Risk Assessment to Support the Review of 

the PM Primary National Ambient Air 

Quality Standards 

External Review Draft 

September 2009 
 i

DISCLAIMER

This draft document has been prepared by staff from the Ambient Standards 

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

Agency. Any opinions, findings, conclusions, or recommendations are those of the 

authors and do not necessarily reflect the views of the EPA. This document is being 

circulated to obtain review and comment from the Clean Air Scientific Advisory 

Committee (CASAC) and the general public. Comments on this draft document should 

be addressed to Zachary Pekar, U.S. Environmental Protection Agency, Office of Air 

Quality Planning and Standards, C504-06, Research Triangle Park, North Carolina 27711 

(email: pekar.zachary@epa.gov). 

Elements of this report (see Acknowledgements below) have been provided to the 

U.S. Environmental Protection Agency (EPA) by Abt Associates, Inc. in partial 

fulfillment of Contract No. EP-D-08-100, Work Assignment 0-02. Any opinions, 

findings, conclusions, or recommendations are those of the authors and do not necessarily 

reflect the views of the EPA or Abt Associates, Inc. Any analyses, interpretations, or 

conclusions presented in this report based on emergency department, hospitalization and 

mortality baseline incidence data obtained from outside sources, are credited to the 

authors and not the institutions providing the raw data. 

ACKNOWLEDGEMENTS

In addition to EPA staff, personnel from Abt Associates, Inc. contributed to the 

writing of this document. Specific chapters and appendices where Abt Associates, Inc. 

made contributions include: chapter 3 (Overview of Methods Used in Estimating Risk for 

the Urban Case Studies), and appendices A (Air Quality Assessment), C 

(Epidemiological – Epi - Study Specific Information On PM2.5), E (Risk Analysis - Core 

Analysis), and F (Sensitivity Analysis Results). 

 

 
 ii

 EPA 452/P-09-006 

September 2009 

Risk Assessment to Support the Review of the PM Primary National Ambient Air 

Quality Standards - External Review Draft 

US Environmental Protection Agency 

Office of Air and Radiation 

Office of Air Quality Planning and Standards 

Health and Environmental Impacts Division 

Ambient Standards Group 

Research Triangle Park, North Carolina 27711 
 iii

Table of Contents 

List of Acronyms/Abbreviations........................................................................................ ix 

1 INTRODUCTION ....................................................................................................... 1 

1.1 Background...................................................................................................... 3 

1.2 Current Health Risk Assessment: Goals and Planned Approach .................... 6 

1.3 Organization of Document .............................................................................. 7 

2 SCOPE......................................................................................................................... 8 

2.1 Overview of the PM NAAQS risk assessment from the last review............... 9 

2.2 Original assessment plan ............................................................................... 11 

2.2.1 Risk assessment.................................................................................... 11 

2.2.2 Population exposure analysis ............................................................... 13 

2.3 CASAC comments provided on the Scope and Methods Plan...................... 13 

2.4 Current scope and key design elements......................................................... 15 

2.4.1 Risk Assessment .................................................................................. 15 

2.4.2 Population exposure analysis ............................................................... 17 

2.5 Alternative Standard Levels Included in the Risk Assessment ..................... 18 

3 METHODS USED IN URBAN CASE STUDY ANALYSIS.................................. 22 

3.1 General Approach.......................................................................................... 22 

3.1.1 Basic Structure of the Risk Assessment............................................... 22 

3.1.2 Calculating PM-Related Health Effects Incidence .............................. 29 

3.1.2.1 General approach .......................................................................... 29 

3.1.2.2 Short-term vs. long-term exposure ............................................... 30 

3.1.2.3 Calculating annual incidence ........................................................ 31 

3.2 Air Quality Inputs.......................................................................................... 32 

3.2.1 Characterizing recent conditions.......................................................... 32 

3.2.2 Estimating policy relevant background................................................ 34 

3.2.3 Simulating air quality to just meet current and alternative standards .. 34 

3.3 Selection of model inputs .............................................................................. 38 

3.3.1 Health endpoints .................................................................................. 38 

3.3.2 Selection and delineation of urban study areas.................................... 41 

3.3.3 Selection of epidemiological studies and concentration-response 

(C-R) functions within those studies.................................................... 45 
 iv

3.3.4 A summary of selected health endpoints, urban areas, studies, and 

concentration-response (C-R) functions used in the risk assessment .. 50 

3.4 Baseline Health Effects Incidence Data ........................................................ 63 

3.4.1 Data sources ......................................................................................... 63 

3.4.1.1 Mortality ....................................................................................... 63 

3.4.1.2 Hospital admission and emergency department visits.................. 63 

3.4.1.3 Populations.................................................................................... 65 

3.4.2 Calculation of baseline incidence rates................................................ 68 

3.5 Addressing Uncertainty and Variability ........................................................ 72 

3.5.1 Overview.............................................................................................. 72 

3.5.2 Key sources of variability .................................................................... 75 

3.5.3 Qualitative assessment of uncertainty.................................................. 77 

3.5.4 Single and multi-factor sensitivity analyses......................................... 85 

3.5.5 Summary of approach to addressing variability and uncertainty......... 89 

4 RESULTS.................................................................................................................. 91 

4.1 Assessment of health risk associated with recent conditions (core 

analysis) ......................................................................................................... 96 

4.1.1 Long-term mortality............................................................................. 96 

4.1.2 Short-term mortality........................................................................... 100 

4.1.3 Short-term morbidity.......................................................................... 102 

4.2 Assessment of health risk associated with Just meeting the current and 

alternative standards (core analysis)........................................................... 103 

4.2.1 Long-term mortality........................................................................... 105 

4.2.2 Short-term mortality........................................................................... 117 

4.2.3 Short-term morbidity.......................................................................... 123 

4.3 Sensitivity analysis results........................................................................... 127 

4.3.1 Single-factor sensitivity analysis results ............................................ 132 

4.3.1.1 Sensitivity analysis results associated with long-term exposure 

mortality...................................................................................... 132 

4.3.1.2 Sensitivity analysis results associated with short-term 

mortality...................................................................................... 134 

4.3.1.3 Sensitivity analysis results associated with short-term 

morbidity..................................................................................... 136 

4.3.1.4 Single-factor sensitivity analysis addressing model selection, 

lags, and co-pollutant models ..................................................... 137 

4.3.2 Multi-Factor Sensitivity Analysis ...................................................... 138 
 v

4.3.2.1 Multi-factor sensitivity analyses – long-term exposure 

mortality...................................................................................... 139 

4.3.2.2 Multi-factor sensitivity analyses – short-term exposure 

mortality...................................................................................... 140 

4.4 Evaluating the representativeness of the urban study areas in the national 

context.......................................................................................................... 141 

4.5 Overall Summary and Key Observations .................................................... 158 

4.5.1 Core risk results from the recent conditions, current NAAQS, and 

alternative NAAQS analyses.............................................................. 159 

4.5.2 Use of the reasonable set of alternative risk estimates generated 

through the sensitivity analysis .......................................................... 162 

4.5.3 Representativeness of the urban study areas in the national context 

based on consideration for coverage of PM2.5 risk-related 

parameters .......................................................................................... 166 

4.5.4 Use of the results of the national-scale long-term mortality analysis 

to evaluate degree of coverage of the 15 urban study areas for 

national-distribution of risk................................................................ 166 

5 NATIONAL-SCALE ASSESSMENT OF LONG-TERM MORTALITY 

RELATED TO PM2.5 Exposure.............................................................................. 168 

5.1 Overview...................................................................................................... 168 

5.2 Methods ....................................................................................................... 169 

5.2.1 Population Estimates.......................................................................... 169 

5.2.2 Population Exposure .......................................................................... 169 

5.2.3 Premature Mortality Estimates........................................................... 171 

5.3 Results.......................................................................................................... 171 

REFERENCES ............................................................................................................... 175 

Appendix A. Air Quality Assessment 

Appendix B. Hybrid (Non-Proportional) Rollback Approach 

Appendix C. Epidemiological Study Specific Information for PM Risk Assessment 

Appendix D. Supplement to Representativeness of the 15 Urban Study Areas 

Appendix E. Risk Estimates (Core Analysis)

Appendix F. Sensitivity Analysis Results 

Appendix G. Supplement to the National-Scale Assessment of Long-Term 

 Mortality Related to PM2.5 Exposure 
 vi

List of Tables 

Table 3-1. Numbers of Monitors and Numbers of Missing Days at Composite Monitors 

in Risk Assessment Locations from 2005 Through 2007. 33 

Table 3-2 Regional Policy-Relevant Background Estimates Used in the Risk 

Assessment. 34 

Table 3-3. EPA Design Values for Annual and \24-hour PM2.5 Standards for the Period 

2005-2007. 36 

Table 3-4. Urban Study Areas Selected for the Risk Assessment. 43 

Table 3-5. Locations, Health Endpoints, and Short-Term Exposure Studies Included in 

the PM2.5 Risk Assessment 51 

Table 3-6. Locations, Health Endpoints, and Long-Term Exposure Studies Included in 

the PM2.5 Risk Assessment 52 

Table 3-7. Summary of Locations, Health Endpoints, Studies and ConcentrationResponse Functions Included in the Core Analysis. 53 

Table 3-8. Summary of Locations, Health Endpoints, Studies and ConcentrationResponse Functions Included in Sensitivity Analyses. 61 

Table 3-9. Sources of Hospital Admissions (HA) and Emergency Department (ED) 

Visit Data. 64 

Table 3-10. Relevant Population Sizes for PM Risk Assessment Locations. 66 

Table 3-11. Baseline Mortality Rates (Deaths per 100,000 Relevant Population per Year) 

for 2006 for PM Risk Assessment Locations. 69 

Table 3-12. Baseline Hospital Admission (HA) and Emergency Department (ED) Rates 

(Admissions/Visits per 100,000 Relevant Population per Year) for 2007 for 

PM Risk Assessment Locations. 71 

Table 3-13. Summary of Qualitative Uncertainty Analysis of Key Modeling Elements in 

the PM NAAQS Risk Assessment. 79 

Table 4-1. Overview of Sensitivity Analysis Results. 130 

Table 4-2. Data Sources for PM NAAQS Risk Assessment Risk Distribution Analysis.

143 

Table 4-3. Summary Statistics for Selected PM Risk Attributes. 146 

Table 4-4 Results of Kolomogrov-Smirnoff Tests for Equality Between National and 

Urban Study Area Distributions for Selected National Risk Characteristic 

Variables 150 

Table 4-5 Derivation of a set of reasonable alternative risk estimates to supplement the 

core risk estimates (Los Angeles, current standards, for long-term all cause 

mortality). 164 

Table 5-1 Estimated PM2.5-related premature mortality associated with incremental 

air quality differences between 2005 ambient mean pm2.5 levels and lowest 

measured level from the epidemiology studies or policy relevant 

background (90th percentile confidence interval) 172 
 vii

List of Figures 

Figure 3-1. Major components of particulate matter health risk assessment. 24 

Figure 3-2. Flow diagram of risk assessment for short-term exposure studies. 27 

Figure 3-3. Flow diagram of risk assessment for long-term exposure studies. 28 

Figure 3-4 15 urban study areas included in the risk assessment (including seven PM 

regions used to guide selection of study areas). 44 

Figure 4-1. Estimated Percent Reductions From the Current Standards to Alternative Set 

of Standards in All Cause Mortality Associated with Long- Term Exposure 

to PM2.5 (Exposure Period: 1979 – 1983): Based on 2007 Air Quality Data. 

109 

Figure 4-2. Estimated Percent Reductions From the Current Standards to Alternative Set 

of Standards in All Cause Mortality Associated with Long-Term Exposure to 

PM2.5 (Exposure Period: 1999 – 2000): Based on 2007 Air Quality Data. 

110 

Figure 4-3. Estimated Percent Reductions From the Current Standards to Alternative Set 

of Standards in Ischemic Heart Disease Mortality Associated with Long-Term 

Exposure to PM2.5 (Exposure Period: 1979 – 1983): Based on 2007 Air 

Quality Data. 111 

Figure 4-4. Estimated Percent Reductions From the Current Standards to Alternative Set 

of Standards in Ischemic Heart Disease Mortality Associated with Long-Term 

Exposure to PM2.5 (Exposure Period: 1999 – 2000): Based on 2007 Air 

Quality Data. 112 

Figure 4-5. Estimated Percent Reductions From the Current Standards to Alternative Set 

of Standards in Cardiopulmonary Disease Mortality Associated with LongTerm Exposure to PM2.5 (Exposure Period:1979 – 1983): Based on 2007 Air 

Quality Data. 113 

Figure 4-6. Estimated Percent Reductions From the Current Standards to Alternative Set 

of Standards in Cardiopulmonary Disease Mortality Associated with LongTerm Exposure to PM2.5 (Exposure Period: 1999 – 2000): Based on 2007 Air 

Quality Data. 114 

Figure 4-7. Estimated Percent Reductions From the Current Standards to Alternative Set 

of Standards in Lung Cancer Mortality Associated with Long-Term Exposure 

to PM2.5 (Exposure Period: 1979 – 1983): Based on 2007 Air Quality Data. 

115 

Figure 4-8. Estimated Percent Reductions From the Current Standards to Alternative Set 

of Standards in Lung Cancer Mortality Associated with Long-Term Exposure 

to PM2.5 (Exposure Period: 1999 – 2000): Based on 2007 Air Quality Data. 

116 

Figure 4-9. Estimated Percent Reductions From the Current Standards to Alternative Sets 

of Standards in Non-Accidental Mortality Associated with Short-Term 

Exposure to PM2.5: Based on 2007 Air Quality Data. 120 

Figure 4-10.Estimated Percent Reductions From the Current Standards to Alternative 

Sets of Standards in Cardiovascular Mortality Associated with Short-Term 

Exposure to PM2.5: Based on 2007 Air Quality Data. 121 
 viii

Figure 4-11. Estimated Percent Reductions From the Current Standards to Alternative 

Sets of Standards in Respiratory Mortality Associated with Short-Term 

Exposure to PM2.5: Based on 2007 Air Quality Data. 122 

Figure 4-12. Estimated Percent Reductions From the Current Standards to Alternative 

Sets of Standards in Cardiovascular Hospital Admissions Associated with 

Short-Term Exposure to PM2.5: Based on 2007 Air Quality Data. 125 

Figure 4-13. Estimated Percent Reductions From the Current Standards to Alternative 

Sets of Standards in Respiratory Hospital Admissions Associated with ShortTerm Exposure to PM2.5: Based on 2007 Air Quality Data. 126 

Figure 4-14. Comparison of distributions for key elements of the risk equation: total 

population. 151 

Figure 4-15. Comparison of distributions for key elements of the risk equation: 98th

percentile 24-hour average PM2.5 152 

Figure 4-16. Comparison of distributions for key elements of the risk equation: all cause 

mortality rate. 153 

Figure 4-17. Comparison of distributions for key elements of the risk equation: 

mortality risk effect estimate from Zanobetti and Schwartz (2008). 154 

Figure 4-18. Comparison of distributions for selected variables expected to influence the 

relative risk from PM2.5: long term average July emperature. 155 

Figure 4-19. Comparison of distributions for selected variables expected to influence the 

relative risk from PM2.5: percent of population 65 and older. 156 

Figure 4-20. Comparison of distributions for selected variables expected to influence the 

relative risk from PM2.5: per capita annual personal income. 157 

Figure 4-21. Comparison of distributions for selected variables expected to influence the 

relative risk from PM2.5: cardiovascular disease prevalence days. 158 

Figure 5-1 Conceptual diagram of data inputs and outputs for national long-term 

mortality risk assessment 169 

Figure 5-2 2005 fused surface baseline PM2.5 concentrations 170 

Figure 5-3 Percentage of premature mortality attributable to PM2.5 exposure at various 

2005 annual average PM2.5 levels 173 

Figure 5-4 Cumulative distribution of county-level percentage of total mortality 

attributable to PM2.5 for the U.S. with markers identifying where along that 

distribution the urban case study area analysis fall 174 
September 2009 Draft – Do Not Quote or Cite ix

1 LIST OF ACRONYMS/ABBREVIATIONS 

2 

3 A/C Air conditioning 

4 ACS American Cancer Society 

5 Act Clean Air Act 

6 AMI Acute Myocardial Infarction 

7 AQS EPA's Air Quality System 

8 β Slope coefficient 

9 BenMAP Benefits Mapping Analysis Program 

10 BMI Body Mass Index 

11 BRFSS Behavioral Risk Factor Surveillance System 

12 CASAC Clean Air Scientific Advisory Committee 

13 CAA Clean Air Act 

14 CBSA Core-based Statistical Area 

15 CDC Centers for Disease Control 

16 CDF Cumulative Distribution Function 

17 CFR Code of Federal Regulations 

18 CHD Coronary Heart Disease 

19 CMAQ Community Multiscale Air Quality 

20 CO Carbon Monoxide 

21 COPD Chronic Obstructive Pulmonary Disease 

22 CPD Cardio-pulmonary Disease 

23 C-R Concentration-response 

24 CSA Consolidated Statistical Area 

25 CV Cardiovascular 

26 CVD Cardiovascular Disease 

27 df Degrees of freedom 

28 ED Emergency Department 

29 ER Emergency Room 

30 EPA United States Environmental Protection Agency 

31 FACA Federal Advisory Committee Act 

32 FIPS Federal Information Processing System 

33 GAM Generalized additive model 

34 GEOS-CHEM Goddard Earth Observing System-Chemical Model 

35 GLMs Generalized linear model 

36 HA Hospital Admissions 
September 2009 Draft – Do Not Quote or Cite x

1 HCUP Healthcare Cost and Utilization Project 

2 HEI Health Effects Institute 

3 HS High School 

4 ICD International Classification of Diseases 

5 IHD ischemic heart disease 

6 INF Influence of uncertainty on risk estimates 

7 IRP Integrated Review Plan 

8 ISA Integrated Science Assessment Document 

9 KB Knowledge Base 

10 km Kilometer 

11 K-S Kolmogorov-Smirnov 

12 LML Lowest Measured Level 

13 MCAPS Medicare Air Pollution Study 

14 MSA Metropolitan Statistical Area 

15 NA Not Applicable 

16 NAAQS National Ambient Air Quality Standards 

17 NCEA National Center for Environmental Assessment 

18 NEI National Emissions Inventory 

19 NCHS National Center for Health Statistics 

20 NMMAPS National Morbidity, Mortality, and Air Pollution Study 

21 NOx Nitrogen oxides 

22 O3 Ozone 

23 OAQPS Office of Air Quality Planning and Standards 

24 PA Policy Assessment Document 

25 PM Particulate Matter 

26 PMX The legal definition for PMX, as defined in the Code of Federal 

27 Regulations, includes both a 50% cut-point and a penetration 

28 curve. A 50% cut-point of X μm diameter means that 50% of 

29 particles with aerodynamic diameter of X are removed by the inlet 

30 and 50% pass through the inlet and are collected on the filter. 

31 Depending on the specific penetration curve specified, particles 

32 larger than X μm aerodynamic diameter are collected with an 

33 efficiently than decreases rapidly for particles larger than X while 

34 the collection efficiency for particles smaller than X increases 

35 rapidly with decreasing size until 100 % efficiency is reached. 

36 PM10 Particles with a 50% upper cut-point of 10± 0.5 μm aerodynamic 

37 diameter and a penetration curve as specified in the Code of 

38 Federal Regulations. 

39 
September 2009 Draft – Do Not Quote or Cite xi

1 PM2.5 Particles with a 50% upper cut-point of 2.5 μm aerodynamic 

2 diameter and a penetration curve as specified in the Code of 

3 Federal Regulations. 

4 PM10-2.5 Particles with a 50% upper cut-point of 10 μm aerodynamic 

5 diameter and a lower 50% cut-point of 2.5 μm aerodynamic 

6 diameter. 

7 PRB Policy-Relevant Background 

8 RA Risk Assessment Document 

9 RR Relative risk 

10 REA Risk and Exposure Assessment 

11 SAB Science Advisory Board 

12 SEDD State Emergency Department Databases 

13 SID State Inpatient Database 

14 SO2 Sulfur Dioxide 

15 SOx Sulfur Oxides 

16 SES Socio-economic Status 

17 TRIM Total Risk Integrated Methodology 

18 TRIM.Risk Total Risk Integrated Methodology - Risk Assessment component 

19 UFP Ultrafine Particles 

20 USDA U.S. Department of Agriculture 

21 VNA Voronoi Neighbor Averaging 

22 WHI Women's Health Initiative 

23 WHO World Health Organization 

24 ZCA Zip Code Area 
September 2009 Draft – Do Not Quote or Cite 1

1 

2 1 INTRODUCTION 

3 The U.S. Environmental Protection Agency (EPA) is presently conducting a review of 

4 the national ambient air quality standards (NAAQS) for particulate matter (PM). Sections 108 

5 and 109 of the Clean Air Act (Act) govern the establishment and periodic review of the NAAQS. 

6 These standards are established for pollutants that may reasonably be anticipated to endanger 

7 public health and welfare, and whose presence in the ambient air results from numerous or 

8 diverse mobile or stationary sources. The NAAQS are to be based on air quality criteria, which 

9 are to accurately reflect the latest scientific knowledge useful in indicating the kind and extent of 

10 identifiable effects on public health or welfare that may be expected from the presence of the 

11 pollutant in ambient air. The EPA Administrator is to promulgate and periodically review, at 

12 five-year intervals, “primary” (health-based) and “secondary” (welfare-based) NAAQS for such 

13 pollutants. Based on periodic reviews of the air quality criteria and standards, the Administrator 

14 is to make revisions in the criteria and standards, and promulgate any new standards, as may be 

15 appropriate. The Act also requires that an independent scientific review committee advise the 

16 Administrator as part of this NAAQS review process, a function performed by the Clean Air 

Scientific Advisory Committee (CASAC).1 17 

18 The current NAAQS for PM include a suite of standards to provide protection for 

19 exposures to fine and coarse particles using PM2.5 and PM10, as indicators, respectively (71 FR 

20 61144, October 17, 2006). With regard to the primary and secondary standards for fine particles, 

in 2006 EPA revised the level of the 24-hour PM2.5 standard to 35 μg/m3 21 (calculated as a 3-year 

average of the 98th 22 percentile of 24-hour concentrations at each population-oriented monitor), 

retained the level of the annual PM2.5 annual standard at 15 μg/m3 23 (calculated as the 3-year 

24 average of the weighted annual mean PM2.5 concentrations from single or multiple community25 oriented monitors), and revised the form of the annual PM2.5 standard by narrowing the 

constraints on the optional use of spatial averaging.2 26 With regard to the primary and secondary 

 1

 The Clean Air Scientific Advisory Committee (CASAC) was established under section 109(d)(2) of the Clean Air 

Act (CAA or Act) (42 U.S.C. 7409) as an independent scientific advisory committee. CASAC provides advice, 

information and recommendations on the scientific and technical aspects of air quality criteria and NAAQS under 

sections 108 and 109 of the CAA. The CASAC is a Federal advisory committee chartered under the Federal 

Advisory Committee Act (FACA). See 

http://yosemite.epa.gov/sab/sabpeople.nsf/WebCommitteesSubcommittees/CASAC%20Particulate%20Matter%20R

eview%20Panel for a list of the CASAC PM Panel members and current advisory activities. 

2 In the revisions to the PM NAAQS finalized in 2006, EPA tightened the constraints on the spatial averaging 

criteria by further limiting the conditions under which some areas may average measurements from multiple 

community-oriented monitors to determine compliance (see 71 FR 61165-61167, October 17, 2006) . 
September 2009 Draft – Do Not Quote or Cite 2

standards for PM10, EPA retained the 24-hour PM10 standard at 150 μg/m3 1 (not to be exceeded 

2 more than once per year on average over 3 years) and revoked the annual standard because 

3 available evidence generally did not suggest a link between long-term exposure to current 

4 ambient levels of coarse particles and health or welfare effects. These standards were based 

5 primarily on a large body of epidemiological evidence relating ambient PM concentrations to 

6 various adverse health endpoints. Secondary standards for PM2.5 and PM10 were revised to be 

7 identical to the primary standards. 

The next periodic review of the PM NAAQS is now underway.3 8 The EPA outlined the 

9 science-policy questions that will frame this review, outlined the process and schedule that the 

10 review will follow, and provided more complete descriptions of the purpose, contents, and 

11 approach for developing the key documents for this review in the Integrated Review Plan for the 

12 National Ambient Air Quality Standards for Particulate Matter, henceforth referred as the IRP 

(EPA, 2008a).4 13 The EPA is currently completing the process of assessing the latest available 

14 policy-relevant scientific information to inform the review of the PM standards. The latest draft 

15 of this assessment is contained in the Integrated Science Assessment for Particulate Matter: 

16 Second External Review Draft, henceforth referred to as the draft ISA (EPA, 2009a) which was 

17 released in July 2009 for review by the CASAC and for public comment. The draft ISA includes 

18 an evaluation of the scientific evidence on the health effects of PM, including information on 

19 exposure, physiological mechanisms by which PM might damage human health, and an 

20 evaluation of the epidemiological evidence including information on reported concentration21 response (C-R) relationships and lag structures for PM-related morbidity and mortality 

22 associations, including consideration of effects in at-risk populations.. 

23 Drawing from the health effects evidence presented in the draft ISA as well as CASAC 

24 advice (Samet, 2009) and public comments on a Particulate Matter National Ambient Air 

25 Quality Standards: Scope and Methods Plan for Health Risk and Exposure Assessment, 

26 henceforth referred to as the Scope and Methods Plan (EPA, 2009b), EPA’s Office of Air 

27 Quality Planning and Standards (OAQPS) has developed this draft Risk Assessment (RA) 

28 describing the quantitative assessments being conducted by the Agency to support the review of 

29 the primary PM standards. This draft document is a concise presentation of the scope, methods, 

30 key results, observations, and related uncertainties associated with the quantitative analyses 

 3

 See http://www.epa.gov/ttn/naaqs/standards/pm/s_pm_index.html for more information on the current and 

previous PM NAAQS reviews. 

4

 On November 30, 2007, EPA held a consultation with the CASAC on the draft IRP (72 FR 63177, November 8, 

2007). Public comments were also requested on the draft plan and presented at that CASAC teleconference. The 

final IRP incorporated comments received from CASAC and the general public on the draft plan as well as input 

from senior Agency managers. 
September 2009 Draft – Do Not Quote or Cite 3

1 performed. Revisions to this draft RA will draw upon the final ISA and will reflect 

2 consideration of CASAC and public comments on this draft. 

3 The final ISA and final RA will inform the policy assessment and rulemaking steps that 

4 will lead to final decisions on the primary PM NAAQS. A Policy Assessment (PA) is now being 

5 prepared by OAQPS staff to provide a transparent staff analysis of the scientific basis for 

6 alternative policy options for consideration by senior EPA management prior to rulemaking. The 

7 PA is intended to help “bridge the gap” between the Agency’s scientific assessments, presented 

8 in the ISA and RA, and the judgments required of the Administrator in determining whether it is 

9 appropriate to retain or revise the standards. The PA will integrate and interpret information 

10 from the ISA and the RA to frame policy options and to facilitate CASAC’s advice to the 

11 Agency and recommendations on any new standards or revisions to existing standards as may be 

12 appropriate, as provided for in the Clean Air Act. A preliminary draft PA is planned for release 

13 in September 2009 to facilitate discussion on the overall structure, areas of focus, and level of 

14 detail to be included in an external review draft of the document, which EPA plans to release for 

15 CASAC review and public comment later this year. A discussion of the preliminary draft PA 

16 with CASAC will be held in conjunction with CASAC review and public comment of the draft 

17 ISA, this draft RA, and a draft assessment document that will inform the review of the secondary 

18 PM standards - Particulate Matter Urban-Focused Visibility Assessment – External Review 

19 Draft (EPA, 2009c). 

20 1.1 BACKGROUND 

21 As part of the last PM NAAQS review completed in 2006, EPA’s OAQPS conducted a 

22 quantitative risk assessment to estimate risks of various health effects associated with exposure 

23 to ambient PM2.5 and PM10-2.5 in a number of urban study areas selected to illustrate the public 

24 health impacts of these pollutants (U.S. EPA, 2005, Chapter 4; Abt Associates, 2005). The 

25 assessment scope and methodology were developed with considerable input from the CASAC 

26 Review Panel and the public, with CASAC concluding that the general assessment methodology 

27 and framework were appropriate (Hopke, 2002). In addition, the final risk assessment took into 

28 consideration CASAC advice (Hopke, 2004; Henderson, 2005) and public comments on two 

29 drafts of the risk assessment. 

30 The extensive assessment conducted for fine particles in the last review included 

31 estimates of risks of mortality (total non-accidental, cardiovascular, and respiratory), morbidity 

32 (hospital admissions for cardiovascular and respiratory causes), and respiratory symptoms (not 

33 requiring hospitalization) associated with recent short-term (daily) ambient PM2.5 levels and risks 

34 of total, cardiopulmonary, and lung cancer mortality associated with long-term exposure to PM2.5 

35 in nine urban study areas. The risk assessment included estimates of: (1) risks of mortality, 
September 2009 Draft – Do Not Quote or Cite 4

1 morbidity, and symptoms associated with recent ambient PM2.5 levels; (2) risk reductions and 

2 remaining risks associated with just meeting the existing suite of PM2.5 NAAQS (1997 

3 standards); and (3) risk reductions and remaining risks associated with just meeting various 

4 alternative PM2.5 standards. 

5 The quantitative risk assessment conducted in the last review for thoracic coarse particles 

6 was much more limited than the analyses conducted for fine particles. Estimates of hospital 

7 admissions attributable to short-term exposure to PM10-2.5 were developed for Detroit 

8 (cardiovascular and respiratory admissions) and Seattle (respiratory admissions), and estimates 

9 of respiratory symptoms were developed for St. Louis. While one of the goals of the PM10-2.5 

10 risk assessment was to provide estimates of the risk reductions associated with just meeting 

11 alternative PM10-2.5 standards, EPA staff concluded that the nature and magnitude of the 

12 uncertainties and concerns associated with this portion of the risk assessment weighed against 

13 use of these risk estimates as a basis for recommending specific standard levels (U.S. EPA, 2005, 

14 p. 5-69). 

15 Prior to the issuance of a proposed rulemaking in the last review, CASAC presented 

16 recommendations to the Administrator supporting revisions of the PM2.5 primary standards. 

17 These recommendations placed substantial reliance on the results of the quantitative risk 

18 assessment (Henderson, 2005, pp 6-7). In a letter to the Administrator following the 2006 

19 proposed rule (71 FR 12592, January 17, 2006), CASAC requested reconsideration of the 

20 Agency’s proposed decisions and reiterated and elaborated on the scientific bases for its earlier 

21 recommendations which included placing greater weight on the result of the Agency’s risk 

22 assessment. With regard to the quantitative risk assessment, CASAC concluded, “While the risk 

23 assessment is subject to uncertainties, most of the PM Panel found EPA’s risk assessment to be 

24 of sufficient quality to inform its recommendations.” (Henderson, 2006a, p. 3). 

25 In the 2006 final rule, the EPA Administrator recognized that the quantitative risk 

26 assessment for fine particles was based upon a more extensive body of data and was more 

27 comprehensive in scope than the previous assessment conducted for the review completed in 

28 1997. However, as presented in the final rulemaking notice, the Administrator was mindful of 

29 significant uncertainties associated with the risk estimates for fine particles. More specifically, 

30 

31 Such uncertainties generally related to a lack of clear understanding of a number of 

32 important factors, including, for example, the shape of the concentration-response 

33 functions, particularly when, as here, effect thresholds can neither be discerned nor 

34 determined not to exist; issues related to selection of appropriate statistical models for the 

35 analysis of the epidemiologic data; the role of potentially confounding and modifying 

36 factors in the concentration-response relationships; issues related to simulating how PM2.5 

37 air quality distributions will likely change in any given area upon attaining a particular 

38 standard, since strategies to reduce emissions are not yet defined; and whether there 
September 2009 Draft – Do Not Quote or Cite 5

1 would be differential reductions in the many components within PM2.5 and, if so, whether 

2 this would result in differential reductions in risk. In the case of fine particles, the 

3 Administrator recognized that for purposes of developing quantitative risk estimates, 

4 such uncertainties are likely to [be] amplified by the complexity in the composition of the 

5 mix of fine particles generally present in the ambient air. (72 FR 61168, October 17, 

6 2006). 

7 

8 As a result, the Administrator viewed that the quantitative risk assessment provided supporting 

9 evidence for the conclusion that there was a need to revise the PM2.5 primary standards, but he 

10 judged that the assessment did not provide an appropriate basis to determine the level of the 

11 standards (72 FR 61168, October 17, 2006). 

12 In a letter to the EPA Administrator following the issuance of the final rule, CASAC 

13 expressed “serious scientific concerns” regarding the final PM standards. In particular, CASAC 

14 was concerned that the Agency “did not accept our finding that the annual PM2.5 standard was 

15 not protective of human health and did not follow our recommendation for a change in that 

16 standard” (Henderson et al, 2006b, p.1). With respect to the use of the risk assessment to inform 

17 EPA’s decision on the primary PM2.5 standard, CASAC stated, “While there is uncertainty 

18 associated with the risk assessment for the PM2.5 standard, this very uncertainty suggests a need 

19 for a prudent approach to providing an adequate margin of safety” (Henderson et al., 2006b, p.2) 

20 Several parties filed petitions for review following promulgation of the revised PM 

21 NAAQS in 2006. These petitions for review addressed the following issues with regard to the 

22 primary PM NAAQS: (1) selecting the level of the annual primary PM2.5 standard, (2) retaining 

23 PM10 as the indicator for coarse particles and retaining the level and form of the 24-hour PM10

24 standard, and (3) revoking the PM10 annual standard. On judicial review, the D.C. Circuit 

25 remanded the annual primary PM2.5 NAAQS to EPA because the Agency failed to adequately 

26 explain why the standard provided the requisite protection from both short- and long-term 

27 exposures to fine particles including protection for at-risk populations. The court upheld the 

28 Agency’s use of the quantitative risk assessment to inform the decision to revise the PM2.5 

standards but not to inform the selection of level.5 29 The court also upheld the decision to retain 

30 the 24-hour PM10 standard and revoke the annual PM10 standard. American Farm Bureau 

31 Federation v. EPA, 559 F. 3d 512, (D.C. Cir. 2009). 

32 

33 

 5

 One petition for review addressed the issue of setting the secondary PM2.5 standards identical to the primary 

standards. On judicial review, the court remanded the secondary PM2.5 NAAQS to EPA because the Agency failed 

to adequately explain why the standards provided the required protection from visibility impairment. American 

Farm Bureau Federation v. EPA, 559 F. 3d 512, (D.C. Cir. 2009). 
September 2009 Draft – Do Not Quote or Cite 6

1 1.2 CURRENT HEALTH RISK ASSESSMENT: GOALS AND PLANNED 

2 APPROACH 

3 The goals of the current risk assessment remain largely the same as those articulated in 

4 the risk assessment conducted as part of the last review. These goals include: (a) to provide 

5 estimates of the potential magnitude of premature mortality and/or selected morbidity effects in 

6 the population associated with recent ambient levels of PM and with just meeting the current 

7 suite of PM standards and any alternative standards that might be considered in selected urban 

8 study areas, including, where data are available, consideration of impacts on at-risk populations; 

9 (b) to develop a better understanding of the influence of various inputs and assumptions on the 

10 risk estimates to more clearly differentiate alternative standards that might be considered 

11 including potential impacts on various at-risk populations; and (c) to gain insights into the 

12 distribution of risks and patterns of risk reduction and uncertainties in those risk estimates. In 

13 addition, EPA is conducting an assessment to provide nationwide estimates of the potential 

14 magnitude of premature mortality associated with long-term exposure to ambient PM2.5 to more 

15 broadly characterize this risk on a national scale and to support the interpretation of the more 

16 detailed risk estimates generated for selected urban study areas. The overall scope and design of 

17 the risk assessment reflect efforts to achieve these goals. 

18 The current risk assessment builds on the approach used and lessons learned in the last 

19 PM NAAQS risk assessment and attempts to reduce overall uncertainty associated with the 

20 analysis through incorporation of a number of enhancements, in terms of both the methods and 

21 data used in the analyses. In preparing the Scope and Methods Plan for the health risk/exposure 

22 assessment, EPA considered the scientific evidence presented in the first draft ISA (EPA, 2008b) 

23 and the key science policy issues raised in the IRP (EPA, 2008a). The EPA held a consultation 

24 with CASAC to solicit comments on the Scope and Methods Plan during an April 2009 CASAC 

25 meeting. Public comments were also requested (74 FR 11580, March 18, 2009). CASAC 

26 (Samet, 2009) and public comments were considered in advance of the conduct of the analyses 

27 and results presented in this draft REA. The design of the current risk assessment builds upon 

28 information presented in the draft ISA (EPA, 2009b) with particular emphasis on conclusions 

29 regarding causality determinations for specific PM-related health effect categories and discussion 

30 of the scientific strengths and weaknesses underlying key epidemiological studies addressing 

31 specific health effect endpoints of interest. 

32 The risk assessment described in this draft document covers a variety of health endpoints 

33 for which there is adequate information to develop quantitative risk estimates. Evidence of 

34 relationships between PM and other health endpoints for which there currently is insufficient 

35 information to develop quantitative risk estimates will be discussed in the OAQPS staff Policy 

36 Assessment. 
September 2009 Draft – Do Not Quote or Cite 7

1 1.3 ORGANIZATION OF DOCUMENT 

2 The remainder of this document is organized as follows. Chapter 2 provides an overview 

3 of the scope of the risk assessment, including a summary of the previous risk assessment (section 

4 2.1), the planned approach as presented in the Scope and Methods Plan (section 2.2), a summary 

5 of CASAC comments on the Scope and Methods Plan (section 2.3) and how these comments as 

6 well as public comments were addressed in the design of the analyses (section 2.4), and 

7 summary of the alternative levels evaluated in the risk assessment including the rationale for 

8 their selection (section 2.5). Chapter 3 describes the analytical approach, methods, and data used 

9 in conducting the risk assessment. This includes a description of the approach used to generate 

10 risk estimates for the set of urban case studies included in this analysis, as well as the approaches 

11 used in addressing variability and uncertainty as part of the analysis (Appendices A, B, and C 

12 provide supplemental information regarding the data and methods used in the analysis). Chapter 

13 4 presents the risk estimates generated for the urban case studies, including key observations 

14 resulting from review and interpretation of the results (Appendices E and F provide detailed risk 

15 estimates and sensitivity analysis results, respectively). Chapter 5 presents the approach used 

16 and results of a national-scale assessment of PM2.5-related long-term mortality risks (Appendix G 

17 provides supplemental information to the national-scale mortality analysis). In addition, 

18 Appendix D provides supplemental information to a representativeness analysis completed for 

19 the 15 urban study areas (see Section 2.4.1). 
September 2009 Draft – Do Not Quote or Cite 8

1 2 SCOPE 

2 This chapter provides an overview of the scope and key design elements of the PM 

3 risk assessment being conducted for this review, including the process that has been followed 

4 to design the analyses. Following initiation of the current PM NAAQS review, we began the 

5 design of this risk assessment by reviewing the risk assessment completed during the previous 

6 PM NAAQS review (Abt Associates, 2005; EPA, 2005, chapter 4) with an emphasis on 

7 considering key limitations and sources of uncertainty recognized in that analysis. 

8 Furthermore, as an initial step in the overall PM NAAQS review, EPA invited a wide range of 

9 external experts as well as EPA staff, representing a variety of areas of expertise (e.g., 

10 epidemiology, human and animal toxicology, statistics, risk/exposure analysis, atmospheric 

11 science) to participate in a workshop titled, “Workshop to Discuss Policy-Relevant Science to 

12 Inform EPA’s Integrated Plan for the Review of the Primary PM NAAQS” (72 FR 34003, 

13 June 20, 2007). This workshop provided an opportunity for the participants to broadly 

14 discuss the key policy-relevant issues around which EPA would structure the PM NAAQS 

15 review and to discuss the most meaningful new science that would be available to inform our 

16 understanding of these issues. One session of this workshop was centered around planning 

17 for the quantitative risk/exposure assessments. Specifically, the discussions focused on the 

18 extent to which new research and/or improved methodologies were available to inform how 

19 EPA designed a quantitative risk assessment and whether it was appropriate to conduct a 

20 quantitative exposure assessment, and, if so, how that assessment might be structured. 

21 Based in part on these workshop discussions, EPA developed a draft IRP outlining 

22 the schedule, the process, and the key policy-relevant science issues that would guide the 

23 evaluation of the air quality criteria for PM and the review of the primary and secondary PM 

24 NAAQS including initial thoughts for conducting quantitative assessments (EPA, 2007, 

25 chapter 5). On November 30, 2007, CASAC held a teleconference with EPA to provide its 

26 comments on the draft IRP (72 FR 63177, November 8, 2007). Public comments were also 

27 presented at that teleconference. A final IRP incorporating comments received from CASAC 

28 and the general public on the draft plan was issued in March 2008 (EPA, 2008a). 

29 As a next step in the design of the quantitative assessments, EPA developed a planning 

30 document outlining the initial design for the PM NAAQS risk assessment - Particulate Matter 

31 National Ambient Air Quality Standards: Scope and Methods Plan for Health Risk and 

32 Exposure Assessment, henceforth Scope and Methods Plan (EPA, 2009b). This planning 

33 document was released for CASAC consultation and public review in February 2009. Based 

34 on consideration of CASAC and public comments on that Scope and Methods Plan, along 
September 2009 Draft – Do Not Quote or Cite 9

1 with ongoing review of the latest PM-related literature, we made modifications to the scope 

2 and design of the risk assessment and completed our initial analyses. 

3 In presenting the scope and key design elements of the current risk assessment, this 

4 chapter first provides a brief overview of the risk assessment completed for the previous PM 

5 NAAQS review in section 2.1, including key limitations and uncertainties associated with that 

6 analysis. Section 2.2 provides a summary of the initial design of the risk assessment as 

7 outlined in the Scope and Methods Plan. Next, section 2.3 summarizes comments received 

8 during the CASAC consultation on the Scope and Methods Plan. Key design elements for the 

9 current risk assessment, including modifications made to the overall scope of the assessments 

10 relative to the initial Scope and Methods Plan and explanations to support these changes are 

11 outlined in section 2.4. Finally, section 2.5 provides a summary of the alternative air quality 

12 scenarios modeled in the current assessment, including the rationale behind selection of 

13 specific alternative levels. 

14 2.1 OVERVIEW OF THE PM NAAQS RISK ASSESSMENT FROM THE 

15 LAST REVIEW 

16 The PM NAAQS risk assessment from the last review completed in 2006 included a 

17 broad assessment of PM2.5-related risk and a more limited treatment of PM10-2.5-related risk. 

18 The assessment conducted for the review completed in 2006 included estimates of risks of 

19 mortality (total non-accidental, cardiovascular, and respiratory), morbidity (hospital 

20 admissions for cardiovascular and respiratory causes), and respiratory symptoms (not 

21 requiring hospitalization) associated with recent short-term (daily) ambient PM2.5 levels and 

22 risks of total, cardiopulmonary, and lung cancer mortality associated with long-term exposure 

23 to PM2.5 in selected urban areas. Nine urban areas were included in this assessment to provide 

24 some sense of the variability in the PM2.5-related risk estimates across the U.S. The areas 

25 evaluated were: Boston, MA; Detroit, MI; Los Angeles, CA; Philadelphia, PA; Phoenix, AZ; 

26 Pittsburgh, PA; San Jose, CA; Seattle, WA; and St. Louis, MO. 

27 The EPA recognized that there were many sources of uncertainty and variability 

28 inherent in the inputs to this assessment and that there was a high degree of uncertainty in the 

29 resulting PM2.5 risk estimates. Such uncertainties generally related to a lack of clear 

30 understanding of a number of important factors, including, for example: (a) the shape of the 

31 concentration-response (C-R) function (and whether or not a population threshold exists); (b) 

32 issues related to the selection of appropriate statistical models for the analysis of 

33 epidemiological data; (c) the role of potentially confounding and modifying factors in the C-R 

34 relationships; (d) the method for simulating how daily PM2.5 ambient concentrations would 

35 likely change in any given area upon meeting a particular suite of standards, since strategies 

36 to reduce emissions had not yet been defined; and (e) the issue of whether there would be 
September 2009 Draft – Do Not Quote or Cite 10

1 differential reductions in the many components within PM2.5 and, if so, whether this would 

2 result in differential reductions in risk. 

3 While some of these uncertainties were addressed quantitatively in the form of 

4 estimated confidence ranges around central risk estimates, other uncertainties and the 

5 variability in key inputs were not reflected in these confidence ranges, but rather were 

6 addressed through separate sensitivity analyses or characterized qualitatively (EPA, 2005, 

7 chapter 4; Abt Associates, 2005). The C-R relationships used in the quantitative risk 

8 assessment were based on findings from human epidemiological studies that relied on fixed9 site, population oriented, ambient monitors as a surrogate for actual ambient PM2.5 exposures. 

10 The assessment included a series of base case estimates that, for example, included various 

11 cutpoints intended as surrogates for alternative potential population thresholds. Other 

12 uncertainties were addressed in various sensitivity analyses (e.g., the use of single- versus 

13 multi-pollutant models, use of single versus multi-city models, use of a distributed lag model) 

14 and had a more moderate and often variable impact on the risk estimates in some or all of the 

15 cities. 

16 The general overview and discussion of key components of the quantitative risk 

17 assessment used to develop risk estimates for PM2.5 presented above is also applicable to the 

18 risk assessment conducted for PM10-2.5 as part of the last review. However, the scope of the 

19 risk assessment for PM10-2.5 was much more limited than that for PM2.5 reflecting the much 

20 more limited body of epidemiological evidence and air quality information available for 

21 PM10-2.5. As discussed in section 4.5 of the Staff Paper (EPA, 2005), the PM10-2.5 risk 

22 assessment included risk estimates for just three urban areas for two categories of health 

23 endpoints related to short-term exposure to PM10-2.5: hospital admissions for cardiovascular 

24 and respiratory causes and respiratory symptoms (see also Abt, 2005, chapter 9). 

25 Estimates of hospital admissions attributable to short-term exposure to PM10-2.5 were 

26 developed for Detroit, MI (cardiovascular and respiratory admissions) and Seattle, WA 

27 (respiratory admissions), and estimates of respiratory symptoms were developed for St. Louis, 

28 MO. While one of the goals of the PM10-2.5 risk assessment was to provide estimates of the 

29 risk reductions associated with just meeting alternative PM10-2.5 standards, EPA staff 

30 concluded that the nature and magnitude of the uncertainties and concerns associated with this 

31 portion of the risk assessment weighed against use of these risk estimates as a basis for 

32 recommending specific standard levels (EPA, 2005, see p. 5-69). These uncertainties and 

33 concerns were summarized in the proposal notice (see FR 71 2662, January 17, 2006) and 

34 discussed more fully in the Staff Paper (EPA, 2005, chapter 4) and associated technical 

35 support document (Abt Associates, 2005). 

36 
September 2009 Draft – Do Not Quote or Cite 11

1 2.2 ORIGINAL ASSESSMENT PLAN 

2 As noted earlier, the Scope and Methods Plan reflected consideration of the design of 

3 the risk assessment completed for the last review (specifically the uncertainties and 

4 limitations associated with that assessment) as well as more recent PM-related research 

5 published since completion of the last assessment. The Scope and Methods Plan outlined a 

6 planned approach for conducting the current PM risk assessment, including broader design 

7 issues as well as more detailed aspects of the analyses. The Scope and Methods Plan also 

8 outlined plans for a population exposure analysis based on micro-environmental exposure 

9 modeling. The planned approaches for conducting both analyses are briefly summarized 

10 below. 

11 2.2.1 Risk assessment 

12 Key design elements for the risk assessment, as presented in the Scope and Methods 

Plan included:6 13 

14  PM size fractions: We planned to focus primarily on estimating risk associated 

15 with exposure to PM2.5 with a more limited assessment of PM10-2.5. Regarding PM 

16 components and ultrafine particles, we concluded that, based on review of 

17 evidence in the first draft ISA, there was insufficient data to support quantitative 

18 risk assessment at this time. 

19  Selection of health effects categories (PM2.5): We planned to focus on categories 

20 for which the evidence supports a judgment that there is at least a likely causal

21 relationship. However, consideration would be given to expanding the risk 

22 assessment to cover additional categories for which evidence supports a judgment 

23 that there is a suggestive causal relationship (e.g., reproductive, developmental 

24 outcomes), if sufficient information was available to develop risk estimates for 

25 these additional categories. 

26  Selection of health effect categories (PM10-2.5): We planned to build on the 

27 limited risk assessment conducted in the last review (EPA, 2005) with a focus on 

28 health effect categories that staff judged to be sufficiently suggestive of a causal 

29 relationship with short-term exposure to warrant analysis. 

30  Selection of study areas: We planned to expand the number of urban study areas 

31 to between 15 and 20, with selection of these study areas being based on 

32 consideration of a number of factors (e.g., availability of location-specific C-R 

33 functions and baseline incidence data, coverage for geographic heterogeneity in 

34 PM risk-related attributes, coverage for areas with more vulnerable populations). 

35 We also discussed the possibility of including more refined risk assessments for 

36 locations where more detailed exposure studies had been completed (e.g., L.A., 

 6

 We have focused here on highlighting design details that have broader implications for the risk assessment and 

have not included some of the more detailed aspects of the planned approach. These more detailed factors were 

carefully considered in conducting the risk assessment described in this document, but they are not discussed as 

part of this discussion focusing on the overall scope of the analysis. 
September 2009 Draft – Do Not Quote or Cite 12

1 where a zip code level analysis of long-term PM2.-exposure related mortality was 

2 presented in Krewski et al., 2009). 

3  Simulation of air quality levels that just meet either current or alternative 

4 suites of standards: We planned to consider the use of non-proportional air 

5 quality adjustment methods, together with the proportional approach that has been 

6 used previously. These non-proportional adjustment methods could be based on 

7 (a) historical patterns of reductions in urban areas, if these result in support for 

8 non-proportional reductions across monitors and/or (b) model-based (e.g., CMAQ) 

9 rollback designed to more realistically reflect patterns of PM reductions across 

10 monitors in an urban area. 

11  Characterization of policy relevant background (PRB): We planned to use 

12 modeling (combination of the global-scale circulation model, GEOS-Chem, with 

13 the regional scale air quality model, CMAQ) as presented in the first draft PM 

14 ISA, rather than empirical data to characterize PRB levels for use in the risk 

15 assessment model. 

16  Selection of epidemiological studies to provide C-R functions: We planned to 

17 include both multi- and single-city studies (given advantages associated with both 

18 designs) as well as multi- and single-pollutant studies. However, we also proposed 

19 placing greater weight on the use of C-R functions reflecting adjusted single-city 

20 estimates obtained from multi-city studies. 

21  Shape of the functional form of the risk model: We planned to emphasize non22 threshold C-R functions in the risk assessment model, based on the first draft ISA 

23 conclusion that there was little support in the literature for population thresholds 

24 for mortality effects associated with either long-term or short-term PM2.5 ambient 

concentrations.7 25 However, we stated that we may consider population thresholds 

26 as part of the sensitivity analysis. 

27  Modeling of risk down to PRB versus Lowest Measured Level (LML): We 

28 planned to model risk down to LML for estimating risk associated with long-term 

29 PM2.5 exposures and down to PRB for estimated risks associated with short-term 

30 PM2.5 exposure effects. 

31  Characterization of uncertainty and variability: We planned to include a 

32 discussion in the risk assessment report on the degree to which the risk assessment 

33 covers key sources of variability related to PM risk. For uncertainty, we planned 

34 to include a qualitative discussion of key sources of uncertainty and provide 

35 ratings (low, medium and high) in terms of their potential impact on risk estimates. 

36 We also described the use of sensitivity analysis methods planned both to 

37 characterize the potential impact of sources of uncertainty on risk estimates and to 

38 provide an alternative set of reasonable estimates to supplement the main (“core”) 

39 set of risk estimates generated for the urban study areas. 

 7

 Note, that the draft ISA in discussing short-term exposure mortality studies while indicating support for nothreshold log-linear models, acknowledges the “possible influence of exposure error and heterogeneity of shapes 

across cities remains to be resolved” (draft ISA, section 6.5.2.7). 
September 2009 Draft – Do Not Quote or Cite 13

1  National-scale health impact analysis: We planned to conduct a national-scale 

2 health impact assessment focused on mortality associated with long-term exposure 

3 to PM2.5 using a recent conditions scenario. 

4  Representativeness analysis for the urban study areas: We planned to conduct 

5 an analysis to evaluate the representativeness of the selected urban study areas 

6 against national distributions for key PM risk-related attributes to determine 

7 whether they are nationally-representative, or more focused on a particular portion 

8 of the distribution for a given parameter. 

9 2.2.2 Population exposure analysis 

10 The Scope and Methods Plan also described a population exposure analysis based on 

11 micro-environmental exposure modeling using the Air Pollution Exposure Model (APEX). 

12 The planned analysis would have focused on PM2.5 and have involved a subset of the urban 

13 study areas included in the risk assessment. The results of this analysis were planned to focus 

14 on providing insights on population exposure with respect to informing the interpretation of 

15 available epidemiological studies. For reasons presented below in section 2.4.2, this analysis 

16 will not be completed as part of the current PM NAAQS review. We have decided to 

17 continue development of the population exposure analysis methodology with the goal of 

18 considering any results from this exposure assessment in support of the next PM NAAQS 

19 review. 

20 2.3 CASAC COMMENTS PROVIDED ON THE SCOPE AND METHODS 

21 PLAN 

22 CASAC met on April 2, 2009 to conduct a consultation on the Scope and Methods 

23 Plan for the PM NAAQS risk assessment. Following that meeting, CASAC provided 

24 comments from the Panel, summarized below, as well as more detailed comments providing 

individual views from CASAC PM Panel Members (Samet, 2009).8 25 

26  Regarding the overall analysis, CASAC suggested that “priorities be established 

27 quickly in developing the health risk and exposure assessment, giving emphasis to 

28 those analyses that may be most informative for establishing particulate matter 

29 standards.” 

30  With regard to the selection of health effects endpoints, CASAC recommended 

31 that EPA “provide a transparent algorithm for selecting endpoints based on the 

32 level of certainty and the relative and attributable risks.” Furthermore, CASAC 

33 suggested that “weight be given to the level of classification while still considering 

34 the Administrator’s obligation to set a standard with a ’margin of safety’ as 

35 described in the Clean Air Act.” By way of example, the letter stated that “several 

36 CASAC members do not recommend a risk assessment based on birth outcomes, 

 8

 See 

http://yosemite.epa.gov/sab/sabproduct.nsf/4620a620d0120f93852572410080d786/350899ec1345529485257466

00691de5!OpenDocument&TableRow=2.0#2. 
September 2009 Draft – Do Not Quote or Cite 14

1 in part because the level of evidence is still at the suggestive level.” The letter 

2 went on to note that “one panel member proposed setting a higher priority for 

3 those health effects shown to have the highest risks in the epidemiological 

4 literature.” (Samet, 2009, p.1-2). 

5  Regarding the inclusion of PM10-2.5 in the risk assessment, the letter stateed that 

6 “there was support (among CASAC members) for doing a limited risk assessment 

7 for short-term exposure to PM10-2.5 for appropriate outcomes such as 

8 hospitalization” (Samet, 2009, p.2). 

9  With regard to aspects of the plan related to air quality characterization, 

10 particularly characterizing policy relevant background (PRB) and simulation of 

11 ambient air levels associated with alternative standards, the letter stated that 

12 “CASAC generally supports EPA’s proposed approach for estimating PRB 

13 levels.” Furthermore, there was general support for the proportional rollback 

14 approach that EPA had followed in previous risk assessments. Individual 

15 comments did include support for considering a non-proportional rollback 

16 approach as an alternative to the proportional approach although several Panel 

17 members noted that there could be considerable uncertainty associated with the 

18 non-proportional approach. 

19  With regard to the risk assessment component, CASAC generally agreed with the 

20 planned approach to identifying C-R relationships. 

21  There was also strong support for the planned national scale health impact 

22 assessment for long-term exposure mortality related to PM2.5. In fact, CASAC 

23 stated that it believed such a national assessment “should play a central role in the 

24 overall risk assessment” (Samet, 2009, p.2). 

25  Regarding the characterization of uncertainty, CASAC expressed support for the 

26 general approach, but did emphasize the need to carefully separate sensitivity 

27 analyses from uncertainty analyses. With regard to the approach for classifying 

28 the degree of uncertainty, CASAC suggested that EPA explore the use of “various 

29 structured approaches for describing uncertainty,” noting that “recent examples 

30 may be found in the work of the World Health Organization and the 

31 Intergovernmental Panel on Climate Change” (Samet, 2009, p.2). 

32  Regarding the population exposure analysis, CASAC welcomed its inclusion 

33 noting that the planned analysis “rightly seeks to identify various personal and 

34 building-related factors that may account for some of the variability in PM2.5-

35 related health risks” (Samet, 2009, p.2). However, CASAC also noted that “more 

36 information is needed on how the results from the exposure assessment will be 

37 integrated and used to interpret epidemiological studies” (Samet, 2009, p.2). In 

38 pointing out potential benefits of the analysis, CASAC also acknowledged that the 

39 “Agency’s time and resources are not unlimited” (Samet, 2009, p.2). 

40 Comments from the CASAC PM Panel and individual Panel members were carefully 

41 considered in finalizing the scope and methods for the risk assessment described in this 

42 document. 
September 2009 Draft – Do Not Quote or Cite 15

1 2.4 CURRENT SCOPE AND KEY DESIGN ELEMENTS 

2 The current scope and design of the risk assessment is based on consideration of the 

3 following: (1) lessons learned from the risk assessment conducted for the previous review, as 

4 summarized in section 2.1 (see also EPA, 2005, chapter 4; Abt Associates, 2005); (2) 

5 consideration of CASAC’s advice on the Scope and Methods Plan, as described in section 

6 2.3; and (3) public comments on the Scope and Methods Plan; and consideration of the new 

7 scientific evidence presented in the second draft ISA (EPA, 2009a). These considerations 

8 also led to our decision to continue development of the population exposure analysis 

9 methodology, rather than applying it for this review. Key design elements of the risk 

10 assessment, as well as the rationale for the decision to continue development of the population 

11 exposure analysis for consideration in the next PM NAAQS review are presented below. 

12 2.4.1 Risk Assessment 

13 Key design elements, along with the rationale for any differences between the design 

14 of the risk assessment as implemented and the approach described in the Scope and Methods 

15 Plan, include: 

16  PM size fractions: The risk assessment characterizes risk associated with PM2.5-

17 related exposures only. Careful consideration of evidence provided in the draft 

18 ISA regarding health effects potentially associated with short-term exposure to 

19 PM10-2.5 as well as limited air quality data has resulted in the decision not to 

20 quantitatively assess risk for this size fraction as part of the current risk assessment 

21 (see section 3.3.1 for additional discussion). Furthermore, EPA staff have 

22 determined that data are too limited, at this time, to support a quantitative risk 

23 assessment for specific PM components, including ultrafine particles (UFPs). We 

24 note, however, that the evidence for health effects associated with thoracic coarse 

25 particles, UFPs, and PM components will be addressed as part of the evidence26 based analysis that will be presented in the forthcoming draft PA. 

27  Selection of health effects categories (PM2.5): The final set of health effects 

28 categories included in the risk assessment for PM2.5 (see section 3.3.1) are 

29 consistent with those outlined in the Scope and Methods plan for PM2.5 (i.e., those 

30 classified as having a causal or likely causal relationship with PM2.5 exposure, as 

31 presented in the draft ISA). However, we decided not to include any of the health 

32 effect categories classified as suggestive of a casual relationship in the draft ISA, 

33 based on a number of considerations including: (1) CASAC Panel member views, 

34 which did not express strong support for inclusion of these less-well supported 

35 health effect categories (see section 1.3); (2) limited information available to 

36 support selection of C-R functions for specific endpoints within these health effect 

37 categories; and/or (3) lack of available baseline incidence data for these other 

38 health effect endpoints. 

39  Selection of health effect categories (PM10-2.5): As noted above, we have decided 

40 not to model risk related to PM10-2.5 exposure (see section 3.3.1). 
September 2009 Draft – Do Not Quote or Cite 16

1  Selection of urban study areas: We have included 15 urban study areas in the 

2 risk assessment, with the selection of these areas being based on a number of 

3 criteria including: (a) consideration of urban study areas evaluated in the risk 

4 assessment conducted to inform the previous PM NAAQS review; (b) 

5 consideration of locations evaluated in key epidemiological studies; (c) preference 

6 for locations with relatively elevated 24-hour and/or annual PM2.5 monitored levels 

7 so that the assessment can provide potential insights into the degree of risk 

8 reduction associated with alternative standard levels and (d) desire to include 

9 locations that would provide coverage for different regions across the country 

10 where these regions are defined to reflect potential differences in PM sources, 

11 composition and potentially other factors which might impact PM-related risk ( see 

section 3.3.2).9 12 We note that, due to the time and resource limitations, we have 

13 not included a specialized analysis of risk based on epidemiology studies using 

14 more highly-refined exposure analysis (e.g., the study of L.A. involving zip code15 level effect estimates as presented in Krewski et al., 2009). However, we have 

16 included consideration of studies with more refined surrogate measures of 

17 exposure in our discussion of uncertainty related to long-term mortality, since they 

18 can inform our interpretation of the degree of potential bias associated with the 

19 effect estimates used to model risks (see section 3.5.3). 

20  Simulation of air quality levels that just meet either current or alternative 

21 standard levels: For this analysis, we used a proportional rollback approach as the 

22 basis for simulating current and alternative standard levels for the core risk 

estimates that were generated.10 23 However, as part of the sensitivity analysis, we 

24 also included application of a hybrid (non-proportional) adjustment procedure, 

25 which simulated a combination of regional and local controls (see section 3.2.3). 

26  Characterization of PRB: Consistent with the planned approach described in the 

27 Scope and Methods Plan, we used regional PRB estimates generated using a 

28 combination of GEOS-Chem and CMAQ modeling (these estimates were obtained 

29 directly from the assessments prepared for and summarized in the draft ISA – see 

30 section 3.2.2). 

31  Selection of epidemiological studies to provide C-R functions: In line with the 

32 planned approach outlined in the Scope and Methods Plan, in modeling risk 

33 associated with short-term PM2.5 exposures, we focused on two large multi-city 

34 studies based on our conclusion that these studies provided more defensible effect 

35 estimates (see section 3.3.1 for additional details). C-R functions selected from 

 9

 An error was identified in the approach used to simulate ambient PM2.5 levels just for the Pittsburgh study area 

for the scenarios involving just meeting the current and alternative sets of standards. This impacts risk estimates 

generated for these air quality scenarios, as well as sensitivity analysis results involving this urban study area. 

While we have removed discussion of these risk estimates (and sensitivity analysis results) form the body of this 

report, there was insufficient time after identifying this error to either generate corrected risk estimates or remove 

the erroneous risk estimates from the summary tables (presented in Appendix E and F). We will correct this 

error and release updated results for the Pittsburgh study area as soon as is practicable and will include the 

corrected results in the next version of this document. 

10 As described in section 3.1, the risk assessment includes a set of core risk estimates based on application of 

model inputs having the greatest support in the literature. The analysis also includes a reasonable alternative set 

of risk estimates generated as part of the sensitivity analysis, where these estimates, while not having as much 

support as the core risk results, are still based on inputs having a reasonable degree of support in the literature. 
September 2009 Draft – Do Not Quote or Cite 17

1 several single city studies were also included in our analysis to provide coverage 

2 for additional health effect endpoints associated with short-term PM2.5 exposures 

3 (e.g., emergency department visits). Modeling of long-term exposure-related 

4 mortality focused on the latest reanalysis of the ACS dataset (Krewski et al., 

5 2009). This study was published after the Scope and Methods Plan was the subject 

6 of a CASAC consultation and public review and, therefore, was not included in the 

7 preliminary set of studies under consideration (EPA, 2009b, Table 3-2). However, 

8 as discussed in section 3.3.3, use of this study is consistent with the planned 

9 approach presented in the Scope and Methods Plan and, extends and expands upon 

10 previous publications presenting evaluations of the ACS long-term cohort study. 

11  Characterization of uncertainty and variability: The approach for 

12 characterizing uncertainty and variability in the current risk assessment closely 

13 follows the planned approach as outlined in the Scope and Methods Plan. 

14 However, reflecting consideration of comments received from CASAC, we have 

15 considered: (a) the WHO Guidance on Characterizing and Communicating 

16 Uncertainty In Exposure Assessment (WHO, 2008) to ensure that our approach is 

17 consistent with the recommended step-wise process described in that document, 

18 and (b) the interpretation of the results of our sensitivity analysis and the most 

19 effective ways to communicate these results as a set of reasonable additional risk 

20 estimates that supplement the core estimates, recognizing that they do not 

21 represent a formal uncertainty distribution (see section 4.3). 

22  Representativeness analysis for the urban study areas: Consistent with the 

23 approach described in the Scope and Methods Plan, EPA staff have completed a 

24 representativeness analysis providing a comparison of the 15 urban study areas 

25 against national distributions for key PM risk-related attributes to evaluate whether 

26 they are more nationally-representative, or more representative of a particular 

27 portion of the distribution for a given parameter (see section 4.4). 

28  National-scale health impact analysis: Consistent with the approach described in 

29 the Scope and Methods Plan, a national-scale PM2.5-related long-term exposure 

30 mortality analysis, using recent air quality data for the continental U.S. has been 

31 completed (see chapter 5). 

32 2.4.2 Population exposure analysis 

33 Following release of the Scope and Methods Plan, we continued development of the 

34 approach for conducting a population exposure analysis, with the goal of completing the 

35 analysis as part of the current PM review. However, this additional design work further 

36 emphasized the need for clearly outlining the purpose of the analysis, including specific ways 

37 in which the results would be used to interpret the estimates generated from the risk 

38 assessment (e.g., potentially identifying sources of exposure measurement error associated 

39 with the epidemiological studies providing the C-R functions and the magnitude of the impact 

40 of those sources of error on risk estimates). When combined with consideration for CASAC 

41 comments on the Scope and Methods Plan which emphasized the same point regarding the 

42 importance of clearly outlining how the estimates from the analysis would be used, we 
September 2009 Draft – Do Not Quote or Cite 18

1 decided to continue methods development work, rather than attempt to complete a preliminary 

2 population exposure analysis as part of this review. Development of the population exposure 

3 analysis methodology is ongoing and we anticipate considering any results from this exposure 

4 assessment within the context of the next PM NAAQS review. 

5 2.5 ALTERNATIVE STANDARD LEVELS INCLUDED IN THE RISK 

6 ASSESSMENT 

7 As noted earlier, EPA staff has modified the scope of the risk assessment to focus on 

8 evaluating potential public health impacts of fine particles only and consequently 

9 consideration of alternative standards to be evaluated in the risk assessment were developed 

10 exclusively for PM2.5. Specifically, we selected alternative levels for the annual and 24-hour 

11 PM2.5 standards that we judged to be appropriate to evaluate in the context of this quantitative 

12 risk assessment. Alternative averaging times and forms were not considered in our analyses. 

13 The averaging times and forms used in evaluating alternative levels were those associated 

with the current 24-hour and annual standards.11 14 We note that all of the basic elements of the 

15 standards (e.g., indicator, averaging time, level, and form) will be discussed in a forthcoming 

16 draft Policy Assessment which will present staff conclusions based on both evidence-based 

17 and risk-based approaches to inform judgments that the EPA Administrator must make in 

18 deciding whether to retain or revise the existing PM standards. 

19 In selecting alternative levels for the annual and 24-hour PM2.5 standards for the 

20 purpose of inclusion in the quantitative risk assessment, we focused on the range of standard 

21 levels likely to be discussed in the draft PA. This range of alternative standard levels, in turn, 

22 reflects consideration of ambient air quality levels associated with health effects as reflected 

23 in key short- and long-term PM2.5 exposure epidemiological studies discussed in the draft 

24 ISA. 

25 As discussed further in section 3.3.3, in selecting alternative levels for consideration in 

26 the risk assessment, we placed emphasis on effect estimates reported in multi-city studies 

27 because these studies have a number of advantages compared to single-city studies including: 

28 (1) multi-city studies reflect ambient PM2.5 levels and potential health impacts across a range 

29 of diverse locations; (2) multi-city studies “clearly do not suffer from potential omission of 

30 negative analyses due to ‘publication bias’” (EPA, 2004a, p. 8-30); and (3) multi-city studies 

31 generally have higher statistical power. 

 11 The “form” of a standard defines the air quality statistic that is compared to the level of the standard in 

determining whether an area attains the standard. The form of the 24-hour PM2.5 standard is the 98th percentile of 

the distribution of 24-hour PM2.5 concentrations at each population-oriented monitor within an area, averaged 

over 3 years. The form of the annual PM2.5 standard is an annual arithmetic mean, averaged over 3 years, from 

single or multiple community-oriented monitors. 
September 2009 Draft – Do Not Quote or Cite 19

1 Specifically, regarding alternative levels for the annual PM2.5 standard to be evaluated 

2 in this risk assessment, we first considered long-term average PM2.5 concentrations associated 

3 with health effects observed in long-term epidemiological studies as summarized in Figure 2-

4 2 of the draft ISA. In general, the draft ISA concludes that the association between increased 

5 risk of mortality and long-term PM2.5 exposure “becomes more precise and consistently 

positive in locations with mean PM2.5 concentrations of 13.5 μg/m3 6 and above.” (EPA, 2009a, 

7 section 2.3.1.2). The draft ISA also concludes that the strongest evidence for cardiovascular8 related effects related to long-term PM2.5 exposures has been reported in large, multi-city 

9 U.S.-based studies and, specifically, one of these studies, the Women’s Health Initiative 

10 (WHI) Study, “reports associations between PM2.5 and cardiovascular effects among postmenopausal women using a 1-yr average PM2.5 concentration (mean = 13.5 μg/m3 11 )” (EPA, 

12 2009a, section 2.3.1.2). In addition, we evaluated long-term average PM2.5 concentrations in 

13 short-term exposure studies that reported statistically significant effects. More specifically, as 

14 reported in the draft ISA, both cardiovascular and respiratory morbidity effects (e.g., 

15 emergency department visits, hospital admissions) have been observed and become “more 

precise and consistently positive in locations with mean PM2.5 concentrations of 13 μg/m3 16 and 

above” (EPA, 2009a, section 2.3.1; also see Figure 2-1).12 17 

18 Based on the available epidemiological evidence indicating effects associated with a 

19 range of annual averaged PM2.5 concentrations, as briefly described above, we selected levels 

of 12 and 13 μg/m3 20 as the alternative annual standard levels to be evaluated in the quantitative 

21 risk assessment. 

22 In identifying alternative levels for the 24-hour PM2.5 standard to be evaluated in this 

23 risk assessment, we considered the ambient PM2.5 levels associated with mortality and 

24 morbidity effects as reported in key short-term epidemiological studies. We focused on the 

98th 25 percentile PM2.5 ambient levels reported in two multi-city studies that provided C-R 

26 functions used in the core risk assessment, Zanobetti and Schwartz (2009) and Bell et al. 

(2008). The focus on the 98th 27 percentile of the 24-hour PM2.5 concentrations observed in the 

28 epidemiological studies is consistent with the approach used in the prior PM NAAQS review 

29 and is consistent with the current form of the 24-hour PM2.5 standard. 

The draft ISA presents 98th 30 percentile 24-hour PM2.5 values for each of the 112 urban 

31 areas included in the Zanobetti and Schwartz (2009) short-term mortality study (EPA, 2009a, 

Figure 6-22). We evaluated the trend in these county-level 98th 32 percentile 24-hour PM2.5

 12 We note that the association between long-term mean ambient PM2.5 levels and statistically-significant health 

effects reported in short-term exposure studies would be dependent on the specific relationship between day-today variation in the 24-hour PM2.5 levels (in the underlying study counties) and the associated long-term mean 

PM2.5 levels (i.e., the association between mean PM2.5 levels and short-term health effects, would not hold for 

counties with notably different relationships between short-term day-to-day variation and longer-term mean 

PM2.5 levels). 
September 2009 Draft – Do Not Quote or Cite 20

1 levels in conjunction with the statistical significance of the associated county-level effect 

2 estimates. If we had found an association between the air quality levels and statistically 

significant effect estimates (i.e., higher 98th 3 percentile PM2.5 levels were consistently 

4 associated with statistically significant effect estimates), then it would have been reasonable 

to consider the lowest 98th 5 percentile PM2.5 level associated with the set of counties for which 

6 a statistically significant effect estimates was observed as the basis for selecting an alternative 

7 standard level for evaluation in this risk assessment. However, no such association was 

observed. Rather, we observed mixed results with no clear correlation between 98th 8 percentile 

9 air quality levels and statistically significant effect estimates. Therefore, we focused on the 

overall range of 98th 10 percentile values across the entire set of counties and considered the 

11 lower quartile of that distribution as representative of a reasonably cautious approach for 

identifying alternative levels for consideration in the risk assessment. The 10th and 25th 12 

percentiles values were 25.5 and 29.8 μg/m3 13 , respectively (Zanobetti, 2009). We note that the 

overall 98th 14 percentile value across the entire set of urban areas analyzed in Zanobetti and 

Schwartz. (2009) was 34.3 μg/m3 15 (EPA, 2009a, Figure 2-1; Zanobetti and Schwartz, 2009) 

16 Next, we completed a similar analysis of the county-level ambient air quality data 

17 (Bell, 2009) for the 202 counties associated with the Bell et al. (2008) study. Analysis of the 

overall distribution of 98th 18 percentile values across the entire dataset resulted in identifying 

10th and 25th percentile values of about 24.4 and 29.3 μg/m3 19 , respectively. We note that the 

overall 98th 20 percentile value across the entire set of counties analyzed in Bell et al. (2008)) 

was 34.2 μg/m3 21 (EPA, 2009a, Table 6-11; Bell, 2009). 

22 Based on the available epidemiological evidence indicating effects associated with a 

range of 98th 23 percentile 24-hour PM2.5 concentrations, as briefly described above, we selected 

levels of 25 and 30 μg/m3 24 as the alternative 24-hour standard levels to be evaluated in this 

25 quantitative risk assessment. 

26 Once alternative levels were identified for the annual and 24-hour PM standards, the 

27 next step was to identify specific combinations of these standard levels to be considered in the 

28 risk assessment. In selecting the pairing of annual and 24-hour standard levels, we considered 

29 which standard was predicted to be controlling across the set of 15 urban study areas (either 

30 the annual or 24-hour standard will be the “controlling standard” at a given location, 

depending on the design value associated with that location).13 31 Ultimately, for this risk 

32 assessment, the goal was to select combinations of annual and 24-hour levels that would result 

33 in a mixture of behavior in terms of which standards would control across the various urban 

study areas. For example, with the 12/35 combination, the annual level of 12 μg/m3 34 is the 

 13 The controlling standard is the standard which requires the greatest percentage reduction to get the design 

value monitor to meet that standard - see section 3.3.3 for additional detail on the issue of controlling standards. 
September 2009 Draft – Do Not Quote or Cite 21

1 controlling standard for all 15 urban study areas, while with the 12/25 combination, the 

2 annual standard is the controlling standard at some locations and the 24-hour standard is the 

3 controlling standard at other locations. Consideration of these factors resulted in a set of four 

4 alternative combinations of annual and 24-hour standards being identified for inclusion in the 

5 risk assessment. 

6 The full set of air quality scenarios included in the risk assessment, including the 

7 recent conditions air quality scenario and current standards scenario along with the four 

8 alternative sets of standards are as follows:

9  Recent conditions (risk estimates based on ambient PM2.5 monitoring data for the 

10 analysis period – 2005 to 2007) 

 Current PM2.5 NAAQS: annual 15 μg/m3; 24-hour 35 μg/m3 11 

 Alternative PM2.5 standards: annual 13 μg/m3; 24-hour 35 μg/m3 12 

 Alternative PM2.5 standards: annual 12 μg/m3

; 24-hour 35 μg/m3 13 

 Alternative PM2.5 standards: annual 13 μg/m3

; 24-hour 30 μg/m3 14 

 Alternative PM2.5 standards: annual 12 μg/m3

; 24-hour 25 μg/m3 15 
September 2009 Draft – Do Not Quote or Cite 22

1 3 METHODS USED IN URBAN CASE STUDY ANALYSIS 

2 This section provides an overview of the methods used in the risk assessment. Section 

3 3.1 discusses the basic structure of the risk assessment, identifying the modeling elements and 

4 related sources of input data needed for the analysis. Section 3.2 discusses air quality 

5 considerations. Section 3.3 discusses the selection of health endpoints, urban study areas and 

6 C-R functions from key epidemiological studies used in modeling those endpoints. Section 

7 3.4 discusses baseline health effects incidence rates. Finally, section 3.5 describes how 

8 uncertainty and variability are addressed in the risk assessment. 

9 3.1 GENERAL APPROACH 

10 3.1.1 Basic Structure of the Risk Assessment 

11 The general approach used in both the prior and the current PM risk assessment relies 

12 upon C-R functions which have been estimated in epidemiological studies. Since these 

13 studies estimate C-R functions using ambient air quality data from fixed-site, population14 oriented monitors, the appropriate application of these functions in a PM risk assessment 

15 similarly requires the use of ambient air quality data at fixed-site, population-oriented 

16 monitors. 

17 The general PM health risk model, illustrated in Figure 3-1, combines information 

18 about PM2.5 air quality for specific urban areas with C-R functions derived from 

19 epidemiological studies, baseline health incidence data for specific health endpoints, and 

20 population estimates to derive estimates of the annual incidence of specified health effects 

21 attributable to ambient PM2.5 concentrations under different air quality scenarios. The 

22 analyses were conducted for recent air quality and for air quality simulated to reflect 

23 attainment of current and alternative suites of PM2.5 ambient standards. 

24 The PM2.5 risk assessment was implemented within TRIM.Risk, the component of 

EPA’s Total Risk Integrated Methodology (TRIM) model that estimates human health risks.14 25 

26 In the first part of the risk assessment, we estimate health effects incidence associated with 

27 recent PM2.5 levels. In the second part, we estimate the reduced health effects incidence 

28 associated with those PM2.5 concentrations that would result if the current or alternative PM2.5 

29 standards were just met in the assessment locations, as well as the percent reductions in 

30 incidence from incidence under the current suite of standards. Both parts of the risk 

31 assessment consider only the incidence of health effects associated with PM2.5 concentrations 

32 in excess of either policy-relevant background (PRB) for evaluating effects associated with 

 14 For more detailed information about TRIM.Risk, go to: http://www.epa.gov/ttn/fera/trim_risk.html 
September 2009 Draft – Do Not Quote or Cite 23

1 short-term PM2.5 concentrations or the lowest measured level (LML) for evaluating effects 

2 associated with long-term PM2.5 concentrations. 

3 Consistent with past risk assessments for NAAQS reviews, the risk assessment is 

4 intended to estimate risks attributable to anthropogenic sources and activities, and thus risks 

5 are only estimated for concentrations in excess of PRB levels. For all health endpoints 

6 associated with short-term exposure to PM2.5, the risk assessment considers only the incidence 

7 of health effects associated with PM2.5 concentrations in excess of PRB levels. In the studies 

8 estimating a relationship between mortality and long-term exposure to PM2.5, however, the 

9 LMLs in the studies were substantially above PRB. Thus, estimating risk down to PRB 

10 would have required substantial extrapolation of the estimated C-R functions below the range 

11 of the data on which they were estimated. We therefore estimated risk only down to the LML 

12 to avoid extrapolating the estimated C-R functions too far below the range of the PM2.5 data 

13 on which they were estimated. To provide consistency across the long-term exposure C-R 

14 functions, however, and, in particular, to avoid the choice of LML unduly influencing the 

results of the risk assessment, we selected a single LML – 5.8 μg/m3 15 from the later exposure 

16 period used in Krewski et al. (2009) – to be used in all cases involving long-term exposure. 

17 
September 2009 Draft – Do Not 

24

Figure 3-1. Major components of particulate matter health risk assessment. 
September 2009 Draft – Do Not Quote or Cite 25

For each health effect that has been associated with PM2.5, the risk assessment may be 

viewed as assessing the incidence of the health effect associated with PM2.5 concentrations 

under a given air quality scenario (e.g., a scenario in which PM2.5 concentrations just meet a 

specified set of standards) above PRB or the LML . Equivalently, the risk assessment may be 

viewed as assessing the change in incidence of each health effect associated with a change in 

PM2.5 concentrations from some upper levels (e.g., PM2.5 concentrations that just meet a 

specified set of standards) to specified lower levels (PRB levels or the LML). 

 To estimate the change in incidence of a given health effect resulting from a given 

change in ambient PM2.5 concentrations in an assessment location, the following analysis 

inputs are necessary: 

 Air quality information including: (1) PM2.5 air quality data from one or more 

recent years from population-oriented monitors in the assessment location, (2) 

estimates of PM2.5 PRB concentrations appropriate to this location, and (3) a method 

for adjusting the air quality data to reflect patterns of air quality change estimated to 

occur when the area just meets the specified standards. (These air quality inputs are 

discussed in more detail in section 3.2). 

 C-R function(s) which provide an estimate of the relationship between the health 

endpoint of interest and PM2.5 concentrations (preferably derived in the assessment 

location, although functions estimated in other locations can be used at the cost of 

increased uncertainty -- see section 3.5.3). For PM2.5, C-R functions are available 

from epidemiological studies that assessed PM2.5-related health effects associated with 

either short- or long-term exposures. (Section 3.1.2 describes the role of C-R 

functions in estimating health risks associated with PM2.5). 

 Baseline health effects incidence rate and population. The baseline incidence rate 

provides an estimate of the incidence rate (number of cases of the health effect per 

year, usually per 10,000 or 100,000 general population) in the assessment location 

corresponding to recent ambient PM2.5 levels in that location. To derive the total 

baseline incidence per year, this rate must be multiplied by the corresponding 

population number (e.g., if the baseline incidence rate is number of cases per year per 

100,000 population, it must be multiplied by the number of 100,000s in the 

population). (Section 3.4 summarizes considerations related to the baseline incidence 

rate and population data inputs to the risk assessment). 

 As noted below (in section 3.2.1), the risk assessment was carried out using three 

years of recent air quality data –2005, 2006, and 2007. We matched the population data used 

in the risk assessment to the year of the air quality data. For example, when we used 2005 air 

quality data, we used 2005 population estimates. Because it was not possible to obtain the 

necessary data to calculate baseline incidence rates separately for each of the three years for 

each of the risk assessment locations, we calculated these rates for a single year, under the 

assumption that these rates are unlikely to have changed significantly from 2005 to 2007. The 

calculation of baseline incidence rates is described in detail in section 3.4. 
September 2009 Draft – Do Not Quote or Cite 26

 The risk assessment procedures described in more detail below are diagramed in 

Figure 3-2 for analyses based on short-term exposure studies and in Figure 3-3 for analyses 

based on long-term exposure studies. 

For this risk assessment, we have developed a core (primary) set of risk results based 

on the application of modeling element choices (e.g., C-R functions, lag periods) that we 

believe have the greatest overall support in the literature (hereafter referred to as the “core” 

results). While it is not possible at this time to assign quantitative levels of confidence to 

these core risk estimates, EPA does believe that these estimates are generally based on inputs 

having higher overall levels of confidence, relative to risk estimates that could have been 

generated using other inputs identified in the literature. In addition, as discussed above in 

section 2.1 and later in section 3.5, we have also used single-element and multi-element 

sensitivity analysis techniques to generate a set of reasonable alternative risk estimates based 

on the application of alternative modeling element choices that, while not having as much 

support in the literature as those used in the core analysis, do still represent plausible inputs. 

The results of these sensitivity analyses allow us to gain insights into which sources of 

uncertainty may have the greatest impact on risk estimates when acting alone, or in 

combination with other sources of uncertainty. In addition, the sensitivity analysis-based risk 

estimates also provide us with an additional set of reasonable risk results that allow us to 

place the results of the core analysis in context with regard to uncertainty. The potential 

utility of the sensitivity analysis-based risk estimates in informing consideration of 

uncertainty in the core results is discussed in section 4.5.2. A number of modeling elements 

are used in differentiating core analyses from sensitivity analyses (e.g., C-R function shape, 

alternative effect estimates, alternative lag structures, different methods used to rollback air 

quality to simulate attainment to current or alternative standard levels, application of PRB 

versus LML). Specific choices made in relation to individual modeling elements in 

differentiating the core analysis from sensitivity analyses are described, as appropriate, in the 

sections that follow, which cover specific aspects of the risk assessment design.
September 2009 Draft – Do Not 

27

Figure 3-2. Flow diagram of risk assessment for short-term exposure studies. 
September 2009 Draft – Do Not 

28

Figure 3-3. Flow diagram of risk assessment for long-term exposure studies. 
September 2009 Draft – Do Not Quote or Cite 29

1 3.1.2 Calculating PM-Related Health Effects Incidence 

2 3.1.2.1 General approach 

3 The C-R functions used in the risk assessment are empirically estimated relations 

4 between average ambient concentrations of PM2.5 and the health endpoints of interest (e.g., 

5 mortality or hospital admissions associated with short- and long-term exposure to PM2.5) 

6 reported by epidemiological studies for specific locations. This section describes the basic 

7 method used to estimate changes in the incidence of a health endpoint associated with 

8 changes in PM, using a “generic” C-R function of the most common functional form. 

9 Although some epidemiological studies have estimated linear C-R functions and some 

10 have estimated logistic functions, most of the studies used a method referred to as “Poisson 

11 regression” to estimate exponential (or log-linear) C-R functions in which the natural 

12 logarithm of the health endpoint is a linear function of PM2.5: 

13 

 x Bey  14  (1) 

15 

16 where x is the ambient PM2.5 level, y is the incidence of the health endpoint of interest 

17 at PM2.5 level x, β is the coefficient of ambient PM2.5 concentration, and B is the incidence at 

18 x=0, i.e., when there is no ambient PM2.5. The relationship between a specified ambient PM2.5

19 level, x0, for example, and the incidence of a given health endpoint associated with that level 

20 (denoted as y0) is then 

21 

 0

0

x Bey  22  . (2) 

23 

24 Because the log-linear form of a C-R function (equation (1)) is by far the most 

25 common form, we use this form to illustrate the “health impact function” used in the PM2.5

26 risk assessment. 

27 If we let x0 denote the baseline (upper) PM2.5 level, and x1 denote the lower PM2.5 

28 level, and y0 and y1 denote the corresponding incidences of the health effect, we can derive the 

29 following relationship between the change in x, Δx= (x0- x1), and the corresponding change in 

y, Δy, from equation (1)15 30 : 

31 

  

yyy y e x    ( ) [ ]. 01 0 1  32 (3) 

 15 If Δx < 0 – i.e., if Δx = (x1- x0) – then the relationship between Δx and Δy can be shown to be 

]1[)( 001  x eyyyy  . If Δx < 0, Δy will similarly be negative. However, the magnitude of Δy will be 

the same whether Δx > 0 or Δx < 0 – i.e., the absolute value of Δy does not depend on which equation is used. 
September 2009 Draft – Do Not Quote or Cite 30

1 Alternatively, the difference in health effects incidence can be calculated indirectly 

2 using relative risk. Relative risk (RR) is a measure commonly used by epidemiologists to 

3 characterize the comparative health effects associated with a particular air quality comparison. 

4 The risk of mortality at ambient PM2.5 level x0 relative to the risk of mortality at ambient 

5 PM2.5 level x1, for example, may be characterized by the ratio of the two mortality rates: the 

6 mortality rate among individuals when the ambient PM2.5 level is x0 and the mortality rate 

7 among (otherwise identical) individuals when the ambient PM2.5 level is x1. This is the RR for 

8 mortality associated with the difference between the two ambient PM2.5 levels, x0 and x1. 

9 Given a C-R function of the form shown in equation (1) and a particular difference in ambient 

10 PM2.5 levels, Δx, the RR associated with that difference in ambient PM2.5, denoted as RRΔx, is 

equal to eβΔx 11 . The difference in health effects incidence, Δy, corresponding to a given 

12 difference in ambient PM2.5 levels, Δx, can then be calculated based on this RRΔx as: 

13 

)]/1(1[)( 010 RR x yyyy       14 . (4) 

15 

16 Equations (3) and (4) are simply alternative ways of expressing the relationship 

17 between a given difference in ambient PM2.5 levels, Δx > 0, and the corresponding difference 

18 in health effects incidence, Δy. These health impact equations are the key equations that 

19 combine air quality information, C-R function information, and baseline health effects 

20 incidence information to estimate ambient PM2.5 health risk. 

21 3.1.2.2 Short-term vs. long-term exposure 

22 C-R functions that use as input annual average PM2.5 levels (or some function of these, 

23 such as the average over a period of several years) relate these to the annual incidence of the 

24 health endpoint – i.e., in such studies x in equation (1) above is the average PM2.5 

25 concentration over a period of one or more years, meant to represent long-term exposure, and 

26 y is the annual incidence of the health effect associated with that long-term exposure. 

27 C-R functions that use as input 24-hour average PM2.5 levels (or some function of 

28 these, such as the average over one or more days) relate these to the daily incidence of the 

29 health endpoint – i.e., in such studies x in equation (1) above is the average PM2.5 

30 concentration over a period of one or a few days (short-term exposure), and y is the daily 

31 incidence of the health effect associated with that short-term exposure. 

32 There are several variants of the short-term (daily) C-R function. Some C-R functions 

33 were estimated by using moving averages of ambient PM2.5 to predict daily health effects 

34 incidence. Such a function might, for example, relate the incidence of the health effect on day 

35 t to the average of PM2.5 concentrations on days t and (t-1). Some C-R functions consider the 

36 relationship between daily incidence and daily average PM2.5 lagged a certain number of days. 
September 2009 Draft – Do Not Quote or Cite 31

1 For example, a study might estimate the C-R relationship between mortality on day t and 

2 average PM2.5 on a prior day (t-1). A few studies have estimated distributed lag models, in 

3 which health effect incidence is a function of PM2.5 concentrations on several prior days – that 

4 is, the incidence of the health endpoint on day t is a function of the PM2.5 concentration on day 

5 t, day (t-1), day (t-2), and so forth. Such models can be reconfigured so that the sum of the 

6 coefficients of the different PM2.5 lags in the model can be used to predict the changes in 

7 incidence on several days. For example, corresponding to a change in PM on day t in a 

8 distributed lag model with 0-day, 1-day, and 2- day lags considered, the sum of the 

9 coefficients of the 0-day, 1-day, and 2-day lagged PM2.5 concentrations can be used to predict 

10 the sum of incidence changes on days t, (t+1) and (t+2). 

11 Most daily time-series epidemiological studies estimated C-R functions in which the 

12 PM-related incidence on a given day depends only on same-day PM concentration or 

13 previous-day PM concentration (or some variant of those, such as a two-day average 

14 concentration). Such models necessarily assume that the longer pattern of PM levels 

15 preceding the PM concentration on a given day does not affect mortality on that day. To the 

16 extent that PM-related mortality on a given day is affected by PM concentrations over a 

17 longer period of time, then these models would be mis-specified, and this mis-specification 

18 would affect the predictions of daily incidence based on the model. 

19 The extent to which time-series studies using single-day PM2.5 concentrations may 

20 misrepresent the relationship between short-term PM2.5 exposure and mortality is unknown. 

21 However, there is some evidence, based on analyses of PM10 data, that mortality on a given 

22 day is influenced by prior PM exposures up to more than a month before the date of death 

23 (Schwartz, 2000). The extent to which short-term exposure studies (including those that 

24 consider distributed lags) may not capture the full impact of long-term exposures to PM2.5 is 

25 similarly not adequately understood, although the current evidence (e.g., Krewski et al., 2009; 

26 Krewski et al., 2000) suggests that there is a substantial impact of long-term exposures on 

27 health effects that is not picked up in the short-term exposure studies. 

28 3.1.2.3 Calculating annual incidence 

29 The risk assessment estimated health effects incidence, and changes in incidence, on 

30 an annual basis, for 2005, 2006, and 2007. For mortality, both short-term and long-term 

31 exposure studies have reported estimated C-R functions. As noted above, most short-term 

32 exposure C-R functions estimated by daily time-series epidemiological studies relate daily 

33 mortality to same-day PM2.5 concentration or previous-day PM2.5 concentration (or some 

34 variant of those). 

35 To estimate the daily health impacts of 24-hour average ambient PM2.5 levels above 

36 PRB, C-R functions from short-term exposure studies were used together with estimated 
September 2009 Draft – Do Not Quote or Cite 32

1 changes in 24-hour ambient PM2.5 concentrations to calculate the daily changes in the 

2 incidence of the health endpoint. After daily changes in health effects were calculated, an 

3 annual change was calculated by summing the daily changes. 

4 The mortality associated with long-term exposure is likely to include mortality related 

5 to short-term exposures as well as mortality related to longer-term exposures. As discussed 

6 previously, estimates of daily mortality based on the time-series studies also are likely 

7 influenced by prior PM exposures. Therefore, the estimated annual incidences of mortality 

8 calculated based on the short- and long-term exposure studies are not likely to be completely 

9 independent and should not be added together. While we can characterize the statistical 

10 uncertainty surrounding the estimated PM2.5 coefficient in a reported C-R function, there are 

11 other sources of uncertainty associated with the C-R functions used in the risk assessment 

12 that are addressed via sensitivity analyses and/or qualitatively discussed in section 3.5.3. 

13 3.2 AIR QUALITY INPUTS 

14 3.2.1 Characterizing recent conditions 

15 As noted earlier, a major input to the PM2.5 risk assessment is ambient PM2.5 air 

16 quality data for each assessment location. Twenty-four hour PM2.5 air quality data for 2005, 

17 2006, and 2007 were obtained for each of the urban study areas from monitors in EPA’s Air 

18 Quality System (AQS). To characterize PM2.5 air quality in each risk assessment location as 

19 accurately as possible, we used only those monitors that were located within the county or 

20 counties that were analyzed in the epidemiological studies used to select C-R functions.. In a 

21 few cases, an urban area was delineated differently by two or more epidemiological studies 

22 used in the risk assessment. For example, Birmingham, AL was defined as Blount, Jefferson, 

23 Shelby, St. Clair, and Walker Counties in one study and as only Jefferson County in another 

24 study. In such cases, we matched our delineation of the urban study area to that used in each 

25 study, resulting in two or more different delineations of the urban study area and identified 

26 them as, for example, Birmingham 1 and Birmingham 2. The counties and the number of air 

27 quality monitors included within each urban area are given in Table 3-1. 

28 In order to be consistent with the approach generally used in the epidemiological 

29 studies that estimated PM2.5 C-R functions, the average ambient PM2.5 concentration on each 

30 day for which measured data were available was deemed most appropriate for use in the risk 

31 assessment. Consistent with the approach used in the prior PM risk assessment, a composite 

32 monitor data set was created for each assessment location based on a composite of all 

33 monitors located within each urban study area. Specifically, the value at the composite 

34 monitor on a given day was calculated as the average of the values at those monitors in a 

35 specific urban study area that reported a measured value for that day. 
September 2009 Draft – Do Not Quote or Cite 33

1 There were some days on which none of the monitors in a risk assessment location 

2 reported PM2.5 concentrations. The numbers of missing days at the composite monitors in the 

3 risk assessment locations are given in Table 3-1. We used 7-day moving averages to fill in 

4 missing values at composite monitors. 

5 To summarize, air quality data inputs for the risk assessment model were developed as 

6 follows: first we calculated the composite monitor value for each day. For any day that had a 

7 missing value at the composite monitor, we inserted the 7-day moving average centered on 

8 that day. We then evaluated the new series of composite monitor values (with missing days 

9 filled in as described); if any day still had a missing value, we filled it in with the 7-day 

10 moving average centered on the missing day, where the values in the 7-day moving average 

11 were calculated from the series created on the previous step. We repeated this process until 

12 all missing days were filled in. 

13 Table 3-1. Numbers of Monitors and Numbers of Missing Days at Composite 

14 Monitors in Risk Assessment Locations from 2005 Through 2007. 

Risk Assessment 

Location Counties 

Number of 

Monitors 

Number of Missing 

Days at Composite 

Monitor Over the 3-

Year Period* 

Atlanta, GA - 1 Cobb, De Kalb, Fulton, Gwinnett 8 8 

Atlanta, GA - 2 Cobb, De Kalb, Fulton 7 8 

Atlanta, GA - 3 20-County MSA** 10 7 

Baltimore, MD Baltimore city, Baltimore county 8 2 

Birmingham, AL – 

1 

Blount, Jefferson, Shelby, St. Clair, 

Walker 

10 1 

Birmingham, AL – 

2 

Jefferson 8 1 

Dallas, TX Dallas 6 21 

Detroit, MI Wayne 9 22 

Fresno, CA Fresno 3 40 

Houston, TX Harris 6 59 

Los Angeles, CA Los Angeles 10 0 

New York, NY - 1 Kings, New York City (Manhattan), 

Queens, Richmond, Bronx 

12 4 

New York, NY - 2 New York City (Manhattan) 5 731*** 

Philadelphia, PA Philadelphia 7 14 

Phoenix, AZ Maricopa 5 710 

Pittsburgh, PA Allegheny 12 1 

Salt Lake City, UT Salt Lake 7 4 

St. Louis, MO - 1 Jefferson, Madison (IL), St. Louis, St. 

Louis City, St. Clair (IL) 

15 0 

St. Louis, MO - 2 Madison (IL), St. Louis, St. Louis City, 

St. Clair (IL) 

14 1 

Tacoma, WA Pierce 1 741*** 

15 *The value on a given day at the composite monitor is the average of all monitors reporting on that day. 

16 ** Barrow, Bartow, Carroll, Cherokee, Clayton, Cobb, Coweta, DeKalb, Douglas, Fayette, Forsyth, Fulton, 

17 Gwinett, Henry, Newton, Paulding, Pickens, Rockdale, Spalding, and Walton. 

18 *** Note, that the sets of monitors for New York (Manhatten) have 1 in 3 day sampling, with sampling 

19 schedules synced across monitors. This means that for the three year simulation period, roughly 2/3 of the days 
September 2009 Draft – Do Not Quote or Cite 34

1 (i.e., 731) had no monitor coverage for the New York urban study area, resulting in a need to interpolate 

2 estimates for these days (for the composite monitor) using the approach described above. Similarly, with 

3 Tacoma, the single monitor at that location also has 1 in 3 day sampling, resulting again, in 2/3 of the days not 

4 having data with interpolation being used to derive estimates for those days (for the composite monitor). 

 5 

6 Appendix A summarizes the PM2.5 air quality data that were used in each of the 

7 assessment locations, including quarterly and annual counts, quarterly and annual averages, 

and the 98th 8 percentile of the daily (24-hour) averages. 

9 3.2.2 Estimating policy relevant background 

10 PRB estimates used in the risk assessment model (see Table 3-2 below) were obtained 

11 from the draft ISA (Table 3.7-6, draft ISA, EPA, 2009a). These values were generated based 

12 on a combination of Community Multiscale Air Quality model (CMAQ) and Goddard Earth 

13 Observing System (GEOS)-Chem modeling as described in the draft ISA (see section 

14 3.6.1.2). Annual values presented in Table 3-2 were used in modeling health endpoints 

15 associated with long-term exposure (in those sensitivity analysis scenarios where risk was 

16 modeled down to PRB – see Section 3.5.4). For health endpoints associated with short-term 

17 exposure (which involved modeling down to PRB, exclusively), quarterly values presented in 

18 Table 3-2 were used to represent the appropriate block of days within a simulated year. 

19 Table 3-2 Regional Policy-Relevant Background Estimates Used in the Risk 

20 Assessment. 

U.S. Region Annual 

JanuaryMarch April-June JulySeptember OctoberDecember 

Northeast 0.74 0.85 0.78 0.67 0.68 

Southeast 1.72 2.43 1.41 1.41 1.64 

Industrial Midwest 0.86 0.89 0.89 0.94 0.73 

Upper Midwest 0.84 0.79 0.93 0.99 0.66 

Southwest 0.62 0.61 0.76 0.70 0.40 

Northwest 1.01 0.48 0.81 1.42 1.32 

Southern California 0.84 0.54 0.92 1.21 0.67 

21 

22 3.2.3 Simulating air quality to just meet current and alternative standards 

23 This section describes the methodology used to simulate ambient PM2.5 levels in an 

24 area upon just meeting specified PM2.5 standards. The form of the PM2.5 standards 

25 promulgated in October 2006 requires that the 3-year average (rounded to the nearest 0.1 

μg/m3 26 ) of the annual means from single monitors or the average of multiple monitors must be 

27 at or below the level of the annual standard and the 3-year average (rounded to the nearest 1 

μg/m3 28 ) of the ninety-eighth percentile values at each monitor cannot exceed the level of the 
September 2009 Draft – Do Not Quote or Cite 35

1 24-hour standard. In determining attainment of the annual average standard, an area may 

2 choose to use either the spatially averaged concentrations across all population-oriented 

3 monitors, subject to meeting certain criteria detailed in Part 50, Appendix N, of the CFR, or it 

4 may use the highest 3-year average based on individual monitors. The most realistic 

5 simulation of just meeting both the annual and the 24-hour PM2.5 standards in a location 

6 would require changing the distribution of 24-hour PM2.5 concentrations at each monitor 

7 separately, reflecting the specific mix of local and regional controls impacting that particular 

8 location. This would require extensive analysis and assumptions about the nature of future 

9 control strategies that was considered beyond the scope of the previous risk assessment and is 

10 similarly considered beyond the scope of the current risk assessment. 

11 In the previous PM risk assessment, just meeting the current or alternative PM2.5

12 standards was simulated by changing 24-hour PM2.5 concentrations at a “composite monitor,” 

13 which represented the average of the monitors in a location. In the current PM risk 

14 assessment, just meeting the current or alternative PM2.5 standards was simulated by changing 

15 24-hour PM2.5 concentrations at each monitor separately. This change was made because the 

16 current PM risk assessment considers two alternative approaches to simulating PM2.5

17 concentrations that just meet a given set of standards. One of these approaches (the 

18 “proportional rollback” approach) was used in previous PM2.5 risk assessments and involves 

19 proportional adjustments to monitor levels, in which PM2.5 concentrations are reduced 

20 (“rolled back”) by the same percentage each day. When this approach is used, it doesn’t 

21 matter whether (1) PM2.5 concentrations are first rolled back by the same percentage each day 

22 at each monitor, and then the composite monitor values are calculated from these monitor23 specific values or (2) first the composite monitor values are calculated and then these are 

24 rolled back by the same percentage each day – the results will be the same. 

25 The second approach (the “hybrid rollback” approach) used in a sensitivity analysis in 

26 some of the risk assessment locations (in comparison to the proportional rollback approach), 

27 has two steps: (1) first PM2.5 concentrations are reduced at a specific monitor location within 

28 an urban study area and then additional monitors within that urban study area are adjusted to a 

29 lesser extent (with the magnitude of adjustment based on a distance-decay function); then (2) 

30 a proportional rollback of the adjusted PM2.5 concentrations at all of the different monitors is 

31 carried out. This two-step approach is intended to simulate situations in which it is likely that 

32 attainment of a set of standards will be achieved by first implementing more localized 

33 controls to target a specific monitor (with lesser reductions resulting at other near-by monitors 

34 due to the influence of adopting more localized controls) followed by regional controls that 

35 result in a more universal (proportional) reduction across all the monitors in a study area. 

36 Because the initial step reflecting localized controls is non-proportional, this needs to be 

37 completed on the monitor datasets (associated with a particular study area) prior to 
September 2009 Draft – Do Not Quote or Cite 36

1 construction of the composite monitor. However, once those non-proportional reductions have 

2 been implemented, a composite monitor can then be constructed (as described earlier) and the 

3 second step of conducting proportional adjustment to simulate the current or alternative set of 

4 standard levels, can be calculated for the composite monitor. 

5 The percent reduction of 24-hour PM2.5 concentrations in the proportional rollback 

6 approach (and in the second step of the hybrid rollback approach) at each monitor each day to 

7 simulate just meeting current and alternative set of standard levels is determined by the PM2.5

annual and 24-hour design values. The annual design value (in μg/m3 8 ) was calculated as 

9 follows: 

10  At each monitor, the annual average PM2.5 concentration was calculated for each of 

11 the years 2005, 2006, and 2007, and these three annual average concentrations were 

12 then averaged. 

13  The maximum of these monitor-specific 3-year averages of annual averages is the 

14 annual design value, denoted dvannual; 

The 98th percentile design value (in μg/m3 15 ) was similarly calculated as follows: 

 At each monitor, the 98th 16 percentile 24-hour PM2.5 concentration was calculated for 

each of the years 2005, 2006, and 2007, and these three 98th 17 percentile concentrations 

18 were then averaged. 

 The maximum of these monitor-specific 3-year averages of 98th 19 percentile 

20 concentrations is the 24-hour design value, denoted dvdaily 98 (note, we will refer to the 

98th 21 percentile design value as the 24-hour design value throughout the rest of the 

22 document). 

23 The annual and 24-hour design values used in assessing the current and alternative 

24 standards for PM2.5 are given in Table 3-3. Note, that monitors that were closed in 2005 (and 

25 therefore, did not include monitoring data for the majority of the three year simulation 

26 period), or which were missing an entire year’s worth of monitoring data during any of the 

27 three simulation years (2005, 2006 or 2007) were excluded from consideration as design 

28 value monitors, although these monitors were still used to construct composite monitors for 

29 purposes of estimating risks. 

30 

31 Table 3-3. EPA Design Values for Annual and \24-hour PM2.5 Standards for the 

32 Period 2005-2007.* 

Location 

Annual 

 (μg/m3) 

24-hour 

(μg/m3) 

Atlanta 17 35 

Baltimore 16 37 

Birmingham 19 44 

Dallas 13 26 

Detroit 17 43 
September 2009 Draft – Do Not Quote or Cite 37

Location 

Annual 

 (μg/m3) 

24-hour 

(μg/m3) 

Fresno 17 63 

Houston 16 31 

Los Angeles 20 55 

New York 16 42 

Philadelphia 15 38 

Phoenix 13 32 

Pittsburgh 20 60 

Salt Lake City 12 55 

St. Louis 17 39 

Tacoma 10 43 

1 *The calculation of design values is explained in the text above. 

 2 

3 The percent reduction required to meet a standard (annual or 24-hour) was determined 

4 by comparing the design value for that standard with the level of the standard. Because 

5 pollution abatement methods are applied largely to anthropogenic sources of PM2.5, rollbacks 

6 were applied only to PM2.5 above estimated PRB levels. The percent reduction was 

7 determined by the controlling standard. For example, suppose both an annual and a 24-hour 

8 PM2.5 standard are being simulated. Suppose pa is the percent reduction required to just meet 

9 the annual standard (i.e., the percent reduction of daily PM2.5 above background necessary to 

10 get the annual design value down to the current or alternative annual standard). Suppose pd is 

11 the percent reduction required to just meet the 24-hour standard (i.e., the percent reduction of 

12 daily PM2.5 above background necessary to get the 24-hour PM2.5 design value down to the 

13 24-hour standard). If pd is greater than pa, then all 24-hour average PM2.5 concentrations 

14 above background are reduced by pd percent. If pa is greater than pd, then all 24-hour average 

15 PM2.5 concentrations are reduced by pa percent. The method of rollbacks to meet a set of 

16 annual and 24-hour PM2.5 standards is summarized as follows: 

17 1. The percent by which the above-PRB portion of all daily PM2.5 concentrations (at the 

18 composite monitor) would have to be reduced to just meet the annual standard 

19 (denoted stda) is 

)

( ) 1

annual avg

a avg

a dv PRB

PRBstd

p 

 20  , 

21 

 where PRBavg is the average of the daily PRB concentrations.16 22 

23 

 16 In the previous PM risk assessment, a constant PRB level was assumed for all days, and that constant PRB 

level was used in the formulas to calculate percent rollbacks necessary to just meet a standard. It can be shown 

that, if PRB levels vary from day to day, the average PRB level takes the place of the constant PRB level in the 

previous formula, as shown in the above equation. 
September 2009 38 Draft – Do Not Quote or Cite 

1 

2 2. The percent by which the above-PRB portion of all 24-hour PM2.5 concentrations (at 

3 the composite monitor) would have to be reduced to just meet the current or 

4 alternative 24-hour standard (denoted stdd98) is: 

5 

)

( ) 1

98

98

98

daily avg

d avg

d dv PRB

std PRB

p 

 6 

7 

Let pmax = maximum of (maximum of pa and pd98) and zero.17 8 

9 

10 

11 3. Then if PMo denotes the original PM value on a given day (at the composite monitor), 

12 the rolled back PM value on that day, denoted PMrb, is: 

13 

14 PMrb = PRB +(PMo − PRB)*(1− pmax ). 

15 

16 3.3 SELECTION OF MODEL INPUTS 

17 3.3.1 Health endpoints 

18 As noted in the Scope and Methods Plan, selection of health effect endpoints reflects 

19 consideration for a number of factors including: (a) the extent to which a particular health 

20 effect endpoint is considered significant from a public health standpoint, (b) the overall 

21 weight of evidence from the collective body of epidemiological, controlled human exposure, 

22 and toxicological studies and the determination made in the draft ISA as to whether there is a 

23 causal or likely causal relationship between PM2.5 and the more general health effect category, 

24 and (c) whether there are well-conducted studies providing estimated C-R functions for 

25 specific health effect endpoints within the broader health effects category associated with 

26 ambient PM2.5 levels (section 3.2.2, EPA, 2009b). An additional factor, not specifically 

27 mentioned in the Scope and Methods Plan, that we considered is the availability of baseline 

28 health effects incidence data that matches the study population(s) evaluated in the 

29 epidemiological study(ies) from which C-R function(s) were selected. 

 17 If the percent rollback necessary to just meet the annual standard and the percent rollback necessary to just 

meet the 24-hour standard were both negative -- i.e., if both standards were already met -- then the percent 

rollback applied in the risk assessment was zero. That is, PM values were never increased, or “rolled up.” 
September 2009 39 Draft – Do Not Quote or Cite 

1 Based on application of the above criteria, as outlined in the Scope and Methods Plan, 

2 we identified the following health effects endpoint categories as candidates for inclusion in 

3 the risk assessment: 

4 Health effect categories associated with short-term PM2.5 exposure: 

5  Cardiovascular effects (causal relationship) 

6  Respiratory effects (likely causal relationship) 

7  Mortality (likely causal relationship) 

8 Health effect categories associated with long-term PM2.5 exposure:

9  Cardiovascular effects (causal relationship) 

10  Respiratory effects (likely causal relationship) 

11  Mortality (likely causal relationship) 

12 In addition, as noted in the Scope and Methods Plan, we considered expanding the 

13 focus of the risk assessment to include additional endpoints from health effects categories that 

14 had been initially judged in the draft ISA to have evidence from the scientific evidence 

15 evaluated that was suggestive of a casual relationship between ambient PM2.5 measurements 

16 and the general category of health effects, if those additional endpoints allowed us to address 

17 potentially important policy issues related to the review of the PM NAAQS. In the Scope and 

18 Methods Plan, we cited birth outcomes as a potential candidate for inclusion in the PM2.5 risk 

19 assessment based on this additional criterion, recognizing that, in considering endpoints 

20 classified as suggestive of a causal relationship, it would be important to appropriately 

21 characterize the additional uncertainty associated with the risk estimates (section 3.2.2, EPA, 

22 2009). 

23 In selecting the set of health effect endpoint categories (and associated endpoints) to 

24 include in the PM2.5 risk assessment, we built upon the health effects evidence presented in the 

25 draft ISA (EPA, 2009a), as well as CASAC (Samet, 2009) and public comments received on 

26 the Scope and Methods Plan. Comments provided by CASAC regarding the selection of 

27 health effects endpoints included providing “a transparent algorithm for selecting endpoints 

28 based on the level of certainty and the relative and attributable risks” as well as the suggestion 

29 “that weight be given to the level of classification while still considering the Administrator’s 

30 obligation to set a standard with a “margin of safety” as describe in the Clean Air Act” (Samet 

31 2009, p.1). As an example, several CASAC members did not recommend a risk assessment 

32 based on birth outcomes, “in part because the level of evidence is still at a suggestive level 

33 (Samet 2009, p. 1-2). 
September 2009 40 Draft – Do Not Quote or Cite 

1 In reviewing the draft ISA in relation to PM2.5, we focused on the following sections: 

2 (a) section 2.3.1.1 (Effects of Short-Term Exposure to PM2.5), (b) section 2.3.1.2 (Effects of 

3 Long-Term Exposure to PM2.5), (c) section 2.3.2 (Integration of PM2.5 Health Effects), (d) 

4 6.2.12 (Summary and Causal Determinations [for effects related to short-term PM2.5

5 exposure]), and (e) 7.3.9 (Summary and Causal Determinations [for effects related to long6 term PM2.5 exposure]). Our overall conclusions regarding the set of health effect endpoint 

7 categories to include in the risk assessment for PM2.5, based on review of these sections of the 

8 draft ISA, did not change from the provisional set provided in the Scope and Methods Plan. 

9 Consideration of information provided in the draft ISA (as referenced above) and 

10 CASAC and public comments on the Scope and Methods Plan, as well as review of the 

11 available epidemiological studies for deriving C-R functions (see section 3.3.3) as well as 

12 availability of baseline health effect incidence data to support risk modeling (see section 3.4), 

13 has resulted in the following health effect categories (and associated health effect endpoints) 

14 being selected for modeling PM2.5 in the risk assessment: 

15 Short-term exposure

16  Premature mortality (non-accidental, respiratory, cardiovascular) 

17  Respiratory effects (respiratory-related hospital admissions and asthma-related 

18 ED visits) 

19  Cardiovascular effects (cardiovascular-related hospital admissions) 

20 Long-term exposure

21  Mortality (all-cause, ischemic heart disease (IHD), cardiopulmonary, lung 

22 cancer) 

23 In addition to estimating risk for PM2.5, in the Scope and Methods Plan, we also 

24 outlined plans for modeling risk associated with short-term exposures to thoracic coarse 

25 particles (PM10-2.5) (section 3.6, EPA, 2009). Specifically, we identified a set of short-term 

26 cardiovascular and respiratory morbidity endpoints as potential candidates for inclusion in the 

27 risk assessment (cardiovascular and respiratory hospital admissions, asthma-related ED visits 

28 and respiratory symptoms), noting that support in the first draft ISA for these endpoints did 

29 not rise above being suggestive of a causal relationship. We noted in the Scope and Methods 

30 Plan that the decision whether to include these thoracic coarse particle-related health 

31 endpoints in a quantitative risk assessment would depend on review of the scientific evidence 

32 presented in the second draft ISA as well as consideration for public and CASAC comments 

33 on the Scope and Methods Plan. During a consultation on the Scope and Methods Plan, 
September 2009 41 Draft – Do Not Quote or Cite 

1 CASAC expressed support for a limited risk assessment focusing on exposure to PM10-2.5, for 

2 appropriate outcomes such as hospitalizations (Samet 2009, p. 2). 

3 In the risk assessment conducted for the last PM NAAQS review, EPA concluded that 

4 the nature and magnitude of the uncertainties and concerns associated with this portion of the 

5 risk assessment weighed against use of these risk estimates as a basis for recommending 

6 specific standard levels (EPA, 2005, p. 5-69). In reviewing the evidence provided in the 

7 second draft ISA (US EPA, 2009, ref specific sections or chapters) specifically addressing 

8 effects associated with exposure to PM10-2.5, we recognize that the ISA concludes that there is 

9 suggestive support for an relationship between short-term exposure to PM10-2.5 and 

10 cardiovascular and respiratory effects, as well as mortality. However, we believe that the 

11 underlying epidemiological evidence does not readily support derivation of C-R functions 

12 applicable to urban case studies in the U.S without the introduction of significant uncertainty 

13 into the risk estimates. Further, we find that research to inform the uncertainties identified in 

14 the last review have not fundamentally changed these uncertainties. Therefore, we conclude 

15 that additional analyses quantifying PM10-2.5-related risks would not provide additional 

16 information beyond the assessment done in the last review and, therefore, no quantitative risk 

17 assessment has been conducted for PM10-2.5 in this document. 

18 3.3.2 Selection and delineation of urban study areas 

19 This section describes the approach used in selecting the 15 urban study areas included 

20 in this risk assessment (see Table 3-3 for a listing of the urban study areas). The approach for 

21 selecting urban study areas considered criteria from the prior risk assessment and adds two 

22 new criteria. 

23 Criteria used in the prior risk assessment include: (a) sufficient air quality data for at 

24 least one year for the period 1999 or later (at least 11 observations per quarter for a one year 

25 period and at least 122 observations per year), (b) coverage of the location by one of the key 

26 epidemiology studies included in the risk assessment (at or close to the location where at least 

27 one C-R function for one of the recommended health endpoints has been estimated by a study 

28 satisfying the selection criteria used in the risk assessment), and (c) sufficient baseline 

29 incidence data for the location (see EPA, 2005, section 3.2 p. 37, for additional detail on these 

30 three criteria). Regarding the first criteria (sufficiency of air quality), we assessed prospective 

31 study areas by insuring that there was at least one PM2.5 monitor within the boundaries of the 

32 prospective study area that met completeness criteria for the period 2005 to 2007 (note, that 

33 locations with more than one PM2.5 monitor meeting completeness criteria were favored, since 

34 this provided a better characterization of ambient air levels for that urban location). The two 

35 remaining criteria from the prior risk assessment were largely addressed due to new 

36 epidemiological studies and baseline incidence data that are now available. Specifically, 
September 2009 42 Draft – Do Not Quote or Cite 

1 regarding coverage by key epidemiology studies, because the current risk assessment 

2 primarily utilizes multi-city studies to evaluate risk for key short-term and long-term health 

3 endpoints (whereas the prior risk assessment used city-specific studies in modeling short-term 

4 endpoints), this criterion no longer applies for most prospective areas. Regarding sufficiency 

5 of baseline health effects incidence data, an ongoing effort by EPA to collect county-level 

6 hospital and emergency department admissions data from states to support this risk 

7 assessment (see section 3.5) has resulted in enhanced health effects baseline incidence data, 

8 largely addressing this criterion (i.e., most urban areas in the U.S. now have coverage with the 

9 updated baseline health effects incidence data). 

10 In addition to these criteria from the prior risk assessment, as noted above, we have 

11 also included consideration for two additional factors in selecting urban study areas. First, we 

12 focused on those urban areas with PM2.5 monitoring levels suggesting the potential for risk 

13 reduction under alternative (daily or annual) standards. Specifically, only those urban 

locations with at least one monitor having an annual average above 12 μg/m3 14 and/or a 24-hour 

value above 25 μg/m3 15 (the levels in the lowest alternative standard considered in the risk 

16 assessment) were considered. Furthermore, locations with ambient PM2.5 level significantly 

17 higher than these levels were favored (with several urban study areas selected having annual 

18 and daily design values exceeding the current standard level, being selected – see Table 3-4). 

19 Application of this criterion reflects a desire to include urban case studies that are 

20 representative of areas likely to experience some degree of risk reduction under alternative 

21 standard levels. 

22 The second criterion we added for study area selection, was the goal of providing 

23 coverage for factors believed to play a role in influencing risk heterogeneity at the national24 level (e.g., PM source characteristics and composition, demographics, SES status, air 

25 conditioner use). We implemented this criterion by using the 7 PM regions originally 

26 identified in the 1996 PM Criteria Document (US EPA, 1996), to guide selection of urban 

27 study areas. Specifically, we attempted to include several urban locations from each of the 

28 PM regions in our suite of 15 urban study areas, to insure that each of the regions was 

29 represented by one or more of the urban study areas (see Table 3-4). Note, that ultimately, 

30 consideration of the criteria described here resulted in an urban study area not being identified 

31 for one of the PM regions (the Upper Midwest). However, the remaining six regions each 

32 included at least one of the 15 urban study areas evaluated in the risk assessment. While the 

33 1996 PM regions as defined (see footnote 2), focused primarily on differences in PM 

34 composition, size and seasonality, by selecting urban study areas from regions that cover the 

35 continental U.S., we also have a better potential for covering regional differences in other 

36 factors related to risk heterogeneity (e.g., demographics, SES, and behavior related to PM 

37 exposure such as air conditioner use). Note, that the representativeness analysis (which is 
September 2009 43 Draft – Do Not Quote or Cite 

1 discussed in section 4.4) specifically assesses the degree to which the 15 urban study areas 

2 provide coverage for national trends in key risk-related factors such as those listed here. 

3 Table 3-4 presents the 15 urban study areas selected for the risk assessment, including 

4 (a) which state it is located in, (b) whether the urban study area was included in the prior risk 

5 assessment, (c) which PM region the urban study area is located in, and (d) the daily and 

6 annual design values considered in selected the location. Figure 3-4 identifies each of the 15 

7 urban study areas in relation to the 7 PM regions used to guide the selection of the urban 

8 study areas. 

9 Table 3-4. Urban Study Areas Selected for the Risk Assessment. 

Urban study 

area 

State 

Modeled in last 

NAAQS review 

PM 

Region* 

Annual design 

value (μg/m3) 

Daily design 

value (μg/m3) 

Atlanta GA SE 16 35 

Baltimore MD NE 16 37 

Birmingham AL SE 19 44 

Dallas TX SE 13 26 

Detroit MI X IM 17 43 

Fresno CA SCA 17 63 

Houston TX SE 16 31 

LA CA X SCA 20 55 

New York NY NE 16 42 

Philadelphia PA X NE 15 38 

Phoenix AZ X SW 13 32 

Pittsburgh PA X IM 20 60 

Salt Lake City UT NW 12 55 

Tacoma WA X NW 10 43 

St. Louis MO X IM 17 39 

10 * SE (Southeast), IM (industrial Midwest), SCA (Southern California), NE (Northeast), NW (Northwest), SW 

11 (Southwest) (See, EPA, 1996, section 6.4 for description of these PM regions).

12 

13 
September 2009 44 Draft – Do Not Quote or Cite 

Northwest

Southwest Southeast

Northeast

Upper Midwest Industrial Midwest

Southern California

Dallas

Fresno

Tacoma

Atlanta

Detroit

Houston

Phoenix

New York

Baltimore St. Louis

Birmingham Los Angeles

Salt Lake City Pittsburgh Philadelphia

1 

2 Figure 3-4 15 urban study areas included in the risk assessment (including seven PM 

3 regions used to guide selection of study areas). 

4 

5 Once the 15 urban study areas were selected, the next step was to identify the spatial 

6 template to use in defining each study area (i.e., the geographical area associated with each 

7 study area that would be used in identifying which counties and PM2.5 monitors were 

8 associated with a particular study area). For 12 of the 15 urban study areas, we either used a 

9 combined statistical area (CSA) as the basis for the spatial template, or if that was not 

10 available, we used a core-based statistical area (CBSA). The three remaining urban study 

11 areas were special cases and were handled as follows: (a) for Baltimore we used counties in 

12 the Baltimore CBSA (and not the Baltimore-DC CSA, even though this CSA was available 

13 since we felt it unlikely that this entire larger CSA would behave similarly with regard to PM 

14 reduction strategies), (b) for Philadelphia, we used the Philadelphia CSA, but excluded Berks 

15 County (Reading), and (c) for Tacoma, we only used Pierce County (since we felt it unlikely 

16 that efforts to reduce emissions at the “elevated” monitor in Pierce County, would 

17 significantly impact monitors in Seattle). 

18 As noted above, in a few instances, two or more epidemiological studies used different 

19 geographic boundaries for determining which populations were included in their studies. For 

20 example, in one study conducted in Birmingham, AL populations from Blount, Jefferson, 

21 Shelby, St. Clair, and Walker Counties were included, while another study included the 

22 population residing in only Jefferson County. In such cases, we matched our delineation of 
September 2009 45 Draft – Do Not Quote or Cite 

1 the urban area to that of each study, resulting in two or more different delineations of the 

2 urban area. 

3 As we discuss below, two of the studies on which we rely for our core analysis – 

4 Zanobetti and Schwartz (2009) and Bell et al. (2008) – are multi-location studies. Zanobetti 

5 and Schwartz (2009) specified the county or counties included in each of the urban areas they 

6 included in their analysis. Bell et al. (2008), however, did not focus on urban areas, but 

7 instead focused on counties with populations above a specified threshold number. To limit 

8 the number of different “versions” of a risk assessment location, wherever possible we 

9 specified the counties in a risk assessment location for Bell et al. (2008) to match the set 

10 specified for Zanobetti and Schwartz (2009). This was possible in those cases in which 

11 Zanobetti and Schwartz (2009) identified an urban area as a single county, and that county 

12 was also included in Bell et al. (2008). This was the case for several of the risk assessment 

13 locations. In some cases, however, Zanobetti and Schwartz (2009) used a multi-county 

14 delineation of an urban area where at least one of the counties was not among those included 

15 in Bell et al. (2008). In those cases, we had to delineate two definitions of the urban area – 

16 one corresponding to Zanobetti and Schwartz (2009) and the other corresponding to Bell et al. 

17 (2008). This was the case for Atlanta, Birmingham, and St. Louis. In both Atlanta and New 

18 York, other delineations by other studies forced additional delineation of these urban areas, as 

19 shown in Table 3-1 above. 

20 Finally, we applied the studies of mortality associated with long-term exposure to 

21 PM2.5 to the urban areas as defined by the short-term exposure mortality study, Zanobetti and 

22 Schwartz (2009), to enable meaningful comparisons between estimates of premature morality 

23 associated with short-term and long-term exposure to PM2.5. 

24 3.3.3 Selection of epidemiological studies and concentration-response (C-R) 

25 functions within those studies 

26 As discussed above, we included in the PM2.5 risk assessment only the better27 understood health effects for which the weight of the evidence supports a likely causal 

28 inference. Thus, in cases where the majority of the available studies did not report a 

29 statistically significant relationship, the effect endpoint was not included. Once it had been 

30 determined that a health endpoint would be included in the analysis, however, inclusion of a 

31 study on that health endpoint was not based on statistical significance. 

32 A significant change since the previous PM risk assessment is the addition to the 

33 relevant epidemiological literature of several multi-city studies. This type of study has 

34 several advantages over single-city studies. First, multi-city studies use the same study design 

35 in each of the cities included in the study, so that city-specific results are readily comparable. 

36 Second, when they are estimating a single C-R function based on several cities, multi-city 
September 2009 46 Draft – Do Not Quote or Cite 

1 studies also tend to have more statistical power and provide effect estimates with relatively 

2 greater precision than single city studies due to larger sample sizes, reducing the uncertainty 

3 around the estimated coefficient. Moreover, in a multi-city study the statistical power to 

4 detect an effect in any given city can be supplemented by drawing statistical power from data 

5 across all the cities included in the study (or all the cities in the same region) to adjust city6 specific estimates towards the mean across all cities included in the analysis (or in the same 

7 region). This is particularly useful in those instances, where a city has relatively less data 

8 resulting in a larger standard error for the effect estimate. In this situation, the information on 

9 the C-R relationship in all the other cities included in a multi-city study can be used to help 

10 inform an assessment of the C-R relationship in the city in question. Finally, multi-city 

11 studies tend to avoid the often-noted problem of publication bias that single-city studies 

12 confront (in which studies with statistically insignificant or negative results are less likely to 

13 get published than those with positive and/or statistically significant results). 

14 For this risk assessment, we selected what we considered to be the best study to assess 

15 the C-R relationship between PM2.5 and a given health endpoint, and we included other 

16 studies for that health endpoint only if they were judged to contribute something above and 

17 beyond what we could learn from the primary study selected. 

18 A primary study for a given health endpoint had to satisfy the study selection criteria 

19 that we have used in past PM (and other) risk assessments. In particular: 

20  It had to be a published, peer-reviewed study that has been evaluated in the PM ISA 

21 and judged adequate by EPA staff for purposes of inclusion in this risk assessment 

22 based on that evaluation. 

23  It had to directly measure, rather than estimate, PM2.5 on a reasonable proportion of the 

24 days in the study. 

25  It had to either not rely on Generalized Additive Models (GAMs) using the S-Plus 

26 software to estimate C-R functions or to appropriately have re-estimated these 

functions using revised methods.18 27 

28 Because of the advantages noted above, we selected multi-city studies as our primary 

29 studies for assessing the risks of premature non-accidental, cardiovascular, and respiratory 

30 mortality (Zanobetti and Schwartz, 2009) and cardiovascular and respiratory hospital 

31 admissions (Bell et al., 2008) associated with short-term exposure to PM2.5 in our core 

32 analysis. In each of these studies, the 15 urban areas selected for the PM risk assessment were 

33 among the locations included in their analysis. 

 18 The GAM S-Plus problem was discovered prior to the recent final PM risk assessment carried out as part of 

the PM NAAQS review completed in 2006. It is discussed in the 2004 PM Criteria Document (EPA, 2004), PM 

Staff Paper (EPA, 2005c), and PM Health Risk Assessment Technical Support Document (Abt Associates, 

2005). 
September 2009 47 Draft – Do Not Quote or Cite 

1 Studies often report more than one estimated C-R function for the same location and 

2 health endpoint. Sometimes models including different sets of co-pollutants are estimated in 

3 a study; sometimes different lag structures are used. Sometimes different modeling 

4 approaches are used to fit weather and temporal variables in the model. Once a study has 

5 been selected, the next step is to select one or more C-R functions from among those reported 

6 in the study. 

7 Zanobetti and Schwartz (2009) divided the United States into six regions, based on the 

8 Köppen climate classification (Kottek 2006; Kottek et al. 2006)(http://koeppeneiger.vuwien.ac.at/).19 9 They estimated the coefficient of PM2.5 in single-pollutant log-linear 

10 models using Poisson regression for each of 112 cities, as well as in two-pollutant models 

11 with coarse PM. They estimated annual models (which assume that the relationship between 

12 mortality and PM2.5 is the same through the year), as well as four seasonal models per 

13 location. They then used a random effects meta-analysis to combine the city-specific results 

14 (Berkey et al. 1998). Pooling of city-specific results was done at the national level as well as 

15 at the regional level, and separately for each season as well as for the annual functions. 

16 With respect to the multi-city study for short-term exposure mortality, at the request of 

17 EPA, the authors produced Empirical Bayes “shrunken” city-specific estimates, adjusted 

18 towards the appropriate regional mean, using the approach described in Le Tertre et al. 

(2005). This was done for the annual estimates as well as for each season-specific estimate.20 19 

The annual city-specific “shrunken” estimates were used in our core analysis.21 20 The seasonal 

21 estimates were used in a sensitivity analysis. City-specific estimates have the advantage of 

22 relying on city-specific data; however, as noted above, such estimates can have large standard 

23 errors (and thus be unreliable); “shrinking” city-specific estimates towards the regional mean 

estimate is a more efficient use of the data.22 24 Such “shrinking” can be thought of as 

25 combining the advantages of a single-city study (in which the estimation of a city-specific 

 19 Zanobetti and Schwartz delineate regions as follows: “region 1: humid subtropical climates and maritime 

temperate climates (Cfa, Cfb), which includes FL, LA TX, GA, AL, MS, AR, OK, KS, MO, TN, SC, NC, VA, 

WV, KY; region 2: warm summer continental climates (Dfb), including ND, MN, WI, MI, PA, NY, CT, RI, 

MA, VT, NH, ME; region 3: hot summer continental climates (Dfa) with SD, NE, IA, IL, IN, OH; region 4: dry 

climates (BSk) (NM, AZ, NV); region 5: dry climates together with continental climate (Dfc, BSk) with MT, ID, 

WY, UT, CO; region 6: Mediterranean climates which includes CA, OR, WA (Csa, Csb)” (p. 10). 

20 These city-specific “shrunken” estimates were provided to EPA (see Zanobetti, 2009) . 21 One reason we selected the annual functions over the season-specific functions for the core analysis is that, 

while we can sum the season-specific mortality estimates across the four seasons, we cannot do the same for the 

upper and lower bounds of 95% confidence intervals around those estimates. To produce correct confidence 

bounds around annual mortality estimates based on seasonal functions, we would need the covariance matrix of 

the season-specific estimates, separately for each location, which we do not have. 22 The degree to which a city-specific estimate is “shrunken” towards the regional mean depends on the size of 

the standard error of the city-specific estimate relative to that of the regional mean estimate. The larger the cityspecific estimate relative to the regional mean estimate, the less shrinkage toward the regional mean. 
September 2009 48 Draft – Do Not Quote or Cite 

1 coefficient is not influened by data from other locations) with the advantages of a multi-city 

2 study (in which there is much greater statistical power to detect small effects). 

3 Since all models with PM2.5 in Zanobetti and Schwartz (2009) used the same lag 

4 structure (an average of same-day and the previous day’s PM2.5), there was no selection from 

5 among different C-R functions with different lag structures from this study. There were, 

6 however, both single-pollutant and two-pollutant models (with coarse PM). We selected the 

7 single-pollutant models, in part to avoid collinearity problems, and in part to be consistent 

8 with most of the other studies used in the risk assessment, which were single-pollutant 

9 studies. 

10 Bell et al. (2008) estimated log-linear models relating short-term exposure to PM2.5

11 and hospital admissions for cardiovascular and respiratory illnesses among people 65 and 

12 older, using Poisson regression, for each of 202 counties in the United States. They reported 

13 both annual and season-specific results, nationally and regionally (for four regions: 

14 Northeast, Southeast, Northwest, and Southwest), but not at the local (city-specific) level. All 

15 cardiovascular hospital admissions models were single-pollutant, 0-day lag models; for 

16 respiratory hospital admissions, both single-pollutant 0-day models and single-pollutant 2-day 

17 models were estimated. We used the regional, annual C-R functions in our core analysis 

(identifying the appropriate region for each of our 15 risk assessment locations).23 18 For 

19 respiratory hospital admissions (for the core analysis), we selected the 2-day lag models, 

20 based on evidence that for respiratory effects the strongest associations with PM exposure 

may be associated with longer lag periods (on the order of 2 days or more).24 21 We used the 

22 regional season-specific functions in a sensitivity analysis. 

23 We identified two studies that estimated C-R relationships between short-term 

24 exposure to PM2.5 and emergency department (ED) visits for cardiovascular and/or respiratory 

25 illnesses. (There were no multi-city studies for this category of health endpoint.) Tolbert et al. 

26 (2007) examined both cardiovascular and respiratory ED visits in Atlanta, GA, using single27 pollutant log-linear models with a 3-day moving average (0-day, 1-day, and 2-day lags) of 

28 PM2.5. Ito et al. (2007) estimated the relationship between short-term exposure to PM2.5 and 

29 ED visits for asthma in New York City (Manhattan). They estimated two single-pollutant 

30 models, one for the whole year and one for the period from April through August; in addition, 

31 they estimated several two-pollutant models for the period from April through August. We 

32 selected the single-pollutant model for the whole year for the core analysis, and we explored 

 23 The region into which each of the 202 counties in Bell et al. (2008) falls is given at: 

http://www.biostat.jhsph.edu/MCAPS/estimates-full.html. 24 The ISA states that, “Generally, recent studies of respiratory HAs that evaluate multiple lags, have found 

effect sizes to be larger when using longer moving averages or distributed lag models. For example, when 

examining HAs for all respiratory diseases among older adults, the strongest associations where observed when 

using PM concentrations 2 days prior to the HA.” (EPA, 2009, section 2.4.2.2). 
September 2009 49 Draft – Do Not Quote or Cite 

1 the impacts of using the annual versus the April-through-August model, as well as the single2 versus multi-pollutant models in sensitivity analyses. 

3 For the purpose of conducting a sensitivity analysis to show the impact of different lag 

4 structures, different modeling approaches, and single- versus two-pollutant models on 

5 estimates of the risks of premature mortality and hospital admissions associated with short6 term exposure to PM2.5, we selected Moolgavkar (2003). This study reported results for 

7 premature non-accidental, cardiovascular, and respiratory mortality and for cardiovascular 

8 and respiratory hospital admissions associated with short-term exposures to PM2.5 in Los 

9 Angeles, using several different lag structures and several different approaches to modeling 

10 the effects of weather and temporal variables. 

11 We selected Krewski et al. (2009) as our primary study for assessing the risks of 

12 premature mortality associated with long-term exposure to PM2.5 in our core analysis. This 

13 study is an extension of the ACS prospective cohort study (Pope et al., 2002), used in the 

14 previous PM risk assessment, extending the period of observation of the cohort to eighteen 

15 years (1982 – 2000). Krewski et al. (2009) considered mortality from all causes, as well as 

16 cardiopulmonary mortality, mortality from ischemic heart disease, and lung cancer mortality. 

17 They presented a variety of C-R functions, in an effort to show how the results changed with 

18 various changes to the method/model used. It was not apparent from review of the HEI 

19 report, that the authors of the study recommended any one of these as clearly superior to the 

20 others. For our core analysis, we selected what appeared to be two reasonable “standard” 

21 options – one corresponding to the earlier exposure period considered in the study, from 1979 

22 – 1983, and the other corresponding to the later exposure period, from 1999 – 2000. Both C23 R functions were based on follow-up of the cohort through 2000. Both used the standard Cox 

24 proportional hazards model, with 44 individual and 7 ecologic covariates. The relative risks 

for a 10 μg/m3 25 change in PM2.5 from which the PM2.5 coefficients were back-calculated were 

taken from Table 33 of Krewski et al. (2009).25 26 

 25 Note, EPA corresponded with the authors of the Krewski et al., 2009 study to obtain additional clarification 

regarding specific aspects of the study and associated results as presented in the HEI report (Krewski, 2009). In 

response to the EPA’s question of whether the study authors had a preference for a particular model (in the 

context of using that model and its hazard ratio(s) in risk assessment), the authors stated that they had “refrained 

from expressing a preference among the results for their use in quantitative risk assessment,” preferring to 

“explore several plausible statistical models that we have fit to the available data.” However, they go on to state 

that “...if one had to choose a model for use in practical applications involved in air quality management, one 

could argue that a random effects model (which accounts for apparent spatial autocorrelation in the data) might 

be preferable. A model that included ecological covariates, which has the effect of reducing the residual 

variation in mortality, might also be of interest. If forced to pick a single model for risk assessment applications 

in air quality management, our random effects model with ecological covariates might be selected” (Krewski, 

2009). Note, that if the study had provided a random effects model with ecological covariates (for both PM 

monitoring periods – 1979-1983 and 1999-2000), then we would have used those models in our core analysis. 

However, a random effects model with ecological covariates was only provided for the more recent PM 

monitoring period. Therefore, we opted to use the standard Cox model with ecological covariates, since this 
September 2009 50 Draft – Do Not Quote or Cite 

1 We selected several additional C-R functions from Krewski et al. (2009) to use in 

2 sensitivity analyses carried out in two risk assessment locations (Los Angeles and 

3 Philadelphia). These are described below. In addition, we used Krewski et al. (2000) 

4 [reanalysis of the Six Cities Study]. 

5 3.3.4 A summary of selected health endpoints, urban areas, studies, and 

6 concentration-response (C-R) functions used in the risk assessment 

7 A summary of the selected health endpoints, urban areas, and epidemiological studies 

8 used in the risk assessment is given below in Tables 3-5 and 3-6 for short-term and long-term 

9 exposure studies, respectively. A more detailed overview of the locations, health endpoints, 

10 studies, and C-R functions included in the core analysis is given in Table 3-7. An overview of 

11 the locations, health endpoints, studies, and C-R functions included in sensitivity analyses is 

12 given in Table 3-8. 

