# Review of the National Ambient Air Quality Standards for Ozone:

Policy Assessment of Scientific and Technical Information

OAQPS Staff PaperEPA-452/R-07-007 July 2007



## REVIEW OF THE NATIONAL AMBIENT AIR QUALITY STANDARDS FOR OZONE:

POLICY ASSESSMENT OF SCIENTIFIC AND TECHNICAL INFORMATION

OAQPS STAFF PAPER

U.S. Environmental Protection Agency Office of Air Quality Planning and Standards Research Triangle Park, North CarolinaDISCLAIMER

This document has been reviewed by the Office of Air Quality Planning and Standards (OAQPS), U.S. Environmental Protection Agency (EPA), and approved for publication. This final OAQPS Staff Paper contains the conclusions and recommendations of staff of OAQPS and does not necessarily represent those of the EP A. Mention of trade names or commercial products is not intended to constitute endorsement or recommendation for use.PREFACE TO JULY 2007 EDITION

The purpose of this July 2007 edition is to include the March 26, 2007 letter from the Clean Air Scientific Advisory Committ ee (CASAC) to the Administrator providing its final comments and advice on the January 2007 edition of the OAQPS Staff Paper. The CASAC letter has been include d as an Attachment to this edition (Attachment B). In addition, this edition of the Staff Paper in cludes technical corrections to the exposure model resulting in revised exposure estimates and revised lung function risk estimates. As noted in chapters 4 and 5 of this edition of the Staff Paper, a small error was detected in the exposure model in January 2007 that resulted in small increases in the exposure estimates. This error has been corrected a nd the model runs have been redone, generally resulting in small increases in the exposure es timates. The corrected results are presented in this edition of the Staff Paper and in the revised Exposure Anal ysis technical support document. The lung function risk estimates al so have been redone based on the corrected exposure estimates and are generally slightly hi gher than the original estimates presented in the January 2007 edition of the Staff Paper. The corrected lung function risk estimates are presented in this edition of the Staff Paper and in the revised Risk Assessment technical support document. Also, Figure 3-4 on page 3-56 has been modified to include a legend of the studies used to create the figur e. Additional minor edits to Chapters 4 and 5 are listed in the errata.ACKNOWLEDGMENTS

This Staff Paper is the product of the Of fice of Air Quality Planning and Standards (OAQPS). For the chapters on ozone-related health effects, exposure, risk, and primary standards, the principal author s include Karen Martin, David McKee, Harvey Richmond, Susan Lyon Stone, and John Langstaff. For the chap ters on ozone-related welfare effects and secondary standards, the princi pal authors include Vicki Sandifo rd and Jeffrey Herrick. The principal authors of the chap ter on air quality characteriza tion include Lance McCluney and Michael Rizzo. Staff from other EPA offi ces, including the Office of Research and Development, the Office of General Counsel, an d the Office of Transportation and Air Quality, also provided valuable comments. Earlier drafts of this document were formally reviewed by the Clean Air Scientific Advisory Committee (CASAC) and made availabl e for public comment. This document has been informed by the expert advice and comment s received from CASAC, as well as by public comments submitted by a number of independent scientists, officials from State and local air pollution organizations, environmental groups , and industrial groups and companies.i 

### Table of Contents

List of Tables ................................................................................................................. ................ ix

List of Figures................................................................................................................ ............... xii

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

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1.1 PURPOSE.................................................................................................................. 1- 1
1.2 BACKGROUND ....................................................................................................... 1-2 1.2.1 Legislative Requirements................................................................................. 1-2 1.2.2 History of Ozone NAAQS Reviews ................................................................ 1-3 1.2.3 Litigation Related to the 1997 Ozone Standards ............................................. 1-4 1.2.4 Current Ozone NAAQS Review...................................................................... 1-5
1.3 GENERAL APPROACH AND ORGANI ZATION OF THE DOCUMENT........... 1-7
REFERENCES ..................................................................................................................... . 1-9

2. AIR QUALITY CHARACTERIZATION .................................................................. 2-1

2.1 INTRODUCTION ..................................................................................................... 2-1
2.2 CHEMICAL AND PHYSICAL PR OPERTIES, FORMATION, AND TRANSPORT ............................................................................................................ 2-1 2.2.1 Properties and Formation................................................................................. 2-1 2.2.2 Relationship of Ozone to Photochemical Oxidants ......................................... 2-7 2.2.3 Transport..........................................................................................................2-7
2.3 DATA SOURCES ..................................................................................................... 2-9 2.3.1 Air Quality System (AQS)............................................................................... 2-9 2.3.2 CASTNET...................................................................................................... 2-10
2.4 OZONE MONITORING METHOD S AND DATA QUALITY ............................ 2-12 2.4.1 Effect of Measurement Precisi on on 8 hour Ozone Averages.......................2-12
2.5 CHARACTERIZATION OF GROUND-LEVEL OZONE CONCENTRATIONS ............................................................................................. 2-13 2.5.1 Metrics ...........................................................................................................2-13 2.5.2 Spatial Variability .......................................................................................... 2-15 2.5.2.1 Distributions of 1-hr, 8-hr, and 24-hr Ozone Metrics...............................2-15 2.5.2.2 8-Hour and 1-Hour Statistics ....................................................................2-19 2.5.2.3 Cumulative Concentration-Weighted Statistics........................................ 2-19 2.5.3 Temporal Variability...................................................................................... 2-30 2.5.3.1 Long Term Variability – Trends............................................................... 2-30 2.5.3.2 Short Term Variability – Annual .............................................................. 2-35 2.5.3.3 Seasonal Variability.................................................................................. 2-35 2.5.3.4 Short Term Variability – Diurnal.............................................................. 2-35ii 2.6 CHARACTERIZATION OF OZONE EPISODES................................................. 2-39
2.7 POLICY RELEVANT BA CKGROUND LEVELS................................................ 2-48
REFERENCES .................................................................................................................... 2 -56

3. POLICY-RELEVANT ASSESSMENT OF HEALTH EFFECTS
EVIDENCE .................................................................................................................... 3-1

3.1 INTRODUCTION ..................................................................................................... 3-1
3.2 MECHANISMS OF TOXICITY............................................................................... 3-3
3.3 NATURE OF EFFECTS............................................................................................ 3-3 3.3.1 Morbidity .........................................................................................................3-4 3.3.1.1 Effects on the Respiratory System from Short-term Exposures .................3-4 3.3.1.2 Effects on the Respiratory System from Long-term Exposures ...............3-20 3.3.1.3 Effects on the Cardiovascular System ...................................................... 3-26 3.3.2 Premature Mortality....................................................................................... 3-27 3.3.2.1 Mortality and Short-term O 3 Exposure.....................................................3-27 3.3.2.2 Mortality and Long-term O 3 Exposure .....................................................3-34 3.3.3 Ozone Effects on UV-B Flux......................................................................... 3-36 3.3.4 Summary........................................................................................................ 3-36
3.4 ASSESSMENT OF EVIDENCE FROM EPIDEMIOLOGICAL STUDIES ......... 3-37 3.4.1 Strength of Associations ................................................................................ 3-38 3.4.2 Robustness of Associations............................................................................ 3-39 3.4.2.1 Exposure Error.......................................................................................... 3-39 3.4.2.2 Confounding by Copollutants...................................................................3-42 3.4.2.3 Model Specification.................................................................................. 3-44 3.4.3 Consistency....................................................................................................3-45 3.4.4 Lag Structure in Short-term Exposure Studies .............................................. 3-45 3.4.5 Concentration-Response Relationshi ps and Potential Thresholds.................3-46 3.4.6 Health Effects of Polluta nt Mixtures Containing O 3 ..................................... 3-48
3.5 BIOLOGICAL PLAUSIBILITY AND COHERENCE OF EVIDENCE ............... 3-50 3.5.1 Animal-to-Human Extr apolation Issues ........................................................ 3-51 3.5.2 Coherence and Plausibility of S hort-term Effects on the Respiratory System...........................................................................................................3-55 3.5.3 Coherence and Plausibility of Eff ects on the Cardiovascular System........... 3-58 3.5.4 Coherence and Plausibility of Effects Related to Long-Term O 3 Exposure........................................................................................................ 3-60 3.5.5 Coherence and Plausibility of S hort-Term Mortality-Related Health Endpoints ...................................................................................................... 3-61
3.6 OZONE-RELATED IMPACTS ON PUBLIC HEALTH ....................................... 3-62 3.6.1 Factors that Modify Re sponsiveness to Ozone..............................................3-63 3.6.2 Susceptible Population Groups......................................................................3-64 3.6.2.1 Active People............................................................................................ 3-64 3.6.2.2 People with Lung Disease......................................................................... 3-66 3.6.2.3 Children and Older Adults........................................................................3-69iii 3.6.2.4 People with Increased Responsiveness to Ozone ..................................... 3-70 3.6.2.5 Other Population Groups .......................................................................... 3-71 3.6.3 What Constitutes an Adverse Health Impact from Ozone Exposure?........... 3-72 3.6.4 Estimation of Potential Numbers of People in At-Risk Susceptible Population Groups in the United States ........................................................3-78
3.7 SUMMARY AND CONCLUSIONS FOR OZONE HEALTH EFFECTS ............3-79 3.7.1 Respiratory Morbidity Effects of Short-term Exposures to Ozone ............... 3-80 3.7.2 Cardiovascular Morbidity Effects of Short-term Exposures to Ozone.......... 3-83 3.7.3 Mortality-Related Effects of Short-term Exposures to Ozone....................... 3-84 3.7.4 Health Effects of Repeated S hort-term Exposures to Ozone.........................3-85 3.7.5 Confidence in Various Health Outc omes Associated with Short-term Exposures to Ozone ...................................................................................... 3-86 3.7.6 Health Effects of Long-term Exposures to Ozone......................................... 3-87 3.7.7 Health Effects of Pollutant Mixtures Containing Ozone ...............................3-89 3.7.8 Populations at Risk/Susceptibility Factors Associated with Ozone Exposure........................................................................................................ 3-90 REFERENCES .................................................................................................................... 3 -91

4. CHARACTERIZATION OF HUMAN EXPOSURE TO OZONE .......................... 4-1

4.1 INTRODUCTION ..................................................................................................... 4-1
4.2 OZONE EXPOSURE STUDIES............................................................................... 4-2 4.2.1 Exposure Concepts and Definitions.................................................................4-2 4.2.2 Monitoring Equipment Considerations............................................................ 4-4 4.2.3 Personal Ozone Exposure Assessment Studies................................................ 4-5 4.2.4 Microenvironment al Studies............................................................................4-5
4.3 EXPOSURE MODELING......................................................................................... 4-6 4.3.1 The APEX Model ............................................................................................ 4-6 4.3.2 Key Algorithms.............................................................................................. 4-11 4.3.3 Model Output................................................................................................. 4-12 4.3.4 Strengths and Limitations of the Model......................................................... 4-13 4.3.4.1 Estimation of Ambient Air Quality........................................................... 4-14 4.3.4.2 Estimation of Concentrations inIndoor Microenvironments ................... 4-15 4.3.4.3 Characterization of Population Demo graphics and Activ ity Patterns ......4-16 4.3.4.4 Modeling Physiological Processes............................................................ 4-17
4.4 SCOPE OF EXPOSURE ASSESSMENT............................................................... 4-18 4.4.1 Selection of Urban Areas to be Modeled....................................................... 4-18 4.4.2 Time Periods Modeled................................................................................... 4-18 4.4.3 Populations Modeled ..................................................................................... 4-18
4.5 INPUTS TO THE EXPOSURE MODEL................................................................ 4-20 4.5.1 Population Demographics.............................................................................. 4-20 4.5.2 Population Commuting Patterns .................................................................... 4-21 4.5.3 Human Activity Data ..................................................................................... 4-22 4.5.4 Physiological Data ......................................................................................... 4-24iv 4.5.5 Microenvironments Modeled......................................................................... 4-24 4.5.5.1 Air Exchange Rates for Indoor Residential Environments....................... 4-24 4.5.5.2 AER Distributions for Other Indoor Environments.................................. 4-26 4.5.5.3 Proximity and Penetration Factor s for Outdoors and In-vehicle .............. 4-27 4.5.5.4 Ozone Decay and Deposition Rates..........................................................4-27 4.5.6 Meteorological Data....................................................................................... 4-27 4.5.7 Ambient Ozone Concentrations..................................................................... 4-28 4.5.8 Modeling Alternative Standards .................................................................... 4-28 4.6 MODEL EVALUATION, SENSITIVITY, & UNCERTAINTY ANALYSES ..... 4-30 4.6.1 Comparison with Exposure Estimates from the Prior Review ......................4-30 4.6.2 Comparison of Model Estimates with Measured Personal Exposures ..........4-31 4.6.3 Sensitivity Analyses....................................................................................... 4-33 4.6.3.1 Near-Road Residential Exposures ............................................................4-33 4.6.3.2 Air Exchange Rates and Prevalence of Residential Air Conditioning .....4-33 4.6.3.3 Activity Patterns: Repres entativeness of CHAD ...................................... 4-34 4.6.3.4 Activity Patterns: Underestimation of Repeated Exposures..................... 4-34 4.6.4 Uncertainty Analysis...................................................................................... 4-37 4.6.5 Key Findings.................................................................................................. 4-41
4.7 EXPOSURE ASSESSMENT RESULTS................................................................ 4-43 4.7.1 APEX Modeling Results................................................................................ 4-43 4.7.2 Estimated Exposures above Se lected Benchmark Levels.............................. 4-43 4.7.3 Estimates of Repeated Exposures .................................................................. 4-64
REFERENCES .................................................................................................................... 4 -68

5. CHARACTERIZATION OF HEALTH RISKS......................................................... 5

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5.1 INTRODUCTION ..................................................................................................... 5-1 5.1.1 Overview of Risk Assessme nt From Last Review ...................................... 5-2 5.1.2 Development of Approach for Current Risk Assessment............................ 5-2
5.2 SCOPE OF OZONE HEALTH RISK ASSESSMENT............................................. 5-5 5.2.1 Selection of Health Endpoint Categories.....................................................5-6 5.2.2 Selection of Study Areas..............................................................................5-9 5.2.3 Air Quality Considerations ........................................................................ 5-11
5.3 COMPONENTS OF THE RISK MODEL .............................................................. 5-14 5.3.1 Assessment of Risk Based on Controlled Human Exposure Studies ........ 5-14 5.3.1.1 General Approach ..................................................................................... 5-14 5.3.1.2 Exposure Estimates................................................................................... 5-18 5.3.1.3 Exposure-Response Functions.................................................................. 5-18 5.3.1.4 Characterizing Uncertainty and Variability..............................................5-22 5.3.2 Assessment of Risk Based on Epidemiological Studies............................ 5-29 5.3.2.1 General Approach ..................................................................................... 5-29 5.3.2.2 Air Quality Considerations ....................................................................... 5-32 5.3.2.3 Concentration-Response Functions .......................................................... 5-34 5.3.2.4 Baseline Health Effects Incide nce and Population Estimates................... 5-37v 5.3.2.5 Characterizing Uncertainty and Variability..............................................5-40
5.4 OZONE RISK ESTIMATES................................................................................... 5-46 5.4.1 Recent Air Quality ..................................................................................... 5-47 5.4.2 Just Meeting Current and Alte rnative Ozone Standards............................ 5-63 5.4.3 Sensitivity Analyses................................................................................... 5-81 5.4.3.1 Impact of Alternative Assumptions About Background........................... 5-805.4.3.2 Impact of Alternative Assumptions About the Shape of ExposureResponse Relationships for L ung Function Decrements ......................... 5-82 5.4.4 Comparison with Risk Estimates from Prior Review................................ 5-87 5.4.5 Key Observations....................................................................................... 5-92 REFERENCES ..................................................................................................................5-1 00

6. STAFF CONCLUSIONS AND RECOMMENDATIONS ON THE PRIMARY O 3 NAAQS .................................................................................................. 6-1

6.1 INTRODUCTION ..................................................................................................... 6-1
6.2 APPROACH ..............................................................................................................6-1
6.3 PRIMARY O 3 STANDARD ..................................................................................... 6-4 6.3.1 Adequacy of Current O 3 Standard ...................................................................6-5 6.3.1.1 Evidence-based Considerations .................................................................. 6-8 6.3.1.2 Exposure- and Risk-based Considerations................................................6-17 6.3.1.3 CASAC and Public Commenters’ Views on the Adequacy of the Current Standard ...................................................................................... 6-42 6.3.1.4 Staff Conclusions on the Adequacy of the Current Standard ...................6-46 6.3.2 Indicator ......................................................................................................... 6-53 6.3.3 Averaging Time ............................................................................................. 6-53 6.3.3.1 Short-Term and Prolonged (1 to 8 Hours) ................................................ 6-53 6.3.3.2 Long-Term ................................................................................................6-56 6.3.4 Level .............................................................................................................. 6-57 6.3.4.1 Evidence-based Considerations ................................................................ 6-58 6.3.4.2 Exposure/Risk-based Considerations........................................................ 6-61 6.3.4.3 CASAC and Public Commenters’ Views on the Level of the Standard....................................................................................................6-76 6.3.4.4 Staff Conclusions on the Le vel of the Standard........................................6-77 6.3.5 Form............................................................................................................... 6-82 6.3.6 Summary of Staff Conclusions a nd Recommendations on the Primary O 3 NAAQS.................................................................................................... 6-85
6.4 SUMMARY OF KEY UNCERTA INTIES AND RESEARCH RECOMMENDATIONS RELATED TO SETTING A PRIMARY O 3 STANDARD............................................................................................................ 6-87
REFERENCES .................................................................................................................... 6 -92vi 7. POLICY-RELEVANT ASSESSMENT OF WELFARE EFFECTS EVIDENCE .................................................................................................................... 7-1

7.1 INTRODUCTION ..................................................................................................... 7-1
7.2 MECHANISMS GOVERNING PLANT RESPONSE TO OZONE ........................7-2 7.2.1 Ozone Uptake: Canopy, Plant and Leaf...........................................................7-3 7.2.2 Cellular to Systemic Response......................................................................... 7-4 7.2.3 Compensation and Detoxification.................................................................... 7-4 7.2.4 Changes to Plant Metabolism ..........................................................................7-5 7.2.5 Plant Response to Chronic/Long-term O 3 Exposures......................................7-6
7.3 NATURE OF EFFECTS ON VEGETATION .......................................................... 7-6 7.3.1 Ozone Sensitive Plants and Their Re lationship to Public Welfare.................. 7-7 7.3.2 Vegetation Effects Endpoints .......................................................................... 7-7 7.3.2.1 Visible Foliar Injury and Premature Senescence........................................ 7-7 7.3.2.2 Carbohydrate Production and Allocation....................................................7-8 7.3.2.3 Growth and Reproduction........................................................................... 7-9 7.3.2.4 Reduced Plant Vigor................................................................................. 7-10
7.4 IMPACTS ON PUBLIC WELFARE ...................................................................... 7-10 7.4.1 What Constitutes an Adverse Vegeta tion Impact from Ozone Exposure? .... 7-10 7.4.2 Factors That Modify Functi onal and Growth Response................................7-11 7.4.2.1 Genetics..................................................................................................... 7-12 7.4.2.2 Biological Factors ..................................................................................... 7-12 7.4.2.3 Physical Factors ........................................................................................ 7-13 7.4.2.4 Chemical Factors ...................................................................................... 7-14
7.5 CHARACTERIZATION OF VEGETA TION EXPOSURES TO OZONE............ 7-15 7.5.1 Key Considerations in Vegetati on Exposure Characterization......................7-15 7.5.2 Monitor Networks: National Coverage..........................................................7-24 7.5.3 Community Multi-scale Air Quality Model (CMAQ)................................... 7-26 7.5.4 Generation of Potential Ozone Exposure Surfaces (POES) .......................... 7-26 7.5.5 Uncertainties in the O 3 Exposure Analysis.................................................... 7-34
7.6 CHARACTERIZATION OF VEGETATION RISKS ............................................ 7-38 7.6.1 Scope of Vegetation Risk Assessment........................................................... 7-38 7.6.2 Characterization of Crop Risks and Associated Economic Benefits............. 7-40 7.6.2.1 Exposure Methodologies Used in Vegetation Research...........................7-40 7.6.2.2 Basis for C-R Functions............................................................................7-42 7.6.2.3 Considerations for Exposures at Crop Canopy Height.............................7-46 7.6.2.4 Quantifiable Risk of Yield Loss In Select Commodity, Fruit and Vegetable Crops ....................................................................................... 7-47 7.6.2.5 Economic Benefits Assessment – AGSIM ............................................... 7-49 7.6.2.6 Uncertainties In the Crop Risk and Benefit Analyses ..............................7-52 7.6.3 Tree Risk Assessments .................................................................................. 7-55 7.6.3.1 Quantifiable Risk of Biomass Loss In Select Tree Seedling Species....... 7-58 7.6.3.2 Visible Foliar Injury Incidence ................................................................. 7-60 7.6.3.3 Modeled Mature Tree Growth Response: Eastern and Western Species Case Studies ................................................................................7-65vii 7.6.3.4 Uncertainties In the Tree Risk Analyses...................................................7-69 7.7 QUALITATIVE RISK: ECOSYSTE M CONDITION, FUNCTION AND SERVICES............................................................................................................... 7-70 7.7.1 Evidence of Potential Ozone Alteration of Ecosystem Structure and Function ........................................................................................................7-73 7.7.2 Effects on Ecosystem Services and Carbon Sequestration............................ 7-74 REFERENCES ................................................................................................................... 7- 76

8. STAFF CONCLUSIONS AND RECOMMENDATIONS ON THE SECONDARY O 3 NAAQS............................................................................................ 8

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8.1 INTRODUCTION ..................................................................................................... 8-1
8.2 APPROACH ..............................................................................................................8-1
8.3 SECONDARY O 3 STANDARD ............................................................................... 8-4 8.3.1 Adequacy of Current O 3 Standard ...................................................................8-5 8.3.1.1 Vegetation Evidence-, Exposure- a nd Risk-Based Considerations ............8-6 8.3.1.2 CASAC and Public Commenter Views on the Adequacy of the Current Standard ...................................................................................... 8-13 8.3.1.3 Staff Conclusions on the Adequacy of the Current Standard ...................8-14 8.3.2 Pollutant Indicator.......................................................................................... 8-15 8.3.3 Averaging Times............................................................................................ 8-16 8.3.3.1 Seasonal Window...................................................................................... 8-16 8.3.3.2 Diurnal Window........................................................................................ 8-17 8.3.3.3 Alternative Views and Staff Conclusions.................................................8-17 8.3.4 Form of the Standard ..................................................................................... 8-18 8.3.4.1 Comparison of 8-Hour Average an d Cumulative Seasonal Forms........... 8-19 8.3.4.2 Comparison of SUM06 and W 126 Cumulative, ConcentrationWeighted Forms ....................................................................................... 8-21 8.3.5 Level of the Standard.....................................................................................8-22 8.3.6 Summary of Staff Conclusions a nd Recommendations on the Secondary O 3 Standard....................................................................................................8-24
8.4 SUMMARY OF KEY UNCERTA INTIES AND RESEARCH RECOMMENDATIONS RELATED TO SETTING A SECONDARY O 3 STANDARD............................................................................................................ 8-27
REFERENCES .................................................................................................................... 8 -30

ATTACHMENT A : Clean Air Scientific A dvisory Committee Letter (October 24, 2006)

ATTACHMENT B: Clean Air Scientific Advisory Committee Letter (March 26, 2007)viii APPENDICES

APPENDIX 2A. PLOTS OF DIURNAL POLICY RELEVANT BACKGROUND OZONE PATTERNS FOR 12 URBAN AREAS BASED ON RUNS OF THE GEOSCHEM MODEL FOR APRIL-OCTOBER 2001 ..................................................................... 2A-1

APPENDIX 3A. MECHANISMS OF TOXICITY ................................................................. 3A-1

APPENDIX 3B. TABLE OF KEY EPIDEMIOLOGICAL STUDIES................................... 3B-1

APPENDIX 3C. TABLE OF KEY CONTROLLED HUMAN EX POSURE STUDIES....... 3C-1

APPENDIX 4A: EXPOSURE TABLES................................................................................. 4A-1

APPENDIX 5A.1: OZONE AIR QUALITY IN FORMATION FOR 12 URBAN AREAS... 5A-1

APPENDIX 5A.2: SCATTER PLOTS.................................................................................. 5A-10

APPENDIX 5B1: TABLES OF STUDY-SPECIFIC INFORMATION................................. 5B-1

APPENDIX 5B2: CONCENTRATION- RESPONSE FUNCTIONS AND HEALTH IMPACT FUNCTIONS............................................................................................................ 5B- 8

APPENDIX 5B3: THE CALCULATION OF “SHRINKAGE” ESTIMATES FROM THE LOCATION-SPECIFIC ESTI MATES REPORTED IN HUAN G ET AL. (2004)....... 5B-11

APPENDIX 5C: ADDITIONAL HEALTH RI SK ASSESSMENT ESTIMATES ................ 5C-1

APPENDIX 6A: PREDICTED PERCENT OF COUNTIES WITH MONITORS (AND PERCENT OF POPULATION IN CO UNTIES) NOT LIKELY TO MEET ALTERNATIVE OZONE STANDARDS ............................................................................... 6A-1ix 

### List of Tables Number Page

2-1. NOx Emission Sources, 1970-2004 .................................................................................... 2-3 2-2. VOC Emission Sources, 1970-2004.................................................................................... 2-5 2-3. Relationship between Precision of 1- hour Ozone Data and Corresponding Standard Deviation of 8-hour Design Values......................................................................... 2-14

3-1. Acute O3-induced Physiol ogical and Biochemical Changes in Humans and Animals .... 3-52 3-2. Gradation of Individual Responses to Short-Term Ozone Exposure in Healthy Persons..................................................................................................................... 3-7 4 3-3. Gradation of Individual Responses to Short-Term Ozone Exposure in Persons with Impaired Respiratory Systems................................................................................. 3-75

4-1. Exertion levels in terms of equi valent ventilation rates (liters/min-m 2 )..............................4-2 4-2. Urban areas and time periods modeled..............................................................................4-19 4-3. Population coverage of mode led areas (2002 analysis).....................................................4-20 4-4. Studies in CHAD used in this analysis.............................................................................. 4-23 4-5. Microenvironments modeled by APEX ............................................................................ 4-25 4-6. Alternative 8-hr ozon e standard scenarios.........................................................................4-29 4-7. 2002-2004 8-hr ozone design valu es for the modeled areas .............................................4-29 4-8. Comparison of APEX 2002 base case si mulations: All CHAD vs. the NHAPS part of CHAD. Percent of children at m oderate exertion with 8-hour exposures above levels of 0.06, 0.07, 0.08 ppm-8hr. ............................................................... 4-35 4-9. Comparison of APEX simulations: All CHAD vs. the NHAPS part of CHAD. Percent reduction 1 from the 2002 base case to the current standard of the number of children at moderate exerti on with 8-hour exposures above levels of 0.06, 0.07, 0.08 ppm-8hr..................................................................................... 4-35 4-10. Comparison of estimated outdoor workers’ repeated exposures with APEX results for all workers, in Atlanta and Sacram ento, 2002. Numbers of people with at least six repeated 8-hour exposur es above 0.06, 0.07, and 0.08 ppm-8hr............... 4-36 4-11. Uncertainty of the estim ated percent of children exposed at moderate exertion, Boston, 2002............................................................................................................ 4-40 4-12. Uncertainty of the estim ated percent of asthmatic ch ildren exposed at moderate exertion, Boston, 2002.............................................................................................4-40 4-13. Uncertainty of the estim ated percent reduction, from th e base case to the current standard, of all children and asthmatic children exposed at moderate exertion, Boston, 2002............................................................................................................ 4-41

5-1. Health Effects and Associated Popula tion Groups Addressed in Quantitative Risk assessment ............................................................................................................... 5-10 5-2. Health Endpoints and Associated Population Groups Not Included in the Quantitative Risk Assessment ................................................................................. 5-10 5-3. Study-Specific Exposure-Response Da ta for Lung Function Decrements........................5-19 5-4. Locations, Health Endpoints, and Ep idemiological Studies Included in the O 3 Risk Assessment .............................................................................................................. 5-36x 5-5. Relevant Population Sizes for O 3 Risk Assessment Locations ......................................... 5-38 5-6. Baseline Mortalit y Rates (per 100,000 Population) Used in the O 3 Risk Assessment

.............................................................................................................................. ...5-39 5-7. Baseline Rates for Hospital Admissions Used in the O 3 Risk Assessment....................... 5-41 5-8. Number and Percent of All School Age Children Estimated to Experience Lung Function Responses (FEV 1 > 15%) Associated with 8-Hour O 3 Exposure While Engaged in Moderate Ex ertion for Location-Specific O 3 Seasons...............5-49 5-9. Number of Occurrences of Lung Function Responses (FEV1 > 15%) Among All School Age Children Associated with 8- Hour O3 Exposure While Engaged in Moderate Exertion for Location-Specific O3 Seasons............................................ 5-50 5-10. Number and Percent of Asthmatic Sc hool Age Children Estimated to Experience Lung Function Responses (FEV 1 > 10%) Associated with 8-Hour O 3 Exposure While Engaged in Moderate Exertion for Location Specific O 3 Seasons .................................................................................................................... 5-52 5-11. Number of Occurrences of L ung Function Responses (FEV1 > 10%) Among Asthmatic School Age Children Associated with 8-Hour O3 Exposure While Engaged in Moderate Exertion for Location Specific O3 Seasons ......................... 5-53 5-12. Estimated Respiratory Symptoms Associ ated with Recent (April - September, 2004) O 3 Concentrations Above Background in Boston, MA ................................ 5-54 5-13. Estimated Respiratory Symptoms Associ ated with Recent (April - September, 2002) O 3 Concentrations Above Background in Boston, MA ................................ 5-55 5-14. Estimated Hospital Admissions Associ ated with Recent (April - September, 2004) O3 Concentrations in NY, NY ................................................................................ 5-56 5-15. Estimated Hospital Admissions Associ ated with Recent (April - September, 2002) O3 Concentrations in NY, NY ................................................................................ 5-56 5-16. Estimated Non-Accidental Mortality As sociated with Recent (April - September, 2004) O3 Concentrations......................................................................................... 5-57 5-17. Estimated Non-Accidental Mortality As sociated with Recent (April - September, 2002) O3 Concentrations......................................................................................... 5-59

6-1a. Summary of Estimates of Number of People Exposed and Number of Occurrences at Moderate Exertion Associated with 8-Hour Daily Maximum Ozone Concentrations > 0.080 ppm for 12 Urban Areas in the U.S. .................................6-26 6-1b. Summary of Estimates of Number of People Exposed and Number of Occurrences at Moderate Exertion Associated with 8-Hour Daily Maximum Ozone Concentrations > 0.070 ppm for 12 Urban Areas in the U.S. .................................6-27 6-1c. Summary of Estimates of Number of People Exposed and Number of Occurrences at Moderate Exertion Associated with 8-Hour Daily Maximum Ozone Concentrations > 0.060 ppm for 12 Urban Areas in the U.S. .................................6-28 6-2. Summary of Number and Percent of All School Age Children (5-18) in 12 Urban Areas Estimated to Experience Lung F unction Responses and the Number of Occurrences Associated with 8-Hour Ozone Exposures While Engaged in Moderate Exertion for 2002, 2003, and 2004 Air Quality and Just Meeting the Current 8-Hour Standard ......................................................................................... 6-31 6-3. Summary of Number and Percent of Asthmatic School Age Children (5-18) in 5 Urban Areas Estimated to Experience Lung Function Responses and thexi Number of Occurrences Associated with 8-Hour Ozone Exposures While Engaged in Moderate Exertion for 2002, 2003, and 2004 Air Quality and Just Meeting the Current 8-Hour Standard..................................................................... 6-35 6-4. Incidence of Respiratory Symptom Da ys for Chest Tightness Associated with Recent (2004, 2002) Air Quality and Just Meets the Current Standard Based on Adjusting 2004 and 2002 Air Quality in Moderate to Severe Asthmatic Children in Boston, MA ..........................................................................................6-38 6-5. Risks of Respiratory- and Asthma-re lated Hospital Admissions Associated with Recent (2004, 2002) Air Quality and Air Quality Adjusted to Just Meets Current Standard Based on Adjusting 2004 and 2002 Air Quality in New York City, NY ......................................................................................................... 6-40 6-6. Risks of Non-accidental Mortality Asso ciated with Recent (2004, 2002) Air Quality and Air Quality Adjusted to Just Meets Current Standard Based on Adjusting 2004 and 2002 Air Quality......................................................................................6-41 6-7. Estimates of Percent of Children Expos ed While at Moderate Exertion to 8-Hour Daily Maximum Ozone Concentr ations > 0.070 ppm and > 0.060 ppm Combined for 12 Urban Areas in the U. S., and the Range of Estimates for Each of the 12 Cities – Just Meeting Current Standard .......................................... 6-51 6-8. Daily Maximum Ozone Concentrati ons > 0.07 ppm and > 0.06 ppm Combined for 12 Urban Areas in the U.S., and the Ra nge of Estimates for Each of the 12 Cities – Just Meeting Alternative Standards ........................................................... 6-66 6-9. Risks of Respiratory Sy mptom Days for Chest Tightness Associated with Just Meeting the Current and Alternative Ozone Standards Based on Adjusting 2002 and 2004 Air Quality in Moderate to Severe Asthmatic Children in Boston, MA ............................................................................................................. 6-75 6-10. Risks of Hospital Admissions for Respirat ory Illness Associated with Just Meeting the Current and Alternative Ozone Standards Based on Adjusting 2002 and 2004 Air Quality in New York, NY ........................................................................ 6-76

7-1a. Evaluation statistics for the 3-month 12-hr SUM06 interpolations of the Eastern and Western U.S. domains ...................................................................................... 7-36 7-1b. Evaluation statistics for the 3-month 12- hr W126 interpolations of the Eastern and Western U.S. domains. ............................................................................................ 7-36 7-3A-B. Agricultural model resu lts with (A) and without (B) a 10% adjustment of hourly O 3 exposures............................................................................................................ 7-54 7-4. Percentage and number of counties with visible foliar injury (injured) and without injury (not injured) below various sta ndard levels for the years 2001-2004...........7-64 7-5. Relative increase in total annual tree biomass growth, simulated with the TREGRO model, if the level of the current (0.08 pp m) and alternative standards are met.....7-66xii 

### List of Figures

Number Page

2-1. Atmospheric Processes Affecting the Formation of Photochemical Oxidants and Particulate Matter ......................................................................................................2-8 2-2. Locations of Ozone Monito rs from AQS an d CASTNET ................................................ 2-11 2-3. 1-hr Ozone Distributions ac ross 12 Risk Areas, 2002-2004. ............................................ 2-16 2-4. 8-hr Ozone Distributions ac ross 12 Risk Areas, 2002-2004. ............................................ 2-17 2-5. 24-hr Ozone Dist ributions across 12 Risk Areas, 2002-2004. .......................................... 2-18 2-6. Average 2nd Highest Daily Maximum 1- hour Values in U.S. Counties, 2002-2004 AQS Data. ............................................................................................................... 2-20 2-7. Average 4th Highest Daily Maximum 8-hour Values in U.S. Counties, 2002-2004 AQS Data. ............................................................................................................... 2-21 2-8. Highest 3-month 12-hour SUM06 Expos ure Index in U.S. Counties, 2001 AQS Data. ........................................................................................................................ 2- 22 2-9. Highest 3-month 12-hour W126 Exposure I ndex in U.S. Counties, 2001 AQS Data.......2-23 2-10. Highest 3-month 12-hour SUM06 E xposure Index in U.S. Counties, 2001 CASTNET Data. ..................................................................................................... 2-24 2-11. Highest 3-month 12-hour W126 Exposure Index in U.S. Counties, 2001 CASTNET Data. ..................................................................................................... 2-25 2-12. Highest 3-month 12-hour SUM06 Exposur e Index in U.S. Counties, 2002 AQS and CASTNET Data. ..................................................................................................... 2-26 2-13. Highest 3-month 12-hour W1126 Exposur e Index in U.S. Counties, 2002 AQS and CASTNET Data. ..................................................................................................... 2-27 2-14. Highest 3-month 12-hour SUM06 Expos ure Index in U.S. Counties, 2004 AQS and CASTNET Data................................................................................................ 2-28 2-15. Highest 3-month 12-hour W126 Exposure Index in U.S. Counties, 2004 AQS and CASTNET Data. ..................................................................................................... 2-29 2-16. 4th Highest Daily Maximum 8-hour Ozone Values 1990-2004 (Urban)........................ 2-31 2-17. 4th Highest Daily Maximum 8-hour Ozone Values 1990-2004 (Rural)......................... 2-32 2-18. 2nd Highest Daily Maximum 1-hour Ozone Values 1990-2004 (Urban)....................... 2-33 2-19. 2nd Highest Daily Maximum 1-hour Ozone Values 1990-2004 (Rural). ........................ 2-34 2-20. Comparison of 1-hr, 8- hr, and 24-hr Metrics for 2002 and 2004, 12 Risk Areas ............2-36 2-21. 2nd Highest Daily Maximum 1-hour Ozone Values from 2004 by Month..................... 2-37 2-22. 4th Highest Daily Maximum 8-hour Ozone Values from 2004 by Month. .................... 2-38 2-23. 1-Hour Diurnal Week Day Pattern for Urban Sites, May through September 2004....... 2-40 2-24. 1-Hour Diurnal Week End Pattern for Urban Sites, May through September 2004....... 2-41 2-25. 8-Hour Diurnal Week Day Pattern for Urban Sites, May through September 2004....... 2-42 2-26. 8-Hour Diurnal Week End Pattern for Urban Sites, May through September 2004....... 2-43 2-27 1-Hour Week Day Diurnal Pattern for Rural Sites, May through September 2004......... 2-44 2-28. 1-Hour Week End Diurnal Pattern for Rural Sites, May through September 2004. ....... 2-45 2-29. 8-Hour Week Day Diurnal Pattern for Rural Sites, May through September 2004........ 2-46 2-30. 8-Hour Week End Diurnal Pattern for Rural Sites, May through September 2004. ........ 2-47 2-31. Length of Consecutive Day Episodes over 0.12 ppm by Year for 1-hour Ozone Data across all Monitors.......................................................................................... 2-49xiii 2-32. Length of Consecutive Day Episodes over 0.08 ppm by Year for 8-hour Ozone Data across all Monitors.......................................................................................... 2-50 2-33. Length of Consecutive Day Episodes over Displayed Levels for 1-hour Ozone Data (2000-2004) across all Monitors..................................................................... 2-51 2-34. Length of Consecutive Day Episodes over Displayed Levels for 8-hour Ozone Data (2000-2004) across all Monitors..................................................................... 2-52 2-35. Length of Gaps in Days Between Episodes over 0.08 ppm for 8-hour Ozone Data (2000-2004). ............................................................................................................ 2-53

3-1A,B. Frequency distributions of FEV 1 changes following 6.6-hr exposures to a constant concentration of O 3 or filtered air. ..............................................................3-7 3-1 C. Frequency distributions of FEV 1 changes following 6.6-hr exposures to a constant concentration of O 3 or filtered air..............................................................................3-7 3-2. Resolution Time-Line for Acute Ozone -Induced Physiological and Biochemical Responses in Humans.............................................................................................. 3-53 3-3. Postulated Cellular and Molecular Ch anges in Human Airway Epithelial Cells on Acute Exposure to Ozone........................................................................................3-54

4-1. APEX Diagram............................................................................................................. .......4-8 4-2. Modeled and measured weekly aver age personal exposures : means,

................................. 4 -32 minima, maximum for each week. Upland, CA. 4-3. Modeled and measured weekly averag e personal exposures : means, minima

, maxima for each week. Lake Arrowhead, Crestline, and Running Springs ,, CA ................ 4-32 4-4. Uncertainty of percent of childre n with exposures above 0.06 ppm-8hr ......................... 4-38 4-5. Uncertainty of percent of childre n with exposures above 0.07 ppm-8hr ......................... 4-39 4-6. Uncertainty of percent of childre n with exposures above 0.08 ppm-8hr ......................... 4-39 4-7. Comparison of exposures fo r different population groups................................................ 4-44 4-8. Comparison of exposures for different years .................................................................... 4-44 4-9. Percent of children with re peated exposures > 0.08 ppm-8hr ........................................... 4-65 4-10. Percent of children with repeated exposures > 0.07 ppm-8hr ......................................... 4-66 4-11. Percent of children with repeated exposures > 0.06 ppm-8hr ......................................... 4-67

5-1. Major Components of Ozone Health Ri sk Assessment Based on Controlled Human Exposure Studies .....................................................................................................5-17 5-2. a, b, c. Probabilistic Exposure-Re sponse Relationships for FEV1 Decrement > 10%, > 15%, and > 20% for 8-Hour E xposures Under Moderate Exertion.......... 5-24 5-3a, b, c. Probabilistic Exposure-Response Relationships for FEV1 Decrement > 10% and > 15% for 8-Hour Exposures Unde r Moderate Exerti on: Comparison of 90% Logistic/10% Linear (Hockeystick) Split and 80% Logistic/20% Linear (Hockeystick) and 50% Logistic/50% Linear (Hockeystick) Splits in Assumed Relationship Between Exposure and Response....................................... 5-27 5-4. Median Exposure-Response Functions Using Three Different Combinations of Logistic and Linear (Hockeystick) Models .............................................................5-26 5-5. Major Components of Ozone Health Risk Assessment Based on Epidemiological Studies .....................................................................................................................5-3 1 5-6. Estimated Annual Percent of Non-Accident al Mortality Associated with Short-Term Exposure to Recent O 3 Concentrations Above Background for the Periodxiv April – September (Based on Bell et al., 2004) – Total and Contribution of 24-Hour Average O 3 Ranges................................................................................... 5-62 5-7. Percent of All Children (Ages 5-18) E ngaged in Moderate Exertion Estimated to Experience At Least One Lung Function Response (Decrement in FEV1 ≥ 15%) Associated with Exposure to O3 Concentrations That Just Meet the Current and Alternative Average 4t h-highest Daily Maximum 8-Hour Standards, for Location-Specific O 3 Seasons (Based on Adjusting 2002 Air Quality.....................................................................................................................5-6 6 5-8. Percent of All Children (Ages 5-18) E ngaged in Moderate Exertion Estimated to Experience At Least One Lung Function Response (Decrement in FEV 1 ≥ 15 %) Associated with Recent Air Quality (2002) and Just Meeting the Current and Alternative Average nth Daily Maximum 8-Hour Standards, for Location-Specific O 3 Seasons (Based on Adjusting 2002 Air Quality)*................ 5-67 5-9. Percent of Asthmatic Children (Age s 5-18) Engaged in Moderate Exertion Estimated to Experience At Least One Lung Function Response (Decrement in FEV 1 ≥ 10%) Associated with Exposure to O 3 Concentrations That Just Meet the Current and Alternative Av erage 4th-highest Daily Maximum 8- Hour Standards, for Location-Specific O 3 Seasons (Based on Adjusting 2002 Air Quality) .............................................................................................................5-69 5-10. Percent of Asthmatic Children (A ges 5-18) Engaged in Moderate Exertion Estimated to Experience At Least One Lung Function Response (Decrement in FEV1 ≥ 10 %) Associated with Recent Ai r Quality (2002) and Exposure to O3 Concentrations That Just Meet the Current and A lternative 8-Hour Standards, for Location-Specific O3 Seasons: Based on Adjusting 2002 O3 Concentrations......................................................................................................... 5-70 5-11. Estimated Symptom-Days for Chest Tightness Among Moderate/Severe Asthmatic Children (Ages 0 – 12) in Boston Associ ated with Recent (April-September2002) O3 Levels and with Levels Just Meeting Alternative Average 4thHighest Daily Maximum 8-H our Ozone Standards ................................................5-72 5-12. Estimated Incidence of (Unschedul ed) Respiratory Hospital Admissions per 100,000 Relevant Population in New York Associated with Recent (April – September, 2002) O 3 Levels and with O 3 Levels Just Meeting Alternative Average 4th-Highest Daily Maxi mum 8-Hour Standards....................................... 5-73 5-13. Estimated Incidence of Non-Accident al Mortality per 100,000 Relevant Population Associated with Recent Air Quality (2002) and with Just Meeting Alternative Average 4th-Highest Daily Maximum 8- Hour Ozone Standards (Using Bell et al., 2004 – 95 U.S. Cities Function), Based on 2002 Ozone Concentrations.......... 5-74 5-14. Annual Warm Season (April to September) Estimated O 3 -Related Non-Accidental Mortality Associated with Recent (2002) O 3 Levels and Levels Just Meeting Alternative 8-hr O 3 Standards (Using Bell et al., 2004 – 95 U.S. Cities Function) .................................................................................................................5-76 5-15. Estimated Annual Percent of Non-Acci dental Mortality Associated with ShortTerm Exposure to O 3 Above Policy Relevant Ba ckground for the Period April – September When the Current 8-Hour St andard is Just Met (Based on Bell et al., 2004) – Total and Contribu tion of 24-Hour Average O 3 Ranges...................... 5-79xv 5-16. Sensitivity Analysis of Estimated Percent Change in O 3 -related Non-Accidental Mortality (Using Bell et al., 2004 – 95 C ities) From the Current Standard to Alternative 8-hr Standards and a Rece nt Year of Air Qu ality, Using Base Case, Higher, and Lower PRB Estimates................................................................5-83 5-17 Sensitivity Analysis: Impact of Alternative Estimates of Exposure-Response Function on Estimated Percent Changes From the Current Standard in Numbers of All Children (Ages 5-18) Engaged in Moderate Exertion Experiencing at Least One Decrement in FEV 1 > 15% ........................................... 5-88 5-18. Sensitivity Analysis: Impact of Alternative Estimates of Exposure-Response Function on Estimated Percent Changes From the Current Standard in Numbers of Asthmatic Children (Ages 5- 18) Engaged in Moderate Exertion Experiencing at Least One Decrement in FEV 1 > 10% ........................................... 5-90

6-1. Percent Changes in Numbers of School Age Children Experiencing at Least One Decrement in FEV1 >15% when O3 Concentrations are Reduced from Those Just Meeting the Current Standard to Those that Would Just Meet Each Alternative Standard, Based on Adjusting 2002 Data............................................. 6-68 6-2. Percent Changes in Numbers of School Age Children Experiencing at Least One Decrement in FEV1 >15% when O3 Concentrations are Reduced from Those Just Meeting the Current Standard to Those that Would Just Meet Each Alternative Standard, Based on Adjusting 2004 Data............................................. 6-69 6-3. Percent Changes in Numbers of Asth matic School Age Children Experiencing at Least One Decrement in FEV1 >10% when O3 Concentrations are Reduced from Those Just Meeting the Current Sta ndard to Those that Would Just Meet Each Alternative Standard, Base d on Adjusting 2002 Data.................................... 6-70 6-4. Percent Changes in Numbers of Asth matic School Age Children Experiencing at Least One Decrement in FEV1 > 10% wh en O3 Concentrations are Reduced from Those Just Meeting the Current Sta ndard to Those that Would Just Meet Each Alternative Standard, Base d on Adjusting 2004 Data.................................... 6-71 6-5. Percent Changes in O3 -Related Non-Accidental Mo rtality Incidence when O3 Concentrations are Reduced from Those Just Meeting the Current Standard to Those that Would Just Meet Each A lternative Standard, Based on Adjusting 2002 Data (Using Bell et al., 2004 – 95 U.S. Cities) ..............................................6-72 6-6. Percent Changes in O3 -Related Non-Accidental Mo rtality Incidence When O3 Concentrations are Reduced from Those Just Meeting the Current Standard to Those that Would Just Meet Each A lternative Standard, Based on Adjusting 2004 Data (Using Bell et al., 2004 – 95 U.S. Cities) .............................................. 6-73

7-1. The 3-year average (2002-2004) of the 4 th -highest maximum 8-hr average (current standard form) versus the 3-year aver age of the highest 3-month 12-hr W126, by county. ................................................................................................................ 7-18 7-2. Highest 3-month 12-hr W126 values fr om monitors in National Parks and other natural areas in the Southeast (A) and No rtheast (B). Monitors designated as GSMNP are found in different areas of the Great Smoky Mountain National Park.......................................................................................................................... 7 -20xvi 7-3. Highest 3 month 12-hr W126 values fr om monitors in National Parks in the Mountain West (A) and California (B). ..................................................................7-21 7-4. Maximum 3-month 12-hr SUM06 plotte d against maximum 3-month 12-hr W126. Data points are from the AQS and CASTNET O 3 monitors for the year 2001....... 7-23 7-5. Locations of AQS monitors (top) and CASTNET monitoring stations (bottom) ............. 7-25 7-6. Estimated 12-hr W126 Ozone Exposure – Max 3-months for 2001: “As Is” scenario.....7-28 7-7. Estimated 12-hr W126 Ozone Exposur e – Max 3-months for 2001: Quadratic Rollback to just meet 4 th -Highest 8-hr Maximum of >0.084 .................................. 7-30 7-8. Estimated 12-hr W126 Ozone Exposure – Max 3-months for 2001: Quadratic Rollback to just meet 4th Highe st 8-hr Maximum of >0.070 ................................. 7-31 7-9. Estimated 12-hr W126 Ozone Exposure – Max 3-months for 2001: Quadratic Rollback to just meet 12-hr SUM06 of 25 ppm-hr, secondary standard proposed in 1996 ..................................................................................................... 7-32 7-10. Estimated 12-hr W126 Ozone Exposur e – Max 3-months for 2001: Quadratic Rollback to just meet 12-hr SUM06 of 15 ppm-hr ................................................. 7-33 7-11. Comparison of predicted versus obs erved 12-hr W126 at CASTNET and “rural” AQS monitors. Monitor data was pr edicted by dropping out each monitor sequentially and interpolated with the all remaining monitors. .............................. 7-37 7-12 (a-c). Major Components of Vegetation Risk Assessment............................................. 7-39 7-13. Median crop yield loss from NCLAN crops characterized with the 12-hr W126........... 7-44 7-14 (A-D). Median soybean (A), wheat (B ), cotton (C) and corn (D) yield loss from NCLAN crops characterized with the 12-hr W126................................................. 7-45 7-15. Estimated soybean yield loss based on interpolated 2001 3-m onth 12-hr W126 with a 10% downward adjustment of hourly O 3 concentrations. ....................................7-49 7-16. Median tree seedling biomass loss for all 49 cases (A), quaking aspen (B), and ponderosa pine (C) characterized with the 12-hr W126.......................................... 7-56 7-17. Cottonwood ( Populus deltoides ) shoot biomass (mean ± s.e.) at urban (filled) and rural (open) sites in the vicinity of New York City versus ambient O 3 exposure (growing period 12-hr W126, July 7 – Sept. 20) ..................................... 7-57xvii 

### ERRATA

Corrections made to document:

Title page and back page, publication number has been changed to “EPA-452/07-007.”

For Chapter 3: On page 3-56, a list of epidemiology studi es referenced in Figure 3-4 was added.

For Chapter 4: The following tables and figures were revise d and the text was revised to reflect the corrected estimates presented in these tables and figures: Tables 4-8, 4-9, Figures 4-2, 4-3 Figures 4-9, 4-10, 4-11 Exhibits 1 through 9

In the last paragraph on page 4-1, continui ng onto page 4-2, a re dundant sentence was removed.

The footnote on page 4-1 was revised to clar ify why the results for active children were not presented in the Staff Paper. The co rrected exposure modeli ng, conducted after the Staff Paper was published, fixed the error in how children are characterized as active.

Figures 4-2 and 4-3 (comparison of modele d and measured weekly average personal exposures) were changed to pr esent the corrected exposure es timates. The discussion of these results on pages 4-32 and 4-34 was revise d accordingly, and now concludes that the exposures predicted by APEX are generall y in good agreement with the personal exposure measurements.

Tables 4-8 and 4-9 (comparison of APEX model results based on all CHAD with model results based on the NHAPS part of CHAD) were revised to reflect the corrected exposure estimates. The correction results in larger differences between these simulations, and the text on page 4-35 was revised accordingly.

The references for Chapter 4 were edited to make the style consistent and to remove references not cited in the text.xviii 

### ERRATA

For Chapter 5 : The following tables and figures were revise d and the text was revised to reflect the corrected estimates presented in these tables and figures: Tables 5-8, 5-9, 5-10, 5-11 Figures 5-7, 5-8, 5-9, 5-10, 5-17a, b, 5-18a,b

The references to the Exposure Assessm ent TSD and Risk Assessment TSD were updated to reflect the co rrected final reports.

For Chapter 6: The following tables and figures were revise d and the text was revised to reflect the corrected estimates presented in these tables and figures: Tables 6-1a,b,c, 6-2, 6-3, 6-7, 6-8 Figures 6-1, 6-2, 6-3, 6-4

For Appendix 4A: All of the tables in this appendix were revised:

For Appendix 5C: The following tables and figures were revised: Tables 5C-1 through 5C-6 Table 5C-17 Figures 5C-1 through 5C-4

Attachment B was added, which is a copy of the March 26, 2007 CASAC letter to the Administrator of EPA regarding comments on Ch apters 6 and 8 of the final Staff Paper.1-1 

### 1. INTRODUCTION

1.1 PURPOSE This Staff Paper, prepared by staff in the U.S. Environmental Protection Agency’s (EPA) Office of Air Quality Planning and Standards (OAQ PS), evaluates the policy implications of the key studies and scientific inform ation contained in the document, Air Quality Criteria for Ozone
and Related Photochemical Oxidants (USEPA, 2006; henceforth referre d to as the CD), prepared by EPA’s National Center for Environmental Asse ssment (NCEA). This document also presents and interprets results from several quantitati ve analyses (e.g., air qua lity analyses, human exposure analyses, human health risk assessm ents, and an environmental assessment of vegetation-related impacts) that we believe should also be considered in EPA's current review of the national ambient air quality standards (NAAQS) for ozone (O 3 ), and presents factors relevant
to the evaluation of curren t primary and secondary 0 3 standards. Finally, this document presents
staff conclusions and recommendations on a ra nge of policy options that we believe are appropriate for the Administrator to consider concerning whether, and if so how, to revise the primary (health-based) and s econdary (welfare-based) O 3 NAAQS. The policy assessment presented in this Staff Paper is intended to help “bridge the gap”
between the scientific assessment contained in the CD and the judgments required of the EPA Administrator in determining whether it is appr opriate to retain or revise the NAAQS for O 3
. This policy assessment considers the available sc ientific evidence and quantitative risk-based analyses, together with related limitations and un certainties, and focuses on the basic elements of air quality standards: indi cator, averaging times, forms, 1 and levels. These elements, which serve to define each standard, must be consid ered collectively in evaluating the health and welfare protection afforded by the O 3 standards. Our conclusions and policy recommendations on whether, and if so how, to revise these st andard elements are based on the assessment and integrative synthesis of information presented in the CD and on staff analyses and evaluations presented in this document, and are further in formed by comments and advice received from an independent scientific review committee, the Clean Air Scientific Advisory Committee (CASAC), 2 in their review of earlier drafts of this document, as well as comments on earlier drafts submitted by public commenters.

1 The “form” of a standard defines the air quality statistic that is to be compared to the level of the standard in determining whether an area attains the standard.

2 The statutory requirements for CASAC are discussed below in the next section.1-2 While this Staff Paper should be of us e to all parties interested in the O 3 NAAQS review, it is written with an expectation that the r eader has some familiarity with the technical
discussions contained in the CD.

1.2 BACKGROUND

1.2.1 Legislative Requirements Two sections of the Clean Air Act (Act) govern the establishment and revision of the NAAQS. Section 108 (42 U.S.C. 7408) directs the Administrato r to identify and list “air pollutants” that “in his judgment , may reasonably be anticipated to endanger public health and welfare” and whose “presence . . . in the ambient ai r results from numerous or diverse mobile or stationary sources” and, if listed, to issue air quality crite ria for them. These air quality criteria are intended to “accurately reflect the latest sc ientific knowledge useful in indicating the kind and extent of identifiable effects on public health or welfare which may be expected from the presence of [a] pollutant in ambient air . . . .” Section 109 (42 U.S.C. 7409) directs the Administrator to propose and promulgate “primary” and “secondary” NAAQS for polluta nts identified under se ction 108. Section 109(b)(1) defines a primary standard as one “the attainment and maintenance of which in the judgment of the Administrator, based on such crite ria and allowing an adequa te margin of safety, are requisite to prot ect the public health.” 3 A secondary standard, as defined in Section 109(b)(2), must “specify a level of air quality the attainment and mainte nance of which, in the judgment of the Administrator, based on such crite ria, is requisite to pr otect the public welfare from any known or anticipated a dverse effects associated with the presence of [the] pollutant in
the ambient air.” 4 The requirement that primary standards in clude an adequate margin of safety was
intended to address uncertainties associated with inconclusive scientific and technical
information available at the time of standard set ting. It was also intende d to provide a reasonable degree of protection against hazards th at research has not yet identified. Lead Industries

Association v. EPA , 647 F.2d 1130, 1154 (D.C. Cir 1980), cert. denied , 101 S. Ct. 621 (1980);

3 The legislative history of section 109 indicates that a primary standard is to be set at “the maximum permissible ambient air level . . . which will protect the health of any [sensitive] group of the population,” and that for this purpose “reference should be made to a repres entative sample 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)].

4 Welfare effects as defined in section 302(h) [42 U.S. C. 7602(h)] include, but are not limited to, “effects on soils, water, crops, vegetation, man-made materials, anim als, wildlife, weather, visibility and climate, damage to and deterioration of property, and hazards to transportation, as well as ef fects on economic values and on personal comfort and well-being.”1-3 American Petroleum Institute v. Costle , 665 F.2d 1176, 1186 (D.C. Cir. 1981), cert. denied , 102 S.Ct. 1737 (1982). Both kinds of uncertainties are components of the risk associated with pollution at levels below those at which human health effects can be said to occur with reasonable scientific certainty. Thus, in select ing primary standards that include an adequate margin of safety, the Administrator is seeking no t only to prevent pollution levels that have been demonstrated to be harmful but also to prev ent lower pollutant levels that may pose an unacceptable risk of harm, even if the risk is not precisely identified as to nature or degree. In selecting a margin of safety, the EPA cons iders such factors as the nature and severity of the health effects, the size of the sensitive population(s) at ri sk, and the kind and degree of the
uncertainties that must be addressed. The select ion of any particular approach to providing an adequate margin of safety is a policy choice left specifically to the Administrator’s judgment.
Lead Industries Association v. EPA , supra , 647 F.2d at 1161-62. In setting standards that are “requisite” to protect public health a nd welfare, as provided in section 109(b), EPA’s task is to establish standards that are neither more nor less stringent than necessary for these purposes. In so doing, EPA may not consider th e costs of implementing the standards. See generally Whitman v. American Trucking Associations , 531 U.S. 457, 464, 475-76 (2001). Section 109(d)(1) of the Act requires that “not later than December 31, 1980, and at 5- year intervals thereafter, the Administrator shall complete a thorough review of the criteria published under section 108 and th e national ambient air quality st andards . . . and shall make
such revisions in such criteri a and standards and promulgate such new standards as may be appropriate . . . .” Section 109(d)(2) requires th at an independent scient ific review committee “shall complete a review of th e criteria . . . and the national primary and secondary ambient air quality standards . . . and sha ll recommend to the Administrato r any new . . . standards and revisions of existing criteria and standards as ma y be appropriate . . . .” Since the early 1980's, this independent review function has been pe rformed by the Clean Air Scientific Advisory Committee (CASAC), a standing committee of EPA’s Science Advisory Board.

1.2.2 History of Ozone NAAQS Reviews Tropospheric (ground-level) O 3 is formed from biogenic precursor emissions and as a result of anthropogenic precursor emissions. Naturally occurring O 3 in the troposphere can result from biogenic organic precursors reacting wi th naturally occurring nitrogen oxides (NO x ) and by stratospheric O 3 intrusion into the troposphere . Anthropogenic precursors of O 3 , specifically

NO x and volatile organic compounds (VOC), originat e from a wide variety of stationary and
mobile sources. Ambient O 3 concentrations produced by these emissions are directly affected by temperature, solar radiation, wind speed and other meteorological factors.1-4 The EPA initially established primary and secondary NAAQS for photochemical oxidants on April 30, 1971 (36 FR 8186). Both prim ary and secondary standards were set at an hourly average of 0.08 parts per million (ppm), total photochemical oxidants, not to be exceeded more than one hour per year. On February 8, 1979, EPA completed its firs t periodic review of the criteria and
standards for O 3 and other photochemical oxidants (44 FR 8202). In that action, EPA made significant revisions to the orig inal standard: the level of the primary and secondary NAAQS was changed to 0.12 ppm; the indicator was changed to O 3 ; and the form of the standards was changed to be based on the expected number of days per calendar year with a maximum hourly average concentration above 0.12 pp m (i.e., attainment of the sta ndard occurs when that number is equal to or less than one). On March 9, 1993, EPA concluded its sec ond periodic review of the criteria and
standards for O 3 by deciding that revisions to the O 3 NAAQS were not warrant ed at that time (58 FR 13008). The timing of this decision was require d by a court order issued to resolve a lawsuit filed to compel EPA to complete its revi ew of the criteria and standards for O 3 in accordance
with the Act. This decision reflected EPA's revi ew of relevant scientif ic and other information
assembled since the last revi ew, as contained in the 1986 O 3 CD (U.S. EPA, 1986), its Supplement (U.S. EPA, 1992), and the 1989 O 3 Staff Paper (U.S. EPA, 1989), although it did not take into consideration a larg e number of studies on the health and welfare effects of O 3 published since the literature was last assessed in the O 3 Supplement. The final decision emphasized the Administrator's intention to procee d as rapidly as possible with the next periodic review of the air quality crit eria and standards to consider the more recent information. Under a court-ordered schedule and a highly accelerated review process, EPA completed
its third review of the O 3 NAAQS on July 18, 1997, based on the 1996 O 3 CD (U.S. EPA, 1996a)
and 1996 O 3 Staff Paper (U.S. EPA, 1996b). EPA re vised the primary and secondary O 3 standards on the basis of the then latest scientific eviden ce linking exposures to ambient O 3 to
adverse health and welfare effects at levels al lowed by the 1-hr average standards (62 FR 38856).
The O 3 standards were revised by replacing the existi ng primary 1-hr average standard with an 8- hr average O 3 standard set at a level of 0.08 ppm. The form of the primary standard was changed to the annual fourth-highest daily maximum 8- hr average concentrati on, averaged over three years. The secondary O 3 standard was changed by making it identical in all respects to the revised primary standard.

1.2.3 Litigation Related to the 1997 Ozone Standards Following promulgation of the revised O 3 NAAQS, petitions for review were filed addressing a broad range of issu es. On May 14, 1999, in response to those challenges, the U.S.1-5 Court of Appeals for the Distri ct of Columbia Circuit (D.C. Circuit Court) remanded the O 3 NAAQS to EPA, finding that section 109 of th e Act, as interpreted by EPA, effected an unconstitutional delegation of legislative authority. 5 In addition, the D.C. Circuit Court directed that EPA should consider the potentia l beneficial health effects of O 3 pollution in shielding the public from the effects of solar ul traviolet (UV) radiation, as well as the adverse health effects. EPA petitioned the U.S. Supreme Court for ce rtiorari on the constitutional issue but did not request review of the D.C. Circuit Court ruling regarding its obligation to consider the potential beneficial health effects of O 3 . On February 27, 2001, the U.S. Supreme Court unanimously reversed the judgment of the D.C. Circuit Court on the constitutional issue, holding
that section 109 of the CAA does not delegate legislative power to the EPA in contravention of the Constitution, and remanded the cas e to the D.C. Circuit Court to consider those challenges to
the O 3 NAAQS that had not been addresse d by that Court’s earlier decisions. 6 On March 26, 2002, the D.C. Circuit Court issued its final decision, finding the 1997 O 3 NAAQS to be “neither arbitrary nor capricious,” and denying the remaining petitions for review. 7 In response to the D.C. Circuit Court’s rema nd to consider the potenti al beneficial health
effects of O 3 pollution in shielding the public from th e effects of solar (UV) radiation, on November 14, 2001, EPA proposed to leave th e 1997 8-hr NAAQS unchanged (66 FR 52768). After considering public comment on the propos ed decision, EPA reaffirmed the 8-hr O 3 NAAQS set in 1997 (68 FR 614). Finally, on Ap ril 30, 2004, EPA announced the decision to
make the 1-hr O 3 NAAQS no longer applicable to areas one year after the eff ective date of the designation of those areas for th e 8-hr NAAQS (69 FR 23966). For most areas, the date that the 1-hr NAAQS no longer applied was June 15, 2005. (See 40 CFR 50.9 for details.)

1.2.4 Current Ozone NAAQS Review EPA initiated the current NAAQS review in September 2000 with a call for information (65 FR 57810). A project work plan (U.S. EP A, 2002) for the prepar ation of the CD was released in November 2002 for CASAC and public re view. EPA held a series of workshops in mid-2003 on several draft chapters of the CD to obtain broad input from th e relevant scientific communities. These workshops helped to inform the preparation of the first draft CD (U.S. EPA, 2005a), which was released for CA SAC and public review on January 31, 2005.

5 American Trucking Associations v. EPA , 175 F.3d 1027 (D.C. Cir., 1999).

6 Whitman v. American Trucking Associations , 531 U.S. 457 (2001).

7 Whitman v. American Trucking Associations , 283 F.3d 355 (D.C. Cir. 2002).1-6 During the process of preparing the first dr aft CD, NCEA revised the planned format of the CD described in the 2002 work plan. These re visions were made as part of a collaborative effort with OAQPS staff to modify the review pro cess so as to enhance the Agency’s ability to meet this and future NAAQS review schedules. As described in Chapter 1 of the first draft CD, emphasis is placed on interpretativ e evaluation and integration of evidence in the main body of the document, with more detailed descriptions of individual studies being provided in a series of accompanying annexes. This change is intended to streamline the document so as to facilitate timely CASAC and public review and to focus more clearly on issues most relevant to the policy decisions to be made by the Administrator. Th e modified review pro cess envisions that key policy-relevant issues will be identified ear lier in the review process through enhanced collaboration between NCEA and OAQPS, leading to a more efficient linkage between the CD and the Staff Paper. At the CASAC meeting he ld on May 4-5, 2005, to review the first draft CD, this new format for the CD was met with gene ral approval of CASAC and the public. A second draft CD (EPA, 2005b) was released for CASA C and public review on August 31, 2005. In a February 16, 2006 letter to the Administrator, CASAC offered final comments on all chapters of the CD (Henderson, 2006a), and the final CD was released on March 21, 2006. In a June 8, 2006 letter to the Administrator, CA SAC offered additional advice to the Agency concerning Chapter 8 of the final CD (Integrative Synthesis) to he lp inform the second draft Staff Paper (Henderson, 2006b). The second draft Staff Paper was rel eased on July 17, 2006 and reviewed by the CASAC Ozone Panel on August 24 and 25, 2006. In an October 24, 2006 letter to the Administrator, CASAC provided advice and recommendations to the Agency concerning the second draft Staff Paper (Henderson, 2006c). Advice and recommendati ons from CASAC as well as public comments have been taken into account in preparing th is final Staff Paper. The schedule for completion of this review is governed by a consent decree resolving a lawsuit filed in March 2003 by a group of pl aintiffs representing national environmental organizations, alleging that EPA had failed to co mplete the current review within the period provided by statute. American Lung Association v. Whitman (No. 1:03CV00778, D.D.C. 2003). The modified consent decree that now governs th is review, entered by the court on December 16, 2004, provides that EPA sign for publication not ices of proposed and final rulemaking concerning its review of the O 3 NAAQS no later than March 28, 2007 and December 19, 2007, respectively. This consent decree was furthe r modified in October 2006 to change these proposed and final rulemaking dates to no later than May 30, 2007 and February 20, 2008, respectively. The EPA expects that these date s for signing the publicatio n notices of proposed and final rulemaking will now be extended to no later than June 20, 2007 and March 12, 2008, respectively.1-7 1.3 GENERAL APPROACH AND ORGANI ZATION OF THE DOCUMENT The policy assessment in this Staff Paper is based on staff’s evaluation of the policy implications of the scientific evidence containe d in the CD and results of quantitative analyses based on that evidence, as well as the views presented by CASAC and various stakeholders. Taken together, this information informs various conclusions and the identif ication of a range of options on certain elements of the O 3 standards under review. While the CD focuses on new
scientific information available since the last re view, it appropriately inte grates that information with scientific criteria from previous reviews. The quantitative analyses presented in this Staff Paper (and described in more detail in tec hnical support documents) are based on the most recently available air quality information, so as to provide current characterizations of O 3 air quality patterns and estimated health and enviro nmental risks related to exposure to ambient O 3 concentrations. Following this introductory chapter, the Staff Pa per is organized into three main parts: the
characterization of ambient O 3 air quality data; O 3 -related health effects and primary O 3 NAAQS; and O 3 -related welfare effects and secondary O 3 NAAQS. The content of these parts is discussed more fully below.
The characterization of ambient O 3 and related photochemical oxidants is presented in Chapter 2 and includes information on O 3 properties, current O 3 air quality patterns, historic trends, and background levels. This chapter pr ovides a frame of reference for subsequent
discussion of current and alternative O 3 NAAQS and alternative forms of O 3 standards. Chapters 3 through 6 comprise the second main part of this Staff Paper dealing with human health and primary standards. Chapter 3 presents an overview of key policy-relevant health effects evidence, major health-related co nclusions from the CD, and an examination of issues related to the quantita tive assessment of evidence from controlled human exposure and epidemiological studies. Chapters 4 and 5 desc ribe the scope and methods used in conducting human exposure and health risk assessments a nd present results from those assessments. Chapter 6 includes staff conclusi ons and policy recommendations on the adequacy of the current primary standard and on an appropriate rang e of alternative primary standards for the Administrator’s consideration, together with a di scussion of the science and public health policy judgments underlying such standards. Chapters 7 and 8 comprise the third main part of this Staff Paper. Chapter 7 presents a policy-relevant assessment of O 3 welfare effects evidence and di scusses the scope and methods used in conducting vegetation-related exposure and risk assessments. Chapter 8 includes staff conclusions and policy recommendations on the ade quacy of the current secondary standard and on an appropriate range of a lternative secondary standards that for the Administrator’s1-8 consideration, together with a discussion of the science and public welfare policy judgments underlying such standards.1-9 REFERENCES

Federal Register (1971) National Primary and Secondary Ambient Air Quality Standards for Photochemical Oxidants; Final rule. 40 CFR 50; Federal Register 36: 8186

. Federal Register (1979) National Prim ary and Secondary Ambient Air Quality Standards: Revisions to the National Ambient Air Quality Standards for Photochemical Ox idants, Final Rule. 40 CFR 50; Federal Register 44: 8202.

Federal Register (1993) National Ambient Air Quality Standa rds for Ozone, Final rule. 40 CFR 50; Federal Register 58: 13008.

Federal Register (1997) National Ambient Air Quality Standards for Ozone; Final Rule. 40 CFR 50; Federal Register 62: 38856.

Federal Register (2001) National Ambient Air Quality Standards for Ozone; Proposed Response to Remand; Proposed Rule. Federal Register 66: 57368.

Federal Register (2003) National Ambient Air Quality St andards for Ozone; Proposed Response to Remand. Final Rule. Federal Register 68: 614.

Henderson, R. (2006a) Letter from CASAC Chairman Rogene Henderson to EPA Administrator Stephen Johnson, February 16, 2006, EPA-CASAC-06-003.

Henderson, R. (2006b) Letter from CASAC Chairman Rogene Henderson to EPA Administrator Stephen Johnson, June 5, 2006, EPA-CASAC-06-007.

Henderson, R. (2006c) Letter from CASAC Chairman Rogene Henderson to EPA Administrator Stephen Johnson, October 24, 2006, EPA-CASAC-07-001.

U.S. Environmental Protection Agency. (1986) Air Quality Criteria for Ozone and Other Photochemical Oxidants. Research Triangle Park, NC: Office of Health and Environmental Assessment, Environmental Criteria and Assessment Office; EPA report nos. EPA-600/8-84-020aF-eF. Available from NTIS, Springfield, VA; PB87-142949.

U.S. Environmental Protection Agency (1992) Summary of selected new information on effects of ozone on health and vegetation: supplement to 1986 air quality criteria for ozone and other photochemical oxidants. Research Triangle Park, NC: Office of Health and Environmental Assessment, Environmental Criteria and Assessment Office; EPA report no. EPA/600/8-88/105F. Available from NTIS, Springfield, VA; PB92- 235670.

U.S. Environmental Protection Agency (1996) Air Quality Criteria for Ozone and Related Photochemical Oxidants. Research Triangle Park, NC: Office of Research an d Development; report nos. EPA/600/AP-93/004aF-cF. 3v. Available from: NTIS, Springfield, VA; PB96-185582, PB96-185590, and PB96-185608. Available online at: http://cfpub.epa.gov/ncea/cfm/ recordisplay.cfm?deid=2831

. U.S. Environmental Protection Agency (2002) Pr oject Work Plan for Revised Air Quality Criteria for Ozone and Related Photochemical Oxidants . Research Triangle Park, NC: National Center for Environmental Assessment-RTP Report no. NCEA-R-1068.

U.S. Environmental Protection Agency (2005a) Air Quality Criteria for Ozone and Related Photochemical Oxidants (First External Review Draft). Washington, DC, EPA/600/R-05/004aA-cA. Available online at: www.epa.gov/ncea/1-10 U.S. Environmental Protection Agency (2005b) Air Quality Criteria for Ozone and Related Photochemical Oxidants (Second External Review Draft). Washington, DC, EPA/600/R-05/004aB-cB. Available online at: www.epa.gov/ncea/

U.S. Environmental Protection Agency (2006) Air Quality Criteria for Ozone and Related Photochemical Oxidants (Final). Washington, DC, EPA/600/R-05/004aB-cB. Available online at: http://cfpub.epa.gov/ncea/cfm/r ecordisplay.cfm?deid=1373072-1 

### 2. AIR QUALITY CHARACTERIZATION

2.1 INTRODUCTION This chapter generally characterizes ambient ozone (O 3 ) and related photochemical
oxidants in terms of measuremen t methods, recent c oncentrations and tr ends, relationships between different air quality indicators, and estimates of policy-relevant background. This
information is useful for inte rpreting the available exposure, health, and welfare effects information, and for evaluating the adequacy of the current primary and secondary standards for

O 3 and developing options for altern ative standards. The information presented in this chapter was drawn from the 2006 Criteria Document (CD) and additional analyses of data from various

O 3 monitoring networks. This chapter particularly focuses on 1-hr, 8- hr, and 24-hr average concentrations metrics in characterizing urban O 3 air quality because these are the me trics most frequently used in the
health effect studies discussed in the CD and Chapter 3 of this Staff Paper. For the vegetation exposure and risk assessment discussed in Chap ter 7 of this Staff Paper, both the current secondary standard 8-hr. metric and the cumula tive, concentration-weighted metrics, SUM06
and W126 are used. Although this chapter focuses on 2002-2004 air qual ity data in order to be consistent with the CD, recent observations demonstrates the 2005 O 3 data show that national ambient
concentrations have decreased 20% since 1980 and 8% since 1990. 2005 concentrations were the second lowest on record with only 2004 le vels being lower by 5%. Meteorological
conditions for 2005 were similar to those obs erved in 2002 which was much hotter than 2004 and, therefore, more conducive to O 3 formation. Furthermore, the O 3 levels in 2005 were approximately 9% lower than those seen in 2002 for sites east of 100 degrees west longitude. One explanation for this difference can possibly be attributed to the implementation of the NO x SIP Call 1 which occurred in 2002 for many stat es east of the Mississippi River.

2.2 CHEMICAL AND PHYSICAL PROPERTI ES, FORMATION, AND TRANSPORT

2.2.1 Properties and Formation The atmosphere can be divided in to several distinct vertical layers, based primarily on the major mechanisms by which they are heated and cooled. The lowest major layer is the troposphere, which extends from the earth’s surfa ce to about 8 km above the surface in polar

1 EPA's rule, known as the NO x SIP Call, was designed to reduce regional transport of O 3 and O 3 -forming pollutants in the eastern half of the United States by requiring 21 states to reduce O 3 - season NO x emissions that contribute to nonattainment in other states.2-2 regions and to about 16 km above the surface in tropical regions. The planetary boundary layer (PBL) is the lower sub-layer of the troposphere , extending from the surface to about 1 or 2 km, and is most strongly affected by surface conditions. The stratosphere extends from the top of the troposphere, to about 50 km in altitude. The emphasis in this chapter is pl aced on concentrations
of O 3 occurring in the lower troposphere, in particular in th e PBL (CD, p.2-1). Ozone chemistry in the presence of sunlight, nitrogen oxides (NO x ) and volatile organic carbon (VOC) is well understood and a central com ponent of modern air quality models. The
chemical formation of O 3 in the troposphere results from th e oxidation of nitric oxide (NO) to nitrogen dioxide (NO 2 ) by organic (RO 2 ) or hydro-peroxy (HO 2 ) radicals. Photolysis (the chemical process of breaking dow n molecules into smaller units through the absorp tion of light)
of NO 2 yields NO and a ground-state oxygen atom, O( 3 P), which then reacts with molecular oxygen to form O 3 (CD, p.2-2). Oxidized nitrogen compounds are emitted to the atmosphere mainly as NO, which is
oxidized to NO 2 which subsequently can be reduced back to NO. Consequently, NO and NO 2 are often grouped together into their own family called NO x (CD, p.2-3). Oxidized nitrogen containing compounds are essential to the formation of O 3 in the air. There are a large number of oxidized nitrogen containing compounds in the atmosphere including NO, NO 2 , nitrate (NO 3 ), nitrous acid (HNO 2 ), nitric acid (HNO 3 ), nitrogen pentoxide (N 2 O 5 ), pernitric acid (HNO 4 ), peroxy acetyl nitrate (PAN) and its homologues, ot her organic nitrates and particulate nitrate. Collectively these species are referred to as NO y . NO x is considered a good surrogate for NO y and, thus, is commonly monitore d and reported (see Table 2-1). In urban areas, both biogenic and anthropogenic VOCs are important for O 3 formation.
Table 2-2 lists a variet y of VOC sources (see http://www.epa.gov/airtrends/econemissions.html ). The categories in the table are self explanatory w ith the exception of the fires and miscellaneous categories. The fires categor y includes both wild fire s and prescribed burns. The miscellaneous category includes mainly stru ctural fires and sources from agricultural activities. One category not in either table due to insufficient estimates is biogenic emissions. As can be seen in the table, highw ay vehicles have been the sing le largest source of anthropogenic VOC emissions over the years ranging from about 49% of total emissions in 1970 to about 27% of total emissions in 2004. Starting in 2001, so lvent use and highway vehicles were the two main sources of VOCs with roughly equa l contributions to the total emissions. In non-urban, vegetated areas, biogenic VOCs em itted from the vegetation tend to be the most important. In the remote troposphere, CH 4 and CO are the main carbon-containing precursors to O 3 formation. In coastal environments and other selected environments, atomic Cl
and Br radicals can also initiate the ox idation of VOCs (CD, p.2-2 and 2-3).2-3Table 2-1. NOx Emission Sources, 1970-2004Nitrogen Oxides (NOx)National Emissions Totals (thousands of tons)Source Category 1970 1975 1980 1985 1990 1991 1992 1993 1994FUEL COMB. ELEC. UTIL. 4,900 5,694 7,024 6,127 6,663 6,519 6,504 6,651 6,565FUEL COMB. INDUSTRIAL 4,325 4,0073,555 3,209 3,035 2,979 3,071 3,151 3,147FUEL COMB. OTHER 836 785 741 712 1,196 1,281 1,353 1,308 1,303CHEMICAL & ALLIED PRODUCT MFG 271 221 213 262 168 165 163 155 160METALS PROCESSING 77 73 65 87 97 76 81 83 91PETROLEUM & RELATED INDUSTRIES 240 63 72 124 153 121 148 123 117OTHER INDUSTRIAL PROCESSES 187 182 205 327 378 352 361 370 389SOLVENT UTILIZATION 0 0 0 2 1 2 3 3 3STORAGE & TRANSPORT 0 0 0 2 3 6 5 5 5WASTE DISPOSAL & RECYCLING 440 159 111 87 91 95 96 123 114HIGHWAY VEHICLES 12,624 12,061 11,493 10,932 9,592 9,449 9,306 9,162 9,019OFF-HIGHWAY 2,652 2,968 3,3533,576 3,781 3,849 3,915 3,981 4,047MISCELLANEOUS 330 165 248 310 369 286 255 241 390MISCELLANEOUS NA NA NA NA NA NA NA NA NATOTAL 26,883 26,377 27,079 25,75725,529 25,179 25,260 25,357 25,349Total without FIRES 26,883 26,37727,079 25,757 25,167 24,932 25,026 25,123 24,967FIRES NA NA NA NA 362 247 234 234 3822-4Table 2-1. NOx Emission Sources, 1970-2004 (cont’d)Nitrogen Oxides (NOx)National Emissions Totals (thousands of tons)Source Category 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004FUEL COMB. ELEC. UTIL. 6,384 6164 6276 6232 5721 5330 4917 4699 4270 3740FUEL COMB. INDUSTRIAL 3,144 3151 3101 3050 2709 2723 2757 2870 2870 2870FUEL COMB. OTHER 1,298 1197 1177 1101 768 766 779 725 725 725CHEMICAL & ALLIED PRODUCT MFG 158 125 127 129 102 105 107 105 105 105METALS PROCESSING 98 83 89 89 86 89 94 84 84 84PETROLEUM & RELATED INDUSTRIES 110 139 143 143 120 122 124 149 149 149OTHER INDUSTRIAL PROCESSES 399 433 460 467 451 479 504 487 487 487SOLVENT UTILIZATION 3 2 3 3 4 4 4 8 8 8STORAGE & TRANSPORT 6 15 16 16 14 15 16 16 16 16WASTE DISPOSAL & RECYCLING 99 153 157 163 162 129 130 152 152 152HIGHWAY VEHICLES 8,876 8733 8792 8619 8371 8394 7774 7365 7365 7365OFF-HIGHWAY 4,113 4179 4178 4156 4084 4167 4156 4086 4086 4086MISCELLANEOUS 267 412 187 179 251 276 184 356 356 356MISCELLANEOUS NA 0 0 0 0 0 0 0 0 0TOTAL 24,956 24787 24705 24348 22845 22598 21549 21102 20672 20142FIRES 258 405 179 172 236 263 171 341 341 341Total without FIRES 24,698 24,382 24,526 24,176 22,609 22,335 21,378 20,76120,33119,8012-5Table 2-2. VOC Emission Sources, 1970-2004Volatile Organic Compounds (VOC)National Totals (thousands of tons)Source Category 1970 1975 1980 1985 1990 1991 1992 1993 1994FUEL COMB. ELEC. UTIL. 30 40 45 32 47 44 44 45 45FUEL COMB. INDUSTRIAL 150 150 157 134 182 196 187 186 196FUEL COMB. OTHER 541 470 848 1,403 776 835 884 762 748CHEMICAL & ALLIED PRODUCT MFG 1,341 1,351 1,595 881 634 710 715 701 691METALS PROCESSING 394 336 273 76 122 123 124 124 126PETROLEUM & RELATED INDUSTRIES 1,194 1,342 1,440 703 611 640 632 649 647OTHER INDUSTRIAL PROCESSES 270 235 237 390 401 391 414 442 438SOLVENT UTILIZATION 7,174 5,6516,584 5,699 5,750 5,782 5,901 6,016 6,162STORAGE & TRANSPORT 1,954 2,1811,975 1,747 1,490 1,532 1,583 1,600 1,629WASTE DISPOSAL & RECYCLING 1,984 984 758 979 986 999 1,010 1,046 1,046HIGHWAY VEHICLES 16,910 15,392 13,869 12,354 9,388 8,860 8,332 7,804 7,277OFF-HIGHWAY 1,616 1,917 2,1922,439 2,662 2,709 2,754 2,799 2,845MISCELLANEOUS 1,101 716 1,134 566 1,059 756 486 556 720TOTAL 34,659 30,765 31,106 27,40424,108 23,577 23,066 22,730 22,569FIRES 917 587 1,024 465 983 678 407 478 638Total without FIRES 33,742 30,17830,082 26,939 23,125 22,899 22,659 22,252 21,9312-6Table 2-2. VOC Emission Sources, 1970-2004 (cont’d)Volatile Organic Compounds (VOC)National Totals (thousands of tons)Source Category 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004FUEL COMB. ELEC. UTIL. 44 50 52 56 54 62 61 52 52 52FUEL COMB. INDUSTRIAL 206 179 175 174 172 173 176 170 170 170FUEL COMB. OTHER 823 893 893 889 919 949 950 790 790 790CHEMICAL & ALLIED PRODUCT MFG 660 388 388 394 251 254 262 214 214 214METALS PROCESSING 125 73 78 78 66 67 71 69 69 69PETROLEUM & RELATED INDUSTRIES 642 477 487 485 457 428 441 375 375 375OTHER INDUSTRIAL PROCESSES 450 435 438 443 438 454 420 406 406 406SOLVENT UTILIZATION 6,183 5477 5621 5149 5036 4831 5012 4692 4692 4692STORAGE & TRANSPORT 1,652 1294 1328 1327 1237 1176 1192 1205 1205 1205WASTE DISPOSAL & RECYCLING 1,067 509 518 535 487 415 420 457 457 457HIGHWAY VEHICLES 6,749 6221 5985 5859 5681 5325 4952 4543 4543 4543OFF-HIGHWAY 2,890 2935 2752 2673 2682 2644 2622 2688 2688 2688MISCELLANEOUS 551 1940 816 718 791 733 532 883 883 883TOTAL 22,041 20871 19530 18782 18270 17512 17111 16544 16544 16544FIRES 464 1870 744 645 667 615 412 785 785 785Total without FIRES 21,577 19001 18786 18136 17603 16898 16699 15759 15759 157592-7 The effects of sunlight on O 3 formation, aside from the role of solar radiation in meteorological processes, depend on its intensity and its spectral distributi on. Intensity varies diurnally, seasonally, and with latitude, but the e ffect of latitude is strongest in the winter.
Ultraviolet radiation from the sun plays a key role in initiat ing the photochemical processes leading to O 3 formation and affects individual photolytic reaction steps. However, there is little empirical evidence in the literature directly linki ng day-to-day variations in observed surface UV
radiation levels with vari ations in tropospheric O 3 levels (CD, p.AX2-90).

2.2.2 Relationship of Ozone to Photochemical Oxidants The relationship between O 3 , other oxidants, and oxidati on products is complex and involves many factors. Most notably, O 3 acts as a generator of hydroxyl radicals (OH) propagating a variety of integrated and cascading reactions yielding additional oxidizing species (e.g., hydroperoxy radical, HO 2 ; organic peroxy radicals, RO 2 ; hydrogen peroxide, H 2 O 2 ; nitrogen dioxide, NO 2; many of which are short lived in the atmosphere. These “oxidizing” species would be expected, like O 3 , to interfere with cellular processes leading to adverse health
effects. Oxidants also drive the formation of particle bound sulfate, ni trate and organic carbon; which are principal components of secondarily formed PM 2.5 ; and influence positively the formation or reaction of toxic gases such as peroxy acetyl nitrate (PAN), aldehydes (e.g., formaldehyde, acetaldehyde, acrolein), organic nitr ates and organic amines. Furthermore, deposition and subsequent advers e aquatic and terrestrial effect s generally are enhanced through availability of reactive oxidant species. These “enhanced” deposition impacts include acidification, near field deposit ion of reactive mercury, and othe r nitrogen-based eutrophication effects (See Figure 2-1). Benefits of reducing O 3 extend beyond that associated with O 3 autonomously, given the role of O 3 as an oxidizing agent elev ating levels of atmospheric components responsible for a broad range of advers e human health and environmental impacts.

2.2.3 Transport The transport of O 3 and other secondary pollutants is determined by meteorological and chemical processes extending typi cally over spatial scales of several hundred kilometers (e.g., Civerolo et al., 2003; Rao et al., 2003). An analysis of the output of regional model studies conducted by Kasibhatla and Cham eides (2000) suggests that O 3 can be transported over a few thousand kilometers in the upper boundary layer of the eastern half of the United States during specific O 3 episodes. Convection is capable of transporting O 3 and its precursors vertically through the troposphere as shown in Annex AX2.3.2 of the CD. Noct urnal low-level jets (LLJs)2-8Figure 2-1. Atmospheric Processes Affecting the Formation of Photochemical Oxidants and Particulate Matter.Chemicallinks illustrating relationshipsacross, criteria pollutants and HAPs including mercury, as wellas connections across sources,secondarily formed species, gases, particulate matter and deposition. Primary emissions are distinguished from secondarily formedspecies. Note that this diagram is a highly condensed model that doesnot capture numerous variousheterogeneous processes andcomplex chemical pathways. Key atmospheric species that are involved in many reactions across pollutant categories include O3andthe hydroxyl radical, OH. Primary PM emissions are not included as they interact marginally with other other atmospheric species(adopted from NARSTO, 2002).2-9 can also transport pollutants hundreds of kilome ters over the mid-Atlan tic region, the central U.S. and California (Zhang et al., 2001). Tur bulence associated with LLJs can bring these pollutants to the surface and result in secondary O 3 maxima in the early morning in many locations. However, the presence of mountain barriers can limit both horizontal and vertical dispersion such as observed in Los Angeles and Me xico City resulting in a greater frequency and duration of days with high O 3 concentrations (CD, p.2-10).

2.3 DATA SOURCES Two main sources of monitoring data were used for this assessment, the state-supplied data from various types of monitors housed in the Air Quality System (A QS) data base (which includes National Park Service monitors) and the Clean Air Status and Trends Network (CASTNET). The vegetation exposure analysis also uses an enhanced Veroni Neighborhood Average (eVNA) spatial interpolation techniqu e to combine 2001 monitor data from both AQS
and CASTNET with 2001 modeled data from the Community Multi-scale Air Quality (CMAQ) model. This interpolated surface is used to fi ll in the gaps left by a sparse rural monitoring
network in the west ern United States. Air quality models are often used to simulate the formation, transport, and decay of air pollution. The CMAQ modeling system is a co mprehensive three-dimensional grid-based Eulerian air quality model designed to estimate O 3 and particulate concen trations and deposition over large spatial scales (De nnis et al., 1996; Byun and Chi ng, 1999; Byun and Schere, 2006). The CMAQ model is a publicly available, wi dely-used, peer-reviewe d, state-of-the-science model consisting of a number of science attributes that are critical for simulating the oxidant precursors and nonlinear organic and inorganic chemical relationships associated with the
formation of O 3 , as well as sulfate, nitr ate, and organic aerosols.

2.3.1 Air Quality System (AQS) EPA’s ambient air quality surveillance regu lations are found at 40 CFR Part 58. Section 58.20 requires States to provide for the establishmen t of air quality surveill ance systems in their State Implementation Plans (SIP). The air quality surveillance system consists of a network of monitoring stations designated as State and Local Air Monitoring Stations (SLAMS), which
measure ambient concentrations of those pollutants for which standa rds have been established in 40 CFR Part 50. SLAMS, National Air Monitori ng Stations (NAMS), which are a subset of SLAMS, and Photochemical Assessment Mon itoring Stations (PAMS) must meet the requirements of 40 CFR Part 58, Appendices A (Q uality Assurance Requirements), C (Ambient Air Quality Monitoring Methodolog y), D (Network Design Criteri a), and E (Probe and Path Siting Criteria).2-10 The Air Quality System (AQS) is EPA's repository of ambient air quality data. AQS stores data from over 10,000 monitors; 5000 of wh ich are currently active. Of these, over 3000 measure and report O 3 concentration data (See Figure 2-2). These monitors make up the SLAMS, PAMS, NAMS, and other special purpose monitors used and operated by the States. AQS also contains meteorological data, descri ptive information about each monitoring station (including its geographic location and its operator), and data quality assura nce/quality control information. The Office of Air Quality Planni ng and Standards (OAQPS) and other AQS users rely upon the data system to assess air quality, assist in Attainment/Non-Attainment designations, evaluate State Implementation Plan s for Non-Attainment Areas, perform modeling for permit review analysis, and ot her air quality management functions. AQS information is also used to prepare reports for Congress as mandated by the Clean Air Act (see http://www.epa.gov/ttn/airs/airsaqs/sysoverview.htm ).
The NAMS/PAMS/SLAMS O 3 monitor network achieved an overall average bias (upper bound) of 0.2% and an overall mean precision of 3% for 2002. If special purpose and other O 3 monitors are also included the average upper bou nds of bias and precisi on were 0.4% and 2.9% respectively (U.S. EPA 2004a).

2.3.2 CASTNET

CASTNET is the nation's primary source for data on dry acidic deposition and rural, ground-level O 3 . Operating since 1987, CASTNET is used in conjunction with other national monitoring networks to provide information for ev aluating the effectiveness of national emission control strategies. CASTNET consists of over 80 sites across the eastern and western United States (see Figure 2-2) and is cooperatively operate d and funded with the National Park Service. In 1986, EPA established the National Dry Depos ition Network (NDDN) to obtain field data on rural deposition patterns and tr ends at different locations throughout the United States. The
network consisted of 50 monitori ng sites that derived dry depos ition data based on measured air pollutant concentrations and modeled dry deposi tion velocities estimated from meteorology, land use, and site characteristic data. In 1990, amen dments to the Clean Air Act necessitated a longterm, national program to monitor the status and trends of air pollutant emissions, ambient air quality, and pollutant deposition. In response, EP A, in cooperation with the National Oceanic Atmospheric Administration (NOA A), created CASTNET from NDDN. In terms of data quality, CASTNET achieved 98% to 99% of all precision and accuracy audits being within the ±10% criteria for both precision a nd accuracy. Overall, CASTNET O 3 monitors are stable showing only very small variation (U.S. EPA 2003, p.22).2-11(((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((( ((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((( ((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((( ((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((( (((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((( (((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((( ((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((( (((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!SOURCE(AQS!CASTNET(((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((( ((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((( ((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((( ((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((( (((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((( (((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((( ((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((( (((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((( (((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((( ((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((( (((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((( (((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((( ((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((( (((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((( (((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!SOURCE(AQS!CASTNETFigure 2-2. Locations of Ozone Monitors from AQS and CASTNET2-12 2.4 OZONE MONITORING METHODS AND DATA QUALITY 2.4.1 Ozone Monitoring Methods Ozone monitoring is conducted almost exclus ively with UV absorption spectrometry with commercial short path instruments, a method that has been thoroughly evaluated in clean air. The ultimate reference method is a relatively long-p ath UV absorption instrument maintained under carefully controlled conditions at the Nationa l Institute of Standards and Technology (NIST) (CD, p.2-22). Most O 3 UV instruments reference the NI ST method through a network of Standard Reference Photometers (SRPs) that are maintained and operated by EPA. Several reports in the reviewed scientific li terature have investigated interferences in O 3 detection via UV radiation absorption and chemilu minescence which is the reference method but almost never employed. These include the eff ects of water vapor, VOC’s, aromatic compounds and their oxidation products, and other organi c and inorganic compounds. Water vapor had no significant impact on UV absorption-based instrume nts, but could cause a positive interference of up to 9% in chemiluminescence-based detectors at high humidities (dew point of 24 ° C). Aromatic compounds and their oxi dation products were found to ge nerate a positive but small interference in the UV absorption instruments. Howe ver, when the results are applied to ambient
concentrations of toluene and NO

x , the effect appears to be very minor (about 3 percent under the study conditions). Other organic and inorganic compounds displayed interferences, but not at levels likely to interfere with accurate determination of O 3 in an urban environment (CD, p.2-25). Although not widely used, O 3 measurements by differential optical absorption spectroscopy (DOAS) at a variety of wavelengths in the UV and vi sible parts of the spectrum. Comparisons of DOAS results to those fr om a UV absorption instrument showed good agreement on the order of 10%. Researchers have reported a positive interference due to an
unidentified absorber in the 279 to 289 nm spectral region used by many commercial short-path DOAS systems for the measurement of O 3 . Results of that study suggest that compounds from wood burning, used for domestic heating, may be responsible (CD, p.AX2-149).

2.4.1 Effect of Measurement Precision on 8 hour Ozone Averages Staff conducted an analysis to determine the precision of an 8-hr averaged O 3 concentration (Cox and Camalier, 2006). Daily maximum 8-hr O 3 values were simulated using a Weibull distribution to yield a “true” three-year averaged O 3 design value without the influence
of measurement error. From 2002 to 2004, the average pr ecision in the collected O 3 measurements is approximately 3%. This means, for example, that a 1-hr measured concentration of 0.100 ppm could be between 0.097 ppm and 0.103 ppm. Utilizing precision data from 900 O 3 monitors for2-13 the 2002 through 2004 O 3 seasons, a second set of 8-hr O 3 concentrations was generated to incorporate the precision data from the O 3 monitoring network to account for instrument
measurement error. The result was a value which reflected the “true” O 3 design value plus
measurement error. The difference between th e value with measurement error and the “true value” reflects the impact of the instrument measurement error on the calculated 8-hr design
value. The exercise was repeated 1000 times and th e differences between the two previously described design values were su mmarized. Table 2-3 shows the results of the analysis. The percentiles presented in the tabl e reflect the percentage of site s at or below the corresponding 1- hour precision value. The table shows that even at a precision of approximately 4.5%, of which
95% of the O 3 sites are at or below, the standard de viation of the difference between the 8-hr design values is less than 0.001 ppm. A second exercise was performed to incorporat e systematic bias error which includes the instrument drift, noise, precisi on and calibration error associated with the UV absorption method.
It was assumed that each 8-hr measurement was s ubjected to this randomly occurring bias which had an average of zero and a standard deviat ion of approximately 0.004 ppm. The mean and
standard deviation utilized for the simulation were believed to be reasonable estimates for monitors operating under normal conditions. The re sults of this exercise show that assuming a random bias of 0.004 ppm produced an uncertainty in the 8-hr design value of approximately 0.001 ppm. This analysis supports expressing the level of the standard to the nearest thousandth (three decimal places) part per million (ppm), wh ich is equivalent to th e nearest part per billion (ppb). 2 The State of California also reached a si milar conclusion regarding the precision of the existing ozone monitoring methodology (Califor nia Environmental Protection Agency, 2005).

2.5 CHARACTERIZATION OF GROUND-LE VEL OZONE CONCENTRATIONS

2.5.1 Metrics This section characterizes ground level O 3 concentrations based on several metrics. Two daily maximum statistics, 1-hr and 8-hr averages, and one daily average statistic in the form of a 24-hr concentration, and two cumulative concen tration weighted statistics, SUM06 and W126,
are summarized to show how O 3 varies over space and time. The 1-hr and 8-hr daily maximum averaging times reflect the former and current O 3 standards, and much of the health effects
literature for O 3 has focused on effects associated with these averaging times. The 24-hr daily

2 Under the current standard, a rounding convention is used to determine attainment where the design value is rounded to the nearest 0.01 ppm. A Nati onal Ambient Air Quality Standard expressed to the nearest 0.001 ppm would mean that the current rounding conventions become trivial. However, it is envisioned that the data handling guideline within the current regulation where digits past the third deci mal place are truncated would be retained.2-14Table 2-3. Relationship between Precision of 1-hour OzoneData and Corresponding Standard Deviation of 8-hour DesignValuesPrecision of 1- hourozone value (%)Nationwide PercentileStandard Deviation ofDifference in DV's (ppb)1.63 25 0.272.22 50 0.342.97 75 0.453.89 90 0.574.52 95 0.632-15 average has been used for several personal exposure studies (CD, pp.3-72 – 74). The SUM06 and W126 have been used frequently in the scie ntific literature and CD in studying and assessing the relationship between O 3 exposures and adverse effects on vegetation. The daily maximum 8- hr values are found by first calc ulating running or moving 8-hr va lues for all 24 hours in a day (for example, averaging the 1-hr concentrations from 1:00am to 8:00 am, then average the 1-hr values from 2:00am to 9:00 am, etc.). Then th e maximum value for each day is found (note that any 8-hr time period that starts in a day is assigned to that day). On an annual basis, the fourth highest of these values is su mmarized. The daily maximum 1-hr statistic is the maximum value of all 1-hr values in a day. On an annual basis, the second highest of these values in a year is summarized. The 24-hr average is a mean of the 24 individual hour ly concentrations measured from midnight to midnight. The maximum, 3 month, 12 hour SUM06 statisti c is calculated by cumulating all 1-hr values greater than or equal to 0.06ppm that occur during the12 hour daytime window (8:00am to 8:00pm Local Standard Time). For each month of the O 3 monitoring season, the largest
consecutive 3-month sum of the da ily values is calculated accor ding to the secondary standard proposed in 1996 (61 FR 65638), but not adopted in 1997 (62 FR 38856). The SUM06 has a weighting function that is 0 wh en the concentration is less than 0.06 and is 1.0 when the concentration is greater than or equal to 0.06. The W126 seasonal cumulative statistics is calculated similarly to the SUM06 statistic. Th e only difference is the weighting function where the W126 statistic is a continuous, sigmoidal we ighting function with an inflections point between 0.06ppm and 0.07ppm (Lefohn and Runeckles, 1987).

2.5.2 Spatial Variability This section characterizes the spatial variability of O 3 based on all the metrics discussed above. Spatial variability is base d on maps displaying county levels of the various metrics. In this way different levels of O 3 for different areas of the country are displayed. It should be noted that county areas can be much la rger in the West than in the Ea st, but monitors are not spread evenly within a county. As a result, the a ssigned concentration range might not represent conditions throughout a particular county.

2.5.2.1 Distributions of 1-hr, 8-hr , and 24-hr Ozone Metrics Figures 2-3 to 2-5 show the distributions for measured 1-hr, 8- hr, and 24-hour daily average O 3 concentrations for 12 major urban areas in the United States. The Los Angeles area clearly has a distribution which is different from the other 11 cities, in that the hourly concentration interquartile range is within 0.057 to 0.089 ppm as opposed to the next highest interquartile range of Sacramento where 50% of the hourly concentrations lie between 0.056 and 0.079 ppm. In comparison, Houston which also has several 1-hr concentrations greater than2-16

Ozone Concentration (ppm)0.000.010.020.030.040.050.060.070.080.090.100.110.120.130.140.150.160.170.180.190.20CityFigure 2-3. 1-hr Ozone Distributions across 12 Risk Areas, 2002-2004.Box Depicts interquartile range and median; the dotdepicts the mean; whiskers depict 10thand 90th percentile; and ‘x’depicts values outside the10th and 90th percentile.Data Source: AQS2-17

Ozone Concentration (ppm)0.000.010.020.030.040.050.060.070.080.090.100.110.120.130.140.150.16CityFigure 2-4. 8-hr Ozone Distributions across 12 Risk Areas, 2002-2004.Box Depicts interquartile range and median; the dotdepicts the mean; whiskers depict 10thand 90th percentile; and ‘x’depicts values outside the10th and 90th percentile.Data Source: AQS2-18

Ozone Concentration (ppm)0.000.010.020.030.040.050.060.070.080.090.100.110.12CityFigure 2-5. 24-hr Ozone Distributionsacross 12 Risk Areas, 2002-2004.Box Depicts interquartile range and median; the dotdepicts the mean; whiskers depict 10thand 90th percentile; and ‘x’depicts values outside the10th and 90th percentile.Data Source: AQS2-19 0.125 ppm has a lower interquartile range of 0.034 to 0.07 ppm with 10% of its hourly values greater than 0.089 ppm as opposed to approximately 0.106 ppm for Los Angeles. Houston also has a larger interquartile range of 0.036 ppm when compared to the average of the remaining 11 cities of 0.025 ppm. This trend is also observed in the 8-hr averaged concentrations. The remaining 9 cities exhibit similar distributions to one another for all three metrics (1-hr, 8-hr, and 24-hr). For the 24-hour daily averaged concentra tion distributions, Houston shows a lower 75 th percentile than the other cities with areas like Cleveland, Ph iladelphia and New York having higher distributions. The lower 24 hour concen trations in Houston i ndicate a wider range between the daily O 3 minima and maxima unlike an ar ea like Cleveland, which has a higher interquartile range.

2.5.2.2 8-Hour and 1-Hour Statistics High 8-hr average O 3 concentrations tend to occur n ear larger urban areas exhibiting similar patterns as corresponding 1- hr concentrations (see Figure 2-6). Elevated 8-hr levels occurring in smaller urban and non-urban areas are most likely cau sed by transport. Higher 8-hr

O 3 levels observed in smaller urban and non-urban areas are mo st obvious at the end of the northeast corridor (the highly ur banized area running from Wa shington, DC to Boston, MA), North-central New York, and the Northern coast of Lake Michigan. Some of the highest levels occur not only in California, but also in Texas as well as some counties in the Northeast Corridor
and isolated counties in the East (see Figure 2-7) (Fitz-Simons, et al., 2005). The highest 1-hr
levels occur in California. (Fitz-Simons, et al., 2005).

2.5.2.3 Cumulative Concentratio n-Weighted Statistics The highest SUM06 and W126 levels in 2001 (m ost of the analyses in Chapter 7 center on 2001 data) occurred in most of th e agricultural areas of Californi a. When the data were from CASTNET sites, more purely ru ral counties showed higher valu es (See Figures 2-8 through 2- 11) (Fitz-Simons, et al., 2005). The SUM06 and W126 values experience d a sharp decline in 2004 when compared to 2002 primarily in the easter n part of the United States (See Figure 2-12 through 2-15). Although there were reductions in the West, the decreases in the East were more
substantial. As discussed in section 2.1, the overall reductions across the country could possibly be due to lower temperatures experienced during the O 3 season. However, the eastern half of the country was also subject to the emission control requirements implemented under the NO x SIP Call which occurred after 2002. The improvements s een in 2004 for the East are most likely due to a combination of cooler weather, the emission reductions from the NO x SIP Call, and emission
reductions from mobile source and ot her stationary source rules.2-20Concentration PPM X < 0.100; 364 Counties; 63,252,165 People (2000 census)0.125 <= X; 16 Counties; 26,021,093 People0.100 <= X < 0.125; 264 Counties; 100,568,984 PeopleFigure 2-6. Average 2nd Highest Daily Maximum 1-hour Values in U.S. Counties, 2002-2004 AQS Data.2-21Concentration PPM X < 0.074; 140 Counties; 27,502,811 People (2000 census)0.085 <= X; 210 Counties; 96,172,263 People0.074 <= X < 0.085; 294 Counties; 66,167,168 PeopleFigure 2-7. Average 4th Highest Daily Maximum 8-hour Values in U.S. Counties, 2002-2004 AQS Data.2-22Concentration PPM-Hour SUM06<15 15<=SUM06<2525<=SUM06<38 38<=SUM06Figure 2-8. Highest 3-month 12-hour SUM06 Exposure Index in U.S. Counties, 2001 AQS Data.2-23Figure 2-9. Highest 3-month 12-hour W126 Exposure Index in U.S. Counties, 2001 AQS Data.W126<1313<=W126<2121<=W126<3131<=W126Concentration PPM-Hour2-24Concentration PPM-Hour SUM06<15 15<=SUM06<2525<=SUM06<38 38<=SUM06Figure 2-10. Highest 3-month 12-hour SUM06 Exposure Index in U.S. Counties, 2001 CASTNET Data.2-25Figure 2-11. Highest 3-month 12-hour W126 Exposure Index in U.S. Counties, 2001 CASTNET Data.Concentration PPM-HourW126<1313<=W126<2121<=W126<3131<=W1262-26Concentration PPM-Hour SUM06<15 15<=SUM06<2525<=SUM06<38 38<=SUM06Figure 2-12. Highest 3-month 12-hour SUM06 Exposure Index in U.S. Counties, 2002 AQS and CASTNET Data.2-27Figure 2-13. Highest 3-month 12-hour W1126 Exposure Index in U.S. Counties, 2002 AQS and CASTNET Data.Concentration PPM-HourW126<1313<=W126<2121<=W126<3131<=W1262-28Concentration PPM-Hour SUM06<15 15<=SUM06<2525<=SUM06<38 38<=SUM06Figure 2-14. Highest 3-month 12-hour SUM06 ExposureIndex in U.S. Counties, 2004 AQS and CASTNET Data.2-29Figure 2-15. Highest 3-month 12-hour W126 Exposure Index in U.S. Counties, 2004 AQS and CASTNET Data.Concentration PPM-HourW126<1313<=W126<2121<=W126<3131<=W1262-30 2.5.3 Temporal Variability Temporal variability consists of several tim e frames when considering characterization of ground level air quality data. Multi -year variability charac terizes long term variability or year to year variability. Trends usually provide evidence on whether or not air quality is improving over time. For the purposes of displaying long term trends, the data from both AQS and CASTNET are screened for temporally consistent data (onl y data from sites that meet a data completeness criteria of 12 complete years out of 15 and no gaps of more than 3 consecutive years are included). Seasonal variability characterizes mont h to month variability to demonstrate when in the year the highest concentrati ons occur. Diurnal variability characterizes hour-to-hour changes demonstrating when, in the day, the highest c oncentrations occur (Fit z-Simons, et al., 2005).

