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

Second External Review Draft

June 2010DISCLAIMER
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 thos e 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 Advi sory Committee (CASAC) and the general public.
Comments on this draft document should be addressed to Beth Hassett-Sipple, U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards, C504-06, Research Triangle Park, North Carolina 27711 (email: hassett-sipple.beth@epa.gov ).EPA-452/P-10-007
June 2010



# Policy Assessment for the Review of the Particulate Matter National Ambient Air Quality Standards Second External Review Draft

U.S. Environmental Protection Agency
Office of Air and Radiation Office of Air Quality Planning and Standards Health and Environmental Impacts Division Research Triangle Park, North Carolina 27711This page left intentionally blank.Draft-Do Not Quote or Cite June 2010 ES-1 

### EXECUTIVE SUMMARY

This second draft Policy Assessment (PA) has been prepared by staff in the Environmental Protection Agency’s (EPA) Offi ce of Air Quality Planning and Standards (OAQPS) in conjunction with the Agency’s ongoing review of the national ambient air quality standards (NAAQS) for particulate ma tter (PM), which include primary (healthbased) and secondary (welfare-b ased) standards. It presents staff conclusions regarding the adequacy of the current suite of PM standards as well as potential alternative standards for consideration in this revi ew, based on the scient ific and technical information assessed in other EPA documents, including the Integrated Science Assessment for Particulate Matter (Final Report) (ISA, US EPA, 2009a), the Quantitative Health Risk Assessment fo r Particulate Matter (Final Report) (RA, US EPA, 2010a) and the Particulate Matter Urban-Focused Vi sibility Assessment (Final Report) (UFVA, US EPA, 2010b). This PA is intended to “bridge the gap” between the relevant scientific evidence and technical information and the judgments required of the EPA Administrator in determining whether, and if so how, to revi se the PM NAAQS. The current and potential alternative PM standards are considered in terms of the basic elements of the NAAQS: indicator, averaging time, form, and level.

Primary standards for fine particles (Chapter 2) : In assessing the adequacy of the current suite of annual and 24-hour PM 2.5 standards meant to protect public health agai nst long- and short-term exposures to fine particles, staff concludes that the currently available information clearly calls into question the adequacy of the current standard s and that consideration should be given to revising the suite of standards to provid e increased public health protection. In considering alternative PM 2.5 standards, staff concludes th at protection from both longand short-term PM 2.5 exposures can most effectivel y and efficiently be provided by relying primarily on the annual standar d, with the 24-hour standard providing supplemental protection for days with high peak concentrations. On this basis, staff concludes that consideration should be given to alternative annual PM 2.5 standard levels in the range of 13 to 11 μg/m 3 , in conjunction with retaining the current 24-hour PM 2.5 standard level of 35 μg/m 3 , and that consideration could al so be given to an alternative 24-hour PM 2.5 standard level of 30 μg/m 3 particularly in conjunction with an annual standard level of 11 μg/m 3

. Primary standard for thoracic coarse particles (Chapter 3) : In assessing the adequacy of the current primary 24-hour PM 10 standard meant to protect public health against short-term expos ures to thoracic coar se particles, staff concludes that consideration s hould be given to retaining or revising the current standard, depending on the relative weight placed on the evidence supporting associations with PM 10-2.5 and the uncertainties associated with this evidence. With regard to potential alternative standards, staff concludes that, to the extent considerati on is given to revising the current standard to increas e public health protection, consid eration should be given to retaining the PM 10 indicator and the 24-hour averag ing time and revising the form andDraft-Do Not Quote or Cite June 2010 ES-2 level, with consideration of levels from 85  g/m 3 down to about 65  g/m 3 in conjunction with a 98 th percentile form.

Secondary standards for PM-related vi sibility impairment (Chapter 4) : In assessing the adequacy of the curr ent suite of secondary annual and 24-hour PM 2.5 standards (which are id entical to the primary PM 2.5 standards) meant to protect against PM-related visibility impairment, staff concludes that the currently available information clearly calls into question the ad equacy of the current standards and that consideration should be given to revising the suite of sta ndards to provide increased public welfare protection. In considering a lternative standards, staff concludes that consideration should be given to establishi ng a new indicator base d on using speciated PM 2.5 mass and relative humidity to calculate PM 2.5 light extinction. Staff also concludes that consideration should be given to a 1-hour averaging time, considering only daylight hours with relative humidity no higher than 90 %, and a level, defined in terms of PM 2.5 light extinction, in th e range of 191 to 64 Mm -1 to target protection against visibility impairment related to fine particles.

Secondary standards for non-visibili ty welfare effects (Chapter 5): In assessing the adequacy of the current suite of secondary PM standards (which are identical to the primary PM 2.5 and PM 10 standards) meant to protect against PMrelated effects other than visi bility impairment, staff has c onsidered PM-related effects on climate, ecological effects, and effects on mate rials. Staff concludes that the currently available information supports retaining cont rol of both fine and coarse particles to address PM-related effects on ecosystems and materials damage and soiling, but that there insufficient information to assess the ad equacy of protection afforded by the current standards. Staff also concludes that there is insufficient information at this time to base a national ambient standard on climate imp acts associated with current ambient concentrations of PM or its constituents.Draft-Do Not Quote or Cite June 2010 i 

## TABLE OF CONTENTS

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

1.1 PURPOSE.................................................................................................................. 1- 1
1.2 BACKGROUND ....................................................................................................... 1-2 1.2.1 Legislative Requirements.................................................................................1-2 1.2.2 Previous PM NAAQS Reviews .......................................................................1-3 1.2.3 Litigation Related to the 2006 PM Standards..................................................1-9 1.2.4 Current PM NAAQS Review........................................................................... 1-9
1.3 GENERAL APPROACH AND ORGANIZA TION OF THIS DOCUMENT........ 1-11
1.4 REFERENCES ........................................................................................................ 1-13

2 REVIEW OF THE PRIMARY STANDA RDS FOR FINE PARTICLES ............... 2-1

2.1 APPROACH ..............................................................................................................2-1 2.1.1 Approaches Used in Previous Reviews ........................................................... 2-2 2.1.1.1 Review Completed in 1997............................................................. 2-2 2.1.1.2 Review Completed in 2006............................................................. 2-4 2.1.2 Remand of Primary Annual PM 2.5 Standard ....................................................2-6 2.1.3 Current Approach............................................................................................. 2-7 2.2 ADEQUACY OF CURRENT STANDARDS ........................................................ 2-13
2.2.1 Evidence-based Considerations ..................................................................... 2-13 2.2.2 Risk-based Considerations............................................................................. 2-31 2.2.3 Staff Conclusions on Adequacy of Current Standards .................................. 2-42
2.3 CONSIDERATION OF ALTER NATIVE STANDARDS ..................................... 2-43
2.3.1 Indicator ......................................................................................................... 2-44 2.3.2 Averaging Times............................................................................................2-50 2.3.3 Forms ............................................................................................................. 2-52 2.3.3.1 Form of the Annual Standard........................................................2-52 2.3.3.2 Form of the 24-Hour Standard......................................................2-54 2.3.4 Alternative Levels..........................................................................................2-56 2.3.4.1 Evidence-based Considerations .................................................... 2-56 2.3.4.2 Risk-based Considerations............................................................ 2-76 2.3.4.3 Integration of Evidence-based a nd Risk-based Considerations....2-82
2.4 STAFF CONCLUSIONS ON A LTERNATIVE FINE PARTIC LE STANDARDS

....................................................................................................................................... ...2-84
2.5 KEY UNCERTAINTIES AND AREAS FO R FUTURE RESEARCH AND DATA COLLECTION ........................................................................................................ 2-86
2.6 REFERENCES ........................................................................................................ 2-91Draft-Do Not Quote or Cite June 2010 ii 3 REVIEW OF THE PRIMARY ST ANDARD FOR THORACIC COARSE PARTICLES................................................................................................................... 3-1

3.1 APPROACH ..............................................................................................................3-1 3.1.1 Reviews Completed in 1987 and 1997 ............................................................ 3-2 3.1.2 Review Completed in 2006.............................................................................. 3-3 3.1.3 Litigation of 2006 Final Rule for Thoracic Coarse Particles...........................3-5 3.1.4 Current Approach............................................................................................. 3-6 3.2 ADEQUACY OF THE EXIS TING PM10 STANDARD ......................................... 3-9
3.2.1 Evidence-Based Considerations.......................................................................3-9 3.2.2 Staff Conclusions on Adequacy of Current PM10 Standard .........................3-23
3.3 CONSIDERATION OF POTENTIAL ALTERNATIVE STANDARDS .............. 3-26
3.3.1 Indicator ......................................................................................................... 3-26 3.3.2 Averaging Time .............................................................................................3-29 3.3.3 Form............................................................................................................... 3-30 3.3.4 Level .............................................................................................................. 3-32
3.4 STAFF CONCLUSIONS ON A PRIMAR Y THORACIC COARSE PARTICLE STANDARD............................................................................................................ 3-44
3.5 KEY UNCERTAINTIES AND AREAS FO R FUTURE RESEARCH AND DATA COLLECTION ........................................................................................................ 3-45
3.6 REFERENCES ........................................................................................................ 3-47

4 REVIEW OF THE SECONDARY STAN DARDS FOR VISIBILITY-RELATED EFFECTS........................................................................................................................ 4-1

4.1 APPROACH ..............................................................................................................4-1 4.1.1 Approaches Used in Previous Reviews ........................................................... 4-2 4.1.1.1 Review Completed in 1997............................................................ 4-2 4.1.1.2 Review Completed in 2006............................................................ 4-4 4.1.2 Remand of Secondary PM 2.5 Standards ........................................................... 4-8 4.1.3 Current Approach............................................................................................. 4-9 4.2 ADEQUACY OF CURRENT STANDARDS ........................................................ 4-11
4.2.1 Evidence-based Considerations ..................................................................... 4-11 4.2.2 Summary........................................................................................................ 4-29
4.3 CONSIDERATION OF ALTER NATIVE STANDARDS ..................................... 4-30
4.3.1 Nature of the Indicator...................................................................................4-30 4.3.2 Averaging and Applicable Times ..................................................................4-37 4.3.3 Alternative Levels/Forms...............................................................................4-38 4.3.4 Performance of Alternative Standards........................................................... 4-41
4.4 STAFF CONCLUSIONS ON ALTERNATIVE SECONDA RY STANDARDS FOR VISIBILITY-RELATED EFFECTS .......................................................................4-48Draft-Do Not Quote or Cite June 2010 iii 4.5 KEY UNCERTAINTIES AND AREAS FO R FUTURE RESEARCH AND DATA COLLECTION ........................................................................................................ 4-50
4.6 REFERENCES ........................................................................................................ 4-52

5 REVIEW OF THE SECONDARY ST ANDARDS FOR OTHER WELFARE EFFECTS........................................................................................................................ 5-1

5.1 APPROACH ..............................................................................................................5-1 5.1.1 Approaches Used in Previous Reviews ........................................................... 5-2 5.1.1.1 Review Completed in 1997............................................................. 5-2 5.1.1.2 Review Completed in 2006............................................................. 5-2 5.1.2 Scope of Current NAAQS Reviews................................................................. 5-3 5.1.2.1 Scope of the Current Sec ondary PM NAAQS Review................... 5-3 5.1.2.2 Scope of the Current NOx/SOx Secondary NAAQS Review ........5-5 5.1.3 Current Approach............................................................................................. 5-5
5.2 CLIMATE.................................................................................................................. 5- 6 5.2.1 Scope................................................................................................................ 5-6 5.2.2 Adequacy of the Current Standard...................................................................5-7 5.2.3 Staff Conclusions........................................................................................... 5-10 5.2.4 Key Uncertainties and Areas for Future Research and Data Collection........5-12
5.3 ECOLOGICAL EFFECTS ...................................................................................... 5-13 5.3.1 Scope.............................................................................................................. 5-13 5.3.2 Adequacy of the Current Standard.................................................................5-16 5.3.3 Staff Conclusions........................................................................................... 5-23 5.3.4 Key Uncertainties and Areas for Future Research and Data Collection........5-24
5.4 MATERIALS........................................................................................................... 5-25 5.4.1 Scope.............................................................................................................. 5-25 5.4.2 Adequacy of the Current Standard.................................................................5-26 5.4.3 Staff Conclusions........................................................................................... 5-28 5.4.4 Key Uncertainties and Areas for Future Research and Data Collection........5-28
5.5 REFERENCES ........................................................................................................ 5-29

CHAPTER APPENDICES:

APPENDIX 2A: Table 2A-1. Predicted Percen t of Counties with Monitors (and percent of population in counties with monitors) Not Like ly to Meet Alternative Annual and 24-hour PM 2.5 Standards ...................................................................................................2A-1

APPENDIX 3A: Table 3A-1. Predicted Percen t of Counties with Monitors (and percent of population in counties with monitors) Not Likely to Meet Alternative 24-hour PM 10 Standard.....................................................................................................3A-1

APPENDIX 4A: Information Regarding the 1-hour PM 2.5 Mass Indicator ......................4A-1Draft-Do Not Quote or Cite June 2010 iv APPENDIX 4B: Simplified Approaches to Calcul ate Hourly PM Light Extinction Values from Hourly PM 2.5 Mass and Relative Humidity Data plus 24-hour Mean PM Composition.........4B-1

APPENDIX 4C: Assessment of the PM Components Responsible for the Largest Hourly PM Light Extinction and PM 2.5 Mass Hours Selected as Maximum Daily and Using All Hours for 14 Urban Areas ............................................................................................ 4C-1Draft-Do Not Quote or Cite June 2010 v 

### LIST OF TABLES

Table 1-1. Summary of Nationa l Ambient Air Quality Standards Promulgated for Particulate Matter 1971-2006 ...................................................................................................... 1-4 Table 2-1. Summary of Caus al Determinations for PM 2.5 ........................................................ 2-15 Table 2-2. Estimated Incidence and Percent of Total Annual Incidence Associated with Longterm PM 2.5 Exposure Based on Simulation of the Current Suite of Standards (for IHD Mortality based on 2007 PM 2.5 Concentrations) ......................................2-40 Table 2-3. Estimated Incidence and Percent of Total Annual Incidence A ssociated with Shortterm PM 2.5 Exposure Based on Simulation of the Current Suite of Standards (CV mortality and hospital admissions based on 2007 PM 2.5 concentrations)................ 2-41 Table 3-1. Summary of Caus ality Determinations for PM 10-2.5 ................................................ 3-10 Table 3-2. Counties with PM 10 Concentration-Equivalent Design Values > 150  g/m 3 and 98 th percentile PM 10 concentrations > 87  g/m 3 ............................................................ 3-41 Table 4-1. Logit model estimated VAQ values corresponding to various percent acceptability values for the four cities. .........................................................................................4-21 Table 4-2. Percentage of daily ma ximum hourly values of daylight PM 10 light extinction exceeding CPLs (excluding hours with relative humidity greater than 90 percent)4-26 Table 4-3. Percentage of daily ma ximum hourly values of daylight PM 10 light extinction exceeding CPLs when “just meeting” the current PM 2.5 NAAQS (15/35 μ g/m 3 ) (excluding hours with relative humid ity greater than 90 percent) ..........................4-29 Table 4-4. PM 10 light extinction design values for “jus t meeting” secondary NAAQS scenarios based on measured PM 10 light extinction (excluding hours with relative humidity greater than 90 percent)........................................................................................... 4-44 Table 4-5. 90 th percentile maximum daily 1-hour PM light extinction design values (Mm 1 ) after rollback to meet alternative standards of 60 μ g/m 3 , 40 μ g/m 3 , 30 μ g/m 3 ,20 μ g/m 3 and 10 μ g/m 3 maximum daylight 1-hour PM mass c oncentration for the 90th percentile ..................................................................................................4-47 Table 5-1. Scope of the current secondary PM NAAQS review and current NOx/SOx secondary review. ....................................................................................................................... 5 -4Draft-Do Not Quote or Cite June 2010 vi 

### LIST OF FIGURES

Figure 2-1. Overview of Appro ach for Review of Primary PM 2.5 Standards ............................2-12 Figure 2-2. Distribution of s ite-level variation in 98 th and 99 th percentile concentrations, as measured by coefficient of variation (SD/M ean) computed by site across years, 2000-2008................................................................................................................ 2-55 Figure 2-3. Confidence Bounds on PM 2.5 Concentration-Response Relationships from Multi-city Epidemiological Studies..........................................................................................2-59 Figure 2-4. Summary of Eff ect Estimates (per 10 μ g/m 3 ) and Air Quality Distributions for Long-term PM 2.5 Exposure Multi-City Studies of th e General Population and Older Adults ............................................................................................................ 2-62 Figure 2-5. Summary of Eff ect Estimates (per 10 μ g/m 3 ) and Air Quality Distributions for Long-term PM 2.5 Exposure Multi-City Studies of Children....................................2-63 Figure 2-6. Summary of Eff ect Estimates (per 10 μ g/m 3 ) and Air Quality Distributions for Short-term PM 2.5 Exposure Multi-City Studies of th e General Population and Older Adults ............................................................................................................ 2-64 Figure 2-7. Air Quality and Popula tion Distributions: Long-term PM 2.5 Exposure Studies .....2-66 Figure 2-8. Air Quality and Popula tion Distributions: Short-term PM 2.5 Exposure Studies.....2-67 Figure 2-9. Distribution of S ite-Level Ratio of Annual 98 th Percentile Concentration/Annual Mean, 2000-2008..................................................................................................... 2-74 Figure 2-10. Site-level 24-hour DVs versus Annual DVs, 2006-2008..................................... 2-75 Figure 2-11. Percent Reduction in Long-te rm Exposure-related Mortality Risk .................... 2-77 Figure 2-12. Percent Reductions in Short-term Exposure-related Mortal ity and Morbidity Risk....................................................................................................................... 2-78 Figure 3-1. Approach to Consid ering the Current and Potentia l Alternative Thoracic Coarse Particle Standards ...................................................................................................... 3-8 Figure 3-2. PM 10 Air Quality and PM 10-2.5 Effect Estimates in Locations of U.S. PM 10-2.5 Mortality Studies ..................................................................................................... 3-19 Figure 3-3. PM 10 Air Quality PM 10-2.5 Effect Estimates in Locations of U.S. PM 10-2.5 Morbidity Studies............................................................................3-20 Figure 3-4. Site-Level Ratio of Daily PM 10-2.5 to Daily PM 10 ................................................... 3-27 Figure 3-5. 98 th Percentile PM 10 Concentrations in Locations of U.S. PM 10-2.5 Mortality Studies

............................................................................................................................... ..3-35 Figure 3-6. 98 th Percentile PM 10 Concentrations in Locations of U.S. PM 10-2.5 Morbidity Studies

............................................................................................................................... ..3-36 Figure 3-7. Composite 3-year PM 10 98 th percentile 24-hour average concentration versus the PM 10 expected exceedance concentration-equivalent design value ........................3-39 Figure 4-1. Overview of Appro ach for Review of Secondary PM 2.5 Standards .......................4-10 Figure 4-2. Summary of re sults of urban visibility studies in four cities , showing the identified range of the 50% acceptan ce criteria ....................................................................4-20 Figure 4-3. Distribution of estimated maximum daily daylight 1-hour PM 10 light extinction across the 2005-2007 period, by st udy area (excluding hours w ith relative humidity greater than 90 percen t). (Adapted from Figur e 3-8 in UFVA) ..............................4-25Draft-Do Not Quote or Cite June 2010 vii Figure 4-4. Distribution of daylight 1-hour PM 10 light extinction when rolled back to just meet current PM fine NAAQS across the 2 005-2007 period, by study area (excluding hours with relative humidity greater than 90 percent). ..........................................4-28 Figure 4-5. Scatter plots of PM 10 light extinction versus PM 2.5 mass concentration of two cities (from UFVA Appendix D, Figure D2)....................................................................4-32 Figure 4-6. Daily maximu m daylight 1-hour PM 10 light extinction after ro llback to just meet a scenario with daily maximum of 112 Mm -1 for the 90 th percentile excluding hours with relative humidity greater than 90 percent........................................................4-43 Figure 4-7. Maximum daily daylight 1-hour PM 10 light extinction under "just meet" conditions for a NAAQS scenario based on 1-hour PM 2.5 mass of 30 μ g/m 3 , 90th percentile, excluding relative humidity >90%...................................................................... 4-45Draft-Do Not Quote or Cite June 2010 viii 

### LIST OF ACRONYMS/ABBREVIATIONS

ACS American Cancer Society AOD Aerosol optical depth ANS Autonomic nervous system AQCD Air Quality Criteria Document AQS EPA’s Air Quality System

AR4 Fourth Assessment Report of the Intergovernmental Panel on Climate Change

BC Black carbon BP Blood pressure

C Carbon

Ca Calcium

CAA Clean Air Act CAPs Concentrated ambient particles CASAC Clean Air Scientific Advisory Committee

CBVD Cerebrovascular disease

CCN Cloud Condensation Nuclei CCSP US Climate Change Science Program

Cd Cadmium CFR Code of Federal Regulations CHD Coronary heart disease CHF Congestive heart failure CHS Childrens Health Study

CO Carbon monoxide

CO 2 Carbon dioxide

COPD Chronic obstruc tive pulmonary disease C-R Concentration-response relationship CRP C-reactive protein CSN Chemical Speciation Network Cu Copper

CV CardiovascularDraft-Do Not Quote or Cite June 2010 ix CVD Cardiovascular disease

DE Diesel exhaust DEP Diesel exhaust particles

dv deciview DV Design value DVT Deep vein thrombosis

EC Elemental carbon ECG Electrocardiogram EPA Environmental Protection Agency FEM Federal Equivalent Method

FEV 1 Change in forced expiratory volume in one second

FRM Federal Reference Method

GEOS Global Scale Air Circulation Model GHG Greenhouse gas GI Group interviews Hg Mercury

HR Heart rate HRV Heart rate variability

IHD Ischemic heart disease IMPROVE Interagency Monitoring of Protected Visual Environment IPCC Intergovernmental Panel on Climate Change IRP Integrated Review Plan ISA Integrated Science Assessment

IT Intratracheal Lag Time between one event and another Lag 0 Same day as the death, test, hospi tal, ED, clinic, physician visit; that occurs on the same day as th e exposure to the pollutant(s) Lag 0-x All the deaths test, hospital, ED, clinic, physician visit; that occurs on the same day as the exposure to the pollu tant(s) and the x days following the day of exposure MCAPS Medicare Air Pollution Study MEA Millennium Ecosystem AssessmentDraft-Do Not Quote or Cite June 2010 x MI Myocardial infarction Mm Megameter MSA Metropolitan Statistical Area N Nitrogen NAAQS National Ambient Air Quality Standards

NCEA National Center for Environmental Assessment NCore National Core Monitoring Network

Ni Nickel NMMAPS National Morbidity, Mo rtality, and Air Pollution Study

NO Nitric oxide

NO 2 Nitrogen dioxide

NO 3 - Nitrate NOx Nitrogen oxides

NRC National Research Council

O 3 Ozone OAQPS Office of Air Qual ity Planning and Standards

OAR Office of Air and Radiation OC Organic carbon

OR Odds ratio ORD Office of Research and Development PA Policy Assessment PAH Polyaromatic Hydrocarbon PAR Photosynthetically active radiation

Pb Lead PBDES Polybrominated diphenyl ethers

PM Particulate matter

PM 10 Particles with an upper 50% cut-point of 10± 0.5 μ m aerodynamic diameter and a penetration curve as specified in the Code of Federal Regulations.

PM 10-2.5 Particles with an upper 50% cut-point of 10 μ m aerodynamic diameter and a lower 50% cut-point of 2.5 μ m aerodynamic diameter.Draft-Do Not Quote or Cite June 2010 xi PM 2.5 Particles with an upper 50% cut-point of 2.5 μ m aerodynamic diameter and a penetration curve as specified in the Code of Federal Regulations.

PM X The legal definition for PM X , as defined in the Code of Federal Regulations, includes both a 50% cut-poi nt and a penetration curve. A 50% cut-point of X μ m diameter means that 50% of particles with aerodynamic diameter of X are removed by the inlet and 50% pass through the inlet and are co llected on the filter. De pending on the specific penetration curve specified, particles larger than X μ m aerodynamic diameter are collected with an efficiently than decreases rapidly for particles larger than X while the collection efficiency for particles smaller than X increases rapidly with decreas ing size until 100 % efficiency is reached. POP Persistant organic pollutants PRB Policy-Relevant Background

RA Risk Assessment REA Risk and Exposure Assessment RF Radiative forcing RH Relative humidity

RR Relative risk

SCAB South Coast Air Basin

SD Standard deviation

SES Socioeconomic status

Si Silicon

S Sulfur

SO 2 Sulfur Dioxide

SO 4 2- Sulfate

SO x Sulfur Oxides SOCs Semi-volatile organic compounds TSP Total suspended particulate UFPs Ultrafine particles UFVA Urban-Focused Visibility Assessment

V Vanadium VAQ Visual Air Quality VOC Volatile organic compoundsDraft-Do Not Quote or Cite June 2010 xii WACAP Western Airborne Contaminants Assessment Project

WHI Women’s Health Initiative

Zn ZincD raft- Do Not Quote or Cite 1-1 June 2010 

### 1. INTRODUCTION 1

1.1 PURPOSE 2
The U.S. Environmental Protection Agency (EPA) is presently conducting a review of 3 the national ambient air quality standards (NAAQS ) for particulate matter (PM). The plan and 4 schedule for this review were presented in the Integrated Review Plan for the National Ambient 5 Air Quality Standards for Particulate Matter (IRP; US EPA, 2008a). The IRP identified key 6 policy-relevant issues to be addr essed in this review as a series of questions that frame our 7 consideration of whether the current NAAQS for PM should be retained or revised. 8 This Policy Assessment (PA), prepared by st aff in the EPA’s Office of Air Quality 9 Planning and Standards (OAQPS), is intended to help “bridge th e gap” between the relevant 10 scientific information and assessments and the judgments required of the EPA Administrator in 11 determining whether, and if so, how, it is appropriate to revi se the NAAQS for PM. 1 This 12 second draft PA presents factors relevant to EP A’s review of the primary (health-based) and 13 secondary (welfare-based) PM NAAQS. It focuses on both evidence- and risk-based 14 information in evaluating the adequacy of the current PM NAAQS and in identifying potential 15
alternative standards for consideration. 16 In this second draft PA, we consider the scie ntific and technical information available in 17
this review as assessed in the Integrated Science A ssessment for Particulate Matter (Final 18 Report) (ISA, US EPA, 2009a), the Quantitative Health Risk Assessment for Particulate Matter 19 (Final Report) (RA, US EPA, 2010a) and the Particulate Matter Urban- Focused Visibility 20 Assessment (Final Report) (UFVA, US EPA, 2010b). In so doing, we focus on information that 21 is most pertinent to evaluating the ba sic elements of NAAQS: indicator 2 , averaging time, form, 3 22 and level. These elements, which together serv e to define each standard, must be considered 23 collectively in evaluating the health and welfar e protection afforded by the PM standards. 24 Although this second draft PA should be of us e to all parties interested in this PM 25 NAAQS review, it is written with an expectation that the reader ha s familiarity with the technical 26
discussions contained in the IS A (US EPA, 2009a) and in the qua ntitative risk and visibility 27 assessment documents (US EPA, 2010a,b). 28

1 Preparation of a PA by OAQPS staff reflects Administrator Jackson’s decision to modify the NAAQS review process that was presented in the IRP. See http://www.epa.gov/ttn/naaqs/review.html for more information on the current NAAQS review process.
2 The “indicator” of a standard define s the chemical species or mixture that is to be measured in determining whether an area attains the standard.
3 The “form” of a standard defines the ai r quality statistic that is to be compared to the level of the standard in determining whether an area attains the standard.D raft- Do Not Quote or Cite 1-2 June 2010 1.2 BACKGROUND 1

1.2.1 Legislative Requirements 2
Two sections of the Clean Air Act (CAA) gove rn the establishment and revision of the 3 NAAQS. Section 108 (42 U.S.C. se ction 7408) directs the Administ rator to identify and list air 4 pollutants that meet three specified criteria, in cluding air pollutants “emissions of which, in his 5 judgment, cause or contribute to air pollution wh ich may reasonably be anticipated to endanger 6 public health and welfare” and whose “presence . . . in the ambient air results from numerous or 7 diverse mobile or stationary sources” and to issue air quality criteria for th ose that are listed. Air 8 quality criteria are to “accurately reflect the late st scientific knowledge useful in indicating the 9 kind and extent of all identifiable effects on pub lic health or welfare which may be expected 10 from the presence of [a] pollutant in the ambient air . . .” 42 U.S.C. § 7408(b). 11 Section 109 (42 U.S.C. section 7409) dire cts the Administrator to propose and 12 promulgate “primary” and “secondary” NAAQS for po llutants for which air quality criteria are 13 issued. Section 109(b)(1) defines a primary standard as one “the attainment and maintenance of 14 which in the judgment of the Administrator, based on [air quality] criteria and allowing an 15 adequate margin of safety, are requi site to protect the public health.” 4 A secondary standard, as 16 defined in Section 109(b)(2), must “specify a leve l of air quality the attainment and maintenance 17 of which, in the judgment of the Administrator, base d on such [air quality] cr iteria, is requisite to 18 protect the public welfare from any known or anticipated advers e effects associated with the 19 presence of [the] pollutant in the ambient air.” 5 20 The requirement that primary standards incl ude an adequate margin of safety was 21
intended to address uncertainties associated with inconclusive scientific and technical 22
information available at the time of standard set ting. It was also intended to provide a reasonable 23 degree of protection against hazards th at research has not yet identified. Lead Industries 24 Association v. EPA, 647 F.2d 1130, 1154 (D.C. Cir 1980 ), cert. denied, 449 U.S. 1042 (1980); 25
American Petroleum Institute v. Costle , 665 F.2d 1176, 1186 (D.C. Cir. 1981), cert. denied, 455 26 U.S. 1034 (1982); American Farm Bureau Federation v. EPA, 559 F. 3d 512, 533 (D.C. Cir. 27 2009). Both kinds of uncertainties are components of the risk associated with pollution at levels 28
below those at which human health effects can be said to occur with reasonable scientific 29

4 The legislative history of section 109 indicates that a primary standard is to be set at “the maximum permissible ambient air level . . . which will protect the health of an y [sensitive] group of the population,” and that for this purpose “reference should be made to a representative samp le of persons comprising the sensitive group rather than to a single person in such a group.” S. Rep. No. 91-1196, 91 st Cong., 2d Sess. 10 (1970).
5 Welfare effects as defined in section 302(h) (42 U.S.C. section 7602(h)) include, but are not limited to, “effects on soils, water, crops, vegetation, man-made materials, animals, wildlife, weather, visibility and climate, damage to and deterioration of property, and hazards to transportation, as well as effects on economic values and on personal comfort and well-being.”D raft- Do Not Quote or Cite 1-3 June 2010 certainty. Thus, in selecting primary standards th at include an adequate margin of safety, the 1 Administrator is seeking not only to prevent pollution levels that have been demonstrated to be 2 harmful but also to prevent lower pollutant leve ls that may pose an unacceptable risk of harm, 3 even if the risk is not precisely identified as to nature or degree. 4 In selecting a margin of safet y, EPA considers such factors as the nature and severity of 5 the health effects involved, the size of the susc eptible population(s) at risk, and the kind and 6 degree of the uncertainties that must be addresse d. The selection of any particular approach to 7 providing an adequate margin of safety is a policy choice left specifically to the Administrator’s 8 judgment. Lead Industries Association v. EPA , supra, 647 F.2d at 1161-62. 9 In setting standards that are “requisite” to protect public health a nd welfare, as provided 10 in section 109(b), EPA’s task is to establish standards that are neither more nor less stringent 11 than necessary for these purposes. In so doing, EPA may not consider th e costs of implementing 12 the standards. See generally Whitman v. American Trucking Associations , 531 U.S. 457, 471, 13 475-76 (2001). 14 Section 109(d) (1) of the CAA requires that “not later than December 31, 1980, and at 5- 15 year intervals thereafter, the Administrator shall complete a thorough review of the criteria 16 published under section 108 and th e national ambient air quality st andards . . . and shall make 17
such revisions in such criteri a and standards and promulgate such new standards as may be 18 appropriate in accordance with section [108]... and subsection (b) . . .” 42 U.S.C. § 7409(d)(1). 19 Section 109(d)(2) requires that an independent sc ientific review committee “shall complete a 20
review of the criteria . . . and the national primary and secondary ambient air quality standards . . 21 . and shall recommend to the Administrator any new . . . standards and revisions of existing 22 criteria and standards as may be appropriate . . .” 42 U.S.C. § 7409(d)(2). Since the early 23 1980's, this independent review function has been performed by the Clean Air Scientific 24 Advisory Committee (CASAC). 25

1.2.2 Previous PM NAAQS Reviews 26
The EPA initially established NAAQS for PM under section 109 of the CAA in 1971. 27 Since then, the Agency has made a number of ch anges to these standards to reflect continually 28 expanding scientific information, particularly with respect to the se lection of indicator 6 and level. 29 Table 1-1 provides a summary of the PM NAAQS th at have been promulgated to date. These 30 decisions are briefly discussed below. 31

6 Particulate matter is the generic term for a broad class of chemically and physically diverse substances that exist as discrete particles (liquid droplets or solids) over a wide range of sizes, such that the indicator for a PM NAAQS has historically been defined in terms of particle size ranges.D raft- Do Not Quote or Cite 1-4 June 2010 Table 1-1. Summary of National Ambien t Air Quality Standards Promulgated for 1 Particulate Matter 1971-2006 7 2 3
Final Rule Indicator Ave. Time Level Form

24-hour 260 μg/m 3 (primary) 150 μg/m 3 (secondary) Not to be exceeded more than once
per year 1971

36 FR 8186 April 30, 1971 TSP

Annual 75 μg/m 3 (primary) Annual average

24-hour 150 μg/m 3 Not to be exceeded more than once per year on average over a 3-year period 1987

52 FR 24634 July 1, 1987 PM 10

Annual 50 μg/m 3 Annual arithmetic mean, averaged over 3 years 24-hour 65 μg/m 3 98 th percentile, averaged over 3 years PM 2.5 Annual 15 μg/m 3 Annual arithmetic mean, averaged over 3 years 8

24-hour 150 μg/m 3 Initially promulgated 99 th percentile, averaged over 3 years; when 1997 standards were vacated, the form of 1987 standards remained in place (not to be exceeded more than once per year on average over a 3-year period) 1997

62 FR 38652 July 18, 1997 PM 10

Annual 50 μg/m 3 Annual arithmetic mean, averaged over 3 years
24-hour 35 μg/m 3 98 th percentile, averaged over 3 years PM 2.5 Annual 15 μg/m 3 Annual arithmetic mean, averaged over 3 years 9 2006

71 FR 61144 October 17, 2006 PM 10 24-hour 150 μg/m 3 Not to be exceeded more than once per year on average over a 3-year period
4

7 When not specified, primary and secondary standards are identical.
8 The level of the standard was to be compared to meas urements made at sites that represent “community-wide air quality” recording the highest level, or, if specific constraints were met, measurements from multiple communitywide air quality monitoring sites could be averaged (“spatial averaging”).
9 The constraints on the spatial averaging criteria were tig htened by further limiting the conditions under which some areas may average measurements from mu ltiple community-oriented monitors to determine compliance (see 71 FR 61165-61167).D raft- Do Not Quote or Cite 1-5 June 2010 In 1971, EPA established NAAQS for PM base d on the original air quality criteria 1 document (DHEW, 1969; 36 FR 8186, April 30, 1971). The reference method specified for 2 determining attainment of the original standa rds was the high-volume sampler, which collects 3 PM up to a nominal size of 25 to 45 micrometers (μ m) (referred to as total suspended particles or 4 TSP). The primary standards (measured by the indicator TSP) were 260 μg/m 3 , 24-hour average, 5 not to be exceeded more than once per year, and 75 μg/m 3 , annual geometric mean. The 6 secondary standard was 150 μg/m 3 , 24-hour average, not to be exceeded more than once per 7

year. 8 In October 1979, EPA announced the first periodi c review of the crit eria and NAAQS for 9 PM, and significant revisions to the original standards were promulgated in 1987 (52 FR 24634, 10 July 1, 1987). In that decision, EPA cha nged the indicator for PM from TSP to PM 10 , the latter 11 including particles with a median aerodynamic diam eter less than or equal to 10 μm, which 12 delineates thoracic particles (i.e ., that subset of inhalable pa rticles small enough to penetrate 13 beyond the larynx to the thoracic region of the re spiratory tract). The EPA also revised the 14 primary standards by: (1 ) replacing the 24-hour TSP st andard with a 24-hour PM 10 standard of 15 150 μg/m 3 with no more than one e xpected exceedance per year; and (2) replacing the annual 16
TSP standard with a PM 10 standard of 50 μg/m 3 , annual arithmetic mean. The secondary 17 standard was revised by replacing it with 24-hour and annual standard s identical in all respects to 18 the primary standards. The revi sions also included a new reference method for the measurement 19
of PM 10 in the ambient air and rules for determini ng attainment of the new standards. On 20 judicial review, the revised standa rds were upheld in all respects. Natural Resources Defense 21 Council v. EPA, 902 F. 2d 962 (D.C. Cir. 1990), ce rt. denied, 498 U.S. 1082 (1991). 22 In April 1994, EPA announced its plans for the second periodic review of the criteria and 23 NAAQS for PM, and promulgated significant revisions to the NAAQS in 1997 (62 FR 38652, 24 July 18, 1997). Most significantly, EPA dete rmined that although the PM NAAQS should 25 continue to focus on particles less than or e qual to 10 μm in diameter, the fine and coarse 26
fractions of PM 10 should be considered separately. New standards were added, using PM 2.5 , 27 referring to particles with a nominal median aerodynamic diameter less than or equal to 2.5 μm, 28 as the indicator for fine particles. The PM 10 standards were retained for the purpose of 29 regulating the coar se fraction of PM 10 (referred to as thoracic coar se particles or coarse-fraction 30 particles; generally including pa rticles with a nomina l median aerodynamic diameter greater than 31 2.5 μm and less than or equal to 10 μm, or PM 10-2.5 ). The EPA established two new PM 2.5 32 standards: an annual standard of 15 μg/m 3 , based on the 3-year average of annual arithmetic 33
mean PM 2.5 concentrations from single or multiple m onitors sited to represent community-wide 34 air quality; and a 24-hour standard of 65 μg/m 3 , based on the 3-year average of the 98th 35 percentile of 24-hour PM 2.5 concentrations at each population-or iented monitor within an area. 36D raft- Do Not Quote or Cite 1-6 June 2010 Also, EPA established a new referen ce method for the measurement of PM 2.5 in the ambient air 1 and rules for determining attainment of the new standards. To continue to address thoracic 2 coarse particles, the annual PM 10 standard was retained, while the form, but not the level, of the 3
24-hour PM 10 standard was revised to be based on the 99 th percentile of 24-hour PM 10 4
concentrations at each monitor in an area. The EPA revised the secondary standards by making 5 them identical in all respects to the primary standards. 6 Following promulgation of the revised PM NAAQS in 1997, petitions for review were 7 filed by a large number of partie s, addressing a broad range ofissues. In May 1998, a three8 judge panel of the U.S. Court of Appeals for the District of Colu mbia Circuit issu ed an initial 9 decision that upheld EPA’s decision to establish fine particle standards, holding that "the 10 growing empirical evidence dem onstrating a relationship between fine particle pollution and 11 adverse health effects amply justifies estab lishment of new fine particle standards." American 12 Trucking Associations v. EPA , 175 F. 3d 1027, 1055-56 (D.C. Cir. 1999) (rehearing granted in 13 part and denied in part, 195 F. 3d 4 (D.C. Cir. 1999), affirmed in part and reversed in part, 14 Whitman v. American Trucking Associations , 531 U.S. 457 (2001). The panel also found "ample 15 support" for EPA's decision to regulate coar se particle pollution, but vacated the 1997 PM 10 16 standards, concludi ng in part that PM 10 is a "poorly matched indica tor for coarse particulate 17 pollution" because it includes fine particles. Id . at 1053-55. Pursuant to the court’s decision, 18
EPA removed the vacated 1997 PM 10 standards from the Code of Federal Regulations (CFR) (69 19 FR 45592, July 30, 2004) and deleted the regulatory provision [at 40 CFR section 50.6(d)] that 20
controlled the transition fr om the pre-existing 1987 PM 10 standards to the 1997 PM 10 standards. 21 The pre-existing 1987 PM 10 standards remained in place (65 FR 80776, December 22, 2000). 22 The Court also upheld EPA’s determination not to establish more stringe nt secondary standards 23 for fine particles to address eff ects on visibility (175 F. 3d at 1027). 24 More generally, the panel held (over a strong dissent) that EPA’s approach to 25 establishing the level of the standards in 1997, both for the PM and for the ozone (O 3 ) NAAQS 26 promulgated on the same day, effected “an unconstitutional delegation of legislative authority.” 27
Id . at 1034-40. Although the panel stated that “the factors EPA uses in determining the degree of 28 public health concern associated with different levels of ozone and PM are reasonable,” it 29 remanded the rule to EPA, stating that when EPA considers these factors for potential non30 threshold pollutants “what EPA lacks is any determinate criterion for drawing lines” to 31
determine where the standards should be set. Co nsistent with EPA’s l ong-standing interpretation 32 and D.C. Circuit precedent, the panel also reaffi rmed its prior holdings that in setting NAAQS 33 EPA is “not permitted to consider the co st of implementing those standards” Id . at 1040-41. 34 On EPA’s petition for rehearing, the panel adhered to its positi on on these points. 35 American Trucking Associations v. EPA , 195 F. 3d 4 (D.C. Cir. 1999). The full Court of 36D raft- Do Not Quote or Cite 1-7 June 2010 Appeals denied EPA’s request for rehearing en banc, with five judges dissenting. Id . at 13. Both 1 sides filed cross appeals on these issues to th e United States Supreme Court, which granted 2 certiorari. In February 2001, the Supreme C ourt issued a unanimous decision upholding EPA’s 3 position on both the constitutional and cost issues. Whitman v. American Trucking Associations

, 4 531 U.S. 457, 464, 475-76. On the constitutional issue, the Court held that the statutory 5 requirement that NAAQS be “requi site” to protect public health with an adequate margin of 6 safety sufficiently cabined EPA’s discretion, affi rming EPA’s approach of setting standards that 7 are neither more nor less stringent than necessa ry. The Supreme Court remanded the case to the 8 Court of Appeals for resolution of any remaining issues that had not b een addressed in that 9 court’s earlier rulings. Id . at 475-76. In March 2002, the Court of Appeals rejected all 10 remaining challenges to the standards, holding under the traditional standard of review that 11
EPA’s PM 2.5 standards were reasonably supported by the administrative record and were not 12 “arbitrary and capricious.” American Trucking Associations v. EPA, 283 F. 3d 355, 369-72 (D.C. 13 Cir. 2002). 14 In October 1997, EPA published its plans for the next periodic review of the air quality 15 criteria and NAAQS for PM (62 FR 55201, October 23, 1997), including the 1997 PM 2.5 16
standards and the 1987 PM 10 standards. After CASAC and public review of several drafts, EPA’s 17
National Center for Environmental Assessment (NCEA) finalized the Air Quality Criteria 18 Document for Particulate Matter (henceforth, AQCD or the "Cr iteria Document") in October 19 2004 (U.S. EPA, 2004) and OAQPS finalized an assessment document, Particulate Matter 20 Health Risk Assessment for Selected Urban Areas (Abt, 2005), and a “Staff Paper,” Review of the 21 National Ambient Air Quality Standards for Particul ate Matter: Policy Asse ssment of Scientific 22 and Technical Information, in December 2005 (U.S. EPA, 2005). In conjunction with their 23 review of the Staff Paper, CASAC provided advice to the Adminstrator on revisions to the PM 24 NAAQS (Henderson, 2005a). In particular, mo st CASAC PM Panel members favored revising 25
the level of the 24-hour PM 2.5 primary standard in the range of 35 to 30 μg/m 3 with a 98 th 26 percentile form, in concert with revising the level of the annual PM 2.5 standard in the range of 14 27 to 13 μg/m 3 (Henderson, 2005a, p.7). For thoracic coarse particles, the Panel had reservations in 28 recommending a 24-hour PM 10-2.5 primary standard, and agreed th at there was a need for more 29
research on the health effects of thoracic coar se particles (Henderson, 20 05b). With regard to 30 secondary standards, most Panel members stro ngly supported establishing a new, distinct 31 secondary PM 2.5 standard to protect urban visi bility (Henderson, 2005a, p. 9). 32 On January 17, 2006, EPA proposed to revise the primary and secondary NAAQS for PM 33 (71 FR 2620) and solicited comment on a broad range of options. Proposed revisions included: 34 revising the level of the 24-hour PM 2.5 primary standard to 35 μg/m 3 ; revising the form, but not 35 the level, of the annual PM 2.5 primary standard by tightening th e constraints on the use of spatial 36D raft- Do Not Quote or Cite 1-8 June 2010 averaging; replacing the 24-hour PM 10 primary standard with a 24-hour standard defined in 1 terms of a new indicator, PM 10-2.5 10 set at a level of 70 μg/m 3 based on the 3-year average of the 2
98 th percentile of 24-hour PM 10-2.5 concentrations; re voking the annual PM 10 primary standard; 3 and revising the secondary sta ndards by making them identical in all respects to the proposed 4 suite of primary standards fo r fine and coarse particles. 11 Subsequent to the proposal, CASAC 5 provided additional advice to EPA in a letter to the Administrator requesting reconsideration of 6 CASAC’s recommendations for both the primary and secondary PM 2.5 standards as well as the 7
standards for thoracic coarse particles (Henderson, 2006a). 8 On October 17, 2006, EPA promulgated revi sions to the PM NAAQS to provide 9 increased protection of public hea lth and welfare (71 FR 61144). W ith regard to the primary and 10 secondary standards for fine particles, EPA revised the level of the 24-hour PM 2.5 standard to 35 11 μg/m 3 , retained the level of the annual PM 2.5 standard at 15 μg/m 3 , and revised the form of the 12
annual PM 2.5 standard by adding further constraints on the optional use of spatial averaging. The 13 EPA revised the secondary standard s for fine particles by making them identical in all respects to 14 the primary standards. With regard to the prim ary and secondary standards for thoracic coarse 15 particles, EPA retained the le vel and form of the 24-hour PM 10 standard (such that the standard 16 remained at a level of 150 μg/m 3 with a one expected exceedan ce form), and revoked the annual 17

PM 10 standard. The EPA also established a new Federal Reference Method (FRM) for the 18
measurement of PM 10-2.5 in the ambient air (71 FR 61212-13). Although the standards for 19 thoracic coarse particles were not defined in terms of a PM 10-2.5 indicator, the new FRM for 20

PM 10-2.5 was established to provide a basis for ap proving Federal Equivale nt Methods (FEMs) 21 and to promote gathering scien tific data to support future reviews of the PM NAAQS. 22 Following issuance of the final rule, CASAC ar ticulated its concern that “EPA’s final 23 rule on the NAAQS for PM does not reflect several important as pects of the CASAC’s advice” 24 (Henderson et al, 2006b). With regard to the PM 2.5 annual primary standard, CASAC expressed 25 serious concerns regarding the decision to re tain the level of the standard at 15 μg/m 3 . With 26 regard to EPA’s final decisi on to retain the 24-hour PM 10 standard for thoracic coarse particles, 27 CASAC acknowledged concerns asso ciated with retaining this standard while recognizing the 28 need to have a standard in place to protect against effects associat ed with short-term exposures to 29 thoracic coarse particles. With regard to EPA’s final decision to revise the secondary PM 2.5 30

10 This proposed indicator was qualified so as to include any ambient mix of PM 10-2.5 dominated by particles generated by high-density traffic on paved roads, industrial sources, and construction sources, and to exclude any ambient mix of particles dominated by rural windblown dust and soils and agricultural and mining sources.
11 In recognition of an alternative view expressed by most members of the CASAC PM Panel, the Agency also solicited comments on a subdaily (4- to 8-hour averaging time) secondary PM 2.5 standard to address visibility impairment, within the range of 20 to 30 μg/m 3 and with a form within the range of the 92 nd to 98 th percentile (71 FR 2685).D raft- Do Not Quote or Cite 1-9 June 2010 standards to be identical in all respects to the revised primary PM 2.5 standards, CASAC 1 expressed concerns that CASAC’s advice to establish a di stinct secondary standard for fine 2 particles to address visibility impairment was not followed. 3

1.2.3 Litigation Related to the 2006 PM Standards 4
Several parties filed petitions for review following promulgation of the revised PM 5 NAAQS in 2006. These petitions addressed the follo wing issues: (1) selec ting the level of the 6 primary annual PM 2.5 standard; (2) retaining PM 10 as the indicator of a standard for thoracic 7 coarse particles, re taining the level and form of the 24-hour PM 10 standard, and revoking the 8

PM 10 annual standard; and (3) setting the secondary PM 2.5 standards identical to the primary 9 standards. On February 24, 2009, the U.S. Court of Appeals for the District of Columbia Circuit 10 issued its opinion in the case American Farm Bureau Federation v. EPA , 559 F. 3d 512 (D.C. 11 Cir. 2009). The court remanded the primary annual PM 2.5 NAAQS to EPA because EPA failed 12 to adequately explain why the standard provide d the requisite protecti on from both short- and 13 long-term exposures to fine particles, in cluding protection for at-risk populations. American 14
Farm Bureau Federation v. EPA , 559 F. 3d 512, (D.C. Cir. 2009). With regard to the standards 15
for PM 10 , the court upheld EPA’s decisi ons to retain the 24-hour PM 10 standard to provide 16 protection from thoracic coar se particle exposures a nd to revoke the annual PM 10 . standard. 17
American Farm Bureau Federation at 533-38. With regard to the secondary PM 2.5 standards, the 18 court remanded the standards to EPA because the Agency failed to adequately explain why 19 setting the secondary PM standards identical to the primary standard s provided the required 20 protection for public welfare, including pr otection from visibility impairment. 21
The decisions of the court with regard to these three issues are discussed in chapters 2, 3 22 and 4, respectively. The EPA is responding to the c ourt’s remands as part of the current review 23 of the PM NAAQS. 24

1.2.4 Current PM NAAQS Review 25

The EPA initiated the current revi ew of the air quality criteria for PM in June 2007 with a 26 general call for information (72 FR 35462, June 28, 2007). In July 2007, EPA held two “kick27 off” workshops on the primary and seconda ry PM NAAQS, respectively (72 FR 34003 and 28 34005, June 20, 2007). 12 These workshops provided an opport unity for a public discussion of 29 the key policy-relevant issues around which EP A would structure this PM NAAQS review and 30

12 See workshop materials http://www.regulations.gov/s earch/Regs/home.html#home Docket ID numbers EPA-HQOAR-2007-0492-008; EPA-HQ-OAR-2007-0492-009; EPA-HQ-OAR-2007-0492-010; and EPA-HQ-OAR-2007- 0492-012.D raft- Do Not Quote or Cite 1-10 June 2010 the most meaningful new science that would be available to info rm our understanding of these 1
issues. 2 Based in part on the workshop discussions , EPA developed a draft IRP outlining the 3 schedule, process, and key policy-relevant questi ons that would guide the evaluation of the air 4 quality criteria for PM and the review of th e primary and secondary PM NAAQS (US EPA, 5 2007). On November 30, 2007, EPA held a consulta tion with CASAC on the draft IRP (72 FR 6 63177, November 8, 2007), which included the opport unity for public comment. The final IRP 7 (US EPA, 2008a) incorporated comments from CASAC (Henderson, 2008) and the public on the 8 draft plan as well as input fr om senior Agency managers. 13 9 As part of the process of pr eparing the PM ISA, NCEA hoste d a peer review workshop in 10 June 2008 on preliminary drafts of key ISA chapters (73 FR 30391, May 27, 2008). The first 11 external review draft ISA (US EPA, 2008b) wa s reviewed by CASAC and the public at a 12 meeting held in April 2009 (74 FR 2688, Febr uary 19, 2009). Based on CASAC and public 13 comments, NCEA prepared a second draft ISA (US EPA, 2009b), which was reviewed by 14 CASAC and the public at a meeting held on October 5-6, 2009 (74 FR 46586, September 10, 15 2009). Based on CASAC and public comments, NCEA prepared the final ISA (US EPA, 16 2009a; 74 FR 66353, December 15, 2009). 17 In preparing the Risk and Exposure Asse ssment (REA) documents that build on the 18 scientific evidence presented in the ISA, OAQPS released two planning documents: Particulate 19 Matter National Ambient Air Quality Standards: Scope and Methods Plan for Health Risk and 20 Exposure Assessment and Particulate Matter National Ambi ent Air Quality Standards: Scope 21 and Methods Plan for Urban Visi bility Impact Assessment (henceforth, Scope and Methods 22 Plans, US EPA, 2009c,d). These planning documents outlined the scope and approaches that 23 staff planned to use in conducting quantitative assessments as well as key issues that would be 24 addressed as part of the assessments. In desi gning and conducting the in itial health risk and 25 visibility impact assessments, we consider ed CASAC comments (Samet 2009a,b) on the Scope 26 and Methods Plans made during an April 2009 c onsultation (74 FR 7688, February 19, 2009) as 27 well as public comments. Two draft assessment documents, Risk Assessment to Support the 28 Review of the PM 2.5 Primary National Ambient Air Qualit y Standards: External Review Draft - 29 September 2009 (US EPA 2009e) and Particulate Matter Urban-Focu sed Visibility Assessment - 30

13 The process followed in this review varies from the NAAQS review process described in section 1.1 of the IRP (US EPA, 2008a). On May 21, 2009, EPA Administrator Jackson called for key changes to the NAAQS review process including reinstating a policy assessment document th at contains staff analyses of the scientific bases for alternative policy options for consideration by senior Agency management prior to rulemaking. In conjunction with this change, EPA will no longer issue a policy assessment in the form of an advance notice of proposed rulemaking (ANPR) as discussed in the IRP. For more information on the overall process followed in this review including a description of the major elements of the process for reviewing NAAQS see Jackson (2009).D raft- Do Not Quote or Cite 1-11 June 2010 External Review Draft - September 2009 (US EPA, 2009f) we re reviewed by CASAC and the 1 public at a meeting held on October 5-6, 2009. Based on CASAC (Samet 2009c,d) and public 2 comments, OAQPS staff revised these draft docum ents and released second draft assessment 3 documents (US EPA, 2010d,e) in January and February 2010 (75 FR 4067, January 26, 2010) for 4 CASAC and public review at a meeting held on March 10-11, 2010. Based on CASAC (Samet, 5 2010a, b) and public comments on the second draf t assessment documents, we revised these 6 documents and released final assessment documents in June 2010 (US EPA, 2010a,b). 7 A preliminary draft PA (US EPA, 2009g) was released in September 2009 for 8 informational purposes and to facilitate disc ussion with CASAC at the October 5-6, 2009 9 meeting on the overall structure, ar eas of focus, and level of deta il to be included in the PA. 10 CASAC’s comments on the preliminary draft PA encouraged the development of a document 11 focused on the key policy-relevant issues that draw s from and is not repetitive of information in 12
the ISA and REAs. These comments were consid ered in developing a first draft PA (US EPA, 13 2010c) that built upon the information presented a nd assessed in the final ISA and two second 14 draft REAs. The EPA presented an overview of the first draft PA at a CASAC meeting on 15 March 10, 2010. CASAC and public review of th e first draft PA was discussed during public 16 teleconferences on April 8-9, 2010 (75 FR 8062, February 23, 2010) and May 7, 2010 (75 17 FR19971, April 16, 2010). 18 CASAC (Samet, 2010c) and public comments on th e first draft PA were considered in 19 developing this second draft PA which will be reviewed by CASAC at an upcoming meeting 20 scheduled for July 26-27, 2010 (75 FR 32763, June 9, 2010). We will consider CASAC and 21 public comments on this second draft PA in prepar ing a final PA which will include final staff 22 conclusions related to the adequ acy of the current PM standard s and alternative standards for 23 consideration that are supported by the currently available scien tific evidence a nd quantitative 24 assessments. We plan to releas e the final PA in September 2010. 25

1.3 GENERAL APPROACH AND ORGANI ZATION OF THIS DOCUMENT 26

This second draft PA includes staff’s eval uation of the policy implications of the 27 scientific assessment of the evidence presente d and assessed in the IS A and the results of 28 quantitative assessments based on that evidence presented and assessed in the REAs. Taken 29 together, this information informs staff conclusi ons and the identificatio n of policy options for 30 consideration in addressing public health and welfare effects associated with exposure to ambient 31
PM. 32 Since the last review, much new informati on is now available on PM air quality and 33
human health effects di rectly in terms of PM 2.5 and, to a much more limited degree, PM 10-2.5 and 34 ultrafine particles (UFPs). Since the purpose of this review is to evaluate the adequacy of the 35D raft- Do Not Quote or Cite 1-12 June 2010 current standards, which separately address fine and thoracic coar se particles, staff is focusing 1 this policy assessment and associated quantitativ e analyses primarily on the evidence related 2 directly to PM 2.5 and PM 10-2.5 . In so doing, we are considering PM 10 -related evidence primarily 3 to help inform our understanding of key issues and to help interpret and provide context for 4 understanding the public health and welfare impacts of ambient fine and coarse particles. We are 5 also considering the currently available evidence related to UFPs as well as PM 2.5 components to 6 aid in considering whether there is support to co nsider standards with a different size fraction 7
and/or distinct standards fo cused on regulating specific PM 2.5 components or categories of fine 8 particle sources. 9 Following this introductory chapter, this doc ument is organized into two main parts: 10 review of the primary PM NAAQS (chapters 2 a nd 3) and review of the secondary PM NAAQS 11 (chapters 4 and 5). Chapters 2 and 3 present sta ff observations and conclusions related to review 12 of the primary standards for fine and thoracic coarse particles, respectively. Each chapter 13 includes background information on the rationale fo r previous reviews and the policy assessment 14 approaches followed in the current review, fo cusing on evidence-based considerations and, as 15 appropriate, quantitative risk-based considerations. Staff conclusi ons are presented with regard 16 to the adequacy of the current primary standard s and potential alternativ e primary standards for 17 consideration, in terms of indicators, averaging times, forms, and levels. Chapter 4 focuses on 18 PM-related visibility impairment, and presents st aff observations and conclusions with regard to 19 the adequacy of the current standards and potential distinct se condary standards for 20 consideration, in terms of alternative indicators , averaging times, forms, and levels. Chapter 5 21 focuses on other PM-related welfare effects, incl uding effects on climate, ecological effects, and 22 effects on materials, and presents staff observations and conclusions with regard to the adequacy 23
of the current standards and the extent to which information is available to support consideration 24
of alternativ e standards. 25D raft- Do Not Quote or Cite 1-13 June 2010 1.4 REFERENCES 1

Abt Associates (2005). Particulate Matter Health Risk Assessment for Selected Urban Areas. Final Report. 2 Bethesda, MD. Prepared for the Office of Air Qu ality Planning and Standards, U.S. Environmental 3 Protection Agency, Contract No. 68-D-03-002. EPA 452/R-05-007A. Available: 0 4

Henderson, R. (2005a). EPA’s Review of the Nationa l Ambient Air Quality Standards for Particulate Matter 5 (Second Draft PM Staff Paper, January 2005): A review by the Particulate Matter Review Panel of the EPA 6 Clean Air Scientific Advisory Committee. June 6, 2005. Available: http://www.epa.gov/sab/pdf/casac-05- 7 007.pdf

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Henderson, R. (2005b). Clean Air Scientific A dvisory Committee (CASAC) Re view of the EPA Staff 9 Recommendations Concerning a Potential Thoracic Coarse PM Standard in the Review of the National 10 Ambient Air Quality Standards for Particulate Matte r: Policy Assessment of Scientific and Technical 11 Information (Final PM OAQPS Staff Paper, EPA-452/R-05-005). September 15, 2005. Available: 12 http://www.epa.gov/sab/panels/casacpmpanel.html

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Henderson, R. (2006a). Letter from Dr. Rogene Henderso n, Chair, Clean Air Scientific Advisory Committee to the 14 Honorable Stephen L. Johnson, Administrator, US EPA. Clean Air Scientific Advisory Committee 15 Recommendations Concerning the Proposed National Ambient Air Quality Standards for Particulate 16 Matter. March 21, 2006. Available: h ttp://www.epa.gov/sab/pdf/ casac-ltr-06-002.pdf 17

Henderson, R.; Cowling, E.; Crapo, J.D..; Miller, F. J.; Poirot, R.L.; Speizer, F. ; Zielinska, B. (2006b). Letter from 18 Clean Air Scientific Advisory Committee to the Honorable Stephen L. Johnson, Administrator, US EPA. 19 Clean Air Scientific Advisory Committee Recommendati ons Concerning the Final National Ambient Air 20 Quality Standards for Particulate Matter. September 29, 2006. Available: 21 http://www.epa.gov/sab/pd f/casac-ltr-06-002.pdf 22

Henderson, R. (2008). Letter from Dr. Rogene Henderson, Chair, Clean Air Scientific Advisory Committee to the 23 Honorable Stephen L. Johnson, Administrator, US EPA. Clean Air Scientific Advisory Committee 24 Particulate Matter Review Panel’ s Consultation on EPA’s Draft Integrated Review Plan for the National 25 Ambient Air Quality Standards for Particulate Matter . January 3, 2008. Available: 26 http://yosemite.epa.gov/sab/sabproduct.nsf/264cb1227d55e02c85257402007446a4/76D069B8191381DA8 27 52573C500688E74/$File/EPA-CASAC-08-004-unsigned.pdf 28

Jackson (2009). Memo from Administrator Lisa P. Jackson to Elizabeth Craig, Acting Assistant Administrator for 29 OAR and Lek Kadeli, Acting Assistant Administrator for ORD. Process for Reviewing the National 30 Ambient Air Quality Standards. May 21, 2009. Available: 31 http://www.epa.gov/ttn/naaqs/pdfs/N AAQSReviewProcessMemo52109.pdf

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Samet, J. (2009a). Letter from Clean Air Scientific Advisory Committee to the Honorable Lisa P. Jackson, 33 Administrator, US EPA. Consultation on EPA’ s Particulate Matter National Ambient Air Quality 34 Standards: Scope and Methods Plan for Health Risk and Exposure Assessment. May 21, 2009. Available: 35 http://yosemite.epa.gov/sab/sabproduct.nsf/723 FE644C5D758DF852575B D00763A32/$File/EPA36 CASAC-09-009-unsigned.pdf 37

Samet, J. (2009b). Letter from Clean Air Scientific Advisory Committee to the Honorable Lisa P. Jackson, 38 Administrator, US EPA. Consultation on EPA’ s Particulate Matter National Ambient Air Quality 39 Standards: Scope and Methods Plan for Urban Visib ility Impact Assessment. May 21, 2009. Available: 40 http://yosemite.epa.gov/sab/sabproduct.nsf/0F63D 7995F5850D5852575BD0077869C/$File/EPA-CASAC41 09-010-unsigned.pdf 42

Samet, J. (2009c). Letter from Clean Air Scientific Advisory Committee to the Honorable Lisa P. Jackson, 43 Administrator, US EPA. Review of the Risk Assessm ent to Support the Review of the Particulate Matter 44D raft- Do Not Quote or Cite 1-14 June 2010 (PM) Primary National Ambient Air Quality Standard s – External Review Draft (September 2009). 1 November 24, 2009. Available: 2 http://yosemite.epa.gov/sab/sabproduct.nsf/B C1ECC5D539EF72385257678006D5754/$File/EPA3 CASAC-10-003-unsigned.pdf 4

Samet, J. (2009d). Letter from Clean Air Scientific Advisory Committee to the Honorable Lisa P. Jackson, 5 Administrator, US EPA. Review of Particulate Matter Urban-Focused Visibility Assessment (External 6 Review Draft, September 2009). November 24, 2009. Available: 7 http://yosemite.epa.gov/sab/sabproduct.nsf/15872217938041F685257678006A26E3/$File/EPA-CASAC8 10-002-unsigned.pdf 9

Samet, J. (2010a). Letter from Clean Air Scientific Advisory Committee to the Honorable Lisa P. Jackson, 10 Administrator, US EPA. CASAC Review of Quantita tive Health Risk Assessment for Particulate matter – 11 Second External Review Draft (February 2010). April 15, 2010. Available: 12 http://yosemite.epa.gov/sab/sabproduct.nsf/BC4F6E77B6385155852577070002F09F/$File/EPA-CASAC13 10-008-unsigned.pdf 14

Samet, J. (2010b). Letter from Clean Air Scientific Advisory Committee to the Honorable Lisa P. Jackson, 15 Administrator, US EPA. CASAC Review of Par ticulate Matter Urban-Focused Visibility Assessment 16 (Second External Review Draft, January 2010). April 20, 2010. Available: 17 http://yosemite.epa.gov/sab/sabproduct.nsf/0 D5CB76AFE7FA77C8525770D004EED55/$File/EPA18 CASAC-10-009-unsigned.pdf 19

Samet, J. (2010c). Letter from Clean Air Scientific Advisory Committee to the Honorable Lisa P. Jackson, 20 Administrator, US EPA. CASAC Review of Policy Assessment for the Review of the PM NAAQS – First 21 External Revew Draft (March 2010). May 17, 2010. Available: 22 http://yosemite.epa.gov/sab/sabproduct.nsf/264cb1227d55e02c85257402007446a4/E504EE3276D87A9E8 23 525772700647AFB/$File/EPA-CASAC-10-011-unsigned.pdf/. 24

US Department of Health, Education and Welfare (DHEW) . (1969). Air Quality Criteria for Particulate Matter. 25 U.S. Government Printing Office, Washington DC, AP-49. 26

US EPA (2004). Air Quality Criteria for Particulate Matte r. National Center for Envi ronmental Assessment, Office 27 of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711; 28 report no. EPA/600/P-99/002aF and EPA/600/P-99/002bF. October 2004. Available: 29 http://www.epa.gov/ttn/naaqs/standards/pm/s_pm_cr_cd.html 30

US EPA (2005). Review of the National Ambient Air Qua lity Standards for Particulate Matter: Policy Assessment 31 of Scientific and Technical Information, OAQPS Staff Paper. Research Triangle Park, NC 27711: Office 32 of Air Quality Planning and Standa rds; report no. EPA EPA-452/R-05-00 5a. December 2005. Available: 33 http://www.epa.gov/ttn/naaqs/standards/pm/s_pm_cr_sp.html 34

US EPA (2007). Draft Integrated Review Plan for th e National Ambient Air Quality Standards for Particulate 35 matter. National Center for Environmental Assessment and Office of Air Quality Planning and Standards, 36 U.S. Environmental Protection Agency, Research Triangle Park, NC. Report No. EPA 452/P-08-006. 37 Available: http://www.epa.gov/ttn/naaqs/standards/pm/s_pm_2007_pd.html. 38

US EPA (2008a). Integrated Review Plan for the Nationa l Ambient Air Quality Standards for Particulate Matter. 39 National Center for Environmental Assessment and Office of Air Quality Planning and Standards, U.S. 40 Environmental Protection Agency, Research Triangle Park, NC. Report No. EPA 452/R-08-004. March 41 2008. Available at: http://www.epa.gov/ttn/naaqs/standards/pm/s_pm_2007_pd.html

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US EPA (2008b). Integrated Science Assessment for Par ticulate Matter: First External Review Draft. National 43 Center for Environmental Assessment-RTP Division, Office of Air Quality Planning and Standards, 44D raft- Do Not Quote or Cite 1-15 June 2010 Research Triangle Park, NC. EPA/600/R-08/1 39 and 139A. December 2008. Available: 1 http://www.epa.gov/ttn/naaqs/standards/pm/s_pm_2007_isa.html

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US EPA (2009a). Integrated Scien ce Assessment for Particulate Matter: Final Report. National Center for 3 Environmental Assessment-RTP Division, Office of Air Quality Planning and Standards, Research 4 Triangle Park, NC. EPA/600/R-08/139F. December 2009. Available: 5 http://www.epa.gov/ttn/naaqs/standards/pm/s_pm_2007_isa.html

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US EPA (2009b). Integrated Science Assessment for Par ticulate Matter: Second External Review Draft. National 7 Center for Environmental Assessment-RTP Division, Office of Air Quality Planning and Standards, 8 Research Triangle Park, NC. EPA/600/R-08/139B. July 2009. Available: 9 http://www.epa.gov/ttn/naaqs/standards/pm/s_pm_2007_isa.html

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US EPA (2009c). Particulate Matter National Ambient Air Qu ality Standards: Scope and Methods Plan for Health 11 Risk and Exposure Assessment. Office of Air Quality Planning and Standards, U.S. Environmental 12 Protection Agency, Research Triangle Park, NC. EPA-452/P-09-002. February 2009. Available: 13 http://www.epa.gov/ttn/naaqs/standards/pm/s_pm_2007_pd.html

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US EPA (2009d). Particulate Matter National Ambient Air Quality Standards: Scope and Methods Plan for Urban 15 Visibility Impact Assessment. Office of Air Qua lity Planning and Standards, U.S. Environmental 16 Protection Agency, Research Triangle Park, NC. EPA-452/P-09-001. February 2009. Available: 17 http://www.epa.gov/ttn/naaqs/standards/pm/s_pm_2007_pd.html

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US EPA (2009e). Risk Assessment to Support the Re view of the PM Primary National Ambient Air Quality 19 Standards - External Review Draft. Office of Air Qu ality Planning and Standards, U.S. Environmental 20 Protection Agency, Research Triangle Park, NC. EPA-452/P-09-006. September 2009. Available: 21 http://www.epa.gov/ttn/naaqs/standards/pm/s_pm_2007_risk.html

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US EPA (2009f). Particulate Matter Ur ban-Focused Visibility Assessment – Exte rnal Review Draft. Office of Air 23 Quality Planning and Standards, U.S. Environmenta l Protection Agency, Research Triangle Park, NC. 24 EPA-452/P-09-005. September 2009. Available: 25 http://www.epa.gov/ttn/naaqs/standards/pm/s_pm_2007_risk.html

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US EPA (2009g). Policy Assessment for the Review of the Particulate Matter National Ambient Air Quality 27 Standards – Preliminary Draft. Office of Air Qu ality Planning and Standards, U.S. Environmental 28 Protection Agency, Research Triangle Park, NC. EPA-452/P-09-007. September 2009. Available: 29 http://www.epa.gov/ttn/naaqs/standards/pm/s_pm_2007_pa.html

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US EPA (2010a). Quantitative Risk Assessment for Pa rticulate Matter – Final Report. Office of Air Quality 31 Planning and Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC. EPA-452/R32 10-005. June 2010. Available: http://www.epa.gov/ttn/naaqs/standards/pm/s_pm_2007_risk.html

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US EPA (2010b). Particulate Matter Urban-Focused Visi bility Assessment – Final Report. Office of Air Quality 34 Planning and Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC. EPA-452/R35 10-004. June 2010. Available: http://www.epa.gov/ttn/naaqs/standards/pm/s_pm_2007_risk.html

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US EPA (2010c). Policy Assessment for the Review of the Particulate Matter National Ambient Air Quality 37 Standards- First External Review Draft. Office of Ai r Quality Planning and Standards, U.S. Environmental 38 Protection Agency, Research Triangle Park, NC. EPA 452/P-10-003. March 2010. Available: 39 http://www.epa.gov/ttn/naaqs/standards/pm/s_pm_2007_pa.html

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US EPA (2010d). Quantitative Risk Assessment for Partic ulate Matter – Second External Review Draft. Office of 41 Air Quality Planning and Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC. 42 EPA-452/P-10-001. February 2010. Available: 43 http://www.epa.gov/ttn/naaqs/standards/pm/s_pm_2007_risk.html

. 44D raft- Do Not Quote or Cite 1-16 June 2010 US EPA (2010e). Particulate Matter Urban-Focused Visib ility Assessment – Second External Review Draft. Office 1 of Air Quality Planning and Standards, U.S. Enviro nmental Protection Agency, Research Triangle Park, 2 NC. EPA-452/P-10-002. January 2010. Available: 3 http://www.epa.gov/ttn/naaqs/standards/pm/s_pm_2007_risk.html

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### 2 REVIEW OF THE PRIMARY STA NDARDS FOR FINE PARTICLES 1

This chapter presents staff conclusions with re gard to the adequacy of the current suite of 2 primary PM 2.5 standards and the alternative primary st andards for fine particles that are 3 appropriate for consideration in th is review. Our assessment of these issues is framed by a series 4 of key policy-relevant questions, which expand upon those presented at the outset of this review 5 in the IRP. Answers to these questions will in form decisions by the Administrator on whether, 6 and if so how, to revise the current suite of primary fine particle standards. 7
Staff notes that final decisi ons regarding the primary standa rds must draw upon scientific 8 information and analyses about health effects and risks, as well as judgments made about how to 9
deal with the uncertainties that are inherent in the scientific evidence and analyses. Ultimately, 10 the final decisions are largely publ ic health policy judgments. Ou r approach to informing these 11 judgments recognizes that the av ailable health effect s evidence generally reflects a continuum 12 consisting of ambient levels at which scientists generally agree that heal th effects occur through 13 lower levels at which the likelihood and magn itude of the response become increasingly 14
uncertain. 15 Our approach for reviewing the primary stan dards for fine particles is presented in 16 section 2.1. Staff conclusions regarding the ad equacy of the current suite of primary PM 2.5 17 standards are presented in s ection 2.2, focusing on both evidence-based and quantitative risk18 based considerations. Section 2.3 presents our conclusions with respec t to alternative fine 19 particle standards, focusing on each of the basic el ements of the standards: pollutant indicator 20 (section 2.3.1), averaging time (section 2.3.2), fo rm (section 2.3.3), and level (section 2.3.4). 21
Section 2.4 summarizes staff conc lusions on the primary fine particle standards. Key 22
uncertainties and areas for future research and data collection efforts ar e included in section 2.5. 23

2.1 APPROACH 24 Staff’s approach for reviewing the current primary PM 2.5 standards, which involves 25 translating scientific and technical information in to the basis for addressing key policy-relevant 26 questions, takes into considera tion the approaches used in pr evious PM NAAQS reviews and the 27 court’s remand of the primary annual PM 2.5 standard set in 2006. The past and current 28 approaches described below are all based mo st fundamentally on using information from 29 epidemiological studies to inform the selection of PM standards that, in the Administrator’s 30 judgment, protect public health with an adequate margin of safety. Such information can be in 31 the form of air quality di stributions over which health effect associations have been observed, or 32
in the form of concentration-re sponse (C-R) functions that support quantitative risk assessment. 33 However, evidence- and risk-based approaches using information from epidemiological studies 34Draft – Do Not Quote or Cite June 2010 2-2 to inform decisions on PM standards are co mplicated by the recognition that no population 1 threshold, below which it can be concluded with c onfidence that PM-related effects do not occur, 2
can be discerned from the available evidence. As a result, any approach to reaching decisions on 3 what standards are appropriate necessarily re quires judgments about how to translate the 4 information available from the epidemiological st udies into a basis for appropriate standards, 5 which includes consideration of how to weigh th e uncertainties in reported associations across 6 the distributions of PM concentrations in the studies or in quantitative estimates of risk. Such 7 approaches are consistent with setting standards that are neithe r more nor less stringent than 8 necessary, recognizing that a zero-risk st andard is not required by the CAA. 9

2.1.1 Approaches Used in Previous Reviews 10

2.1.1.1 Review Completed in 1997 11

In setting the 1997 primary PM 2.5 annual and 24-hour standards, the Agency relied 12 primarily on an evidence-based approach that focused on epidemiological evidence, especially 13 from short-term exposure studies of fine particle s judged to be the strongest evidence at that 14 time. The EPA did not place much weight on qua ntitative risk estimates from the very limited 15 risk assessment conducted, but did conclude that the risk asse ssment results confirmed the 16 general conclusions drawn from the epidemiol ogical evidence that a serious public health 17 problem was associated with ambient PM levels allowed under the then current PM 10 standards 18 (62 FR 38665/1, July 18, 1997). 19 The EPA considered the epidemiological ev idence and data on air quality relationships 20
to set an annual PM 2.5 standard that was intended to be the “generally controlling” standard; i.e., 21 the primary means of lowering both long- and short-term ambient co ncentrations of PM 2.5
. 1 In 22 conjunction with the annual standard , EPA also established a 24-hour PM 2.5 standard to provide 23 supplemental protection against da ys with high peak concentrati ons, localized “hotspots,” and 24 risks arising from seasonal emissions that mi ght not be well controlled by a national annual 25 standard (62 FR 38669/3). Recogni zing that there are various ways to combine two standards to 26 achieve an appropriate degree of public health protection, such as an approach that only 27 considered short- and long-term exposure evidence, analyses, and standards independently, EPA 28
concluded that the selected a pproach based on a generally cont rolling annual standard was the 29

1 In so doing, EPA noted that because an annual standa rd would focus control prog rams on annual average PM 2.5 concentrations, it would not only control long-term exposu re levels, but would also generally control the overall distribution of 24-hour exposure levels, resulting in fewer and lower 24-hour peak concen trations. Alternatively, a 24-hour standard that focused controls on peak concentrations could also result in lower annual averageconcentrations. Thus, EPA recognized that either standard could provide some degree of protection from both shortand long-term exposures, with the other standard serving to address situations where the daily peaks and annual averages are not consistently correlated (62 FR 38669).Draft – Do Not Quote or Cite June 2010 2-3 most effective and efficient approach. This conclusion was based in part on one of the key 1 observations from the quantitative risk assessmen t that most of the aggregated annual risk 2 associated with short-term exposures through a year results from the large number of days during 3 which the 24-hour average concentrations are in the low- to mid-range, well below the peak 24- 4 hour concentrations. As a result, lowe ring a wide range of ambient 24-hour PM 2.5 concentrations 5 by means of a generally controlli ng annual standard, as opposed to focusing on control of peak 6 24-hour concentrations, was determin ed to be the most effective a nd efficient way to reduce total 7 population risk (62 FR 38670 to 38671). 8 In setting the level of the annual standard in 1997, EPA first determined a level for the 9 annual standard based on the short-term exposur e studies, and then considered whether the key 10 long-term exposure studies suggested the need for a lower level. While recognizing that health 11 effects may occur over the full ra nge of concentrations observed in the studies, EPA concluded 12 that the strongest evidence for short-term PM 2.5 exposure-related effects occurs at concentrations 13 near the long-term (e.g., annual) average in the s hort-term exposure studies. The EPA selected a 14
level for the annual standard at or below the l ong-term mean concentratio ns in studies providing 15 evidence of associations with short-term exposur es, placing greatest weight on those short-term 16 exposure studies that reported cl early statistically significant a ssociations with mortality and 17 morbidity effects (62 FR 38676/1). Furt her consideration of the average PM 2.5 concentrations 18 across the cities in the key long-term exposure st udies of mortality and respiratory effects in 19 children did not provide a basis for establishing a lower annual standard level. Because the 20
annual standard level selected was below the range of annual concentr ations most strongly 21 associated with both short- and long-term exposur e effects at that time, and because even small 22 changes in annual means in this concentration range could make a significant difference in 23
overall risk reduction and total population exposures, EPA conclude d that this standard would 24 provide an adequate margin of safety against effects observed in these epidemiological studies 25 (62 FR 68676/3). 26
The selection of the level of the annual standard was done in conjunction with having 27
first selected the form of the annual standard to be based on th e concentration measured at a 28 single monitor sited to represent community-wid e air quality, or a va lue resulting from an 29 average of measurements from multiple commun ity-wide air quality monitoring sites that met 30 specific criteria and constraints (“spatial averaging”). This decision emphasized consistency 31 with the types of air quality measurements that were used in the relevant epidemiological studies. 32 In reaching this decision, EPA recognized the im portance of ensuring that spatial averaging 33 would not result in inequities in th e level of protection provided by the PM 2.5 standards in some 34 areas. Because the annual standard, defined in terms of single or averaged community-wide air 35 quality monitoring sites, could not be expected to offer an adequate margin of safety against the 36Draft – Do Not Quote or Cite June 2010 2-4 effects of all potential short-term exposures in areas with strong local or seasonal sources that 1 could not be directly evaluated in the epidemio logical studies, EPA set the level of the 24-hour 2 standard to supplement the control afforded by the annual standard based on air quality 3 relationships between annual and 24-hour concentrations. This appr oach was intended to 4 provide an adequate margin of safety against in frequent or isolated peak concentrations that 5
could occur in areas that attain the annual standard (62 FR 38677). 6

2.1.1.2 Review Completed in 2006 7

In 2006, EPA used a different evidence-based a pproach to assess the appropriateness of 8
the levels of the 24-hour and annual PM 2.5 standards. Based on an expanded body of 9 epidemiological evidence that was stronger and mo re robust, including both short- and long-term 10 exposure studies, the Administrator decided that using evidence of eff ects associated with 11 periods of exposure that were most closely matc hed to the averaging time of each standard was 12 the most appropriate public health policy approa ch for evaluating the scientific evidence to 13 inform selecting the level of each standard. T hus, the Administrator relied upon evidence from 14 the short-term exposure studies as the principa l basis for selecting th e level of the 24-hour PM 2.5 15 standard that would protect ag ainst effects associated with short-term exposures. The 16 Administrator relied upon evidence from long-term exposure studies as the principal basis for 17 selecting the level of the annual PM 2.5 standard that would protect ag ainst effects associated with 18 long-term exposures. 19 With respect to quantitative ri sk-based considerations, the Ad ministrator determined that 20 the estimates of risks likely to rema in upon attainment of the 1997 suite of PM 2.5 standards were 21
indicative of risks that could be reasonably judged important from a public health perspective, 22 and, thus, supported revision of the standards. However, the Administrator judged that the 23 quantitative risk assessment had important limitati ons and did not provide an appropriate basis 24 for selecting the levels of the revised standards (71 FR 61174/1-2). Th e Administrator more 25 heavily weighed the implications of the uncerta inties associated with the quantitative risk 26 assessment than the Clean Air Scientific Advisory Committee (CASAC) did in their comments 27 on the proposed rulemaking, where CASAC stated, “[ w]hile the risk assessment is subject to 28 uncertainties, most of the PM Panel found EPA’s ri sk assessment to be of sufficient quality to 29 inform its recommendations...The risk analyses i ndicated that the uncertainties would increase 30 rapidly below an annual level of 13 μg/m 3 – and that was the basis for the PM Panel’s 31 recommendation of 13 μg/m 3 as the lower bound for the annual PM 2.5 standard level” 32 (Henderson, 2006, p.3). 33 With regard to the primary annual PM 2.5 standard, the Administrator placed the greatest 34 weight on the long-term means of the concentrations associated with mortality effects in two key 35Draft – Do Not Quote or Cite June 2010 2-5 long-term exposure studies in the record, the Am erican Cancer Society (ACS) and Harvard Six 1 Cities studies (71 FR at 61172 to 61177). Important validation and reanalyses of the original 2 studies provided “evidence of ge nerally robust associa tions and provide[d] a basis for greater 3 confidence in the reported asso ciations than in the last re view,” and the extended ACS study 4 provided “new evidence of mortality related to lung cancer and further substantiate[d] the 5 statistically significant associations with cardi orespiratory-related mort ality observed in the 6 original studies” (71 FR 61172/1-2) . The Administrator also rec ognized the availability of long7 term exposure studies that provided evidence of respiratory morbidity, including changes in lung 8 function measurements and decreased growth in lung function as reported in the 24-Cities study 9
and the Southern California Children’s Health Study, respectively (Dockery et al. 1996, 10 Gauderman et al. 2002). In retaining the level of the annual standard at 15 μg/m 3 , the 11
Administrator selected a le vel that was “appreciably below” the long-term average 12 concentrations reported in the ke y long-term mortality studies and “basically at the same level” 13 as the long-term average concentrations in the long-term respiratory morbidity studies. In the 14 judgment of the Administrator, th e two long-term respiratory morb idity studies did “not warrant 15 setting a lower level for the annual standard than the level warranted based on the key mortality 16 studies” (71 FR 61176/3). 17 In considering the form of the primary annual PM 2.5 standard, the Administrator 18 strengthened the standard by ti ghtening the criteria for use of spatial averaging. Based on a 19 much larger set of PM 2.5 air quality data than was availabl e in the 1997 review , analyses were 20 conducted concerning the potential for dispropo rtionate impacts on pot entially vulnerable 21 subpopulations. These analyses sugg ested that “the highest concentr ations in an area tend to be 22
measured at monitors located in areas wher e the surrounding population [was] more likely to 23 have lower education and income levels, and hi gher percentages of mi nority populations” (71 FR 24 61166/2, see also US EPA, 2005, section 5.3.6.1; Sc hmidt et al., 2005, Attachment A/Analysis 25 7). 2 26 In revising the level of the 24-hour PM 2.5 standard from 65 μg/m 3 to 35 μg/m 3 , the 27 Administrator placed greatest weight on the much expanded body of epidemiological evidence 28
from U.S. and Canadian short-term PM 2.5 exposure studies with more reliable air quality data 29 that was reanalyzed to address statistical mode ling issues. The Administ rator recognized that 30

2 As summarized in footnote 29 at 71 FR 61166/2, the 2004 AQCD noted that some epidemiologic studies, most notably the ACS study of associations between long-term PM 2.5 exposure and mortality, reported larger effect estimates in the cohort subgroup with lower education levels (US EPA, 2004, p 8-103). The 2004 AQCD also noted that lower education level may be a ma rker for lower socioeconomic status (S ES) that may be related to increased vulnerability to the effects of fine particle exposures, for ex ample, as a result of greater exposure from proximity to sources such as roadways and industry, as well as other fa ctors such as poorer health status and limited access to health care (US EPA, 2004, section 9.2.4.5).Draft – Do Not Quote or Cite June 2010 2-6 these studies provided no evidence of clear effect thresholds or lowest-obs erved effect levels. 1 Nonetheless, in focusing on the 98 th percentile air quality valu es in these studies, the 2 Administrator sought to establish a standard level that would requi re improvements in air quality 3 generally in areas in which the distribu tion of daily short-term exposure to PM 2.5 could 4 reasonably be expected to be associated with serious health effects. The Administrator 5 concluded that although future ai r quality improvement strategies in any particular area were not 6 yet defined, most such strategies were likely to move a broad distribution of PM 2.5 air quality 7 values in an area lower, resulting in reductio ns in risk associated with exposures to PM 2.5 levels 8 across a wide range of concentrations and not just at the 98 th percentile concentrations (71 FR 9 61168/3). 10

2.1.2 Remand of Primary Annual PM 2.5 Standard 11

As noted above in section 1.2.4, several parties filed peti tions for review following 12 promulgation of the revised PM NAAQS in 2006. These petitions challenged several aspects of 13 the final rule including the selection of the level of the primary PM 2.5 annual standard. More 14 specifically, petitioners repres enting public health and enviro nmental groups (American Lung 15 Association, Environmental Defense, and the National Parks Conservation Association) and 16 several states and state agencies argued that th e decision to retain the level of the annual PM 2.5 17 standard at 15 μg/m 3 was “arbitrary, capricious, an abuse of discretion, or otherwise not in 18
accordance with law.” 42 U.S.C. 7 607(d)(9). The primary 24-hour PM 2.5 standard was not 19 challenged by any of the litigants and, thus, not considered in the c ourt’s review and final 20
decision. 21 On judicial review, the D.C. Ci rcuit remanded the primary annual PM 2.5 NAAQS to EPA 22 because the Agency failed to adequately explai n why the annual standard provided the requisite 23 protection from both short- and l ong-term exposures to fine particles including protection for 24 susceptible populations. American Farm Bureau Federation v. EPA, 559 F. 3d 512 (D.C. Cir. 25 2009). With respect to human hea lth protection from short-term PM 2.5 exposures, the court 26 considered the different approaches used by EPA in the 1997 and 2006 PM NAAQS decisions, 27
as summarized above. The court found that EP A failed to adequately explain why a 24-hour 28

PM 2.5 standard by itself would provide the protecti on needed from short-term exposures and 29
remanded the annual PM 2.5 standard to EPA “for further consid eration of whether it is set at a 30 level requisite to protec t the public health while providing an adequate margin of safety from the 31 risk of short-term exposures to PM 2.5 .” American Farm Bureau Federation, 559 F. 3d at 520-24. 32 With respect to protection from long-term expos ure to fine particles, the court found that 33 EPA failed to adequately explain how the primary annual PM 2.5 standard provided an adequate 34 margin of safety for children and other sus ceptible populations. The court found that EPA did 35Draft – Do Not Quote or Cite June 2010 2-7 not provide a reasonable explan ation of why certain morbidit y studies, including a study of 1 children in Southern California showing lung damage associated with long-term PM 2.5 exposure 2 (Gauderman et.al, 2000) and a multi-city study (24-Cities Study) evaluating decreased lung 3 function in children associated with long-term PM 2.5 exposures (Raizenne et al., 1996), did not 4 call for a more stringent annual PM 2.5 standard. Id. at 522-23. Speci fically, the court found that: 5
6 EPA was unreasonably confident that, even though it relied so lely upon long-term 7 mortality studies, the revised standard would provide an adequate margin of safety with 8 respect to morbidity among children. Notably absent from the final rule, moreover, is 9 any indication of how the standard will adequate ly reduce risk to the elderly or to those 10 with certain heart or lung diseases despite (a) the EPA’s determination in its proposed 11 rule that those subpopulations ar e at greater risk from exposur e to fine particles and (b) 12 the evidence in the record supporting that determination. Id. at 525. 13 14 In remanding the primary annual standard for reconsideration, the c ourt did not vacate the 15
annual standard. Id. at 530. 16

2.1.3 Current Approach 17

This review is founded on an assessment of a much expanded body of epidemiological 18 evidence, more extensive air quality data a nd analyses, and a more comprehensive risk 19
assessment relative to the information available in past reviews, as presented in the ISA and RA. 20 As a result, staff’s approach to reaching conclusi ons about the adequacy of the current suite of 21

PM 2.5 standards and potential altern ative standards that are appr opriate for consideration is 22 broader and more integrative than in past review s. Our approach also reflects consideration of 23 the issues raised by the court in its remand of the primary annual PM 2.5 standard, since decisions 24 made in this review, and the rationales for thos e decisions, will comprise the Agency’s response 25
to the remand. 26 Our approach in this second draft PA takes into account both evidence-based and risk27 based considerations, and the uncertainties related to both types of information, as well as advice 28 from CASAC and public comments on the first draft PA. In so doing, we are seeking to provide 29 as broad an array of policy options as is s upportable by the available information, recognizing 30 that the selection of a specific approach to reaching final decisions on the primary PM 2.5 31 standards will reflect the judgmen ts of the Administrator as to what weight to place on the 32 various approaches and types of info rmation presented in the final PA. 33 We believe it is most appropriate to consider the protection against PM 2.5 -related 34 mortality and morbidity effects, associated with both long- and s hort-term exposures, afforded by 35
the annual and 24-hour standards ta ken together, as was done in th e 1997 review, rather than to 36 consider each standard separate ly, as was done in the 2006 review . This approach reflects the 37Draft – Do Not Quote or Cite June 2010 2-8 recognition that changes in PM 2.5 air quality designed to meet an annual standard would likely 1 result not only in lower annual average concentr ations but also in fewer and lower peak 24-hour 2 concentrations. It also reflects the recogniti on that setting the annual standard to be the 3 “generally controlling” standa rd, and setting the 24-hour stan dard to provide supplemental 4 protection, continues to be seen as the most effective and effici ent way to reduce total population 5 risk associated with both long- and short-term e xposures and provide requis ite protection in areas 6 across the country. While we r ecognize that changes designed to meet a 24-hour standard would 7 result not only in fewer and lower peak 24-hour concentrations but also in lower annual average 8 concentrations, we note that simulated changes in annual average concentra tions associated with 9 just meeting alternative 24-hour standards are highly se nsitive to how air quality changes are 10
simulated and are more uncertain and variable across areas. The extent to which these two 11
standards are interrelated in any given area depends in large pa rt on the relative levels of the 12 standards, the peak-to-mean ratios that character ize air quality patterns in an area, and whether 13 changes in air quality designed to meet a given suite of standards are likely to be of a more 14 regional or more localized nature. 15 Our consideration of the protection afforded by the current and alternative suites of 16
standards focuses on PM 2.5 -related health effects associated with long-term exposures, for which 17 quantitative estimates of risks to public health are appreciably la rger, and also considers effects 18 and estimated risks associated with short-term exposures. In both cases, we place greatest 19 weight on associations that have been judged in the ISA to be causal and likely causal, while also 20 considering associations judged to be suggestive of a causal relati onship or that focus on specific 21 susceptible populations. We focu s on studies conducted in the U. S. and Canada, as studies in 22 other countries reflect air quality and exposure pa tterns that are not nece ssarily typical of the 23 U.S., 3 and place relatively greater weight on statistically signifi cant associations that yield 24 relatively more precise effect estimates and th at are judged to be r obust to confounding by other 25 air pollutants. In the case of short-term e xposure studies, we place greatest weight on large 26 multi-city studies, while also considering associations in single-city studies. 27 In translating information from epidemiologi cal studies into the basis for reaching staff 28 conclusions on the adequacy of the current suite of standards (section 2.2), we have considered a 29 number of factors. As an initial matter, we ha ve considered the extent to which the currently 30 available evidence and related uncertainties strengthens or calls into question conclusions from 31 the last review regarding associa tions between fine particle expos ures and health effects. We 32 have also considered evidence on susceptible populations and poten tial impacts on such 33 populations. Further, we have explored the extent to which PM 2.5 -related health effects have 34

3 Nonetheless, we recognize the importance of all studies, in cluding international studies, in the ISA’s assessment of the weight of the evidence that informs causality determinations.Draft – Do Not Quote or Cite June 2010 2-9 been observed in areas where air quality distribu tions extend to lower levels than previously 1 reported or in areas that would likely meet the curre nt suite of standards. 2 In translating information from epidemiologi cal studies into the basis for reaching staff 3
conclusions on alternative standa rd levels for consideration (s ection 2.3.4), we have explored 4 various approaches that reflect the absence of di scernible thresholds in the C-R functions from 5 long- and short-term exposure studies. In so doing, we recognize that ther e is no single criterion 6 that comprises the “correct” approach, but rather there are various approaches that are reasonable 7 to consider. Identifying the implications of various approaches in re aching conclusions on the 8 range of alternative standard le vels that is appropriate to co nsider can help inform decision 9 making, which will necessarily also take into account the limitations and uncertainties in the 10 evidence and public health policy ju dgments as to the degree of h ealth protection that is to be 11
achieved. 12 In reaching staff conclu sions on the range of annual standard levels that is appropriate to 13 consider in setting a generally controlling annua l standard intended to provide protection from 14 effects associated with long-and short-term exposures, we have explored two types of 15 approaches. One such approach looks directly at confidence bounds on the C-R relationships 16 from both long- and short-term exposure studies. The other approach is based on the use of 17 statistical metrics that characterize air quality distributions from multi-city studies. We 18 recognize that these two types of approaches are intrinsically related, since C-R functions are 19 most certain across a concentration range with the greatest data density, in which the bulk of the 20
data exist. 21 In considering the first type of approach, we have explored the extent to which analyses 22 characterizing confidence bounds on C-R relationships have been published for studies of health 23 effects associated with long- or short-term exposures to PM 2.5 . Such analyses could potentially 24
be used to characterize a concentration be low which uncertainty in a C-R relationship 25 substantially increases or is judged to be indi cative of an unacceptable degree of uncertainty 26
about the existence of a c ontinuing C-R relationship. 27 In considering statistical air quality metrics, we first re cognize that there are two air 28 quality distributions that are rele vant to consider. One is the di stribution based on concentrations 29 averaged across ambient monitors within each area included in a given study, which we refer to 30 as a composite monitor distribution. This is the ai r quality data typically used in analyses of C-R 31 relationships presented in epidemiological studi es of both long- and short-term exposures, in 32 both multi- and single-city studies. The second relevant air quality distribution is based on 33
concentrations measured at the monitor within ea ch area that records the highest concentration. 34
This maximum monitor distribution is relevant becau se this is the distribution that is generally 35 used to determine whether a given standard is met in an area, and to determine the extent to 36Draft – Do Not Quote or Cite June 2010 2-10 which ambient PM 2.5 concentrations need to be reduced in order to bring an area into attainment 1 with the standard. For composite monitor di stributions, we have compiled distributional 2
statistics drawn from multi-cit y studies, as supplemented by information obtained from study 3
authors. For maximum monitor distributions, we were able to obtain information for a much 4 more limited set of studies from EPA’s public air quality data base, the Air Quality System 5 (AQS). 4 6 More specifically, to the extent available, we have compiled data for long- and short-term 7 exposure multi-city studies on the long-term mean PM 2.5 concentration over the time period of 8 each study, as well as the standard deviation 5 and lower percentiles of the distribution (e.g., 25 th 9
and 10 th percentiles). We have explored the implica tions of considering th ese various air quality 10 metrics as a basis for reaching st aff conclusions as to the rang e of concentrations that is 11 appropriate to consider for alternative annual st andard levels. This approach also includes a 12
broader consideration of uncertainties related to the C-R relationships from long- and short-term 13 exposure multi-city studies, most notably unc ertainties related to our currently limited 14 understanding of the heterogeneity of relative ri sk estimates in areas across the country, with 15 may be attributed in part to th e potential for different components within the mix of ambient fine 16 particles to differentially contri bute to health effects observed in the studies and to exposure17
related factors. 18 In reaching staff conclusions on alternative 24-hour standard levels that are appropriate 19 to consider in setting a 24-hour standard in tended to supplement the protection afforded by 20 potential alternative annual standards, we ha ve focused on comparing 24-hour and annual air 21 quality statistics for areas across the U.S. Consistent with the aim of the approach used in 1997, 22 such a standard would be intended to provide supplemental protection against the effects of 23
short-term PM 2.5 exposures, especially in areas with high peak-to-mean ratios, possibly 24 associated with strong local or seas onal sources, or for potential PM 2.5 -related effects that may be 25 associated with shorter-than-daily exposure peri ods. By considering information on peak-to26 mean air quality ratios, we reach conclusions as to the level of a 24-hour standard would be 27 appropriate to consider for this purpose. 28
Based on the evidence-based considerations outlined above, we then develop integrated 29 conclusions with regard to alternative suites of standards, including both annual and 24-hour 30 standards that we believe are appropriate for cons ideration in this review based on the currently 31 available evidence and air quality information. In so doing, we discuss the roles that each 32 standard might be expected to play in the protect ion afforded by alternative suites of standards. 33

4 Focusing on multi-city studies, AQS data was available from 1999 and onwards.
5 A range of one standard deviation around the mean represents approximately 68% of normally distributed data, and below the mean falls between the 25 th and 10 th percentiles.Draft – Do Not Quote or Cite June 2010 2-11 Beyond these evidence-based considerations, we also consider the quantitative risk 1 estimates and the key observations presented in the RA. This assessment included an evaluation 2 of 15 urban case study areas and estimated risk associated with a number of health endpoints 3 associated with long-term and short-term PM 2.5 exposures (US EPA, 2010a). As part of our risk4 based considerations, we have consider ed estimates of the magnitude of PM 2.5 -related risks 5 associated with recent air quality levels and air quality simulated to just meet the current and 6 alternative suites of standards using alternat ive simulation approaches. We have also 7
characterized the risk reductions , relative to the risks remaini ng upon just meeting the current 8 standards, associated with just meeting alternative suit es of standards. In so doing, we recognize 9
the uncertainties inherent in such risk estimates , and have taken such uncertainties into account 10 by considering the sensitivity of the “core” risk estimates to alte rnative assumptions and methods 11 likely to have substantial impact on the estimates. In addition, we have conducted additional 12 analyses to characterize the repr esentativeness of the urban study areas within a broader national 13
context. We have considered this risk-based information to help inform our conclusions on the 14 adequacy of the current suite of standards, poten tial alternative suites of standards that are 15 appropriate for consideration in this review, and on the roles that th e annual and 24-hour 16 standards may play in affording protection against effects related to both long- and short-term 17

PM 2.5 exposures. 18 Staff conclusions reflect our understanding of both evidence-based and risk-based 19
considerations to inform two ove rarching questions rela ted to: (1) the adequacy of the current 20
suite of PM 2.5 standards and (2) potential alte rnative standards for consider ation in this review to 21 provide appropriate protection from the effect s associated with both long- and short-term 22 exposures to fine particles. In addressing these broad que stions, we have organized the 23 discussions below around a series of more specifi c questions reflecting different aspects of each 24 overarching question. When evaluating the health protection afforded by the current or any 25
alternative suites of standards cons idered, we have taken into acc ount the four basic elements of 26 the NAAQS (e.g., indicator, averaging time, form, and level). Figure 2- 1 provides an overview 27 of the policy-relevant questions that frame our review, as discussed more fully below. 28 We believe that the approach outlined a bove, when presented in the final PA, will 29 provide a comprehensive basis to help inform the judgments required of the Administrator in 30 reaching decisions about the current and potential alternative primary PM 2.5 standards and in 31 responding to the remand of the 2006 annual PM 2.5 standard. 32Figure 2-1. Overview of Appr oach for Review of Primary PM 2.5 Standards

Evidence-based Considerations  Does currently available evidence and related uncertainties strengthen or call into question nature of associations?  Expanded understanding of susceptible populations?  Effects at lower concentrations then previously seen or in areas that would likely meet current standards? Risk-based Considerations  Nature, magnitude, and uncertainties of estimated risks remaining upon just meeting the current suite of standards?  Roles of annual and 24-hour standards; annual standard as “generally controlling” standard?  Importance of remaining risks from public health perspective?