 

model form had been fitted for both PM monitoring periods. Note, however, that we did consider the random 

effects model form in the sensitivity analysis (see section 3.5.4). 
September 2009 51 Draft – Do No

Table 3-5. Locations, Health Endpoints, and Short-Term Exposure Studies Included in the PM

Assessment* 

Premature Mortality Hospital Admissions 

Urban Area Non-Accidental Cardiovascular Respiratory Cardiovascular Respiratory CardiovaAtlanta, GA Tolbert 

(2007

Baltimore, MDBirmingham, ALDallas, TXDetroit, MIFresno, CAHouston, TX

Zanobetti and 

Schwartz (2009)

Zanobetti and 

Schwartz (2009)

Zanobetti and 

Schwartz (2009)

Bell et al. (2008) Bell et al. (2008) 

Los Angeles, CA

Moolgavkar 

(2003)

Moolgavkar 

(2003)

Moolgavkar 

(2003)

New York, NY Philadelphia, PAPhoenix, AZPittsburgh, PASalt Lake City, UTSt. Louis, MOTacoma, WA

Zanobetti and 

Schwartz (2009) 

Zanobetti and 

Schwartz (2009) 

Zanobetti and 

Schwartz (2009) 

Bell et al. (2008) Bell et al. (2008) 

*Studies in italics are used only in sensitivity analyses. 
September 2009 52 Draft – Do No

Table 3-6. Locations, Health Endpoints, and Long-Term Exposure Studies Included in the PM

Assessment*

Premature Mortality Urban Area

All-Cause Cardiopulmonary Ischemic Heart Disease 

Atlanta, GABaltimore, MDBirmingham, ALDallas, TXDetroit, MIFresno, CAHouston, TXNew York, NY Phoenix, AZ Pittsburgh, PA Salt Lake City, UT St. Louis, MO Tacoma, WA 

Krewski et al. (2009) [extension 

of the ACS study] 

Krewski et al. (2009) [extension 

of the ACS study] 

Kre

Los Angeles, CA Philadelphia, PA

Krewski et al. (2009) [extension 

of the ACS study] 

Krewski et al. (2000) [reanalysis 

of the Six Cities Study]

Krewski et al. (2009) [extension 

of the ACS study] 

Krewski et al. (2000) [reanalysis 

of the Six Cities Study]

Krewski et al. (2009) [extension 

of the ACS study] 

Kre

Kre

*Studies in italics are used only in sensitivity analyses. 
September 2009 53 Draft – Do No

Table 3-7. Summary of Locations, Health Endpoints, Studies and Concentration-Response Fu

the Core Analysis.*

Risk 

Assessment 

Location

Counties Study/C-R Function Health Endpoint 

Zanobetti and Schwartz (2009)1 Short-term exposure non-accidental mortality Zanobetti and Schwartz (2009) 1 Short-term exposure cardiovascular mortality Zanobetti and Schwartz (2009) 1 Short-term exposure respiratory mortality Krewski et al. (2009) 2 Long-term exposure all-cause mortality Krewski et al. (2009) 2 Long-term exposure cardiopulmonary mortality Krewski et al. (2009) 2 Long-term exposure ischemic heart disease mortalit

Cobb, De Kalb, Fulton, Gwinnett 

Krewski et al. (2009) 2 Long-term exposure lung cancer mortality 

Bell et al. (2008)3 Cobb, DeKalb, Fulton, Short-term exposure HA (unscheduled), cardiovasc

Bell et al. (2008)3 Short-term exposure HA (unscheduled), respiratory 

Tolbert et al. (2007) Short-term exposure Emergency room (ED) visits, 

cardiovascular 

Atlanta 

Barrow, Bartow, Carroll, Cherokee, Clayton, Cobb, Coweta, DeKalb, Douglas, Fayette, Forsyth, Fulton, Gwinett, Henry, Newton, Paulding, Pickens, Rockdale, Spalding, Walton 

Tolbert et al. (2007) Short-term exposure Emergency room (ED) visits, 

respiratory 

Zanobetti and Schwartz (2009) Short-term exposure non-accidental mortality 

Baltimore Baltimore city, 

Baltimore county 

Zanobetti and Schwartz (2009) Short-term exposure cardiovascular mortality 
September 2009 54 Draft – Do No

Risk 

Assessment 

Location

Counties Study/C-R Function Health Endpoint 

Zanobetti and Schwartz (2009) Short-term exposure respiratory mortality Krewski et al. (2009) Long-term exposure all-cause mortality Krewski et al. (2009) Long-term exposure cardiopulmonary mortality Krewski et al. (2009) Long-term exposure ischemic heart disease mortaliKrewski et al. (2009) Long-term exposure lung cancer mortality Bell et al. (2008) Short-term exposure HA (unscheduled), cardiovascBell et al. (2008) Short-term exposure HA (unscheduled), respiratory Zanobetti and Schwartz (2009) Short-term exposure non-accidental mortality Zanobetti and Schwartz (2009) Short-term exposure cardiovascular mortality Zanobetti and Schwartz (2009) Short-term exposure respiratory mortality Krewski et al. (2009) Long-term exposure all-cause mortality Krewski et al. (2009) Long-term exposure cardiopulmonary mortality Krewski et al. (2009) Long-term exposure ischemic heart disease mortali

Blount, Jefferson, Shelby, St. Clair, Walker 

Krewski et al. (2009) Long-term exposure lung cancer mortality 

Bell et al. (2008) Short-term exposure HA (unscheduled), cardiovasc

Birmingham 

Jefferson 

Bell et al. (2008) Short-term exposure HA (unscheduled), respiratory 

Zanobetti and Schwartz (2009) Short-term exposure non-accidental mortality Zanobetti and Schwartz (2009) Short-term exposure cardiovascular mortality Zanobetti and Schwartz (2009) Short-term exposure respiratory mortality 

Dallas Dallas 

Krewski et al. (2009) Long-term exposure all-cause mortality 
September 2009 55 Draft – Do No

Risk 

Assessment 

Location

Counties Study/C-R Function Health Endpoint 

Krewski et al. (2009) Long-term exposure cardiopulmonary mortality Krewski et al. (2009) Long-term exposure ischemic heart disease mortaliKrewski et al. (2009) Long-term exposure lung cancer mortality Bell et al. (2008) Short-term exposure HA (unscheduled), cardiovascBell et al. (2008) Short-term exposure HA (unscheduled), respiratory Zanobetti and Schwartz (2009) Short-term exposure non-accidental mortality Zanobetti and Schwartz (2009) Short-term exposure cardiovascular mortality Zanobetti and Schwartz (2009) Short-term exposure respiratory mortality Krewski et al. (2009) Long-term exposure all-cause mortality Krewski et al. (2009) Long-term exposure cardiopulmonary mortality Krewski et al. (2009) Long-term exposure ischemic heart disease mortaliKrewski et al. (2009) Long-term exposure lung cancer mortality Bell et al. (2008) Short-term exposure HA (unscheduled), cardiovasc

Detroit Wayne 

Bell et al. (2008) Short-term exposure HA (unscheduled), respiratory 

Zanobetti and Schwartz (2009) Short-term exposure non-accidental mortality Zanobetti and Schwartz (2009) Short-term exposure cardiovascular mortality Zanobetti and Schwartz (2009) Short-term exposure respiratory mortality Krewski et al. (2009) Long-term exposure all-cause mortality Krewski et al. (2009) Long-term exposure cardiopulmonary mortality Krewski et al. (2009) Long-term exposure ischemic heart disease mortali

Fresno Fresno 

Krewski et al. (2009) Long-term exposure lung cancer mortality 
September 2009 56 Draft – Do No

Risk 

Assessment 

Location

Counties Study/C-R Function Health Endpoint 

Bell et al. (2008) Short-term exposure HA (unscheduled), cardiovascBell et al. (2008) Short-term exposure HA (unscheduled), respiratory Zanobetti and Schwartz (2009) Short-term exposure non-accidental mortality Zanobetti and Schwartz (2009) Short-term exposure cardiovascular mortality Zanobetti and Schwartz (2009) Short-term exposure respiratory mortality Krewski et al. (2009) Long-term exposure all-cause mortality Krewski et al. (2009) Long-term exposure cardiopulmonary mortality Krewski et al. (2009) Long-term exposure ischemic heart disease mortaliKrewski et al. (2009) Long-term exposure lung cancer mortality Bell et al. (2008) Short-term exposure HA (unscheduled), cardiovasc

Houston Harris 

Bell et al. (2008) Short-term exposure HA (unscheduled), respiratory 

Zanobetti and Schwartz (2009) Short-term exposure non-accidental mortality Zanobetti and Schwartz (2009) Short-term exposure cardiovascular mortality Zanobetti and Schwartz (2009) Short-term exposure respiratory mortality Krewski et al. (2009) Long-term exposure all-cause mortality Krewski et al. (2009) Long-term exposure cardiopulmonary mortality Krewski et al. (2009) Long-term exposure ischemic heart disease mortaliKrewski et al. (2009) Long-term exposure lung cancer mortality Bell et al. (2008) Short-term exposure HA (unscheduled), cardiovasc

Los Angeles Los Angeles 

Bell et al. (2008) Short-term exposure HA (unscheduled), respiratory 
September 2009 57 Draft – Do No

Risk 

Assessment 

Location

Counties Study/C-R Function Health Endpoint 

Zanobetti and Schwartz (2009) Short-term exposure non-accidental mortality Zanobetti and Schwartz (2009) Short-term exposure cardiovascular mortality Zanobetti and Schwartz (2009) Short-term exposure respiratory mortality Krewski et al. (2009) Long-term exposure all-cause mortality Krewski et al. (2009) Long-term exposure cardiopulmonary mortality Krewski et al. (2009) Long-term exposure ischemic heart disease mortaliKrewski et al. (2009) Long-term exposure lung cancer mortality Bell et al. (2008) Short-term exposure HA (unscheduled), cardiovasc

Kings, New York City (Manhattan), Queens, Richmond, Bronx 

Bell et al. (2008) Short-term exposure HA (unscheduled), respiratory 

New York 

New York City (Manhattan) 

Ito et al. (2007) Short-term exposure Emergency room (ED) visits, 

asthma 

Zanobetti and Schwartz (2009) Short-term exposure non-accidental mortality Zanobetti and Schwartz (2009) Short-term exposure cardiovascular mortality Zanobetti and Schwartz (2009) Short-term exposure respiratory mortality Krewski et al. (2009) Long-term exposure all-cause mortality Krewski et al. (2009) Long-term exposure cardiopulmonary mortality Krewski et al. (2009) Long-term exposure ischemic heart disease mortaliKrewski et al. (2009) Long-term exposure lung cancer mortality Bell et al. (2008) Short-term exposure HA (unscheduled), cardiovasc

Philadelphia Philadelphia 

Bell et al. (2008) Short-term exposure HA (unscheduled), respiratory 

Phoenix Maricopa Zanobetti and Schwartz (2009) Short-term exposure non-accidental mortality 
September 2009 58 Draft – Do No

Risk 

Assessment 

Location

Counties Study/C-R Function Health Endpoint 

Zanobetti and Schwartz (2009) Short-term exposure cardiovascular mortality Zanobetti and Schwartz (2009) Short-term exposure respiratory mortality Krewski et al. (2009) Long-term exposure all-cause mortality Krewski et al. (2009) Long-term exposure cardiopulmonary mortality Krewski et al. (2009) Long-term exposure ischemic heart disease mortaliKrewski et al. (2009) Long-term exposure lung cancer mortality Bell et al. (2008) Short-term exposure HA (unscheduled), cardiovascBell et al. (2008) Short-term exposure HA (unscheduled), respiratory Zanobetti and Schwartz (2009) Short-term exposure cardiovascular mortality Zanobetti and Schwartz (2009) Short-term exposure respiratory mortality Krewski et al. (2009) Long-term exposure all-cause mortality Krewski et al. (2009) Long-term exposure cardiopulmonary mortality Krewski et al. (2009) Long-term exposure ischemic heart disease mortaliKrewski et al. (2009) Long-term exposure lung cancer mortality Bell et al. (2008) Short-term exposure HA (unscheduled), cardiovasc

Pittsburgh Allegheny 

Bell et al. (2008) Short-term exposure HA (unscheduled), respiratory 

Zanobetti and Schwartz (2009) Short-term exposure cardiovascular mortality Zanobetti and Schwartz (2009) Short-term exposure respiratory mortality Krewski et al. (2009) Long-term exposure all-cause mortality Krewski et al. (2009) Long-term exposure cardiopulmonary mortality 

Salt Lake City Salt Lake 

Krewski et al. (2009) Long-term exposure ischemic heart disease mortali
September 2009 59 Draft – Do No

Risk 

Assessment 

Location

Counties Study/C-R Function Health Endpoint 

Krewski et al. (2009) Long-term exposure lung cancer mortality Bell et al. (2008) Short-term exposure HA (unscheduled), cardiovascBell et al. (2008) Short-term exposure HA (unscheduled), respiratory Zanobetti and Schwartz (2009) Short-term exposure cardiovascular mortality Zanobetti and Schwartz (2009) Short-term exposure respiratory mortality Krewski et al. (2009) Long-term exposure all-cause mortality Krewski et al. (2009) Long-term exposure cardiopulmonary mortality Krewski et al. (2009) Long-term exposure ischemic heart disease mortali

Jeffferson, Madison (IL), St. Louis, St. Louis city, St. Clair (IL)

Krewski et al. (2009) Long-term exposure lung cancer mortality 

Bell et al. (2008) Short-term exposure HA (unscheduled), cardiovasc

St. Louis 

Madison (IL), St. Louis, St. Louis city, St. Clair (IL) Bell et al. (2008) Short-term exposure HA (unscheduled), respiratory 

Zanobetti and Schwartz (2009) Short-term exposure cardiovascular mortality Zanobetti and Schwartz (2009) Short-term exposure respiratory mortality Krewski et al. (2009) Long-term exposure all-cause mortality Krewski et al. (2009) Long-term exposure cardiopulmonary mortality Krewski et al. (2009) Long-term exposure ischemic heart disease mortaliKrewski et al. (2009) Long-term exposure lung cancer mortality Bell et al. (2008) Short-term exposure HA (unscheduled), cardiovasc

Tacoma Pierce 

Bell et al. (2008) Short-term exposure HA (unscheduled), respiratory 

*All C-R functions in the core analysis are single-pollutant, log-linear models; all are for a full year. The exposure metric for all shorfunctions is the 24-hr average; the exposure metric for all long-term exposure C-R functions is the annual average. 1 This is a multi-city study; city-specific estimates “shrunken” towards the mean across all cities in a region were supplied to EPA (Za2 Two C-R functions were used for the core analysis – one corresponding to the earlier exposure period, from 1979 – 1983, and the ot

later exposure period, from 1999 – 2000. Both C-R functions were based on follow-up of the cohort through 2000. Both used the st
September 2009 60 Draft – Do No

hazards model, with 44 individual and 7 ecologic covariates. The relative risks for a 10 μg/m3 change in PM2.5 from which the PM2.5 

calculated were taken from Table 33 of Krewski et al. (2009). 

3 This study estimated four regional C-R functions – for the Northeast, Southeast, Northwest, and Southwest – for each health endpoi

assessment location, we used the regional C-R function for the region containing the risk assessment location. The designation of coufour regions can be found at http://www.biostat.jhsph.edu/MCAPS/estimates-full.html . 
September 2009 61 Draft – Do No

Table 3-8. Summary of Locations, Health Endpoints, Studies and Concentration-Response Fu

 Sensitivity Analyses. 

Sensitivity Analysis Study/C-R Function Health Endpoint** 

Single-Factor Sensitivity Analyses: Impact of using different model choices – fixed effects log-linear vs. random effects log-linear vs. random effects log-log C-R function* 

random effects log-linear: Krewski et al. (2009) [Table 9, "Autocorrelation at MSA and ZCA levels" group - "MSA & Diff" row] random effects log-log: Krewski et al. (2009) [Table 11, "MSA and DIFF" rows] 

All-cause, cardiopulmonary, ischemic heart disease, and lung cancer mortaliassociated with long-term exposure 

Impact of estimating risks down to PRB rather than down to LML 

Krewski et al. (2009) – C-R functions for each of two exposure periods 

Long-term exposure all-cause mortali

Impact of C-R function from alternative long-term exposure study 

Krewski et al. (2000) [reanalysis of the Harvard Six Cities study] 

All-cause, cardiovascular, respiratorylung cancer mortality associated with long-term exposure 

Impact of using alternative hybrid rollback approach Krewski et al. (2009) All-cause mortality associated with 

long-term exposure 

Impact of using season-specific C-R functions (vs. an annual C-R function) 

Zanobetti and Schwartz (2009) – seasonal functions vs. annual function 

Non-accidental mortality, cardiovascular mortality, respiratory mortality associated with short-term exposure 

Impact of using season-specific C-R functions (vs. an annual C-R function) 

Bell et al. (2008) – seasonal functions vs. annual function 

HA (unscheduled), cardiovascular and respiratory, associated with short-term 

exposure

Impact of using an annual C-R function (applied to the whole year) vs. a seasonal function for April through August (applied only to that period) (using a single pollutant model). 

Ito et al. (2007) Asthma ED visits 

Impact of model selection (e.g., log-linear GAM with 30 df; log-linear GAM with 100 df; and log-linear GLM with 100 df) 

Moolgavkar (2003) Non-accidental and cardiovascular 

mortality; and cardiovascular and COPD+ HA associated with short-ter
September 2009 62 Draft – Do No

Sensitivity Analysis Study/C-R Function Health Endpoint** 

exposure 

Impact of lag structure (0-day, 1-day, 2-day) Moolgavkar (2003) Non-accidental and cardiovascular an

COPD+ HA associated with short-terexposure 

Impact of single- vs. multi-pollutant models (PM2.5 with CO) 

Moolgavkar (2003) Non-accidental and cardiovascular 

mortality; and cardiovascular and COPD+ HA associated with short-terexposure 

Impact of using alternative hybrid rollback approach Zanobetti and Schwartz (2009) Non-accidental mortality associated 

with short-term exposure 

Multi-Factor Sensitivity Analyses: Impact of using a fixed effects log-linear vs. a random effects log-log model, estimating incidence down to the lowest measured level (LML) in the study vs. down to PRB, and using a proportional vs. hybrid rollback to estimate incidence associated with long-term exposure to PM2.5 concentrations that just meet the current 

standards 

 All-cause and ischemic heart disease 

mortality associated with long-term exposure 

Impact of using season-specific vs. all-year C-R functions and proportional vs. hybrid rollbacks to estimate incidence associated with short-term exposure to PM2.5 concentrations that just meet the current 

standards 

Zanobetti and Schwartz (2009) Non-accidental mortality associated 

with short-term exposure 

*This “single-factor” sensitivity analysis is actually two factors – first the change from a fixed effects log-linear model to a random ef

and then the change from a random effects log-linear model to a random effects log-log model. These were conbined into a single sen

because Krewski et al. (2009) did not present the results of a fixed effects log-log model (to compare to the core analysis fixed effects 

**”HA” = hospital admissions, “ED” = emergency department visits, “COPD+” = chronic obstructive pulmona
September 2009 63 Draft – Do Not Quote or Cite 

1 3.4 BASELINE HEALTH EFFECTS INCIDENCE DATA 

2 As noted in section 3.2.1 above, the form of C-R function most commonly used in 

3 epidemiological studies on PM, shown in equation (1), is log-linear. To estimate the 

4 change in incidence of a health endpoint associated with a given change in PM2.5 

5 concentrations using this form of C-R function requires the baseline incidence (often 

6 calculated as the baseline incidence rate times the population) of the health endpoint, that 

7 is, the number of cases per unit time (e.g., per year) in the location before a change in 

8 PM2.5 air quality (denoted y0 in equations 3 and 4). 

9 Incidence rates express the occurrence of a disease or event (e.g., asthma episode, 

10 death, hospital admission) in a specific period of time, usually per year. Rates are 

11 expressed either as a value per population group (e.g., the number of cases in 

12 Philadelphia County) or a value per number of people (e.g., the number of cases per 

13 10,000 residents in Philadelphia County), and may be age- and sex-specific. Incidence 

14 rates vary among geographic areas due to differences in population characteristics (e.g, 

15 age distribution) and factors promoting illness (e.g., smoking, air pollution levels). 

16 3.4.1 Data sources 

17 3.4.1.1 Mortality 

18 We obtained individual-level mortality data for 2006 for the whole United States 

19 from the Centers for Disease Control (CDC), National Center for Health Statistics 

20 (NCHS). The data are compressed into a CD-ROM, which contains death information 

21 for each decedent, including residence county FIPS, age at death, month of death, and 

22 underlying causes (ICD-10 codes). The detailed mortality data allow us to generate 

23 cause-specific death counts at the county level for selected age groups. Below we 

24 describe how we generated the county-level death counts. 

25 3.4.1.2 Hospital admission and emergency department visits 

26 For hospital admissions (HA) and emergency department (ED) visits, there are 

27 multiple data sources: 

28  Healthcare Cost and Utilization Project (HCUP) Central Distributor. HCUP 

29 is a family of health care databases developed through a Federal-State-Industry 

30 partnership and sponsored by the Agency for Healthcare Research and Quality 

31 (AHRQ). The HCUP databases are based on the data collection efforts of data 

32 organizations in participating states. We used two HCUP databases: the State 

33 Inpatient Database (SID) and the State Emergency Department Database (SEDD) 

34 respectively. SID/SEDD include detailed HA/ED information for each discharge, 

35 including patient county FIPS, age, admission type (e.g., emergent, urgent), 
September 2009 64 Draft – Do Not Quote or Cite 

1 admission/discharge season, and principle diagnosis (ICD-9 codes). The HCUP 

2 databases can be purchased from the HCUP Central Distributor, although not all 

3 participant states release the data to the Central Distributor. 

4  HCUP State Partners. For those HCUP participating states that don’t release 

5 their data to the Central Distributor, we contacted the HCUP state partners to 

6 obtain the HA and/or ED data. 

7  Communication with the author(s) of selected epidemiological studies. The 

8 ED data for Atlanta in 2004 were sent to EPA by one of the authors of Tolbert et 

9 al. (2007). 

10 Table 3-9 shows the states for which we obtained data from the HCUP Central 

11 Distributor and the HCUP State Partners. The data are at the discharge level if not 

12 otherwise noted, and the data year is 2007 for all the states in the table. The column “PM 

13 RA Location” indicates the selected risk assessment location(s) where the incidence rate 

14 is applied. 

15 The necessary baseline incidence data were not available for Atlanta, 

16 Birmingham, Philadelphia, Pittsburgh and St. Louis. Therefore, for each of these five 

17 risk assessment locations EPA instead used the baseline incidence rate for a designated 

18 surrogate location. Surrogate locations were chosen if they were deemed to be 

19 sufficiently similar to the urban area whose baseline incidence data were not available. 

20 Surrogate locations are noted in Table 3-9. 

21 Table 3-9. Sources of Hospital Admissions (HA) and Emergency Department 

22 (ED) Visit Data. 

States 

HCUP 

Central 

Distributor 

HCUP State 

Partner 

PM RA 

Location Notes 

Arizona HA data -- Phoenix 

California NA* HA data Fresno, Los 

Angeles 

 Due to privacy concerns, CA state 

agency provided county level data. 

Illinois NA HA data St. Louis 

1. Due to privacy concerns, IL state 

agency provided county level data. 

2. Two IL counties (Madison and St. 

Clair) serve as the surrogate for the 

St. Louis metropolitan region. 

Maryland HA data -- Baltimore, 

Philadelphia 

Baltimore serves as the surrogate for 

Philadelphia. 

Michigan HA data -- Detroit 

New York NA HA and ED data New York, 

Pittsburgh 

 Buffalo, NY serves as the surrogate 

for Pittsburgh. 

North Carolina HA data -- Atlanta and 

Birmingham 

Charlotte, NC serves as the surrogate 

for both Atlanta and Birmingham. 

Texas NA HA data Dallas, 

Houston 

Utah HA data -- Salt Lake 
September 2009 65 Draft – Do Not Quote or Cite 

States 

HCUP 

Central 

Distributor 

HCUP State 

Partner 

PM RA 

Location Notes 

City 

Washington HA data -- Tacoma 

1 *NA denotes “not available, or not available with all variables required for our analysis. If data were not 

2 available from the HCUP Central Distributor, we contacted the HCUP State Partner. 

3 3.4.1.3 Populations 

4 To calculate baseline incidence rate, in addition to the health baseline incidence 

5 data we also need the corresponding population. We obtained population data from the 

6 U.S. Census Bureau (http://www.census.gov/popest/counties/asrh/). These data, released 

7 on May 14, 2009, are the population estimates of the resident populations by selected age 

8 groups and sex for counties in each U.S. state from 2000 to 2008. We used 2007 

9 populations for calculating most incidence rates except for the ED visit rate in Atlanta. 

10 Because the ED visit data obtained from the authors of Tolbert et al. (2007) are for 2004, 

11 we used 2004 population estimates for the 20-county Metropolitan area used in the 

12 Tolbert et al. study for the Atlanta area to calculate the ED incidence rates to be applied 

13 when using that study in the risk assessment; we then applied the 2004 rates to the 2007 

14 population, assuming the ED incidence rates in Atlanta didn’t change significantly from 

15 2004 to 2007. The sizes of the populations in the assessment locations that are relevant 

16 to the risk assessment (i.e., the populations for which the PM2.5 C-R functions are 

17 estimated and to which the baseline incidences refer) are given in Table 3-10. 

18 
September 2009 66 Draft – Do Not 

Table 3-10. Relevant Population Sizes for PM Risk Assessment Locations. 

Population (Year 2006 and 2007)* 

City Counties All Ages Ages $30 

2006 2007 2006 2007 

Atlanta, GA - 1 Cobb, De Kalb, Fulton, Gwinnett 3,126,000 3,198,000 1,817,000 1,865,000 23Atlanta, GA - 2 Cobb, De Kalb, Fulton 2,376,000, 2,421,000 1,400,000 1,433,000 19Atlanta, GA - 3 20-County MSA** 4,975,000 5,123,000 2,831,000 2,918,000 39Baltimore, MD Baltimore city, Baltimore county 1,429,000 1,426,000 849,000 848,000 19Birmingham, AL - 1 Blount, Jefferson, Shelby, St. Clair, 

Walker 1,037,000 1,044,000 619,000 625,000 13

Birmingham, AL - 2 Jefferson 660,000 659,000 397,000 397,000 8Dallas, TX Dallas 2,338,000 2,367,000 1,285,000 1,308,000 19Detroit, MI Wayne 2,012,000 1,985,000 1,176,000 1,168,000 23Fresno, CA Fresno 886,000 899,000 444,000 452,000 8Houston, TX Harris 3,876,000 3,936,000 2,097,000 2,139,000 29Los Angeles, CA Los Angeles 9,881,000 9,879,000 5,544,000 5,579,000 1,0New York, NY - 1 Kings, New York City (Manhattan), 

Queens, Richmond, Bronx 8,251,000 8,275,000 4,940,000 4,975,000 1,0

New York, NY - 2 New York city (Manhattan) 1,613,000 1,621,000 1,061,000 1,074,000 20Philadelphia, PA Philadelphia 833,000 1,450,000 833,000 833,000 18Phoenix, AZ Maricopa 3,779,000 3,880,000 2,103,000 2,167,000 41Pittsburgh, PA Allegheny 1,225,000 1,219,000 790,000 786,000 20Salt Lake City, UT Salt Lake 991,000 1,010,000 504,000 517,000 8St. Louis, MO - 1 Jefferson, Madison (IL), St. Louis, St. 

Louis city, St. Clair (IL) 2,093,000 2,091,000 1,259,000 1,261,000 27
September 2009 67 Draft – Do Not 

Population (Year 2006 and 2007)* 

City Counties All Ages Ages $30 

2006 2007 2006 2007 

St. Louis, MO - 2 Madison (IL), St. Louis, St. Louis city, 

St. Clair (IL) 1,879,000 1,875,000 1,134,000 1,134,000 25

Tacoma, WA Pierce 764,000 773,000 437,000 444,000 7

* Not all populations listed in the table were used for calculating the incidence rates. As noted above, the population year needs to madata and the population age group needs to match what is used in the epidemiological studies. In addition, 2004 population (all ages) is Atlanta-3, which is 4,663,946. Populations in this table are rounded to the nearest 1,000. ** The 20 counties are Barrow, Bartow, Carroll, Cherokee, Clayton, Cobb, Coweta, DeKalb, Douglas, Fayette, Forsyth, Fulton, Gwinett, Henry, New

Rockdale, Spalding, and Walton. 
September 2009 68 Draft – Do Not Quote or Cite 

1 3.4.2 Calculation of baseline incidence rates 

2 To calculate a baseline incidence rate to be used with a C-R function from a given 

3 study, we matched the counties, age groupings, and ICD codes used in that study. For 

4 example, Bell et al. (2008) designated Dallas, TX as Dallas County and estimated a C-R 

5 function for ICD-9 codes 490–492, 464–466, and 480–487 (respiratory HA) among ages 

6 65 and up; we therefore selected only those HA records that had corresponding ICD 

7 codes for ages 65 and up in Dallas County and also selected the population for the same 

8 age group in the same county. The incidence rate is simply the ratio of the selected HA 

9 count to the population. The same procedure was used to calculate baseline incidence 

rates for all of the risk assessment locations.26 10 

11 If a C-R function was estimated for a specific season, we selected only those HA 

12 records within that season. The season definitions are: winter (December, January, and 

13 February), spring (March, April, and May), summer (June, July, and August) and fall 

14 (September, October, and November). Note that the HA data for some states didn’t 

15 include information about admission season but only discharge season or discharge 

16 quarter. The admission season was then approximated using discharge season or 

discharge quarter.27 17 

18 Some studies (e.g., Bell et al., 2008) look at the unscheduled HAs only, so we 

19 excluded scheduled admissions from the analyses to match the study. A HA is 

20 unscheduled if the admission type is emergency or urgent. 

21 The baseline mortality rates are given in Table 3-11. The baseline HA and ED 

22 visit rates are given in Table 3-12. 

23 

24 

25 

26 

 26 For Atlanta, Birmingham, Philadelphia, Pittsburgh and St. Louis, the HA data are not available. We 

calculated the hospital admission rates for the surrogates cities. These cities are listed in Table 3-7. 

27 Based on communication with the HCUP state partner in Texas, patients are normally admitted and 

discharged in the same season. 
September 2009 69 Draft – Do Not Qu

Table 3-11. Baseline Mortality Rates (Deaths per 100,000 Relevant Population per Year) for 2006 for PM R

 Locations.* 

Type of Mortality (ICD-10 or ICD-9 Codes) 

City Age Group All-Cause 

Non-accidental 

(A00-R99) 

Cardiovascular 

(I01-I59) 

Respiratory 

(J00-J99) 

Cardiopulmonary 

(401-440, 460-

519) 

Ischemic 

Heart 

Disease 

(410-414) 

Lu

Ca

(1

Atlanta, GA - 1 All ages --- 480 120 41 --- --- -Atlanta, GA - 1 ≥ 30 860 --- --- --- 330 89 5Atlanta, GA - 2 --- --- --- --- --- --- --- -Atlanta, GA - 3 --- --- --- --- --- --- --- -Baltimore, MD All ages --- 950 270 85 --- --- -Baltimore, MD ≥ 30 1,700 --- --- --- 690 300 1Birmingham, AL - 1 All ages --- 920 260 85 --- --- -Birmingham, AL - 1 ≥ 30 1,600 --- --- --- 680 190 1Birmingham, AL - 2 --- --- --- --- --- --- --- -Dallas, TX All ages --- 540 150 48 --- --- -Dallas, TX ≥ 30 1,020 --- --- --- 420 170 6Detroit, MI All ages --- 850 300 67 --- --- -Detroit, MI ≥ 30 1,500 --- --- --- 700 360 1Fresno, CA All ages --- 620 190 67 --- --- -Fresno, CA ≥ 30 1,300 --- --- --- 590 260 6Houston, TX All ages --- 480 130 37 --- --- -Houston, TX ≥ 30 920 --- --- --- 370 150 5Los Angeles, CA All ages --- 560 190 57 --- --- -Los Angeles, CA ≥ 30 1,030 --- --- --- 510 250 5New York, NY - 1 All ages --- 630 270 52 --- --- -
September 2009 70 Draft – Do Not Qu

Type of Mortality (ICD-10 or ICD-9 Codes) 

City Age Group All-Cause 

Non-accidental 

(A00-R99) 

Cardiovascular 

(I01-I59) 

Respiratory 

(J00-J99) 

Cardiopulmonary 

(401-440, 460-

519) 

Ischemic 

Heart 

Disease 

(410-414) 

Lu

Ca

(1

New York, NY - 1 ≥ 30 1,0800 --- --- --- 580 380 5New York, NY - 2 --- --- --- --- --- --- --- -Philadelphia, PA All ages --- 970 280 83 --- --- -Philadelphia, PA ≥ 30 1,700 --- --- --- 720 300 1Phoenix, AZ All ages --- 600 160 67 --- --- -Phoenix, AZ ≥ 30 1,100 --- --- --- 470 220 6Pittsburgh, PA All ages --- 1,090 330 96 --- --- -Pittsburgh, PA ≥ 30 1,800 --- --- --- 770 350 1Salt Lake City, UT All ages --- 480 110 45 --- --- -Salt Lake City, UT ≥ 30 980 --- --- --- 350 101 3St. Louis, MO - 1 All ages --- 870 270 83 --- --- -St. Louis, MO - 1 ≥ 30 1,500 --- --- --- 680 320 1St. Louis, MO - 2 --- --- --- --- --- --- --- -Tacoma, WA All ages --- 660 190 66 --- --- -Tacoma, WA ≥ 30 1,200 --- --- --- 510 240 8National All ages 810 750 220 76 340 140 5National ≥ 30 1,300 1,300 370 130 580 240 9

* Figures in this table are rounded to a two-integer level of precision. 
September 2009 71 Draft – Do Not Qu

Table 3-12. Baseline Hospital Admission (HA) and Emergency Department (ED) Rates (Admissions

Relevant Population per Year) for 2007 for PM Risk Assessment Locations.* 

* Figures in this table are rounded to a two-integer level of precision. ** These are 2004 incidence rates because Tolbert et al. (2007) provided 2004 ED visit data in a 20-county delineation of Atlanta. Howe

applied to the appropriate year population in the risk assessment.

Health Endpoints (ICD-9 Codes) 

City Age Group 

HA, cardiovascular (390-

429) 

HA (unscheduled), 

cardiovascular(426

–429, 430–438, 

410–414, 440–449) 

HA, COPD 

(490-496) 

HA (unscheduled), 

respiratory (490–492, 

464–466, 480–487) 

ED visits, 

cardiovascular (410–

414, 427, 428, 433–

437, 440, 443–445, 

451–453) 

ED visits

(460–465, 

466.19, 477

493, 496, 7

Atlanta, GA - 1 --- --- --- --- --- --- Atlanta, GA - 2 ≥ 65 --- 5,700 --- 2,020 --- Atlanta, GA - 3 All ages --- --- --- --- 690** 26Baltimore, MD ≥ 65 --- 8,600 --- 2,600 --- Birmingham, AL - 1 --- --- --- --- --- --- Birmingham, AL - 2 ≥ 65 --- 5,700 --- 2,020 --- Dallas, TX ≥ 65 --- 5,000 --- 2,000 --- Detroit, MI ≥ 65 --- 8,800 --- 3,000 --- Fresno, CA ≥ 65 --- 5,600 --- 2,100 --- Houston, TX ≥ 65 --- 5,900 --- 2,200 --- Los Angeles, CA All ages --- --- 223 --- --- Los Angeles, CA ≥ 65 5,500 5,500 --- 2,000 --- New York, NY - 1 ≥ 65 --- 6,400 --- 2,030 --- New York, NY - 2 All ages --- --- --- --- --- Philadelphia, PA ≥ 65 --- 8,600 --- 2,600 --- Phoenix, AZ ≥ 65 --- 5,020 --- 1,600 --- Pittsburgh, PA ≥ 65 --- 6,100 --- 1,900 --- Salt Lake City, UT ≥ 65 --- 3,030 --- 1,200 --- St. Louis, MO - 1 --- --- --- --- --- --- St. Louis, MO - 2 ≥ 65 --- 5,600 --- 2,600 --- Tacoma, WA ≥ 65 --- 4,500 --- 1,600 --- 
September 2009 72 Draft – Do Not Quote or Cite 

1 3.5 ADDRESSING UNCERTAINTY AND VARIABILITY 

2 3.5.1 Overview 

3 An important component of a population health risk assessment is the 

4 characterization of both uncertainty and variability. Variability refers to the 

5 heterogeneity of a variable of interest within a population or across different populations. 

6 For example, populations in different regions of the country may have different behavior 

7 and activity patterns (e.g., air conditioning use, time spent indoors) that affect their 

8 exposure to ambient PM and thus the population health response. The composition of 

9 populations in different regions of the country may vary in ways that can affect the 

10 population response to exposure to PM – e.g., two populations exposed to the same levels 

11 of PM might respond differently if one population is older than the other. In addition, the 

12 composition of the PM to which different populations are exposed may differ, with 

13 different levels of toxicity and thus different population responses. Variability is inherent 

14 and cannot be reduced through further research. Refinements in the design of a 

15 population risk assessment are often focused on more completely characterizing 

16 variability in key factors affecting population risk – e.g., factors affecting population 

17 exposure or response – in order to produce risk estimates whose distribution adequately 

18 characterizes the distribution in the underlying population(s). 

19 Uncertainty refers to the lack of knowledge regarding the actual values of inputs 

20 to an analysis. Models are typically used in analyses, and there is uncertainty about the 

21 true values of the parameters of the model (parameter uncertainty) – e.g., the value of the 

22 coefficient for PM2.5 in a C-R function. There is also uncertainty about the extent to 

23 which the model is an accurate representation of the underlying physical systems or 

24 relationships being modeled (model uncertainty) – e.g., the shapes of C-R functions. In 

25 addition, there may be some uncertainty surrounding other inputs to an analysis due to 

26 possible measurement error—e.g., the values of daily PM2.5 concentrations in a risk 

27 assessment location, or the value of the baseline incidence rate for a health effect in a 

28 population. In any risk assessment, uncertainty is, ideally, reduced to the maximum 

29 extent possible through improved measurement of key variables and ongoing model 

30 refinement. However, significant uncertainty often remains, and emphasis is then placed 

31 on characterizing the nature of that uncertainty and its impact on risk estimates. The 

32 characterization of uncertainty can be both qualitative and, if a sufficient knowledgebase 

33 is available, quantitative. 

34 The selection of urban study areas for the PM2.5 risk assessment was designed to 

35 cover the range of PM2.5-related risk experienced by the U.S. population and, in general, 
September 2009 73 Draft – Do Not Quote or Cite 

1 to adequately reflect the inherent variability in those factors affecting the public health 

2 impact of PM2.5 exposure. Sources of variability reflected in the risk assessment design 

3 are discussed in section 3.5.2, along with a discussion of those sources of variability 

4 which are not fully reflected in the risk assessment and consequently introduce 

5 uncertainty into the analysis. 

6 The characterization of uncertainty associated with risk assessment is often 

7 addressed in the regulatory context using a tiered approach in which progressively more 

8 sophisticated methods are used to evaluate and characterize sources of uncertainty 

9 depending on the overall complexity of the risk assessment (WHO, 2008). Guidance 

10 documents developed by EPA for assessing air toxics-related risk and Superfund Site 

11 risks (USEPA, 2004b and 2001, respectively) as well as recent guidance from the World 

12 Health Organization (WHO, 2008) specify multi-tiered approaches for addressing 

13 uncertainty. 

14 The WHO guidance presents a four-tiered approach, where the decision to 

15 proceed to the next tier is based on the outcome of the previous tier’s assessment. The 

16 four tiers described in the WHO guidance include: 

17  Tier 0 – recommended for routine screening assessments, uses default uncertainty 

18 factors (rather than developing site-specific uncertainty characterizations); 

19  Tier 1 – the lowest level of site-specific uncertainty characterization, involves 

20 qualitative characterization of sources of uncertainty (e.g., a qualitative 

21 assessment of the general magnitude and direction of the effect on risk results); 

22  Tier 2 – site-specific deterministic quantitative analysis involving sensitivity 

23 analysis, interval-based assessment, and possibly probability bound (high- and 

24 low-end) assessment; and 

25  Tier 3 – uses probabilistic methods to characterize the effects on risk estimates of 

26 sources of uncertainty, individually and combined. 

27 With this four-tiered approach, the WHO framework provides a means for 

28 systematically linking the characterization of uncertainty to the sophistication of the 

29 underlying risk assessment. Ultimately, the decision as to which tier of uncertainty 

30 characterization to include in a risk assessment will depend both on the overall 

31 sophistication of the risk assessment and the availability of information for characterizing 

32 the various sources of uncertainty. EPA staff has used the WHO guidance as a 

33 framework for developing the approach used for characterizing uncertainty in this risk 

34 assessment. 

35 The overall analysis in the PM NAAQS risk assessment is relatively complex, 

36 thereby warranting consideration of a full probabilistic (WHO Tier 3) uncertainty 
September 2009 74 Draft – Do Not Quote or Cite 

1 analysis. However, limitations in available information prevent this level of analysis 

2 from being completed at this time. In particular, the incorporation of uncertainty related 

3 to key elements of C-R functions (e.g., competing lag structures, alternative functional 

4 forms, etc.) into a full probabilistic WHO Tier 3 analysis would require that probabilities 

5 be assigned to each competing specification of a given model element (with each 

6 probability reflecting a subjective assessment of the probability that the given 

7 specification is the “correct” description of reality). However, for many model elements 

8 there is insufficient information on which to base these probabilities. One approach that 

9 has been taken in such cases is expert elicitation; however, this approach is resource- and 

10 time-intensive and consequently, it was not feasible to use this technique in the current 

PM NAAQS review to support a WHO Tier 3 analysis.28 11 

12 For most elements of this risk assessment, rather than conducting a full 

13 probabilistic uncertainty analysis, we have included qualitative discussions of the 

14 potential impact of uncertainty on risk results (WHO Tier1) and/or completed sensitivity 

15 analyses assessing the potential impact of sources of uncertainty on risk results (WHO 

16 Tier 2). Note, however, that in conducting sensitivity analyses, we have used both single17 and multi-factor approaches (to look at the individual and combined impacts of sources 

18 of uncertainty on risk estimates). Also, as discussed below in section 3.5.4, in conducting 

19 sensitivity analyses, we used only those alternative specifications for input parameters or 

20 modeling approaches that were deemed to have scientific support in the literature (and so 

21 represent alternative reasonable input parameter values or modeling options). This means 

22 that the alternative risk results generated in the sensitivity analyses represent reasonable 

23 risk estimates that can be used to provide a context, with regard to uncertainty, within 

24 which to assess the set of core (base case) risk results (see section 4.5.3). 

25 In addition to the qualitative and quantitative treatment of uncertainty and 

26 variability which are described here, we have also completed two additional analyses 

27 intended to place the risk results generated for the 15 urban study areas in a broader 

28 national context. The first is a representativeness analysis (described in section 4.4) 

29 which evaluates the set of urban study areas against national-distributions of key PM 

30 risk-related attributes (with the goal of determining the degree to which the study areas 

31 are representative of national trends in these parameters). The second is a national-scale 

32 assessment of long-term mortality related to PM2.5 exposures (discussed in chapter 5). In 

 28 Note, that while a full probabilistic uncertainty analysis was not completed for this risk assessment, we 

were able to use confidence intervals associated with effects estimates (obtained from epidemiological 

studies) to incorporate statistical uncertainty associated with sample size considerations in the presentation 

of risk estimates. 
September 2009 75 Draft – Do Not Quote or Cite 

1 addition to providing an estimate of the national impact of PM2.5 on long-term mortality, 

2 this analysis also evaluates whether the set of 15 urban study areas generally represents 

3 the broader distribution of risk across the U.S., or a more focused portion of the national 

4 risk distribution (e.g., the higher-end). 

5 The remainder of this section is organized as follows. Key sources of variability 

6 which are reflected in the design of the risk assessment, along with sources excluded 

7 from the design, are discussed in section 3.5.2. A qualitative discussion of key sources of 

8 uncertainty associated with the risk assessment (including the potential direction, 

9 magnitude and degree of confidence associated with our understanding of the source of 

10 uncertainty – the knowledge base) is presented in section 3.5.3. The methods and results 

11 of the single- and multi-factor sensitivity analyses completed for the risk assessment are 

12 presented in section 3.5.4. An overall summary of the methods used to address 

13 uncertainty and variability for the 15 urban study areas (including the two assessments 

14 intended to place the urban study areas in a broader national context) is presented in 

15 section 3.5.5. 

16 3.5.2 Key sources of variability 

17 The risk assessment was designed to cover the key sources of variability related to 

18 population exposure and exposure response, to the extent supported by available data. 

19 However, as with all risk assessments, there are sources of variability which have not 

20 been fully reflected in the design of the risk assessment and consequently introduce a 

21 degree of uncertainty into the risk estimates. We note, in addition, that while different 

22 sources of variability were captured in the risk assessment, it was generally not possible 

23 to separate out the impact of each factor on population risk estimates, since many of the 

24 sources of variability are reflected collectively in a specific aspect of the risk model. For 

25 example, inclusion of urban study areas from different PM regions likely provides some 

26 degree of coverage for a variety of factors associated with PM2.5 risk (e.g., air conditioner 

27 use, PM2.5 composition, differences in population commuting and exercise patterns, 

28 weather). However, the model is not sufficiently precise or disaggregated to allow the 

29 individual impacts of any one of these sources of variability on the risk estimates to be 

30 characterized. 

31 Key sources of potential variability that are likely to affect population risks are 

32 discussed below, including the degree to which they are (or are not) fully captured in the 

33 design of the risk assessment: 

34  PM2.5 composition: While the risk assessment did not include modeling of risk 

35 associated with different components of PM2.5, the assessment did use effect 
September 2009 76 Draft – Do Not Quote or Cite 

1 estimates (for a number of the short-term exposure-related health endpoints) 

2 differentiated by region of the country, or differentiated for specific urban 

3 locations (see section 3.3.3 and 3.3.4). While many factors may contribute to 

4 differences in effect estimates (for the same health endpoint) across different 

5 locations, compositional differences in PM2.5 may be partially responsible. 

6 Therefore, while the analysis did not explicitly address compositional 

7 differences in generating risk estimates, potential differences in PM2.5

8 composition may be reflected in those effect estimates that are differentiated by 

9 region and/or urban study area. The effect estimates for mortality associated 

10 with long-term exposure to PM2.5 are not regionally differentiated and instead, a 

11 single national-scale estimate is used. This means that any differences in risks 

12 of mortality associated with long-term exposure to PM2.5 that are linked to 

13 differences in PM2.5 composition (or to any other differences across regions or 

14 locations) would not be discernable, since a single national-scale risk estimate 

15 is generated for each mortality category. This remains an important limitation 

16 of the analysis. In addition to using region- or location-specific effect estimates 

17 for health effects associated with short-term exposures, the selection of urban 

18 areas to include in the risk assessment was designed in part to ensure that areas 

19 in different regions of the country, with different PM2.5 composition, were 

20 included. 

21  Intra-urban variability in ambient PM2.5 levels: Several recent studies (e.g., 

22 Jerrett et al., 2005) have addressed the issue of heterogeneity of PM 

23 concentrations within urban areas and its potential impact on the estimation of 

24 premature mortality associated with long-term exposure to PM2.5. Most 

25 recently, the HEI Reanalysis II (Krewski et al., 2009), focusing on the ACS 

26 dataset, discusses epidemiological analyses completed for Los Angeles and 

27 New York City which included more highly-refined (zip code level). 

28 characterizations of spatial gradients in population exposure within each urban 

29 area based on land-use regression methods and/or kriging. While both analyses 

30 provide insights into the issue of intra-urban heterogeneity in PM2.5

31 concentrations and its potential implications for epidemiology-based health 

32 assessments, due to the time and resource necessary to integrate them into the 

33 risk assessment, we were not able to incorporate these studies quantitatively. 

34 The implications of these studies for interpretation of long-term mortality C-R 

35 functions and potential exposure error associated with those functions, is 

36 discussed below in section 3.5.3. 

37  Demographics (e.g., greater concentrations of susceptible populations in 

38 certain locations): We have included multiple urban study areas reflecting 

39 differences in demographics in different regions of the country to address this 

40 issue. 

41  Behavior affecting exposure to PM2.5 (e.g., time spent outdoors, air 

42 conditioning use): We have incorporated, where available, region- and/or city43 specific effect estimates in order to capture behavioral differences across 

44 locations that could affect population exposures to PM2.5. However, while 

45 these location-specific effect estimates may be capturing differences in 
September 2009 77 Draft – Do Not Quote or Cite 

1 behavior, they may also be capturing other differences (e.g., differences in the 

2 composition of PM2.5 to which populations are exposed). As noted above, it 

3 was not possible to separate out the impact of these different factors, which 

4 may vary across locations and populations, on effect estimates. 

5  Baseline incidence of disease: We collected baseline health effects incidence 

6 data (for mortality and morbidity endpoints) from a number of different sources 

7 (see section 3.4). Often the data were available at the county-level, providing a 

8 relatively high degree of spatial refinement in characterizing baseline incidence 

9 given the overall level of spatial refinement reflected in the risk assessment as a 

10 whole. Otherwise, for urban study areas without county-level data, either (a) a 

11 surrogate urban study area (with its baseline incidence rates) was used, or (b) 

12 less refined state-level incidence rate data were used. 

13  Longer-term temporal variability in ambient PM2.5 levels (reflecting 

14 meteorological trends, as well as future changes in the mix of PM2.5 sources and 

15 regulations impacting PM2.5): Risk estimates for the PM2.5 NAAQS review 

16 have been generated using recent years of air quality data. In other words, 

17 efforts have not been made to simulate potential future changes in either the 

18 concentrations or composition of ambient PM2.5 in the risk assessment locations 

19 based on possible changes in economic activity, demographics or meteorology. 

20 Actual risk levels potentially experienced in the future as a result of 

21 implementing alternative standard levels may differ from those presented in this 

22 report due, in part, to potential changes in these factors related to ambient 

23 PM2.5. 

24 3.5.3 Qualitative assessment of uncertainty 

25 As noted in section 3.5.1, we have based the design of the uncertainty analysis 

26 carried out for this risk assessment on the framework outlined in the WHO guidance 

27 document (WHO, 2009). That guidance calls for the completion of a Tier 1 qualitative 

28 uncertainty analysis, provided the initial Tier 0 screening analysis suggests there is 

29 concern that uncertainty associated with the analysis is sufficient to significantly impact 

30 risk results (i.e., to potentially affect decision making based on those risk results). Given 

31 previous sensitivity analyses completed for prior PM NAAQS reviews, which have 

32 shown various sources of uncertainty to have a potentially significant impact on risk 

33 results, we believe that there is justification for conducting a Tier 1 analysis. In fact, as 

34 argued earlier, given the complexity of the overall risk assessment, a full Tier 3 

35 uncertainty analysis is warranted for consideration under WHO’s guidelines. 

36 For the qualitative uncertainty analysis, We have described each source of 

37 uncertainty and qualitatively assessed its potential impact (including both the magnitude 

38 and direction of the impact) on risk results, as specified in the WHO guidance. As shown 

39 in Table 3-13, for each source of uncertainty, we have (a) provided a description, (b) 

40 estimated the direction of influence (over, under, both, or unknown) and magnitude (low, 
September 2009 78 Draft – Do Not Quote or Cite 

1 medium, high) of the potential impact of each source of uncertainty on the risk estimates, 

2 (c) assessed the degree of uncertainty (low, medium, or high) associated with the 

3 knowledge-base (i.e., assessed how well we understand each source of uncertainty), and 

4 (d) provided comments further clarifying the qualitative assessment presented. Table 3-

5 13 includes all key sources of uncertainty identified for the PM2.5 NAAQS risk 

6 assessment. A subset of these sources has been included in the Tier 2 quantitative 

7 assessment discussed in section 3.5.4. 

8 

9 

10 

11 
September 2009 79 Draft – Do 

1 Table 3-13. Summary of Qualitative Uncertainty Analysis of Key Modeling Elements in the P2 Assessment. 

Potential influence of 

uncertainty on risk 

estimates 

Source Description Direction Magnitude 

KnowledgeBase 

uncertainty* 

Comm

(KB: knowledge base, INF: infl

estima

A. Characterizing ambient PM2.5

levels for study populations using the existing ambient monitoring network 

If the set of monitors used in a particular urban study area to characterize population exposure as part of an ongoing risk assessment do not match the ambient monitoring data used in the original epidemiological study, then uncertainty can be introduced into the risk estimates. 

Both Low- medium Low-medium 

KB and INF: In modeling risk, we were included in the epidemiologicunderlying C-R functions. This meendpoints modeled using C-R funcstudies, there is likely a close assocnetwork used in the risk assessmenstudy supplying the C-R function(sinstances where the networks are dstudies are used, resulting in an inchave changed), uncertainty may be assessment and it is challenging to magnitude of the impact that that uestimates, given the complex interpmismatched monitoring networks (monitors used in modeling risk and epidemiological study). 

B. Characterizing policy-relevant background (PRB) 

For this analysis, we have used modeling to estimate PRB levels for each urban study area. Depending on the nature of errors reflected in that modeling, uncertainty (in both directions) may be introduced into the analysis. 

Both Low Low 

INF: Given that the risk assessmenreduction in risk associated with mto alternative standard levels, the imlevels on the risk estimates is expeclong-term exposure related mortalianalysis on modeling risk down to reduces the significance of the PRB modeling long-term exposure-relat

C. Procedure for adjusting air quality to simulate alternate standard levels 

Uncertainty is associated with the manner in which monitor levels are rolled back to simulate just meeting alternative standard levels (e.g., will localized sources be addressed resulting in a geographically focused 

Both Low- medium Low 

INF: There is uncertainty associatestrategies likely to be used to achiewell as the degree to which localizedisproportionately affect levels at pHowever, the sensitivity analysis cassessment suggests that this sourcthrough the use of proportional vs. rollback modeling) may have a rela
September 2009 80 Draft – Do 

Potential influence of 

uncertainty on risk 

estimates 

Source Description Direction Magnitude 

KnowledgeBase 

uncertainty* 

Comm

(KB: knowledge base, INF: infl

estima

reduction in ambient levels, or will more generalized regional strategies be used). 

term mortality risk in some locationslightly larger impact (see section 4analysis addressing this source of u

D. Characterizing intra-urban population exposure in the context of epidemiology studies linking PM2.5 to 

specific health effects 

Exposure misclassification within communities that is associated with the use of generalized population monitors (which may miss important patterns of exposure within urban study areas) introduces uncertainty into the effect estimates obtained from epidemiology studies. 

Under 

(generally) 

Mediumhigh High 

KB and INF: Recent analyses in Lbased on ACS data (as reported in demonstrate the relatively significauncertainty can have on effect estimresults). These analyses also illustrspecific nature of this source of uncAngeles analysis suggest that expoestimates that are biased low and thunderestimation of risk. Specificallevel analysis based on ACS data c(Jerrett et al., 2005), the draft ISA sexposure analysis reported in the Jeimproved exposure assessment and sources of fine particle pollution. SPM2.5 and mortality from all causes 

were reported with the magnitude ogreater than those reported in previthe associations for PM2.5 and mort

[kriging and land-use regression] fosimilar, though the use of land use somewhat smaller hazard ratios and (see Table 7-9). This indicates that not the cause of the associations fostudies. This provides evidence tharesult in stronger associations betw

generally observed in broader studi(draft ISA, section 7.6.3). 

E. Statistical fit of the C-R functions 

Exposure measurement error combined with other factors (e.g., size of the effect itself, sample size, control for confounders) can effect the overall level of confidence 

Both 

 Lowmedium 

(long-term health endpoints) 

 Medium 

Medium 

INF: Long-term mortality studies bsample sizes (given that large natioin deriving national-scale models), models used appears to be subject t(see next row below) and (c) our nospecific effects estimates (but inste
September 2009 81 Draft – Do 

Potential influence of 

uncertainty on risk 

estimates 

Source Description Direction Magnitude 

KnowledgeBase 

uncertainty* 

Comm

(KB: knowledge base, INF: infl

estima

associated with the fitting of statistical effect-response models in epidemiological studies. 

(short-term health endpoints) 

estimates). These factors combine ttend to be statistically robust (as reKrewski et al., 2009). In addition, regarding exposure misclassificatiogenerally we do not believe that the consistently biased in a particular dterm mortality and morbidity health uncertainty associated with the fit osample sizes often involved, difficuetiologically relevant time period fthe fact that models tend to be fitteurban areas (which introduces the pconfounding and effects modificaticontrast to the long-term mortality mortality and morbidity endpoints estimates that are not statistically sfor this risk assessment, in modelinmorbidity endpoints, we are not relmodels. In the case of short-term mspecific effects estimates derived ucombine national-scale models witcommunication with Zanobetti, 200we are using regional effects estimcases, while effects estimates are at significant, these models do beneficompared to city-specific models. 

F. Shape of the C-R functions 

Uncertainty in predicting the shape of the C-R function, particularly in the lower exposure regions which are often the focus in PM NAAQS regulatory reviews. 

Both Low- medium Low-medium 

INF: Regarding long-term mortalitlinear non-threshold model is best modeling both short-term and longAlthough consideration for alternatal., 2009) does suggest that differenestimates to a certain extent, generarelatively modest source of overall is the case in this risk assessment, wthe lowest measured levels found expidemiological studies. With reg
September 2009 82 Draft – Do 

Potential influence of 

uncertainty on risk 

estimates 

Source Description Direction Magnitude 

KnowledgeBase 

uncertainty* 

Comm

(KB: knowledge base, INF: infl

estima

ISA concludes that, “Using a varieof the studies evaluated support the linear model...” (section 2.4.3). Rethe ISA states that, “Overall, the limevaluated supports the use of a no-twhich is consistent with the observexamined the PM-mortality relation

G. Addressing co-pollutants 

The inclusion or exclusion of co-pollutants which may confound, or in other ways, effect the PM effect, introduces uncertainty into the analysis. 

Both Low- medium Medium 

INF: With regard to long-term healthat, “Given similar sources for mudisentangling the health responses in the study of ambient air pollutionISA also notes that in some instanccopollutants can have a significant the more refined study of lung cancin Krewski et al., 2009 – see ISA, sshort-term mortality and morbiditythat observed associations are fairly copollutants (see ISA, sections 6.3

H. Potential variation in effects estimates reflecting compositional differences for PM 

The composition of PM can differ across study areas reflecting underlying differences in primary and secondary PM2.5 sources (both 

natural and anthropogenic). If these compositional differences in fact translate into significant differences in public health impact (per unit exposure) for PM2.5 then significant 

uncertainty may be introduced into risk assessments if these compositional differences are not explicitly addressed. 

Both Medium- High Medium-High 

KB and INF: Epidemiology studies differences in PM2.5-related health 

in the magnitude of those effects (sthe draft ISA). While these may be composition (e.g., different degrees composition remains one potential term exposure morbidity and mortacity-specific and/or regional-specifassessment may well reflect differethus consideration of differences in differences in composition may alrestimates for these endpoints to som

I. Specifying lag structure (short-term 

Different lags may have varying degrees of association with a particular health 

Both Medium Medium 

KB and INF: With regard to lag peattempt has been made to identify wmore strongly associated with spec
September 2009 83 Draft – Do 

Potential influence of 

uncertainty on risk 

estimates 

Source Description Direction Magnitude 

KnowledgeBase 

uncertainty* 

Comm

(KB: knowledge base, INF: infl

estima

exposure studies) 

endpoint and it may be difficult to clearly identify a specific lag as producing the majority of a PM-related effect (recently, distributed lags have been recommended since they allow for a distribution of the impact across multiple days of PM exposure prior to the health outcome). A lack of clarity regarding the specific lag(s) associated with a particular health endpoint adds uncertainty into risk estimates generated for that endpoint. 

epidemiologic evidence evaluated isupported the use of lags of 0-1 daylonger moving averages or distribu(U.S. EPA, 2004a). However, curreto the most appropriate a priori lag 

morbidity and mortality outcomes.suggests that uncertainty remains cappropriate lags, and thus the etioloexposure to PM for specific health 

J. Transferability of C-R functions from study locations to urban study area locations 

The use of effects estimates based on data collected in a particular location(s) as part of the underlying epidemiological study in different locations (the focus of the risk assessment) introduces uncertainty into the analysis. 

Both 

Medium (for 

long-term 

exposure 

mortality) 

Not 

applicable 

(for shortterm 

exposure 

health effect 

risk 

estimates) 

Medium (for 

long-term 

exposure 

mortality) 

Low (for shortterm exposure 

mortality) 

INF: This issue has been amelioratassessment since we are now using short-term endpoints with effects eapplied only to urban study areas munderlying epidemiological study. exposure mortality studies, these argeneralized national signal and thertransferability of functions between 

K. Impact of historical air quality on estimates of health risk from long-term PM2.5

Long-term studies of mortality suggest that different time periods of PM exposure can produce significantly different effects estimates, raising the issue of uncertainty in relation to determining which exposure 

Both Medium Medium 

INF: The latest HEI Reanalysis II sat exposure windows (1979-1983 aexposure in relation to mortality, dto which window was more stronglHowever, the study did suggest thaestimates are associated with the di

the more recent period having large
September 2009 84 Draft – Do 

Potential influence of 

uncertainty on risk 

estimates 

Source Description Direction Magnitude 

KnowledgeBase 

uncertainty* 

Comm

(KB: knowledge base, INF: infl

estima

exposures window is most strongly 

associated with mortality. 

evidence for determining the windoeffects of long-term pollution expoperiod of up to five years, with the the first two years (Draft ISA, secti

L. Characterizing baseline incidence rates 

Uncertainty can be introduced into the characterization of baseline incidence in a number of different ways (e.g., error in reporting incidence for specific endpoints, mismatch between the spatial scale in which the baseline data were captured and the level of the risk assessment). 

Both Low- medium Low 

INF: The degree of influence of thirisk estimates likely varies with the consideration. There is no reason tsystematic biases in estimates of thinfluence on risk estimates that are reductions between alternative stanunaffected by this source of uncertaKB: The county level baseline incat the county level were obtained frrelative degree of uncertainty is low

1 * Refers to the degree of uncertainty associated with our understanding of the phenomenon, in the context of assessing and charact2 (specifically in the context of modeling PM risk) 
September 2009 85 Draft – Do Not Quote or Cite 

1 3.5.4 Single and multi-factor sensitivity analyses 

2 We quantitatively examined the impact of several inputs to the risk assessment in 

3 a series of single-factor sensitivity analyses summarized above in Table 3-8. Rather than 

4 present results for each sensitivity analysis for all of the air quality scenarios considered 

5 in the core analysis, we selected a single air quality scenario – PM2.5 concentrations that 

6 just meet the current standards – to use for the sensitivity analyses. The one exception to 

7 this was the sensitivity analyses examining the impact of an alternative approach to 

simulating just meeting alternative standards (the hybrid rollback).29 8 

9 In discussing the approach used in conducting the sensitivity analysis, we focus 

10 first on methods used in assessing long-term exposure related health endpoints followed 

11 by the methods used in assessing short-term exposure related health endpoints. Note, that 

12 the results of the sensitivity analyses (including both single- and multi-factor analyses) 

13 are presented and discussed in section 4.3. 

14 Because Krewski et al. (2009) presented results based on alternative model 

15 specifications only for the later exposure period (1999 – 2000), our sensitivity analyses 

16 focusing on the estimates of health effects incidence associated with long-term exposure 

17 to PM2.5 similarly used the C-R functions based on this later exposure period. Krewski et 

18 al. (2009) considered several alternative modeling approaches to estimate the relationship 

19 between mortality (both all cause and cause-specific) and long-term exposure to PM2.5, 

20 providing us the opportunity to examine the impact of alternative modeling approaches 

21 on the estimate of mortality risk associated with long-term exposure. In particular, we 

22 examined the impact of using a random effects log-linear model and of using a random 

effects log-log model30 23 (rather than the standard fixed effects log-linear model used in the 

24 core analysis) to estimate the risks of all cause mortality, cardiopulmonary mortality, 

25 ischemic heart disease mortality, and lung cancer mortality associated with long-term 

exposure in Los Angeles and Philadelphia.31 26 The coefficient of PM2.5 in the random 

 29 Sensitivity analyses focusing on the hybrid rollback approach (relative to the proportional rollback 

approach used in the core analysis) involved the full set of alternative standard levels, in order to assess 

potential differences in risk across the range of standard levels. 

30 In the log-log model, the natural logarithm of mortality is a linear function of the natural logarithm of 

PM2.5. 31As noted in Table 3-8, we combined both of these alternative modeling approaches in a single sensitivity 

analysis. In changing from a fixed effects log-linear model to a random effects log-log model, two changes 

are actually being made – the change from a fixed effects log-linear model to a random effects log-linear 

model, and the change from a random effects log-linear model to a random effects log-log model. 

However, because Krewski et al. (2009) did not present results for a fixed effects log-log model, it was not 

possible to compare the impact of making the single change from a fixed effects log-linear model (our core 

analysis selection) to a fixed effects log-log model. We thus instead present a two-stage sensitivity analysis 

incorporating both of the changes. 
September 2009 86 Draft – Do Not Quote or Cite 

1 effects log-linear model was back-calculated from the relative risk reported in Table 9 

2 (“Autocorrelation at MSA and ZCA levels” group – “MSA & DIFF” row) of Krewski et 

3 al. (2009). The coefficient of PM2.5 in the random effects log-log model was back4 calculated from the relative risks reported in Table 11 (“MSA and DIFF” rows) of 

5 Krewski et al. (2009). 

6 As noted above, for all health endpoints associated with long-term exposure to 

PM2.5 we estimated risk associated with PM2.5 concentrations above 5.8 μg/m3 7 (the LML 

8 for the later exposure period used in Krewski et al., 2009). In a sensitivity analysis we 

9 examined the impact of that limitation by comparing those mortality risk estimates to the 

10 mortality risk estimates obtained when we estimated risk associated with PM2.5

11 concentrations above estimated PRB levels. This sensitivity analysis was carried out for 

12 all cause mortality in all 15 risk assessment urban areas. 

13 In addition, we compared the impact of using the primary C-R functions used in 

14 the risk assessment, taken from Table 33 of Krewski et al. (2009), versus C-R functions 

15 for mortality associated with long-term exposure reported in another study, Krewski et al. 

16 (2000), which was based on a reanalysis of the Harvard Six Cities Study. The C-R 

17 functions estimated in Krewski et al. (2000) from the Harvard Six Cities cohort were 

18 estimated for ages 25 and up, while the C-R functions estimated in Krewski et al. (2009) 

19 from the ACS cohort were for ages 30 and up. For purposes of consistency in the 

20 comparison, however, we applied the C-R functions from Krewski et al. (2000) to ages 

30 and up (and used the baseline incidence rates for that age group as well).32 21 This 

22 sensitivity analysis was carried out for all cause mortality, cardiopulmonary mortality, 

23 and lung cancer mortality in Los Angeles and Philadelphia. 

24 Finally, we compared estimates of all-cause mortality associated with long-term 

25 exposure when PM2.5 levels just meet the current and alternative standards, using the 

26 proportional rollback approach versus the hybrid rollback approach. This sensitivity 

27 analysis was carried out in Baltimore, Birmingham, Detroit, Los Angeles, New York, and 

St. Louis.33 28 

29 In all cases, in addition to calculating the incidence of the health effect when an 

30 alternative approach is taken, we calculated the percent difference in estimates from the 

31 core analysis resulting from the change in analysis input. So for example, when we 

32 calculated the incidence of all cause mortality associated with long-term exposure to 

 32 The baseline incidence rates for ages 25 and up and ages 30 and up are likely to be very similar. 

33 As noted earlier in section 2.4.1, an error was identified in the approach used to simulate ambient PM2.5 

levels just for the Pittsburgh study area for the scenarios involving just meeting the current and alternative 

sets of standards. Therefore, while Pittsburgh had initially been included in this sensitivity analysis, these 

results have been removed since they are based on the set of current standard levels. 
September 2009 87 Draft – Do Not Quote or Cite 

1 PM2.5 using a random effects log-log model (instead of the fixed effects log-linear model 

2 used in the core analysis), we calculated the percent difference in the result as (incidence 

3 estimated using a random effects log-log model - incidence estimated using a fixed 

4 effects log-linear model)/( incidence estimated using a fixed effects log-linear model). 

5 The primary studies selected to assess mortality risk and risk of hospitalization 

6 associated with short-term exposure to PM2.5 (Zanobetti and Schwartz, 2009, and Bell et 

7 al., 2008, respectively) both provided all-year C-R functions as well as season-specific C8 R functions. We examined the impact of using season-specific functions by applying 

these functions to each season, as defined by the study authors,34 9 and summing the 

10 estimated season-specific incidences of mortality and hospitalizations. We compared 

11 these estimates to the estimates obtained by applying the corresponding all-year C-R 

functions to a year of air quality data.35 12 This sensitivity analysis was carried out for all 

13 15 of the risk assessment urban areas. 

14 In addition, Ito et al. (2007) estimated an annual C-R function as well as a 

15 seasonal function for April through August for asthma ED visits in New York City. We 

16 compared the results of applying the annual C-R function to a whole year of air quality 

17 data to the results of applying the seasonal function to only those months (April through 

18 August) for which it was estimated. 

19 Moolgavkar (2003) estimated C-R functions for several health endpoints – non20 accidental and cardiovascular mortality; and cardiovascular and respiratory HAs – 

21 associated with short-term exposures to PM2.5 in Los Angeles using different lag 

22 structures, different modeling approaches to incorporating weather and temporal 

23 variables, and single-pollutant versus multi-pollutant models. This study thus provided 

24 an opportunity to show the impact of lag structure, modeling approach, and single- vs. 

25 multi-pollutant models, individually, for several health endpoints associated with short26 term exposures, although it is difficult to generalize to other locations since the study was 

27 only conducted in a single urban area. 

 34 Both studies defined each season as three months, beginning with winter defined as December, January, 

and February. In applying a season-specific function to a year of air quality data, we chose to keep a 

calendar year together, so that, for example, winter 2005 was defined as December 2005, January 2005, and 

February 2005. 

35 The mean season-specific incidence estimates can be summed to produce an all-year estimate of 

incidence. However, the 2.5th and 97.5th percentile season-specific estimates cannot be summed. To 

calculate the 2.5th and 97.5th percentile estimates of all-year incidence from the season-specific estimates 

would require the variance-covariance matrix of the season-specific coefficient estimators, which was not 

available. Therefore our comparison of all-year estimates based on summed season-specific estimates 

versus estimates based on an all-year C-R function was carried out only using the mean estimates. 
September 2009 88 Draft – Do Not Quote or Cite 

1 Finally, we compared estimates of non-accidental mortality associated with short2 term exposures to PM2.5 (using Zanobetti and Schwartz, 2009) when PM2.5 levels just 

3 meet the current and alternative standards, using the proportional rollback approach 

4 versus the hybrid rollback approach. This sensitivity analysis was carried out in 

5 Baltimore, Birmingham, Detroit, Los Angeles, New York, and St. Louis. 

6 In all cases except the ED visits sensitivity analysis, in addition to calculating the 

7 incidence of the health effect when an alternative approach is taken, we calculated the 

8 percent difference in estimates from the core analysis resulting from the change in 

analysis input.36 9 

10 Each single-element sensitivity analysis shows how the estimates of PM2.5–related 

11 health effects incidence change as we change a single element of the analysis (such as the 

12 form of the C-R function or the way we simulate just meeting a set of standards). 

13 Because each of the alternative modeling choices is considered to be a reasonable choice, 

14 the results of these single-element sensitivity analyses provide a set of reasonable 

15 alternative estimates that may similarly be considered plausible (see section 4.3). The 

16 results of the single-element sensitivity analysis are presented and discussed in section 

17 4.3.1. 

18 The single-element sensitivity analyses provide insight into which sources of 

19 uncertainty may have the greatest impact on risk estimates when acting alone. However, 

20 there are several sources of uncertainty in estimating PM2.5–related health effects. To 

21 provide a more complete picture of the uncertainty surrounding estimates of PM2.5–

22 related health effects incidence – and to expand the set of reasonable alternative estimates 

23 – we next carried out multi-element sensitivity analyses. The results of the multi-factor 

24 sensitivity analysis are presented and discussed in section 4.3.2. 

25 The choice of uncertain analysis elements to include in the multi-element 

26 sensitivity analyses was guided by the single-element sensitivity analyses. In particular, 

27 we selected those modeling choices that had the greatest impacts on the estimates of 

28 health effects incidence in the single-element sensitivity analyses to provide insight into 

29 the scope of possible estimates that, while perhaps not based on our first choice of 

30 analysis elements, are nevertheless plausible alternative estimates. 

31 We identified three analysis elements that substantially affected the estimates of 

32 mortality associated with long-term exposure to PM2.5 -- the model choice (fixed effects 

 36 We did not calculate percent different for the ED visits sensitivity analysis because the two different C-R 

functions (all-year in the core analysis vs. April through August in the sensitivity analysis) are also being 

applied to different portions of the year (all year vs. April through August), so it is something of an “apple 

to oranges” comparison. 
September 2009 89 Draft – Do Not Quote or Cite 

1 log linear vs. random effects log-log), whether effects are estimated associated with PM2.5

concentrations down to the LML in the study (5.8 μg/m3 2 ) or down to PRB, and whether a 

3 proportional or a hybrid rollback is used to simulate PM2.5 concentrations that just meet a 

4 given set of standards. This resulted in 2 x 2 x 2 = 8 different estimates of mortality, all 

5 of which could be considered plausible, based on the fact that the underlying model 

6 choices are all considered reasonable. 

7 We identified two analysis elements that substantially affected the estimates of 

8 mortality associated with short-term exposure to PM2.5 – whether season-specific or all9 year C-R functions were used and whether a proportional or a hybrid rollback approach 

10 was used to simulate just meeting the current and alternative standards. 

11 3.5.5 Summary of approach to addressing variability and uncertainty 

12 The characterization of uncertainty and variability associated with the risk 

13 assessment includes a number of elements, which have been discussed in detail above. 

14 These include: 

15  Identification of key sources of variability associated with PM2.5-related 

16 population exposure and hazard response and the degree to which they area 

17 captured in the risk assessment (see section 3.5.2). When important sources of 

18 variability in exposure and/or hazard response are not reflected in a risk 

19 assessment, significant uncertainty can be introduced into the risk estimates that 

20 are generated. While not explicitly referenced in the WHO guidance, this 

21 assessment (focused on coverage for key sources of variability) could be 

22 considered part of a Tier 1 analysis (i.e., the qualitative characterization of 

23 sources of uncertainty). 

24  Qualitative assessment of uncertainty, including both an assessment of the 

25 magnitude of potential impact of each source on risk estimates (along with the 

26 potential direction of that impact) as well as an assessment of overall 

27 confidence associated with our understanding of that source of uncertainty (see 

28 section 3.5.3). This represents a WHO Tier 1 analysis. 

29  Single-factor sensitivity analysis intended to evaluate the impact of individual 

30 sources of uncertainty on risk estimates (see section 3.5.4). The goal of this 

31 assessment is to evaluate the relative importance of these sources of uncertainty 

32 in impacting core risk estimates. The single-factor sensitivity analysis 

33 represents a WHO Tier 2 analysis. Note, that in conducting these assessments, 

34 we have used alternative representations of modeling elements that have 

35 support in the literature to ensure that the risk estimates that are generated 

36 represent reasonable alternate estimates that can supplement the core risk 

37 estimates generated in the analysis (see section 4.5.3). 

38  Multi-factor sensitivity analysis intended to assess the combined impact of 

39 multiple sources of uncertainty on risk estimates (see section 3.5.4). By 
September 2009 90 Draft – Do Not Quote or Cite 

1 considering the combined effect of multiple sources of uncertainty, this analysis 

2 has the potential to identify any non-linearities which can magnify the impact 

3 of uncertainty on risk estimates, especially if several non-linear factors act in 

4 concert. This also represents a WHO Tier 2 analysis. Note, that as with the 

5 single-factor sensitivity analysis results, these risk estimates are also generated 

6 using modeling inputs which have support in the literature and consequently, 

7 they also represent reasonable alternate estimates that supplement the core risk 

8 estimates (see section 4.5.2). 

9 It is important to reiterate that, due to our inability to characterize overall levels of 

10 confidence in alternative model inputs, the uncertainty characterization completed for 

11 this risk assessment did not include a full probabilistic assessment of uncertainty and its 

12 impact on core risk estimates (i.e., a WHO Tier 3 analysis was not completed). 

13 Furthermore, the risk estimates generated using the single- and multi-factor sensitivity 

14 analyses do not represent uncertainty distributions, but rather additional plausible point 

15 estimates of risk (i.e., we do not know whether they represent risk estimates near the 

16 upper or lower bounds of a true but undefined uncertainty distribution and we do not 

17 know the actual population percentiles that they represent). The appropriate use for these 

18 reasonable alternate risk estimates in informing consideration of uncertainty in the core 

19 risk estimates is discussed in section 4.5.3. 

20 In addition to the specific analyses discussed above, we have also completed two 

21 additional analyses intended to place the 15 urban study areas in a broader national 

22 context with regard to risk. These include a representativeness analysis which evaluates 

23 the way the 15 urban study areas compare to national distributions for key PM-related 

24 risk attributes (discussed in section 4.4). We have also completed a national-scale 

25 assessment of long-term mortality related to PM2.5 exposures (Chapter 5), which, in 

26 addition to providing an estimate of the national impact of PM2.5 on long-term mortality, 

27 also evaluates whether the set of 15 urban study areas generally represents the broader 

28 distribution of risk across the U.S., or a more focused portion of the national risk 

29 distribution (e.g., the higher-end). 
September 2009 91 Draft – Do Not Quote or Cite 

1 4 RESULTS 

2 As discussed above in section 3.1.1, for this risk assessment, we have developed a 

3 core set of risk estimates supplemented by an alternative set of risk results generated 

4 using single-factor and multi-factor sensitivity analysis. The core set of risk estimates 

5 was developed using model inputs believed to have a relatively greater degree of support 

6 in the literature (compared with inputs used in the sensitivity analyses). Therefore, we 

7 have emphasized the core set of risk estimates in presenting and discussing risk estimates 

8 in this section, with the results of the sensitivity analysis serving to augment the core 

9 estimates as discussed below. 

10 The results of the sensitivity analysis allow us to evaluate and rank the potential 

11 impact of key sources of uncertainty on the core risk estimates. In addition, as noted in 

12 section 3.5.4, because the sensitivity analysis was conducted using alternative modeling 

13 inputs having some degree of support in the literature, the results of the sensitivity 

14 analysis also represent a set of reasonable alternatives to the core set of risk estimates that 

15 can be used in informing characterization of uncertainty in the core results (see section 

16 4.3 below). 

17 As discussed in section 2.2 and 3.2, this risk assessment includes consideration of 

18 the following air quality scenarios: 

19  Recent conditions: based on PM2.5 concentrations characterized through 

20 monitoring for the period 2005-2007 at each urban case study location; 

21  Current NAAQS: based on rolling back PM2.5 concentrations to just meet the 

22 current suite of standards in each urban study area (annual standard of 15 

μg/m3

 and a 24-hour standard of 35 μg/m3 23 , denoted 15/35); 

24  Alternative NAAQS: based on rolling back PM2.5 concentrations to just meet 

25 an alternative set of standards in each urban study area: 

o annual standard of 13 μg/m3 and a 24-hour standard of 35 μg/m3 26 (denoted 

27 13/35); 

o annual standard of 12 μg/m3 and a 24-hour standard of 35 μg/m3 28 (denoted 

29 12/35); 

o annual standard of 13 μg/m3 and a 24-hour standard of 30 μg/m3 30 (denoted 

31 13/30); 

o annual standard of 12 μg/m3 and a 24-hour standard of 25 μg/m3 32 (denoted 

33 12/25). 

34 In simulating both current and alternative standard levels, for the core analysis, 

35 we used a proportional roll-back approach (see section 3.2.3), while a hybrid roll-back 
September 2009 92 Draft – Do Not Quote or Cite 

1 approach reflecting the potential for local source control was used for a subset of urban 

2 study areas as part of the sensitivity analysis conducted for this assessment (see section 

3 3.2.3). 

4 As described in section 2.1 and 3.3.2, for this risk assessment, we assessed risk 

5 for 15 urban study areas chosen to provide coverage for the diversity of urban settings 

across the U.S. that reflect areas with elevated annual and/or daily PM2.5 concentrations.9 6 

7 At a minimum all areas selected had recent air quality levels at or above the most 

8 stringent annual and/or 24-hour standard analyzed. In addition, our goal was to select 

9 areas reflecting the heterogeneity in PM risk-related attributes such as sources, 

10 composition, demographics, and population behavior. 

11 Risk estimates were generated for the following health effects endpoints: (a) long12 term exposure-related mortality (all-cause, cardiopulmonary disease-related (CPD), 

13 ischemic heart disease-related (IHD) and lung cancer-related), (b) short-term exposure14 related mortality (non-accidental, cardiovascular disease-related (CVD), respiratory), and 

15 (c) short-term exposure-related morbidity (hospital admissions (HA) for CVD and 

16 respiratory illness and emergency department (ED) visits). Risk estimates are presented 

17 separately for each of these 15 study areas, although in certain circumstances, risk 

18 estimates may be restricted to a subset of these locations if, for example, an endpoint is 

19 modeled using a C-R function derived from an epidemiological study that was conducted 

20 only in a subset of the urban areas. For the core analysis, long-term exposure mortality 

21 risk was modeled down to lowest measured level (LML), because the LML was higher 

22 than estimated PRB and because there is substantial uncertainty as to the shape of the 

23 concentration-response (C-R) function at concentrations below the LML. For long-term 

24 exposure mortality a sensitivity analysis was conducted that estimated risk down to 

25 policy-relevant background (PRB). In contrast, all short-term exposure health effects 

26 endpoints were modeled down to PRB, since this was higher than the LML across all 

27 studies and for purposes of NAAQS decision making, EPA is focused on risks associated 

28 with PM2.5 levels that are due to anthropogenic sources that can be controlled by U.S. 

29 regulations (or through international agreements with neighboring countries). 

30 In modeling long-term exposure mortality, for the core analysis, we have based 

31 estimates on the latest reanalysis of the American Cancer Society (ACS) dataset, with 

32 two sets of risk estimates being generated; one using a C-R function derived by fitting 

33 PM2.5 monitoring data from 1979-1983 and a second set based on fitting PM2.5

34 monitoring data from 1999-2000 (Krewski et al., 2009) (see section 3.3.3). In presenting 

35 core risk estimates for long-term mortality, both sets of estimates are given equal weight. 
September 2009 93 Draft – Do Not Quote or Cite 

1 In modeling short-term exposure mortality and morbidity for the core analysis, we 

2 have used the latest multi-city studies (Zanobetti and Schwartz, 2009; Bell et al., 2008) 

3 (see section 3.3.3). In the case of short-term exposure mortality, we obtained and used 

4 city-specific effects estimates derived using empirical Bayes methods from the study 

5 authors (Zanobetti, 2009). Multi-city studies were favored for the core analysis, since 

6 these studies are not subject to publication bias and because they reflect a diverse set of 

7 locations with regard to the observed relationship between short-term PM2.5 exposure and 

8 health affect response in the population. Additional detail on the specific C-R functions 

9 and related modeling elements such as effects estimates and lag periods used in the core 

10 analysis relative to the sensitivity analysis are presented in sections 3.3 and 3.4 and called 

11 out where appropriate below as specific risk estimates are discussed. 

12 Because the recent conditions air quality scenario spans three years (2005-2007), 

13 risk estimates are generated for each of these years, reflecting the underlying air quality 

14 data for a particular year. Risk metrics generated for the above health effects endpoints 

15 include: 

16  Annual incidence of the endpoint due to PM2.5 exposure (annual incidence): 

17 Generated for the population associated with a given urban study area (for a given 

18 simulation year), in most cases, these risk estimates include both a point estimate 

as well as a 95th 19 percentile confidence interval, the latter reflecting sampling error 

20 as characterized in the underlying epidemiological study. 

21  Percent of total annual incidence for the health endpoint due to PM2.5

22 exposure (percent of total incidence attributable to PM2.5): Again, generated for 

23 the population associated with a given urban study area (and simulation year), this 

24 metric characterizes the fraction of total incidence that is associated with PM2.5

25 exposure. As with the underlying PM-related incidence estimates, this risk metric 

also typically includes a 95th 26 percentile confidence interval reflecting sampling 

27 error associated with the effects estimate. Compared with the annual incidence 

28 metric which reflects underlying population size for each study area, this risk 

29 metric has the advantage of not being dependent on the size of the underlying 

30 population, thereby allowing direct comparison of the potential impact of PM2.5

31 for the health effect endpoint of interest across urban study area locations. For 

32 this reason, in discussing risk estimates in this section, the percent of total 

33 incidence attributable to PM2.5 risk metric is given greater emphasis than the 

34 absolute measure of annual incidence attributable to PM2.5. 

35  Percent reduction in PM2.5-related health effect incidence for an alternative 

36 set of standards or the recent conditions scenario, relative to the current 

37 standards (percent change from the current set of standards): Also estimated 

38 separately for each urban study area and simulation year, this metric characterizes 

39 the degree of risk reduction (for alternative standard levels) or increased risk (for 

40 the recent conditions scenario) relative to the current NAAQS. For this metric, a 
September 2009 94 Draft – Do Not Quote or Cite 

1 negative value represents an increase in risk (this is the case for the recent 

2 conditions scenario, where risks are actually higher than the current NAAQS). 

3 This metric is positive, or zero, for alternative NAAQS since they either produce 

4 no risk reduction (if ambient air levels under recent conditions are already at or 

5 below that alternative NAAQS level), or a positive risk reduction for alternative 

6 standards resulting in a reductions in ambient PM2.5 concentrations. We note, that 

because this metric is incremental, it was not possible to generate the 95th 7 

8 percentile confidence intervals included with the other two “absolute” risk metrics 

9 described above. As with the previous risk metric, this metric is not dependent on 

10 the underlying population size and therefore, allows direct comparison across 

11 urban study areas. 

12 Tables presenting estimates for these risk metrics are included in Appendix E and 

13 referenced in the discussion of risk estimates presented in this section (the detailed results 

14 tables themselves are not included in this section due to the large number of tables 

15 generated). In addition to the above risk metrics, we also generated a series of figures 

16 based on the third metric describe above (the percent reduction from the current 

17 standards). These figures allow the reader to quickly evaluate trends across air quality 

18 scenarios and across the 15 urban study areas in terms of the degree of reduction in 

19 PM2.5-related risk. A subset of these figures (for 2007) are in this section, with the full 

20 set of figures for all three simulation years being included in Appendix E. 

21 Although risk estimates were generated for all three simulation years, in this 

22 chapter core risk estimates primarily from 2007 are presented and discussed for both the 

23 recent conditions air quality scenario and current and alternative standards. This reflects 

24 the observation that generally, 2007 represents a reasonable central year (in terms of the 

25 magnitude of risk generated for the three simulated years), when considering results for 

26 all modeled health effect endpoints across the 15 study areas. In addition, 2007 is the 

27 most recent year of the three simulated. We note, however, that while we do focus on 

28 2007 in presenting and discussing risk estimates, we include an assessment of general 

29 trends across the three simulation years to gain perspective on year-to-year variation in 

30 PM2.5-related risk estimates as assessed here. 

31 In presenting the results of the sensitivity analysis, as with the core risk results, 

32 we also focus on 2007. This is done to increase compatibility between the core results 

33 and the sensitivity analysis results (i.e., allow the sensitivity analysis results to be used to 

34 gain insights into uncertainty associated with the core results, without adding the 

35 additional factor of year-to-year variation into the mix). As with the core risk estimates, 

36 the full set of sensitivity analysis results for all three simulation years have been 

37 generated and are presented in Appendix F. 
September 2009 95 Draft – Do Not Quote or Cite 

1 For a subset of the urban case studies (e.g., Dallas and Phoenix), incremental 

2 reductions across alternative standards are initially very low (or even zero) reflecting the 

3 fact that recent ambient PM2.5 concentrations for these study areas are well below the 

4 current annual standard levels. For these study areas, meaningful reductions in risk may 

5 not be seen until relatively lower alternative standards are assessed (and results in the 

6 percent reduction from the current set of standards tables and figures may be zero for 

7 several of the less stringent, alternative sets of standards). 

8 For a number of the urban study areas, confidence intervals (and in some 

9 instances, point estimates) for short-term mortality and morbidity incidence and related 

10 risk metrics include values that fall below zero. Population incidence estimates with 

11 negative lower-confidence bounds (or point estimates) do not imply that additional 

12 exposure to PM2.5 has a beneficial effect, but only that the estimated PM2.5 effect estimate 

13 in the C-R function was not statistically significantly different from zero. In the case of 

14 short-term exposure mortality, where study area-specific effects estimates were used (see 

15 section 3.4), several of the urban locations have non-statistically significant effects 

16 estimates; these result in incidence estimates with non-positive lower bounds and/or best 

17 estimates (e.g., Birmingham, Detroit, and Los Angeles for non-accidental mortality). In 

18 the case of short-term morbidity (e.g., HAs), where regional effects estimates were used, 

19 one of the regional coefficients (for the southeast) is not statistically significant, 

20 producing incidence estimates including negative values in the confidence interval for 

21 urban study areas falling within that region (e.g., Atlanta, Dallas, and Houston, for CV22 related HAs). Lack of statistical significance could mean that there is no relationship 

23 between PM2.5 and the health endpoint or it could mean that there was not sufficient 

24 statistical power to detect a relationship that actually exists. In the case of PM2.5 and both 

25 short-term exposure mortality and morbidity, given the available evidence in the 

26 literature, which has resulted in the draft ISA concluding that there is likely to be a causal 

27 relationship between short-term PM2.5 exposure and adverse health effects (see section 

28 3.3.1), we believe it is reasonable to assume that instances where effects estimates are 

29 not-statistically significant are likely to reflect insufficient sample size, rather than the 

30 absence of an actual association. We note, however, that (as discussed in section 3.6.3) 

31 many factors can potentially result in variations in the magnitude of effect estimates. In 

32 addition to sample size, these include: source and compositional differences for PM2.5, 

33 exposure error associated with the use of ambient monitors as a surrogate for actual 

34 exposure, and differences in population susceptibility and vulnerability. 

35 The remainder of this section is organized as follows. Core modeling results for 

36 the recent conditions air quality scenario are presented in section 4.1. Core modeling 
September 2009 96 Draft – Do Not Quote or Cite 

1 results for just meeting the current NAAQS and just meeting alternative NAAQS are 

2 presented in section 4.2. The results of the sensitivity analysis (including single-factor 

3 and multi-factor results) are presented in section 4.3. The results of a representativeness 

4 analysis involving comparison of counties associated with the 15 urban study area 

5 locations against the national distribution of counties with regard to a set of PM-risk 

6 related attributes are presented in section 4.4. The chapter concludes in section 4.5 with 

7 an overall summary and presentation of key observations drawn from consideration of the 

8 core analysis results combined with the results of the sensitivity analysis results. We note 

9 that all of the risk estimates discussed in this chapter pertain to the 15 urban study areas. 

10 The results of the national-scale health impact analysis are presented separately in chapter 

11 5, although implications for interpretation of risk estimates generated for the 15 urban 

12 study areas are discussed in section 4.5.4. 

13 4.1 ASSESSMENT OF HEALTH RISK ASSOCIATED WITH RECENT 

14 CONDITIONS (CORE ANALYSIS) 

15 This section discusses core risk estimates generated for the recent conditions air 

16 quality scenario, focusing on the 2007 simulation year (although observations related to 

17 the three simulated years are also presented). In discussing results for the recent 

18 conditions air quality scenario, we have focused on absolute risk (either above PRB or 

19 LML, depending on the health effect endpoint). This reflects the fact that this air quality 

20 scenario represents recent conditions within the urban study areas and therefore, does not 

21 lend itself well to an incremental assessment. The section is organized by health 

22 endpoint category, with results discussed in the following order: long-term exposure 

23 mortality, short-term exposure mortality and short-term exposure morbidity. 

24 4.1.1 Long-term exposure mortality 

25 This section summarizes core estimates for long-term exposure mortality (all 

26 cause, IHD, CPD and lung cancer) generated for the recent conditions air quality scenario 

27 for simulation year 2007. 

28  Percent of total incidence and PM2.5-related incidence (all cause 

29 mortality): the percent of total long-term exposure mortality incidence 

30 associated with PM2.5 exposure under recent conditions for the 2007 

31 simulation year is estimated to range from 1.7% (Tacoma) to 5.2% (Fresno) 

32 based on the C-R function derived using 1979-1983 PM2.5 monitoring data 

33 (Appendix E, Table E-7). The percent of total incidence for long-term 

34 exposure mortality (for all-cause) based on the C-R function derived using 

35 1999-2000 PM2.5 monitoring data are somewhat larger, ranging from 2.2% 

36 (Tacoma) to 6.7% (Fresno) (Appendix E, Table E-15). Total all-cause 
September 2009 97 Draft – Do Not Quote or Cite 

1 mortality incidence associated with long-term exposure to PM2.5 ranges from 

2 about 90 (Tacoma) to 2,200 (L.A.) (based on the C-R function derived using 

3 1979-1983 PM2.5 monitoring data - Appendix E, Table E-3) and from 120 

4 (Tacoma) to 2,900 (L.A.) (based on the C-R function derived using 1999-2000 

5 PM2.5 monitoring data - Appendix E, Table E-12). 

6  Percent total incidence and PM2.5-related incidence (IHD-related 

7 mortality): the percent of total long-term exposure mortality incidence (IHD) 

8 associated with PM2.5 exposure under recent conditions for the 2007 

9 simulation year is significantly higher than all-cause mortality, ranging from 

10 6.6% (Tacoma) to 17.3% (Birmingham) based on a C-R function derived 

11 using 1979-1983 PM2.5 data (Appendix E, Table E-24). Percent of total 

12 incidence for this mortality endpoint is even higher when a C-R function 

13 based on 1999-2000 PM2.5 monitoring data is used; ranging from 8.4% 

14 (Tacoma) to 23.6% (Fresno) (Appendix E, Table E-33). We note, that while 

15 the percent of total incidence is significantly larger for this health endpoint (3-

16 4 times as high as for total all-cause mortality), overall PM2.5–associated 

17 incidence is significantly less than PM2.5-associated incidence for all-cause 

18 mortality (on the order of about 50% lower, depending on the city – see 

19 results in Appendix E, Table E-12 versus E-30). This reflects the fact that 

20 baseline health effect incidence for all-cause mortality is significantly higher 

21 than for IHD mortality, which compensates for the greater slope of the IHD 

22 mortality effects estimate (see section 3.5). Total IHD-related mortality 

23 incidence associated with long-term exposure to PM2.5 ranges from about 70 

24 (Tacoma) to 2,000 (L.A.) (based on the C-R function derived using 1979-1983 

25 PM2.5 monitoring data - Appendix E, Table E-21) and from about 90 

26 (Tacoma) to 2,600 (L.A.) (based on the C-R function derived using 1999-2000 

27 PM2.5 monitoring data - Appendix E, Table E-30). 

28  Percent total incidence and PM2.5-related incidence (CPD-related 

29 mortality): overall percent of total incidence results for CPD mortality 

30 associated with long-term PM2.5 exposure under recent conditions for the 2007 

simulation year fall between those for all-cause and ischemic heart disease.37 31 

32 Specifically, estimates based on the C-R function derived using 1979-1982 

33 range from 3.6% (Tacoma) to 10.6% (Fresno) (Appendix E, Table E-42), with 

34 results based on the 1999-2000 C-R function being somewhat higher 

35 (Appendix E, Table E-51). Actual incidence estimates for this mortality 

36 endpoint are slightly less than for all-cause mortality, likely reflecting the fact 

37 that, while the effect estimates for CPD mortality are significantly larger than 

38 for all-cause mortality, the baseline health effects incidence rate is larger for 

39 all-cause mortality, again compensating for the smaller effects estimate. Total 

40 CPD-related mortality incidence associated with long-term exposure to PM2.5

41 ranges from 81 (Tacoma) to 2,300 (L.A.) (based on the C-R function derived 

42 using 1979-1983 PM2.5 monitoring data - Appendix E, Table E-39) and from 

 

37 This is expected, since IHD represents a subset of cardiopulmonary mortality. 
September 2009 98 Draft – Do Not Quote or Cite 

1 120 (Tacoma) to 3,200 (L.A.) (based on the C-R function derived using 1999-

2 2000 PM2.5 monitoring data - Appendix E, Table E-48). 

3  Percent total incidence and PM2.5-related incidence (lung cancer 

4 mortality): overall percent of total incidence estimates for lung caner 

5 mortality associated with long-term PM2.5 exposure under recent conditions 

6 for the 2007 simulation year are similar to estimates for CPD mortality. 

7 Specifically, using a C-R function derived using 1979-1982 PM2.5 monitoring 

8 data, percent incidence estimates range from 3.5% (Tacoma) to 10.4% 

9 (Fresno) (Appendix E, Table E-60). As expected, estimates derived using the 

10 C-R function based on 1999-2000 ambient monitoring data are larger (Seep 

11 Appendix E, Table E-69). We note, however, that actual PM2.5-associated 

12 lung cancer mortality incidence estimates are significant lower than those 

13 generated for CPD mortality, reflecting the significantly lower baseline health 

14 effects incidence rates associated with lung cancer mortality. Total lung 

15 cancer-related mortality incidence associated with long-term exposure to 

16 PM2.5 ranges from about 10 (Salt Lake City) to 240 (L.A.) (based on the C-R 

17 function derived using 1979-1983 PM2.5 monitoring data - Appendix E, Table 

18 E-57) and from 20 (Tacoma) to 340 (L.A.) (based on the C-R function derived 

19 using 1999-2000 PM2.5 monitoring data - Appendix E, Table E-66). 

20  Pattern in percent of total incidence across urban study areas: 

21 Differences across urban study areas for the different long-term mortality 

22 categories can be significant (e.g., a factor of over 2 for all cause mortality 

23 between Tacoma and Fresno, the two locations with the greatest disparity in 

24 estimated incidence – see Appendix E, Table E-3). This spread in incidence 

25 estimates likely results primarily from differences in underlying recent 

26 conditions ambient air PM2.5 levels across the urban study areas (see 

27 Appendix A), with differences in baseline health effects incidence data also 

28 playing a role (see section 3.5). However, because the C-R functions used to 

29 estimate incidence rates for long-term mortality are not differentiated by 

30 region or urban study area (see section 3.4 - i.e., the same function is used for 

31 all study areas for a given long-term mortality endpoint), differences in 

32 incidence estimates generated across the urban study areas do not reflect any 

33 underlying differences in the potential response of populations (located in 

34 different urban areas) to PM2.5 exposure. We note, that as discussed in section 

35 3.6.2 and 3.6.3, there is the potential for regional differences in PM2.5 sources 

36 and composition, as well as other factors related to long-term PM exposure 

37 and risk, that may well produce differences in the response of populations to 

38 PM2.5 exposure, however, we are not currently able to reflect this factor 

39 quantitatively in modeling long-term exposure-related mortality. 

40  Pattern of percent of total incidence across the three simulated years 

41 (2005-2007): A comparison of all-cause mortality incidence estimates (based 

42 on the C-R function derived using 1979-1982 monitoring data) across the 

43 three years (see Appendix E, Tables E-19 through E-21) shows that, while 

44 2007 does produce incidence estimates between those estimated for 2005 and 

45 2006 for some urban areas (e.g., Tacoma, St. Louis, LA), results for 2007 can 
September 2009 99 Draft – Do Not Quote or Cite 

1 be the highest of the three years (e.g., Fresno) or the lowest (e.g., Baltimore) 

2 for some locations. Generally, results for the same urban study area across the 

3 three years are fairly similar (results for Birmingham vary by less than 3% 

4 across the years), although they can vary by as much as 30% or more in some 

5 locations (see results for Tacoma in 2005 and 2006). All of this temporal 

6 variation results from year-to-year variation in the annual average PM2.5 levels 

7 for the study areas (see Appendix A). This is because other candidate input 

8 parameters, which could also involve temporal variability (e.g., demographics 

9 and baseline incidence rates) were not modeled with year-specific values, but 

10 rather using one representative year (see section 3.4.1.3 and 3.5 for 

11 demographics and baseline health effects incidence rates, respectively). 

12  Statistical significance of the effect estimates underlying the risk 

13 estimates and implications for interpretation of those risk estimates: All 

14 of the effects estimates used in modeling long-term mortality categories are 

15 statistically significant and consequently none of the confidence intervals (or 

16 associated best estimates) include negative incidence estimates. We note, that 

17 this is in contrast to results for recent air quality generated for short-term 

18 mortality and morbidity health effects endpoints, in which case some of the 

19 effects estimates were not statistically significant, as noted below. 

20  Relationship between all-cause and IHD PM2.5-associated incidence 

21 estimates for New York City: The estimated incidence attributable to PM2.5

22 for all cause mortality in New York City (for recent conditions in 2007) is 

23 1,500 (see Appendix E, Table E-3). However, estimated incidence for IHD 

24 attributable to PM2.5 (for recent conditions in 2007) is 2,000 (Appendix E, 

25 Table E-21). This set of estimates is counter to what would be expected, since 

26 IHD is a subset of all-cause mortality. This outcome likely results from the 

27 fact that we are applying national-scale effects estimates to individual urban 

28 study areas, which, in the case of New York City has significantly different 

29 baseline incidence rates for all cause and critically, IHD mortality, compared 

with national estimates.38 30 If (a) the fraction of all-cause mortality attributable 

31 to IHD is greater in New York City, compared with the national average 

32 (which is supported by the data cited here) and (b) the effect estimate for IHD 

33 mortality is larger than for all-cause (see section 3.3.4), it would then follow 

34 that the estimate for all-cause mortality generated for New York City is biased 

35 low. Specifically, the effect estimate for all-cause mortality obtained from 

36 Krewski et al., 2009 reflects a fraction of IHD-related deaths that is 

37 significantly lower than that seen in New York City, which would result in a 

38 downward-bias in the effects estimate for all-cause mortality for New York 

39 City. Consequently, if this explanation holds, then the all-cause PM2.5-

 38 Specifically, the baseline incidence rates for IHD mortality for New York City are 380 per 100,000 while 

national rate is 242 per 100,000 (see section 3.5, Table 3-9). This translates into New York City having 

approximately 1.5 times the rate of IHD deaths relative to the national average. All-cause mortality 

baseline incidence also differs, although to a lesser extent, with New York City having 1,077 per 100,000 

and the national-average being 1,327 per 100,000. This translates into New York City having a baseline 

incidence rate for all-cause mortality that is 23% lower than the national average. 
September 2009 100 Draft – Do Not Quote or Cite 

1 associated mortality estimate for New York City should be larger than what is 

2 presented. It is important to note that many other factors can potentially 

3 influence the magnitude of effects estimates for specific locations (e.g., PM2.5

4 sources and composition, differences in population susceptibility and 

5 vulnerability). 

6 4.1.2 Short-term exposure mortality 

7 This section summarizes core estimates for short-term exposure mortality (non8 accidental, IHD, CVD and respiratory) generated for the recent conditions air quality 

9 scenario for simulation year 2007. 

10  Percent of total incidence and PM2.5-related incidence (non-accidental 

11 mortality): the percent of total short-term exposure (non-accidental) mortality 

12 incidence associated with PM2.5 exposure under recent conditions for the 2007 

13 simulation year is estimated to range from 0.2% (Los Angeles) to 1.7% 

14 (Baltimore) (Appendix E, Table E-78). This estimate is notably lower than that 

15 generated for long-term exposure (all cause) mortality (see above). Total PM2.5-

16 related incidence estimates for this mortality category, vary greatly across the 

17 study areas, ranging from about 50 (Birmingham) to 790 (New York) - see 

18 Appendix E., Table E-75). Of the 15 urban study areas modeled for this endpoint, 

19 three locations had negative lower bound estimates of incidence, reflecting use of 

20 non-statistically significant effects estimates (see section 4.0 for additional 

21 discussion). 

22  Percent total incidence (CVD mortality): the percent of short-term exposure 

23 mortality incidence (CVD) associated with PM2.5 exposure under recent 

24 conditions for the 2007 simulation year is similar to non-accidental mortality, 

25 with the highest estimate being 2.3% (Philadelphia) (Appendix E, Tables E-87). 

26 Total PM2.5-related incidence estimates for this mortality category also vary 

27 greatly across the study areas (ranging from -50 (Los Angeles) to 510 (New York) 

28 - see Appendix E., Table E-84). Of the 15 urban study areas modeled for this 

29 endpoint, 12 locations had negative lower bound estimates of incidence (and two 

30 of these head negative point estimates), reflecting use of non-statistically 

31 significant effects estimates (see section 4.0 for additional discussion). 

32  Percent total incidence and PM2.5-related incidence (respiratory mortality): 

33 the percent of short-term exposure mortality incidence (respiratory) associated 

34 with PM2.5 exposure under recent conditions for the 2007 simulation year is also 

35 similar to estimates for non-accidental mortality, with the largest estimate being 

36 2.9% (Fresno) (Appendix E, Table E-96). Total PM2.5-related incidence estimates 

37 for this mortality category, vary greatly across the study areas, ranging from 8 

38 (Tacoma) to 110 (New York) - see Appendix E., Table E-93). Of the 15 urban 

39 study areas modeled for this endpoint, six locations had negative lower bound 

40 estimates of incidence, reflecting use of non-statistically significant effects 

41 estimates (see section 4.0 for additional discussion). 
September 2009 101 Draft – Do Not Quote or Cite 

1  Pattern in percent of total incidence across urban study areas: Differences 

2 across urban study areas for the different short-term exposure mortality categories 

3 can be large (e.g., a factor of 2 or higher for non-accidental mortality between 

4 Detroit and Baltimore, the two locations with the greatest disparity in statistically5 significant percent of total incidence estimates – see Appendix E, Table E-78). 

6 We note, that differences in this risk metric across urban study areas are 

7 substantially higher (up to an order of magnitude) if estimates are compared 

8 without consideration for statistical significance (e.g., compare 0.2% for non9 accidental mortality in Los Angeles with 1.7% in Baltimore – see Appendix E, 

10 Table E-78)). The greater overall difference in this risk metric across urban study 

11 areas for short-term mortality categories compared with long-term mortality 

12 categories (see last section) is to be expected given that both the effect estimates 

13 as well as patterns of daily ambient PM2.5 levels differ across the urban locations, 

14 while with long-term mortality, only annual-average PM2.5 levels differ (as noted 

15 earlier, the same effect estimates is used in modeling incidence for all urban study 

16 areas for a given long-term exposure mortality category – see section 3.3.4). 

17  Pattern of percent of total incidence across the three simulated years (2005-

18 2007): A comparison of non-accidental mortality incidence estimates across the 

19 three years (see Appendix E, Tables E-76 through E-78) shows that, while 2007 

20 does produce incidence estimates between those estimated for 2005 and 2006 for 

21 some urban areas (e.g., Dallas, Houston, Los Angeles, New York, Pittsburgh), 

22 results for 2007 can be the highest of the three years (e.g., Atlanta, Fresno) or the 

23 lowest (e.g., Detroit, Philadelphia) in some of the 15 urban study areas. 

24 Generally, results for the same urban study area across the three years are fairly 

25 similar (results for Atlanta vary by less than 2% across the three years), although 

26 they can vary by as much as 26% or more (compare results for Detroit in 2005 

27 and 2007). As with the long-term mortality risk metrics, all of this temporal 

28 variation results from year-to-year variation in the daily PM2.5 levels for the study 

29 areas (see Appendix A), given that other candidate input parameters, which could 

30 have temporal variability (e.g., demographics and baseline incidence rates) were 

31 not modeled with year-specific values, but rather using one representative year 

32 (see sections 3.4.1.3 and 3.5 for demographics and baseline health effects 

33 incidence rates, respectively). 

34  Comparison of long-term exposure and short-term exposure mortality 

35 estimates: The PM2.5-related incidence for short-term exposure (non-accidental) 

36 mortality is notably smaller than the estimate for long-term exposure (all cause) 

37 mortality, with short-term incidence on an aggregate annual basis generally 

38 ranging from 25 to 50% of the long-term (annual) estimate for the same city. 

39 Furthermore, the maximum value for short-term (non-accidental) mortality is 

40 about 790 for New York, while the largest value for long-term (all cause) 

41 mortality is 2,900 for Los Angeles (both values are for simulation year 2007). It 

42 is interesting to note that maximum estimates for these two mortality endpoints 

43 did not occur in the same urban study area. 

44 
September 2009 102 Draft – Do Not Quote or Cite 

1 4.1.3 Short-term exposure morbidity 

2 This section summarizes core estimates for short-term exposure morbidity (HA 

3 for CVD and respiratory; ED visits for CV, respiratory and asthma) generated for the 

4 recent conditions air quality scenario for simulation year 2007. 

5  Percent of total incidence and PM2.5-related incidence (CVD HAs): the 

6 percent of total short-term exposure (CV) HAs associated with PM2.5 exposure 

7 under recent conditions for the 2007 simulation year is estimated to range from 

8 0.4% (Atlanta) to 1.65% (Pittsburgh) (Appendix E, Table E-105). Total PM2.5-

9 related incidence estimates for this morbidity category, range from 20 (Salt Lake 

10 City) to 810 (New York) (see Appendix E., Table E-102). Of the 15 urban study 

11 areas modeled for this endpoint, five locations had negative lower bound 

12 estimates of incidence, reflecting use of non-statistically significant effects 

13 estimates (see section 4.0 for additional discussion). 

14  Percent of total incidence and PM2.5-related incidence (respiratory HAs): the 

15 percent of total short-term exposure (respiratory) HAs associated with PM2.5 

16 exposure under recent conditions for the 2007 simulation year is estimated to 

17 range from 0.17% (Tacoma) to 1.6% (Fresno) (Appendix E, Table E-114). This 

18 estimate is similar to estimates generated for total short-term (CV) HAs. Total 

19 PM2.5-related incidence estimates for this morbidity category, range from <10 

20 (Tacoma) to 270 (Los Angeles) (see Appendix E., Table E-110). Of the 15 urban 

21 study areas modeled for this endpoint, eleven locations had negative lower bound 

22 estimates of incidence, reflecting use of non-statistically significant effects 

23 estimates (see section 4.0 for additional discussion). 

24  Percent of total incidence and PM2.5-related incidence (ED visits for CV, 

25 respiratory and asthma illness): in contrast to the other short-term and long26 term exposure endpoints discussed in this section (and included in the core 

27 analysis), ED visit endpoints were assessed for specific urban case study 

28 locations, using epidemiological studies (and associated effects estimates) derived 

29 specifically for those locations. Percent of total incidence estimates for both 

30 endpoints for the recent conditions air quality scenario was 0.6% (see Appendix 

31 E, Table E-123) with PM2.5-related incidence estimates being 220 (CV) and 830 

32 (respiratory) for recent conditions in simulation year 2007. The results for 

33 Atlanta both included negative lower bound estimates, reflecting use of non34 statistically significant effects estimates (see section 4.1 for additional 

35 discussion). Percent of total incidence attributable to PM2.5 for ED visits in New 

36 York (for asthma) is 6.2% while the related total PM2.5-associated incidence 

37 estimate is 1,100 (Appendix E, Table E-120). The effect estimates used in 

38 evaluating ED visits for New York is statistically significant. 

39  Pattern in percent of total incidence across urban study areas: Differences 

40 across urban study areas for the different short-term exposure HAs categories can 

41 be significant (e.g., a factor of over 3 for CV HAs between Houston and 

42 Pittsburgh, the two locations with the greatest disparity in percent of total 

43 incidence estimates – see Appendix E, Table E-105). We note, that variation in 
September 2009 103 Draft – Do Not Quote or Cite 

1 risk estimates across cities for this endpoint category is significantly smaller than 

2 that for short-term mortality. This is not unexpected since location-specific 

3 effects estimates were not used in modeling short-term exposure HAs (regional 

4 estimates were used), while short-term exposure mortality, as noted earlier, was 

5 modeled using location-specific effects estimates. 

6  Pattern of percent of total incidence across the three simulated years (2005-

7 2007): A comparison of CV illness-related HAs incidence estimates across the 

8 three years (see Appendix E, Tables E-100 through E-102) shows that, while 2007 

9 does produce incidence estimates between those estimated for 2005 and 2006 for 

10 six of the 15 urban study areas, for the remaining locations, estimates for 2007 

11 sometimes represent the highest and sometimes the lowest estimates. Generally, 

12 results for the same urban study area across the three years are fairly similar 

13 (results for Atlanta vary by less than 2% across the years), although they can vary 

14 by as much as 17% or more (compare results for St Louis in 2005 and 2007). As 

15 with the long-term and short-term exposure mortality risk metrics, all of this 

16 temporal variation results from year-to-year variation in the daily PM2.5 levels for 

17 the study areas (see Appendix A), given that other candidate input parameters, 

18 which could have temporal variability (e.g., demographics and baseline incidence 

19 rates) were not modeled with year-specific values, but rather using one 

20 representative year (see section 3.4.1.3 and 3.5 for demographics and baseline 

21 health effects incidence rates, respectively). 

22 4.2 ASSESSMENT OF HEALTH RISK ASSOCIATED WITH JUST 

23 MEETING THE CURRENT AND ALTERNATIVE STANDARDS 

24 (CORE ANALYSIS) 

25 This section discusses core (i.e., base case) risk estimates generated for the 

26 current set of standards and alternative sets of standard, focusing on the 2007 simulation 

27 year (although general trends in observations across the three simulated years are 

28 discussed to a limited extent). The results discussed below are based on results from 14 

29 of the 15 study areas, with Pittsburgh being excluded at this time due to an error that was 

30 identified in the approach used to simulate ambient PM2.5 levels just for the Pittsburgh 

31 study area for the scenarios involving just meeting the current and alternative sets of 

32 standards. As noted earlier in section 2.4.1, there was insufficient time after identifying 

33 this error to either generate corrected risk estimates or remove the erroneous risk 

34 estimates from the summary tables (presented in Appendix E). We will correct this error 

35 and release updated results for the Pittsburgh study area as soon as is practicable and will 

36 include the corrected results in the next version of this document. 

37 In discussing risk estimates for the current and alternative standards, we have 

38 emphasized the incremental reduction (delta) across sets of standards rather than focusing 

39 on the absolute degree of risk (total PM2.5-related incidence) for a particular set of 

40 standards. This reflects the fact that we have greater confidence in the ability of the risk 
September 2009 104 Draft – Do Not Quote or Cite 

1 models to differentiate risk between sets of standards, since this requires the models to 

2 estimate risk for ambient air PM2.5 levels likely near or within the range of ambient air 

3 quality data used in the underlying epidemiology studies. By contrast, estimates of 

4 absolute risk (for a given air quality scenario) require the models to perform at the lower 

5 boundary of ambient air PM2.5 levels reflected in the studies (i.e., down to the LML 

6 reflected in the long-term exposure mortality epidemiology studies or down to PRB 

7 levels in the short-term exposure morbidity and mortality studies). There is greater 

8 overall uncertainty in risk estimates generated based on the contribution to risk of 

9 exposures at these lower ambient air PM2.5 levels. 

10 This section is organized by health endpoint category, with results discussed in 

11 the following order: long-term exposure mortality, short-term exposure mortality and 

12 short-term exposure morbidity. We note, that observations presented in the last section 

13 regarding the statistical significance of effects estimates used in generating risk estimates 

14 and their implications for interpretation of those risk estimates also hold for estimates 

15 presented in this section. Consequently, observations regarding risk results with 

16 confidence intervals including negative estimates are not presented here and the reader is 

17 referred back to the earlier discussion in section 4.1. 

18 An important factor to consider in interpreting the risk estimates for both the 

19 current set of standards and sets of alternative standards is whether the annual or 24-hour 

standard for a given pairing of standards is controlling for a particular area.39 20 This factor 

21 can have a significant impact on the pattern of risk reductions predicted for a given 

22 location under the simulation of just meeting a specific set of standards. A brief 

23 overview of which urban study areas are predicted to have risk reductions under the set of 

24 current standards and alternative sets of standards included in the risk assessment is 

25 presented below. 

26  Current set of standards: Two of the 14 urban study areas (Dallas and Phoenix) 

27 have both annual and 24-hr design values that are below the matching current 

standard levels of 15 and 35 μg/m3, respectively (see Table 3-3).40 28 This means 

29 that these two urban study areas would not have any reduction in long-term or 

30 short-term exposure risk under the current standards, as reflected in the 

 39 For a given pairing of standard levels (e.g., 13/35), the controlling standard can be identified by 

comparing these levels to the design values for a given study area (see Table 3-3 for the annual and 24-hr 

design values for each of the urban study areas). The controlling standard is the standard (annual or 24 hr) 

that requires the greatest percent reduction in the matching design value to meet that standard. 40 As noted earlier, Pittsburgh has been excluded due to an error that was identified in the approach used to 

simulate ambient PM2.5 levels just for the Pittsburgh study area for the scenarios involving just meeting the 

current and alternative sets of standards. Consequently, the number of study areas discussed in relation to 

the current set of standards (as well as alternative sets of standards) is 14, rather than 15. 
September 2009 105 Draft – Do Not Quote or Cite 

1 summaries presented below (note, however, that both areas have predicted risk 

2 reductions under some of the alternative sets of standards). 

3  Alternative sets of standards focusing on lower annual standard levels (13/35 

4 and 12/35): Dallas and Phoenix had annual and 24-hour design values which 

5 were lower than the 13/35 set of alternative standards, but annual design values 

6 were above the 12/35 set of alternative standards (see Table 3-3). For two of the 

7 other study areas (Fresno and Los Angeles), where the 24-hr standard was 

8 controlling, simulating just meeting the current standard resulted in significant 

9 reductions in the annual PM2.5 levels, such that no risk reduction was seen for the 

10 13/35 alternative set of standards (i.e., adjusted annual PM2.5 levels for these 

study areas under the current set of standards were already below 13 μg/m3 11 ). We 

12 note, however, that Los Angeles did show risk reductions under the 12/35 set of 

13 standards, while Fresno continued not to have predicted risk reductions under the 

14 12/35 set of alternative standards due to the significant reduction in annual levels 

15 associated with just meeting the current set of standards. Because Tacoma and 

Salt Lake City already had annual design values (10 and 12 μg/m3 16 , respectively) 

at or below the 12 μg/m3 17 associated with the lower of these two alternative sets of 

18 standards, neither study area exhibited risk reductions. 

19  Alternative sets of standards focusing on combinations of lower annul and 

20 lower 24-hour standard levels (13/30, 12/25): Because of the combination of 

21 lower 24-hr and annual levels, 13 of the 14 urban study areas had risk reductions 

22 under the 13/30 standard level (only Dallas continued not to have predicted risk 

23 reductions), while all 14 urban study areas exhibited risk reductions under the 

24 12/25 alternative set of standards. 

25 Note, that this pattern of urban areas experiencing risk reductions under various 

26 standard levels, is reflected in the detailed discussion of risk estimates provided below in 

27 sections 4.2.1 through 4.2.3. 

28 4.2.1 Long-term exposure mortality 

29 This section summarizes core estimates for long-term exposure mortality (all 

30 cause, IHD, CPD and lung cancer) generated for the current and alternative sets of 

31 standards for simulation year 2007. 

32  Comparison of recent conditions risk with risk associated with current 

33 standards: a shift in ambient air PM2.5 levels from recent conditions to the 

34 current standards is predicted to result in notable reductions in the percent of total 

35 incidence (for long-term exposure all cause mortality) attributable to PM2.5 across 

36 most of the urban case study locations. For example, Fresno is estimated to have 

37 a ~60% reduction in percent of total incidence attributable to PM2.5 under the 

38 current standards for simulation year 2007 using C-R functions based on either 

39 ambient monitoring period (relative to recent conditions – see Appendix E, Table 

40 E-6 and E-15). However, a subset of urban case studies with recent ambient air 

41 PM2.5 levels at or below the current standards (e.g., Dallas, Phoenix – see 

42 Appendix E, Table E-6 and E-15) are not estimated to experience reductions in 
September 2009 106 Draft – Do Not Quote or Cite 

1 long-term exposure mortality-related risk. A similar pattern of risk reduction is 

2 seen for the other long-term mortality categories, with most locations having 

3 estimated reductions of up to ~60% and a subset of locations not estimated to 

4 have any reductions because their recent conditions ambient air PM2.5 levels are 

5 already at or below the current standards. This pattern of risk changes associated 

6 with moving from recent conditions to the current standards is depicted 

7 graphically in Figures 4-1 through 4-8. We note, however, that in these plots, risk 

8 for each of the long-term mortality categories is expressed in terms of the percent 

9 change relative to the current standards, and thus, the values are depicted as 

10 negative values reflecting the fact that these figures focus on reductions in risk for 

11 alternative sets of standards, relative to the current set of standards. 

12  Trends in risk reduction across alternative sets of standards focusing on 

13 lower annual levels (13/35 and 12/35 combinations): reducing ambient PM2.5

14 levels to meet alternative sets of standards with lower annual levels (i.e., 13/35 

15 and 12/35) is estimated to produce a systematic reduction in PM2.5-related all 

16 cause mortality for roughly half of the urban study areas. Specifically, in 

17 simulation year 2007, 8 of the 14 study areas would see estimated reductions in 

18 PM2.5-related all-cause mortality on the order of 5 to ~25% under a 13/35 

19 standard level combination with this reduction increasing to between 10 and 35% 

20 under the 12/35 combination (see Appendix E, Tables E-9 and E-18). These 

21 percentage reductions hold for incidence estimates generated using C-R functions 

22 based on ambient PM2.5 data from both ambient monitoring periods (see 

23 Appendix E, Tables E-9 and E-18). The estimated degree of reduction in PM2.5-

24 related mortality across these standard combinations with reduced annual levels is 

25 similar for the other long-term exposure mortality categories. This pattern of 

26 estimated risk reductions associated with moving from the current standards to 

27 alternative standard combinations (including lower annual levels) is depicted 

28 graphically in Figures 4-1 through 4-8. 

29  Trends in risk reduction across alternative sets of standards focusing on 

30 lower combinations of 24-hour and annual levels (13/30 and 12/25 

31 combinations): Under the 13/30 combination, PM2.5-related all cause mortality 

32 is reduced by a slightly greater amount than under the 13/35 combination 

33 discussed above with estimated percent reductions ranging from 14 to 44% - see 

34 Appendix E, Tables E-9 and E-18. With the more stringent 24-hour level (but 

35 same alternative annual level of 13), this standard level combination is estimated 

36 to reduce long-term exposure mortality risk in 13 of the 14 urban study areas, 

37 which is due to the fact that the 24-hour standard level is controlling in most of 

38 the urban study area locations for this combination of standards. When the most 

39 stringent set of standards (12/25) included in this analysis is modeled, the overall 

40 degree of reduction in PM2.5-attributable all cause long-term mortality is the 

41 largest (relative to the current standards) with estimated percent reductions 

42 ranging from 12 to 89% - see Appendix E, Tables E-9 and E-18 (and all of the 

43 urban study areas are predicted to experience some degree of risk reduction). We 

44 note that estimates for the other long-term exposure mortality categories in terms 

45 of risk reductions associated with these two alternative standard combinations are 
September 2009 107 Draft – Do Not Quote or Cite 

1 similar to those presented above for all-cause. This pattern of risk reductions 

2 associated with moving from the current standards to alternative standard 

3 combinations (including lower 24-hour and annual levels) is depicted graphically 

4 in Figures 4-1 through 4-8. 

5  Pattern of reduction of PM2.5-associated long-term mortality incidence across 

6 urban study areas under alternative combinations of standards: Differences 

7 in the degree of reduction of PM2.5-related long-term exposure mortality risk 

8 across the 14 urban study areas can be substantial. For example, considering 

9 reductions in all-cause mortality under the most stringent alternative standards 

10 combination (12/25), percent reductions in incidence (relative to risk associated 

11 with just meeting the current standards) range from 12% (Dallas) to 89% 

12 (Tacoma) (Appendix E, Tables E-9 and E-18). In the case of Dallas, reductions 

13 are more modest because of relatively low recent conditions ambient air PM2.5

14 levels (relative to the alternative standards considered – see Appendix A). With 

15 Tacoma, the greater degree of risk reduction results from having a single monitor 

16 with an annual average PM2.5 estimate (under recent conditions) that is lower than 

17 the alternative standards considered, but 24-hour average levels that are elevated 

18 relative to the 24-hour standard. Therefore, for Tacoma, the most stringent 

alternative standard combination (12/25), with a 24-hour level of 25 μg/m3 19 , has a 

20 relatively large impact on overall risk, as reflected in the 89% reduction in the risk 

21 estimate. Both of these examples illustrate that, with regard to the degree of risk 

22 reduction under alternative sets of standards, variation across urban study areas 

23 not only reflects variation in baseline incidence rates, but also a number of factors 

24 related to ambient air PM2.5 levels, including absolute levels in terms of both 

25 annual-averaged values and the distribution of 24-hour levels, and how these 

26 translate into design values for a given study area. Figures 4-1 through 4-8 

27 provide a ready means for comparing the spread in the relative degree of risk 

28 reduction for long-term exposure mortality resulting from alternative sets of 

29 standards across the 14 urban study areas. 

30  Pattern of percent reduction of total incidence across the three simulated 

31 years (2005-2007): Reductions in PM2.5-associated long-term exposure mortality 

32 associated with alternative sets of standards across the simulation years (2005-

33 2007) do display significant variation, however, this variation is smaller than the 

34 variation in risk reductions across urban study areas for the same simulation year

35 (as discussed in the previous bullet). For example, for long-term PM2.5-related 

36 all-cause mortality, the two urban study areas with the greatest degree of 

37 reduction under the most stringent standard level combination (12/25) (Salt Lake 

38 City and Tacoma), retain that status across all three years and have percent 

39 reductions that vary by 12 and 32%, respectively, across the three simulation 

40 years (based on comparison of results in Appendix E, Tables E-7 through E-9 and 

41 Tables E-16 through E-18). Variation across the three simulation years (for the 

42 same urban study area) for other long-term mortality categories and for other 

43 alternative suite of standards is generally somewhat below this range, with greater 

44 variation in degree of risk reduction (across the three years for a given study area) 

45 seen with more stringent sets of standards, and with urban study areas modeled 
September 2009 108 Draft – Do Not Quote or Cite 

1 using fewer PM2.5 monitors. It appears that, as a generality, urban locations with 

2 a greater number of monitors, such as Los Angeles, are buffered somewhat from 

3 year-to-year variations in annual levels, relative to locations with a smaller 

4 number of monitors, such as Tacoma. 
September 2009 109 Draft – Do Not Quote or Cite 

1 Figure 4-1. Estimated Percent Reductions From the Current Standards to 

2 Alternative Set of Standards in All Cause Mortality Associated with 

3 Long- Term Exposure to PM2.5 (Exposure Period: 1979 – 1983): 

4 Based on 2007 Air Quality Data.* 

-200%

-180%

-160%

-140%

-120%

-100%

-80%

-60%

-40%

-20%

0%

20%

40%

60%

80%

100%

2007 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Reduction from Current Standard

 Atlanta, GA 571 (370 - 769); 3.6% (2.3% - 4.8%)

 Baltimore, MD 439 (284 - 592); 3.1% (2% - 4.2%)

 Birmingham, AL 335 (217 - 451); 3.3% (2.2% - 4.5%)

 Dallas, TX 311 (201 - 420); 2.3% (1.5% - 3.1%)

 Detroit, MI 366 (236 - 494); 2.1% (1.3% - 2.8%)

 Fresno, CA 112 (73 - 152); 2% (1.3% - 2.6%)

 Houston, TX 687 (445 - 926); 3.5% (2.3% - 4.7%)

 Los Angeles, CA 979 (632 - 1323); 1.7% (1.1% - 2.3%)

 New York, NY 1067 (690 - 1442); 2% (1.3% - 2.7%)

 Philadelphia, PA 413 (267 - 557); 2.8% (1.8% - 3.8%)

 Phoenix, AZ 451 (292 - 610); 1.8% (1.2% - 2.5%)

 Pittsburgh, PA 236 (153 - 319); 1.7% (1.1% - 2.3%)

 Salt Lake City, UT 52 (34 - 71); 1% (0.7% - 1.4%)

 St. Louis, MO 545 (353 - 735); 2.9% (1.9% - 3.9%)

 Tacoma, WA 53 (34 - 72); 1% (0.7% - 1.4%)

5 

6 *Based on Krewski et al. (2009), exposure period from 1979 – 1983. The legend contains, for each urban 

7 area, the incidence estimate (and 95% CI) and the estimate of percent of total incidence (and 95% CI) under 

8 the current standards. 

** The current standards consist of an annual standard of 15 μg/m3 and a 24-hour standard of 35 μg/m3 9 . 

10 Combinations of an annual standard (n) and a 24-hour standard (m) are denoted n/m in this figure. 

11 

12 

13 
September 2009 110 Draft – Do Not Quote or Cite 

1 Figure 4-2. Estimated Percent Reductions From the Current Standards to 

2 Alternative Set of Standards in All Cause Mortality Associated with 

3 Long-Term Exposure to PM2.5 (Exposure Period: 1999 – 

4 2000): Based on 2007 Air Quality Data.* 

-200%

-180%

-160%

-140%

-120%

-100%

-80%

-60%

-40%

-20%

0%

20%

40%

60%

80%

100%

2007 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Redcution from Current Standard

 Atlanta, GA 731 (467 - 990); 4.6% (2.9% - 6.2%)

 Baltimore, MD 563 (359 - 764); 4% (2.5% - 5.4%)

 Birmingham, AL 429 (274 - 581); 4.3% (2.7% - 5.8%)

 Dallas, TX 399 (254 - 542); 3% (1.9% - 4.1%)

 Detroit, MI 469 (299 - 638); 2.7% (1.7% - 3.6%)

 Fresno, CA 144 (92 - 196); 2.5% (1.6% - 3.4%)

 Houston, TX 880 (562 - 1193); 4.5% (2.9% - 6.1%)

 Los Angeles, CA 1257 (799 - 1711); 2.2% (1.4% - 3%)

 New York, NY 1370 (871 - 1863); 2.6% (1.6% - 3.5%)

 Philadelphia, PA 530 (338 - 719); 3.6% (2.3% - 4.9%)

 Phoenix, AZ 580 (369 - 789); 2.3% (1.5% - 3.2%)

 Pittsburgh, PA 303 (193 - 413); 2.2% (1.4% - 3%)

 Salt Lake City, UT 67 (43 - 91); 1.3% (0.8% - 1.8%)

 St. Louis, MO 698 (445 - 948); 3.7% (2.3% - 5%)

 Tacoma, WA 69 (44 - 94); 1.3% (0.8% - 1.8%)

5 

6 *Based on Krewski et al. (2009), exposure period from 1999 - 2000. The legend contains, for each urban 

7 area, the incidence estimate (and 95% CI) and the estimate of percent of total incidence (and 95% CI) under 

8 the current standards. 

** The current standards consist of an annual standard of 15 μg/m3 and a 24-hour standard of 35 μg/m3 9 . 

10 Combinations of an annual standard (n) and a 24-hour standard (m) are denoted n/m in this figure. 
September 2009 111 Draft – Do Not Quote or Cite 

1 Figure 4-3. Estimated Percent Reductions From the Current Standards to 

2 Alternative Set of Standards in Ischemic Heart Disease Mortality 

3 Associated with Long-Term Exposure to PM2.5 (Exposure Period: 

4 1979 – 1983): Based on 2007 Air Quality Data.* 

-200%

-180%

-160%

-140%

-120%

-100%

-80%

-60%

-40%

-20%

0%

20%

40%

60%

80%

100%

2007 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Reduction from Current Standard

 Atlanta, GA 221 (181 - 260); 13.3% (10.9% - 15.6%)

 Baltimore, MD 296 (243 - 349); 11.7% (9.6% - 13.7%)

 Birmingham, AL 149 (122 - 175); 12.5% (10.2% - 14.7%)

 Dallas, TX 191 (156 - 226); 8.8% (7.2% - 10.4%)

 Detroit, MI 327 (267 - 386); 7.9% (6.4% - 9.3%)

 Fresno, CA 86 (70 - 102); 7.5% (6.1% - 8.8%)

 Houston, TX 417 (342 - 489); 13% (10.7% - 15.3%)

 Los Angeles, CA 923 (752 - 1091); 6.5% (5.3% - 7.7%)

 New York, NY 1432 (1169 - 1692); 7.6% (6.2% - 9%)

 Philadelphia, PA 267 (218 - 314); 10.7% (8.7% - 12.6%)

 Phoenix, AZ 329 (269 - 389); 7% (5.7% - 8.3%)

 Pittsburgh, PA 180 (147 - 213); 6.6% (5.3% - 7.8%)

 Salt Lake City, UT 21 (17 - 25); 4% (3.2% - 4.7%)

 St. Louis, MO 429 (351 - 505); 10.8% (8.8% - 12.7%)

 Tacoma, WA 41 (33 - 48); 3.9% (3.2% - 4.6%)

5 

6 *Based on Krewski et al. (2009), exposure period from 1979 – 1983. The legend contains, for each urban 

7 area, the incidence estimate (and 95% CI) and the estimate of percent of total incidence (and 95% CI) under 

8 the current standards. 

** The current standards consist of an annual standard of 15 μg/m3 and a 24-hour standard of 35 μg/m3 9 . 

10 Combinations of an annual standard (n) and a 24-hour standard (m) are denoted n/m in this figure. 

11 
September 2009 112 Draft – Do Not Quote or Cite 

1 Figure 4-4. Estimated Percent Reductions From the Current Standards to 

2 Alternative Set of Standards in Ischemic Heart Disease Mortality 

3 Associated with Long-Term Exposure to PM2.5 (Exposure Period: 

4 1999 – 2000): Based on 2007 Air Quality Data.* 

-200%

-180%

-160%

-140%

-120%

-100%

-80%

-60%

-40%

-20%

0%

20%

40%

60%

80%

100%

2007 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Reduction from Current Standard

 Atlanta, GA 278 (228 - 326); 16.8% (13.7% - 19.6%)

 Baltimore, MD 374 (306 - 440); 14.7% (12% - 17.3%)

 Birmingham, AL 188 (154 - 220); 15.7% (12.9% - 18.4%)

 Dallas, TX 243 (198 - 286); 11.2% (9.1% - 13.2%)

 Detroit, MI 415 (338 - 490); 10% (8.1% - 11.8%)

 Fresno, CA 109 (89 - 129); 9.5% (7.7% - 11.2%)

 Houston, TX 524 (430 - 615); 16.4% (13.5% - 19.2%)

 Los Angeles, CA 1173 (954 - 1388); 8.3% (6.7% - 9.8%)

 New York, NY 1818 (1481 - 2148); 9.6% (7.8% - 11.4%)

 Philadelphia, PA 337 (276 - 397); 13.5% (11% - 15.9%)

 Phoenix, AZ 418 (341 - 495); 8.9% (7.2% - 10.5%)

 Pittsburgh, PA 229 (187 - 271); 8.3% (6.8% - 9.9%)

 Salt Lake City, UT 27 (22 - 31); 5.1% (4.1% - 6.1%)

 St. Louis, MO 541 (443 - 637); 13.7% (11.2% - 16.1%)

 Tacoma, WA 52 (42 - 62); 5% (4.1% - 5.9%)

5 

6 *Based on Krewski et al. (2009), exposure period from 1999 – 2000. The legend contains, for each urban 

7 area, the incidence estimate (and 95% CI) and the estimate of percent of total incidence (and 95% CI) under 

8 the current standards. 

** The current standards consist of an annual standard of 15 μg/m3 and a 24-hour standard of 35 μg/m3 9 . 

10 Combinations of an annual standard (n) and a 24-hour standard (m) are denoted n/m in this figure. 

11 
September 2009 113 Draft – Do Not Quote or Cite 

1 Figure 4-5. Estimated Percent Reductions From the Current Standards to 

2 Alternative Set of Standards in Cardiopulmonary Disease Mortality 

3 Associated with Long-Term Exposure to PM2.5 (Exposure Period: 

4 1979 – 1983): Based on 2007 Air Quality Data.* 

-200%

-180%

-160%

-140%

-120%

-100%

-80%

-60%

-40%

-20%

0%

20%

40%

60%

80%

100%

2007 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Reduction from Current Standard

 Atlanta, GA 452 (345 - 558); 7.3% (5.6% - 9%)

 Baltimore, MD 375 (286 - 463); 6.4% (4.9% - 7.9%)

 Birmingham, AL 290 (221 - 358); 6.8% (5.2% - 8.4%)

 Dallas, TX 264 (201 - 326); 4.8% (3.6% - 5.9%)

 Detroit, MI 347 (264 - 430); 4.3% (3.2% - 5.3%)

 Fresno, CA 108 (82 - 133); 4% (3.1% - 5%)

 Houston, TX 563 (429 - 694); 7.2% (5.5% - 8.8%)

 Los Angeles, CA 1002 (761 - 1241); 3.5% (2.7% - 4.4%)

 New York, NY 1188 (903 - 1471); 4.1% (3.1% - 5.1%)

 Philadelphia, PA 349 (266 - 431); 5.8% (4.4% - 7.2%)

 Phoenix, AZ 381 (289 - 471); 3.8% (2.9% - 4.7%)

 Pittsburgh, PA 214 (162 - 265); 3.5% (2.7% - 4.4%)

 Salt Lake City, UT 39 (30 - 48); 2.1% (1.6% - 2.7%)

 St. Louis, MO 505 (384 - 623); 5.9% (4.5% - 7.3%)

 Tacoma, WA 48 (36 - 60); 2.1% (1.6% - 2.6%)

5 

6 *Based on Krewski et al. (2009), exposure period from 1979 – 1983. The legend contains, for each urban 

7 area, the incidence estimate (and 95% CI) and the estimate of percent of total incidence (and 95% CI) under 

8 the current standards. 

** The current standards consist of an annual standard of 15 μg/m3 and a 24-hour standard of 35 μg/m3 9 . 

10 Combinations of an annual standard (n) and a 24-hour standard (m) are denoted n/m in this figure. 
September 2009 114 Draft – Do Not Quote or Cite 

1 

2 Figure 4-6. Estimated Percent Reductions From the Current Standards to 

3 Alternative Set of Standards in Cardiopulmonary Disease Mortality 

4 Associated with Long-Term Exposure to PM2.5 (Exposure Period: 

5 1999 – 2000): Based on 2007 Air Quality Data.* 

-200%

-180%

-160%

-140%

-120%

-100%

-80%

-60%

-40%

-20%

0%

20%

40%

60%

80%

100%

2007 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Reduction from Current Standard

 Atlanta, GA 640 (503 - 774); 10.4% (8.1% - 12.5%)

 Baltimore, MD 533 (418 - 645); 9.1% (7.1% - 11%)

 Birmingham, AL 411 (322 - 498); 9.7% (7.6% - 11.7%)

 Dallas, TX 376 (294 - 456); 6.8% (5.3% - 8.3%)

 Detroit, MI 495 (387 - 602); 6.1% (4.7% - 7.4%)

 Fresno, CA 154 (120 - 187); 5.8% (4.5% - 7%)

 Houston, TX 797 (625 - 964); 10.1% (8% - 12.3%)

 Los Angeles, CA 1431 (1116 - 1741); 5% (3.9% - 6.1%)

 New York, NY 1694 (1323 - 2060); 5.9% (4.6% - 7.1%)

 Philadelphia, PA 496 (388 - 601); 8.3% (6.5% - 10%)

 Phoenix, AZ 543 (424 - 661); 5.4% (4.2% - 6.6%)

 Pittsburgh, PA 305 (238 - 372); 5.1% (4% - 6.2%)

 Salt Lake City, UT 56 (44 - 68); 3.1% (2.4% - 3.7%)

 St. Louis, MO 717 (561 - 869); 8.4% (6.6% - 10.2%)

 Tacoma, WA 69 (53 - 84); 3% (2.3% - 3.7%)

6 

7 *Based on Krewski et al. (2009), exposure period from 1999 – 2000. The legend contains, for each urban 

8 area, the incidence estimate (and 95% CI) and the estimate of percent of total incidence (and 95% CI) under 

9 the current standards. 

** The current standards consist of an annual standard of 15 μg/m3 and a 24-hour standard of 35 μg/m3 10 . 

11 Combinations of an annual standard (n) and a 24-hour standard (m) are denoted n/m in this figure. 
September 2009 115 Draft – Do Not Quote or Cite 

1 Figure 4-7. Estimated Percent Reductions From the Current Standards to 

2 Alternative Set of Standards in Lung Cancer Mortality Associated 

3 with Long-Term Exposure to PM2.5 (Exposure Period: 1979 – 1983): 

4 Based on 2007 Air Quality Data.* 

-200%

-180%

-160%

-140%

-120%

-100%

-80%

-60%

-40%

-20%

0%

20%

40%

60%

80%

100%

2007 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Reduction from Current Standard

 Atlanta, GA 68 (26 - 108); 7.2% (2.7% - 11.4%)

 Baltimore, MD 60 (23 - 96); 6.3% (2.4% - 10%)

 Birmingham, AL 44 (17 - 70); 6.7% (2.5% - 10.7%)

 Dallas, TX 41 (15 - 66); 4.7% (1.8% - 7.5%)

 Detroit, MI 52 (20 - 84); 4.2% (1.6% - 6.7%)

 Fresno, CA 12 (4 - 19); 4% (1.5% - 6.4%)

 Houston, TX 86 (33 - 137); 7% (2.7% - 11.2%)

 Los Angeles, CA 105 (39 - 170); 3.5% (1.3% - 5.6%)

 New York, NY 112 (42 - 180); 4% (1.5% - 6.5%)

 Philadelphia, PA 56 (21 - 89); 5.7% (2.2% - 9.1%)

 Phoenix, AZ 55 (21 - 88); 3.7% (1.4% - 6%)

 Pittsburgh, PA 32 (12 - 52); 3.5% (1.3% - 5.6%)

 Salt Lake City, UT 4 (2 - 7); 2.1% (0.8% - 3.4%)

 St. Louis, MO 77 (29 - 123); 5.8% (2.2% - 9.3%)

 Tacoma, WA 8 (3 - 13); 2.1% (0.8% - 3.3%)

5 

6 *Based on Krewski et al. (2009), exposure period from 1979 – 1983. The legend contains, for each urban 

7 area, the incidence estimate (and 95% CI) and the estimate of percent of total incidence (and 95% CI) under 

8 the current standards. 

** The current standards consist of an annual standard of 15 μg/m3 and a 24-hour standard of 35 μg/m3 9 . 

10 Combinations of an annual standard (n) and a 24-hour standard (m) are denoted n/m in this figure. 
September 2009 116 Draft – Do Not Quote or Cite 

1 Figure 4-8. Estimated Percent Reductions From the Current Standards to 

2 Alternative Set of Standards in Lung Cancer Mortality Associated 

3 with Long-Term Exposure to PM2.5 (Exposure Period: 1999 – 2000): 

4 Based on 2007 Air Quality Data.* 

-200%

-180%

-160%

-140%

-120%

-100%

-80%

-60%

-40%

-20%

0%

20%

40%

60%

80%

100%

2007 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Reduction from Current Standard

 Atlanta, GA 98 (43 - 149); 10.4% (4.6% - 15.8%)

 Baltimore, MD 87 (38 - 133); 9.1% (4% - 13.8%)

 Birmingham, AL 63 (28 - 96); 9.7% (4.3% - 14.8%)

 Dallas, TX 59 (26 - 91); 6.8% (3% - 10.5%)

 Detroit, MI 76 (33 - 117); 6.1% (2.7% - 9.4%)

 Fresno, CA 17 (7 - 26); 5.8% (2.5% - 8.9%)

 Houston, TX 125 (55 - 190); 10.1% (4.5% - 15.4%)

 Los Angeles, CA 153 (67 - 238); 5% (2.2% - 7.8%)

 New York, NY 163 (71 - 252); 5.9% (2.6% - 9%)

 Philadelphia, PA 80 (35 - 123); 8.3% (3.6% - 12.7%)

 Phoenix, AZ 80 (35 - 123); 5.4% (2.4% - 8.3%)

 Pittsburgh, PA 47 (21 - 73); 5.1% (2.2% - 7.8%)

 Salt Lake City, UT 6 (3 - 9); 3.1% (1.3% - 4.8%)

 St. Louis, MO 112 (49 - 171); 8.4% (3.7% - 12.8%)

 Tacoma, WA 12 (5 - 18); 3% (1.3% - 4.7%)

5 

6 *Based on Krewski et al. (2009), exposure period from 1999 – 2000. The legend contains, for each urban 

7 area, the incidence estimate (and 95% CI) and the estimate of percent of total incidence (and 95% CI) under 

8 the current standards. 

