- level data in these two studies to be a highly uncertain basis for informing her selection of the annual standard level. Based on the above considerations, the Administrator vi ews the additional population

level data for the two short

- term exposure studies as appropriate to help inform her judgment of how much below the long

- term mean concentrations to set the level of the annual standard. The Administrator notes that the long

- t erm mean PM 2.5 concentrations corresponding with study areas contributing to the 25 th percentiles of the distribution of deaths and cardiovascular

related hospitalizations in these two short

- term exposure studies were 12.5 μg/m 3 and 11.5

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- 407 μg/m 3 , respectivel y, for Zanobetti and Schwartz (2009) and for Bell et al. (2008) , with the 10 th percentiles being lower by approximately 2 μg/m 3 in each study.

. The Administrator recognizes, as summarized in section III.B above and discussed more fully in section III.B.2 of the proposal, that important uncertainties remain in the evidence and information considered in this review of the primary fine particle standards. These uncertainties are generally related to understanding the relative toxicity of the different
compone nts in the fine particle mixture, the role of PM 2.5 in the complex ambient mixture, exposure measurement errors, and the nature and magnitude of estimated risks related to increasingly lower ambient PM 2.5 concentrations. Furthermore, the Administrator note s that epidemiological studies have reported heterogeneity in responses both within and between cities and geographic regions across the U.S. She recognizes that this heterogeneity may be attributed, in part, to differences in fine particle composition in different regions and cities. 131 With regard to evidence for reproductive and developmental effects identified as being suggestive of a causal relationship with long

- term PM 2.5 exposures, the Administrator recognizes that t here are a number of limitations as sociated with this body of evidence including: the limited number of studies evaluating such effects; uncertainties related to identifying the relevant exposure time periods of concern; and limited toxicological evidence providing little information on the mode of action(s) or biological plausibility for an association

131 Nonetheless, as explained in section III.E.1, the currently available evidence is not sufficient to support replacing or supplementing the PM 2.5 indicator with any other indicator defined in terms of a specific fine particle c omponent or group of components associated with any source categories of fine particles. Furthermore, the evidence is not sufficient to support eliminating any component or group of components associated with any source categories of fine particles from th e mix of fine particles included in the PM 2.5 indicator.

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- 408 between long

- term PM 2.5 exposures and adverse birth outcomes. Nonetheless, the Administrator believes that this more limited body of evidence provides some support for considering that seriou s effects may be occurring in a susceptible population at concentrations lower than those associated with effects classified as having a causal or likely causal relationship with long

- term PM 2.5 exposures (i.e., mortality, cardiovascular, and respiratory

e ffects). Overall, the Administrator believes that the available evidence interpreted in light of the remaining uncertainties, as summarized above and discussed more fully in the Integrated Science Assessment and the Policy Assessment, provides increased co nfidence relative to information available in the last review and provides a strong basis for informing her final decisions in the current review. The Administrator is mindful that considering what standards are requisite to protect public health with an a dequate margin of safety requires public health policy judgments that neither overstate nor understate the strength and limitations of the evidence or the appropriate inferences to be drawn from the evidence. In considering how to translate the available i nformation into appropriate standard levels, the Administrator weighs the available scientific information and associated uncertainties and limitations. For the purpose of determining what annual standard level is appropriate the Administrator recognizes
t hat there is no single factor or criterion that comprises the ‘‘correct’’ approach to weighing the various types of available evidence and information. In considering this information, the Administrator notes the advice of CASAC that “there are significant public health consequences at the current levels of the standards that justify

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- 409 consideration of lowering the PM 2.5 NAAQS further” (Samet, 2010c, p. 12). In addition, she recognizes that CASAC concluded, “although there is increasing uncertainty at lower l evels, there is no evidence of a threshold (i.e., a level below which there is no risk for adverse effects)” (Samet, 2010, p.ii) and that the final decisions on standard levels must reflect a judgment of the available scientific information with respect to her interpretation of the CAA’s requirement to set primary standards that provide requisite protection to public health with an adequate margin of safety (Samet, 2010d, p. 4). The Administrator recognizes CASAC’s advice that the currently available scient ific information provided support for considering an annual standard level within a range of 13 to 11 μg/m 3 and a 24