Alternative Suites of Standards Supported by Current Information?

Indicator  PM 2.5 indicator?  Other indicators? • Ultrafine particles? • Components? Averaging Times  Annual and 24-hour?  Other averaging times? • Sub-daily exposures? • Seasonal exposures?

Levels  For a generally controlling annual standard?  For a supplemental 24-hour standard?

Evidence-based Considerations  Epidemiological and air quality data •Relative weight placed on information? •Confidence bounds around C-R relationships? •Statistical air quality metrics? •Peak-to-mean ratios? Forms  Annual standard: spatial averaging?  24-hour standard: 98 th or 99 th percentiles? Support for retaining current

suite of PM 2.5 standards

Alternative suites of standards for consideration YES NO Adequacy of Current Suite of PM 2.5 Standards?

Does information call into question adequacy of current suite of PM 2.5 standards?

Risk-based Considerations

 Nature, magnitude, and uncertainties of estimated risks remaining upon just meeting alternative standards? •Alternative annual standards? •Alternative 24-hour standards?  Confidence in risk estimates?Draft – Do Not Quote or Cite June 2010 2-13 2.2 ADEQUACY OF CURRENT STANDARDS 1 In considering the adequacy of the current suite of PM 2.5 standards, staff addresses the 2 following overarching question: 3

Does the currently available scientific evidence and risk-based information, as reflected in 4 the ISA and RA, support or call into question the adequacy of the protection afforded by 5 the current suite of fine particle standards? 6 To inform the answer to this broad ques tion, we address a series of more specific 7 questions to aid in considering the currently availa ble scientific evidence a nd the results of recent 8 quantitative risk analyses in a pol icy-relevant context, as discu ssed below. In considering the 9
scientific and technical informa tion, we reflect upon both the info rmation available in the last 10
review and information that is ne wly available since the last revi ew as assessed and presented in 11 the ISA and the RA (US EPA, 2009a; US EPA, 2010a). 12

2.2.1 Evidence-based Considerations 13 Our review of the adequacy of the current suite of PM 2.5 primary standards begins by 14 considering the strength of the ev idence, susceptible populations, a nd the air quality distributions 15
over which health effects asso ciations have been reported. 16

 To what extent does the currently available scientific evidence and related uncertainties 17 strengthen or call into question evidence of as sociations between ambient fine particle 18 exposures and health effects? 19 In considering the strength of the associati ons between long- and short-term exposures to 20

PM 2.5 and health effects, we note that in the last review EPA concluded that there was “strong 21 epidemiological evidence” for PM 2.5 linking long-term exposures with cardiovascular and lung 22 cancer mortality and respiratory morbidity and short-term exposures with cardiovascular and 23 respiratory mortality and morbidity (US EPA, 2004, p. 9-46; US EPA, 2005, p. 5-4). Overall, 24 the epidemiological evidence supported “likely causal associations” between PM 2.5 and both 25 mortality and morbidity from cardiovascular an d respiratory diseases, based on “an assessment 26 of strength, robustness, a nd consistency in results” (US EPA, 2004, p. 9-48). 27 In looking across the extensive new scientific evidence available in this review, our 28 overall understanding of health effects associated with fine par ticle exposures has been greatly 29 expanded. The currently available evidence is st ronger in comparison to evidence available in 30
the last review because of its breadth and the subs tantiation of previously observed health effects 31 (US EPA, 2009a, section 2.3.1). A number of larg e multi-city epidemiological studies have been 32 conducted throughout the U.S. including extended an alyses of studies that were important to 33 inform decisionmaking in the last review. Thes e studies have reported c onsistent increases in 34Draft – Do Not Quote or Cite June 2010 2-14 morbidity and/or mortality related to ambient PM 2.5 concentrations, with the strongest evidence 1 reported for cardiovascular-related effects. In addition, the findings of new toxicological and 2 controlled human exposure studies provide stro nger support for a number of potential biologic 3 mechanisms or pathways for PM-related cardiova scular and respiratory effects (US EPA, 2009a, 4 chapter 5; Figures 5-4 and 5-5). In summary, th e ISA concludes, “[t]he new evidence ... greatly 5 expands upon the evidence availa ble in the 2004 PM AQCD particul arly in providing greater 6 understanding of the underlying mechanisms for PM 2.5 induced cardiovascular and respiratory 7 effects for both short- and long-term exposures” (US EPA, 2009a, p. 2-17). 8 With regard to causal inferences described in the ISA, we note that since the last review 9 EPA has developed a more formal framework fo r reaching causal determinations that draws 10 upon the assessment and integration of evidence fr om across epidemiological, controlled human 11 exposure, and toxicological studi es, and the related uncertainties, that ultimately influence our 12 understanding of the evidence (US EPA, 2009a, sec tion 1.5). This framework employs a five13 level hierarchy that classifies the overall wei ght of evidence and causality using the following 14 categorizations: causal relationship, likely to be a causal relationship, suggestive of a causal 15 relationship, inadequate to infer a causal relati onship, and not likely to be a causal relationship 16 (US EPA, 2009a, Table 1-3). 17 Using this causal framework, the ISA conclude s that the collective evidence is largely 18 consistent with past studies and substantially strengthens what was known in the last review to 19
reach the conclusion that a causal relationship exists between both long- and short-term 20 exposures to PM 2.5 and mortality and cardiovascular eff ects including cardiovascular-related 21 mortality. The ISA also conc ludes that the collective ev idence continues to support likely causal 22 associations between long- and short-term PM 2.5 exposures and respiratory effects, including 23 respiratory-related mortality. Further, th e ISA concludes that available evidence is suggestive of 24 a causal relationship between long-term PM 2.5 exposures and other health effects, including 25 developmental and reproductive e ffects (e.g., low birth weight) and carcinogenic, mutagenic, and 26 genotoxic effects (e.g., lung can cer mortality). Table 2- 1 summarizes these causal 27 determinations (US EPA, 2009a, sections 2.3.1 and 2.6). 28Draft – Do Not Quote or Cite June 2010 2-15 Table 2-1. Summary of Causal Determinations for PM 2.5 1

Exposure Duration Outcome Causality Determination Mortality Causal

Cardiovascular Effects Causal
Respiratory Effects Li kely to be Causal
Reproductive and Developmental Effects Suggestive Long-term

Cancer, Mutagenicity, Genotoxicity Effects Suggestive
Mortality Causal

Cardiovascular Effects Causal
Respiratory Effects Li kely to be Causal Short-term

Central Nervous System Effects Inadequate
Source: adapted from US EPA, 2009, Table 2-6. 2
Health Effects Associated with Long-term PM 2.5 Exposure 3
With regard to mortality , the ISA concludes that newly available evidence significantly 4 strengthens the link between long-term exposure to PM 2.5 and mortality, while providing 5 indications that the magnitude of the PM 2.5 -mortality association may be larger than previously 6 estimated (US EPA, 2009a, sections 7.2.10, 7.2.11, 7.6.1; Figures 7-6 and 7-7). A number of 7 large U.S. cohort studies have b een published since the last review , including extended analyses 8 of the American Cancer Society (ACS) and Harv ard Six Cities studies (US EPA, 2009a, pp 7-84 9 to 7-85; Figure 7-6; Krewski et al., 2009; Pope et al., 2004; Jerrett et al., 2005; Laden et al., 10 2006). In addition, new long-term PM 2.5 exposure studies evaluating mortality impacts in 11 additional cohorts are now available (US EPA, 2009a, section 7.6). For example, the Women’s 12 Health Initiative (WHI) reported effects of PM 2.5 on cardiovascular-relate d mortality in post13 menopausal women with no previous history of cardiac disease (Miller et al., 2007), while 14 multiple studies observed PM 2.5 -associated mortality among older adults using Medicare data 15 (Eftim et al., 2008; Zeger et al., 2007, 2008). Collectively, these new studies, along with 16 evidence available in the last review, provide us with consistent a nd stronger evidence of 17 associations between long-term exposure to PM 2.5 and mortality (U.S. EPA, 2009a, sections 2.3.1 18 and 7.6). 19
The strength of the causal association between long-term PM 2.5 exposure and mortality 20 also builds upon new studies providing evidence of improvement in community health following 21Draft – Do Not Quote or Cite June 2010 2-16 reductions in ambient fine particles. Pope et al. (2009) have documented the population health 1 benefits of reducing ambient air pollution by correlating past reductions in ambient PM 2.5 2 concentrations with increased life expectancy. These investigators re port that reductions in 3 ambient fine particles during the 1980s and 1990s account for as much as 15 percent of the 4 overall improvement in life expectancy in 51 U. S. metropolitan areas, with the fine particle 5 reductions reported to be associated with an es timated increase in mean life expectancy of 6 approximately 5 to 9 months (US EPA, 2009a, p. 7- 95; Pope et al., 2009). An extended analysis 7 of the Harvard Six Cities study found that as cities cleaned up their air, lo cations with the largest 8
reductions in PM 2.5 saw the largest improvements in reduced mortality rates, while those with the 9
smallest decreases in PM 2.5 concentrations saw the smallest improvements (Laden et al., 2006). 10 Another extended follow-up to the Harvard Six Cities study investigated the delay between 11 changes in ambient PM 2.5 concentrations and changes in mo rtality (Schwartz et al., 2008) and 12 reported that the effects of changes in PM 2.5 were seen within the 2 years prior to death (US 13 EPA, 2009a, p. 7-92; Figure 7-9). 14 With regard to cardiovascular effects, several new studies have examined the association 15
between cardiovascular effects and long-term PM 2.5 exposures in multi-city studies conducted in 16 the U.S. and Europe. The ISA concludes that the strongest evidence comes from recent studies 17 investigating cardiovascular-related mortality . This includes evidence from a number of large, 18 multi-city U.S. long-term cohort studies includi ng extended follow-up analyses of the ACS and 19 Harvard Six Cities studies, as well as the WHI (US EPA, 2009a, sections 7.2.10 and 7.6.1; 20 Krewski et al., 2009; Pope et al., 2004; Laden et al., 2006; Miller et al., 2007). Pope et al. (2004) 21 reported a positive association between mortality and long-term PM 2.5 exposure for a number of 22 specific cardiovascular diseases, including isch emic heart disease (IHD), dysrhythmia, heart 23 failure, and cardiac arrest (US EPA, 2009a, p. 7-84; Figure 7-7). Krewski et al. (2009) provides 24
further evidence for IHD-related mort ality associated with long-term PM 2.5 exposure (US EPA, 25 2009a, p. 7-84, Figure 7-7). 26 With regard to cardiovascular-related morbidit y associated with long-term PM 2.5 27 exposures, studies were not availa ble in the last review. Recent studies, however, have provided 28 new evidence linking long-term exposure to PM 2.5 with cardiovascular outcomes that has 29 “expanded upon the continuum of effects ranging from the more subtle subclinical measures to 30 cardiopulmonary mortality” (US EPA, 2009a, p. 2-17) . In the current re view, studies are now 31
available that evaluated a number of endpoints ranging from subtle indicators of cardiovascular 32
health to serious clinical events associated with coronary heart disease (CHD) and 33 cerebrovascular disease (CVD) , including myocardial infarction (MI), coronary artery 34 revascularization (e.g., bypass graf t, angioplasty, stent, atherect omy), congestive heart failure 35 (CHF), and stroke. The most significant new evidence comes from the WHI study which 36Draft – Do Not Quote or Cite June 2010 2-17 provides evidence of nonfatal cardiovascular even ts including both coronary and cerebrovascular 1 events (Miller et al., 2007; US EPA, 2009a, sections 7.2.9 and 7.6.1). Toxicological studies 2 provide supportive evidence that the cardiovascular morbidity effects observed in long-term 3 exposure epidemiological studies are biologically plausible and cohere nt with studies of 4 cardiovascular-related mortality as well as with studies of cardiovascular-related effects 5 associated with short-term exposures to PM 2.5 , as described below (US EPA, 2009a, p 7-19). 6 With regard to respiratory effects , the ISA concludes that ex tended analyses of studies 7
available in the last review as well as new epidemiological studies conducted in the U.S. and 8 abroad provide stronger evidence of respiratory-related morbidity associated with long-term 9

PM 2.5 exposure. The strongest evidence for respiratory- related effects availabl e in this review is 10 from studies that evaluated decrements in lung function growth, increase d respiratory symptoms, 11 and asthma development (U.S. EPA, 2009a, sections 2.3.1.2, 7.3.1.1, and 7.3.2.1). 6 Specifically, 12 extended analyses of the Southern California Children’s Health Study (CHS) provided evidence 13 that clinically important deficits in lung function 7 associated with long-term exposure to PM 2.5 14 persisted into early adulthood (U.S., EPA, 2009a , p. 7-27; Gauderman et al., 2004). Additional 15 analyses of the CHS cohort reported an association between long-term PM 2.5 exposure and 16 bronchitic symptoms (US EPA, 2009a, p. 7-24; McConnell et al., 2003) and a strong modifying 17 effect on the association between lung functi on and asthma incidence (US EPA, 2009, 7-25; 18 Islam et al., 2007). The outcomes observed in th ese more recent reports from the Southern 19 California CHS, including evaluation of a br oader range of endpoints and longer follow-up 20 periods, were larger in magnitude and more precise. Supporting these results are new 21 longitudinal cohort studies conducted by other res earchers in varying loca tions using different 22 methods (U.S. EPA, 2009a, section 7.3.9.1). New ev idence from a U.S. cohort of cystic fibrosis 23 (CF) patients provided evidence of association between long-term PM 2.5 exposures and 24 exacerbations of respiratory symptoms resulting in hospital admissions or use of home 25 intravenous antibiotics (US EPA, 2009a, p. 7-25; Goss et al., 2004). 26 Toxicological studies provide coherence and biological plausibility for the respiratory 27 effects observed in epidemiological studies (U S EPA, 2009a, p. 7-42). For example, pre- and 28 postnatal exposure to ambient levels of ur ban particles has been found to affect lung 29 development in an animal model (US EPA, 2009a , section 7.3.2.2; p. 7-43). This finding is 30

6 Supporting evidence comes from studies “that observ ed associations between long-term exposure to PM 10 and an increase in respiratory symptoms and reducti ons in lung function grown in areas where PM 10 is dominated by PM 2.5 ” (US EPA, 2009a, p. 2-12).
7 Clinical significance was defined as a FEV 1 below 80% of the predicted value, a criterion commonly used in clinical settings to identify persons at increased risk for adverse respiratory conditions (US EPA, 2009a, p. 7-29-7- 30). The primary NAAQS for SO 2 also includes this interpretation for FEV 1 (75 FR 35525 , June 22, 2010 ).Draft – Do Not Quote or Cite June 2010 2-18 important because impaired lung development is one mechanism by which PM exposure may 1 decrease lung function growth in children (US EPA, 2009a, p. 2-12; section 7.3). 2 With regard to respiratory-related mortality associated with long-term PM 2.5 exposure, 3
the ISA concludes that the evidence is “lim ited and inconclusive” (US EPA, 2009a, p. 7-41). 4 The extended follow-up of the Harvard Six Cities study reported a positive but non-statistically 5 significant association between long-term PM 2.5 exposure and respiratory-related mortality 6 (Laden et al., 2006), whereas P ope et al. (2004) found no associ ation (US EPA, 2009a, p. 7-84). 7 There is emerging but limited evidence fo r an association between long-term PM 2.5 exposure and 8 respiratory mortality in post- neonatal infants where long-ter m exposure was considered as 9 approximately one month to one year (US EPA, 2009a, pp. 7-54 to 7-55). Emerging evidence of 10 short- and long-term exposure to PM 2.5 and respiratory morbidity and infant mortality provide 11 some support for the weak respirat ory mortality eff ects observed. 12 Beyond effects considered to have causal or likely causal associat ions with long-term 13

PM 2.5 exposure discussed above, the following health ou tcomes are classified as having evidence 14 suggestive of a causal association with long-term PM 2.5 exposure: (1 ) reproductive and 15 developmental effects and (2) cancer, mutageni city, and genotoxicity effects (US EPA, 2009a, 16 Table 2-6). With regard to reproductive and developmental effects , the ISA notes, “[e]vidence is 17 accumulating for PM 2.5 effects on low birth weight and infa nt mortality, especially due to 18 respiratory causes during the post-neonatal pe riod” (US EPA, 2009a, section 2.3.1.2). New 19 evidence available in this review reports a significant association between exposure to PM 2.5 20 during pregnancy and lower birth we ight, pre-term birth, and intrau terine growth restriction, and 21 a significant association betw een post-natal exposure to PM 2.5 and an increased risk of infant 22 mortality (US EPA, 2009a, section 7.4). The IS A further notes that “[i]nfants and fetal 23 development processes may be particularly vulnerable to PM exposure, and although the 24 physical mechanisms are not fully understood, several hypotheses have been proposed involving 25 direct effects on fetal health, a ltered placenta function, or indirect effects on the mother’s health” 26 (US EPA, 2009a, section 7.4.1). While toxicological studies provide some evidence that 27 supports an association between long-term PM 2.5 exposure and adverse reproductive and 28 developmental outcomes, there is “little mechanistic information or biological plausibility for an 29 association between long-term PM exposure and adverse birth outcomes (e.g., low birth weight 30 or infant mortality)” (US EPA, 2009a, p. 2-13). 31 With regard to cancer, mutagenic and genotoxic effects , “[m]ultiple epidemiologic 32 studies have shown a consistent positive associ ation between PM 2.5 and lung cancer mortality, 33 but studies have generally not reported associa tions between PM 2.5 and lung cancer incidence” 34 (US EPA, 2009a, p. 2-13 and sections 2.3.1.2 and 7.5; Table 7-7; Figures 7-6 and 7-7). The 35 extended follow-up to the ACS study reporte d an association between long-term PM 2.5 exposure 36Draft – Do Not Quote or Cite June 2010 2-19 and lung cancer mortality (US EPA, 2009a, p. 7-71; Krewski et al., 2009) as did the extended 1 follow-up to the Harvard Six Cities study when cons idering the entire 25-year follow-up period. 2 There is some evidence, primarily from in vitro studies, providing biological plausibility for the 3 PM-lung cancer relationships observed in epid emiological studies (U S EPA, 2009a, p. 7-80), 4 although toxicological studies of carcinogenicity, mutagenicit y, and genotoxicity generally 5 reported mixed results (US EPA, 2009a, section 7.5). 6

Health Effects Associated with Short-term PM 2.5 Exposure 7
In considering effects associated with short-term PM 2.5 exposure, the body of currently 8 available scientific evidence has been expanded greatly by the publication of a number of new 9 multi-city time-series studies that have used unifo rm methodologies to investigate the effects of 10 short-term fine particle exposures on public health. This body of evidence provides a more 11 expansive data base and considers multiple locations representing varying regions and seasons 12 that provide evidence on the influence of climate and air pollution mixes on PM 2.5 -associated 13 health effects. These studies provide more precise estimates of the magnitude of effects 14
associated with short-term PM 2.5 exposure than most smaller-scale single-city studies that were 15 more commonly available in the last review (U.S. EPA 2009a, chapter 6). 16 With regard to mortality , extended and expanded analyses of a multi-city study available 17
in the last review as well as new U.S. multi-city and single-city short-term PM 2.5 exposure 18 studies have found generally consistent pos itive associations be tween short-term PM 2.5 exposures 19 and cardiovascular- and respiratory-related mort ality as well as all-cause (non-accidental) 20 mortality (US EPA, 2009a, sections 2.3.1.1, 6.2.11 and 6.5.2.2; Figures 6-26, 6-27, and 6-28). A 21 Canadian multi-city study available in the last review was expanded from 8 to 12 cities (Burnett 22 and Goldberg, 2003; Burnett et al., 2004), with cons istent findings of a positive and statistically 23 significant association between short-term PM 2.5 exposure and mortalit y (US EPA, 2009a, p 6- 24 182, Figure 2-1), although the influence of NO 2 and limited PM 2.5 data for several years during 25 the study period somewhat diminish these findings. In an analysis of National Morbidity, 26 Mortality, and Air Pollution Study (NMMAPS) da ta, Dominici et al. (2007a) reported 27 associations between fine particle exposures a nd all-cause and cardio-respiratory mortality (US 28 EPA, 2009a, p. 6-175, Figure 6-26). In a study of 112 U.S. cities, Zanobetti and Schwartz 29 (2009) reported positive associatio ns (in 99% of the cities) and fr equently statistically significant 30 associations (in 55% of the cities) between short-term PM 2.5 exposure and total (non-accidental) 31 mortality (US EPA, 2009a, pp 6-176 to 6-179; Figures 6-23 and 6-24). Collectively, these 32 studies provide generally consistent and much stronger evidence for PM 2.5 -associated mortality 33
than the evidence available in the last review. 34Draft – Do Not Quote or Cite June 2010 2-20 With regard to cardiovascular effects , new multi-city as well as single-city short-term 1

PM 2.5 exposure studies conducted since the last revi ew supports a largely positive and frequently 2 statistically significant relationship between short-term exposure to PM 2.5 and cardiovascular3 related disease and mortality, substantiating pr ior findings. For example, among a multi-city 4 cohort of older adults participating in the Me dicare Air Pollution Study (MCAPS) investigators 5 reported evidence of a positive association between short-term PM 2.5 exposures and hospital 6 admissions related to cardiovascular outcomes (U S EPA, 2009a, pp. 6-57 to 58; Dominici et al, 7 2006a; Bell et al, 2008). The str ongest evidence for cardiovascular morbidity effects has been 8 observed predominately for ischemic heart dis ease (IHD) and congestive heart failure (CHF) 9 hospital admissions and emergency department vi sits, and cardiovascular-related mortality (US 10 EPA, 2009a, Figure 2-1, p. 6-79, sections 6.2.10.3, 6.2.10.5, and 6.2.11; Bell et al., 2008; 11 Dominici et al., 2006a; Tolbert et al., 2007; Zanobetti and Schwartz, 2009). Furthermore, these 12 findings are supported by a recent study of a multi- city cohort of women participating in the 13 WHI that reported a positive but non-statistically significant association between short-term 14 exposure to PM 2.5 and ECG measures of myocardial ischemia (Zhang et al., 2009). 15 In focusing on respiratory effects , the strongest evidence from short-term PM 2.5 exposure 16 studies has been observed for respiratory-rela ted emergency department visits and hospital 17 admissions for chronic obstructive pulmonary dis ease (COPD) and respiratory infections (U.S. 18 EPA, 2009a, sections 2.3.1.1 and 6.3.8.3; Figures 2-1 and 6-13; Dominici et al., 2006a;). 19
Evidence for PM 2.5 -related respiratory effects has also been observed in panel studies, which 20 indicate associations with respiratory symptoms, pulmonary function, and pulmonary 21 inflammation among asthmatic children. Although not consistently observed, some controlled 22 human exposure studies have reported small d ecrements in various measures of pulmonary 23 function following controlled exposures to PM 2.5 (US EPA, 20009a, p. 2-10). Furthermore, the 24 comparatively larger body of toxi cological evidence since the last review is coherent with the 25 evidence from epidemiological and controlled hu man exposure studies that examined short-term 26 exposures to PM 2.5 and respiratory effects (U S EPA 2009a, section 6.3.10.1). 27

Uncertainties in the Evidence 28
With respect to understanding th e nature and magnitude of PM 2.5 -related risks, as 29 discussed above, we recognize that epidemiological studies evaluating health effects associated 30 with long- and short-term PM 2.5 exposures have reported heteroge neity in responses both within 31 and between cities and geographic regions within the U.S. This heterogeneity may be attributed, 32 in part, to differences in the fine particle com position. However, the currently available evidence 33 and limited availability of city-specific PM 2.5 speciation data does not allow conclusions to be 34 drawn regarding the re lative toxicity of PM 2.5 components, combinations of PM 2.5 components, 35Draft – Do Not Quote or Cite June 2010 2-21 or sources of fine particles in different lo cations. Overall, the ISA concludes “that many 1
constituents of PM 2.5 can be linked with multiple health e ffects, and the evidence is not yet 2
sufficient to allow differentiation of those constituents or sources th at are more closely related to 3 specific health outcomes” (US EPA, 2009a, p. 2-17.) 4 Measurement error is also an important s ource of uncertainty. Variability in the 5
associations observed across PM 2.5 epidemiological studies may be due in part to exposure error 6 related to the use of county-leve l air quality data and our limi ted understanding of factors that 7 may influence exposures (e.g., topography, the built e nvironment, climate, source characteristics, 8 ventilation usage, personal activity patterns). As noted in the ISA, biases and uncertainties in 9 exposure estimates can result in biases and uncertain ties in associated health effect estimates (US 10 EPA, 2009a, p. 2-17). 11 We note challenges with interpre ting differences in health e ffects observed in the eastern 12 versus western parts of the U.S. As noted in section 2.3.2 of the ISA, we stern U.S. counties tend 13 to be larger and more topographically diverse th an eastern U.S. counties and regional differences 14
in climate and infrastructure can effect time spent outdoors or indoors, housing characteristics 15 including air conditioning usage, and personal activity patterns. In light of these differences, the 16 ISA notes “...the available evidence and the limited amount of city-specific speciated PM 2.5 data 17 does not allow conclusions to be drawn that specif ically differentiate eff ects of PM in different 18 locations “ (US EPA 2009a, p. 2-17). Therefor e, we recognize that important uncertainties 19
remain in this review related to understandi ng the temporal and spatial variability in PM 2.5 20 concentrations, including PM 2.5 components, and associated h ealth impacts across different 21 geographic areas. 22
Summary 23
In considering the extent to which newly availa ble scientific evidence strengthens or calls 24 into question evidence of associations identified in the last review betwee n ambient fine particle 25 exposures and health effects, we recognize that much progress ha s been made in assessing some 26 key uncertainties related to our understanding of h ealth effects associated with short- and long27 term exposure to PM 2.5. As briefly discussed above as well as in the more complete discussion of 28 the evidence as assessed in the ISA, we note th at the newly available information combined with 29 information available in the last review pr ovides substantially str onger confidence in a causal 30
association between short- a nd long-term exposures to PM 2.5 and mortality and cardiovascular 31 effects. In addition, the newl y available evidence reinforc es and expands the evidence 32 supporting the likely causal nature of the associat ions between short- a nd long-term exposure to 33

PM 2.5 and respiratory effects. Causal inferences, as discussed in the ISA, are based not only on 34 the more expansive epidemiological evidence av ailable in this review but also reflects 35Draft – Do Not Quote or Cite June 2010 2-22 consideration of important progress that has be en made to advance our understanding of a 1 number of potential biologic modes of action or pathways for PM-relate d cardiovascular and 2 respiratory effects (US EPA 2009a, chapter 5). With respect to suggestive evidence for a 3 broader range of effects, the body of scientific evidence is somewhat expanded but is still limited 4 with respect to associat ions between long-term PM 2.5 exposures and developmental and 5 reproductive effects as well as cance r, mutagenic, and genotoxic eff ects. Thus, we conclude that 6 there is stronger and more consistent and cohere nt support for associations between short- and 7 long-term PM 2.5 exposure and a broader range of health outcomes than was available in the last 8 review, providing the basis for fine particle st andards at least as protective as the current PM 2.5 9
standards. 10 Having reached this initial conclusion, we then consider how the new evidence informs 11 our understanding of susceptib le populations by addressi ng the following question: 12

 To what extent does the currently ava ilable scientific evidence expand our 13 understanding of susceptible populations? 14 Specific groups within the ge neral population, referred to as susceptible populations, are 15 at increased risk for experiencing adverse health effects related to PM exposures. 8 These groups 16 could exhibit a greater risk of PM-related health effects than the genera l population for a number 17 of reasons including, being affected by lower concentrations of PM , experiencing a larger health 18 impact at a given PM concentra tion, and/or being exposed to highe r PM concentrations than the 19 general population. Given the heterogeneity of individual responses to PM exposures, the 20 severity of the health effects experienced by a susceptible population may be much greater than 21 that experienced by the population at large. 22 As summarized below, the currently availa ble epidemiological and controlled human 23 exposure evidence expands our understanding of pr eviously identified su sceptible populations 24 (e.g., children, older adults, and individuals wi th pre-existing heart and lung disease) and 25 supports the identification of additional sus ceptible populations (e.g., persons with lower 26 socioeconomic status (SES), genetic differences ) (US EPA, 2009a, section 2.4.1, Table 8-2). In 27 addition, toxicological studies provide underlying support for th e biological mechanisms that 28 potentially lead to increased susceptibility to PM -related health effects. These studies also. 29
Lifestages: Children and Older Adults 30
Two different lifestages have been associated with increased susceptibility to PM-related 31 health effects: childhood (i.e., less than 18 years of age) and older adulthood (i.e., 65 years of 32 age and older). Childhood repres ents a lifestage where susceptibility to PM exposures may be 33

8 Although studies have primarily used exposures to PM 10 or PM 2.5 , the available evidence suggests that the identified factors also increase risk from PM 10-2.5 (US EPA, 2009a, section 8.1.8).Draft – Do Not Quote or Cite June 2010 2-23 related to the following observati ons: children spend more time outdoors; children have greater 1 activity levels than adults; children have expos ures resulting in higher doses per body weight and 2 lung surface area; and the developing lung is pron e to damage, including irreversible effects, 3 from environmental pollutants as it continue s to develop through adol escence (US EPA, 2009a, 4 section 8.1.1.2). Older adults represent a lifestag e where susceptibility to PM-associated health 5 effects may be related to the higher prevalence of pre-existing cardiov ascular and respiratory 6 diseases found in this age group compared to you nger age groups as well as the gradual decline 7 in physiological processes that occur as part of the aging process (US EPA, 2009a, section 8 8.1.1.1). 9 With regard to mortality, recent epidemiological studies have found that older adults are 10 at greater risk of all-cause (non-accidental) morta lity associated with short-term exposure to both 11

PM 2.5 and PM 10 , providing consistent and stronger ev idence of effects in this susceptible 12 population compared to the last review. Epidemiological studies that ex amined the association 13 between mortality and long-term exposure to PM 2.5 that stratified the results by age (i.e., less 14 than 65 years of age compared to aged 65 and ol der; different age groups within the aged 65 and 15 older population) reported re sults that are generally consistent with the findings of these short16 term exposure studies while also providing some evidence that risk declin es with increasing age 17 starting at age 60, such that there is no eviden ce of an association among persons 85 years and 18 older (US EPA, 2009a, Figure 7-7, section 8.1.1.1, Zeger et al., 2008). 19 With regard to morbidity effects, currently available studies provide evidence that older 20 adults have heightened responses, especially for cardiovascular-related effects, and children have 21 heightened responses for respiratory-related e ffects associated with long- and short-term PM 2.5 22 exposures. With regard to older adults, epidemio logical studies provide ev idence of increases in 23

PM 2.5 -related risk of MI, cor onary revascularization, 9 and their combination with CHD-related 24 death for participants free of CVD at baseline (Miller et al., 2007) as well as cardiovascular25 related hospitalizati on (Dominici et al., 2006; Be ll et al., 2008). Further, dosimetry studies have 26 shown a depression of fine and coarse PM clearan ce in all regions of the respiratory tract with 27 increasing age beyond young adulthood, suggesting that older adults are at greater risk of PM28 related respiratory health eff ects (US EPA, 2009a, section 8.1.1). 29 With regard to respiratory-related effects in children associated with long-term PM 30 exposures, our understanding of effects on lung development has been strengthened based on 31 newly available evidence that is consistent and coherent acr oss different study designs, locations, 32 and research groups. For example, the stronge st evidence comes from the extended follow-up 33
for the Southern California CHS which include s several new studies that report positive 34

9 Coronary revascularization includes percutaneous coronary interventions, such as angioplasty.Draft – Do Not Quote or Cite June 2010 2-24 associations between long-term exposure to PM 2.5 and respiratory morbidity, particularly for 1 such endpoints as lung function growth, respirat ory symptoms (i.e., bronchitic symptoms), and 2 respiratory disease incidence (US EPA, 2009a, section 7.3; Gauderman et al., 2004). These 3 analyses provide evidence that PM 2.5 –related effects persist into early adulthood and are more 4 robust and larger in magnitude than previously reported. 5 With regard to respiratory eff ects in children associated with short-term exposures to PM, 6 currently available studies provide stronger evidence of respirator y-related hospitalizations with 7 larger effect estimates observed among childre n. In addition, reductions in lung function (FEV 1 ) 8 and an increase in respiratory symptoms and me dication use associated with PM exposures has 9 been reported among asthmatic children (U S EPA, 2009a, sections 6.3.1, 6.3.2.1, 8.4.9). 10 In addition, accumulating evidence suggests that the developing fetus may also represent 11 an additional lifestage that is susceptible to PM exposures. The IS A further notes that “[i]nfants 12 and fetal development processes may be particul arly vulnerable to PM exposure, and although 13 the physical mechanisms are not fully understo od, several hypotheses have been proposed 14 involving direct effects on fetal health, altered placenta function, or indirect effects on the 15 mother’s health” (US EPA, 2009a, section 7.4.1). Evidence is accumulating for PM 2.5 -related 16 effects on low birthweight and in fant mortality, especially due to respiratory causes during the 17 post-neonatal period (US EPA, 2009a, sections 2.3.1.2 and 7.4). 18
Pre-existing Diseases/Health Conditions 19

A number of health conditions have been found to put individuals at greater risk for 20 adverse effects following exposure to PM. Th e currently available evidence confirms and 21 strengthens evidence in the last review that individuals with underlying cardiovascular and 22 respiratory diseases are more susceptible to PM exposures. 23 The majority of the epidemiological studies that examined associations between short24 term PM exposures and cardiovascular outco mes focused on cardiovascular-related hospital 25 admissions and emergency department visits (US EPA, section 8.1.6.1). There is some new 26
evidence that individuals with pre-existing IHD are at greater risk of PM-associated hospital 27 admissions and emergency department visits relate d to cardiovascular effect s. Additional studies 28 have focused on hypertension and on the effects of PM on cardiac function in individuals with 29 dysrhythmia with mixed results. One epid emiological study (US EP A, 2009a, section 7.2.9; 30 Zanobetti and Schwartz, 2007) investigated asso ciations between long-term exposure to PM 10 31 and the progression of disease or reduced surv ival in a 21-city study of people discharged 32 following an acute MI, finding significant associations for mortality, CHF and new 33 hospitalization for MI. 34Draft – Do Not Quote or Cite June 2010 2-25 With regard to individuals with pre-existi ng respiratory illnesse s (e.g, asthma, COPD), 1 the ISA presents and assesses a number of studies that evaluate a broad range of health outcomes 2 (e.g., mortality, asthma symptoms) in respons e to PM exposures (US EPA, 2009a, section 3 8.1.6.2). Evidence in asthmatics is stronger and more consistent, while studi es of persons with 4 COPD have reported mixed results. Epidemiologi cal studies have examined the effect of short5 term exposure to PM in asthmatics finding an in crease in medication use, asthma attacks, and 6 respiratory symptoms (i.e., asth ma symptoms, cough, shortness of breath, and chest tightness). 7 Controlled human exposure studies report that healthy and asthmatic subjects exposed to coarse, 8 fine and ultrafine CAPs, exhibit similar resp iratory responses, although these studies excluded 9
moderate and severe asthmatics th at would be expected to show increased susceptibility to PM 10 exposure. Toxicological studies using diesel exhaust particles (DEPs) provide mechanistic 11 support that PM exposure results in allergic sensitization, and indi viduals with al lergic airway 12 conditions are at greater risk of adverse effects upon exposure to PM 2.5 . Further, there is 13 emerging but limited evidence which suggests that non-allergic respiratory morbidities may also 14 increase the susceptibility of an individual to PM-related resp iratory effects (US EPA, 2009a, p. 15 8-12). 16 There is also emerging evidence that suggest s the influence of additional pre-existing 17 diseases or health conditions, in cluding diabetes and obesity on the manifestation of PM-related 18
health effects. The ISA notes that additional re search exploring the effect of PM exposures on 19 obese individuals and identifying the biological pathway(s) that could increase the susceptibility 20
of diabetic and obese individuals to PM coul d improve our understand ing of these potentially 21 susceptible populations (US EPA 2009a, pp. 2-23-2-24). 22

Socioeconomic Status 23
Stronger evidence is availabl e in this review indicating that people from lower 24
socioeconomic strata are a su sceptible population re lative to PM exposures (US EPA, 2009a, 25 section 8.1.7). Persons with lower SES 10 have been generally found to have a higher prevalence 26 of pre-existing diseases; limite d access to medical treatment; a nd limited access to fresh foods 27 leading to a reduced intake of antioxidants, polyunsaturated fatty acids and vitamins, which can 28 increase this population’s risk to PM-related effects. Evidence avai lable in the last review from 29
the ACS and Harvard Six Cities cohort studies indi cated increased mortality risk with long-term 30 exposure to PM 2.5 in the cohort subgroups with lower education levels (US EPA 2004, section 31 9.2.4.5). In this review, additiona l support is available to identify persons with lower SES as a 32 susceptible population. For example, Krewski et al. (2009) found moderate evidence for 33

10 SES is a composite measure that usually consists of economic status, measured by income; social status measured by education; and work status measured by occupation (US EPA, 2009a, p. 8-14).Draft – Do Not Quote or Cite June 2010 2-26 increased lung cancer mortality in individuals with a high school education or less in response to 1 long-term exposure to PM 2.5 . However, IHD-related mortality associated with long-term PM 2.5 2 exposures was most strongly associ ated with individuals with hi gher education levels (US EPA, 3 2009a, p. 8-15). 4

Genetic Factors 5
Investigation of potential genetic susceptibility has provide d evidence that individuals 6 with null alleles or polymorphisms in genes that mediate the antioxidant response to oxidative 7 stress (e.g., GSTM1), regulate enzyme activity (i.e ., MTHFR and cSHMT), or regulate levels of 8 procoagulants (i.e., fibrinogen) ar e more susceptible to PM-related effects. However, some 9 evidence suggests that polymorphisms in gene s (e.g., HFE) may provide protection for PM10 related effects. Emerging evidence also suggests th at PM exposure can impa rt epigenetic effects 11 (i.e., DNA methylation) (US EPA, 2009a, p. 8-16). More research is needed to better understand 12 the relationship between genetic e ffects and potential susceptibility to PM-related effects. 13
Summary 14
In summary, we conclude that there are several susceptible populations that are likely to 15 be at increased risk of PM-related effects, including the lifestage s of childhood and older 16 adulthood, those with preexisting he art and lung diseases, and thos e of lower SES. We also 17 recognize that there is emerging, though still limited evidence for additional potentially 18 susceptible populations, such as those with diabet es, people who are obese, or those with genetic 19
factors. We note that the available evidence doe s not generally allow dist inctions to be drawn 20
between the PM indicators in te rms of whether populations are more susceptible to a particular 21 size fraction (i.e., PM 2.5 and PM 10-2.5 ). 22

 To what extent does the currently available scientific evidence report associations that 23 extend to air quality concentrations that are lower than had previously been observed 24 or that are observed in areas that would likely meet the current suite of PM 2.5 25 standards? 26 In focusing our attention on whether the av ailable evidence supports consideration of 27 standards that are more protectiv e than the current suite of PM 2.5 standards, we first recognize 28
that the ISA concludes there is no evidence to su pport the existence of a discernible threshold 29 below which effects would not occur (US EP A, 2009a, section 2.4.3). Next, we consider 30 whether the evidence provides information for health effects associated with air quality 31 concentrations that are lower than had previous ly been observed, or if epidemiological studies 32 have reported effects in areas that w ould likely meet the current suite of PM 2.5 standards. 33Draft – Do Not Quote or Cite June 2010 2-27 Associations with Long-term PM 2.5 Exposure 1
Extended follow-up analyses of the ACS and Harvard Six Cities studies provide 2 consistent and stronger evidence of a causal association with mo rtality at lower air quality 3 distributions than had previously been observed. The original and reanalysis of the ACS study 4 reported positive and statistically significant e ffects associated with a long-term mean PM 2.5 5 concentration of 18.2 μg/m 3 across 50 metropolitan areas for 1979-1983 (Pope et al., 1995; 6 Krewski et al., 2000). 11 In extended analyses, positive and statistically significant effects of 7 approximately similar magnitude we re associated with declining PM 2.5 concentrations, from an 8 aggregate long-term mean in 58 metropolitan areas of 21.2 μg/m 3 in the original monitoring 9 period (1979-1983) to 14.0 μg/m 3 for 116 metropolitan areas in the most recent years evaluated 10 (1999-2000), with an overall average across the two study periods in 51 metropolitan areas of 11 17.7 μg/m 3 (Pope et al., 2002; Krewski et al., 2009). With regard to the Harvard Six Cities 12 Study, the original and reanalysis reported positive and st atistically significant effects associated 13 with a long-term mean PM 2.5 concentration of 18.0 μg/m 3 for 1980-1985 (Dockery et al., 1993; 14 Krewski et al., 2000). In an extended follow-up of this study, the aggregate long-term mean 15 concentration across all y ears evaluated was 16.4 μg/m 3 for 1980-1988 12 (Laden et al., 2006). 16 In an additional analysis of the extended follow-up of the Harvard Six Cities cohort study, 17 investigators reported the C-R relationship was lin ear and “clearly continuing below the level” of 18 the current annual standard (US EPA, 2009a , p. 7-92; Schwartz et al., 2008). 19 We then consider new cohort studies that pr ovide evidence of mortality associated with 20 air quality distributions that ar e generally lower than those repor ted in the ACS and Harvard Six 21 Cities studies, with effect estimates that were similar or greater in magnitude. The Women’s 22 Health Initiative (WHI) reported positive and most often statistic ally significant associations 23 between long-term PM 2.5 exposure and cardiovascular-relate d mortality, with much larger 24
relative risk estimates than in the ACS and Ha rvard Six Cities studies, as well as morbidity 25 effects at an aggregate long-term mean PM 2.5 concentration of 13.5 μ g/m 3 for 2000 (Miller et al., 26 2007). Using the Medicare cohort, Eftim et al. (2008) reported somewhat higher effect estimates 27
than in the ACS and Harvard Six Cities studies with aggregate long -term mean concentrations of 28
13.6 μ g/m 3 and 14.1 μ g/m 3 , respectively, for 2000-2002. The MCAPS reported associations 29 between long-term PM 2.5 exposure and mortality for the easte rn region of the U.S. at an 30 aggregated long-term PM 2.5 median concentration of 14.0 μg/m 3 , although no association was 31 reported for the western region wi th an aggregated long-term PM 2.5 median concentration of 13.1 32

11 The study periods referred to in this document reflect the years of air quality data that were included in the analyses, whereas the study periods identif ied in the ISA reflect the years of hea lth status data that were included.
12 Aggregate mean concentration provided by study author (Laden, 2009).Draft – Do Not Quote or Cite June 2010 2-28 μg/m 3 (US EPA, 2009a, p. 7-88; Zeger et al., 2008) 13 . Premature mortality in children reported 1 in a national infant mortality study as well as mo rtality in a cystic fibrosis cohort including both 2 children and adults reported positiv e but not statistically significant effects associated with long3 term aggregate mean concentrations of 14.8 μ g/m 3 and 13.7 μ g/m 3 , respectively (Woodruff et al., 4 2008; Goss et al., 2004). 5 With respect to respiratory morbidity effects associated with long-term PM 2.5 exposure, 6 the across-city mean of 2-week average PM 2.5 concentrations reported in the initial Southern 7 California CHS was approximately 15.1 μg/m 3 (Peters et al., 1999). Th ese results were found to 8
be consistent with results of cross-sectional an alyses of the 24-City St udy (Dockery et al., 1996; 9 Raizenne et al., 1996), which reported a long-term cross-city mean PM 2.5 concentration of 14.5 10 μg/m 3 . In this review, extended analysis of th e Southern California CHS provided stronger 11
evidence of PM 2.5 -related respiratory effects, at lower air quality concentrations than had 12 previously been reported, w ith a four-year aggregate m ean concentration of 13.8 μg/m 3 across 13 the 12 study communities (McConnell et al., 2003; Gauderman et al., 2004, US EPA, 2009a, 14 Figure 7-4). 15 Broadening our consideration to effects for which eviden ce is suggestive of a causal 16 association, we note birth outcome studies that reported positive and st atistically significant 17 effects related to aggregate long-term mean PM 2.5 concentrations of approximately 12 μg/m 3 (US 18 EPA, 2009a, Table 7-5; Bell et al., 2007; Liu et al., 2007; Pa rker et al, 2005). In contrast, Parker 19 and Woodruff (2008) reported no overa ll association with birthwei ght with an aggregate long20 term mean concentration of 13.5 μg/m 3 (US EPA, 2009a, section 7.4.1.1). 21 Collectively, the currently available eviden ce provides support for associations between 22 long-term PM 2.5 exposure and mortality and morbidity effects that extend to air quality 23 concentrations that are lower than had previ ously been observed, with aggregated long-term 24
mean PM 2.5 concentrations extending to well below th e level of the current standard. These 25 studies evaluated a broader range of health outcomes in the gene ral population and in susceptible 26 populations than were considered in the la st review, and include extended follow-up for 27 prospective epidemiological studies that were impor tant in the last review as well as additional 28 evidence in important new cohorts. 29

13 Zeger et al. (2008) also reported positive and statisti cally significant effects for the central region, with an aggregate long-term mean PM 2.5 concentration of 10.7 μg/m 3 . However, in contrast to the eastern and western risk estimates, the central risk estimate in creased with adjustment for COPD (used as a proxy for smoking status). Due to the potential for confounding bias influencing the risk es timate for the central region, we have not focused on the results reported in the central region to inform the adequacy of the current suite of standards.Draft – Do Not Quote or Cite June 2010 2-29 Associations with Short-term PM 2.5 Exposure 1
In considering long-term average ambi ent concentrations from short-term PM 2.5 exposure 2 studies, an expanded follow-up analyses of a Canadian multi-city study provides evidence of a 3
causal association between s hort-term exposures to PM 2.5 and mortality at lower air quality 4 distributions than had previously been observe d. Specifically, the expansion of the multi-city 5 Canadian study from 8 (Burnett and Goldbe rg, 2003; aggregate long-term mean PM 2.5 6 concentration of 13.3 μg/m 3 ) to 12 Cities (Burnett et al 2004) yielded results consistent with 7 prior findings of a positive and statistically significant association, but at a lower aggregate long8
term mean PM 2.5 concentration of 12.8 μg/m 3 . In a multi-city time-series analysis of 112 U.S. 9 cities published since the last review, Zanobett i and Schwartz (2009) reported a positive and 10 statistically significant associa tion with all-cause, cardiovascula r-related (e.g., MI, stroke), and 11 respiratory-related mortality and short-term PM 2.5 exposure, in which the aggregate long-term 12
mean PM 2.5 concentration was 13.2 μg/m 3 (ranging from 6.6 μg/m 3 to 24.7 μg/m 3 ) (US EPA, 13 2009a, Figure 6-24). Furthermore, city-specific eff ect estimates indicate the association between 14 short-term exposure to PM 2.5 and total mortality and cardiovascular- and respiratory-related 15 mortality is consistently positive for an overwhe lming majority (99%) of the 112 cities across a 16 wide range of air quality concentrations (U S EPA, 2009a, Figure 6-24, p. 6-178 to 179). The 17 authors report that for all-cause mortality, city -specific effect estimates were statistically 18 significant for 55% of the 112 citi es, with long-term city-mean PM 2.5 concentrations ranging 19 from 7.8 μg/m 3 to 18.7 μg/m 3 and 24-hour PM 2.5 city-mean 98 th percentile concentrations 20 ranging from 18.4 to 64.9 μg/m 3

. 21 With regard to cardiovascular a nd respiratory morbidity effects, in the first analysis of the 22 MCAPS cohort conducted by Dominici et al. ( 2006a) across 204 US c ounties, investigators 23 reported a statistically significant association with hospitalizations fo r cardiovascular and 24 respiratory diseases and short-term PM 2.5 exposure, in which the aggregate long-term mean 25

PM 2.5 concentration was 13.4 μg/m 3 (ranging from 4 μg/m 3 to 23 μg/m 3 ). Furthermore, a sub26 analysis restricted to days with 24-hour average concentrations of PM 2.5 at or below 35 μg/m 3 27 indicated that, in spite of a reduced statistical power from a smaller number of study days, 28 statistically significant associa tions were still observed betw een short-term exposure to PM 2.5 29 and hospital admissions for cardiovascular and respiratory diseases (Dominici, 2006b 14 ). These 30 results, along with the observation that appr oximately 50% of the 204 county-specific mean 98 th 31 percentile PM 2.5 concentrations aggregated across all years were below the 24-hour standard of 32

14 This sub-analysis was not included in the original publication (Dominici et al., 2006a). Authors provided subanalysis results for the Administrator’s consideration as a letter to the docket following publication of the proposed rule in January 2006.Draft – Do Not Quote or Cite June 2010 2-30 35 μg/m 3

, suggests that the overall health effects obs erved across the U.S. are not primarily 1 driven by the higher end of the PM 2.5 air quality distribution (Bell, 2009, personal 2 communication from Dr. Michelle Bell regardin g air quality data for Bell et al., 2008 and 3 Dominici et al., 2006). In an extended analysis of the MCAPS study, Bell et al (2008) reported a 4 positive and statistically significant increase in ca rdiovascular hospitalizations associated with 5
short-term PM 2.5 exposure, in which the aggregate long-term mean PM 2.5 concentration was 12.9 6 μg/m 3 (ranging from 4 μg/m 3 to 20 μg/m 3 ). 7 In considering single-city short-term PM 2.5 exposure studies that would likely have met 8 the current suite of standards, the following st udies reported positive and statistically significant 9 associations in areas: Mar et al. (200 4) reported an association for short-term PM 2.5 exposures 10 in relation to respiratory symptoms among children in Phoenix; and two studi es noted in the last 11 review, Peters et al. (2001) and Delfino et al. (2007), reported an associ ation with short-term 12 exposure to PM 2.5 and MI- and respiratory-related hosp ital admissions in Boston and Montreal, 13 Canada, respectively. Single-city studies that reported positive but statistically non-significant 14
associations for cardiovascular and respiratory endpoints include a number of studies reporting a 15 wide range of air quality dist ributions conducted in Saint Jo hn (Steib et al., 2000), Phoenix 16 (Wilson et al., 2007), Denver (Rabinovitch et al., 2006), Edmonton (Villeneuve et al., 2006), and 17 Nueces County, TX (Lisabeth et al., 2008). Other single-city short-term PM 2.5 exposure 18 analyses reported null findings fo r cardiovascular and respiratory morbidity effects in association 19 with short-term exposure to PM 2.5 in areas that would likely ha ve met the current suite of 20 standards, including Phoenix (i.e., respiratory symptoms in adults; Ma r et al., 2004); Spokane 21 (Slaughter et al. 2005), Denver (Rabinovitch et al., 2004) and Edmonton (Villeneuve et al., 22 2006). In light of the mixed findings reported in single-city studies, particularly for studies 23 conducted in areas such as Phoenix, Denver, an d Edmonton that report both positive and null 24 findings, we place comparatively greater weight on the results from multi-city studies in 25 considering the adequacy of the current suite of standards. 26 Collectively, the findings from multi-city short-term PM 2.5 exposure studies together with 27 support from single city studies at concentrations that would likel y have met the current suite of 28 standards provide evidence of PM 2.5 associated health effects. These findings are further 29 bolstered by evidence of statistically significant PM 2.5 associated health effects occurring in 30 analyses restricted to days in which 24-hour average PM 2.5 concentrations were below 35 μg/m 3 31 (Dominici, 2006b). 32
Summary 33
In evaluating the currently available scientific evidence, we conclude that the evidence 34 from long and short-term PM 2.5 exposure studies calls into questi on whether the current suite of 35Draft – Do Not Quote or Cite June 2010 2-31 PM 2.5 primary standards protects public health with an adequate ma rgin of safety from effects 1 associated with long- and short-term exposures to PM 2.5 . We also conclude that this evidence 2 provides strong support for considering fine par ticle standards that would impart increased 3 protection beyond that afforded by the current annual and 24-hour PM 2.5 standards. More 4 protective standards would reflect the substantia lly stronger and broader body of evidence for 5 mortality and cardiovascular and re spiratory morbidity effects now available in this review both 6 at lower concentrations of air qua lity than had previously been observed and at levels allowed by 7
the current suite of PM 2.5 standards. 8

2.2.2 Risk-based Considerations 9 Looking beyond evidence-based considerations, staff also has considered the extent to 10
which health risks estimated to occur upon just meeting the current suite of PM 2.5 standards may 11 be judged to be important from a public health pe rspective. For this review, we have estimated 12 risk for a set of health effect endpoints based on a number of selection criteria (US EPA, 2010a, 13 section 3.3.1). Specifically, we have estimated ri sks for (a) all-cause, IHD, cardiopulmonary and 14 lung cancer mortality related to long-term PM 2.5 exposure, (b) non-acciden tal, cardiovascular 15 (CV) and respiratory mortality related to short-term PM 2.5 exposure, and (c) cardiovascular16 related and respiratory-related hospital admi ssions and asthma-related emergency department 17
visits associated with short-term PM 2.5 exposure. In the discussion below, we focus on 18 cardiovascular-related endpoints, since the cau sal association for these endpoints based on 19
available literature is assessed in the ISA to be the strongest of the endpoints considered. The 20
modeled risks for the broader set of health e ffect endpoints are included in the RA (US EPA, 21 2010a). 22 As discussed below, three factors figure prom inently in the interpretation of the risk 23 estimates associated with simulating just meeting the current suite of standards, including: (1) the 24 importance of changes in annual mean PM 2.5 concentrations in a study area in estimating changes 25 in risks for both long- and short-term exposures, (2) the peakiness of ambient PM 2.5 26 concentrations in a study area, 15 and (3) the spatial pattern of ambient PM 2.5 reductions that result 27 from using different approaches to simulate just meeting the current standard levels (i.e., rollback 28 approaches). The latter two factors are interrel ated and influence the degree of risk reduction 29
estimated under the curren t suite of standards. 30 The magnitude of both long- and short-term exposure-related risk estimated to remain 31 upon just meeting the current suite of standards is strongly associat ed with the simulated change 32

15 The term “peakiness” refers to air qu ality distributions across urban areas that have high peak-to-mean ratios (i.e. the ratio of the 24-hour design value to the annual mean design value) relative to distributions in other urban study areas in the U.S.Draft – Do Not Quote or Cite June 2010 2-32 in annual mean PM 2.5 concentrations. The role of annual mean PM 2.5 concentrations in driving 1 long-term exposure-related risk estimates is in tuitive given that risks are modeled using the 2 annual mean air quality metric. 16 The fact that short-term e xposure-related risk estimates are 3 also driven by changes in long-term mean PM 2.5 concentrations is less intuitive, since changes in 4
mean 24-hour PM 2.5 concentrations are used to estimate changes in risk for this time period. 17 5 Analyses show that short-term exposure-relate d risks are not primarily driven by the small 6 number of days with PM 2.5 concentrations in the upper tail of the air quality distribution, but 7 rather by the large number of days with PM 2.5 concentrations at and around the mean of the 8 distribution (US EPA, 2010a, section 3.1.2.2). Consequently, changes in annual mean PM 2.5 9 concentrations are related, to a large extent, to changes in shor t-term exposure-related risk. 10 Therefore, we focus on changes in annual mean PM 2.5 concentrations to inform our 11 understanding of patterns of both long-term and short-term exposure-related risk estimates across 12 the set of urban study areas evaluated in the quantitative RA. 13 The peakiness of ambient PM 2.5 concentrations within a st udy area informs the type of 14 rollback approach used to simulate just meeting the current suite of standards to determine the 15 magnitude of the reduction in annual mean PM 2.5 concentrations for that study area and 16 consequently the degree of risk reduction. 18 For example, study areas with relative peaky PM 2.5 17 distributions are likely to have greater estimated risk reductions fo r the current suite of standards 18 (depending on their mix of 24-hour and annual de sign values), and such locations can be 19 especially sensitive to the type of rollback approach used, with the proportional rollback 20 approach resulting in notably greater estimated ri sk reduction compared with the locally-focused 21 rollback approach. In contrast, study areas with less peaky PM 2.5 concentrations typically 22 experience greater simulated risk reductions for the current annual-standard level compared with 23 24-hour standard levels (again depending on the mix of 24-hour and annual design values). In 24 addition, the type of rollback approach used will tend to have less of an impact on the magnitude 25 of risk reductions for study areas with less peaky PM 2.5 concentrations. Rigorous consideration 26

16 As noted in section 3.2.1 of the RA (U.S.EPA, 2010a), estimates of long-term exposure-related mortality are actually based on an annual mean PM 2.5 concentration across monitors in a study area (i.e., the composite monitor mean). Therefore, in consider ing changes in long-term exposure-related mortality, it is most appropriate to compare composite monitor estimates generated for a study area under each suite of standards. The annual mean at the highest reporting monitor (i.e., maximum monitor) for a study area (i.e., the annual design value) determines the percent reduction in PM 2.5 concentrations required to meet a particular standard. Both types of air quality estimates are provided in Table 3-4 of the RA and both are referenced in this discussion of core ri sk estimates, as appropriate.
17 Estimates of short-term exposure-related mortality and morbidity are based on composite monitor 24-hour PM 2.5 concentrations. However, similar to the case with long-term exposure-related mortality, it is the 98 th percentile 24- hour concentration estimated at the maximum monitor (the 24-hour design value) that will determine the degree of reduction required to meet a given 24-hour standard.
18 The peakiness of ambient PM 2.5 levels also has a direct bearing on whether the 24-hour or annual standard will be controlling for a particular study area, with more peaky dist ributions generally being associated with locations where the 24-hour standard is controlling.Draft – Do Not Quote or Cite June 2010 2-33 of these two factors, allowed us to better understand th e nature and pattern of estimated risk 1 reductions and risk remaining upon simulation of just meeting the current suite of standards 2 across the urban study areas (see U.S.EPA, 2010a, section 5.2.1). 3 We have considered a series of questions to inform our understanding of the adequacy of 4 the current suite of fine partic le standards based on insights obta ined from the quantitative RA. 5 We begin by considering the overall confidence asso ciated with the RA and the degree to which 6 the set of urban study areas included in the RA is representative of urban areas across the U.S.. 7 We then consider the nature and magnitude of ri sk estimated to remain based on simulating just 8 meeting the current suite of standards. 9

 What is the level of confidence associated with risk estimates generated for simulating 10 just meeting the current suite of PM 2.5 standards? 11 A number of design elements we re included in the qua ntitative RA to in crease the overall 12 confidence in the risk estimates generated fo r the 15 urban study areas. These elements 13 included: (a) use of a deliberative process in specifying components of the risk model that 14
reflects consideration of the latest research on PM 2.5 exposure and risk (US EPA, 2010a, section 15 5.1.1), (b) integration of key sources of variability into the design as well as the in terpretation of 16 risk estimates (U.S.EPA, 2010a, section 5.1.2), (c) a ssessment of the degree to which the urban 17 study areas are representati ve of areas in the U.S. experiencing higher PM 2.5 -related risk 18 (U.S.EPA, 2010a, section 5.1.3), an d (d) identification and assessment of im portant sources of 19 uncertainty and the impact of these uncertainti es on the core risk es timates (U.S.EPA, 2010a, 20 section 5.1.4). 19 Two additional analyses examined poten tial bias and overall confidence in the 21 risk estimates. The first analysis explored poten tial bias in the core risk estimates by considering 22 a set of alternative reasonable risk estimates ge nerated as part of a se nsitivity analysis. The 23 second analysis compared the annual mean PM 2.5 concentrations associated with simulating just 24 meeting the current suite of standards with the air quality distribution us ed in deriving the C-R 25 functions applied in modeling mortality risk. 20 Greater confidence is associated with risk 26
estimates based on annual mean PM 2.5 concentrations that are within the region of the air quality 27 distribution used in deriving the C- R functions where the bulk of th e data reside (i.e., within one 28 standard deviation (SD) around the mean). Each of the design elements listed above together 29 with the two additional analys es is discussed below. 30 Staff used a deliberative process to speci fy each of the key analytical elements 31 comprising the core risk model, including: sele ction of urban study areas; selection of health 32

19 The “core” risk estimates produced in this assessment refer to those generated using the combination of modeling elements and input datasets in which we had the highest confidence relative to other modeling choices considered (note, that alternative modeling elements have been included as part off the sensitivity analyses completed).
20 This analysis also considered simulations of alternative standards as discussed in section 2.4.2.Draft – Do Not Quote or Cite June 2010 2-34 endpoints, including specification of the C-R functions to use in modeling those endpoints; and 1 choice of rollback approach used to simulate ju st meeting the current suite of standards. This 2 deliberative process involved rigor ous review of the currently avai lable literature addressing both 3

PM 2.5 exposure and risk combined with the applica tion of a formal set of criteria to guide 4 development of each of the key analytical el ements in the RA (US EPA, 2010a, section 5.1.1) 21 5 The application of this deliberative process incr eases overall confidence in the risk estimates by 6 insuring that the estimates are based on the best available science and data characterizing PM 2.5 7 exposure and risk, and that they reflect consideration of input from external experts on PM 8 exposure and risk through CASAC and public reviews. 9 We considered key sources of variability th at can impact the nature and magnitude of 10
risks associated with the current standard levels across the urba n study areas. These sources of 11 uncertainty include those that co ntribute to differences in risk across urban study areas, but do 12 not directly affect the degree of risk reduction associated with the simulation of the current 13 standard levels (e.g., differences in baseline incidence rate s, demographics and population 14 behavior). We also focused on factors that not only introduce variability into risk estimates 15 across study areas, but also play an important role in determ ining the magnitude of risk 16 reductions upon simulation of current standa rd levels (e.g., peakiness in ambient PM 2.5 17
concentrations within in dividual urban study areas and the natu re of the rollback approach used 18 to simulate just meeting the curren t standards – see earlier discussion). 19 Single and multi-factor sensitivity analyses we re combined with a qualitative analysis to 20 assess the impact of potential sour ces of uncertainty on the core risk estimates. The qualitative 21 uncertainty analysis supplemented the quantitativ e sensitivity analyses by allowing coverage for 22 sources of uncertainty which could not be readily included in the sensitivity analysis (US EPA, 23 2010a, section 3.5.3). The quantitative sensitivit y analyses informed our understanding of 24 sources of uncertainty which may have a moderate to large impact on the core risk estimates. 25 With respect to the long-term exposure-related mortality risk estimates, the most important 26 sources of uncertainty identified in the quantitativ e sensitivity analyses in cluded: selection of C27 R function; 22 modeling risk down to polic y-relevant background (PRB) versus lowest measured 28 level (LML); and the choice of roll back approach used. With regard to the qualitative analysis of 29 uncertainty the following sources were identifi ed as potentially having a large impact on core 30 risk estimates for the long-term exposure-relate d mortality: characteri zation of inter-urban 31

21 In addition, as discussed in section 1.2.4, the RA design reflects consideration of CASAC and public comments on the Scope and Methods Plan and two draft assessment documents.
22 In the case of long-term exposure-related mortality, we considered both alternative C-R functions from the epidemiological study providing the C-R function used in the core analysis (i.e., alternative functions obtained from the Krewski et al. (2009) study involving the ACS dataset) as well as alternative C-R functions identified in other studies (i.e., C-R functions obtained from Krewski et al. (2000) based on the Harvard Six Cities dataset).Draft – Do Not Quote or Cite June 2010 2-35 population exposures; impact of histor ical air quality; and potential variation in effect estimates 1 reflecting differences in PM 2.5 composition. Together, the qualitat ive analysis of uncertainty and 2 quantitative sensitivity analyses provided us with a comprehensive understanding of which 3 sources of uncertainty could have a significant impact on the core risk estimates. This 4 information proved useful in interpreting core risk estimat es and increased our overall 5 confidence in the analysis. 23 6 In addition to identifying sources of uncertain ty with a moderate to large impact on the 7 core risk estimates, the single and multi-element sensitivity analyses also produced a set of 8
reasonable alternative risk estimates that allowed us to place the re sults of the core analysis in 9 context with regard to uncer tainty and potential bias. 24 Most of the alternative model 10 specifications supported by availabl e literature produced risk estimat es that are higher (by up to a 11 factor of 2 to 3) than the core risk estimates. This was not unexpected. The C-R functions used 12 in the core analysis for estimating mort ality risks associated with long-term PM 2.5 exposures 13 were selected from the extended analysis of the ACS study (Krewski et al., 2009). The C-R 14 functions used in the sensitivity analysis were from the reanalysis and validation of the Harvard 15 Six Cities study (Krewski et al., 2000). In genera lizing the results of th e extended analyses of 16 the ACS and Harvard Six Cities studies across the broader national population, we recognize 17 differences in the underlying populations enrolled in these long-term cohort studies, specifically 18 related to socioeconomic status (SES), a f actor in considering impacts on susceptible 19 populations. As noted in the last review, th e ACS study population has a higher SES status (e.g., 20 educational status) rela tive to the Harvard Six Cities study population (12% versus 28% of the 21 cohort had less than a high school education, re spectively) (US EPA, 2004a, p. 8-118). The 22 Harvard Six Cities cohort may provide a more re presentative sample of the broader national 23 population than the ACS cohort. 24 As discussed above, lower SES groups have be en identified as a susceptible population. 25 Therefore, use of effect estimates repor ted in the ACS study which does not provide 26 representative coverage for lower-SES groups, may re sult in risk estimates that are biased low. 27 In contrast, risk estimates developed in the se nsitivity analysis based on the Harvard Six Cities 28

23 Given increased emphasis placed in this analysis on long-te rm exposure-related mortality, the uncertainty analysescompleted for this health endpoint category are more comprehensive than those conducted for short-term exposurerelated mortality and morbidity, which to some extent reflects limitations in study data available for addressing uncertainty in the later category (U .S.EPA 2010a, section 3.5.4.2).
24 The alternative set of reasonable risk estimates are based on alternative model specifications to those used in the core risk model. These alternative reasonable risk estimates were only generated for long-term exposure-related mortality and not for any of the short-term exposure-related mortality or morbidity endpoints. Consequently, consideration of overall confidence (and potential bias) in the core risk estimates based on consideration for these alternative risk estimates is limited to estimates of mortality associated with long-term PM 2.5 exposures.Draft – Do Not Quote or Cite June 2010 2-36 study data set, provide better coverage for lowe r SES populations and ther efore result in higher 1 risk estimates (US EPA, 2010a, section 5.1.5). 2 While being mindful that the use of C-R func tions from Krewski et al. (2009) introduces 3 potential for low bias in the core risk estimat es, we also recognize many strengths of this study 4
and reasons for continued use in generating the core risk estimat es, including: the large number 5 of metropolitan statistical areas (MSAs), inclus ion of two time periods for the air quality data 6 which allowed us to consider different exposure windows; and analysis of a wide range of C-R 7 function models. Therefore, we concluded that C-R functions obtained from this study had the 8 greatest overall support and should be used in th e core risk model. Consideration of the 9
alternative set of reasonable ri sk estimates provided several observations relevant to the 10 interpretation of the core risk estimates including: (a) the core estimates are unlikely to 11 underestimate risk and (b) the degree of potential bi as in the core risk estimates could range up to 12 at least a factor of 2-3 higher. 25 13 In considering the overall confidence in the core risk estimates, we have compared the 14

PM 2.5 concentrations simulated under the current suite of standard levels across the urban study 15
areas to the distribution of PM 2.5 concentrations used in deriving the C-R functions used for 16 long-term exposure-related mortality (as presented in Krewski et al., 2009). Specifically, this 17 assessment compared the composite monitor annual mean PM 2.5 concentrations used in modeling 18 long-term exposure-related mortality risk in the co re analysis to the distribution of annual mean 19

PM 2.5 concentrations from the 1999-2000 ACS exposure period. 26 Generally, when composite 20
monitor annual mean concentrations were within one SD of the mean of the ACS dataset (i.e., in 21 the range of 14 +/- 3 μg/m 3 ), we had relatively high confiden ce in the risk estimates, since they 22
were based on PM 2.5 concentrations that roughly matche d those used in deriving the C-R 23 functions. However, as composite monitor annual mean PM 2.5 concentrations extend below this 24

25 We note that these findings regarding potential bias in the core risk estimates were based on modeling PM 2.5 - attributable IHD and all-cause mort ality associated with long-term PM 2.5 exposure for the current suite of standards. However, we would expect these observations regarding overall confidence in the core risk estimates to hold for other long-term exposure-related mortality endpoints modeled in the RA for bot h the alternative annual and 24-hour standard levels considered. Furthermore, given increased emphasis placed in this analys is on long-term exposurerelated mortality, as noted earlier, th e uncertainty analyses completed for th is health endpoint category are more comprehensive than those conducted for short-term exposure-related mortality a nd morbidity effects, which to some extent reflects limitations in study data available for addr essing uncertainty in the la ter category. Therefore, an alternative set of reasonable risk estimates was not genera ted to supplement core risk estimates generated for shortterm PM 2.5 exposure. 26 As discussed in sections 3.3.3 and 4.0 of the RA (U.S.EPA, 2010a), each category of long-term exposure-related mortality was estimated using separate C-R functions derived from the 1979-1983 and 1999-2000 ACS monitoring periods. For purposes of comparing composite monitor annual mean PM 2.5 concentrations to the ACS data sets used in deriving the C-R functions, we focused on the later monitoring period (1999-2000), since ambient PM 2.5 concentrations from this period more closely matched thos e associated with the study ar eas in our consideration of recent air quality conditions. The 1999-2000 ACS monitori ng period had a mean PM 2.5 concentration of 14 μg/m 3 , a SD of 3.0 μg/m 3 and an LML of 5.8 μg/m 3 (see Table 1 in Krewski et al., 2009).Draft – Do Not Quote or Cite June 2010 2-37 range, our confidence in the risk estimates decreased, with our confidence being significantly 1 reduced when composite monitor annual mean concentrations approach the LML of the ACS 2 dataset (i.e., 5.8 μg/m 3 ). 3

 How representative is the set of urban study areas for the broader set of urban areas in 4 the U.S. expected to experience elevated risk from ambient PM 2.5 exposure? 5 The goal in selecting urban study areas was to provide coverage for the range of larger 6 urban areas in the U.S. expected to experien ce relatively elevated risk due to ambient PM 2.5 7 exposure and other factors associated with PM 2.5 risk (e.g., elevated baseline incidence rates for 8 relevant health endpoints, relativ ely larger susceptible populations). As part of considering our 9 overall confidence in the quantitative RA, we assessed the representativ eness of the 15 urban 10 study areas in the broader national context.. Thre e separate analyses were used to explore 11 representativeness: 12

 A comparison of PM 2.5 -risk-related attributes of the 15 urban study areas against 13 national distributions of these same attri butes suggested that the urban study areas 14 likely reflect the distribution of risk for the nation, with the potential for better 15 characterization at the high end of that distribution (US EPA, 2010a, section 4.4.1). 27 16

 An analysis of where the 15 urban study ar eas fall along the di stribution of U.S. 17 counties included in a nationa l-scale mortality analysis suggested that we have 18 captured counties likely to experience elevated PM 2.5 -related risk (US EPA, 2010a, 19 section 4.4.2). 20

 An evaluation of the mix of design values across the 15 urban study areas as 21 contrasted with design values for the broader set of urban study areas in the U.S. This 22 analysis suggested that (a) the 15 urba n study areas reasonably capture the key 23 groupings of urban areas in the U.S. likely to experience elevated risk due to PM 2.5 24 exposures and (b) we have included study area s likely to experience relatively greater 25 degrees of PM 2.5 -related risk (US EPA, 2010a, section 4.5.1). 26 Based on these analyses, we conclude that these study areas are ge nerally representative 27 of urban areas in the U.S. likely to experience relatively elevated le vels of risk related to ambient 28

PM 2.5 exposure. 29

 What is the nature and magnitude of the long-term and short-term exposure-related 30 risks remaining upon just meeting the current suite of PM 2.5 standards? 31 In considering PM 2.5 -related risks likely to remain upon just meeting the current PM 2.5 32
annual and 24-hour standards in the 15 urban stud y areas included in the quantitative RA, we 33

27 This representativeness analysis also showed that the urban study areas do not capture areas with the highest baseline morality risks or the oldest populations (both of which can result in higher PM 2.5 -related mortality estimates). However, some of the areas with the highe st values for these attributes have relatively low PM 2.5 concentrations (e.g., urban areas in Florida) and consequently failure to include these areas in the set of urban study areas is unlikely to exclude high PM 2.5 -risk locations.Draft – Do Not Quote or Cite June 2010 2-38 focus on the 13 areas that would not meet the cu rrent standards based on recent air quality (2005- 1 2007). These 13 areas have annual a nd/or 24-hour design values that are above the levels of the 2 current standards (see Tables 2-2 and 2-3). 28 Based on the core risk estimates for these areas, 3 using the proportional rollback approach, we make the following key observations regarding the 4 magnitude of risk remaining upon simulation of just meeting the current suite of standards: 5

 Long-term exposure-related mortality risk remaining : IHD-related mortality 6 attributable to long-term PM 2.5 exposure was estimated to range from less than 100 to 7 approximately 2,000 cases per year. The vari ability in these estim ates reflect, to a 8 great extent, differences in the size of study area populations. These estimates 9 represent from 4 to 17% of all IHD-related mortality in a given year for the urban 10 study areas, representing a measure of risk that takes into account differences in 11 population size and baseline mortal ity rates (see Table 2-2). 12

 Short-term exposure-related mortality risk remaining : CV-related mortality 13 associated with short-term PM 2.5 exposure was estimated to range from less than 10 to 14 500 cases per year. These estimates repres ent approximately 1 to 2% of total CV15 related mortality in a given year for th e urban study areas (see Table 2-3). 16

 Short-term exposure-related mo rbidity risk remaining: CV-related hospitalizations 17 were estimated to range from approximately 10 to 800 cases per year across the study 18 areas, which is approximatel y equivalent to less than 1% of total CV-related 19 hospitalizations (see Table 2-3). 20 Although long- and short-term exposure-related mortality have similar patterns (in terms 21 of the subset of urban study ar eas experiencing risk reductions fo r the current suite of standard 22 levels), the magnitude of risk remaining is s ubstantially lower for shor t-term exposure-related 23 mortality. These findings were expected, since, as noted earlier, changes in annual mean PM 2.5 24 concentrations were expected to drive both long- and short-term exposure-re lated risk, resulting 25 in similar overall patterns in risk reduction for both exposure periods (in terms of the subset of 26 study areas experiencing risk reductions). We no te, however, that the vari ability in the effect 27 estimates used to model short-term exposure-re lated health endpoints ac ross urban study areas 28 introduced additional variation into the pattern of risk reduction across study areas. 29

 Substantial variability exists in the magnitude of risk re maining across study areas: 30 Estimated risks remaining upon just meeti ng the current suite of standards vary 31 substantially across study areas, even when considering risks normalized for 32 differences in population size and baseline in cidence rates. This variability is a 33 consequence of the substantial di fferences in the annual mean PM 2.5 concentrations 34 across study areas that result from simulating just meeting the current standards. This 35 is important because, as discussed above , annual mean concentrations are highly 36 correlated with both long- and short-term exposure-related risk. This variability in 37

28 Of the 15 study areas, only Dallas and Phoenix have both annual and 24-hour design values below the levels of the current standards based on 2005-2007 air quality.Draft – Do Not Quote or Cite June 2010 2-39 annual mean PM 2.5 concentrations occurred especially in those study areas in which 1 the 24-hour standard is the “cont rolling” standard. In su ch areas, the variability in 2 estimated risks across study areas was larges t when regional patterns of reductions in 3 PM 2.5 concentrations were simulated, usi ng the proportional rollback approach, as 4 was done in the core analyses. Less vari ability was observed when more localized 5 patterns of PM 2.5 reductions were simulated using the locally-focused rollback 6 approach, as was done in a se nsitivity analysis. When simulations were done using 7 the locally-focused rollback approach, es timated risks remaining upon just meeting 8 the current suite of standards were appreciably larger than those estimated in the core 9 analysis (US EPA, 2010a, section 4.3.1.1). 10

 Simulation of just meeting the current su ite of standards results in annual mean PM 2.5 11 concentrations well below the current standard for some study areas: In simulating 12 just meeting the current suite of standa rds, the resulting composite monitor annual 13 mean PM 2.5 concentrations ranged from about 15 μg/m 3 (for those study areas in 14 which the annual standard was controlling) down to as low as about 8 μg/m 3 (for 15 those study areas in which the 24-hour sta ndard was controlling or the annual mean 16 concentration was well below 15 μg/m 3 based on recent air quality). As discussed 17 above, as the composite monitor annual mean PM 2.5 concentrations used in generating 18 risk estimates extend below 11.0 μg/m 3 (one SD below the mean for the 1999-2000 19 ACS monitoring period, Krewski et al., 2009) we have increasingly less confidence in 20 the risk estimates, with confidence decr easing significantly as composite monitor 21 concentrations approach the LM L for the ACS dataset (5.8 μg/m 3 ). Typically, for the 22 15 urban study areas assessed, the locatio ns where the 24-hour standard was the 23 controlling standard were simulated to ha ve the lowest composite monitor annual 24 mean PM 2.5 concentrations. We observe that all four of the urban study areas with 25 simulated composite monitor annual mean PM 2.5 concentrations below 11 μg/m 3 have 26 the 24-hour standard controlling (U.S.EPA, 2010a, Table 3-4). While such locations 27 often are estimated to have the greatest risk reductions, ther e is also reduced 28 confidence associated with these risk estimates. 29