** The current standards consist of an annual standard of 15 μg/m3 and a 24-hour standard of 35 μg/m3 9 . 

10 Combinations of an annual standard (n) and a 24-hour standard (m) are denoted n/m in this figure. 
September 2009 117 Draft – Do Not Quote or Cite 

1 

2 4.2.2 Short-term exposure mortality 

3 This section summarizes core estimates for short-term exposure mortality (non4 accidental, IHD, CVD and respiratory) generated for the current and alternative sets of 

5 standards for simulation year 2007. 

6  Comparison of recent conditions risk with risk associated with current 

7 standards: A shift in ambient air PM2.5 levels from recent conditions to just 

8 meeting the current set of standards results in notable reductions in the estimates 

9 of percent of total incidence for short-term exposure non-accidental mortality 

10 attributable to PM2.5 across most of the urban case studies. For example, Fresno, 

11 Los Angeles and Salt Lake City are estimated to have reductions in the range of 

12 up to 40 to 50% of total incidence attributable to PM2.5 under the current 

13 standards for simulation year 2007 – see Appendix E, Table E-78). However, a 

14 subset of urban case studies with recent ambient air PM2.5 levels at or below the 

15 current standards (e.g., Dallas, Phoenix – see Appendix E, Table E-78) do not 

16 experience any reductions in estimated short-term mortality-related risk, as would 

17 be expected. A similar pattern of risk reduction is seen for the other short-term 

18 exposure mortality categories, although overall reductions are somewhat lower for 

19 these categories compared with non-accidental mortality. As noted earlier, in 

20 presenting results for recent conditions, the point estimate for Los Angeles, for 

21 CV mortality, is negative. As discussed earlier (see section 4.1), negative point 

22 estimates reflect the use of non-statistically significant effects estimates, which 

23 can in turn, reflect a number of factors, including insufficient sample size in the 

24 epidemiological study that provided the effects estimate. The pattern of risk 

25 reductions associated with moving from recent conditions to just meeting the 

26 current set of standards is depicted graphically for short-term exposure mortality 

27 in Figures 4-9 through 4-11. 

28  Trends in risk reduction across alternative sets of standards focusing on 

29 lower annual levels (13/35 and 12/35 combinations): reducing ambient PM2.5

30 levels to meet alternative sets of standards with lower annual levels (i.e., 13/35 

31 and 12/35) is estimated to produce a systematic reduction in PM2.5-related non32 accidental mortality in roughly half of the urban study areas. Specifically, for 

33 simulation year 2007, 8 of the 14 study areas have estimated reductions in PM2.5-

34 related non-accidental mortality on the order of 3 to 15% under a 13/35 set of 

35 standards with this reduction increasing to between 5 and 23% under the 12/35 set 

36 of standards (see Appendix E, Table E-81). The degree of estimated reduction in 

37 PM2.5-related short-term exposure mortality across these sets of standards with 

38 reduced annual levels is similar for the other short-term exposure mortality 

39 categories. The degree of reduction in short-term exposure mortality is somewhat 

40 lower than what is estimated for long-term mortality (see section 4.2.1), which is 

41 expected since these two alternative standards focus on lower annual levels and 

42 consequently would impact long-term exposure mortality risk more than short43 term. This pattern of risk reductions associated with moving from just meeting 
September 2009 118 Draft – Do Not Quote or Cite 

1 the current set of standards to just meeting alternative sets of standards (including 

2 lower annual levels) is depicted graphically in Figures 4-9 through 4-11. 

3  Trends in risk reduction across alternative sets of standards focusing on 

4 lower combinations of 24-hour and annual levels (13/30 and 12/25 

5 combinations): Under the 13/30 standards combination, PM2.5-related non6 accidental mortality is reduced by a slightly greater amount than under the 13/35 

7 combination discussed above (with percent reductions relative to just meeting the 

8 current set of standards ranging from 6 to 15% - see Appendix E, Table E-81). 

9 When the most stringent set of standards (12/25) included in this analysis is 

10 modeled, the overall degree of reduction in PM2.5-attributable non-accidental 

11 short-term mortality is increased to between 7 and 29% (and all of the urban study 

12 areas are predicted to experience some degree of risk reduction). We note that 

13 results for the other short-term mortality categories (in terms of risk reductions 

14 associated with these two alternative standard combinations) are similar to those 

15 presented above for all non-accidental mortality. This pattern of risk reductions 

16 associated with moving from just meeting the current set of standards to just 

17 meeting alternative sets of standards (including lower 24-hour and annual levels) 

18 is depicted graphically in Figures 4-9 through 4-11. 

19  Pattern of reductions of PM2.5-associated short-term exposure mortality 

20 incidence across urban study areas under alternative sets of standards: 

21 Differences in the degree of reduction of PM2.5-related short-term exposure 

22 mortality risk across the 14 urban study areas relative to just meeting the current 

23 set of standards are moderate for the alternative sets of standards reflecting lower 

24 annual standards (i.e., 13/35 and 12/35), with risk reductions ranging from 3 to 

25 15% (for 13/35) and 5 to 23% (for 12/35) (Appendix E, Table E-81). Differences 

26 in risk reduction across urban study areas are notably small, for the alternative 

27 sets of standards reflecting lower 24-hour standards (i.e., 13/30 and 12/25) 

28 (Appendix E, Table E-81). Specifically, for these two alternative standard levels, 

29 12 of the 14 urban study area locations have estimated percent reductions that 

30 vary from each other by only 1% (or are the same). In the case of all four sets of 

31 alternative standard levels, the range of risk reductions across urban study areas is 

32 notably lower for short-term mortality than it is for long-term morality (see 

33 section 4.3.1). We believe this reflects, in part, the fact that short-term exposure 

34 mortality is modeled down to PRB, which represents a larger span in absolute 

35 ambient air levels relative to the annual standard which is modeled to a relatively 

36 higher ambient concentration (i.e., the LML). Modeling risk down to PRB for 

37 short-term exposure health impacts has a dampening effect on estimates of the 

38 percent risk reduction associated with reductions in ambient air levels, since these 

39 changes represent a relatively smaller fraction of the total range in ambient air 

40 levels being considered. Conversely, for long-term exposure mortality, which is 

41 modeled down to LML, incremental reductions in ambient air levels and the 

42 associated risk reductions represent a larger relative change, since the overall 

43 spread being modeled is less (i.e., only down to LML and not PRB). 

44  Pattern of percent reduction of total incidence across the three simulated 

45 years (2005-2007): Reductions in PM2.5-associated long-term mortality under 
September 2009 119 Draft – Do Not Quote or Cite 

1 alternative sets of standards across the simulation years (2005-2007) are also 

2 relatively uniform (e.g., for non-accidental mortality, see Appendix F, Tables E3 79 through E-81). As with the relatively uniform pattern across urban study 

4 areas, we believe this consistency across the simulation years reflects, in part, the 

5 fact that short-term exposure endpoints are modeled down to PRB, which can 

6 have a dampening effect on the percent reduction risk estimates. 
September 2009 120 Draft – Do Not Quote or Cite 

1 

2 Figure 4-9. Estimated Percent Reductions From the Current Standards to 

3 Alternative Sets of Standards in Non-Accidental Mortality Associated 

4 with Short-Term Exposure to PM2.5: Based on 2007 

5 Air Quality Data.* 

-90%

-80%

-70%

-60%

-50%

-40%

-30%

-20%

-10%

0%

10%

20%

30%

2007 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Reduction from Current Standard

 Atlanta, GA 177 (34 - 319); 1.2% (0.2% - 2.1%)

 Baltimore, MD 225 (91 - 357); 1.7% (0.7% - 2.6%)

 Birmingham, AL 37 (-58 - 131); 0.4% (-0.6% - 1.4%)

 Dallas, TX 137 (33 - 240); 1.1% (0.3% - 1.9%)

 Detroit, MI 112 (-20 - 242); 0.7% (-0.1% - 1.4%)

 Fresno, CA 51 (7 - 94); 0.9% (0.1% - 1.7%)

 Houston, TX 240 (49 - 429); 1.3% (0.3% - 2.3%)

 Los Angeles, CA 79 (-113 - 270); 0.1% (-0.2% - 0.5%)

 New York, NY 659 (387 - 930); 1.3% (0.7% - 1.8%)

 Philadelphia, PA 206 (76 - 334); 1.5% (0.5% - 2.4%)

 Phoenix, AZ 242 (40 - 441); 1% (0.2% - 1.9%)

 Pittsburgh, PA 123 (36 - 209); 0.9% (0.3% - 1.6%)

 Salt Lake City, UT 36 (7 - 65); 0.7% (0.2% - 1.3%)

 St. Louis, MO 222 (64 - 378); 1.2% (0.4% - 2.1%)

 Tacoma, WA 42 (7 - 76); 0.8% (0.1% - 1.5%)

6 

7 *Based on Zanobetti and Schwartz (2009). The legend contains, for each urban area, the incidence estimate 

8 (and 95% CI) and the estimate of percent of total incidence (and 95% CI) under the current standards. 

** The current standards consist of an annual standard of 15 μg/m3 and a 24-hour standard of 35 μg/m3 9 . 

10 Combinations of an annual standard (n) and a 24-hour standard (m) are denoted n/m in this figure. 
September 2009 121 Draft – Do Not Quote or Cite 

1 

2 Figure 4-10. Estimated Percent Reductions From the Current Standards to 

3 Alternative Sets of Standards in Cardiovascular Mortality Associated 

4 with Short-Term Exposure to PM2.5: Based on 2007 

5 Air Quality Data.* 

-90%

-80%

-70%

-60%

-50%

-40%

-30%

-20%

-10%

0%

10%

20%

30%

2007 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Reduction from Current Standard

 Atlanta, GA 32 (-33 - 95); 0.8% (-0.8% - 2.4%)

 Baltimore, MD 61 (-4 - 125); 1.6% (-0.1% - 3.2%)

 Birmingham, AL -1 (-46 - 44); 0% (-1.7% - 1.6%)

 Dallas, TX 29 (-19 - 75); 0.8% (-0.5% - 2.1%)

 Detroit, MI 55 (-7 - 117); 0.9% (-0.1% - 2%)

 Fresno, CA 13 (-9 - 35); 0.8% (-0.5% - 2.1%)

 Houston, TX 52 (-36 - 139); 1% (-0.7% - 2.7%)

 Los Angeles, CA -30 (-136 - 74); -0.2% (-0.7% - 0.4%)

 New York, NY 425 (248 - 600); 1.9% (1.1% - 2.7%)

 Philadelphia, PA 83 (22 - 143); 2.1% (0.5% - 3.6%)

 Phoenix, AZ 84 (-4 - 170); 1.3% (-0.1% - 2.7%)

 Pittsburgh, PA 37 (-7 - 80); 0.9% (-0.2% - 2%)

 Salt Lake City, UT 10 (-2 - 21); 0.8% (-0.2% - 1.8%)

 St. Louis, MO 104 (23 - 184); 1.8% (0.4% - 3.2%)

 Tacoma, WA 11 (-6 - 27); 0.7% (-0.4% - 1.8%)

`

6 

7 * Based on Zanobetti and Schwartz (2009). The legend contains, for each urban area, the incidence 

8 estimate (and 95% CI) and the estimate of percent of total incidence (and 95% CI) under the current 

9 standards. 

** The current standards consist of an annual standard of 15 μg/m3 and a 24-hour standard of 35 μg/m3 10 . 

11 Combinations of an annual standard (n) and a 24-hour standard (m) are denoted n/m in this figure. 
September 2009 122 Draft – Do Not Quote or Cite 

1 

2 Figure 4-11. Estimated Percent Reductions From the Current Standards to 

3 Alternative Sets of Standards in Respiratory Mortality Associated 

4 with Short-Term Exposure to PM2.5: Based on 2007 

5 Air Quality Data.* 

-80%

-70%

-60%

-50%

-40%

-30%

-20%

-10%

0%

10%

20%

30%

2007 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Reduction from Current Standard

 Atlanta, GA 20 (-8 - 47); (-0.6% - 3.6%) 2.6%

 Baltimore, MD 31 (6 - 56); (0.5% - 4.6%) 1.1%

 Birmingham, AL 10 (-8 - 28); (-0.9% - 3.1%) 0.9%

 Dallas, TX 10 (-9 - 29); (-0.8% - 2.5%) 1.6%

 Detroit, MI 22 (1 - 42); (0.1% - 3.2%) 1.6%

 Fresno, CA 10 (0 - 19); (0.1% - 3.2%) 2.6%

 Houston, TX 38 (6 - 68); (0.4% - 4.7%) 1%

 Los Angeles, CA 56 (5 - 105); (0.1% - 1.9%) 2.1%

 New York, NY 90 (32 - 147); (0.7% - 3.4%) 1.8%

 Philadelphia, PA 22 (-2 - 45); (-0.2% - 3.8%) 1.8%

 Phoenix, AZ 47 (4 - 90); (0.1% - 3.5%) 1.3%

 Pittsburgh, PA 16 (-2 - 32); (-0.1% - 2.7%) 1.4%

 Salt Lake City, UT 6 (1 - 12); (0.2% - 2.5%) 1.5%

 St. Louis, MO 27 (-7 - 59); (-0.4% - 3.4%) 1.3%

 Tacoma, WA 6 (0 - 13); (0% - 2.5%) 

6 

7 * Based on Zanobetti and Schwartz (2009). The legend contains, for each urban area, the incidence 

8 estimate (and 95% CI) and the estimate of percent of total incidence (and 95% CI) under the current 

9 standards. 

** The current standards consist of an annual standard of 15 μg/m3 and a 24-hour standard of 35 μg/m3 10 . 

11 Combinations of an annual standard (n) and a 24-hour standard (m) are denoted n/m in this figure. 
September 2009 123 Draft – Do Not Quote or Cite 

1 

2 4.2.3 Short-term exposure morbidity 

3 This section summarizes core estimates for short-term exposure morbidity (HA 

4 for CVD and respiratory causes; ED visits for CV, respiratory and asthma) generated for 

5 the current and alternative sets of standards for simulation year 2007. 

6  Comparison of recent conditions risk with risk associated with current 

7 standards: A shift in ambient air PM2.5 levels from recent conditions to just 

8 meeting the current set of standards results in notable estimated reductions in the 

9 percent of total incidence (for short-term CV HAs) attributable to PM2.5 across 

10 most of the urban case studies. For example, Fresno and Salt Lake City have 

11 estimated reductions in the range of up to 40 to 50% in the percent of total 

12 incidence attributable to PM2.5 under the current standards for simulation year 

13 2007 – see Appendix E, Table E-105). However, as expected, a subset of urban 

14 case studies with recent ambient air PM2.5 levels near or below the current 

15 standards (e.g., Dallas, Phoenix – see Appendix E, Table E-105) do not show any 

16 estimated reductions in short-term mortality-related risk. A similar pattern of 

17 risk reduction (in comparing just meeting the current set of standards to recent 

18 conditions) is seen for respiratory-related HAs, although overall reductions are 

19 somewhat lower for these categories compared with CV HAs for most urban 

20 study areas. The pattern of risk reductions associated with moving from recent 

21 conditions to just meeting the current set of standards is depicted graphically for 

22 short-term exposure morbidity in Figures 4-12 and 4-13. Since these figures 

23 show the change in risk for each of the short-term exposure morbidity categories 

24 expressed in terms of the percent change relative to just meeting the current set of 

25 standards, the change from recent conditions relative to just meeting the current 

26 set of standards is often negative, reflecting higher risks under recent conditions. 

27  Trends in risk reduction across alternative sets of standards focusing on 

28 lower annual levels (13/35 and 12/35 combinations): reducing ambient PM2.5

29 levels to simulate just meeting alternative suites of standards with lower annual 

30 levels (i.e., 13/35 and 12/35) produces a systematic reduction in estimated PM2.5-

31 related CV HAs for roughly half of the urban study areas. Specifically, in 

32 simulation year 2007, 8 of the 14 study areas are estimated to have reductions in 

33 PM2.5-related CV HAs on the order of 3% to 15% under a 13/35 suite of standards 

34 with this reduction increasing to between 5 and 23% under the 12/35 set of 

35 standards (see Appendix E, Table E-107). The degree of reduction in PM2.5-

36 related mortality across these sets of standards with reduced annual levels is 

37 similar for respiratory-related HAs. This pattern of risk reductions associated 

38 with moving from the current set of standards to alternative sets of standards 

39 (including lower annual levels) is depicted graphically in Figures 4-12 and 4-13. 

40  Trends in risk reduction across alternative sets of standards focusing on 

41 lower 24-hour and annual levels (13/30 and 12/25 combinations): Under the 

42 13/30 set of standards, PM2.5-related CV HAs are reduced by a slightly greater 

43 amount than under the 13/35 set discussed above (with percent reductions ranging 
September 2009 124 Draft – Do Not Quote or Cite 

1 from 6 to 15% - see Appendix E, Table E-107). When the most stringent set of 

2 standards (12/25) included in this analysis is modeled, the overall degree of 

3 reduction in PM2.5-attributable estimated CV HAs increases to between 7 and 

4 30% (and all of the urban study areas are predicted to experience some degree of 

5 risk reduction). We note, that results for respiratory HAs (in terms of estimated 

6 risk reductions associated with these two alternative standard combinations) are 

7 similar to those presented above for non-accidental mortality. This pattern of risk 

8 reductions associated with moving from just meeting the current set of standards 

9 to just meeting alternative sets of standards (including lower annual and 24-hour 

10 levels) is depicted graphically in Figures 4-12 and 4-13. 

11  Pattern of the reduction of PM2.5-associated short-term exposure morbidity 

12 incidence across urban study areas under alternative sets of standards: As 

13 with short-term exposure mortality, differences in the degree of reduction of 

14 PM2.5-related short-term morbidity risk across the 14 urban study areas are 

15 moderate for those sets of alternative standards focusing on lower annual levels 

16 (13/35 and 12/35) and notably smaller for those alternative sets of standards with 

17 lower annual and 24-hour levels (13/30 and 12/25) (see Appendix E, Table E18 107). We believe the same factors discussed above for short-term exposure 

19 mortality are responsible for this trend in estimated incidence for short-term 

20 exposure morbidity (see section 4.2.2). 

21  Pattern of percent reduction of total incidence across the three simulated 

22 years (2005-2007): Reductions in PM2.5-associated short-term exposure 

23 morbidity under alternative sets of standards across the simulation years (2005-

24 2007) are also relatively uniform (see Appendix E, Tables E-106 through E-108). 

25 As with the relatively uniform pattern across urban study areas, we believe this 

26 consistency across the simulation years reflects the combination of using a 

27 proportional reduction approach to simulate alternative 24-hour standard levels, 

28 combined with modeling of short-term exposure morbidity. 
September 2009 125 Draft – Do Not Quote or Cite 

1 

2 Figure 4-12. Estimated Percent Reductions From the Current Standards to 

3 Alternative Sets of Standards in Cardiovascular Hospital Admissions 

4 Associated with Short-Term Exposure to PM2.5: Based on 

5 2007 Air Quality Data.* 

-90%

-80%

-70%

-60%

-50%

-40%

-30%

-20%

-10%

0%

10%

20%

30%

2007 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Reduction from Current Standard

 Atlanta, GA 41 (-27 - 108); 0.36% (-0.24% - 0.96%)

 Baltimore, MD 215 (158 - 271); 1.32% (0.97% - 1.67%)

 Birmingham, AL 17 (-11 - 46); 0.35% (-0.23% - 0.92%)

 Dallas, TX 27 (-18 - 72); 0.28% (-0.18% - 0.73%)

 Detroit, MI 215 (158 - 272); 1.04% (0.77% - 1.32%)

 Fresno, CA 24 (0 - 48); 0.5% (0.01% - 0.99%)

 Houston, TX 64 (-42 - 169); 0.36% (-0.23% - 0.94%)

 Los Angeles, CA 265 (3 - 526); 0.47% (0.01% - 0.93%)

 New York, NY 676 (496 - 855); 1.04% (0.76% - 1.31%)

 Philadelphia, PA 201 (148 - 254); 1.25% (0.92% - 1.58%)

 Phoenix, AZ 108 (1 - 215); 0.5% (0.01% - 0.99%)

 Pittsburgh, PA 120 (88 - 152); 0.96% (0.7% - 1.21%)

 Salt Lake City, UT 10 (0 - 20); 0.38% (0% - 0.75%)

 St. Louis, MO 176 (129 - 222); 1.25% (0.92% - 1.58%)

 Tacoma, WA 19 (-46 - 82); 0.52% (-1.28% - 2.26%)

6 

7 * Based on Bell et al. (2008). The legend contains, for each urban area, the incidence estimate (and 95% 

8 CI) and the estimate of percent of total incidence (and 95% CI) under the current standards. 

** The current standards consist of an annual standard of 15 μg/m3 and a 24-hour standard of 35 μg/m3 9 . 

10 Combinations of an annual standard (n) and a 24-hour standard (m) are denoted n/m in this figure. 
September 2009 126 Draft – Do Not Quote or Cite 

1 

2 Figure 4-13. Estimated Percent Reductions From the Current Standards to 

3 Alternative Sets of Standards in Respiratory Hospital Admissions 

4 Associated with Short-Term Exposure to PM2.5: Based 

5 on 2007 Air Quality Data.* 

-90%

-80%

-70%

-60%

-50%

-40%

-30%

-20%

-10%

0%

10%

20%

30%

2007 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Reduction from Current Standard

 Atlanta, GA 17 (-22 - 56); 0.44% (-0.55% - 1.42%)

 Baltimore, MD 17 (-10 - 44); 0.35% (-0.2% - 0.89%)

 Birmingham, AL 7 (-9 - 24); 0.42% (-0.53% - 1.36%)

 Dallas, TX 13 (-16 - 42); 0.33% (-0.42% - 1.08%)

 Detroit, MI 19 (-11 - 49); 0.27% (-0.16% - 0.7%)

 Fresno, CA 16 (4 - 29); 0.89% (0.21% - 1.55%)

 Houston, TX 29 (-36 - 93); 0.43% (-0.54% - 1.39%)

 Los Angeles, CA 171 (40 - 301); 0.83% (0.19% - 1.47%)

 New York, NY 56 (-33 - 144); 0.27% (-0.16% - 0.7%)

 Philadelphia, PA 16 (-9 - 42); 0.33% (-0.19% - 0.84%)

 Phoenix, AZ 61 (14 - 108); 0.88% (0.21% - 1.55%)

 Pittsburgh, PA 10 (-6 - 25); 0.25% (-0.15% - 0.64%)

 Salt Lake City, UT 7 (2 - 13); 0.67% (0.16% - 1.18%)

 St. Louis, MO 21 (-12 - 54); 0.33% (-0.19% - 0.85%)

 Tacoma, WA 2 (-24 - 27); 0.14% (-1.87% - 2.05%)

6 

7 * Based on Bell et al. (2008). The legend contains, for each urban area, the incidence estimate (and 95% 

8 CI) and the estimate of percent of total incidence (and 95% CI) under the current standards. 

** The current standards consist of an annual standard of 15 μg/m3 and a 24-hour standard of 35 μg/m3 9 . 

10 Combinations of an annual standard (n) and a 24-hour standard (m) are denoted n/m in this figure. 

11 figure. 
September 2009 127 Draft – Do Not Quote or Cite 

1 4.3 SENSITIVITY ANALYSIS RESULTS 

2 As noted in section 3.6.4 and section 4.1 the sensitivity analysis was conducted in 

3 order to gain insights into which of the identified sources of uncertainty in the risk 

4 assessment model may have significant impacts on risk estimates. A second goal of the 

5 sensitivity analysis was to generate an additional set of reasonable risk estimates to 

6 supplement the core set of risk estimates and which can be used to inform staff's 

7 characterization of uncertainty associated with those core estimates. 

8 The first goal can be achieved by considering the magnitude of the impact of 

9 individual modeling elements based on results from the sensitivity analysis and 

10 identifying those elements which have the greatest impact on the core risk estimates. 

11 Regarding the second goal, given the design of the sensitivity analysis, staff judges that 

12 the results of this analysis represent a reasonable set of alternate risk estimates, that fall 

13 within an overall set of plausible risk estimates surrounding the core estimates. While 

14 not representing a formal uncertainty distribution, the output of the sensitivity analysis, 

15 when combined with the core risk estimates, represent a set of plausible risk estimates, 

16 which reflect consideration for uncertainty in various elements of the risk assessment 

17 model. Therefore, later in section 4.5, when discussing risk estimates for a particular 

18 scenario, we focus on the core estimates as representing higher-confidence estimates and 

19 then use the output of the sensitivity analysis to provide some perspective on the potential 

20 range of uncertainty about the risk estimates given consideration of key sources of 

21 uncertainty. While we do not know what confidence interval is captured by this range of 

22 estimates, or what specific percentiles of the risk distribution are represented by points 

23 within that range, the output of the sensitivity analysis does provide a set of plausible risk 

24 estimates and, therefore provides some perspective on the magnitude of potential 

25 uncertainty associated with the core estimates. 

26 In conducting the sensitivity analysis we modeled 2 of the 15 urban study areas 

27 (Philadelphia and Los Angeles - representing east and west coast urban areas, 

28 respectively) for most simulations. We note, however, that for some modeling elements 

29 (e.g., the hybrid rollback approach), we included a larger number of the urban study areas 

that were applicable to the topic being assessed.41 30 In conducting the sensitivity analysis, 

31 we have also focused on long-term exposure mortality and short-term exposure mortality 

32 and have included short-term morbidity to a lesser extent because we expect similar 

 41 As noted earlier in section 2.4.1, an error was identified in the approach used to simulate ambient PM2.5 

levels just for the Pittsburgh study area for the scenarios involving just meeting the current and alternative 

sets of standards. Therefore, while Pittsburgh had initially been included in this sensitivity analysis, these 

results have been removed since they are based on the set of current standard levels. 
September 2009 128 Draft – Do Not Quote or Cite 

1 patterns with that observed for short-term exposure mortality based on our review of the 

2 core estimates. 

3 The results of the sensitivity analysis are summarized in Table 4-1 (detailed 

4 results tables are presented in Appendix F). In presenting the results of the sensitivity 

5 analysis, we have compared the risk estimates for the particular simulation to the core set 

6 of risk estimates generated for the same health effect endpoint/urban study area 

7 combination. Specifically, we have calculated a percent difference between the 

8 sensitivity analysis result and the associated core risk estimate to foster comparisons of 

9 the results of the sensitivity analysis across the different modeling elements that were 

10 considered. These percent difference results are emphasized in Table 4-1 and in the 

11 discussion presented below. 

12 In discussing the results of the sensitivity analysis, we have developed four 

13 descriptive categories, based on the general magnitude of the percent difference estimate 

14 generated for a particular modeling element: 

15  Small contributors to uncertainty in the core risk estimates: Modeling 

16 elements estimated to have percent differences of 20% or smaller (i.e., they 

17 produced risk estimates that differed from the core risk estimates by no more 

18 than 20%) are classified as having a small contribution to uncertainty in the 

19 core risk estimates. 

20  Moderate contributors to uncertainty in the core risk estimates: Modeling 

21 elements estimated to have percent difference estimates in the range of 20 to 

22 50% are classified as having a moderate contribution to uncertainty in the core 

23 risk estimates. 

24  Moderate-Large contributors to uncertainty in the core risk estimates: 

25 Modeling elements estimated to have percent difference estimates in the range 

26 of 50 to 100% are classified as having a moderate-large contribution to 

27 uncertainty in the core risk estimates. 

28  Large contributors to uncertainty in the core risk estimates: Modeling 

29 elements estimated to have percent difference results >100% are classified as 

30 having a large contribution to uncertainty in the core risk estimates. 

31 These categories are used in discussing the results of the sensitivity analysis, 

32 particularly in section 4.5. 

33 In discussing the results of the sensitivity analysis, results of the single-factor 

34 simulations are presented first, followed by the results of the multi-factor simulations 

35 (within these categories, results are organized by health effect endpoint with results for 

36 long-term exposure mortality discussed first and then short-term exposure mortality, 

37 followed by short-term exposure morbidity). 
September 2009 129 Draft – Do Not Quote or Cite 

1 The sensitivity analysis based on Moolgavkar’s (2003) study in Los Angeles 

2 addressing model specifications for both short-term mortality and morbidity (e.g., model 

3 selection, lag structure and co-pollutant models) are discussed together as a group, rather 

4 than being divided up and discussed with other sensitivity analyses. This reflects the fact 

5 that the Moolgavkar-based simulations were all based on the same underlying dataset and 

6 focused on Los Angeles. In addition, the discussion of the Moolgavkar-based sensitivity 

7 analysis results presented below (and the summary of results presented in Table 4-1) 

8 focus on the difference in spread of risk results across the Moolgavkar-based model 

9 specifications (for a particular endpoint), rather than the percent difference results (based 

10 on comparison against the core result) that are emphasized with the other sensitivity 

analyses.42 11 

12 Although the sensitivity analysis was completed for all three simulation years, we 

13 have focused on results for 2007 in this presentation to foster comparability with the core 

14 results discussed in sections 4.1 and 4.2. 

15 The discussion provided below for each of the simulations conducted as part of 

16 the sensitivity analysis, first gives a brief overview of the purpose of the simulation (i.e., 

17 what aspect of the risk assessment model is being evaluated). Next the results of the 

18 simulation are discussed in the context of the first goal described above (i.e., the relative 

19 impact of a given source of uncertainty on the core risk estimates). An overall conclusion 

20 regarding which of the factors included in the sensitivity analysis represent potentially 

21 significant sources of uncertainty impacting the core risk estimates is presented at the end 

22 of each sub-section. Use of the alternative risk estimates generated through the 

23 sensitivity analysis in informing characterization of uncertainty associated with the core 

24 risk estimates is discussed in section 4.5. 

 42 Comparison of the Moolgavkar-based risk estimates against the core risk estimates consistently produce 

percent difference estimates that range to levels well above +100%, resulting in a blanket conclusion, based 

on this metric, that all of the factors considered in the Moolgavkar-based sensitivity analysis are large 

contributors to uncertainty in the core risk estimates. However, there is significant uncertainty in assuming 

that the behavior of the Moolgavkar-based risk models (reflecting consideration for alternate design 

elements) would be representative of how models derived from either of the key short-term studies 

considered in this risk assessment (Zanobetti and Schwartz., 2009 and Bell et al., 2008) would respond to 

variations in design. Therefore, while sensitivity analysis results based on comparing Moolgavkar-based 

risk estimates against the core risk estimates are included in the detailed sensitivity analysis results tables 

presented in Appendix F (see Tables F-31 through F-33), we do not discuss these results here due to the 

degree of uncertainty associated with them. 
September 2009 130 Draft – Do Not Quote or Cite 

1 

2 Table 4-1. Overview of Sensitivity Analysis Results. 

Sensitivity Analysis1

Health Endpoint and 

Risk Assessment 

Location 

Summary of Results 

(percent difference in risk 

estimate relative to the core 

estimate)

Appendix F 

Tables with 

Detailed 

Results (for 

2007) 

Single-Factor Sensitivity Analyses (long-term exposure mortality): 

Impact of using different 

model choices: 

fixed effects log-linear (the 

core) vs. random effects 

log-linear C-R function 

 All-cause, CPD, 

IHD 

 Los Angeles and 

Philadelphia 

Random effects log-linear C-R 

model: 

 all-cause: +23% 

 IHD: +12% 

Table F-3 

Impact of using different 

model choices: 

fixed effects log-linear (the 

core) vs. random effects loglog C-R function 

 All-cause, CPD, 

IHD 

 Los Angeles and 

Philadelphia 

Random effects log-log C-R 

model: 

 All-cause: +122 to 155% 

 CPD: +49 to 71% 

 IHD: +79 to 107% 

 Lung Cancer: +68 to 92% 

Table F-3 

Impact of estimating risks 

down to PRB rather than 

down to LML (the core) 

 All cause 

 All 15 urban 

study areas 

 All-cause: +47 to +197% Table F-6 

Impact of using alternative 

C-R function from another 

long-term exposure mortality 

study 

 All-cause, CPD, 

lung cancer 

 Los Angeles, 

Philadelphia 

 All-cause: -25% 

 CPD: -55 to -56% 

 Lung cancer: -192 to - 195% 

Table F-9 

Impact of using alternative 

hybrid rollback approach 

reflecting potential for 

greater use of localized 

controls in some study 

areas(evaluated across 

current and alternative 

standard levels) 

 All-cause 

mortality 

 Baltimore, 

Birmingham, 

Detroit, Los 

Angeles, New 

York and St. 

Louis 

 4 urban locations had 

impacts of <20% across all 

alternative standard levels 

(with most of these in the 

<10% range). 

 1 urban locations had 

impacts of up to +54% 

Table F-12 

Single-Factor Sensitivity Analyses (short--term exposure mortality):

Impact of using seasonspecific C-R functions (vs. 

an annual C-R function) 

 Non-accidental 

mortality, CV, 

respiratory 

 All 15 urban 

study areas 

 Non-accidental: -114 to 

+186% 

 CV: -92 to +600% 

 Respiratory: -47 to +162% 

(Note, overall incidence 

estimates, particularly for the 

locations with higher percent 

change estimates, is very low, 

raising concerns over the stability 

of these sensitivity analysis 

results) 

Table F-15 

Table F-18 

Table F-21 

Impact of using alternative 

hybrid rollback approach 

 Non-accidental 

mortality 

 Results for all seven urban 

study areas (across the 

Table F-36 
September 2009 131 Draft – Do Not Quote or Cite 

Sensitivity Analysis1

Health Endpoint and 

Risk Assessment 

Location 

Summary of Results 

(percent difference in risk 

estimate relative to the core 

estimate)

Appendix F 

Tables with 

Detailed 

Results (for 

2007) 

reflecting potential for 

greater use of localized 

controls in some study areas 

 Baltimore, 

Birmingham, 

Detroit, Los 

Angeles, New 

York and St. 

Louis 

current and alternative 

standard levels) do not 

exceed +20%, with most 

<+10%. 

Single-Factor Sensitivity Analyses (short-term morbidity: hospital admissions (HA) and ED visits):

Impact of using seasonspecific C-R functions (vs. 

an annual C-R function) 

 HA 

(unscheduled), 

CV and 

respiratory 

 All 15 urban 

study areas 

 HA (CV): -105 to +10% 

 HA (respiratory): -54 to 

+71% 

(Note, overall incidence 

estimates, particularly for the 

locations with higher percent 

change estimates, is very low, 

raising concerns over the stability 

of these sensitivity analysis 

results) 

Table F-24 

Table F-27 

Impact of using an annual CR function (applied to the 

whole year) vs. a seasonal 

function for April through 

August (applied only to that 

period) (using a single 

pollutant model) 

 Asthma ED visits 

 New York 

NA (although incidence 

estimates were generated for this 

simulation, “percent difference 

from the core” were not 

generated since the alternate 

simulation focused on a subset of 

the year). 

Table F-30 

Single-Factor Sensitivity Analysis (short-term exposure mortality and morbidity in LA based on 

Moolgavkar, 2003 study model options) (Note, results presented here reflect spread in risk estimates 

across Moolgavkar-based model specifications and not percent difference from core risk estimates, 

unless so stated – see text) 

Impact of model selection 

(e.g., log-linear GAM with 

30 df; log-linear GAM with 

100 df; and log-linear GLM 

with 100 df) 

 Mortality (nonaccidental, CV); 

HA (CV) 

 Los Angeles 

 Non-accidental mortality: 

+79% 

 CV mortality: +49 

 CV HA: +36% 

Table F-33 

Impact of lag structure (0-

day, 1-day, 2-day, 3-day, 4-

day, 5-day) 

 Mortality (nonaccidental) 

 Los Angeles 

 Non-accidental mortality: 

+55% 

Table F-33 

Impact of single- vs. multipollutant models (PM2.5 with 

CO) 

 Mortality (CV); 

HA (CV) 

 Los Angeles 

 CV mortality: +105% 

 CV HA: +142% 

Table F-33 

Multi-Factor Sensitivity Analyses (long-term mortality): 

Impact of using a fixed 

effects log-linear vs. a 

random effects log-log 

model, estimating incidence 

down to the lowest measured 

level (LML) in the study vs. 

down to PRB, and using a 

proportional vs. hybrid 

 All-cause, IHD 

long-term 

mortality 

 Los Angeles and 

Philadelphia 

 All-cause: +26 to +1,020% 

 IHD: +25 to +627% 

F-39 
September 2009 132 Draft – Do Not Quote or Cite 

Sensitivity Analysis1

Health Endpoint and 

Risk Assessment 

Location 

Summary of Results 

(percent difference in risk 

estimate relative to the core 

estimate)

Appendix F 

Tables with 

Detailed 

Results (for 

2007) 

rollback to estimate 

incidence associated with 

long-term exposure to PM2.5

concentrations that just meet 

the current standards 

Multi-Factor Sensitivity Analyses (short--term mortality):

Impact of using seasonspecific vs. all-year C-R 

functions and proportional 

vs. hybrid rollbacks to 

estimate incidence 

associated with short-term 

exposure to PM2.5

concentrations that just meet 

the current standards 

 Non-accidental 

 Baltimore, 

Birmingham, 

Detroit, Los 

Angeles, New 

York and St. 

Louis 

 Non-accidental (four seasons 

+ hybrid): -109 to +119% 

F-42 

1 1 Unless otherwise noted, sensitivity analysis results are based on the scenario reflecting just meeting the 

2 current set of PM2.5 standards. l 2 3 Note: this metric is the percent spread in risk estimates across the Moolgavkar-based model specifications 

4 (not the percent difference estimates – see text discussion above). 

5 4.3.1 Single-factor sensitivity analysis results 

6 This section presents the results of the single-factor sensitivity analysis, which 

7 involved consideration of alternate model inputs on the core risk estimates, when those 

8 alternate inputs are considered one at a time (consideration for the combined effect of 

9 several model inputs being varied is covered by the multi-factor sensitivity analysis 

10 discussed in section 4.3.2). Note, that the results of the single-factor sensitivity analysis 

11 are characterized qualitatively using the four-category approach described above (i.e., 

12 low, moderate, moderate-large and large, with each of these representing a defined range 

13 of percent difference from the core risk estimates, as detailed above). 

14 4.3.1.1 Sensitivity analysis results associated with long-term 

15 exposure mortality 

16 This section summarizes the results of the sensitivity analysis focused on long17 term exposure-related mortality endpoints (see Table 5-1 for the specific modeling 

18 elements considered in the sensitivity analysis). The results of individual sensitivity 

19 analysis simulations are presented below, with overall observations presented at the end 

20 of the section. 

21  Impact of using different model choices for C-R function - fixed effects log22 linear (the core approach) vs. random effects log-linear or random effects 

23 log-log models: This simulation considered two alternative C-R model forms 

24 obtained from Krewski et al., 2009 for modeling all-cause, CPD, IHD and lung 
September 2009 133 Draft – Do Not Quote or Cite 

1 cancer mortality, including (a) random effects log-linear model and (b) a random 

2 effects log-log model (note, the core effect estimate was derived using a fixed 

3 effects log-linear model obtained from Krewswki et al., 2009). The results of the 

4 simulation suggest that the use of a random effects log-linear model, rather than 

5 the core fixed effects model has a relatively small effect on risk, raising it by 12 to 

6 23% across the mortality categories and urban study areas modeled (Appendix F, 

7 Table F-3). However, use of a random effects log-log model has a larger impact 

8 on risk estimates, raising them by 49 to 155% (Appendix F, Table F-3). The 

9 greater impact of the log-log model results from this function having an 

10 incrementally steeper slope at lower PM levels, which quickly increases incidence 

11 estimates compared with the core log-linear model (whose slope has a much more 

12 gradual incremental increase in slope at lower PM levels). 

13  Impact of estimating risks down to PRB rather than down to LML: This 

14 simulation compared long-term exposure mortality incidence associated with 

15 modeling risk down to PRB (which varies by region – see section 3.2.1) with the 

core approach of modeling down to LML (5.8 μg/m3 16 for long-term mortality – see 

17 section 3.1). This simulation involved all 15 urban study areas, given that PRB is 

18 stratified by region and therefore, results of the simulation could differ 

19 significantly across the 15 urban study areas (or at least across the six PM regions 

20 represented by those study areas). The results of this simulation suggest that 

21 modeling risk down to PRB could have a moderate to large impact on long-term 

22 exposure mortality incidence, with estimates ranging from 47 to 197% higher than 

23 the core estimates (for matching urban locations) (Appendix F, Table F-6). Note, 

24 however, that risk metrics based on considering the incremental reduction in risk 

25 between two standard levels would not be impacted by this source of uncertainty, 

26 since it only effects estimates of absolute risk (for a particular standard level). 

27  Impact of C-R function from alternative long-term exposure mortality study: 

28 This simulation considered use of alternative C-R functions (and effect estimates) 

29 based on the reanalysis of the Six Cities study (Krewski et al., 2000). The results 

30 suggest that use of the alternative C-R function could have a moderate to 

31 moderate-large effect on all cause and CPD mortality (-25% for all-cause and 

32 about -55% for CPD) (Appendix F, Table F-9). The effect of using the alternative 

33 function on risk estimates for lung cancer mortality was much larger (-192 to -

34 195%) (Appendix F, Table F-9). The results of this simulation suggest that (at 

35 least with regard to application of C-R functions obtained from the Six Cities 

36 study), the potential impact of functions from alternative studies on long-term 

37 exposure mortality depends on the mortality category being considered. In this 

38 analysis, use of the alternative C-R functions was shown to have a significant 

39 impact on lung cancer mortality, but a much smaller impact on the other long40 term exposure mortality categories. 

41  Impact of using alternative hybrid rollback approach to simulate just 

42 meeting the current and alternative suite of standards: This simulation 

43 evaluated the potential impact of simulating just meeting the current and 

44 alternative sets of standards using a hybrid rollback approach that employs a 

45 combination of localized controls (resulting in non-proportional rollbacks of 
September 2009 134 Draft – Do Not Quote or Cite 

1 monitored PM2.5 concentrations) with a second phase of proportional adjustments 

2 (see section 3.3.3). We note that the core analysis utilized proportional 

3 adjustment exclusively in simulating conditions for the current and alternative sets 

4 of standards. In discussing these results, we focus on risk estimates generated for 

5 the most stringent alternative set of standards (12/25) since this is the level where 

6 the greatest differences between the core and hybrid rollback approach were seen 

7 (for all relevant urban study areas). The results of this simulation suggest that the 

8 use of the hybrid rollback strategy can have widely varying impacts on long-term 

9 mortality incidence. For five of the seven urban study areas for which this 

10 procedure was evaluated, the results were relatively small (e.g., percent 

11 differences ranged from +2% to +17%) (Appendix F, Table F-12). For the urban 

12 study area demonstrating the greatest impact (Los Angeles), percent differences 

13 were moderate-large (+54%) (Appendix F, Table F-12). The results of this 

14 simulation suggest that for many of the urban study areas, the use of an alternative 

15 rollback strategy employing non-proportional adjustment, did not produce a very 

16 large impact on long-term mortality risk estimates. However, for a subset of the 

17 study areas, the use of this rollback approach was shown to have moderate 

18 impact. 

19 Based on the simulations discussed above covering potential sources of 

20 uncertainty impacting long-term mortality, we conclude that the following factors 

21 contribute potentially large sources of uncertainty to the core risk estimates (i.e., they 

22 produce risk estimates that are at least 100% different from the core risk estimate): (a) 

23 use of alternative form of the C-R function, specifically use of a random-effects log-log 

24 model form obtained from the updated ACS study (Krewski et al., 2009) (b) use of an 

25 alternative C-R function with effects estimates obtained from the reanalysis of the Six 

26 Cities study (Krewski et al. 2000) (specifically in modeling lung-cancer risk), and (c) 

27 estimation of risk down to PRB. We note, that the use of the hybrid (non-proportional 

28 adjustment) approach for simulating conditions for alternative suites of standards was 

29 shown to have a moderate-large impact (+90%) in one of the urban study areas. Other 

30 factors considered in the sensitivity analysis had smaller impacts on core risk estimates. 

31 4.3.1.2 Sensitivity analysis results associated with short-term 

32 exposure mortality 

33 This section summarizes the results of the sensitivity analysis focused on short34 term exposure-related mortality endpoints (see Table 5-1 for the specific modeling 

35 elements considered in the sensitivity analysis). The results of individual sensitivity 

36 analysis simulations are presented below, with overall observations presented at the end 

37 of the section. 

38  Impact of using season-specific C-R functions (vs. an annual C-R function): 

39 This simulation considered the impact on short-term exposure mortality risk of 
September 2009 135 Draft – Do Not Quote or Cite 

1 using seasonally-differentiated effects estimates rather than the core approach of 

2 using a single C-R function for the whole year (note, that the seasonal models 

3 were based on the same study as the model used in the core analysis – Zanobetti 

4 and Schwartz, 2009). The results of the simulation suggest that this source of 

5 uncertainty can have a wide range of effects across urban study areas (including 

6 not only variation in the magnitude of effect, but also in the direction). Percent 

7 changes compared with the core risk estimate were large, ranging from -114% 

8 (Los Angeles) to +186% (Birmingham) (these results are for non-accidental 

9 mortality – see Appendix F, Table F-15). We note that these two locations also 

10 have relatively low overall incidence estimates, which does raise concerns over 

11 the degree of stability in the sensitivity analysis estimates. Furthermore, for 9 of 

12 the 15 urban study areas (for non-accidental morality), percent changes from the 

13 core were small, with absolute values of 12% or less (Appendix F, Tables F-15). 

14 The results for CV and respiratory mortality also demonstrate considerable 

15 variation across locations, but are generally smaller than results cited above for 

16 non-accidental, with one exception. Birmingham is estimated to have short-term 

17 CV mortality that is +600% higher using seasonal effects estimates compared 

18 with the core results (We note, however, that this endpoint category also has very 

19 small incidence, again raising concerns over the stability of the sensitivity 

20 analysis results) (see Table F-18). The results for respiratory-related mortality 

21 also demonstrate considerable variability with results that could suggest a 

22 moderate to large impact (i.e., -47 to +162% - see Appendix F, Table F-21). We 

23 note, however, that small incidence estimates again raise concerns regarding the 

24 stability of these percent difference results. 

25  Impact of using alternative hybrid rollback approach: This simulation 

26 evaluates the potential impact of using the hybrid (non-proportional) approach for 

27 simulating just meeting current and alternative sets of standards to reflect the 

28 potential greater use of more localized controls in some urban study areas (see 

29 section 3.3.3), in place of the proportional approach used in the core analysis. 

30 The results of this simulation (as contrasted with the impact of using the hybrid 

31 approach on long-term exposure mortality) suggest that use of the hybrid rollback 

32 approach has relatively little effect on short-term mortality risk (e.g., percentage 

33 differences relative to the core risk estimates were in the low single digits for 

34 most locations, with one location having a difference of +20% - see Appendix F, 

35 Table F-36). These results suggest that the issue of how alternative standard 

36 levels are simulated appears to introduce relatively little uncertainty into the 

37 modeling of short-term exposure mortality. 

38 The sensitivity analysis results discussed above, result in a number of overall 

39 observations regarding sources of uncertainty potentially impacting short-term exposure 

40 morality endpoints. The results of using the seasonally-differentiated effect estimates in 

41 modeling short-term exposure mortality appear to generally have a relatively small 

42 impact (e.g., <15%) in most study areas. For some study areas, the impact does appear to 

43 be much larger, with results including both substantial negative and positive percent 

44 differences from the core estimates. However, in all of these cases, the total incidence 
September 2009 136 Draft – Do Not Quote or Cite 

1 estimates involved are very small, raising concerns over the stability of the risk estimates 

2 generated as part of this particular sensitivity analysis (in many of these instances, the 

3 estimates include negative lower bounds, reflecting the use of non-statistically significant 

4 effects estimates). For these reasons, the results of this sensitivity analysis, while initially 

5 appearing to be notable in terms of magnitude in some study areas, need to be interpreted 

6 with care. At this point, we are not able to reach a definitive conclusion as to how 

7 important this source of uncertainty is in the context of short-term exposure mortality 

8 estimation (due to the limitations regarding small incidence estimates and the stability of 

9 the relative differences in percent incidence estimates). Regarding the use of the 

10 alternative hybrid (non-proportional) approach for simulating conditions under alternative 

11 standard levels, the results suggest that this factor has a modest impact on short-term 

12 exposure mortality (significantly less impact than with the use of the hybrid approach in 

13 estimating long-term exposure mortality). With the exception of factors examined using 

14 the Moolgavkar et al., (2003) study in Los Angeles (see section 4.3.1.4), it would appear 

15 that the factors examined here do not have a large impact on risk estimates generated for 

16 short-term exposure mortality. 

17 4.3.1.3 Sensitivity analysis results associated with short-term 

18 exposure morbidity 

19 This section summarizes the results of the sensitivity analysis focused on short20 term exposure-related morbidity endpoints (see Table 5-1 for the specific modeling 

21 elements considered in the sensitivity analysis). The results of individual sensitivity 

22 analysis simulations are presented below, with overall observations presented at the end 

23 of the section. 

24  Impact of using season-specific C-R functions (vs. an annual C-R function):

25 This simulation considered the impact on short-term exposure morbidity (HAs) of 

26 using seasonally-differentiated effects estimates rather than the core approach of 

27 using a single C-R function for the whole year (we note that the seasonal models 

28 were obtained from the same study as the model used in the core analysis – Bell et 

29 al, 2008). The results of the simulation suggest that, as with short-term exposure 

30 mortality this source of uncertainty can have a wide range of impacts on the risk 

31 estimates across urban study areas (including not only variation in the magnitude 

32 of risk, but also in the direction) depending on the specific health endpoint 

33 examined. We note, however, that the magnitude of impact appears to be less for 

34 short-term morbidity than for short-term mortality. Percent changes for most of 

35 the 15 urban study areas were small for CV HAs (generally less than a 20% 

36 difference in either direction, although there was a large impact for Tacoma (-

37 105%)) (see Appendix F, Table F-24). This source of uncertainty has a moderate 

38 to moderate-large impact for respiratory-related HAs with most locations having 

39 greater than a 40% to 70% absolute effect (see Appendix F, Table F-27). 
September 2009 137 Draft – Do Not Quote or Cite 

1  Impact of using a seasonal function for April through August (applied only 

2 to that period) in modeling asthma-related ED visits in New York, relative to 

3 the core approach of using a single annual effect estimate (and applying that 

4 to the whole year): This sensitivity analysis compared the core approach of 

5 using a single effect estimate to model asthma-related ED visits in New York 

6 (based on Ito et al., 2007) to the approach of using a season-specific estimate to 

7 model incidence for the period April through August (also obtained from Ito et 

8 al., 2007). Because the simulation periods used with the two approaches do not 

9 match (i.e., a seasonal estimate versus annual estimate), we have not directly 

10 compared the two to generate a percent difference estimate (as is done with the 

11 other sensitivity analysis simulations). While we do not draw a conclusion 

12 regarding the importance of this factor, the results do argue for further research to 

13 more fully characterize the impact of using seasonally-differentiated estimates in 

14 modeling this endpoint). As part of ongoing efforts to refine the sensitivity 

15 analysis, we are considering compare risk estimates (for April-August) generated 

16 using the single (annual) effect estimates, to estimates generated for this same 

17 time period using the seasonally-differentiated effect estimates. 

18 Given the results of the set of simulations completed for short-term exposure 

19 morbidity (both of which focused on the use of seasonally-differentiated effects 

20 estimates), it would appear that this factor does not have a substantial impact on risk 

21 estimates. Additional factors potentially impacting short-term exposure morbidity are 

22 addressed below in relation to the sensitivity analysis based on alternative models from 

23 Moolgavkar et al. (2003). 

24 4.3.1.4 Single-factor sensitivity analysis addressing model 

25 selection, lags, and co-pollutant models 

26 As noted earlier in the introduction to section 4.3, the results of sensitivity 

27 analysis based on Moolgavkar et al., (2003) include percent difference estimates based on 

28 considering the range of risk estimates generated using alternative model specifications 

29 from this study for a given health endpoint and it is these results that are discussed below. 

30 However, sensitivity analysis results reflecting comparison of Moolgavkar-based risk 

31 estimates against the core risk estimates, while included in the detailed results tables in 

32 Appendix F, are not discussed here due to their high degree of uncertainty. 

33  Impact of model selection (e.g., log-linear GAM with 30df, log-linear GAM 

34 with 100df, and log-linear GLM with 100df) on estimating short-term 

35 exposure mortality and morbidity: Application of models obtained from 

36 Moolgavkar et al., (2003) with various formulations related to model selection 

37 (degrees of freedom, GLM vs. GAM) to the Los Angeles urban case study 

38 location results in a range of short-term exposure mortality estimates (for non39 accidental and CV) that differ by 79% and 49%, respectively (see Appendix F, 

40 Table F-33). In the case of short-term exposure morbidity (specifically, CV-
September 2009 138 Draft – Do Not Quote or Cite 

1 related HAs), incidence estimates differ by 36% (see Appendix F, Table F-33). 

2 These results suggest that these elements of model specification represent a 

3 moderate source of uncertainty in estimating short-term mortality and morbidity. 

4  Impact of lag structure (0-day through 5-day) on estimating short-term 

5 exposure mortality: Consideration of the range of risk estimates for non6 accidental mortality generated using different lag structures (and associated effect 

7 estimates) provided in Moolgavkar et al., (2003), suggest that this factor could 

8 have a moderate impact on risk (in the range of 55% when comparing the lowest 

9 and highest positive incidence estimates generated). (see Appendix F, Table F10 33). 

11  Impact of considering multi-pollutant models on estimating short-term 

12 exposure mortality and morbidity: The results of the Moolgavkar-based 

13 simulations (when considering the spread in risk estimates specifically across

14 these simulations) suggest that the multi-pollutant versus single-pollutant model 

15 issue (i.e., including CO in addition to PM2.5), could have a large impact on the 

16 estimation of short-term exposure mortality (105% for all-cause) and morbidity 

17 (142% for CV-related HAs). 

18 Overall observations regarding key sources of uncertainty impacting short-term 

19 exposure mortality and morbidity risk estimates (based on the Moolgavkar et al., 2003 

20 study) include the following. The spread in risk estimates generated across the 

21 Moolgavkar-based model specifications (for a particular endpoint), suggests that C-R 

22 model selection factors may have a moderate to large impact. More specifically, 

23 specification of lag structure has a moderate impact on risk and use of single versus 

24 multi-pollutant models could have a potentially large impact on risk. Note, however, that 

25 as discussed earlier, the relevance of these sensitivity analysis results to the interpretation 

26 of risk estimates generated using C-R functions derived from alternative epidemiology 

27 studies that used different underlying datasets and analytical approaches (i.e., Bell et al., 

28 2008 and Zannobetti and Schwartz et al., 2009) is not clear and may be relatively low. 

29 4.3.2 Multi-Factor Sensitivity Analysis 

30 The results of the multi-factor sensitivity analyses are intended to support both 

31 goals of the sensitivity analysis: (a) identify which factors (now in combination), appear 

32 to have a significant impact on uncertainty in the core estimates and (b) to derive a set of 

33 reasonable alternative risk estimates for use in considering uncertainty associated with 

34 the core risk estimates. Regarding the second goal, given that these sensitivity analysis 

35 results reflect the combined impact of multiple uncertainty factors, they will likely 

36 provide high- and low-bounds on the range of reasonable alternative risk estimates, 

37 thereby providing key information in the consideration of uncertainty associated with the 

38 core risk estimates. Consequently, in providing an overall observations section here, we 
September 2009 139 Draft – Do Not Quote or Cite 

1 emphasize the potential reasonableness of each of the multi-element combinations 

2 included in the sensitivity analysis, since this factor is key to determining the degree to 

3 which these risk estimates can inform consideration of uncertainty related to the core risk 

4 estimates. 

5 Note, that as discussed in section 4.4.3, while we have included sensitivity 

6 analyses involving estimation of risk down to PRB for long-term exposure mortality, 

7 overall uncertainty associated with these estimates is considered higher than other 

8 estimates (due to the need to extrapolate the behavior of the C-R function below the 

9 LML). Consequently, results of the simulations involving estimation of risk down to 

10 PRB will not be included in the set of reasonable alternative risk estimates used in 

11 supporting consideration of uncertainty in the core risk estimates, although these results 

12 are discussed below in the context of understanding key sources of uncertainty associated 

13 with the core risk estimates. 

14 4.3.2.1 Multi-factor sensitivity analyses – long-term exposure 

15 mortality 

16 This section summarizes the results of the sensitivity analysis focused on long17 term exposure-related mortality endpoints (see Table 4-1 for the specific modeling 

18 elements considered in the sensitivity analysis). The results of individual sensitivity 

19 analysis simulations are presented below, with overall observations presented at the end 

20 of the section. 

21  Impact of using log-linear vs. log-log C-R model with fixed or random 

22 effects, estimating incidence down to the LML vs. PRB, and using 

23 proportional vs. hybrid rollback to estimate long-term exposure mortality: 

24 This multi-factor sensitivity analysis focused on a number of model design 

25 choices related to modeling long-term exposure mortality (all-cause and IHD). 

26 Modeling elements reflected in the simulations included: model form (log27 linear vs log-log and random vs fixed effects), modeling risk down to PRB (vs 

28 LML), and use of an alternative hybrid rollback approach (vs proportional 

29 rollback) to simulate just meeting the current and alternative sets of standards. 

30 Various permutations of these various design elements choices (relative to the 

31 elements selected for the core analysis) were considered. Percent difference 

32 estimates (for all-cause mortality) ranged from 147% (for a model estimating 

33 risk down to PRB and use of the hybrid rollback approach) to 1,020% (for a 

34 model with random effects log-log model, risk estimated down to PRB, and use 

35 of the hybrid rollback approach). 

36 We believe that application of a log-log model with random effects is a 

37 reasonable alternative to the core model (fixed-effects log-linear model), based on our 

38 review of the discussion in Krewski et al. (2009). Similarly, the use of a hybrid rollback 
September 2009 140 Draft – Do Not Quote or Cite 

1 approach involving non-proportional adjustment where there is the potential for greater 

2 use of local control strategies to address local-sources, is a reasonable alternative to 

3 solely using a proportional rollback approach in all study areas. Therefore, we believe 

4 that the combinations of modeling elements including these alternative choices are 

5 reasonable. However, there is more concern in predicting risk down to PRB. This is not 

6 because there is evidence for a threshold, but rather because we do not have data to 

7 support characterization of the nature of the C-R function in the vicinity of PRB. 

8 Specifically, there is increasing uncertainty in predicting the nature of the C-R function as 

9 you move below the LML. So, while we believe it is reasonable conceptually to estimate 

10 risk down to PRB, the quantitative process of doing this requires use of a function with 

11 very high uncertainty. Therefore, we concluded that those alternative risk estimates 

12 generated using risk estimated down to PRB should not be used in creating the reasonable 

13 alternative set of risk estimates in considering uncertainty associated with the core risk 

14 estimates. 

15 4.3.2.2 Multi-factor sensitivity analyses – short-term exposure 

16 mortality 

17 This section summarizes the results of the sensitivity analysis focused on short18 term exposure-related mortality endpoints (see Table 4-1 for the specific modeling 

19 elements considered in the sensitivity analysis). The results of individual sensitivity 

20 analysis simulations are presented below, with overall observations presented at the end 

21 of the section. 

22  Impact of using season-specific vs. annual effect estimates and 

23 proportional vs. hybrid rollback approaches in modeling short -term 

24 exposure mortality: This multi-factor sensitivity analysis focused on a 

25 number of model design choices related to modeling short-term mortality (non26 accidental). Modeling elements included in this sensitivity analysis were use of 

27 seasonal vs. annual effects estimates and use of hybrid vs proportional rollback 

28 to simulate just meeting current and alternative standard levels. Percent 

29 difference estimates (for non-accidental mortality) across the 7 urban study 

30 areas included in the simulation ranged from -109% (LA) to +119% 

31 (Birmingham) (see Appendix F, Table F-42). However, we note that the total 

32 incidence estimates associated with these higher-impact locations were 

33 relatively low, again raising the concern for the stability in relative differences 

34 with the core estimates. 

35 We believe that the application of both alternative model formulations reflected in 

36 this multi-factor sensitivity analysis (seasonally-differentiated C-R functions and the 

37 hybrid rollback approach) are reasonable, and consequently the risk estimates that are 

38 generated do represent reasonable alternatives to the core estimates. 
September 2009 141 Draft – Do Not Quote or Cite 

1 4.4 EVALUATING THE REPRESENTATIVENESS OF THE URBAN 

2 STUDY AREAS IN THE NATIONAL CONTEXT 

3 The goal in selecting the 15 urban study areas included in this risk assessment was 

4 two fold: (a) to choose urban locations with relatively elevated ambient PM levels (in 

5 order to evaluate risk for locations likely to experience some degree of risk reduction 

6 under alternative standards) and (b) to include a range of urban areas reflecting 

7 heterogeneity in other PM risk-related attributes across the country. To further support 

8 interpretation of risk estimates generated in this analysis, we are assessing the degree to 

9 which urban study areas represent the range of key PM2.5 risk-related attributes that 

10 spatially vary across the nation. We have partially addressed this issue by selecting urban 

11 study areas that provide coverage for different PM regions of the country (see section 

12 3.3.2). In addition, we are considering how well the selected urban areas represent the 

13 overall U.S. for a set of spatially-distributed PM2.5 risk related variables (e.g., PM2.5

14 composition, weather, demographics including SES, baseline health incidence rates). 

15 This analysis will help to inform how well the urban study areas reflect national-level 

16 variability in these key PM risk-related variables. Based on generally available data (e.g. 

17 from the 2000 Census, Centers for Disease Control (CDC), or other sources), 

18 distributions for risk-related variables across U.S. counties and for the specific counties 

19 represented in the urban study areas are generated. The specific values of these variables 

20 for the selected urban study areas are then plotted on these distributions, and an 

21 evaluation is conducted of how representative the selected study areas are with respect to 

22 these individual variables, relative to the national distributions. 

23 Estimates of risk (either relative or absolute, e.g. number of cases) within our risk 

24 assessment framework are based on four elements: population, baseline incidence rates, 

25 air quality, and the coefficient relating air quality and the health outcome (i.e., the PM2.5 

26 effect estimates). Each of these elements can contribute to heterogeneity in risk across 

27 urban locations, and each is variable across locations. In addition, there may be 

28 additional identifiable factors that contribute to the variability of the four elements across 

29 locations. In this assessment, we examine the representativeness of the selected urban 

30 area locations for the four main elements, and also provide additional assessment of 

31 factors that have been identified as influential in determining the magnitude of the C-R 

32 function across locations. 

33 The specific choice of variables which may affect the PM2.5 effect estimates for 

34 which we will examine urban study area representativeness is informed by an assessment 

35 of the epidemiology literature. We particularly focused on meta-analyses and multi-city 

36 studies which identified variables that influence heterogeneity in PM2.5 effect estimates, 
September 2009 142 Draft – Do Not Quote or Cite 

1 and exposure studies which explored determinants of differences in personal exposures to 

2 ambient PM2.5. While personal exposure is not incorporated directly into PM 

3 epidemiology studies, differences in the PM2.5 effect estimates between cities clearly is 

4 impacted by differing levels of exposure and differences in exposure are clearly related to 

5 a number of exposure determinants. Broadly speaking, determinants of PM2.5 effect 

6 estimates can be grouped into three areas: demographics, baseline health conditions, and 

7 climate and air quality. Based on a review of these studies, we identified the following 

8 variables within each group as potentially determining the PM2.5 effect estimates: 

9  Demographics: education (see Zeka et al, 2006; Ostro et al, 2006), age and 

10 gender (see Zeka et al, 2006), population density (see Zeka et al, 2005), 

11 unemployment rates (see Bell and Dominici, 2008), race (see Bell and 

12 Dominici, 2008), public transportation use (see Bell and Dominici, 2008), 

13  Baseline health conditions: disease prevalence (diabetes – Bateson and 

14 Schwartz, 2004; Ostro et al, 2006; Zeka et al, 2006; pneumonia – Zeka et al, 

15 2006; stroke – Zeka et al, 2006; heart and lung disease – Bateson and 

16 Schwartz, 2004; acute myocardial infarction – Bateson and Schwartz, 2004). 

 Climate and air quality: PM2.5 levels (average, 98th 17 percentiles, and numbers 

of days over the level of the 24-hour standard, e.g. 35 μg/m3 18 ), co-pollutant 

19 levels, PM composition (see Bell et al, 2009; Dominici et al, 2007; Samet, 

20 2008; Tolbert, 2007), temperatures (temp) (days above 90 degrees, variance of 

summer temp, mean summer temp, 98th 21 percentile temp, mean winter temp -- 

22 see Roberts, 2004; Medina-Ramon et al, 2006; Zeka et al., 2005), air 

23 conditioning prevalence (see Zanobetti and Schwartz, 2009; Franklin et al, 

24 2007; Medina-Ramon et al, 2006), ventilation (see Sarnat et al, 2006), percent 

25 of primary PM from traffic (see Zeka et al., 2005), 

26 Based on these identified potential risk determinants, we identified possible 

27 datasets that could be used to generate nationally representative distributions for each 

28 parameter. We were not able to identify readily available national datasets for all 

29 variables. In these cases, if we were able to identify a broad enough dataset covering a 

30 large enough portion of the U.S., we used that dataset to generate the parameter 

31 distribution. In addition, we were not able to find exact matches for all of the variables 

32 identified through our review of the literature. In cases where an exact match was not 

33 available, we identified proxy variables to serve as surrogates. For each parameter, we 

34 report the source of the dataset, its degree of coverage, and whether it is a direct measure 

35 of the parameter or a proxy measure. The target variables and sources for the data are 

36 provided in Table 4-2. Summary statistics for the most relevant variables are provided in 

37 Table D-3. 
September 2009 143 Draft – Do Not Quote or Cite 

1 

2 Table 4-2. Data Sources for PM NAAQS Risk Assessment Risk Distribution 

3 Analysis. 

4 

Potential Risk 

Determinant Metric Year Source 

Degree of 

National 

Coverage 

Demographics 

Age Median Age 2005 

County Characteristics, 2000-2007 

Inter-university Consortium for 

Political and Social Research 

All counties 

Age Percent over 65 2005 

County Characteristics, 2000-2007 

Inter-university Consortium for 

Political and Social Research 

All counties 

Age Percent under 15 2005 

County Characteristics, 2000-2007 

Inter-university Consortium for 

Political and Social Research 

All counties 

Education Population with less 

than HS diploma 2000 

USDA/ERS, 

http://www.ers.usda.gov/Data/Edu

cation/ 

All counties 

Unemployment Percent unemployed 2005 

County Characteristics, 2000-2007 

Inter-university Consortium for 

Political and Social Research 

All counties 

Income Per Capita Personal 

Income 2005 

County Characteristics, 2000-2007 

Inter-university Consortium for 

Political and Social Research 

All counties 

Race Percent nonwhite 2006 

County Characteristics, 2000-2007 

Inter-university Consortium for 

Political and Social Research 

All counties 

Population Total population 2008 

Cumulative Estimates of Resident 

Population Change for the United 

States, States, Counties, Puerto 

Rico, and Puerto Rico Municipios: 

April 1, 2000 to July 1, 2008, 

Source: Population Division, U.S. 

Census Bureau 

All counties 

Population density Population/square mile 2008 

Cumulative Estimates of Resident 

Population Change for the United 

States, States, Counties, Puerto 

Rico, and Puerto Rico Municipios: 

April 1, 2000 to July 1, 2008, 

Source: Population Division, U.S. 

Census Bureau 

All counties 

Urbanicity ERS Classification 

Code 2003 

County Characteristics, 2000-2007 

Inter-university Consortium for 

Political and Social Research 

All counties 

Climate and Air Quality 

PM2.5 Levels PM2.5 Levels -- 

Monitored Ann Mean 2007 AQS 617 Monitored counties 

PM2.5 Levels PM2.5 Levels -- 2007 AQS 617 Monitored 
September 2009 144 Draft – Do Not Quote or Cite 

Potential Risk 

Determinant Metric Year Source 

Degree of 

National 

Coverage 

Monitored 98th %ile counties 

PM2.5 Levels Average MCAPS MCAPS website 204 counties 204 MCAPS 

counties 

PM2.5 Levels % days exceeding 35 

μg/m3 MCAPS website 204 counties 204 MCAPS 

counties 

Copollutant Levels Ozone AQS 725 Monitored 

counties 

Roadway 

emissions/Exposure 

% of primary emissions 

from traffic 1999 NEI All counties 

Temperature Annual Average MCAPS website 204 counties 204 MCAPS 

counties 

Temperature Mean July Temp 1941-

1970 

County Characteristics, 2000-2007 

Inter-university Consortium for 

Political and Social Research 

All counties 

Relative Humidity Mean July RH 1941-

1970 

County Characteristics, 2000-2007 

Inter-university Consortium for 

Political and Social Research 

All counties 

Ventilation Air conditioning 

prevalence 2005 

American Housing Survey, with 

additional processing as in Reid et 

al (2009) 

83 urban areas 

Baseline Health Conditions

Baseline Mortality All Cause CDC Wonder 1999-2005 All counties 

Baseline Mortality Non Accidental CDC Wonder 1999-2006 All counties 

Baseline Mortality Cardiovascular CDC Wonder 1999-2007 All counties 

Baseline Mortality Respiratory CDC Wonder 1999-2008 All counties 

Baseline Morbidity AMI prevelence 2007 BRFSS MSA estimates 184 BRFSS 

MSA 

Baseline Morbidity Diabetes Prevalence 2007 BRFSS MSA estimates 184 BRFSS 

MSA 

Baseline Morbidity Pneumonia Prevalence 

Baseline Morbidity Stroke Prevalence 2007 BRFSS MSA estimates 184 BRFSS 

MSA 

Baseline Morbidity CHD Prevelence 2007 BRFSS MSA estimates 184 BRFSS 

MSA 

Baseline Morbidity COPD Prevalence 

Obsesity BMI 2007 BRFSS MSA estimates 184 BRFSS 

MSA 

Level of exercise vigorous activity 20 

minutes 2007 BRFSS MSA estimates 184 BRFSS MSA 

Level of exercise 

moderate activity 30 

minutes or vigorous 

activity 20 minutes 

2007 BRFSS MSA estimates 184 BRFSS 

MSA 

Respiratory Risk 

Factors Current Asthma 2007 BRFSS MSA estimates 184 BRFSS MSA 

Smoking Ever Smoked 2007 BRFSS MSA estimates 184 BRFSS 

MSA 

C-R Estimates 

Mortality Risk All Cause 2009 Zanobetti and Schwartz (2009) 212 

cities 212 cities 

Mortality Risk Respiratory 2009 Zanobetti and Schwartz (2009) 212 

cities 212 cities 
September 2009 145 Draft – Do Not Quote or Cite 

Potential Risk 

Determinant Metric Year Source 

Degree of 

National 

Coverage 

Mortality Risk Cardiovascular 2009 Zanobetti and Schwartz (2009) 212 

cities 212 cities 

1 
September 2009 146 Draft – Do Not 

1 Table 4-3. Summary Statistics for Selected PM Risk Attributes. 

Average Standard Deviation Maximum Minimum 

Risk Attributes 

Urban study 

areas 

U.S. 

counties 

Urban study 

areas 

U.S. 

counties 

Urban study 

areas 

U.S. 

counties 

Urban study 

areas 

co

Demographics Population 1,410,331 97,020 1,870,237 312,348 9,862,049 9,862,049 57,441 Population Density (Pop/sq mile) 7,212 258 14,960 1,757 71,758 71,758 87 Median Age (years) 35.5 38.6 2.6 4.4 41.5 55.3 30.2 % Age 65 Plus 11.3 14.9 2.6 4.1 17.2 34.7 5.8 Unemployment rate (%) 5.4 5.4 1.5 1.8 9.0 20.9 2.7 % with Less than High School Diploma 21.8 22.6 7.7 8.8 37.7 65.3 11.2 Income ($2005) 35691 27367 12605 6604 93377 93377 23492 5Air conditioning prevalence (%) 85.8 83.3 13.3 21.5 99.4 100.0 58.6 % Non-white 29.5 13.0 18.2 16.2 68.3 95.3 2.7 Health Conditions Prevalence of CHD (%) 3.9 4.3 0.9 1.3 5.2 8.7 1.8 Prevalence of Obesity (%) 26.4 26.0 3.0 4.1 32.7 35.7 22.2 Prevalence of Stroke (%) 2.7 2.7 0.8 1.0 4.1 6.5 1.1 Prevalence of Smoking (ever) (%) 18.4 19.6 3.1 4.0 23.1 34.4 14.2 Prevalence of Exercise (20 minutes) (%) 28.4 28.0 3.6 4.8 33.9 44.1 20.5 All Cause Mortality (per 100,000 population) 833.7 1022.3 241.1 258.6 1342.9 2064.2 402.5 1Non-accidental Mortality (per 100,000 population) 774.1 950.6 227.3 249.6 1242.0 1958.4 361.6 1Cardiovascular Mortality (per 100,000 population) 317.5 392.1 100.6 121.0 535.7 970.4 122.4 Respiratory Mortality (per 100,000 population) 70.8 97.3 23.0 32.3 130.3 351.0 34.8 Air Quality and Climate AQ - PM25 Annual Mean (μg/m3) 15.1 11.7 2.2 3.1 19.6 22.5 9.7 AQ - PM25 98th %ile 24-hour Average (μg/m3) 38.7 30.7 11.6 9.3 79.2 81.1 26.8 AQ - O3 4th High Maximum 8-hour Average (ppm) 0.087 0.077 0.009 0.010 0.105 0.126 0.064 0% Mobile Source PM Emissions 34.0 44.4 11.2 21.9 56.6 97.6 13.7 
September 2009 147 Draft – Do Not 

Average Standard Deviation Maximum Minimum 

Risk Attributes 

Urban study 

areas 

U.S. 

counties 

Urban study 

areas 

U.S. 

counties 

Urban study 

areas 

U.S. 

counties 

Urban study 

areas 

co

July Temperature Long Term Average (°F) 78.1 75.9 4.5 5.4 91.2 93.7 64.8 July Relative Humidity Long Term Average (°F) 58.2 56.2 14.0 14.6 70.0 80.0 19.0 C-R Estimates All Cause Mortality PM2.5 Risk Estimate 0.000971 0.000974 0.000340 0.000216 0.001349 0.001508 0.000159 -0.0Respiratory Mortality PM2.5 Risk Estimate 0.001606 0.001670 0.000419 0.000305 0.002157 0.002221 0.000931 -0.0Cardiovascular Mortality PM2.5 Risk Estimate 0.001013 0.000842 0.000586 0.000324 0.001958 0.001958 -0.000180 -0.0
September 2009 148 Draft – Do Not Quote or Cite 

1 Formal comparisons of parameter distributions for the set of urban study areas 

2 and the national parameter distributions are conducted using standard statistical tests, e.g. 

3 the Kolmogorov-Smirnov non-parametric test for equality of distributions. In addition, 

4 visual comparisons are made using cumulative distribution functions, and boxplots. 

5 The formal Kolmogorov-Smirnov test results are provided in Table 4-4. The K-S 

6 tests the hypotheses that two distributions are not significantly different. A high p-value 

7 indicates a failure to reject the null hypotheses that the case-study and national 

8 distributions are the same. We used a rejection criterion of p≤0.05, which is a standard 

9 rejection criteria. It should be noted that the K-S test provides a good overall measure of 

10 fit, but will not provide a test of how well specific percentiles of the distributions are 

11 matched. As such, the K-S test results will not be sufficient to determine whether the 

12 urban study areas adequately capture the tails of the distributions of specific risk related 

13 variables. Additional visual analyses are used to assess representativeness for the tails of 

14 the distributions. Overall, the K-S test results show that for many of the important risk 

15 variables such as population, air quality, age, and baseline mortality rates, the urban study 

16 areas are not representative of the distributions of these variables for the U.S. as a whole. 

17 However, for some important potential risk determinants, such as prevalence of 

18 underlying hear and lung diseases, the case study areas are representative of the national 

19 distributions. However, for these specific variables, the national distribution is 

20 represented primarily by large urban areas, so it is more accurate in these cases to suggest 

21 that the urban study areas are representative of the overall distribution across urban areas. 

22 Figures 4-14 through 4-17 show for the four critical risk function elements 

23 (population, air quality, baseline incidence, and the PM2.5 effect estimate) the cumulative 

24 distribution functions plotted for the nation, as well as for the urban study areas. These 

25 four figures focus on critical variables representing each type of risk determinant, e.g. we 

26 focus on all-cause mortality rates, but we also have conducted analyses for cardiovascular 

27 and respiratory mortality separately. The complete set of analyses is provided in 

28 Appendix D. The vertical black lines in each graph show the values of the variables for 

29 the individual urban study areas. These figures show that the selected urban study areas 

30 represent the upper percentiles of the distributions of population and air quality, while not 

31 representing lower population locations with lower 24-hour PM2.5 levels. This is 

32 consistent with the objectives of our case study selection process, e.g. we are 

33 characterizing risk in areas that are likely to be experiencing excess risk due to PM levels 

34 above alternative standards. The urban case study locations represent the full distribution 

35 of PM2.5 risk coefficients, but do not capture the upper end of the distribution of baseline 

36 all-cause mortality. The interpretation of this is that the case study risk estimates may not 
September 2009 149 Draft – Do Not Quote or Cite 

1 capture the additional risk that may exist in locations that have the highest baseline 

2 mortality rates. 

3 Figures 4-18 through 4-21 shows for several selected potential risk attributes the 

4 CDF plotted for the nation as well as for the urban study areas. These potential risk 

5 attributes do not directly enter the risk equations, but have been identified in the literature 

6 as potentially affecting the magnitude of the PM2.5 C-R functions reported in the 

7 epidemiological literature. The selected urban study areas do not capture the higher end 

8 percentiles of several risk characteristics, including populations over 65, income, and 

9 baseline cardiovascular disease prevalence. Comparison graphs for other risk attributes 

10 are provided in Appendix D. Summarizing the analyses of the other risk attributes, we 

11 conclude that the urban study areas provide adequate coverage across population, 

12 population density, annual and 24-hour PM2.5 levels, ozone co-pollutant levels, 

13 temperature and relative humidity, unemployment rates, percent non-white population, 

14 asthma prevalence, obesity prevalence, stroke prevalence, exercise prevalence, and less 

15 than high school education. We also conclude that while the urban study areas cover a 

16 wide portion of the distributions, they do not provide coverage for the upper end of the 

distributions of age (all case study locations are below the 85th 17 %ile), % of population 65 

and older (below 85th 18 %ile), percent of primary PM emissions from mobile sources 

(below 8oth %ile), prevalence of angina/coronary heart disease (below 85th 19 %ile), 

prevalence of diabetes (below 85th %ile), prevalence of heart attack (below 80th 20 %ile), 

prevalence of smoking (below 85th %ile), all-cause mortality rates (below 90th 21 %ile), 

cardiovascular mortality rates (below 90th 22 %ile) and respiratory mortality rates (below 

90th %ile). In addition, all of the case study locations were above the 25th 23 percentile of 

24 the distribution of personal income. 

25 Based on the above analyses, we can draw several inferences regarding the 

26 representativeness of the urban case studies. First, the case studies represent urban areas 

27 that are among the most populated and most densely population in the U.S. Second, they 

represent areas with relatively higher levels of annual mean and 24-hour 98th 28 percentile 

29 PM2.5. Third, they capture well the range of effect estimates represented in the Zanobetti 

30 and Schwartz (2009) study. These three factors would suggest that the urban study areas 

31 should capture well overall risk for the nation, with a potential for better characterization 

32 of the high end of the risk distribution. However, there are several other factors that 

33 suggest that the urban study areas may not be representing areas that may have a high risk 

34 per microgram of PM2.5. The analysis suggests that the urban study areas are not 

35 capturing areas with the highest baseline mortality risks, nor those with the oldest 

36 populations. These areas may have higher risks per microgram of PM2.5, and thus the 
September 2009 150 Draft – Do Not Quote or Cite 

1 high end of the risk distribution may not be captured, although the impact on 

2 characterization of overall PM risk may not be as large, for the following reasons. 

3 It should be noted that several of the factors with underrepresented tails, including 

4 age and baseline mortality (R=0.81) are spatially correlated, so that certain counties 

5 which have high proportions of older adults also have high baseline mortality and high 

6 prevalence of underlying chronic health conditions. Because of this, omission of certain 

7 urban areas with higher percentages of older populations, for example, cities in Florida, 

8 may lead to underrepresentation of high risk populations. However, with the exception 

9 of areas in Florida, most locations with high percentages of older populations have low 

10 overall populations, less than 50,000 people in a county. And even in Florida, the 

11 counties with the highest PM2.5 levels do not have a high percent of older populations. 

12 This suggests that while the risk per exposed person per microgram of PM2.5 may be 

13 higher in these locations, the overall risk to the population is likely to be within the range 

14 of risks represented by the urban case study locations. 

15 Table 4-4 Results of Kolomogrov-Smirnoff Tests for Equality Between National 

16 and Urban Study Area Distributions for Selected National Risk 

17 Characteristic Variables 

18 (null hypothesis is no difference between the distributions) 

Risk Attributes Reject H0? p-value 

Demographics 

Population Y 0.0001 

Population Density (Pop/sq mile) Y 0.0001 

Median Age Y 0.0001 

% Age 65 Plus Y 0.0001 

Unemployment rate N 0.5850 

% with Less than High School Diploma N 0.8535 

Income Y 0.0001 

Air Conditioning Prevalence (%) N 0.9592 

% Non-white Y 0.0001 

Health Conditions 

Prevalence of CHD N 0.7705 

Prevalence of Obesity N 0.9180 

Prevalence of Stroke N 0.7064 

Prevalence of Smoking (ever) N 0.5748 

Prevalence of Exercise (20 minutes) N 0.7649 

All Cause Mortality Y 0.0001 

Non-accidental Mortality Y 0.0002 

Cardiovascular Mortality Y 0.0060 

Respiratory Mortality Y 0.0001 
September 2009 151 Draft – Do Not Quote or Cite 

Comparison of Urban Case Study Area Population with U.S. Distribution of 

Population (all U.S. Counties)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

100 1000 10000 100000 1000000 10000000

Population

% of Counties

All Counties CDF Case Study Counties CDF Case Study Counties

Urban case study areas are 

all above the 65th Percentile 

of county populations

Risk Attributes Reject H0? p-value 

Air Quality and Climate 

AQ - PM25 Annual Mean Y 0.0001 

AQ - PM25 98th %ile 24-hour Average Y 0.0001 

AQ - PM25 % of days above 35 ug/m3 Y 0.0248 

AQ - O3 4th High Maximum 8-hour 

Average Y 0.0003 

% Mobile Source PM Emissions Y 0.0133 

July Temperature Long Term Average Y 0.0003 

July Relative Humidity Long Term 

Average N 0.0614 

C-R Estimates 

All Cause Mortality PM2.5 Risk N 0.1585 

Respiratory Mortality PM2.5 Risk N 0.2864 

Cardiovascular Mortality PM2.5 Risk N 0.1161 

1 

2 

3 Figure 4-14. Comparison of distributions for key elements of the risk equation: 

5 total population. 

7 

9 
September 2009 152 Draft – Do Not Quote or Cite 

Comparison of Urban Case Study Area 98th %ile PM2.5 with U.S. Distribution of 

98th %ile PM2.5 

(617 U.S. Counties with PM2.5 Monitors)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0 10 20 30 40 50 60 70 80 90

98th Percentile Daily PM2.5

% of Monitored Counties

All Counties CDF Case Study Counties CDF Case Study Counties

1 Figure 4-15 Comparison of distributions for key elements of the risk equation: 

 98th 2 percentile 24-hour average PM2.5 

3 
September 2009 153 Draft – Do Not Quote or Cite 

1 Figure 4-16. Comparison of distributions for key elements of 

2 the risk equation: all cause mortality rate. 

Comparison of Urban Case Study All Cause Mortality Rate to U.S. Distribution of All 

Cause Mortality Rate

(3143 U.S. Counties)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

100 300 500 700 900 1100 1300 1500 1700 1900 2100

All Cause Mortality per 100,000 Population

% of U.S. Counties

All Counties CDF Case Study Counties CDF Case Study Counties

Urban case study areas are 

all below the 90th percentile 

of county all cause mortality

3 
September 2009 154 Draft – Do Not Quote or Cite 

1 Figure 4-17. Comparison of distributions for key elements of the risk equation: 

2 mortality risk effect estimate from Zanobetti and Schwartz (2008). 

Comparison of Urban Case Study PM All-cause Mortality Risk (β) to 

U.S. Distribution of PM All-cause Mortality Risk

(212 U.S. Urban Areas)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0 0.0002 0.0004 0.0006 0.0008 0.001 0.0012 0.0014 0.0016

Bayesian Shrunken PM All Cause Mortality Risk Coefficient (β)

% of Z&S Urban Areas

All Z&S Urban Areas CDF Case Study Urban Area CDF Case Study Urban Areas 3 

4 

5 

6 

7 
September 2009 155 Draft – Do Not Quote or Cite 

1 Figure 4-18. Comparison of distributions for selected variables expected to 

2 influence the relative risk from PM2.5: long term average July 

3 temperature. 

Comparison of Urban Case Study Area Long Term Average July Temperature to 

U.S. Distribution of Long Term Average July Temperature

(3141 U.S. Counties)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

50 60 70 80 90 100

July 30 Year Average Temperature, 1941-1970

% of U.S. Counties

All Counties CDF Case Study Counties CDF Case Study Counties 4 

5 
September 2009 156 Draft – Do Not Quote or Cite 

1 

2 Figure 4-19. Comparison of distributions for selected variables expected to 

3 influence the relative risk from PM2.5: percent of population 65 and 

4 older. 

Comparison of Urban Case Study Area % 65 and Older to U.S. Distribution of % 65 

and Older

(3141 U.S. Counties)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0 5 10 15 20 25 30 35

% of Population 65 and Older, 2005

% of U.S. Counties

All Counties CDF Case Study Counties CDF Case Study Counties

Urban case study areas are 

all below the 75th percentile 

of county % of population 65 

and older

5 
September 2009 157 Draft – Do Not Quote or Cite 

1 

2 Figure 4-20. Comparison of distributions for selected variables expected to 

3 influence the relative risk from PM2.5: per capita annual personal 

4 income. 

Comparison of Urban Case Study Area Per Capita Personal Income to U.S. 

Distribution of Per Capita Personal Income

(3141 U.S. Counties)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

$10,000 $20,000 $30,000 $40,000 $50,000 $60,000 $70,000 $80,000 $90,000

Per Capita Personal Income, 2005

% of U.S. Counties

All Counties CDF Case Study Counties CDF Case Study Counties

Urban case study areas are 

all above the 25th percentile 

of county per capita income

5 

6 
September 2009 158 Draft – Do Not Quote or Cite 

1 

2 Figure 4-21. Comparison of distributions for selected variables expected to 

3 influence the relative risk from PM2.5: cardiovascular disease 

4 prevalence days. 

Comparison of Urban Case Study Area Angina/CHD Prevalence to U.S. Distribution 

of Angina/CHD Prevalence

(183 U.S. MSA)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

123456789

% Prevalence of Angina or CHD, BRFSS, 2007

% of BRFSS MSA

All BRFSS MSA CDF Case Study County MSA CDF Case Study County MSA

Urban case study areas are 

all below the 85th percentile 

of MSA angina or CHD 

prevalence

5 

6 4.5 OVERALL SUMMARY AND KEY OBSERVATIONS 

7 This section provides a summary of the key observations related to the core risk 

8 results, including both the recent conditions analysis results and estimates generated for 

9 the current and alternative sets of standards (section 4.5.1). Next, observations resulting 

10 from the sensitivity analyses related to the first goal for the analyses (what they tell us 

11 about the key sources of uncertainty potentially impacting the core risk estimates) are 

12 presented (section 4.5.2). Then, observations related to the second goal of the sensitivity 

13 analysis (how the output of the sensitivity analysis can be used to gain some perspective 

14 on the magnitude of uncertainty related to the core risk estimates) are presented (section 

15 4.5.3). The final two subsections end by discussing the results of two national-scale 

16 assessments designed to evaluate the representativeness of the 15 urban study areas (and 

17 the 31 counties comprising those urban areas) in the national context with regard to PM18 related risk. Specifically, section 4.5.4 discuses observations from an assessment of how 
September 2009 159 Draft – Do Not Quote or Cite 

1 the 15 urban study areas (and their 31 counties) compare against a set of national 

2 distributions for key PM risk-related attributes. Section 4.5.5 discusses observations 

3 resulting from seeing how the set of 15 urban study areas (and their 31 counties) are 

4 distributed across a cumulative plot of national-scale long-term PM2.5-related mortality 

5 generated for all counties in the U.S. 

6 4.5.1 Core risk results from the recent conditions, current NAAQS, and 

7 alternative NAAQS analyses 

8 This section provides an overall summary and key observations related to the core 

9 risk estimates (see section 4.1 and 4.2 for a detailed discussion of these results). As 

10 discussed in section 4.1, the core risk estimates are generated using model inputs believed 

11 to have the greatest support in the literature and therefore, they have received greater 

12 focus in the discussions of risk estimates generated for the urban study areas. The results 

13 discussed below related to just meeting the current and alternative sets of standards are 

14 based on results from 14 of the 15 study areas, with Pittsburgh being excluded at this 

15 time due to an error that was identified in the approach used to simulate ambient PM2.5

16 levels just for the Pittsburgh study area for the scenarios involving just meeting the 

17 current and alternative sets of standards. As noted earlier in sections 2.4.1 and 4.2, there 

18 was insufficient time after identifying this error to either generate corrected risk estimates 

19 or remove the erroneous risk estimates from the summary tables (presented in Appendix 

20 E). We will correct this error and release updated results for the Pittsburgh study area as 

21 soon as is practicable and will include the corrected results in the next version of this 

22 document. 

23 This overview of risk results is organized by air quality scenario, beginning with 

24 recent conditions followed by just meeting the current set of standards and each of the 

25 four sets of alternative standards considered. An important factor to consider in 

26 interpreting the risk estimates for both the current set of standards and set of alternative 

27 standards is whether the annual or 24-hour standard for a given pairing of standards is 

controlling for a particular area.43 28 This factor can have a significant impact on the pattern 

29 of risk reductions predicted for a given location under the simulation of just meeting a 

30 specific set of standards. As such, particular attention is given to this factor when 

31 discussing risk reductions associated with the current and alternative sets of standards. 

 43 For a given pairing of standard levels (e.g., 13/35), the controlling standard can be identified by 

comparing these levels to the design values for a given study area (see Table 3-3 for the annual and 24-hr 

design values for each of the urban study areas). The controlling standard is the standard (annual or 24 hr) 

that requires the greatest percent reduction in the matching design value to meet that standard. 
September 2009 160 Draft – Do Not Quote or Cite 

1 Recent conditions analysis: Because this air quality scenario represents recent 

2 conditions, risk estimates are described in absolute terms, not in terms of a change or 

3 reduction relative to another air quality scenario. 

4  Long-term exposure mortality: The recent conditions analysis for long-term 

5 exposure mortality suggests that across the 15 urban study areas, for the 

6 simulation year 2007, from 1.7 to 6.7% of all cause mortality incidence is 

7 estimated to be associated with PM2.5 exposure. Risk estimates are notably 

8 higher for specific mortality categories, with IHD having the highest percent 

9 contribution from PM2.5, ranging from 6.7 to 23.5% across the 15 urban study 

10 areas. We note that a significant portion of these ranges results from 

11 application of two sets of C-R functions – one based on monitoring data from 

12 1979-1983 and a second set derived using monitoring data from 1999-2000 

13 from the same cohort study (i.e., the extended analysis of the ACS). 

14  Short-term exposure mortality and morbidity: Recent conditions estimates 

15 for short-term exposure mortality suggest that from 0.2 to 1.7 percent of all 

16 non-accidental mortality is associated with PM2.5. As with long-term mortality, 

17 estimates for individual short-term exposure mortality categories (e.g., 

18 respiratory) are higher, ranging up to 2.9%. Estimates for short-term exposure 

19 morbidity (HAs) are similar in magnitude to short-term mortality. The analysis 

20 of emergency department visits in New York and Los Angeles produced 

21 estimates nearer the lower end of this range (e.g., 0.6% of incidence attributable 

22 to PM2.5). 

23 Simulating just meeting the current standards: Risk estimates for this air quality 

24 scenario in 14 study areas are described by comparing estimates of risk attributable to 

PM2.5 under the current set of standards to risk estimates under recent conditions.44 25 Note 

26 that two of the 14 urban study areas (Dallas and Phoenix) have both annual and 24-hr 

design values that are below the matching current standard levels of 15 and 35 μg/m3 27 , 

28 respectively (see Table 3-3). This means that these two urban study areas would not have 

29 any reduction in long-term or short-term risk under the current standards, as reflected in 

30 the summaries presented below (note, however, that both areas have predicted risk 

31 reductions under some of the alternative sets of standards). 

32  Long-term exposure mortality: Of the 12 urban study areas with at least one 

33 design value exceeding the current standard levels, we estimated that the 

34 percent of total all-cause mortality (associated with PM2.5) would be reduced by 

35 5 to 15% (for 5 urban study areas), by 30 to 40% (for 4 urban study areas), and 

36 by ~60% (for 3 urban study areas) relative to risk estimated under recent 

37 conditions. The magnitude of risk reductions is similar for the other long-term 

38 cause-specific mortality categories. 

 44 As noted earlier, Pittsburgh has been excluded due to an error that was identified in the approach used to 

simulate ambient PM2.5 levels just for the Pittsburgh study area for the scenarios involving just meeting the 

current and alternative sets of standards. Consequently, the number of study areas discussed in relation to 

the current standard (as well as alternative standards) is 14, rather than 15. 
September 2009 161 Draft – Do Not Quote or Cite 

1  Short-term exposure mortality and morbidity: Short-term exposure non2 accidental mortality is estimated to have a slightly smaller overall degree of risk 

3 reduction under the current set of standards compared with reductions estimated 

4 for long-term exposure mortality. With regard to the 12 urban study areas 

5 predicted to have risk reductions under the current standards, we estimated that 

6 total non-accidental mortality associated with PM2.5 would be reduced by less 

7 than 10% (for 4 areas), by 10 to 30% (for 5 areas), and by 40 to ~70% (for 4 

8 areas) relative to risk estimated under recent conditions. Other short-term 

9 exposure mortality categories, as well as short-term exposure morbidity 

10 categories (HAs), display a similar distribution of risk reduction across the 

11 urban study areas for the current set of standards. 

12 Simulating just meeting alternative sets of standards focusing on lower annual 

13 standard levels (13/35, 12/35): Risk reductions for alternative sets of standards were 

calculated relative to risk estimated under the current set of standards.44 14 We note that 

15 Dallas and Phoenix had annual and 24-hour design values which were lower than the 

16 13/35 set of alternative standards , but the annual design values were above the 12/35 set 

17 of alternative standards (see Table 3-3). For two of the other study areas (Fresno and 

18 Los Angeles), where the 24-hr standard was controlling, simulating just meeting the 

19 current standard resulted in significant reductions in the annual PM2.5 levels, such that no 

20 risk reduction was seen for the 13/35 alternative set of standards (i.e., adjusted annual 

21 PM2.5 levels for these study areas under the current set of standards were already below 

13 μg/m3 22 ). We note, however, that Los Angeles did show risk reductions under the 12/35 

23 set of standards , while Fresno continued not to have predicted risk reductions under the 

24 12/35 set of alternative standards due to the significant reduction in annual levels 

25 associated with just meeting the current set of standards. Because Tacoma and Salt Lake 

City already had annual design values (10 and 12 μg/m3 26 , respectively) at or below the 12 

μg/m3 27 associated with the lower of these two alternative sets of standards, neither study 

28 area exhibited risk reductions. Specific ranges of risk reductions for those urban study 

29 areas predicted to have reductions under these two alternative sets of standards are 

30 summarized below: 

31  Long-term exposure mortality: For the 8 study areas predicted to have risk 

32 reductions under the 13/35 set of standards, one area had reductions in all-cause 

33 mortality (attributable to PM2.5) of about 5%, while the remaining 7 had 

34 reductions from over 10 to ~25% relative to risk estimated under the current set 

35 of standards. Under the 12/35 set of standards, 11 of the urban study areas were 

36 predicted to have risk reductions, with 4 areas having 10 to 22% reductions and 

37 7 locations having 25 to 35% reductions relative to risk estimated under the 

38 current set of standards. The magnitude of risk reductions is similar for the 

39 other long-term exposure cause-specific mortality categories. 

40 Short-term exposure mortality and morbidity: For the 8 study areas predicted to have 

41 risk reductions for short-term exposure mortality and morbidity endpoints under the 

42 13/35 set of standards, reductions range from 3 to 15% across all endpoints relative to 

43 risk estimated under the current set of standards. For the 11 urban study areas predicted 

44 to have risk reductions for short-term exposure mortality and morbidity endpoints under 

45 the 12/35 set of standards, reductions range from 5 to 23% across all endpoints. 
September 2009 162 Draft – Do Not Quote or Cite 

1 Simulating just meeting alternative sets of standards focusing on combinations of 

2 lower annul and lower 24-hour levels (13/30, 12/25): Because of the combination of 

3 lower 24-hr and annual levels, 13 of the 14 urban study areas had risk reductions under 

4 the 13/30 standard level (only Dallas continued not to have predicted risk reductions), 

5 while all 14 urban study areas exhibited risk reductions under the 12/25 alternative set of 

6 standards. 

7  Long-term exposure mortality: Under the 13/30 set of standards, reductions 

8 in all-cause mortality attributable to PM2.5 ranged from 14 and 44% relative to 

9 risk under the current set of standards across 13 study areas. Under the 12/25 

10 set of standards, the degree of risk reduction in all-cause mortality was between 

11 12 and 89% across all 14 study areas . The magnitude of risk reductions was 

12 similar for the other long-term cause-specific mortality categories. 

13  Short-term exposure mortality and morbidity: Under the 13/30 set of 

14 standards, reductions in non-accidental mortality attributable to PM2.5 ranged 

15 from 6 to 15% relative to the current set of standards. Under the 12/25 set of 

16 standards, risk reductions ranged from 7 to 29%. Other short-term exposure 

17 mortality categories, as well as short-term exposure morbidity categories 

18 (HAs), display a similar distribution of risk reduction across the urban study 

19 areas. 

20 4.5.2 Use of the reasonable set of alternative risk estimates generated 

21 through the sensitivity analysis 

22 As discussed in the introduction to this chapter, the use of alternative inputs to the 

23 risk assessment model that have some degree of support in the literature (for the single 

24 and multi-element sensitivity analyses) results in a set of reasonable risk estimates that 

25 supplement the core risk estimates (the full set of sensitivity analysis-related risk 

26 estimates are presented in the detailed tables presented in Appendix F and summarized in 

27 section 4.3). Specifically, these additional risk estimates represent a set of alternative 

28 realizations around the core set of risk results and while these results collectively do not 

29 represent a formal uncertainty distribution, they can be used to gain some perspective 

30 regarding the range of uncertainty around the core risk results. 

31 After careful consideration of the results of the sensitivity analysis completed for 

32 the three categories of health endpoints included in the risk assessment (long-term 

33 exposure mortality, short-term exposure mortality, and short-term exposure morbidity), 

34 we have concluded that only the sensitivity analysis results generated for long-term 

35 exposure mortality are robust enough to support using those estimates to inform 

consideration of uncertainty associated with the core risk estimates.45 36 In the case of both 

 45 Note, however, that as discussed earlier in section 4.3.1, uncertainty associated with modeling risk down 

to PRB is such that we have not included these risk estimates as part of the reasonable set of risk estimates 

and therefore they are not discussed here. However, the PRB-based risk estimates can be used generally, to 
September 2009 163 Draft – Do Not Quote or Cite 

1 short-term exposure mortality and morbidity, the sensitivity analyses were not as 

2 comprehensive (the number of modeling elements considered was smaller), reflecting 

3 information readily available in the underlying epidemiological studies. As noted above 

4 (sections 4.3.1 and 4.3.2), the results of the sensitivity analysis conducted for these two 

5 short-term health impact categories, resulted in a combination of inconclusive results (in 

6 the case of seasonally-differentiated effects estimates) and fairly small impacts on risk 

7 (for the application of the hybrid rollback approach for simulating just meeting 

8 alternative suites of standards). Therefore, there would be little utility in using these 

9 sensitivity analysis results to generate an additional set of risk estimates to inform 

consideration of uncertainty associated with the core risk results.46 10 

11 We also considered the use of the Moolgavakar-based sensitivity analysis results, 

12 reflecting the range of risk across alternative model choices based on this single study. 

13 However, use of this study to generate alternative sets of risk estimates to supplement the 

14 core estimates is problematic given the questionable relevance of the Moolgavkar-based 

15 sensitivity analysis findings to the core risk results (i.e., core risk estimates are based on 

16 large multi-location studies with different design elements relative to the Moolgavkar et 

17 al., 2003 study conducted only for Los Angeles). Therefore, we concluded that the 

18 Moolgavkar-based results should not be used to generate an additional set of risk 

19 estimates to supplement the core estimates in considering uncertainty. This means that 

20 only the long-term mortality endpoints have been included in this effort to use the results 

21 of the sensitivity analysis to inform consideration of uncertainty related to the core risk 

22 estimates. 

23 For purposes of illustrating how the results of the sensitivity analysis (specifically 

24 the multi-factor analysis) can be used to inform consideration of the range of uncertainty 

25 associated with the core risk estimates involving long-term mortality, we have provided 

26 one example below, focusing on Los Angeles for long-term (all cause) mortality. We 

 

gain perspective for the overall magnitude of uncertainty that modeling risk down to PRB (rather than 

LML) might produce and for that reason they are discussed in the context of identifying key sources of 

uncertainty impacting the core risk estimates. 

46 As part of ongoing refinements to the risk assessment, we may consider additional sensitivity analyses 

focused on short-term exposure mortality and morbidity endpoints. One potential area of exploration is the 

C-R functions used, although in the case of short-term exposure mortality, it may not be possible to gain 

further insights into alternate model specifications (from a quantitative standpoint) since we obtained a set 

of location-specific effects estimates from the authors and various model designs provided in the original 

study would have little applicability to assessing sensitivity of the location-specific effect estimates. 
September 2009 164 Draft – Do Not Quote or Cite 

1 note that the approach illustrated here for this urban study area location/health endpoint 

2 combination can be readily repeated for other combinations (based on application of data 

3 in Appendices E and F). We also note that the sensitivity analyses were conducted based 

4 exclusively for the scenario where the current set of standards is just met, so our 

5 observations here are limited to that scenario. However, we believe that observations 

6 made based on these results can be extrapolated with care to other air quality scenarios, 

7 for the same health endpoint/urban study area location. 

8 The process of generating the additional set of reasonable risk estimates based on 

9 the sensitivity analysis results involves using the results of the sensitivity analysis (which 

10 are in the form of percent difference compared to the core estimates) to adjust the core 

11 risk estimates. This procedure results in the additional set of reasonable risk estimates 

12 which can be used to inform consideration of uncertainty in the underlying core results. 

13 Table 4-5 provides the underlying core risk estimates, the percent difference results (from 

14 the sensitivity analysis) and the resulting adjusted risk estimates that represent the 

15 additional set of reasonable risk results (for Los Angeles/all-cause mortality combination 

16 for simulation year 2007). 

17 Table 4-5 Derivation of a set of reasonable alternative risk estimates to 

18 supplement the core risk estimates (Los Angeles, current standards, 

19 for long-term all cause mortality). 

Sensitivity analysis 

Core risk estimate Description simulation 

Results 

(percent difference: 

sensitivity analysis 

versus core estimate) 

Adjusted set of risk 

estimate to 

supplement core 

risk estimates1 

Single-element sensitivity analysis results 

Impact of using different 

model choices: random effects 

log-linear model 

+23% 2.1 to 2.7% 

Impact of using different 

model choices: random effects 

log-log model 

+155% 4.3 to 5.6% 

Impact of C-R function from 

alternative long-term exposure 

study (Krewski et al., 2000) -25% 1.3 to 1.7% 

Impact of using alternative 

hybrid roll-back approach to 

simulate just meeting 

alternative standards 

+24% 2.1 to 2.7% 

Multi-element sensitivity analysis results 

Percent of total 

incidence for all cause 

mortality (current suite 

of standards ): 1.7 to 

2.2%

(range reflects two CR functions based on 

different periods of 

ambient data - see 

Appendix F, Tables F6 and F-15) 

Random effects log-log & 

hybrid non-proportional 

rollback 

+203% 5.2 to 6.7% 

1 20 Percent of total incidence that is PM2.5- related. 

21 
September 2009 165 Draft – Do Not Quote or Cite 

1 The reasonable set of alternative risk estimates is presented along with the core 

2 set of risk estimates for the example scenario in Figure 4-22. As noted earlier in 

3 discussing the results of the single-factor sensitivity analysis (and in Table 4-5), we 

4 consider estimates based on modeling risk down to PRB to be less reasonable than the 

5 other scenarios included in the sensitivity analysis, since there is substantial uncertainty 

6 associated with the C-R function shape below the LML (i.e., for long-term ambient PM2.5

7 levels below the levels for any of the urban areas included in the underlying 

8 epidemiological studies). Therefore, results of modeling risk down to PRB are not 

9 included in Figure 4-22. 

10 Figure 4-22. Comparison of core risk estimates with reasonable alternative set of 

11 risk estimates generated as part of sensitivity analyses. 

Percent total incidence attributable to PM2.5 (all cause mortality)

Core risk estimates

Additional set of 

reasonable risk 

estimates

0 1 2 3 4 6 5 7

Los Angeles for current conditions air quality scenario (2007 simulation year)

Percent total incidence attributable to PM2.5 (all cause mortality)

Core risk estimates

Additional set of 

reasonable risk 

estimates

0 1 2 3 4 6 5 7

Los Angeles for current conditions air quality scenario (2007 simulation year)

12 

13 The additional sets of risk estimates presented in Table 4-5 (and illustrated in 

14 Figure 4-22) can be used to inform consideration for the range of uncertainty associated 

15 with the core risk estimates. Given consideration for alternative model specifications that 

16 have some degree of support in the literature, the range of risk estimates around the core 

17 estimates of 1.7 to 2.2% extends from 1.3 to 6.7% for total all cause mortality attributable 

18 to PM2.5. It is important to reiterate that this set of alternative realizations presented in 

19 Table 4-5 and depicted in Figure 4-22, does not represent an uncertainty distribution. 

20 Therefore, we can not assign percentiles to the individual data points presented and 

21 (importantly), we do not draw any conclusions based on any clustering of the alternative 

22 risk estimates see in Figure 4-22. Furthermore, we do not know whether any of the 

23 higher-end estimates generated actually represent true bounding risk estimates given 

24 overall uncertainty associated with the core risk estimates. Despite these key caveats, 

25 having a range of risk estimates reflecting the impact of modeling element uncertainties 
September 2009 166 Draft – Do Not Quote or Cite 

1 does provide information that helps to inform our characterization of uncertainty related 

2 to the core risk estimates. 

3 4.5.3 Representativeness of the urban study areas in the national context 

4 based on consideration for coverage of PM2.5 risk-related parameters 

5 The representativeness analysis (discussed in detail in section 4.4) considered 

6 how well the 15 urban study areas represent the overall U.S. for a set of spatially7 distributed PM2.5 risk related variables (e.g., PM2.5 composition, weather, demographics 

8 including SES, baseline health incidence rates). In doing so, this analysis helps inform 

9 how well the urban study areas reflect national-level variability in these key PM risk10 related variables. 

11 The results of the representativeness analysis suggest that, in relation to three of 

12 the factors considered (coverage for: more heavily populated urban areas, urban areas 

13 with higher ambient PM2.5 levels, and the range of effects estimates for short-term 

14 mortality from Zannobetti and Schwartz., 2009), the 15 urban study areas would appear 

15 to capture well the overall risk for the nation, with a potential for better characterization 

16 of the higher end of the national risk distribution. However, consideration for other 

17 factors (coverage for areas with higher baseline mortality rates and with the oldest 

18 populations) suggests that the 15 urban study areas may not capture areas having the 

19 highest risk per microgram of PM2.5 (i.e., they may not be capturing the high-end of the 

20 national risk distribution). The limitations in coverage for high baseline mortality rates 

21 and older populations, are tempered by the fact that many locations with these types of 

22 “at risk” populations do not have elevated PM2.5 levels (e.g., urban locations in Florida). 

23 4.5.4 Use of the results of the national-scale long-term mortality analysis to 

24 evaluate degree of coverage of the 15 urban study areas for national25 distribution of risk 

26 As part of the national-scale long-term mortality analysis related to PM2.5 

27 exposure, which is discussed in detail in chapter 5, we developed a cumulative 

28 distribution of county-level long-term exposure mortality risk for the U.S. (see Figure 5-

29 4). This then allowed us to determine where along this cumulative distribution the 31 

30 counties associated with the 15 urban study areas modeled in the risk assessment fell 

31 (note, the location of the 31 counties along the cumulative distribution is also shown in 5-

32 4). 

33 Comparison of the 31 counties (from the 15 urban study areas) against the 

34 national county-level distribution of long-term exposure mortality risk results in the 

35 observation that most of the 31 counties fall towards the upper end of the national 
September 2009 167 Draft – Do Not Quote or Cite 

distribution with 23 of the 31 counties falling within the upper 5th 1 percentile of the 

2 distribution. These observations suggest that the 15 urban study areas included in the PM 

3 NAAQS risk assessment capture well the upper-end of the national distribution of long4 term PM2.5 exposure-related risk. 

5 
September 2009 168 Draft – Do Not Quote or Cite 

1 5 NATIONAL-SCALE ASSESSMENT OF LONG-TERM 

2 MORTALITY RELATED TO PM2.5 EXPOSURE 

3 5.1 OVERVIEW 

4 In this section we present the estimated nationwide premature mortality resulting 

5 from recent exposures to ambient PM2.5. The goal of this assessment is twofold: (1) 

6 estimate the incidence of premature mortality within the U.S. related to long-term PM2.5

7 exposure; and (2) identify where the subset of counties assessed in the urban case study 

areas analysis fall along the distribution of national county-level risk.47 8 To perform this 

9 assessment we use 2005 PM2.5 fused air quality estimates from the Community Model for 

10 Air Quality (CMAQ) (Byun and Schere, 2006) in conjunction with the environmental 

11 Benefits Mapping and Analysis Program (BenMAP) to estimate long-term PM2.5-related 

12 premature mortality nationwide. 

13 To address the first goal of the assessment, we estimate excess PM2.5-related long14 term mortality by applying two estimates of all-cause mortality risk found in the Krewski 

15 et al. (2009) PM2.5 mortality extended analysis of the American Cancer Society (ACS) 

16 cohort, and an estimate of all-cause mortality risk found in the Laden et al. (2006) PM2.5

17 mortality extended analysis of the Six-Cities cohort. We estimate that total PM2.5-related 

premature mortality ranges from 63,000 (39,000—87,000) (95th 18 percentile confidence 

19 interval) and 88,000 (49,000—130,000), respectively; in each case we estimated deaths 

20 per year down to the lowest measured levels (LMLs) in each epidemiological study. 

21 In addressing the second goal of this assessment, we observe that the subset of 31 

22 counties for the 15 urban study areas considered in the urban case study fall toward the 

23 upper end of the national distribution. Specifically, all of the 31 counties were above the 

median of the national risk distribution and 23 of the 31 fell within the upper 5th 24 

25 percentile of the national distribution. Therefore, according to this analysis, we appear to 

26 be capturing high-end percentiles of the national risk distribution with the set of urban 

27 case study areas we are evaluating in the PM2.5 NAAQS risk assessment. 

28 

29 

30 

 

47 We do not directly compare the estimated county-level risks generated in the urban case study 

assessment and the county-level risks generated in the national-scale analysis. Rather, we identify where 

the 31 counties modeled for urban case study fell along the national risk distribution. This assessment 

revealed whether the baseline PM2.5 mortality risks in the 31counties modeled in the urban case study areas 

represented more typical or higher-end risk relative to the national risk distribution. 
September 2009 169 Draft – Do Not Quote or Cite 

1 5.2 METHODS 

2 This assessment combines information regarding estimated PM2.5 air quality 

3 levels, population projections, baseline mortality rates, and mortality risk coefficients to 

4 estimate PM2.5-related premature mortality. Figure 5-1 below provides a conceptual 

5 diagram, detailing each of the key steps involved in performing this BenMAP-based 

6 health impact assessment. Appendix G contains additional information regarding the 

7 data inputs to this analysis. 

8 Figure 5-1 Conceptual diagram of data inputs and outputs for national long-term 

10 mortality risk assessment 

12 

14 

16 

18 

19 5.2.1 Population Estimates 

20 The starting point for estimating the size and demographics of the potentially 

21 exposed population is the 2000 census-block level population, which BenMAP 

22 aggregates up to the same grid resolution as the air quality model. Using county-level 

23 growth factors based on economic projections (Woods and Poole Inc., 2001), BenMAP 

24 projects this 2000 population to the analysis year of 2005; we selected this population 

25 year because it matches both the year in which the emissions inventory was developed for 

26 the air quality modeling and the year to which the baseline mortality rates were projected 

27 (see below). 

28 5.2.2 Population Exposure 

29 Having first estimated the size and geographic distribution of the potentially 

30 exposed population, BenMAP then matches these population projections with estimates 

31 of the ambient levels of PM2.5. In contrast to the urban study areas analysis, the national-
September 2009 170 Draft – Do Not Quote or Cite 

1 scale analysis employed a data fusion approach, which joined 2005 monitored PM2.5

2 concentrations with 2005 CMAQ-modeled air quality levels using the Voronoi Neighbor 

3 Averaging (VNA) technique (Abt, 2003). CMAQ was run at a horizontal grid resolution 

4 of 12km for the east and 36km in the west using 2005 estimated emission levels and 

5 meteorology. More information on this model run can be found in Appendix G of this 

6 document. Figure 5-2 shows the geographic distribution of baseline annual mean PM2.5

7 concentrations across the continental U.S. The maximum predicted value within the U.S. 

is 31 μg/m3

, the mean PM2.5 value is 8.7 μg/m3, median is 8.8 μg/m3 and the 95th 8 

percentile value is about 14 μg/m3 9 . 

11 Figure 5-2 2005 fused surface baseline PM2.5 concentrations 

12 

13 This assessment applies PM2.5 mortality risk coefficients drawn from long-term 

14 cohort studies which estimate changes in risk based on annual mean changes in PM2.5

15 concentration. For this reason, EPA used the CMAQ model to estimate annual mean 
September 2009 171 Draft – Do Not Quote or Cite 

1 concentrations at each grid cell. These grid-level annual average concentrations were 

2 then input to BenMAP. 

3 5.2.3 Premature Mortality Estimates 

4 In this assessment of PM2.5-related premature mortality we considered risk 

5 estimates drawn from studies based on two prospective cohorts. The first study is the 

6 recently published Krewski et al. (2009) extended reanalysis of the ACS cohort. To 

7 remain consistent with the urban study areas analysis, we applied the two log-linear all8 cause mortality risk coefficients based on the 1979-1983 and the 1999-2000 time periods 

9 that control for 44 individual and 7 ecologic covariates. We also applied a log-linear all10 cause mortality risk coefficient drawn from the extended analysis of the Six Cities cohort 

11 as reported by Laden et al. (2006). When estimating premature mortality using these 

12 functions we considered air quality levels down to the lowest measured levels (LML) in 

each study; for the Krewski et al. (2009) study this is 5.8 μg/m3 13 and for the Laden et al. 

(2006) study this is 10 μg/m3 14 . In general, we place a higher degree of confidence in 

15 health impacts estimated at air quality levels at or above the LML because the portion of 

16 the concentration-response curve below this point is extrapolated beyond the observed 

17 data. We also estimated health impacts down to Policy Relevant Background (PRB) 

18 levels (EPA, 2008). The second draft ISA presents estimates of annual mean PRB for 

each of 7 Health Effects Institute PM regions; this value ranges from 0.62 μg/m3 19 in the 

southwest to 1.72 μg/m3 20 in the southeast. 

21 BenMAP contains baseline age-, cause- and county-specific mortality rates drawn 

22 from the CDC-WONDER. Current baseline mortality estimates are an average of a three 

23 year period from 1996-1998. EPA is in the process of updating these rates with 2006-

24 2008 data; a sensitivity analysis suggests that the results reported here are largely 

25 insensitive to the use of more current mortality rates. 

26 5.3 RESULTS 

27 Table 5-1 and figures 5-3 through 5-4 below summarize the results of the 

28 national-scale analysis. Table 5-1 summarizes the total PM2.5-related premature mortality 

29 associated with modeled 2005 PM2.5 levels. 

30 Estimated PM2.5-Related Premature Mortality Associated with Incremental Air 

31 Quality Differences Between 2005 Ambient Mean PM2.5 Levels and LML from the 

32 Epidemiology Studies or PRB (90th percentile confidence interval) 

33 

34 
September 2009 172 Draft – Do Not Quote or Cite 

1 Table 5-1 Estimated PM2.5-related premature mortality associated with 

2 incremental air quality differences between 2005 ambient mean 

3 pm2.5 levels and lowest measured level from the epidemiology studies 

 or policy relevant background (90th 4 percentile confidence interval) 

Estimates Based on Krewski et al. (2009) 

Air Quality 

Level 

‘79-’83 estimate 

(90th percentile 

confidence interval) 

‘99-’00 estimate 

(90th percentile 

confidence interval) 

Estimates Based on 

Laden et al. (2006) 

(90th percentile 

confidence interval) 

10 μg/m3 (LML 

for Laden et al., 

2006) 

26,000 

(16,000—36,000) 

33,000 

(22,000—44,000) 

88,000

(49,000—130,000)

5.8 μg/m3 (LML 

for Krewski et 

al., 2009) 

63,000

(39,000—87,000)

80,000

(54,000—110,000)

210,000 

(120,000—300,000) 

Policy-Relevant 

Background 110,000 

(68,000—150,000) 

140,000 

(94,000—180,000) 

360,000 

(200,000—500,000) 

Bold indicates that the minimum air quality level used to calculate this estimate corresponds to the 

lowest measured level identified in the epidemiological study

5 

6 In this table, the bold figures indicate the estimate that corresponds with the LML 

7 identified in the epidemiological study. The bold estimates in the column Krewski et al. 

8 (2009) were calculated using the same risk coefficients as the urban case study analysis. 

9 We place a greater emphasis on those results calculated using the LML reported in the 

epidemiological studies.48 10 Figure 3 illustrates the percentage of baseline mortality 

11 attributable to PM2.5 exposure in each of the grid cells according to the 2005 PM2.5 air 

12 quality levels, using the Krewski et al. (2009) estimate based on 1999-2000 air quality 

13 levels. 

14 

15 

16 

 48 Note, that as stated in Section 4.3.2, modeling of risk down to PRB is subject to considerable uncertainty. 

While there is no evidence for a threshold (which conceptually supports estimation of risk below LML), we 

do not have information characterizing the nature of the C-R function for long-term mortality below the 

LML and consequently estimates of mortality based on incremental exposure below LML (and down to 

PRB) is subject to greater uncertainty. 
September 2009 173 Draft – Do Not Quote or Cite 

1 Figure 5-3 Percentage of premature mortality attributable to PM2.5 exposure 

3 at various 2005 annual average PM2.5 levels* 

4 This figure illustrates the number of deaths attributable to PM2.5 according to the 

baseline level of ambient average PM2.5 levels down to 5.8 μg/m3 5 (the LML for the 

6 Krewski et al. (2009) analysis). Each of four box plots characterizes the range of 

7 premature mortality attributable to PM2.5 according to the baseline level of annual mean 

8 PM2.5 levels in that model grid cell. Note that while the lower whisker of the box plots 

for the baseline air quality values of 5.8 μg/m3 to 10 μg/m3 9 appear to extend to zero, the 

10 minimum value is greater than zero. The number above each box plot indicates the 

11 number of grid cells summarized by that plot. 

12 Figure 5-4 displays the cumulative distribution of total mortality attributable to 

13 PM2.5 exposure at the county level developed as part of the national-scale analysis. The 

14 location of the 31 counties included in the urban case study analysis is then superimposed 

15 on top of the cumulative distribution. 

16 

17 

18 

19 

20 
September 2009 174 Draft – Do Not Quote or Cite 

1 Figure 5-4 Cumulative distribution of county-level percentage of total 

2 mortality attributable to PM2.5 for the U.S. with markers 

3 identifying where along that distribution the urban case study area 

5 analysis fall* 

6 

7 Counties considered in the urban scale analysis that are located toward the lower 

8 end of the distribution of all counties nationwide include Maricopa County, Arizona and 

9 Salt Lake City, Utah. Counties assessed in the urban scale analysis that are located 

10 toward the upper end of the distribution of all counties include Jefferson County, 

11 Alabama and Los Angeles County, California. The results of this analysis indicate that 

12 most of the 31 counties included in the urban case study counties fall toward the upper 

end of the national risk distribution and that 23 of these counties fall within the upper 5th 13 

14 percentile of the risk distribution—suggesting that the PM2.5 mortality risk estimates 

15 included in the urban case study analysis generally represent the upper end of urban area 

16 mortality risks within the nation. 
September 2009 175 Draft – Do Not Quote or Cite 

REFERENCES 

Abt Associates Inc, (2003), “Environmental Benefits Mapping and Analysis Program (BenMAP), User’s 

Manual. Available on the Internet at <http://www.epa.gov/ttn/ecas/benmodels.html>. 

Abt Associates Inc. (2005). Particulate Matter Health Risk Assessment for Selected Urban Areas. Prepared 

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

Research Triangle Park, NC. June 2005. Available electronically on the internet at: 

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

Abt Associates Inc. (2008). Environmental Benefits Mapping and Analysis Program (Version 3.0). 

Bethesda, MD. Prepared for Environmental Protection Agency, Office of Air Quality Planning 

and Standards, Air Benefits and Costs Group. Research Triangle Park, NC. 

American Farm Bureau Federation v. EPA, 559 F. 3d 512 (D.C. Cir. 2009). 

Bateson, T.F.; Schwartz, J. (2004). Who is sensitive to the effects of particulate air pollution on mortality? 

A case-crossover analysis of effect modifiers. Epidemiology. 15(2):143-9. 

Bell, M.L.; Ebisu, K.; Peng, R.D.; Walker, J.; Samet, JM; Zeger, S.L.; Dominici, F. (2008). Seasonal and 

regional short-term effects of fine particles on hospital admissions in 202 US counties, 1999-2005. 

Am J Epidemiol. 168(11):1301-1310. 

Bell, M.L.; Dominici, F. (2008). Effect modification by community characteristics on the short-term effects 

of ozone exposure and mortality in 98 US communities. Am J Epidemiol. 167(8):986-97. 

Bell (2009). Personal communication via e-mail between Dr. Michelle Bell and Beth Hasset-Sipple, June 

26th, 2009 (e-mail with attachments placed in docket #EPA-HQ-OAR-2007-0492). 

Bell M.L.; Ebisu K.; Peng R.D.; Samet J.M.; Dominici, F. (2009). Hospital admissions and chemical 

composition of fine particle air pollution. Am J Respir Crit Care Med. 179(12):1115-20. 

Berkey, C.S.; Hoaglin, D.C.; Antczak-Bouckoms, A.; Mosteller, F.; Colditz, G.A. (1998). Meta-analysis of 

multiple outcomes by regression with random effects. Stat Med. 17(22):2537-2550. 

Byun, D., and K.L. Schere, (2006). Review of the Governing Equations, Computational Algorithms, and 

Other Components of the Models-3 Community Multiscale Air Quality (CMAQ) Modeling 

System. Applied Mechanics Reviews, 59, 51-77. 

Dominici, F.; Peng, R.D.; Ebisu, K.; Zeger, S.L.; Samet, J.M.; Bell, M.L. (2007). Does the effect of PM10 

on mortality depend on PM nickel and vanadium content? A reanalysis of the NMMAPS data. 

Environ Health Perspect. 115(12):1701-3. 

Franklin, M.; Zeka, A.; Schwartz, J. (2007). Association between PM2.5 and all-cause and specific-cause 

motrality in 27 US communities. J Expo Sci Environ Epidemiol. 17:279-287. 

Henderson, R. (2005). EPA’s Review of the National Ambient Air Quality Standards for 

Particulate Matter (Second Draft PM Staff Paper, January 2005): A review by the Particulate Matter 

Review Panel of the EPA Clean Air Scientific Advisory Committee. June 6, 2005. Available 

electronically on the internet at: http://www.epa.gov/sab/pdf/casac-05-007.pdf. 
September 2009 176 Draft – Do Not Quote or Cite 

Henderson, R. (2006). Clean Air Scientific Advisory Committee Recommendations Concerning the 

Proposed National Ambient Air Quality Standards for Particulate Matter. March 21, 2006. 

Available electronically on the internet at: http://www.epa.gov/sab/pdf/casac-ltr-06-002.pdf

Henderson, R; Poirot, R.L.; Cowling, E.; Speizer, F.; Crapo, J.D.; Zielinska, B.; Miller, F.J. (2006). Clean 

Air Scientific Advisory Committee Recommendations Concerning the Final National Ambient Air 

Quality Standards for Particulate Matter. September 29, 2006. Available electronically on the 

internet at: http://www.epa.gov/sab/pdf/casac-ltr-06-003.pdf. 

Hopke, P. (2002). Letter from Dr. Phil Hopke, Chair, Clean Air Scientific Advisory Committee (CASAC) 

Particulate Matter Review Panel, to Honorable Christine Todd Whitman, Administrator, U.S. 

EPA. Final advisory review report by the CASAC Particulate Matter Review Panel on the 

proposed particulate matter risk assessment. EPA-SAB-CASAC-ADV-02- 002. May 23. 

Available electronically on the internet at:http://www.epa.gov/sab/pdf/casacadv02002.pdf. 

Hopke, P. (2004). Letter from Dr. Phil Hopke, Clean Air Scientific Advisory Committee 

(CASAC) Particulate Matter (PM) Review Panel, to Honorable Michael O. Leavitt. CASAC PM Review 

Panel’s Ongoing Peer Review of the Agency’s Fourth External Review Draft of Air Quality 

Criteria for Particulate Matter (June 2003); and Peer Review of the Review of the National 

Ambient Air Quality Standards for Particulate Matter: Policy Assessment of Scientific and 

Technical Information (OAQPS Staff Paper - First Draft) (August 2003) and a Related Draft 

Technical Report, Particulate Matter Health Risk Assessment for Selected Urban Areas (Draft 

Report) (August 2003). EPA-SAB-CASAC-04-004. February 18. Available electronically on the 

internet at: http://www.epa.gov/sab/pdf. 

Ito, K.; Thurston, G.; Silverman, R.A. (2007). Characterization of PM2.5 gaseous pollutants and 

meteorological interactions in the context of time-series health effects models. J Expo Sci Environ 

Epidemiol. 17: 45-60. 

Jerrett. M.; Burnett, R.T.; Ma, R.; Pope, C.A. III; Krewski, D.; Newbold, K.B.; Thurston, G.; Shi, Y.; 

Finkelstein, N.; Calle, E.; Thun, M.J. (2005). Spatial analysis of air pollution and mortality in Los 

Angeles. Epidemiology. 6(6): 1-10. 

Kottek, M.; Grieser, J.; Beck, C.; Rudolf, B.; Rubel, F. (2006). World map of the Köppen-Geiger climate 

classification updated. Meteorol Zeit. 15(3): 259-263. 

Kottek, M. (2008). World Map of the Köppen-Geiger climate classification updated.Available: 

http://koeppen-geiger.vu-wien.ac.at/ [accessed 12/5/2008]. 

Krewski (2009). Letter from Dr. Daniel Krewski to HEI’s Dr. Kate Adams (dated July July 7, 2009) 

regarding “EPA queries regarding HEI Report 140”. Dr. Adams then forwarded the letter on July 

10, 2009 to EPA’s Beth Hassett-Sipple. (letter placed in docket #EPA-HQ-OAR-2007-0492). 

Krewski, D.; Burnett, R.T.; Goldberg, M.S.; Hoover, K.; Siemiatycki, J.; Jerrett, M.; Abrahamowicz, M.; 

White, W.H. (2000). Reanalysis of the Harvard Six Cities study and the American Cancer Society 

study of particulate air matter pollution and mortality. HEI Research Report, Health Effects 

Institute, Boston, MA. 

Krewski, D.; Jerrett, M.; Burnett, R.T.; Ma, R.; Hughes, E.; Shi, Y.; Turner, M.C.; Pope, C.A. III; 

Thurston, G.; Calle, E.E.; Thun, M.J. (2009). Extended follow-up and spatial analysis of the 

American Cancer Society study linking particulate air pollution and mortality. HEI Research 

Report, 140, Health Effects Institute, Boston, MA. 
September 2009 177 Draft – Do Not Quote or Cite 

Laden, F., J. Schwartz, F.E. Speizer, and D.W. Dockery. (2006). Reduction in Fine Particulate Air 

Pollution and Mortality. American Journal of Respiratory and Critical Care Medicine 173:667-672 

Le Terte, A.; Schwartz, J.; Touloumi, G. (2005). Empirical bayes and adjusted estimates approach to 

estimating the relation of mortality to exposure of PM10. Risk Anal. 25(3):711-718. 

Medina-Ramón, M.; Zanobetti, A.; Schwartz, J. (2006). The effect of ozone and PM10 on hospital 

admissions for pneumonia and chronic obstructive pulmonary disease: a national multicity study. 

Am J Epidemiol. 163(6):579-88. 

Moolgavkar, S. (2000). Air pollution and hospital admissions for chronic obstructive pulmonary disease in 

three metropolitan areas in the United States. Inhal Toxicol. 12(Supplement 4): 75-90. 

Moolgavkar, S. (2003). Air pollution and daily deaths and hospital admissions in Los Angeles and Cook 

counties. pp. 183-198. In: Health Effects Institute Special Report, Revised Analyses of TimeSeries Studies of Air Pollution and Health. Health Effects Institute, Cambridge, MA. 

Ostro, B.; Broadwin, R.; Green, S.; Feng, W.Y.; Lipsett, M. (2006). Fine particulate air pollution and 

mortality in nine California counties: results from CALFINE. Environ Health Perspect. 114(1):29-

33. 

Pope, C.A. III ; Burnett, R.T. ; Thun, M.J. ; Calle, E.E. ; Krewski, D. ; Ito, K. ; Thurston G.D. (2002). Lung 

cancer, cardiopulmonary mortality, and long-term exposure to fine particulate air pollution. 

JAMA. 287(9):1132-1141. 

Roberts, S. (2004). Interactions between particulate air pollution and temperature in air pollution mortality 

time series studies. Environ Res. 96(3):328-37. 

Samet, J.M. (2008). Air pollution risk estimates: determinants of heterogeneity. J Toxicol Environ Health 

A. 71(9-10):578-82. 

Samet, 2009. Letter from Dr. Jonathan M. Samet, Chair Clean Air Scientific Advisory Committee, to Lisa 

P. Jackson, Administrator U.S. Environmental Protection Agency regarding “Consultation on 

EPA’s Particulate Matter National Ambient Air Quality Standards: Scope and Methods Plan for 

Health Risk and Exposure Assessment.” May, 21, 2009. (letter placed in docket #EPA-HQ-OAR2007-0492). 

Sarnat, S.E.; Coull, B.A.; Schwartz, J.; Gold, D.R.; Suh, H.H. (2006). Factors affecting the association 

between ambient concentrations and personal exposures to particles and gases. Environ Health 

Perspect. 114(5):649-54. 

Schwartz, J. (2000). The distributed lag between air pollution and daily deaths. Epidemiology 11(3):320-

326. 

Tolbert, P.E. (2007). Invited commentary: heterogeneity of particulate matter health risks. Am J Epidemiol. 

166(8):889-91; discussion 892-3. 

Tolbert, P.E.; Klein, M.; Peel, J.L.; Sarnat, S.E.; Sarnat, J.A. (2007). Multipollutant Modeling Issues in a 

Study of Ambient Air Quality and Emergency Department Visits in Atlanta. J Expo Sci Environ 

Epidemiol. 17:S29-S35. 

U.S. Environmental Protection Agency. (1996). Air Quality Criteria for Particulate Matter. National 

Center for Environmental Assessment, Office of Research and Development, U.S. Environmental 

Protection Agency, Research Triangle Park, NC 27711; report no. EPA/600/P-99/002aF and 
September 2009 178 Draft – Do Not Quote or Cite 

EPA/600/P-99/002bF. October 2004. Available: 

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

U.S. Environmental Protection Agency. (2001). Risk assessment guidance for Superfund. Vol. III, Part A. 

Process for conducting probabilistic risk assessment (RAGS 3A). Washington, DC, United States 

Environmental Protection Agency, EPA 540-R-02-002; OSWER 9285.7-45; PB2002 963302; 

http://www.epa.gov/oswer/riskassessment/rags3adt/index.htm. 

US Environmental Protection Agency. (2004a). Air Quality Criteria for Particulate Matter. National Center 

for Environmental Assessment, Office of Research and Development, U.S. Environmental 

Protection Agency, Research Triangle Park, NC 27711; report no. EPA/600/P-99/002aF and 

EPA/600/P-99/002bF. October 2004. Available: 

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

U.S. Environmental Protection Agency. (2004b) EPA’s risk assessment process for air toxics: History and 

overview. In: Air toxics risk assessment reference library. Vol. 1. Technical resource manual.

Washington, DC, United States Environmental Protection Agency, pp. 3-1 – 3-30, EPA-453-K04-001A; http://www.epa.gov/ttn/fera/data/risk/vol_1/chapter_03.pdf. 

U.S. Environmental Protection Agency. (2005). Review of the National Ambient Air Quality Standards for 

Particulate Matter: Policy Assessment of Scientific and Technical Information - OAQPS Staff 

Paper, Office of Air Quality Planning and Standards, Research Triangle Park, NC, EPA-452/R-05-

005. Available: http://www.epa.gov/ttn/naaqs/standards/pm/s_pm_cr_sp.html

U.S. Environmental Protection Agency. (2007). Draft Integrated Review Plan for the National Ambient 

Air Quality Standards for Particulate Matter. U.S. Environmental Protection Agency, Research 

Triangle Park, NC, EPA 452/P-08-006. 

U.S. Environmental Protection Agency. (2008a). Integrated Review Plan for the National Ambient Air 

Quality Standards for Particulate Matter. U.S. Environmental Protection Agency, Research 

Triangle Park, NC, EPA 452/R-08/004. 

U.S. Environmental Protection Agency. (2008b). Integrated Science Assessment for Particulate Matter: 

First External Review Draft. U.S. Environmental Protection Agency, Research Triangle Park, 

NC, EPA/600/R-08/139 and 139A. Available: 

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

U.S. Environmental Protection Agency. (2009a). Integrated Science Assessment for Particulate Matter: 

Second External Review Draft. U.S. Environmental Protection Agency, Research Triangle Park, 

NC, EPA 600/R-08/139B. Available: 

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

U.S. Environmental Protection Agency. (2009b). Particulate Matter National Ambient Air Quality 

Standards: Scope and Methods Plan for Health Risk and Exposure Assessment. U.S. 

Environmental Protection Agency, Research Triangle Park, NC, EPA-452/P-09-002. 

U.S. Environmental Protection Agency. (2009c). Particulate Matter Urban-Focused Visibility Assessment – 

External Review Draft. Office of Air Quality Planning and Standards, U.S. Environmental 

Protection Agency, Research Triangle Park, NC. EPA-452/P-09/005. September 2009. 

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

Woods & Poole Economics Inc. (2001). Population by Single Year of Age CD. CD-ROM. Woods & Poole 

Economics, Inc. Washington, D.C. 
September 2009 179 Draft – Do Not Quote or Cite 

World Health Organization. (2008). Part 1: Guidance Document on Characterizing and Communicating 

Uncertainty in Exposure Assessment, Harmonization Project Document No. 6. Published under 

joint sponsorship of the World Health Organization, the International Labour Organization and the 

United Nations Environment Programme. WHO Press, World Health Organization, 20 Avenue 

Appia, 1211 Geneva 27, Switzerland (tel.: +41 22 791 2476). 

Zanobetti (2009). Shrunken estimates for PM2.5. Personal Communication, June 1, 2009. (e-mail with 

attachments placed in docket #EPA-HQ-OAR-2007-0492). 

Zanobetti, A.; Schwartz, J. (2009). The effect of fine and coarse particulate air pollution on mortality: A 

National Analysis. Environ Health Perspect. 117(6): 898-903. 

Zeka, A.; Zanobetti, A.; Schwartz, J. (2005). Short term effects of particulate matter on cause specific 

mortality: effects of lags and modification by city characteristics. Occup Environ Med. 

62(10):718-25. 
 
APPENDIX A: AIR QUALITY ASSESSMENT 

A-1

September 2009 Draft - Do Not Quote or Cite
1 Appendix A. Air Quality Assessment 

2 

3 

4 

5 

6 

7 

This Appendix describes the PM data for the 15 urban study areas evaluated in the risk 

assessment, including summaries of PM2.5 monitoring data associated with each study area as 

well as the composite monitor estimates generated for each study area based on that monitoring 

data (see section 3.2 for additional detail regarding selection of monitors and derivation of 

composite monitor values). 