- hour standard level within a range of 35 to 30 μg/m 3 . In considering how the annual and 24

- hour standards work together to provide appropri ate public health protection, the Administrator observes that CASAC did not express support for any specific levels or combinations of standards within these ranges. She also notes that CASAC encouraged the EPA staff to consider additional data from epidem iological studies to help quantify the characterization of the PM 2.5 concentrations that were most influential in generating the health effect estimates in these studies (Samet, 2010d, p. 2). In response to CASAC’s advice, the Administrator recognizes tha t the EPA staff acquired additional data from authors of key epidemiological studies and analyzed these data to characterize the distribution of PM 2.5 concentrations in relation to health events data to better understand the degree of confidence in the ass ociations observed in the studies as discussed above. The Administrator recognizes that the final Policy Assessment included consideration of these additional analyses in reaching final staff conclusions with regard to the broadest range of

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- 410 alternative sta ndard levels supported by the science. She takes note that the final Policy Assessment concluded that while alternative standard levels within the range of 13 to 11 μg/m 3 were appropriate to consider, the evidence most strongly supported consideration of a n annual standard level in the range of 12 to 11 μg/m 3 . The Administrator is aware that, in transmitting the final Policy Assessment to CASAC, the Agency notified CASAC that the final staff conclusions reflected consideration of CASAC’s advice and that tho se staff conclusions were based, in part, on the specific distributional analysis that CASAC had urged the EPA to conduct (Wegman, 2011). Thus, CASAC had an opportunity to comment on the final Policy Assessment, but chose not to provide any additional comm ents or advice after receiving it. In selecting the annual standard level, the Administrator has considered many factors including the nature and severity of the health effects involved, the strength of the overall body of scientific evidence as considered in reaching causality determinatio ns, the size of the at

- risk populations, and the estimated public health impacts. She has also considered the kind and degree of the uncertainties that remain in the available scientific information. She recognizes that the association between PM 2.5 and se rious health effects is well established, including at concentrations below those allowed by the current standard. Further, she recognizes the CAA requirement that requires primary standards to provide an adequate margin of safety was intended to address u ncertainties associated with inconclusive scientific and technical information as well as to provide a reasonable degree of protection against hazards that research has not yet identified. In considering the currently available evidence, as summarized and discussed more broadly above, the information on risk, CASAC advice, the conclusions of

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- 411 the Policy Assessment, and public comments on the proposal, the Administrator strongly believes that a lower annual standard level is needed to protect public health wi th an adequate margin of safety. In reaching her final decision on the appropriate annual standard level to set, the Administrator is mindful that the CAA does not require that primary standards be set at a zero

risk level, but rather at a level that reduc es risk sufficiently so as to protect public health, including the health of at

- risk populations, with an adequate margin of safety. On balance, the Administrator concludes that an annual standard level of 12 μg/m 3 would be requisite to protect the public health with an adequate margin of safety from effects associated with long

and short

- term PM 2.5 exposures, while still recognizing that uncertainties remain in the scientific information. In the Administrator’s judgment, an annual standard of 12 μg/m 3 ap propriately reflects placing greatest weight on evidence of effects for which the Integrated Science Assessment determined there is a causal or likely causal relationship with long

- and short

- term PM 2.5 exposures. An annual standard level of 12 μg/m 3 is be low the long

- term mean PM 2.5 concentrations reported in each of the key multi

- city, long

- and short

- term exposures studies providing evidence of an array of serious health effects (e.g., premature mortality, increased hospitalization for cardiovascular and respiratory effects). As noted above, the importance of

cons idering a level somewhat below the lowest long

- term mean concentration in the full set of studies considered is to set a standard that would provide appropriate protecti on against the observed effects in all such studies.