 To what extent are the risks remaining upon simulation of the current suite of 30 standards important from a public health perspective? 31 Estimates of long-term exposure-related I HD mortality risk under simulation of the 32
current suite of standard levels range from less than 100 deaths per year for the urban study area 33 with the lowest risk to approximately 2,000 deat hs per year for the urban study areas with the 34 greatest risk. Estimates of risk for the urban areas included in the RA sugge st that IHD mortality 35 related to long-term PM 2.5 exposure would likely be in the th ousands of deaths per year on a 36
national scale. Based on these risk estimates fo r IHD mortality alone, we conclude that risks 37 estimated to remain upon simulation of the current suite of standards are important from a public 38 health standpoint. This reflects co nsideration of both the severity of the effect and the magnitude 39
of the effect. We have also es timated risks for long-term exposur e related mortality risk related 40 to cardiopulmonary effects and lung cancer, which increase th e total annual incidence of 41Draft Do Not Quote or Cite June 2 010 Table 2-2. Estimated Incidence and Percent of Total Annual Incidence Associated with 1 Long-term PM 2.5 Exposure Based on Simulation of the Current Suite of 2 Standards (for IHD mortality based on 2007 PM 2.5 Concentrations) 1,2 3 4

Exposure Period: 1979-1983 Exposure Period: 1999-2000 Exposure Period: 1979-1983 Exposure Period: 1999- 2000

220 277 13.2% 16.7% (180 - 258) (227 - 324) (10.9% - 15.5%) (13.7% - 19.5%) 297 374 11.7% 14.7% (243 - 349) (307 - 440) (9.6% - 13.7%) (12.1% - 17.3%) 131 165 10.9% 13.8% (107 - 154) (135 - 194) (8.9% - 12.9%) (11.3% - 16.2%) 195 247 9% 11.4% (159 - 230) (202 - 291) (7.3% - 10.6%) (9.3% - 13.4%) 377 478 9.1% 11.5% (308 - 445) (390 - 563) (7.4% - 10.7%) (9.4% - 13.5%) 77 98 6.7% 8.5% (63 - 92) (80 - 116) (5.5% - 8%) (7% - 10.1%)

344 434 10.7% 13.6% (281 - 405) (355 - 511) (8.8% - 12.6%) (11.1% - 16%) 860 1094 6.1% 7.7% (701 - 1018) (890 - 1296) (4.9% - 7.2%) (6.3% - 9.1%) 1755 2222 9.3% 11.8% (1435 - 2070) (1814 - 2620) (7.6% - 11%) (9.6% - 13.9%) 261 330 10.5% 13.2% (214 - 308) (270 - 389) (8.6% - 12.3%) (10.8% - 15.6%) 317 402 6.7% 8.5% (258 - 374) (327 - 476) (5.5% - 7.9%) (6.9% - 10.1%) 256 324 9.3% 11.8% (209 - 302) (264 - 382) (7.6% - 11%) (9.6% - 13.9%) 15 19 2.9% 3.7% (12 - 18) (16 - 23) (2.4% - 3.4%) (3% - 4.4%)

446 563 11.2% 14.2% (365 - 525) (461 - 662) (9.2% - 13.2%) (11.6% - 16.7%) 38 49 3.7% 4.7% (31 - 46) (40 - 58) (3% - 4.4%) (3.8% - 5.6%) Risk Assessment Location Incidence of Ischemic Heart Disease Mortality Associated with Long-term Exposure to PM 2.5 3 Percent of Incidence of Ischemic Heart Disease Mortality Associated with Long-term Exposure
to PM 2.5 3

Atlanta, GA

Baltimore, MD

Birmingham, AL

Dallas, TX

Detroit, MI

Fresno, CA

Houston, TX

Los Angeles, CA

New York, NY

Philadelphia, PA

Phoenix, AZ

Pittsburgh, PA

Salt Lake City, UT

St. Louis, MO

Tacoma, WA

1 The current primary PM 2.5 standards include an annual standard set at 15 μg/m 3 and a 24-hour standard set at 35 μg/m 3

. 2 Numbers rounded to the nearest whole number. Numbers in parentheses are 95% confidenc e or credible intervals based on statist ical uncertainty surrounding the PM coefficient. 3 Estimates based on Krewski et al. (2009), using ambient PM 2.5 concentrations from 1979 - 1983 and from 1999-2000, respectively. Incidence is for 30+ year olds within each urban study area. 5 6Draft ' o 1 ot Quote or Cite June 2010 Table 2-3. Estimated Incidence and Percent of Total Annual Incidence Associated with 1 Short-Term PM 2.5 Exposure Based on Simulation of the Current Suite of 2 Standards (CV mortality and hosp ital admissions based on 2007 PM 2.5 3 concentrations) 1,2 4 5

32 41 0.8% 0.4% (-33 - 95) (-27 - 109) (-0.8% - 2.4%) (-0.2% - 1%) 62 216 1.6% 1.3% (-4 - 126) (159 - 273) (-0.1% - 3.2%) (1% - 1.7%) -1 16 0% 0.3% (-42 - 40) (-11 - 43) (-1.5% - 1.5%) (-0.2% - 0.9%) 29 28 0.8% 0.3% (-19 - 76) (-18 - 73) (-0.5% - 2.2%) (-0.2% - 0.7%) 60 233 1% 1.1% (-8 - 127) (171 - 295) (-0.1% - 2.2%) (0.8% - 1.4%) 12 23 0.7% 0.5% (-9 - 33) (0 - 46) (-0.5% - 2%) (0% - 0.9%)

46 56 0.9% 0.3% (-31 - 122) (-37 - 149) (-0.6% - 2.4%) (-0.2% - 0.8%) -30 258 -0.2% 0.5% (-132 - 72) (3 - 511) (-0.7% - 0.4%) (0% - 0.9%) 473 752 2.1% 1.2% (276 - 668) (552 - 951) (1.2% - 3%) (0.8% - 1.5%) 84 203 2.1% 1.3% (22 - 145) (149 - 257) (0.5% - 3.6%) (0.9% - 1.6%) 84 108 1.3% 0.5% (-4 - 170) (1 - 215) (-0.1% - 2.7%) (0% - 1%) 43 140 1.1% 1.1% (-9 - 93) (103 - 177) (-0.2% - 2.3%) (0.8% - 1.4%) 9 9 0.8% 0.4% (-2 - 20) (0 - 18) (-0.2% - 1.7%) (0% - 0.7%)

106 178 1.9% 1.3% (24 - 187) (131 - 225) (0.4% - 3.3%) (0.9% - 1.6%) 11 19 0.7% 0.5% (-6 - 27) (-46 - 82) (-0.4% - 1.8%) (-1.3% - 2.3%) Risk Assessment Location Percent of Incidence of Cardiovascular Mortality Associated

with Short-term Exposure to PM2.5 3 Percent of Incidence of Cardiovascular Hospital Admissions Associated with Short-term Exposure to PM2.5 4 Incidence of Cardiovascular Mortality Associated

with Short-term Exposure to PM2.5 3 Incidence of Cardiovascular Hospitalizations A ssociated with Short

term Exposure to
PM2.5 4

Atlanta, GA

Baltimore, MD

Birmingham, AL

Dallas, TX

Detroit, MI

Fresno, CA

Houston, TX

Los Angeles, CA

New York, NY

Philadelphia, PA

Phoenix, AZ

Pittsburgh, PA

Salt Lake City, UT

St. Louis, MO

Tacoma, WA

1 The current primary PM 2.5 standards include an annual standard set at 15 μg/m 3 and a 24-hour standard set at 35 μg/m 3

. 2 Percents rounded to the nearest tenth. Numbers in parentheses ar e 95% confidence or credible intervals based on statistical u ncertainty surrounding the PM coefficient. 3 Based on location-specific single pollutan t 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. 4 Incidence estimates were calculated using the appropriate regi onal concentration-response func tion estimates reported in Table 2 of Bell et al. (2008). Location-specific C-R function esti mates were not available from this study. 6 7

8
9
10

. 11Draft – Do Not Quote or Cite June 2010 2-42 mortality attributable to long-term PM 2.5 exposure (see U.S. EPA, 2010a, section 4.2.1). 1 In addition to long-term exposure-related mo rtality, we estimated cardiovascular and 2 respiratory-related mortality risk associated with short-term PM 2.5 exposure. We note that these 3 mortality estimates are up to an order of magnit ude smaller than estimates related to long-term 4 exposure-related mortality. 29 As part of the RA, we also estimated respiratory and 5 cardiovascular-related hospital admissions as we ll as asthma-related emergency department 6 visits associated with short-term exposure to PM 2.5 , with estimates of cardiovascular and 7 respiratory hospital admissions together rangi ng up to approximately 1,000 admissions per year 8 across the urban study areas, with the estimated incidence of asthma-related emergency 9 department visits being several fold higher. Further, as disc ussed in section 2.2.1, we recognize 10 that the currently available scientific informati on includes evidence for a br oader range of health 11 endpoints and susceptible populations beyond thos e included in the quantitative RA, including 12 lung function growth and respiratory symptoms in children and reproductive and developmental 13 effects. Taken together, the set of quantitative risk estimates related to long- and short-term 14

PM 2.5 exposure, together with cons ideration of the health en dpoints which could not be 15 quantified, further strengthen the conclusion that risks estimated to remain following simulated 16
attainment of the current suite of standards are important from a public health perspective, both 17 in terms of severity and magnitude. 18

2.2.3 Staff Conclusions on Adequacy of Current Standards 19 Collectively, taking into consideration the responses to specific questions focusing on 20 different ways to address the adeq uacy of the current suite of PM 2.5 standards, we revisit the 21 overarching policy question: does th e currently available scientific evidence and risk-based 22 information support or call into question the ade quacy of the protection afforded by the current 23 suite of fine particle standards? 24 With respect to evidence-based considerati ons, the currently available evidence provides 25 stronger evidence beyond what was available in the last review, that associations between short26 and long-term PM 2.5 exposures and a broad range of adverse health effects exis t. The currently 27 available information strengthens the associations between PM 2.5 and mortality and 28 cardiovascular and respiratory morbidity effects observed in the last review and expands our 29 understanding of a broader range of health outcomes as well as our understanding of effects in 30 susceptible populations. The currently available evidence provides support for associations that 31
extend to lower concentrations than what had be en observed in the last review, including at 32

29 Estimates of short-term exposure-re lated and long-term exposure-related mo rtality should not be added because there is the potential for overlap (i.e., the long-term exposure-related mortality estimate picking up some of the short-term exposure-related signal on a daily basis, aggregated over the year).Draft – Do Not Quote or Cite June 2010 2-43 ambient concentrations below the levels of the current standards providing the basis for 1
consideration of alternative standards that would provide increased protection beyond that 2 afforded by the current PM 2.5 standards. 3
In relation to risk-based considerations for informing our understand ing of the adequacy 4 of the current fine particle standa rds, we focus on the estimates of PM 2.5 -related mortality and 5 morbidity effects likely to remain upon simulations of just meeting the current standards in a 6 number of example urban areas. In consideri ng the core risk estimates together with our 7 understanding of the uncertainties in these estimates, based upon extensive sensitivity analyses, 8
we conclude that the risks estimated to be associ ated with just meeting the current standards can 9 reasonably be judged to be important from a public health perspective. We further conclude that 10 these estimated risks provide support for consid eration of alternative standards that would 11 provide increased protection beyond that afforded by the current PM 2.5 standards. 12 We recognize that important uncertaintie s and research questions remain when 13 considering both evidence- and risk -based approaches. Nonetheless, we note that much progress 14 has been made in reducing some key uncertainti es since the last revi ew, including important 15 progress in advancing our unde rstanding of potential mech anisms by which ambient PM 2.5 is 16 causally linked with mortality, cardiovascular, and respiratory effects observed in 17 epidemiological studies. Additional information continues to emerge for a broader range of 18 health effects including reproducti ve and development effects and more information is available 19 to understand susceptible populations including children, older adults, individuals with pre20 existing cardiovascular and respir atory disease, persons at lower SES, and persons with genetic 21 susceptibility. 22
As was true in the last re view, we recognize that as th e body of available evidence has 23 expanded, it has added greatly both to our knowledge of health effects associated with fine 24 particle exposures, as well as to the complexity inherent in interpreting the evidence in a policy25 relevant context as a basis for setting appropriate standards. In evaluating both evidence-based 26 and risk-based considerations, along with associat ed limitations and uncertainties, we reach the 27 conclusion that the available information clearly calls into question the adequacy of the current 28
suite of PM 2.5 standards and provides strong support fo r giving consideration to revising the 29 current standards to provide in creased public health protection. 30

2.3 CONSIDERATION OF ALTERNATIVE STANDARDS 31 Having reached the conclusion that the currently available scie ntific evidence calls into 32 question the adequacy of the current suite of PM 2.5 standards, staff considers a second 33 overarching question: 34Draft – Do Not Quote or Cite June 2010 2-44 What alternative suites of fine particle st andards are supported by the currently available 1 scientific evidence and risk-based inform ation, as reflected in the ISA and RA? 2 To inform the answer to this overarching que stion, we have posed a series of more 3 specific questions to inform decisions regardin g the basic elements of the NAAQS: indicator 4 (section 2.3.1), averaging time (section 2.3.2), form (section 2.3.3), and level (section 2.3.4). 5 These elements are considered collectively in evaluating the health protection afforded by 6
alternative suites of standards under consideration. In consid ering the currently available 7
scientific and technical informati on, we consider both the information available in the last review 8 and information that is newly available since the la st review as assessed and presented in the ISA 9 and RA prepared for this review (US EPA, 2009a; US EPA, 2010a). 10

2.3.1 Indicator 11 In initially setting standards for fine pa rticles in 1997, EPA concluded it was more 12 appropriate to control fine part icles as a group, rather than sing ling out any particular component 13 or class of fine particles for which only very limited evidence wa s available. In establishing a 14 size-based indicator to distinguis h fine particles from particles in the coarse mode, EPA noted 15 that the available epidemiological studies of fine particles were based largely on PM 2.5 and also 16 considered monitoring technology th at was generally available. The selection of a 2.5 μm size 17 cut reflected the regulatory importance of defi ning an indicator that would more completely 18 capture fine particles under all conditions likely to be encounter ed across the U.S., especially 19 when fine particle concentrati ons are likely to be high, while r ecognizing that some small coarse 20 particles would also be captured by current methods to monitor PM 2.5 (62 FR 38667 to 38668, 21 July, 18, 1997). In the last review, based on th e same considerations, EPA again recognized that 22 the available information supported retaining the PM 2.5 indicator and remained too limited to 23 support a distinct standard for any specific PM 2.5 component or fine particle source (71 FR 61162 24 to 61164, October 17, 2006). 25

 Does the currently available information pr ovide support for the continued use of a 26 PM 2.5 mass-based indicator for fine particles? 27 In this review, epidemiological studies linki ng cardiovascular and respiratory effects as 28 well as mortality with long- and short-term fine pa rticle exposures continue to be largely indexed 29 by PM 2.5 . Based on the same considerations that informed the last two reviews, we again 30 conclude that it is appropriate to retain a PM 2.5 indicator to provide pr otection associated with 31 long- and short-term expos ure to fine particles. 32Draft – Do Not Quote or Cite June 2010 2-45 We also look to the expanded body of eviden ce available in this review to consider 1
whether there is sufficient evid ence to support a separate standard for ultrafine particles 30 (UFPs) 2
and whether there is sufficient evidence to esta blish distinct standards focused on regulating 3 specific PM 2.5 components or sources of fine pa rticles, as addressed below. 4

 To what extent does the currently ava ilable information provide support for 5 considering a separate indicator for UFPs? 6

A number of studies available in this review have focuse d on UFPs, as a subset of PM 2.5
. 7 As noted in the ISA, the enormous number a nd larger surface area of UFPs are important 8 considerations for focusing on this subfraction of fine particles in assessing potential public 9 health impacts (US EPA, 2009a, p. 6-83). 31 Per unit mass, UFPs may have more opportunity to 10
interact with cell surf aces due to their greate r surface area and their gr eater particle number 11 compared with larger particles (US EPA, 2009a, p. 5-3). Greater surface area also increases the 12 potential for soluble components (e.g., transition metals, organi cs) to adbsorb to UFPs and 13 potentially cross cell membranes and epithelia l barriers (US EPA, 2009a, p. 6-83). . In 14 addition, evidence available in th is review suggests that the ab ility of particles to enhance 15 allergic sensitization is associated more strongly with par ticle number and surface area than 16 particle mass (US EPA, 2009a, p. 6-127). 32 17 New evidence, primarily from controlled human exposure and toxicological studies, 18 expands our understanding of UFP-re lated cardiovascular and respirator y effects. However, this 19 evidence is still very limited a nd largely focused on exposure to diesel exhaust (DE), for which 20
the ISA concludes “it is unclear if the effects observed are due to UFP, larger particles (i.e., 21

PM 2.5 ), or the gaseous components of DE” (US EPA, 2009a, p. 2-22). In addition, the ISA notes 22
uncertainties associated with the controlled human exposure studies as concentrated ambient 23 particle (CAP) systems have b een shown to modify the composition of UFPs (US EPA, 2009a, p. 24 2-22, see also section 1.5.3). Relatively few ep idemiological studies have examined potential 25 cardiovascular and respiratory e ffects associated with short-te rm exposures to UFPs. These 26 studies have reported inconsistent and mixe d results (US EPA, 2009a, section 2.3.5). 27 Collectively, in considering the body of scien tific evidence available in this review, the 28 ISA concludes that the currently available evidence is suggestive of a c ausal association between 29 short-term exposures to UFPs a nd cardiovascular and respiratory e ffects. Furthermore, the ISA 30

30 Ultrafine particles, generally including particles with a nominal aerodynamic diamet er less than 0.1 μm, are emitted directly to the atmosphere or are formed by nucl eation of gaseous constituents in the atmosphere (US EPA, 2009a, p. 3-3).
31 Particle number is most highly concentrated in the U FP fraction with volume (or mass) most concentrated in the larger size fractions (US EPA, 2009a, p. 3-2).
32 More information on possible modes of action for effects associated with UFPs exposures is discussed in sections 5.1 and 5.4 of the ISA.Draft – Do Not Quote or Cite June 2010 2-46 concludes that evidence is inadequate to infer a causal association between short-term exposure 1 to UFPs and mortality as well as long-term exposure to UFPs and all outcomes evaluated (US 2 EPA, 2009a, sections 2.3.5, 6.2.12.3, 6.3.10.3, 6.5.3.3, 7.2.11.3, 7.3.9, 7.4.3.3, 7.5.4.3, and 3 7.6.5.3; Table 2-6). 4 With respect to our understanding of ambient UFP concentrations, at present, there is no 5 national network of UFP samplers; thus, only epis odic and/or site-specifi c data sets exist (US 6 EPA, 2009a, p. 2-2). 33 Therefore, a national characterization of concentrations, temporal and 7 spatial patterns, and trends is not possible, and the availability of ambient UFP measurements to 8 support health studies are extremely limited. In general, measurements of UFPs are highly 9 dependent on monitor location and, therefore, mo re subject to exposure error than accumulation 10 mode particles (US EPA, 2009a, p. 2-22). The UFP number concentrations fall off sharply 11 downwind from sources, as UFPs may grow in to the accumulation mode by coagulation or 12 condensation (US EPA, 2009a, p. 3-89). Limited st udies of UFP ambient measurements suggest 13 these particles exhibit a high degr ee of spatial and temporal he terogeneity driven primarily by 14 differences in nearby source characteristics (US EPA, 2009a, p. 3-84). Internal combustion 15 engines and, therefore, roadways are a notable source of UFPs, so concentrations of UFPs near 16 roadways are generally expected to be elevated (US EPA, 2009a, p. 2-3) . Concentrations of 17 UFPs have been reported to drop off much mo re quickly with distance from roadways than 18 larger particle sizes (US EPA, 2009a, p. 3-84). 19 In considering both the currently available heal th effects evidence and the air quality data 20 for UFPs, we conclude that this information is still too limited to support a distinct PM standard 21
for UFPs. 22

 To what extent does the currently ava ilable information provide support for 23 considering a separate indicator for a specific PM 2.5 component or source category of 24 fine particles? Conversely, to what extent does the currently available information 25 provide support for eliminating any component or source category from the mix of fine 26 particles included in the PM 2.5 indicator? 27 In addressing the issue of particle composition, the ISA concludes that, “[f]rom a 28 mechanistic perspective, it is highly plausible th at the chemical composition of PM would be a 29 better predictor of health effects than partic le size” (US EPA, 2009a, p. 6-202). Heterogeneity of 30
ambient concentrations of PM 2.5 constituents (e.g., elemental carbon (EC), organic carbon (OC), 31 sulfates, and nitrates) observed in different geographical regions as well as regional 32 heterogeneity in PM 2.5 -related health effects reported in a numb er of epidemiological studies are 33 consistent with this hypothesis (US EPA, 2009a, section 6.6). 34

33 The ISA contains a review of the current scientific information related to measur ements of UFPs (US EPA, 2009a, sections 3.5.1 and 3.5.2).Draft – Do Not Quote or Cite June 2010 2-47 With respect to the availabil ity of ambient measurement data for fine particle components 1 in this review, there are now more extensive ambient PM 2.5 speciation measurement data 2 available through the Chemical Speciation Network (CSN). 34 Data from the CSN monitoring 3 network provide further evidence of sp atial and seasonal variation in both PM 2.5 mass and 4 composition among cities/regions (US EPA, 2009a , pp. 3-50 to 3-60; Figures 3-12 to 3-18; 5 Figure 3-47). Some of this va riation may be related to regi onal differences in meteorology, 6 sources, and topography (US EPA, 2009a, p. 2-3). 7 The currently available epidemiological, to xicological, and contro lled human exposure 8
studies have evaluated the health effects associated with ambient PM 2.5 constituents and 9 categories of fine particle sources, using a variet y of quantitative methods applied to a broad set 10
of PM 2.5 constituents, rather than selecting a few cons tituents a priori (US EPA, 2009a, p. 2-26). 11 Epidemiological studies have used measured ambient PM 2.5 speciation data, including 12 monitoring data from the CSN, while all of th e controlled human exposure and most of the 13 toxicological studies have used CAPs and analyzed the constituents th erein (US EPA, 2009a, p. 14 6-203). 35 The CSN provides PM 2.5 speciation measurements gene rally on a one-in-three or one15 in-six day schedule and, thus, do not capture data every day at most sites. To expand our 16 understanding of the role of specific PM 2.5 components and sources with respect to the observed 17 health effects, researchers have expresse d a strong interest in having access to PM 2.5 speciation 18 measurements collected more frequently. 36 19 With respect to epidemiological studies evalua ting short-term exposures to fine particle 20 constituents, several new multi-city studies are now available. These studies continue to show an 21 association between mortality and cardiovascular and/or respiratory morbidity effects and short- 22

34 The CSN consists of 54 Speciation Trends Network (STN ) sites as well as about 150 SLAMS supplemental sites across the country measuring over 40 chemical species. A limited number of CSN monitors began collecting ambient data in 2000 with the majority of sites collecting data starting in 2001. These sites collect aerosol samples over 24 hours on filters that are analyzed for PM 2.5 mass, trace elements, major ions (e.g., sulfates, nitrates, ammonium), and EC/OC.
35 Most studies considered between 7 to 20 ambient PM 2.5 constituents, with EC, OC, sulfate, nitrate, and metals most commonly measured. Many of the studies grouped the constituents with various factorization or source apportionment techniques to examine the relationship between the grouped constituents and various health effects. However, not all studies labeled the constituent groupings according to their presumed source and a small number of controlled human exposure and toxicological studies did not use any constituent grouping. These differences across studies substantially limit any integrative interpretati on of these studies (US EPA, 2009a, p. 6-203).
36 As outlined in section 6.6.2.11of th e ISA, some investigators have circumvented the issue of less than daily speciation data by using the PM 2.5 chemical species data in a second stage re gression to explain the heterogeneity in PM 10 or PM 2.5 mortality risk estimates across cities and assuming that the relative contributions of PM 2.5 have remained the same over time (US EPA, 2009a, p. 6-206). In April 2008, EPA co-sponsored a workshop to discuss modifications to the current ambient air quality monitoring networks that would advance our understanding of the impacts of PM exposures on public health/welfare in the most meaningful way, including improving our understanding of fine particle components. A summary of the workshop recommendations, including recommendations for daily PM 2.5 speciation measurements in larg e urban areas, is available at www.epa.gov/ORD/npd/pdfs/FINAL-April-2008-AQ-Health-Research-Workshop-Summary-Dec-2008.pdf

.Draft – Do Not Quote or Cite June 2010 2-48 term exposures to various PM 2.5 components including nickel (Ni) , vanadium (V), EC, OC, and 1 sulfates (US EPA, 2009a, sections 6.5.2.5 and 6.6). Lippmann et al. (2006) and Dominici et al. 2 (2007) evaluated the heterogeneity in the PM 10 –mortality association as evaluated in the 3 NMMAPS data by analyzing the PM 2.5 speciation data. Nickel a nd V were identified as 4 significant predictors of variation in PM 10 -related mortality across citi es, with Ni levels in New 5 York City being reported as particularly high (US EPA, 2009a, sect ion 6.5.2.5; Figure 6-31). 37 6 Bell et al. (2009) and Peng et al . (2009) conducted similar analys es focusing on the variation in 7

PM 2.5 -related cardiovascular and resp iratory hospital admissions in older adults. Peng et al. 8 (2009) focused on the components th at make up the majority of PM 2.5 mass and using multi9 pollutant models reported only EC and OC we re significantly associ ated with risk of 10 hospitalization for cardiovascular disease. Be ll et al. (2009) used data from twenty PM 2.5 11 components and found that EC, Ni, and V were most positively and significan tly associated with 12
the risk of PM 2.5 -related hospitalizations s uggesting that the observed associations between PM 2.5 13 and hospitalizations may be primarily due to part icles from oil combustion and traffic (US EPA, 14 2009a, section 6.2.10.1). In a study of 25 U.S. cities, Franklin et al. (2008) focused on a time15 series regression of mo rtality related to PM 2.5 mass by season and also examined effect 16
modification due to various PM 2.5 species. They concluded that Al, As, Ni, Si and sulfates were 17 significant effect modifiers of PM 2.5 mortality risk estimates, and “simultaneously including Al, 18 Ni, and sulfates together or Al, Ni, and As together further incr eased explanatory power. Of the 19 species examined, Al and Ni explained the mo st residual heterogeneity ” (US EPA, 2009a, p. 6- 20 194; Table 6-17). 38 Furthermore, Ostro et al (2006 ) examined associations between PM 2.5 21 components and mortality in six California count ies and found an association between mortality, 22 especially cardiovascular-related mortality and several PM 2.5 components including EC, OC, 23 nitrates, iron (Fe), potassium (K), and titanium (Ti) at various lags (US EPA, 2009a, p. 6-195). 24
Limited evidence is available to evaluate th e health effects associated with long-term 25 exposures to PM 2.5 components (US EPA, 2009a, section 7.6.2). The most significant new 26 evidence is provided by a study that evaluated multiple PM 2.5 components and an indicator of 27 traffic density in an assessment of health effects related to long-term exposure to PM 2.5 (Lipfert 28 et al., 2006). Using health data from a cohort of U.S. military veterans and PM 2.5 data from 29 EPA’s CSN, Lipfert et al. (2006) reported positive asso ciations between mort ality and long-term 30 exposures to nitrates, EC, Ni and V as well as traffic density and peak O 3 concentrations. 31 Additional evidence from a long-term exposur e study conducted in a Dutch cohort provides 32

37 However, as noted in the ISA, in a sensitivity analysis when selectively removing cities from the overall estimate, the significant association between the PM 10 mortality risk estimate and the PM 2.5 Ni fraction was diminished upon removing New York City from the analysis, which is consistent with the results presented by Dominici et al. (2007) (US EPA, 2009a, section 6.5.2.5; Figure 6-32).
38 We note that New York City was not included in the 25 cities examined by Franklin et al. (2008).Draft – Do Not Quote or Cite June 2010 2-49 supportive evidence that long-term exposure to tr affic-related particles is associated with 1 increased mortality (Breelen et al., 2008). 2 With respect to source categories of fine pa rticles associated with a range of health 3 endpoints, the ISA reports that currently available evidence suggests associat ions between 4 cardiovascular effects and a number of specific PM 2.5 –related source categories, specifically oil 5 combustion, wood or biomass burning, motor vehicle emissions, and crustal or road dust sources 6 (US EPA, 2009a, section 6.6; Table 6-18). In add ition, a few studies have evaluated associations 7
between PM 2.5 –related source categories and mortality. Thes e studies included a reported 8 association between mortality and a PM 2.5 coal combustion factor (L aden et al., 2000), while 9 others linked mortality to a secondary sulfate long-range transport PM 2.5 source (Ito et al., 2006; 10 Mar et al., 2006) (US EPA, 2009a, section 6.6.2.1). There is less consistency in associations 11
observed between PM 2.5 sources and respiratory health effects, which may be partially due to the 12 fact that fewer studies have evaluated respiratory-related outcomes and measures. However, 13 there is some evidence for associations with secondary SO 4 2– .and decrements in lung function in 14 asthmatic and healthy adults (US EPA, 2009a, p. 6-211; Gong et al., 2005; Lanki et al., 2006). 15 Respiratory effects relating to the crustal/soil/r oad dust and traffic sources of PM have been 16 observed in asthmatic children and adults (US EP A, 2009a, p. 6-205; Gent et al., 2009; Penttinen 17 et al., 2006). 18 Recent studies have shown that source apportio nment methods have the potential to add 19 useful insights into which sources and/or PM constituents may contribute to different health 20 effects. Of particular inte rest are several epidemiological studies that compared source 21 apportionment methods and reporte d consistent results across re search groups (US EPA, 2009a, 22 p. 6-211; Hopke et al., 2006; It o et al., 2006; Mar et al., 2006; Thurston et al., 2005). These 23 studies reported associations between total morta lity and secondary sulfate in two cities for two 24 different lag times. The sulfate effect was str onger for total mortality in Washington D.C. and 25 for cardiovascular-related morality in Phoenix (U S EPA, 2009a, p. 6-204). These studies also 26
found some evidence for associations with mort ality and a number of source categories (e.g., 27 biomass/wood combustion, traffic, copper smelter, coal combustion, sea salt) at various lag times 28 (US EPA, 2009a, p. 6-204). Sarn at et al., (2008) compared thr ee different source apportionment 29 methods and reported consistent associations between ED visits for cardiovascular diseases with 30 mobile sources and biomass combustion as well as increased respiratory-related ED visits 31 associated with secondary sulfate (US EPA, 2009a, pp. 6-204 and 6-211; Sarnat et al., 2008). 32 In summary, in considering the currently ava ilable evidence for health effects associated 33 with chemical components and source categories of PM 2.5 as presented in the ISA, we conclude 34
that additional information available in this review continues to pr ovide evidence that many 35 different constituents of the fine particle mixture as well as specific source categories of fine 36Draft – Do Not Quote or Cite June 2010 2-50 particles are linked to adve rse health effects. However, as no ted in the ISA, while “[t]here is 1 some evidence for trends and patterns that link particular ambient PM constituents or sources 2 with specific health outcomes...there is insufficient evidence to determine whether these patterns 3 are consistent or robust” (US EPA, 2009a, p. 6-2 10). Furthermore, the ISA concludes that “the 4 evidence is not yet sufficient to allow differentia tion of those constituents or sources that are 5 more closely related to specific health out comes” (US EPA, 2009a, pp. 2-26 and 6-212). 6 Therefore, we conclude that the currently av ailable evidence is not sufficient to support 7 consideration of a separate indicator for a specific PM 2.5 component or source category of fine 8 particles. We also conclude that the evid ence is not sufficient to support eliminating any 9 component or source from the mix of fine particles included in the PM 2.5 indicator. 10 Summary 11 In considering whether curre ntly available evidence pr ovides support for retaining, 12 revising, or supplementing the current PM 2.5 mass-based indicator, we fi rst conclude that it is 13 appropriate to retain PM 2.5 as the indicator for fine particle s. Secondly, we conclude that the 14 currently available evidence doe s not provide a sufficient basis for supplementing the mass15
based PM 2.5 indicator by considering a sepa rate indicator for ultrafine particles as a subfraction 16 of fine particles. We also conc lude that the currently available evidence is too limited to provide 17 support for considering a separate indicator for a specific PM 2.5 component or source category of 18 fine particles or for eliminating any individual component or source category from the mix of 19 fine particles included in the PM 2.5 mass-based indicator. 20

2.3.2 Averaging Times 21 In 1997, EPA initially set both an annual sta ndard, to provide prot ection from health 22 effects associated with both long- and short-term exposures to PM 2.5 , and a 24-hour standard to 23 supplement the protection afforded by the annual sta ndard. In the last review, EPA retained both 24 annual and 24-hour averaging times (62 FR 38667 to 38668, July, 18, 1997). 25 In this review, we consider whether the cu rrently available inform ation provides support 26 for maintaining standards with annual and 24-hour averaging times and whether there is 27 sufficient evidence to suppor t setting standards with other aver aging times to address subdaily or 28 seasonal exposures. 29

 To what extent does the currently available information continue to provide support for 30 annual and 24-hour averaging times? 31 The overwhelming majority of st udies conducted since the last review continue to utilize 32 annual and 24-hour averaging times, and largely contribute to the body of evidence for health 33
effects related to both short-te rm (from less than 1 day to up to several days) and long-term 34Draft – Do Not Quote or Cite June 2010 2-51 (from a year to several years) measures of PM 2.5 . Consequently, we conc lude that the currently 1 available evidence continues to support annual and 24-hour averaging times. 2

 To what extent does the currently availabl e scientific evidence provide support for 3 considering a standard with an averaging ti me less than 24 hours to address health 4 effects associated with subdaily fine particle exposures? 5

Relative to information available in the la st review, recent studies provide additional 6
evidence for cardiovascular effects associated wi th subdaily (e.g., one to several hours) exposure 7 to PM, especially effects related to cardiac ischemia, vasomotor function, and more subtle 8 changes in markers of systemic inflammation, he mostasis, thrombosis and coagulation (US EPA, 9 2009a, section 6.2). 39 Because these studies have used different indicators (e.g., PM 2.5 , PM 10 , 10

PM 10-2.5 , UFPs), averaging times (e.g., 1, 2, and 4 hours) , and health outcomes, it is difficult to 11
draw conclusions about cardiovascu lar effects associated specifical ly with subdaily exposures to 12

PM 2.5
. 13 With regard to respiratory eff ects associated with subdaily PM 2.5 exposures, the currently 14 available evidence is much sparser than for car diovascular effects and continues to be very 15 limited. The ISA concludes that for several studies of hospital admissions or medical visits for 16 respiratory diseases, the stronge st associations were observed with 24-hour average or longer 17 exposures, not with less then 24-hour expos ures (US EPA, 2009a , section 6.3). 18 Collectively, we conclude that this inform ation is too unclear, with respect to the 19 indicator, averaging time and heal th outcome, to serve as a basis for establishing a shorter-than20
24-hour PM 2.5 primary standard at this time. 21

 To what extent does the currently availabl e scientific evidence provide support for 22 considering separate standards with dist inct averaging times to address effects 23 associated with seasonal fine particle exposures? 24 With regard to health effects associated with PM 2.5 exposure across varying seasons in 25 this review, Bell et al . (2008) reported higher PM 2.5 risk estimates for hospitalization for 26 cardiovascular and respiratory diseases in the wi nter compared to other seasons. In comparison 27 to the winter season, smaller sta tistically significant associations were also reported between 28

PM 2.5 and cardiovascular morbidity for spring and autumn, and a positive non-significant 29
association was observed for the summer months . In the case of mortality, Zanobetti and 30 Schwartz (2009) reported a 4-fold higher effect estimate for PM 2.5 associated mortality for the 31 spring as compared to the winter. Taken toge ther, these results are inconsistent, suggesting 32

39 A limited number of additional studies have also pr ovided evidence of reported electrocardiogram changes typically representative of cardiac ischemia (S-T segment de pression) or reported changes in heart rate variability (HRV) (US EPA, 2009a, sections 6.2.1.2 and 6.2.12.1), however, these changes are often variable and difficult to interpret the PM 2.5 etiologically relevant mechanism underlying the observed effects.Draft – Do Not Quote or Cite June 2010 2-52 individuals are at greater risk of dying from higher exposures to PM 2.5 in the warmer months, and 1 at greater risk of PM associat ed hospitalization for car diovascular and respir atory diseases during 2 colder months of the year. 3 Overall, we observe that there are few studi es presently available to deduce a general 4 pattern in PM 2.5 -related risk across seasons. In addition, th ese studies utilized 24-hour exposure 5 periods within each season to assess the PM 2.5 associated health effects, and do not provide 6
information on health effects associat ed with a season-long exposure to PM 2.5 . Due to these 7 limitations in the currently available evidence, we conclude that there is no basis to consider a 8 seasonal averaging time separate from a 24-hour averaging time. 9 Summary 10 We recognize that the currently availabl e evidence informs our understanding of 11 exposure durations of concern and continues to pr ovide strong support for standards that provide 12 protection for both short- and long-term exposures . In considering the possibility of effects 13 associated with subdaily PM 2.5 exposures (i.e., less than 24-hour exposures), we recognize that 14
there is additional evidence available in this re view, primarily focused on cardiovascular effects 15 with more limited evidence for respiratory effects. However, because these studies have used 16
different indicators of PM exposure (e.g., PM 2.5, PM 10 , UFPs), averaging times, and a broad 17 range of health outcomes, it is difficult to use this evidence to serve as a basis for establishing a 18
standard with a shorter-than-24- hour averaging time. W ith respect to seasonal effects, while we 19 recognize there is some new evidence for PM 2.5 - related effects differentiated by season, we 20
conclude that this evidence is too limite d to use as a basis for establishing a PM 2.5 standard with a 21 seasonal averaging time. Based on the above cons iderations, we conclude that the currently 22 available information provides strong support for retaining the current annual and 24-hour 23 averaging times but does not provide support for considering alternative averaging times. 24

2.3.3 Forms 25 The “form” of a standard defines the air quality statistic that is to be compared to the 26 level of the standard in determining whether an area attains the standard. In this review, we 27 consider whether currently availa ble information supports consider ation of alternative forms for 28
the annual or 24-hour PM 2.5 standards. 29

2.3.3.1 Form of the Annual Standard 30

In 1997, EPA established the form of the annual PM 2.5 standard as an annual arithmetic 31 mean, averaged over 3 years, from single or multiple community-oriented monitors. This form 32 was intended to represent a relatively stable meas ure of air quality and to characterize area-wide 33

PM 2.5 concentrations. The level of the standard wa s to be compared to measurements made at 34Draft – Do Not Quote or Cite June 2010 2-53 the community-oriented monitoring site recording the highest level, or, if specific constraints 1

were met 40 , measurements from multiple community -oriented monitoring sites could be 2 averaged (62 FR 38671 to 38672, July 18, 1997). The constraints were intended to ensure that 3 spatial averaging would not result in inequities in the level of protection (62 FR 38672). This 4 approach was consistent with the ep idemiological studies on which the PM 2.5 standard was 5 primarily based, in which air quality data were ge nerally averaged across multiple monitors in an 6 area or were taken from a single monitor that was selected to represent community-wide 7 exposures, not localized “hot spots.” 8 In the last review, EPA tightened the criteria for use of spatial averaging 41 to provide 9 increased protection for vulnera ble populations exposed to PM 2.5 . This change was based in part 10 on an analysis of the potential for disproportiona te impacts on potentially vulnerable populations, 11 which found that the highest concentrations in an area tend to be measured at monitors located in 12 areas where the surrounding population is more likely to have lower education and income 13 levels, and higher percentages of minority popu lations (71 FR 61166/2; US EPA, 2005, section 14 5.3.6.1). 15 In this review, we again cons ider the potential impact of allowing for spatial averaging, 16 noting that persons from lower socioeconomic st rata have been identified as an additional 17 susceptible population (see section 2.2.1). 18

 Does the currently available evidence provide support for the continued use of spatial 19 averaging as part of the form of the annual standard? 20 In considering the potential for dispropor tionate impacts on potentially vulnerable 21 populations, we updated analyses conducted for the last review. Specifically, we evaluated 22 whether persons with a lower SES status are mo re likely than the gene ral population to live in 23 census tracts in which the monitors recording the hi ghest air quality values in an area are located. 24 Data used in this analysis included demographi c parameters measured at the census tract level, 25 including income level and percent minority populat ion. Data from the census tract in each area 26 in which the highest air quality value was mon itored were compared to the area-wide average 27 value (consistent with the constraints on spatial averaging provided by the current standard) in 28 each area (Schmidt, 2010). 29 Recognizing the limitations of such cross-sec tional analyses, we observe that the highest 30 concentrations in an area tend to be measured at monitors located in areas where the surrounding 31

40 The original criteria for spat ial averaging included: (1) the annual mean concentration at each site shall be within 20 percent of the spatially averaged annual mean, and (2) th e daily values for each monitoring site pair shall yield a correlation coefficient of at l east 0.6 for each calendar quarter.
41 The current criteria for spatial averaging include: (1) the an nual mean concentration at each site shall be within 10 percent of the spatially averaged annual mean, and (2) the daily values for each monitoring site pair shall yield a correlation coefficient of at leas t 0.9 for each calendar quarter (71 FR 61167/2-3, October 17, 2006).Draft – Do Not Quote or Cite June 2010 2-54 populations are more likely to have lower income le vels and higher percentage of minority levels. 1 Based upon this analysis, we be lieve that the existing constr aints on spatial averaging, as 2 modified in 2006, may not be adequate to avoid s ubstantially greater expo sures in some areas, 3 potentially resulting in disproportionate im pacts on persons with lower SES levels and 4 minorities. Therefore, we conclude that it is appropriate to consider a form for the annual PM 2.5 5 standard that does not allow for the use of spatia l averaging across monitors, such that the level 6
of the annual PM 2.5 standard would be compared to measur ements made at the monitoring site 7 that represents “community-wide ai r quality” recording the highest PM 2.5 concentrations. 8

2.3.3.2 Form of the 24-Hour Standard 9

In 1997, EPA established the form of the 24-hour PM 2.5 standard as the 98 th percentile of 10 24-hour concentrations at each population-oriented monitor within an area, averaged over three 11 years (62 FR at 38671 to 38674, July 18, 1997). The Agency selected the 98 th percentile as an 12 appropriate balance between adequately limiting the occurrence of peak concentrations and 13 providing increased stability which, when averaged over 3 years, facilitat ed the development of 14 more stable implementation programs. By basing the form of the standard on concentrations 15 measured at population-oriented monitoring sites, EPA intended to provide protection for people 16 residing in or near localized areas of elevated co ncentrations. In the la st review, in conjunction 17 with lowering the level of the 24-hour standard, EPA retained this form based in part on a 18 comparison with the 99 th percentile form. 42 19 In this review, we have again consid ered the relative stability of the 98 th and 99 th 20 percentile forms. 21

 Does the currently available evidence provide support for the continued use of the 98 th 22 percentile form of the 24-hour standard? 23 We recognize that the selection of the appr opriate form of the 24-hour standard includes 24 maintaining adequate protection against peak 24 -hour concentrations while also providing a 25 stable target for risk management programs, which serves to provide for the most effective 26 public health protec tion in the long run. 43 As in previous reviews, we recognize that a 27 concentration-based form provides proportionally greater weight to days when concentrations are 28

42 In reaching this final decision, EPA recognized a technical problem associated with a potential bias in the method used to calculate the 98 th percentile concentration for this form. EP A adjusted the sampling frequency requirement in order to reduce this bias. Accordin gly, the Agency modified the final mon itoring requirements such that areas that are within 5 percent of the standards are required to increase the sampling frequency to every day (71 FR 61164 to 61165, October 17, 2006).
43 See ATA III , 283 F.3d at 374-375 which concludes it is legiti mate for EPA to consider promotion of overall effectiveness of NAAQS implementation programs, including their overall stability, in setting a standard that is requisite to protect the public health.Draft – Do Not Quote or Cite June 2010 2-55 well above the level of the standard than to da ys when the concentrations are just above the 1 standard. Further, a concentration-based form compensates for missing data and less-than-every2 day monitoring; and, when averaged over 3 years, it has greater stability a nd, thus, facilitates the 3 development of more stable implementation programs. 4 In revisiting the stability of a 98 th versus 99 th percentile form for a 24-hour standard 5 intended to provide supplemental protection for a generally c ontrolling annual standard, we 6 consider air quality data re ported in 2000 to 2008 to update our understanding of the ratio 7 between peak-to-mean PM 2.5 concentrations. 44 As illustrated in Figure 2-2, the 98 th percentile 8
value is a more stable metric than the 99 th percentile. 9

Figure 2-2. Distribution of site-level variation in 98th and 99th percentile concentrations, as 10 measured by coefficient of variation (SD/Mean) 45 computed by site across years, 2000-2008 11Coefficient of variation

98 th percentile concentrations 99 th percentile concentrations 16.13 18.76

12
On this basis, we conclude that it is appropriate to consider retaining the current 98 th 13 percentile form of the 24-hour standard as it represents an appropriate balance between 14 adequately limiting the occurrence of peak c oncentrations and providing increased stability 15
relative to an alternative 99 th percentile form. In addition, by basing the form of the standard on 16 concentrations measured at popula tion-oriented monitoring sites, th e standard would continue to 17 focus on providing protection for people residing in or near localized areas of elevated 18
concentrations. 19

44 We consider a coefficient of variation instead of simply the standard deviation because the 99 th percentile values have higher concentration levels and dividing by the mean normalizes the data. In focusing on three years of recent air quality (2006 to 2008), we see a similar pa ttern of peak-to-mean ratios (Schmidt, 2010).
45 Coefficient of variation x 100.Draft – Do Not Quote or Cite June 2010 2-56 2.3.4 Alternative Levels 1 In reaching staff conclusions for alternative standard levels that are appropriate to 2 consider, we take into account both evid ence-based (section 2 .3.4.1) and risk-based 3 considerations (section 2.3.4.2) as well as the related limita tions and uncertain ties associated 4 with this information as presented and discusse d more fully in the ISA and RA (US EPA, 2009a; 5 US EPA, 2010a). Alternative le vels are discussed in conjunction with staff conclusions on other 6 elements of the standard pres ented above, notably, retaining PM 2.5 as the indicator for fine 7 particles (see section 2.3.1); retaining the current annual a nd 24-hour averaging times (see 8 section 2.3.2); modifying the current form of the annual standard (see section 2.3.3.1) and 9 retaining the current form of the 24-hour standa rd (see section 2.3.3.2). Specifically, we address 10 the following overarching question: 11

What alternative standard levels are appr opriate to consider to provide requisite 12 protection for long- and short-term PM 2.5 exposures? 13 Staff conclusions based on the integration of the evidence-based and risk-based 14 approaches are presented in section 2.3.4.3. 15

2.3.4.1 Evidence-based Considerations 16

In translating information from epidemiologi cal studies into the basis for reaching staff 17 conclusions on alternative standard levels, we apply the policy framework outlined in section 18 2.1.3. In doing so, we focus on identifying levels for a generally controlling annual standard and 19 a 24-hour standard that provides supplemental protection against days with high peak 20 concentrations especially in areas with high peak-to-mean ratios, possibly associated with strong 21 local or seasonal sources, or for potential PM 2.5 -related effects that may be associated with 22 shorter-than-daily exposure periods , that might not be well contro lled by an annual standard. 23 We address a series of specific questions be ginning with considera tion of the relative 24 weight to place on different evidence. Using th e available epidemiological evidence, we then 25 consider two approaches for identifying alternat ive annual standard levels : (1) looking directly 26 at confidence bounds on C-R relationships reported in long- and short-term exposure studies and 27 (2) exploring different statistical metrics that ch aracterize air quality dist ributions from multi-city 28 epidemiological studies. We also consider in formation on peak-to-mean air quality ratios in 29 reaching conclusions regarding 24-hour standard levels that are appropriate to consider. 30

 What factors do we weigh in placing emphasi s on epidemiological evidence to translate 31 this information into staff conclusi ons on alternative standard levels? 32 As discussed in section 2.1.3, we initia lly focus on long- and short-term PM 2.5 multi-city 33 exposure studies conducted in the U.S. and Canada and place the greatest weight on associations 34Draft – Do Not Quote or Cite June 2010 2-57 that have been judged in the ISA to be causal or likely causal. We also consider the evidence for 1 a broader range of health outcomes judged in th e ISA to have suggestiv e evidence of a causal 2 association, specifically studies that focus on effects in susceptible populations, to evaluate 3 whether this evidence provides support for considering lower alternative levels. 4 We take several factors into account in plac ing relative weight on the body of available 5 epidemiological studies, for example, study char acteristics, including study design (e.g., time 6 period of air quality monitoring, control for pot ential confounders); streng th of the study (in 7 terms of statistical significance and precision of result); and availabi lity of air quality distribution 8 data. We place greatest weight on information from multi-city epidemiological studies. These 9 studies have a number of advantages compared to single-city studies 46 that include providing 10 representation of ambient PM 2.5 concentrations and potential h ealth impacts across a range of 11 diverse locations providing spatial coverage for different regions across the country, reflecting 12
differences in PM 2.5 sources, composition, and potentially ot her exposure-related factors which 13 might impact PM 2.5 -related risks; lack of ‘publication bi as’ (US EPA, 2004a, p. 8-30); and 14 consideration of larger study popula tions that afford the possibility of generalizing to the broader 15 national population and provide hi gher statistical power than si ngle-city studies to detect 16 potentially statistically significant associations with relatively more precise effect estimates. 17

 To what extent have confidence bounds on concentration-response relationships 18 reported in epidemiological studies been characterized? 19 As outlined in section 2.1.3, to the extent analyses characterizing confidence bounds on 20 concentration-response (C-R) rela tionships have been published fr om both long- and short-term 21 exposure studies we have explored this evidence in reaching staff conclusions on the range of 22
annual standard levels that is appropriate to consider. We not e that although epidemiological 23 studies reporting C-R functions and associated 95% confidence in tervals provide information on 24 the precision of the effect es timates across the air quality di stribution, these analyses do not 25 provide evidence of a concentra tion below which the confidence in terval becomes notably wider 26 and uncertainty in a C-R relationship substantially increases. If an analysis characterizing the 27 confidence bounds on the C-R relationships is ava ilable and indicates an unacceptable degree of 28 uncertainty about the existence of a continuing C-R relationship, th e possibility that an effects 29 threshold may exist becomes more likely. 30

46 As discussed in section 2.2.1, we recognize that single-city studies provide ancillary evidence to multi-city studies in support of calling into question the adequacy of the current suite of standards. However, in light of the mixed findings reported in single-city short-term PM 2.5 exposure studies, and the likelihood that these results are influenced by localized events and not representative of air quality across the country, we place comparatively greater weight on the results from multi-city studies in consid ering alternative annual standard levels.Draft – Do Not Quote or Cite June 2010 2-58 Although we have identified a number of PM 10 studies reporting confidence bounds 1 around C-R functions (e.g., Daniels et al., 2004; Sa moli et al., 2005; Wong et al., 2008), we have 2 identified only three PM 2.5 studies reporting confidence bounds around C-R functions (i.e., Pope 3 et al., 2002; Miller et al., 2007; Schwartz et al., 2008; see Figu re 2-3). We found that these 4 studies analyzed the C-R function not to characte rize the confidence bounds associated with the 5 C-R function, but primarily to determine if a linear curve most appropriat ely represented the C-R 6 relationship. In particular, one long-term exposure study utilized a nonparametric smoothing 7 model to depict the shap e of the C-R function and associated confidence intervals using mortality 8 data from the ACS cohort (Pope et al., 2002). Goodness-of-fit testing indicated these data 9 supported a log-linear C-R relations hip. We observe (and observed in the last review) that there 10 was an appreciable widening of confidence bounds on the smoothing plot for all-cause mortality 11 at approximately 13 to 12 μ g/m 3 (US EPA, 2005, p. 3-56; Figure 3-4) which is somewhat below 12 where the bulk of the air quality di stribution in the study occurs (i.e., 14 μ g/m 3 is one standard 13 deviation below the long-ter m mean concentration of 17.7 μ g/m 3 ). The widening of the 14 confidence bounds in the smoothing pl ot is likely a consequence of the relative paucity of air 15 quality data at lower PM 2.5 concentrations in this study, and does not suggest the possibility that 16 an effects threshold may exist at lower PM 2.5 concentrations. 17 Additional evidence continues to support lo g-linear C-R relationships (US EPA, 2009a, 18 section 2.4.3). A recent long-term exposure study also provides information on the shape of the 19
C-R function and associated confidence interval s using cardiovascular mortality and morbidity 20 data from the WHI cohort (Miller et al., 2007). This analysis of cardiovascular events in relation 21 to long-term PM 2.5 exposure is indicative of a continued reduction in risk at lower concentrations 22
of PM 2.5 . However, since the reference value for th e C-R function in this analysis is 11μg/m 3

, we 23 are unable to ascertain a point on the C-R relationship where there is an appreciable widening of 24 confidence bounds and greater uncertainty in the C-R relationship in this study. 25 Statistical analyses have been conducted to examine the PM-mortality C-R relationship 26
and whether a threshold exists. Schwartz et al . (2008) analyzed the shap e of the concentration 27 response relationship associ ated with long-term PM 2.5 exposure using a variety of statistical 28 methods. Similar to the above noted studies, the C-R function reported by Schwartz et al. (2008) 29 was found to be linear, with “....little evidence for a threshold in the association between 30 exposure to fine particles and the risk of death...”. Although confidence bounds were provided 31 in Schwartz et al. (2008) fo r the association between PM 2.5 and mortality, widening of 32 confidence bounds occurred just below the long-term mean concentration of 17.5 μg/m 3 , and 33 continued broadening of confidence bounds at lower PM 2.5 concentrations is likely attributable to 34 the comparative lack of data at the lower end of th e air quality distribution fo r this analysis (i.e., 35Draft-Do Not Quote or Cite June 2010 Figure 2-3. Confidence Bounds on PM 2.5 Concentration-Response Relationships from Multi-city Epidemiological Studies

Source: Pope et al., 2002

Source: Miller et al., 2007

Source: Schwartz et al., 2008Draft – Do Not Quote or Cite June 2010 2-60 10.7 μ g/m 3 is one standard deviation below the long- term mean concentration). Therefore we 1 are unable to identify from this study where unc ertainty in the C-R relationship substantially 2
increases at lower PM 2.5 concentrations and the potential in creases for an effects threshold. 3 While these long-term studies provide info rmation on the lack of any discernible 4 threshold and on the precision of PM 2.5 -associated health effects, we have found no new 5 evidence to inform our understanding of th e confidence intervals around the estimated PM 2.5 C-R 6 functions. Consequently, without sufficient information available at this time we are unable to 7 use this type of approach as the basis for reaching conclusions on a range of alternative PM 2.5 8 standard levels that would be appropriate for consideration in this review. 9 In the absence of this type of evidence, we focus on the second approach by addressing 10 the following questions: 11

 How do we consider different statistical air quality metrics for identifying alternative 12 levels to be considered for a gene rally controlling annual standard? 13 We first recognize that health effects may occur over the full range of concentrations 14 observed in the long- and short- term epidemiological studies and that the ISA concluded no 15 discernible threshold for any effects can be iden tified based on the currently available evidence 16 (US EPA 2009a, section 2.4.3). As outlined in se ction 2.1.3, there is no singl e criterion that is 17 recognized as the “correct” approach to translate air quality metrics from epidemiological studies 18 into the basis for considering alternative standard levels, therefore, we e xplore various statistical 19 metrics that are reasonable to consider using two air quality distributions that are relevant to 20
inform alternative standard levels. 21 We first consider air quality distributions based on concentrations averaged across 22
ambient monitors within each ar ea included in a given study (i.e., composite monitor ) and then 23 averaged across study areas for an overall study mean concentration. The composite monitor 24 distribution is representative of the air quality data typically used in epidemiological analyses 25 and provides a direct link between PM 2.5 concentrations and the obs erved health effects. 26 We then consider a second air quality distri bution based on concentr ations estimated at 27
the monitor within each area that records the highest concentration (i.e., maximum monitor ) and 28 then averaged across study areas for an ove rall study mean concentration. The maximum 29
monitor distribution is relevant because it reflects the distributi on that is generally used to 30 determine whether a given standard is met in an area, and determines the extent to which 31
ambient PM 2.5 concentrations need to be reduced in orde r to bring an area into attainment with 32
the standard. 33 In identifying alternative standard levels th at are appropriate to consider, we recognize 34 that the protection provided depends on whether these levels are se t just below or substantially 35 below the long-term mean concentrations reported in the epidemiological studies and whether a 36Draft – Do Not Quote or Cite June 2010 2-61 composite or maximum monitor distribution is us ed as the basis for selecting the levels. 1 Statistical metrics based upon composite monitor distributions are below, and in some places 2 well below, the same statistical metrics base d upon maximum monitor di stributions. A policy 3 approach that uses data based on composite monitor distributions to identify alternative standard 4 levels, and then compares those levels to concentr ations at maximum monitors to determine if an 5 area meets a given standard, inherently builds in a margin of safety. In recognition of this 6 margin of safety, we believe it is appropriate to consider a policy approach that places 7 appreciably greater weight on fo cusing on alternative levels that are just somewhat below the 8 long-term mean concentrations reported in the epidemiologica l studies using the composite 9
monitor distributions. 47 10 Alternatively, a policy approach that uses maximum monito r distributions to identify 11
alternative standard levels that are then compared to concentrations at maximum monitors has no 12 inherent margin of safety. Therefore, to id entify alternative standard levels using maximum 13 monitor distributions that provide a margin of safety, staff believes it is appropriate to consider a 14 policy approach that places greater weight on id entifying alternative levels substantially below 15 the long-term mean concentrations from long- and short-term exposure studies. Using this 16 approach, we believe it is reasonable to focus on the lower end of the re gion within which the C17 R relationship is strongest, in wh ich the bulk of the data reside. In doing so, we believe that 18 focusing on concentrations down to approximately one standard deviation below the long-term 19 mean concentrations using the maximum m onitor distribution is also appropriate. 20 For the reasons discussed above, we focus our consideration of the long-term means and 21 associated standard deviations from multi-city epidemiological studies (see Figures 2-4 through 22 2-6). The studies included in these figures represent long- and short-term exposure studies that 23 evaluated endpoints classified in the ISA as having a causal or lik ely causal association at long24
term mean concentrations close to or below the level of the current annual PM 2.5 standard (i.e., 25 below 17 μg/m 3 ). 48 In addition, Figure 2-5 includes long-te rm exposure studies of children that 26
evaluated effects classified as ha ving evidence suggestive of an association be low the level of the 27 current annual standard. These figures presen t long-term mean concentrations and associated 28 standard deviations to the extent they are available for the composite monitor and maximum 29
monitor distributions. 30 Beyond looking at standard deviations, we al so have considered distributions from 31 epidemiological studies that provide a more conti nuous measure of the density of the data from 32

47 A similar approach was followed in the SO 2 primary NAAQS review (75 FR 35547 to 35548, June 22, 2010).
48 We note that additional studies presented and assessed in the ISA report effects at higher long-term mean PM 2.5 concentrations.Figure 2-4. Summary of Effect Estimates (per 10 μg/m3) and Air Quality Distributions for Long-term PM2.5Exposure Multi-City Studies of the General Population andOlder AdultsAir Quality Data (μg/m3)Author Reported DataEPA Analysis (Max Monitor)aStudyCiteGeographicAreaYears of AirQualityDataEndpointMeanMean -1SDRangeMeanMean -1SDRangeEffect Estimate (95% CI)General PopulationMortality-CVAll CVDIncident MIRevascularizationStrokeWHIMiller et al. (2007)36 US cities2000CBVD13.510.23.4 – 28.316.812.55-28Mortality-All-causeCystic FibrosisGoss et al. (2004)b6 US regions(NE,SE, NC, SC, NW,SW)2000Pulmonaryexacerbation13.79.511.8-15.9(IQR)---Mortality-all causeMortality-IHDMortality-CPDACS-Reanalysis IIKrewski et al. (2009)51 US MSAs1999-2000Mortality-Lung cancer14.011.05.8 - 2215.411.39-25VALipfert et al. (2006)1999-2001Mortality-all cause14.311.35.0 - ?---Mortality-all causeMortality-CVMortality-RespiratoryHarvard Six Cities(SCS)-ExtendedLaden et al. (2006)6 US cities(Northeast/Midwest)1979-1998Mortality-Lung cancer16.4c10.810-22---Older AdultsMCAPS-Western USZeger et al. (2008)62 US counties2000-2005Mortality-all cause13.1d-10.4-18.5(IQR)---Medicare-ACSEftim et al. (2008)51 US MSAs2000-2002Mortality-all cause13.610.86.0-25.114.911.39-24MCAPS-Eastern USZeger et al. (2008)421 US counties2000-2005Mortality-all cause14.0d-12.3-15.3(IQR)---Medicare -SCSEftim et al. (2008)6 US cities2000-2002Mortality-all cause14.111.09.6-19.1---aMaximum monitor calculations noted in Hassett-Sipple et al. (2010)0.8 1 1.2 1.4 1.6 1.8 2 2.2 2.4bcohort included persons with cystic fibrosis age 6 and older, mean age: 18.4 yrscEstimated from data provided by study authordMedian (IQR: Interquartile range); overall US reported median (IQR) of 13.2 μg/m3(11.1-14.9)Figure 2-5. Summary of Effect Estimates (per 10 μg/m3) and Air Quality Distributions for Long-term PM2.5Exposure Multi-City Studies of ChildrenChildrenAir Quality Data(μg/m3)StudyCiteGeographicAreaYears of Air QualityDataEndpointMeanMean –1SDRangeEffect Estimate (95% CI)Bell et al.(2007)CT,MA1998-2002Low Birth Weight11.910.3IUGR -1ndtrimesterIUGR -2ndtrimesterLiu et al.(2007)3 Canadian cities1985-1999IUGR – 3rdtrimester12.2-6.3-15Parker andWoodruff(2008)Continental US2000-2003Low Birth Weight13.5-10.9-16.1(IQR)S CA CHSMcConnell etal. (2003)12 communities –S CA1996-1999BronchiticSymptoms13.86.16-2924-CitiesDockery et al.(1996)24 communities –US, Canada1988-1991Bronchitis14.510.35.8-20.7Woodruff et al.(2008)96 US counties1999-2002Infant mortality14.9a--12.0-18.6(IQR)amedian for all cause mortality; median (IQR: interquartile range) for survivors = 14.8 (11.7-18.7) μg/m30.8 11.2 1.4 1.6 1.8 2Figure 2-6. Summary of Effect Estimates (per 10 μg/m3) and Air Quality Distributions for Short-term PM2.5Exposure Multi-City Studies of the General Population andOlder AdultsAir Quality Data (μg/m3)Author Reported DataEPA Analysis (Max Monitor)aStudy/CiteGeographicAreaYears ofAirQualityDataEndpointMeanMean -1SDRangeMeanMean -1SDRangeEffect Estimate (95% CI)General PopulationBurnett et al. (2004)12 Canadian Cities1981-1999Nonaccidentalmortality12.8-----Zanobetti & Schwartz (2009)112 US counties1999-2005Nonaccidentalmortality13.2b10.3b6.6-24.714.110.96.7-26.4Burnett & Goldberg (2003)8 Canadian Cities1986-1996Nonaccidentalmortality13.33.9c----Harvard Six Cities/ Klemm and Mason(2003)6 US cities(Northeast/Midwest)1979-1988Nonaccidentalmortality14.7d-9-23(IQR)---Franklin et al. (2008)25 UScommunities2000-2005Nonaccidentalmortality14.8b-9.9-27.4b---Franklin et al. (2007)27 UScommunities1997-2002Nonaccidentalmortality15.6b-8.8-23.9---Older AdultsCVD HAMCAPS/Bell et al. (2008)202 US counties1999-2005Resp HA12.9b10.2b4-2013.410.35-26IHD HACHF HADysrhythmia HACBVD HAPVD HACOPD HAMCAPS/Dominici et al. 2006204 US counties1999-2002RTI HA13.4b10.5b4-2313.910.55-290.9911.011.021.03aMaximum monitor calculations noted in Hassett-Sipple et al. (2010)bEstimated from data provided by study author or published studycEstimated from coefficient of variation reported in original study by Burnett et al. (2000)dMean value not reported in study, median presented from original study by Schwartz et al. (1996)IQR: interquartile rangeDraft – Do Not Quote or Cite June 2010 2-65 multi-city studies as a function of annual mean concentrations (from both composite and 1 maximum monitor distributions) across the cities in each study, as shown in Figures 2-7 and 2-8. 2 Specifically, we consider distributions of air qua lity data as well as di stributions of population 3 data across air quality concentrations, which serve as a surrogate for the density of the health 4 effects data. Taken together, st atistics from these distributions can inform our understanding of 5 the relative density of air quality and health effects data in the lower region of the C-R 6 relationship. We focus on the lower quartile of these distributi ons, and consider the range from 7
the 25 th to 10 th percentiles as a range within which the da ta become more sparse and that the C-R 8 relationship becomes appreciably more uncertain. 49 In so doing, we recognize that focusing on 9 any specific percentile from such distributions is somewhat ar bitrary, although we believe the 10
25 th and 10 th percentiles are reasonable to consider. In staff's view, placing weight on PM 2.5 11 concentrations from air quali ty and population distributions below the range from the 25 th to 10 th 12 percentiles would be a highly unc ertain basis for selecting alternative standard levels for 13
consideration. 14
We note the interrelatedness of these distributional statistics and a range of one standard 15 deviation around the mean, which co ntains approximately 68% of normally distributed data, in 16
that one standard deviation belo w the mean falls between the 25 th and 10 th percentiles of the air 17 quality distribution. Having considered both these distributional stat istics and the concentrations 18 that are one standard deviation below study mean concentrations, we conclude that they provide 19
similar information to inform selection of altern ative standard levels for consideration. In the 20 following discussion, we focus on the standard devi ation statistic as bein g a more comparable 21 statistical measure across studies, rather th an focusing on what are somewhat arbitrary 22 distributional percentiles, to inform our translatio n of the epidemiological evidence into the basis 23
for alternative standard levels th at are appropriate to consider. 24

Composite Monitor Distributions 25

Information on composite monitor distributions is available for each epidemiological 26 study considered and, therefore, represents the most robust data set available to inform our 27 conclusions regarding alternative standard levels. In addition, th ese data were used in the 28

49 In looking at the distributions between the 25 th and 10 th percentiles of either the air quality or population data, we note that the difference between the maximum and composite monitor distributions is much smaller for the three short-term exposure studies (Figure 2-8) than for the thr ee long-term exposure studies (F igure 2-7). This difference is most likely associated with the greater number of years of air quality data considered in the short-term exposure studies (3 to 6 years) compared to the long-term exposure studies (1 to 3 years) as well as the greater number of study areas considered in the short-term exposure studies (112 to 204 counties) compared to the long-term exposure studies (36 to 51 cities/MSAs).0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100

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

0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100

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 30Cumulative Frequency (%)Cumulative Population (% of total study population) Annual Mean (μg/m 3 )

Annual Mean (μg/m 3 ) 

## - Eftim et al., 2008

- Krewski et al., 2009

- Miller et al, 2007



# • Composite monitor



## ° High site Figure 2-7. Air Quality and Population Di stributions: Long-Term PM2.5 Exposure StudiesCumulative Frequency (%)Cumulative Population (% of total study population) Annual Mean (μg/m 3 )

Annual Mean (μg/m 3 ) 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100

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

0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100

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 

### - Bell et al., 2008

- Dominici et al., 2006

- Zanobetti Zanobetti & Schwartz, 2009 & Schwartz, 2009



# • Composite monitor



## ° High site Figure 2-8. Air Quality and Population Di stributions: Short-Term PM2.5 Exposure StudiesDraft – Do Not Quote or Cite June 2010 2-68 epidemiological studies to generate PM 2.5 effect estimates and, therefore, provide a direct link to 1
health evidence. 2 By applying the policy approach discussed a bove, we focus on alternative levels that are 3 just somewhat below the long-term mean concentr ations reported in the epidemiological studies 4 using the composite monitor distributions. We initi ally consider studies th at evaluated mortality 5 (causal association), cardiovascular effects (cau sal association) or resp iratory effects (likely 6 causal association). In the long-term exposure studies, we observe posi tive and statistically 7 significant associations at l ong-term mean concentrations ranging from 16.4 to 13.5 μg/m 3 8 (Laden et al., 2006; Lipfert et al., 2006; Krewski et al., 2009; Go ss et al., 2004; Miller et al.; 9 2007; Zeger et al., 2008; Eftim et al., 2008; Dock ery et al., 1996; McConnell et al., 2003; see 10 Figures 2-4 and 2-5). In then considering information from short-term exposure studies 11 reporting positive and statistically significant associations with these same broad health effect 12 categories, we observe positive and statistically significant associations at long-term mean 13 concentrations in a somewhat lower range of 15.6 to 12.8 μg/m 3 (Franklin et al., 2007, 2008; 14 Klemm and Mason, 2003; Burnett and Goldberg, 2003; Zanobetti and Schwar ts, 2009; Burnett et 15 al., 2005; Bell et al., 2008; Domini ci et al., 2006; See Figure 2-6). 50 16 In taking into consideration specific sus ceptible populations (i.e ., children), we expand 17 our evaluation of the long-term exposure studies to include a broader range of health outcomes 18 judged in the ISA to have suggestive evidence of a causal association. This evidence is taken 19 into account to evaluate whether it provides supp ort for considering lower alternative levels than 20 if weight were only placed on studies for which a ssociations have been judged in the ISA to be 21 causal or likely causal. We make note of st udies that provide emergi ng evidence for low birth 22 weight and infant mortality, especially relate d to respiratory causes during the post-neonatal 23 period (see Figure 2-5). This more limited body of evidence indicates positive and often 24 statistically significant effects a ssociated with long-term mean c oncentrations in the range of 25 14.9 to 11.9 μg/m 3 (Woodruff et al., 2008; Li u et al., 2009; Bell et al., 2007). As illustrated in 26 this figure, although Parker and Woodruff (2008) did not observe an association between 27 quarterly estimates of exposure to PM 2.5 and low birth weight in a multi-city U.S. study, other 28 U.S. and Canadian studies did report positive an d statistically significant associations between 29

PM 2.5 and low birth weight at lower ambient concentrations (Bell et al., 2007; Li u et al., 2007). 51 30

50 When integrating evidence from short-term exposure studies reporting positive and statistically significant associations with mortality, cardiovascular, and respirator y effects, the ISA concluded that these associations are generally consistent and precise at long-term mean PM 2.5 concentrations of 12.8 μg/m 3 and above (US EPA, 2009a, pp. 2-10 to 2-11)
51 As noted in section 7.4 of the ISA. Parker et al. (2005) reported that over a 9 month exposure period (mean concentrations of 15.4 μg/m 3 ) a significant decrease in birth weight wa s associated with infants in the highest quartile of PM 2.5 exposure as compared to infants exposed in the lowest quartile.Draft – Do Not Quote or Cite June 2010 2-69 There remain significant limitations (e.g., identifyi ng the etiologically rele vant time period) in 1 the evaluation of evidence on the relationship between PM 2.5 exposures and birth outcomes (US 2 EPA, 2009a, pp. 7-48 and 7-56); nonetheless, we believe it is important to give some weight to 3 these studies in taking into account potential im pacts on specific suscep tible populations and in 4 considering alternative standard levels that provide protection with a margin of safety. 5 With respect to carcinogenicity, mutagenicit y, and genotoxicity (suggestive evidence of a 6 causal association), the strongest evidence currently available is from long-term prospective 7 cohort studies that report pos itive relationships between PM 2.5 and lung cancer mortality. At this 8 time, the PM 2.5 concentrations reported in studies ev aluating these effects reported ambient 9 concentrations that are equal to or greater than ambient concentrations ob served in studies that 10 reported mortality and cardiovascular and resp iratory effects (US EPA, 2009a, section 7.5). 11 Therefore, in selecting alternative levels, we not e that in providing protection for mortality and 12 cardiovascular and respiratory effects, it is reason able to anticipate that protection will also be 13 provided for carcinogenicity, mutageni city, and genotoxicity effects. 14 A different policy approach might place greater weight on selecting alte rnative levels that 15 are substantially below the long-term mean c oncentrations reported in the epidemiological 16 studies based on composite monitor distributions. In focusing on effects classified as having a 17 causal or likely causal association with long- or short-term PM 2.5 exposures, we observe 18
concentrations one standard deviation below th e long-term means for long-term exposure studies 19 generally in the range of about 11 to 9.5 μg/m 3 (Laden et al., 2006; Lipf ert et al., 2006; Krewski 20 et al., 2009; Goss et al., 2004; Mill er et al., 2007; Eftim et al., 2008; Dockery et al., 1996; see 21 Figures 2-4 and 2-5). 52 As presented in Figure 2-6, one st andard deviation below the long-term 22
mean concentrations for short-term e xposure studies is generally about 10 μg/m 3

. 53 In expanding 23
our consideration to include effects classified as having evidence suggestive of a causal 24 association with long-term PM 2.5 exposures, information is av ailable for one study which 25 reported one standard deviati on below the mean at 10.3 μg/m 3 (Bell et al., 2007; see Figure 2-5). 26 We believe focusing on statistical metrics looking at levels that are substantially below the long27 term mean concentrations reported in the epid emiological studies using the composite monitor 28

52 With respect to considering air quality concentratio ns reported in the extended follow-up to the Southern California CHS, we recognize that on e standard deviation below the long-t erm mean concentration aggregated across the 12 study communities is a significantly lower co ncentration than looking at one standard deviation below the long-term means reported in other long-term exposure studies, if fact, this concentration is close to or below the LML reported in the majority of the long-term exposure studies. This reflects the large standard deviation reported in this study related to the wide range of ambient c oncentrations considered in the 12 study communities. (McConnell et al., 2003).
53 Burnett and Goldberg (2003) reported a comparatively greater variability in the air quality distribution across 8 Canadian cities: estimated SD from coefficient of variation reported in original study by Burnett et al.(2000) is 9.4 μg/m 3

.Draft – Do Not Quote or Cite June 2010 2-70 distributions could potentially result in standard levels that are lower than necessary to provide 1 appropriate protection given the margin of safe ty already provided by the approach discussed 2
above. 3 Therefore, in focusing on composite monito r distributions, staff believes it is most 4 appropriate and reasonable to co nsider an alternative annual PM 2.5 standard level just somewhat 5 below the lowest long-term mean concentrations reported in the multi-city epidemiological 6 studies, that is, in the range of 13 to 11 μg/m 3

. 7

 An alternative level of 13 μg/m 3 would be somewhat below the lowest long-term 8 mean concentrations reported in the multi-city long-term exposure studies that 9 provide evidence of positive and statistically significant associations with health 10 effects classified as having a causal or likely causal association . This level would 11 also be below the long-term mean concentrations reported in many, but not all, short12 term exposure studies that provided similar evidence. 13

 An alternative level of 12 μg/m 3 would be somewhat below the lowest long-term 14 mean concentrations reported in the multi-city long- and short-term exposure studies 15 that provide evidence of positive and statisti cally significant associations with health 16 effects classified as having a causal or likely causal association . This level would 17 also be below the long-term mean concentr ations reported in two of the three long18 term exposure stud ies that provide suggestive evidence of positive and often 19 statistically significant associations with low birth weight and infant mortality. 20

 An alternative level of 11 μg/m 3 would place appreciably greater weight on 21 information from multi-city, long-term exposure studies for which we have 22 suggestive evidence of low birth weight and infant mortality by considering a level 23 somewhat below the lowest long-term mean concentrations reported in such studies 24 that provide evidence of positive and statistically significant associations. 25

Maximum Monitor Distributions 26

With regard to maximum monitor distributions, we first note that this data set represents 27 a far less robust metric compared to the data set using composite monitor di stributions because it 28 is based upon far fewer epidemiological studies. Furthermore, as previously noted, maximum 29 monitor distributions are not used in analyses of associations between air quality data and PM 2.5 - 30 associated health effects in epidemiological studies. 31
Maximum monitor distributions were calculated by OAQPS for studies for which we 32 could reasonably match geographic study areas and air quality data from recent years assessed in 33 epidemiological studies that considered mortality (causal association), cardiovascular effects 34 (causal association) or respirator y effects (likely causal association) (Hassett-Sipple et al., 2010). 35
This data set includes consider ation of three long-term exposur e studies, specifically the 36 extended follow-up analyses of the ACS study (K rewski et al., 2009), the WHI study (Miller et 37 al., 2007), and the MCAPS cohort using the ACS study sites (Eftim et al., 2008) as well as three 38Draft – Do Not Quote or Cite June 2010 2-71 short-term exposure studies including the MCA PS cohort (Dominici et al., 2006; Bell et al., 1 2008), and a national mortality study (Zanobetti a nd Schwartz, 2009). Information for maximum 2
monitor distributions for studies that evaluated health outcom es judged in the ISA to have 3 suggestive evidence of a causal a ssociation were not calculated a nd, thus, are not considered in 4
the discussion below. 5 By applying the policy approach discu ssed above, in using the maximum monitor 6 distributions, we focus on alternative levels th at reflect considerati on of concentrations 7 substantially below the long-term mean concentrations reported in the epidemiological studies to 8 provide a margin of safety. In considering conc entrations that are one standard deviation below 9 the long-term mean concentrations for the th ree long-term exposure studies, we observe 10 concentrations of 12.5, 11.3 and 11.3 μg/m 3 (Miller et al., 2007; Krew ski et al., 2009; Eftim et 11 al., 2008; see Figure 2-4) from th ese studies that report positiv e and statistically significant 12 associations. In considering this same statistical metric for the three short-term exposure studies, 13 we observe somewhat lower concentrations of 10.9, 10.3, and 10.5 μg/m 3 (Zanobetti and 14 Schwartz, 2009; Bell et al., 2008; Domini ci et al., 2006; s ee Figure 2-6). 15 A different policy approach might focus on alte rnative levels that are only just somewhat 16 below the long-term mean concentrations fo r epidemiological studies using the maximum 17
monitor distributions. For the three long-term exposure studie s, positive and statistically 18 significant effects were associated with l ong-term mean concentrations of 16.8, 15.4, and 14.9 19 μg/m 3 (Miller et al., 20007; Krewsk i et al., 2009; Eftim et al., 2008; see Figure 2-3). For the 20 three short-term exposure studies, positive and pr imarily statistically significant effects were 21 reported at lower long-term mean co ncentrations of 14.1, 13.4, and 13.9 μg/m 3 ((Zanobetti and 22 Schwartz, 2009; Bell et al., 2008; Do minic et al., 2006; Figure 2-5) . In staff’s view, focusing on 23 statistical metrics looking at levels that are just below the long-term mean concentrations 24 reported in the epidemiological studies usi ng the maximum monitor distributions would 25 potentially result in standard levels that are too high to provide protection with a margin of 26 safety. 27 Therefore, in focusing on maximum monito r distributions, we consider it most 28 appropriate to focus on a policy approach that considers alternative annual PM 2.5 standard levels 29 that are substantially below the long-term m ean concentrations reported in the multi-city 30 epidemiological studies, sp ecifically, at 11 or 10 μg/m 3

. 31

 An alternative level of 11 μg/m 3 would be approximately one standard deviation 32 below the long-term mean concentrations reported in the multi-city long-term 33 exposure studies reporting positive and statistically significant associations with 34 health effects classified as having a causal or likely causal association

. 35Draft – Do Not Quote or Cite June 2010 2-72  An alternative level of 10 μg/m 3 would be approximately one standard deviation 1 below the long-term mean concentrations reported in the multi-city long- and short2 term exposure studies reporting positive and statistically significant associations with 3 health effects classified as having a causal or likely causal association

. 4 Summary of Evidence-based Considerations 5
In considering the currently available eviden ce, we have identified a set of alternative 6
annual standard levels that we conclude are appropriate to consider. Based upon composite 7 monitor distributions, we conclude it is appropriate to consider al ternative annual standard levels 8 from 13 to 11 μg/m 3 . Alternatively, based upon maximum m onitor distributions, we conclude it 9 is appropriate to consider alternative annual standard levels of 11 or 10 μg/m 3 . We also observe 10 that these alternative standard levels are genera lly within the range of levels that would be 11 identified based on considering distributiona l statistics, within the range of the 25 th to 10 th 12 percentiles, of distri butions of air qualit y data and population da ta across air quality 13 concentrations, as discussed above. 14
While we believe alternative annual standard levels based on either composite monitor 15 and maximum monitor distributions are appropriate to consider, we think it is reasonable to place 16 more weight on an approach based on compos ite monitor distributions. As noted above, 17 information on composite monitor distributions is available for each epidemiological study 18 considered and, therefore, represen ts the most robust data set avai lable to inform our conclusions 19 regarding alternative standard leve ls. Further, this distribution represents the ai r quality data 20 typically used in epidemiological analys es and provides a direct link between PM 2.5 21
concentrations and the observed health effects. In contrast, maximum monitor distributions 22 represent a far less robust metric because they are available for only a few studies. Moreover, 23 while this distribution is generally used to determine whether a give n standard is met in an area, 24 it is not used to link air quality data with PM 2.5 -associated health effects in the epidemiological 25
evidence. 26 Therefore, in considering the emphasis to place on the two policy approaches considered, 27 staff concludes it is most appr opriate to place weight on the composite monitor approach and 28 focus on alternative levels that are just somewhat below the lowest long-term mean 29 concentrations reported in the multi-city studies. As noted above, by basing this level on the 30 composite monitor distribution but by applying it at monitors that represent the maximum 31 monitor distribution, this approach inherently builds in a margin of safety. Thus, based upon the 32 currently available evidence, we co nclude alternative annual standard levels in the range of 13 to 33 11 is μg/m 3 are most strongly supported by the ava ilable evidence and are appropriate to 34
consider. 35Draft – Do Not Quote or Cite June 2010 2-73 We next take into account evidence-based cons iderations and air quali ty data to inform 1
alternative standard le vels for the 24-hour PM 2.5 standard by addressing the following question: 2

 What alternative standard levels are appr opriate to consider for setting a 24-hour 3 standard intended to supplement the protecti on afforded by a generally controlling 4 annual standard? 5 As recognized above, a generally controlling annual standard intende d to serve as the 6 primary means for providing protection for effect s associated with both long- and short-term 7

PM 2.5 exposures cannot be expected to offer an adequa te margin of safety against the effects of 8
all short-term PM 2.5 exposures, especially in areas with high peak-to-mean ratios, possibly 9 associated with strong local or seas onal sources, or for potential PM 2.5 -related effects that may be 10 associated with shorter-than-daily exposure periods. As a result, in conjunction with such an 11 annual standard, we believe it is appropria te to consider alternative 24-hour PM 2.5 standard levels 12 that would provide supplemental protection while still maintaining the annual standard as the 13 generally controlling standard. Such a 24-hour standard can r easonably be based on considering 14 air quality information based on si te-level 24-hour and annual desi gn values. Such information is 15 presented in Figure 2-9 in terms of distributions of the ratios of 98 th percentile design values to 16 annual mean design values by re gion across the U.S. A diffe rent way of looking at such 17 information is presented in Figure 2-10, which is a scatter plot of 24-hour and annual design 18
values in urban areas across the U.S., color-coded by region. 19 In general, as illustrated in Figure 2-9, 98 th percentile PM 2.5 concentrations are on average 20 approximately 2.5 times greater than annual concentra tions in almost all regi ons of the U.S. with 21 the notable exception of the Northwest, where th e ratio is approximately 3.5. In narrowing this 22 analysis to three recent years of air quality data (2006 to 200 8), we see the same patterns 23 throughout the U.S. (Schmidt, 2010). Based on this information, we believe it is reasonable to 24
focus on 24-hour standard levels that are at least 2.5 times higher th an the annual standard level. 25 Based on this consideration, we c onclude that it is appropriate to consider retaining the current 26 24-hour standard level of 35 μg/m 3 in conjunction with annual sta ndard levels of 13 to 11 μg/m 3

. 27
We have also considered whether it is al so appropriate to consider a lower 24-hour 28 standard level in conjunction with any annual st andard levels within this range, while still 29 maintaining the annual standard as the generally control ling standard. As illustrated in Figure 2- 30 10, we have examined the implications of a 24-hour standard level of 30 μg/m 3 as compared to a 31 level of 35 μg/m 3 in conjunction with an annual standard of 12 μg/m 3 . As seen in Figure 2-10, 32 combining an annual standard of 12 μg/m 3 with a 24-hour standard of 30 μg/m 3 will result in 33 many more areas outside the Northwest in wh ich the 24-hour standard would become the 34 controlling standard. This can be seen by looking to the left of the “12/30” and “12/35” lines, 35Draft – Do Not Quote or Cite June 2010 2-74 which is the region on the graph in which the 24-hour standard would be controlling. 54 In 1 contrast, based on the same type of consideration, we observe that a 24-hour standard level of 30 2 μg/m 3 in conjunction with an annual standard of 11 μg/m 3 would not result in the 24-hour 3 standard becoming the controlling standard in an appreciable number of areas. Based on these 4 considerations, we conclude that it is appropriate to also consid er a 24-hour standard level of 30 5 μg/m 3 in conjunction with an annual standard of 11 μg/m 3

. 6 In summary, based on the above considerations , we conclude that it is appropriate to 7 consider retaining the current 24 -hour standard level of 35 μg/m 3 in conjunction with annual 8 standard levels of 13 to 11 μg/m 3 , and that consideration could also be given to an alternative 24- 9 hour standard level of 30 μg/m 3 particularly in conjunction with an annual standard level of 11 10 μg/m 3 . Such combinations of 24-hour and annual sta ndards levels would be expected to result in 11 the annual standard being the ge nerally controlling standard, ex cept in areas in the Northwest 12 with particular high peak-to-mean ratios, to protect against PM 2.5 -related health effects 13 associated with long- and short-term exposures, with the 24-hour standa rd providing appropriate 14 supplemental protection. 15

Figure 2-9. Distribution of Si te-Level Ratio of Annual 98 th Percentile 16 Concentration/Annual Mean, 2000-2008 17

1 2 3 4 5 6

Overall U.S. Southeast Northeast Industrial Midwest Upper Midwest Southwest Northwest So. CA Outlying Sites 18

54 Figures similar to Figure 2-10 are presented in the RA (US EPA 2010a, section 4.5.1) together with a more detailed discussion of interpreting the information in such figures.12/30 line12/35 line05101520253035404550556065700 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30Annual Design Value (μg/m3)

24-hour Design Value (μg/m 3 )Sites in this area of the plotexceed the 24-hr level onlySites in this area of the plotexceed the annual level onlySites in this area of theplot exceed neither level24-hr levelsAnnual levelOther (AK, HI, VI, PR)So. CANorthwestUpper MidwestNortheastIndustrial MidwestSoutheastSouthwestSymbol color indentifiesgeographic region:Figure 2-10. Site-level 24-hour DVs versus Annual DVs, 2006-2008Sites in this area of theplot exceed both levelsDraft – Do Not Quote or Cite June 2010 2-76 2.3.4.2 Risk-based Considerations 1

Beyond looking directly at the re levant epidemiologic evidence, staff has also considered 2 the extent to which specific levels of alternative PM 2.5 standards are likely to reduce both long3 term exposure-related mortality risk and short- term exposure-related mortality and morbidity 4
risk. In addition to consideri ng the nature and magnitude of PM 2.5 -attributable risk remaining 5 under each set of alternative standards, we have al so considered the nature and magnitude of risk 6
reductions under the alternative standards considered. These risk estimates for the set of 7
alternative standard levels cons idered are based on the same methodology used in estimating risk 8
for the current suite of standa rd levels (see section 2.2.2). 9 The RA initially included analyses of altern ative annual standard levels of 14, 13, and 12 10 μg/m 3 paired with either the curren t 24-hour standard level of 35 μg/m 3 or with alternative 24- 11 hour standard levels of 30 and 25 μg/m 3 . The specific combinations of alternative standard 12 levels assessed in the RA included: (a) suites fo cusing on alternative annual standard levels alone 13 including combinations of alte rnative standard levels deno ted by 14/35, 13/25 and 12/35 and (b) 14
combinations of alternative annual and 24-hour st andard levels including combinations denoted 15 by 13/30 and 12/25. In addition, subsequent to the release of the second draft RA, we expanded 16 the range of alternative annua l standard levels evaluated to include a level of 10 μg/m 3 . In 17 simulating ambient PM 2.5 levels associated with these altern ative standard levels, we included a 18 more regional spatial pattern of reductions (reflected in th e use of a proportional rollback 19 approach) as well as more localized spatial patterns of reductions (reflected in the use of a hybrid 20 approach and to an even greater extent in the use of a locally focused rollback approach) (see 21 U.S. EPA, 2010a, section 3.2.3). While the pr oportional rollback approach was used in 22 generating the core risk estimat es, the other two more localized rollback approaches were 23 considered as part of sensitivity analyses. 24
Results for the alternative suites of standard levels considered are presented in Figures 2- 25 11 and 2-12, which depict patterns in risk reduction for long-termexposure-related risk (Figure 26 2-11) and short-term exposure-related risk (F igure 2-12) using differe nt combinations of 27
alternative standard levels relative to the risk under the current standard. These figures include 28 results for each of the 15 urban study areas, th ereby allowing patterns in risk reduction across 29
alternative standard levels and urban study areas to be considered together. 55 The discussion 30

55 Patterns of risk reduction across alternative annual standard levels (in terms of percent change relative to risk for the current annual standard level) are similar for all health endpoints modeled for a particular exposure duration (i.e., patterns of percent risk reduction will be similar for long -term exposure related all-caus e, IHD and cardiopulmonary mortality). This reflects the fact that the C-R functions used in the quantitative RA are close to linear across the range of ambient air concentrations evaluated..Draft-Do Not Quote or CiteJune 2010Figure 2-11 Percent reduction in long-term exposure-related mortality risk(alternative standards relative to the current standard)1(Note: inset shows PM2.5related incidence and percent of total incidence forIHD mortality under the current suite of standards*)23Atlanta, GABaltimore, MDBirmingham, ALDallas, TXDetroit, MIFresno, CAHouston, TXLos Angeles, CANew York, NYPhiladelphia, PAPhoenix, AZPittsburgh, PASalt Lake City, UTSt. Louis, MOTacoma, WA0%20%40%60%15/35**14/3513/3512/3513/3012/25Current and Alternative Standards