2.5.3.1 Long Term Variability – Trends Long term, nationwide trends for 8-hr O 3 values are presented in Figures 2-16 and 2-17. Figure 2-16 presents data from sites in the AQS that meet trends criteria and have locations
described as Urban and Center C ity. Figure 2-17 presents data from CASTNET which are rural
locations. The rural and urban trends are similar, but the urban trends have more data and more variation. The rural means are slightly lower th an the urban means; how ever the largest urban concentrations are much higher th an the largest rural concentrations (Fitz-Simons, et al., 2005). Long term trends for 1-hr O 3 values are presented in Figur es 2-18 and 2-19. Figure 2-18 presents data from sites in the AQS that meet trends criteria and have locations described as Urban and Center City. Figure 2- 19 presents data from CASTNET which are rural locations. As with the 8-hr data, the 1-hr urban trends and rura l trends are similar, but urban have more data
and more variation. The 1-hr means for the urba n trends are higher than the means for the rural trends. This difference is more pronounced than in the 8-hr trends (Fitz-Simons, et al., 2005). The long term trends for both 1-hr and 8-hr O 3 data are similar. The 8-hr concentrations are lower, but the trends are basically parallel. The urban area peak values in both the 1-hr and
8-hr concentrations have shown a gradual decline during the 15-y ear period, while the mean and
median concentrations have not varied much. The highest means occur in 1990, 1991, 1995, 1998 and 2002. The highest extreme values are clear ly in the 1990s. In many cases, short term variation (3 years or less) is as sociated with meteorological conditi ons that are generally more or
less conducive to O 3 formation in a particular year. One high year between two low years or one low year between two higher years are examples of this 3 years or less variation (see Evaluating Ozone Control Programs in the Eastern United States: NO X p.17, U.S. EPA, 2005b)2-31Urban

Ozone Concentration (ppm)0.000.020.040.060.080.100.120.140.160.180.201990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004487505505543545569560592602618633650670670670Figure 2-16. 4th Highest Daily Maximum 8-hour Ozone Values 1990-2004 (Urban).Box Depicts interquartile range and median;the dot depicts the mean; whiskers depict10th and 90th percentile; ‘x’ depicts values outsidethe 10th and 90th percentile; andnumbers above the boxes depicts the number of sites.Data Source: AQS2-32Rural

Ozone Concentration (ppm)0.000.020.040.060.080.100.120.140.160.180.201990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004525555515255556672757575767781Figure 2-17. 4th Highest Daily Maximum 8-hour Ozone Values 1990-2004 (Rural).Box Depicts interquartile range and median;the dot depicts the mean; whiskers depict10th and 90th percentile; ‘x’ depicts values outsidethe 10th and 90th percentile; andnumbers above the boxes depicts the number of sites.Data Source: CASTNET2-33Urban

Ozone Concentration (ppm)0.000.020.040.060.080.100.120.140.160.180.200.220.240.260.280.300.321990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004494507513547546572566595604620631650668667671Figure 2-18. 2nd Highest Daily Maximum 1-hour Ozone Values 1990-2004 (Urban).Box Depicts interquartile range and median;the dot depicts the mean; whiskers depict10th and 90th percentile; ‘x’ depicts values outsidethe 10th and 90th percentile; andnumbers above the boxes depicts the number of sites.Data Source: AQS2-34Rural

Ozone Concentration (ppm)0.000.020.040.060.080.100.120.140.160.180.200.220.240.260.280.300.321990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004525555515255556672757575767780Figure 2-19. 2nd Highest Daily Maximum 1-hour Ozone Values 1990-2004 (Rural).Box Depicts interquartile range and median;the dot depicts the mean; whiskers depict10th and 90th percentile; ‘x’ depicts values outsidethe 10th and 90th percentile; andnumbers above the boxes depicts the number of sites.Data Source: CASTNET2-35 2.5.3.2 Short Term Variability – Annual Figure 2-20 shows a map of the number of exceedance days for 2002 and 2004 at 12 urban locations in the United States. Each gr ouping of two bars represents the number of exceedance days for 1-hr, 8-hr averaged and 24-hr averaged O 3 concentrations. The 1-hr
measured concentrations were co mpared to the previous 1-hr O 3 standard of 0.12 ppm, 8 hour averaged concentrations were compared to the current O 3 standard of 0.08 ppm and the average 24 hour concentrations were compared to 0.055 ppm which is the 95 th percentile for 24 hour O 3 concentrations across the United States for 2002 th rough 2004. The data show that in all sites in the Midwest and the East, O 3 concentrations were down drama tically in 2004 when compared to 2002. This is due in part to the fact that 2004 wa s much cooler than 2002. The reduction in peak

O 3 concentrations also reflects the improvement in air quality due to emission reductions from
the NO x SIP Call, mobile source and other stationary source rules. The NOx SIP Call provided large NO x reductions in the eastern part of the co untry in 2003 and 2004, thereby reducing peak

O 3 concentrations (U.S. EPA, 2005b). The numbe r of 8-hr exceedance days actually increased for Houston while showing a decrease in Los Angeles. The difference between 2002 and 2004 for days greater than 0.055 ppm for the 24 hour aver aged concentrations is smaller for the three cities west of the Mississippi River than it is for cities in the eastern United States.

2.5.3.3 Seasonal Variability Monthly statistics are the best method to characterize seas onal variation in O 3 concentrations. However in many areas, monitors are not active during cooler months. As a result, data from May through September are the onl y universally available data for all monitors. Although this is a limited characterization of season al variability, it is cons istent across the entire
national network. Figure 2-21 shows box-plots of all 2004 da ta from May through September for the second highest daily 1-hr maximums. The cen ter of the distribution shows a slight, steady increase from May to September while the ex treme values show a more pronounced but more variable increase for the same pe riod (Fitz-Simons, et al., 2005). Figure 2-22 shows box-plots of all 2004 data fr om May through September for the fourth highest daily 8-hr maximums. The center of th e distribution and the ex tremes show a slight, steady increase from May to July followed by a slight decrease from July through September (Fitz-Simons, et al., 2005).

2.5.3.4 Short Term Variability – Diurnal The daily cycles of human ac tivity and the solar phase driv e the hour-to-hour daily cycle seen in ground level O 3 concentrations. The daily 1-hr p eak levels generally occur in the
afternoon with the lowest concen tration occurring in the early morning. However, on any given2-36AtlantaBostonChicagoClevelandDetroitHoustonLos AngelesNew YorkPhiladelphiaSacramentoSt. LouisWashington, DC20028-hr24-hr2004 2002 20042002 20041-hrFigure 2-20. Comparison of 1-hr, 8-hr, and24-hr Metrics for 2002 and 2004, 12 Risk AreasData Source: AQS2-37

Ozone Concentration (ppm)0.000.020.040.060.080.100.120.140.160.180.200.220.240.260.280.300.32May June July August September3011002976913378Figure 2-21. 2nd Highest Daily Maximum 1-hour Ozone Values from 2004 by Month.Box Depicts interquartile range andmedian; the dot depicts the mean; whiskers depict 10th and 90thpercentile; ‘x’ depicts valuesoutside the 10th and 90th percentile;and numbers above the boxes depicts the number of sites.Data Source: AQS2-38

Ozone Concentration (ppm)0.000.020.040.060.080.100.120.140.160.180.20May June July August September3601053940800392Figure 2-22. 4th Highest Daily Maximum 8-hour Ozone Values from 2004 by Month.Box Depicts interquartile range andmedian; the dot depicts the mean; whiskers depict 10th and 90thpercentile; ‘x’ depicts valuesoutside the 10th and 90th percentile;and numbers above the boxes depicts the number of sites.Data Source: AQS2-39 day when conditions are right, this phase can be reversed with the highest values occurring at night or early morning. Ozone tran sport can also effect at what time peaks can occur. For example, some sites in Maine peak late in the evening due to transport. In order to examine diurnal patterns, box-plot s summarize 1-hr values and 8-hr for each hour in the day. Figures 2-23 and 2-24 summarize 1-hr data from AQS th at was classified as urban and center city. The pattern is similar for both weekend and week day data. The pattern
of the center of the distribution of values show s a smooth sinusoidal port ion of the curve from 6:00AM until 8:00PM and reaches a peak at 1:00 PM to 3:00 PM. Then the pattern alters to a gradual decrease from 9:00 PM to 6:00AM (Fitz-Simons, et al., 2005). Figures 2-25 and 2-26 show the same set of summaries for 8-hr data. 8-hr values run
from 0 to 23 hours. Hour1 is the av erage of 1-hr values from 1 to 8 while hour 2 is the average of
hours 2 to 9 and so on. The main difference between th e 1-hr data and the 8-hr data is that the 8-
hr data exhibit a smoother sinusoi dal pattern throughout the day with a peak for the center of the distribution occurring at 10:00 AM or 11:00 AM and a minimum at about 12:00 midnight. The week end pattern is similar to the week day pattern (Fitz-Simons, et al., 2005). Figures 2-27 through 2-30 summarize 1-hr a nd 8-hr data from CA STNET sites which are
considered rural. Several differences are not ed here. The patterns for the center of the distribution are similar to the patt erns for the urban sites. The la rgest values of the 1-hr data exhibit no pattern but the largest values for the 8-hr data have a discernable pattern that differs from the patterns for the values in the center of the distribution. The weekday pattern for the highest values, shown in figure 2-29, has a smoot h sinusoidal pattern but reaches 2 peaks in the day (12:00 midnight and 12:00 noon). The weekend pattern, shown in figure 2-30, also shows a pronounced peak in the afternoon at about 1:00 PM which occurs about 2 hours after the peak for
the values in the center of the di stribution (Fitz-Simons, et al., 2005).

2.6 CHARACTERIZATION OF OZONE EPISODES Major episodes of high O 3 concentrations in the United St ates are associated with slow moving, high pressure systems. High pressure sy stems during the warmer seasons are associated with the sinking of air, resulting in warm, ge nerally cloudless skies, wi th light winds. These conditions result in the development of stable air masses near the surf ace which inhibit the vertical mixing of O 3 precursors. The combination of inhibited limited vertical mixing and light winds minimizes the dispersal of pollutants emitte d in urban areas, allowi ng their concentrations to build up. Photochemical activity involving these precursors is al so enhanced because of higher temperatures and the availability of sunlight. Downward entrainment of overnight transported O 3 and precursors trapped al oft begins on the following day as th e PBL starts growing. In the2-4022 23 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18 19 20 21 22 23 00 0100.0500.1000.1500.200

1 hour ozone (ppm)hourFigure 2-23. 1-Hour Diurnal Week Day Patternfor Urban Sites, May through September 2004.Box Depicts interquartile rangeand median; whiskers depict maximum andminimum values; and ‘+’ depicts the mean.Data Source: AQS2-4122 23 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18 19 20 21 22 23 00 0100.0500.1000.1500.200

1 hour ozone (ppm)hourFigure 2-24. 1-Hour Diurnal Week End Patternfor Urban Sites, May through September 2004.Box Depicts interquartile rangeand median; whiskers depict maximum andminimum values; and ‘+’ depicts the mean.Data Source: AQS2-4222 23 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18 19 20 21 22 23 00 010.0000.0250.0500.0750.1000.125

8 hour ozone (ppm)hourFigure 2-25. 8-Hour Diurnal Week Day Patternfor Urban Sites, May through September 2004.Box Depicts interquartile rangeand median; whiskers depict maximum andminimum values; and ‘+’ depicts the mean.Data Source: AQS2-4322 23 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18 19 20 21 22 23 00 010.0000.0250.0500.0750.1000.125

8 hour ozone (ppm)hourFigure 2-26. 8-Hour Diurnal Week End Patternfor Urban Sites, May through September 2004.Box Depicts interquartile rangeand median; whiskers depict maximum andminimum values; and ‘+’ depicts the mean.Data Source: AQS2-4422 23 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18 19 20 21 22 23 00 01-0.05000.0500.1000.150

1-hour ozone (ppm)hourFigure 2-27 1-Hour Week Day Diurnal Patternfor Rural Sites, May through September 2004.Box Depicts interquartile rangeand median; whiskers depict maximum andminimum values; and ‘+’ depicts the mean.Data Source: CASTNET2-4522 23 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18 19 20 21 22 23 00 01-0.05000.0500.1000.1500.200

1-hour ozone (ppm)hourFigure 2-28. 1-Hour Week End Diurnal Patternfor Rural Sites, May through September 2004.Box Depicts interquartile rangeand median; whiskers depict maximum andminimum values; and ‘+’ depicts the mean.Data Source: CASTNET2-4622 23 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18 19 20 21 22 23 00 01-0.02500.0250.0500.0750.1000.1250.150

8-hour ozone (ppm)hourFigure 2-29. 8-Hour Week DayDiurnal Pattern for Rural Sites, May through September 2004.Box Depicts interquartile rangeand median; whiskers depict maximum andminimum values; and ‘+’ depicts the mean.Data Source: CASTNET2-4722 23 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18 19 20 21 22 23 00 01-0.02500.0250.0500.0750.1000.1250.150

8-hour ozone (ppm)hourFigure 2-30. 8-Hour Week End Diurnal Patternfor Rural Sites, May through September 2004.Box Depicts interquartile rangeand median; whiskers depict maximum andminimum values; and ‘+’ depicts the mean.Data Source: CASTNET2-48 eastern United States, high O 3 concentrations during an episode can extend over hundreds of thousands of square kilometers for several days. Episodes have two main characteristics: the concentration level reach ed and the length of
time that this level is reached in consecutive da ys. The following discussion addresses how these characteristics of episodes have varied through both space and time. Numbers of episodes define d by daily maximum 1-hr O 3 concentrations reaching a level of 0.12 ppm for 1 day generally follow the long term trend of central valu es (means or medians)
of the 1-hr O 3 data (See Figures 2-18 and 2-31). As th e length of these episodes increases, the frequency of these episodes decreases. In the most recent years (1997-2004) episodes lasting 5 days or more often have not occurred at all (F itz-Simons, et al., 2005). From this we conclude that control strategies have been reducing peak 1-hr O 3 across major urban areas. Numbers of episodes define d by daily maximum 8-hr O 3 concentrations reaching a level of 0.08 ppm for 1 day generally follow the long te rm trend of central values of the 8-hr O 3 data (See Figures 2-16 and 2-32). As the length of th ese episodes increase, the frequency of these episodes decreases. However, some of the longer ep isodes (6 days of more) continue to occur at this level even in the most recent years. In fact, the episode must be defined by a level of 0.10 ppm before these longer episodes disappear in th e most recent years (Fitz-Simons, et al., 2005). As episode length and level incr ease for both 1-hr and 8-hr O 3 data the frequency decreases (Figure 2-33 and 2-34). The longer peri ods and higher levels di sappear altogether in the period from 2000-2004 (Fitz-Simons, et al., 2005). One final aspect of episodes to examine is the return time or the number of days between episodes. Looking at the intervals between epis odes of 0.08ppm for 8-hr data, the most prevalent gap length in days is 1 day. There is a slight peak again at 4 days followed by a gradual decrease in frequency as the gap-length increases (see Figure 2-35). Looking at the same data for episodes of 0.12ppm, it appears that some periodicities appear at 1 day, 5-6 days, 21 days, and 33-34 days. The frequencies for these episodes are so small compared to frequencies lower level episodes that these indications should not be considered real or si gnificant indications of periodicities. The 1-hr O 3 data exhibit much the same lack ofperiodicity as the 8-hr data (FitzSimons, et al., 2005).

2.7 POLICY RELEVANT B ACKGROUND LEVELS For purposes of this document, backgr ound or policy relevant background (PRB) O 3 is
defined as the di stribution of O 3 concentrations that would be obs erved in the U.S. in the absence of anthropogenic (man-made) emissions of prec ursor emissions (e.g., VOC, NOx, and CO) in the U.S., Canada, and Mexico. This is referred to as policy-relevant background, since this definition of background facilitate s separating pollution levels that can be controlled by U.S.2-49> 6654321

e p i s o d e l e n g t h ( d a y s )1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004year16241513761422181627261014101421364641231819910233382497160443634281040103162061134137105847510071435725192248387317336208910233382497160443634281040103162061134137105847510071435725192248387317336208188189243147154164148999213711031112312058918948191133667649866822553514711528214Figure 2-31. Length of Consecutive Day Episodes over 0.12ppm by Year for 1-hour Ozone Data across all Monitors.Data Source: AQS2-50> 6654321

e p i s o d e l e n g t h ( d a y s )1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004year3343372725313439333424173525841616247436561477470464511044187815485939115510471161202671012696636172225131147178371180147313372163274375166603965583233583875794511044187815485939115510471161202671012696636172225131147178371180147313372163274375166603965583233583875794683906547474224017324161211041127778895810851270106311531644164099111071641789440336932852561326032213828306832994460486431323257390626341589Figure 2-32. Length of Consecutive Day Episodes over 0.08ppm by Year for 8-hour Ozone Data across all Monitors.Data Source: AQS2-51> 6654321

ep i s od e l e n gt h ( d a y s )0.09 0.1 0.11 0.12 0.13 0.14 0.15level35595176330364101159719163132102935913146112285952326134291235433265511684702097433180559552501625221264625299Figure 2-33. Length of Consecutive Day Episodes over Displayed Levels for 1-hour Ozone Data (2000-2004) across allMonitors.Data Source: AQS2-52> 6654321

e p i s o d e l e n g t h (d a y s )0.06 0.07 0.08 0.09 0.1 0.11 0.12level586114233155713229579682634154536183553911218473813031103830749412223552720927411893572294511964496818856261753648777300411451865412588937316Figure 2-34. Length of Consecutive Day Episodes over Displayed Levels for 8-hour Ozone Data (2000-2004) across allMonitors.Data Source: AQS2-53

FREQUENCY0100020003000gap length (days)1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50Figure 2-35. Length of Gaps in Days Between Episodes over 0.08 ppm for 8-hour Ozone Data (2000-2004).2-54 regulations (or through internationa l agreements with neighboring c ountries) from levels that are not generally controllable in this manner. As defined here, PRB includes (1) O 3 in the U.S. from
natural sources of emissions in the U.S., Canada, and Mexico and (2) O 3 in the U.S. from the transport of O 3 or the transport of emissions from bot h natural and man-made sources, from outside of the U.S. and its neighbor ing countries. As discussed in Chapter 5 of this Staff Paper,
PRB concentrations enter into the a ssessments of risk to human health.
Contributions to PRB levels of O 3 include: photochemical interactions involving natural
emissions of VOCs, NO X , and CO; the long-range transport of O 3 and its precursors from outside North America; and stratospheri c-tropospheric exchange (STE). Processes involved in STE are
described in detail in Annex AX2.3 of the CD. Natural sources of O 3 precursors include biogenic emissions, wildfires, and lightning. Biogenic em issions from agricultu ral activities are not considered in the formation of PRB (CD, p.AX2-145). As a result of long-range transport of O 3 and its precursors from anthropogenic sources
within North America, estimates of PRB O 3 concentrations cannot be derived solely from

measurements of O 3 , and must be based on modeling. The global photochemical transport model GEOS-CHEM (Fiore et al., 2003) has been applied to estimate PRB O 3 concentrations across the U.S. (U.S. EPA, 2005a, AX3-131). The CD refers to a number of GEOS-CHEM publications (Bey et al., 2001; Liu et al., 2002; Martin et al., 2002; Fusc o and Logan, 2003; Li et al., 2002, 2005), summarizing their conclusions as "results indicate no significant bias, and agreement to generally within 5 ppbv (parts per billion volume) for monthly mean concentrations at different altitudes." The CD goes on to review de tailed evaluations of GEOS-CHEM with O 3 observations at U.S. surface sites (Fiore et al., 2002, 2003) and comparisons of GEOS-CHEM predictions with observations at Trinidad Head, CA (Goldstein et al., 2004). The comparisons at Trinidad Head are especially re levant because sources of the O 3 found there are often limited to
those in the PRB definition. The observations, filtered to remove local influence, averaged 41 ± 5 ppbv, as compared to GEOS-CHEM predictio ns of 39 ± 5 ppbv, indicating no significant differences between the model predictions and ob servations for conditions suggestive of PRB. The CD further notes that "several other pape rs have evaluated the GEOS-CHEM simulation for
surface O 3 and its precursors over the United States." Summarizing their assessment of the validity of the GEOS-CHEM model, the CD stat es "in conclusion, we estimate that the PRB O 3 values reported by Fiore et al. (2003) for afternoon surface air ove r the United States are likely 10 ppbv too high in the southeast in summer, a nd accurate within 5 ppbv in other regions and
seasons." These error estimates are based on co mparison of model output with observations for conditions which most nearly reflect those given in the PRB definition, i.e., at the lower end of the probability distribution. For O 3 (cf. Figures 8 and 9 of Fiore et al., (2003) for the SE and2-55 Figure 3 of Fiore et al. (2002) for the NE.) it can be seen that GEOS-CHEM overestimates O 3 for
the SE and underestimates it for the NE.
The GEOS-CHEM model shows that PRB O 3 concentrations are related to season,

altitude and total surface O 3 concentration. PRB O 3 concentrations at th e surface are generally predicted to be in the range of 0.015 to 0.035 pp m in the afternoon, and they tend to decline under conditions conducive to high O 3 episodes. They are highest during spring and decline into summer. Higher values tend to occur at higher elevations during spring due to contributions from hemispheric pollution and st ratospheric intrusions. The stratospheric contribution to
surface O 3 is typically well below 0.020 ppm and only rarely elevates O 3 concentrations at lowaltitude sites and only slightly more often elev ates them at high-altitude sites (U.S. EPA, 2005a, AX3-148). In the previous review of the O 3 NAAQS, the criteria document and staff paper adopted a value of 40 ppb for PRB O 3 . However, Figure 3-17 in the CD shows that mean daily maximum
8-h O 3 concentrations were less than 40 ppb at over 10 % of U.S. sites. In 2004, the mean daily
maximum 8-h O 3 concentrations were less than 40 ppb at 25 % of U.S. sites. It is highly unlikely
that this fraction of O 3 monitoring sites would be unaffected by O 3 generated by sources from within continental North America. Figure 3-19, in the CD, shows that over the past 15 years, mean daily maximum 8-h O 3 concentrations at Voyageurs Nati onal Park were typically less than 40 ppb. Simulations of O 3 at Voyageurs, the si te with the lowest O 3 show that there is still a substantial regional contribution to O 3 (Figure AX2-86). Thus, 40 ppb is likely to be too high for
the mean PRB O 3 concentration. The exposure and health risk analyses descri bed in Chapter 4 and 5 use estimates of PRB based on runs of the GEOS-CHEM model applie d for the 2001 warm season (i.e., April to September). The GEOS-CHEM data consist of hour ly gridded values with latitude running from 12o to 80 o in 2 o steps and longitu de running from -177.5 o to -47.5o in 2.5 o steps. These data are used to create monthly average diurnal profiles which are fixed for each month during the O 3 season. The PRB estimates from the grid near est each of the 12 urban areas included in the exposure and risk analyses have been used to es timate PRB in each of these areas. Appendix 2A provides plots of the PRB estimates by month for each of the 12 urban areas.2-56 REFERENCES

Bey, I.; Jacob, D. J.; Logan, J. A.; Yantosca, R. M. (2001a) Asian chemical outflow to the Pacific in spring: origins, pathways, and budgets. J. Geophys. Res. [Atmos.] 106: 23,097-23,113.

Byun, D.W., and Ching, J.K.S., Eds, 1999. Science algo rithms of EPA Models-3 Community Multiscale Air Quality (CMAQ) modeling system, EPA/600/R-99/030, Office of Research and Development, U.S. Environmental Protection Agency.

Byun, D,W, and Schere, K.L. 2006, Review of the governing equations, computational algorithms, and other components of the Models-3 Community Multis cale Air Quality (CMAQ) modeling system, Applied Mechanics Reviews , Vol 59, pp 51-77.

California Environmental Protection Agency: Air Resources Board (2005) Review of the California Ambient Air Quality Standard for Ozone.

Civerolo, K. L.; Mao, H. T.; Rao, S. T. (2003) The airshed for ozone and fine particulate pollution in the eastern United States. Pure Appl. Geophys. 160: 81-105.

Cox, W. M.; Camalier, L. (2006) The effect of measurement error on 8-hour ozone design concentrations. Memo to Ozone NAAQS Review Docket.

Dennis, R.L., Byun, D.W., Novak, J.H., Galluppi, K.J., Coats, C.J., and Vouk, M.A., 1996. The next generation of integrated air quality modeling: EPA’s Models-3, Atmospheric Environment, 30, 1925-1938.

Fiore, A. M.; Jacob, D. J.; Bey, I.; Ya ntosca, R. M.; Field, B. D.; Fusco, A. C.; Wilkinson, J. G. (2002) Background ozone over the United States in summer: origin, trend, and contribution to pollution episodes. J. Geophys. Res. (Atmos.) 107(D15): 10.1029/2001JD000982.

Fiore, A.; Jacob, D.J.;Liu, H.; Ya ntosca, R.M.; Fairlie, T.D.; Li, Q. (2003). Variability in Surface Ozone Background over the United States: Implications for Air Quality Policy. J. of Geophysical Research, 108(D24)19-1 – 19-12

. Fitz-Simons, T.; McCluney, L.; Rizzo, M.(2 005) U.S. EPA Memorandum to File. Subject: Analysis of 2004 Ozone Data for the Ozone NAAQS Review, November 7.

Kasibhatla, P.; Chameides, W. L. (200 0) Seasonal modeling of regional ozone pollution in the eastern United States. Geophys. Res. Lett. 27: 1415-1418.

Lefohn A.S. and Runeckles V.C., Establishing Standards to Protect Vegetation - Ozone Exposure/Dose Considerations. Atmospheric Environment 21:561-568, 1987.

Rao, S. T.; Ku, J.-Y.; Berman, S.; Zhang, K.; Mao, H. (2003) Summertime characteristics of the atmospheric boundary layer and relationships to ozone levels over the eastern United States. Pure Appl. Geophys. 160:21- 55. U.S. Environmental Protection Agency (1986). Guideline on the Identification and Use of Air Quality Data Affected by Exceptional Events. EPA-450/4-86-007.

U.S. Environmental Protection Agency (1996). Air Quality Criteria for Ozone and Related Photochemical Oxidants. Research Triangle Park, NC: Office of Research and Development; Report no. EPA/600/P-93/004aF.

U.S. Environmental Protection Agency (2003).Clean Ai r Status and Trends Network (CASTNet) 2001 Quality Assurance Report; Research Triangle Park, NC: Office of Air Quality Planning and Standards. Report from EPA Contract No. 68-D-98-112.2-57 U.S. Environmental Protection Agency (2004a). 2003 Criteria Pollutant Quality Indicator Summary Report for July 14, 2004, AQS Data; Research Triangle Park, NC: Office of Air Quality Planning and Standards. Report from EPA Contract No. 68-D-02-061.

U.S. Environmental Protection Agency (2004b).The Ozone Report: Measuring Progress through 2003. Research Triangle Park, NC: Office of Air Quality Planning and Standards; Report no.EPA-454-K-04-001.

U.S. Environmental Protection Agency (2005a).Air Quality Criteria for Ozone and Related Photochemical Oxidants. Research Triangle Park, NC: Office of Research and Development; Report no. EPA/600/R-05/0054aB.

U.S. Environmental Protection Agency (2005b).Evaluating Ozone Control Programs in the Eastern United States: NO X Budget Trading Program Progress and Compliance. Research Triangle Park, NC: Office of Air Quality Planning and Standards; Report no. EPA-454- K-05-001.

Zhang, H. Mao, K. Civerolo, S. Berman, J. Ku, S.T. Ra o, B. Doddridge, C.R. Philbri ck, and R. Clark (2001). Numerical investigation of boundary layer evolution and nocturnal low-level jets: Local versus non-local PBL schemes. Environmental Fluid Mechanics . 1: 171-208.3- 1 

### 3. POLICY-RELEVANT ASSESSMENT OF HEALTH EFFECTS EVIDENCE

3.1 INTRODUCTION This chapter assesses key policy-relevant information on the known and potential health
effects associated with exposure to ambient O 3 , alone and in combinatio n with other pollutants that are routinely present in ambient air. Th is assessment focuses sp ecifically on the health
effects evidence evaluated in Ch apters 4 through 7 of the CD w ith particular emphasis on the integrative synthesis presented in Chapter 8. That in tegrative synthesis fo cuses on integrating newly available scientific inform ation with that available from the last review, as well as integrating information from va rious disciplines, to address a set of issues central to the
assessment of scientific informati on upon which this review of the O 3 NAAQS is based. This chapter also addresses key issues relevant to quantitative assessment of controlled-human exposure and epidemiological ev idence, to provide a foundation for the quantitative human exposure and health risk assessments presente d in Chapters 4 and 5. Those quantitative assessments, together with this evidence-base d assessment, provide the foundation for the development of staff conclusions and identificat ion of options for cons ideration related to primary standards for O 3 presented in Chapter 6.
The decision in the last re view focused primarily on ev idence from short-term and prolonged controlled-exposure studies reporting lung functio n decrements, respiratory symptoms, and respiratory inflammation in human s, as well as epidemio logy studies reporting excess hospital admissions and em ergency department (ED) visits for respiratory causes. The CD prepared for this review emphasizes a la rge number of epidemiol ogical studies published
since the last review wi th these and additional health endpoi nts, including the effects of acute and chronic exposures to O 3 on premature mortality, enhanced respiratory symptoms and lung
function decrements in asthmatic individuals, and school absences. It also emphasizes important
new information from toxicol ogy, dosimetry, and controlled human exposure studies.
As discussed in more detail below (section 3.3), highlights of the new evidence include:

• New controlled human-exposure studies have observed that very small (<5%) lung function decrements occur in some healt hy adults under moderate exertion for 6.6 hr exposures to levels as low as 0.04 an d 0.06 ppm; however, in a few subjects, decrements of >10% were observed.

• New controlled human-exposure studies o ffer evidence of increased airway responsiveness to allergens in subjects with allergic as thma and allergic rhinitis exposed to O 3
.

• Numerous controlled human-exposure stud ies have reported indicators of O 3 -induced inflammatory response in both the upper resp iratory tract (URT) a nd lower respiratory3- 2 tract (LRT), while other studies have s hown significant changes in host defense capability following O 3 exposure of hea lthy young adults.

• Animal toxicology studies pr ovide new information regarding mechanisms of action, increased susceptibility to re spiratory infection, and the biol ogical plausibility of acute effects and chronic, irrevers ible respiratory damage.

• Numerous acute exposure epidemiological studies published duri ng the past decade offer added evidence of ambient O 3 -related lung function decr ements and respiratory symptoms in physically active healthy subj ects and asthmatic subj ects, as well as evidence on new health endpoi nts, such as the relati onships between ambient O 3 concentrations and school abse nteeism and between ambient O 3 and cardiac physiologic endpoints.

• Several new studies have been published over the last decade examining the temporal associations between O 3 exposures and ED visits for respiratory diseases and on respiratory-related hos pital admissions.

 Newly available, large multicity studies, designed specifically to examine the effects of acute exposure to PM and O 3 on mortality, provide much more robust and credible information than was available in the last review. The results from two key studies carried out in 95 U.S. communities (U.S. Na tional Morbidity, Mortality Air Pollution Study [NMMAPS]) and in 23 European cities (Air Pollution and H ealth: European Approach [APHEA]) reported positive and significant O 3 effect estimates for all cause (nonaccidental) mortality.

• In a recent study, Bell et al. ( 2006) applied several statisti cal models to data on air pollution, weather, and mortality for th e 98 NMMAPS communities to evaluate whether a threshold level exists for prematur e mortality. The results indicate that even low levels of tropospheric O 3 are associated with premature mortality.

• Three recent meta-analyses evaluated potential sources of heterogeneity in O 3 -mortality associations, and these studi es provide evidence of a robust association between ambient O 3 and mortality, especi ally for the warm O 3 season.

Section 3.2 provides an overview of mechanisms of toxicity, with more detailed discussion in Appendix 3A. Section 3.3 summarizes the nature of effects induced by O 3 exposure or associated with exposure to O 3 , alone and in combination with other pollutants, drawing on information in Chapters 5-8 of the CD. Section 3.4 summarizes conclusions and judgments from the CD’s integrative assessment of the epidemiological evidence regarding the extent to which

causal inferences can be made about observe d associations between health endpoints and exposure to O 3 , and discusses key issues related to quantitative risk assessment based on such evidence. Section 3.5 discusses biological plau sibility and coherence of evidence for O 3 -related
adverse health effects, including short-term respir atory effects, short-term cardiovascular effects,3- 3 long-term health effects, and mortality-related health endpoin t. Drawing from the CD’s integrative synthesis, secti on 3.6 discusses factors that modify responsiveness to O 3 ; potentially susceptible and vulnerable populat ions groups; and public health impacts of exposure to ambient

O 3 . Finally, section 3.7, summari zes key policy-relevant conc lusions from the CD about O 3 - related health effects, in the context of a discussi on of issues related to ou r confidence in and the utility of the underlying evidence.

3.2 MECHANISMS OF TOXICITY

Evidence is covered in Ch apters 5 and 6 of the CD on possible mechanisms by which exposure to O 3 may result in acute and ch ronic health effects. Wh ile most of the available
evidence addresses mechanisms for O 3 , we recognize that O 3 serves as an indicator for the total photochemical oxidant mixture found in the ambi ent air. Some effects may be caused by one or more components in the overall pollutant mix, either separate ly or in combination with O 3 . Evidence from dosimetry, toxico logy, and human exposure studies has contributed to an understanding of the mechanisms th at help to explain the biological plausibility and coherence of
evidence for O 3 -induced respiratory health effects reported in epidemio logical studies. In the past, however, little information was available to help explain potential biological mechanisms
which linked O 3 exposure to premature mortality or card iovascular effects. More recently, however, an emerging body of animal toxicology evidence is beginning to suggest mechanisms that may mediate acute O 3 cardiovascular effects. Scientific evidence discussed in the CD (sec tion 5.2) indicates that reactions with lipids and antioxidants are the initial step in me diating deleterious h ealth effects of O 3 . There is subsequent activation of a cascade of events starting with infla mmation, altered permeability of the epithelial barrier, impaired host defense (including clearan ce mechanisms), and pulmonary structural alterations th at can potentially exacerba te a preexisting disease status. According to the CD, the scientific evidence is still lacki ng for clearly establishing a role for one or a group of mechanistic pathways underlying O 3 health effects observed in epidemiological studies. Appendix 3A provides a further discu ssion of mechanisms of toxicity.

3.3 NATURE OF EFFECTS The CD provides new eviden ce that notably enhances our understanding of short-term exposure effects, including ef fects on lung function, symptoms, and inflammatory effects reported in controlled exposure st udies. These studies support and extend the findings of the previous CD. There is also a significant body of new epidemiol ogical evidence of associations between short-term exposure to O 3 and effects such as prematur e mortality, hospital admissions3- 4 and ED visits for respiratory (e.g., asthma) cause s. Key epidemiological and human controlled exposure studies are summarized in A ppendices 3B and 3C , respectively. The following discussions of O 3 -related health effects are based on scientific evidence critically reviewed in chapters 5, 6, and 7 of the CD, as well as th e CD’s integrati on of scientific evidence contained in Chapter 8. In addition, these health effect s discussions rely on the more detailed information and tables presented in the CD’s annexes AX5, AX6, and AX7.
Conclusions drawn about O 3 -related health effects depend on the full body of evidence from controlled-exposure human, epidem iological and toxicological da ta contained in the CD. Section 3.3.1 focuses on a broad array of morbid ity effects, including bo th acute and chronic exposures. Section 3.3.2 focuse s on the expanded body of evid ence on associations between

acute O 3 exposure and mortality, as well as th e more limited evidence on chronic O 3 exposures and mortality.

3.3.1 Morbidity

This section summarizes scien tific information contained in the CD on respiratory and
cardiovascular effects associ ated with exposure to O 3 . Evidence of the effe cts of short-term and long-term exposure to O 3 on the respiratory system is discussed in sections 3.3.1.1 and 3.3.1.2,
and evidence of O 3 -related cardiovascular ef fects in section 3.3.1.3.

3.3.1.1 Effects on the Respiratory Syst em from Short-term Exposures Short-term exposures to O 3 have been reported to induce a wide variety of respiratory
health effects. These effects include a range of effects, such as morphologica l changes in the respiratory tract, pulmonary function decr ements, respiratory symptoms, respiratory inflammation, increased airway responsiveness, changes in host defense capability, acute morphological effects, increased ED visits and hospital admiss ions, and effects on exercise performance. Short-term O 3 exposure has also been associated with increases in restricted activity days and school absences but evid ence is limited for these effects.

3.3.1.1.1 Pulmonary Function Decrements, Re spiratory Symptoms, and Asthma Medication Use A very large literature base of studies pub lished prior to 1996, wh ich investigated the health effects on the respirat ory system from short-term O 3 exposures, was reviewed in the 1986 and 1996 CDs (U.S. Environmental Protection Ag ency, 1986, 1996). In the last review, the
lowest O 3 concentration at which statis tically significant reductions in forced vital capacity (FVC) and forced expirato ry volume in 1 second (FEV 1 ) had been reported in sedentary subjects was 0.5 ppm (CD, p 6-3). During exercise, sp irometric and symptomatic responses were
observed at much lower O 3 exposures. When minute ventilat ion was considerably increased by3- 5 continuous exercise (CE) during O 3 exposures lasting 2 hr or less at > 0.12 ppm, healthy subjects generally experienced decreases in FEV 1 , FVC, total lung capacity ( TLC), inspiratory capacity (IC), mean forced expiratory fl ow from 25% to 75% of FVC (FEF 25-75 ), and tidal volume (V T ); increases in specific airway resist ance (sRaw), breathing frequency (f B ), and airway responsiveness; and symptoms such as cough, pa in on deep inspiration, shortness of breath, throat irritation, and wheezing. When exposures were increased to 4- to 8-hr in duration, statistically significant spirometric a nd symptom responses were reported at O 3 concentrations as low as 0.08 ppm and at lower minu te ventilation (i.e., m oderate rather than high level exercise)
than the shorter duratio n studies (CD. p. 6-6). The most important observati ons drawn from studies reviewed in the 1996 CD were that: (1) young healthy adu lts exposed to O 3 concentrations > 0.08 ppm develop significant, reversible, transient decrements in pulmonary function if minute vent ilation or duration of exposure is increased sufficiently, (2) childre n experience similar spirometric responses but lesser symptoms from O 3 exposure relative to young adults, (3) O 3 -induced spirometric responses are decreased in the elderly relative to young adults , (4) there is a large degree of intersubject variability in physiolo gic and symptomatic responses to O 3 but responses tend to be reproducible within a given indi vidual over a period of severa l months, (5) subjects exposed repeatedly to O 3 for several days show an attenua tion of response upon successive exposures;
this attenuation is lost after about a week without exposure; and (6) acute O 3 exposure initiates an inflammatory response which may persist for at least 18 to 24 hr post exposure (CD, p. 6-2). Since 1996, there have been a number of stud ies published investigating spirometric and symptomatic responses, and they generally support the observations previously drawn. Recent studies for acute exposures of 1 to 2 hr and 6 to 8 hr in durati on are summarized in Tables AX6-1 and AX6-2 of the CD (p. AX6-5 to AX 6-7 and p. AX6-11 to AX6-12) and reproduced as Tables 3C-1 and 3C-2 in Appendix 3C. Among the more important of the recent studies was McDonnell et al. (1997) which exam ined reported changes in FEV 1 in 485 white males (ages 18- 36) exposed for 2 hr to O 3 concentrations from as low as 0.08 ppm up to 0.40 ppm, at rest or with intermittent exercise (IE). Decrements in FEV 1 were modeled by sigmoi d-shaped curve as a function of subject age, O 3 concentration, minute ventilation, and duration of exposure. In another study, Ultman et al. (2004) found that exposing 60 y oung, healthy subjects to 0.25 ppm

O 3 for 1 hr with continuous exer cise produced considerable inte rsubject variability in FEV 1 decrements ranging from 4% im provement to a 56% decrement, which was consistent with findings in the 1996 CD. One third of subjects had FEV 1 decrements > 15% and 7% had decrements > 40%. Foster et al. ( 1993, 1997) examined the effects of O 3 on ventilation distribution and reported resu lts suggesting a prolonged O 3 effect on the sm all airways and
ventilation distribut ion (CD, p. 6-5).3- 6 For prolonged exposures (4 to 8 hr ) in the range of 0.08 to 0.16 ppm O 3 using moderate quasi-continuous exercise (QCE; 50 min exercise [minute ventila tion of 35 to 40 L/min] and 10 min rest per hr), several pre- and post-1996 studies (F olinsbee et al., 1988,1994; Horstman et al., 1990; Adams, 2002, 2003a, 2006) have reported statis tically significant spirometric responses and increased symptoms in healthy adults with increasing duration of exposure, O 3 concentration,
and minute ventilation. Based on review of several prolonged e xposure studies, the CD (p. 6-6)
concluded that FEV 1 decrements are a function of minute ve ntilation in 6.6 hr exposure studies and that data from recent studies do not support the contention that minut e ventilation should be normalized to body surface area (BSA) for adults. Triangular exposure (i.e., integrated exposures that begin at a low le vel, rise to a peak, and return to a low level during time of exposure) studies (Hazucha et al., 1992; Ad ams 2003a, 2006) suggest that, depending upon the profile of the exposure, the tr iangular exposure, which may re flect the pattern of ambient exposures in some locations, can potentially lead to greater FEV 1 decrements than square wave exposures (i.e., a constant e xposure level during time of e xposure) when the overall O 3 doses are equal (CD, p. 6-10), suggesti ng that peak exposures are important in terms of O 3 toxicology. McDonnell (1996) used data from a series of studies to investigate the frequency
distributions of FEV 1 decrements following 6.6 hr expos ures and found that average FEV 1 responses were relatively small (b etween 5 and 10 %) at 0.08 ppm O 3 (CD, p. 8-17) 1 . However, about 18% of the exposed subject s had moderate functional decr ements (10 to 20%), and about 8% experienced large decrements (>20%). Figure 3-1A,B,C (C D, Figures 8-1A,B and 8-2, pp. 8-17 and 8-19) is based on study data that are in McDonnell ( 1996) together with data from Adams (2002, 2006) that were not published but were obtained from the author. This figure demonstrates that while average responses may appear small and in significant, some individuals can experience much more signific ant and severe effects that may be clinically significant. The

FEV 1 responses illustrated in this figure were not corr ected for the effect of ex ercise in clear air.
When that is done for the Ad ams (2002, 2006) data, the percen tage of subjects experiencing

> 10% FEV 1 decrements changes to 7% at O 3 exposures of 0.04 ppm, to 7% at O 3 exposures of

1 The studies conducted in EPA’s clinical research faci lity in Chapel Hill, NC that are considered in the lung function risk assessment measured ozone concentrations to within +/- 5% or +/- 0.004 ppm at the 0.08 ppm exposure level. The accuracy of these measurements was confirmed in an email sent by Steve Jackson, Program Manager for the Human Studies Division in the National Health & Environmental Effects Research Laboratory, Office of Research and Development, USEPA. He has overall responsibility for the monitoring program at the USEPA clinical research facility in Chapel Hill, NC. This email has been placed in the Ozone NAAQS review docket.3-7 Figure 3-1A and B. Freque ncy distributions of FEV 1 changes following 6.6-h exposures to a constant concentration of O 3 or filtered air. Note that the percentage in each panel indicates the distribut ions of % decrement. Source:Panel A, McDonnell (1996); Panel B, Adams (2002, 2006), pre- and post-FEV 1 data for each subject provided by author.



### C.

Figure 3-1C. Frequency distributions of FEV 1 changes following 6.6-h exposures to a constant concentration of O 3 or filtered air. The FEV 1 changes following O 3 exposures have been corrected for filtered air responses, i.e., they are O 3 -induced FEV 1 chan g es. Note that the percentage in each panel indica tes the distributions of % decrement. Source: Adams (2002, 2006), pre- and post- FEV 1 data for each subject provided by author.3- 8 0.06 ppm, and to 23% at O 3 exposures of 0.08 ppm, in studies c onducted in California (CD, p. 8- 18). The development of these effects is time-dependent duri ng both exposure and recovery periods, with great overlap for de velopment and disappearance of th e effects. In healthy human subjects exposed to typical ambient O 3 levels near 0.12 ppm, spirom etric responses largely resolve within 4 to 6 hr postexposur e, but cellular effects persist for about 24 hr . In these healthy subjects, small residual lung func tion effects are almost complete ly gone within 24 hr, while in hyperresponsive subjects, recovery ca n take as much as 48 hr to retu rn to baseline. The majority of these responses are attenu ated after repeated exposure, but such attenuation to O 3 is lost one week postexposure (CD, p. 8-19). In the Adams (2006) inves tigation of the eff ects of square-wave (0.00, 0.06, and 0.08 ppm O 3 ) and triangular (averaging 0.04, 0.06, and 0.08 ppm O 3 ) exposures for 6.6 hr during quasi continuous exercise on pulm onary function in 30 healthy adu lts, the study was designed to compare pulmonary function responses between th e six exposure protocol s at each of six time points (1, 2, 3, 4.6, 5.6, and 6.6 hr) 2 . Accordingly, the author utilized a multiple comparison technique to avoid Type I error (falsely rejecting the null hypothesis of no difference). At 6.6 hr, FEV1 responses from the 0.08 ppm O 3 exposures were found to be significantly different from the responses observed for the 0.0, 0.04, and 0.06 ppm O 3 exposures. The FEV 1 responses did not differ significantly at 6.6 hr between the two 0.08 ppm O 3 exposures (i.e., the square-wave vs. the triangular). Another statistically insignificant comparison was between the FEV 1 responses at 0.06 ppm O 3 and filtered air (0.0 ppm O 3 ) at 6.6 hr. On examination of the group mean FEV 1 responses in Figure 1 of Adams (2006), however, responses during the 0.06 ppm O 3 exposures appear to di verge from responses for filtered-air and 0.04 ppm O 3 (CD, 8-42). In addition to redu cing Type I error, the correction for the multiple comparisons by Adams (2006) may ha ve also increased Type II error (falsely accepting the null) for the simple evaluation of pre- to postexposure effects of O 3 versus filtered
air on FEV 1 , as has been commonly asse ssed by others (e.g., Horstm an et al., 1990; McDonnell et al., 1991). A cursory evaluati on of pre- to postexposure effects can be completed utilizing the summary data in Table 3 of the Adams (2006) publication. For the filtered air, 0.06 ppm O 3 (square-wave), and 0.06 ppm O 3 (triangular) exposures, the FEV 1 responses were 1.35±0.54 [mean±standard error (SE)],

− 1.51±0.77, and

− 1.43±1.09%, respectively. Under the null hypothesis of no pre- to pos texposure difference in FEV 1 responses between filtered air and O 3 exposure, the lack of an overlap in the range of responses (i.e ., the means±SEs) at 0.06 ppm O 3 versus filtered air is suggestive of a significant effect on FEV 1 . Furthermore, in a prior publication (Adams, 2002), the author stated that, “some sensitiv e subjects experience notable

2 These studies reported O 3 concentrations to be accurate within +/- 0.003 ppm over the range of concentrations included in these studies.3- 9 effects at 0.06 ppm,” based on the observation that 20% of subjects exposed to 0.06 ppm O 3 (in a face mask exposure study) had great er than a 10% decrement in FEV 1 even though the group
mean response was not st atistically different from the filtered air response. The effects described by Adams (2002), along with the cursory evaluation of the Adam s (2006) data as described above, strongly suggest that exposure to 0.06 ppm O 3 causes small group mean FEV 1 decrements in healthy adults with some indi viduals having notable effects. Although not mentioned in th e CD, Adams (2006) reported th at total subjective symptom scores (TSS) during the triangular 0.06 ppm exposure reached statis tical significance (relative to preexposure) at 5.6 and 6.6 hr, whereas they did not reach significance during the square-wave 0.06 ppm exposure. Data in Tabl e 4 of the Adams (2006) publication allow fu rther evaluation of pre- to postexposure effects on respiratory symptoms, both TSS and pain on deep inspiration (PDI). For the filtered air, 0.06 ppm (square-wave), and 0.06 ppm (triangular) exposures, the TSS responses were 0.6±0.40 (mean±SE), 2.5± 0.89, and 3.9±1.35, respect ively, and the PDI responses were 0.2±0.16 (mean±SE), 1.4±0.53, and 2.0±0.80, respecitively. As noted above for

FEV 1 changes, the lack of an ov erlap in the ranges of respon ses (i.e., the means±SEs) at 0.06 ppm O 3 versus filtered air for those two sympom scor es is suggestive of a significant effect on respiratory symptoms. A relatively large number of field studies investigati ng the effects of ambient O 3 concentrations, in combination with other ai r pollutants, on lung func tion decrements and respiratory symptoms have been publishe d since 1996 (see CD, sections 7.2.3, 7.2.4, and 8.4.4.1). These newer studies support the major findings of the 1996 CD that lung function changes, as measured by decrements in FEV 1 or peak expiratory flow (PEF), and respiratory symptoms in healthy adults a nd asthmatic children are closely correlated to ambient O 3 concentrations. Pre-1996 fiel d studies focused primarily on children attending summer camps
and found O 3 -related impacts on measures of lung function, but not respiratory symptoms, in healthy children. The newer studies have expanded to evaluate O 3 -related effects on outdoor workers, athletes, the elderly, hikers, school child ren, and asthmatics. Co llectively, these studies
confirm and extend clinical obs ervations that prolonged exposu re periods, combined with
elevated levels of exertion or exer cise, may magnify the effect of O 3 on lung function. The most representative data come fro m the hiker study (Korrick et al., 1998), which provided outcome measures stratified by several factors (e.g., ge nder, age, smoking status , presence of asthma) within a population capable of more than normal exertion. In this study, lung function was measured before and after hiking, and both ambient and personal O 3 exposure measurements were made. The mean 8-hr average O 3 concentration was 40 ppb (SD 12). Decreased lung
function was associated with O 3 exposure, with the greatest effect estimates reported for the3- 10 subgroup that reported having asthma or wheezing, and for those who hiked for longer periods of time, thus increasing the e xposure period (CD, p. 7-36). Asthma panel studies, conducted both in the U.S. and in other countries, have reported
that decrements in PEF are associated with routine O 3 exposures among asthmatic and healthy persons (CD, sections 7.2.3.2 and 8.4.4.1). One la rge U.S. multicity study (Mortimer et al., 2002) examined O 3 -related changes in PEF in 846 asth matic children from 8 urban areas and reported that the incidence of > 10% decrements in morning PE F are associated with a 30 ppb increase in 8-hr average O 3 for a 5-day cumulative lag, suggesting that O 3 exposure may be associated with clinically significant change s in PEF in asthmatic children; however, no associations were reported with evening PEF (CD, p. 7-43). The authors also reported that the associations reported with morni ng PEF remained statistically signi ficant when days with 8-hr

O 3 concentrations above 80 ppb were excluded (C D, p. 7-46). Two studi es (Romieu et al., 1996, 1997) carried out simultaneously in northern and southwestern Mexico City with mildly asthmatic school children repor ted statistically significant O 3 -related reductions in PEF, with variations in effect depending on lag time and time of day. In the northern study, the mean 1-hr

max O 3 concentrations were 190 ppb (SD 80), and in the southwestern study, mean 1-hr max levels were 196 ppb (SD 78). While several studies (Gielen et al ., 1997; Jalaludin et al., 2000; Ross et al., 2002; Thurston et al., 1997) report statisti cally significant associations between O 3 exposure and reduced PEF in asthmatics, other st udies (Hiltermann et al ., 1998; Delfino et al., 1997a) did not, possibly due to very low levels of O 3 . Collectively, however, these studies
indicate that O 3 may be associated with short-term declines in lung function in asthmatic individuals and that they occurr ed at concentrations below thos e used in chamber studies using exercise (CD, p. 7-40 to 7-46). Mortimer et al. (2002) disc ussed biological mechanisms fo r delayed effects on pulmonary function in asthma, which included increased no nspecific airway respons iveness secondary to airway inflammation due to O 3 exposure (CD, p. 7-43). An imal toxicological and human chamber studies (CD, Chapters 5 and 6) pr ovide supporting evidence that exposure to O 3 may augment cellular infiltration and cellular activati on, enhance release of cy totoxic inflammatory mediators, and alter membrane pe rmeability (CD, p.7-44). In mo st laboratory animals studied, biochemical markers of lung inju ry and associated morphological changes were not found to be attenuated, even though at similar exposures pulmona ry function changes might be attenuated. Most of the panel studies which have investigated associations between O 3 exposure and respiratory symptoms or increased use of asth ma medication are focuse d on asthmatic children (CD, sections 7.2.4 and 8.4.4.1). Two large U.S. studies (Mortimer et al., 2002; Gent et al., 2003), as well as several smaller U.S. (Delfino et al., 2003; Just et al., 2002; Newhouse et al., 2004; Romieu et al., 1996, 1997; Ross et al., 2002; Thurston et al., 1997) and international3- 11 studies (Hilterman et al., 1998; Desqueyroux et al., 2002a,b), ha ve reported fairly robust
associations between ambient O 3 concentrations and daily symptoms/asthma medication use, even after adjustment for copollutants. The National Cooperative Inner-City Asthma Study (NCICAS) reported morning symptoms in 846 asthmatic children from 8 U.S. urba n areas to be most strongly associated with a cumulative 1- to 4-day lag of O 3 concentrations (Mortimer et al., 2002). The NCICAS used standard protocols that included instructing careta kers of the subjects to record symptoms in the daily diary by observing or aski ng the child (Mitchell et al., 1997). Symptoms reported included cough, chest tightness, and wheeze. In the analysis pooling individual subject data from all eight cities, the odds ratio for th e incidence of symptoms was 1.35 (95% CI: 1.04, 1.69) per 30 ppb increase in 8-hr avg O 3 (10 a.m.-6 p.m.). The mean 8-hr avg O 3 was 48 ppb across the 8 cities. Excluding days when 8-hr avg O 3 was greater than 80 ppb (less than 5% of days), the odds ratio was 1.37 (95% CI: 1.02, 1.82) for in cidence of morning symptoms. Gent and colleagues (2003) followed 271 asthmatic children under age 12 and living in southern New England for 6 months (April th rough September) in a diary study of daily symptoms in relation to O 3 and PM 2.5 . Mean 1-hr max O 3 and 8-hr max O 3 concentrations were 58.6 ppb (SD 19.0) and 51.3 ppb (SD 15.5), respectivel y. The data were analyzed for two separate groups of subjects, 130 who used main tenance asthma medicatio ns during the follow-up period and 141 who did not. The need for regular medication wa s considered to be a proxy for more severe asthma. Not taking any medicati on on a regular basis and not needing to use a bronchodilator would suggest the presence of ve ry mild asthma. Ef fects of 1-day lag O 3 were observed on a variety of respirat ory symptoms only in the medication user group. Both daily 1-
hr max and 8-hr max O 3 concentrations were similarly rela ted to symptoms such as chest tightness and shortness of breath. Effects of O 3 , but not PM 2.5 , remained significant and even increased in magnitude in two-po llutant models. Some of the asso ciations were noted at 1-hr

max O 3 levels below 60 ppb. In contrast, no effect s were observed among asthmatics not using
maintenance medication. In terms of person days of follow-up, this is one of the larger studies currently available that address symptom outcomes in relation to O 3 , and provides supportive
evidence for effects of O 3 independent of PM 2.5 . Study limitations incl ude limited control for meteorological factors and the post-hoc nature of the population stratification by medication use (CD, p. 7-53). The multicities study by Mortim er et al. (2002), which prov ides an asthmatic population most representative of the Un ited States, and several single-c ity studies indicate a robust
association of O 3 concentrations with resp iratory symptoms and incr eased medication use in
asthmatics. While there are a number of well-conducted, albeit re latively smaller, studies which showed only limited or a lack of evidence for symptom increases associated with O 3 exposure,3- 12 these studies had less st atistical power and/or were conduct ed in areas with relatively low O 3 levels (CD, p. 7-54). The CD ( p. 7-55) concludes that the asthma panel studies, as a group, and the NCICAS in particular, indi cate a positive association betw een ambient concentrations and respiratory symptoms and increased medication us e in asthmatics. The evidence has continued to expand since 1996 and now is cons idered to be much stronger th an in the previous review of
the O 3 primary standard.
The association between schoo l absenteeism and ambient O 3 concentrations was assessed in two relatively large field st udies (CD, section 7.2.6). Chen et al. (2000) examined daily school absenteeism in 27,793 elementa ry school students in Nevada over a 2-year period (after adjusting for PM 10 and CO concentrations) and found that ambient O 3 concentrations were
associated with 10.41% excess rate of school absences per 40 ppb increase in 1-hr max O 3 with a distributed lag of 1 to 14 days. Gilliland et al . (2001) studied O 3 -related absences among 1,933

4 th grade students in 12 southe rn California communities and found significant associations between 30-day distributed lag of 8-hr average O 3 concentrations and all absence categories, and particularly for respirat ory causes. Neither PM 10 nor NO 2 were associated w ith any respiratory or nonrespiratory illness-related absences in si ngle pollutant models. The CD concludes that
these studies of school absen ces suggest that ambient O 3 concentrations, accumulated over two to four weeks, may be associated with schoo l absenteeism, and particularly illness-related absences, but further replication is needed before firm conclusions can be reached regarding the
effect of O 3 on school absences (CD, p. 7-60).

3.3.1.1.2 Airway Responsiveness Airway hyperresponsiveness (AHR), also know as bronchial hyperreactivity, refers to a condition in which the pr opensity for the airways to bronchocon strict due to a variety of stimuli (e.g., exposure to cold air, allerg ens, or exercise) becomes augmen ted (CD, section 6.8). This condition is typically quanti fied by measuring the decrement in pulmonary function (e.g., spirometry or plethysmography) after inhalation exposure to speci fic (e.g., antigen, allergen) or nonspecific (e.g., methacholine, hi stamine) bronchoconstrictor stimuli. Exposure to O 3 causes an increase in nonspecific ai rway responsiveness as indicated by a reduction in the concentration of methacholine or histamine required to produce a given reduction in FEV 1 or increase in SRaw. Increased airway responsiveness is an important consequence of exposure to O 3 because its presence means that the airways are predisposed to narrowing on inhalation of various stimuli, such as specific allerg ens, cold air or SO 2 (CD, p. 8-21). Signifi cant, clinically relevant decreases in pulmonary function ha ve been observed in early phase allergen response in subjects
with rhinitis after consecutive (4-day) exposure to 0.125 ppm O 3 (Holz et al., 2002). Similar increased airway responsiveness in asthmatics to house dust mi te antigen 16 to 18 hrs after3- 13 exposure to a single dose of O 3 (0.16 ppm for 7.6 hrs) was observ ed. These observations suggest
that O 3 exposure may be a clinically important fact or that can exacerbate the response to ambient
bronchoconstrictor substances in individuals with pr eexisting allergic as thma. Further, O 3 may have an immediate impact on asth matics as well as contribute to effects that persist for longer periods (CD, p. 8-21). An important aspect of increa sed airway responsiveness after O 3 exposure is that it represents a plausible link between O 3 exposure and increased hospita l admissions. Kreit et al. (1989) found that O 3 can induce increased airway respons iveness in asthmatic subjects to O 3 , who typically have increased airw ay responsiveness at baseline. A subsequent study (Jorres et al., 1996) suggested an increase in specific (i.e., allergen-induced ) airway reactivity in subjects with allergic asthma, and to a le sser extent in subjects with alle rgic rhinitis after exposure to 0.25 ppm O 3 for 3 hrs; other studies (Mol fino et al., 1991; Kehrl et al., 1999) reported similar results. According to one study (Folinsb ee and Hazucha, 2000), changes in airway responsiveness after

O 3 exposure resolve more slowly than changes in FEV 1 or respiratory symptoms. Other studies of repeated exposure to O 3 suggest that changes in airway responsiveness tend to be somewhat less affected by attenuati on with consecutiv e exposures than changes in FEV 1 (Dimeo et al., 1981; Folinsbee et al., 1994; Gong et al., 1997a; Kulle et al., 1982) (CD, p. 6-31). An extensive laboratory animal data base exploring the eff ects of acute, long-term, and repeated exposure, at rest, to O 3 indicates that induction of AHR occurs at relatively high (> 1ppm) O 3 concentrations (p. 8-21). These studies provide clues to the roles of physiological and biochemical component s involved in this process, but caution should be exercised in interpreting these results, as different mechanis ms may be involved in mediating high- and lowdose responses. As observed in humans, the acute changes in AHR do not persist after long-term exposure of animals exposed to n ear-ambient concentrations of O 3 , and attenuation has been reported. In addition, dosimetr ic adjustments potentially co uld be made to allow better
estimation of levels that would be relevant to huma n exposure effect levels.
The CD concludes that O 3 exposure is linked with increas ed AHR (CD, section 6.8).
Both human and animal studies indicate that AHR is not mechanistica lly associated with inflammation, but they do suggest a likely role for neuronal invol vement (CD, p. 8-21). Increases in AHR do not appear to be strong ly associated with decrements in lung function or increases in symptoms (CD, p. 6-31).

3.3.1.1.3 Respiratory Inflammation and Permeability Based on evidence from the pr evious review, acute inflamma tory responses in the lung have been observed subsequent to 6.6 hr O 3 exposures to the lowest te sted level of 0.08 ppm in healthy adults engaged in modera tely high exercise. Some studi es suggest that inflammatory3- 14 responses may be detected in some individuals following O 3 exposures in the absence of O 3 - induced pulmonary decrements in those subjects. Short-te rm exposures to O 3 also can cause increased permeability in the lungs of humans and experimental animals (CD, sections 5.2.3, 6.9, 7.2.5 and 8.4.3). Not only are the ne wer findings consistent with th e previous review, but also
there is better characterization of the physiological mechanisms by which O 3 causes these
effects. Lung inflammation and increased permeabilit y, which are distinct events controlled by different mechanisms, are two well characterized effects of O 3 exposure observed in all species studied. Disruption of the l ung barrier leads to leakage of serum proteins, influx of polymorphonuclear leukocytes (PMN s), release of bioactive me diators, and movement of compounds from the airspaces into the blood. In the animal toxicologica l studies discussed in the CD (Chapter 5), the lowest O 3 concentration that indu ced inflammation in the mouse lung was 0.11 ppm for 24 hr exposures. Shorter exposures of 8 hours required concen trations of 0.26 ppm to induce epithelial permeability, although there was no effect on inflammation. The lowest O 3 concentration that affected epithelial permeability or inflammati on in the rat was 0.5 ppm for a 3 hr exposure or 0.12 ppm for 6 hr (CD, p. 8-23). After acute exposu res, the influence of the duration of exposure
increases as the concentration of O 3 increases; however, dosimetric adjustments would need to be done before one can compare levels . The exact role of inflamma tion in causation of lung disease is not known; nor is the relati onship between inflammation and lung function (CD, p. 5-23).
A number of human O 3 -exposure studies have analyzed bronchoalveolar lavage (BAL) and nasal lavage (NL) fluids and cells for markers of infla mmation and lung damage. These
studies are summarized in the CD (Annex AX6, Tables AX6-12 and AX6-13). Increased lung inflammation is demonstrated by the presence of neutrophils (PMN s) found in BA L fluid in the lungs, which has long been accepted as a hallmark of inflammation. It is apparent, however, that inflammation within airway tissu es may persist beyond the point that inflammatory cells are
found in the BAL fluid. Soluble mediators of inflammation, such as cytokines and arachidonic
acid metabolites have been measured in the BAL fluid of humans exposed to O 3 . In addition to their role in inflammation, many of these compounds have broncho constrictive properties and may be involved in increased ai rway responsiveness following O 3 exposure (CD, p. 6-31, p. 8- 22). An in vitro study of epithelial cells from nonatopic and atopic asthmatics exposed to 0.01 to 0.10 ppm O 3 showed significantly increased permea bility compared to cells from normal persons. This indicates a potentia lly inherent susceptibility of cells from asthmatic individuals
for O 3 -induced permeability. In the 1996 CD, assessment of human exposure st udies indicated that a single, acute (1 to 4 hr) O 3 exposure (> 0.08 to 0.1 ppm) of subjects engaged in moderate to heavy exercise could3- 15 induce a number of cellular a nd biochemical changes suggestive of pulmonary inflammation and lung permeability (CD, p. 8-22). Th ese changes persisted for at l east 18 hrs. Graham and Koren (1990) compared inflammatory mediators present in NL and BAL fluids of humans exposed to 0.4 ppm O 3 for 2 hrs and found similar increases in PM Ns in both fluids, s uggesting a qualitative correlation between inflammatory changes in the lower airways (BAL ) and upper respiratory tract (NL). Acute airway inflammation was shown in Devlin et al. (1990) to occur among adults exposed to 0.08 ppm O 3 for 6.6 hr with exercise, and McBr ide et al. (1994) reported that asthmatic subjects were more sensitive than non- asthmatics to upper airway inflammation for O 3 exposures (0.24 ppm, 1.5 hr, with li ght IE) that did not affect pulmonary func tion (CD, p. 6-33). The studies reporting inflamma tory responses and markers of lung injury have clearly acknowledged that there is significant variation in response of subjects exposed, especially to 6.6
hour O 3 exposures at 0.08 and 0.10 ppm. To provid e some perspective on the public health impact for these effects, we note that one study (Devlin et al ., 1991, Figure 5) showed that roughly 10 to 50% of the 18 young healthy adult su bjects experienced nota ble increases (i.e., > 2 fold increase) in most of the inflammatory a nd cellular injury indicator s analyzed, associated with 6.6-hour exposures at 0.08 ppm. Similar, although in some ca ses higher, fractions of the population of 10 healthy adults te sted saw > 2 fold increases a ssociated with 6.6-hour exposures to 0.10 ppm. The authors of this study suggest that “susceptible subpopulations such as the very young, elderly, and people with pulmonary impairme nt or disease may be even more affected” (Devlin et al., 1991). Since 1996, a substantial number of human exposure studies have been published which have provided important new in formation on lung inflammation and epithelial permeability. Mudway and Kelly (2004) examined O 3 -induced inflammatory re sponses and epithelial permeability with a meta-analysi s of 21 controlled human expos ure studies and showed that PMN influx in healthy subjects is associated with total O 3 dose ( product of O 3 concentration, exposure duration, and minute ventilati on) (CD, p. 6-34). Results of the analysis s uggest that the time course for inflammatory responses (including recruitment of neutrophils and other soluble mediators) is not clearly esta blished, but differential attenu ation profiles for many of these parameters are evident (CD, p. 8-22). A number of studies (Peden et al., 1997; Scannell et al ., 1996; Hiltermann et al., 1999; Bosson et al., 2003) have provi ded evidence suggesting that asthmatics show greater inflammatory response than healthy subjects when exposed to similar O 3 levels (CD, section 6.9). Markers from BAL fluid following both 2-hr (D evlin et al., 1997) and 4- hr (Christian et al., 1998; Jorres et al., 2000) O 3 exposures repeated up to 5 days indicate that there is ongoing cellular damage irrespective of attenuation of some cellular in flammatory responses of the airways, pulmonary function, and sy mptom responses (CD, p. 8-22).3- 16 The CD (p. 8-24) conclude s that interaction of O 3 with lipid constitu ents of epithelial lining fluid (ELF) and cell membranes and the indu ction of oxidative stress is implicated in injury and inflammation. Altera tions in the expression of cyto kines, chemokines, and adhesion molecules, indicative of an ongo ing oxidative stress response, as well as injury repair and regeneration processes, have been reported in animal toxicology and human in vitro studies evaluating biochemical mediators implicated in injury and infla mmation. While antioxidants in ELF confer some protection, O 3 reactivity is not eliminated at environmentally relevant exposures. Further, antioxidant reactivity with O 3 is both species-speci fic and dose-dependent (CD, p. 8-24).

3.3.1.1.4 Changes in Host Defense Capability As discussed in the CD (sections 5.2 .2, 6.9.6, and 8.4.2), short-term exposures to O 3 have been shown to impair host de fense capabilities in both human s and experimental animals by depressing alveolar macrophage (A M) functions and by altering the mucociliary clearance of inhaled particles and mic robes. Short-term O 3 exposures also interf ere with th e clearance process by accelerating clearance for low doses and slowing clea rance for high doses. Animal toxicological studies have reported that acute O 3 exposures suppress alve olar phagocytosis and immune functions. Dysfunction of host defenses and subsequent increased susceptibility to bacterial lung infection in laboratory animals has been induced by short-term exposures to O 3 levels as low as 0.08 ppm (CD, p. 8-26). Changes in antibacterial defenses are depend ent on exposure regimens, species and strain of lab animals, species of bacteria, and age of the animals used. Acute O 3 -induced suppression of alveolar phagocytosis and i mmune function in experi mental animals appeared to be transient
and attenuated with continuous or repeated exposures. Ozone e xposure has also been shown to
interfere with AM-mediated cleara nce in the respiratory region of the lung and wi th mucociliary
clearance of the tracheobronchi al airways. These interferences with clearance are dose dependent, with low doses acceler ating clearance and high doses slowing the process (CD, p. 8- 26). A single controlled human exposure study (Dev lin et al., 1991) revi ewed in the 1996 CD reported that exposure to 0.08 to 0.10 ppm O 3 for 6.6 hrs (with moderate exercise) induced decrements in the ability of AMs to phagocytos e microorganisms (CD, p. 8-26). Integrating the recent study results with eviden ce available in the 1996 CD, the CD concludes that available
evidence indicates that short-term O 3 exposures have the potentia l to impair host defenses, primarily by interfering with AM function. Any impairment in AM function may lead to decreased clearance of microorgani sms or nonviable particles. Compromised AM functions in3- 17 asthmatics may increase thei r susceptibility to other O 3 effects, the effect s of particles, and respiratory infections (CD, p. 8-26).

3.3.1.1.5 Morphological Effects

The 1996 CD found that short-term O 3 exposures cause similar alterations in lung morphology in all laboratory animal species studied, includin g primates. Cells in the centriacinar region (CAR) of the lung (the segment between the last conducting airway and the gas exchange region) have been r ecognized as a prim ary target of O 3 -induced damage (epithelial cell necrosis and remodeling of respiratory bronchioles), possibl y because epithelium in this region receives the greatest dose of O 3 delivered to the lower respiratory tract. Following
chronic O 3 exposure, structural changes have been observed in the CAR, the region typically affected in most chronic airway dis eases of the human lung (CD, p. 8-24). Ciliated cells in the nasal cavity and airways, as well as Type I cells in the gas-exchange region, are also identified as targets. While short-term O 3 exposures can cause epithelial cell profileration and fibrolit ic changes in the CAR, these chan ges appear to be transient with recovery time after exposure, depending on species and O 3 dose. The potential impacts of repeated short-term and chr onic morphological effects of O 3 exposure are discussed later in
section 3.3.1.2.5.
Recent studies continue to show that short-term and sub-ch ronic exposures to O 3 cause similar alterations in lung struct ure in a variety of experimental animal species, at concentrations of 0.15 ppm in rats (12 hr/day for 6 weeks) and even lower concentr ations in primates (8 hr/day for 90 days) (CD, section 5.2.4.). Recent work has shown that a topical anti-inflammatory corticosteroid can prevent these effects in nasa l epithelia, while exposure to bacterial endotoxin can potentiate effects. Ozone- induced fibrotic chan ges in the CAR are ma ximal at 3 days of exposure and recover 3 days post-ex posure with exposures of 0.2 ppm O 3 in rodents. One study
has demonstrated vari ability of local O 3 dose and subsequent injury in the respiratory tract due to depletion of glutathione (GSH). The proximal respiratory bron chiole receives the most acute epithelial injury from exposures < 1 ppm, while metabolic effects were greatest in the distal bronchioles and minor daughte r airways (CD, p. 5-38). Based on evidence from animal toxicologi cal studies, short-term and sub-chronic exposures to O 3 can cause morphological changes in the re spiratory systems, particularly in the CAR, of a number of laboratory animal species (CD, section 5.2.4).

3.3.1.1.6 Emergency Department Visits/Hospital Admissions for Respiratory Causes

The 1996 CD evaluated ED visits and hos pital admissions as possible outcomes following exposure to O 3 (CD, section 7.3). The evidence was limited for ED visits, but results3- 18 of several studies generally indicated that short-term exposures to O 3 were associated with respiratory ED visits. The st rongest and most consistent ev idence, both below and above 0.12 ppm 1-hr max O 3 , was found in the group of studies wh ich investigated summertime daily hospital admissions for respirator y causes in different eastern North American cities. These
studies were consistent in demonstrating that ambient O 3 levels were associated with increased hospital admissions and accounted for about one to three excess respirator y hospital admissions per million persons with each 100 ppb increase in 1-hr max O 3 , with adjustment for possible confounding effects of temperatur e and copollutants. Overall, the 1996 CD concluded that there was strong evidence that ambient O 3 exposures can cause significan t exacerbations of preexisting respiratory disease in the gene ral public (CD, p. 7-66). Excess respiratory-related hospital
admissions associated with O 3 exposures for the New York City area (bas ed on Thurston et al., 1992) were included in the quant itative risk assessment in the pr ior review and are included in the current assessment along with estimates for respiratory-related hos pital admissions in Cleveland, Detroit, and Los Angeles based on more recent studies (see Chapter 5). Significant uncertainties and the difficulty of obtaining reliable baseline inci dence numbers resulted in ED visits not being used in th e quantitative risk assessment conducted in the last O 3 NAAQS review. In the past decade, a number of studies have examined the temporal pattern associations
between O 3 exposures and ED visits for respiratory causes (CD, sect ion 7.3.2). These studies are summarized in the CD (Table AX7 -3, Chapter 7 Annex). Respir atory causes for ED visits include asthma, bronch itis, emphysema, pneum onia, and other upper and lower respiratory infections, such as influenza, but asthma visits typi cally dominate the dail y incidence counts. Among studies with adequate co ntrols for seasonal patterns, many reported at least one significant positive association involving O 3 . These studies examined ED visits for total respiratory complaints (Delfi no et al., 1997b, 1998b; Hernandez-Gar duno et al., 1997; Ilabaca et al., 1999; Lin et al., 1999), asthma (Friedman et al., 2001; Jaffe et al., 2003; Stieb et al., 1996; Tenias et al., 1998; Tobias et al., 1999 ; Tolb ert et al., 2000 ; Weisel et al., 2002), and COPD (Tenias et al., 2002). Figure 7-8 (CD, p. 7-68) provide s effect estimates for associa tions between ED visits for
asthma and short-term O 3 exposures. In general, O 3 effect estimates from summer only analyses tended to be positive and larger compared to resu lts from cool season or all year analyses (CD, p. 7-67). Several of the studies reported significant associations between O 3 concentrations and ED visits for respiratory causes. However, inconsistencies were observed which were at least partially attributable to differ ences in model specifi cations and analysis approach among various studies. For example, ambient O 3 concentrations, length of th e study period, and statistical methods used to control confounding by seasonal patterns and copo llutants appear to affect the
observed O 3 effect on ED visits. Thus, th e CD (p. 7-71) has concluded that stratified analyses by3- 19 season generally supported a po sitive association between O 3 concentrations and ED visits for
asthma in the warm season. Unscheduled hospital admissions occur in response to unanticipated disease exacerbations and are more likely to be affected by environmen tal factors, such as high O 3 levels. Thus, hospital admissions studies focus specifically on unschedul ed admissions. Results of a fairly large number of these st udies published during the past d ecade are summarized in Table AX7-4 (CD, Chapter 7 Annex). As a group, these hospital admissions studi es tend to be larger geographically and temporally than the ED visit studies and provi de results that are generally more consistent. The largest and most significant associations of respiratory hospital admissions
with O 3 concentrations were observed using short lag periods, in particular for a 0-day lag (same day exposure) and a 1-day lag (previous day exposure ). Most studies in the United States and Canada indicated positive, st atistically significant asso ciations betw een ambient O 3 concentrations and resp iratory hospital admissions in the warm season, including studies with 98th percentile 8-hr maximum O 3 levels as low as about 50 ppb. However, not all studies found a statistically significant relationship with O 3 , possibly because of very low ambient O 3 levels. Analyses for confounding using multipollutant regression models sugg est that copollutants generally do not confound the association between O 3 and respiratory hospitalizations. Ozone effect estimates were robust to PM adjustment in all-year and warm -season only data. Overall, the CD concludes that positive and robust associations were found between
ambient O 3 concentrations and various respiratory disease hospitalization outcomes, when focusing particularly on results of warm-seas on analyses. Recent st udies also generally supported a positive association between O 3 concentrations and ED vi sits for asthma during the warm season (CD, p. 7-175). These observation s are strongly supported by the human clinical, animal toxicologic, and epidemiologic evid ence for lung function decrements, increased respiratory symptoms, airway inflammation, a nd increased airway responsiveness. Taken together, the overall eviden ce supports a causal relationshi p between acute ambient O 3 exposures and increased respiratory morbidity outcom es resulting in increased ED visits and hospitalizations during the warm season (CD, p. 8-77).

3.3.1.1.7 Effects on Exercise Performance

The effects of O 3 exposure on exercise performance of healthy individuals have been investigated in a number of c ontrolled exposure studies (CD, section 6.7). Several studies discussed in the 1996 CD reported that endurance exercise performance and VO 2max may be limited by acute exposure to O 3 . Other studies found that sign ificant reductions in maximal endurance exercise performance may occur in well-conditioned athlet es while they perform CE (V E > 80 L/min) for 1 hr at O 3 concentrations > 0.18 ppm. There ar e no new studies available in3- 20 the CD. Thus, as in the 1996 CD, the CD concludes that repo rts from studies of O 3 exposure during high-intensity exercise indicate that breathing discomfo rt associated with maximal ventilation may be an important factor in limiting exercise pe rformance in some, but not all, subjects (CD, p. 6-30).

3.3.1.2 Effects on the Respiratory Sy stem from Long-term Exposures

The 1996 CD concluded that th ere was insufficient evidence from the limited number of
studies to determine whether long-term O 3 exposures resulted in ch ronic health effects at ambient levels observed in the U.S. However, the aggregate evidence suggested that O 3 exposure, along with other envir onmental factors, could be res ponsible for health effects in exposed populations (CD, section 7.5). Animal toxicological studies carried out in the 1980’s
and 1990’s demonstrated that l ong-term exposures can result in a variety of morphological effects, including permanent changes in the smal l airways of the lungs, including remodeling of the distal airways and CAR and de position of collagen, possibly re presenting fibrotic changes. These changes result from the dama ge and repair proce sses that occur with repeated exposure. Fibrotic changes were also f ound to persist after months of exposure providing a potential pathophysiologic basis for changes in airway fu nction observed in childr en in some recent epidemiological studies. It app ears that variable seasonal ambi ent patterns of exposure may be of greater concern than c ontinuous daily exposures.
This section reviews studies published since 1996 in which h ealth effects were assessed
for O 3 exposures lasting from weeks to several y ears. Summaries of recent morphological
effects studies of subchronic a nd chronic exposures are listed in Table AX5-10 (CD, Annex AX5). Summaries of recent morb idity effects epidemio logical studies of l ong-term exposure are listed in Table AX7-6 (CD, Annex AX7).

3.3.1.2.1 Seasonal Ozone Effects on Lung Function

It is well documented in controlled huma n exposure and field studi es that daily multihour exposures to O 3 produce transient declines in lung function; however, lung function effects of repeated exposures to O 3 over extended periods are not as we ll characterized. Several studies published since 1996 have investig ated lung function changes over seasonal time periods (CD, section 7.5.3). One large, thr ee-year study (Frischer et al., 1999) collected repeated lung function measurements in 1,150 young, Austrian sc hool children in 9 communities and reported that there may be an association between deve lopmental changes in l ung function over the
summer season and seasonal mean O 3 levels. Mean summertime 24-hr avg O 3 concentrations during the three summers was 34.8 ppb (SD 8.7). The number of days w ith half-hour maximum

O 3 concentrations greater than 60 ppb ranged from 44 to 99 da ys across the 9 communities.
Seasonal mean O 3 was associated with reduced lung function development. It was cautioned that3- 21 it was difficult to attribut e the reported effects to O 3 alone independently of copollutants (CD, p. 7-113). A one-year extension of this study by Horak et al. (2002a,b ) confirmed the results that
seasonal mean O 3 levels may be related to a negative effect on in creases in lung function in children. A study (Kopp et al., 2000) of 797 children in Austri a and southwestern Germany reported smaller increases in lung function in children exposed to higher levels of ambient O 3 (mean O 3 concentration of 44 to 52 ppb) compared to children living in area s with lower ambient

O 3 levels (25 to 33 ppb). Another Austrian study (Ihorst et al., 2000) of 2,153 young children found significantly lower FVC and FEV 1 increases associat ed with higher O 3 exposures in the summer but not in the winter. A pilot st udy (Kinney and Lippmann, 2000) of 72 young adult, military academy students provided results that ar e consistent with a seasonal decline in lung function that may be due, in part, to O 3 exposures. According to th e CD (p. 7-114), these studies collectively indicate that seasonal O 3 exposure is associated w ith smaller growth-related increases in lung function in chil dren than they would have expe rienced living in clean air and
that there is some limited evidence that seasonal O 3 also may affect lung function in young adults, although uncertainty about the role of copollutants make s it difficult to attribute the
effects to O 3 alone.

3.3.1.2.2 Reduced Baseline Lung Function and Respiratory Symptoms Lung capacity grows during childhood and adol escence as body size increases, reaches a maximum during the twenties, and th en begins to decline steadily and progressively with age. Long-term exposure to air polluti on has long been thought to contri bute to slower growth in lung capacity, diminished maximally at tained capacity, and/or more ra pid decline in lung capacity with age (CD, section 7.5.4). To xicological findings evaluated in the 1996 CD demo nstrated that repeated daily exposure of rats to an episodic profile of O 3 caused small, but significant, decrements in growth-related l ung function that were consistent with early indicators of focal fibrogenesis in the proximal al veolar region, without overt fi brosis (CD, section 5.2.5.2).

Because O 3 is a strong respiratory ir ritant and has been shown to cause inflammation and restructuring of the respiratory airway s, it is plausible that long-term O 3 exposures might have a negative impact on baseline lung function, particularly during childhood when these exposures might have long-term risks. As noted in the current CD, however, no recent toxicological studies have been published on effects of chronic O 3 exposure. Several epidemiological studi es published since 1996 have examined the relationship between lung function deve lopment and long-term O 3 exposure. The most extensive and robust study of respiratory effects in re lation to long-term air pollution exposures among children in the U.S. is the Children’s Health Study carried out in 12 communities of southern California starting in 1993 (Avol et al., 2001; Gaud erman et al., 2000, 2002, 2004a,b; Pe ters et al., 1999a,b). One3- 22 study (Peters et al., 1999a) examined the relationship between long-term O 3 exposures and self reports of respiratory symptoms and asthma in a cross sectional anal ysis and found a limited relationship between outcomes of current as thma, bronchitis, cough and wheeze and a 40 ppb
increase in 1-hr max O 3 (CD, p. 7-115). Another analysis (Peters et al., 1999b) examined the relationship between lung function at baseline and levels of ai r pollution in the community and reported evidence that annual mean O 3 levels were asso ciated with decreases in FVC, FEV 1 , PEF
and FEF 25-75 (the latter two being statis tically significant) among fema les but not males (CD, p. 7- 116). In a separate study (G auderman et al., 2000) of 4 th , 7 th , and 10 th grade students, a longitudinal analysis of lung fu nction development over four years found no association with O 3 exposure. Subsequent studies by the same group (Gauderman et al ., 2002, 2004a,b) led the authors to conclude that results pr ovide little evidence that ambient O 3 at current levels is
associated with chronic deficits in the rate of increase in growth -related lung function in children (CD, p. 7-116 to 7-118). A vol et al. (2001) examined children who had moved from participating communities in sout hern California to other states with improved air quality and found, with the ex ception of FEV 1 , the O 3 effect estimates for all other spirometric parameters were negative, but the associations were not as strong as th ose observed for PM 10 (CD, p. 7-116). Collectively, the resu lts of these reports from the children’s health cohorts provide little evidence for impact of long-term O 3 exposures on lung function development (CD, p. 7-122). Evidence for a sign ificant relationship between long-term O 3 exposures and decrements in maximally attained lung func tion was reported in a nationwi de study of first year Yale students (CD, p. 7-120). Males had much larger effect estimates than females, which might reflect higher outdoor activity leve ls and correspondingly higher O 3 exposures during childhood. A similar study (Kunzli et al., 1997 ; Tager et al., 1998) of college freshmen at University of California at Berkeley also reported significant effects of long-term O 3 exposures on lung function (CD, p. 7-121). In a co mparison of students whose city of origin was either Los Angeles or San Francisco, long-term O 3 exposures were associated with significant changes in mid- and end-expiratory flow measures, which could be c onsidered early indicators for pathologic changes that mi ght progress to COPD. In summary, recent publications from the southern California children’s cohort study provide no evidence for an a ssociation between long-term O 3 exposure and lung function development in children (CD, p. 7- 118), while limited evidence av ailable from studies of adults and college students suggest that long-term O 3 exposure may affect lung function or respiratory symptoms (CD, pp. 7-120, 7-121). Overall, the CD concluded that this body of evidence was
inconclusive for eff ects of long-term O 3 exposure on respiratory symp toms or lung function (CD, p. 7-175).3- 23 3.3.1.2.3 Long-term O 3 Exposure and Respiratory Inflammation

As noted above in sectio n 3.3.1.1.3 and in the CD (Chapter 6), chamber studies of exercising humans exposed to O 3 for 2 to 6.6 hrs have demonstrat ed inflammation in the lungs, including the alveolar region where gas exch ange takes place. The potential long-term significance of short- term exposures to O 3 is that they can result in the release of reactive substances from inflammatory ce lls that can damage the sensitive cells lining the lungs. Over time repeated inflammation can lead to permanen t lung damage and restru cturing of the small airways and alveoli. Also, sinc e inflammation is a hallmark charact eristic of asthma, there is the possibility that O 3 -induced inflammation may exacerbate existing asthma or contribute to the development of asthma in genetically pr edisposed individuals (CD, section 7.5.5). For subchronic exposures of animals, pe rmeability changes are transient (and speciesdependent) and return to cont rol levels even with continui ng exposure. For long-term O 3 exposures, persistent O 3 -induced inflammation play s an important role in alterations of lung structure and function. Signifi cant remodeling of the epithel ium and underly ing connective tissues in distal airways have been re ported in rats exposed to 0.25 ppm O 3 (12 hr/day for 6 weeks) and in monkeys exposed to 0.15 ppm O 3 (8 hr/day for 90 days)(CD, p. 8-23). In one epidemiological fiel d study (Kinney et al., 1996), BAL fluids were taken in the summer and winter from a group of joggers in New York and were compared for evidence of
acute inflammation and of enhanced cell dama ge (CD, p. 7-122). The mean 1-hr max concentrations for a 3-month pe riod were 58 ppb (max 110 ppb) in the summer and 32 ppb (max 64 ppb) in the winter. There was little evidence of an a ssociation between O 3 and acute inflammation in the summer BAL fluids compared to winter, but there wa s evidence of enhanced cell damage. This suggests that even though in flammation may diminish over the summer, cell damage may be continuing. A cross-sectional cohort study (Calderon-Ga rciduenas et al., 1995) conducted in Mexico City provide s evidence of inflammation and ge netic damage to cells in the nasal passages of children chronically exposed to O 3 and other air pollutants (CD, p. 7-123). In Mexico City, th e 1-hr avg O 3 concentrations exceeded 120 pp b for 4.4 hr/day, on average. Significantly higher DNA damage wa s reported in children living in Mexico City compared to nonurban children and in older comp ared to younger children. A nother marker of inflammation, urinary eosinophils, was analyzed in an Austri an school children study (Frischer et al., 2001), and it was reported that O 3 exposure (mean 30 day avg O 3 concentration before sample collection was 31.6 ppb) was significantly associated with eosinophil infl ammation (CD, p. 7-122). In assessing these studies, th e CD (p. 7-123) concluded that specific attribu tion of these adverse respiratory and genotoxic effects to O 3 is difficult given the co mplex mixture in ambient air, although inflammatory change s like eosinophil levels observe d in the Austrian study would
be consistent with known effects of O 3
.3- 24 3.3.1.2.4 Risk of Asthma Development There have been a few studies investig ating associations between long-term O 3 exposures and the onset of new cases of asthma (CD, section 7.5.6). The Adventist Health and Smog (AHSMOG) study cohort of 3,914 was drawn from nonsmoking, non-Hispanic white adult Seventh Day Adventists living in California (Greer et al., 199 3; McDonnell et al., 1999). Subjects were surveyed in 1977, 1987, and 1992. During the ten-year fo llow-up in 1987, it was reported that the incidence of ne w asthma was 2.1% for males and 2.2% for females (Greer et al., 1993). A statistically significan t relative risk of 3.12 (95% CI : 1.16, 5.85) per 10 ppb increase in
annual mean O 3 was observed in males, compared to a nons ignificant relative risk of 0.94 (95% CI: 0.65, 1.34) in females. In the 15-year follow- up in 1992, it was reported that 3.2% of eligible males and 4.3% of eligible fe males had developed adult asthma (McDonnell et al., 1999). For males, the relative risk of developing asthma was 2.27 (95% CI: 1.03, 4.87) per 30 ppb increase in 8-hr average O 3 , but there was no evid ence of an association in females. The lack of an association in females does not necessarily mean there is no effect but ma y be due to differences in time-activity patterns in male s and females, which could lead to greater misclassification of exposure in females. Consistenc y of results in the two studies with different follow-up times provides supportive evidence of an association between long-term O 3 exposure and asthma incidence in adult males; however, representati veness of this cohort to the general U.S. population may be limi ted (CD, p. 7-125). In a similar study (McConnell et al., 2002) of incident asthma among children (ages 9 to 16 at enrollment), annual survey s of 3,535 children initially without asthma were used to identify
new-onset asthma cases as part of the Children’s Health Study. Six high-O 3 (75.4 ppb mean 1-hr max over four year s) and six low-O 3 (50.1 ppb, mean 1-hr max) comm unities were identified
where the children resided. There were 265 childr en who reported new-on set asthma during the follow-up period. Although asthma risk was no higher for all reside nts of the six high-O 3 communities versus the six low-O 3 communities, asthma risk was 3.3 times greater for children who played three or more sports as compared with children who played no sports within the high-O 3 communities. This associ ation was absent in the communities with lower O 3 concentrations. No other polluta nts were found to be associated with new-onset asthma (CD, p. 7-125). Playing sports may result in extended outdoor activity a nd exposure occurring during periods when O 3 levels are higher. The sports activitie s would cause an increased ventilation rate, thus resulting in increased O 3 dose. It should be noted, however, that the results of the Children’s Health Study (McConn ell et al., 2002) were based on a small number (20 in high-O 3 areas and 9 in low- O 3 areas) of new-onset asthma cases among children who played three or3- 25 more sports (CD, p. 7-125). Fu ture replication of these findings in other cohorts would help
determine whether a causal in terpretation is appropriate.

3.3.1.2.5 Morphological Effects In animal toxicology studies, the progre ssion of morphological e ffects reported during and after a chronic exposure in the range of 0.5 to 1.0 ppm O 3 is complex, with inflammation peaking over the first few days of exposure, then dropping, then plateauing, and finally, largely disappearing (CD, section 5.2.4.4). By contrast, fibrotic changes in the tissue increase very slowly over months of exposure, and, after exposure ceases, the change s sometimes persist or increase. Epithelial hyp erplasia peaks soon after the infla mmatory response but is usually
maintained in both the no se and lungs with conti nuous exposure. Epithelial hyperplasia/metaplasia also does not return to pre-exposure levels after the end of exposure. Patterns of exposure in this same concentration range determine e ffects, with 18 months of daily exposure, causing less morphologi c damage than exposures on al ternating months. This is important as environmental O 3 exposure is typically seasonal. Long-term studies of Plopper and colleagues (Evans et al ., 2003; Schelegle et al ., 2003; Chen et al., 2003; Plopper and Fanucchi, 2000) investigated infant rhesus monke ys exposed to simulated, seasonal O 3 (0.5 ppm, 8 hrs/day for 5 days, every 14 days for 11 episodes) and dem onstrated: 1) remodeling in the distal airways, 2) abnormalities in tracheal basement me mbrane; 3) eosinophil accumulation in conducting airways; and 4) decrements in airway innervation (CD, p. 5-45). As with other effects, these findings advance earlier informat ion regarding possible injury-repair processes occurring with long-term O 3 exposures suggesting that these processes are only pa rtially reversible and may progress following cessation of O 3 exposure. Further, these proc esses may lead to nonreversible structural damage to lung tissue; however, ther e is still too much uncer tainty to quantitatively extrapolate these levels to human effect levels at this time (CD, p. 8-25).

3.3.1.2.6 Summary In the past decade, important new longitudi nal studies have exam ined the effect of
chronic O 3 exposure on respiratory health outcomes. Evidence from recent long-term morbidity studies have suggested in some ca ses that chronic exposure to O 3 may be associated with
seasonal declines in lung function or reduced lung fu nction development, increases in inflammation, and development of asthma in children and adults . Seasonal decrements or smaller increases in lung function measures have been reported in several studies; however, it
remains uncertain to what extent these changes are transient. While there is s upportive evidence from animal studies involving chr onic exposures, large uncertainties still remain as to whether current ambient levels and exposure patterns might cause these sa me effects in human3- 26 populations. The CD also conclu des that epidemiological studie s of new asthma development and longer-term lung function d eclines remain inconclusive at present (CD, p. 7-134).

3.3.1.3 Effects on the Cardiovascular System

At the time of the 1997 re view, the possibility of O 3 -induced cardiovascular effects was a largely unrecognized issue. Si nce then, a very limited body of evidence from animal, controlled human exposure and epidemiologic studies has em erged that provides some potential plausible
mechanisms for how O 3 exposures might exert cardiovascul ar system effects, however much
needs to be done to substantiate these ef fects. Possible mechanisms may involve O 3 -induced
secretions of vasoconstrictive subs tances and/or effects on neuronal reflexes that may result in increased arterial blood pressure and/or altered electrophysiologi c control of heart rate or rhythm. Some animal toxicology studies have shown O 3 -induced decreases in heart rate, mean arterial pressure, and core temperature. On e controlled human exposur e study that evaluated
effects of O 3 exposure on cardiovascular health outcomes found no significant O 3 -induced differences in ECG or blood pressure in heal thy or hypertensive subj ects but did observe a significant O 3 -induced increase the al veolar-to-arterial PO 2 gradient and heart rate in both groups resulting in an overall increase in myocardial work and impair ment in pulmonary gas exchange (Gong et al., 1998). In anothe r controlled human exposure st udy, inhalation of a mixture of

PM 2.5 and O 3 by healthy subjects in creased brachial artery tone and reactivity (Brook et al., 2002).
The evidence from a few animal studies also includes potential direct effects such as O 3 - induced release from lung epithelial cells of plat elet activating factor (P AF) that may contribute
to blood clot formation that w ould increase the risk of seri ous cardiovascular outcomes (e.g., heart attack, stroke, mortality) . Also, interactions of O 3 with surfactant com ponents in epithelial lining fluid of the lung may resu lt in production of oxysterols a nd reactive oxygen species that may exhibit PAF-like activity contributing to cl otting and also may exert cytotoxic effects on lung and heart muscle cells. Epidemiologic panel and field studies that examined associations between O 3 and various cardiac physiologic endpoints have yielded limited evidence sugges tive of a potential association
between acute O 3 exposure and altered heart rate variab ility, ventricular arrhythmias, and
incidence of heart attacks. A number of epidemiological studies have also reporte d associations between short-term exposures a nd hospitalization for cardiovascu lar diseases. As shown in Figure 7-13 of the CD, many of the studies reported negative or inconsistent asso ciations. Some other studies, especially those that examined the relationship when O 3 exposures were higher, have found robust positive associations between O 3 and cardiovascular hosp ital admissions (CD, p. 7-82). For example, one study report ed a positive asso ciation between O 3 and cardiovascular3- 27 hospital admissions in Toront o, Canada in a summer-only an alysis (mean 1-hr max O 3 of 41.2 ppb) (Burnett et al., 1997b). The results were robust to adjustme nt for various PM indices,
whereas the PM effects diminish ed when adjusting for gaseou s pollutants. Other studies stratified their analysis by te mperature, i.e., by warms days ( ≥ 20°C) versus cool days (< 20°C). Several analyses using warms days cons istently produced positive associations. The epidemiologic evidence for cardiovascular morbidity is much more mixed than for respiratory morbidity, with only one of several U.S./Canadian studies showing statistically significant positive associations of cardiova scular hospitalizations with warm-season O 3 concentrations. Most of the available European and Australia n studies, all of which conducted all-year O 3 analyses, did not find an asso ciation between short-term O 3 concentrations and cardiovascular hospitalizations. Overall, the currently available evidence is inconclusive regarding an association between cardiov ascular hospital admissions and ambient O 3 exposure (CD, p. 7-83).
Based on the evidence from animal toxicology, human controlled exposure, and epidemiologic studies, the CD concludes that this generally limited body of evidence is highly suggestive that O 3 can directly and/or indirectly contri bute to cardiovascula r-related morbidity,
but that much needs to be done to more fully substantiate links between ambient O 3 exposures and adverse cardiovascular outcomes (CD, p. 8-77).

3.3.2 Premature Mortality There were only a limited number of studies which examined the relationship between O 3 and mortality available for revi ew in the 1996 CD. Some studie s suggested that mortality was
associated with short-term exposure to O 3 , but conclusions could not be drawn regarding such associations (CD, p. 7-84). Numerous recent studies have provided new and more substantial evidence supporting such an association, as discussed below in section 3.3.2.1.
At the time of the last review, little epid emiological evidence was available on potential
associations between lo ng-term exposure to O 3 and mortality. Some recent studies have evaluated this relationship and provide limited, if any, evidence for an association between
chronic O 3 exposure and mortality, as described in section 3.3.2.2.