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- 412 In reaching her decision, the Adm inistrator has taken into account that at and around the mean PM 2.5 concentration in any given study represents a part of the air quality distribution in which the health event data in that study are generally most concentrated. Furthermore, in identifying an appropriate annual standard level below the long

- term mean concentrations, she recognizes that there is no evidence to support the existence of any discernible threshold, and, therefore, she has a high degree of confidence that the observed effects are associated with concentrations not just at but extending somewhat below the long

- term mean concentration. To further inform her judgment in setting the annual standard level so as to protect public health with an adequate margin of safety , the Administrat or has placed weight on additional population

- level information available from a subset of these epidemiological studies, consistent with CASAC advice. In particular, she has drawn from two short

- term exposure studies, which provide the most relevant infor mation for evaluating the distribution of health events and corresponding long

- term PM 2.5 concentrations. As explained above, this helps inform her judgment as to the degree of confidence in the observed associations in the epidemiological studies. In this regard, the Administrator generally judges the region around the 25 th percentile as a reasonable part of the distribution to help guide her decision on the appropriate standard level. Since this evidence comes primarily from two studies, a relatively mode st data set, the Administrator deems it reasonable not to draw further inferences from air quality and health event data in the lower part of the distribution for the purpose of setting a standard level. The Administrator notes that the long

- term mean PM 2. 5 concentrations around the 25 th percentile of the distributions of deaths and cardiovascular

- related hospitalizations

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- 413 were approximately around 12 μg/m 3 in these two studies . The Administrator views this information as helpful in guiding her determination as to where her confidence in the magnitude and significance of the associations is reduced to such a degree that a standard set at a lower level would not be warrant ed to provide requisite protection that is neither more nor less than needed to provide a n adequate margin of safety

. The Administrator also recognizes that a level of 12 μg/m 3 places some weight on studies which provide evidence of reproductive and developmental effects (e.g., infant mortality, low birth weight). These studies were identified in the Integrated Science Assessment as having evidence suggestive of a causal relationship with long

- term PM 2.5 concentrations. A level of 12 μg/m 3 is approximately the same level as the lowest long

- term mean concentration reported in such studies (Figur es 2 and 4; 11.9 μg/m 3 for Bell et al., 2007). 132 While the Administrator acknowledges that this evidence is limited, she believes it is appropriate to place some weight on these studies in order to set a standard that provides protection with an adequate ma rgin of safety, including providing protection for at

- risk populations, as required by the CAA. Due to the limited nature of this evidence, she has determined it is not necessary to set a standard below the lowest long

- term mean concentration in these stud ies.

132 With respect to cancer, mutagenic, and genotoxic effects, the Administrator observes that the PM 2.5 concentrations reported in studies evaluating these effects generally included ambient concentra tions that are equal to or greater than ambient concentrations observed in studies that reported mortality and cardiovascular and respiratory effects (U.S. EPA, 2009a, section 7.5). Therefore, the Administrator concludes that in selecting alternative stand ard levels that provide protection from mortality and cardiovascular and respiratory effects, it is reasonable to anticipate that protection will also be provided for carcinogenic effects.

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- 414 In reflecting on extensive public comments received on the proposal as discussed in section III.E.4.c above, the Administrator recognizes that some commenters have offered different evaluations of the evidence and other information available in this review and would make different judgments about the weight to place on the relative strengths and limitations of the scientific information and about how such information could be used in making public health policy decisions on the annual standard level. One group of such commenters who supported a higher annual standard level (e.g., above 13 μg/m 3 ) would place greater weight on the remaining uncertainties in the evidence as a basis for supporting a higher standard than the Administrator judges to be appropriate. Such an approach is based on these commenters’ judgment that the uncertainties remaining in the evidence are too great to warrant setting a n annual standard below the current level. The Admini strator does not agree. As an initial matter, an annual standard level of 13 μg/m 3 or higher would be above the long

- term mean concentrations reported in two well

- conducted, multi

- city short

- term exposure studies reporting positive and statistically signi ficant associations of serious effects (Burnett et al., 2004 and Bell et al., 2008). These important studies are fully consistent with the pattern of evidence presented by the large body of evidence in this review. As the Administrator recognized in the pr oposal, and as advised by CASAC, the appropriate focus for selecting the level of the annual PM 2.5 standard is on concentrations somewhat below the lowest long

- term mean concentrations from the set of key studies of both long

- term and short

- term PM 2.5 expo sures considered by the EPA (i.e., as shown in Figure 4). Thus, a standard level set at 13 μg/m 3 or higher would clearly not provide protection for the effects observed in the full set

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- 415 epidemiological studies and, therefore, this standard level could not b e judged to be requisite with an adequate margin of safety. 133 In addition, as noted above, in recognizing that there is no evidence to support the existence of a discernible threshold below which an effect would not occur, the Administrator is mindful that effects occur around and below the long