A-2

September 2009 Draft - Do Not Quote or Cite
Table A-1. Air Quality Data for Atlanta

 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q

130630091 (3) 27 30 25 30 112 12.63 16.83 21.22 15.9

130670003 (1,2,3) 27 30 29 29 115 13.75 17.39 18.57 15.6130670004 (1,2,3) 30 28 26 27 111 12.98 17.17 18.03 13.9130890002 (1,2,3) 82 84 81 88 335 12.72 15.72 18.81 14.5130892001 (1,2,3) 80 75 67 85 307 12.84 15.10 20.44 14.8131210032 (1,2,3) 84 89 76 80 329 13.64 16.00 19.43 14.3131210039 (1,2,3) 27 30 23 29 109 15.03 18.35 17.97 16.5131210048 (1,2,3) 0 0 0 0 0 --- --- --- -

131350002 (1,3) 13 14 12 14 53 14.35 14.62 20.39 15.1

132230003 (3) 28 29 26 26 109 11.41 15.52 18.62 12.9Composite monitor for Atlanta - 1 90 91 92 92 365 13.30 16.01 19.86 14.6Composite monitor for Atlanta - 2 90 91 92 92 365 13.28 16.05 19.85 14.6Composite monitor for Atlanta - 3 90 91 92 92 365 13.15 15.93 19.95 14.5130630091 (3) 29 29 31 30 119 12.94 17.91 21.32 14.4130670003 (1,2,3) 28 29 31 30 118 12.22 17.88 21.52 14.2130670004 (1,2,3) 28 29 27 28 112 12.09 17.75 21.04 12.3130890002 (1,2,3) 85 86 81 81 333 12.25 16.09 19.86 13.4130892001 (1,2,3) 86 84 77 81 328 11.94 15.75 18.31 12.1131210032 (1,2,3) 88 86 84 90 348 12.46 15.99 19.28 13.7131210039 (1,2,3) 29 28 26 0 83 15.12 19.15 20.88 -131210048 (1,2,3) 0 0 2 30 32 --- --- 15.25 15.0

131350002 (1,3) 12 14 13 15 54 15.21 18.98 20.31 12.9

132230003 (3) 29 27 31 29 116 10.91 15.20 18.90 10.7Composite monitor for Atlanta - 1 90 91 92 92 365 12.30 16.33 19.29 13.2Composite monitor for Atlanta - 2 90 91 92 92 365 12.30 16.33 19.27 13.2Composite monitor for Atlanta - 3 90 91 92 92 365 12.19 16.28 19.38 13.1

Monitor

20062005

Quarterly Counts Quarterly Averages (ug/m3) Annual 

Total

A-3

September 2009 
Table A-1 cont'd. Air Quality Data for Atlanta

 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q

130630091 (3) 29 30 30 29 118 13.87 16.51 18.83 13.0

130670003 (1,2,3) 29 30 29 29 117 13.49 17.03 19.49 13.4130670004 (1,2,3) 26 27 30 30 113 12.50 17.47 18.77 11.3130890002 (1,2,3) 85 83 90 85 343 12.78 15.54 19.38 12.1130892001 (1,2,3) 69 79 76 75 299 12.48 17.11 20.04 12.3131210032 (1,2,3) 87 88 91 85 351 12.99 17.95 19.64 13.0131210039 (1,2,3) 0 0 0 0 0 --- --- --- -

131210048 (1,2,3) 28 28 31 28 115 13.45 18.97 18.24 12.8

131350002 (1,3) 27 27 29 29 112 13.05 14.03 17.97 11.6132230003 (3) 29 30 29 30 118 12.21 17.12 18.95 10.6Composite monitor for Atlanta - 1 90 91 92 92 365 12.60 17.23 19.32 12.3Composite monitor for Atlanta - 2 90 91 92 92 365 12.58 17.34 19.40 12.4Composite monitor for Atlanta - 3 90 91 92 92 365 12.60 17.22 19.29 12.3Note 1: Different definitions of Atlanta include different monitors. The number(s) shown in the parenthesis next to the monitor indicates thincluded. For example, monitor 130630091 is used in Atlanta - 3 only while 130670003 is used for all definitions of Atlanta.Note 2: The information on the composite monitors in this table is based on the composite monitors after missing values have been filled 

2007

Monitor

Quarterly Counts Quarterly Averages (ug/m3) Annual 

Total

A-4

September 2009 
Table A-2. Air Quality Data for Baltimore

 Q1 Q2 Q3 Q4 Q1 Q2 Q3 

240051007 30 28 27 27 112 14.78 11.86 20.66 240053001 75 80 85 92 332 16.09 12.60 18.27 245100006 28 31 27 28 114 15.76 12.47 20.18 245100007 27 27 30 30 114 16.09 12.50 20.05 245100008 24 30 30 29 113 18.85 14.16 20.99 245100035 79 75 78 70 302 17.58 13.59 20.24 245100040 79 81 90 76 326 18.47 14.68 19.40 245100049 26 30 25 27 108 17.72 13.19 20.62 Composite Monitor for Baltimore 90 91 92 92 365 16.76 13.58 19.19 240051007 29 29 28 30 116 12.03 11.37 15.73 240053001 90 85 90 92 357 12.81 11.79 18.51 245100006 27 30 27 30 114 13.20 11.62 16.24 245100007 30 29 29 31 119 12.64 11.59 15.19 245100008 30 28 31 30 119 14.80 13.34 16.88 245100035 74 90 83 82 329 13.31 12.57 19.27 245100040 85 86 87 86 344 13.83 12.58 18.64 245100049 0 0 0 0 0 --- --- --- Composite Monitor for Baltimore 90 91 92 92 365 13.14 12.28 18.41 240051007 29 29 31 30 119 12.09 13.54 15.53 240053001 74 87 83 89 333 12.53 12.95 16.93 245100006 30 29 31 27 117 12.10 12.83 16.28 245100007 29 30 30 28 117 12.07 13.20 15.84 245100008 30 30 31 27 118 13.53 14.68 16.90 245100035 79 85 74 76 314 12.11 14.03 17.23 245100040 82 85 89 76 332 13.42 13.66 16.32 245100049 0 0 0 0 0 --- --- --- Composite Monitor for Baltimore 90 91 92 92 365 12.33 13.39 16.42 Note: The information on the composite monitors in this table is based on the composite monitors after missing values have been 

2007

20052006

Monitor

Quarterly Counts Annual 

Total

Quarterly Averages (ug/m3)

A-5

September 2009 
Table A-3. Air Quality Data for Birmingham

 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4

10730023* 90 90 89 92 361 14.35 20.49 26.42 17.27 10731005* 30 31 29 31 121 11.62 16.70 22.61 14.33 10731009* 30 31 29 31 121 9.82 16.12 20.26 11.87 10731010* 15 15 15 16 61 11.71 16.91 22.77 15.51 10732003* 88 90 91 91 360 14.49 18.48 23.75 15.03 10732006* 30 30 30 31 121 11.53 16.46 21.11 13.79 10735002* 30 31 30 31 122 10.84 16.33 21.08 12.61 10735003* 30 30 30 31 121 10.60 16.42 21.94 12.74 11170006 30 31 30 28 119 11.23 15.67 19.60 12.92 11270002 27 31 28 30 116 10.37 15.31 18.86 12.17 Composite Monitor for Birmingham - 1 90 91 92 92 365 13.25 18.28 23.98 15.50 Composite Monitor for Birmingham - 2 90 91 92 92 365 13.34 18.44 24.19 15.56 10730023* 89 91 92 92 364 13.61 20.57 22.35 17.02 10731005* 30 30 31 31 122 10.51 18.84 19.59 13.38 10731009* 30 29 30 30 119 8.81 17.16 17.78 10.02 10731010* 15 15 15 16 61 11.57 18.63 18.71 12.37 10732003* 89 90 90 92 361 14.41 20.48 21.62 15.67 10732006* 30 30 31 31 122 10.76 18.08 20.02 12.33 10735002* 30 30 31 31 122 9.87 17.15 19.61 10.60 10735003* 29 30 30 30 119 10.37 17.42 18.84 11.31 11170006 30 30 31 31 122 9.95 16.37 18.38 11.65 11270002 29 30 30 29 118 9.85 17.49 17.38 11.83 Composite Monitor for Birmingham - 1 90 91 92 92 365 13.13 19.64 21.07 15.07 Composite Monitor for Birmingham - 2 90 91 92 92 365 13.21 19.75 21.22 15.15 

20052006

Monitor

Quarterly Counts Annual 

Total

Quarterly Averages (ug/m3)

A-6

September 2009 
Table A-3 cont'd. Air Quality Data for Birmingham

 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4

10731010* 15 15 15 15 60 14.53 18.69 19.31 13.63 10732003* 89 90 89 90 358 15.40 21.38 19.18 12.42 10732006* 30 30 31 30 121 12.24 19.29 18.53 10.93 10735002* 30 28 31 30 119 12.15 19.16 18.41 10.40 10735003* 29 30 31 30 120 11.79 18.99 17.83 10.38 11170006 29 30 31 30 120 12.97 18.27 17.52 10.84 11270002 28 29 31 29 117 11.97 17.81 17.72 10.95 Composite Monitor for Birmingham - 1 90 91 92 92 365 14.47 21.23 19.97 12.40 Composite Monitor for Birmingham - 2 90 91 92 92 365 14.52 21.40 20.06 12.45 Note 1: The monitors marked with * are used for Birmingham - 2. All monitors shown in this table are used for Birmingham - 1.Note 2: The information on the composite monitors in this table is based on the composite monitors after missing values have been filled in

2007

Monitor

Quarterly Counts Annual 

Total

Quarterly Averages (ug/m3)

A-7

September 2009 
Table A-4. Air Quality Data for Dallas

 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4

481130035 30 31 20 0 81 11.78 15.16 13.90 --- 481130050 15 30 27 31 103 11.95 15.01 15.64 12.47 481130057 27 21 22 0 70 12.00 16.07 14.41 --- 481130069 78 88 90 91 347 11.07 13.80 14.03 11.11 481130087 27 31 30 30 118 9.87 13.32 13.45 10.18 481133004 88 89 61 0 238 10.86 13.58 12.82 --- Composite Monitor for Dallas 90 91 92 92 365 11.05 13.87 14.07 11.07 481130035 0 0 0 0 0 --- --- --- --- 481130050 28 30 31 31 120 10.99 12.53 12.98 10.68 481130057 0 0 0 0 0 --- --- --- --- 481130069 84 90 92 90 356 9.97 12.15 11.73 9.26 481130087 30 30 30 28 118 9.22 11.66 10.89 8.45 481133004 0 0 0 0 0 --- --- --- --- Composite Monitor for Dallas 90 91 92 92 365 10.05 12.19 11.77 9.27 481130035 0 0 0 0 0 --- --- --- --- 481130050 29 28 30 0 87 11.54 11.76 15.42 --- 481130057 0 0 0 0 0 --- --- --- --- 481130069 88 91 91 79 349 10.13 10.91 13.78 10.14 481130087 28 21 29 30 108 9.96 11.16 12.70 9.30 481133004 0 0 0 0 0 --- --- --- --- Composite Monitor for Dallas 90 91 92 92 365 10.43 11.04 13.91 9.66 Note: The information on the composite monitors in this table is based on the composite monitors after missing values have been filled 

2007

20052006

Monitor

Quarterly Counts Annual 

Total

Quarterly Averages (ug/m3)

A-8

September 2009 
Table A-5. Air Quality Data for Detroit

 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4

261630001 88 87 89 86 350 18.45 13.87 17.15 14.38 261630015 27 27 30 30 114 20.20 14.73 18.73 15.18 261630016 87 79 84 88 338 18.92 14.78 16.62 13.70 261630019 28 31 29 29 117 19.82 14.48 17.43 14.20 261630025 26 28 30 30 114 17.86 11.74 17.45 12.68 261630033 28 31 28 28 115 21.50 16.57 18.22 17.90 261630036 29 28 29 27 113 16.96 14.92 18.58 15.19 261630038 28 25 22 0 75 16.98 14.60 17.66 --- 

261630039 0 0 7 28 35 --- --- 18.20 14.25 

Composite Monitor for Detroit 90 91 92 92 365 18.25 13.86 16.58 13.87 261630001 82 85 88 90 345 13.66 11.89 13.68 13.65 261630015 29 26 28 31 114 16.98 12.26 14.93 14.56 261630016 79 14 13 17 123 13.04 11.58 12.58 14.97 261630019 30 15 14 16 75 15.20 10.39 11.78 13.46 261630025 27 14 15 17 73 13.49 11.23 10.01 12.70 261630033 28 29 27 31 115 18.79 12.85 15.56 17.30 261630036 29 26 29 29 113 15.10 10.95 13.69 11.94 261630038 0 29 27 28 84 --- 11.10 14.34 11.98 

261630039 29 30 31 30 120 14.78 11.71 14.20 11.84 Composite Monitor for Detroit 90 91 92 92 365 13.61 11.85 13.69 13.67 261630001 86 89 87 92 354 12.92 10.28 14.00 14.08 261630015 28 30 27 29 114 15.15 13.06 15.12 14.82 261630016 26 26 30 29 111 13.98 12.12 14.74 14.61 261630019 30 28 31 27 116 13.20 11.16 14.36 13.31 261630025 26 30 31 27 114 12.23 10.59 13.76 14.42 261630033 29 29 29 27 114 18.84 15.20 16.02 17.49 261630036 29 28 30 29 116 13.75 11.96 14.60 13.47 261630038 27 27 28 30 112 13.63 12.85 15.35 14.23 261630039 29 30 30 28 117 13.83 12.98 14.65 13.86 Composite Monitor for Detroit 90 91 92 92 365 13.00 10.28 13.78 14.00 Note: The information on the composite monitors in this table is based on the composite monitors after missing values have been filled 

2007

20052006

Monitor

Quarterly Counts Annual 

Total

Quarterly Averages (ug/m3)

A-9

September 2009 
Table A-6. Air Quality Data for Fresno

 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4

60190008 85 78 89 91 343 19.53 7.19 11.42 28.65 60195001 30 15 15 22 82 17.11 7.55 10.78 29.95 60195025 30 15 13 31 89 20.24 8.29 11.24 27.92 Composite Monitor for Fresno 90 91 92 92 365 18.97 7.24 11.34 28.07 60190008 89 87 87 85 348 21.82 9.10 12.39 23.85 60195001 30 15 14 29 88 18.38 9.47 12.99 24.96 60195025 30 15 12 31 88 20.13 9.81 13.66 26.87 Composite Monitor for Fresno 90 91 92 92 365 21.04 9.27 12.49 24.95 60190008 87 90 88 91 356 27.61 8.32 10.70 28.71 60195001 29 13 14 27 83 23.70 7.16 9.91 24.91 60195025 29 14 15 30 88 24.91 8.73 9.65 24.10 Composite Monitor for Fresno 90 91 92 92 365 26.39 8.37 10.41 27.80 Note: The information on the composite monitors in this table is based on the composite monitors after missing values have been filled in

20062007

A

2005

Monitor

Quarterly Counts Annual 

Total

Quarterly Averages (ug/m3)

A-10

September 2009 
Table A-7. Air Quality Data for Houston

 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4

482010024 26 31 22 15 94 11.77 14.39 17.17 11.83 482010026 23 31 20 0 74 10.47 13.10 14.47 --- 482010055 25 28 19 0 72 9.12 12.31 12.97 --- 482010058 20 28 23 26 97 11.95 12.99 14.40 12.19 482011034 10 15 10 0 35 11.79 15.36 14.49 --- 482011035 84 68 78 87 317 13.09 16.59 18.41 15.47 Composite Monitor for Houston 90 91 92 92 365 12.25 14.97 17.69 14.90 482010024 15 13 13 13 54 10.92 11.66 15.97 12.58 482010026 0 0 0 0 0 --- --- --- --- 482010055 0 0 0 0 0 --- --- --- --- 482010058 26 29 29 29 113 9.74 12.34 9.04 9.82 482011034 0 0 0 0 0 --- --- --- --- 482011035 85 87 88 88 348 13.98 18.15 17.38 14.48 Composite Monitor for Houston 90 91 92 92 365 13.65 17.32 16.15 13.56 482010024 15 14 13 0 42 11.01 12.82 14.64 --- 482010026 0 0 0 0 0 --- --- --- --- 482010055 0 0 0 0 0 --- --- --- --- 482010058 26 30 30 30 116 9.40 10.96 11.84 11.75 482011034 0 0 0 0 0 --- --- --- --- 482011035 87 91 91 82 351 14.42 17.02 16.62 14.50 Composite Monitor for Houston 90 91 92 92 365 13.59 15.87 15.95 13.79 Note: The information on the composite monitors in this table is based on the composite monitors after missing values have been filled in.

2007

20052006

Monitor

Quarterly Counts Annual 

Total

Quarterly Averages (ug/m3)

A-11

September 2009 
Table A-8. Air Quality Data for Los Angeles

 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4

60370002 65 78 87 62 292 11.37 13.97 20.71 21.78 60371002 29 25 30 22 106 17.01 13.75 18.55 21.95 60371103 90 84 87 89 350 15.26 13.78 19.62 22.48 60371201 25 29 28 22 104 12.27 11.97 15.01 16.18 60371301 29 26 28 31 114 16.68 13.28 18.15 21.75 60371602 29 9 9 29 76 16.90 11.63 17.13 22.31 60372005 30 26 26 31 113 12.98 12.95 17.15 17.28 60374002 87 82 88 67 324 13.39 11.54 16.21 22.56 60374004 90 84 87 83 344 12.64 10.83 15.63 19.59 60379033 28 30 27 18 103 8.18 8.27 9.96 9.00 Composite Monitor for Los Angeles 90 91 92 92 365 13.24 12.20 17.68 20.44 60370002 66 73 84 55 278 12.62 16.17 16.95 15.87 60371002 25 24 30 25 104 15.33 18.34 15.87 16.66 60371103 89 82 85 74 330 14.49 14.69 16.34 16.80 60371201 20 27 28 17 92 11.19 14.21 12.95 13.00 60371301 28 28 27 24 107 17.62 14.76 15.11 19.26 60371602 29 28 31 28 116 16.82 13.92 17.19 18.57 60372005 29 27 28 29 113 12.85 14.64 13.46 12.51 60374002 73 81 73 63 290 15.19 12.27 13.53 15.57 60374004 89 86 79 66 320 14.35 11.99 14.21 17.22 60379033 15 15 14 14 58 6.13 7.27 8.36 8.00 Composite Monitor for Los Angeles 90 91 92 92 365 13.72 13.56 15.52 16.32 

 

A

(

20052006

Monitor

Quarterly Counts Annual 

Total

Quarterly Averages (ug/m3)

A-12

September 2009 
Table A-8 cont'd. Air Quality Data for Los Angeles

 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4

60370002 64 77 74 77 292 13.57 17.11 14.68 17.47 60371002 23 26 27 22 98 13.64 15.96 15.36 22.47 60371103 67 83 90 84 324 16.25 16.05 14.62 20.19 60371201 22 26 28 19 95 9.50 13.24 12.55 17.72 60371301 25 27 29 25 106 16.98 14.05 13.00 19.99 60371602 27 27 21 26 101 16.75 14.01 15.18 20.45 60372005 28 23 30 27 108 12.62 15.60 14.02 15.24 60374002 76 86 88 82 332 15.45 12.42 11.50 19.04 60374004 65 81 90 90 326 13.84 12.26 11.30 17.31 60379033 15 15 15 15 60 6.73 7.67 9.00 8.67 Composite Monitor for Los Angeles 90 91 92 92 365 14.33 14.37 13.01 17.99 Note: The information on the composite monitors in this table is based on the composite monitors after missing values have been filled 

2007

 

A

(

Monitor

Quarterly Counts Annual 

Total

Quarterly Averages (ug/m3)

A-13

September 2009 
Table A-9. Air Quality Data for New York

 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4

360050080 28 31 29 27 115 18.59 14.78 18.42 15.68 360050083 30 31 30 31 122 13.77 12.21 16.90 12.71 360050110 90 91 91 91 363 14.93 12.17 15.38 12.30 360470122 28 30 28 27 113 16.04 13.74 17.31 14.13 360610056* 30 31 30 31 122 18.44 15.51 19.16 15.17 360610062* 27 31 30 31 119 17.14 13.84 18.34 13.54 360610079* 30 31 30 31 122 14.60 13.12 17.03 12.56 360610128* 25 31 30 31 117 17.74 14.11 18.37 15.21 360610134* 0 0 0 0 0 --- --- --- --- 360810124 89 79 62 74 304 13.02 10.44 15.21 10.84 360850055 28 25 28 27 108 14.92 12.49 17.81 12.91 360850067 24 28 28 30 110 12.60 10.75 16.17 10.41 Composite Monitor for New York City - 1 90 91 92 92 365 14.46 11.94 15.44 12.29 Composite Monitor for New York City - 2 90 91 92 92 365 16.89 14.02 18.11 14.20 360050080 29 30 27 29 115 16.57 13.17 13.95 11.88 360050083 30 30 29 29 118 13.44 11.06 13.34 10.33 360050110 86 91 84 86 347 13.10 11.15 14.49 11.40 360470122 28 30 29 25 112 15.00 12.49 14.75 9.00 360610056* 30 30 27 30 117 16.61 14.03 14.41 12.59 360610062* 30 28 28 27 113 14.33 13.00 13.82 9.86 360610079* 30 30 31 29 120 14.12 12.08 13.32 10.59 360610128* 26 30 29 29 114 15.79 13.07 14.39 12.64 360610134* 0 0 0 0 0 --- --- --- --- 360810124 69 86 84 76 315 11.17 10.67 13.68 10.91 360850055 25 27 29 29 110 12.27 12.07 14.06 10.56 360850067 30 26 31 29 116 10.01 10.49 12.60 8.54 Composite Monitor for New York City - 1 90 91 92 92 365 12.67 11.11 14.33 11.45 Composite Monitor for New York City - 2 90 91 92 92 365 15.09 13.22 14.00 11.70 

20052006

Monitor

Quarterly Counts Annual 

Total

Quarterly Averages (ug/m3)

A-14

September 2009 
Table A-9 cont'd. Air Quality Data for New York

 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4

360050080 30 30 30 29 119 17.45 13.49 16.20 15.43 360050083 30 30 30 29 119 14.14 11.72 13.91 12.87 360050110 89 84 85 91 349 12.90 11.64 14.22 12.31 360470122 29 30 28 30 117 13.67 12.82 15.92 13.00 360610056* 30 27 31 30 118 18.43 14.73 15.99 15.29 360610062* 27 0 0 0 27 15.84 --- --- --- 360610079* 30 30 31 30 121 14.11 12.48 14.92 12.89 360610128* 30 30 29 21 110 19.10 13.83 14.63 14.76 360610134* 3 30 31 30 94 8.53 14.12 16.43 14.08 360810124 74 86 80 92 332 11.34 10.66 12.30 11.35 360850055 30 28 31 30 119 13.04 12.37 14.55 11.91 360850067 27 30 26 26 109 10.60 10.49 14.29 10.54 Composite Monitor for New York City - 1 90 91 92 92 365 12.70 11.26 13.64 12.22 Composite Monitor for New York City - 2 90 91 92 92 365 16.77 13.55 15.67 14.10 Note 1: The monitors marked with * are used for New York City - 2. All monitors in the table are used for New York City - 1.Note 2: The information on the composite monitors in this table is based on the composite monitors after missing values have been filled 

2007

Monitor

Quarterly Counts Annual 

Total

Quarterly Averages (ug/m3)

A-15

September 2009 
Table A-10. Air Quality Data for Philadelphia

 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4

421010003 0 0 0 62 62 --- --- --- 14.35 421010004 55 61 78 74 268 13.23 13.06 17.26 13.28 421010020 19 0 0 0 19 15.51 --- --- --- 421010024 37 54 67 71 229 12.68 10.76 16.26 12.02 421010047 19 28 26 12 85 16.99 12.04 18.91 12.31 421010057 0 0 0 0 0 --- --- --- --- 421010136 86 89 29 33 237 13.57 11.40 19.06 12.91 Composite Monitor for Philadelphia 90 91 92 92 365 14.09 11.81 16.76 12.33 421010003 85 26 0 0 111 12.21 8.74 --- --- 421010004 81 70 53 84 288 12.74 11.85 17.23 12.41 421010020 0 0 0 0 0 --- --- --- --- 421010024 34 70 71 80 255 11.52 10.56 16.17 11.34 421010047 40 67 45 47 199 14.44 14.57 18.04 15.04 421010057 0 0 0 0 0 --- --- --- --- 421010136 47 50 79 73 249 11.97 12.06 16.29 12.25 Composite Monitor for Philadelphia 90 91 92 92 365 12.35 12.32 16.95 12.76 421010003 0 0 0 0 0 --- --- --- --- 421010004 87 71 86 90 334 13.61 13.19 15.15 12.96 421010020 0 0 0 0 0 --- --- --- --- 421010024 87 58 86 90 321 12.05 12.76 14.88 11.73 421010047 71 59 90 92 312 14.49 13.05 16.33 13.43 421010057 0 0 18 90 108 --- --- 10.96 13.13 421010136 75 65 72 82 294 12.60 13.38 14.36 12.99 Composite Monitor for Philadelphia 90 91 92 92 365 12.98 12.93 15.32 12.82 Note: The information on the composite monitors in this table is based on the composite monitors after missing values have been filled in.

2007

20052006

Monitor

Quarterly Counts Annual 

Total

Quarterly Averages (ug/m3)

A-16

September 2009 
Table A-11. Air Quality Data for Phoenix

 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4

40130019 32 32 30 31 125 11.04 10.78 11.11 18.37 40131003 0 22 30 29 81 --- 8.77 8.26 9.72 40134003 29 31 27 31 118 10.94 13.04 10.40 16.98 40137020 0 30 29 31 90 --- 8.08 7.72 9.46 40139997 29 31 30 31 121 9.04 8.69 7.58 13.56 Composite Monitor for Phoenix 90 91 92 92 365 9.69 10.00 9.03 13.82 40130019 30 30 31 31 122 14.17 13.58 8.07 17.82 40131003 26 28 31 31 116 8.87 9.52 8.92 11.33 40134003 28 28 31 29 116 13.53 10.34 9.31 17.58 40137020 29 30 31 30 120 8.09 7.98 7.14 9.12 40139997 29 29 30 30 118 10.74 8.66 7.46 14.04 Composite Monitor for Phoenix 90 91 92 92 365 11.38 10.03 8.28 13.92 40130019 32 30 31 30 123 10.26 8.85 8.63 15.42 40131003 29 28 30 30 117 7.66 10.45 9.50 11.27 40134003 30 29 30 29 118 10.54 11.76 11.32 15.45 40137020 30 30 31 20 111 5.85 7.81 7.35 8.21 40139997 30 29 32 30 121 8.85 8.12 8.21 12.75 Composite Monitor for Phoenix 90 91 92 92 365 8.95 9.30 9.01 13.05 Note: The information on the composite monitors in this table is based on the composite monitors after missing values have been filled in.

2007

A

20052006

Monitor

Quarterly Counts Annual 

Total

Quarterly Averages (ug/m3)

A-17

September 2009 
Table A-12. Air Quality Data for Pittsburgh

 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4

420030008 89 90 92 89 360 13.80 15.29 20.72 13.40 420030021 28 27 30 27 112 12.91 14.99 22.00 11.49 420030064 88 90 92 86 356 16.28 22.26 25.94 21.10 420030067 26 28 29 27 110 12.32 13.95 20.35 10.26 420030093 13 11 12 13 49 10.66 13.83 23.66 9.63 420030095 14 13 14 15 56 12.79 14.49 21.55 9.83 420030116 23 29 28 26 106 13.82 16.42 21.68 12.66 420030133 14 13 13 9 49 13.54 12.62 20.51 9.51 420031008 30 29 30 29 118 12.79 15.60 21.90 13.52 420031301 29 29 29 26 113 14.39 16.86 23.90 13.37 420033007 15 13 14 15 57 14.13 14.25 24.36 12.71 420039002 13 13 14 15 55 12.95 14.01 21.32 11.25 Composite Monitor for Pittsburgh 90 91 92 92 365 14.68 17.81 22.54 15.91 420030008 85 89 91 92 357 11.60 13.28 20.19 12.54 420030021 0 0 0 0 0 --- --- --- --- 420030064 85 90 87 89 351 14.86 17.89 22.78 20.97 420030067 23 26 28 21 98 9.61 9.52 16.39 9.06 420030093 14 6 13 13 46 10.37 9.85 16.38 9.41 420030095 13 13 13 14 53 10.02 10.97 18.22 10.31 420030116 0 0 0 0 0 --- --- --- --- 420030133 0 0 0 0 0 --- --- --- --- 420031008 27 23 28 25 103 11.87 14.30 18.32 11.63 420031301 26 28 29 29 112 12.56 14.55 19.89 13.11 420033007 15 15 14 15 59 12.93 13.51 19.16 12.36 420039002 0 0 0 0 0 --- --- --- --- Composite Monitor for Pittsburgh 90 91 92 92 365 12.54 15.10 21.11 15.93 

20052006

Monitor

Quarterly Counts Annual 

Total

Quarterly Averages (ug/m3)

A-18

September 2009 
Table A-12. Air Quality Data for Pittsburgh

 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4

420030008 85 86 86 89 346 11.80 14.72 20.30 12.74 420030021 0 0 0 0 0 --- --- --- --- 420030064 88 90 91 90 359 14.16 18.64 25.16 17.57 420030067 19 25 28 26 98 10.28 13.40 19.46 10.73 420030093 15 12 14 14 55 9.67 10.50 19.35 12.57 420030095 14 13 15 14 56 10.96 9.89 20.79 12.90 420030116 0 0 0 0 0 --- --- --- --- 

2007

Monitor

Quarterly Counts Annual 

Total

Quarterly Averages (ug/m3)

420030133 0 0 0 0 0 --- --- --- --- 

420031008 27 27 30 27 111 12.79 14.55 19.68 13.23 420031301 28 27 31 26 112 14.02 15.18 21.90 15.16 420033007 14 14 14 13 55 12.36 13.03 21.19 13.85 420039002 0 0 0 0 0 --- --- --- --- 

Composite Monitor for Pittsburgh 90 91 92 92 365 12.36 16.25 22.33 14.49 Note: The information on the composite monitors in this table is based on the composite monitors after missing values have been filled in.

A-19

September 2009 
Table A-13. Air Quality Data for Salt Lake City

 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4

490350003 30 29 30 31 120 14.16 6.58 8.98 14.49 490350012 82 89 85 85 341 16.73 9.59 12.68 17.24 490351001 29 30 28 30 117 11.85 5.47 8.61 11.35 490353006 88 90 90 85 353 13.95 6.27 9.56 14.17 490353007 28 27 29 28 112 13.64 7.40 10.57 16.36 490353008 30 31 24 31 116 9.90 6.03 7.76 7.45 490353010 0 0 0 0 0 --- --- --- --- Composite Monitor for Salt Lake City 90 91 92 92 365 14.77 7.43 10.47 14.93 490350003 28 28 29 30 115 10.76 6.98 9.41 13.58 490350012 76 87 82 90 335 11.80 11.22 14.19 14.91 490351001 27 28 29 27 111 7.95 5.65 8.65 9.29 490353006 88 90 90 88 356 10.59 7.21 8.54 12.37 490353007 30 30 31 29 120 10.11 7.18 11.56 13.61 490353008 29 26 30 30 115 6.14 6.85 9.26 7.09 490353010 0 0 0 0 0 --- --- --- --- Composite Monitor for Salt Lake City 90 91 92 92 365 10.54 8.60 10.80 12.72 490350003 30 30 29 28 117 18.12 6.97 10.99 13.89 490350012 80 86 0 0 166 20.84 11.45 --- --- 490351001 24 30 31 26 111 11.42 6.44 10.08 9.71 490353006 89 85 78 89 341 18.17 6.11 9.42 12.05 490353007 29 29 29 31 118 17.72 7.17 11.53 13.42 490353008 23 28 28 30 109 10.03 6.06 9.66 7.09 490353010 0 80 83 92 255 --- 7.68 11.62 13.00 Composite Monitor for Salt Lake City 90 91 92 92 365 18.77 8.06 10.72 12.35 Note: The information on the composite monitors in this table is based on the composite monitors after missing values have been filled in.

2007

20052006

Monitor

Quarterly Counts Annual 

Total

Quarterly Averages (ug/m3)

A-20

September 2009 
Table A-14. Air Quality Data for St. Louis

 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4

171190023* 28 28 29 29 114 18.01 19.10 21.49 16.95 171190024* 0 0 0 0 0 --- --- --- --- 171191007* 26 31 29 30 116 18.40 16.49 21.47 16.27 171192009* 12 12 13 12 49 14.94 16.35 20.82 11.98 171193007* 29 31 27 29 116 16.42 15.20 19.99 12.49 171630010* 13 15 14 15 57 17.31 16.81 19.97 14.47 171634001* 30 30 29 28 117 17.86 14.17 17.20 14.69 290990012 90 87 90 91 358 15.22 14.69 19.26 12.42 291890004* 29 29 28 31 117 16.01 12.64 17.80 11.87 291892003* 57 30 29 31 147 16.73 14.15 18.44 12.65 295100007* 88 88 83 81 340 16.99 14.67 18.92 12.87 295100085* 90 86 78 88 342 16.78 14.46 19.67 13.33 295100086* 84 26 30 29 169 15.11 14.34 18.43 13.14 295100087* 90 87 82 81 340 17.02 14.80 18.74 12.94 295100093* 0 0 0 0 0 --- --- --- --- Composite Monitor for St Louis - 1 90 91 92 92 365 16.24 14.64 19.17 12.97 Composite Monitor for St Louis - 2 90 91 92 92 365 16.44 14.59 18.95 13.10 171190023* 30 26 31 29 116 15.21 17.34 19.40 12.11 171190024* 0 0 0 0 0 --- --- --- --- 171191007* 27 24 24 27 102 14.95 16.12 20.18 14.05 171192009* 15 15 14 16 60 12.59 13.35 13.49 12.92 171193007* 28 30 31 31 120 13.08 12.00 16.47 10.87 171630010* 12 14 15 14 55 14.18 13.75 15.72 14.48 171634001* 28 28 31 29 116 13.43 12.87 15.20 12.00 290990012 82 81 91 89 343 11.62 11.79 15.46 11.49 291890004* 30 29 0 0 59 10.56 10.49 --- --- 291892003* 29 29 28 26 112 11.36 10.69 13.87 11.00 295100007* 78 88 91 90 347 12.27 11.82 15.89 12.51 295100085* 86 77 84 92 339 13.04 12.46 15.26 12.68 295100086* 30 30 31 29 120 11.94 11.55 15.48 10.90 295100087* 85 90 86 91 352 12.92 12.32 16.17 13.18 295100093* 0 0 0 0 0 --- --- --- --- Composite Monitor for St Louis - 1 90 91 92 92 365 12.77 12.21 16.20 12.56 Composite Monitor for St Louis - 2 90 91 92 92 365 12.97 12.27 16.28 12.82 

20052006

Monitor

Quarterly Counts Annual 

Total

Quarterly Averages (ug/m3)

A-21

September 2009 
Table A-14 cont'd. Air Quality Data for St. Louis

 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4

171190023* 0 0 0 0 0 --- --- --- --- 171190024* 0 0 6 29 35 --- --- 15.07 14.94 

171191007* 29 27 29 26 111 14.28 15.31 17.61 13.23 171192009* 15 12 14 13 54 14.31 16.02 15.66 13.51 171193007* 29 28 26 30 113 12.42 14.84 17.39 12.32 171630010* 13 13 14 14 54 14.94 17.65 15.94 13.79 171634001* 26 30 31 29 116 13.35 13.95 14.83 10.90 290990012 82 81 90 86 339 11.94 14.44 16.23 12.13 291890004* 0 0 0 0 0 --- --- --- --- 291892003* 89 90 91 90 360 11.63 12.96 15.25 12.49 295100007* 88 91 91 92 362 12.56 14.50 16.13 12.97 295100085* 90 88 89 90 357 12.59 13.79 16.09 13.30 295100086* 27 30 0 0 57 11.79 14.50 --- --- 

295100087* 90 86 92 86 354 13.24 14.43 16.61 13.10 295100093* 0 0 24 29 53 --- --- 17.26 13.82 

Composite Monitor for St Louis - 1 90 91 92 92 365 12.42 14.15 16.22 12.96 Composite Monitor for St Louis - 2 90 91 92 92 365 12.58 14.13 16.14 13.09 Note 1: The monitors marked with * are used for St Louis - 2. All monitors shown in the table are used for St Louis - 1.Note 2: The information on the composite monitors in this table is based on the composite monitors after missing values have been filled in.

2007

Monitor

Quarterly Counts Annual 

Total

Quarterly Averages (ug/m3)

A-22

September 2009 
Table A-15. Air Quality Data for Tacoma

 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4

530530029 29 30 30 31 120 16.46 5.34 7.13 17.07 Composite Monitor for Tacoma 90 91 92 92 365 16.01 5.38 7.07 17.21 530530029 30 30 31 26 117 8.92 5.89 7.45 15.93 Composite Monitor for Tacoma 90 91 92 92 365 8.91 5.94 7.40 15.13 530530029 29 28 31 29 117 13.76 5.94 5.23 13.76 Composite Monitor for Tacoma 90 91 92 92 365 14.74 6.00 5.25 13.47 Note: The information on the composite monitors in this table is based on the composite monitors after missing values have been filled in.

2007

20052006

Monitor

Quarterly Counts Annual 

Total

Quarterly Averages (ug/m3)

A-23

September 2009 
APPENDIX B: HYBRID (NON-PROPORTIONAL) ROLLBACK

APPROACH 

B-1

September 2009 Draft - Do Not Quote or Cite
Appendix B. Methodology for Rolling Back PM2.5 Concentrations Due to Local 

Source Impacts (hybrid non-proportional approach) 

1 

2 

3 

4 

5 

6 

7 

8 

9 

10 

11 

12 

13 

14 

15 

16 

17 

18 

19 

20 

21 

22 

23 

24 

25 

26 

27 

 

During the last review of the Particulate Matter National Ambient Air Quality Standards 

(NAAQS), a technique was employed to simulate fine particulate concentrations under a series 

of attainment scenarios to determine the risk associated with each. The “rolling back” of the 

concentrations consisted of simply using a proportional rollback calculation where every 

measured concentration value was multiplied by a constant to obtain a set of concentrations 

which would meet alternative standard levels. This technique was reviewed by the Clean Air 

Scientific Advisory Committee (CASAC) and was considered to be a satisfactory way to 

simulating alternative PM2.5 distributions. The rolled back values, however, only constituted a 

regional reduction in PM concentrations without accounting for in any way emission reductions 

at local point sources. 

For the current review, an alternative rollback approach reflecting the combined effect of 

both local and regional reduction strategies was considered (this alternative approach is referred 

to as the hybrid non-proportional approach in the risk assessment). In addition to utilizing a 

traditional proportional rollback to represent the regional PM reductions, a distance weighted 

rollback was conducted on a subset of the 15 study areas which contain source oriented monitors 

measuring concentrations higher than those observed at other sites within a particular area.1

Unique sites with high design values exceeding the NAAQS were further investigated to 

determine if they were in close proximity to a large source of PM2.5 (Figure 1). The presence of 

possible source oriented sites in each area was visually determined using satellite photographs 

provided by Google Earth. Areas where source oriented adjustments were made include Detroit 

MI, Pittsburgh PA, St. Louis MO-IL, Baltimore MD, New York NY, Los Angeles CA and 

Birmingham AL. 

1

 In the risk assessment, as outlined in Section 3.1, the proportional rollback approach was used in 

generating the core risk estimates, while the hybrid non-proportional approach described here, was considered as 

part of the sensitivity analysis. 

B-2

September 2009 Draft - Do Not Quote or Cite
1 

2 

3 

4 

5 

6 

7 

8 

9 

10 

Figure B-1. Example of a PM2.5 source oriented monitoring site 

For those sites that were within proximity to a large emitter, the site’s measured 

concentrations were reduced using a proportional rollback depending on the magnitude of the 

reduction needed to either the highest 24-hour or annual design value of a non-source oriented 

site within the area whose design values were close to those of the source oriented site (Figure 

2). 

B-3

September 2009 Draft - Do Not Quote or Cite
1 

2 

3 

4 

5 

6 

7 

8 

9 

10 

11 

12 

13 

14 

15 

Figure B-2. Plot of the 24-hour versus the annual average PM2.5 design values for 

 individual sites in Detroit MI 

The fractional reduction made to the site near the point source was then weighted by the 

inverse distance in kilometers between the source oriented site and all of the other individual 

sites in the area to determine their fractional reductions in relation to the source oriented site. If 

more than one source oriented site was reduced, a distance weighted average fractional reduction 

was calculated and implemented across the non-source oriented sites. Sites within one kilometer 

of the source oriented site received the same amount of reduction as the source oriented site. An 

example of the effect of this reduction technique for Detroit is presented in Table I. For Detroit, 

adjustments were based on the difference between the two sites’ annual design values. 

Table B-1. Comparison of the original and adjusted design values for Detroit, MI 

Site ID 

Original 

Annual Design 

Value (2005-

2007) 

Adjusted 

Annual Design 

Value (2005-

2007) 

Original 

24-hour Design 

Value (2005-

2007) 

Adjusted 

24-hour Design 

Value (2005-

2007) 

260490021 11.6 11.5 29 29 

260990009 12.5 12.4 35 35 

261150005 13.8 13.7 38 38 

261250001 13.6 13.5 40 40 

B-4

September 2009 Draft - Do Not Quote or Cite
B-5

Site ID 

Original 

Annual Design 

Value (2005-

2007) 

Adjusted 

Annual Design 

Value (2005-

2007) 

Original 

24-hour Design 

Value (2005-

2007) 

Adjusted 

24-hour Design 

Value (2005-

2007) 

261470005 13.2 13.1 41 40 

261610005 13.2 13.1 39 39 

261610008 13.7 13.6 39 39 

261630001 14 13.9 36 36 

261630015 15.5 15.2 40 39 

261630016 14.3 14.2 41 41 

261630019 14.1 14 40 40 

261630025 13.2 13.1 34 34 

261630033 17.2 15.4 43 39 

261630036 14.3 14.2 36 36 

261630038 14.3 14.1 40 39 

261630039 14.4 14.3 37 37 

Site in blue represents source oriented site 

Site in red represents reference site used for reduction 

1 

2 

3 

4 

5 

6 

7 

8 

9 

10 

11 

Reduction of the concentrations of the source oriented site reduced either the 24-hour or 

annual design value of the site to either the maximum non-source oriented site’s 24-hour or 

annual design value. This did not necessarily mean that the adjusted values at the source 

oriented site met either the 24-hour or annual standard after the reduction. Since, the adjusted 

design values were calculated using the same data handling rules as contained within 40 CFR 

Part 50 Appendix N, truncation or rounding of the adjusted concentrations could sometimes give 

adjusted design values at the source oriented site that were not exactly the same value as the 

original design value at the reference site. However, they were usually within 1 ug/m3

 for the 

24-hour standard and a few tenths of a microgram per cubic meter for the annual standard.

September 2009 Draft - Do Not Quote or Cite
APPENDIX C: EPIDEMIOLOGY STUDY-SPECIFIC 

INFORMATION FOR PM RISK ASSESSMENT 

C-1

September 2009 Draft - Do Not Quote or Cite
1 Appendix C. Epidemiology Study-Specific Information for PM2.5 Risk Assessment 

2 

3 

4 

5 

6 

This Appendix provides detailed summary information for the epidemiological studies 

used to obtain the concentration-response (C-R) functions used in the risk assessment. For 

additional details on selection of epidemiological studies and specification of the C-R functions, 

see section 3.3.3. 

C-2

September 2009 Draft - Do Not Quote or Cite
Table C-1. Information about the Concentration-Response Functions Used in the PM2.5 Risk Assessment: All-Year Functions

Study Health Endpoint ICD-9 or 10 Codes Ages Covered Model Other Pollutants in Model Lag Metric Region Covered 

Mortality, all-cause All 

Mortality, 

cardiopulmonary 401-440, 460-519 

Mortality, ischemic 

heart disease 410-414 

Mortality, lung cancer 162 

Mortality, all-cause All 

Mortality, 

cardiopulmonary 401-440, 460-519 

Mortality, ischemic 

heart disease 410-414 

Mortality, lung cancer 162 

Mortality, all-cause All 

Mortality, ischemic 

heart disease 410-414 

Mortality, all-cause All 

Mortality, 

cardiopulmonary 401-440, 460-519 

Mortality, ischemic 

heart disease 410-414 

Mortality, lung cancer 162 

Mortality, all-cause All Six U.S. Cities 

Mortality, 

cardiopulmonary 400-440, 485-495 

Mortality, lung cancer 162 

Krewski et al. (2009) - exposure period 1979-1983Krewski et al. (2009) - exposure period 1999-2000Krewski et al. (2000) [reanalysis of Six Cities Study]

none

log-linear National

National

30+ none n/a annual mean

30+ log-linear none annual mean30+ log-linear (random effects) none n/a annual mean

n/a

annual mean

25+ log-linear none n/a annual mean30+ log-log n/a

 Health Effects Associated with Long-Term Exposure to PM 2.5 :

C-3

September 2009 
Table C-1 cont'd. Information about the Concentration-Response Functions Used in the PM2.5 Risk Assessment: All-Year Functions

Study Health Endpoint ICD-9 or 10 Codes Ages Covered Model Other Pollutants in Model Lag Metric Region Covered 

Northeast 

Northwest 

Southeast 

Southwest 

Northeast 

Northwest 

Southeast 

Southwest 

Ito et al. (2007) ER visits, asthma 493 all ages log-linear none avg of 0- and 1-day 24-hr avg. New York 

log-linear, GAM 

(stringent), 30 df 

log-linear, GAM 

(stringent), 100 df 

log-linear, GLM, 

100 df 

log-linear, GAM 

(stringent), 100 df 

log-linear, GLM, 

100 df 

log-linear, GAM 

(stringent), 30 df 

log-linear, GAM 

(stringent), 100 df 

log-linear, GLM, 

100 df 

log-linear, GAM 

(stringent), 100 df 

log-linear, GLM, 

100 df 

Los Angeles

 Health Effects Associated with Short-Term Exposure to PM 2.5 :

0-day2-day

24-hr avg.24-hr avg.

65+65+

log-linearlog-linear

Moolgavkar (2003) [reanalysis of Moolgavkar (2000a)]

426–427, 428, 

430–438; 410–414, 

429; 440–449

490–492; 464–466, 

480–487

nonenone

24-hr avg.

none

CO

none

CO

0 day1 day

390-429 all ages

HA (unscheduled), 

respiratory

Bell et al. (2008)

Mortality, 

cardiovascular

HA (unscheduled), 

cardiovascular

C-4

September 2009 
Table C-1 cont'd. Information about the Concentration-Response Functions Used in the PM2.5 Risk Assessment: All-Year Functions

Study Health Endpoint ICD-9 or 10 Codes Ages Covered Model Other Pollutants in Model Lag Metric Region Covered 

log-linear, GAM 

(stringent), 30 df 

log-linear, GLM, 30 

df 

log-linear, GAM 

(stringent), 100 df 

log-linear, GLM, 

100 df 

log-linear, GAM 

(stringent), 30 df 

log-linear, GLM, 30 

df 

log-linear, GAM 

(stringent), 100 df 

log-linear, GLM, 

100 df 

log-linear, GAM 

(stringent), 30 df 

log-linear, GAM 

(stringent), 100 df 

log-linear, GLM, 

100 df 

0 day 1 day 2 day 3 day 4 day 5 day 

Mortality, nonaccidental <800 all ages

log-linear, GAM 

(stringent), 30 df

nonenone

Moolgavkar (2003) [reanalysis of Moolgavkar (2000a)]

Los Angeles

24-hr avg.24-hr avg.

CO 1 day 24-hr avg.

1 day0 day

none 24-hr avg.

C-5

September 2009 
Table C-1 cont'd. Information about the Concentration-Response Functions Used in the PM2.5 Risk Assessment: All-Year Functions

Study Health Endpoint ICD-9 or 10 Codes Ages Covered Model Other Pollutants in Model Lag Metric Region Covered 

log-linear, GAM 

(stringent), 30 df 

log-linear, GAM 

(stringent), 100 df 

log-linear, GLM, 

100 df 

log-linear, GAM 

(stringent), 30 df 

log-linear, GAM 

(stringent), 100 df 

log-linear, GLM, 

100 df 

log-linear, GAM 

(stringent), 30 df 

log-linear, GAM 

(stringent), 100 df 

log-linear, GLM, 

100 df 

log-linear, GAM 

(stringent), 100 df 

log-linear, GLM, 

100 df 

log-linear, GAM 

(stringent), 30 df 

log-linear, GAM 

(stringent), 100 df 

log-linear, GLM, 

100 df 

log-linear, GAM 

(stringent), 100 df 

log-linear, GLM, 

100 df 

CO 1 day 24-hr avg.

24-hr avg.

none 1 day 24-hr avg.none 0 day 24-hr avg.

CO 0 day 24-hr avg.

none 0 day 24-hr avg.

Los AngelesLos Angeles

490-496

none 1 day

390-429 65+

all ages

Moolgavkar (2003) [reanalysis of Moolgavkar (2000b)]Moolgavkar (2003) [reanalysis of Moolgavkar (2000a)]

HA, cardiovascular

Mortality, respiratory 

(COPD+)

C-6

September 2009 
Table C-1 cont'd. Information about the Concentration-Response Functions Used in the PM2.5 Risk Assessment: All-Year Functions

Study Health Endpoint ICD-9 or 10 Codes Ages Covered Model Other Pollutants in Model Lag Metric Region Covered 

log-linear, GAM 

(stringent), 30 df 

log-linear, GAM 

(stringent), 100 df 

log-linear, GLM, 

100 df 

log-linear, GAM 

(stringent), 30 df 

log-linear, GAM 

(stringent), 100 df 

log-linear, GLM, 

100 df 

log-linear, GAM 

(stringent), 30 df 

log-linear, GAM 

(stringent), 100 df 

log-linear, GLM, 

100 df 

0 day 1 day 2 day 3 day 

ER visits, 

cardiovascular

410–414, 427, 428, 

433–437, 440, 

443–445, 451–453

all ages log-linear none

avg of 0-,1-

day, and 2-

day

24-hr avg. Atlanta 

ER visits, respiratory

493, 786.07, 786.09; 

491, 492, and 496; 

460–465, 460.0, and 

477; 480–486; 466.1, 

466.11, and 466.19

all ages log-linear none

avg of 0-,1-

day, and 2-

day

24-hr avg. Atlanta 

HA, respiratory 

(COPD+)

Moolgavkar (2003) [reanalysis of Moolgavkar (2000c)]Tolbert et al. (2007) 

490-496 all ages

log-linear, GAM 

(stringent), 100 df

Los Angeles

none 1 day 24-hr avg.none 0 day 24-hr avg.

NO2 24-hr avg.

none 2 day 24-hr avg.

C-7

September 2009 
Table C-1 cont'd. Information about the Concentration-Response Functions Used in the PM2.5 Risk Assessment: All-Year Functions

Study Health Endpoint ICD-9 or 10 Codes Ages Covered Model Other Pollutants in Model Lag Metric Region Covered 

Atlanta 

Baltimore 

Birmingham 

Dallas 

Detroit 

Fresno 

Houston 

Los Angeles 

New York 

Philadelphia 

Phoenix 

Pittsburgh 

Salt Lake City 

St. Louis 

Tacoma 

24-hr avg. avg of 0- and 1-day I01-I59 none all ages log-linear Mortality, cardiovascular Zanobetti and Schwartz (2009)

C-8

September 2009 
Table C-1 cont'd. Information about the Concentration-Response Functions Used in the PM2.5 Risk Assessment: All-Year Functions

Study Health Endpoint ICD-9 or 10 Codes Ages Covered Model Other Pollutants in Model Lag Metric Region Covered 

Atlanta 

Baltimore 

Birmingham 

Dallas 

Detroit 

Fresno 

Houston 

Los Angeles 

New York 

Philadelphia 

Phoenix 

Pittsburgh 

Salt Lake City 

St. Louis 

Tacoma 

Zanobetti and Schwartz (2009)

Mortality, nonaccidental A00-R99 24-hr avg. all ages avg of 0- and 1-day log-linear none

C-9

September 2009 
Table C-1 cont'd. Information about the Concentration-Response Functions Used in the PM2.5 Risk Assessment: All-Year Functions

Study Health Endpoint ICD-9 or 10 Codes Ages Covered Model Other Pollutants in Model Lag Metric Region Covered 

Atlanta 

Baltimore 

Birmingham 

Dallas 

Detroit 

Fresno 

Houston 

Los Angeles 

New York 

Philadelphia 

Phoenix 

Pittsburgh 

Salt Lake City 

St. Louis 

Tacoma 

24-hr avg. avg of 0- and 1-day J00-J99 all ages log-linear none Zanobetti and Schwartz (2009) Mortality, respiratory

C-10

September 2009 
Table C-2. Information about the Concentration-Response Functions Used in the PM2.5 Risk Assessment: Season-Specific Functions

Study Health Endpoint ICD-9 or 10 Codes Ages Covered Other Pollutants in Model Lag Region Covered Season Covered Coeffic

Winter 0.0Spring 0.0Summer 0.0Fall 0.0Winter 0.0Spring -0.0Summer -0.0Fall -0.0Winter 0.0Spring 0.0Summer -0.0Fall 0.0Winter 0.0Spring 0.0Summer -0.0Fall 0.0Winter 0.0Spring 0.0Summer 0.0Fall 0.0Winter -0.0Spring 0.0Summer 0.0Fall -0.0Winter 0.0Spring 0.0Summer -0.0Fall 0.0Winter 0.0Spring 0.0Summer 0.0Fall 0.0

none New York April-August 0.0

O3 New York April-August 0.0

NO2 New York April-August 0.0

CO New York April-August 0.0

SO2 New York April-August 0.0

Bell et al. (2008)

Ito et al. (2007) ER visits, asthma

HA (unscheduled), 

respiratory

HA (unscheduled), 

cardiovascular

493

490–492; 464–466, 

480–487

426–427, 428, 

430–438; 

410–414, 429; 

440–449

none

65+65+

0-day2-day

avg of 0- 

and 1-day all ages

NortheastNorthwestSoutheastSouthwestNortheastNorthwestSoutheastSouthwest

C-11

September 2009 
Table C-2 cont'd. Information about the Concentration-Response Functions Used in the PM2.5 Risk Assessment: Season-Specific Functions

Study Health Endpoint ICD-9 or 10 Codes Ages Covered Other Pollutants in Model Lag Region Covered Season Covered Coeffic

Atlanta Winter 0.0Atlanta Spring 0.0Atlanta Summer 0.0Atlanta Fall -0.0Baltimore Winter 0.0Baltimore Spring 0.0Baltimore Summer 0.0Baltimore Fall 0.0Birmingham Winter 0.0Birmingham Spring 0.0Birmingham Summer -0.0Birmingham Fall -0.0Dallas Winter 0.0Dallas Spring 0.0Dallas Summer 0.0

Dallas Fall -0.0

Detroit Winter -0.0Detroit Spring 0.0Detroit Summer 0.0Detroit Fall 0.0Fresno Winter -0.0Fresno Spring 0.0Fresno Summer 0.0Fresno Fall 0.0Houston Winter 0.0Houston Spring 0.0Houston Summer 0.0Houston Fall 0.0Los Angeles Winter -0.0Los Angeles Spring 0.0Los Angeles Summer -0.0Los Angeles Fall 0.0

all ages avg of 0- and 1-day Zanobetti and Schwartz (2009) Mortality, short-term cardiovascular I01-I59 none

C-12

September 2009 
Table C-2 cont'd. Information about the Concentration-Response Functions Used in the PM2.5 Risk Assessment: Season-Specific Functions

Study Health Endpoint ICD-9 or 10 Codes Ages Covered Other Pollutants in Model Lag Region Covered Season Covered Coeffic

New York Winter 0.0New York Spring 0.0New York Summer 0.0New York Fall 0.0Philadelphia Winter 0.0Philadelphia Spring 0.0Philadelphia Summer 0.0Philadelphia Fall 0.0Phoenix Winter 

Phoenix Spring Phoenix Summer 

Phoenix Fall 

Pittsburgh Winter 0.0Pittsburgh Spring 0.0Pittsburgh Summer 0.0Pittsburgh Fall 0.0Salt Lake City Winter 

Salt Lake City Spring Salt Lake City Summer 

Salt Lake City Fall 

St. Louis Winter -0.0St. Louis Spring 0.0St. Louis Summer 0.0St. Louis Fall 0.0Tacoma Winter 0.0Tacoma Spring 0.0Tacoma Summer 0.0Tacoma Fall 0.0

Mortality, short-term 

cardiovascular none

Zanobetti and 

Schwartz (2009) I01-I59 all ages avg of 0- and 1-day

C-13

September 2009 
Table C-2 cont'd. Information about the Concentration-Response Functions Used in the PM2.5 Risk Assessment: Season-Specific Functions

Study Health Endpoint ICD-9 or 10 Codes Ages Covered Other Pollutants in Model Lag Region Covered Season Covered Coeffic

Atlanta Winter 0.0Atlanta Spring 0.0Atlanta Summer 0.0Atlanta Fall 0.0Baltimore Winter 0.0Baltimore Spring 0.0Baltimore Summer 0.0Baltimore Fall 0.0Birmingham Winter 0.0Birmingham Spring 0.0Birmingham Summer 0.0Birmingham Fall 0.0Dallas Winter 0.0Dallas Spring 0.0Dallas Summer 0.0

Dallas Fall 0.0Detroit Winter -0.0Detroit Spring 0.0Detroit Summer 0.0Detroit Fall 0.0Fresno Winter 0.0Fresno Spring 0.0Fresno Summer 0.0Fresno Fall 0.0Houston Winter 0.0Houston Spring 0.0Houston Summer 0.0Houston Fall 0.0Los Angeles Winter 0.0Los Angeles Spring 0.0Los Angeles Summer -0.0Los Angeles Fall -0.0

avg of 0- 

and 1-day

Zanobetti and 

Schwartz (2009)

Mortality, short-term nonaccidental A00-R99 all ages none

C-14

September 2009 
Table C-2 cont'd. Information about the Concentration-Response Functions Used in the PM2.5 Risk Assessment: Season-Specific Functions

Study Health Endpoint ICD-9 or 10 Codes Ages Covered Other Pollutants in Model Lag Region Covered Season Covered Coeffic

New York Winter 0.0New York Spring 0.0New York Summer 0.0New York Fall 0.0Philadelphia Winter 0.0Philadelphia Spring 0.0Philadelphia Summer 0.0Philadelphia Fall 0.0Phoenix Winter Phoenix Spring Phoenix Summer 

Phoenix Fall 

Pittsburgh Winter 0.0Pittsburgh Spring 0.0Pittsburgh Summer 0.0Pittsburgh Fall 0.0Salt Lake City Winter 0.0Salt Lake City Spring 0.0Salt Lake City Summer 0.0Salt Lake City Fall 0.0St. Louis Winter 0.0St. Louis Spring 0.0St. Louis Summer 0.0St. Louis Fall 0.0Tacoma Winter 0.0Tacoma Spring 0.0Tacoma Summer 0.0

Tacoma Fall 0.0

A00-R99 Zanobetti and Schwartz (2009) Mortality, short-term non- accidental all ages none avg of 0- and 1-day

C-15

September 2009 
Table C-2 cont'd. Information about the Concentration-Response Functions Used in the PM2.5 Risk Assessment: Season-Specific Functions

Study Health Endpoint ICD-9 or 10 Codes Ages Covered Other Pollutants in Model Lag Region Covered Season Covered Coeffic

Atlanta Winter 0.0Atlanta Spring 0.0Atlanta Summer 0.0Atlanta Fall 0.0Baltimore Winter 0.0Baltimore Spring 0.0Baltimore Summer 0.0Baltimore Fall 0.0Birmingham Winter 0.0Birmingham Spring 0.0Birmingham Summer -0.0Birmingham Fall 0.0Dallas Winter 0.0Dallas Spring 0.0Dallas Summer 0.0

Dallas Fall 0.0Detroit Winter 0.0Detroit Spring 0.0Detroit Summer 0.0Detroit Fall 0.0Fresno Winter -0.0Fresno Spring 0.0Fresno Summer 0.0Fresno Fall 0.0Houston Winter 0.0Houston Spring 0.0Houston Summer 0.0Houston Fall 0.0Los Angeles Winter 0.0Los Angeles Spring 0.0Los Angeles Summer -0.0Los Angeles Fall -0.0

all ages none avg of 0- and 1-day Zanobetti and Schwartz (2009) Mortality, short-term respiratory J00-J99

C-16

September 2009 
Table C-2 cont'd. Information about the Concentration-Response Functions Used in the PM2.5 Risk Assessment: Season-Specific Functions

Study Health Endpoint ICD-9 or 10 Codes Ages Covered Other Pollutants in Model Lag Region Covered Season Covered Coeffic

New York Winter 0.0New York Spring 0.0New York Summer 0.0New York Fall 0.0Philadelphia Winter 0.0Philadelphia Spring 0.0Philadelphia Summer 0.0Philadelphia Fall 0.0Phoenix Winter 0.0Phoenix Spring 0.0Phoenix Summer 0.0Phoenix Fall 0.0Pittsburgh Winter 0.0Pittsburgh Spring 0.0Pittsburgh Summer 0.0Pittsburgh Fall 0.0Salt Lake City Winter 0.0Salt Lake City Spring 0.0Salt Lake City Summer -0.0Salt Lake City Fall -0.0St. Louis Winter 0.0St. Louis Spring 0.0St. Louis Summer 0.0St. Louis Fall 0.0Tacoma Winter 0.0Tacoma Spring 0.0Tacoma Summer 0.0Tacoma Fall 0.0

J00-J99 none

1 --- indicates that results were not available.

Zanobetti and 

Schwartz (2009)

Mortality, short-term 

respiratory

avg of 0- 

and 1-day all ages

C-17

September 2009 
APPENDIX D: SUPPLEMENT TO THE REPRESENTATIVENESS 

ANALYSIS OF THE 15 URBAN STUDY AREAS

D-1

September 2009 Draft - Do Not Quote or Cite
Appendix D. Supplement to the Representativeness of the 15 Urban Study Areas 

 (additional graphical comparisons of distributions for key contributors to 

 PM2.5 risk) 

1 

2 

3 

4 

5 

6 

7 

8 

9 

10 

11 

12 

13 

14 

15 

16 

Following the analysis discussed in Section 4.4, this appendix provides graphical 

comparisons of the empirical distributions of components of the risk function, and additional 

variables that have been identified as potentially influencing the risk associated with PM 

exposures. 

 In each graph, the orange line represents the empirical cumulative distribution 

function (CDF) for the complete set of data available for the variable. In some cases, this may 

encompass all counties in the U.S., while in others, it may be based on a subset of the U.S., 

usually for large urban areas. The green line in each graph represents the empirical cumulative 

distribution function for the variable based only on the data available for the set of urban case 

study locations. The black squares at the bottom of each graph represents the specific value of 

the variable for one of the case study locations, with the line showing where that value intersects 

the two empirical CDFs.

D-2

September 2009 Draft - Do Not Quote or Cite
D.1 Elements of the Risk Equation 

Figure D-1. Comparison of Distributions for Key Elements of the Risk Equation: 

 Total Population 

Comparison of Urban Case Study Area Population with U.S. Distribution of 

Population (all U.S. Counties)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

100 1000 10000 100000 1000000 10000000

Population

% of Counties

All Counties CDF Case Study Counties CDF Case Study Counties

Urban case study areas are 

all above the 65th Percentile 

of county populations

D-3

September 2009 Draft - Do Not Quote or Cite
Figure D-2. Comparison of Distributions for Key Elements of the Risk Equation: 

 Percent of Population Under 15 Years of Age 

Comparison of Urban Case Study Area % Under 15 to U.S. Distribution of % Under 

15

(3141 U.S. Counties)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

10 15 20 25 30 35

% of Population Under Age 15, 2005

% of U.S. Counties

All Counties CDF Case Study Counties Case Study Counties

D-4

September 2009 Draft - Do Not Quote or Cite
Figure D-3. Comparison of Distributions for Key Elements of the Risk Equation: 

 Percent of Population 65 Years of Age and Older 

Comparison of Urban Case Study Area % 65 and Older to U.S. Distribution of % 65 

and Older

(3141 U.S. Counties)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0 5 10 15 20 25 30 35

% of Population 65 and Older, 2005

% of U.S. Counties

Urban case study areas are 

all below the 75th percentile 

of county % of population 65 

and older

All Counties CDF Case Study Counties CDF Case Study Counties

D-5

September 2009 Draft - Do Not Quote or Cite
Figure D-4. Comparison of Distributions for Key Elements of the Risk Equation: 

 Percent of Population 85 Years of Age and Older 

Comparison of Urban Case Study Area % 85 and Older to U.S. Distribution of % 85 

and Older

(3141 U.S. Counties)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

12345678

% of Population 85 and Older, 2005

% of U.S. Counties

Urban case study areas are 

all below the 85th percentile 

of county % of population 85 

and older

All Counties CDF Case Study Counties CDF Case Study Counties

D-6

September 2009 Draft - Do Not Quote or Cite
Figure D-5. Comparison of Distributions for Key Elements of the Risk Equation: Annual 

 Mean PM2.5 

Comparison of Urban Case Study Area Annual Mean PM2.5 with U.S. 

Distribution of Annual Mean PM2.5 (617 U.S. Counties with PM2.5 Monitors)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0 5 10 15 20 25

Annual Mean PM2.5

% of Monitored Counties

All Counties CDF Case Study Counties CDF Case Study Counties

D-7

September 2009 Draft - Do Not Quote or Cite
Figure D-6. Comparison of Distributions for Key Elements of the Risk Equation: 98th 

 %ile Daily Average PM2.5 

Comparison of Urban Case Study Area 98th %ile PM2.5 with U.S. Distribution of 

98th %ile PM2.5 

(617 U.S. Counties with PM2.5 Monitors)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0 10 20 30 40 50 60 70 80 90

98th Percentile Daily PM2.5

% of Monitored Counties

All Counties CDF Case Study Counties CDF Case Study Counties

D-8

September 2009 Draft - Do Not Quote or Cite
Figure D-7. Comparison of Distributions for Key Elements of the Risk Equation: % of 

 Days with PM2.5>35 μg/m3

Comparison of Urban Case Study Area % of Days with PM2.5>35 ug/m3 to U.S. 

Distribution of % of Days with PM2.5>35 ug/m3

(204 U.S. Counties in MCAPS Study)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0 5 10 15 20 25

% of Days Above 35 ug/m3

% of MCAPS Counties

All Counties CDF Case Study Counties CDF Case Study Counties

D-9

September 2009 Draft - Do Not Quote or Cite
Figure D-8. Comparison of Distributions for Key Elements of the Risk Equation: All 

 Cause Mortality Rate 

Comparison of Urban Case Study All Cause Mortality Rate to U.S. Distribution of All 

Cause Mortality Rate

(3143 U.S. Counties)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

100 300 500 700 900 1100 1300 1500 1700 1900 2100

All Cause Mortality per 100,000 Population

% of U.S. Counties

All Counties CDF Case Study Counties CDF Case Study Counties

Urban case study areas are 

all below the 90th percentile 

of county all cause mortality

D-10

September 2009 Draft - Do Not Quote or Cite
Figure D-9. Comparison of Distributions for Key Elements of the Risk Equation: Non- 

 accidental Mortality Rate 

Comparison of Urban Case Study Non-accidental Mortality Rate to U.S. Distribution of 

Non-accidental Mortality Rate

(3143 U.S. Counties)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

200 400 600 800 1000 1200 1400 1600 1800 2000

Non-accidental Mortality per 100,000 Population

% of U.S. Counties

Urban case study areas are 

all below the 90th percentile 

of county non-accidental 

mortality

All Counties CDF Case Study Counties CDF Case Study Counties

D-11

September 2009 Draft - Do Not Quote or Cite
Figure D-10. Comparison of Distributions for Key Elements of the Risk Equation: 

 Cardiovascular Mortality Rate 

Comparison of Urban Case Study Cardiovascular Mortality Rate to U.S. Distribution of 

Cardiovascular Mortality Rate

(3143 U.S. Counties)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

50 150 250 350 450 550 650 750 850 950

Cardiovascular Mortality per 100,000 Population

% of U.S. Counties

Urban case study areas are 

all below the 90th percentile 

of county cardiovascular 

mortality

All Counties CDF Case Study Counties CDF Case Study Counties

D-12

September 2009 Draft - Do Not Quote or Cite
Figure D-11. Comparison of Distributions for Key Elements of the Risk Equation: 

 Respiratory Mortality Rate 

Comparison of Urban Case Study Respiratory Mortality Rate to U.S. Distribution of 

Respiratory Mortality Rate

(3143 U.S. Counties)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

10 60 110 160 210 260

Respiratory Mortality per 100,000 Population

% of U.S. Counties

Urban case study areas are 

all below the 90th percentile 

of county respiratory 

mortality

All Counties CDF Case Study Counties CDF Case Study Counties

D-13

September 2009 Draft - Do Not Quote or Cite
Figure D-12. Comparison of Distributions for Key Elements of the Risk Equation: All 

 Cause Mortality Risk Effect Estimate from Zanobetti and Schwartz (2008) 

Comparison of Urban Case Study PM All-cause Mortality Risk (β) to 

U.S. Distribution of PM All-cause Mortality Risk

(212 U.S. Urban Areas)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0 0.0002 0.0004 0.0006 0.0008 0.001 0.0012 0.0014 0.0016

Bayesian Shrunken PM All Cause Mortality Risk Coefficient (β)

% of Z&S Urban Areas

All Z&S Urban Areas CDF Case Study Urban Area CDF Case Study Urban Areas

D-14

September 2009 Draft - Do Not Quote or Cite
Figure D-13. Comparison of Distributions for Key Elements of the Risk Equation: 

 Cardiovascular Mortality Risk Effect Estimate from Zanobetti and 

Schwartz (2008) 

Comparison of Urban Case Study PM Cardiovascular Mortality Risk (β) to U.S. 

Distribution of PM Cardiovascular Mortality Risk

(212 U.S. Urban Areas)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0 0.0002 0.0004 0.0006 0.0008 0.001 0.0012 0.0014 0.0016 0.0018 0.002

Bayesian Shrunken PM Cardiovascular Mortality Risk Coefficient (β)

% of Z&S Urban Areas

All Z&S Urban Areas CDF Case Study Urban Area CDF Case Study Urban Areas

D-15

September 2009 Draft - Do Not Quote or Cite
Figure D-14. Comparison of Distributions for Key Elements of the Risk Equation: 

 Respiratory Mortality Risk Effect Estimate from Zanobetti and Schwartz 

 (2008) 

Comparison of Urban Case Study PM Respiratory Mortality Risk (β) to U.S. 

Distribution of PM Respiratory Mortality Risk

(212 U.S. Urban Areas)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0 0.0005 0.001 0.0015 0.002

Bayesian Shrunken PM Respiratory Mortality Risk Coefficient (β)

% of Z&S Urban Areas

All Z&S Urban Areas CDF Case Study Urban Area CDF Case Study Urban Areas

D-16

September 2009 Draft - Do Not Quote or Cite
D.2. Variables Expected to Influence the Relative Risk from PM2.5 

 D.2.1. Demographic Variables 

Figure D-15. Comparison of Distributions for Selected Variables Expected to 

Influence the Relative Risk from PM2.5: Population Density 

Comparison of Urban Case Study Area Population Density with U.S. Distribution of 

Population Density (all U.S. Counties)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

% of Counties

Urban case study areas are 

all above the 65th Percentile 

of county population density

1 10 100 1000 10000 100000

Population Density (persons per sq mile)

All Counties CDF Case Study Counties CDF Case Study Counties

D-17

September 2009 Draft - Do Not Quote or Cite
Figure D-16. Comparison of Distributions for Selected Variables Expected to 

 Influence the Relative Risk from PM2.5: Unemployment Rate 

Comparison of Urban Case Study Area Unemployment Rate to U.S. Distribution of 

Unemployment Rates

(3141 U.S. Counties)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0 2 4 6 8 10 12 14 16 18 20

Unemployment Rate (%)

% of U.S. Counties

All Counties CDF Case Study Counties CDF Case Study Counties

D-18

September 2009 Draft - Do Not Quote or Cite
Figure D-17. Comparison of Distributions for Selected Variables Expected to Influence the 

 Relative Risk from PM2.5: % with Less than a High School Education 

 

Comparison of Urban Case Study % Less than High School Education to U.S. 

Distribution of % Less than High School Education

(3146 U.S. Counties)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

3 13 23 33 43 53 63

% of Population with Less than a High School Education, 2000

% of U.S. Counties

All Counties CDF Case Study Counties CDF Case Study Counties

D-19

September 2009 Draft - Do Not Quote or Cite
Figure D-18. Comparison of Distributions for Selected Variables Expected to Influence the 

 Relative Risk from PM2.5: Per Capita Personal Income 

Comparison of Urban Case Study Area Per Capita Personal Income to U.S. 

Distribution of Per Capita Personal Income

(3141 U.S. Counties)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

$10,000 $20,000 $30,000 $40,000 $50,000 $60,000 $70,000 $80,000 $90,000

Per Capita Personal Income, 2005

% of U.S. Counties

Urban case study areas are 

all above the 25th percentile 

of county per capita income

All Counties CDF Case Study Counties CDF Case Study Counties

D-20

September 2009 Draft - Do Not Quote or Cite
Figure D-19. Comparison of Distributions for Selected Variables Expected to Influence the 

 Relative Risk from PM2.5: Air Conditioning Prevalence 

Comparison of Urban Case Study Air Conditioning Prevalence to U.S. Distribution of 

Air Conditioning Prevalence

(70 U.S. Urban Areas)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0 0.2 0.4 0.6 0.8 1

% Air Conditioning Prevalence

% of Urban Areas

All Urban Areas CDF Case Study Urban Areas CDF Case Study Urban Areas

D-21

September 2009 Draft - Do Not Quote or Cite
Figure D-20. Comparison of Distributions for Selected Variables Expected to Influence the 

 Relative Risk from PM2.5: % Non-white Population 

Comparison of Urban Case Study Air Conditioning Prevalence to U.S. Distribution of 

Air Conditioning Prevalence

(70 U.S. Urban Areas)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0 0.2 0.4 0.6 0.8 1

% Air Conditioning Prevalence

% of Urban Areas

All Urban Areas CDF Case Study Urban Areas CDF Case Study Urban Areas

D-22

September 2009 Draft - Do Not Quote or Cite
D.2.2. Health Conditions 

Figure D-21. Comparison of Distributions for Selected Variables Expected to 

 Influence the Relative Risk from PM2.5: Angina/Coronary Heart 

 Disease Prevalence 

Comparison of Urban Case Study Area Angina/CHD Prevalence to U.S. Distribution 

of Angina/CHD Prevalence

(183 U.S. MSA)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

123456789

% of BRFSS MSA

Urban case study areas are 

all below the 85th percentile 

of MSA angina or CHD 

prevalence

% Prevalence of Angina or CHD, BRFSS, 2007

All BRFSS MSA CDF Case Study County MSA CDF Case Study County MSA

D-23

September 2009 Draft - Do Not Quote or Cite
Figure D-22. Comparison of Distributions for Selected Variables Expected to 

 Influence the Relative Risk from PM2.5: Asthma Prevalence 

Comparison of Urban Case Study Area Current Asthma Prevalence to U.S. 

Distribution of Current Asthma Prevalence

(183 U.S. MSA)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

3 5 7 9 11 13

% Current Prevalence of Asthma, BRFSS 2007

% of BRFSS MSA

All BRFSS MSA CDF Case Study County MSA CDF Case Study County MSA

D-24

September 2009 Draft - Do Not Quote or Cite
Figure D-23. Comparison of Distributions for Selected Variables Expected to Influence the 

 Relative Risk from PM2.5: Diabetes Prevalence 

Comparison of Urban Case Study Area Diabetes Prevalence to U.S. Distribution of 

Diabetes Prevalence

(183 U.S. MSA)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2 4 6 8 10 12 14 16

% Prevalence of Diabetes, BRFSS 2007

% of BRFSS MSA

All BRFSS MSA CDF Case Study County MSA CDF Case Study County MSA

Urban case study areas are 

all below the 85th percentile 

of MSA diabetes prevalence

D-25

September 2009 Draft - Do Not Quote or Cite
Figure D-24. Comparison of Distributions for Selected Variables Expected to Influence the 

 Relative Risk from PM2.5: Heart Attack Prevalence 

Comparison of Urban Case Study Area Heart Attack Prevalence to U.S. Distribution of 

Heart Attack Prevalence

(183 U.S. MSA)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2 3 4 5 6 7 8 9 10 1

% Prevalence of Heart Attacks, BRFSS 2007

% of BRFSS MSA

1

All BRFSS MSA CDF Case Study County MSA CDF Case Study County MSA

Urban case study areas are 

all below the 80th percentile 

of MSA heart attack 

prevalence

D-26

September 2009 Draft - Do Not Quote or Cite
Figure D-25. Comparison of Distributions for Selected Variables Expected to Influence the 

 Relative Risk from PM2.5: Obesity Prevalence 

Comparison of Urban Case Study Area Obesity Prevalence to U.S. Distribution of 

Obesity Prevalence

(183 U.S. MSA)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

14 19 24 29 34

% Prevalence of Obesity, BRFSS 2007

% of BRFSS MSA

All BRFSS MSA CDF Case Study County MSA CDF Case Study County MSA

D-27

September 2009 Draft - Do Not Quote or Cite
Figure D-26. Comparison of Distributions for Selected Variables Expected to Influence the 

 Relative Risk from PM2.5: Stroke Prevalence 

Comparison of Urban Case Study Area Stroke Prevalence to U.S. Distribution of 

Stroke Prevalence

(183 U.S. MSA)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0123456

% Prevalence of Stroke, BRFSS 2007

% of BRFSS MSA

All BRFSS MSA CDF Case Study County MSA CDF Case Study County MSA

D-28

September 2009 Draft - Do Not Quote or Cite
Figure D-27. Comparison of Distributions for Selected Variables Expected to Influence the 

 Relative Risk from PM2.5: Smoking Prevalence 

Comparison of Urban Case Study Area Smoking Prevalence to U.S. Distribution of 

Smoking Prevalence

(183 U.S. MSA)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

6 11 16 21 26 31

% Prevalence of Smoking (ever), BRFSS 2007

% of BRFSS MSA

Urban case study areas are 

all below the 85th percentile 

of MSA smoking prevalence

All BRFSS MSA CDF Case Study County MSA CDF Case Study County MSA

D-29

September 2009 Draft - Do Not Quote or Cite
Figure D-28. Comparison of Distributions for Selected Variables Expected to Influence the 

 Relative Risk from PM2.5: Exercise Prevalence 

Comparison of Urban Case Study Area Exercise Prevalence to U.S. Distribution of 

Exercise Prevalence

(183 U.S. MSA)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

15 20 25 30 35 40 45

% Prevalence of Exercise (Adults with 20+ minutes of vigorous physical activity 3 or 

more days per week), BRFSS 2007

% of BRFSS MSA

All BRFSS MSA CDF Case Study County MSA CDF Case Study County MSA

D-30

September 2009 Draft - Do Not Quote or Cite
D.2.3. Air Quality and Climate Variables 

Figure D-29. Comparison of Distributions for Selected Variables Expected to 

 Influence the Relative Risk from PM2.5: 4th Highest Daily Max 8- 

 hour Average 

Comparison of Urban Case Study Area 4th Highest Daily 8-Hour Ozone with U.S. 

Distribution of 4th Highest Daily 8-Hour Ozone 

(725 U.S. Counties with Ozone Monitors)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0.02 0.04 0.06 0.08 0.1 0.12

% of Monitored Counties

4th Highest Daily 8-Hour Maximum

All Counties CDF Case Study Counties CDF Case Study Counties

D-31

September 2009 Draft - Do Not Quote or Cite
Figure D-30. Comparison of Distributions for Selected Variables Expected to Influence the 

 Relative Risk from PM2.5: % Mobile Source Direct PM2.5 Emissions 

Comparison of Urban Case Study Mobile Source Carbon to U.S. Distribution of Mobile 

Source Carbon

(3142 U.S. Counties)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Mobile Source Proportion of Total Organic and Elemental Carbon Emissions

% of U.S. Counties

Urban case study areas are 

all below the 80th percentile 

of county mobile source 

proportion of EC/OC 

emissions

All Counties CDF Case Study Counties CDF Case Study Counties

 

D-32

September 2009 Draft - Do Not Quote or Cite
Figure D-31. Comparison of Distributions for Selected Variables Expected to 

 Influence the Relative Risk from PM2.5: July Temperature Long 

 Term Average 

Comparison of Urban Case Study Area Long Term Average July Temperature to 

U.S. Distribution of Long Term Average July Temperature

(3141 U.S. Counties)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

50 60 70 80 90 100

July 30 Year Average Temperature, 1941-1970

% of U.S. Counties

All Counties CDF Case Study Counties CDF Case Study Counties

D-33

September 2009 Draft - Do Not Quote or Cite
Figure D-32. Comparison of Distributions for Selected Variables Expected to Influence the 

 Relative Risk from PM2.5: July Relative Humidity Long Term Average 

Comparison of Urban Case Study Area Long Term Average July Relative Humidity to 

U.S. Distribution of Long Term Average July Relative Humidity

(3141 U.S. Counties)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0 10 20 30 40 50 60 70 80 90

July 30 Year Average Relative Humidity, 1941-1970

% of U.S. Counties

All Counties CDF

D-34

Case Study Counties CDF Case Study Counties

 

September 2009 Draft - Do Not Quote or Cite
APPENDIX E: RISK ESTIMATES (CORE ANALYSIS) 

E-1

September 2009 Draft - Do Not Quote or Cite
1 Appendix E. Risk Analysis (core analysis) 

2 

3 

4 

5 

6 

7 

8 

9 

10 

11 

12 

13 

14 

15 

16 

This Appendix provides detailed risk estimates generated for the core analysis for the 15 

urban study areas. The tables cover all of the air quality scenarios modeled, including recent 

conditions, the current standard, and alternative standard levels. For additional detail on the types 

of risk metrics (and figures summarizing key metrics) presented in this Appendix, see section 

4.0. 

We have identified an error in the approach used to simulate ambient PM2.5 levels for the 

Pittsburgh study area for the scenarios involving just meeting the current and alternative sets of 

standards. Consequently, this error impacts the risk estimates generated for the current and 

alternative standards but does not impact the risk estimates for the recent conditions scenario. 

There was insufficient time after identifying this error to either generate corrected risk estimates 

or remove the erroneous risk estimates from the summary tables presented in this Appendix. We 

will correct this error and release updated results for the Pittsburgh study area as soon as is 

practicable and will include the corrected results in the next version of this document. Note, that 

this error does not impact risk estimates for any of the other urban study areas. 

E-2

September 2009 Draft - Do Not Quote or Cite
Table E-1. Estimated Annual Incidence of All-Cause Mortality Associated with Long-Term Exposure to Ambient PM2.5 Co

 a Recent Year (2005) and PM2.5 Concentrations that Just Meet the Current and Alternative Standards, Based on 

 PM2.5 Concentrations: Estimates Based on Krewski et al. (2009), Using Ambient PM2.5 from 1979 - 19831 

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

645 572 449 386 449 

(419 - 869) (371 - 770) (290 - 605) (250 - 522) (290 - 605) 

592 543 438 378 422 

(384 - 796) (352 - 732) (284 - 590) (245 - 510) (273 - 569) 

494 352 275 236 275 

(321 - 663) (228 - 474) (178 - 370) (152 - 318) (178 - 370) 

366 366 366 324 366 

(237 - 494) (237 - 494) (237 - 494) (210 - 437) (237 - 494) 

754 544 469 400 411 

(490 - 1015) (352 - 733) (303 - 633) (259 - 540) (266 - 555) 

249 86 86 86 56 

(161 - 334) (55 - 116) (55 - 116) (55 - 116) (36 - 76) 

721 663 517 443 517 

(468 - 971) (430 - 893) (335 - 697) (287 - 599) (335 - 697) 

2443 1116 1116 985 779 

(1585 - 3286) (721 - 1507) (721 - 1507) (636 - 1332) (503 - 1053) 

1725 1247 1186 998 903 

(1118 - 2326) (807 - 1684) (767 - 1601) (645 - 1349) (583 - 1220) 

490 427 379 324 320 

(318 - 661) (276 - 576) (245 - 512) (209 - 437) (207 - 432) 

476 476 476 427 414 

(308 - 643) (308 - 643) (308 - 643) (276 - 577) (267 - 559) 

698 285 285 285 201 

(454 - 938) (184 - 386) (184 - 386) (184 - 386) (130 - 272) 

123 42 42 42 22 

(80 - 166) (27 - 57) (27 - 57) (27 - 57) (14 - 29) 

791 669 530 454 515 

(513 - 1064) (433 - 901) (343 - 715) (294 - 614) (334 - 695) 

121 79 79 79 52 

(79 - 164) (51 - 107) (51 - 107) (51 - 107) (34 - 70) 

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

 Incidence of All-Cause Mortality Associated with Long-Term Exposure to PM2.5 Concentrations in a 

PM2.5 Concentrations that Just Meet the Current and Alternative Annual (n) and Daily (m) Standar

Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

E-3

September 2009 
Table E-2. Estimated Annual Incidence of All-Cause Mortality Associated with Long-Term Exposure to Ambient PM2.5 Co

 in a Recent Year (2006) and PM2.5 Concentrations that Just Meet the Current and Alternative Standards, Based o

 2006 PM2.5 Concentrations: Estimates Based on Krewski et al. (2009), Using Ambient PM2.5 from 1979 - 19831

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

624 551 430 368 430 

(405 - 840) (357 - 743) (278 - 580) (238 - 497) (278 - 580) 

515 470 374 319 359 

(334 - 693) (305 - 634) (242 - 504) (206 - 431) (232 - 485) 

478 339 263 225 263 

(310 - 642) (220 - 457) (170 - 355) (145 - 304) (170 - 355) 

281 281 281 244 281 

(181 - 379) (181 - 379) (181 - 379) (158 - 330) (181 - 379) 

573 396 332 275 284 

(371 - 773) (256 - 534) (215 - 449) (177 - 371) (183 - 384) 

264 94 94 94 63 

(172 - 355) (60 - 127) (60 - 127) (60 - 127) (40 - 85) 

762 701 548 471 548 

(494 - 1026) (455 - 945) (355 - 739) (304 - 635) (355 - 739) 

2191 950 950 829 636 

(1421 - 2951) (614 - 1285) (614 - 1285) (535 - 1121) (410 - 861) 

1489 1047 991 818 729 

(964 - 2009) (677 - 1415) (640 - 1339) (528 - 1106) (471 - 987) 

481 418 371 316 312 

(311 - 648) (270 - 563) (240 - 501) (204 - 426) (202 - 422) 

520 520 520 468 454 

(336 - 703) (336 - 703) (336 - 703) (303 - 633) (294 - 614) 

605 231 231 231 155 

(393 - 814) (149 - 312) (149 - 312) (149 - 312) (100 - 210) 

102 27 27 27 8 

(66 - 138) (18 - 37) (18 - 37) (18 - 37) (5 - 11) 

613 508 389 325 377 

(397 - 826) (329 - 686) (252 - 526) (210 - 439) (244 - 510) 

79 44 44 44 22 

(51 - 106) (28 - 59) (28 - 59) (28 - 59) (14 - 29) 

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

 Incidence of All-Cause Mortality Associated with Long-Term Exposure to PM2.5 Concentrations in a Recent 

Concentrations that Just Meet the Current and Alternative Annual (n) and Daily (m) Standards (Standard C

Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

E-4

September 2009 
Table E-3. Estimated Annual Incidence of All-Cause Mortality Associated with Long-Term Exposure to Ambient PM2.5 Co

 a Recent Year (2007) and PM2.5 Concentrations that Just Meet the Current and Alternative Standards, Based on 

 2007 PM2.5 Concentrations: Estimates Based on Krewski et al. (2009), Using Ambient PM2.5 from 1979 - 19831

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

646 571 445 382 445 

(419 - 869) (370 - 769) (288 - 600) (247 - 516) (288 - 600) 

482 439 346 294 332 

(312 - 649) (284 - 592) (224 - 467) (190 - 397) (215 - 449) 

473 335 259 221 259 

(307 - 636) (217 - 451) (168 - 350) (143 - 299) (168 - 350) 

311 311 311 272 311 

(201 - 420) (201 - 420) (201 - 420) (176 - 367) (201 - 420) 

536 366 305 250 258 

(347 - 723) (236 - 494) (197 - 412) (161 - 337) (167 - 349) 

299 112 112 112 78 

(194 - 402) (73 - 152) (73 - 152) (73 - 152) (51 - 106) 

748 687 535 458 535 

(485 - 1007) (445 - 926) (346 - 721) (296 - 618) (346 - 721) 

2240 979 979 855 659 

(1453 - 3016) (632 - 1323) (632 - 1323) (552 - 1156) (425 - 892) 

1514 1067 1010 834 745 

(980 - 2043) (690 - 1442) (652 - 1364) (539 - 1128) (481 - 1008) 

476 413 367 312 308 

(308 - 641) (267 - 557) (237 - 495) (202 - 421) (199 - 417) 

451 451 451 402 388 

(292 - 610) (292 - 610) (292 - 610) (260 - 543) (251 - 525) 

613 236 236 236 160 

(398 - 825) (153 - 319) (153 - 319) (153 - 319) (103 - 216) 

142 52 52 52 29 

(92 - 192) (34 - 71) (34 - 71) (34 - 71) (19 - 40) 

653 545 421 354 408 

(423 - 880) (353 - 735) (272 - 569) (229 - 479) (264 - 551) 

91 53 53 53 30 

(59 - 123) (34 - 72) (34 - 72) (34 - 72) (19 - 40) 

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

 Incidence of All-Cause Mortality Associated with Long-Term Exposure to PM2.5 Concentrations in a 

PM2.5 Concentrations that Just Meet the Current and Alternative Annual (n) and Daily (m) Standa

Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

E-5

September 2009 
Table E-4. Estimated Percent of Total Annual Incidence of All-Cause Mortality Associated with Long-Term Exposure to A

 Concentrations in a Recent Year (2005) and PM2.5 Concentrations that Just Meet the Current and Alternative Sta

 on Adjusting 2005 PM2.5 Concentrations: Estimates Based on Krewski et al. (2009), Using Ambient PM2.5 from 19

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

4.3% 3.8% 3% 2.6% 3% 

(2.8% - 5.8%) (2.5% - 5.1%) (1.9% - 4%) (1.7% - 3.5%) (1.9% - 4%) 

4.2% 3.8% 3.1% 2.7% 3% 

(2.7% - 5.6%) (2.5% - 5.2%) (2% - 4.2%) (1.7% - 3.6%) (1.9% - 4%) 

5% 3.6% 2.8% 2.4% 2.8% 

(3.3% - 6.8%) (2.3% - 4.8%) (1.8% - 3.8%) (1.6% - 3.2%) (1.8% - 3.8%) 

2.9% 2.9% 2.9% 2.5% 2.9% 

(1.8% - 3.8%) (1.8% - 3.8%) (1.8% - 3.8%) (1.6% - 3.4%) (1.8% - 3.8%) 

4.2% 3% 2.6% 2.2% 2.3% 

(2.7% - 5.7%) (2% - 4.1%) (1.7% - 3.5%) (1.5% - 3%) (1.5% - 3.1%) 

4.5% 1.5% 1.5% 1.5% 1% 

(2.9% - 6%) (1% - 2.1%) (1% - 2.1%) (1% - 2.1%) (0.6% - 1.4%) 

3.9% 3.6% 2.8% 2.4% 2.8% 

(2.5% - 5.2%) (2.3% - 4.8%) (1.8% - 3.7%) (1.5% - 3.2%) (1.8% - 3.7%) 

4.3% 2% 2% 1.7% 1.4% 

(2.8% - 5.8%) (1.3% - 2.7%) (1.3% - 2.7%) (1.1% - 2.3%) (0.9% - 1.9%) 

3.3% 2.4% 2.3% 1.9% 1.7% 

(2.1% - 4.4%) (1.5% - 3.2%) (1.5% - 3%) (1.2% - 2.6%) (1.1% - 2.3%) 

3.4% 2.9% 2.6% 2.2% 2.2% 

(2.2% - 4.5%) (1.9% - 4%) (1.7% - 3.5%) (1.4% - 3%) (1.4% - 3%) 

2.1% 2.1% 2.1% 1.9% 1.8% 

(1.3% - 2.8%) (1.3% - 2.8%) (1.3% - 2.8%) (1.2% - 2.5%) (1.2% - 2.4%) 

5% 2.1% 2.1% 2.1% 1.4% 

(3.3% - 6.7%) (1.3% - 2.8%) (1.3% - 2.8%) (1.3% - 2.8%) (0.9% - 2%) 

2.6% 0.9% 0.9% 0.9% 0.5% 

(1.7% - 3.5%) (0.6% - 1.2%) (0.6% - 1.2%) (0.6% - 1.2%) (0.3% - 0.6%) 

4.2% 3.6% 2.8% 2.4% 2.7% 

(2.7% - 5.6%) (2.3% - 4.8%) (1.8% - 3.8%) (1.6% - 3.3%) (1.8% - 3.7%) 

2.4% 1.6% 1.6% 1.6% 1% 

(1.5% - 3.2%) (1% - 2.1%) (1% - 2.1%) (1% - 2.1%) (0.7% - 1.4%) 

Percent of Total Incidence of All-Cause Mortality Associated with Long-Term Exposure to PM2.5 Con

Recent Year and PM2.5 Concentrations that Just Meet the Current and Alternative Annual (n) and Dail

(Standard Combination Denoted n/m):

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL Baltimore, MD Detroit, MI Houston, TX New York, NY St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT

E-6

September 2009 
Table E-5. Estimated Percent of Total Annual Incidence of All-Cause Mortality Associated with Long-Term Exposure to A

 Concentrations in a Recent Year (2006) and PM2.5 Concentrations that Just Meet the Current and Alternative Sta

 on Adjusting 2006 PM2.5 Concentrations: Estimates Based on Krewski et al. (2009), Using Ambient PM2.5 from 19

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

4% 3.5% 2.8% 2.4% 2.8% 

(2.6% - 5.4%) (2.3% - 4.8%) (1.8% - 3.7%) (1.5% - 3.2%) (1.8% - 3.7%) (

3.6% 3.3% 2.6% 2.3% 2.5% 

(2.4% - 4.9%) (2.2% - 4.5%) (1.7% - 3.6%) (1.5% - 3%) (1.6% - 3.4%) (

4.8% 3.4% 2.6% 2.3% 2.6% 

(3.1% - 6.5%) (2.2% - 4.6%) (1.7% - 3.6%) (1.5% - 3.1%) (1.7% - 3.6%) (

2.1% 2.1% 2.1% 1.9% 2.1% 

(1.4% - 2.9%) (1.4% - 2.9%) (1.4% - 2.9%) (1.2% - 2.5%) (1.4% - 2.9%) (

3.2% 2.2% 1.9% 1.5% 1.6% 

(2.1% - 4.3%) (1.4% - 3%) (1.2% - 2.5%) (1% - 2.1%) (1% - 2.2%) (

4.7% 1.7% 1.7% 1.7% 1.1% 

(3% - 6.3%) (1.1% - 2.2%) (1.1% - 2.2%) (1.1% - 2.2%) (0.7% - 1.5%) (

4% 3.6% 2.8% 2.4% 2.8% 

(2.6% - 5.3%) (2.4% - 4.9%) (1.8% - 3.8%) (1.6% - 3.3%) (1.8% - 3.8%) (

3.8% 1.7% 1.7% 1.5% 1.1% 

(2.5% - 5.2%) (1.1% - 2.2%) (1.1% - 2.2%) (0.9% - 2%) (0.7% - 1.5%) (

2.8% 2% 1.9% 1.5% 1.4% 

(1.8% - 3.8%) (1.3% - 2.7%) (1.2% - 2.5%) (1% - 2.1%) (0.9% - 1.9%) 

3.3% 2.9% 2.6% 2.2% 2.1% 

(2.1% - 4.5%) (1.9% - 3.9%) (1.7% - 3.4%) (1.4% - 2.9%) (1.4% - 2.9%) (

2.2% 2.2% 2.2% 2% 1.9% 

(1.4% - 2.9%) (1.4% - 2.9%) (1.4% - 2.9%) (1.3% - 2.6%) (1.2% - 2.6%) (

4.4% 1.7% 1.7% 1.7% 1.1% 

(2.8% - 5.9%) (1.1% - 2.3%) (1.1% - 2.3%) (1.1% - 2.3%) (0.7% - 1.5%) (

2.1% 0.6% 0.6% 0.6% 0.2% 

(1.3% - 2.8%) (0.4% - 0.8%) (0.4% - 0.8%) (0.4% - 0.8%) (0.1% - 0.2%) 

3.2% 2.7% 2.1% 1.7% 2% 

(2.1% - 4.4%) (1.7% - 3.6%) (1.3% - 2.8%) (1.1% - 2.3%) (1.3% - 2.7%) (

1.5% 0.8% 0.8% 0.8% 0.4% 

(1% - 2.1%) (0.5% - 1.1%) (0.5% - 1.1%) (0.5% - 1.1%) (0.3% - 0.6%) 

 Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Detroit, MI Houston, TX New York, NY St. Louis, MO

Percent of Total Incidence of All-Cause Mortality Associated with Long-Term Exposure to PM2.5 Conce

Recent Year and PM2.5 Concentrations that Just Meet the Current and Alternative Annual (n) and Daily 

(Standard Combination Denoted n/m):

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL Baltimore, MD

E-7

September 2009 
Table E-6. Estimated Percent of Total Annual Incidence of All-Cause Mortality Associated with Long-Term Exposure to A

 Concentrations in a Recent Year (2007) and PM2.5 Concentrations that Just Meet the Current and Alternative Sta

 on Adjusting 2007 PM2.5 Concentrations: Estimates Based on Krewski et al. (2009), Using Ambient PM2.5 from 19

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

4% 3.6% 2.8% 2.4% 2.8% 

(2.6% - 5.4%) (2.3% - 4.8%) (1.8% - 3.8%) (1.5% - 3.2%) (1.8% - 3.8%) (

3.4% 3.1% 2.5% 2.1% 2.4% 

(2.2% - 4.6%) (2% - 4.2%) (1.6% - 3.3%) (1.3% - 2.8%) (1.5% - 3.2%) 

4.7% 3.3% 2.6% 2.2% 2.6% 

(3.1% - 6.3%) (2.2% - 4.5%) (1.7% - 3.5%) (1.4% - 3%) (1.7% - 3.5%) (

2.3% 2.3% 2.3% 2% 2.3% 

(1.5% - 3.1%) (1.5% - 3.1%) (1.5% - 3.1%) (1.3% - 2.8%) (1.5% - 3.1%) (

3% 2.1% 1.7% 1.4% 1.5% 

(2% - 4.1%) (1.3% - 2.8%) (1.1% - 2.3%) (0.9% - 1.9%) (0.9% - 2%) (

5.2% 2% 2% 2% 1.4% 

(3.4% - 7%) (1.3% - 2.6%) (1.3% - 2.6%) (1.3% - 2.6%) (0.9% - 1.8%) 

3.8% 3.5% 2.7% 2.3% 2.7% 

(2.5% - 5.1%) (2.3% - 4.7%) (1.8% - 3.7%) (1.5% - 3.1%) (1.8% - 3.7%) (

3.9% 1.7% 1.7% 1.5% 1.1% 

(2.5% - 5.2%) (1.1% - 2.3%) (1.1% - 2.3%) (1% - 2%) (0.7% - 1.6%) (

2.8% 2% 1.9% 1.6% 1.4% 

(1.8% - 3.8%) (1.3% - 2.7%) (1.2% - 2.5%) (1% - 2.1%) (0.9% - 1.9%) (

3.3% 2.8% 2.5% 2.1% 2.1% 

(2.1% - 4.4%) (1.8% - 3.8%) (1.6% - 3.4%) (1.4% - 2.9%) (1.4% - 2.9%) (

1.8% 1.8% 1.8% 1.6% 1.6% 

(1.2% - 2.5%) (1.2% - 2.5%) (1.2% - 2.5%) (1.1% - 2.2%) (1% - 2.1%) (

4.5% 1.7% 1.7% 1.7% 1.2% 

(2.9% - 6%) (1.1% - 2.3%) (1.1% - 2.3%) (1.1% - 2.3%) (0.7% - 1.6%) (

2.8% 1% 1% 1% 0.6% 

(1.8% - 3.8%) (0.7% - 1.4%) (0.7% - 1.4%) (0.7% - 1.4%) (0.4% - 0.8%) (

3.4% 2.9% 2.2% 1.9% 2.2% 

(2.2% - 4.6%) (1.9% - 3.9%) (1.4% - 3%) (1.2% - 2.5%) (1.4% - 2.9%) (

1.7% 1% 1% 1% 0.6% 

(1.1% - 2.3%) (0.7% - 1.4%) (0.7% - 1.4%) (0.7% - 1.4%) (0.4% - 0.8%) (

Percent of Total Incidence of All-Cause Mortality Associated with Long-Term Exposure to PM2.5 Conc

Recent Year and PM2.5 Concentrations that Just Meet the Current and Alternative Annual (n) and Daily 

(Standard Combination Denoted n/m):

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL Baltimore, MD Detroit, MI Houston, TX New York, NY St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT

E-8

September 2009 
Table E-7. Percent Reduction from the Current Standards: Estimated Annual Incidence of All Cause Mortality Associated w

 Long-Term Exposure to Ambient PM2.5 Concentrations, Based on Adjusting 2005 PM2.5 Concentrations: Estimates B

 Krewski et al. (2009), Using Ambient PM2.5 from 1979 - 19831

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 1

-13% 0% 22% 32% 22% 3

(-13% - -13%) (0% - 0%) (21% - 22%) (32% - 33%) (21% - 22%) (34% 

-9% 0% 19% 30% 22% 4

(-9% - -9%) (0% - 0%) (19% - 20%) (30% - 31%) (22% - 22%) (45% 

-40% 0% 22% 33% 22% 4

(-40% - -41%) (0% - 0%) (22% - 22%) (33% - 33%) (22% - 22%) (43% 

0% 0% 0% 11% 0% 1

(0% - 0%) (0% - 0%) (0% - 0%) (11% - 12%) (0% - 0%) (11% 

-39% 0% 14% 26% 24% 4

(-38% - -39%) (0% - 0%) (14% - 14%) (26% - 27%) (24% - 25%) (49% 

-191% 0% 0% 0% 35% 6

(-189% - -192%) (0% - 0%) (0% - 0%) (0% - 0%) (35% - 35%) (69% 

-9% 0% 22% 33% 22% 3

(-9% - -9%) (0% - 0%) (22% - 22%) (33% - 33%) (22% - 22%) (33% 

-119% 0% 0% 12% 30% 6

(-118% - -120%) (0% - 0%) (0% - 0%) (12% - 12%) (30% - 30%) (60% 

-38% 0% 5% 20% 28% 5

(-38% - -39%) (0% - 0%) (5% - 5%) (20% - 20%) (28% - 28%) (55% 

-15% 0% 11% 24% 25% 5

(-15% - -15%) (0% - 0%) (11% - 11%) (24% - 24%) (25% - 25%) (50% 

0% 0% 0% 10% 13% 4

(0% - 0%) (0% - 0%) (0% - 0%) (10% - 10%) (13% - 13%) (46% 

-145% 0% 0% 0% 29% 5

(-143% - -146%) (0% - 0%) (0% - 0%) (0% - 0%) (29% - 30%) (59% 

-193% 0% 0% 0% 49% 9

(-192% - -194%) (0% - 0%) (0% - 0%) (0% - 0%) (49% - 49%) (98% 

-18% 0% 21% 32% 23% 4

(-18% - -18%) (0% - 0%) (21% - 21%) (32% - 32%) (23% - 23%) (46% 

-54% 0% 0% 0% 34% 6

(-54% - -54%) (0% - 0%) (0% - 0%) (0% - 0%) (34% - 34%) (68% 

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009). Percents are rounded to th

whole number.

 Dallas, TX Fresno, CA Los Angeles, CA

Percent Reduction from the Current Standards: Annual Incidence of All Cause Mortality Associated with L

Exposure to PM2.5 Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the Curre

Alternative Annual (n) and Daily (m) Standards (Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

E-9

September 2009 
Table E-8. Percent Reduction from the Current Standards: Estimated Annual Incidence of All Cause Mortality Associated w

 Long-Term Exposure to Ambient PM2.5 Concentrations, Based on Adjusting 2006 PM2.5 Concentrations: Estimates B

 Krewski et al. (2009), Using Ambient PM2.5 from 1979 - 19831 

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 1

-13% 0% 22% 33% 22% 3

(-13% - -13%) (0% - 0%) (22% - 22%) (33% - 33%) (22% - 22%) (35% 

-9% 0% 21% 32% 24% 4

(-9% - -9%) (0% - 0%) (20% - 21%) (32% - 32%) (24% - 24%) (47% 

-41% 0% 22% 34% 22% 4

(-41% - -41%) (0% - 0%) (22% - 22%) (33% - 34%) (22% - 22%) (44% 

0% 0% 0% 13% 0% 1

(0% - 0%) (0% - 0%) (0% - 0%) (13% - 13%) (0% - 0%) (13% 

-45% 0% 16% 31% 28% 5

(-45% - -45%) (0% - 0%) (16% - 16%) (31% - 31%) (28% - 28%) (57% 

-182% 0% 0% 0% 33% 6

(-181% - -184%) (0% - 0%) (0% - 0%) (0% - 0%) (33% - 33%) (66% 

-9% 0% 22% 33% 22% 3

(-9% - -9%) (0% - 0%) (22% - 22%) (33% - 33%) (22% - 22%) (33% 

-131% 0% 0% 13% 33% 6

(-130% - -131%) (0% - 0%) (0% - 0%) (13% - 13%) (33% - 33%) (66% 

-42% 0% 5% 22% 30% 6

(-42% - -42%) (0% - 0%) (5% - 5%) (22% - 22%) (30% - 30%) (61% 

-15% 0% 11% 24% 25% 5

(-15% - -15%) (0% - 0%) (11% - 11%) (24% - 24%) (25% - 25%) (50% 

0% 0% 0% 10% 13% 4

(0% - 0%) (0% - 0%) (0% - 0%) (10% - 10%) (13% - 13%) (45% 

-162% 0% 0% 0% 33% 6

(-161% - -163%) (0% - 0%) (0% - 0%) (0% - 0%) (33% - 33%) (66% 

-274% 0% 0% 0% 69% 1

(-273% - -275%) (0% - 0%) (0% - 0%) (0% - 0%) (69% - 69%) (100% 

-21% 0% 23% 36% 26% 5

(-20% - -21%) (0% - 0%) (23% - 23%) (36% - 36%) (26% - 26%) (52% 

-80% 0% 0% 0% 50% 1

(-80% - -80%) (0% - 0%) (0% - 0%) (0% - 0%) (50% - 50%) (100% 

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009). Percents are rounded to th

whole number.

 Dallas, TX Fresno, CA Los Angeles, CA

Percent Reduction from the Current Standards: Annual Incidence of All Cause Mortality Associated with L

Exposure to PM2.5 Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the Curre

Alternative Annual (n) and Daily (m) Standards (Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

E-10

September 2009 
Table E-9. Percent Reduction from the Current Standards: Estimated Annual Incidence of All Cause Mortality Associated w

 Long-Term Exposure to Ambient PM2.5 Concentrations, Based on Adjusting 2007 PM2.5 Concentrations: Estimates B

 Krewski et al. (2009), Using Ambient PM2.5 from 1979 - 19831 

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 1

-13% 0% 22% 33% 22% 3

(-13% - -13%) (0% - 0%) (22% - 22%) (33% - 33%) (22% - 22%) (35% 

-10% 0% 21% 33% 24% 4

(-10% - -10%) (0% - 0%) (21% - 21%) (33% - 33%) (24% - 24%) (49% 

-41% 0% 23% 34% 23% 4

(-41% - -42%) (0% - 0%) (22% - 23%) (34% - 34%) (22% - 23%) (44% 

0% 0% 0% 12% 0% 1

(0% - 0%) (0% - 0%) (0% - 0%) (12% - 13%) (0% - 0%) (12% 

-47% 0% 17% 32% 29% 5

(-46% - -47%) (0% - 0%) (17% - 17%) (32% - 32%) (29% - 29%) (59% 

-166% 0% 0% 0% 30% 6

(-165% - -168%) (0% - 0%) (0% - 0%) (0% - 0%) (30% - 30%) (61% 

-9% 0% 22% 33% 22% 3

(-9% - -9%) (0% - 0%) (22% - 22%) (33% - 33%) (22% - 22%) (33% 

-129% 0% 0% 13% 33% 6

(-128% - -130%) (0% - 0%) (0% - 0%) (13% - 13%) (33% - 33%) (65% 

-42% 0% 5% 22% 30% 6

(-42% - -42%) (0% - 0%) (5% - 5%) (22% - 22%) (30% - 30%) (60% 

-15% 0% 11% 25% 25% 5

(-15% - -15%) (0% - 0%) (11% - 11%) (24% - 25%) (25% - 25%) (51% 

0% 0% 0% 11% 14% 4

(0% - 0%) (0% - 0%) (0% - 0%) (11% - 11%) (14% - 14%) (49% 

-160% 0% 0% 0% 32% 6

(-158% - -161%) (0% - 0%) (0% - 0%) (0% - 0%) (32% - 33%) (65% 

-173% 0% 0% 0% 44% 8

(-172% - -174%) (0% - 0%) (0% - 0%) (0% - 0%) (44% - 44%) (88% 

-20% 0% 23% 35% 25% 5

(-20% - -20%) (0% - 0%) (23% - 23%) (35% - 35%) (25% - 25%) (50% 

-71% 0% 0% 0% 44% 8

(-70% - -71%) (0% - 0%) (0% - 0%) (0% - 0%) (44% - 44%) (89% 

Percent Reduction from the Current Standards: Annual Incidence of All Cause Mortality Associated with L

Exposure to PM2.5 Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the Curre

Alternative Annual (n) and Daily (m) Standards (Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009). Percents are rounded to th

whole number.

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

E-11

September 2009 
Figure E-1. Estimated Percent Reductions From the Current Standard to Alternative 

Standards in All Cause Mortality Associated with Long-Term Exposure to PM2.5

(Exposure Period: 1979 – 1983): Based on 2005 Air Quality Data* 

-200%

-180%

-160%

-140%

-120%

-100%

-80%

-60%

-40%

-20%

0%

20%

40%

60%

80%

100%

2005 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Reduction from Current Standard

 Atlanta, GA 572 (371 - 770); 3.8% (2.5% - 5.1%)

 Baltimore, MD 543 (352 - 732); 3.8% (2.5% - 5.2%)

 Birmingham, AL 352 (228 - 474); 3.6% (2.3% - 4.8%)

 Dallas, TX 366 (237 - 494); 2.9% (1.8% - 3.8%)

 Detroit, MI 544 (352 - 733); 3% (2% - 4.1%)

 Fresno, CA 86 (55 - 116); 1.5% (1% - 2.1%)

 Houston, TX 663 (430 - 893); 3.6% (2.3% - 4.8%)

 Los Angeles, CA 1116 (721 - 1507); 2% (1.3% - 2.7%)

 New York, NY 1247 (807 - 1684); 2.4% (1.5% - 3.2%)

 Philadelphia, PA 427 (276 - 576); 2.9% (1.9% - 4%)

 Phoenix, AZ 476 (308 - 643); 2.1% (1.3% - 2.8%)

 Pittsburgh, PA 285 (184 - 386); 2.1% (1.3% - 2.8%)

 Salt Lake City, UT 42 (27 - 57); 0.9% (0.6% - 1.2%)

 St. Louis, MO 669 (433 - 901); 3.6% (2.3% - 4.8%)

 Tacoma, WA 79 (51 - 107); 1.6% (1% - 2.1%)

*Based on Krewski et al. (2009), exposure period from 1979 – 1983. The legend contains, for each urban area, the 

incidence estimate (and 95% CI) and the estimate of percent of total incidence (and 95% CI) under the current 

standards. 

**The current standards consist of an annual standard of 15 μg/m3

 and a daily standard of 35 μg/m3. Combinations 

of an annual standard (n) and a daily standard (m) are denoted n/m in this figure. 

E-12

September 2009 Draft - Do Not Quote or Cite
Figure E-2. Estimated Percent Reductions From the Current Standard to Alternative 

Standards in All Cause Mortality Associated with Long-Term Exposure to PM2.5

(Exposure Period: 1979 – 1983): Based on 2006 Air Quality Data* 

-200%

-180%

-160%

-140%

-120%

-100%

-80%

-60%

-40%

-20%

0%

20%

40%

60%

80%

100%

2006 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Reduction from Current Standard

 Atlanta, GA 551 (357 - 743); 3.5% (2.3% - 4.8%)

 Baltimore, MD 470 (305 - 634); 3.3% (2.2% - 4.5%)

 Birmingham, AL 339 (220 - 457); 3.4% (2.2% - 4.6%)

 Dallas, TX 281 (181 - 379); 2.1% (1.4% - 2.9%)

 Detroit, MI 396 (256 - 534); 2.2% (1.4% - 3%)

 Fresno, CA 94 (60 - 127); 1.7% (1.1% - 2.2%)

 Houston, TX 701 (455 - 945); 3.6% (2.4% - 4.9%)

 Los Angeles, CA 950 (614 - 1285); 1.7% (1.1% - 2.2%)

 New York, NY 1047 (677 - 1415); 2% (1.3% - 2.7%)

 Philadelphia, PA 418 (270 - 563); 2.9% (1.9% - 3.9%)

 Phoenix, AZ 520 (336 - 703); 2.2% (1.4% - 2.9%)

 Pittsburgh, PA 231 (149 - 312); 1.7% (1.1% - 2.3%)

 Salt Lake City, UT 27 (18 - 37); 0.6% (0.4% - 0.8%)

 St. Louis, MO 508 (329 - 686); 2.7% (1.7% - 3.6%)

 Tacoma, WA 44 (28 - 59); 0.8% (0.5% - 1.1%)

*Based on Krewski et al. (2009), exposure period from 1979 – 1983. The legend contains, for each urban area, the 

incidence estimate (and 95% CI) and the estimate of percent of total incidence (and 95% CI) under the current 

standards. 

**The current standards consist of an annual standard of 15 μg/m3

 and a daily standard of 35 μg/m3. Combinations 

of an annual standard (n) and a daily standard (m) are denoted n/m in this figure. 

***The percent reduction for 2006 air quality in Salt Lake City is -274%. 

E-13

September 2009 Draft - Do Not Quote or Cite
Figure E-3. Estimated Percent Reductions From the Current Standard to Alternative 

Standards in All Cause Mortality Associated with Long-Term Exposure to PM2.5

(Exposure Period: 1979 – 1983): Based on 2007 Air Quality Data* 

-200%

-180%

-160%

-140%

-120%

-100%

-80%

-60%

-40%

-20%

0%

20%

40%

60%

80%

100%

2007 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Reduction from Current Standard

 Atlanta, GA 571 (370 - 769); 3.6% (2.3% - 4.8%)

 Baltimore, MD 439 (284 - 592); 3.1% (2% - 4.2%)

 Birmingham, AL 335 (217 - 451); 3.3% (2.2% - 4.5%)

 Dallas, TX 311 (201 - 420); 2.3% (1.5% - 3.1%)

 Detroit, MI 366 (236 - 494); 2.1% (1.3% - 2.8%)

 Fresno, CA 112 (73 - 152); 2% (1.3% - 2.6%)

 Houston, TX 687 (445 - 926); 3.5% (2.3% - 4.7%)

 Los Angeles, CA 979 (632 - 1323); 1.7% (1.1% - 2.3%)

 New York, NY 1067 (690 - 1442); 2% (1.3% - 2.7%)

 Philadelphia, PA 413 (267 - 557); 2.8% (1.8% - 3.8%)

 Phoenix, AZ 451 (292 - 610); 1.8% (1.2% - 2.5%)

 Pittsburgh, PA 236 (153 - 319); 1.7% (1.1% - 2.3%)

 Salt Lake City, UT 52 (34 - 71); 1% (0.7% - 1.4%)

 St. Louis, MO 545 (353 - 735); 2.9% (1.9% - 3.9%)

 Tacoma, WA 53 (34 - 72); 1% (0.7% - 1.4%)

*Based on Krewski et al. (2009), exposure period from 1979 – 1983. The legend contains, for each urban area, the 

incidence estimate (and 95% CI) and the estimate of percent of total incidence (and 95% CI) under the current 

standards. 

**The current standards consist of an annual standard of 15 μg/m3

 and a daily standard of 35 μg/m3. Combinations 

of an annual standard (n) and a daily standard (m) are denoted n/m in this figure. 

E-14

September 2009 Draft - Do Not Quote or Cite
Table E-10. Estimated Annual Incidence of All-Cause Mortality Associated with Long-Term Exposure to Ambient PM2.5 

 in a Recent Year (2005) and PM2.5 Concentrations that Just Meet the Current and Alternative Standards, Based 

 2005 PM2.5 Concentrations: Estimates Based on Krewski et al. (2009), Using Ambient PM2.5 from 1999 - 20001 

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

826 732 575 496 575 

(528 - 1117) (468 - 992) (367 - 780) (316 - 673) (367 - 780) 

757 696 561 485 541 

(484 - 1024) (444 - 942) (358 - 761) (309 - 659) (345 - 734) 

631 451 352 302 352 

(404 - 852) (288 - 611) (224 - 478) (193 - 411) (224 - 478) 

469 469 469 416 469 

(299 - 637) (299 - 637) (299 - 637) (265 - 565) (299 - 637) 

965 697 601 514 528 

(617 - 1306) (445 - 946) (383 - 817) (327 - 698) (336 - 717) 

318 110 110 110 72 

(204 - 430) (70 - 150) (70 - 150) (70 - 150) (46 - 98) 

923 849 663 569 663 

(590 - 1250) (542 - 1151) (422 - 900) (362 - 773) (422 - 900) 

3125 1432 1432 1265 1001 

(1999 - 4227) (911 - 1948) (911 - 1948) (804 - 1722) (636 - 1363) 

2211 1600 1521 1282 1159 

(1411 - 2998) (1019 - 2174) (969 - 2068) (815 - 1744) (737 - 1578) 

628 547 487 415 411 

(401 - 852) (349 - 743) (310 - 661) (264 - 564) (261 - 558) 

611 611 611 548 531 

(389 - 831) (389 - 831) (389 - 831) (349 - 746) (338 - 723) 

892 366 366 366 259 

(572 - 1205) (233 - 498) (233 - 498) (233 - 498) (164 - 352) 

158 54 54 54 28 

(101 - 214) (34 - 74) (34 - 74) (34 - 74) (18 - 38) 

1012 857 679 583 661 

(647 - 1369) (547 - 1161) (433 - 922) (371 - 792) (421 - 897) 

156 101 101 101 67 

(99 - 212) (64 - 138) (64 - 138) (64 - 138) (42 - 91) 

 Incidence of All-Cause Mortality Associated with Long-Term Exposure to PM2.5 Concentrations in a 

PM2.5 Concentrations that Just Meet the Current and Alternative Annual (n) and Daily (m) Standar

Combination Denoted n/m):

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL Baltimore, MD Detroit, MI Houston, TX New York, NY St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT

E-15

September 2009 
Table E-11. Estimated Annual Incidence of All-Cause Mortality Associated with Long-Term Exposure to Ambient PM2.5 

 in a Recent Year (2006) and PM2.5 Concentrations that Just Meet the Current and Alternative Standards, Based 

 2006 PM2.5 Concentrations: Estimates Based on Krewski et al. (2009), Using Ambient PM2.5 from 1999 - 20001 

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

798 706 551 473 551 

(510 - 1081) (451 - 957) (351 - 748) (301 - 642) (351 - 748) 

659 603 479 409 460 

(421 - 893) (385 - 817) (305 - 651) (261 - 557) (293 - 626) 

611 434 337 289 337 

(391 - 825) (277 - 589) (215 - 458) (184 - 392) (215 - 458) 

360 360 360 314 360 

(229 - 490) (229 - 490) (229 - 490) (199 - 427) (229 - 490) 

735 508 427 353 364 

(469 - 996) (323 - 690) (271 - 581) (224 - 480) (232 - 496) 

338 120 120 120 80 

(216 - 457) (76 - 164) (76 - 164) (76 - 164) (51 - 110) 

976 898 702 604 702 

(624 - 1321) (574 - 1217) (448 - 953) (384 - 820) (448 - 953) 

2805 1221 1221 1064 817 

(1793 - 3799) (776 - 1662) (776 - 1662) (676 - 1450) (519 - 1114) 

1910 1345 1272 1050 937 

(1217 - 2593) (855 - 1829) (809 - 1731) (668 - 1430) (595 - 1277) 

616 536 476 405 401 

(393 - 835) (341 - 727) (303 - 646) (258 - 551) (255 - 545) 

668 668 668 601 583 

(425 - 908) (425 - 908) (425 - 908) (382 - 818) (371 - 793) 

774 297 297 297 199 

(496 - 1047) (189 - 404) (189 - 404) (189 - 404) (126 - 272) 

131 35 35 35 11 

(83 - 178) (22 - 48) (22 - 48) (22 - 48) (7 - 15) 

785 652 500 417 484 

(501 - 1065) (415 - 885) (318 - 680) (265 - 568) (308 - 659) 

101 56 56 56 28 

(64 - 138) (36 - 77) (36 - 77) (36 - 77) (18 - 38) 

 Incidence of All-Cause Mortality Associated with Long-Term Exposure to PM2.5 Concentrations in a 

PM2.5 Concentrations that Just Meet the Current and Alternative Annual (n) and Daily (m) Standar

Combination Denoted n/m):

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL Baltimore, MD Detroit, MI Houston, TX New York, NY St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT

E-16

September 2009 
Table E-12. Estimated Annual Incidence of All-Cause Mortality Associated with Long-Term Exposure to Ambient PM2.5 

 in a Recent Year (2007) and PM2.5 Concentrations that Just Meet the Current and Alternative Standards, Based 

 2007 PM2.5 Concentrations: Estimates Based on Krewski et al. (2009), Using Ambient PM2.5 from 1999 - 20001 

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

826 731 571 490 571 

(528 - 1118) (467 - 990) (364 - 775) (312 - 666) (364 - 775) 

617 563 444 377 426 

(394 - 837) (359 - 764) (283 - 604) (240 - 513) (271 - 579) 

605 429 332 284 332 

(387 - 817) (274 - 581) (212 - 452) (181 - 386) (212 - 452) 

399 399 399 349 399 

(254 - 542) (254 - 542) (254 - 542) (222 - 475) (254 - 542) 

687 469 392 321 332 

(438 - 932) (299 - 638) (249 - 533) (204 - 437) (211 - 452) 

382 144 144 144 101 

(245 - 516) (92 - 196) (92 - 196) (92 - 196) (64 - 137) 

957 880 686 588 686 

(612 - 1297) (562 - 1193) (437 - 931) (374 - 799) (437 - 931) 

2867 1257 1257 1098 847 

(1833 - 3883) (799 - 1711) (799 - 1711) (698 - 1496) (538 - 1155) 

1942 1370 1296 1072 957 

(1238 - 2636) (871 - 1863) (824 - 1764) (681 - 1459) (608 - 1304) 

609 530 470 400 396 

(389 - 826) (338 - 719) (300 - 639) (255 - 544) (252 - 538) 

580 580 580 516 499 

(369 - 789) (369 - 789) (369 - 789) (328 - 703) (317 - 679) 

784 303 303 303 205 

(502 - 1061) (193 - 413) (193 - 413) (193 - 413) (130 - 280) 

183 67 67 67 38 

(116 - 248) (43 - 91) (43 - 91) (43 - 91) (24 - 52) 

837 698 540 455 524 

(534 - 1134) (445 - 948) (344 - 735) (289 - 619) (334 - 713) 

117 69 69 69 38 

(74 - 159) (44 - 94) (44 - 94) (44 - 94) (24 - 52) 

 Incidence of All-Cause Mortality Associated with Long-Term Exposure to PM2.5 Concentrations in a 

PM2.5 Concentrations that Just Meet the Current and Alternative Annual (n) and Daily (m) Standa

Combination Denoted n/m):

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL Baltimore, MD Detroit, MI Houston, TX New York, NY St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT

E-17

September 2009 
Table E-13. Estimated Percent of Total Annual Incidence of All-Cause Mortality Associated with Long-Term Exposure to 

 Concentrations in a Recent Year (2005) and PM2.5 Concentrations that Just Meet the Current and Alternative Sta

 on Adjusting 2005 PM2.5 Concentrations: Estimates Based on Krewski et al. (2009), Using Ambient PM2.5 from 19

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

5.5% 4.9% 3.8% 3.3% 3.8% 

(3.5% - 7.4%) (3.1% - 6.6%) (2.4% - 5.2%) (2.1% - 4.5%) (2.4% - 5.2%) 

5.4% 4.9% 4% 3.4% 3.8% 

(3.4% - 7.3%) (3.1% - 6.7%) (2.5% - 5.4%) (2.2% - 4.7%) (2.4% - 5.2%) 

6.4% 4.6% 3.6% 3.1% 3.6% 

(4.1% - 8.7%) (2.9% - 6.2%) (2.3% - 4.9%) (2% - 4.2%) (2.3% - 4.9%) 

3.7% 3.7% 3.7% 3.2% 3.7% 

(2.3% - 5%) (2.3% - 5%) (2.3% - 5%) (2.1% - 4.4%) (2.3% - 5%) 

5.4% 3.9% 3.4% 2.9% 3% 

(3.5% - 7.3%) (2.5% - 5.3%) (2.1% - 4.6%) (1.8% - 3.9%) (1.9% - 4%) 

5.7% 2% 2% 2% 1.3% 

(3.7% - 7.7%) (1.3% - 2.7%) (1.3% - 2.7%) (1.3% - 2.7%) (0.8% - 1.8%) 

5% 4.6% 3.6% 3.1% 3.6% 

(3.2% - 6.7%) (2.9% - 6.2%) (2.3% - 4.8%) (1.9% - 4.1%) (2.3% - 4.8%) 

5.5% 2.5% 2.5% 2.2% 1.8% 

(3.5% - 7.4%) (1.6% - 3.4%) (1.6% - 3.4%) (1.4% - 3%) (1.1% - 2.4%) 

4.2% 3% 2.9% 2.4% 2.2% 

(2.7% - 5.7%) (1.9% - 4.1%) (1.8% - 3.9%) (1.5% - 3.3%) (1.4% - 3%) 

4.3% 3.8% 3.3% 2.8% 2.8% 

(2.8% - 5.8%) (2.4% - 5.1%) (2.1% - 4.5%) (1.8% - 3.9%) (1.8% - 3.8%) 

2.6% 2.6% 2.6% 2.4% 2.3% 

(1.7% - 3.6%) (1.7% - 3.6%) (1.7% - 3.6%) (1.5% - 3.2%) (1.5% - 3.1%) 

6.4% 2.6% 2.6% 2.6% 1.9% 

(4.1% - 8.7%) (1.7% - 3.6%) (1.7% - 3.6%) (1.7% - 3.6%) (1.2% - 2.5%) 

3.3% 1.1% 1.1% 1.1% 0.6% 

(2.1% - 4.5%) (0.7% - 1.6%) (0.7% - 1.6%) (0.7% - 1.6%) (0.4% - 0.8%) 

5.4% 4.5% 3.6% 3.1% 3.5% 

(3.4% - 7.3%) (2.9% - 6.2%) (2.3% - 4.9%) (2% - 4.2%) (2.2% - 4.8%) 

3.1% 2% 2% 2% 1.3% 

(1.9% - 4.2%) (1.3% - 2.7%) (1.3% - 2.7%) (1.3% - 2.7%) (0.8% - 1.8%) 

Percent of Total Incidence of All-Cause Mortality Associated with Long-Term Exposure to PM2.5 Co

Recent Year and PM2.5 Concentrations that Just Meet the Current and Alternative Annual (n) and Da

(Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

E-18

September 2009 
Table E-14. Estimated Percent of Total Annual Incidence of All-Cause Mortality Associated with Long-Term Exposure to 

 Concentrations in a Recent Year (2006) and PM2.5 Concentrations that Just Meet the Current and Alternative Sta

 on Adjusting 2006 PM2.5 Concentrations: Estimates Based on Krewski et al. (2009), Using Ambient PM2.5 from 19

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

5.1% 4.5% 3.5% 3% 3.5% 

(3.3% - 7%) (2.9% - 6.2%) (2.3% - 4.8%) (1.9% - 4.1%) (2.3% - 4.8%) 

4.7% 4.3% 3.4% 2.9% 3.3% 

(3% - 6.3%) (2.7% - 5.8%) (2.2% - 4.6%) (1.8% - 3.9%) (2.1% - 4.4%) 

6.1% 4.4% 3.4% 2.9% 3.4% 

(3.9% - 8.3%) (2.8% - 5.9%) (2.2% - 4.6%) (1.8% - 3.9%) (2.2% - 4.6%) 

2.7% 2.7% 2.7% 2.4% 2.7% 

(1.7% - 3.7%) (1.7% - 3.7%) (1.7% - 3.7%) (1.5% - 3.3%) (1.7% - 3.7%) 

4.1% 2.8% 2.4% 2% 2% 

(2.6% - 5.6%) (1.8% - 3.9%) (1.5% - 3.3%) (1.3% - 2.7%) (1.3% - 2.8%) 

6% 2.1% 2.1% 2.1% 1.4% 

(3.8% - 8.1%) (1.4% - 2.9%) (1.4% - 2.9%) (1.4% - 2.9%) (0.9% - 1.9%) 

5.1% 4.7% 3.6% 3.1% 3.6% 

(3.2% - 6.9%) (3% - 6.3%) (2.3% - 4.9%) (2% - 4.3%) (2.3% - 4.9%) 

4.9% 2.1% 2.1% 1.9% 1.4% 

(3.1% - 6.7%) (1.4% - 2.9%) (1.4% - 2.9%) (1.2% - 2.5%) (0.9% - 2%) 

3.6% 2.5% 2.4% 2% 1.8% 

(2.3% - 4.9%) (1.6% - 3.4%) (1.5% - 3.3%) (1.3% - 2.7%) (1.1% - 2.4%) 

4.2% 3.7% 3.3% 2.8% 2.8% 

(2.7% - 5.7%) (2.3% - 5%) (2.1% - 4.4%) (1.8% - 3.8%) (1.8% - 3.7%) 

2.8% 2.8% 2.8% 2.5% 2.4% 

(1.8% - 3.8%) (1.8% - 3.8%) (1.8% - 3.8%) (1.6% - 3.4%) (1.5% - 3.3%) 

5.6% 2.1% 2.1% 2.1% 1.4% 

(3.6% - 7.6%) (1.4% - 2.9%) (1.4% - 2.9%) (1.4% - 2.9%) (0.9% - 2%) 

2.7% 0.7% 0.7% 0.7% 0.2% 

(1.7% - 3.6%) (0.5% - 1%) (0.5% - 1%) (0.5% - 1%) (0.1% - 0.3%) 

4.1% 3.4% 2.6% 2.2% 2.6% 

(2.6% - 5.6%) (2.2% - 4.7%) (1.7% - 3.6%) (1.4% - 3%) (1.6% - 3.5%) 

2% 1.1% 1.1% 1.1% 0.5% 

(1.2% - 2.7%) (0.7% - 1.5%) (0.7% - 1.5%) (0.7% - 1.5%) (0.3% - 0.7%) 

Percent of Total Incidence of All-Cause Mortality Associated with Long-Term Exposure to PM2.5 Co

Recent Year and PM2.5 Concentrations that Just Meet the Current and Alternative Annual (n) and Da

(Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

E-19

September 2009 
Table E-15. Estimated Percent of Total Annual Incidence of All-Cause Mortality Associated with Long-Term Exposure to 

 Concentrations in a Recent Year (2007) and PM2.5 Concentrations that Just Meet the Current and Alternative Sta

 on Adjusting 2007 PM2.5 Concentrations: Estimates Based on Krewski et al. (2009), Using Ambient PM2.5 from 19

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

5.2% 4.6% 3.6% 3.1% 3.6% 

(3.3% - 7%) (2.9% - 6.2%) (2.3% - 4.9%) (2% - 4.2%) (2.3% - 4.9%) 

4.4% 4% 3.1% 2.7% 3% 

(2.8% - 5.9%) (2.5% - 5.4%) (2% - 4.3%) (1.7% - 3.6%) (1.9% - 4.1%) 

6% 4.3% 3.3% 2.8% 3.3% 

(3.9% - 8.2%) (2.7% - 5.8%) (2.1% - 4.5%) (1.8% - 3.9%) (2.1% - 4.5%) 

3% 3% 3% 2.6% 3% 

(1.9% - 4.1%) (1.9% - 4.1%) (1.9% - 4.1%) (1.7% - 3.6%) (1.9% - 4.1%) 

3.9% 2.7% 2.2% 1.8% 1.9% 

(2.5% - 5.3%) (1.7% - 3.6%) (1.4% - 3%) (1.2% - 2.5%) (1.2% - 2.6%) 

6.7% 2.5% 2.5% 2.5% 1.8% 

(4.3% - 9%) (1.6% - 3.4%) (1.6% - 3.4%) (1.6% - 3.4%) (1.1% - 2.4%) 

4.9% 4.5% 3.5% 3% 3.5% 

(3.1% - 6.6%) (2.9% - 6.1%) (2.2% - 4.7%) (1.9% - 4.1%) (2.2% - 4.7%) 

5% 2.2% 2.2% 1.9% 1.5% 

(3.2% - 6.8%) (1.4% - 3%) (1.4% - 3%) (1.2% - 2.6%) (0.9% - 2%) 

3.6% 2.6% 2.4% 2% 1.8% 

(2.3% - 4.9%) (1.6% - 3.5%) (1.5% - 3.3%) (1.3% - 2.7%) (1.1% - 2.4%) 

4.2% 3.6% 3.2% 2.8% 2.7% 

(2.7% - 5.7%) (2.3% - 4.9%) (2.1% - 4.4%) (1.8% - 3.7%) (1.7% - 3.7%) 

2.3% 2.3% 2.3% 2.1% 2% 

(1.5% - 3.2%) (1.5% - 3.2%) (1.5% - 3.2%) (1.3% - 2.8%) (1.3% - 2.8%) 

5.7% 2.2% 2.2% 2.2% 1.5% 

(3.6% - 7.7%) (1.4% - 3%) (1.4% - 3%) (1.4% - 3%) (0.9% - 2%) 

3.6% 1.3% 1.3% 1.3% 0.7% 

(2.3% - 4.9%) (0.8% - 1.8%) (0.8% - 1.8%) (0.8% - 1.8%) (0.5% - 1%) 

4.4% 3.7% 2.9% 2.4% 2.8% 

(2.8% - 6%) (2.3% - 5%) (1.8% - 3.9%) (1.5% - 3.3%) (1.8% - 3.8%) 

2.2% 1.3% 1.3% 1.3% 0.7% 

(1.4% - 3%) (0.8% - 1.8%) (0.8% - 1.8%) (0.8% - 1.8%) (0.5% - 1%) 

Percent of Total Incidence of All-Cause Mortality Associated with Long-Term Exposure to PM2.5 Conc

Recent Year and PM2.5 Concentrations that Just Meet the Current and Alternative Annual (n) and Dail

(Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

E-20

September 2009 
Table E-16. Percent Reduction from the Current Standards: Estimated Annual Incidence of All Cause Mortality Associat

 Long-Term Exposure to Ambient PM2.5 Concentrations, Based on Adjusting 2005 PM2.5 Concentrations: Estimate

 Krewski et al. (2009), Using Ambient PM2.5 from 1999 - 20001 

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

-13% 0% 21% 32% 21% 

(-13% - -13%) (0% - 0%) (21% - 22%) (32% - 33%) (21% - 22%) (3

-9% 0% 19% 30% 22% 

(-9% - -9%) (0% - 0%) (19% - 19%) (30% - 30%) (22% - 22%) (4

-40% 0% 22% 33% 22% 

(-39% - -40%) (0% - 0%) (22% - 22%) (33% - 33%) (22% - 22%) (4

0% 0% 0% 11% 0% 

(0% - 0%) (0% - 0%) (0% - 0%) (11% - 11%) (0% - 0%) (

-38% 0% 14% 26% 24% 

(-38% - -39%) (0% - 0%) (14% - 14%) (26% - 26%) (24% - 24%) (4

-189% 0% 0% 0% 35% 

(-187% - -191%) (0% - 0%) (0% - 0%) (0% - 0%) (35% - 35%) (6

-9% 0% 22% 33% 22% 

(-9% - -9%) (0% - 0%) (22% - 22%) (33% - 33%) (22% - 22%) (3

-118% 0% 0% 12% 30% 

(-117% - -119%) (0% - 0%) (0% - 0%) (12% - 12%) (30% - 30%) (6

-38% 0% 5% 20% 28% 

(-38% - -38%) (0% - 0%) (5% - 5%) (20% - 20%) (27% - 28%) (5

-15% 0% 11% 24% 25% 

(-15% - -15%) (0% - 0%) (11% - 11%) (24% - 24%) (25% - 25%) (5

0% 0% 0% 10% 13% 

(0% - 0%) (0% - 0%) (0% - 0%) (10% - 10%) (13% - 13%) (4

-144% 0% 0% 0% 29% 

(-142% - -145%) (0% - 0%) (0% - 0%) (0% - 0%) (29% - 29%) (5

-192% 0% 0% 0% 49% 

(-191% - -193%) (0% - 0%) (0% - 0%) (0% - 0%) (49% - 49%) (9

-18% 0% 21% 32% 23% 

(-18% - -18%) (0% - 0%) (21% - 21%) (32% - 32%) (23% - 23%) (4

-54% 0% 0% 0% 34% 

(-53% - -54%) (0% - 0%) (0% - 0%) (0% - 0%) (34% - 34%) (6

Percent Reduction from the Current Standards: Annual Incidence of All Cause Mortality Associated wi

Exposure to PM2.5 Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the Cu

Alternative Annual (n) and Daily (m) Standards (Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

E-21

September 2009 
Table E-17. Percent Reduction from the Current Standards: Estimated Annual Incidence of All Cause Mortality Associat

 Long-Term Exposure to Ambient PM2.5 Concentrations, Based on Adjusting 2006 PM2.5 Concentrations: Estimate

 Krewski et al. (2009), Using Ambient PM2.5 from 1999 - 20001

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

-13% 0% 22% 33% 22% 

(-13% - -13%) (0% - 0%) (22% - 22%) (33% - 33%) (22% - 22%) (3

-9% 0% 20% 32% 24% 

(-9% - -9%) (0% - 0%) (20% - 21%) (32% - 32%) (23% - 24%) (4

-41% 0% 22% 34% 22% 

(-40% - -41%) (0% - 0%) (22% - 22%) (33% - 34%) (22% - 22%) (4

0% 0% 0% 13% 0% 

(0% - 0%) (0% - 0%) (0% - 0%) (13% - 13%) (0% - 0%) (

-45% 0% 16% 31% 28% 

(-44% - -45%) (0% - 0%) (16% - 16%) (30% - 31%) (28% - 28%) (5

-181% 0% 0% 0% 33% 

(-179% - -183%) (0% - 0%) (0% - 0%) (0% - 0%) (33% - 33%) (6

-9% 0% 22% 33% 22% 

(-9% - -9%) (0% - 0%) (22% - 22%) (33% - 33%) (22% - 22%) (3

-130% 0% 0% 13% 33% 

(-129% - -131%) (0% - 0%) (0% - 0%) (13% - 13%) (33% - 33%) (6

-42% 0% 5% 22% 30% 

(-42% - -42%) (0% - 0%) (5% - 5%) (22% - 22%) (30% - 30%) (6

-15% 0% 11% 24% 25% 

(-15% - -15%) (0% - 0%) (11% - 11%) (24% - 24%) (25% - 25%) (5

0% 0% 0% 10% 13% 

(0% - 0%) (0% - 0%) (0% - 0%) (10% - 10%) (13% - 13%) (4

-161% 0% 0% 0% 33% 

(-159% - -163%) (0% - 0%) (0% - 0%) (0% - 0%) (33% - 33%) (6

-273% 0% 0% 0% 69% 

(-272% - -274%) (0% - 0%) (0% - 0%) (0% - 0%) (69% - 69%) (10

-20% 0% 23% 36% 26% 

(-20% - -21%) (0% - 0%) (23% - 23%) (36% - 36%) (26% - 26%) (5

-80% 0% 0% 0% 50% 

(-80% - -80%) (0% - 0%) (0% - 0%) (0% - 0%) (50% - 50%) (10

Percent Reduction from the Current Standards: Annual Incidence of All Cause Mortality Associated wi

Exposure to PM2.5 Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the Cu

Alternative Annual (n) and Daily (m) Standards (Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

E-22

September 2009 
Table E-18. Percent Reduction from the Current Standards: Estimated Annual Incidence of All Cause Mortality Associat

 Long-Term Exposure to Ambient PM2.5 Concentrations, Based on Adjusting 2007 PM2.5 Concentrations: Estimate

 Krewski et al. (2009), Using Ambient PM2.5 from 1999 - 20001

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

-13% 0% 22% 33% 22% 

(-13% - -13%) (0% - 0%) (22% - 22%) (33% - 33%) (22% - 22%) (3

-10% 0% 21% 33% 24% 

(-10% - -10%) (0% - 0%) (21% - 21%) (33% - 33%) (24% - 24%) (4

-41% 0% 22% 34% 22% 

(-41% - -41%) (0% - 0%) (22% - 23%) (34% - 34%) (22% - 23%) (4

0% 0% 0% 12% 0% 

(0% - 0%) (0% - 0%) (0% - 0%) (12% - 13%) (0% - 0%) (

-46% 0% 17% 32% 29% 

(-46% - -47%) (0% - 0%) (16% - 17%) (32% - 32%) (29% - 29%) (5

-165% 0% 0% 0% 30% 

(-163% - -167%) (0% - 0%) (0% - 0%) (0% - 0%) (30% - 30%) (6

-9% 0% 22% 33% 22% 

(-9% - -9%) (0% - 0%) (22% - 22%) (33% - 33%) (22% - 22%) (3

-128% 0% 0% 13% 33% 

(-127% - -129%) (0% - 0%) (0% - 0%) (13% - 13%) (33% - 33%) (6

-42% 0% 5% 22% 30% 

(-41% - -42%) (0% - 0%) (5% - 5%) (22% - 22%) (30% - 30%) (6

-15% 0% 11% 24% 25% 

(-15% - -15%) (0% - 0%) (11% - 11%) (24% - 25%) (25% - 25%) (5

0% 0% 0% 11% 14% 

(0% - 0%) (0% - 0%) (0% - 0%) (11% - 11%) (14% - 14%) (4

-158% 0% 0% 0% 32% 

(-157% - -160%) (0% - 0%) (0% - 0%) (0% - 0%) (32% - 32%) (6

-172% 0% 0% 0% 44% 

(-171% - -174%) (0% - 0%) (0% - 0%) (0% - 0%) (44% - 44%) (8

-20% 0% 23% 35% 25% 

(-20% - -20%) (0% - 0%) (23% - 23%) (35% - 35%) (25% - 25%) (5

-70% 0% 0% 0% 44% 

(-70% - -71%) (0% - 0%) (0% - 0%) (0% - 0%) (44% - 44%) (8

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Percent Reduction from the Current Standards: Annual Incidence of All Cause Mortality Associated wi

Exposure to PM2.5 Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the Cu

Alternative Annual (n) and Daily (m) Standards (Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

E-23

September 2009 
Figure E-4. Estimated Percent Reductions From the Current Standard to Alternative 

Standards in All Cause Mortality Associated with Long-Term Exposure to PM2.5 (Exposure 

Period: 1999 – 2000): Based on 2005 Air Quality Data* 

-200%

-180%

-160%

-140%

-120%

-100%

-80%

-60%

-40%

-20%

0%

20%

40%

60%

80%

100%

2005 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Reduction from Current Standard

 Atlanta, GA 732 (468 - 992); 4.9% (3.1% - 6.6%)

 Baltimore, MD 696 (444 - 942); 4.9% (3.1% - 6.7%)

 Birmingham, AL 451 (288 - 611); 4.6% (2.9% - 6.2%)

 Dallas, TX 469 (299 - 637); 3.7% (2.3% - 5%)

 Detroit, MI 697 (445 - 946); 3.9% (2.5% - 5.3%)

 Fresno, CA 110 (70 - 150); 2% (1.3% - 2.7%)

 Houston, TX 849 (542 - 1151); 4.6% (2.9% - 6.2%)

 Los Angeles, CA 1432 (911 - 1948); 2.5% (1.6% - 3.4%)

 New York, NY 1600 (1019 - 2174); 3% (1.9% - 4.1%)

 Philadelphia, PA 547 (349 - 743); 3.8% (2.4% - 5.1%)

 Phoenix, AZ 611 (389 - 831); 2.6% (1.7% - 3.6%)

 Pittsburgh, PA 366 (233 - 498); 2.6% (1.7% - 3.6%)

 Salt Lake City, UT 54 (34 - 74); 1.1% (0.7% - 1.6%)

 St. Louis, MO 857 (547 - 1161); 4.5% (2.9% - 6.2%)

 Tacoma, WA 101 (64 - 138); 2% (1.3% - 2.7%)

*Based on Krewski et al. (2009), exposure period from 1999 - 2000. The legend contains, for each urban area, the 

incidence estimate (and 95% CI) and the estimate of percent of total incidence (and 95% CI) under the current 

standards. 

**The current standards consist of an annual standard of 15 μg/m3

 and a daily standard of 35 μg/m3. Combinations of 

an annual standard (n) and a daily standard (m) are denoted n/m in this figure. 