3.3.2.1 Mortality and Short-term O 3 Exposure

The 1996 CD concluded that an associ ation between daily mortality and O 3 concentration for areas with high O 3 levels (e.g., Los Angeles) was suggeste d. However, due to a very limited
number of studies available at th at time, there was in sufficient evidence to conclude that the observed association was likely causal , and thus the possibility that O 3 exposure may be associated with mortality was not relied upon in the 1997 decision on the O 3 primary standard.3- 28 The 2006 CD includes resu lts from numerous epidemiol ogical analyses of the relationship between O 3 and mortality. Key findings are av ailable from multi-city time-series studies that report as sociations between O 3 and mortality. These stud ies include analyses using
data from 90 U.S. cities in the National Mo rtality, Morbidity and Air Pollution (NMMAPS) study (Dominici et al., 2003) and from 95 U.S. communities in an exte nsion to the NMMAPS analyses (Bell et al., 200 4). The analyses conduct ed by Huang et al. (2005) used a subset of 19 U.S. cities and focused primarily on cause-speci fic mortality associa tions during the warm season. An additional study (Schwartz, 2005) used case-crossover design and data from 14 U.S. cities to further investigate the influence of adjustment for weather variables in the O 3 -mortality relationship (CD, p. 8-38). Fi nally, results are available from a European study, Air Pollution and Health: a European Approach (APHEA), using data from 23 cities (Gryparis et al., 2004) and 4 cities (Toulomi et al., 1997) (CD, p. 7-93). The original 90-city NMMAPS analysis, with data from 1987 to 1994, was primarily focused on investigating effects of PM 10 on mortality. A significan t association was reported between mortality and 24-hr average O 3 concentrations during the warm season, but the association was not significant in analyses for the full year (Samet et al., 2000) (C D, Figure 7-21; p. 7-98). This is because the estimate using al l available data was a bout half that for the summer-only data at a lag of 1- day. The extended NMMAPS anal ysis included data from 95
U.S. cities and included an ad ditional 6 years of data, from 1987-2000 (Bell et al., 2004), and significant associations were reported between O 3 and mortality. The effect estimate for increased mortality was 0.5% per 24-hr average O 3 measured on the same day (20 ppb change; 95% PI: 0.24, 0.78), and 1.04% per 24-hr average O 3 in a 7-day distributed lag model (20 ppb change; 95% PI: 0.54, 1.55) (CD, p. 7-88). In an alyses using only data from the warm season, the results were not significantly different from the full-year re sults; the effect estimate for increased mortality was 0.44% per 24-hr average O 3 measured on the same day (20 ppb change; 95% PI: 0.14, 0.74), and 0.78% per 24-hr average O 3 in a 7-day distributed lag model (20 ppb change; 95% PI: 0.26, 1.30). The au thors also report that O 3 -mortality associations were robust to adjustment for PM (CD, p. 7-100). Using a subset of the NMMAPS data set, Huang et al. (2005) fo cused on associations between cardiopulmonary mortality and O 3 exposure (24-hr avg) duri ng the summer season only. The authors report a 1.47% increase per 20 ppb change in O 3 concentration measured on the same day (95% PI: 0.54, 2.39) and a 2.52% increase per 20 ppb change in O 3 concentration using a 7-day distributed lag model ( 95% PI: 0.94, 4.10)(CD, p. 7-92). Th ese findings sugg est that the
effect of O 3 on mortality is immediate but also persists for several days. As discussed below in section 3.4, confounding by weather, especially temperature, is complicated by the fact that higher temperatures are associated with th e increased photochemical3- 29 activities that are important for O 3 formation. Using a case-cro ssover study design, Schwartz (2005) assessed associations between daily maximum concentr ations and mortality, matching case and control periods by temperature, and using data only from the warm season. The reported effect estimate of 0.92% change in mortality per 40 ppb O 3 (1-hr max, 95% PI: 0.06, 1.80) was similar to time-series an alysis results with adjustment for temperature (0.76% per 40 ppb O 3 , 95% PI, 0.13, 1.40), suggesting th at associations between O 3 and mortality were robust to the different adjustment met hods for temperature (CD, p. 7-93). An initial publication from APHEA, a Euro pean multi-city study, reported statistically significant associations between daily maximum O 3 concentrations and mort ality, with an effect
estimate of a 4.5% increase in mortality per 40 ppb O 3 (95% CI: 1.6, 7.7) in four cities (Toulomi et al., 1997). An extended analysis was done using data from 23 cities throughout Europe (Gryparis et al., 2004). In this report, a positive but not statistically signif icant association was found between mortality and 1-hr daily maximum O 3 in a full year anal ysis (CD, p. 7-93). Gryparis et al. (2004) noted th at there was a considerable seasonal differ ence in the O 3 effect on mortality; thus, the sma ll effect for the all-year data might be attributable to inadequate adjustment for confounding by se asonality. Focusing on analyses using summer measurements, the authors report statistically significant associations with total mortality [1.8% increase per 30 ppb 8-hr O 3 (95% CI: 0.8, 2.9)], cardi ovascular mortality [2.7% increase per 30 ppb 8-hr O 3 (95% CI: 1.2, 4.3)] and with respiratory mortality (6.8% increase per 30 ppb 8-hr O 3 , 95% CI: 4.5, 9.2) (CD, p. 7-93, 7-99). Two of the recent multi-city mortality studies (Bell et al ., 2004; Gryparis et al., 2004) have also reported associations for multiple averaging times (CD, p. 8-38). Bell and colleagues (2004) reported associations betw een mortality and 1-hr daily ma x, 8-hr daily max and 24-hr avg

O 3 concentrations. Effect estimates for associations with 1-hr O 3 was slightly larger than that reported for 8-hr O 3 concentrations, and both were slightly larger than the asso ciation with 24-hr avg O 3 , but the effect estimates di d not differ statistically. Th e APHEA study (Gryparis et al., 2004) also reported effect estimates that were slightly larger with 1- hr than with 8-hr O 3 concentrations, but not significantly so. Numerous single-city analyses have also reported associ ations between mortality and
short-term O 3 exposure, especially for those analyses using warm season data. As shown in Figure 7-21 of the CD, the result s of recent publications show a pattern of positive, often statistically significant associ ations between short-term O 3 exposure and mort ality during the warm season (CD, p. 7-97). For example, statisti cally significant associat ions were reported in southern California (Ostro, 1995) , Philadelphia (Moolgavkar et al ., 1995), Dallas (Gamble et al., 1998), and Vancouver (Vedal et al., 2003), as well as numerous studies conducted in other countries. However, no evidence of an asso ciation was seen in a st udy conducted in Pittsburgh3- 30 (Chock et al., 2000). In considering results from year-round an alyses, there remains a pattern of positive results but the findings are less consiste nt. For example, st atistically significant associations were reported in Philadelphia (Moo lgavkar et al., 1995) and Dallas (Gamble et al., 1998), while positive but not statisti cally significant associations were reported in Detroit (Lippmann et al., 2000, reanalyzed in Ito, 2003), San Jose (Fairl ey, 1999, reanalyzed Fairley, 2003), and Atlanta (Klemm et al., 2004). No evidence for asso ciations was reported in Los Angeles (Kinney et al., 1995), Coach ella Valley (Ostro et al., 2003), and St. Louis and Eastern Tennessee (Dockery et al., 1992). In most single-city analyses , effect estima tes were not substantially changed with adjustment for PM (CD Figure 7-22, p. 7-101). In addition, several meta-ana lyses have been conducted on the relationship between O 3 and mortality. As described in section 7.4.4 of the CD, these analyses report ed fairly consistent and positive combined effect estimates ranging from 1.5 to 2.5% increase in mortality for a standardized change in O 3 (CD, Figure 7-20, p. 7-95). Thre e recent meta-analyses evaluated potential sources of heterogeneity in O 3 -mortality associations (Be ll et al., 2005; Ito et al., 2005; Levy et al., 2005). The CD (p. 7- 96) observes common findi ngs across all three analyses, in that all reported that effect estimates were larger in warm season analys es, reanalysis of results using
default GAM criteria did not chan ge the effect estimates, and th ere was no strong evidence of confounding by PM (CD, p. 7-97). Bell et al. (2005) and It o et al. (2005) both provided suggestive evidence of publication bias, but O 3 -mortality associations remained after accounting for that potential bias. The CD (7-97) concludes that the “positive O 3 effects estimates, along with the sensitivity analyses in these three meta-analyses, provide evidence of a robust
association between ambient O 3 and mortality.” Most of the single-pollutant model estimates from single-city studies range from 0.5 to 5% excess deaths per standardi zed increments. Corr esponding summary estimates in large U.S. multi-city studies ranged between 0.5 to 1% with some studies noting hete rogeneity across cities and studies (CD, p. 7-110). In the CD (p. 7-101), Figure 7-22 shows the O 3 risk estimates with and without adjustment for PM indices using al l-year data in studies that c onducted two-pollutant analyses. Approximately half of the O 3 risk estimates increased slightl y, whereas the other half decreased slightly with the inclusion of PM in the models. In general, the O 3 - mortality risk estimates were robust to adjustment for PM in the models, with the exception of Los Angeles, CA data with

PM 10 (Kinney et al., 1995) and Mexico City data with TSP (Borja-A burto et al., 1997). The U.S. 95 communities study (Bell et al., 2004) examined the sensitivity of acute O 3 -mortality effects to potential confounding by PM 10 (CD, 7-100). Restricting anal ysis to days when both O 3 and PM 10 data were available, the community-specific O 3 -mortality effect estimates as well as the national average results indicated that O 3 was robust to adjustment for PM 10 (Bell et al., 2004).3- 31 Several O 3 -mortality studies examined the eff ect of confounding by PM indices in different seasons (CD, p. 7-102, Fi gure 7-23). In analyses usi ng all-year data and warm-season only data, O 3 effect estimates were once ag ain fairly robust to adjustment for PM indices, with values showing both slight increases and decreases with the inclus ion of PM in the model. In the analyses using cool season data only, the O 3 effect estimates all incr eased slightly with the adjustment of PM indices, although none reached statisti cal significance. The three recent meta-analyses (Bell et al ., 2005; Ito et al., 2005; Levy et al., 2005) all
examined the influence of PM on O 3 risk estimates. No substant ial influence was observed in any of these studies. In the an alysis by Bell et al . (2005), the combined estimate without PM adjustment was 1.7% (95% PI: 1.10, 2.37) from 41 estimates, and th e combined estimate with PM adjustment was 1.95% (95% PI: 1.06, 4.00) from 11 estimates per 20 ppb increase in 24-hr avg O 3 . In the meta-analysis of 15 cities (Ito et al., 2005), the comb ined estimate was 1.6% (95% PI: 1.1, 2.2) and 1.5% (95% PI: 0.8, 2.2) per 20 ppb in 24-hr avg O 3 without and with PM adjustment, respectively (CD, p. 7- 103). The additional time-series analysis of six cities by Ito et al. (2005) found that the influence of PM by season varied across alternative weather models but was never substantial. Levy et al. (2005) examined the regr ession relationships between O 3 and PM indices (PM 10 and PM 2.5 ) with O 3 -mortality effect estimates for all year and by season. Positive slopes, which might indicate pot ential confounding, were observed for PM 2.5 on O 3 effect estimates in the summer a nd all-year periods, but the relati onships were weak. The effect of one causal variable (i.e., O 3 ) is expected to be overestimat ed when a second causal variable (e.g., PM) is excluded from the an alysis, if the two variables are positively correlated and act in the same direction. However, the results from these meta-analyses, as well as seve ral single- and multiple-city studies, indicate that copollutants ge nerally do not appear to substantially confound
the association between O 3 and mortality (CD, p. 7-103). Finally, from those studies that included assessment of associ ations with specific causes of death, it appears that effect es timates for associations with car diovascular mortality are larger than those for total mortality; ef fect estimates for respiratory mort ality are less consistent in size, possibly due to reduced statistical power in this sub category of mortality (CD, p. 7-108). The U.S. 95 communities study (1987-2000) analyzed O 3 effect estimates from cardiovascular and respiratory mortality. The analysis by Bell et al. (2005) used all available data, which included all-year data from 55 communities and warm-s eason only data from 40 communities. The national average estimate from the constrained di stributed lag model was slightly greater for cardiopulmonary deaths than deat hs from all causes, with an excess risk of 1.28% (95% PI: 0.62, 1.97) compared to 1.04% (95% PI: 0.54, 1.55) per 20 ppb increase in 24-hr avg O 3 in the preceding week.3- 32 One recent multi-city study (Be ll et al., 2006) examined the shape of the concentrationresponse function for the O 3 -mortality relationship in 98 U.S. urban communities for the period 1987 to 2000 specifically to evaluate whether a “s afe” threshold level exists. Results from various analytic methods all indi cated that any threshold would ex ist at very low concentrations,
far below the level of the current O 3 NAAQS and other, lower international O 3 standards, 3 and nearing background levels. Notably, in a subset analysis using only days that were below the
level of the current O 3 NAAQS, the O 3 -mortality association remained statistically significant with only a small change in the size of the effect estimate. Further, in a subset analysis based on 24-hr average O 3 concentrations, the effect estimates declined and lost statistical significance only when the maximum daily average concentration included was < 10 ppb (Bell et al., 2006, p. 14 and Figure 2), which corresponds to daily ma ximum 8-hr average conc entrations in U.S. cities that are within the rang e of background concentrations. The authors conclude that
“interventions to further reduce ozone pollution would be nefit public health, ev en in regions that meet current regulatory standards an d guidelines” (Be ll et al., 2006, p. 3). A related study (Huang et al., 2005) examined O 3 effects on cardiopulmonary mortality during the summers (June to September) of 19 87 to 1994 in 19 large U.S. cities from the NMMAPS database. Figure 7-24 in the CD (p. 7-104), presents th e Bayesian city-specific and overall average O 3 effect estimates for cardiopulmonary mortality per 20 ppb increase in 24-hr avg O 3 from a constrained 7-day distributed la g model. The O 3 effect estimate was 2.52% (95% PI: 0.94, 4.10) excess risk in cardiopulmonary mortality per 20 ppb increase in 24-hr avg O 3 in the preceding week for the combined analysis of all cities. For anal yses of summer data, confounding of the O 3 effect by PM is of concer n as daily variations in O 3 may be positively correlated to PM during the summer months. Huang et al. (2005) observed that when PM 10 was included in the model, the O 3 effect estimate, on aver age, remained positive and significant. As

PM 10 measurements were available only every 1 to 6 days, only single-day lags were examined. At a 0-day lag, O 3 was associated with a 1.47% (95% PI: 0.54, 2.39) excess risk versus a 1.49% (95% PI: 0.66, 3.47) excess risk in cardiopulmonary mortality in the O 3 -only model and after adjustment for PM 10 , respectively. The slight sensitivity of the O 3 health effects to the inclusion
of PM 10 in the model may indicate a tr ue confounding effect. Howeve r, as only the days with

PM 10 data available were included in the analysis, th e lack of significance is likely attributable to higher statistical uncertainty due to the reduced data availability (CD, p. 7-105). Figure 7-25 in the CD (p., 7-106), presents effect estimat es for associations between O 3 and cardiovascular mortality for all-year and warm-season anal yses. All studies, with the

3 Other international 8-hr O 3 standards considered by Bell et al. (2006, Table 1) include the California standard of 70 ppb, the Canadian standard of 65 ppb, and the World Health Organization guideline and European Commission target value of approximately 61 ppb.3- 33 exception of Ponka et al. (1998), show ed positive associations between O 3 and cardiovascular mortality (CD, p. 7-105). As with all-cause mort ality, there appears to be heterogeneity in the
effect estimates across studies. The cardiovas cular mortality estimate from one meta-analysis (Bell et al., 2005) appears to be close to the mode of the ef fect estimates from the various studies, as shown in Figure 7-25, in the CD (p. 7-106). This is expected, given that many of
these studies were also included in the meta-analysis. Th is study observed th at the posterior mean estimate for cardiovascular causes (2.23% excess risk per 20 ppb increase in 24-hr avg O 3 from 25 estimates) was slightly la rger than that for total mortality (1.75% excess risk from 41 estimates). However, since cardiovascular deat hs account for the larges t fraction (over 40%) of total deaths, it is not surprising that the risk es timates for cardiovascular mortality are somewhat
similar to those from all-cause mo rtality. Overall, the cardiovascular mortality risk estimates in
the current literature show cons istently positive associations with some heterogeneity (most
estimates fall within the range of 1 to 8% per 40 p pb increase in 1-hr avg O 3 (CD, p. 7-107).
Several studies observed that the risk estimat es for the respiratory category were larger
than the cardiovascular and total nonaccidental categories (Anderson et al., 1996; Gouveia and Fletcher, 2000; Gryparis et al ., 2004; Zmirou et al., 1998). The ap parent inconsistencies across studies may be due in part to the differences in mode l specifications, but th ey may also reflect the lower statistical power associ ated with the smaller daily co unts of the respiratory category (usually accounting for less than 10% of total deaths) co mpared to the larger daily counts for the cardiovascular category (approximate ly 40 to 50% of total deaths). Thus, an examination of the
differences in risk estimates across specific causes requires a large population and/or a long period of data collection. In summary, several single-city studies ob served positive associat ions of ambient O 3 concentrations with total nonaccidental and cardi opulmonary mortality. The CD finds that the results from U.S. multi-city time-series studies provide the strongest evidence to date for O 3 effects on acute mort ality. Recent meta-analyses also indi cate positive risk es timates that are unlikely to be confounded by PM; however, future work is need ed to better understand the influence of model specifications on the risk coefficient (CD, p. 7-175). A meta-analysis that examined specific causes of mort ality found that the cardiovascular mortality risk estimates were higher than those for total mo rtality. For cardiovascular mort ality, the CD (F igure 7-25, p. 7- 106) suggests that effect estimates are consiste ntly positive and more likely to be larger and statistically significant in warm season analyses . The findings regarding the effect size for respiratory mortality have been le ss consistent, possibly because of lower statistical power in this subcategory of mortality. The CD (p. 8-78) concludes that these findings are hi ghly suggestive that short-term O 3 exposure directly or indirectly contribute to non-accidental and cardiopulmonary-related mortality, but additional research is need ed to more fully establish underlying mechanisms by which such effects occur.3- 34 3.3.2.2 Mortality and Long-term O 3 Exposure

Little evidence was av ailable in the last review on the potential for associations between mortality and long-term exposure to O 3 . In the Harvard Six City pr ospective cohort analysis, the authors report that mortality was not as sociated with long-term exposure to O 3 (Dockery et al., 1993). The authors note that the range of O 3 concentrations across th e six cities was small (19.7 to 28.0 ppb in average 24-hr con centrations over the 7-year study period), which may have limited the power of the st udy to detect associations between mortality and O 3 levels (CD, p. 7- 127). As discussed in section 7.5.8 of the CD, in th is review there are re sults available from three prospective cohort studies : the American Can cer Society (ACS) st udy, the Adventist Health and Smog (AHSMOG) study, and the U.S. Veterans Cohort study. In addition, a major reanalysis report includes evalua tion of data from the Harvard Si x City cohort study (Krewski et al., 2000). This reanalysis also includes additional eval uation of data from the initial ACS cohort study report that had only repor ted results of associations be tween mortality and long-term exposure to fine particles a nd sulfates (Pope et al., 1995). 4 In this reanalysis of data from the previ ous Harvard Six City pr ospective cohort study, the investigators replicated and validated the fi ndings of the original studies, and the report included additional quantitative results beyond those available in the original report (Krewski et al., 2000). In the reanalysis of data from the Harvard Six Cities study, the effect estimate for the association between long-term O 3 concentrations (8.3 ppb betw een the highest and lowest concentrations in the cities) and mortality was negative and ne arly statistically significant (relative risk = 0.87, 95% CI: 0.76, 1.00). The ACS study is based on health data from a large prospective c ohort of approximately 500,000 adults and air quality data from about 150 U.S. cities. The initial report (Pope et al., 1995) focused on associations with fine particles and sulfates, fo r which significant associations had been reported in the earlier Harvard Six Cities study (Dockery et al., 1993). As part of the major reanalysis of these data, results for asso ciations with other ai r pollutants were also reported, and the authors report that no significant associat ions were found between O 3 and all cause mortality (95% CI: 0.96-1.07). A si gnificant associatio n was reported for cardiopulmonary mortality (rel ative risk=1.08, 95% CI: 1.01, 1.16) (Krewski et al., 2000, p. 174). For some specifications of O 3 exposure in the ACS study, ther e was an effect in the warm quarter, as there was in the reanal ysis of the Harvard Six Cities study.

4 This reanalysis report and the original prospective cohort study findings are discussed in more detail in section 8.2.3 in Air Quality Criteria for Particulate Matter (EPA, 2004).3- 35 The ACS II study (Pope et al ., 2002) reported results of asso ciations with an extended data base; the mortality records for the cohort had been updated to incl ude 16 years of follow-up (compared with 8 years in the firs t report) and more recent air qual ity data were included in the analyses. Results are presented for full-year and summer season an alyses, and show no evidence for a significant association be tween long-term exposure to O 3 and mortality. As shown in Figure 7-27 of the CD, th e effect estimates are not statistically signifi cant for associations between long-term O 3 exposure and all-cause, cardiopulmona ry, and lung cancer mortality (CD, p. 7-128) in all year analyses. However, in the summer season, ma rginally significant
associations were observed for cardiopulmonary mortality. The Adventist Health and Smog (AHSMOG) co hort includes about 6,000 adults living in
California. In two studi es from this cohort, a significant a ssociation has been reported between long-term O 3 exposure and increased risk of lung cancer mortality among males only (Beeson et al., 1998; Abbey et al., 1999). No significant associations were reported between long-term O 3 exposure and mortality from all ca uses or cardiopulmonary causes. Due to the small numbers of lung cancer deaths (12 for males, 18 for females) and the precision of the effect estimate (i.e., the wide confidence intervals), the CD raised con cerns about the plausibi lity of the reported association with lung cancer (CD, p. 7-130).
The U.S. Veterans Cohort study (Lipfert et al., 20 00b, 2003) of approximately 50,000 middle-aged males diagnosed with hypertension, reported some positive associations between mortality and peak O 3 exposures (95 th percentile level for severa l years of data). The study included numerous analyses us ing subsets of exposure and mort ality follow-up periods which spanned the years 1960 to 1996. In the resu lts of analyses using deaths and O 3 exposure estimates concurrently across the study period, there were positive, sta tistically significant associations between peak O 3 and mortality, with a 9.4% excess risk ( 95% CI: 0.4, 18.4) per mean 95% percentile O 3 (CD, p. 7-129). Thus, the results from all-year analyses in the Harvard Six C ities and ACS cohorts provide no evidence for associ ations between long-term O 3 exposure and mortality, though the
warm-season results in the rean alysis of the ACS cohort study suggest a potential association. Imprecise and inconclusive asso ciations were reported in analyses for the AHSMOG cohort study. Significant associa tions between long-term O 3 exposure and mortality were only reported for the Veterans cohort study; however, this study used an indicator of peak O 3 concentrations
and the cohort is also a rath er specific subgroup of the U.S. population. Overall, the CD
concludes that consistent associations ha ve not been reported between long-term O 3 exposure and all-cause, cardiopulmonary or l ung cancer mortality (CD, p. 7-130).3- 36 3.3.3 Ozone Effects on UV-B Flux The CD (Chapter 10) provide s a thorough analysis of the current understanding of the relationship between reducing tropospheric O 3 concentrations and the potential impact these reductions might have on increasing UV-B surface fl uxes and indirectly contributing to increased
UV-B related health effects. It is clear that there ar e many factors that influence UV-B radiation penetration to the earth’s surf ace, including cloud cover, surface albedo, PM concentration and composition, and gas phase pollu tion. A risk assessment of UV-B related health effects would
need to take into account human ha bits, such as outdoor activities, dress and skin care. However,
little is known about th e impact of these factors on indivi dual exposure to UV-B, and detailed information does not exist regarding type (e .g., peak or cumulative ) and time period (e.g., childhood, lifetime, current) of e xposure, wavelength dependency of biological responses, and interindividual variability in UV-B resistance. In fact there have been recent reports indicating the necessity of UV-B in produci ng vitamin D, suggesting that in creased risks of human disease due to slight excess UV-B expos ure may be offset by the bene fits of enhanced vitamin D production. However, as with ot her impacts of UV-B on human healt h, this beneficial effect of
UV-B radiation has not been studied in sufficient deta il to allow for a credib le health benefits or risk assessment. The CD (p. 10-38) concluded that the effect s of changes in surface-level O 3 concentrations on UV-induced heal th effects cannot be critically assessed given the significant
uncertainties summarized above.

3.3.4 Summary The CD (Chapters 4-8) summarizes and asse sses substantial new evidence which builds upon what was previously known a bout the health effects of O 3 . The new information supports previous findings that short-term O 3 is associated with lung func tion decrements and respiratory symptoms, as well as numerous more subtle effects on the respiratory system such as morphological changes and al tered host defense mech anisms. Short-term O 3 exposure has also been associated with hospital admissions for respiratory causes in numerous new studies that further confirm the findings eval uated in the 1996 CD. The CD reports that warm-season studies show evidence for posi tive and robust associatio ns between ambient O 3 concentrations and respiratory hospital admissions, asthma ED visits, and respirat ory symptoms and lung function
effects in asthmatic chil dren (CD, p. 7-175). Some new studies have suggested associations between increased inci dence of asthma or reduced lung function and long-term exposure to elevated ambient O 3 levels. The findings of this small group of studies are in consistent, however, and the CD co ncludes that the evidence for this group of associations is inconclusive (CD, p. 7-175).3- 37 A new body of studies has suggested associations between short-term O 3 exposure and effects on the cardiovascular sy stem, including changes in he art rate variability, cardiac arrhythmia, incidence of MI and hospitalization for cardiovascular diseases. The CD finds this body of evidence to be limited but supportive of potentia l effects of O 3 on the cardiovascular system (CD, p. 8-77). A major area where new information presente d in the CD has signifi cantly expanded our knowledge on health effects is evid ence of an elevated risk of mortality associated with acute exposure to O 3 , especially in the summer or warm season when O 3 levels are typically high. Results from recent large U.S. multicity time- series studies and meta -analyses provide the strongest evidence for associa tions between short-term O 3 exposure and mortality (CD, p. 7- 175). The risk estimates shown are consistent across studies and robust to control for potential
confounders. This overa ll body of evidence is hi ghly suggestive that O 3 directly or indirectly contributes to nonaccidental and cardiopulmonary-r elated mortality, but additional research is needed to more fully establish underlying mech anisms by which such effects occur (CD, p. 8- 78).

3.4 ASSESSMENT OF EVIDENCE FROM EPIDEMIOLOGICAL STUDIES In Chapter 8, the CD assesses the new health evidence, integrating findings from experimental (e.g., toxicological, dosimetri c and controlled human exposure) and epidemiological studies, to make judgments about the extent to which caus al inferences can be
made about observed associations betwee n health endpoints and exposure to O 3 . Section 8.4.4.3
of the CD in dicates that strength of the O 3 effects (including the ma gnitude and precision of reported O 3 effect estimates and thei r statistical significance), robustness of epidemiological associations (i.e., stability in the effect estim ates after considering a number of factors), and consistency of effects associations (looking across re sults of multiple- and single-city studies conducted by different i nvestigators in different places and times) are a ll important in forming judgments as to the likely caus al significance of observed a ssociations (CD, p. 8-40). In evaluating the evidence from epidemiological studies in sections 7.1.3 and 8.4.4.3, the
CD focuses on well-r ecognized criteria, in cluding: (1) the strength of reported associations, including the magnitude and precision of repor ted effect estimates and their statistical significance; (2) the robustness of reported associations, or stabili ty in the effect estimates after considering factors such as a lternative models and model spec ification, potential confounding by co-pollutants, and issues relate d to the consequences of exposur e measurement erro r; and (3) the consistency of the effects asso ciations as observed by looking across results of multiple- and single-city studies conducted by different investigator s in different places and times (CD, p. 8- 40). Integrating more broadly across epidemiolo gical and experimental evidence, the CD also3- 38 focuses on the coherence and plausibility of observed O 3 -related health ef fects to reach judgments about causality (CD, section 8.6). Subsequent to the final CD being published, CASAC sent a letter to the Administrator (Henderson, 2006b) providing ad ditional advice on some key i ssues in order to inform specifically the preparat ion of this draft Staff Paper speci fically and the re view of the O 3 NAAQS in general. The issues re lated to assessment of epidemio logical studies are addressed in
this section and include the general issue of the utility of tim e-series epidemiol ogical studies in assessing the risks from exposure to O 3 and other criteria pollutants, as well as related issues about exposure measur ement error in O 3 mortality time-series studies and O 3 as a surrogate for the broader mix of photochemical ox idant pollution in time-series stud ies. Implications of these issues for staff conclusions about the adequacy of the current O 3 NAAQS and the identification of options for consideration w ill be considered in Chapter 6. The following discussion su mmarizes the conclusions and judgments from the CD’s summary of epidemiologic evidence and integrative assessment, focusing in particular on discussions of strength, robustness, and consistency in the epidemiological evidence; judgments
in the CD about coherence and plausibility are summarized belo w in section 3.5. This section
also addresses issues relate d to lag periods between O 3 ambient exposure levels and health outcomes, the nature of O 3 -health effect concentration-respon se relationships, and the assessment of air pollutant mi xtures containing O 3 in time-series epidemiological studies.

3.4.1 Strength of Associations The strength of associ ations most directly refers to th e magnitude of the reported relative risk estimates. Taking a broader view, the CD draws upon the criteria summarized in a recent report from the U.S. Surgeon General, which define strength of an associa tion as “the magnitude
of the association and its statistical strength” which includes assessment of both effect estimate size and precision, which is related to the statis tical power of the study (C DC, 2004). In general, when associations are strong in te rms of yielding large relative risk estimates, it is less likely that the association could be completely accounted for by a potential confounder or some other source of bias (CDC, 2004). Wi th associations that yield sma ll relative risk estimates it is especially important to consider potential confounding and other factors in assessing causality.
Effect estimates between O 3 and many health outcomes are generally small in size and
could thus be characterized as weak. For example, effect estimates for associations with mortality generally range from 0.5 to 5% incr eases per 40 ppb increase in 1-hr max O 3 or equivalent, whereas associations for hospitalization range up to 50% increases per standardized

O 3 increment. The CD particularly notes that th ere are several multicity studies for associations
between short-term O 3 exposure and mortality or morbidity that, although small in size, have3- 39 great precision due to the statistical power of the studies (CD, p.8-40). That is, the associations were strong enough to have been reliably meas ured by the studies su ch that many of the associations can be distingui shed from the null hypothesis with statistical confidence.

3.4.2 Robustness of Associations Factors considered in assessing robustness include impact of e xposure error, potential confounding by copollutants, and al ternative models and model sp ecifications, as evaluated in the CD (sections 7.1.3 and 8.4.4.3) and discussed below.

3.4.2.1 Exposure Error In time-series epidemiologic studies, con centrations measured at centrally-located ambient monitoring stations are generally used to represent a community’s exposure to ambient

O 3 . For time-series studies and pa nel studies that use these ambient concentrations, the emphasis is on the temporal (e.g., daily or hourly) changes in ambient O 3 . In other cohort or crosssectional studies, air quality data averaged over a period of months to years are used as indicators of a community’s long-term exposure to ambient O 3 and other pollutants. In both types of analyses, exposure error is an im portant consideration, as actual exposures to individuals in the population will vary across the community. In considering exposure error, it should be noted that total person al exposure can be partitioned into two types of sources, ambient an d nonambient. As described in the CD, there
are few sources of O 3 exposure for most people other than ambient air; potential indoor sources
of O 3 include office equipment, air cleaners, and small el ectric motors (CD, p. 7-6). Sheppard (2005) notes that nonambient so urce exposures typically vary across individuals, but the community averages do not vary across communiti es. In addition, nonambi ent exposures are not likely to have strong temporal correlations. In contrast, ambient concentrations across individuals should be highly corr elated, as they tend to vary ov er time similarly for everyone because of changes in source generation, weather, and season. The independence of ambient and non-ambient exposure sources has important implicat ions. Sheppard et al . (2005) observes that
when ambient and nonambient sour ces are independent, exposure variation due to nonambient source exposures behaves like Berk son measurement error and does not bias the effect estimates.
Ozone concentrations measured at central am bient monitoring sites may explain, at least partially, the variance in indivi dual exposures to ambient O 3 ; however, this relationship is influenced by various factors re lated to building ventilation practic es and personal behaviors. Further, the pattern of exposur e misclassification error and th e influence of confounders may
differ across the outcomes of intere st as well as in susceptible popu lations. As discussed in the CD Section 3.9, only a limited num ber of studies have examin ed the relationship between
ambient O 3 concentrations and person al exposures to ambient O 3 . One of the strongest3- 40 predictors of the relationship between ambient concentrations a nd personal exposur es appears to be time spent outdoors. The str ongest relationships were observe d in outdoor workers (Brauer and Brook, 1995, 1997; O’Neill et al., 2003). For example, Br auer and Brook (1995, 1997)
observed that in farmers who worked 6-14 hour s outdoors each day, the pe rsonal to ambient O 3 concentration ratio was 0.96, with a Spearman correlation coeffi cient of 0.64. Statistically significant correlations between ambient concentrations and pe rsonal exposures were also observed for children, who likely spend more time outdoors in th e warm season (Linn et al., 1996; Xue et al., 2005).
There is some concern abou t the extent to which am bient concentrations are representative of personal O 3 exposures of another particularly susceptible group of individuals, the debilitated elderly, and what impact that may have on mort ality and hospitalization timeseries studies. Those who suff er from chronic cardiovascular or respiratory conditions may tend to protect themselves more from environmenta l threats by reducing th eir exposure to both O 3 and its confounders, such as high te mperature and PM, than those w ho are healthy. The correlation between ambient concentrations and personal expo sure measurements in older adults (mean age 75 years) has been examined by Sa rnat et al. (2001, 2005). These studies by Sarnat et al. also
included children and COPD patients, and only results fo r the combined populations are reported. The first study conduct ed in Baltimore, MD observed no relationship between ambient concentrations and personal exposures in both the summer and the winter. However, the second study conducted in Boston, MA, f ound statistically signi ficant associations between ambient O 3 concentrations and personal exposures to O 3 . The regression coeffici ent was larger in the summer ( β = 0.27), compared to the winter ( β = 0.04), suggesting once again that time spent outdoors had a large influence on th e relationship between ambient concentrations and personal exposures. Eight of 29 subj ects had personal-ambient O 3 correlations greate r than 0.8 during the

summer. Collectively, these studies observed that the daily averaged personal O 3 exposures from the population were well co rrelated with ambient O 3 concentrations desp ite the substantial variability that existed among the personal meas urements. Averaging likely removes the noise
associated with other sources of variation. These studies provide s upportive evidence that
ambient O 3 concentrations from centra l monitors may serve as va lid surrogate measures for mean personal exposures expe rienced by the population, which is of most relevance for timeseries studies. A better unders tanding of the relationship betw een ambient concentrations and personal exposures, as well as of the other f actors that affect relationship will improve the interpretation of concentrat ion-population health response as sociations observed. The CD discusses the potent ial influence of exposure erro r on epidemiologic study results in Section 7.1.3.1. Zeger et al. (2000) outlined the three components to exposure measurement3- 41 error: (1) the use of average popu lation rather than individual exposure data; (2) the difference between average personal ambient exposure and ambient concentrations at central monitoring sites; and (3) the difference between true and measured ambient concentr ations (CD, p. 7-7). These components are expected to have different effects, with the fi rst and third likely not causing bias in a particular di rection (“nondifferential error”) but increasing the standard error, while the second component may result in downwar d bias, or attenuation of the risk estimate (CD, pp. 7-7 to 7-8). Ambient exposure can be assumed to be the product of the ambient
concentration and an attenuation factor (i.e., building filter). Panel studies and time-series
studies that use ambient concentrations instead of personal exposure m easurements will estimate
a health risk that is attenuated by that factor . Navidi et al. (1999) us ed data from a children’s cohort study to compare effect estimates from a simulated “true” exposure level to results of analyses from O 3 exposures determined by several methods. The results indicate d that the use of

O 3 exposures from personal sampling or microenvi ronmental approaches is associated with
nondifferential error in O 3 effect estimates, compared with effect estimates from “true” exposures. However, O 3 exposures based on the use of ambi ent monitoring data overestimates
the individual’s O 3 exposure and thus ge nerally results in O 3 effect estimates that are biased downward (CD, p. 7-8). Similarly, Zidek (1997) observed th at a statistical anal ysis must balance bias and imprecision (error varian ce). For example, in a reanalys is of a study by Burnett et al. (1994) on the acute respiratory effe cts of ambient air pollution, Zide k et al. (1998) reported that accounting for measurement, as well as making a few additional chan ges to the analysis, resulted in qualitatively similar conclusi ons, but the effects estimates we re considerably larger in magnitude (CD, p. 7-8). A simulation study by Sheppard et al. (2005) also considered at tenuation of the risk based on personal behavior, their microen vironment, and the qualities of the pollutant in time-series studies. Of particular interest is their finding that significant variation in nonambient exposure or in ambient source exposur e that is independent of ambient concentration doe s not furthe r bias the effect estimate. In other words, risk estimates were not further attenuated in time-series studies
even when the correlations betw een personal exposures and ambient concentrations were weak.
In addition to overestimation of exposure and the resulting u nderestimation of effects, the
use of ambient O 3 concentrations may obscure the pres ence of thresholds in epidemiologic studies (CD p. 7-9). Brauer et al. (2002) concluded that surroga te measures of exposure, such as those from centrally located ambi ent monitors, that were not hi ghly correlated with personal exposures obscured the presence of thresholds in epidemiologic studies at the population level,
even if a common threshold exists fo r individuals with in the population. Existing epidemiologic models may not fully take into consideration all of the biologically relevant exposure history or reflect the complexi ties of all of the underlying3- 42 biological processes. As disc ussed in the CD, Section 3.9, usin g ambient concentrations to determine exposure generally ov erestimates true personal O 3 exposures by approximately 2- to 4-fold in available studies, resu lting in attenuated risk estimates . The implicati on is that the effects being estimated occur at fairly low exposures and the potency of O 3 is greater than these
effects estimates indicate. As very few studies evaluating O 3 health effects with personal O 3 exposure measurements exist in the literature , effect estimates determined from ambient O 3 concentrations must be evalua ted and used with caution to assess the health risks of O 3 . Until more data on personal O 3 exposure becomes available, the us e of routinely monitored ambient

O 3 concentrations as a surrogate for personal exposures is not ge nerally expected to change the principal conclusions from O 3 epidemiologic studies. Therefor e, population health risk estimates derived using ambient O 3 levels from currently available obs ervational studies, with appropriate caveats about personal exposure considerations, remain useful.
The CD recommends caution in th e quantitative use of effect estimates calculated using
ambient O 3 concentrations as they may lead to underestimation of the potency of O 3 . However, staff observes that the use of these risk estimates for comparing relative risk reductions between
alternative ambient O 3 standards considered in the risk as sessment is less likely to suffer from
this concern. In addi tion, as discussed in Chapter 5, staf f has conducted an exposure assessment in conjunction with a portion of the health risk assessment that incorporates estimated population exposures in developing risk estimates for hea lth outcomes based on controlled human exposure
studies.

3.4.2.2 Confounding by Copollutants Confounding occurs when a health effect that is caused by one risk factor is attributed to
another variable that is correlated with the causal risk factor; epidemiologi cal analyses attempt to adjust or control for potential conf ounders. Copollutants (e.g., PM, CO, SO 2 and NO 2 ) can meet the criteria for poten tial confounding in O 3 -health associations if they are potential risk factors
for the health effect under st udy and are correlated with O 3 . Effect modifier s include variables that may influence the he alth response to the poll utant exposure (e.g., co-p ollutants, individual susceptibility, smoking or age). Both are important considerati ons for evaluating effects in a mixture of pollutants, but for confounding, the emphasis is on controlling or adjusting for potential confounders in estimating the effects of one pollutant, wh ile the emphasis for effect modification is on identifying and assessi ng the effects for different modifiers.
The CD observes that O 3 is generally not highly correlated with other criteria pollutants (e.g., PM 10 , CO, SO 2 and NO 2 ), but may be more highly correlated with secondary fine particles, especially during the summer months (CD, p. 7- 148). In addition, the correlation between O 3 and other pollutants may va ry across seasons, since O 3 concentrations are ge nerally higher in the3- 43 summer months. For example, positive associations are observed between O 3 and pollutants such as fine particles during the warmer months, but negati ve correlations may be observed
between O 3 and these pollutants during the cooler mont hs (CD, p. 7-17). Thus, the CD pays particular attention to the result s of season-specific an alyses and studies that assess effects of PM in potential confounding of O 3 -health relationships in it s discussions in section 7.6.4. Multipollutant models are commonly us ed to assess potential confounding in epidemiological studies. As disc ussed in the CD, the limitations to the use of multipollutant
models include the diffic ulty in interpreting results where th e copollutants are hi ghly colinear, or where correlations between polluta nts change by season (CD, p. 7-150) . This is particularly the
situation where O 3 and a copollutant, such as sulfates, are formed under the same atmospheric condition; in such cas es multipollutant models would produ ce unstable and possibly misleading results (CD, p. 7-152). For mortality, the results fro m numerous multi-city and single- city studies are shown in Figure 7-22 of the CD. These result s indicate that O 3 -mortality associations do not appear to be substantially changed in multi pollutant models including PM 10 or PM 2.5 (CD, p. 7-101). Focusing on results of warm season analyses, Fi gure 7-23 of the CD show s effect estimates for

O 3 -mortality associations that are fairly robust to adjustment for PM in multipollutant models (CD, p. 7-102). In general, ba sed on results from several single - and multiple-city studies, and on recent meta-analyses, the CD (p. 7-103) concludes that “copollu tants generally do not appear to substantially confound the association between O 3 and mortality.” Similarly, multipollutant models are presen ted for associations between short-term O 3 exposures and respiratory hospitalization in Fi gure 7-12 of the CD; th e CD concludes that copollutants generally do not c onfound the relationship between O 3 and respiratory hospitalization (CD, p. 7-79 to 7-80). Multipollu tant models were not used as commonly in studies of relationships between respir atory symptoms or lung function with O 3 , but the CD reports that results of available analyses indicate that such associ ations generally were robust to adjustment for PM 2.5 (CD, p. 7-154). For various co-polluta nt models, in a large multicity study of asthmatic children (Mor timer et al., 2002), the O 3 effect was attenuated , but there was still a positive association. In Gent et al. (2003), effects of O 3 , but not PM 2.5 , remained statistically significant and even increased in magnitude in two-pollutant models (CD, p. 7-53). Considering this body of studi es, the CD concludes: “Multi pollultant regression analyses
indicated that O 3 risk estimates, in general, were not se nsitive to the inclus ion of copollutants, including PM 2.5 and sulfate. These results suggest that the effects of O 3 on respiratory health outcomes appear to be robust and independent of the effects of other copollutants (CD, p. 7- 154).” We use the result s of single-pollutant model results in presentation of results in this chapter and in quantitative risk assessments conducted as part of this review (see Chapter 5) for3- 44 purposes of comparing results from different studies. However, we also include the use of multipollutant model results in pres enting risk estimates, when av ailable, to more completely characterize the quantitative health risks associated with ambient O 3 levels

.

3.4.2.3 Model Specification

The CD observes that one challenge of time-series epidem iological analysis is assessing the relationship between O 3 and health outcomes while a voiding bias due to confounding by other time-varying factors, particularly seasonal trends and weather variables (CD, p. 7-14). These variables are of par ticular interest because O 3 concentrations have a well-characterized seasonal pattern (see Chapter 2) and are also highly correlated with changes in temperature.
Thus it can be difficult to distinguish whether effe cts are associ ated with O 3 or with seasonal or weather variables in statistical analyses.
Section 7.1.3.4 of the CD discus ses statistical modeling approa ches that have been used to adjust for time-varying factors, highlighting a series of analys es that were done in a Health
Effects Institute-funded reanalysis of numerous time-series studies. While the focus of these reanalyses was on associations wi th PM, a number of investigator s also examined the sensitivity
of O 3 coefficients to the extent of adjustment fo r temporal trends and weather factors. In addition, several recent studies, including U.S. mu lti-city studies (Bell et al., 2005; Huang et al., 2005; Schwartz et al., 2005) and a meta-analysis study (Ito et al., 2005), evaluated the effect of model specification on O 3 -mortality associations. As discus sed in the CD (s ection 7.6.3.1), these studies generally report that associations reported with O 3 are not substantially changed with alternative modeling strategi es for adjusting for temporal trends and meteorologic effects. In the meta-analysis by Ito et al. (2005), a separate multicity analysis was presented that found that alternative adjustments for weather resulted in up to 2-fold difference in the O 3 effect estimate. However, significant confounding can occur when strong seasonal cy cles are present, suggesting that season-specific results are more generally robust than ye ar-round results in such cases. The CD concludes that “seasonal dependence of O 3 -mortality effects compli cates interpretation of O 3 risk estimates calculated from year-round data wit hout adequate adjustment of temporal trends” (CD, p. 7-99), and that more work is needed in this area to reduc e the uncertainty involved in the epidemiologic interpretation of O 3 effect estimates (CD, p. 7-141). A number of epidemiologica l studies have conducted s eason-specific analyses, as
discussed in section 7.6.3.2 of th e CD. As observed above in section 3.3, such studies have generally reported stronger and more precise effect estimates for O 3 associations in the warm season than in analyses conducted in the cool seasons or over the full year. For assessing relationships between O 3 and health outcomes, the CD highl ights several reasons to focus on warm season analyses: (1) the seasonal nature of O 3 concentrations; (2) the relationship between3- 45 O 3 formation and temperat ure; (3) correlations between other pollutants, particularly fine particles, and O 3 variations across seasons in some areas; and (4) fact ors affecting exposure to
ambient O 3 , such as air conditioning use, varies seasonally in most areas of the U.S.. We have therefore focused on epidemiologi cal findings from warm season an alyses, where available, for qualitative assessments and for the quantitative risk assessm ent discussed in Chapter 5.

3.4.3 Consistency Consistency refers to the persistent finding of an asso ciation between exposure and outcome in multiple stud ies of adequate power in differen t persons, places, circumstances and times (CDC, 2004). In consideri ng results from multicity studie s and single-city studies in different areas, the CD observes general consistency in effects of short-term O 3 exposure on mortality, respiratory hospitaliza tion and other respiratory health outcomes (CD, p. 8-41). The
variations in effects that are observed may be attributable to differences in relative personal exposure to O 3 , as well as varying concentrations a nd composition of copo llutants present in different regions. Thus, the CD concludes that “consideration of consistency or heterogeneity of effects is appropriately understood as an evaluati on of the similarity or general conc ordance of results, rather than an expecta tion of finding quantitativ e results with a very narrow range” (CD, p.8-41).

3.4.4 Lag Structure in Short-term Exposure Studies In the short-term exposure epidemiological studies, many investigators have tested associations for a range of lag peri ods between the hea lth outcome and O 3 concentration (see CD, sections 7.1.3.3). The CD obser ves that the selection of an appropriate lag period can depend on the health outcome under study. For ex ample, if cough is resulting from the irritant
action of O 3 , that would be expected to occur with a short lag time; however, exacerbation of asthma through an inflammatory response might oc cur up to several days after initial exposure (CD, p. 7-12). For both mortalit y and respiratory hospital admissi ons, the CD repor ts that most significant associations between O 3 and mortality were observed with O 3 measured on the same day or a 1-day lag period in studi es using individual lag periods (C D, p. 7-14). In U.S. multi-city studies, larger effect estimate sizes were reported for the O 3 -mortality relationship with the distributed lag structure (CD, p. 7-88). Field studies of lung f unction or respiratory symptoms reported associations with O 3 across a range of lag periods fro m exposure on the same day to exposures averaged over severa l days (CD, sections 7.2.3 and 7.2.4). Cardiovascular effects appeared to be a ssociated with O 3 at shorter lag periods; cardiovasc ular health outcomes such as changes in cardiac autonomic control were associated with O 3 measured on the same day (CD, section 7.2.7.1). In addition, Pete rs et al. (2001) reported a positive but not statistically3- 46 significant association between m yocardial infarction onset and O 3 with very short lag times of 1- to 4 hr (CD, p. 7-64). In focusing on an effect estimate reported for any individual lag period, the CD observes that it is important to consider th e pattern of results across the series of lag periods. If there is an apparent pattern of results across the different la gs, then selecting the si ngle-day lag with the largest effect from a series of positive associatio ns is still likely to underestimate the overall effect size, since single-day la g effect estimates do not fully capture the risk that may be distributed over adjacent or other days (CD, p. 7- 13). However, if the re ported effect estimates vary substantially across lag peri ods, any result for a single da y may well be biased (CD, p. 7- 14). If the effect of O 3 on health outcomes persists over several days, distributed lag model results may provide more accurate effect estimates for quant itative assessment than an effect estimate for a single lag period (CD, p. 7-12). Conversely, if the underlying O 3 -health relationship is truly an acute ef fect, then a distributed lag mode l would likely result in a reduced effect estimate size that may under estimate the effect (CD, p. 7-12). On this basis, the CD focuses on effect estimates from models using 0- or 1-day lag periods, with some considera tion of multi-day lag effects (C D, p. 7-14). For quantitative assessments, we conclude that it is appropriate to use results from lag peri od analyses consistent with those reported in the CD, focusing on single day lag periods of 0-1 days for associations with mortality or respiratory hos pitalization, depending on availability of resu lts (CD, p. 7-14). When available, distributed lag model results also have been used in the quantitative risk assessment. However, for those few studies that show inconsistent patte rns, the use of singleday lag results is not appr opriate for inclusion in th e quantitative assessment.

3.4.5 Concentration-Response Relation ships and Potential Thresholds It has been recognized that it is reasonable to expect that there likely are biological
thresholds for different health ef fects in individuals or groups of individuals with similar innate
characteristics and heal th status. For O 3 exposure, individual threshol ds would presumably vary substantially from person to person due to indivi dual differences in ge netic susceptibility, preexisting disease conditions and possi bly individual risk factors such as diet or exercise levels (and could even vary from one time to another for a give n person). Thus, it would be difficult to
detect a distinct threshold at the population level, below which no individual would experience a given effect, especially if some members of a population are u nusually sensitive even down to very low concentrations (U.S. EPA, 2004, p. 9-43, 9-44).
Some studies have tested associations between O 3 and health outcomes after removal of days with higher O 3 levels from the data set; such analys es do not necess arily indicate the presence or absence of a thresh old, but provide some informati on on whether the relationship is3- 47 found using only lower-concentration data. For exam ple, using data from 95 U.S. cities, Bell et al. (2004) found that the eff ect estimate for an associa tion between short-term O 3 exposure and mortality was little changed when days exceeding 60 ppb (24-hr average) were excluded in the analysis. Bell et al. ( 2006) found no difference in estimated effect even when all days with 24-hr

O 3 concentrations <20 ppb were excluded (CD, p. 8-43). Usi ng data from 8 U.S. cities, Mortimer and colleagues (2002) also re ported that associations between O 3 and both lung function and respiratory symptoms remained statis tically significant and of the same or greater magnitude in effect size when concentrations greater than 80 ppb (8-hr avg) were excluded (CD, p. 7-46). Several single-city studi es are also summarized in sec tion 7.6.5 of the CD that report similar findings of associations that remain or are increased in magnitude and statistical significance when data at th e upper end of the concentr ation range are removed. Other time-series epidemiologi cal studies have used statis tical modeling approaches to
evaluate whether thresholds exist in associations betw een short-term O 3 exposure and mortality.
As discussed in section 7.6.5 of the CD, one European multi-city study incl uded evaluation of the shape of the concentration-response curve, and observed no deviati on from a linear function across the range of O 3 measurements from the study (Gry paris et al., 2004; CD p. 7-154). Several single-city studies al so observed a monotoni c increase in asso ciations between O 3 and morbidity that suggest that no population threshold exists (CD, p. 7-159). On the other hand, a study in Korea used several differ ent modeling approaches and reported that a threshold model provided the best fit for the da ta. The results suggested a potential threshold level of about 45 ppb (1-hr ma ximum concentration; < 35 ppb, 8-hr avg) for
an association between mo rtality and short-term O 3 exposure during the su mmer months (Kim et al., 2004; CD, p. 8-43). The authors reported larger effect estimates for the association for data above the potential threshold level, suggesting that an O 3 -mortality association might be
underestimated in the non-threshold model. A th reshold analysis recently reported by Bell et al. (2006) for 98 U.S. communities , including the same 95 communiti es in Bell et al. (2004), indicated that if a population th reshold existed for mortality, it would likely fall below a 24-h average O 3 concentration of 15 ppb (< 25 ppb, 8-hr avg) . In addition, Burnett and colleagues (1997) plotted the relationships between air pollutant concentra tions and both respiratory and cardiovascular hospitalization, and it appears in these results that the a ssociations with O 3 are found in the concentration rang e above about 30 ppb (1-hr maximu m; < 25 ppb, 8-hr avg). Vedal and colleagues (2003) reported a significant asso ciation between O 3 and mortality
in British Columbia where O 3 concentrations were quite low (mean concentrati on of 27.3 ppb). The authors did not specifi cally test for threshold levels, but the fact th at the association was
found in an area with such low O 3 concentrations suggests that any potential threshold level would be quite low in this data set.3- 48 In summary, the CD finds that, taken togeth er, the available evidence from clinical and epidemiological studies suggests that no clear conclusion can now be reached with regard to possible threshold levels for O 3 -related effects (CD, p. 8-44). We also recognize that the available epidemiological evidence neither supports nor re futes the existence of thresholds at the population level for effects such as increased hospital admiss ions and premature mortality. There are limitations in epidemiologi cal studies that make discerni ng thresholds in populations difficult, including low data dens ity in the lower concentration ra nges, the possible influence of exposure measurement error, and interindivid ual differences in susceptibility to O 3 -related effects in populations. We rec ognize, however, the possibility th at thresholds for individuals may exist in reported associations at fairly low levels within the range of air quality observed in
the studies but not be detectable as population thresholds in ep idemiological analyses. Based on the CD’s conclusions, we judge that there is insufficient ev idence to support use of potential threshold levels in quantitative risk assessments a nd that it is appropriate to estimate risks within the range of air quality concentrations down to estimated po licy-relevant background level.



### 3.4.6 Health Effects of Pollutan t Mixtures Containing O 3 The potential for O 3 -related enhancements of PM fo rmation, particle uptake, and
exacerbation of PM-induced cardiovascular effect s underscores the importance of considering
contributions of O 3 interactions with other often co-occurri ng air pollutants to health effects due

to O 3 -containing pollutant mixes. Chapters 4, 5, and 6 of the CD provide a discussion of experimental studies that ev aluate interactions of O 3 with other co-occurring pollutants. Some examples of important polluta nt mixture effects noted th ere are highlighted below. In Chapter 4, the CD noted some important interactive effects of coexposures to O 3 , and

NO 2 and SO 2 , two other common gaseous copollutants f ound in ambient air mixes. A study by Rigas et al. (1997) showed th at continuous exposure of healthy human adults to SO 2 or to NO 2 increased inhaled bolus O 3 absorption, while conti nuous exposure to O 3 alone decreased bolus absorption of O 3 . This suggests enhancement of O 3 uptake by NO 2 or SO 2 coexposure in ambient air mixes. Another study by Jenk ins et al. (1999) s howed that asthmatics exhibited enhanced airway responsiveness to house dust mite following exposures to O 3 , NO 2 , and the combination of the two gases (CD, Chapter 6). Spirometric responses, however, were impaired only by O 3 and O 3 +NO 2 at higher concentrations. On the ot her hand, animal toxicology studies (CD, Chapter 5) that eval uated exposures to O 3 in mixture with NO 2 , formaldehyde, and PM demonstrated additive, synergistic or antagonist ic effects, depending on the exposure regimen and the specific heal th endpoints evaluated. Several studies have demonstrated the enhancement by O 3 exposure of various respiratory responses of sensitive in dividuals to allergens. For exam ple, Peden et al. (1995) showed O 3 -3- 49 induced increased response to nasal allergen ch allenge among allergic asthmatic subjects, and Michelson et al. (1999) s howed promotion by 0.4 ppm O 3 exposure of inflammatory cell influx in response to nasal allergen challenge in as ymptomatic dust-mite sensitive asthmatics. In addition, Jörres et al. (1996) dem onstrated enhancement by 0.25 ppm O 3 exposure of airway responsiveness in mildly allergic asthmatics that was increased in respons e to an individual’s historical allergen (grass and bi rch pollen, house dust mite, animal dander). These results were further extended by Holz et al. (2002) who showed that repeat ed daily exposure to 0.125 ppm O 3 for 4 days exacerbated lung function decrements (e.g., decreased FEV 1 ) in response to bronchial allergen challenges among subjects with preexisting allergic airw ay disease, with or without asthma (see Chapter 6 of the CD). This suggests that O 3 exposure can place allergic people who do not have asthma, as well as people who do have asthma, at increased risk for allergic respiratory effects. Consiste nt with and supporting the above findings ar e animal toxicology studies reviewed in detail by Harkema and Wagner (2005), which indicate that (a) O 3 -induced epithelial and inflammatory responses in labo ratory rodents are ma rkedly enhanced by coexposure to inhaled biogenic substances (e.g., bacterial endotoxi n or ovalbumin, an experimental aeroallergen) and (b) adverse airw ay effects of biogenic substances can be exacerbated by coexposure to O 3
. Also of much note is a newly emergi ng literature which indicates that O 3 can modify the biological potency of certain ty pes of ambient PM, as shown by experimental tests. For example, as described in the CD, Section 5.4.2, the reaction of diesel PM with 0.1 ppm O 3 for 48 hr increased the potency (com pared to non-exposed or air-ex posed diesel PM) to induce neutrophil influx, total protein, a nd LDH in lung lavage fluid in response to intratracheal PM instillation in rats (Madden et al., 2000). However, the potency of carbon black particles was not enhanced by exposure to O 3 , suggesting that O 3 reaction with organic co mponents of the diesel PM were responsible for the observe d increased diesel PM effects.
Potential interaction of O 3 with fine PM in aged rats wa s examined by Kleinman et al. (2000). In this study the effects of fine PM containing two comm on toxic constituents,
ammonium bisulfate (ABS, 0.3 μm 70 μg/m 3 ) and elemental carbon (C, 0.3 μm 50 μg/m 3 ) and a mixture (ABS + C) with 0.2 ppm O 3 was evaluated on aged rat l ung structure and macrophage function. Exposures of O 3 , elemental carbon or ABS alone did not cause significant lung injury, lung tissue collagen content or re spiratory burst activity. On the other hand, mixtures (ABS + C

+ O 3 ) caused significant lung injury as assessed by increased cell pr oliferation response in lung epithelial and interstitial cells, loss of lung tissue collagen and in crease in respiratory burst and phagocytic activity. The majority of toxicological studies discussed in the CD evaluated effe cts of individual pollutants or simple mixtures of the constituents of urban smog mixtur es, and these toxicology3- 50 studies may not fully explain epidemiologic fi ndings that have increasingly shown ambient O 3 , other gaseous pollutants, an d/or PM to be associated with vari ous health effects at relatively low
concentrations. In a recent report, Sexton et al. (2004) utilized “smog ch ambers”, i.e., environmental irradiation chambers to genera te synthetic photoche mical oxidants mixtures similar to urban smog, and studied the toxicity of such mixtures on the inflammatory response of A549 cells in an in vitro expos ure system. In this prelimin ary study, the aut hors found the simulated urban photochemical oxidant mi xture generated with the addition of O 3 to have enhanced toxicity (as assessed by the expression of IL-8 mR NA). Additional toxicology studies using similar realistic air polluti on smog mixtures in the future may provide more relevant biological understanding for the potential intera ctions that occur in the ambient air among various pollutants. The body of epidemiologica l studies discussed in this Sta ff Paper emphasizes the role of

O 3 acting autonomously, from a stat istical sense, in associatio n with a variety of adverse respiratory and cardiovascular effect s. Despite a variety of plau sible mechanisms, there exists a general consensus suggesting that O 3 , either directly or through initiation, interferes with basic cellular oxidation processes re sponsible for inflammation, re duced antioxidant capacity,
atherosclerosis and other eff ects. Reasoning that O 3 influences cellular chemistry through basic oxidative properties (as opposed to a unique chem ical interaction), other reactive oxidizing species (ROS) in the atmosphere acting either independently or in combination with O 3 may also
contribute to a number of adverse respiratory and cardiovascular hea lth effects. Consequently,
the role of O 3 should be considered more broadly as O 3 behaves as a gene rator of numerous oxidizing species in the atmosphere. All of the above types of interactive effects of O 3 with other co-occurring gaseous and nongaseous viable and nonviable PM components of ambient air mixes ar gue for not only being
concerned about dir ect effects of O 3 acting alone, but also the need for viewing O 3 as a surrogate indicator for air pollution mixes which may enhance risk of adve rse effects due to O 3 acting in combination with other pollutants. Viewed from this perspective, thos e epidemiologic findings of morbidity and mortality as sociations, w ith ambient O 3 concentrations extending to concentrations below 0.08 ppm, become more understandable and plausible.

3.5 BIOLOGICAL PLAUSIBILITY AND COHERENCE OF EVIDENCE

This section summarizes material containe d in section 8.4.3 and s ection 8.6 of the CD, which integrates epidemiological studies with mechanistic info rmation from controlled human exposure studies and animal toxicolo gical studies to draw conclusi ons regarding th e coherence of evidence and biological plausibility of O 3 -related health effects. For its assessment, the CD’s discussion draws from epidemiol ogical evidence on a range of re levant health endpoints (from3- 51 cardiopulmonary and physiological changes to morbidity and mortality) and assessment of available toxicological and biochemical evidence on potential plausible causal relationships for the observed epidemiological asso ciations (CD, p. 8-45).

3.5.1 Animal-to-Human Extr apolation Issues Table 3-1 (Table 8-1, CD, p. 8-29) su mmarizes physiological and biochemical observations which represent the knowledge base available from studies in humans and animals that support conclusions dr awn about biological altera tions that cause acute O 3 -induced health effects. Table 3-1 was based upon experimental data (contained in CD Chapters 5 and 6, as well as the chapter annexes), which used environm entally relevant exposure regimens. Although
most of the acute O 3 -induced biological alterations are transient a nd attenuate over time, this does not mean that injury at th e cellular and tissue level does not continue. Most inflammatory markers (e.g., PMN influx) attenuat e after 5 days of exposure, but markers of cell damage (e.g., LDH enzyme activity) do not attenu ate and continue to increase. The time-line for resolution of many of the physiological and biol ogical parameters presented in Figure 3-2 (Figure 8-3, CD, p. 8-30) differ for healthy human subjects and those with underly ing cardiopulmona ry diseases.
The CD also notes that alterations in acute O 3 -induced cellular and mo lecular changes observed in human airway epithelium evol ve over time, depicted in Figu re 3-3 (Figure 8-4, CD, p. 8-31), and that the knowledge of this pr ofile is important in assessing bi ological plausibility to integrate across evidence of various health endpoints. The similarities in physiol ogical, biochemical and pathol ogical processes between humans and many animal species are due to the high level of genome sequence homology that exists across species (CD, p. 8-28). It is this homology that supports the use of knowledge gained on initiation, progression, and treatment regimes for dise ase processes across species, especially on the acute O 3 -induced effects in the respiratory tr acts of humans and various animal species, as depicted in CD Table 3-1 and Figu res 3-2 and 3-3. The si milarities observed in human and rat respiratory syst em effects (e.g., in measures of lung function, ventilatory response, host defense), attenu ation, and at higher levels of cellular organization (e.g., neutrophilic inflammation, macroph age phagocytosis processes) lend support to animal-tohuman extrapolation. This is pa rticularly important in collecti ng information that would not be possible to gather in human exposure or epid emiological studies but may corroborate data from both types of studies.Table 3-1. Acute O 3 -induced Physiological and Biochemical Changes in Human and Animals

Physiological/Biochemical Alterations Human Exposure Studies 1,2 Animal Toxicology Studies 3,4

Pulmonary Function: 9 FEV 1 8 Frequency of breathing (rapid, shallow ) 9 FVC (cough, breathing discomfort, throat irritation, wheezing) Mild bronchoconstriction 8 Frequency of breathing (rapid, shallow ) 9 FVC

Airway Responsiveness: 8 (neuronal involvement) Change in lung resistance 8 (vagal mediation) Change in lung resistance

Inflammation: Yes 8 inflammatory mediators Yes 8 inflammatory mediators

Reactive Oxygen Species: 8 8

Host Defense: 8 particle clearance 8 permeability 9 AM phagocytosis 8 particle clearance 8 permeability 9 clearance of bacteria 8 severity of infection 8 mortality & morbidity

Lung Injury: Morphology: Yes Yes

Susceptibility: Age, Interindividual variability Disease status Polymorphism in certain genes being recognized Species-specific differences Genetic basis for susceptibility indicated

Cardiovascular Changes: Im pairment in arterial O 2 transfer Ventilation-perfusion mismatch (suggesting potential arterial vasoconstriction) 8 rate pressure product 5
8 myocardial work 5 Heart rate 9 core body temperature 8 atrial natriuretic factor Role for platelet activity factor (PAF) indicated Increased pulmonary vascular resistance

1 Controlled chamber exposure studies in human volunteers were carried out for a duration of 1 to 6.6 h with O 3 concentration in the range of 0.08-0.40 ppm with intermittent exercise.

2 Data on some of the biochemical parameters were obtained from in v itro studies using cells recovered from BALF.

3 Responses were observed in animal toxicology studies with expos ure for a duration of 2 to 72 h with O 3 concentration in the range of 0.1 to 2.0 ppm.

4 Various species (mice, rat, gui nea pigs and rabbit) and strains.

5 In hypertensive subjects.

3-523-53 Figure 3-2. Resolution time-line for the respiratory, physiological, and biochemical parameters are derived from studies reported in the CD, Chapter 6 and Chapter 6 Annex.3-54 Figure 3-3. Acute (1-8 h) O 3 exposure-induced cellular and molecular changes and timelines for their resolution de picted here are derived from the data reported in Leikauf et al. (1995) and Mudway and Ke lly (2000)3-4.Acute (1-8 h) O 3 exposure-induced cellular and molecular changes and timelines for their resolution depicted here are derived from the data reported in Leikauf et al . (1995) and Mudway and Kelly (2000).3- 55 Quantitative extrapolation requires a combin ation of dosimetry, end point homology, and species sensitivity. Although uncertainties continue to exist, animal-to-human extrapolation can
be done for a number of health e ndpoints with suffi cient accuracy to be us eful in evaluating the potential for human health effects. For example, the amount of pr otein in lavage fluid shows a striking relationship when inters pecies dosimetric adju stments are applied to the individual species and exposure studies. One study (Hatch et al., 1994) of inflammatory markers suggests that a 2 ppm O 3 exposure in sedentary rats approxim ates a 0.4 ppm expos ure in exercising humans (i.e., if one cons iders the dosimetry, the sensitivities of rats and humans are consistent). This supports the use of some anim al data collected at higher O 3 exposures to help understand molecular changes in acutely exposed humans (CD, 8-31). Also of importance are the chronic exposure studies (12 to 24 months) reporti ng lesions in animals caused by long-term O 3 exposures that may analogously occur in humans with long-term (months, years) exposure to relatively high levels of O 3 . However, specific exposure patterns of O 3 concentrations that could produce comparable alterations in human lungs remain to be substantiated (CD, p. 8-32).

3.5.2 Coherence and Plausibility of Short-term Effects on the Respiratory System Acute respiratory morbidity eff ects that have been associated with short-term exposure to

O 3 include such health endpoi nts as decrements in lung function, increased airway responsiveness, airway inflammatio n, epithelial injury, immune sy stem effects, ED visits for respiratory diseases, and hospitali zation due to respiratory illness Recent epidemiological studi es have supported evidence av ailable in the previous O 3 NAAQS review on associations between ambient O 3 exposure and decline in lung function for
children. Earlier observations that children and asthmatic individual s are particularly susceptible
to ambient O 3 are supported by a meta-analysis (Kinne y et al., 1996) of summer camp studies. The CD (p. 8-34) concludes th at exposure to ambient O 3 has a significant ef fect on lung function
and is associated with increased respiratory symptoms and medication use, particularly in
asthmatics. Short-term exposure to O 3 has also been associated with more severe morbidity endpoints, such as ED visits and hospital admissions for respir atory cases, including specific respiratory illness (e.g., asthma) (CD, s ections 7.3.2 and 7.3.3). In addition, a few epidemiological studies have reported positive associati ons between short-term O 3 exposure and respiratory mortality, though the asso ciations are not generally stat istically significant (CD, p. 7- 108). Considering the evidence from epidemiologi cal studies, the resu lts described above provide evidence for coherence in O 3 -related effects on th e respiratory system. Effect estimates
from U.S. and Canadian studies are shown in Figure 3-4, where it can be seen thatRespiratory Mortality:1. Moolgavkar, 2003 Cook County2. Ito, 2003 Detroit(a=1986-1990; b=1992-1994)3. Vedal et al., 2003 Vancouver4. Villeneuve et al., 2003 Vancouver5. Ostro et al., 2003, Coachella ValleyRespiratory Symptoms:1. Mortimer et al., 2003 8 cities2. Gent et al., 2003 New England3. Schwartz et al., 1994 6 cities4. Delfino et al., 2003 San Diego(a=score>1; b=score>2)5. Ross et al., 2002 East Moline6. Neas et al., 1995 Uniontown7. Delfino et al., 1998 San Diego8. Ostro et al., 2001 S. California9. Thurston et al., 1997 ConnecticutEmergency Department Visits:1. Peel et al., 2005 Atlanta2. Wilson et al., 2005 Portland NH3. Wilson et al., 2005 Manchester NH4. Stieb et al., 1996 St. John Canada5. Jones et al., 1995 Baton Rouge(a=0-17 yo; b=18-60 yo; c=>60 yo)6. Delfino et al., 1997 Montreal7. Tolbert et al., 2000 Atlanta8. Jaffe et al., 2003 3 Ohio cities9. Jaffe et al., 2003 Cleveland10. Jaffe et al., 2003 Columbus11. Jaffe et al., 2003 Cincinnati12. Friedman et al., 2001 Atlanta13. Zhu et al., 2003 AtlantaHospital Admissions:1. Burnett et al., 1994 Toronto2. Gwynn et al., 2001 New York City(a=nonwhite; b=white)3 . Gwynn et al., 2000 Buffalo4. Yang et al., 2003 Vancouver(a=<3 yo; b=65+ yo)5. Moolgavkar et al., Minneapolis/St. Paul6. Thurston et al., 1992 New York City7. Burnett et al., 1997 Toronto8. Schwartz et al., 1996 Cleveland9. Delfino et al., 1994 Montreal10. Burnett et al., 1997 16 Canadian cities11. Luginaah et al., 2003 Windsor(a=males; b=females)12. Thurston et al., 1992 Buffalo13. Thurston et al., 1994 Toronto14. Schwartz et al., 1996 Spokane15. Burnett et al., 1999 Toronto16. Lin et al., 2003 Windsor17. Burnett et al., 2001Toronto18. Sheppard et al., 2003 Seattle19. Nauenberg and Basu, 1999 Los Angeles20. Ito, 2003 Detroit21. Schwartz et al., 1994 DetroitFigure 3-4. Effect estimates (with 95% confidence intervals) for associationsbetween short-term ozone exposure and respiratory health outcomes.Effect estimates expressed as odds ratios for associations with respiratory symptoms and % increase for other outcomes, perstandardized increments: 20 ppb for 24-hr O3, 30 ppb for 8-hr O3, and 40 ppb for 1-hr O3, presented in order of decreasingstatistical power from left to right in each category. Dotted line (blue) indicates all year analyses; solid line (red) indicateswarm season results. LRS=lower respiratory symptoms; COPD=chronic obstructive pulmonary diseaseRespiratory Symptoms(Odds Ratios)0.001.002.003.004.005.001235(40)878234a4b559886AsthmasymptomsWheezeShortnessof breathMedicationuse7Respiratory-60-40-20020406080115a42aCOPDPneumoniaRespiratoryAsthmaRespiratoryAsthmaRespiratoryInfectionCOPDCOPDPneumoniaRespiratoryInfectionRespiratory EmergencyDepartment VisitsRespiratory Hospital AdmissionsRespiratoryMortality111 13232695b5c71011b81312111 982b4b4a3765642b2a311a10201913151412121521151718161621205 55

% Increase in RiskCoughLRS3-563- 57 mostly positive associations have been reported with respiratory effects ranging from respiratory symptoms, such as cough or wheeze, to hospitaliza tion for various respiratory diseases, and there is suggestive evidence for asso ciations with respiratory mo rtality. Many of the reported
associations are statis tically significant. Considering also evidence from toxicological , chamber, and field st udies, the CD (section 8.6) discusses biological plausibility and coherence of evidence for acute O 3 -induced respiratory
health effects. Inhalation of O 3 for several hours while subjects are physically active can elicit both acute adverse pathophysiological changes an d subjective respiratory tract symptoms (CD, section 8.4.2). Acute pulmonary responses observed in healthy humans exposed to O 3 at ambient
concentrations include: decreas ed inspiratory capacity; mild bronchoconstriction; rapid, shallow breathing during exercise; subject ive symptoms of tracheobronch ial airway irritation, including cough and pain on deep inspiration; decreases in measures of lung function (e.g., FVC and

FEV 1 ); and increased airway resistance (SR
aw ). The severity of symptoms and magnitude of response depends on inhale d dose, individual O 3 sensitivity, and the degr ee of attenuation or enhancement of response re sulting from previous O 3 exposures. Lung function studies of several animal species acutely expos ed to relatively low O 3 levels (0.25 to 0.4 ppm) show responses
similar to those observed in humans, including increased breat hing frequency, decreased tidal volume, increased resistance, and decreased FVC. Alterations in breathing pattern return to normal within hours of exposure, and attenuation in functional responses following repeated O 3 exposures is similar to th ose observed in humans. Physiological and biochemical alterations investigated in controlled human exposure and animal toxicology studies tend to support cer tain hypotheses of under lying pathological mechanisms which lead to the development of respiratory-relate d effects reported in epidemiology studies (e.g., increas ed hospitalization and medication use). Some of these are: (a) decrements in lung function, (b) bronchoconstriction, (c) increa sed airway responsiveness, (d) airway inflammation, (e) epithelial injury, (f) immune system activation, (g) host defense impairment, and sensitivity of indi viduals, such as age, genetic susceptibility, and the degree of attenuation present due to prior exposures. The time sequence, magnitude, and overlap of these complex events, both in terms of development and recovery (as depi cted in Figures 3-2 and 3-3), illustrate the inherent difficulty of inte rpreting the biological plausibility of O 3 -induced cardiopulmonary health effects (CD, p. 8-48).
The interaction of O 3 with airway epithelial cell memb ranes and epithelial lining fluid (ELF) to form lipid ozonati on products and ROS is supported by numerous human, animal and in vitro studies. Ozonation products and ROS initiate a cascade of events that lead to oxidative stress, injury, inflammation, ai rway epithelial damage and in creased epithelial damage and increased alveolar permeability to vascular fluids. Repeated respiratory inflammation can lead to3- 58 a chronic inflammatory state with altered lung structure and lung function and may lead to chronic respiratory dis eases such as fibrosis and emphys ema (CD, section 8.6.2). Continued respiratory inflammation also can alter the ability to respond to infectious agents, allergens and toxins. Acute inflammatory responses to O 3 are well documented, and lu ng injury can become apparent within 3 hr after e xposure in humans. Ozone-induce d lung injury and subsequent disruption of the airway epithelia l barrier has been implicated in increased mucoci liary clearance of particles in human subjects. Taken together, the CD concludes that the evidence from experimental human and animal toxicology studies indi cates that acute O 3 exposure is causally associat ed with respiratory system effects, including O 3 -induced pulmonary function decrem ents, respiratory symptoms, lung inflammation, and increased lung pe rmeability, airway hyperrespons iveness, increased uptake of nonviable and viable particles, and consequent increased suscep tibility to PM-related toxic effects and respiratory infe ctions (CD, p. 8-48).

3.5.3 Coherence and Plausibility of Effect s on the Cardiovascular System There is very limited experime ntal evidence of animals a nd humans that has evaluated possible mechanisms or physiological pathways by which acute O 3 exposures may induce cardiovascular system effects. Ozone induces lu ng injury, inflamma tion, and impaired mucociliary clearance, with a host of associated biochemical changes all leading to increased lung epithelial permeability. As discussed in section 3.2.1.3, th e generation of lipid ozonation products and reactive o xygen species in lung tissues can influence pulmonary hemodynamics, and ultimately the cardiovascular system. Other potential mechanisms by which O 3 exposure may be associat ed with cardiovascular
disease outcomes have been de scribed. Laboratory animals e xposed to relatively high O 3 concentrations ( ≥ 0.5 ppm) demonstrate tissue edema in the heart and lungs. Ozone-induced changes in heart rate, edema of heart tissue, and incr eased tissue and serum levels of ANF found with 8-h 0.5 ppm O 3 exposure in animal toxicology studies (Vesely et al., 1994a,b,c) also raise the possibility of potenti al cardiovascular effect s of acute ambient O 3 exposures. Animal toxicology studies have found both transient and pers istent ventilatory responses with and without progressive decr eases in heart rate (Arito et al., 1997). Observations of O 3 - induced vasoconstriction in a controlled human exposure study by Brook et al. (2002) suggests another possible mechanism for O 3 -related exacerbations of preexi sting cardiovascular disease. One controlled human study (Gong et al., 1998) evalua ted potential cardiovasc ular health effects
of O 3 exposure. The overall re sults did not indicate acute cardiovascular effects of O 3 in either the hypertensive or control subjects. The author s observed an increase in rate-pressure product and heart rate, a decrement for FEV 1 , and a >10 mm Hg increase in th e alveolar/arterial pressure3- 59 difference for O 2 following O 3 exposure. The mechanism for the decrease in arterial oxygen (O 2 ) tension study could be due to an O 3 -induced ventilation-perfusion mi smatch. Foster et al. (1993)
demonstrated that even in relatively young healthy adults, O 3 exposure can cause ventilation to shift away from the well-perfuse d basal lung. This effect of O 3 on ventilation distribution may persist beyond 24-hr post-exposur e (Foster et al., 1997). Thes e findings suggest that O 3 may exert cardiovascular effects indirect ly by impairing alveolar-arterial O 2 transfer and potentially reducing O 2 supply to the myocardium. Ozone exposure may increas e myocardial work and impair pulmonary gas exchange to a degree that could perhaps be clinically important in persons with significant preexisting cardiovascular impairment. As noted in section 3.3.1.3, a limited number of new epid emiological studies have reported associations between short-term O 3 exposure and effects on th e cardiovascular system. Among these studies, three were population-base d and involved relativel y large cohorts. Two studies, the ARIC (Liao at al., 2004) and the NAS (Parks et al ., 2005) evaluated associations
between O 3 and HRV. The other study, MONICA (R uidavets et al., 20 05) evaluated the
association between O 3 levels and the relative risk of MI. Such studies may offer more informative results based on their large subject- pool and design. Results from these three studies were suggestive of an association between O 3 exposure and the cardiovas cular endpoints studies.
In other recent studies on incidence of myocardial infa rction and some more subtle cardiovascular health endpoints, su ch as changes in heart rate va riability or cardiac arrhythmia, some but not all studies reported associ ations with short-term exposure to O 3 (CD, section 7.2.7.1). From these studies, the CD concludes th at the “current evidence is rather limited but suggestive of a potential effect on HRV, ventricular arrhythmias, and MI incidence” (CD, p. 7- 65). An increasing number of studies have evaluated the association between O 3 exposure and cardiovascular hospital admissions. As shown in Figure 7-13 a nd discussed in section 7.3.4 of the CD, many reported negative or inconsistent associations, wher eas other studies, especially those that examined the relationship when O 3 exposures were higher, have found positive and
robust associations between O 3 and cardiovascular hospital admi ssions. The CD finds that the
overall evidence from these studies remains inconclusive regardi ng the effect of O 3 on cardiovascular hospitali zations (CD, p. 7-83). The CD notes that the suggestive po sitive epidemiologic findings of O 3 exposure on cardiac autonomic control, incl uding effects on HRV, ventricu lar arrhythmias and MI, and reported associations between O 3 exposure and cardiovascular hospitalizations in the warm season gain credibility and scien tific support from the results of experimental animal toxicology and human clinical studies, which are indi cative of plausible pa thways by which O 3 may exert
cardiovascular effects (CD, Section 8.6.1).3- 60 3.5.4 Coherence and Plausibility of Effects Related to Long-Term O 3 Exposure

Human chamber studies can not evaluate effects of long-term exposures to O 3 ; there is
some evidence available from t oxicological studies. While earl y animal toxicology studies of long-term O 3 exposures were conducted using continuous exposures, more recent studies have focused on exposures which mimic diurnal and seasonal patterns and more realistic O 3 exposure levels (CD, p. 8-50). Studies of monkeys that compared thes e two exposure scenarios found increased airway pathology only with the latter design. Persis tent and irreversible effects reported in chronic animal toxico logy studies suggest that add itional complementary human data are needed from epidemiol ogic studies (CD, p. 8-50). A long-term study of infant rhesus monke ys exposed to simulated seasonal O 3 (0.5 ppm , 8 hr/day for 5 days ev ery 14 days for 11 episodes) reported remodeling of the distal airways,
abnormalities in tracheal base ment membrane, accumulation of eosinophils in conducting airways, and decrements in airway innervati on. Another long-term exposure study of monkeys exposed to 0.61 ppm O 3 for a year and studies of rats exposed for 20 months (0.5-1.0 ppm O 3 for 6 hr/day) reported increased depos ition of collagen and thickeni ng of the CAR, suggestive of irreversible long-term O 3 impacts on the lungs. Although some earlier seasonal exposure studies of rats reported small, but significant, decr ements in lung function consistent with focal fibrogenesis in the proximal al veolar region, other chronic expos ure studies with exposures of 0.5 to 1.0 ppm O 3 report epithelial hyperplasia th at disappears in a few days. At this time, there is limited eviden ce from human studies for long-term O 3 -induced effects on lung function. As di scussed in section 8.6.2 of the CD, previous epidemiological studies have provided only inconclusive evidence for either mortality or morbidity effects of long-term O 3 exposure. The CD observes that the inconsiste ncy in findings may be due to a lack of precise exposure information, th e possibility of selection bias, and the difficulty of controlling for confounders (CD, p. 8-50). Several new l ongitudinal epidemiology st udies have evaluated associations between long-term O 3 exposures and morbidity and mo rtality and sugg est that these long-term exposures may be rela ted to changes in lung functi on in children; however, little evidence is available to support a relationship between chronic O 3 exposure and mortality or lung cancer incidence (CD, p. 8-50). The CD (p. 8-51) conclude s that evidence from animal toxicology studies strongly suggests that chronic O 3 exposure is capable of damaging the di stal airways and proximal alveoli, resulting in lung tissue remodeling leading to apparent irreversible changes. Such structural changes and compromised pulmonary functi on caused by persistent inflammation may exacerbate the progression and development of chr onic lung disease. Toge ther with the limited evidence available from epidemiological studies, these findings offer some insight into potential biological mechanisms for suggested associations between long-term or seasonal exposures to O 33- 61 and reduced lung function developm ent in children which have b een observed in epidemiologic studies (CD, p. 8-51).

3.5.5 Coherence and Plausibility of Sho rt-Term Mortality-Related Health Endpoints An extensive epidemiological literature on air pollution rela ted mortality risk estimates from the U.S., Canada, and Europe is discussed in the CD (sec tions 7.4 and 8.6.3). These singleand multi-city mortality studies coupled with meta-analyse s generally indicate associations
between acute O 3 exposure and elevated risk for all-cause mortality, even after adjustment for the
influence of season and PM. Several single-city studies th at specifically evaluated the relationship between O 3 exposure and cardiopulmonary mortality also reported re sults suggestive of a positive association (CD, p. 8-51). These mo rtality studies suggest a pattern of effects for causality that have biological ly plausible explanations, but our knowledge regarding potential underlying mechanisms is very limit ed at this time and requires fu rther research. Most of the physiological and biochemical para meters investigated in human and animal studies suggest that

O 3 -induced biochemical effects are relatively transient and attenu ate over time. The CD (p. 8- 52) hypothesizes a generic pathway of O 3 -induced lung damage, poten tially involvi ng oxidative lung damage with subsequent infl ammation and/or decline in lung function leading to respiratory distress in some sensitive populati on groups (e.g., asthmatics), or other plausible pathways noted below that may lead to O 3 -related contributions to cardiovascul ar effects that ultimately increase risk of mortality.
The third National Health and Nutrition Ex amination Follow-up data analysis indicates
that about 20% of the adult populatio n has reduced FEV 1 values, suggesting impaired lung function in some portion of the population. Most of these indivi duals have COPD, asthma or fibrotic lung disease (Manino et al., 2003), which are asso ciated with persistent low-grade inflammation. Furthermore, patients with COPD are at increased risk for cardiovascular disease. Also, lung disease with underl ying inflammation may be link ed to low-grade systemic inflammation associated with atherosclerosis, independent of cigarett e smoking (CD, p. 8-52). Lung function decrements in pers ons with cardiopulmonary diseas e have been associated with inflammatory markers, such as C-reactive prot ein (CRP) in the blood. At a population level it
has been found that indivi duals with the lowest FEV 1 values have the highest levels of CRP, and those with the highest FEV 1 values have the lowe st CRP levels (Mani no et al., 2003; Sin and Man, 2003). This complex series of physiolo gical and biochemical reactions following O 3 exposure may tilt the biological homeostasis mech anisms which could lead to adverse health effects in people with compromised cardiopulmonary systems.3- 62 Of much interest are several other types of newly available data that support reasonable hypotheses that may help to explain the findings of O 3 -related increases in cardiovascular mortality observed in some epid emiological studies. These in clude the direct effect of O 3 on increasing PAF in lung tissue that can then enter the general circ ulation and possibly contribute
to increased risk of blood clot formation and the conseq uent increased risk of MI, cerebrovascular events (stroke), or associated cardiovascular-rela ted mortality. Ozone reactions with cholesterol in lung surfactan t to form epoxides and oxysterol s that are cytot oxic to lung and
heart muscles and that contribute to atherosclerotic plaque format ion in arterial walls represent another potential pathway. Stimulation of airway irritant receptors may lead to increases in tissue and serum levels of ANF, changes in hear t rate, and edema of h eart tissue. A few new field and panel studies of hum an adults have reported as sociations between ambient O 3 concentrations and changes in cardiac autonomic control (e.g., HRV, ventricula r arrhythmias, and MI). These represent plausibl e pathways that may lead to O 3 -related contributions to
cardiovascular effects that ultimatel y increase the risk of mortality. In addition, O 3 -induced increases in lung permeability allow more ready entry for inhaled PM into the blood stream, and O 3 exposure may increase the risk of PM-related cardiovascular effects. Furthermore, increased ambient O 3 levels contribute to ultr afine PM formation in the ambient air and indoor environments. Thus, the contributions of elevated ambient O 3 concentrations to ultrafine PM formation and human exposure, along with the enhanced uptake of inhaled fine particles, consequently may contribute to exacerbation of PM-induced
cardiovascular effects in addition to those more directly induced by O 3 (CD, p. 8-53).

3.6 OZONE-RELATED IMPACTS ON PUBLIC HEALTH The following discussion draws from section 8. 7 of the CD to char acterize factors which modify responsiveness to O 3, subpopulations potentially at risk for O 3 -related health effects, and potential public health impacts asso ciated with exposure to ambient O 3 . Providing appropriate protection of public health requir es that a distinction be made between those effects that are
considered adverse health effects and those that are not adverse. What constitutes an adverse health effect depends not only on the type and magnitude of e ffect but also on the population group being affected. While some changes in healthy individuals woul d not be considered adverse, similar changes in susceptible individu als would be seen as ad verse. In order to estimate the potential public hea lth impact, it is important to consider both the susceptible subpopulations for O 3 exposure and the defini tion of adversity for O 3 health effects.3- 63 3.6.1 Factors that Modify Responsiveness to Ozone

There are numerous factor s that can modify indivi dual responsiveness to O 3 . These
include: influe nce of physical activity; age; gender and hormonal in fluences; racial, ethnic and socioeconomic status (SES) factor s; environmental factors; and oxidant-antioxidant balance.
These factors are discussed in more detail in section 6.5 of the CD.
It is well established that physical activity increases an individual’s mi nute ventilation
and will thus incr ease the dose of O 3 inhaled (CD, section 6.5.4). Increased phys ical activity results in deeper penetration of O 3 into more distal regions of th e lungs, which are more sensitive

to acute O 3 response and injury. This will result in greater lung function decrements for acute exposures of individuals during in creased physical activity. Resear ch has shown that respiratory
effects are observed at lower O 3 concentrations if the level of exertion is increased and/or duration of exposure and exerti on are extended. Predicted O 3 -induced decrements in lung
function have been shown to be a function of exposure duration and exercise level for healthy, young adults (McDonnell et al., 1997). Most of the studies investig ating the influence of age have used lung function decrements and symptoms as measures of response. Fo r healthy adults, lung function and symptom responses to O 3 decline as age increases. The rate of decline in O 3 responsiveness appears greater in those 18 to 35 years old compared to those 35 to 55 years old, while there is very little change after age 55. In one study (Seal et al., 1996) analyzing a la rge data set, a 5.4% decrement
in FEV 1 was estimated for 20 year old individuals exposed to 0.12 ppm O 3 , whereas similar exposure of 35 year old individu als were estimated to have a 2.6% decrement. While healthy children tend not to report respiratory sy mptoms when exposed to low levels of O 3 , for subjects 18 to 36 years old symptom responses induced by O 3 tend to decrease w ith increasing age (McDonnell et al., 1999). Limited evidence of gender di fferences in response to O 3 exposure has suggested that females may be predisposed to a greater susceptibility to O 3 . Lower plasma a nd NL fluid levels of the most prevalent antioxidant , uric acid, in females relative to males may be a contributing factor (Housley et al., 1996). C onsequently, reduced removal of O 3 in the upper airways may promote deeper penetration. However, most of th e evidence on gender diffe rences appears to be equivocal, with one study (Haz ucha et al., 2003) suggesting th at physiological responses of young healthy males and females may be comparable (CD, section 6.5.2). A few studies have suggeste d that ethnic minor ities might be more responsive to O 3 than Caucasian population groups (CD, section 6.5.3). This may be more the result of a lack of adequate health care and socioeconomic status than any differences in sensitivity to O 3 . The limited data available, which ha ve investigated the influence of race, ethnic or other related factors on responsiveness to O 3, prevent drawing any clear conclusions at this time.3- 64 Few human studies have examined the poten tial influence of envir onmental factors such as the sensitivity of i ndividuals who voluntarily smoke tobacc o (i.e., smokers) a nd the effect of high temperatures. New controlled human expos ure studies have confirmed that smokers are less responsive to O 3 than nonsmokers; however, time course of development and recovery of these effects, as well as repr oducibility, was not different fro m nonsmokers (CD, section 6.5.5). Influence of ambient temperature on pulmonary effects induced by O 3 has been studied very little, but additive e ffects of heat and O 3 exposure have been reported. Antioxidants, which scavenge free radicals and limit lipid peroxi dation in the ELF, are the first line of defense against oxidative stre ss. Ozone exposure l eads to absorption of O 3 in the ELF with subsequent depletion of ELF antioxidant level in the nasal ELF, but concentration and antioxidant enzyme activity in ELF or plasma do not appear related to O 3 responsiveness (CD, section 6.5.6). Controlled studies of dietar y antioxidant supplements have shown some protective effects on lung functi on decrements but not on symptoms and airway inflammatory responses. Dietary antioxidant supplements have provided so me protection to asthmatics by attenuating post-exposure airway hyperresponsiveness. Animal st udies have also supported the protective effects of ELF antioxidants.

3.6.2 Susceptible Population Groups

Several characteristics that may increase the extent to which a population group shows sensitivity to O 3 have been discussed in the CD, in the sections on clinical studies in Chapter 6, epidemiological studies in Chapter 7, and in the integrated assessm ent in Chapter 8; this section will draw on all of these. The characteris tics that likely increase susceptibility to O 3 are based on: (1) activity patterns; (2) lung disease; (3) age; and (4) biological responsiveness to O 3
. Other groups that might have enhanced sensitivity to O 3 , but for which there is currently very little evidence, include: people with hear t disease; groups base d on race, gender and socioeconomic status; and those wi th nutritional deficiencies.

3.6.2.1 Active People A large group of indivi duals at risk from O 3 exposure consists of outdoor workers and children, adolescents, and adults who engage in outdoor activities involving exertion or exercise during summer daylight hours when ambient O 3 concentrations tend to be higher. This conclusion is based on a larg e number of controlled-exposur e human studies and several epidemiologic field/panel studies which have b een conducted with heal thy children and adults and those with preexisting respir atory diseases (CD, sections 6.2 and 6.3). The controlled human exposure stud ies show a clear O 3 exposure-response relationship with increasing spirometric and symptomatic response as exercise level increases. Furthermore, O 3 -induced response increases as time of exposure increases. Studies of outdoor workers and others who3- 65 participate in outdoor ac tivities indicate that extended exposures to O 3 at elevated exertion levels can produce marked effe cts on lung function.
The effects of O 3 on the respiratory health of outdoor workers and others who participate
in outdoor activities have been in vestigated in several recent epidemiologic studies. These individuals may experience increased vulnerability for O 3 health effects, because they are typically exposed to high doses of O 3 as they spend long hours out doors often at elevated exertion levels. In a group of berry pickers in Fraser Valle y, Canada, decrements in lung function (~5% decrease in FEV 1 per 40 ppb increase in 1-hr max O 3 ) were associated with acute exposure to relatively lo w concentrations of O 3 (Brauer et al., 1996). The mean ambient 1-hr

max O 3 was 40.3 ppb (SD 15.2) over the study period of Ju ne to August 1993. The berry pickers worked outdoors for an average of 11 hr at elevated heart rate s (on average, 36 % higher than resting levels). These results indi cate that extended exposures to O 3 at elevated exertion levels can produce marked effects on lung function among outdoor workers. Höppe et al. (1995) examined forestry workers for O 3 -related changes in pulmonary function in Munich, Germany. Vent ilation rates, estimated from their average activity levels, were elevated. When comparis ons were made between high O 3 days (mean 1⁄2-hr max O 3 of 64 ppb) and low O 3 days (mean 1⁄2-hr max O 3 of 32 ppb), 59% of the fore stry workers experienced a notable decrement in lung function (i.e., at least a 20% in crease in specific ai rway resistance or
at least a 10% decrease in FEV 1 , FVC, or PEF) on high O 3 days. None experienced improved lung function. This study also examined athletes following a 2- hr outdoor training period in the afternoon yielding a ventilation rate double the estimate for the forestry workers. Though a significant association between ambient O 3 levels and decrements in FEV 1 was observed overall, a smaller percentage of the at hletes (14%) experienced a notab le decrement in lung function on high O 3 days compared to the forestry workers; a nd 19% of the athletes actually showed an improvement. A large field study by Korrick et al. (1998) examined th e effects of multi-hour O 3 exposures (on average, 8 hr) on adults hiking outdoors on Mount Washington, in NH. The mean of the hourly O 3 concentrations during the hike was 40 ppb (range 21-74). After the hike, all subjects combined experienced a relatively small mean decline in FEV 1 (1.5% decrease per 30 ppb increase in mean hourly O 3 concentrations) during the hike. Ozone-related changes in lung function parameters were estimated. Stratifyi ng the data by hiking duration indicated that
individuals who hiked 8 to 12 hr experienced a 2-fold greater decline in FEV 1 versus those only hiking 2 to 8 hr.
Results from the above field studies are consistent with those from earlier summer camp studies (Avol et al., 1990; Higgi ns et al., 1990; Raiz enne et al., 1987, 1989; Spektor et al., 1988,3- 66 1991), which also observed strong associations between acute O 3 exposure and decrements in lung function among children who spent long ho urs outdoors. In a recent analysis by the Southern California Children’s Health Study, a total of 3,535 initially nonasthmatic children (ages 9 to 16 years at enrollment) were followe d for up to 5 years to identify new-onset asthma
cases associated with hi gher long-term ambient O 3 concentrations (McConnell et al., 2002). Communities were stratified by po llution levels, with six high-O 3 communities (mean 1-hr max

O 3 of 75.4 ppb [SD 6.8] over four years) and six low-O 3 communities (mean 50.1 ppb [SD 11.0]). In the combined anal ysis using all children, asthma ri sk was not found to be higher for residents of the six high-O 3 communities versus those from the six low-O 3 communities. However, within the high-O 3 communities, asthma risk was mo re than 3 times greater for children who played three or more sports versus those who played no spor ts, an association not
observed in the low-O 3 communities. Therefore, among children repeatedly exposed to higher

O 3 levels, increased exertion outdoo rs (and resulting increased O 3 dose) was associated with
excess asthma risk.
These field studies with s ubjects at elevated exertion levels support the extensive evidence derived from controlled human exposure studies. The majority of human chamber
studies have examined the effects of O 3 exposure in subjects performing continuous or
intermittent exercise for variable periods of time. Significant O 3 -induced respiratory responses
have been observed in clinical studies of exercisi ng individuals. The epidemiologic studies
discussed above also indicate that prolonged exposure periods, comb ined with elevat ed levels of exertion or exercise, may magnify O 3 effects on lung function. Thus, outdoor workers and others who participate in higher exerti on activities outdoors during the time of day when high peak O 3 concentrations occur appear to be particularly vulnerable to O 3 effects on respiratory health. Although these studies show a wi de variability of response a nd sensitivity among subjects and the factors contributing to this variability continue to be in completely understood, the effect of
increased exertion is consistent. It should be noted that this wide variability of response and sensitivity among subjects may be in part due to the wide ra nge of other highly reactive photochemical oxidants coexisting with O 3 in the ambient air.

3.6.2.2 People with Lung Disease People with preexisting pulmonary disease are likely to be among those at increased risk
from O 3 exposure. Altered physiological, morphologi cal and biochemical states typical of respiratory diseases like asthma, COPD and ch ronic bronchitis may render people sensitive to
additional oxidativ e burden induced by O 3 exposure. The new results from controlled exposure and epidemiologic studies contin ue to indicate that asthmatics are a sensitive subpopulation for

O 3 health effects.3- 67 A number of epidemiologica l studies have been conduc ted using asthmatic study populations. The majority of epid emiological panel studies that evaluated respiratory symptoms
and medication use related to O 3 exposures focused on children. These studies s uggest that O 3 exposure may be associated with increased respiratory symptoms and medication use in children with asthma. Other reported effects include respiratory symp toms, lung function decrements, and ED visits, as discussed in the CD (section 7.6.7.1). Strong evidence from a large multi-city study (Mortimer et al., 2002), along with support from several single- city studies suggest that O 3 exposure may be associated with increased respiratory symptoms and medication use in children
with asthma. With regard to ambient O 3 levels and increased hospita l admissions and ED visits for asthma and other respiratory causes, strong and consistent ev idence establishes a correlation
between O 3 exposure and increased exacerbations of pr eexisting respiratory disease for 1-hr
maximum O 3 concentrations <0.12 ppm. Several hospital admission and ED visit studies in the U.S. (Peel et al., 2005), Canada (Burnett et al., 1997a; Anders on et al., 1997), and Europe (Anderson et al., 1997) have reported positiv e associations between increase in O 3 and increased
risk of ED visits and hos pital admissions, especiallyduring the warm season.
Several clinical studies reviewed in th e 1996 CD on atopic and as thmatic subjects had suggested but not clearly demonstrated enhanced responsiveness to acute O 3 exposure compared to healthy subjects. The majority of the newer studies reviewed in Chap ter 6 of the CD indicate that asthmatics are as sensitive as, if not more sensitive than, normal subjects in manifesting induced pulmonary function decrements.
Ozone-induced increases in neut rophils, protein, and IL-8 we re found to be significantly higher in the BAL flui d from asthmatics compared to heal thy subjects, suggesting mechanisms for the increased sensitivity of asthmatics. Si milarly, subjects with alle rgic asthma exhibited increased airway responsiveness to inhaled alle rgens upon acute O 3 exposure. Asthmatics present a differential response prof ile for cellular, molecular, a nd biochemical pa rameters (CD, Figure 8-1) that are altere d in response to acute O 3 exposure. Increases in O 3 -induced nonspecific airway responsiveness incidence an d duration could have important clinical implications for asthmatics. Bronchial constriction following provocation with allergens presents a two-phase response. The early response is mediated by release of histamine and leukotrienes that leads to
contraction of smooth muscle cel ls in the bronchi, narrowing the lumen and decreasing the airflow. In asthmatics, thes e mediators also cause accumula tion of eosinophils, followed by production of mucus and a late-phase bronchial c onstriction and reduced ai rflow. Holz et al. (2002) reported an early phase response in su bjects with rhinitis af ter a consecutive 4-day exposure to 0.125 ppm O 3 that resulted in a clinically relevant (>20%) decrease in FEV 1
. Allergen challenge in m ild asthmatics 24 hr before exposure to 0.27 ppm O 3 for 2 hr resulted in3- 68 significantly increased eosinophil counts in samples of respir atory tract lining fluid, obtained by sputum induction, compared to results in healthy subjects (Vag aggini et al., 2002). Epithelial cells from mucosal biopsies of allergic asthmatics indicated significant increases in the expression of IL-5, IL-8 a nd GM-CSF, suggesting increased neutrophilic inflammation compared to healthy subj ects (Bosson et al., 2003). Several human exposure studies have shown differences between as thmatics and healthy human subjects with regard to PMN influx in BA L fluid. In vitro studi es (Schierhorn et al., 1999) of nasal mucosal biopsies from atopic and nonatopic subjects exposed to 0.1 ppm O 3 found significant differences in releas e of IL-4, IL-6, IL-8, and TNF- α . Another study by Schierhorn et al. (2002) found significant differences in the O 3 -induced release of the neuropeptides neurokinin A and substance P for allergic patients in co mparison to nonallergic controls, suggesting
increased activation of sensory nerves by O 3 in the allergic tissues. Another study by Bayram et al. (2002) using in vitro culture of bronchial epithelial cells re covered from atopic and nonatopic asthmatics also found significan t increases in epithelial perm eability in response to O 3 exposure. In addition, some controlled human O 3 exposure studies in asthmati cs (Hiltermann et al., 1999; Scannell et al., 1996) reported increased secret ion of IL-8, suggesting increased neutrophilic inflammation. Two studies (Jörre s et al., 1996; Holz et al., 20 02) observed increased airway responsiveness to repeated daily O 3 exposure to bronchial allergen challenge in subjects with preexisting allergic airway disease. Newly available reports from controlled human exposure stud ies (see Chapter 6 in the CD) utilized subjects with preexi sting cardiopulmonary diseases su ch as COPD, asthma, allergic rhinitis, and hypertension. The data generated from these stud ies that evaluated pulmonary function changes in spirometry did not find cl ear differences between filtered air and O 3 exposure in COPD subjects. However, the new data on ai rway responsiveness, in flammation, and various molecular markers of inflammation and bronchoc onstriction indicate that people with atopic asthma and allergic rhinitis comprise susceptible groups for O 3 -induced adverse heal th effects. Although controlled human exposure studies have not found evidence of larger spirometric changes in people with COPD relative to healthy subjects, this may be due to the fact that most people with COPD are older adults who would not be ex pected to have such changes based on their age. However, in Section 8.7.1, th e CD notes that new ep idemiological evidence indicates that people with COPD may be more likely to experience ot her effects, including emergency room visits, hospital admissions, or premature mortalit y. For example, results from an analysis of five European citi es indicated strong and consistent O 3 effects on unscheduled respiratory hospital admissions, in cluding COPD (Anderson et al., 1997 ). Also, an analysis of a 9-year data set for the whole population of the Netherlands provi ded risk estimates for more specific causes of morta lity, including COPD (Hoek et al., 2000, 2001; re analysis Hoek, 2003); a3- 69 positive, but nonsignificant, excess risk of COPD-r elated mortality was found to be associated
with short-term O 3 concentrations. Moreover, as indicated by Gong et al. (1998), the effects of

O 3 exposure on alveolar-arterial oxygen gradient s may be more pronounced in patients with preexisting obstructive lung diseas es. Relative to healthy elderl y subjects, COPD patients have reduced gas exchange and low SaO 2 . Any inflammatory or ed ematous responses due to O 3 delivered to the we ll-ventilated regions of th e COPD lung could further inhibit gas exchange and reduce oxygen satura tion. In addition, O 3 -induced vasoconstriction c ould also acutely induce pulmonary hypertension. Indu cing pulmonary vasoconstrictio n and hypertension in these patients would perhaps worsen th eir condition, especially if their right ventricular function was already compromised (CD, Section 6.10).

3.6.2.3 Children and Older Adults Supporting evidence exists for hete rogeneity in the effects of O 3 by age. As discussed in
section 6.5.1 of the CD , children, adolescents, and young adu lts (<18 yrs of age) appear, on average, to have nearly equivalent spirometric responses to O 3 , but have greater responses than middle-aged and older adults wh en exposed to comparable O 3 doses. Symptomatic responses to

O 3 exposure, however, do not appear to occur in healthy children, but ar e observed in asthmatic children, particularly those who use maintenan ce medications. For adults (>17 yrs of age) symptoms gradually decrease with increasing age. In contrast to young adults, the diminished symptomatic responses in children and symptoma tic and spirometric resp onses in the elderly may put them at an increased risk for continued exposure.
As described in the section 7.6.7.2 of the CD , many epidemiological field studies focused
on the effect of O 3 on the respiratory health of school children. In ge neral, children experienced decrements in pulmonary functi on parameters, in cluding PEF, FEV 1 , and FVC. Increases in respiratory symptoms and asthma medication use we re also observed in as thmatic children. In one German study, children with an d without asthma were found to be particularly susceptible to

O 3 effects on lung function. Appr oximately 20% of the children, bo th with and without asthma, experienced a greater than 10% change in FEV 1 , compared to only 5% of the elderly population and athletes (Höppe et al., 2003). The American Academy of Pediatrics (2004) notes that children and infants are among the population groups most susceptible to many air polluta nts, including O 3 . This is in part because their lungs are still deve loping. For example, eighty percen t of alveoli are formed after birth, and changes in lung development continue through adolescence (Die tert et al., 2000). Children are also likely to spend more time outdo ors than adults do, which results in increased exposure to air pollutants (Wiley et al., 1991 a,b). Moreover, children have high minute3- 70 ventilation rates and high levels of physical activity which also increases their dose (Plunkett et al., 1992). Several mortality studies have invest igated age-related differences in O 3 effects. Among the studies that observed pos itive associations between O 3 and mortality, a comparison of all age or younger age ( # 65 years of age) O 3 -mortality effect estimates to that of the elderly population (>65 years) indicates that, in general, the elderly populati on is more susceptible to O 3 mortality effects (Borja-Aburto et al., 1997; Bremner et al., 1999; Gouve ia and Fletcher, 2000; O’Neill et al., 2004; Simpson et al., 1997; Sartor et al., 1995; Sunyer et al., 2002). For example, a study by Gouveia and Fletcher (2000) examined the O 3 -mortality effect by age in S n o Paulo, Brazil. Among all ages, O 3 was associated with a 0.6% excess ri sk in all cause mortality per 40 ppb
increase in 1-hr max O 3 . In comparison, in th e elderly population, the O 3 -mortality risk estimate was nearly threefold greater, at 1.7%. Si milarly, a Mexico City study found that O 3 -mortality
effect estimates were 1. 3% and 2.8% per 20 ppb incr ease in 24-hr average O 3 concentration in all ages and the elderly, respec tively (O’Neill et al., 2004). The meta-analysis by Bell et al. (2005) found a larger eff ect estimate for the elderly (2.92% per 20 ppb increase in 24-hr average O 3 ) than for all ages (1.75%). In the large U.S. 95 communities study (Bell et al., 2004), effect estimates were slightly higher for those aged 65 to 74 years, 1.40% excess risk per 20 ppb increase in 24-hr average O 3 , compared to individuals less than 65 years and 75 year s or greater, 1.00% and 1.04%, re spectively, using a constrained distributed 7-day lag model. Be ll et al. (2004) note that despit e similar effects estimates, the
absolute effect of O 3 is substantially greater in the el derly population du e to the higher underlying mortality rates, which lead to a larger number of extra deaths for the elderly compared to the general populati on. The CD concludes that the elderly population (>65 years of age) appear to be at greater risk of O 3 -related mortality and hospitali zations compared to all ages or younger populations (CD, p. 7-177). The CD notes that, co llectively, there is suppor ting evidence of age-re lated differences in susceptibility to O 3 lung function effects. Th e elderly population (>65 year s of age) appear to be
at increased risk of O 3 -related mortality and hospitalizati ons, and children (<18 years of age) experience other potentially adverse respir atory health outcomes with increased O 3 exposure (CD, section 7.6.7.2).

3.6.2.4 People with Increased Responsiveness to Ozone
New animal toxicology studies using various strains of mice and rats have identified O 3 - sensitive and resistant strains and illustra ted the importance of genetic background in determining O 3 susceptibility (CD, secti on 8.7.4). Using subacute low exposure regimen (0.3 ppm O 3 , 48h) studies on inbred strain s that have been designated as inflammation prone or3- 71 resistant, Kleeberger et al ., (1997) identified the pro-in flammatory cytokine gene, Tnf

- α , as a susceptibility gene. Further char acterization of this model indi cated a role fo r TNF receptors (TNFR1, TNFR2) in O 3 -induced pulmonary epit helial injury and inflammation (Cho et al., 2001). Studies on five inbred strains of mouse with differing response to O 3 exposure (acute high dose or low dose continuous ex posure for 3 days), re ported a protective role for clara cell secretory protein (CCSP) against O 3 -induced oxidative damage (Broec kaert et al., 2003; Wattiez et al., 2003). The role for these genes and/or their orthologs in hum an susceptibility to O 3 exposure is yet to be examined. Apart from age at the time of exposure, c ontrolled human exposure studies have also indicated a high degree of interi ndividual variability in some of the pulmonary physiological parameters. Recent studies by David et al. (2003) and Romieu et al. (2004) reported a role for genetic polymorphism in antioxida nt enzymes and genes involved in inflammation to modulate pulmonary function and inflammatory responses to O 3 exposure. Similar to mouse studies referred above, polymorphism in Tnf

- α has been implicated in O 3 -induced lung function changes in healthy, mild asthmatics and individuals with rhini tis. These observations suggest a potential role for these markers in the innate susceptibility to O 3 , however, the validity of these markers
and their relevance in the co ntext of prediction to populati on studies needs additional experimentation. Biochemical and molecular parameters extens ively evaluated in these experiments were used to identify specific loci on the chromosomes and, in some cas es, to relate the differential expression of specific genes to biochemical and physiological differences observed among these species. Utilizing O 3 -sensitive and O 3 -resistant species, it has been possible to identify the involvement of AHR and inflammation processes in O 3 susceptibility. However, most of these
studies were carried out usi ng relatively high doses of O 3 , making the relevanc e of these studies questionable in human health eff ects assessment. The molecular parameters identified in these studies may serve as useful bi omarkers with the availability of suitable technologies and, ultimately, can likely be integrated with epidemiological studies. Interindividual differences in

O 3 responsiveness have been observed across a spectrum of symptoms and lung function responses do not yet allow identification of im portant underlying factors, except a significant role for age.

3.6.2.5 Other Population Groups There is limited, new evidence supporting associations between short-term O 3 exposures and a range of effects on the cardiovascular system. Some but not all, epidemiological studies have reported associatio ns between short-term O 3 exposures and the inci dence of myocardial
infarction and more subtle cardi ovascular health endpoi nts, such as changes in heart rate3- 72 variability and cardiac arrhythmia. Others have reported associati ons with hospitalization or ED
visits for cardiovascular diseas es, although the results across the studies are not consistent. Studies also report associa tions between short-term O 3 exposure and mortality from cardiovascular or cardiopulmonary causes. The CD concludes th at current cardiac physiologic
effects evidence from some field studies is rather limited but s upportive of a potential effect of
short-term O 3 exposure and HRV, cardiac arrhythmia, a nd MI incidence (CD, p. 7-65). In the
CD’s evaluation of studies of hospital admissions for cardiovascu lar disease (CD, section 7.3.4),
it is concluded that evidence from this growing group of studies is generally inconclusive regarding an association with O 3 in studies conducted during th e warm season (CD, p. 7-83). This body of evidence suggests th at people with heart disease may be at increased risk from short-term exposures to O 3; however, more evidence is needed to conclude that people with heart disease are a susceptible population. Other groups that might have enhanced sensitivity to O 3 , but for which there is currently very little evidence, include groups based on r ace, gender and socioeconomic status, and those with nutritional deficiencies, as discussed in section 3.6.1 which presents factors which modify responsiveness to O 3
.