Long-Term Exposure-Related Risk: Percent Reduction from Current StandardAtlanta, GA 277 (227 - 324); 16.7% (13.7% - 19.5%)Baltimore, MD 374 (307 - 440); 14.7% (12.1% - 17.3%)Birmingham, AL 165 (135 - 194); 13.8% (11.3% - 16.2%)Dallas, TX 247 (202 - 291); 11.4% (9.3% - 13.4%)Detroit, MI 478 (390 - 563); 11.5% (9.4% - 13.5%)Fresno, CA 98 (80 - 116); 8.5% (7% - 10.1%)Houston, TX 434 (355 - 511); 13.6% (11.1% - 16%)Los Angeles, CA 1094 (890 - 1296); 7.7% (6.3% - 9.1%)New York, NY 2222 (1814 - 2620); 11.8% (9.6% - 13.9%)Philadelphia, PA 330 (270 - 389); 13.2% (10.8% - 15.6%)Phoenix, AZ 402 (327 - 476); 8.5% (6.9% - 10.1%)Pittsburgh, PA 324 (264 - 382); 11.8% (9.6% - 13.9%)Salt Lake City, UT 19 (16 - 23); 3.7% (3% - 4.4%)St. Louis, MO 563 (461 - 662); 14.2% (11.6% - 16.7%)Tacoma, WA 49 (40 - 58); 4.7% (3.8% - 5.6%)45*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 the6estimate of percent of total incidence (and 95% CI) under the current standards. While incidence and percent of total incidenceestimates are provided7specifically for IHD-related mortality, the percent reduction plots provided in the figure apply toall long-term exposure-related mortality categories assessed –8see text.9**The current standards consist of an annual standard of 15 μg/m3and a daily standard of 35 μg/m3. Combinations of an annual standard (n) and a daily standard10(m) are denoted n/m in this figure. Note, that the percent reductions for Salt Lake City and Tacoma at the 12/25 standard are 100% and 93%, respectively.11Draft-Do Not Quote or CiteJune 2010Figure 2-12. Percent Reduction in Short-term Exposure-related Mortality and Morbidity Risk(alternative standards relative to the1current standards) (Note: inset shows PM2.5related incidence and percent of total incidence for CV mortality under the current suite of2standards*)34Atlanta, GABaltimore,MDBirmingham, ALDallas, TXDetroit, MIFresno, CAHouston, TXLos Angeles,CANew York,NYPhiladelphia,PAPhoenix, AZPittsburgh, PASalt Lake City, UTSt. Louis, MOTacoma,WA0%5%10%15%20%25%30%35%15/35**14/3513/3512/3513/3012/25Recent Air Quality, Current Standard and Alternative Standards

Short-Term Exposure-Related Risk: Percent Reduction from Current StandardAtlanta, GA 32 (-33 - 95); 0.8% (-0.8% - 2.4%)Baltimore, MD 62 (-4 - 126); 1.6% (-0.1% - 3.2%)Birmingham, AL -1 (-42 - 40); 0% (-1.5% - 1.5%)Dallas, TX 29 (-19 - 76); 0.8% (-0.5% - 2.2%)Detroit, MI 60 (-8 - 127); 1% (-0.1% - 2.2%)Fresno, CA 12 (-9 - 33); 0.7% (-0.5% - 2%)Houston, TX 46 (-31 - 122); 0.9% (-0.6% - 2.4%)Los Angeles, CA -30 (-132 - 72); -0.2% (-0.7% - 0.4%)New York, NY 473 (276 - 668); 2.1% (1.2% - 3%)Philadelphia, PA 84 (22 - 145); 2.1% (0.5% - 3.6%)Phoenix, AZ 84 (-4 - 170); 1.3% (-0.1% - 2.7%)Pittsburgh, PA 43 (-9 - 93); 1.1% (-0.2% - 2.3%)Salt Lake City, UT 9 (-2 - 20); 0.8% (-0.2% - 1.7%)St. Louis, MO 106 (24 - 187); 1.9% (0.4% - 3.3%)Tacoma, WA 11 (-6 - 27); 0.7% (-0.4% - 1.8%)`56*Based on Zanobetti and Schwartz(2009). The legend contains,for each urban area, the incidence estimate (and 95% CI) and theestimate of percent of total7incidence (and 95% CI) under the current standards. While incidence and percent of total incidence estimates are provided specifically for CV-related mortality,8the percent reduction plots provided in the figure apply to all short-term exposure-related mortality and morbidity categoriesassessed – see text.9**The current standards consist of an annual standard of 15 μg/m3and a daily standard of 35 μg/m3. Combinations of an annual standard (n) and a 24-hour10standard (m) are denoted n/m in this figure.11Draft – Do Not Quote or Cite June 2010 2-79 below of the magnitude of risk remaining under si mulated attainment of the alternative standard 1 levels is based on risk estimates pr esented in U.S.EPA, 2010a, section 4.2.2. 2

 What is the nature and magnitude of risk associated with just meeting the alternative 3 annual PM 2.5 standards considered? 4 In characterizing estimates of PM 2.5 -related risk associated with simulation of the 5
alternative annual standards comb ined with the current 24-hour standard level (i.e., 14/35, 13/35 6 and 12/35), we estimated both the magnitude of ri sk reductions (relative to risk remaining upon 7 just meeting the current suite of standards), as well as the risk estimated to remain upon just 8 meeting the alternative standards. Our analysis included the assessment of risk associated with 9
an alternative annual st andard level of 10 μg/m 3 . In discussing these risks, we focus on the set 10 of urban study areas experiencing risk reducti ons under each alternative annual standard. Key 11 policy-relevant observations associated with these risk estimates include: 12

 Magnitude of estimated reductions in l ong-term exposure-related mortality risk: 13 Upon simulation of just meeting the alternat ive annual standard levels considered (14, 14 13, and 12 μg/m 3 ) in conjunction with the current 24-hour standard (denoted as 14/35, 15 13/35 and 12/35 suites of standards), the co re analysis estimates reductions in long16 term exposure-related mortality for 12 of the 15 urban study areas, with the degree of 17 estimated risk reduction increasing increm entally across the alternative standard 18 levels (both in terms of the number of st udy areas experiencing risk reduction and the 19 magnitude of those reductions). For the alternative annual standard level of 12 μg/m 3 20 (in conjunction with the current 24-hour sta ndard), the core analysis estimates that 21 these study areas have reductions in risk (r elative to risk remaining upon just meeting 22 the current suite of standards) ranging from about 11 to 35%. 23

For some of those areas in which the 24-hour standard is the generally controlling 24 standard, larger risk reducti ons would have been estimated in this case (12/35 suite of 25 standards) if the locally-focus ed rollback approach had been used to simulate just 26 meeting the current suite of standards. This result would be expected since the 27 magnitude of risk remaining upon just mee ting the current suite of standards would 28 have been higher than that estimated ba sed on the proportional rollback approach 29 used in the core analysis. Therefore, wh ile the absolute risks would not change, the 30 percentage difference would have been great er if we had starte d with higher risks 31 related to simulation of just m eeting the current annual standard. 32

 Long-term exposure-related mortality risk remaining: For an annual standard level of 33 14 μg/m 3 , the percent of total in cidence of long-term expos ure-related IHD mortality 34 attributable to PM 2.5 (i.e., risk remaining) in the 5 urban study areas experiencing risk 35 reductions ranges from an estimate of 9 to 15%. For an alternative annual standard of 36 12 μg/m 3 , estimated risk remaining in the 12 urban study areas experiencing risk 37 reductions ranges from 6 to 11% in terms of PM 2.5 -attributable long-term exposure38 related mortality. This translates into es timates of between 90 and 300 cases per year 39 attributable to long-term PM 2.5 exposure for those study areas experiencing the 40Draft – Do Not Quote or Cite June 2010 2-80 greatest reductions in risk under the lo west alternative a nnual standard level 1 simulated. 2

 Short-term exposure-related mortality and morbidity risk : For the alternative annual 3 standard level of 12 μg/m 3 (in conjunction with the current 24-hour standard), the 4 core analysis estimates that reductions in both short-term exposure-related CV 5 mortality and morbidity risk ranged from 5 to 23%. 56 In terms of risk remaining upon 6 simulation of 12 μg/m 3 (in conjunction with the current 24-hour standard), the urban 7 study areas with the greatest percent reduc tion have CV-related mortality estimates 8 ranging from 25 to 50 deaths per year. 9

 Simulation of risks for an alterna tive annual standard level below 12 μg/m 3 : 10 Simulation of risks for an alternative annual standard of 10 μg/m 3 suggests that 11 additional risk reductions could be expected with alternative annual standards below 12 12 μg/m 3 . However, we recognize that ther e is potentially greater uncertainty 13 associated with these risk estimates compared with estimates generated for the higher 14 alternative annual standards considered in the RA, sin ce these estimates require 15 simulation of relatively greater reductions in ambient PM 2.5 concentrations. As lower 16 ambient PM 2.5 concentrations are simulated (i.e., ambient concentrations further from 17 recent conditions), potential variability in such factors as the spatial pattern of 18 ambient PM 2.5 reductions (rollback) increases, ther eby introducing greater uncertainty 19 into the simulation of com posite monitor annual mean PM 2.5 concentrations and, 20 consequently, risk estimates (US EPA, 2010a, Appendix J). 21

 Substantial variability in magnitude of es timated risk reduction across urban study 22

areas: While there is a consistent pattern of estimated risk reduction across the 23 alternative annual standards w ith lower alternativ e standard levels resulting in more 24 urban study areas experienci ng increasingly larger risk reductions, there is 25 considerable variability in the magnitude of these reductions across study areas for a 26 given alternative annual standard level. Th is variability in estimated risk reflects 27 differing degrees of reduction in annual m ean concentrations across the study areas, 28 which results, in part, because the study areas began with varying annual mean PM 2.5 29 concentrations after simulating just meeting th e current suite of standards. Therefore, 30 even if study areas have si milar “ending” annual mean PM 2.5 concentrations after 31 simulation of just meeting a specific altern ative annual standard, because the starting 32 point in the calculati on (the annual mean PM 2.5 concentrations upon just meeting the 33 current suite of standards) can be variab le, the overall reductio n in annual mean PM 2.5 34 concentrations across the standards can also be variable. This translates into variation 35 in reductions in long-term exposure-related risk upon just meeting alternative annual 36 standard levels across the study areas. 37

 The nature of the spatial pattern in PM 2.5 reductions (reflected in the rollback 38 approach used) can impact the magnitude of estimated risk reductions: The 39 sensitivity analysis involving application of locally focused rollback revealed that the 40 pattern of reductions in ambient PM 2.5 concentrations upon just meeting the current 41

56 Because the same air quality metric (annual distributions of 24-hour PM 2.5 concentrations) was used in generating short-term exposure-related mortality and morbidity endpoints , patterns of risk reduction (as a percent of risk under the current suite of standards) are similar for both sets of endpoints (see US EPA, 2010a, section 4.2.2).Draft – Do Not Quote or Cite June 2010 2-81 suite of standards can impact the magnitude of additional risk reductions estimated 1 for just meeting alternative (lower) annual standard levels. Specifically, for those 2 study areas with more peaky PM 2.5 distributions, application of the locally focused 3 rollback approach resulted in higher annual mean PM 2.5 concentrations remaining 4 upon just meeting the current suite of sta ndards. If a proportional rollback approach 5 was then used to simulate just meeting a lternative annual standa rd levels, a greater 6 degree of reduction in compos ite monitor annual mean PM 2.5 concentrations will 7 result, since the “starting point” for the calculation (annual mean PM 2.5 concentrations 8 upon just meeting the current suite of sta ndards) would be higher. These findings 9 highlight the important roll played by vari ability in the spatial pattern of ambient 10 PM 2.5 concentrations in influencing the magnit ude of risk reductions under alternative 11 annual standard levels. 12

 Based on consideration of the composite monitor annual mean PM 2.5 concentrations 13 involved in estimating long-term exposure- related mortality, we have varying levels 14 of confidence in risk estimates genera ted for the three a lternative annual standard 15 levels considered: With the exception of one study area, those study areas estimated 16 to have risk reductions under the altern ative annual standards of 14 and 13 μg/m 3 17 have simulated composite monitor annual mean PM 2.5 concentrations ranging from 18 just below 10.6 to over 13.3 μg/m 3 (see US EPA, 2010a, Table 3-4). In other words, 19 these composite monitor annual mean PM 2.5 concentrations generally fall well within 20 the range of ambient PM 2.5 concentrations considered in fitting the C-R functions 21 used (i.e., within one SD of the mean PM 2.5 concentration from 1999-2000 ACS 22 dataset). The urban study areas estimated to have risk reductions under the lower 23 alternative annual sta ndard level of 12 μg/m 3 have lower composite monitor annual 24 mean values ranging from 9.0 to over 11.4 μg/m 3 . These values generally extend to 25 below one SD of the mean of the ACS da taset and therefore, we have somewhat 26 lower confidence in these risk estimates, relative to those generated for the two higher 27 alternative annual standards. By contrast, urban study area s estimated to have risk 28 reductions under the alternativ e standard level of 10 μg/m 3 (paired with the current 29 24-hour standard) have simulated composite monitor annual estimates ranging from 30 7.6 to 8.9 μg/m 3 (see US EPA, 2010a, Table 3-4). Th ese concentrations are towards 31 the lower end of the range of ACS data used in fitting the C-R functions (in some 32 cases approaching the LML) and, therefore, we have substantially less confidence in 33 these risk estimates, compared with those for the higher alterna tive annual standards 34 assessed. 35

 What is the nature and magnitude of risk associated with simulating different 36 combinations of alternative annual and 24-hour PM 2.5 standards? 37 In characterizing PM 2.5 -related risks associated with simulation of alternative annual 38
standards combined with alternative 24-hour standards (13/30 and 12/25), we estimated both the 39 magnitude of risk remaining upon just meeting these alternative standa rds, as well as the 40 magnitude of risk reductions (relative to risk remaining upon just meeting the current suite of 41 standards). While the alternative 24-hour standard levels consider ed did result in estimated risk 42Draft – Do Not Quote or Cite June 2010 2-82 reductions, we have lower confidence in these risk estimates because of the relatively low 1 annual-average PM 2.5 concentrations associated with si mulation of these standard levels. 2 Of the 11 urban study areas estimated to have risk reductions under the alternative 24- 3 hour standard of 30 μg/m 3 (with the 24-hour standard control ling – see US EPA 2010a, Table 3- 4 4), composite monitor annual mean PM 2.5 concentrations ranged from 6.6 to 11.3 μg/m 3 with 5 most of the urban study areas having concentrations in the 8 to 10 μg/m 3 range. These 6 concentrations extend into the lower range of PM 2.5 concentrations considered in the ACS study 7 to fit the C-R functions and therefore, we have somewhat lower confidence in these estimates. 8 When we consider composite monitor concen trations for urban study areas assessed to 9
have risk reductions under the alterna tive 24-hour standard level of 25 μg/m 3 (again, where the 10 24-hour standard is controlling), we observed composite monitor annual mean PM 2.5 11 concentrations that are even lower, ranging from 5.6 to 11.2 μg/m 3 with most study areas having 12 concentrations in the range of 7 to 9 μg/m 3 . Because this range extends well into the lower range 13
of PM 2.5 concentrations considered in the ACS st udy to fit the C-R functions (in some cases 14 extending below the LML), we have substantially lower confidence in these risk estimates. 15 Furthermore, we find that those urban study areas with the greatest degree of estimated risk 16
reduction under these alternative 24-hour standard levels also had the lowest composite monitor 17 annual average PM 2.5 levels, and therefore we have the lowest overall confidence in these results. 18

2.3.4.3 Integration of Evidence-based and Risk-based Considerations 19

In considering the epidemiological evidence, es timates of risk reductions associated with 20 just meeting alternative annual and/or 24-hour standards, air quality analyses, and related 21 limitations and uncertainties, staff concludes that there is clear support for considering revisions 22
to the suite of current PM 2.5 standards to provide additional pr otection against health effects 23 associated with long- and short-term exposures. We recognize that health effects may occur over 24 the full range of concentrations observed in the long- and short-term epidemiological studies and 25 that no discernible threshold for any effects can be identified based on the currently available 26 evidence. In reaching staff conclusions regardin g appropriate alternative standard levels to 27 consider, we have examined where the evidence of associations is strongest and, conversely, 28 where we have substantially less confidence in C- R relationships and in qua ntitative estimates of 29
risk. 30 As an initial matter, based on the availabl e evidence and insights from the quantitative 31 risk assessment, we conclude that it is appropr iate to consider altern ative annual and 24-hour 32
standard levels consistent with the goal of estab lishing a suite of sta ndards that includes a 33 “generally controlling” annua l standard and a 24-hour standard that provides supplemental 34 protection, especially for areas with high peak-t o-mean ratios, possibly associated with strong 35Draft – Do Not Quote or Cite June 2010 2-83 local or seasonal sources, or for potential PM 2.5 -related effects that may be associated with 1 shorter-than-daily exposure periods . Based upon the currently avai lable evidence, we conclude 2
alternative annual sta ndard levels in the range of 13 to 11 μg/m 3 are appropriate to consider. 3 This conclusion reflects the much stronger body of scientific evidence available in this review 4 supporting a causal association be tween long- and short-term PM 2.5 exposures and mortality and 5 cardiovascular effects and a likely causal a ssociation between long- and short-term PM 2.5 6 exposures and respiratory effects, as well as ev idence that is suggestive of a causal association 7
with other health outcomes such as low bi rth weight and infant mortality and cancer, 8 mutagenicity, and genotoxicity effects. In conjun ction with an annual standard within this range, 9 we conclude it is appropriate to consider retaining the curr ent 24-hour standard level of 35 10 μg/m 3 , as well as considering an alternat ive 24-hour standard level of 30 μg/m 3 , particularly in 11 conjunction with consideration of an annual standard level of 11 μg/m 3

. 12 Beyond evidence-based consideratio ns, we have also considered the extent to which the 13 quantitative risk assessment suppor ts consideration of these alternative standard levels or 14 provides support for lower levels. We first conclude that risks estimated to remain upon 15 simulation of just meeting the current suite of standards are important from a public health 16 perspective, considering both the severity and es timated magnitude of effects. In considering 17 simulations of just meeting alte rnative annual standard levels w ithin the range of 13 to 11 μg/m 3 18 in conjunction with the current 24- hour standard level of 35 μg/m 3 , we conclude that important 19 public health improvements are associated with ri sk reductions estimated fo r standard levels of 20 13 and 12 μg/m 3 , noting that the level of 11 μg/m 3 was not included in the quantitative risk 21 assessment. Our overall confidence in the quant itative risk estimates is strongest for the 22
alternative annual sta ndard level of 13 μg/m 3 . We have somewhat lower confidence in risk 23
estimates for the alternativ e annual standard of 12 μg/m 3 . We also estimated risks likely to 24 remain upon just meeting an annual standard level of 10 μg/m 3 , although we have substantially 25
lower confidence in those estimates. We also have somewhat lower confidence in our risk 26
estimates for an alternative 24- hour standard level of 30 μg/m 3 , and substantially lower 27
confidence in our estimates of risks for an alternative 24-hour sta ndard level of 25 μg/m 3 . Based 28 on the above considerations, we conclude that the quantitative risk a ssessment provides support 29 for considering an alternative annual st andard within a range of 13 to 11 μg/m 3 , in conjunction 30 with a 24-hour standard of 35 or 30 μg/m 3 , but does not provide st rong support for considering 31
lower alternative levels. 32 In identifying this range of annual standard levels, staff has taken into consideration the 33 importance of balancing the strength of the cu rrently available evidence and risk-based 34 information with the remaining unc ertainties and limitations associ ated with this information. 35 The upper end of this range of annual standard levels (13 μg/m 3 ) reflects placing appreciably 36Draft – Do Not Quote or Cite June 2010 2-84 more weight on the uncertainties and limitations in the information which would serve to reduce 1 the potential to overestimate public health risks a nd protection likely to be associated with just 2 meeting a standard set at this level. This pol icy option would reflect pl acing greater weight on 3 the remaining uncertainties in the evidence, including uncertainties associated with 4 understanding the heterogeneity obse rved in the epidemiological studi es such as those associated 5 with the role of specific com ponents, sources, and subfractions (e.g., UFPs) within the current 6

PM 2.5 mass-based indicator, the role of fine part icles and co-pollutants within the broader 7 ambient mixture, and exposure-rela ted factors that influence the magnitude and duration of fine 8 particle exposures. The lower end of this range (11 μg/m 3 ) reflects placing much less weight on 9
uncertainties and limitations in the information which would serve to reduce the potential to 10 underestimate public health improvements likely to be associated with just meeting a standard 11 set at this level. This polic y option would reflect placing considerably more weight on limited 12
evidence of serious effects in su sceptible populations such as pot ential developmental effects, 13 while recognizing that significant limitations remain in assessing the relationship between PM 2.5 14 exposures and these effects, specifically, unde rstanding the nature of the association and 15 exposure windows of concern. 16 To provide some perspective on the implicati ons of applying various combinations of 17 alternative annual and 24-hour standards, staff assessed (based on 2006 to 2008 air quality data) 18 the percentage of counties, and the population in those counties , that would not likely attain 19
varies alternative suites of PM 2.5 standards. This assessment, shown in Appendix 2A, Table 2A20 1, was not considered as a basis for the above staff conclusions. 21

2.4 STAFF CONCLUSIONS ON ALTERNAT IVE FINE PARTICLE STANDARDS 22 In reaching conclusions on poten tial alternative standards to provide requisite protection 23 for health effects associated with long- and s hort-term fine particle exposures, staff has 24
considered these standards in terms of the ba sic elements of the NAAQS : indicator, averaging 25 time, form, and level. In cons idering the scientific and techni cal information, we reflect upon the 26 information available in the last review integrat ed with information that is newly available as 27 assessed and presented in the ISA and RA (US EPA, 2009a; US EPA, 2010a) and as summarized 28
in sections 2.2 and 2.3. We also consider the is sues raised by the court in its remand of the 29 primary annual PM 2.5 standard. 30 As outlined in section 2.1.3, our approach to reaching conclusions about the adequacy of 31
the current suite of PM 2.5 standards and potential alternative standards that are appropriate for 32
consideration is broader and more integrative than approaches used in past reviews. Our 33 approach integrates a much expanded body of health effects evidence, more extensive air quality 34 data and analyses, and a more comprehensive qu antitative risk assessment, and considers the 35Draft – Do Not Quote or Cite June 2010 2-85 combined protection against PM 2.5 -related mortality and morbidity effects associated with both 1 long- and short-term exposures afforded by the annual and 24-hour standards. 2 We recognize that selecting from among alte rnative standards will necessarily reflect 3 consideration of the qualitative a nd quantitative uncertainties inhe rent in the relevant evidence 4 and in the assumptions that unde rlie the quantitative risk asse ssment. In identifying these 5 alternative suites of primary stan dards and ranges of levels for c onsideration, we are mindful that 6 the Clean Air Act (CAA) requires standards to be set that are requisite to protect public health 7 with an adequate margin of safety, such that the standards are to be neither more nor less 8 stringent than necessary. Thus, the CAA does no t require that the NAAQS be set at zero-risk 9 levels, but rather at levels that a void unacceptable risks to public health. 10
(1) Consideration should be give n to revising the current PM 2.5 primary standards to provide 11 increased public health protection from the eff ects of both long- and short-term exposures to 12 fine particles in the ambient air. This conclu sion is based in genera l on the evaluation in the 13 ISA of the currently available epidemiological, toxicologic, dosimetric, and exposure-related 14 evidence, and on air quality in formation and analyses related to the epidemiological 15 evidence, together with judgments as to th e public health significance of the estimated 16 incidence of effects upon just meeting the current suite of standards. 17 (2) The indicator for fine particle st andards should continue to be PM 2.5 . We conclude that the 18 available evidence does not provide a suffici ent basis for replacing or supplementing the 19 PM 2.5 indicator with an indicator de fined in terms of UFPs or fo r any specific fine particle 20 component or source category of fine particles, nor does it provide a basis for excluding any 21 component or source category from the mix of particles included in the PM 2.5 indicator. 22 (3) Averaging times for PM 2.5 standards should continue to in clude annual and 24-hour averages 23 to protect against health effects associated with long-term (seasons to years) and short-term 24 (hours to days) exposure periods. Considerati on of other averaging times, including an 25 averaging time less than 24 hours to address health effects associated with subdaily 26 exposures or a longer averaging time to address effects associat ed with seasonal exposures, 27 was limited by the relatively small amount of relevant information available. 28 (4) Consideration should be given to revising the form of the annual standard to one based on the 29 highest community-oriented monitor in an area rather than a form that allows averaging 30 across monitors (e.g., spa tial averaging). The 98 th percentile form of the current 24-hour 31 standard should be retained. 32 (5) Consideration should be given to alternative suites of PM 2.5 standards to provide protection 33 against effects associated with both long- and short-term expos ures, taking into account both 34 evidence-based and risk-based considerations. 35 (a) Consideration should be given to setti ng the levels of the annual and 24-hour 36 standards such that the annual standard would be the “generally controlling” 37 standard to provide protection for both long- and short-term PM 2.5 exposures in 38 conjunction with a 24-hour standard to provide supplemental protection against 39 days with high peak concentrations to lim it peak concentrations in areas with high 40 peak-to-mean ratios, possibly associated with strong local or seasonal sources, or 41Draft – Do Not Quote or Cite June 2010 2-86 for potential PM 2.5 -related effects that may be asso ciated with shorter-than-daily 1 exposure periods. We conclude that this is the most effective and efficient way to 2 reduce total population risk associated w ith both long- and short-term exposures 3 and provide requisite protecti on in areas across the country. 4 (b) Consideration should be given to alternative annual standa rd levels in the range of 5 13 to 11 μg/m 3 . We conclude that this range is most strongly supported by the 6 currently available scientific evidence and risk-based information 7 (c) Consideration should be give n to retaining the current 24-hour standard level of 8 35 μg/m 3 in conjunction with annual standard le vels in this range; consideration 9 could also be given to an alternat ive 24-hour standard level of 30 μg/m 3 10 particularly in conjunction with an annual standard level of 11 μg/m 3

. 11

2.5 KEY UNCERTAINTIES AND AREAS FOR FUTURE RESEARCH AND DATA 12 COLLECTION 13 In this section, we briefly discuss key uncer tainties and areas for future health-related 14 research, model development, and data collection activities. These efforts, if undertaken, could 15 provide important evidence for informing futu re PM NAAQS reviews and, in particular, 16 consideration of possible alternat ive indicators, averaging times, a nd/or levels. In some cases, 17 research in these areas can go beyond aiding standa rd setting to informing the development of 18 more efficient and effective control strategies. We note, however, that a full set of research 19 recommendations to meet standards implemen tation and strategy development needs is beyond 20 the scope of this discussion. 21 As has been presented and discussed in the PM ISA, particularly in Chapters 4 through 7, 22 the scientific body of evidence in forming our understanding of h ealth effects associated with 23 long- and short-term exposures to fine particle s has been broadened and strengthened since the 24 last review. In reviewing the adequ acy of the current suite of primary PM 2.5 standards and in 25 evaluating alternative he alth-based fine particle standard s appropriate for consideration, we 26 identify the following key uncertainties and areas fo r future research and data collection efforts 27 that have been highlighted in th is review. We recognize that some research could be available to 28 inform the next PM NAAQS review, while other re search may require longer-term efforts. 29
Interpretation of Epidemiological Evidence 30 Additional research focused on identifying the most important factors contributing to the 31 observed heterogeneity in the epidemiological evidence could provide in sights for interpreting 32 these studies. We encourage research and data collection efforts directed at improving our 33 understanding of the nature of the exposures contributing to th e observed health effects, for 34 example, the role of specific components, s ources, and subfractions (e.g., UFPs) within the 35
current PM 2.5 mass-based indicator and the role of fine particles and co-pollutants within the 36 broader ambient mixture, as well as improving our understanding of exposur e-related factors that 37Draft – Do Not Quote or Cite June 2010 2-87 influence the magnitude and duration of fine par ticle exposures. Much of this research may 1 depend on the availability of increased monitoring data, as discussed below. 2

 Components/Sources. The currently available scientific evidence continues to be largely 3 indexed by aggregate PM 2.5 mass-based concentrations wh ich vary in composition both 4 regionally and seasonally. Source characte rization, exposure, epidemiological, and 5 toxicological research focused on improving our understanding of the relative toxicity of 6 different fine particle components, properties, and sources that may be more closely linked 7 with various health effects. Critical to this better understandi ng of the impacts of 8 components and their associated sources are da ta that refines the temporal and spatial 9 variability of the fine particle mixture.. Th is research would redu ce the uncertainties in 10 estimating risks. It could also inform consider ation of alternative indicators in future PM 11 NAAQS reviews as well as aid in the developm ent of efficient and effective source control 12 strategies for reduci ng health risks. 13

 Ultrafine Particles (UFPs). Additional monitoring methods development work, health 14 research, and ambient monitoring data collection efforts are needed to expand the currently 15 available scientific data base for UFPs. U FP measurements should include surface area as 16 well as number, mass and composition. It woul d be most useful for a UFPs monitoring 17 network to be designed to inform our understandi ng of the spatial and te mporal variability of 18 these particles, including in near-roadway environments. This information would improve 19 our ability to explore consideration of a separate indicator for UFPs as a subfraction of fine 20 particles in future PM NAAQS reviews. 21

 Co-pollutant Exposures. Research focused on furthering our understanding of the extent to 22 which an association between fine particles a nd specific health effects can be modified by 23 one or more co-pollutants would inform our abilit y to discern the role of PM in the complex 24 ambient mixture. For example, does the magnitude of a PM 2.5 -related effect estimate differ 25 on days when O 3 levels are higher compared to days when O 3 levels are lower? 26

 Exposure-related Factors. Additional research and analyses would be useful to provide 27 insights on population exposures, specifically in improving our understanding of intra-city 28 and inter-city differences rela ted to various PM component s, source contributions and 29 personal and building-related factors (e.g., air conditioning use; residence near roadways) 30 that may enhance our interpreta tion of the epidemiological evid ence. This research could 31 focus on different size fractions in PM 2.5 (i.e.,UFPs) as well as components. Coordination 32 between exposure and health studies could advance our understanding of exposure-related 33 factors. For example, epidemiological panel studies might use measured personal exposure 34 measurements to explore differences in pers onal exposures related to (1) indoor generated 35 fine particles, (2) fine particle exposures measured by community monitors, and (3) fine 36 particle exposures not captur ed by community monitors (i .e., personal exposures during 37 commuting). 38 Health Outcomes, Exposure Durations of Concern, and Susceptible Populations 39

New information available in this review reinforces and expands the evidence of 40 associations between long- and short-term PM 2.5 exposures and mortalit y and cardiovascular and 41 respiratory effects. Less evidence is availa ble to understand other health effects (e.g., 42Draft – Do Not Quote or Cite June 2010 2-88 developmental/reproductive effects; central nervous system effect s). Additional research could 1 expand our understanding of th e associations between PM 2.5 and a broader range of health 2 outcomes; reduce uncertainties associated with our current understand ing of concentration3 response relationships; improve our understanding of exposure durations of concern; and 4 improve our understanding of the potential public health impacts of fine particle exposures in 5 susceptible populations. 6

 Health Effects. Research on a broader range of ca rdiovascular and respiratory endpoints 7 could improve our understanding of the mechanisms by which these effects occur. In 8 addition, future research could expand the scien tific data base for health effects that are 9 currently less understood incl uding effects categorized with in the ISA as having evidence 10 suggestive of a causal relationship or for which currently available evidence is inadequate. 11 To the extent that research supports a link betw een fine particles and adverse effects on the 12 nervous system, reproduction, development, or ot her endpoints, such effects could play an 13 increased role for informing future PM NAA QS reviews including e xpanding the health 14 endpoints that could potentially be evaluated in future qua ntitative risk assessments. 15

 Concentration-Response Relationships. Research focused on improving our understanding 16 of the shape of the C-R relationships, esp ecially at lower ambient fine particle 17 concentrations, as well as the confidence bounds around these C-R relationships, could 18 reduce uncertainties associated with estima ting and characterizing risks throughout the full 19 range of air quality distributi ons. As more information beco mes available on fine particle 20 components and sources, it will be important to understand the C-R relationships for key 21 constituents of the fine particle mixture, as well. 22

 Exposure Durations of Concern. Research should be direct ed at broadening the scientific 23 data base to improve our understanding of hea lth effects associated with short-term, peak 24 exposures, such as those related to traffic-re lated sources, wildfires, agricultural burning, or 25 other episodic events, as well as to improve our understanding of health effects associated 26 with seasonal-length exposures, such as those related to wintertime wood-burning emissions. 27 Additional quantitative measures of exposure might take into account factors including the 28 magnitude and duration of s ub-daily and seasonal length PM 2.5 exposures and the frequency 29 of health impacts associated with repeated peak exposures. More research is needed to better 30 understand effects that occur at longer lag times than have histor ically been studied (e.g., 0 to 31 2 day lags). 32

 Susceptible Populations. Improving our understanding of the populations that are more 33 likely to experience adverse health effects re lated to fine particle exposures and the 34 concentrations at which these effects may o ccur is important for informing future PM 35 NAAQS reviews and for developing programs to reduce related public health risks. This 36 evidence may also provide insights into the biologic modes of action for toxicity. 37

o Pre-existing Health Conditions. While currently identified susceptible populations 38 include persons with pre-existing cardiova scular and respiratory disease, evidence 39 continues to emerge related to additio nal health conditions that may increase 40 susceptibility to fine particle exposur es (e.g., diabetes, obesity, neurological 41 disorders). Research to replicate or extend these findings would enhance our 42 understanding of these and other pote ntially susceptible populations. 43Draft – Do Not Quote or Cite June 2010 2-89 o Children. Epidemiological and toxicological studies provide evidence that children 1 are more susceptible to PM exposures, prim arily for respiratory-related effects. 2 Evidence of developmental effects associ ated with PM exposures continues to 3 emerge. Additional research exploring issues to better understand key windows of 4 development impacted by PM exposures c ould enhance our unders tanding of this 5 important susceptible population. 6

o Genetic Susceptibility . Research to expand our understanding of genetic 7 susceptibility could inform our understandi ng of potentially susceptible populations 8 and provide additional information for id entifying the specif ic pathways and 9 mechanisms of action by which PM initiates health effects. 10

o Socioeconomic status (SES) . Additional research is need ed to identity what factors 11 (e.g., general health status, diet, medicati on, stress, unmeasured pollution) cause SES 12 differences in response to pollution measured at a community site. 13

Data Collection Needs and Me thods Development Activities 14

Additional research and data collection efforts focused on expanding current monitoring 15
methods and networks as well as continued development of exposure models expand data 16
available for health studies c ould improve our understanding of potential alternative indicators, 17 averaging times, and levels to consider in fu ture PM NAAQS reviews. In particular, staff 18 encourages work to enhance our understanding of the temporal and spatial variability of PM 2.5 , 19

PM 2.5 components, and subfractions (e.g., UFPs). 20

 Monitoring Measurements. In order to improve our understanding of the association 21 between fine particles and health effects, more frequent measurement data could be collected. 22 This would provide information that could in form our understanding of alternative lags. 23

o PM 2.5 Components. With respect to improving our understanding of the impacts of 24 PM 2.5 components, enhancements to the Ch emical Speciation Network (CSN), 25 including more frequent measuremen t schedules and the development and 26 deployment of continuous monitoring methods for specific fine particle components 27 (e.g., EC/OC, sulfates), could enhance our understanding of the temporal and spatial 28 variability of specific compone nts. Furthermore, identifying chemical species within 29 the mix of OC would improve our understanding of the arti facts associated with semi30 volatile PM components and aid in de signing toxicological experiments. 31

o Ultrafine Particles. In order to improve our unde rstanding of the public health 32 impacts of UFPs, consideration should be given to establishing a Federal Reference 33 Method (FRM) for UFPs and establishi ng a national UFP monitoring network. 34

o Source Apportionment . Composition data with better time resolution (e.g., 1 to 6 35 hour) and better size resolution (e.g., UFPs , accumulation mode particles, coarse 36 particles in PM 2.5 and PM 10-2.5 ) could provide more precise and accurate information 37 on sources of fine particles to inform health research as well as development of more 38 efficient and effective control strategies. 39

o Areas of Peak Exposures. Some portion of the required PM 2.5 monitoring network 40 could be dedicated to improving our abil ity to characterize community-wide air 41Draft – Do Not Quote or Cite June 2010 2-90 quality at a neighborhood or ur ban scale that represents wh ere we expect to find peak 1 exposures. A portion of the required network could be targeted to monitor short-term 2 PM 2.5 concentrations in areas that are not affirmatively designated as “community3 wide” air quality. Requiring monitors in ar eas not designated as “community-wide” 4 would ensure protection for those populations whose ambient exposures may be 5 affected by unique local sources or terrain which are often located in areas with 6 smaller spatial scales. These areas, such as population-oriented micro- and middle7 scale “hot spots,” are not re quired to be monitored in the current network design. 8

 Model Development. Continuing work to improve models for estimating PM 2.5 mass and 9 composition in areas with only every third or sixth day measurements, and by space, where 10 measurements are not available could enhance our understanding of the temporal and spatial 11 variability of fine particles. Refinement of these models to finer sp atial scales may improve 12 exposure estimates in epidemiological studies as well as in quantitati ve risk and exposure 13
assessments 14

 Air Quality Distributions Repor ted in Epidemiological Studies . Most epidemiological 15 studies provide some information on the distri bution of ambient measurement data evaluated, 16 however, published information is often gene rally limited in scope and the descriptive 17 statistics reported vary from one study to another. Understandi ng the air quality distributions 18 at which effects have been observed is important for informing consideration of the adequacy 19 of the current NAAQS as well as potential alternative indicators, averag ing times, and levels 20 to consider. Working with intramural and extr amural research groups, we plan to encourage 21 a more comprehensive and more consis tent reporting of air quality data. 22Draft – Do Not Quote or Cite June 2010 2-91 2.6 REFERENCES 1
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Zanobetti A; Schwartz J. (2007). Particulate air pollution, progression, and survival after myocardial infarction. 10 Environ Health Perspect, 115: 769-775. 11

Zanobetti A, Schwartz J. (2009). The effect of fine an d coarse particulate air pollution on mortality: A national 12 analysis. Environ Health Perspect, 117: 1-40. 13

Zhang Z, Whitsel E, Quibrera P, Smith R, Liao D, Anderson G, Prineas R (2009). Ambient fine particulate matter 14 exposure and myocardial ischemia in the Environmental Epidemiology of Arrhythmogenesis in the 15 Women's Health Initiative (EEAWHI) study. Environ Health Perspect, 117: 751-756. 16

Zeger S, McDermott A, Dominicit F, Samet J. (2007). Mortality in the Medicare population and chronic exposure 17 to fine particulate air pollution. Johns Hopkins University. Baltimore. 18 http://www.bepress.com/jhubiostat/paper133

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Zeger S, Dominici F, McDermott A, Samet J. (2008). Mort ality in the Medicare population and chronic exposure to 20 fine particulate air pollution in urban centers (2000-2005). Environ Health Perspect, 116: 1614. 213-1 D raft-Do Not Quote or Cite June 2010 

### 3 REVIEW OF THE PRIMARY STANDARD FOR THORACIC 1 

### COARSE PARTICLES 2

This chapter presents staff conclusions with re gard to the adequacy of the current primary 3

PM 10 standard, which is intended to protect public health against e xposures to thoracic coarse 4 particles (PM 10-2.5 ), and potential alternative primary standa rds for consideration in this review. 5 Our assessment of these issues is framed by a series of key policy-relevant questions, which 6 expand upon those presented in the IRP (US EPA, 2008a). The answers to these questions will 7 inform decisions on whether, and if so how, to revise the current PM 10 standard. 8 Our approach for reviewing the primary PM 10 standard is presented in section 3.1. Our 9 considerations and conclusions regard ing the adequacy of the current PM 10 standard are 10 presented in section 3.2. Section 3.3 presents our considerations a nd conclusions with respect to 11 potential alternative standards, focusing on each of the basic elements of the standards: pollutant 12 indicator (section 3.3.1), averag ing time (section 3.3.2), form (s ection 3.3.3), and level (section 13 3.3.4). Section 3.4 summarizes staff conclusi ons on the current and potential alternative 14 standards. Section 3.5 discusses key uncertainties and suggested future research areas and data 15
collection efforts. 16

3.1 APPROACH 17 Staff’s approach for reviewing the current primary PM 10 standard builds upon the 18 approaches used in previous PM NAAQS reviews. The past and curren t approaches described 19 below are all based most fundamentally on usi ng information from epidemiologic studies to 20 inform the selection of PM standards that, in th e Administrator’s judgment, protect public health 21 with an adequate margin of safety. Evidence -based approaches to using information from 22 epidemiologic studies to inform decisions on PM standards are complicated by the recognition 23 that no population threshold, below which it can be concluded with confidence that PM-related 24 effects do not occur, can be discerned from th e available evidence (ISA, section 2.4.3). As a 25 result, any approach to reaching decisions on wh at standards are appropriate requires judgments 26
about how to translate the information available from the epidemiologic studies into a basis for 27 appropriate standards, which incl udes consideration of how to wei gh the uncertainties in reported 28
associations across the distributio ns of PM concentrations in the studies. Our approach to 29 informing these decisions, discussed more fully below, recognizes that the available health 30 effects evidence reflects a continuum consisting of ambient levels at whic h scientists generally 31 agree that health effects are li kely to occur through lower levels at which the likelihood and 32 magnitude of the response become increasingly uncer tain. Such an approach is consistent with 333-2 D raft-Do Not Quote or Cite June 2010 setting standards that are neither more nor less stringent than necessary, recognizing that a zero1 risk standard is not required by the CAA. 2

3.1.1 Reviews Completed in 1987 and 1997 3 The PM NAAQS have always included some type of a primary standard to protect 4 against effects associated with exposures to thoracic co arse particles. In 1987, when EPA first 5 revised the PM NAAQS, EPA changed the indicat or for PM from Total Suspended Particles 6 (essentially applicable to particles smaller than 25-45 micrometers) to focus on inhalable 7 particles, those which can pene trate into the trachea, bronchi , and deep lungs (52 FR 24634). 8 EPA changed the PM indicator to PM 10 based on evidence that the ri sk of adverse health effects 9 associated with particles of 10 micrometers or le ss was significantly greater than that associated 10 with larger partic les (52 FR at 24639). 11 In the 1997 review, in conjunction with es tablishing new fine particle (i.e., PM 2.5 ) 12 standards (see above, sections 1.2.3, 2.1.1), EPA c oncluded that continued protection remained 13 warranted against potential effects associated with thoracic coarse particle s in the size range of 14 2.5 to 10 μm. This conclusion was based on par ticle dosimetry, toxicological information, and 15 on limited epidemiologic evidence from studies that measured PM 10 in areas where coarse 16 particles were likely to dominate the dist ribution (62 FR 38677, July 18, 1997). Thus, EPA 17 concluded that the existing PM 10 standards would provide requisi te protection against effects 18 associated with particles in the size range of 2.5 to 10 μm. Although EPA considered a more 19 narrowly defined indicator for thoracic coar se particles in that review (i.e., PM 10-2.5 ), EPA 20
concluded that it was more a ppropriate, based on existing ev idence, to continue to use PM 10 as 21 the indicator. This decision was based, in part, on the recognition that th e only studies of clear 22 quantitative relevance to health effects most likel y associated with thoraci c coarse particles used 23

PM 10 in areas where the coarse fracti on was the dominant fraction of PM 10 , namely two studies 24
conducted in areas that substa ntially exceeded the 24-hour PM 10 standard (62 FR 38679). In 25 addition, there were only very limited ambient ai r quality data then ava ilable specifically for 26 thoracic coarse particles, in contrast to th e extensive monitoring network already in place for 27

PM 10, Therefore, it was judged more ad ministratively feasible to use PM 10 as an indicator. EPA 28
also stated that the PM 10 standards would work in conjunction with the PM 2.5 standards by 29 regulating the portion of particulat e pollution not regulated by the PM 2.5 standards. 30 As explained in chapter 1, in May 1998, a thre e-judge panel of the U.S. Court of Appeals 31 for the District of Columbia Circuit found "ample support" for EPA's decision to regulate coarse 32 particle pollution, but vacated the 1997 PM 10 standards, concluding that EPA had failed to 33 adequately explai n its choice of PM 10 as the indicator for thoracic co arse particles pointing to the 34 lack of reasoned explanation for the variable leve l of allowable concentrati ons of thoracic coarse 353-3 D raft-Do Not Quote or Cite June 2010 particles (varying by levels of PM 2.5 ) and the consequent double regulation of PM 2.5
. American 1 Trucking Associations v. EPA , 175 F. 3d 1027, 1054-56 (D.C. Cir. 1999). The court also 2 rejected considerations of administrative feasib ility as justification for a NAAQS, which are to 3 be based exclusively on health a nd welfare considerations. Id. at 1054. Pursuant to the court’s 4 decision, EPA removed the vacated 1997 PM 10 standards from the Code of Federal Regulations 5 (CFR) (69 FR 45592, July 30, 2004) and deleted the regulatory provision (at 40 CFR section 6 50.6(d)) that controlled the transiti on from the pre-existing 1987 PM 10 standards to the 1997 7

PM 10 standards (65 FR 80776, December 22, 2000). The pre-existing 1987 PM 10 standards 8 remained in place. Id. at 80777. 9

3.1.2 Review Completed in 2006 10 In the review of the PM NAAQS that c oncluded in 2006, EPA considered the growing, 11 but still limited, body of evidence supporting associations between health effects and thoracic 12 coarse particles measured as PM 10-2.5
. 1 The new studies available in the 2006 review included 13 epidemiologic studies that reported associations w ith health effects using direct measurements of 14

PM 10-2.5 , as well as dosimetric and toxicological st udies. In considering this growing body of 15

PM 10-2.5 evidence, as well as evidence from studies that measured PM 10 in locations where the 16 majority of PM 10 was in the PM 10-2.5 fraction (US EPA, 2005, section 5.4.1), staff concluded that 17 that the level of protection afforded by the existing 1987 PM 10 standard remained appropriate 18 (US EPA, 2005, p. 5-67), but recommended that th e indicator for the standard be revised. 19 Specifically, staff recommended urban coarse part icles in the size range of 10-2.5 micrometers as 20 the indicator, thus focusing on those thoracic coarse particles that are gene rally present in urban 21 environments (US EPA, 2005, p. 5-71). The agency pr oposed to retain a standard for a subset of 22 thoracic coarse particles, proposing a qualified PM 10-2.5 indicator to focus on the mix of thoracic 23 coarse particles generally present in urban environments. More specifically, the proposed 24 revised thoracic coarse particle standard would have applied only to an ambient mix of PM 10-2.5 25 dominated by resuspended dust from high-density traffic on paved roads a nd/or by industrial and 26 construction sources. The proposed revised standa rd would not have applied to any ambient mix 27
of PM 10-2.5 dominated by rural windblown dust and so ils. In addition, ag ricultural sources, 28 mining sources, and other similar sources of crus tal material would not have been subject to 29 control in meeting the standard (71 FR 2667 to 2668, January 17, 2006). 30 The Agency received a large number of comments overwhelmingly opposed to the 31 proposed qualified PM 10-2.5 indicator (71 FR 61188 to 61197). Afte r careful consideration of the 32

1 The PM Staff Paper (US EPA, 2005) also presented results of a quantitative assessment of health risks for PM 10-2.5 . However, staff concluded that the nature and magnitude of the uncertainties and concerns associated with this risk assessment weighed against its use as a basis for recomme nding specific levels for a thoracic coarse particle standard.3-4 D raft-Do Not Quote or Cite June 2010 scientific evidence and the reco mmendations contained in the 2005 Staff Paper, the advice and 1 recommendations from CASAC, the public comments received regarding the appropriate 2 indicator for coarse particles, and after extensiv e evaluation of the alternatives available to the 3 Agency, the Administrator decided it would not be appropriate to adopt a qualified PM 10-2.5 4 indicator. Underlying this determination was the decision that it was requisite to provide 5 protection from exposure to all thoracic coarse PM , regardless of its orig in, rejecting arguments 6
that there are no health effects from community-level exposures to coarse PM in non-urban areas 7 (71 FR 61189). The EPA concluded that dos imetric, toxicologi cal, occupational and 8 epidemiologic evidence supported re tention of a primary standard for short-term exposures that 9 included all thoracic coarse part icles (i.e. both urban and non-urba n), consistent with the Act’s 10 requirement that primary NAAQS provide an adequa te margin of safety. At the same time, the 11 agency concluded that the sta ndard should target pr otection toward urban areas, where the 12 evidence of health effects from exposure to PM 10-2.5 was strongest (71 FR at 61193, 61197). The 13 proposed indicator was not suitab le for that purpose. Not only did it inappropriately provide no 14 protection at all to many areas, but it failed to identify many areas where the ambient mix was 15 dominated by coarse particles contaminated with urban/industrial types of coarse particles for 16 which evidence of health effects was strongest (71 FR 61193). 17 The agency ultimately concluded that the existing indicator, PM 10 , was most consistent 18 with the evidence. Although PM 10 includes both coarse and fine PM, the Agency concluded that 19 it remained an appropriate indicator for thoracic coarse particles because , as reported by Schmidt 20 et al. (2005), fine particle le vels are generally higher in urban areas and, therefore, a PM 10 21 standard set at a single unvarying level will generally result in lo wer allowable concentrations of 22 thoracic coarse particles in urba n areas than in non-urban areas. EPA considered this to be an 23 appropriate targeting of protecti on given that the strongest eviden ce for effects associated with 24 thoracic coarse particles came from epidemiol ogic studies conducted in urban areas and that 25 elevated fine particle concentrations in urban areas could result in increased contamination of 26 coarse fraction particles by PM 2.5 , potentially increasing the toxici ty of thoracic co arse particles 27 in urban areas (71 FR 61195-96). Give n the evidence that the existing PM 10 standard afforded 28 requisite protection with an ample margin of safe ty, the Agency retained the level and form of 29
the 24-hour PM 10 standard. 2 30 The Agency also revoked the annual PM 10 standard, in light of the conclusion in the PM 31 Criteria Document (US EPA, 2004) that the avai lable evidence does not s uggest an association 32 with long-term exposure to PM 10-2.5 and the conclusion in the Sta ff Paper (US EPA, 2005) that 33 there is no quantitative evidence that dire ctly supports an annual standard. 34

2 Thus, the standard is met when a PM 10 concentration of 150  g/m 3 is not exceeded more than once per year on average over a three-year period.3-5 D raft-Do Not Quote or Cite June 2010 In the same rulemaking, EPA also included a new Federal Reference Method (FRM) for 1
the measurement of PM 10-2.5 in the ambient air (71 FR 61212 to 61213). Although the standard 2 for thoracic coarse pa rticles does not use a PM 10-2.5 indicator, the new FRM for PM 10-2.5 was 3 established to provide a basis for approving Federal Equivalent Methods (FEMs) and to promote 4 the gathering of scientific data to suppor t future reviews of the PM NAAQS. 5

3.1.3 Litigation of 2006 Final Rule for Thoracic Coarse Particles 6 A number of groups filed suit in response to the final decisions made in the 2006 review. 7
See American Farm Bureau Federation and th e National Pork Producers Council v. EPA (DC 8 Cir. 2009). Among the petitions for review were challenges from industry groups on the 9
decision to retain the PM 10 indicator and the level of the PM 10 standard and from environmental 10 and public health groups on the decision to revoke the annual PM 10 standard. The court upheld 11 both the daily PM 10 standard and the decision to revoke the annual standard. 12 First, the court upheld EPA’s decision for a standard to cover all thoracic coarse PM, 13 both of urban and non-urban origi n. The court rejected argument s that the evidence showed 14 there are no risks from exposure to non-urban co arse PM. The court further found that EPA had 15
a reasonable basis not to set se parate standards for urban and non-urban coarse PM, namely the 16 inability to reasonably define what ambient mi xes would be included under either ‘urban’ or 17 ‘non-urban;’ and that the eviden ce in the record supported EPA’ s cautious decision to provide 18 “some protection from exposure to thoracic coarse particles... in all areas.” 559 F. 3d at 532-33. 19 Specifically, the court stated, 20
21 Although the evidence of danger from coarse PM is, as EPA recognizes, 22 “inconclusive,” (71 FR 61193, October 17, 2006), the agency need not wait for 23 conclusive findings before regulating a pollutant it reasonably believes may pose 24 a significant risk to public health. The evidence in the record supports the EPA’s 25 cautious decision that “some protection from exposure to thoraci c coarse particles 26 is warranted in all areas.” Id. As the court has consistently reaffirmed, the CAA 27 permits the Administrator to “err on the side of caution” in setting NAAQS

. 28 559 F. 3d at 533. 29 30 The court also upheld EPA’s decision to re tain the level of th e standard at 150 μg/m 3 and 31
to use PM 10 as the indicator for a standa rd meant to protect against exposures to thoracic coarse 32 particles. In upholding the level of the standard, the court referre d to the conclusion in the Staff 33 Paper that there is “little basis for concludi ng that the degree of pr otection afforded by the 34
current PM 10 standards in urban areas is greater than warranted, since potential mortality effects 35 have been associated with air quality levels not allowed by the current 24-hour standard, but 36 have not been associated with air quality levels that would generally m eet that standard, and 373-6 D raft-Do Not Quote or Cite June 2010 morbidity effects have been associated with ai r quality levels that exceeded the current 24-hour 1 standard only a few times.” 559 F. 3d at 534. The court also rejected arguments that a PM 10 2 standard established at an unvarying level will re sult in arbitrarily varyin g levels of protection 3 given that the level of coarse PM would vary ba sed on the amount of fine PM present. The court 4 agreed that the variation in allowable coarse PM accorded with the strength of the evidence: 5 typically less coarse PM would be allowed in urban areas (where levels of fine PM are typically 6 higher), in accord with the stronge st evidence of health effects fr om coarse particles. 559 F. 3d 7 at 535-36. In addition, such regulation would not impermissibly double regulate fine particles, 8 since any additional regulation of fine part icles (beyond that afforded by the primary PM 2.5 9 standard) would be for a different purpose: to prevent contaminat ion of coarse particles by fine 10 particles. 559 F. 3d at 535, 536. These same explanations explained the choice of PM 10 as an 11 indicator, and provided the reason ed explanation for that choice lacking in the record for the 12
1997 standard. 559 F. 3d at 536. 13 With regard to the challenge from envir onmental and public health groups, the court 14 upheld EPA’s decision to revoke the annual PM 10 standard. Specifically, the court stated the 15 following: 16 The EPA reasonably decided that an annual coarse PM standard is not necessary 17 because, as the Criteria Document and th e Staff Paper make clear, the latest 18 scientific data do not indicat e that long-term exposure to coarse particles poses a 19 health risk. The CASAC also agreed th at an annual coarse PM standard is 20 unnecessary. 559 F. 3d at 538-39. 21 22

3.1.4 Current Approach 23 Our approach relies most heavily on the h ealth evidence, primarily the epidemiologic 24 evidence, assessed in the ISA (US EPA, 2009a) and on available PM air quality information. As 25
discussed in more detail in the Quantitative Health Risk Assess ment for Particulate Matter – 26
Final (US EPA, 2010a), we have not conducted a quantitative assessment of health risks 27
associated with PM 10-2.5 . Staff concluded that limitations in the monitoring network and in the 28 health studies that rely on that monitoring network, which would be the basis for estimating 29

PM 10-2.5 health risks, would introduce si gnificant uncertainty into a PM 10-2.5 risk assessment such 30 that the risk estimates generated would be of lim ited value in informing review of the standard. 31 Therefore, staff concluded in the RA th at a quantitative risk assessment for PM 10-2.5 is not 32 supportable at this time (U S EPA, 2010a, p. 2-6). 33 For purposes of this policy assessment, we seek to provide as broad an array of options 34 for consideration as is supportable by the av ailable evidence and ai r quality information, 35 recognizing that the final d ecisions on the primary PM 10 standard will reflect the judgments of 36 the Administrator. In developing these options for consideration, we consider the available 373-7 D raft-Do Not Quote or Cite June 2010 evidence and air quality inform ation that informs overarching questions related to: (1) the 1 adequacy of the current 24-hour PM 10 standard to protect agains t effects associated with 2 exposures to thoracic coarse pa rticles and (2) what potential al ternative standard(s), if any, 3
should be considered in this review. In addres sing these broad questions , we have organized the 4 discussions below around a series of more specifi c questions reflecting different aspects of each 5 overarching question. When evaluating the health protection afforded by the current or potential 6 alternative standards, we have taken into acc ount the four basic elem ents of the NAAQS (e.g., 7 indicator, averaging time, form, and level). 8 Figure 3-1 provides an overview of the policy -relevant questions that frame our review, 9 as discussed more fully below. We believe th e approach outlined here, when presented in the 10 final Policy Assessment, will provide a comprehe nsive basis to help inform the judgments 11 required of the Administrator in reaching decisions about the cu rrent and potential alternative 12 primary standards meant to protect public health against exposures to thoracic coarse particles. 133-8 D raft-Do Not Quote or Cite June 2010 Figure 3-1. Approach to Considering the Current and Potential Alternative Thoracic 1 Coarse Particle Standards 2

33-9 D raft-Do Not Quote or Cite June 2010 3.2 ADEQUACY OF THE EXISTING PM 10 STANDARD 1 In considering the adequacy of the current 24-hour PM 10 standard to protect against 2 effects associated with exposur es to thoracic coarse particles, we address the following 3 overarching question: 4

Does the available scientific evidence, as reflect ed in the ISA, suppor t or call into question 5 the adequacy of the protection af forded by the current 24-hour PM 10 standard against 6 effects associated with exposures to thoracic coarse particles? 7

To inform our consideration of this overar ching question, we consider the scientific 8
evidence for associations between PM 10-2.5 and mortality and morbidity, evidence linking 9

PM 10-2.5 toxicity to specific sources/locations, uncer tainties in the evidence, and available PM 10 10 air quality concentrations in PM 10-2.5 study locations (section 3.2.1). Evidence for populations 11 that are particularly susceptible to PM exposures is discussed in detail in section 2.2.1 above, and 12 is not repeated here. Staff conclusions regard ing the adequacy of the current standard are 13 presented in section 3.2.2. 14

3.2.1 Evidence-Based Considerations 15 In considering the currently available body of scientific evidence for health effects of 16 thoracic coarse particles, we consider the following question: 17

 To what extent does the available scientif ic evidence support or call into question 18 associations between ambient thoracic coar se particle exposures and adverse health 19 effects? 20
Since the conclusion of the last review, the Agency has developed a more formal 21 framework for reaching causal inferences from th e body of scientific evidence. As discussed 22 above in section 2.2.1, this framework uses a five -level hierarchy that classifies the overall 23 weight of evidence using the following categoriza tions: causal relationship, likely to be a causal 24 relationship, suggestive of a causal relationship, inadequate to infer a causal relationship, and not 25 likely to be a causal relationshi p (ISA, section 1.5, Table 1-3). Applying this framework to 26 thoracic coarse particles, the ISA concludes th at the existing evidence is suggestive of a causal 27 relationship between short-term PM 10-2.5 exposures and mortality, cardiovascular effects, and 28 respiratory effects (US EPA, 2009a, section 2.3.3; see Table 3-1 below). In contrast, the ISA 29
concludes that available evidence is inadequate to infer a causal relationship between long-term 30

PM 10-2.5 exposures and various health effects (US EP A, 2009a, section 2.3; Table 3-1 below). 31 Similar to the judgment made in the AQCD rega rding long-term exposures (US EPA, 2004), the 32 ISA states, “To date, a sufficient amount of evid ence does not exist in order to draw conclusions 33 regarding the health effects and outcomes associated w ith long-term exposure to PM 10-2.5 ” (US 343-10 D raft-Do Not Quote or Cite June 2010 EPA, 2009a, section 2.3.4). Given these weight of evidence conclusions in the ISA, our 1 evidence-based considerations regardi ng the adequacy of the current 24-hour PM 10 standard 2 focus on effects that have been linked with short-term exposures to PM 10-2.5
. 3 As noted above, in the last review of the PM NAAQS, PM 10 studies conducted in 4
locations where PM 10 is comprised predominantly of PM 10-2.5 were also considered (US EPA, 5 2005, pp. 5-49 to 5-50). However, PM 10 studies are difficult to interpret within the context of a 6 standard meant to protect against exposures to PM 10-2.5 because PM 10 is comprised of both fine 7 and coarse particles, even in locations with the highest concentrations of PM 10-2.5 (see below). In 8 light of the considerable uncerta inty in the extent to which PM 10 effect estimates reflect 9
associations with PM 10-2.5 , together with the availability in this review of recent studies that 10
evaluate associations with PM 10-2.5 specifically and the fact that the ISA weight of evidence 11
conclusions for thoracic coarse particles were based on studies of PM 10-2.5 , we focus in this 12 Policy Assessment on studies that have specifically evaluated PM 10-2.5
. The evidence supporting 13
a link between short-term thoraci c coarse particle exposures a nd adverse health effects is 14
discussed in detail in the ISA (US EPA, 2009a, Chapter 6) and is summarized briefly below for 15 mortality, cardiovascular effect s, and respiratory effects. 16

Table 3-1. Summary of Causality Determinations for PM 10-2.5 17 Exposure Duration Outcome Causal Determination Cardiovascular Effects Suggestive Respiratory Effects Suggestive Mortality Suggestive Short-term Central Nervous System Effects Inadequate Cardiovascular Effects Inadequate Respiratory Effects Inadequate Mortality Inadequate Reproductive and Developmental Effects Inadequate Long-term

Cancer Mutagenicity, Genotoxi city Effects Inadequate
Source: adapted from US EPA, 2009a; Table 2-6 18

Short-Term PM 10-2.5 and Mortality 19 The ISA assesses a number of multi-city and single-city epidemiologic studies that have 20 evaluated associations between mortality and short-term PM 10-2.5 concentrations (US EPA, 21 2009a, Figure 6-30 presents PM 10-2.5 mortality studies assessed in th e last review and the current 22 review). Different studies have used di fferent approaches to estimate ambient PM 10-2.5 . Some 23
studies have used the difference between PM 10 and PM 2.5 mass, either measured at co-located 243-11 D raft-Do Not Quote or Cite June 2010 monitors (e.g., Lipfert et al., 2000; Mar et al., 2003; Ostro et al., 2003; Sheppard et al., 2003; 1 Wilson et al., 2007) or as the difference in coun ty-wide average concentrations (Zanobetti and 2 Schwartz, 2009), while other studies have measured PM 10-2.5 directly with dichotomous samplers 3 (e.g., Burnett and Goldberg, 2003; Fairley et al., 2003; Burnett et al., 2004; Klemm et al., 2004). 4 Despite differences in the approaches used to estimate ambient PM 10-2.5 concentrations, the 5 majority of multi- and single-city studies ha ve reported positive associations between PM 10-2.5 6 and mortality, though most of these associations were not statistically significant (US EPA, 7 2009a, Figure 6-30). When considered as a whole, the ISA concluded that epidemiologic studies 8 have reported consistent, positive associations between short-term PM 10-2.5 and mortality (US 9 EPA, 2009a, section 6.5.2.3). 10 In considering specific mortality studies, we note that the U.S. multi-city study by 11 Zanobetti and Schwartz (2009) reported positive a nd statistically significant associations with 12

PM 10-2.5 for all-cause, cardiovascular, and respir atory mortality (US EPA, 2009a, section 6.5.2.3) 13 while other multi-city studies have reported pos itive, but not statistically significant, PM 10-2.5 14 effect estimates (US EPA, 2009a, Figure 6-30, Bu rnett and Goldberg, 2003; Klemm et al., 2003; 15 Burnett et al., 2004). In the study by Zanobetti a nd Schwartz, the effect estimates for all-cause 16 and respiratory mortality remained statistically significant in co-pollutant models that included 17

PM 2.5 , while the effect estimate for cardiovascular mortality remained positive but not 18 statistically significant. When risk estimates in this study were evaluated by climatic region (US 19 EPA, 2009a, Figure 6-28), the “d ry continental” region, which included areas with relatively 20 high PM 10-2.5 concentrations (see US EPA, 2009a, Figur e 6-29; Schmidt and Jenkins, 2010; and 21 discussion of regional differences in PM 10-2.5 concentrations below) such as Salt Lake City, 22 Provo, and Denver, showed the largest risk es timates. However, the “dry” region, which 23 included Phoenix and Albuquerque, two locatio ns that also have relatively high PM 10-2.5 24 concentrations, did not show positive associations with all-cause or respiratory mortality and 25 only a relatively small positive association for cardiovascular mortality. In addition, the 26 “Mediterranean” region (which included cities in California, Oregon, a nd Washington) did not 27 show positive associations while the other three regions (i.e., “hot summer, continental,” “warm 28 summer, continental,” and “humid, subtropical and maritime”), which included cities that 29 correspond to the mid-west, northeast, and sout heast geographic regions, all showed positive 30 associations (US EPA, 2009a, Figure 6-28). 31 The ISA also presents empirical Bayes-adjusted city-specific effect estimates for cities 32 evaluated by Zanobetti and Schw artz (US EPA, 2009a, Figure 6- 29). City-specific estimates 33 were positive, though generally not statistically si gnificant, for cardiovascular mortality in all 47 34 cities evaluated. Effect estimates were positiv e for all-cause and respiratory mortality in all 35 cities except Los Angeles (negative for all-cau se and respiratory) and Phoenix (negative for 363-12 D raft-Do Not Quote or Cite June 2010 respiratory) (US EPA, 2009a, Fi gure 6-29). In addition, positiv e and statistically significant 1 associations between mortality (all-cause, cardiovascular, and/or respiratory) and PM 10-2.5 were 2 reported for six locations (St. Louis, MO; Sa lt Lake City, UT; Chicago, IL; Pittsburgh, PA; 3 Detroit, MI; and Birmingham, AL). 4 In considering single-city PM 10-2.5 mortality studies, we note that all of the studies 5 included in Figure 6-30 of the ISA (US EPA, 2009a) reported positive PM 10-2.5 effect estimates, 6 with three single-city studies reporting effect esti mates that were statistically significant (Mar et 7 al., 2003; Ostro et al., 2003; Wilson et al ., 2007). One study reported a negative PM 10-2.5 effect 8 estimate for respiratory mortality (Villeneuve et al., 2003), though effect es timates for all-cause 9 and cardiovascular mortality were positive in this study (US EPA, 2009a, Figure 6-30). 10
Short-Term PM 10-2.5 and Cardiovascular Effects 11
The ISA assesses a number of studies that ha ve evaluated the link between short-term 12
ambient concentrations of thoracic coarse particles and cardiovascular effects. In considering the 13 available epidemiologic evidence, the ISA concl udes that single- and multi-city epidemiologic 14 studies generally report positive associations between short-term PM 10-2.5 concentrations and 15 hospital admissions or emergency department vi sits for cardiovascular causes (US EPA, 2009a, 16 section 2.3.3, 6.2.12.2). Some of these studies have reported positive and statistically significant 17

PM 10-2.5 effect estimates in co-pollutant models while others report that PM 10-2.5 effect estimates 18 remain positive, but not statistically significant (US EPA, 2009a, Figure 6-5). 19
These studies include a recent U.S. multi-c ity study evaluating hospital admissions and 20 emergency department visits for cardiovascular disease in Medicare patients (Peng et al., 2008). 21 In this study of older adults , the authors reported a positive and statistically significant 22
association between 24-hour PM 10-2.5 concentrations and cardiovasc ular disease hospitalizations 23 in a single pollutant model using air quality data for 108 U.S. counties with co-located PM 10 and 24

PM 2.5 monitors. The effect estimate was reduced onl y slightly in a two-pollutant model that 25
included PM 2.5, but it was no longer statistically signi ficant (US EPA, 2009a, sections 2.3.3, 26 6.2.10.9). Regional and/or county- specific analyses were not conducted for the locations 27 evaluated by Peng. Therefore, it is not possible, based on the data from this study, to consider 28
differences in PM 10-2.5 effect estimates in specific locations or regions. In addi tion to this U.S. 29 multi-city study, positive associatio ns reported for short-term PM 10-2.5 and cardiovascular 30 morbidity reached statistical significance in a mu lti-city study in France (Host et al., 2007) and 31 single-city studies in Detroit and Toronto (US EPA, 2009a, Figures 6-2, 6-3). In contrast, 32 associations were positive but not statistically significant in single-city studies conducted in 33 Atlanta and Boston (and for some endpoints in Detroit) (US EP A, 2009a, Figures 6-1 to 6-3, 6- 34 5). 353-13 D raft-Do Not Quote or Cite June 2010 The plausibility of the positive associations reported for PM 10-2.5 and cardiovascular1 related hospital admissions and emergency departme nt visits is supported by a small number of 2 controlled human exposure studies that have reported alterations in heart rate variability 3 following exposure to PM 10-2.5 ; by short-term PM 10-2.5 epidemiologic studies reporting positive 4 associations with cardiovascular mortality; by a small number of recent epidemiologic studies 5
that have examined dust storm events and reported increases in cardiovascular-related 6 emergency department visits and hospital admissions (see below); and by a ssociations with other 7 cardiovascular effects including hear t rhythm disturbances and cha nges in heart rate variability 8 (US EPA, 2009a, sections 2.3.3, 6.2.12.2). The few toxicological studies that examined the 9
effect of PM 10-2.5 on cardiovascular health effects used in tratracheal instillati on and, as a result, 10 provide only limited evidence on th e biological plausibility of PM 10-2.5 induced cardiovascular 11 effects (US EPA, 2009a, sections 2.3.3, 6.2.12.2). 12
Short-Term PM 10-2.5 and Respiratory Effects 13
The ISA also assesses a number of studies that have evaluated the link between short14
term ambient concentrations of thoracic coarse particles and respiratory effects. This includes 15 recent studies conducted in the U.S., Canada , and France (US EPA, 2009a, section 6.3.8), 16 including the U.S. multi-city study of Medicare patients by Peng et al. (2009). As discussed 17 above, Peng estimated PM 10-2.5 concentrations as the difference between PM 10 and PM 2.5 18 concentrations measured by co-located monito rs. The authors reported a positive, but not 19 statistically significant, PM 10-2.5 effect estimate for respirator y-related hospital admissions. 20 Single-city studies have reporte d positive, and in some cases statistically significant, PM 10-2.5 21 effect estimates for respiratory-related hospital admissions and emergency department visits (US 22 EPA, 2009a, Figures 6-10 to 6-15). Some of these PM 10-2.5 respiratory morbidity studies have 23 reported positive and statistically significant PM 10-2.5 effect estimates in co-pollutant models that 24 included gaseous pollutants while others reported that PM 10-2.5 effect estimates remain positive, 25 but not statistically significant, in such co-pol lutant models (US EPA, 2009a, Figure 6-15). 26 A limited number of epidemiologic studies have focused on specific respiratory 27 morbidity outcomes and reported both positive and negative, but generally not statistically 28 significant, associations between PM 10-2.5 and lower respiratory symptoms, wheeze, and 29 medication use (US EPA, 2009a, sections 2.3.3. 1 and 6.3.1.1; Figures 6-7, 6-8, 6-9). Although 30 controlled human exposure studies have not obser ved an effect on lung function or respiratory 31 symptoms in healthy or asthmatic adults in response to short-term exposure to PM 10-2.5 , healthy 32
volunteers have exhibited an increase in markers of pulmona ry inflammation. Toxicological 33 studies using inhalation exposures are still lacking, but pulmonary injury and inflammation has 34 been reported in animals afte r intratracheal instillation e xposure (US EPA, 2009a, section 35 6.3.5.3) and, in some cases, PM 10-2.5 was found to be more potent than PM 2.5
. 363-14 D raft-Do Not Quote or Cite June 2010 PM 10-2.5 Toxicity: Impacts of Sources and Composition 1 As discussed above, positive, and in some cas es statistically significant, associations 2
between short-term PM 10-2.5 concentrations and mortality and mo rbidity have been reported in a 3
number of different locations. Little is known about how PM 10-2.5 composition varies across 4
these locations and how that variation could aff ect particle toxicity (US EPA, 2009a, sections 5 2.3.3, 2.3.4, 2.4.4). However, the limited available ev idence suggests that specific components 6 of thoracic coarse particles tend to comprise different fractions of PM 10-2.5 mass in different 7 environments (e.g., urban versus rural envir onments) (US EPA, 2009a, section 3.5.1.1; Schmidt 8 et al., 2005; Edgerton et al., 2009). It is possible that such differences in particle composition 9 could affect particle toxicity, though the ISA concludes that existi ng evidence is not sufficient to 10 draw distinctions in toxicity based on composition and notes that recent studies have reported 11 that PM from different sources, including crustal sources, is a ssociated with adverse health 12 effects (US EPA, 2009a, section 2.4. 4). The evidence for associati ons with particles originating 13 from different types of sources and in differe nt locations is discussed briefly below. 14 As discussed above, most PM 10-2.5 epidemiologic studies have been conducted in urban 15 locations in the U.S., Canada, and Europe while a small number of studies have examined the 16 health impacts of dust storm events (US EPA, 2009a, sections 6.2.10.1, 6.5.2.3). Although these 17 dust storm studies do not link specific particle co nstituents to health effects, it is useful to 18 consider them within the context of the toxicity of particles of non-urban crustal origin. Several 19 studies have reported positive and statistically si gnificant associations between dust storm events 20 and morbidity or mortality, including the following: 21

 Middleton et al. (2008) reported that dust storms in Cyprus were associated with a 22 statistically significant incr ease in risk of hospitaliza tion for all causes and a non23 significant increase in hospitalizations for cardiovascular disease. 24

 Chan et al. (2008) studied the effects of Asian dust storms on cardiovascular hospital 25 admissions in Taipei, Taiwan and reported a st atistically significant increase associated 26 with 39 Asian dust events. Evaluating the sa me data, Bell et al . (2008) also reported 27 positive and statistically significant associa tions between hospitalization for ischemic 28
heart disease and PM 10-2.5
. 29

 Perez et al. (2008) tested the hypothesis that outbreaks of Saharan dust exacerbate the 30
effects of PM 10-2.5 on daily mortality in Spain. During Saharan dust days, the PM 10-2.5 31 effect estimate was larger than on non-dust da ys and it became statistically significant, 32 whereas it was not statistically significant on non-dust days. 33 In contrast to the studies noted above, some dust storm studies have reported associations that 34 were not statistically si gnificant. Specifically, Bennett et al. (2006) reported on a dust storm in 35 the Gobi desert that transported PM across the Pacific Ocean, reaching we stern North America in 363-15 D raft-Do Not Quote or Cite June 2010 the spring of 1998. The authors reported no exce ss risk of cardiac or respiratory hospital 1 admissions associated with the dust storm in the population of British Columbia’s Lower Fraser 2 Valley (Bennett et al., 2006). In addition, Yang et al. (2009) reported that hospitalizations for 3 congestive heart failure were elevated duri ng or immediately followi ng 54 Asian dust storm 4 events, though effect estimates we re not statistically significant. The implications of these 5 studies for the current review, for consideration of potential standard in dicators, are discussed 6
below. 7 Next we consider uncertainties associated with the evidence by addressing the following 8 question: 9

 What are the important uncertainties associat ed with the currently available scientific 10 evidence that should be considered in e valuating the adequacy of the current PM 10 11 standard? 12 The majority of the health evidence suppor ting the link between short-term thoracic 13 coarse particle exposures and mortality and morbidity comes from epidemiologic studies. 14 Although new studies have become available si nce the last review and have expanded our 15 understanding of the association between PM 10-2.5 and adverse health effects (see above and U.S. 16 EPA, 2009a, Chapter 6), important uncertainties remain. These uncertainties, and their 17 implications for interpreting the scientific evidence, are discussed below. 18 The ISA (sections 2.3.3, 2.3.4) concludes that an important uncertainty in the PM 10-2.5 19 epidemiologic literature is that associated with the air quality estimates used in these studies. 20 Specifically, the ISA concludes that there is gr eater error in estimating ambient exposures to 21

PM 10-2.5 than to PM 2.5 and that such uncertainty is a partic ularly relevant consideration when 22 interpreting PM 10-2.5 epidemiologic studies. Contributing to this uncertainty is the relatively 23 limited spatial coverage provided by existing PM 10-2.5 monitors (US EPA, 2009a, sections 2.2.3, 24 2.3.3, 2.3.4, 3.5.1.1 and see above). As discussed above, a national network to monitor PM 10-2.5 25 is not in place, limiting the spatial area over which PM 10-2.5 concentrations are measured. In 26 addition, based on the limited available evidence, the ISA concluded that “there is greater spatial 27 variability in PM 10-2.5 concentrations than PM 2.5 concentrations, resulting in increased exposure 28 error for the larger size fraction” (US EPA, 2009a , p. 2-8) and that available measurements do 29 not provide sufficient information to adequate ly characterize the spatial distribution of PM 10-2.5 30 concentrations (US EPA, 2009a, section 3.5.1.1). The net effect of these uncertainties on 31 epidemiologic studies of PM 10-2.5 is to bias the results of such st udies toward the null hypothesis. 32 That is, as noted in the ISA, these limitations in estimates of ambient PM 10-2.5 concentrations 33 “would tend to increase uncertainty and make it more difficult to detect effects of PM 10-2.5 in 34 epidemiologic studies” (U S EPA 2009a, p. 2-21). 353-16 D raft-Do Not Quote or Cite June 2010 Given these limitations in PM 10-2.5 monitoring, different epidemiologic studies have 1 employed different approaches to estimating PM 10-2.5 concentrations, further contributing to 2 uncertainty in interpreting these studies. For example, as discussed above, the multi-city study 3 by Peng et al. (2008) estimated PM 10-2.5 by taking the difference between collocated PM 10 and 4

PM 2.5 monitors while the study by Zanobetti and Sc hwartz (2009) used th e difference between 5 county average PM 10 and PM 2.5 concentrations. A small numbe r of studies have directly 6
measured PM 10-2.5 concentrations with dichotomous samplers (e.g., Burnett et al., 2004; 7 Villeneuve et al., 2003; Klemm et al., 2004) . It is not clear how computed PM 10-2.5 8 measurements, such as those used by Za nobetti and Schwartz, compare with the PM 10-2.5 9
concentrations obtained in other studies eith er by direct measurement with a dichotomous 10 sampler or by calculating the difference using co-located samplers (US EPA, 2009a, section 11 6.5.2.3). 3 Given the use of these differe nt approaches to estimating PM 10-2.5 concentrations 12 across studies, and their inherent limitations, the distributions of thoracic coarse particle 13 concentrations over which reported health ou tcomes occur remain highly uncertain. 14 The ISA also notes that the potential fo r confounding by co-occurring pollutants, 15 particularly PM 2.5 , has been addressed in only a relatively small number of PM 10-2.5 16 epidemiologic studies, introducing additional uncerta inty into the interpretation of these studies 17 (US EPA, 2009a, section 2.3.3). This is a par ticularly important consideration given the 18 relatively limited body of experimental evidence available to support the plausibility of 19
associations between PM 10-2.5 itself and health effects reported in epidemiologic studies. As 20 discussed above, many epidemiologic studies that have evaluated co-pollutant models have 21 reported that PM 10-2.5 effect estimates remain positive, but lose precision and are not statistically 22 significant in these models (US EPA, 2009a, Figures 6-5, 6-9, 6-15). The net effect of this 23 limitation in the number of epidemiologic studie s that have evaluated co-pollutant models, 24 combined with the limited number of supporting experimental studies, is to increase the 25 uncertainty associated with estimates of the extent to which PM 10-2.5 itself, rather than one or 26 more co-occurring pollutants, is responsible for repor ted health effects. 27 Another uncertainty results from the relativ e lack of information on the chemical and 28 biological composition of PM 10-2.5 , and the effects associated with the various components (ISA, 29 section 2.3.4). As discussed above, a few recent studies have evaluated associations between 30 health effects and particles of non-urban, crustal origin by evalua ting the health impacts of sand 31 storm events. Though these studies provide some information on the health effects of particles 32 that likely differ in composition from the partic les of urban origin that are typically studied, 33

3 In addition, when the difference between PM 2.5 and PM 10 is calculated, the potential for differences among operational flow rates and temperatures for PM 10 and PM 2.5 monitors add to the potential for exposure misclassification.3-17 D raft-Do Not Quote or Cite June 2010 without more information on the chemical speciation of PM 10-2.5 , the apparent variability in 1
associations with health effect s across locations is difficult to characterize (US EPA, 2009a, 2 section 6.5.2.3). 3 As discussed above, a 24-hour PM 10 standard is in place to protect the public health 4 against exposures to thoracic coarse particles. Therefore, in furt her considering the adequacy of 5
the current PM 10 standard, we ask the following question: 6

 To what extent does the available scient ific evidence report associations between 7 PM 10-2.5 and morbidity and mortality in areas that would likely meet the current PM 10 8 standard? 9 In addressing this question, we have used EPA’s Air Quality System (AQS) 4 to 10
characterize PM 10 concentrations in U.S. locations where both single-city and multi-city PM 10-2.5 11 studies have been conducted (see U.S. EPA, 200 9a, Figures 6-1 to 6-30 for studies). When 12 compared to single-city studies, we note that multi-city studies assess PM 10-2.5 -associated health 13 effects among larger study populations, pr oviding enhanced power to detect PM 10-2.5 -associated 14 health effects. In addition, multi-city studies often provide spatial coverage for different regions 15 across the country, reflecting differences in PM 10-2.5 sources, composition, and potentially other 16 factors that could impact PM 10-2.5 -related effects. These fact ors make multi-city studies 17 particularly important when draw ing conclusions about health e ffect associations. However, 18 multi-city studies often present overall effect estimates rather than single-city effect estimates, 19 while short-term air quality can va ry considerably across cities. Therefore, the extent to which 20 effects reported in multi-city studies are associated with the short-term air quality in any 21 particular location is uncertain, especially when considering shor t-term concentrations at the 22 upper end of the distribution of daily concentratio ns for pollutants with relatively heterogeneous 23 spatial distributions such as PM 10-2.5 and PM 10 (US EPA, 2009a, section 2.1.1.2). In contrast, 24 single-city studies are more limited in terms of power and geographic coverage but the link 25 between reported health effects and the short- term air quality in a given city is more 26 straightforward to establish. As a result, in considering 24-hour PM 10 concentrations in locations 27 of epidemiologic studies, we have focused belo w primarily on single-city studies (Figures 3-2 28 and 3-3) and single-city analyses of the loca tions evaluated in the multi-city study by Zanobetti 29 and Schwartz (US EPA, 2009a, Figure 6-29). 30
The current PM 10 standard has a form of one-expect ed-exceedance per year, averaged 31 over 3 years. In order to compare PM 10 concentrations in study locat ions to the level of the 32 current standard, we have identified the PM 10 3-year expected exceedance concentration33 equivalent design value for each study period (label ed “DV” in Figures 3-2 and 3-3 below) using 34

4 http://www.epa.gov/ttn/airs/airsaqs/3-18 D raft-Do Not Quote or Cite June 2010 the protocol specified in the PM 10 State Implementation Plan (SIP) Development Guidelines (US 1 EPA, 1987). 5 Some studies (indicated by a * in Figure 3-3) covered time periods of less than 2 three years. For these study areas, to characterize ambient PM 10 concentrations relative to 3
concentrations allowed under the current PM 10 standard, we averaged the second highest 24-hour 4

PM 10 concentrations for each year of the study (i .e., second highest concentration measured at 5 the single monitor in the study ar ea recording the highest such c oncentration). The identification 6 of concentration-equivalent de sign values and second highest PM 10 concentrations for each study 7
area are described in more detail in the me mo by Schmidt and Jenkins (2010). 8

5 Specifically, the PM 10 3-year expected exceedance concentration-equivalent design value is identified as the highest 24-hour average concentr ation (i.e., from a single monitor in the study area) over a 3-year peri od when there are 347 or fewer samples reported for that time-frame, the second highest 24-hour average concentration when there are 348 to 695 samples in the 3-year period, the third highest 24-hour average concentration when there are 696 to 1042 samples in the 3-year period, and the fourth highest 24-hour average concentration when there are 1043 or more samples reported over the 3-year period. Concentration-equivalent design values were not identified for study periods less than 3 years.3-19Draft-Do Not Quote or CiteJune 2010Figure 3-2.PM10Air Quality and PM10-2.5Effect Estimates in Locations of U.S. PM10-2.5Mortality Studies++12++Studies in Figures 3-2 and 3-3 are a combination of those assessedin the last review and those assessed in the ISA in the current review. Studies in these3figures are ordered by increasing PM10concentration-equivalent design values.43-20Draft-Do Not Quote or CiteJune 2010Figure 3-3.PM10Air Quality PM10-2.5Effect Estimates in Locations of U.S. PM10-2.5Morbidity Studies12* Concentration-equivalent design values were not identified for study periods less than three years. For study periods of less than three years, we averaged the3second highest 24-hour PM10concentrations for each year of the study (i.e., second highest concentration measured by thesingle monitor in the study area4recording the highest such concentration).53-21 D raft-Do Not Quote or Cite June 2010 In addition to the single-city studies included in Figures 3-2 and 3-3 above, multi-city 1 averages of the 3-year expected exceedance c oncentration-equivalent design values for U.S. 2 multi-city studies were 114  g/m 3 (for the locations evaluate d by Zanobetti and Schwartz, 2009) 3

and 100  g/m 3 (for the locations evaluated by Peng et al ., 2008). As discussed above, the extent 4
to which overall PM 10-2.5 effect estimates reported in multi-city studies are associated with the air 5 quality in any particular locati on is uncertain. However, the IS A also presents Bayes-adjusted 6 single-city effect estimates for each of the citi es evaluated by Zanobetti and Schwartz (US EPA, 7 2009a, Figure 6-29), providing the opportunity to consider associations between PM 10-2.5 and 8 mortality, and to consider the PM 10 air quality, in each of the indivi dual cities evaluated in this 9 study. 10 As discussed above, in single-city analyses in the locations evaluated by Zanobetti and 11 Schwartz, PM 10-2.5 effect estimates for mortality were generally positive but not statistically 12 significant, and most were sim ilar in magnitude and precision, particularly for cardiovascular 13 mortality, across a wide range of estimated PM 10-2.5 concentrations (US EPA, 2009a, Figure 6- 14 29). Three-year PM 10 expected exceedance concentration- equivalent design values in these 15 cities ranged from 50  g/m 3 (Davie, FL) to 381  g/m 3 (El Paso, TX). In most of the cities 16 evaluated (36 of 47), concentration-e quivalent design valu es were below 150  g/m 3 (Schmidt 17 and Jenkins, 2010). In the six cities wher e positive and statistically significant PM 10-2.5 mortality 18 effect estimates were reported (see above), conc entration-equivalent de sign values were as 19 follows (Schmidt and Jenkins, 2010): 20

 Chicago: 113  g/m 3 21

 Pittsburgh: 139  g/m 3 22

 Birmingham: 154  g/m 3 23

 Detroit: 165  g/m 3 24

 St. Louis: 165  g/m 3 25

 Salt Lake City: 283  g/m 3 26 Therefore, while PM 10-2.5 effect estimates in single-city analyses were not statistically significant 27 for most locations evaluated by Zanobetti a nd Schwartz, including some locations with PM 10 28
concentrations well above those allowed by the current 24-hour PM 10 standard, positive and 29 statistically significant PM 10-2.5 effect estimates were reporte d in two loca tions (Chicago, 30 Pittsburgh) with concentration-e quivalent design values below 150  g/m 3

. 31 In considering PM 10-2.5 epidemiologic studies conducted in Canada and elsewhere outside 32 the U.S., we note that we ge nerally do not have access to PM 10 air quality information beyond 33 that published by the study authors. Many of th ese studies report PM concentrations averaged 34 across monitors, rather than from the highest mon itor in the study area, and/ or report only mean 353-22 D raft-Do Not Quote or Cite June 2010 or median concentrations. Lin et al. (2002) reported positive and st atistically significant 1
associations between PM 10-2.5 and asthma hospital admissions in children in Toronto (US EPA, 2 2009a; Figures 6-12, 6-15). The authors reported a maximum PM 10 concentration measured at a 3 single monitor in the study area of 116  g/m 3 , suggesting that the PM 10 air quality in Toronto 4 during this study would have been permitted by the current 24-hour PM 10 standard. In contrast 5 Middleton et al. (2008), who repor ted that dust storms in Cypr us were associated with a 6 statistically significant increase in risk of hospitalization for all causes and a non-significant 7 increase in hospitalizations for cardiovas cular diseases, reported a maximum 24-hour PM 10 8 concentration of 1,371  g/m 3 . Thus, the dust storm-associated increases in hospitalizations 9 reported in this study occurred in an area with PM 10 concentrations that were likely well above 10 those allowed by the current standard. Other dus t storm studies did not report maximum 24-hour 11