E-24

September 2009 Draft - Do Not Quote or Cite
Figure E-5. Estimated Percent Reductions From the Current Standard to Alternative 

Standards in All Cause Mortality Associated with Long-Term Exposure to PM2.5 (Exposure 

Period: 1999 – 2000): Based on 2006 Air Quality Data* 

-200%

-180%

-160%

-140%

-120%

-100%

-80%

-60%

-40%

-20%

0%

20%

40%

60%

80%

100%

2006 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Reduction from Current Standard

 Atlanta, GA 706 (451 - 957); 4.5% (2.9% - 6.2%)

 Baltimore, MD 603 (385 - 817); 4.3% (2.7% - 5.8%)

 Birmingham, AL 434 (277 - 589); 4.4% (2.8% - 5.9%)

 Dallas, TX 360 (229 - 490); 2.7% (1.7% - 3.7%)

 Detroit, MI 508 (323 - 690); 2.8% (1.8% - 3.9%)

 Fresno, CA 120 (76 - 164); 2.1% (1.4% - 2.9%)

 Houston, TX 898 (574 - 1217); 4.7% (3% - 6.3%)

 Los Angeles, CA 1221 (776 - 1662); 2.1% (1.4% - 2.9%)

 New York, NY 1345 (855 - 1829); 2.5% (1.6% - 3.4%)

 Philadelphia, PA 536 (341 - 727); 3.7% (2.3% - 5%)

 Phoenix, AZ 668 (425 - 908); 2.8% (1.8% - 3.8%)

 Pittsburgh, PA 297 (189 - 404); 2.1% (1.4% - 2.9%)

 Salt Lake City, UT 35 (22 - 48); 0.7% (0.5% - 1%)

 St. Louis, MO 652 (415 - 885); 3.4% (2.2% - 4.7%)

 Tacoma, WA 56 (36 - 77); 1.1% (0.7% - 1.5%)

*Based on Krewski et al. (2009), exposure period from 1999 - 2000. The legend contains, for each urban area, the 

incidence estimate (and 95% CI) and the estimate of percent of total incidence (and 95% CI) under the current 

standards. 

**The current standards consist of an annual standard of 15 μg/m3

 and a daily standard of 35 μg/m3. Combinations of 

an annual standard (n) and a daily standard (m) are denoted n/m in this figure. 

***The percent reduction for 2006 air quality in Salt Lake City is -274%. 

E-25

September 2009 Draft - Do Not Quote or Cite
Figure E-6. Estimated Percent Reductions From the Current Standard to Alternative 

Standards in All Cause Mortality Associated with Long-Term Exposure to PM2.5 (Exposure 

Period: 1999 – 2000): Based on 2007 Air Quality Data* 

-200%

-180%

-160%

-140%

-120%

-100%

-80%

-60%

-40%

-20%

0%

20%

40%

60%

80%

100%

2007 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Redcution from Current Standard

 Atlanta, GA 731 (467 - 990); 4.6% (2.9% - 6.2%)

 Baltimore, MD 563 (359 - 764); 4% (2.5% - 5.4%)

 Birmingham, AL 429 (274 - 581); 4.3% (2.7% - 5.8%)

 Dallas, TX 399 (254 - 542); 3% (1.9% - 4.1%)

 Detroit, MI 469 (299 - 638); 2.7% (1.7% - 3.6%)

 Fresno, CA 144 (92 - 196); 2.5% (1.6% - 3.4%)

 Houston, TX 880 (562 - 1193); 4.5% (2.9% - 6.1%)

 Los Angeles, CA 1257 (799 - 1711); 2.2% (1.4% - 3%)

 New York, NY 1370 (871 - 1863); 2.6% (1.6% - 3.5%)

 Philadelphia, PA 530 (338 - 719); 3.6% (2.3% - 4.9%)

 Phoenix, AZ 580 (369 - 789); 2.3% (1.5% - 3.2%)

 Pittsburgh, PA 303 (193 - 413); 2.2% (1.4% - 3%)

 Salt Lake City, UT 67 (43 - 91); 1.3% (0.8% - 1.8%)

 St. Louis, MO 698 (445 - 948); 3.7% (2.3% - 5%)

 Tacoma, WA 69 (44 - 94); 1.3% (0.8% - 1.8%)

*Based on Krewski et al. (2009), exposure period from 1999 - 2000. The legend contains, for each urban area, the 

incidence estimate (and 95% CI) and the estimate of percent of total incidence (and 95% CI) under the current 

standards. 

**The current standards consist of an annual standard of 15 μg/m3

 and a daily standard of 35 μg/m3. Combinations of 

an annual standard (n) and a daily standard (m) are denoted n/m in this figure. 

E-26

September 2009 Draft - Do Not Quote or Cite
Table E-19. Estimated Annual Incidence of Ischemic Heart Disease Mortality Associated with Long-Term Exposure to 

 Concentrations in a Recent Year (2005) and PM2.5 Concentrations that Just Meet the Current and Alternative 

 on Adjusting 2005 PM2.5 Concentrations: Estimates Based on Krewski et al. (2009), Using Ambient PM2.5 from 

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

247 221 175 152 175 

(204 - 290) (181 - 259) (144 - 206) (124 - 179) (144 - 206) 

393 363 296 257 285 

(323 - 461) (298 - 426) (242 - 348) (210 - 303) (234 - 336) 

214 156 123 106 123 

(177 - 250) (128 - 183) (101 - 145) (87 - 125) (101 - 145) 

224 224 224 199 224 

(183 - 264) (183 - 264) (183 - 264) (163 - 235) (183 - 264) 

653 479 416 357 366 

(538 - 766) (393 - 564) (340 - 490) (291 - 421) (299 - 432) 

183 66 66 66 43 

(151 - 215) (54 - 78) (54 - 78) (54 - 78) (35 - 51) 

435 402 317 273 317 

(357 - 510) (330 - 472) (259 - 373) (223 - 322) (259 - 373) 

2217 1048 1048 928 738 

(1824 - 2596) (855 - 1238) (855 - 1238) (757 - 1098) (601 - 874) 

2273 1665 1586 1342 1217 

(1863 - 2672) (1360 - 1964) (1295 - 1871) (1095 - 1586) (992 - 1439) 

314 275 246 211 209 

(258 - 369) (225 - 324) (201 - 290) (172 - 249) (170 - 246) 

346 346 346 312 302 

(283 - 409) (283 - 409) (283 - 409) (254 - 368) (246 - 357) 

508 217 217 217 154 

(419 - 593) (177 - 256) (177 - 256) (177 - 256) (126 - 183) 

48 17 17 17 9 

(39 - 56) (14 - 20) (14 - 20) (14 - 20) (7 - 10) 

610 521 417 360 406 

(502 - 715) (428 - 612) (341 - 491) (294 - 425) (333 - 479) 

91 60 60 60 40 

(74 - 108) (49 - 71) (49 - 71) (49 - 71) (32 - 47) 

 Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Detroit, MI Houston, TX New York, NY St. Louis, MO

 Incidence of Ischemic Heart Disease Mortality Associated with Long-Term Exposure to PM2.5 Co

Recent Year and PM2.5 Concentrations that Just Meet the Current and Alternative Annual (n) and D

(Standard Combination Denoted n/m):

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL Baltimore, MD

E-27

September 2009 
Table E-20. Estimated Annual Incidence of Ischemic Heart Disease Mortality Associated with Long-Term Exposure to 

 Concentrations in a Recent Year (2006) and PM2.5 Concentrations that Just Meet the Current and Alternative 

 on Adjusting 2006 PM2.5 Concentrations: Estimates Based on Krewski et al. (2009), Using Ambient PM2.5 from 

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

240 214 168 145 168 

(197 - 282) (175 - 251) (138 - 198) (119 - 171) (138 - 198) 

345 317 254 218 244 

(283 - 405) (260 - 372) (208 - 299) (178 - 257) (200 - 288) 

208 151 118 102 118 

(172 - 243) (124 - 177) (97 - 139) (83 - 120) (97 - 139) 

173 173 173 151 173 

(142 - 205) (142 - 205) (142 - 205) (124 - 179) (142 - 205) 

504 353 298 247 255 

(413 - 593) (288 - 417) (243 - 352) (202 - 293) (208 - 302) 

194 72 72 72 48 

(160 - 227) (59 - 85) (59 - 85) (59 - 85) (39 - 57) 

459 424 335 290 335 

(377 - 538) (348 - 498) (274 - 395) (237 - 342) (274 - 395) 

2002 897 897 784 605 

(1645 - 2349) (731 - 1060) (731 - 1060) (638 - 928) (492 - 717) 

1976 1407 1333 1105 988 

(1617 - 2327) (1148 - 1662) (1087 - 1575) (900 - 1308) (804 - 1170) 

308 270 241 206 204 

(253 - 362) (221 - 317) (197 - 284) (168 - 243) (166 - 241) 

378 378 378 341 331 

(309 - 446) (309 - 446) (309 - 446) (278 - 403) (270 - 391) 

445 177 177 177 119 

(366 - 521) (144 - 209) (144 - 209) (144 - 209) (97 - 141) 

40 11 11 11 3 

(33 - 47) (9 - 13) (9 - 13) (9 - 13) (3 - 4) 

480 401 310 260 301 

(393 - 564) (328 - 473) (253 - 366) (212 - 308) (245 - 355) 

60 34 34 34 17 

(49 - 71) (27 - 40) (27 - 40) (27 - 40) (14 - 20) 

 Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Detroit, MI Houston, TX New York, NY St. Louis, MO

 Incidence of Ischemic Heart Disease Mortality Associated with Long-Term Exposure to PM2.5 Co

Recent Year and PM2.5 Concentrations that Just Meet the Current and Alternative Annual (n) and D

(Standard Combination Denoted n/m):

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL Baltimore, MD

E-28

September 2009 
Table E-21. Estimated Annual Incidence of Ischemic Heart Disease Mortality Associated with Long-Term Exposure to 

 Concentrations in a Recent Year (2007) and PM2.5 Concentrations that Just Meet the Current and Alternative 

 on Adjusting 2007 PM2.5 Concentrations: Estimates Based on Krewski et al. (2009), Using Ambient PM2.5 from 

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

248 221 174 151 174 

(204 - 291) (181 - 260) (143 - 205) (123 - 178) (143 - 205) 

324 296 236 201 227 

(266 - 381) (243 - 349) (193 - 278) (164 - 238) (185 - 268) 

206 149 117 100 117 

(170 - 241) (122 - 175) (95 - 138) (82 - 118) (95 - 138) 

191 191 191 168 191 

(156 - 226) (156 - 226) (156 - 226) (137 - 199) (156 - 226) 

472 327 274 225 233 

(387 - 556) (267 - 386) (223 - 324) (183 - 267) (190 - 276) 

218 86 86 86 60 

(180 - 255) (70 - 102) (70 - 102) (70 - 102) (49 - 72) 

451 417 328 282 328 

(371 - 530) (342 - 489) (268 - 386) (231 - 333) (268 - 386) 

2045 923 923 809 627 

(1680 - 2399) (752 - 1091) (752 - 1091) (659 - 957) (510 - 743) 

2008 1432 1358 1127 1009 

(1644 - 2365) (1169 - 1692) (1107 - 1604) (918 - 1334) (821 - 1195) 

305 267 238 203 201 

(250 - 359) (218 - 314) (194 - 280) (166 - 240) (164 - 238) 

329 329 329 294 284 

(269 - 389) (269 - 389) (269 - 389) (240 - 348) (232 - 337) 

450 180 180 180 123 

(370 - 527) (147 - 213) (147 - 213) (147 - 213) (100 - 146) 

55 21 21 21 12 

(45 - 65) (17 - 25) (17 - 25) (17 - 25) (10 - 14) 

510 429 335 283 325 

(418 - 599) (351 - 505) (273 - 395) (231 - 334) (265 - 383) 

69 41 41 41 23 

(56 - 82) (33 - 48) (33 - 48) (33 - 48) (19 - 27) 

 Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Detroit, MI Houston, TX New York, NY St. Louis, MO

 Incidence of Ischemic Heart Disease Mortality Associated with Long-Term Exposure to PM2.5 Co

Recent Year and PM2.5 Concentrations that Just Meet the Current and Alternative Annual (n) and D

(Standard Combination Denoted n/m):

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL Baltimore, MD

E-29

September 2009 
Table E-22. Estimated Percent of Total Annual Incidence of Ischemic Heart Disease Mortality Associated with Long-Term 

 Ambient PM2.5 Concentrations in a Recent Year (2005) and PM2.5 Concentrations that Just Meet the Current and 

 Standards, Based on Adjusting 2005 PM2.5 Concentrations: Estimates Based on Krewski et al. (2009), Using Ambie

 from 1979 - 19831

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

15.8% 14.1% 11.2% 9.7% 11.2% 

(13% - 18.5%) (11.6% - 16.5%) (9.1% - 13.1%) (7.9% - 11.4%) (9.1% - 13.1%) (7.7

15.4% 14.3% 11.6% 10.1% 11.2% 

(12.7% - 18.1%) (11.7% - 16.7%) (9.5% - 13.7%) (8.3% - 11.9%) (9.2% - 13.2%) (6.

18.3% 13.3% 10.5% 9.1% 10.5% 

(15.1% - 21.4%) (11% - 15.7%) (8.6% - 12.4%) (7.4% - 10.7%) (8.6% - 12.4%) (6.

10.7% 10.7% 10.7% 9.5% 10.7% 

(8.8% - 12.6%) (8.8% - 12.6%) (8.8% - 12.6%) (7.8% - 11.3%) (8.8% - 12.6%) (7.8

15.6% 11.4% 9.9% 8.5% 8.7% 

(12.8% - 18.3%) (9.4% - 13.5%) (8.1% - 11.7%) (7% - 10%) (7.1% - 10.3%) (4.

16.4% 5.9% 5.9% 5.9% 3.9% 

(13.5% - 19.2%) (4.8% - 7%) (4.8% - 7%) (4.8% - 7%) (3.2% - 4.6%) (1.

14.3% 13.2% 10.4% 9% 10.4% 

(11.8% - 16.8%) (10.9% - 15.6%) (8.5% - 12.3%) (7.4% - 10.6%) (8.5% - 12.3%) (7.4

15.8% 7.5% 7.5% 6.6% 5.3% 

(13% - 18.6%) (6.1% - 8.8%) (6.1% - 8.8%) (5.4% - 7.8%) (4.3% - 6.2%) (2.

12.2% 9% 8.5% 7.2% 6.6% 

(10% - 14.4%) (7.3% - 10.6%) (7% - 10.1%) (5.9% - 8.5%) (5.3% - 7.7%) (3.

12.6% 11% 9.8% 8.4% 8.3% 

(10.3% - 14.8%) (9% - 13%) (8% - 11.6%) (6.9% - 9.9%) (6.8% - 9.8%) (4.

7.9% 7.9% 7.9% 7.1% 6.9% 

(6.4% - 9.3%) (6.4% - 9.3%) (6.4% - 9.3%) (5.8% - 8.4%) (5.6% - 8.1%) (3.

18.3% 7.8% 7.8% 7.8% 5.6% 

(15.1% - 21.4%) (6.4% - 9.2%) (6.4% - 9.2%) (6.4% - 9.2%) (4.5% - 6.6%) (2.

9.8% 3.4% 3.4% 3.4% 1.8% 

(8% - 11.5%) (2.8% - 4.1%) (2.8% - 4.1%) (2.8% - 4.1%) (1.4% - 2.1%) (0.

15.5% 13.2% 10.6% 9.1% 10.3% 

(12.7% - 18.1%) (10.9% - 15.5%) (8.7% - 12.5%) (7.5% - 10.8%) (8.4% - 12.1%) (6

9% 5.9% 5.9% 5.9% 4% 

(7.4% - 10.7%) (4.8% - 7%) (4.8% - 7%) (4.8% - 7%) (3.2% - 4.7%) (1.

Percent of Total Incidence of Ischemic Heart Disease Mortality Associated with Long-Term Exposur

Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the Current and Alternative A

Daily (m) Standards (Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

E-30

September 2009 
Table E-23. Estimated Percent of Total Annual Incidence of Ischemic Heart Disease Mortality Associated with Long-Term 

 Ambient PM2.5 Concentrations in a Recent Year (2006) and PM2.5 Concentrations that Just Meet the Current and 

 Standards, Based on Adjusting 2006 PM2.5 Concentrations: Estimates Based on Krewski et al. (2009), Using Ambie

 from 1979 - 19831

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

14.8% 13.2% 10.4% 9% 10.4% 

(12.2% - 17.4%) (10.8% - 15.5%) (8.5% - 12.3%) (7.3% - 10.6%) (8.5% - 12.3%) (7.2

13.5% 12.4% 10% 8.6% 9.6% 

(11.1% - 15.9%) (10.2% - 14.6%) (8.2% - 11.7%) (7% - 10.1%) (7.8% - 11.3%) (5.

17.6% 12.7% 10% 8.6% 10% 

(14.5% - 20.5%) (10.4% - 15%) (8.2% - 11.8%) (7% - 10.1%) (8.2% - 11.8%) (5.

8.1% 8.1% 8.1% 7.1% 8.1% 

(6.6% - 9.6%) (6.6% - 9.6%) (6.6% - 9.6%) (5.8% - 8.4%) (6.6% - 9.6%) (5.

12% 8.4% 7.1% 5.9% 6.1% 

(9.9% - 14.2%) (6.9% - 10%) (5.8% - 8.4%) (4.8% - 7%) (5% - 7.2%) (3

17.1% 6.3% 6.3% 6.3% 4.3% 

(14.1% - 20.1%) (5.2% - 7.5%) (5.2% - 7.5%) (5.2% - 7.5%) (3.5% - 5.1%) (1.

14.6% 13.5% 10.7% 9.2% 10.7% 

(12% - 17.2%) (11.1% - 15.9%) (8.8% - 12.6%) (7.6% - 10.9%) (8.8% - 12.6%) (7.6

14.2% 6.4% 6.4% 5.6% 4.3% 

(11.7% - 16.7%) (5.2% - 7.5%) (5.2% - 7.5%) (4.5% - 6.6%) (3.5% - 5.1%) (1.

10.5% 7.5% 7.1% 5.9% 5.3% 

(8.6% - 12.4%) (6.1% - 8.9%) (5.8% - 8.4%) (4.8% - 7%) (4.3% - 6.2%) (2.

12.4% 10.8% 9.6% 8.3% 8.2% 

(10.1% - 14.5%) (8.8% - 12.7%) (7.9% - 11.4%) (6.7% - 9.7%) (6.7% - 9.6%) (4.

8.3% 8.3% 8.3% 7.5% 7.2% 

(6.7% - 9.7%) (6.7% - 9.7%) (6.7% - 9.7%) (6.1% - 8.8%) (5.9% - 8.5%) (3.

16.1% 6.4% 6.4% 6.4% 4.3% 

(13.3% - 18.9%) (5.2% - 7.6%) (5.2% - 7.6%) (5.2% - 7.6%) (3.5% - 5.1%) (1.

7.9% 2.2% 2.2% 2.2% 0.7% 

(6.4% - 9.3%) (1.8% - 2.6%) (1.8% - 2.6%) (1.8% - 2.6%) (0.5% - 0.8%) (

12.1% 10.1% 7.8% 6.6% 7.6% 

(9.9% - 14.2%) (8.3% - 11.9%) (6.4% - 9.2%) (5.4% - 7.8%) (6.2% - 9%) (4.

5.8% 3.3% 3.3% 3.3% 1.6% 

(4.7% - 6.9%) (2.7% - 3.9%) (2.7% - 3.9%) (2.7% - 3.9%) (1.3% - 1.9%) (

Percent of Total Incidence of Ischemic Heart Disease Mortality Associated with Long-Term Exposur

Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the Current and Alternative A

Daily (m) Standards (Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

E-31

September 2009 
Table E-24. Estimated Percent of Total Annual Incidence of Ischemic Heart Disease Mortality Associated with Long-Term 

 Ambient PM2.5 Concentrations in a Recent Year (2007) and PM2.5 Concentrations that Just Meet the Current and 

 Standards, Based on Adjusting 2007 PM2.5 Concentrations: Estimates Based on Krewski et al. (2009), Using Ambie

 from 1979 - 19831

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

15% 13.3% 10.5% 9.1% 10.5% 

(12.3% - 17.5%) (10.9% - 15.6%) (8.6% - 12.4%) (7.4% - 10.7%) (8.6% - 12.4%) (7.2

12.7% 11.7% 9.3% 7.9% 8.9% 

(10.4% - 15%) (9.6% - 13.7%) (7.6% - 10.9%) (6.5% - 9.4%) (7.3% - 10.5%) (5

17.3% 12.5% 9.8% 8.4% 9.8% 

(14.2% - 20.2%) (10.2% - 14.7%) (8% - 11.5%) (6.8% - 9.9%) (8% - 11.5%) (5

8.8% 8.8% 8.8% 7.8% 8.8% 

(7.2% - 10.4%) (7.2% - 10.4%) (7.2% - 10.4%) (6.3% - 9.2%) (7.2% - 10.4%) (6

11.4% 7.9% 6.6% 5.4% 5.6% 

(9.3% - 13.4%) (6.4% - 9.3%) (5.4% - 7.8%) (4.4% - 6.4%) (4.6% - 6.6%) (2

18.9% 7.5% 7.5% 7.5% 5.3% 

(15.6% - 22.1%) (6.1% - 8.8%) (6.1% - 8.8%) (6.1% - 8.8%) (4.3% - 6.2%) (2

14.1% 13% 10.2% 8.8% 10.2% 

(11.6% - 16.6%) (10.7% - 15.3%) (8.4% - 12.1%) (7.2% - 10.4%) (8.4% - 12.1%) (7.2

14.4% 6.5% 6.5% 5.7% 4.4% 

(11.9% - 16.9%) (5.3% - 7.7%) (5.3% - 7.7%) (4.6% - 6.8%) (3.6% - 5.2%) (1

10.6% 7.6% 7.2% 6% 5.3% 

(8.7% - 12.5%) (6.2% - 9%) (5.9% - 8.5%) (4.9% - 7.1%) (4.3% - 6.3%) (2

12.2% 10.7% 9.5% 8.1% 8.1% 

(10% - 14.4%) (8.7% - 12.6%) (7.8% - 11.2%) (6.7% - 9.6%) (6.6% - 9.5%) (4

7% 7% 7% 6.2% 6% 

(5.7% - 8.3%) (5.7% - 8.3%) (5.7% - 8.3%) (5.1% - 7.4%) (4.9% - 7.1%) (2

16.4% 6.6% 6.6% 6.6% 4.5% 

(13.5% - 19.2%) (5.3% - 7.8%) (5.3% - 7.8%) (5.3% - 7.8%) (3.6% - 5.3%) (1

10.6% 4% 4% 4% 2.3% 

(8.7% - 12.5%) (3.2% - 4.7%) (3.2% - 4.7%) (3.2% - 4.7%) (1.8% - 2.7%) (0

12.9% 10.8% 8.4% 7.1% 8.2% 

(10.5% - 15.1%) (8.8% - 12.7%) (6.9% - 10%) (5.8% - 8.4%) (6.7% - 9.7%) (4

6.6% 3.9% 3.9% 3.9% 2.2% 

(5.4% - 7.8%) (3.2% - 4.6%) (3.2% - 4.6%) (3.2% - 4.6%) (1.8% - 2.6%) (0

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Percent of Total Incidence of Ischemic Heart Disease Mortality Associated with Long-Term Exposur

Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the Current and Alternative A

Daily (m) Standards (Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

E-32

September 2009 
Table E-25. Percent Reduction from the Current Standards: Estimated Annual Incidence of Ischemic Heart Disease Morta

 Associated with Long-Term Exposure to Ambient PM2.5 Concentrations, Based on Adjusting 2005 PM2.5 Concentr

 Estimates Based on Krewski et al. (2009), Using Ambient PM2.5 from 1979 - 19831 

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

-12% 0% 21% 31% 21% 

(-12% - -12%) (0% - 0%) (20% - 21%) (31% - 32%) (20% - 21%) (3

-8% 0% 19% 29% 21% 

(-8% - -8%) (0% - 0%) (18% - 19%) (29% - 29%) (21% - 22%) (4

-37% 0% 21% 32% 21% 

(-37% - -38%) (0% - 0%) (21% - 21%) (32% - 32%) (21% - 21%) (4

0% 0% 0% 11% 0% 

(0% - 0%) (0% - 0%) (0% - 0%) (11% - 11%) (0% - 0%) (1

-36% 0% 13% 26% 24% 

(-36% - -37%) (0% - 0%) (13% - 13%) (25% - 26%) (23% - 24%) (4

-178% 0% 0% 0% 34% 

(-175% - -181%) (0% - 0%) (0% - 0%) (0% - 0%) (34% - 34%) (6

-8% 0% 21% 32% 21% 

(-8% - -8%) (0% - 0%) (21% - 21%) (32% - 32%) (21% - 21%) (3

-112% 0% 0% 11% 30% 

(-110% - -113%) (0% - 0%) (0% - 0%) (11% - 11%) (29% - 30%) (6

-37% 0% 5% 19% 27% 

(-36% - -37%) (0% - 0%) (5% - 5%) (19% - 20%) (27% - 27%) (5

-14% 0% 11% 23% 24% 

(-14% - -14%) (0% - 0%) (11% - 11%) (23% - 24%) (24% - 24%) (4

0% 0% 0% 10% 13% 

(0% - 0%) (0% - 0%) (0% - 0%) (10% - 10%) (13% - 13%) (4

-134% 0% 0% 0% 29% 

(-132% - -137%) (0% - 0%) (0% - 0%) (0% - 0%) (29% - 29%) (5

-186% 0% 0% 0% 48% 

(-184% - -187%) (0% - 0%) (0% - 0%) (0% - 0%) (48% - 48%) (9

-17% 0% 20% 31% 22% 

(-17% - -17%) (0% - 0%) (20% - 20%) (31% - 31%) (22% - 22%) (4

-52% 0% 0% 0% 33% 

(-52% - -53%) (0% - 0%) (0% - 0%) (0% - 0%) (33% - 34%) (6

Percent Reduction from the Current Standards: Annual Incidence of Ischemic Heart Disease Mortality Asso

Long-Term Exposure to PM2.5 Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the 

Alternative Annual (n) and Daily (m) Standards (Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

E-33

September 2009 
Table E-26. Percent Reduction from the Current Standards: Estimated Annual Incidence of Ischemic Heart Disease Morta

 Associated with Long-Term Exposure to Ambient PM2.5 Concentrations, Based on Adjusting 2006 PM2.5 Concentr

 Estimates Based on Krewski et al. (2009), Using Ambient PM2.5 from 1979 - 19831

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

-12% 0% 21% 32% 21% 

(-12% - -13%) (0% - 0%) (21% - 21%) (32% - 32%) (21% - 21%) (3

-9% 0% 20% 31% 23% 

(-9% - -9%) (0% - 0%) (20% - 20%) (31% - 31%) (23% - 23%) (4

-38% 0% 22% 33% 22% 

(-37% - -39%) (0% - 0%) (21% - 22%) (32% - 33%) (21% - 22%) (4

0% 0% 0% 13% 0% 

(0% - 0%) (0% - 0%) (0% - 0%) (13% - 13%) (0% - 0%) (1

-43% 0% 16% 30% 28% 

(-42% - -43%) (0% - 0%) (15% - 16%) (30% - 30%) (27% - 28%) (5

-170% 0% 0% 0% 33% 

(-167% - -173%) (0% - 0%) (0% - 0%) (0% - 0%) (32% - 33%) (6

-8% 0% 21% 32% 21% 

(-8% - -8%) (0% - 0%) (21% - 21%) (31% - 32%) (21% - 21%) (3

-123% 0% 0% 13% 33% 

(-122% - -125%) (0% - 0%) (0% - 0%) (12% - 13%) (32% - 33%) (6

-40% 0% 5% 21% 30% 

(-40% - -41%) (0% - 0%) (5% - 5%) (21% - 22%) (30% - 30%) (6

-14% 0% 11% 24% 24% 

(-14% - -14%) (0% - 0%) (11% - 11%) (23% - 24%) (24% - 25%) (4

0% 0% 0% 10% 12% 

(0% - 0%) (0% - 0%) (0% - 0%) (10% - 10%) (12% - 12%) (4

-152% 0% 0% 0% 32% 

(-149% - -154%) (0% - 0%) (0% - 0%) (0% - 0%) (32% - 33%) (6

-266% 0% 0% 0% 69% 

(-263% - -268%) (0% - 0%) (0% - 0%) (0% - 0%) (69% - 69%) (10

-20% 0% 23% 35% 25% 

(-19% - -20%) (0% - 0%) (23% - 23%) (35% - 35%) (25% - 25%) (5

-78% 0% 0% 0% 50% 

(-78% - -79%) (0% - 0%) (0% - 0%) (0% - 0%) (50% - 50%) (10

Percent Reduction from the Current Standards: Annual Incidence of Ischemic Heart Disease Mortality Asso

Long-Term Exposure to PM2.5 Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the 

Alternative Annual (n) and Daily (m) Standards (Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

E-34

September 2009 
Table E-27. Percent Reduction from the Current Standards: Estimated Annual Incidence of Ischemic Heart Disease Morta

 Associated with Long-Term Exposure to Ambient PM2.5 Concentrations, Based on Adjusting 2007 PM2.5 Concentr

 Estimates Based on Krewski et al. (2009), Using Ambient PM2.5 from 1979 - 19831 

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

-12% 0% 21% 32% 21% 

(-12% - -13%) (0% - 0%) (21% - 21%) (32% - 32%) (21% - 21%) (3

-9% 0% 20% 32% 24% 

(-9% - -9%) (0% - 0%) (20% - 21%) (32% - 32%) (23% - 24%) (4

-38% 0% 22% 33% 22% 

(-38% - -39%) (0% - 0%) (21% - 22%) (33% - 33%) (21% - 22%) (4

0% 0% 0% 12% 0% 

(0% - 0%) (0% - 0%) (0% - 0%) (12% - 12%) (0% - 0%) (1

-45% 0% 16% 31% 29% 

(-44% - -45%) (0% - 0%) (16% - 16%) (31% - 31%) (29% - 29%) (5

-154% 0% 0% 0% 30% 

(-151% - -157%) (0% - 0%) (0% - 0%) (0% - 0%) (29% - 30%) (6

-8% 0% 21% 32% 21% 

(-8% - -8%) (0% - 0%) (21% - 22%) (32% - 32%) (21% - 22%) (3

-122% 0% 0% 12% 32% 

(-120% - -123%) (0% - 0%) (0% - 0%) (12% - 12%) (32% - 32%) (6

-40% 0% 5% 21% 30% 

(-40% - -41%) (0% - 0%) (5% - 5%) (21% - 21%) (29% - 30%) (6

-14% 0% 11% 24% 25% 

(-14% - -15%) (0% - 0%) (11% - 11%) (24% - 24%) (24% - 25%) (5

0% 0% 0% 11% 14% 

(0% - 0%) (0% - 0%) (0% - 0%) (11% - 11%) (14% - 14%) (4

-149% 0% 0% 0% 32% 

(-147% - -152%) (0% - 0%) (0% - 0%) (0% - 0%) (32% - 32%) (6

-166% 0% 0% 0% 43% 

(-164% - -168%) (0% - 0%) (0% - 0%) (0% - 0%) (43% - 43%) (8

-19% 0% 22% 34% 24% 

(-19% - -19%) (0% - 0%) (22% - 22%) (34% - 34%) (24% - 24%) (4

-69% 0% 0% 0% 44% 

(-68% - -69%) (0% - 0%) (0% - 0%) (0% - 0%) (44% - 44%) (8

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Percent Reduction from the Current Standards: Annual Incidence of Ischemic Heart Disease Mortality Asso

Long-Term Exposure to PM2.5 Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the 

Alternative Annual (n) and Daily (m) Standards (Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

E-35

September 2009 
Figure E-7. Estimated Percent Reductions From the Current Standard to Alternative 

Standards in Ischemic Heart Disease Mortality Associated with Long-Term Exposure to PM2.5

(Exposure Period: 1979 – 1983): Based on 2005 Air Quality Data* 

-200%

-180%

-160%

-140%

-120%

-100%

-80%

-60%

-40%

-20%

0%

20%

40%

60%

80%

100%

2005 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Reduction from Current Standard

 Atlanta, GA 221 (181 - 259); 14.1% (11.6% - 16.5%)

 Baltimore, MD 363 (298 - 426); 14.3% (11.7% - 16.7%)

 Birmingham, AL 156 (128 - 183); 13.3% (11% - 15.7%)

 Dallas, TX 224 (183 - 264); 10.7% (8.8% - 12.6%)

 Detroit, MI 479 (393 - 564); 11.4% (9.4% - 13.5%)

 Fresno, CA 66 (54 - 78); 5.9% (4.8% - 7%)

 Houston, TX 402 (330 - 472); 13.2% (10.9% - 15.6%)

 Los Angeles, CA 1048 (855 - 1238); 7.5% (6.1% - 8.8%)

 New York, NY 1665 (1360 - 1964); 9% (7.3% - 10.6%)

 Philadelphia, PA 275 (225 - 324); 11% (9% - 13%)

 Phoenix, AZ 346 (283 - 409); 7.9% (6.4% - 9.3%)

 Pittsburgh, PA 217 (177 - 256); 7.8% (6.4% - 9.2%)

 Salt Lake City, UT 17 (14 - 20); 3.4% (2.8% - 4.1%)

 St. Louis, MO 521 (428 - 612); 13.2% (10.9% - 15.5%)

 Tacoma, WA 60 (49 - 71); 5.9% (4.8% - 7%)

*Based on Krewski et al. (2009), exposure period from 1979 – 1983. The legend contains, for each urban area, the 

incidence estimate (and 95% CI) and the estimate of percent of total incidence (and 95% CI) under the current 

standards. 

**The current standards consist of an annual standard of 15 μg/m3

 and a daily standard of 35 μg/m3. Combinations of 

an annual standard (n) and a daily standard (m) are denoted n/m in this figure. 

E-36

September 2009 Draft - Do Not Quote or Cite
Figure E-8. Estimated Percent Reductions From the Current Standard to Alternative 

Standards in Ischemic Heart Disease Mortality Associated with Long-Term Exposure to PM2.5

(Exposure Period: 1979 – 1983): Based on 2006 Air Quality Data* 

-200%

-180%

-160%

-140%

-120%

-100%

-80%

-60%

-40%

-20%

0%

20%

40%

60%

80%

100%

2006 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Reduction from Current Standard

 Atlanta, GA 214 (175 - 251); 13.2% (10.8% - 15.5%)

 Baltimore, MD 317 (260 - 372); 12.4% (10.2% - 14.6%)

 Birmingham, AL 151 (124 - 177); 12.7% (10.4% - 15%)

 Dallas, TX 173 (142 - 205); 8.1% (6.6% - 9.6%)

 Detroit, MI 353 (288 - 417); 8.4% (6.9% - 10%)

 Fresno, CA 72 (59 - 85); 6.3% (5.2% - 7.5%)

 Houston, TX 424 (348 - 498); 13.5% (11.1% - 15.9%)

 Los Angeles, CA 897 (731 - 1060); 6.4% (5.2% - 7.5%)

 New York, NY 1407 (1148 - 1662); 7.5% (6.1% - 8.9%)

 Philadelphia, PA 270 (221 - 317); 10.8% (8.8% - 12.7%)

 Phoenix, AZ 378 (309 - 446); 8.3% (6.7% - 9.7%)

 Pittsburgh, PA 177 (144 - 209); 6.4% (5.2% - 7.6%)

 Salt Lake City, UT 11 (9 - 13); 2.2% (1.8% - 2.6%)

 St. Louis, MO 401 (328 - 473); 10.1% (8.3% - 11.9%)

 Tacoma, WA 34 (27 - 40); 3.3% (2.7% - 3.9%)

*Based on Krewski et al. (2009), exposure period from 1979 – 1983. The legend contains, for each urban area, the 

incidence estimate (and 95% CI) and the estimate of percent of total incidence (and 95% CI) under the current 

standards. 

** The current standards consist of an annual standard of 15 μg/m3

 and a daily standard of 35 μg/m3. Combinations of 

an annual standard (n) and a daily standard (m) are denoted n/m in this figure. 

***The percent reduction for 2006 air quality in Salt Lake City is -264%. 

E-37

September 2009 Draft - Do Not Quote or Cite
Figure E-9. Estimated Percent Reductions From the Current Standard to Alternative 

Standards in Ischemic Heart Disease Mortality Associated with Long-Term Exposure to PM2.5

(Exposure Period: 1979 – 1983): Based on 2007 Air Quality Data* 

-200%

-180%

-160%

-140%

-120%

-100%

-80%

-60%

-40%

-20%

0%

20%

40%

60%

80%

100%

2007 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Reduction from Current Standard

 Atlanta, GA 221 (181 - 260); 13.3% (10.9% - 15.6%)

 Baltimore, MD 296 (243 - 349); 11.7% (9.6% - 13.7%)

 Birmingham, AL 149 (122 - 175); 12.5% (10.2% - 14.7%)

 Dallas, TX 191 (156 - 226); 8.8% (7.2% - 10.4%)

 Detroit, MI 327 (267 - 386); 7.9% (6.4% - 9.3%)

 Fresno, CA 86 (70 - 102); 7.5% (6.1% - 8.8%)

 Houston, TX 417 (342 - 489); 13% (10.7% - 15.3%)

 Los Angeles, CA 923 (752 - 1091); 6.5% (5.3% - 7.7%)

 New York, NY 1432 (1169 - 1692); 7.6% (6.2% - 9%)

 Philadelphia, PA 267 (218 - 314); 10.7% (8.7% - 12.6%)

 Phoenix, AZ 329 (269 - 389); 7% (5.7% - 8.3%)

 Pittsburgh, PA 180 (147 - 213); 6.6% (5.3% - 7.8%)

 Salt Lake City, UT 21 (17 - 25); 4% (3.2% - 4.7%)

 St. Louis, MO 429 (351 - 505); 10.8% (8.8% - 12.7%)

 Tacoma, WA 41 (33 - 48); 3.9% (3.2% - 4.6%)

*Based on Krewski et al. (2009), exposure period from 1979 – 1983. The legend contains, for each urban area, the 

incidence estimate (and 95% CI) and the estimate of percent of total incidence (and 95% CI) under the current 

standards. 

**The current standards consist of an annual standard of 15 μg/m3

 and a daily standard of 35 μg/m3. Combinations of 

an annual standard (n) and a daily standard (m) are denoted n/m in this figure.

E-38

September 2009 Draft - Do Not Quote or Cite
Table E-28. Estimated Annual Incidence of Ischemic Heart Disease Mortality Associated with Long-Term Exposure to Am

 Concentrations in a Recent Year (2005) and PM2.5 Concentrations that Just Meet the Current and Alternative Sta

 on Adjusting 2005 PM2.5 Concentrations: Estimates Based on Krewski et al. (2009), Using Ambient PM2.5 from 1

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

310 278 221 192 221 

(255 - 363) (228 - 325) (181 - 260) (157 - 227) (181 - 260) 

493 456 373 325 360 

(406 - 577) (375 - 534) (305 - 438) (266 - 383) (295 - 424) 

268 197 156 135 156 

(221 - 312) (161 - 230) (127 - 183) (110 - 159) (127 - 183) 

283 283 283 252 283 

(231 - 333) (231 - 333) (231 - 333) (206 - 297) (231 - 333) 

819 605 526 452 464 

(674 - 958) (495 - 711) (430 - 619) (369 - 534) (379 - 548) 

229 84 84 84 55 

(189 - 268) (68 - 99) (68 - 99) (68 - 99) (45 - 66) 

546 505 400 346 400 

(449 - 640) (415 - 593) (327 - 471) (282 - 408) (327 - 471) 

2778 1330 1330 1180 940 

(2288 - 3247) (1083 - 1572) (1083 - 1572) (960 - 1396) (763 - 1114) 

2865 2109 2010 1704 1546 

(2348 - 3365) (1721 - 2487) (1639 - 2372) (1388 - 2015) (1258 - 1830) 

396 347 311 267 264 

(325 - 465) (284 - 409) (254 - 366) (218 - 315) (216 - 312) 

439 439 439 396 384 

(358 - 519) (358 - 519) (358 - 519) (322 - 468) (312 - 454) 

634 275 275 275 196 

(524 - 739) (224 - 325) (224 - 325) (224 - 325) (160 - 233) 

61 21 21 21 11 

(50 - 71) (17 - 25) (17 - 25) (17 - 25) (9 - 13) 

765 656 527 456 514 

(630 - 895) (538 - 769) (431 - 621) (372 - 538) (420 - 605) 

115 76 76 76 51 

(94 - 136) (62 - 90) (62 - 90) (62 - 90) (41 - 60) 

 Incidence of Ischemic Heart Disease Mortality Associated with Long-Term Exposure to PM2.5 Conce

Recent Year and PM2.5 Concentrations that Just Meet the Current and Alternative Annual (n) and Daily 

(Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

E-39

September 2009 
Table E-29. Estimated Annual Incidence of Ischemic Heart Disease Mortality Associated with Long-Term Exposure to Am

 Concentrations in a Recent Year (2006) and PM2.5 Concentrations that Just Meet the Current and Alternative Sta

 on Adjusting 2006 PM2.5 Concentrations: Estimates Based on Krewski et al. (2009), Using Ambient PM2.5 from 19

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

301 269 213 184 213 

(248 - 353) (221 - 315) (174 - 251) (150 - 217) (174 - 251) 

434 399 321 276 309 

(356 - 509) (327 - 468) (263 - 378) (225 - 326) (253 - 365) 

260 190 150 129 150 

(215 - 303) (156 - 223) (122 - 176) (105 - 152) (122 - 176) 

220 220 220 192 220 

(179 - 260) (179 - 260) (179 - 260) (157 - 227) (179 - 260) 

635 447 379 315 325 

(521 - 746) (365 - 528) (308 - 448) (256 - 373) (264 - 385) 

243 91 91 91 62 

(200 - 283) (74 - 108) (74 - 108) (74 - 108) (50 - 73) 

576 534 424 367 424 

(474 - 675) (438 - 626) (347 - 499) (300 - 433) (347 - 499) 

2515 1140 1140 998 771 

(2067 - 2947) (927 - 1349) (927 - 1349) (811 - 1182) (626 - 915) 

2497 1785 1693 1406 1258 

(2042 - 2939) (1454 - 2110) (1378 - 2001) (1143 - 1665) (1022 - 1492) 

388 340 304 261 258 

(318 - 456) (279 - 401) (249 - 359) (213 - 308) (211 - 305) 

479 479 479 433 420 

(391 - 566) (391 - 566) (391 - 566) (353 - 512) (342 - 497) 

557 224 224 224 152 

(459 - 651) (183 - 266) (183 - 266) (183 - 266) (124 - 181) 

51 14 14 14 4 

(41 - 60) (11 - 17) (11 - 17) (11 - 17) (4 - 5) 

605 507 393 331 382 

(495 - 710) (415 - 597) (321 - 465) (269 - 391) (311 - 451) 

76 43 43 43 21 

(62 - 90) (35 - 51) (35 - 51) (35 - 51) (17 - 26) 

 Incidence of Ischemic Heart Disease Mortality Associated with Long-Term Exposure to PM2.5 Conce

Recent Year and PM2.5 Concentrations that Just Meet the Current and Alternative Annual (n) and Daily 

(Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

E-40

September 2009 
Table E-30. Estimated Annual Incidence of Ischemic Heart Disease Mortality Associated with Long-Term Exposure to Am

 Concentrations in a Recent Year (2007) and PM2.5 Concentrations that Just Meet the Current and Alternative Sta

 on Adjusting 2007 PM2.5 Concentrations: Estimates Based on Krewski et al. (2009), Using Ambient PM2.5 from 19

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

312 278 220 191 220 

(256 - 365) (228 - 326) (180 - 259) (156 - 225) (180 - 259) 

408 374 299 255 287 

(334 - 479) (306 - 440) (244 - 352) (208 - 302) (234 - 339) 

258 188 148 127 148 

(213 - 301) (154 - 220) (121 - 174) (104 - 150) (121 - 174) 

243 243 243 213 243 

(198 - 286) (198 - 286) (198 - 286) (174 - 252) (198 - 286) 

596 415 348 287 297 

(488 - 701) (338 - 490) (283 - 412) (233 - 340) (241 - 351) 

272 109 109 109 77 

(225 - 316) (89 - 129) (89 - 129) (89 - 129) (63 - 91) 

567 524 415 358 415 

(466 - 665) (430 - 615) (339 - 488) (292 - 422) (339 - 488) 

2568 1173 1173 1029 799 

(2111 - 3008) (954 - 1388) (954 - 1388) (836 - 1219) (648 - 948) 

2537 1818 1724 1434 1285 

(2075 - 2987) (1481 - 2148) (1404 - 2038) (1166 - 1698) (1044 - 1523) 

385 337 301 258 255 

(315 - 452) (276 - 397) (246 - 355) (210 - 305) (208 - 301) 

418 418 418 374 362 

(341 - 495) (341 - 495) (341 - 495) (304 - 443) (294 - 428) 

563 229 229 229 157 

(464 - 658) (187 - 271) (187 - 271) (187 - 271) (127 - 186) 

70 27 27 27 15 

(57 - 82) (22 - 31) (22 - 31) (22 - 31) (12 - 18) 

642 541 424 359 412 

(527 - 753) (443 - 637) (346 - 501) (292 - 425) (336 - 486) 

88 52 52 52 29 

(71 - 104) (42 - 62) (42 - 62) (42 - 62) (24 - 35) 

 Incidence of Ischemic Heart Disease Mortality Associated with Long-Term Exposure to PM2.5 Conce

Recent Year and PM2.5 Concentrations that Just Meet the Current and Alternative Annual (n) and Daily 

(Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

E-41

September 2009 
Table E-31. Estimated Percent of Total Annual Incidence of Ischemic Heart Disease Mortality Associated with Long-Term Exp

 Ambient PM2.5 Concentrations in a Recent Year (2005) and PM2.5 Concentrations that Just Meet the Current and Alte

 Standards, Based on Adjusting 2005 PM2.5 Concentrations: Estimates Based on Krewski et al. (2009), Using Ambient P

 from 1999 - 20001

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 12

19.8% 17.7% 14.1% 12.3% 14.1% 12

(16.3% - 23.1%) (14.5% - 20.7%) (11.5% - 16.6%) (10% - 14.4%) (11.5% - 16.6%) (9.8% - 

19.4% 17.9% 14.7% 12.8% 14.2% 10.

(15.9% - 22.7%) (14.7% - 21%) (12% - 17.2%) (10.4% - 15%) (11.6% - 16.6%) (8.3% - 

22.9% 16.8% 13.3% 11.5% 13.3% 9.8

(18.9% - 26.6%) (13.8% - 19.7%) (10.9% - 15.7%) (9.4% - 13.6%) (10.9% - 15.7%) (8% - 1

13.5% 13.5% 13.5% 12.1% 13.5% 12.

(11.1% - 15.9%) (11.1% - 15.9%) (11.1% - 15.9%) (9.9% - 14.2%) (11.1% - 15.9%) (9.9% - 

19.5% 14.4% 12.5% 10.8% 11.1% 7.6

(16.1% - 22.9%) (11.8% - 17%) (10.3% - 14.8%) (8.8% - 12.7%) (9% - 13.1%) (6.2% 

20.6% 7.5% 7.5% 7.5% 5% 2.3

(16.9% - 24%) (6.1% - 8.9%) (6.1% - 8.9%) (6.1% - 8.9%) (4% - 5.9%) (1.9% - 

18% 16.7% 13.2% 11.4% 13.2% 11.

(14.8% - 21.1%) (13.7% - 19.6%) (10.8% - 15.5%) (9.3% - 13.5%) (10.8% - 15.5%) (9.3% - 

19.9% 9.5% 9.5% 8.4% 6.7% 3.8

(16.4% - 23.2%) (7.7% - 11.2%) (7.7% - 11.2%) (6.9% - 10%) (5.5% - 8%) (3.1% - 

15.4% 11.4% 10.8% 9.2% 8.3% 5.2

(12.6% - 18.1%) (9.3% - 13.4%) (8.8% - 12.8%) (7.5% - 10.9%) (6.8% - 9.9%) (4.2% - 

15.8% 13.9% 12.4% 10.7% 10.6% 7.1

(13% - 18.6%) (11.4% - 16.3%) (10.2% - 14.6%) (8.7% - 12.6%) (8.6% - 12.5%) (5.8% - 

10% 10% 10% 9% 8.7% 5.5

(8.1% - 11.8%) (8.1% - 11.8%) (8.1% - 11.8%) (7.3% - 10.6%) (7.1% - 10.3%) (4.5% - 

22.8% 9.9% 9.9% 9.9% 7.1% 4.2

(18.9% - 26.6%) (8.1% - 11.7%) (8.1% - 11.7%) (8.1% - 11.7%) (5.7% - 8.4%) (3.4% - 

12.4% 4.4% 4.4% 4.4% 2.3% 0.1

(10.1% - 14.6%) (3.5% - 5.2%) (3.5% - 5.2%) (3.5% - 5.2%) (1.8% - 2.7%) (0.1% - 

19.4% 16.6% 13.4% 11.6% 13% 9.3

(16% - 22.7%) (13.7% - 19.5%) (10.9% - 15.7%) (9.4% - 13.6%) (10.7% - 15.3%) (7.6% 

11.4% 7.6% 7.6% 7.6% 5% 2.5

(9.3% - 13.5%) (6.1% - 9%) (6.1% - 9%) (6.1% - 9%) (4.1% - 6%) (2% - 

 Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Detroit, MI Houston, TX New York, NY St. Louis, MO

Percent of Total Incidence of Ischemic Heart Disease Mortality Associated with Long-Term Exposure to 

Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the Current and Alternative Annu

Daily (m) Standards (Standard Combination Denoted n/m):

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL Baltimore, MD

E-42

September 2009 
Table E-32. Estimated Percent of Total Annual Incidence of Ischemic Heart Disease Mortality Associated with Long-Term 

 Ambient PM2.5 Concentrations in a Recent Year (2006) and PM2.5 Concentrations that Just Meet the Current and 

 Standards, Based on Adjusting 2006 PM2.5 Concentrations: Estimates Based on Krewski et al. (2009), Using Ambie

 from 1999 - 20001 

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

18.6% 16.6% 13.2% 11.4% 13.2% 

(15.3% - 21.8%) (13.6% - 19.5%) (10.8% - 15.5%) (9.3% - 13.4%) (10.8% - 15.5%) (9.1

17% 15.6% 12.6% 10.8% 12.1% 

(14% - 20%) (12.8% - 18.4%) (10.3% - 14.8%) (8.8% - 12.8%) (9.9% - 14.3%) (6

22% 16% 12.6% 10.9% 12.6% 

(18.1% - 25.6%) (13.1% - 18.8%) (10.3% - 14.9%) (8.9% - 12.8%) (10.3% - 14.9%) (7.5

10.3% 10.3% 10.3% 9% 10.3% 

(8.4% - 12.2%) (8.4% - 12.2%) (8.4% - 12.2%) (7.3% - 10.7%) (8.4% - 12.2%) (7.3

15.2% 10.7% 9% 7.5% 7.8% 

(12.4% - 17.8%) (8.7% - 12.6%) (7.4% - 10.7%) (6.1% - 8.9%) (6.3% - 9.2%) (3.

21.4% 8.1% 8.1% 8.1% 5.5% 

(17.7% - 25%) (6.6% - 9.6%) (6.6% - 9.6%) (6.6% - 9.6%) (4.4% - 6.5%) (2.

18.4% 17% 13.5% 11.7% 13.5% 

(15.1% - 21.5%) (14% - 20%) (11% - 15.9%) (9.6% - 13.8%) (11% - 15.9%) (9.6

17.9% 8.1% 8.1% 7.1% 5.5% 

(14.7% - 20.9%) (6.6% - 9.6%) (6.6% - 9.6%) (5.8% - 8.4%) (4.4% - 6.5%) (2.

13.3% 9.5% 9% 7.5% 6.7% 

(10.9% - 15.7%) (7.8% - 11.3%) (7.3% - 10.7%) (6.1% - 8.9%) (5.5% - 8%) (3.

15.6% 13.6% 12.2% 10.5% 10.4% 

(12.8% - 18.3%) (11.2% - 16.1%) (10% - 14.4%) (8.5% - 12.4%) (8.4% - 12.2%) (5.

10.5% 10.5% 10.5% 9.5% 9.2% 

(8.5% - 12.4%) (8.5% - 12.4%) (8.5% - 12.4%) (7.7% - 11.2%) (7.5% - 10.9%) (4

20.2% 8.1% 8.1% 8.1% 5.5% 

(16.6% - 23.6%) (6.6% - 9.6%) (6.6% - 9.6%) (6.6% - 9.6%) (4.5% - 6.5%) (2.

10% 2.8% 2.8% 2.8% 0.9% 

(8.2% - 11.8%) (2.2% - 3.3%) (2.2% - 3.3%) (2.2% - 3.3%) (0.7% - 1%) (

15.3% 12.8% 9.9% 8.3% 9.6% 

(12.5% - 17.9%) (10.5% - 15.1%) (8.1% - 11.7%) (6.8% - 9.9%) (7.8% - 11.4%) (5.

7.4% 4.2% 4.2% 4.2% 2.1% 

(6% - 8.8%) (3.4% - 5%) (3.4% - 5%) (3.4% - 5%) (1.7% - 2.5%) (

Percent of Total Incidence of Ischemic Heart Disease Mortality Associated with Long-Term Exposur

Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the Current and Alternative A

Daily (m) Standards (Standard Combination Denoted n/m):

1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL Baltimore, MD Detroit, MI Houston, TX New York, NY St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 

E-43

September 2009 
Table E-33. Estimated Percent of Total Annual Incidence of Ischemic Heart Disease Mortality Associated with Long-Term 

 Ambient PM2.5 Concentrations in a Recent Year (2007) and PM2.5 Concentrations that Just Meet the Current and 

 Standards, Based on Adjusting 2007 PM2.5 Concentrations: Estimates Based on Krewski et al. (2009), Using Ambie

 from 1999 - 20001 

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

18.8% 16.8% 13.3% 11.5% 13.3% 

(15.4% - 22%) (13.7% - 19.6%) (10.9% - 15.6%) (9.4% - 13.5%) (10.9% - 15.6%) (9.1

16% 14.7% 11.8% 10% 11.3% 

(13.2% - 18.8%) (12% - 17.3%) (9.6% - 13.9%) (8.2% - 11.9%) (9.2% - 13.3%) (6.

21.6% 15.7% 12.4% 10.6% 12.4% 

(17.8% - 25.2%) (12.9% - 18.4%) (10.1% - 14.6%) (8.7% - 12.5%) (10.1% - 14.6%) (7.3

11.2% 11.2% 11.2% 9.8% 11.2% 

(9.1% - 13.2%) (9.1% - 13.2%) (9.1% - 13.2%) (8% - 11.6%) (9.1% - 13.2%) (8

14.3% 10% 8.4% 6.9% 7.1% 

(11.7% - 16.9%) (8.1% - 11.8%) (6.8% - 9.9%) (5.6% - 8.2%) (5.8% - 8.5%) (3

23.6% 9.5% 9.5% 9.5% 6.7% 

(19.5% - 27.5%) (7.7% - 11.2%) (7.7% - 11.2%) (7.7% - 11.2%) (5.4% - 7.9%) (3.

17.7% 16.4% 13% 11.2% 13% 

(14.6% - 20.8%) (13.5% - 19.2%) (10.6% - 15.3%) (9.1% - 13.2%) (10.6% - 15.3%) (9.1

18.1% 8.3% 8.3% 7.3% 5.6% 

(14.9% - 21.2%) (6.7% - 9.8%) (6.7% - 9.8%) (5.9% - 8.6%) (4.6% - 6.7%) (2.

13.4% 9.6% 9.1% 7.6% 6.8% 

(11% - 15.8%) (7.8% - 11.4%) (7.4% - 10.8%) (6.2% - 9%) (5.5% - 8.1%) (3.

15.4% 13.5% 12.1% 10.3% 10.2% 

(12.6% - 18.1%) (11% - 15.9%) (9.8% - 14.2%) (8.4% - 12.2%) (8.3% - 12.1%) (5.

8.9% 8.9% 8.9% 7.9% 7.7% 

(7.2% - 10.5%) (7.2% - 10.5%) (7.2% - 10.5%) (6.4% - 9.4%) (6.2% - 9.1%) (3.

20.5% 8.3% 8.3% 8.3% 5.7% 

(16.9% - 23.9%) (6.8% - 9.9%) (6.8% - 9.9%) (6.8% - 9.9%) (4.6% - 6.8%) (2.

13.4% 5.1% 5.1% 5.1% 2.9% 

(11% - 15.8%) (4.1% - 6.1%) (4.1% - 6.1%) (4.1% - 6.1%) (2.3% - 3.4%) (0.

16.2% 13.7% 10.7% 9.1% 10.4% 

(13.3% - 19%) (11.2% - 16.1%) (8.7% - 12.6%) (7.4% - 10.7%) (8.5% - 12.3%) (5.

8.4% 5% 5% 5% 2.8% 

(6.8% - 9.9%) (4.1% - 5.9%) (4.1% - 5.9%) (4.1% - 5.9%) (2.3% - 3.3%) (0.

 Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Detroit, MI Houston, TX New York, NY St. Louis, MO

Percent of Total Incidence of Ischemic Heart Disease Mortality Associated with Long-Term Exposur

Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the Current and Alternative A

Daily (m) Standards (Standard Combination Denoted n/m):

1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL Baltimore, MD

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 

E-44

September 2009 
Table E-34. Percent Reduction from the Current Standards: Estimated Annual Incidence of Ischemic Heart Disease Mortal

 Associated with Long-Term Exposure to Ambient PM2.5 Concentrations, Based on Adjusting 2005 PM2.5 Concentra

 Estimates Based on Krewski et al. (2009), Using Ambient PM2.5 from 1999 - 20001

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

-12% 0% 20% 31% 20% 

(-11% - -12%) (0% - 0%) (20% - 21%) (30% - 31%) (20% - 21%) (32

-8% 0% 18% 29% 21% 

(-8% - -8%) (0% - 0%) (18% - 18%) (28% - 29%) (21% - 21%) (42

-36% 0% 21% 31% 21% 

(-35% - -37%) (0% - 0%) (20% - 21%) (31% - 32%) (20% - 21%) (41

0% 0% 0% 11% 0% 

(0% - 0%) (0% - 0%) (0% - 0%) (11% - 11%) (0% - 0%) (11

-35% 0% 13% 25% 23% 

(-35% - -36%) (0% - 0%) (13% - 13%) (25% - 26%) (23% - 24%) (47

-174% 0% 0% 0% 34% 

(-170% - -178%) (0% - 0%) (0% - 0%) (0% - 0%) (34% - 34%) (69

-8% 0% 21% 32% 21% 

(-8% - -8%) (0% - 0%) (21% - 21%) (31% - 32%) (21% - 21%) (31

-109% 0% 0% 11% 29% 

(-107% - -111%) (0% - 0%) (0% - 0%) (11% - 11%) (29% - 30%) (59

-36% 0% 5% 19% 27% 

(-35% - -36%) (0% - 0%) (5% - 5%) (19% - 19%) (26% - 27%) (54

-14% 0% 11% 23% 24% 

(-14% - -14%) (0% - 0%) (10% - 11%) (23% - 23%) (24% - 24%) (48

0% 0% 0% 10% 13% 

(0% - 0%) (0% - 0%) (0% - 0%) (10% - 10%) (12% - 13%) (45

-130% 0% 0% 0% 29% 

(-127% - -134%) (0% - 0%) (0% - 0%) (0% - 0%) (28% - 29%) (58

-183% 0% 0% 0% 48% 

(-181% - -185%) (0% - 0%) (0% - 0%) (0% - 0%) (48% - 48%) (98

-17% 0% 20% 30% 22% 

(-16% - -17%) (0% - 0%) (19% - 20%) (30% - 31%) (21% - 22%) (44

-51% 0% 0% 0% 33% 

(-51% - -52%) (0% - 0%) (0% - 0%) (0% - 0%) (33% - 33%) (67

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Percent Reduction from the Current Standards: Annual Incidence of Ischemic Heart Disease Mortality Assoc

Long-Term Exposure to PM2.5 Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the C

Alternative Annual (n) and Daily (m) Standards (Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

E-45

September 2009 
Table E-35. Percent Reduction from the Current Standards: Estimated Annual Incidence of Ischemic Heart Disease Mortal

 Associated with Long-Term Exposure to Ambient PM2.5 Concentrations, Based on Adjusting 2006 PM2.5 Concentrat

 Estimates Based on Krewski et al. (2009), Using Ambient PM2.5 from 1999 - 20001

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

-12% 0% 21% 32% 21% 

(-12% - -12%) (0% - 0%) (21% - 21%) (31% - 32%) (21% - 21%) (33

-9% 0% 19% 31% 22% 

(-9% - -9%) (0% - 0%) (19% - 20%) (30% - 31%) (22% - 23%) (45

-37% 0% 21% 32% 21% 

(-36% - -38%) (0% - 0%) (21% - 21%) (32% - 32%) (21% - 21%) (42

0% 0% 0% 12% 0% 

(0% - 0%) (0% - 0%) (0% - 0%) (12% - 13%) (0% - 0%) (12

-42% 0% 15% 30% 27% 

(-41% - -43%) (0% - 0%) (15% - 16%) (29% - 30%) (27% - 28%) (55

-166% 0% 0% 0% 32% 

(-162% - -170%) (0% - 0%) (0% - 0%) (0% - 0%) (32% - 33%) (66

-8% 0% 21% 31% 21% 

(-8% - -8%) (0% - 0%) (20% - 21%) (31% - 32%) (20% - 21%) (31

-121% 0% 0% 12% 32% 

(-118% - -123%) (0% - 0%) (0% - 0%) (12% - 13%) (32% - 33%) (65

-40% 0% 5% 21% 30% 

(-39% - -40%) (0% - 0%) (5% - 5%) (21% - 21%) (29% - 30%) (60

-14% 0% 11% 23% 24% 

(-14% - -14%) (0% - 0%) (10% - 11%) (23% - 24%) (24% - 24%) (49

0% 0% 0% 10% 12% 

(0% - 0%) (0% - 0%) (0% - 0%) (10% - 10%) (12% - 12%) (43

-148% 0% 0% 0% 32% 

(-145% - -151%) (0% - 0%) (0% - 0%) (0% - 0%) (32% - 32%) (65

-262% 0% 0% 0% 69% 

(-260% - -265%) (0% - 0%) (0% - 0%) (0% - 0%) (69% - 69%) (100

-19% 0% 22% 35% 25% 

(-19% - -20%) (0% - 0%) (22% - 23%) (35% - 35%) (25% - 25%) (50

-78% 0% 0% 0% 50% 

(-77% - -78%) (0% - 0%) (0% - 0%) (0% - 0%) (50% - 50%) (100

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Percent Reduction from the Current Standards: Annual Incidence of Ischemic Heart Disease Mortality Assoc

Long-Term Exposure to PM2.5 Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the C

Alternative Annual (n) and Daily (m) Standards (Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

E-46

September 2009 
Table E-36. Percent Reduction from the Current Standards: Estimated Annual Incidence of Ischemic Heart Disease Morta

 Associated with Long-Term Exposure to Ambient PM2.5 Concentrations, Based on Adjusting 2007 PM2.5 Concentr

 Estimates Based on Krewski et al. (2009), Using Ambient PM2.5 from 1999 - 20001

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

-12% 0% 21% 31% 21% 

(-12% - -12%) (0% - 0%) (20% - 21%) (31% - 32%) (20% - 21%) (3

-9% 0% 20% 32% 23% 

(-9% - -9%) (0% - 0%) (20% - 20%) (31% - 32%) (23% - 23%) (4

-37% 0% 21% 32% 21% 

(-37% - -38%) (0% - 0%) (21% - 22%) (32% - 33%) (21% - 22%) (4

0% 0% 0% 12% 0% 

(0% - 0%) (0% - 0%) (0% - 0%) (12% - 12%) (0% - 0%) (1

-44% 0% 16% 31% 28% 

(-43% - -44%) (0% - 0%) (16% - 16%) (31% - 31%) (28% - 29%) (5

-149% 0% 0% 0% 29% 

(-145% - -153%) (0% - 0%) (0% - 0%) (0% - 0%) (29% - 30%) (5

-8% 0% 21% 32% 21% 

(-8% - -8%) (0% - 0%) (21% - 21%) (31% - 32%) (21% - 21%) (3

-119% 0% 0% 12% 32% 

(-117% - -121%) (0% - 0%) (0% - 0%) (12% - 12%) (32% - 32%) (6

-40% 0% 5% 21% 29% 

(-39% - -40%) (0% - 0%) (5% - 5%) (21% - 21%) (29% - 30%) (5

-14% 0% 11% 23% 24% 

(-14% - -14%) (0% - 0%) (11% - 11%) (23% - 24%) (24% - 25%) (4

0% 0% 0% 11% 14% 

(0% - 0%) (0% - 0%) (0% - 0%) (11% - 11%) (13% - 14%) (4

-146% 0% 0% 0% 32% 

(-142% - -149%) (0% - 0%) (0% - 0%) (0% - 0%) (32% - 32%) (6

-163% 0% 0% 0% 43% 

(-161% - -166%) (0% - 0%) (0% - 0%) (0% - 0%) (43% - 43%) (8

-19% 0% 22% 34% 24% 

(-18% - -19%) (0% - 0%) (21% - 22%) (33% - 34%) (24% - 24%) (4

-68% 0% 0% 0% 44% 

(-68% - -69%) (0% - 0%) (0% - 0%) (0% - 0%) (44% - 44%) (8

Percent Reduction from the Current Standards: Annual Incidence of Ischemic Heart Disease Mortality Asso

Long-Term Exposure to PM2.5 Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the 

Alternative Annual (n) and Daily (m) Standards (Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

E-47

September 2009 
Figure E-10. Estimated Percent Reductions From the Current Standard to Alternative 

Standards in Ischemic Heart Disease Mortality Associated with Long-Term Exposure to PM2.5

(Exposure Period: 1999 – 2000): Based on 2005 Air Quality Data*

-200%

-180%

-160%

-140%

-120%

-100%

-80%

-60%

-40%

-20%

0%

20%

40%

60%

80%

100%

2005 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Reduction from Current Standard

 Atlanta, GA 278 (228 - 325); 17.7% (14.5% - 20.7%)

 Baltimore, MD 456 (375 - 534); 17.9% (14.7% - 21%)

 Birmingham, AL 197 (161 - 230); 16.8% (13.8% - 19.7%)

 Dallas, TX 283 (231 - 333); 13.5% (11.1% - 15.9%)

 Detroit, MI 605 (495 - 711); 14.4% (11.8% - 17%)

 Fresno, CA 84 (68 - 99); 7.5% (6.1% - 8.9%)

 Houston, TX 505 (415 - 593); 16.7% (13.7% - 19.6%)

 Los Angeles, CA 1330 (1083 - 1572); 9.5% (7.7% - 11.2%)

 New York, NY 2109 (1721 - 2487); 11.4% (9.3% - 13.4%)

 Philadelphia, PA 347 (284 - 409); 13.9% (11.4% - 16.3%)

 Phoenix, AZ 439 (358 - 519); 10% (8.1% - 11.8%)

 Pittsburgh, PA 275 (224 - 325); 9.9% (8.1% - 11.7%)

 Salt Lake City, UT 21 (17 - 25); 4.4% (3.5% - 5.2%)

 St. Louis, MO 656 (538 - 769); 16.6% (13.7% - 19.5%)

 Tacoma, WA 76 (62 - 90); 7.6% (6.1% - 9%)

 

*Based on Krewski et al. (2009), exposure period from 1999 – 2000. The legend contains, for each urban area, the 

incidence estimate (and 95% CI) and the estimate of percent of total incidence (and 95% CI) under the current 

standards. 

**The current standards consist of an annual standard of 15 μg/m3

 and a daily standard of 35 μg/m3. Combinations of 

an annual standard (n) and a daily standard (m) are denoted n/m in this figure. 

E-48

September 2009 Draft - Do Not Quote or Cite
Figure E-11. Estimated Percent Reductions From the Current Standard to Alternative 

Standards in Ischemic Heart Disease Mortality Associated with Long-Term Exposure to PM2.5

(Exposure Period: 1999 – 2000): Based on 2006 Air Quality Data* 

-200%

-180%

-160%

-140%

-120%

-100%

-80%

-60%

-40%

-20%

0%

20%

40%

60%

80%

100%

2006 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Reduction from Current Standard

 Atlanta, GA 269 (221 - 315); 16.6% (13.6% - 19.5%)

 Baltimore, MD 399 (327 - 468); 15.6% (12.8% - 18.4%)

 Birmingham, AL 190 (156 - 223); 16% (13.1% - 18.8%)

 Dallas, TX 220 (179 - 260); 10.3% (8.4% - 12.2%)

 Detroit, MI 447 (365 - 528); 10.7% (8.7% - 12.6%)

 Fresno, CA 91 (74 - 108); 8.1% (6.6% - 9.6%)

 Houston, TX 534 (438 - 626); 17% (14% - 20%)

 Los Angeles, CA 1140 (927 - 1349); 8.1% (6.6% - 9.6%)

 New York, NY 1785 (1454 - 2110); 9.5% (7.8% - 11.3%)

 Philadelphia, PA 340 (279 - 401); 13.6% (11.2% - 16.1%)

 Phoenix, AZ 479 (391 - 566); 10.5% (8.5% - 12.4%)

 Pittsburgh, PA 224 (183 - 266); 8.1% (6.6% - 9.6%)

 Salt Lake City, UT 14 (11 - 17); 2.8% (2.2% - 3.3%)

 St. Louis, MO 507 (415 - 597); 12.8% (10.5% - 15.1%)

 Tacoma, WA 43 (35 - 51); 4.2% (3.4% - 5%)

*Based on Krewski et al. (2009), exposure period from 1999 – 2000. The legend contains, for each urban area, the 

incidence estimate (and 95% CI) and the estimate of percent of total incidence (and 95% CI) under the current 

standards. 

**The current standards consist of an annual standard of 15 μg/m3

 and a daily standard of 35 μg/m3. Combinations of 

an annual standard (n) and a daily standard (m) are denoted n/m in this figure. 

***The percent reduction for 2006 air quality in Salt Lake City is -262%. 

E-49

September 2009 Draft - Do Not Quote or Cite
Figure E-12. Estimated Percent Reductions From the Current Standard to Alternative 

Standards in Ischemic Heart Disease Mortality Associated with Long-Term Exposure to PM2.5

(Exposure Period: 1999 – 2000): Based on 2007 Air Quality Data*

-200%

-180%

-160%

-140%

-120%

-100%

-80%

-60%

-40%

-20%

0%

20%

40%

60%

80%

100%

2007 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Reduction from Current Standard

 Atlanta, GA 278 (228 - 326); 16.8% (13.7% - 19.6%)

 Baltimore, MD 374 (306 - 440); 14.7% (12% - 17.3%)

 Birmingham, AL 188 (154 - 220); 15.7% (12.9% - 18.4%)

 Dallas, TX 243 (198 - 286); 11.2% (9.1% - 13.2%)

 Detroit, MI 415 (338 - 490); 10% (8.1% - 11.8%)

 Fresno, CA 109 (89 - 129); 9.5% (7.7% - 11.2%)

 Houston, TX 524 (430 - 615); 16.4% (13.5% - 19.2%)

 Los Angeles, CA 1173 (954 - 1388); 8.3% (6.7% - 9.8%)

 New York, NY 1818 (1481 - 2148); 9.6% (7.8% - 11.4%)

 Philadelphia, PA 337 (276 - 397); 13.5% (11% - 15.9%)

 Phoenix, AZ 418 (341 - 495); 8.9% (7.2% - 10.5%)

 Pittsburgh, PA 229 (187 - 271); 8.3% (6.8% - 9.9%)

 Salt Lake City, UT 27 (22 - 31); 5.1% (4.1% - 6.1%)

 St. Louis, MO 541 (443 - 637); 13.7% (11.2% - 16.1%)

 Tacoma, WA 52 (42 - 62); 5% (4.1% - 5.9%)

*Based on Krewski et al. (2009), exposure period from 1999 – 2000. The legend contains, for each urban area, the 

incidence estimate (and 95% CI) and the estimate of percent of total incidence (and 95% CI) under the current 

standards. 

**The current standards consist of an annual standard of 15 μg/m3

 and a daily standard of 35 μg/m3. Combinations of 

an annual standard (n) and a daily standard (m) are denoted n/m in this figure. 

E-50

September 2009 Draft - Do Not Quote or Cite
Table E-37. Estimated Annual Incidence of Cardiopulmonary Mortality Associated with Long-Term Exposure to Amb

 Concentrations in a Recent Year (2005) and PM2.5 Concentrations that Just Meet the Current and Alternative 

 on Adjusting 2005 PM2.5 Concentrations: Estimates Based on Krewski et al. (2009), Using Ambient PM2.5 from 

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

510 453 357 308 357 

(389 - 627) (346 - 558) (272 - 440) (234 - 381) (272 - 440) 

503 463 374 324 361 

(384 - 619) (353 - 570) (285 - 462) (247 - 401) (275 - 446) 

424 305 239 205 239 

(324 - 520) (232 - 376) (182 - 295) (156 - 254) (182 - 295) 

310 310 310 275 310 

(236 - 383) (236 - 383) (236 - 383) (209 - 340) (236 - 383) 

708 514 444 380 390 

(541 - 871) (391 - 634) (338 - 548) (288 - 470) (296 - 482) 

235 82 82 82 54 

(180 - 289) (62 - 102) (62 - 102) (62 - 102) (41 - 67) 

589 543 425 365 425 

(450 - 726) (414 - 669) (323 - 525) (278 - 452) (323 - 525) 

2465 1140 1140 1008 799 

(1883 - 3033) (866 - 1412) (866 - 1412) (765 - 1249) (606 - 990) 

1908 1386 1318 1112 1007 

(1454 - 2354) (1054 - 1714) (1002 - 1631) (845 - 1377) (764 - 1247) 

413 361 321 274 271 

(315 - 510) (275 - 445) (244 - 397) (209 - 339) (206 - 336) 

401 401 401 360 349 

(305 - 496) (305 - 496) (305 - 496) (273 - 446) (265 - 432) 

621 258 258 258 183 

(475 - 762) (196 - 319) (196 - 319) (196 - 319) (138 - 226) 

91 32 32 32 16 

(70 - 113) (24 - 39) (24 - 39) (24 - 39) (12 - 20) 

727 617 491 422 478 

(555 - 895) (471 - 761) (374 - 606) (321 - 522) (364 - 590) 

108 71 71 71 47 

(82 - 134) (54 - 88) (54 - 88) (54 - 88) (35 - 58) 

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

 Incidence of Cardiopulmonary Mortality Associated with Long-Term Exposure to PM2.5 Concentr

Year and PM2.5 Concentrations that Just Meet the Current and Alternative Annual (n) and Daily 

(Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

E-51

September 2009 
Table E-38. Estimated Annual Incidence of Cardiopulmonary Mortality Associated with Long-Term Exposure to Ambien

 Concentrations in a Recent Year (2006) and PM2.5 Concentrations that Just Meet the Current and Alternative St

 on Adjusting 2006 PM2.5 Concentrations: Estimates Based on Krewski et al. (2009), Using Ambient PM2.5 from 1

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

493 437 342 294 342 

(377 - 607) (333 - 539) (260 - 422) (223 - 363) (260 - 422) 

439 402 320 274 308 

(335 - 541) (306 - 496) (244 - 396) (208 - 339) (234 - 381) 

411 294 229 196 229 

(314 - 505) (224 - 362) (174 - 283) (149 - 243) (174 - 283) 

239 239 239 208 239 

(181 - 295) (181 - 295) (181 - 295) (158 - 257) (181 - 295) 

541 375 316 261 270 

(412 - 667) (285 - 464) (240 - 391) (198 - 324) (205 - 335) 

249 90 90 90 60 

(191 - 307) (68 - 111) (68 - 111) (68 - 111) (46 - 75) 

622 574 450 387 450 

(475 - 767) (438 - 707) (343 - 556) (295 - 479) (343 - 556) 

2217 973 973 849 653 

(1692 - 2731) (739 - 1206) (739 - 1206) (644 - 1053) (495 - 810) 

1651 1167 1104 913 815 

(1257 - 2040) (886 - 1444) (838 - 1367) (693 - 1131) (618 - 1011) 

405 353 314 268 265 

(309 - 500) (269 - 436) (239 - 388) (204 - 331) (201 - 328) 

438 438 438 395 383 

(333 - 542) (333 - 542) (333 - 542) (300 - 489) (291 - 474) 

540 209 209 209 141 

(413 - 665) (159 - 259) (159 - 259) (159 - 259) (107 - 175) 

76 20 20 20 6 

(58 - 94) (16 - 25) (16 - 25) (16 - 25) (5 - 8) 

566 471 362 303 351 

(432 - 699) (359 - 582) (275 - 448) (230 - 375) (267 - 435) 

71 39 39 39 20 

(54 - 87) (30 - 49) (30 - 49) (30 - 49) (15 - 24) 

 Incidence of Cardiopulmonary Mortality Associated with Long-Term Exposure to PM2.5 Concentratio

Year and PM2.5 Concentrations that Just Meet the Current and Alternative Annual (n) and Daily (m

(Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

E-52

September 2009 
Table E-39. Estimated Annual Incidence of Cardiopulmonary Mortality Associated with Long-Term Exposure to Ambient 

 Concentrations in a Recent Year (2007) and PM2.5 Concentrations that Just Meet the Current and Alternative Stan

 on Adjusting 2007 PM2.5 Concentrations: Estimates Based on Krewski et al. (2009), Using Ambient PM2.5 from 197

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

510 452 354 305 354 

(390 - 628) (345 - 558) (270 - 438) (232 - 377) (270 - 438) 

411 375 297 253 285 

(313 - 507) (286 - 463) (226 - 367) (192 - 313) (217 - 353) 

407 290 226 193 226 

(311 - 500) (221 - 358) (172 - 279) (147 - 239) (172 - 279) 

264 264 264 231 264 

(201 - 326) (201 - 326) (201 - 326) (176 - 286) (201 - 326) 

506 347 290 238 246 

(385 - 625) (264 - 430) (220 - 359) (180 - 295) (187 - 305) 

281 108 108 108 75 

(216 - 346) (82 - 133) (82 - 133) (82 - 133) (57 - 93) 

611 563 440 377 440 

(466 - 753) (429 - 694) (335 - 543) (287 - 467) (335 - 543) 

2265 1002 1002 876 677 

(1729 - 2791) (761 - 1241) (761 - 1241) (665 - 1086) (513 - 840) 

1679 1188 1125 931 832 

(1278 - 2074) (903 - 1471) (854 - 1393) (707 - 1154) (631 - 1032) 

401 349 310 265 262 

(306 - 495) (266 - 431) (236 - 384) (201 - 327) (199 - 324) 

381 381 381 339 328 

(289 - 471) (289 - 471) (289 - 471) (257 - 420) (249 - 406) 

547 214 214 214 145 

(418 - 673) (162 - 265) (162 - 265) (162 - 265) (110 - 180) 

106 39 39 39 22 

(80 - 130) (30 - 48) (30 - 48) (30 - 48) (17 - 27) 

603 505 391 330 380 

(460 - 744) (384 - 623) (297 - 484) (250 - 408) (289 - 470) 

81 48 48 48 27 

(62 - 101) (36 - 60) (36 - 60) (36 - 60) (20 - 33) 

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

 Incidence of Cardiopulmonary Mortality Associated with Long-Term Exposure to PM2.5 Concentration

Year and PM2.5 Concentrations that Just Meet the Current and Alternative Annual (n) and Daily (m) 

(Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

E-53

September 2009 
Table E-40. Estimated Percent of Total Annual Incidence of Cardiopulmonary Mortality Associated with Long-Term Expos

 Ambient PM2.5 Concentrations in a Recent Year (2005) and PM2.5 Concentrations that Just Meet the Current and A

 Standards, Based on Adjusting 2005 PM2.5 Concentrations: Estimates Based on Krewski et al. (2009), Using Ambie

 from 1979 - 19831 

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

8.7% 7.8% 6.1% 5.3% 6.1% 

(6.7% - 10.7%) (5.9% - 9.6%) (4.7% - 7.5%) (4% - 6.5%) (4.7% - 7.5%) (3.9

8.5% 7.9% 6.4% 5.5% 6.1% 

(6.5% - 10.5%) (6% - 9.7%) (4.8% - 7.8%) (4.2% - 6.8%) (4.7% - 7.6%) (3.3

10.2% 7.3% 5.7% 4.9% 5.7% 

(7.8% - 12.5%) (5.6% - 9%) (4.4% - 7.1%) (3.8% - 6.1%) (4.4% - 7.1%) (3.2

5.9% 5.9% 5.9% 5.2% 5.9% 

(4.5% - 7.2%) (4.5% - 7.2%) (4.5% - 7.2%) (4% - 6.4%) (4.5% - 7.2%) (4% 

8.6% 6.3% 5.4% 4.6% 4.7% 

(6.6% - 10.6%) (4.8% - 7.7%) (4.1% - 6.7%) (3.5% - 5.7%) (3.6% - 5.9%) (2.

9.1% 3.2% 3.2% 3.2% 2.1% 

(7% - 11.2%) (2.4% - 3.9%) (2.4% - 3.9%) (2.4% - 3.9%) (1.6% - 2.6%) (0.7

7.9% 7.3% 5.7% 4.9% 5.7% 

(6% - 9.7%) (5.6% - 9%) (4.3% - 7%) (3.7% - 6.1%) (4.3% - 7%) (3.7

8.8% 4.1% 4.1% 3.6% 2.8% 

(6.7% - 10.8%) (3.1% - 5%) (3.1% - 5%) (2.7% - 4.4%) (2.2% - 3.5%) (1.

6.7% 4.9% 4.6% 3.9% 3.5% 

(5.1% - 8.3%) (3.7% - 6%) (3.5% - 5.7%) (3% - 4.8%) (2.7% - 4.4%) (1.7

6.9% 6% 5.4% 4.6% 4.5% 

(5.3% - 8.5%) (4.6% - 7.4%) (4.1% - 6.6%) (3.5% - 5.7%) (3.4% - 5.6%) (2.3

4.3% 4.3% 4.3% 3.8% 3.7% 

(3.2% - 5.3%) (3.2% - 5.3%) (3.2% - 5.3%) (2.9% - 4.7%) (2.8% - 4.6%) (1.8

10.2% 4.2% 4.2% 4.2% 3% 

(7.8% - 12.5%) (3.2% - 5.2%) (3.2% - 5.2%) (3.2% - 5.2%) (2.3% - 3.7%) (1.3

5.3% 1.8% 1.8% 1.8% 0.9% 

(4.1% - 6.6%) (1.4% - 2.3%) (1.4% - 2.3%) (1.4% - 2.3%) (0.7% - 1.2%) (0% 

8.6% 7.3% 5.8% 5% 5.6% 

(6.5% - 10.5%) (5.5% - 9%) (4.4% - 7.1%) (3.8% - 6.1%) (4.3% - 6.9%) (3% 

4.9% 3.2% 3.2% 3.2% 2.1% 

(3.7% - 6.1%) (2.4% - 4%) (2.4% - 4%) (2.4% - 4%) (1.6% - 2.6%) (0.8

 Percent of Total Incidence of Cardiopulmonary Mortality Associated with Long-Term Exposure to 

Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the Current and Alternative An

Daily (m) Standards (Standard Combination Denoted n/m):

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL Baltimore, MD Detroit, MI Houston, TX New York, NY St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT

E-54

September 2009 
Table E-41. Estimated Percent of Total Annual Incidence of Cardiopulmonary Mortality Associated with Long-Term Expo

 Ambient PM2.5 Concentrations in a Recent Year (2006) and PM2.5 Concentrations that Just Meet the Current and 

 Standards, Based on Adjusting 2006 PM2.5 Concentrations: Estimates Based on Krewski et al. (2009), Using Ambi

 from 1979 - 19831

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

8.2% 7.3% 5.7% 4.9% 5.7% 

(6.3% - 10.1%) (5.5% - 8.9%) (4.3% - 7%) (3.7% - 6%) (4.3% - 7%) (3

7.4% 6.8% 5.4% 4.6% 5.2% 

(5.7% - 9.2%) (5.2% - 8.4%) (4.1% - 6.7%) (3.5% - 5.7%) (4% - 6.5%) (2

9.8% 7% 5.4% 4.7% 5.4% 

(7.5% - 12%) (5.3% - 8.6%) (4.1% - 6.7%) (3.5% - 5.8%) (4.1% - 6.7%) (

4.4% 4.4% 4.4% 3.8% 4.4% 

(3.4% - 5.5%) (3.4% - 5.5%) (3.4% - 5.5%) (2.9% - 4.8%) (3.4% - 5.5%) (2

6.6% 4.6% 3.9% 3.2% 3.3% 

(5% - 8.1%) (3.5% - 5.7%) (2.9% - 4.8%) (2.4% - 4%) (2.5% - 4.1%) (1

9.5% 3.4% 3.4% 3.4% 2.3% 

(7.3% - 11.7%) (2.6% - 4.2%) (2.6% - 4.2%) (2.6% - 4.2%) (1.7% - 2.9%) (0

8.1% 7.4% 5.8% 5% 5.8% 

(6.2% - 9.9%) (5.7% - 9.2%) (4.4% - 7.2%) (3.8% - 6.2%) (4.4% - 7.2%) (3

7.8% 3.4% 3.4% 3% 2.3% 

(6% - 9.7%) (2.6% - 4.3%) (2.6% - 4.3%) (2.3% - 3.7%) (1.8% - 2.9%) (0

5.8% 4.1% 3.8% 3.2% 2.8% 

(4.4% - 7.1%) (3.1% - 5%) (2.9% - 4.8%) (2.4% - 3.9%) (2.2% - 3.5%) (

6.8% 5.9% 5.2% 4.5% 4.4% 

(5.2% - 8.4%) (4.5% - 7.3%) (4% - 6.5%) (3.4% - 5.5%) (3.4% - 5.5%) (2

4.5% 4.5% 4.5% 4% 3.9% 

(3.4% - 5.5%) (3.4% - 5.5%) (3.4% - 5.5%) (3.1% - 5%) (3% - 4.8%) (1

8.9% 3.5% 3.5% 3.5% 2.3% 

(6.8% - 11%) (2.6% - 4.3%) (2.6% - 4.3%) (2.6% - 4.3%) (1.8% - 2.9%) (0

4.3% 1.2% 1.2% 1.2% 0.4% 

(3.3% - 5.3%) (0.9% - 1.4%) (0.9% - 1.4%) (0.9% - 1.4%) (0.3% - 0.4%) 

6.6% 5.5% 4.2% 3.5% 4.1% 

(5.1% - 8.2%) (4.2% - 6.8%) (3.2% - 5.3%) (2.7% - 4.4%) (3.1% - 5.1%) (

3.1% 1.8% 1.8% 1.8% 0.9% 

(2.4% - 3.9%) (1.3% - 2.2%) (1.3% - 2.2%) (1.3% - 2.2%) (0.7% - 1.1%) 

 Percent of Total Incidence of Cardiopulmonary Mortality Associated with Long-Term Exposure t

Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the Current and Alternative A

Daily (m) Standards (Standard Combination Denoted n/m):

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL Baltimore, MD Detroit, MI Houston, TX New York, NY St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT

E-55

September 2009 
Table E-42. Estimated Percent of Total Annual Incidence of Cardiopulmonary Mortality Associated with Long-Term Expo

 Ambient PM2.5 Concentrations in a Recent Year (2007) and PM2.5 Concentrations that Just Meet the Current and 

 Standards, Based on Adjusting 2007 PM2.5 Concentrations: Estimates Based on Krewski et al. (2009), Using Ambi

 from 1979 - 19831

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

8.3% 7.3% 5.7% 4.9% 5.7% 

(6.3% - 10.2%) (5.6% - 9%) (4.4% - 7.1%) (3.7% - 6.1%) (4.4% - 7.1%) (3

7% 6.4% 5% 4.3% 4.8% 

(5.3% - 8.6%) (4.9% - 7.9%) (3.8% - 6.2%) (3.3% - 5.3%) (3.7% - 6%) (2

9.6% 6.8% 5.3% 4.5% 5.3% 

(7.3% - 11.8%) (5.2% - 8.4%) (4% - 6.6%) (3.5% - 5.6%) (4% - 6.6%) (2

4.8% 4.8% 4.8% 4.2% 4.8% 

(3.6% - 5.9%) (3.6% - 5.9%) (3.6% - 5.9%) (3.2% - 5.2%) (3.6% - 5.9%) (3

6.2% 4.3% 3.6% 2.9% 3% 

(4.7% - 7.7%) (3.2% - 5.3%) (2.7% - 4.4%) (2.2% - 3.6%) (2.3% - 3.7%) (1

10.6% 4% 4% 4% 2.8% 

(8.1% - 13%) (3.1% - 5%) (3.1% - 5%) (3.1% - 5%) (2.1% - 3.5%) (

7.8% 7.2% 5.6% 4.8% 5.6% 

(5.9% - 9.6%) (5.5% - 8.8%) (4.3% - 6.9%) (3.6% - 5.9%) (4.3% - 6.9%) (3

8% 3.5% 3.5% 3.1% 2.4% 

(6.1% - 9.8%) (2.7% - 4.4%) (2.7% - 4.4%) (2.3% - 3.8%) (1.8% - 3%) (0

5.8% 4.1% 3.9% 3.2% 2.9% 

(4.4% - 7.2%) (3.1% - 5.1%) (3% - 4.8%) (2.4% - 4%) (2.2% - 3.6%) (

6.7% 5.8% 5.2% 4.4% 4.4% 

(5.1% - 8.3%) (4.4% - 7.2%) (3.9% - 6.4%) (3.4% - 5.5%) (3.3% - 5.4%) (2

3.8% 3.8% 3.8% 3.4% 3.3% 

(2.9% - 4.7%) (2.9% - 4.7%) (2.9% - 4.7%) (2.6% - 4.2%) (2.5% - 4%) (1

9.1% 3.5% 3.5% 3.5% 2.4% 

(6.9% - 11.2%) (2.7% - 4.4%) (2.7% - 4.4%) (2.7% - 4.4%) (1.8% - 3%) (0

5.8% 2.1% 2.1% 2.1% 1.2% 

(4.4% - 7.2%) (1.6% - 2.7%) (1.6% - 2.7%) (1.6% - 2.7%) (0.9% - 1.5%) (0

7.1% 5.9% 4.6% 3.9% 4.4% 

(5.4% - 8.7%) (4.5% - 7.3%) (3.5% - 5.7%) (2.9% - 4.8%) (3.4% - 5.5%) (2

3.6% 2.1% 2.1% 2.1% 1.2% 

(2.7% - 4.4%) (1.6% - 2.6%) (1.6% - 2.6%) (1.6% - 2.6%) (0.9% - 1.5%) (0

 Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Detroit, MI Houston, TX New York, NY St. Louis, MO

 Percent of Total Incidence of Cardiopulmonary Mortality Associated with Long-Term Exposure t

Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the Current and Alternative A

Daily (m) Standards (Standard Combination Denoted n/m):

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL Baltimore, MD

E-56

September 2009 
Table E-43. Percent Reduction from the Current Standards: Estimated Annual Incidence of Cardiopulmonary Disease M

 Associated with Long-Term Exposure to Ambient PM2.5 Concentrations, Based on Adjusting 2005 PM2.5 Concen

 Estimates Based on Krewski et al. (2009), Using Ambient PM2.5 from 1979 - 19831 

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

-13% 0% 21% 32% 21% 

(-12% - -13%) (0% - 0%) (21% - 21%) (32% - 32%) (21% - 21%) 

-9% 0% 19% 30% 22% 

(-9% - -9%) (0% - 0%) (19% - 19%) (30% - 30%) (22% - 22%) 

-39% 0% 22% 33% 22% 

(-39% - -40%) (0% - 0%) (21% - 22%) (32% - 33%) (21% - 22%) 

0% 0% 0% 11% 0% 

(0% - 0%) (0% - 0%) (0% - 0%) (11% - 11%) (0% - 0%) 

-38% 0% 14% 26% 24% 

(-37% - -38%) (0% - 0%) (14% - 14%) (26% - 26%) (24% - 24%) 

-186% 0% 0% 0% 34% 

(-184% - -188%) (0% - 0%) (0% - 0%) (0% - 0%) (34% - 35%) 

-9% 0% 22% 33% 22% 

(-8% - -9%) (0% - 0%) (22% - 22%) (33% - 33%) (22% - 22%) 

-116% 0% 0% 12% 30% 

(-115% - -117%) (0% - 0%) (0% - 0%) (12% - 12%) (30% - 30%) 

-38% 0% 5% 20% 27% 

(-37% - -38%) (0% - 0%) (5% - 5%) (20% - 20%) (27% - 27%) 

-15% 0% 11% 24% 25% 

(-15% - -15%) (0% - 0%) (11% - 11%) (24% - 24%) (25% - 25%) 

0% 0% 0% 10% 13% 

(0% - 0%) (0% - 0%) (0% - 0%) (10% - 10%) (13% - 13%) 

-141% 0% 0% 0% 29% 

(-139% - -142%) (0% - 0%) (0% - 0%) (0% - 0%) (29% - 29%) 

-190% 0% 0% 0% 49% 

(-189% - -191%) (0% - 0%) (0% - 0%) (0% - 0%) (49% - 49%) 

-18% 0% 20% 32% 23% 

(-18% - -18%) (0% - 0%) (20% - 21%) (31% - 32%) (22% - 23%) 

-53% 0% 0% 0% 34% 

(-53% - -54%) (0% - 0%) (0% - 0%) (0% - 0%) (34% - 34%) 

Percent Reduction from the Current Standards: Annual Incidence of Cardiopulmonary Disease Mortality A

Long-Term Exposure to PM2.5 Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet th

Alternative Annual (n) and Daily (m) Standards (Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

E-57

September 2009 
Table E-44. Percent Reduction from the Current Standards: Estimated Annual Incidence of Cardiopulmonary Disease 

 Associated with Long-Term Exposure to Ambient PM2.5 Concentrations, Based on Adjusting 2006 PM2.5 Conc

 Estimates Based on Krewski et al. (2009), Using Ambient PM2.5 from 1979 - 19831

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

-13% 0% 21% 32% 21% 

(-12% - -13%) (0% - 0%) (21% - 22%) (32% - 33%) (21% - 22%) 

-9% 0% 20% 31% 23% 

(-9% - -9%) (0% - 0%) (20% - 20%) (31% - 32%) (23% - 23%) 

-39% 0% 22% 33% 22% 

(-38% - -40%) (0% - 0%) (22% - 22%) (33% - 33%) (22% - 22%) 

0% 0% 0% 13% 0% 

(0% - 0%) (0% - 0%) (0% - 0%) (13% - 13%) (0% - 0%) 

-43% 0% 16% 30% 28% 

(-43% - -44%) (0% - 0%) (16% - 16%) (30% - 30%) (28% - 28%) 

-174% 0% 0% 0% 33% 

(-171% - -177%) (0% - 0%) (0% - 0%) (0% - 0%) (33% - 33%) 

-8% 0% 21% 32% 21% 

(-8% - -8%) (0% - 0%) (21% - 21%) (32% - 32%) (21% - 21%) 

-126% 0% 0% 13% 33% 

(-124% - -127%) (0% - 0%) (0% - 0%) (13% - 13%) (33% - 33%) 

-41% 0% 5% 22% 30% 

(-41% - -41%) (0% - 0%) (5% - 5%) (21% - 22%) (30% - 30%) 

-15% 0% 11% 24% 25% 

(-14% - -15%) (0% - 0%) (11% - 11%) (24% - 24%) (24% - 25%) 

0% 0% 0% 10% 12% 

(0% - 0%) (0% - 0%) (0% - 0%) (10% - 10%) (12% - 13%) 

-155% 0% 0% 0% 33% 

(-153% - -157%) (0% - 0%) (0% - 0%) (0% - 0%) (32% - 33%) 

-268% 0% 0% 0% 69% 

(-266% - -270%) (0% - 0%) (0% - 0%) (0% - 0%) (69% - 69%) 

-20% 0% 23% 35% 25% 

(-20% - -20%) (0% - 0%) (23% - 23%) (35% - 36%) (25% - 25%) 

-79% 0% 0% 0% 50% 

(-79% - -79%) (0% - 0%) (0% - 0%) (0% - 0%) (50% - 50%) 

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Percent Reduction from the Current Standards: Annual Incidence of Cardiopulmonary Disease Morta

Long-Term Exposure to PM2.5 Concentrations in a Recent Year and PM2.5 Concentrations that Just M

Alternative Annual (n) and Daily (m) Standards (Standard Combination Denoted n/m

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

E-58

September 2009 
Table E-45. Percent Reduction from the Current Standards: Estimated Annual Incidence of Cardiopulmonary Disease 

 Associated with Long-Term Exposure to Ambient PM2.5 Concentrations, Based on Adjusting 2007 PM2.5 Conc

 Estimates Based on Krewski et al. (2009), Using Ambient PM2.5 from 1979 - 19831 

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

-13% 0% 22% 33% 22% 

(-13% - -13%) (0% - 0%) (22% - 22%) (32% - 33%) (22% - 22%) 

-10% 0% 21% 33% 24% 

(-9% - -10%) (0% - 0%) (21% - 21%) (33% - 33%) (24% - 24%) 

-40% 0% 22% 33% 22% 

(-40% - -41%) (0% - 0%) (22% - 22%) (33% - 34%) (22% - 22%) 

0% 0% 0% 12% 0% 

(0% - 0%) (0% - 0%) (0% - 0%) (12% - 12%) (0% - 0%) 

-46% 0% 16% 32% 29% 

(-45% - -46%) (0% - 0%) (16% - 17%) (31% - 32%) (29% - 29%) 

-161% 0% 0% 0% 30% 

(-159% - -164%) (0% - 0%) (0% - 0%) (0% - 0%) (30% - 30%) 

-9% 0% 22% 33% 22% 

(-9% - -9%) (0% - 0%) (22% - 22%) (33% - 33%) (22% - 22%) 

-126% 0% 0% 13% 32% 

(-125% - -127%) (0% - 0%) (0% - 0%) (13% - 13%) (32% - 33%) 

-41% 0% 5% 22% 30% 

(-41% - -42%) (0% - 0%) (5% - 5%) (22% - 22%) (30% - 30%) 

-15% 0% 11% 24% 25% 

(-15% - -15%) (0% - 0%) (11% - 11%) (24% - 24%) (25% - 25%) 

0% 0% 0% 11% 14% 

(0% - 0%) (0% - 0%) (0% - 0%) (11% - 11%) (14% - 14%) 

-156% 0% 0% 0% 32% 

(-154% - -157%) (0% - 0%) (0% - 0%) (0% - 0%) (32% - 32%) 

-170% 0% 0% 0% 44% 

(-169% - -172%) (0% - 0%) (0% - 0%) (0% - 0%) (44% - 44%) 

-20% 0% 22% 35% 25% 

(-19% - -20%) (0% - 0%) (22% - 23%) (34% - 35%) (25% - 25%) 

-70% 0% 0% 0% 44% 

(-70% - -70%) (0% - 0%) (0% - 0%) (0% - 0%) (44% - 44%) 

Percent Reduction from the Current Standards: Annual Incidence of Cardiopulmonary Disease Mor

Long-Term Exposure to PM2.5 Concentrations in a Recent Year and PM2.5 Concentrations that Just 

Alternative Annual (n) and Daily (m) Standards (Standard Combination Denoted n/

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

E-59

September 2009 
Figure E-13. Estimated Percent Reductions From the Current Standard to Alternative 

Standards in Cardiopulmonary Disease Mortality Associated with Long-Term Exposure to 

PM2.5 (Exposure Period: 1979 – 1983): Based on 2005 Air Quality Data*

-200%

-180%

-160%

-140%

-120%

-100%

-80%

-60%

-40%

-20%

0%

20%

40%

60%

80%

100%

2005 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Reduction from Current Standard

 Atlanta, GA 453 (346 - 558); 7.8% (5.9% - 9.6%)

 Baltimore, MD 463 (353 - 570); 7.9% (6% - 9.7%)

 Birmingham, AL 305 (232 - 376); 7.3% (5.6% - 9%)

 Dallas, TX 310 (236 - 383); 5.9% (4.5% - 7.2%)

 Detroit, MI 514 (391 - 634); 6.3% (4.8% - 7.7%)

 Fresno, CA 82 (62 - 102); 3.2% (2.4% - 3.9%)

 Houston, TX 543 (414 - 669); 7.3% (5.6% - 9%)

 Los Angeles, CA 1140 (866 - 1412); 4.1% (3.1% - 5%)

 New York, NY 1386 (1054 - 1714); 4.9% (3.7% - 6%)

 Philadelphia, PA 361 (275 - 445); 6% (4.6% - 7.4%)

 Phoenix, AZ 401 (305 - 496); 4.3% (3.2% - 5.3%)

 Pittsburgh, PA 258 (196 - 319); 4.2% (3.2% - 5.2%)

 Salt Lake City, UT 32 (24 - 39); 1.8% (1.4% - 2.3%)

 St. Louis, MO 617 (471 - 761); 7.3% (5.5% - 9%)

 Tacoma, WA 71 (54 - 88); 3.2% (2.4% - 4%)

*Based on Krewski et al. (2009), exposure period from 1979 – 1983. The legend contains, for each urban area, the 

incidence estimate (and 95% CI) and the estimate of percent of total incidence (and 95% CI) under the current 

standards. 

**The current standards consist of an annual standard of 15 μg/m3

 and a daily standard of 35 μg/m3. Combinations of 

an annual standard (n) and a daily standard (m) are denoted n/m in this figure. 

E-60

September 2009 Draft - Do Not Quote or Cite
Figure E-14. Estimated Percent Reductions From the Current Standard to Alternative 

Standards in Cardiopulmonary Disease Mortality Associated with Long-Term Exposure to 

PM2.5 (Exposure Period: 1979 – 1983): Based on 2006 Air Quality Data* 

-200%

-180%

-160%

-140%

-120%

-100%

-80%

-60%

-40%

-20%

0%

20%

40%

60%

80%

100%

2006 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Reduction from Current Standard

 Atlanta, GA 437 (333 - 539); 7.3% (5.5% - 8.9%)

 Baltimore, MD 402 (306 - 496); 6.8% (5.2% - 8.4%)

 Birmingham, AL 294 (224 - 362); 7% (5.3% - 8.6%)

 Dallas, TX 239 (181 - 295); 4.4% (3.4% - 5.5%)

 Detroit, MI 375 (285 - 464); 4.6% (3.5% - 5.7%)

 Fresno, CA 90 (68 - 111); 3.4% (2.6% - 4.2%)

 Houston, TX 574 (438 - 707); 7.4% (5.7% - 9.2%)

 Los Angeles, CA 973 (739 - 1206); 3.4% (2.6% - 4.3%)

 New York, NY 1167 (886 - 1444); 4.1% (3.1% - 5%)

 Philadelphia, PA 353 (269 - 436); 5.9% (4.5% - 7.3%)

 Phoenix, AZ 438 (333 - 542); 4.5% (3.4% - 5.5%)

 Pittsburgh, PA 209 (159 - 259); 3.5% (2.6% - 4.3%)

 Salt Lake City, UT 20 (16 - 25); 1.2% (0.9% - 1.4%)

 St. Louis, MO 471 (359 - 582); 5.5% (4.2% - 6.8%)

 Tacoma, WA 39 (30 - 49); 1.8% (1.3% - 2.2%)

*Based on Krewski et al. (2009), exposure period from 1979 – 1983. The legend contains, for each urban area, the 

incidence estimate (and 95% CI) and the estimate of percent of total incidence (and 95% CI) under the current 

standards. 

**The current standards consist of an annual standard of 15 μg/m3

 and a daily standard of 35 μg/m3. Combinations of 

an annual standard (n) and a daily standard (m) are denoted n/m in this figure. 

***The percent reduction for 2006 air quality in Salt Lake City is -268%. 

E-61

September 2009 Draft - Do Not Quote or Cite
Figure E-15. Estimated Percent Reductions From the Current Standard to Alternative 

Standards in Cardiopulmonary Disease Mortality Associated with Long-Term Exposure to 

PM2.5 (Exposure Period: 1979 – 1983): Based on 2007 Air Quality Data*

-200%

-180%

-160%

-140%

-120%

-100%

-80%

-60%

-40%

-20%

0%

20%

40%

60%

80%

100%

2007 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Reduction from Current Standard

 Atlanta, GA 452 (345 - 558); 7.3% (5.6% - 9%)

 Baltimore, MD 375 (286 - 463); 6.4% (4.9% - 7.9%)

 Birmingham, AL 290 (221 - 358); 6.8% (5.2% - 8.4%)

 Dallas, TX 264 (201 - 326); 4.8% (3.6% - 5.9%)

 Detroit, MI 347 (264 - 430); 4.3% (3.2% - 5.3%)

 Fresno, CA 108 (82 - 133); 4% (3.1% - 5%)

 Houston, TX 563 (429 - 694); 7.2% (5.5% - 8.8%)

 Los Angeles, CA 1002 (761 - 1241); 3.5% (2.7% - 4.4%)

 New York, NY 1188 (903 - 1471); 4.1% (3.1% - 5.1%)

 Philadelphia, PA 349 (266 - 431); 5.8% (4.4% - 7.2%)

 Phoenix, AZ 381 (289 - 471); 3.8% (2.9% - 4.7%)

 Pittsburgh, PA 214 (162 - 265); 3.5% (2.7% - 4.4%)

 Salt Lake City, UT 39 (30 - 48); 2.1% (1.6% - 2.7%)

 St. Louis, MO 505 (384 - 623); 5.9% (4.5% - 7.3%)

 Tacoma, WA 48 (36 - 60); 2.1% (1.6% - 2.6%)

*Based on Krewski et al. (2009), exposure period from 1979 – 1983. The legend contains, for each urban area, the 

incidence estimate (and 95% CI) and the estimate of percent of total incidence (and 95% CI) under the current 

standards. 

**The current standards consist of an annual standard of 15 μg/m3

 and a daily standard of 35 μg/m3. Combinations of 

an annual standard (n) and a daily standard (m) are denoted n/m in this figure. 

E-62

September 2009 Draft - Do Not Quote or Cite
Table E-46. Estimated Annual Incidence of Cardiopulmonary Mortality Associated with Long-Term Exposure to Ambi

 Concentrations in a Recent Year (2005) and PM2.5 Concentrations that Just Meet the Current and Alternative 

 on Adjusting 2005 PM2.5 Concentrations: Estimates Based on Krewski et al. (2009), Using Ambient PM2.5 from 

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

719 640 506 438 506 

(566 - 868) (503 - 774) (397 - 614) (343 - 532) (397 - 614) 

710 654 531 461 512 

(558 - 857) (514 - 790) (416 - 643) (361 - 559) (401 - 621) 

596 431 339 292 339 

(470 - 717) (339 - 522) (266 - 411) (228 - 355) (266 - 411) 

440 440 440 391 440 

(345 - 534) (345 - 534) (345 - 534) (306 - 475) (345 - 534) 

999 729 631 541 555 

(786 - 1205) (571 - 883) (494 - 765) (423 - 657) (434 - 674) 

331 117 117 117 77 

(261 - 399) (92 - 143) (92 - 143) (92 - 143) (60 - 94) 

833 768 604 520 604 

(655 - 1007) (603 - 929) (473 - 732) (406 - 631) (473 - 732) 

3477 1626 1626 1439 1142 

(2737 - 4196) (1270 - 1977) (1270 - 1977) (1123 - 1752) (890 - 1392) 

2704 1972 1878 1586 1437 

(2121 - 3274) (1542 - 2395) (1468 - 2281) (1239 - 1930) (1121 - 1749) 

586 512 457 391 387 

(459 - 709) (401 - 620) (357 - 554) (305 - 475) (302 - 470) 

571 571 571 514 498 

(446 - 695) (446 - 695) (446 - 695) (401 - 625) (389 - 606) 

873 368 368 368 261 

(689 - 1051) (287 - 447) (287 - 447) (287 - 447) (203 - 318) 

130 45 45 45 23 

(102 - 158) (35 - 55) (35 - 55) (35 - 55) (18 - 28) 

1026 874 697 601 679 

(807 - 1238) (686 - 1057) (546 - 845) (470 - 729) (532 - 823) 

154 101 101 101 67 

(121 - 187) (79 - 123) (79 - 123) (79 - 123) (52 - 82) 

 Incidence of Cardiopulmonary Mortality Associated with Long-Term Exposure to PM2.5 Concentra

Year and PM2.5 Concentrations that Just Meet the Current and Alternative Annual (n) and Daily 

(Standard Combination Denoted n/m):

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL Baltimore, MD Detroit, MI Houston, TX New York, NY St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT

E-63

September 2009 
Table E-47. Estimated Annual Incidence of Cardiopulmonary Mortality Associated with Long-Term Exposure to Ambi

 Concentrations in a Recent Year (2006) and PM2.5 Concentrations that Just Meet the Current and Alternative 

 on Adjusting 2006 PM2.5 Concentrations: Estimates Based on Krewski et al. (2009), Using Ambient PM2.5 from 

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

697 619 486 418 486 

(548 - 841) (486 - 748) (380 - 589) (327 - 508) (380 - 589) 

621 569 455 390 438 

(488 - 751) (447 - 689) (356 - 552) (305 - 474) (343 - 532) 

578 416 325 279 325 

(456 - 696) (326 - 503) (255 - 395) (218 - 339) (255 - 395) 

340 340 340 297 340 

(266 - 413) (266 - 413) (266 - 413) (232 - 361) (266 - 413) 

767 535 451 373 386 

(601 - 929) (418 - 650) (352 - 548) (291 - 455) (301 - 470) 

351 128 128 128 86 

(277 - 423) (100 - 156) (100 - 156) (100 - 156) (67 - 105) 

879 812 639 551 639 

(691 - 1062) (637 - 982) (501 - 775) (431 - 669) (501 - 775) 

3134 1390 1390 1214 935 

(2463 - 3788) (1084 - 1692) (1084 - 1692) (946 - 1479) (728 - 1140) 

2346 1663 1575 1304 1165 

(1837 - 2845) (1299 - 2023) (1230 - 1916) (1017 - 1588) (908 - 1420) 

574 501 447 382 378 

(450 - 695) (393 - 608) (349 - 542) (298 - 464) (295 - 459) 

624 624 624 563 546 

(488 - 758) (488 - 758) (488 - 758) (440 - 685) (426 - 664) 

762 299 299 299 202 

(600 - 919) (233 - 364) (233 - 364) (233 - 364) (157 - 246) 

108 29 29 29 9 

(85 - 132) (23 - 36) (23 - 36) (23 - 36) (7 - 11) 

803 670 516 433 500 

(630 - 972) (524 - 813) (403 - 628) (338 - 526) (391 - 609) 

101 56 56 56 28 

(79 - 123) (44 - 69) (44 - 69) (44 - 69) (22 - 34) 

 Incidence of Cardiopulmonary Mortality Associated with Long-Term Exposure to PM2.5 Concen

Year and PM2.5 Concentrations that Just Meet the Current and Alternative Annual (n) and Da

(Standard Combination Denoted n/m):

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL Baltimore, MD Detroit, MI Houston, TX New York, NY St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT

E-64

September 2009 
Table E-48. Estimated Annual Incidence of Cardiopulmonary Mortality Associated with Long-Term Exposure to Ambi

 Concentrations in a Recent Year (2007) and PM2.5 Concentrations that Just Meet the Current and Alternative 

 on Adjusting 2007 PM2.5 Concentrations: Estimates Based on Krewski et al. (2009), Using Ambient PM2.5 from 

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

721 640 503 434 503 

(567 - 870) (503 - 774) (394 - 610) (339 - 527) (394 - 610) 

582 533 423 360 406 

(457 - 705) (418 - 645) (331 - 513) (281 - 438) (317 - 493) 

573 411 321 275 321 

(451 - 690) (322 - 498) (251 - 389) (215 - 334) (251 - 389) 

376 376 376 330 376 

(294 - 456) (294 - 456) (294 - 456) (258 - 401) (294 - 456) 

718 495 414 340 352 

(563 - 870) (387 - 602) (323 - 504) (265 - 414) (274 - 429) 

395 154 154 154 108 

(312 - 476) (120 - 187) (120 - 187) (120 - 187) (84 - 131) 

864 797 625 537 625 

(679 - 1044) (625 - 964) (489 - 758) (420 - 652) (489 - 758) 

3202 1431 1431 1252 969 

(2517 - 3869) (1116 - 1741) (1116 - 1741) (976 - 1525) (755 - 1181) 

2385 1694 1605 1331 1190 

(1868 - 2891) (1323 - 2060) (1253 - 1952) (1038 - 1620) (928 - 1450) 

568 496 441 377 373 

(446 - 688) (388 - 601) (345 - 536) (295 - 458) (291 - 453) 

543 543 543 485 469 

(424 - 661) (424 - 661) (424 - 661) (378 - 590) (365 - 571) 

771 305 305 305 208 

(607 - 930) (238 - 372) (238 - 372) (238 - 372) (162 - 253) 

150 56 56 56 32 

(118 - 182) (44 - 68) (44 - 68) (44 - 68) (25 - 39) 

854 717 557 471 541 

(670 - 1034) (561 - 869) (436 - 677) (367 - 572) (423 - 657) 

116 69 69 69 38 

(91 - 142) (53 - 84) (53 - 84) (53 - 84) (30 - 47) 

 Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Detroit, MI Houston, TX New York, NY St. Louis, MO

 Incidence of Cardiopulmonary Mortality Associated with Long-Term Exposure to PM2.5 Concentr

Year and PM2.5 Concentrations that Just Meet the Current and Alternative Annual (n) and Daily 

(Standard Combination Denoted n/m):

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL Baltimore, MD

E-65

September 2009 
Table E-49. Estimated Percent of Total Annual Incidence of Cardiopulmonary Mortality Associated with Long-Term Expo

 Ambient PM2.5 Concentrations in a Recent Year (2005) and PM2.5 Concentrations that Just Meet the Current and 

 Standards, Based on Adjusting 2005 PM2.5 Concentrations: Estimates Based on Krewski et al. (2009), Using Ambi

 from 1999 - 20001 

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

12.3% 11% 8.7% 7.5% 8.7% 

(9.7% - 14.9%) (8.6% - 13.2%) (6.8% - 10.5%) (5.9% - 9.1%) (6.8% - 10.5%) (5

12.1% 11.1% 9% 7.8% 8.7% 

(9.5% - 14.6%) (8.7% - 13.4%) (7.1% - 10.9%) (6.1% - 9.5%) (6.8% - 10.5%) (4

14.3% 10.4% 8.2% 7% 8.2% 

(11.3% - 17.3%) (8.2% - 12.6%) (6.4% - 9.9%) (5.5% - 8.5%) (6.4% - 9.9%) (4

8.3% 8.3% 8.3% 7.4% 8.3% 

(6.5% - 10.1%) (6.5% - 10.1%) (6.5% - 10.1%) (5.8% - 9%) (6.5% - 10.1%) (

12.2% 8.9% 7.7% 6.6% 6.8% 

(9.6% - 14.7%) (7% - 10.8%) (6% - 9.3%) (5.1% - 8%) (5.3% - 8.2%) (3

12.8% 4.5% 4.5% 4.5% 3% 

(10.1% - 15.5%) (3.5% - 5.5%) (3.5% - 5.5%) (3.5% - 5.5%) (2.3% - 3.6%) (1

11.2% 10.3% 8.1% 7% 8.1% 

(8.8% - 13.5%) (8.1% - 12.5%) (6.3% - 9.8%) (5.5% - 8.5%) (6.3% - 9.8%) (5

12.4% 5.8% 5.8% 5.1% 4.1% 

(9.7% - 14.9%) (4.5% - 7%) (4.5% - 7%) (4% - 6.2%) (3.2% - 5%) (1

9.5% 6.9% 6.6% 5.6% 5.1% 

(7.5% - 11.5%) (5.4% - 8.4%) (5.2% - 8%) (4.4% - 6.8%) (3.9% - 6.2%) (2

9.8% 8.5% 7.6% 6.5% 6.5% 

(7.7% - 11.8%) (6.7% - 10.3%) (6% - 9.2%) (5.1% - 7.9%) (5% - 7.8%) (3

6.1% 6.1% 6.1% 5.5% 5.3% 

(4.7% - 7.4%) (4.7% - 7.4%) (4.7% - 7.4%) (4.3% - 6.6%) (4.1% - 6.4%) (

14.3% 6% 6% 6% 4.3% 

(11.3% - 17.2%) (4.7% - 7.3%) (4.7% - 7.3%) (4.7% - 7.3%) (3.3% - 5.2%) (

7.6% 2.6% 2.6% 2.6% 1.4% 

(5.9% - 9.2%) (2% - 3.2%) (2% - 3.2%) (2% - 3.2%) (1.1% - 1.7%) (

12.1% 10.3% 8.2% 7.1% 8% 

(9.5% - 14.6%) (8.1% - 12.4%) (6.4% - 10%) (5.5% - 8.6%) (6.3% - 9.7%) (4

7% 4.6% 4.6% 4.6% 3% 

(5.5% - 8.5%) (3.6% - 5.6%) (3.6% - 5.6%) (3.6% - 5.6%) (2.4% - 3.7%) (1

 Percent of Total Incidence of Cardiopulmonary Mortality Associated with Long-Term Exposure t

Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the Current and Alternative A

Daily (m) Standards (Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

E-66

September 2009 
Table E-50. Estimated Percent of Total Annual Incidence of Cardiopulmonary Mortality Associated with Long-Term Expo

 Ambient PM2.5 Concentrations in a Recent Year (2006) and PM2.5 Concentrations that Just Meet the Current and 

 Standards, Based on Adjusting 2006 PM2.5 Concentrations: Estimates Based on Krewski et al. (2009), Using Ambi

 from 1999 - 20001

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

11.6% 10.3% 8.1% 6.9% 8.1% 

(9.1% - 14%) (8.1% - 12.4%) (6.3% - 9.8%) (5.4% - 8.4%) (6.3% - 9.8%) (5

10.5% 9.7% 7.7% 6.6% 7.4% 

(8.3% - 12.7%) (7.6% - 11.7%) (6% - 9.4%) (5.2% - 8%) (5.8% - 9%) (

13.8% 9.9% 7.7% 6.6% 7.7% 

(10.8% - 16.6%) (7.8% - 12%) (6.1% - 9.4%) (5.2% - 8.1%) (6.1% - 9.4%) (4

6.3% 6.3% 6.3% 5.5% 6.3% 

(4.9% - 7.6%) (4.9% - 7.6%) (4.9% - 7.6%) (4.3% - 6.7%) (4.9% - 7.6%) (4

9.4% 6.5% 5.5% 4.6% 4.7% 

(7.3% - 11.3%) (5.1% - 7.9%) (4.3% - 6.7%) (3.6% - 5.5%) (3.7% - 5.7%) (2

13.4% 4.9% 4.9% 4.9% 3.3% 

(10.6% - 16.2%) (3.8% - 6%) (3.8% - 6%) (3.8% - 6%) (2.6% - 4%) (

11.4% 10.5% 8.3% 7.2% 8.3% 

(9% - 13.8%) (8.3% - 12.7%) (6.5% - 10.1%) (5.6% - 8.7%) (6.5% - 10.1%) (5

11.1% 4.9% 4.9% 4.3% 3.3% 

(8.7% - 13.4%) (3.8% - 6%) (3.8% - 6%) (3.3% - 5.2%) (2.6% - 4%) (

8.2% 5.8% 5.5% 4.5% 4.1% 

(6.4% - 9.9%) (4.5% - 7%) (4.3% - 6.7%) (3.5% - 5.5%) (3.2% - 4.9%) (1

9.6% 8.4% 7.5% 6.4% 6.3% 

(7.5% - 11.6%) (6.6% - 10.2%) (5.8% - 9.1%) (5% - 7.8%) (4.9% - 7.7%) (3

6.4% 6.4% 6.4% 5.8% 5.6% 

(5% - 7.8%) (5% - 7.8%) (5% - 7.8%) (4.5% - 7%) (4.4% - 6.8%) (2

12.6% 4.9% 4.9% 4.9% 3.3% 

(9.9% - 15.2%) (3.8% - 6%) (3.8% - 6%) (3.8% - 6%) (2.6% - 4.1%) (1

6.1% 1.7% 1.7% 1.7% 0.5% 

(4.8% - 7.4%) (1.3% - 2%) (1.3% - 2%) (1.3% - 2%) (0.4% - 0.6%) 

9.4% 7.8% 6.1% 5.1% 5.9% 

(7.4% - 11.4%) (6.1% - 9.5%) (4.7% - 7.4%) (4% - 6.2%) (4.6% - 7.1%) (

4.5% 2.5% 2.5% 2.5% 1.2% 

(3.5% - 5.5%) (2% - 3.1%) (2% - 3.1%) (2% - 3.1%) (1% - 1.5%) 

 Percent of Total Incidence of Cardiopulmonary Mortality Associated with Long-Term Exposure t

Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the Current and Alternative A

Daily (m) Standards (Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

E-67

September 2009 
Table E-51. Estimated Percent of Total Annual Incidence of Cardiopulmonary Mortality Associated with Long-Term Expo

 Ambient PM2.5 Concentrations in a Recent Year (2007) and PM2.5 Concentrations that Just Meet the Current and 

 Standards, Based on Adjusting 2007 PM2.5 Concentrations: Estimates Based on Krewski et al. (2009), Using Ambi

 from 1999 - 20001 

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

11.7% 10.4% 8.1% 7% 8.1% 

(9.2% - 14.1%) (8.1% - 12.5%) (6.4% - 9.9%) (5.5% - 8.5%) (6.4% - 9.9%) (5

9.9% 9.1% 7.2% 6.1% 6.9% 

(7.8% - 12%) (7.1% - 11%) (5.6% - 8.7%) (4.8% - 7.4%) (5.4% - 8.4%) (3

13.5% 9.7% 7.6% 6.5% 7.6% 

(10.6% - 16.3%) (7.6% - 11.7%) (5.9% - 9.2%) (5.1% - 7.9%) (5.9% - 9.2%) (4

6.8% 6.8% 6.8% 6% 6.8% 

(5.3% - 8.3%) (5.3% - 8.3%) (5.3% - 8.3%) (4.7% - 7.3%) (5.3% - 8.3%) (4

8.8% 6.1% 5.1% 4.2% 4.3% 

(6.9% - 10.7%) (4.7% - 7.4%) (4% - 6.2%) (3.3% - 5.1%) (3.4% - 5.3%) (

14.8% 5.8% 5.8% 5.8% 4% 

(11.7% - 17.8%) (4.5% - 7%) (4.5% - 7%) (4.5% - 7%) (3.2% - 4.9%) (1

11% 10.1% 7.9% 6.8% 7.9% 

(8.6% - 13.3%) (8% - 12.3%) (6.2% - 9.6%) (5.3% - 8.3%) (6.2% - 9.6%) (5

11.2% 5% 5% 4.4% 3.4% 

(8.8% - 13.6%) (3.9% - 6.1%) (3.9% - 6.1%) (3.4% - 5.4%) (2.7% - 4.2%) (1

8.2% 5.9% 5.5% 4.6% 4.1% 

(6.5% - 10%) (4.6% - 7.1%) (4.3% - 6.8%) (3.6% - 5.6%) (3.2% - 5%) (1

9.5% 8.3% 7.4% 6.3% 6.2% 

(7.4% - 11.5%) (6.5% - 10%) (5.8% - 9%) (4.9% - 7.7%) (4.9% - 7.6%) (

5.4% 5.4% 5.4% 4.8% 4.6% 

(4.2% - 6.6%) (4.2% - 6.6%) (4.2% - 6.6%) (3.8% - 5.9%) (3.6% - 5.7%) (2

12.8% 5.1% 5.1% 5.1% 3.4% 

(10.1% - 15.4%) (4% - 6.2%) (4% - 6.2%) (4% - 6.2%) (2.7% - 4.2%) (1

8.2% 3.1% 3.1% 3.1% 1.7% 

(6.5% - 10%) (2.4% - 3.7%) (2.4% - 3.7%) (2.4% - 3.7%) (1.3% - 2.1%) (0

10% 8.4% 6.5% 5.5% 6.3% 

(7.8% - 12.1%) (6.6% - 10.2%) (5.1% - 7.9%) (4.3% - 6.7%) (4.9% - 7.7%) (3

5.1% 3% 3% 3% 1.7% 

(4% - 6.2%) (2.3% - 3.7%) (2.3% - 3.7%) (2.3% - 3.7%) (1.3% - 2.1%) (0

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

 Percent of Total Incidence of Cardiopulmonary Mortality Associated with Long-Term Exposure t

Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the Current and Alternative A

Daily (m) Standards (Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

E-68

September 2009 
Table E-52. Percent Reduction from the Current Standards: Estimated Annual Incidence of Cardiopulmonary Disease 

 Associated with Long-Term Exposure to Ambient PM2.5 Concentrations, Based on Adjusting 2005 PM2.5 Conc

 Estimates Based on Krewski et al. (2009), Using Ambient PM2.5 from 1999 - 20001 

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

-12% 0% 21% 32% 21% 

(-12% - -12%) (0% - 0%) (21% - 21%) (31% - 32%) (21% - 21%) 

-9% 0% 19% 30% 22% 

(-8% - -9%) (0% - 0%) (19% - 19%) (29% - 30%) (21% - 22%) 

-38% 0% 21% 32% 21% 

(-38% - -39%) (0% - 0%) (21% - 22%) (32% - 33%) (21% - 22%) 

0% 0% 0% 11% 0% 

(0% - 0%) (0% - 0%) (0% - 0%) (11% - 11%) (0% - 0%) 

-37% 0% 13% 26% 24% 

(-36% - -38%) (0% - 0%) (13% - 14%) (26% - 26%) (24% - 24%) 

-182% 0% 0% 0% 34% 

(-179% - -185%) (0% - 0%) (0% - 0%) (0% - 0%) (34% - 34%) 

-8% 0% 21% 32% 21% 

(-8% - -9%) (0% - 0%) (21% - 22%) (32% - 33%) (21% - 22%) 

-114% 0% 0% 11% 30% 

(-112% - -116%) (0% - 0%) (0% - 0%) (11% - 12%) (30% - 30%) 

-37% 0% 5% 20% 27% 

(-37% - -38%) (0% - 0%) (5% - 5%) (19% - 20%) (27% - 27%) 

-14% 0% 11% 24% 24% 

(-14% - -15%) (0% - 0%) (11% - 11%) (23% - 24%) (24% - 25%) 

0% 0% 0% 10% 13% 

(0% - 0%) (0% - 0%) (0% - 0%) (10% - 10%) (13% - 13%) 

-137% 0% 0% 0% 29% 

(-135% - -140%) (0% - 0%) (0% - 0%) (0% - 0%) (29% - 29%) 

-188% 0% 0% 0% 48% 

(-186% - -189%) (0% - 0%) (0% - 0%) (0% - 0%) (48% - 49%) 

-17% 0% 20% 31% 22% 

(-17% - -18%) (0% - 0%) (20% - 20%) (31% - 32%) (22% - 23%) 

-53% 0% 0% 0% 34% 

(-52% - -53%) (0% - 0%) (0% - 0%) (0% - 0%) (33% - 34%) 

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Percent Reduction from the Current Standards: Annual Incidence of Cardiopulmonary Disease Mort

Long-Term Exposure to PM2.5 Concentrations in a Recent Year and PM2.5 Concentrations that Just M

Alternative Annual (n) and Daily (m) Standards (Standard Combination Denoted n/

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

E-69

September 2009 
Table E-53. Percent Reduction from the Current Standards: Estimated Annual Incidence of Cardiopulmonary Disease 

 Associated with Long-Term Exposure to Ambient PM2.5 Concentrations, Based on Adjusting 2006 PM2.5 Conc

 Estimates Based on Krewski et al. (2009), Using Ambient PM2.5 from 1999 - 20001

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

-13% 0% 21% 32% 21% 

(-12% - -13%) (0% - 0%) (21% - 22%) (32% - 33%) (21% - 22%) 

-9% 0% 20% 31% 23% 

(-9% - -9%) (0% - 0%) (20% - 20%) (31% - 32%) (23% - 23%) 

-39% 0% 22% 33% 22% 

(-38% - -40%) (0% - 0%) (22% - 22%) (33% - 33%) (22% - 22%) 

0% 0% 0% 13% 0% 

(0% - 0%) (0% - 0%) (0% - 0%) (13% - 13%) (0% - 0%) 

-43% 0% 16% 30% 28% 

(-43% - -44%) (0% - 0%) (16% - 16%) (30% - 30%) (28% - 28%) 

-174% 0% 0% 0% 33% 

(-171% - -177%) (0% - 0%) (0% - 0%) (0% - 0%) (33% - 33%) 

-8% 0% 21% 32% 21% 

(-8% - -8%) (0% - 0%) (21% - 21%) (32% - 32%) (21% - 21%) 

-126% 0% 0% 13% 33% 

(-124% - -127%) (0% - 0%) (0% - 0%) (13% - 13%) (33% - 33%) 

-41% 0% 5% 22% 30% 

(-41% - -41%) (0% - 0%) (5% - 5%) (21% - 22%) (30% - 30%) 

-15% 0% 11% 24% 25% 

(-14% - -15%) (0% - 0%) (11% - 11%) (24% - 24%) (24% - 25%) 

0% 0% 0% 10% 12% 

(0% - 0%) (0% - 0%) (0% - 0%) (10% - 10%) (12% - 13%) 

-155% 0% 0% 0% 33% 

(-153% - -157%) (0% - 0%) (0% - 0%) (0% - 0%) (32% - 33%) 

-268% 0% 0% 0% 69% 

(-266% - -270%) (0% - 0%) (0% - 0%) (0% - 0%) (69% - 69%) 

-20% 0% 23% 35% 25% 

(-20% - -20%) (0% - 0%) (23% - 23%) (35% - 36%) (25% - 25%) 

-79% 0% 0% 0% 50% 

(-79% - -79%) (0% - 0%) (0% - 0%) (0% - 0%) (50% - 50%) 

Percent Reduction from the Current Standards: Annual Incidence of Cardiopulmonary Disease Mort

Long-Term Exposure to PM2.5 Concentrations in a Recent Year and PM2.5 Concentrations that Just M

Alternative Annual (n) and Daily (m) Standards (Standard Combination Denoted n/

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

E-70

September 2009 
Table E-54. Percent Reduction from the Current Standards: Estimated Annual Incidence of Cardiopulmonary Disease 

 Associated with Long-Term Exposure to Ambient PM2.5 Concentrations, Based on Adjusting 2007 PM2.5 Conc

 Estimates Based on Krewski et al. (2009), Using Ambient PM2.5 from 1999 - 20001 

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

-13% 0% 21% 32% 21% 

(-12% - -13%) (0% - 0%) (21% - 22%) (32% - 33%) (21% - 22%) 

-9% 0% 21% 32% 24% 

(-9% - -9%) (0% - 0%) (20% - 21%) (32% - 33%) (24% - 24%) 

-39% 0% 22% 33% 22% 

(-39% - -40%) (0% - 0%) (22% - 22%) (33% - 33%) (22% - 22%) 

0% 0% 0% 12% 0% 

(0% - 0%) (0% - 0%) (0% - 0%) (12% - 12%) (0% - 0%) 

-45% 0% 16% 31% 29% 

(-45% - -46%) (0% - 0%) (16% - 16%) (31% - 31%) (29% - 29%) 

-157% 0% 0% 0% 30% 

(-155% - -160%) (0% - 0%) (0% - 0%) (0% - 0%) (30% - 30%) 

-8% 0% 22% 33% 22% 

(-8% - -9%) (0% - 0%) (21% - 22%) (32% - 33%) (21% - 22%) 

-124% 0% 0% 12% 32% 

(-122% - -125%) (0% - 0%) (0% - 0%) (12% - 13%) (32% - 32%) 

-41% 0% 5% 21% 30% 

(-40% - -41%) (0% - 0%) (5% - 5%) (21% - 22%) (30% - 30%) 

-15% 0% 11% 24% 25% 

(-14% - -15%) (0% - 0%) (11% - 11%) (24% - 24%) (25% - 25%) 

0% 0% 0% 11% 14% 

(0% - 0%) (0% - 0%) (0% - 0%) (11% - 11%) (14% - 14%) 

-152% 0% 0% 0% 32% 

(-150% - -155%) (0% - 0%) (0% - 0%) (0% - 0%) (32% - 32%) 

-168% 0% 0% 0% 44% 

(-167% - -170%) (0% - 0%) (0% - 0%) (0% - 0%) (43% - 44%) 

-19% 0% 22% 34% 25% 

(-19% - -19%) (0% - 0%) (22% - 22%) (34% - 35%) (24% - 25%) 

-69% 0% 0% 0% 44% 

(-69% - -70%) (0% - 0%) (0% - 0%) (0% - 0%) (44% - 44%) 

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Percent Reduction from the Current Standards: Annual Incidence of Cardiopulmonary Disease Mort

Long-Term Exposure to PM2.5 Concentrations in a Recent Year and PM2.5 Concentrations that Just M

Alternative Annual (n) and Daily (m) Standards (Standard Combination Denoted n/

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

E-71

September 2009 
Figure E-16. Estimated Percent Reductions From the Current Standard to Alternative 

Standards in Cardiopulmonary Disease Mortality Associated with Long-Term Exposure to 

PM2.5 (Exposure Period: 1999 – 2000): Based on 2005 Air Quality Data*

-200%

-180%

-160%

-140%

-120%

-100%

-80%

-60%

-40%

-20%

0%

20%

40%

60%

80%

100%

2005 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Reduction from Current Standard

 Atlanta, GA 640 (503 - 774); 11% (8.6% - 13.2%)

 Baltimore, MD 654 (514 - 790); 11.1% (8.7% - 13.4%)

 Birmingham, AL 431 (339 - 522); 10.4% (8.2% - 12.6%)

 Dallas, TX 440 (345 - 534); 8.3% (6.5% - 10.1%)

 Detroit, MI 729 (571 - 883); 8.9% (7% - 10.8%)

 Fresno, CA 117 (92 - 143); 4.5% (3.5% - 5.5%)

 Houston, TX 768 (603 - 929); 10.3% (8.1% - 12.5%)

 Los Angeles, CA 1626 (1270 - 1977); 5.8% (4.5% - 7%)

 New York, NY 1972 (1542 - 2395); 6.9% (5.4% - 8.4%)

 Philadelphia, PA 512 (401 - 620); 8.5% (6.7% - 10.3%)

 Phoenix, AZ 571 (446 - 695); 6.1% (4.7% - 7.4%)

 Pittsburgh, PA 368 (287 - 447); 6% (4.7% - 7.3%)

 Salt Lake City, UT 45 (35 - 55); 2.6% (2% - 3.2%)

 St. Louis, MO 874 (686 - 1057); 10.3% (8.1% - 12.4%)

 Tacoma, WA 101 (79 - 123); 4.6% (3.6% - 5.6%)

*Based on Krewski et al. (2009), exposure period from 1979 – 1983. The legend contains, for each urban area, the 

incidence estimate (and 95% CI) and the estimate of percent of total incidence (and 95% CI) under the current 

standards. 

**The current standards consist of an annual standard of 15 μg/m3

 and a daily standard of 35 μg/m3. Combinations of 

an annual standard (n) and a daily standard (m) are denoted n/m in this figure. 

E-72

September 2009 Draft - Do Not Quote or Cite
Figure E-17. Estimated Percent Reductions From the Current Standard to Alternative 

Standards in Cardiopulmonary Disease Mortality Associated with Long-Term Exposure to 

PM2.5 (Exposure Period: 1999 – 2000): Based on 2006 Air Quality Data* 

-200%

-180%

-160%

-140%

-120%

-100%

-80%

-60%

-40%

-20%

0%

20%

40%

60%

80%

100%

2006 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Reduction from Current Standard

 Atlanta, GA 619 (486 - 748); 10.3% (8.1% - 12.4%)

 Baltimore, MD 569 (447 - 689); 9.7% (7.6% - 11.7%)

 Birmingham, AL 416 (326 - 503); 9.9% (7.8% - 12%)

 Dallas, TX 340 (266 - 413); 6.3% (4.9% - 7.6%)

 Detroit, MI 535 (418 - 650); 6.5% (5.1% - 7.9%)

 Fresno, CA 128 (100 - 156); 4.9% (3.8% - 6%)

 Houston, TX 812 (637 - 982); 10.5% (8.3% - 12.7%)

 Los Angeles, CA 1390 (1084 - 1692); 4.9% (3.8% - 6%)

 New York, NY 1663 (1299 - 2023); 5.8% (4.5% - 7%)

 Philadelphia, PA 501 (393 - 608); 8.4% (6.6% - 10.2%)

 Phoenix, AZ 624 (488 - 758); 6.4% (5% - 7.8%)

 Pittsburgh, PA 299 (233 - 364); 4.9% (3.8% - 6%)

 Salt Lake City, UT 29 (23 - 36); 1.7% (1.3% - 2%)

 St. Louis, MO 670 (524 - 813); 7.8% (6.1% - 9.5%)

 Tacoma, WA 56 (44 - 69); 2.5% (2% - 3.1%)

*Based on Krewski et al. (2009), exposure period from 1979 – 1983. The legend contains, for each urban area, the 

incidence estimate (and 95% CI) and the estimate of percent of total incidence (and 95% CI) under the current 

standards. 

**The current standards consist of an annual standard of 15 μg/m3

 and a daily standard of 35 μg/m3. Combinations of 

an annual standard (n) and a daily standard (m) are denoted n/m in this figure. 

***The percent reduction for 2006 air quality in Salt Lake City is -268%. 

E-73

September 2009 Draft - Do Not Quote or Cite
Figure E-18. Estimated Percent Reductions From the Current Standard to Alternative 

Standards in Cardiopulmonary Disease Mortality Associated with Long-Term Exposure to 

PM2.5 (Exposure Period: 1999 – 2000): Based on 2007 Air Quality Data* 

-200%

-180%

-160%

-140%

-120%

-100%

-80%

-60%

-40%

-20%

0%

20%

40%

60%

80%

100%

2007 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Reduction from Current Standard

 Atlanta, GA 640 (503 - 774); 10.4% (8.1% - 12.5%)

 Baltimore, MD 533 (418 - 645); 9.1% (7.1% - 11%)

 Birmingham, AL 411 (322 - 498); 9.7% (7.6% - 11.7%)

 Dallas, TX 376 (294 - 456); 6.8% (5.3% - 8.3%)

 Detroit, MI 495 (387 - 602); 6.1% (4.7% - 7.4%)

 Fresno, CA 154 (120 - 187); 5.8% (4.5% - 7%)

 Houston, TX 797 (625 - 964); 10.1% (8% - 12.3%)

 Los Angeles, CA 1431 (1116 - 1741); 5% (3.9% - 6.1%)

 New York, NY 1694 (1323 - 2060); 5.9% (4.6% - 7.1%)

 Philadelphia, PA 496 (388 - 601); 8.3% (6.5% - 10%)

 Phoenix, AZ 543 (424 - 661); 5.4% (4.2% - 6.6%)

 Pittsburgh, PA 305 (238 - 372); 5.1% (4% - 6.2%)

 Salt Lake City, UT 56 (44 - 68); 3.1% (2.4% - 3.7%)

 St. Louis, MO 717 (561 - 869); 8.4% (6.6% - 10.2%)

 Tacoma, WA 69 (53 - 84); 3% (2.3% - 3.7%)

*Based on Krewski et al. (2009), exposure period from 1979 – 1983. The legend contains, for each urban area, the 

incidence estimate (and 95% CI) and the estimate of percent of total incidence (and 95% CI) under the current 

standards. 

**The current standards consist of an annual standard of 15 μg/m3

 and a daily standard of 35 μg/m3. Combinations of 

an annual standard (n) and a daily standard (m) are denoted n/m in this figure. 