- term mean concentrations reported in both the short

- term and long

- term the epidemiological studies. A standard level of 13 μg/m 3 or higher would not appropriately take into account evidence from the two well

- conduct ed, multi

city, short

- term exposure studies reporting serious effects with long

- term mean concentrations below 13 μg/m 3 noted above (Burnett et al, 2004; Bell et al., 2008). Such a standard level would also not appropriately take into account additional po pulation

- level data from a limited number of epidemiological studies. This approach would ignore CASAC’s advice to consider such information in order to better understand the concentrations over which there is a high degree of confidence regarding the magn itude and significance of the associations observed in individual epidemiological studies and where there is appreciably less confidence

. Furthermore, a standard level of 13 μg/m 3 or higher would not appropriately take into
account the more limited eviden ce of effects in some at

- risk populations (e.g., low birth weight). In the Administrator’s view, a standard set at this level would not provide protection

133 The Administrator is mindful that, in reviewing the 2006 final PM NAAQS decisions, the D.C. Circuit Court of Appeals concluded that the EPA failed to adequately explain why that annual standard provided requisite protection from effects associated with both long

- and short

term exposures or from morbidity effects in chi ldren and other at

- risk populations when long

- term means of important short

- term studies were below the level the Administrator selected for the annual standard. See American Farm Bureau v. EPA. 559 F. 3d 512, 524

- 26. There is no reasonable basis to discou nt these two studies for purposes of setting the level of the annual standard.

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- 416 with an adequate margin of safety, including providing protection for at

- risk populations. The Admini strator is mindful that the CAA requirement that primary standards provide an adequate margin of safety, discussed in section II.A above, was intended to address uncertainties associated with inconclusive scientific and technical information available at t he time of standard setting as well as to provide a reasonable degree of protection against hazards that research has not yet identified. In light of the entire body of evidence as discussed above, the Administrator judges that an annual standard level se t above 12 μg/m 3 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 exposure to PM 2.5. The Administrator also recognizes that a second group of commenters supported a lower annual standard level (e.g., no higher than 11 μg/m 3 ). Such a standard level would reflect placing essentially as much weight on the relatively more limited data providing evidence suggestive of a causal relationship for effects observed in some at

- risk populations (e.g., low birth weight) as on more certain evidence of effects classified as having a causal or likely causal relationship with PM 2.5 exposures. In the Administrator’s view, while it is important to place some weight on such suggestive evidence, it would not be appropriate to place as much weight on it as the commenters would do. An annual standard level of 11 μg/m 3 would also reflect these commenters’ judgment that it is appropriate to focus on a lower part of the distributions of health event data from the small number of epidemiological studies for which this information was made available than

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- 417 the Administrator believes is warranted . In the Administrator’s view, using this type of information to set a standard level of 11 μg/m 3 or below would assume too high a degree of confidence in the magnitude and significance of the associations observed in the lower part of the distributions of health events observed in these studies. Given the uncertainties in the evidence and the limited set of studies for which the EPA has information on the distribution of health event data and corresponding air quality data, the Administrator believes it is not appropriate to focus on the lower part of the distributions of health events data. On balance, the Administrator finds that the available evidence interpreted in light of the remaining uncertainties does not justify a standard level set below 12 μg/m 3 as necessary to protect public health with an adequate margin of safety. After carefully considering the above considerations and the public comments summarized in section III.E.4.c above, the Administrator has decided to set the level of the primary an nual PM 2.5 standard at 12 μg/m 3 . In her judgment, a standard set at this level provides the requisite degree of public health protection, including the health of at

- risk populations, with an adequate margin of safety and is neither more nor less stringent than necessary for this purpose. As discussed above, the Administrator concludes that an approach that focuses on setting a generally controlling annual standard is the most effective and efficient way to reduce total population risk associated with both l ong - and short

- term PM 2.5 exposures. Such an approach would result in more uniform protection across the U.S. than the alternative of

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- 418 setting the levels of the 24

- hour and annual standard such that the 24

- hour standard would generally be the controlling st andard in areas across the country (see section III.A.3). The Administrator recognizes that potential air quality changes associated with meeting an annual standard level of 12.μg/m 3 will result in lowering risks associated with both long