3.6.3 What Constitutes an Adverse Heal th Impact from Ozone Exposure? In making judgments as to when various O 3 -related effects become regarded as adverse to the health of individuals, in previous NAAQS reviews st aff has relied upon the guidelines published by the American Thoracic Society (ATS) and the advice of CASAC. While recognizing that perceptions of “medical signi ficance” and “normal activity” may differ among physicians, lung physiologists and experimental subjects, the ATS ( 1985) defined adverse respiratory health effects as “medically significant physiologi c changes generally evidenced by one or more of the following: (1) interference with the normal activity of th e affected person or persons, (2) episodic respiratory illness, (3) incapacitating illnes s, (4) permanent respiratory injury, and/or (5) progressive respiratory dysfunction.” During the 1997 review, it was co ncluded that there was evid ence of causal associations from controlled human exposure st udies for effects in the first of thes e five ATS-defined categories, evidence of statisti cally significant associations fr om epidemiologi cal studies for
effects in the second an d third categories, and evidence fro m animal toxicology studies, which could be extrapolated to humans only with a sign ificant degree of uncertainty, for the last two categories. For the current review, the evidence of O 3 -related effects is st ronger across all the categories. For ethical reasons , clear causal evidence from c ontrolled human exposure studies still covers only effect s in the first category. However, for this review there are results from epidemiological studies, upon which to base judgments about advers ity, for effects in all of the3- 73 categories. Statistically signifi cant and robust associations have been reported in epidemiology studies falling into the second and third categories. These more serious effects include respiratory illness that may requi re medication (e.g., asthma), but not necessarily hospitalization, as well as respiratory hospital ad missions and ED visits for resp iratory causes. Less conclusive, but still positive a ssociations have been reported for school absences and cardiovascular hospital
admissions. Human health effect s for which associations have been suggested through evidence from epidemiological and animal toxicology studies, but ha ve not been conclusively demonstrated still fall primarily into the last two categories. In the last review of the O 3 standard, evidence for these more serious effects came from studi es of effects in laboratory
animals. Evidence from animal studies evaluated in this CD strongly suggests that O 3 is capable of damaging the distal airways and proximal alveoli, resulting in lung tissue remodeling leading to apparently irreversible changes. Recent ad vancements of dosimetry modeling also provide a better basis for extrapolation fro m animals to humans. Informa tion from epidemiological studies provides supporting, but limited evidence of irreversible resp iratory effects in humans (as described in section 6.3.3.2 below) . Moreover, the CD conclude s that the findi ngs from singlecity and multi-city time-series epidemiology studies and meta-a nalyses of these epidemiology studies support a likely causal as sociation between short-term O 3 exposure and mortality particularly in the warm season.
While O 3 has been associated with effects that are clearly adverse, application of these guidelines, in particular to the least seri ous category of effects related to ambient O 3 exposures, involves judgments about which medical expe rts on the CASAC panel and public commenters have in the past expressed dive rse views. To help frame su ch judgments, we have defined gradations of individual functional responses (e .g., decrements in FEV 1 and airway responsiveness) and symptomatic responses (e .g., cough, chest pain, wheeze), together with judgments as to the potential im pact on individuals experiencing va rying degrees of severity of these responses, that have been used in previous NAAQS reviews. These gradations and impacts
are summarized in Tables 3-2 and 3-3. For active healthy people, moderate le vels of functional responses (e.g., FEV 1 decrements of > 10% but < 20%, lasting up to 24 hrs) an d/or moderate symptomatic responses (e.g., frequent spontaneous cough, marked discomfort on exercise or deep breath, lasting up to 24 hrs) would likely interfere wi th normal activity for relativ ely few sensitiv e individuals; whereas large function al responses (e.g., FEV 1 decrements > 20%, lasting long er than 24 hrs) and/or severe symptomatic respons es (e.g., persistent uncontrollab le cough, severe discomfort on exercise or deep breath, lasting l onger than 24 hrs) woul d likely interfere with normal activitiesTable 3-2. Gradation of Individual Respon ses to Short-Term Ozone Exposure in Healthy Persons 1

Functional Response None Small Moderate Large

FEV 1 Within normal range (±3%) Decrements of 3 to # 10% Decrements of >10 but <20% Decrements of

$ 20%

Nonspecific airway responsiveness 2 Within normal range Increases of <100% Increases of

# 300% Increases of >300% Duration of response None <4 hrs >4 hrs but

# 24 hrs >24 hrs

Symptom Response Normal Mild Moderate Severe
Cough Infrequent cough Cough with deep breath Frequent spontaneous cough Persistent uncontrollable cough
Chest pain None Discomfort just noticeable on exercise or deep breath Marked discomfort on exercise or deep breath Severe discomfort on exercise or deep breath

Duration of response None <4 hrs >4 hrs but # 24 hrs >24 hrs Impact of Responses Normal Normal Mild Moderate

Interference with normal activity None None A few sensitive individuals choose to limit activity Many sensitive individuals choose to limit activity

3-74

1 This table is reproduced from the 1996 O 3 AQCD (Table 9-1, page 9-24) (U.S. Environmental Protection Agency, 1996).

2 An increase in nonspecific airway responsiveness of 100% is equivalent to a 50% decrease in PD 20 or PD 100 .Table 3-3. Gradation of Individual Response s to Short-Term Ozone Exposure in Persons with Impaired Respiratory Systems 3

Functional Response None Small Moderate Large

FEV 1 change Decrements of <3% Decrements of 3 to # 10% Decrements of >10 but <20% Decrements of

$ 20%

Nonspecific airway responsiveness 4 Within normal
range Increases of <100% Increases of # 300% Increases of >300%

Airway resistance (SRaw) Within normal range (±20%) SRaw increased <100% SRaw increased up to 200% or up to 15 cm H2O/s SRaw increased >200% or more than 15 cm H2O/s

Duration of
response None <4 hr >4 hr but # 24 hr >24 hr

Symptom Response Normal Mild Moderate Severe

Wheeze None With otherwise normal breathing With shortness of breath Persistent with shortness of breath

Cough Infrequent cough Cough with deep breath Frequent spontaneous cough Persistent uncontrollable cough

Chest pain None Discomfort just noticeable on exercise or deep breath Marked discomfort on exercise or deep breath Severe discomfort on exercise or deep breath

Duration of
response None < 4 hr >4 hr but # 24 hr >24 hr

Impact of Responses Normal Mild Moderate Severe

Interference with normal activity None Few individuals choose to limit activity Many individuals choose to limit activity Most individuals choose to limit activity

Medical treatment No chan ge Normal medication as needed Increased frequency of medication use or additional medication Physician or
emergency room visit

3-75 1

3 This table is reproduced from the 1996 O 3 AQCD (Table 9-1, page 9-25) (U.S. Environmental Protection Agency, 1996). 4 An increase in nonspecific airway responsiveness of 100% is equivalent to a 50% decrease in PD 20 or PD 100 .3- 76 for many sensitive individuals and therefore would be considered adverse under ATS guidelines. For the purpose of estimating po tentially adverse lung function decrements in active healthy people, the CASAC indica ted that a focus on the mid to upper end of th e range of moderate levels of functional responses is most appropriate (e.g., FEV 1 decrements ≥ 15% but < 20%) 5

. However, for people with lung disease, even moderate functional (e.g., FEV 1 decrements > 10% but < 20%, lasting up to 24 hr) or symptomati c responses (e.g., frequent spontaneous cough, marked discomfort on exercise or with deep breath, wheeze accompanied by shortness of breath, lasting up to 24 hr) would likely interfere with no rmal activity for many individuals, and would likely result in additional and more frequent use of medication. For people with lung disease, large functional responses (e.g., FEV 1 decrements > 20%, lasting longer than 24 hrs) and/or severe symptomatic responses (e.g., persistent uncontrollable cough, severe discomfort on exercise or deep breath, persistent wheeze accomp anied by shortness of br eath, lasting longer than 24 hrs) would likely interf ere with normal activity for most individuals a nd would increase
the likelihood that these indi viduals would seek medical tr eatment. For the purpose of estimating potentially adverse lung function decrem ents in people with lu ng disease, the CASAC
indicated that a focu s on the lower end of the range of moderate levels of functional responses is most appropriate (e.g., FEV 1 decrements ≥ 10%). In judging the extent to which these impacts re present effects that s hould be regarded as
adverse to the health st atus of individuals, an additional f actor that has been considered in previous NAAQS reviews is whet her such effects are experienced repeatedly during the course of a year or only on a single o ccasion. While some experts woul d judge single occurrences of moderate responses to be a “ nuisance,” especially for health y individuals, a more general
consensus view of the adversit y of such moderate responses emerges as the frequency of
occurrence increases. Thus it ha s been judged that repeated occu rrences of moderate responses,
even in otherwise health y individuals, may be considered to be adverse since they could well set the stage for more serious illness (61 FR 65723). The CASAC panel in the last review expressed
a consensus view that these “crit eria for the determination of an adverse physiological response were reasonable” (Wolff, 1995). In 2000, the American Thoracic Society (ATS) published an official statement on “What
Constitutes an Adverse Health Effect of Air Pollution?” (ATS, 2000), which updated its earlier guidance (ATS, 1985). The revi sed guidance was intended to address new investigative approaches used to identify the effects of air pollution, and to re flect the concern for the impacts of air pollution on specific groups that had been expressed th rough the environmental justice

movement.

5 Transcript of CASAC meeting, day 8/24/06, page 149.3- 77 The new guidance builds upon a nd expands the 1985 definition of adversity in several ways. There is an increased focu s on quality of life measures as indicators of adve rsity. There is also a more specific consideration of population risk. Exposure to air pollution that increases the
risk of an adverse effect to th e entire population is adverse, ev en though it may not increase the risk of any individual to an unacceptable level. For example, a population of asthmatics could
have a distribution of lu ng function such that no i ndividual has a level asso ciated with significant impairment. Exposure to air pollution could shift the distribution to lower levels that still do not bring any individual to a level that is associated with clinically relevant effects. However, this
would be considered to be adverse because individuals within the population would have diminished reserve function, and therefore would be at increased risk if affected by another
agent.
Of the various effects of O 3 exposure that have been st udied, many would meet the ATS definition of adversity. Su ch effects include, for example, any detectible level of permanent lung function loss attributable to air pollution, in cluding both reductions in lung growth or acceleration of the age-related d ecline of lung function; exacerbations of disease in individuals with chronic cardiopulmonary diseases; reversible loss of lung function in combination with the presence of symptoms; as well as more serious effects such as those requiring medical care including hospitalization and, obviously, mortality. As discussed above, relatively small, reversible declines in lung function parameters may be of questionable significance in healthy people. However, a 5 to 15 % change in FEV 1 is
considered to have clinical importance to asthma morbidity (ATS 1991; Lebowitz et al. 1987; Lippmann, 1988). This is in line with the vi ew expressed by the CASA C that a focus on the lower end of the range of modera te levels of functional respon ses is most appropriate (e.g., FEV 1 decrements ≥ 10%) to estimate the risk of potentially adverse lung function responses in people with lung disease. The National Institutes of H ealth (1997) has stated th at a PEF below 80% of a person’s personal best indicates a need for continued me dication use in asthma tics. In Mortimer et al. (2002), O 3 was associated with in creased incidence of > 10% declines in morning PEF as well as morning symptoms, indicating that O 3 exposure may have clinica lly significant effects on
asthmatic children. Reflecting new investigative approaches, the ATS statement describes the potential
usefulness of research into the genetic basis for dise ase, including responses to environmental agents that will provide insight s into the mechanistic basis for susceptibility, and provide
markers of risk status . Likewise biomarkers , that are indicators of exposure, effect or susceptibility, may someday be useful in defi ning the point at whic h a response should be equated with an adverse effect. Based on concern for segments of the population that may be disproportionately exposed to environmental co ntaminants, or have ot her factors that may3- 78 increase susceptibility (e.g., genetic or nutritional f actors), there was a call for increased research
in these areas. Overall, the new guidance does not fundamentally change th e approach previously taken to define adversity, nor does it sugg est a need at this time to chan ge the structure or content of the tables describing gradation of severity and adversity of effects in Tables 3-2 or 3-3 above.

3.6.4 Estimation of Potential Numbers of Pe ople in At-Risk Susceptible Population Groups in the United States Although O 3 -related health risk esti mates may appear to be numerically small, their significance from an overall public health perspective is aff ected by the larg e numbers of individuals in potential risk groups. Several subpopulations may be identified as having increased susceptibility or vulnerability to adverse health effects from O 3 , including: older adults, children, individuals with preexis ting pulmonary disease, and those with higher exposure levels,
such as outdoor workers.
One consideration in the asse ssment of potential public heal th impacts is the size of various population groups that ma y be at increased risk for hea lth effects associated with O 3 - related air pollution exposure. Ta ble 8-4 in the CD summarizes in formation on the prevalence of chronic respiratory conditions in the U.S. population in 2002 and 2003 (Dey and Bloom, 2005; Lethbridge-Çejku et al., 2004). I ndividuals with preexi sting cardiopulmonary disease constitute a fairly large proportion of the population, with tens of millions of people included in each disease category. Of most con cern here are those individuals with preexisting respiratory conditions, with approximately 11% of U.S. adults and 13% of children having been diagnosed
with asthma and 6% of adults having COPD (chronic bronchi tis and/or emphysema). Table 8-5 in the CD provides further inform ation on the number of various specific respiratory conditions per 100 persons by age among the U.S. populatio n during the mid-1990s. Asthma prevalence tends to be higher in children than adults. In addition, subpopulations based on age group al so comprise substantial segments of the population that may be pot entially at risk for O 3 -related health impacts. Based on U.S. census data from 2003, about 26% of th e U.S. population are under 18 years of age and 12% are 65 years of age or older. Hence, large proportions of the U.S. populat ion are included in age groups that are considered likely to have increased su sceptibility and vulnerabil ity for health effects
from ambient O 3 exposure. The health statistics data illustrate what is know n as the “pyramid” of effects. At the top of the pyramid, there are approximately 2.5 millions deaths from all causes per year in the U.S. population, with about 100,000 deaths from chronic lower respirator y diseases (Kochanek et al., 2004). For respiratory health di seases, there ar e nearly 4 million hospita l discharges per year3- 79 (DeFrances et al., 2005), 14 m illion ED visits (McCaig and Bu rt, 2005), 112 million ambulatory care visits (Woodwell and Cherry, 2004), and an estimated 700 million restricted activity days per year due to respiratory cond itions (Adams et al., 1999). Comb ining small risk estimates with relatively large baseline levels of health outcomes can re sult in quite large public health impacts. Thus, even a small perc entage reduction in O 3 health impacts on cardiopu lmonary diseases would reflect a large number of avoided cases. Another key input for public health impact assessment is the ra nge of concentration response functions for various health outcomes. Epidemiolo gic studies have reported
associations between shor t-term exposure to O 3 with mortality, hospitalizations for pulmonary diseases, ED visits for asthma, reduced lung fu nction, and incidence of respiratory symptoms. Effect estimates for morbidity resp onses to short-term changes in O 3 tend to be larger and more variable in magnitude th an those for mortality.
In addition to attribution of risks fo r various health outcomes related to O 3 and other copollutants, important considerations in assessing the impact of O 3 on public health include the size of population groups at risk, as well as the concentration- response relationship and potential

identification of threshold leve ls. Taken together, based on the above information, it can be concluded that exposure to ambient O 3 likely has a significant impact on public health in the U.S.

3.7 SUMMARY AND CONCLUSIONS FOR OZONE HEALTH EFFECTS Based on dosimetric, experimental, and epid emiological evidence assessed in the 1996 CD, a set of findings and conclu sions were drawn regarding po tential health effects of O 3 exposure as of 1996. These conclu sions are integrated into th e Summary and Conclusions for Ozone Health Effects in the 2006 CD (section 8.8). The revised CD will be referred to as the
“2006 CD” in this section in orde r to be more easily distinguished from the “1996 CD.” Section
8.8 of the 2006 CD also has su mmarized the main conclusions derived from the integrated analysis of animal toxicology (2006 CD, Chapter 5), human expe rimental (2006 CD, Chapter 6) and epidemiological (2006 CD, Ch apter 7) studies that evaluate d evidence of health effects associated with short-term, prolong ed, and long-term exposures to O 3 alone or in combination with other pollutants commonly found in the ambien t air. This section summarizes conclusions
drawn from section 8.8 of the 2006 CD with respect to the hea lth effects associated with exposure to O 3 that are most relevant to our assessment of the adequacy of the current primary

O 3 standard and the identificati on of options to consider co ncerning potential alternative standards to protect public health wi th an adequate margin of safety.3- 80 3.7.1 Respiratory Morbidity Effects of Short-term Exposures to Ozone In the 1996 CD, it was concluded from assess ment of controlled hum an exposure studies
that short-term O 3 exposures to O 3 concentrations of > 0.08 ppm for 6.6 to 8 hr under moderate
exertion and > 0.12 ppm for 1 hr under heavy exertion cause decrements in lung function in children and increased lung functi on and respiratory symptoms in healthy adults and asthmatic individuals exposed (20 06 CD, p. 8-73). Lung inflammatory re sponses have been observed in healthy human adults following 6.6 hr O 3 exposures as low as 0.08 ppm (2006 CD, p. 8-75). Changes in lung function, respiratory symptoms , and lung inflammatory responses occur as a function of exposure concentra tion, duration, and level of exer tion. Such experimentally
demonstrated effects were consistent with and helped support the plausibility of epidemiological findings assessed in the 1996 CD regarding daily hospital ad missions and ED visits for respiratory causes. The 1996 CD concluded that group mean data from numerous controll ed human exposure and field studies of healthy subject s (18 to 45 years of age) exposed for 1 to 3 hr indicate that, in general, statistically significant pulmonary function decrements beyond the range of normal measurement variability (e.g., 3 to 5% for FEV 1 ) occur in subjects exposed:

• at >0.12 ppm O 3 after very heavy exerci se (competitive running).

• at >0.18 ppm O 3 after heavy exercise (easy jogging),

• at >0.30 ppm O 3 after moderate exerci se (brisk walking),

• at >0.37 ppm O 3 after light exercise (slow walking), and

• at >0.50 ppm O 3 when at rest. Small group mean changes (e.g., <5%) in FEV 1 have been observed in healthy young adults at levels as low as 0.12 ppm O 3 for 1 to 3 hr exposure pe riods. Also, lung function
decrements have been observed in children a nd adolescents at concen trations of 0.12 and 0.14 ppm O 3 with heavy exercise. Some individu als within a study may experience FEV 1 decrements in excess of 15% under these conditions, even when group mean decrements are less than 5%. For exposures of healthy, young adult subj ects performing modera te exercise during longer duration exposures (6 to 8 hr ), 5% group mean decrements in FEV 1 were observed at

• 0.08 ppm after O 3 5.6 hr,

• 0.10 ppm after O 3 4.6 hr, and

• 0.12 ppm after O 3 3 hr.3- 81 For these same subjects, 10% group mean FEV 1 decrements were observed at 0.12 ppm O 3 after
5.6 and 6.6 hr. As in the shorter duration studies , some individuals expe rience changes larger than those represented by group mean changes. The 2006 CD (section 8.8) conc ludes that newer meta-analy ses confirmed interindividual differences in lung function decrements reported in the 1996 CD. Age-sp ecific differences in lung function responses were also observed. Spiromet ric responses (i.e., decrements in lung function) in healthy adults exposed to near ambient O 3 levels typically resolve to near baseline within 4-6 hr. Meta-analyses of four controlled human expos ure studies (two new and two assessed in the 1996 CD) reporti ng the effects of prolonged ( 6.6 hr) exposures to 0.08 ppm O 3 during moderate exertion on lung function in young healthy adults (M=90, F=30; mean age 23 years) indicate an absolute FEV 1 decrease of 6%, whereas FEV 1 increased by 1% following fresh air exposures. Newer studies from Adams (200 2, 2006), as illustrated earlier in Figure 3-1B,
demonstrate notable interindi vidual variability for O 3 exposure concentrations of 0.04, 0.06 and 0.08 ppm. Following a continuous exposure to 0.08 ppm O 3 during intermittent, moderate exertion, the group mean FEV 1 decrement (corrected for filtered air) was 6%, but 23 % of subjects had FEV 1 decrements of 10% or more. Following exposure to 0.06 ppm O 3 , the group

mean FEV 1 decrement was less than 3%, but 7% of subjects had greater than 10% FEV 1 decrements (2006 CD, p. 8-18). However, as discussed in Section 3.3.1.1.1, we note that the pre- and post-exposure data pr esented in the Adams (2006) st udy show a small (< 3%) group

mean FEV 1 decrement following the 6.6-hr exposure at 0.06 ppm, which may be statistically significantly different fro m filtered air responses. A few controlled human exposure studies (Adams, 2003; 2006; Ha zucha et al., 1992) investigated a triangular exposure pattern at O 3 concentrations that ha d 6.6 to 8-hr averages between 0.08 and 0.12 ppm in order to mo re closely mimic typical ambient O 3 exposure patterns.
Greater overall FEV 1 decrements were observed with tr iangular exposures compared to the
constant or square-wave exposur es. Furthermore, peak FEV 1 decrements observed during triangular exposures were greater than those observed during squa re-wave patterns. At a lower average O 3 concentration of 0.06 ppm, no temporal (i.e., hour by hour responses) differences
were observed in FEV 1 decrements between square-wave and triangular exposure patterns. There was, however, a statistically significant effect of the 0.06 ppm triangul ar exposure on total respiratory symptoms following 5.6 and 6.6 h of exposure that was not observed for the 0.06 ppm square-wave exposure protocol . Results of these studies s uggest the potential for somewhat greater effects on lung function in ambient O 3 exposure scenarios that typically involve gradually increasing daily exposure up to a peak in the late afternoon an d a subsequent gradual decline (2006 CD, p. 8-19). The quantitati ve risk assessment, discusse d below in Chapter 5, provides3- 82 estimates of the percentages of schoo l age children likely to experience FEV 1 decrements greater than or equal to 10, 15, and 20% after 8-hr exposures to O 3 while engaged in moderate exertion. Decrements in lung function associated with ambient O 3 levels have al so been found in children attending summer camps in southern Ontario, Canada, in th e northeastern U.S., and in southern California (2006 CD, p. 8-74). The U.S. multicities study by Mortimer et al. (2002)
observed an association between acute O 3 exposure and the incidence of a > 10% decrement in morning PEF in asthmatic childr en. Meta-analyses indicate th at a 0.50-mL decrease in FEV 1 is associated with a 1 ppb increase in O 3 concentration. For preadoles cent children exposed to 120 ppb (0.12 ppm) ambient O 3 , this amounts to an average decrement of 2.4 to 3.0% in FEV 1 . Similar responses are reported for exercisi ng children and adolescents exposed to O 3 in ambient
air or O 3 in purified air for 1-2 hours.
The 1996 CD conc luded that an increase in the incidence of cough ha s been reported at O 3 concentrations as low as 0.12 ppm in healthy adults during 1 to 3 hr of exposure with very heavy exercise. Other respiratory symptoms, such as pa in on deep inspiration, s hortness of breath, and lower respiratory scores (i.e., a combination of several symptoms ), have been observed at 0.16 ppm to 0.18 ppm O 3 , 1-hr average, with heavy and very heavy exertion. Respiratory symptoms
also have been observed followi ng exposure to 0.08, 0.10 and 0.12 ppm O 3 for 6.6 hr with moderate exertion levels. Also, increases in non specific airway responsiven ess in healthy adults
at rest have been observed after 1 to 3 hr of exposures to 0.40 ppm but not to 0.20 ppm O 3 ; during very heavy exertion, these increases were observed at conc entrations as low as 0.18 ppm but not at 0.12 ppm O 3 . Increases in nonspecific airway responsiveness during the 6.6 hr exposures with moderate levels of exertion have been obse rved at 0.08, 0.10 and 0.12 ppm O 3
. The majority of asthma panel studies evaluated the associations of ambient O 3 with lung function and respiratory symptoms in asthmatic children. Results obtained from these studies show some inconsistencies, wi th some indicating significant positive associations and other smaller studies not finding such effects. Overall, how ever, the multicity study by Mortimer et al. (2002) and several credible single -city studies (e.g., Ge nt et al., 2003) indica te a fairly robust
association between ambient O 3 concentrations and increased re spiratory symptoms in moderate
to severe asthmatic chil dren (2006 CD, p. 8-35). The 2006 CD (p. 8-75) conclude s that lung inflammatory res ponses have been observed in healthy human adults following 6.6 hr O 3 exposures as low as 0.08 ppm. These responses
have been found even in the absence of O 3 -induced lung function d ecrements for some
individuals. Attenuati on of most inflammatory markers o ccurs with repeated exposures over several days, but none of the several markers of lung injury and permeab ility show attenuation,
which is indicative of contin ued lung tissue damage during re peated exposure. Laboratory animal studies have repo rted that 1 to 3 hr O 3 exposures as low as 0.1 to 0.5 ppm can cause (1)3- 83 lung inflammatory responses (e.g., increased ROS a nd inflammatory cytokines, influx of PMNs, and activation of AMs); (2) damage to epithelial airway tissues, (3 ) increases in permeability of both lung endothelium and epithelium, and (4) increases in susceptibi lity to infectious diseases due to modulation of lung host defenses. Consiste nt with the above result s of human and animal experimental studies, there is lim ited epidemiologic evidence of an association between acute
ambient O 3 exposure (1-hr max of about 0.1 ppm) and airway inflamma tion in children, all of which taken together is indica tive of a causal role for O 3 in inflammatory responses in the airways (2006 CD, p. 8-76). See Table 3.4 for a summary of shor t-term health effects of O 3 based on clinical studies assessed in both the 1996 CD and 2006 CD.
The 1996 CD concluded that increased O 3 levels are associated with increased hospital admissions and ED visits for resp iratory causes. Analyses from data in the northeastern U.S. suggested that O 3 air pollution is associated with a substantial portion of all summertime respiratory hospital visits and admissions. The 2006 CD conclude s (CD, p. 8-36) that a large multi-city and several single-city studies have in dicated a positive association between increased

O 3 levels (especially during the warm season) and increased risk for respiratory hospital
admissions and asthma ED visits.

3.7.2 Cardiovascular Morbidity Effects of Short-term Exposures to Ozone One health endpoint that was unrecognized in the 1996 CD, but is ad dressed in the 2006 CD, is O 3 -induced cardiovascular effe cts. Newly available evidence has emerged since 1996 which provides considerable plausibility for how O 3 could exert cardiovascular effects (2006 CD, p. 8-77). Exam ples of such O 3 -induced cardiovascular ef fects include: (1) O 3 -induced release from lung epithelial cells of PAF that may contribute to blood clot formation that would
increase the risk of serious car diovascular outcomes (e.g., heart attack, stroke, mortality); (2)
interactions of O 3 with surfactant component s in ELF of the lung resu lting in production of oxysterols and ROS that may exhibit PAF-like ac tivity contributing to clotting and/or exerting cytotoxic effects on lung and h eart cells; (3) possi ble mechanisms that may involve O 3 -induced
secretions of vasoconstrictive subs tances and/or effects on neuronal reflexes that may result in increased arterial blood pressure and/or altered electrophysiologic of heart rate or rhythm; (4)
associations between O 3 and various cardiac physiologic e ndpoints suggesti ng a potential relationship between O 3 exposure and altered HRV, ventricu lar arrhythmias, and incidence of MI; and (5) positive associations during th e warm season only between ambient O 3 concentrations and cardiovascular hospitalizations. While th e only controlled human exposure study that evaluated effects of O 3 exposure on the cardiovas cular system found no O 3 -induced differences in ECG or blood pressure in healt hy or hypertensive subjects, the study did report overall increases in myocardial work and heart rate, and impairme nt in pulmonary gas exchange.3-84 Table 3-4. Summary of Ozone-Induced Respir atory Health Effects from Clinical Studies 6

Health Effect Exerci se Level Prolonged Exposure Short-term Exposure Lowest Ozone Effect Level Pulmonary Function Decrements Moderate Moderate Moderate Moderate Competitive Very Heavy Heavy Moderate Light At rest 6.6 hr 6.6 hr 4.6 hr 3.0 hr 1 hr 1-3 hr 1-3 hr 1-3 hr 1-3 hr 1-3 hr 0.06 ppm 0.08 ppm 0.10 ppm 0.12 ppm 0.12-0.14 ppm 0.16 ppm 0.18 ppm 0.30 ppm 0.37 ppm 0.50 ppm Increased Respiratory Symptoms Moderate Moderate Very Heavy 6.6 hr 6.6 hr 1-3 hr 0.06 ppm 0.08 ppm 0.12 ppm Airway Responsiveness Moderate Very Heavy At rest 6.6 hr 1-3 hr 1-3 hr 0.08 ppm 0.18 ppm 0.40 ppm Respiratory Inflammation Moderate Very Heavy 6.6 hr 1-3 hr 0.08 ppm 0.20 ppm Changes in Host Defenses Moderate 6.6 hr 0.08 ppm

Decreased Exercise Performance Competitive 1 hr 0.18 ppm

Also, animal toxicological studies have reported O 3 -induced decreases in heart rate, mean arterial pressure and core temp erature. Overall, the 2006 CD (p. 8-77) concludes that this generally limited body of evidence is highly suggestive that O 3 directly and/or indirectly
contributes to cardiovas cular-related morbidity, but much re mains to be done to more fully
substantiate links between short-term ambient O 3 exposures and adverse ca rdiovascular effects.

3.7.3 Mortality-Related Effects of Short-term Exposures to Ozone

The 1996 CD concluded that an associ ation between daily mortality and O 3 concentration for areas with high O 3 levels (e.g., Los Angeles) was suggeste d. However, due to a very limited
number of studies available at th at time, there was in sufficient evidence to conclude that the observed association was likely ca usal. Since 1996, new data are available from large multicity

6 Information contained in this table is based on scientific data assessed in Chapters 6 and 8 of the 2006 CD.3-85 studies conducted in the U.S. a nd Europe, and several single-city studies conducted all over the world, as well as from several meta-analyses th at have combined information from multiple studies. The majority of these studies suggest an elevated risk of total nonaccidental mortality associated with acute exposure to O 3 , especially in the summe r or warm season when O 3 levels are typically high, with somewhat larger e ffect estimate sizes fo r associations with cardiovascular mortality (2006 CD, p. 7-175). Th e 2006 CD finds that the results from U.S. multicity time-series studies prov ide the strongest evid ence to-date for as sociations between
short-term O 3 exposure and mortality. These studies, along with recent meta-analyses, showed
consistent effect estimates that are unlikely to be co nfounded by PM, though the 2006 CD
observes that future work is ne eded to better understand the in fluence of model specifications on the effect estimates (2006 CD, p. 7-175). For cardiovascular mo rtality, the 2006 CD reports that effect estimates are consistently positive, falling in th e range of 1 to 8% increases per 40 ppb in
1-hr max O 3 (2006 CD, p. 7-107). Overall, the 2006 CD concludes that the majority of these findings suggest an elev ated risk of all-cause mortality associated with short-term O 3 exposure, especially in the summer or warm season when O 3 levels are typically high. Slightly greater
effects were observed for cardiovascu lar mortality (2006 CD, p. 7-175).

3.7.4 Health Effects of Repeated Short-term Exposures to Ozone

The 1996 CD drew several conclusions regarding repeated short-term O 3 exposures (2006 CD, p. 8-15). Partial or co mplete attenuation is obse rved for some of the O 3 -induced responses after more than 2 days of expos ure. After 5 days of exposure, lung function changes return to control levels with the greatest changes usuall y occurring on the second day, but the attenuation was reversed after 7 to 10 days without O 3 exposure. Most infla mmatory markers (e.g., PMN influx) attenuate after 5 days of exposure, but markers of cell dama ge (e.g., LDH enzyme activity) do not attenuate and cont inue to increase. Recovery of some inflammatory markers occurred a week to 10 days after exposure cease d, but some responses were not normal after 20 days. Animal studies suggest underlying cell damage continues thr oughout the attenuation process. Also, attenuation ma y alter normal di stribution of O 3 within the lungs, allowing more

O 3 to reach sensitive regions, po ssibly affecting lung defenses. Newer studies assessed in the 2006 CD (p. 8-74 and 8-75) supported all of thes e conclusions in addi tion to which it was concluded that repeated da ily, multi-hour exposure to lo wer concentrations of O 3 (0.125 ppm for 4 days) causes an increased res ponse to bronchial allergen challe nge in subjects w ith preexisting allergic airway disease, with or without asthma. In thes e subjects, changes in airway responsiveness after O 3 exposure appear to be resolved mo re slowly than changes in FEV 1 or respiratory symptoms.3-86 3.7.5 Confidence in Various Health Outcomes Associated with Short-term Exposures to Ozone In characterizing the extent to which relationships between the various health outcomes
discussed above and short-te rm exposures to ambient O 3 are likely causal, we note that several different factors have informed the judgments ma de in the CD and here. These factors include
the nature of the eviden ce (i.e., controlled human exposure, epidemiological, and/or toxicological studies) and the weight of eviden ce, including such considerations as biological plausibility, coherence of evidence, stre ngth of association, and consistency of evidence. In assessing the health effects data base for O 3 , it is clear that human studies provide the most directly applicable info rmation because they are not lim ited by the uncertainties of dosimetry differences and species sensitivity differences, which w ould need to be addressed in extrapolating animal toxicology data to human health effects. Cont rolled human exposure studies provide dat a with the highest level of confidence since th ey provide human effect s data under closely monitored conditions and can pr ovide clear exposure-response re lationships. Epidemiological data provide evidence of as sociations betw een ambient O 3 levels and more serious acute and
chronic health effects (e.g., hospital admissions and mortalit y) that cannot be assessed in controlled human exposure studie s. For these studies the degr ee of uncertainty regarding potential confounding variables (e.g., other pollutants, temperature) and other factors affects the
level of confidence that the health effect s being investigated are attributable to O 3 exposures, alone and in comb ination with othe r copollutants. In using a weight of eviden ce approach to inform judgm ents about the degree of
confidence that various health outcomes are likely to be caused by exposure to O 3 , confidence
increases as the number of studies and other factors, such as strength, consistency, and coherence of evidence, consistently reporting a particular health endpoin t grows. For example, there is a very high level of confidence that O 3 induces lung function decrem ents in healthy adults and children due in part to the do zens of studies consistently sh owing that these effects were observed. As noted above, the 2006 CD (p. 8-74) states that studies provid e clear evidence of causality for associations between short-term O 3 exposures and statistically significant declines in lung function in children, asthmatics and adults who exercise outdoors. An increase in respiratory symptoms (e.g., cough, shortness of br eath) has been observed in controlled human exposure studies of short-term O 3 exposures, and significant as sociations between ambient O 3 exposures and a wide variety of symptoms have been reported in epidemiology studies (2006 CD, p. 8-75). Aggregate population time-series studies showing robust associations with respiratory hospital admissions and ED visits are strongly sup ported by human clinical, animal toxicologic, and epidemiologic evidence for lung function decrements, respiratory symptoms,3-87 airway inflammation, and airway hyperreactivity . Taken together, the 2006 CD (p. 8-77)
concludes that the over all evidence supports the inference of a causal relationship between acute
ambient O 3 exposures and increased respiratory mo rbidity outcomes resulting in increased asthma ED visits and respirator y hospitalizations during the warm season. Recent epidemiologic
evidence has been characteriz ed in the CD (p. 8-78) as highly suggestive that O 3 directly or indirectly contributes to non-accidental and cardiopulmonary-related mortality.
As discussed above in section 3.5 and in section 8.6 of the 2006 CD, conclusions regarding biological plausibi lity, consistency, and cohe rence of evidence of O 3 -related health effects are drawn from the integration of epide miological studies with mechanistic information from controlled human exposure st udies and animal toxicological studies. This type of mechanistic linkage has been firmly establis hed for several respirat ory endpoints (e.g., lung function decrements, lung inflammation) but re mains far more equivocal for cardiovascular endpoints (e.g., cardiovascular-rela ted hospital admissions). Finall y, for epidemiological studies, strength of association refers to the magnitude of the associa tion and its statistical strength,
which includes assessment of bo th effects estimate size and precis ion (section 3.4.1). In general, when associations yield large rela tive risk estimates, it is less lik ely that the asso ciation could be completely accounted for by a potenti al confounder or some other bias . Consistency refers to the persistent finding of an associ ation between exposure and ou tcome in multiple studies of adequate power in different persons, places, circumstances and times (section 3.4.3). For example, the magnitude of effect estimates is relatively consistent across recent studies showing
association between short- term, but not long-term, O 3 exposure and mortality. Figure 3-5 summarizes our judgments for the various health outcom es discussed above concerning the extent to which relationships between various health outcomes and ambient O 3 exposures are likely causal . These judgments are informed by the conclusions and discussion in
the CD and in earlier sections of this chapter, reflecting the natu re of the evidence and overall weight of the evidence, and are taken into cons ideration in our quantita tive risk assessment, presented below in Chapter 5.

3.7.6 Health Effects of Long-te rm Exposures to Ozone In the 1996 CD, available data, primarily fro m animal toxicology st udies, indicated that exposure to O 3 for periods of months to years causes stru ctural changes in several regions of the respiratory tract (2006 CD, p. 8-79) . Effects may be of greatest importance in the CAR, where the gas exchange region and conducting airways me et. This region of th e lungs is typically affected in most human airway diseases. Howe ver, data from epidemio logical are limited or inconclusive, and data from clinical studies are lacking. Most information on chronic O 3 effects in the distal lungs cont inues to come from animal toxicology studies.Figure 3-5. Qualitative Characterization of Ozone-Related Health Effect Outcomes

-Lung function decrements in healthy children -Lung function decrements in asthmatic children -Lung function decrements in healthy adults -Respiratory symptoms in asthmatic children -Respiratory symptoms in healthy adults -Increased lung inflammation -Aggravation of asthma (i.e., increased medication usage, increased asthma attacks)

-Respiratory-related hospital admissions -Respiratory related emergency department visits -Respiratory-related doctors visits

-Increased school absences -Respiratory-related mortality during the O 3 season

-Cardiorespiratory-related mortality during the O 3 season -Total nonaccidental mortality during the O 3 season

-Cardiovascular-related hospital admissions Characterization Overall Confidence in Causal Relationship With Ambient Ozone

Causal

Suggestive

3-883-89 What had been viewed previously as an apparent lack of reversibility of O 3 -induced effects with a clean air recovery period has b een investigated since 1996 with animal toxicology studies using exposure regimens simulating a seasonal exposure pattern. One long-term study exposed rhesus monkeys to a simulated seasonal O 3 pattern (0.5 ppm O 3 8hr/day for 5 days, every 14 days for 11 episodes) and reported: (1) remodeling in the distal airways; (2) abnormalities in tracheal basement membrane; (3) eosinophil accumulation in conducting airways; and (4) decrements in airway innervation. These find ings support and advan ce the earlier inform ation suggestive of injury and repair processes wh ich are caused by seasonal O 3 exposures (2006 CD, p.8-79). Epidemiological studi es investigating chronic effects in humans followi ng long-term exposures

to O 3 have provided only limited su ggestive evidence. Further investigation will be necessary
before we are able to draw firmer conc lusions about chronic health effects of O 3 in human populations.

3.7.7 Health Effects of Pollutant Mixtures Containing Ozone In the 1996 CD, it was recogniz ed that coexposure to O 3 and other pollutants, such as

NO 2 , SO 2 , H 2 SO 4 , HNO 3 , or CO, showed additive response fo r lung spirometry or respiratory symptoms (2006 CD, p. 8-82). Since 1996, most animal toxicology stud ies investigating O 3 in a
mixture with NO 2 and H 2 SO 4 have shown that effects can be additive, synergistic, or even antagonistic, depending on the expos ure regimen and the endpoint st udied. Ozone has served for a long time as a surrogate or in dicator for the overall photochemical oxida nt mix. It is well recognized that the observed ef fects may be due to component s of that mix alone or in
combination with O 3 and other gases and PM in the ambient air. Although the issue of exposure to copollutants was previously de scribed as poorly understood, especi ally with regard to chronic effects, newer information from human and an imal studies of binary mixtures containing O 3 suggest potential interactions depending on th e exposure regimen and pol lutant mix (CD, p. 8- 82). Examples of this newer information include: (1) contin uous exposure to SO 2 and NO 2 increased inhaled O 3 bolus absorption, while co ntinuous exposure to O 3 decreased O 3 bolus absorption; (2) asthmatics exhibited enhanced airway reactivity to house dust mite allergen following exposures to O 3 , NO 2 and the combination of the tw o gases; however, spirometric response was impaired only by O 3 and O 3 + NO 2 at higher concentrations; and (3) animal toxicology studies with O 3 in mixture with NO 2 , formaldehyde, and PM demonstrated additive, synergistic, or antagonistic effects depending on the exposu re regimen and the endpoints
evaluated. One controlled-exposure study of children, de signed to approximate conditions of an epidemiological study by ma tching population and exposur e atmosphere (0.1 ppm O 3 , 0.1 ppm
SO 2 , and 101 ug/m 2 H 2 SO 4 ), failed to support the findings of the epidemiologi cal study. This3-90 demonstrates the difficulty of trying to link outcomes of epidem iological studies and controlledexposure studies with pollutant mixtures.

3.7.8 Populations at Risk/Susce ptibility Factors Associat ed with Ozone Exposure The 1996 CD (2006 CD, p. 8-80) id entified several factors that may increase sensitivity

to O 3 of population groups, includ ing: (1) biological varia tion in responsiveness to O 3 ; (2) preexisting lung disease (e.g., asth ma); (3) activity patterns (e.g., exertion levels); (4) personal exposure history (e.g., time spent indoors v. out doors); and (5) person al factors (e.g., age, nutritional status, gender, smoking hi story, ethnicity). Based on th e information assessed in the 1996 CD (2006 CD, p. 8-80), populati on groups that demonstrated increased responsiveness to
ambient concentrations of O 3 consisted of exercising, health y and asthmatic individuals, including children, adolescents, and adults. Since 1996, eviden ce from controlled-exposure human and animal studies, as well as from epidemiological studi es, has provided further support for these and other susceptibility factors and populations at ri sk. For example, controlledexposure human studies contin ue to show differential biological response to O 3 based on physical activity (exertion) and age. These stud ies demonstrate a large variation in sensitivity and responsiveness to O 3 , although specific factors that contribut e to this intersubject variability are yet to be identified. Asso ciations of increased summertim e hospital admissions for asthma
with ambient O 3 levels suggest that indivi duals with these respiratory diseases are populations at
risk to O 3 exposure effects. Also, based on O 3 -induced differential response in lung inflammation and airway responsiveness, asth matic adults and child ren appear to have potentially increased susceptibility to O 3 . There is limited evidence from epidemiologic studies and no evidence from controlled-exposure human studies which suggest that individuals with
COPD are more sensitive to health effects of O 3 . There is some animal t oxicology and limited epidemio logic evidence which has demonstrated the importance of genetic background in O 3 susceptibility. Ge netic and molecular characterization studies of experi mental animals have identified ge netic loci responsible for both sensitivity and resistance. Taking all of this information into account, the CD (p. 8-80 to 8-81) concludes that exercising (moderate to high physic al exertion) healthy and asthma tic adults, adolescents, and children appear to exhibit increa sed responsiveness to ambient O 3 levels and continue to be

considered at incr eased risk of O 3 -induced health effects. Als o, any individual with respiratory

or cardiovascular disease or a ny healthy individual who is enga ged in vigorous physical activity outdoors during periods when O 3 levels are high (e.g., active outdoor children) is potentially at

increased risk to O 3 -induced health effects. In additi on, healthy individual s and those with3-91 cardiorespiratory impairment (e .g., those with asthma or card iovascular disease) who are “hyperresponsive” to O 3 exposure (i.e., exhibit much high er than normal lung function decrements and/or respiratory symptoms) w ould be considered at greater risk to O 3 exposure. Finally, individuals who are more likely to be exposed to air po llution while engaged in physical activity (e.g., outdoor workers) a nd those with genetic polymor phisms for antioxidant enzymes and inflammatory genes may be at heightened risk of effects of O 3 (2006 CD, p. 8-81).3-92 References
Abbey, D. E.; Nishino, N.; McDonnell, W. F.; Burchette, R. J.; Knutsen, S. F.; Beeson, W. L.; Yang, J. X. (1999) Long-term inhalable particles and other air pollutants related to mortality in nonsmokers. Am. J. Respir. Crit. Care Med. 159: 373-382. Adams, W. C. (2000a) Feasibility study of prolonged ozone inhalation exposur e via face mask. Inhalation Toxicol. 12: 299-313. Adams, W. C. (2000b) Ozone dose-response effects of vari ed equivalent minute ventilation rates. J. Exposure Anal. Environ. Epidemiol. 10: 217-226. Adams, W. C. (2002) Comparison of chamber and face-mask 6.6-hr exposures to ozone on pulmonary function and symptoms responses. Inhalation Toxicol. 14: 745-764. Adams, W. C. (2003a) Comparison of chamber and face ma sk 6.6-hr exposure to 0.08 ppm ozone via square-wave and triangular profiles on pulmonary responses. Inhalation Toxicol. 15: 265-281. Adams, W. C. (2003b) Relation of pulmonary responses induced by 6.6 h exposures to 0.08 ppm ozone and 2-h exposures to 0.30 ppm via chamber and face-mask inhalation. Inhalation Toxicol. 15: 745-759. Adams, W. C. (2006) Comparison of chamber 6.6 h exposures to 0.04-0.08 ppm ozone via square-wave and triangular profiles on pulmonary responses. Inhalation Toxicol. 18: 127-136. Adams, W. C.; Schelegle, E. S. (1983) Ozone and high ventilation effects on pulmonary function and endurance performance. J. Appl. Physiol.: Respir. Environ. Exercise Physiol. 55: 805-812. Adams, W. C.; Ollison, W. M. (1997) Effects of prolonged simulated ambient ozone dosing patterns on human pulmonary function and symptomatology. Presented at: 90th annual meeting of the Air & Waste Management Association; June; Toronto, Ontario, Canada. Pittsburgh, PA: Air & Waste Management Association; paper no. 97-MP9.02. Adams, P. F.; Hendershot, G. E.; Marano, M. A. (1999) Current estimates from the National Health Interview Survey, 1996. Hyattsville, MD: U.S. Department of Health and Human Services, Public Health Service, National Center for Health Statistics; DHHS publication no. (PHS) 99-1528. (Vital and health statistics: v. 10, data from the National Health Survey, no. 200). Available: http://www.cdc.gov/nchs/products/pubs/pubd/series/sr10/pre-200/pre-200.htm [12 March, 2001]. Alexis, N.; Urch, B.; Tarlo, S.; Corey, P.; Pengelly, D.; O'Byrne, P.; Silverman, F. (2000) Cyclooxygenase metabolites play a different role in ozone-induced pul monary function decline in asthmatics compared to normals. Inhalation Toxicol. 12: 1205-1224. American Academy of Pediatrics, Committee on Environm ental Health. (2004) Ambient air pollution: health hazards to children. Pe diatrics 114: 1699-1707. American Thoracic Society (19 85) Guidelines as to what constitutes an adverse respiratory health effect, with special reference to epidemiological studies of air po llution. Am. Rev. Respir. Dis. 131: 666-668. American Thoracic Society (19 91) Lung function testing: selection of reference values and interpreatative strategies. Am. Rev. Respir. Dis. 144: 1202-1218. American Thoracic Society (20 00) What constitutes an adverse health eff ect of air pollution? Am. J. Respir. Crit. Care Med. 161: 665-673. Anderson, H. R.; Ponce de Leon, A.; Bland, J. M.; Bower, J. S.; Strachan, D. P. (1996) Air pollution and daily mortality in London: 1987-92. Br. Med. J. 312: 665-669. Anderson, H. R.; Spix, C.; Medina, S.; Schouten, J. P.; Castellsague, J.; Rossi, G.; Zmirou, D.; Touloumi, G.; Wojtyniak, B.; Ponka, A.; Bacharov a, L.; Schwartz, J.; Katsouyanni, K. (1997) Air pollution and daily admissions for chronic obstructive pu lmonary disease in 6 European cities : results from the APHEA project. Eur. Respir. J. 10: 1064-1071. Anderson, H. R.; Ponce de Leon, A.; Bland, J. M.; Bower, J. S.; Emberlin, J.; Strachen, D. P. (1998) Air pollution, pollens, and daily admissions for asthma in London 1987-92. Thorax 53: 842-848. Arito, H.; Takahashi, M.; Iwasaki, T.; Uchiyama, I. ( 1997) Age-related changes in ventilatory and heart rate responses to acute ozone exposure in the conscious rat. Ind. Health 35: 78-86. Aris, R. M.; Christian, D.; Hearne, P. Q.; Kerr, K.; Finkbeiner, W. E.; Balmes, J. R. (1993) Ozone-induced airway inflammation in human subjects as determined by airway lavage and biopsy. Am. Rev. Respir. Dis. 148: 1363-1372. Aris, R. M.; Tager, I.; Christian, D.; Kelly, T.; Balmes, J. R. (1995) Methacholine responsiveness is not associated with O 3 -induced decreases in FEV 1 . Chest 107: 621-628. Avol, E. L.; Trim, S. C.; Little, D. E.; Spier, C. E.; Smith, M. N.; Peng, R.-C.; Linn, W. S.; Hackney, J. D.; Gross, K. B.; D'Arcy, J. B.; Gibbons, D.; Higgins, I. T. T. (1990) Ozone exposure and lung function in children3-93 attending a southern California summer camp. Presented at: 83rd annual meeting and exhibition of the Air & Waste Management Association; June; Pittsburg h, PA. Pittsburgh, PA: Air & Waste Management Association; paper no. 90-150.3. Avol, E. L.; Navidi, W. C.; Rappaport, E. B.; Peters, J. M. (1998) Acute effects of ambient ozone on asthmatic, wheezy, and healthy children. Ca mbridge, MA: Health Effects In stitute; research report no. 82. Avol, E. L.; Gauderman, W. J.; Tan, S. M.; London, S. J.; Peters, J. M. (2001) Respiratory effects of relocating to areas of differing air pollution levels. Am. J. Respir. Crit. Care Med. 164: 2067-2072. Bates, D. V.; Baker-Anderson, M.; Sizto, R. (1990) Asthma attack periodicity: a study of hospital emergency visits in Vancouver. Environ. Res. 51: 51-70. Bates, D. V.; Sizto, R. (1983) Relationship between air pollutant levels and hospital admissions in Southern Ontario. Can. J. Public Health 74: 117-122. Bates, D. V.; Sizto, R. (1987) Air pollution and hospital admissions in sout hern Ontario: the acid summer haze effect. Environ. Res. 43: 317-331. Bates, D. V.; Sizto, R. (1989) The Ontario Air Pollution st udy: identification of the caus ative agent. Environ. Health Perspect. 79: 69-72. Bayram, H.; Rusznak, C.; Khair, O. A.; Sapsford, R. J.; Abdelaziz, M. M. (2002) Effect of ozone and nitrogen dioxide on the permeability of bronchial epithelial cell cultures of non-asthmatic and asthmatic subjects. Clin. Exp. Allergy 32: 1285-1292. Beeson, W. L.; Abbey, D. E.; Knutsen, S. F. (1998) Long-term concentrations of ambient air pollutants and incident lung cancer in California adults: results from the AHSMOG study. Environ. Health Perspect. 106: 813-823. Bell, M. L.; McDermott, A.; Zeger, S. L.; Samet, J. M. ; Dominici, F. (2004) Ozone and short-term mortality in 95 US urban communities, 1987-2000. JAMA J. Am. Med. Assoc. 292: 2372-2378. Bell, M. L.; Dominici, F.; Samet, J. M. (2005) A meta-ana lysis of time-series studies of ozone and mortality with comparison to the national morbidity, mortality, and air pollution study. Epidemiology 16: 436-445. Bell, M. L.; Peng, R. D.; Dominici, F. (2006) The exposure-response curve for ozone and risk of mortality and the adequacy of current ozone regulations. Environ. Health Perspect.: in press, doi:10.1289/ehp.8816. Available: http://dx.doi.org/ [23 January, 2006]. Bell, M. L. (2006) Community-specific maximum likelihood estimates of O 3 -related excess risk in mortality for the NMMAPS U.S. 95 communities study [personal communication with attachments to Jee Young Kim]. New Haven, CT: Yale University School of Forestry and Environmental Studies; January 6. Blomberg, A.; Mudway, I. S.; Nordenhäll, C.; Hedenström, H.; Kelly, F. J.; Frew, A. J.; Holgate, S. T.; Sandström, T. (1999) Ozone-induced lung function decrements do not correlate with early airway inflammatory or antioxidant responses. Eur. Respir. J. 13: 1418-1428. Blomberg, A.; Mudway, I.; Svensson, M.; Hagenbjörk-Gustafsson, A.; Thomasson, L.; Helleday, R.; Dumont, X.; Forsberg, B.; Nordberg, G.; Bernard, A. (2003) Clara cell protein as a biomarker for ozone-induced lung injury in humans. Eur. Respir. J. 22: 883-888. Borja-Aburto, V. H.; Loomis, D. P.; Bangdiwala, S. I.; Shy, C. M.; Rascon-Pacheco, R. A. (1997) Ozone, suspended particulates, and daily mortality in Mexico City. Am. J. Epidemiol. 145: 258-268. Bosson, J.; Stenfors, N.; Bucht, A.; Helleday, R.; Pourazar, J.; Holgate, S. T.; Kelly, F. J.; Sandström, T.; Wilson, S.; Frew, A. J.; Blomberg, A. (2003) Ozone-induced bronchial epithelial cytokine expression differs between healthy and asthmatic subjects. Clin. Exp. Allergy 33: 777-782. Brauer, M.; Blair, J.; Vedal, S. (1996) Effect of ambient ozone exposure on lung function in farm workers. Am. J. Respir. Crit. Care Med. 154: 981-987. Brauer, M; Brumm, J.; Vedal, S.; Petkau, A.J. (2002) Exposure misclassification and threshold concentrations in time-series analyses of air pollution heal th effects. Risk Anal. 22: 1183-1193. Bremner, S. A.; Anderson, H. R.; Atkinson, R. W.; McMichael, A. J.; Strachan, D. P.; Bland, J. M.; Bower, J. S. (1999) Short term associations between outdoor air pollution and mortality in London 1992-4. Occup. Environ. Med. 56: 237-244. Brook, R. D.; Brook, J. R.; Urch, B.; Vincent, R.; Rajagopalan, S.; Silverman, F. (2002) Inhalation of fine particulate air pollution and ozone causes acute arterial vasoconstriction in healthy adults. Circulation 105: 1534-1536. Brook, R. D.; Franklin, B.; Cascio, W.; Hong, Y.; Howard, G.; Lipsett, M.; Luepker, R.; Mittleman, M.; Samet, J.; Smith, S. C., Jr.; Tager, I. (2004) Air pollution and cardiovascular disease. A statement for healthcare professionals from the Expert Panel on Population and Prevention Science of the American Heart Association. Circulation 109: 2655-2671.3-94 Burnett, R. T.; Dales, R. E.; Raizenne, M. E.; Krewski, D.; Summers, P. W.; Roberts, G. R.; Raad-Young, M.; Dann, T.; Brook, J. (1994) Effects of low ambient levels of ozone and sulfates on the frequency of respiratory admissions to Ontario hospitals. Environ. Res. 65: 172-194. Burnett, R. T.; Brook, J. R.; Yung, W. T.; Dales, R. E.; Krewski, D. (1997a) Association between ozone and hospitalization for respiratory diseases in 16 Canadian cities. Environ. Res. 72: 24-31. Burnett, R. T.; Brook, J. R.; Yung, W. T.; Dales, R. E.; Krewski, D. (1997b) Association between ozone and hospitalization for respiratory diseases in 16 Canadian cities. Environ. Res. 72: 24-31. Burnett, R. T.; Smith-Doiron, M.; Stieb, D.; Cakmak, S.; Brook, J. R. (1999) Effects of particulate and gaseous air pollution on cardiorespiratory hospitalizations. Arch. Environ. Health 54: 130-139. Burnett, R. T.; Smith-Doiron, M.; Stieb, D.; Raizenne, M. E.; Brook, J. R.; Dales, R. E.; Leech, J. A.; Cakmak, S.; Krewski, D. (2001) Association between ozone and hospitalization for acute respiratory diseases in children less than 2 years of age. Am. J. Epidemiol. 153: 444-452. Calderón-Garciduenas, L.; Rodriguez-Alcaraz, A.; García, R.; Ramírez, L.; Barragan, G. (1995) Nasal inflammatory responses in children exposed to a polluted urban atmosphere. J. Toxicol. Environ. Health 45: 427-437. Calderón-Garciduenas, L.; Osnaya, N.; Rodríguez-Alcaraz, A.; Villarreal-Calderón, A. (1997) DNA damage in nasal respiratory epithelium from children exposed to urban pollution. Environ. Mol. Mutagen. 30: 11-20. Calderón-Garciduenas, L.; Wen-Wang, L.; Zhang, Y.-J.; Rodriguez-Alcaraz, A.; Osnaya, N.; Villarreal-Calderón, A.; Santella, R. M. (1999) 8-hydroxy-2'-deoxyguanosine, a major mutagenic oxidative DNA lesion, and DNA strand breaks in nasal respiratory epithelium of children exposed to urban pollution. Environ. Health Perspect. 107: 469-474. Calderón-Garciduenas, L.; Valencia-Sal azar, G.; Rodríguez-Alcaraz , A.; Gambling, T. M.; García, R.; Osnaya, N.; Villarreal-Calderon, A.; Devlin, R. B.; Carson, J. L. (2001) Ultrastructural na sal pathology in children chronically and sequentially exposed to air pollutants. Am. J. Respir. Cell Mol. Biol. 24: 132-138. Calderón-Garciduenas, L.; Mora-Tiscar eno, A.; Fordham, L. A.; Valencia -Salazar, G.; Chung, C. J.; RodriguezAlcaraz, A.; Paredes, R.; Variakojis , D.; Villarreal-Calderón, A.; Flores-Camacho, L.; Antunez-Solis, A.; Henríquez-Roldán, C.; Hazucha, M. J. (2003) Respiratory damage in children exposed to urban pollution. Pediatr. Pulmonol. 36: 148-161. Cassino, C.; Ito, K.; Bader, I.; Ciotoli, C.; Thurston, G.; Reibman, J. (1999) Cigarette smoking and ozone-associated emergency department use for asthma by adults in New York City. Am. J. Respir. Crit. Care Med. 159: 1773- 1779. Centers for Disease Control and Prevention. (2004) The health consequences of smoking: a report of the Surgeon General. Atlanta, GA: U.S. Department of Health an d Human Services, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health. Available: http://www.cdc.gov/tobacco/sgr/sgr_2004/chapters.htm (18 August, 2004). Chen, L.; Jennison, B. L.; Yang, W.; Omaye, S. T. (2000) Elementary school absenteeism and air pollution. Inhalation Toxicol. 12: 997-1016. Chen, C.-Y.; Bonham, A. C.; Plopper, C. G.; Joad, J. P. (2003) Plasticity in respiratory motor control: selected contribution: neuroplasticity in nucleus tractus solitarius neurons following episodic ozone exposure in infant primates. J. Appl. Physiol. 94: 819-827. Chock, D. P.; Winkler, S. L.; Chen, C. (2000) A study of the association between daily mortality and ambient air pollutant concentrations in Pittsburgh, Pennsylvania. J. Air Waste Manage. Assoc. 50: 1481-1500. Christian, D. L.; Chen, L. L.; Scannell, C. H.; Ferrando, R. E.; Welch, B. S.; Balmes, J. R. (1998) Ozone-induced inflammation is attenuated with multiday exposure. Am. J. Respir. Crit. Care Med. 158: 532-537. Cody, R. P.; Weisel, C. P.; Birnbaum, G.; Lioy, P. J. (1992) The effect of ozone associated with summertime photochemical smog on the frequency of asthma visits to hospital emergency departments. Environ. Res. 58: 184-194. Daly, C.; Fox, K.; Henein, M. (2002) Natriuretic peptides in the diagnosis of heart disease--first amongst equals? Int. J. Cardiol. 84: 107-113. DeFrances, C. J.; Hall, M. J.; Podgornik, M. N. (2005) 2003 National Hospital Discharge Survey. Hyattsville, MD: National Center for Health Statistics; DHHS publication no. (PHS) 2004-1250. (Advance data from vital and health statistics; no. 359). Available: http://www.cdc.gov/nchs/data/ad/ad359.pdf [3 August, 2005]. Delfino, R. J.; Becklake, M. R.; Hanley, J. A. (1994) The relationship of urgent hospital admissions for respiratory illnesses to photochemical air pollution levels in Montreal. Environ. Res. 67: 1-19. Delfino, R. J.; Coate, B. D.; Zeiger, R. S.; Seltzer, J. M.; Street, D. H.; Koutra kis, P. (1996) Daily asthma severity in relation to personal ozone exposure and outdoor fungal spores. Am. J. Respir. Crit. Care Med. 154: 633-641.3-95 Delfino, R. J.; Zeiger, R. S.; Seltzer, J. M.; Street, D. H.; Matteucci, R. M.; Anderson, P. R.; Koutrakis, P. (1997a) The effect of outdoor fungal spore concentrations on daily asthma severity. Environ. Health Perspect. 105: 622-635. Delfino, R. J.; Murphy-Moulton, A. M.; Burnett, R. T.; Brook, J. R.; Becklake, M. R. (1997b) Effects of air pollution on emergency room visits for respiratory illn esses in Montreal, Quebec. Am. J. Respir. Crit. Care Med. 155: 568-576. Delfino, R. J.; Zeiger, R. S.; Seltzer, J. M.; Street, D. H. (1998) Symptoms in pediatric asthmatics and air pollution: differences in effects by symptom severity, anti-infl ammatory medication use and particulate averaging time. Environ. Health Perspect. 106: 751-761. Delfino, R. J.; Gone, H.; Linn, W. S.; Pellizzari, E. D.; Hu, Y. (2003) Asthma symptoms in Hispanic children and daily ambient exposures to toxic and criteria air pollutants. Environ. Health Perspect. 111: 647-656. Desqueyroux, H.; Pujet, J.-C.; Prosper, M.; Squinazi, F.; Momas, I. (2002a) Short-term effects of low-level air pollution on respiratory health of adults suffering from moderate to severe asthma. Environ. Res. A 89: 29- 37. Desqueyroux, H.; Pujet, J.-C.; Prosper, M.; Le Moullec, Y.; Momas, I. (2002b) Effects of air pollution on adults with chronic obstructive pulmonary disease. Arch. Environ. Health 57: 554-560. Devlin, R. B.; Folinsbee, L. J.; Biscardi, F.; Hatch, G.; Becker, S.; Madden, M. C.; Robbins, M.; Koren, H. S. (1997) Inflammation and cell damage induced by repeated exposure of humans to ozone. Inhalation Toxicol. 9: 211- 235. Devlin, R. B.; McDonnell, W. F.; Mann, R.; Becker, S.; Ho use, D. E.; Schreinemachers, D.; Koren, H. S. (1991) Exposure of humans to ambient levels of ozone for 6.6 hrs causes cellular and biochemical changes in the lung. Am. J. Respir. Cell Mol. Biol. 4: 72-81. Devlin, R. B.; McDonnell, W. F.; Koren, H. S.; Beck er, S. (1990) Prolonged exposure of humans to 0.10 and 0.08 ppm ozone results in inflammation in the lung. Presented at: 83rd annual meeting of the Air & Waste Management Association; June; Pittsburgh, PA. Pittsburgh, PA: Air & Waste Management Association; paper no. 90-150.2. Dey, A. N.; Bloom, B. (2005) Summary health statistics for U.S. children: National Health Interview Survey, 2003. Hyattsville, MD: U.S. Department of Health & Human Se rvices, National Center for Health Statistics. (Vital and health statistics, series 10, no. 223). Available: http://www.cdc.gov/nchs/data/series/sr_10/sr10_223.pdf [3 August, 2005]. Dietert, R. R.; Etzel, R. A.; Chen, D.; Halonen, M.; Holladay, S. D.; Jarabek, A. M.; Landreth, K.; Peden, D. B.; Pinkerton, K.; Smialowicz, R. J.; Zoetis, T. (2000) Workshop to identify critical window of exposure for children's health: immune and respiratory systems work group summary. Environ. Health Perspect. Suppl. 108(3): 483-490. Dimeo, M. J.; Glenn, M. G.; Holtzman, M. J.; Sheller, J. R.; Nadel, J. A.; Boushey, H. A. (1981) Threshold concentration of ozone causing an increase in bronchial reactivity in humans and adaptation with repeated exposures. Am. Rev. Respir. Dis. 124: 245-248. Dockery, D. W.; Schwartz, J.; Spengler, J. D. (1992) Air pollution and daily mortality: associations with particulates and acid aerosols. Environ. Res. 59: 362-373. Dockery, D. W.; Pope, C. A., III; Xu, X.; Spengler, J. D.; Ware, J. H.; Fay, M. E.; Ferris, B. G., Jr.; Speizer, F. E. (1993) An association between air pollution and mortality in six U.S. cities. N. Engl. J. Med. 329: 1753-1759. Dockery, D. W.; Luttmann-Gibson, H.; Rich, D. Q.; Link, M. S.; Mittleman, M. A.; Gold, D. R.; Koutrakis, P.; Schwartz, J. D.; Verrier, R. L. (2005) Association of air pollution with increased incidence of ventricular tachyarrhythmias recorded by implanted cardioverter defibrillators. Environ. Health Perspect. 113: 670-674. Dominici, F.; McDermott, A.; Daniels, M.; Zeger, S. L.; Samet, J. M. (2003) Mortality among residents of 90 cities. In: Revised analyses of time-series studies of air pollution and health. Special report. Boston, MA: Health Effects Institute; pp. 9-24. Available: http://www.h ealtheffects.org/Pubs/TimeSeries.pdf [12 May, 2004]. Dormans, J. A. M. A.; Van Bree, L.; Boere, A. J. F.; Marra, M.; Rombout, P. J. A. (1999) Interspecies differences in time course of pulmonary toxicity following repeated exposure to ozone. Inhalation Toxicol. 11: 309-329. Evans, M. J.; Fanucchi, M. V.; Baker, G. L.; Van Winkle, L. S.; Pantle, L. M.; Nishio, S. J.; Schelegle, E. S.; Gershwhin, L. J.; Miller, L. A.; Hyde, D. M.; Sannes, P. L.; Plopper, C. G. (2003) Atypical development of the tracheal basement membrane zone of infant rhesus monkeys exposed to ozone and allergen. Am. J. Physiol. 285: L931-L939. Fairley, D. (1999) Daily mortality and air pollution in Santa Clara County, California: 1989-1996. Environ. Health Perspect. 107: 637-641.3-96 Fairley, D. (2003) Mortality and air pollution for Santa Clara County, California, 1989-1996. In: Revised analyses of time-series studies of air pollution and health. Sp ecial report. Boston, MA: Health Effects Institute; pp. 97-106. Available: http://www.healtheffect s.org/Pubs/TimeSeries.pdf [18 October, 2004]. Fanucchi, M. V.; Hotchkiss, J. A.; Harkema, J. R. (1998) Endotoxin potentiates ozone-induced mucous cell metaplasia in rat nasal epithelium. Toxicol. Appl. Pharmacol. 152: 1-9. Folinsbee, L. J.; Silverman, F.; Shephard, R. J. (1977) Decrease of maximum work performance following ozone exposure. J. Appl. Physiol.: Respir. Environ. Exercise Physiol. 42: 531-536. Folinsbee, L. J.; McDonnell, W. F. ; Horstman, D. H. (1988) Pulmonary f unction and symptom responses after 6.6-hr exposure to 0.12 ppm ozone with moderate exercise. JAPCA 38: 28-35. Folinsbee, L. J.; Horstman, D. H.; Kehrl, H. R.; Harder, S.; Abdul-Salaam, S.; Ives, P. J. (1994) Respiratory responses to repeated prolonged exposure to 0.12 ppm ozone. Am. J. Respir. Crit. Care Med. 149: 98-105. Folinsbee, L. J.; Hazucha, M. J. (2000) Time course of response to ozone exposure in healthy adult females. Inhalation Toxicol. 12: 151-167. Foster, W. M.; Silver, J. A.; Groth, M. L. (1993) Exposure to ozone alters regional function and particle dosimetry in the human lung. J. Appl. Physiol. 75: 1938-1945. Foster, W. M.; Weinmann, G. G.; Menkes, E.; Macri, K. (1997) Acute exposure of humans to ozone impairs small airway function. Ann. Occup. Hyg. 41(suppl. 1): 659-666. Foxcroft, W. J.; Adams, W. C. (1986) Effects of ozone exposure on four consecutive days on work performance and V _O2max. J. Appl. Physiol. 61: 960-966. Friedman, M. S.; Powell, K. E.; Hutwagner, L.; Graham, L. M.; Teague, W. G. (2001) Impact of changes in transportation and commuting behaviors during the 1996 summer olympic games in Atlanta on air quality and childhood asthma. JAMA J. Am. Med. Assoc. 285: 897-905. Frischer, T.; Studnicka, M.; Gartner, C.; Tauber, E.; Horak, F.; Veiter, A.; Spengler, J.; Kühr, J.; Urbanek, R. (1999) Lung function growth and ambient ozone: a three-year population study in school children. Am. J. Respir. Crit. Care Med. 160: 390-396. Frischer, T.; Studnicka, M.; Halmerbauer, G.; Horak, F.; Gartner, C.; Tauber, E.; Koller, D. Y. (2001) Ambient ozone exposure is associated with eosinophil activation in healthy children. Clin. Exp. Allergy 31: 1213- 1219. Fung, K. Y.; Luginaah, I.; Gorey, K. M.; Webster, G. (2005) Air pollution and daily hospital admissions for cardiovascular diseases in Windsor, Ontario. Can. J. Public Health 96: 29-33. Galizia, J.L..; Kinney, P. L. (1999) Long-term residence in areas of high ozone: associations with respiratory health in a nationwide sample of nonsmoking young adults. Environ. Health Perspect. 107: 675-679. Gamble, J. L. (1998) Effects of ambient air pollution on daily mortality: a time series analysis of Dallas, Texas, 1990-1994. Presented at: 91st annual meeting and exhibition of the Air & Waste Management Association; June; San Diego, CA. Pittsburgh, PA: Air & Waste Management Association; paper no. 98-MP26.03. Gauderman, W. J.; McConnell, R.; Gilliland, F.; London, S.; Thomas, D.; Avol, E.; Vora, H.; Berhane, K.; Rappaport, E. B.; Lurmann, F.; Margolis, H. G.; Peters, J. (2000) Association between air pollution and lung function growth in southern California children. Am. J. Respir. Crit. Care Med. 162: 1383-1390. Gauderman, W. J.; Gilliland, G. F.; Vora, H.; Avol, E.; Stram, D.; McConnell, R.; Thomas, D.; Lurmann, F.; Margolis, H. G.; Rappaport, E. B.; Berhane, K.; Peters, J. M. (2002) Association between air pollution and lung function growth in southern California children: results from a second cohort. Am. J. Respir. Crit. Care Med. 166: 76-84. Gauderman, W. J.; Avol, E.; Gilliland, F.; Vora, H.; Thomas, D.; Berhane, K.; McConnell, R.; Kuenzli, N.; Lurmann, F.; Rappaport, E.; Margolis, H.; Bates, D.; Peters, J. (2004a) The effect of air pollution on lung development from 10 to 18 years of age. N. Engl. J. Med. 351: 1057-1067. Gauderman, W. J.; Avol, E.; Gilliland, F. (2004b) Air pollu tion and lung function [reply letter]. N. Engl. J. Med. 351: 2653. Gent, J. F.; Triche, E. W.; Holford, T. R.; Belanger, K.; Bracken, M. B.; Beckett, W. S.; Leaderer, B. P. (2003) Association of low-level ozone and fine particles with respiratory symptoms in children with asthma. JAMA J. Am. Med. Assoc. 290: 1859-1867. Gielen, M. H.; Van Der Zee, S. C.; Van Wijnen, J. H.; Van Steen, C. J.; Brunekreef, B. (1997) Acute effects of summer air pollution on respiratory health of asthmatic children. Am. J. Respir. Crit. Care Med. 155: 2105- 2108. Gilliland, F. D.; Berhane, K.; Rappaport, E. B.; Thomas, D. C.; Avol, E.; Gauderman, W. J.; London, S. J.; Margolis, H. G.; McConnell, R.; Islam, K. T.; Peters, J. M. (2001) The effects of ambient air pollution on school absenteeism due to respiratory illnesses. Epidemiology 12: 43-54.3-97 Gold, D. R.; Litonjua, A.; Schwartz, J.; Lovett, E.; Larson, A.; Nearing, B.; Allen, G.; Verrier, M.; Cherry, R.; Verrier, R. (2000) Ambient pollution and heart rate variability. Circulation 101: 1267-1273. Goldberg, M. S.; Burnett, R. T.; Brook, J.; Bailar, J. C., III;Valois, M.-F.; Vincent, R. (2001) Associations between daily cause-specific mortality and concentrations of ground-level ozone in Montreal, Quebec. Am. J. Epidemiol. 154: 817-826. Goldberg, M. S.; Burnett, R. T.; Valois, M.-F.; Flegel, K.; Ba ilar, J. C., III; Brook, J.; Vincent, R.; Radon, K. (2003) Associations between ambient air pollution and daily mortality among persons with congestive heart failure. Environ. Res. 91: 8-20. Gong, H., Jr.; Bradley, P. W.; Simmons, M. S.; Tashkin, D. P. (1986) Impaired exercise performance and pulmonary function in elite cyclists during low-level ozone expo sure in a hot environment. Am. Rev. Respir. Dis. 134: 726-733. Gong, H., Jr.; McManus, M. S.; Linn, W. S. (1997a) Attenuated response to repeated daily ozone exposures in asthmatic subjects. Arch. Envi ron. Health 52: 34-41. Gong, H., Jr.; Shamoo, D. A.; Anderson, K. R.; Linn, W. S. (1997b) Responses of older men with and without chronic obstructive pulmonary disease to prolonged ozone exposure. Arch. Environ. Health 52: 18-25. Gong, H., Jr.; Wong, R.; Sarma, R. J.; Linn, W. S.; Sullivan, E. D.; Shamoo, D. A.; Anderson, K. R.; Prasad, S. B. (1998a) Cardiovascular effects of ozone exposure in human volunteers. Am. J. Respir. Crit. Care Med. 158: 538-546. Gong, H., Jr.; Simmons, M. S.; Linn, W. S.; McDonnell, W. F.; Westerdahl, D. (1998b) Relationship between acute ozone responsiveness and chronic loss of lung function in residents of a high-ozone community. Arch. Environ. Health 53: 313-319. Gouveia, N.; Fletcher, T. (2000) Time series analysis of air po llution and mortality: effects by cause, age and socioeconomic status. J. Epidemiol. Community Health 54: 750-755. Graham, D. E.; Koren, H. S. (1990) Biomarkers of inflammation in ozone-exposed humans: comparison of the nasal and bronchoalveolar lavage. Am. Rev. Respir. Dis. 142: 152-156. Greer, J. R.; Abbey, D. E.; Burchette, R. J. (1993) Asthma related to occupational and ambient air pollutants in nonsmokers. J. Occup. Med. 35: 909-915. Gryparis, A.; Forsberg, B.; Katsouyanni, K.; Analitis, A.; Touloumi, G.; Schwartz, J.; Samoli, E.; Medina, S.; Anderson, H. R.; Niciu, E. M.; Wichmann, H.-E.; Kriz, B.; Kosnik, M.; Skorkovsky, J.; Vonk, J. M.; Dörtbudak, Z. (2004) Acute effects of ozone on mortality from the "air pollution and health: a European approach" project. Am. J. Respir. Crit. Care Med. 170: 1080-1087. Gwynn, R. C.; Burnett, R. T.; Thurston, G. D. (2000) A time-series analysis of acidi c particulate matter and daily mortality and morbidity in the Buffalo, New York, region. Environ. Health Perspect. 108: 125-133. Gwynn, R. C.; Thurston, G. D. (2001) The burden of air pollution: impacts among racial minorities. Environ. Health Perspect. Suppl. 109(4): 501-506. Harkema, J. R.; Plopper , C. G.; Hyde, D. M.; St. George, J. A.; Wilson, D. W.; Dungworth, D. L. (1993) Response of macaque bronchiolar epithelium to ambient concentrations of ozone. Am J. Pathol. 143: 857-66. Harkema, J. R.; Wagner, J. G. (2005) Epithelial and inflammatory responses in the airways of laboratory rats coexposed to ozone and biogenic substances: enhancemen t of toxicant-induced airway injury. Exp. Toxicol. Pathol. 57(suppl. 1): 129-141. Hatch, G. E.; Slade, R.; Harris, L.P.; McDonnell, W.F.; Devlin, R.B.; Koren, H.S.; Costa, D. L., McKee, J. (1994) Ozone dose and effect in humans and rats: a comparison using oxygen-18 labeling and bornchoalveolar lavage. Am.J. Respir. Crit. Care Med. 150:676-683. Hazucha, M. J.; Folinsbee, L. J.; Brom berg, P. A. (2003) Distribution and repr oducibility of spirometric response to ozone by gender and age. J. Appl. Physiol. 95: 1917-1925. Hazucha, M. J.; Folinsbee, L. J.; Seal, E., Jr. (1992) Eff ects of steady-state and variable ozone concentration profiles on pulmonary function. Am. Rev. Respir. Dis. 146: 1487-1493.Hernández-Garduno, E.; Pérez-Neria, J.; Paccagnella, A. M.; Pina-García, M.; Munguía-Castro, M.; CatalánVázquez, M.; Rojas-Ramos, M. (1997) Air pollution and respiratory health in Mexico City. J. Occup. Environ. Med. 39: 299-307. Henderson, R. (2006a) Letter from CASAC Chairman Rogene Henderson to EPA Administrator Stephen Johnson, February 16, 2006, EPA-CASAC-06-003. Henderson, R. (2006b) Letter from CASAC Chairman Rogene Henderson to EPA Administrator Stephen Johnson, June 5, 2006, EPA-CASAC-06-007.3-98 Henderson, R. (2006c) Letter from CASAC Chairman Rogene Henderson to EPA Administrator Stephen Johnson, October 24, 2006, EPA-CASAC-07-001. Higgins, I. T. T.; D'Arcy, J. B.; Gibbons, D. I.; Avol, E. L.; Gross, K. B. (1990) Eff ect of exposures to ambient ozone on ventilatory lung function in children. Am. Rev. Respir. Dis. 141: 1136-1146. Hiltermann, T. J. N.; Stolk, J.; Van der Zee, S. C.; Brunekreef, B.; De Bruijne, C. R.; Fischer, P. H.; Ameling, C. B.; Sterk, P. J.; Hiemstra, P. S.; Van Bree, L. (1998) Asthma severity and susceptibility to air pollution. Eur. Respir. J. 11: 686-693. Hiltermann, J. T. N.; Lapperre, T. S.; Van Bree, L.; Steeren berg, P. A.; Brahim, J. J.; Sont, J. K.; Sterk, P. J.; Hiemstra, P. S.; Stolk, J. (1999) Ozone-induced inflammation assessed in sputum and bronchial lavage fluid from asthmatics: a new noninvasive tool in epidemiological studies on air pollution and asthma. Free Radical Biol. Med. 27: 1448-1454. Hoek, G.; Brunekreef, B.; Verhoeff, A.; Van Wijnen, J.; Fisc her, P. (2000) Daily mortality and air pollution in the Netherlands. J. Air Waste Manage. Assoc. 50: 1380-1389. Hoek, G.; Brunekreef, B.; Fischer, P.; Van Wijnen, J. (2001) The association between air pollution and heart failure, arrhythmia, embolism, thrombosis, and other cardiovascular causes of death in a time series study. Epidemiology 12: 355-357. Hoek, G. (2003) Daily mortality and air pollution in The Netherlands. In: Revised analyses of time-series studies of air pollution and health. Special report. Boston, MA: Health Effects Institute; pp. 133-142. Available: http://www.healtheffects.org/Pubs/TimeSeries.pdf [12 May, 2004]. Holguín, F.; Téllez-Rojo, M. M.; Hernández, M.; Cortez, M.; Chow, J. C.; Watson, J. G.; Mannino, D.; Romieu, I. (2003) Air pollution and heart rate variability among the elderly in Mexico City. Epidemiology 14: 521-527. Holz, O.; Jörres, R. A.; Timm, P.; Mücke, M.; Richter, K.; Koschyk, S.; Magnussen, H. (1999) Ozone-induced airway inflammatory changes differ between individuals and are reproducible. Am. J. Respir. Crit. Care Med. 159: 776-784. Holz, O.; Mücke, M.; Paasch, K.; Böhme, S.; Timm, P.; Rich ter, K.; Magnussen, H.; Jörres, R. A. (2002) Repeated ozone exposures enhance bronchial allergen responses in subjects with rhinitis or asthma. Clin. Exp. Allergy. 32: 681-689. Höppe, P.; Praml, G.; Rabe, G.; Lindner, J.; Fruhmann, G.; Kessel, R. (1995) Environmental ozone field study on pulmonary and subjective responses of assumed risk groups. Environ. Res. 71: 109-121. Höppe, P.; Peters, A.; Rabe, G.; Praml, G.; Lindner, J.; Jakobi, G.; Fruhmann, G.; Nowak, D. (2003) Environmental ozone effects in different population subgroups. Int. J. Hyg. Environ. Health 206: 505-516. Horak, F., Jr.; Studnicka, M.; Gartner, C.; Spengler, J. D. ; Tauber, E.; Urbanek, R.; Veiter, A.; Frischer, T. (2002a) Particulate matter and lung function growth in children: a 3-yr follow-up study in Austrian schoolchildren. Eur. Respir. J. 19: 838-845. Horak, F., Jr.; Studnicka, M.; Gartner, C.; Spengler, J. D. ; Tauber, E.; Urbanek, R.; Veiter, A.; Frischer, T. (2002b) Particulate matter and lung function growth in children: a 3-yr follow-up study in Austrian schoolchildren [author response]. Eur. Respir. J. 20: 1355. Horstman, D. H.; Folinsbee, L. J.; Ives, P. J.; Abdul-Salaam, S.; McDonnell, W. F. (1990) Ozone concentration and pulmonary response relationships for 6.6-hr exposures with five hrs of moderate exercise to 0.08, 0.10, and 0.12 ppm. Am. Rev. Respir. Dis. 142: 1158-1163. Horstman, D. H.; Ball, B. A.; Brown, J.; Gerrity, T.; Folin sbee, L. J. (1995) Comparison of pulmonary responses of asthmatic and nonasthmatic subjects performing light exercise while exposed to a low level of ozone. Toxicol. Ind. Health 11: 369-385. Hotchkiss, J. A.; Hilaski, R.; Cho, H.; Regan, K.; Spencer, P.; Slack, K.; Harkema, J. R. (1998) Fluticasone propionate attenuates ozone-induced rhinitis and mucous cell metaplasia in rat nasal airway epithelium. Am. J. Respir. Cell Mol. Biol. 18: 91-99. Housley, D. G.; Eccles, R.; Richards, R. J. (1996) Gender differen ce in the concentration of the antioxidant uric acid in human nasal lavage. Acta Oto-Laryngol. 116: 751-754. Huang, Y.; Dominici, F.; Bell, M. L. (2005) Bayesian hierarchical distributed lag models for summer ozone exposure and cardio-respiratory mort ality. Environmetrics 16: 547-562. Ihorst, G.; Frischer, T.; Horak, F.; Schumacher, M.; Kopp, M.; Forster, J.; Mattes, J.; Kuehr, J. (2004) Long- and medium-term ozone effects on lung growth including a broad spectrum of exposure. Eur. Respir. J. 23: 292- 299. Ilabaca, M.; Olaeta, I.; Campos, E.; Vill aire, J.; Tellez-Rojo, M. M.; Romieu, I. (1999) Association between levels of fine particulate and emergency visits for pneumonia and other respiratory illnesses among children in Santiago, Chile. J. Air Waste Manage. Assoc. 49: 154-163.3-99 Ito, K.; Thurston, G. D. (1996) Daily PM 10 /mortality associations: an investigation of at-risk subpopulations. J. Exposure Anal. Environ. Epidemiol. 6: 79-95. Ito, K. (2003) Associations of particulate matter components with daily mortality and morbidity in Detroit, Michigan. In: Revised analyses of time-series studies of air pollution and health. Special report. Boston, MA: Health Effects Institute; pp. 143-156. Available: http://www.healtheffects. org/Pubs/TimeSeries.pdf [12 May, 2004].Ito, K.; De Leon, S. F.; Lippmann, M. (2005) Associations between ozone and daily mortality, analysis and metaanalysis. Epidemiology 16: 446-457. Iwasaki, T.; Takahashi, M.; Saito, H.; Arito, H. (1998) Adaptation of extrapulmonary responses to ozone exposure in conscious rats. Ind. Health 36: 57-60. Jaffe, D. H.; Singer, M. E.; Rimm, A. A. (2003) Air pollution and emergency department visits for asthma among Ohio Medicaid recipients, 1991-1996. Environ. Res. 91: 21-28. Jalaludin, B. B.; Chey, T.; O'Toole, B. I.; Smith, W. T.; Capon, A. G.; Leeder, S. R. (2000) Acute effects of low levels of ambient ozone on peak expiratory flow rate in a cohort of Australian children. Int. J. Epidemiol. 29: 549-557. Jalaludin, B. B.; O'Toole, B. I.; Leeder, S. R. (2004) Acute effects of urban ambient air pollution on respiratory symptoms, asthma medication use, and doctor visits for asthma in a cohort of Australian children. Environ Res. 95: 32-42. Jenkins, H. S.; Devalia, J. L.; Mister, R. L.; Bevan, A. M.; Rusznak, C.; Davies, R. J. (1999) The effect of exposure to ozone and nitrogen dioxide on the airway response of atopic asthmatics to inhaled allergen: dose- and time-dependent effects. Am. J. Respir. Crit. Care Med. 160: 33-39. Jones, G. N.; Sletten, C.; Mandry, C. ; Brantley, P. J. (1995) Ozone level effect on respiratory illness: an investigation of emergency department visits. South. Med. J. 88: 1049-1056. Jörres, R.; Nowak, D.; Magnussen, H.; Speckin, P.; Koschyk, S. (1996) The effect of ozone exposure on allergen responsiveness in subjects with asthma or rhinitis. Am. J. Respir. Crit. Care Med. 153: 56-64. Jörres, R. A.; Holz, O.; Zachgo, W.; Timm, P.; Koschyk, S.; Müller, B.; Grimminger, F.; Seeger, W.; Kelly, F. J.; Dunster, C.; Frischer, T.; Lubec, G.; Waschewski, M.; Niendorf, A.; Magnussen, H. (2000) The effect of repeated ozone exposures on inflammatory markers in bronchoalveolar lavage fluid and mucosal biopsies. Am. J. Respir. Crit. Care Med. 161: 1855-1861. Just, J.; Ségala, C.; Sahraoui, F.; Priol, G.; Grimfeld, A.; Neukirch, F. (2002) Short-term health effects of particulate and photochemical air pollution in asthmatic children. Eur. Respir. J. 20: 899-906. Kafoury, R. M.; Pryor, W. A.; Squadrito, G. L.; Salgo, M. G.; Zou, X.; Friedman, M. (1999) Induction of inflammatory mediators in human airway epithelial cells by lipid ozonation products. Am. J. Respir. Crit. Care Med. 160: 1934-1942. Kehrl, H. R.; Peden, D. B.; Ball, B. A. ; Folinsbee, L. J.; Horstman, D. H. (1999 ) Increased specific airway reactivity of persons with mild allergic asthma after 7.6 hrs of exposure to 0.16 ppm ozone. J. Allergy. Clin. Immunol. 104. Kim, S.-Y.; Lee, J.-T.; Hong, Y.-C.; Ahn, K.-J.; Kim, H. (2004) Determining the threshold effect of ozone on daily mortality: an analysis of ozone and mortality in Seoul, Korea, 1995-1999. Environ. Res. 94: 113-119. Kinney, P. L.; Özkaynak, H. (1991) Associations of daily mortality and air pollution in Los Angeles County. Environ. Res. 54: 99-120. Kinney, P. L.; Ito, K.; Thurston, G. D. (1995) A sensitivity analysis of mortality/PM10 associations in Los Angeles. In: Phalen, R. F.; Bates, D. V., eds. Proceedings of the colloquium on particulate air pollution and human mortality and morbidity; January 1994; Irvine, CA. Inhalation Toxicol. 7: 59-69. Kinney, P. L.; Nilsen, D. M.; Lippmann, M.; Brescia, M.; Gordon, T.; McGovern, T.; El Fawal, H.; Devlin, R. B.; Rom, W. N. (1996) Biomarkers of lung inflammation in recreational joggers exposed to ozone. Am. J. Respir. Crit. Care Med. 154: 1430-1435. Kinney, P. L.; Aggarwal, M.; Nikiforov, S. V.; Nadas, A. (1998) Methods development for epidemiological investigations of the health effects of prolonged ozone exposure. Part III: an approach to retrospective estimation of lifetime ozone exposure using a questionnaire and ambient monitoring data (U.S. sites). Cambridge, MA: Health Effects Institute; research report no. 81; pp. 79-108. Kinney, P. L.; Lippmann, M. (2000) Respiratory effects of seasonal exposures to ozone and particles. Arch. Environ. Health 55: 210-216.i. Kleinman, M. T.; Bufalino, C.; Rasmussen, R.; Hyde, D.; Bhalla, D. K.; Mautz, W. J. (2000) Toxicity of chemical components of ambient fine particulate matter (PM2.5) inhaled by aged rats. J. Appl. Toxicol. 20: 357-364.3-100 Klemm, R. J.; Mason, R. M., Jr. (2000) Aerosol Research and Inhalation Epidemiological Study (ARIES): air quality and daily mortality statistical modeling–interim re sults. J. Air. Waste Manage. Assoc. 50: 1433-1439. Klemm, R. J.; Lipfert, F. W.; Wyzga, R. E.; Gust, C. (2004) Daily mortality and air pollution in Atlanta: two years of data from ARIES. Inhalation Toxicol. 16(suppl. 1): 131-141. Koken, P. J.; Piver, W. T.; Ye, F.; Elixhauser, A.; Olsen, L. M.; Portier, C. J. (2003) Temperature, air pollution, and hospitalization for cardiovascular diseases among elderly people in Denver. Environ. Health Perspect. 111: 1312-1317. Kopp, M. V.; Ulmer, C.; Ihorst, G.; Seydewitz, H. H.; Fr ischer, T.; Forster, J.; Kueh r, J. (1999) Upper airway inflammation in children exposed to ambient ozone and potential signs of adaptation. Eur. Respir. J. 14: 854- 861. Kopp, M. V.; Bohnet, W.; Frischer, T.; Ulmer, C.; Studnicka, M.; Ihorst, G.; Gardner, C.; Forster, J.; Urbanek, R.; Kuehr, J. (2000) Effects of ambient ozone on lung function in children over a two-summer period. Eur. Respir. J. 16: 893-900. Korrick, S. A.; Neas, L. M.; Dockery, D. W.; Gold, D. R.; Allen, G. A.; Hill, L. B.; Kimball, K. D.; Rosner, B. A.; Speizer, F. E. (1998) Effects of ozone and other pollutants on the pulmonary function of adult hikers. Environ. Health Perspect. 106: 93-99. Kreit, J. W.; Gross, K. B.; Moore, T. B.; Lorenzen, T. J.; D'Arcy, J.; Eschenbacher, W. L. (1989) Ozone-induced changes in pulmonary function and bronchial responsiveness in asthmatics. J. Appl. Physiol. 66: 217-222. Krewski, D.; Burnett, R. T.; Goldberg, M. S.; Hoover, K.; Siemiatycki, J,; Jerrett, M.; Abrahamowicz, M.; White, W. H. (2000) Reanalysis of the Harvard Six Cities Study and the American Cancer Society Study of particulate air pollution and mortality. A special report of the Institute’s particle epidemiology reanalysis project. Cambridge, MA: Health Effects Institute. Kulle, T. J.; Sauder, L. R.; Kerr, H. D.; Farrell, B. P.; Bermel, M. S.; Smith, D. M. (1982) Duration of pulmonary function adaptation to ozone in humans. Am. Ind. Hyg. Assoc. J. 43: 832-837. Künzli, N.; Lurmann, F.; Segal, M.; Ngo, L.; Balmes, J.; Tager, I. B. (1997) Association between lifetime ambient ozone exposure and pulmonary function in college freshmen—results of a pilot study. Environ. Res. 72: 8-23. Lebowitz, M. D.; Camilli, A. E.; Bronnimann, D.; Quackenboss, J. (1987) The significance and meaningfulness of intraindividual changes in ob jective test results as responses to ai r contaminants. Presented at: 80th annual meeting of the Air Pollution Control Association; June; New York, NY. Pittsburgh, PA: Air Pollution Control Association; paper no. 87-32.1. Lethbridge-Çejku, M.; Schiller, J. S.; Bernadel, L. (2004) Summary health statistics for U.S. adults: National Health Interview Survey, 2002. Hyattsville, MD: Centers for Disease Control and Preventi on; DHHS publication no. (PHS) 2004-1550. (Vital and health statistics, series 10, number 222). Available: http://www.cdc.gov/nchs/data/series/sr_10/sr10_222.pdf [3, August, 2005]. Levy, J. I.; Chemerynski, S. M.; Sarnat, J. A. (200 5) Ozone exposure and mortality, an empiric Bayes metaregression analysis. Epidemiology 16: 458-468. Liao, D.; Duan, Y.; Whitsel, E. A.; Zheng, Z.-J.; Heiss, G.; Chinchilli, V. M.; Lin, H.-M. (2004) Association of higher levels of ambient criteria pollutants with impaired cardiac autonomic control: a population-based study. Am. J. Epidemiol. 159: 768-777. Lin, C. A.; Martins, M. A.; Farhat, S. C. L.; Pope, C. A., III; Conceiçno, G. M. S.; Anastácio, V. M.; Hatanaka, M.; Andrade, W. C.; Hamaue, W. R.; Böhm, G. M.; Saldiva, P. H. N. (1999) Air pollution and respiratory illness of children in Sao Paulo, Brazil. Paediatr. Perinat. Epidemiol. 13: 475-488. Lin, M.; Chen, Y.; Burnett, R. T.; Villeneuve, P. J.; Krewski, D. (2003) Effect of short-term exposure to gaseous pollution on asthma hospitalisation in children: a bi-directional case-crossover analysis. J. Epidemiol. Community Health 57: 50-55. Lin, M.; Chen, Y.; Villeneuve, P. J.; Burnett, R. T.; Lemyre, L.; Hertzman, C.; McGrail, K. M.; Krewski, D. (2004) Gaseous air pollutants and asthma hospitalization of children with low household income in Vancouver, British Columbia, Canada. Am. J. Epidemiol. 159: 294-303. Linder, J.; Herren, D.; Monn, C.; Wanner, H.-U. (1988) Die Wirkung von Ozon auf die körperliche Leistungsfähigkeit [The effect of ozone on physical activity]. Schweiz Z. Sportmed. 36: 5-10.Linn, W. S.; Shamoo, D. A.; Anderson, K. R.; Peng, R.-C.; Avol, E. L.; Hackney, J. D.; Gong, H., Jr. (1996) Shortterm air pollution exposures and responses in Los Angeles area schoolchildren. J. Exposure Anal. Environ. Epidemiol. 6: 449-472. Linn, W. S.; Szlachcic, Y.; Gong, H., Jr.; Kinney, P. L.; Berhane, K. T. (2000) Air pollution and daily hospital admissions in metropolitan Los Angeles. Environ. Health Perspect. 108: 427-434.3-101 Lipfert, F. W.; Hammerstrom, T. (1992) Temporal patterns in air pollution and hospital admissions. Environ. Res. 59: 374-399. Lipfert, F. W.; Perry, H. M., Jr.; Mill er, J. P.; Baty, J. D.; Wyzga, R. E.; Carmody, S. E. (2000) The Washington University-EPRI veterans' cohort mortality study: preliminary results. In: Grant, L. D., ed. PM2000: particulate matter and health. Inhalation Toxicol. 12(suppl. 4): 41-73. Lippmann, M. (1988) Health significance of pulmonary function responses to airborne irritants. JAPCA 38: 881- 887. Lippmann, M.; Ito, K.; Nádas, A.; Burnett, R. T. (2000) Association of particulate matter components with daily mortality and morbidity in urban populations. Cambridge, MA: Health Effects Institute; research report no. 95. Longphre, M.; Zhang, L.-Y.; Harkema, J. R.; Kleeberger , S. R. (1999) Ozone-induced pulmonary inflammation and epithelial proliferation are partially mediated by PAF. J. Appl. Physiol. 86: 341-349. Luginaah, I. N.; Fung, K. Y.; Gorey, K. M.; Webster, G.; Wills, C. (2005) Association of ambient air pollution with respiratory hospitalization in a government designated "area of concern": the case of Windsor, Ontario. Environ. Health Perspect. 113: 290-296. Mannino, D. M.; Ford, E. S.; Redd, S. C. (2003) Obstructive and restrictive lung disease and markers of inflammation: data from the Third National Health and Nutrition Examination. Am. J. Med. 114: 758-762. McBride, D. E.; Koenig, J. Q.; Luchtel, D. L.; Williams, P. V.; Henderson, W. R., Jr. (1994) Inflammatory effects of ozone in the upper airways of subjects with asthma. Am. J. Respir. Crit. Care Med. 149: 1192-1197. McCaig, L. F.; Burt, C. W. (2005) National Hospital Ambulatory Medical Care Survey: 2003 Emergency Department Summary. Hyattsville, MD: National Center for Health Statistics; DHHS publication no. (PHS) 2005-1250. (Advance data from vital and health statistics; no. 358). Available: http://www.cdc.gov/nchs/data/ad/ad358.pdf [3 August, 2005]. McConnell, R.; Berhane, K.; Gilliland, F.; London, S. J. ; Vora, H.; Avol, E.; Gauderman, W. J.; Margolis, H. G.; Lurmann, F.; Thomas, D. C.; Peters, J. M. (1999) Air pollution and bronchitic symptoms in southern California children with asthma. Environ. Health Perspect. 107: 757-760. McConnell, R.; Berhane, K.; Gilliland, F.; London, S. J.; Islam, T.; Gauderman, W. J.; Avol, E.; Margolis, H. G.; Peters, J. M. (2002) Asthma in exercising children exposed to ozone: a cohort study. Lancet 359: 386-391. McDonnell, W. F. (1996) Individual variability in human lung function responses to ozone exposure. Environ. Toxicol. Pharmacol. 2: 171-175. McDonnell, W. F.; Stewart, P. W.; Andreoni, S.; Seal, E., Jr.; Kehrl, H. R.; Horstman, D. H.; Folinsbee, L. J.; Smith, M. V. (1997) Prediction of ozone-induced FEV1 changes: effects of concentration, duration, and ventilation. Am. J. Respir. Crit. Care Med. 156: 715-722. McDonnell, W. F.; Abbey, D. E.; Nishino, N.; Lebowitz, M. D. (1999) Long-term ambient ozone concentration and the incidence of asthma in nonsmoking adults: the ahsmog study. Environ. Res. 80: 110-121. Metzger, K. B.; Tolbert, P. E.; Klein, M.; Peel, J. L.; Fl anders, W. D.; Todd, K. H.; Mulholland, J. A.; Ryan, P. B.; Frumkin , H. (2004) Ambient air pollution and cardiovascular emergency department visits. Epidemiology 15: 46-56. Michelson, P. H.; Dailey, L.; Devlin, R. B.; Peden, D. B. (1999) Ozone effects on the immediate-phase response to allergen in the nasal airways of allergic asthmatic subjects. Otolaryngol. Head Neck Surg. 120: 225-232. Molfino, N. A.; Wright, S. C.; Katz, I.; Tarlo, S.; Silverman, F.; McClean, P. A.; Szalai, J. P.; Raizenne, M.; Slutsky, A. S.; Zamel, N. (1991) Effect of low concentrations of ozone on inhaled allergen responses in asthmatic subjects. Lancet 338(8761): 199-203. Montuschi, P.; Nightingale, J. A.; Kharitonov, S. A.; Barnes, P. J. (2002) Ozone -induced increase in exhaled 8-isoprostane in healthy subjects is resistant to inhaled budesonide. Free Radical Biol. Med. 33: 1403-1408. Moolgavkar, S. H. (2003) Air pollution and daily mortality in two U.S. counties: season-specific analyses and exposure-response relationships. Inhalation Toxicol. 15: 877-907. Moolgavkar, S. H.; Luebeck, E. G.; Hall, T. A.; Anderson, E. L. (1995) Air pollution and daily mortality in Philadelphia. Epidemiology 6: 476-484. Moolgavkar, S. H.; Luebeck, E. G.; An derson, E. L. (1997) Air pollution and hospital admissions for respiratory causes in Minneapolis-St. Paul and Birmingham. Epidemiology 8: 364-370. Mortimer, K. M.; Tager, I. B.; Dockery, D. W.; Neas, L. M.; Redline, S. (2000) The e ffect of ozone on inner-city children with asthma: identification of susceptible gr oups. Am. J. Respir. Crit. Care Med. 162: 1838-1845.Mortimer, K. M.; Neas, L. M.; Dockery, D. W.; Redline, S.; Tager, I. B. (2002) The effect of air pollution on innercity children with asthma. Eur. Respir. J. 19: 699-705.3-102 Mudway, I. S.; Stenfors, N.; Blomberg, A.; Helleday, R.; Dunster, C.; Marklund, S. L.; Frew, A. J.; Sandström, T.; Kelly, F. J. (2001) Differences in basal airway antioxi dant concentrations are not predictive of individual responsiveness to ozone: a comparison of healthy an d mild asthmatic subjects. Free Radical Biol. Med. 31: 962-974. Mudway, I. S.; Kelly, F. J. (2004) An investigation of inhaled ozone dose and the magnitude of airway inflammation in healthy adults. Am. J. Respir. Crit. Care Med. 169: 1089-1095. Naeher, L. P.; Holford, T. R.; Beckett, W. S.; Belanger, K.; Triche, E. W.; Bracken, M. B.; Leaderer, B. P. (1999) Healthy women's PEF variations with ambient summer concentrations of PM 10 , PN 2.5 , SO 42- , H + , and O 3 . Am. J. Respir. Crit. Care Med. 160: 117-125. National Institutes of Health. (1997) Guidelines for the diagnosis and management of asthma: expert panel report 2. Bethesda, MD: U.S. Department of Health and Human Services, National Heart, Lung, and Blood Institute; publication no. 97-4051. Available: http://www.nhlbi.nih.gov/guidelines/asthma/asthgdln.pdf (11 April 2003). Navidi, W.; Thomas, D.; Langholz, B.; Stram, D. (1999) Statistical methods for epidemiologic studies of the health effects of air pollution. Cambri dge, MA: Health Eff ects Institute; research report no. 86. Neas, L. M.; Dockery, D. W.; Koutrakis, P.; Tollerud, D. J.; Speizer, F. E. (1995) Th e association of ambient air pollution with twice daily peak expiratory flow rate measurements in children. Am. J. Epidemiol. 141: 111-122. Neas, L. M.; Dockery, D. W.; Koutrakis, P.; Speizer, F. E. (1999) Fine particles and peak flow in children: acidity