PM 10 concentrations from individual monitors, th ough the studies by Chan et al. (2008) and Bell 12 et al. (2008), who reported positive and statisticall y significant associations between dust storm 13 metrics and cardiovascular-related hospita l admissions, reported that 24-hour PM 10 14 concentrations, averaged acr oss monitors, exceeded 200  g/m 3 . It is likely that peak 15
concentrations measured at individual monitors in these studies were much higher and, therefore, 16
24-hour PM 10 concentrations in these study areas were likely above those allowed by the current 17
standard. 18 Summary of Evidence-Based Considerations 19 New evidence supporting an association between PM 10-2.5 and mortality and morbidity 20
has become available since the last review of the PM NAAQS. The available evidence was 21 judged in the ISA to be suggestive of a causal relationship between short-term PM 10-2.5 22 exposures and mortality, cardiov ascular effects, and respirator y effects while the evidence was 23 judged inadequate to infer a causal relationship with long-term PM 10-2.5 exposures (US EPA, 24 2009a, section 2.3.3; see Table 3-1 above). The evidence supporting a link between short-term 25 thoracic coarse particle exposures and a dverse health effects comes primarily from 26 epidemiologic studies, with limited supporting evidence from controlled human exposure studies 27 and, to a lesser extent, animal instillation studi es. This evidence includes several recent (i.e., 28 published since the last review of the PM NA AQS) multi-city epidemiologic studies conducted 29 in the U.S., Canada, and Europe and a small numb er of recent studies of particles of non-urban 30 origin. In general, epidemiologic studies have reported positive, and in some cases statistically 31 significant, PM 10-2.5 effect estimates. In the limited number of studies that have evaluated co32 pollutant models that include either ga seous pollutants or fine particles, PM 10-2.5 effect estimates 33 generally remain positive, and in a few cases statistically significant. 34
Positive associations between PM 10-2.5 and mortality and morbidity have been reported in 35
a number of locations across the U.S. with a wide range of PM 10-2.5 and PM 10 concentrations. 363-23 D raft-Do Not Quote or Cite June 2010 Among single-city analyses, PM 10-2.5 effect estimates were positive and statistically significant in 1 a few U.S. cities and at least one Canadian city with ambient PM 10 concentrations that would be 2 allowed by the current 24-hour PM 10 standard. However, most PM 10-2.5 effect estimates, even 3 those reported in locations with PM 10 concentrations above the concentrations allowed by the 4 current standard, were not st atistically significant. 5

3.2.2 Staff Conclusions on Adequacy of Current PM 10 Standard 6 In light of the available PM 10-2.5 health evidence and the PM 10 air quality concentrations 7 in study locations, as discussed above, we revi sit the overarching question: Does the currently 8 available scientific evidence, as reflected in th e ISA, and air quality information support or call 9 into question the adequacy of the prot ection afforded by the current 24-hour PM 10 standard 10 against effects associated with exposur es to thoracic coarse particles? 11 In considering the evidence and information as they relate to the adequacy of the current 12
24-hour PM 10 standard we note that, as discussed above , this standard is meant to protect the 13 public health against effects associat ed with short-term exposures to PM 10-2.5 . In the last review, 14 it was judged appropriate to maintain such a standard given the “growing body of evidence 15 suggesting causal associations between short-term exposure to thoracic coarse particles and 16 morbidity effects, such as respiratory symptoms and hospital admissions for respiratory diseases, 17 and possibly mortality” (71 FR 61185, October 17, 2006). Given the expanded body of evidence 18 available in the current review, discussed in detail in the ISA (US EPA, 2009a, Chapter 6) and 19 summarized above, we conclude th at the evidence continues to support the appropriateness of a 20 standard to protect the public health against effects associated with short-term exposures to 21

PM 10-2.5 . In addition, when considering th e evidence for associations with PM 10-2.5 from different 22 types of sources and in different locations (e .g., urban/industrial as we ll as windblown dust of 23 non-urban origin), we conclude that it rema ins appropriate to provide some measure of 24 protection against exposures to a ll thoracic coarse particles. 25 In considering the evidence, we note that a decision on the adequacy of the public health 26 protection provided by the current PM 10 standard will be a public health policy judgment in 27 which the Administrator weighs that evidence and its inherent uncertainties. Therefore, 28 depending on the emphasis placed on different aspects of the evidence and uncertainties, 29
consideration of different conclusion s on adequacy could be supported. 30 For example, one approach to considering the evidence and its associated uncertainties 31 would be to place emphasis on the following: 32

 Several multi-city epidemiologic studies c onducted in the U.S., Canada, and Europe, as 33 well as a number of single-city studies, have reported generally positive, and in some 34 cases statistically significant, a ssociations betwee n short-term PM 10-2.5 concentrations and 353-24 D raft-Do Not Quote or Cite June 2010 adverse health endpoints including mortality and cardiovascular- and respiratory-related 1 hospital admissions and emergency department visits. 2 3

 A number of single-city anal yses (including the majority of the Bayes-adjusted single4 city analyses in locations evaluated by Za nobetti and Schwartz ( 2009)), using different 5 approaches to estimate ambient PM 10-2.5 concentrations, have reported positive PM 10-2.5 6 effect estimates in lo cations with 24-hour PM 10 concentrations that are allowed by the 7 current PM 10 standard. In a few cases, these PM 10-2.5 effect estimates were statistically 8 significant. 9 10

 While limited in number, studies that have ev aluated co-pollutant models have generally 11 reported that PM 10-2.5 effect estimates remain positive, and in a few cases statistically 12 significant, when these models include ga seous pollutants or fine particles. 13 14

 Support for the plausibility of the associati ons reported in epidemiologic studies is 15 provided by a limited number of controlled human exposure studies reporting that short16 term (i.e., 2-hour) exposures to PM 10-2.5 decrease heart rate variability and increase 17 markers of pulmonary inflammation. 18 19 Such an approach to considering the evidence would place substantial weight on the generally 20 positive PM 10-2.5 effect estimates that have been reporte d for mortality and morbidity, even those 21
effect estimates that are not sta tistically significant. This coul d be judged appropr iate given that 22
consistent results have been reported across multipl e studies using different approaches to 23
estimate ambient PM 10-2.5 concentrations and that exposure meas urement error, which is likely to 24 be larger for PM 10-2.5 than for PM 2.5 , tends to bias the results of epidemiologic studies toward the 25 null hypothesis, making it less likely that associati ons will be detected. To the extent that a 26 decision on the adequacy of the current 24-hour PM 10 standard were to place emphasis on the 27 considerations noted above, it could be judged that the current 24-hour PM 10 standard does not 28 provide adequate public health pr otection and that it should be revised in order to increase 29 protection against effects associat ed with short-term exposures to thoracic coarse particles. 30 Another approach to considering the eviden ce and its uncertainties would be to place 31 emphasis on the following: 32

 While most of PM 10-2.5 effect estimates reported for mortality and morbidity were 33 positive, many were not statistically significant, even in single-pollutant models. This 34 includes effect estimates repor ted in study locations with PM 10 concentrations well35 above those allowed by the current 24-hour PM 10 standard. 36

 The number of epidemiologic studies that have employed co-pollutant models to 37 address the potential for confounding, particularly by PM 2.5 , remains limited. 38 Therefore, the extent to which PM 10-2.5 itself, rather than one or more co-pollutants, 39 contributes to reported health effects remains uncertain. 403-25 D raft-Do Not Quote or Cite June 2010  Only a limited number of experimental stud ies provide support for the associations 1 reported in epidemiologic studies, resulti ng in further uncertainty regarding the 2 plausibility of the associations between PM 10-2.5 and mortality and morbidity reported 3 in epidemiologic studies. 4

 Limitations in PM 10-2.5 monitoring and the different ap proaches used to estimate 5 PM 10-2.5 concentrations across epidemiologic studies result in uncertainty in the 6 ambient PM 10-2.5 concentrations at which the reported effects occur. 7

 The chemical and biological composition of PM 10-2.5 , and the effects associated with 8 the various components, remains uncertain. Without more information on the chemical 9 speciation of PM 10-2.5 , the apparent variability in a ssociations across locations is 10 difficult to characterize. 11 To the extent that a decision on the adequacy of the current 24-hour PM 10 standard were to place 12 emphasis on the considerations no ted above, it could be judged that , while it remains appropriate 13 to maintain a standard to protec t against short-term exposures to thoracic coarse particles, the 14 available evidence does not provi de a sound basis for concludi ng that the current 24-hour PM 10 15 standard fails to protect public he alth with an adequate margin of safety. Such an approach to 16 considering the evidence could al so note the ISA conclusions that , when considered as a whole, 17 the available evidence is “suggestive” of a causal relationship between short-term PM 10-2.5 18 exposures and mortality, cardiov ascular effects, and respirator y effects. These weight-of19
evidence conclusions contrast with t hose for the relationships between PM 2.5 exposures and 20 adverse health effects, which were judged in the ISA to be either “causal” or “likely causal” for 21 mortality, cardiovascular effects, and respirat ory effects. Thus, while this approach to 22 considering the evidence would recognize the positiv e, and in some cases statistically significant, 23
associations between PM 10-2.5 and mortality and morbidity by ma intaining a standard to protect 24 against exposures to thoracic co arse particles, it would place re latively greater emphasis on the 25 limitations and uncertainties noted above, which tend to complicate the interpretation of that 26
evidence. 27

Given all of the above, we concl ude that consideration could be given to either retaining or 28 revising the current 24-hour PM 10 standard, depending on the appro ach taken to considering the 29 available evidence and information. Therefore, we judge that it is appr opriate in this Policy 30 Assessment to consider what pot ential alternative sta ndards, if any, could be supported by the 31
available scientific evidence in order to increas e public health protecti on against exposures to 32

PM 10-2.5
. 333-26 D raft-Do Not Quote or Cite June 2010 3.3 CONSIDERATION OF POTENTIAL ALTERNATIVE STANDARDS 1

Staff next considers the fo llowing overarching question: 2

What potential alternative standard(s) coul d be supported by the currently available 3 scientific evidence and air quality information to increase public health protection against 4 exposures to PM 10-2.5 ? 5

In addressing this overarching question, we consider how the currently available 6 scientific evidence and air quality information could inform decisions regarding the basic 7 elements of the NAAQS: indicator (section 3.3.1 ), averaging time (section 3.3.2), form (section 8 3.3.3), and level (section 3.3.4). 9

3.3.1 Indicator 10
As discussed above, PM 10 includes both PM 10-2.5 and PM 2.5 , with the relative contribution 11
of each to PM 10 mass varying across locations (see below) . In the most recent review completed 12 in 2006, EPA concluded that the PM 10 indicator remained appropriate because a PM 10 standard 13 would be expected to provide a ppropriate protection against effect s associated with exposures to 14

PM 10-2.5 . In particular, a PM 10 indicator would be expected to target protection to urban areas, 15 where the evidence of effects from exposure to co arse PM is the strongest (71 FR at 61196). In 16 considering potential alternative standards in the current review, we have considered the 17 following question with regard to indicator: 18

 To what extent does the available eviden ce and/or air quality information provide 19 support for retaining or revising the current PM 10 indicator? 20 In addressing this question, we fo cus on the following considerations: 21

 The extent to which PM 10 is comprised of PM 10-2.5 22 23

 The appropriateness of a standard that allows lower PM 10-2.5 concentrations in areas with 24 higher fine particle concentrati ons (i.e., urban areas) than ar eas with lower fine particle 25 concentrations (i.e., rural areas) (see Schmidt, 2005 for urban-rural comparison) 26 27 As an initial matter, we consider the proportion of PM 10 mass in different regions of the 28
U.S. that is PM 10-2.5 (see US EPA, 2009a, section 3.5.1.1; Schmidt and Jenkins, 2010). Schmidt 29 and Jenkins (2010) divided the U.S. into climatic regions using the same approach as used in the 30 multi-city epidemiologic study by Zanobetti and Schwartz (2009) (see above). 6 Consistent with 31

6 The Mediterranean region includes CA, OR, WA. The Dr y region includes NM, AZ, NV. The Dry Continental region includes MT, ID, WY, UT, CO. The Hot Summer Continental region includes SD, NE, IA, IL, IN, OH. The Warm Summer Continental region includes ND, MN, WI, MI, PA, NY, CT, RI, MA, VT, NH, ME. The Humid Subtropical and Maritime region includes FL, LA, TX , GA, AL, MS, AR, OK, KS, MO, TN, SC, NC, VA, WV, KY, NJ, DE, DC, MD.3-27 D raft-Do Not Quote or Cite June 2010 the air quality analyses in the ISA (US EP A, 2009a, section 3.5.1.1) and the concentration 1 estimates of Zanobetti and Schwartz (2009), PM 10-2.5 concentrations were higher in the western 2 U.S. than the east, with the highest concentr ations in the southwest (data not shown, from 3 Schmidt and Jenkins, 2010). On average, ratios of PM 10-2.5 concentrations to PM 10 4 concentrations were also higher in the western U.S. than in the eastern U.S., with the southwest 5 (i.e., Dry region in Figure 3-4) having the highest ra tios. Consistent results were reported in the 6 ISA analyses of PM air quality (US EPA, 2009a, compare Tables 3-9 and 3-10). While the same 7 general pattern persisted when the anal ysis was restricted to days with PM 10 concentrations at the 8 high end of the distribution of daily concentrations (i.e., at or above 95 th percentile), ratios of 9

PM 10-2.5 to PM 10 on these days tended to be somewhat highe r, on average, across most regions of 10 the U.S. (see right-hand columns in Figure 3-4). 11

Figure 3-4. Site-Level Ratio of Daily PM 10-2.5 to Daily PM 10 * 12

13 *Blue stars represent mean concentrations, horizont al lines represent median concentrations, boxes 14 represent 75% confidence intervals, and error bars represent 95% confidence intervals. N values 15 equal the number of site years of monitoring data for each region

. 16 17 Thus, on average across the U.S., PM 10-2.5 comprises a larger portion of PM 10 on days with 18 relatively high PM 10 concentrations than on days with more typical PM 10 concentrations. This 19 suggests that elevated PM 10 concentrations across much of th e U.S. are due in large part to 20
elevations in PM 10-2.5 mass. Given this, we conclude that a PM 10 standard would be most 21 effective at limiting PM 10-2.5 concentrations if it focuses on th e upper end of the distribution of 22 daily PM 10 concentrations. This issue is discussed fu rther below in the context of the standard 23 form (section 3.3.3). 24 Given the above conclusion, in further consid ering the issue of indicator we note that 25 most of the evidence for positive associations between PM 10-2.5 and morbidity and mortality, 263-28 D raft-Do Not Quote or Cite June 2010 particularly evidence for these associations at relatively low concentrations of PM 10-2.5 , continues 1
to come from studies conducted in locations where the PM 10-2.5 is expected to be largely of urban 2 origin. While some studies have reported pos itive associations between relatively high 3 concentrations of particles of non-urban origin (i.e., crustal material from windblown dust in 4 non-urban areas, see above) and mortality and morbid ity, we note that the extent to which these 5 associations would remain at the lower partic le concentrations more typical of U.S. and 6 Canadian urban study locations remains uncertain. 7 Given these considerations, and given the 7 increased potential for coarse particles in urban areas to become contaminated by toxic 8 components of fine particles from urban/industria l sources (US EPA, 2004), we conclude that it 9 remains appropriate to maintain a standard that allows lower ambient th oracic coarse particle 10
concentrations in urban areas than in non-urban areas. 11 Given this conclusion, we note that it would be reasonable to consider an indicator that 12 targets control on areas with the types of ambient mixes generally present in urban areas. Such 13
an indicator would focus control on areas with am bient mixes known with greater certainty to be 14
associated with adverse health effects and, therefore, would prov ide public health benefits with 15 the greatest degree of certai nty. As noted in the last review of the PM NAAQS, a PM 10 standard 16
would allow lower concentrations of PM 10-2.5 in areas with higher fine particle concentrations, 17 which tend to be urban locations, than areas with lower fine particle c oncentrations, which tend 18 to be rural locations (Schmidt et al., 2005). Therefore, we reach the conclusion that a PM 10 19 indicator would appropriately targ et protection to those locations where the evidence is strongest 20
for associations between adverse health effects a nd exposures to thoracic coarse particles. In 21 contrast, we note that a PM 10-2.5 indicator, for a standard set at a single unvarying level, would 22 not achieve this targeting, given that allowable thoracic coarse particle concentrations would be 23 the same regardless of the location or the likely sources of PM. Theref ore, given the currently 24 available evidence, one possi ble result of using a PM 10-2.5 indicator would be a standard that is 25 overprotective in rural areas and/or underprotective in urban areas. 26 In addition, while we note that administrative feasibility is not an appropriate basis for 27 informing decisions on the NAAQS (s ee above), we also note that PM 10-2.5 concentrations are not 28 routinely measured and reported at present (US EPA, 2009a, section 3.5.1.1). In the last review 29 of the PM NAAQS, EPA required monitoring of PM 10-2.5 mass and expects approximately 80 30 stations to be reporting mass concentrations by January 1, 2011, as part of the National Core 31

7 Other than the dust storm studies, we note that the stud y in Coachella Valley by Ostro et al. (2003) reported statistically significant associations in a location where coarse particles are exp ected to be largely due to windblown dust. Specifically, we note the CASAC conclusion in the last review that “studies from Ostro et al. showed significant adverse health effects, pr imarily involving exposures to coarse -mode particles arising from crustal sources” (Henderson, 2005). In considering this study, we also note the relatively high PM 10 concentrations in the study area (see Figure 3-2 above).3-29 D raft-Do Not Quote or Cite June 2010 (NCore) network ( http://www.epa.gov/ttn amti1/ncore/index.html ). However, data from those 1 monitors are not yet available for locations and time periods of PM 10-2.5 health studies. 2 Given all of the above considerations, we c onclude that the available evidence supports 3
consideration in the current review of a PM 10 indicator for a standard that protects against 4 exposures to thoracic coarse part icles. We further conclude th at consideration of alternative 5 indicators (e.g., PM 10-2.5 ) in future reviews is desirable and could be informed by additional 6 research, as described be low (section 3.4). 7

3.3.2 Averaging Time 8 Based primarily on epidemiologic studies that reported positive a ssociations between 9 short-term (24-hour) PM 10–2.5 concentrations and mortality a nd morbidity, the Administrator 10
concluded in the last review th at the available evid ence supported a 24-hour averaging time for a 11
standard intended to control thorac ic coarse particles. In cont rast, given the relative lack of 12 studies supporting a link between long-term exposures to thoracic coarse particles and morbidity 13 or mortality (US EPA, 2004a, Chapter 9), the Ad ministrator further concluded that an annual 14 coarse particle standard was not warr anted at that time (71 FR 61198-61199). 15 In the current review, we consider the exte nt to which the available evidence provides 16 information relevant for decisions on averagi ng time by considering the following question: 17

 To what extent does the available evidence continue to support a 24-hour averaging 18 time for a standard meant to protect agains t effects associated with exposures to 19 PM 10-2.5 ? 20 With regard to this question, we note the c onclusions from the ISA regarding the weight 21 of evidence for short-term and long-term PM 10-2.5 exposures as well as th e studies on which those 22 conclusions are based. Specifi cally, as discussed above (see Table 3-1 above), the ISA 23 concludes that the existing evidence is suggestive of a causal relationship between short-term 24

PM 10-2.5 exposures and mortality, cardi ovascular effects, and respir atory effects (ISA, section 25 2.3.3). This conclusion is based largely on ep idemiologic studies which have primarily 26
evaluated associations between 24-hour PM 10-2.5 concentrations and morbidity and mortality 27 (e.g., see ISA, Figure 2-3), though a small number of controlled human exposure studies have 28 reported effects following shorter exposures (i.e., 2-hours) to PM 10-2.5 (e.g., see ISA, sections 29 6.2.1.2, 6.3.3.2). In contrast, with respect to l ong-term exposures, the ISA concludes that 30
available evidence is inadequate to infer a causal relationship with all health outcomes 31 evaluated (US EPA, 2009a, secti on 2.3). Specifically, the ISA st ates, “To date, a sufficient 32
amount of evidence does not exist in order to draw conclusions regarding the health effects and 33 outcomes associated with long-term exposure to PM 10-2.5 ” (US EPA, 2009a, section 2.3.4; see 34 Table 3-1 above). 353-30 D raft-Do Not Quote or Cite June 2010 In considering these weight of evidence determin ations in the ISA, we conclude that, at a 1 minimum, they suggest the importa nce of maintaining a standard th at protects against short-term 2 exposures to thoracic coarse pa rticles. Given that the major ity of the evidence supporting the 3
link between short-term PM 10-2.5 and morbidity and mortality is based on 24-hour average 4 thoracic coarse particle concentrations, we conc lude that the evidence av ailable in this review 5 continues to support consideration of a 24-hour averaging time for a PM 10 standard meant to 6 protect against effects associated with short-term exposures to PM 10-2.5 . We further conclude that 7 the available evidence does not support consider ation of an annual thoracic coarse particle 8 standard at this time. In reaching this conclusi on, we also note that, to the extent a short-term 9 standard requires areas to reduce their 24-hou r ambient particle concentrations, long-term 10 concentrations would also be expected to decr ease. Therefore, a 24-hour standard meant to 11 protect against short-term exposur es to thoracic coarse particle s would also be expected to 12 provide some protection agains t any potential effects of l ong-term exposures at ambient 13
concentrations. 14

3.3.3 Form 15 The “form” of a standard defines the air quality statistic that is to be compared to the 16 level of the standard in determining whether an ar ea attains that standard. In identifying a single 17 statistic for the form, we note that although futu re air quality improveme nt strategies in any 18 particular area are not yet defined, most such strategies are likely to affect a broad distribution of 19 PM air quality concentrations in an area. Therefore, although the form of the standard defines a 20 single statistic, any resulting reductions in health risks are likely to occur across a wide range of 21
concentrations. 22 As discussed above, in the last review th e Administrator retained the one-expected 23 exceedance form of the primary 24-hour PM 10 standard. This decision was linked to the overall 24 conclusion that “the level of protection from coarse particles provide d by the current 24-hour 25

PM 10 standard remains requisite to protect public h ealth with an adequate margin of safety” (71 26 FR 61202). Because revising either the level or th e form of the standard would have altered the 27 protection provided, it was concluded that such changes “would not be appropriate based on the 28
scientific evidence available at this time” (71 FR 21202). Theref ore, the decision in the last 29 review to retain the one-expected-exceedance fo rm was part of the broader decision that the 30 existing 24-hour standard provided requi site public health protection. 31 In the current review, we are also considering the form of the standard within the context 32 of the overall decision on whether, and if so how, to revise the current 24-hour PM 10 standard. 33
Given the conclusions above re garding the appropriate indi cator and averaging time for 343-31 D raft-Do Not Quote or Cite June 2010 consideration for potential altern ative standards, we consider pot ential alternative forms for a 24- 1
hour PM 10 standard. To frame our c onsideration of this issue, we pose the following question: 2

 To what extent does availa ble evidence and information s upport consideration of an 3 alternative form for a 24-hour PM 10 standard? 4 Although the selection of a specifi c form must be made within the context of decisions on 5 the other elements of the standard, EPA genera lly favors concentration-based forms for short6
term standards. In 1997 EPA established a 98 th percentile form for the 24-hour PM 2.5 standard 7
and in 2010 EPA established a 98 th percentile form for the 1-hour NO 2 standard (62 FR 38671; 8 75 FR 6474). 8 In making these decisions, EPA noted th at, as compared to an exceedance-based 9 form, such as the form of the current PM 10 standard, a concentration-based form is more 10 reflective of the health risks posed by elevat ed pollutant concentrations because it gives 11 proportionally greater weight to days when concentrations ar e well above the level of the 12 standard than to days when the concentrations are just above the level of the standard. In 13 addition, when averaged over thr ee years, a concentr ation-based form can provide a stable 14 regulatory target, facilitating the development of stable implementation programs. 15 In further considering the issue of form in the current review of the 24-hour PM 10 16 standard, we note that a concentration-based fo rm better compensates for missing data and less 17 than-daily monitoring than an exceedance-based form. This is a particularly important 18
consideration in the case of PM 10 because, depending on ambient PM 10 concentrations, the 19 frequency of PM 10 monitoring differs across locations (U S EPA, 1987). With a concentration20 based form, such as a 98 th percentile form, attainment status would be determined based on PM 10 21 concentrations from the same part of the annual distribution of 24-hour PM 10 concentrations, 22 despite the potential for differences in the frequency of PM 10 monitoring across locations. In 23 contrast, with the current one-expected-exceedan ce form, differences in monitoring frequency 24
can result in attainment status in some locations being based on estimates of the number of days 25 per year that the standard level is expected to be exceeded (i.e., in locations with less-than-daily 26 monitoring), rather than actua l counts of the number of exceeda nces (see Appendix K to Part 50 27 of the CFR). The extent to which these es timates reflect actual exceedances becomes more 28 uncertain as the monitoring frequency decreases. 29 In considering specific concentration-based forms for a 24-hour PM 10 standard, we note 30 that, as discussed above, in past review s (62 FR 38671; 75 FR 6474) EPA has judged it 31 appropriate to define a standa rd that provides a balance between adequately limiting the 32

8 In the recently completed review of the SO 2 primary NAAQS, a 99 th percentile form was adopted. In the case of SO 2 , there was specific evidence that a 99 th percentile form would be more effective than a 98 th percentile form for controlling 5-minute peak SO 2 concentrations, which were of concern because controlled human exposure studies have linked 5-minute SO 2 exposures to respiratory effects (See 75 FR at 35541 (June 22, 2010)).3-32 D raft-Do Not Quote or Cite June 2010 occurrence of peak pollutant concentrations and providing a stable re gulatory target for 1 implementation programs. For short-term standard s, this balance has b een achieved by setting 2
the form of the standard at the upper end of the distribution of pollutant concentrations, but not 3 using the most extreme statistics, and by averagi ng pollutant concentratio ns over three years. 4
We conclude that similar considerations are rele vant in the current review for a decision on the 5
form of a PM 10 standard. Specifically, given that PM 10-2.5 is likely to make a larger contribution 6
to PM 10 mass on days with relatively high PM 10 concentrations than on days with more typical 7

PM 10 concentrations (see above), we conclude that it is appropriate to set the standard form at the 8 upper end of the annual di stribution of 24-hour PM 10 concentrations. In addition, given the 9 potential for local sources to have important impacts on monitored PM 10 concentrations (US 10 EPA, 2009a, section 2.1.1.2), we also c onclude that it is desirable to select a form that promotes 11 stability of local implementation programs. 9 12 Based on all of the above considerations, we conclude that, to the extent it is judged 13 appropriate to revise the current 24-hour PM 10 standard, it would be appropriate to consider a 14 range of potential al ternative standard levels based on 98 th percentile PM 10 concentrations. In 15 drawing this conclusion we note that, because of the current expected-e xceedance-based form 16 and the differences in monitoring frequency across locations, the stringency of a standard with a 17
98 th percentile form, relative to th e stringency of the current standard, will differ acr oss locations. 18 One consequence of this is that, compared to the current standard, a standard with a 98 th 19 percentile form (or any other concentration-based form) could be more stringent than the current 20
standard in some locations and less stringent in other locations , depending on the level of the 21
standard. This issue is discussed in more deta il below within the cont ext of specific potential 22
alternative standard levels. 23

3.3.4 Level 24 As noted above, to the extent it is judged in the current review that the 24-hour PM 10 25 standard does not provide adequate public health protection against exposur es to thoracic coarse 26 particles, potential alternative standard levels could be considered. Given the conclusions 27 described above for indicator, averaging time, and form, we conclude that it would be 28 appropriate to consider potential alternative levels for a 24-hour PM 10 standard with a 98 th 29

9 We note that in the most recent review of the NO 2 primary NAAQS, a 98 th percentile form was adopted, rather than a 99 th percentile form, due to the potential for “instability in the higher percentile concentr ations” near local sources (i.e., mobile sources on major roads) (75 FR 6493). See also, ATA III , 283 F. 3d at 374-75 (upholding 98 th percentile form since “otherwise States would have to design their pollution control programs around single high exposure events that may be due to unusual meteorological conditions alone, rendering the programs less stable – and hence, we assume, less effective – than programs de signed to address longer-ter m average conditions.”).3-33 D raft-Do Not Quote or Cite June 2010 percentile form. To inform our consideration of this issue, we have considered the following 1 question: 2

 To what extent does available evid ence and air quality information support 3 consideration of alternative standard levels for a 24-hour PM 10 standard with a 98 th 4 percentile form? 5

Evidence-based Considerations 6 In considering the evidence as it relates to potential alternative standard levels for 7 consideration, we first consider the relative we ight to place on specific epidemiologic studies, 8 including the weight to place on the uncertainties associated with those studies. We have 9 considered several factors in placing weight on specific epidemiologic studies including the 10 extent to which studies report statisti cally significant associations with PM 10-2.5 and the extent to 11 which the reported associations are robust to co-pollutant confounding. 12 In addition, we consider the extent to which associations with PM 10-2.5 can be linked to 13 the air quality in a specific location. With regard to this, we place greatest weight on information 14 from single-city analyses. Alt hough, as discussed above, multi-cit y studies have advantages in 15 terms of power to detect associations and ge ographic coverage, the ex tent to which effects 16 reported in multi-city studies are associated with the short-term air quality in any particular 17 location is highly uncertain, especially when cons idering short-term con centrations at the upper 18 end of the distribution of daily concentrations fo r pollutants with relative ly heterogeneous spatial 19
distributions such as PM 10-2.5 and PM 10 (US EPA, 2009a, section 2.1.1.2). In contrast, single-city 20 studies are more limited in terms of power and geographic coverage but the link between 21 reported health effects and the air quality in a give n city is more straightforward to establish (US 22 EPA, 2009a, section 2.1.1.2). Gi ven this, in considering PM 10 concentrations in locations of 23 epidemiologic studies, we place the most weight on single-city studies (Figures 3-2 and 3-3) and 24 single-city analyses of the locations evaluate d in the multi-city study by Zanobetti and Schwartz 25 (US EPA, 2009a, Figure 6-29). 26 In considering PM air quality in study locations, we also note that the available evidence 27 does not support the existence of thresholds, or lowest-observed- effects levels, in terms of 24- 28 hour average concentrations (US EPA, 2009a, sec tion 2.4.3). In the absence of an apparent 29 threshold, for purposes of identifying a range of standard levels pot entially supported by the 30 health evidence, we focus on the range of PM 10 concentrations that have been measured in 31 locations where U.S. epidemiologic studi es have reported associations with PM 10-2.5 (see U.S. 32 EPA, 2009a, Figures 6-1 to 6-30 for studies). In characterizing PM 10 air quality in PM 10-2.5 study 33 locations, we have used EPA’s AQS to identify the highest 98 th percentile 24-hour PM 10 34 concentrations for each year in each study locati on (i.e., from the monitor in the study area 35 recording highest 98 th percentile concentratio n), as described in Schm idt and Jenkins (2010). 363-34 D raft-Do Not Quote or Cite June 2010 The 98 th percentile concentrations from each study year were averaged together and these 1 averages are presented below in Figures 3-5 (PM 10-2.5 mortality studies) and 3-6 (PM 10-2.5 2 morbidity studies) for locations of single-city studies. 33-35Draft-Do Not Quote or CiteJune 2010Figure 3-5.98thPercentile PM10Concentrations in Locations of U.S. PM10-2.5Mortality Studies*12*Studies in Figures 3-5 and 3-6 are a combination of those assessed in the last review and those assessed in the ISA in the current review. Studies in these3figures are ordered by increasing 98thpercentile PM10concentrations.43-36Draft-Do Not Quote or CiteJune 2010Figure 3-6. 98thPercentile PM10Concentrations in Locations of U.S. PM10-2.5Morbidity Studies123-37 D raft-Do Not Quote or Cite June 2010 In addition to the single-city study locations in Figures 3-5 and 3-6, 98 th percentile PM 10 1 concentrations averaged acro ss the study locations evaluated in the multi-city studies by 2 Zanobetti and Schwartz (2009) and Peng et al. (2008) were 78  g/m 3 and 68  g/m 3 , respectively. 3 Multi-city effect estimates remained positive, and in some cases (i.e., Zanobetti and Schwartz for 4 all-cause and respiratory mortality) statistically significant, in co-polluta nt models that included 5 fine particles. 6 Bayes-adjusted single-city effect estimates for the 47 cities evaluated by Zanobetti and 7 Schwartz (US EPA, 2009a, Figur e 6-29), which were generally positive but not statistically 8 significant, can provide some additional insight into the PM 10 concentrations in specific locations 9
where associations between PM 10-2.5 and mortality have been reported. The 98 th percentile PM 10 10 concentrations in these cities ranged from 39  g/m 3 (Davie, FL) to 195  g/m 3 (El Paso, TX), and 11 in the 6 cities where positive and statistically significant PM 10-2.5 mortality effect estimates were 12 reported, 98 th percentile PM 10 concentrations were as follows (Schmidt and Jenkins, 2010): 13

 Chicago: 92  g/m 3 14

 Salt Lake City: 98  g/m 3 15

 Detroit: 105  g/m 3 16

 Pittsburgh: 110  g/m 3 17

 Birmingham: 122  g/m 3 18

 St. Louis: 138  g/m 3 19 Thus, in the single-city mortal ity studies in Figure 3-5 above, as well as the Bayes-adjusted 20 single-city analyses of the locations ev aluated by Zanobetti and Schwartz, positive and 21 statistically significant PM 10-2.5 effect estimates were reported in some locations with 98 th 22 percentile PM 10 concentrations as low as 92  g/m 3 (i.e., locations evaluated by Mar et al., 2003; 23 Ostro et al., 2003; Wilson et al., 2007; and the cities listed above, US EPA 2009a, Figure 6-29). 24 Similarly, among the U.S. morbidity studies, It o (2003) reported a positive and statistically 25 significant PM 10-2.5 effect estimate for hospital admissions for ischemic heart disease in Detroit, 26
where the 98 th percentile PM 10 concentration was well above 92  g/m 3 . PM 10-2.5 effect estimates 27 in this study remained positive, and in some cases statistically significant, in co-pollutant models 28 with gaseous pollutants (US EPA, 2009a, Figur es 6-5 and 6-15). Other morbidity studies 29 generally did not report st atistically significant PM 10-2.5 effect estimates, though effect estimates 30 were marginally significant (i.e., the lower confidence limit was 0) for asthma hospital 31 admissions in the Bronx (NYSDOH, 2006) and for respiratory infection-related admissions in 32 Detroit (Ito et al., 2003). 333-38 D raft-Do Not Quote or Cite June 2010 Air Quality-based Considerations 1
In addition to the evidence-based considera tions described above, we have used EPA’s 2 AQS to estimate the level of a 24-hour PM 10 standard with a 98 th percentile form that would 3 approximate the degree of prot ection, on average acro ss the country, provided by the current 24- 4
hour PM 10 standard with its one-expected-exceed ance form. Based on regression of 98 th 5 percentile PM 10 concentrations onto one-expected-exceed ance concentration equivalent design 6 values, a 98 th percentile PM 10 concentration of 87  g/m 3 is, on average, equivalent to a one7 expected-exceedance design value of 150  g/m 3 (see Figure 3-7 below and Schmidt and Jenkins, 8 2010). However, as indicated in Figure 3-7, the range of equi valent concentrations varies 9 considerably across monitoring sites (95% confidence interval ranges from 63 to 111  g/m 3 ) (see 10 Schmidt and Jenkins, 2010). As a consequence, while we note that a 98 th percentile 24-hour 11

PM 10 standard with a level of 87  g/m 3 would be expected to provi de public health protection 12 that is, on average across the U.S., equivalent to the protection provided by the current standard, 13
in some locations such a 98 th percentile standard could be more protective than the current 14
standard while in other locatio ns it could be less pr otective than the cu rrent standard. 153-39 D raft-Do Not Quote or Cite June 2010 Figure 3-7. Composite 3-year PM 10 98th percentile 24-hour average concentration versus 1 the PM 10 expected exceedance concentratio n-equivalent design value 2

3 4 In considering this issue in the specific locati ons where we have evidence for associations 5
between PM 10-2.5 and mortality or morbidity, we note that, as described above, positive and 6 statistically significant PM 10-2.5 effect estimates have been reported in the following U.S. 7
locations: 8

 Coachella Valley (Ostro et al., 2003) 9

 Detroit (Ito et al., 2003) 10

 Phoenix (Mar et al., 2003; Wilson et al., 2007) 11

 Chicago, Salt Lake City, De troit, Pittsburgh, Birmingham, St. Louis (US EPA, 2009a, 12 Figure 6-29) 13 In considering the PM 10 air quality, we note that 98 th percentile PM 10 concentrations were above 14

87  g/m 3 in all of these cities, even those with PM 10 concentration-equivalent design values 15

below 150  g/m 3 (Detroit, Chicago, Pittsburgh) (see section 3.2.1 above for PM 10 concentration16 equivalent design values). 173-40 D raft-Do Not Quote or Cite June 2010 To provide a broader perspective, we also used EPA’s AQS to compare the number of 1
U.S. counties with PM 10 one-expected-exceedance concentrati on-equivalent design values above 2

150  g/m 3 to the number with 98 th percentile PM 10 concentrations above 87  g/m 3 (for the years 3 2006 to 2008) (see Schmidt and Jenkins, 2010). The results in Table 3-2 below indicate the 4 following: 5

 In the eastern U.S., the number of counties with PM 10 one-expected-exceedance 6 concentration-equivalent design values above 150  g/m 3 is the same as that with 98 th 7 percentile PM 10 concentrations above 87  g/m 3 (i.e, none in the northeast and three in the 8 southeast). 9
10

 Some counties in the western U.S. (i.e., ten c ounties total in the s outhwest, northwest, and 11 Southern California) had PM 10 one-expected-exceedance concen tration-equivalent design 12
values above 150  g/m 3 but had 98 th percentile PM 10 concentrations below 87  g/m 3

. 13
14

 A small number of counties in th e midwest (i.e., four counties to tal in the industrial midwest 15 and upper midwest) had one-expected-exceedance concentration-equivalent design values 16
below 150  g/m 3 but had 98 th percentile PM 10 concentrations above 87  g/m 3

. 173-41Draft-Do Not Quote or CiteJune 20101Table 3-2. Counties with PM10Concentration-Equivalent Design Values > 150g/m3and 98thpercentile PM10concentrations2> 87g/m33Region >All U.S. Northeast SoutheastIndustrialMidwestUpperMidwest Southwest NorthwestSouthernCaliforniaTotal # of counties > 318 40 60 57 35 24 79 18Total population > 122,582 15,753 27,009 23,646 5,143 11,037 16,188 22,695Statistic Numbers of counties, populations, and percentages of total# counties 38 0 3 3 3 12 8 10population 22,450 0 4,159 1,789 710 6,106 1,366 8,220% # counties 12% 0% 5% 5% 9% 50% 10% 56%3-year average98thpercentile >87 μg/m3% population 18% 0% 15% 8% 14% 55% 8% 36%# counties 45 0 3 1 1 14 15 11population 32,169 0 4,159 348 28 7,675 2,075 17,724% # counties 14% 0% 5% 2% 3% 58% 19% 61%3-Year ExpectedExceedanceEquivalentDesign Value >150 μg/m3% population 26% 0% 15% 1% 1% 70% 13% 78%43-42 D raft-Do Not Quote or Cite June 2010 Integration of evidence- and ai r quality-based considerations 1 In considering the evidence a nd air quality information with in the context of identifying 2 potential alternative standard levels fo r consideration, we note the following: 3

 Although a 98 th percentile 24-hour PM 10 concentration of 87  g/m 3 is equivalent, on 4 average across the country, to a PM 10 concentration-equivale nt design value of 150 5
 g/m 3 , the 98 th percentile standard could be more st ringent than the current standard in 6 some locations (e.g., in the industrial and upper midwest) and less stringent than the 7 current standard in other locations (e.g., northwe st, southwest, and southern California). 8

 A 98 th percentile 24-hour PM 10 standard with a level at or below 87  g/m 3 would be 9 expected to maintain PM 10 and PM 10-2.5 concentrations below those present in U.S. study 10 locations where PM 10-2.5 effect estimates have been reported to be positive and 11 statistically significant. 12

 While studies generally reported positive PM 10-2.5 effect estimates in locations with 98 th 13 percentile PM 10 concentrations below 87  g/m 3 , these effect estimates were not 14 statistically significant. 15

To the extent the above considerations ar e emphasized, the approach to considering 16 potential alternative standard levels would place more weight on potential alternative standard 17 levels for which the evidence is strongest (e.g., mu ltiple single-city studies conducted in different 18 locations, using different approaches, and reporting positive and statistically significant 19
associations with PM 10-2.5 ). In particular, such an approach would plac e more weight on positive 20 and statistically significant PM 10-2.5 effect estimates that have been reported in single-city 21 analyses and less weight on PM 10-2.5 effect estimates that are not statistically significant and/or 22 that reflect estimates across multiple cities. It could be judged appropriate to place less weight 23
on PM 10-2.5 effect estimates that are not statistically significant given the re latively large amount 24 of uncertainty that is associ ated with the broader body of PM 10-2.5 health evidence, including 25 uncertainty in the extent to which health effect s evaluated in epidemiologic studies result from 26 exposures to PM 10-2.5 itself, rather than one or more co-o ccurring pollutants. In addition, it could 27 be judged appropriate to place less weight on 98 th percentile PM 10 concentrations averaged 28 across multiple cities, given the uncertainty in linking multi-city effect estimates with the air 29 quality in any particular location. To the extent this approach to cons idering the evidence and 30 uncertainties is applied, we concl ude that a standard level around 85  g/m 3 would be appropriate 31
to consider. 32 In contrast, alternative appro aches to considering the evidence could lead to consideration 33
of standard levels below 85  g/m 3 . For example, given that e xposure error is particularly 34 important for PM 10-2.5 epidemiologic studies and can bias the results of these studies toward the 35 null hypothesis, it could be judged appropriate to place more weight on positive associations 36 reported in epidemiologic studies, even when those associations are not sta tistically significant. 373-43 D raft-Do Not Quote or Cite June 2010 In addition, despite the uncertainties associated with interpreting multi-city average air quality 1 concentrations, it could be judged appropriate to place weight on PM 10-2.5 multi-city effect 2 estimates and, therefore, on the multi-city averages of 98 th percentile PM 10 concentrations in 3 study locations. To the extent that these cons iderations are emphasize d, we conclude that a 4
standard level as low as 65  g/m 3 could potentially be cons idered. A level of 65  g/m 3 would be 5 expected to maintain PM 10 and PM 10-2.5 concentrations below those in all of the single-city 6 mortality study locations in Figur e 3-5 above, including those where PM 10-2.5 effect estimates 7 were not statistically si gnificant. In addition, a standard level of 65  g/m 3 would be expected to 8
maintain PM 10 and PM 10-2.5 concentrations below the multi-city averages of 98 th percentile PM 10 9 concentrations in the locations evaluated by Za nobetti and Schwartz (2009) and Peng et al. 10 (2008), below concentrations in most locations of single-city morbidity st udies (including studies 11 conducted in Atlanta reporting both positive an d negative effect estimates), and below 12 concentrations in many locations where Bayes-adjusted single-city PM 10-2.5 effect estimates were 13 positive, though not statistically significant. 14 In considering potential altern ative standard levels below 65  g/m 3 , we note that, as 15 discussed above, the overall body of PM 10-2.5 health evidence is relatively uncertain, with 16 somewhat stronger support in U.S. studies for associations with PM 10-2.5 in locations with 98 th 17 percentile PM 10 concentrations above 87  g/m 3 than in locations with 98 th percentile PM 10 18

concentrations below 65  g/m 3 . Specifically, we note the following: 19

 Epidemiologic studies, either single-city or multi-city, have not reported positive and 20 statistically significant PM 10-2.5 effect estimates in locations with 98 th percentile PM 10 21 concentrations (multi-city average 98 th percentile concentrations in the case of multi-city 22 studies) at or below 65  g/m 3

. 23 24

 Although single-city morbidity studies have reported positive, but not statistically 25 significant, associations with PM 10-2.5 in locations with 98 th percentile PM 10 26 concentrations below 65  g/m 3 , the results of U.S. morbidity studies were generally less 27 consistent than those of mort ality studies, with some PM 10-2.5 effect estimates being 28 positive while others were negative (i.e., negative effect estimates were reported in 29 several studies conducted in Atlanta, where the 98 th percentile PM 10 concentrations 30 ranged from 67  g/m 3 to 71  g/m 3 ). 31 32

 Although Bayes-adjusted single-city PM 10-2.5 effect estimates were positive, but not 33 statistically significant, in some locations with PM 10 concentrations below 65  g/m 3

, 34 these effect estimates were based on the difference between community-wide PM 10 and 35 PM 2.5 concentrations. As discussed above, it is not clear how these estimates of PM 10-2.5 36 concentrations compare to those more typica lly used in other studies to calculate PM 10-2.5 37 effect estimates. At present, corroborating studies are lacking that use other approaches 38 (i.e., co-located monitors, dichotomous samplers) to estimate/measure PM 10-2.5 in 39 locations with the lowest PM 10 concentrations. 403-44 D raft-Do Not Quote or Cite June 2010 In light of these limitations in the evidence for a relationship between PM 10-2.5 and 1
adverse health effects in locat ions with relatively low PM 10 concentrations, along with the 2 overall uncertainties in the body of PM 10-2.5 health evidence as described above and in the ISA, 3 we conclude that while it could be judged appropri ate to consider standard levels as low as 65 4

 g/m 3 , it is not appropriate, based on the curren tly available body of evidence, to consider 5

standard levels below 65  g/m 3

. 6 To provide some perspective on the potential imp lications of standard levels from different 7 parts of the range of 65 to 85  g/m 3 , staff assessed (based on 2006 to 2008 air quality data) the 8 percentage of counties, and the population in those counties, that would likely not attain different 9 standard levels within this range. The results of this analysis are presented in appendix 3A 10 (Table 3A-1), but these results were not considered as a basis for the above staff conclusions. 11

3.4 STAFF CONCLUSIONS ON A PR IMARY THORACIC COARSE PARTICLE 12 STANDARD 13 In reaching conclusions on the adequacy of the current PM 10 standard and potential 14 alternative standards to provide requisite protection against health effects associated with short15 term exposures to thoracic coarse particles, st aff has considered the basic elements of the 16 NAAQS: indicator, averaging time, form, a nd level (section 3.3.1 to 3.3.4 above). In 17 considering available scientific evidence a nd air quality information, we reflect upon the 18
evidence and information available in the last re view integrated with evidence and information 19
that has become available since that review as assessed and presented in the ISA (US EPA, 20 2009a) and summarized above in sections 3.2 and 3.3. 21 We recognize that selecting from among poten tial alternative sta ndards will necessarily 22
reflect consideration of the evidence as well as th e uncertainties inherent in that evidence. In 23 considering the current PM 10 standard and identifying potential alternative primary standards for 24 consideration, we are mindful that the Clean Ai r Act requires standards to be set that are 25 requisite to protect public health wi th an adequate margin of safet y, such that the standards are to 26 be neither more nor less stringent than necessa ry. Thus, the Act does not require that the 27 NAAQS be set at zero-risk levels, but rather at levels that avoid unacceptable risks to public 28
health. 29

(1) Consideration should be given to reta ining or revising the current 24-hour PM 10 primary 30 standard, depending on the relativ e weight placed on the evid ence supporting associations 31 with PM 10-2.5 and the uncertainties associated with this evidence. 32 (2) The indicator for thoracic coarse particles should continue to be PM 10 . This conclusion is 33 based on our assessment of the evidence for eff ects related to partic les of urban and non34 urban origins. We also concl ude that future research should be targeted so as to inform 35 consideration of different indi cators in future reviews. 363-45 D raft-Do Not Quote or Cite June 2010 (3) The averaging time should be 24-hours for a PM 10 standard meant to protect against short1 term exposures to thoracic coarse particle s. This conclusion reflects the body of 2 epidemiologic studies, which are most often based on 24-hour average PM 10-2.5 3 concentrations. 4 (4) To the extent consideration is give n to revising the current standard: 5 (a) Consideration should be given to a 98 th percentile form for a 24-hour PM 10 6 standard. This conclusion is based on c onsideration of providi ng a balance between 7 limiting peak concentrations and providing a stable regulatory target, compensating 8 for differences in monitoring frequency acr oss locations, and focusing the standard 9 on days when PM 10-2.5 is likely to make a relatively larger contribution to PM 10 10

mass. 11
(b) Consideration should be given to PM 10 standard levels from 85  g/m 3 down to 12 about 65  g/m 3 . This range of levels is based on consideration of 98 th percentile 13 PM 10 concentrations in U.S. study locations where PM 10-2.5 epidemiologic studies 14 have been conducted. We conclude that standard levels aro und the upper end of 15 this range are most strongly supported by th e evidence given the availability of 16 multiple single-city analyses in different lo cations and using different approaches to 17 estimate PM 10-2.5 , with some reporting positive and statistically significant PM 10-2.5 18 effect estimates. Standard levels as low as 65  g/m 3 could be considered to the 19 extent more weight is placed on posit ive, but not statistically significant, 20 associations and on multi-city PM 10-2.5 effect estimates. 21

3.5 KEY UNCERTAINTIES AND AREA S FOR FUTURE RESEARCH AND 22 DATA COLLECTION 23 In this section, we highlight ke y uncertainties and areas for fu ture health-related research, 24 model development, and data colle ction activities. These effort s, if undertaken, could provide 25 important evidence for informing future PM NAAQS reviews and, in particular, consideration of 26 possible alternative indicators, averaging times, forms, and/or levels. In some cases, research in 27 these areas can go beyond aiding stan dard setting to informing the development of more efficient 28 and effective control strategies. 29 As an initial matter, we note that many of the research needs identified for fine particles 30 (see above, section 2.5) are also re levant for thoracic coar se particles. This includes research in 31 the following areas: 32

 Sources and components of PM 10-2.5 , including source apportionment modeling; 33 monitoring of components; linking specific sources/compone nts to health outcomes; 34 linking sources/components to intr a- and inter-city differences in health effects; and 35 linking sources/components to population exposures 36

 Understanding the extent to which an associ ation between thoracic coarse particles and 37 specific health effects can be modified by co-pollutants 383-46 D raft-Do Not Quote or Cite June 2010  Understanding associations with a broad range of cardiovascul ar and respiratory 1 endpoints as well as adverse effects in th e nervous system, on reproduction, and/or on 2 development 3

 Understanding C-R relationships and the confidence bounds around these relationships, 4 especially at lower ambient thoracic coarse particle concentrations 5

 Understanding air quality distributions in locations of epidemiologic studies 6

 Identifying populations susceptible to PM 10-2.5 -related health effects 7

 Modeling to estimate PM 10-2.5 mass and composition in area s with less-than-daily 8 monitoring 9

These uncertainties and areas for future res earch are discussed a bove in section 2.5 and 10 that discussion will not be repeated here. In addition to the above, there are several areas for 11 future research that are particularly relevant for thoracic coarse partic les. These include the 12 following: 13

 The body of experimental inhalation studies (e.g., controlled human exposure and animal 14 toxicology studies) is currently relatively sp arse. Additional well-c onducted experimental 15 studies could play an important role in weight of eviden ce judgments in future ISAs. 16 Therefore, experimental evaluation of effects (e.g., vasomotor function, airways 17 responsiveness, pulmonary function/infl ammation) of concentrated ambient PM 10-2.5 from 18 specific sources (e.g., traffic, industrial, non-i ndustrial) would be usef ul, particularly if 19 exposure-response relations hips are evaluated. 20

 Exposure error is of particular concern for thoraci c coarse particles, give n the relative lack of 21 monitoring and its less homogeneous atmospheric distribution compared to fine particles (US 22 EPA, 2009a, section 2.1.1.2). Therefore, short-te rm studies with well-characterized personal 23 exposures (e.g., panel studies) w ould be useful. Such studies could examine indicators of 24 cardiovascular and respiratory morbidity (e .g., arrhythmia, ischemia, vasomotor function, 25 respiratory symptoms, pulmonary inflammati on, pulmonary function, pulmonary injury) and 26 would be particularly useful if they evalua ted concentration-respons e relationships and/or 27 effects of repeated peak exposures. 28

 Epidemiologic studies currently use a vari ety of approaches to measure/estimate PM 10-2.5 29 concentrations. It is important that we be tter understand the rela tionship between results 30 from studies that estimate PM 10-2.5 concentrations using either(1) difference method of co31 located monitors, (2) difference met hod of county-wide averages of PM 10 and PM 2.5 , or (3) 32 direct measurement of PM 10-2.5 using a dichotomous sampler. In addition, as described 33 above, PM 10-2.5 monitoring will be required at NCORE s ites by 2011. It would be useful for 34 future epidemiologic studies to make use of these new PM 10-2.5 monitoring sites. 35

 Very little information is available to inform weight of evidence conclusions for endpoints 36 associated with long-term PM 10-2.5 exposures. Epidemiologic and animal toxicological 37 studies of long-term exposures (i.e., months to years) to PM 10-2.5 would be helpful. Such 38 studies could evaluate links w ith cardiovascular and respirat ory morbidity, reproductive and 39 developmental outcomes, cancer, and mortality. 403-47 D raft-Do Not Quote or Cite June 2010 3.6 REFERENCES 1
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### 4 REVIEW OF THE SECONDARY STANDARDS FOR VISIBILITY1 

### RELATED EFFECTS 2

This chapter presents staff conclusions with re gard to the adequacy of the current suite of 3 secondary PM 2.5 standards to protect against PM-related visibility impairment as well as 4 alternative secondary PM standards that are appr opriate for consideration in this review. Our 5 assessment of these issues is framed by a series of key policy-relevant questions, which expand 6 upon those presented at the outset of this review in the IRP. The answers to these questions will 7 inform decisions on whether, and if so how, to revise the current suite of secondary PM 2.5 8 standards for the purpose of providing appropr iate protection from PM-related visibility 9 impairment. 10 In presenting staff conclusions on a range of alternative secondary standards that are 11 appropriate for consideration, we note that the final decision is largel y a public welfare policy 12 judgment. A final decision must draw upon scie ntific information and analyses about PM13 related visibility impairment a nd related impacts on public welfare, as well as judgments about 14 how to deal with the range of uncertainties th at are inherent in the scientific evidence and 15 analyses. Our approach to informing these j udgments is discussed more fully below. 16 Information on the approaches used to set the secondary PM 2.5 standards in past reviews 17 as well as our current approach for this review are presented in section 4.1. Our conclusions 18 regarding the adequacy of the current suite of secondary PM 2.5 standards to protect against PM19 related visibility impairment ar e presented in section 4.2. Sec tion 4.3 presents our conclusions 20 with respect to alternative PM standards by focusing on each of the basic elements of the 21 standards: pollutant indicator (section 4.3.1), averaging time (sect ion 4.3.2), and level and form 22 (section 4.3.3). The performance of alternative standards, with a focus on the uniformity of 23 protection from visibility impairment afforded by the alternative standards, is evaluated in 24
section 4.3.4. Section 4.4 summarizes all staff c onclusions on the secondary PM standards for 25 visibility protection. This chap ter concludes with an overview of areas of key uncertainties and 26 suggested future research areas and data collection efforts (section 4.5) 27

4.1 APPROACH 28 Staff’s approach for reviewing th e current suite of secondary PM 2.5 standards builds upon 29 and broadens the approaches used in previous PM NAAQS reviews. We first present a brief 30 summary of the approaches used to review and establish secondary PM sta ndards in the last two 31 reviews of the PM NAAQS (section 4.1.1). Recent litigation on the 2006 st andards has resulted 32
in the remand of the s econdary annual and 24-hour PM 2.5 NAAQS to EPA as discussed in section 33Draft-Do Not Quote or Cite June 2010 4-2 4.1.2. Our current approach fo r evaluating the secondary PM 2.5 standards using both evidence1 and impact assessment-based considerations is outlined in section 4.1.3. 2

4.1.1 Approaches Used in Previous Reviews 3 The original suite of secondary PM 2.5 standards was establishe d in 1997 and revisions to 4 those standards were made in 2006. The appr oaches used in making final decisions on 5 secondary standards in those reviews, as well as the current review, uti lize different ways to 6 consider the underlying body of sc ientific evidence. They also reflect an evolution in our 7 understanding of the nature of the effect on public welfare from visibility impairment, from that 8 focused only on Class I area visibility impacts to a more multifaceted approach that also 9 considers PM-related impacts on non- Class I area visibility, such as in urban areas. This 10 evolution has occurred in conjunction with the expansion of available PM data and information 11 from associated studies of public perception, va luation and personal comfort and well being. 12 4.1.1.1 Review Completed in 1997 13 In 1997, EPA revised the identical primary and secondary PM 10 NAAQS in part by 14 establishing new identical primary and secondary PM 2.5 standards. In revising the secondary 15 standards, EPA recognized that PM produces advers e effects on visibility a nd that impairment of 16 visibility was experienced thr oughout the U.S., in multi-state regi ons, urban areas, and remote 17 mandatory Class I Federal areas alike. Howeve r, in considering an appropriate level for a 18 secondary standard to addr ess adverse effects of PM 2.5 on visibility, EPA concluded that the 19 determination of a single national level was co mplicated by regional differences in several 20 factors that influence visibility such as background and current levels of PM 2.5, composition of 21

PM 2.5, and average relative humidity. Variations in these factors across regi ons could thus result 22 in situations where attaining an appropriately pr otective concentration of fine particles in one 23 region might or might not provide adequate pr otection in a different region. The EPA also 24
determined that there was insufficient information at that time to establish a level for a national 25 secondary standard that would represent a th reshold above which visibility conditions would 26 always be adverse and below which visibility conditions would always be acceptable. 27 Based on these considerations, EPA assessed po tential visibility improvements in urban 28 areas and on a regional scale that would result from attainment of the new primary standards for 29

PM 2.5 . The agency concluded that the spatially averaged form of the annual PM 2.5 standard was 30 well suited to the protection of visi bility, which involves effects of PM 2.5 throughout an extended 31 viewing distance across an urban area. Based on air quality data available at that time, many 32 urban areas in the Northeast, Midwest, and Southeas t, as well as Los Angeles, were expected to 33 see perceptible improvement in visibility if the annual PM 2.5 primary standard was attained. The 34
EPA also concluded that in some areas attainment of the 24-hour PM 2.5 standard would be 35Draft-Do Not Quote or Cite June 2010 4-3 expected to reduce, to some degree, the number a nd intensity of ‘‘bad visibility’’ days, i.e., the 1 20% of days having the greatest impair ment over the course of a year. 2 Having concluded that attainment of the annual and 24-hour PM 2.5 primary standards 3 would lead to visibility improvements in many eas tern and some western urban areas, EPA also 4
considered whether these sta ndards could provide potential improvements to visibility on a 5 regional scale. Based on information available at the time, EPA conclude d that attainment of 6

PM 2.5 secondary standards set identical to the primar y standards would be expected to result in 7 visibility improvements in the eastern U.S. at both urban and regional sc ales, but little or no 8 change in the western U.S., except in and near certain urban areas. 9 The EPA then considered the potential effec tiveness of a regional haze program, required 10 by sections 169A and 169B of the Act 1 to address those effects of PM on visibility that would 11 not be addressed through a ttainment of the primary PM 2.5 standards. The regional haze program 12 would be designed to address the widespread, regionally uniform type of haze caused by a 13 multitude of sources. The structure and require ments of sections 169A and 169B of the Act 14 provide for visibility protection programs that can be more res ponsive to the factors contributing 15 to regional differences in visibility than can programs addressing a nationally applicable 16 secondary NAAQS. The regional haze visibility goal is more protective than a secondary 17 NAAQS since the goal addresses any man-made impair ment rather than just impairment at levels 18 determined to be adverse. Thus, an important factor considered in the 1997 review was whether 19 a regional haze program, in conjunction with sec ondary standards set identical to the suite of 20

PM 2.5 primary standards, would provide appropriate protection for visi bility in non-Class I areas. 21 The EPA concluded that the two programs and associated control strategies should provide such 22 protection due to the regional approaches needed to manage emissions of pollutants that impair 23 visibility in many of these areas. 24 For these reasons, EPA concluded that a na tional regional haze program, combined with 25 a nationally applicable level of pr otection achieved through secondary PM 2.5 standards set 26 identical to the primary PM 2.5 standards, would be an appr opriate approach for addressing 27 regional variations in th e adverse effects of PM 2.5 on visibility than establishing national 28 secondary standards for PM at lo wer levels than the primary PM 2.5 standards. The EPA further 29 recognized that people living in certain urban areas may place a high value on unique scenic 30
resources in or near these areas , and as a result might experience visibility problems attributable 31
to sources that would not nece ssarily be addressed by the combined effects of a regional haze 32

1 In 1977, Congress established as a national goal ‘‘the prevention of any future, and the remedying of any existing, impairment of visibility in mandatory Class I Federal areas which impairment results from manmade air pollution’’, section 169A(a)(1) of the Act. The EPA is required by section 169A(a)(4) of the Act to promulgate regulations to ensure that ‘‘reasonable progress’’ is ac hieved toward meeting the national goal.Draft-Do Not Quote or Cite June 2010 4-4 program and PM 2.5 secondary standards. The EPA conclude d that in such cas es, state or local 1 regulatory approaches, such as past action in Colorado to establish a local visibility standard for 2 the City of Denver, would be more appropria te and effective in addressing these special 3
situations because of the lo calized and unique characteristics of the problems involved. 4 Visibility in an urban area loca ted near a mandatory Class I Fede ral area could also be improved 5 through state implementation of the current visib ility regulations, by which emission limitations 6 can be imposed on a source or group of sour ces found to be contributing to ‘‘reasonably 7 attributable’’ impairment in th e mandatory Class I Federal area. 8
Based on these considerati ons, EPA set secondary PM 2.5 standards identical to the 9 primary PM 2.5 standards, in conjunction with a regional haze program under sections 169A and 10 169B of the Act, as the most appropriate and e ffective means of addre ssing the welfare effects 11 associated with visibility impairment. Toge ther, the two programs and associated control 12 strategies were expected to provi de appropriate protection against the effects of PM on visibility 13 and enable all regions of the country to make reasonable progress toward the national visibility 14 goal. 15 4.1.1.2 Review Completed in 2006 16 In 2006, EPA revised the secondary PM 2.5 standards to address visibility impairment by 17 making them identical to the revised primary sta ndards. The EPA’s decision regarding the need 18 to revise the secondary PM 2.5 standards reflected a number of ne w developments and sources of 19 information that had occurred and/or become available following the 1997 review. First, EPA 20 promulgated a regional haze program in 1999 (65 FR 35713) which required states to establish 21 goals for improving visibility in Class I areas an d to adopt control strategies to achieve these 22 goals. Second, extensive new information from visibility and fine particle monitoring networks 23 had become available, allowing for updated characte rizations of visibility trends and PM levels 24 in urban areas, as well as Class I areas. Th ese new data allowed EPA to better characterize 25 visibility impairment in urban areas and the relationship between visibility and PM 2.5 26 concentrations. Finally, additi onal studies in the U.S. and abroad provided the basis for the 27 establishment of standards and programs to addre ss specific visibility concerns in a number of 28 local areas. These studies (e .g., in Denver, Phoenix, British Columbia) utilized photographic 29 representations of visibility impairment and produced reasonably consistent results in terms of 30 the visual ranges found to be generally acceptabl e by study participants. EPA considered the 31 information generated by these studies useful in characterizing the natu re of particle-induced 32 haze and for informing judgments about the acceptabi lity of various levels of visual air quality in 33
urban areas across the U.S. Base d largely on this information, th e Administrator concluded that 34 it was appropriate to revise the secondary PM standards to provide increased protection from 35Draft-Do Not Quote or Cite June 2010 4-5 visibility impairment principally in urban areas , in conjunction with th e regional haze program 1 for protection of visual air quality in Class I areas. 2 In so doing, the Administrator recognized th at PM-related visibility impairment is 3 principally related to fine particle levels, such that it was appropriate to focus the review on 4 whether the current secondary PM 2.5 standards should be revised. The Administrator also 5 recognized that perception of visibility impairment is most directly re lated to instantaneous 6 levels of visual air quality, such that in c onsidering whether the current suite of secondary 7 standards would provide the appropriate degr ee of protection, he concluded that it was 8 appropriate to focus on just the 24-hour secondary PM 2.5 standard to provide requisite protection. 9
The EPA then considered whether PM 2.5 remained the appropriate indicator for a 10 secondary standard to protect visibility, primarily in urban areas. EPA noted that PM-related 11 visibility impairment is principa lly related to fine particle le vels. Hygroscopic components of 12 fine particles, in particular sulfates and nitrates, contribute disproportionately to visibility 13 impairment under high humidity conditions. Particles in the coarse mode generally contribute 14 only marginally to visibility impairment in urban areas. With the substantial addition to the air 15 quality and visibility data made possible by the national urban PM 2.5 monitoring networks, an 16 analysis conducted for the 2006 re view found that, in urban areas, visibility levels showed far 17
less difference between eastern and western re gions on a 24-hour or shorter time basis than 18 implied by the largely non-urban data availabl e in the 1997 review. In analyzing how well PM 2.5 19
concentrations correlated with visibility in urban locations across the U.S., the 2005 Staff Paper 20 (US EPA, 2005) concluded that clear corr elations existed between 24-hour average PM 2.5 21
concentrations and reconstructed li ght extinction, which is directly related to visual range. These 22
correlations were similar in the eastern and wester n regions of the U.S. These correlations were 23 less influenced by relative humidity and mo re consistent across regions when PM 2.5 24 concentrations are averaged over shorter, daylig ht time periods (e.g., 4 to 8 hours) when relative 25 humidity was generally lower and less variable. The 2005 Staff Paper noted that a standard set at 26 any specific PM 2.5 concentration would necessarily result in visual ranges that vary somewhat in 27 urban areas across the country, reflecting the variability in the co rrelations between PM 2.5 28 concentrations and light extinction. The 2005 Sta ff Paper concluded that it was appropriate to 29
use PM 2.5 as an indicator for standards to address visibility impairment in urban areas, especially 30 when the indicator is defined for a relatively sh ort period (e.g., 4 to 8 hours) of daylight hours. 31 Based on their review of the Staff Paper, mo st CASAC Panel members also endorsed such a 32

PM 2.5 indicator for a secondary standard to addre ss visibility impairment (Henderson, 2005a). 33 Based on the above considerations, th e Administrator concluded that PM 2.5 should be retained as 34 the indicator for fine particles as part of a secondary standard to address visibility protection, in 35 conjunction with averaging times from 4 to 24 hours. 36Draft-Do Not Quote or Cite June 2010 4-6 In considering what level of protection agains t PM-related visibility impairment would be 1 appropriate, the Administrator took into account th e results of the public perception and attitude 2 surveys in the U.S. and Canada, state and local visibility standa rds within the U.S., and visual 3 inspection of photographic representations of se veral urban areas across the U.S. In the 4 Administrator’s judgment, these sources provided useful but still quite limited information on the 5 range of levels appropriate for consideration in setting a national visibility standard primarily for 6 urban areas, given the generally subjective nature of the public welfare effect involved. Based 7 on photographic representations of va rying levels of visual air qua lity, public perception studies, 8 and local and state visibility standards, the 2005 Staff Paper concluded that 30 to 20 μ g/m 3 PM 2.5 9 represented a reasonable range fo r a national visibility standard primarily for urban areas, based 10 on a sub-daily averaging time. The upper end of this range was below the levels at which 11 illustrative scenic views are significantly obscu red, and the lower end was around the level at 12 which visual air quality genera lly appeared to be good based on observation of the illustrative 13 views. This concentration range generally corr esponded to median visual ranges in urban areas 14 within regions across the U.S. of approximate ly 25 to 35 km, a range which was bounded above 15 by the visual range targets selected in specifi c areas where state or local agencies placed 16 particular emphasis on protecting visual air qualit y. In considering a reasonable range of forms 17
for a PM 2.5 standard within this range of levels , the 2005 Staff Paper concluded that a 18 concentration-based percentile form was appropriate, and that the upper end of the range of 19 concentration percentiles shoul d be consistent with the 98 th percentile used for the primary 20
standard and that the lower e nd of the range should be the 92 nd percentile, which represented the 21
mean of the distribution of the 20 percent most impaired days, as targeted in the regional haze 22 program. While recognizing that it was difficult to select any sp ecific level and form based on 23 then currently available information (Hende rson, 2005a), the CASAC Panel was generally in 24 agreement with the ranges of levels and forms presented in the 2005 Staff Paper. 25
The Administrator also considered the level of protection that would be afforded by the 26 proposed suite of primary PM 2.5 standards (71 FR 2681), on the basis that although significantly 27
more information was available than in the 1997 review concerning the relationship between fine 28 PM levels and visibility across the country, there was still little available information for use in 29 making the relatively subjective value judgment n eeded in selecting the appropriate degree of 30 protection to be afforded by such a standard. In so doing, the Administrator compared the extent 31 to which the proposed suite of primary standa rds would require areas across the country to 32 improve visual air quality with the extent of increased protection likely to be afforded by a 33 standard based on a sub-daily averaging time. Based on such an analysis, the Administrator 34 observed that the predicted percent of counties with monitors not likely to meet the proposed 35 suite of primary PM 2.5 standards was actually somewhat grea ter than the predicted percent of 36Draft-Do Not Quote or Cite June 2010 4-7 counties with monitors not likely to meet a sub-da ily secondary standard w ith an averaging time 1 of 4 daylight hours, a level toward the upper e nd of the range recommended in the 2005 Staff 2 Paper, and a form within the recommended range. Based on this comparison, the Administrator 3 concluded that revising the secondary 24-hour PM 2.5 standard to be identical to the proposed 4 revised primary PM 2.5 standard (and retaining the current annual secondary PM 2.5 standard) was a 5 reasonable policy approach to addressing visibi lity protection primarily in urban areas. In 6 proposing this approach, the Administrator also solicited comment on a sub-daily (4- to 8-hour 7 averaging time) secondary PM 2.5 standard (71 FR 2675-2781). 8 In commenting on EPA’s proposal, the CASAC re quested that a sub- daily standard to 9 protect visibility be favora bly reconsidered (Henderson, 200 6). The CASAC noted three 10 cautions regarding the Agency’s proposed reliance on a secondary PM 2.5 standard identical to the 11 proposed 24-hour primary PM 2.5 standard: (1) PM 2.5 mass measurement is a better indicator of 12 visibility impairment during daylight hours, when relative humidity is generally low; the sub13 daily standard more clearly matches the nature of visibility impairment, whose adverse effects 14 are most evident during the daylight hours; using a 24- hour standard as a proxy introduces error 15 and uncertainty in protecting visibility; and sub-daily standards are used for other NAAQS and 16 should be the focus for visibility; (2) CASAC an d its monitoring subcommittees have repeatedly 17 commended EPA’s initiatives promoting the intr oduction of continuous and near-continuous PM 18 monitoring, and expanded depl oyment of continuous PM 2.5 monitors is consistent with setting a 19 sub-daily standard to protect visibility; (3) The analysis showing a similarity between 20 percentages of counties not likely to meet what they considered to be a lenient 4- to 8-hour 21 secondary standard and a secondary standard id entical to the proposed 24-hour primary standard 22
was a numerical coincidence that was not indi cative of any fundamental relationship between 23 visibility and health. The CASA C Panel further stated that ”visual air quality is substantially 24 impaired at PM 2.5 concentrations of 35 μ g/m 3 ” and that ‘‘it is not reasonable to have the visibility 25 standard tied to the health standard, which may ch ange in ways that make it even less appropriate 26 for visibility concerns.” 27 In reaching a final decision, the Administrato r focused on the relative protection provided 28 by the proposed primary standards and the limita tions in the information available concerning 29 studies of public perception a nd attitudes regarding the acceptability of various degrees of 30 visibility impairment in urban areas, as well as on the subjective nature of the judgment required. 31 In so doing, the Administrator c oncluded that caution was warrante d in establishing a distinct 32 secondary standard for visibility impairment a nd that the available info rmation did not warrant 33 adopting a secondary standard that would provide either more or less protection against visibility 34 impairment in urban areas than would be pr ovided by secondary standards set equal to the 35 proposed primary PM 2.5 standards. 36Draft-Do Not Quote or Cite June 2010 4-8 4.1.2 Remand of Secondary PM 2.5 Standards 1 Several parties filed petitions for review following promulgation of the revised PM 2 NAAQS in 2006. These petitions challenged severa l aspects of the final rule including EPA’s 3 decision to set the secondary NAAQS for fine PM, which protect the public welfare from 4 adverse visibility effects, at the same level as the primary NAAQS, which protect public health. 5 On judicial review, the D.C. Circuit remande d to EPA for reconsideration the secondary 6 NAAQS for fine PM because the Agency’s de cision was unreasonable and contrary to the 7 requirements of section 109(b)(2). The petitioners argued that EPA’s decision lacked a reasoned 8 basis. First, they asserted that EPA never determ ined what level of visibility was “requisite to 9 protect the public welfare”. They argued that EPA unreasonably rejected the target level of 10 protection provided by its staff, while failing to provide a target level of its own. The court 11 stated “the EPA’s failure to identify such a le vel when deciding where to set the level of air 12 quality required by the revised secondary fine PM NAAQS is contrary to the statute and 13 therefore unlawful. Furthermore, the failure to set any target level of visibility protection 14 deprived the EPA’s decision-making of a reasoned basis.” American Farm Bureau Federation v. 15 EPA, 559 F. 3d 512 (D.C. Cir. 2009). 16 Second, the petitioners challe nged EPA’s method of compar ing the protection expected 17 from potential standards. They contended that the EPA relied on a meaningless numerical 18 comparison, ignored the effect of humidity on the usefulness of a standard using a daily 19 averaging time, and unreasonably c oncluded that the primary standa rds would achieve a level of 20 visibility roughly equivalent to the level the EPA staff and CASAC deemed “requisite to protect 21 the public welfare.” Again, the court found that EPA’s equivalenc y analysis failed on its own 22 terms. The same table showing the alternative secondary standa rd used for comparison to the 23 alternative primary to show equivalency al so included six other standards within the 24 recommended CASAC range that would be more “protective” under EPA’s definition than the 25 primary standards. Two-thirds of the potential standards within the CASAC’s recommended 26 range would be substantially more protective than the primary standards. The court found that 27 EPA failed to explain why it looked only at one of the few potentia l standards that would be less 28 protective and only sligh tly so than the primary standards. More fundamentally, however, the 29 court found that EPA’s equivalency analysis dem onstrated nothing about the relative protection 30 offered by the different standard s, and that the tables offered no valid infor mation about the 31 relative visibility protection pr ovided by the standards. 32 Finally, the Staff Paper made cl ear that a visibility standard using a daily averaging time 33 would be confounded by regional differences in humidity. The EPA acknowledged this 34 problem, yet did not address this issue in c oncluding that the primary standards would be 35 sufficiently protective of visibili ty. Therefore, the court gran ted the petition for review and 36Draft-Do Not Quote or Cite June 2010 4-9 remanded for reconsideration the secondary fine PM NAAQS. American Farm Bureau 1 Federation, 559 F. 3d at 520-24. 2

4.1.3 Current Approach 3 The staff’s approach in this review broadens the general approaches used in the last two 4 PM NAAQS reviews by utilizing, to the extent av ailable, enhanced tools, methods, and data to 5 more comprehensively characterize visibility impact s. As such, staff is taking into account both 6 evidence-based and impact-based considerations to inform staff conclusions related to the 7 adequacy of the current secondary PM 2.5 standards and alternative sta ndards that are appropriate 8 for consideration in this review. In so doing, we are seeking to provide as broad an array of 9 options as is supportable by the available informa tion, recognizing that the selection of a specific 10 approach to reaching final decisions on the secondary PM 2.5 standards will reflect the judgments 11 of the Administrator. Figure 4-1 below provides a diagram of our approach. 12 For the purposes of this second draft Policy Assessment (PA), staff has drawn from the 13 qualitative evaluation of a ll studies discussed in the Integrated Science Assessment for 14 Particulate Matter (Final Report) (ISA, USEPA, 2009a). The discussions presented in this 15 chapter consider the extensive new air quality and source apportionment information available 16 from the regional planning organizations, long-sta nding evidence of PM eff ects on visibility, and 17 public preference studies from four urban areas, as discussed in chapter 9 of the ISA, as well as 18 the integration of evidence across disciplines presented in chapte r 2 of the ISA. In addition, 19
limited information that has become availabl e regarding the charac terization of public 20 preferences in urban areas has provided some new perspectives on the usefulness of this 21 information in informing the select ion of target levels of urban visibility pr otection. On these 22 bases, we are again focusing our assessments in this review on visibili ty conditions in urban 23

areas. 24 Our conclusions reflect our understanding of both evidence-based and impact-based 25
considerations to inform two ove rarching questions rela ted to: (1) the adequacy of the current 26
suite of PM 2.5 standards and (2) what potential alternative standards, if any, should be considered 27 in this review to provide a ppropriate protection fro m PM-related visibility impairment. In 28 addressing these broad questions, we have orga nized the discussions below around a series of 29 more specific questions reflecting different aspects of each overarching question. When 30 evaluating the visibility protection afforded by the current or any alternative standards 31 considered, we have taken into account the f our basic elements of the NAAQS (e.g., indicator, 32 averaging time, level, and form). 33Draft

–

Do Not Quote or Cite 4 -10 June 2010 Figure 4 -1. Overview of Approach for Review of Secondary PM 2 .5 StandardsDraft-Do Not Quote or Cite June 2010 4-11 4.2 ADEQUACY OF CURRENT STANDARDS 1 In considering the adequacy of the current suite of PM 2.5 standards, staff addresses the 2 following overarching question: 3

Does the currently available scientific eviden ce and visibility impact information, as 4 reflected in the ISA and UFVA, support or call into question the adequacy of the visibility 5 protection afforded by the current su ite of fine particle standards? 6 To inform the answer to this overarching que stion, we have posed a series of more 7 specific questions to aid in cons idering the currently available scientific evidence and the results 8 of recent quantitative visibility im pact analyses in a policy-relevant context, as discussed below. 9 In considering the scientific and technical information, we re flect upon both the information 10
available in the last review and information that is newly available since the last review as 11 assessed and presented in the final ISA and fi nal UFVA (US EPA, 2009a; US EPA, 2010b). 12

4.2.1 Evidence-based Considerations 13 In reviewing the adequacy of the current suite of PM 2.5 standards, we have taken into 14
account evidence-based cons iderations, primarily as presented in the ISA, by considering causal 15 inference, impacts on susceptible populations, and th e kind of visibility e ffects that have been 16
observed in urban areas that would likely meet the current standards. 17

 To what extent does the newly available sc ientific evidence strengthen or call into 18 question evidence of associations between ambient fine particle exposures and visibility 19 effects? 20 New research conducted by regional planning organizations in support of the Regional 21 Haze Rule, as discussed in chapter 9 of th e ISA, continues to support and refine our 22 understanding of the nature of the PM visibility effect and the sour ce contributions to that effect 23 in rural and remote locations. Additional byprod ucts of this research include new insights 24 regarding the regional source cont ributions to urban visibility a nd better characterization of the 25 urban excess that occurs in many cities above regional background. Ongoing urban PM 2.5 26 speciated and mass monitoring has produced ne w information that has allowed for updated 27 characterization of visibility trends and current levels in urban areas. Information from both of 28 these sources of PM data, while useful, has not however changed the fundamental and long 29 understood science characterizing the contribution of PM, especially fi ne particles, to visibility 30 impairment from the last review. This science, briefly summarized below, provides the basis for 31 the ISA designation of the relationship between PM and visibility impairment as causal. 32 Visibility impairment is caused by the scat tering and absorption of light by suspended 33 particles and gases in the atmosphere. The combin ed effect of light scattering and absorption by 34Draft-Do Not Quote or Cite June 2010 4-12 both particles and gases is characterized as light extinction, (i.e. the frac tion of light that is 1 scattered or absorbed per unit of distance in the atmosphere). Light extinction is measured in 2 units of 1/distance, which is often expressed in the technical literature as 1/(million meters) or 3 inverse megameters (abbreviated Mm -1 ). When PM is present in th e air, its contribution to light 4 extinction typically greatly exceeds that of gases. 5 The amount of light extinction contribut ed by PM depends on the particle size 6 distribution and composition, as well as its concentration. If detail s of the ambient particle size 7 distribution and composition (including the mixi ng of components) are known, Mie theory can 8 be used to accurately calculate PM light ex tinction (ISA chapter 9). However, routine 9 monitoring rarely includes measurements of particle size and composition information with 10
sufficient detail for such calculations. A much si mpler algorithm can be used to estimate light 11 extinction using routinely m onitored fine particle (PM 2.5 ) speciation and coarse particle mass 12 (PM 10 – 2.5 ) data, plus relative humidity information n eeded to estimate the contribution by liquid 13 water in solution with hygroscopic PM componen ts (ISA section 9.2.2.2 and UFVA chapter 3). 14 The concentration of each of the major aerosol components is multiplied by a dry 15 extinction efficiency value and for the hygroscopic components (e.g., ammoniated sulfate and 16 ammonium nitrate) an additional multiplicative term to account for the water growth to estimate 17 these components’ contribution to light extinction. Both the dry extinction efficiency and water 18 growth terms are developed by some combina tion of empirical assessment and theoretical 19 calculation using typical particle size distributions associated with each of the major aerosol 20 components, and they are evaluated by compari ng the algorithm estimates of light extinction 21 with coincident optical measurements. Summin g the contribution of each component gives the 22 estimate of total light extinction. The most co mmonly used algorithm is referred to as the 23 IMPROVE algorithm because it was developed speci fically to use the aerosol monitoring data 24 generated at network sites and with equipment specifically designed to support the Interagency 25 Monitoring of Protected Visual Environments (IMPROVE) program and was evaluated using 26 IMPROVE optical measurements at the subset of sites that make those measurements (Malm et 27 al., 1994). The formula for the traditional IMPROVE algorithm is shown below. 28
29 b ext ≈ 3 x f(RH) x [Sulfate] 30 + 3 x f(RH) x [Nitrate] 31 + 4 x [Organic Mass] 32 + 10 x [Elemental Carbon] 33 + 1 x [Fine Soil] 34 + 0.6 x [Coarse Mass] 35 + 10 36 37Draft-Do Not Quote or Cite June 2010 4-13 Light extinction ( b ext ) is in units of Mm -1 , the mass concentrations of the components 1
indicated in brackets are in μ g/m 3 , and f(RH) is the unitless water growth term that depends on 2 relative humidity. The dry extinction efficiency for particulate organic mass is larger than those 3 for particulate sulfate and nitrate principally be cause the density of the dry inorganic compounds 4 is higher than that assumed for the PM organic mass components. Since IMPROVE does not 5 include ammonium ion monitoring, the assumption is made that all sulfat e is fully neutralized 6
ammonium sulfate and all nitrate is assumed to be ammonium nitrate. Though often reasonable, 7 neither assumption is always true (see Section 9.2.3.1). In the eastern U.S. during the summer 8 there is insufficient ammonia in the atmosphere to neutralize the sulfate fully. Fine particle 9 nitrates can include sodium or calcium nitrate, which are the fine partic le fraction of generally 10 much coarser particles due to nitric acid interac tions with sea salt at ne ar-coastal areas (sodium 11 nitrate) or nitric acid interacti ons with calcium carbonate in cr ustal aerosol (calcium nitrate). 12 Despite the simplicity of the algorithm, it perfor ms reasonably well and permits the contributions 13 to light extinction from each of the major com ponents (including the water associated with the 14 sulfate and nitrate compounds) to be separately approximated. 15
The f(RH) terms inflate the particulate sulfate and nitrate light scatteri ng for high relative 16 humidity conditions. For relative humidity below 40% the f(RH) value is 1, but it increases to 2 17 at ~66%, 3 at ~83%, 4 at ~90%, 5 at ~93% and 6 at ~95% relative humidity. The result is that 18 both particulate sulfate and nitrate are more efficient per unit mass than any other aerosol 19 component for relative humidity above ~85% wher e its total light extinction efficiency exceeds 20
the 10 m 2 /g associated with elemental carbon (EC). Based on this algorithm, particulate sulfate 21 and nitrate are estimated to have comparable lig ht extinction efficiencies (i.e., the same dry 22 extinction efficiency and f(RH) water growth terms), so on a per unit mass concentration basis at 23 any specific relative humidity they are treated as equally effective contributors to visibility 24
effects. 25 Inspection of the PM component-specific term s in the simple algorithm shows that most 26
of the PM 2.5 components contribute 5 times or more light extinction than a similar concentration 27
of PM 10 – 2.5 . We also know that particles with hygr oscopic components (e.g. particulate sulfate 28 and nitrate) contribute mo re light extinction at higher relative humidity than at lower relative 29 humidity because they change size in the atmos phere in response to ambient relative humidity 30 conditions. PM containing elemental or black carbon absorbs light as well as scattering it, 31 making it the component with the greatest light extinction contributi ons per unit of mass 32 concentration, except for the hygroscopic compon ents under high relative humidity conditions. 33
As a result of better character ization of PM in rural and re mote locations, refinements in 34 the original IMPROVE algorithm have been made to better account for th e aging of the organic 35 aerosols that occurs during transport from urban to more distant areas, and to add a component 36Draft-Do Not Quote or Cite June 2010 4-14 for sea salt. However, the focus on urban ar eas in this review made these refinements 1 unnecessary due to the fact that urban area s contain a higher proportion of newly emitted 2 aerosols, and because particulate sea salt, while exp ected to contribute to vi sibility impairment in 3 coastal areas, is natura l in origin and not controllable through regulation. Therefore, the 4 assessments done in support of this review have relied on the original IMPROVE algorithm, 5 As mentioned above, particles are not the only contributor to ambient visibility 6 conditions. Light scattering by ga ses also occurs in ambient ai r. Under pristine atmospheric 7 conditions, naturally occurring gases such as N 2 and O 2 cause what is known as Rayleigh 8 scattering. Rayleigh scattering, whic h depends on the density of air as a function primarily of the 9 elevation above sea level, can be treated as a si te-dependent constant. Rayleigh contribution to 10 light extinction is only significan t under pristine condi tions. The only other commonly occurring 11 atmospheric gas to appreciably absorb light in the visible spectrum is NO 2 . NO 2 forms in the 12 atmosphere from NO emissions associated w ith combustion processes. These combustion 13 processes also emit PM at levels that generally contribute much higher light extinction than the 14
NO 2 (i.e. NO 2 absorption is generally less than approxi mately 5% of the light extinction, except 15
where emission controls remove most of the PM prior to releasing the remaining gases to the 16 atmosphere). The remainder of this documen t focuses on the contribution of PM, which is 17 typically much greater th an that of gases, to ambient light extinction, unless ot herwise specified. 18

 To what extent does the available evidence inform our understanding of the temporal 19 nature of the PM visibility effect, includi ng relevant exposure periods, associated 20 atmospheric conditions, and diurnal patterns of exposure? 21