E-74

September 2009 Draft - Do Not Quote or Cite
Table E-55. Estimated Annual Incidence of Lung Cancer Mortality Associated with Long-Term Exposure to Ambient P

 Concentrations in a Recent Year (2005) and PM2.5 Concentrations that Just Meet the Current and Alternative 

 on Adjusting 2005 PM2.5 Concentrations: Estimates Based on Krewski et al. (2009), Using Ambient PM2.5 from 

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

76 68 53 46 53 

(29 - 121) (26 - 108) (20 - 85) (17 - 74) (20 - 85) 

80 74 60 52 58 

(31 - 127) (28 - 117) (23 - 95) (20 - 83) (22 - 92) 

64 46 36 31 36 

(24 - 101) (17 - 73) (14 - 58) (12 - 50) (14 - 58) 

48 48 48 43 48 

(18 - 77) (18 - 77) (18 - 77) (16 - 68) (18 - 77) 

106 77 67 57 59 

(40 - 168) (29 - 123) (25 - 107) (21 - 91) (22 - 94) 

269 9 9 6 

(10 - 41) (3 - 14) (3 - 14) (3 - 14) (2 - 10) 

90 83 65 56 65 

(34 - 144) (32 - 132) (25 - 104) (21 - 90) (25 - 104) 

259 120 120 106 84 

(99 - 411) (45 - 193) (45 - 193) (40 - 171) (31 - 136) 

180 131 124 105 95 

(68 - 287) (49 - 210) (47 - 200) (39 - 169) (36 - 153) 

66 57 51 44 43 

(25 - 105) (22 - 92) (19 - 82) (16 - 70) (16 - 69) 

58 58 58 52 50 

(22 - 93) (22 - 93) (22 - 93) (19 - 83) (19 - 81) 

94 39 39 39 28 

(36 - 148) (15 - 63) (15 - 63) (15 - 63) (10 - 45) 

93332

(4 - 15) (1 - 5) (1 - 5) (1 - 5) (1 - 3) 

111 94 75 64 73 

(42 - 176) (36 - 150) (28 - 120) (24 - 103) (28 - 117) 

18 12 12 12 8 

(7 - 29) (4 - 19) (4 - 19) (4 - 19) (3 - 13) 

 Incidence of Lung Cancer Mortality Associated with Long-Term Exposure to PM2.5 Concentration

and PM2.5 Concentrations that Just Meet the Current and Alternative Annual (n) and Daily (m) Sta

Combination Denoted n/m):

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL Baltimore, MD Detroit, MI Houston, TX New York, NY St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT

E-75

September 2009 
Table E-56. Estimated Annual Incidence of Lung Cancer Mortality Associated with Long-Term Exposure to Ambient P

 Concentrations in a Recent Year (2006) and PM2.5 Concentrations that Just Meet the Current and Alternative 

 on Adjusting 2006 PM2.5 Concentrations: Estimates Based on Krewski et al. (2009), Using Ambient PM2.5 from 

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

74 65 51 44 51 

(28 - 117) (25 - 104) (19 - 82) (17 - 71) (19 - 82) 

70 64 51 44 49 

(27 - 111) (24 - 102) (19 - 82) (16 - 70) (19 - 79) 

62 44 34 30 34 

(24 - 98) (17 - 71) (13 - 55) (11 - 47) (13 - 55) 

37 37 37 32 37 

(14 - 59) (14 - 59) (14 - 59) (12 - 52) (14 - 59) 

81 56 47 39 41 

(31 - 130) (21 - 90) (18 - 76) (15 - 63) (15 - 65) 

27 10 10 10 7 

(10 - 43) (4 - 16) (4 - 16) (4 - 16) (2 - 11) 

95 88 69 59 69 

(36 - 152) (33 - 140) (26 - 110) (22 - 95) (26 - 110) 

233 102 102 89 69 

(89 - 371) (38 - 165) (38 - 165) (33 - 144) (26 - 111) 

156 110 104 86 77 

(59 - 249) (41 - 177) (39 - 168) (32 - 139) (29 - 124) 

64 56 50 43 42 

(24 - 103) (21 - 90) (19 - 80) (16 - 68) (16 - 68) 

63 63 63 57 55 

(24 - 101) (24 - 101) (24 - 101) (21 - 91) (21 - 89) 

82 32 32 32 21 

(31 - 130) (12 - 51) (12 - 51) (12 - 51) (8 - 34) 

82221

(3 - 13) (1 - 3) (1 - 3) (1 - 3) (0 - 1) 

87 72 55 46 54 

(33 - 138) (27 - 115) (21 - 89) (17 - 75) (20 - 86) 

127 7 7 3 

(4 - 19) (2 - 11) (2 - 11) (2 - 11) (1 - 5) 

 Incidence of Lung Cancer Mortality Associated with Long-Term Exposure to PM2.5 Concentratio

and PM2.5 Concentrations that Just Meet the Current and Alternative Annual (n) and Daily (m) St

Combination Denoted n/m):

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL Baltimore, MD Detroit, MI Houston, TX New York, NY St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT

E-76

September 2009 
Table E-57. Estimated Annual Incidence of Lung Cancer Mortality Associated with Long-Term Exposure to Ambient P

 Concentrations in a Recent Year (2007) and PM2.5 Concentrations that Just Meet the Current and Alternative 

 on Adjusting 2007 PM2.5 Concentrations: Estimates Based on Krewski et al. (2009), Using Ambient PM2.5 from 

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

76 68 53 46 53 

(29 - 121) (26 - 108) (20 - 85) (17 - 73) (20 - 85) 

66 60 47 40 46 

(25 - 105) (23 - 96) (18 - 76) (15 - 65) (17 - 73) 

61 44 34 29 34 

(23 - 97) (17 - 70) (13 - 54) (11 - 47) (13 - 54) 

41 41 41 36 41 

(15 - 66) (15 - 66) (15 - 66) (13 - 58) (15 - 66) 

76 52 44 36 37 

(29 - 121) (20 - 84) (16 - 70) (13 - 58) (14 - 60) 

31 12 12 12 8 

(12 - 48) (4 - 19) (4 - 19) (4 - 19) (3 - 13) 

94 86 67 58 67 

(36 - 149) (33 - 137) (25 - 108) (22 - 93) (25 - 108) 

238 105 105 92 71 

(91 - 379) (39 - 170) (39 - 170) (34 - 149) (27 - 115) 

158 112 106 88 79 

(60 - 254) (42 - 180) (40 - 171) (33 - 142) (29 - 127) 

64 56 49 42 42 

(24 - 102) (21 - 89) (19 - 79) (16 - 68) (16 - 67) 

55 55 55 49 47 

(21 - 88) (21 - 88) (21 - 88) (18 - 79) (18 - 76) 

83 32 32 32 22 

(32 - 131) (12 - 52) (12 - 52) (12 - 52) (8 - 35) 

114 4 4 2 

(4 - 17) (2 - 7) (2 - 7) (2 - 7) (1 - 4) 

92 77 60 50 58 

(35 - 147) (29 - 123) (22 - 96) (19 - 81) (22 - 93) 

148 8 8 5 

(5 - 22) (3 - 13) (3 - 13) (3 - 13) (2 - 7) 

 Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Detroit, MI Houston, TX New York, NY St. Louis, MO

 Incidence of Lung Cancer Mortality Associated with Long-Term Exposure to PM2.5 Concentration

and PM2.5 Concentrations that Just Meet the Current and Alternative Annual (n) and Daily (m) Sta

Combination Denoted n/m):

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL Baltimore, MD

E-77

September 2009 
Table E-58. Estimated Percent of Total Annual Incidence of Lung Cancer Mortality Associated with Long-Term Exposure 

 PM2.5 Concentrations in a Recent Year (2005) and PM2.5 Concentrations that Just Meet the Current and Alternat Based on Adjusting 2005 PM2.5 Concentrations: Estimates Based on Krewski et al. (2009), Using Ambient PM2.5 fr

 1979 - 19831

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

8.6% 7.6% 6% 5.2% 6% 

(3.3% - 13.6%) (2.9% - 12.1%) (2.3% - 9.6%) (1.9% - 8.3%) (2.3% - 9.6%) (1

8.4% 7.7% 6.2% 5.4% 6% 

(3.2% - 13.3%) (2.9% - 12.2%) (2.4% - 10%) (2% - 8.6%) (2.3% - 9.6%) (1

10% 7.2% 5.6% 4.8% 5.6% 

(3.8% - 15.8%) (2.7% - 11.4%) (2.1% - 9%) (1.8% - 7.8%) (2.1% - 9%) (1

5.7% 5.7% 5.7% 5.1% 5.7% 

(2.2% - 9.2%) (2.2% - 9.2%) (2.2% - 9.2%) (1.9% - 8.2%) (2.2% - 9.2%) (1

8.5% 6.1% 5.3% 4.5% 4.7% 

(3.2% - 13.4%) (2.3% - 9.8%) (2% - 8.5%) (1.7% - 7.3%) (1.8% - 7.5%) (1

8.9% 3.1% 3.1% 3.1% 2% 

(3.4% - 14.1%) (1.2% - 5%) (1.2% - 5%) (1.2% - 5%) (0.8% - 3.3%) (0

7.8% 7.1% 5.6% 4.8% 5.6% 

(2.9% - 12.3%) (2.7% - 11.4%) (2.1% - 8.9%) (1.8% - 7.7%) (2.1% - 8.9%) (1

8.6% 4% 4% 3.5% 2.8% 

(3.3% - 13.6%) (1.5% - 6.4%) (1.5% - 6.4%) (1.3% - 5.7%) (1% - 4.5%) (0

6.6% 4.8% 4.5% 3.8% 3.5% 

(2.5% - 10.5%) (1.8% - 7.7%) (1.7% - 7.3%) (1.4% - 6.2%) (1.3% - 5.6%) (0

6.8% 5.9% 5.2% 4.5% 4.4% 

(2.6% - 10.8%) (2.2% - 9.4%) (2% - 8.4%) (1.7% - 7.2%) (1.7% - 7.1%) (1

4.2% 4.2% 4.2% 3.7% 3.6% 

(1.6% - 6.7%) (1.6% - 6.7%) (1.6% - 6.7%) (1.4% - 6%) (1.4% - 5.9%) (0

10% 4.1% 4.1% 4.1% 2.9% 

(3.8% - 15.7%) (1.6% - 6.7%) (1.6% - 6.7%) (1.6% - 6.7%) (1.1% - 4.7%) (0

5.2% 1.8% 1.8% 1.8% 0.9% 

(2% - 8.4%) (0.7% - 2.9%) (0.7% - 2.9%) (0.7% - 2.9%) (0.3% - 1.5%) (

8.4% 7.1% 5.7% 4.9% 5.5% 

(3.2% - 13.3%) (2.7% - 11.3%) (2.1% - 9.1%) (1.8% - 7.8%) (2.1% - 8.8%) (1

4.8% 3.1% 3.1% 3.1% 2.1% 

(1.8% - 7.7%) (1.2% - 5.1%) (1.2% - 5.1%) (1.2% - 5.1%) (0.8% - 3.4%) (0

Percent of Total Incidence of Lung Cancer Mortality Associated with Long-Term Exposure to PM2.5 Co

in a Recent Year and PM2.5 Concentrations that Just Meet the Current and Alternative Annual (n) an

Standards (Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

E-78

September 2009 
Table E-59. Estimated Percent of Total Annual Incidence of Lung Cancer Mortality Associated with Long-Term Exposure 

 to Ambient PM2.5 Concentrations in a Recent Year (2006) and PM2.5 Concentrations that Just Meet the Current 

 and Alternative Standards, Based on Adjusting 2006 PM2.5 Concentrations: Estimates Based on Krewski et al. (20

 Using Ambient PM2.5 from 1979 - 19831

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

8% 7.1% 5.6% 4.8% 5.6% 

(3.1% - 12.7%) (2.7% - 11.3%) (2.1% - 8.9%) (1.8% - 7.7%) (2.1% - 8.9%) (1

7.3% 6.7% 5.3% 4.6% 5.1% 

(2.8% - 11.6%) (2.5% - 10.6%) (2% - 8.5%) (1.7% - 7.3%) (1.9% - 8.2%) (1

9.6% 6.8% 5.3% 4.6% 5.3% 

(3.7% - 15.1%) (2.6% - 10.9%) (2% - 8.5%) (1.7% - 7.3%) (2% - 8.5%) (1

4.3% 4.3% 4.3% 3.8% 4.3% 

(1.6% - 6.9%) (1.6% - 6.9%) (1.6% - 6.9%) (1.4% - 6.1%) (1.6% - 6.9%) (1

6.5% 4.5% 3.8% 3.1% 3.2% 

(2.4% - 10.3%) (1.7% - 7.2%) (1.4% - 6.1%) (1.2% - 5%) (1.2% - 5.2%) (0

9.3% 3.4% 3.4% 3.4% 2.3% 

(3.6% - 14.8%) (1.3% - 5.4%) (1.3% - 5.4%) (1.3% - 5.4%) (0.8% - 3.6%) (0

7.9% 7.3% 5.7% 4.9% 5.7% 

(3% - 12.6%) (2.8% - 11.6%) (2.2% - 9.2%) (1.9% - 7.9%) (2.2% - 9.2%) (1

7.7% 3.4% 3.4% 2.9% 2.3% 

(2.9% - 12.2%) (1.3% - 5.4%) (1.3% - 5.4%) (1.1% - 4.8%) (0.8% - 3.7%) (0

5.6% 4% 3.8% 3.1% 2.8% 

(2.1% - 9%) (1.5% - 6.4%) (1.4% - 6.1%) (1.2% - 5%) (1% - 4.5%) (0

6.6% 5.8% 5.1% 4.4% 4.3% 

(2.5% - 10.6%) (2.2% - 9.3%) (1.9% - 8.2%) (1.6% - 7.1%) (1.6% - 7%) (1

4.4% 4.4% 4.4% 4% 3.8% 

(1.7% - 7.1%) (1.7% - 7.1%) (1.7% - 7.1%) (1.5% - 6.4%) (1.4% - 6.2%) (0

8.7% 3.4% 3.4% 3.4% 2.3% 

(3.3% - 13.8%) (1.3% - 5.5%) (1.3% - 5.5%) (1.3% - 5.5%) (0.9% - 3.7%) (0

4.2% 1.1% 1.1% 1.1% 0.4% 

(1.6% - 6.7%) (0.4% - 1.8%) (0.4% - 1.8%) (0.4% - 1.8%) (0.1% - 0.6%) 

6.5% 5.4% 4.2% 3.5% 4% 

(2.5% - 10.4%) (2% - 8.7%) (1.6% - 6.7%) (1.3% - 5.6%) (1.5% - 6.5%) (

3.1% 1.7% 1.7% 1.7% 0.9% 

(1.2% - 5%) (0.6% - 2.8%) (0.6% - 2.8%) (0.6% - 2.8%) (0.3% - 1.4%) 

Percent of Total Incidence of Lung Cancer Mortality Associated with Long-Term Exposure to PM2.5 Co

in a Recent Year and PM2.5 Concentrations that Just Meet the Current and Alternative Annual (n) an

Standards (Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

E-79

September 2009 
Table E-60. Estimated Percent of Total Annual Incidence of Lung Cancer Mortality Associated with Long-Term Exposure 

 PM2.5 Concentrations in a Recent Year (2007) and PM2.5 Concentrations that Just Meet the Current and Alternat

 Based on Adjusting 2007 PM2.5 Concentrations: Estimates Based on Krewski et al. (2009), Using Ambient PM2.5 fr

 1979 - 19831

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

8.1% 7.2% 5.6% 4.8% 5.6% 

(3.1% - 12.9%) (2.7% - 11.4%) (2.1% - 9%) (1.8% - 7.8%) (2.1% - 9%) (1

6.9% 6.3% 4.9% 4.2% 4.8% 

(2.6% - 10.9%) (2.4% - 10%) (1.9% - 7.9%) (1.6% - 6.8%) (1.8% - 7.6%) (1

9.4% 6.7% 5.2% 4.5% 5.2% 

(3.6% - 14.9%) (2.5% - 10.7%) (2% - 8.4%) (1.7% - 7.2%) (2% - 8.4%) (

4.7% 4.7% 4.7% 4.1% 4.7% 

(1.8% - 7.5%) (1.8% - 7.5%) (1.8% - 7.5%) (1.5% - 6.6%) (1.8% - 7.5%) (1

6.1% 4.2% 3.5% 2.9% 3% 

(2.3% - 9.7%) (1.6% - 6.7%) (1.3% - 5.6%) (1.1% - 4.6%) (1.1% - 4.8%) (0

10.4% 4% 4% 4% 2.8% 

(4% - 16.3%) (1.5% - 6.4%) (1.5% - 6.4%) (1.5% - 6.4%) (1% - 4.5%) (0

7.6% 7% 5.5% 4.7% 5.5% 

(2.9% - 12.1%) (2.7% - 11.2%) (2.1% - 8.8%) (1.8% - 7.5%) (2.1% - 8.8%) (1

7.8% 3.5% 3.5% 3% 2.3% 

(3% - 12.4%) (1.3% - 5.6%) (1.3% - 5.6%) (1.1% - 4.9%) (0.9% - 3.8%) (0

5.7% 4% 3.8% 3.2% 2.8% 

(2.1% - 9.1%) (1.5% - 6.5%) (1.4% - 6.1%) (1.2% - 5.1%) (1.1% - 4.6%) (0

6.6% 5.7% 5.1% 4.3% 4.3% 

(2.5% - 10.5%) (2.2% - 9.1%) (1.9% - 8.1%) (1.6% - 7%) (1.6% - 6.9%) (1

3.7% 3.7% 3.7% 3.3% 3.2% 

(1.4% - 6%) (1.4% - 6%) (1.4% - 6%) (1.2% - 5.3%) (1.2% - 5.1%) (0

8.9% 3.5% 3.5% 3.5% 2.4% 

(3.4% - 14.1%) (1.3% - 5.6%) (1.3% - 5.6%) (1.3% - 5.6%) (0.9% - 3.8%) (

5.7% 2.1% 2.1% 2.1% 1.2% 

(2.1% - 9.1%) (0.8% - 3.4%) (0.8% - 3.4%) (0.8% - 3.4%) (0.4% - 1.9%) (0

6.9% 5.8% 4.5% 3.8% 4.4% 

(2.6% - 11%) (2.2% - 9.3%) (1.7% - 7.2%) (1.4% - 6.1%) (1.6% - 7%) (1

3.5% 2.1% 2.1% 2.1% 1.1% 

(1.3% - 5.6%) (0.8% - 3.3%) (0.8% - 3.3%) (0.8% - 3.3%) (0.4% - 1.9%) (0

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Percent of Total Incidence of Lung Cancer Mortality Associated with Long-Term Exposure to PM2.5 Co

in a Recent Year and PM2.5 Concentrations that Just Meet the Current and Alternative Annual (n) an

Standards (Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

E-80

September 2009 
Table E-61. Percent Reduction from the Current Standards: Estimated Annual Incidence of Lung Cancer Mortality A

 Long-Term Exposure to Ambient PM2.5 Concentrations, Based on Adjusting 2005 PM2.5 Concentrations: Estim

 Krewski et al. (2009), Using Ambient PM2.5 from 1979 - 19831

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

-13% 0% 21% 32% 21% 

(-12% - -13%) (0% - 0%) (21% - 22%) (31% - 33%) (21% - 22%) 

-9% 0% 19% 30% 22% 

(-8% - -9%) (0% - 0%) (19% - 19%) (29% - 30%) (22% - 22%) 

-39% 0% 22% 33% 22% 

(-38% - -40%) (0% - 0%) (21% - 22%) (32% - 33%) (21% - 22%) 

0% 0% 0% 11% 0% 

(0% - 0%) (0% - 0%) (0% - 0%) (11% - 11%) (0% - 0%) 

-38% 0% 14% 26% 24% 

(-37% - -39%) (0% - 0%) (13% - 14%) (26% - 27%) (24% - 24%) 

-186% 0% 0% 0% 34% 

(-181% - -192%) (0% - 0%) (0% - 0%) (0% - 0%) (34% - 35%) 

-9% 0% 22% 33% 22% 

(-8% - -9%) (0% - 0%) (21% - 22%) (32% - 33%) (21% - 22%) 

-116% 0% 0% 12% 30% 

(-113% - -120%) (0% - 0%) (0% - 0%) (11% - 12%) (30% - 30%) 

-38% 0% 5% 20% 27% 

(-37% - -39%) (0% - 0%) (5% - 5%) (20% - 20%) (27% - 28%) 

-15% 0% 11% 24% 25% 

(-14% - -15%) (0% - 0%) (11% - 11%) (24% - 24%) (24% - 25%) 

0% 0% 0% 10% 13% 

(0% - 0%) (0% - 0%) (0% - 0%) (10% - 10%) (13% - 13%) 

-141% 0% 0% 0% 29% 

(-136% - -146%) (0% - 0%) (0% - 0%) (0% - 0%) (29% - 30%) 

-190% 0% 0% 0% 49% 

(-187% - -193%) (0% - 0%) (0% - 0%) (0% - 0%) (48% - 49%) 

-18% 0% 20% 32% 23% 

(-17% - -18%) (0% - 0%) (20% - 21%) (31% - 32%) (22% - 23%) 

-53% 0% 0% 0% 34% 

(-52% - -54%) (0% - 0%) (0% - 0%) (0% - 0%) (34% - 34%) 

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Percent Reduction from the Current Standards: Annual Incidence of Lung Cancer Mortality Associated 

Exposure to PM2.5 Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the Curren

Annual (n) and Daily (m) Standards (Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

E-81

September 2009 
Table E-62. Percent Reduction from the Current Standards: Estimated Annual Incidence of Lung Cancer Mortality A

 Long-Term Exposure to Ambient PM2.5 Concentrations, Based on Adjusting 2006 PM2.5 Concentrations: Estim

 Krewski et al. (2009), Using Ambient PM2.5 from 1979 - 19831

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

-13% 0% 22% 33% 22% 

(-13% - -13%) (0% - 0%) (21% - 22%) (32% - 33%) (21% - 22%) 

-9% 0% 20% 32% 23% 

(-9% - -9%) (0% - 0%) (20% - 21%) (31% - 32%) (23% - 24%) 

-40% 0% 22% 33% 22% 

(-39% - -41%) (0% - 0%) (22% - 22%) (33% - 34%) (22% - 22%) 

0% 0% 0% 13% 0% 

(0% - 0%) (0% - 0%) (0% - 0%) (13% - 13%) (0% - 0%) 

-44% 0% 16% 30% 28% 

(-43% - -45%) (0% - 0%) (16% - 16%) (30% - 31%) (28% - 28%) 

-178% 0% 0% 0% 33% 

(-172% - -183%) (0% - 0%) (0% - 0%) (0% - 0%) (33% - 33%) 

-9% 0% 22% 32% 22% 

(-8% - -9%) (0% - 0%) (21% - 22%) (32% - 33%) (21% - 22%) 

-128% 0% 0% 13% 33% 

(-125% - -131%) (0% - 0%) (0% - 0%) (13% - 13%) (33% - 33%) 

-42% 0% 5% 22% 30% 

(-41% - -42%) (0% - 0%) (5% - 5%) (22% - 22%) (30% - 30%) 

-15% 0% 11% 24% 25% 

(-14% - -15%) (0% - 0%) (11% - 11%) (24% - 24%) (25% - 25%) 

0% 0% 0% 10% 13% 

(0% - 0%) (0% - 0%) (0% - 0%) (10% - 10%) (12% - 13%) 

-158% 0% 0% 0% 33% 

(-154% - -163%) (0% - 0%) (0% - 0%) (0% - 0%) (33% - 33%) 

-271% 0% 0% 0% 69% 

(-267% - -274%) (0% - 0%) (0% - 0%) (0% - 0%) (69% - 69%) 

-20% 0% 23% 36% 26% 

(-20% - -21%) (0% - 0%) (23% - 23%) (35% - 36%) (25% - 26%) 

-80% 0% 0% 0% 50% 

(-79% - -80%) (0% - 0%) (0% - 0%) (0% - 0%) (50% - 50%) 

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Percent Reduction from the Current Standards: Annual Incidence of Lung Cancer Mortality Associated 

Exposure to PM2.5 Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the Curren

Annual (n) and Daily (m) Standards (Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

E-82

September 2009 
Table E-63. Percent Reduction from the Current Standards: Estimated Annual Incidence of Lung Cancer Mortality A

 Long-Term Exposure to Ambient PM2.5 Concentrations, Based on Adjusting 2007 PM2.5 Concentrations: Estim

 Krewski et al. (2009), Using Ambient PM2.5 from 1979 - 19831

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

-13% 0% 22% 33% 22% 

(-12% - -13%) (0% - 0%) (21% - 22%) (32% - 33%) (21% - 22%) 

-10% 0% 21% 33% 24% 

(-9% - -10%) (0% - 0%) (21% - 21%) (32% - 33%) (24% - 24%) 

-40% 0% 22% 34% 22% 

(-39% - -42%) (0% - 0%) (22% - 23%) (33% - 34%) (22% - 23%) 

0% 0% 0% 12% 0% 

(0% - 0%) (0% - 0%) (0% - 0%) (12% - 13%) (0% - 0%) 

-46% 0% 16% 32% 29% 

(-45% - -47%) (0% - 0%) (16% - 17%) (31% - 32%) (29% - 29%) 

-162% 0% 0% 0% 30% 

(-156% - -167%) (0% - 0%) (0% - 0%) (0% - 0%) (30% - 30%) 

-9% 0% 22% 33% 22% 

(-8% - -9%) (0% - 0%) (21% - 22%) (32% - 33%) (21% - 22%) 

-126% 0% 0% 13% 32% 

(-123% - -129%) (0% - 0%) (0% - 0%) (12% - 13%) (32% - 33%) 

-41% 0% 5% 22% 30% 

(-41% - -42%) (0% - 0%) (5% - 5%) (21% - 22%) (30% - 30%) 

-15% 0% 11% 24% 25% 

(-15% - -15%) (0% - 0%) (11% - 11%) (24% - 25%) (25% - 25%) 

0% 0% 0% 11% 14% 

(0% - 0%) (0% - 0%) (0% - 0%) (11% - 11%) (14% - 14%) 

-156% 0% 0% 0% 32% 

(-151% - -160%) (0% - 0%) (0% - 0%) (0% - 0%) (32% - 32%) 

-170% 0% 0% 0% 44% 

(-167% - -174%) (0% - 0%) (0% - 0%) (0% - 0%) (43% - 44%) 

-20% 0% 22% 35% 25% 

(-19% - -20%) (0% - 0%) (22% - 23%) (34% - 35%) (24% - 25%) 

-70% 0% 0% 0% 44% 

(-69% - -71%) (0% - 0%) (0% - 0%) (0% - 0%) (44% - 44%) 

Percent Reduction from the Current Standards: Annual Incidence of Lung Cancer Mortality Associated 

Exposure to PM2.5 Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the Curren

Annual (n) and Daily (m) Standards (Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

E-83

September 2009 
Figure E-19. Estimated Percent Reductions From the Current Standard to Alternative 

Standards in Lung Cancer Mortality Associated with Long-Term Exposure to PM2.5

(Exposure Period: 1979 – 1983): Based on 2005 Air Quality Data*

-200%

-180%

-160%

-140%

-120%

-100%

-80%

-60%

-40%

-20%

0%

20%

40%

60%

80%

100%

2005 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Reduction from Current Standard

 Atlanta, GA 68 (26 - 108); 7.6% (2.9% - 12.1%)

 Baltimore, MD 74 (28 - 117); 7.7% (2.9% - 12.2%)

 Birmingham, AL 46 (17 - 73); 7.2% (2.7% - 11.4%)

 Dallas, TX 48 (18 - 77); 5.7% (2.2% - 9.2%)

 Detroit, MI 77 (29 - 123); 6.1% (2.3% - 9.8%)

 Fresno, CA 9 (3 - 14); 3.1% (1.2% - 5%)

 Houston, TX 83 (32 - 132); 7.1% (2.7% - 11.4%)

 Los Angeles, CA 120 (45 - 193); 4% (1.5% - 6.4%)

 New York, NY 131 (49 - 210); 4.8% (1.8% - 7.7%)

 Philadelphia, PA 57 (22 - 92); 5.9% (2.2% - 9.4%)

 Phoenix, AZ 58 (22 - 93); 4.2% (1.6% - 6.7%)

 Pittsburgh, PA 39 (15 - 63); 4.1% (1.6% - 6.7%)

 Salt Lake City, UT 3 (1 - 5); 1.8% (0.7% - 2.9%)

 St. Louis, MO 94 (36 - 150); 7.1% (2.7% - 11.3%)

 Tacoma, WA 12 (4 - 19); 3.1% (1.2% - 5.1%)

*Based on Krewski et al. (2009), exposure period from 1999 – 2000. The legend contains, for each urban area, the 

incidence estimate (and 95% CI) and the estimate of percent of total incidence (and 95% CI) under the current 

standards. 

**The current standards consist of an annual standard of 15 μg/m3

 and a daily standard of 35 μg/m3. Combinations of 

an annual standard (n) and a daily standard (m) are denoted n/m in this figure. 

E-84

September 2009 Draft - Do Not Quote or Cite
Figure E-20. Estimated Percent Reductions From the Current Standard to Alternative 

Standards in Lung Cancer Mortality Associated with Long-Term Exposure to PM2.5

(Exposure Period: 1979 – 1983): Based on 2006 Air Quality Data* 

-200%

-180%

-160%

-140%

-120%

-100%

-80%

-60%

-40%

-20%

0%

20%

40%

60%

80%

100%

2006 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Reduction from Current Standard

 Atlanta, GA 65 (25 - 104); 7.1% (2.7% - 11.3%)

 Baltimore, MD 64 (24 - 102); 6.7% (2.5% - 10.6%)

 Birmingham, AL 44 (17 - 71); 6.8% (2.6% - 10.9%)

 Dallas, TX 37 (14 - 59); 4.3% (1.6% - 6.9%)

 Detroit, MI 56 (21 - 90); 4.5% (1.7% - 7.2%)

 Fresno, CA 10 (4 - 16); 3.4% (1.3% - 5.4%)

 Houston, TX 88 (33 - 140); 7.3% (2.8% - 11.6%)

 Los Angeles, CA 102 (38 - 165); 3.4% (1.3% - 5.4%)

 New York, NY 110 (41 - 177); 4% (1.5% - 6.4%)

 Philadelphia, PA 56 (21 - 90); 5.8% (2.2% - 9.3%)

 Phoenix, AZ 63 (24 - 101); 4.4% (1.7% - 7.1%)

 Pittsburgh, PA 32 (12 - 51); 3.4% (1.3% - 5.5%)

 Salt Lake City, UT 2 (1 - 3); 1.1% (0.4% - 1.8%)

 St. Louis, MO 72 (27 - 115); 5.4% (2% - 8.7%)

 Tacoma, WA 7 (2 - 11); 1.7% (0.6% - 2.8%)

*Based on Krewski et al. (2009), exposure period from 1999 – 2000. The legend contains, for each urban area, the 

incidence estimate (and 95% CI) and the estimate of percent of total incidence (and 95% CI) under the current 

standards. 

**The current standards consist of an annual standard of 15 μg/m3

 and a daily standard of 35 μg/m3. Combinations of 

an annual standard (n) and a daily standard (m) are denoted n/m in this figure. 

***The percent reduction for 2006 air quality in Salt Lake City is -271%. 

E-85

September 2009 Draft - Do Not Quote or Cite
Figure E-21. Estimated Percent Reductions From the Current Standard to Alternative 

Standards in Lung Cancer Mortality Associated with Long-Term Exposure to PM2.5

(Exposure Period: 1979 – 1983): Based on 2007 Air Quality Data* 

-200%

-180%

-160%

-140%

-120%

-100%

-80%

-60%

-40%

-20%

0%

20%

40%

60%

80%

100%

2007 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Reduction from Current Standard

 Atlanta, GA 68 (26 - 108); 7.2% (2.7% - 11.4%)

 Baltimore, MD 60 (23 - 96); 6.3% (2.4% - 10%)

 Birmingham, AL 44 (17 - 70); 6.7% (2.5% - 10.7%)

 Dallas, TX 41 (15 - 66); 4.7% (1.8% - 7.5%)

 Detroit, MI 52 (20 - 84); 4.2% (1.6% - 6.7%)

 Fresno, CA 12 (4 - 19); 4% (1.5% - 6.4%)

 Houston, TX 86 (33 - 137); 7% (2.7% - 11.2%)

 Los Angeles, CA 105 (39 - 170); 3.5% (1.3% - 5.6%)

 New York, NY 112 (42 - 180); 4% (1.5% - 6.5%)

 Philadelphia, PA 56 (21 - 89); 5.7% (2.2% - 9.1%)

 Phoenix, AZ 55 (21 - 88); 3.7% (1.4% - 6%)

 Pittsburgh, PA 32 (12 - 52); 3.5% (1.3% - 5.6%)

 Salt Lake City, UT 4 (2 - 7); 2.1% (0.8% - 3.4%)

 St. Louis, MO 77 (29 - 123); 5.8% (2.2% - 9.3%)

 Tacoma, WA 8 (3 - 13); 2.1% (0.8% - 3.3%)

*Based on Krewski et al. (2009), exposure period from 1999 – 2000. The legend contains, for each urban area, the 

incidence estimate (and 95% CI) and the estimate of percent of total incidence (and 95% CI) under the current 

standards. 

**The current standards consist of an annual standard of 15 μg/m3

 and a daily standard of 35 μg/m3. Combinations of 

an annual standard (n) and a daily standard (m) are denoted n/m in this figure. 

E-86

September 2009 Draft - Do Not Quote or Cite
Table E-64. Estimated Annual Incidence of Lung Cancer Mortality Associated with Long-Term Exposure to Ambient P

 Concentrations in a Recent Year (2005) and PM2.5 Concentrations that Just Meet the Current and Alternative 

 on Adjusting 2005 PM2.5 Concentrations: Estimates Based on Krewski et al. (2009), Using Ambient PM2.5 from 

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

110 98 77 67 77 

(49 - 166) (43 - 149) (34 - 118) (29 - 103) (34 - 118) 

116 106 86 75 83 

(51 - 175) (47 - 162) (38 - 132) (33 - 115) (37 - 128) 

92 66 52 45 52 

(41 - 138) (29 - 101) (23 - 80) (20 - 69) (23 - 80) 

69 69 69 62 69 

(31 - 107) (31 - 107) (31 - 107) (27 - 95) (31 - 107) 

153 112 97 83 85 

(68 - 232) (49 - 171) (42 - 148) (36 - 128) (37 - 131) 

37 13 13 13 9 

(16 - 56) (6 - 20) (6 - 20) (6 - 20) (4 - 13) 

130 120 94 81 94 

(58 - 198) (53 - 183) (42 - 145) (36 - 125) (42 - 145) 

373 174 174 154 123 

(166 - 565) (76 - 269) (76 - 269) (67 - 239) (53 - 190) 

260 190 181 153 138 

(115 - 398) (83 - 292) (79 - 279) (67 - 236) (60 - 214) 

95 83 74 63 63 

(42 - 145) (37 - 127) (33 - 114) (28 - 98) (27 - 97) 

84 84 84 75 73 

(37 - 129) (37 - 129) (37 - 129) (33 - 117) (32 - 113) 

135 57 57 57 40 

(60 - 203) (25 - 88) (25 - 88) (25 - 88) (18 - 63) 

14 5 5 5 2 

(6 - 21) (2 - 7) (2 - 7) (2 - 7) (1 - 4) 

160 136 109 94 106 

(71 - 242) (60 - 207) (48 - 167) (41 - 144) (47 - 162) 

27 17 17 17 12 

(12 - 41) (8 - 27) (8 - 27) (8 - 27) (5 - 18) 

 Incidence of Lung Cancer Mortality Associated with Long-Term Exposure to PM2.5 Concentratio

and PM2.5 Concentrations that Just Meet the Current and Alternative Annual (n) and Daily (m) St

Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

E-87

September 2009 
Table E-65. Estimated Annual Incidence of Lung Cancer Mortality Associated with Long-Term Exposure to Ambient P

 Concentrations in a Recent Year (2006) and PM2.5 Concentrations that Just Meet the Current and Alternative 

 on Adjusting 2006 PM2.5 Concentrations: Estimates Based on Krewski et al. (2009), Using Ambient PM2.5 from 

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

106 95 74 64 74 

(47 - 162) (42 - 144) (33 - 114) (28 - 98) (33 - 114) 

101 93 74 64 71 

(45 - 154) (41 - 141) (33 - 114) (28 - 98) (31 - 110) 

89 64 50 43 50 

(40 - 134) (28 - 98) (22 - 77) (19 - 66) (22 - 77) 

54 54 54 47 54 

(23 - 83) (23 - 83) (23 - 83) (20 - 72) (23 - 83) 

117 82 69 57 59 

(52 - 179) (36 - 126) (30 - 107) (25 - 89) (26 - 92) 

39 14 14 14 10 

(18 - 59) (6 - 22) (6 - 22) (6 - 22) (4 - 15) 

138 127 100 86 100 

(61 - 209) (56 - 193) (44 - 153) (38 - 133) (44 - 153) 

336 149 149 130 100 

(149 - 511) (65 - 231) (65 - 231) (57 - 202) (43 - 156) 

226 160 152 126 112 

(99 - 346) (70 - 247) (66 - 234) (55 - 195) (49 - 174) 

93 81 72 62 61 

(41 - 142) (36 - 125) (32 - 111) (27 - 95) (27 - 94) 

92 92 92 83 80 

(40 - 141) (40 - 141) (40 - 141) (36 - 128) (35 - 124) 

118 46 46 46 31 

(52 - 178) (20 - 71) (20 - 71) (20 - 71) (13 - 48) 

11 3 3 3 1 

(5 - 18) (1 - 5) (1 - 5) (1 - 5) (0 - 2) 

125 104 80 67 78 

(55 - 191) (46 - 160) (35 - 124) (29 - 104) (34 - 120) 

17 10 10 10 5 

(8 - 27) (4 - 15) (4 - 15) (4 - 15) (2 - 8) 

 Incidence of Lung Cancer Mortality Associated with Long-Term Exposure to PM2.5 Concentratio

and PM2.5 Concentrations that Just Meet the Current and Alternative Annual (n) and Daily (m) St

Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

E-88

September 2009 
Table E-66. Estimated Annual Incidence of Lung Cancer Mortality Associated with Long-Term Exposure to Ambient P

 Concentrations in a Recent Year (2007) and PM2.5 Concentrations that Just Meet the Current and Alternative 

 on Adjusting 2007 PM2.5 Concentrations: Estimates Based on Krewski et al. (2009), Using Ambient PM2.5 fro

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

110 98 77 66 77 

(49 - 167) (43 - 149) (34 - 118) (29 - 102) (34 - 118) 

95 87 69 59 66 

(42 - 145) (38 - 133) (30 - 106) (26 - 90) (29 - 102) 

88 63 49 42 49 

(39 - 133) (28 - 96) (22 - 76) (18 - 65) (22 - 76) 

59 59 59 52 59 

(26 - 91) (26 - 91) (26 - 91) (23 - 80) (26 - 91) 

110 76 63 52 54 

(48 - 168) (33 - 117) (28 - 98) (23 - 81) (23 - 84) 

44 17 17 17 12 

(20 - 66) (7 - 26) (7 - 26) (7 - 26) (5 - 19) 

135 125 98 84 98 

(60 - 205) (55 - 190) (43 - 150) (37 - 129) (43 - 150) 

343 153 153 134 104 

(153 - 522) (67 - 238) (67 - 238) (58 - 208) (45 - 162) 

230 163 155 128 115 

(101 - 352) (71 - 252) (67 - 239) (56 - 199) (50 - 178) 

92 80 72 61 61 

(41 - 141) (35 - 123) (31 - 110) (27 - 94) (26 - 93) 

80 80 80 71 69 

(35 - 123) (35 - 123) (35 - 123) (31 - 110) (30 - 106) 

119 47 47 47 32 

(53 - 180) (21 - 73) (21 - 73) (21 - 73) (14 - 50) 

166 6 6 3 

(7 - 24) (3 - 9) (3 - 9) (3 - 9) (1 - 5) 

133 112 87 73 84 

(59 - 203) (49 - 171) (38 - 134) (32 - 113) (37 - 130) 

20 12 12 12 7 

(9 - 31) (5 - 18) (5 - 18) (5 - 18) (3 - 10) 

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

 Incidence of Lung Cancer Mortality Associated with Long-Term Exposure to PM2.5 Concentration

and PM2.5 Concentrations that Just Meet the Current and Alternative Annual (n) and Daily (m) Sta

Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

E-89

September 2009 
Table E-67. Estimated Percent of Total Annual Incidence of Lung Cancer Mortality Associated with Long-Term Exposure 

 PM2.5 Concentrations in a Recent Year (2005) and PM2.5 Concentrations that Just Meet the Current and Alternati Based on Adjusting 2005 PM2.5 Concentrations: Estimates Based on Krewski et al. (2009), Using Ambient PM2.5  from 1999 - 20001

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

12.3% 11% 8.7% 7.5% 8.7% 

(5.5% - 18.6%) (4.9% - 16.7%) (3.8% - 13.3%) (3.3% - 11.5%) (3.8% - 13.3%) (3.

12.1% 11.1% 9% 7.8% 8.7% 

(5.4% - 18.3%) (4.9% - 16.9%) (4% - 13.8%) (3.4% - 12%) (3.8% - 13.3%) (2

14.3% 10.4% 8.2% 7% 8.2% 

(6.4% - 21.6%) (4.6% - 15.8%) (3.6% - 12.5%) (3.1% - 10.8%) (3.6% - 12.5%) (2

8.3% 8.3% 8.3% 7.4% 8.3% 

(3.7% - 12.7%) (3.7% - 12.7%) (3.7% - 12.7%) (3.2% - 11.4%) (3.7% - 12.7%) (3.

12.2% 8.9% 7.7% 6.6% 6.8% 

(5.4% - 18.4%) (3.9% - 13.6%) (3.4% - 11.8%) (2.9% - 10.1%) (3% - 10.4%) (2

12.8% 4.5% 4.5% 4.5% 3% 

(5.7% - 19.4%) (2% - 7%) (2% - 7%) (2% - 7%) (1.3% - 4.6%) (0

11.2% 10.3% 8.1% 7% 8.1% 

(5% - 17%) (4.6% - 15.7%) (3.6% - 12.4%) (3.1% - 10.7%) (3.6% - 12.4%) (3.

12.4% 5.8% 5.8% 5.1% 4.1% 

(5.5% - 18.7%) (2.5% - 8.9%) (2.5% - 8.9%) (2.2% - 7.9%) (1.8% - 6.3%) (

9.5% 6.9% 6.6% 5.6% 5.1% 

(4.2% - 14.5%) (3% - 10.7%) (2.9% - 10.2%) (2.4% - 8.6%) (2.2% - 7.8%) (1

9.8% 8.5% 7.6% 6.5% 6.5% 

(4.3% - 14.9%) (3.8% - 13.1%) (3.3% - 11.7%) (2.9% - 10%) (2.8% - 9.9%) (1

6.1% 6.1% 6.1% 5.5% 5.3% 

(2.7% - 9.4%) (2.7% - 9.4%) (2.7% - 9.4%) (2.4% - 8.4%) (2.3% - 8.2%) (1

14.3% 6% 6% 6% 4.3% 

(6.4% - 21.5%) (2.6% - 9.3%) (2.6% - 9.3%) (2.6% - 9.3%) (1.9% - 6.6%) (1

7.6% 2.6% 2.6% 2.6% 1.4% 

(3.3% - 11.6%) (1.1% - 4.1%) (1.1% - 4.1%) (1.1% - 4.1%) (0.6% - 2.1%) (0

12.1% 10.3% 8.2% 7.1% 8% 

(5.4% - 18.3%) (4.6% - 15.7%) (3.6% - 12.6%) (3.1% - 10.9%) (3.5% - 12.3%) (2

7% 4.6% 4.6% 4.6% 3% 

(3.1% - 10.8%) (2% - 7.1%) (2% - 7.1%) (2% - 7.1%) (1.3% - 4.7%) (0

Percent of Total Incidence of Lung Cancer Mortality Associated with Long-Term Exposure to PM2.5 Co

in a Recent Year and PM2.5 Concentrations that Just Meet the Current and Alternative Annual (n) and 

Standards (Standard Combination Denoted n/m):

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL Baltimore, MD Detroit, MI Houston, TX New York, NY St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT

E-90

September 2009 
Table E-68. Estimated Percent of Total Annual Incidence of Lung Cancer Mortality Associated with Long-Term Exposure 

 PM2.5 Concentrations in a Recent Year (2006) and PM2.5 Concentrations that Just Meet the Current and Alternati

 Based on Adjusting 2006 PM2.5 Concentrations: Estimates Based on Krewski et al. (2009), Using Ambient PM2.5 f

 1999 - 20001

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

11.6% 10.3% 8.1% 6.9% 8.1% 

(5.1% - 17.6%) (4.5% - 15.7%) (3.5% - 12.4%) (3% - 10.7%) (3.5% - 12.4%) 

10.5% 9.7% 7.7% 6.6% 7.4% 

(4.7% - 16%) (4.3% - 14.7%) (3.4% - 11.9%) (2.9% - 10.2%) (3.3% - 11.4%) 

13.8% 9.9% 7.7% 6.6% 7.7% 

(6.2% - 20.7%) (4.4% - 15.1%) (3.4% - 11.9%) (2.9% - 10.2%) (3.4% - 11.9%) 

6.3% 6.3% 6.3% 5.5% 6.3% 

(2.7% - 9.7%) (2.7% - 9.7%) (2.7% - 9.7%) (2.4% - 8.5%) (2.7% - 9.7%) 

9.4% 6.5% 5.5% 4.6% 4.7% 

(4.1% - 14.3%) (2.9% - 10%) (2.4% - 8.5%) (2% - 7.1%) (2% - 7.3%) 

13.4% 4.9% 4.9% 4.9% 3.3% 

(6% - 20.2%) (2.1% - 7.6%) (2.1% - 7.6%) (2.1% - 7.6%) (1.4% - 5.1%) 

11.4% 10.5% 8.3% 7.2% 8.3% 

(5.1% - 17.3%) (4.7% - 16%) (3.6% - 12.7%) (3.1% - 11%) (3.6% - 12.7%) 

11.1% 4.9% 4.9% 4.3% 3.3% 

(4.9% - 16.8%) (2.1% - 7.6%) (2.1% - 7.6%) (1.9% - 6.7%) (1.4% - 5.1%) 

8.2% 5.8% 5.5% 4.5% 4.1% 

(3.6% - 12.5%) (2.5% - 8.9%) (2.4% - 8.5%) (2% - 7%) (1.8% - 6.3%) 

9.6% 8.4% 7.5% 6.4% 6.3% 

(4.2% - 14.7%) (3.7% - 12.8%) (3.3% - 11.5%) (2.8% - 9.8%) (2.8% - 9.7%) 

6.4% 6.4% 6.4% 5.8% 5.6% 

(2.8% - 9.8%) (2.8% - 9.8%) (2.8% - 9.8%) (2.5% - 8.9%) (2.4% - 8.6%) 

12.6% 4.9% 4.9% 4.9% 3.3% 

(5.6% - 19%) (2.1% - 7.6%) (2.1% - 7.6%) (2.1% - 7.6%) (1.4% - 5.2%) 

6.1% 1.7% 1.7% 1.7% 0.5% 

(2.7% - 9.4%) (0.7% - 2.6%) (0.7% - 2.6%) (0.7% - 2.6%) (0.2% - 0.8%) 

9.4% 7.8% 6.1% 5.1% 5.9% 

(4.2% - 14.4%) (3.4% - 12%) (2.6% - 9.3%) (2.2% - 7.8%) (2.6% - 9.1%) 

4.5% 2.5% 2.5% 2.5% 1.2% 

(2% - 7%) (1.1% - 3.9%) (1.1% - 3.9%) (1.1% - 3.9%) (0.5% - 2%) 

Percent of Total Incidence of Lung Cancer Mortality Associated with Long-Term Exposure to PM2.5 C

in a Recent Year and PM2.5 Concentrations that Just Meet the Current and Alternative Annual (n) a

Standards (Standard Combination Denoted n/m):

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL Baltimore, MD Detroit, MI Houston, TX New York, NY St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT

E-91

September 2009 
Table E-69. Estimated Percent of Total Annual Incidence of Lung Cancer Mortality Associated with Long-Term Exposure 

 PM2.5 Concentrations in a Recent Year (2007) and PM2.5 Concentrations that Just Meet the Current and Alternati

 Based on Adjusting 2007 PM2.5 Concentrations: Estimates Based on Krewski et al. (2009), Using Ambient PM2.5 fr

 1999 - 20001 

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

11.7% 10.4% 8.1% 7% 8.1% 

(5.2% - 17.7%) (4.6% - 15.8%) (3.6% - 12.5%) (3.1% - 10.8%) (3.6% - 12.5%) 

9.9% 9.1% 7.2% 6.1% 6.9% 

(4.4% - 15.1%) (4% - 13.8%) (3.2% - 11.1%) (2.7% - 9.4%) (3% - 10.6%) 

13.5% 9.7% 7.6% 6.5% 7.6% 

(6% - 20.4%) (4.3% - 14.8%) (3.3% - 11.6%) (2.8% - 10%) (3.3% - 11.6%) 

6.8% 6.8% 6.8% 6% 6.8% 

(3% - 10.5%) (3% - 10.5%) (3% - 10.5%) (2.6% - 9.2%) (3% - 10.5%) 

8.8% 6.1% 5.1% 4.2% 4.3% 

(3.9% - 13.5%) (2.7% - 9.4%) (2.2% - 7.9%) (1.8% - 6.5%) (1.9% - 6.7%) 

14.8% 5.8% 5.8% 5.8% 4% 

(6.7% - 22.3%) (2.5% - 8.9%) (2.5% - 8.9%) (2.5% - 8.9%) (1.8% - 6.3%) 

11% 10.1% 7.9% 6.8% 7.9% 

(4.9% - 16.7%) (4.5% - 15.4%) (3.5% - 12.2%) (3% - 10.5%) (3.5% - 12.2%) 

11.2% 5% 5% 4.4% 3.4% 

(5% - 17.1%) (2.2% - 7.8%) (2.2% - 7.8%) (1.9% - 6.8%) (1.5% - 5.3%) 

8.2% 5.9% 5.5% 4.6% 4.1% 

(3.6% - 12.6%) (2.6% - 9%) (2.4% - 8.6%) (2% - 7.1%) (1.8% - 6.4%) 

9.5% 8.3% 7.4% 6.3% 6.2% 

(4.2% - 14.5%) (3.6% - 12.7%) (3.2% - 11.3%) (2.8% - 9.7%) (2.7% - 9.6%) 

5.4% 5.4% 5.4% 4.8% 4.6% 

(2.4% - 8.3%) (2.4% - 8.3%) (2.4% - 8.3%) (2.1% - 7.4%) (2% - 7.2%) 

12.8% 5.1% 5.1% 5.1% 3.4% 

(5.7% - 19.3%) (2.2% - 7.8%) (2.2% - 7.8%) (2.2% - 7.8%) (1.5% - 5.3%) 

8.2% 3.1% 3.1% 3.1% 1.7% 

(3.6% - 12.6%) (1.3% - 4.8%) (1.3% - 4.8%) (1.3% - 4.8%) (0.7% - 2.7%) 

10% 8.4% 6.5% 5.5% 6.3% 

(4.4% - 15.2%) (3.7% - 12.8%) (2.9% - 10%) (2.4% - 8.5%) (2.8% - 9.8%) 

5.1% 3% 3% 3% 1.7% 

(2.2% - 7.9%) (1.3% - 4.7%) (1.3% - 4.7%) (1.3% - 4.7%) (0.7% - 2.6%) 

 Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Detroit, MI Houston, TX New York, NY St. Louis, MO

Percent of Total Incidence of Lung Cancer Mortality Associated with Long-Term Exposure to PM2.5 C

in a Recent Year and PM2.5 Concentrations that Just Meet the Current and Alternative Annual (n) a

Standards (Standard Combination Denoted n/m):

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL Baltimore, MD

E-92

September 2009 
Table E-70. Percent Reduction from the Current Standards: Estimated Annual Incidence of Lung Cancer Mortality A

 Long-Term Exposure to Ambient PM2.5 Concentrations, Based on Adjusting 2005 PM2.5 Concentrations -- Est

 on Krewski et al. (2009), Using Ambient PM2.5 from 1999 - 20001

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

-12% 0% 21% 32% 21% 

(-12% - -13%) (0% - 0%) (20% - 21%) (31% - 32%) (20% - 21%) 

-9% 0% 19% 30% 22% 

(-8% - -9%) (0% - 0%) (18% - 19%) (29% - 30%) (21% - 22%) 

-38% 0% 21% 32% 21% 

(-37% - -40%) (0% - 0%) (21% - 22%) (32% - 33%) (21% - 22%) 

0% 0% 0% 11% 0% 

(0% - 0%) (0% - 0%) (0% - 0%) (11% - 11%) (0% - 0%) 

-37% 0% 13% 26% 24% 

(-36% - -38%) (0% - 0%) (13% - 14%) (25% - 26%) (23% - 24%) 

-182% 0% 0% 0% 34% 

(-175% - -189%) (0% - 0%) (0% - 0%) (0% - 0%) (34% - 35%) 

-8% 0% 21% 32% 21% 

(-8% - -9%) (0% - 0%) (21% - 22%) (32% - 33%) (21% - 22%) 

-114% 0% 0% 11% 30% 

(-110% - -118%) (0% - 0%) (0% - 0%) (11% - 12%) (29% - 30%) 

-37% 0% 5% 20% 27% 

(-36% - -38%) (0% - 0%) (5% - 5%) (19% - 20%) (27% - 28%) 

-14% 0% 11% 24% 24% 

(-14% - -15%) (0% - 0%) (11% - 11%) (23% - 24%) (24% - 25%) 

0% 0% 0% 10% 13% 

(0% - 0%) (0% - 0%) (0% - 0%) (10% - 10%) (13% - 13%) 

-137% 0% 0% 0% 29% 

(-131% - -144%) (0% - 0%) (0% - 0%) (0% - 0%) (29% - 29%) 

-188% 0% 0% 0% 48% 

(-184% - -192%) (0% - 0%) (0% - 0%) (0% - 0%) (48% - 49%) 

-17% 0% 20% 31% 22% 

(-17% - -18%) (0% - 0%) (20% - 21%) (31% - 32%) (22% - 23%) 

-53% 0% 0% 0% 34% 

(-52% - -54%) (0% - 0%) (0% - 0%) (0% - 0%) (33% - 34%) 

Percent Reduction from the Current Standards: Annual Incidence of Lung Cancer Mortality Associated 

Exposure to PM2.5 Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the Curren

Annual (n) and Daily (m) Standards (Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

E-93

September 2009 
Table E-71. Percent Reduction from the Current Standards: Estimated Annual Incidence of Lung Cancer Mortality A

 Long-Term Exposure to Ambient PM2.5 Concentrations, Based on Adjusting 2006 PM2.5 Concentrations -- Esti

 Krewski et al. (2009), Using Ambient PM2.5 from 1999 - 20001

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

-13% 0% 21% 32% 21% 

(-12% - -13%) (0% - 0%) (21% - 22%) (32% - 33%) (21% - 22%) 

-9% 0% 20% 31% 23% 

(-9% - -9%) (0% - 0%) (20% - 20%) (31% - 32%) (23% - 24%) 

-39% 0% 22% 33% 22% 

(-37% - -41%) (0% - 0%) (21% - 22%) (32% - 34%) (21% - 22%) 

0% 0% 0% 13% 0% 

(0% - 0%) (0% - 0%) (0% - 0%) (13% - 13%) (0% - 0%) 

-43% 0% 16% 30% 28% 

(-42% - -45%) (0% - 0%) (15% - 16%) (30% - 31%) (27% - 28%) 

-174% 0% 0% 0% 33% 

(-167% - -181%) (0% - 0%) (0% - 0%) (0% - 0%) (32% - 33%) 

-8% 0% 21% 32% 21% 

(-8% - -9%) (0% - 0%) (21% - 22%) (31% - 33%) (21% - 22%) 

-126% 0% 0% 13% 33% 

(-121% - -130%) (0% - 0%) (0% - 0%) (12% - 13%) (32% - 33%) 

-41% 0% 5% 22% 30% 

(-40% - -42%) (0% - 0%) (5% - 5%) (21% - 22%) (30% - 30%) 

-15% 0% 11% 24% 25% 

(-14% - -15%) (0% - 0%) (11% - 11%) (23% - 24%) (24% - 25%) 

0% 0% 0% 10% 12% 

(0% - 0%) (0% - 0%) (0% - 0%) (10% - 10%) (12% - 13%) 

-155% 0% 0% 0% 33% 

(-149% - -161%) (0% - 0%) (0% - 0%) (0% - 0%) (32% - 33%) 

-268% 0% 0% 0% 69% 

(-263% - -273%) (0% - 0%) (0% - 0%) (0% - 0%) (69% - 69%) 

-20% 0% 23% 35% 25% 

(-19% - -20%) (0% - 0%) (23% - 23%) (35% - 36%) (25% - 26%) 

-79% 0% 0% 0% 50% 

(-78% - -80%) (0% - 0%) (0% - 0%) (0% - 0%) (50% - 50%) 

Percent Reduction from the Current Standards: Annual Incidence of Lung Cancer Mortality Associated 

Exposure to PM2.5 Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the Curren

Annual (n) and Daily (m) Standards (Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

E-94

September 2009 
Table E-72. Percent Reduction from the Current Standards: Estimated Annual Incidence of Lung Cancer Mortality A

 Long-Term Exposure to Ambient PM2.5 Concentrations, Based on Adjusting 2007 PM2.5 Concentrations -- Est

 Krewski et al. (2009), Using Ambient PM2.5 from 1999 - 20001 

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

-13% 0% 21% 32% 21% 

(-12% - -13%) (0% - 0%) (21% - 22%) (32% - 33%) (21% - 22%) 

-9% 0% 21% 32% 24% 

(-9% - -10%) (0% - 0%) (20% - 21%) (32% - 33%) (23% - 24%) 

-39% 0% 22% 33% 22% 

(-38% - -41%) (0% - 0%) (21% - 22%) (32% - 34%) (21% - 22%) 

0% 0% 0% 12% 0% 

(0% - 0%) (0% - 0%) (0% - 0%) (12% - 12%) (0% - 0%) 

-45% 0% 16% 31% 29% 

(-44% - -46%) (0% - 0%) (16% - 17%) (31% - 32%) (29% - 29%) 

-157% 0% 0% 0% 30% 

(-150% - -165%) (0% - 0%) (0% - 0%) (0% - 0%) (29% - 30%) 

-8% 0% 22% 33% 22% 

(-8% - -9%) (0% - 0%) (21% - 22%) (32% - 33%) (21% - 22%) 

-124% 0% 0% 12% 32% 

(-120% - -128%) (0% - 0%) (0% - 0%) (12% - 13%) (32% - 33%) 

-41% 0% 5% 21% 30% 

(-40% - -42%) (0% - 0%) (5% - 5%) (21% - 22%) (29% - 30%) 

-15% 0% 11% 24% 25% 

(-14% - -15%) (0% - 0%) (11% - 11%) (24% - 24%) (24% - 25%) 

0% 0% 0% 11% 14% 

(0% - 0%) (0% - 0%) (0% - 0%) (11% - 11%) (14% - 14%) 

-152% 0% 0% 0% 32% 

(-147% - -158%) (0% - 0%) (0% - 0%) (0% - 0%) (32% - 32%) 

-168% 0% 0% 0% 44% 

(-164% - -172%) (0% - 0%) (0% - 0%) (0% - 0%) (43% - 44%) 

-19% 0% 22% 34% 25% 

(-19% - -20%) (0% - 0%) (22% - 23%) (34% - 35%) (24% - 25%) 

-69% 0% 0% 0% 44% 

(-68% - -70%) (0% - 0%) (0% - 0%) (0% - 0%) (44% - 44%) 

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on follow-up through 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Krewski et al., 2009).

 Dallas, TX Fresno, CA Los Angeles, CA

Percent Reduction from the Current Standards: Annual Incidence of Lung Cancer Mortality Associated 

Exposure to PM2.5 Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the Curren

Annual (n) and Daily (m) Standards (Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

E-95

September 2009 
Figure E-22. Estimated Percent Reductions From the Current Standard to Alternative 

Standards in Lung Cancer Mortality Associated with Long-Term Exposure to PM2.5

(Exposure Period: 1999 – 2000): Based on 2005 Air Quality Data*

-200%

-180%

-160%

-140%

-120%

-100%

-80%

-60%

-40%

-20%

0%

20%

40%

60%

80%

100%

2005 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Reduction from Current Standard

 Atlanta, GA 98 (43 - 149); 11% (4.9% - 16.7%)

 Baltimore, MD 106 (47 - 162); 11.1% (4.9% - 16.9%)

 Birmingham, AL 66 (29 - 101); 10.4% (4.6% - 15.8%)

 Dallas, TX 69 (31 - 107); 8.3% (3.7% - 12.7%)

 Detroit, MI 112 (49 - 171); 8.9% (3.9% - 13.6%)

 Fresno, CA 13 (6 - 20); 4.5% (2% - 7%)

 Houston, TX 120 (53 - 183); 10.3% (4.6% - 15.7%)

 Los Angeles, CA 174 (76 - 269); 5.8% (2.5% - 8.9%)

 New York, NY 190 (83 - 292); 6.9% (3% - 10.7%)

 Philadelphia, PA 83 (37 - 127); 8.5% (3.8% - 13.1%)

 Phoenix, AZ 84 (37 - 129); 6.1% (2.7% - 9.4%)

 Pittsburgh, PA 57 (25 - 88); 6% (2.6% - 9.3%)

 Salt Lake City, UT 5 (2 - 7); 2.6% (1.1% - 4.1%)

 St. Louis, MO 136 (60 - 207); 10.3% (4.6% - 15.7%)

 Tacoma, WA 17 (8 - 27); 4.6% (2% - 7.1%)

*Based on Krewski et al. (2009), exposure period from 1999 – 2000. The legend contains, for each urban area, the 

incidence estimate (and 95% CI) and the estimate of percent of total incidence (and 95% CI) under the current 

standards. 

**The current standards consist of an annual standard of 15 μg/m3

 and a daily standard of 35 μg/m3. Combinations of 

an annual standard (n) and a daily standard (m) are denoted n/m in this figure. 

E-96

September 2009 Draft - Do Not Quote or Cite
Figure E-23. Estimated Percent Reductions From the Current Standard to Alternative 

Standards in Lung Cancer Mortality Associated with Long-Term Exposure to PM2.5

(Exposure Period: 1999 – 2000): Based on 2006 Air Quality Data*

-200%

-180%

-160%

-140%

-120%

-100%

-80%

-60%

-40%

-20%

0%

20%

40%

60%

80%

100%

2006 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Reduction from Current Standard

 Atlanta, GA 95 (42 - 144); 10.3% (4.5% - 15.7%)

 Baltimore, MD 93 (41 - 141); 9.7% (4.3% - 14.7%)

 Birmingham, AL 64 (28 - 98); 9.9% (4.4% - 15.1%)

 Dallas, TX 54 (23 - 83); 6.3% (2.7% - 9.7%)

 Detroit, MI 82 (36 - 126); 6.5% (2.9% - 10%)

 Fresno, CA 14 (6 - 22); 4.9% (2.1% - 7.6%)

 Houston, TX 127 (56 - 193); 10.5% (4.7% - 16%)

 Los Angeles, CA 149 (65 - 231); 4.9% (2.1% - 7.6%)

 New York, NY 160 (70 - 247); 5.8% (2.5% - 8.9%)

 Philadelphia, PA 81 (36 - 125); 8.4% (3.7% - 12.8%)

 Phoenix, AZ 92 (40 - 141); 6.4% (2.8% - 9.8%)

 Pittsburgh, PA 46 (20 - 71); 4.9% (2.1% - 7.6%)

 Salt Lake City, UT 3 (1 - 5); 1.7% (0.7% - 2.6%)

 St. Louis, MO 104 (46 - 160); 7.8% (3.4% - 12%)

 Tacoma, WA 10 (4 - 15); 2.5% (1.1% - 3.9%)

*Based on Krewski et al. (2009), exposure period from 1999 – 2000. The legend contains, for each urban area, the 

incidence estimate (and 95% CI) and the estimate of percent of total incidence (and 95% CI) under the current 

standards. 

**The current standards consist of an annual standard of 15 μg/m3

 and a daily standard of 35 μg/m3. Combinations of 

an annual standard (n) and a daily standard (m) are denoted n/m in this figure. 

***The percent reduction for 2006 air quality in Salt Lake City is -268%. 

E-97

September 2009 Draft - Do Not Quote or Cite
Figure E-24. Estimated Percent Reductions From the Current Standard to Alternative 

Standards in Lung Cancer Mortality Associated with Long-Term Exposure to PM2.5

(Exposure Period: 1999 – 2000): Based on 2007 Air Quality Data*

-200%

-180%

-160%

-140%

-120%

-100%

-80%

-60%

-40%

-20%

0%

20%

40%

60%

80%

100%

2007 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Reduction from Current Standard

 Atlanta, GA 98 (43 - 149); 10.4% (4.6% - 15.8%)

 Baltimore, MD 87 (38 - 133); 9.1% (4% - 13.8%)

 Birmingham, AL 63 (28 - 96); 9.7% (4.3% - 14.8%)

 Dallas, TX 59 (26 - 91); 6.8% (3% - 10.5%)

 Detroit, MI 76 (33 - 117); 6.1% (2.7% - 9.4%)

 Fresno, CA 17 (7 - 26); 5.8% (2.5% - 8.9%)

 Houston, TX 125 (55 - 190); 10.1% (4.5% - 15.4%)

 Los Angeles, CA 153 (67 - 238); 5% (2.2% - 7.8%)

 New York, NY 163 (71 - 252); 5.9% (2.6% - 9%)

 Philadelphia, PA 80 (35 - 123); 8.3% (3.6% - 12.7%)

 Phoenix, AZ 80 (35 - 123); 5.4% (2.4% - 8.3%)

 Pittsburgh, PA 47 (21 - 73); 5.1% (2.2% - 7.8%)

 Salt Lake City, UT 6 (3 - 9); 3.1% (1.3% - 4.8%)

 St. Louis, MO 112 (49 - 171); 8.4% (3.7% - 12.8%)

 Tacoma, WA 12 (5 - 18); 3% (1.3% - 4.7%)

*Based on Krewski et al. (2009), exposure period from 1999 – 2000. The legend contains, for each urban area, the 

incidence estimate (and 95% CI) and the estimate of percent of total incidence (and 95% CI) under the current 

standards. 

**The current standards consist of an annual standard of 15 μg/m3

 and a daily standard of 35 μg/m3. Combinations of 

an annual standard (n) and a daily standard (m) are denoted n/m in this figure. 

E-98

September 2009 Draft - Do Not Quote or Cite
Table E-73. Estimated Annual Incidence of Non-Accidental Mortality Associated with Short-Term Exposure to Ambient P

 Concentrations in a Recent Year (2005) and PM2.5 Concentrations that Just Meet the Current and Alternative Sta

 Based on Adjusting 2005 PM2.5 Concentrations1

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

191 175 149 136 149 

(36 - 344) (33 - 316) (28 - 269) (26 - 245) (28 - 269) 

271 256 224 206 219 

(110 - 429) (104 - 406) (91 - 355) (84 - 327) (89 - 348) 

49 38 33 30 33 

(-77 - 173) (-60 - 135) (-51 - 115) (-46 - 105) (-51 - 115) 

151 151 151 140 151 

(36 - 264) (36 - 264) (36 - 264) (34 - 245) (36 - 264) 

174 141 129 119 121 

(-31 - 375) (-25 - 305) (-23 - 280) (-21 - 257) (-21 - 260) 

80 44 44 44 38 

(11 - 147) (6 - 82) (6 - 82) (6 - 82) (5 - 70) 

245 232 197 180 197 

(50 - 438) (47 - 414) (40 - 352) (37 - 321) (40 - 352) 

134 85 85 80 72 

(-192 - 458) (-121 - 289) (-121 - 289) (-114 - 273) (-103 - 247) 

858 714 696 639 611 

(504 - 1209) (419 - 1007) (408 - 981) (375 - 902) (358 - 861) (

229 211 197 181 180 

(85 - 372) (78 - 342) (73 - 321) (67 - 295) (67 - 293) 

240 240 240 228 225 

(40 - 438) (40 - 438) (40 - 438) (38 - 417) (37 - 411) 

233 135 135 135 116 

(69 - 395) (40 - 230) (40 - 230) (40 - 230) (34 - 197) 

52 33 33 33 28 

(11 - 93) (7 - 59) (7 - 59) (7 - 59) (6 - 51) 

281 252 219 201 215 

(81 - 478) (73 - 429) (63 - 373) (58 - 342) (62 - 367) 

59 48 48 48 41 

(10 - 107) (8 - 87) (8 - 87) (8 - 87) (7 - 74) 

Incidence of Non-Accidental Mortality Associated with Short-Term Exposure to PM2.5 Concentrations 

Year and PM2.5 Concentrations that Just Meet the Current and Alternative Annual (n) and Daily (m) S

(Standard Combination Denoted n/m):

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on location-specific single pollutant concentration-response function estimates from Zanobetti and Schwartz (2009) that have been "shrunken" toward

regional means. "Shrunken" coefficient estimates and their standard errors were sent to EPA by A. Zanobetti via email. Numbers are rounded to the neares

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL Baltimore, MD Detroit, MI Houston, TX New York, NY St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT

E-99

September 2009 
Table E-74. Estimated Annual Incidence of Non-Accidental Mortality Associated with Short-Term Exposure to Ambient P

 Concentrations in a Recent Year (2006) and PM2.5 Concentrations that Just Meet the Current and Alternative Sta

 Based on Adjusting 2006 PM2.5 Concentrations1

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

188 172 146 134 146 

(36 - 338) (33 - 310) (28 - 264) (25 - 241) (28 - 264) 

248 234 205 188 201 

(101 - 393) (95 - 372) (83 - 325) (76 - 299) (81 - 318) 

48 38 32 29 32 

(-75 - 169) (-59 - 132) (-50 - 113) (-45 - 103) (-50 - 113) 

129 129 129 120 129 

(31 - 226) (31 - 226) (31 - 226) (29 - 210) (31 - 226) 

145 117 108 99 100 

(-25 - 313) (-21 - 254) (-19 - 233) (-17 - 214) (-18 - 217) 

84 46 46 46 40 

(12 - 155) (7 - 86) (7 - 86) (7 - 86) (6 - 73) 

258 243 207 188 207 

(53 - 460) (50 - 434) (42 - 369) (38 - 337) (42 - 369) 

124 78 78 74 67 

(-178 - 423) (-112 - 267) (-112 - 267) (-106 - 252) (-96 - 228) 

786 654 637 585 559 

(461 - 1107) (384 - 922) (374 - 898) (343 - 826) (328 - 789) (

226 208 194 179 178 

(83 - 366) (77 - 337) (72 - 315) (66 - 290) (65 - 288) 

255 255 255 243 239 

(42 - 466) (42 - 466) (42 - 466) (40 - 443) (40 - 436) 

210 122 122 122 104 

(62 - 357) (36 - 208) (36 - 208) (36 - 208) (31 - 177) 

48 30 30 30 26 

(10 - 86) (6 - 54) (6 - 54) (6 - 54) (5 - 46) 

238 214 185 170 183 

(69 - 406) (62 - 364) (53 - 316) (49 - 290) (53 - 311) 

48 39 39 39 34 

(8 - 88) (7 - 71) (7 - 71) (7 - 71) (6 - 61) 

Incidence of Non-Accidental Mortality Associated with Short-Term Exposure to PM2.5 Concentrations 

Year and PM2.5 Concentrations that Just Meet the Current and Alternative Annual (n) and Daily (m) S

(Standard Combination Denoted n/m):

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on location-specific single pollutant concentration-response function estimates from Zanobetti and Schwartz (2009) that have been "shrunken" toward

regional means. "Shrunken" coefficient estimates and their standard errors were sent to EPA by A. Zanobetti via email. Numbers are rounded to the neares

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL Baltimore, MD Detroit, MI Houston, TX New York, NY St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT

E-100

September 2009 
Table E-75. Estimated Annual Incidence of Non-Accidental Mortality Associated with Short-Term Exposure to Ambient P

 Concentrations in a Recent Year (2007) and PM2.5 Concentrations that Just Meet the Current and Alternative Sta

 Based on Adjusting 2007 PM2.5 Concentrations1 

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

193 177 151 137 151 

(37 - 347) (34 - 319) (29 - 271) (26 - 248) (29 - 271) 

238 225 197 181 192 

(97 - 377) (91 - 357) (80 - 312) (73 - 287) (78 - 306) 

48 37 32 29 32 

(-74 - 168) (-58 - 131) (-49 - 112) (-45 - 102) (-49 - 112) 

137 137 137 127 137 

(33 - 240) (33 - 240) (33 - 240) (31 - 223) (33 - 240) 

138 112 102 94 95 

(-24 - 298) (-20 - 242) (-18 - 222) (-16 - 204) (-17 - 207) 

92 51 51 51 43 

(13 - 168) (7 - 94) (7 - 94) (7 - 94) (6 - 80) 

254 240 204 186 204 

(52 - 454) (49 - 429) (42 - 365) (38 - 333) (42 - 365) 

125 79 79 74 67 

(-180 - 427) (-113 - 270) (-113 - 270) (-107 - 255) (-97 - 231) 

793 659 642 590 564 

(465 - 1117) (387 - 930) (377 - 906) (346 - 833) (331 - 795) (

224 206 193 177 176 

(83 - 363) (76 - 334) (71 - 313) (65 - 287) (65 - 286) 

242 242 242 230 226 

(40 - 441) (40 - 441) (40 - 441) (38 - 419) (37 - 413) 

212 123 123 123 105 

(62 - 359) (36 - 209) (36 - 209) (36 - 209) (31 - 179) 

58 36 36 36 31 

(12 - 102) (7 - 65) (7 - 65) (7 - 65) (6 - 56) 

248 222 193 177 190 

(71 - 421) (64 - 378) (56 - 328) (51 - 301) (55 - 323) 

52 42 42 42 36 

(9 - 94) (7 - 76) (7 - 76) (7 - 76) (6 - 65) 

 Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Detroit, MI Houston, TX New York, NY St. Louis, MO

Incidence of Non-Accidental Mortality Associated with Short-Term Exposure to PM2.5 Concentrations 

Year and PM2.5 Concentrations that Just Meet the Current and Alternative Annual (n) and Daily (m) S

(Standard Combination Denoted n/m):

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on location-specific single pollutant concentration-response function estimates from Zanobetti and Schwartz (2009) that have been "shrunken" toward

regional means. "Shrunken" coefficient estimates and their standard errors were sent to EPA by A. Zanobetti via email. Numbers are rounded to the neares

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL Baltimore, MD

E-101

September 2009 
Table E-76. Estimated Percent of Total Annual Incidence of Non-Accidental Mortality Associated with Short-Term Exposu

 PM2.5 Concentrations in a Recent Year (2005) and PM2.5 Concentrations that Just Meet the Current and Alternati

 Based on Adjusting 2005 PM2.5 Concentrations1

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

1.3% 1.2% 1% 0.9% 1% 

(0.3% - 2.4%) (0.2% - 2.2%) (0.2% - 1.9%) (0.2% - 1.7%) (0.2% - 1.9%) 

2% 1.9% 1.7% 1.5% 1.6% 

(0.8% - 3.2%) (0.8% - 3%) (0.7% - 2.6%) (0.6% - 2.4%) (0.7% - 2.6%) 

0.5% 0.4% 0.3% 0.3% 0.3% 

(-0.8% - 1.8%) (-0.6% - 1.4%) (-0.5% - 1.2%) (-0.5% - 1.1%) (-0.5% - 1.2%) 

1.2% 1.2% 1.2% 1.1% 1.2% 

(0.3% - 2.1%) (0.3% - 2.1%) (0.3% - 2.1%) (0.3% - 2%) (0.3% - 2.1%) 

1% 0.8% 0.7% 0.7% 0.7% 

(-0.2% - 2.2%) (-0.1% - 1.8%) (-0.1% - 1.6%) (-0.1% - 1.5%) (-0.1% - 1.5%) 

1.5% 0.8% 0.8% 0.8% 0.7% 

(0.2% - 2.7%) (0.1% - 1.5%) (0.1% - 1.5%) (0.1% - 1.5%) (0.1% - 1.3%) 

1.4% 1.3% 1.1% 1% 1.1% 

(0.3% - 2.5%) (0.3% - 2.3%) (0.2% - 2%) (0.2% - 1.8%) (0.2% - 2%) 

0.2% 0.2% 0.2% 0.1% 0.1% 

(-0.3% - 0.8%) (-0.2% - 0.5%) (-0.2% - 0.5%) (-0.2% - 0.5%) (-0.2% - 0.4%) 

1.7% 1.4% 1.3% 1.2% 1.2% 

(1% - 2.3%) (0.8% - 2%) (0.8% - 1.9%) (0.7% - 1.7%) (0.7% - 1.7%) 

1.6% 1.5% 1.4% 1.3% 1.3% 

(0.6% - 2.6%) (0.6% - 2.4%) (0.5% - 2.3%) (0.5% - 2.1%) (0.5% - 2.1%) 

1.1% 1.1% 1.1% 1% 1% 

(0.2% - 2%) (0.2% - 2%) (0.2% - 2%) (0.2% - 1.9%) (0.2% - 1.9%) 

1.7% 1% 1% 1% 0.9% 

(0.5% - 2.9%) (0.3% - 1.7%) (0.3% - 1.7%) (0.3% - 1.7%) (0.3% - 1.5%) 

1.1% 0.7% 0.7% 0.7% 0.6% 

(0.2% - 2%) (0.1% - 1.3%) (0.1% - 1.3%) (0.1% - 1.3%) (0.1% - 1.1%) 

1.5% 1.4% 1.2% 1.1% 1.2% 

(0.4% - 2.6%) (0.4% - 2.4%) (0.3% - 2%) (0.3% - 1.9%) (0.3% - 2%) 

1.2% 1% 1% 1% 0.8% 

(0.2% - 2.2%) (0.2% - 1.8%) (0.2% - 1.8%) (0.2% - 1.8%) (0.1% - 1.5%) 

Percent of Total Incidence of Non-Accidental Mortality Associated with Short-Term Exposure 

Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the Current and Alternative 

Daily (m) Standards (Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on location-specific single pollutant concentration-response function estimates from Zanobetti and Schwartz (2009) that have been "shrunken" toward

regional means. "Shrunken" coefficient estimates and their standard errors were sent to EPA by A. Zanobetti via email. Percents are rounded to the nearest 

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

E-102

September 2009 
Table E-77. Estimated Percent of Total Annual Incidence of Non-Accidental Mortality Associated with Short-Term Exposu

 PM2.5 Concentrations in a Recent Year (2006) and PM2.5 Concentrations that Just Meet the Current and Alternati

 Based on Adjusting 2006 PM2.5 Concentrations1 

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

1.3% 1.2% 1% 0.9% 1% 

(0.2% - 2.3%) (0.2% - 2.1%) (0.2% - 1.8%) (0.2% - 1.6%) (0.2% - 1.8%) 

1.8% 1.7% 1.5% 1.4% 1.5% 

(0.7% - 2.9%) (0.7% - 2.7%) (0.6% - 2.4%) (0.6% - 2.2%) (0.6% - 2.3%) 

0.5% 0.4% 0.3% 0.3% 0.3% 

(-0.8% - 1.8%) (-0.6% - 1.4%) (-0.5% - 1.2%) (-0.5% - 1.1%) (-0.5% - 1.2%) 

1% 1% 1% 0.9% 1% 

(0.2% - 1.8%) (0.2% - 1.8%) (0.2% - 1.8%) (0.2% - 1.7%) (0.2% - 1.8%) 

0.8% 0.7% 0.6% 0.6% 0.6% 

(-0.1% - 1.8%) (-0.1% - 1.5%) (-0.1% - 1.4%) (-0.1% - 1.2%) (-0.1% - 1.3%) 

1.5% 0.8% 0.8% 0.8% 0.7% 

(0.2% - 2.8%) (0.1% - 1.6%) (0.1% - 1.6%) (0.1% - 1.6%) (0.1% - 1.3%) 

1.4% 1.3% 1.1% 1% 1.1% 

(0.3% - 2.5%) (0.3% - 2.3%) (0.2% - 2%) (0.2% - 1.8%) (0.2% - 2%) 

0.2% 0.1% 0.1% 0.1% 0.1% 

(-0.3% - 0.8%) (-0.2% - 0.5%) (-0.2% - 0.5%) (-0.2% - 0.5%) (-0.2% - 0.4%) 

1.5% 1.3% 1.2% 1.1% 1.1% 

(0.9% - 2.1%) (0.7% - 1.8%) (0.7% - 1.7%) (0.7% - 1.6%) (0.6% - 1.5%) 

1.6% 1.5% 1.4% 1.3% 1.3% 

(0.6% - 2.6%) (0.5% - 2.4%) (0.5% - 2.2%) (0.5% - 2.1%) (0.5% - 2.1%) 

1.1% 1.1% 1.1% 1.1% 1.1% 

(0.2% - 2.1%) (0.2% - 2.1%) (0.2% - 2.1%) (0.2% - 2%) (0.2% - 1.9%) 

1.6% 0.9% 0.9% 0.9% 0.8% 

(0.5% - 2.7%) (0.3% - 1.5%) (0.3% - 1.5%) (0.3% - 1.5%) (0.2% - 1.3%) 

1% 0.6% 0.6% 0.6% 0.5% 

(0.2% - 1.8%) (0.1% - 1.1%) (0.1% - 1.1%) (0.1% - 1.1%) (0.1% - 1%) 

1.3% 1.2% 1% 0.9% 1% 

(0.4% - 2.2%) (0.3% - 2%) (0.3% - 1.7%) (0.3% - 1.6%) (0.3% - 1.7%) 

1% 0.8% 0.8% 0.8% 0.7% 

(0.2% - 1.8%) (0.1% - 1.4%) (0.1% - 1.4%) (0.1% - 1.4%) (0.1% - 1.2%) 

Percent of Total Incidence of Non-Accidental Mortality Associated with Short-Term Exposure 

Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the Current and Alternative 

Daily (m) Standards (Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on location-specific single pollutant concentration-response function estimates from Zanobetti and Schwartz (2009) that have been "shrunken" toward

regional means. "Shrunken" coefficient estimates and their standard errors were sent to EPA by A. Zanobetti via email. Percents are rounded to the nearest 

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

E-103

September 2009 
Table E-78. Estimated Percent of Total Annual Incidence of Non-Accidental Mortality Associated with Short-Term Exposu

 PM2.5 Concentrations in a Recent Year (2007) and PM2.5 Concentrations that Just Meet the Current and Alternati

 Based on Adjusting 2007 PM2.5 Concentrations1 

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

1.3% 1.2% 1% 0.9% 1% 

(0.2% - 2.3%) (0.2% - 2.1%) (0.2% - 1.8%) (0.2% - 1.6%) (0.2% - 1.8%) (

1.7% 1.7% 1.4% 1.3% 1.4% 

(0.7% - 2.8%) (0.7% - 2.6%) (0.6% - 2.3%) (0.5% - 2.1%) (0.6% - 2.2%) (

0.5% 0.4% 0.3% 0.3% 0.3% 

(-0.8% - 1.7%) (-0.6% - 1.4%) (-0.5% - 1.2%) (-0.5% - 1.1%) (-0.5% - 1.2%) 

1.1% 1.1% 1.1% 1% 1.1% 

(0.3% - 1.9%) (0.3% - 1.9%) (0.3% - 1.9%) (0.2% - 1.7%) (0.3% - 1.9%) (

0.8% 0.7% 0.6% 0.6% 0.6% 

(-0.1% - 1.8%) (-0.1% - 1.4%) (-0.1% - 1.3%) (-0.1% - 1.2%) (-0.1% - 1.2%) 

1.6% 0.9% 0.9% 0.9% 0.8% 

(0.2% - 3%) (0.1% - 1.7%) (0.1% - 1.7%) (0.1% - 1.7%) (0.1% - 1.4%) (

1.4% 1.3% 1.1% 1% 1.1% 

(0.3% - 2.4%) (0.3% - 2.3%) (0.2% - 1.9%) (0.2% - 1.8%) (0.2% - 1.9%) (

0.2% 0.1% 0.1% 0.1% 0.1% 

(-0.3% - 0.8%) (-0.2% - 0.5%) (-0.2% - 0.5%) (-0.2% - 0.5%) (-0.2% - 0.4%) (

1.5% 1.3% 1.2% 1.1% 1.1% 

(0.9% - 2.2%) (0.7% - 1.8%) (0.7% - 1.7%) (0.7% - 1.6%) (0.6% - 1.5%) (

1.6% 1.5% 1.4% 1.3% 1.3% 

(0.6% - 2.6%) (0.5% - 2.4%) (0.5% - 2.2%) (0.5% - 2.1%) (0.5% - 2%) (

1% 1% 1% 1% 1% 

(0.2% - 1.9%) (0.2% - 1.9%) (0.2% - 1.9%) (0.2% - 1.8%) (0.2% - 1.8%) (

1.6% 0.9% 0.9% 0.9% 0.8% 

(0.5% - 2.7%) (0.3% - 1.6%) (0.3% - 1.6%) (0.3% - 1.6%) (0.2% - 1.3%) (

1.2% 0.7% 0.7% 0.7% 0.6% 

(0.2% - 2.1%) (0.2% - 1.3%) (0.2% - 1.3%) (0.2% - 1.3%) (0.1% - 1.1%) (

1.4% 1.2% 1.1% 1% 1% 

(0.4% - 2.3%) (0.4% - 2.1%) (0.3% - 1.8%) (0.3% - 1.7%) (0.3% - 1.8%) (

1% 0.8% 0.8% 0.8% 0.7% 

(0.2% - 1.9%) (0.1% - 1.5%) (0.1% - 1.5%) (0.1% - 1.5%) (0.1% - 1.3%) (

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on location-specific single pollutant concentration-response function estimates from Zanobetti and Schwartz (2009) that have been "shrunken" toward

regional means. "Shrunken" coefficient estimates and their standard errors were sent to EPA by A. Zanobetti via email. Percents are rounded to the nearest 

 Dallas, TX Fresno, CA Los Angeles, CA

Percent of Total Incidence of Non-Accidental Mortality Associated with Short-Term Exposure t

Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the Current and Alternative 

Daily (m) Standards (Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

E-104

September 2009 
Table E-79. Percent Reduction from the Current Standards: Estimated Annual Incidence of Non-Accidental Mortality Asso

 Short-Term Exposure to Ambient PM2.5 Concentrations, Based on Adjusting 2005 PM2.5 Concentrations1

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

 Atlanta, GA -9% 0% 15% 22% 15% 

(-9% - -9%) (0% - 0%) (15% - 15%) (22% - 23%) (15% - 15%) (23

 Baltimore, MD -6% 0% 13% 20% 14% 

(-6% - -6%) (0% - 0%) (12% - 13%) (19% - 20%) (14% - 15%) (29

 Birmingham, AL -28% 0% 15% 23% 15% 

(-28% - -28%) (0% - 0%) (15% - 15%) (22% - 23%) (15% - 15%) (29

 Dallas, TX 0% 0% 0% 7% 0% 

(0% - 0%) (0% - 0%) (0% - 0%) (7% - 7%) (0% - 0%) (7

 Detroit, MI -23% 0% 8% 16% 15% 

(-23% - -23%) (0% - 0%) (8% - 8%) (16% - 16%) (14% - 15%) (29

 Fresno, CA -81% 0% 0% 0% 15% 

(-80% - -82%) (0% - 0%) (0% - 0%) (0% - 0%) (14% - 15%) (29

 Houston, TX -6% 0% 15% 22% 15% 

(-6% - -6%) (0% - 0%) (15% - 15%) (22% - 23%) (15% - 15%) (22

 Los Angeles, CA -58% 0% 0% 6% 15% 

(-58% - -59%) (0% - 0%) (0% - 0%) (6% - 6%) (15% - 15%) (29

 New York, NY -20% 0% 3% 10% 14% 

(-20% - -20%) (0% - 0%) (3% - 3%) (10% - 10%) (14% - 15%) (29

 Philadelphia, PA -9% 0% 6% 14% 14% 

(-9% - -9%) (0% - 0%) (6% - 6%) (14% - 14%) (14% - 15%) (29

 Phoenix, AZ 0% 0% 0% 5% 6% 

(0% - 0%) (0% - 0%) (0% - 0%) (5% - 5%) (6% - 6%) (22

 Pittsburgh, PA -72% 0% 0% 0% 15% 

(-72% - -73%) (0% - 0%) (0% - 0%) (0% - 0%) (14% - 15%) (29

 Salt Lake City, UT -58% 0% 0% 0% 15% 

(-58% - -59%) (0% - 0%) (0% - 0%) (0% - 0%) (15% - 15%) (29

 St. Louis, MO -12% 0% 13% 20% 15% 

(-12% - -12%) (0% - 0%) (13% - 13%) (20% - 20%) (14% - 15%) (29

 Tacoma, WA -23% 0% 0% 0% 15% 

(-23% - -23%) (0% - 0%) (0% - 0%) (0% - 0%) (15% - 15%) (29

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on location-specific single pollutant concentration-response function estimates from Zanobetti and Schwartz (2009) that have been "shrunken" towards 

regional means. "Shrunken" coefficient estimates and their standard errors were sent to EPA by A. Zanobetti via email.

Risk Assessment 

Location

Estimated Percent Reduction From the Current Standards to Several Alternative Standards in Non-Accident

Associated with Short-Term Exposure to PM2.5 Concentrations in a Recent Year and PM2.5 Concentrations th

the Current and Alternative Annual (n) and Daily (m) Standards (Standard Combination Denoted n/m

E-105

September 2009 
Table E-80. Percent Reduction from the Current Standards: Estimated Annual Incidence of Non-Accidental Mortality Asso

 Short-Term Exposure to Ambient PM2.5 Concentrations, Based on Adjusting 2006 PM2.5 Concentrations1

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

 Atlanta, GA -9% 0% 15% 22% 15% 

(-9% - -9%) (0% - 0%) (15% - 15%) (22% - 23%) (15% - 15%) (23

 Baltimore, MD -6% 0% 13% 20% 14% 

(-6% - -6%) (0% - 0%) (12% - 13%) (20% - 20%) (14% - 15%) (29

 Birmingham, AL -28% 0% 15% 23% 15% 

(-28% - -28%) (0% - 0%) (15% - 15%) (22% - 23%) (15% - 15%) (29

 Dallas, TX 0% 0% 0% 7% 0% 

(0% - 0%) (0% - 0%) (0% - 0%) (7% - 7%) (0% - 0%) (7

 Detroit, MI -23% 0% 8% 16% 15% 

(-23% - -23%) (0% - 0%) (8% - 8%) (16% - 16%) (15% - 15%) (29

 Fresno, CA -81% 0% 0% 0% 15% 

(-80% - -82%) (0% - 0%) (0% - 0%) (0% - 0%) (14% - 15%) (29

 Houston, TX -6% 0% 15% 22% 15% 

(-6% - -6%) (0% - 0%) (15% - 15%) (22% - 23%) (15% - 15%) (22

 Los Angeles, CA -58% 0% 0% 6% 15% 

(-58% - -59%) (0% - 0%) (0% - 0%) (6% - 6%) (15% - 15%) (29

 New York, NY -20% 0% 3% 10% 14% 

(-20% - -20%) (0% - 0%) (3% - 3%) (10% - 10%) (14% - 15%) (29

 Philadelphia, PA -9% 0% 6% 14% 14% 

(-9% - -9%) (0% - 0%) (6% - 6%) (14% - 14%) (14% - 15%) (29

 Phoenix, AZ 0% 0% 0% 5% 6% 

(0% - 0%) (0% - 0%) (0% - 0%) (5% - 5%) (6% - 6%) (22

 Pittsburgh, PA -72% 0% 0% 0% 15% 

(-72% - -73%) (0% - 0%) (0% - 0%) (0% - 0%) (15% - 15%) (29

 Salt Lake City, UT -58% 0% 0% 0% 15% 

(-58% - -59%) (0% - 0%) (0% - 0%) (0% - 0%) (15% - 15%) (29

 St. Louis, MO -12% 0% 13% 20% 15% 

(-12% - -12%) (0% - 0%) (13% - 13%) (20% - 20%) (14% - 15%) (29

 Tacoma, WA -23% 0% 0% 0% 15% 

(-23% - -23%) (0% - 0%) (0% - 0%) (0% - 0%) (15% - 15%) (29

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on location-specific single pollutant concentration-response function estimates from Zanobetti and Schwartz (2009) that have been "shrunken" towards 

regional means. "Shrunken" coefficient estimates and their standard errors were sent to EPA by A. Zanobetti via email.

Risk Assessment 

Location

Estimated Percent Reduction From the Current Standards to Several Alternative Standards in Non-Accidenta

Associated with Short-Term Exposure to PM2.5 Concentrations in a Recent Year and PM2.5 Concentrations tha

the Current and Alternative Annual (n) and Daily (m) Standards (Standard Combination Denoted n/m

E-106

September 2009 
Table E-81. Percent Reduction from the Current Standards: Estimated Annual Incidence of Non-Accidental Mortality Asso

 Short-Term Exposure to Ambient PM2.5 Concentrations, Based on Adjusting 2007 PM2.5 Concentrations1

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

 Atlanta, GA -9% 0% 15% 22% 15% 

(-9% - -9%) (0% - 0%) (15% - 15%) (22% - 23%) (15% - 15%) (23

 Baltimore, MD -6% 0% 13% 20% 14% 

(-6% - -6%) (0% - 0%) (12% - 13%) (20% - 20%) (14% - 15%) (29

 Birmingham, AL -28% 0% 15% 23% 15% 

(-28% - -28%) (0% - 0%) (15% - 15%) (22% - 23%) (15% - 15%) (29

 Dallas, TX 0% 0% 0% 7% 0% 

(0% - 0%) (0% - 0%) (0% - 0%) (7% - 7%) (0% - 0%) (7

 Detroit, MI -23% 0% 8% 16% 15% 

(-23% - -23%) (0% - 0%) (8% - 8%) (16% - 16%) (15% - 15%) (29

 Fresno, CA -81% 0% 0% 0% 15% 

(-79% - -82%) (0% - 0%) (0% - 0%) (0% - 0%) (14% - 15%) (29

 Houston, TX -6% 0% 15% 22% 15% 

(-6% - -6%) (0% - 0%) (15% - 15%) (22% - 23%) (15% - 15%) (22

 Los Angeles, CA -58% 0% 0% 6% 15% 

(-58% - -59%) (0% - 0%) (0% - 0%) (6% - 6%) (15% - 15%) (29

 New York, NY -20% 0% 3% 10% 14% 

(-20% - -20%) (0% - 0%) (3% - 3%) (10% - 10%) (14% - 15%) (29

 Philadelphia, PA -9% 0% 6% 14% 14% 

(-9% - -9%) (0% - 0%) (6% - 6%) (14% - 14%) (14% - 15%) (29

 Phoenix, AZ 0% 0% 0% 5% 6% 

(0% - 0%) (0% - 0%) (0% - 0%) (5% - 5%) (6% - 6%) (22

 Pittsburgh, PA -72% 0% 0% 0% 15% 

(-72% - -73%) (0% - 0%) (0% - 0%) (0% - 0%) (15% - 15%) (29

 Salt Lake City, UT -58% 0% 0% 0% 15% 

(-58% - -59%) (0% - 0%) (0% - 0%) (0% - 0%) (15% - 15%) (29

 St. Louis, MO -12% 0% 13% 20% 15% 

(-12% - -12%) (0% - 0%) (13% - 13%) (20% - 20%) (14% - 15%) (29

 Tacoma, WA -23% 0% 0% 0% 15% 

(-23% - -23%) (0% - 0%) (0% - 0%) (0% - 0%) (14% - 15%) (29

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on location-specific single pollutant concentration-response function estimates from Zanobetti and Schwartz (2009) that have been "shrunken" towards t

regional means. "Shrunken" coefficient estimates and their standard errors were sent to EPA by A. Zanobetti via email.

Risk Assessment 

Location

Estimated Percent Reduction From the Current Standards to Several Alternative Standards in Non-Accidenta

Associated with Short-Term Exposure to PM2.5 Concentrations in a Recent Year and PM2.5 Concentrations tha

the Current and Alternative Annual (n) and Daily (m) Standards (Standard Combination Denoted n/m

E-107

September 2009 
Figure E-25. Estimated Percent Reductions From the Current Standard to Alternative 

Standards in Non-Accidental Mortality Associated with Short-Term Exposure to PM2.5: 

Based on 2005 Air Quality Data*

-90%

-80%

-70%

-60%

-50%

-40%

-30%

-20%

-10%

0%

10%

20%

30%

2005 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Reduction from Current Standard

 Atlanta, GA 175 (33 - 316); 1.2% (0.2% - 2.2%)

 Baltimore, MD 256 (104 - 406); 1.9% (0.8% - 3%)

 Birmingham, AL 38 (-60 - 135); 0.4% (-0.6% - 1.4%)

 Dallas, TX 151 (36 - 264); 1.2% (0.3% - 2.1%)

 Detroit, MI 141 (-25 - 305); 0.8% (-0.1% - 1.8%)

 Fresno, CA 44 (6 - 82); 0.8% (0.1% - 1.5%)

 Houston, TX 232 (47 - 414); 1.3% (0.3% - 2.3%)

 Los Angeles, CA 85 (-121 - 289); 0.2% (-0.2% - 0.5%)

 New York, NY 714 (419 - 1007); 1.4% (0.8% - 2%)

 Philadelphia, PA 211 (78 - 342); 1.5% (0.6% - 2.4%)

 Phoenix, AZ 240 (40 - 438); 1.1% (0.2% - 2%)

 Pittsburgh, PA 135 (40 - 230); 1% (0.3% - 1.7%)

 Salt Lake City, UT 33 (7 - 59); 0.7% (0.1% - 1.3%)

 St. Louis, MO 252 (73 - 429); 1.4% (0.4% - 2.4%)

 Tacoma, WA 48 (8 - 87); 1% (0.2% - 1.8%)

*Based on Krewski et al. (2009), exposure period from 1999 – 2000. The legend contains, for each urban area, the 

incidence estimate (and 95% CI) and the estimate of percent of total incidence (and 95% CI) under the current 

standards. 

**The current standards consist of an annual standard of 15 μg/m3

 and a daily standard of 35 μg/m3. Combinations of 

an annual standard (n) and a daily standard (m) are denoted n/m in this figure. 

E-108

September 2009 Draft - Do Not Quote or Cite
Figure E-26. Estimated Percent Reductions From the Current Standard to Alternative 

Standards in Non-Accidental Mortality Associated with Short-Term Exposure to PM2.5: 

Based on 2006 Air Quality Data* 

-90%

-80%

-70%

-60%

-50%

-40%

-30%

-20%

-10%

0%

10%

20%

30%

2006 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Reduction from Current Standard

 Atlanta, GA 172 (33 - 310); 1.2% (0.2% - 2.1%)

 Baltimore, MD 234 (95 - 372); 1.7% (0.7% - 2.7%)

 Birmingham, AL 38 (-59 - 132); 0.4% (-0.6% - 1.4%)

 Dallas, TX 129 (31 - 226); 1% (0.2% - 1.8%)

 Detroit, MI 117 (-21 - 254); 0.7% (-0.1% - 1.5%)

 Fresno, CA 46 (7 - 86); 0.8% (0.1% - 1.6%)

 Houston, TX 243 (50 - 434); 1.3% (0.3% - 2.3%)

 Los Angeles, CA 78 (-112 - 267); 0.1% (-0.2% - 0.5%)

 New York, NY 654 (384 - 922); 1.3% (0.7% - 1.8%)

 Philadelphia, PA 208 (77 - 337); 1.5% (0.5% - 2.4%)

 Phoenix, AZ 255 (42 - 466); 1.1% (0.2% - 2.1%)

 Pittsburgh, PA 122 (36 - 208); 0.9% (0.3% - 1.5%)

 Salt Lake City, UT 30 (6 - 54); 0.6% (0.1% - 1.1%)

 St. Louis, MO 214 (62 - 364); 1.2% (0.3% - 2%)

 Tacoma, WA 39 (7 - 71); 0.8% (0.1% - 1.4%)

*Based on Krewski et al. (2009), exposure period from 1999 – 2000. The legend contains, for each urban area, the 

incidence estimate (and 95% CI) and the estimate of percent of total incidence (and 95% CI) under the current 

standards. 

**The current standards consist of an annual standard of 15 μg/m3

 and a daily standard of 35 μg/m3. Combinations of 

an annual standard (n) and a daily standard (m) are denoted n/m in this figure. 

E-109

September 2009 Draft - Do Not Quote or Cite
Figure E-27. Estimated Percent Reductions From the Current Standard to Alternative 

Standards in Non-Accidental Mortality Associated with Short-Term Exposure to PM2.5: 

Based on 2007 Air Quality Data*

-90%

-80%

-70%

-60%

-50%

-40%

-30%

-20%

-10%

0%

10%

20%

30%

2007 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Reduction from Current Standard

 Atlanta, GA 177 (34 - 319); 1.2% (0.2% - 2.1%)

 Baltimore, MD 225 (91 - 357); 1.7% (0.7% - 2.6%)

 Birmingham, AL 37 (-58 - 131); 0.4% (-0.6% - 1.4%)

 Dallas, TX 137 (33 - 240); 1.1% (0.3% - 1.9%)

 Detroit, MI 112 (-20 - 242); 0.7% (-0.1% - 1.4%)

 Fresno, CA 51 (7 - 94); 0.9% (0.1% - 1.7%)

 Houston, TX 240 (49 - 429); 1.3% (0.3% - 2.3%)

 Los Angeles, CA 79 (-113 - 270); 0.1% (-0.2% - 0.5%)

 New York, NY 659 (387 - 930); 1.3% (0.7% - 1.8%)

 Philadelphia, PA 206 (76 - 334); 1.5% (0.5% - 2.4%)

 Phoenix, AZ 242 (40 - 441); 1% (0.2% - 1.9%)

 Pittsburgh, PA 123 (36 - 209); 0.9% (0.3% - 1.6%)

 Salt Lake City, UT 36 (7 - 65); 0.7% (0.2% - 1.3%)

 St. Louis, MO 222 (64 - 378); 1.2% (0.4% - 2.1%)

 Tacoma, WA 42 (7 - 76); 0.8% (0.1% - 1.5%)

*Based on Krewski et al. (2009), exposure period from 1999 – 2000. The legend contains, for each urban area, the 

incidence estimate (and 95% CI) and the estimate of percent of total incidence (and 95% CI) under the current 

standards. 

**The current standards consist of an annual standard of 15 μg/m3

 and a daily standard of 35 μg/m3. Combinations of 

an annual standard (n) and a daily standard (m) are denoted n/m in this figure. 

E-110

September 2009 Draft - Do Not Quote or Cite
Table E-82. Estimated Annual Incidence of Cardiovascular Mortality Associated with Short-Term Exposure to Ambient P

 Concentrations in a Recent Year (2005) and PM2.5 Concentrations that Just Meet the Current and Alternative Sta

 Based on Adjusting 2005 PM2.5 Concentrations1

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

34 32 27 25 27 

(-35 - 103) (-32 - 94) (-28 - 80) (-25 - 73) (-28 - 80) 

74 70 61 56 60 

(-5 - 151) (-5 - 142) (-4 - 125) (-4 - 115) (-4 - 122) 

-1 -1 -1 -1 -1 

(-61 - 58) (-48 - 45) (-41 - 38) (-37 - 35) (-41 - 38) 

31 31 31 29 31 

(-21 - 82) (-21 - 82) (-21 - 82) (-19 - 76) (-21 - 82) 

86 70 64 59 60 

(-11 - 180) (-9 - 147) (-8 - 135) (-7 - 124) (-7 - 126) 

21 11 11 11 10 

(-14 - 55) (-8 - 30) (-8 - 30) (-8 - 30) (-7 - 26) 

54 51 43 39 43 

(-36 - 142) (-34 - 134) (-29 - 114) (-27 - 104) (-29 - 114) 

-52 -33 -33 -31 -28 

(-231 - 126) (-146 - 79) (-146 - 79) (-137 - 75) (-124 - 68) 

552 460 448 412 394 

(323 - 779) (268 - 649) (261 - 633) (240 - 582) (229 - 556) (

92 85 80 73 73 

(24 - 159) (22 - 147) (21 - 137) (19 - 126) (19 - 126) 

83 83 83 79 78 

(-4 - 169) (-4 - 169) (-4 - 169) (-3 - 160) (-3 - 158) 

70 40 40 40 35 

(-14 - 151) (-8 - 88) (-8 - 88) (-8 - 88) (-7 - 75) 

149 9 9 7 

(-3 - 30) (-2 - 19) (-2 - 19) (-2 - 19) (-2 - 16) 

132 118 103 94 101 

(29 - 232) (26 - 208) (23 - 181) (21 - 167) (23 - 179) 

15 12 12 12 11 

(-8 - 38) (-7 - 31) (-7 - 31) (-7 - 31) (-6 - 27) 

Incidence of Cardiovascular Mortality Associated with Short-Term Exposure to PM2.5 Concentrations 

Year and PM2.5 Concentrations that Just Meet the Current and Alternative Annual (n) and Daily (m) S

(Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on location-specific single pollutant concentration-response function estimates from Zanobetti and Schwartz (2009) that have been "shrunken" toward

regional means. "Shrunken" coefficient estimates and their standard errors were sent to EPA by A. Zanobetti via email. Numbers are rounded to the neares

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

E-111

September 2009 
Table E-83. Estimated Annual Incidence of Cardiovascular Mortality Associated with Short-Term Exposure to Ambient P

 Concentrations in a Recent Year (2006) and PM2.5 Concentrations that Just Meet the Current and Alternative Sta

 Based on Adjusting 2006 PM2.5 Concentrations1 

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

34 31 26 24 26 

(-35 - 101) (-32 - 93) (-27 - 79) (-25 - 72) (-27 - 79) 

68 64 56 51 55 

(-5 - 138) (-4 - 130) (-4 - 114) (-3 - 105) (-4 - 112) 

-1 -1 -1 -1 -1 

(-60 - 56) (-47 - 44) (-40 - 38) (-36 - 34) (-40 - 38) 

27 27 27 25 27 

(-18 - 71) (-18 - 71) (-18 - 71) (-16 - 66) (-18 - 71) 

72 58 53 49 50 

(-9 - 151) (-7 - 122) (-7 - 112) (-6 - 103) (-6 - 105) 

22 12 12 12 10 

(-15 - 57) (-8 - 32) (-8 - 32) (-8 - 32) (-7 - 27) 

56 53 45 41 45 

(-38 - 149) (-36 - 140) (-31 - 119) (-28 - 109) (-31 - 119) 

-48 -30 -30 -28 -26 

(-214 - 116) (-134 - 73) (-134 - 73) (-127 - 69) (-115 - 63) 

506 421 410 377 360 

(295 - 713) (246 - 595) (239 - 580) (220 - 533) (210 - 509) (

91 84 78 72 72 

(24 - 157) (22 - 144) (20 - 135) (19 - 124) (19 - 124) 

88 88 88 84 83 

(-4 - 179) (-4 - 179) (-4 - 179) (-4 - 170) (-4 - 168) 

63 36 36 36 31 

(-13 - 136) (-7 - 80) (-7 - 80) (-7 - 80) (-6 - 68) 

138 8 8 7 

(-3 - 28) (-2 - 18) (-2 - 18) (-2 - 18) (-2 - 15) 

112 101 87 80 86 

(25 - 198) (22 - 177) (19 - 154) (18 - 142) (19 - 152) 

13 10 10 10 9 

(-7 - 31) (-5 - 26) (-5 - 26) (-5 - 26) (-5 - 22) 

Incidence of Cardiovascular Mortality Associated with Short-Term Exposure to PM2.5 Concentrations 

Year and PM2.5 Concentrations that Just Meet the Current and Alternative Annual (n) and Daily (m) S

(Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on location-specific single pollutant concentration-response function estimates from Zanobetti and Schwartz (2009) that have been "shrunken" toward

regional means. "Shrunken" coefficient estimates and their standard errors were sent to EPA by A. Zanobetti via email. Numbers are rounded to the neares

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

E-112

September 2009 
Table E-84. Estimated Annual Incidence of Cardiovascular Mortality Associated with Short-Term Exposure to Ambient P

 Concentrations in a Recent Year (2007) and PM2.5 Concentrations that Just Meet the Current and Alternative Sta

 Based on Adjusting 2007 PM2.5 Concentrations1 

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

35 32 27 25 27 

(-36 - 104) (-33 - 95) (-28 - 81) (-25 - 74) (-28 - 81) 

65 61 54 49 52 

(-4 - 132) (-4 - 125) (-4 - 110) (-3 - 101) (-4 - 107) 

-1 -1 -1 -1 -1 

(-59 - 56) (-46 - 44) (-39 - 37) (-36 - 34) (-39 - 37) 

29 29 29 26 29 

(-19 - 75) (-19 - 75) (-19 - 75) (-17 - 70) (-19 - 75) 

68 55 51 47 47 

(-9 - 143) (-7 - 117) (-6 - 107) (-6 - 98) (-6 - 100) 

24 13 13 13 11 

(-17 - 62) (-9 - 35) (-9 - 35) (-9 - 35) (-8 - 30) 

56 52 45 41 45 

(-38 - 147) (-36 - 139) (-30 - 118) (-28 - 108) (-30 - 118) 

-48 -30 -30 -29 -26 

(-216 - 117) (-136 - 74) (-136 - 74) (-128 - 70) (-116 - 63) 

510 425 414 381 364 

(298 - 720) (248 - 600) (241 - 585) (222 - 538) (212 - 514) (

90 83 78 71 71 

(23 - 155) (22 - 143) (20 - 134) (18 - 123) (18 - 123) 

84 84 84 80 78 

(-4 - 170) (-4 - 170) (-4 - 170) (-3 - 161) (-3 - 159) 

63 37 37 37 31 

(-13 - 137) (-7 - 80) (-7 - 80) (-7 - 80) (-6 - 69) 

15 10 10 10 8 

(-4 - 33) (-2 - 21) (-2 - 21) (-2 - 21) (-2 - 18) 

116 104 91 83 89 

(26 - 205) (23 - 184) (20 - 160) (18 - 147) (20 - 157) 

14 11 11 11 9 

(-7 - 34) (-6 - 27) (-6 - 27) (-6 - 27) (-5 - 23) 

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on location-specific single pollutant concentration-response function estimates from Zanobetti and Schwartz (2009) that have been "shrunken" toward

regional means. "Shrunken" coefficient estimates and their standard errors were sent to EPA by A. Zanobetti via email. Numbers are rounded to the neares

 Dallas, TX Fresno, CA Los Angeles, CA

Incidence of Cardiovascular Mortality Associated with Short-Term Exposure to PM2.5 Concentrations 

Year and PM2.5 Concentrations that Just Meet the Current and Alternative Annual (n) and Daily (m) S

(Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

E-113

September 2009 
Table E-85. Estimated Percent of Total Annual Incidence of Cardiovascular Mortality Associated with Short-Term Exposu

 PM2.5 Concentrations in a Recent Year (2005) and PM2.5 Concentrations that Just Meet the Current and Alternativ

 Based on Adjusting 2005 PM2.5 Concentrations1

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

0.9% 0.9% 0.7% 0.7% 0.7% 

(-1% - 2.8%) (-0.9% - 2.5%) (-0.7% - 2.2%) (-0.7% - 2%) (-0.7% - 2.2%) (-

1.9% 1.8% 1.6% 1.4% 1.5% 

(-0.1% - 3.9%) (-0.1% - 3.7%) (-0.1% - 3.2%) (-0.1% - 2.9%) (-0.1% - 3.1%) (-

0% 0% 0% 0% 0% 

(-2.3% - 2.1%) (-1.8% - 1.7%) (-1.5% - 1.4%) (-1.4% - 1.3%) (-1.5% - 1.4%) (-

0.9% 0.9% 0.9% 0.9% 0.9% 

(-0.6% - 2.4%) (-0.6% - 2.4%) (-0.6% - 2.4%) (-0.6% - 2.2%) (-0.6% - 2.4%) (-

1.4% 1.2% 1.1% 1% 1% 

(-0.2% - 3%) (-0.1% - 2.4%) (-0.1% - 2.2%) (-0.1% - 2.1%) (-0.1% - 2.1%) (-

1.3% 0.7% 0.7% 0.7% 0.6% 

(-0.9% - 3.3%) (-0.5% - 1.8%) (-0.5% - 1.8%) (-0.5% - 1.8%) (-0.4% - 1.6%) (-

1.1% 1% 0.9% 0.8% 0.9% 

(-0.7% - 2.9%) (-0.7% - 2.7%) (-0.6% - 2.3%) (-0.5% - 2.1%) (-0.6% - 2.3%) (-

-0.3% -0.2% -0.2% -0.2% -0.1% 

(-1.2% - 0.7%) (-0.8% - 0.4%) (-0.8% - 0.4%) (-0.7% - 0.4%) (-0.7% - 0.4%) (-

2.5% 2% 2% 1.8% 1.8% 

(1.4% - 3.5%) (1.2% - 2.9%) (1.2% - 2.8%) (1.1% - 2.6%) (1% - 2.5%) (

2.3% 2.1% 2% 1.8% 1.8% 

(0.6% - 4%) (0.5% - 3.6%) (0.5% - 3.4%) (0.5% - 3.1%) (0.5% - 3.1%) (

1.4% 1.4% 1.4% 1.3% 1.3% 

(-0.1% - 2.9%) (-0.1% - 2.9%) (-0.1% - 2.9%) (-0.1% - 2.7%) (-0.1% - 2.7%) 

1.7% 1% 1% 1% 0.8% 

(-0.3% - 3.7%) (-0.2% - 2.2%) (-0.2% - 2.2%) (-0.2% - 2.2%) (-0.2% - 1.8%) (-

1.3% 0.8% 0.8% 0.8% 0.7% 

(-0.3% - 2.8%) (-0.2% - 1.8%) (-0.2% - 1.8%) (-0.2% - 1.8%) (-0.2% - 1.5%) (-

2.3% 2.1% 1.8% 1.7% 1.8% 

(0.5% - 4.1%) (0.5% - 3.7%) (0.4% - 3.2%) (0.4% - 2.9%) (0.4% - 3.1%) (

1.1% 0.9% 0.9% 0.9% 0.7% 

(-0.6% - 2.7%) (-0.5% - 2.2%) (-0.5% - 2.2%) (-0.5% - 2.2%) (-0.4% - 1.8%) (-

Percent of Total Incidence of Cardiovascular Mortality Associated with Short-Term Exposure t

Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the Current and Alternative 

Daily (m) Standards (Standard Combination Denoted n/m):

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on location-specific single pollutant concentration-response function estimates from Zanobetti and Schwartz (2009) that have been "shrunken" towards 

regional means. "Shrunken" coefficient estimates and their standard errors were sent to EPA by A. Zanobetti via email. Percents are rounded to the nearest t

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL Baltimore, MD Detroit, MI Houston, TX New York, NY St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT

E-114

September 2009 
Table E-86. Estimated Percent of Total Annual Incidence of Cardiovascular Mortality Associated with Short-Term Exposu

 PM2.5 Concentrations in a Recent Year (2006) and PM2.5 Concentrations that Just Meet the Current and Alternativ

 Based on Adjusting 2006 PM2.5 Concentrations1 

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

0.9% 0.8% 0.7% 0.6% 0.7% 

(-0.9% - 2.6%) (-0.8% - 2.4%) (-0.7% - 2.1%) (-0.6% - 1.9%) (-0.7% - 2.1%) (

1.7% 1.6% 1.4% 1.3% 1.4% 

(-0.1% - 3.5%) (-0.1% - 3.3%) (-0.1% - 2.9%) (-0.1% - 2.7%) (-0.1% - 2.9%) (

0% 0% 0% 0% 0% 

(-2.2% - 2.1%) (-1.7% - 1.6%) (-1.5% - 1.4%) (-1.3% - 1.3%) (-1.5% - 1.4%) (

0.8% 0.8% 0.8% 0.7% 0.8% 

(-0.5% - 2%) (-0.5% - 2%) (-0.5% - 2%) (-0.5% - 1.9%) (-0.5% - 2%) (

1.2% 1% 0.9% 0.8% 0.8% 

(-0.2% - 2.5%) (-0.1% - 2.1%) (-0.1% - 1.9%) (-0.1% - 1.7%) (-0.1% - 1.8%) (

1.3% 0.7% 0.7% 0.7% 0.6% 

(-0.9% - 3.4%) (-0.5% - 1.9%) (-0.5% - 1.9%) (-0.5% - 1.9%) (-0.4% - 1.6%) (

1.1% 1.1% 0.9% 0.8% 0.9% 

(-0.8% - 2.9%) (-0.7% - 2.8%) (-0.6% - 2.4%) (-0.6% - 2.2%) (-0.6% - 2.4%) (

-0.3% -0.2% -0.2% -0.2% -0.1% 

(-1.1% - 0.6%) (-0.7% - 0.4%) (-0.7% - 0.4%) (-0.7% - 0.4%) (-0.6% - 0.3%) (

2.2% 1.9% 1.8% 1.7% 1.6% 

(1.3% - 3.2%) (1.1% - 2.6%) (1.1% - 2.6%) (1% - 2.4%) (0.9% - 2.3%) (

2.3% 2.1% 2% 1.8% 1.8% 

(0.6% - 3.9%) (0.5% - 3.6%) (0.5% - 3.4%) (0.5% - 3.1%) (0.5% - 3.1%) (

1.5% 1.5% 1.5% 1.4% 1.4% 

(-0.1% - 2.9%) (-0.1% - 2.9%) (-0.1% - 2.9%) (-0.1% - 2.8%) (-0.1% - 2.8%) 

1.6% 0.9% 0.9% 0.9% 0.8% 

(-0.3% - 3.4%) (-0.2% - 2%) (-0.2% - 2%) (-0.2% - 2%) (-0.2% - 1.7%) (

1.1% 0.7% 0.7% 0.7% 0.6% 

(-0.3% - 2.5%) (-0.2% - 1.6%) (-0.2% - 1.6%) (-0.2% - 1.6%) (-0.1% - 1.3%) (

2% 1.8% 1.5% 1.4% 1.5% 

(0.4% - 3.5%) (0.4% - 3.1%) (0.3% - 2.7%) (0.3% - 2.5%) (0.3% - 2.7%) (

0.9% 0.7% 0.7% 0.7% 0.6% 

(-0.5% - 2.1%) (-0.4% - 1.7%) (-0.4% - 1.7%) (-0.4% - 1.7%) (-0.3% - 1.5%) (

Percent of Total Incidence of Cardiovascular Mortality Associated with Short-Term Exposure t

Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the Current and Alternative 

Daily (m) Standards (Standard Combination Denoted n/m):

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on location-specific single pollutant concentration-response function estimates from Zanobetti and Schwartz (2009) that have been "shrunken" towards 

regional means. "Shrunken" coefficient estimates and their standard errors were sent to EPA by A. Zanobetti via email. Percents are rounded to the nearest t

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL Baltimore, MD Detroit, MI Houston, TX New York, NY St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT

E-115

September 2009 
Table E-87. Estimated Percent of Total Annual Incidence of Cardiovascular Mortality Associated with Short-Term Exposu

 PM2.5 Concentrations in a Recent Year (2007) and PM2.5 Concentrations that Just Meet the Current and Alternativ

 Based on Adjusting 2007 PM2.5 Concentrations1 

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

0.9% 0.8% 0.7% 0.6% 0.7% 

(-0.9% - 2.7%) (-0.8% - 2.4%) (-0.7% - 2.1%) (-0.6% - 1.9%) (-0.7% - 2.1%) (

1.7% 1.6% 1.4% 1.3% 1.3% 

(-0.1% - 3.4%) (-0.1% - 3.2%) (-0.1% - 2.8%) (-0.1% - 2.6%) (-0.1% - 2.8%) (

0% 0% 0% 0% 0% 

(-2.2% - 2%) (-1.7% - 1.6%) (-1.4% - 1.4%) (-1.3% - 1.2%) (-1.4% - 1.4%) (

0.8% 0.8% 0.8% 0.8% 0.8% 

(-0.5% - 2.1%) (-0.5% - 2.1%) (-0.5% - 2.1%) (-0.5% - 2%) (-0.5% - 2.1%) 

1.2% 0.9% 0.9% 0.8% 0.8% 

(-0.1% - 2.4%) (-0.1% - 2%) (-0.1% - 1.8%) (-0.1% - 1.7%) (-0.1% - 1.7%) (

1.4% 0.8% 0.8% 0.8% 0.7% 

(-1% - 3.7%) (-0.5% - 2.1%) (-0.5% - 2.1%) (-0.5% - 2.1%) (-0.5% - 1.8%) (

1.1% 1% 0.9% 0.8% 0.9% 

(-0.7% - 2.9%) (-0.7% - 2.7%) (-0.6% - 2.3%) (-0.5% - 2.1%) (-0.6% - 2.3%) (

-0.3% -0.2% -0.2% -0.2% -0.1% 

(-1.1% - 0.6%) (-0.7% - 0.4%) (-0.7% - 0.4%) (-0.7% - 0.4%) (-0.6% - 0.3%) (

2.3% 1.9% 1.8% 1.7% 1.6% 

(1.3% - 3.2%) (1.1% - 2.7%) (1.1% - 2.6%) (1% - 2.4%) (0.9% - 2.3%) (

2.3% 2.1% 1.9% 1.8% 1.8% 

(0.6% - 3.9%) (0.5% - 3.6%) (0.5% - 3.4%) (0.5% - 3.1%) (0.5% - 3.1%) (

1.3% 1.3% 1.3% 1.3% 1.3% 

(-0.1% - 2.7%) (-0.1% - 2.7%) (-0.1% - 2.7%) (-0.1% - 2.6%) (-0.1% - 2.5%) 

1.6% 0.9% 0.9% 0.9% 0.8% 

(-0.3% - 3.4%) (-0.2% - 2%) (-0.2% - 2%) (-0.2% - 2%) (-0.2% - 1.7%) (

1.3% 0.8% 0.8% 0.8% 0.7% 

(-0.3% - 2.9%) (-0.2% - 1.8%) (-0.2% - 1.8%) (-0.2% - 1.8%) (-0.2% - 1.6%) (

2% 1.8% 1.6% 1.5% 1.6% 

(0.5% - 3.6%) (0.4% - 3.2%) (0.4% - 2.8%) (0.3% - 2.6%) (0.3% - 2.8%) (

0.9% 0.7% 0.7% 0.7% 0.6% 

(-0.5% - 2.3%) (-0.4% - 1.8%) (-0.4% - 1.8%) (-0.4% - 1.8%) (-0.3% - 1.6%) (

 Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Detroit, MI Houston, TX New York, NY St. Louis, MO

Percent of Total Incidence of Cardiovascular Mortality Associated with Short-Term Exposure t

Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the Current and Alternative 

Daily (m) Standards (Standard Combination Denoted n/m):

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on location-specific single pollutant concentration-response function estimates from Zanobetti and Schwartz (2009) that have been "shrunken" towards 

regional means. "Shrunken" coefficient estimates and their standard errors were sent to EPA by A. Zanobetti via email. Percents are rounded to the nearest t

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL Baltimore, MD

E-116

September 2009 
Table E-88. Percent Reduction from the Current Standards: Estimated Annual Incidence of Cardiovascular Mortality 

 Short-Term Exposure to Ambient PM2.5 Concentrations, Based on Adjusting 2005 PM2.5 Concentrations1

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

-9% 0% 15% 22% 15% 

(-9% - -9%) (0% - 0%) (15% - 15%) (22% - 23%) (15% - 15%) 

-6% 0% 13% 20% 14% 

(-6% - -6%) (0% - 0%) (12% - 13%) (19% - 20%) (14% - 15%) 

-28% 0% 15% 23% 15% 

(-27% - -28%) (0% - 0%) (15% - 15%) (22% - 23%) (15% - 15%) 

0% 0% 0% 7% 0% 

(0% - 0%) (0% - 0%) (0% - 0%) (7% - 7%) (0% - 0%) 

-23% 0% 8% 16% 15% 

(-23% - -23%) (0% - 0%) (8% - 8%) (16% - 16%) (14% - 15%) 

-81% 0% 0% 0% 15% 

(-79% - -83%) (0% - 0%) (0% - 0%) (0% - 0%) (14% - 15%) 

-6% 0% 15% 22% 15% 

(-6% - -6%) (0% - 0%) (15% - 15%) (22% - 23%) (15% - 15%) 

-59% 0% 0% 6% 15% 

(-58% - -59%) (0% - 0%) (0% - 0%) (6% - 6%) (15% - 15%) 

-20% 0% 3% 10% 14% 

(-20% - -20%) (0% - 0%) (3% - 3%) (10% - 10%) (14% - 14%) 

-9% 0% 6% 14% 14% 

(-9% - -9%) (0% - 0%) (6% - 6%) (14% - 14%) (14% - 15%) 

0% 0% 0% 5% 6% 

(0% - 0%) (0% - 0%) (0% - 0%) (5% - 5%) (6% - 6%) 

-72% 0% 0% 0% 15% 

(-71% - -73%) (0% - 0%) (0% - 0%) (0% - 0%) (14% - 15%) 

-58% 0% 0% 0% 15% 

(-57% - -59%) (0% - 0%) (0% - 0%) (0% - 0%) (15% - 15%) 

-12% 0% 13% 20% 14% 

(-11% - -12%) (0% - 0%) (13% - 13%) (20% - 20%) (14% - 15%) 

-23% 0% 0% 0% 15% 

(-23% - -24%) (0% - 0%) (0% - 0%) (0% - 0%) (14% - 15%) 

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on location-specific single pollutant concentration-response function estimates from Zanobetti and Schwartz (2009) that have been "shrunken" tow

regional means. "Shrunken" coefficient estimates and their standard errors were sent to EPA by A. Zanobetti via email. Percents are rounded to whole n

 Dallas, TX Fresno, CA Los Angeles, CA

Percent Reduction from the Current Standards: Annual Incidence of Cardiovascular Mortality Associate

Exposure to PM2.5 Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the Curren

Annual (n) and Daily (m) Standards (Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

E-117

September 2009 
Table E-89. Percent Reduction from the Current Standards: Estimated Annual Incidence of Cardiovascular Mortality 

 Short-Term Exposure to Ambient PM2.5 Concentrations, Based on Adjusting 2006 PM2.5 Concentrations1 

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

-9% 0% 15% 23% 15% 

(-9% - -9%) (0% - 0%) (15% - 15%) (22% - 23%) (15% - 15%) 

-6% 0% 13% 20% 14% 

(-6% - -6%) (0% - 0%) (12% - 13%) (19% - 20%) (14% - 15%) 

-28% 0% 15% 23% 15% 

(-27% - -28%) (0% - 0%) (15% - 15%) (22% - 23%) (15% - 15%) 

0% 0% 0% 7% 0% 

(0% - 0%) (0% - 0%) (0% - 0%) (7% - 7%) (0% - 0%) 

-23% 0% 8% 16% 15% 

(-23% - -23%) (0% - 0%) (8% - 8%) (16% - 16%) (14% - 15%) 

-81% 0% 0% 0% 15% 

(-80% - -83%) (0% - 0%) (0% - 0%) (0% - 0%) (14% - 15%) 

-6% 0% 15% 22% 15% 

(-6% - -6%) (0% - 0%) (15% - 15%) (22% - 23%) (15% - 15%) 

-59% 0% 0% 6% 15% 

(-58% - -59%) (0% - 0%) (0% - 0%) (6% - 6%) (15% - 15%) 

-20% 0% 3% 10% 14% 

(-20% - -20%) (0% - 0%) (3% - 3%) (10% - 10%) (14% - 14%) 

-9% 0% 6% 14% 14% 

(-9% - -9%) (0% - 0%) (6% - 6%) (14% - 14%) (14% - 15%) 

0% 0% 0% 5% 6% 

(0% - 0%) (0% - 0%) (0% - 0%) (5% - 5%) (6% - 6%) 

-72% 0% 0% 0% 15% 

(-71% - -73%) (0% - 0%) (0% - 0%) (0% - 0%) (14% - 15%) 

-58% 0% 0% 0% 15% 

(-58% - -59%) (0% - 0%) (0% - 0%) (0% - 0%) (15% - 15%) 

-12% 0% 13% 20% 15% 

(-11% - -12%) (0% - 0%) (13% - 13%) (20% - 20%) (14% - 15%) 

-23% 0% 0% 0% 15% 

(-23% - -24%) (0% - 0%) (0% - 0%) (0% - 0%) (14% - 15%) 

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on location-specific single pollutant concentration-response function estimates from Zanobetti and Schwartz (2009) that have been "shrunken" tow

regional means. "Shrunken" coefficient estimates and their standard errors were sent to EPA by A. Zanobetti via email. Percents are rounded to whole n

 Dallas, TX Fresno, CA Los Angeles, CA

Percent Reduction from the Current Standards: Annual Incidence of Cardiovascular Mortality Associated 

Exposure to PM2.5 Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the Curren

Annual (n) and Daily (m) Standards (Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

E-118

September 2009 
Table E-90. Percent Reduction from the Current Standards: Estimated Annual Incidence of Cardiovascular Mortality 

 Short-Term Exposure to Ambient PM2.5 Concentrations, Based on Adjusting 2007 PM2.5 Concentrations1

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

-9% 0% 15% 22% 15% 

(-9% - -9%) (0% - 0%) (15% - 15%) (22% - 23%) (15% - 15%) 

-6% 0% 13% 20% 14% 

(-6% - -6%) (0% - 0%) (12% - 13%) (19% - 20%) (14% - 15%) 

-28% 0% 15% 23% 15% 

(-27% - -28%) (0% - 0%) (15% - 15%) (22% - 23%) (15% - 15%) 

0% 0% 0% 7% 0% 

(0% - 0%) (0% - 0%) (0% - 0%) (7% - 7%) (0% - 0%) 

-23% 0% 8% 16% 15% 

(-23% - -23%) (0% - 0%) (8% - 8%) (16% - 16%) (14% - 15%) 

-81% 0% 0% 0% 15% 

(-79% - -83%) (0% - 0%) (0% - 0%) (0% - 0%) (14% - 15%) 

-6% 0% 15% 22% 15% 

(-6% - -6%) (0% - 0%) (15% - 15%) (22% - 23%) (15% - 15%) 

-59% 0% 0% 6% 15% 

(-58% - -59%) (0% - 0%) (0% - 0%) (6% - 6%) (15% - 15%) 

-20% 0% 3% 10% 14% 

(-20% - -20%) (0% - 0%) (3% - 3%) (10% - 10%) (14% - 14%) 

-9% 0% 6% 14% 14% 

(-9% - -9%) (0% - 0%) (6% - 6%) (14% - 14%) (14% - 15%) 

0% 0% 0% 5% 6% 

(0% - 0%) (0% - 0%) (0% - 0%) (5% - 5%) (6% - 6%) 

-72% 0% 0% 0% 15% 

(-71% - -73%) (0% - 0%) (0% - 0%) (0% - 0%) (14% - 15%) 

-58% 0% 0% 0% 15% 

(-57% - -59%) (0% - 0%) (0% - 0%) (0% - 0%) (14% - 15%) 

-12% 0% 13% 20% 14% 

(-11% - -12%) (0% - 0%) (13% - 13%) (20% - 20%) (14% - 15%) 

-23% 0% 0% 0% 15% 

(-23% - -24%) (0% - 0%) (0% - 0%) (0% - 0%) (14% - 15%) 

Percent Reduction from the Current Standards: Annual Incidence of Cardiovascular Mortality Associated 

Exposure to PM2.5 Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the Curren

Annual (n) and Daily (m) Standards (Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on location-specific single pollutant concentration-response function estimates from Zanobetti and Schwartz (2009) that have been "shrunken" tow

regional means. "Shrunken" coefficient estimates and their standard errors were sent to EPA by A. Zanobetti via email. Percents are rounded to whole n

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

E-119

September 2009 
Figure E-28. Estimated Percent Reductions From the Current Standard to Alternative 

Standards in Cardiovascular Mortality Associated with Short-Term Exposure to PM2.5: 

Based on 2005 Air Quality Data* 

-90%

-80%

-70%

-60%

-50%

-40%

-30%

-20%

-10%

0%

10%

20%

30%

2005 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Reduction from Current Standard

 Atlanta, GA 32 (-32 - 94); 0.9% (-0.9% - 2.5%)

 Baltimore, MD 70 (-5 - 142); 1.8% (-0.1% - 3.7%)

 Birmingham, AL -1 (-48 - 45); 0% (-1.8% - 1.7%)

 Dallas, TX 31 (-21 - 82); 0.9% (-0.6% - 2.4%)

 Detroit, MI 70 (-9 - 147); 1.2% (-0.1% - 2.4%)

 Fresno, CA 11 (-8 - 30); 0.7% (-0.5% - 1.8%)

 Houston, TX 51 (-34 - 134); 1% (-0.7% - 2.7%)

 Los Angeles, CA -33 (-146 - 79); -0.2% (-0.8% - 0.4%)

 New York, NY 460 (268 - 649); 2% (1.2% - 2.9%)

 Philadelphia, PA 85 (22 - 147); 2.1% (0.5% - 3.6%)

 Phoenix, AZ 83 (-4 - 169); 1.4% (-0.1% - 2.9%)

 Pittsburgh, PA 40 (-8 - 88); 1% (-0.2% - 2.2%)

 Salt Lake City, UT 9 (-2 - 19); 0.8% (-0.2% - 1.8%)

 St. Louis, MO 118 (26 - 208); 2.1% (0.5% - 3.7%)

 Tacoma, WA 12 (-7 - 31); 0.9% (-0.5% - 2.2%)

*Based on Zanobetti and Schwartz (2009). The legend contains, for each urban area, the incidence estimate (and 95% 

CI) and the estimate of percent of total incidence (and 95% CI) under the current standards. 

**The current standards consist of an annual standard of 15 μg/m3

 and a daily standard of 35 μg/m3. Combinations of 

an annual standard (n) and a daily standard (m) are denoted n/m in this figure. 

E-120

September 2009 Draft - Do Not Quote or Cite
Figure E-29. Estimated Percent Reductions From the Current Standard to Alternative 

Standards in Cardiovascular Mortality Associated with Short-Term Exposure to PM2.5: 

Based on 2006 Air Quality Data*

-90%

-80%

-70%

-60%

-50%

-40%

-30%

-20%

-10%

0%

10%

20%

30%

2006 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Reduction from Current Standard

 Atlanta, GA 31 (-32 - 93); 0.8% (-0.8% - 2.4%)

 Baltimore, MD 64 (-4 - 130); 1.6% (-0.1% - 3.3%)

 Birmingham, AL -1 (-47 - 44); 0% (-1.7% - 1.6%)

 Dallas, TX 27 (-18 - 71); 0.8% (-0.5% - 2%)

 Detroit, MI 58 (-7 - 122); 1% (-0.1% - 2.1%)

 Fresno, CA 12 (-8 - 32); 0.7% (-0.5% - 1.9%)

 Houston, TX 53 (-36 - 140); 1.1% (-0.7% - 2.8%)

 Los Angeles, CA -30 (-134 - 73); -0.2% (-0.7% - 0.4%)

 New York, NY 421 (246 - 595); 1.9% (1.1% - 2.6%)

 Philadelphia, PA 84 (22 - 144); 2.1% (0.5% - 3.6%)

 Phoenix, AZ 88 (-4 - 179); 1.5% (-0.1% - 2.9%)

 Pittsburgh, PA 36 (-7 - 80); 0.9% (-0.2% - 2%)

 Salt Lake City, UT 8 (-2 - 18); 0.7% (-0.2% - 1.6%)

 St. Louis, MO 101 (22 - 177); 1.8% (0.4% - 3.1%)

 Tacoma, WA 10 (-5 - 26); 0.7% (-0.4% - 1.7%)

`

*Based on Zanobetti and Schwartz (2009). The legend contains, for each urban area, the incidence estimate (and 95% 

CI) and the estimate of percent of total incidence (and 95% CI) under the current standards. 

**The current standards consist of an annual standard of 15 μg/m3

 and a daily standard of 35 μg/m3. Combinations of 

an annual standard (n) and a daily standard (m) are denoted n/m in this figure. 

E-121

September 2009 Draft - Do Not Quote or Cite
Figure E-30. Estimated Percent Reductions From the Current Standard to Alternative 

Standards in Cardiovascular Mortality Associated with Short-Term Exposure to PM2.5: 

Based on 2007 Air Quality Data*

-90%

-80%

-70%

-60%

-50%

-40%

-30%

-20%

-10%

0%

10%

20%

30%

2007 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Reduction from Current Standard

 Atlanta, GA 32 (-33 - 95); 0.8% (-0.8% - 2.4%)

 Baltimore, MD 61 (-4 - 125); 1.6% (-0.1% - 3.2%)

 Birmingham, AL -1 (-46 - 44); 0% (-1.7% - 1.6%)

 Dallas, TX 29 (-19 - 75); 0.8% (-0.5% - 2.1%)

 Detroit, MI 55 (-7 - 117); 0.9% (-0.1% - 2%)

 Fresno, CA 13 (-9 - 35); 0.8% (-0.5% - 2.1%)

 Houston, TX 52 (-36 - 139); 1% (-0.7% - 2.7%)

 Los Angeles, CA -30 (-136 - 74); -0.2% (-0.7% - 0.4%)

 New York, NY 425 (248 - 600); 1.9% (1.1% - 2.7%)

 Philadelphia, PA 83 (22 - 143); 2.1% (0.5% - 3.6%)

 Phoenix, AZ 84 (-4 - 170); 1.3% (-0.1% - 2.7%)

 Pittsburgh, PA 37 (-7 - 80); 0.9% (-0.2% - 2%)

 Salt Lake City, UT 10 (-2 - 21); 0.8% (-0.2% - 1.8%)

 St. Louis, MO 104 (23 - 184); 1.8% (0.4% - 3.2%)

 Tacoma, WA 11 (-6 - 27); 0.7% (-0.4% - 1.8%)

*Based on Zanobetti and Schwartz (2009). The legend contains, for each urban area, the incidence estimate (and 95% 

CI) and the estimate of percent of total incidence (and 95% CI) under the current standards. 

**The current standards consist of an annual standard of 15 μg/m3

 and a daily standard of 35 μg/m3. Combinations of 

an annual standard (n) and a daily standard (m) are denoted n/m in this figure. 