versus mass. Epidemiology 10: 550-553. Newhouse, C. P.; Levetin, B. S.; Levetin , E. (2004) Correlation of environmen tal factors with asthma and rhinitis symptoms in Tulsa, OK. Ann. Allergy Asthma Immunol. 92: 356-366. Nightingale, J. A.; Rogers, D. F.; Chung, K. F.; Barnes, P. J. (2000) No effect of inhaled budesonide on the response to inhaled ozone in normal subjects. Am. J. Respir. Crit. Care Med. 161: 479-486. O'Neill, M. S.; Loomis, D.; Borja-Aburto, V. H. (2004) Ozone, area social conditions, and mortality in Mexico City. Environ. Res. 94: 234-242. Ostro, B. (1995) Fine particulate air pollution and mortality in two Southern California counties. Environ. Res. 70: 98-104. Ostro, B.; Lipsett, M.; Mann, J.; Brax ton-Owens, H.; White, M. ( 2001) Air pollution and ex acerbation of asthma in African-American children in Los Angeles. Epidemiology 12: 200-208. Ostro, B. D.; Broadwin, R.; Lipsett, M. J. (2003) Coarse particles and daily mortality in Coachella Valley, California. In: Revised analyses of time-series studies of air pollution and health. Special report. Boston, MA: Health Effects Institute; pp. 199-204. Available: http://www.healtheffects.or g/Pubs/TimeSeries.pdf [18 October, 2004]. Park, H.; Lee, B.; Ha, E.-H.; Lee, J.-T.; Kim, H.; Ho ng, Y.-C. (2002) Association of air pollution with school absenteeism due to illness. Arch. Pe diatr. Adolesc. Med. 156: 1235-1239. Park, S. K.; O’Neill, M. S.; Vokonas, P. S.; Sparrow, D.; Schwartz, J. (2005) Effects of air pollution on heart rate variability: the VA normative aging study. Environ. Health Perspect. 113: 304-309. Passannante, A. N.; Hazucha, M. J.; Bromberg, P. A.; Seal, E.; Folinsbee, L.; Koch, G. (1998) Nociceptive mechanisms modulate ozone-induced human lung function decrements. J. Appl. Physiol. 85: 1863-1870. Peden, D. B.; Setzer, R. W., Jr.; Devlin, R. B. (1995) Ozone exposure has both a priming effect on allergen-induced responses and an intrinsic inflammatory action in the nasal airways of perennially allergic asthmatics. Am. J. Respir. Crit. Care Med. 151: 1336-1345. Peden, D. B.; Boehlecke, B.; Horstman, D.; Devlin, R. (1997) Prolonged acute exposure to 0.16 ppm ozone induces eosinophilic airway inflammation in asthmatic subjects with allergies. J. Allergy Clin. Immunol. 100: 802-808. Peel, J. L.; Tolbert, P. E.; Klein, M.; Metzger, K. B.; Flanders, W. D.; Knox, T.; Mulholland, J. A.; Ryan, P. B.; Frumkin, H. (2005) Ambient air pollution and respiratory emergency department visits. Epidemiology 16: 164-174. Peters, J. M.; Avol, E.; Navidi, W.; London, S. J.; Gaude rman, W. J.; Lurmann, F.; Linn, W. S.; Margolis, H.; Rappaport, E.; Gong, H., Jr.; Thomas, D. C. (1999a) A study of twelve southern California communities with differing levels and types of air pollution. I. Prevalence of respiratory morbidity. Am. J. Respir. Crit. Care Med. 159: 760-767. Peters, J. M.; Avol, E.; Gauderman, W. J.; Linn, W. S.; Navidi, W.; London, S. J.; Margolis, H.; Rappaport, E.; Vora, H.; Gong, H., Jr.; Thomas, D. C. (1999b) A study of twelve southern California communities with3-103 differing levels and types of air pollution. II. Effects on pulmonary function. Am. J. Respir. Crit. Care Med. 159: 768-775. Peters, A.; Liu, E.; Verrier, R. L.; Schwartz, J.; Gold, D. R.; Mittleman, M.; Baliff, J.; Oh, J. A.; Allen, G.; Monahan, K.; Dockery, D. W. (2000a) Air pollution and incidence of cardiac arrhythmia. Epidemiology 11: 11-17. Peters, A.; Skorkovsky, J.; Kotesovec, F.; Brynda, J.; Spix, C.; Wichmann, H. E.; Heinrich, J. (2000b) Associations between mortality and air pollution in central Euro pe. Environ. Health Perspect. 108: 283-287. Peters, A.; Dockery, D. W.; Muller, J. E.; Mittleman, M. A. (2001) Increased particulate air pollution and the triggering of myocardial infarction. Circulation 103: 2810-2815. Petroeschevsky, A.; Simpson, R. W.; Thalib, L.; Rutherford, S. (2001) Associations between outdoor air pollution and hospital admissions in Brisbane, Australia. Arch. Environ. Health 56: 37-52. Plopper, C. G.; Hatch, G. E.; Wong, V.; Duan, X.; Weir, A. J.; Tarkington, B. K.; Devlin, R. B.; Becker, S.; Buckpitt, A. R. (1998) Relationship of inhaled ozone concentration to acute tracheobronchial epithelial injury, site-specific ozone dose and glutathione depletion in rhesus monkeys. Am. J. Respir. Cell Mol. Biol. 19: 387-399. Plopper, C. G.; Fanucchi, M. V. (2000) Do urban environmental pollutants exacerbate childhood lung diseases? Environ. Health Perspect. 108: A252-A253. Plunkett, L. M.; Turnbull, D.; Rodricks, J. V. (1992) Differences between adults and children affecting exposure assessment. In: Guzelian, P. S.; Henry, D. J.; Olin, S. S., eds. Similarities and differences between children and adults: implications for risk assessment. Washington, DC: ILSI Press, pp. 79-96. Ponce de Leon, A.; Anderson, H. R.; Bland, J. M.; Strachan, D. P.; Bower, J. (1996) Effects of air pollution on daily hospital admissions for respiratory disease in London between 1987-88 and 1991-92. In: St Leger, S., ed. The APHEA project. Short term ef fects of air pollution on hea lth: a European approach using epidemiological time series data. J. Epidemiol. Commun. Health 50(suppl. 1): S63-S70. Pönkä, A.; Savela, M.; Virtanen, M. (1998) Mortality and air pollution in Helsinki. Arch. Environ. Health 53: 281- 286. Pope, C. A., III; Thun, M. J.; Namboodiri, M. M.; Dockery, D. W.; Evans, J. S.; Speizer, F. E.; Heath, C. W., Jr. (1995) Particulate air pollution as a predictor of mortality in a prospective study of U.S. adults. Am. J. Respir. Crit. Care Med. 151: 669-674. Pope, C. A., III; Burnett, R. T.; Thun, M. J.; Calle, E. E.; Krewski, D.; Ito, K.; Thurston, G. D. (2002) Lung cancer, cardiopulmonary mortality, and long-term exposure to fine particulate air pollution. JAMA J. Am. Med. Assoc. 287: 1132-1141. Pulfer, M. K.; Murphy, R. C. (2004) Formation of biologically active oxysterols during ozonolysis of cholesterol present in lung surfactant. J. Biol. Chem. 279: 26331-26338. Pulfer, M. K.; Taube, C.; Gelfand, E.; Murphy, R. C. (2005) Ozone exposure in vivo and formation of biologically active oxysterols in the lung. J. Pharmacol. Exp. Ther. 312: 256-264. Raizenne, M.; Stern, B.; Burnett, R.; Spengler, J. (1987) Acute respiratory function and transported air pollutants: observational studies. Presented at: 80th annual meeting of the Air Pollution Control Association; June; New York, NY. Pittsburgh, PA: Air Pollution Control Association; paper no. 87-32.6. Raizenne, M. E.; Burnett, R. T.; Stern, B.; Franklin, C. A.; Spengler, J. D. (1989) Acute lung function responses to ambient acid aerosol exposures in children. Environ. Health Perspect. 79: 179-185. Rich, D. Q.; Schwartz, J.; Mittleman, M. A.; Link, M.; Luttmann-Gibson, H.; Catalano, P. J.; Speizer, F. E.; Dockery, D. W. (2005) Association of short-term ambient air pollution concentrations and ventricular arrhythmias. Am. J. Epidemiol. 161: 1123-1132. Rigas, M. L.; Ben-Jebria, A.; Ultman, J. S. (1997) Longitudinal distribution of ozone absorption in the lung: effects of nitrogen dioxide, sulfur dioxide, and ozone exposures. Arch. Environ. Health 52: 173-178. Romieu, I.; Meneses, F.; Ruiz, S.; Sienra , J. J.; Huerta, J.; White, M. C.; Etzel, R. A. (1996) Effects of air pollution on the respiratory health of asthmatic children living in Mexico City. Am. J. Respir. Crit. Care Med. 154: 300-307. Romieu, I.; Meneses, F.; Ruiz, S.; Huerta, J.; Sienra, J. J.; White, M.; Etzel, R.; Hernandez, M. (1997) Effects of intermittent ozone exposure on peak expiratory flow and respiratory symptoms among asthmatic children in Mexico City. Arch. Environ. Health 52: 368-376. Romieu, I.; Meneses, F.; Ramirez, M.; Ruiz, S.; Padilla, R. P.; Sienra, J. J.; Gerber, M.; Grievink, L.; Dekker, R.; Walda, I.; Brunekreef, B. (1998) Antioxidant supplementation and respiratory functions among workers exposed to high levels of ozone. Am. J. Respir. Crit. Care Med. 158: 226-232.3-104 Romieu, I.; Sienra-Monge, J. J.; Ramírez-Aguilar, M.; Téllez-Rojo, M. M.; Moreno-Macías, H.; Reyes-Ruiz, N. I.; Del Río-Navarro, B. E.; Ruiz-Navarro, M. X.; Hatch, G.; Slade, R.; Hernández-Avila, M. (2002) Antioxidant supplementation and lung functions among children with asthma exposed to high levels of air pollutants. Am. J. Respir. Crit. Care Med. 166: 703-709.Romieu, I.; Sienra-Monge, J. J.; Ramírez-Aguilar, M.; Moreno-Macias, H.; Reyes-Ruiz, N. I.; Estela del RioNavarro, B.; Hernández-Avila, M.; London, S. J. (2004) Genetic polymorphism of GSTM1 and antioxidant supplementation influence lung function in relation to ozone exposure in asthmatic children in Mexico City. Thorax 59: 8-10. Ross, M. A.; Persky, V. W.; Scheff, P. A.; Chung, J.; Curtis, L.; Ramakrishnan, V.; Wadden, R. A.; Hryhorczuk, D. O. (2002) Effect of ozone and aeroa llergens on the respiratory health of asthmatics. Arch. Environ. Health 57: 568-578. Ruidavets, J.-B.; Cournot, M.; Cassadou, S.; Giroux, M.; Meybeck, M.; Ferrires, J. (2005) Ozone air pollution is associated with acute myocardial infarction. Circulation 111: 563-569. Samet, J. M.; Zeger, S. L.; Dominici, F.; Curriero, F.; Coursac, I.; Dockery, D. W.; Schwartz, J.; Zanobetti, A. (2000) The national morbidity, mortality, and air pollution study. Part II: morbidity, mortality, and air pollution in the United States. Cambridge, MA: Health Effects Institute; research report no. 94, part II. Samet, J. M.; Hatch, G. E.; Horstman, D.; Steck-Scott, S.; Arab, L.; Bromberg, P. A.; Levine, M.; McDonnell, W. F.; Devlin, R. B. (2001) Effect of antioxidant supplementation on ozone-induced lung injury in human subjects. Am. J. Respir. Crit. Care Med. 164: 819-825. Sartor, F.; Snacken, R.; Demuth, C.; Walckiers, D. (1995) Temperature, ambient ozone levels, and mortality during summer, 1994, in Belgium. Environ. Res. 70: 105-113. Sathishkumar, K.; Haque, M.; Perumal, T. E.; Francis, J.; Uppu, R. M. (2005) A major ozonation product of cholesterol, 3" β "-hydroxy-5-oxo-5,6-secocholestan-6-al, indu ces apoptosis in H9c2 cardiomyoblasts. FEBS Lett. 579: 6444-6450. Scannell, C.; Chen, L.; Aris, R. M.; Tager, I.; Christian, D.; Ferrando, R.; Welch, B.; Kelly, T.; Balmes, J. R. (1996) Greater ozone-induced inflam matory responses in subjects with asthma. Am. J. Respir. Crit. Care Med. 154: 24-29. Scarlett, J. F.; Abbott, K. J.; Peacock, J. L.; Strachan, D. P.; Anderson, H. R. (1996) Acute effects of summer air pollution on respiratory function in primary school children in southern England. Thorax 51: 1109-1114. Schelegle, E. S.; Adams, W. C. (1986 ) Reduced exercise time in competitiv e simulations consequent to low level ozone exposure. Med. Sci. Sports Exercise 18: 408-414. Schelegle, E. S.; Miller, L. A.; Gershwin, L. J.; Fanucchi, M. V.; Van Winkle, L. S.; Gerriets, J. E.; Walby, W. F.; Mitchell, V.; Tarkington, B. K.; Wong, V. J.; Baker, G. L.; Pantle, L. M.; Joad, J. P.; Pinkerton, K. E.; Wu, R.; Evans, M. J.; Hyde, D. M.; Plopper, C. G. (2003) Repeated episodes of ozone inhalation amplifies the effects of allergen sensitization and inhalation on airway immune and structural development in Rhesus monkeys. Toxicol. Appl. Pharmacol. 191: 74-85. Schierhorn, K.; Zhang, M.; Matthias, C.; Kunkel, G. (1999) Influence of ozone and nitrogen dioxide on histamine and interleukin formation in a human nasal mucosa culture system. Am. J. Respir. Cell Mol. Biol. 20: 1013- 1019. Schierhorn, K.; Hanf, G.; Fischer, A.; Umland, B.; Olze, H.; Kunkel, G. (2002) Ozone-induced release of neuropeptides from human nasal mucosa cells. Int. Arch. Allergy Immunol. 129: 145-151. Schindler, C.; Künzli, N.; Bongard, J.-P.; Leuenberger, P.; Karrer, W.; Rapp, R.; Monn, C.; Ackermann-Liebrich, U.; Swiss Study on Air Pollution and Lung Diseases in Adults Investigators. (2001) Short-term variation in air pollution and in average lung function among never-smokers. Am. J. Respir. Crit. Care Med. 163: 356- 361. Schwartz, J. (1994) Air pollution and hospital admissions for the elderly in Detroit, Michigan. Am. J. Respir. Crit. Care Med. 150: 648-655. Schwartz, J. (1996) Air pollution and hospital admissions for respiratory disease. Epidemiology 7: 20-28. Schwartz, J.; Spix, C.; Touloumi, G.; Bachárová, L.; Barumamdzadeh, T.; le Tert re, A.; Piekarksi, T.; Ponce de Leon, A.; Pönkä, A.; Rossi, G.; Saez, M.; Schout en, J. P. (1996) Methodological issues in studies of air pollution and daily counts of deaths or hospital admissions. In: St Leger, S., ed. The APHEA project. Short term effects of air pollution on health: a European approach using epidemiological time series data. J. Epidemiol. Commun. Health 50(suppl. 1): S3-S11. Schwartz, J. (2005) How sensitive is the association between ozone and daily deaths to control for temperature? Am. J. Respir. Crit. Care Med. 171: 627-631.3-105 Seal, E., Jr.; McDonnell, W. F.; House, D. E. (1996) Effects of age, socio economic status, and menstrual cycle on pulmonary response to ozone. Arch. Environ. Health 51: 132-137. Sexton, K. G.; Jeffries, H. E.; Jang, M.; Kamens, R. M.; Doyle, M.; Voicu, I.; Jaspers, I. (2004) Photochemical products in urban mixtures enhance inflammatory responses in lung cells. Inhalation Toxicol. 16(suppl. 1): 107-114. Sheppard, L.; Levy, D.; Norris, G.; Larson, T. V.; Koenig, J. Q. (1999) Effects of ambient air pollution on nonelderly asthma hospital admissions in Seattle, Washington, 1987-1994. Epidemiology 10: 23-30. Sheppard, L. (2003) Ambient air pollution and nonelderly asthma hospital admissions in Seattle, Washington, 1987- 1994. In: Revised analyses of time-series studies of air pollution and health. Special report. Boston, MA: Health Effects Institute; pp. 227-230. Available: http://www.healtheffects. org/Pubs/TimeSeries.pdf [18 October, 2004]. Simpson, R. W.; Williams, G.; Petroeschevsky, A.; Morgan, G.; Rutherford, S. (1997) Associations between outdoor air pollution and daily mortality in Brisbane, Australia. Arch. Environ. Health 52: 442-454. Sin, D. D.; Man, S. F. P. (2003) Why are patients with chronic obstructive pulmonary disease at increased risk of cardiovascular diseases? Circulation 107: 1514-1519. Spektor, D. M.; Lippmann, M.; Lioy, P. J.; Thurston, G. D.; Citak, K.; James, D. J.; Bock, N.; Speizer, F. E.; Hayes, C. (1988a) Effects of ambient ozone on respiratory function in active, normal children. Am. Rev. Respir. Dis. 137: 313-320. Spektor, D. M.; Lippmann, M.; Thurston, G. D.; Lioy, P. J.; Stecko, J.; O'Connor, G.; Garshick, E.; Speizer, F. E.; Hayes, C. (1988b) Effects of ambient ozone on respiratory function in healthy adults exercising outdoors. Am. Rev. Respir. Dis. 138: 821-828. Spektor, D. M.; Lippmann, M. (1991) Health effects of ambient ozone on healthy children at a summer camp. In: Berglund, R. L.; Lawson, D. R.; McKee, D. J., eds. Tropospheric ozone and the environment: papers from an international conference; March 1990; Los Angeles, CA. Pittsburgh, PA: Air & Waste Management Association; pp. 83-89. (A&WMA transactions series no. TR-19). Steck-Scott, S.; Arab, L.; Craft, N. E.; Samet, J. M. (2004) Plasma and lung macrophage responsiveness to carotenoid supplementation and ozone exposure in humans. Eur. J. Clin. Nutr. 1-9. Stenfors, N.; Pourazar, J.; Blomberg, A. ; Krishna, M. T.; Mudway, I.; Helleday , R.; Kelly, F. J.; Frew, A. J.; Sandström, T. (2002) Effect of ozone on bronchial mucosal inflammation in asthmatic and healthy subjects. Respir. Med. 96: 352-358. Stieb, D. M.; Burnett, R. T.; Beveridge, R. C.; Brook, J. R. (1996) Association between ozone and asthma emergency department visits in Saint John, New Brunswick, Canada. Environ. Health Perspect. 104: 1354- 1360. Sunyer, J.; Basagaa, X.; Belmonte, J.; An tó, J. M. (2002) Effect of nitrogen dioxide and ozone on the risk of dying in patients with severe asthma. Thorax 57: 687-693. Tager, I. B.; Künzli, N.; Lurmann, F.; Ngo, L.; Segal, M.; Balmes, J. (1998) Methods development for epidemiological investigations of the health effects of prolonged ozone exposure. Part II: an approach to retrospective estimation of lifetime ozone exposure using a questionnaire and ambient monitoring data (California sites). Cambridge, MA: Health Effect s Institute; research report no. 81; pp. 27-78. Taggart, S. C. O.; Custovic, A.; Francis, H. C.; Faragher, E. B.; Yates, C. J.; Higgins, B. G.; Woodcock, A. (1996) Asthmatic bronchial hyperresponsiveness varies with ambient levels of summertime air pollution. Eur. Respir. J. 9: 1146-1154. Tenías, J. M.; Ballester, F.; Rivera, M. L. (1998) Association between hospital emergency visits for asthma and air pollution in Valencia, Spain. Occup. Environ. Med. 55: 541-547. Tenías, J. M.; Ballester, F.; Pérez-Hoyos, S.; Rivera, M. L. (2002) Air pollution and hospital emergency room admissions for chronic obstructive pulmonary disease in Valencia, Spain. Arch. Environ. Health 57: 41-47. Thurston, G. D.; Ito, K.; Kinney, P. L.; Lippmann, M. (1992) A multi-year study of air pollution and respiratory hospital admissions in three New York State metropolitan areas: results for 1988 and 1989 summers. J. Exposure Anal. Environ. Epidemiol. 2: 429-450. Thurston, G. D.; Ito, K.; Hayes, C. G.; Bates, D. V.; Lippmann, M. (1994) Respiratory hospital admissions and summertime haze air pollution in Toront o, Ontario: consideration of the ro le of acid aerosols. Environ. Res. 65: 271-290. Thurston, G. D.; Lippmann, M.; Scott, M. B.; Fine, J. M. (1997) Summer time haze air pollution and children with asthma. Am. J. Respir. Crit. Care Med. 155: 654-660. Tobías, A.; Campbell, M. J.; Sáez, M. (1999) Modelling asth ma epidemics on the relationship between air pollution and asthma emergency visits in Barcelona, Spain. Eur. J. Epidemiol. 15: 799-803.3-106 Tolbert, P. E.; Mulholland, J. A.; Maclntosh, D. L.; Xu, F.; Daniels, D.; Devine, O. J.; Carlin, B. P.; Klein, M.; Dorley, J.; Butler, A. J.; Nordenberg, D. F.; Frumkin, H.; Ryan, P. B.; White, M. C. (2000) Air quality and pediatric emergency room visits for asthma in Atlanta, Georgia. Am. J. Epidemiol. 151: 798-810. Touloumi, G.; Katsouyanni, K.; Zmirou, D.; Schwartz, J.; Spix, C.; Ponce de Leon, A.; Tobias, A.; Quennel, P.; Rabczenko, D.; Bacharova, L.; Bisanti, L.; Vonk, J. M.; Ponka, A. (1997) Short-term effects of ambient oxidant exposure on mortality: a combined analysis within the APHEA project. Am. J. Epidemiol. 146: 177- 185. Tsai, J.-J.; Lin, Y.-C.; Kwan, Z.-H.; Kao, H.-L. (1998) Effects of ozone on ovalbumin sensitization in guinea pigs. J. Microbiol. Immunol. Infect. 31: 225-232. Tsai, B. M.; Wang, M.; Pitcher, J. M.; Meldrum, K. K.; Meldrum, D. R. (2004) Hypoxic pulmonary vasoconstriction and pulmonary artery tissue cytokine expression are mediated by protein kinase C. Am. J. Physiol. Lung Cell Mol. Physiol. 287: L1215-L1219. U.S. Environmental Protection Agency. (1986) Air quality criteria for ozone and other photochemical oxidants. Research Triangle Park, NC: Office of Health and En vironmental Assessment, Environmental Criteria and Assessment Office; report nos. EPA-600/8-84-020aF-eF. 5v. Available from: NTIS, Springfield, VA; PB87- 142949. U.S. Environmental Protection Agency. (1996) Air quality criteria for ozone and related photochemical oxidants. Research Triangle Park, NC: Office of Research an d Development; report nos. EPA/600/AP-93/004aF-cF. 3v. Available from: NTIS, Springfield, VA; PB96-185582, PB96-185590, and PB96-185608. Available: http://cfpub2.epa.gov/ncea/. U.S. Environmental Protection Agency. (2004) Air quality criteria for particulate matter. Research Triangle Park, NC: National Center for Environmental Assessment; report no. EPA/600/P-99/002aF-bF. 2v. Available: http://www.epa.gov/ttn/naaqs/standards/pm/s_pm_cr_cd.html [9 November, 2004]. U.S. Environmental Protection Agency (2006) Air quality criteria for ozone and related photochemical oxidants (second external review draft) Res earch Triangle Park, NC: National Center for Environmental Assessment; report no. EPA/600R-05/004aB-cB, 3v. Available: http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=137307 [March 2006] Ulmer, C.; Kopp, M.; Ihorst, G.; Frischer, T.; Forster, J.; Kuehr, J. (1997) Effects of ambient ozone exposures during the spring and summer of 1994 on pulmonary function of schoolchildren. Pediatr. Pulmonol. 23: 344- 353. Ultman, J. S.; Ben-Jebria, A.; Arnold, S. F. (2004) Uptake distribution of ozone in human lungs: intersubject variability in physiologic response. Boston, MA: Health Effects Institute. Vagaggini, B.; Taccola, M.; Clanchetti, S.; Carnevali, S.; Bartoli, M. L.; B acci, E.; Dente, F. L.; Di Franco, A.; Giannini, D.; Paggiaro, P. L. (2002) Ozone exposure increases eosinophilic airway response induced by previous allergen challenge. Am. J. Respir. Crit. Care Med. 166: 1073-1077. Vedal, S.; Brauer, M.; White, R.; Petkau, J. (2003) Air pollution and daily mortality in a city with low levels of pollution. Environ. Health Perspect. 111: 45-51.Vesely, D. L.; Giordano, A. T.; Raska-Emery, P.; Montgomery, M. R. (1994a) Ozone increases amino- and carboxyterminal atrial natriuretic factor prohormone peptides in lung, heart, and circulation. J. Biochem. Toxicol. 9: 107-112. Vesely, D. L.; Giordano, A. T.; Raska-Emery, P.; Montgomery , M. R. (1994b) Increase in at rial natriuretic factor in the lungs, heart, and circulatory system owing to ozone. Chest 105: 1551-1554. Vesely, D. L.; Giordano, A. T.; Raska-Emery, P.; Montgo mery, M. R. (1994c) Ozone in creases atrial natriuretic peptides in heart, lung and circulation of aged vs. adult animals. Gerontology (Basel) 40: 227-236. Villeneuve, P. J.; Burnett, R. T.; Shi, Y.; Krewski, D.; Goldberg, M. S.; Hertzman, C.; Chen, Y.; Brook, J. (2003) A time-series study of air pollution, socioeconomic status, and mortality in Vancouver, Canada. J. Exposure Anal. Environ. Epidemiol. 13: 427-435. Watkinson, W. P.; Wiester, M. J.; Highfill, J. W. (1995) Ozone toxicity in the rat. I. Effect of changes in ambient temperature on extrapulmonary physiological parameters. J. Appl. Physiol. 78: 1108-1120. Watkinson, W. P.; Campen, M. J.; Nolan, J. P.; Costa, D. L. (2001) Cardiovascular and systemic responses to inhaled pollutants in rodents: effects of ozone an d particulate matter. Environ. Health Perspect. 109(suppl. 4): 539-546. Watkinson, W. P.; Campen, M. J.; Wichers, L. B.; Nolan, J. P.; Costa, D. L. (2003) Cardiac and thermoregulatory responses to inhaled pollutants in healthy and compromised rodents: modulation via interaction with environmental factors. Environ. Res. 92: 35-47.3-107 Weisel, C. P.; Cody, R. P.; Lioy, P. J. (1995) Relationship between summertime ambient ozone levels and emergency department visits for asthma in central New Jersey. Environ. Health Perspect. 103(suppl. 2): 97- 102. Weisel, C. P.; Cody, R. P.; Georgopoulos, P. G.; Purushothaman, V.; Weiss, S. H.; Bielory, L.; Gregory, P.; Stern, A. H. (2002) Concepts in developing health-based indicators for ozone. Int. Arch. Occup. Environ. Health 75: 415-422. Wentworth, P., Jr.; Nieva, J.; Takeuchi, C.; Galve, R.; Wentworth, A. D.; Dilley, R. B.; DeLaria, G. A.; Saven, A.; Babior, B. M.; Janda, K. D.; Eschenmoser, A.; Lerner, R. A. (2003) Evidence for ozone formation in human atherosclerotic arteries. Science (Washington, DC, U.S.) 302: 1053-1056. White, M. C.; Etzel, R. A.; Wilcox, W. D.; Lloyd, C. (1 994) Exacerbations of childhood asthma and ozone pollution in Atlanta. Environ. Res. 65: 56-68. Wiley, J. A.; Robinson, J. P.; Piazza, T.; Garrett, K.; Ci rksena, K.; Cheng, Y.-T.; Ma rtin, G. (1991a) Activity patterns of California residents. Final report. Sacramento, CA: California Air Resources Board; report no. ARB/R93/487. Available from: NTIS, Springfield, VA.; PB94-108719. Wiley, J. A.; Robinson, J. P. ; Cheng, Y.-T.; Piazza, T.; Stork, L.; Pladse n, K. (1991b) Study of children's activity patterns: final report. Sacramento, CA: California Air Resources Board; report no. ARB-R. Wilson, A. M.; Wake, C. P.; Kelly, T.; Salloway, J. C. (2005) Air pollution, weather, and respiratory emergency room visits in two northern New England cities: an ecological time-series study. Environ. Res. 97: 312-321. Wolff, G.T. (1995) Letter to EPA Administrator Carol Browner: “CASAC Closure on the Primary Standard Portion of the Staff Paper for Ozone” EPA-SAB-CASAC-LTR-96-002, November 30, 1995. Woodwell, D. A.; Cherry, D. K. (2004) National Ambulatory Medical Care Survey: 2002 summary. Hyattsville, MD: National Center for Health Statistics; DHHS publication no. (PHS) 2004-1250. (Advance data from vital and health statistics; no. 346). Available: http://www.cdc.gov/nchs/data/ad/ad346.pdf [3 August, 2005]. Yang, Q.; Chen, Y.; Shi, Y.; Burnett, R. T.; McGrail, K. M.; Krewski, D. (2003) Association between ozone and respiratory admissions among children and the elderly in Vancouver, Canada. Inhalation Toxicol. 15: 1297- 1308. Zidek, J. V. (1997) Interpolating air pollution for health impact assessment. In: Barnett, E. V.; Turkman, K. F., eds. Pollution Assessment and Control. New York, NY: John Wiley & Sons. (Statistics for the Environment, no. 3). Zhu, L.; Carlin, B. P.; Gelfand, A. E. (2003) Hierarchical regression with misaligned spatial data: relating ambient ozone and pediatric asthma visits in Atlanta. Environmetrics 14: 537-557. Zidek, J.V.; Shaddick, G.; White, R.; Meloche, J.; Chatfield, C. (2005) Using a probabilistic model (pCNEM) to estimate personal exposure air pollut ion. Environmetrics 16: 481-493. Zmirou, D.; Schwartz, J.; Saez, M.; Zanobetti, A.; Wojty niak, B.; Touloumi, G.; Spix, C.; Ponce de León, A.; Le Moullec, Y.; Bacharova, L.; Schouten, J.; Pönkä, A.; Katsouyanni, K. (1998) Time-series analysis of air pollution and cause-specific mortality. Epidemiology 9: 495-503.4-1 

### 4. CHARACTERIZATION OF HU MAN EXPOSURE TO OZONE

4.1 INTRODUCTION
As part of the last O 3 NAAQS review, EPA conducted exposure analyses for the general population, children who spent more time outdoors, and outdoor workers. Exposure estimates were generated for nine urban areas for “as is” (i.e ., a recent year) air quality and for just meeting the existing 1-hr standard and se veral alternative 8-hr standards. EPA also conducted a health risk assessment that produced risk estimates fo r the number of children and percent of children experiencing impaired lung function and other respiratory symptoms associated with the exposures estimated for these same nine urban areas. The exposure analysis conducted for the current review builds upon the methodology and lessons learned from the exposure analyses cond ucted for the last review (U.S. EPA, 1996a). The methodology used to conduct the exposure an alysis as well as summary results from the exposure analysis are described in this chapter. The exposur e analysis technical support document, Ozone Population Exposure Anal ysis for Selected Urban Areas (U.S. EPA, 2007) (hereafter cited as “Exposure Analysis TSD”) pr esents a detailed description of the exposure analysis methodology. Population exposures to ambient O 3 levels are modeled for 12 urban areas located across the U.S. using the Air Pollutants Exposure (APEX) model, also referred to as the Total Risk Integrated Methodology Inhalation Exposure (TRIM.Expo) model (U.S. EPA, 2006a,b). Exposure estimates are developed for O 3 levels in recent years, based on 2002, 2003, and 2004 ambient air quality measurements. Exposures are also estimated for O 3 levels associated with just meeting the current 8-hr O 3 NAAQS and several potential al ternative standards, based on adjusting data derived from the ambient mon itoring network as described in section 4.5.8

. Exposures to background levels of O 3 are also estimated, based on O 3 concentrations predicted by the GEOS-CHEM atmospheric photochemical model. Exposures are modeled for 1) the general population, 2) all school-age children (ages 5-18), 3) active school-age children, and 4) asthmatic school-age children. 1 The strong emphasis on children reflects the finding of the last O 3 NAAQS review that children are an important at-risk group. Two groups at potentia lly increased risk where exposure modeling

1 Subsequent to completion of the modeling conducted in 2006, EPA analysis of uncertainty of the exposure modeling results uncovered an error in how children are characterized as active. This error resulted in an overestimate of the number of active children in the popula tion. Thus, exposure estimates for active children are not included in this chapter.4-2 results are not presented are olde r adults and outdoor workers. Although older adu lts are in the general population exposure estimates, we did not separately tabulate exposures for older adults since we do not have specific exposure-respons e data for this group. Exposure to outdoor
workers has not been modeled due to insufficient data to properly charac terize this population. This chapter provides a brief overview of the types of studies that provide data on which this analysis is based, followed by a description of the exposure m odel used for this analysis, the model input data, and the results of the analysis. The final secti ons of this chapter discuss the exposure estimates in comparison to those from the prior review and summarize the sensitivity analyses and model evaluation that have been conducted for the O 3 exposure model described in this chapter. The uncertainty assessment and a technical descri ption of the modeling effort are provided in separate documents (Langstaff, 2007; U.S. EPA, 2007).

4.2 OZONE EXPOSURE STUDIES
Many studies have produced information and data supporting the development of methods for estimating human exposure to ambient O 3 over the past several decades. These studies have been reviewed in the current and previous EPA Ozone Air Quality Criteria Documents (U.S. EPA, 1986, 1996b, 2006c). The types of studies which provide the basis for modeling human exposure to O 3 include studies of people’s activities, work and ex ercise patterns, physiology, physics and O 3 -related chemistry in microenvironments , atmospheric modeling of O 3 , chamber studies of atmospheric chemistry, and modeling of meteorology. Measurem ents that have proven to be useful for understanding and estimating exposure obtaine d from personal exposure assessment studies include fixed-site ambient concentrations, conc entrations in specific indoor and outdoor microenvironments, personal exposure levels, pers onal activity patterns, air exchange rates, infiltration rates, deposition a nd decay rates, and meteorology.

4.2.1 Exposure Concepts and Definitions Human exposure to a contaminant is defined as “contact at a boundary between a human and the environment at a specific contaminant concen tration for a specific in terval of time,” and
has units of concentration times time (National Research Council, 1991). For airborne pollutants the contact boundary is nasal a nd oral openings in the body, and personal exposure of an
individual to a chemical in the air for a discrete time period is quantified as (Lioy, 1990; National Research Council, 1991): 

# ∫

= 2

1 

### ) ( ]

, [ 2

1 t

t 

### dt t C E t t (4-1)4-3 where E [ t 1 , t 2 ] is the personal exposure during the time period from t 1 to t 2 , and C( t ) is the
concentration at time t in the breathing zone. We refer to the exposure concentration to mean the concentration to which one is exposed. The br eathing rate (ventilation rate) at the time of exposure is an important determinant of the dose received by the individu al. Although we do not estimate dose, we refer to intake as the total amount of O 3 inhaled (product of exposure concentration, duration, and minute ventilation rate). Personal exposure to O 3 can be estimated directly by m onitoring the concentration of O 3 in the person’s breathing zone (close to the nose/mouth) using a pers onal exposure monitor. Exposure can also be estimated indirectly, by es timating or monitoring the concentrations over time in locations in which the individual spends time and estimating the time and duration the individual spends in each location. In both of th ese methods, Equation 4-1 is used to calculate an estimate of personal exposure. A key concept in modeli ng exposure is the microenvironment , a term that refers to the immediate surroundings of an individual. A microenvironment is a location in which pollutant concen trations are relatively homogeneous for short periods of time.
Microenvironments can be outdoor s or indoors; some examples are outdoors near the home, outdoors near the place of work, bedrooms, kitchens , vehicles, stores, rest aurants, street-corner bus stops, schools, and places of work. A bedroom may be treated as a different
microenvironment than a kitchen if the concentr ations are significantly different in the two
rooms. The concentrations in a microenvironm ent typically change ove r time; for example, O 3 concentrations in a kitchen while cooking with a gas stove may be lower than when these activities are not being perfor med, due to scavenging of O 3 by nitric oxide (NO) emissions from the gas burned. An important factor affec ting the concentrations of O 3 indoors is the degree to which the ambient outdoor air is transported indoors. This can be modeled using physical factors such as air exchange rates (AERs), deposition and d ecay rates, and penetration factors. The volumetric exchange rate (m 3 /hour) is the rate of air exchange be tween the indoor and outdoor air. The AER
between indoors and outdoors is th e number of complete air exch anges per hour and is equal to the volumetric exchange rate divided by the vol ume of the well-mixed indoor air. Indoor
concentrations of O 3 can be decreased by uptake of O 3 by surfaces and by chemical reactions.
The deposition and chemical decay rates are the rates (per hour) at which O 3 is removed from the air by surface uptake and chemical reactions. Some exposure models employ an infiltration factor, which is conceptually us eful if distinguishing between the air exchange processes of air blowing through open doors and windows and the inf iltration of air through smaller openings.
Since measurements of AERs account for both of these processes (including infiltration), this
distinction is not useful in applied modeling of O 3 exposures and will not be discussed further here. Simpler exposure models use a “factor model” approach to estimate indoor O 34-4 concentrations by multiplying the ambient outdoor concentrations by an indoor/outdoor concentration ratio, referred to as a penetration factor

.

4.2.2 Monitoring Equipment Considerations Exposure assessment studies i nvolve monitoring airborne O 3 and/or other pollutants, and monitor design and placement play a critical role in interpreting the results of these studies. For exposure assessment purposes there are two gene ral classes of monitors, personal exposure monitors (PEMs) and fixed site monitors. PEMs are designed to be worn or carried easily by individuals and to measure the concentrations experienced by individuals ove r a period of hours, days, or weeks. The placement of PEMs is important; the desired placemen t is usually in the breathing zone near the mouth and nose, but where the monitor will not be excessively impacted by exhaled air. This placement is intended to represent the concentrat ions the individual breathes in. PEMs typically report continuously measured O 3 concentrations with averag ing times ranging from 1 to 24
hours.
The CD reviews O 3 PEMS (CD, Appendix AX3, p. 163-5) and notes that humidity, wind velocity, badge placement, and interference with other pollutants may result in measurement error. The CD reports PEM de tection limits ranging from 5 to 23 ppb for averaging times from 24-hr to 1-hr, respectively.
Fixed-site monitors measure concentrations over time at a given location. There are
numerous fixed-site O 3 monitors which are part of nationa l, state, and local air monitoring networks. In addition to their role of being used to determine which areas are in compliance with existing O 3 NAAQS, these are also useful fo r alerting the public to high O 3 days, providing air quality data in support of photochemical modeli ng and exposure assessments for a study area, for tracking O 3 levels and trends, and for studying the repr esentativeness of measurements at these monitors for the study area. Existing fixed-si te monitors usually report hourly averaged concentrations, and are in operati on over a period of years. Fede ral reference and equivalent O 3 monitoring methods are required to have a lowe r detectable limit of 0.01 ppm and precision of 0.01 ppm for 1-hr average concen trations (40 CFR Ch. 1, §53.21). A discussion of monitoring equipment and networks can be found in Chapter 2 of this draft Staff Paper and in section 2.6 in
the CD.
There are also stationa ry monitors expressly set up for pa rticular exposure field studies.
These are used to measure concentrations over ti me in microenvironments, such as rooms in a home, just outside a home, roadsides, and so fo rth. The stationary monitors which are outdoors can provide information about community-scale re presentativeness of routinely operated fixedsite monitors in or near the community.4-5 4.2.3 Personal Ozone Exposure Assessment Studies

Useful PEM studies would have data collect ed repeatedly from each individual in the study over a period of time, yielding a longitudina l time series of hourly (or shorter) average concentrations each individual is exposed to. These studies would permit analysis of both the temporal and spatial variability of each person’s personal exposure to O 3
. Some studies could be de signed so that the data are sampled randomly from the population, which reduces bias and allows one to make inferences about exposure in the broader population. Most st udies addressing O 3 exposure have not been of random design and the measurement averaging times are longer than hou rly. They might have specific goals for which randomness is not required, or be subject to cons traints which do not allow for random sampling. These non-random studies have been helpful in the development of models of exposure; however, we recognize that they may not be representative of the broader population.

4.2.4 Microenvironmental Studies

The focus of microenvironmental studies is on measuring concentrations in different locations that people spend time in, as well as on measuring the movement of pollutants from
one microenvironment to another and on measur ing other parameters that contribute to variability in exposure. Typically, microenv ironmental measurements include indoor and
outdoor concentrations of O 3 and other pollutants, AERs, infiltration factors, deposition rates, decay rates, emissions of O 3 , NO x , VOCs, and other pollutants, ope rating characteristics of air conditioning systems, and meteorol ogical data such as wind veloci ty, temperature, and humidity.
The CD discusses several studies of microenviro nments that contribute to our understanding of the factors and processes th at affect exposure to O 3 (CD Appendix AX3, p. 191-216). There is a great deal of variability among i ndividuals in the amount of time spent indoors, but the majority of people spend most of their time indoors (Graham & McCurdy, 2004), and
therefore the concentrations of O 3 indoors can be an important determinant of people’s exposure

to O 3 . There are several factors affecting O 3 concentrations indoors. The ambient outdoor
concentration of O 3 and the AER are the primary determinan ts of the indoor concentrations. Removal processes are also significant, the most important of which is deposition onto indoor surfaces such as carpets, furnishings, and vent ilation ductwork. Chemical reactions of O 3 with other compounds, such as solvents from consumer products or nitric oxide emissions from gas stoves, also deplete O 3 indoors (Weschler, 2000; Monn, 2001). The primary sources of O 3 indoors are O 3 -generating air cleaners and some photocopiers and laser printers. Ozone genera tors can increase indoor concentra tions by more than 0.05 ppm. Some older photocopiers, if run continuously in an encl osed area, can increase O 3 concentrations4-6 by as much as 0.15 ppm. Older laser printers can produce concentrations of up to 0.18 ppm indoors (U.S. EPA, 1995; CARB, 2005).

4.3 EXPOSURE MODELING
Models of human exposure to airborne pollu tants are typically dr iven by estimates of
ambient outdoor concentrations of the pollutants, which vary by time of day as well as by
location. These outdoor concentr ation estimates may be provided by measurements, by air quality models, or by a combination of these. It is only possible to address hypothetical future scenarios using some form of modeling. The main purpose of this exposure analysis is to allow comparisons of population exposures to O 3 within each urban area, a ssociated with current air quality levels and with several potential alternat ive air quality standards or scenarios. Human exposure, regardless of the pollutant, depends on where an individual is located and what they are doing. Inhalation exposure models are useful in realistically estimating personal exposures and intake based on activity-specific ventilation rates, particularly when recognizing that these measurements cannot be performed for a give n population. This se ction provides a brief overview of the model used by EPA to estimate O 3 population exposure. Details about the application of the model to estimate O 3 population exposure are provided in the following sections and in the Exposure Analysis TSD (U.S. EPA, 2007).

4.3.1 The APEX Model The EPA has developed the APEX model for estimating human population exposure to criteria and air toxic pollutan ts. APEX also serves as the human inhalation exposure model within the Total Risk Integrated Methodology (TRIM) framework (Richmond et al., 2002; EPA 2006c). APEX is conceptually based on the probabilistic NAAQS Exposure Model (pNEM) that
was used in the last O 3 NAAQS review (Johnson et al., 199 6a; 1996b: 1996c). Since that time the model has been restructured, improved, and e xpanded to reflect conceptual advances in the science of exposure modeling and newer input data available for the model. Key improvements to algorithms include replacement of the cohort a pproach with a probabilistic sampling approach focused on individuals, accounting for fatigue an d oxygen debt after exercise in the calculation of ventilation rates, and a new approach for c onstruction of longitudina l activity patterns for simulated persons. Major improvements to da ta input to the mode l include updated AERs, census and commuting data, and the daily time- activities database. These improvements are described later in this chapter. APEX is a probabilistic model designed to account for the numerous sources of variability that affect people’s exposures. AP EX simulates the movement of individuals through time and space and estimates their exposure to a given pollutant in indoor, outdoor, and in-4-7 vehicle microenvironments. Figur e 4-1 provides a schematic overvie w of the APEX model. The model stochastically generates simulated in dividuals using census -derived probability distributions for demographic characterist ics (Figure 4-1, steps 1-3). The population demographics are drawn from the year 2000 Census at the tract level, and a national commuting database based on 2000 census data provides ho me-to-work commuting flows between tracts. 2 Any number of simulated individuals can be modeled, and collectively they approximate a random sampling of people residi ng in a particular study area. Daily activity patterns for individuals in a study area, an input to APEX, are obtained from detailed diaries that are compiled in th e Consolidated Human Ac tivity Database (CHAD) (McCurdy et al., 2000; EPA, 2002). The diaries ar e used to construct a sequence of activity
events for simulated individuals consistent with their demographic characteristics, day type, and season of the year, as define d by ambient temperature regi mes (Graham & McCurdy, 2004) (Figure 4-1, step 4). The time-location-activit y diaries input to APEX contain information regarding an individuals’ age, gender, race, em ployment status, occupation, day-of-week, daily maximum hourly average temperature, the location, start time, duration, and type of each activity performed. Much of this information is used to best match the activity diary with the generated personal profile, using age, gender, employment status, day of week, a nd temperature as firstorder characteristics. The appro ach is designed to capture the impor tant attributes contributing to an individuals’ behavior, and of particular relevance here, time spent outdoors (Graham and McCurdy, 2004). Furthermore, these diary selecti on criteria give credence to the use of the variable data that comprise CHAD (e.g., data co llected were from diff erent seasons, different states of origin, etc.). APEX calculates the concentration in the microenvironment associated with each event in an individual’s activity patter n and sums the event-spec ific exposures within each hour to obtain a continuous series of hourly exposures spanning the time period of interest (Figure 4-1, steps 5, 6). APEX has a flexible approach for modeli ng microenvironmental concentrations, where
the user can define the microenv ironments to be modeled and th eir characteristics. Typical indoor microenvironments include residences, sc hools, and offices. Outdoor microenvironments include near roadways, at bus stops, and playgr ounds. Inside cars, trucks, and mass transit
vehicles are microenvironments which are classified separately from indoors and outdoors.

2 There are approximately 65,400 census tracts in the ~3,200 counties in the U.S.- Nationaldatabase- Area-specificinput data- Intermediate stepor data- Simulationstep- Data processor- Output dataSector location data(latitude, longitude)Defined study area (sectorswithin a city radius and with airquality and meteorological datawithin their radii of influence)Sector population data(age/gender/race)Population withinthe study areaCommuting flow data(origin/destination sectors)Age/gender-specificphysiologicaldistribution data (bodyweight, height, etc)Distribution functions forprofile variables(e.g, probability of airconditioning)Locations of air quality andmeteorological measurements;radii of influenceStochasticprofile generatorDistribution functionsfor seasonal and dailyvarying profile variables(e.g., window status, carspeed)A simulated individual with thefollowing profile:• Home sector• Work sector (if employed)• Age• Gender• Race• Employment status• Home gas stove• Home gas pilot• Home air conditioner• Car air conditioner• Physiological parameters(height, weight, etc.)2000 Census tract-level data for the entire U.S. (sectors=tracts for the NAAQS ozone exposure application)Age/gender/tract-specificemployment probabilities1. Characterize study area2. Characterize study population3. Generate N number ofsimulated individuals (profiles)Figure 4-1. Overview of the APEX Model4-8Diary events/activitiesand personal information(e.g., from CHAD)Maximum/mean dailytemperature dataActivity diary pools by daytype/temperature categoryEach day in the simulationperiod is assigned to anactivity pool based on day typeand temperature categorySelected diary records for each day in the simulationperiod, resulting in a sequence of events(microenvironments visited, minutes spent, andactivity) in the simulation period, for an individualStochastic diaryselector usingage, gender, andemploymentStochasticcalculation of energyexpended per event (adjusted forphysiological limits and EPOC)and ventilationratesPhysiologicalparameters fromprofileSequence of events for anindividualProfile for anindividual4. Construct sequence of activity eventsfor each simulated individualFigure 4-1. Overview of the APEX Model, continued4-9Hourly air qualitydata for all sectorsSelect calculation method foreach microenvironment:• Factors• Mass balanceConcentrations for all eventsfor each simulated individualHourly concentrations andminutes spent in eachmicroenvironment visited bythe simulated individualAverage exposuresfor simulated person,stratified by ventilationrate:• Hourly• Daily 1-hour max• Daily 8-hour max• Daily...Microenvironments defined bygrouping of CHAD location codesCalculate hourlyconcentrations inmicroenvironmentsvisitedPopulation exposureindicators for:• Total population• Children• Asthmatic childrenSequence of events foreach simulated individualCalculateconcentrations in allmicroenvironments5. Calculate concentrations inmicroenvironments for all events foreach simulated individual6. Calculate hourlyexposures for eachsimulated individual7. Calculatepopulation exposurestatisticsFigure 4-1. Overview of the APEX Model, concluded4-104-11 Activity-specific simulated breathing rates of individuals are used in APEX to characterize intake received from an exposure. These breathing, or ventilation, rates are derivedfrom energy expenditure estimates for each activity included in CHAD and are adjusted for ageand gender-specific physiological parameters associ ated with each simulated individual. Energy expenditure estimates themselves are derived from METS (metabolic equivalents of work)
distributions associated with every activity in CHAD (McCurdy et al., 2000), largely based upon the Ainsworth et al. (1993) “Compendium of Ph ysical Activities.” METS are a dimensionless ratio of the activity-specific ener gy expenditure rate to the basa l or resting en ergy expenditure rate, and the metric is used by exercise physiologists and clinical nutritionists to estimate work undertaken by individuals as th ey go through their daily life (Montoye et al., 1996). This approach is discussed more thoroughly in McCurdy (2000).

4.3.2 Key Algorithms

Ozone concentrations in each microenvir onment are estimated using either a massbalance or transfer factors approach, and the us er specifies probability distributions for the parameters that are used in the microenvironment model that reflect the observed variabilities in the parameters. These distributi ons can depend on the values of ot her variables calculated in the model or input to APEX. For example, the distribution of AERs in a home, office, or car can depend on the type of heating and air conditioning pr esent, which are also st ochastic inputs to the model, as well as the ambient temperature. The us er can choose to keep th e value of a stochastic parameter constant for the entire simulation (whi ch would be appropriate for the volume of a house), or can specify that a new value shall be drawn hourly, daily, or seasonally from specified
distributions. APEX also allows the user to specify diurnal, weekly, or seasonal patterns for various microenvironmental parameters. The di stributions of parameters input to APEX characterize the variability of parameter values, and are not intended to reflect uncertainties in the parameter estimates.
The mass balance method used within APEX assumes that the air in an enclosed
microenvironment is well-mixed and that the air concentration is fairly spatially uniform at a given time within the microenv ironment. The following four processes are modeled to predict the concentration of an air pollutant in such a microenvironment:

• Inflow of air into the microenvironment;

• Outflow of air from the microenvironment;

• Removal of a pollutant from the microe nvironment due to deposition, filtration, and chemical degradation; and

• Emissions from sources of a polluta nt inside the microenvironment.4-12 The transfer factors model is simpler than the mass balance model, however, still most parameters are derived from distributions rath er than single values, to account for observed variability. It does not calculate concentration in a microenvi ronment from the concentration in the previous hour and it has only two paramete rs, a proximity factor, used to account for proximity of the microenvironment to sources or sinks of pollution, or other systematic differences between concentrations just out side the microenvironment and the ambient concentrations (at the measurements site), and a penetration factor, which quantifies the degree to which the outdoor air penetrates into the microenvironment. When there are no indoor sources, the penetration factor is essentia lly the ratio of the concentration in the
microenvironment to the outdoor concentration. Regardless of the method used to estimate the microenvironmental concentrations, APEX calculates a time series of exposur e concentrations that a simulate d individual experiences during the modeled time period. APEX estimates the e xposure using the concentrations calculated for each microenvironment and the time spent in eac h of a sequence of microenvironments visited according to the “activity diary” of each indivi dual. The hourly average exposures of each
simulated individual are time-wei ghted averages of the within -hour exposures. From hourly exposures, APEX calculates the tim e series of 8-hr and daily av erage exposures that simulated individuals experience during the simulation period. APEX then statistically summarizes and tabulates the hourly, 8-hr , and daily exposures.

4.3.3 Model Output

There are several useful indicators of exposure and intake of people to O 3 air pollution. Factors that are important include the magnitude and duration of e xposure, frequency of repeated high exposures, and the breathing rate of individuals at the time of exposure. In this analysis, exposure indicators include daily ma ximum 1-hr and 8-hr average O 3 exposures, stratified by a
measure of the level of exertion at the time of exposure. The le vel of exertion of individuals engaged in particular activities is measured by an equivalent ventilation rate (EVR), ventilation normalized by body surface area (BSA, in m 2 ), which is calculated as V E /BSA, where V E is the ventilation rate (liters/minute). Table 4-1 lists the ranges of EVR corresponding to moderate and heavy levels of exertion.

Table 4-1. Exertion levels in terms of equivalent ventilation rates (liters/min-m 2 ) Averaging time Moderate exertion Heavy exertion
1 hour 16-30 EVR ≥ 30 EVR
8 hour 13-27 EVR ≥ 27 EVR from Whitfield et al., 1996, page 15.4-13 APEX calculates two genera l types of exposure estimates: counts of the estimated number of people exposed to a specified O 3 concentration level and the number of times per O 3 season that they are so exposed; the latter metric is in terms of person-occurrences or persondays. The former highlights the number of individuals exposed one or more times per O 3 season to the exposure indicator of interest. In the case where the exposure indicator is a benchmark concentration level, the model estimates the num ber of people who are expected to experience exposures to that level of air pollution, or higher, at least onc e during the modeled period. APEX also reports counts of individuals with multip le exposures. The person-occurrences measure estimates the number of times per season that in dividuals are exposed to the exposure indicator
of interest and then accumulates these estimates for the entire population residing in an area. This metric conflates people and occurrences: one occurrence for each of 10 people is counted the same as 10 occurrences for one person. APEX tabulates and displays the two measur es for exposures above levels ranging from 0.0 to 0.16 ppm by 0.01 ppm increments , where the exposures are:

• Daily maximum 1-hour average exposures

• Daily maximum 8-hour average exposures

• Daily average exposures.

These results are tabulated for the following population groups:

• All ages and activity levels

• Children at all activity levels

• Asthmatic children. Separate output tables are produced for differe nt levels of exertion concomitant with the
exposures:

• All exertion levels

• Moderate exertion levels

• Heavy exertion levels. APEX also produces tables of the time spent in different microenvironments, stratified by exposure levels.

4.3.4 Strengths and Limitations of the Model APEX has a strong scientific foundation and in corporates several si gnificant algorithmic improvements and updates to input data since it ’s predecessor, pNEM, was used in the last
review. In this section we disc uss qualitatively some of the ge neral strengths and limitations of the application of APEX to model population exposures to O 3 pollution. The discussion is
divided into four fundamental areas: estimation of ambien t air quality, estimation of concentrations in microenvironments, characteri zation of population dem ographics and activity patterns, and modeling physiologi cal processes as applicable to this exposure assessment.4-14 Additional details for advancements made to th e model of specific relevance for this ozone exposure assessment are given in section 4.5. In general, limitations and uncertainties resu lt from variability not modeled or modeled incorrectly, erroneous or uncertain inputs, errors in coding, simplif ications of physical, chemical, and biological processes to form the conceptual model, and flaws in the conceptual model. The implications of these limitations for the uncertainty of the APEX results is discussed in Langstaff (2007).

4.3.4.1 Estimation of Am bient Air Quality For estimating ambient O 3 concentrations to use in the exposure model, the urban areas modeled here have several monitors measuring hourly O 3 concentrations. Having multiple monitors in the simulated areas collecting time-reso lved data allows for the utilization of APEX spatial and temporal capabilities in estimating exposure. Since APEX uses actual records of where individuals are located at specific times of the day, more realistic exposure estimates are obtained in simulating the contac t of individuals with these sp atially and temporally diverse concentrations. Primary uncertainties in the air quality data input to the model result from estimating concentrations at locations which may not be in close proximity to monitoring sites (as estimated by spatial interpola tion of actual data points) and from the method used to estimate missing data. In addition, concentrations of O 3 near roadways are part icularly difficult to
estimate due to the rapid reaction of O 3 with nitric oxide emitted from motor vehicles.
We have modeled the O 3 seasons for 2002, 2003, and 2004, to better account for year-toyear variability of air quality and meteorology. For most of the 12 areas modeled, O 3 concentrations were lower in 2004 than previ ous years, due to a combination of reduced emissions of precursors and weather pattern s less conducive to the formation of O 3 . Having this wide range of air quality data across multiple years available for use in the exposure simulation has a direct impact on more realistically estimati ng the range of exposures, rather than using a single year of air quality data. Modeling exposures for an unspecified future year simulated to just meet alternative air quality standards has, in addition to the un certainties involved with modeling historical scenarios, the uncertainties of the complex proc ess of projecting to fu ture years air quality, population demographics, activity patterns, and othe r changing parameters. For the purpose of estimating population exposure as an input to de cisions about the approp riate level of a NAAQS, EPA has historically not incorporated any pr ojections in population demographics, activity patterns, or other factors (e.g., air conditioning use, changes in housing types, etc). This allows policy makers to focus on the impact of changing the allowed air quality distribution on4-15 population exposure and public health while avoidi ng the additional uncertainties that inclusion
of these other factors would introduce.

4.3.4.2 Estimation of Concentrations in Indoor Microenvironments The importance of estimation of concentrations in indoor microenvironments (e.g., homes, offices, schools, rest aurants, vehicles) is undersco red by the finding that personal exposure measurements of O 3 are often not well-correlated w ith ambient measurements (CD, pages 3-59 to 3-61). APEX has been designed to better estim ate human exposure through use of algorithms that attempt to capture the full range of O 3 concentrations expected within several important
microenvironments. Parameters used to estimate the concentrations in microenvironments can be highly variable, both between microenvir onments (e.g., different houses have varying characteristics) and within microenvironments (e .g., the characteristics of a given house can vary over time). Since APEX is a probabilistic model, if data accurately characterizing this variability are provided to the model, then such variab ilities would not result in uncertainties in the
estimation of the microenvironmental concentrati ons. Thus, it is the input data used in development of the parameters that are the lim iting factor, and to date, APEX uses the most
current available data to devel op required input parameters for estimation of microenvironmental
concentrations.

Air Exchange Processes The AER is the single most important factor in determining the relationship between
outdoor and indoor concentrations of O 3 . AERs are highly variable, both within a
microenvironment over time and between microenvi ronments of the same type. AERs depend on the physical characteristics of a microenvironment and also on the behavior of the occupants of the microenvironment. There is a strong dependence on temperature, and some dependence on other atmospheric conditions. APEX uses proba bilistic distributions of AERs which were
derived from several measurement studies in a number of locations, and are stratified by both temperature and the presence or absence of air conditioning. These two variables are the most
influential variables influenci ng AER distributions (see Appendix A of the Exposure Analysis TSD).

Removal Processes
Concentrations within indoor microenvir onments can be reduced due to removal processes such as deposition to surfaces and by react ion with other chemicals in the air. The rate of deposition of O 3 to a surface depends on the surface composition, the humidity, and the
concentration of O 3 . The rate of removal of O 3 from a microenvironment depends on its dimensions, the ratio of surface area to volume, and of course the presence, amount, and type of4-16 surface coverings and furnishings in the mi croenvironment. Deposition is modeled probabilistically in APEX by a us ing a distribution of decay rates derived from a study that measured decay rates in 26 homes in Southern Ca lifornia (Lee et al., 1999). Although it is not expected that inter-city differences in decay rates would be more important than differences between homes within cities, there is uncertainty given the small sample size the distribution was derived from. The lack of capturing inter-city vari ability in decay rates is not anticipated to be a large contributor to the uncertainty in the modeling results. There can be additional O 3 loss, which is not currently modeled, due to the use of HVAC systems, which significantly increase
the effective surface area as air reci rculates through ductwork and filters. Ozone reacts with a number of indoor polluta nts, such as nitric oxide from gas stoves and VOCs from consumer products. With the exception of nitric oxide, O 3 reacts slowly with most indoor pollutants, and this is t ypically a less influential removal process than air exchange and surface removal (Weschler, 2000). The lack of a be tter treatment of indoor air chemistry is not considered to be a significant limitation of APEX for modeling O 3
.

4.3.4.3 Characterization of Population De mographics and Activity Patterns The approach to reasonably estimating e xposure considering a va riety of alternative scenarios is best done using models that bett er represent the contac t of a human with the contaminant of concern. By using actual time-lo cation-activity diaries that capture the duration and frequency of occurrence of visitations/activ ities performed, APEX can simulate expected variability in human behavior, both within and between indivi duals. Fundamentals of energy expenditure are then used to estimate relative in tensity of activities performed. This, combined with microenvironmental concentrations, allows for the reasonable estimation of the magnitude, frequency, pattern, and duration of e xposures an indivi dual experiences.
CHAD is the best source of human activ ity data for use in exposure modeling. The database contains time-location-activity patterns for individuals of both genders across a wide range of ages (0-99). The database is geographi cally diverse, containing diaries from individuals residing in major cities, suburban and rural ar eas across the U.S. Time spent performing activities within particular locations can be on a minute-by minute basis, thus avoiding the smoothing of potential peak exposures longer time periods would give.
There are some limitations to the databa se, however, many of which are founded in the
individual studies from which activity patterns were derive d (Graham and McCurdy, 2004). A few questions remain regarding the represen tativeness of CHAD diaries to the simulated population, such as the numbers of diaries available for use in a simulation (i.e., 20,000 used to represent several million people over long periods of time), the age of diary data (i.e., some data were generated in the 1980s), and diary structur e differences (i.e., real- time versus recall method4-17 of data collection). Many of the assumptions about use of these activity patterns in exposure modeling are strengthened by the manner in wh ich they are used by APEX, through focusing on the most important individual attributes that co ntribute to variability in human behavior (e.g., age, gender, time spent outdoors, day of week, ambient temperature, occupation). The extent to which the human activity data base provides a balanced representation of the population being modeled is likely to vary across areas. Alt hough the algorithm that constructs activity sequences accoun ts to some extent for the e ffects of population demographics and local climate on activity, this adjustment procedure may not account for all inter-city differences in people’s activities . A new methodology has been deve loped to more appropriately assign individual diaries to reflect time-location-activity patterns in simulated individuals (discussed further in section 4.5.3). Input di stributions used in the new procedure for constructing multi-day activity patterns are based on longitudinal activity data from children of a specific age range (appropriate for this applicatio n where similar aged children are simulated), however the data used were limited to one study and may not be appropriate for other simulated individuals. Thus, there are li mitations in approximating with in-person variance and betweenperson variance for certain variables (e.g., time sp ent outdoors). Personal activity patterns are also likely to be affected by many local factor s, including topography, land use, traffic patterns, mass transit systems, and recreational opportunities , which are not incorporated in the current exposure analysis approach due to the complexity of scale and lack of data to support the development of a reasonable approach.

4.3.4.4 Modeling Physiological Processes The modeling of physiological processes that are relevant to the e xposure and intake of

O 3 is a complicated endeavor, particularly when attempting to capture inter- and intra-personal variability in these rates. APEX has a physio logical module capable of estimating ventilation rates (V E ) for every activity perfor med by an individual, which primarily drives O 3 intake dose
rate estimates. See section 2.5 of the draft Exposure Assessment TSD for a discussion of this module. Briefly, the module is based on the relationship between en ergy expenditure and oxygen consumption rate, thus both within- and between-person variab ility in ventilation can be addressed through utilization of the unique sequence of events individuals go through each simulated day. These activity-specific V E estimates, when normalized by BSA, are then used to
characterize an individual’s ex ertion level in compiling the su mmary exposure tables (Table 4-1). One of the key determinants of estimated V E is the exertion level of an individual’s activity, where exertion levels have units of metabolic equivalent s of work (MET), which is the ratio of energy expenditure for an activity to th e person’s basal, or resting, metabolic rate.4-18 There are some limitations in using MET va lues for this purpose, due mostly to the manner in which the time-location-activity diaries were generated and subsequent estimates of exertion level. An individual (o r their caregiver if younger than eight years old) would record the activity performed with a st art and end time, with no information on the associated exertion level of the activity. Exerti on level (MET) was then inferred by developers of the CHAD database (McCurdy et al., 2000) using standard valu es and distributions of those values reported by a expert panel of exercise physiologists (Ainsworth et al ., 1993). Although this approach allows for an appropriate range of exertion levels to be assigned to the individuals’ activities (and to the simulated population), children’s activ ity levels fluctuate widely within a single activity category; their pattern is often characte rized as having bursts of high energy expenditure within a longer time frame of less energy expe nditure (Freedson, 1989). These fluctuations in energy expenditure that occur within an activ ity (and thus a simulated event) are not well captured by the MET assignment procedure.

4.4 SCOPE OF EXPOSURE ASSESSMENT

4.4.1 Selection of Urban Areas to be Modeled

The selection of urban areas to include in the exposure analysis ta kes into consideration
the location of O 3 epidemiological studies, the availability of ambient O 3 data, and the desire to represent a range of geographic ar eas, population demographics, and O 3 climatology. These selection criteria are discussed further in Chap ter 5. Based on these criteria, we chose the 12
urban areas listed in Table 4-2 to develop population exposure estimates. 3 The geographic extent
of each modeled area consists of the census tracts in the combined statistical area (CSA) as defined by OMB (OMB, 2005).

4.4.2 Time Periods Modeled The exposure periods modeled are the O 3 seasons for which routine hourly O 3 monitoring data are available. These periods include mostof the high-ozone even ts in each area. The
seasons modeled for each area are listed in Table 4-2.

4.4.3 Populations Modeled Exposure modeling was conducted for the ge neral population residing in each area modeled, as well as for school-age children (age s 5 to 18) and asthmatic school-age children. Due to the increased amount of time spent outdoors engaged in relatively high levels of physical activity (which increases intake), school-age children as a group are particularly at risk for experiencing O 3 -related health effects. We report re sults for school-age children down to age

3 In the remainder of this chapter the city name in bold in Table 4-2 is used to represent the entire CSA.4-19 Table 4-2. Urban areas and time periods modeled
Urban Area (CSA) Period modeled

Atlanta -Sandy Springs-Gainesville, GA-AL March 1 to Oct. 31

Boston -Worcester-Manchester, MA-NH April 1 to Sept. 30 Chicago -Naperville-Michigan City, IL -IN-WI April 1 to Sept. 30

Cleveland -Akron-Elyria, OH April 1 to Oct. 31

Detroit -Warren-Flint, MI April 1 to Sept. 30

Houston -Baytown-Huntsville, TX Jan. 1 to Dec. 30 Los Angeles -Long Beach-Riverside, CA Jan. 1 to Dec. 30

New York -Newark-Bridgeport, NY-NJ-CT-PA April 1 to Sept. 30 Philadelphia -Camden-Vineland, PA-NJ-DE-MD April 1 to Oct. 31

Sacramento --Arden-Arcade--Truckee, CA-NV Jan. 1 to Dec. 30

St. Louis -St. Charles-Farmington, MO-IL April 1 to Oct. 31 Washington -Baltimore-N. Virginia, DC-MD-VA-WV April 1 to Oct. 31

five, however, there is a trend for younger children to attend school. Some states allow 4-yearolds to attend kindergarten, and more than 40 states have preschool programs for children younger than five (Blank and Mitchell, 2001). In 2000, six percent of U.S. children ages 3 to 19 who attend school were younger than five years old (2000 Census Summary File 3, Table QTP19: School Enrollment). We are not taking thes e younger children into ac count in our analysis
due to a lack of information which would let us characterize th is group of children. The population of asthmatic children is estimated for each city using asthma prevalence
data from the National Health Interview Su rvey (NHIS) for 2003 (Dey and Bloom, 2005). Asthma prevalence rates for children aged 0 to 17 years were calculated for each age, gender, and geographic region. The regi ons defined by NHIS are “Midwest ,” “Northeast,” “South,” and “West.” For this analysis, asthma prevalence was defined as the probability of a “Yes” response to the question: “Ever been told that ... had asthma?” among thos e that responded “Yes” or “No” to this question. The responses were weighted to take into account the complex survey design of the NHIS survey. Standard errors and confidence intervals for the prevalence were calculated using a logistic model, taking in to account the survey design. A scatter plot smoothing technique using the LOESS smoother was applied to sm ooth the prevalence curves and compute the
standard errors and confidence intervals for th e smoothed prevalence estimates. Logistic analysis of the prevalence curves shows statis tically significant diffe rences in prevalence by4-20 gender and by region. Therefore we did not combine the prevalence rates for different genders or regions. A detailed descrip tion of this analysis is presented in the Exposure Analysis TSD. The “modeled population” column in Table 4-3 lists the year 2000 populations of the
modeled CSAs. The 12 modeled areas combined re present 40 percent of the total U.S. urban population (approximately 222 million in 2000). Ta ble 4-3 also gives the modeled populations of children ages 5-18 and children ages 5-18 characterized as asthmatic.

Table 4-3. Population coverage of modeled areas (2002 analysis)
Urban Area (CSA) Modeled population (thousands) Modeled children 1 (thousands) Asthmatic children (thousands) Atlanta 4,548 943 117 Boston 5,714 1,096 182 Chicago 9,311 1,951 279 Cleveland 2,945 594 89 Detroit 5,357 1,110 162 Houston 4,815 1,089 136 Los Angeles 16,371 3,667 457 New York 21,357 4,147 643 Philadelphia 5,832 1,186 193 Sacramento 1,930 412 51 St. Louis 2,754 582 83 Washington, DC 7,572 1,485 187 Total of all 12 areas 88,506 18,262 2579

1 ages 5-18.

4.5 INPUTS TO THE EXPOSURE MODEL
The data inputs to the APEX model are briefly described in this section. A more detailed description of the development of these data an d the derivation of input distributions can be found in the Exposure Analysis TSD.

4.5.1 Population Demographics APEX takes population characteristics into acco unt to develop accurate representations of study area demographics. Population counts a nd employment probabilities by age and gender are used to develop representative profiles of hypothetical individuals fo r the simulation. Tractlevel population counts by age in one-year increments, from birth to 99 years, come from the4-21 2000 Census of Population and Housing Summary F ile 1. The Summary File 1 contains the 100- percent data, which is the information compiled fr om the questions asked of all people and about every housing unit. Employment data from the 2000 Census provide employment probabilities for each gender and specific age groups for every Census tract. The employment age groupings are: 16- 19, 20-21, 22-24, 25-29, 30-34, 35-44, 45-54, 55-59, 60-61, 62-64, 65-69, 70-74, and >75 years of age. Children under the age of 16 are assigned employment probabilities of zero.

4.5.2 Population Commuting Patterns To ensure that individuals’ daily activities are accurately represented within APEX, it is important to integrate working patterns into the assessment. The APEX commuting data are
derived from the 2000 Census and collected as part of the Census Transportation Planning Package (CTPP). CTPP contains tabulations by place of residence, place of work, and the flows
between the residence and work. These data are available from the U.S. Department of Transportation, Bureau of Transportation Statistics (U.S. Department of Transportation and U.S. Census Bureau, 2000). For school age children we have not incl uded commuting to and from school. This results in the implicit assumption that children attend a school with ambient O 3 concentrations
similar to concentrations near their residence. To the extent that the highest ozone levels are generally in the period June th rough August when most students ar e not in school, the absence of school commuting is less likely to have a signifi cant impact on the exposure estimates. As more communities go to year-round schools, school commuting patterns may become important to
model. It is assumed that all pe rsons with home-to-work distances up to 120 km are daily commuters, and that persons who travel furthe r than 120 km do not commute daily. Therefore the list of commuting destinations for each home trac t is restricted to only those work tracts that
are within 120 km of the home tract. APEX allows the user to specify how to ha ndle individuals who commu te to destinations outside the study area. One option is to drop them from the simu lation. If they are included, the user specifies values for two additional parameters, called L M

and L A (M ultiplicative and

A dditive factors for commuters who L eave the area). While a commuter is at work, if the workplace is outside the study area , then the ambient concentration cannot be determined from any air district (since districts ar e inside the study area). Instead, it is assumed to be related to the average concentration C AVE ( t ) over all air districts at the time in question. The ambient concentration outside the study area at time t , C OUT ( t ), is estimated as:

C OUT ( t ) = L M

* C AVE ( t ) + L A (4-2)4-22 The microenvironmental concentration (for ex ample, in an office outside the study area)
is determined from this ambient concentration by the same model (mass balance or factor) as applies inside the study area. The parameters L M

and L A were both set to zero for this modeling analysis; thus, exposures to indivi duals are set to zero when they are outside of the study area. Although this tends to underestimate exposures, it is a small effect and this was done since we
have not estimated ambien t concentrations of O 3 in counties outside of the modeled areas.

4.5.3 Human Activity Data The human activity data are drawn from the most recent version (December 2000) of the Consolidated Human Activity Database (CHAD) (McCurdy et al., 2000; EPA, 2002), developed and maintained by the Office of Research and Development’s (ORD ) National Exposure Research Laboratory (NERL). The CHAD include s data from several surveys covering specific time periods at city, state, and national levels, w ith varying degrees of re presentativeness. Table
4-4 summarizes the studies in CHAD used in this modeling analys is, providing nearly 16,000 diary-days of activity data (3,075 diary-days for ages 5-18) collected between 1982 and 1998. A key issue in this assessment is the development of an approach for creating O 3 -season or year-long activity sequences for individuals ba sed on a cross-sectional activity data base of 24-hour records. The typical subject in the tim e/activity studies in CHAD provided less than two days of diary data. For this reason, the constr uction of a season-long activity sequence for each individual requires some combination of repeating the same data from one subject and using data from multiple subjects. An appropriate appro ach should adequately account for the day-to-day and week-to-week repetition of activities common to individuals while maintaining realistic variability between individuals. The method in APEX for creating longitudinal diaries was designed to capture the tendency of individuals to repeat activiti es, based on reproducing realistic variation in a key diary variable, which is a user-selected function of diary variables. For this analysis the key variable is se t to the amount of time an i ndividual spends outdoors each day, which is one of the most important determ inants of exposure to high levels of O 3
. The actual diary construction method targets tw o statistics, a population diversity statistic ( D ) and a within-person autocorrelation statistic ( A ). The D statistic reflects the relative importance of within-person variance and betw een-person variance in the key variable. The A statistic quantifies the lag- one (day-to-day) key variab le autocorrelation. Desired D and A values for the key variable are selected by the user and set in the APEX parameters file, and the method algorithm constructs longitudinal diaries that pres erve these parameters. Longitudinal diary data from a field study of school-age children (Geyh et al., 2000) and subsequent analyses (Xue et al., 2004) suggest that D and A are stable over time (and perhaps over cohorts as well). Based on these studies of children ages 7-12, appropriate target values for the two statistics for outdoor4-23Table 4-4. Studies in CHAD used in this analysisStudy name GeographiccoverageStudy timeperiodSubjectagesDiarydaysDiary-days(ages 5-18)Diary type andstudy designReferenceBaltimore One buildingin Baltimore01/1997-02/1997,07/1998-08/199872 - 93 292 0 Diary Williams et al. (2000)CaliforniaAdolescents (CARB)California 10/1987-09/1988 12 - 17 181 181 Recall; Random Robinson et al. (1989),Wiley et al. (1991a)California Adults(CARB)California 10/1987-09/1988 18 - 94 1,552 36Recall; Random Robinson et al. (1989),Wiley et al. (1991a)California Children(CARB)California 04/1989- 02/1990 <1 - 11 1,200683 Recall; Random Wiley et al. (1991b)Cincinnati (EPRI) Cincinnatimetro. area03/1985-04/1985,08/1985<1 - 86 2,587 740 Diary; Random Johnson (1989)Denver (EPA) Denvermetro. area11/1982- 02/1983 18 - 70 791 7 Diary; Random Johnson (1984), Aklandet al. (1985)Los Angeles:Elementary SchoolLos Angeles 10/1989 10 - 12 51 51 Diary Spier et al. (1992)Los Angeles: HighSchoolLos Angeles 09/1990-10/1990 13 - 17 42 42 Diary Spier et al. (1992)National: NHAPS-Air National 09/1992-10/1994 <1 -93 4,326 634 Recall; Random Klepeis et al. (1996),Tsang and Klepeis (1996)National: NHAPSWaterNational 09/1992-10/1994 <1 - 93 4,332 691Recall; Random Klepeis et al. (1996),Tsang and Klepeis (1996)Washington, D.C.(EPA)Wash., D.C.metro. area11/1982-02/1983 18 - 98 639 10 Diary; Random Hartwell et al. (1984),Akland et al. (1985)Total diary days 15,993 3,0754-24 time are determined to be 0.2 for D and 0.2 for A . In the absence of data for estimating these statistics for younger children and ot hers outside the study age range, these values are used for all ages. This new method for constructing longitudina l diaries from the CHAD data is described in detail in the Exposure Analysis TSD.

4.5.4 Physiological Data APEX requires values for various physiologi cal parameters for subjects in order to accurately model their metabolic processes that affect pollutant intake. This is because physiological differences may cause people with the same exposure and activity scenarios to have different pollutant intake levels. The physiolo gical parameters file distributed with APEX contains physiological data or distributions by age and gender for maximum ventilatory capacity (in terms of age- and gender-specific ma ximum oxygen consumption potential), body mass, resting metabolic rate, and oxygen consump tion-to-ventilation ra te relationships.

4.5.5 Microenvironments Modeled In APEX, microenvironments provide the expos ure locations for modeled individuals. For exposures to be accurately estimated, it is important to have realistic microenvironments that are matched closely to where people are physically locat ed on a daily and hourly basis. As discussed in section 4.3.2 above, the two methods available in APEX for calculating po llutant concentrations
within microenvironments are a mass balance mode l and a transfer factor approach. Table 4-5
lists the 12 microenvironments sele cted for this analysis and th e exposure calculation method for each. The parameters used in this analysis for modeling these microenvironments are described in
this section.

4.5.5.1 Air Exchange Rates for Indoor Residential Environments

Distributions of AERs for th e indoor microenvironments were developed using data from several studies. The analysis of these data and the development of the distributions used in the modeling are described in detail in the Exposure Analysis TSD. This analysis showed that the AER distributions for the residential microenvironments depend on the type of air conditioning (A/C) and on the outdoor temperature, as well as other variables for which we do not have sufficient data to estimate. This analysis clear ly demonstrates that th e AER distributions vary greatly across cities and A/C types and temperatures, so that the se lected AER distributions for the modeled cities should also depend upon the city, A/ C type, and temperature. For example, the mean AER for residences with A/C ranges from 0.39 for Los Angeles between 30 and 40 oC to
1.73 for New York between 20 and 25 oC. The m ean AER for residences without A/C ranges from 0.46 for San Francisco on days with te mperature between 10 and 20 oC to 2.29 for4-25 Table 4-5. Microenvironments modeled by APEX

Microenvironment Calculation Method Parameters 1

Indoors – Residence Mass balance AER and DE

Indoors – Bars and restaurants Mass balance AER and DE

Indoors – Schools Mass balance AER and DE Indoors – Day-care centers Mass balance AER and DE

Indoors – Office Mass balance AER and DE Indoors – Shopping Mass balance AER and DE

Indoors – Other Mass balance AER and DE

Outdoors – Near road Factors PR Outdoors – Public garage/parking lot Factors PR

Outdoors – Other Factors None

In-vehicle – Cars and Trucks Factors PE and PR

In-vehicle – Mass Transit Factors PE and PR

1 AER=air exchange rate, DE=decay-deposition rate , PR=proximity factor, PE=penetration factor

New York on days with temperature between 20 a nd 25 oC. The need to account for the city as well as the A/C type and temperature is illustra ted by the result that for residences with A/C on days with temperature between 20 and 25 oC, the mean AER ranges from 0.52 for Research Triangle Park to 1.73 for New York. For each co mbination of A/C type, city, and temperature with a minimum of 11 AER values, exponential, lognormal, normal, and Weibull distributions were fit to the AER values and compared. Ge nerally, the lognormal di stribution was the bestfitting of the four distributions, and so, for cons istency, the fitted lognormal distributions are
used for all the cases. One limitation of this analysis was that distributions were available only for selected cities, and yet the summary statistics and comp arisons demonstrate that the AER distributions depend upon the city as well as the temperatur e range and A/C type. Another important limitation of the analysis was that distributions were not able to be fitted to all of the temperature ranges due to limited data in these ranges. A desc ription of how these limitations were addressed can be found in the Exposure Analysis TSD. City-specific AER distributions were used where possible; otherwise data for a similar city were used. We obtained estimates of A/C prevalence from the American Housing Survey (AHS, 2003) for each metropolitan area. The fina l AER distributions used for the exposure modeling are given the Exposure Analysis TSD.4-26 Some residences, particularly in the Southwest, use evapor ative coolers, also known as “swamp coolers,” for cooling. We performed an analysis of AER distributions of residences without A/C, with and without evaporative cool ers, using data from three AER measurement studies. This comparison is described in Appe ndix F in the Exposure Analysis TSD. This analysis showed no improvement in the statistical air exchange model when the data were also stratified by evaporative cooler pr esence or absence, given that they are already stratified by CSA, air conditioner presence or absence, and outdoor temperature range.

4.5.5.2 AER Distributions for Other Indoor Environments

To estimate AER distributions for non-reside ntial, indoor environments (e.g., offices and schools), we obtained and analyzed two AER data sets: “Turk” (Turk et al., 1989); and “Persily” (Persily and Gorfain, 2004; Persil y et al., 2005). The earlier Turk data set includes 40 AER measurements from offices (25 values), schools (7 values), libraries (3 values), and multipurpose buildings (5 values), each measured using an SF 6 tracer over two or four hours in different seasons of the year. The more recent Persily data were derived from the U.S. EPA Building Assessment Survey and Evaluation (BASE) study, which was conducted to assess indoor air quality, including vent ilation, in a large number of random ly selected office buildings throughout the U.S. This data base consists of a total of 390 AER measurements in 96 large, mechanically ventilated offi ces. AERs were measured both by a volumetric method and by a

CO 2 ratio method, and included thei r uncertainty estimates. For these analyses, we used the recommended “Best Estimates” defined by the values with the lower estimated uncertainty; in the vast majority of cases the best estimate was from the volumetric method. Due to the small sample size of the Turk data, the data were analyzed without stratification by building type and/ or season. For the Persily data, the AER values for each office space were averaged, rather using the indivi dual measurements, to account for the strong dependence of the AER measurements for the sa me office space over a relatively short period. The mean values are similar for the two studies, but the standard deviati ons are about twice as high for the Persily data. The proposed AER di stributions were derived from the more recent Persily data only. We fitted exponential, lognormal, normal, a nd Weibull distributions to the 96 office space average AER values, and the best fitting of these was the lognormal. The fitted parameters for this distribution, used for AER dist ributions for the i ndoor non-residential microenvironments, can be found in the Exposure Analysis TSD.4-27 4.5.5.3 Proximity and Penetration Factor s for Outdoors and In-vehicle Microenvironments For the outdoors near-road, public garage/parki ng lot, and in-vehicle proximity factors, and for the in-vehicle penetration factors, we use distributions develope d from the Cincinnati Ozone Study (American Petroleum Institute, 1997, Appendix B; Johnson et al., 1995). This field study was conducted in the greater Cincinnati metropolitan area in August and September, 1994.
Vehicle tests were conducted ac cording to an experimental de sign specifying the vehicle type, road type, vehicle speed, and ventilation mode. Vehicle types were defined by the three study vehicles: a minivan, a full-size car, and a compact car. Road types were interstate highways (interstate), principal ur ban arterial roads (urban), and loca l roads (local). Nominal vehicle speeds (typically met over one minute intervals within 5 mph) were at 35 mph, 45 mph, or 55 mph. Ventilation modes were as follows:

• Vent Open: Air conditioner off. Ventilation fan at medium. Driver’s window half open. Other windows closed.

• Normal A/C: Air conditioner at normal. All windows closed.

• Max A/C: Air conditioner at maximum. All windows closed.

Ozone concentrations were measured inside the vehi cle, outside the vehicle, and at six fixed-site
monitors in the Cincinnati area. The Exposure Analysis TSD documents the distributions and the rationale for the
selection of distributions of penetration and proximity factors for outdoors and in-vehicle
microenvironments used in this modeling analysis.

4.5.5.4 Ozone Decay and Deposition Rates

A distribution for combined O 3 decay and deposition rates was obtained from the analysis of measurements from a study by Lee et al. (19 99). This study measured decay rates in the living rooms of 43 residences in Southern California. Measuremen ts of decay rates in a second
room were made in 24 of these residences . The 67 decay rates range from 0.95 to 8.05 hour -1 . A lognormal distribution was fit to the measurements from this st udy, yielding a geometric mean of 2.5 and a geometric standard deviation of 1.5. This distribution is used for all indoor
microenvironments.

4.5.6 Meteorological Data Daily average and maximum 1-hour temperat ures were obtained from hourly surface temperature measurements obtained from the Nati onal Weather Service. APEX uses the data
from the closest weather station to each Census tract. Temperatures are used in APEX both in selecting human activity data and in estimating AERs fo r indoor microenvironments.4-28 4.5.7 Ambient Ozone Concentrations APEX requires hourly ambient O 3 concentrations at a set of locations in the study area. Data from EPA’s AIRS Air Qual ity Subsystem were used to pr epare the ambient air quality input files for 2002, 2003, and 2004. The hourly O 3 concentrations at the AIRS sites in each CSA were used as input to APEX to represent the ambient concentrations within each urban area. For near-road and parking garage microenvironments the ambient concentrations are adjusted by proximity factors, as desc ribed in the Exposure Analysis TSD.

4.5.8 Modeling Alternative Standards In addition to modeling exposures based on historical air quality, an analysis was conducted using air quality representative of just meeting the current 8-hr O 3 standard of 0.08 ppm, and considering the previ ous rounding convention that allo wed for concentrations up to 0.084 ppm. Several alternative stan dards, reflecting different comb inations of standard levels
and form were also considere d. Alternatives examined were intended to reflect improved precision in the measurement of the ambient con centrations, where the precision would extend to three instead of two decimal places (in ppm) (e.g., 0.080 ppm rather than 0.08 ppm) for several different levels. Differing forms of the standard were also explored outside of the average 4 th daily maximum 8-hr average scenario currently used. For example, a 3 rd -highest form (the average of the annual 3 rd -highest daily maximum 8-hour concen trations averaged over the three year period) was considered fo r 0.084 and 0.074 ppm levels, and a 5 th -highest form for the 0.074 ppm level (the average of the annual 5 th -highest daily maximum 8-hour concentrations averaged over the three year period). Th ese alternative scenarios are modeled using a quadratic rollback approach to adjust the hourly O 3 concentrations observed in 2002-2004 to yield a design value corresponding to the standard be ing modeled. Table 4-6 shows th e attainment thresholds (to which the design values are rolled ba ck), the form of the standard used for each scenario, and the notation used in the remainder of this chap ter. Design values for the current 8-hr O 3 standard are calculated as the 3-year averages of the annual 4 th -highest daily maximum 8-hr average
concentration based on the maximum monitor within an urban area. These are given in Table 4-7 for the 2002-2004 period. The quadratic rollback technique combines both linear and quadratic elements to reduce higher concentrations more than lower concen trations near ambient background levels. The quadratic rollback adjustment procedure was consid ered in a sensitivity an alysis during the last
review of the O 3 NAAQS and has been shown to be more realistic than the linear proportional rollback method, where all of the ambient measur ements are reduced by a constant multiplicative factor regardless of their individual magnitudes. The quadratic rollback approach and evaluation of this approach are described by Johnson ( 1997), Duff et al. (1998) , and Rizzo (2005, 2006).4-29 Table 4-6. Alternative 8-hr ozone standard scenarios

Attain. Threshold Form of Standard Notation

0.084 ppm 3 rd -highest form 4 th -highest form 84/3 84/4 0.080 ppm 4 th -highest form 80/4

0.074 ppm 3 rd -highest form 4 th -highest form 5 th -highest form 74/3 74/4 74/5 0.070 ppm 4 th -highest form 70/4 0.064 ppm 4 th -highest form 64/4

Table 4-7. 2002-2004 8-hr ozone design values for the modeled areas
Urban Area (CSA) 2002-2004 design value 1 (ppm) Ratio of 0.084 to the design value

Atlanta 0.093 0.90

Boston 0.091 0.92 Chicago 0.094 0.89

Cleveland 0.095 0.88

Detroit 0.092 0.91

Houston 0.101 0.83 Los Angeles 0.127 0.66

New York 0.094 0.89 Philadelphia 0.094 0.89

Sacramento 0.102 0.82

St. Louis 0.089 0.94 Washington, DC 0.089 0.94

1 These design values are calculated based on the entire CSA, which in some cases differ slightly from current non-attainment area definitions.4-30 4.6 MODEL EVALUATION, SENSITIVITY, AND UNCERTAINTY ANALYSES

The methods used to evaluate the APEX m odel and characterize the uncertainty of the model predictions are described in this section. First, we discuss the results of the exposure modeling in comparison to the modeling performed as part of the previous review of the O 3 NAAQS, completed in 1997. Second, we report the results of a limited APEX model evaluation, which involves the comparison of model exposure estimates to pers onal exposure measurement data. Although the available exposure measurements are 6-day averages, this comparison can serve to gain insight on whether the model is reasonably estimating exposures. Another approach for evaluating the m odel involves model sensitivity analyses, evaluating how the model responds to variation in the input data and parameters used in several of the key algorithms. An analysis such as th is is important for several reasons, such as indicating those data that have the greatest impact on estimated exposures and the relative
confidence that one has in the model estimates as measured by the degree of certainty in the model inputs and their appropriate use. A comprehensive analysis of the uncertain ties of the exposure modeling was performed, and the results of that analysis are described he re. At the end of this section, the conclusions drawn from the evaluation, sensitivity, a nd uncertainty analyses are summarized.

4.6.1 Comparison with Exposure Estimates from the Prior Review There have been significant improvements to the exposure model and the model inputs since the review in 1997, as disc ussed in Section 4.3.1. In the pr evious review, six urban areas were modeled using the pNEM model, Houst on, Los Angeles, New York, Philadelphia, St. Louis, and Washington (U.S. EPA, 1996a,c). Thes e six cities (as well as six others) are also modeled in the current review, although the geogr aphic areas modeled are larger than in the previous review, with over twice the population coverage. When modeling a larger area, extending well beyond the urban core, there w ill be more people exposed, but a smaller percentage of the modeled population will be exposed at high levels, if O 3 concentrations are
lower in the extended areas. Typical years, in terms of O 3 air quality, were modeled in the 1997 review (1990 for some cities and 1991 for others ). The only alternative standard for which we
have results for both reviews is the “84/3” standard. Exposures to children who tend to spend more time outdoors were estimated in the previous review but not in th e current review, and there is no population group for which we can make a direct comparison of the exposure estimates for the two reviews. Therefore, a qua ntitative comparison of the exposure results is not appropriate.4-31 4.6.2 Comparison of Model Estimates wi th Measured Personal Exposures APEX simulation results were compared to personal O 3 concentration measurements
obtained from the Harvard Sout hern California Chronic Ozone Exposure Study (Xue et al. 2004, Geyh et al. 2000). Although this study was limite d in scope, and the measurements of ozone are averaged over 6 or 7 days, it is the only study found that measured enough personal exposures to

O 3 to be useful for this evaluation and for which the data are available. In this study, children 7 to 12 years old were monitored from June 1995 to May 1996. There were 160 subjects on which longitudinal O 3 concentrations were collected in at leas t 6 of the 12 months of the study period.
Passive O 3 samplers were used to measure 6-day or 7-day average personal O 3 concentrations, as well as indoor and outdoor concentrations at pa rticipants’ homes, for six days each month. The subjects resided in two separa te areas of San Bernardino County: urban Upland CA, and the small mountain towns of Lake Arrowhead, Cres tline, and Running Springs, CA. There was a total of 91 6-day or 7-day periods with measurements used in this evaluation.
For the APEX simulations we used the sa me model inputs as for the Los Angeles simulations, described in Section 4.5 above, except for the air exchange rates. The AERs used were those developed for Sacramento from meas urements taken in Sacramento and the inland portions of the Los Angeles area: Riverside a nd San Bernardino Counties. The hourly outdoor

O 3 concentrations were from fixed site m onitors located in Upland and Crestline. For each period for which personal measurem ents were available we simulated 10,000 subjects in the 7 – 12 age range in each of the two study areas. For each case the distribution of simulated 6-day or 7-day average exposure c oncentrations was compared to the corresponding
distribution of measured valu es, which ranged from 8 to 31 subjects. Comparisons were also
made between the continuous measurements made inside the subjects’ homes and the APEX
indoor residential concentrati on estimates during the times of exposure, and between the O 3 concentrations measured outside the homes of the study subjects and those measured at the nearby fixed site monitors. Figures 4-2 and 4-3 show the ranges and means of the population distributions of modeled exposures from APEX and the ranges and means of the 8 to 31 measured personal exposures for each 6-day or 7-day period, for Up land and for Lake Arrowhead, Crestline, and Running Springs. Variability in exposure is reasonably estim ated by APEX across the population, although the APEX predictions tend to have a lower variance than the measured values. The mean4-32 Figure 4-2. Modeled and measured weekly av erage personal exposures: means, minima, maxima for each week. Upland, CA.

Figure 4-3. Modeled and measured weekly av erage personal exposures: means, minima, maxima for each week. Lake Arrowhead, Crestline, and Running Springs, CA.4-33 exposures predicted by APEX are generally in good agreement with the measured means, except for the Winter and Spring seasons for the La ke Arrowhead, Crestline, and Running Springs communities, when the exposures are very low. It is not clear how these results might translate to model performance of 8-hour average expos ures, although the underprediction of variance indicates that APEX may be unde rpredicting the upper quantiles of the 8-hour exposures. Additional results and analyses of the evaluation are discussed in the Exposure Assessment TSD. Since this evaluation is based on 6-day and 7- day average exposures, it is only of limited relevance for evaluating daily maximum 8- hr average exposure simulation results.

4.6.3 Sensitivity Analyses The sensitivity analyses most relevant to evaluating APEX are summarized here. Additional sensitivity analyses are desc ribed in the Exposure Assessment TSD.

4.6.3.1 Near-Road Residential Exposures

APEX does not take into acc ount the effects of mobile source emissions of NO on the
concentrations of O 3 in residences near roadways; therefor e, we conducted a se nsitivity analysis to assess the potential effect on exposur es in residences of the titration of O 3 by mobile source NO. We performed APEX simulations for the Boston and Houston 2002 base cases for each of these three subsets of the populat ion, defined by the distance of their residence from a major roadway, based on the fractions of the population in each Census tract that live in three bands:

a) 0-75 m from a major roadway, b) 75-200 m from a major roadway, and c) >200 m from a major roadway. We used proximity factors to decrease the ambient concentrations outside their
residences in accordance with the distance from roadways. The combined results of these three simulations account for the decreased exposures in residences near roadways. A comparison of
these model results with the standard simulations show decreases of one to three percent in the estimated counts of exposures above 0.07 ppm-8hr. This demonstrates that the uncertainty engendered by not accounting for the titration of O 3 by NO in residences near roadways is quite small for high exposures. Since high exposures are generally associated with outdoor and not indoor activities, this is not surprising.

4.6.3.2 Air Exchange Rates and the Prevalence of Residential Air Conditioning Air exchange rates and the prevalence of residential air conditioning are two of the influential determinants of exposures while i ndoors, and while the uncertainty of these two model input parameters are accounted for in the uncertainty analysis described below, it is possible that these inputs might be biased, and this sensitivity an alysis assessed the effect of4-34 potential biases in the values used in the AP EX exposure modeling. APEX simulations for the
Boston 2002 base case and current standard sc enarios were performed, varying the air conditioning prevalence rate from 85% to 70% and to 50%, and also varying the geometric
means of all of the AER distribut ions simultaneously by +0.1 and by

− 0.1. Biases of these magnitudes in these parameters turn out to ha ve little effect on the high 8-hour average exposures predicted by APEX. For example, cha nges in the percents of children experiencing exposures over 0.06, 0.07, and 0.08 ppm-8hr cha nge by less than one percentage point.

4.6.3.3 Activity Patterns: Representativeness of CHAD Many of the studies included in the CHAD da ta base are not national in scope, nor do they necessarily correspo nd to the modeled urban areas, and we conducted an analysis to assess how similar the exposure results are when using i ndividual component studies. Strong similarity would suggest that extrapolation of activity data gath ered from one sample population to another population is appropriate. The largest and most comprehensive individual study in CHAD is the National Human Activity Pattern Study (NHAPS), a nd we compared the APEX exposure results using all of CHAD with corre sponding results using only the NHAPS data. NHAPS is national in scope, with a random design, and comprises more than half of the CHAD diaries for all ages, and 43 percent of the diary days in CHAD for children ages 5 to 18. Sensitivity analyses conducted using other subsets of CHAD are de scribed in the Exposure Assessment TSD. APEX simulations were performed using onl y NHAPS diaries for all 12 urban areas, for the 2002 base case and the scenario of meeting the current NAAQS. The results of this comparison for the 2002 base case simulations are presented in Table 4-8 for the percent of
children at moderate exertion with 8-hour exposures above exposure levels of 0.06, 0.07, and 0.08 ppm-8hr. The comparison of estimated reducti ons in exposures to children at moderate exertion in going from the base case to the current standard is pr esented in Table 4-9. There is good agreement between the APEX predictions of the re ductions in exposures
from the current base case to the current st andard, whether all of CHAD or only the NHAPS component of CHAD is used, indicating that thes e results are not being unduly influenced by any single study in CHAD. The differences are larger for the absolute percentages, reflecting the
effect of the uncertainties of the CHAD database.

4.6.3.4 Activity Patterns: Underestima tion of Repeated Exposures Not only is the actual exposure level importa nt for the development of adverse health outcomes but also the frequency of exposures at given levels of concern. In the absence of specific data to directly evaluate the rep eated exposure results generated by APEX,4-35 Table 4-8. Comparison of APEX 2002 base case simula tions: All CHAD vs. the NHAPS part of CHAD. Percent of children at moderate exertion with 8-hour exposures above levels of 0.06, 0.07, 0.08 ppm-8hr. Above 0.06 ppm-8hr Above 0.07 ppm-8hr Above 0.08 ppm-8hr

CSA All CHAD NHAPS only difference All CHAD NHAPS only difference All CHAD NHAPS only difference
Atlanta 68% 62% ( 6%) 42% 38% ( 4%) 15% 14% ( 1%) Boston 66% 60% ( 6%) 46% 41% ( 5%) 24% 21% ( 2%) Chicago 69% 61% ( 8%) 44% 38% ( 6%) 17% 16% ( 1%) Cleveland 77% 71% ( 6%) 63% 56% ( 7%) 38% 33% ( 4%) Detroit 72% 65% ( 7%) 51% 45% ( 7%) 20% 20% 0% Houston 58% 51% ( 7%) 31% 28% ( 3%) 13% 12% ( 0%) Los Angeles 61% 58% ( 3%) 36% 33% ( 2%) 16% 16% 0% New York 74% 68% ( 6%) 54% 48% ( 6%) 28% 25% ( 2%) Philadelphia 77% 69% ( 8%) 60% 53% ( 7%) 38% 33% ( 5%) Sacramento 66% 59% ( 7%) 39% 35% ( 3%) 15% 15% 0% St. Louis 70% 61% ( 9%) 51% 43% ( 8%) 21% 20% ( 1%) Washington 73% 66% ( 7%) 53% 48% ( 6%) 29% 25% ( 3%)

Table 4-9. Comparison of APEX simulations: All CHAD vs. the NHAPS part of CHAD. Percent reduction 1 from the 2002 base case to the current standa rd of the number of children at moderate exertion with 8-hour exposures above le vels of 0.06, 0.07, 0.08 ppm-8hr. Above 0.06 ppm-8hr Above 0.07 ppm-8hr Above 0.08 ppm-8hr

CSA All CHAD NHAPS only difference All CHAD NHAPS only difference All CHAD NHAPS only difference
Atlanta 22% 22% ( 0%) 51% 52% 1% 71% 67% ( 4%) Boston 18% 19% 1% 38% 37% ( 1%) 57% 56% ( 1%) Chicago 24% 25% 1% 55% 50% ( 5%) 85% 81% ( 4%) Cleveland 14% 17% 3% 39% 41% 1% 81% 78% ( 2%) Detroit 15% 17% 2% 44% 38% ( 5%) 85% 81% ( 5%) Houston 53% 51% ( 2%) 76% 73% ( 3%) 91% 91% 0% Los Angeles 88% 85% ( 3%) 98% 96% ( 1%) 100% 99% ( 0%) New York 32% 34% 1% 70% 67% ( 3%) 91% 89% ( 2%) Philadelphia 17% 18% 1% 39% 39% 0% 71% 71% ( 0%) Sacramento 49% 47% ( 2%) 81% 78% ( 3%) 93% 93% 1% St. Louis 9% 11% 2% 28% 24% ( 4%) 53% 48% ( 5%) Washington 19% 20% 1% 45% 46% 0% 74% 75% 1%

1 The percent reductions are calculated as 100(base case results – current standard results)/(base case results).4-36 the population of outdoor workers was targeted as a group that can be used indirectly for this type of evaluation. To this end, a comparison of estimated exposures of outdoor workers in two urban areas (Atlanta and Sacramento) with expos ures estimated by APEX for those urban areas was performed. Due to data limitations, APEX has not been se t up to specifically model outdoor workers, but can estimate exposures for all employed adults in an urban area. Comparison of estimates of repeated exposures to outdoor workers with th e corresponding APEX esti mates for all workers reveals that APEX significantly underestimates the number of multiple exposures for working adults. For example, in Atlanta, APEX estimat es 490,000 workers to be exposed at least once to levels above 0.07 ppm-8hr in 2002; however, only 220 were estimat ed to experience repeated exposures above 0.07 ppm-8hr six or more times. Because there is no information on the exertion levels of outdoor workers, these esti mates include all exertion levels and are not restricted to moderate or greater exertion. In contrast to the APEX estimates, a separate estimate of exposures to outdoor workers, based on outdo or worker frequency estimates for occupation categories, gives a range of from 62,000 to 140,000 outdoor workers experiencing six or more repeated exposures to levels above 0.07 ppm- 8hr in Atlanta for 2002 air quality. Table 4-10 summarizes the comparisons performed for Atlant a and Sacramento for repeated exposures to levels above 0.06, 0.07, and 0.08 ppm-8hr. A description of the method used for estimating these exposures of outdoor work ers is given in Langstaff (2007). Since outdoor workers are a subset of all employed adults, it is clear from Table 4-10 that APEX is underestimating repeated exposures to adult workers.

Table 4-10. Comparison of estimated outdoor workers’ repeated exposures with APEX results for all workers, in Atlanta and Sacrame nto, 2002. Numbers of people with at least six repeated 8-hour exposures above 0.06, 0.07, and 0.08 ppm-8hr. 1 # above 0.06 ppm-8hr # above 0.07 ppm-8hr # above 0.08 ppm-8hr Est. outdoor workers APEX all workers Est. outdoor workers APEX all workers Est. outdoor workers APEX all workers Atlanta 63,000 – 150,000 74,000 62,000 – 140,000 220 41,000 – 94,000 0

Sacramento 30,000 – 61,000 30,000 27,000 – 55,000 95 21,000 – 42,000 0

1 The numbers in this table have b een rounded to two significant digits.

This underestimation results primarily from the way that people’s activities are modeled using CHAD, which does not properly account for repeated behavior of individuals. The new longitudinal methodology does increase the similari ty of daily activities for a given simulated individual in terms of the time spent outdoors, and some simulated individuals tend to spend4-37 more time outdoors than others, compared to a more random assignment of diaries from CHAD to modeled individuals. However, repeated routine behavior from one weekday to the next is not simulated. For example, there are no simulate d individuals representi ng children in summer camps who spend a large portion of their time outdoors, or adults with well-correlated weekday schedules. These limitations apply to both childr en and adults, and therefore multiple exposures to children are also expected to be underestimated by APEX.

4.6.4 Uncertainty Analysis An understanding of the uncertainty of the APEX model predictions has been developed through sets of complementary an alyses addressing different asp ects of the overall uncertainty. A Monte Carlo analysis was performed which ac counts for most of the uncertainties of the APEX model inputs. Sensitivity analyses have b een conducted to address the potential influence of other sources of uncertainty, described in th e previous section. This section provides a summary of the results of th e exposure modeling uncertainty analysis; the details of the uncertainty analysis are de scribed in Langstaff (2007). A Monte Carlo approach was selected for a detailed uncertainty analyses. Monte Carlo methods for analysis of model uncertainty use sta tistical sampling tec hniques to estimate statistics which characterize uncertainty. Essen tially, a Monte Carlo appr oach entails performing many model runs with model inputs randomly sampled from distribut ions reflecting the uncertainty of the inputs. This propagates the uncertainty of the model inputs through to the model results, taking into account input para meter dependencies and the interaction of
uncertainties within the model. These simulations provide uncertainties of model results in terms of uncertainty distributions of the model outputs. From these we calculate 95 percent uncertainty intervals (UI) for a particular mode l result as the interval from the 2.5 th to the 97.5 th percentile of the uncertainty distribution for that result. The Monte Carlo uncertainty analysis perf ormed accounts for the following sources of uncertainty:

• Ambient air concentrations measurement error

• Spatial interpolation of ambient concentrations

• Air exchange rates

• Air conditioning prevalence rates

• Ozone deposition and decay rates

• Vehicle penetration factors

• Longitudinal diary assembly parameters

• Metabolic equivalents (MET)

• Model convergence4-38 The Monte Carlo uncertainty analysis was performed for Boston 2002, for the recent year
base case and the current standard scenarios, as well as for the estimated reductions in exposures in going from the base case to th e current standard. Uncertainties of model results for other areas and years are expected to be similar. Figure 4-4 illustrates the uncertainty distri butions for one model re sult, the percent of children with exposures above 0.06 ppm-8hr while at moderate exertion. This distribution results from approximately 2000 Monte Carlo AP EX simulations of the Boston 2002 base case with model inputs varied randomly according to their uncertainty. The “point estimate” of 62 percent is the result from the APEX simulation using our best es timates of the model inputs, as described in Section 4.5. The corresponding resu lt from the Monte Carlo simulations ranges from 56 to 67 percent, with a 95 percent UI of 58 to 65 percent. Figure 4-5 and Figure 4-6 illustrate the uncertainty distributions for two ot her model results, the percents of children with exposures above 0.07 and 0.08 ppm-8hr while at moderate exertion.

Uncertainty distribution for the estimated percent of children with any 8-hour exposures above 0.06 ppm-8hr at moderate exertion (point estimate is 62%)

0 100 200 300 400 500 600

56% 57% 58% 59% 60% 61% 62% 63% 64% 65% 66% 67%

Percent of childrenNumber of Monte Carlo simulations

Figure 4-4. Uncertainty of percent of childre n with exposures above 0.06 ppm-8hr (Boston 2002 base case)4-39 Uncertainty distribution for the estimated percent of children with any 8-hour exposures above 0.08 ppm-8hr at moderate exertion (point estimate is 20%)

0 50 100 150 200 250 300 350 400 450

17% 18% 19% 20% 21% 22% 23% 24% 25% 26%

Percent of childrenNumber of Monte Carlo simulations Uncertainty distribution for the estimated percent of children with any 8-hour exposures above 0.07 ppm-8hr at moderate exertion (point estimate is 41%)

0 100 200 300 400 500 600

35% 36% 37% 38% 39% 40% 41% 42% 43% 44% 45% 46% 47%

Percent of childrenNumber of Monte Carlo simulations

Figure 4-5. Uncertainty of percent of childre n with exposures above 0.07 ppm-8hr (Boston 2002 base case)

Figure 4-6. Uncertainty of percent of childre n with exposures above 0.08 ppm-8hr (Boston 2002 base case)4-40 Uncertainty intervals are presented in Table 4-11 and Table 4-12 for the estimated percentages of all children and asthmatic ch ildren with exposures above different 8-hour exposure levels under moderate exertion. The UI s for the estimated reductions in exposures, going from the 2002 base case to the current standa rd, for these two groups are given in Table 4-13. Across these three tables, the spans of the 95 percent UIs range from 2 to 10 percentage points, and the point estimates are generally within 5 percentage poi nts of the UI endpoints. The uncertainties of the exposures to asthmatic child ren are slightly higher than for all children. These results are very positive, and the modeling uncertainty is small enough to lend confidence
to the use of the model results.

Table 4-11. Uncertainty of the es timated percent of children exposed at moderate exertion, Boston, 2002 Exposure level (ppm-8hr) Air quality scenario Point estimate 95% UI

0.06 base case 62% 58-65%

0.07 base case 41% 38-44%

0.08 base case 20% 19-24%

0.06 current standard 49% 46-52%

0.07 current standard 24% 23-27%

0.08 current standard 8.5% 8-10%

Table 4-12. Uncertainty of the es timated percent of asthmatic children exposed at moderate exertion, Boston, 2002 Exposure level (ppm-8hr) Air quality scenario Point estimate 95% UI

0.06 base case 65% 60-67%

0.07 base case 43% 39-46%

0.08 base case 21% 19-25%

0.06 current standard 52% 48-56%

0.07 current standard 24% 23-30%

0.08 current standard 9% 8-11%4-41 Table 4-13. Uncertainty of the estimated percent reduction, from the base case to the curren t standard, of all children and asthmatic children exposed at moderate exertion, Boston, 2002
All children Asthmatic children Exposure level (ppm-8hr) Point estimate 95% UI Point estimate 95% UI

0.06 21% 18-22% 19% 16-22%

0.07 41% 38-42% 43% 37-45%

0.08 58% 55-59% 58% 53-63%

4.6.5 Key Findings Uncertainty of the APEX model predictions results from uncertainties in the spatial interpolation of measured concentrations, the microenvironment models and parameters, people’s activity patterns, and, to a lesser extent, model structure. The predominant sources of uncertainty appear to be the activity pattern info rmation and the spatial interpolation of ambient concentrations from monitoring si tes to other locations. The prim ary findings of these analysis are the following:

• The Monte Carlo analysis of the uncertainties of the APEX model estimates of exposure distributions indicates th at the uncertainty is relatively small. The APEX estimates of the percent of children or asthmatic childr en with exposures above 0.06, 0.07, or 0.08 ppm8hr under moderate exertion have 95% uncertain ty intervals of at most ±6 percentage points.

• An investigation into the repr esentativeness of the CHAD activ ity diaries with respect to the specific urban areas and time periods m odeled indicates uncerta inties of only a few percent in the APEX estimates of the nu mbers of children with exposures above 0.06, 0.07, or 0.08 ppm-8hr under moderate exertion.

• Although the effect on exposures in re sidences of the titration of O 3 by mobile source NO is not explicitly modeled by APEX, the resulting uncertainty is small, on the order of 1 to 3 percent.

• APEX significantly underestimates the fr equency of occurrence of individuals experiencing repeated 8-hour average exposures greater th an 0.06, 0.07, and 0.08 ppm8hr. The reasons for this are understood, and fu rther research will be required to address this.4-424-43 4.7 EXPOSURE ASSESSMENT RESULTS

4.7.1 APEX Modeling Results The results of the exposure analysis 4 are presented as a series of exhibits and graphs focusing on a range of benchmark levels, described in Chapters 3 and 6, as being of particular health concern. In addition, a wide range of con centrations in the air qua lity data collected over the three year period (2002-2004) were used in the exposure model, providing a broad range of estimated exposures output by the model. Expos ure results are presen ted for the range of alternative standard scenarios given in Table 4- 6. Estimates of exposures for the year 2003 were developed since the second draft of this Staff Pape r for only two alternative standard levels (74/4 and 64/4) due to time constraints. This section is organized into two main subsections, the first addressing the exposures estimated for each of the particular benchmarks and the second reporting on the estimates of repeated exposures. Tables of exposures fo r children and asthmatic
children under moderate exertion are presented in Appendix 4-A.

4.7.2 Estimated Exposures above Selected Benchmark Levels A series of exhibits are presented for each of the benchmark levels of persons who experience daily maximum 8-hour average e xposures above 0.080, 0.070, and 0.060 ppm-8hr. A few notes regarding the exhibits are necessary to mention. Expos ure estimates are presented for those individuals experiencing moderate levels of exertion during the same 8-hr period that the exposure occurred. The exertion level is characteri zed by breathing rates, as described in section 4.3.3. Results for children exposed to O 3 while engaged in moderate exertion are presented in each of the subsequent exhibits, however result s for any other population group could have been presented with similar exposure outcomes and patterns across the 12 cities modeled. For example, the comparison of three population groups, children, asth matic children, and all persons, indicates a very similar pattern of exposure estimates, regardless of the subgroup considered (Figure 4-7). In addition, use of the multiple years of ambient air quality data generated a range of exposure concentrations , bracketed by the year 2002 (highest exposure estimates) and the year 2004 (lowest exposure es timates). Exposure estimates for year 2003 generally fell in between the exposures esti mated for the other two years (Figure 4-8).

4 An error was found in the exposure model in January 2007. This error has been corrected and the model runs have been redone, generally resulting in small increases in the exposure estimates. The corrected results are presented in this Staff Paper and in the Exposure Analysis TSD.4-44 WASH ST.L SACR PHIL NY LA HOUS DETR CLEV CHIC BOST ATLA children

asthmatic children all people 0 5 10 15 20 25 30 35 40Percent of subgroup with 1 or moreexposures >0.07ppm-8hr

City Population Subgroup

Figure 4-7. Comparison of population groups . Percent of population subgroups with one or more 8-hr ozone exposures above 0.070 ppm-8hr , concomitant with moderate or greater exertion, with just reaching the current st andard, based on 2002 ambient air quality.

WASH ST.L SACR PHIL NY LA HOUS DETR CLEV CHIC BOST ATLA 2002

2003

2004 0 5 10 15 20 25 30 35 40Percent of children with 1 or moreexposures >0.07 ppm-8hr

City Year

Figure 4-8. Comparison of years . Percent of children with one or more 8-hr ozone exposures above 0.07 ppm-8hr, concomitant with moderate or greater exertion, with just reaching the current standard.4-45 Nine exhibits follow, representing the exposures estimated for years 2002, 2003, and 2004, each at the three benchmark levels (0.080, 0.070, and 0.060 ppm-8hr). Each exhibit contains three exposure metrics: the estimated percent of children exposed, the estimated number of children exposed, and the number of person-days exposure occurred above the particular benchmark level. The notation used fo r the alternative standards is defined in Table 4-6. Exposures were also estimat ed using the respective year air quality data wit hout application of the rollback procedure, and are presented as th e “base” scenario in each exhibit. The numbers
for the base scenarios are omitted from some of th e figures within the exhibits (i.e., the numbers of children and person days) since they increase d the vertical scale, obscuring the details of
interest. The patterns of estimated exposures are vari able from city to city, primarily due to differences in air quality (local emissions and meteorology affect these), the rollback procedure as applied to each separate area, and people’s time-location-activity patterns. The year-to-year variability in exposures is also evident. All of the urban ar eas modeled except Houston and Los Angeles have fewer exposures in 2003 and 2004 than in 2002, due in varying degrees to changes
in weather and emissions of precursors to O 3
. Inspection of these exhibits shows marked di fferences between urban areas in the levels of exposures under alternativ e standards. For example, under the same 0.074 ppm, 4 th daily maximum 8-hr average alternative standard, it is estimated that 10 percen t of the Boston children but very few of the Los Angeles children experience 8-hr O 3 exposures above 0.070 ppm-8hr while engaged in moderate exertion using 2002 air quality. This is primarily due to the larger range of 2002-2004 4 th -highest concentrations fo r Boston compared to the rest of its air quality distribution, which in general, allowed for rete ntion of higher concentr ations within the air quality distribution (and therefore exposures) foll owing the rollback of th e air quality. In Los Angeles, much more of the upper range of the air qua lity distribution needed to be rolled back to allow for the meeting of the alternative standard s, thus significantly re ducing the frequency of occurrence of high ambient concentr ations (and therefore exposures). The form of the standard had an impact on the number of estimated exposures, the general magnitude of which is dependent on the be nchmark level selected and year of air quality data used. For example in considering the seri es of 74/x scenarios (74/ 5, 74/4, 74/3), the impact could be a low as a few percent (percent of ch ildren with estimated e xposures above 0.060 ppm using 2004 air quality go from, on average, 3% to 1%) or much greater (percent of children with estimated exposures above 0.060 ppm using 2002 ai r quality go from, on av erage, 28% to 21%)4-46 Exhibit 1 . Summary of exposure metrics regardi ng estimated exceedances of 0.080 ppm 8-hr ozone exposures, concomitant with moderate or greater exertion, based on 2002 air quality. A) Table of percent of children with at least one exposure above 0.080 ppm 8-hr, B) Illustration of percent of children with at least one exposure above 0.080 ppm 8-hr, C) Illustration of the number of children with at least one exposur e above 0.080 ppm 8-hr, D) Illustration of the number of children person days with exposure above 0.080 ppm 8-hr.