Diurnal Periods of Interest 22
Typically, we think of visibi lity associated with day time periods. We recognize, 23 however, that PM light extincti on behaves the same at night as during the day, enhancing the 24 scattering of anthropogenic light, contributing to the “s kyglow” within and ove r populated areas, 25 adding to the total sky brightness, and contributing to the reducti on in contrast of stars against 26 the background. These effects produce the visual result of a reduction of the number of visible 27 stars and the disappearance of diffuse or subtle phenomena such as the Milky Way. The 28 extinction of starlight is a secondary and minor effect also caused by increased PM scattering 29 and absorption. 30 However, there are significant and important differences between daytime and nighttime 31 visual environments that potentially make the ni ghttime period inappropriate to address at this 32 time. First, daytime visibility has dominate d the attention of those who have studied the 33 visibility effects of air pollution. As a result , little research has been conducted on nighttime 34 visibility and the state of the science is not ye t comparable to that a ssociated with daytime 35Draft-Do Not Quote or Cite June 2010 4-15 visibility impairment. Second, in addition to ai r pollution, nighttime visibili ty is affected by the 1 addition of light into th e sight path from numerous sources, including anthropogenic light sources 2 such as artificial outdoor lighti ng, which varies dramatically across space, and natural sources 3 including the moon, planets, and stars. Light sour ces and ambient conditions are typically five to 4 seven orders of magnitude dimmer at night than in sunlight. Moonlight, like sunlight, introduces 5 light throughout an observer’s sigh t path at a constant angle. On the other hand, dim starlight 6 emanates from all over the celestial hemisphere while artificial lights are concentrated in cities 7 and illuminate the atmosphere from below. Th ese different light sources will yield variable 8 changes in visibility as compared to what has be en established for the daytime scenario, in which 9 a single source, the sun, is by far the brightest source of light. Third, the human psychophysical 10 response (e.g., how the human eye sees and processe s visual stimuli) at night is expected to 11 differ (ISA, section 9.2.2). 12 Given the above, we do not believe that the sc ience is available at this time to support 13 adequate characterization of nighttime PM light ex tinction effects. In ad dition, we are not aware 14 of preference or valuation studies providing information on public preferences for nighttime 15 visual air quality (VAQ). Thus, we limit our consideration of PM visibility impacts to daylight 16 hours only. 17
Exposure Durations of Interest 18
Very little is known about the role exposure duration plays in determining the 19 acceptability or unacceptability of a given level of VAQ on the public welfare. We do know 20 from preference and/or valuation studies that at mospheric visibility conditions can be quickly 21 assessed and preferences determined. These studie s show that a momentary glance at an image 22 of a scene (i.e. less than a minute) is enough fo r study participants to consistently judge the 23 acceptability or unacceptability of the viewed visual air quality conditions. Outside these 24 controlled settings, we are unaware of any studies that characteri ze the extent to which different 25 frequencies and durations of exposure to visibilit y conditions contribute to the degree of public 26 welfare impact that occurs. 27 Recognizing the need for further research in this area, it is useful to consider a variety of 28 circumstances that are commonly expected to occur and to eval uate the potential impact of 29 visibility impairment on the public welfare base d on the information we do have. In some 30 circumstances, such as infrequent visits to scen ic vistas in natural or urban environments, people 31 are motivated specifically to take the opportunity to view a valued scene and are likely to do so 32 for many minutes to hours to apprec iate various aspects of the vista they choose to view. In such 33 circumstances, the viewer may consciously eval uate how the VAQ at that time either enhances 34 or diminishes the experience or view. However, the public also has many more opportunities to 35Draft-Do Not Quote or Cite June 2010 4-16 notice visibility conditions on a daily basis in setti ngs associated with performing daily routines 1 (e.g. during commutes, while walking the dog, or when taking out the recyclables). These 2 scenes, whether iconic or generic, may not be cons ciously viewed for their scenic value, but their 3 VAQ may still affect a person’s sens e of wellbeing. Research has demonstrated that people are 4 emotionally affected by low VAQ, that percepti on of pollution is correlated with stress, 5 annoyance and symptoms of depression, and that VAQ is deeply intertwined with a “sense of 6 place,” affecting peoples sense of the desirabi lity of a neighborhood (ISA section 9.2.4). Though 7
we do not know the extent to which these emoti onal effects are linked to different periods of 8 exposure to poor VAQ, providing add itional protection against short-te rm exposures to levels of 9 VAQ considered unacceptable in the context of th e preference studies would be expected to 10 provide some degree of protection against the risk of loss in the public’s “sense of wellbeing”. 11 Some people have mostly intermittent opportu nities on a daily basis (e.g. during morning 12 and/or afternoon commutes) to e xperience ambient visibility conditions as they spend much of 13
their time indoors without access to windows. For such people a view of poor VAQ during their 14 morning commute may provide thei r perception of the day’s visibi lity conditions until the next 15 time they venture outside during da ylight hours later or perhaps th e next day. Other people have 16 exposure to visibility conditions throughout th e day, so that a day with multiple hours of 17 visibility impairment would likely be judged as having a greater impact on their wellbeing than a 18 day with just one such hour. 19
We have no information or studies on the fract ion of the public that has only one or a few 20 opportunities to experience visibil ity during the day, or informati on or studies on the duration of 21 the effect on wellbeing from exposure to differe nt durations of poor VAQ conditions. However, 22 it is logical to conclude that people with limited opportunities to experience visibility conditions 23 on a daily basis would receive the entire imp act of the day’s VAQ based on the visibility 24 conditions that occur during the short time period when they can see it. Since this group could 25 be affected on the basis of observing VAQ conditions for periods as short as one hour or less, 26 and because in some areas the worst PM VAQ of the day occurs during the morning (see UFVA, 27 figure 3-12) when many people ar e commuting, we believe it is appropriate to consider 28 characterizing PM visibility conditions in terms of the worst or maximum hourly value during 29 daylight hours for each day for purposes of eval uating the adequacy of the current suite of 30 secondary standards. 31 For another group of observers, those who have access to v isibility conditions often or 32 continuously throughout the day, the entire impact of the day’s visibility conditions may be 33 based on the varying visibility conditions they observe throughout the day. For this group, it 34 might be more appropriate to eval uate the adequacy of the current suite of secondary standards in 35 terms of all daylight hours in the day. 36Draft-Do Not Quote or Cite June 2010 4-17 Temporal Variations of Visibility Impacts 1
While visibility conditions can change quick ly (i.e., less than a minute), atmospheric 2 sight path averaged light extinc tion which is pertinent to visibility impacts generally changes 3 more slowly (i.e. tens of minutes generally). Sub-hourly variations in light extinction 4 determined at any point in the atmosphere are li kely the result of small-scale spatial pollution 5 features (i.e. plumes) being tr ansported by the wind across that point. At typical wind speeds 6 found in U.S. cities, an hour corresponds to a few te ns of kilometers of air flowing past a point, 7 which is similar to visibility sight path lengths of interest in urban areas. 8 PM concentrations and light extinction in urban environments vary from hour to hour 9 throughout the day due to a combination of diur nal meteorological conditions and systematic 10 changes in emissions activity (e.g. rush hour traffic). Generally low mixing heights at night and 11 during the early morning hour tend to trap locally produced emissi ons, which are diluted as the 12 mixing height increases due to heating during the day. Low te mperatures and high relative 13 humidity at night are conducive to the presence of ammonium nitr ate particles and water growth 14 by hygroscopic particles compared with the generally higher temp eratures and lower relative 15 humidity later in the day. These combine to make early morning the most likely time for peak 16 urban visibility impacts. Superimposed on such sy stematic time of day variations are the effects 17 of synoptic meteorology (i.e., those associated with changing weather) and regional-scale air 18 quality that can generate peak visibility im pacts any time of day. The net effects of the 19 systematic urban and larger scale variations are that peak daytime PM light extinction can occur 20 any time of day though more often in early morning hours (UFVA section 3.4.2 and 3.4.3 and 21 shown in Figures 3-9, 3-10 and 3-12). Use of mu lti-hour averaging of PM light extinction would 22 suppress peak hourly conditions that are expect ed to represent peak visibility impacts. 23
Meteorological Causes of Visibility Impacts 24
Visibility is also reduced di rectly by the presence of preci pitation and fog regardless of 25 the presence or absence of PM. A secondary PM NAAQS is not meant to protect against such 26 sources of visibility impairme nt that occur irrespective of PM levels. Therefore, one 27 consideration in the development of alternative standard forms (discussed below in section 4.3) 28
was the inclusion of a relative humid ity screen in an effort to avoi d misinterpretation of the direct 29 effect of meteorological conditions on vi sibility and those caused by PM air quality. 30

 Based on currently available information, what range of levels of visibility impairment 31 is reasonable to consider in reaching judg ments about the adequa cy of the current 32 NAAQS? 33 In order to identify levels of visibility impairment appropriate for consideration in setting 34 secondary PM NAAQS to protect the public welfare, we comprehensively examined information 35Draft-Do Not Quote or Cite June 2010 4-18 that was available in this review regarding people’s stated prefer ences for acceptable and 1 unacceptable visual air quality. 2 Light extinction is an atmosphe ric property that by itself does not directly translate into a 3 public welfare effect. Instead, li ght extinction becomes meaningful in the context of the impact 4 of visibility on the human observer. This has been studied in terms of the acceptability or 5 unacceptability expressed for it by a human observer. The perception of the visibility impact of 6 a given level of light extinction occurs in conj unction with the associat ed characteristics and 7 lighting conditions of the viewed scene. Thus, a given level of light extin ction may be perceived 8 differently by an observer looking at a different scene or the same scene with different lighting 9 characteristics. Likewise, diffe rent observers looking at the same scene with the same lighting 10 may have different preferences regarding th e associated VAQ. When scene and lighting 11
characteristics are held constant , the perceived appearance of a scene (i.e., how well the scenic 12
features can be seen and the amount of visible haze) depends only on change s in light extinction. 13 This has been demonstrated using the WinHaze m odel that uses image processing technology to 14 apply user-specified changes in light extincti on values to the same base photograph with set 15 scene and lighting characteristics. 16
Much of what we know about th e acceptability of le vels of visibility comes from survey 17 studies in which participants we re asked questions about their pr eference or the va lue they place 18 on various visibility levels as displayed to them in scenic photographs and/or WinHaze images 19 with a range of known light extinction levels. Ur ban visibility preference studies for four urban 20
areas were reviewed in the UFVA (chapter 2) to assess the light extinction levels judged by the 21 participant to have acceptable visibility. While the results differed among the four urban areas, 22 results from a rating exercise showed that wi thin each preference st udy, survey participants 23 consistently distinguish between di fferent levels of light extinction and prefer and value visibility 24 associated with lower light extinction levels among the scenic images they are shown. 25 The reanalysis of urban preference studies included three completed urban visibility 26 preference survey studies plus a pair of smaller focus studies designed to explore and further 27 develop urban visibility survey instruments. The three western studies included one in Denver, 28 Colorado (E ly et al., 1991), one in the lower Fraser River valley near Vancouver, British 29 Columbia (BC), Canada (Pryor, 1996), and one in Phoenix, Arizona (BBC Research & 30 Consulting, 2003). A pilot focus group study wa s also conducted for Washington, DC (Abt 31 Associates Inc., 2001). In response to an EP A request for public comment on the Scope and 32 Methods Plan (74 FR 11580, March 18, 2009), we r eceived comments (Smith, 2009) about the 33 results of a new Washington, DC focus group study that had been conducted using methods and 34 approaches similar to the method and approach employed in the EPA pilot study (Smith and 35 Howell, 2009). When taken together, these studies from the four different urban areas included a 36Draft-Do Not Quote or Cite June 2010 4-19 total of 852 individuals, with each individual responding to a series of questions answered while 1 viewing a set of images of various urban VAQ conditions. 2 The approaches used in the four studies are similar and are all derived from the method 3 first developed for the Denver urban visibility study. In particular , the studies all used a similar 4 group interview type of survey to investigate the level of visibility impairment that participants 5 described as “acceptable.” While each study asked the basic question, “What level of visibility 6 degradation is acceptable?”, th e term “acceptable” was not defined, so that each person’s 7 response was based on his/her own values and preferences for VAQ. Given the similarities in 8 the approaches used, we concluded that it is reasonable to compare the results to identify overall 9 trends in the study findings and that this comparis on can usefully inform the selection of a range 10
of levels for use in further anal yses. However, variations in the specific materials and methods 11 used in each study introduce uncer tainties that should also be c onsidered when interpreting the 12 results of these comparisons. Key differences betw een the studies include: 1) image presentation 13 methods (e.g., projected slides of actual photos , projected images generated using WinHaze (a 14 significant technical advance in the method of presenting VAQ cond itions), or use of computer 15 monitor screen; 2) number of participants in each study; 3) participan t representativeness of the 16 general population of the relevant metropolitan area; and 4) specific wording used to frame the 17 questions used in the group interview process. 18 In the UFVA, each study was evaluated separately and figures developed to display the 19 percentage of participants that rated each photograph as “acceptable ”. The horizontal axis was in 20 terms of light extinction (deciview or dv) and the vertical axis in terms of percent of participants 21 rating “acceptable”. Ely et al. ( 1991) introduced a “50% acceptabi lity” criteria analysis of the 22 Denver preference study results. The 50% acceptability criteria is designed to identify the VAQ 23 level that best divides the photographs into two groups: those with a VAQ rated as acceptable by 24 the majority of the participants, and those rate d not acceptable by the majority of participants. 25 We adopted the criteria as a usef ul index for comparison between studies. The results of each 26 individual analysis were then combined graphi cally to allow for visual comparison. Figure 4-2 27 (Figure 2-16 in UFVA) presents the graphical summa ry of the results of the studies in the four 28 cities and draws on results previously presented in Figures 2-3, 2-5, 2-7 and 2-11 of chapter 2 in 29 the UFVA. Figure 4-2 also contai ns lines at 20 dv and 30 dv that ef fectively and pragmatically 30 identify a range where the 50% acceptance criteria occur across all four of the urban preference 31 studies. Out of the 114 data points shown in Figure 4-2, only one photograph (or image) with a 32 VAQ below 20 dv was rated as acceptable by less than 50% of the participants who rated that 33Draft-Do Not Quote or Cite June 2010 4-20 photograph. 2 Similarly, only one image with a VAQ above 30 dv was rated acceptable by more 1 than 50% of the partic ipants who viewed it. 3 2
3 Figure 4-2. Summary of results of urban visibility studies in four cities, showing the identified range of the 50 % acceptance criteria . 4

4 As can be seen in the figure, each urban area has a separate and unique response curve 5 that appears to indicate that it is distinct from the others. Th ese curves are the result of a 6 logistical regression analysis using a logit model of the greater than 19,000 ratings of haze 7 images as acceptable or unacceptable. The mo del results can be us ed to estimate the VAQ 8 deciview values where the estimated response f unctions cross the 50% ac ceptability level, as 9 well as any alternative criteria levels. Selected examples of these are shown in Table 4-1 (Table 10 2-4 in UFVA, Chapter 2). These results show that the logit model data also support the upper 11 and lower ends of the range of 50 th percentile acceptabi lity values (e.g. near 20 dv for Denver 12 and near 30 dv for Washington, DC) already identif ied in Figure 4-2 (see Table 2-4 UFVA). 13

2 Only 47% of the BC participants ra ted a 19.2 dv photograph as acceptable.
3 In the 2001 Washington, D.C. study, a 30.9 dv image was used as a repeated slide. The first time it was shown 56% of the participants rated it as acceptable, and 11% ra ted it as acceptable the second time it was shown. The same VAQ level was rated as acceptable by 42% of the participants in the 2009 study (Test 1).
4 Top scale shows light extinction in inverse megameter units ; bottom scale in deciviews. Logit analysis estimated response functions are shown as the color-coded curved lines for each of the four urban areasDraft-Do Not Quote or Cite June 2010 4-21 Table 4-1. Logit model estimated VAQ values corresponding to various percent 1 acceptability values for the four cities. 2 3
Denver British Columbia Phoenix Washington, DC 90% Acceptability criteria 14.21 16.80 24.15 23.03 75% Acceptability criteria 17.05 19.63 21.80 26.03
50% Acceptability Criteria 19.90 22.45 24.15 29.03

25% Acceptability criteria 22.74 25.28 26.51 32.03 10% Acceptability criteria 25.59 28.10 28.87 35.03

4 Based on the composite results and the effective range of 50 th percentile acceptability 5 across the four urban preference studies shown in Figure 4-2 a nd Table 4-1, benchmark levels 6 have been selected in a range from 20 dv to 30 dv (74 Mm -1 to 201 Mm -1 ) for the purpose of 7 provisionally assessing whether visibility cond itions would be consider ed acceptable (i.e., less 8 than the low end of the range, unacceptable (i.e., greater than the high end of the range, or 9 potentially acceptable (within the ra nge). A midpoint of 25 dv (122 Mm -1 ) was also selected for 10 use in the assessment. This level is also very near to the 50 th percentile criteri a value from the 11 Phoenix study (i.e. 24.3 dv), which is by far the best of the four st udies in terms of least noisy 12 preference results and the most representative sel ection of participants. Based on the currently 13 available information, we conclude that the use of 25 dv to represent the middle of the 14
distribution of results seems well supported. 15 These three benchmark values provide a low, middle, and high set of light extinction 16 conditions that are used to provi sionally define daylight hours w ith urban haze conditions that 17 have been judged unacceptable by the participants of these preference studies. As discussed 18 above, PM light extinction is taken to be light extinction minus the Rayl eigh scatter (i.e. light 19 scattering by atmospheric gases which is on average about 10 Mm -1 ), so the low, middle and 20 high levels correspond to PM light extinction levels of about 64 Mm -1 , 112 Mm -1 and 191 Mm -1

. 21 In the UFVA, these three levels were called Cand idate Protection Levels (CPLs). We continue 22 to use this term in this document. However, it is important to note that the degree of protection 23 provided by a secondary NAAQS is not determined solely by the level of the standard but by all 24 the components (e.g., indicator, form, level, averag ing time) being applied together. Therefore, 25 the reader should keep in mind that the term CPL is meant only to indicate levels within a range 26 that we feel are appropriate for consideration th at could, in conjunction wi th other aspects of the 27 standard, provide an appropriate degree of visibility protection. 28Draft-Do Not Quote or Cite June 2010 4-22 In characterizing our degree of confidence in each CPL and across th e range, a number of 1 issues were considered. Looking first at the two studies that define the upper and lower bounds 2 of the range, we considered whether they represen t a true regional distinction in preferences for 3 urban visibility conditions between western and east ern U.S. There is little information available 4 to help evaluate this, especially given that we have preference studies in only one eastern urban 5 area. Smith and Howell (2009) found little differe nce in preference response to Washington, DC 6 haze photographs between the study participants from Washington, DC and those from Houston, 7 TX. This provides some limited evidence that the value judgment of the public in different areas 8 of the country may not be an important factor in explaining the differences in these study results. 9 In further considering what f actors could explain the observe d differences in preferences 10 across the four urban areas, we noted that th e urban scenes used in each study had different 11 characteristics. For example, each of the western urban visibility preference study scenes 12 included mountains in the backgroun d while the single eastern urban st udy did not. It is also true 13 that each of the western scenes included objects at greater distances from the camera location 14 than in the Washington, DC study. There is no que stion that objects at a greater distance have a 15 greater sensitivity to perceived visibility changes as light extinction is changed compared to 16 otherwise similar scenes with obj ects at a shorter range. This alone might explain the difference 17 between the results of the Washington DC, st udy and those from the Western urban studies. 18 Also, it seems likely that people value the view s of mountains in the background more than 19 generic distant buildings in the foreground of the we stern scenes; just as it seems likely that the 20 Capital Mall and Washington Monument were the likely objects of greatest interest for the 21 Washington, DC study base photograph. Having s cenes with the object of greatest intrinsic 22 value nearer and hence less sensitive for Washington compared with more distant objects of 23 greatest intrinsic value in the western urban areas could furt her explain the difference in 24 preference results. 25 Another question that we cons idered was whether the high CP L value that is based on the 26 Washington DC preference results is likely to be generally represen tative of urban areas that do 27
not have associated mountains or other valued objects visible in the di stant background. Such 28
areas would include the middle of the country and many areas in th e eastern US. In order to 29

exam ine this issue, an effort would have to be ma de to see if scenes in such areas could be found 30 that would be generally comparable to the western scenes (e.g., contain valued scenic elements at 31
more sensitive distances than that used in th e Washington, DC study). This is only one of a 32 family of issues concerning how exposure to ur ban scenes of varying sensitivity affects public 33 perception, for which no information is currentl y available. Additional urban visibility 34 preference studies employing images selected of potentially more sensit ive scenes could help 35 evaluate whether a lower value for the high CP L is supportable. Othe r investigations to 36Draft-Do Not Quote or Cite June 2010 4-23 determine how common such scenes are in va rious regions of the country would also be 1 informative. Until such information becomes available, the high end of the CPL range (30 dv) 2 seems to be an appropriate level to consider. 3 With respect to the low end of the range, we considered factors that might further refine 4 our understanding of the robustness of this level. We concluded that additional urban preference 5 studies, especially with a greater variety in types of scenes, in cluding potentially more sensitive 6 western urban scenes, could help evaluate whether a lower CPL value than the currently selected 7 20 dv is supportable. Further, the reason for the noisiness in data points around the curves 8 apparent in both the Denver and British Columbia results compared to the smoother curve fit of 9 Phoenix study results could be explored. One po ssible explanation that we identified is that 10 these older studies used photogra phs taken at different times of day and on different days to 11 capture the range of light extincti on levels needed for the preference studies. In contrast, the use 12 of WinHaze in the Phoenix (and Washington, DC) st udy reduced variations in scene appearance 13 that affects preference rating and avoided th e uncertainty inherent in using ambient 14 measurements to represent sight path averaged light extinction values. Reducing these sources 15 of noisiness and uncertainty in th e results of future studies of sensitive urban scenes could 16 provide more certainty in the selection of a low CPL value. 17

 To what extent does the available informatio n demonstrate or suggest that PM-related 18 visibility impairment (within the range of CPLs) is occurring at current ambient 19 conditions or at levels that wo uld meet the current standards? 20 Current Visibility Levels 21
Chapter 3 of the UFVA characterized current visibility conditions in terms of both PM 2.5 22 and light extinction levels for the 14 urban areas 5 selected and compared them to the CPLs 23
identified above. 24 As an initial matter, we note that visibil ity impairment during periods with fog or 25 precipitation occurs irrespective of the presen ce or absence of PM. In order to avoid 26 precipitation and fog confounding estimates of PM visibility impairment, and as advised by 27 CASAC as part of its comments on the first public review draft of the UFVA, we restricted our 28 assessment of visibility conditions to daylight hours with relativ e humidity less than or equal to 29 90% (UFVA section 3.3.5 and Appendix G). Howeve r, not all periods with relative humidity 30 above 90% have fog or precipitation. Removing those hours from application of a secondary PM 31

5 Comments on the second review draft of the UFVA from those familiar with the monitoring sites in St. Louis indicate that the site select ed to provide continuous PM 10 monitoring, though less than a mile from the site of the PM 2.5 data is not representative of the urban area and resulted in unrealistically large PM 10-2.5 values. The EPA staff considers these comm ents credible and removed the St. Louis assessm ent results, leaving 14 of the 15 urban areas from the UFVA to be included in the Policy Assessment.Draft-Do Not Quote or Cite June 2010 4-24 standard involves a tradeoff between the be nefits of avoiding many of the hours with 1 meteorological causes of visibility impacts and the cost of not counting some hours with high 2 relative humidity without fog or precipitation, where the growth of hygroscopic PM into large 3 solution droplets results in enhanced PM visibil ity impacts. For the 14 urban areas included in 4 the assessment for which updated meteorological da ta were obtained, a 90% relative humidity 5 cutoff criterion is effective in that on averag e less than 6% of the hours are removed from 6 consideration, yet those hours have on average ten times th e likelihood of rain, six time the 7 likelihood of snow/sleet, and 34 times the likeli hood of fog compared with hours with 90% or 8 lower relative humidity. 9 Figure 4-3 (Figure 3-8 in UFVA) presents box-and-whisker plots to illustrate the 10
distributions of the estimates of daylight 1-hour reconstructed PM 10 light extinction levels in 11 each area during the 2005-2007 time period. The distribution of the daily maximum 1-hour 12
values is shown. The horizontal dashed lines in the plots represent th e low, middle, and high 13
CPLs for PM 10 light extinction of 64, 112, and 191 Mm -1 , corresponding to the benchmark VAQ 14 values of 20 dv, 25 dv and 30 dv as discussed above . Table 4-2 (Table 3-7 in UFVA) provides 15 the percentages of days ( across all of 2005-2007, unweighted) in which the daily maximum 16 daylight 1-hour PM 10 light extinction level was greater than each of the three CPLs (excluding 17 hours with relative humidity greater than 90 percent). 18 From these displays it can be seen that among the 14 urban areas, those in the East and in 19 California tend to have a higher frequency of vi sibility conditions above the high CPL compared 20 with those in the western US. Both Figure 4-3 and Table 4-2 indicate that all 14 urban areas 21 have daily maximum hourly PM 10 light extinctions that exceed ev en the highest CPL some of the 22 time. Again, the non-California we stern urban locations have the lowest frequency of maximum 23 hourly PM 10 light extinction with values in excess of the high CPL fo r 8 percent or fewer of the 24 days. Except for the two Texas and the non-California western urban area s, all of the other 25 urban areas exceed that high CPL from about 20 pe rcent to over 60 percent of the days. Based 26 on these estimated maximum hourly PM 10 light extinction estimates, all 14 of the urban areas 27 exceed the low CPL for about 40 percent to over 90 percent of the days. Based on all of the 28 above, we conclude that current levels of PM 10 light extinction associat ed with recent PM air 29 quality exceed levels that could reasonably be considered as protective of the public welfare. 30Draft-Do Not Quote or Cite June 2010 4-25 Figure 4-3. Distribution of estimate d maximum daily daylight 1-hour PM 10 light extinction 1 across the 2005-2007 period, by study area (exc luding hours with relative humidity greater 2 than 90 percent). (Adapted from Figure 3-8 in UFVA )* 3

4
* In the box-and-whisker plot, the box represents the 25 th to 75 th percentile range and the whiskers 5 represent the 10 th and 90 th percentile points of the data; individual data points below the 10 th percentile 6 and above the 90 th percentile are graphed as small circles. The three dashed horizontal lines represent 7 the three CPL levels of 64, 112, and 191 Mm -1

. 8Draft-Do Not Quote or Cite June 2010 4-26 1 Table 4-2. Percentage of daily maximum hourly values of daylight PM 10 light extinction 2 exceeding CPLs (excluding hours with relativ e humidity greater than 90 percent). (adapted 3 from Table 3-7 in UFVA) 4 5

Candidate Protection Level 64 Mm -1 112 Mm -1 191 Mm -1
Study Area Number of Days with Estimates (a) Percentage of Daily Maximum Hourly Values Exceeding CPL Tacoma 109 52 22 4

Fresno 324 75 52 30 Los Angeles 300 90 83 62
Phoenix 86 42 7 1 Salt Lake City 306 44 17 8

Dallas 273 80 41 10

Houston 148 79 45 11 Birmingham 349 89 65 34

Atlanta 279 91 75 31
Detroit 141 87 68 43 Pittsburgh 277 85 57 26
Baltimore 181 80 50 23 Philadelphia 143 86 64 31

New York 225 83 59 28 Average 224 75 50 25

Visibility Levels That Ju st Meet Current Standards 6

In the UFVA, we modeled the “what if” scen ario based on simulating just meeting the 7
current suite of PM 2.5 secondary standards: 15 μg/m 3 annual average PM 2.5 concentration and 35 8 μg/m 3 24-hour average PM 2.5 concentration with a 98 th percentile form, averaged over three 9 years. The steps needed to model the “what if” conditions involve e xplicit consideration of 10 changes in PM 2.5 components and are described here. Firs t, we applied proportional rollback to 11
all the PM 2.5 monitoring sites in each study area, taki ng into account polic y relevant background 12 (PRB) PM 2.5 mass, to “just meet” the NAAQS scenario fo r the area as a whole, not just at the 13 visibility assessment study site. The health risk assessment document (EPA 2010a) describes 14 this procedure in detail. Th e degree of rollback is controlle d by the highest annual or 24-hour 15 design value, which in most study areas is from a s ite other than the site us ed in this visibility 16
assessment. The relevant result from this an alysis is the percenta ge reduction in non-PRB PM 2.5 17 mass need to “just meet” the NAAQS scenario, for each study area. These percentage reductions 18
are shown in Table 4-4 of the UFVA. Note th at Phoenix and Salt Lake City meet the 15/35 19Draft-Do Not Quote or Cite June 2010 4-27 NAAQS scenario under current conditi ons and require no reduction. PM 2.5 levels in these two 1 cities were not “rolled up.” Second, for each day and hour for each PM 2.5 component, we 2
subtracted the PRB concentrati on from the current conditions concentration, to determine the 3 non-PRB portion of the current conditions concentration. Third, we applied the percentage 4 reduction from step 1 to the non-P RB portion of each of the five PM 2.5 components and added 5 back the PRB portion of the component. Finally , we applied the IMPROVE algorithm, using the 6
reduced PM 2.5 component concentrations, the current conditions PM 10-2.5 concentration for the 7 day and hour, and relative humidity for the day and hour to calculate the PM 10 light extinction. 8 We then included the term for Rayleigh scattering. 9 Figure 4-4 and Table 4-3 disp lay the results of the rollback procedure as a box and 10 whisker plot of daily maximum daylight 1-hour PM 10 light extinction and the percentage of daily 11 maximum hourly PM 10 light extinction values exceeding the CPLs when just meeting the current 12

PM 2.5 NAAQS scenario of 15/35 μ g/m 3 (excluding hours with relative humidity greater than 90 13 percent. These displays show that at the curren t PM NAAQS level (i.e., 15/35) all of the eastern 14 urban areas and Los Angeles exceed the least restrictive CPL more th an 10% of the time and that 15 only Tacoma would not exceed the least restri ctive CPL more than 2% of the time. 16Draft-Do Not Quote or Cite June 2010 4-28 1 Figure 4-4. Distribution of daylight 1-hour PM 10 light extinction when rolled back to just 2 meet current PM fine NAAQS across the 2005-2007 period, by study area (excluding hours 3 with relative humidity greater than 90 percent). * 4 NAAQS Scenario: 15 μ g/m 3 annual; 35 μ g/m 3 24-hour 5 Displayed: Daily Max Daylight Light Ex tinction (excluding hours >90% RH) 6

7
8 * In the box-and-whisker plot, the box represents the 25 th to 75 th percentile range and the 9 whiskers represent the 10 th and 90 th percentile points of the data; individual data points below the 10 th 10 percentile and above the 90 th percentile are graphed as small circles. The three dashed horizontal lines 11 represent the three CPL levels of 64, 112, and 191 Mm -1 12Draft-Do Not Quote or Cite June 2010 4-29 1 Table 4-3 Percentage of daily maximum hourly values of daylight PM 10 light extinction 2 exceeding CPLs when “jus t meeting” the current PM 2.5 NAAQS (15/35 μ g/m 3 ) (excluding 3 hours with relative humidity greater than 90 percent). (Adapted from Table 4-7 in UFVA). 4 5

Candidate Protection Level 64 Mm -1 112 Mm -1 191 Mm -1
Study Area Number of Days with Estimates (a) Percentage of Daily Maximum Hourly Values Exceeding CPL Tacoma 109 43 10 1

Fresno 324 54 30 10 Los Angeles 300 85 69 39
Phoenix 86 44 6 1 Salt Lake City 306 24 9 4

Dallas 273 81 41 10

Houston 148 75 41 11 Birmingham 349 84 55 24

Atlanta 279 90 71 25
Detroit 141 80 61 33 Pittsburgh 277 78 48 16
Baltimore 181 78 48 19 Philadelphia 143 85 61 28

New York 225 76 45 19

Average 224 70 43 17

4.2.2 Summary 6 In summary, we conclude that the availabl e information in this review, as described 7 above and in the UFVA and ISA, clearly calls into question the adequacy of the current suite of 8

PM 2.5 standards in the context of public welfare protection from vi sibility impairment, primarily 9 in urban areas, and supports consideration of alternative standards to provide appropriate 10 protection. 11 This conclusion is based first on the large per centage of days that exceed the range of 12
CPLs identified for consideration under both current and just meet PM air quality conditions. In 13 particular, under just meet conditions for th e suite of secondary PM NAAQS (i.e. 15/35 μ g/m 3 ) 14 greater than 10% of the days exceed th e highest, least prot ective CPL of 191 Mm -1 for 9 of the 15
14 urban areas. When the middle CPL of 112 Mm -1 is considered, 11 of the 14 cities have 16 greater than 10% of their days ex ceeding with a range of 30 to 74% of days exceeding this level. 17Draft-Do Not Quote or Cite June 2010 4-30 At the lowest CPL of 64 Mm -1 , the percentage of days exceeding this level range from 24 to 90% 1
across the 14 urban areas. 2 Second, we conclude that the averaging times associated with th e current suite of PM 2.5 3 NAAQS are not well suited to protect against PM-re lated visibility impairment on the basis that, 4 in the context of the studies, short-term expos ure (e.g., 1 hour or less) is sufficient for an 5 unacceptable level of visual air quality to be observed and the associated impacts of that 6 observation to be registered by the observer. Since some portion of the population may only 7 have the opportunity to observe one hour or less of ambient daylight visibility conditions, relying 8 on an averaging time as long as that of the current 24-hour and annual PM 2.5 standards would 9 make it difficult to identify a requisite level of protection that would tran slate into appropriate 10 protection against the maximum daily value. In addition, these longer averag ing times also result 11 in the inclusion of nighttime conditions, for whic h the science needed to support identification of 12 appropriate levels of visibility protec tion is not well developed or understood. 13 In reaching the conclusion th at the current suite of PM 2.5 standards is inadequate to 14 provide the appropriate protecti on of the public welfare from know n and/or anticipated adverse 15 effects by calling into ques tion the adequacy of the current levels and averaging times, we also 16
considered whether the current indicator of PM 2.5 remains useful in relating ambient PM to the 17 public welfare effect of visibility impairment . Section 4.3 below discusses these and other 18
considerations in its disc ussion of alternative stan dards for consideration. 19

4.3 CONSIDERATION OF ALTERNATIVE STANDARDS 20 Having reached the conclusion that ju st meeting the current suite of PM 2.5 standards 21 continues to allow levels of visual air quality impairment that, based on the scientific evidence 22 and information available in this review, can r easonably be considered adverse to the public 23 welfare, this section will discuss alternative standards that could potentially provide requisite 24 public welfare protection from known and/or anticipa ted adverse effects. This section discusses 25 indicator, averaging time and form, including ho w they relate to the characteristics of the 26 visibility effect of interest. 27

4.3.1 Nature of the Indicator 28

 To what extent does currently available in formation provide support for considering a 29 different indicator(s) for PM to replace or supplement the PM2.5 mass-based indicator? 30 As described below, EPA staff has cons idered three alternative indicators: PM 2.5 mass, 31 directly measured PM 2.5 light extinction, and speciated PM 2.5 mass-calculated light extinction. 32

PM 2.5 mass is the same indicator as is used by the current suite of PM 2.5 NAAQS. Directly 33
measured PM 2.5 light extinction is a measurement of the light extinction caused by PM 2.5 under 34 ambient conditions. Speciated PM 2.5 mass-calculated light extin ction uses the IMPROVE 35Draft-Do Not Quote or Cite June 2010 4-31 algorithm to calculate PM 2.5 light extinction us ing measured dry PM 2.5 speciation and relative 1 humidity data. We believe that considerati on of the use of either directly measured PM 2.5 light 2 extinction or speciated PM 2.5 mass-calculated light extinction as an indicator is justified because 3 light extinction is a physically mean ingful measure of the ambient PM 2.5 characteristic that is 4 most relevant and directly related to visibility effects. Further, PM 2.5 is the component of PM 5 responsible for most of the visi bility impairment in most urban areas. In these areas, the 6
contribution of PM 10 – 2.5 is a minor contributor to visibili ty impairment most of the time, 7 although at some locations (see UFVA Figure 3-13 for Phoenix) PM 10 – 2.5 can be a major 8 contributor to urban visibility effects. In the absence of PM air quality information from a much 9 larger number of urban areas acro ss the country, it is not possible at this time to know how many 10 urban areas fall into this categor y, though it is reasonable to presume that other urban areas in the 11 desert southwestern region of the country may have conditions similar to the conditions shown 12 for Phoenix. A possible solution to this issue would be to add a companion PM 10 – 2.5 standard to 13 provide control under those circumstances. Insufficient information is available at this time to 14
consider this latt er refinement. 15 The basis for considering each of these three indicators is discussed below. The 16 discussion also addresses monitoring data requirements for the directly measured PM 2.5 light 17 extinction and for speciated PM 2.5 mass-calculated light extinction. 18

PM 2.5 Mass Indicator 19

PM 2.5 mass monitoring methods are in wide spre ad use, including the Federal Reference 20 Method (FRM) involving the collection of periodic (1 day in 6 and 1 day in 3) 24-hour filter 21 samples. These samples are then subsequently analyzed to determine 24-hour PM fine mass. 22 The Chemical Speciation Network (CSN) and continuous PM 2.5 monitoring produce hourly 23 average mass concentrations and are conducte d at many locations. At a few locations, 24 continuous speciation sampling produces measures of some of the major PM 2.5 chemical 25 components. These routine monitoring activit ies do not include measurement of the water 26 content of the ambient PM that contributes, often si gnificantly, to visibility impacts. Further, the 27 PM mass concentration monitoring does not pr ovide information on the composition of the 28 ambient PM which also contributes to the variability in the amount of visibi lity impact associated 29 with any ambient PM mass concentration. 30 The overall performance of PM 2.5 mass as a predictor of visibility effects as indicated by 31

PM 10 light extinction can be seen in scatter plots shown in Figure 4-5 for Pittsburgh and 32 Philadelphia, PA (Similar plots for all 14 urba n areas are in Appendix D, Figure D-2 of the 33 UFVA). These demonstrate the variation in hourly PM 10 light extinction corresponding to any 34Draft-Do Not Quote or Cite June 2010 4-32 specific level of PM 2.5 mass concentration as well as sta tistical differences of the average 1 relationships (depicted as the best fit lines) between cities. 2

Figure 4-5 Scatter plots of PM 10 light extinction versus PM 2.5 mass concentration of two 3 cities (from UFVA Appendix D, Figure D2). 4

5

Directly Measured PM 2.5 Light Extinction Indicator 6
PM light extinction 6 is the major component of or cont ributor to light ex tinction, which is 7 the property of the atmosphere that is most directly related to visibi lity effects. It differs from 8 light extinction by the nearly c onstant contributions for Raylei gh (or clean air) light scattering 9 and the minor contributions by NO 2 light absorption. The net result is that PM light extinction 10 has a one-to-one relationship to light extinction, unlike PM 2.5 mass concentration which, as 11 shown above, does not have this characteristic. PM 2.5 light extinction 7 can be directly measured. 12
Direct measurement of PM 2.5 light extinction can be accomplishe d using several instrumental 13 methods, some of which have been used for deca des to routinely monito r the two components of 14

PM 2.5 light extinction (light scatteri ng and absorption) or to join tly measure both as total light 15 extinction (from which Rayleigh sca ttering is subtracted to get PM 2.5 light extinction). There are 16 a number of advantages to direct measurements for use in a secondary standard relative to 17
calculated PM 2.5 light extinction that was used to genera te hourly values for the UFVA. These 18 include the greater accuracy of direct measurem ents with shorter averaging times and the overall 19

6 PM light extinction is used here to refer to the light extinction caused by PM regardless of particle size, so it includes the contributions from particle larger that 10  m that are additive to the PM 10 light extinction.
7 PM 2.5 light extinction is the contribution to PM light extincti on by particles sampled through an inlet with a particle size 50% cutpoint of 2.5  m diameter.Draft-Do Not Quote or Cite June 2010 4-33 greater simplicity when compared to the need fo r measurements of multiple parameters needed 1 to generate the calculated PM light extinction level for a standard. 2 In evaluating whether direct measurement of PM 10 light extinction is appropriate to 3 consider in the context of this PM NAAQS revi ew, EPA produced a White Paper on Particulate 4 Matter (PM) Light Extinction Measurements (US EPA, 2010f), and solicited comment on the 5 white paper from the Ambient Air Monito ring and Methods Subc ommittee (AAMMS) of 6 CASAC. In its review (Russell and Samet, 2010) of the white paper, the AAMMS made the 7
recommendation to EPA that direct measurement be limited to PM 2.5 light extinction as this can 8 be accomplished by a number of commercia lly available instruments and because PM 2.5 is 9 generally responsible for most of the PM visibility impairment in urban areas. They indicated 10 that it is technically more challenging at this time to accurately measure the PM 10 – 2.5 component 11 of light extinction. 12
Speciated PM 2.5 Mass-Calculated Light Extinction Indicator 13

PM 2.5 light extinction can be estimated from PM 2.5 mass and speciation data plus relative 14 humidity data, as is presently routinely done on a 24-hour average basis under the Regional Haze 15 Program using data from the rural IMPROVE monitoring network. Applying a conceptually 16 similar approach on an hourly basis using data from the urban CSN monitoring network would 17 permit the use of routinely collected data from the current CSN network, and possibly similar 18 new monitoring sites, as input to a simple algorithm to calculate PM 2.5 light extinction for use in 19 a secondary PM NAAQS. 20 The approach used to generate hourly PM 10 light extinction for the UFVA was one 21 particular implementation of such a conceptual approach. It involved the use of the original 22 IMPROVE algorithm with estimates of hourly PM 2.5 components derived from day-specific 24- 23 hour and hourly measurements of PM 2.5 mass, 24-hour measurements of PM 2.5 composition, and 24 (for some but not all study sites) hourly PM 10-2.5 mass, along with daily temperature data and 25 hourly relative humidity information (UFVA, Section 3.3). 8 The UFVA approach entailed 26 numerous and complex data processing steps to generate hourly PM composition information 27 from these less time-resolved data, including app lication of the SANDWICH approach to adjust 28 for nitrate losses and to estimate organic carbona ceous material via mass balance. EPA staff 29 employed complex custom software to do these da ta processing steps. The complexity of the 30 approach used was reasonable for assessment purposes at 15 urban ar eas. While the UFVA 31 approach conceivably could also be the basis for defining a national visibility standard, a simpler 32 approach would have greater transparency, and s implicity, and thus should be considered for that 33

8 Daily temperature data enters the UFVA approach via the SANDWICH method. This fact was not highlighted in the UFVA.Draft-Do Not Quote or Cite June 2010 4-34 purpose. Therefore, we evaluate d the degree to which simpler appr oaches would wo rk as well as 1 the more complex method used in the UFVA. Th is evaluation (described briefly below and in 2 more detail in Appendix 4B, especially Table 4B-2) demonstrated that the PM 10 light extinction 3 values developed for the UFVA can be well ap proximated using the same IMPROVE algorithm 4 applied to hourly PM 2.5 composition values that were much more simply generated in locations 5
where PM 10-2.5 does not contribute signi ficantly to PM VAQ. 6 The simplified approach favored by EPA sta ff (i.e., approach F in Appendix 4B), is 7 aimed at calculating hourly PM 2.5 light extinction using the original IMPROVE equation (see 8 section 4.2.1 above) excluding the Rayleigh term fo r light scattering by atmospheric gases (i.e. 9
10 Mm -1 ) and the term for light scattering by PM 10-2.5 (i.e., 0.6 x [Coarse Mass]). This leaves 10
five PM 2.5 species concentration terms (i.e., sulfat e, nitrate, organic carbonaceous mass, 11 elemental carbon, and fine soil/cru stal), plus relative humidity that need to be determined on an 12 hourly basis from monitoring data. Table 4B-2 in Appendix 4B describe s ten steps in this 13 simplified approach (denoted approach F in A ppendix 4B) in detail, which are summarized here: 14

i. Estimate 24-hour organic carbonaceous mass from the CSN organic carbon 15 measurement, via a multiplier, ra ther than by the SANDWICH method. 16

ii. Calculate 24-hour fine soil/crustal from the CSN measurements of the related PM 2.5 17 crustal elements. 18

iii. Calculate 24-hour neutralized, dry sulfate and nitrate in the same manner as in the 19 IMPROVE network and Regional Haze prog ram, by multiplication by factors of 20 1.375 and 1.29 respectively. 21

iv. Sum the five components, for each day. 22

v. Calculate the five component fractions (i.e ., percentages) of the sum-of-five, for 23 each day. 24

vi. Looking across all CSN sampling days in a given calendar month, average the daily 25 component fractions for sulfat e, for nitrate, etc. These monthly-average component 26 fractions will be applied on every day in that month. 27

vii. For each day, determine a scaling factor to reconcile hourly PM 2.5 mass 28 measurements from a continuous instrument with the 24-hour PM 2.5 mass 29 determined by FRM sampling. 9 30

viii. For each day, apply this scaling factor to the 1-hour measurements of PM 2.5 mass 31 from the continuous instrument. 32

ix. For each day and daylight hour in the m onth, multiply the scaled value of hourly 33 PM 2.5 mass by the component fractions from step (v). 34

9 Steps (vii) and (viii) were performed in the analysis that is presented in Appendix 4B, but perhaps would not need to part of the approach for actual implementation. The Comments column of Table 4B-2 discusses this aspect in more detail.Draft-Do Not Quote or Cite June 2010 4-35 x. These hourly speciated PM 2.5 concentrations are then combined with collocated 1 hourly averaged relative humidity as input to the IMPROVE al gorithm to calculate 2 the speciated PM 2.5 mass-calculated light extinction. 3

A more detailed description of the sources of the data and steps required to determine 4 speciated PM 2.5 mass-calculated light extinction by this approach is contained in Appendix 4B 5 (see Table 4B-2). Also, Table 4B -1 of Appendix 4B compares/cont rasts this approach with the 6 UFVA approach and with another approach of in termediate complexity. Use of this approach 7 would require establishing Federal Reference Me thods for sampling and laboratory analysis for 8
each of the PM 2.5 components that is measured, whic h could be based on existing CSN 9 procedures, including the IMPR OVE-like procedures for elemen tal carbon and organic carbon 10 that have recently been fully implemented in the CSN network. 11
The PM 2.5 light extinction values generated by using this simplified approach are 12 comparable to those developed for use in the UFVA as indicated by the regression statistics for 13 scatter plots of the paired data (i.e ., slopes of the regression equation and R 2 values are near 1 as 14 show in Tables 4B-3 and 4B-4 in Appendix 4B). We believe that this simplified approach 15 provides reasonably good estimates of PM 2.5 light extinction. 16
Comparison of PM Components: PM 2.5 Mass and PM 10 Light Extinction Indicators 17
Given our understanding of th e causal relationship between ambient PM and PM visual 18 air quality and the contribution of various PM components to PM light extinction under ambient 19 conditions, an environmentally-re levant indicator for PM VAQ s hould be able to appropriately 20 order the hours/days by the magnitude of PM VA Q impairment. One benefit of selecting such 21 an indicator would be to identify the component s of PM that are most important for improving 22 PM VAQ in a given area. 23 Because the PM component contributions to PM 10 light extincti on are weighted 24 according to their light extinction effici ency while their contributions to PM 2.5 mass are equally 25 weighted (i.e., the sum of the component concentrations is the total PM 2.5 mass concentration), 26 our initial hypothesis was that the choice of indicator could si gnificantly influence the relative 27 contributions by PM components for the percent of hours selected above th e level of a standard. 28
In order to evaluate this hypothesis, EPA staff conducted an assessment which explored 29
the PM 10 components contributi ng to the top 10% of the maximu m daily 1-hour and top 2% of 30
all hours for PM 2.5 mass and PM 10 light extinction (see Appendix 4C, Indicator Comparisons and 31 Component Apportionment Comparisons). Wh ile this comparison used calculated PM 10 light 32
extinction instead of th e directly measured PM 2.5 light extinction or speciated PM 2.5 mass33 calculated light extinction indi cators described above, we beli eve that comparisons done with 34 these latter indicators would pr oduce sufficiently similar results for those areas in which PM 10-2.5 35Draft-Do Not Quote or Cite June 2010 4-36 is not a concern. These findings, described below and in Appendix 4C, are considered useful in 1 informing judgments regarding the impli cations of indicat or selection. 2
A careful examination of stacked bar charts for each hour included in the top 10% of the 3 maximum daily 1-hour and top 2% of all hours forms for both the PM 2.5 mass and PM 10 light 4
extinction indicators shows that the two indicators often select the same hour or another hour 5 during the same day as top contributors (compare plot a to plot d and plot e to plot h in Figures 6 4C-1 to 4C-14 and see a tally of the numbers of common and unique days in Table 4C-1). When 7 the two indicators select unique hour s among the top contributors, the PM 2.5 mass selected hours 8 necessarily have lower PM 10 light extinction values than those selected by PM 10 light extinction 9 as the indicator, generating a bias. However, th e average results for each of the 14 urban areas 10 show a remarkably similar identificati on of the relative amounts of the PM 10 components 11 responsible for the highest values regardless of which indicator is used to select the hours 12 (compare plot a to d and plot e to plot h in Figure 4C-15). 13 For any selected hour, the rela tive contributions of component s to PM mass is not the 14
same as the relative contributions of the components to PM light extinction because the differing 15 light extinction efficiencies of the components. These differences can be seen by comparing 16 paired plots in Figure 4C-1 to 4C-15 (i.e. compare a and b
, c and d
, e and f , etc.). The result is 17 that components that contribute little to PM lig ht extinction are more prominent contributors to 18 PM mass concentration (e.g., fine soil). Similarl y the relative importance of the hygroscopic PM 19 components (i.e., PM sulfates and nitrates) comp ared to that of the non-hygroscopic components 20 (i.e. primarily organic and elemen tal carbon) to PM mass is generally different than it is to PM 21 light extinction and that di fference changes as a function of relative humidity. 22 In summary, this comparison demonstrates that the selection of indicator has little effect 23 on which hours/days contribute to the top 10% of the maximum daily 1-hour and top 2% of all 24
hours for PM 2.5 mass and PM 10 light extinction. However, in terms of properl y identifying the 25

PM 2.5 species that are the largest contributors to the visibility impairment in those selected 26 hours/days for the purpose of ta rgeting controls, a calculated PM 2.5 light extinction indicator 27 would correctly weight the different components in terms of their differing contributions to 28 visibility impairment, while the PM 2.5 mass indicator would not. Li kewise, a direct measurement 29
of PM 2.5 light extinction could not, by itself, provid e speciated component information useful for 30 targeting controls. Therefore, we conclude that the speciated PM 2.5 mass-calculated light 31 extinction indicator has advantages over the PM 2.5 mass indicator in the context of this PM 32 NAAQS review. 33Draft-Do Not Quote or Cite June 2010 4-37 4.3.2 Averaging and Applicable Times 1 Consideration of appropriate averaging times, diurnal peri ods, and ambient conditions 2
over which the indicator would be measured were in formed by consideration of the nature of PM 3 visibility effects. 4 With respect to consideration of appropriate averaging times, as discussed above (section 5 4.2.1), we took into account what we know from the studies concerning how quickly people 6 experience and judge visibility conditions, the possibi lity that some fraction of the public 7 experience infrequent or short periods of expos ure to ambient visibility conditions, and the 8 typical rate of change of the path averaged PM light extinc tion over urban areas. While 9 perception of change in visibili ty can occur in less than a minut e, meaningful changes to path10 averaged light extinction occur more slowly a nd can be well represented by hourly averaging. 11 Multi-hour averaging times, on the other hand, woul d have the effect of reducing and masking 12 the magnitude of hourly peak visibility values which can change significantly from one hour to 13 the next (see UFVA Figure 3-12). Reduction of peak values through multi-hour averaging 14 reduces the ability of the indica tor to accurately characterize the visibility effects experienced by 15 the segment of the population that experiences infrequent shor t-term exposures during peak 16 periods. Therefore, we c onclude that a 1-hr averag ing time is appropriately suited to characterize 17 meaningful short-term variati ons in visibility conditions. 18 With respect to selection of an appropriate diurnal period, staff recognized that nighttime 19 visibility impacts, described in the ISA (secti on 9.2.2) are significantly different from daytime 20 impacts and not sufficiently well understood to be incl uded at this time. As a result, we conclude 21 that a secondary standard to prot ect visibility should onl y apply to daylight hours at this time. In 22 the UFVA, daylight hours were defined to be those morning hours having no minutes prior to 23 local sunrise and afternoon hours having no minutes after local sunset. This definition ensures 24 the exclusion of periods of time where the sun is not the primary outdoor source of light to 25
illuminate scenic features. 26 In considering the well-known interaction of PM with ambien t relative humidity 27 conditions, staff acknowledges that PM is not n ecessarily the primary source of visibility 28 impairment during periods with fog or precipitati on. In order to reduce the probability that hours 29 identified as having a high degree of visibili ty impairment for purposes of determining 30

com pliance with a standard were caused by fog or precipitation, staff determined that a relative 31 humidity screen that excludes daylight hours with average relative humidity above 90% is 32 appropriate (UFVA section 3.3.5 and Appendix G). For example, for the 15 urban areas 10 33

10 The 90% relative humidity cap assessment was conducted as part of the UFVA on all 15 of the urban areas, including St. Louis that is not displayed in the Policy Assessment.Draft-Do Not Quote or Cite June 2010 4-38 included in the final UFVA, a 90% relative humidity cutoff criterion proved effective in that on 1 average less than 6% of the daylight hours were removed from consideration, yet those same 2 hours had on average 10 times the likelihood of ra in, 6 times the likelihood of snow/sleet, and 34 3 times the likelihood of fog compared with hours w ith 90% or lower relative humidity. However, 4 not all periods with relative humidity above 90% have fog or precipitatio n. We recognize that 5 removing those hours from consider ation involves a tradeoff between the benefits of avoiding 6 many of the hours with meteorologi cal causes of visibility impacts and not counting some hours 7 without fog or precipitation in which high humid ity levels (> 90%) lead to the growth of 8 hygroscopic PM to large solution droplets resu lting in enhanced PM visibility impacts. 9

4.3.3 Alternative Levels/Forms 10

Candidate Protection Levels 11
The results from the visibility preferences st udies conducted in four urban areas define a 12 range of low, middle and high CPLs of 20 dv, 25 dv and 30 dv which are equivalent to PM 10 13 light extinction of values of 64 Mm -1 , 112 Mm -1 , and 191 Mm -1 (see section 4.2 above). With 14 only the four preference study resu lts, the individual low and high CPL are in fact reflective of 15 the results from the Denver and Washington, DC studies in particular, and the middle CPL is 16 very near to the 50 th percentile criteria re sult from Phoenix. 17 Determining PM 2.5 mass concentration values that correspond to the low, middle and 18 high CPL is complicated by the lack of a one-to-one relationship between PM 2.5 light extinction 19
and PM 2.5 mass. By considering the extinction ef ficiency values (i.e., the ratio of PM 2.5 light 20
extinction to PM 2.5 mass) used in the original IMPR OVE algorithm that range from 3 m 2 /g to 10 21

m 2 /g, a range of PM 2.5 concentration levels that roughly corresponds to a low estimate of the low 22 CPL and high estimate of the high CPL values can be determined. The full range is from ~6 23

μ g/m 3 to ~60 μ g/m 3 . Keeping in mind that there is no exact one-to-one correspondence between 24

PM 2.5 mass concentration and PM 2.5 light extinction, no individu al value in this range of 25 conditions corresponds to the CPL va lues expressed in terms of PM 2.5 light extinction, so a 26
number of alternate values within the range were selected for asse ssing their visibility protection 27 performance when combined with alternative fo rms (as described below). Five alternative PM 2.5 28 mass concentration values were selected for this purpose: 10 μ g/m 3 , 20 μ g/m 3 , 30 μ g/m 3 , 40 29

μ g/m 3 and 60 μ g/m 3

. 30

Alternative Forms 31

The form of the current 24-hour PM 2.5 NAAQS is set so that the level of the standard is 32 compared to the three -year average of the annual 98 th percentile of the meas ured indicator. The 33 purpose in averaging for three years is to provid e stability from the occasional effects of inter- 34Draft-Do Not Quote or Cite June 2010 4-39 annual meteorological variability that can result in unusual high pollution levels for a particular 1 year that is otherwise typical . The use of a percentile form, among other things, makes the 2 standard less subject to the possi bility of inappropriate violati ons caused by statistical outlier 3 indicator values. A percentile form can also be used to take into account the number of times an 4 exposure might occur as part of the judgment on protectiveness in setti ng a NAAQS. For all of 5 these reasons, we believe it is appropriate to consider incorporating the use of a three-year 6 average of a specified percentile for the PM secondary standard. 7 The urban visibility preference studies that pr ovided results leading to the range of CPLs 8 being considered in this documen t, offer no information that addr esses the frequency of time that 9 visibility levels should be below those values. Given this lack of in formation and recognizing 10 that the nature of the public welf are effect is one of aesthetics and/or feelings of wellbeing, we 11 believe that it is not necessary to consider e liminating all exposures above the level of the 12 standard and that allowing some number of hour s/days with reduced visi bility can reasonably be 13 considered. In the UFVA, 90 th , 95 th and 98 th percentile forms are as sessed in the PM light 14 extinction NAAQS scenarios (C hapter 4). The hourly PM 2.5 mass concentration scenarios that 15
are described and assessed below an d in Appendix 4A include only the 90 th and 95 th percentile 16
forms. 11 17 Another aspect of the form that needs to be considered is whether to include all daylight 18 hours or only the maximum daily daylight 1-hour. The maximum daily daylight 1-hour form is 19 more appropriate for protecting the welfare of people who have limited, infrequent or 20 intermittent exposure to visibili ty during the day (e.g. during commu tes), but spend most of their 21 time without an outdoor view. For such people a view of poor visibility during their morning 22 commute may represent their percep tion of the day’s visibility c onditions until the next time they 23 venture outside during daylight, hours later or pe rhaps the next day. Other people have exposure 24 to visibility conditions throughout the day. For those people it might be more appropriate to 25 include every daylight hour in assessing complia nce with a standard, since a day with multiple 26 hours with visibility impairment is likely to be judged to have a greater impact on their wellbeing 27 than a day with just one such hour. 28 We do not have information regarding the fract ion of the public that has only one or a 29 few opportunities to experience visibility during the day, nor do we have information on the role 30
the duration of the observed visibi lity conditions has on wellbeing effects associated with those 31 visibility conditions. However, it is logical to conc lude that people with limited opportunities to 32 experience visibility conditions on a daily basis would experience the entire impact associated 33 with visibility based on their shor t term exposure. The impact of visibility for those who have 34

11 Assessment of the 98 th percentile with PM 2.5 mass was thought to be unnecessarily restrictive so it was not conducted to simply and sp eed the assessment process.Draft-Do Not Quote or Cite June 2010 4-40 access to visibility conditions often or cont inuously during the day may be based on varying 1 conditions throughout the day. Based on these c onsiderations, the segment of the population 2 with infrequent access to visibili ty could be characterized as a susceptible population relative to 3 peak visibility impairment, while those with l onger exposures are a su sceptible population for 4 somewhat longer-term visibility impairment. 5 In light of these considerations, the UFVA assessment of the various PM 10 light 6
extinction scenarios included both the maximum daily and all daylig ht hours forms. We noticed 7 a close correspondence between the level of prot ection afforded for all 15 urban areas in the 8 assessment by the maximum daily daylight1-hour using the 90 th percentile form and the all 9 daylight 1-hour combined with the 98 th percentile form (UFVA sec tion 4.1.4). On this basis, 10
staff notes that the reductions in visibility impairment required to meet either form of the 11 standard would provide protecti on to both fractions of the pub lic (i.e., those with limited 12 opportunities and those with greate r opportunities to view PM-relate d visibility conditions). 13 Another way to assess the two forms (i.e., ma ximum daily and all daylight hours) is to 14 compare the PM components for hours that would be targeted for reduction by the use of each. 15 This was done for both indicators (i.e. PM 2.5 mass concentration and PM 10 light extinction) by 16 examining and comparing the component contribu tions for current condi tions (i.e., 2005 – 2007) 17 for the hours with the highest levels for each indicator. Stacked bar plots showing the PM 10 18 component composition of the top 10% of hours for the maximum daily 1-hour and of the top 19 2% of all daylight hours for bot h indicators and each of the 14 urban areas are described in 20 Appendix 4C. 21 For Figures 4C-1 to 4C-14 compos ition displayed in plots labeled a and e for the light 22
extinction indicator and c and g for the PM 2.5 mass indicator can be compared to assess the effect 23 of using the maximum daily compared with the all daylight hours forms. Some of the same 24 hours are selected by both forms. By defin ition the top 10% maximum daily hour form never 25 has more than 1 hour selected per day. There ar e very nearly twice as many hours in the top 2% 26 of all hours compared to the top 10% of maximu m daily hours. However, it is not unusual to 27 have multiple hours selected in the same day by the top 2% of all hours form. These hours 28 selected in the same day tend to have nearly identical composition. The top 2% of all hours may 29 select hours on a greater number of days compared with the top 10% of maximum daily hours, or 30 if there are enough instances of multiple hours pe r day, it could select hours on a smaller number 31 of days compared with the t op 10% of maximum daily hours. A list of the numbers of common 32 and unique days selected comparing the two form s for both indicators and the number of days 33 selected by each combination of indicator and form is shown in Table 4C-2. 34
For most of the urban areas the number of co mmon days is much larger than the number 35 of unique days. Generally, the PM component mix is less similar for sites with a lower number 36Draft-Do Not Quote or Cite June 2010 4-41 of common and a greater number of unique days. For most of the 14 urban areas, the differences 1 in components contributions for the two forms ar e minor. The greatest difference between the 2 two forms is for Salt Lake City. Average effects of the choice of form for each urban areas is 3 displayed in Figure 4C-15 (compare plot a to plot e and plot c to plot g ). This shows that the 4 differences in PM component contributions di ffer more depending on the choice of indicator 5 than the choice of form. Thus, these two speci fic percentile levels co rrespond to the nearly 6 equivalent levels of protection afforded by the maximum daily 90 th percentile and the all daylight 7
hours 98 th percentile forms. 8

4.3.4 Performance of Alternative Standards 9

We conducted assessments of alterna tive standards based both on hourly PM 10 light 10 extinction as the indicator (see Chapte r 4 of the UFVA) and on the hourly PM 2.5 mass 11 concentration indicator (see Appendi x 4A in this document). In the context of these assessments 12 of the 14 urban areas, PM 10 light extinction is dominated by PM 2.5 light extinction except for 13 Phoenix, and therefore we consider these asse ssments reasonably comparable to either the 14 directly measured or speciated PM 2.5 mass-calculated light extinction indicators. 12 There are 15
nine PM 10 light extinction alternative standards disc ussed here (i.e., daily maximum daylight 1- 16
hour PM 10 light extinction at the low, mi ddle and high CPL for each of the 90 th , 95 th and 98 th 17 percentile forms) and there are ten PM 2.5 mass concentration alternative standards (i.e., five 18
concentration levels for each of the 90 th and 95 th percentile forms). In both cases the assessment 19 involves rolling back non-polic y relevant background (PRB) PM 2.5 light extinction or PM 2.5 mass 20 concentration values until these specific alternative standards are just met. 21 In considering the performance of alternativ e standards, we focu sed on the consistency 22 across the 14 urban areas of the resulting visibi lity conditions, as measured in terms of light 23 extinction, when the alternative scenarios ar e just met. Because of the one-to-one 24 correspondence between li ght extinction and PM 10 light extinction, 13 the PM 10 light extinction 25 indicator based standards should pr oduce visibility conditions exactly as prescribed. The ability 26
to structure a PM 10 light extinction based alternative standard to the level of visibility protection 27 desired is an advantage because it could afford the most uniform degree of visibility protection 28
nationwide. 29 Figures similar to Figur e 4-5 for the other PM 10 light extinction scenarios are shown in 30 Appendix F of the UFVA. Table 4-4 shows th e design values for the 9 scenarios based on 31 maximum daily 1-hour PM 10 light extinction. When an area just meets a scenario, its design 32

12 These assessments were conducted prior to the decision to focus on PM 2.5 light extinction indicators.
13 In this assessment light extinction = PM 10 light extinction + 10Mm -1 , where the last term is Rayleigh or clean air light scattering that in fact can range from about 8Mm -1 to 12Mm -1 depending on average sight path elevation above sea level.Draft-Do Not Quote or Cite June 2010 4-42 value in principle should exactly equal the NAAQS level, so prepara tion of this table serves as a 1 check against calculation errors. Note that th e design values in Table 4-4, resulting from the 2 rollback steps described in section 4.1.4 of the UFVA, in some cases do not exactly equal the 3 assumed level of the NAAQS, although all are quite close. In some cases (e.g. Phoenix for 191 4

Mm -1 /90 th and 95 th percentile), current condi tions already meet the scen ario specifications so no 5 rollback was necessary and current design values are shown in Table 4-4 and reflected in box 6 and whisker plot figures. The minor differences between prescr ibed and assessed design values 7 seen for some applications of the rollback assessment are due to hours switching in the PM 10 8 light extinction frequency distri bution that is purely an artifac t of the rollback methodology as 9 described in the UFVA (section 4.3). These disc repancies were judged too small to justify 10
iterative rollback that could have been used to eliminate them. 11Draft-Do Not Quote or Cite June 2010 4-43 1 Figure 4-6 Daily maximum daylight 1-hour PM 10 light extinction after rollback to just meet 2 a scenario with daily maximum of 112 Mm -1 for the 90 th percentile excluding hours with 3 relative humidity greater than 90 percent. 4 5

6Draft-Do Not Quote or Cite June 2010 4-44 1
Table 4-4. PM 10 light extinction design values for “just meeting” secondary NAAQS 2 scenarios based on measured PM 10 light extinction (excluding hours with relative humidity 3 greater than 90 percent) 4

Secondary NAAQS Scenarios Based on Daily Maximum

(a) (b) (c) (d) (e) (f) (g) (h) (i)
Level (Mm -1 ) 191 191 191 112 112 112 64 64 64

Percentile

Form 90 th 95 th 98th 90 th 95 th 98th 90 th 95 th 98th
PM light extinction Design Value (based on same percentile form as the NAAQS scenario) Tacoma, WA 140 157 191 112 112 108 66 70 60

Fresno, CA 191 191 191 112 112 112 64 64 64

Los Angeles, CA 191 191 191 112 112 112 65 64 64

Phoenix, AZ 105 144 185 105 112 112 64 64 64

Salt Lake City, UT 164 191 191 112 112 112 64 64 64

Dallas, TX 183 191 191 113 113 112 64 66 66

Houston, TX 191 191 191 115 112 112 67 61 67

Birmingham, AL 191 192 191 113 114 112 64 66 64

Atlanta, GA 191 191 191 112 111 112 64 63 65

Detroit, MI 191 191 191 112 112 112 64 64 65

Pittsburgh, PA 191 191 191 112 112 112 64 64 64

Baltimore, MD 191 191 191 111 112 112 63 64 65

Philadelphia, PA 191 191 191 112 112 112 65 64 64

New York, NY 192 191 191 113 112 112 65 64 64

5 A complete description of the rollback assessment for th e ten maximum daily 1-hour 6

PM 2.5 mass concentration scenarios is available in Appendix 4A of this document. The process 7 used is very similar to that used in the UFVA for rollback of the PM 10 light extinction based 8
scenarios. 9Draft-Do Not Quote or Cite June 2010 4-45 Since PM 2.5 mass does not have a one-to-one correspondence to light extinction, the PM 10 1 light extinction conditions resulting from just meeting standards based on PM 2.5 mass are not as 2
uniform as those shown above for PM 10 light extinction scenarios. This is demonstrated in the 3 box and whisker plot of the maximum daily 1-hour PM 10 light extinction based on 1-hr PM 2.5 4
mass for the 30 μ g/m 3 , 90 th percentile scenario shown below (Figure 4-7), which shows greater 5
variation across the urban areas than is seen in the PM 10 light extinction based scenarios. Similar 6 plots for all ten PM 2.5 mass based scenarios are shown in Appendix 4A (Figure 4A-2). 7

Figure 4-7. Maximum daily daylight 1-hour PM 10 light extinction under "just meet" 8 conditions for a NAAQS scenario based on 1-hour PM 2.5 mass of 30 μ g/m 3 , 90th percentile, 9 excluding relative humidity >90%. 10

11 The 90 th percentile PM 10 light extinction design va lues corresponding to the 90 th 12 percentile PM 2.5 mass concentration based scenarios for the five mass concentration levels are 13
shown in Table 4-5. Values in the table that ex ceed each of the CPL values are highlighted using 14
different colors. The values in the table are the same for some urban areas for the less restrictive 15

PM 2.5 mass concentration standard (e.g. Tacoma at 60 μ g/m 3 and 40 μ g/m 3 , or Phoenix at 60 16

μ g/m 3 , 40 μ g/m 3 , 30 μ g/m 3 and 20 μ g/m 3 ), because those areas required no rollback to meet the 17
less restrictive PM 2.5 mass concentration standards. In or der for most or all urban areas to 18Draft-Do Not Quote or Cite June 2010 4-46 achieve even the highest CPL at the 90 th percentile, a PM 2.5 mass based standard set below 40 1

μ g/m 3 would be necessary. Based on the CPL’s considered, the higher PM 2.5 mass levels of 60 2

μ g/m 3 and 40 μ g/m 3 clearly are not sufficiently protective, since they permit 10 and 9 of the 14 3 areas, respectively, to have design values larger than the high CPL value (i.e.,191 Mm -1 ). The 30 4

μ g/m 3 standard level has PM 10 light extinction values that are marginally above the high CPL at 5
3 of the 14 urban areas and has a mean value below the high CPL. At the 20 μ g/m 3 PM 2.5 6 standard level, all areas meet the highest CPL benchmark, and the mean PM 10 light extinction 7
value across the 14 urban areas is nearer to the middle CPL (i.e., 112 Mm -1 ) than to the high 8
CPL. The 10 μ g/m 3 standard level produces a mean PM 10 light extinction value of 79.1 Mm -1

, 9 which is greater than the low CPL (i.e., 64 Mm -1 ) but nearer to it than the middle CPL. 10Draft-Do Not Quote or Cite June 2010 4-47 Table 4-5. 90 th percentile maximum daily 1-hour PM light extinction design values (Mm 1 ) 1 after rollback to meet al ternative standards of 60 μ g/m 3 , 40 μ g/m 3 , 30 μ g/m 3 ,20 μ g/m 3 and 2 10 μ g/m 3 maximum daylight 1-hour PM mass concentration for the 90th percentile.* 3 4 60 μ g/m 3 40 μ g/m 3 30 μ g/m 3 20 μ g/m 3 10 μ g/m 3
Tacoma, WA 140 Mm -1 140 Mm -1 140 Mm -1 128 Mm -1 82 Mm -1

Fresno, CA 338 Mm -1 248 Mm -1 190 Mm -1 132 Mm -1 74 Mm -1 Los Angeles, CA 403 Mm -1 284 Mm -1 220 Mm -1 156 Mm -1 105 Mm -1
Phoenix, AZ 105 Mm -1 105 Mm -1 105 Mm -1 105 Mm -1 86 Mm -1 Salt Lake City, UT 164 Mm -1 164 Mm -1 153 Mm -1 107 Mm -1 59 Mm -1
Dallas, TX 183 Mm -1 183 Mm -1 183 Mm -1 146 Mm -1 80 Mm -1
Houston, TX 194 Mm -1 194 Mm -1 179 Mm -1 125 Mm -1 73 Mm -1 Birmingham, AL 357 Mm -1 266 Mm -1 208 Mm -1 152 Mm -1 102 Mm -1
Atlanta, GA 249 Mm -1 249 Mm -1 191 Mm -1 134 Mm -1 76 Mm -1
Detroit, MI 291 Mm -1 202 Mm -1 157 Mm -1 120 Mm -1 88 Mm -1 Pittsburgh, PA 278 Mm -1 243 Mm -1 185 Mm -1 127 Mm -1 69 Mm -1
Baltimore, MD 246 Mm -1 246 Mm -1 201 Mm -1 138 Mm -1 76 Mm -1 Philadelphia, PA 258 Mm -1 175 Mm -1 134 Mm -1 98 Mm -1 63 Mm -1
New York, NY 306 Mm -1 281 Mm -1 212 Mm -1 141 Mm -1 74 Mm -1

Mean Values 250.9 Mm -1 212.9 Mm -1 175.6 Mm -1 129.2 Mm -1 79.1 Mm -1

5

* Colored highlighting shows which of the C PL levels the values are near, using the 6 following definitions: PM light exti nction equal or above the high CPL > 191 Mm -1 ; above the 7 middle CPL, 112 Mm -1 – 190 Mm -1 ; above the low CPL, 64 Mm -1 – 111 Mm -1 ; below the low 8 CPL, < 64 Mm -1 . Values without color highlighting indi cate no rollback, so no information 9 about the effectiveness of the hourly PM mass based alternative standards 10 11 The range of 90 th percentile PM 2.5 light extinction design leve ls resulting from rollback to 12 just meet a 90 th percentile 20 μ g/m 3 PM 2.5 mass concentration is from 98 Mm -1 for Philadelphia 13
to 156 Mm -1 for Los Angeles with most values near the middle CPL value of 112 Mm -1 . A 14 similar range for the 30 μ g/m 3 PM mass concentration is from 134 Mm -1 to 220 Mm -1 for the 15
same two cities. This demonstrates the amount of variability in visibility conditions that would 16 likely result from using a standard with PM 2.5 mass concentration instead of PM 2.5 light 17 extinction as the indicator. While this degree of variation is not particul arly large, it does mean 18 that some areas would be required to further redu ce ambient levels to meet a secondary standard 19 though they have visibility conditio ns that are as good or better th an other areas which meet the 20

PM 2.5 mass based standard. Some measure of the ex tent to which this occurs may be gained by 21Draft-Do Not Quote or Cite June 2010 4-48 comparing the percent rollback values required to meet the various PM mass and PM light 1
extinction values. 2 Based on inspection of the design values for individual urban areas and means shown in 3 Table 4-5, among the PM 2.5 mass concentration levels that were assessed, 30 μ g/m 3 provides 4 protection somewhat comparab le to the high CPL (191 Mm -1 ), 20 μ g/m 3 provides protection 5 somewhat comparable to the middle CPL (112 Mm -1 ) and 10 μ g/m 3 provides protection 6 somewhat comparable to the low CPL (64 Mm -1 ). Additional assessmen ts could be conducted to 7
refine the PM 2.5 mass concentration values to better correspond to the three CPL PM light 8
extinction values for these 14 urba n areas, though this would not mu ch change the variations in 9 performance across urban areas. 10 Care must be taken to avoid misinterpret ation of this suggestion of approximate 11 comparability of protection afforded the va rious urban areas by PM mass at the three 12
concentration levels in terms of the three CPLs. The values in Table 4-5 are the 90 th percentile 13
values of the PM 2.5 light extinction distribution that re sults from transf orming the hourly PM 2.5 14 mass and composition values of the rolled back PM distributions for each urban area. Hours 15
with values above the 90 th percentile of PM mass do not neces sarily have PM light extinction 16
above the 90 th percentile and visa versa. As discu ssed earlier (section 4.3.1) for any individual 17 hourly PM mass concentration ther e is a substantial range of co rresponding PM light extinction 18 values possible. 19

4.4 STAFF CONCLUSIONS ON ALTERNAT IVE SECONDARY STANDARDS FOR 20 VISIBILITY-RELATED EFFECTS 21 In reaching conclusions on poten tial alternative standards to provide requisite protection 22 of PM-related visibility impairment, staff has considered the basic elements of the NAAQS: 23 indicator, averaging time, form and level. In considering the scientific and technical 24 information, we considered the information avai lable in the last revi ew integrated with 25 information that is newly available as assesse d and presented in the ISA and UFVA and as 26 summarized in sections 4.2, 4.3, a nd Appendices 4A, 4B and 4C. 27 As outlined in section 4.1.3, we emphasize a policy approach that broadens the general 28 approaches used in the last two PM NAAQS reviews by utilizi ng, to the extent available, 29 enhanced tools, methods, and data to more compre hensively characterize visibility impacts. As 30 such, we have taken into account both ev idence-based and impact assessment-based 31
considerations to inform our conclusions related to the adequacy of the current PM 2.5 secondary 32 standards and alternative standards that are approp riate for consideration in this review. In so 33 doing, we are seeking to provide as broad an array of options as is supportable by the available 34 information, recognizing that the selection of a specific approach to reaching final decisions on 35Draft-Do Not Quote or Cite June 2010 4-49 the secondary PM standards for protection from PM -related visibility impairment will reflect the 1 judgments of the Administrator. We recognize that selecting from am ong alternative standards 2 will necessarily reflect consideration of the qualita tive and quantitative uncertainties inherent in 3
the relevant evidence and in th e assumptions that underlie the quantitative visibility impact 4

assessment. 5

(1) Consideration should be given to revising the current suite of PM 2.5 secondary standards to 6 provide increased public we lfare protection from PM 2.5 -related visibility impairment, 7 primarily in urban areas. This conclusion is ba sed in general on the evaluation in the ISA of 8 the currently available inform ation, including a more extens ive characterization of the 9 sources contributing to visibility impairment in both rural and urban locations; a refined 10 understanding of the contributions of various PM components in such ar eas; exposure-related 11 evidence supporting a causal rela tionship between ambient PM and impaired VAQ, evidence 12 that a significant number of days with levels of VAQ that could reason ably be considered 13 unacceptable would continue to occur in areas where the current standards were met; and 14 judgments as to the public welfare significan ce of these occurrences upon just meeting the 15 current suite of PM 2.5 standards. 16 (2) Consideration should be given to establishing a new speciated PM 2.5 mass-calculated light 17 extinction indicator. This conclusion takes into consideration the available evidence that 18 demonstrates a one-to-one correspondence between directly measured or calculated PM light 19 extinction and PM-related visibility impairme nt as well as the significant degree of 20 variability in visibility protection across the U.S. allowed by a PM 2.5 mass indicator. While a 21 secondary standard that uses a PM 2.5 mass indicator could be set to provide additional 22 protection from PM 2.5 -related visibility impairment, we conc lude that the advantages of using 23 a speciated PM 2.5 mass-calculated light extinction indi cator (as described above in section 24 4.3.1) make it the preferred choice. 25 (3) Consideration should be given to a one hour av eraging time to protect against daytime PM 2.5 26 -related visibility impairment that takes into account the short-term (instantaneous) nature of 27 the perception of visibility impairment, short- term variability in PM-related VAQ (partial 28 hour to hourly), and the short-te rm nature of relevant exposure periods for the viewing public 29 (partial hour to multiple hours). Due to limitati ons in the science related to assessing public 30 welfare impacts associated with nighttime visi bility impairment, consideration should be 31 given to including daylight hours only. Further, consideration should be given to applying a 32 90% relative humidity screen to remove hours in which fog or precip itation is much more 33 likely to contribute to the obser ved visibility impairment. 34 (4) In conjunction with a 1-hour averaging time, consideration should be given to either a 35 maximum daily daylight 1-hour form or a fo rm that includes all daylight hours. 36 Consideration should be given to a form defined in terms of the 90 th , 95 th or 98 th percentile of 37 the distribution of calculated PM 2.5 light extinction, averag ed over three years. 38 (5) Consideration should be given to selecting a target level of acceptable PM-related VAQ in 39 terms of PM 2.5 light extinction. Further, consider ation should be given to a range of 40 alternative candidate protection levels from down to 64 Mm -1 and up to 191 Mm -1 , with a 41Draft-Do Not Quote or Cite June 2010 4-50 midpoint level of 112 Mm -1 to provide appropriate protection against PM 2.5 -related visibility 1 impairment. 2 (6) Consideration should be given to th e following alternative secondary PM 2.5 standards to 3 provide protection against PM 2.5 -related visibility impairment during daylight hours: 4 (a) Consideration should be given to es tablishing a new 1-hour daily maximum 5 speciated PM 2.5 mass-calculated light extinction s econdary standard set at a level 6 within the range of 64 to 191 Mm -1 in combination with a 90 th or 95 th percentile 7 form, averaged over 3 years. 8 (b) Alternatively, considerati on could be given to a new all daylight hours speciated 9 PM 2.5 mass-calculated light extinction secondary standard set at a level within the 10 range of 64 to 191 Mm -1 in combination with a 98 th percentile form, averaged 11 over 3 years. 12

4.5 KEY UNCERTAINTIES AND AREAS FOR FUTURE RESEARCH AND DATA 13 COLLECTION 14 This section will be organized into two overarching topic areas: refining current 15 understanding of visibility preferences and ch aracterization of ambi ent urban visibility 16 conditions. The first deals principally with how the public reacts to a nd values visibility 17 conditions, while the second is more concerned w ith determining ambient visibility conditions 18 and the relationships between PM compone nt concentrations and light extinction. 19
Visibility Preferences 20

 Levels: The results of the reanalys is of the four urban prefer ence studies (UFVA Chapter 2) 21 demonstrated well defined though significant statis tical differences in vi sibility impairment 22 levels that divide acceptable from unacceptable conditions across the study areas. A number 23 of hypothesis concerning why the results differed for each area are discussed in chapter 2 of 24 the UFVA, but the current stat e of knowledge does not support a definitive explanation for 25 the range of results. A better understanding of the reasons for the differences in preference 26 response among the studies of the four urban areas could influence the design of future 27 visibility preference survey studies and the inte rpretation of their results ultimately leading to 28 a better defined range of CPLs for the next PM NAAQS review. 29

 Averaging Times/Forms : Additional information would al so be helpful in deciding among 30 the various forms and averaging times to devel op an effective visibili ty based secondary PM 31 NAAQS and to assess the overall benefits of visibility improvements. Our current 32 understanding of urban visibi lity effects does not provi de insights concerning: 33

o relative importance of intensity versus frequency of visibility impairment, 34

o strength of preference for different distributions of visibility conditions, and 35

o public exposure rates and mechanisms. 36

Future research to address these deficien cies should include designing and conducting 37 additional preference, valuati on and exposure studies to: 38Draft-Do Not Quote or Cite June 2010 4-51 o expand the number and geographic covera ge of urban area preference results, 1

o evaluate the sensitivity of results to the differences in survey study methodology, 2

o apply consistent methodology at multiple urban areas to better understand reasons for 3 preference difference among results in different urban areas, 4

o develop information on the stre ngth of preference and rela tive importance of intensity 5 versus frequency of visibility impairment 6

o identify the types of scenic elements that are most influential for informing public 7 visibility impact awareness, and 8

o provide insights concerning vi sibility impact exposure dur ation, intensity and timing 9 and their relationship to the degree and longevity of public welfare effects. 10

Additionally, prior to the next PM NAAQS re view and as part of the planning for 11 additional preference and valuation survey studies, a literature review of recent social science 12 literature could usefully be conducted to assess the state of knowledge of view exposure 13 mechanisms, and the psychological and behavioral effects associated with viewed stimuli. 14
Urban Visibility Conditions 15
The paucity of light extinction monitoring data for urban areas lead to the use of the 16 IMPROVE algorithm to calculate hourly light extinction from continuous PM mass and 24-hour 17

PM 2.5 component and relative humidity data (UFVA Chapter 3). The steps used to apportion 24- 18
hour PM 2.5 component to calculate hourly averagedvalues used monthly mean diurnal PM 19 component variations from regional air quality modeling. The mass balance methods used to 20 estimate organic concentration and the loss of nitrat e are reasonable but not likely to be precise. 21 The IMPROVE algorithm was originally developed for remote area application to estimate 24- 22 hour light extinction and it was not verified for use in generating urban hourly estimates. The 23 resulting hourly PM light extinc tion data set is thought to be r easonably representative of the 24 hourly PM light extinction levels that is adequate for assessment purposes, but these data are less 25
accurate than those from direct measurements. 26 A pilot PM light extinction monitoring program could usefully be designed and deployed 27
at some number of locations selected to cover a range of PM air quality conditions with emphasis 28 given to locations with continuous PM mass a nd speciation monitoring as well as 24-hour mass 29 and speciation sampling. Information from such a pilot monitoring program could be used to: 30

o evaluate the performance of PM light extinction monitoring methods that could 31 ultimately be use as an FRM, 32

o evaluate and refine approaches for apportio ning 24-hour PM species to hourly values 33 (needed for sites without conti nuous PM speciation monitoring), 34

o evaluate and refine light extinction calcul ation algorithms for use in urban settings, 35 and 36

o conduct the visibility eff ects assessment for the next PM secondary NAAQS. 37Draft-Do Not Quote or Cite June 2010 4-52 4.6 REFERENCES 1
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Smith, A. (2009). Comments on the First External Revi ew Draft of EPA’s “Integra ted Science Assessment for 33 Particulate Matter.” CRA Internation. Washington, DC . March 30. Prepared for the Utility Air Regulatory 34 Group,. Submitted as public comments to the public meeting EPA Clean Air Science Advisory Council. 35 April 2. 36

Smith AE; Howell S (2009). An assessment of the robust ness of visual air quality preference study results. CRA 37 International. Washington, 38 DC.http://yosemite.epa.gov/sab/sabproduct.nsf/ B55911DF9796E5E38525759 2006FB737/$File/CRA+VA 39 Q+Pref+Robustness+Study+3+30+09+final.pdf. 40

US EPA (2005). Review of the National Ambient Air Qua lity Standards for Particulate Matter: Policy Assessment 41 of Scientific and Technical Information, OAQPS Staff Paper. Research Triangle Park, NC 27711: Office 42 of Air Quality Planning and Standa rds; report no. EPA EPA-452/R-05-00 5a. December 2005. Available: 43 http://www.epa.gov/ttn/naaqs/standards/pm/s_pm_cr_sp.html 44Draft-Do Not Quote or Cite June 2010 4-53 US EPA (2008a). Integrated Review Plan for the Nationa l Ambient Air Quality Standards for Particulate Matter. 1 National Center for Environmental Assessment and Office of Air Quality Planning and Standards, U.S. 2 Environmental Protection Agency, Research Triangle Park, NC. Report No. EPA 452/R-08-004. March 3 2008. Available at: http://www.epa.gov/ttn/naaqs/standards/pm/s_pm_2007_pd.html

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US EPA (2010 a). Quantitative Risk Assessment for Par ticulate Matter – Final Report. Office of Air Quality 9 Planning and Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC. EPA-452/R10 10-005. June 2010. Available: http://www.epa.gov/ttn/naaqs/standards/pm/s_pm_2007_risk.html 11 12 US EPA (2010b). Particulate Matter Urban-Focused Visi bility Assessment – Final Report. Office of Air Quality 13 Planning and Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC. EPA-452/R14 10-004. June 2010. Available: http://www.epa.gov/ttn/naaqs/standards/pm/s_pm_2007_risk.html

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16 US EPA (2010f). White Paper on PM Light Extinction Measurements. Office of Air Quality Planning and 17 Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC. January 2010. Available 18
at: 19 http://yosemite.epa.gov/sab/sabproduct.nsf/264cb1227d55e02c85257402007446a4/823a6c8842610e76852 20 5764900659b22!OpenDocument 21This page left intentionally blank.Draft-Do Not Quote or Cite June 2010 5-1 

### 5 REVIEW OF THE SECONDARY STANDARDS FOR OTHER 1 

### WELFARE EFFECTS 2

This chapter presents staff conclusions with regard to the current suite of secondary PM 3 standards to protect against PM -related welfare effects other than visibility impairment. 4 Specifically, staff has assessed the relevant inform ation related to effects of atmospheric PM on 5 the environment, including effects on climate, ec ological effects, and effects on materials. Our 6 assessment is framed by a series of key po licy-relevant questions, which expand upon those 7 presented in the Integrated Review Plan (IRP) (US EPA, 2008a, section 3.2). The answers to 8 these questions will inform decisions on whether to retain or revise the current suite of secondary 9
PM standards. 10 In presenting staff conclusions with regard to the current secondary standards relative to 11 PM-related effects on climate, ecological effects, a nd materials, we note that the final decision is 12 largely a public welfare policy j udgment. A final decision must draw upon scientific information 13 and analyses about non-visibility PM-related e ffects and related impacts on public welfare, as 14 well as judgments about how to d eal with the range of uncertainti es that are inherent in the 15 scientific evidence and analyses. Our approach to informing thes e judgments is discussed more 16 fully below. This approach is consistent with the requirements of the NAAQS provisions of the 17
Act and with how EPA and the cour ts have historically interpreted the Act. These provisions 18 require the Administrator to esta blish secondary standa rds that, in the Administrator’s judgment, 19 are requisite to protect public welfare from any known or anticipa ted adverse effects associated 20 with the presence of the pollutant in the ambient air. In so doing, the Administrator seeks to 21
establish standards that are neither more nor less stringent than necessary for this purpose. The 22 Act does not require that secondary standards be set at a zero-risk level, but rather at a level that 23 avoids unacceptable public welfare impacts. 24 Information on the approaches used to set the secondary PM standards in past reviews as 25 well as our current approach for this review are presented in section 5.1. A discussion of the 26 scope of the review as related to non-visibility welfare effects of PM is included in section 5.1.2. 27 This chapter considers each of the non-visibility welfare effects separate ly. The discussion of 28 PM-associated effects on climate (section 5.2), ecological effects (sect ion 5.3), and materials 29 (section 5.4) are each followed by a consideratio n of key uncertainties and areas for future 30
research and data collection. 31

5.1 APPROACH 32 Background information on the approaches used to establish the PM secondary standards 33
in 1997 and revisions to those standards in 2006 are summarized below. This section also 34Draft-Do Not Quote or Cite June 2010 5-2 includes a discussion of the ongoing joint review of ecological effects of oxides of nitrogen and 1 sulfur (NOx/SOx secondary review) for clarity, since depositional effect s of PM components of 2 NOx and SOx to ecosystems were historically c onsidered as a component of the PM secondary 3 review. Lastly, there is a disc ussion of the current approach fo r evaluating the effects of PM on 4 climate, ecosystems, and materials using evidence-based considerations to inform our 5 understanding of the key po licy-relevant issues. 6

5.1.1 Approaches Used in Previous Reviews 7

5.1.1.1 Review Completed in 1997 8

In the 1997 review, as discussed in section 2.1.1.1, EPA determined that for the primary 9
standard the fine and coarse fractions of PM 10 should be considered separately and added a suite 10 of new primary standards, using PM 2.5 , as the indicator for fine particles, and retaining PM 10 as 11 the indicator for regulating thoracic coarse particles. The EPA established two new PM 2.5 12 standards: an annual standard of 15 μg/m 3 , based on the 3-year average of annual arithmetic 13
mean PM 2.5 concentrations from single or multiple community-oriented monitors; and a 24-hour 14 standard of 65 μg/m 3 , based on the 3-year average of the 98 th percentile of 24-hour PM 2.5 15 concentrations at each populat ion-oriented monitor within an area (62 FR 38652, July 18, 1997). 16 With respect to the secondary PM standard s, EPA concluded in 1997, that the available 17
evidence on effects of PM on non-vi sibility welfare endpoints wa s not sufficient to warrant a 18 separate secondary standard. Therefore, the se condary standards were set equal to the primary 19

PM 2.5 and PM 10 standards in the final rule to provide protection against eff ects on visibility as 20 well as materials damage and soiling effects rela ted to fine and coarse particles (62 FR 38683). 21

5.1.1.2 Review Completed in 2006 22

In 2006, the Administrator concluded that there was insufficient information to consider a 23 distinct secondary standard ba sed on PM-related impacts to ecos ystems, materials damage and 24 soiling, and climatic and radiative processe s (71 FR 61144, October 17, 2006). Specifically, 25
there was a lack of evidence linki ng various non-visibility welfare e ffects to specific levels of 26 ambient PM. To provide a level of protecti on for welfare-related effects, the secondary 27 standards were set equal to the revised primary standards to directionally improve the level of 28 protection afforded vegetation, ecos ystems and materials (71 FR 61210). 29 In the last review, the 2004 AQCD concluded that regardless of size fraction, particles 30 containing nitrates and sulfates have the greatest potential for widespread environmental 31 significance (US EPA, 2004, sections 4.2.2 and 4.2.3.1). Considerable supporting evidence was 32
available that indicated a si gnificant role of NOx, SOx, a nd transformation products in 33Draft-Do Not Quote or Cite June 2010 5-3 acidification and nutrient enrichment of terre strial and aquatic ecosystems (71 FR 61209). The 1 recognition of these ecological eff ects, coupled with other considerations detailed below, led 2 EPA to initiate a joint review of the NO 2 and SO 2 secondary NAAQS that will consider the 3 gaseous and particulate species of NOx and SOx with respect to the ecosystem-related welfare 4 effects that result from the deposition of these pollutants and transformation products. 5

5.1.2 Scope of Current NAAQS Reviews 6 Non-visibility welfare-based e ffects of oxides of nitrogen a nd sulfur are divided between 7 two NAAQS reviews; (1) the PM NAAQS revi ew and, (2) the joint NOx/SOx secondary 8 NAAQS review. The scope of each document and the components of N and S considered in 9
each review are detailed in this se ction and summarized in Table 5-1. 10