- and short

- term PM 2.5 exposures by lowering the overall air quality distribution. However, the Administrator recognizes that such an annual standard alone would not be expected to offer sufficient protection with an adequate margin of safety against the effects of sho rt
- term PM 2.5 exposures in all parts of the country . As a result, in conjunction with an annual standard level of 12 μg/m 3 , the Administrator concludes that it is appropriate to continue to provide supplemental protection by means of a 24

- hour standard set at the appropriate level, particularly for areas with high peak

- to
- mean ratios possibly associated with strong local or seasonal sources and for areas with PM 2.5 - related effects that may be associated with shorter

than

- daily exposure periods. In selectin g the level of a 24

- hour standard meant to provide such supplemental protection, the Administrator relies upon evidence and air quality information from key short

term exposure studies. In considering these studies, the Administrator notes that to the exte nt air quality distributions in the study areas considered are reduced to meet the current 24

- hour standard (at a level of 35 μg/m 3 ) or to meet the revised annual standard discussed above (at a level of 12 μg/m 3 ), additional protection would be anticipated against the effects observed in these studies. In light of this, when selecting the appropriate level for the 24

- hour standard, the Administrator considers both the 98 th percentiles of 24

- hour PM 2.5 concentrations and the long

-

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- 419 term mean PM 2.5 concentratio ns in the locations of the short

- term exposure studies. She notes that such consideration of both short

- and long

- term PM 2.5 concentrations can inform her decision on the extent to which a given 24

- hour standard, in combination with the revised annual stan dard established in this notice, would provide protection against the health effects reported in short

- term studies. As discussed in section III.E.4.a above, the Administrator concludes that multi

- city short

term exposure studies provide the strongest dat a set for informing her decisions on appropriate 24

- hour standard levels. With regard to the limited number of single

- city studies that reported positive and statistically significant associations for a range of health endpoints related to short

- term PM 2.5 concentrations in areas that would likely have met the current suite of PM 2.5 standards, the Administrator recognizes that many of these studies had significant limitations (e.g., limited statistical power, limited exposure data) or equivocal results (mix ed results within the same study area) that make them unsuitable to form the basis for setting the level of a 24

- hour standard. With regard to multi

- city studies that evaluated effects associated with short

- term PM 2.5 exposures, the Administrator observes an overall pattern of positive and statistically significant associations in studies with 98 th percentile 24

- hour values averaged across study areas within the range of 45.8 to 34.2 μg/m 3 (Burnett et al., 2004; Zanobe tti and Schwartz, 2009; Bell et al., 2008; Dominici et al., 2006a, Burnett and Goldberg, 2003; Franklin et al., 2008). The Administrator notes that, to the extent air quality distributions are reduced to reflect just meeting the current 24

- hour standard, a dditional protection would be provided for the effects

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- 420 observed in the three multi

- city studies with 98 th percentile values greater than 35 μg/m 3 (Burnett et al., 2004; Burnett and Goldberg, 2003; Franklin et al., 2008). In the three additional multi

- city studies with 98 th percentile values below 35 μg/m 3 , specifically 98 th percentile concentrations of 34.2, 34.3, and 34.8 μg/m 3 , the Administrator notes that these studies reported long

- term mean PM 2.5 concentrations of 12.9, 13.2, and 13.4 μg/m 3 , respective ly (Bell et al., 2008; Zanobetti and Schwartz, 2009; Dominici et al., 2006a). In revising the level of the annual standard to 12 μg/m 3 , as discussed above, the Administrator recognizes that additional protection would be provided for the short

- term effects observed in these multi

- city studies such that revision to the 24

- hour standard would not be warranted. That is, by lowering the level of the annual standard to 12 μg/m 3 , the 98 th percentile of the distribution would be lowered as well such that additiona l protection from effects associated with short

- term exposures would be afforded. Therefore, the epidemiological evidence supports a conclusion that it is appropriate to retain the level of the 24

- hour standard at 35 μg/m 3 , in conjunction with a revised an nual standard level of 12 μg/m 3

. In addition to considering the epidemiological evidence, the Administrator also has taken into account air quality information based on county

- level 24

- hour and annual design values to understand the implications of revisi ng the annual standard level from 15 to 12 μg/m 3 in conjunction with retaining the 24

- hour standard level at 35 μg/m 3 . She has considered this information to evaluate the public health protection provided by the two standards in combination and to evaluate the most appropriate means of developing a suite of standards providing requisite public health protection with an adequate margin of safety.