1-A) Percent of children with exposures > 0.080 ppm, moderate exertion, 2002 data

City base 84/4 84/3 80/4 74/5 74/4 74/3 70/4 64/4

Atlanta 15% 4% 4% 2% 1% 0% 0% 0% 0%
Boston 24% 10% 6% 6% 5% 2% 1% 0% 0% Chica g o 17% 3% 2% 1% 0% 0% 0% 0% 0% Clevelan d 38% 7% 2% 2% 0% 0% 0% 0% 0% Detroit 20% 3% 1% 0% 0% 0% 0% 0% 0%
Houston 13% 1% 1% 0% 0% 0% 0% 0% 0%
Los An g eles 16% 0% 0% 0% 0% 0% 0% 0% 0%
New Yor k 28% 3% 2% 1% 0% 0% 0% 0% 0% Philadel p hi a 38% 11% 6% 5% 2% 1% 0% 0% 0% Sacramento 15% 1% 0% 0% 0% 0% 0% 0% 0% St. Louis 21% 10% 6% 4% 1% 1% 0% 0% 0% Washin g to n 29% 7% 4% 3% 1% 1% 0% 0% 0%

base

84/4

80/4

74/4

70/4

64/4

ATLA BOST CHIC CLEV DETR HOUS LA NY PHIL SACR ST.L WASH 0 5 10 15 20 25 30 35 40Percent of children with 1 or moreexposures >0.08 ppm-8hr

Alternative Standard City 1-B)4-47 84/4

80/4

74/4

70/4

64/4

ATLA BOST CHIC CLEV DETR HOUS LA NY PHIL SACR ST.L WASH 0.0E+0 2.0E+4 4.0E+4 6.0E+4 8.0E+4 1.0E+5 1.2E+5 1.4E+5Number of children withexposures >0.08 ppm-8hr

Alternative Standard City

84/4

80/4

74/4

70/4

64/4

ATLA BOST CHIC CLEV DETR HOUS LA NY PHIL SACR ST.L WASH 0.0E+0 2.0E+4 4.0E+4 6.0E+4 8.0E+4 1.0E+5 1.2E+5 1.4E+5 1.6E+5Number of children person days withexposures >0.08 ppm-8hr

Alternative Standard City 1-C)

1-D)4-48 Exhibit 2. Summary of exposure metrics regarding estimated exceedances of 0.070 ppm 8-hr ozone exposures, concomitant with moderate or greater exertion, based on 2002 air quality. A) Table of percent of children with at least one exposure above 0.070 ppm 8-hr, B) Illustration of percent of children with at least one exposure above 0.070 ppm 8-hr, C) Illustration of the number of children with at least one exposur e above 0.070 ppm 8-hr, D) Illustration of the number of children person days with exposure above 0.070 ppm 8-hr.

2-A) Percent of children with exposures > 0.070 ppm, moderate exertion, 2002 data

City base 84/4 84/3 80/4 74/5 74/4 74/3 70/4 64/4

Atlanta 42% 21% 19% 12% 7% 5% 5% 1% 0%
Boston 46% 28% 21% 20% 18% 10% 7% 5% 1% Chica g o 44% 20% 15% 12% 6% 3% 2% 1% 0% Clevelan d 63% 38% 29% 27% 12% 9% 3% 2% 0% Detroit 51% 29% 20% 17% 15% 4% 1% 0% 0%
Houston 31% 7% 4% 4% 1% 1% 0% 0% 0%
Los An g eles 36% 1% 1% 0% 0% 0% 0% 0% 0%
New Yor k 54% 16% 13% 9% 2% 3% 2% 1% 0% Philadel p hi a 60% 37% 30% 28% 16% 13% 8% 5% 0% Sacramento 39% 7% 5% 4% 2% 1% 1% 0% 0% St. Louis 51% 37% 31% 27% 15% 11% 7% 5% 0% Washin g to n 53% 29% 21% 20% 12% 8% 4% 3% 0%

base

84/4

80/4

74/4

70/4

64/4

ATLA BOST CHIC CLEV DETR HOUS LA NY PHIL SACR ST.L WASH 0 10 20 30 40 50 60 70Percent of children with 1 or moreexposures >0.07 ppm-8hr

Alternative Standard City 2-B)4-49 84/4

80/4

74/4

70/4

64/4

ATLA BOST CHIC CLEV DETR HOUS LA NY PHIL SACR ST.L WASH 0.0E+0 1.0E+5 2.0E+5 3.0E+5 4.0E+5 5.0E+5 6.0E+5 7.0E+5Number of children withexposures >0.07 ppm-8hr

Alternative Standard City

84/4

80/4

74/4

70/4

64/4

ATLA BOST CHIC CLEV DETR HOUS LA NY PHIL SACR ST.L WASH 0.0E+0 1.0E+5 2.0E+5 3.0E+5 4.0E+5 5.0E+5 6.0E+5 7.0E+5 8.0E+5 9.0E+5Number of children person days withexposures >0.07 ppm-8hr

Alternative Standard City 2-C)

2-D)4-50 Exhibit 3. Summary of exposure metrics regarding estimated exceedances of 0.060 ppm 8-hr ozone exposures, concomitant with moderate or greater exertion, based on 2002 air quality. A) Table of percent of children with at least one exposure above 0.060 ppm 8-hr, B) Illustration of percent of children with at least one exposure above 0.060 ppm 8-hr, C) Illustration of the number of children with at least one exposur e above 0.060 ppm 8-hr, D) Illustration of the number of children person days with exposure above 0.060 ppm 8-hr.

3-A) Percent of children with exposures > 0.060 ppm, moderate exertion, 2002 data

City base 84/4 84/3 80/4 74/5 74/4 74/3 70/4 64/4

Atlanta 68% 53% 53% 45% 35% 29% 29% 18% 5%
Boston 66% 54% 48% 47% 44% 35% 29% 25% 11% Chica g o 69% 53% 48% 44% 37% 28% 23% 17% 3% Clevelan d 77% 66% 62% 60% 51% 48% 40% 35% 13% Detroit 72% 61% 55% 54% 52% 39% 30% 25% 6%
Houston 58% 27% 21% 19% 11% 9% 7% 5% 1%
Los An g eles 61% 7% 6% 4% 1% 1% 1% 0% 0%
New Yor k 74% 50% 46% 41% 23% 25% 21% 15% 3% Philadel p hi a 77% 64% 60% 58% 49% 46% 41% 36% 17% Sacramento 66% 33% 29% 24% 15% 12% 10% 6% 1% St. Louis 70% 63% 60% 58% 50% 46% 40% 34% 14% Washin g to n 73% 59% 52% 51% 43% 38% 30% 28% 10%

base

84/4

80/4

74/4

70/4

64/4

ATLA BOST CHIC CLEV DETR HOUS LA NY PHIL SACR ST.L WASH 0 10 20 30 40 50 60 70 80Percent of children with 1 or moreexposures >0.06 ppm-8hr

Alternative Standard City

3-B)4-51 84/4

80/4

74/4

70/4

64/4

ATLA BOST CHIC CLEV DETR HOUS LA NY PHIL SACR ST.L WASH 0.0E+0 5.0E+5 1.0E+6 1.5E+6 2.0E+6 2.5E+6Number of children withexposures >0.06 ppm-8hr

Alternative Standard City

84/4

80/4

74/4

70/4

64/4

ATLA BOST CHIC CLEV DETR HOUS LA NY PHIL SACR ST.L WASH 0.0E+0 5.0E+5 1.0E+6 1.5E+6 2.0E+6 2.5E+6 3.0E+6 3.5E+6 4.0E+6 4.5E+6Number of children person days withexposures >0.06 ppm-8hr

Alternative Standard City 3-C)

3-D)4-52 Exhibit 4 . Summary of exposure metrics regardi ng estimated exceedances of 0.080 ppm 8-hr ozone exposures, concomitant with moderate or greater exertion, based on 2003 air quality. A) Table of percent of children with at least one exposure above 0.080 ppm 8-hr, B) Illustration of percent of children with at least one exposure above 0.080 ppm 8-hr, C) Illustration of the number of children with at least one exposur e above 0.080 ppm 8-hr, D) Illustration of the number of children person days with exposure above 0.080 ppm 8-hr.

4-A) Percent of children with exposures > 0.080 ppm, moderate exertion, 2003 data

City base 84/4 84/3 80/4 74/5 74/4 74/3 70/4 64/4

Atlanta 4% 1% . . . 0% . . 0%
Boston 3% 1% . . . 0% . . 0% Chica g o 1% 0% . . . 0% . . 0% Clevelan d 11% 1% . . . 0% . . 0% Detroit 16% 1% . . . 0% . . 0%
Houston 18% 0% . . . 0% . . 0%
Los An g eles 26% 0% . . . 0% . . 0%
New Yor k 13% 1% . . . 0% . . 0% Philadel p hi a 14% 3% . . . 0% . . 0% Sacramento 8% 0% . . . 0% . . 0% St. Louis 8% 2% . . . 0% . . 0% Washin g to n 11% 3% . . . 0% . . 0%

base

84/4

80/4

74/4

70/4

64/4

ATLA BOST CHIC CLEV DETR HOUS LA NY PHIL SACR ST.L WASH 0 5 10 15 20 25 30Percent of children with 1 or moreexposures >0.08 ppm-8hr

Alternative Standard City

4-B)4-53 84/4

80/4

74/4

70/4

64/4

ATLA BOST CHIC CLEV DETR HOUS LA NY PHIL SACR ST.L WASH 0.0E+0 5.0E+3 1.0E+4 1.5E+4 2.0E+4 2.5E+4 3.0E+4 3.5E+4 4.0E+4 4.5E+4Number of children withexposures >0.08 ppm-8hr

Alternative Standard City

84/4

80/4

74/4

70/4

64/4

ATLA BOST CHIC CLEV DETR HOUS LA NY PHIL SACR ST.L WASH 0.0E+0 5.0E+3 1.0E+4 1.5E+4 2.0E+4 2.5E+4 3.0E+4 3.5E+4 4.0E+4 4.5E+4Number of children person days withexposures >0.08 ppm-8hr

Alternative Standard City 4-C)

4-D)4-54 Exhibit 5 . Summary of exposure metrics regardi ng estimated exceedances of 0.070 ppm 8-hr ozone exposures, concomitant with moderate or greater exertion, based on 2003 air quality. A) Table of percent of children with at least one exposure above 0.070 ppm 8-hr, B) Illustration of percent of children with at least one exposure above 0.070 ppm 8-hr, C) Illustration of the number of children with at least one exposur e above 0.070 ppm 8-hr, D) Illustration of the number of children person days with exposure above 0.070 ppm 8-hr.

5-A) Percent of children with exposures > 0.070 ppm, moderate exertion, 2003 data

City base 84/4 84/3 80/4 74/5 74/4 74/3 70/4 64/4

Atlanta 17% 7% . . . 1% . . 0%
Boston 13% 7% . . . 1% . . 0% Chica g o 10% 4% . . . 0% . . 0% Clevelan d 25% 8% . . . 1% . . 0% Detroit 32% 7% . . . 1% . . 0%
Houston 42% 3% . . . 0% . . 0%
Los An g eles 49% 1% . . . 0% . . 0%
New Yor k 31% 6% . . . 0% . . 0% Philadel p hi a 32% 10% . . . 2% . . 0% Sacramento 28% 2% . . . 0% . . 0% St. Louis 24% 11% . . . 2% . . 0% Washin g to n 22% 8% . . . 2% . . 0%

base

84/4

80/4

74/4

70/4

64/4

ATLA BOST CHIC CLEV DETR HOUS LA NY PHIL SACR ST.L WASH 0 5 10 15 20 25 30 35 40 45 50Percent of children with 1 or moreexposures >0.07 ppm-8hr

Alternative Standard City

5-B)4-55 84/4

80/4

74/4

70/4

64/4

ATLA BOST CHIC CLEV DETR HOUS LA NY PHIL SACR ST.L WASH 0.0E+0 5.0E+4 1.0E+5 1.5E+5 2.0E+5 2.5E+5Number of children withexposures >0.07 ppm-8hr

Alternative Standard City

84/4

80/4

74/4

70/4

64/4

ATLA BOST CHIC CLEV DETR HOUS LA NY PHIL SACR ST.L WASH 0.0E+0 5.0E+4 1.0E+5 1.5E+5 2.0E+5 2.5E+5 3.0E+5Number of children person days withexposures >0.07 ppm-8hr

Alternative Standard City

5-C)

5-D)4-56 Exhibit 6 . Summary of exposure metrics regardi ng estimated exceedances of 0.060 ppm 8-hr ozone exposures, concomitant with moderate or greater exertion, based on 2003 air quality. A) Table of percent of children with at least one exposure above 0.060 ppm 8-hr, B) Illustration of percent of children with at least one exposure above 0.060 ppm 8-hr, C) Illustration of the number of children with at least one exposur e above 0.060 ppm 8-hr, D) Illustration of the number of children person days with exposure above 0.060 ppm 8-hr.

6-A) Percent of children with exposures > 0.060 ppm, moderate exertion, 2003 data

City base 84/4 84/3 80/4 74/5 74/4 74/3 70/4 64/4

Atlanta 52% 33% . . . 10% . . 1%
Boston 38% 28% . . . 9% . . 1% Chica g o 37% 26% . . . 7% . . 0% Clevelan d 49% 22% . . . 9% . . 0% Detroit 56% 26% . . . 10% . . 0%
Houston 67% 19% . . . 4% . . 0%
Los An g eles 71% 8% . . . 2% . . 0%
New Yor k 57% 24% . . . 7% . . 0% Philadel p hi a 58% 33% . . . 11% . . 1% Sacramento 59% 15% . . . 3% . . 0% St. Louis 54% 39% . . . 15% . . 1% Washin g to n 47% 21% . . . 8% . . 1%

base

84/4

80/4

74/4

70/4

64/4

ATLA BOST CHIC CLEV DETR HOUS LA NY PHIL SACR ST.L WASH 0 10 20 30 40 50 60 70 80Percent of children with 1 or moreexposures >0.06 ppm-8hr

Alternative Standard City

6-B)4-57 84/4

80/4

74/4

70/4

64/4

ATLA BOST CHIC CLEV DETR HOUS LA NY PHIL SACR ST.L WASH 0.0E+0 1.0E+5 2.0E+5 3.0E+5 4.0E+5 5.0E+5 6.0E+5 7.0E+5 8.0E+5 9.0E+5 1.0E+6Number of children withexposures >0.06 ppm-8hr

Alternative Standard City

84/4

80/4

74/4

70/4

64/4

ATLA BOST CHIC CLEV DETR HOUS LA NY PHIL SACR ST.L WASH 0.0E+0 2.0E+5 4.0E+5 6.0E+5 8.0E+5 1.0E+6 1.2E+6 1.4E+6Number of children person days withexposures >0.06 ppm-8hr

Alternative Standard City

6-C)

6-D)4-58 Exhibit 7. Summary of exposure metrics regardi ng estimated exceedances of 0.080 ppm 8-hr ozone exposures, concomitant with moderate or greater exertion, based on 2004 air quality. A) Table of percent of children with at least one exposure above 0.080 ppm 8-hr, B) Illustration of percent of children with at least one exposure above 0.080 ppm 8-hr, C) Illustration of the number of children with at least one exposur e above 0.080 ppm 8-hr, D) Illustration of the number of children person days with exposure above 0.080 ppm 8-hr.

7-A) Percent of children with exposures > 0.080 ppm, moderate exertion, 2004 data

City base 84/4 84/3 80/4 74/5 74/4 74/3 70/4 64/4

Atlanta 4% 1% 1% 0% 0% 0% 0% 0% 0%
Boston 2% 0% 0% 0% 0% 0% 0% 0% 0% Chica g o 0% 0% 0% 0% 0% 0% 0% 0% 0% Clevelan d 0% 0% 0% 0% 0% 0% 0% 0% 0% Detroit 0% 0% 0% 0% 0% 0% 0% 0% 0%
Houston 12% 1% 0% 0% 0% 0% 0% 0% 0%
Los An g eles 14% 0% 0% 0% 0% 0% 0% 0% 0%
New Yor k 2% 0% 0% 0% 0% 0% 0% 0% 0% Philadel p hi a 2% 0% 0% 0% 0% 0% 0% 0% 0% Sacramento 1% 0% 0% 0% 0% 0% 0% 0% 0% St. Louis 0% 0% 0% 0% 0% 0% 0% 0% 0% Washin g to n 6% 0% 0% 0% 0% 0% 0% 0% 0%

base

84/4

80/4

74/4

70/4

64/4

ATLA BOST CHIC CLEV DETR HOUS LA NY PHIL SACR ST.L WASH 0 3 6 9 12 15Percent of children with 1 or moreexposures >0.08 ppm-8hr

Alternative Standard City 7-B)4-59 84/4

80/4

74/4

70/4

64/4

ATLA BOST CHIC CLEV DETR HOUS LA NY PHIL SACR ST.L WASH 0.0E+0 2.0E+3 4.0E+3 6.0E+3 8.0E+3 1.0E+4 1.2E+4Number of children withexposures >0.08 ppm-8hr

Alternative Standard City

84/4

80/4

74/4

70/4

64/4

ATLA BOST CHIC CLEV DETR HOUS LA NY PHIL SACR ST.L WASH 0.0E+0 2.0E+3 4.0E+3 6.0E+3 8.0E+3 1.0E+4 1.2E+4 1.4E+4Number of children person days withexposures >0.08 ppm-8hr

Alternative Standard City 7-C)

7-D)4-60 Exhibit 8. Summary of exposure metrics regardi ng estimated exceedances of 0.070 ppm 8-hr ozone exposures, concomitant with moderate or greater exertion, based on 2004 air quality. A) Table of percent of children with at least one exposure above 0.070 ppm 8-hr, B) Illustration of percent of children with at least one exposure above 0.070 ppm 8-hr, C) Illustration of the number of children with at least one exposur e above 0.070 ppm 8-hr, D) Illustration of the number of children person days with exposure above 0.070 ppm 8-hr.

8-A) Percent of children with exposures > 0.070 ppm, moderate exertion, 2004 data

City base 84/4 84/3 80/4 74/5 74/4 74/3 70/4 64/4

Atlanta 17% 6% 5% 3% 1% 1% 1% 0% 0%
Boston 8% 2% 1% 1% 0% 0% 0% 0% 0% Chica g o 1% 0% 0% 0% 0% 0% 0% 0% 0% Clevelan d 4% 0% 0% 0% 0% 0% 0% 0% 0% Detroit 3% 0% 0% 0% 0% 0% 0% 0% 0%
Houston 30% 7% 4% 3% 1% 1% 0% 0% 0%
Los An g eles 38% 0% 0% 0% 0% 0% 0% 0% 0%
New Yor k 11% 0% 0% 0% 0% 0% 0% 0% 0% Philadel p hi a 15% 1% 0% 0% 0% 0% 0% 0% 0% Sacramento 10% 0% 0% 0% 0% 0% 0% 0% 0% St. Louis 1% 0% 0% 0% 0% 0% 0% 0% 0% Washin g to n 19% 5% 1% 1% 0% 0% 0% 0% 0%

base

84/4

80/4

74/4

70/4

64/4

ATLA BOST CHIC CLEV DETR HOUS LA NY PHIL SACR ST.L WASH 0 5 10 15 20 25 30 35 40Percent of children with 1 or moreexposures >0.07 ppm-8hr

Alternative Standard City 8-B)4-61 84/4

80/4

74/4

70/4

64/4

ATLA BOST CHIC CLEV DETR HOUS LA NY PHIL SACR ST.L WASH 0.0E+0 1.0E+4 2.0E+4 3.0E+4 4.0E+4 5.0E+4 6.0E+4 7.0E+4 8.0E+4Number of children withexposures >0.07 ppm-8hr

Alternative Standard City

84/4

80/4

74/4

70/4

64/4

ATLA BOST CHIC CLEV DETR HOUS LA NY PHIL SACR ST.L WASH 0.0E+0 1.0E+4 2.0E+4 3.0E+4 4.0E+4 5.0E+4 6.0E+4 7.0E+4 8.0E+4Number of children person days withexposures >0.07 ppm-8hr

Alternative Standard City 8-C)

8-D)4-62 Exhibit 9. Summary of exposure metrics regardi ng estimated exceedances of 0.060 ppm 8-hr ozone exposures, concomitant with moderate or greater exertion, based on 2004 air quality. A) Table of percent of children with at least one exposure above 0.060 ppm 8-hr, B) Illustration of percent of children with at least one exposure above 0.060 ppm 8-hr, C) Illustration of the number of children with at least one exposur e above 0.060 ppm 8-hr, D) Illustration of the number of children person days with exposure above 0.060 ppm 8-hr.

9-A) Percent of children with exposures > 0.060 ppm, moderate exertion, 2004 data

City base 84/4 84/3 80/4 74/5 74/4 74/3 70/4 64/4

Atlanta 48% 26% 25% 18% 11% 8% 8% 3% 0%
Boston 30% 13% 8% 8% 6% 2% 1% 1% 0% Chica g o 12% 1% 0% 0% 0% 0% 0% 0% 0% Clevelan d 26% 5% 3% 2% 0% 0% 0% 0% 0% Detroit 22% 7% 4% 3% 2% 0% 0% 0% 0%
Houston 57% 25% 20% 17% 10% 9% 6% 4% 1%
Los An g eles 69% 5% 4% 3% 1% 1% 1% 0% 0%
New Yor k 35% 6% 4% 3% 0% 0% 0% 0% 0% Philadel p hi a 47% 16% 11% 9% 3% 2% 1% 0% 0% Sacramento 43% 6% 4% 3% 1% 0% 0% 0% 0% St. Louis 22% 8% 5% 3% 1% 0% 0% 0% 0% Washin g to n 48% 21% 15% 14% 7% 6% 2% 1% 0%

base

84/4

80/4

74/4

70/4

64/4

ATLA BOST CHIC CLEV DETR HOUS LA NY PHIL SACR ST.L WASH 0 10 20 30 40 50 60 70Percent of children with 1 or moreexposures >0.06 ppm-8hr

Alternative Standard City 9-B)4-63 84/4

80/4

74/4

70/4

64/4

ATLA BOST CHIC CLEV DETR HOUS LA NY PHIL SACR ST.L WASH 0.0E+0 5.0E+4 1.0E+5 1.5E+5 2.0E+5 2.5E+5 3.0E+5 3.5E+5Number of children withexposures >0.06 ppm-8hr

Alternative Standard City

84/4

80/4

74/4

70/4

64/4

ATLA BOST CHIC CLEV DETR HOUS LA NY PHIL SACR ST.L WASH 0.0E+0 5.0E+4 1.0E+5 1.5E+5 2.0E+5 2.5E+5 3.0E+5 3.5E+5 4.0E+5 4.5E+5Number of children person days withexposures >0.06 ppm-8hr

Alternative Standard City 9-C)

9-D)4-64 4.7.3 Estimates of Repeated Exposures As discussed in section 3.6.3, multiple expos ures pose a greater health concern than single exposures. However, multiple repeat ed exposures are underestimated by APEX (discussed previously in the model evaluati on section), which should be kept in mind for interpretation of these results. Figures 4-9 through 4-11 illustrate the effect of the current and alternative standards has on the estimated percen t of children experiencing 1, 2, and 3 or more repeated exposures above 0.080, 0.070, and 0.060 pp m-8hr, respectively, concomitant with moderate or greater exertion, for each of the urban areas modeled, based on rollback of 2002 O 3 concentrations. When considering the alternative standard scenarios, clear trends are evident.
The reduction in both the number of those e xperiencing exposures a bove a given benchmark level and the frequency of occurrence of those exceedances is directly correlated with the
standard level.4-65 exposur es 1 2 3 +

A TLA BOST CH IC CLEV DETR HOUS LA NY PH I L SACR ST .L WASH

84 /4 80 /4 74 /4 70 /4 64 /4 4% 2% 0% 0% 0% 1 0% 6% 2% 0% 0% 3% 1% 0% 0% 0% 7% 2% 0% 0% 0% 3% 0% 0% 0% 0% 1% 0% 0% 0% 0% 0% 0% 0% 0% 0% 3% 1% 0% 0% 0% 1 1% 5% 1% 0% 0% 1% 0% 0% 0% 0% 1 0% 4% 1% 0% 0% 7% 3% 1% 0% 0%

Figure 4-9. Percent of children (ages 5-18) with repeated 8-hr ozone exposures > 0.08 ppm-8hr, for exposures concomitant with moderate or greater exertion, based on 2002 air quality data.4-66 exposur es 1 2 3 +

A TLA BOST CH IC CLEV DETR HOUS LA NY PH I L SACR ST .L WASH

84 /4 80 /4 74 /4 70 /4 64 /4 2 1% 1 2% 5% 1% 0% 2 8% 2 0% 1 0% 5% 1% 2 0% 1 2% 3% 1% 0% 3 8% 2 7% 9% 2% 0% 2 9% 1 7% 4% 0% 0% 7% 4% 1% 0% 0% 1% 0% 0% 0% 0% 1 6% 9% 3% 1% 0% 3 7% 2 8% 1 3% 5% 0% 7% 4% 1% 0% 0% 3 7% 2 7% 1 1% 5% 0% 2 9% 2 0% 8% 3% 0%

Figure 4-10. Percent of children (ages 5-18) with repeated 8-hr ozone exposures > 0.07 ppm-8hr, for exposures concomitant with moderate or greater exertion, base d on 2002 air quality.4-67 exposur es 1 2 3 +

A TLA BOST CH IC CLEV DETR HOUS LA NY PH I L SACR ST .L WASH

84 /4 80 /4 74 /4 70 /4 64 /4 5 3% 4 5% 2 9% 1 8% 5% 5 4% 4 7% 3 5% 2 5% 1 1% 5 3% 4 4% 2 8% 1 7% 3% 6 6% 6 0% 4 8% 3 5% 1 3% 6 1% 5 4% 3 9% 2 5% 6% 2 7% 1 9% 9% 5% 1% 7% 4% 1% 0% 0% 5 0% 4 1% 2 5% 1 5% 3% 6 4% 5 8% 4 6% 3 6% 1 7% 3 3% 2 4% 1 2% 6% 1% 6 3% 5 8% 4 6% 3 4% 1 4% 5 9% 5 1% 3 8% 2 8% 1 0%

Figure 4-11. Percent of children (ages 5-18) with repeated 8-hr ozone exposures > 0.06 ppm-8hr, for exposures concomitant with moderate or greater exertion, based on 2002 air quality data.4-68 REFERENCES

AHS (2003). U.S. Bureau of the Census a nd U.S. Department of Housing and Urban Development. 2003 American Housing Survey (AHS): National Survey Data. Available
at: http://www.census.gov/hhes/www/housing/ahs/ahs.html , and http://www.huduser.org/datasets/ahs.html
Ainsworth, B. E., Haskell, W. L., Leon, A. S., Jacobs, D. R., Jr., Montoye, H. J., Sallis, J. F., Paffenbarger, R. S., Jr. (1993). Compendium of physical activities: classification of energy costs of human physical activities. Med Sci Sports Exer . 25: 71-80.

Akland, G. G., Hartwell, T. D., Johnson, T. R., Whitmore, R. W. (1985). Measuring human exposure to carbon monoxide in Washington, D. C. and Denver, Colorado during the winter of 1982-83. Environ Sci Technol . 19: 911-918.
American Petroleum Institute. (1997). Sensitivity Testing of pNEM/O 3 Exposure to Changes in the Model Algorithms. Health and Environmental Sciences Department.
Blank, H. and Mitchell, A. (2001). The Status of Preschool Policy in the States. Children’s Defense Fund and Early Childhood Policy Research. Available at: www.earlychildhoodfinance.org/handouts/Stat usOfPreschoolPolicyInTheStates.doc
CARB (2005). Review of the California Ambien t Air Quality Standard for Ozone. California Environmental Protection Agency Air Resources Board. Available at: http://www.arb.ca.gov/research/aaqs/ ozone-rs/rev-sta ff/rev-staff.htm
Dey, A. N., and Bloom B. (2005). Summary Health Statistics for U.S. Children: National Health Interview Survey, 2003. National Center for Heal th Statistics. Vital Health Stat 10(223). Available at: http://www.cdc.gov/nchs/d ata/series/sr_10/sr10_223.pdf
Duff, M., Horst, R. L., Johnson, T. R. (1998) . Quadratic Rollback: A Technique to Model Ambient Concentrations Due to Undefined Em ission Controls. Presented at the Air and Waste Management Annual Meeti ng, San Diego, CA. June 14-18, 1998.
Freedson, P. S. (1989). Field monitori ng of physical activity in children. Pediatr Exerc Sci . 1: 8-18.
Geyh, A. S., Xue, J., Ozkaynak, H., Spengler, J. D. (2000). The Harvard Southern California chronic ozone exposure study: as sessing ozone exposure of gr ade-school-age children in two southern California communities. Environ Health Perspect . 108: 265-270.
Graham, S. E. and McCurdy, T. (2004). Deve loping meaningful cohorts for human exposure models. J Expo Anal Environ Epidemiol . 14: 23-43.
Hartwell, T. D., Clayton, C. A., Ritchie, R. M ., Whitmore, R. W., Zelon, H. S., Jones, S. M., Whitehurst, D. A. (1984). Study of Car bon Monoxide Exposure of Residents of Washington, DC and Denver, Colorado. Resear ch Triangle Park, NC: U.S. Environmental Protection Agency, Office of Research a nd Development, Environmental Monitoring Systems Laboratory. EPA-600/4-84-031.4-69 Johnson, T. (1984). A Study of Personal Exposure to Carbon Monoxide in Denver, Colorado. Research Triangle Park, NC: U.S. Envir onmental Protection Agency, Environmental Monitoring Systems Laboratory. EPA-600/4-84-014.
Johnson, T. (1989). Human Activity Patterns in Ci ncinnati, Ohio. Palo Alto, CA: Electric Power Research Institute. EPRI EN-6204.
Johnson, T. (1997). Sensitivity of Exposure Estimates to Air Quality Adjustment Procedure. Letter to Harvey Richmond, Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, Resear ch Triangle Park, North Carolina.
Johnson, T., Capel, J., McCoy, M. (1996a). Es timation of Ozone Exposures Experienced by Urban Residents Using a Pr obabilistic Version of NEM and 1990 Population Data. Prepared by International Technology Air Qu ality Services for Of fice of Air Quality Planning and Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC. Contract no. 63-D-30094. April 1996. Available at: http://www.epa.gov/ttn/naaqs/ standards/ozone/s_o3_pr_td.html

. Johnson, T., Capel, J., McCoy, M., Warnasch, J. (1996b). Estimation of Ozone Exposures Experienced by Outdoor Childre n in Nine Urban Areas Usin g a Probabilistic Version of NEM. Prepared by International Technology Air Quality Services for Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC. Contract no. 63-D-30094. April 1996. Available at: http://www.epa.gov/ttn/naaqs/ standards/ozone/s_o3_pr_td.html
Johnson, T., Capel, J., McCoy, M., Warnasch, J. (1996c). Estimation of Ozone Exposures Experienced by Outdoor Worker s in Nine Urban Areas Usin g a Probabilistic Version of NEM. 1996. Prepared by International Technol ogy Air Quality Services for Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC. Contract no. 63-D-30094. April, 1996. Available at: http://www.epa.gov/ttn/naaqs/ standards/ozone/s_o3_pr_td.html

Johnson, T., Pakrasi, A., Wisbeth, A., Meiners, G., Ollison, W. (1995). Ozone exposures Within Motor Vehicles – Results of a Field St udy in Cincinnati, Ohio. Proceedings 88 th annual meeting and exposition of the Air & Waste Management Association, San Antonio, TX. June 18-23, 1995

. Preprint paper 95-WA84A.02.
Klepeis, N. E., Tsang, A. M., Behar, J. V. (1996). Analysis of the National Human Activity Pattern Survey (NHAPS) Respondents from a Standpoint of Exposure Assessment. Washington, DC: U.S. Environmental Prot ection Agency, Office of Research and Development. EPA/600/R-96/074.
Langstaff, J. E. (2007). OAQPS Staff Memora ndum to Ozone NAAQS Review Docket (OAR2005-0172). Subject: Analysis of Uncertainty in Ozone Population Exposure Modeling. [January 31, 2007]. Available at: http://www.epa.gov/ttn/naaqs/st andards/ozone/s_o3_cr_td.html
Lee, K., Vallarino, J., Dumyahn, T., Ozkaynak, H ., and Spengler, J. D. (1999). Ozone decay rates in residences. J Air Waste Manag Assoc . 49: 1238-1244.4-70Lioy, P.J. (1990). The analysis of total human exposure for exposure assessment: A multidiscipline science for examining human contact with contaminants. Environ Sci Technol

. 24: 938-945.
McCurdy, T. (2000). Conceptual basis for mu lti-route intake dose modeling using an energy expenditure approach. J Expo Anal Environ Epidemiol . 10: 1-12.
McCurdy, T., Glen, G., Smith, L., Lakkadi, Y. (2000). The National Exposure Research Laboratory's Consolidated Human Activity Database. J Expo Anal Environ Epidemiol . 10: 566-578.
Monn, C. (2001). Exposure assessment of air pollu tants: a review on spatial heterogeneity and indoor/outdoor/personal exposure to suspended particulate matter, nitrogen dioxide and

ozone. Atmos Environ . 35(1):1-32.
Montoye, H. J., Kemper, H. C. G., Saris, W. H.N., Washburn, R.A. (1996) . Measuring Physical Activity and Energy Expenditure

. Champaign IL: Human Kinetics.
National Research Council (1991) . Human Exposure Assessment for Airborne Pollutants: Advances and Opportunities. Washingt on, DC: National Academy of Sciences.
OMB (2005). Update of Statisti cal Area Definitions and Guidance on Their Uses. U.S. Office of Management and Budget, Bulletin No. 05-02. February 22, 2005.
Persily, A. and Gorfain, J. (2004). Analysis of Ventilation Data from the U.S. Environmental Protection Agency Building Assessment Survey and Evaluation (BASE) Study. National Institute of Standards and Technology, NISTIR 7145, December 2004.
Persily, A., J. Gorfain, G. Brunner (2005). Vent ilation Design and Performance in U.S. Office Buildings. ASHRAE Journal. April 2005, 30-35.
Richmond H., Palma, T, Langstaff, J., McCurd y, T., Glenn, G., Smith, L. (2002). Further Refinements and Testing of APEX (3.0): EPA' s population exposure mo del for criteria and air toxic inhalation exposures. Joint meeting of the Inte rnational Society of Exposure Analysis and International Society of Environmental Epidemiology, Vancouver, CAN. August 11-15, 2002.
Rizzo, M. (2005). A Comparison of Different Rollback Methodologies Applied to Ozone Concentrations. November 7, 2005. Available at: http://www.epa.gov/ttn/naaqs/st andards/ozone/s_o3_cr_td.html
Rizzo, M. (2006). A Distributional Comparison between Different Rollback Methodologies Applied to Ambient Ozone Concentr ations. May 31, 2006. Available at: http://www.epa.gov/ttn/naaqs/st andards/ozone/s_o3_cr_td.html
Robinson, J. P., Wiley, J. A., Piazza, T., Garrett, K., and Cirksena, K. (1989). Activity Patterns of California Residents and their Implica tions for Potential Exposure to Pollution. California Air Resources Board, Sacramento, CA. CARB-A6-177-33.
Spier, C. E., Little, D. E., Trim, S. C., J ohnson, T. R., Linn, W. S., Hackney, J. D. (1992). Activity patterns in elementary and high school students exposed to oxidant pollution. J Expo Anal Environ Epidemiol . 2: 277-293.4-71 Tsang A. M., and Klepeis, N. E. (1996). Descript ive Statistics Tables from a Detailed Analysis of the National Human Activity Pattern Surv ey (NHAPS) Data. U.S. Environmental Protection Agency. EPA/600/R-96/148.

Turk, B. H., Grimsrud, D. T., Brown, J. T., Geis ling-Sobotka, K. L., Harrison, J., Prill, R. J. (1989). Commercial Building Ventilation Rate s and Particle Concen trations. ASHRAE No. 3248.
U.S. Department of Transportation and U.S. Ce nsus Bureau (2000). Census of Population and Housing, 2000 long-form (sample) data, Census Transportation Planning Package (CTPP) 2000. Available at: http://transtats.bts.gov/
U.S. EPA (1986). Air Quality Criteria for Ozone and Other Photochemical Oxidants. Office of Health and Environmental Assessment, Envi ronmental Criteria and Assessment Office, U.S. Environmental Protection Agency, Re search Triangle Park, NC. EPA-600/8-84- 020aF-eF. Available from: NT IS, Springfield, VA., PB87-142949.
U.S. EPA (1995). Office Equipment: Design, Indoor Air Emissions, and Pollution Prevention Opportunities. Office of Re search and Development, U. S. Environmental Protection Agency, Washington, DC. EPA/600/R-95/045.
U.S. EPA (1996a). Review of National Ambien t Air Quality Standards for Ozone: Assessment of Scientific and Technical Information - OAQPS Staff Paper. O ffice of Air Quality Planning and Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC. EPA/452/R-96-007. Available at: http://www.epa.gov/ttn/naaqs/ standards/ozone/s_o3_pr_sp.html
U.S. EPA (1996b). Air Quality Criteria for Ozon e and Related Photochemical Oxidants. Office of Research and Development, National Ce nter for Environmental Assessment, U.S. Environmental Protection Agency, Research Tr iangle Park, NC. EPA/600/P-93/004aF-cF. Available at: http://cfpub.epa.gov/ncea/cfm/ recordisplay.cfm?deid=2831
U.S. EPA (2002). Consolidated Human Activitie s Database (CHAD) User s Guide. Database and documentation available at: http://www.epa.gov/chadnet1/
U.S. EPA (2006a). Total Risk Integrated Met hodology (TRIM) - Air Poll utants Exposure Model Documentation (TRIM.Expo / APEX, Version 4) Volume I: User’s Guide. Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC. June 2006. Available at: http://www.epa.gov/ttn/fera/human_apex.html
U.S. EPA (2006b). Total Risk Integrated Method ology (TRIM) - Air Pollut ants Exposure Model Documentation (TRIM.Expo / APEX, Version 4) Volume II: Technical Support Document. Office of Air Quality Planning and Standard s, U.S. Environmental Protection Agency, Research Triangle Park, NC. June 2006. Available at: http://www.epa.gov/ttn/fera/human_apex.html
U.S. EPA (2006c). Air Quality Criteria for Ozon e and Related Photochemical Oxidants (Final). National Center for Environmental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC. EPA/ 600/R-05/004aF-cF. Available at: http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=1499234-72 U.S. EPA (2007). Ozone Population Exposure Analys is for Selected Urban Areas. Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC. Available at: http://www.epa.gov/ttn/naaqs/st andards/ozone/s_o3_cr_td.html
Weschler, C. J. (2000). Ozone in indoor e nvironments: concentra tion and chemistry. Indoor Air . 10: 269-288.

Whitfield, R., Biller, W., Jusko, M., Keisler, J. (1996). A Proba bilistic Assessment of Health Risks Associated with Short- and Long-Te rm Exposure to Tropospheric Ozone. Argonne National Laboratory, Argonne, IL.
Wiley, J. A., Robinson, J. P., Piazza, T., Garrett , K., Cirksena, K., Cheng, Y.-T., Martin, G. (1991a). Activity Patterns of California Reside nts: Final Report. California Air Resources Board, Sacramento, CA. ARB/R93/487. Ava ilable from: NTIS, Springfield, VA., PB94- 108719.
Wiley, J. A., Robinson, J. P., Cheng, Y.-T., Piazz a, T., Stork, L., Pladse n, K. (1991b). Study of Children's Activity Patterns: Final Report. Ca lifornia Air Resources Board, Sacramento, CA. ARB-R-93/489.
Williams, R., Suggs, J., Creason, J., Rodes, C., Lawless, P., Kwok, R., Zweidinger, R., Sheldon, L. (2000). The 1998 Baltimore particulate ma tter epidemiology-exposure study: Part 2. Personal exposure associated wi th an elderly population. J Expo Anal Environ Epidemiol

. 10(6): 533-543. Xue, J., McCurdy, T., Spengler, J., Özkaynak, H. (2004). Understanding variability in time spent in selected locations for 7-12-year old children. J Expo Anal Environ Epidemiol

. 14(3): 222-33.5-1 

### 5. CHARACTERIZATION OF HEALTH RISKS

5.1 INTRODUCTION This chapter presents information rega rding the results from an updated ozone (O 3 ) health risk assessment that builds upon the methodology used in the assessment conducted as part of the
last O 3 NAAQS review. This updated assessment include s estimates of (1) ri sks of lung function decrements in school age children, respiratory symptoms in asthmatic children, respiratoryrelated hospital admissions, and respiratory, non -accidental, and cardior espiratory mortality
associated with recent ambient O 3 levels; and (2) risk reductions a ssociated with just meeting the
current and several alternative 8-hr O 3 NAAQS. The current risk assessment is more fully described and presented in a technical support document, Ozone Health Risk Assessment for
Selected Urban Areas (Abt Associates, 2007; henceforth referred to as the Risk Assessment Technical Support Document and cited as Risk Assessment TSD). The goals of this O 3 risk assessment are: (1) to pr ovide estimates of the potential magnitude of mortality and several morbidity effects associated with current O 3 levels, and with meeting the current 8-hr O 3 NAAQS and alternative O 3 8-hr standards, in specific urban areas; (2) to develop a better understa nding of the influence of vari ous inputs and assumptions on the risk estimates; and (3) to gain insights into the di stribution of risks and patterns of risk reductions associated with meeting alternative O 3 standards. The risk assessment covers a variety of health effects for which there is adequate information to develop quantitative risk estimates. However,
there are several health e ndpoints (e.g., increased lung inflammation, increased airway responsiveness, impaired host defenses, increas ed medications use, increased asthma-elated emergency department visits, increased school abse nces) for which there currently is insufficient information to develop quantitative risk es timates. These additiona l health endpoints are discussed qualitatively in Chapte r 3 of this Staff Paper. We recognize that while there are many sources of uncertainty and variabil ity inherent in the inputs to this assessment, which make the specific estimates uncertain, there is sufficient co nfidence in the directi on and general magnitude of the estimates provided by the assessment, particularly with respect to relative differences between alternative potential standa rds, for the assessment to serve as a useful input to decisions on the adequacy of the O 3 standard. While some of these uncertainties have been addressed quantitatively in the form of estimated conf idence ranges around central risk estimates, other uncertainties and the variability in key inputs ar e not reflected in these confidence ranges, but rather are addressed through sepa rate sensitivity analyses or are characterized qualitatively. Following this introductory section, this chapter discu sses the scope of the risk assessment, including selection of urban areas and health endpoi nts and the degree of confidence
associated with the various health outcomes that have been associated with ambient O 35-2 exposures; components of the risk model; char acterization of uncertainty and variability associated with the risk estimates; and key results from the assessment. The Risk Assessment TSD provides a more detailed discussion of the risk assessment methodology and includes
additional risk estimates be yond those summarized herein.

5.1.1 Overview of Risk Assessment From Last Review

EPA conducted a health risk assessment that produced risk estimates for the number and percent of children and outdoor workers experi encing lung function and respiratory symptoms
associated with O 3 exposures for 9 urban areas. This portion of the risk assessment was based on exposure-response relationships deve loped from analysis of data from several controlled human exposure studies which was combined with exposu re estimates developed for children who spent
more time outdoors and for outdoor workers. The risk assessment for th e last review also included risk estimates for excess respirator y-related hospital admissions related to O 3 concentrations for New York City, based on a co ncentration-response relationship reported in an epidemiological study (Thurston et al., 1992). Ri sk estimates for lung function decrements, respiratory symptoms, and hospital admissions were developed associ ated with recent air quality levels (referred to as “as is” air quality) and for just meeting the existing 1-hr standard and
several alternative 8-hr standards. The met hodological approach followe d in conducting the last risk assessment and risk estimates resulting from that assessment are described in Chapter 6 of the 1996 Staff Paper (U.S. EPA, 1996b) and in several technical reports and publications (Whitfield et al., 1996; Whitfiel d, 1997; Whitfield et al., 1998).
In the 1997 review of the O 3 NAAQS, the risk estimates played a significant role in both the staff recommendations and in the propos ed and final decisions to revise the O 3 standards. CASAC stated (Wolff, 1995) in its advice and recommendations to the Administrator on the O 3 Staff Paper that “EPA’s risk assessments must pl ay a central role in identifying an appropriate level,” while also noting that “because of the my riad of assumptions that are made to estimate population exposure and risk, large un certainties exist in these esti mates.” In the 1997 notice (62 FR 38856) announcing the deci sion to revise the O 3 standards, EPA indicated that the
Administrator considered the resu lts of the exposure and risk an alyses and key observations and conclusions from these analyses in putting effects considered to be adverse to individuals into a broader public health perspective and in making judgments about the level of a standard that would be requisite to protect public health with an adequate margin of safety.

5.1.2 Development of Approach for Current Risk Assessment

The health risk assessment described in th is chapter and in the Risk Assessment TSD builds upon the methodology and lessons learned from the risk assessment work conducted for
the last review. The current risk assessment al so is based on the information evaluated in the5-3 final CD. The general approach used in the cu rrent risk assessment was described in the draft Health Assessment Plan (U.S. EPA, 2005a), that was released to the CASAC and general public in April 2005 for review and comment and whic h was the subject of a consultation with the

CASAC O 3 Panel on May 5, 2005. The approach used in the current risk assessment reflects consideration of the comments offered by CASA C members and the public on the draft Health Assessment Plan, comments offered by CASAC me mbers and the public on the first and second drafts of the Staff Paper and first and sec ond drafts of the Risk Assessment TSD at and subsequent to a consultation with CASAC on De cember 8, 2005, and at and subsequent to a review by CASAC on August 24-25, 2006. CASA C comments reflec ting both the Ozone Panel’s views and additional comments by individua l members were provided to the Agency in letters dated February 16, 2006 (Henders on, 2006a), June 5, 2006 (Henderson, 2006b) and October 24, 2006 (Henderson, 2006c). This risk a ssessment chapter indicates where significant
new information has been added sinc e the second draft Staff Paper.
The basic structure of the current risk a ssessment reflects the two different types of
human studies on which the O 3 health risk assessment is based: controlled human exposure studies and epidemiological studies. Controll ed human exposure stud ies involve volunteer subjects who are exposed while engaged in different exercise regimens to specified levels of O 3 under controlled conditio ns for specified amounts of time. For the current health risk assessment, we are using probabilistic exposure- response relationships based on analysis of
individual data that describe the relationship between a meas ure of personal exposure to O 3 and measures of lung function recorded in the studies. The meas ure of personal exposure to ambient

O 3 is typically some function of hourly exposur es – e.g., 1-hr maximu m or 8-hr maximum. Therefore, a risk assessment based on exposure -response relationships derived from controlled human exposure study data requires estimates of personal exposure to ambient O 3 , typically on a
1-hr or multi-hour basis. Because data on personal hourly exposures to O 3 of ambient origin are not available, estimates of personal exposures to varying ambient con centrations are derived through exposure modeling, as described in Chap ter 4. While the quantitative risk assessment based on controlled human exposure studies ad dresses only lung function responses, it is important to note that other respiratory res ponses have been found to be related to O 3 exposures in these types of studies, includ ing increased lung inflammation, in creased respiratory symptoms, increased airway responsiveness, and impaired host defenses. Chapter 3 of this Staff Paper provides a more complete discussion of these additional health endpoints which are an important part of the overall characterization of risks associated with ambient O 3 exposures. In contrast to the exposure-response relationships derived from controlled human exposure studies, epidemiological studies provide estimated concentration-response relationships based on data collected in r eal world community settings. Ambient O 35-4 concentrations, measured as the average of monitor-specific measurements, using populationoriented monitors, are used as a surrogate meas ure of population exposure. It is important to
consider that O 3 in ambient air is present in a complex mixture of air pollutants, and that some other components of the mixture may play an importa nt role in some of the health-related effects observed. It is also importan t to recognize that p opulation health responses included in the quantitative risk assessment for O 3 (i.e., respiratory symptoms in asthmatic children, hospital admissions for respiratory illness, and premature mortality) represent only a portion of the health
effects that are associated with O 3 exposures. As discussed more fully in Chapter 3, a wide variety of respiratory and cardiorespiratory e ffects have been shown to be related to O 3 exposures including increased medication usage in asthmatics, increased doctor’s visits and emergency department visits, and increased school absences. As described more fully below, a risk assessment based on epidemiological studies typically requires base line incidence rates and population data for the risk assessment locations.
The characteristics that are relevant to car rying out a risk assessment based on controlled human exposure studies versus one based on epid emiology studies evaluated in the CD can be
summarized as follows:

• The relevant controlled human exposure studies in the CD provide data that can be used to estimate exposure-response functions, and therefore a risk assessment based on these studies requires as input (modeled) personal exposures to ambient O 3 . The relevant epidemiological studies in the CD provi de concentration-re sponse functions, and, therefore, a risk assessment ba sed on these studies requires as input (actual monitored or adjusted based on monitored) ambient O 3 concentrations, and pers onal exposures are not required as inputs to the assessment.

• Epidemiological studies are ca rried out in specific real world locations (e.g., specific urban areas). To minimize uncertainty, a risk assessment based on epidemiological studies has been performed for the locations in which the studies were carried out. Controlled human exposure stud ies, carried out in laborator y settings, are generally not specific to any particular real world loca tion. A risk assessment based on controlled human exposure studies can ther efore appropriately be carr ied out for any location for which there are adequate air quality and other data on which to base the modeling of personal exposures. There are, therefore, some locations for which a risk assessment based on controlled human expos ure studies could appropriately be carried out but a risk assessment based on epidemiological studi es would involve gr eater uncertainty.

• The adequate modeling of hourly persona l exposures associated with ambient concentrations for use with exposure-res ponse relationships requires more complete ambient monitoring data than are necessary to estimate average ambient concentrations used to calculate risks base d on concentration-re sponse relationships. Therefore, there may be some locations in which an epidemio logical studies-based risk assessment could appropriately be carried out, but a contro lled human exposure studies-based risk assessment would involve greater uncertainty.5-5 • To derive estimates of risk from concen tration-response relati onships estimated in epidemiological studies, it is usually nece ssary to have estima tes of the baseline incidences of the health effects involved. Such baseline incidence estimates are not needed in a controlled human exposur e studies-based risk assessment. The scope of the current O 3 risk assessment is described in the next sectio n along with air quality considerations th at are relevant to both parts of the risk assessment. Then, the methods for the two parts of the risk assessment – the part based on controlled human exposure studies and the part based on epidemiological and field studies – are discussed in sections 5.3.1 and 5.3.2 below, followed by presentation and discussion of the O 3 risk estimates in section 5.4. Both parts of the risk assessment were implemented w ithin a new probabilistic version of TRIM.Risk, the component of EPA’s Total Risk Integrat ed Methodology (TRIM) model that estimates
human health risks.

5.2 SCOPE OF OZONE HEALTH RISK ASSESSMENT

The current O 3 health risk assessment estimates risks of various health effects associated with exposure to ambient O 3 in a number of urban areas select ed to illustrate the public health impacts of this pollutant. The short-term expos ure related health endpoin ts selected for the O 3 risk assessment, discussed in section 5.2.1, includ e those for which the CD concludes that the evidence as a whole supports the general conclusion that O 3, acting alone and/or in combination with other components in the ambien t air pollution mix is likely causal. 1
As discussed in section 3.7, we recognize that there are varying levels of confidence that various health effect endpoints are associated with O 3 at ambient levels. As discussed in section
3.7.5 there is clear evidence of a causal relationship between lung function decrements and O 3 exposures for school age childre n engaged in moderate exertion for 6 to 8-hours based on the numerous controlled human exposure studie s and summer camp field studies conducted by various investigators over the last 30 years. We also judge that there is clear evidence of a causal relationship between increased re spiratory symptoms in moderate to severe asthmatic children
and O 3 exposures. There also is strong evidence of a causal relationship between increased respiratory-related hospital admissions and O 3 exposure during the warm O 3 season, based on extensive and fairly consistent epidemiological studies as well as evidence from controlled human exposure studies reporting increased lung inflammation a nd airway responsiveness. The CD concludes that there is strong ev idence which is highly suggestive of a causal relationship between respiratory- related, non-accidental, and cardiorespiratory-related mortality

1 As discussed in 5.2.1, certain endpoints met this criteria of likely causality, but were not included in the risk assessment for other reasons, such as insufficient exposure-response data or lack of baseline incidence data.5-6 and O 3 exposures during the warm O 3 season. Our judgment with respect to these health outcomes is based on the fairly consistent posit ive associations found be tween elevated warm O 3 season levels and these mortality outcomes even when the effect of PM is controlled for, and supporting evidence about potential m echanisms of effects on the cardiovascular system from animal toxicology, human clinical and epidemio logical studies. There is certainly greater uncertainty about these outcomes than the other e ffects discussed above. We also recognize, as discussed in section 3.7.5, that fo r some of the effects observed in epidemiological studies, such as increased respiratory-related hospital admi ssions and non-accidental and cardiorespiratory mortality, O 3 may be serving as an indicator for reactive oxidant species in the overall photochemical oxidant mix and that these other constituents may be responsible in whole or part
for the observed effects.
The current risk assessment includes risk estimates for 12 urban areas

. The basis for
selection of these areas is discussed below (section 5.2.2). Another important aspect of the current risk assessment is that the risks estimated are only those associated with ambient O 3 concentrations exceeding estimated policy-relevant background (PRB) levels (hereafter, referred to as either “background” or “PRB” in this chapter). 2 Risks associated with concentrations above this background are judged to be more relevant to policy decisions a bout the NAAQS than estimates th at include risks potentially
attributable to uncontrollab le background concentrations.

5.2.1 Selection of Health Endpoint Categories As noted above, in the last review a significant portion of the health risk assessment involved developing risk estimates fo r both lung function decrements ( ≥ 10, ≥ 15, and ≥ 20% changes in FEV 1 ) and respiratory symptoms in children (a ge 6 to 18 years old) who spend more time outdoors and outdoor workers with 1-hr exposur es at moderate and heavy exertion and 8-hr exposures at moderate exertion. As discussed insection 3.3.1.1 and Chapter 6 of the CD, there is a significant body of controlled human exposure studies reporting lung f unction decrements and respiratory symptoms in adu lts associated with 1- and 6 to 8-hr exposures to O 3 , as well as similar responses in outdoor workers and others engaged in recreati onal outdoor activities. Consistent with the approach used in the last review, we judge th at it is reasonable to estimate exposure-response relationships for l ung function decrements associated with O 3 exposures in children 5-18 years old based on data from young adu lt subjects (18-35 years old). As discussed in the 1996 Staff Paper and 1996 CD, findings from other chamber studies

2 Policy relevant background is defined in section 2.7 of this Staff Paper and development of estimates for policy relevant background for use in the risk assessment is discussed in section 5.2.3.5-7 (McDonnell et al., 1985) for children 8-11 years ol d at a single exposure level and summer camp
field studies in at least six different locations in the U.S. and Canada found lung function decrements in healthy children similar to thos e observed in healthy adults exposed to O 3 under controlled chamber conditions. The same approach is being used in the current assessment. In the prior risk assessment, staff focused on the risk estimates for lung function decrements associated with 1-hr heavy exertion, 1-hr m oderate exertion, and 8-hr moderate exertion exposures in children age 5-18 year s of age. Since the 8-hr mode rate exertion exposure scenario in children who spend more time outdoors clearly resu lted in the greatest health risks in terms of both the magnitude of the lung function decremen ts and the percent of the population estimated to experience these effects, and since no ne w information published since the last review suggests any changes that would impact this c onclusion, we have include d only the lung function decrements ( ≥ 10, 15, and 20% FEV 1 ) associated with 8-hr moderate exertion exposures in children and asthmatic children (age 5 to 18 years old) in the current risk assessment. 3 Risk estimates for asthmatic school age children have been added to the risk assessment since the second draft Staff Paper based on comments offe red by the CASAC emphasizing the importance of health effects for this population.
While outdoor workers and other adults w ho engage in moderate exertion for prolonged periods during the day also are clearly at risk for experiencing similar lung function responses when exposed to elevated ambient O 3 concentrations, the exposure and risk assessment conducted during the prior review s uggested that school age children ar e at greatest risk in terms of the number of individuals likely affected. Given the lack of information about the number of individuals who regularly work or exercise outdoors, we chose to focus the current quantitative risk assessment for lung function decrements on all and asthmatic school age children. Therefore, it is important to r ecognize that the current risk as sessment does not account for all of the lung function effects in the general population that would be associated with exposure to O 3 under the various air quality scenarios examined. Although respiratory symptoms in healthy children were estima ted in the last review, we have not included this endpoint in the current quantita tive risk assessment. This is because

3 Subsequent to completion of the Risk Assessmen t TSD, EPA analysis of uncertainty of the exposure modeling results uncovered an error in how children are ch aracterized as active. This error resulted in an overestimat e of the number of active childr en included in the exposure estimates which are an input to the lung functio n risk estimates for active children. Thus, the lung function risk estimates prov ided for active children in the Risk Assessment TSD are not accurate and we did not include risk estimates for active children in this chapter.5-8 several field studies conducted si nce the last review did not ob serve respiratory symptoms in field studies examining responses in healthy ch ildren. The CD concludes that “collectively,
these studies indicate that there is no cons istent evidence of an association between O 3 and respiratory symptoms among healthy children” (CD, p. 7-55). Thus, we decided to limit this portion of the risk assessment to lung function decrements in children and to again base the exposure-response relationships on data obtained for 18-35 year old subjects. While a number of controlled human exposur e studies have reported additional health endpoints associated with s hort-term exposures to O 3 , including airway hyperresponsiveness, inflammation, and immune system effects, ther e is insufficient exposure-response data at
different concentrations to devel op quantitative risk estimates for these effects. These important additional effects are discussed in Chapter 3, and we want to empha size that the current quantitative risk assessment presents only a partial picture of the risk s to public health associated
with short-term O 3 exposures. As discussed in the CD and Chapter 3, a si gnificant number of epidemiological studies examining a variety of health e ffects associated with ambient O 3 concentrations in various locations throughout the U.S., Canada, Europe, and other regions of the world have been published since the last O 3 NAAQS review. Chapter 3 reviews the epidemiological evidence evaluated in Chapter 7 of the CD . In selecting health endpoints to be included in the current quantitative risk assessment, we have focused on health endpoints that are better understood in terms of health consequences (i.e., where there is greater consensus about the degree of response that should be considered as representing an adve rse health effect in th e population) and endpoint categories for which the weight of the eviden ce supports the inference of a likely causal relationship between O 3 and the effect category. Certain h ealth endpoints met the criteria of likely causality, but were not included in the risk assessment for other reasons, such as insufficient exposure-response data or lack of baseline incidence data. Based on these considerations, the following endpoints associ ated with short-term exposures to O 3 during the

“warm O 3 season” (April 1 to September 30) have been included:

• Respiratory symptoms in moderate/sev ere asthmatic children (ages 0 to 12);

• Hospital admissions for respiratory illness and asthma;

• Premature total non-accidental and cardiorespiratory mortality. As discussed above in section 3.3.1.1.1, the CD also concludes that collectively, the results of epidemiological studies suggest that respiratory symptoms and increased medication
use in asthmatic children are asso ciated with acute exposure to O 3 . These recent studies provide very strong evidence that asthmatic children experience O 3 -related effects.5-9 Large multi-city studies, as well as many studies from individual cities, have reported an
association of O 3 concentrations with respiratory-relate d hospital admissions. Studies with data restricted to the summer or warm season, in ge neral, indicated positive and robust associations
between ambient O 3 concentrations and respiratory-related hospital admissions. With respect to

acute O 3 effects on mortality, the CD concludes (p.7- 175) that, “The majority of the studies suggest an elevated risk of all cause mort ality associated with acute exposure to O 3 , especially in
the summer or warm season when O 3 levels are typically high.” As discussed in Chapter 7 of the CD and in sections 3.3.1.1.1 and 3.3.1.1.6 above, several additional health endpoints including ED visits for respiratory illness and increased school absences have been reported to be associated with short-term O 3 exposures. The current quantitative risk assessment does not include these additional h ealth endpoints. Emergency department visits were excluded from the quantit ative risk assessment because of the lack of baseline incidence data for ED visits, as well as the more limited and less consistent database. We also judge that the data reporting an association between short-term O 3 exposures and school
absences is too limited to include in the current risk assessment. Table 5-1 provides a summary of the health effects and the corresponding populations for each health effect which were included in the quan titative risk assessment. Table 5-2 lists some
of the health effects that have been associated with elevated O 3 exposures which were not included in the quantitative risk assessment. Ch apter 3 provides additional discussion of the
health effects not included in this risk assessment.

5.2.2 Selection of Study Areas

The criteria and considerations that went into selection of urban areas for the O 3 risk assessment included the following:

• The overall set of urban locations should re present a range of geographic areas, urban population demographics, and climatology and be focused on areas that do not meet the current 8-hr O 3 NAAQS.

• The largest areas with major O 3 nonattainment problems should be included.

• There must be sufficient air quality da ta for a recent three year period.

• An area should be the same or close to th e location where at least one concentrationresponse function for the health endpoints incl uded in the assessment has been estimated by a study that satisfies the study selection cr iteria (see below). If the study was a hospital admissions study, then relatively recent location-specific baseline incidence data had to be available.5-10 Table 5-1. Health Effects and Associated Po pulation Groups Addressed in Quantitative Risk assessment

Health Effect Population Lung function decrements (FEV 1 ) All school age children (age 5-18)

School age asthmatic children (age 5-18) Respiratory symptoms (chest tightness, shortness of breath, wheeze) Asthmatic children (age 0 - 12) in Boston

Hospital admissions: -For respiratory illness

-Asthma-related -Pneumonia -Age 30+ in Los Angeles, Age 65+ in Cleveland, All ages in New York -All ages in New York -Age 65+ in Detroit Mortality: -Total (not incl uding accidental) -Cardiorespiratory All ages

Table 5-2. Health Endpoints and Associat ed Population Groups Not Included in the Quantitative Risk Assessment*

Health Effect Population Lung function decrements Adults (outd oor workers, recreational exercisers, athletes) Respiratory symptoms (cough, chest discomfort) Adults (outdoor workers, recreational exercisers, athletes) School absences for respiratory illness Children Asthma-related emergency department visits Asthmatics Doctors visits Adults and children Lung inflammation Adults and children Increased medication usage Asthmatic children and adults Decreased resistance to infection, impaired host defense Adults and children

* The list of health endpoints and populations not included in the risk assessment is not a comprehensive list, but rather provides a general indication of the types of health endpoints that are associated with exposures to ozone but not included in the quantitative risk assessment.5-11 • Locations in which more health endpoints ha ve been assessed were preferred to those with fewer. Since the exposure-respons e functions for lung functi on decrements based on the controlled human exposure studies were based on controlled laboratory conditions, the location of these studies played no role in selec ting urban locations for the risk assessment.
Based on the selection criteria and considerations listed a bove, the following urban areas
were included in the risk assessment:

• Atlanta

• Boston

• Chicago

• Cleveland

• Detroit

• Houston

• Los Angeles

• New York City

• Philadelphia

• Sacramento

• St. Louis

• Washington, D.C. As discussed in Chapter 4, for the purposes of estimating population exposure and the risk of lung function decrements associ ated with these population ex posure estimates, the 12 urban
areas have been defined based on consolidat ed statistical areas (CSAs). The population estimates for these 12 urban area CSAs are given in Table 4-3. About 40% of the total U.S. urban population (88.5 million persons) resides in these 12 urban areas including 18.3 million school age children (ages 5 to 18). In contra st to the risk assessment for lung function decrements, for the risk estimates for prematur e mortality and excess hospital admissions, the
urban areas have been defined to be generally consistent with the geographic boundaries used in the epidemiological studies which were the sour ce of the concentration-response functions used in this risk assessment. In most cases the ep idemiological studies only included the core urban county or a limited number of counties in one or more of the 12 urban areas. In addition, estimates of respiratory symptoms in asthmatic children were developed for one urban area (the Boston CSA).

5.2.3 Air Quality Considerations Both the portion of the risk assessment based on controlled human exposure and the portion based on epidemiological studies include ri sk estimates for a recent year of air quality (labeled “as is” air quality in th e Risk Assessment TSD) and for ai r quality adjusted so that it simulates just meeting the current and several alternative 8-hr O 3 NAAQS based on a recent5-12 three-year period (2002-2004). This period was sele cted to represent the most recent air quality data for which complete data were availa ble when the risk assessment was conducted.
In order to estimate health risks associated wi th just meeting the current and alternative 8-
hr O 3 NAAQS, it is necessary to estima te the distribution of hourly O 3 concentrations that would occur under any given standard. Si nce compliance with the current O 3 standard is based on a 3- year average, air quality data from 2002 to 2004 have been used to determine the amount of
reduction in O 3 concentrations required to meet the cu rrent standard. Estimated design values 4 are used to determine the adjustment necessary to just meet the current 8-hr daily maximum
standard. The amount of control has then been applied to each year of data (2002, 2003, and 2004) to estimate risks for a single O 3 season or single warm O 3 season, depending on the health effect, in each of these indivi dual years. As described in se ction 4.5.6 and in more detail in Rizzo (2006), after considering several approaches , we concluded that th e Quadratic air quality adjustment procedure generally best repres ented the pattern of reductions across the O 3 air quality distribution observed over the last decade. The Quadratic air quality adjustment procedure was applied in each of the 12 urban areas to the 2002 and 2004 O 3 air quality data and in a subset of 5 urban areas (Atlanta, Chica go, New York, Houston, and Los Angeles) to the

2003 O 3 air quality data, based on th e 3-year period (2002-2004) O 3 design values, to generate new time series of hourly O 3 concentrations for 2002, 2003, a nd 2004 that reflect air quality levels that just meet the current 8-hr O 3 standard over this three y ear period. Risk estimates
associated with 2003 O 3 monitoring data and 2003 air quality adjusted to just meet the current
and alternative 8-hr standards have been adde d to the assessment since the second draft Staff Paper. We note that since compliance with the curren t standard is based on the 3-year average
of the 4 th -highest daily maximum 8-hr values, the air quality distribution in each of the 3 years can, and generally does, vary. As a consequence, the risk estima tes associated with air quality just meeting the current standard also will vary depending on the year chosen for the analysis. We include assessments involving adjustment of both 2002 and 2004 air quality data to illustrate the magnitude of this year-to-year variability in the risk estimates. The year 2002 generally had meteorology that was very conducive to producing O 3 over the eastern half of the U.S. and this resulted in the highest O 3 levels over the 2002-2004 time period in the vast majority of the 12 urban study areas. In contrast, 2004 was a year associated with an unusually cool and rainy

4 A design value is a statistic that describes the air quality status of a given area relative to the level of the NAAQS. Design values are often based on multiple years of data, consistent with the specification of the NAAQS in Part 50 of the CFR. Fo r example, for the current O 3 NAAQS, the 3-year average of the annual 4 th -highest daily maximum 8-hr average concentrations, based on the monitor within an urban area yielding the highest 3-yr average, is the design value.5-13 summer in the eastern half of the U.S. and this contributed to the f act that the lowest O 3 levels over this same three-year period we re observed in this year in most of the urban areas included in
the assessment. The lower O 3 levels observed in 2004 also were lower, in part, as a result of reductions in nitrogen oxides (NO x ) emissions associated with implementation of additional regional controls on large power plants in the eastern half of the U.S. Differences in meteorology were less evident in Texas and Cali fornia and these latter areas also were not impacted by the recent additional regional controls imposed on large power plants. Thus, its not surprising that the daily maximum 8-hr levels observed in Houston in 2004 were somewhat higher than those observed in 2002 and that 8-hr levels were similar in Los Angeles between these two years. The risk results for 2002 and 2004, thus, provide generally lower-end and upper-end estimates of the annual risks that can o ccur over a three-year pe riod when alternative standards are just met. Daily maximum 1-hr and 8-hr O 3 levels in 2003 generally fell
somewhere between 2002 and 2004 levels in most of the 12 urban areas. As noted earlier, the risk es timates developed for both the re cent air quality scenario and just meeting the current 8-hr standard represent risks associated with O 3 levels in excess of estimated background concentrations. Th e results of the global tropospheric O 3 model GEOSCHEM have been used to estimate average background O 3 levels for different geographic regions across the U.S. These GEOS-CHEM si mulations include a background simulation in which North American anthropogenic emissions of NO x , non-methane volatile organic compounds, and carbon monoxide are se t to zero, as described in Fiore et al . (2003). We estimated monthly background concentrations for each of the 12 urban areas based on the GEOS-CHEM simulations, including daily diurnal profiles which were fixed for each day of each month during the O 3 season (See Appendix 2-A of this Staff Paper for plots of these estimated background values). The CD and s ection 2.7 above indicate that background O 3 concentrations at the surface are generally pred icted to be in the range of 0.015 to 0.035 ppm in the afternoon, and they declin e under conditions conducive to O 3 episodes. They are highest during spring and decline into summer. This ra nge is lower than the estimated range of 0.03 to 0.05 ppm for typical summertime background levels included in the 1996 CD and the single value of 0.04 ppm used for background in the prior risk assessment.
As discussed in section 2.7, the CD summari zes its evaluation of the validity of the
GEOS-CHEM model, and states "in conclusion, we estimate that the PRB ozone values reported by Fiore et al. (2003) for afternoon surface air over the United States are likely 10 ppbv too high
in the southeast in summer, and accurate with in 5 ppbv in other regions and seasons" (CD, p.3-5-14 53 ). These error estimates are based on comp arison of model output with observations for conditions which most nearly reflect those given in the PRB definition (i.e., at the lower end of the probability distribution). For O 3 (cf. Figures 8 and 9 of Fiore et al. (2003) for the southeast and Figure 3 of Fiore et al. (2002) for the northeast) it can be seen that GEOS-CHEM

overestimates O 3 for the southeast and underestimates it for the northeast. Sensitivity analyses examining the impact of alternative estimates for background on lung func tion and mortality risk estimates have been developed since the second draft Staff Paper and are presented in section
5.4.3. As discussed in section 5.4.3, estimated ri sk reductions associat ed with alternative standards relative to just meeting the current st andard are generally unaffected by the estimated PRB levels within the range of alternative estimates examined.

5.3 COMPONENTS OF THE RISK MODEL As noted above in section 5.1.2, there are two parts to the he alth risk assessment: one based on combining information from contro lled human exposure st udies with modeled population exposure and the other based on combining information from community epidemiological studies with either monitored or adjusted ambient concentrations le vels. Section 5.3.1 below discusses the portion of the current ri sk assessment related to effects reported in controlled human exposure studies and section 5. 3.2 below discusses the portion of the current
risk assessment related to health effects re ported in community epidemiological studies.

5.3.1 Assessment of Risk Based on Co ntrolled Human Exposure Studies

5.3.1.1 General Approach The major components of the portion of the h ealth risk assessment based on data from controlled human exposure studies are illustrate d in Figure 5-1. As shown in Figure 5-1, under this portion of the risk assessment, exposure es timates for a number of different air quality scenarios (i.e, recent year of air quality, just meeting the current 8-hr standard, just meeting alternative standards, and background) are co mbined with probabilistic exposure-response relationships derived from the controlled human exposure studies to develop risk estimates associated with recent air quality and just meetin g the current and alternative standards in excess of background. As discussed above, the health e ffect included in this portion of the risk assessment is lung function decrement, as measured by FEV 1 in school aged children engaged in moderate exertion for 8 hours. The air quali ty and exposure analysis components that are integral to this portion of the risk assessment are discussed in greater deta il in Chapter 4 and in the Exposure Assessment TSD.5-15 Several risk measures were generated for this portion of the risk a ssessment. In addition
to the estimates of the number of all and asth matic school age children ex periencing one or more occurrences of a lung function decrement > 10, > 15, and > 20% in an O 3 season, risk estimates have been developed for the total number of o ccurrences of these lung function decrements in these same population groups. The mean number of occurrences per child has been calculated to provide an indicator of the av erage number of times that a responder would experience the specified effect during an O 3 season. The population sizes fo r all and asthmatic school age
children for each of the 12 urban area s used in this part of the risk assessment are given in Table 4-3 of this Staff Paper. We note that the as thmatic school age children subpopulation is a subset of all school age children, and thus the risk es timates presented for these two groups should not
be combined. A population risk estimate for a given lung function decrement (e.g., $ 15% change in

FEV 1 ) is an estimate of the expected number of people who will experience that lung function
decrement. Since we are interested in risk estimates associated with O 3 concentrations in excess of background concentrations, the following steps were taken to estimate the risk associated with
recent conditions in excess of background: (1) expected risk given the personal exposures
associated with recent ambient O 3 concentrations was estimated, (2) expected risk given the personal exposures associated wi th estimated background ambient O 3 concentrations was estimated, and (3) the latter was s ubtracted from the former. As shown in Equation 5-1 below, the population risk is then calculated by multiplyi ng the resulting expected risk by the number of people in the relevant population. See Appe ndix 5B.2 for additional information concerning notation and the derivation of the risk estimate algor ithms used in this risk assessment. Because response rates are calculated for 21 fractiles (i.e., 0.01, 0.05, 0.10, 0.15 ... 0.50, 0.55, ... 0.90, 0.95, 0.99), estimated population risks are similarly fractile-specific. The risk (i.e., expected fractional response rate) for the k th fractile, R k is:

) | ( ) | (

1 1 b i k N

i b i j k N

j j k e RR x P e RR x P R b 

## ∑ ∑

=

= − = (Equation 5-1)

where:

e j = (the midpoint of) the j th category of personal exposure to O 3 , given recent ambient

O 3 concentrations;

b i e = (the midpoint of) the ith cate gory of personal exposure to O 3 , given background

ambient O 3 concentrations;5-16 P

j = the fraction of the population having personal exposures to O 3 concentration of e j ppm, given recent ambient O 3 concentrations;

b i P = the fraction of the population having personal exposures to O 3 concentration of

b i e ppm, given background ambient O 3 concentrations;

j k e RR | = k-fractile response rate at O 3 concentration e j ;

b i k e RR | = k-fractile response rate at O 3 concentration b i e ; and

N

= number of intervals (categories) of O 3 personal exposure concentration, given recent
ambient O 3 concentrations; and

b N = number of intervals of O 3 personal exposure concentration, given background

ambient O 3 concentrations.

For example, if the median expected respons e rate for recent ambient concentrations is 0.065 (i.e., the median expected fraction of th e population responding is 6.5%) and the median expected response rate for background ambient con centrations is 0.001 (i.e., the median expected fraction of the population responding is 0.1%), then the median expected response rate
associated with recent ambient concentrations above background concentrations is 0.065 – 0.001 = 0.064. If there are 300,000 people in the releva nt population, then the population risk is 0.064 x 300,000 = 19,200. 5

5 A normalization procedure had to be applied to the number of responders (or the number of occurrences of response) given personal exposures associated with recent ambient O 3 concentrations (or concentrations rolled back to simulate just meeting a standard) because the population size used in the exposure runs for background concentrations were not identical to those used in the exposure runs conducted for the recent air quality and alternative standard scenarios. This normalization procedure is described in section 3.3.1 of the Risk Assessment TSD.5-17Figure 5-1. Major Components of Ozone Health RiskAssessment Based on Controlled Human Exposure StudiesAmbientMonitoring forSelected UrbanAreasAir QualityAdjustmentProceduresCurrent andAlternativeProposedStandardsRisk Estimates:•Recent AirQuality•CurrentStandard•AlternativeStandardsHealthRiskModelControlled HumanExposure StudiesProbabilisticExposure -ResponseRelationshipsExposure-ResponseAir QualityModeledBackgroundConcentrationsRecent(“As Is”)AmbientO3LevelsExposureModelExposure EstimatesAssociated with:•BackgroundConcentrations•Recent Air Quality•Current Standard•AlternativeStandardsExposureAmbientMonitoring forSelected UrbanAreasAir QualityAdjustmentProceduresCurrent andAlternativeProposedStandardsRisk Estimates:•Recent AirQuality•CurrentStandard•AlternativeStandardsHealthRiskModelControlled HumanExposure StudiesProbabilisticExposure -ResponseRelationshipsExposure-ResponseAir QualityModeledBackgroundConcentrationsRecent(“As Is”)AmbientO3LevelsExposureModelExposure EstimatesAssociated with:•BackgroundConcentrations•Recent Air Quality•Current Standard•AlternativeStandardsExposure5-18 5.3.1.2 Exposure Estimates Exposure estimates used in this portion of the risk assessment were obtained from running TRIM.Expo for each of the 12 urban areas fo r the various air quality scenarios (i.e., for 2004 and 2002 air quality representing recent years, for 2004 and 2002 air quality adjusted to just meet the current and several potential altern ative 8-hr standards, for 2003 air quality and 2003 air quality adjusted to just meet several poten tial alternative standard s in 5 urban areas, and for air quality levels representing backgr ound based on estimates from the GEOS-CHEM model). 6 Chapter 4 and the Exposure Assessment TSD (U.S. EPA, 2007) provide additional details about the inputs and me thodology used to estimate populati on exposure in the 12 urban areas. Exposure estimates fo r all and asthmatic school age children (ages 5 to 18) were separately combined with probabilistic expos ure-response relationships for lung function decrements associated with 8-hr exposure while engaged in moderate exertion. Individuals engaged in activities that resulted in an averag e equivalent ventilation rate (EVR) for the 8-hr period at or above 13 l/min-m 2 were included in the exposure estimates for 8-hr moderate or greater exertion. This range was selected to match the EVR for the gr oup of subjects in the controlled human exposure studies that were the basis for the exposure-response relationships used in this portion of the risk assessment.

5.3.1.3 Exposure-Response Functions

As described in section 3.1.2 of the Risk Assessment TSD, a Bayesian Markov Chain Monte Carlo approach was used to estimate probabilistic exposure-response relationships for lung function decrements associat ed with 8-hr moderate exerti on exposures using the WinBUGS software (Spiegelhalter et al., 1996). 7 The combined data set including the data from the Folinsbee et al. (1988), Horstman et al. (1990) , and McDonnell et al. (1991) studies used previously and the more recent data from Adam s (2002, 2003, 2006) have been used to estimate exposure-response relationships for 8-hr exposures under moderate exertion for each of the three measures of lung function decrement listed above . Table 5-3 presents a summary of the studyspecific results based on correc ting all individual responses fo r the effect on lung function decrements of exercise in clean air. The pr eviously used studies we re all conducted in EPA’s facility in Chapel Hill, while the Adams studies we re conducted at the University of California at

6 As noted in chapter 4, a small error was detected in the exposure model in January 2007 that resulted in small increases in the exposure estimates. The lung functio n risk estimates presented in this final Staff Paper reflect corrected exposure estimates and are generally slightly higher than the original estimates presented in the January 2007 version of the Staff Paper.

7 See Gelman et al. (1995) or Gilks et al. (1996) for an explanation of these methods.5-19Table 5-3. Study-Specific Exposure-Response Data for Lung Function DecrementsChange in FEV1>10% Change in FEV1>15% Change in FEV1>20%Study ProtocolNumberExposedNumberRespondingNumberExposedNumberRespondingNumberExposedNumberResponding0.04 ppm O3Adams (2006) Triangular 30 0 30 0 30 0Adams (2002) Square-wave,face mask 30 2 30 0 30 00.06 ppm O3Square-wave 30 2 30 0 30 0Adams (2006)Triangular 30 2 30 2 30 00.08 ppm O3Square-wave 30 7 30 2 30 1Adams (2006)Triangular 30 9 30 3 30 1Square-wave, chamber 30 6 30 2 30 1Square-wave, face mask 30 9 30 3 30 1Variable levels (0.08 ppmavg), chamber30 6 30 1 30 1Adams (2003)Variable levels (0.08 ppmavg), face mask30 5 30 3 30 0Adams (2002) Square-wave,face mask 30 6 30 5 30 2F-H-M* Square-wave 60 18 60 11 60 50.1 ppm O3F-H-M Square-wave 32 13 32 9 32 50.12 ppm O3Square-wave, chamber 30 17 30 12 30 10Adams (2002)Square-wave, face mask 30 21 30 13 30 7F-H-M Square-wave 30 15 30** 15** 30 6*F-H-M includes combined data fromFolinsbee et al. (1988), Horstman et al. (1990), andMcDonnell et al. (1991) .**This data point was sufficiently inconsistent with the other data from the F-H-M combined data set that it was considered anoutlier and was not included in theanalysis.5-20 Davis. Data from these controlled human expos ure studies were correct ed for the effect of
exercise in clean air to remove a ny systematic bias that might be present in the data attributable to an exercise effect. Generally, this correction for exercise in clean air was small relative to the
total effects measures in the O 3 -exposed cases. For the risk assessment conducted during the last O 3 NAAQS review, there were data for only 3 exposure levels (0.08, 0.10, and 0.12 ppm) 8 and a linear exposure-response relationship
was estimated for use in the risk assessment. W ith the addition of data from three more recent
Adams studies 9 that included 0.04, 0.06, and/or 0.08 pp m, 6.6 hour exposures, the combined data set appears to be more S-shaped , although there is sti ll considerable uncertainty about the overall functional form, given the limited data at expos ure levels below 0.08 ppm. Consistent with
advice from the CASAC O 3 Panel in its October 24, 2006 letter (Henderson, 2006c), EPA considered both linear and logistic functional forms in estimating the exposure-response relationship and revised this aspect of the assessment by adopting a Bayesian Markov Chain Monte Carlo approach. This Bayesian estimati on approach incorporated both model uncertainty and uncertainty due to sampling variability. We chose a 90 percent logistic/10 percent linear split as the base case for the current risk assessment based on the following considerations: 1) the prior 1997 risk assessment had used a
linear form consistent with the advice from the CASAC O 3 Panel at the time that a linear model reasonably fit the available lung function response data at 0.08, 0.10, and 0.12 ppm from three 6.6 hour exposure studies, 2) with the addition of data at 0.06 and 0. 04 ppm, a logistic model provided a very good fit to the data, and 3) as members of the current CASAC O 3 Panel have noted there is only very limited data at the two lowest exposure levels and, therefore, a linear model cannot entirely be ruled out. We have included a sensitivity analysis that examines the impact on the lung function risk estimates of two alternative choices , an 80 percent logistic/20% linear split and 50% logistic/50% linear split (see section 5.4.3.2). For each of the three measures of lung func tion decrement, we assumed for the base case a 90% probability that the exposure-response f unction has the following 3-parameter logistic
form: 10,11

8 The studies conducted in EPA’s facility in Chapel H ill that are considered in the lung function risk assessment measured O 3 concentrations to within +/- 5% or +/- 0.004 ppm at the 0.08 ppm exposure level.
9 These studies reported O 3 concentrations to be accuate within +/- 0.003 ppm over the range of concentrations included in these studies.
10 As noted in Whitfield et al., 1996, the response data point associated with 0.12 ppm for the response measure FEV 1 ≥ 15% appeared to be inconsistent with the other data points (see Whitfield et al., 1996, Table 10, footnote c). Because of this, we estimat ed the probability of a response of FEV 1 ≥ 15% at an O 3 concentration of 0.12 ppm by interpolating between the FEV 1 ≥ 10% and FEV 1 ≥ 20% response rates at that O 3 concentration.5-21 ) 1 )( 1 ( ) 1 ( * )

, , ; ( γ β γ β

γ α γ β α + + + −

= x x

e e e

e x y , (Equation 5-2)

where x denotes the O 3 concentration (in ppm) to which the individual is expos ed, y denotes the corresponding response (decrement in FEV 1 > 10%, > 15% or > 20%), and α , β , and γ are the three parameters whose values are estimated. We assumed for the base case a 10 percen t probability that the exposure-response function has the following linear (hockeystick) form:

⎩ ⎨ ⎧

< + > + +

= 0

, 0 0

, )

, ; (

x for x for x x y β α β α β α β α (Equation 5-3)

We assumed that the number of responses, S , out of N subjects exposed to a given concentration,

x , has a binomial distribution w ith response probability given by model (5-1) w ith 90 percent probability and response probability given by model (5-2) with 10 percent probability. In some of the controlled human exposure studies, subjects were exposed to a given O 3 concentration more than once – for example, using a square -wave exposure pattern in one protocol and a triangular exposure pattern in anot her protocol. However, because there were insufficient data to estimate subject-specific response probabilities, we assumed a singl e response probability (for a given definition of response) for all individuals and treated the repeated exposures for a single subject as independent exposures in the binomial distribution. For each of the two functional forms (logi stic and linear), we derived a Bayesian posterior distribution using th is binomial likelihood functi on in combination with prior distributions for each of the unknown parameters. We assumed lognormal priors with maximum
likelihood estimates of the means and variances for the parameters of the logistic function, and normal priors, similarly with maximum likelihood estimates for the means and variances, for the parameters of the linear functi on. For each of the two functional forms considered, we used 1000 iterations as the “burn-in” period followed by 9,000 iterations for the estimation. Each iteration corresponds to a set of values for the parameters of the (log istic or linear) exposureresponse function. We then combined the 9,000 sets of values from the logistic model runs with the last 1,000 sets of values from the linear m odel runs to get a single combined distribution of 10,000 sets of values reflecting the 90 percent/1 0 percent assumption stated above. As noted

11 The 3-parameter logistic function is a special case of the 4-parameter logistic, in which the function is forced to go through the origin, so that the probability of response to 0.00 ppm is 0.5-22 above, sensitivity analyses examining the im pact on lung function risk estimates of two alternative choices are pres ented in section 5.4.3.2. For any O 3 concentration, x , we could then derive the n th percentile response value, for any n, by evaluating the exposure-response function at x using each of the10,000 sets of parameter values (9,000 of which were for a lo gistic model and 1,000 of which were for a linear model). The resulting 2.5 th percentile, median (50 th percentile), and 97.5 th percentile exposureresponse functions for changes in FEV 1 > 10%, > 15% and > 20% are shown separately in Figure 5-2a, b, and c along with the res ponse data to which they were fit.
We note that the fraction of the population experiencing FEV 1 > 10, 15, and > 20% associated with 0.08 ppm O 3 exposures was generally lowe r in the three Adams studies compared to the combined data set based on the studies by Folinsbee et al. (1991), Horstmann et al. (1990), and McDonell et al. (1991). For exam ple, the fraction of the population experiencing

FEV 1 decrements > 15% associated with 0.08 ppm O 3 exposures ranged from 3.3 to16.7% in the three Adams studies compared to 18.3% in the comb ined data set from the Chapel Hill studies. The 0.08 ppm level is the only co mmon level tested in both sets of studies. This observed difference may be due to differences in sensitivit y of the subjects tested , random variability due to the relatively small number of subjects tested, and/or possibl y greater attenuation of response for subjects living in or near Davis, California (where the Ad ams studies were conducted) compared to subjects living in or near Chapel H ill, NC (where the other studies were conducted). Adams notes in his studies that they were c onducted over a 6-month period when the 0.09 ppm,
1-hr California standard was not exceeded in the area where his s ubjects resided. The difference in observed responses between thes e two sets of studies is an a dditional uncertainty that should
be considered. As noted above, the Risk Assessment TSD incl udes risk estimates for all three measures of lung function response (i.e., > 10, 15, and 20% decrements in FEV 1 ). However, we are focusing on FEV 1 decrements > 15% for all school age children and > 10% FEV 1 decrements for asthmatic school age children in this Staff Pa per, consistent with the advice from CASAC expressed in its October 24, 2006 letter (Hende rson, 2006c) that these levels of response represent indicators of adverse health effects for these populations.

5.3.1.4 Characterizing Uncertainty and Variability An important issue associated with a ny population health risk assessment is the characterization of uncertainty and variability. Uncertainty refers to the lack of knowledge regarding both the actual valu es of model input va riables (parameter uncertainty) and the physical systems or relationships (model uncertainty – e.g., the shapes of concentration-response functions). In any risk assessment, uncertain ty is, ideally, reduced to the maximum extent5-23 possible, but significant uncertain ty often remains. It can be reduced by improved measurement and improved model formulation. In addition, the degree of uncertainty can be characterized, sometimes quantitatively. For example, the st atistical uncertainty su rrounding the estimated O 3 coefficients in the exposure-response functions is reflected in the credible intervals provided for the risk estimates in this chapte r and in the Risk Assessment TSD.
As described in section 3.1.3 of the Risk Assessment TSD and section 5.3.1.3 above, we have revised the approach used in the second dr aft Staff Paper and have now used a Bayesian Markov Chain Monte Carlo approach to characterize uncertainty attributable to sampling error. Using this approach, we could derive the n th percentile response value, for any n , for any O 3 concentration, x , as described above. Because the e xposure estimates were generated at the midpoints of 0.01 ppm intervals (i.e., for 0.005 ppm, 0.015 ppm, etc), we derived 2.5 th percentile,

50 th percentile (median), and 97.5 th percentile response estimates for O 3 concentrations at these midpoint values. As illustrated in Figure 5-2a, b, and c, for each of the lung function response definitions, the 2.5 th percentile and 97.5 th percentile response estimat es comprise the lower and upper bounds of the credible interval around each point estimate (median estimate) of response. As noted above, the exposure-response relati onships shown in Figures 5-2a, b, and c are based on the assumption that the relationship betw een exposure and response has a logistic form with 90 percent probability and a linear (hockeys tick) form with 10 perc ent probability. The resulting 2.5 th percentile, median (50 th percentile), and 97.5 th percentile exposure-response
functions for decrements in FEV 1 > 10% and > 15% for the base case and two alternative exposure-response functions, based on an 80 perc ent logistic/20 percent linear split and a 50 percent logistic/50 percent linear split are show n in Figures 5-3a and b To aid comparison
between the base case and the two alternative ex posure-response functions, Figures 5-4a and b show the median exposure-response relationships in the same graph for these same two FEV 1 endpoint definitions for the base case and two al ternative exposure-response functions. Section 5.4.4 presents results from a sensitivity analysis that examines the impact of using these two alternative exposure-response re lationships on the lung function risk estimates for all and asthmatic school age children. In addition to uncertainties arising from sa mpling variability considerations, there are
other uncertainties associated with the use of the exposure-response relationships for lung function responses. For example, while we have used the combined data set for the current risk assessment, as it represents the best available da ta, we believe that the observed differences in response between the Adams studies and the Chap el Hill studies contribute to additional uncertainty about the exact shape of the exposure-response relationshi p, especially for levels at5-24 Figure 5-2. a, b, c. Probabilistic Exposure-Response Relationships for FEV 1 Decrement > 10%, > 15%, and > 20% for 8-Hour Exposures Under Moderate Exertion * a) FEV 1 Decrement > 10%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 Ozone Concentration (ppm)Probability of a Response Original Response Data 2.5th percentile curve

median curve 97.5th percentile curve

b) FEV 1 Decrement > 15%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 Ozone Concentration (ppm)Probability of a Response Original Response Data 2.5th percentile curve

median curve 97.5th percentile curve

c) FEV 1 Decrement > 20%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 Ozone Concentration (ppm)Probability of a Response Original Response Data 2.5th percentile curve

median curve 97.5th percentile curve

*Derived from Folinsbee et al., 1988; Horstman et al. 1990; McDonnell et al., 1991; Adams 2002, 2003, 2006). Each curve assumes a 90% probability that the form of the exposure-response relationship is logistic and 10% probability that the form is linear (see text above).5-25Figure 5-3a, b, c. Probabilistic Exposure-Response Relationships for FEV1Decrement >10% and >15% for 8-Hour ExposuresUnder Moderate Exertion: Comparison of 90% Logistic/10% Linear (Hockeystick) Split and 80% Logistic/20%Linear (Hockeystick) and 50% Logistic/50% Linear (Hockeystick) Splitsin Assumed Relationship BetweenExposure and Response*FEV1Decrement >10%: 90% Logistic/10% Linear0%10%20%30%40%50%60%70%80%90%100%0 0.02 0.04 0.06 0.08 0.1 0.12 0.14Ozone Concentration (ppm)

Probability of a ResponseFEV1Decrement >10%: 80% Logistic/20% Linear0%10%20%30%40%50%60%70%80%90%100%0 0.02 0.04 0.06 0.08 0.1 0.12 0.14Ozone Concentration (ppm)

Probability of a Res ponseFEV1Decrement >10%: 50% Logistic/50% Linear0%10%20%30%40%50%60%70%80%90%100%0 0.02 0.04 0.06 0.08 0.1 0.12 0.14Ozone Concentration (ppm)

Probability of a Res ponseFEV1Decrement >15%: 90% Logistic/10% Linear0%10%20%30%40%50%60%70%80%90%100%0 0.02 0.04 0.06 0.08 0.1 0.12 0.14Ozone Concentration (ppm)

Probability of a Res ponseFEV1Decrement >15%: 80% Logistic/20% Linear0%10%20%30%40%50%60%70%80%90%100%0 0.02 0.04 0.06 0.08 0.1 0.12 0.14Ozone Concentration (ppm)

Probability of a ResponseFEV1Decrement >15%: 50% Logistic/50% Linear0%10%20%30%40%50%60%70%80%90%100%0 0.02 0.04 0.06 0.08 0.1 0.12 0.14Ozone Concentration (ppm)

Probability of a Res ponse*Derived from Folinsbee et al., 1988; Horstman et al. 1990; McDonnell et al., 1991; Adams 2002, 2003, 2006.5-26 Figure 5-4. Median Exposure-Response Func tions Using Three Different Combinations of Logistic and Linear (Hockeystick) Models

Figure 5-4a. FEV 1 Decrements > 10%

0% 10% 20% 30% 40% 50% 60% 70%

0.00 0.02 0.04 0.06 0.08 0.10 0.12 0.14 Ozone Exposure (ppm)Response Rate

90% logistic - 10% linear 80% logistic - 20% linear 50% logistic - 50% linear

Figure 5-4b. FEV 1 Decrements > 15%

0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50%

0.00 0.02 0.04 0.06 0.08 0.10 0.12 0.14 Ozone Exposure (ppm)Response Rate

90% logistic - 10% linear 80% logistic - 20% linear 50% logistic - 50% linear5-27 or below 0.08 ppm. Additional uncertainties wi th respect to the estimated exposure-response relationships are brie fly summarized below. 12 These additional uncertainties include:

• Length of exposure

. The 8-hr moderate exertion risk estimates are based on a combined data set from six controlled human exposure studies conducted using 6.6-hr exposures. The use of these data to estimate responses associated with an 8-hr exposure are reasonable, in our judgment, because lung f unction response appears to level off after exposure for 4 to 6 hours. It is unlikely th at the exposure-response relationships would have been appreciably different had the st udies been conducted over an 8-hr period.

• Extrapolation of exposure-response relationships . It was necessary to estimate responses at O 3 levels below the lowest exposure levels us ed in the controlled human studies (i.e., 0.04 ppm) down to background levels.

• Reproducibility of O 3- induced responses

. The risk assessment assumed that the O 3 - induced responses for individuals are reprodu cible. This assumption is supported by the evaluation in the CD (see section AX6.4 ) which cites studies by McDonnell et al. (1985b) and Hazucha et al. (2003) as showing significant repr oducibility of response.

• Age and lung function response . As in the prior review, exposure-response relationships based on controlled human expos ure studies involving 18-35 year old subjects were used in the risk assessment to estimate responses for school age children (ages 5-18). This approach is supported by evaluation in th e CD (see section AX6.4) which cites the findings of McDonnell et al. (1985a) who reported that children 8-11 years old experienced FEV 1 responses similar to those observe d in adults 18-35 years old when both groups were exposed to concentrations of 0.12 ppm at an EVR of 35 L/min/m 2 . In addition, a number of summer camp studies of school age children exposed in outdoor environments in the northeast also showed O 3 -induced lung function changes similar to and in some cases somewhat larger than t hose observed in cont rolled human exposure studies.

• Exposure history . The risk assessment assumed that the O 3 -induced response on any given day is independe nt of previous O 3 exposures. As discussed in Chapter 3 and in the CD, O 3 -induced responses can be enhanced on th e second day of exposure or attenuated after more than 2 consecutive days of expos ure. The possible impact of recent exposure history on the risk estimates is an additional so urce of uncertainty that is not quantified in this assessment. We note that the three Ad ams studies which were conducted in Davis, California reported a smaller fraction of the subjects experiencing FEV 1 decrements > 15 and 20% associated with O 3 exposures to 0.08 ppm for 6.6 hours than the Folinsbee/Horstman/McDonnell stud ies conducted in Chapel Hill, NC at this same level and exposure period. While Adams indicat es in each of these studies that O 3 levels did not exceed the 0.09 ppm, 1-hr California standard, we do not know whether the exposures outside the chamber played any role in the differences observed between these

12 Additional uncertainties with respect to the exposu re inputs to the risk assessment are described in Chapter 4 of this Staff Paper, in the Exposure Assessment TSD, and in Langstaff (2007).5-28 two sets of studies or whether the differen ces might reflect differential sensitivity among the pools of subjects tested.

• Exposure-response relationships for a ll and asthmatic school age children . The risk assessment used the same O 3 exposure-response relationshi ps developed from data on “healthy” subjects, for all and asthmatic sc hool age children. Based on evidence from epidemiological studies, it is likely that mode rate to severe asthmatic children would experience greater lung function decrements th an other children wit hout these conditions. This would tend to lead to underestimating the lung function decrements for asthmatic children in the current risk assessment. One consideration working in the opposite direction is that the activity patterns used in the exposure analysis to estimate exposures for asthmatic children were not specific to as thmatic individuals. To the extent that asthmatic children, especially those with moderate to severe asthma, are less active or spend less time outdoors than other children of the same age, the estimates of their 8-hr exposures to O 3 under moderate exertion may be oversta ted. This factor would tend to lead to overestimates of risks for lung f unction decrements in th e asthmatic school age population.

• Interaction between O 3 and other pollutants . Because the controlled human exposure studies used in the risk assessment involved only O 3 exposures, it was assumed that estimates of O 3 -induced health responses would not be affected by the presence of other pollutants (e.g., SO 2, PM 2.5 ). Some evidence exists that other pollutants may enhance the respiratory effects associ ated with exposure to O 3 , but the evidence is not consistent across studies. Variability refers to the heterogeneity in a popula tion or variable of interest that is
inherent and cannot be reduced through further research. The cu rrent controlled human exposure studies portion of the risk assessment incorporates some of the variability in key inputs to the analysis by using location-specific inputs for th e exposure analysis (e.g., location-specific population data, air exchange rates, air quality and temperature data). Although spatial variability in these key inputs across all U.S. locations has not been fully characterized, variability across the selected locations is embe dded in the analysis by using, to the extent possible, inputs specific to each urban area. The extent to which there is variability in the exposure-response relationships for the populatio ns included in the risk assessment across different geographic areas is curre ntly unknown. Temporal variability also is more difficult to address, because the risk assessment focuses on some unspecified time in the future. To minimize the degree to which values of inputs to th e analysis may be different from the values of those inputs at that unspecified time, we have used the most current inputs available – for example, year 2002, 2003, and 2004 air quality data for the urban locations, and the most recent available population data (from the 2000 Census). However, future changes in inputs have not been predicted (e.g., futu re population levels).5-29 5.3.2 Assessment of Risk Based on Epidemiological Studies As discussed above, the current quantitativ e risk assessment based on epidemiological
studies includes risk estimates for respiratory symptoms in moderate to severe asthmatic children, respiratory-related hospi tal admissions, and total non-acciden tal and cardiorespiratory mortality associated with short-term O 3 exposures in selected urban locations in the U.S. We want to emphasize that there is considerable evidence that O 3 exposures also results in additional respiratory-related effects beyond those included in the quantitative risk assessment. These effects include, e.g., increased school absences , increased asthma-related emergency department visits, and increased medication usage in asthmatics. These additional effects are discussed in Chapter 3 and considered in the overall risk ch aracterization presented in Chapter 6. The methods used in the epidemiol ogical portion of the qua ntitative risk assessment are described
below.

5.3.2.1 General Approach The general approach used in this part of the risk asse ssment relies upon concentrationresponse functions which have been estimated in epidemiological studies evaluated in the CD. Since these studies estimate concentration-response functions using ambient air quality data from fixed-site, population-oriented monitors, the appropr iate application of these functions in a risk assessment similarly requires the use of ambient ai r quality data at fixed- site, population-oriented
monitors. In order to estimate the incidence of a particular health effect associated with recent conditions in a specific county or set of counties attributable to ambient O 3 exposures in excess of background, as well as the change in incidence of the health effect in that county or set of counties corresponding to a given change in O 3 levels resulting from just meeting the current or
alternative 8-hr O 3 standards, the following three elements are required:

• Air quality information including: (1) recent air quality data for O 3 from populationoriented monitors in the assessment location, (2) estimates of background O 3 concentrations appropriate to this location, and (3) recent concentrations adjusted to reflect patterns of air quality estimated to occur when the area just meets the specified standards. (These air qualit y inputs are discussed in more detail in section 4.5.6)

• Concentration-response function(s) which provide an estimate of the relationship between the health endpoint of interest and ambient O 3 concentrations, preferably derived in the assessment location, as use of functions estimated in other locations increases uncertainty.

• Seasonal baseline health effect s incidence rate and population . The baseline incidence rate provides an estimate of th e incidence rate in the assessment location corresponding to recent O 3 levels in that location.5-30 Figure 5-5 provides a broad schematic depicting the role of these components in this part of the risk assessment. Each of the key components (i.e., air quality information, estimated concentration-response functions , and baseline incidence and population data) is discussed below, highlighting those points at which judgments have been made. These inputs are combined to estimate health effect incidence changes associated with specified changes in O 3 levels. Although some epidemiological studies have estimated linear or logistic concentration -response functions, by far the most common form is the exponential (or log-linear) form:

x Be y β

= , (Equation 5-4)

where x is the ambient O 3 level, y is the incidence of the heal th endpoint of interest at O 3 level x , β is the coefficient of ambient O 3 concentration (describing the extent of change in y with a unit change in x ), and B is the incidence at x =0, i.e., when there is no ambient O 3 . The relationship between a specified ambient O 3 level, x 0 , for example, and the incidence of a given health endpoint associated with th at level (denoted as y 0 ) is then

0 0 x Be y β
= . (Equation 5-5) Because the log-linear form of concentrati on-response function (equation (5-4)) is by far the most common form, we use this form to illustrate the derivation of the “health impact function” used in this portion of the risk assessment. 13

If we let x 0 denote the baseline (upper) O 3 level, and x 1 denote the lower O 3 level, and y 0 and y 1 denote the corresponding inciden ces of the health effect, we can derive the following relationship between the change in x , Δ x= (x 0 - x 1 ), and the corresponding change in y , Δ y, from equation (5-4) 14 :

Δ Δ yyy y e x

=−= − −

( ) [ ]. 01 0 1 β (Equation 5-6)

Alternatively, the difference in health effect s incidence can be calcu lated indirectly using relative risk. Relative risk (RR) is a measure commonly used by epidemiologists to characterize

13 The derivations of the health impact functions from concentration-response functions for all three functional forms found in the epidemiological literature and us ed in this risk assessment – the log-linear, linear, and logistic – are given in section B.2 of Appendix B in the Risk Assessment TSD.

14 If Δ x < 0 – i.e., if Δ x = (x 1 - x 0 ) – then the relationship between Δ x and Δ y can be shown to be ] 1 [ ) ( 0 0 1 − = − = Δ Δ x e y y y y β . If Δ x < 0, Δ y will similarly be negative. However, the magnitude of Δ y will be the
same whether Δ x > 0 or Δ x < 0 – i.e., the absolute value of Δ y does not depend on which equation is used.5-31Figure 5-5. Major Components of Ozone HealthRisk Assessment Based on Epidemiological StudiesAmbient Monitoring forSelected Urban AreasAir Quality AdjustmentProceduresCurrent and AlternativeProposed StandardsChanges inDistributionof O3AirQualityRisk Estimates:•Recent AirQuality•CurrentStandard•AlternativeStandardsHealthRiskModelEstimates of City-specificBaseline Health EffectsIncidence Rates andPopulation DataHuman EpidemiologicalStudiesConcentration -ResponseRelationshipsConcentration-ResponseAir QualityModeled BackgroundConcentrationsRecent (“As Is”)Ambient O3LevelsAmbient Monitoring forSelected Urban AreasAir Quality AdjustmentProceduresCurrent and AlternativeProposed StandardsChanges inDistributionof O3AirQualityRisk Estimates:•Recent AirQuality•CurrentStandard•AlternativeStandardsHealthRiskModelEstimates of City-specificBaseline Health EffectsIncidence Rates andPopulation DataHuman EpidemiologicalStudiesConcentration -ResponseRelationshipsConcentration-ResponseAir QualityModeled BackgroundConcentrationsRecent (“As Is”)Ambient O3Levels5-32 the comparative health effects asso ciated with a particular air qua lity comparison. The risk of mortality at ambient O 3 level x 0 relative to the risk of mortality at ambient O 3 level x 1 , for example, may be characterized by the ratio of th e two mortality rates: the mortality rate among
individuals when the ambient O 3 level is x 0 and the mortality rate among (otherwise identical)
individuals when the ambient O 3 level is x 1 . This is the RR for mortality associated with the
difference between the two ambient O 3 levels, x 0 and x 1 . Given a concentration-response function of the form shown in equation (5-4 ) and a particular difference in ambient O 3 levels, Δ x, the RR associated with that difference in ambient O 3 , denoted as RR Δ x , is equal to e βΔ x . The difference in health effects incidence, Δ y, corresponding to a given difference in ambient O 3 levels, Δ x, can then be calculated based on this RR Δ x :

)] / 1 ( 1 [ ) ( 0 1 0 x RR y y y y Δ − = − = Δ (Equation 5-7)

Equations (5-6) and (5-7) are simply alternativ e ways of expressing th e relationship between a given difference in ambient O 3 levels, Δ x, and the corresponding difference in health effects incidence, Δ y. These health impact equations are th e key equations that combine air quality information, concentration-response function inform ation, and baseline h ealth effects incidence
information to estimate ambient O 3 health risk.

5.3.2.2 Air Quality Considerations As illustrated in Figure 5-5, and noted earlier, air quality information required to conduct
the O 3 risk assessment includes: (1 ) recent air quality data for O 3 from suitable monitors for each selected location, (2) estimates of background con centrations for each selected location, and (3) air quality adjustment procedures to modify the recent data to re flect changes in the distribution of hourly O 3 air quality estimated to occur wh en an area just meets a given O 3 standard. The approach used to adjust air quality data to simu late just meeting alternative 8-hr standards is discussed in more detail in Chap ter 4 and in Rizzo (2005, 2006).
We retrieved O 3 ambient air quality data for th e years 2002 through 2004 from EPA’s Air Quality System (AQS). Although the O 3 season varies somewhat fo r different regions of the country, for much of the country the season co incides with spring and summer. To allow comparison across locations, and because O 3 effects observed in epidemiological studies have been more clearly and consisten tly shown for warm season analyses , all analyses for this portion
of the risk assessment were carried out for th e same time period, April through September.
Because O 3 concentrations varied su bstantially over the 3-year period from 2002 through 2004, separate analyses were carried out usi ng air quality data from 2002, in which O 3 concentrations were relatively higher in most locations over this 3-year period , and air quality data from 2004,5-33 in which O 3 concentrations were relatively lower in mo st locations for this 3-year period. These two years provide generally upper- and lower-end cases within this 3-year period. However, two of the 12 urban areas, Houston and Lo s Angeles, had similar or higher O 3 concentrations in 2004 compared to 2002. In addition, a more limited set of analyses, focusing only on mortality in a subset of five urban areas (Atlanta, Chicago, H ouston, Los Angeles, and New York), was carried out since the second draft Staff Paper, using air quality data from 2003. To estimate the change in incidence of a hea lth effect associated with a change in O 3 concentrations from recent leve ls to background levels in an a ssessment location, two time series
of O 3 concentrations are needed for that location: (1) hourly O 3 concentrations from a recent year for the period April 1 through September 30, and (2) hourly background O 3 concentrations for the same time period. In order to be consis tent with the approach generally used in the epidemiological studies that estimated O 3 concentration-response functions, the (spatial) average
ambient O 3 concentration on each hour for which measur ed data are available is deemed most appropriate for the risk assessment. A com posite monitor data set was created for each assessment location based on averaging each hourl y value from all monitors eligible for comparison with the current standard for each hour of the day. Table 4-7 provides a summary of the design values for the 12 urban study areas. Appendix 5A.1 to this chapter provides more
detailed information on ambient O 3 concentrations for these locations. Different exposure metrics have b een used in epidemiological O 3 studies, including the 24-hr average and the daily 1-hr and 8-hr maximum. Therefore, daily changes at the composite
monitor in the O 3 exposure metric appropriate to a give n concentration-response function were calculated for use in the risk assessment (s ee Tables 5A-13 and 5A-14, Appendix 5A.1 for summary statistics for the composite monitor O 3 concentrations in the 12 urban locations for 2002, 2003, and 2004). For example, if a concentra tion-response function re lated daily mortality to daily 1-hr maximum O 3 concentrations, the daily changes in 1-hr maximum O 3 concentrations at the composite monitor were ca lculated. In the first part of the epidemiology-based risk assessment, in which risks associated with the recent levels of O 3 above background levels were estimated, this required the following steps:

• Using the monitor-specific input streams of hourly O 3 concentrations from a recent year, calculate a stream of hourly O 3 concentrations at the composite monitor. The recent O 3 concentration at the composite monitor for a given hour on a given da y is the average of the monitor-specific O 3 concentrations for that hour on that day.