5.1.2.1 Scope of the Current Secondary PM NAAQS Review 11

In reviewing the current suite of secondary PM standards to address visibility impairment 12 (chapter 4), climate forcing eff ects (section 5.2), and other welf are-related effects (sections 5.3 13 and 5.4), all PM-related effects that are not being covered in the NOx/SOx review are 14 considered. With regard to the materials sec tion (5.4), the discussion has been expanded to 15 include particles and gases that are associated with the presence of ambient NOx and SOx, as 16 well as NOy, NH 3 and NH X for completeness. By excludi ng the effects associated with 17 deposited particulate matter components of NOx and SOx and their transformation products 18 which are addressed fully in the NOx/SOx seconda ry review, as outlined below, the discussion 19 of ecological effects of PM has been narrowed to focus on effects associat ed with the deposition 20 of metals and, to a lesser ex tent, organics (section 5.3). 21Draft-Do Not Quote or Cite June 20105-4Table 5-1. Scope of the current secondary PM NAAQS review and current NOx/SOx secondary review.1NOx/SOx SecondaryReviewPM SecondaryReviewMaterialsWelfareEffectAcidifyingdeposition,nutrientenrichmentDirect effectsof gas-phaseNOx/SOx onvegetationVisibilityimpairmentClimateForcing effectsEcologicaleffectsDamage SoilingDocumentsISANOx/SOxNOx/SOxPMPMPMPM andNOx/SOxAnnex E PMREANOx/SOx NOx/SOxPM (Urbanfocusedvisibilityassessment)PANOx/SOx NOx/SOx PM PM PM PM PMComponentsDepositedparticulate andgaseous formsof oxides ofnitrogen andsulfur andrelated N and Scontainingcompounds.Gaseous formsof oxides ofnitrogen andsulfur andrelated N and Scontainingcompounds inthe ambient air.All particles10 microns orsmaller in theambient air.Climate-relatedparticles(aerosols) inthe ambient air.Depositedcomponentsof PM,includingmetals andorganics butnot N and Scontainingcompounds.Particles andgasesassociated withambient NOxand SOxincluding NOy,NH3and NHx.Depositedparticles2Draft-Do Not Quote or Cite June 2010 5-5 5.1.2.2 Scope of the Current NOx/SOx Secondary NAAQS Review 1

This is the first time since the NAAQS were es tablished in 1971 that a joint review of the 2 secondary NAAQS for NOx and SOx

, has been conducted. This review is being conducted 3 because the atmospheric chemistry and environmen tal effects of NOx, SOx, and their associated 4 transformation products are linked, and because the National Research Council (NRC) has 5 recommended that EPA consider multiple pollutants, as appropriate, in forming the scientific 6 basis for the NAAQS. The NOx/SOx secondary revi ew focuses on the welfar e effects associated 7 with exposures from deposited particulate and ga seous forms of oxides of nitrogen and sulfur 8 and related N and S containing compounds and tran sformation products on ecosystem receptors. 9 An assessment of the complex ecological eff ects associated with N deposition requires 10 consideration of multiple forms of N. These include evaluation of data on inorganic reduced 11 forms of N (e.g., ammonia [NH 3 ] and ammonium ion [NH 4 +]), inorganic oxidized forms (e.g., 12 NOx, nitric acid [HNO 3 ], nitrous oxide [N 2 O], nitrate [NO 3

− ]), and organic N compounds (e.g., 13 urea, amines, proteins, nucleic acids). In addi tion to acidification and N-nutrient enrichment, 14
other welfare effects related to deposition of N-and S-containi ng compounds are discussed, such 15 as SOx interactions with mercury (Hg) methyl ation. In addition, the NOx/SOx secondary review 16 includes evidence related to direct ecological eff ects of gas-phase NOx and SOx since the direct 17 effects of gas-phase SOx on vegetation formed a pr imary basis for the initial establishment of the 18 secondary NAAQS for SO 2
. 19 Effects of acidifying deposition associated w ith particulate N and S are covered in the 20

recent Integrated Science Assessmen t for Oxides of Nitrogen and Sulfur-Ecological Criteria 21 ( Final Report (US EPA, 2008c). The Risk and Exposure Assessment for Review of the 22 Secondary National Ambient Air Q uality Standards for Oxides of Nitrogen and Oxides of Sulfur 23 (Final) (NOx/SOx REA) (US EPA, 2 009h) considers four main targeted ecosystem effects 24 considered in the review of secondary effects of NOx and SOx: (1) aquatic acidification due to N 25 and S, (2) terrestrial acidificat ion due to N and S, (3) aquatic nutrient enrichment, including 26 eutrophication and (4) terrestrial nu trient enrichment. In the draft Policy Assessment for Review 27 of the Secondary National Ambien t Air Quality Standards for Oxides of Nitrogen and Oxides of 28 Sulfur (US EPA 2010c) ecologically-based indicators that link atmospheric concentrations to 29 deposition are being considered. 30

5.1.3 Current Approach 31 The remainder of this chapter summarizes and highlights key aspects of the policy 32 relevant information from the ISA to help info rm the Administrator’s judgments regarding the 33 adequacy of the current suite of secondary PM NAAQS in relation to climate processes, 34Draft-Do Not Quote or Cite June 2010 5-6 ecological effects, and materials damage. The ISA uses a five-level hierarchy that classifies the 1 weight of evidence for causation, not just asso ciation, into a qualitative statement about the 2 overall weight of evidence and causality (U S EPA, 2009a, section 1.5.5, Table 1-3): causal 3 relationship; likely to be a causa l relationship; suggestiv e of a causal relations hip; inadequate to 4 infer a causal relationship; not likely to be a causal relationship (see US EPA, 2009a, Table 1-3). 5 Staff is evaluating evidence-based consideratio ns primarily by assessing the evidence of 6
associations identified in the ISA. All relations hips between PM and climate, ecological effects, 7 and materials damage effects identified in the ISA are considered to be either “likely causal” or 8 “causal”. The staff’s approach in this review of non-visibility welfare effects of PM is to 9 consider information regarding pa rticulate matter effects on c limate, ecological endpoints and 10
materials. This includes new literature availa ble since the last review as well as existing, 11 relevant information as presented in the ISA (US EPA 2009a). 12

5.2 CLIMATE 13

5.2.1 Scope 14

Information and conclusions about what is currently known about the role of PM in 15 climate is summarized in Chapter 9 of the PM ISA (US EPA, 2009a). The ISA concludes; “that 16 a causal relationship exists between PM and effects on climate, including both direct effects on 17 radiative forcing and indirect effects that involve cloud feedb acks that influence precipitation 18 formation and cloud lifetimes” (US EPA, 2009a, s ection 9.3.10). Material from the climate 19 section of the ISA is principally drawn from the U.S. Climate Change Science Program 20 Synthesis and Assessment Product 2.3, Atmospheric Aerosol Prope rties and Climate Impacts , by 21 Chin et al., (CCSP 2009) and Chapter 2, Changes in Atmospheric Cons tituents and in Radiative 22 Forcing ,(Forster et al., 2007) in the comprehensive Working Group I report in the Fourth 23 Assessment Report (AR4) from the Intergovernmen tal Panel on Climate Change (IPCC), Climate 24 Change 2007: The Physical Science Basis . Sections 9.3.7 (Fire as a Special Source of PM 25 Welfare Effects), 9.3.9 (Other Special Sources and Effects), 9.3.9.1 (Gla ciers and Snowpack) 26 and 9.3.9.3 (Effects on Local and Regional Climate) of the ISA were written by NCEA staff. 27
This section of the PA summarizes and synthesizes the policy-releva nt science in the ISA for the 28 purpose of helping to inform consideration of clim ate aspects in the review of the secondary PM 29 NAAQS. 30 Atmospheric PM (referred to as aerosols 1 in the remainder of this section to be consistent 31 with the ISA) affects multiple aspects of clim ate. These include absorbing and scattering of 32

1 In the sections of the ISA included from IPCC AR4 and CCSP SAP2.3, ‘aerosols’ is more frequently used than “PM” and that word is retained.Draft-Do Not Quote or Cite June 2010 5-7 incoming solar radiation, alterations in terrestr ial radiation, effects on th e hydrological cycle, and 1 changes in cloud properties (US EPA, 2009a, s ection 9.3.1). Major aerosol components that 2 contribute to climate processes in clude black carbon (BC), organic ca rbon (OC), sulfates, nitrates 3
and mineral dusts. There is a considerable ongoing research effort focused on understanding 4 aerosol contributions to changes in global mean temperature and precip itation patterns. The 5 Climate Change Research Initiative identified re search on atmospheric concentrations and effects 6 of aerosols as a high research priority (Nationa l Research Council, 2001) and the IPCC 2007 7 Summary for Policymakers states that anthropogenic cont ributions to aerosols remain the 8 dominant uncertainty in radiative forcing (IP CC 2007). The current state of the science of 9
climate alterations attributed to PM is in flux as a result of c ontinually updated information. 10

5.2.2 Adequacy of the Current Standard 11 In considering the adequacy of the suite of secondary standards, staff addresses the 12 following overarching question: 13

Does currently available scientific information, as reflected in the ISA, support or call into 14 question the adequacy of the protection for clim ate effects afforded by the current suite of 15 secondary PM standards? 16 To inform the answer to this overarching que stion, staff has posed specific questions to 17 aid in assessing the available scientific eviden ce as related to climate effects attributed to 18 aerosols. In considering the curr ently available scientific and t echnical information, we included 19
both the information available from the last review and information that is newly available since 20 the last review synthesized in Chapter 9 of the ISA (US EPA, 2009a). 21

 What new techniques are available to improve our understanding of climate effects of 22 aerosols? 23 Global climate change has increasingly been th e focus of intense international research 24 endeavors. Major efforts are underway to unders tand the complexities inherent in atmospheric 25
aerosol interactions and to decrease uncertainties associated with climate estimations. Two recent 26 reports, the US CCSP Product 2.3 and sections of the IPCC AR4 were combined to form the 27 climate discussion in the ISA (CCSP 2009; Forster et al., 2007). A review of the most recently 28 available techniques for assessing climate-aerosol relationships is presented in the ISA. Aerosol 29 measurement capabilities review ed in the ISA include a di scussion of the increasingly 30 sophisticated instrumentation and techniques av ailable for quantifying ae rosols, the enhanced 31 sensing capabilities of satellites , development of remote sensing networks and synergy of 32 measurements with model simulations (US EP A 2009a, section 9.3.2). Advances in measured 33 aerosol properties as related to modeling as well as outstandi ng issues remaining in these 34
measurement-based studies are elaborated in the ISA (US EPA 2009a sections 9.3.3 and 9.3.4). 35Draft-Do Not Quote or Cite June 2010 5-8 Section 9.3.6 of the ISA, “Global Aerosol Mode ling” considers the capabilities of climate 1 modeling that have developed over the last decade and limitations of the techniques currently in 2 use (US EPA 2009a). 3

 To what extent does newly available eviden ce improve our understanding of the nature 4 and magnitude of climate res ponses to PM (aerosols)? 5

Aerosols have direct and indi rect effects on climate processes. The direct effects of 6 aerosols on climate result mainly from particles scattering light away fr om earth into space, 7 directly altering the radiative ba lance of the Earth-atmosphere sy stem. This reflection of solar 8 radiation back to space decreases the transmission of visible radiation to the surface of the earth 9 and results in a decrease in the heating rate of the surface and the lower atmosphere. At the same 10 time, absorption of either incoming solar radiatio n or outgoing terrestrial radiation by particles, 11 primarily BC, results in an increased heating ra te in the lower atmosphere. Global estimates of 12
aerosol direct radiative forci ng (RF) were recently summarized using a combined model-based 13 estimate (Forster et al., 2007). The overall, model- derived aerosol direct RF was estimated in the 14 IPCC AR4 as -0.5 (-0.9 to -0.1) watts per square meter (W/m 2 ), with an overall level of scientific 15 understanding of this effect as “medium low” (Forster et al., 2007), i ndicating a net cooling 16 effect in contrast to greenhouse gases ( GHGs) which have a warming effect. 17 The contribution of individual aerosol component s to total aerosol dire ct radiative forcing 18 is more uncertain than the globa l average (US EPA, 2009a, section 9.3.6.6). The direct effect of 19 radiative scattering by atmospheri c particles exerts an overall ne t cooling of the atmosphere, 20 while particle absorption of solar radiation leads to warming. For example, the presence of OC 21 and sulfates decrease warming from sunlight by scattering shortwave radia tion back into space. 22 Such a perturbation of incoming radiation by an thropogenic aerosols is designated as aerosol 23 climate forcing, which is distinguished from the aerosol radiative effect of the total aerosol 24 (natural plus anthropogenic). The aerosol climat e forcing and radiative e ffect are characterized 25 by large spatial and temporal hete rogeneities due to the wide va riety of aerosol sources, the 26 spatial non-uniformity and intermittency of thes e sources, the short atmospheric lifetime of 27 aerosols (relative to that of the greenhouse gases), and processing (chemical and microphysical) 28 that occurs in the atmosphere. For example, OC can be warming (positive forcer) when 29 deposited on or suspended over a highly reflectiv e surface such as snow or ice but, on a global 30 average, is a negative forcer in the atmosphere. 31
More information has also become available on indirect effects of aer osols. Particles in 32 the atmosphere indirectly affect both cloud albe do (reflectivity) and cl oud lifetime by modifying 33 the cloud amount, and microphysical and radiativ e properties (US EPA, 2009a, section 9.3.6.4). 34
The RF due to these indirect e ffects (cloud albedo effect) of aerosols is estimated in the IPCC 35 AR4 to be -0.7(-1.8 to -0.3) W/m 2 with the level of sc ientific understanding of this effect as 36Draft-Do Not Quote or Cite June 2010 5-9 “low” (Forster et al., 2007). Aerosols act as cloud condensation nuclei (CCN) for cloud 1 formation. Increased particulates in the atmo sphere available as CCN with no change in 2
moisture content of the clouds have resulted in an increase in th e number and decrease in the size 3 of cloud droplets in certain clouds that can increase the albe do of the clouds (the Twomey 4 effect). Smaller partic les slow the onset of precipitation and prolong cloud lifetime. This effect, 5 coupled with changes in cloud albedo, increase the reflection of solar radiation back into space. 6
The altitude of clouds also eff ects cloud radiative forcing. Low clouds reflect incoming sunlight 7 back to space but do not effectively trap outgoin g radiation, thus, cooling the planet, while higher 8 elevation clouds reflect some sunlight but more e ffectively can trap outgoi ng radiation and act to 9 warm the planet (US EPA, 2009a, section 9.3.3.5). 10 The total negative RF due to di rect and indirect effects of aerosols computed from the top 11 of the atmosphere, on a global average, is estimated at -1.3 (-2.2 to -0.5) W/m 2 in contrast to the 12 positive RF of +2.9 (+3.2 to +2.6) W/m 2 for anthropogenic GHGs (IPCC 2007, pg. 200). 13 The understanding of the magnitude of aer osol effects on climate has increased 14 substantially in the last decade. Data on the atmospheric transport and deposition of aerosols 15 indicate a significant role for PM components in multiple aspects of climate. Aerosols can 16 impact glaciers, snowpack, regi onal water supplies, precipitat ion and climate patterns (US EPA 17 2009a section 9.3.9). Aerosols de posited on ice or snow can le ad to melting and subsequent 18 decrease of surface albedo (US EPA 2009a, secti on 9.3.9.2). Aerosols are potentially important 19 agents of climate warming in the Arctic and other locations (US EPA, 2009a, section 9.3.9). 20 Incidental fires and biomass burning are bei ng recognized as having a significant impact on 21

PM 2.5 concentrations and climate forcing. Intermitten t fires can occur at large enough scales to 22 affect hemispheric aerosol concentra tions (US EPA 2009a, section 9.3.7). 23
A series of studies available since the last review examine the role of aerosols on local 24 and regional scale climate processes (US EP A, 2009a, section 9.3.9.3). Studies on the South 25 Coast Air Basin (SCAB) in California indicate aerosols may reduce near-surface wind speeds, 26 which, in turn reduce evaporation rates and increase cl oud lifetimes. The overall impact can be a 27 reduction in local precipitation (Jacobson and Kaufmann, 2006). Conditions in the SCAB impact 28 ecologically sensitive areas including the Sie rra Nevadas. Precipitation suppression due to 29 aerosols in California (Givati and Rosenfield, 2004) and other similar studies in Utah and 30 Colorado found that orographic precipitation decreased by 15-30% downwind of pollution 31 sources. Evidence of regional-scale impacts of aerosols on meteorological conditions in other 32 regions of the U.S. are lacking. 33Draft-Do Not Quote or Cite June 2010 5-10  To what extent does the currently available information provide evidence of association 1 between specific PM constituents (i.e. BC, OC , sulfates) and climat e-related effects? 2 Advances in the understanding of aerosol components and how they contribute to climate 3 change have enabled refined global forcing estimates of individual PM constituents. The global 4 mean radiative effect from individual components of aerosols was estimated for the first time in 5 the IPCC AR4 where they were reported to be (all in W/m 2 units): -0.4 (+ 0.2) for sulfate, -0.05 6 (+ 0.05) for fossil fuel-derived OC, +0.2 (+0.15) for fossil fuel derived BC, +0.03 (+ 0.12) for 7 biomass burning, -0.1 (+ 0.1) for nitrates, and -0.1 (+ 0.2) for mineral dust (US EPA, 2009a, 8 section 9.3.10). Sulfate and fossil fuel-derived OC cause negative forcing whereas BC causes 9 positive forcing because of its highly abso rbing nature (US EPA, 2009a, 9.3.6.3). Although BC 10 comprises only a small fraction of anthropogenic aerosol mass load and aerosol optical depth 11 (AOD), its forcing efficiency (w ith respect to either AOD or ma ss) is an order of magnitude 12 stronger than sulfate and particulate organic ma tter (POM), so its positive shortwave forcing 13 largely offsets the negative direct forcing from sulfate and POM (IPCC, 2007; US EPA 2009a, 14 9.3.6.3). Global loadings for nitrates and anthropo genic dust remain very difficult to estimate, 15 making the radiative forcing estimates for these constituents particularly uncertain (US EPA, 16 2009a, section 9.3.7). 17 Improved estimates of anthropogenic emissions of some aerosols, especially BC and OC, 18 have promoted the development of improved glob al emissions inventorie s and source-specific 19
emissions factors useful in cl imate modeling (Bond et al. 2004). Recent data suggests that BC is 20 one of the largest individual warm ing agents after carbon dioxide (CO 2 ) and perhaps methane 21 (CH 4 ) (Jacobson 2000; Sato et al., 2003; Bond a nd Sun 2005). There are several studies 22 modeling BC effects on climate and/or c onsidering emission reduction measures on 23 anthropogenic warming detailed in section 9.3.9 of the ISA. Fire s release large amounts of BC, 24
CO 2 , CH 4 and OC (US EPA, 2009a, section 9.3.7). 25

5.2.3 Staff Conclusions 26

 Aerosols alter climate processes directly through radiative forc ing and by indirect 27 effects on cloud brightness, changes in pr ecipitation and possibl e changes in cloud 28 lifetimes. 29

 Individual components of aeros ols differ in their reflective properties, and direction of 30 climate forcing. Overall, based on current estimates of aerosol radiative forcing, 31 aerosols have a net climate cooling effect. 32

 Most climate model simulations are based on global scale scenarios. These models 33 may fail to consider the local variations in climate forcing due to emissions sources and 34 local meteorological patterns. 35Draft-Do Not Quote or Cite June 2010 5-11  Most of the warming aerosols in the U.S. are emitted by biomass burning and internal 1 engine combustion. Much of the cooling ae rosols are formed in the atmosphere by 2 oxidation of SO 2 or VOC’s. The relative mix and sources of warming and cooling 3 components will vary in areas across the U.S. and over time. Thus, a set of controls to 4 reduce warming PM would not necessarily reduce cooling PM and vice versa. 5

Collectively taking into consideration the res ponses to specific que stions regarding the 6 adequacy of the current secondary PM standards for climate effects, we revisit the overarching 7 question: “does available scientif ic information, as reflected in the ISA, support or call into 8 question the adequacy of the pr otection for climate effects affo rded by the current suite of 9 secondary PM standards?” As an initial matter, we considered the appropri ateness of the current 10 secondary standard defined in terms of PM 2.5 and PM 10 indicators, for providing protection 11 against potential climate effects of aerosols. Ne wly available scientific information on climate12 aerosol relationships has improved our understanding of direct and indirect effects of aerosols 13 and aerosol properties. The major aerosol com ponents that contribute to climate processes 14 include BC, OC, sulfate, nitrate and mineral dusts . These components vary in their reflectivity, 15 forcing efficiencies and even in the direction of climat e forcing. The current standards that are 16 defined in terms of aggregate size mass cannot be expected to appropriate ly target controls on 17 components of fine and coarse particles that ar e related to climate forc ing effects. Thus, the 18
current mass-based PM 2.5 and PM 10 secondary standards are not an appropriate or effective 19 means of focusing protection agai nst PM-associated climate effects due to these differences in 20
components. 21 Overall, there is a net climate cooling associ ated with aerosols in the global atmosphere 22 (US EPA, 2009a, section 9.2.10). Staff recognizes that some individual aerosol components, 23 such as BC, are positive climate forcers, wherea s others, such as OC a nd sulfates, are negative 24 climate forcers. The relative mix of compone nts will vary in areas across the U.S. and over 25 time. Due to the spatial and temporal heterogeneity of PM components that contribute to climate 26 forcing, uncertainties in the measurement of aer osol components, inadequate consideration of 27 aerosol impacts in climate modeling, insuffici ent data on local and regional microclimate 28 variations and heterogeneity of cloud formations, it is not cu rrently feasible to conduct a 29 quantitative analysis for the pur pose of informing revisions of the current NAAQS PM standard 30
based on climate. Based on these consideratio ns, we conclude that there is insufficient 31
information at this time to base a national ambi ent standard on climate impacts associated with 32
current ambient concentrations of PM or its constituents 2

. 33

2 Given the reasons discussed above, this conclusion would apply for both the secondary (welfare based) and the primary (health based) standards.Draft-Do Not Quote or Cite June 2010 5-12 5.2.4 Key Uncertainties and Areas for Futu re Research and Data Collection 1 Although considerable progress is being made in estimating aerosol contributions to 2 radiative forcing and climate fluctuations, si gnificant uncertainties remain that preclude 3
consideration of climate eff ects as a basis for establishing a separate NAAQS secondary 4
standard. Further research in to the effects of aerosols on c limate could provide important 5
information to reduce these uncertainties. 6 A major impediment at this time to establis hing a secondary standard for PM based on 7
climate is the lack of accurate measurement of aerosol contributions, spec ifically quantification 8 of aerosol absorption and inabi lity to separate the anthropogeni c component from total aerosol 9 forcing. Section 9.3.4 of the ISA details the curr ent limitations in aerosol measurement. Most 10
measurement studies focus on the sum of natura l and anthropogenic contributions under clear 11 sky conditions, however, this scenario is simp listic when effects of cloud cover and differing 12 reflective properties of land and ocean are consid ered. Satellite measurements do not currently 13 have the capability to distingui sh anthropogenic from natural aeros ols. Due to a lack of data on 14
the vertical distribution of aeros ols, above-cloud aerosols and pr ofiles of atmospheric radiative 15 heating are poorly understood (U S EPA, 2009a, section 9.3.4). 16 Another uncertainty in consid ering climate effects of PM in the NAAQS review is the 17 spatial and temporal heterogeneity of aerosols. In regions having high concentrations of 18 anthropogenic aerosols, aerosol forcing is greate r than the global average, and can exceed 19 warming by GHGs, locally reversing the sign of the forcing (US EPA, 2009a, section 9.3.1). 20 The contributions of policy-rele vant background (PRB) concentrati ons to aerosol climate forcing 21 are not sufficiently characterized (US EPA, 200 9a, section 3.7). Emissions of carbonaceous 22
aerosols from intermittent fires and volcanic ac tivity can further complicate regional climate 23 forcing estimates (US EPA, 2009a, sections 9.3.7 and 9.3.8). Individual co mponents of aerosols 24 may either be positive or negative climate forcer s. Airborne PM components may be directly 25 emitted or undergo a variety of physical and chem ical interactions and transformations. These 26 result in changes in particle size, structur e and composition which alter aerosol reflective 27 properties. Aerosols can grow in size in the atmosphere because ambient water vapor condenses 28 on individual particles, a phe nomenon known as hygroscopic growth (US EPA, 2009a, section 29 9.3.6.2). Atmospheric lifetimes of individual aer osol components vary greatly confounding 30 tracking source receptor relationships. 31 Improved representation of aerosols in climat e models is essentia l to more accurately 32 predict the role of PM in climate forcing (US EPA, 2009a, section 9.3.6.7). The influence of 33 aerosols on climate is not yet adequately take n into account in computer predictions although 34 considerable progress in being made in this ar ea. For example, PM components underrepresented 35 or missing from many models incl ude nitrate aerosols and anthr opogenic secondary aerosols (US 36Draft-Do Not Quote or Cite June 2010 5-13 EPA, 2009a, section 9.3.6.7). The modeling of aero sol indirect effects and absorption are 1 difficult due to the high level of uncertainty associated with these climate factors. 2
The interaction of PM with clouds remains a large source of uncertainty in climate 3
estimates. The interactions of aerosols with clouds and linkage s between clouds and the overall 4 climate system are complex and limit the feasib ility of conducting quantitative analysis for the 5 purpose of establishing a secondary PM standard based on welfare effects on climate processes. 6 There are uncertainties associated with the po tential effects of the alternative standards 7 for visibility discussed in Chapter 4 on regional radiative forcing and climate. A secondary 8 standard for visibility based on light extinction would result in re duced emissions that affect PM 9 in areas where monitoring shows exceedance of the standard. The extinction budget work 10 conducted for the UFVA (Figure 3-13, U.S. EPA 2010b) and second draft PA (Appendix B) 11 indicates that most of the current visibility im pact contributions on worst days comes from light 12 scattering particles (e.g., nitrates, sulfates) that are negative climat e forcers, and a smaller portion 13 from absorbing aerosols (e.g., bl ack carbon) that are positive c limate forcers. The relative 14 proportions of scattering and ab sorbing particles vary by locati on and some major contributing 15
emission sources contribute to both scattering and absorbing PM, so it is unclear how the ratio of 16 scattering to absorption might change in response to a secondary standard for visibility affects. 17 However, since the prevailing mixture of aerosol is thought to have a net cooling effect on 18 regional climate, reducing PM and light scatteri ng aerosols could lead to increased radiative 19 forcing and regional climate warming while ha ving a beneficial eff ect on visibility. 20

5.3 ECOLOGICAL EFFECTS 21

5.3.1 Scope 22 Information on what is currently known about ecological effects of PM is summarized in 23 Chapter 9 of the ISA (US EPA 2009a). Four main categories of ecological effects are identified 24 in the ISA: direct effects, effect s of PM-altered radiative flux, i ndirect effects of trace metals and 25 indirect effects of organics. Exposure to PM for direct effects occur via deposition (e.g. wet, dry 26 or occult) to vegetation surfaces, while indirect effects occur via deposition to ecosystem soils or 27 surface waters where the deposited constituents of PM then interacts with biological organisms. 28 Both fine and coarse-mode particles may affect plants and other orga nisms; however, PM size 29 classes do not necessarily relate to ecological e ffects (U.S. EPA, 1996). More often the chemical 30 constituents drive the ecosystem response to PM (Grantz et al., 2003). The trace metal 31
constituents of PM considered in the ecological effects sectio n of the ISA are cadmium (Cd), 32 copper (Cu), chromium (Cr), mercury (Hg), nickel (Ni) and zinc (Zn). Ecol ogical effects of lead 33 (Pb) in particulate form are covered in the Ai r Quality Criteria Document for Lead (US EPA, 34 2006). The organics included in th e ecological effects s ection of the ISA are persistent organic 35Draft-Do Not Quote or Cite June 2010 5-14 pollutants (POPs), polyaromatic hydrocarbons (PAHs) and polybromiated diphenyl ethers 1 (PBDEs). 2 Ecological effects of PM include direct eff ects to metabolic processes of plant foliage; 3 contribution to total metal loading resulting in alteration of soil biogeochemistry and 4 microbiology, plant and animal growth and repro duction; and contribution to total organics 5 loading resulting in bioaccumulati on and biomagnification across trophi c levels. It is important 6 to emphasize that the metal and organic constituents of PM contribute to total metal and organic 7 loads in ecosystems. 8 The ISA states that overall, ecological evidence is sufficient to conclude that a causal 9 relationship is likely to exist between depositi on of PM and a variety of effects on individual 10 organisms and ecosystems based on informati on from the previous review and limited new 11 findings in this review (US EPA 2009a, sectio ns 2.5.3 and 9.4.7). However the ISA also finds, 12 in many cases, it is difficult to characterize the na ture and magnitude of effects and to quantify 13 relationships between ambient co ncentrations of PM and ecosystem response due to significant 14 data gaps and uncertainties as well as considerable variability that exists in the components of 15
PM and their various ecological effects. 16 Ecological effects of PM must then be eval uated to determine if they are known or 17 anticipated to have an adverse impact on public welfare. Characterizi ng a known or anticipated 18 adverse effect to public welf are is an important component of developing any secondary 19 NAAQS. The most recent secondary NAAQS re views have assessed changes in ecosystem 20 structure or processes using a weight-of-evidence approach that uses both quantitative and 21 qualitative data. For example, the 2008 ozone (O 3 ) final rule and 2010 O 3 proposal conclude that 22
a determination of what constitutes an “advers e” welfare effect in th e context of secondary 23 NAAQS review can appropriately occur by consid ering effects at higher ecological levels 24 (populations, communities, ecosystems) as s upported by recent literature. In the 2008 25 rulemaking and current ozone proposa l, the interpretation of what constitutes an adverse effect 26 on vegetation can vary depending on the location a nd intended use of the plant. The degree to 27
which O 3 -related effects are considered adverse depe nds on the intended use of the vegetation 28 and its significance to public welfare (73 FR 16496) . Therefore, effects (e.g. biomass loss, foliar 29 injury, impairment of intended use) may be judged to have a different degree of impact on public 30 welfare depending, for example, on whether that e ffect occurs in a Cla ss I area, a city park, 31 commercial cropland or private land. 32 A paradigm useful in evaluating ecological adversity is the concept of ecosystem 33 services. Ecosystem services identify the varied and numerous ways that ecosystems are 34 important to human welfare. Ecosystems provi de many goods and services that are of vital 35 importance for the functioning of the biosphere an d provide the basis for the delivery of tangible 36Draft-Do Not Quote or Cite June 2010 5-15 benefits to human society. An EPA initiative to consider how ecosystem structure and function 1 can be interpreted through an ecosystem services approach has resulted in the inclusion of 2 ecosystem services in the NOx/SOx REA (U S EPA, 2009h). The Millennium Ecosystem 3 Assessment (MEA) defines these to include supporting, provisioning, re gulating and cultural 4 services (Hassan et al., 2005): 5

 Supporting services are necessary for the pr oduction of all other ecosystem services. 6 Some examples include biomass pr oduction, production of atmospheric O 2 , soil 7 formation and retention, nutri ent cycling, water cycling, a nd provisioning of habitat. 8 Biodiversity is a supporting serv ice that is increasingly reco gnized to sustain many of 9 the goods and services that humans enjoy from ecosystems. These provide a basis for 10 three higher-level categories of services. 11

 Provisioning services, such as products (Git ay et al., 2001) i.e., food (including game, 12 roots, seeds, nuts, and other fruit, spices, fodder), fiber (including wood, textiles), and 13 medicinal and cosmetic products (inc luding aromatic plants, pigments). 14

 Regulating services that are of paramount importance for human society such as (a) C 15 sequestration, (b) climate and water regula tion, (c) protection from natural hazards 16 such as floods, avalanches, or rock-fall, (d) water and ai r purification, an d (e) disease 17 and pest regulation. 18

 Cultural services that satisfy human spirit ual and aesthetic appreciation of ecosystems 19 and their components. 20

An important consideration in evaluating biologically advers e effects of PM and linkages 21 to ecosystem services is that many of the ME A categories overlap and any one pollutant may 22 impact multiple services. For example, depos ited PM may alter th e composition of soil23 associated microbial communities, which may affect supporting services such as nutrient 24 cycling. Changes in available soil nutrients coul d result in alterations to provisioning services 25 such as timber yield and regulating services su ch as climate regulation. If enough information is 26 available, these alterations can be quantified based upon economic approaches for estimating the 27 value of ecosystem services. Valuation may be important from a policy perspective because it 28 can be used to compare the benefits of alteri ng versus maintaining an ecosystem. Knowledge 29 about the relationships linking ambient concentra tions and ecosystem services can be used to 30 inform a policy judgment on a known or anti cipated adverse public welfare effect. 31 This review seeks to build upon and focus th is body of science us ing the concept of 32 ecosystem services to qualitatively evaluate linkages between biologically adverse effects and 33 particulate deposition. This approach is similar to that taken in the NOx/SOx REA in which the 34 relationship between air quality indicators, deposition of N and S, ecologically relevant 35
indicators and effects on sensit ive receptors are linked to cha nges in ecosystem structure and 36 services (US EPA, 2009h). This approach consider s the benefits received from the resources and 37Draft-Do Not Quote or Cite June 2010 5-16 processes that are supplied by ecosystems. Ecos ystem components (e.g. plants, soils, water, 1 wildlife) are impacted by PM air pollution, wh ich may alter the services provided by the 2 ecosystems in question. The goals of this policy assessment are to (1) iden tify ecological effects 3 associated with PM deposition that can be li nked to ecosystem services and (2) qualitatively 4 evaluate ecological endpoints when possible. Keeping these goals and guidelines in mind, 5 limited new data on PM effects on plants, soil and nutrient cycling, wildlife and water are 6
evaluated in the context of eco system services to qualitative ly evaluate linkages between 7 biologically adverse effects and particulate deposition for the purpos e of evaluating the adequacy 8
of the current standard. 9

5.3.2 Adequacy of the Current Standard 10 In considering the adequacy of the suite of secondary standards, staff addresses the 11 following overarching question: 12

Does available scientific information, as refl ected in the ISA support or call into question 13 the adequacy of the protection afforded by th e current suite of secondary PM standards for 14 vegetation and ecosystems from the effects of deposited particulate metals and organics? 15 To inform the answer to this overarching que stion, staff has posed specific questions to 16 aid in assessing the available scie ntific evidence as related to ecosy stem effects attributed to PM 17 deposition as presented in the ISA (US EPA, 2009a). 18

 To what extent has key scientific ev idence become availabl e to improve our 19 understanding of the nature and magnitude of ecosystem responses, the variability 20 associated with these responses, and the impact of PM on ecosystem services? 21 Key scientific evidence regarding PM effect s on plants, soil and nut rient cycling, wildlife 22
and water available since the last review is summ arized below to evaluate how this information 23 has improved our understanding of ecosystem responses to PM. 24

Plants 25
As primary producers, plants play a pivotal role in energy flow through ecosystems. 26 Ecosystem services derived from plants incl ude all of the categorie s (supporting, provisioning, 27 regulating, cultural) identified in the MEA (Hassan et al., 20 05). Vegetation supports other 28 ecosystem processes by cycling nu trients through food webs and serving as a source of organic 29
material for soil formation and enrichment. Tree s and plants provide food, wood, fiber, and fuel 30 for human consumption. Flora help to regulate climate by sequestering CO 2 , control flooding by 31 stabilizing soils and cycling water via uptake and evapotranspiration. Plants are significant in 32 aesthetic, spiritual and recreationa l aspects of human interactions. 33Draft-Do Not Quote or Cite June 2010 5-17 Particulate matter can adversely impact plants and ecosystem services provided by plants 1 by deposition to vegetative surfaces (US EPA, 2009a, section 9.4.3). Par ticulates deposited on 2
the surfaces of leaves and needle s can block light, altering the ra diation received by the plant. 3 PM deposition can obstruct stomata limiting gas exchange, damage leaf cuticles and increase 4 plant temperatures. This level of PM accumulati on is typically observed near sources of heavy 5 deposition such as smelters and mining opera tions (US EPA, 2009a, section 9.4.3). Plants 6 growing on roadsides exhibit impact damage from near-road PM deposition, having higher levels 7 of organics and heavy metals, and accumulate sa lt from road de-icing dur ing winter months (US 8 EPA, section 2009a, sections 9.4.3.1 and 9.4.5.7). 9 In addition to damage to plant surfaces, depos ited PM can be taken up by plants from soil 10 or foliage. The ability of vegetation to take up heavy metals and organics is dependent upon the 11 amount, solubility and chemical composition of the deposited PM. Uptake of PM by plants from 12 soils and vegetative surfaces can disrupt photosynthesis, alter pigments and mineral content, 13 reduce plant vigor, decrease frost hardiness and impair root developm ent. The ISA indicates that 14
there are little or no effects on foliar processes at ambient leve ls of PM (sections 9.4.3 and 9.4.7) 15 however, damage due to atmospheric pollution ca n occur near point-sources or under conditions 16 where plants are subjected to multiple stressors. 17 Though all heavy metals can be directly toxi c at sufficiently high concentrations, only 18 Cu, Ni, and Zn have been documented as being frequently toxic to pl ants (U.S. EPA, 2004), 19 while toxicity due to Cd, Co, and Pb has b een observed less frequently (Smith, 1990; US EPA 20 2009a, section 9.4.5.3). In general, plant growth is negatively correlated with trace metal and 21 heavy metal concentration in soils and plant tissue (Audet and Charest, 2007). Trace metals, 22 particularly heavy metals, can influence forest growth. Growth suppression of foliar microflora 23 has been shown to result from Fe, Al, and Zn. These three metals can al so inhibit fungal spore 24 formation, as can Cd, Cr, Mg, and Ni (see Sm ith, 1990). Metals cause stress and decreased 25 photosynthesis (Kucera et al., 2008 ) and disrupt numerous enzy mes and metabolic pathways 26 (Strydom et al., 2006). Excessive concentrations of metals result in phyto toxicity through: (i) 27 changes in the permeability of the cell membrane; (i i) reactions of sulfydryl (-SH) groups with 28 cations; (iii) affinity for reacting with phosphate groups and active groups of ADP or ATP; and 29 (iv) replacement of essentia l ions (Patra et al., 2004). 30 New information since the last review provides additional evidence of plant uptake of 31 organics (US EPA, 2009a, sect ion 9.4.6). An area of active study is the impact of PAHs on 32 provisioning ecosystem services due to the poten tial for human and other animal exposure via 33 food consumption (US EPA, 2009a, section 9.4.6 pa ge 9-190). The uptake of PAHs depends on 34 the plant species, site of de position, physical and chemical pr operties of the organic compound 35 and prevailing environmental conditions. It has b een established that most bioaccumulation of 36Draft-Do Not Quote or Cite June 2010 5-18 PAHs by plants occurs via leaf uptake, and to a lesser extent, thr ough roots. Differences 1 between species in uptake of PAHs confound a ttempts to quantify impacts to ecosystem 2 provisioning services. For example, zucchini ( Cucurbita pepo ) accumulated significantly more 3 PAHs than related plant species (Parrish et al., 2006). 4 Plants as ecosystem regulators can serve as passive monitors of pollution (US EPA, 5 2009a, section 9.4.2.3). Lichens and mosses are sensit ive to pollutants associated with PM and 6
have been used with limited success to show spatial and temporal pa tterns of atmospheric 7 deposition of metals (US EPA, 2009a, section 9.4.2.3). For example, the presence or absence of 8 a specific species of lichen can be used as a bioindicator of me tal or organics contamination. 9
PBDEs detected in moss and lichens in Anta rctica indicate long-ra nge transport of PM 10 components (Yogui and Sericano 2008). In the U. S. Blue Ridge Mountains, a study linked metal 11
concentrations in mosses to elevation and tr ee canopy species at some sites but not with 12
concentrations of metals in the O horizon of soil (Schilling, 2002). A limitation to employing 13 mosses and lichens to detect for the presence of air pollutants is th e difference in uptake 14
efficiencies of metals between species. The European Moss Biomonitoring Network has been 15 shown to be useful in Europe for estimating general trends in metal concentrations and 16
identification of some sources of trace contaminants, however , quantification of ecological 17 effects is not possible due to the variability of species responses (US EPA, 2009a, section 18 9.4.2.3). 19 A potentially important regulating ecosystem se rvice of plants is their capacity to 20 sequester contaminants (US EPA, 2009a, sect ion 9.4.5.3). Ongoing resear ch on the application 21 of plants to environmental remediation effo rts are yielding some success in removing heavy 22 metals and organics from contaminated sites (phyto remediation) with tolera nt plants such as the 23 willow tree ( Salix spp.) and members of the family Brassicaceae (US EPA, 2009a, section 24 9.4.5.3). Tree canopies can be used in urban locati ons to capture particul ates and improve air 25 quality (Freer-Smith et al., 2004). Plant foliag e is a sink for Hg and other metals and this 26 regulating ecosystem service may be impacted by atmospheric deposition of trace metals. 27 An ecological endpoint (phytochelatin concentrat ion) associated with presence of metals 28
in the environment has been correlated with the ecological effect of tree mortality (Grantz et al., 29 2003). Metal stress may be contributi ng to tree injury and forest de cline in the Northeastern U.S. 30 where red spruce populations are d eclining with increasi ng elevation. Quantitative assessment of 31 PM damage to forests potentially could be conducted by overlaying PM sampling data and 32 elevated phytochelatin levels. However, limite d data on phytochelatin levels in other species 33 currently hinders use of this pep tide as a general biomarker for PM. 34 The presence of PM in the atmosphere affect s ambient radiation as discussed in the ISA 35 which can impact the amount of sunlight rece ived by plants (US EPA, 2009a, section 9.4.4). 36Draft-Do Not Quote or Cite June 2010 5-19 Atmospheric PM can change the radiation reac hing leaf surfaces th rough attenuation and by 1 converting direct radiation to diffu se radiation. Diffuse radiation is more uniformly distributed in 2 a tree canopy, allowing radiation to reach lower leaves. The net effect of PM on photosynthesis 3 depends on the reduction of photosynthetically ac tive radiation (PAR) a nd the increase in the 4
diffuse fraction of PAR. Decreas es in crop yields (provisioning ecosystem service) have been 5 attributed to regional scale ai r pollution, however, global models suggest that the diffuse light 6 fraction of PAR can increase grow th (US EPA, 2009a, section 9.4.4). 7
Soil and Nutrient Cycling 8
Many of the major indirect pl ant responses to PM depositio n are chiefly soil-mediated 9 and depend on the chemical composition of i ndividual components of deposited PM. Major 10 ecosystem services impacted by PM deposition to soils include support services such as nutrient 11 cycling, products such as crops and regulating flooding and water quality. Upon entering the soil 12 environment, PM pollutants can alter ecological proce sses of energy flow and nutrient cycling, 13 inhibit nutrient uptake to plants, change microbial community stru cture and, affect biodiversity. 14 Accumulation of heavy metals in soils depends on factors such as local soil characteristics, 15 geologic origin of parent soils, and metal bioavailab ility. It can be difficult to assess the extent 16 to which observed heavy metal concentrations in soil are of anthropogenic origin (US EPA, 17 2009a, section 9.4.5.1). Trace element concentrations are higher in some soils that are remote 18 from air pollution sources due to pare nt material and local geomorphology. 19 Heavy metals such as Zn, Cu, and Cd a nd some pesticides can interfere with 20 microorganisms that are responsible for decompos ition of soil litter, an important regulating 21 ecosystem service that serves as a source of soil nutrients (US EPA, 2009a, sections 9.4.5.1 and 22 9.4.5.2). Surface litter decomposition is reduced in soils having high metal concentrations. Soil 23 communities have associated bacteria, fungi, and i nvertebrates that are esse ntial to soil nutrient 24 cycling processes. Changes to the relative species abundance and community composition can 25 be quantified to measure impacts of deposited PM to soil biota. A mutualistic relationship exists 26 in the rhizophere (plant root zone) between plant roots, f ungi, and microbes. Fungi in 27 association with plant roots form mycorrhizae that are essential for nutrient uptake by plants. 28 The role of mychorrizal fungi in plant uptake of metals from so ils and effects of deposited PM 29
on soil microbes is discussed in section 9.4.5.2 of the ISA. 30

Wildlife 31
Animals play a significant role in ecosyste m function including nutrient cycling and crop 32 production (supporting ecosystem se rvice), and as a source of food (provisioning ecosystem 33 service). Cultural ecosystem services provide d by wildlife include bird and animal watching, 34 recreational hunting and fishing. Impacts on these services are dependent upon the 35Draft-Do Not Quote or Cite June 2010 5-20 bioavailability of deposited metals and organi cs and their respective toxicities to ecosystem 1 receptors. Pathways of PM exposure to fauna include ingestion, absorption and trophic transfer. 2 Bioindicator species (known as se ntinel organisms) can provide evidence of contamination due 3 to atmospheric pollutants. Use of sentinel spec ies can be of particular value because chemical 4 constituents of deposited PM are difficult to ch aracterize and have vary ing bioavailability (US 5 EPA, 2009a, section 9.4.5.5). Snails readily bioa ccumulate contaminants such as PAHs and 6 trace metals. These organisms have been deploy ed as biomonitors for urban pollution and have 7 quantifiable biomarkers of exposure including growth inhibition, impairment of reproduction, 8 peroxidomal proliferation and induction of metal detoxifying proteins (metallothioneins) 9 (Gomet-de Vaufleury, 2002; Regoli, 2006). Earthw orms have also been used as sensitive 10
indicators of soil metal contamination. 11 Evidence of deposited PM effects on animals is limited (US EPA, 2009a, section 9.4.5.5). 12 Trophic transfer of pollutants of atmospheric orig in has been demonstrated in limited studies. 13 PM may also be transferred between aquatic a nd terrestrial compartments. There is limited 14 evidence for biomagnifications of heavy metals up the food chain except for Hg which is well 15 known to move readily through environmental compartments (US EPA, 2009a section 9.4.5.6). 16
Bioconcentration of POPs and PBDEs in the Arc tic and deep-water ocea nic food webs indicates 17 the global transport of partic le-associated organics (US EP A, 2009a, section 9.4.6). Salmon 18 migrations are contributing to metal accumula tion in inland aquatic systems, potentially 19 impacting the provisioning and cultural ecosyste m service of fishing (US EPA, 2009a, section 20 9.4.6). Stable isotope analysis can be applied to establish linkages between PM exposure and 21 impacts to food webs, however, the use of this evaluation tool is limited for this ecological 22 endpoint due to the complexity of most troph ic interactions (US EP A 2009a, section 9.4.5.6). 23 Foraging cattle have been used to assess atmos pheric deposition and subs equent bioaccumulation 24 of Hg and trace metals and their impacts on provisioning services (US EPA, 2009a, section 25 9.4.2.3). 26

Water 27
New limited information on impacts of deposite d PM on receiving water bodies indicate 28 that the ecosystem services of primary production , provision of fresh water, regulation of climate 29 and floods, recreational fishing and water purifi cation are adversely impacted by atmospheric 30 inputs of metals and organics (US EPA, 2009a , sections 9.4.2.3 and 9.4.5.4). Deposition of PM 31 to surfaces in urban settings increases the me tal and organic component of storm water runoff 32 (US EPA, 2009a, sections 9.4.2.3). This atmospheri cally-associated pollutant burden can then be 33 toxic to aquatic biota. 34Draft-Do Not Quote or Cite June 2010 5-21 Atmospheric deposition can be the primary s ource of some organics and metals to 1
watersheds. The contribution of atmospherically deposited PAHs to aquatic food webs was 2 demonstrated in high elevation mountain lakes with no other anthropogenic contaminant sources 3 (US EPA, 2009a, section 9.4.6). Metals associ ated with PM deposition limit phytoplankton 4 growth, impacting aquatic trophic structure. Long-range atmosphe ric transport of 47 pesticides 5 and degradation products to the snowpack in seven national parks in the Western U.S. was 6 recently quantified indicating PM-associated cont aminant inputs to receiving waters during 7 spring snowmelt (Hageman et al., 2006). 8

 What new techniques are available to improve our understanding of ecosystem effects 9 associated with metal and organic components of PM? 10 The recently completed Western Airborne Contaminants Assessment Project (WACAP) 11 is the most comprehensive database on contaminant transport and PM depositional effects on 12 sensitive ecosystems in the U.S. In this project , the transport, fate, a nd ecological impacts of 13 anthropogenic contaminants from atmospheric s ources were assessed from 2002 to 2007 in seven 14 ecosystem components (air, snow, water, sedime nt, lichen, conifer needles and fish) in eight 15 core national parks (Landers et al., 2008). The goals of the study were to identify where the 16 pollutants were accumulating, identify ecologi cal indicators for t hose pollutants causing 17 ecological harm, and to determine the source of the air masses most likely to have transported 18 the contaminants to the parks (US EPA, 2009a, s ection 9.4.6). Collected data were analyzed to 19 identify probable local, regional and/or global sources of depo sited PM components and their 20 concurrent effects on ecological receptors. Th e study concluded that bioaccumulation of semi21 volatile organic compounds (VOCs) was observed throughout park ecosystems (Landers et al., 22 2008). Findings from this study included the obs ervation of an elevati onal gradient in PM 23 deposition with greater accumulation at higher altitude areas of the parks. Furthermore, specific 24 ecological indicators were iden tified in the WACAP that can be useful in assessing 25 contamination on larger spatial scales. For exampl e, quantification of con centrations of selected 26 pesticides in second-year coni fer needles served as a method for regional-scale comparison of 27 pollutant distribution (L anders et al., 2008). 28 In the WACAP study, bioaccumulation and biom agnification of airborne contaminants 29 were demonstrated on a regional scale in remo te ecosystems in the Western United States. 30 Contaminants were shown to accumulate geogr aphically based on proximity to individual 31 sources or source areas, primarily agriculture and industry (Lande rs et al., 2008). This finding 32 was counter to the original work ing hypothesis that most of th e contaminants found in western 33 parks would originate from Easter n Europe and Asia (Landers et al., 2008 p 6-8). The WACAP 34 study represents an experimental design in whic h ecological effects coul d be correlated to 35 ambient pollutant levels on a regional scale. Although this assessment focuses on chemical 36Draft-Do Not Quote or Cite June 2010 5-22 species that are components of PM, it does not sp ecifically assess the eff ects of particulates 1 versus gas-phase forms; therefore, in most cases it is difficult to a pply the results to this 2 assessment based on particulate concentration and size fraction (US EPA, 2009a, section 9.4.6). 3 There is a need for ecological modeling of PM components in different environmental 4 compartments to further elucidate links between PM and ecological indicators. 5 Europe and other countries are us ing the critical load approach to assess pollutant effects 6 at the level of the ecosystem. Th is type of assessment requires si te-specific data and information 7 on individual species responses to PM. In re spect to trace metals and organics, there are 8 insufficient data for the vast majority of U.S. ec osystems to calculate critical loads, however, a 9 methodology is being presented in the NOx/SOx Secondary REA (US EPA 2009h) to calculate 10 atmospheric concentrations from deposition that may be applicable to other environmental 11
contaminants. 12

 Is there currently available information on am bient levels of PM that cause adverse 13 effects on ecosys tem components? 14 As reviewed above, there is c onsiderable data on impacts of PM on ecological receptors, 15
but few studies that link ambient PM levels to observ ed effect. This is due, in part, to the nature, 16 deposition, transport and fate of PM in ecosystems. PM is not a single pollutant, but a 17 heterogeneous mixture of particles differing in size, origin and chemical composition (US EPA, 18 2009a, section 9.4.1). The heterogeneity of PM exis ts not only within in dividual particles or 19 samples from individual sites, but to even a greate r extent, between samples from different sites. 20 Since vegetation and other ecosystem components are affected more by particulate chemistry 21 than size fraction, exposure to a given mass concen tration of airborne PM may lead to widely 22 differing plant or ecosystem responses, depending on the particular mix of deposited particles. 23 Many of the PM components bioaccumulat e over time in organisms or plants, making 24
correlations to ambient levels of PM diffi cult. For example, in the WACAP study, SOC 25 accumulation in vegetation and air showed differe nt patterns, possibly because each medium 26 absorbs different types of SOCs with vary ing efficiencies (La nders et al., 2008). 27 Bioindicator organisms demonstrated biologi cal effects including growth inhibition, 28 metallothionein induction and repr oductive impairment when exposed to complex mixtures of 29 ambient air pollutants (US EPA 2009a, section 9.4.5.5). Other studie s quantify uptak e of metals 30 and organics by plants or animals. However, due to the difficulty in correlating individual PM 31 components to a specific physiolo gical response, these studies ar e limited. Furthermore, there 32 may be differences in uptake between species such as differing responses to metal uptake 33 observed in mosses and lichens (US EPA 2009a, section 9.4.2.3). PM may also biomagnify 34 across trophic levels confounding efforts to link atmospheric concentrations to physiological 35 endpoints (US EPA, 2009a, section 9.4.5.6). 36Draft-Do Not Quote or Cite June 2010 5-23 Evidence of PM effects that are linked to a specific ecological endpoint can be observed 1
when ambient levels are exceeded. Most direct ecosystem effects associated with particulate 2 pollution occur in severely polluted areas near in dustrial point sources (quarries, cement kilns, 3 metal smelting) (US EPA, 2009a, sections 9.4.3 and 9.4.5.7). Extensive research on biota near 4 point sources provide some of th e best evidence of ecosystem f unction impacts and demonstrates 5 that deposited PM has the potential to alte r species composition over long time scales. 6 Ecological field studies c onducted in proximity to Cu-Ni smelte r in Harjavalta, Finland indicated 7 ecological structure and community composition are altered in response to PM and these effects 8 decrease with increasing distance from the point source (US EPA 2009a , section 9.4.5.7). The 9 ISA indicates at 4 km distance, species com position of vegetation, insects, birds, and soil 10 microbiota changed, and within 1 km only the mo st resistant organisms were surviving (US 11 EPA, 2009a, section 9.4.5.7). Heavy metal concentr ations were quantified in understory plant 12 species growing at varying distance from the Ha rjavalta smelter (Salem aa et al., 2004). Heavy 13 metal concentrations were highest in bryophyt es, followed by lichens and were lowest in 14 vascular plants. At the Harjavalta smelter ther e are clear links between PM deposition levels, 15 ecological endpoints and compromised ecosystem st ructure. However, these conditions are not 16
reflective of ambient concentrations of PM in the majority of US ecosystems (US EPA, 2009a, 17 section 9.4.7). 18

5.3.3 Staff Conclusions 19

 A number of significant envir onmental effects that either have already occurred or are 20 currently occurring are linked to deposition of chemical constituents found in ambient 21 PM. 22

 Ecosystem services can be adversely impact ed by PM in the environment, including 23 supporting, provisioning, regula ting and cultural services. 24

 The lack of sufficient information to relate specific ambient concentrations of 25 particulate metals and organics to a degr ee of impairment of a specific ecological 26 endpoint hinders our ability to identify a ra nge of appropriate indi cators, levels, forms 27 and averaging times of a dist inct secondary standard to protect against associated 28 effects. 29

 Data from regionally-based ecological studies can be used to establish probable local, 30 regional and/or global sources of depos ited PM components and their concurrent 31 effects on ecological receptors. 32 Taking into consideration the re sponses to specific questions regarding the adequacy of 33 the current secondary PM standards for ecologica l effects, we revisit the overarching question: 34
“does available scientific inform ation, as reflected in the ISA, support or call into question the 35 adequacy of the protection for ecosystems afforded by the current suite of secondary PM 36
standards?” Staff concl udes that the available information is insufficient to assess the adequacy 37Draft-Do Not Quote or Cite June 2010 5-24 of the protection for ecosystems afforded by the current suite of PM secondary standards. 1 Ecosystem effects linked to PM are difficult to determine because the changes may not be 2 observed until pollutant deposition has occurred for many decades. Because the high levels 3 necessary to cause injury occur only near a fe w limited point sources and/or on a very local 4 scale, protection against these effects alone ma y not provide sufficient basis for considering a 5 separate secondary NAAQS based on the ecological effects of particulate metals and organics. 6 Data on ecological responses cl early linked with atmospheric PM is not abundant enough to 7 perform a quantitative analysis although th e WACAP study may represent an opportunity for 8 quantification at a regional scale. At this time, we conclude that available evidence is not 9 sufficient for establishing a distinct national st andard for ambient PM based on ecosystem effects 10 of particulates not addressed in the NOx/SOx secondary review (e.g. metals, organics). 11 Staff considered the appropriatene ss of continuing to use the PM 2.5 and PM 10 size 12
fractions as the indicators fo r protection of ecological effect s of PM. Though the chemical 13
constitution of individual particles can be strongly correlated with size, the relationship between 14 particle size and particle compos ition can also be quite complex, making it difficult in most cases 15 to use particle size as a surrogate for chemistry. At this time it remains to be determined as to 16 what extent PM secondary standards focused on a given size fraction woul d result in reductions 17 of the ecologically relevant constituents of PM fo r any given area. Nonetheless, in the absence of 18 information that provides a basis for specific standards in terms of particle composition, 19 observations continue to support retaining an appropriate degree of control on both fine and 20 coarse particles to help address effects to eco systems and ecosystem components associated with 21
PM. 22

5.3.4 Key Uncertainties and Areas for Futu re Research and Data Collection 23 The above discussions identify linkages between ecological effects of deposited PM and 24 potential impacts to ecosystem services. Un fortunately, our ability to relate ambient 25 concentrations of PM to ecosystem response is hampered by a number of significant data gaps 26 and uncertainties. These limitations include the presence of multiple ecological stressors 27 confounding attempts to link specific ecosystem responses to PM deposition. These stressors 28 can be anthropogenic (e.g. habita t destruction, eutrophicat ion, other pollutants) or natural (e.g. 29 drought, fire, disease). Deposited PM interacts with other stressors to affect ecosystem patterns 30 and processes. Furthermore, the environmental effects of deposited PM are decoupled in space 31 and time from the point of emission confounding efforts to identify ecological perturbations 32 attributed to PM deposition. 33 A second source of uncertainty lies in predic ting the amount of PM deposited to sensitive 34 receptors from measured concentrations of PM in the ambient air. This makes it difficult to 35Draft-Do Not Quote or Cite June 2010 5-25 relate a given air concentration to a receptor response, an important factor in being able to set a 1 national ambient air quality standard. A multitude of factors such as the mode of deposition 2 (wet, dry and occult), wind speed, surface r oughness or stickiness, elevation, particle 3 characteristics (e.g. size, shape, chemical co mposition), and relative humidity exert varying 4 degrees of influence on the depos ition velocities for different PM components in any point in 5 time. Composition of ambient PM varies in time and space and th e particulate mixture may have 6 synergistic, antagonistic or a dditive effects on ecologi cal receptors depending upon the chemical 7 species present. Furthermore, presence of co-occ urring pollutants make it difficult to attribute 8 observed effects to ecological receptors to PM alone or one component of deposited PM. 9 Third, each ecosystem has developed within a context framed by the topography, 10 underlying bedrock, soils, climate, meteorology, hydrologic regime, natural and land use history, 11 and species composition that make it unique from all others. Sensitivity of ecosystem response 12 is highly variable in space and tim e. Because of this variety and lack of sufficient baseline data 13 on each of these features for most ecosystems, it is currently not possible to extrapolate with 14 confidence any effect from one ecosystem to anothe r. Further research is needed to decrease the 15
uncertainties associated with ambient PM e ffects on ecosystems and ecosystem components. 16

5.4 MATERIALS 17

5.4.1 Scope 18

Welfare effects on materials associated with deposition of PM include both physical 19 damage (materials damage effects) and impaired aesthetic qualities (soili ng effects). Because the 20 effects of PM are exacerbated by the presence of acidic gases and can be a dditive or synergistic 21 due to the complex mixture of pollutants in the air and surface characteristic s of the material, this 22 discussion will also include those particles and ga ses that are associated with the presence of 23 ambient NOx and SOx, as well as NH 3 and NH X for completeness. Building upon the 24 information presented in the last Staff Pape r (US EPA, 2005), and including the limited new 25 information presented in Chapter 9 of the PM ISA (US EPA, 2009a) and Annex E. Effects of 26 NOy, NHx, and SOx on Structures and Material s of the Integrated Science Assessment for 27 Oxides of Nitrogen and Sulfur-Ecological Criteria (NOx/SOx ISA) (US EPA, 2008c) the 28 following sections consider the po licy-relevant aspects of physical damage and aesthetic soiling 29 effects of PM on materials including metal and stone. 30
The ISA concludes that evidence is sufficien t to support a causal relationship between 31 PM and effects on materials (US EPA, 2009a, s ections 2.5.4 and 9.5.4). The deposition of PM 32 can physically affect materials, adding to the effects of natural weat hering processes, by 33 potentially promoting or accelerating the corr osion of metals, by degrading paints and by 34 deteriorating building materials such as stone, concrete and marble (US EPA, 2009a, section 35Draft-Do Not Quote or Cite June 2010 5-26 9.5). Particles contribute to these physical eff ects because of their electrolytic, hygroscopic and 1 acidic properties, and thei r ability to sorb corrosive gases (principally SO 2 ). In addition, the 2 deposition of ambient PM can reduce the aest hetic appeal of buildings and objects through 3 soiling. Particles consisting primarily of carbonaceous compounds cause soiling of commonly 4 used building materials a nd culturally important items such as statues and works of art. Soiling 5 is the deposition of particles on surfaces by im pingement, and the accumulation of particles on 6 the surface of an exposed material results in degradation of its appearance (US EPA 2009a, 7 section 9.5). Soiling can be remedied by cleaning or washing, and depending on the soiled 8 material, repainting. 9

5.4.2 Adequacy of the Current Standard 10 In considering the adequacy of the suite of secondary standards, staff addresses the 11 following overarching question: 12

Does available scientific information, as refl ected in the ISA support or call into question 13 the adequacy of the protection for materials a fforded by the current suite of secondary PM 14 standards? 15 To inform the answer to this overarching quest ion, staff has posed a specific question to 16 aid in assessing the available scientific evid ence as related to mate rials damage and soiling 17 attributed to PM deposition as pr esented in the ISA (US EPA, 2009a). 18

 What new evidence is available to improve our understanding of effects of PM on 19 materials and linking ambient concentrations to materials damage? 20 The majority of available new studies on mate rials effects of PM are from outside the 21 U.S., however, they provide limited new data fo r consideration of the secondary standard. 22 Metal and stone are susceptible to damage by ambient PM. Considerable research has 23 been conducted on the effects of air pollutants on metal surfaces due to the economic importance 24 of these materials, especially steel, zinc, alum inum, and copper. Chapter 9 of the PM ISA and 25
Annex E of the NOx/SOx ISA summarize the results of a number of studi es on the corrosion of 26 metals (US EPA, 2009a; US EPA, 2008c). Moisture is the single greatest factor promoting metal 27 corrosion, however, deposited PM can have additive, antagonistic or syne rgistic effects. In 28 general, SO 2 is more corrosive than NOx although mixtures of NOx, SO 2 and other particulate 29
matter corrode some metals at a faster rate th an either pollutant al one (US EPA, 2008c, Annex 30 E.5.2). Information from both the PM ISA and NOx /SOx ISA suggest that the extent of damage 31
to metals due to ambient PM is variable a nd dependent upon the type of metal, prevailing 32 environmental conditions, rate of natural weathering and presence or absence of other pollutants. 33
The PM ISA and NOx/SOx ISA summarize the re sults of a number of studies on PM and 34 stone surfaces. While it is clear from the available information that gaseous air pollutants, in 35Draft-Do Not Quote or Cite June 2010 5-27 particular SO 2 , will promote the deterioration of some types of stones under specific conditions, 1 carbonaceous particles (non-carbonat e carbon) and particles containi ng metal oxides may help to 2 promote the decay process. Studies on metal an d stone summarized in the ISA do not show an 3 association between particle size, chemical composition and frequency of repair. 4
A limited number of new studies available on ma terials damage effects of PM since the 5 last review consider the relationship between pollutants and biodeterior ation of structures 6
associated with microbial communities that colonize monuments and buildings (US EPA 2009a, 7 section 9.5). Presence of air pollutants may syne rgistically enhance mi crobial deterioration 8 processes. The role of heterotr ophic bacteria, fungi and cyanobact eria in biodeteri oration varied 9 by local meterological conditions and pollutant components. In a comparative study of 10 biodeterioration processes on monu ments in Latin America, limest one deterioration at the Mayan 11 site of Uxmal was enhanced by biosolubilizatio n by metabolic acids from bacteria and fungi 12
while destruction of the Cathedra l of La Plata was attributed pr imarily to atmospheric pollutants 13 (Herrera and Videla, 2004). 14 PM deposition onto surfaces such as metal, gl ass, stone and paint can lead to soiling. 15 Soiling results when PM accumulates on an objec t and alters the optical characteristics 16 (appearance). The reflectivity of a surface may be changed or presence of particulates may alter 17 light transmission. These effects can impact the aesthetic value of a structure or result in 18 reversible or irreversible damage to statues, ar twork and architecturally or culturally significant 19 buildings. Due to soiling of building surfaces by PM, the frequency and duration of cleaning 20 may be increased. Soiling affects the aesthetic app eal of painted surfaces. In addition to natural 21 factors, exposure to PM may give painted surfaces a di rty appearance. Pigments in works of art 22 can be degraded or discolored by atmospheric pollutants, especially sulfates (US EPA, 2008c, 23 Annex E-15). 24
Formation of black crusts due to carb onaceous compounds and buildup of microbial 25
biofilms results in discoloration of surfaces. Bl ack crust includes a carbonate component derived 26 from building material and organic carbon (OC) and elemental carbon (EC). In limited new 27 studies quantifying the OC and EC contribution to soiling by black crust, OC predominated over 28 EC at almost all locations (Bonazza et al., 2005). Limited new studies suggest that traffic is the 29 major source of carbon associated with black crust formation (Putaud et al., 2004) and that 30 soiling of structures in Oxford, UK show ed a relationship with traffic and NO 2 concentrations 31 (Viles and Gorbushina, 2003). These findings atte mpt to link atmospheric concentrations of PM 32 to observed damage. However, no data on rates of damage are available and all studies were 33
conducted outside of the U.S. 34Draft-Do Not Quote or Cite June 2010 5-28 5.4.3 Staff Conclusions 1 Available evidence in regards to material s damage and soiling supports the following 2
observations: 3

 Materials damage and soiling that occur through natural weathe ring processes are 4 enhanced by exposure to atmosphe ric pollutants, most notably SO 2 and particulate 5 sulfates. 6

 While ambient particles play a role in the co rrosion of metals and in the weathering of 7 materials, no quantitative relationships be tween ambient particle concentrations and 8 rates of damage have been established. 9

 While soiling associated with fine and cour se particles can result in increased cleaning 10 frequency and repainting of surfaces, no quant itative relationships between particle 11 characteristics and the frequency of cleani ng or repainting have been established. 12

 Limited new data on the role of microbial colonizers in biodeteri oration processes and 13 contributions of black crust to soiling are not sufficient for quantitative analysis. 14

 While several studies in the PM ISA and NOx/SOx ISA suggest that particles can 15 promote corrosion of metals there remains insufficient evidence to relate corrosive 16 effects to specific particulate levels or to establish a qua ntitative relationship between 17 ambient PM and metal degradation. With respect to damage to calcareous stone, 18 numerous studies suggest that wet or dry deposition of pa rticles and dry deposition of 19 gypsum particles can enhance na tural weathering processes. 20

Revisiting the overarching policy question as to whether the available scientific evidence 21 supports or calls into question the adequacy of the protection for materials afforded by the 22 current suite of secondary PM standards, we conc lude that no new evidence in this review calls 23 into question the adequacy of th e protection for materials afford ed by the current standard. PM 24 effects on materials can play no quantitative role in considering whethe r any revisions of the 25 secondary PM NAAQS are appropriate at this time . Nonetheless, in the absence of information 26 that provides a basis for establis hing a different level of control, observations continue to support 27 retaining an appropriate degree of control on both fine and coar se particles to help address 28 materials damage and soiling associated with PM. 29

5.4.4 Key Uncertainties and Areas for Futu re Research and Data Collection 30 Quantitative relationships are needed between particle size, con centration, chemical 31 concentrations and frequency of repainting and repair. Deposition rates of airborne PM to 32 surfaces would provide an indication of rate and degree of damage to surfaces. There is 33 considerable uncertainty with regard to inter action of co-pollutants in regards to materials 34 damage and soiling processes. 35Draft-Do Not Quote or Cite June 2010 5-29 5.5 REFERENCES 1
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Parrish ZD; White JC; Isleyen M; Gent MPN; Iannucci -Berger W; Eitzer BD; Kelsey JW; Mattina MI. (2006). 17 Accumulation of weathered polycyclic aromatic hydrocarbons (PAHs) by plant and earthworm species. 18 Chemosphere, 64: 609-618. 19

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Putaud J-P; Raes F; Van Dengenen R; Bruggemann E; Facchi ni M-C; Decesari S; Fuzzi S; Gehrig R; Huglin C; Laj 23 P; Lorbeer G; Maenhaut W; Mihalopoulos N; Muller K; Querol X; Rodriguez S; Schneider J; Spindler G; 24 ten Brink H; Torseth K; Wiedensohler A. (2004) . A European aerosol phenomenology--2: chemical 25 characteristics of particulate matter at kerbside, urban, rural and background sites in Europe. Atmos 26 Environ, 38: 2579-2595. 27

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# APPENDICESThis page left intentionally blank.

### Appendix 2A

All U.S. Northeast Southeast Industrial Midwest Upper Midwest Southwest Northwest Southern California Outlying

areas

526 87 150 134 44 21 63 16 12 182,075 42,841 40,904 38,646 7,361 9,311 18,446 22,610 2,099

annual
μ g/m 3 24-hou r
μ g/m 3 Statistic

# counties 62 9 6 15 0 4 19 9 1 population 47,896 5,639 5,157 8,551 0 1,040 9,847 17,721 83 % # counties 12% 10% 4% 11% 0% 19% 30% 56% 8% % population 26% 13% 13% 22% 0% 11% 53% 78% 4%

annual
μ g/m 3 24-hou r
μ g/m 3 Statistic

# counties 151 19 45 53 0 4 20 10 1 population 77,390 10,202 13,678 22,128 0 1,040 9,866 20,535 83 % # counties 29% 22% 30% 40% 0% 19% 32% 63% 8% % population 43% 24% 33% 57% 0% 11% 53% 91% 4%

# counties 211 40 49 72 0 4 34 11 2 population 104,539 26,228 14,063 28,417 0 1,040 14,266 20,553 114 % # counties 40% 46% 33% 54% 0% 19% 54% 69% 17% % population 57% 61% 34% 74% 0% 11% 77% 91% 5%

# counties 239 36 79 90 0 4 20 10 1 population 102,274 21,725 18,913 30,255 0 1,040 9,866 20,535 83 % # counties 45% 41% 53% 67% 0% 19% 32% 63% 8% % population 56% 51% 46% 78% 0% 11% 53% 91% 4%

# counties 270 46 79 95 0 4 34 11 2 population 114,610 27,991 18,913 31,876 0 1,040 14,266 20,553 114 % # counties 51% 53% 53% 71% 0% 19% 54% 69% 17% % population 63% 65% 46% 82% 0% 11% 77% 91% 5%

# counties 343 53 115 119 5 5 34 11 2 population 132,785 30,053 26,400 36,179 1,250 4,112 14,266 20,553 114 % # counties 65% 61% 77% 89% 11% 24% 54% 69% 17% % population 73% 70% 65% 94% 17% 44% 77% 91% 5%

# counties 393 71 116 130 11 7 44 12 3 population 147,943 39,345 26,547 38,494 2,164 4,317 15,739 21,306 173 % # counties 75% 82% 77% 97% 25% 33% 70% 75% 25% % population 81% 92% 65% 100% 29% 46% 85% 94% 8%

# counties 391 62 133 128 14 7 34 12 2 population 146,671 35,932 29,392 38,335 2,611 4,856 14,266 21,306 114 % # counties 74% 71% 89% 96% 32% 33% 54% 75% 17% % population 81% 84% 72% 99% 35% 52% 77% 94% 5%

# counties 417 71 133 130 17 8 44 12 3 population 151,975 39,345 29,392 38,494 2,782 4,887 15,739 21,306 173 % # counties 79% 82% 89% 97% 39% 38% 70% 75% 25% % population 83% 92% 72% 100% 38% 52% 85% 94% 8% Numbers of counties, populations, and percentages of total Current levels

Alternative levels Numbers of counties, populations, and percentages of total

15 35

11 25 12 35

30

11 30 12 Region >

Total # of counties > Total population (x 1,000)> Table 2A-1. Predicted Percent of Counties with Monitors (and percent of Population in counties with monitors) Not Likely to Meet Alternative Annual and 24-hour PM 2.5 Standards

10 25 10 30 13 30 13 35

Draft-Do Not Quote or Cite 2A-1 June 2010This page left intentionally blank.Appendix 3A

All U.S. Northeast Southeast Industrial Midwest Upper Midwest Southwest Northwes
t Californi

a Outlying

areas

318 40 60 57 35 24 79 18 8 122,582 15,753 27,009 23,646 5,143 11,037 16,188 22,695 1,525

μg/m 3 Statistic
# counties 45 0 3 1 1 14 15 11 2 population 32,169 0 4,159 348 28 7,675 2,075 17,724 320 % # counties 14% 0% 5% 2% 3% 58% 19% 61% 25% % population 26% 0% 15% 1% 1% 70% 13% 78% 21%

μg/m 3 Statistic # counties 38 0 3 3 3 12 8 10 1 population 22,450 0 4,159 1,789 710 6,106 1,366 8,220 260 % # counties 12% 0% 5% 5% 9% 50% 10% 56% 13% % population 18% 0% 15% 8% 14% 55% 8% 36% 17%

# counties 41 0 3 3 4 12 9 11 1 population 22,736 0 4,159 1,789 734 6,106 1,381 8,467 260 % # counties 13% 0% 5% 5% 11% 50% 11% 61% 13% % population 19% 0% 15% 8% 14% 55% 9% 37% 17%

# counties 48 0 4 4 5 12 11 12 2 population 25,914 0 4,176 1,838 781 6,106 1,499 11,313 360 % # counties 15% 0% 7% 7% 14% 50% 14% 67% 25% % population 21% 0% 15% 8% 15% 55% 9% 50% 24%

# counties 60 1 6 4 6 12 18 13 2 population 37,835 74 4,441 1,838 885 6,106 3,458 20,832 360 % # counties 19% 3% 10% 7% 17% 50% 23% 72% 25% % population 31% 0% 16% 8% 17% 55% 21% 92% 24%

# counties 75 1 7 7 8 15 22 13 4 population 47,280 74 4,462 9,094 986 7,745 3,798 20,832 450 % # counties 24% 3% 12% 12% 23% 63% 28% 72% 50% % population 39% 0% 17% 38% 19% 70% 23% 92% 29%

# counties 100 4 8 12 9 15 35 14 5 population 54,170 666 4,776 12,527 1,003 7,745 5,538 21,585 490 % # counties 31% 10% 13% 21% 26% 63% 44% 78% 63% % population 44% 4% 18% 53% 20% 70% 34% 95% 32% 87 Alternative 24-hour level (3-year average 98th percentile)

65 75

70 85

80 Numbers of counties, populations, and percentages of total Table 3A-1. Predicted Percent of Counties with Monitors (and percent of Population in counties with monitors) Not Likely to Meet Alternative 24-hour PM 10

Standards

Current 3-Year Expected Exceedance Equivalent Design Value
Numbers of counties, populations, and percentages of total

150 Total # of counties > Total population > Region >

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## Chapter 4 Appendices

Appendix 4A : Information Regarding the 1-Hour PM 2.5 

### Mass Indicator

Appendix 4B : Simplified Approaches to Calcu late Hourly PM Light Extinction Values from Hourly PM 2.5 

### Mass and Relative Humidity Data plus 24-hour Mean PM Composition Data
Appendix 4C : Assessment of the PM Com ponents Responsible for the Largest Hourly PM Light Extinction and PM 2.5 

### Mass Hours Selected as Maximum Daily and using All Hours for 14 Urban AreasThis page left intentionally blank.Draft-Do Not Quote or Cite June 2010 4A-1 

## Appendix 4A 1

2 

## Information Regarding the 1-hour PM 2.5 

## Mass Indicator 3 4 This Appendix presents inform ation on 2005-2007 levels of 1-hour PM 2.5 mass 5 concentrations in the 14 urban st udy areas and on the “what if” PM 10 light extinction conditions 6 that would exist if the study areas met each of 10 alternative secondary PM NAAQS scenarios 7 based on a 1-hour PM 2.5 mass indicator. With respect to th e latter subject, this Appendix is 8 therefore similar to Chapter 4 of the Particul ate Matter Urban-Focused Visibility Assessment 9 (UFVA), which presented similar information for 18 secondary PM NAAQS scenarios based on 10 PM 10 light extinction as the indicator, for the current annual and 24-hour PM 2.5 NAAQS, and for 11 a scenario with an annual NAAQS of 12 μg/m 3 and a 24-hour NAAQS of 25 μg/m 3

. 12 13 1.0 Indicator and Monitoring Method 14 15 As in Chapter 4 of the UFVA, this Appendix excludes from all NAAQS scenarios and 16 results all non-daylight hours and all daylight hours with re lative humidity greater than 90 17 percent. This applies to both the definition of 10 secondary NAAQS scenarios, and to graphics 18 and tables that characterize ambient conditions . While ambient humidity should not affect 19 conventional measurement approaches for 1-hour PM 2.5 mass, the issue of co-occurrence of high 20 humidity levels with light exti nction due to natural conditions would still apply. See section 21 3.3.5 of the UFVA. The assumed hours of daylight are the same as those used in the UFVA, as 22 shown in Table 3-5 of the UFVA. 23 24 All values for 1-hour PM 2.5 mass concentration in this appendix come from the 25 continuous instruments at the 14 urban study sites, with no adjustment to make these values 26 consistent with the collocated 24-hour FRM measurement of PM 2.5 mass. Appendix A of the 27 UFVA provides details on the type of continuous instrument at each study site. TEOMs were 28 used at all sites except for be ta attenuation instruments in Fr esno and Philadelphia, nephelometer 29 instruments in Tacoma and Phoenix, and an FDMS instrument in Salt Lake City. 30 31 For conciseness in this second external revi ew draft, only the daily maximum daylight 1- 32 hour PM 2.5 mass concentration indicator is considered in this Appendix. It would also be 33 possible to construct al ternative NAAQS scenarios of an all- hours type, which could be analyzed 34 in the same manner as presented in this Appendix. 35 36 2.0 Current Conditions of 1-hour PM 2.5 Mass 37 38 Figure 4A-1 is a box plot of 2005-2007 daily maximum daylight 1-hour PM 2.5 mass 39 concentrations for the 14 study areas, excludi ng hours with relative hum idity greater than 90 40 percent, to give a sense of the range and centr al tendency of this parameter. The horizontal 41 reference lines are at 10, 20, 30, 40 and 60 μg/m 3

. The relative positions of the 90 percentile 42 concentrations (indicated by the horizontal stroke at the top of the whisker) are generally 43 consistent with the relative ranking of these site s according to their design values for the 24-hour 44 PM 2.5 NAAQS (see Table 3-2 of the UFVA); simila rly, the relative positions of the median 45Draft-Do Not Quote or Cite June 2010 4A-2 concentrations are generally consistent with the annual PM 2.5 design values. Table 4A-1, based 1 on the same data as Figure 4A-1, presents the percentage of days in 2005-2007 on which the 2 daily maximum daylight 1-hour PM 2.5 concentration exceeded the reference levels represented 3 by the horizontal lines in Figure 4A-1. 4 5 Figure 4A-1. 2005-2007 daily maximum daylight 1-hour PM 2.5 mass concentrations 6 (μg/m 3 ) for the 14 study areas (excluding hour s with relative humidity greater than 90 7 percent) 8 9

10 11 12 13 14 15 16 17 18 19 20 21 22 23 24Draft-Do Not Quote or Cite June 2010 4A-3 Table 4A-1. Percentage of days with daily maximum daylight 1-hour PM 2.5 mass 1 concentration exceeding reference levels in 2005-2007 (excluding hours with relative 2 humidity greater than 90 percent) 3 4
1-hour PM 2.5 Mass Reference Level (μg/m 3 ) Study Area Number of Days with Estimates 10 20 30 40 60

Tacoma 109 50 11 1 0 0 Fresno 324 88 62 37 20 8 Los Angeles 300 92 81 67 46 20 Phoenix 86 60 8 1 1 1 Salt Lake City 306 64 20 11 7 2 Dallas 273 75 25 5 0 0 Houston 148 80 42 14 5 0 Birmingham 349 92 60 37 23 8 Atlanta 279 86 56 28 10 1 Detroit 141 92 72 52 36 13 Pittsburgh 277 94 57 28 15 3 Baltimore 181 90 46 22 8 1 Philadelphia 143 99 84 63 45 20 New York 225 75 43 25 13 3 5 3.0 Alternative NAAQS Scenar ios Based on 1-hour PM 2.5 Mass as the Indicator 6 7 To ensure examination of a wide enough range of alternative sta ndards based on 1-hour 8 PM 2.5 mass to encompass the range of standards that might be considered as alternatives to the 9 PM 10 light extinction NAAQS scenarios examined in Chapter 4 of the UFVA, we considered 10 levels of 10, 20, 30, 40, and 60 μg/m 3 . Only the daily maximu m daylight hour form was 11 considered. Each level was comb ined with two statistical forms: the three-year average of the 12 annual 90 th percentile value and the three- year average of the annual 95 th percentile value. For 13 ease of reference, these scenarios are designated by letters from “aa” to “jj” and listed in Table 14 4A-2. Looking somewhat ahead to results presente d below, the scenarios are arranged in Table 15 4A-2 in order of least to most stringen t in terms of the reductions in ambient PM 2.5 needed from 16 current levels to meet the current a nd alternative NAAQS levels and forms. 17 18 Table 4A-2. Alternative NAAQS scenarios ba sed on daily maximum daylight 1-hour PM 2.5 19 mass, averaged over three years (excluding ho urs with relative humidity greater than 90 20 percent) 21 22 NAAQS Scenario Level (μg/m 3) Statistical Form aa 60 3-year average of 90 th percentile bb 60 3-year average of 95 th percentile cc 40 3-year average of 90 th percentile dd 40 3-year average of 95 th percentile ee 30 3-year average of 90 th percentile ff 30 3-year average of 95 th percentile gg 20 3-year average of 90 th percentile hh 20 3-year average of 95 th percentile ii 10 3-year average of 90 th percentile jj 10 3-year average of 95 th percentileDraft-Do Not Quote or Cite June 2010 4A-4 4.0 Approach to Modeling “What If” Conditions of PM 10 Light Extinction for 1 Alternative Secondary NAAQS Based on 1-hour PM 2.5 Mass 2 3 Before modeling “what if” condi tions, we augmented the data set described in Table 4 of 4 the UFVA in the same manner as described in Section 4.1.4 of the UFVA, to achieve seasonal 5 balance despite the lack of mon itoring data for one quarter in each of Houston and Phoenix. In 6 Tacoma and Phoenix, which had data only for two years in the 2005-2007 period, we averaged 7 the percentile values from the only two available years rather than the th ree years defined for the 8 statistical form of the NAAQS scenarios. 9 10 The modeling of daily ma ximum daylight 1-hour PM 2.5 mass under each of the scenarios 11 listed in Table 4A-2 used a rollback approach th at combined relevant concepts and steps from 12 the rollback methods described in sections 4.1.4 (for PM 10 light extinction scenarios) and 4.2.2 13 (for scenarios based on annual average and 24-hour average PM 2.5 ) of the UFVA. The following 14 are the steps in the modeling. 15 16 1. Identify the 90 th percentile daily maximum daylight 1-hour PM 2.5 mass value in each of 17 2005, 2006, and 2007 for a study area. Average these to determine the 3-year average design 18 value for that percentile form. Repeat for the 95 th percentile form. These design values are 19 presented in Table 4A-3. Th ey range from 22 to 81 μg/m 3 , indicating that some study areas meet 20 some of the NAAQS scenarios under current conditions. In such cases, PM 2.5 concentrations 21 were not adjusted, i.e., there was no “r oll up” for any area in any scenario. 22 23 2. Using the same days and hours as contributed by th e three annual 90 th percentile values 24 for actual 1-hour PM 2.5 mass, find the three corresponding va lues of policy relevant background 25 (PRB) 1-hour PM 2.5 mass. Average these three annual values of PRB 1-hour PM 2.5 to obtain the 26 3 year average PRB portion of the actual 1-hour PM 2.5 design value for the 90 th percentile form. 27 Repeat for the 95 th percentile form. 28 29 In the modeling for the NAAQS scenarios examined in the UF VA, PRB for 1-hour PM 2.5 30 mass was not explicitly calculated because it was not needed in the rollback modeling for the 31 scenarios addressed in the UFVA. Therefore, it was necessary to recons truct this parameter by 32 adding the values for the PRB concentr ations of the five components of PM 2.5 : nitrate, sulfate, 33 elemental carbon, organic carbon material, and so il. The method for estimating PRB for these 34 five components is described in Appendix C of the UFVA. 35 36 3. Subtract the value from step 2 from the value from step 1, to determine the non-PRB 37 portion of the 1-hour PM 2.5 mass design value. 38 39 4. Calculate the percentage reduc tion required in non-PRB 1-hour PM 2.5 mass in order to 40 reduce the design value to the level that de fines the NAAQS scenario, using the following 41 equation: 42 43 Percent reduction required = 1 – (NAAQS level – PRB portion of the design value)/(non-PRB 44 portion of the design value) 45 46Draft-Do Not Quote or Cite June 2010 4A-5 The percentage reductions determined in step 4 are shown in Table 4A-4. Note that for 1 some combinations of area and scenario no re duction is required because the 2005-2007 design 2 value already meets the NAAQS scenario. 3 4 5. Turning to the entire set of day/hour-s pecific actual and PRB daylight 1-hour 5 concentrations of the five PM 2.5 components for the three (or tw o) year period, determine the 6 non-PRB portion of each of the fi ve components in an hour by subtracting the PRB value from 7 actual value, reduce it by the percentage dete rmined in step 4, and add back in the PRB 1-hour 8 concentration of the component. 9 10 6. Finally, calculate PM 10 light extinction using the reduced values of the five components, 11 the original value of 1-hour PM 10-2.5 , and the 1-hour value of f(RH), according to the following 12 equation for PM 10 light extinction (see section 3.2.3 of the UFVA for an explanation of the 13 variables in this equation). 14 15 b extPM = 3 x f(RH) x [Sulfate] 16 + 3 x f (RH) x [Nitrate] 17 + 4 x [Organic Mass] 18 +10 x [Elemental Carbon] 19 + 1 x [Fine Soil] 20 + 0.6 x [Coarse Mass] 21 22 These steps assume that in order to m eet a PM NAAQS scenario based on 1-hour PM 2.5 23 as the indicator, ea ch component of PM 2.5 is reduced by an equal percentage, across the five 24 components and across all hours. In actual implementation of such a NAAQS, each state would 25 develop an attainment strategy, which might re sult in unequal percenta ge reductions of the 26 components. If the strategy emphasized reductions in the fine soil component, for example, PM 27 light extinction levels would rema in high relative to those estima ted by these steps, because fine 28 soil is not efficient in terms of reducing visibi lity compared to the other four components on a 29 dry mass-to-mass basis. On the other hand, a strate gy that involves relativel y large reductions in 30 sulfate or nitrate would achieve greater reductions in PM light extinction than estimated by these 31 steps. The uncertainty in how the results of th is rollback method compare to the results of actual 32 attainment strategies should be kept in mind wh en comparing the results of “what if” scenarios 33 for NAAQS based on PM 2.5 mass as the indicator versus scenarios based on PM 10 light 34 extinction. Unlike the eff ect of humidity variation between ar eas, this source of uncertainty is 35 not reflected in any of the results presented in this Appendix and will not be apparent in 36 comparisons of results in this Appendix to results presente d in the UFVA for NAAQS scenarios 37 based on PM 10 light extinction. 38 39 These steps also assume no change in PM 10-2.5 concentrations between current conditions 40 and “what if” conditions. While reductions in PM 10-2.5 would not be needed to meet a secondary 41 NAAQS based on 1-hour PM 2.5 mass, it is possible that strategies to control PM 2.5 concentrations 42 might also achieve reductions in PM 10-2.5 concentrations because some sources emit both and 43 some control methods achieve some reductions in both. However, in most of the 14 study areas, 44 PM 10-2.5 makes a small contribution to estimated PM 10 light extinction, in part because in many 45 of the areas no local data on PM 10-2.5 concentrations were availabl e and the method used to fill 46Draft-Do Not Quote or Cite June 2010 4A-6 this gap (application of a factor to PM 2.5 concentration) simply c ould not produce a high estimate 1 of PM 10-2.5
. 2 3 Table 4A-3. 2005-2007 design values for 1-hour PM 2.5 mass (μg/m 3 ) 4 5 Study Area Percentile Form 90th 95th Tacoma 22 27 Fresno 55 66 Los Angeles 72 81 Phoenix 20 24 Salt Lake City 32 45 Dallas 26 29 Houston 33 37 Birmingham 55 74 Atlanta 40 45 Detroit 64 79 Pittsburgh 46 51 Baltimore 37 43 Philadelphia 67 77 New York 44 55 6 7 Table 4A-4. Percentage reductions in non-PRB PM 2.5 components required to meet 8 NAAQS scenarios based on 1-hour PM 2.5 mass 9 10
Scenario aa bb cc dd ee ff gg hh ii jj Level (μg/m 3 ) 60 60 40 40 30 30 20 20 10 10 Percentile Form 90 95 90 95 90 95 90 95 90 95 Study Area Percentage Reduction Tacoma 0 0 0 0 0 0 11 27 60 69 Fresno 0 10 28 40 46 55 65 71 83 86 Los Angeles 17 26 45 51 59 64 73 76 87 88 Phoenix 0 0 0 0 0 0 0 15 51 58 Salt Lake City 0 0 0 12 7 34 39 56 70 78 Dallas 0 0 0 0 0 0 23 34 64 69 Houston 0 0 0 0 9 20 40 49 71 78 Birmingham 0 19 28 46 46 60 65 74 84 87 Atlanta 0 0 0 12 25 34 51 57 77 80 Detroit 7 24 38 50 54 63 70 75 85 88 Pittsburgh 0 0 13 22 35 42 57 62 79 81 Baltimore 0 0 0 8 19 31 47 55 74 78 Philadelphia 10 22 40 49 55 62 71 75 86 88 New York 0 0 8 28 32 46 55 65 78 83 11 12Draft-Do Not Quote or Cite June 2010 4A-7 5.0. 1-hour PM 2.5 Mass Results for “Just Meeting” Alternative Secondary NAAQS 1 Scenarios Based on 1-hour PM 2.5 Mass 2 3 As a check on the reasonableness of the ro llback method described in section 4.0 and on 4 the accuracy of the code used to implement it, it is of interest to examin e the distribution of the 5 levels of 1-hour PM 2.5 that result from the method. Ideall y, after rollback any area that had a 6 non-zero required reduction should have a pos t-rollback design value for 1-hour PM 2.5 mass that 7 is exactly equal to the target design value. Als o, there should be a progres sion of reductions in 1- 8 hour PM 2.5 medians and other percentile points on th e distribution as progressively more 9 stringent scenarios are modeled. 10 11 Table 4A-5 shows th e post-rollback 1-hour PM 2.5 mass design values for the scenarios, 12 with percentile forms matched. Design values for area-scenario combinations for which the 13 required reductions were zero have been omitted, because the current conditions design values 14 for these combinations would not be expected to re flect the target design va lue. It can be seen 15 that the design values progress as expected and are in the vicinity of the target design values, but 16 are not always exactly equal to the targets. EPA staff attributes this to the fact that PRB 17 concentrations of 1-hour PM 2.5 mass vary from hour to hour. It is possible for the daily 18 maximum PM 2.5 mass concentration on a certain day in 2005 with a percentile rank of, for 19 example, 96 th to have a relatively small PRB porti on and a large non-PRB portion compared to 20 the daily maximum concentration that ranks 95 th . When an equal reduction is made to the non21 PRB portion of each total concentration, the two values may switch rank positions, and so a new 22 day and hour becomes the 2005 contributor to the roll ed back three-year desi gn value. Since this 23 day and hour was not used to determine the requi red percentage reduction, the resulting design 24 value will not exactly meet the target design valu e. It would be possible to iterate with higher 25 and lower percentage reductions until the rolled back design va lue exactly matched the target 26 design value, but EPA considered this degree of refinement to be unnecessary in order to meet 27 the objectives of the Policy Assessment Document , given other uncertainti es in the underlying 28 data and in the assumptions used to estimate PM 10 light extinction values. 29 30 EPA staff also generated and examined box plots of daily maximum daylight 1-hour 31 PM 2.5 mass concentrations as a check for conceptu al or programming errors, and found them to 32 match expectations. They are not included here, for conciseness. 33Draft-Do Not Quote or Cite June 2010 4A-8 Table 4A-5. Post-rollback design values for daily maximum 1-hour PM 2.5 mass. Design 1 values are shown only for combinations of stud y area and scenario for which the study area 2 does not meet the scenario under current co nditions, such that reductions were made 3 during the rollback modeling. 4 5
Scenario aa bb cc dd ee ff gg hh ii jj Level (μg/m 3 ) 60 60 40 40 30 30 20 20 10 10 Statistical Form 90th 95th 90th 95th 90th 95th 90th 95th 90th 95th Study Area Corresponding Design Value (μg/m 3 ) (same percentile form as the scenario) Tacoma 20 21 11 12 Fresno 63 40 42 30 31 20 21 10 10 Los Angeles 53 53 35 35 26 26 18 18 9 9 Phoenix 19 10 10 Salt Lake City 38 29 28 19 19 10 10 Dallas 23 23 12 11 Houston 29 27 19 18 10 9 Birmingham 58 42 39 32 29 21 20 11 10 Atlanta 36 28 27 19 18 10 10 Detroit 52 59 34 39 26 29 17 20 9 10 Pittsburgh 33 33 24 25 16 17 8 9 Baltimore 38 31 28 21 19 10 10 Philadelphia 46 44 31 30 23 22 16 15 8 8 New York 42 40 32 30 21 20 11 10 6 7 6.0 PM 10 Light Extinction Results for “Just Meeting” Alternative Secondary NAAQS 8 Scenarios Based on 1-hour PM 2.5 Mass 9 10 The rollback steps described in sec tion 4.0 resulted in estimates of PM 10 light extinction 11 for each day and hour in each study area, for each of the 10 NAAQS scenarios based on 1-hour 12 PM 2.5 mass as the indicator. Two summaries of these conditions are presented here. 13 14 Figure 4A-2 presents a box plot of daily maximum daylight 1-hour PM 10 light extinction 15 for each NAAQS scenario based on 1-hour PM 2.5 mass. These can be compared to Figure 3-8(a) 16 of the UFVA representing pr e-rollback daily maximum PM 10 light extinction, and to the upper 17 panel of the figures in Appendix F of the UFVA representing the daily maximum PM 10 light 18 extinction levels resulting from the 20 NAAQS s cenarios examined in the UFVA (18 scenarios 19 based on PM 10 light extinction as the indicator, the current annual and 24-hour PM 2.5 NAAQS, 20 and a scenario with an annual NAAQS of 12 μg/m 3 and a 24-hour NAAQS of 25 μg/m 3 ). It can 21 be seen that the distribution of PM 2.5 mass in a given study area shifts downward as the NAAQS 22 scenarios progress from least to most stringent (as indicated by the required percentage 23 reduction) and in most cases become more sim ilar to other areas (once the progression of 24 scenarios begins to require re ductions in a given area). 25 26 Table 4A-6 presents the percentage of da ys in 2005-2007 on which daily maximum 1-hour PM 10 27 light extinction exceeded each of the CPLs , under each of the 10 secondary PM NAAQS 28 scenarios based on 1-hour PM 2.5 mass. These percentages are necessarily based on the days for 29 which data to estimate PM 10 light extinction were available, but are best estimates of the 30 percentage of all days in the ye ar given that the days with data were well distributed across the 31Draft-Do Not Quote or Cite June 2010 4A-9 year on either a one-in-three or one-in-six sampling schedule. These percentages can be 1 compared to the same-basis percentages presented in Table 4-7 of the UFVA. 2Draft-Do Not Quote or Cite June 2010 4A-10 Figure 4A-2. Distributions of ma ximum daily daylight 1-hour PM 10 light extinction under 1 “just meet” conditions for NAAQS scenarios based on 1-hour PM 2.5 mass (excluding hours 2 >90% RH) 3 4 (aa) NAAQS Scenario: 60 μg/m 3 and 90 th percentile 5