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- 421 In considering the air quality information, the Administrator observes that a suite of
PM 2.5 standards that incl udes an annual standard level of 12 μg/m 3 and a 24

- hour standard level of 35 μg/m 3 would result in the annual standard as the generally controlling standard in most regions across the country, except for certain areas in the Northwest, where the annual

mea n PM 2.5 concentrations have historically been low but where relatively high 24

- hour concentrations occur, often related to seasonal wood smoke emissions (U.S. EPA, 2011a, pp. 2

- 89 to 2

- 91, Figure 2

- 10). In fact, these are the type of areas for which the su pplemental protection afforded by the 24

- hour standard is intended, such that the two standards together provide the requisite degree of protection. The Administrator concludes the current 24

- hour standard at a level of 35 μg/m 3 , in conjunction with a revi sed annual standard level of 12 μg/m 3 , will provide appropriate protection from effects observed in studies in such areas in which the long

- term mean concentrations were below 12 μg/m 3 and the 98 th percentile 24

- hour concentrations were above 35 μg/m 3 (e.g ., areas in the Northwest U.S.). After carefully taking the public comments and above considerations into account, the Administrator has decided to retain the current level of the primary PM 2.5 24

- hour standard at 35 μg/m 3 in conjunction with revising the annual standard level from 15.0 μg/m 3 to 12.0 μg/m 3

. 134 In the Administrator’s judgment, this suite of primary PM 2.5 standards and the rationale supporting these levels appropriately reflects consideration of the strength of the available evidence and other information and its associated uncertainties as well as the advice

134 As noted in section II.B.1, Table 1 and section III.E.4.a above, the annual standard level is defined to one decimal place. Throughout this section, the annual standard levels discussed have been denoted as integer values (e.g., 12 μg/m 3 ) for simplicity.

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- 422 of CASAC and consideration of public comments. In the Administrator’s judgment, this suite of primary PM 2.5 standards is sufficient but not more protective than necessary to protect the
pu blic health, including at

- risk populations, with an adequate margin of safety from effects associated with long

- and short

- term exposures to fine particles. This suite of standards will provide significant protection from serious health effects including p remature mortality and cardiovascular and respiratory morbidity effects that are causally or likely causally related to long

- and short

- term PM 2.5 exposures. These standards will also provide an appropriate degree of protection against other health effects for which there is more limited evidence of effects and causality, such as reproductive and developmental effects. This judgment by the Administrator appropriately considers the requirement for a standard that is requisite to protect public health but is neither more nor less stringent than necessary. 135
D. Administrator’s Final Decisions on Primary PM 2.5 Standards For the reasons discussed above, and taking into account the information and assessments presented in the Integrated Science Assessment, Risk Assessment, and Policy Assessment, the advice and recommendations of CASAC, and public comments to date, the Administrator revises the current suite of primary PM 2.5 standards. Specifically, the Administrator revises: (1) the level of the primary annual P M 2.5 standard to 12.0 μg/m 3 and (2) the form of the primary annual PM 2.5 standard to one based on the highest appropriate area

wide monitor in an area, with no option for spatial averaging. In conjunction with revising the

135 The Administrator also judges that this suite of standards addresses the issues raised by the D.C. Circuit’s remand of the 2006 primary annual PM 2.5 standard by appropriately revising that standard.

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- 423 primary annual PM 2.5 standard to provide protection from effects associated with long

- and short

- term PM 2.5 exposures, the Administrator retains the level of 35 μg/m 3 and the 98 th percentile form of the primary 24

- hour PM 2.5 standard to continue to provide supplemental protection for area s with high peak PM 2.5 concentrations. The Administrator is not revising the
current PM 2.5 indicator or the annual and 24

- hour averaging times for the primary PM 2.5 standards. The Administrator concludes that this suite of standards would be requisite to
p rotect public health with an adequate margin of safety against health effects potentially associated with long

- and short

- term PM 2.5 exposures.