• Using this stream of hourly O 3 concentrations from a recent year at the composite monitor, calculate the 1-hr maximum O 3 concentration for each day at the composite monitor.

• Using the monitor-specific inpu t streams of hourly background O 3 concentrations, calculate a stream of hourly background O 3 concentrations at the composite monitor.5-34 • Using this stream of background hourly O 3 concentrations at the composite monitor, calculate the 1-hr maximum background O 3 concentration for each day at the composite monitor.

• For each day, calculate Δ x = (the 1-hr maximum O 3 concentration for that day at the composite monitor) - (the 1-hr maximum background O 3 concentration for that day at the composite monitor). The calculations for the second part of the ep idemiology-based risk assessment, in which
risks associated with estimated O 3 levels that just meet the curre nt and potential alternative 8-hr standards above background levels , were done analogously. For this case the series of monitorspecific adjusted hourly concentrat ions were used rather than the series of monitor-specific recent monitored hourly concentrations. Simila rly, calculations for concentration-response functions that used a different exposure metric (e.g., the 8-hr daily maxi mum or 24-hr average) were done analogously, using the exposure metric appropriate to the concentration-response
function.

5.3.2.3 Concentration-Response Functions As indicated in Figure 5-5, another ke y component in the risk model based on epidemiological studies is the se t of concentration-re sponse functions which provide estimates of the relationships between each health endpoint of interest and ambient concentrations. As discussed above, the health endpoints th at have been included in the O 3 risk assessment include respiratory symptoms in moderate-to-severe asthmatic children, respiratory-related hospital admissions, and premature mortality associated w ith short-term exposures. For those health endpoints, the assessment includes all estimates of response magnitude from studies judged suitable for inclusion in this assessment, including those that did not yiel d statistically significant
results. Effect estimates that ar e not statistically significant are us ed from studies judged suitable
for inclusion in this assessment to avoid introduc ing bias into the estimat e of the magnitude of
the effect. Table 5-4 summarizes the studies include d in this part of the risk assessment for each
of the urban locations. Studies often report more than one estimat ed concentration-res ponse function for the same location and health endpoint. Sometimes models including di fferent sets of co-pollutants are estimated in a study; sometimes different lags are estimated. In some cases, two or more
studies estimated a concentr ation-response function for O 3 and the same health endpoint in the same location (this is the case, for example, with O 3 and mortality associated with short-term exposures). For some health endpoints, there are studies that estimated mu lti-city and single-city
O 3 concentration-response functi ons, while other studies estimated only single-city functions.5-35 All else being equal, a co ncentration-response function estimated in the assessment location is preferable to a function estimated else where, since it avoids uncertainties related to potential differences due to geograp hic location. That is why the ur ban areas selected this part of
the O 3 risk assessment are, generally, those locati ons in which concentration-response functions have been estimated. There are several advantages, however, to using estimates from multi-city
studies versus studies carried ou t in single cities. These advantages include, but are not limited to: (1) more precise effect estimates due to la rger data sets, reducing the uncertainty around the estimated coefficient, (2) greater consistency in data handling and mode l specification that can eliminate city- to-city variation due to study desi gn, and (3) less likelihood of publication bias or exclusion of reporting of negative or nonsignificant findi ngs. Multi-city studies are applicable to a variety of settings, since they estimate a cen tral tendency across multiple locations. Because single-city and multi-city studies have different advantages, where both are available for a given location, risk estimates have b een developed for both functions.
As discussed in the CD and secti on 3.3.2.1 of this Staff Paper, O 3 epidemiological studies have reported relationships based on single pollutant models and/or multi-pollutant models (i.e., where PM, NO 2 , SO 2 , or CO were entered into the health effects model along with O 3 . To the extent that any of the co-pollutants present in th e ambient air may have co ntributed to the health
effects attributed to O 3 in single pollutant models, risks attributed to O 3 might be overestimated where concentration-response functions are based on single pollutant models. However, if copollutants are highly correlated with O 3 , their inclusion in an O 3 health effects model can lead to misleading conclusions in identifying a specific causal pollutant. When collinearity exists, inclusion of multiple pollutants in models ofte n produces unstable and statistically insignificant
effect estimates for both O 3 and the co-pollutants. Given that single and multi-pollutant models each have both potential advantages and disadvantag es, with neither type cl early preferable over the other in all cases, risk estimates based on both single- and multi-pollutant models have been
included in the risk assessment where both are available. Epidemiological studies have reported eff ect estimates associated with varying lag periods, but for the reasons discussed in the CD and summarized in section 3.4.5 above the CD focuses on effect estimates from models using 0- or 1-day lag periods, w ith some consideration of multi-day lag effects (CD, p. 7-11). For quant itative assessments, we conclude that it is appropriate to use results from lag period analys es consistent with those reported in the CD, focusing on single day lag periods of 0-1 days for associations with mortality or respiratory hospitalization, depending on availa bility of results (CD, p. 8-59). If the effect of O 3 on health outcomes persists over several days, distributed lag model results can provide more accurate effect estimates for quantitative assessment than an effect estimate for a single lag period (CD, p. 7-10). Therefore, we have used distributed lag models when th ey are available. Where only5-36 Table 5-4. Locations, Health Endpoints, a nd Epidemiological Studies Included in the O 3 Risk Assessment*

Urban Area Premature Mortality Hospital Admissions for Respiratory Illnesses Respiratory Symptoms in Asthmatic Children

Atlanta Bell et al. (2004) Bell et al. (2004) – 95 cities Huang et al. (2004)** Huang et al. (2004) – 19 cities** Boston Bell et al. (2004) – 95 cities Gent et al. (2003) Chicago Bell et al. (2004) – 95 cities Huang et al. (2004)** Huang et al. (2004) – 19 cities** Schwartz (2004) Schwartz (2004) – 14 cities Cleveland Bell et al. (2004) Bell et al. (2004) – 95 cities Huang et al. (2004)** Huang et al. (2004) – 19 cities** Schwartz et al. (1996)

Detroit Bell et al. (2004) Bell et al. (2004) – 95 cities Huang et al. (2004)** Huang et al. (2004) – 19 cities** Schwartz (2004) Schwartz (2004) – 14 cities Ito (2003) Ito (2003)

Houston Bell et al. (2004) Bell et al. (2004) – 95 cities Huang et al. (2004)** Huang et al. (2004) – 19 cities** Schwartz (2004) Schwartz (2004) – 14 cities Los Angeles Bell et al. (2004) Bell et al. (2004) – 95 cities Huang et al. (2004)** Huang et al. (2004) – 19 cities** Linn et al. (2000)

New York Bell et al. (2004) – 95 cities Huang et al. (2004)** Huang et al. (2004) – 19 cities** Thurston et al. (1992)

Philadelphia Bell et al. (2004) – 95 cities Huang et al. (2004) ** Huang et al. (2004) – 19 cities** Moolgavkar et al. (1995) Sacramento Bell et al. (2004) Bell et al. (2004) – 95 cities St. Louis Bell et al. (2004) Bell et al. (2004) – 95 cities Washington, D.C. Bell et al. (2004) – 95 cities *Where a study indicates “14 cities,” “19 cities,” or “95 cities,” a multi-city concentration-response function was used in the risk assessment and the assessment location was one of the cities included in the original epidemiological study. **This study estimated concentration-response functions for cardiorespiratory mortality.5-37 single day lags are available we have focuse d on single day lag periods of 0-1 days for associations with mortality or respiratory hospitalization, depe nding on availability of effect estimates (CD, p. 8-59). In summary:

• if a single-city concentra tion-response function was estimated in a risk assessment location and a multi-city function which include s that location was also available for the same health endpoint, both functions were included for that location in the risk assessment;

• risk estimates based on both single- and multi-pollutant models were used when both were available;

• distributed lag models were used, when avai lable; when a study re ported several single lag models for a health effect, the initial sel ection of the appropriate lag structure for the health effect was based on the overall assessment in the CD, considering all studies reporting concentration-response func tions for that health effect. The locations, health endpoints, studies, and concentration-response f unctions included in that portion of the risk assessm ent based on epidemiological studi es are summarized in Tables 5B-1 through 5B-12 in Appendix 5B.1.

5.3.2.4 Baseline Health Effects Incide nce and Population Estimates As illustrated in Equation 5-4, the most common health risk model based on epidemiological studies expresses the reduction in health risk ( ) y) associated with a given

reduction in O 3 concentrations ( ) x) as a percentage of the baseline incidence (y). To accurately assess the impact of changes in O 3 air quality on health risk in the selected urban areas,
information on the baseline incidence of health ef fects in each location is therefore needed. For this assessment, baseline inci dence is the incidence under r ecent air quality conditions. Population sizes, for both total population and various age ranges used in the risk assessment were obtained for the year 2000 (U.S. Census) and are summarized in Table 5-5. Where possible, county-specific inciden ce or incidence rates have been used in the assessment. County specific mortality incidences were available for the year 2002 from CDC Wonder (CDC, 2005), an interface for public health da ta dissemination provided by the Centers for Disease Control (CDC). The baseline mortality rates for each ri sk assessment location are provided in Table 5-6 and are expressed as a ra te per 100,000 population. County-specific rates for respiratory hospita l discharges, and various subcategories (e.g., asthma, pneumonia) have been obtained, where possibl e, from state, local, and regional health5-38Table 5-5. Relevant Population Sizes for O3Risk Assessment Locations*Population (in millions)*CityCountiesTotalAges$30Ages$65Children, Ages≤12, withasthma**AtlantaFulton, DeKalb 1.5 --- --- ---BostonSuffolk 0.7 --- ---BostonEssex, Middlesex, Norfolk, Suffolk, Worcester --- --- --- 0.025ChicagoCook 5.4 --- --- ---ClevelandCuyahoga 1.4 --- 0.2DetroitWayne 2.1 --- --- ---HoustonHarris 3.4 --- --- ---Los AngelesLos Angeles 9.5 --- --- ---Los AngelesLos Angeles, Riverside, San Bernardino, Orange --- 8.4 --- ---New YorkBronx, Kings, Queens, New York, Richmond,Westchester8.9 --- --- ---New YorkBronx, Kings, Queens, New York, Richmond 8.0 --- --- ---PhiladelphiaPhiladelphia 1.5 --- --- ---SacramentoSacramento 1.2 --- --- ---St. LouisSt. Louis City 0.3 --- --- ---Washington, D.C.Washington, D.C. 0.6 --- --- ---*Total population and age-specific population estimates taken from the 2000 U.S. Census. Populations are rounded to the nearest0.1 million. The urban areasgiven in this table are those considered in the studies used inthe risk assessment, with the exception of the larger Boston area, which is the CSA for Boston (sincethe study that estimated a concentration-response function in moderate and severe asthmatic children (ages 0 – 12) was conducted in Springfield, MA and CT).** Population derived as follows: The populations of children<5 and 5 - 12 in the counties listed were multiplied by corresponding percents of children [in eachage group] in New England with “current asthma” -- 5.1% and 10.7% for the two age groups, respectively (see "The Burden of Asthma in New England."Asthma Regional Council. March 2006. Table S-2.www.asthmaregionalcouncil.org). These estimated numbers of asthmatic children were then multiplied bythe estimated percent of asthmatic children using maintenance medications (40%) (obtained via email 4-05-06 from Jeanne Moorman, CDC) and the results weresummed.5-39Table 5-6. Baseline Mortality Rates (per 100,000 Population) Used in the O3Risk Assessment*Type of Mortality(ICD-9 Codes)City CountiesNon-accidental(<800)Cardiorespiratory(390-448; 490-496;487; 480-486; 507)Respiratory(460-519)AtlantaFulton, DeKalb 623 131 ---BostonSuffolk 736 --- ---ChicagoCook 781 189 ---ClevelandCuyahoga 1,058 268 ---DetroitWayne 913 234 76HoustonHarris 533 123 ---Los AngelesLos Angeles 569 155 ---New YorkBronx, Kings, Queens, NewYork, Richmond, Westchester704 199 ---PhiladelphiaPhiladelphia 1,057 242 ---SacramentoSacramento 686 --- ---St. LouisSt. Louis City 1147 --- ---Washington, D.C.Washington, D.C. 942 --- ---National--- 790 196 80*Data for the year 2002 from United States Department of Health and Human Services (US DHHS), Centers for Disease Control and Prevention (CDC),National Center for Health Statistics (NCHS), Compressed MortalityFile (CMF) compiled from CMF 1968-1988, Series 20, No. 2A 2000, CMF 1989-1998, Series 20, No. 2E 2003 and CMF 1999-2002, Series 20, No. 2H 2004 on CDC WONDER On-line Database. Seehttp://wonder.cdc.gov/.5-40 departments and hospital planni ng commissions for each of the risk assessment locations. 15 Baseline hospitalization rates used in each risk assessment location are summarized in Table 5-7 and are expressed as a rate per 100,000 relevant population. Baseline rates of symptoms among asthmatic children who used maintenance
medications in the Boston area were estimated by using the median rates of the respiratory symptoms reported in Table 3 of Gent et al. (200 3). Each symptom rate, the percentage of days on which the symptom occurred, wa s calculated for each subject by dividing the number of days of the symptom by the number of days of partic ipation in the study and then multiplying by 100. Median symptom rates among maintenance medi cation users for wheeze, chest tightness, and shortness of breath were 2.8%, 1.2%, and 1.5% of days, respectively.

5.3.2.5 Characterizing Uncertainty and Variability Section 5.3.1.4 previously defined what is meant by uncertainty and variability in the
context of this risk assessment . For the portion of the risk assessment based on epidemiological studies, the statistical uncerta inty surrounding the estimated O .3 coefficients in the reported concentration-response functions is reflected in the confidence or credible intervals provided for the risk estimates in this chapter and in the Ri sk Assessment TSD. Additional uncertainties have been addressed quantitatively thr ough sensitivity analyses and/or have been discussed throughout
section 5.3. With respect to variability within this portion of the risk assessment, there may be variability among concentrati on-response functions describi ng the relation between O 3 and mortality across urban areas. This variability ma y be due to differences in population (e.g., age distribution), population activities that aff ect exposure to O 3 (e.g., use of air conditioning), levels and composition of co-pollutants, and/or ot her factors that vary across urban areas. The current risk assessment incorporates some of the variability in key inputs to the analysis by using location-specific inputs (e.g ., location-specific c oncentration-response functions, baseline incidence rates, and air qual ity data). Although spatial variability in these key inputs across all U.S. locations has not been fully characterized, variability across the
selected locations is imbedded in the analysis by using, to the exte nt possible, inputs specific to each urban area. Temporal variability is more di fficult to address, because the risk assessment

15 The data were annual hospital discharge data, which were used as a proxy for hospital admissions. Hospital discharges are issued to all people who are admitted to the hospital, including those who die in the hospital. Use of the annual or seasonal discharge rate is based on the assumption that the admissions at the end of the year (or season) that carry over to the beginning of the next year (or season), and are therefore not included in the discharge data, are offset by the admissions in the previous year (or season) that carry over to the beginning of the current year (or season).5-41 Table 5-7. Baseline Rates for Hospital Admissions Used in the O 3 Risk Assessment

Rate per 100,000 Relevant Population*

Los Angeles 1 New

York 2 Detroit 3 Cleveland 4 Relevant Population

Ages 30+ All Ages Ages
65+ Ages 65+

Admissions for: Pulmonary illness (DRG Codes 75 – 101) – spring 208 --- --- ---

Pulmonary illness (DRG Codes 75 – 101) –

summer 174 --- --- ---

Respiratory illness (ICD codes 466, 480- 486, 490, 491, 492, 493) --- 800 --- ---

Asthma (ICD code 493) --- 327 --- --- Pneumonia (ICD codes 480-486) --- --- 2,068 --- Respiratory illness ((ICD codes 460-519) --- --- --- 3,632

1 Rates of unscheduled hospital admissions were calculated from patient discharge data for 1999, obtained from California’s Office of Statewide Health Planning and Development, which also provided records of hospital admissions for the study by Linn et al. (2000).

2 Rates of unscheduled hospital admissions were calculated from patient discharge data for 2001, obtained from the New York Statewide Planning and Research Cooperative.
3 Rates were calculated from hospitalization data for Wayne County for the year 2000, obtained from the Michigan Health and Hospital Association in April 2002. EPA expr essly understands that the Michigan Health and Hospital Association has not performed an analysis of the hospitalization data obtained or warranted the accuracy of this information and, therefore, it cannot be held responsible in any manner for the outcome.

4 Based on mean daily hospital admissions for ages 65+ for ICD-9 codes 460-519 -- Table 1 in Schwartz et al. (1996).5-42 focuses on some unspecified time in the future. To minimize the degree to which values of inputs to the analysis may be different from the values of those inputs atthat unspecified time, we have used recent input data – for example, years 2002 through 2004 air quality data for all of the urban locations, and recent mortality ba seline incidence rates (from 2002). However, future changes in inputs have not been predic ted (e.g., future population levels or possible changes in baseline incidence rates). A number of important sources of uncertain ty were addressed where possible. Section
4.1.9 in the Risk Assessment TSD discusses in greater detail the uncertainties and variability present in the health risk assessment. The follo wing is a brief discussion of the major sources of uncertainty and variability in the epidemiological portion of the risk assessment and how they are
dealt with or considered in the risk assessment:

• Causality . There is uncertainty about whether each of the estimated associations between O 3 indicators and the various health endpoints included in this risk assessment actually reflect a causal relationship. Our judgment, drawing on the c onclusions in the CD and as discussed in more detail in Ch apter 3 (section 3.7.5), is that for the health effects included in the risk assessment (i.e, increased resp iratory symptoms in moderate to severe asthmatic children, increased respiratory-re lated hospital admissions , total non-accidental mortality, and cardiorespiratory mortality) there is, at a minimum, a likely causal relationship with either short-term O 3 exposure itself or with O 3 serving as an indicator for itself and other components of the photoche mical oxidant mix, especially during the warm O 3 season.

• Empirically estimated concen tration-response relationships . In estimating the concentration-response relationships, there ar e uncertainties: (1) su rrounding estimates of O 3 coefficients in concentration-response functions used in the assessment, (2) concerning the specification of the concentra tion-response model (including the shape of the relationship) and whether or not a popul ation threshold or non-linear relationship exists within the range of concentrations examin ed in the studies , (3) related to the extent to which concentration-response relationships derived from studies in a given location and time when O 3 levels were higher or behavior and/or housing conditions were different provide accurate representations of th e relationships for the same locations with lower air quality distributions and different behavior and/or hous ing conditions, and (4) concerning the possible role of co-pollutant s which also may have varied between the time of the studies and the current assessment period. The approach taken to characterize uncertainties in the concentration-response functions arising from sample size considerations is discussed below. With re spect to the shape of the function and whether or not a population threshold may exist, as disc ussed in Chapter 3, the CD states that in those studies that provide suggestive evidence of thresholds, the potential thresholds are at low concentrations at or approaching background levels (CD, p. 7-159). As discussed in Chapter 3 and in the CD (CD, p.7-175), re sults from recent large U.S. multi-city timeseries studies and meta-analyses also show effect estimates that are consistent across studies and robust to contro l for potential confounders.5-43 • Adequacy of ambient O 3 monitors as surrogate for population exposure . The extent to which there are differences in the relationship between spat ial variation in ambient O 3 concentrations and ambient exposures in the original epidemiology studies compared to more recent ambient O 3 data introduces additional uncertain ty in the risk estimates. We recognize that ambient concentrations at central monitors may not provide a good representation of personal e xposures. The CD identifies the following three components to exposure measurement error: (1) the use of average population rath er than individual exposure data; (2) the difference between average personal ambient exposure and ambient concentrations at central monitoring sites; and (3) the difference between true and measured ambient concentrations (CD, p. 7-7). The CD notes that “these components are expected to have different e ffects, with the first and third likely not causing bias in a particular direction (“nondifferen tial error”) but incr easing the standard error, while the second component may result in downward bias, or attenuation of the risk estimate” (CD, pp. 7-7 to 7-8). While a concentration -response function may understate the effect of personal exposures to O 3 on the incidence of a health effect, it will give an unbiased estimate of the effect of ambient concentrations on the incidence of the health effect if the ambi ent concentrations at monitori ng stations provide an unbiased estimate of the ambient concentrations to which the population is exposed. A more comprehensive discussion of exposure measurem ent is given in section 3.4.2.1 of this Staff Paper.

• Adjustment of air quality distributions to simulate just meeting the current standard . The shape of the distribution of hourly O 3 concentrations that would result upon just meeting the current or alternative 8-hr standards is unknown. Based on an analysis of historical data, we believe that the Quadratic air qual ity adjustment procedure provides reasonable estimates of the shape of the distribution; how ever, there is greater uncertainty for those urban areas that have air quality well above the current standard (e.g., Los Angeles, Houston). As noted previously, there is c onsiderable year-to-year variability in O 3 concentrations over a three-year period in ma ny of the urban areas ex amined. This leads to substantial year-to-year variability in risk estimates associated with O 3 concentrations when air quality is simulated to just meet the current and potential alternative standards.

• Estimated background concentrations for each location . The calculation of risk associated with recent air quality in excess of background requires as an input estimates of background concentrations for each locati on throughout the period of the assessment. The estimated background concentrations for each location have been estimated based on runs of the GEOS-CHEM global model (see se ction 2.7) for all hou rs of an “average day” in a given month, for each of the months from April through September. As discussed in section 2.7, evaluation of th e GEOS-CHEM suggests that the model is generally within 5 ppb in most regions of the country and that it may be 10 ppb too high in the southeast. Section 5.4.3 presents results from a sensitivity analysis that characterizes the impact of the uncertainty about background concen trations on the nonaccidental mortality risk estimates associated with recent air quality and just meeting the current and several alternative 8-hr standards.

• Baseline incidence rates and population data . There are uncertainties related to: (1) the extent to which baseline incidence rates, age distributions, and other relevant demographic variables that impact the risk es timates vary for the year(s) when the actual5-44 epidemiological studies were conducted, the r ecent year of air quality used in this assessment, and some unspecified future year wh en air quality is adjusted to simulate just meeting the current or alternative standa rds and (2) the use of annual or seasonal incidence rate data to develop daily health e ffects incidence data. Spatial variability in baseline incidence and population data is take n into account by use of city-specific data in most cases.

One of the most critical elements in the risk assessment is the concentration-response relationships used in the assessment. The uncerta inty resulting from the statistical uncertainty
associated with the estimate of the O 3 coefficient in the concentration-response function was characterized either by confid ence intervals or by Bayesian credible intervals around the corresponding point estimates of risk. Confidence and credible intervals express the range
within which the true risk is likely to fall if the only uncertainty surrounding the O 3 coefficient involved sampling error. Other unc ertainties, such as differences in study location, time period,
and model uncertainties are not re presented by the confidence or credible intervals presented. Two large scale multi-city mortality studies, Bell et al. (2004) a nd Huang et al. (2004), reported both multi-location and single-locati on concentration-response functions, using a Bayesian two-stage hierarchical model. In these cases, the single-location estimates can be adjusted to make more efficient use of the da ta from all locations. The resulting “shrinkage”
estimates are so called because th ey “shrink” the location-specif ic estimates towards the overall mean estimate (the mean of the posterior di stribution of the multi-location concentrationresponse function coefficient). The greater the uncertainty about the es timate of the locationspecific coefficient relative to the estimate of between-study heterogeneity, the more the location-specific estimate is “p ulled in” towards the overall mean estimate. Bell et al. (2004) calculated these shrinkage estimates, which were presented in Figure 2 of that paper. These location-specific shrinkage estimates, and their adjusted standard errors were provided by the study authors and were used in the risk assessment. The location-specific estimates reported in Table 1 of Huang et al. (2004) are not “shrinkage” estimates. However, the study auth ors provided the posterior distribution for the heterogeneity parameter, τ , for their distributed lag model, show n in Figure 4(b) of their paper. Given this posterior distribution, and the original location-specific estimates presented in Table 1 of their paper, we calculated location-specific “shrinkage” esti mates using a Bayesian method described in DuMouchel (1994) (see section 5B.3 in Appendix 5B of this Staff Paper). As with the shrinkage estimates presented in Bell et al. (2004), the resulting Bayesian shrinkage estimates
use the data from all of the loca tions considered in the study more efficiently than do the original location-specific estimates. The calculation of these shrinkage estimates is thus one way to address the relatively large uncer tainty surrounding estim ates of coefficients in location-specific concentration-response functions.5-45 With respect to model form, most of the epidemiological studies estimated O 3 coefficients using log-linear models. However, there still is substantial uncertainty about the correct functional form of the relationship between O 3 and various health endpoint s, especially at the low end of the range of observed concentrations. Wh ile there are likely biol ogical thresholds in individuals for specific health re sponses, as discussed in secti on 3.4.6 available studies have found little evidence for population thresholds. For example, in a recent study, Bell et al. (2006), applied several statistical models to data on air pollution, weather, and mortality for the 98
NMMAPS communities to evaluate whether a thres hold level exists for premature mortality. The results suggested that even low levels of tropospheric O 3 , well below 0.08 ppm, are associated with premature mortality. However, as discussed in section 3.4.6 and in the CD, the
use of ambient O 3 concentrations may obscure the presen ce of thresholds in epidemiological studies (CD p. 7-158). In thos e studies that provide suggestive evidence of thresholds, the potential thresholds are at low concentrations at or approachi ng background levels (CD, p. 7- 159).
The CD finds that no definitive conclusion can be reached with regard to the existence of thresholds in epidemiological studies (CD, p. 8- 44). We recognize, however , the possibility that thresholds for individuals may exis t for reported associations at fair ly low levels within the range of air quality observed in the studies, but not be detectable as popul ation thresholds in epidemiological analyses. Based on the CD’s c onclusions, we judge that there is insufficient evidence to support use of potential threshold levels in the quantita tive risk assessment, but we do recognize there is increasing uncertainty about the concentrat ion-response relationship at
lower concentrations that is not captured by the characterization of the statistical uncertainty due to sampling error. Therefore, as discussed later in this chapter, the risk estimates for premature mortality, respiratory symptoms in moderate to severe asthmatic children, and respiratory-related hospital admissions associat ed with exposure to O 3 must be considered in the light of
uncertainties about whether or not these O 3 -related effects occur in the population at very low
concentrations. Several recent meta-analyses (Bell et al . 2005; Levy et al., 2005; and Ito et al., 2005) have addressed the impact of various factors on es timates of mortality associated with short-term exposures to O 3 . We reviewed these meta-analyses for a dditional information that might be used to assist in characterizing the uncertainties as sociated with concentra tion-response functions for this health outcome. As discussed in Chapte r 3, the CD observes common findings across all three analyses, in that all reported that effect estimates were larger in warm season analyses, reanalysis of results using default GAM criteria did not change the effect estimates, and there was no strong evidence of confounding by PM (CD, p. 7-97). Bell et al. (2005) and Ito et al. (2005) both provided suggestive evid ence of publication bias, but O 3 -mortality associations5-46 remained after accounting for that potential bias. The results from these meta-analyses, as well as several single- and multiple-city studies, also indicate that copollutants generally do not appear to substantially conf ound the association between O 3 and mortality. As discussed in Chapter 3, while concluding that O 3 -health associations are found to be generally consistent, the recent O 3 -mortality meta-analyses indicate that some heterogeneity exists across studies (CD, pp. 7-96 – 7-97). The CD discusses a number of factors that could result in heterogeneity in associations between different geographic areas, focusing particularly
on variables that can aff ect exposure to ambient O 3 . For example, the use of air conditioning can reduce ambient exposures during the warm season , while increased outdoor activity can increase

exposure.

5.4 OZONE RISK ESTIMATES We present risk estimates associated with several air quality scenarios, including three recent years of air quality as represented by 2002, 2003, and 2004 monitoring data in section 5.4.1. In section 5.4.2 we summarize risk estimates associated with air quality adjusted to simulate just meeting the current and several potentia l alternative 8-hr standa rds. In section 5.4.3 we present and discuss the results of sensitivity analyses examining the influence of alternative estimates of background O 3 concentrations and alternative as sumptions about the shape of the exposure-response relationship fo r lung function decrements in all and asthmatic school age children. In section 5.4.4 we discuss and comp are the risk estimates developed for the current
review with the risk estima tes developed for the prior O 3 NAAQS review completed in July 1997. Finally, in section 5.4.5 we present key observations from the h ealth risk assessment. Throughout this section the un certainty surrounding risk es timates resulting from the statistical uncertainty of the O 3 coefficients in the concen tration- and exposure-response functions used is characterized by ninety-five percent confidence or cr edible intervals around estimates of incidence, incide nce per 100,000 population, and the pe rcent of total incidence that
is O 3 -related. In some cases, the lower bound of a c onfidence or credible interval falls below zero. This does not imply that additional exposure to O 3 has a beneficial eff ect, but only that the
estimated O 3 coefficient in the concentration- or e xposure-response function was not statistically significantly different from zero. Lack of st atistical significance could reflect insufficient statistical power to detect a re lationship that exists or that a relationship does not exist. Conversely, the fact that a st udy reports statistical significan t associations does not prove causation. The judgments about whether a causal relationship likel y exists between O 3 and various health endpoints rests on a variety of types of supporting evidence and involves a weight of the evidence judgment, as discussed in Chapter 3.5-47 5.4.1 Recent Air Quality In the prior 1997 risk assessment, risks for l ung function decrements a ssociated with 1-hr heavy exertion, 1-hr moderate exertion, and 8-hr moderate exertion expos ures were estimated. Since the 8-hr moderate exertion exposure scenar io for children clearly resulted in the greatest health risks in terms of lung function decrements, we have ch osen to include only the 8-hr moderate exertion exposures in th e current risk assessment for th is health endpoint. Thus, the risk estimates presented here are most useful for making relative comparisons across alternative air quality scenarios and do not represent the total risks for lung function decrements in children or other groups within the genera l population associated with any of the air quality scenarios. Thus, some outdoor workers and adults engage d in moderate exertion over multi-hour periods (e.g., 6-8 hr exposures) also woul d be expected to experience si milar lung function decrements. However, the percentage of each of these othe r subpopulations expected to experience these effects is expected to be sm aller than all school age childre n who tend to spend more hours outdoors while active based on the exposure anal yses conducted during the prior review.
We have included risk estimates for all and asthmatic school age child ren in this section. As noted previously, risk estimates for asthma tic school age children have been added to the assessment since the second draft Staff Paper. Risk estimates associated w ith recent air quality (2002 and 2004) for up to 12 urban locations are pr esented in this secti on. Additional risk estimates developed since the se cond draft Staff Paper associat ed with 2003 air quality for a subset of five locations (Atlanta, Chicago, H ouston, Los Angeles, and New York) are presented
in the Risk Assessment TSD and for all 12 ur ban areas in a recent memo (Post, 2007). Tables 5-8 and 5-9 display the risk estim ates for all school age children (ages 5-18)
associated with 2004 and 2002 O 3 concentrations for > 15% lung function decrement responses
for the 12 urban areas. Tables 5-8 and 5-9 also include risk estimates associated with air quality adjusted to simulate just meeting the current 0. 08 ppm, 8-hr standard, which will be discussed in
the next section. Consistent with CASAC’ s advice contained in its October 24, 2006 letter (Hendeson, 2006), we have focused on FEV 1 decrements > 15% for all school age children since this level of response is judged to be an indicator of adverse hea lth effects for healthy children.
Similar estimates for > 10 and > 20% decrement in lung function for all school age children can be found in Chapter 3 of the Risk Assessment TSD. All estimates in both tables reflect responses associated with exposure to O 3 in excess of exposures a ssociated with background O 3 concentrations. Table 5-8 shows the number and percent of all school ag e children estimated to have at least 1 lung functi on response (defined as FEV 1 > 15%) during the O 3 season. Table 5-9 displays the total number of o ccurrences for this same lung function response during the O 3 season. As illustrated by the estimates show n in these two tables, a child may experience multiple occurrences of a lung function response during the O 3 season. For example, in Atlanta5-48 the median estimate is that 34,000 school age children experienced an FEV 1 decrement > 15% during the O 3 season with a median estimate of about 191,000 occurrences of this same response in this population for 2004 air quality data. Th us, for this example on average each child is
estimated to have over 5 occurrences of this lung function response during the O 3 season. As shown in Table 5-8, across the 12 urban ar eas, the ranges in median estimates of the percent of all school age children estimated to expe rience at least one FEV 1 decrement > 15% during the O 3 season are 1.4 to 6.0% for 2004 and 5.3 to 9.9% for 2002. In terms of total
occurrences of FEV 1 decrement > 15% during the O 3 season, Table 5-9 show s a range of median estimates from 69,000 to nearly 1.5 million responses in 2004 and from about 145,000 to over 1.5 million responses in 2002 for all school age children across the 12 urban areas associated
with O 3 concentrations. Both Tables 5-8 and 5-9 also include 95% credible intervals for the lung function decrement risk estimates based on sample size considerations. These credible intervals only represent part of the uncertainty associ ated with these risk estimates. Additional
uncertainties are summarized in section 5.3.2.5 and should be kept in mind as one considers the
risk estimates in these tables. Comparable tables to those discussed above for lung function responses in all school age children are presented in Tables 5-10 and 5-11 for asthmatic school age children for 5 urban
areas that are a subset of the 12 urban areas included for all childre n. Again, the risk estimates associated with just meeting the current 8-hr stan dard presented in these ta bles will be discussed
in the next section. For asth matic children a lung function re sponse defined in terms of FEV 1 decrement > 10% is shown, consistent with CASAC’s advice (Henderson, 2006c) that this level of response serves as an indica tor of adverse health effects for this population. As shown in Table 5-10, across the 5 urban areas , the ranges in median estimates of the number of asthmatic school age children estimated to experience at least one FEV 1 decrement > 10% during the O 3 season are 12,000 to 62,000 for 2004 air quality and 17,000 to about 118,000 for 2002 air quality. These median ranges represent 4.9 to 13.6% of asthmatic school age children for 2004 air quality and 12.5 to 18.3% of asthmatic school age children for 2002 air quality. In terms of
total occurrences of FEV 1 decrement > 10% associated with O 3 concentrations during the O 3 season, Table 5-11 shows a range of median estimates from 109,000 to about 660,000 responses in 2004 and from about 96,000 to 834,000 response s in 2002 for asthmatic school age children
across the 5 urban areas. Dividi ng the estimated total number of occurrences by the number of asthmatic children estimated to experience this lung function response, results in each child being estimated to have on average between roug hly 5 and 10 occurrences of this lung function response during the O 3 season depending on the urban area and year of air quality analyzed.5-49Table 5-8. Number and Percent of All School Age ChildrenEstimated to Experience Lung Function Responses (FEV1>15%)Associated with 8-Hour O3Exposure While Engaged in ModerateExertion for Location-Specific O3Seasons*Number of Children (Ages 5-18) Havingat Least 1 Lung Function Response (FEV1>15%) Associated with 8-Hour O3Exposure**Recent Air Quality (2004)Just Meeting Current 8-HourStandard (based on adjusting2004 air quality)Recent Air Quality (2002)Just Meeting Current 8-HourStandard (based on adjusting2002 air quality)Location(O3Season)Number(1000s)PercentNumber(1000s)PercentNumber(1000s)PercentNumber(1000s)Percent34 3.6% 20 2.2% 59 6.3% 36 3.8%Atlanta(19 - 51) (2% - 5.4%) (8 - 34) (0.9% - 3.6%) (40 - 81) (4.2% - 8.6%) (21 - 54) (2.2% - 5.7%)26 2.4% 15 1.4% 84 7.6% 52 4.7%Boston(12 - 42) (1.1% - 3.8%) (4 - 27) (0.4% - 2.5%) (58 - 112) (5.3% - 10.3%) (33 - 74) (3% - 6.8%)27 1.4% 15 0.8% 123 6.3% 71 3.6%Chicago(6 - 49) (0.3% - 2.5%) (1 - 31) (0% - 1.6%) (83 - 169) (4.2% - 8.7%) (41 - 106) (2.1% - 5.4%)12 2% 6 1% 56 9.4% 30 5.1%Cleveland(5 - 20) (0.8% - 3.3%) (1 - 12) (0.1% - 2%) (40 - 74) (6.7% - 12.4%) (19 - 43) (3.3% - 7.2%)20 1.8% 12 1.1% 76 6.8% 47 4.3%Detroit(7 - 35) (0.6% - 3.1%) (2 - 24) (0.2% - 2.1%) (51 - 103) (4.6% - 9.3%) (29 - 69) (2.6% - 6.3%)57 5.2% 23 2.1% 58 5.3% 24 2.2%Houston(37 - 79) (3.4% - 7.3%) (10 - 37) (0.9% - 3.4%) (38 - 80) (3.5% - 7.4%) (11 - 38) (1% - 3.5%)220 6% 34 0.9% 220 6% 35 0.9%Los Angeles(149 - 298) (4.1% - 8.1%) (5 - 62) (0.1% - 1.7%)(150 - 297) (4.1% - 8.1%) (7 - 62) (0.2% - 1.7%)112 2.7% 43 1% 346 8.3% 142 3.4%New York(55 - 176) (1.3% - 4.2%) (6 - 84) (0.2% - 2%) (244 - 462) (5.9% - 11.2%) (79 - 216) (1.9% - 5.2%)38 3.2% 19 1.6% 118 9.9% 63 5.4%Philadelphia(21 - 59) (1.8% - 4.9%) (5 - 33) (0.4% - 2.8%) (85 - 155) (7.2% - 13.1%) (41 - 89) (3.5% - 7.5%)11 2.7% 4 1% 24 5.8% 10 2.3%Sacramento(6 - 17) (1.4% - 4.1%) (1 - 7) (0.2% - 1.8%) (16 - 32) (3.9% - 7.9%) (5 - 15) (1.1% - 3.5%)10 1.8% 7 1.3% 41 7.1% 30 5.2%St. Louis(3 - 18) (0.6% - 3.1%) (1 - 14) (0.2% - 2.4%) (28 - 56) (4.8% - 9.6%) (20 - 43) (3.4% - 7.4%)57 3.8% 28 1.9% 125 8.4% 68 4.6%Washington, DC(33 - 84) (2.2% - 5.6%) (10 - 48) (0.7% - 3.2%) (88 - 167) (5.9% - 11.2%) (42 - 98) (2.9% - 6.6%)*Risks are estimated for exposures inexcess of policy relevant background.**Numbers are median (0.5 fractile) numbers of children. Numbers in parentheses below the median are 95% credible intervals based on statistical uncertainty surroundingthe O3coefficient. Numbers are rounded to the nearest1000. Percents are rounded to the nearest tenth.5-50Table 5-9. Number of Occurrences of Lung Function Responses (FEV1>15%) Among All SchoolAge Children Associatedwith 8-Hour O3Exposure While Engaged in ModerateExertion for Location-Specific O3Seasons**Risks are estimated for exposures inexcess of policy relevant background.**Numbers are median (0.5 fractile) numbers of occurrences in thousands. Numbers in parentheses below the median are 95% credible intervalsbased on statistical uncertainty surrounding the O3coefficient. Numbers are rounded to the nearest 1000Occurrences of Lung Function Response (FEV1>15%) Associated with 8-Hour O3Exposure AmongChildren (Ages 5-18), in Thousands**LocationRecent Air Quality(2004)Just Meeting Current 8-Hour Standard (based onadjusting 2004 air quality)Recent Air Quality(2002)Just Meeting Current 8-Hour Standard (based onadjusting 2002 air quality)191 131 290 196Atlanta(March-October)(29 - 456) (10 - 344) (88 - 593) (39 - 442)125 86 311 210Boston(April-September)(16 - 315) (5 - 238) (115 - 611) (56 - 458)167 110 511 325Chicago(April-September)(6 - 460) (1 - 328) (171 - 1015) (68 - 727)69 43 259 153Cleveland(April-October)(6 - 179) (1 - 125) (110 - 473) (43 - 320)111 79 333 226Detroit(April-September)(8 - 296) (2 - 227) (119 - 649) (56 - 488)230 110 209 99Houston(All year)(63 - 465) (13 - 253) (62 - 419) (13 - 223)1470 371 1265 315Los Angeles(All year)(393 - 3073) (6 - 1044) (355 - 2642) (9 - 869)563 296 1522 753New York(April-September)(77 - 1383) (7 - 851) (585 - 2885) (140 - 1727)218 130 570 335Philadelphia(April-October)(35 - 509) (6 - 345) (239 - 1037) (92 - 696)86 41 145 72Sacramento(All year)(11 - 206) (1 - 114) (39 - 305) (8 - 179)69 54 183 141St. Louis(April-October)(4 - 181) (1 - 148) (65 - 356) (40 - 292)268 164 565 345Washington, DC(April-October)(50 - 622) (12 - 432) (209 - 1086) (82 - 752)5-51 The risk estimates associated with 2004 and 2002 O 3 concentrations for morbidity health endpoints based on epidemiological studies are shown in Tables 5-12 and 5-13 for respiratory symptoms in moderate to severe asthmatic chil dren for the Boston urban area and in Tables 5-14 and 5-15 for excess hospital admissions for total resp iratory illness and asthma (which is a subset of total respiratory illness admissions) for the New York City urban ar ea. Additional hospital
admission estimates for three other locations ar e provided in the Risk Assessment TSD. All results for morbidity health endpoints based on epidemiological studies are for health risks associated with short-term exposures to O 3 concentrations in excess of background levels from April through September for 2004 and 2002, respectively. As discussed previously, risk estimates were developed for several respiratory symptoms in asthmatic children ages 0 to 12 who use main tenance medications based on the concentrationresponse functions provided in Gent et al. (2003). These estimates were developed only for the
Boston urban area which was near the location of the original epidemiol ogical study. Tables 5-
12 and 5-13 show risk estimates for three different respiratory symptoms (i .e., chest tightness, shortness of breath, and wheeze) for the Boston area associated with O 3 levels above background for April through September of 2004 and 2002, respec tively. The risk estim ates are expressed in terms of cases, cases per 100,000 relevant populati on, and percent of total incidence
Tables 5-14 and 5-15 show risk estimates of unscheduled hospital admissions for respiratory illness in the New Yo rk City area associated with O 3 levels above background for April through September of 2004 and 2002, respectiv ely. The risk estimates are expressed in terms of cases, cases per 100,000 relevant popula tion, and percent of total incidence.
Tables 5-16 and 5-17 show risk estimates fo r non-accidental mortalit y associated with O 3 levels above background for April through Septem ber of 2004 and 2002, respectively. Similar tables for cardiorespiratory mortality are incl uded in the Risk Assessment TSD. The risk estimates are presented in terms of estimated incidence, incidence per 100,000 relevant population, and percent of total incidence. As discussed in section 5.3.2.5,, Bell et al. (2004) reported both multi-location and single-location concentration-respon se functions in a variety of locations, using a Bayesian twostage hierarchical model. Thus, where available, risk estimates are incl uded in Tables 5-16 and 5-17 based on both single-city and multi-city func tions. The ranges shown in these tables are based either on the 95 percent c onfidence intervals around those es timates (if the coefficients were estimated using classical statistical techni ques) or on the 95 percent credible intervals (if the coefficients were estimated using Bayesian statistical techniques).5-52Table 5-10. Number and Percent of Asthmatic School Age Children Estimated to Experience Lung Function Responses (FEV1>10%) Associated with 8-Hour O3Exposure While Engaged in ModerateExertion for Location Specific O3Seasons*Asthmatic Children (Ages 5-18) Havingat Least 1 Lung Function Response (FEV1>10%) Associated with 8-Hour O3Exposure UnderModerate Exertion**Recent Air Quality (2004)Just Meeting Current 8-HourStandard (based on adjusting2004 air quality)Recent Air Quality (2002)Just Meeting Current 8-HourStandard (based on adjusting2002 air quality)Location (O3Season)Number(1000s)PercentNumber(1000s)PercentNumber(1000s)PercentNumber(1000s)Percent12 9.9% 8 6.9% 18 15.2% 13 10.9%Atlanta(MarchOctober(9 - 17) (7.4% - 14.2%) (6 - 12) (4.8% - 10.6%) (14 - 23) (12.2% - 19.8%) (10 - 18) (8.3% - 15.3%)14 4.9% 9 3.2% 40 14.5% 27 9.8%Chicago(AprilSeptember)(9 - 22) (3.1% - 7.8%) (5 - 14) (1.8% - 5.1%) (32 - 53) (11.6% - 18.9%) (20 - 39) (7.3% - 14%)17 12.6% 9 6.7% 17 12.5% 9 6.7%Houston(All year)(14 - 23) (10% - 16.8%) (6 - 14) (4.7% - 10.1%) (13 - 23) (9.9% - 16.7%) (6 - 14) (4.8% - 10.1%)62 13.6% 16 3.5% 61 13.3% 16 3.4%Los Angeles(All year)(52 - 81) (11.4% - 17.7%) (11 - 25) (2.5% - 5.5%)(51 - 79) (11.1% - 17.2%) (11 - 24) (2.5% - 5.3%)51 8% 26 4.1% 118 18.3% 63 9.8%New York(AprilSeptember)(37 - 76) (5.8% - 11.8%) (16 - 42) (2.5% - 6.6%) (97 - 147) (15.1% - 22.9%) (47 - 91) (7.3% - 14.1%)*Risks are estimated for exposures inexcess of policy relevant background.**Numbers are median (0.5 fractile) numbers of children. Numbers in parentheses below the median are 95% credible intervals based on statistical uncertaintysurrounding the O3coefficient. Numbers are rounded to the nearest 1000. Percents are rounded to the nearest tenth.5-53Table 5-11. Number of Occurrences of Lung Function Responses (FEV1>10%) Among Asthmatic School Age ChildrenAssociated with 8-Hour O3Exposure While Engaged in ModerateExertion for Location Specific O3Seasons*Occurrences of Lung Function Response (FEV1>10%) Associated with 8-Hour O3Exposure Among Asthmatic Children(Ages 5-18) While Engaged in Moderate Exertion, in Thousands**LocationRecent Air Quality(2004)Just Meeting Current 8-HourStandard (based on adjusting2004 air quality)Recent Air Quality(2002)Just Meeting Current 8-HourStandard (based on adjusting2002 air quality)109 82 145 109Atlanta(March-October)(38 - 196) (22 - 151) (68 - 244) (44 - 190)114 80 257 186Chicago(April-October)(27 - 214) (12 - 154) (125 - 427) (75 - 324)110 61 96 52Houston(All year)(51 - 181) (22 - 103) (45 - 158) (20 - 88)660 219 561 182Los Angeles(All year)(308 - 1108) (49 - 405) (255 - 942) (42 - 335)399 240 834 509New York(April-September)(131 - 720) (46 - 458) (435 - 1356) (200 - 894)*Risks are estimated for exposures in excess of policy relevant background.**Numbers are median (0.5 fractile) numbers of occurrences. Numbers in parentheses below the median are 95% credible intervalsbased on statisticaluncertainty surrounding the O3coefficient. Numbers are rounded to the nearest 1000.5-54Table 5-12. Estimated Respiratory Symptoms Associated with Recent (April - September, 2004) O3Concentrations AboveBackground in Boston, MAHealth Effects Associated with O3Above PolicyRelevant Background Levels**Health Effects* Study Ages LagExposureMetricOtherPollutantsin ModelIncidenceIncidence per100,000 RelevantPopulationPercent of TotalIncidence0 - 12 1-day lag 1 hr max. none 5300 20700 9.4%Respiratory symptoms among asthmaticmedication-users -- chest tightnessGent et al. (2003)(800 - 9200) (3300 - 36300) (1.5% - 16.5%)0 - 12 0-day lag 1 hr max. PM2.5 8400 33100 15.1%Respiratory symptoms among asthmaticmedication-users -- chest tightnessGent et al. (2003)(3800 - 12400) (14900 - 49100) (6.8% - 22.3%)0 - 12 1-day lag 1 hr max. PM2.5 7700 30400 13.8%Respiratory symptoms among asthmaticmedication-users -- chest tightnessGent et al. (2003)(3000 - 11800) (11800 - 46800) (5.4% - 21.3%)0 - 12 1-day lag 8 hr max. none 5400 21400 9.7%Respiratory symptoms among asthmaticmedication-users -- chest tightnessGent et al. (2003)(1700 - 8700) (6900 - 34500) (3.1% - 15.7%)0 - 12 1-day lag 1 hr max. none 5700 22500 8.2%Respiratory symptoms among asthmaticmedication-users -- shortness of breathGent et al. (2003)(700 - 10200) (2700 - 40200) (1% - 14.7%)0 - 12 1-day lag 8 hr max. none 6300 24700 9%Respiratory symptoms among asthmaticmedication-users -- shortness of breathGent et al. (2003)(1200 - 10800) (4800 - 42500) (1.8% - 15.5%)0 - 12 0-day lag 1 hr max. PM2.5 15400 60800 11.9%Respiratory symptoms among asthmaticmedication-users -- wheezeGent et al. (2003)(5500 - 24200) (21800 - 95600) (4.3% - 18.7%)*Health effects are associated with short-term exposures to O3.**Incidence was quantified down to estimated policy relevant background levels. Incidences of respiratory symptom-days and respiratory symptom-days per 100,000 relevantpopulation are rounded to the nearest 100. Percents are rounded tothe nearest tenth.Note: Numbers in parentheses are 95% confidence or credibleintervals based on statistical uncertainty surrounding the O3coefficient.5-55Table 5-13. Estimated Respiratory Symptoms Associated with Recent (April - September, 2002) O3Concentrations AboveBackground in Boston, MAHealth Effects Associated with O3Above PolicyRelevant Background Levels**Health Effects* Study Ages LagExposureMetricOtherPollutantsin ModelIncidenceIncidence per100,000 RelevantPopulationPercent of TotalIncidence0 - 12 1-day lag 1 hr max. none 6900 27200 12.4%Respiratory symptoms among asthmaticmedication-users -- chest tightnessGent et al. (2003)(1100 - 11800) (4500 - 46600) (2% - 21.2%)0 - 12 0-day lag 1 hr max. PM2.5 10800 42700 19.5%Respiratory symptoms among asthmaticmedication-users -- chest tightnessGent et al. (2003)(5000 - 15700) (19700 - 62100) (9% - 28.3%)0 - 12 1-day lag 1 hr max. PM2.5 10000 39400 17.9%Respiratory symptoms among asthmaticmedication-users -- chest tightnessGent et al. (2003)(4000 - 15000) (15700 - 59400) (7.1% - 27%)0 - 12 1-day lag 8 hr max. none 7200 28400 12.9%Respiratory symptoms among asthmaticmedication-users -- chest tightnessGent et al. (2003)(2400 - 11400) (9300 - 44900) (4.2% - 20.5%)0 - 12 1-day lag 1 hr max. none 7500 29500 10.8%Respiratory symptoms among asthmaticmedication-users -- shortness of breathGent et al. (2003)(900 - 13200) (3700 - 52000) (1.3% - 19%)0 - 12 1-day lag 8 hr max. none 8300 32800 11.9%Respiratory symptoms among asthmaticmedication-users -- shortness of breathGent et al. (2003)(1700 - 14000) (6600 - 55300) (2.4% - 20.2%)0 - 12 0-day lag 1 hr max. PM2.5 20100 79200 15.5%Respiratory symptoms among asthmaticmedication-users -- wheezeGent et al. (2003)(7400 - 31000) (29000 - 122300) (5.7% - 23.9%)*Health effects are associated with short-term exposures to O3.**Incidence was quantified down to estimated policy relevant background levels. Incidences of respiratory symptom-days and respiratory symptom-days per 100,000 relevantpopulation are rounded to the nearest 100. Percents are rounded tothe nearest tenth.Note: Numbers in parentheses are 95% credible intervals based on statistical uncertainty surrounding the O3coefficient.5-56Table 5-14. Estimated Hospital Admissions Associated with Recent (April- September, 2004) O3Concentrations in NY, NY**Health Effects Associated with O3Above PolicyRelevant Background Levels*Health Effects* Study Ages LagExposureMetricOtherPollutants inModelIncidenceIncidence per100,000RelevantPopulationPercent of TotalIncidenceThurston et al. (1992)*** all 3-day lag 1 hr max. none 447 5.6 1.3%Hospital admissions(unscheduled),respiratory illness(108 - 786) (1.4 - 9.8) (0.3% - 2.2%)Thurston et al. (1992)*** all 1-day lag 1 hr max. none 382 4.8 2.9%Hospital admissions(unscheduled), asthma(81 - 683) (1 - 8.5) (0.6% - 5.2%)*Incidences are rounded to the nearest whole number; incidences per 100,000 relevant population and percents are rounded to thenearest tenth.**New York in this study is defined as the five boroughs of New York City.Note: Numbers in parentheses are 95% confidence or credibleintervals based on statistical uncertainty surrounding the O3coefficient.Table 5-15. Estimated Hospital Admissions Associated with Recent (April- September, 2002) O3Concentrations in NY, NY**Health Effects Associated with O3Above PolicyRelevant Background Levels*Health Effects Study Ages LagExposureMetricOtherPollutants inModelIncidenceIncidence per100,000RelevantPopulationPercent of TotalIncidenceThurston et al. (1992)*** all 3-day lag 1 hr max. none 608 7.6 1.7%Hospital admissions(unscheduled),respiratory illness(147 - 1068) (1.8 - 13.3) (0.4% - 3%)Thurston et al. (1992)*** all 1-day lag 1 hr max. none 519 6.5 4%Hospital admissions(unscheduled),asthma(110 - 928) (1.4 - 11.6) (0.8% - 7.1%)*Incidences are rounded to the nearest whole number; incidences per 100,000 relevant population and percents are rounded to thenearest tenth.**New York in this study is defined as the five boroughs of New York City.Note: Numbers in parentheses are 95% confidence or credibleintervals based on statistical uncertainty surrounding the O3coefficient.5-57Table 5-16. Estimated Non-Accidental Mortality Associated with Recent (April - September, 2004) O3 Concentrations*Location Study Lag Exposure MetricNon-Accidental Mortality Associated with O3Above Policy RelevantBackground Levels**IncidenceIncidence per 100,000Relevant PopulationPercent of TotalIncidencedistributed lag 24 hravg. 6 0.4 0.1%Bell et al. (2004)(-26 - 38) (-1.8 - 2.6) (-0.6% - 0.8%)distributed lag 24 hravg. 12 0.8 0.3%AtlantaBell et al. -- 95 US Cities (2004)(4 - 20) (0.3 - 1.4) (0.1% - 0.4%)distributed lag 24 hravg. 7 1.0 0.3%BostonBell et al. -- 95 US Cities (2004)(2 - 12) (0.3 - 1.7) (0.1% - 0.5%)distributed lag 24 hravg. 49 0.9 0.2%Bell et al. -- 95 US Cities (2004)(16 - 81) (0.3 - 1.5) (0.1% - 0.4%)0-day lag 1 hr max. 394 7.3 1.9%Schwartz (2004)(125 - 658) (2.3 - 12.2) (0.6% - 3.1%)0-day lag 1 hr max. 148 2.8 0.7%ChicagoSchwartz -- 14 US Cities (2004)(46 - 250) (0.9 - 4.6) (0.2% - 1.2%)distributed lag 24 hravg. 27 1.9 0.4%Bell et al. (2004)(-17 - 69) (-1.2 - 5) (-0.2% - 0.9%)distributed lag 24 hravg. 17 1.2 0.2%ClevelandBell et al. -- 95 US Cities (2004)(6 - 28) (0.4 - 2) (0.1% - 0.4%)Bell et al. (2004) distributedlag 24 hr avg. 33 1.6 0.4%(-11 - 76) (-0.5 - 3.7) (-0.1% - 0.8%)distributed lag 24 hravg. 17 0.8 0.2%Bell et al. -- 95 US Cities (2004)(6 - 28) (0.3 - 1.4) (0.1% - 0.3%)Schwartz (2004) 0-day lag1 hr max. 128 6.2 1.4%(-21 - 274) (-1 - 13.3) (-0.2% - 2.9%)0-day lag 1 hr max. 70 3.4 0.7%Schwartz -- 14 US Cities (2004)(22 - 117) (1.1 - 5.7) (0.2% - 1.2%)Ito (2003) 0-day lag 24hr avg. 40 2.0 0.4%Detroit(-37 - 116) (-1.8 - 5.6) (-0.4% - 1.2%)HoustonBell et al. (2004) distributedlag 24 hr avg. 35 1.0 0.4%5-58Location Study Lag Exposure MetricNon-Accidental Mortality Associated with O3Above Policy RelevantBackground Levels**IncidenceIncidence per 100,000Relevant PopulationPercent of TotalIncidence(2 - 67) (0.1 - 2) (0% - 0.7%)distributed lag 24 hravg. 17 0.5 0.2%Bell et al. -- 95 US Cities (2004)(6 - 28) (0.2 - 0.8) (0.1% - 0.3%)Schwartz (2004) 0-day lag 1 hr max. 93 2.7 1%(9 - 176) (0.3 - 5.2) (0.1% - 1.9%)0-day lag 1 hr max. 78 2.3 0.9%Schwartz -- 14 US Cities (2004)(24 - 130) (0.7 - 3.8) (0.3% - 1.4%)Bell et al. (2004) distributedlag 24 hr avg. 62 0.6 0.2%(-149 - 271) (-1.6 - 2.8) (-0.5% - 1%)distributed lag 24 hravg. 133 1.4 0.5%Los AngelesBell et al. -- 95 US Cities (2004)(45 - 221) (0.5 - 2.3) (0.2% - 0.8%)distributed lag 24 hravg. 60 0.7 0.2%New YorkBell et al. -- 95 US Cities (2004)(20 - 100) (0.2 - 1.1) (0.1% - 0.3%)distributed lag 24 hravg. 23 1.5 0.3%Bell et al. -- 95 US Cities (2004)(8 - 38) (0.5 - 2.5) (0.1% - 0.5%)1-day lag 24 hr avg. 82 5.4 1%PhiladelphiaMoolgavkar et al. (1995)(52 - 112) (3.4 - 7.4) (0.6% - 1.4%)Bell et al. (2004) distributedlag 24 hr avg. 12 1.0 0.3%(-36 - 59) (-3 - 4.8) (-0.9% - 1.4%)distributed lag 24 hravg. 18 1.4 0.4%SacramentoBell et al. -- 95 US Cities (2004)(6 - 29) (0.5 - 2.4) (0.1% - 0.7%)Bell et al. (2004) distributedlag 24 hr avg. 3 1.0 0.2%(-6 - 13) (-1.7 - 3.6) (-0.3% - 0.6%)distributed lag 24 hravg. 3 0.9 0.2%St LouisBell et al. -- 95 US Cities (2004)(1 - 5) (0.3 - 1.5) (0.1% - 0.3%)distributed lag 24 hravg. 8 1.5 0.3%Washington, D.C.Bell et al. -- 95 US Cities (2004)(3 - 14) (0.5 - 2.4) (0.1% - 0.5%)*All results are for mortality (among all ages) associated with short-term exposures to O3. All results are based on single-pollutant models.**Incidence was quantified down to estimated policy relevant background levels. Incidences are rounded to the nearest whole number; incidences per 100,000 relevantpopulation and percents are rounded to the nearest tenth.Note: Numbers in parentheses are 95% confidence or credibleintervals based on statistical uncertainty surrounding the O3coefficient.5-59Table 5-17. Estimated Non-Accidental Mortality Associated with Recent (April - September, 2002) O3Concentrations*Location Study Lag Exposure MetricNon-Accidental Mortality Associated with O3Above Policy RelevantBackground Levels**Incidence Incidence per 100,000Relevant PopulationPercent of TotalIncidencedistributed lag 24 hravg. 9 0.6 0.2%Bell et al. (2004)(-37 - 54) (-2.5 - 3.6) (-0.8% - 1.2%)distributed lag 24 hravg. 17 1.2 0.4%AtlantaBell et al. -- 95 US Cities (2004)(6 - 29) (0.4 - 1.9) (0.1% - 0.6%)distributed lag 24 hravg. 10 1.5 0.4%BostonBell et al. -- 95 US Cities (2004)(3 - 17) (0.5 - 2.5) (0.1% - 0.7%)distributed lag 24 hravg. 69 1.3 0.3%Bell et al. -- 95 US Cities (2004)(23 - 115) (0.4 - 2.1) (0.1% - 0.5%)0-day lag 1 hr max. 505 9.4 2.4%Schwartz (2004)(161 - 840) (3 - 15.6) (0.8% - 4%)0-day lag 1 hr max. 191 3.6 0.9%ChicagoSchwartz -- 14 US Cities (2004)(60 - 321) (1.1 - 6) (0.3% - 1.5%)distributed lag 24 hravg. 61 4.3 0.8%Bell et al. (2004)(-38 - 157) (-2.7 - 11.3) (-0.5% - 2.1%)distributed lag 24 hravg. 38 2.8 0.5%ClevelandBell et al. -- 95 US Cities (2004)(13 - 64) (0.9 - 4.6) (0.2% - 0.9%)Bell et al. (2004) distributedlag 24 hr avg. 57 2.8 0.6%(-18 - 131) (-0.9 - 6.3) (-0.2% - 1.4%)distributed lag 24 hravg. 29 1.4 0.3%Bell et al. -- 95 US Cities (2004)(10 - 48) (0.5 - 2.3) (0.1% - 0.5%)Schwartz (2004) 0-day lag1 hr max. 181 8.8 1.9%(-30 - 385) (-1.4 - 18.7) (-0.3% - 4.1%)0-day lag 1 hr max. 99 4.8 1%Schwartz -- 14 US Cities (2004)(31 - 165) (1.5 - 8) (0.3% - 1.8%)Ito (2003)0-day lag 24 hr avg. 69 3.4 0.7%Detroit(-64 - 198) (-3.1 - 9.6) (-0.7% - 2.1%)5-60Location Study Lag Exposure MetricNon-Accidental Mortality Associated with O3Above Policy RelevantBackground Levels**Incidence Incidence per 100,000Relevant PopulationPercent of TotalIncidenceBell et al. (2004) distributedlag 24 hr avg. 29 0.9 0.3%(2 - 57) (0.1 - 1.7) (0% - 0.6%)distributed lag 24 hravg. 14 0.4 0.2%Bell et al. -- 95 US Cities (2004)(5 - 24) (0.1 - 0.7) (0.1% - 0.3%)Schwartz (2004) 0-day lag1 hr max. 85 2.5 0.9%(8 - 161) (0.2 - 4.7) (0.1% - 1.8%)0-day lag 1 hr max. 71 2.1 0.8%HoustonSchwartz -- 14 US Cities (2004)(22 - 119) (0.7 - 3.5) (0.2% - 1.3%)Bell et al. (2004) distributedlag 24 hr avg. 51 0.5 0.2%(-124 - 224) (-1.3 - 2.4) (-0.5% - 0.8%)distributed lag 24 hravg. 110 1.2 0.4%Los AngelesBell et al. -- 95 US Cities (2004)(37 - 184) (0.4 - 1.9) (0.1% - 0.7%)distributed lag 24 hravg. 105 1.2 0.3%New YorkBell et al. -- 95 US Cities (2004)(35 - 174) (0.4 - 2) (0.1% - 0.6%)distributed lag 24 hravg. 37 2.4 0.5%Bell et al. -- 95 US Cities (2004)(12 - 62) (0.8 - 4.1) (0.2% - 0.8%)1-day lag 24 hr avg. 132 8.7 1.6%PhiladelphiaMoolgavkar et al. (1995)(83 - 180) (5.5 - 11.9) (1% - 2.2%)Bell et al. (2004) distributedlag 24 hr avg. 16 1.3 0.4%(-48 - 78) (-3.9 - 6.4) (-1.1% - 1.9%)distributed lag 24 hravg. 23 1.9 0.6%SacramentoBell et al. -- 95 US Cities (2004)(8 - 39) (0.6 - 3.2) (0.2% - 0.9%)Bell et al. (2004) distributedlag 24 hr avg. 6 1.9 0.3%(-11 - 23) (-3.1 - 6.7) (-0.5% - 1.2%)distributed lag 24 hravg. 6 1.7 0.3%St LouisBell et al. -- 95 US Cities (2004)(2 - 10) (0.6 - 2.8) (0.1% - 0.5%)distributed lag 24 hravg. 15 2.6 0.6%Washington, D.C.Bell et al. -- 95 US Cities (2004)(5 - 25) (0.9 - 4.4) (0.2% - 0.9%)*All results are for mortality (among all ages) associated with short-term exposures to O3. All results are based on single-pollutant models.**Incidence was quantified down to estimated policy relevant background levels. Incidences are rounded to the nearest whole number; incidences per 100,000relevant population and percents arerounded to the nearest tenth.Note: Numbers in parentheses are 95% confidence or credibleintervals based on statistical uncertainty surrounding the O3coefficient.5-61 We observe from Tables 5-16 and 5-17 that estimates of O 3 -related non-accidental mortality reported by Schwartz (2004) for Chica go, Detroit, and Houston, based on both single city and multi-city concentration-response functions, tend to be higher than other estimates for these locations. This is mainly due to the use of the 1-hr maximum O 3 concentration in Schwartz (2004), rather than the 24-hr average, as the e xposure metric. The changes from recent (2004 or 2002)) 1-hr maximum to b ackground 1-hr maximum O 3 concentrations were generally larger in the assessment locations than the correspondi ng changes from recent 24-hr average to background 24-hr average O 3 concentrations. For example, for 2004 air quality the estimated
O 3 -related (non-accidental) mortalit y in Detroit based on Bell et al . (2004), which used a 24-hr average indicator, ranged from 0.2% (based on 95 c ity model) to 0.4% of total incidence (based on single-city model). In contrast, the estimated O 3 -related (non-accidental) mortality in Detroit based on Schwartz (2004), which used a 1-hr maximum O 3 concentration as the indicator, ranged from 0.7% (based on 14 city model) to 1.4% (based on single-city model). Figures 5-6a and b show the estimated annual percent of non- accidental mortality associated with short-term exposure to O 3 concentrations within specified ranges for the warm
O 3 season (April 1 to September 30) in tw o recent years. While the current O 3 standard is expressed in terms of an 8-hr daily maximum inidicator, the large mu lticity non-accidental (Bell et al. (2004) and cardiorespirato ry (Huang et al. (2004) mortality studies reported concentrationresponse relationships for 24-hr average O 3 levels. Thus, the intervals shown in this figure are for 24-hr average concentrations. To provide some perspective on the 24-hr interv als shown, scatter plots comparing 8-hr da ily maximum concentrations at the highest monitor with the average of the 24-hr average over all monitors within an urban area were developed and are included in Appendix 5A.2. These scatter plots show that 8-hr daily maximum concentrations on average are roughly twice the observed 24-hr av erage levels, although there is considerable variability in this relationship from day-to- day within an urban area. As shown in Figure 5-6a, in 2004, all O 3 -related non-accidental mortality was associated
with O 3 concentrations less than 0.06 ppm, 24 hr aver age, and most of that was associated with
O 3 concentrations less than 0.04 ppm, 24-hr averag e. As shown in Figure 5-6b, in 2002, all O 3 - related non-accidental mortality was associated with O 3 concentrations less than 0.08 ppm, 24-hr average and the great majority was associated with O 3 concentrations less than 0.05 ppm, 24-hr average. The results for cardiorespiratory mort ality follow a similar pattern and are shown in Figure 4-15 in the Risk Assessment TSD.5-62 Figure 5-6. Estimated Annual Percent of Non-A ccidental Mortality Associated with Short- Term Exposure to Recent O 3 Concentrations Above Background for the Period April – September (Based on Be ll et al., 2004) – Total and Contribution of 24-Hour Average O 3 Ranges*

Figure 5-6a. Based on 2004 Air Quality

Figure 5-6b. Based on 2002 Air Quality

*Note that as shown in scatter plots in Appendix 5A.2, 8-hr daily maximum concentrations at the highest monitor are roughly twice the level of the average of the 24-hr average O 3 concentrations over all monitors within an urban area which are used in this figure, this ratio varies across areas. 0.00% 0.20% 0.40% 0.60% 0.80% 1.00%AtlantaBostonChicagoClevelandDetroitHoustonLosAngelesNew YorkPhiladelphiaSacramentoSt. LouisWashington,D.C.Percent of Total Incidence (and 95% CI) Attributable to 0.05 ppm<=ozone<0.06 ppm

Attributable to 0.04 ppm<=ozone<0.05 ppm

Attributable to 0.03 ppm<=ozone<0.04 ppm

Attributable to ozone < 0.03 ppm

0.00% 0.20% 0.40% 0.60% 0.80% 1.00%AtlantaBostonChicagoClevelandDetroitHoustonLosAngelesNew YorkPhiladelphiaSacramentoSt. LouisWashington,D.C.Percent of Total Incidence (and 95% CI) Attributable to 0.07 ppm<=ozone<0.08 ppm Attributable to 0.06 ppm<=ozone<0.07 ppm Attributable to 0.05 ppm<=ozone<0.06 ppm Attributable to 0.04 ppm<=ozone<0.05 ppm Attributable to 0.03 ppm<=ozone<0.04 ppm Attributable to ozone < 0.03 ppm5-63 5.4.2 Just Meeting Current and Alternative Ozone Standards As described in Chapter 4 and briefly in sec tion 5.3.2.2, the risk estimates described in this section represent the risks for two separate O 3 seasons based on adjusting the O 3 levels
observed in 2004 or 2002 to simulate O 3 levels associated with just meeting the current 0.08 ppm standard and several potential alte rnative 8-hr standards, using th e 3-year design value from the 2002-2004 time period. To facilitate comparison of risk estimates across th e urban areas, figures used in this section present summaries of th e risk estimates for the current and potential alternative 8-hr daily maximum standards. Most of the figures and tables in this section examine
the risks associated with alternative standards using the average 4th-highe st daily maximum 8-hr average form of the current standard. We present only limited results for several additional
alternative standards in this section. Risk estim ates for three additional al ternative 8-hr standards (0.084 and 0.074 ppm, using an average of the annual 3 rd -highest daily maximum 8-hr concentrations averaged over th e three year period, and 0.074 ppm using an average of the
annual 5 th -highest daily maximum 8-hr averages ove r the three year period are more fully presented in tables in the Risk Assessment TSD. Because we had to simulate the profiles of O 3 concentrations that just meet the curren t and alternative 8-hour daily maximum O 3 standards in each location, there is additio nal uncertainty surrounding estimat es of the reduced incidence
associated with O 3 concentrations that just meet these O 3 standards.
This section first discusses the risk estim ates for lung function responses in all and asthmatic school age children, which are based on exposure-response relationships derived from controlled human exposure studie s, and then risk estimates are explored for respiratory symptoms in asthmatic children, respiratory-re lated hospital admissions, and premature mortality
which are based on concentration -response relationships obtained fr om epidemiological studies The risk estimates for lung f unction responses are for the O 3 season, which is all year in 3 of the study areas (Houston, Los Angeles, and Sa cramento) and which is generally 6-7 months long in the other 9 urban study area s (e.g., March or April to September or October). The risk estimates for lung function responses in all school age children (ages 5 to 18) for just meeting the
current 8-hr standard for 12 urba n areas are summarized in Tables 5-6 and 5-7 presented in the previous section. Similarly, risk estimates for lung function responses in asthmatic school age children (ages 5 to 18) for just meeting the current 8-hr standard for 5 urban areas are summarized in Tables 5-8 and 5-9 in the previous section. Additional risk estimates for all and asthmatic school age children are presented in the Risk Assessment TSD and Post (2007), including estimates based on adju sting 2003 air quality to just meet the current and several
alternative standards.5-64 Figure 5-7 shows the median estimates of the percent of all school ag e children estimated to experience at least one FEV 1 decrement > 15% during the O 3 season across the 12 urban areas for recent air quality (2002) and upon just meet ing the current and several alternative 8-hr standards. Figure 5C-1 in Appendix 5C of th is Staff Paper shows a similar figure based on 2004 air quality data. For just meeting the current 8- hr standard the ranges of median estimates across the 12 urban areas are 0.9 - 5.4% based on adju sting 2002 air quality data and 0.8 - 2.2% based on adjusting 2004 air quality data. In terms of total oc currences of FEV 1 decrement > 15% during the O 3 season, Table 5-9 shows a range of medi an estimates from about 72,000 to over 750,000 responses during the O 3 season for all school age childr en based on adjusting 2002 air quality data to just meeting the current 8- hour standard and from about 40,000 to about 370,000 responses across the 12 urban areas associated with adjusting 2004 O 3 concentrations to just meeting the current 8-hour standard. As an illustration of the changes in the number of school age children estimated to experience FEV 1 decrements > 15% across the range of alternative standards, under the current standard the median estimates range from 10,000 to about 142,000 children per urban area across
the 12 urban areas and this woul d be reduced to a range of 1,000 to 20,000 children under the most stringent alternative standard examined (i.e., 0.064 ppm, 4th-highest daily 8-hr maximum).
Somewhat lower estimates are observed based on adjusting 2004 air quality to just meet the
current and alternative 8-hr sta ndards, with a range from 4,000 to about 43,000 children for just meeting the current standard which is reduced to a range from 1,000 to 14,000 children under the 0.064 ppm, 4th-highest daily 8-hr maximum standard. By compar ing the estimated number of
occurrences shown in Tables 5C-5 with the num ber of children estimated to experience 1 or more responses shown in Tables 5C-1, one can get an estimate of the average number of occurrences of a give n response in an O 3 season. For example, for Atlanta it is estimated that 36,000 children would have an FEV 1 decrement > 15% and that there would be 196,000 occurrences of this response in this same popul ation when 2002 air quality is adjusted to just meet the current 8-hr standard. Thus, on averag e it is estimated that there would be about 5 occurrences per O 3 season per responding child for air qu ality just meeting the current 8-hr standard in this urban area. We recognize that some children in the population might have only 1 or 2 occurrences while others likely have 6 or more occurrences per O 3 season. Figure 5-8 shows the 95% confidence interv als for the lung function risk estimates for each of the 12 urban areas using the FEV 1 decrement > 15% health response for recent O 3 levels (2002) and for 2002 air quality adjust ed to just meet the current and alternative 8-hr average n th daily maximum standards. A comparable fi gure (Figure 5C-2) usi ng 2004 air quality and adjusting 2004 air quality to just meet the curren t and alternative 8-hr st andards is included in Appendix 5C.5-65 Figures 5-9 shows the median estimates of the percent of asthmatic school age children estimated to experience at least one FEV 1 decrement > 10% during the O 3 season across the five urban areas for recent air quality (2002) and upon just meeting the current and several alternative 8-hr average 4th-highest daily ma ximum standards. Figure 5C-3 in Appendix 5C of this Staff Paper shows a similar figure based on 2004 air qual ity data. For just meeting the current 8-hr standard the ranges of median estimates acro ss the 5 urban areas are 3.2 - 6.9% based on adjusting 2004 air quality data and 3.4 – 10.9% based on adjusting 2002 air quality data. In
terms of total occurrences of FEV 1 decrement > 15% during the O 3 season, Table 5-9 shows a range of median estimates from abou t 61,000 to 240,000 responses during the O 3 season for asthmatic school age children based on adjusting 2004 air quality data to just meeting the current 8-hour standard and from about 52,000 to near ly 510,000 responses across the 5 urban areas associated with adjusting 2002 O 3 concentrations to just meeti ng the current 8-hour standard. Figure 5-10 shows the 95% confidence interval s for the lung function risk estimates for asthmatic school age children in each of the 5 urban areas using the FEV 1 decrement > 10% health response for recent O 3 levels (2002) and for 2002 air quali ty adjusted to just meet the current and alternative 8-hr average 4th-highest daily maximum standards. A comparable figure (Figure 5C-4) using 2004 air quali ty and adjusting 2004 air quality to just meet the current and
alternative 8-hr standards is included in Appendix 5C. Figure 5-11 summarizes respirat ory symptom response risk es timates associated with O 3 exposures during the April to September period for moderate/severe asthmatic children ages 0 to
12 in the Boston urban area based on the concentrati on-response relationships reported in Gent et al. (2003) for 2002 air quality and the current and alternative 8-hr standards based on adjusting 2004 air quality data. Figure 5C-5 (Appendix 5C) pres ents comparable estimates associated with 2004 air quality and just meeting the current and alternative 8-hr standards based on adjusting 2004 air quality data. These figures include risk estimates for chest tightness based on single pollutant models and models that included PM 2.5 . Two additional symptom endpoints, shortness
of breath and wheeze are included in the tables in the Risk Assessment TSD and show similar patterns as the risk estimates for chest tightness. The median estimated number of days invol ving chest tightness (u sing the concentrationresponse relationship with only O 3 in the model) ranges from 4,500 (based on adjusting 2004 air quality) to 6,100 (based on adjusting 2002 air qual ity) upon meeting the cu rrent 8-hr standard and these are reduced to 3,100 (based on adju sting 2004 air quality) to 4,600 days upon meeting the most stringent alternative examined (0.064 pp m, 4th-highest daily maximum 8-hr average). These same ranges correspond to 8 - 11% of tota l incidence of chest tightness upon meeting the5-66 Figure 5-7. Percent of All Child ren (Ages 5-18) Engaged in Moderate Exertion Estimated to Experience At Least One Lung F unction Response (Decrement in FEV 1 ≥ 15%) Associated with Exposure to O 3 Concentrations That Just Meet the Current and Alternative Average 4t h-highest Daily Maximum 8-Hour Standards, for Location-Specific O 3 Seasons (Based on Adjusting 2002 Air Quality)*

Recent (2002) 0.084/4

0.080/4

0.074/4

0.070/4

0.064/4

A t l a n t a
B o s t o n

C h i c a g o

C

l e v e l a n d
D e t r o i t

H o u s t o n

L o s An

g e l e s

N e w Yo

r k

P h i l a d e l p h i a

S a c r a m e n t o

S t

. L o u i s

W

a s h i n g t o n

, D

. C

. 0% 1% 2% 3% 4% 5% 6% 7% 8% 9% 10%Percent All Children Responding

Ozone Stds. (ppm)

Urban Areas

*An 8-hr average standard, denoted m/n is characterized by a concentration m ppm and an nth daily maximum. So for example, the current standard is 0.084/4 – 0.084 ppm, 4 th -highest daily maximum 8-hr average. The 4 th -highest daily maximum standards, denoted m/4, require that the average of the 3 annual nth-highest daily maxima over a three year period be at or below the specified level (m ppm ). 95% credible intervals based on statistical uncertainty surrounding the O 3 coefficient are presented in Table 5C-2 in Appendix 5C.5-67 Figure 5-8. Percent of All Children (A ges 5-18) Engaged in Moderate Ex ertion Estimated to Experience At Least One Lung Function Response (Decrement in FEV 1 ≥ 15 %) Associated with Recent Air Quality (2002) and Just Meeting the Current an d Alternative Average nt h Daily Maximum 8-Hour Standards, for Location-Specific O 3 Seasons (Based on Adjusting 2002 Air Quality)*

Atlanta

0% 2% 4% 6% 8% 10% 12%

R

ecent (2002) 0.084/4 0.084 / 3 0.080 / 4 0.074/5 0.074/4 0.074/3 0.

070/ 4 0.

064/ 4

Ozone Concentrations/StandardsPercent All ChildrenResponding (and 95% CI) Boston

0% 2% 4% 6% 8% 10% 12%

Recent (2002) 0.0

84

/4

0.

084/ 3 0.

080/ 4 0.

074/ 5 0.

074/ 4 0.

074

/3

0 .070/ 4 0.

064/ 4

Ozone Concentrations/StandardsPercent All ChildrenResponding (and 95% CI)

Chicago

0% 2% 4% 6% 8% 10% 12%

Recent (2002)

0

. 084/4

0 .084/ 3

0 .080/ 4

0 .074/5

0

. 074/4

0

. 074/3

0 .070/ 4

0 .064/ 4

Ozone Concentrations/StandardsPercent All ChildrenResponding (and 95% CI) Cleveland

0% 2% 4% 6% 8% 10% 12%

Recent (200 2 ) 0.

084/ 4 0.

084/ 3 0.

080/ 4 0.074/5 0.074/4 0.074/3 0.070/4 0.064 / 4

Ozone Concentrations/StandardsPercent All Children Responding(and 95% CI)

Detroit

0% 2% 4% 6% 8% 10% 12%

Recent ( 2002) 0.084/4 0.084 / 3 0.080 / 4 0.074/5 0.074/4 0.074/3 0.070/4 0.064/4

Ozone Concentrations/StandardsPercent All Children Responding(and 95% CI) Houston

0% 2% 4% 6% 8% 10% 12%

Recent (2002)

0 .0

84

/ 4 0.

0 84

/ 3 0.0

80

/4

0.0

74

/5

0.0

74

/4

0.

0 74/3 0.070/4 0.

0 64

/ 4

Ozone Concentrations/StandardsPercent All Children Responding(and 95% CI)5-68 Figure 5-8. (Continued)

Los Angeles

0% 2% 4% 6% 8% 10% 12%

R

ecent ( 2002)

0 .084/ 4

0

. 084/3

0 .080/ 4

0

. 074/5

0

. 074

/ 4 0.074/3

0 .07

0 / 4

0

. 064/4

Ozone Concentrations/StandardsPercent All Children Responding(and 95% CI) New York

0% 2% 4% 6% 8% 10% 12%

R

e cent (2002) 0.

08

4 / 4

0 .

084/3 0.080/4 0.

074/ 5 0.074/4 0.

074/ 3 0.070/4 0.

064/ 4

Ozone Concentrations/StandardsPercent All Children Responding(and 95% CI)

Philadelphia

0% 2% 4% 6% 8% 10% 12%

R

ecen t (2002) 0.084/4 0.

084/3 0.080 / 4 0.074/5 0.

074/ 4 0.074/3 0.

070/ 4 0.064/4

Ozone Concentrations/StandardsPercent All Children Responding(and 95% CI) Sacramento

0% 2% 4% 6% 8% 10% 12%

R

ecent ( 2002) 0.084/4 0.

0 84

/ 3

0.

0 80

/ 4 0.0

74

/5

0.

0 74

/ 4

0.

0 74/3

0 .0

70

/ 4 0.0

64

/4

Ozone Concentrations/StandardsPercent All Children Responding(and 95% CI)

St. Louis

0% 2% 4% 6% 8% 10% 12%

R

ecent ( 2002)

0 .084/ 4

0

. 084/3

0

. 080/4

0 .074/ 5

0

. 074

/ 4

0

. 074

/ 3

0

. 070/4

0 .06

4 / 4

Ozone Concentrations/StandardsPercent All Children Responding(and 95% CI) Washington, D.C.

0% 2% 4% 6% 8% 10% 12%

R

e cent (2002) 0.

08

4 / 4

0.084 / 3 0.

080/ 4

0.

074/ 5 0.074/4 0.

074/ 3

0.

070/ 4 0.064/4

Ozone Concentrations/StandardsPercent All Children Responding(and 95% CI)

*An 8-hr average standard, denoted m/n is characterized by a concentration of m ppm and an nth-highest daily maximum. So, for example, the current standard is 0.084/4 – 0.084 ppm, 4th-highest daily maximum 8-hr average. Percents are median (0.5 fractile) percen ts of children. The bars are 95% credible intervals based on statistical uncertainty surrounding the O 3 coefficient.5-69 Figure 5-9. Percent of Asthmatic Children (A ges 5-18) Engaged in Moderate Exertion Estimated to Experience At Least One Lung Function Response (Decrement in FEV 1 ≥ 10%) Associated with Exposure to O 3 Concentrations That Just Meet the Current and Alternative Average 4th-highest Daily Maximum 8-Hour Standards, for Location-Specific O 3 Seasons (Based on Adjusting 2002 Air Quality)

*An 8-hr average standard, denoted m/n is characterized by a concentration of m ppm and an nth-highest daily maximum. So, for example, the current standard is 0.084/4 – 0.084 ppm, 4th-highest daily maximum 8-hr average. The 4th-highest daily maximum standards, denoted m/4, require that the average of the 3 annual nth-highest daily maxima over a 3-year period be at or below the specified level. 95% credible intervals based on statistical uncertainty surrounding the O 3 coefficient are presented in Table 5C-5 in Appendix 5C. Recent (2002)

0.084/4

0.074/4

0.064/4

Atlanta Chicago Houston Los Angeles New York 0% 5% 10% 15% 20%Percent Asthmatic Children Responding

Ozone Conc./ Standards (ppm)

Urban Areas5-70 Figure 5-10. Percent of Asthmatic Children (Ag es 5-18) Engaged in Moderate Exertion Estimated to Experience At Least One Lung Function Response (Decrement in FEV 1 ≥ 10 %) Associated with Recent Air Quality (2002) and Exposure to O 3 Concentrations That Just Meet the Current and Alternative 8- Hour Standards, for Location-Specific O 3 Seasons: Based on Adjusting 2002 O 3 Concentrations*

Atlanta

0% 5% 10% 15% 20% 25%

Rece n t (2002 )

0 .084/4 0.074/4 0.064/4

Ozone Concentrations/StandardsPercent Asthmatic ChildrenResponding (and 95% CI) Chicago

0% 5% 10% 15% 20% 25%

Recent (2002) 0.0 8 4/4 0.0 7 4/4 0.0 6 4/4

Ozone Concentrations/StandardsPercent Asthmatic ChildrenResponding (and 95% CI)

Houston

0% 5% 10% 15% 20% 25%

R

e cent ( 2 00

2 )

0 . 084/4

0 . 074/4

0 . 064/4

Ozone Concentrations/StandardsPercent Asthmatic ChildrenResponding (and 95% CI) Los Angeles

0% 5% 10% 15% 20% 25%

R

ec

e n t ( 20

0 2 )

0 . 0 84/4 0.074/4 0.06 4/

4

Ozone Concentrations/StandardsPercent Asthmatic ChildrenResponding (and 95% CI)

New York

0% 5% 10% 15% 20% 25%

R

e ce

nt

(2

00

2)

0 . 0 84/

4

0 . 0 74/

4

0 . 0 64/

4

Ozone Concentrations/StandardsPercent Asthmatic ChildrenResponding (and 95% CI) * An 8-hr average standard, denoted m/n is characterized by a concentr ation of m ppm and an nth daily maximum. So, for example, the current standard is 0.084/4 – 0.084 ppm, 4 th -highest daily maximum 8-hr average. The 4 th -highest daily maximum standards, denoted m/4, require that the average of the 3 annual nth-highest daily maxima over a 3-year period be at or below the specified level (e.g., 0.084 ppm). Percents are median (0.5 fractile) percents of children. The bars are 95% credible intervals based on statistical uncertainty surroundin g the O 3 coefficient.5-71 current 8-hr standard and to a bout 5.5 - 8% of total inciden ce of chest tightness upon meeting a 0.064 ppm, 4th-highest daily maxi mum 8-hr average standard. As shown in Tables 5C-7 and 5C-9 (Appendix 5C), the symptom with the greatest incidence is wheeze and is based on an O 3 concentration-response rela tionship that included PM 2.5 in the model. These median estimates range from about 13,000 days with wheeze (based on adjusting 2004 air quality) to nearly 18,000 days (based on adjusting 2002 air quality) upon m eeting the current 8-hr standard and these estimates are reduced to 9,000 (based on adju sting 2004 air quality) to about 13,000 (based on adjusting 2002 air quality) upon meeting a 0.064 pp m, 4th-highest daily maximum 8-hr average
standard. Confidence intervals, based on statistical uncertainty reflecting sample size
considerations for incidence and percent of total incidence are s hown in Tables 5C-7 through 5C10 (Appendix 5C) based on adju sting 2004 and 2002 air quality. Figure 5-12 summarizes unscheduled hospital admission risk estimates for respiratory illness and asthma in New York City associated with short-term exposures to O 3 concentrations in excess of background levels from April thr ough September under recent air quality and when
the current and altern ative 8-hr standards are just me t based on adjusting 2004 and 2002 air quality data, respectively. For total respirator y illness, Figure 5-12 s hows about 6.4 cases per 100,000 relevant population, which represents 1. 5% of total incidence or 513 cases when 2002
O 3 levels are adjusted to just meet the current 8-hr standard. For asthma-related hospital admissions, which are a subset of total respiratory illness admissions, the estimates are about 5.5 cases per 100,000 relevant populatio n, which represents about 3.3% of total incidence or 438 cases for this same air quality scenario. Fo r increasingly more stringent alternative 8-hr standards, Figure 5-12 shows a gradual reduction in respiratory illness cases per 100,000 relevant population from 6.4 cases per 100,000 upon just mee ting the current 8-hr st andard to 4.6 cases per 100,000 under the most stringent 8-hr standard (i.e., 0.064 ppm, aver age 4th-highest daily maximum) analyzed. The comparable estimate s based on adjusting 2004 air quality are shown in Figure 5C-6 (Appendix 5C) and are somewhat hi gher, but show a simila r pattern of gradual reduction. Confidence intervals, based on st atistical uncertainty reflecting sample size considerations for incidence, incidence per 100,000 relevant popul ation, and percent of total
incidence are shown in Tables 5C-11 and 5C -12 (Appendix 5C) based on adjusting 2004 and 2002 air quality data to just meet the curre nt and potential alternative standards. Additional respiratory-related hospital admission estimates for three other locations are provided in the Risk Assessment TSD. We not e that the concentratio n-response functions for
each of these locations examined different outco mes in different age groups (e.g., > age 30 in Los Angeles, >age 64 in Cleveland and Detroi t, vs. all ages in New York City), making comparison of the risk estimates across the areas very difficult. For hospital admissions in Detroit, none of the estimates were statistica lly significant and the median estimates were5-72 Figure 5-11. Estimated Symptom-Days fo r Chest Tightness Among Moderate/Severe Asthmatic Children (Ages 0 – 12) in Bo ston Associated with Recent (AprilSeptember 2002) O 3 Levels and with Levels Just Meeting Alternative Average 4th-Highest Daily Maximum 8-Hour Ozone Standards* (Based on Gent et al., 2003)

*An 8-hr average standard, denoted m/n is characterized by a concentration of m ppm and an nth daily maximum.So, for example, the current standard is 0.084/4 – 0.084 ppm, 4th-highest daily maximum 8-hr average. The 4thhighest daily maximum standards, denoted m/4, require that the average of the 3 annual nth daily maxima over a 3- year period be at or below the specified level. 95% co nfidence intervals associated w ith these risk estimates are presented in Table 5C-9 in Appendix 5C. Recent (2002) 0.084/4 0.080/4 0.074/4 0.070/4 0.064/4

1-day lag/ 1 hr max./ no other

pollutants 0-day lag/ 1 hr max./ PM2.5 1-day lag/ 1 hr max./ PM2.5 1-day lag/ 8 hr max./ no other

pollutants 0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 9,000 10,000 11,000Estimated Symptom-Days

Ozone Stds. (ppm)

Concentration-Response Model5-73 Figure 5-12. Estimated Incidence of (Unsche duled) Respiratory Hospital Admissions per 100,000 Relevant Population in New York Associated with Recent (April – September, 2002) O 3 Levels and with O 3 Levels Just Meeting Alternative Average 4th-Highest Daily Maximum 8-Hour Standards (based on Thurston et al., 1992)

* An 8-hr average standard, denoted m/n is characterized by a concentration of m ppm and an nth daily maximum.So, for example, the current standard is 0.084/4 – 0.084 ppm, 4th-highest daily maximum 8-hr average. The 4thhighest daily maximum standards, denoted m/4, require that the average of the 3 annual nth daily maxima over a 3- year period be at or below the specified level. 95% confidence intervals associated with these risk estimates are provided in Table 5C-12 in Appendix 5C. Recent (2002) 0.084/4

0.080/4

0.074/4

0.070/4

0.064/4 Respiratory Illness Asthma 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0

Incidence per 100,000 Relevant Population

Ozone Stds. (ppm)

Diagnosis Category5-74 Figure 5-13. Estimated Incidence of No n-Accidental Mortality per 100,000 Relevant Population Associated with Recent Air Quality (2002) and with Just Meeting Alternative Average 4th-Highest Daily Maximum 8-Hour Ozone Standards (Using Bell et al., 2004 – 95 U.S. Citi es Function), Based on 2002 Ozone Concentrations

*An 8-hr average standard, denoted m/n is characterized by a concentration of m ppm and an nth daily maximum.So, for example, the current standard is 0.084/4 – 0.084 ppm, 4th-highest daily maximum 8-hr average. The 4thhighest daily maximum standards, denoted m/4, require that the average of the 3 annual nth daily maxima over a 3- year period be at or below the specified level. 95% confidence intervals associated with these risk estimates are provided in Figure 5-14. Recent (2002) 0.084/4

0.080/4

0.074/4

0.070/4

0.064/4

A t l a n t a

B o s t o n

C h i c a g o

C l e v e l a n d
D e t r o i t

H o u s t o n

L o s A

n g e l e s

N

e w Y

o r k

P h i l a d

e l p h i a

S

a c r a m e n t o

S t

. L o u i s

W

a s h i n g t o n

, D

. C

. 0 0.5 1 1.5 2 2.5 3Incidence per 100,000 Relevant Population

Ozone

Stds. (ppm)

Urban Areas5-75 negative for 0- and 1-day lags and small but posit ive for 2- and 3-day lags for COPD-related and pneumonia hospital admissions. Figure 5-13 summarizes the results of the assessment of the reduced non-accidental mortality risks associated with O 3 concentrations above background that just meet the current and several potential alternativ e 8-hr daily maximum standards across the 12 urban areas for air quality adjusted based on 2002 air quality data . This figure shows the annual median risk estimates for recent air quality and for just m eeting alternative 8-hr standards based on the O 3 coefficients estimated in the studies based on adjusting 2002 air quality data. Ranges reflecting
the statistical uncer tainty, taking into account sample size considerations, based either on the 95 percent confidence intervals around those estimates (if the coeffi cients were estimated using classical statistical techniques) or on the 95 percent credible inte rvals (if the coefficients were estimated using Bayesian statistical techniques) are presented in Tables 5C-13 through 5C-16 (Appendix 5C) and in the Risk Assessment TSD. The risk estimates in this figure are based on the 95-city function reported in Bell et al. ( 2004) for non-accidental mort ality. Additional risk estimates for cardiorespiratory mortality are incl uded in the Risk Assessment TSD for 8 of the 12 urban areas. Also, Figure 5C-7 (Appendix 5C) shows comparable risk estimates based on adjusting 2004 air quality data. Figure 5-14 shows the median estimates and 95% credible intervals for each of the 12 urban areas for non-accidental mortality based on the 95-cities concentration-response function in Bell et al. (2004) for 2002 air quality data and just meeting alternative standards based on adjusting 2002 air quality data. Figure 5C-8 (Appendix 5C) pres ents the comparable figure for 2004 air quality and just meeting a lternative standards based on ad justing 2004 air quality data. For example, Figure 5-14 shows a median risk estimate associated with just meeting the current 8-hr standard for non-accidental mortality in At lanta is around 0.9% of total incidence and the
95% credible interval is about 0. 3% to about 1.5% of total inci dence. While the 95% credible intervals get progressively smaller as one cons iders more stringent standards, as discussed previously these credible intervals do not consid er overall model uncertainty (e.g., whether or not the shape of the concentration-response rela tionship is best repres ented by a log linear relationship versus a more sigmoida l shape, particularly at lower O 3 concentration levels). The results in this portion of the risk assessment across the 12 urban areas follow the same patterns as the results discussed in secti on 5.4.1 for risks associated with recent year O 3 concentrations, because they are largely driven by the same concentration-response function
coefficient estimates and confidence or credible intervals. While there is a noticeable reduction
in the median risk estimates in some of the ur ban areas between that associated with a recent year of air quality and just meeting the current 8-hr standard, the reduc tions associated with progressively more stringent al ternative 8-hr standards are mo re modest. Based on adjusting5-76 Figure 5-14. Annual Warm Season (A pril to September) Estimated O 3 -Related Non-Accidental Mortality Associated with Recent (2002) O 3 Levels and Levels Just Meeting Alternative 8-hr O 3 Standards (Using Bell et al ., 2004 – 95 U.S. Cities Function)

Atlanta

0.0 0.6 1.2 1.8 2.4 3.0 3.6 4.2 4.8

Recent (2002) 0.084 / 4 0.

084/ 3 0.

080/ 4 0.

074/ 5 0.

074/ 4 0.

074/ 3 0.

070/4 0.064/4

Ozone Concentrations/StandardsMortality per 100,000 RelevantPopulation (and 95% CI) Boston

0.0 0.6 1.2 1.8 2.4 3.0 3.6 4.2 4.8

R

ecent ( 2002)

0 .084/ 4

0 .084/ 3

0 .080/ 4

0

. 074

/ 5

0 .074/ 4

0 .074/ 3

0 .070/ 4

0 .064/ 4

Ozone Concentrations/StandardsMortality per 100,000 RelevantPopulation (and 95% CI)

Chicago

0.0 0.6 1.2 1.8 2.4 3.0 3.6 4.2 4.8

R

ecen t (2002) 0.084/4 0.

084/ 3 0.

080/ 4 0.

074/ 5 0.

074/ 4 0.

074/ 3 0.070/4 0.064 / 4

Ozone Concentrations/StandardsMortality per 100,000 RelevantPopulation (and 95% CI) Cleveland

0.0 0.6 1.2 1.8 2.4 3.0 3.6 4.2 4.8

Recent ( 2002) 0.

084/ 4 0.

084/3

0

. 080/4 0.

074/ 5 0.

074/ 4 0.

074/ 3 0.070/4 0.064/4

Ozone Concentrations/StandardsMortality per 100,000 RelevantPopulation (and 95% CI)

Detroit

0.0 0.6 1.2 1.8 2.4 3.0 3.6 4.2 4.8

Recent (2002)

0

. 084/4 0.084/3 0.

080/ 4 0.

074/ 5 0.

074/ 4 0.074/3 0.070 / 4 0.064/4

Ozone Concentrations/StandardsMortality per 100,000 RelevantPopulation (and 95% CI) Houston

0.0 0.6 1.2 1.8 2.4 3.0 3.6 4.2 4.8

R

ecent ( 2002)

0

. 084/4

0

. 084/3

0 .080/ 4

0

. 074

/ 5

0 .074/ 4

0

. 074/3

0

. 070/4

0 .064/ 4

Ozone Concentrations/StandardsMortality per 100,000 RelevantPopulation (and 95% CI)5-77 Figure 5-14 (continued) Los Angeles

0.0 0.6 1.2 1.8 2.4 3.0 3.6 4.2 4.8

R

ecen t (2002) 0.

084/ 4 0.084/3 0.080/4 0.

074/ 5 0.074/4 0.074/3 0.

070/ 4 0.064 / 4

Ozone Concentrations/StandardsMortality per 100,000 RelevantPopulation (and 95% CI) New York

0.0 0.6 1.2 1.8 2.4 3.0 3.6 4.2 4.8

Recent ( 2002) 0.

084/ 4 0.084 / 3

0

. 080/4 0.

074/ 5 0.

074/ 4 0.074/3 0.

070/ 4 0.064/4

Ozone Concentrations/StandardsMortality per 100,000 RelevantPopulation (and 95% CI)

Philadelphia

0.0 0.6 1.2 1.8 2.4 3.0 3.6 4.2 4.8

Recent (2002)

0 .0

84

/ 4 0.0

84

/3

0.

0 80

/ 4 0.0

74

/5

0.

0 74

/ 4 0.0

74

/3

0.070/4 0.

0 64

/ 4

Ozone Concentrations/StandardsMortality per 100,000 RelevantPopulation (and 95% CI) Sacramento

0.0 0.6 1.2 1.8 2.4 3.0 3.6 4.2 4.8

R

ecent ( 2002)

0 .084/ 4

0

. 084/3

0 .080/ 4

0

. 074/5 0.074/4

0

. 074

/ 3

0

. 070/4

0 .06

4 / 4

Ozone Concentrations/StandardsMortality per 100,000 RelevantPopulation (and 95% CI)

St. Louis

0.0 0.6 1.2 1.8 2.4 3.0 3.6 4.2 4.8

R

ecen t (2002) 0.

084/ 4 0.084/3 0.

080/ 4

0.

074/ 5 0.074/4 0.

074/ 3 0.070/4 0.

064/4

Ozone Concentrations/StandardsMortality per 100,000 RelevantPopulation (and 95% CI) Washington, D.C.

0.0 0.6 1.2 1.8 2.4 3.0 3.6 4.2 4.8

Recen t ( 2002) 0.

084/ 4 0.084 / 3

0.080 / 4 0.074/5 0.

074/ 4

0.

074/ 3 0.070/4 0.

064/ 4

Ozone Concentrations/StandardsMortality per 100,000 RelevantPopulation (and 95% CI)

*An 8-hr average standard, denoted m/n is characterized by a concentration of m ppm and an nth daily maximum. So, for example, the current standard is 0.084/4 – 0.084 ppm, 4th-highest daily maximum 8-hr average. Percents are median (0.5 fractile) percents of children. The bars ar e 95% credible intervals based on statistical uncertainty surrounding the O 3 coefficient.5-78 2002 air quality data, the range of medi an estimates associated with O 3 upon just meeting the current standard is about 0.3 to 2.4 cases pe r hundred thousand releva nt population across the 12 urban areas and this range is re duced to about 0.1 to 1.7 cases per 100,000 relevant population upon just meeting the most stringent alternativ e standard analyzed (0.064 ppm, average 4thhighest daily maximum 8-hr average) We also note that the ri sk estimates expressed in terms of incidence per 100,000 population are noticeably smaller for Houston based on both 2002 and 2004 air quality data and for Los Angeles based on 2002 air quality, especially upon just meeting
the current or alternative 8-hr standards than the other urban areas. The risk estimates are notably higher in most of the urban areas for 2002 air quality data and air quality data simulated to just meet the current and alternat ive standards based on adjusting 2002 data. As shown in Table 5C-13 through 5C-16 in Appendix 5C of this chapter, estimated O 3 - related (non-accidental) mortal ity reported by Schwartz (2004) for Chicago, Detroit, and Houston, based on both the single-city and the multi-city concentration -response functions, tend to be higher than the Bell et al . (2004) estimates in t hose locations in large part because Schwartz
used the 1-hr maximum O 3 concentration, rather than the 24-h r average, as the exposure metric. The changes from 1-hr maximum O 3 concentrations that just meet the current 8-hr O 3 standard to background 1-hr maximum O 3 concentrations were generally larger in these assessment locations than the corresponding changes using the 24-hr average metric. Figure 5-15a and b shows the estimated annual percent of non-accidental mortality mortality associated with short-term exposure to O 3 concentrations that just meet the current 8-hour daily maximum standard that fall within specified ranges. The pattern of results is similar to the pattern seen for recent year O 3 concentrations discussed in section 5.4.1. Using simulated O 3 concentrations that just meet the current 8-hour standard based on 2004 air quality data, all O 3 -related non-accidental mortality was associated with O 3 concentrations less than 0.06 ppm, 24-hr average and most of that
was associated with O 3 concentrations less than 0.04 ppm, 24-hr average. Using simulated O 3 concentrations that just meet the current 8- hour standard based on 2002 air quality data, all O 3 -related non-accidental mortality was associated with O 3 concentrations less than 0.08 ppm, 24-hr average and the great majority was associated with O 3 concentrations less than 0. 05 ppm, 24-hr average. The results for cardiorespiratory mortality follow a simila r pattern. As discussed in section 5.4.1, scatter plots comparing 8-hr daily maximum concentrations at the highest monitor with the average of the 24- hr average over all monitors with in an urban area were developed and are included in Appendix 5A.2 to provide some perspective on the 24-hr intervals shown. These sca tter plots show that 8-hr daily maximum concentrations on average are roughly twice the observed 24-hr average levels, although there is considerable variability in this relationship from day-to-day within an urban area. There also is some variability in this relationship between 8-hr daily maximum and 24-hr average levels across the 12 urban areas.5-79 Figure 5-15. Estimated Annual Percent of No n-Accidental Mortality Associated with Short-Term Exposure to O 3 Above Policy Relevant Background for the Period April – September When the Current 8-Hour Standard is Just Met (Based on Bell et al., 2004) – Total and Co ntribution of 24-Hour Average O 3 Ranges

Figure 5-15a. Based on Adjusting 2004 Air Quality Data

Figure 5-15b. Based on Adjusting 2002 Air Quality Data

*Note that as shown in scatter plots in Appendix 5A.2, 8-hr daily maximum concentrations at the highest monitor are roughly twice the level of the average of the 24-hr average O 3 concentrations over all monitors within an urban area which are used in this figure, although this ratio varies across areas. 0.00% 0.20% 0.40% 0.60% 0.80% 1.00%AtlantaBostonChicagoClevelandDetroitHoustonLos AngelesNew YorkPhiladelphiaSacramentoSt. LouisWashington,D.C.Percent of Total Incidence (and 95% CI) Attributable to 0.04 ppm<=ozone<0.05 ppm
Attributable to 0.03 ppm<=ozone<0.04 ppm
Attributable to ozone<0.03 ppm

0.00% 0.20% 0.40% 0.60% 0.80% 1.00%AtlantaBostonChicagoClevelandDetroitHoustonLos AngelesNew YorkPhiladelphiaSacramentoSt. LouisWashington,D.C.Percent of Total Incidence (and 95% CI) Attributable to 0.06 ppm<=ozone<0.07 ppm Attributable to 0.05 ppm<=ozone<0.06 ppm Attributable to 0.04 ppm<=ozone<0.05 ppm Attributable to 0.03 ppm<=ozone<0.04 ppm Attributable to ozone<0.03 ppm5-80 5.4.3 Sensitivity Analyses We have conducted sensitivity analyses examining the influence of alternative assumptions about background (i.e., PRB) leve ls on the lung function and mortality risk estimates and the impact of alternative assumptions about the shape of th e lung function exposure-response relationship on the lung function health risk estimates. These sensitivity analyses were motivated by the discussion at the August 24-25, 2006 CASAC meeting and are presented below and in sections 3.3 and 4.3 of the Risk Assessment TSD. Reflecting the discussion at the August CASAC meeting, the CASAC panel suggested (Henderson, 2006c) that one approach to deal with the uncertainties surrounding estimation of
PRB levels would be to assess the change in total risk (i.e., all O 3 -related risks above 0 ppm)
associated with alternative standards relative to the total risks associated with just meeting the current standard, without subtracting estimated ri sks associated with PRB levels from either
estimate. As shown in Tables 4-48 and 4-49 of the Risk Assessment TSD, where non-accidental mortality risks associated with O 3 were estimated for all days above 0 ppm for two recent years of air quality (2002 and 2004), the la rgest part of the to tal risk was related to levels between 0 and our baseline estimated PRB levels. Adop ting the approach sugge sted by CASAC would place emphasis on the region of th e concentration-response relati onship (i.e., at levels below 0.035 ppm down to 0 ppm) where there is the great est uncertainty about wh ether effects occur. In addition, the approach sugge sted by CASAC only addresses ri sks relative to the current
standard and does not address the risk rema ining upon meeting the current and alternative standards, which is an importa nt consideration in setting a NAAQS. For assessing risks remaining upon just meeting a standard, EPA has deci ded as a matter of policy that only risks in
excess of PRB are relevant to the decision, and thus staff judges it is still appropriate to estimate
risks in excess of estimated PRB levels. As discussed below, we have examined the change in lung function risk estimates
associated with alternative sta ndards relative to the current st andard and have found that these estimates are generally insensitiv e to alternative assumptions about PRB. Similarly, changes in non-accidental mortality risk estimates for just meeting alternative sta ndards relative to the
current standard also are less sens itive to assumptions about the le vels used to represent PRB. We recognize that the lung f unction and non-accidental mortality risk estimates remaining upon just meeting the current and alternative sta ndards are impacted to varying degrees by the assumptions about PRB levels depending on area, year of air quality, and health endpoint.