6 (bb) NAAQS Scenario: 60 μg/m 3 and 95th percentile 7

8Draft-Do Not Quote or Cite June 2010 4A-11 Figure 4A-2 (cont). Distributions of maximum daily daylight 1-hour PM 10 light extinction 1 under “just meet” conditions for NAAQ S scenarios based on 1-hour PM 2.5 mass (excluding 2 hours >90% RH) (continued) 3 4 (cc) NAAQS Scenario: 40 μg/m 3 and 90 th percentile 5

6 (dd) NAAQS Scenario: 40 μg/m 3 and 95 th percentile 7

8Draft-Do Not Quote or Cite June 2010 4A-12 Figure 4A-2 (cont). Distributions of maximum daily daylight 1-hour PM 10 light extinction 1 under “just meet” conditions for NAAQ S scenarios based on 1-hour PM 2.5 mass (excluding 2 hours >90% RH) (continued) 3 4 (ee) NAAQS Scenario: 30 μg/m 3 and 90 th percentile 5

6 (ff) NAAQS Scenario: 30 μg/m 3 and 95 th percentile 7

8Draft-Do Not Quote or Cite June 2010 4A-13 Figure 4A-2 (cont). Distributions of maximum daily daylight 1-hour PM 10 light extinction 1 under “just meet” conditions for NAAQ S scenarios based on 1-hour PM 2.5 mass (excluding 2 hours >90% RH) (continued) 3 4 (gg) NAAQS Scenario: 20 μg/m 3 and 90 th percentile 5

6 (hh) NAAQS Scenario: 20 μg/m 3 and 95 th percentile 7

8Draft-Do Not Quote or Cite June 2010 4A-14 Figure 4A-2 (cont). Distributions of maximum daily daylight 1-hour PM 10 light extinction 1 under “just meet” conditions for NAAQ S scenarios based on 1-hour PM 2.5 mass (excluding 2 hours >90% RH) (continued) 3 4 (ii) NAAQS Scenario: Daily Max: 10 μg/m 3 and 90 th percentile 5

6 (jj) NAAQS Scenario: Daily Max: 10 μg/m 3 and 95 th percentile 7

8Draft-Do Not Quote or Cite June 20104A-15Table 4A-6. Percentage of days across three years (two years inthe case of Phoenix and Houston) with maximum 1-hourdaylight PM10light extinction above CPLs when “justmeeting” NAAQS scenarios based on 1-hour PM2.5mass. Blue shadingindicates no reduction required from current conditions.Days with max hour above64 Mm-1Days with max hour above112 Mm-1Days with max hour above191 Mm-1ScenarioaabbccddeeffgghhiijjaabbccddeeffgghhiijjaabbccddeeffgghhiijjNAAQSLevel(μg/m3)606040403030202010106060404030302020101060604040303020201010NAAQSPercentileForm909590959095909590959095909590959095909590959095909590959095AreaPercentage of daysPercentage of daysPercentage of daysTacoma535353535353 53 53 43 35232323232323 23 23 11 6444444 4 4 1 1Fresno76 73 65 57 69 60 55 44 28 1752 48 37 31 44 32 29 18 9 430 27 17 11 23 12 10 5 1 0Los Angeles89 87 84 81 84 79 74 69 41 30 78 76 65 57 65 53 41 31 11 7 52 46 30 24 30 19 11 6 3 3Phoenix44444444444444 44 37 326666666 6 6 61111111 1 1 1Salt LakeCity454545 37 45 45 45 26 17 10171717 15 17 17 17 11 8 5888 7 8 8 8 5 2 1Dallas818181818181 81 71 41 29414141414141 41 32 8 5101010101010 10 7 0 0Houston79797979 79 79 74 65 32 2744444444 44 44 35 28 6 311111111 11 11 9 6 1 0Birmingham89 85 80 68 87 80 72 62 41 3465 56 51 36 58 51 40 30 15 1234 26 21 13 30 20 15 11 4 3Atlanta919191 89 91 89 82 77 47 34757575 68 74 66 51 35 3 3313131 21 31 19 5 3 0 0Detroit84 80 74 72 76 73 65 60 40 33 67 57 51 43 53 48 34 21 9 6 43 28 13 7 14 9 6 4 1 1Pittsburgh8585 81 77 81 77 63 55 27 195757 51 45 52 44 29 22 3 02626 18 14 21 13 6 2 0 0Baltimore818181 76 81 74 64 56 31 20515151 45 51 44 31 23 4 3232323 18 23 16 8 2 1 1Philadelphia84 78 71 62 72 63 55 43 17 10 60 54 33 29 37 31 16 10 3 3 26 17 8 5 8 5 0 0 0 0New York8383 80 71 81 73 63 56 27 196060 56 39 56 40 32 22 6 32929 25 16 25 17 9 5 0 0Average 76 75 72 68 73 69 64 56 34 25 50 48 43 37 45 38 31 23 7 4 23 21 15 11 17 12 8 4 1 1This page left intentionally blank.Draft – Do Not Quote or Cite June 2010 4B- 1 

## Appendix 4B 1



## Simplified Approaches to Calculate Hourly PM 2.5 

## Light Extinction 2 

## Values from Hourly PM 2.5 

## Mass and Relative Humidity Data plus 3 

## 24-hour Mean PM 2.5 

## Composition Data 4
5

Overview: The goal of the assessmen t described in this appendix is to identify a simpler 6 procedure for calculating PM 2.5 light extinction that produces hour ly values that are comparable 7 to those developed for the 15-city 1 assessment (UFVA Section 3.3). The expected benefits of 8 moving to a simpler approach in clude an increase the numbers of sites at which it could be 9 applied (i.e., by not requiring so many collocate d monitors), and periods of time (i.e., by not 10 using sample day-specific CSN data) for which th e calculation of PM li ght extinction could be 11
conducted. 12 The UFVA approach used the following: 13
1. SANDWICH mass balance model to estimate or ganic carbonaceous material and nitrate 14
mass concentrations on the FRM filter fo r each Chemical Speci ation Network (CSN) 15 sample day, and thus also organic carbonace ous material mass on the CSN filter. Other 16 component concentrations on the CSN f ilter are taken by direct measurement. 17
2. Monthly mean diurnal PM 2.5 variations of each of the major PM 2.5 components from 18 CMAQ air quality simulation modeling result s applied to sample day specific CSN 24- 19 hour samples. 20
3. Hourly FRM-consistent PM 2.5 mass developed by normalizing continuous PM 2.5 21 measurements to the 24-hour FRM filter mass. 22
4. Hourly sum of the FRM-consistent components scaled to hourly PM 2.5 mass. 23
5. An adjustment to the hourly PM 2.5 nitrate component concentration to reflect actual 24 atmospheric concentration, which is assumed to be represented by the CSN filter nitrate 25 measurement. (This step in effect un-doe s the FRM nitrate loss introduced by the 26 SANDWICH mass balance model as part of estimating organic carbonaceous material 27 mass.) 28

1 The PM 10-2.5 values for St. Louis were determined by difference between two nearby monitoring sites. Based on comments received on the UFVA to the effect that the PM 10 monitoring site was not representative of the St. Louis urban area, EPA does not consider the PM 10-2.5 concentrations to be credible. However, for this assessment of various simplified methods to calculate PM 2.5 light extinction, St. Louis data were not excluded since all but one of the comparisons are for calculated PM 2.5 light extinction

.Draft – Do Not Quote or Cite June 2010 4B- 2 6. Hourly PM 10-2.5 data estimated by difference at site s with continuous monitors for both 1
PM 2.5 and PM 10-2.5 or by using typical regional ratios of PM 10-2.5 to PM 2.5 times the PM 2.5 2 concentrations where there are no PM 10 measurements. 3
7. IMPROVE algorithm to estimate hourly PM 2.5 light extinction from hourly PM 2.5 4 component and hourly relative humidity values. 5

The process that was followed for this anal ysis was to examine the difference between 6 calculated hourly PM 10 light extinction values used in the UFVA and values generated using 7 simpler approaches, explored in a step-wise fash ion. All of the simpler approaches (designated 8 by letter of the alphabet and described below) use the IMPROVE algorithm and measured hourly 9

PM 2.5 mass and relative humidity data. 10
A. Omission of PM 10-2.5 contributions to PM light extinction (Step 6 above). (This was done 11 primarily to simplify comparisons with other simplified approaches; coarse mass 12 contributions were separately examined in approach C.) For cl arity, light extinction 13 estimates are referred to as either PM 2.5 or PM 10 light extinction in the remainder of this 14 Appendix to indica te whether the PM 10-2.5 contribution to PM light extinction is included. 15
B. Use of a simpler approach to organic carbonaceous mass and n itrate than in the 16 SANDWICH-based UFVA approach briefly desc ribed in the steps listed above. Table 17 4B-1 contrasts the steps in th is simpler approach B (and appr oach F, below) to the steps 18 of approach A. The key distinguishing feat ures of approach B ar e (i) a multiplier of 1.7 19 is applied to the CSN measurem ent of organic carbon (after a correction for blank filter 20 artifact) rather than estimating organic carbonaceous material by the mass-balance 21 SANDWICH approach, and (ii) the hourly PM 2.5 mass is normalized to match the FRM 22 value for the 24-hour PM 2.5 mass and then speciated using the CSN-measured component 23 mix, with no correction for nitrate loss from the FRM Teflon filter. 24
C. Same as approach B except that it includes PM 10-2.5 contributions to PM 10 light 25 extinction, 26
D. Same as B except that the diurnal component distributi on is assumed to be flat 27 (unvarying) for each sample day. 28
E. Same as B except that monthly averaged PM 2.5 component distributions are used in place 29 of the CSN sample period-specific values. 30
F. Same as B except both flat diurnal PM 2.5 component variation are assumed and monthly 31 averaged PM 2.5 component distribution are used in pl ace of sample period specific values 32 (i.e., combines simplification of approaches D and E). Because staff recommends 33 consideration of this partic ular approach, for greatest clarity the data sources and 34 calculation steps used in this appr oach are listed in Table 4B-2. 35Draft – Do Not Quote or Cite June 2010 4B- 3 I. Simply uses the PM 2.5 mass concentration times a singl e constant. (This approach was 1 included to show the pe rformance of using PM 2.5 mass without adjusting for particle 2 composition and humidity effects on hygroscopic particles.) 2 3

2 Note that the letter designations for the approaches are no t contiguous. This is because EPA staff tested additional approaches that are not included in this discussion appendix. Note also that all of the figures include approach designators, as plan designators.Draft – Do Not Quote or CiteJune 20104B-4Table 4B-1. Detailed Comparative Description of Approaches A,B, and F for Estimating 1-hour PM2.5Light ExtinctionUFVA Step‡Aspect of Approach Approach AApproach B Approach F1 Estimation of 24-hour organiccarbonaceous massThe SANDWICH method(Frank, 2006) is used tosubdivide the 24-hour PM2.5mass reported by the FRM foreach day and site into sulfate,nitrate elemental carbon,organic carbonaceous mass,and fine soil/crustal mass.This is done usinginformation from the CSNmeasurements, physicalmodels, and day-specifictemperatures and relativehumidty. The primarypurpose of this SANDWICHstep is to estimate organiccarbonaceous mass on theFRM Teflon filter.Organic carbonaceous mass isassumed to equal the organiccarbon value reported fromCSN sampling, minus anetwork-wide blank filtercorrection, times 1.7.Same as B1, continued Estimation of 24-hourelemental carbon massCSN elemental carbonconcentrationSame as A Same as A1, continued Estimation of 24-hour sulfatemassCSN sulfate concentration,with day-specificSANDWICH estimates ofassociated ammonium andwater.Sulfate ion measurementfrom the CSN filter ismultiplied by 1.375 torepresent dry, neutralizedsulfate.Same as B1, continued Estimation of 24-hour nitratemassNitrate ion on the FRMTeflon filter is estimated bySANDWICH, with dayspecific estimates ofassociated ammonium andwater.Nitrate ion measurement fromthe CSN filter is multipliedby 1.29 to represent dry,neutralized nitrate.Same as B‡The numbering of steps follows that used to describe the UFVA approach in section 3.3.1 of the UFVA.Draft – Do Not Quote or CiteJune 20104B-5UFVA Step‡Aspect of Approach Approach AApproach B Approach F1, continued Estimation of 24-hour finesoil/crustal massCalculated from CSNelements, but without Al (adifference from theIMPROVE approach)Same as A Same as A2 Diurnal pattern of PM2.5componentsThe CMAQ-derived monthlynormalized diurnal profilesfor the sulfate, nitrate,elemental carbon, organiccarbon and fine soil/crustalcomponents (which averageto 1.0 across 24 hours) weremultiplied by the day-specificSANDWICH-based estimatesof the 24-hour averageconcentrations of the fivePM2.5components, to getintermediate day-specifichourly estimates of the fivecomponents (includingammonium and waterassociated with sulfate andnitrate ion).CMAQ-derived profiles wereapplied to the fivecomponents to getintermediate estimates.However, as described above,in Approach B the sulfate,nitrate, and organiccarbonaceous materialcomponents are defined andestimated differently than inApproach A.No diurnal profiles are used.This approach assumes thatthe percentage mix of PM2.5components is the same in allhours of a single day, equal tothe mix observed on the CSNfilter (with the stated methodfor OCM).3 Sum the 5 components The hourly concentrations ofthese five components(including day-specificammonium and waterassociated with sulfate andnitrate ion when the FRMTeflon filter is weighed) wereadded together, to get a sumof-components estimate ofhourly PM2.5mass for the dayof the FRM/CSN sampling.The hourly concentrations ofthe five components wereadded together, to get a sumof-components estimate ofhourly PM2.5for the day ofFRM/CSN sampling. Notethat water is not included.Calculate the monthlyaverage percentage mix of the5 PM2.5components, asfollows:For each day of 24-hour CSNsampling, sum the fivecomponents. Calculate thefraction of sum-of-5 for eachcomponent. Average thefraction for each componentacross the CSN samplingdays in the month.Draft – Do Not Quote or CiteJune 20104B-6UFVA Step‡Aspect of Approach Approach AApproach B Approach F4 Hourly PM2.5concentration,consistent with 24-hour FRMconcentration.The hourly data from thecontinuous PM2.5instrumenton the day of the FRMsampling were normalized bytheir 24-hour average, to get anormalized diurnal profile.This profile was applied tothe 24-hour PM2.5massreported by the FRM sampler,to get a preliminary, FRMconsistent estimate of hourlyPM2.5mass for the day of theFRM sampling. This keepsthe average of the valid 1-hour PM2.5values equal to the24-hour value from the FRMsampler.Same as A Same as A, but see thecomment on this topic inTable B-2.5, 6 Adjust preliminary estimatesof hourly PM2.5componentconcentrations (reflectingCMAQ diurnal profiles and24-hour measurements) to beconsistent with estimate ofhourly PM2.5 mass.The two estimates of hourlyPM2.5mass from steps 3 and4 were compared, hour-byhour. Within each hour, theestimates of all fivecomponents from step 2 wereincreased or decreased by acommon percentage (referredto below as Aiwhere thesubscript i indicates the hour)so that the sum of the fivecomponents after thisadjustment was equal to theestimate of the hourly PM2.5mass from step 4. Theadjustment percentage variedfrom hour-to-hour.Same as A Not applicable.Monthly-average percentagemix of PM2.5components isdirectly applied to the dayspecific FRM-consistenthourly PM2.5mass.Draft – Do Not Quote or CiteJune 20104B-7UFVA Step‡Aspect of Approach Approach AApproach B Approach F7 Adjust the FRM-consistentestimate of sulfate to theCSN/IMPROVE-consistentbasis expected by theIMPROVE algorithm.Each hourly estimate ofsulfate concentration on theFRM filter from step 6(which includes estimates ofassociated ammonium andparticle bound water) wasadjusted so that it excludeswater and reflects fullneutralization and therefore isconsistent with the reportingpractices of the IMPROVEprogram and the IMPROVEalgorithm.No adjustment is needed,given that the factors of 1.375and 1.29 already assume fullneutralization and no water.In effect, the mass of wateron the FRM filter is allocatedamong the 5 components.Same as B.8 Adjust the FRM-consistentestimate of nitrate to theCSN/IMPROVE-consistentbasis expected by theIMPROVE algorithm.A similar adjustment as instep 7 (for sulfate) was madeto each hour’s nitrateconcentration from step 6, sothat the estimate of hourlynitrate would reflect actualatmospheric conditions andbe consistent with theIMPROVE algorithm.This can result in the estimateof nitrate used in theIMPROVE algorithm beinghigher than the FRMconsistent estimate, for dayson which the SANDWICHmethod predicts a loss ofnitrate from the FRM filter.No adjustment is made.Implication:On warm days when the FRMfilter has lost nitrate mass, theestimates of hourly PM2.5willbe lower than actualatmospheric mass. All hourlyPM2.5components will bereduced, by the fraction thatthe lost nitrate is of totalPM2.5mass..Same as B.Draft – Do Not Quote or CiteJune 20104B-8UFVA Step‡Aspect of Approach Approach AApproach B Approach FNot numbered in UFVA Estimation of PM2.5lightextinction from estimates ofhourly concentrations ofPM2.5components.Original IMPROVEalgorithm, including f(RH)determined from hourly RH.Hours with RH >90% wereexcluded from design valuesand from most graphicaldisplays of results.Same as A Same as ADraft – Do Not Quote or Cite June 2010 4B- 9 Table 4B-2. Data Sources and Ca lculation Steps for Approach F 1
2 

### Approach F (As performed for results shown in this Appendix) 

### Comments

Data Sources CSN values for sulfate ion (S), nitrate ion (N), elemental carbon (EC), organic carbon (OC), and the crustal elements Si, Ca, Fe, and Ti. CSN sampling is currently performed at about 200 sites, some with one -in-six-days operation and some with one-in-thr ee-days operation. In 2005-2007, several different sampler models were in use among the 15 study sites. Prospectively, all CSN sampling for S, N, EC, and the crustal elements will be based the Met One SASS or Met One SuperSASS sampler, and all CSN sites now use the URG2000 sampler for carbon measurements.

If the revised IMPROVE algorithm were to be used in Step (ix) in stead of the original IMPROVE algorithm, an option the Administrator may wish to consider, additional analysis results from CSN would be needed, in particular chlorine or chloride. Fixed external estimates of organic carbonartifact on quartz filters, based on networkwide field blank data. Estimate depends on sampler model used for carbon sampling. These values ranged from 0.32 to 1.53 μg/m 3

, depending on sampler model. The artifact adjustment for the URG2000 sampler is of most in terest prospectively, because it is the single sampler now in use for carbon sampling in CSN. The URG2000 was used only at about one-half of the 15 study sites and only in the s econd half of 2007. For those sites and days, an organic carbon artifact of 0.5 ug/m 3 was assumed for the purposes of the UFVA and this document, based on early experience with this sampler. Should the Administrator choose to invite public comment on an approach like Appr oach F, this value could be updated prior to NPRM based on a more recent, larger field blank data set. Hourly PM 2.5 mass concentration from continuous instrument.

FRM or FEM 24-hour PM 2.5 mass concentration Steps (vii) and (viii) involve the scaling of hourly PM 2.5 mass concentrations from a continuous instrument to match the same-day 24-hour concentration re ported by a collocated FRM/FEM filter-based sampler. Including this scaling in a regulatory program based on Approach F would mean that estimates of PM 2.5 light extinction could only be developedDraft – Do Not Quote or Cite June 2010 4B- 10for days and locations with FRM/FEM filterbased sampling, implying the need for daily filter-based FRM/FEM sampling if estimates of light extinction are required on a daily basis.

The Administrator may wish to consider requiring that only continuous instruments approved as federal equivalent methods (FEM) (for purposes of measuring 24-hour PM 2.5 mass concentrations) may be used for PM 2.5 light extinction estimation, and omitting the scaling steps. None of the continuous PM 2.5 instruments used to co llect the 2005-2007 data used in the UFVA analysis had been approved as FEM. Several models have now been approved. If the scaling steps are omitted, then FRM measurements would not be a required data source for this approach. Steps (i) For each CSN sampli ng day, subtract OC artifact from OC measurement, and multiply by 1.7 to estimate organic carbonaceous material (OCM). (ii) For each CSN sampling day, calculate fine soil/crustal PM 2.5 (FS) from CSN measurements of crustal elements Si, Ca, Fe, and Ti, using the formula Fine soil PM 2.5 = 3.73 × [Si] + 1.63 × [Ca] + 2.42 × [Fe] + 1.94 × [Ti] (iii) For each CSN sampling day, multiply CSN measurement of sulfate ion by 1.375, and multiply CSN measurement of nitrate ion by 1.29, to reflect associated ammonium under an assumption of full neutralization. (iv) Sum the above estimates of the 5 components of PM 2.5 :

Sum = 1.375*S + 1.29*N + OCM + EC + FS (v) For each CSN sampling day, calculate the 5 component factions: sulfate fraction = 1.375*S/Sum Nitrate fraction = 1.29*N/Sum OCM fraction = OCM/Sum EC fraction = EC/Sum FS fraction = FS/Sum (vi) Average the fraction for sulfate from stepDraft – Do Not Quote or Cite June 2010 4B- 11 (v) across the CSN sampling days of that calendar month of that calendar year. Repeatn for the other 4 components. Call these the monthly-average component fractions. (vii) For each CSN sampling day, average the 24 values of 1-hour PM 2.5 mass from the continuous instrument. Divide the 24-hour FRM value for PM 2.5 mass by this average. Call this the “instrument scaling factor”. (viii) For each CSN sampling day, multiply each 1-hour PM 2.5 mass value from the continuous instrument by the instrument scaling factor. (ix) For each daylight h our of each day of that month (including days without CSN sampling) multiply the value of hourly PM 2.5 mass from step (viii) by the m onthly-average component fractions from step (vi). (x) Insert the results from step (ix) into the original IMPROVE algorithm, along with f(RH) calculated based on same-hour RH. Omit the Rayleigh scattering term and the contribution from PM 10-2.5 . Estimates of PM 2.5 light extinction in hours with RH greater than 90% are not used in de sign value calculations and graphics presented in this document. The Administrator may wish to consider proposing or seeking comment on the alternative of using the revised IMPROVE algorithm instead of the original algorithm, omitting the terms for Rayleigh scattering and NO 2 absorption. This approach that would allow explicit consideration of sea salt effects on light extinction.

The exclusion of hours with RH>90% originated out of concern that an instrumental measurement of PM light extinction might results in high values of light extinction due to natural conditions of fog or precipitation. In as much as Approach F does not employ a light extinction instrument, the Administrator may wish to consider no t excluding these hours from the form of the NAAQS. However, the accuracy of RH measurements at such high values of RH would s till be a consideration.Draft – Do Not Quote or Cite June 2010 4B- 12 As the results below show, approaches B, D, E, and F produce hourly PM 2.5 light 1 extinction values that are quite comparable to the hourly PM 2.5 light extinction values in the 2 original UFVA (i.e., approach A). EPA staff favors cons ideration of approach F because it is the 3 most simplified of the methods tested that ma ke use of CSN measurements, and its use of 4 monthly averaged PM 2.5 components information means that it can be applied every day, not just 5 on days with CSN monitoring data (i .e., 1 day in 3 or 1 day in 6). 4 6 Comparative Performance of Simplified PM 2.5 Light Extinction Approaches : The 7 performance assessment of simplif ied approaches for calculated PM 2.5 light extinction was 8 accomplished by comparing hourly values of PM 2.5 light extinction generated by each approach 9 to their corresponding paired values generated us ing the original UFVA method, which is labeled 10 above as approach A. Annual box and whisker pl ots of the percentage differences between the 11 paired values, as well as annual and monthly scatter plot s and regression analys is of these paired 12 data, were generated. Selected graphs and summar y tables of regression statistics are included 13 below to show the degree of comparability be tween the various approaches to the original 14
estimates of PM 2.5 light extinction. The complete set of these figures is available on EPA’s web 15 site (http://www.epa.gov/ttn/analysis/pm_pad.htm). 16 The box and whisker plots of the diffe rences between calculated hourly PM 2.5 light 17 extinction by approaches B, D, E, and F are sh own in Figures 4B-1 and 4B-2. In the box and 18 whisker plots of percentage difference, the pe rcentage difference is calculated as follows: 19
20 Percentage difference = [(“A” estimate) – (simpl er approach estimate)]/(“A” estimate) * 100% 21 22 The patterns of relatively small bias for the 15 urban areas are notably similar in each of the 23 plots. Keeping in mind that the differences in the approach are iterative with approach B 24 differing from approach A onl y by not using the SANDWICH model to estimate organic 25 component mass concentration and to adjust ni trate concentrations, while the three other 26 approaches (i.e., D, E, and F) add additional simplifications, it is perhaps surprising that the city27 to-city pattern of the box positions and sizes are remarkably similar for these four approaches. 28 This suggests that the simplifications betw een approaches A and B (i.e., replacing the 29 SANDWICH model) is responsible for the greatest amount of di fferences in calculated hourly 30

PM 2.5 light extinction between approach A and D, E, and F, or in other words, the additional 31

4 Note that Approach F as applied for this Appendix requ ired the availability of filter-based FRM/FEM data for 24- hour concentration, and that most filter-based PM 2.5 monitoring sites do not operate every day. However, see the related comment in Table 4B-2.Draft – Do Not Quote or Cite June 2010 4B- 13 changes introduced in the remain ing three approaches did not mu ch affect the resulting hourly 1
values. 5 2 The degree of comparability for paired hourly PM 2.5 light extinction between approach F 3 and A, and between approach F and B values by month and urban area is evident in regression 4 statistics (Tables 4B-3 and 4B-4). In both tables the regression lines have slopes and R 2 values 5 near one with small intercepts for most urban areas and months implying that the values are 6 highly comparable. The western urban areas (e.g ., Fresno, Houston, Los Angeles, Phoenix, Salt 7 Lake City and Tacoma) have slopes and R 2 values for some months that imply a bias and/or 8 noisier relationship between values calculated by approaches F and A. As expected the 9 regression relationships show that values calculated by approach F are more similar to those of 10 approach B (Table 4B-4) since neither uses the SANDWICH model, than to those of approach A 11 (Table 4B-3) which included the SANDWICH model estimates. Four scatter plots of calculated 12 hourly PM 2.5 light extinction for all months that compare approach F to approach A and 13 approach F to approach B for Baltimore and Fresno are show in Figure 4B-3 as examples of the 14 degree of comparability for easte rn and western urban areas. 15 A comprehensive assessment of the reasons that there are greater differences between 16 approaches A and B than between approaches B a nd any of D, E, and F has not been conducted. 17 However, some explanations are suggested by the results themselves. The fact that hour-to-hour 18 and day-to-day variations in the dry PM 2.5 composition can be replaced by monthly averaged 19 values without much loss of pr ecision in calculated hourly PM 2.5 light extinction suggests that 20 these shorter term variations within a single month at a single monitoring site are not very 21 influential. This may imply th at the differences between approach A and the other approaches 22 considered here are probably not due to the relative composition cha nges caused by use of the 23 SANDWICH model and the simpler approach B. Th is suggests that the di fference may be due to 24 the adjustment to the FRM measured PM 2.5 mass concentration that was done to account for 25 negative sampling artifact for ammonium nitrate. This is consistent with the behavior for sites 26 that have high ammonium nitrate (e.g., Fresno and Los Angeles). Depending on the results of 27 this more complete assessment of why the difference in hourly values are higher between 28 approach A and B then between those of B and any of D, E, and F, another approach that retains 29 the SANDWICH model but otherwise has the simplif ications of approach F might be developed 30
as the better method to calculate PM 2.5 light extinction. 31

5 In the box and whisker plots, some extreme values of th e percentage change are due to rounding effects when the values involved were very small.Draft – Do Not Quote or Cite June 2010 4B- 14 Figure 4B-1 Box and whisker plot of the percent difference in calculated hourly PM 2.5 light extinction between 1 approaches B and A (top plot) and D and A (bottom plot) by urban area. 2

3 4 5Draft – Do Not Quote or Cite June 2010 4B- 15 Figure 4B-2 Box and whisker plot of the percent difference in calculated hourly PM 2.5 light extinction 1 between approaches E and A (top plot) and F and A (bottom plot) by urban area. 2

3Draft – Do Not Quote or Cite June 2010 4B- 16 1

Figure 4B-3 Scatter plots of calculated PM 2.5 light extinction by approach F versus approach A (left) and B 2 (right) for Baltimore (top ) and Fresno (bottom). 3

4Draft – Do Not Quote or CiteJune 20104B-17Table 4B-3 Linear regression equation and R2values for relating hourly PM2.5light extinction values calculated usingapproach F (x in the equation) to those using approachA (y in the equation) by month for 15 urban areas.Month123456789101112Atlanta,GAy=1.09*x+‐0.74;Rsq=0.98y=1.03*x+1.85;Rsq=0.98y=1.01*x+‐1.53;Rsq=0.97y=1.06*x+‐4.65;Rsq=0.98y=1.02*x+‐4.41;Rsq=0.97y=0.99*x+‐3.52;Rsq=0.97y=0.96*x+‐1.38;Rsq=0.96y=0.98*x+‐4.01;Rsq=0.98y=0.98*x+‐2.8;Rsq=0.98y=0.97*x+0.42;Rsq=0.99y=1.04*x+0.12;Rsq=0.96y=1.04*x+0.67;Rsq=0.98Baltimore,MDy=0.99*x+1.31;Rsq=0.99y=1.07*x+‐3.64;Rsq=1y=0.97*x+3.35;Rsq=0.99y=1.02*x+0.36;Rsq=0.96y=0.99*x+0.83;Rsq=0.9y=0.98*x+‐3.78;Rsq=0.96y=0.94*x+‐2.59;Rsq=0.98y=0.88*x+2.1;Rsq=0.99y=0.96*x+‐3.25;Rsq=0.98y=1.05*x+‐2.77;Rsq=0.98y=1.01*x+5.62;Rsq=0.99y=1.02*x+0.19;Rsq=0.97Birmingham,ALy=1.1*x+‐2.32;Rsq=0.97y=1.04*x+0.59;Rsq=0.97y=1.06*x+‐2.86;Rsq=0.97y=1.06*x+‐3.91;Rsq=0.97y=0.94*x+2.05;Rsq=0.97y=0.98*x+‐4.9;Rsq=0.98y=1.02*x+‐6.87;Rsq=0.97y=0.9*x+2.31;Rsq=0.93y=1*x+‐6.31;Rsq=0.98y=1.06*x+‐3.87;Rsq=0.97y=1.05*x+‐2.22;Rsq=0.98y=1.02*x+0.37;Rsq=0.99Dallas,TXy=1.17*x+‐1;Rsq=0.97y=1.1*x+0.12;Rsq=0.98y=1.15*x+‐4.59;Rsq=0.96y=1.04*x+‐2.64;Rsq=0.97y=1.03*x+‐3.1;Rsq=0.96y=0.93*x+0.75;Rsq=0.95y=0.96*x+‐0.01;Rsq=0.96y=0.98*x+‐0.63;Rsq=0.91y=1.01*x+‐3.02;Rsq=0.93y=1.06*x+‐2.35;Rsq=0.97y=1.04*x+‐1.16;Rsq=0.96y=1.07*x+1.11;Rsq=0.99Detroit,MIy=1.02*x+2.64;Rsq=0.97y=0.96*x+3.31;Rsq=0.99y=1*x+1.92;Rsq=0.99y=1.1*x+‐0.43;Rsq=0.96y=0.92*x+5.49;Rsq=0.96y=0.96*x+2.14;Rsq=0.96y=0.99*x+0.17;Rsq=0.93y=1.29*x+‐18.07;Rsq=0.9y=1.11*x+‐8.62;Rsq=0.97y=1.18*x+‐3.49;Rsq=0.95y=1.05*x+5.63;Rsq=1y=0.95*x+3.25;Rsq=0.99Fresno,CAy=1.05*x+‐0.61;Rsq=0.98y=1.06*x+2.02;Rsq=0.99y=1.17*x+4.27;Rsq=0.96y=1.32*x+‐4.32;Rsq=0.86y=1.27*x+‐2.92;Rsq=0.83y=1.24*x+‐5.26;Rsq=0.87y=1.06*x+‐0.97;Rsq=0.97y=1.3*x+‐6.59;Rsq=0.86y=1.39*x+‐6.67;Rsq=0.89y=1.51*x+‐8.53;Rsq=0.94y=1.08*x+5.8;Rsq=0.98y=0.98*x+6.01;Rsq=0.99Houston,TXy=0.83*x+4.6;Rsq=0.96y=0.97*x+‐1.12;Rsq=0.99y=0.9*x+0.8;Rsq=0.99y=1.02*x+‐3.72;Rsq=0.98y=0.97*x+‐2.87;Rsq=0.97y=0.84*x+7.59;Rsq=0.92y=0.76*x+11.38;Rsq=0.85y=0.88*x+4.71;Rsq=0.94y=0.99*x+‐2.92;Rsq=0.98y=1.06*x+‐3.39;Rsq=0.99y=1.07*x+‐3.64;Rsq=0.95y=1.06*x+‐2.09;Rsq=0.98LosAngeles,CAy=1.21*x+‐0.76;Rsq=0.98y=1.13*x+1.34;Rsq=0.98y=1.1*x+7.13;Rsq=0.96y=1.16*x+1.82;Rsq=0.96y=1.05*x+13.01;Rsq=0.96y=1.35*x+‐4.71;Rsq=0.86y=1.29*x+‐4.96;Rsq=0.91y=1.4*x+‐14.24;Rsq=0.82y=1.43*x+‐10.81;Rsq=0.91y=1.27*x+‐1.2;Rsq=0.95y=1.1*x+8.4;Rsq=0.97y=1.1*x+5.08;Rsq=0.97NewYork,NYy=1.04*x+1.72;Rsq=0.98y=1.03*x+‐1.34;Rsq=1y=1.01*x+3.48;Rsq=0.99y=1.11*x+‐0.74;Rsq=0.98y=1.06*x+‐1.45;Rsq=0.97y=1.11*x+‐6.56;Rsq=0.96y=1.02*x+‐7.96;Rsq=0.96y=0.98*x+‐1.61;Rsq=0.97y=1.03*x+0.24;Rsq=0.96y=1.22*x+‐7.88;Rsq=0.97y=1.09*x+‐0.86;Rsq=0.99y=1.06*x+1.17;Rsq=0.98Draft – Do Not Quote or CiteJune 20104B-18Philadelphia,PAy=0.98*x+2.25;Rsq=0.99y=1.01*x+‐1.64;Rsq=0.99y=1*x+1.32;Rsq=0.99y=0.96*x+2.4;Rsq=0.94y=0.9*x+1.44;Rsq=0.98y=0.92*x+‐0.44;Rsq=0.98y=0.91*x+1.75;Rsq=0.98y=0.85*x+5.59;Rsq=0.98y=0.89*x+1.3;Rsq=0.96y=0.95*x+3.87;Rsq=0.97y=1.08*x+0.34;Rsq=0.99y=0.97*x+2.37;Rsq=0.99Phoenix,AZy=1.21*x+‐2.37;Rsq=0.89y=1.13*x+‐1.38;Rsq=0.97y=0.88*x+1.25;Rsq=0.96y=0.85*x+1.94;Rsq=0.94y=0.93*x+0.87;Rsq=0.9y=0.88*x+1.65;Rsq=0.97y=0.77*x+4.02;Rsq=0.69y=0.92*x+0.62;Rsq=0.99y=0.86*x+0.48;Rsq=0.97y=0.92*x+1.18;Rsq=0.72y=1.05*x+‐1.68;Rsq=0.92y=1.16*x+‐2.68;Rsq=0.94Pittsburgh,PAy=1.1*x+‐3.59;Rsq=0.95y=0.99*x+1.91;Rsq=0.97y=0.99*x+‐0.27;Rsq=0.99y=1.09*x+‐2.34;Rsq=0.96y=1.07*x+‐5.67;Rsq=0.92y=0.95*x+‐1.28;Rsq=0.97y=1.03*x+‐9.91;Rsq=0.96y=0.94*x+‐1.93;Rsq=0.97y=1.04*x+‐7.42;Rsq=0.94y=1.02*x+‐1.66;Rsq=0.97y=1.06*x+‐1.26;Rsq=0.99y=0.99*x+2.25;Rsq=0.98SaltLakeCity,UTy=0.91*x+8.57;Rsq=1y=0.97*x+4.76;Rsq=0.99y=1.12*x+1.93;Rsq=0.97y=1.14*x+‐1.25;Rsq=0.88y=0.98*x+0.92;Rsq=0.83y=1.02*x+0.99;Rsq=0.87y=1*x+0;Rsq=0.99y=0.98*x+‐0.43;Rsq=0.97y=0.88*x+5.49;Rsq=0.87y=1.09*x+0.11;Rsq=0.93y=1.06*x+0.77;Rsq=0.97y=0.91*x+5.95;Rsq=0.99StLouis,MOy=1.01*x+1.63;Rsq=0.99y=1.03*x+‐0.41;Rsq=1y=1.07*x+‐0.47;Rsq=0.98y=1.14*x+‐3.93;Rsq=0.94y=1.06*x+‐2.9;Rsq=0.92y=0.92*x+0.97;Rsq=0.95y=0.98*x+‐2.77;Rsq=0.97y=1*x+‐7.97;Rsq=0.98y=0.94*x+‐0.89;Rsq=0.97y=1.2*x+‐4.17;Rsq=0.95y=1*x+4.66;Rsq=0.98y=1.01*x+1.69;Rsq=0.99Tacoma,WAy=1.02*x+‐0.05;Rsq=1y=0.98*x+0.71;Rsq=0.94y=1.07*x+‐0.1;Rsq=0.97y=1.22*x+‐3.78;Rsq=0.96y=1.18*x+‐4.43;Rsq=0.92y=1.09*x+‐0.14;Rsq=0.9y=1.1*x+‐1.28;Rsq=0.94y=1.22*x+‐4.35;Rsq=0.95y=1.06*x+0.02;Rsq=0.96y=0.97*x+1.2;Rsq=0.98y=1.05*x+0.83;Rsq=1y=1.02*x+2.4;Rsq=0.97Draft – Do Not Quote or CiteJune 20104B-19Table 4B-4 Linear regression equation and R2values for relating hourly PM2.5light extinction values calculated usingapproach F (x in the equation) to those using approachB (y in the equation) bymonth for15 urban areas.Month123456789101112Atlanta,GAy=1.01*x+0.4;Rsq=0.98y=1.06*x+0.26;Rsq=0.96y=1.02*x+‐0.15;Rsq=0.99y=1.02*x+‐0.72;Rsq=0.99y=1.02*x+‐0.83;Rsq=0.99y=1.02*x+‐1.06;Rsq=0.99y=1.02*x+‐0.38;Rsq=0.95y=1.04*x+‐3.54;Rsq=0.98y=1.02*x+‐0.74;Rsq=0.99y=1*x+1.11;Rsq=0.99y=1*x+1.2;Rsq=0.98y=0.99*x+0.81;Rsq=0.99Baltimore,MDy=0.96*x+1.84;Rsq=0.99y=1.09*x+‐5.5;Rsq=0.99y=1.04*x+‐1.21;Rsq=1y=1.01*x+1.15;Rsq=0.98y=1.02*x+‐1.15;Rsq=1y=0.99*x+0.73;Rsq=0.99y=1.01*x+‐0.36;Rsq=0.98y=1*x+0.25;Rsq=1y=1.02*x+‐1;Rsq=1y=0.97*x+2.23;Rsq=0.98y=0.99*x+2.98;Rsq=0.99y=1.02*x+‐0.17;Rsq=0.98Birmingham,ALy=1.08*x+‐2.37;Rsq=0.98y=0.98*x+3.39;Rsq=0.96y=1.02*x+0;Rsq=0.99y=1.07*x+‐2.22;Rsq=0.98y=1*x+1.38;Rsq=0.99y=1.01*x+‐0.71;Rsq=0.99y=1.06*x+‐4.76;Rsq=0.98y=0.98*x+2.12;Rsq=0.95y=1.02*x+‐2.17;Rsq=0.98y=1*x+1.46;Rsq=0.98y=1.02*x+0.76;Rsq=0.99y=1*x+1.59;Rsq=0.99Dallas,TXy=1.08*x+‐1.32;Rsq=0.99y=1.05*x+‐1.39;Rsq=0.99y=1.06*x+‐1.42;Rsq=0.99y=1.08*x+‐2.66;Rsq=0.99y=1.04*x+‐1.58;Rsq=0.99y=0.98*x+1.45;Rsq=0.95y=0.99*x+0.46;Rsq=0.96y=0.94*x+2.44;Rsq=0.91y=1*x+‐0.52;Rsq=0.99y=1.02*x+‐0.48;Rsq=0.99y=1.03*x+‐0.71;Rsq=0.99y=1.13*x+‐3.74;Rsq=0.99Detroit,MIy=1.06*x+‐4.03;Rsq=0.98y=1.05*x+‐2.66;Rsq=1y=1.03*x+‐1.35;Rsq=0.99y=1.01*x+0.23;Rsq=0.99y=1*x+‐0.08;Rsq=1y=0.98*x+0.79;Rsq=0.99y=1.02*x+‐0.65;Rsq=0.99y=1.09*x+‐5.76;Rsq=0.97y=1.01*x+‐0.83;Rsq=0.99y=1.05*x+‐1.29;Rsq=0.99y=0.99*x+4.66;Rsq=1y=1.09*x+‐5.58;Rsq=0.95Fresno,CAy=1.06*x+‐5.57;Rsq=0.99y=1.05*x+‐4.18;Rsq=0.99y=1.03*x+‐0.85;Rsq=1y=1.02*x+‐0.57;Rsq=0.99y=1.02*x+‐0.24;Rsq=0.98y=1.03*x+‐0.55;Rsq=0.99y=1*x+‐0.76;Rsq=1y=1.02*x+‐0.58;Rsq=0.99y=1.04*x+‐1.01;Rsq=0.99y=1.1*x+‐3.18;Rsq=0.99y=1.05*x+‐4.61;Rsq=0.99y=1.04*x+‐4.37;Rsq=0.99Houston,TXy=0.97*x+2.57;Rsq=0.99y=1.08*x+‐1.78;Rsq=0.97y=1.01*x+0.8;Rsq=0.99y=1.04*x+‐0.93;Rsq=0.99y=1.02*x+‐0.48;Rsq=0.98y=0.9*x+8.05;Rsq=0.93y=0.77*x+13.92;Rsq=0.81y=0.92*x+6.43;Rsq=0.94y=1.01*x+‐0.91;Rsq=0.99y=1.05*x+‐1.77;Rsq=0.99y=1.12*x+‐3.15;Rsq=0.99y=1.14*x+‐2.39;Rsq=0.97LosAngeles,CAy=1.08*x+‐3.01;Rsq=0.99y=1.04*x+‐1.62;Rsq=1y=1.02*x+0.27;Rsq=0.99y=1.05*x+‐2.99;Rsq=0.99y=1*x+0.88;Rsq=1y=1.05*x+‐2.15;Rsq=0.99y=1.03*x+‐0.32;Rsq=0.99y=1.03*x+‐0.34;Rsq=0.99y=1.06*x+‐1.65;Rsq=0.99y=1.08*x+‐3.22;Rsq=0.99y=1.06*x+‐0.62;Rsq=1y=1.04*x+‐0.14;Rsq=0.99Draft – Do Not Quote or CiteJune 20104B-20NewYork,NYy=1*x+‐0.52;Rsq=1y=1.01*x+‐0.82;Rsq=1y=0.99*x+0.86;Rsq=1y=1.03*x+‐0.26;Rsq=1y=1*x+0.17;Rsq=0.99y=1.07*x+‐3.4;Rsq=0.99y=1.03*x+‐4.03;Rsq=0.99y=1.02*x+‐2.43;Rsq=0.99y=1.01*x+‐0.94;Rsq=1y=1.06*x+‐3.4;Rsq=0.99y=1.02*x+‐0.84;Rsq=1y=1*x+‐1.11;Rsq=1Philadelphia,PAy=1.03*x+‐1.63;Rsq=0.99y=1.02*x+‐2.07;Rsq=0.99y=1.02*x+‐0.65;Rsq=1y=1.05*x+‐1.63;Rsq=0.98y=0.99*x+0.1;Rsq=1y=0.99*x+0.42;Rsq=1y=1.02*x+0.32;Rsq=0.98y=0.99*x+2.35;Rsq=0.99y=0.96*x+1.39;Rsq=0.99y=1.01*x+0.84;Rsq=1y=1.02*x+‐0.83;Rsq=1y=1*x+‐0.41;Rsq=1Phoenix,AZy=1.17*x+‐3.94;Rsq=0.93y=0.95*x+1.15;Rsq=0.99y=0.84*x+1.91;Rsq=0.97y=0.9*x+1.35;Rsq=0.94y=0.98*x+0.6;Rsq=0.96y=0.98*x+0.63;Rsq=0.98y=0.88*x+3.02;Rsq=0.81y=0.94*x+1.07;Rsq=0.99y=0.97*x+0.28;Rsq=0.98y=0.98*x+1.01;Rsq=0.89y=0.98*x+0.03;Rsq=0.96y=1.06*x+‐3.32;Rsq=0.97Pittsburgh,PAy=1.04*x+‐0.5;Rsq=0.97y=1*x+0.78;Rsq=0.99y=1.01*x+0.29;Rsq=1y=1.05*x+‐0.59;Rsq=0.99y=1.01*x+‐0.89;Rsq=0.99y=1*x+0.02;Rsq=0.99y=1.02*x+‐3.12;Rsq=0.99y=1.04*x+‐3.96;Rsq=0.99y=1.02*x+‐1.58;Rsq=0.99y=0.98*x+2.1;Rsq=0.98y=1.05*x+‐2.23;Rsq=0.99y=0.95*x+4.33;Rsq=0.98SaltLakeCity,UTy=1*x+1;Rsq=1y=1.02*x+‐0.94;Rsq=1y=1.07*x+‐0.81;Rsq=0.99y=1.05*x+‐0.51;Rsq=0.95y=0.98*x+0.79;Rsq=0.96y=1.02*x+‐0.44;Rsq=0.99y=0.97*x+0.77;Rsq=0.99y=0.96*x+0.74;Rsq=0.96y=0.75*x+8.1;Rsq=0.8y=0.97*x+1.37;Rsq=0.99y=1*x+‐0.22;Rsq=1y=1*x+‐0.24;Rsq=1StLouis,MOy=1.04*x+‐0.73;Rsq=0.99y=1.03*x+‐0.62;Rsq=1y=1.08*x+‐4.01;Rsq=0.99y=1.08*x+‐2.89;Rsq=0.98y=1.03*x+‐0.95;Rsq=0.97y=0.99*x+0.5;Rsq=0.99y=1.03*x+‐1.96;Rsq=0.99y=1.02*x+‐3.12;Rsq=0.99y=1*x+‐0.23;Rsq=0.99y=1*x+1.03;Rsq=0.99y=0.93*x+4.74;Rsq=0.98y=1.09*x+‐4.55;Rsq=0.98Tacoma,WAy=0.97*x+1.51;Rsq=1y=1.08*x+3.92;Rsq=0.73y=1.02*x+0.31;Rsq=0.97y=1.03*x+‐0.72;Rsq=0.99y=1.02*x+‐0.71;Rsq=0.98y=1.02*x+‐0.21;Rsq=0.99y=1.04*x+‐0.37;Rsq=0.98y=1.03*x+‐0.58;Rsq=0.99y=0.98*x+1.41;Rsq=0.98y=0.97*x+0.92;Rsq=0.99y=1.02*x+‐0.03;Rsq=1y=0.99*x+2.77;Rsq=0.97Draft – Do Not Quote or Cite June 2010 4B- 21 PM 10-2.5 Light Extinction: The source of the PM 10-2.5 data used to calculate its
contribution to PM 10 light extinction for the 14 cities varies by urban area. As described in the UFVA (section 3.2.1), for some urban areas hourly PM 10-2.5 was estimated by the difference method. Birmingham, Detroit, Baltimore a nd Philadelphia had collocated continuous PM 10 and

PM 2.5 monitors, while Tacoma, Los Angeles, Phoenix, Atlanta, and New York had two separate
sites with continuous PM 10 and PM 2.5 monitors. The other urban areas used a regional ratio of

PM 10-2.5 to PM 2.5 multiplied by hourly PM 2.5 to estimate PM 10-2.5 . While this approach provides some insight about the long-term c ontributions to li ght extinction by PM 10-2.5 , the hourly estimates using a ratio times PM 2.5 do not provide meaningful hourly information, so the results
for those urban areas are not discussed in this assessment. Figure 4B-4 is a box plot of the percent difference between the estimate of hourly PM 10 light extinction estimated by approach C (includes coarse PM contributi ons) and the estim ate of hourly PM 2.5 light extinction by approach A (does not include coarse PM contributions). Urban areas th at used the ratio method to
estimate PM 10-2.5 are labeled with an asterisk above th e figure box. The other difference between calculated PM light extinction between the two a pproaches is the use of the SANDWICH model in approach A that is not used in Approach C. It is this difference that is responsible for the negative values in the box plots.Draft – Do Not Quote or Cite June 2010 4B- 22 Figure 4B-4 Box and whisker plot of the percent diff erence between approaches C and approach A paired estimates of hourly PM 10 light extinction. Urban areas that used the ratio method to estimate PM 10-2.5 are designated with an asterisk (*) above the figure box.

The relative importance of PM 10-2.5 to light extinction is more clearly shown by comparing hourly calculated PM 10 light extinction values from approach C to paired hourly

PM 2.5 light extinction from approach B, which is identical except for the PM 10-2.5 contributions. As can be seen in example scatter plots 4Figur e B-5 (urban areas with collocated sampler) and Figure 4B-6 (urban areas us ing two different sites), PM 10 light extinction equals or exceeds

PM 2.5 when approaches C and B are compare d. Not surprisingly these show that PM 10-2.5 contributions to PM light exti nction are not often important fo r most of the urban areas, especially those in the Eastern U.S., though they can on rare occasions contribute as much as 100

Mm -1 to the PM 2.5 light extinction at some sites (e.g., Bi rmingham, Detroit, Philadelphia, and Atlanta). Based on these scatter plots PM 10-2.5 light extinction is a much more frequent and relatively large contributor to PM 10 light extinction at Phoenix (i .e., regression slope of 1.55) and an infrequent but large cont ributor to otherwise low PM 10 light extinction hours at Los Angeles. However, the Los Angeles PM 10-2.5 data should be treated skeptically, since the PM 10 monitoring
was done at a site outside the LA basin that may be unrepresentative of LA conditions. The

PM 10-2.5 contribution to PM light exti nction at Tacoma is about 50 Mm -1 , contributing about 7% (i.e., regression slope is 1.07).Draft – Do Not Quote or Cite June 2010 4B- 23 Figure 4B-5 Scatter plots comparing hourly PM light ex tinction for approaches C and B, for the four urban areas with collocated PM 10 and PM 2.5 monitoring.Draft – Do Not Quote or Cite June 2010 4B- 24 Figure 4B-6 Scatter plots comparing hourly PM light ex tinction for approaches C and B, for the five urban areas with different sites for PM 10 and PM 2.5 monitoring.Draft – Do Not Quote or Cite June 2010 4B- 25 PM 2.5 Mass Concentration Used Alone to Calculate PM 2.5 Light Extinction: Approach I predicts PM 2.5 light extinction by merely multiplying the same hourly PM 2.5 values as used in approach A (continuous PM 2.5 instrument normalized to matc h the FRM 24-hour concentration) by a constant (i.e., 4.35 m 2 /g). 6 As shown in Figures 4B-7 and 4B -8, the results are not nearly as comparable as those calculated using approach F (or any of the methods that include composition and hourly relative humidity data). In Figures 4B-7 and 4B-8, the percentage difference is calculated as follows, which is different th an for the earlier box and whisker plots:

Percentage difference = [(“C” estimate) – “A” estimate)]/(“C” estimate) * 100%

The variations in the relationships are ev en more evident in the monthly regression equations as shown in Table 4B-5. The slopes ra nge from about one half to nearly two with R 2

values that are often below 0.9 and as low as 0.4.

Figure 4B-7 Box and whisker plot of the percent difference in calculated hourly PM 2.5 light extinction between approaches I and A by urban area.

6 The value of 4.35 m 2 /g has no derivation of particular importance. It was chosen by EPA staff as an initial estimate of the value that would make the mean PM 2.5 light extinction estimated by a pproach I be the same as in approach B in one particular city.Draft – Do Not Quote or Cite June 2010 4B- 26 Figure 4B-8 Scatter plots of hourly calculated PM 2.5 light extinction for approach I versus approach A for four selected urban areas.Draft – Do Not Quote or CiteJune 20104B-27Table 4B-5Linear regression equation and R2values for relating hourly PM2.5light extinction values calculated using approach I (x in the equation) tothose using approach A (y in the equation) by month for 15 urban areas.Month123456789101112Atlanta,GAy=1.49*x+‐6.02;Rsq=0.91y=1.46*x+‐6.61;Rsq=0.85y=1.25*x+‐8.03;Rsq=0.85y=1.33*x+‐11.91;Rsq=0.85y=1.2*x+‐7.04;Rsq=0.77y=1.06*x+5.99;Rsq=0.65y=0.87*x+25.82;Rsq=0.55y=1.06*x+8.1;Rsq=0.62y=1.21*x+‐2.64;Rsq=0.75y=1.22*x+‐2.26;Rsq=0.89y=1.53*x+‐12.49;Rsq=0.91y=1.56*x+‐13.07;Rsq=0.92Baltimore,MDy=1.28*x+‐8.03;Rsq=0.88y=1.65*x+‐31.13;Rsq=0.84y=1.47*x+‐17.1;Rsq=0.79y=1.03*x+0.11;Rsq=0.79y=1.05*x+6.54;Rsq=0.62y=1.23*x+‐6.26;Rsq=0.7y=1.1*x+‐1.47;Rsq=0.74y=1.09*x+7.77;Rsq=0.85y=1.33*x+‐8.8;Rsq=0.81y=1.49*x+‐7.7;Rsq=0.72y=1.69*x+‐15.94;Rsq=0.94y=1.34*x+‐5.56;Rsq=0.71Birmingham,ALy=1.29*x+‐5.86;Rsq=0.8y=1.31*x+‐7.3;Rsq=0.85y=1.11*x+‐5.08;Rsq=0.89y=1.05*x+‐2.93;Rsq=0.85y=1.06*x+‐6.34;Rsq=0.9y=1*x+‐2.72;Rsq=0.82y=1.09*x+‐0.42;Rsq=0.77y=0.95*x+2.44;Rsq=0.77y=1.16*x+‐13.85;Rsq=0.8y=1.24*x+‐7.38;Rsq=0.87y=1.17*x+‐5;Rsq=0.89y=1.2*x+‐0.63;Rsq=0.92Dallas,TXy=1.69*x+‐8.95;Rsq=0.84y=1.94*x+‐21.97;Rsq=0.88y=1.54*x+‐13.47;Rsq=0.79y=1.34*x+‐10.87;Rsq=0.75y=1.16*x+‐2.83;Rsq=0.69y=0.86*x+3.04;Rsq=0.74y=0.86*x+3.72;Rsq=0.75y=0.96*x+‐2.36;Rsq=0.7y=1.04*x+‐2.03;Rsq=0.71y=1.19*x+‐2.94;Rsq=0.81y=1.15*x+‐2.83;Rsq=0.8y=1.68*x+‐10.83;Rsq=0.92Detroit,MIy=1.18*x+13.01;Rsq=0.7y=1.26*x+5.26;Rsq=0.84y=1.12*x+7.51;Rsq=0.66y=1.17*x+‐5.53;Rsq=0.85y=0.79*x+11.4;Rsq=0.82y=0.78*x+14.2;Rsq=0.84y=0.99*x+8.98;Rsq=0.73y=1.22*x+1.21;Rsq=0.55y=1.22*x+‐11.05;Rsq=0.72y=1.42*x+‐6.44;Rsq=0.79y=1.7*x+‐24.85;Rsq=0.91y=1.14*x+18.66;Rsq=0.76Fresno,CAy=1.2*x+2.75;Rsq=0.82y=1.28*x+1.8;Rsq=0.84y=1.46*x+‐0.46;Rsq=0.83y=1.29*x+‐2.15;Rsq=0.66y=0.98*x+4.24;Rsq=0.54y=1.01*x+‐1.51;Rsq=0.68y=0.94*x+‐1.1;Rsq=0.93y=1.13*x+‐5.1;Rsq=0.73y=1.24*x+‐4.61;Rsq=0.73y=1.63*x+‐8.37;Rsq=0.7y=1.23*x+9.65;Rsq=0.81y=1.31*x+3.3;Rsq=0.87Houston,TXy=1.29*x+‐2.32;Rsq=0.87y=1.35*x+‐6.35;Rsq=0.81y=1.23*x+‐7.63;Rsq=0.85y=1.38*x+‐18.36;Rsq=0.82y=1.33*x+‐19.81;Rsq=0.76y=1.07*x+‐2.13;Rsq=0.77y=0.54*x+20.69;Rsq=0.57y=0.75*x+11.34;Rsq=0.43y=1.21*x+‐12.05;Rsq=0.82y=1.3*x+‐10.7;Rsq=0.95y=1.21*x+‐7.66;Rsq=0.86y=1.32*x+‐4.95;Rsq=0.88LosAngeles,CAy=1.45*x+‐6.19;Rsq=0.87y=1.22*x+3.21;Rsq=0.85y=1.26*x+6.69;Rsq=0.79y=1.43*x+‐6.52;Rsq=0.78y=1.41*x+‐3.21;Rsq=0.78y=1.72*x+‐25.83;Rsq=0.56y=1.24*x+4.44;Rsq=0.57y=1.59*x+‐21.91;Rsq=0.49y=1.42*x+‐7.87;Rsq=0.71y=1.46*x+‐14.3;Rsq=0.81y=1.49*x+‐12.55;Rsq=0.86y=1.18*x+6.72;Rsq=0.85NewYork,NYy=1.5*x+‐14.28;Rsq=0.89y=1.16*x+‐5.06;Rsq=0.92y=1.39*x+‐5.96;Rsq=0.87y=1.22*x+‐1.7;Rsq=0.89y=1.2*x+‐2.33;Rsq=0.8y=1.36*x+‐9.36;Rsq=0.78y=1.17*x+0.71;Rsq=0.65y=1.29*x+‐13.03;Rsq=0.79y=1.37*x+‐5.7;Rsq=0.89y=1.89*x+‐21.18;Rsq=0.83y=1.42*x+‐0.51;Rsq=0.92y=1.3*x+0.85;Rsq=0.86Draft – Do Not Quote or CiteJune 20104B-28Philadelphia,PAy=1.38*x+‐9.12;Rsq=0.76y=1.1*x+2.37;Rsq=0.78y=1.03*x+1.61;Rsq=0.83y=0.81*x+7.81;Rsq=0.68y=0.88*x+4.55;Rsq=0.85y=0.97*x+3.07;Rsq=0.78y=1.03*x+1.63;Rsq=0.82y=0.79*x+34.86;Rsq=0.69y=0.8*x+10.76;Rsq=0.64y=1.01*x+8.02;Rsq=0.86y=1.3*x+‐0.08;Rsq=0.85y=1.06*x+10.34;Rsq=0.74Phoenix,AZy=0.83*x+‐2.5;Rsq=0.89y=0.76*x+‐1.53;Rsq=0.97y=0.65*x+1.46;Rsq=0.96y=0.56*x+2.12;Rsq=0.92y=0.6*x+1.7;Rsq=0.88y=0.62*x+1.11;Rsq=0.96y=0.5*x+5.73;Rsq=0.61y=0.69*x+0.51;Rsq=0.97y=0.6*x+0.85;Rsq=0.95y=0.6*x+2.35;Rsq=0.58y=0.76*x+‐0.91;Rsq=0.91y=0.97*x+‐2.04;Rsq=0.89Pittsburgh,PAy=1.6*x+‐7.31;Rsq=0.75y=1.22*x+0.13;Rsq=0.76y=1.19*x+‐2.09;Rsq=0.76y=1.06*x+0.19;Rsq=0.74y=1.06*x+0.15;Rsq=0.56y=0.97*x+11.89;Rsq=0.67y=1.06*x+10.46;Rsq=0.51y=1.28*x+‐9.71;Rsq=0.74y=1.18*x+‐2.72;Rsq=0.62y=1.16*x+2.65;Rsq=0.72y=1.4*x+‐9.05;Rsq=0.82y=1.47*x+‐6.84;Rsq=0.83SaltLakeCity,UTy=1.38*x+‐4.78;Rsq=0.93y=1.25*x+‐0.98;Rsq=0.91y=1.23*x+‐0.88;Rsq=0.87y=0.92*x+2.06;Rsq=0.75y=0.73*x+4.3;Rsq=0.69y=0.83*x+2.89;Rsq=0.79y=0.9*x+0.11;Rsq=0.98y=0.88*x+‐0.16;Rsq=0.96y=0.79*x+5.83;Rsq=0.87y=1.1*x+2.23;Rsq=0.82y=1.06*x+2.81;Rsq=0.92y=1.12*x+9.19;Rsq=0.94StLouis,,MOy=1.5*x+‐0.2;Rsq=0.9y=1.7*x+‐23.42;Rsq=0.87y=1.79*x+‐23.76;Rsq=0.83y=1.29*x+‐5.93;Rsq=0.69y=1.24*x+‐7.67;Rsq=0.73y=0.88*x+8.95;Rsq=0.74y=1.12*x+‐5.02;Rsq=0.75y=1.07*x+‐2.69;Rsq=0.72y=1.03*x+2.61;Rsq=0.74y=1.71*x+‐15.49;Rsq=0.79y=1.67*x+‐14.71;Rsq=0.94y=1.75*x+‐15.12;Rsq=0.81Tacoma,WAy=1.11*x+2.25;Rsq=0.98y=1.51*x+‐2.18;Rsq=0.94y=1.28*x+0.12;Rsq=0.92y=1.37*x+‐3.6;Rsq=0.86y=1.15*x+‐1.92;Rsq=0.71y=1.1*x+2.17;Rsq=0.63y=1.03*x+2.64;Rsq=0.81y=1.3*x+‐2.74;Rsq=0.68y=1.07*x+2.74;Rsq=0.84y=1.35*x+‐0.62;Rsq=0.92y=1.37*x+‐2.65;Rsq=0.98y=1.17*x+2.34;Rsq=0.96Draft-Do Not Quote or Cite June 2010 4C-1 

### Appendix 4C 1



### Assessment of the PM Components Re sponsible for the Largest Hourly PM 10 2 

### Light Extinction and PM 2.5 

### Mass Hours Selected as Maximum Daily and 3 

### Using All Hours for 14 Urban Areas 4
5

As discussed in the UFVA, light extinction is considered a better indicator of visibility 6 impacts than PM 2.5 mass concentration. The UFVA also considers two different forms: the 7 maximum daily and all daylight hours for possi ble use in a secondary PM NAAQS to protect 8 visibility. One way to explore th e ramifications of the selection of indicator and form is to assess 9 how much difference these choices make to the type s of sources that might need to be controlled 10 to improve visibility conditions. The purpose of this assessment is to provide a better 11 understanding of the dependency of the mix of PM components (i.e ., a reflection of the types of 12 sources) responsible for the high haze values on th e choice of form and indicator used. This was 13 done using the hourly PM 10 light extinction and PM 2.5 speciated mass composition data set as 14 developed for the UFVA for the 14 urban areas 1 . As was demonstrated in the UFVA (section 15 4.1.4) for PM 10 light extinction, the 90 th percentile maximum daily daylight hour has design 16 values that are nearly identical to the 98 th percentile of all daylight hours for each of the urban 17
areas. In order to reduce the numbers of cases for comparison, only these two forms, which give 18 comparable design values, are included in this assessment. 19 Stacked bar plots that show the PM species contributions to PM 10 light extinction for 20 each hour that is in the top 10% of daily maximum daylight hours of PM 10 light extinction and 21 the top 2% of all daylight hours of PM 10 light extinction for each of the urban areas are displayed 22 in Figure 3-13 of the UFVA. These show the com ponents that contribute to light extinction for 23
the hours that would need to be reduced in order to meet the 90 th percentile maximum daily and 24
98 th percentile of all daylight hours PM 10 light extinction. Similar figur es were generated for this 25 comparison to display the mass components of each hour that is in the top 10% daily maximum 26 daylight hours and top 2% of all daylight hours for PM 2.5 mass. To aid making the comparisons, 27 the plots already available in th e UFVA are repeated in this a ppendix and each set of plots is 28 shown both as components contributing to li ght extinction and those contributing to PM 2.5 29 speciated mass concentration. This leads to eight separate stacked bar plots (i.e., 2 indicators x 2 30 forms x 2 component displays) for each of th e 14 urban areas (see Fi gures 4C1 to 4C14). 31

1 Due to the inappropriate coarse mass values developed for the St. Louis dataset, it was excluded in this assessment.Draft-Do Not Quote or Cite June 2010 4C-2 Figure 4C-1 Tacoma PM components contributin g to the top 10% of maximum daily 1-hour PM 10 light 1 extinction (a & b) and PM 2.5 mass (c & d), and to the top 2% of all daylight hours for PM 10 light extinction (e 2 & f) and for PM 2.5 mass (g & h). 3

4Draft-Do Not Quote or Cite June 2010 4C-3 1Draft-Do Not Quote or Cite June 2010 4C-4 Figure 4C-2 Fresno PM components contributin g to the top 10% of maximum daily 1-hour PM 10 light 1 extinction (a & b) and PM 2.5 mass (c & d), and to the top 2% of all daylight hours for PM 10 light extinction (e 2 & f) and for PM 2.5 mass (g & h). 3

4Draft-Do Not Quote or Cite June 2010 4C-5 1

2Draft-Do Not Quote or Cite June 2010 4C-6 Figure 4C-3 Los Angeles PM components contributi ng to the top 10% of maximum daily 1-hour PM 10 light 1 extinction (a & b) and PM 2.5 mass (c & d), and to the top 2% of all daylight hours for PM 10 light extinction (e 2 & f) and for PM 2.5 mass (g & h). 3

4Draft-Do Not Quote or Cite June 2010 4C-7 1Draft-Do Not Quote or Cite June 2010 4C-8 Figure 4C-4 Phoenix PM components contributin g to the top 10% of maximum daily 1-hour PM 10 light 1 extinction (a & b) and PM 2.5 mass (c & d), and to the top 2% of all daylight hours for PM 10 light extinction (e 2 & f) and for PM 2.5 mass (g & h). 3

4Draft-Do Not Quote or Cite June 2010 4C-9 1

2Draft-Do Not Quote or Cite June 2010 4C-10 1

Figure 4C-5 Salt Lake City PM co mponents contributing to the top 10% of maximum daily 1-hour PM 10 light 2 extinction (a & b) and PM 2.5 mass (c & d), and to the top 2% of all daylight hours for PM 10 light extinction (e 3 & f) and for PM 2.5 mass (g & h)

. 4

5Draft-Do Not Quote or Cite June 2010 4C-11 1

2Draft-Do Not Quote or Cite June 2010 4C-12 1

Figure 4C-6 Dallas PM components contributing to the top 10% of maximum daily 1-hour PM 10 light 2 extinction (a & b) and PM 2.5 mass (c & d), and to the top 2% of all daylight hours for PM 10 light extinction (e 3 & f) and for PM 2.5 mass (g & h). 4

5Draft-Do Not Quote or Cite June 2010 4C-13 1

2Draft-Do Not Quote or Cite June 2010 4C-14 1

Figure 4C-7 Houston PM components contributing to the top 10% of maximum daily 1-hour PM 10 light 2 extinction (a & b) and PM 2.5 mass (c & d), and to the top 2% of all daylight hours for PM 10 light extinction (e 3 & f) and for PM 2.5 mass (g & h). 4

5Draft-Do Not Quote or Cite June 2010 4C-15 1

2Draft-Do Not Quote or Cite June 2010 4C-16 1

Figure 4C-8 Birmingham PM compon ents contributing to the top 10% of maximum daily 1-hour PM 10 light 2 extinction (a & b) and PM 2.5 mass (c & d), and to the top 2% of all daylight hours for PM 10 light extinction (e 3 & f) and for PM 2.5 mass (g & h). 4

5Draft-Do Not Quote or Cite June 2010 4C-17 1Draft-Do Not Quote or Cite June 2010 4C-18 1

Figure 4C-9 Atlanta PM componen ts contributing to the top 10 % of maximum daily 1-hour PM 10 light 2 extinction (a & b) and PM 2.5 mass (c & d), and to the top 2% of all daylight hours for PM 10 light extinction (e 3 & f) and for PM 2.5 mass (g & h). 4

5Draft-Do Not Quote or Cite June 2010 4C-19 1

2Draft-Do Not Quote or Cite June 2010 4C-20 1

Figure 4C-10 Detroit PM components contributin g to the top 10% of maximum daily 1-hour PM 10 light 2 extinction (a & b) and PM 2.5 mass (c & d), and to the top 2% of all daylight hours for PM 10 light extinction (e 3 & f) and for PM 2.5 mass (g & h). 4

5Draft-Do Not Quote or Cite June 2010 4C-21 1

2Draft-Do Not Quote or Cite June 2010 4C-22 1

Figure 4C-11 Baltimore PM components contributin g to the top 10% of maximum daily 1-hour PM 10 light 2 extinction (a & b) and PM 2.5 mass (c & d), and to the top 2% of all daylight hours for PM 10 light extinction (e 3 & f) and for PM 2.5 mass (g & h). 4

5Draft-Do Not Quote or Cite June 2010 4C-23 1

2Draft-Do Not Quote or Cite June 2010 4C-24 1

Figure 4C-12 Pittsburgh PM components contributi ng to the top 10% of maximum daily 1-hour PM 10 light 2 extinction (a & b) and PM 2.5 mass (c & d), and to the top 2% of all daylight hours for PM 10 light extinction (e 3 & f) and for PM 2.5 mass (g & h). 4

5Draft-Do Not Quote or Cite June 2010 4C-25 1

2Draft-Do Not Quote or Cite June 2010 4C-26 1

Figure 4C-13 Philadelphia PM components contributing to the top 10% of maximum daily 1-hour PM 10 light 2 extinction (a & b) and PM 2.5 mass (c & d), and to the top 2% of all daylight hours for PM 10 light extinction (e 3 & f) and for PM 2.5 mass (g & h). 4

5Draft-Do Not Quote or Cite June 2010 4C-27 1

2Draft-Do Not Quote or Cite June 2010 4C-28 1

Figure 4C-14 New York City PM components contribu ting to the top 10% of maximum daily 1-hour PM 10 2 light extinction (a & b) and PM 2.5 mass (c & d), and to the top 2% of all daylight hours for PM 10 light 3 extinction (e & f) and for PM 2.5 mass (g & h). 4

5Draft-Do Not Quote or Cite June 2010 4C-29 1

2Draft-Do Not Quote or Cite June 2010 4C-30 In each set of the 8 stacked bar plots, the plots labeled (a) and (b) are the PM 10 light 1 extinction and PM 2.5 mass components for hours selected as the top 10 percent of the maximum 2 daily PM 10 light extinction; and the plot s labeled (c) and (d) are the PM 2.5 mass and PM 10 light 3 extinction components for the hours selected as the top 10 percent of the maximum daily PM 2.5 4 mass concentration. The plots labeled (e) throug h (h) are in the same order as (a) through (d) 5 except these hours were selected based on their be ing in the top 2% of all daylight hours for 6
PM 10 light extinction (e) and (f), and th e top 2% of all daylight hours for PM 2.5 mass (g) and (h). 7 In other words, there are four unique selections of hours based on two diff erent indicators (i.e., 8
PM 10 light extinction and PM 2.5 mass) and two different forms (i.e. top 10% of maximum hourly 9 and top 2% of all daylight hours). Each of these four selections of hours is displayed first as the 10 components of the indicator used to make the selection, then in the following plot as the 11 components of the indicator not used in the selection of the hours. 12

Three sets of comparisons are possible using the plots in Figures 4C1 to 4C14. The first 13 two are the comparisons of the PM composition for hours selected for the two PM indicators 14 (i.e., light extinction and mass) and the two forms (i.e., 90 th percentile maximum daily and 98 th 15 percentile of all daylighthours). The key difference for these first two types of comparisons has 16 to do with the PM components for the hours select ed by these four combinations of indicator and 17 form. The third set of comparisons is the apportionments of components using PM 10 light 18 extinction versus using PM 2.5 mass where the hours selected are identical. 19 For any selected hour, the rela tive contributions of component s to PM mass is not the 20
same as the relative contributi ons of the components to PM light extinction because of the 21 differing light extinction efficien cies of the components. Simila rly, the relative importance of 22 the hygroscopic PM components (i.e., PM sulfates and nitrates) compared to that of the non23 hygroscopic components (i.e. primarily organic a nd elemental carbon) to PM mass is generally 24 different than it is to PM light extinction and that difference ch anges as a function of relative 25 humidity. 26 Indicator Comparisons: To assess the similarity of li ght extinction components selected 27 by the two indicators compare plot s (a) and (d) for the daily maximum form, as well as plots (e) 28 and (h) for the all hours form for each urban ar ea. A corresponding set of comparisons of the 29 PM components can be done by comparing plots (b) and (c), as well as plot s (f) and (g) for each 30
urban area. For each of the urban areas there are multiple examples of identical or very nearly 31 identical contributions among the top contributors for PM 10 light extinction and PM 2.5 mass. A 32
more careful examination shows that the two indi cators have selected th e same hour or another 33 hour during the same day as top contributors (note that the dates and times are listed below each 34 stacked bar). 35 To more efficiently identify the degree to which common and unique periods are selected 36 by the two indicators, Table 4C-1 lists the numbe rs of common and unique days selected by the 37Draft-Do Not Quote or Cite June 2010 4C-31 two. The greater the number of common days co mpared to the number of unique days, the more 1 similar are the components of PM selected by th e two indicators. For example, Tacoma, Fresno, 2 Salt Lake City, Birmingham and New York each have almost twice as many common days as 3 unique day for the maximum daily form, though only Tacoma and Fresno have this characteristic 4
for the all hours form. Most of the other urba n areas have nearly comparable number of unique 5 and common days for the 1-hour maximum daily fo rm, and comparable to as much as three 6 times (Dallas) the number of unique days compar ed to common days for the all hours form. 7 Locations with relatively large numbers of uniqu e days selected are more likely to have the 8 greatest differences of the mix of PM components. For example, Los Angeles and Dallas have 9 greater contributions by organics when PM 2.5 mass is the indicator than when PM 10 light 10 extinction is used. In addition, many of the eastern urban areas have higher contributions of 11 organics and less contributi ons by PM nitrate when PM 2.5 mass is the indicator than when PM 10 12 light extinction is used. 13 Even if the unique hours selected by PM 2.5 mass have similar composition they 14 necessarily have lower light extin ction than those selected based on being in the top percentage 15 of light extinction. This can be seen by compar ing the magnitude of the lowest selected light 16 extinction hour in plots (a) or (e) with the light extinction valu es for the hours selected using 17

PM 2.5 mass in corresponding plots (d) or (h) for Figur es 4C-1 to 4C-14. For example, notice that 18 for Birmingham (Figure 4C-8) th ere are many hours selected by PM 2.5 mass with light extinction 19
values well below the minimum PM 10 light extinction value for hours selected based on PM 10 20 light extinction (i.e. compare (d) to (a) and (h) to (e)). 21Draft-Do Not Quote or Cite June 2010 4C-32 1 Table 4C-1 The numbers of common and unique days selected for each urban area 2 comparing PM 10 light extinction versus PM 2.5 mass for the top 10% of daily maximum and 3 for the top 2% of all hours. 4

10% maximum 2% all hours

common unique common unique

Tacoma 9 4 11 6

Fresno 27 10 20 10

Los Angeles 18 24 14 38

Phoenix 5 8 9 18

Salt Lake City 25 12 14 12

Dallas 17 20 13 43

Houston 11 7 16 23

Birmingham 27 16 32 26

Atlanta 18 19 19 27

Detroit 9 10 8 22

Baltimore 12 12 6 22

Pittsburgh 19 18 16 30

Philadelphia 9 10 8 17

New York City 18 10 17 16

5

Form Comparisons: A similar set of comparisons of PM component mixtures can be 6
made between hours selected base d on their being in the top 10% of daily maximum or the top 7 2% of all daylight hours. For Figures 4C-1 to 4C-14 composition displayed in plots labeled (a) 8 and (e) for the PM 10 light extinction indicator and (c) and (g) for the PM 2.5 indicator can be 9 compared. Some of the same hours are select ed by both forms. By definition the top 10% 10 maximum daily hour form never has more than 1 hour selected per day. There are very nearly 11 twice as many hours in the top 2% of all hours compared to the top 10% of maximum daily 12Draft-Do Not Quote or Cite June 2010 4C-33 hours. However, it is not unusual to have multip le hours selected in the same day by the top 2% 1
of all hours form. These hours selected in th e same day tend to have nearly identical 2 composition (e.g., Figure 4C-1 (e) has 4 consecutive hours on 11/08/2007, which is also selected 3 with a 10% maximum daily form (a)). The top 2% of all hours may select hours on a greater 4 number of days compared with the top 10% of maximum daily hours, or if there are enough 5 instances of multiple hours per day, it could se lect hours on a smaller number of days compared 6 with the top 10% of maximum daily hours. A list of the numbers of common and unique days 7 selected comparing the two forms for both indica tors and the number of days selected by each 8
combination of indicator and form is shown in Table 4C-2. 9 In addition to affecting the component mixtur e for the top hours selected, the number of 10 multiple hours per day selected among the top 2% of all hours affects whether its design values 11 are greater than or less than the corresponding design values for the top 10% of maximum daily 12 hours. If the number of multiple hours per day is small enough that the 2% of all hours form has 13 more days selected than the top 10 percent of all hours, then the design value for the 2% form is 14 smaller than that of the 10% daily maximum form . An example of this is light extinction for 15 Birmingham where the 2% of all hours form selects hours on 47 days and has a PM light 16 extinction design value of 309 Mm -1 compared to the 35 days that have hours in the top 10% of 17 daily maximum light extincti on with a design value of 357 Mm -1 . Among the 14 urban areas, 18 Salt Lake City light extinction is the most extr eme example of the opposite situation with only 16 19 days having the top 2% of all hours and a design value of 225 Mm -1 compared with 31 days 20 selected by the top 10% maximum daily li ght extinction and a design value of 164 Mm -1

. 21
For most of the urban areas the number of co mmon days is much larger than the number 22 of unique days. Generally, the PM component mix is less similar for sites with a lower number 23 of common and a greater number of unique days. For example, the 2% of all hours form for Salt 24 Lake City selected only one hour of one of the days where the PM carbonaceous components 25 was the major contributor compared with the 4 hours with high PM carbonaceous components 26 selected in the top 10% of the maximum daily form (compare Figure 4C-5 (a) with (e)). By 27 comparison for Salt Lake City most of the multip le hours in single days had high contributions 28 from PM nitrate. Composition of the hours select ed for the two forms by either indicator are 29 generally very similar. To f acilitate comparisons among the PM component contributions for the 30 two forms and indicators, Figure 4C-15 shows st acked bar plots of the average PM component 31 contributions by city. 32Draft-Do Not Quote or Cite June 2010 4C-34 Table 4C-2 The numbers of common and unique days selected for each urban area comparing the top 10% 1 of 1-hr daily maximum to the top 2% of all hours for PM 10 light extinction and PM 2.5 mass indicators. Also 2 shown are the number of days select ed for each form and indicator. 3

PM 10 Light Extinction PM 2.5 Mass

10% vs. 2% Number of days 10% vs. 2% Number of days

common unique 10% 2% common unique 10% 2%

Tacoma 11 3 11 14 11 1 11 12

Fresno 25 7 32 25 20 12 32 20

Los Angeles 30 8 30 38 18 12 30 18

Phoenix 9 6 9 14 9 5 9 14

Salt Lake City 16 15 31 16 18 13 31 18

Dallas 25 2 27 25 23 4 27 23

Houston 14 11 14 23 15 8 15 23

Birmingham 35 14 35 47 35 1 35 46

Atlanta 27 6 27 33 27 1 28 27

Detroit 13 1 14 13 13 1 14 13

Baltimore 12 6 18 12 11 7 18 11

Pittsburgh 28 3 28 31 24 4 28 24

Philadelphia 14 0 14 14 12 2 14 12

New York City 23 0 23 23 19 4 23 19

4Draft-Do Not Quote or Cite June 2010 4C-35 1
Figure 4C-15 Average by ur ban areas of the PM components contribu ting to the top 10% of maximum daily 2 1-hour PM 10 light extinction (a & b) and PM 2.5 mass (c & d), and to the top 2% of all daylight hours for PM 10 3 light extinction (e & f) and for PM 2.5 mass (g & h). 4

5Draft-Do Not Quote or Cite June 2010 4C-36 1

2Draft-Do Not Quote or Cite June 2010 4C-37 As discussed above the greatest differences be tween the two forms is for Salt Lake City. 1 For most of the 14 urban areas, the differences in results comparing the two forms are minor 2 (compare (a) to (e) and (c) to (g)). Figure 4C -15 also facilitates comp arisons of the average 3 effects on PM component mixtures depending on which of the two indicators is used (compare 4 (a) to (d) and (e) to (h)). It shows that the difference in PM co mponent contributions differ more 5 depending on the choice of indicat or than the choice of form. 6

Component Apportionment Comparisons: This is the simplest of the three types of 7 comparisons because the exact same hours are comp ared and the only difference is in the relative 8 contributions of the components to PM 10 light extinction compared to the relative component 9
contributions to PM 2.5 mass. To see these differences for individual hours or averages by urban 10 areas compare plots labeled (a) and (b), (c) and (d), (e) and (f), or (g) and (h) in Figures 4C-1 to 11 4C-15. The differences directly result from the application of the IMPROVE algorithm which 12 weights the various PM mass components differe ntly when expressing them as components of 13 light extinction. For example, no tice that the soil component of PM 10 light extinction is barely 14 discernable for Birmingham and Detroit, but is easily discerned as a component of PM 2.5 mass. 15 In many of the urban areas the relative contri butions by soil and organic mass PM components 16 are greater and the relative contributions by elem ental carbon, sulfate and nitrate components are 17 less when expressed as contributions to PM 2.5 mass than when expressed as PM 10 light 18
extinction. 19 The differences in the relative apportionment of the PM components are of concern when 20 emission control efforts are designed to reduce visibility impacts. Use of the relative 21 contribution by PM 10 light extinction components recognizes that some PM components cause 22 more visibility impacts per unit of mass concentration, whereas th e use of relative contributions 23

to PM 2.5 mass treat the most and least effective co mponents as though they contributed equally 24 on a per unit mass contribution basis. 25This page left intentionally blank.United StatesEnvironmental ProtectionAgencyOffice of Air Quality Planning and StandardsHealth and Environmental Impacts DivisionResearch Triangle Park, NCPublication No. EPA-452/P-10-007June 2010