E-122

September 2009 Draft - Do Not Quote or Cite
Table E-91. Estimated Annual Incidence of Respiratory Mortality Associated with Short-Term Exposure to Ambient PM2.5 

 Concentrations in a Recent Year (2005) and PM2.5 Concentrations that Just Meet the Current and Alternative Stan

 Based on Adjusting 2005 PM2.5 Concentrations1

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

21 19 17 15 17 

(-9 - 50) (-8 - 46) (-7 - 39) (-6 - 36) (-7 - 39) (

38 35 31 29 30 

(7 - 67) (7 - 63) (6 - 56) (5 - 51) (6 - 54) 

13 10 9 8 9 

(-11 - 36) (-8 - 29) (-7 - 24) (-6 - 22) (-7 - 24) (

11 11 11 10 11 

(-10 - 31) (-10 - 31) (-10 - 31) (-9 - 29) (-10 - 31) (

34 27 25 23 23 

(2 - 64) (1 - 52) (1 - 48) (1 - 44) (1 - 45) 

169 9 9 7 

(1 - 30) (0 - 17) (0 - 17) (0 - 17) (0 - 14) 

38 36 31 28 31 

(6 - 70) (6 - 66) (5 - 56) (5 - 51) (5 - 56) 

94 59 59 56 51 

(9 - 177) (6 - 112) (6 - 112) (5 - 106) (5 - 96) 

117 97 95 87 83 

(41 - 190) (34 - 159) (33 - 155) (31 - 142) (29 - 136) (2

24 23 21 19 19 

(-2 - 50) (-2 - 46) (-2 - 44) (-2 - 40) (-2 - 40) (

47 47 47 45 44 

(4 - 89) (4 - 89) (4 - 89) (4 - 85) (3 - 84) 

29 17 17 17 15 

(-3 - 60) (-2 - 35) (-2 - 35) (-2 - 35) (-1 - 30) (

96665

(1 - 17) (1 - 11) (1 - 11) (1 - 11) (1 - 9) 

34 30 26 24 26 

(-9 - 75) (-8 - 67) (-7 - 59) (-6 - 54) (-7 - 58) (

97776

(0 - 18) (0 - 15) (0 - 15) (0 - 15) (0 - 13) 

 Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Detroit, MI Houston, TX New York, NY St. Louis, MO

Incidence of Respiratory Mortality Associated with Short-Term Exposure to PM2.5 Concentrations in a R

and PM2.5 Concentrations that Just Meet the Current and Alternative Annual (n) and Daily (m) Standard

Combination Denoted n/m):

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on location-specific single pollutant concentration-response function estimates from Zanobetti and Schwartz (2009) that have been "shrunken" towards 

regional means. "Shrunken" coefficient estimates and their standard errors were sent to EPA by A. Zanobetti via email. Numbers are rounded to the nearest w

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL Baltimore, MD

E-123

September 2009 
Table E-92. Estimated Annual Incidence of Respiratory Mortality Associated with Short-Term Exposure to Ambient PM2.5 

 Concentrations in a Recent Year (2006) and PM2.5 Concentrations that Just Meet the Current and Alternative Stan

 Based on Adjusting 2006 PM2.5 Concentrations1 

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

21 19 16 15 16 

(-8 - 49) (-8 - 45) (-7 - 39) (-6 - 35) (-7 - 39) (

34 32 28 26 28 

(6 - 61) (6 - 58) (5 - 51) (5 - 47) (5 - 50) 

13 10 9 8 9 

(-11 - 36) (-8 - 28) (-7 - 24) (-6 - 22) (-7 - 24) (

99999

(-9 - 27) (-9 - 27) (-9 - 27) (-8 - 25) (-9 - 27) (

28 23 21 19 19 

(1 - 54) (1 - 44) (1 - 40) (1 - 37) (1 - 38) 

169 9 9 8 

(1 - 32) (0 - 18) (0 - 18) (0 - 18) (0 - 15) 

40 38 32 30 32 

(6 - 73) (6 - 69) (5 - 59) (5 - 54) (5 - 59) 

87 55 55 52 47 

(8 - 164) (5 - 104) (5 - 104) (5 - 98) (5 - 89) 

107 89 87 80 76 

(38 - 174) (31 - 145) (31 - 142) (28 - 130) (27 - 125) (2

24 22 21 19 19 

(-2 - 50) (-2 - 46) (-2 - 43) (-2 - 39) (-2 - 39) (

50 50 50 47 47 

(4 - 95) (4 - 95) (4 - 95) (4 - 90) (4 - 89) 

27 15 15 15 13 

(-3 - 55) (-2 - 32) (-2 - 32) (-2 - 32) (-1 - 27) (

85554

(1 - 15) (1 - 10) (1 - 10) (1 - 10) (1 - 8) 

29 26 22 20 22 

(-8 - 64) (-7 - 57) (-6 - 50) (-5 - 46) (-6 - 49) (

76665

(0 - 15) (0 - 12) (0 - 12) (0 - 12) (0 - 10) 

 Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Detroit, MI Houston, TX New York, NY St. Louis, MO

Incidence of Respiratory Mortality Associated with Short-Term Exposure to PM2.5 Concentrations in a R

and PM2.5 Concentrations that Just Meet the Current and Alternative Annual (n) and Daily (m) Standard

Combination Denoted n/m):

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on location-specific single pollutant concentration-response function estimates from Zanobetti and Schwartz (2009) that have been "shrunken" towards 

regional means. "Shrunken" coefficient estimates and their standard errors were sent to EPA by A. Zanobetti via email. Numbers are rounded to the nearest w

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL Baltimore, MD

E-124

September 2009 
Table E-93. Estimated Annual Incidence of Respiratory Mortality Associated with Short-Term Exposure to Ambient PM2.5 

 Concentrations in a Recent Year (2007) and PM2.5 Concentrations that Just Meet the Current and Alternative Stan

 Based on Adjusting 2007 PM2.5 Concentrations1 

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

21 20 17 15 17 

(-9 - 51) (-8 - 47) (-7 - 40) (-6 - 36) (-7 - 40) (

33 31 27 25 27 

(6 - 59) (6 - 56) (5 - 49) (5 - 45) (5 - 48) 

13 10 9 8 9 

(-10 - 35) (-8 - 28) (-7 - 24) (-6 - 22) (-7 - 24) (

10 10 10 9 10 

(-9 - 29) (-9 - 29) (-9 - 29) (-8 - 27) (-9 - 29) (

27 22 20 18 19 

(1 - 51) (1 - 42) (1 - 38) (1 - 35) (1 - 36) 

18 10 10 10 8 

(1 - 34) (0 - 19) (0 - 19) (0 - 19) (0 - 16) 

40 38 32 29 32 

(6 - 72) (6 - 68) (5 - 58) (5 - 53) (5 - 58) 

88 56 56 52 47 

(9 - 165) (5 - 105) (5 - 105) (5 - 99) (5 - 90) 

108 90 87 80 77 

(38 - 176) (32 - 147) (31 - 143) (28 - 132) (27 - 126) (2

24 22 21 19 19 

(-2 - 49) (-2 - 45) (-2 - 42) (-2 - 39) (-2 - 39) (

47 47 47 45 44 

(4 - 90) (4 - 90) (4 - 90) (4 - 85) (4 - 84) 

27 16 16 16 13 

(-3 - 55) (-2 - 32) (-2 - 32) (-2 - 32) (-1 - 28) (

106 6 6 5 

(1 - 18) (1 - 12) (1 - 12) (1 - 12) (1 - 10) 

30 27 23 21 23 

(-8 - 66) (-7 - 59) (-6 - 52) (-6 - 48) (-6 - 51) (

86665

(0 - 16) (0 - 13) (0 - 13) (0 - 13) (0 - 11) 

Incidence of Respiratory Mortality Associated with Short-Term Exposure to PM2.5 Concentrations in a R

and PM2.5 Concentrations that Just Meet the Current and Alternative Annual (n) and Daily (m) Standard

Combination Denoted n/m):

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on location-specific single pollutant concentration-response function estimates from Zanobetti and Schwartz (2009) that have been "shrunken" towards 

regional means. "Shrunken" coefficient estimates and their standard errors were sent to EPA by A. Zanobetti via email. Numbers are rounded to the nearest w

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL Baltimore, MD Detroit, MI Houston, TX New York, NY St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT

E-125

September 2009 
Table E-94. Estimated Percent of Total Annual Incidence of Respiratory Mortality Associated with Short-Term Exposure t

 PM2.5 Concentrations in a Recent Year (2005) and PM2.5 Concentrations that Just Meet the Current and Alternati Based on Adjusting 2005 PM2.5 Concentrations1

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

1.7% 1.6% 1.3% 1.2% 1.3% 

(-0.7% - 4%) (-0.6% - 3.7%) (-0.5% - 3.2%) (-0.5% - 2.9%) (-0.5% - 3.2%) (-0

3.1% 2.9% 2.6% 2.4% 2.5% 

(0.6% - 5.5%) (0.5% - 5.3%) (0.5% - 4.6%) (0.4% - 4.2%) (0.5% - 4.5%) (0

1.5% 1.2% 1% 0.9% 1% 

(-1.2% - 4.2%) (-1% - 3.3%) (-0.8% - 2.8%) (-0.7% - 2.6%) (-0.8% - 2.8%) (-0

1% 1% 1% 0.9% 1% 

(-0.9% - 2.9%) (-0.9% - 2.9%) (-0.9% - 2.9%) (-0.8% - 2.7%) (-0.9% - 2.9%) (-0

2.5% 2% 1.9% 1.7% 1.7% 

(0.1% - 4.8%) (0.1% - 3.9%) (0.1% - 3.6%) (0.1% - 3.3%) (0.1% - 3.3%) (0

2.7% 1.5% 1.5% 1.5% 1.3% 

(0.1% - 5.1%) (0% - 2.9%) (0% - 2.9%) (0% - 2.9%) (0% - 2.5%) (

2.7% 2.6% 2.2% 2% 2.2% 

(0.4% - 5%) (0.4% - 4.7%) (0.4% - 4%) (0.3% - 3.7%) (0.4% - 4%) (0

1.7% 1.1% 1.1% 1% 0.9% 

(0.2% - 3.2%) (0.1% - 2%) (0.1% - 2%) (0.1% - 1.9%) (0.1% - 1.7%) (0

2.7% 2.3% 2.2% 2% 1.9% 

(1% - 4.4%) (0.8% - 3.7%) (0.8% - 3.6%) (0.7% - 3.3%) (0.7% - 3.2%) (0

2% 1.9% 1.7% 1.6% 1.6% 

(-0.2% - 4.2%) (-0.2% - 3.8%) (-0.2% - 3.6%) (-0.1% - 3.3%) (-0.1% - 3.3%) (-0

1.9% 1.9% 1.9% 1.8% 1.8% 

(0.2% - 3.7%) (0.2% - 3.7%) (0.2% - 3.7%) (0.1% - 3.5%) (0.1% - 3.4%) (0

2.5% 1.4% 1.4% 1.4% 1.2% 

(-0.2% - 5.1%) (-0.1% - 3%) (-0.1% - 3%) (-0.1% - 3%) (-0.1% - 2.6%) (-0

2.1% 1.3% 1.3% 1.3% 1.1% 

(0.3% - 3.8%) (0.2% - 2.4%) (0.2% - 2.4%) (0.2% - 2.4%) (0.1% - 2.1%) (0

1.9% 1.7% 1.5% 1.4% 1.5% 

(-0.5% - 4.3%) (-0.5% - 3.9%) (-0.4% - 3.4%) (-0.4% - 3.1%) (-0.4% - 3.3%) (-0

1.8% 1.5% 1.5% 1.5% 1.3% 

(0% - 3.6%) (0% - 3%) (0% - 3%) (0% - 3%) (0% - 2.5%) (0

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on location-specific single pollutant concentration-response function estimates from Zanobetti and Schwartz (2009) that have been "shrunken" towards 

regional means. "Shrunken" coefficient estimates and their standard errors were sent to EPA by A. Zanobetti via email. Percents are rounded to the nearest 

 Dallas, TX Fresno, CA Los Angeles, CA

Percent of Total Incidence of Respiratory Mortality Associated with Short-Term Exposure to PM2.5 Conc

a Recent Year and PM2.5 Concentrations that Just Meet the Current and Alternative Annual (n) and 

Standards (Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

E-126

September 2009 
Table E-95. Estimated Percent of Total Annual Incidence of Respiratory Mortality Associated with Short-Term Exposure t

 PM2.5 Concentrations in a Recent Year (2006) and PM2.5 Concentrations that Just Meet the Current and Alternati Based on Adjusting 2006 PM2.5 Concentrations1 

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

1.6% 1.5% 1.3% 1.2% 1.3% 

(-0.7% - 3.9%) (-0.6% - 3.5%) (-0.5% - 3%) (-0.5% - 2.8%) (-0.5% - 3%) (-0

2.8% 2.7% 2.3% 2.2% 2.3% 

(0.5% - 5.1%) (0.5% - 4.8%) (0.4% - 4.2%) (0.4% - 3.9%) (0.4% - 4.1%) (0

1.5% 1.2% 1% 0.9% 1% 

(-1.2% - 4%) (-0.9% - 3.2%) (-0.8% - 2.7%) (-0.7% - 2.5%) (-0.8% - 2.7%) (-0

0.8% 0.8% 0.8% 0.8% 0.8% 

(-0.8% - 2.4%) (-0.8% - 2.4%) (-0.8% - 2.4%) (-0.7% - 2.2%) (-0.8% - 2.4%) (-0

2.1% 1.7% 1.6% 1.4% 1.5% 

(0.1% - 4%) (0.1% - 3.3%) (0.1% - 3%) (0.1% - 2.8%) (0.1% - 2.8%) (0

2.8% 1.5% 1.5% 1.5% 1.3% 

(0.1% - 5.3%) (0% - 3%) (0% - 3%) (0% - 3%) (0% - 2.5%) (0

2.8% 2.6% 2.2% 2% 2.2% 

(0.4% - 5.1%) (0.4% - 4.8%) (0.4% - 4.1%) (0.3% - 3.7%) (0.4% - 4.1%) (0

1.6% 1% 1% 0.9% 0.8% 

(0.2% - 2.9%) (0.1% - 1.9%) (0.1% - 1.9%) (0.1% - 1.8%) (0.1% - 1.6%) (0

2.5% 2.1% 2% 1.8% 1.8% 

(0.9% - 4%) (0.7% - 3.4%) (0.7% - 3.3%) (0.6% - 3%) (0.6% - 2.9%) (0

2% 1.8% 1.7% 1.6% 1.6% 

(-0.2% - 4.1%) (-0.2% - 3.8%) (-0.2% - 3.5%) (-0.1% - 3.3%) (-0.1% - 3.2%) (-0

2% 2% 2% 1.9% 1.9% 

(0.2% - 3.8%) (0.2% - 3.8%) (0.2% - 3.8%) (0.1% - 3.6%) (0.1% - 3.5%) (0

2.2% 1.3% 1.3% 1.3% 1.1% 

(-0.2% - 4.6%) (-0.1% - 2.7%) (-0.1% - 2.7%) (-0.1% - 2.7%) (-0.1% - 2.3%) (-0

1.8% 1.2% 1.2% 1.2% 1% 

(0.2% - 3.4%) (0.1% - 2.2%) (0.1% - 2.2%) (0.1% - 2.2%) (0.1% - 1.9%) (0

1.6% 1.5% 1.3% 1.2% 1.3% 

(-0.4% - 3.7%) (-0.4% - 3.3%) (-0.3% - 2.9%) (-0.3% - 2.6%) (-0.3% - 2.8%) (-0

1.5% 1.2% 1.2% 1.2% 1% 

(0% - 2.9%) (0% - 2.4%) (0% - 2.4%) (0% - 2.4%) (0% - 2%) (0

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on location-specific single pollutant concentration-response function estimates from Zanobetti and Schwartz (2009) that have been "shrunken" towards 

regional means. "Shrunken" coefficient estimates and their standard errors were sent to EPA by A. Zanobetti via email. Percents are rounded to the nearest 

 Dallas, TX Fresno, CA Los Angeles, CA

Percent of Total Incidence of Respiratory Mortality Associated with Short-Term Exposure to PM2.5 Conc

a Recent Year and PM2.5 Concentrations that Just Meet the Current and Alternative Annual (n) and 

Standards (Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

E-127

September 2009 
Table E-96. Estimated Percent of Total Annual Incidence of Respiratory Mortality Associated with Short-Term Exposure t

 PM2.5 Concentrations in a Recent Year (2007) and PM2.5 Concentrations that Just Meet the Current and Alternati Based on Adjusting 2007 PM2.5 Concentrations1 

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

1.6% 1.5% 1.3% 1.2% 1.3% 

(-0.7% - 3.9%) (-0.6% - 3.6%) (-0.5% - 3%) (-0.5% - 2.8%) (-0.5% - 3%) (-0

2.7% 2.6% 2.3% 2.1% 2.2% 

(0.5% - 4.9%) (0.5% - 4.6%) (0.4% - 4%) (0.4% - 3.7%) (0.4% - 4%) (0

1.5% 1.1% 1% 0.9% 1% 

(-1.2% - 4%) (-0.9% - 3.1%) (-0.8% - 2.7%) (-0.7% - 2.4%) (-0.8% - 2.7%) (-0

0.9% 0.9% 0.9% 0.8% 0.9% 

(-0.8% - 2.5%) (-0.8% - 2.5%) (-0.8% - 2.5%) (-0.7% - 2.4%) (-0.8% - 2.5%) (-0

2% 1.6% 1.5% 1.4% 1.4% 

(0.1% - 3.9%) (0.1% - 3.2%) (0.1% - 2.9%) (0.1% - 2.7%) (0.1% - 2.7%) (0

2.9% 1.6% 1.6% 1.6% 1.4% 

(0.1% - 5.6%) (0.1% - 3.2%) (0.1% - 3.2%) (0.1% - 3.2%) (0% - 2.7%) (0

2.7% 2.6% 2.2% 2% 2.2% 

(0.4% - 4.9%) (0.4% - 4.7%) (0.3% - 4%) (0.3% - 3.6%) (0.3% - 4%) (0

1.6% 1% 1% 0.9% 0.8% 

(0.2% - 3%) (0.1% - 1.9%) (0.1% - 1.9%) (0.1% - 1.8%) (0.1% - 1.6%) (0

2.5% 2.1% 2% 1.9% 1.8% 

(0.9% - 4.1%) (0.7% - 3.4%) (0.7% - 3.3%) (0.7% - 3%) (0.6% - 2.9%) (0

2% 1.8% 1.7% 1.6% 1.6% 

(-0.2% - 4.1%) (-0.2% - 3.8%) (-0.2% - 3.5%) (-0.1% - 3.2%) (-0.1% - 3.2%) (-0

1.8% 1.8% 1.8% 1.7% 1.7% 

(0.1% - 3.5%) (0.1% - 3.5%) (0.1% - 3.5%) (0.1% - 3.3%) (0.1% - 3.2%) (0

2.3% 1.3% 1.3% 1.3% 1.1% 

(-0.2% - 4.7%) (-0.1% - 2.7%) (-0.1% - 2.7%) (-0.1% - 2.7%) (-0.1% - 2.4%) (-

2.2% 1.4% 1.4% 1.4% 1.2% 

(0.3% - 4%) (0.2% - 2.5%) (0.2% - 2.5%) (0.2% - 2.5%) (0.1% - 2.2%) (0

1.7% 1.5% 1.3% 1.2% 1.3% 

(-0.4% - 3.8%) (-0.4% - 3.4%) (-0.3% - 3%) (-0.3% - 2.7%) (-0.3% - 2.9%) (-0

1.6% 1.3% 1.3% 1.3% 1.1% 

(0% - 3.1%) (0% - 2.5%) (0% - 2.5%) (0% - 2.5%) (0% - 2.2%) (0

Percent of Total Incidence of Respiratory Mortality Associated with Short-Term Exposure to PM2.5 Conc

a Recent Year and PM2.5 Concentrations that Just Meet the Current and Alternative Annual (n) and 

Standards (Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on location-specific single pollutant concentration-response function estimates from Zanobetti and Schwartz (2009) that have been "shrunken" towards 

regional means. "Shrunken" coefficient estimates and their standard errors were sent to EPA by A. Zanobetti via email. Percents are rounded to the nearest 

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

E-128

September 2009 
Table E-97. Percent Reduction from the Current Standards: Estimated Annual Incidence of Respiratory Mortality Ass

 Short-Term Exposure to Ambient PM2.5 Concentrations, Based on Adjusting 2005 PM2.5 Concentrations1

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

-9% 0% 15% 22% 15% 

(-9% - -9%) (0% - 0%) (15% - 15%) (22% - 23%) (15% - 15%) 

-6% 0% 12% 19% 14% 

(-6% - -6%) (0% - 0%) (12% - 13%) (19% - 20%) (14% - 15%) 

-28% 0% 15% 22% 15% 

(-27% - -28%) (0% - 0%) (15% - 15%) (22% - 23%) (15% - 15%) 

0% 0% 0% 7% 0% 

(0% - 0%) (0% - 0%) (0% - 0%) (7% - 7%) (0% - 0%) 

-23% 0% 8% 16% 14% 

(-23% - -23%) (0% - 0%) (8% - 8%) (15% - 16%) (14% - 15%) 

-80% 0% 0% 0% 14% 

(-78% - -82%) (0% - 0%) (0% - 0%) (0% - 0%) (14% - 15%) 

-6% 0% 15% 22% 15% 

(-6% - -6%) (0% - 0%) (15% - 15%) (22% - 23%) (15% - 15%) 

-58% 0% 0% 6% 15% 

(-57% - -58%) (0% - 0%) (0% - 0%) (6% - 6%) (14% - 15%) 

-20% 0% 3% 10% 14% 

(-20% - -20%) (0% - 0%) (3% - 3%) (10% - 10%) (14% - 15%) 

-9% 0% 6% 14% 14% 

(-9% - -9%) (0% - 0%) (6% - 7%) (14% - 14%) (14% - 15%) 

0% 0% 0% 5% 6% 

(0% - 0%) (0% - 0%) (0% - 0%) (5% - 5%) (6% - 6%) 

-72% 0% 0% 0% 15% 

(-71% - -73%) (0% - 0%) (0% - 0%) (0% - 0%) (14% - 15%) 

-58% 0% 0% 0% 15% 

(-57% - -59%) (0% - 0%) (0% - 0%) (0% - 0%) (14% - 15%) 

-12% 0% 13% 20% 15% 

(-11% - -12%) (0% - 0%) (13% - 13%) (20% - 20%) (14% - 15%) 

-23% 0% 0% 0% 15% 

(-23% - -24%) (0% - 0%) (0% - 0%) (0% - 0%) (14% - 15%) 

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on location-specific single pollutant concentration-response function estimates from Zanobetti and Schwartz (2009) that have been "shrunken" tow

regional means. "Shrunken" coefficient estimates and their standard errors were sent to EPA by A. Zanobetti via email. Percents are rounded to whole n

 Dallas, TX Fresno, CA Los Angeles, CA

Percent Reduction from the Current Standards: Annual Incidence of Respiratory Mortality Associated w

Exposure to PM2.5 Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the Current 

Annual (n) and Daily (m) Standards (Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

E-129

September 2009 
Table E-98. Percent Reduction from the Current Standards: Estimated Annual Incidence of Respiratory Mortality Ass

 Short-Term Exposure to Ambient PM2.5 Concentrations, Based on Adjusting 2006 PM2.5 Concentrations1 

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

-9% 0% 15% 22% 15% 

(-9% - -9%) (0% - 0%) (15% - 15%) (22% - 23%) (15% - 15%) 

-6% 0% 12% 20% 14% 

(-6% - -6%) (0% - 0%) (12% - 13%) (19% - 20%) (14% - 15%) 

-28% 0% 15% 22% 15% 

(-27% - -28%) (0% - 0%) (15% - 15%) (22% - 23%) (15% - 15%) 

0% 0% 0% 7% 0% 

(0% - 0%) (0% - 0%) (0% - 0%) (7% - 7%) (0% - 0%) 

-23% 0% 8% 16% 14% 

(-23% - -23%) (0% - 0%) (8% - 8%) (16% - 16%) (14% - 15%) 

-80% 0% 0% 0% 14% 

(-79% - -82%) (0% - 0%) (0% - 0%) (0% - 0%) (14% - 15%) 

-6% 0% 15% 22% 15% 

(-6% - -6%) (0% - 0%) (15% - 15%) (22% - 23%) (15% - 15%) 

-58% 0% 0% 6% 15% 

(-57% - -58%) (0% - 0%) (0% - 0%) (6% - 6%) (14% - 15%) 

-20% 0% 3% 10% 14% 

(-20% - -20%) (0% - 0%) (3% - 3%) (10% - 10%) (14% - 15%) 

-9% 0% 6% 14% 14% 

(-8% - -9%) (0% - 0%) (6% - 7%) (14% - 14%) (14% - 15%) 

0% 0% 0% 5% 6% 

(0% - 0%) (0% - 0%) (0% - 0%) (5% - 5%) (6% - 6%) 

-72% 0% 0% 0% 15% 

(-71% - -73%) (0% - 0%) (0% - 0%) (0% - 0%) (14% - 15%) 

-58% 0% 0% 0% 15% 

(-57% - -59%) (0% - 0%) (0% - 0%) (0% - 0%) (14% - 15%) 

-12% 0% 13% 20% 15% 

(-11% - -12%) (0% - 0%) (13% - 13%) (20% - 20%) (14% - 15%) 

-23% 0% 0% 0% 15% 

(-23% - -24%) (0% - 0%) (0% - 0%) (0% - 0%) (14% - 15%) 

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on location-specific single pollutant concentration-response function estimates from Zanobetti and Schwartz (2009) that have been "shrunken" tow

regional means. "Shrunken" coefficient estimates and their standard errors were sent to EPA by A. Zanobetti via email. Percents are rounded to whole n

 Dallas, TX Fresno, CA Los Angeles, CA

Percent Reduction from the Current Standards: Annual Incidence of Respiratory Mortality Associated w

Exposure to PM2.5 Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the Current 

Annual (n) and Daily (m) Standards (Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

E-130

September 2009 
Table E-99. Percent Reduction from the Current Standards: Estimated Annual Incidence of Respiratory Mortality Ass

 Short-Term Exposure to Ambient PM2.5 Concentrations, Based on Adjusting 2007 PM2.5 Concentrations1

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

-9% 0% 15% 22% 15% 

(-9% - -9%) (0% - 0%) (15% - 15%) (22% - 23%) (15% - 15%) 

-6% 0% 12% 20% 14% 

(-6% - -6%) (0% - 0%) (12% - 13%) (19% - 20%) (14% - 15%) 

-28% 0% 15% 22% 15% 

(-27% - -28%) (0% - 0%) (15% - 15%) (22% - 23%) (15% - 15%) 

0% 0% 0% 7% 0% 

(0% - 0%) (0% - 0%) (0% - 0%) (7% - 7%) (0% - 0%) 

-23% 0% 8% 16% 15% 

(-23% - -23%) (0% - 0%) (8% - 8%) (16% - 16%) (14% - 15%) 

-79% 0% 0% 0% 14% 

(-77% - -82%) (0% - 0%) (0% - 0%) (0% - 0%) (14% - 15%) 

-6% 0% 15% 22% 15% 

(-6% - -6%) (0% - 0%) (15% - 15%) (22% - 23%) (15% - 15%) 

-58% 0% 0% 6% 15% 

(-57% - -58%) (0% - 0%) (0% - 0%) (6% - 6%) (14% - 15%) 

-20% 0% 3% 10% 14% 

(-20% - -20%) (0% - 0%) (3% - 3%) (10% - 11%) (14% - 15%) 

-9% 0% 6% 14% 14% 

(-9% - -9%) (0% - 0%) (6% - 7%) (14% - 14%) (14% - 15%) 

0% 0% 0% 5% 6% 

(0% - 0%) (0% - 0%) (0% - 0%) (5% - 5%) (6% - 6%) 

-72% 0% 0% 0% 15% 

(-71% - -73%) (0% - 0%) (0% - 0%) (0% - 0%) (14% - 15%) 

-58% 0% 0% 0% 15% 

(-56% - -59%) (0% - 0%) (0% - 0%) (0% - 0%) (14% - 15%) 

-12% 0% 13% 20% 15% 

(-11% - -12%) (0% - 0%) (13% - 13%) (20% - 20%) (14% - 15%) 

-23% 0% 0% 0% 15% 

(-23% - -24%) (0% - 0%) (0% - 0%) (0% - 0%) (14% - 15%) 

Percent Reduction from the Current Standards: Annual Incidence of Respiratory Mortality Associated w

Exposure to PM2.5 Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the Current 

Annual (n) and Daily (m) Standards (Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on location-specific single pollutant concentration-response function estimates from Zanobetti and Schwartz (2009) that have been "shrunken" tow

regional means. "Shrunken" coefficient estimates and their standard errors were sent to EPA by A. Zanobetti via email. Percents are rounded to whole n

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

E-131

September 2009 
Figure E-31. Estimated Percent Reductions From the Current Standard to Alternative 

Standards in Respiratory Mortality Associated with Short-Term Exposure to PM2.5: Based 

on 2005 Air Quality Data*

-80%

-70%

-60%

-50%

-40%

-30%

-20%

-10%

0%

10%

20%

30%

2005 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Reduction from Current Standard

 Atlanta, GA 19 (-8 - 46); (-0.6% - 3.7%) 2.9%

 Baltimore, MD 35 (7 - 63); (0.5% - 5.3%) 1.2%

 Birmingham, AL 10 (-8 - 29); (-1% - 3.3%) 1%

 Dallas, TX 11 (-10 - 31); (-0.9% - 2.9%) 2%

 Detroit, MI 27 (1 - 52); (0.1% - 3.9%) 1.5%

 Fresno, CA 9 (0 - 17); (0% - 2.9%) 2.6%

 Houston, TX 36 (6 - 66); (0.4% - 4.7%) 1.1%

 Los Angeles, CA 59 (6 - 112); (0.1% - 2%) 2.3%

 New York, NY 97 (34 - 159); (0.8% - 3.7%) 1.9%

 Philadelphia, PA 23 (-2 - 46); (-0.2% - 3.8%) 1.9%

 Phoenix, AZ 47 (4 - 89); (0.2% - 3.7%) 1.4%

 Pittsburgh, PA 17 (-2 - 35); (-0.1% - 3%) 1.3%

 Salt Lake City, UT 6 (1 - 11); (0.2% - 2.4%) 1.7%

 St. Louis, MO 30 (-8 - 67); (-0.5% - 3.9%) 1.5%

 Tacoma, WA 7 (0 - 15); (0% - 3%) 

*Based on Bell et al. (2008). The legend contains, for each urban area, the incidence estimate (and 95% CI) and the 

estimate of percent of total incidence (and 95% CI) under the current standards. 

**The current standards consist of an annual standard of 15 μg/m3

 and a daily standard of 35 μg/m3. Combinations of 

an annual standard (n) and a daily standard (m) are denoted n/m in this figure. 

E-132

September 2009 Draft - Do Not Quote or Cite
Figure E-32. Estimated Percent Reductions From the Current Standard to Alternative 

Standards in Respiratory Mortality Associated with Short-Term Exposure to PM2.5: Based 

on 2006 Air Quality Data*

-80%

-70%

-60%

-50%

-40%

-30%

-20%

-10%

0%

10%

20%

30%

2006 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Reduction from Current Standard

 Atlanta, GA 19 (-8 - 45); (-0.6% - 3.5%) 2.7%

 Baltimore, MD 32 (6 - 58); (0.5% - 4.8%) 1.2%

 Birmingham, AL 10 (-8 - 28); (-0.9% - 3.2%) 0.8%

 Dallas, TX 9 (-9 - 27); (-0.8% - 2.4%) 1.7%

 Detroit, MI 23 (1 - 44); (0.1% - 3.3%) 1.5%

 Fresno, CA 9 (0 - 18); (0% - 3%) 2.6%

 Houston, TX 38 (6 - 69); (0.4% - 4.8%) 1%

 Los Angeles, CA 55 (5 - 104); (0.1% - 1.9%) 2.1%

 New York, NY 89 (31 - 145); (0.7% - 3.4%) 1.8%

 Philadelphia, PA 22 (-2 - 46); (-0.2% - 3.8%) 2%

 Phoenix, AZ 50 (4 - 95); (0.2% - 3.8%) 1.3%

 Pittsburgh, PA 15 (-2 - 32); (-0.1% - 2.7%) 1.2%

 Salt Lake City, UT 5 (1 - 10); (0.1% - 2.2%) 1.5%

 St. Louis, MO 26 (-7 - 57); (-0.4% - 3.3%) 1.2%

 Tacoma, WA 6 (0 - 12); (0% - 2.4%) 

*Based on Bell et al. (2008). The legend contains, for each urban area, the incidence estimate (and 95% CI) and the 

estimate of percent of total incidence (and 95% CI) under the current standards. 

**The current standards consist of an annual standard of 15 μg/m3

 and a daily standard of 35 μg/m3. Combinations of 

an annual standard (n) and a daily standard (m) are denoted n/m in this figure. 

E-133

September 2009 Draft - Do Not Quote or Cite
Figure E-33. Estimated Percent Reductions From the Current Standard to Alternative 

Standards in Respiratory Mortality Associated with Short-Term Exposure to PM2.5: Based 

on 2007 Air Quality Data*

-80%

-70%

-60%

-50%

-40%

-30%

-20%

-10%

0%

10%

20%

30%

2007 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Reduction from Current Standard

 Atlanta, GA 20 (-8 - 47); (-0.6% - 3.6%) 2.6%

 Baltimore, MD 31 (6 - 56); (0.5% - 4.6%) 1.1%

 Birmingham, AL 10 (-8 - 28); (-0.9% - 3.1%) 0.9%

 Dallas, TX 10 (-9 - 29); (-0.8% - 2.5%) 1.6%

 Detroit, MI 22 (1 - 42); (0.1% - 3.2%) 1.6%

 Fresno, CA 10 (0 - 19); (0.1% - 3.2%) 2.6%

 Houston, TX 38 (6 - 68); (0.4% - 4.7%) 1%

 Los Angeles, CA 56 (5 - 105); (0.1% - 1.9%) 2.1%

 New York, NY 90 (32 - 147); (0.7% - 3.4%) 1.8%

 Philadelphia, PA 22 (-2 - 45); (-0.2% - 3.8%) 1.8%

 Phoenix, AZ 47 (4 - 90); (0.1% - 3.5%) 1.3%

 Pittsburgh, PA 16 (-2 - 32); (-0.1% - 2.7%) 1.4%

 Salt Lake City, UT 6 (1 - 12); (0.2% - 2.5%) 1.5%

 St. Louis, MO 27 (-7 - 59); (-0.4% - 3.4%) 1.3%

 Tacoma, WA 6 (0 - 13); (0% - 2.5%) 

 

*Based on Bell et al. (2008). The legend contains, for each urban area, the incidence estimate (and 95% CI) and the 

estimate of percent of total incidence (and 95% CI) under the current standards. 

**The current standards consist of an annual standard of 15 μg/m3

 and a daily standard of 35 μg/m3. Combinations of 

an annual standard (n) and a daily standard (m) are denoted n/m in this figure. 

E-134

September 2009 Draft - Do Not Quote or Cite
Table E-100. Estimated Annual Incidence of Hospital Admissions for Cardiovascular Illness Associated with Short-Term 

 Ambient PM2.5 Concentrations in a Recent Year (2005) and PM2.5 Concentrations that Just Meet the Current a

 Standards, Based on Adjusting 2005 PM2.5 Concentrations1

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

43 40 34 31 34 

(-28 - 114) (-26 - 105) (-22 - 89) (-20 - 81) (-22 - 89) 

262 247 216 199 212 

(192 - 331) (182 - 313) (159 - 273) (146 - 251) (155 - 267) 

23 18 16 14 16 

(-15 - 62) (-12 - 48) (-10 - 41) (-9 - 37) (-10 - 41) 

30 30 30 27 30 

(-19 - 78) (-19 - 78) (-19 - 78) (-18 - 73) (-19 - 78) 

331 269 247 227 230 

(243 - 418) (198 - 340) (181 - 312) (166 - 286) (169 - 290) 

38 21 21 21 18 

(0 - 76) (0 - 42) (0 - 42) (0 - 42) (0 - 36) 

65 61 52 47 52 

(-42 - 171) (-40 - 161) (-34 - 137) (-31 - 125) (-34 - 137) 

434 274 274 259 234 

(5 - 858) (3 - 543) (3 - 543) (3 - 513) (3 - 464) 

870 724 705 648 619 

(639 - 1100) (532 - 915) (518 - 891) (476 - 819) (454 - 783) 

228 210 196 180 179 

(167 - 288) (154 - 265) (144 - 248) (132 - 228) (132 - 227) 

107 107 107 102 100 

(1 - 212) (1 - 212) (1 - 212) (1 - 201) (1 - 198) 

231 134 134 134 114 

(170 - 291) (98 - 169) (98 - 169) (98 - 169) (84 - 145) 

149 9 9 7 

(0 - 28) (0 - 17) (0 - 17) (0 - 17) (0 - 15) 

223 200 174 159 171 

(164 - 282) (147 - 253) (128 - 220) (117 - 202) (126 - 216) 

26 21 21 21 18 

(-65 - 113) (-52 - 92) (-52 - 92) (-52 - 92) (-44 - 79) 

Total Incidence of Hospital Admissions for Cardiovascular Illness Associated with Short-Term Exp

Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the Current and Alternativ

Daily (m) Standards (Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Incidence estimates were calculated using the appropriate regional concentration-response function estimates reported in Table 2 of Bell et al. (2008). Lo

function estimates were not available from this study.

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

E-135

September 2009 
Table E-101. Estimated Annual Incidence of Hospital Admissions for Cardiovascular Illness Associated with Short-Term 

 Ambient PM2.5 Concentrations in a Recent Year (2006) and PM2.5 Concentrations that Just Meet the Current a

 Standards, Based on Adjusting 2006 PM2.5 Concentrations1

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

43 39 33 30 33 

(-28 - 113) (-26 - 103) (-22 - 88) (-20 - 80) (-22 - 88) 

237 224 196 180 192 

(174 - 300) (165 - 284) (144 - 248) (132 - 228) (141 - 243) 

23 18 15 14 15 

(-15 - 60) (-12 - 47) (-10 - 40) (-9 - 36) (-10 - 40) 

25 25 25 24 25 

(-17 - 67) (-17 - 67) (-17 - 67) (-15 - 63) (-17 - 67) 

276 224 206 189 192 

(203 - 349) (165 - 284) (151 - 260) (139 - 239) (141 - 242) 

40 22 22 22 19 

(0 - 79) (0 - 44) (0 - 44) (0 - 44) (0 - 38) 

68 64 54 50 54 

(-45 - 180) (-42 - 170) (-36 - 144) (-33 - 131) (-36 - 144) 

408 258 258 243 220 

(5 - 807) (3 - 511) (3 - 511) (3 - 482) (3 - 437) 

801 666 649 597 570 

(589 - 1013) (489 - 843) (477 - 821) (438 - 755) (418 - 721) 

222 204 191 176 175 

(163 - 281) (150 - 258) (140 - 242) (129 - 222) (128 - 221) 

113 113 113 108 106 

(1 - 225) (1 - 225) (1 - 225) (1 - 213) (1 - 210) 

207 120 120 120 102 

(152 - 261) (88 - 152) (88 - 152) (88 - 152) (75 - 130) 

138 8 8 7 

(0 - 25) (0 - 16) (0 - 16) (0 - 16) (0 - 14) 

190 171 148 136 146 

(140 - 241) (125 - 216) (109 - 187) (100 - 172) (107 - 184) 

22 18 18 18 15 

(-53 - 93) (-43 - 76) (-43 - 76) (-43 - 76) (-36 - 65) 

Total Incidence of Hospital Admissions for Cardiovascular Illness Associated with Short-Term Exp

Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the Current and Alternativ

Daily (m) Standards (Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Incidence estimates were calculated using the appropriate regional concentration-response function estimates reported in Table 2 of Bell et al. (2008). Lo

function estimates were not available from this study.

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

E-136

September 2009 
Table E-102. Estimated Annual Incidence of Hospital Admissions for Cardiovascular Illness Associated with Short-Ter

 Ambient PM2.5 Concentrations in a Recent Year (2007) and PM2.5 Concentrations that Just Meet the Current a

 Standards, Based on Adjusting 2007 PM2.5 Concentrations1

Recent Ambient 

PM2.5 

Concentrations

15/352 13/35 12/35 13/30 

44 41 35 32 35 

(-29 - 117) (-27 - 108) (-23 - 92) (-21 - 84) (-23 - 92) 

227 215 188 173 184 

(167 - 287) (158 - 271) (138 - 237) (127 - 218) (135 - 232) 

22 17 15 14 15 

(-15 - 59) (-11 - 46) (-10 - 39) (-9 - 36) (-10 - 39) 

27 27 27 25 27 

(-18 - 72) (-18 - 72) (-18 - 72) (-17 - 67) (-18 - 72) 

265 215 197 181 184 

(195 - 335) (158 - 272) (145 - 249) (133 - 229) (135 - 232) 

44 24 24 24 21 

(1 - 87) (0 - 48) (0 - 48) (0 - 48) (0 - 41) 

68 64 54 50 54 

(-45 - 180) (-42 - 169) (-36 - 144) (-33 - 131) (-36 - 144) 

420 265 265 250 227 

(5 - 831) (3 - 526) (3 - 526) (3 - 496) (3 - 449) 

813 676 659 605 578 

(597 - 1028) (496 - 855) (484 - 833) (444 - 765) (424 - 731) 

218 201 188 173 172 

(160 - 276) (148 - 254) (138 - 238) (127 - 218) (126 - 217) 

108 108 108 103 101 

(1 - 215) (1 - 215) (1 - 215) (1 - 204) (1 - 201) 

207 120 120 120 102 

(152 - 261) (88 - 152) (88 - 152) (88 - 152) (75 - 130) 

16 10 10 10 8 

(0 - 31) (0 - 20) (0 - 20) (0 - 20) (0 - 17) 

196 176 152 140 150 

(144 - 248) (129 - 222) (112 - 193) (103 - 177) (110 - 190) 

23 19 19 19 16 

(-57 - 100) (-46 - 82) (-46 - 82) (-46 - 82) (-39 - 70) 

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Incidence estimates were calculated using the appropriate regional concentration-response function estimates reported in Table 2 of Bell et al. (2008). L

function estimates were not available from this study.

 Dallas, TX Fresno, CA Los Angeles, CA

Total Incidence of Hospital Admissions for Cardiovascular Illness Associated with Short-Term Ex

Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the Current and Alternativ

Daily (m) Standards (Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

E-137

September 2009 
Table E-103. Estimated Percent of Total Annual Incidence of Hospital Admissions for Cardiovascular Illness Associated 

 Short-Term Exposure to Ambient PM2.5 Concentrations in a Recent Year (2005) and PM2.5 Concentrations that 

 the Current and Alternative Standards, Based on Adjusting 2005 PM2.5 Concentrations1

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

0.41% 0.38% 0.32% 0.29% 0.32% 

(-0.27% - 1.09%) (-0.25% - 1%) (-0.21% - 0.85%) (-0.19% - 0.77%) (-0.21% - 0.85%) (

1.59% 1.51% 1.32% 1.21% 1.29% 

(1.17% - 2.01%) (1.11% - 1.9%) (0.97% - 1.66%) (0.89% - 1.53%) (0.95% - 1.63%) 

0.47% 0.37% 0.31% 0.28% 0.31% 

(-0.31% - 1.23%) (-0.24% - 0.97%) (-0.2% - 0.82%) (-0.19% - 0.75%) (-0.2% - 0.82%) (

0.31% 0.31% 0.31% 0.29% 0.31% 

(-0.2% - 0.83%) (-0.2% - 0.83%) (-0.2% - 0.83%) (-0.19% - 0.77%) (-0.2% - 0.83%) (

1.59% 1.29% 1.18% 1.09% 1.1% 

(1.17% - 2.01%) (0.95% - 1.63%) (0.87% - 1.5%) (0.8% - 1.37%) (0.81% - 1.39%) 

0.82% 0.45% 0.45% 0.45% 0.38% 

(0.01% - 1.61%) (0.01% - 0.89%) (0.01% - 0.89%) (0.01% - 0.89%) (0% - 0.76%) 

0.38% 0.36% 0.31% 0.28% 0.31% 

(-0.25% - 1.01%) (-0.24% - 0.95%) (-0.2% - 0.81%) (-0.18% - 0.74%) (-0.2% - 0.81%) (

0.8% 0.5% 0.5% 0.48% 0.43% 

(0.01% - 1.58%) (0.01% - 1%) (0.01% - 1%) (0.01% - 0.94%) (0.01% - 0.85%) 

1.36% 1.13% 1.1% 1.01% 0.97% 

(1% - 1.72%) (0.83% - 1.43%) (0.81% - 1.39%) (0.74% - 1.28%) (0.71% - 1.22%) 

1.38% 1.27% 1.19% 1.09% 1.09% 

(1.02% - 1.75%) (0.94% - 1.61%) (0.88% - 1.51%) (0.8% - 1.38%) (0.8% - 1.38%) 

0.53% 0.53% 0.53% 0.5% 0.49% 

(0.01% - 1.05%) (0.01% - 1.05%) (0.01% - 1.05%) (0.01% - 0.99%) (0.01% - 0.98%) 

1.79% 1.04% 1.04% 1.04% 0.89% 

(1.32% - 2.26%) (0.76% - 1.31%) (0.76% - 1.31%) (0.76% - 1.31%) (0.65% - 1.12%) 

0.57% 0.36% 0.36% 0.36% 0.31% 

(0.01% - 1.13%) (0% - 0.72%) (0% - 0.72%) (0% - 0.72%) (0% - 0.61%) 

1.58% 1.42% 1.23% 1.13% 1.21% 

(1.16% - 2%) (1.04% - 1.8%) (0.91% - 1.56%) (0.83% - 1.43%) (0.89% - 1.53%) 

0.76% 0.62% 0.62% 0.62% 0.53% 

(-1.86% - 3.26%) (-1.5% - 2.65%) (-1.5% - 2.65%) (-1.5% - 2.65%) (-1.28% - 2.27%) (

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Incidence estimates were calculated using the appropriate regional concentration-response function estimates reported in Table 2 of Bell et al. (2008). Lo

function estimates were not available from this study.

 Dallas, TX Fresno, CA Los Angeles, CA

Percent of Total Incidence of Hospital Admissions for Cardiovascular Illness Associated with Short-

to PM2.5 Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the Current an

Annual (n) and Daily (m) Standards (Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

E-138

September 2009 
Table E-104. Estimated Percent of Total Annual Incidence of Hospital Admissions for Cardiovascular Illness Associated 

 Short-Term Exposure to Ambient PM2.5 Concentrations in a Recent Year (2006) and PM2.5 Concentrations that 

 Current and Alternative Standards, Based on Adjusting 2006 PM2.5 Concentrations1

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

0.39% 0.36% 0.31% 0.28% 0.31% 

(-0.26% - 1.04%) (-0.24% - 0.95%) (-0.2% - 0.81%) (-0.18% - 0.74%) (-0.2% - 0.81%) (

1.45% 1.37% 1.2% 1.1% 1.17% 

(1.07% - 1.84%) (1.01% - 1.74%) (0.88% - 1.52%) (0.81% - 1.4%) (0.86% - 1.49%) 

0.45% 0.35% 0.3% 0.27% 0.3% 

(-0.3% - 1.19%) (-0.23% - 0.93%) (-0.2% - 0.79%) (-0.18% - 0.72%) (-0.2% - 0.79%) (

0.26% 0.26% 0.26% 0.24% 0.26% 

(-0.17% - 0.7%) (-0.17% - 0.7%) (-0.17% - 0.7%) (-0.16% - 0.65%) (-0.17% - 0.7%) (

1.33% 1.08% 0.99% 0.91% 0.92% 

(0.98% - 1.69%) (0.79% - 1.37%) (0.73% - 1.26%) (0.67% - 1.15%) (0.68% - 1.17%) 

0.85% 0.47% 0.47% 0.47% 0.4% 

(0.01% - 1.67%) (0.01% - 0.92%) (0.01% - 0.92%) (0.01% - 0.92%) (0% - 0.79%) 

0.39% 0.37% 0.31% 0.28% 0.31% 

(-0.25% - 1.03%) (-0.24% - 0.97%) (-0.2% - 0.82%) (-0.19% - 0.75%) (-0.2% - 0.82%) (

0.74% 0.47% 0.47% 0.44% 0.4% 

(0.01% - 1.46%) (0.01% - 0.93%) (0.01% - 0.93%) (0.01% - 0.87%) (0% - 0.79%) 

1.24% 1.03% 1% 0.92% 0.88% 

(0.91% - 1.57%) (0.76% - 1.3%) (0.74% - 1.27%) (0.68% - 1.17%) (0.65% - 1.12%) 

1.37% 1.26% 1.18% 1.08% 1.08% 

(1.01% - 1.73%) (0.92% - 1.59%) (0.87% - 1.49%) (0.79% - 1.37%) (0.79% - 1.36%) 

0.54% 0.54% 0.54% 0.51% 0.51% 

(0.01% - 1.07%) (0.01% - 1.07%) (0.01% - 1.07%) (0.01% - 1.02%) (0.01% - 1.01%) 

1.63% 0.94% 0.94% 0.94% 0.81% 

(1.2% - 2.06%) (0.69% - 1.19%) (0.69% - 1.19%) (0.69% - 1.19%) (0.59% - 1.02%) 

0.51% 0.32% 0.32% 0.32% 0.27% 

(0.01% - 1.01%) (0% - 0.64%) (0% - 0.64%) (0% - 0.64%) (0% - 0.54%) 

1.36% 1.21% 1.05% 0.97% 1.04% 

(1% - 1.71%) (0.89% - 1.54%) (0.77% - 1.33%) (0.71% - 1.22%) (0.76% - 1.31%) 

0.61% 0.5% 0.5% 0.5% 0.42% 

(-1.49% - 2.63%) (-1.2% - 2.14%) (-1.2% - 2.14%) (-1.2% - 2.14%) (-1.02% - 1.83%) (

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Incidence estimates were calculated using the appropriate regional concentration-response function estimates reported in Table 2 of Bell et al. (2008). Lo

function estimates were not available from this study.

 Dallas, TX Fresno, CA Los Angeles, CA

Percent of Total Incidence of Hospital Admissions for Cardiovascular Illness Associated with Short-

to PM2.5 Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the Current an

Annual (n) and Daily (m) Standards (Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

E-139

September 2009 
Table E-105. Estimated Percent of Total Annual Incidence of Hospital Admissions for Cardiovascular Illness Associated 

 Exposure to Ambient PM2.5 Concentrations in a Recent Year (2007) and PM2.5 Concentrations that Just Meet th

 Alternative Standards, Based on Adjusting 2007 PM2.5 Concentrations1

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

0.4% 0.36% 0.31% 0.28% 0.31% 

(-0.26% - 1.05%) (-0.24% - 0.96%) (-0.2% - 0.82%) (-0.18% - 0.75%) (-0.2% - 0.82%) (

1.4% 1.32% 1.15% 1.06% 1.13% 

(1.03% - 1.76%) (0.97% - 1.67%) (0.85% - 1.46%) (0.78% - 1.34%) (0.83% - 1.43%) 

0.44% 0.35% 0.3% 0.27% 0.3% 

(-0.29% - 1.17%) (-0.23% - 0.92%) (-0.19% - 0.78%) (-0.18% - 0.71%) (-0.19% - 0.78%) (

0.28% 0.28% 0.28% 0.26% 0.28% 

(-0.18% - 0.73%) (-0.18% - 0.73%) (-0.18% - 0.73%) (-0.17% - 0.68%) (-0.18% - 0.73%) (

1.29% 1.04% 0.96% 0.88% 0.89% 

(0.95% - 1.63%) (0.77% - 1.32%) (0.7% - 1.21%) (0.65% - 1.11%) (0.65% - 1.13%) 

0.91% 0.5% 0.5% 0.5% 0.43% 

(0.01% - 1.79%) (0.01% - 0.99%) (0.01% - 0.99%) (0.01% - 0.99%) (0.01% - 0.85%) 

0.38% 0.36% 0.3% 0.28% 0.3% 

(-0.25% - 1%) (-0.23% - 0.94%) (-0.2% - 0.8%) (-0.18% - 0.73%) (-0.2% - 0.8%) (

0.75% 0.47% 0.47% 0.45% 0.4% 

(0.01% - 1.48%) (0.01% - 0.93%) (0.01% - 0.93%) (0.01% - 0.88%) (0% - 0.8%) 

1.25% 1.04% 1.01% 0.93% 0.89% 

(0.92% - 1.58%) (0.76% - 1.31%) (0.74% - 1.28%) (0.68% - 1.17%) (0.65% - 1.12%) 

1.36% 1.25% 1.17% 1.08% 1.07% 

(1% - 1.72%) (0.92% - 1.58%) (0.86% - 1.48%) (0.79% - 1.36%) (0.79% - 1.35%) 

0.5% 0.5% 0.5% 0.47% 0.47% 

(0.01% - 0.99%) (0.01% - 0.99%) (0.01% - 0.99%) (0.01% - 0.94%) (0.01% - 0.93%) 

1.65% 0.96% 0.96% 0.96% 0.82% 

(1.21% - 2.08%) (0.7% - 1.21%) (0.7% - 1.21%) (0.7% - 1.21%) (0.6% - 1.03%) 

0.6% 0.38% 0.38% 0.38% 0.32% 

(0.01% - 1.19%) (0% - 0.75%) (0% - 0.75%) (0% - 0.75%) (0% - 0.64%) 

1.4% 1.25% 1.09% 1% 1.07% 

(1.03% - 1.77%) (0.92% - 1.58%) (0.8% - 1.37%) (0.73% - 1.26%) (0.79% - 1.35%) 

0.65% 0.52% 0.52% 0.52% 0.45% 

(-1.58% - 2.77%) (-1.28% - 2.26%) (-1.28% - 2.26%) (-1.28% - 2.26%) (-1.09% - 1.93%) 

Percent of Total Incidence of Hospital Admissions for Cardiovascular Illness Associated with Short-

to PM2.5 Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the Current an

Annual (n) and Daily (m) Standards (Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Incidence estimates were calculated using the appropriate regional concentration-response function estimates reported in Table 2 of Bell et al. (2008). Lo

function estimates were not available from this study.

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

E-140

September 2009 
Table E-106. Percent Reduction from the Current Standards: Estimated Annual Incidence of Cardiovascular Hospit

 Associated with Short-Term Exposure to Ambient PM2.5 Concentrations, Based on Adjusting 2005 PM2.5 Con

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

-9% 0% 15% 23% 15% 

(-9% - -9%) (0% - 0%) (15% - 15%) (22% - 23%) (15% - 15%) 

-6% 0% 13% 20% 14% 

(-6% - -6%) (0% - 0%) (13% - 13%) (20% - 20%) (14% - 15%) 

-28% 0% 15% 23% 15% 

(-28% - -28%) (0% - 0%) (15% - 15%) (22% - 23%) (15% - 15%) 

0% 0% 0% 7% 0% 

(0% - 0%) (0% - 0%) (0% - 0%) (7% - 7%) (0% - 0%) 

-23% 0% 8% 16% 15% 

(-23% - -23%) (0% - 0%) (8% - 8%) (16% - 16%) (14% - 15%) 

-81% 0% 0% 0% 15% 

(-81% - -82%) (0% - 0%) (0% - 0%) (0% - 0%) (15% - 15%) 

-6% 0% 15% 23% 15% 

(-6% - -6%) (0% - 0%) (15% - 15%) (22% - 23%) (15% - 15%) 

-58% 0% 0% 6% 15% 

(-58% - -59%) (0% - 0%) (0% - 0%) (6% - 6%) (15% - 15%) 

-20% 0% 3% 10% 14% 

(-20% - -20%) (0% - 0%) (3% - 3%) (10% - 10%) (14% - 15%) 

-9% 0% 6% 14% 14% 

(-9% - -9%) (0% - 0%) (6% - 6%) (14% - 14%) (14% - 15%) 

0% 0% 0% 5% 6% 

(0% - 0%) (0% - 0%) (0% - 0%) (5% - 5%) (6% - 6%) 

-72% 0% 0% 0% 15% 

(-72% - -73%) (0% - 0%) (0% - 0%) (0% - 0%) (15% - 15%) 

-59% 0% 0% 0% 15% 

(-58% - -59%) (0% - 0%) (0% - 0%) (0% - 0%) (15% - 15%) 

-12% 0% 13% 20% 15% 

(-12% - -12%) (0% - 0%) (13% - 13%) (20% - 20%) (14% - 15%) 

-23% 0% 0% 0% 15% 

(-23% - -24%) (0% - 0%) (0% - 0%) (0% - 0%) (14% - 15%) 

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Incidence estimates were calculated using the appropriate regional concentration-response function estimates reported in Table 2 of Bell et al. (2008)

function estimates were not available from this study.

 Dallas, TX Fresno, CA Los Angeles, CA

Percent Reduction from the Current Standards: Annual Incidence of Cardiovascular Hospital Admi

Short-Term Exposure to PM2.5 Concentrations in a Recent Year and PM2.5 Concentrations that Jus

Alternative Annual (n) and Daily (m) Standards (Standard Combination Denoted 

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

E-141

September 2009 
Table E-107. Percent Reduction from the Current Standards: Estimated Annual Incidence of Cardiovascular Hospit

 Associated with Short-Term Exposure to Ambient PM2.5 Concentrations, Based on Adjusting 2006 PM2.5 Con

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

-9% 0% 15% 23% 15% 

(-9% - -9%) (0% - 0%) (15% - 15%) (22% - 23%) (15% - 15%) 

-6% 0% 13% 20% 14% 

(-6% - -6%) (0% - 0%) (13% - 13%) (20% - 20%) (14% - 15%) 

-28% 0% 15% 23% 15% 

(-28% - -28%) (0% - 0%) (15% - 15%) (22% - 23%) (15% - 15%) 

0% 0% 0% 7% 0% 

(0% - 0%) (0% - 0%) (0% - 0%) (7% - 7%) (0% - 0%) 

-23% 0% 8% 16% 15% 

(-23% - -23%) (0% - 0%) (8% - 8%) (16% - 16%) (15% - 15%) 

-81% 0% 0% 0% 15% 

(-81% - -82%) (0% - 0%) (0% - 0%) (0% - 0%) (15% - 15%) 

-6% 0% 15% 23% 15% 

(-6% - -6%) (0% - 0%) (15% - 15%) (22% - 23%) (15% - 15%) 

-58% 0% 0% 6% 15% 

(-58% - -59%) (0% - 0%) (0% - 0%) (6% - 6%) (15% - 15%) 

-20% 0% 3% 10% 14% 

(-20% - -20%) (0% - 0%) (3% - 3%) (10% - 10%) (14% - 15%) 

-9% 0% 6% 14% 14% 

(-9% - -9%) (0% - 0%) (6% - 6%) (14% - 14%) (14% - 15%) 

0% 0% 0% 5% 6% 

(0% - 0%) (0% - 0%) (0% - 0%) (5% - 5%) (6% - 6%) 

-72% 0% 0% 0% 15% 

(-72% - -73%) (0% - 0%) (0% - 0%) (0% - 0%) (15% - 15%) 

-59% 0% 0% 0% 15% 

(-58% - -59%) (0% - 0%) (0% - 0%) (0% - 0%) (15% - 15%) 

-12% 0% 13% 20% 15% 

(-12% - -12%) (0% - 0%) (13% - 13%) (20% - 20%) (15% - 15%) 

-23% 0% 0% 0% 15% 

(-23% - -24%) (0% - 0%) (0% - 0%) (0% - 0%) (14% - 15%) 

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Incidence estimates were calculated using the appropriate regional concentration-response function estimates reported in Table 2 of Bell et al. (2008)

function estimates were not available from this study.

 Dallas, TX Fresno, CA Los Angeles, CA

Percent Reduction from the Current Standards: Annual Incidence of Cardiovascular Hospital Admi

Short-Term Exposure to PM2.5 Concentrations in a Recent Year and PM2.5 Concentrations that Jus

Alternative Annual (n) and Daily (m) Standards (Standard Combination Denoted n

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

E-142

September 2009 
Table E-108. Percent Reduction from the Current Standards: Estimated Annual Incidence of Cardiovascular Hospit

 Associated with Short-Term Exposure to Ambient PM2.5 Concentrations, Based on Adjusting 2007 PM2.5 Co

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

-9% 0% 15% 23% 15% 

(-9% - -9%) (0% - 0%) (15% - 15%) (22% - 23%) (15% - 15%) 

-6% 0% 13% 20% 14% 

(-6% - -6%) (0% - 0%) (13% - 13%) (20% - 20%) (14% - 15%) 

-28% 0% 15% 23% 15% 

(-28% - -28%) (0% - 0%) (15% - 15%) (22% - 23%) (15% - 15%) 

0% 0% 0% 7% 0% 

(0% - 0%) (0% - 0%) (0% - 0%) (7% - 7%) (0% - 0%) 

-23% 0% 8% 16% 15% 

(-23% - -23%) (0% - 0%) (8% - 8%) (16% - 16%) (15% - 15%) 

-81% 0% 0% 0% 15% 

(-80% - -82%) (0% - 0%) (0% - 0%) (0% - 0%) (15% - 15%) 

-6% 0% 15% 23% 15% 

(-6% - -6%) (0% - 0%) (15% - 15%) (22% - 23%) (15% - 15%) 

-58% 0% 0% 6% 15% 

(-58% - -59%) (0% - 0%) (0% - 0%) (6% - 6%) (15% - 15%) 

-20% 0% 3% 10% 15% 

(-20% - -20%) (0% - 0%) (3% - 3%) (10% - 10%) (14% - 15%) 

-9% 0% 6% 14% 14% 

(-9% - -9%) (0% - 0%) (6% - 6%) (14% - 14%) (14% - 15%) 

0% 0% 0% 5% 6% 

(0% - 0%) (0% - 0%) (0% - 0%) (5% - 5%) (6% - 6%) 

-72% 0% 0% 0% 15% 

(-72% - -73%) (0% - 0%) (0% - 0%) (0% - 0%) (15% - 15%) 

-58% 0% 0% 0% 15% 

(-58% - -59%) (0% - 0%) (0% - 0%) (0% - 0%) (15% - 15%) 

-12% 0% 13% 20% 15% 

(-12% - -12%) (0% - 0%) (13% - 13%) (20% - 20%) (15% - 15%) 

-23% 0% 0% 0% 15% 

(-23% - -24%) (0% - 0%) (0% - 0%) (0% - 0%) (14% - 15%) 

Percent Reduction from the Current Standards: Annual Incidence of Cardiovascular Hospital Admi

Short-Term Exposure to PM2.5 Concentrations in a Recent Year and PM2.5 Concentrations that Jus

Alternative Annual (n) and Daily (m) Standards (Standard Combination Denoted 

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Incidence estimates were calculated using the appropriate regional concentration-response function estimates reported in Table 2 of Bell et al. (2008)

function estimates were not available from this study.

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

E-143

September 2009 
Figure E-34. Estimated Percent Reductions From the Current Standard to Alternative 

Standards in Cardiovascular Hospital Admissions Associated with Short-Term Exposure to 

PM2.5: Based on 2005 Air Quality Data*

-90%

-80%

-70%

-60%

-50%

-40%

-30%

-20%

-10%

0%

10%

20%

30%

2005 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Reduction from Current Standard

 Atlanta, GA 40 (-26 - 105); 0.38% (-0.25% - 1%)

 Baltimore, MD 247 (182 - 313); 1.51% (1.11% - 1.9%)

 Birmingham, AL 18 (-12 - 48); 0.37% (-0.24% - 0.97%)

 Dallas, TX 30 (-19 - 78); 0.31% (-0.2% - 0.83%)

 Detroit, MI 269 (198 - 340); 1.29% (0.95% - 1.63%)

 Fresno, CA 21 (0 - 42); 0.45% (0.01% - 0.89%)

 Houston, TX 61 (-40 - 161); 0.36% (-0.24% - 0.95%)

 Los Angeles, CA 274 (3 - 543); 0.5% (0.01% - 1%)

 New York, NY 724 (532 - 915); 1.13% (0.83% - 1.43%)

 Philadelphia, PA 210 (154 - 265); 1.27% (0.94% - 1.61%)

 Phoenix, AZ 107 (1 - 212); 0.53% (0.01% - 1.05%)

 Pittsburgh, PA 134 (98 - 169); 1.04% (0.76% - 1.31%)

 Salt Lake City, UT 9 (0 - 17); 0.36% (0% - 0.72%)

 St. Louis, MO 200 (147 - 253); 1.42% (1.04% - 1.8%)

 Tacoma, WA 21 (-52 - 92); 0.62% (-1.5% - 2.65%)

*Based on Zanobetti and Schwartz (2009). The legend contains, for each urban area, the incidence estimate (and 95% 

CI) and the estimate of percent of total incidence (and 95% CI) under the current standards. 

**The current standards consist of an annual standard of 15 μg/m3

 and a daily standard of 35 μg/m3. Combinations of 

an annual standard (n) and a daily standard (m) are denoted n/m in this figure. 

E-144

September 2009 Draft - Do Not Quote or Cite
Figure E-35. Estimated Percent Reductions From the Current Standard to Alternative 

Standards in Cardiovascular Hospital Admissions Associated with Short-Term Exposure to 

PM2.5: Based on 2006 Air Quality Data* 

-90%

-80%

-70%

-60%

-50%

-40%

-30%

-20%

-10%

0%

10%

20%

30%

2006 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Reduction from Current Standard

 Atlanta, GA 39 (-26 - 103); 0.36% (-0.24% - 0.95%)

 Baltimore, MD 224 (165 - 284); 1.37% (1.01% - 1.74%)

 Birmingham, AL 18 (-12 - 47); 0.35% (-0.23% - 0.93%)

 Dallas, TX 25 (-17 - 67); 0.26% (-0.17% - 0.7%)

 Detroit, MI 224 (165 - 284); 1.08% (0.79% - 1.37%)

 Fresno, CA 22 (0 - 44); 0.47% (0.01% - 0.92%)

 Houston, TX 64 (-42 - 170); 0.37% (-0.24% - 0.97%)

 Los Angeles, CA 258 (3 - 511); 0.47% (0.01% - 0.93%)

 New York, NY 666 (489 - 843); 1.03% (0.76% - 1.3%)

 Philadelphia, PA 204 (150 - 258); 1.26% (0.92% - 1.59%)

 Phoenix, AZ 113 (1 - 225); 0.54% (0.01% - 1.07%)

 Pittsburgh, PA 120 (88 - 152); 0.94% (0.69% - 1.19%)

 Salt Lake City, UT 8 (0 - 16); 0.32% (0% - 0.64%)

 St. Louis, MO 171 (125 - 216); 1.21% (0.89% - 1.54%)

 Tacoma, WA 18 (-43 - 76); 0.5% (-1.2% - 2.14%)

*Based on Zanobetti and Schwartz (2009). The legend contains, for each urban area, the incidence estimate (and 95% 

CI) and the estimate of percent of total incidence (and 95% CI) under the current standards. 

**The current standards consist of an annual standard of 15 μg/m3

 and a daily standard of 35 μg/m3. Combinations of 

an annual standard (n) and a daily standard (m) are denoted n/m in this figure. 

E-145

September 2009 Draft - Do Not Quote or Cite
Figure E-36. Estimated Percent Reductions From the Current Standard to Alternative 

Standards in Cardiovascular Hospital Admissions Associated with Short-Term Exposure to 

PM2.5: Based on 2007 Air Quality Data* 

-90%

-80%

-70%

-60%

-50%

-40%

-30%

-20%

-10%

0%

10%

20%

30%

2007 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Reduction from Current Standard

 Atlanta, GA 41 (-27 - 108); 0.36% (-0.24% - 0.96%)

 Baltimore, MD 215 (158 - 271); 1.32% (0.97% - 1.67%)

 Birmingham, AL 17 (-11 - 46); 0.35% (-0.23% - 0.92%)

 Dallas, TX 27 (-18 - 72); 0.28% (-0.18% - 0.73%)

 Detroit, MI 215 (158 - 272); 1.04% (0.77% - 1.32%)

 Fresno, CA 24 (0 - 48); 0.5% (0.01% - 0.99%)

 Houston, TX 64 (-42 - 169); 0.36% (-0.23% - 0.94%)

 Los Angeles, CA 265 (3 - 526); 0.47% (0.01% - 0.93%)

 New York, NY 676 (496 - 855); 1.04% (0.76% - 1.31%)

 Philadelphia, PA 201 (148 - 254); 1.25% (0.92% - 1.58%)

 Phoenix, AZ 108 (1 - 215); 0.5% (0.01% - 0.99%)

 Pittsburgh, PA 120 (88 - 152); 0.96% (0.7% - 1.21%)

 Salt Lake City, UT 10 (0 - 20); 0.38% (0% - 0.75%)

 St. Louis, MO 176 (129 - 222); 1.25% (0.92% - 1.58%)

 Tacoma, WA 19 (-46 - 82); 0.52% (-1.28% - 2.26%)

*Based on Zanobetti and Schwartz (2009). The legend contains, for each urban area, the incidence estimate (and 95% 

CI) and the estimate of percent of total incidence (and 95% CI) under the current standards. 

**The current standards consist of an annual standard of 15 μg/m3

 and a daily standard of 35 μg/m3. Combinations of 

an annual standard (n) and a daily standard (m) are denoted n/m in this figure. 

E-146

September 2009 Draft - Do Not Quote or Cite
Table E-109. Estimated Annual Incidence of Hospital Admissions for Respiratory Illness Associated with Short-Term Ex

 Ambient PM2.5 Concentrations in a Recent Year (2005) and PM2.5 Concentrations that Just Meet the Current an

 Alternative Standards, Based on Adjusting 2005 PM2.5 Concentrations1

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

19 17 14 13 14 

(-23 - 60) (-21 - 55) (-18 - 47) (-17 - 43) (-18 - 47) 

21 20 17 16 17 

(-12 - 54) (-12 - 51) (-10 - 45) (-9 - 41) (-10 - 44) 

108 7 6 7 

(-13 - 32) (-10 - 25) (-8 - 21) (-8 - 20) (-8 - 21) 

14 14 14 13 14 

(-18 - 46) (-18 - 46) (-18 - 46) (-17 - 43) (-18 - 46) 

30 24 22 20 20 

(-17 - 76) (-14 - 62) (-13 - 57) (-12 - 52) (-12 - 53) 

26 14 14 14 12 

(6 - 45) (3 - 25) (3 - 25) (3 - 25) (3 - 21) 

29 27 23 21 23 

(-36 - 93) (-34 - 88) (-29 - 75) (-27 - 68) (-29 - 75) 

279 177 177 167 151 

(65 - 490) (41 - 311) (41 - 311) (39 - 293) (35 - 266) 

72 60 58 53 51 

(-42 - 185) (-35 - 154) (-34 - 150) (-31 - 138) (-30 - 132) 

18 17 16 14 14 

(-11 - 47) (-10 - 43) (-9 - 41) (-8 - 37) (-8 - 37) 

61 61 61 57 57 

(14 - 106) (14 - 106) (14 - 106) (13 - 101) (13 - 100) 

19 11 11 11 9 

(-11 - 49) (-6 - 28) (-6 - 28) (-6 - 28) (-5 - 24) 

106 6 6 5 

(2 - 18) (1 - 11) (1 - 11) (1 - 11) (1 - 10) 

27 24 21 19 21 

(-16 - 69) (-14 - 62) (-12 - 54) (-11 - 49) (-12 - 53) 

22222

(-34 - 37) (-27 - 30) (-27 - 30) (-27 - 30) (-23 - 26) 

Incidence of Hospital Admissions for Respiratory Illness Associated with Short-Term Exposure 

Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the Current and Alternative 

Daily (m) Standards (Standard Combination Denoted n/m):

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Incidence estimates were calculated using the appropriate regional concentration-response function estimates from models with a 2-day lag for respiratory 

admissions reported in Table 2 of Bell et al. (2008). Location-specific C-R function estimates were not available from this study.

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL Baltimore, MD Detroit, MI Houston, TX New York, NY St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT

E-147

September 2009 
Table E-110. Estimated Annual Incidence of Hospital Admissions for Respiratory Illness Associated with Short-Term Ex

 Ambient PM2.5 Concentrations in a Recent Year (2006) and PM2.5 Concentrations that Just Meet the Current an

 Standards, Based on Adjusting 2006 PM2.5 Concentrations1

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

18 17 14 13 14 

(-23 - 59) (-21 - 54) (-18 - 46) (-16 - 42) (-18 - 46) 

19 18 16 14 15 

(-11 - 49) (-11 - 46) (-9 - 41) (-9 - 37) (-9 - 40) 

108 6 6 6 

(-12 - 31) (-10 - 24) (-8 - 21) (-7 - 19) (-8 - 21) 

12 12 12 11 12 

(-15 - 40) (-15 - 40) (-15 - 40) (-14 - 37) (-15 - 40) 

25 20 18 17 17 

(-15 - 64) (-12 - 52) (-11 - 47) (-10 - 43) (-10 - 44) 

27 15 15 15 13 

(6 - 47) (3 - 26) (3 - 26) (3 - 26) (3 - 22) 

30 29 24 22 24 

(-38 - 98) (-36 - 93) (-31 - 79) (-28 - 72) (-31 - 79) 

263 166 166 157 142 

(61 - 462) (39 - 293) (39 - 293) (37 - 276) (33 - 250) 

66 55 54 49 47 

(-39 - 171) (-32 - 142) (-32 - 138) (-29 - 127) (-28 - 121) 

18 16 15 14 14 

(-10 - 46) (-10 - 42) (-9 - 39) (-8 - 36) (-8 - 36) 

64 64 64 61 60 

(15 - 113) (15 - 113) (15 - 113) (14 - 107) (14 - 106) 

17 10 10 10 8 

(-10 - 43) (-6 - 25) (-6 - 25) (-6 - 25) (-5 - 22) 

96665

(2 - 16) (1 - 10) (1 - 10) (1 - 10) (1 - 9) 

23 21 18 16 18 

(-13 - 59) (-12 - 53) (-10 - 46) (-10 - 42) (-10 - 45) 

22221

(-28 - 30) (-22 - 25) (-22 - 25) (-22 - 25) (-19 - 21) 

Incidence of Hospital Admissions for Respiratory Illness Associated with Short-Term Exposure 

Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the Current and Alternative 

Daily (m) Standards (Standard Combination Denoted n/m):

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Incidence estimates were calculated using the appropriate regional concentration-response function estimates from models with a 2-day lag for respiratory 

admissions reported in Table 2 of Bell et al. (2008). Location-specific C-R function estimates were not available from this study.

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL Baltimore, MD Detroit, MI Houston, TX New York, NY St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT

E-148

September 2009 
Table E-111. Estimated Annual Incidence of Hospital Admissions for Respiratory Illness Associated with Short-Term Ex

 Ambient PM2.5 Concentrations in a Recent Year (2007) and PM2.5 Concentrations that Just Meet the Current an

 Standards, Based on Adjusting 2007 PM2.5 Concentrations1

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

19 17 15 14 15 

(-24 - 61) (-22 - 56) (-19 - 48) (-17 - 44) (-19 - 48) 

18 17 15 14 15 

(-11 - 47) (-10 - 44) (-9 - 39) (-8 - 36) (-9 - 38) 

107 6 6 6 

(-12 - 31) (-9 - 24) (-8 - 21) (-7 - 19) (-8 - 21) 

13 13 13 12 13 

(-16 - 42) (-16 - 42) (-16 - 42) (-15 - 39) (-16 - 42) 

24 19 18 16 16 

(-14 - 61) (-11 - 49) (-10 - 45) (-9 - 42) (-10 - 42) 

29 16 16 16 14 

(7 - 51) (4 - 29) (4 - 29) (4 - 29) (3 - 24) 

30 29 24 22 24 

(-38 - 98) (-36 - 93) (-31 - 79) (-28 - 72) (-31 - 79) 

270 171 171 161 146 

(63 - 475) (40 - 301) (40 - 301) (38 - 284) (34 - 257) 

67 56 54 50 48 

(-40 - 173) (-33 - 144) (-32 - 140) (-29 - 129) (-28 - 123) 

18 16 15 14 14 

(-10 - 45) (-9 - 42) (-9 - 39) (-8 - 36) (-8 - 35) 

61 61 61 58 57 

(14 - 108) (14 - 108) (14 - 108) (14 - 103) (13 - 101) 

17 10 10 10 8 

(-10 - 43) (-6 - 25) (-6 - 25) (-6 - 25) (-5 - 22) 

117 7 7 6 

(3 - 20) (2 - 13) (2 - 13) (2 - 13) (1 - 11) 

24 21 18 17 18 

(-14 - 61) (-12 - 54) (-11 - 47) (-10 - 43) (-11 - 46) 

22222

(-30 - 33) (-24 - 27) (-24 - 27) (-24 - 27) (-21 - 23) 

 Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Detroit, MI Houston, TX New York, NY St. Louis, MO

Incidence of Hospital Admissions for Respiratory Illness Associated with Short-Term Exposure 

Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the Current and Alternative 

Daily (m) Standards (Standard Combination Denoted n/m):

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Incidence estimates were calculated using the appropriate regional concentration-response function estimates from models with a 2-day lag for respiratory 

admissions reported in Table 2 of Bell et al. (2008). Location-specific C-R function estimates were not available from this study.

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL Baltimore, MD

E-149

September 2009 
Table E-112. Estimated Percent of Total Annual Incidence of Hospital Admissions for Respiratory Illness Associated wit

 Exposure to Ambient PM2.5 Concentrations in a Recent Year (2005) and PM2.5 Concentrations that Just Meet th

 Alternative Standards, Based on Adjusting 2005 PM2.5 Concentrations1

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

0.5% 0.46% 0.39% 0.35% 0.39% 

(-0.63% - 1.6%) (-0.57% - 1.47%) (-0.49% - 1.25%) (-0.44% - 1.14%) (-0.49% - 1.25%) (

0.42% 0.4% 0.35% 0.32% 0.34% 

(-0.25% - 1.08%) (-0.23% - 1.02%) (-0.2% - 0.89%) (-0.19% - 0.82%) (-0.2% - 0.87%) (

0.56% 0.44% 0.37% 0.34% 0.37% 

(-0.71% - 1.82%) (-0.56% - 1.43%) (-0.47% - 1.21%) (-0.43% - 1.11%) (-0.47% - 1.21%) (

0.38% 0.38% 0.38% 0.35% 0.38% 

(-0.47% - 1.22%) (-0.47% - 1.22%) (-0.47% - 1.22%) (-0.44% - 1.13%) (-0.47% - 1.22%) (

0.42% 0.34% 0.31% 0.28% 0.29% 

(-0.25% - 1.07%) (-0.2% - 0.87%) (-0.18% - 0.8%) (-0.17% - 0.73%) (-0.17% - 0.74%) (

1.44% 0.79% 0.79% 0.79% 0.68% 

(0.34% - 2.51%) (0.19% - 1.4%) (0.19% - 1.4%) (0.19% - 1.4%) (0.16% - 1.19%) (

0.46% 0.44% 0.37% 0.34% 0.37% 

(-0.58% - 1.49%) (-0.55% - 1.41%) (-0.47% - 1.2%) (-0.42% - 1.09%) (-0.47% - 1.2%) (

1.41% 0.89% 0.89% 0.84% 0.76% 

(0.33% - 2.47%) (0.21% - 1.57%) (0.21% - 1.57%) (0.2% - 1.48%) (0.18% - 1.34%) (

0.36% 0.3% 0.29% 0.27% 0.25% 

(-0.21% - 0.92%) (-0.17% - 0.76%) (-0.17% - 0.74%) (-0.16% - 0.68%) (-0.15% - 0.65%) (

0.36% 0.33% 0.31% 0.29% 0.29% 

(-0.21% - 0.93%) (-0.2% - 0.86%) (-0.18% - 0.8%) (-0.17% - 0.74%) (-0.17% - 0.74%) (

0.93% 0.93% 0.93% 0.89% 0.87% 

(0.22% - 1.64%) (0.22% - 1.64%) (0.22% - 1.64%) (0.21% - 1.56%) (0.2% - 1.54%) (

0.47% 0.27% 0.27% 0.27% 0.23% 

(-0.28% - 1.21%) (-0.16% - 0.7%) (-0.16% - 0.7%) (-0.16% - 0.7%) (-0.14% - 0.6%) 

1.01% 0.64% 0.64% 0.64% 0.54% 

(0.24% - 1.77%) (0.15% - 1.12%) (0.15% - 1.12%) (0.15% - 1.12%) (0.13% - 0.96%) (

0.42% 0.37% 0.32% 0.3% 0.32% 

(-0.25% - 1.07%) (-0.22% - 0.96%) (-0.19% - 0.83%) (-0.17% - 0.76%) (-0.19% - 0.82%) (

0.2% 0.16% 0.16% 0.16% 0.14% 

(-2.72% - 2.97%) (-2.19% - 2.41%) (-2.19% - 2.41%) (-2.19% - 2.41%) (-1.87% - 2.07%) (

 Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Detroit, MI Houston, TX New York, NY St. Louis, MO

Percent of Total Incidence of Hospital Admissions for Respiratory Illness Associated with Short-Ter

PM2.5 Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the Current and Alte

(n) and Daily (m) Standards (Standard Combination Denoted n/m):

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Estimates were calculated using the appropriate regional concentration-response function estimates from models with a 2-day lag for respiratory hospital 

in Table 2 of Bell et al. (2008). Location-specific C-R function estimates were not available from this study.

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL Baltimore, MD

E-150

September 2009 
Table E-113. Estimated Percent of Total Annual Incidence of Hospital Admissions for Respiratory Illness Associated wit

 Exposure to Ambient PM2.5 Concentrations in a Recent Year (2006) and PM2.5 Concentrations that Just Meet th

 Alternative Standards, Based on Adjusting 2006 PM2.5 Concentrations1

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

0.47% 0.43% 0.37% 0.34% 0.37% 

(-0.6% - 1.53%) (-0.55% - 1.4%) (-0.46% - 1.19%) (-0.42% - 1.09%) (-0.46% - 1.19%) (-

0.38% 0.36% 0.31% 0.29% 0.31% 

(-0.22% - 0.98%) (-0.21% - 0.93%) (-0.19% - 0.81%) (-0.17% - 0.74%) (-0.18% - 0.79%) (-

0.54% 0.43% 0.36% 0.33% 0.36% 

(-0.69% - 1.76%) (-0.54% - 1.38%) (-0.46% - 1.17%) (-0.42% - 1.07%) (-0.46% - 1.17%) (-

0.32% 0.32% 0.32% 0.29% 0.32% 

(-0.4% - 1.03%) (-0.4% - 1.03%) (-0.4% - 1.03%) (-0.37% - 0.95%) (-0.4% - 1.03%) (-

0.35% 0.28% 0.26% 0.24% 0.24% 

(-0.21% - 0.9%) (-0.17% - 0.73%) (-0.15% - 0.67%) (-0.14% - 0.62%) (-0.14% - 0.62%) (-

1.49% 0.82% 0.82% 0.82% 0.7% 

(0.35% - 2.61%) (0.19% - 1.45%) (0.19% - 1.45%) (0.19% - 1.45%) (0.16% - 1.24%) (

0.47% 0.44% 0.38% 0.34% 0.38% 

(-0.59% - 1.51%) (-0.56% - 1.43%) (-0.47% - 1.22%) (-0.43% - 1.11%) (-0.47% - 1.22%) (-

1.3% 0.82% 0.82% 0.78% 0.7% 

(0.3% - 2.29%) (0.19% - 1.45%) (0.19% - 1.45%) (0.18% - 1.37%) (0.16% - 1.24%) (

0.32% 0.27% 0.26% 0.24% 0.23% 

(-0.19% - 0.84%) (-0.16% - 0.7%) (-0.15% - 0.68%) (-0.14% - 0.62%) (-0.14% - 0.59%) (-

0.36% 0.33% 0.31% 0.28% 0.28% 

(-0.21% - 0.92%) (-0.19% - 0.85%) (-0.18% - 0.8%) (-0.17% - 0.73%) (-0.17% - 0.73%) (

0.96% 0.96% 0.96% 0.91% 0.9% 

(0.22% - 1.68%) (0.22% - 1.68%) (0.22% - 1.68%) (0.21% - 1.6%) (0.21% - 1.58%) (

0.43% 0.25% 0.25% 0.25% 0.21% 

(-0.25% - 1.1%) (-0.15% - 0.64%) (-0.15% - 0.64%) (-0.15% - 0.64%) (-0.12% - 0.54%) (

0.9% 0.57% 0.57% 0.57% 0.48% 

(0.21% - 1.58%) (0.13% - 1%) (0.13% - 1%) (0.13% - 1%) (0.11% - 0.85%) (

0.36% 0.32% 0.28% 0.25% 0.27% 

(-0.21% - 0.92%) (-0.19% - 0.82%) (-0.16% - 0.71%) (-0.15% - 0.65%) (-0.16% - 0.7%) (-

0.16% 0.13% 0.13% 0.13% 0.11% 

(-2.18% - 2.39%) (-1.76% - 1.94%) (-1.76% - 1.94%) (-1.76% - 1.94%) (-1.49% - 1.66%) (-

 Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Detroit, MI Houston, TX New York, NY St. Louis, MO

Percent of Total Incidence of Hospital Admissions for Respiratory Illness Associated with Short-Ter

PM2.5 Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the Current and Alte

(n) and Daily (m) Standards (Standard Combination Denoted n/m):

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Estimates were calculated using the appropriate regional concentration-response function estimates from models with a 2-day lag for respiratory hospital a

in Table 2 of Bell et al. (2008). Location-specific C-R function estimates were not available from this study.

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL Baltimore, MD

E-151

September 2009 
Table E-114. Estimated Percent of Total Annual Incidence of Hospital Admissions for Respiratory Illness Associated wit

 Exposure to Ambient PM2.5 Concentrations in a Recent Year (2007) and PM2.5 Concentrations that Just Meet th

 Alternative Standards, Based on Adjusting 2007 PM2.5 Concentrations1

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

0.48% 0.44% 0.37% 0.34% 0.37% 

(-0.6% - 1.54%) (-0.55% - 1.42%) (-0.47% - 1.21%) (-0.43% - 1.1%) (-0.47% - 1.21%) (

0.37% 0.35% 0.3% 0.28% 0.3% 

(-0.22% - 0.94%) (-0.2% - 0.89%) (-0.18% - 0.78%) (-0.16% - 0.72%) (-0.17% - 0.76%) (

0.54% 0.42% 0.36% 0.32% 0.36% 

(-0.68% - 1.73%) (-0.53% - 1.36%) (-0.45% - 1.15%) (-0.41% - 1.05%) (-0.45% - 1.15%) (

0.33% 0.33% 0.33% 0.31% 0.33% 

(-0.42% - 1.08%) (-0.42% - 1.08%) (-0.42% - 1.08%) (-0.39% - 1%) (-0.42% - 1.08%) 

0.34% 0.27% 0.25% 0.23% 0.23% 

(-0.2% - 0.87%) (-0.16% - 0.7%) (-0.15% - 0.65%) (-0.14% - 0.59%) (-0.14% - 0.6%) 

1.6% 0.89% 0.89% 0.89% 0.76% 

(0.38% - 2.79%) (0.21% - 1.55%) (0.21% - 1.55%) (0.21% - 1.55%) (0.18% - 1.33%) 

0.46% 0.43% 0.37% 0.33% 0.37% 

(-0.57% - 1.47%) (-0.54% - 1.39%) (-0.46% - 1.18%) (-0.42% - 1.08%) (-0.46% - 1.18%) (

1.32% 0.83% 0.83% 0.79% 0.71% 

(0.31% - 2.31%) (0.19% - 1.47%) (0.19% - 1.47%) (0.18% - 1.38%) (0.17% - 1.25%) (

0.33% 0.27% 0.26% 0.24% 0.23% 

(-0.19% - 0.84%) (-0.16% - 0.7%) (-0.16% - 0.68%) (-0.14% - 0.63%) (-0.14% - 0.6%) 

0.36% 0.33% 0.31% 0.28% 0.28% 

(-0.21% - 0.92%) (-0.19% - 0.84%) (-0.18% - 0.79%) (-0.17% - 0.73%) (-0.16% - 0.72%) 

0.88% 0.88% 0.88% 0.84% 0.83% 

(0.21% - 1.55%) (0.21% - 1.55%) (0.21% - 1.55%) (0.2% - 1.47%) (0.19% - 1.45%) (

0.43% 0.25% 0.25% 0.25% 0.21% 

(-0.26% - 1.11%) (-0.15% - 0.64%) (-0.15% - 0.64%) (-0.15% - 0.64%) (-0.13% - 0.55%) 

1.06% 0.67% 0.67% 0.67% 0.57% 

(0.25% - 1.86%) (0.16% - 1.18%) (0.16% - 1.18%) (0.16% - 1.18%) (0.13% - 1.01%) (

0.37% 0.33% 0.28% 0.26% 0.28% 

(-0.22% - 0.94%) (-0.19% - 0.85%) (-0.17% - 0.73%) (-0.15% - 0.67%) (-0.16% - 0.72%) 

0.17% 0.14% 0.14% 0.14% 0.12% 

(-2.32% - 2.52%) (-1.87% - 2.05%) (-1.87% - 2.05%) (-1.87% - 2.05%) (-1.59% - 1.76%) (

Percent of Total Incidence of Hospital Admissions for Respiratory Illness Associated with Short-Ter

PM2.5 Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet the Current and Alte

(n) and Daily (m) Standards (Standard Combination Denoted n/m):

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Estimates were calculated using the appropriate regional concentration-response function estimates from models with a 2-day lag for respiratory hospital 

in Table 2 of Bell et al. (2008). Location-specific C-R function estimates were not available from this study.

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL Baltimore, MD Detroit, MI Houston, TX New York, NY St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT

E-152

September 2009 
Table E-115. Percent Reduction from the Current Standards: Estimated Annual Incidence of Respiratory Hospital Adm

 Associated with Short-Term Exposure to Ambient PM2.5 Concentrations, Based on Adjusting 2005 PM2.5 Conce

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

-9% 0% 15% 23% 15% 

(-9% - -9%) (0% - 0%) (15% - 15%) (22% - 23%) (15% - 15%) 

-6% 0% 13% 20% 15% 

(-6% - -6%) (0% - 0%) (13% - 13%) (20% - 20%) (15% - 15%) 

-28% 0% 15% 23% 15% 

(-28% - -28%) (0% - 0%) (15% - 15%) (22% - 23%) (15% - 15%) 

0% 0% 0% 7% 0% 

(0% - 0%) (0% - 0%) (0% - 0%) (7% - 7%) (0% - 0%) 

-23% 0% 8% 16% 15% 

(-23% - -23%) (0% - 0%) (8% - 8%) (16% - 16%) (15% - 15%) 

-81% 0% 0% 0% 15% 

(-80% - -82%) (0% - 0%) (0% - 0%) (0% - 0%) (14% - 15%) 

-6% 0% 15% 23% 15% 

(-6% - -6%) (0% - 0%) (15% - 15%) (22% - 23%) (15% - 15%) 

-58% 0% 0% 6% 15% 

(-58% - -58%) (0% - 0%) (0% - 0%) (6% - 6%) (15% - 15%) 

-20% 0% 3% 11% 15% 

(-20% - -20%) (0% - 0%) (3% - 3%) (10% - 11%) (15% - 15%) 

-9% 0% 6% 14% 15% 

(-9% - -9%) (0% - 0%) (6% - 7%) (14% - 14%) (15% - 15%) 

0% 0% 0% 5% 6% 

(0% - 0%) (0% - 0%) (0% - 0%) (5% - 5%) (6% - 6%) 

-73% 0% 0% 0% 15% 

(-73% - -73%) (0% - 0%) (0% - 0%) (0% - 0%) (15% - 15%) 

-58% 0% 0% 0% 15% 

(-58% - -59%) (0% - 0%) (0% - 0%) (0% - 0%) (15% - 15%) 

-12% 0% 13% 20% 15% 

(-12% - -12%) (0% - 0%) (13% - 13%) (20% - 20%) (15% - 15%) 

-23% 0% 0% 0% 15% 

(-23% - -24%) (0% - 0%) (0% - 0%) (0% - 0%) (14% - 15%) 

Percent Reduction from the Current Standards: Annual Incidence of Respiratory Hospital Admissions A

Short-Term Exposure to PM2.5 Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet 

Alternative Annual (n) and Daily (m) Standards (Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Estimates were calculated using the appropriate regional concentration-response function estimates from models with a 2-day lag for respiratory hospital 

in Table 2 of Bell et al. (2008). Location-specific C-R function estimates were not available from this study. Percents are rounded to the nearest whole nu

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

E-153

September 2009 
Table E-116. Percent Reduction from the Current Standards: Estimated Annual Incidence of Respiratory Hospital Adm

 Associated with Short-Term Exposure to Ambient PM2.5 Concentrations, Based on Adjusting 2006 PM2.5 Conce

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

-9% 0% 15% 23% 15% 

(-9% - -9%) (0% - 0%) (15% - 15%) (22% - 23%) (15% - 15%) 

-6% 0% 13% 20% 15% 

(-6% - -6%) (0% - 0%) (13% - 13%) (20% - 20%) (15% - 15%) 

-28% 0% 15% 23% 15% 

(-28% - -28%) (0% - 0%) (15% - 15%) (22% - 23%) (15% - 15%) 

0% 0% 0% 7% 0% 

(0% - 0%) (0% - 0%) (0% - 0%) (7% - 7%) (0% - 0%) 

-23% 0% 8% 16% 15% 

(-23% - -23%) (0% - 0%) (8% - 8%) (16% - 16%) (15% - 15%) 

-81% 0% 0% 0% 15% 

(-80% - -82%) (0% - 0%) (0% - 0%) (0% - 0%) (14% - 15%) 

-6% 0% 15% 23% 15% 

(-6% - -6%) (0% - 0%) (15% - 15%) (22% - 23%) (15% - 15%) 

-58% 0% 0% 6% 15% 

(-58% - -58%) (0% - 0%) (0% - 0%) (6% - 6%) (15% - 15%) 

-20% 0% 3% 11% 15% 

(-20% - -20%) (0% - 0%) (3% - 3%) (11% - 11%) (15% - 15%) 

-9% 0% 6% 14% 15% 

(-9% - -9%) (0% - 0%) (6% - 7%) (14% - 14%) (15% - 15%) 

0% 0% 0% 5% 6% 

(0% - 0%) (0% - 0%) (0% - 0%) (5% - 5%) (6% - 6%) 

-73% 0% 0% 0% 15% 

(-73% - -73%) (0% - 0%) (0% - 0%) (0% - 0%) (15% - 15%) 

-58% 0% 0% 0% 15% 

(-58% - -59%) (0% - 0%) (0% - 0%) (0% - 0%) (15% - 15%) 

-12% 0% 13% 20% 15% 

(-12% - -12%) (0% - 0%) (13% - 13%) (20% - 20%) (15% - 15%) 

-23% 0% 0% 0% 15% 

(-23% - -24%) (0% - 0%) (0% - 0%) (0% - 0%) (14% - 15%) 

Percent Reduction from the Current Standards: Annual Incidence of Respiratory Hospital Admissions A

Short-Term Exposure to PM2.5 Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet 

Alternative Annual (n) and Daily (m) Standards (Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Estimates were calculated using the appropriate regional concentration-response function estimates from models with a 2-day lag for respiratory hospital 

in Table 2 of Bell et al. (2008). Location-specific C-R function estimates were not available from this study. Percents are rounded to the nearest whole nu

 Dallas, TX Fresno, CA Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

E-154

September 2009 
Table E-117. Percent Reduction from the Current Standards: Estimated Annual Incidence of Respiratory Hospital Adm

 Associated with Short-Term Exposure to Ambient PM2.5 Concentrations, Based on Adjusting 2007 PM2.5 Conce

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13/30 

-9% 0% 15% 23% 15% 

(-9% - -9%) (0% - 0%) (15% - 15%) (22% - 23%) (15% - 15%) 

-6% 0% 13% 20% 15% 

(-6% - -6%) (0% - 0%) (13% - 13%) (20% - 20%) (15% - 15%) 

-28% 0% 15% 23% 15% 

(-28% - -28%) (0% - 0%) (15% - 15%) (22% - 23%) (15% - 15%) 

0% 0% 0% 7% 0% 

(0% - 0%) (0% - 0%) (0% - 0%) (7% - 7%) (0% - 0%) 

-23% 0% 8% 16% 15% 

(-23% - -23%) (0% - 0%) (8% - 8%) (16% - 16%) (15% - 15%) 

-81% 0% 0% 0% 15% 

(-80% - -82%) (0% - 0%) (0% - 0%) (0% - 0%) (14% - 15%) 

-6% 0% 15% 23% 15% 

(-6% - -6%) (0% - 0%) (15% - 15%) (22% - 23%) (15% - 15%) 

-58% 0% 0% 6% 15% 

(-58% - -58%) (0% - 0%) (0% - 0%) (6% - 6%) (15% - 15%) 

-20% 0% 3% 11% 15% 

(-20% - -20%) (0% - 0%) (3% - 3%) (11% - 11%) (15% - 15%) 

-9% 0% 6% 14% 15% 

(-9% - -9%) (0% - 0%) (6% - 7%) (14% - 14%) (15% - 15%) 

0% 0% 0% 5% 6% 

(0% - 0%) (0% - 0%) (0% - 0%) (5% - 5%) (6% - 6%) 

-73% 0% 0% 0% 15% 

(-73% - -73%) (0% - 0%) (0% - 0%) (0% - 0%) (15% - 15%) 

-58% 0% 0% 0% 15% 

(-58% - -59%) (0% - 0%) (0% - 0%) (0% - 0%) (15% - 15%) 

-12% 0% 13% 20% 15% 

(-12% - -12%) (0% - 0%) (13% - 13%) (20% - 20%) (15% - 15%) 

-23% 0% 0% 0% 15% 

(-23% - -24%) (0% - 0%) (0% - 0%) (0% - 0%) (14% - 15%) 

Risk Assessment 

Location

 Atlanta, GA Birmingham, AL New York, NY

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Estimates were calculated using the appropriate regional concentration-response function estimates from models with a 2-day lag for respiratory hospital 

in Table 2 of Bell et al. (2008). Location-specific C-R function estimates were not available from this study. Percents are rounded to the nearest whole nu

 Dallas, TX Fresno, CA Los Angeles, CA

Percent Reduction from the Current Standards: Annual Incidence of Respiratory Hospital Admissions A

Short-Term Exposure to PM2.5 Concentrations in a Recent Year and PM2.5 Concentrations that Just Meet 

Alternative Annual (n) and Daily (m) Standards (Standard Combination Denoted n/m):

 St. Louis, MO Tacoma, WA Philadelphia, PA Phoenix, AZ Pittsburgh, PA Salt Lake City, UT Baltimore, MD Detroit, MI Houston, TX

E-155

September 2009 
Figure E-37. Estimated Percent Reductions From the Current Standard to Alternative 

Standards in Respiratory Hospital Admissions Associated with Short-Term Exposure to 

PM2.5: Based on 2005 Air Quality Data* 

-90%

-80%

-70%

-60%

-50%

-40%

-30%

-20%

-10%

0%

10%

20%

30%

2005 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Reduction from Current Standard

 Atlanta, GA 17 (-21 - 55); 0.46% (-0.57% - 1.47%)

 Baltimore, MD 20 (-12 - 51); 0.4% (-0.23% - 1.02%)

 Birmingham, AL 8 (-10 - 25); 0.44% (-0.56% - 1.43%)

 Dallas, TX 14 (-18 - 46); 0.38% (-0.47% - 1.22%)

 Detroit, MI 24 (-14 - 62); 0.34% (-0.2% - 0.87%)

 Fresno, CA 14 (3 - 25); 0.79% (0.19% - 1.4%)

 Houston, TX 27 (-34 - 88); 0.44% (-0.55% - 1.41%)

 Los Angeles, CA 177 (41 - 311); 0.89% (0.21% - 1.57%)

 New York, NY 60 (-35 - 154); 0.3% (-0.17% - 0.76%)

 Philadelphia, PA 17 (-10 - 43); 0.33% (-0.2% - 0.86%)

 Phoenix, AZ 61 (14 - 106); 0.93% (0.22% - 1.64%)

 Pittsburgh, PA 11 (-6 - 28); 0.27% (-0.16% - 0.7%)

 Salt Lake City, UT 6 (1 - 11); 0.64% (0.15% - 1.12%)

 St. Louis, MO 24 (-14 - 62); 0.37% (-0.22% - 0.96%)

 Tacoma, WA 2 (-27 - 30); 0.16% (-2.19% - 2.41%)

*Based on Bell et al. (2008). The legend contains, for each urban area, the incidence estimate (and 95% CI) and the 

estimate of percent of total incidence (and 95% CI) under the current standards. 

**The current standards consist of an annual standard of 15 μg/m3

 and a daily standard of 35 μg/m3. Combinations of 

an annual standard (n) and a daily standard (m) are denoted n/m in this figure. 

E-156

September 2009 Draft - Do Not Quote or Cite
Figure E-38. Estimated Percent Reductions From the Current Standard to Alternative 

Standards in Respiratory Hospital Admissions Associated with Short-Term Exposure to 

PM2.5: Based on 2006 Air Quality Data* 

-90%

-80%

-70%

-60%

-50%

-40%

-30%

-20%

-10%

0%

10%

20%

30%

2006 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Reduction from Current Standard

 Atlanta, GA 17 (-21 - 54); 0.43% (-0.55% - 1.4%)

 Baltimore, MD 18 (-11 - 46); 0.36% (-0.21% - 0.93%)

 Birmingham, AL 8 (-10 - 24); 0.43% (-0.54% - 1.38%)

 Dallas, TX 12 (-15 - 40); 0.32% (-0.4% - 1.03%)

 Detroit, MI 20 (-12 - 52); 0.28% (-0.17% - 0.73%)

 Fresno, CA 15 (3 - 26); 0.82% (0.19% - 1.45%)

 Houston, TX 29 (-36 - 93); 0.44% (-0.56% - 1.43%)

 Los Angeles, CA 166 (39 - 293); 0.82% (0.19% - 1.45%)

 New York, NY 55 (-32 - 142); 0.27% (-0.16% - 0.7%)

 Philadelphia, PA 16 (-10 - 42); 0.33% (-0.19% - 0.85%)

 Phoenix, AZ 64 (15 - 113); 0.96% (0.22% - 1.68%)

 Pittsburgh, PA 10 (-6 - 25); 0.25% (-0.15% - 0.64%)

 Salt Lake City, UT 6 (1 - 10); 0.57% (0.13% - 1%)

 St. Louis, MO 21 (-12 - 53); 0.32% (-0.19% - 0.82%)

 Tacoma, WA 2 (-22 - 25); 0.13% (-1.76% - 1.94%)

*Based on Bell et al. (2008). The legend contains, for each urban area, the incidence estimate (and 95% CI) and the 

estimate of percent of total incidence (and 95% CI) under the current standards. 

**The current standards consist of an annual standard of 15 μg/m3

 and a daily standard of 35 μg/m3. Combinations of 

an annual standard (n) and a daily standard (m) are denoted n/m in this figure. 

E-157

September 2009 Draft - Do Not Quote or Cite
Figure E-39. Estimated Percent Reductions From the Current Standard to Alternative 

Standards in Respiratory Hospital Admissions Associated with Short-Term Exposure to 

PM2.5: Based on 2007 Air Quality Data* 

-90%

-80%

-70%

-60%

-50%

-40%

-30%

-20%

-10%

0%

10%

20%

30%

2007 air

quality

15/35** 13/35 12/35 13/30 12/25

Alternative Standard

Percent Reduction from Current Standard

 Atlanta, GA 17 (-22 - 56); 0.44% (-0.55% - 1.42%)

 Baltimore, MD 17 (-10 - 44); 0.35% (-0.2% - 0.89%)

 Birmingham, AL 7 (-9 - 24); 0.42% (-0.53% - 1.36%)

 Dallas, TX 13 (-16 - 42); 0.33% (-0.42% - 1.08%)

 Detroit, MI 19 (-11 - 49); 0.27% (-0.16% - 0.7%)

 Fresno, CA 16 (4 - 29); 0.89% (0.21% - 1.55%)

 Houston, TX 29 (-36 - 93); 0.43% (-0.54% - 1.39%)

 Los Angeles, CA 171 (40 - 301); 0.83% (0.19% - 1.47%)

 New York, NY 56 (-33 - 144); 0.27% (-0.16% - 0.7%)

 Philadelphia, PA 16 (-9 - 42); 0.33% (-0.19% - 0.84%)

 Phoenix, AZ 61 (14 - 108); 0.88% (0.21% - 1.55%)

 Pittsburgh, PA 10 (-6 - 25); 0.25% (-0.15% - 0.64%)

 Salt Lake City, UT 7 (2 - 13); 0.67% (0.16% - 1.18%)

 St. Louis, MO 21 (-12 - 54); 0.33% (-0.19% - 0.85%)

 Tacoma, WA 2 (-24 - 27); 0.14% (-1.87% - 2.05%)

*Based on Bell et al. (2008). The legend contains, for each urban area, the incidence estimate (and 95% CI) and the 

estimate of percent of total incidence (and 95% CI) under the current standards. 

**The current standards consist of an annual standard of 15 μg/m3

 and a daily standard of 35 μg/m3. Combinations of 

an annual standard (n) and a daily standard (m) are denoted n/m in this figure. 

E-158

September 2009 Draft - Do Not Quote or Cite
Table E-118. Estimated Annual Incidence of Emergency Room (ER) Visits Associated with Short-Term Exposure to Amb

 Concentrations in a Recent Year (2005) and PM2.5 Concentrations that Just Meet the Current and Alternative St

 Based on Adjusting 2005 PM2.5 Concentrations1

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13

215 197 167 153 1

(-302 - 722) (-277 - 663) (-235 - 564) (-214 - 514) (-235 

808 741 630 574 6

(-811 - 2400) (-743 - 2203) (-631 - 1875) (-575 - 1710) (-631 

1162 971 947 872 8

(743 - 1567) (620 - 1314) (604 - 1281) (556 - 1181) (531 

Asthma

Atlanta, GA Cardiovascular illness

Atlanta, GA Respiratory illness Tolbert et al. (2007)

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Numbers rounded to the nearest whole number.

Study

 Tolbert et al. (2007) Ito et al. (2007)

Location ER Visit for:

Incidence of ER Visits Associated with Short-Term Exposure to PM2.5 Con

Year and PM2.5 Concentrations that Just Meet the Current and Alternativ

(m) Standards (Standard Combination Denoted n/m

New York, NY

E-159

September 2009 
Table E-119. Estimated Annual Incidence of Emergency Room (ER) Visits Associated with Short-Term Exposure to Ambie

 Concentrations in a Recent Year (2006) and PM2.5 Concentrations that Just Meet the Current and Alternative Stan

 Adjusting 2006 PM2.5 Concentrations1

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13

212 195 165 151 1

(-298 - 713) (-274 - 655) (-232 - 557) (-212 - 508) (-232 

798 732 622 567 6

(-800 - 2373) (-734 - 2178) (-623 - 1853) (-568 - 1690) (-623 

991 828 807 743 7

(633 - 1340) (528 - 1122) (515 - 1094) (473 - 1008) (452 

Asthma

Atlanta, GA Cardiovascular illness

Atlanta, GA Respiratory illness

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 

 Tolbert et al. (2007)

1Numbers rounded to the nearest whole number.

Study

 Tolbert et al. (2007) Ito et al. (2007)

Location ER Visit for:

Incidence of ER Visits Associated with Short-Term Exposure to PM2.5 Con

Year and PM2.5 Concentrations that Just Meet the Current and Alternative 

Standards (Standard Combination Denoted n/m):

New York, NY

E-160

September 2009 
Table E-120. Estimated Annual Incidence of Emergency Room (ER) Visits Associated with Short-Term Exposure to Amb

 Concentrations in a Recent Year (2007) and PM2.5 Concentrations that Just Meet the Current and Alternative St

 Adjusting 2007 PM2.5 Concentrations1

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13

220 202 171 156 1

(-310 - 739) (-284 - 678) (-241 - 577) (-219 - 527) (-241 

827 759 645 588 6

(-830 - 2457) (-761 - 2256) (-646 - 1920) (-589 - 1751) (-646 

1114 931 907 836 7

(712 - 1504) (594 - 1260) (579 - 1229) (532 - 1133) (509 

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 

 Tolbert et al. (2007)

1Numbers rounded to the nearest whole number.

Study

 Tolbert et al. (2007) Ito et al. (2007)

Location ER Visit for:

Incidence of ER Visits Associated with Short-Term Exposure to PM2.5 

Recent Year and PM2.5 Concentrations that Just Meet the Current and Al

Daily (m) Standards (Standard Combination Denoted 

New York, NY Asthma

Atlanta, GA Cardiovascular illness

Atlanta, GA Respiratory illness

E-161

September 2009 
Table E-121. Estimated Percent of Total Annual Incidence of Emergency Room (ER) Visits Associated with Short-Term E

 to Ambient PM2.5 Concentrations in a Recent Year (2005) and PM2.5 Concentrations that Just Meet the Current 

 Standards, Based on Adjusting 2005 PM2.5 Concentrations1

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13

0.6% 0.6% 0.5% 0.5% 0.

(-0.9% - 2.2%) (-0.8% - 2%) (-0.7% - 1.7%) (-0.6% - 1.5%) (-0.7% 

0.6% 0.6% 0.5% 0.5% 0.

(-0.6% - 1.9%) (-0.6% - 1.8%) (-0.5% - 1.5%) (-0.5% - 1.4%) (-0.5% 

6.5% 5.5% 5.3% 4.9% 4.

(4.2% - 8.8%) (3.5% - 7.4%) (3.4% - 7.2%) (3.1% - 6.7%) (3% - 

Percent of Total Incidence of ER Visits Associated with Short-Term 

Concentrations in a Recent Year and PM2.5 Concentrations that Just M

Alternative Annual (n) and Daily (m) Standards (Standard Combinat

 Tolbert et al. (2007)

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Percents rounded to the nearest tenth.

Study

 Tolbert et al. (2007) Ito et al. (2007)

Location ER Visit for:

New York, NY Asthma

Atlanta, GA Cardiovascular illness

Atlanta, GA Respiratory illness

E-162

September 2009 
Table E-122. Estimated Percent of Total Annual Incidence of Emergency Room (ER) Visits Associated with Short-Term E

 PM2.5 Concentrations in a Recent Year (2006) and PM2.5 Concentrations that Just Meet the Current and Alternat

 Based on Adjusting 2006 PM2.5 Concentrations1

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13

0.6% 0.6% 0.5% 0.4% 0

(-0.9% - 2.1%) (-0.8% - 1.9%) (-0.7% - 1.6%) (-0.6% - 1.5%) (-0.7% 

0.6% 0.6% 0.5% 0.4% 0

(-0.6% - 1.8%) (-0.6% - 1.7%) (-0.5% - 1.4%) (-0.4% - 1.3%) (-0.5% 

5.6% 4.7% 4.5% 4.2% 4

(3.6% - 7.5%) (3% - 6.3%) (2.9% - 6.1%) (2.7% - 5.7%) (2.5% 

Percent of Total Incidence of ER Visits Associated with Short-Term 

Concentrations in a Recent Year and PM2.5 Concentrations that Just M

Alternative Annual (n) and Daily (m) Standards (Standard Combinat

 Tolbert et al. (2007)

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Percents rounded to the nearest tenth.

Study

 Tolbert et al. (2007) Ito et al. (2007)

Location ER Visit for:

New York, NY Asthma

Atlanta, GA Cardiovascular illness

Atlanta, GA Respiratory illness

E-163

September 2009 
Table E-123. Estimated Percent of Total Annual Incidence of Emergency Room (ER) Visits Associated with Short-Term E

 Ambient PM2.5 Concentrations in a Recent Year (2007) and PM2.5 Concentrations that Just Meet the Current and 

 Standards, Based on Adjusting 2007 PM2.5 Concentrations1

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13

0.6% 0.6% 0.5% 0.4% 0

(-0.9% - 2.1%) (-0.8% - 1.9%) (-0.7% - 1.6%) (-0.6% - 1.5%) (-0.7% 

0.6% 0.6% 0.5% 0.4% 0

(-0.6% - 1.8%) (-0.6% - 1.7%) (-0.5% - 1.4%) (-0.4% - 1.3%) (-0.5% 

6.2% 5.2% 5.1% 4.7% 4

(4% - 8.4%) (3.3% - 7%) (3.2% - 6.9%) (3% - 6.3%) (2.8% 

Asthma

Atlanta, GA Cardiovascular illnessAtlanta, GA Respiratory illness

Percent of Total Incidence of ER Visits Associated with Short-Term 

Concentrations in a Recent Year and PM2.5 Concentrations that Just M

Alternative Annual (n) and Daily (m) Standards (Standard Combinat

 Tolbert et al. (2007)

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Percents rounded to the nearest tenth.

Study

 Tolbert et al. (2007) Ito et al. (2007)

Location ER Visit for:

New York, NY

E-164

September 2009 
APPENDIX F: SENSITIVITY ANALYSIS RESULTS 

F-1

September 2009 Draft - Do Not Quote or Cite
1 Appendix F. Sensitivity Analysis Results 

2 

3 

4 

5 

6 

7 

8 

9 

10 

11 

12 

13 

14 

15 

16 

This Appendix provides detailed results of the single- and multi-factor sensitivity 

analyses completed as part of this risk analysis. For additional detail on the sensitivity analysis 

results completed for this analysis, as well as the types of results generated, see section 4.3. 

We have identified an error in the approach used to simulate ambient PM2.5 levels for the 

Pittsburgh study area for the scenarios involving just meeting the current and alternative sets of 

standards. Sensitivity analyses involving the Pittsburgh study area (focusing on the impact of 

using the alternative hybrid rollback approach – see section 3.5.4) involved the current and 

alternative sets of standard levels and consequently, these sensitivity analyses results are 

impacted. However, there was insufficient time after identifying this error to either generate 

corrected risk estimates or remove the erroneous risk estimates from the summary tables 

presented in this Appendix. We will correct this error and release updated results for the 

Pittsburgh study area as soon as is practicable and will include the corrected results in the next 

version of this document. Note, that this error does not impact sensitivity analysis results for any 

of the other urban study areas. 

F-2

September 2009 Draft - Do Not Quote or Cite
Table F-1. Sensitivity Analysis: Impact of Using Different Model Choices to Estimate the Incidence of Mortality Associate

 Exposure to PM2.5 Concentrations that Just Meet the Current Standards, Based on Adjusting 2005 PM2.5 Concen

Standard Fixed 

Effects Log-Linear 

(Cox Proportional 

Hazard) Model3

Random Effects LogLinear Model 4 Random Effects Log- Log Model 5 Fixed Effects vs. Random Effects Log

Linear Models 

1432 1767 3526

(911 - 1948) (824 - 2694) (2179 - 4841)

1626 2694

(1270 - 1977) (1794 - 3563)

1330 1486 2652

(1083 - 1572) (903 - 2044) (1878 - 3376)

174 322

(76 - 269) (168 - 467)

547 674 1201

(349 - 743) (316 - 1023) (745 - 1641)

512 757

(401 - 620) (507 - 996)

347 387 614

(284 - 409) (238 - 527) (439 - 774)

83 137

(37 - 127) (72 - 196)

6Calculated as (core analysis model estimate - alternative model estimate)/(core analysis model estimate.)5Estimates based on Table 11, "MSA and DIFF" rows, in Krewski et al. (2009) -- exposure period from 1999 - 2000. 7Estimates for cardiopulmonary mortality and lung cancer mortality were not available for the random effects log-linear model.1The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 2Mortality incidence was estimated for PM2.5 concentrations down to the lowest measured level in the study (5.8 ug/m3).3Estimates Based on Krewski et al. (2009), exposure period from 1999 - 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in 4Estimates based on Table 9. Autocorrelation at MSA and ZCA levels; MSA & DIFF, in Krewski et al. (2009) -- exposure period from 1999 - 2000. 

 Ischemic Heart Disease Mortality 12%  Lung Cancer Mortality --- ---  Cardiopulmonary Mortality --- --- 

Philadelphia, PA

 All Cause Mortality 23% 

 Ischemic Heart Disease Mortality 12%  Lung Cancer Mortality --- ---  All Cause Mortality 23%  Cardiopulmonary Mortality --- 7 --- 

Health Endpoint

Incidence of Mortality Associated with Long-Term Exposure to 

PM2.5 Concentrations Using:2 Percent 

Los Angeles, CA

F-3

September 2009 
Table F-2. Sensitivity Analysis: Impact of Using Different Model Choices to Estimate the Incidence of Mortality Associated 

 Exposure to PM2.5 Concentrations that Just Meet the Current Standards, Based on Adjusting 2006 PM2.5 Concentr

Standard Fixed 

Effects Log-Linear 

(Cox Proportional 

Hazard) Model3

Random Effects LogLinear Model 4 Random Effects Log- Log Model 5 Fixed Effects vs. Random Effects Log

Linear Models 

1221 1507 3130

(776 - 1662) (702 - 2300) (1931 - 4303)

1390 2396

(1084 - 1692) (1592 - 3176)

1140 1275 2374

(927 - 1349) (772 - 1760) (1675 - 3034)

149 286

(65 - 231) (149 - 417)

536 660 1182

(341 - 727) (309 - 1002) (733 - 1617)

501 746

(393 - 608) (500 - 982)

340 380 606

(279 - 401) (233 - 517) (433 - 764)

81 134

(36 - 125) (71 - 194)

6Calculated as (core analysis model estimate - alternative model estimate)/(core analysis model estimate.)

Health Endpoint

Incidence of Mortality Associated with Long-Term Exposure to 

PM2.5 Concentrations Using:2 Percent 

Los Angeles, CA

 All Cause Mortality 23% 

 Cardiopulmonary Mortality --- 7 ---  Ischemic Heart Disease Mortality 12%  Lung Cancer Mortality --- --- 

Philadelphia, PA

 All Cause Mortality 23% 

 Cardiopulmonary Mortality --- ---  Ischemic Heart Disease Mortality 12%  Lung Cancer Mortality --- --- 

5Estimates based on Table 11, "MSA and DIFF" rows, in Krewski et al. (2009) -- exposure period from 1999 - 2000. 7Estimates for cardiopulmonary mortality and lung cancer mortality were not available for the random effects log-linear model.1The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 2Mortality incidence was estimated for PM2.5 concentrations down to the lowest measured level in the study (5.8 ug/m3).3Estimates Based on Krewski et al. (2009), exposure period from 1999 - 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Kre4Estimates based on Table 9. Autocorrelation at MSA and ZCA levels; MSA & DIFF, in Krewski et al. (2009) -- exposure period from 1999 - 2000. 

F-4

September 2009 
Table F-3. Sensitivity Analysis: Impact of Using Different Model Choices to Estimate the Incidence of Mortality Associate

 Exposure to PM2.5 Concentrations that Just Meet the Current Standards, Based on Adjusting 2007 PM2.5 Concen

Standard Fixed 

Effects Log-Linear 

(Cox Proportional 

Hazard) Model3

Random Effects LogLinear Model 4 Random Effects Log- Log Model 5 Fixed Effects vs. Random Effects Log

Linear Models 

1257 1552 3206

(799 - 1711) (723 - 2368) (1979 - 4407)

1431 2454

(1116 - 1741) (1631 - 3251)

1173 1312 2429

(954 - 1388) (795 - 1810) (1715 - 3102)

153 293

(67 - 238) (153 - 427)

530 653 1174

(338 - 719) (305 - 991) (728 - 1605)

496 741

(388 - 601) (496 - 975)

337 376 602

(276 - 397) (230 - 512) (430 - 759)

80 134

(35 - 123) (70 - 192)

6Calculated as (core analysis model estimate - alternative model estimate)/(core analysis model estimate.)

Health Endpoint

---

4Estimates based on Table 9. Autocorrelation at MSA and ZCA levels; MSA & DIFF, in Krewski et al. (2009) -- exposure period from 1999 - 2000. 7Estimates for cardiopulmonary mortality and lung cancer mortality were not available for the random effects log-linear model.

--- 7

---------

12%

---

Philadelphia, PA

--- 

Incidence of Mortality Associated with Long-Term Exposure to 

PM2.5 Concentrations Using:2

Los Angeles, CA

 Cardiopulmonary Mortality ---

Percent 

23%12%

5Estimates based on Table 11, "MSA and DIFF" rows, in Krewski et al. (2009) -- exposure period from 1999 - 2000. 3Estimates Based on Krewski et al. (2009), exposure period from 1999 - 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in 1The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 

 All Cause Mortality Ischemic Heart Disease Mortality

2Mortality incidence was estimated for PM2.5 concentrations down to the lowest measured level in the study (5.8 ug/m3).

 Lung Cancer Mortality

23%

 All Cause Mortality Cardiopulmonary Mortality Ischemic Heart Disease Mortality Lung Cancer Mortality

F-5

September 2009 
Table F-4. Sensitivity Analysis: Impact of Limiting Estimated Annual Incidence of All-Cause Mortality 

 Associated with Long-Term Exposure to PM2.5 Concentrations that Just Meet the Current 

 Standards to the Lowest Measured Level in the Study vs. to PRB, Based on Adjusting 2005 

 PM2.5 Concentrations1, 2

Lowest Measured Level in 

Study (5.8 ug/m3) Estimated PRB

732 1053

(468 - 992) (676 - 1421)

696 1067

(444 - 942) (685 - 1437)

451 660

(288 - 611) (423 - 891)

469 746

(299 - 637) (477 - 1009)

697 1160

(445 - 946) (744 - 1566)

110 258

(70 - 150) (165 - 350)

849 1247

(542 - 1151) (800 - 1683)

1432 2934

(911 - 1948) (1876 - 3972)

1600 3012

(1019 - 2174) (1928 - 4073)

547 935

(349 - 743) (599 - 1262)

611 1247

(389 - 831) (797 - 1687)

366 732

(233 - 498) (468 - 991)

54 177

(34 - 74) (113 - 240)

857 1342

(547 - 1161) (861 - 1810)

101 232

(64 - 138) (148 - 314)

3

 Calculated as (mortality estimated down to PRB - mortality estimated down to LML)/(mortality estimated down to LML).

66%

135%

47%

105%

44%

53%

46%

 Dallas, TX 59%

 Fresno, CA

 Los Angeles, CA

Risk Assessment Location

 Atlanta, GA

 Birmingham, AL

 Houston, TX

 New York, NY

2

The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 

1

Estimates based on Table 33 in Krewski et al. (2009) -- exposure period from 1999 - 2000, follow-up through 2000, models with 44 individual 

and 7 ecological covariates. 

88%

71%

104%

100%

228%

57%

130%

Incidence of All Cause Mortality Associated with LongTerm Exposure to PM2.5 Concentrations Measured 

Down to: Percent Difference3

 St. Louis, MO

 Tacoma, WA

 Philadelphia, PA

 Phoenix, AZ

 Pittsburgh, PA

 Salt Lake City, UT

 Baltimore, MD

 Detroit, MI

F-6

September 2009 Draft - Do Not Quote or Cite
Table F-5. Sensitivity Analysis: Impact of Limiting Estimated Annual Incidence of Ischemic Heart Disease 

 Mortality Associated with Long-Term Exposure to PM2.5 Concentrations that Just Meet the Current 

 Standards to the Lowest Measured Level in the Study vs. to PRB, Based on Adjusting 2006 PM2.5 

 Concentrations1, 2 

Lowest Measured Level in 

Study (5.8 ug/m3

) Estimated PRB

269 383

(221 - 315) (317 - 446)

399 622

(327 - 468) (515 - 723)

190 274

(156 - 223) (227 - 319)

220 382

(179 - 260) (314 - 447)

447 827

(365 - 528) (681 - 967)

91 198

(74 - 108) (162 - 232)

534 754

(438 - 626) (624 - 877)

1140 2459

(927 - 1349) (2020 - 2882)

1785 3546

(1454 - 2110) (2918 - 4149)

340 564

(279 - 401) (466 - 657)

479 915

(391 - 566) (753 - 1069)

224 482

(183 - 266) (396 - 565)

14 63

(11 - 17) (51 - 74)

507 858

(415 - 597) (708 - 1001)

43 140

(35 - 51) (114 - 165)

3

 Calculated as (IHD mortality estimated down to PRB - IHD mortality estimated down to LML)/(IHD mortality estimated down to LML).

Risk Assessment Location

 Atlanta, GA

 Birmingham, AL 44%

 Baltimore, MD

Incidence of Ischemic Heart Disease Mortality 

Associated with Long-Term Exposure to PM2.5 

Concentrations Measured Down to: Percent Difference3

42%

56%

2

The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 

1

Estimates based on Table 33 in Krewski et al. (2009) -- exposure period from 1999 - 2000, follow-up through 2000, models with 44 individual 

and 7 ecological covariates. 

 Dallas, TX

 Fresno, CA

 Los Angeles, CA

74%

 Detroit, MI

 Houston, TX

 New York, NY

 St. Louis, MO

 Tacoma, WA

 Philadelphia, PA

 Phoenix, AZ

 Pittsburgh, PA

 Salt Lake City, UT

85%

118%

41%

116%

350%

69%

226%

99%

66%

91%

115%

F-7

September 2009 Draft - Do Not Quote or Cite
Table F-6. Sensitivity Analysis: Impact of Limiting Estimated Annual Incidence of All-Cause Mortality 

 Associated with Long-Term Exposure to PM2.5 Concentrations that Just Meet the Current 

 Standards to the Lowest Measured Level in the Study vs. to PRB, Based on Adjusting 2007 

 PM2.5 Concentrations1, 2

Lowest Measured Level in 

Study (5.8 ug/m3) Estimated PRB

731 1071

(467 - 990) (687 - 1446)

563 937

(359 - 764) (601 - 1265)

429 643

(274 - 581) (412 - 869)

399 689

(254 - 542) (440 - 932)

469 934

(299 - 638) (598 - 1265)

144 296

(92 - 196) (189 - 401)

880 1300

(562 - 1193) (834 - 1755)

1257 2783

(799 - 1711) (1778 - 3770)

1370 2813

(871 - 1863) (1799 - 3807)

530 917

(338 - 719) (588 - 1239)

580 1262

(369 - 789) (807 - 1709)

303 667

(193 - 413) (426 - 904)

67 197

(43 - 91) (126 - 268)

698 1191

(445 - 948) (763 - 1609)

69 205

(44 - 94) (131 - 278)

3

 Calculated as (mortality estimated down to PRB - mortality estimated down to LML)/(mortality estimated down to LML).

99%

106%

48%

121%

47%

66%

50%

 Dallas, TX 73%

 Fresno, CA

 Los Angeles, CA

Risk Assessment Location

 Atlanta, GA

 Birmingham, AL

 Houston, TX

 New York, NY

2

The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 

1

Estimates based on Table 33 in Krewski et al. (2009) -- exposure period from 1999 - 2000, follow-up through 2000, models with 44 individual 

and 7 ecological covariates. 

105%

73%

118%

120%

194%

71%

197%

Incidence of All Cause Mortality Associated with LongTerm Exposure to PM2.5 Concentrations Measured 

Down to: Percent Difference3

 St. Louis, MO

 Tacoma, WA

 Philadelphia, PA

 Phoenix, AZ

 Pittsburgh, PA

 Salt Lake City, UT

 Baltimore, MD

 Detroit, MI

F-8

September 2009 Draft - Do Not Quote or Cite
Table F-7. Sensitivity Analysis: Impact of Using a Different Study to Estimate the Incidence of Mortality 

 Associated with Long-Term Exposure to PM2.5 Concentrations that Just Meet the Current 

 Standards, Based on Adjusting 2005 PM2.5 Concentrations1

Krewski et al. (2009)3 Krewski et al. (2000)4

1432 1072

(911 - 1948) (-1096 - 3160)

1626 718

(1270 - 1977) (-726 - 2089)

174 -162

(76 - 269) (-604 - 227)

547 410

(349 - 743) (-423 - 1198)

512 228

(401 - 620) (-233 - 655)

83 -79

(37 - 127) (-306 - 107)

-56%

-193%

2

Mortality incidence was estimated for PM2.5 concentrations down to the lowest measured level in Krewski et al., 2009 (5.8 ug/m3).

5

Calculated as (Krewski et al. (2000) estimate - Krewski et al. (2009) estimate)/(Krewski et al. (2009) estimate).

4

Estimates based on Table 21b in Krewski et al. (2000) [reanalysis of Six Cities Study].

3

Estimates Based on Krewski et al. (2009), exposure period from 1999 - 2000, using models with 44 individual and 7 ecological covariates 

(see Table 33 in Krewski et al., 2009).

1

The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 

-195%

Incidence of Mortality Associated with Long-Term 

Exposure to PM2.5 Concentrations Using:2

Percent Difference5

-25%

-55%

-25%

Los Angeles, CA

 Cardiopulmonary Mortality

Philadelphia, PA

Health Endpoint

 All Cause Mortality

 All Cause Mortality

 Cardiopulmonary Mortality

 Lung Cancer Mortality

 Lung Cancer Mortality

F-9

September 2009 Draft - Do Not Quote or Cite
Table F-8. Sensitivity Analysis: Impact of Using a Different Study to Estimate the Incidence of Mortality 

 Associated with Long-Term Exposure to PM2.5 Concentrations that Just Meet the Current 

 Standards, Based on Adjusting 2006 PM2.5 Concentrations1

Krewski et al. (2009)3 Krewski et al. (2000)4

1221 914

(776 - 1662) (-931 - 2700)

1390 612

(1084 - 1692) (-616 - 1787)

149 -137

(65 - 231) (-507 - 194)

536 402

(341 - 727) (-414 - 1173)

501 223

(393 - 608) (-228 - 641)

81 -77

(36 - 125) (-299 - 105)

 All Cause Mortality

 Cardiopulmonary Mortality

 Lung Cancer Mortality

 Lung Cancer Mortality

Incidence of Mortality Associated with Long-Term 

Exposure to PM2.5 Concentrations Using:2

Percent Difference5

-25%

-55%

-25%

Los Angeles, CA

 Cardiopulmonary Mortality

Philadelphia, PA

Health Endpoint

 All Cause Mortality

-56%

-192%

2

Mortality incidence was estimated for PM2.5 concentrations down to the lowest measured level in Krewski et al., 2009 (5.8 ug/m3).

5

Calculated as (Krewski et al. (2000) estimate - Krewski et al. (2009) estimate)/(Krewski et al. (2009) estimate).

4

Estimates based on Table 21b in Krewski et al. (2000) [reanalysis of Six Cities Study].

3

Estimates Based on Krewski et al. (2009), exposure period from 1999 - 2000, using models with 44 individual and 7 ecological covariates 

(see Table 33 in Krewski et al., 2009).

1

The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 

-195%

F-10

September 2009 Draft - Do Not Quote or Cite
Table F-9. Sensitivity Analysis: Impact of Using a Different Study to Estimate the Incidence of Mortality 

 Associated with Long-Term Exposure to PM2.5 Concentrations that Just Meet the Current 

 Standards, Based on Adjusting 2007 PM2.5 Concentrations1

Krewski et al. (2009)3 Krewski et al. (2000)4

1257 941

(799 - 1711) (-959 - 2780)

1431 630

(1116 - 1741) (-635 - 1840)

153 -141

(67 - 238) (-523 - 200)

530 397

(338 - 719) (-410 - 1160)

496 221

(388 - 601) (-226 - 635)

80 -76

(35 - 123) (-295 - 104)

-56%

-192%

2

Mortality incidence was estimated for PM2.5 concentrations down to the lowest measured level in Krewski et al., 2009 (5.8 ug/m3).

5

Calculated as (Krewski et al. (2000) estimate - Krewski et al. (2009) estimate)/(Krewski et al. (2009) estimate).

4

Estimates based on Table 21b in Krewski et al. (2000) [reanalysis of Six Cities Study].

3

Estimates Based on Krewski et al. (2009), exposure period from 1999 - 2000, using models with 44 individual and 7 ecological covariates 

(see Table 33 in Krewski et al., 2009).

1

The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 

-195%

Incidence of Mortality Associated with Long-Term 

Exposure to PM2.5 Concentrations Using:2

Percent Difference5

-25%

-55%

-25%

Los Angeles, CA

 Cardiopulmonary Mortality

Philadelphia, PA

Health Endpoint

 All Cause Mortality

 All Cause Mortality

 Cardiopulmonary Mortality

 Lung Cancer Mortality

 Lung Cancer Mortality

F-11

September 2009 Draft - Do Not Quote or Cite
Table F-10. Sensitivity Analysis: Estimated Annual Incidence of All Cause Mortality Associated with Long-Term Exposur

 Concentrations that Just Meet the Current and Alternative Standards, Based on Adjusting 2005 PM2.5 Concentra

 Comparison of Proportional and Hybrid Rollback Methods1

15/35 2 13/35 12/35 13/30 

Proportional 696 561 485 541 

(444 - 942) (358 - 761) (309 - 659) (345 - 734) (

Hybrid 687 586 508 534 

(439 - 931) (374 - 795) (324 - 690) (340 - 724) (

Percent Difference 3 -1% 4% 5% -1% 

Proportional 451 352 302 352 

(288 - 611) (224 - 478) (193 - 411) (224 - 478) (

Hybrid 452 353 304 353 

(289 - 613) (225 - 480) (193 - 412) (225 - 480) (

Percent Difference 0% 0% 1% 0% 

Proportional 697 601 514 528 

(445 - 946) (383 - 817) (327 - 698) (336 - 717) (

Hybrid 738 716 620 563 

(471 - 1001) (457 - 972) (395 - 841) (358 - 765) (

Percent Difference 6% 19% 21% 7% 

Proportional 1432 1432 1265 1001 

(911 - 1948) (911 - 1948) (804 - 1722) (636 - 1363) (

Hybrid 1775 1698 1435 1296 

(1131 - 2412) (1081 - 2308) (913 - 1952) (824 - 1764) (5

Percent Difference 24% 19% 13% 29% 

Proportional 1600 1521 1282 1159 

(1019 - 2174) (969 - 2068) (815 - 1744) (737 - 1578) (

Hybrid 1650 1518 1278 1202 

(1051 - 2242) (966 - 2063) (813 - 1739) (765 - 1637) (4

Percent Difference 3% 0% 0% 4% 

Proportional 366 366 366 259 

(233 - 498) (233 - 498) (233 - 498) (164 - 352) 

Hybrid 518 487 417 389 

(330 - 703) (310 - 661) (266 - 567) (248 - 530) (

Percent Difference 42% 33% 14% 50% 

Proportional 857 679 583 661 

(547 - 1161) (433 - 922) (371 - 792) (421 - 897) (

Hybrid 930 732 631 732 

(594 - 1260) (467 - 993) (402 - 858) (467 - 993) (

Percent Difference 9% 8% 8% 11% 

3 Calculated as (mortality based on hybrid rollbacks - mortality based on proportional rollbacks)/(mortality based on proportional rollbacks).

 Los Angeles, CA

 New York, NY

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 

Incidence of All Cause Mortality Associated with Long-Term Exposure to PM2.5 Con

that Just Meet the Current and Alternative Combinations of Annual (n) and Daily (m

Type of Rollback (Standard Combination Denoted n/m):

1Estimates Based on Krewski et al. (2009), exposure period from 1999 - 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Kr

2009).

Risk Assessment 

Location

 Pittsburgh, PA

 St. Louis, MO

 Baltimore, MD

 Birmingham, AL

 Detroit, MI

F-12

September 2009 
Table F-11. Sensitivity Analysis: Estimated Annual Incidence of All Cause Mortality Associated with Long-Term Exposur

 Concentrations that Just Meet the Current and Alternative Standards, Based on Adjusting 2006 PM2.5 Concentra

 Comparison of Proportional and Hybrid Rollback Methods1

15/35 2 13/35 12/35 13/30 

Proportional 603 479 409 460 

(385 - 817) (305 - 651) (261 - 557) (293 - 626) (

Hybrid 594 501 430 453 

(379 - 806) (320 - 681) (274 - 584) (289 - 616) (

Percent Difference 3 -1% 5% 5% -2% 

Proportional 434 337 289 337 

(277 - 589) (215 - 458) (184 - 392) (215 - 458) (

Hybrid 434 337 289 337 

(277 - 589) (215 - 458) (184 - 392) (215 - 458) (

Percent Difference 0% 0% 0% 0% 

Proportional 508 427 353 364 

(323 - 690) (271 - 581) (224 - 480) (232 - 496) (

Hybrid 541 523 441 393 

(344 - 735) (333 - 710) (280 - 600) (250 - 535) (

Percent Difference 6% 22% 25% 8% 

Proportional 1221 1221 1064 817 

(776 - 1662) (776 - 1662) (676 - 1450) (519 - 1114) (

Hybrid 1540 1468 1222 1092 

(980 - 2094) (934 - 1996) (777 - 1664) (694 - 1487) (

Percent Difference 26% 20% 15% 34% 

Proportional 1345 1272 1050 937 

(855 - 1829) (809 - 1731) (668 - 1430) (595 - 1277) (

Hybrid 1389 1267 1045 975 

(884 - 1889) (806 - 1724) (664 - 1424) (620 - 1329) (

Percent Difference 3% 0% 0% 4% 

Proportional 297 297 297 199 

(189 - 404) (189 - 404) (189 - 404) (126 - 272) 

Hybrid 430 402 339 314 

(274 - 584) (256 - 546) (215 - 461) (200 - 427) (

Percent Difference 45% 35% 14% 58% 

Proportional 652 500 417 484 

(415 - 885) (318 - 680) (265 - 568) (308 - 659) (

Hybrid 714 543 458 543 

(455 - 969) (346 - 739) (291 - 623) (346 - 739) (

Percent Difference 10% 9% 10% 12% 

3 Calculated as (mortality based on hybrid rollbacks - mortality based on proportional rollbacks)/(mortality based on proportional rollbacks).

 Detroit, MI

 Los Angeles, CA

 New York, NY

 Pittsburgh, PA

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 

Incidence of All Cause Mortality Associated with Long-Term Exposure to PM2.5 Con

that Just Meet the Current and Alternative Combinations of Annual (n) and Daily (m

Type of Rollback (Standard Combination Denoted n/m):

1Estimates Based on Krewski et al. (2009), exposure period from 1999 - 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Kr

2009).

Risk Assessment 

Location

 Baltimore, MD

 Birmingham, AL

 St. Louis, MO

F-13

September 2009 
Table F-12. Sensitivity Analysis: Estimated Annual Incidence of All Cause Mortality Associated with Long-Term Exposur

 Concentrations that Just Meet the Current and Alternative Standards, Based on Adjusting 2007 PM2.5 Concentra

 Comparison of Proportional and Hybrid Rollback Methods1

15/35 2 13/35 12/35 13/30 

Proportional 563 444 377 426 

(359 - 764) (283 - 604) (240 - 513) (271 - 579) (

Hybrid 555 465 397 419 

(354 - 555) (296 - 465) (252 - 397) (267 - 419) (

Percent Difference 3 -1% 5% 5% -2% 

Proportional 429 332 284 332 

(274 - 581) (212 - 452) (181 - 386) (212 - 452) (

Hybrid 429 333 284 333 

(274 - 429) (212 - 333) (181 - 284) (212 - 333) (

Percent Difference 0% 0% 0% 0% 

Proportional 469 392 321 332 

(299 - 638) (249 - 533) (204 - 437) (211 - 452) (

Hybrid 502 484 406 360 

(319 - 502) (308 - 484) (258 - 406) (229 - 360) (

Percent Difference 7% 23% 26% 8% 

Proportional 1257 1257 1098 847 

(799 - 1711) (799 - 1711) (698 - 1496) (538 - 1155) (

Hybrid 1582 1508 1259 1126 

(1007 - 1582) (960 - 1508) (800 - 1259) (716 - 1126) (

Percent Difference 26% 20% 15% 33% 

Proportional 1370 1296 1072 957 

(871 - 1863) (824 - 1764) (681 - 1459) (608 - 1304) (

Hybrid 1415 1291 1067 996 

(900 - 1415) (821 - 1291) (678 - 1067) (633 - 996) (

Percent Difference 3% 0% 0% 4% 

Proportional 303 303 303 205 

(193 - 413) (193 - 413) (193 - 413) (130 - 280) 

Hybrid 437 408 345 320 

(278 - 437) (260 - 408) (219 - 345) (203 - 320) (

Percent Difference 44% 35% 14% 56% 

Proportional 698 540 455 524 

(445 - 948) (344 - 735) (289 - 619) (334 - 713) (

Hybrid 766 589 500 589 

(489 - 766) (375 - 589) (318 - 500) (375 - 589) (

Percent Difference 10% 9% 10% 12% 

3 Calculated as (mortality based on hybrid rollbacks - mortality based on proportional rollbacks)/(mortality based on proportional rollbacks).

Incidence of All Cause Mortality Associated with Long-Term Exposure to PM2.5 Con

that Just Meet the Current and Alternative Combinations of Annual (n) and Daily (m

Type of Rollback (Standard Combination Denoted n/m):

1Estimates Based on Krewski et al. (2009), exposure period from 1999 - 2000, using models with 44 individual and 7 ecological covariates (see Table 33 in Kr

2009).

Risk Assessment 

Location

 St. Louis, MO

 Pittsburgh, PA

 New York, NY

 Los Angeles, CA

 Detroit, MI

 Birmingham, AL

 Baltimore, MD

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 

F-14

September 2009 
Table F-13. Sensitivity Analysis: Impact of Using Season-Specific Concentration-Response Functions vs. an Annual Concentration-Res

 Function to Estimate the Incidence of Non-Accidental Mortality Associated with Short-Term Exposure to PM2.5 Concentration

 that Just Meet the Current Standards, Based on Adjusting 2005 PM2.5 Concentrations 1, 2

Winter Spring Summer Fall Sum of Four Seasons All Year 

53 52 43 33 181 175

(8 - 97) (3 - 99) (-15 - 101) (-17 - 83) --- 4 (33 - 316)

67 47 59 49 222 256

(9 - 124) (1 - 93) (-7 - 123) (7 - 91) --- (104 - 406)

21 28 18 11 78 38

(-5 - 47) (-3 - 59) (-23 - 59) (-24 - 45) --- (-60 - 135)

30 28 41 44 143 151

(-5 - 64) (-8 - 64) (-3 - 85) (6 - 82) --- (36 - 264)

-6 76 53 30 153 141

(-81 - 67) (19 - 132) (-32 - 136) (-28 - 86) --- (-25 - 305)

0 15 3 11 29 44

(-34 - 34) (-1 - 32) (-14 - 21) (-12 - 34) --- (6 - 82)

49 64 56 59 228 232

(-5 - 102) (5 - 123) (-14 - 125) (-10 - 127) --- (47 - 414)

17 66 -109 -2 -28 85

(-86 - 120) (-35 - 167) (-271 - 50) (-96 - 90) --- (-121 - 289)

264 142 122 189 717 714

(97 - 428) (1 - 281) (-49 - 289) (82 - 295) --- (419 - 1007)

90 29 33 63 215 211

(19 - 159) (-33 - 89) (-47 - 110) (16 - 110) --- (78 - 342)

--- --- --- --- --- 240--- --- --- --- --- (40 - 438)

39 56 36 20 151 135

(-4 - 80) (10 - 101) (-19 - 91) (-23 - 62) --- (40 - 230)

17 7 7 9 40 33

(-2 - 35) (-2 - 16) (-6 - 19) (-4 - 21) --- (7 - 59)

36 70 67 70 243 252

(-36 - 106) (13 - 126) (-6 - 138) (12 - 126) --- (73 - 429)

1 9 4 14 28 48

(-53 - 53) (-7 - 25) (-9 - 17) (-10 - 37) --- (8 - 87)

3 Calculated as (sum-of-4-seasons mortality - all-year mortality)/(all-year mortality).4 It was not possible to calculate the 2.5th and 97.5th percentile estimates of the sum of the season-specific incidences because the variance-covariance matrix for the season-

coefficient estimators was not available.

1Based on season-specific and all-year location-specific coefficient estimates from Zanobetti and Schwartz (2009) that have been "shrunken" towards the appropriate regional 

Numbers are rounded to the nearest whole number. 

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 

D

 Dallas, TX Fresno, CA Houston, TX Detroit, MI

5 Season-specific coefficient estimates were not available from Zanobetti and Schwartz (2009) for this location.

 St. Louis, MO

Estimated Incidence of Non-Accidental Mortality Associated with Short-Term Exposure to PM2.5 

Concentrations that Just Meet the Current Standards

 Los Angeles, CA New York, NY

Risk Assessment 

Location

 Atlanta, GA Baltimore, MD Birmingham, AL Philadelphia, PA Phoenix, AZ 5

 Pittsburgh, PA Tacoma, WA Salt Lake City, UT

F-15

September 2009 
Table F-14. Sensitivity Analysis: Impact of Using Season-Specific Concentration-Response Functions vs. an Annual Concentration-Re

 Function to Estimate the Incidence of Non-Accidental Mortality Associated with Short-Term Exposure to PM2.5 Concentratio

 that Just Meet the Current Standards, Based on Adjusting 2006 PM2.5 Concentrations 1, 2

Winter Spring Summer Fall Sum of Four Seasons All Year 

47 54 49 28 178 172

(7 - 86) (3 - 105) (-17 - 113) (-14 - 69) --- 4 (33 - 310)

55 42 56 49 202 234

(7 - 102) (1 - 82) (-6 - 118) (7 - 91) --- (95 - 372)

22 31 19981 38

(-5 - 49) (-3 - 64) (-24 - 61) (-19 - 36) --- (-59 - 132)

23 29 36 33 121 129

(-4 - 50) (-9 - 66) (-3 - 75) (4 - 61) --- (31 - 226)

-4 75 42 26 139 117

(-59 - 50) (19 - 130) (-25 - 107) (-24 - 76) --- (-21 - 254)

1 15411 31 46

(-37 - 37) (-1 - 30) (-15 - 23) (-12 - 34) --- (7 - 86)

49 82 61 51 243 243

(-5 - 103) (6 - 156) (-15 - 135) (-8 - 109) --- (50 - 434)

18 57 -102 -2 -29 78

(-88 - 123) (-30 - 144) (-252 - 47) (-83 - 79) --- (-112 - 267)

230 126 113 187 656 654

(84 - 374) (1 - 250) (-45 - 268) (81 - 292) --- (384 - 922)

78 27 33 72 210 208

(16 - 139) (-31 - 84) (-47 - 111) (18 - 125) --- (77 - 337)

--- --- --- --- --- 255

--- --- --- --- --- (42 - 466)

34 52 35 16 137 122

(-3 - 71) (9 - 94) (-18 - 88) (-19 - 50) --- (36 - 208)

13 7 7 8 35 30

(-2 - 28) (-2 - 16) (-7 - 21) (-3 - 19) --- (6 - 54)

27 65 57 60 209 214

(-27 - 79) (12 - 118) (-5 - 118) (10 - 110) --- (62 - 364)

1 10412 27 39

(-36 - 36) (-8 - 26) (-10 - 19) (-8 - 31) --- (7 - 71)

3 Calculated as (sum-of-4-seasons mortality - all-year mortality)/(all-year mortality).

D

 Dallas, TX Fresno, CA Houston, TX Detroit, MI

5 Season-specific coefficient estimates were not available from Zanobetti and Schwartz (2009) for this location.

 St. Louis, MO

Estimated Incidence of Non-Accidental Mortality Associated with Short-Term Exposure to PM2.5 

Concentrations that Just Meet the Current Standards

 Los Angeles, CA New York, NY

Risk Assessment 

Location

 Atlanta, GA Baltimore, MD Birmingham, AL Philadelphia, PA Phoenix, AZ 5

 Pittsburgh, PA

4 It was not possible to calculate the 2.5th and 97.5th percentile estimates of the sum of the season-specific incidences because the variance-covariance matrix for the 

season-specific coefficient estimators was not available.

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on season-specific and all-year location-specific coefficient estimates from Zanobetti and Schwartz (2009) that have been "shrunken" towards the appropriate 

regional means. Numbers are rounded to the nearest whole number. 

 Tacoma, WA Salt Lake City, UT

F-16

September 2009 
Table F-15. Sensitivity Analysis: Impact of Using Season-Specific Concentration-Response Functions vs. an Annual Concentration-Re

 Function to Estimate the Incidence of Non-Accidental Mortality Associated with Short-Term Exposure to PM2.5 Concentration

 that Just Meet the Current Standards, Based on Adjusting 2007 PM2.5 Concentrations 1, 2

Winter Spring Summer Fall Sum of Four Seasons All Year

47 70 53 31 201 177

(7 - 86) (4 - 134) (-18 - 122) (-16 - 77) --- 4 (34 - 319)

55 44 57 50 206 225

(7 - 102) (1 - 87) (-6 - 118) (7 - 92) --- (91 - 357)

23 50 22 11 106 37

(-5 - 50) (-6 - 104) (-28 - 70) (-23 - 43) --- (-58 - 131)

28 25 38 39 130 137

(-5 - 60) (-8 - 57) (-3 - 79) (5 - 72) --- (33 - 240)

-5 71 43 39 148 112

(-76 - 63) (18 - 124) (-26 - 109) (-37 - 113) --- (-20 - 242)

1 26623 56 51

(-84 - 80) (-2 - 53) (-24 - 34) (-24 - 68) --- (7 - 94)

58 73 65 55 251 240

(-6 - 121) (6 - 140) (-16 - 146) (-9 - 118) --- (49 - 429)

23 117 -148 -3 -11 79

(-115 - 160) (-62 - 294) (-369 - 68) (-145 - 136) --- (-113 - 270)

269 161 133 234 797 659

(98 - 436) (1 - 319) (-54 - 316) (102 - 365) --- (387 - 930)

87 31 34 76 228 206

(18 - 155) (-35 - 95) (-49 - 115) (19 - 132) --- (76 - 334)

--- --- --- --- --- 242

--- --- --- --- --- (40 - 441)

54 89 59 32 234 123

(-5 - 112) (16 - 160) (-31 - 146) (-37 - 99) --- (36 - 209)

29 13 12 14 68 36

(-3 - 60) (-4 - 29) (-10 - 33) (-6 - 34) --- (7 - 65)

31 80 64 69 244 222

(-32 - 93) (15 - 144) (-6 - 132) (12 - 124) --- (64 - 378)

1 12420 37 42

(-47 - 46) (-9 - 32) (-9 - 16) (-14 - 52) --- (7 - 76)

3 Calculated as (sum-of-4-seasons mortality - all-year mortality)/(all-year mortality).

 Fresno, CA Houston, TX Salt Lake City, UT Detroit, MI

Estimated Incidence of Non-Accidental Mortality Associated with Short-Term Exposure to PM2.5 

Concentrations that Just Meet the Current Standards

 Los Angeles, CA New York, NY

Risk Assessment 

Location

 Atlanta, GA Baltimore, MD Birmingham, AL Dallas, TX

D

5 Season-specific coefficient estimates were not available from Zanobetti and Schwartz (2009) for this location.

 Philadelphia, PA Phoenix, AZ 5 Pittsburgh, PA

4 It was not possible to calculate the 2.5th and 97.5th percentile estimates of the sum of the season-specific incidences because the variance-covariance matrix for the 

season-specific coefficient estimators was not available.

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on season-specific and all-year location-specific coefficient estimates from Zanobetti and Schwartz (2009) that have been "shrunken" towards the appropriate 

regional means. Numbers are rounded to the nearest whole number. 

 Tacoma, WA St. Louis, MO

F-17

September 2009 
Table F-16. Sensitivity Analysis: Impact of Using Season-Specific Concentration-Response Functions vs. an Annual Concentration-R

 Function to Estimate the Incidence of Cardiovascular Mortality Associated with Short-Term Exposure to PM2.5 Concentra

 that Just Meet the Current Standards, Based on Adjusting 2005 PM2.5 Concentrations 1, 2

Winter Spring Summer Fall Sum of Four Seasons All Year

14 9 9 -2 30 32

(-20 - 46) (-32 - 47) (-32 - 47) (-37 - 31) --- 4 (-32 - 94)

16 10 11 32 69 70

(-31 - 60) (-32 - 49) (-44 - 63) (-2 - 64) --- (-5 - 142)

5 1 0-18 -12 -1

(-18 - 27) (-27 - 28) (-32 - 29) (-46 - 10) --- (-48 - 45)

10 11 12 -2 31 31

(-18 - 36) (-19 - 40) (-24 - 47) (-32 - 27) --- (-21 - 82)

-1 25 28 32 84 70

(-47 - 42) (-7 - 56) (-21 - 74) (0 - 63) --- (-9 - 147)

-21 0 3 2 11

(-13 - 8) (-3 - 5) (-4 - 4) (-4 - 9) --- (-8 - 30)

9 230849 51

(-37 - 53) (-49 - 50) (-24 - 81) (-44 - 58) --- (-34 - 134)

-7 3-460-50 -33

(-55 - 40) (-45 - 50) (-111 - 18) (-46 - 46) --- (-146 - 79)

141 116 143 92 492 460

(33 - 246) (26 - 204) (27 - 256) (21 - 160) --- (268 - 649)

27 16 26 27 96 85

(-5 - 58) (-15 - 46) (-12 - 63) (4 - 49) --- (22 - 147)

--- --- --- --- --- 83

--- --- --- --- --- (-4 - 169)

13 26 11 4 54 40

(-9 - 34) (2 - 48) (-19 - 39) (-17 - 24) --- (-8 - 88)

--- --- --- --- --- 9

--- --- --- --- --- (-2 - 19)

-3 44 38 41 120 118

(-66 - 57) (-2 - 88) (-18 - 91) (-4 - 84) --- (26 - 208)

00022 12

(-12 - 13) (-3 - 4) (-2 - 3) (-4 - 7) --- (-7 - 31)

3 Calculated as (sum-of-4-seasons mortality - all-year mortality)/(all-year mortality).2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 4 It was not possible to calculate the 2.5th and 97.5th percentile estimates of the sum of the season-specific incidences because the variance-covariance matrix for the seaso

coefficient estimators was not available.

1Based on season-specific and all-year location-specific coefficient estimates from Zanobetti and Schwartz (2009) that have been "shrunken" towards the appropriate regiona

Numbers are rounded to the nearest whole number. 

 Birmingham, AL  Dallas, TX  Pittsburgh, PA

Estimated Incidence of Cardiovascular Mortality Associated with Short-Term Exposure to PM2.5 

Concentrations that Just Meet the Current Standards

 Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Baltimore, MD

 Detroit, MI

5 Season-specific coefficient estimates were not available from Zanobetti and Schwartz (2009) for this location.

 Fresno, CA Houston, TX Salt Lake City, UT 5 St. Louis, MO Philadelphia, PA Phoenix, AZ 5 Tacoma, WA New York, NY

F-18

September 2009 
Table F-17. Sensitivity Analysis: Impact of Using Season-Specific Concentration-Response Functions vs. an Annual Concentration

 Function to Estimate the Incidence of Cardiovascular Mortality Associated with Short-Term Exposure to PM2.5 Concent

 that Just Meet the Current Standards, Based on Adjusting 2006 PM2.5 Concentrations 1, 2

Winter Spring Summer Fall Sum of Four Seasons All Year 

12 9 10 -2 29 31

(-18 - 41) (-33 - 50) (-36 - 53) (-31 - 26) --- 4 (-32 - 93)

13 9 11 32 65 64

(-25 - 50) (-28 - 43) (-42 - 60) (-2 - 64) --- (-4 - 130)

5 1 0 -14 -8 -1

(-19 - 28) (-29 - 31) (-33 - 30) (-36 - 8) --- (-47 - 44)

8 11 11 -1 29 27

(-14 - 28) (-20 - 41) (-21 - 41) (-23 - 20) --- (-18 - 71)

-1 25 22 28 74 58

(-34 - 31) (-7 - 55) (-16 - 58) (0 - 56) --- (-7 - 122)

-2 1 0 3 2 12

(-14 - 9) (-3 - 5) (-4 - 5) (-4 - 9) --- (-8 - 32)

9 2 32 7 50 53

(-37 - 53) (-63 - 64) (-26 - 87) (-38 - 50) --- (-36 - 140)

-8 2 -43 0 -49 -30

(-57 - 41) (-39 - 43) (-103 - 17) (-40 - 40) --- (-134 - 73)

123 103 133 90 449 421

(29 - 215) (23 - 182) (25 - 237) (21 - 158) --- (246 - 595)

23 15 27 31 96 84

(-5 - 51) (-14 - 43) (-13 - 63) (5 - 56) --- (22 - 144)

--- --- --- --- --- 88--- --- --- --- --- (-4 - 179)

11 24 10 3 48 36

(-8 - 30) (2 - 45) (-18 - 38) (-14 - 20) --- (-7 - 80)

--- --- --- --- --- 8

--- --- --- --- --- (-2 - 18)

-2 41 33 36 108 101

(-49 - 43) (-2 - 83) (-15 - 79) (-3 - 73) --- (22 - 177)

00011 10

(-9 - 9) (-3 - 4) (-2 - 3) (-3 - 6) --- (-5 - 26)

3 Calculated as (sum-of-4-seasons mortality - all-year mortality)/(all-year mortality).

Estimated Incidence of Cardiovascular Mortality Associated with Short-Term Exposure to PM2.5 

Concentrations that Just Meet the Current Standards

 Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Baltimore, MD

5 Season-specific coefficient estimates were not available from Zanobetti and Schwartz (2009) for this location.

 Fresno, CA Houston, TX Salt Lake City, UT 5 St. Louis, MO Philadelphia, PA Phoenix, AZ 5

1Based on season-specific and all-year location-specific coefficient estimates from Zanobetti and Schwartz (2009) that have been "shrunken" towards the appropriate 

regional means. Numbers are rounded to the nearest whole number. 

 Tacoma, WA New York, NY Pittsburgh, PA

4 It was not possible to calculate the 2.5th and 97.5th percentile estimates of the sum of the season-specific incidences because the variance-covariance matrix for the 

season-specific coefficient estimators was not available.

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 

 Birmingham, AL Dallas, TX Detroit, MI

F-19

September 2009 
Table F-18. Sensitivity Analysis: Impact of Using Season-Specific Concentration-Response Functions vs. an Annual Concentration-R

 Function to Estimate the Incidence of Cardiovascular Mortality Associated with Short-Term Exposure to PM2.5 Concentra

 that Just Meet the Current Standards, Based on Adjusting 2007 PM2.5 Concentrations 1, 2

Winter Spring Summer Fall Sum of Four Seasons All Year 

11 11 10 -2 30 32

(-16 - 38) (-40 - 58) (-35 - 52) (-31 - 27) --- 4 (-33 - 95)

12 9 10 31 62 61

(-24 - 47) (-28 - 44) (-40 - 57) (-2 - 62) --- (-4 - 125)

4 2 0 -13 -7 -1

(-15 - 23) (-38 - 39) (-30 - 27) (-34 - 7) --- (-46 - 44)

9 10 11 -2 28 29

(-16 - 34) (-17 - 36) (-22 - 44) (-28 - 24) --- (-19 - 75)

-1 19 18 34 70 55

(-36 - 33) (-5 - 43) (-13 - 48) (0 - 67) --- (-7 - 117)

-3 1 0 3 1 13

(-17 - 11) (-3 - 5) (-3 - 4) (-4 - 10) --- (-9 - 35)

10 2 33 7 52 52

(-42 - 59) (-53 - 54) (-26 - 89) (-39 - 51) --- (-36 - 139)

-6 3 -39 0 -42 -30

(-47 - 34) (-50 - 55) (-94 - 15) (-44 - 43) --- (-136 - 74)

120 109 130 94 453 425

(28 - 209) (24 - 193) (25 - 233) (22 - 165) --- (248 - 600)

24 16 25 30 95 83

(-5 - 52) (-14 - 45) (-12 - 60) (4 - 54) --- (22 - 143)

--- --- --- --- --- 84--- --- --- --- --- (-4 - 170)

10 24 10 4 48 37

(-7 - 28) (2 - 45) (-18 - 37) (-16 - 23) --- (-7 - 80)

--- --- --- --- --- 10--- --- --- --- --- (-2 - 21)

-2 45 33 36 112 104

(-52 - 45) (-2 - 91) (-15 - 79) (-3 - 74) --- (23 - 184)

00022 11

(-9 - 9) (-3 - 4) (-2 - 2) (-5 - 8) --- (-6 - 27)

3 Calculated as (sum-of-4-seasons mortality - all-year mortality)/(all-year mortality).

Estimated Incidence of Cardiovascular Mortality Associated with Short-Term Exposure to PM2.5 

Concentrations that Just Meet the Current Standards

 Los Angeles, CA

Risk Assessment 

Location

 Atlanta, GA Baltimore, MD

5 Season-specific coefficient estimates were not available from Zanobetti and Schwartz (2009) for this location.4 It was not possible to calculate the 2.5th and 97.5th percentile estimates of the sum of the season-specific incidences because the variance-covariance matrix for the 

season-specific coefficient estimators was not available.

 Fresno, CA Houston, TX Salt Lake City, UT 5 St. Louis, MO Philadelphia, PA

1Based on season-specific and all-year location-specific coefficient estimates from Zanobetti and Schwartz (2009) that have been "shrunken" towards the appropriate 

regional means. Numbers are rounded to the nearest whole number. 

 Tacoma, WA New York, NY Phoenix, AZ 5 Pittsburgh, PA

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 

 Birmingham, AL Dallas, TX Detroit, MI

F-20

September 2009 
Table F-19. Sensitivity Analysis: Impact of Using Season-Specific Concentration-Response Functions vs. an Annual Concentration-

 Function to Estimate the Incidence of Respiratory Mortality Associated with Short-Term Exposure to PM2.5 Concentration

 that Just Meet the Current Standards, Based on Adjusting 2005 PM2.5 Concentrations 1, 2

Winter Spring Summer Fall Sum of Four Seasons All Year 

4 1 3 311 19

(-6 - 13) (-8 - 11) (-7 - 13) (-5 - 11) --- 4 (-8 - 46)

5 6 6 3 20 35

(-6 - 16) (-4 - 15) (-6 - 17) (-4 - 10) --- (7 - 63)

1 2 -1 4 6 10

(-4 - 6) (-4 - 8) (-9 - 7) (-2 - 10) --- (-8 - 29)

13217 11

(-6 - 9) (-4 - 9) (-5 - 9) (-5 - 7) --- (-10 - 31)

5 9 10 8 32 27

(-6 - 16) (-1 - 18) (0 - 19) (0 - 16) --- (1 - 52)

-1 4 1 1 5 9

(-11 - 9) (-1 - 9) (-2 - 4) (-6 - 8) --- (0 - 17)

6 5 4 5 20 36

(-4 - 16) (-4 - 14) (-6 - 14) (-7 - 16) --- (6 - 66)

27 28 -16 0 39 59

(-3 - 57) (-2 - 56) (-61 - 27) (-24 - 23) --- (6 - 112)

48 16 20 20 104 97

(18 - 78) (-5 - 37) (-9 - 47) (1 - 39) --- (34 - 159)

10 7 7 5 29 23

(-1 - 21) (-1 - 15) (-3 - 16) (-2 - 11) --- (-2 - 46)

27 30 21 41 119 47

(-28 - 77) (-8 - 66) (-3 - 45) (14 - 67) --- (4 - 89)

4 6 6 622 17

(-3 - 10) (-1 - 13) (-2 - 14) (0 - 12) --- (-2 - 35)

4 2 -2 -1 3 6

(-1 - 10) (-2 - 6) (-7 - 3) (-6 - 4) --- (1 - 11)

1 7 4 618 30

(-14 - 16) (-6 - 19) (-10 - 17) (-5 - 18) --- (-8 - 67)

02114 7

(-15 - 13) (-2 - 6) (-2 - 3) (-4 - 6) --- (0 - 15)

3 Calculated as (sum-of-4-seasons mortality - all-year mortality)/(all-year mortality).

 St. Louis, MO Salt Lake City, UT 

Estimated Incidence of Respiratory Mortality Associated with Short-Term Exposure to PM2.5 Concentrations 

that Just Meet the Current Standards

 Los Angeles, CA New York, NY

Risk Assessment 

Location

 Atlanta, GA Baltimore, MD Philadelphia, PA Phoenix, AZ Pittsburgh, PA Tacoma, WA

4 It was not possible to calculate the 2.5th and 97.5th percentile estimates of the sum of the season-specific incidences because the variance-covariance matrix for the sea

coefficient estimators was not available.

1Based on season-specific and all-year location-specific coefficient estimates from Zanobetti and Schwartz (2009) that have been "shrunken" towards the appropriate regio

Numbers are rounded to the nearest whole number. 

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 

 Birmingham, AL Dallas, TX Detroit, MI Houston, TX Fresno, CA

F-21

September 2009 
Table F-20. Sensitivity Analysis: Impact of Using Season-Specific Concentration-Response Functions vs. an Annual Concentration-

 Function to Estimate the Incidence of Respiratory Mortality Associated with Short-Term Exposure to PM2.5 Concentration

 that Just Meet the Current Standards, Based on Adjusting 2006 PM2.5 Concentrations 1, 2

Winter Spring Summer Fall Sum of Four Seasons All Year 

3 1 4 311 19

(-5 - 11) (-9 - 11) (-8 - 15) (-4 - 9) --- 4 (-8 - 45)

4 5 5 3 17 32

(-5 - 13) (-4 - 13) (-6 - 16) (-4 - 10) --- (6 - 58)

1 2 -1 3 5 10

(-4 - 6) (-5 - 9) (-9 - 7) (-2 - 8) --- (-8 - 28)

13217 9

(-5 - 7) (-4 - 10) (-5 - 8) (-4 - 5) --- (-9 - 27)

4 8 8 7 27 23

(-5 - 12) (-1 - 17) (0 - 15) (0 - 14) --- (1 - 44)

-1 4 1 1 5 9

(-12 - 10) (-1 - 9) (-2 - 5) (-6 - 8) --- (0 - 18)

6 6 5 4 21 38

(-4 - 16) (-6 - 18) (-7 - 15) (-6 - 14) --- (6 - 69)

28 24 -15 0 37 55

(-3 - 59) (-2 - 49) (-57 - 26) (-21 - 20) --- (5 - 104)

42 14 18 20 94 89

(16 - 68) (-5 - 33) (-8 - 44) (1 - 38) --- (31 - 145)

9 7 7 528 22

(-1 - 18) (-1 - 14) (-3 - 16) (-2 - 12) --- (-2 - 46)

31 30 22 41 124 50

(-33 - 89) (-8 - 66) (-3 - 46) (14 - 67) --- (4 - 95)

3 6 6 520 15

(-3 - 9) (-1 - 12) (-2 - 14) (0 - 10) --- (-2 - 32)

4 2 -2 -1 3 5

(-1 - 8) (-2 - 6) (-7 - 3) (-5 - 3) --- (1 - 10)

1 6 3 515 26

(-11 - 12) (-6 - 18) (-9 - 14) (-5 - 15) --- (-7 - 57)

02114 6

(-10 - 9) (-2 - 6) (-2 - 4) (-3 - 5) --- (0 - 12)

3 Calculated as (sum-of-4-seasons mortality - all-year mortality)/(all-year mortality).

 Philadelphia, PA Phoenix, AZ Pittsburgh, PA

4 It was not possible to calculate the 2.5th and 97.5th percentile estimates of the sum of the season-specific incidences because the variance-covariance matrix for the 

season-specific coefficient estimators was not available.

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on season-specific and all-year location-specific coefficient estimates from Zanobetti and Schwartz (2009) that have been "shrunken" towards the appropriate 

regional means. Numbers are rounded to the nearest whole number. 

 Tacoma, WA Fresno, CA

Estimated Incidence of Respiratory Mortality Associated with Short-Term Exposure to PM2.5 Concentrations 

that Just Meet the Current Standards

 Los Angeles, CA New York, NY

Risk Assessment 

Location

 Atlanta, GA Baltimore, MD Birmingham, AL Dallas, TX Detroit, MI Houston, TX Salt Lake City, UT St. Louis, MO

F-22

September 2009 
Table F-21. Sensitivity Analysis: Impact of Using Season-Specific Concentration-Response Functions vs. an Annual Concentration

 Function to Estimate the Incidence of Respiratory Mortality Associated with Short-Term Exposure to PM2.5 Concentration

 that Just Meet the Current Standards, Based on Adjusting 2007 PM2.5 Concentrations 1, 2

Winter Spring Summer Fall Sum of Four Seasons All Year 

3 2 4 312 20

(-5 - 10) (-10 - 13) (-8 - 15) (-4 - 9) --- 4 (-8 - 47)

4 5 5 3 17 31

(-5 - 12) (-4 - 14) (-5 - 15) (-4 - 10) --- (6 - 56)

1 3 -1 3 6 10

(-4 - 5) (-6 - 11) (-8 - 7) (-2 - 7) --- (-8 - 28)

13217 10

(-6 - 8) (-3 - 9) (-5 - 8) (-5 - 6) --- (-9 - 29)

4 7 7 9 27 22

(-5 - 12) (0 - 13) (0 - 13) (0 - 17) --- (1 - 42)

-1 4 1 2 6 10

(-14 - 12) (-1 - 8) (-2 - 4) (-6 - 9) --- (0 - 19)

6 5 5 4 20 38

(-5 - 18) (-5 - 15) (-7 - 15) (-6 - 14) --- (6 - 68)

23 31 -14 0 40 56

(-2 - 48) (-2 - 63) (-52 - 23) (-23 - 21) --- (5 - 105)

41 15 18 21 95 90

(15 - 66) (-5 - 35) (-8 - 43) (1 - 40) --- (32 - 147)

9 7 7 5 28 22

(-1 - 18) (-1 - 15) (-3 - 15) (-2 - 12) --- (-2 - 45)

24 29 25 45 123 47

(-25 - 69) (-8 - 63) (-4 - 51) (15 - 73) --- (4 - 90)

3 6 6 5 20 16

(-2 - 8) (-1 - 12) (-2 - 13) (0 - 11) --- (-2 - 32)

5 2 -2 -1 4 6

(-2 - 11) (-3 - 7) (-7 - 3) (-6 - 4) --- (1 - 12)

1 7 3 6 17 27

(-11 - 13) (-6 - 19) (-9 - 14) (-5 - 15) --- (-7 - 59)

02114 6

(-11 - 10) (-2 - 6) (-1 - 3) (-5 - 7) --- (0 - 13)

3 Calculated as (sum-of-4-seasons mortality - all-year mortality)/(all-year mortality).

 Fresno, CA Philadelphia, PA Phoenix, AZ Pittsburgh, PA

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on season-specific and all-year location-specific coefficient estimates from Zanobetti and Schwartz (2009) that have been "shrunken" towards the appropriate 

regional means. Numbers are rounded to the nearest whole number. 

 Tacoma, WA

4 It was not possible to calculate the 2.5th and 97.5th percentile estimates of the sum of the season-specific incidences because the variance-covariance matrix for the 

season-specific coefficient estimators was not available.

 Salt Lake City, UT

Estimated Incidence of Respiratory Mortality Associated with Short-Term Exposure to PM2.5 Concentrations 

that Just Meet the Current Standards

 Los Angeles, CA New York, NY

Risk Assessment 

Location

 Atlanta, GA Baltimore, MD Birmingham, AL Dallas, TX Detroit, MI Houston, TX St. Louis, MO

F-23

September 2009 
Table F-22. Sensitivity Analysis: Impact of Using Season-Specific Concentration-Response Functions vs. an Annual Concentration-

 Function to Estimate the Incidence of Hospital Admissions for Cardiovascular Illness Associated with Short-Term Exposur Concentrations that Just Meet the Current Standards, Based on Adjusting 2005 PM2.5 Concentrations 1, 2

Winter Spring Summer Fall Sum of Four Seasons All Year 

29 24 -29 6 30 40

(-2 - 59) (-8 - 55) (-70 - 11) (-27 - 39) --- 4 (-26 - 105)

131 46 39 47 263 247

(92 - 171) (16 - 76) (6 - 72) (22 - 72) --- (182 - 313)

12 11 -14 3 12 18

(-1 - 24) (-4 - 25) (-34 - 5) (-13 - 19) --- (-12 - 48)

24 18 -20 4 26 30

(-2 - 49) (-6 - 42) (-49 - 8) (-19 - 27) --- (-19 - 78)

149 54 40 50 293 269

(104 - 193) (18 - 88) (6 - 73) (24 - 77) --- (198 - 340)

14 11 -7 3 21 21

(-5 - 32) (-5 - 27) (-29 - 15) (-11 - 17) --- (0 - 42)

48 36 -39 10 55 61

(-3 - 98) (-13 - 85) (-94 - 15) (-44 - 64) --- (-40 - 161)

106 196 -152 44 194 274

(-36 - 247) (-99 - 481) (-647 - 322) (-147 - 232) --- (3 - 543)

370 144 117 133 764 724

(258 - 481) (49 - 238) (17 - 216) (63 - 203) --- (532 - 915)

114 39 34 38 225 210

(79 - 148) (13 - 64) (5 - 63) (18 - 58) --- (154 - 265)

57 82 -47 14 106 107

(-19 - 132) (-41 - 202) (-198 - 99) (-47 - 75) --- (1 - 212)

52 27 23 31 133 134

(36 - 68) (9 - 44) (3 - 43) (14 - 47) --- (98 - 169)

6 4 -4 1 7 9

(-2 - 14) (-2 - 11) (-17 - 8) (-4 - 6) --- (0 - 17)

100 41 30 41 212 200

(70 - 130) (14 - 67) (4 - 55) (19 - 63) --- (147 - 253)

12 0 -5 -5 2 21

(-65 - 82) (-61 - 55) (-56 - 42) (-53 - 40) --- (-52 - 92)

3 Calculated as (sum-of-4-seasons hospital admissions - all-year hospital admissions)/(all-year hospital admissions).1Incidence estimates were calculated using the appropriate season-specific or all-year regional concentration-response function estimates reported in Table 2 of Bell et al. 

specific C-R function estimates were not available from this study. Numbers are rounded to the nearest whole number. 

 Fresno, CA Houston, TX Salt Lake City, UT Detroit, MI

Estimated Incidence of Hospital Admissions for Cardiovascular Illness Associated with Short-Term Exposure 

to PM2.5 Concentrations that Just Meet the Current Standards

 Los Angeles, CA New York, NY

Risk Assessment 

Location

 Atlanta, GA Baltimore, MD Birmingham, AL Dallas, TX

 Philadelphia, PA Phoenix, AZ Pittsburgh, PA Tacoma, WA St. Louis, MO

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 4 It was not possible to calculate the 2.5th and 97.5th percentile estimates of the sum of the season-specific incidences because the variance-covariance matrix for the sea

coefficient estimators was not available.

F-24

September 2009 
Table F-23. Sensitivity Analysis: Impact of Using Season-Specific Concentration-Response Functions vs. an Annual Concentration-

 Function to Estimate the Incidence of Hospital Admissions for Cardiovascular Illness Associated with Short-Term Exposu Concentrations that Just Meet the Current Standards, Based on Adjusting 2006 PM2.5 Concentrations 1, 2

Winter Spring Summer Fall Sum of Four Seasons All Year 

26 25 -32 5 24 39

(-2 - 53) (-9 - 58) (-78 - 13) (-23 - 33) --- 4 (-26 - 103)

107 41 37 47 232 224

(75 - 139) (14 - 67) (6 - 69) (22 - 72) --- (165 - 284)

12 12 -14 2 12 18

(-1 - 24) (-4 - 27) (-34 - 6) (-10 - 15) --- (-12 - 47)

19 19 -18 3 23 25

(-1 - 39) (-7 - 44) (-43 - 7) (-14 - 21) --- (-17 - 67)

110 53 31 45 239 224

(77 - 144) (18 - 87) (5 - 57) (21 - 68) --- (165 - 284)

15 10 -7 3 21 22

(-5 - 35) (-5 - 26) (-32 - 16) (-11 - 17) --- (0 - 44)

48 46 -42 9 61 64

(-3 - 100) (-17 - 108) (-102 - 16) (-38 - 55) --- (-42 - 170)

111 172 -144 39 178 258

(-38 - 258) (-86 - 424) (-612 - 306) (-129 - 205) --- (3 - 511)

325 129 109 132 695 666

(227 - 422) (44 - 213) (16 - 201) (62 - 202) --- (489 - 843)

98 36 34 43 211 204

(69 - 128) (12 - 60) (5 - 63) (20 - 65) --- (150 - 258)

66 81 -48 14 113 113

(-22 - 153) (-41 - 199) (-205 - 103) (-47 - 75) --- (1 - 225)

46 25 22 25 118 120

(32 - 60) (8 - 41) (3 - 41) (12 - 38) --- (88 - 152)

5 5 -4 1 7 8

(-2 - 11) (-2 - 12) (-19 - 9) (-3 - 5) --- (0 - 16)

76 38 26 36 176 171

(53 - 98) (13 - 63) (4 - 48) (17 - 55) --- (125 - 216)

9 0 -6 -4 -1 18

(-45 - 57) (-64 - 59) (-61 - 46) (-43 - 33) --- (-43 - 76)

3 Calculated as (sum-of-4-seasons hospital admissions - all-year hospital admissions)/(all-year hospital admissions).

 Fresno, CA Houston, TX Salt Lake City, UT Detroit, MI

Estimated Incidence of Hospital Admissions for Cardiovascular Illness Associated with Short-Term Exposure 

to PM2.5 Concentrations that Just Meet the Current Standards

 Los Angeles, CA New York, NY

Risk Assessment 

Location

 Atlanta, GA Baltimore, MD Birmingham, AL Dallas, TX

 Philadelphia, PA Phoenix, AZ Pittsburgh, PA

4 It was not possible to calculate the 2.5th and 97.5th percentile estimates of the sum of the season-specific incidences because the variance-covariance matrix for the 

season-specific coefficient estimators was not available.

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Incidence estimates were calculated using the appropriate season-specific or all-year regional concentration-response function estimates reported in Table 2 of Bell et al. 

(2008). Location-specific C-R function estimates were not available from this study. Numbers are rounded to the nearest whole number. 

 Tacoma, WA St. Louis, MO

F-25

September 2009 
Table F-24. Sensitivity Analysis: Impact of Using Season-Specific Concentration-Response Functions vs. an Annual Concentration

 Function to Estimate the Incidence of Hospital Admissions for Cardiovascular Illness Associated with Short-Term Exposu Concentrations that Just Meet the Current Standards, Based on Adjusting 2007 PM2.5 Concentrations 1, 2

Winter Spring Summer Fall Sum of Four Seasons All Year 

24 30 -33 5 26 41

(-2 - 49) (-11 - 69) (-79 - 13) (-23 - 34) --- 4 (-27 - 108)

101 41 35 45 222 215

(70 - 131) (14 - 67) (5 - 65) (21 - 69) --- (158 - 271)

10 15 -13 2 14 17

(-1 - 20) (-5 - 35) (-31 - 5) (-10 - 14) --- (-11 - 46)

23 16 -19 4 24 27

(-2 - 47) (-6 - 38) (-46 - 7) (-17 - 25) --- (-18 - 72)

115 41 26 54 236 215

(81 - 150) (14 - 68) (4 - 48) (26 - 83) --- (158 - 272)

18 10 -6 4 26 24

(-6 - 42) (-5 - 25) (-27 - 13) (-12 - 19) --- (0 - 48)

55 40 -43 9 61 64

(-4 - 112) (-14 - 93) (-105 - 17) (-39 - 57) --- (-42 - 169)

93 226 -135 44 228 265

(-32 - 217) (-114 - 556) (-571 - 286) (-144 - 228) --- (3 - 526)

318 137 108 139 702 676

(222 - 413) (47 - 227) (16 - 199) (65 - 212) --- (496 - 855)

100 37 32 41 210 201

(70 - 130) (13 - 62) (5 - 59) (19 - 63) --- (148 - 254)

51 78 -54 16 91 108

(-17 - 118) (-39 - 192) (-228 - 114) (-52 - 82) --- (1 - 215)

42 24 21 28 115 120

(29 - 54) (8 - 40) (3 - 39) (13 - 43) --- (88 - 152)

7 5 -4 1 9 10

(-2 - 15) (-3 - 13) (-19 - 10) (-4 - 6) --- (0 - 20)

79 41 26 36 182 176

(55 - 103) (14 - 69) (4 - 47) (17 - 55) --- (129 - 222)

9 0 -4 -6 -1 19

(-48 - 59) (-64 - 59) (-43 - 33) (-63 - 47) --- (-46 - 82)

3 Calculated as (sum-of-4-seasons hospital admissions - all-year hospital admissions)/(all-year hospital admissions).

 Fresno, CA Houston, TX Salt Lake City, UT Detroit, MI

Estimated Incidence of Hospital Admissions for Cardiovascular Illness Associated with Short-Term Exposure 

to PM2.5 Concentrations that Just Meet the Current Standards

 Los Angeles, CA New York, NY

Risk Assessment 

Location

 Atlanta, GA Baltimore, MD Birmingham, AL Dallas, TX

 Philadelphia, PA Phoenix, AZ Pittsburgh, PA

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Incidence estimates were calculated using the appropriate season-specific or all-year regional concentration-response function estimates reported in Table 2 of Bell et al. 

(2008). Location-specific C-R function estimates were not available from this study. Numbers are rounded to the nearest whole number. 

 Tacoma, WA

4 It was not possible to calculate the 2.5th and 97.5th percentile estimates of the sum of the season-specific incidences because the variance-covariance matrix for the 

season-specific coefficient estimators was not available.

 St. Louis, MO

F-26

September 2009 
Table F-25. Sensitivity Analysis: Impact of Using Season-Specific Concentration-Response Functions vs. an Annual Concentration-Res

 Function to Estimate the Incidence of Hospital Admissions for Respiratory Illness Associated with Short-Term Exposure to PM

 Concentrations that Just Meet the Current Standards, Based on Adjusting 2005 PM2.5 Concentrations 1, 2

Winter Spring Summer Fall Sum of Four Seasons All Year 

6 9-6110 17

(-20 - 31) (-10 - 27) (-25 - 12) (-13 - 15) --- 4 (-21 - 55)

18 1 14 2 35 20

(-5 - 41) (-14 - 15) (0 - 28) (-12 - 15) --- (-12 - 51)

2 4 -3 1 4 8

(-8 - 12) (-5 - 13) (-12 - 6) (-6 - 7) --- (-10 - 25)

4 7 -5 1 7 14

(-17 - 25) (-8 - 21) (-20 - 10) (-13 - 15) --- (-18 - 46)

23 1 17 2 43 24

(-6 - 51) (-18 - 20) (0 - 35) (-12 - 16) --- (-14 - 62)

10 3 4 3 20 14

(-1 - 21) (-6 - 11) (-4 - 12) (-5 - 11) --- (3 - 25)

8 13 -9 3 15 27

(-30 - 45) (-14 - 40) (-37 - 18) (-29 - 35) --- (-34 - 88)

73 46 90 44 253 177

(-6 - 151) (-98 - 184) (-103 - 273) (-64 - 149) --- (41 - 311)

54 2 44 4 104 60

(-15 - 122) (-46 - 50) (-1 - 88) (-31 - 39) --- (-35 - 154)

16 1 12 1 30 17

(-4 - 36) (-12 - 13) (0 - 24) (-9 - 12) --- (-10 - 43)

34 17 23 13 87 61

(-3 - 70) (-36 - 68) (-26 - 70) (-18 - 43) --- (14 - 106)

7 0 8 1 16 11

(-2 - 16) (-9 - 9) (0 - 16) (-8 - 10) --- (-6 - 28)

41319 6

(0 - 9) (-3 - 5) (-3 - 8) (-2 - 4) --- (1 - 11)

23 1 15 2 41 24

(-6 - 51) (-18 - 19) (0 - 29) (-15 - 19) --- (-14 - 62)

0 4 1 -2 3 2

(-50 - 43) (-27 - 32) (-19 - 19) (-25 - 18) --- (-27 - 30)

3 Calculated as (sum-of-4-seasons hospital admissions - all-year hospital admissions)/(all-year hospital admissions).

 St. Louis, MO Salt Lake City, UT 

Estimated Incidence of Hospital Admissions for Respiratory Illness Associated with Short-Term Exposure to 

PM2.5 Concentrations that Just Meet the Current Standards

 Los Angeles, CA New York, NY

Risk Assessment 

Location

 Atlanta, GA Baltimore, MD Philadelphia, PA Phoenix, AZ Pittsburgh, PA Tacoma, WA

4 It was not possible to calculate the 2.5th and 97.5th percentile estimates of the sum of the season-specific incidences because the variance-covariance matrix for the season-

coefficient estimators was not available.

1Incidence estimates were calculated using the appropriate season-specific or all-year regional concentration-response function estimates from models with a 2-day lag for resp

hospital admissions reported in Table 2 of Bell et al. (2008). Location-specific C-R function estimates were not available from this study. Numbers are rounded to the nearest w

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 

 Birmingham, AL Dallas, TX Detroit, MI Houston, TX Fresno, CA

D

F-27

September 2009 
Table F-26. Sensitivity Analysis: Impact of Using Season-Specific Concentration-Response Functions vs. an Annual Concentration-Re

 Function to Estimate the Incidence of Hospital Admissions for Respiratory Illness Associated with Short-Term Exposure to P Concentrations that Just Meet the Current Standards, Based on Adjusting 2006 PM2.5 Concentrations 1, 2

Winter Spring Summer Fall Sum of Four Seasons All Year 

5 9-71 8 17

(-18 - 27) (-11 - 29) (-29 - 14) (-11 - 13) --- 4 (-21 - 54)

15 1 13 2 31 18

(-4 - 34) (-12 - 13) (0 - 26) (-12 - 15) --- (-11 - 46)

2 4 -3 0 3 8

(-8 - 13) (-5 - 14) (-13 - 6) (-5 - 6) --- (-10 - 24)

4 7 -4 1 8 12

(-13 - 20) (-8 - 22) (-18 - 9) (-10 - 11) --- (-15 - 40)

17 1 14 2 34 20

(-5 - 38) (-18 - 19) (0 - 27) (-11 - 14) --- (-12 - 52)

11 3 4 3 21 15

(-1 - 23) (-5 - 10) (-5 - 13) (-5 - 11) --- (3 - 26)

8 17 -10 3 18 29

(-30 - 45) (-19 - 51) (-40 - 20) (-25 - 30) --- (-36 - 93)

77 40 86 39 242 166

(-7 - 158) (-86 - 162) (-98 - 261) (-56 - 132) --- (39 - 293)

48 2 41 4 95 55

(-13 - 107) (-41 - 45) (-1 - 82) (-30 - 39) --- (-32 - 142)

14 0 12 2 28 16

(-4 - 31) (-11 - 12) (0 - 24) (-10 - 13) --- (-10 - 42)

40 17 24 13 94 64

(-3 - 82) (-36 - 67) (-27 - 73) (-18 - 43) --- (15 - 113)

6 0 7 1 14 10

(-2 - 14) (-8 - 9) (0 - 15) (-6 - 8) --- (-6 - 25)

31318 6

(0 - 7) (-3 - 5) (-3 - 9) (-2 - 4) --- (1 - 10)

17 1 13 2 33 21

(-5 - 39) (-17 - 18) (0 - 25) (-13 - 16) --- (-12 - 53)

0 4 1 -1 4 2

(-35 - 29) (-29 - 34) (-21 - 20) (-20 - 15) --- (-22 - 25)

3 Calculated as (sum-of-4-seasons hospital admissions - all-year hospital admissions)/(all-year hospital admissions).

 Philadelphia, PA Phoenix, AZ Pittsburgh, PA

4 It was not possible to calculate the 2.5th and 97.5th percentile estimates of the sum of the season-specific incidences because the variance-covariance matrix for the 

season-specific coefficient estimators was not available.

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Incidence estimates were calculated using the appropriate season-specific or all-year regional concentration-response function estimates from models with a 2-day lag for 

respiratory hospital admissions reported in Table 2 of Bell et al. (2008). Location-specific C-R function estimates were not available from this study. Numbers are rounded 

to the nearest whole number. 

 Tacoma, WA Fresno, CA

Estimated Incidence of Hospital Admissions for Respiratory Illness Associated with Short-Term Exposure to 

PM2.5 Concentrations that Just Meet the Current Standards

 Los Angeles, CA New York, NY

Risk Assessment 

Location

 Atlanta, GA Baltimore, MD Birmingham, AL Dallas, TX Detroit, MI Houston, TX Salt Lake City, UT St. Louis, MO

F-28

September 2009 
Table F-27. Sensitivity Analysis: Impact of Using Season-Specific Concentration-Response Functions vs. an Annual Concentration-Re

 Function to Estimate the Incidence of Hospital Admissions for Respiratory Illness Associated with Short-Term Exposure to P Concentrations that Just Meet the Current Standards, Based on Adjusting 2007 PM2.5 Concentrations 1, 2

Winter Spring Summer Fall Sum of Four Seasons All Year 

5 11 -7110 17

(-17 - 25) (-13 - 34) (-29 - 14) (-11 - 13) --- 4 (-22 - 56)

14 1 12 2 29 17

(-4 - 32) (-12 - 13) (0 - 25) (-11 - 14) --- (-10 - 44)

2 6 -3 0 5 7

(-7 - 10) (-6 - 17) (-11 - 6) (-4 - 5) --- (-9 - 24)

4 6 -5 1 6 13

(-16 - 24) (-7 - 20) (-19 - 9) (-11 - 14) --- (-16 - 42)

18 1 11 2 32 19

(-5 - 40) (-14 - 15) (0 - 23) (-13 - 17) --- (-11 - 49)

13 2 4 4 23 16

(-1 - 28) (-5 - 10) (-4 - 11) (-6 - 13) --- (4 - 29)

9 14 -10 3 16 29

(-34 - 51) (-16 - 44) (-41 - 20) (-26 - 31) --- (-36 - 93)

64 53 80 44 241 171

(-6 - 133) (-113 - 213) (-92 - 245) (-63 - 146) --- (40 - 301)

46 2 41 5 94 56

(-12 - 105) (-44 - 48) (-1 - 81) (-32 - 40) --- (-33 - 144)

14 1 11 1 27 16

(-4 - 31) (-11 - 12) (0 - 23) (-10 - 13) --- (-9 - 42)

31 16 27 14 88 61

(-3 - 63) (-34 - 65) (-30 - 81) (-20 - 47) --- (14 - 108)

6 0 7 1 14 10

(-2 - 13) (-8 - 9) (0 - 14) (-7 - 9) --- (-6 - 25)

5 1 3 1 10 7

(0 - 10) (-3 - 6) (-3 - 9) (-2 - 5) --- (2 - 13)

18 1 13 2 34 21

(-5 - 40) (-18 - 20) (0 - 25) (-13 - 16) --- (-12 - 54)

0 4 1 -2 3 2

(-37 - 31) (-29 - 34) (-15 - 15) (-29 - 22) --- (-24 - 27)

3 Calculated as (sum-of-4-seasons hospital admissions - all-year hospital admissions)/(all-year hospital admissions).

 Fresno, CA Philadelphia, PA Phoenix, AZ Pittsburgh, PA

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Incidence estimates were calculated using the appropriate season-specific or all-year regional concentration-response function estimates from models with a 2-day lag for 

respiratory hospital admissions reported in Table 2 of Bell et al. (2008). Location-specific C-R function estimates were not available from this study. Numbers are rounded 

to the nearest whole number. 

 Tacoma, WA

4 It was not possible to calculate the 2.5th and 97.5th percentile estimates of the sum of the season-specific incidences because the variance-covariance matrix for the 

season-specific coefficient estimators was not available.

 Salt Lake City, UT

Estimated Incidence of Hospital Admissions for Respiratory Illness Associated with Short-Term Exposure to 

PM2.5 Concentrations that Just Meet the Current Standards

 Los Angeles, CA New York, NY

Risk Assessment 

Location

 Atlanta, GA Baltimore, MD Birmingham, AL Dallas, TX Detroit, MI Houston, TX St. Louis, MO

F-29

September 2009 
Table F-28. Sensitivity Analysis: Impact of Using an Annual Concentration-Response Function vs. a Seasonal Function 

 Applied Only to that Period to Estimate the Incidence of Emergency Room Visits for Asthma Associated with S Exposure to Concentrations in a Recent Year (2005) and PM2.5 Concentrations that Just Meet the Current and 

 Standards in New York City, Based on Adjusting 2005 PM2.5 Concentrations1 

Recent PM2.5 

Concentration 15/352 13/35 12/35 13

1162 971 947 872 8

(743 - 1567) (620 - 1314) (604 - 1281) (556 - 1181) (531 - 

737 620 605 558 5

(485 - 977) (406 - 824) (396 - 805) (364 - 744) (349 

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on Ito et al. (2007). New York City in this study consisted only of Manhattan.

Incidence of ER Visits Associated with Short-Term Exposure to PM2

Recent Year and PM2.5 Concentrations that Just Meet the Current and 

and Daily (m) Standards (Standard Combination Denote

Annual C-R Function Applied to the Whole Year Seasonal C-R Function for April - August Applied Only to that Period:

Concentration-Response (C-R) Function and 

Period to Which Applied:

F-30

September 2009 
Table F-29. Sensitivity Analysis: Impact of Using an Annual Concentration-Response Function vs. a Seasonal Function 

 Applied Only to that Period to Estimate the Incidence of Emergency Room Visits for Asthma Associated with S to Concentrations in a Recent Year (2006) and PM2.5 Concentrations that Just Meet the Current and Alternativ

 New York City, Based on Adjusting 2006 PM2.5 Concentrations1

Recent PM2.5 

Concentration 15/352 13/35 12/35 13

991 828 807 743 7

(633 - 1340) (528 - 1122) (515 - 1094) (473 - 1008) (452 

627 526 513 474 4

(411 - 832) (344 - 702) (335 - 685) (309 - 632) (295 

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on Ito et al. (2007). New York City in this study consisted only of Manhattan.

Incidence of ER Visits Associated with Short-Term Exposure to PM2

Recent Year and PM2.5 Concentrations that Just Meet the Current and 

and Daily (m) Standards (Standard Combination Denote

Annual C-R Function Applied to the Whole Year Seasonal C-R Function for April - August Applied Only to that Period:

Concentration-Response (C-R) Function and 

Period to Which Applied:

F-31

September 2009 
Table F-30. Sensitivity Analysis: Impact of Using an Annual Concentration-Response Function vs. a Seasonal Function 

 Applied Only to that Period to Estimate the Incidence of Emergency Room Visits for Asthma Associated with S Exposure to Concentrations in a Recent Year (2007) and PM2.5 Concentrations that Just Meet the Current and 

 Standards in New York City, Based on Adjusting 2007 PM2.5 Concentrations1 

Recent PM2.5 

Concentrations 15/352 13/35 12/35 13

1114 931 907 836 7

(712 - 1504) (594 - 1260) (579 - 1229) (532 - 1133) (509 - 

684 575 561 517 4

(449 - 908) (376 - 766) (366 - 747) (337 - 691) (323 

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 1Based on Ito et al. (2007). New York City in this study consisted only of Manhattan.

Incidence of ER Visits Associated with Short-Term Exposure to PM2.5 Con

Year and PM2.5 Concentrations that Just Meet the Current and Alternative A

Standards (Standard Combination Denoted n/m):

Annual C-R Function Applied to the Whole Year Seasonal C-R Function for April - August Applied Only to that Period:

Concentration-Response (C-R) Function and Period 

to Which Applied:

F-32

September 2009 
Table F-31. Sensitivity Analysis: Estimated Annual Incidence and Percent of Total Incidence of Mortality in Los Angeles, CA Associated wi

 Exposure to PM2.5 Concentrations that Just Meet the Current Standards, Based on Adjusting 2005 PM2.5 Concentrations1 

Mortality, short-term non-accidental log-linear, GAM (stringent), 30 df 0 day none 286 Max. positive est. = 85

(-36 - 606) 312 (-121 - 28

Mortality, short-term non-accidental log-linear, GAM (stringent), 30 df 1 day none 312 Min. positive est. =

(0 - 622) 201

Mortality, short-term non-accidental log-linear, GAM (stringent), 30 df 2 day none 201

(-100 - 501) Percent diff. =

Mortality, short-term non-accidental log-linear, GAM (stringent), 30 df 3 day none -80 55%

(-388 - 226)

Mortality, short-term non-accidental log-linear, GAM (stringent), 30 df 4 day none -48

(-342 - 244)

Mortality, short-term non-accidental log-linear, GAM (stringent), 30 df 5 day none -299

(-616 - 16)

Mortality, short-term non-accidental log-linear, GAM (stringent), 30 df 0 day none 286 Max. positive est. = 85

(-36 - 606) 286 (-121 - 28

Mortality, short-term non-accidental log-linear, GLM, 30 df 0 day none 212 Min. positive est. =

(-181 - 601) 159

Mortality, short-term non-accidental log-linear, GAM (stringent), 100 df 0 day none 170

(-120 - 457) Percent diff. =

Mortality, short-term non-accidental log-linear, GLM, 100 df 0 day none 159 80%

(-227 - 542)

Mortality, short-term non-accidental log-linear, GAM (stringent), 30 df 1 day none 312 Max. positive est. = 85

(0 - 622) 312 (-121 - 28

Mortality, short-term non-accidental log-linear, GLM, 30 df 1 day none 291 Min. positive est. =

(-90 - 669) 53

Mortality, short-term non-accidental log-linear, GAM (stringent), 100 df 1 day none 53

(-245 - 349) Percent diff. =

Mortality, short-term non-accidental log-linear, GLM, 100 df 1 day none -5 489%

(-530 - 512)

Mortality, short-term non-accidental log-linear, GAM (stringent), 30 df 1 day CO -283 85

(-703 - 133) (-121 - 28

Mortality, short-term non-accidental log-linear, GAM (stringent), 100 df 1 day CO -176

(-561 - 206)

Mortality, short-term non-accidental log-linear, GLM, 100 df 1 day CO -176

(-627 - 270)

Non-Accidental Mortality Associated with Short-Term Exposure to P

M 2.5 -- Impact of Changing the Type of Model, with a 0-Day Lag

Incidenc

Estimate U

Core Anal

Model 

Non-Accidental Mortality Associated with Short-Term Exposure to P

M 2.5 -- Impact of Changing the Lag Structure:

Lag

Other 

Pollutants 

in Model

Incidence 

Associated with 

PM2.5 Above Policy 

Relevant 

Background

Range of Positive 

Estimates and 

Percent Difference 

Between Maximum 

and Minimum 2

Non-Accidental Mortality Associated with Short-Term Exposure to P

M 2.5 -- Impact of a Copollutant Model

Non-Accidental Mortality Associated with Short-Term Exposure to P

M 2.5 -- Impact of Changing the Type of Model, with a 1-Day Lag

Health Effects Model

F-33

September 2009 
Table F-31 cont'd. Sensitivity Analysis: Estimated Annual Incidence and Percent of Total Incidence of Mortality in Los Angeles, CA Ass

 Exposure to PM2.5 Concentrations that Just Meet the Current Standards, Based on Adjusting 2005 PM2.5 Concentrations1 

Mortality, short-term cardiovascular log-linear, GAM (stringent), 30 df 0 day none 178 Max. positive est. = -3

(17 - 336) 178 (-146 

Mortality, short-term cardiovascular log-linear, GAM (stringent), 100 df 0 day none 174 Min. positive est. =

(25 - 322) 174

Mortality, short-term cardiovascular log-linear, GLM, 100 df 0 day none 174 Percent diff. =

(-4 - 350) 2%

Mortality, short-term cardiovascular log-linear, GAM (stringent), 30 df 1 day none 185 Max. positive est. = -3

(27 - 341) 185 (-146 

Mortality, short-term cardiovascular log-linear, GAM (stringent), 100 df 1 day none 144 Min. positive est. =

(-6 - 292) 124

Mortality, short-term cardiovascular log-linear, GLM, 100 df 1 day none 124 Percent diff. =

(-58 - 304) 49%

Mortality, short-term cardiovascular log-linear, GAM (stringent), 100 df 0 day CO 318 Max. positive est. = -3

(135 - 499) 336 (-146 

Mortality, short-term cardiovascular log-linear, GLM, 100 df 0 day CO 336 Min. positive est. =

(120 - 548) 163

Mortality, short-term cardiovascular log-linear, GAM (stringent), 100 df 1 day CO 163 Percent diff. =

(-23 - 347) 106%

Mortality, short-term cardiovascular log-linear, GLM, 100 df 1 day CO 163

(-63 - 386)

log-linear, GAM (stringent), 30 df 0 day none -15 --- 

(-83 - 51)

log-linear, GAM (stringent), 100 df 0 day none -39

(-106 - 26)

log-linear, GLM, 100 df 0 day none -33

(-114 - 44)

log-linear, GAM (stringent), 30 df 1 day none 10 Max. positive est. = --

(-58 - 76) 23

log-linear, GAM (stringent), 100 df 1 day none 23 Min. positive est. =

(-44 - 88) 5

log-linear, GLM, 100 df 1 day none 5 Percent diff. =

(-78 - 86) 360%

Mortality, short-term respiratory (COPD+)Mortality, short-term respiratory (COPD+)Mortality, short-term respiratory (COPD+)

Respiratory Mortality Associated with Short-Term Exposure to PM 2.5 -- Impact of Changing the Type of Model, with a 0-Day LagCardiovascular Mortality Associated with Short-Term Exposure to PM 2.5 -- Impact of a Copollutant ModelCardiovascular Mortality Associated with Short-Term Exposure to PM 2.5 -- Impact of Changing the Type of Model, with a 0-Day Lag

Range of Positive 

Estimates and 

Percent Difference 

Between Maximum 

and Minimum 2

Incid

Estimat

Core A

Mod

Model Lag

Other 

Pollutants 

in Model

Incidence 

Associated with 

PM2.5 Above Policy 

Relevant 

Background

Mortality, short-term respiratory (COPD+)

Respiratory Mortality Associated with Short-Term Exposure to PM 2.5 -- Impact of Changing the Type of Model, with a 1-Day Lag

Mortality, short-term respiratory (COPD+)Mortality, short-term respiratory (COPD+)

Cardiovascular Mortality Associated with Short-Term Exposure to PM 2.5 -- Impact of Changing the Type of Model, with a 1-Day Lag

Health Effects

F-34

September 2009 
Table F-31 cont'd. Sensitivity Analysis: Estimated Annual Incidence and Percent of Total Incidence of Mortality in Los Angeles, CA Ass

 Exposure to PM2.5 Concentrations that Just Meet the Current Standards, Based on Adjusting 2005 PM2.5 Concentrations1 

HA, cardiovascular log-linear, GAM (stringent), 30 df 0 day none 824 Max. positive est. = 27

(474 - 1170) 824 (3 - 

HA, cardiovascular log-linear, GAM (stringent), 100 df 0 day none 606 Min. positive est. =

(264 - 946) 606

HA, cardiovascular log-linear, GLM, 100 df 0 day none 658 Percent diff. =

(235 - 1077) 36%

HA, cardiovascular log-linear, GLM, 100 df 0 day CO 725 Max. positive est. = 27

(361 - 1087) 725 (3 - 5

HA, cardiovascular log-linear, GLM, 100 df 0 day CO 591 Min. positive est. =

(243 - 935) 591

HA, cardiovascular log-linear, GLM, 100 df 0 day CO 627 Percent diff. =

(201 - 1048) 23%

HA, cardiovascular log-linear, GAM (stringent), 100 df 0 day CO 205 Max. positive est. = 27

(-233 - 638) 304 (3 - 5

HA, cardiovascular log-linear, GLM, 100 df 0 day CO 304 Min. positive est. =

(-216 - 818) 126

HA, cardiovascular log-linear, GLM, 100 df 0 day CO 126 Percent diff. =

(-342 - 589) 141%

HA, cardiovascular log-linear, GLM, 100 df 0 day CO 142

(-396 - 672)

HA, cardiovascular log-linear, GLM, 100 df 0 day CO 348 Max. positive est. = --

(143 - 551) 348

HA, cardiovascular log-linear, GLM, 100 df 0 day CO 288 Min. positive est. =

(108 - 466) 288

HA, cardiovascular log-linear, GLM, 100 df 0 day CO 311 Percent diff. =

(86 - 533) 21%

HA, respiratory (COPD+) log-linear, GAM (stringent), 30 df 1 day none 249 Max. positive est. = --

(47 - 448) 249

HA, respiratory (COPD+) log-linear, GAM (stringent), 100 df 1 day none 157 Min. positive est. =

(-23 - 336) 157

HA, respiratory (COPD+) log-linear, GLM, 100 df 1 day none 161 Percent diff. =

(-57 - 377) 59%

Respiratory Hospital Admissions Associated with Short-Term Exposure to PM 2.5 -- Impact of Changing the Type of Model, with a 1-Day LagRespiratory Hospital Admissions Associated with Short-Term Exposure to PM 2.5 -- Impact of Changing the Type of Model, with a 0-Day LagCardiovascular Hospital Admissions Associated with Short-Term Exposure to PM 2.5 -- Impact of a Copollutant ModelCardiovascular Hospital Admissions Associated with Short-Term Exposure to PM 2.5 -- Impact of Changing the Type of Model, with a 1-Day LCardiovascular Hospital Admissions Associated with Short-Term Exposure to PM 2.5 -- Impact of Changing the Type of Model, with a 0-Day L

Range of Positive 

Estimates and 

Percent Difference 

Between Maximum 

and Minimum 2

Incid

Estimat

Core A

Mod

Model Lag

Other 

Pollutants 

in Model

Incidence 

Associated with 

PM2.5 Above Policy 

Relevant 

Background

Health Effects

F-35

September 2009 
Table F-31 cont'd. Sensitivity Analysis: Estimated Annual Incidence and Percent of Total Incidence of Mortality in Los Angeles, CA Ass

 Exposure to PM2.5 Concentrations that Just Meet the Current Standards, Based on Adjusting 2005 PM2.5 Concentrations1 

HA, respiratory (COPD+) log-linear, GAM (stringent), 30 df 2 day none 385 Max. positive est. = --

(172 - 595) 385

HA, respiratory (COPD+) log-linear, GAM (stringent), 100 df 2 day none 238 Min. positive est. =

(45 - 430) 216

HA, respiratory (COPD+) log-linear, GLM, 100 df 2 day none 216 Percent diff. =

(-25 - 452) 78%

HA, respiratory (COPD+) log-linear, GAM (stringent), 100 df 0 day NO2 88 Max. positive est. = --

(-192 - 364) 88

HA, respiratory (COPD+) log-linear, GAM (stringent), 100 df 1 day NO2 -8 Min. positive est. =

(-342 - 319) 74

HA, respiratory (COPD+) log-linear, GAM (stringent), 100 df 2 day NO2 74 Percent diff. =

(-217 - 359) 19%

HA, respiratory (COPD+) log-linear, GAM (stringent), 100 df 3 day NO2 -231

(-510 - 43)

Range of Positive 

Estimates and 

Percent Difference 

Between Maximum 

and Minimum 2

Incid

Estimat

Core A

Mod

Model Lag

Other 

Pollutants 

in Model

Incidence 

Associated with 

PM2.5 Above Policy 

Relevant 

Background

Health Effects

Respiratory Hospital Admissions Associated with Short-Term Exposure to PM 2.5 -- Impact of Changing the Type of Model, with a 2-Day LagRespiratory Hospital Admissions Associated with Short-Term Exposure to PM 2.5 -- Impact of Changing the Lag Structure, with a Copollutan

5Because "respiratory illness" was much more broadly defined in both Zanobetti and Schwartz (2009) and Bell et al. (2008) than in Moolgavkar (2003), a comparison between t

and the corresponding core analysis estimates is not shown.

1The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. Results are based on Moolgavkar (2003) [reanalysis of M

2000c)].

2The core analysis estimates for non-accidental mortality and cardiovascular mortality associated with short-term exposure to PM2.5 are from Zanobetti and Schwartz (2009). T

cardiovascular hospital admissions associated with short-term exposure to PM2.5 are from Bell et al. (2008). 

3Calculated as (maximum positive estimate - minimum positive estimate)/(minimum positive estimate).4Calculated as (Moolgavkar (2003) estimate - core analysis estimate)/(core analysis estimate).

F-36

September 2009 
Table F-32. Sensitivity Analysis: Estimated Annual Incidence and Percent of Total Incidence of Mortality in Los Angeles, CA Associated wi

 Exposure to PM2.5 Concentrations that Just Meet the Current Standards, Based on Adjusting 2006 PM2.5 Concentrations1 

Mortality, short-term non-accidental log-linear, GAM (stringent), 30 df 0 day none 265 Max. positive est. = 78

(-34 - 561) 289 (-112 - 26

Mortality, short-term non-accidental log-linear, GAM (stringent), 30 df 1 day none 289 Min. positive est. =

(0 - 576) 186

Mortality, short-term non-accidental log-linear, GAM (stringent), 30 df 2 day none 186

(-93 - 464) Percent diff. =

Mortality, short-term non-accidental log-linear, GAM (stringent), 30 df 3 day none -74 55%

(-358 - 209)

Mortality, short-term non-accidental log-linear, GAM (stringent), 30 df 4 day none -44

(-316 - 226)

Mortality, short-term non-accidental log-linear, GAM (stringent), 30 df 5 day none -276

(-569 - 15)

Mortality, short-term non-accidental log-linear, GAM (stringent), 30 df 0 day none 265 Max. positive est. = 78

(-34 - 561) 265 (-112 - 26

Mortality, short-term non-accidental log-linear, GLM, 30 df 0 day none 196 Min. positive est. =

(-167 - 556) 147

Mortality, short-term non-accidental log-linear, GAM (stringent), 100 df 0 day none 157

(-111 - 423) Percent diff. =

Mortality, short-term non-accidental log-linear, GLM, 100 df 0 day none 147 80%

(-210 - 501)

Mortality, short-term non-accidental log-linear, GAM (stringent), 30 df 1 day none 289 Max. positive est. = 78

(0 - 576) 289 (-112 - 26

Mortality, short-term non-accidental log-linear, GLM, 30 df 1 day none 269 Min. positive est. =

(-83 - 619) 49

Mortality, short-term non-accidental log-linear, GAM (stringent), 100 df 1 day none 49

(-227 - 323) Percent diff. =

Mortality, short-term non-accidental log-linear, GLM, 100 df 1 day none -5 490%

(-489 - 474)

Mortality, short-term non-accidental log-linear, GAM (stringent), 30 df 1 day CO -261 78

(-649 - 123) (-112 - 26

Mortality, short-term non-accidental log-linear, GAM (stringent), 100 df 1 day CO -162

(-518 - 191)

Mortality, short-term non-accidental log-linear, GLM, 100 df 1 day CO -162

(-579 - 250)

Non-Accidental Mortality Associated with Short-Term Exposure to P

M 2.5 -- Impact of Changing the Type of Model, with a 0-Day Lag

Incidenc

Estimate U

Core Anal

Model 

Non-Accidental Mortality Associated with Short-Term Exposure to P

M 2.5 -- Impact of Changing the Lag Structure:

Lag

Other 

Pollutants 

in Model

Incidence 

Associated with 

PM2.5 Above Policy 

Relevant 

Background

Range of Positive 

Estimates and 

Percent Difference 

Between Maximum 

and Minimum 2

Non-Accidental Mortality Associated with Short-Term Exposure to P

M 2.5 -- Impact of a Copollutant Model

Non-Accidental Mortality Associated with Short-Term Exposure to P

M 2.5 -- Impact of Changing the Type of Model, with a 1-Day Lag

Health Effects Model

F-37

September 2009 
Table F-32 cont'd. Sensitivity Analysis: Estimated Annual Incidence and Percent of Total Incidence of Mortality in Los Angeles, CA Ass

 Exposure to PM2.5 Concentrations that Just Meet the Current Standards, Based on Adjusting 2006 PM2.5 Concentrations1 

Mortality, short-term cardiovascular log-linear, GAM (stringent), 30 df 0 day none 165 Max. positive est. = -3

(16 - 312) 165 (-134 

Mortality, short-term cardiovascular log-linear, GAM (stringent), 100 df 0 day none 161 Min. positive est. =

(23 - 298) 161

Mortality, short-term cardiovascular log-linear, GLM, 100 df 0 day none 161 Percent diff. =

(-3 - 324) 2%

Mortality, short-term cardiovascular log-linear, GAM (stringent), 30 df 1 day none 171 Max. positive est. = -3

(25 - 315) 171 (-134 

Mortality, short-term cardiovascular log-linear, GAM (stringent), 100 df 1 day none 133 Min. positive est. =

(-6 - 271) 115

Mortality, short-term cardiovascular log-linear, GLM, 100 df 1 day none 115 Percent diff. =

(-53 - 281) 49%

Mortality, short-term cardiovascular log-linear, GAM (stringent), 100 df 0 day CO 294 Max. positive est. = -3

(125 - 462) 311 (-134 

Mortality, short-term cardiovascular log-linear, GLM, 100 df 0 day CO 311 Min. positive est. =

(111 - 508) 151

Mortality, short-term cardiovascular log-linear, GAM (stringent), 100 df 1 day CO 151 Percent diff. =

(-21 - 322) 106%

Mortality, short-term cardiovascular log-linear, GLM, 100 df 1 day CO 151

(-58 - 358)

log-linear, GAM (stringent), 30 df 0 day none -14 --- 

(-77 - 47)

log-linear, GAM (stringent), 100 df 0 day none -36

(-98 - 24)

log-linear, GLM, 100 df 0 day none -31

(-105 - 41)

log-linear, GAM (stringent), 30 df 1 day none 10 Max. positive est. = --

(-54 - 71) 22

log-linear, GAM (stringent), 100 df 1 day none 22 Min. positive est. =

(-40 - 82) 5

log-linear, GLM, 100 df 1 day none 5 Percent diff. =

(-72 - 79) 340%

Mortality, short-term respiratory (COPD+)Mortality, short-term respiratory (COPD+)Mortality, short-term respiratory (COPD+)

Respiratory Mortality Associated with Short-Term Exposure to PM 2.5 -- Impact of Changing the Type of Model, with a 0-Day LagCardiovascular Mortality Associated with Short-Term Exposure to PM 2.5 -- Impact of a Copollutant ModelCardiovascular Mortality Associated with Short-Term Exposure to PM 2.5 -- Impact of Changing the Type of Model, with a 0-Day Lag

Range of Positive 

Estimates and 

Percent Difference 

Between Maximum 

and Minimum 2

Incid

Estimat

Core A

Mod

Model Lag

Other 

Pollutants 

in Model

Incidence 

Associated with 

PM2.5 Above Policy 

Relevant 

Background

Mortality, short-term respiratory (COPD+)

Respiratory Mortality Associated with Short-Term Exposure to PM 2.5 -- Impact of Changing the Type of Model, with a 1-Day Lag

Mortality, short-term respiratory (COPD+)Mortality, short-term respiratory (COPD+)

Cardiovascular Mortality Associated with Short-Term Exposure to PM 2.5 -- Impact of Changing the Type of Model, with a 1-Day Lag

Health Effects

F-38

September 2009 
Table F-32 cont'd. Sensitivity Analysis: Estimated Annual Incidence and Percent of Total Incidence of Mortality in Los Angeles, CA Ass

 Exposure to PM2.5 Concentrations that Just Meet the Current Standards, Based on Adjusting 2006 PM2.5 Concentrations1 

HA, cardiovascular log-linear, GAM (stringent), 30 df 0 day none 775 Max. positive est. = 25

(446 - 1102) 775 (3 - 

HA, cardiovascular log-linear, GAM (stringent), 100 df 0 day none 570 Min. positive est. =

(248 - 890) 570

HA, cardiovascular log-linear, GLM, 100 df 0 day none 619 Percent diff. =

(221 - 1014) 36%

HA, cardiovascular log-linear, GAM (stringent), 30 df 1 day none 683 Max. positive est. = 25

(339 - 1024) 683 (3 - 

HA, cardiovascular log-linear, GAM (stringent), 100 df 1 day none 556 Min. positive est. =

(229 - 881) 556

HA, cardiovascular log-linear, GLM, 100 df 1 day none 590 Percent diff. =

(189 - 987) 23%

HA, cardiovascular log-linear, GAM (stringent), 100 df 0 day CO 193 Max. positive est. = 25

(-219 - 600) 286 (3 - 5

HA, cardiovascular log-linear, GLM, 100 df 0 day CO 286 Min. positive est. =

(-203 - 770) 119

HA, cardiovascular log-linear, GAM (stringent), 100 df 1 day CO 119 Percent diff. =

(-322 - 555) 140%

HA, cardiovascular log-linear, GLM, 100 df 1 day CO 133

(-372 - 633)

HA, respiratory (COPD+) log-linear, GAM (stringent), 30 df 0 day none 322 Max. positive est. = --

(132 - 510) 322

HA, respiratory (COPD+) log-linear, GAM (stringent), 100 df 0 day none 267 Min. positive est. =

(100 - 432) 267

HA, respiratory (COPD+) log-linear, GLM, 100 df 0 day none 288 Percent diff. =

(79 - 494) 21%

HA, respiratory (COPD+) log-linear, GAM (stringent), 30 df 1 day none 230 Max. positive est. = --

(43 - 415) 230

HA, respiratory (COPD+) log-linear, GAM (stringent), 100 df 1 day none 146 Min. positive est. =

(-21 - 311) 146

HA, respiratory (COPD+) log-linear, GLM, 100 df 1 day none 149 Percent diff. =

(-53 - 349) 58%

Respiratory Hospital Admissions Associated with Short-Term Exposure to PM 2.5 -- Impact of Changing the Type of Model, with a 1-Day LagCardiovascular Hospital Admissions Associated with Short-Term Exposure to PM 2.5 -- Impact of Changing the Type of Model, with a 0-Day LRespiratory Hospital Admissions Associated with Short-Term Exposure to PM 2.5 -- Impact of Changing the Type of Model, with a 0-Day LagCardiovascular Hospital Admissions Associated with Short-Term Exposure to PM 2.5 -- Impact of a Copollutant Model

Range of Positive 

Estimates and 

Percent Difference 

Between Maximum 

and Minimum 2

Incid

Estimat

Core A

Mod

Model Lag

Other 

Pollutants 

in Model

Incidence 

Associated with 

PM2.5 Above Policy 

Relevant 

Background

Cardiovascular Hospital Admissions Associated with Short-Term Exposure to PM 2.5 -- Impact of Changing the Type of Model, with a 1-Day L

Health Effects

F-39

September 2009 
Table F-32 cont'd. Sensitivity Analysis: Estimated Annual Incidence and Percent of Total Incidence of Mortality in Los Angeles, CA Ass

 Exposure to PM2.5 Concentrations that Just Meet the Current Standards, Based on Adjusting 2006 PM2.5 Concentrations1 

HA, respiratory (COPD+) log-linear, GAM (stringent), 30 df 2 day none 357 Max. positive est. = --

(160 - 552) 357

HA, respiratory (COPD+) log-linear, GAM (stringent), 100 df 2 day none 221 Min. positive est. =

(41 - 398) 200

HA, respiratory (COPD+) log-linear, GLM, 100 df 2 day none 200 Percent diff. =

(-23 - 419) 79%

HA, respiratory (COPD+) log-linear, GAM (stringent), 100 df 0 day NO2 82 Max. positive est. = --

(-178 - 337) 82

HA, respiratory (COPD+) log-linear, GAM (stringent), 100 df 1 day NO2 -8 Min. positive est. =

(-316 - 295) 68

HA, respiratory (COPD+) log-linear, GAM (stringent), 100 df 2 day NO2 68 Percent diff. =

(-200 - 332) 21%

HA, respiratory (COPD+) log-linear, GAM (stringent), 100 df 3 day NO2 -214

(-471 - 40)

Range of Positive 

Estimates and 

Percent Difference 

Between Maximum 

and Minimum 2

Incid

Estimat

Core A

Mod

Model Lag

Other 

Pollutants 

in Model

Incidence 

Associated with 

PM2.5 Above Policy 

Relevant 

Background

Health Effects

Respiratory Hospital Admissions Associated with Short-Term Exposure to PM 2.5 -- Impact of Changing the Type of Model, with a 2-Day LagRespiratory Hospital Admissions Associated with Short-Term Exposure to PM 2.5 -- Impact of Changing the Lag Structure, with a Copollutan

1The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. Results are based on Moolgavkar (2003) [reanalysis of M

2000c)].

2The core analysis estimates for non-accidental mortality and cardiovascular mortality associated with short-term exposure to PM2.5 are from Zanobetti and Schwartz (2009). T

cardiovascular hospital admissions associated with short-term exposure to PM2.5 are from Bell et al. (2008). 

3Calculated as (maximum positive estimate - minimum positive estimate)/(minimum positive estimate).4Calculated as (Moolgavkar (2003) estimate - core analysis estimate)/(core analysis estimate).5Because "respiratory illness" was much more broadly defined in both Zanobetti and Schwartz (2009) and Bell et al. (2008) than in Moolgavkar (2003), a comparison between t

and the corresponding core analysis estimates is not shown.

F-40

September 2009 
Table F-33. Sensitivity Analysis: Estimated Annual Incidence and Percent of Total Incidence of Mortality in Los Angeles, CA Associated wi

 Exposure to PM2.5 Concentrations that Just Meet the Current Standards, Based on Adjusting 2007 PM2.5 Concentrations1 

Mortality, short-term non-accidental log-linear, GAM (stringent), 30 df 0 day none 267 Max. positive est. = 79

(-34 - 566) 292 (-113 - 27

Mortality, short-term non-accidental log-linear, GAM (stringent), 30 df 1 day none 292 Min. positive est. =

(0 - 582) 188

Mortality, short-term non-accidental log-linear, GAM (stringent), 30 df 2 day none 188

(-94 - 468) Percent diff. =

Mortality, short-term non-accidental log-linear, GAM (stringent), 30 df 3 day none -75 55%

(-362 - 211)

Mortality, short-term non-accidental log-linear, GAM (stringent), 30 df 4 day none -45

(-320 - 228)

Mortality, short-term non-accidental log-linear, GAM (stringent), 30 df 5 day none -279

(-575 - 15)

Mortality, short-term non-accidental log-linear, GAM (stringent), 30 df 0 day none 267 Max. positive est. = 79

(-34 - 566) 267 (-113 - 27

Mortality, short-term non-accidental log-linear, GLM, 30 df 0 day none 198 Min. positive est. =

(-169 - 562) 149

Mortality, short-term non-accidental log-linear, GAM (stringent), 100 df 0 day none 159

(-112 - 427) Percent diff. =

Mortality, short-term non-accidental log-linear, GLM, 100 df 0 day none 149 79%

(-212 - 506)

Mortality, short-term non-accidental log-linear, GAM (stringent), 30 df 1 day none 292 Max. positive est. = 79

(0 - 582) 292 (-113 - 27

Mortality, short-term non-accidental log-linear, GLM, 30 df 1 day none 272 Min. positive est. =

(-84 - 625) 50

Mortality, short-term non-accidental log-linear, GAM (stringent), 100 df 1 day none 50

(-229 - 326) Percent diff. =

Mortality, short-term non-accidental log-linear, GLM, 100 df 1 day none -5 484%

(-494 - 479)

Mortality, short-term non-accidental log-linear, GAM (stringent), 30 df 1 day CO -264 79

(-656 - 124) (-113 - 27

Mortality, short-term non-accidental log-linear, GAM (stringent), 100 df 1 day CO -164

(-524 - 192)

Mortality, short-term non-accidental log-linear, GLM, 100 df 1 day CO -164

(-585 - 252)

Non-Accidental Mortality Associated with Short-Term Exposure to P

M 2.5 -- Impact of a Copollutant Model

Non-Accidental Mortality Associated with Short-Term Exposure to P

M 2.5 -- Impact of Changing the Type of Model, with a 0-Day Lag

Non-Accidental Mortality Associated with Short-Term Exposure to P

M 2.5 -- Impact of Changing the Lag Structure:

Incidence 

Associated with 

PM2.5 Above Policy 

Relevant 

Background

Range of Positive 

Estimates and 

Percent Difference 

Between Maximum 

and Minimum 2

Incidenc

Estimate U

Core Anal

Model 

Health Effects Model Lag

Other 

Pollutants 

in Model

Non-Accidental Mortality Associated with Short-Term Exposure to P

M 2.5 -- Impact of Changing the Type of Model, with a 1-Day Lag

F-41

September 2009 
Table F-33 cont'd. Sensitivity Analysis: Estimated Annual Incidence and Percent of Total Incidence of Mortality in Los Angeles, CA Ass

 Exposure to PM2.5 Concentrations that Just Meet the Current Standards, Based on Adjusting 2007 PM2.5 Concentrations1 

Mortality, short-term cardiovascular log-linear, GAM (stringent), 30 df 0 day none 166 Max. positive est. = -3

(16 - 314) 166 (-136 

Mortality, short-term cardiovascular log-linear, GAM (stringent), 100 df 0 day none 163 Min. positive est. =

(24 - 301) 163

Mortality, short-term cardiovascular log-linear, GLM, 100 df 0 day none 163 Percent diff. =

(-3 - 327) 2%

Mortality, short-term cardiovascular log-linear, GAM (stringent), 30 df 1 day none 173 Max. positive est. = -3

(26 - 318) 173 (-136 

Mortality, short-term cardiovascular log-linear, GAM (stringent), 100 df 1 day none 134 Min. positive est. =

(-6 - 273) 116

Mortality, short-term cardiovascular log-linear, GLM, 100 df 1 day none 116 Percent diff. =

(-54 - 284) 49%

Mortality, short-term cardiovascular log-linear, GAM (stringent), 100 df 0 day CO 297 Max. positive est. = -3

(126 - 466) 314 (-136 

Mortality, short-term cardiovascular log-linear, GLM, 100 df 0 day CO 314 Min. positive est. =

(112 - 512) 153

Mortality, short-term cardiovascular log-linear, GAM (stringent), 100 df 1 day CO 153 Percent diff. =

(-21 - 325) 105%

Mortality, short-term cardiovascular log-linear, GLM, 100 df 1 day CO 153

(-59 - 361)

log-linear, GAM (stringent), 30 df 0 day none -14 --- 

(-78 - 47)

log-linear, GAM (stringent), 100 df 0 day none -36

(-99 - 24)

log-linear, GLM, 100 df 0 day none -31

(-106 - 41)

log-linear, GAM (stringent), 30 df 1 day none 10 Max. positive est. = --

(-54 - 71) 22

log-linear, GAM (stringent), 100 df 1 day none 22 Min. positive est. =

(-41 - 82) 5

log-linear, GLM, 100 df 1 day none 5 Percent diff. =

(-73 - 80) 340%

Mortality, short-term respiratory (COPD+)Mortality, short-term respiratory (COPD+)Mortality, short-term respiratory (COPD+)

Respiratory Mortality Associated with Short-Term Exposure to PM 2.5 -- Impact of Changing the Type of Model, with a 1-Day LagCardiovascular Mortality Associated with Short-Term Exposure to PM 2.5 -- Impact of a Copollutant ModelCardiovascular Mortality Associated with Short-Term Exposure to PM 2.5 -- Impact of Changing the Type of Model, with a 0-Day Lag

Mortality, short-term respiratory (COPD+)Mortality, short-term respiratory (COPD+)

Respiratory Mortality Associated with Short-Term Exposure to PM 2.5 -- Impact of Changing the Type of Model, with a 0-Day Lag

Mortality, short-term respiratory (COPD+)

Cardiovascular Mortality Associated with Short-Term Exposure to PM 2.5 -- Impact of Changing the Type of Model, with a 1-Day Lag

Health Effects Model Lag

Other 

Pollutants 

in Model

Incidence 

Associated with 

PM2.5 Above Policy 

Relevant 

Background

Range of Positive 

Estimates and 

Percent Difference 

Between Maximum 

and Minimum 2

Incid

Estimat

Core A

Mod

F-42

September 2009 
Table F-33 cont'd. Sensitivity Analysis: Estimated Annual Incidence and Percent of Total Incidence of Mortality in Los Angeles, CA Ass

 Exposure to PM2.5 Concentrations that Just Meet the Current Standards, Based on Adjusting 2007 PM2.5 Concentrations1 

HA, cardiovascular log-linear, GAM (stringent), 30 df 0 day none 798 Max. positive est. = 26

(459 - 1134) 798 (3 - 

HA, cardiovascular log-linear, GAM (stringent), 100 df 0 day none 587 Min. positive est. =

(256 - 916) 587

HA, cardiovascular log-linear, GLM, 100 df 0 day none 637 Percent diff. =

(228 - 1043) 36%

HA, cardiovascular log-linear, GAM (stringent), 30 df 1 day none 703 Max. positive est. = 26

(349 - 1053) 703 (3 - 

HA, cardiovascular log-linear, GAM (stringent), 100 df 1 day none 572 Min. positive est. =

(235 - 906) 572

HA, cardiovascular log-linear, GLM, 100 df 1 day none 607 Percent diff. =

(195 - 1015) 23%

HA, cardiovascular log-linear, GAM (stringent), 100 df 0 day CO 198 Max. positive est. = 26

(-225 - 618) 295 (3 - 5

HA, cardiovascular log-linear, GLM, 100 df 0 day CO 295 Min. positive est. =

(-209 - 792) 122

HA, cardiovascular log-linear, GAM (stringent), 100 df 1 day CO 122 Percent diff. =

(-331 - 571) 142%

HA, cardiovascular log-linear, GLM, 100 df 1 day CO 137

(-383 - 651)

HA, respiratory (COPD+) log-linear, GAM (stringent), 30 df 0 day none 325 Max. positive est. = --

(134 - 515) 325

HA, respiratory (COPD+) log-linear, GAM (stringent), 100 df 0 day none 269 Min. positive est. =

(101 - 436) 269

HA, respiratory (COPD+) log-linear, GLM, 100 df 0 day none 291 Percent diff. =

(80 - 498) 21%

HA, respiratory (COPD+) log-linear, GAM (stringent), 30 df 1 day none 233 Max. positive est. = --

(44 - 419) 233

HA, respiratory (COPD+) log-linear, GAM (stringent), 100 df 1 day none 147 Min. positive est. =

(-22 - 314) 147

HA, respiratory (COPD+) log-linear, GLM, 100 df 1 day none 151 Percent diff. =

(-53 - 353) 59%

Respiratory Hospital Admissions Associated with Short-Term Exposure to PM 2.5 -- Impact of Changing the Type of Model, with a 1-Day LagRespiratory Hospital Admissions Associated with Short-Term Exposure to PM 2.5 -- Impact of Changing the Type of Model, with a 0-Day LagCardiovascular Hospital Admissions Associated with Short-Term Exposure to PM 2.5 -- Impact of a Copollutant ModelCardiovascular Hospital Admissions Associated with Short-Term Exposure to PM 2.5 -- Impact of Changing the Type of Model, with a 1-Day L

Range of Positive 

Estimates and 

Percent Difference 

Between Maximum 

and Minimum 2

Incid

Estimat

Core A

Mod

Model Lag

Other 

Pollutants 

in Model

Incidence 

Associated with 

PM2.5 Above Policy 

Relevant 

Background

Cardiovascular Hospital Admissions Associated with Short-Term Exposure to PM 2.5 -- Impact of Changing the Type of Model, with a 0-Day L

Health Effects

F-43

September 2009 
Table F-33 cont'd. Sensitivity Analysis: Estimated Annual Incidence and Percent of Total Incidence of Mortality in Los Angeles, CA Ass

 Exposure to PM2.5 Concentrations that Just Meet the Current Standards, Based on Adjusting 2007 PM2.5 Concentrations1 

HA, respiratory (COPD+) log-linear, GAM (stringent), 30 df 2 day none 360 Max. positive est. = --

(161 - 557) 360

HA, respiratory (COPD+) log-linear, GAM (stringent), 100 df 2 day none 223 Min. positive est. =

(42 - 402) 201

HA, respiratory (COPD+) log-linear, GLM, 100 df 2 day none 201 Percent diff. =

(-23 - 423) 79%

HA, respiratory (COPD+) log-linear, GAM (stringent), 100 df 0 day NO2 82 Max. positive est. = --

(-180 - 340) 82

HA, respiratory (COPD+) log-linear, GAM (stringent), 100 df 1 day NO2 -8 Min. positive est. =

(-320 - 298) 69

HA, respiratory (COPD+) log-linear, GAM (stringent), 100 df 2 day NO2 69 Percent diff. =

(-202 - 335) 19%

HA, respiratory (COPD+) log-linear, GAM (stringent), 100 df 3 day NO2 -216

(-476 - 40)

Health Effects Model Lag

Other 

Pollutants 

in Model

Incidence 

Associated with 

PM2.5 Above Policy 

Relevant 

Background

Range of Positive 

Estimates and 

Percent Difference 

Between Maximum 

and Minimum 2

Incid

Estimat

Core A

Mod

Respiratory Hospital Admissions Associated with Short-Term Exposure to PM 2.5 -- Impact of Changing the Type of Model, with a 2-Day LagRespiratory Hospital Admissions Associated with Short-Term Exposure to PM 2.5 -- Impact of Changing the Lag Structure, with a Copollutan

5Because "respiratory illness" was much more broadly defined in both Zanobetti and Schwartz (2009) and Bell et al. (2008) than in Moolgavkar (2003), a comparison between t

and the corresponding core analysis estimates is not shown.

1The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. Results are based on Moolgavkar (2003) [reanalysis of M

2000c)].

2The core analysis estimates for non-accidental mortality and cardiovascular mortality associated with short-term exposure to PM2.5 are from Zanobetti and Schwartz (2009). T

cardiovascular hospital admissions associated with short-term exposure to PM2.5 are from Bell et al. (2008). 

3Calculated as (maximum positive estimate - minimum positive estimate)/(minimum positive estimate).4Calculated as (Moolgavkar (2003) estimate - core analysis estimate)/(core analysis estimate).

F-44

September 2009 
Table F-34. Sensitivity Analysis: Estimated Annual Incidence of Non-Accidental Mortality Associated with Short-Term Exposure to 

 PM2.5 Concentrations that Just Meet the Current and Alternative Standards, Based on Adjusting 2005 PM2.5 Concentrations: 

 Comparison of Proportional and Hybrid Rollback Methods1

15/35 2 13/35 12/35 13/30 12/25

Proportional 256 224 206 219 182

(104 - 406) (91 - 355) (84 - 327) (89 - 348) (74 - 289)

Hybrid 254 230 211 217 181

(103 - 403) (93 - 365) (86 - 335) (88 - 345) (73 - 287)

Percent Difference 3 -1% 3% 2% -1% -1%

Proportional 38 33 30 33 27

(-60 - 135) (-51 - 115) (-46 - 105) (-51 - 115) (-42 - 96)

Hybrid 39 33 30 33 28

(-60 - 136) (-51 - 115) (-46 - 105) (-51 - 115) (-43 - 98)

Percent Difference 3% 0% 0% 0% 4%

Proportional 141 129 119 121 100

(-25 - 305) (-23 - 280) (-21 - 257) (-21 - 260) (-18 - 216)

Hybrid 146 143 132 125 103

(-26 - 315) (-25 - 310) (-23 - 284) (-22 - 270) (-18 - 224)

Percent Difference 4% 11% 11% 3% 3%

Proportional 85 85 80 72 60

(-121 - 289) (-121 - 289) (-114 - 273) (-103 - 247) (-86 - 205)

Hybrid 94 92 85 81 67

(-135 - 323) (-132 - 315) (-121 - 289) (-116 - 276) (-96 - 229)

Percent Difference 11% 8% 6% 13% 12%

Proportional 714 696 639 611 507

(419 - 1007) (408 - 981) (375 - 902) (358 - 861) (297 - 716)

Hybrid 726 695 638 621 515

(426 - 1023) (408 - 979) (375 - 900) (364 - 876) (302 - 727)

Percent Difference 2% 0% 0% 2% 2%

Proportional 135 135 135 116 96

(40 - 230) (40 - 230) (40 - 230) (34 - 197) (28 - 163)

Hybrid 163 158 145 140 116

(48 - 277) (46 - 268) (43 - 246) (41 - 237) (34 - 197)

Percent Difference 21% 17% 7% 21% 21%

Proportional 252 219 201 215 179

(73 - 429) (63 - 373) (58 - 342) (62 - 367) (51 - 305)

Hybrid 266 228 210 228 191

(77 - 452) (66 - 389) (61 - 357) (66 - 389) (55 - 325)

Percent Difference 6% 4% 4% 6% 7%

3 Calculated as (mortality based on hybrid rollbacks - mortality based on proportional rollbacks)/(mortality based on proportional rollbacks).

 Pittsburgh, PA

 St. Louis, MO

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 

Incidence of Non-Accidental Mortality Associated with Short-Term Exposure to PM2.5 

Concentrations that Just Meet the Current and Alternative Combinations of Annual (n) and 

Daily (m) Standards (Standard Combination Denoted n/m):

1Based on location-specific single pollutant concentration-response function estimates from Zanobetti and Schwartz (2009) that have been "shrunken" towards the appropriate 

regional means. "Shrunken" coefficient estimates and their standard errors were sent to EPA by A. Zanobetti via email. Numbers are rounded to the nearest whole number. 

Risk Assessment 

Location

 Baltimore, MD

 Birmingham, AL

Type of Rollback

 Detroit, MI

 Los Angeles, CA

 New York, NY

F-45

September 2009 
Table F-35. Sensitivity Analysis: Estimated Annual Incidence of Non-Accidental Mortality Associated with Short-Term Exposure to PM2.5

 Concentrations that Just Meet the Current and Alternative Standards, Based on Adjusting 2006 PM2.5 Concentrations: 

 Comparison of Proportional and Hybrid Rollback Methods1

15/35 2 13/35 12/35 13/30 12/25

Proportional 234 205 188 201 167

(95 - 372) (83 - 325) (76 - 299) (81 - 318) (68 - 265)

Hybrid 233 210 193 199 165

(94 - 369) (85 - 334) (78 - 307) (81 - 316) (67 - 263)

Percent Difference 3 0% 2% 3% -1% -1%

Proportional 38 32 29 32 26

(-59 - 132) (-50 - 113) (-45 - 103) (-50 - 113) (-41 - 94)

Hybrid 38 32 29 32 27

(-59 - 132) (-50 - 113) (-45 - 103) (-50 - 113) (-42 - 96)

Percent Difference 0% 0% 0% 0% 4%

Proportional 117 108 99 100 83

(-21 - 254) (-19 - 233) (-17 - 214) (-18 - 217) (-15 - 180)

Hybrid 121 119 109 104 86

(-21 - 262) (-21 - 258) (-19 - 237) (-18 - 224) (-15 - 186)

Percent Difference 3% 10% 10% 4% 4%

Proportional 78 78 74 67 55

(-112 - 267) (-112 - 267) (-106 - 252) (-96 - 228) (-79 - 189)

Hybrid 87 85 78 74 62

(-125 - 299) (-122 - 291) (-112 - 268) (-107 - 255) (-88 - 211)

Percent Difference 12% 9% 5% 10% 13%

Proportional 654 637 585 559 464

(384 - 922) (374 - 898) (343 - 826) (328 - 789) (272 - 655)

Hybrid 664 635 584 568 471

(390 - 936) (373 - 896) (343 - 824) (333 - 801) (276 - 665)

Percent Difference 2% 0% 0% 2% 2%

Proportional 122 122 122 104 87

(36 - 208) (36 - 208) (36 - 208) (31 - 177) (25 - 147)

Hybrid 147 141 130 125 104

(43 - 249) (41 - 240) (38 - 221) (37 - 213) (30 - 177)

Percent Difference 20% 16% 7% 20% 20%

Proportional 214 185 170 183 151

(62 - 364) (53 - 316) (49 - 290) (53 - 311) (44 - 258)

Hybrid 225 194 178 194 162

(65 - 384) (56 - 330) (51 - 303) (56 - 330) (47 - 276)

Percent Difference 5% 5% 5% 6% 7%

3 Calculated as (mortality based on hybrid rollbacks - mortality based on proportional rollbacks)/(mortality based on proportional rollbacks).

 Baltimore, MD

 Birmingham, AL

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 

Incidence of Non-Accidental Mortality Associated with Short-Term Exposure to PM2.5 

Concentrations that Just Meet the Current and Alternative Combinations of Annual (n) and 

Daily (m) Standards (Standard Combination Denoted n/m):

1Based on location-specific single pollutant concentration-response function estimates from Zanobetti and Schwartz (2009) that have been "shrunken" towards the appropriate 

regional means. "Shrunken" coefficient estimates and their standard errors were sent to EPA by A. Zanobetti via email. Numbers are rounded to the nearest whole number. 

Risk Assessment 

Location Type of Rollback

 St. Louis, MO

 Detroit, MI

 Los Angeles, CA

 New York, NY

 Pittsburgh, PA

F-46

September 2009 
Table F-36. Sensitivity Analysis: Estimated Annual Incidence of Non-Accidental Mortality Associated with Short-Term Exposure to PM2.5

 Concentrations that Just Meet the Current and Alternative Standards, Based on Adjusting 2007 PM2.5 Concentrations: 

 Comparison of Proportional and Hybrid Rollback Methods1

15/35 2 13/35 12/35 13/30 12/25

Proportional 225 197 181 192 160

(91 - 357) (80 - 312) (73 - 287) (78 - 306) (65 - 254)

Hybrid 223 202 185 191 158

(90 - 354) (82 - 320) (75 - 294) (77 - 303) (64 - 252)

Percent Difference 3 -1% 3% 2% -1% -1%

Proportional 37 32 29 32 26

(-58 - 131) (-49 - 112) (-45 - 102) (-49 - 112) (-41 - 93)

Hybrid 37 32 29 32 27

(-58 - 132) (-49 - 112) (-45 - 102) (-49 - 112) (-42 - 95)

Percent Difference 0% 0% 0% 0% 4%

Proportional 112 102 94 95 79

(-20 - 242) (-18 - 222) (-16 - 204) (-17 - 207) (-14 - 171)

Hybrid 116 113 104 99 82

(-20 - 250) (-20 - 245) (-18 - 225) (-17 - 214) (-14 - 177)

Percent Difference 4% 11% 11% 4% 4%

Proportional 79 79 74 67 56

(-113 - 270) (-113 - 270) (-107 - 255) (-97 - 231) (-80 - 191)

Hybrid 88 86 79 75 62

(-126 - 302) (-123 - 294) (-113 - 270) (-108 - 258) (-89 - 213)

Percent Difference 11% 9% 7% 12% 11%

Proportional 659 642 590 564 468

(387 - 930) (377 - 906) (346 - 833) (331 - 795) (274 - 661)

Hybrid 670 641 589 573 476

(393 - 944) (376 - 904) (346 - 831) (336 - 808) (279 - 671)

Percent Difference 2% 0% 0% 2% 2%

Proportional 123 123 123 105 87

(36 - 209) (36 - 209) (36 - 209) (31 - 179) (26 - 148)

Hybrid 147 142 131 126 104

(43 - 250) (42 - 242) (38 - 222) (37 - 214) (31 - 178)

Percent Difference 20% 15% 7% 20% 20%

Proportional 222 193 177 190 157

(64 - 378) (56 - 328) (51 - 301) (55 - 323) (45 - 268)

Hybrid 234 201 185 201 168

(68 - 399) (58 - 343) (53 - 315) (58 - 343) (48 - 287)

Percent Difference 5% 4% 5% 6% 7%

3 Calculated as (mortality based on hybrid rollbacks - mortality based on proportional rollbacks)/(mortality based on proportional rollbacks).

Incidence of Non-Accidental Mortality Associated with Short-Term Exposure to PM2.5 

Concentrations that Just Meet the Current and Alternative Combinations of Annual (n) and 

Daily (m) Standards (Standard Combination Denoted n/m):

1Based on location-specific single pollutant concentration-response function estimates from Zanobetti and Schwartz (2009) that have been "shrunken" towards the appropriate 

regional means. "Shrunken" coefficient estimates and their standard errors were sent to EPA by A. Zanobetti via email. Numbers are rounded to the nearest whole number. 

Risk Assessment 

Location Type of Rollback

 Detroit, MI

 Birmingham, AL

 Baltimore, MD

 Los Angeles, CA

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 

 St. Louis, MO

 Pittsburgh, PA

 New York, NY

F-47

September 2009 
Table F-37. Multi-Factor Sensitivity Analysis: Impact of Using a Log-Linear vs. a Log-Log Model, Estimating Incidence Down to the Low

 Measured Level (LML) in the Study vs. PRB, and Using a Proportional vs. a Hybrid Rollback to Estimate the Incidence of All Ca and Ischemic Heart Disease Mortality Associated with Long-Term Exposure to PM2.5 Concentrations that Just Meet the Current 

 Standards, Based on Adjusting 2005 PM2.5 Concentrations1

Modeling Choices:

Fixed Effects (FE) Log-linear vs. Random Effects (RE) log-log model FE Log-Linear FE Log-Linear FE Log-Linear FE Log-Linear RE Log-Log RE Log-Log RE 

Down to LML (5.8 ug/m3) vs. PRB LML LML PRB PRB LML LML 

Proportional vs. hybrid rollback Proportional Hybrid Proportional Hybrid Proportional Hybrid Pro

1432 1775 2934 3268 3526 4121 

(911 - 1948) (1131 - 2412) (1876 - 3972) (2091 - 4418) (2179 - 4841) (2551 - 5644) (88

Percent Difference: 3 --- 24% 105% 128% 146% 188% 

1330 1634 2621 2894 2652 3061 

(1083 - 1572) (1334 - 1927) (2156 - 3067) (2386 - 3380) (1878 - 3376) (2180 - 3877) (64

Percent Difference: --- 23% 97% 118% 99% 130% 

547 732 1201 

(349 - 743) (468 - 991) (745 - 1641) (25

Percent Difference: --- --- 34% --- 120% --- 

347 571 614 

(284 - 409) (472 - 665) (439 - 774) (12

Percent Difference --- --- 65% --- 77% --- 

Incidence of Mortality Associated with Long-Term Exposure to PM2.5 Concentration

Los Angeles, CA

 All Cause Mortality Ischemic Heart Disease Mortality

2Estimates Based on Krewski et al. (2009), exposure period from 1999 - 2000. The fixed effects log-linear estimates are from Table 33, using models with 44 individual and 7 eco

effects log-log estimates are from Table 11, "MSA and DIFF" rows.

3 Percent differences are calculated relative to the model selections used in the core analysis (fixed effects log-linear model; LML, and proportional rollbacks). So, for example, th

all cause mortality in Los Angeles resulting from changing from the core analysis input selections to instead using (1) a fixed effects log-linear model, (2) PRB, and (3) hybrid rollb147%. 

4 Philadelphia was not among the risk assessment urban areas for which hybrid rollbacks were calculated.

Philadelphia, PA

 All Cause Mortality Ischemic Heart Disease Mortality

1The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 

---

--- ---

--- 

--- 4

---

F-48

September 2009 
Table F-38. Multi-Factor Sensitivity Analysis: Impact of Using a Log-Linear vs. a Log-Log Model, Estimating Incidence Down to the Low

 Measured Level (LML) in the Study vs. PRB, and Using a Proportional vs. a Hybrid Rollback to Estimate the Incidence of All Ca and Ischemic Heart Disease Mortality Associated with Long-Term Exposure to PM2.5 Concentrations that Just Meet the Current 

 Standards, Based on Adjusting 2006 PM2.5 Concentrations1

Modeling Choices:

Fixed Effects (FE) Log-linear vs. Random Effects (RE) log-log model FE Log-Linear FE Log-Linear FE Log-Linear FE Log-Linear RE Log-Log RE Log-Log RE 

Down to LML (5.8 ug/m3) vs. PRB LML LML PRB PRB LML LML 

Proportional vs. hybrid rollback Proportional Hybrid Proportional Hybrid Proportional Hybrid Pro

1221 1540 2738 3048 3130 3726 

(776 - 1662) (980 - 2094) (1749 - 3709) (1949 - 4125) (1931 - 4303) (2304 - 5112) (86

Percent Difference: 3 --- 26% 124% 150% 156% 205% 

1140 1426 2459 2716 2374 2792 

(927 - 1349) (1163 - 1685) (2020 - 2882) (2236 - 3177) (1675 - 3034) (1981 - 3549) (63

Percent Difference: --- 25% 116% 138% 108% 145% 

536 923 1182 

(341 - 727) (591 - 1246) (733 - 1617) (25

Percent Difference: --- --- 72% --- 121% --- 

340 564 606 

(279 - 401) (466 - 657) (433 - 764) (12

Percent Difference --- --- 66% --- 78% --- 

Incidence of Mortality Associated with Long-Term Exposure to PM2.5 Concentration

Los Angeles, CA

 All Cause Mortality Ischemic Heart Disease Mortality

Philadelphia, PA

 All Cause Mortality Ischemic Heart Disease Mortality

1The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 

--- 4

2Estimates Based on Krewski et al. (2009), exposure period from 1999 - 2000. The fixed effects log-linear estimates are from Table 33, using models with 44 individual and 7 eco

effects log-log estimates are from Table 11, "MSA and DIFF" rows.

3 Percent differences are calculated relative to the model selections used in the core analysis (fixed effects log-linear model; LML, and proportional rollbacks). So, for example, th

all cause mortality in Los Angeles resulting from changing from the core analysis input selections to instead using (1) a fixed effects log-linear model, (2) PRB, and (3) hybrid rollb147%. 

4 Philadelphia was not among the risk assessment urban areas for which hybrid rollbacks were calculated.

------

---

--- ---

F-49

September 2009 
Table F-39. Multi-Factor Sensitivity Analysis: Impact of Using a Log-Linear vs. a Log-Log Model, Estimating Incidence Down to the Low

 Measured Level (LML) in the Study vs. PRB, and Using a Proportional vs. a Hybrid Rollback to Estimate the Incidence of All Ca and Ischemic Heart Disease Mortality Associated with Long-Term Exposure to PM2.5 Concentrations that Just Meet the Current 

 Standards, Based on Adjusting 2007 PM2.5 Concentrations1

Modeling Choices:

Fixed Effects (FE) Log-linear vs. Random Effects (RE) log-log model FE Log-Linear FE Log-Linear FE Log-Linear FE Log-Linear RE Log-Log RE Log-Log RE 

Down to LML (5.8 ug/m3) vs. PRB LML LML PRB PRB LML LML 

Proportional vs. hybrid rollback Proportional Hybrid Proportional Hybrid Proportional Hybrid Pro

1257 1582 2783 3099 3206 3807 

(799 - 1711) (1007 - 1582) (1778 - 3770) (1982 - 4193) (1979 - 4407) (2354 - 5221) (87

Percent Difference: 3 --- 26% 121% 147% 155% 203% 

1173 1464 2498 2759 2429 2849 

(954 - 1388) (1193 - 1464) (2053 - 2927) (2272 - 3227) (1715 - 3102) (2022 - 3620) (64

Percent Difference: --- 25% 113% 135% 107% 143% 

530 --- 4 917 --- 1174 --- 

(338 - 719) --- (588 - 1239) --- (728 - 1605) --- (25

Percent Difference: --- --- 73% --- 122% --- 

337 --- 561 --- 602 --- 

(276 - 397) --- (464 - 654) --- (430 - 759) --- (12

Percent Difference --- --- 66% --- 79% --- 

Los Angeles, CA

Philadelphia, PA

3 Percent differences are calculated relative to the model selections used in the core analysis (fixed effects log-linear model; LML, and proportional rollbacks). So, for example, th

all cause mortality in Los Angeles resulting from changing from the core analysis input selections to instead using (1) a fixed effects log-linear model, (2) PRB, and (3) hybrid rollb147%. 

Incidence of Mortality Associated with Long-Term Exposure to PM2.5 Concentration

 All Cause Mortality Ischemic Heart Disease Mortality

4 Philadelphia was not among the risk assessment urban areas for which hybrid rollbacks were calculated.2Estimates Based on Krewski et al. (2009), exposure period from 1999 - 2000. The fixed effects log-linear estimates are from Table 33, using models with 44 individual and 7 eco

effects log-log estimates are from Table 11, "MSA and DIFF" rows.

1The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 

 All Cause Mortality Ischemic Heart Disease Mortality

F-50

September 2009 
Table F-40. Sensitivity Analysis: Impact of Using Season-Specific vs. Annual Concentration-Response Functions and 

 Proportional vs. Hybrid Rollbacks to Estimate the Incidence of Non-Accidental Mortality Associated with Short- Term Exposure to PM2.5 Concentrations that Just Meet the Current Standards, Based on Adjustin

g 2005 PM2.5 Co

Modeling Choices:

Seasonal C-R Functions vs. an All-Year Function All Year All Year Sum of Four Seasons Sum 

Proportional vs. Hybrid Rollback Proportional Hybrid Proportional 

256 254 222 

(104 - 406) (103 - 403) --- 4 

Percent Difference 3 --- -1% -13% 

38 39 78 

(-60 - 135) (-60 - 136) --- 

Percent Difference --- 3% 105% 

141 146 153 

(-25 - 305) (-26 - 315) --- 

Percent Difference --- 4% 9% 

85 94 -28 

(-121 - 289) (-135 - 323) --- 

Percent Difference --- 11% -133% 

714 726 717 

(419 - 1007) (426 - 1023) --- 

Percent Difference --- 2% 0% 

135 163 151 

(40 - 230) (48 - 277) --- 

Percent Difference --- 21% 12% 

252 266 243 

(73 - 429) (77 - 452) --- 

Percent Difference --- 6% -4% 

1Based on season-specific and all-year location-specific coefficient estimates from Zanobetti and Schwartz (2009) that have been "shrunken" towards the ap

means. Numbers are rounded to the nearest whole number. 

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 3 Percent differences are calculated relative to the model selections used in the core analysis (all-year C-R function and proportional rollback). So, for examp

difference in estimated non-accidental mortality in Baltimore resulting from changing from the core analysis input selections to instead using the sum of four s

estimates and hybrid rollbacks is (192 - 225)/225 = -15%. 

4 It was not possible to calculate the 2.5th and 97.5th percentile estimates of the sum of the season-specific incidences because the variance-covariance ma

specific coefficient estimators was not available.

 Pittsburgh, PA St. Louis, MO Los Angeles, CA New York, NY Birmingham, AL Detroit, MI

Estimated Incidence of Non-Accidental Mortality Associated with Short-Term E

Concentrations that Just Meet the Current Standards

 Baltimore, MD

F-51

September 2009 
Table F-41. Sensitivity Analysis: Impact of Using Season-Specific vs. Annual Concentration-Response Functions and 

 Proportional vs. Hybrid Rollbacks to Estimate the Incidence of Non-Accidental Mortality Associated with Short- Term Exposure to PM2.5 Concentrations that Just Meet the Current Standards, Based on Adjustin

g 2006 PM2.5 Co

Modeling Choices:

Seasonal C-R Functions vs. an All-Year Function All Year All Year Sum of Four Seasons Sum 

Proportional vs. Hybrid Rollback Proportional Hybrid Proportional 

234 233 202 

(95 - 372) (94 - 369) --- 4 

Percent Difference 3 --- 0% -14% 

38 38 81 

(-59 - 132) (-59 - 132) --- 

Percent Difference --- 0% 113% 

117 121 139 

(-21 - 254) (-21 - 262) --- 

Percent Difference --- 3% 19% 

78 87 -29 

(-112 - 267) (-125 - 299) --- 

Percent Difference --- 12% -137% 

654 664 656 

(384 - 922) (390 - 936) --- 

Percent Difference --- 2% 0% 

122 147 137 

(36 - 208) (43 - 249) --- 

Percent Difference --- 20% 12% 

214 225 209 

(62 - 364) (65 - 384) --- 

Percent Difference --- 5% -2% 

1Based on season-specific and all-year location-specific coefficient estimates from Zanobetti and Schwartz (2009) that have been "shrunken" towards the ap

means. Numbers are rounded to the nearest whole number. 

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 3 Percent differences are calculated relative to the model selections used in the core analysis (all-year C-R function and proportional rollback). So, for examp

difference in estimated non-accidental mortality in Baltimore resulting from changing from the core analysis input selections to instead using the sum of four s

estimates and hybrid rollbacks is (192 - 225)/225 = -15%. 

4 It was not possible to calculate the 2.5th and 97.5th percentile estimates of the sum of the season-specific incidences because the variance-covariance ma

specific coefficient estimators was not available.

 Pittsburgh, PA St. Louis, MO Los Angeles, CA New York, NY Birmingham, AL Detroit, MI

Estimated Incidence of Non-Accidental Mortality Associated with Short-Term E

Concentrations that Just Meet the Current Standards

 Baltimore, MD

F-52

September 2009 
\

Table F-42. Sensitivity Analysis: Impact of Using Season-Specific vs. Annual Concentration-Response Functions and  Proportional vs. Hybrid Rollbacks to Estimate the Incidence of Non-Accidental Mortality Associated with Short- Term Exposure to PM2.5 Concentrations that Just Meet the Current Standards, Based on Adjusting 2007 PM2.5 Co

Modeling Choices:

Seasonal C-R Functions vs. an All-Year Function All Year All Year Sum of Four Seasons Sum 

Proportional vs. Hybrid Rollback Proportional Hybrid Proportional 

225 223 206 

(91 - 357) (90 - 354) --- 4 

Percent Difference 3 --- -1% -8% 

37 37 106 

(-58 - 131) (-58 - 132) --- 

Percent Difference --- 0% 186% 

112 116 148 

(-20 - 242) (-20 - 250) --- 

Percent Difference --- 4% 32% 

79 88 -11 

(-113 - 270) (-126 - 302) --- 

Percent Difference --- 11% -114% 

659 670 797 

(387 - 930) (393 - 944) --- 

Percent Difference --- 2% 21% 

123 147 234 

(36 - 209) (43 - 250) --- 

Percent Difference --- 20% 90% 

222 234 244 

(64 - 378) (68 - 399) --- 

Percent Difference --- 5% 10% 

 St. Louis, MO New York, NY Pittsburgh, PA Detroit, MI Los Angeles, CA Birmingham, AL

Estimated Incidence of Non-Accidental Mortality Associated with Short-T

PM2.5 Concentrations that Just Meet the Current Standard

 Baltimore, MD

1Based on season-specific and all-year location-specific coefficient estimates from Zanobetti and Schwartz (2009) that have been "shrunken" towards the ap

means. Numbers are rounded to the nearest whole number. 

2The current primary PM2.5 standards include an annual standard set at 15 ug/m3 and a daily standard set at 35 ug/m3. 3 Percent differences are calculated relative to the model selections used in the core analysis (all-year C-R function and proportional rollback). So, for exam

difference in estimated non-accidental mortality in Baltimore resulting from changing from the core analysis input selections to instead using the sum of four 

estimates and hybrid rollbacks is (192 - 225)/225 = -15%. 

4 It was not possible to calculate the 2.5th and 97.5th percentile estimates of the sum of the season-specific incidences because the variance-covariance ma

specific coefficient estimators was not available.

F-53

September 2009 
APPENDIX G: SUPPLEMEMNT TO THE NATIONAL-SCALE 

ASSESSMENT OF LONG-TERM MORTALITY RELATED TO PM2.5 

EXPOSURE

G-1

September 2009 Draft - Do Not Quote or Cite
Appendix G National-Scale Assessment Of Long-Term Mortality Related To PM2.5

 Exposure (additional technical detail regarding inputs used in the analysis) 

1 

2 

3 

4 

5 

6 

7 

8 

9 

10 

11 

12 

13 

14 

15 

16 

17 

18 

19 

20 

21 

22 

23 

24 

25 

26 

27 

28 

29 

30 

31 

32 

33 

 

This technical appendix includes additional details regarding the inputs to the nationalscale current conditions health impact analysis. Below we present air quality modeling, exposure 

and risk information. 

Air Quality Modeled Inputs 

The Community Model for Air Quality (CMAQ) model was used to estimate annual 

PM2.5 concentrations for the year 2005 for the continental US. These data were then combined 

with ambient monitored PM2.5 measurements to create “fused” spatial surfaces supplied to 

BenMAP.

CMAQ Model Application and Evaluation 

CMAQ is a non-proprietary computer model that simulates the formation and fate of 

photochemical oxidants, including PM2.5 and ozone, for given input sets of meteorological 

conditions and emissions. This analysis employed a version of CMAQ based on the latest 

publicly released version (i.e. CMAQ version 4.72

). 

Model Domain and Grid Resolution 

The CMAQ modeling analyses were performed for two domains covering the continental 

United States, as shown in Figure 4-1. These domains consist of a horizontal grid of 36 km 

covering the entire continental US and a finer-scale 12-km grid covering the Eastern U.S. The 

model extends vertically from the surface to 100 millibars (approximately 15 km) using a sigmapressure coordinate system. The 36-km grid was used to establish the incoming air quality 

concentrations along the boundaries of the 12-km grids. Table G-1 provides some basic 

geographic information regarding the CMAQ domains. The 36-km and both 12-km CMAQ 

modeling domains were modeled for the entire year of 2005. All 365 model days were used in 

the annual average levels of PM2.5. 

2

CMAQ version 4.7 was released on December 1, 2008. It is available from the Community Modeling and 

Analysis System (CMAS) at: http://www.cmascenter.org. 

G-2

September 2009 Draft - Do Not Quote or Cite
1 Table G-1. Geographic Information for Modeling Domains 

CMAQ Modeling Configuration 

Eastern U.S. Fine 

Grid 

National Grid 

Map 

Projection 

Lambert Conformal Projection 

Grid 

Resolution 

36 km 12 km 

Coordinate 

Center 97 W, 40 N 

True 

Latitudes 

33 and 45 N 

Dimensions 148 x 112 x 24 279 x 240 x 24 

Vertical 

extent 24 Layers: Surface to 100 mb level 

2 

G-3

September 2009 Draft - Do Not Quote or Cite
1 

2 

3 

4 

5 

6 

Figure G-1. Map of the CMAQ Modeling Domain (Note, the black outer box denotes the 

36-km national modeling domain; the red inner box is the 12-km Eastern U.S. fine 

grid). 

CMAQ Model Inputs 

7 Emissions:

8 

9 

10 

11 

The 2005 emissions inputs to CMAQ included five source sectors: a) Electric Generating 

Units (EGUs); b) Other Stationary Sources (Point and Nonpoint); c) Onroad and Nonroad 

Mobile Sources; d) Biogenic Emissions; and e) Fires. The fires portion of the inventory included 

emissions from wildfires and prescribed burning computed as hour-specific point sources. 

12 

13 

14 

15 

Electric Generating Units (EGUs)

Annual emissions estimates for EGUs for all National Emissions Inventory (NEI) air 

pollutants for 2005 were developed using data reported to the USEPA’s Clean Air Marketing 

Division’s (CAMD) Acid Rain database. The Acid Rain database contains hourly emissions for 

G-4

September 2009 Draft - Do Not Quote or Cite
SO2 and NOx emissions plus hourly heat input amounts. These three values are reported to the 

database by the largest electric generating facilities, usually based upon Continuous Emissions 

Monitors (CEMs). For all pollutants except the directly monitored SO2 and NOx, the ratio of the 

Acid Rain heat input for 2005 to the Acid Rain heat input for 2002 was used as the adjusting 

ratio to estimate the 2005 emissions. 

1 

2 

3 

4 

5 

6 Other Stationary Sources (Point and Nonpoint)

7 

8 

9 

10 

11 

Emission estimates for other stationary sources including both point and nonpoint 

stationary sources were held constant at the level in Version 3 of the 2002 NEI. The only 

exception to this was that some information on plants that closed after 2002 was incorporated 

into the emissions modeled. Emissions for plants that closed were set to zero. U.S. EPA, 2008c 

provides complete documentation on the development of the 2002 NEI. 

12 Onroad and Nonroad Mobile Sources

13 

14 

15 

16 

17 

18 

19 

20 

21 

22 

23 

24 

25 

26 

27 

Emission estimates for all pollutants were developed using EPA’s National Mobile 

Inventory Model (NMIM), which uses MOBILE6 to calculate onroad emission factors. A full 

VMT database at the county, roadway type, and vehicle type level of detail was developed from 

Federal Highway Administration (FHWA) information. However, state and local agencies had 

the opportunity to provide model inputs (vehicle populations, fuel characteristics, VMT, etc) for 

2002 and 2005. If the state or local area submitted 2005 VMT estimates, these data were used. 

However, if the state or local area only provided 2002 VMT estimates that were incorporated in 

the 2002 NEI, the 2002 NEI VMT data were grown to 2005 using growth factors developed from 

the FHWA data, and these grown VMT data replaced the baseline FHWA-based VMT data. 

Otherwise, the FHWA-based VMT data were used. 

Emission estimates for NONROAD model engines were developed using EPA’s National 

Mobile Inventory Model (NMIM), which incorporates NONROAD2005. Where states provided 

alternate nonroad inputs, these data replaced EPA default inputs, as described above. For more 

information on how NMIM is run, refer to the 2005 NEI documentation posted at 

ftp://ftp.epa.gov/EmisInventory/2005_nei/mobile/2005_mobile_nei_version_2_report.pdf. 

28 Fires

29 

30 

31 

Fires in the 2005 emissions inventory were modeled with the same methodology as used 

for the 2002 NEI (U.S. EPA, 2008). However, as described in Raffuse et al., 2008, the wildland 

fire emission inventories for 2005 were produced using the BlueSky framework for the 

G-5

September 2009 Draft - Do Not Quote or Cite
conterminous United States, which used the Satellite Mapping Automatic Reanalysis Tool for 

Fire Incident Reconciliation (SMARTFIRE) as the fire information source. SMARTFIRE is an 

algorithm and database system designed to reconcile these disparate fire information sources to 

produce daily fire location and size information (Sullivan et al., 2008). 

1 

2 

3 

4 

5 Biogenic Emissions

6 

7 

8 

9 

10 

11 

12 

13 

14 

15 

Biogenic emissions were computed for CMAQ based on 2005 meteorology data using the 

BEIS3.13 model (Schwede, et. al, 2005) from the Sparse Matrix Operator Kernel Emissions 

(SMOKE). The BEIS3.13 model creates gridded, hourly, model-species emissions from 

vegetation and soils. It estimates CO, VOC, and NOX emissions for the U.S., Mexico, and 

Canada. The inputs to BEIS include: 

• temperature data at 10 meters which were obtained from the CMAQ 

meteorological input files, and 

• land-use data from the Biogenic Emissions Landuse Database, version 3 

(BELD3), which provides data on the 230 vegetation classes at 1 km resolution over most 

of North America. 

16 

17 

18 

19 

20 

21 

22 

23 

24 

25 

26 

27 

28 

29 

30 

31 

Meteorological Input Data: 

The gridded meteorological input data for the entire year of 2005 were derived from 

simulations of the Pennsylvania State University / National Center for Atmospheric Research 

Mesoscale Model. This model, commonly referred to as MM5, is a limited-area, nonhydrostatic, 

terrain-following system that solves for the full set of physical and thermodynamic equations 

which govern atmospheric motions (Grell et al., 1994). Meteorological model input fields were 

prepared separately for both of the domains shown in Figure G-1 using MM5 version 3.7.4. The 

MM5 simulations were run on the same map projection as CMAQ. 

Both meteorological model runs were configured similarly. The selections for key MM5 

physics options are shown below: 

 Pleim-Xiu PBL and land surface schemes 

 Kain-Fritsh 2 cumulus parameterization 

 Reisner 2 mixed phase moisture scheme 

 RRTM longwave radiation scheme 

 Dudhia shortwave radiation scheme 

G-6

September 2009 Draft - Do Not Quote or Cite
Three dimensional analysis nudging for temperature and moisture was applied above the 

boundary layer only. Analysis nudging for the wind field was applied above and below the 

boundary layer. The 36 km domain nudging weighting factors were 3.0 x 104 for wind fields and 

temperatures and 1.0 x 105

 for moisture fields. The 12 km domain nudging weighting factors 

were 1.0 x 104

 for wind fields and temperatures and 1.0 x 105 for moisture fields. 

1 

2 

3 

4 

5 

6 

7 

8 

9 

10 

11 

12 

13 

All model runs were conducted in 5.5 day segments with 12 hours of overlap for spin-up 

purposes. Both domains contained 34 vertical layers with an approximately 38 m deep surface 

layer and a 100 millibar top. The MM5 and CMAQ vertical structures are shown in Table G-2 

and do not vary by horizontal grid resolution. 

Table G-2. Vertical Layer Structure for MM5 and CMAQ (heights are layer top). 

CMAQ 

Layers 

MM5 

Layers Sigma P 

Approximate 

Height (m)

Approximate 

Pressure (mb)

0 0 1 0 1000 

1 1 0.995 38 995 

2 2 0.99 77 991 

3 0.985 115 987 3 

4 0.98 154 982 

4 5 0.97 232 973 

5 6 0.96 310 964 

7 0.95 389 955 6 

8 0.94 469 946 

9 0.93 550 937 7 

10 0.92 631 928 

11 0.91 712 919 8 

12 0.9 794 910 

9 13 0.88 961 892 

10 14 0.86 1,130 874 

11 15 0.84 1,303 856 

12 16 0.82 1,478 838 

13 17 0.8 1,657 820 

14 18 0.77 1,930 793 

15 19 0.74 2,212 766 

16 20 0.7 2,600 730 

17 21 0.65 3,108 685 

18 22 0.6 3,644 640 

23 0.55 4,212 595 19 

24 0.5 4,816 550 

20 25 0.45 5,461 505 

G-7

September 2009 Draft - Do Not Quote or Cite
CMAQ 

Layers 

MM5 

Layers Sigma P 

Approximate 

Height (m)

Approximate 

Pressure (mb)

26 0.4 6,153 460 

27 0.35 6,903 415 21 

28 0.3 7,720 370 

29 0.25 8,621 325 22 

30 0.2 9,625 280 

31 0.15 10,764 235 23 

32 0.1 12,085 190 

33 0.05 13,670 145 24 

34 0 15,674 100 

1 

2 

3 

4 

5 

6 

7 

8 

9 

10 

11 

12 

13 

14 

15 

16 

17 

18 

19 

The meteorological outputs from the MM5 sets were processed to create model-ready 

inputs for CMAQ using the Meteorology-Chemistry Interface Processor (MCIP), version 3.4, to 

derive the specific inputs to CMAQ. 

Before initiating the air quality simulations, it was important to identify the biases and 

errors associated with the meteorological modeling inputs. The 2005 MM5 model performance 

evaluations used an approach which included a combination of qualitative and quantitative 

analyses to assess the adequacy of the MM5 simulated fields. The qualitative aspects involved 

comparisons of the model-estimated synoptic patterns against observed patterns from historical 

weather chart archives. Additionally, the evaluations compared spatial patterns of monthly 

average rainfall and monthly maximum planetary boundary layer (PBL) heights. Qualitatively, 

the model fields closely matched the observed synoptic patterns, which is not unexpected given 

the use of nudging. The operational evaluation included statistical comparisons of 

model/observed pairs (e.g., mean normalized bias, mean normalized error, index of agreement, 

root mean square errors, etc.) for multiple meteorological parameters, including temperature, 

humidity, shortwave downward radiation, wind speed, and wind direction (Baker and Dolwick, 

2009a, Baker and Dolwick, 2009b). It was ultimately determined that the bias and error values 

associated with the 2005 meteorological data were generally within the range of past 

meteorological modeling results that have been used for air quality applications. 

20 Initial and Boundary Conditions: 

21 

22 

23 

24 

25 

26 

The lateral boundary and initial species concentrations are provided by a threedimensional global atmospheric chemistry model, the GEOS-CHEM model (Yantosca, 2004). 

The global GEOS-CHEM model simulates atmospheric chemical and physical processes driven 

by assimilated meteorological observations from the NASA’s Goddard Earth Observing System 

(GEOS). This model was run for 2002 with a grid resolution of 2.0 degrees x 2.5 degrees 

(latitude-longitude) and 24 vertical layers. The 2005 CMAQ 36km simulation used non-year 

G-8

September 2009 Draft - Do Not Quote or Cite
specific GEOS-CHEM data, which was created by taking the median value for each month in 

each individual grid cell of the 2002 GEOS-CHEM data described above. The predictions were 

used to provide one-way dynamic boundary conditions and an initial concentration field for the 

CMAQ simulations. More information is available about the GEOS-CHEM model and other 

applications using this tool at: http://www-as.harvard.edu/chemistry/trop/geos. 

1 

2 

3 

4 

5 

6 

7 

8 

9 

10 

11 

12 

13 

14 

15 

16 

17 

18 

19 

20 

21 

22 

23 

24 

25 

26 

27 

28 

29 

30 

31 

CMAQ Model Performance Evaluation 

An operational model performance evaluation for PM2.5 and its related speciated 

components was conducted for 2005 using state/local monitoring sites data in order to estimate 

the ability of the CMAQ modeling system to replicate the concentrations for the 12-km Eastern 

domain and 36-km domain in the west. The principal evaluation statistics used to evaluate 

CMAQ performance included two bias metrics, normalized mean bias and fractional bias; and 

two error metrics, normalized mean error and fractional error. For the 12-km Eastern domain, 

performance evaluation statistics were computed for the entire domain as well as its subregions. 

For the 36-km domain, evaluation focuses on the parts of the US not covered by the 12-km 

Eastern domain by computing performance evaluation statistics for the states included in the 

Western Regional Air Partnership (WRAP). 

The PM2.5 evaluation focuses on PM2.5 total mass and its components, including sulfate 

(SO4), nitrate (NO3), total nitrate (TNO3 = NO3 + HNO3), ammonium (NH4), elemental carbon 

(EC), and organic carbon (OC). PM2.5 ambient measurements for 2005 were obtained from the 

following networks for model evaluation: Speciation Trends Network (STN), Interagency 

Monitoring of PROtected Visual Environments (IMPROVE), and Clean Air Status and Trends 

Network (CASTNET). For PM2.5 species that are measured by more than one network, we 

calculated separate sets of statistics for each network. Table G-3 provides annual model 

performance statistics for PM2.5 and its component species. Based on the bias and error values 

associated with the 2005 CMAQ-modeled PM2.5 concentration data, it was determined that the 

annual average PM2.5 data were generally within the range of past modeling results used for air 

quality applications and are applicable to be used for this national-scale current conditions 

analysis. 

Table G-3. CMAQ modeled performance evaluation statistics for PM2.5 for 2005. 

CMAQ 2005 Annual 

No. of 

Obs. NMB (%) NME (%) FB (%) FE (%) 

PM2.5 Total 12-km EUS 11622 -2.2 39.1 -4.7 40.3 

Mass 

STN 

Northeast 2795 4.2 41.3 3.4 39.5 

G-9

September 2009 Draft - Do Not Quote or Cite
CMAQ 2005 Annual 

No. of 

Obs. NMB (%) NME (%) FB (%) FE (%) 

Midwest 2318 4.3 35.2 5.0 34.1 

Southeast 2960 -13.0 37.5 -15.9 41.1 

Central 2523 -2.2 43.1 -8.4 45.6 

36-km 

West 

WRAP 

3082 -35.1 50.7 -40.3 57.4 

12-km EUS 10534 -9.4 44.3 -13.8 48.6 

Northeast 2464 5.3 48.6 2.3 46.2 

Midwest 668 -4.6 38.2 -7.3 40.8 

Southeast 1963 -20.8 42.8 -25.9 51.3 

Central 2768 -10.5 42.8 -12.9 47.7 

IMPROVE 

36-km 

West 

WRAP 

10,122 -21.0 56.0 -24.4 57.6 

12-km EUS 13317 -17.1 34.0 -13.5 37.0 

Northeast 3247 -13.7 32.4 -9.4 34.3 

Midwest 2495 -10.9 33.9 -4.4 34.9 

Southeast 3499 -19.2 32.8 -16.8 35.8 

Central 2944 -25.7 38.7 -23.1 43.5 

STN 

36-km 

West 

WRAP 

3450 -21.9 46.4 -15.0 46.5 

12-km EUS 10164 -21.8 36.4 -13.2 41.1 

Northeast 2393 -14.6 35.5 -6.6 38.6 

Midwest 622 -19.0 34.5 -9.4 36.7 

Southeast 1990 -25.2 35.9 -22.3 41.1 

Central 2640 -27.9 38.0 -22.0 42.4 

Sulfate IMPROVE 

36-km

West 

WRAP 

9693 -5.2 45.2 9.6 47.6 

12-km EUS 3170 -16.5 22.9 -15.6 26.0 

Northeast 786 -11.7 20.5 -9.8 22.6 

Midwest 615 -13.6 21.4 -11.2 22.2 

Southeast 1099 -18.4 22.9 -19.6 25.7 

Central 300 -29.4 32.5 -30.3 36.1 

CASTNet 

36-km

West 

WRAP 

1112 -12.6 34.5 -3.2 36.7 

Nitrate STN 12-km EUS 12186 20.1 67.8 -10.1 76.3 

Northeast 3248 28.7 70.2 -3.7 74.1 

G-10

September 2009 Draft - Do Not Quote or Cite
CMAQ 2005 Annual 

No. of 

Obs. NMB (%) NME (%) FB (%) FE (%) 

Midwest 2495 20.2 61.0 9.2 63.0 

Southeast 3499 23.5 84.0 -25.0 87.2 

Central 1812 8.1 60.2 -5.9 72.4 

36-km 

West 

WRAP 

15,533 15.2 79.3 -15.6 85.9 

12-km EUS 10157 30.1 85.2 -32.5 99.1 

Northeast 2388 67.0 108.9 0.5 93.4 

Midwest 622 14.0 67.9 -24.1 88.9 

Southeast 1990 37.4 104.6 -46.2 105.9 

Central 2640 17.3 70.8 -19.3 89.6 

IMPROVE 

36-km 

West 

WRAP 

17,452 33.1 99.1 -41.9 109.9 

12-km EUS 3170 24.6 39.7 17.8 38.0 

Northeast 786 36.5 43.0 30.3 40.6 

Midwest 615 23.3 36.5 23.9 33.2 

Southeast 1099 23.6 42.2 12.8 40.5 

Central 300 10.6 35.5 5.0 35.0 

Total Nitrate 

(NO3+HNO3) 

CASTNet 

36-km 

West 

WRAP 

4065 37.7 51.9 24.2 45.1 

12-km EUS 13317 1.8 41.9 8.3 45.6 

Northeast 3247 7.1 42.9 18.9 45.7 

Midwest 2495 7.1 40.5 16.4 41.4 

Southeast 3499 -2.1 40.5 2.9 43.3 

Central 2944 -7.6 44.0 -4.0 51.4 

STN 

36-km 

West 

WRAP 

16,680 8.1 47.2 12.8 48.9 

12-km EUS 3170 2.2 35.4 3.1 36.5 

Ammonium 

Northeast 786 9.2 38.1 13.3 36.6 

Midwest 615 10.9 35.3 14.8 33.7 

Southeast 1099 -9.2 33.3 -9.7 37.6 

Central 300 1.5 36.9 3.0 40.2 

CASTNet 

36-km

West 

WRAP 

4065 12.8 39.6 13.0 40.1 

Elemental 12-km EUS 13460 19.7 63.5 11.9 53.9 

Carbon 

STN 

Northeast 3230 20.8 61.9 14.6 52.0 

G-11

September 2009 Draft - Do Not Quote or Cite
CMAQ 2005 Annual 

No. of 

Obs. NMB (%) NME (%) FB (%) FE (%) 

Midwest 2502 7.3 46.1 10.8 44.9 

Southeast 3495 10.2 60.2 3.0 50.6 

Central 3107 47.6 88.2 23.0 64.9 

36-km 

West 

WRAP 

16,700 2.6 56.7 2.6 55.0 

12-km EUS 10244 -29.0 49.7 -39.1 61.3 

Northeast 2341 -17.8 49.2 -25.6 57.7 

Midwest 696 -26.7 41.9 -39.6 55.7 

Southeast 1995 -45.6 53.3 -58.5 69.8 

Central 2626 -22.9 49.2 -31.3 56.8 

IMPROVE 

36-km 

West 

WRAP 

17,289 -16.6 53.4 -23.4 60.2 

12-km EUS 12118 -36.5 53.6 -40.6 66.5 

Northeast 3083 -29.1 53.1 -27.6 64.2 

Midwest 2385 -42.5 52.6 -41.7 65.3 

Southeast 3442 -42.6 53.5 -55.6 70.2 

Central 2164 -30.6 57.7 -39.6 66.5 

STN 

36-km 

West 

WRAP 

15,397 -41.2 56.1 -45.7 69.2 

12-km EUS 10210 -34.7 53.7 -53.0 70.0 Organic Carbon 

Northeast 2336 -21.0 52.2 -29.2 58.4 

Midwest 696 -41.3 47.6 -55.7 63.6 

Southeast 1993 -40.4 53.7 -64.0 74.2 

Central 2622 -34.1 52.8 -52.7 68.1 

IMPROVE 

36-km 

West 

WRAP 

17,295 -22.5 57.5 -40.8 67.6 

1 

2 

3 

4 

5 

6 

7 

8 

9 

“Fused” Spatial Surfaces

Spatial surfaces of the 2005 data were created by fusing CMAQ-modeled annual average 

PM2.5 concentrations with total PM2.5 data from STN, IMPROVE, and CASTNET monitoring 

sites for the two domains shown in Figure 1. We used the EPA’s Model Attainment Test 

Software (MATS) (Abt, 2009) which employees the Voronoi Neighbor Averaging (VNA) 

interpolation technique (Abt, 2008). This technique identifies the set of monitors that are nearest 

to the center of each grid cell, and then takes an inverse distance squared weighted average of the 

G-12

September 2009 Draft - Do Not Quote or Cite
1 

2 

3 

4 

5 

6 

7 

8 

9 

10 

11 

12 

13 

14 

monitor concentrations. The “fused” spatial fields are calculated by adjusting the interpolated 

ambient data (in each grid cell) up or down by a multiplicative factor calculated as the ratio of 

the modeled concentration at the grid cell divided by the modeled concentration at the nearest 

neighbor monitor locations (weighted by distance). 

To create the spatial surfaces for use in BenMAP, the 2005 CMAQ-modeled annual 

average PM2.5 concentrations were “fused” with 2005 total PM2.5 ambient monitoring data from 

STN, IMPROVE, and CASTNET sites. This was done for both the 36km national domain and 

the 12km eastern US domain. The spatial surface of annual average PM2.5 air quality 

concentrations produced by this technique is shown in Figure G-2 for the continental U.S. Where 

available, the 12km spatial surface was used to supply BenMAP with annual average PM2.5 

concentrations. In the western part of the U.S., annual average PM2.5 concentrations were 

supplied from the 36km domain. 

Figure G-2: 2005 Predicted Annual Mean PM2.5 Levels 

15 

16 

17 

G-13

September 2009 Draft - Do Not Quote or Cite
G-14

1 Advantages and Limitations

2 

3 

4 

5 

6 

7 

8 

9 

10 

11 

12 

13 

14 

15 

16 

17 

18 

As compared to using monitored data alone, an advantage of using the CMAQ model 

output for comparing with health outcomes is that it has the potential to provide more complete 

spatial and temporal coverage. In addition, “fusing” the CMAQ data with ambient monitoring 

data allows for an improvement over non-fused fields (Timin et al., 2009). Doing so allows for a 

combination of the advantages of both sets of data: better spatial coverage and more accurate air 

quality estimates. Of course, the more accurate the model estimates of PM2.5, the better the 

performance of the “fused” spatial fields. Therefore, it is important to use model outputs that 

have adequate PM2.5 performance. As discussed above, we believe that the 2005 CMAQmodeled PM2.5 concentration data showed adequate model performance to be used for this 

national-scale current conditions analysis. 

As with any model estimate of air quality, there are limitations. For example, the 

emissions and meteorological data used in CMAQ can each have large uncertainties, in particular 

for unusual emission or meteorological events. There are also uncertainties associated with the 

chemical transformation and fate process algorithms used in air quality models. For these 

reasons, CMAQ predicts best on longer time scale bases (e.g., synoptic, monthly, and annual 

scales). These limitations have led us to use modeled air quality estimates in this analysis that 

are “fused” with measured ambient data and averaged over an annual scale. 

19 Air Quality Estimates

20 

21 

22 

23 

24 

Figures G-3 through G-6 below illustrate the spatial distribution of air quality impacts. 

Figure 1 illustrates the modeled 2005 PM2.5 air quality levels across the U.S. Figures 2 and 3 

display the PM2.5 air quality levels after being adjusted so that the maximum level is no higher 

than the LML reported in the Krewski et al. (2009) and Laden et al. (2006) studies. Figure G-4 

displays the PRB by region of the county.

September 2009 Draft - Do Not Quote or Cite
Figure G-3: 2005 Predicted Annual Mean PM2.5 Levels 

G-15

September 2009 Draft - Do Not Quote or Cite
Figure G-4: 2005 Predicted Annual Mean PM2.5 Levels Adjusted for LML of the 

Krewski et al. (2009) study 

G-16

September 2009 Draft - Do Not Quote or Cite
Figure G-5: 2005 Predicted Annual Mean PM2.5 Levels Adjusted for LML of the 

Laden et al. (2006) study 

G-17

September 2009 Draft - Do Not Quote or Cite
Figure G-6: PRB by Geographic Area in the U.S. 

Figure G-7 displays the distribution of grid cells at different baseline PM2.5 air quality 

levels. Figures G-8 through G-10 displays the distribution of grid cells according to the 

incremental change in PM2.5 air quality for each of three scenarios: current conditions to 10 

μg/m3, current conditions to 5.8 μg/m3 and current conditions to PRB. 

G-18

September 2009 Draft - Do Not Quote or Cite
Figure G-7: The Number of Grid Cells at Each Level of PM2.5 Concentration in 

2005 Current Conditions Air Quality Modeling Run 

G-19

September 2009 Draft - Do Not Quote or Cite
Figure G-8: The Number of CMAQ Grid Cells Experiencing an Incremental 

Change in Annual Mean PM2.5 (μg/m3

) (Current Conditions – 10 

μg/m3) 

G-20

September 2009 Draft - Do Not Quote or Cite
Figure G-9: The Number of CMAQ Grid Cells Experiencing an Incremental 

Change in Annual Mean PM2.5 (μg/m3

) (Current Conditions – 5.8 

μg/m3) 

G-21

September 2009 Draft - Do Not Quote or Cite
Figure G-10: The Number of CMAQ Grid Cells Experiencing an Incremental 

Change in Annual Mean PM2.5 (μg/m3

) (Current Conditions – Policy 

Relevant Background) 

Figure G-11 displays the cumulative distribution of grid cells at each baseline 

concentration. Figures G-12 through G-14 display the cumulative distribution of grid cells 

experiencing an incremental air quality change. 

G-22

September 2009 Draft - Do Not Quote or Cite
Figure G-11: Cumulative Distribution of Baseline PM2.5 Concentrations (μg/m3

) 

G-23

September 2009 Draft - Do Not Quote or Cite
Figure G-12: Cumulative Distribution of PM2.5 (μg/m3

) Changes (Baseline – 10 

μg/m3

) 

G-24

September 2009 Draft - Do Not Quote or Cite
Figure G-13: Cumulative Distribution of PM2.5 (μg/m3

) Changes (Baseline – 5.8 

μg/m3

) 

G-25

September 2009 Draft - Do Not Quote or Cite
Figure G-14: Cumulative Distribution of PM2.5 (μg/m3

) (Baseline – Policy Relevant 

Background) 

Exposure Estimates

Below we provide additional details regarding the estimated exposure changes occurring 

as a result of each of the air quality changes assumed in each of the three health impact 

assessments: current conditions incremental to 10 μg/m3, 5.8 μg/m3 and PRB. Table G-4 

summarizes the population-weighted air quality change occurring among populations 30-99 (the 

age range considered in the ACS cohort) for each scenario. 

Population-weighted air quality change is the average per-person change in PM2.5. It is 

estimated by calculating the summation of the population in each grid cell multiplied against the 

change in annual mean PM2.5 concentration in that grid cell and then dividing by the total 

population. 

G-26

September 2009 Draft - Do Not Quote or Cite
Table G-4. Estimated Change in Annual Mean Population-Weighted PM2.5 by 

Model Scenario 

Population-weighted air quality change or 

Model scenario baseline 

Current conditions to 10 μg/m3 2.6 μg/m3

Current conditions to 5.8 μg/m3 6.3 μg/m3

11 μg/m3 Current conditions to PRB 

12 μg/m3 Current conditions 

Health Impact Estimates

Figure G-15 through G-17 illustrate the distribution of total mortality attributable to 

PM2.5 exposure for each of three scenarios: current conditions to 10 μg/m3

, 5.8 μg/m3 and PRB. 

G-27

September 2009 Draft - Do Not Quote or Cite
Figure G-15: The Percentage of Total Mortality Attributable to PM2.5 Exposure: 

Baseline – 10 μg/m3

G-28

September 2009 Draft - Do Not Quote or Cite
Figure G-16: The Percentage of Total Mortality Attributable to PM2.5 Exposure: 

Baseline – 5.8 μg/m3

G-29

September 2009 Draft - Do Not Quote or Cite
Figure G-17: The Percentage of Total Mortality Attributable to PM2.5 Exposure: 

Baseline – Policy Relevant Background 

Figures G-18 through G-20 illustrate the cumulative distribution of total mortality 

attributable to PM2.5 exposure for each of three scenarios: current conditions to 10 μg/m3, 5.8 

μg/m3 and PRB. 

G-30

September 2009 Draft - Do Not Quote or Cite
Figure G-18: The Cumulative Distribution of the Percentage of Total Mortality 

Attributable to PM2.5 Exposure: Baseline – 10 μg/m3

G-31

September 2009 Draft - Do Not Quote or Cite
Figure G-19: The Cumulative Distribution of the Percentage of Total Mortality 

Attributable to PM2.5 Exposure: Baseline – 5.8 μg/m3

G-32

September 2009 Draft - Do Not Quote or Cite
Figure G-20: The Cumulative Distribution of the Percentage of Total Mortality 

Attributable to PM2.5 Exposure: Baseline – Policy Relevant Background 

G-33

September 2009 Draft - Do Not Quote or Cite
 

 

United States 

Environmental Protection 

Agency 

Office of Air Quality Planning and Standards 

Health and Environmental Effects Division 

Research Triangle Park, NC 

Publication No. 

EPA-452/P-09-006

September, 2009