5.4.3.1 Impact of Alternative Assumptions About Background

Risk estimates associated with O 3 concentrations discussed in this chapter and in the Risk Assessment TSD have been developed– either based on O 3 concentrations from a recent year of5-81 air quality or O 3 concentrations “rolled back” to just meet a standard – above PRB. We selected
three locations – Atlant a, Los Angeles, and New York – for a sensitivity analysis for lung function responses, and calculated lung function responses using (1 ) the original PRB estimates, (2) lower PRB estimates for each location, and (3) higher PRB estimates for each location. We also conducted a sensitivity analysis for non- accidental mortality associated with O 3 exposure for
all 12 urban areas. For all of the urban areas, except Atlanta, the lower PRB estimates were calculated by subtracting 5 ppb fr om the original PRB estimates; for Atlanta, the lower PRB estimates were calculated by subtracting 10 ppb from the original PRB estimates. In all locations, the higher PRB estimates were calcu lated by adding 5 ppb to the original PRB
estimates. 16 The lung function sensitivity analyses for a lternative estimates of PRB were run for all school age children, with response defined as a decrement in FEV 1 > 15%, and for asthmatic school age children, with lung function response defined as a decrement in FEV 1 > 10%. Table
5C-17 shows the results of this se nsitivity analysis for all school age children in terms of the number of children estimated to experience a lung function response of concern (i.e., FEV 1

> 15%) based on adjusting 2002 and 2004 air quality to just meet the curren t and two alternative 8-hr standards. Additional tables showing the se nsitivity analysis results for total occurrences of this lung function response for all children are included in the Risk Asse ssment TSD (see section 3.3.1). The sensitivity analysis results for lung function responses in asthmatic children are similar in pattern and also are presented in the Risk Assessment TSD (see section 3.3.1). The impact of alternative lower and hi gher assumed PRB leve ls on lung function responses in all school age children (with responses defined as a decrement in FEV 1 > 15%,) was relatively small, generally much less than +/- 3%. Assuming lower PRB levels increased the
estimated number of children with a response, while assuming higher PRB levels decreased the
estimated number of children w ith a response. In terms of to tal occurrences of moderate lung function responses, different assumptions about PRB had a somewhat larger impact, but the impact was still generally less th an about +/- 10% relative to our base case assumption for PRB. Figure 5-16 shows the impact of lower and higher PRB assumed levels in terms of the relative percent changes in non-accidental mortality risk fr om the current 8-hr sta ndard based on adjusting 2002 air quality data in each of the 12 urban areas. One observes th at for most, but not all of the locations, the general pattern is not significantly impacted by the choice of PRB assumptions. The

16 Summarizing its assessment of the validity of the GEOS-CHEM model, the O 3 CD states, “in conclusion, we estimate that the PRB ozone values reported by Fior e et al. (2003) for afternoo n surface air over the United States are likely 10 ppbv too high in the southeast in summer, and accurate within 5 ppbv in other regions and seasons.” These error estimates are based on comparison of model output with observations for conditions that most nearly reflect those given in the PRB definition, i.e. , at the lower end of the probability distribution.5-82 choice of PRB has a somewhat greater impact on the non-accidental mortality based on adjusting 2004 air quality data (see Figure 4-19 in the Risk Assessment TSD), which is likely due to the significantly
lower O 3 levels associated with just meeting the alternative standards based on this year of air quality
data. Results of the PRB sensitivity analysis fo r non-accidental mortality associated with O 3 exposures expressed in terms of absolute estim ates are presented in Table 5C-18 for 2002 air quality adjusted to just meet the current standa rd. Additional sensitivity analysis results for recent air quality (both 2002 and 2004 air quality ) and for 2004 and 2002 air quality adjusted to just meet the current and two alternative standa rds are included in the Risk Assessment TSD (see section 4.3 and Appendix I). Table 5C-18 illust rates the impact of alternative assumed PRB
levels on incidence of O 3 -related non-accidental mortality per 100,000 population. Lower and higher assumed PRB levels generally resulted in increased and decreased, respectively, estimates in the incidence of mortality per 100,000 population. As shown in this table, estimates assuming
lower PRB levels results in increased estimat es of non-accidental mortality incidence per 100,000 that are often 50 to 100% greater than th e base case estimates. Similarly, estimates assuming higher PRB levels results in decreased estimates of non-accidental mortality incidence per 100,000 that are 50% or greater less than the base case estimates.
As discussed in section 4.3 of the Risk Assessment TSD, because O 3 concentrations just meeting the current standard are substantially lower than O 3 concentrations observed for the recent years of air quality (for most of the urban areas), the ch ange in the assumed PRB levels had a greater impact on the estimates of mortality associated with levels just meeting the current standard, in terms of percent change in the estim ate. Similarly, changing the estimates of PRB tended to have progressively greater impacts on the estimates of mortality risk as progressively more stringent standards were considered. Not surprisingly, assumptions about PRB have a greater impact on risk estimates associated with the most stringent standard examined, since a greater percentage of days is im pacted, in terms of being classified as above or below PRB, by the assumptions concerning PRB levels.

5.4.3.2 Impact of Alternative Assumptions Ab out the Shape of Exposure-Response Relationships for Lung Function Decrements As described in section 5.3.1.3, the expos ure-response functions used in the primary analyses are based on the assumption that the relationship between exposure and response has a5-83 Figure 5-16. Sensitivity Analysis of Estimated Percent Change in O 3 -related NonAccidental Mortality (Using Bell et al., 2004 – 95 Cities) From the Current Standard to Alternative 8-hr Standards and a Recent Year of Air Quality, Using Base Case, Higher, and Lower PRB Estimates*

Figure 5-16a. Based on Adjusting 2004 O 3 Concentrations

Atlanta

-250.0% -200.0% -150.0% -100.0% -50.0%

0.0% 50.0% 100.0%

2004 air quality 0.084/4 0.074/4 0.064/4

Alternative 8-Hr StandardsPercent Change from Current Standard

Original PRB Estimates
Lower PRB Estimates Higher PRB Estimates Boston

-250.0% -200.0% -150.0% -100.0% -50.0%

0.0% 50.0% 100.0%

2004 air quality 0.084/4 0.074/4 0.064/4

Alternative 8-Hr StandardsPercent Change from Current Standard

Original PRB Estimates
Lower PRB Estimates Higher PRB Estimates

Chicago

-250.0% -200.0% -150.0% -100.0% -50.0%

0.0% 50.0% 100.0%

2004 air quality 0.084/4 0.074/4 0.064/4

Alternative 8-Hr StandardsPercent Change from Current Standard

Original PRB Estimates
Lower PRB Estimates Higher PRB Estimates Cleveland

-250.0% -200.0% -150.0% -100.0% -50.0%

0.0% 50.0% 100.0%

2004 air quality 0.084/4 0.074/4 0.064/4

Alternative 8-Hr StandardsPercent Change from Current Standard

Original PRB Estimates
Lower PRB Estimates Higher PRB Estimates

Detroit

-250.0% -200.0% -150.0% -100.0% -50.0%

0.0% 50.0% 100.0%

2004 air quality 0.084/4 0.074/4 0.064/4

Alternative 8-Hr StandardsPercent Change from Current Standard

Original PRB Estimates
Lower PRB Estimates Higher PRB Estimates Houston

-250.0% -200.0% -150.0% -100.0% -50.0%

0.0% 50.0% 100.0%

2004 air quality 0.084/4 0.074/4 0.064/4

Alternative 8-Hr StandardsPercent Change from Current Standard

Original PRB Estimates
Lower PRB Estimates Higher PRB Estimates5-84 Figure 5-16a ccntinued Los Angeles

-250.0% -200.0% -150.0% -100.0% -50.0%

0.0% 50.0% 100.0%

2004 air quality 0.084/4 0.074/4 0.064/4

Alternative 8-Hr StandardsPercent Change from Current Standard

Original PRB Estimates
Lower PRB Estimates Higher PRB Estimates New York

-250.0% -200.0% -150.0% -100.0% -50.0%

0.0% 50.0% 100.0%

2004 air quality 0.084/4 0.074/4 0.064/4

Alternative 8-Hr StandardsPercent Change from Current Standard

Original PRB Estimates
Lower PRB Estimates Higher PRB Estimates

Philadelphia

-250.0% -200.0% -150.0% -100.0% -50.0%

0.0% 50.0% 100.0%

2004 air quality 0.084/4 0.074/4 0.064/4

Alternative 8-Hr StandardsPercent Change from Current Standard

Original PRB Estimates
Lower PRB Estimates Higher PRB Estimates Sacramento

-250.0% -200.0% -150.0% -100.0% -50.0%

0.0% 50.0% 100.0%

2004 air quality 0.084/4 0.074/4 0.064/4

Alternative 8-Hr StandardsPercent Change from Current Standard

Original PRB Estimates
Lower PRB Estimates Higher PRB Estimates

St. Louis

-250.0% -200.0% -150.0% -100.0% -50.0%

0.0% 50.0% 100.0%

2004 air quality 0.084/4 0.074/4 0.064/4

Alternative 8-Hr StandardsPercent Change from Current Standard

Original PRB Estimates
Lower PRB Estimates Higher PRB Estimates Washington, D.C.

-250.0% -200.0% -150.0% -100.0% -50.0%

0.0% 50.0% 100.0%

2004 air quality 0.084/4 0.074/4 0.064/4

Alternative 8-Hr StandardsPercent Change from Current Standard

Original PRB Estimates
Lower PRB Estimates Higher PRB Estimates

*The 8-hr average standards shown in these figures, denoted m/n, are characterized by a concentration of m ppm and an nth-highest daily maximum. So, for example, the current standard is 0.084/4 -- 0.084 ppm, 4 th -highest daily maximum 8-hr average. The figure also compares th e current standard to a recent year of air quality.5-85 Figure 5-16b. Based on Adjusting 2002 O 3 Concentrations

Atlanta

-250.0% -200.0% -150.0% -100.0% -50.0%

0.0% 50.0% 100.0%

2002 air quality 0.084/4 0.074/4 0.064/4

Alternative 8-Hr StandardsPercent Change from Current Standard

Original PRB Estimates
Lower PRB Estimates Higher PRB Estimates Boston

-250.0% -200.0% -150.0% -100.0% -50.0%

0.0% 50.0% 100

. 0%

2002 air quality 0.084/4 0.074/4 0.064/4

Alternative 8-Hr StandardsPercent Change from Current Standard

Original PRB Estimates
Lower PRB Estimates Higher PRB Estimates

Chicago

-250.0% -200.0% -150.0% -100.0% -50.0%

0.0% 50.0% 100

. 0%

2002 air quality 0.084/4 0.074/4 0.064/4

Alternative 8-Hr StandardsPercent Change from Current Standard

Original PRB Estimates
Lower PRB Estimates Higher PRB Estimates Cleveland

-250.0% -200.0% -150.0% -100.0% -50.0%

0.0% 50.0% 100

. 0%

2002 air quality 0.084/4 0.074/4 0.064/4

Alternative 8-Hr StandardsPercent Change from Current Standard

Original PRB Estimates
Lower PRB Estimates Higher PRB Estimates

Detroit

-250.0% -200.0% -150.0% -100.0% -50.0%

0.0% 50.0% 100

. 0%

2002 air quality 0.084/4 0.074/4 0.064/4

Alternative 8-Hr StandardsPercent Change from Current Standard

Original PRB Estimates
Lower PRB Estimates Higher PRB Estimates Houston

-250.0% -200.0% -150.0% -100.0% -50.0%

0.0% 50.0% 100

. 0%

2002 air quality 0.084/4 0.074/4 0.064/4

Alternative 8-Hr StandardsPercent Change from Current Standard

Original PRB Estimates
Lower PRB Estimates Higher PRB Estimates5-86 Figure 5-16b continued

Los Angeles

-250.0% -200.0% -150.0% -100.0% -50.0%

0.0% 50.0% 100

. 0%

2002 air quality 0.084/4 0.074/4 0.064/4

Alternative 8-Hr StandardsPercent Change from Current Standard

Original PRB Estimates
Lower PRB Estimates Higher PRB Estimates New York

-250.0% -200.0% -150.0% -100.0% -50.0%

0.0% 50.0% 100

. 0%

2002 air quality 0.084/4 0.074/4 0.064/4

Alternative 8-Hr StandardsPercent Change from Current Standard

Original PRB Estimates
Lower PRB Estimates Higher PRB Estimates

Philadelphia

-250.0% -200.0% -150.0% -100.0% -50.0%

0.0% 50.0% 100

. 0%

2002 air quality 0.084/4 0.074/4 0.064/4

Alternative 8-Hr StandardsPercent Change from Current Standard

Original PRB Estimates
Lower PRB Estimates Higher PRB Estimates Sacramento

-250.0% -200.0% -150.0% -100.0% -50.0%

0.0% 50.0% 100

. 0%

2002 air quality 0.084/4 0.074/4 0.064/4

Alternative 8-Hr StandardsPercent Change from Current Standard

Original PRB Estimates
Lower PRB Estimates Higher PRB Estimates

St. Louis

-250.0% -200.0% -150.0% -100.0% -50.0%

0.0% 50.0% 100.0%

2002 air quality 0.084/4 0.074/4 0.064/4

Alternative 8-Hr StandardsPercent Change from Current Standard

Original PRB Estimates
Lower PRB Estimates Higher PRB Estimates Washington, D.C.

-250.0% -200.0% -150.0% -100.0% -50.0%

0.0% 50.0% 100

. 0%

2002 air quality 0.084/4 0.074/4 0.064/4

Alternative 8-Hr StandardsPercent Change from Current Standard

Original PRB Estimates
Lower PRB Estimates Higher PRB Estimates

*The 8-hr average standards shown in these figures, denoted m/n, are characterized by a concentration of m ppm and an nth-highest daily maximum. So, for example, the current standard is 0.084/4 -- 0.084 ppm, 4 th -highest daily maximum 8-hr average. The figure also compares th e current standard to a recent year of air quality.5-87 logistic form with 90 percent probability and a linear (hocke ystick) form with 10 percent probability. We have conducted sensitivity anal yses which examine the influence of two alternative assumptions about th e exposure-response f unctions for lung function decrements in all and asthmatic school age children. These a lternative exposure-response functions are based on an 80 percent logistic/20 percen t linear split and a 50 percent lo gistic/50 percent linear split, in five locations – Atlanta, Chicago, Houston, Los Angeles, and New York. Appendix C of the Risk Assessment TSD presents tables showing the results of the sensitivity analysis for a change

in FEV 1 ≥ 15% for all school age children for a recen t year of air quality as well as when O 3 concentrations just meet each of three 4th-hi ghest daily maximum standards – 0.084/4, 0.074/4 and 0.064/4, based on adjusting 2004 and 2002 data, respectively . Appendix C also shows the corresponding impacts on the estim ated number of asthmatic school age children experiencing at least one lung function response, defined as a change in FEV 1 ≥ 10%. Figures 5-17a and b and 5-18a and b show the impacts of altern ative estimates of exposure-response functions on estimated percen t changes in response among all school age children and asthmatic school age children, respectively, when O 3 concentrations are changed from those just meeting the current standard to a recent year of air quality (results are shown based on both 2004 and 2002 air quality) and to those just meeting each of the two alternative standards given above. A positive percent change re flects a reduction in risk relative to just meeting the current 8-hr standard. Since the co mparisons are with respec t to just meeting the current standard, the percent changes for the recent year of air quality are negative (i.e., going from just meeting the current standard to 2002 or 2004 air quality represents an increase in risk). The impacts of changing the functional form of the exposure-response relationship varied substantially. Changing from the 90 percent logi stic/10 percent linear base case to the 80%/20% split generally had only a small impact for all and asthmatic school age children, with most risk estimates being within 5% of the base case estim ates. The impacts of changing from the base case to the 50% logistic/50% linear case were generally (although not always) larger. We observed greater changes for all and asthmatic school age children between the 50/50 split and the base case in terms of percent change in risk for the two more stringent alternative standards
relative to the current standard

5.4.4 Comparison with Risk Estimates from Prior Review As noted in section 5.1.1, EPA conducted a health risk assessme nt during the prior O 3 NAAQS review. We recognize that two of the health endpoints, lung function (FEV 1 ) decrements for children and respiratory-related a nd asthma hospital admissions were included in5-88 Figure 5-17. Sensitivity Analysis: Impact of Alternative Estimates of Exposure-Response Function on Estimated Percent Changes From the Current St andard in Numbers of All Children (Ages 5- 18) Engaged in Moderate Exertion Experi encing at Least One Decrement in FEV 1 > 15%

Figure 5-17a. Based on Adjusting 2004 O 3 Concentrations

Atlanta

-350% -300% -250% -200% -150% -100% -50%

0% 50% 100%

2004 air quality 0.084/4 0.074/4 0.064/4

Alternative 8-Hr StandardsPercent Change from Current Standard

90% logistic-10% linear 80% logistic-20% linear 50% logistic-50% linear Chicago

-350% -300% -250% -200% -150% -100% -50%

0% 50% 100%

2004 air quality 0.084/4 0.074/4 0.064/4

Alternative 8-Hr StandardsPercent Change from Current Standard

90% logistic-10% linear 80% logistic-20% linear 50% logistic-50% linear

Houston

-350% -300% -250% -200% -150% -100% -50%

0% 50% 100%

2004 air quality 0.084/4 0.074/4 0.064/4

Alternative 8-Hr StandardsPercent Change from Current Standard

90% logistic-10% linear 80% logistic-20% linear 50% logistic-50% linear Los Angeles*

-350% -300% -250% -200% -150% -100% -50%

0% 50% 100%

2004 air quality 0.084/4 0.074/4 0.064/4

Alternative 8-Hr StandardsPercent Change from Current Standard

90% logistic-10% linear 80% logistic-20% linear 50% logistic-50% linear

New York

-350% -300% -250% -200% -150% -100% -50%

0% 50% 100%

2004 air quality 0.084/4 0.074/4 0.064/4

Alternative 8-Hr StandardsPercent Change from Current Standard

90% logistic-10% linear 80% logistic-20% linear 50% logistic-50% linear * The percent reductions from the current standard (0.084/4) to 2004 air quality were omitted for Los Angeles because they were so large in magnitude (-556%, -590%, and – 1016% for the 90/10, 80/20 and 50/50 splits, respectively).5-89 Figure 5-17b. Based on Adjusting 2002 O 3 Concentrations

Atlanta

-180% -160% -140% -120% -100% -80% -60% -40% -20%

0% 20% 40% 60% 80% 100%

2002 air quality 0.084/4 0.074/4 0.064/4

Alternative 8-Hr StandardsPercent Change from Current Standard

90% logistic-10% linear 80% logistic-20% linear 50% logistic-50% linear Chicago

-180% -160% -140% -120% -100% -80% -60% -40% -20%

0% 20% 40% 60% 80% 100%

2002 air quality 0.084/4 0.074/4 0.064/4

Alternative 8-Hr StandardsPercent Change from Current Standard

90% logistic-10% linear 80% logistic-20% linear 50% logistic-50% linear

Houston

-180% -160% -140% -120% -100% -80% -60% -40% -20%

0% 20% 40% 60% 80% 100%

2002 air quality 0.084/4 0.074/4 0.064/4

Alternative 8-Hr StandardsPercent Change from Current Standard

90% logistic-10% linear 80% logistic-20% linear 50% logistic-50% linear Los Angeles*

-180% -160% -140% -120% -100% -80% -60% -40% -20%

0% 20% 40% 60% 80% 100%

2002 air quality 0.084/4 0.074/4 0.064/4

Alternative 8-Hr StandardsPercent Change from Current Standard

90% logistic-10% linear 80% logistic-20% linear 50% logistic-50% linear

New York

-180% -160% -140% -120% -100% -80% -60% -40% -20%

0% 20% 40% 60% 80% 100%

2002 air quality 0.084/4 0.074/4 0.064/4

Alternative 8-Hr StandardsPercent Change from Current Standard

90% logistic-10% linear 80% logistic-20% linear 50% logistic-50% linear *The percent reductions from the current standard (0.084/4) to 2002 air quality were omitted for Los Angeles because they were so large in magnitude (- 538%, -562%, and – 863% for the 90/10, 80/20 and 50/50 splits, respectively).5-90 Figure 5-18. Sensitivity Analysis: Impact of Alternative Estimates of Exposure-Response Function on Estimated Percent Changes From the Current Stan dard in Numbers of Asthmatic Children (Ages 5-18) Engaged in Moderate Exertion Expe riencing at Least One Decrement in FEV 1 > 10%

Figure 5-18a. Based on Adjusting 2004 O 3 Concentrations

Atlanta

-180% -160% -140% -120% -100% -80% -60% -40% -20%

0% 20% 40% 60% 80% 100%

2004 air quality 0.084/4 0.074/4 0.064/4

Alternative 8-Hr StandardsPercent Change from Current Standard

90% logistic-10% linear 80% logistic-20% linear 50% logistic-50% linear Chicago

-180% -160% -140% -120% -100% -80% -60% -40% -20%

0% 20% 40% 60% 80% 100%

2004 air quality 0.084/4 0.074/4 0.064/4

Alternative 8-Hr StandardsPercent Change from Current Standard

90% logistic-10% linear 80% logistic-20% linear 50% logistic-50% linear

Houston

-180% -160% -140% -120% -100% -80% -60% -40% -20%

0% 20% 40% 60% 80% 100%

2004 air quality 0.084/4 0.074/4 0.064/4

Alternative 8-Hr StandardsPercent Change from Current Standard

90% logistic-10% linear 80% logistic-20% linear 50% logistic-50% linear Los Angeles*

-180% -160% -140% -120% -100% -80% -60% -40% -20%

0% 20% 40% 60% 80% 100%

2004 air quality 0.084/4 0.074/4 0.064/4

Alternative 8-Hr StandardsPercent Change from Current Standard

90% logistic-10% linear 80% logistic-20% linear 50% logistic-50% linear

New York

-180% -160% -140% -120% -100% -80% -60% -40% -20%

0% 20% 40% 60% 80% 100%

2004 air quality 0.084/4 0.074/4 0.064/4

Alternative 8-Hr StandardsPercent Change from Current Standard

90% logistic-10% linear 80% logistic-20% linear 50% logistic-50% linear * The percent reductions from the current standard (0.084/4) to 2004 air quality, based on the 90/10, 80/20, and 50/50 split exposure-response functions for Los Angeles were - 294%, -280%, and – 198%, respectively.5-91 Figure 5-18b. Based on Adjusting 2002 O 3 Concentrations

Atlanta

-180% -160% -140% -120% -100% -80% -60% -40% -20%

0% 20% 40% 60% 80% 100%

2002 air quality 0.084/4 0.074/4 0.064/4

Alternative 8-Hr StandardsPercent Change from Current Standard

90% logistic-10% linear 80% logistic-20% linear 50% logistic-50% linear Chicago

-180% -160% -140% -120% -100% -80% -60% -40% -20%

0% 20% 40% 60% 80% 100%

2002 air quality 0.084/4 0.074/4 0.064/4

Alternative 8-Hr StandardsPercent Change from Current Standard

90% logistic-10% linear 80% logistic-20% linear 50% logistic-50% linear

Houston

-180% -160% -140% -120% -100% -80% -60% -40% -20%

0% 20% 40% 60% 80% 100%

2002 air quality 0.084/4 0.074/4 0.064/4

Alternative 8-Hr StandardsPercent Change from Current Standard

90% logistic-10% linear 80% logistic-20% linear 50% logistic-50% linear Los Angeles*

-180% -160% -140% -120% -100% -80% -60% -40% -20%

0% 20% 40% 60% 80% 100%

2002 air quality 0.084/4 0.074/4 0.064/4

Alternative 8-Hr StandardsPercent Change from Current Standard

90% logistic-10% linear 80% logistic-20% linear 50% logistic-50% linear

New York

-180% -160% -140% -120% -100% -80% -60% -40% -20%

0% 20% 40% 60% 80% 100%

2002 air quality 0.084/4 0.074/4 0.064/4

Alternative 8-Hr StandardsPercent Change from Current Standard

90% logistic-10% linear 80% logistic-20% linear 50% logistic-50% linear *The percent reductions from the current standard (0.084/4) to 2002 air quality, based on the 90/10, 80/20, and50/50 split exposureresponse functions for Los Angeles were -292%, -279%, and – 200%, respectively.5-92 the current and prior reviews. The other health endpoints included in the current risk assessment, lung function decrements in as thmatic children, respiratory symptoms in moderate/severe asthmatic children, and non-accidental and cardiorespiratory mortality are based on more recent scientific studies and, were not included in the prior review. The lung function risk estimates developed fo r the current and prio r review are based on exposure distributions generated by running O 3 exposure models and exposure-response relationships developed using the available controlled human expos ure studies data. There have been significant changes in the exposure mode l between the prior and current review. As discussed in Chapter 4, no direct comparison is being made of the differences in exposure estimates for children engaged in moderate exerti on associated with just meeting the current 8-hr standard between the past and current reviews. Th is is due to differences in the exposure model, differences in the population coverage within the urban areas included in the analyses, and differences in the population definitions included in the past and current exposure analyses. Due to the differences in the exposure analyses, as well as changes in the exposure-response relationships (e.g., change in the shape of the exposure-response relationship from a linear relationship to one that is more sigmoidal or s-sh aped), and changes in estimates for PRB used in the assessments, no direct compar ison is being made of the differences in lung function risk
estimates for children between th e current and prior review.
We note that the current estimates for O 3 -related hospital admissions for respiratory illness and asthma for New York City are higher than the estimates in the risk assessment conducted during the prior O 3 NAAQS review. Both the prior and current assessments used the same concentration-response func tions for these health outcomes . The main reason for higher
estimates in the current assessmen t is the use of a single value of 0.04 ppm for background in the prior review which is higher th an the current modele d values for background in the current assessment which are in the rang e of about 0.015 to 0.035 ppm. Thus, under the current risk
assessment O 3 levels above background but below 0.04 ppm are contributing additional estimated cases that were not included in the assessment for the prior O 3 NAAQS review.

5.4.5 Key Observations In considering the quantitative estimates from the risk assessment the limitations and
uncertainties associated with th e risk estimates discussed in section 5.3.1.4 for lung function decrements and section 5.3.2.5 for respirator y symptoms, hospital admissions, and pre-mature mortality should be kept in mind. It is also im portant to consider the degree of confidence about
the extent to which O 3 is causally related to each of the e ffects for which risk estimates were produced (see section 3.7.5). Fo r example, there is clear and convincing evidence of causality for lung function decrements in healthy childre n under moderate exertion for 8-hr average O 35-93 exposures. We also judge that there is st rong evidence for a causal relationship between respiratory symptoms in asthmatic children and O 3 exposures and between hospital admissions for respiratory causes and ambient O 3 exposures. There is greater uncertainty and somewhat less confidence about the relationship between O 3 and non-accidental and cardi orespiratory mortality, although the CD’s overall evaluation is that it is highly suggestive th at this relationship exists.

Recent O 3 Air Quality Levels Section 5.4.1 has presented risk estimates asso ciated with two recent years of air quality as represented by 2002 and 2004 monitoring data . Presented below are key observations resulting from this part of the risk assessment.

• The ranges in median estimates of the number of school age children (ages 5-18) estimated to experience at least one FEV 1 decrement > 15% due to 8-hr O 3 exposures during the O 3 season across the 12 urban areas are 10,000 to nearly 220,000 (based on 2004 air quality) and 24,000 to about 345,000 (bas ed on 2002 air quality). In terms of percent of this population the ra nges in median estimates are 1.4 to 6.0% (based on 2004 air quality) and 5.3 to 9.9% (based on 2002 air quality). In terms of estimated occurrences of this same response the ranges in median estimates are 69,000 to nearly 1.5 million (based on 2004 air quality) and about 145,000 to over 1.5 million (based on 2002 air quality). The average number of occurrences per child in an O 3 season ranged from about 4 to 8 depending on urban area and year.

• The ranges in median estimates of the numbe r of asthmatic school age children (ages 5- 18) estimated to experience at least one FEV1 decrement > 10% due to 8-hr O 3 exposures during the O 3 season across the five urban areas are 12,000 to 62,000 (based on 2004 air quality) and 17,000 to about 118,000 (based on 2002 air quality). In terms of the percent of this population the ranges in median es timates are 4.9 to 13.6% (based on 2004 air quality) and 12.5 to 18.3% (based on 2002). In terms of total occurrences of this same response the ranges in median estimates ar e 109,000 to about 660,000 responses (based on 2004 air quality) and from about 96,000 to 834,000 responses (based on 2002 air quality). Dividing the estimated total number of occurrences by the number of asthmatic children estimated to experien ce this lung function response, results in each child being estimated to have on average between roughl y 5 and 10 occurrences depending on urban area and year.

• Estimates for increased respiratory symptoms (i.e., chest tightness, shortness of breath, and wheeze) in asthmatic children (ages 0-12) who used maintenance medications were only developed for the Boston urban area. Th e ranges in median estimates of symptom days for these three health outcomes are about 5,000 to 15,000 (based on 2004 air quality) and about 7,000 to 20,000 (based on 2002 air qua lity). In term s of percent of total incidence for these three health outcomes the ranges in median estimates are about 8 to 14% (based on 2004 air quality) and about 11 to 20% (based on 2002 air quality).

• Estimates for respiratory-related hospital admissions (e.g,, asthma-related) were developed for three urban areas (New York, Los Angeles, and Detroit). The median5-94 estimates for New York are about 380 (based on 2004 air quality) and about 520 (based on 2002 air quality) O 3 -related excess hospital admissions for asthma. For 2004 and 2002 air quality, these estimates represent a bout 3 and 4%, respectively, of total incidence.

• The risk assessment included a variety of estimates based on single- and multi-city studies for non-accidental and cardiorespiratory mortality. Since the median estimates from single-city and multi-city studies and models were generally of similar magnitude, with a few notable exceptions, we have focused on the estimates based on the multi-city studies to compare risk estimates across the 12 urban areas. The median estimates for incidence for non-accidental mortality (based on Bell et al., 2004 – 95 cities concentration-response function) range from about 3 to 130 (based on 2004 air quality) which is about 0.2 to 0.4% of total incide nce. These same estimates based on 2002 air quality range from about 10 to 110 which is about 0.2 to 0.6% of total incidence. Estimates of O 3 -related non-accidental mortality reported by Schwartz (2004) forChicago, Detroit, and Houston, based on both single city and multi-city concentrationresponse functions, are somewhat higher than other estimates for these locations. This is mainly due to the use of the 1-hr maximum O 3 concentration in Schwartz (2004), rather than the 24-hr average, as the exposure metric.

• Examining the contribution of various O 3 ranges to these non-accidental mortality estimates, we found all of the mortality was associated with 24-hr average concentrations less than 0.06 ppm and most of it was associat ed with concentrations less than 0.04 ppm for 2004 air quality. For 2002, all of the O 3 -related non-accidental mortality was associated with 24-hr average concentrations less than 0.08 ppm and the great majority was associated with concentrations less than 0.05 ppm. Based on an examination of O 3 air quality relationships between 24-hr averag e concentrations averaged over the urban monitors in an urban area on a given day a nd the highest daily maxi mum 8-hr average at any of the monitors in the same area on the corresponding day, we note that the 8-hr daily maximum concentrations are on average about twice the 24-hr average level. So, for example, a range of 0.04 to 0.06 ppm, 24-hr average corresponds with roughly daily maximum 8-hr levels in the range 0.08 to 0. 12 ppm measured at th e highest fixed-site monitor within an urban area.

Meeting the Current and Alternative 8-hr Standards

Section 5.4.2 has presented risk estimates a ssociated with just meeting the current and several potential altern ative 8-hr standards based on ad justing 2004 and 2002 monitoring data using design values for the 2002-2004 time peri od. Presented below are key observations resulting from this part of the risk assessment.

• In comparing risk estimates for alternativ e standards, uncertain ties in quantifying the health risks associated ambient O 3 concentrations would be expected to remain relatively constant in different models. Thus, we have greater confidence in relative comparisons in risk estimates between alternative standard s than in the absolute magnitude of risk5-95 estimates associated with any particular st andard. As discussed in section 5.4.3.1, differences in risk between alternative standa rds (e.g., reductions in risk for alternative standards relative to the current standard or recent ai r quality levels) is in most situations not impacted by assumptions about estimated PRB levels. Reductions in risks for alternative standards relative to the risks associated with just meeting the current standard are presented in section 6.3.4.

• Significant year-to-year variability in O 3 concentrations combined with the use of a 3- year design value to determine the amount of ai r quality adjustment to be applied to each year analyzed, results in signi ficant year-to-year variability in the annual health risk estimates associated with just meeting the current and potential alternative 8-hr standards.

• The range in median estimates of the nu mber of school age children (ages 5-18) estimated to experience at least one FEV 1 decrement > 15% due to 8-hr O 3 exposures during the O 3 season across the 12 urban areas when th e current 8-hr standard is just met (based on adjusting 2002 air quality) are about 10 ,000 to 12,000. These estimated risks would be reduced to a range of 3,000 to 43,000 children under the most stringent alternative standard examined (i.e., 0.064 ppm, 4th-highest daily 8-hr maximum –i.e., the 0.064/4 alternative) based on adjusting 2002 air quality. In terms of percent of this population the ranges in median estimates ar e about 1.0 to 5.4% (based on 2002 air quality) for just meeting the current standard and these estimates are reduced to about 0.2 to 1.6% upon just meeting the 0.064/4 alte rnative standard. In terms of estimated occurrences of this same response the range in median estimates are 72,000 to about 750,000 when the current 8-hr standard is just met (based on 2002 air quality) These estimated risks would be reduced to a ra nge of 26,000 to about 340,000 occurrences upon just meeting the most stringent alternative standard (0.064/4). The average number of occurrences per child in an O 3 season ranged from about 4 to 10 for air quality just meeting the current standard across the 12 ur ban areas (based on 2002 air quality). The average number of occurrences per child ra nged from 4 to 15 for the most stringent alternative standard analyzed (0.064/4). The risk estimates associated with just meeting the current and alternative 8-hr standa rds based on adjusting 2004 air quality are generally of similar magnitude , although somewhat lower in 10 of the 12 urban areas.

• The ranges in median estimates of the numbe r of asthmatic school age children (ages 5- 18) estimated to experience at least one FEV 1 decrement > 10% due to 8-hr O 3 exposures during the O 3 season across the five urban areas ar e about 9,000 to 63,000 or in terms of percentage of this population range from 3.4 to 10.9% associated with just meeting the current standard (based on adjusting 2002 air quality). These estimated risks would be reduced to a range of about 4,000 to 27,000 asthmatic children under the most stringent alternative standard examined (i.e., 0.064 ppm, 4th-highest daily 8-hr maximum –i.e., the 0.064/4 alternative) based on adjusting 2002 air quality. In terms of estimated occurrences of this same response the range of median estimates are 52,000 to nearly 510,000 responses associated with just meeti ng the current standard (based on adjusting 2002 air quality). These estimated risks would be reduced to a range of 14,000 to about 275,000 occurrences upon just meeting the most stringent alternative standard (0.064/4). The average number of occurrences per asthmatic child in an O 3 season ranged from5-96 about 6 to 11 associated with just mee ting the current standard (based on 2002 air quality). The average number of occurrences per asthmatic child ranged from about 4 to 12 upon meeting the most stringe nt alternative examined (0.064 ppm, 4th-highest daily maximum 8-hr average). The risk estimates a ssociated with just meeting the current and alternative 8-hr standards based on adjusting 2004 air quality are generally of similar magnitude, although somewhat lower in 3 of the 5 areas analyzed.

• Estimates for increased respiratory symptoms (i.e., chest tightness, shortness of breath, and wheeze) in moderate/severe asthmatic children (ages 0-12) were only developed for the Boston urban area. The median estimated number of days invol ving chest tightness (using the concentration-res ponse relationship with only O 3 in the model) ranges from 4,500 (based on adjusting 2004 air quality) to 6,100 (based on adjusting 2002 air quality) upon meeting the current 8-hr standard a nd these are reduced to 3,100 (based on adjusting 2004 air quality) to 4,600 days upon meeting the most st ringent alternative examined (0.064 ppm, 4th-highest daily ma ximum 8-hr average). These same ranges correspond to 8 to 11% of tota l incidence of chest tightness upon meeting the current 8-hr standard and to about 5.5 to 8% of total incidence of chest tightness upon meeting a 0.064 ppm, 4th-highest daily maximu m 8-hr average standard. Similar patterns of reduction were observed for each of the reported respiratory symptoms.

• Estimates for respiratory-related hospital admissions (e.g,, respiratory illness, asthmarelated) were developed for three urban lo cations (New York City, Los Angeles, and Detroit). For asthma-related admissions in New York City the estimates are about 3.9 cases per 100,000 relevant popula tion, which represents about 2.4% of total incidence or 313 cases upon just meeting the current standa rd based on adjusting 2004 air quality data. For increasingly more stringent alternative 8-hr standards, a gr adual reduction in the cases per 100,000 relevant popul ation is observed from 3.9 cases per 100,000 upon just meeting the current 8-hr sta ndard to about 2.6 cases per 100,000 under the most stringent 8-hr standard (i.e., 0.064 ppm, average 4th- highest daily maximum) analyzed. Based on adjusting 2002 air quality data, asthma-related admissions in New York City are about 5.5 cases per 100,000 relevant population, which represents about 3.3% of total incidence or about 440 cases upon just meeting the cu rrent standard. For increasingly more stringent alternative 8-hr standards, a gra dual reduction is observed from 5.5 cases per 100,000 (3.3% of total incidence) upon just meeting the current 8-hr standard to about 3.9 cases per 100,000 (2.4% of total incidence).

• Based on the median estimates for inciden ce for non-accidental mortality (based on Bell et al., 2004 – 95 cities concentration-respons e function), meeting the most stringent standard shown (0.064 ppm, 4th-highest daily maximum) is estimated to reduce mortality by 55 percent of what it would be associated with just meeting the current standard (based on adjusting 2004 air qua lity data). Adjusting 2002 air quality data to just meet the 0.064 ppm, standard results in a 40 pe rcent reduction in non- accidental mortality relative to just meeting the current 8-hr st andard . The patterns for cardiorespiratory mortality are similar. The aggregate O 3 -related cardiorespiratory mortality at the most stringent standard shown is estimated to be about 57 percent of what it would be at the current standard, using simulated O 3 concentrations that just meet the current and5-97 alternative 8-hour standards ba sed on 2004 air quality data. Using 2002 air quality data, the corresponding result is about 42 percent.

• Much of the contribution to the risk estimates for non-acci dental and cardiorespiratory mortality upon just meeting the current 8-hr standard is associated with 24-hr O 3 concentrations between background and 0.04 ppm. Based on examining relationships between 24-hr concentrations averaged across the monitors within an urban area and 8-hr daily maximum concentrations, 8-hr daily maxi mum levels at the highest monitor in an urban area associated with these averaged 24-hr levels are generally about twice as high.

Uncertainty and Variability

• There is noticeable variability in estimated O 3 -related incidence of morbidity and mortality across the 12 urban areas analyzed fo r both recent years of air quality and for air quality adjusted to simulate just meeti ng the current and several potential alternative 8-hr standards. This variability is likely due to differences in air quality distributions, differences in exposure related to many fact ors including varying act ivity patterns and air exchange rates, differences in baseline inci dence rates, and differences in susceptible populations and the age distribut ion across the 12 urban areas. For the lung function part of the risk assessment, spatia l variability in air quality a nd population exposure inputs has been included in the assessment by use of a location specific exposure analysis and location specific input data to that anal ysis. For the epidemiology-based health endpoints, spatial variability in key inputs has been embedde d in the analysis by use of location specific inputs (e .g., air quality, population data , baseline incidence data, concentration-response relationships).

• An important uncertainty to consider is the extent to which the associations between O 3 and the health endpoints included in the asse ssment actually reflect causal relationships. For lung function decrements, respiratory symp toms in moderate to severe asthmatic children, and respiratory-re lated hospital admissions ther e is clear and very strong evidence supporting the judgment that the relati onships are causal. With respect to nonaccidental and cardiorespiratory mortality, th ere is greater uncerta inty, with the CD concluding that the overall body of ev idence is highly suggestive that O 3 directly or indirectly contributes to nonaccidental and cardiopulmonary-related mortality (CD, p. 8- 78). Given the overall evidence, including th e strong evidence from the time-series studies reporting associations with non-accid ental and cardiorespiratory mortality, along with information about potential mechanisms and a range of health effects observed in controlled human exposure studies (i.e., in creased lung inflammation, impacts on host defense, and increased airway responsivene ss), and strong eviden ce showing respiratoryrelated hospital admissions and emergency depa rtment visits for asthmatics, the staff judges that there is a likely causal relationship between O 3 exposures and non-accidental and cardiorespiratory mortality.

• Statistical uncertainty in th e exposure-response relationshi ps associated with sampling error has been characterized in the lung func tion part of the risk assessment. Other5-98 important uncertainties in the exposure-respons e relationship for the lung function health outcomes include:

- uncertainty associated with the shape of the exposure-response relationship, which also has been considered usin g a Bayesian Markov Chain Monte Carlo approach recommended by members of th e CASAC panel and extrapolation of the relationship to levels below 0.04 ppm, the lowest tested level in controlled human exposure studies;

- uncertainty due to use of 6.6-hr data fo r subjects engaged in moderate exertion to estimate response associated with 8-hr exposures under moderate or greater exertion;

- uncertainty about whether O 3 -induced responses are re producible, although this is generally supported by other cont rolled human exposure studies showing significant reproducibility of response;

- uncertainty introduced by use of exposure- response relationships based on 18 to 35 year old subjects to repr esent the relationships for all and asthmatic school age children age 5 to 18, although the use of adult data is supported by a study testing 8 to 11 year olds and observations from a number of summer camp field studies of school age children which found compar able responses to those observed in adults;

- uncertainty in the estimated exposure -response relationship due to assumption that response on any given day is independent of previous O 3 exposure; and

- uncertainty in the estimated exposure -response due to assumption that the response would not be affected by th e presence of other co-pollutants.

• Uncertainties related to es timating the concentration-response relationships for the epidemiological-based part of the risk assessment include:

- statistical uncertainty due to sampli ng error which is characterized in the assessment; - model uncertainty (i.e., uncertainty about the shape and magnitude of the concentration-response relationshi p taking into account lags, other pollutants, etc.); and - uncertainty about whether a concen tration-response function provides an accurate representation of the relatio nship in the location of interest because of a) the possible role of asso ciated co-pollutants, b) variations in the relationship of total ambient exposure to ambient monitoring in different location, and c) differen ces in population ch aracteristics and population behavior patterns across lo cations or over time in the same location.

• Uncertainties related to the air quality data affect both the controlled human exposure studies-based and epidemiological studies-based parts of the risk assessment and include:

- uncertainties associated with the air quality adjustment procedure that was used to simulate just meeting the current a nd alternative 8-hr standards; and5-99 - uncertainties about estimated background c oncentrations for e ach location, for which sensitivity analyses were conducte d examining the impact of alternative lower and higher assumed background concentrations.

• Based on the sensitivity analyses presented in the prior review, alternative air quality adjustment procedure had only a modest impact on the risk estimates. With respect to the uncertainties about estimated background concen trations, as discussed in section 5.4.3, alternative assumptions about PRB levels had a variable impact depending on the health effect considered and the location and standard analyzed in terms of the absolute magnitude of the risk estimates. In most, but not all cases, there was a relatively small impact on either absolute or relative changes in lung function risk estimates due to alternative assumptions about PRB levels. With respect to O 3 -related non-accidental mort ality, alternative assumptions about background levels had a greater impact. Estimates of ri sk remaining upon just meeting the current or alternative standards were most affected, with di fferences of +/-50% or larger observed in many of the areas. Alternative a ssumptions about PRB levels had a greater impact on the nonaccidental mortality risk estimates associated with more stringent 8-hr standards. While noteable differences were observed for non-accidental mort ality in some areas, particularly for more stringent standards, the overall pattern of reduc tions, expressed in terms of percentage reduction relative to the current standard, was significantly less impacted by alternative assumptions for PRB than the absolute magnitude of the risks.5-100 References

Abt Associates Inc. (2005a). Ozone Health Risk Assessment for Selected Ur ban Areas: Draft Report. Prepared for Office of Air Quality Planning and Standards, U.S. Environmental Pr otection Agency, Research Triangle Park, NC. October 2005. Available electronically on the internet at: http://www.epa.gov/ttn/naaqs/standards/ozone/s_o3_cr_td.html

.
Abt Associates Inc. (2005b) . Particulate Matter Health Risk Assessmen t for Selected Urban Areas. Prepared for Office of Air Quality Planning and Standards, U.S. Environmental Pr otection Agency, Research Triangle Park, NC. June 2005. Available electronically on the internet at: http://www.epa.gov/ttn/naaqs/standards/pm/s_pm_cr_td.html

. Abt Associates Inc. (2007). Ozone Health Risk Assessment for Selected Urban Areas. Prepared for Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC. July 2007. Available electronically on the internet at: http://www.epa.gov/ttn/naaqs/standards/ozone/s_o3_cr_td.html

. Adams, W.C. (2002). “Comparison of Chamber and Face-Mask 6.6-Hour Exposures to Ozone on Pulmonary Function and Symptoms Responses.” Inhalation Toxicology 14:745-764.

Adams, W.C. (2003). “Comparison of Chamber and Face Mask 6.6-Hour Expo sure to 0.08 ppm Ozone via SquareWave and Triangular Profiles on Pulmonary Responses.” Inhalation Toxicology 15: 265-281.

Adams, W.C. (2006). “Comparison of Chamber 6.6-h Exposures to 0.04-0.08 ppm Ozone via Square-Wave and Triangular Profiles on Pulmonary Responses.” Inhalation Toxicology 18: 127-136.

Bell, M,A. McDermott, S.L. Zeger, J.M. Samet, and F. Dominici (2004). “Ozone and short-term mortality in 95 US urban communities, 1987-2000.” JAMA 292(19):2372-2378.

Bell, M,A. R.D. Peng, and F. Dominici (2006). “The Exposure-Response Curve for Ozone and Risk of Mortality and the Adequacy of Current Ozone Regulations.” Envi ronmental Health Perspectives. Available online at: http://dx.doi.org/

CDC, 2005. United States Department of Health and Human Services (US DHHS), Centers for Disease Control and Prevention (CDC), National Center for Health St atistics (NCHS), Compressed Mortality File (CMF) compiled from CMF 1968-1988, Series 20, No. 2A 2000, CMF 1989-1998, Series 20, No. 2E 2003 and CMF 1999-2002, Series 20, No. 2H 2004 on CDC WONDER On-line Database. See http://wonder.cdc.gov/

. DuMouchel, W. (1994). “Hierarchical Bayes Linear M odels for Meta-Analysis.” Technical Report #27. September, 1994. National Institute of Statistical Scie nces, P. O. Box 14162, Rese arch Triangle Park, N.C. 27709.

Fiore, A.M., D.J. Jacob, I. Bey, R.M. Yantosca, B.D. Field, A.C. Fusco, and J.G. Wilkinson (2002a). “Background ozone over the United States in summer: Origin, tren d, and contribution to pollution episodes.” J. Geophys. Res., 107(D15), 4275.

Fiore, A.M., D.J. Jacob, B.D. Field, D.G. Streets, S.D. Fernandes, and C. Jang (2002b). “Linking ozone pollution with climate change: The case for controlling methane.” Geophys. Res. Lett., 29(19), 1919.

Fiore, A.M., D.J. Jacob, H. Liu, R.M. Yantosca, T.D. Fairlie, and Q. Li (2003). “Variability in surface ozone background over the United States: Implications for air quality policy.” Journal Of Geophysical Research Vol. 108(D24), 4787.5-101 Fitz-Simons, T., L. McCluney, and M. Rizzo (2005). OAQPS Staff Memorandum to Ozone NAAQS Review Docket (OAR-2005-1072). Subject: Analysis of 2004 Ozone Data for the Ozone NAAQS Review. November 7, 2005. Available at: http://www.epa.gov/ttn/naaqs/standards/ozone/s_o3_cr_td.html

Friedman, M.S., K.E. Powell, L. Hutwagner, L.M. Grah am, and W.G. Teague (2001). “Impact of changes in transportation and commuting behaviors during the 1996 summer Olympic games in Atlanta on air quality and childhood asthma.” JAMA 285:897-905.

Fusco, A. C., and J. A. Logan (2003). “Analysis of 1970– 1995 trends in tropospheric ozone at Northern Hemisphere midlatitudes with the GEOSCHEM model.” J. Geophys. Res., 108(D15), 4449.

Gent, J.F., E.W. Triche, T.R. Holford, K. Belanger, M.B. Bracken, W.S. Beckett, B.P. Leaderer (2003). “Association of low-level ozone and fine particles with respiratory symptoms in children with asthma.” JAMA 290(14):1859-1867.

Graham, S. and T. McCurdy (2004). “Developing meaningful cohorts for human exposure models.” Journal of Exposure Analysis and Environmental Epidemiology 14:23-43.

Gilliland, F.D., K. Berhane, E. B. Rappaport, D.C. Thomas, E. Avol, W.J. Gauderman, S. J. London, H.G. Margolis, R. McConnell, K.T. Islam and J.M. Peters (2001). “The effects of ambient air pollution on school absenteeism due to respiratory illnesses.” Epidemiology 12(1):43-54.

Hazucha, M. J.; Folinsbee, L. J.; Brom berg, P. A. (2003) “Distribution and reproducibility of spirometric response to ozone by gender and age.” J. Appl. Physiol. 95: 1917-1925.

Henderson, R. (2006a). Letter from CASAC Chairman Rogene Henderson to EPA Administrator Stephen Johnson, June 5, 2006, EPA-CASAC-CON-06-003

Henderson, R. (2006b) Letter from CASAC Chairman Rogene Henderson to EPA Administrator Stephen Johnson, June 5, 2006, EPA-CASAC-06-007.

Henderson, R. (2006c) Letter from CASAC Chairman Rogene Henderson to EPA Administrator Stephen Johnson, October 24, 2006, EPA-CASAC-07-001.

Horstman, D.H. et al. (1990). “Ozone concentration and pulmonary response relationships for 6.6-hr exposures with five hours of moderate exercise to 0.08, 0.10, and 0.12 ppm.” American Review of Respiratory Disease 142:1158-1163.

Huang, Y., F. Dominici, M.L. Bell (2004). “Bayesian hierarchical distributed lag models for summer ozone exposure and cardio-respiratory mortality.” John Ho pkins University, Department of Biostatistics Working Paper. 46.

Ito, K. (2003). Associations of particulate matter components with daily mortality and morbidity in Detroit, Michigan. In: “Revised An alyses of Time-Series Studies of Air Pollution and Health,” Health Effects Institute Special Report, May.

Jaffe, D.H., Singer, M.E., and Rimm, A.A. (2003). “Air pollution and emergency department visits for asthma among Ohio Medicaid recipients, 1991-1996.” Environmental Research 91:21-28.

Johnson, T., Capel, J., and McCoy, M. (1996a). Estimation of Ozone Exposures Experienced by Urban Residents Using a Probabilistic Version of NEM and 1990 Populatio n Data. Prepared by International Technology Air Quality Services for Office of Air Quallity Planning and Standards, EPA, Resear ch Triangle Park, NC. Available electronically on the internet at: http://www.epa.gov/ttn/naaqs/standards/ozone/s_o3_pr_td.html

. Johnson, T., Capel, J., McCoy, M., and Warnasch, J. (1996b). Estimation of Ozone Exposures Experienced by Outdoor Children in Nine Urban Areas Using a Probabilis tic Version of NEM. Prepared by International5-102 Technology Air Quality Services for Office of Air Quallity Planning and Standards, EPA, Research Triangle Park, NC. Available electronically on the internet at: http://www.epa.gov/ttn/naaqs/standards/ozone/s_o3_pr_td.html

. Johnson, T. (1997). “Sensitivity of Exposure Estimates to Air Quality Adjustment Procedure,” Letter to Harvey Richmond, Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina.

Kann, L. et al. (2000). “Youth risk behavior surveillanc e--United States, 1999.” Mortality and Morbidity Weekly Report 49(SS05):1-96.

Langstaff, J. E. (2006). OAQPS Staff Memorandum to Ozone NAAQS Review Docket (OAR-2005-0172). Subject: Analysis of uncertainty in ozone population exposure modeling. July 17. Available at: http://www.epa.gov/ttn/naaqs/standards/ozone/s_o3_cr_td.html

. Linn, W., Y. Szlachcis, H.J. Gong, P. Kinney, K. Berhan e (2000). “Air pollution and daily hospital admissions in metropolitan Los Angeles.” Environmen tal Health Perspective 108:427-434.

McCurdy, T. (2000). “Conceptual basis for multi-route intake dose modeling using an energy expenditure approach.” J. Exposure Anal. Environ. Epidemiol. 10:1-12.

McCurdy, T., Glen, G., Smith, L., Lakkadi, Y. (2000). “The National Exposure Research Laboratory's Consolidated Human Activity Database.” J. Exposure Anal. Environ. Epidemiol. 10:566-578.

McDonnell, W.F. et al. (1985a). “Reproducibility of indi vidual responses to ozone exposure.” American Review of Respiratory Disease 131:36-40.

McDonnell, W. F., III; Chapman, R. S.; Leigh, M. W.; Strope, G. L.; Collier, A. M. (1985b) “Respiratory responses of vigorously exercising children to 0.12 ppm ozone exposure.” Am. Rev. Respir. Dis. 132: 875-879.

McDonnell, W.F. et al. (1991). “Respiratory response of humans exposed to low levels of ozone for 6.6 hours.” American Review of Respir atory Disease 147:804-810.

Moolgavkar, S. H.; Luebeck, E. G.; Hall, T. A.; Anders on, E. L. (1995). “Air pollution and daily mortality in Philadelphia.” Epidemiology 6: 476-484.

Morgan and Henrion (1990). Uncertainty: A Guide To D ealing with Uncertainty in Qualitative Risk and Policy Analysis. Cambridge University Press.

Mortimer, K.M., L.M. Neas, D.W. Dockery, S. Redline, an d I.B. Tager (2002). “The effects on air pollution on inner-city children with asthma.” Euro pean Respiratory Journal. 19:699-705.

Peel, J.L., P.E. Tolbert, M. Klein, K.B. Metzger, W.D. Flanders, K. Todd, J.M. Mulholland, P.B. Ryan, and H. Frumkin, (2005). “Ambient air pollution and respiratory emergency department visits.” Epidemiology 16(2):164-174.

Pope, C. A., R. T. Burnett, M. J. Thun, E. E. Calle, D. Kr ewski, K. Ito, and G. D. Thurston. 2002. Lung Cancer, Cardiopulmonary Mortality, and Long-term Exposure to Fine Particulate Air Pollution. Journal of the American Medical Association, vol 287, no 9: 287:1132-1141.

Post, E., D. Hoaglin, L. Deck, and K. Larntz (2001). “An Empirical Bayes approach to estimating the relation of mortality to exposure to particulate matt er,” Risk Analysis 21(5): 837-842

Richmond H., T. Palma, J. Langstaff, T. McCurdy, G. Glenn, and L. Smith (2002). “Further refinements and testing of APEX (3.0): EPA's population exposure model for criteria and air toxic inhalation exposures.” Poster5-103 presentation. Joint meeting of the International Societ y of Exposure Analysis and International Society of Environmental Epidemiology, August 11-15, 2002, Vancouver, Canada.

Rizzo, M. (2005). OAQPS Staff Memorandum to Ozone NAAQS Review Docket (OAR-2005-1072). Subject: Evaluation of a quadratic approach for adjusting distributions of hourly ozone concentrations to meet air quality standards. November 7. Available at: http://www.epa.gov/ttn/naaqs/standards/ozone/s_o3_cr_td.html

.

Rizzo, M. (2006). OAQPS Staff Memorandum to Ozone NAAQS Review Docket (OAR-2005-1072). Subject: A Comparison between Different Rollback Methodologies Applied to Ambient Ozone Concentrations. May 31. Available at: http://www.epa.gov/ttn/naaqs/sta ndards/ozone/s_o3_cr_td.html

. Schwartz, J. (2000). “The distributed lag between air pollution and daily deaths.” Epidemiology 11(3):320-326.

Schwartz, J. (2004). “How sensitive is the association between ozone and daily deaths to control for temperature?” Am. J. Resp. Crit. Care Med.

Schwartz, J., C. Spix, G. Touloumi, L. Bacharova, T. Baru mamdzadeh, A. le Tertre, T. Pi ekarksi, A. Ponce de Leon, A. Ponka, G. Rossi, M. Saez, J.P. Schouten (1996). “Methodological issues in studies of air pollution and daily counts of deaths or hospital admissions.” J. Epid. and Comm. Health 50(Suppl 1):S3-S11.

Thurston, G.D., K. Ito, P.L. Kinney, M. Lippmann (1992) . “A multi-year study of air pollution and respiratory hospital admission in three New York State metropo litan areas: Results for 1988 and 1989 summers.” J. Exposure Anal. Environ. Epidemiol. 2(4):429-450.

Thurston, G.D. and Ito, K. (2001). “E pidemiological studies of acute ozone exposures and mortality.” J. Exposure Anal. Environ. Epidemiol. 11:286.

Tolbert, P.E., J.A. Mulholland, D.L. MacIntosh, F. Xu, et al. (2000). “Air quality and Pediatric Emergency Room Visits for Asthma in Atlanta, GA, USA.” Amer ican Journal of Epidemiology 151(8):798-810.

U. S. EPA (1996a). Review of National Ambient Air Qu ality Standards for Ozone: Assessment of Scientific and Technical Information - OAQPS Staff Paper. EPA/452/R-96-007. Offi ce of Air Quality Planning and Standards, Research Triangle Park, NC. Av ailable electronically on the internet at: http://www.epa.gov/ttn/naaqs/standards/ozone/s_o3_pr_sp.html

. U.S. EPA (1996b). Air Quality Criteria for Ozone and Related Photochemical Oxidants. EPA/600/P-93/004aF-cF. Office of Research and Development, National Center for Environmen tal Assessment, Research Triangle Park, NC. Available electronically on the internet at: http://cfpub.epa.gov/ncea/cfm/ recordisplay.cfm?deid=2831

. U.S. EPA (2002). Consolidated Human Activities Databa se Users Guide. The database and documentation are available electronically on the internet at: http://www.epa.gov/chadnet1/.

U.S. EPA (2003). Total Risk Integrated Meth odology TRIM.Expo/Inhalation User's Document Volume I: Air Pollutants Exposure Model (APEX, version 3) User’s Guide. Office of Air Quality Planning and Standards, Research Triangle Park, NC. Av ailable electronically on the internet at: http://www.epa.gov/ttn/fera/human_apex.html

. U.S. EPA (2004). Air Quality Criteria for Particulate Matter. EPA 600/P-99/002bF, 2v. National Center for Environmental Assessment, Research Triangle Park, NC . Available electronically on the internet at: http://www.epa.gov/ttn/naaqs/standards/pm/s_pm_cr_cd.html

U.S. EPA (2005a). Health Assessment Plan for Review of the National Ambient Air Quality Standards for Ozone.5-104 Office of Air Quality Planning and Standards, Research Tr iangle Park, NC. April. Available electronically on the internet at http://www.epa.gov/ttn/naaqs/standards/ozone/s_o3_cr_pd.html

. U.S. EPA (2005b). Review of National Ambient Air Qu ality Standards for Particulate Matter: Assessment of Scientific and Technical Information - OAQPS Staff Pa per. EPA-452/D-05-001. Office of Air Quality Planning and Standards, Research Triangle Park, NC. Available electronically on the internet at: http://www.epa.gov/ttn/naaqs/standards/pm/s_pm_cr_sp.html

. U. S. EPA (2006a). Air Quality Criteria for Ozone and Ot her Related Photochemical Oxidants. National Center for Environmental Assessment, Research Triangle Park, NC . Available electronically on the internet at: http://cfpub.epa.gov/ncea/cfm/r ecordisplay.cfm?deid=137307

U. S. EPA (2006b). Ozone Population Exposure Analys is for Selected Urban Areas. Office of Air Quality Planning and Standards, Research Triangle Park, NC. December. Available electronically on the internet at: http://www.epa.gov/ttn/naaqs/standards/ozone/s_o3_cr_td.html

.
Whitfield, R., Biller, W., Jusko, M., and Keisler, J. (1996). A Probabilistic A ssessment of Health Risks Associated with Short- and Long-Term Exposure to Tropospheric Ozone. Argonne National Laboratory, Argonne, IL.

Whitfield, R. (1997). A Probabilistic Assessment of Health Risks Associated with Short-term Exposure to Tropospheric Ozone: A Supplement. Argonne National Laboratory, Argonne, IL.

Whitfield, R.G., Richmond, H.M. and Johnson, T.R. (1998). “Overview of Ozone Human Exposure and Health Risk Analyses Used in the U.S. EPA’s Review of the Ozone Air Quality Standard,” pp.483-516 in: T. Schneider, ed. Air Pollution in the 21 st Century: Priority Issues and Policy Elsevier; Amsterdam.6-1 

### 6. STAFF CONCLUSIONS AND RE COMMENDATIONS ON THE PRIMARY O 3 

### NAAQS

6.1 INTRODUCTION This chapter presents staff conclusions and recommendations for the Administrator to consider in deciding whet her the existing primary O 3 standard should be re vised and, if so, what revised standard is appropriate. Our conc lusions and recommendations are based on the assessment and integrative synthesis of informa tion presented in the CD, staff analyses and evaluations presented in Chapters 2 through 5 herein, and the comments and advice of CASAC and interested parties who commented on earlier drafts of this documen t and related technical support documents. In recommending policy options for the Admi nistrator’s considera tion, we note that the final decision on retaining or revising the current O 3 standard is largely a public health policy judgment. A final decision should draw upon scien tific information and analyses about health effects, population exposure and risks, as well as judgments about the appr opriate response to the range of uncertainties that are i nherent in the scientific evidence and analyses. Our approach to informing these judgments, discussed more fully below, is based on a recognition that the available health effects evidence generally reflec ts a continuum consisting of ambient levels at which scientists generally agree that health effects are likely to occur through lower levels at which the likelihood and magnitude of the re sponse become increasingly uncertain. This approach is consistent with the re quirements of the NAAQS provisions of the Act and with how EPA and the courts have historically interpreted the Act. These provisions require the Administrator to establish primary standard s that, in the Administrator's judgment, are requisite to protect public health with an ad equate margin of safety. In so doing, the
Administrator seeks to establish standards that ar e neither more nor less stringent than necessary for this purpose. The Act does not require that primary standards be set at a zero -risk level but rather at a level that avoids unacceptable risks to public health, including the health of sensitive

groups.

6.2 APPROACH

To evaluate whether it is appropriate to consider re taining the current primary O 3 standard, or whether considerati on of revisions is appropriate, we adopted an approach in this review that builds upon the general approach used in the last re view and reflects the broader body of evidence now available. The 1997 final decision notice (62 FR 38856) outlined the key factors considered in selecting th e elements of a standard for O 3 (judged to be the most6-2 appropriate indicator for photochemi cal oxidants): the averaging tim e; the level (i.e., an ambient

O 3 concentration); and the form (i.e., the air qua lity statistic used as a basis for determining compliance with the standard). Decisions on th ese elements were based on an integration of
information on acute and chronic health eff ects associated with exposure to ambient O 3 ; expert judgments on the adversity of such effects on i ndividuals; and policy judg ments as to when the standard is requisite to protect public health wi th an adequate margin of safety, which were informed by air quality analysis and quantitative exposure and ri sk assessments when possible, as well as qualitative assessment of public he alth impacts that could not be quantified. As in the last review, in developing conclusions and r ecommendations on the primary O 3 standard in this review, staff has taken in to account both evidence- based and quantitative exposure- and risk-based considerations. Evid ence-based considerations include the assessment of evidence from controlled human exposure, an imal toxicological, fiel d, and epidemiological studies for a variety of health endpoints. For those endpoints based on epidemiological studies, we have placed greater weight on associations with health endpoint s that the CD has judged to be likely causal based on an integrativ e synthesis of the entire body of evidence, including not only all available epidemiological evidence but al so evidence from animal toxicological and controlled human exposure studies. Less weight has been placed on evidence of associations that were judged to be only suggestive of po ssible causal relationships . For the purpose of evaluating the level of the O 3 standard in this review, we have placed greater weight on U.S. and Canadian studies, taking into acc ount the extent to which such st udies have reported statistically significant associations. This is because findings of U.S. and Cana dian studies are more directly applicable for quantitative consider ations in this review as studi es conducted in other countries may well reflect quite different popula tions, exposure characteristics, and air pollution mixtures. Staff’s consideration of quantitative exposure- and risk-based information draws from the results of the exposure and risk assessments conducted for as many as twelve urban areas in the U.S. (discussed in Chapters 4 and 5). More sp ecifically, we have considered estimates of the magnitude of O 3 -related exposures and risks associated w ith recent air quality levels, as well as the exposure and risk reductions likely to be a ssociated with just meeting the current 8-hr primary O 3 NAAQS and potential alternative 8-hr st andards. We rec ognize the uncertainties inherent in such estimates, which are discussed in Chapters 4 and 5, in part by providing where possible some sense of the direct ion and/or magnitude of the uncer tainties which should be taken
into account as one c onsiders these estimates. In this review, a series of general questions frames our approach to reaching conclusions and recommendations in section 6.3 below, based on the available evidence and information, as to whether consideration should be given to retaining or revising the current primary O 36-3 standard. Our review of the adequacy of th e current standard in section 6.3.1 begins by addressing questions such as the following:

• To what extent does newly available info rmation reinforce or call into question evidence of associations of O 3 exposures with effects identified in the last review?

• To what extent has evidence of new eff ects and/or sensitive populations become available since the last review?

• To what extent have important uncertainties identified in th e last review been reduced and have new uncertainties emerged?

• To what extent does newly available informa tion reinforce or call into question any of the basic elements of the current standards? To the extent that the available information sugge sts that revision of the current standard may be appropriate to consider, we al so explore whether the currentl y available information supports
consideration of a standard that is either mo re or less protective by addressing the following questions:

• Is there evidence that associations, especi ally likely causal as sociations, extend to ambient O 3 concentration levels that are as low as or lower than had previously been observed, and what are the important uncerta inties associated with that evidence?

• Are exposures of concern and health risks es timated to occur in areas upon meeting the current standard; are they important from a public health perspectiv e; and what are the important uncertainties associated with the estimated risks? To the extent that there is support for c onsideration of a revised standard, we then consider the specific elements of the standard (in terms of an indicator for photochemical oxidants, averaging time, level, and form in sections 6.3.2 through 6.3.5, respectively) and identify policy options that we conclude would be appropriate fo r the Administrator to consider in making public health policy judgments, based on the currently available information, as to the degree of protection that is requisit e to protect public he alth with an adequate margin of safety. In so doing, we address the following questions:

• Does the evidence provide support for considering a different O 3 indicator?

• Does the evidence provide support for c onsidering different averaging times?

• What ranges of levels and forms of alternat ive standards are supported by the evidence, and what are the uncertainties and limitations in that evidence?

• To what extent do specific levels and fo rms of alternative standards reduce the estimated exposures of concern and risks attributable to O 3 and other photochemical6-4 oxidants, and what are the uncertainties associ ated with the estimated exposure and risk reductions? A summary of staff conc lusions and recommendations on policy options for the
Administrator’s consideration c oncerning whether and, if so, how to revise the current primary

O 3 standard is presented in se ction 6.3.6. This chapter conclu des with a discussion of key uncertainties and recommendations for additional research related to setting a primary O 3 standard in section 6.4.

6.3 PRIMARY O 3 STANDARD The current primary O 3 standard is an 8-hr standard set at a level of 0.08 ppm, with a form of the annual fourth-highest daily maxi mum 8-hr average concentration, averaged over three years, to provide protecti on to the public, especia lly children and othe r at-risk populations, against a wide range of O 3 -induced effects. As an introduction to the discussion in this section of the adequacy of the current O 3 standard and potential options for alternative standards, it is useful to summarize the key factors that formed th e basis of the decision in the last review to revise the averaging time, level, and fo rm of the then curr ent 1-hr standard. In the last review, the key f actor in deciding to revise the averaging time of the primary
standard was evidence from controlled human exposure studies of healthy young adult subjects exposed for 1 to 8 hr to O 3 . The best documented health en dpoints in these studies were decrements in indices of lung function, such as forced expiratory volume in 1 second (FEV 1 ), and respiratory symptoms, such as cough and ches t pain on deep inspira tion. For short-term exposures of 1 to 3 hr, group mean FEV 1 decrements were statistically significant for O 3 concentrations only at and above 0.12 ppm, a nd only when subjects engaged in very heavy exertion. By contrast, prolonged exposures of 6 to 8 hr produced statis tically significant group

mean FEV 1 decrements at the lowest O 3 concentrations evaluated in those studies, 0.08 ppm, even when experimental subjects were engaged in more realistic intermittent moderate exertion levels. The health significance of this newer ev idence led to the conclusion in the 1997 final decision that the 8-hr averaging tim e is more directly associated w ith health effects of concern at
lower O 3 concentrations than is the 1-hr averaging time.
Based on the available evidence of O 3 -related health effects, the following factors were of particular importance in the last review in in forming the selection of the level and form of a new 8-hr standard: (1) quantitative estimates of O 3 -related risks to active children, who were judged to be a sensitive subgroup of concern, in terms of transient and reversible respiratory effects judged to be adverse, including moderate to large decreases in lung function and moderate to severe pain on deep inspiration, and the uncertainty and variability in such estimates; (2) consideration of both the estimate d percentages, total numbers of children, and6-5 number of times they were likely to experien ce such effects; (3) epidemiological evidence of
associations between ambient O 3 and increased respiratory hospital admissions, and quantitative estimates of percentages and to tal numbers of asthma-related ad missions in one example urban area that were judged to be indicative of a pyramid of much larger effect s, including respiratoryrelated hospital admissions, emergency department (ED) visits, doctor visits, and asthma attacks and related increased medication use; (4) quantit ative estimates of the number of “exposures of concern” (defined as exposures > 0.08 ppm for 6 to 8 hr) that active children are likely to experience, and the uncertainty and variability in such estimates; (5) the judgment that such exposures are an important indicator of public health impacts of O 3 -related effects for which information is too limited to develop quantitativ e risk estimates, including increased nonspecific bronchial responsiveness (e.g., rela ted to aggravation of asthma), decreased pulmonary defense mechanisms (suggestive of increased susceptibilit y to respiratory infectio n), and indicators of pulmonary inflammation (related to potential ag gravation of chronic bronchitis or long-term damage to the lungs); (6) the broader public heal th perspective of the num ber of people living in
areas that would breathe cleaner air as a result of the revised standard; (7 ) consideration of the
relative seriousness of various hea lth effects and the relative de gree of certainty in both the likelihood that people will experien ce various health effects and their medical significance; (8) the relationship of a standard level to estimated “background ” levels associated with nonanthropogenic sources of O 3 ; and (9) CASAC advice and recommendations. Additional factors that were considered in selecting the fo rm of the standard included the public health implications of the expected number of times in an O 3 season that the standard level might be
exceeded in an area that is in atta inment with the standard and the year-to-year stability of the air quality statistic, so as to avoi d disruptions to ongoing contro l programs which could interrupt public health protections. In reaching a final decision in the last re view, the Administrator was mindful that O 3 exhibits a continuum of effects, such that th ere is no discernible thre shold above which public health protection requires that no exposures be allowed or below which all risks to public health
can be avoided. The final decision reflected a re cognition that important uncertainties remained, for example with regard to interpreting the role of other pollutant s co-occurring with O 3 in observed associations, understand ing biological mechanisms of O 3 -related health effects, and estimating human exposures and quan titative risks to at-risk populations for these health effects.

6.3.1 Adequacy of Current O 3 Standard Overall, the new evidence available in this review generally supports and builds further upon key health-related conclusions drawn in the pr evious review. New hu man clinical studies provide information about lung function and re spiratory symptom responses to prolonged6-6 exposures at O 3 levels at and below 0.08 ppm. There is an expanded body of evidence about the mechanisms of respiratory effects, includi ng important new evidence about increased susceptibility of people with asthma and limite d new evidence about plausible mechanisms by
which O 3 exposure could induce effects on the cardiovasc ular system. In this review, there is additional epidemiological evidence supporting associations between O 3 exposure and respiratory symptoms in asthmatic children, ED visits and hospital admissions for respiratory causes, and new evidence that links O 3 exposure to premature mortality. As discussed in Chapter 3, the CD concl udes that, based on the extensive body of human clinical, toxicological, and epidemiological ev idence, there is a causal relationship between
short-term O 3 exposure and a range of respiratory mo rbidity effects, including lung function decrements, increased respiratory symptoms, airway inflammation, and increased airway responsiveness. Aggregate popul ation time-series studies provi de evidence that ambient O 3 concentrations are positively and robustly associat ed with respiratory-related hospitalizations and ED visits during the warm season. The CD concl udes that the overall body of evidence supports a causal relationship be tween acute ambient O 3 exposures and these respiratory morbidity outcomes (CD, p. 8-77). Based on the evidence from animal toxicology, human clinical, and epidemiological studies, the CD concludes that a generally limited body of evidence provides considerable plausibility for cardiovascular mechanisms and is highly suggestive that O 3 can directly or indirectly contribute to cardiovasc ular-related morbidity, but that much needs to be done to more fully substantiate links between ambient O 3 exposures and adverse cardiovascular outcomes (CD, p. 8-77-78). The CD also finds that, consistent with observed O 3 -related increases in respiratory- and cardiovascular-re lated morbidity, several newer U.S. multi-city time-series studies, single-city studies, and se veral meta-analyses of these studies, provide relatively strong epidemiological evidence for associations between short-term O 3 exposure and all-cause (non-accidental) mortalit y, even after adjustment for th e influence of season and PM (CD, p. 8-78). In considering this evidence as a basis fo r evaluating the adequacy of the current O 3 standard, we recognize that important uncertainties remain. For example, as discussed above in section 3.4, we note that inherent limitations in time-series epidemiological studies raise questions about the utility of such evidence to inform j udgments about a NAAQS for an individual pollutant such as O 3 within a mix of highl y correlated pollutants, such as the mix of photochemical oxidants, especially at ambient O 3 concentrations below levels at which O 3 - related effects have been observe d in controlled human exposure stud ies. We also recognize that the available epidemiological evid ence neither supports nor refutes th e existence of thresholds at the population level for effects such as increas ed hospital admissions and premature mortality. There are limitations in epidemio logical studies that make discer ning thresholds in populations6-7 difficult, including low data density in the lower concentration ranges, th e possible influence of exposure measurement error, and interindivi dual differences in susceptibility to O 3 -related effects in populations. While there clearly are limitations in interp reting the findings from the epidemiological studies, as noted above, we conclude for the following reasons that if a population threshold level does exist, it would likely be well below the level of the current O 3 standard and possibly within the range of background levels. This conclusion is supported by the discussions in Chapter 3 above (section 3.4.5) and more fully in the CD (Chapter 7, section 7.6.5) of the several epidemiological studies that have explored the question of potential thresholds and of the studies that included analyses exclud ing days over 0.08 ppm or even lower O 3 levels. We note that seasonal epidemiological studies show no consistent O 3 -related effects during the cold
season when O 3 concentrations are generally low, in c ontrast to a pattern of generally positive and statistically significant O 3 -related effects in the warm season when O 3 concentrations are generally appreciably higher. In addition to direct considerati on of the epidemiological studies, the findings from controlled human exposure st udies strongly suggest that both lung function decrements and respiratory symptoms occur in hea lthy adult subjects at le vels down to at least 0.060 ppm (+/- 0.003 ppm) with some subjects experiencing notable effects (e.g., >10% FEV 1 decrement, pain on deep inspiration). Controll ed human exposure studie s also found significant responses in indicators of l ung inflammation and cell injury at 0.080 ppm (+/- 0.004 ppm) in healthy adult subjects. These effects were observed in healthy young adult subjects and it is likely that greater responses and responses at lower levels woul d occur in people with asthma and other respiratory diseases. As discussed in Chapter 3, the physiological effects observed in controlled human exposure studies have been linked to aggravation of asthma and increased susceptibility to respiratory inf ection, potentially leading to incr eased medication use, increased school and work absences, increased visits to doc tors’ offices and emergency departments (EDs), and increased hospital admissions. These obs ervations provide additional support for the
conclusion that the associations observed in the epidemiological studies, particularly for respiratory-related effects and potentially for card iovascular effects, extend down to ozone levels well below 0.084 ppm.
Based on the above considerations and findi ngs from the CD, while being mindful of important remaining uncertainties, staff concludes that the newly available information generally reinforces our judgments about causal relationships between O 3 exposure and respiratory effects
observed in the last review a nd broadens the evidence of O 3 -related associations to include additional respiratory-related endpoints, newly identified card iovascular-related health endpoints, and mortality. Newly available evidence also has id entified increased susceptibility in people with asthma. While rec ognizing that importan t uncertainties and research questions6-8 remain, we also conclude that progress has been made since the last review in advancing the understanding of potential m echanisms by which ambient O 3 , alone and in combination with other pollutants, is causally linked to a range of respiratory- and cardiov ascular-related health endpoints. Thus, we generally find support in the available evid ence, including the direction of the evidence developed since the last review, for consideration of an O 3 standard that is at least as protective as the current standard and do not find support for consideration of an O 3 standard that is less protective than the current standard. This general conclusion is consistent with the
advice and recommendations of CASAC and with the views expressed by a ll interested parties who provided comments on the previous draft of this document. While CASAC and some commenters supported revising th e current standard to prov ide increased public health protection, and other commenters supported retaining the current standard, no one who provided comments supported a standard th at would be less protective than the current standard. Having reached this general conclusion, we disc uss in greater detail below the available evidence (section 6.3.1.1) and exposure- and risk-b ased considerations (section 6.3.1.2) to more fully inform consideration of the adequacy of the current standa rd. We also take into account the views expressed by CASAC and public comm enters (section 6.3.1.3) in reaching staff conclusions on the adequacy of th e current standard (section 6.3.1.4).

6.3.1.1 Evidence-based Considerations In looking more specifically at the controlled human e xposure and epidemiological evidence summarized in Chapter 3 and Appendix 3B, staff first notes that controlled human exposure studies provide the clearest and most compelling evidence for an array of human health effects that are directly attrib utable to acute exposures to O 3 per se (CD, p. 8-73). We also note that evidence from such human studies, together with animal toxicol ogical studies, help to provide biological plausibility for health eff ects observed in epidemiological studies. In considering the available evidence, we have focuse d on studies that examined health effects that have been demonstrated to be caused by exposure to O 3 or for which the CD judges associations
with O 3 to be causal or likely causal. In consider ing the epidemiological evidence as a basis for reaching conclusions about the adequacy of the current standard, we have focused on studies reporting effects in the warm season, for which the effect estimates are more consistently positive and statistically significant than those fro m all-year studies. We have considered the extent to which such studies provide evidence of associations that extend down to ambient O 3 concentrations below the level of the current standard, which would call into question the adequacy of the current standar d. In so doing, we note, as disc ussed above, that if a population
threshold level does exist for an effect observed in such studies, it would likely be at a level well
below the level of the current stan dard. We have also sought to characterize whether the area in6-9 which a study was conducted likely would or woul d not have met the current standard during the time of the study, although we recognize that the confidence that would a ppropriately be placed on the associations observed in any given study, or on the extent to which the association would likely extend down to relatively low O 3 concentrations, is not depe ndent on this distinction. Further, we have considered stud ies that examined subsets of da ta that include only days with
ambient O 3 concentrations below the level of the current O 3 standard, or below even lower O 3 concentrations, and continue to re port statistically signi ficant associations. We judge that such studies are directly relevant to considering the ad equacy of the current st andard, particularly in light of reported responses to O 3 at levels below the current st andard found in controlled human exposure studies. In examining air quality information from th e epidemiological studies for the purpose of determining whether they were conducted in area s that likely would or would not have met the current standard, we note that it is difficult to consistently characterize relevant air quality
statistics. 1 These difficulties arise in particular in panel studies of lung function or respiratory symptoms in which the study periods we re often shorter than a complete O 3 season; Appendix
3B includes 98 th and 99 th percentile values as a way to appr oximate the fourth-highest value for studies with differing study periods . Difficulties also arise in all studies in which the air quality data were averaged across multiple monitors in a study area (as are re ported in Appendix 3B),
since an area’s attainment status is dete rmined by the monitor measuring the highest O 3 concentrations in an area, not averaged across monitors. For studies with relatively low air quality values that are based on averaging across multiple monitors, we have further explored the available air quality data so as to help inform a comparison with the level of the current standard,
as discussed below.

Lung Function, Respiratory Symptoms, and Other Respiratory Effects
Health effects for which the CD continues to find clear evidence of causal associations
with short-term O 3 exposures include lung function d ecrements, respiratory symptoms, pulmonary inflammation, and increased airway re sponsiveness. In the last review, these O 3 - induced effects were demonstrated with statistical significance down to the lowest level tested in controlled human exposure studies at that time (i.e., 0.08 ppm). As discussed in Chapter 3 (section 3.3.1.1.1), in new controlled human expos ure studies, healthy adult volunteers were exposed to 6.6-hr average O 3 levels down to lower levels (i.e., 0.04 and 0.06 ppm) while engaged in moderate exertion. These studies did not repo rt statistically signifi cant changes in the group

mean FEV 1 decrements between lung function decrem ents associated with the 0.06 ppm or 0.04

1 Determining attainment with the current standard is based on the 3-year average of the annual (over an O 3 season) fourth-highest daily maximum 8-hr average O 3 concentration at each monitor in an area.6-10 ppm levels versus the filtered air (i.e., essentially 0 ppm O 3 ) exposure when lung function changes were analyzed for each hourly interval (i.e., after 1, 2, 3, 4.6, 5.6, and 6.6 hours of exposure). However, as discussed in Secti on 3.3.1.1.1, we note that the pre- and post-exposure data presented in the Adams (2006) study show a small (< 3%) group mean FEV 1 decrement following the 6.6-hr exposure at 0.06 ppm, which ma y be statistically significantly different from filtered air responses. Notably, total respirat ory symptoms (which includes pain on deep inspiration, shortness of br eath, and cough) following 5.6 and 6.6 h exposures at 0.06 ppm (during a triangular exposure patt ern, that is more representative of those encountered in summer air pollution episodes than a square-wave exposure pattern) r eached statistical significance. In addition to information about group mean decrem ents, this study also reports that a small percentage (7%) of healthy adult subjects expe rienced moderate lung function decrements ( ≥
10% FEV 1 ) with exposure to 0.06 and 0.04 ppm O 3 when corrected for the effects of exercise in

clean air. The distribution of individual re sponses related to lung function decrements ( ≥ 10, 15,
and 20% FEV 1 ) found in these new studies are considered as part of the quantitative risk assessment for lung function responses in children discussed below. Newer information indicates that people with moderate-to-severe asthma have somewhat larger decreases in lung function in response to O 3 relative to healthy in dividuals and that lung function responses in people with asthma appear to be affected by baseline lung function (i.e., responses increase with increasing disease severity, CD, p. 8-80). As discussed in the CD (Chapter 6, sections 6.8 and 6.9; Chapter 8, sections 8.7 and 8.8) this newer information expands our understanding of the physiologica l basis for increased sensitivity in people with asthma and other airway diseases, recognizi ng that people with asthma pres ent a different response profile for cellular, molecular, and biochemical respons es than people who do not have asthma. New evidence indicates that some people with asth ma have increased occurrence and duration of nonspecific airway responsiveness, which is an increased bronchoconstric tive response to airway irritants. Controlled-human exposure studies also indicate that some peopl e with allergic asthma
and rhinitis have increased airway responsiveness to allergens following O 3 exposure. Exposures to O 3 exacerbated lung function decrements in people with pre-existing allergic airway disease, with and wit hout asthma. Ozone-induced exacer bation of airway responsiveness persists longer and attenu ates more slowly than O 3 -induced lung function decrements and respiratory symptom responses and can have importa nt clinical implicatio ns for asthmatics. Newly available human exposure studies suggest that some people with asthma also have increased inflammatory responses, relative to no n-asthmatic subjects, and that this inflammation may take longer to resolve. The new data on airway responsiveness, inflammation, and various
molecular markers of inflammation and bronchoc onstriction indicate that people with asthma and allergic rhinitis (with or without asthma) comprise susceptible groups for O 3 -induced6-11 adverse effects. This body of evidence qualitatively informs our evaluation of the adequacy of
the current O 3 standard in that it indicates that human clinical and epidemiological panel studies of lung function decrements and respiratory symp toms that evaluate only healthy, non-asthmatic subjects likely underestimate the effects of O 3 exposure on asthmatics and other susceptible populations. In addition to the experimental evidence of lung function decr ements, respiratory symptoms, and other respiratory effects in h ealthy and asthmatic populations discussed above, epidemiological studies have reported associatio ns of lung function decrements and respiratory symptoms in several locations (Appendix 3B; also Figure 3-4 for respiratory symptoms). As discussed in Chapter 3, two large U.S. studies (Mortimer et al., 2002 (the National Cooperative Inner-City Asthma Study (NCICAS )), Gent et al., 2003), as well as several smaller U.S. and international studies, have reported fairly robust associations between ambient O 3 concentrations and measures of lung function and daily symptoms (e.g., chest tightness, wheeze, shortness of breath) in children with moderate to severe asthma and between O 3 and increased asthma medication use. The NCICAS reported statistica lly significant increases in incidence of > 10% declines in morning lung function and respirat ory symptoms in asthmatic children for multi-day lags in 8-hr average O 3 concentrations in single pollutant models. For various co-pollutant models, the O 3 effect was attenuated, but there was still a positive association. Gent et al. (2003)
included asthmatic children in the area of sout hern New England and reported associations between various respiratory symptoms and bot h daily 1-hr maximum and 8-hr maximum O 3 levels for asthmatics who used maintenance medi cations and would be considered moderate to severe asthmatics, while not finding an associa tion for mild asthmatics, defined as not using
maintenance medication. In this study, effects of O 3 , but not PM 2.5 , remained statistically significant and even increased in magnitude in two-pollutant models (CD, p.7-53). The CD concludes that overall the multi-city NCICAS, Gent et al. (2003) and several other single-city studies indicate a fairly robust pos itive association between ambient O 3 concentrations and increased respiratory symptoms in asthmatics. We recognize, however, that uncertainties remain with regard to the relative contribution of O 3 and other co-pollutants, some of which show moderate correlations during the summer time, fo r the effects observed in asthmatic individuals. In considering the large number of single- city epidemiological studies reporting lung function or respiratory symptoms in healthy or asthmatic populat ions (Appendix 3B), we note that most such studies that reported positive and often statistically significant associations in the
warm season were conducted in ar eas with relevant air quality statistics th at are indicative of areas that likely would not have met the current standard (e.g., Gent et al., 2003; Ostro et al., 2001; Neas et al., 1995; Delfino et al, 1998; Linn et al., 1996; Korrick et al., 1998). In considering the large multi-c ity NCICAS (Mortimer et al., 2002), we note that the 98 th percentile6-12 8-hr daily maximum O 3 concentrations at the mo nitor reporting the highest O 3 concentrations in each of the study areas ranged from 0.084 ppm to > 0.10 ppm. The authors indicate that less than 5 percent of the days in the eight areas had 8-hr daily O 3 concentrations exceeding 0.080 ppm. The authors observed that when days with 8-hr average O 3 levels greater than 0.080 ppm were excluded, similar effect estimates were seen.
There also are other studies in which the re levant air quality statistics provide some indication that lung function and respiratory symptom effects ma y be occurring in areas that likely would have met the current standard (e.g., N aeher et al., 1999; Ross et al., 2002; Brauer et al., 1996). We note that this last group of studies reported associ ations that were often but not always statistically significant, and that Brauer et al. (1996) was an outdoor worker study of berry pickers with exposure patterns that w ould not be typical of the general population.

Respiratory Hospital Admissions and Emergency Department Visits As discussed in Chapter 3 (section 3.3.1.1.6), at the time of the last review, many timeseries studies indicated positive associations between ambient O 3 and increased respiratory hospital admissions and emergency room visits , providing strong evidence for a relationship
between O 3 exposure and increased exacerbations of preexisting lung disease at O 3 levels below
the level of the then current 1- hr standard. Analyses of data from studies conducted in the
northeastern U.S. indicated that O 3 air pollution was consistently and strongly associated with summertime respiratory hospital admissions (CD, section 8.4.4). Since the last review, new epidemiological studies have evalua ted the association between short-term exposures to O 3 and unscheduled hospital admi ssions for respiratory causes (CD, section 7.3.3). Large multi-city studies, as we ll as many studies from individual cities have reported positive and often statistically significant O 3 associations with total respiratory hospitalizations as well as asth ma- and COPD-related hospitaliza tions, especially in studies analyzing the O 3 effect during the summer or warm s eason. Analyses using multipollutant regression models suggest that copollutants generally do not confound the association between

O 3 and respiratory hospitaliz ations, and that the O 3 effect estimates were generally robust to PM adjustment in all-year and warm-season only data (CD, p. 7-79; Figure 7-12). The CD concludes that the evidence supports a causa l relationship between acute O 3 exposures and increased respiratory-related hospitalizations during the warm season (CD, p. 8-77). In looking specifically at U.S. and Canadian respiratory hospitali zation studies that reported positive and often statistically significant associations (and that either did not use GAM or were reanalyzed to address GAM-related prob lems), we note that many such studies were conducted in areas that likely w ould not have met the current O 3 standard, with many providing only all-year effect estimates, and with some repo rting a statistically significant association in the warm season (e.g., Schwartz (1996) – Cleveland). Of the studies that provide some indication6-13 that O 3 -related respiratory hospitalizations may be o ccurring in areas that likely would have met the current standard, we note that some are all- year studies (e.g., Sheppard et al., 2003; Yang et al., 2003), whereas others reported statistica lly significant warm-season associations (e.g., Burnett et al., 1997a, in 16 Canadian cities; and Burnett et al., 1997b, 2001, in Toronto). In further examining the relevant air quality statistics in the 16 Canadian citi es study (Burnett et al., 1997a), we observe that while the aggregated 98 th percentile O 3 concentration was calculated as 47 ppb (Appendix 3B), the fourth-highest values at the monitors reporting the highest O 3 concentrations in each of the cities ranged fr om approximately 35 to 110 ppb, making it difficult to determine the extent to which the reported associ ation can be attributed to effects occurring in areas that likely would have met the current U. S. standard. We also further examined the relevant air quality statistics in the Burnett et al. (1997b, 2001) st udies in Toronto. We observed that in one of those studies (Bur nett et al., 2001) the fourth-highest values at the highest monitor ranged from approximately 80 to 150 ppb across the years of the study (from 1980 to 1994). In the other study (Burnett et al., 1997b) the calculated 98 th percentile values averaged across the several monitors used in the study ranged from 62 to 64 ppb in each of the three years of the study (Appendix 3B), but individual monitor data were not availa ble for further examination. Based on these observations, we fi nd it difficult to judge the ex tent to which these studies provide evidence of an a ssociation with respiratory-related hospitalizations in areas that likely
would have met the current standard. Nonetheles s, as discussed above, we recognize that these studies do provide evidence of associations that likely extend down to relatively low ambient O 3 concentrations, well below the level of the current standard. Emergency department visits for respiratory causes have been the focus of a number of
new studies that have examined visits rela ted to asthma, COPD, bronchitis, pneumonia, and other upper and lower respiratory infections, such as influenza, with asthma visits typically dominating the daily incidence counts (CD, section 7.3.2). Among studies with adequate controls for seasonal patterns, many reported at least one significant positive association involving O 3 . However, inconsistencies were observed wh ich were at least partially attributable to differences in model specifications and analys is approach among various studies. In general,

O 3 effect estimates from summer-only analyses tended to be positive and larger compared to results from cool season or all-year analyses. Almost all of the st udies that reported statistically significant effect estimates had calculated 98 th percentile O 3 concentrations (Appendix 3B), averaged across monitors, that ar e indicative of areas that likely would not have met the current standard. The notable exception were two studie s in Montreal (Delfino et al., 1997, 1998) that reported statistically significant warm-season associations with O 3 and ED visits in a population
of older adults with a calculated 98 th percentile value, averaged across several monitors, of approximately 60 ppb (and for which individual m onitor data were not available for further6-14 examination), although the CD raises questions about the plausibility of this result due to the low

O 3 concentrations and inconsistent results acro ss years and age groups. The CD concluded that analyses stratified by season generally s upported a positive asso ciation between O 3 concentrations and ED visits for asthma in the warm season. These studies provide evidence of effects in areas that likely would not have met the current standard, and evidence of associations that likely extend down to relatively low ambient O 3 concentrations.

Mortality
The 1996 CD concluded that an associ ation between daily mortality and O 3 concentrations for areas with high O 3 levels (e.g., Los Angeles) was suggested. However, due to a very limited number of studies available at that time, ther e was insufficient evidence to
conclude that the observed asso ciation was likely causal, and thus the possibility that O 3 exposure may be associated with mortality was not relied upon in the 1997 decision on the O 3 primary standard. Since the last review, as de scribed above, the body of evidence with regard to O 3 -related health effects has been expanded by animal, huma n clinical, and epidemiological studies, and now includes biologically plausible mechanisms by which O 3 may affect the cardiovascular system. In addition, there is stronger informa tion linking ozone to serious morbidity outcomes, such as hospitalization, that ar e associated with increased mo rtality. Thus, there is now a coherent body of evidence that describes a range of health outcomes from pulmonary function decrements to hospitalization and premature mortality. Newly available large multi-city studies designe d specifically to examine the effect of O 3 and other pollutants on mortality have provided much more robus t and credible information. The extended NMMAPS analysis included data from 95 U.S. cities and included an additional 6 years of data, from 1987-2000 (Bell et al., 2004), and significant associat ions were reported
between O 3 and mortality that were robust to adjustme nt for PM (CD, p. 7-100). Using a subset of the NMMAPS data set, Huang et al. (2005) fo cused on associations between cardiopulmonary mortality and O 3 exposure (24-hr average) during the su mmer season only. The authors report the increase in mortality per 20 ppb change in O 3 concentration using a 7-day distributed lag model was greater than the increase in mortal ity measured on the same day (CD, p. 7-92), suggesting that the effect of O 3 on mortality is immediate but also persists for several days. Using a case-crossover study design, Schwartz (2 005) assessed associations between daily maximum concentrations and mortality in 14 cities, matching case and control periods by temperature, and using data only from the wa rm season. The reported effect estimate was similar to time-series analysis results with adjustment for temperature, suggesting that
associations between O 3 and mortality were robust to th e different adjustment methods for temperature (CD, p. 7-93). Two of the recent mu lti-city mortality studies (Bell et al., 2004;6-15 Gryparis et al., 2004) have also re ported associations for multiple averaging times (CD, p. 8-38). Bell and colleagues (2004) reported an effect estimate for the association with 1-hr O 3 concentrations that was slightly la rger than that reported for 8-hr O 3 concentrations, and both were slightly larger than the association with 24-hr average O 3 , but the effect estimates did not differ statistically. One recent multi-city study (Bell et al., 2006) examined the shape of the concentrationresponse function for the O 3 -mortality relationship in 98 U.S. urban communities for the period 1987 to 2000 specifically to evaluate whether a “s afe” threshold level ex ists. Results from various analytic methods all indi cated that any threshol d, if it exists, would likely occur at very low concentrations, far below the level of the current O 3 NAAQS and other, lower international

O 3 standards, 2 and nearing background levels. Notably, in a subset analysis using only days that
were below the level of the current O 3 NAAQS, the O 3 -mortality association remained statistically significant with only a small change in the size of the effect es timate. Further, in a subset analysis based on 24-hr average O 3 concentrations, the effect estimates declined and lost statistical significance only when the maximu m daily average concentration included was < 10 ppb (Bell et al., 2006, p. 14 and Figure 2), which corresponds to daily maximum 8-hr average
concentrations in U.S. cities th at are within the range of background concentrations. The authors
conclude that “interventions to further reduce ozone pollution w ould benefit public health, even in regions that meet current regulatory standards and guide lines” (Bell et al., 2006, p. 3).
New data are also available from several single-city studies c onducted world-wide, as well as from several meta-analyses that have combined information from multiple studies. The majority of these studies suggest that there is an elevated risk of tota l non-accidental mortality associated with acute exposure to O 3 , especially in the summer or warm season when O 3 levels are typically high, with somewhat larger e ffect estimate sizes for associations with cardiovascular mortality (CD, p. 7-175). As s hown in Figure 7-21 of the CD, the results of recent publications show a pattern of positive, often statistically significant associations between
short-term O 3 exposure and mortality during the warm season (CD, p. 7-97). For example, statistically significant associ ations were reported in sout hern California (Ostro, 1995), Philadelphia (Moolgavkar et al ., 1995), Dallas (Gamble et al., 1998), and Vancouver (Vedal et al., 2003), as well as numerous studies conducted in other countries. In contrast, no evidence of an association was seen in a study conducted in Pittsburgh (Chock et al., 2000). In considering results from year-round analyses, there remains a pattern of positive results but the findings are

2 Other international 8-hr O 3 standards considered by Bell et al. (2006, Table 1) include the California standard of 0.070 ppm, the Canadian standard of 0.065 ppm, and the World Health Organization guideline and European Commission target value of approximately 0.061 ppm.6-16 less consistent. For example, st atistically significant associations were reported in Philadelphia (Moolgavkar et al., 1995) and Dallas (Gamble et al., 1998), while positive but not statistically significant associations were re ported in Detroit (Lippmann et al., 2000, reanalyzed in Ito, 2003), San Jose (Fairley, 1999, reanalyzed Fairley, 200 3), and Atlanta (Klemm et al., 2004). No evidence for associations was reported in Los Angeles (Kinney et al., 1995), Coachella Valley (Ostro et al., 2003), and St. Loui s and Eastern Tennessee (Dockery et al., 1992). In most singlecity analyses, effect estimates were not subs tantially changed with adjustment for PM (CD Figure 7-22, p. 7-101). Almost all single-city studies that show statistically significant associations with mortality had calculated 98 th percentile O 3 concentrations (Appendix 3B ) that are indicative of

O 3 levels that likely would not have met the curr ent standard. The notable exception was a study in Vancouver (Vedal et al., 2003) that reported a statistically significant warm-season association
with O 3 and total non-accidental mort ality that was robust in tw o-pollutant models, with a
calculated 98 th percentile value, averag ed across many monitors, of approximately 53 ppb. Upon further examination, the relevant air quality stat istics for each individual monitor in this study ranged from 57 to 59 ppb. This study provides evidence of an O 3 -related mortality association in
the warm season in an area with O 3 levels that were well below those that would have met the current standard. However, th e authors questioned whether O 3 , other gaseous pollutants, and PM may be acting as surrogate markers of pollutant mixes that contain more toxic compounds, since the low measured concentrations were unlikely, in their opinion, to cause the observed effects (CD, p.7-155). Another study done in Vancouver ove r a much longer time period (Villeneuve et al., 2003) did not provide evidence of O 3 -related mortality associations , but only all-year results were presented which may be more likely conf ounded by other pollutants than the warm-season results in Vedal et al. (2003). Three recent meta-analyses evaluated pot ential sources of heterogeneity in O 3 -mortality associations (Bell et al., 2005; Ito et al., 2005; Levy et al., 2005) . The CD (p. 7-96) observes common findings across all three analyses, in that al l reported that effect estimates were larger in warm season analyses, reanalysis of results usin g default GAM criteria did not change the effect estimates, and there was no strong evidence of confounding by PM (CD, p. 7-97). Bell et al. (2005) and Ito et al. (2005) both provided s uggestive evidence of publication bias, but O 3 - mortality associations remain ed after accounting for that pot ential bias. The CD (7-97) concludes that the “positive O 3 effects estimates, along with the sens itivity analyses in these three meta-analyses, provide evidence of a robust association between ambient O 3 and mortality.”
The CD finds that the results from U.S. multi-city time-series studies, along with the meta-analyses, provide relatively strong evid ence for associations between short-term O 3 exposure and all-cause mortality ev en after adjustment for the in fluence of season and PM (CD,6-17 p. 8-78). The results of these analyses indicate that copollutants gene rally do not appear to substantially confound the association between O 3 and mortality (CD, p. 7-103; Figures 7-22 and 7-23). In addition, several single-city studies observed positive associations of ambient O 3 concentrations with total nonaccidental and ca rdiopulmonary mortality. Finally, from those
studies that included assessment of associations with specific causes of death, it appears that
effect estimates for associations with cardiovas cular mortality are larger than those for total mortality; effect estimates for respiratory mo rtality are less consistent in size, possibly due to reduced statistical power in this subcategory of mortality (CD, p. 7-108). For cardiovascular mortality, the CD (Figure 7-25, p. 7-106) suggests th at effect estimates are consistently positive and more likely to be larger and statistically si gnificant in warm season analyses. The CD (p. 8- 78) concludes that these findings are highly suggestive that short-term O 3 exposure directly or indirectly contributes to non-accidental and cardiopulmonary-related mortality, but additional research is needed to more fully establish unde rlying mechanisms by which such effects occur.

6.3.1.2 Exposure- and Risk-based Considerations

In addition to the evidence-base d considerations, staff has al so considered exposures and
health risks estimated to o ccur upon meeting the current O 3 standard to help inform judgments about the extent to which expos ure and risk estimates may be judged to be important from a public health perspective, taking into account ke y uncertainties associated with the estimated exposures and risks. For this review, exposures have been estimated for people of all ages, school age children (ages 5-18), and asthmatic sc hool age children in 12 urban areas across the
U.S. 3 In this discussion we focu s particularly on the exposure estimates for all and asthmatic school age children while at moderate or gr eater exertion levels since these groups are particularly at risk for experiencing O 3 -related health effects due to the greater amount of time spent outdoors during the O 3 season engaged in relatively high levels of physical activity. With regard to the quantitative risk assessment, we have estimated th e occurrences of moderate or greater lung function decrements in all and asth matic school age children, respiratory symptoms
in children with moderate to severe asthma , respiratory-related hospital admissions, and nonaccidental and cardiorespiratory mo rtality. We have selected th ese particular health endpoints because they can be considered to be adverse to the health of individuals, either in single or with repeated occurrences, and the requisite data for the assessment are available. In making judgments as to when various O 3 -related effects become regarded as adverse to the health of individuals, staff has re lied upon the guidelines published by the American

3 As discussed in Chapter 4, since the proportion of ch ildren classified as “active” in the exposure analysis has been overestimated, in part due to uncertainty in the CHAD MET values, we have not discussed this population group in this chapter.6-18 Thoracic Society (ATS) and the ad vice of CASAC. As discussed in Chapter 3, the ATS (1985) has defined adverse respiratory health effects as medically si gnificant physiologic changes, which include acute changes such as those that interfere with the normal activity or acute respiratory illness, and longer-term changes such as progressive respiratory dysfunction, permanent respiratory injury, or in capacitating illness. Of the mo rbidity effects estimated in the risk assessment, hospital admissions are clearly adverse to the health of the individual. Recognizing that respiratory symp toms in moderate to severe as thmatic children are likely to cause increased medication use, interference with normal activities, or increased absences from school, occurrences of such sympto ms are considered to be advers e. For active healthy people, moderate lung function decrements would likely in terfere with normal activity for relatively few individuals within this group who are particularly responsive to O 3 exposures; whereas large functional responses would likely interfere with normal activiti es for a greater proportion of individuals within this group, such that even si ngle occurrences of la rge functional responses would be considered adverse under ATS guidelines. In judging the extent to which moderate lung function decrements are adverse, especially in healthy people, an additional factor that has been considered is whether these occur on a single occasion or repeatedly over the course of an

O 3 season. It has been judged that repeated occurrences of moderate responses, even in otherwise healthy individuals, may be considered to be adverse since they could well set the stage for more serious illness. For people w ith lung disease, even moderate lung function decrements would likely interfere with normal activity for many individuals within this group, and would likely result in additional and more frequent use of medication; large functional responses would likely interfere with normal activ ity for most individuals in this group and
would increase the likelihood that these indivi duals would seek medical treatment. Thus, occurrences of either moderate or large functi onal responses in people with lung disease would
be considered to be adverse to the health of individuals experi encing these effects. Beyond the health effects discussed above th at are included in the risk assessment, Chapter 3 discusses a broader array of O 3 -related health endpoints that are representative of a “pyramid of effects” that include various indicators of morbidity that could not be included in the risk assessment (e.g., school absences, increase d medication use, ED visits). Ozone-related effects that are judged to be impor tant indicators of this broade r array of health endpoints, and are thus potentially adverse to the individuals experiencing such effects, include: (1) increased nonspecific airway responsiveness which is related, for example, to aggravation of asthma, potentially leading to increased medication use, increased school and work absences, increased visits to doctors’ offices and EDs, and incr eased admissions to hospitals; (2) decreased pulmonary defense mechanisms which are suggestiv e of increased suscepti bility to respiratory infection, potentially leading to increased school and work absences , increased visits to doctors’6-19 offices and EDs, and increased admissions to hospitals; and (3) indicators of pulmonary inflammation which are related to aggravation of asthma, potentially leading to increased medication use, increased school and work absen ces, increased visits to doctors’ offices and EDs, and increased admissions to hospitals; in creased cellular permeability associated with inflammation may be a mechanism by which O 3 exposure can lead to cardiovascular system effects; and potential chronic eff ects such as chronic bronchitis or long-term damage to the lungs that can lead to reduced quality of life. Some perspective on the O 3 -related public health impacts of these types of effects are characterized based on the resu lts of the exposure analysis in
terms of estimates of the number of occurrences of “exposures of concern,” as discussed below. We estimated exposures and risks for the thr ee most recent years (2002 - 2004) for which data were available at the time of the analyses, as discussed in Chapters 4 and 5. Within this 3- year period, 2002 was a year with generally poorer air quality in most, but not all, areas and provides a generally more upper-end estimate of e xposures and risks, while 2004 was a year with generally better air quality in mo st, but not all, areas and provides a generally more lower-end estimate of exposures and risks. Exposure and risk estimates for the year 2003 generally fall between the estimates for 2002 and 2004. In presen ting these results, we note that the exposure analysis and risk assessment discussed in Chapte rs 4 and 5, respectively, identify a number of uncertainties, as highlighted below. With respect to the exposure analysis, the exposure modeling approach accounts for variability in ambient O 3 levels, demographic characteristic s, physiological attributes, activity patterns, and factors affecting microenvironmenta l concentrations. In our judgment the most important uncertainties affecting the exposure es timates are related to the modeling of activity patterns over an O 3 season, modeling micro-scal e variations in ambient concentrations (e.g., near roadways), and modeling air exchange rates in microenvironments. Another important uncertainty that does not directly affect estimates of exposure, but affects the characterization of how many exposures are associated with moderate or greater exertion, is the characterization of energy expenditure (i.e., measur ed in terms of METS - metabolic equivalents of work) for children engaged in various activ ities. As discussed in sec tion 4.3.4.7, the uncertainty in METS values carries over to the uncertainty of the mode led ventilation rates, which are important since they are used to classify exposures of potentially greater risk. A comprehensive picture of the uncertainty of the exposure model estimations has been developed through sets of comple mentary analyses addressing th ese different aspects of the overall uncertainty. An analysis was performed which accounts for the uncertainties associated with the microenvironment models and the ambient air quality data. Analyses have been conducted to address the remaining significant s ources of uncertainty: near-road exposures and the activity data. The uncertainty of the model st ructure (as distinct from uncertainty driven by6-20 uncertain model inputs) is judged to be less important than the un certainties of th e model inputs and parameters. Based on these analyses, relatively small uncertainties are associated with the
estimation of ambient concentrations and microe nvironment model parameters. Relatively larger uncertainties are associated with the representati veness of the CHAD activity diaries with respect to the specific cities and time pe riods modeled. The APEX mode l significantly underestimates the frequency of occurrences of individuals experiencing repeated 8-hour average exposures greater than 0.06, 0.07, and 0.08 ppm. While the frequency of repeated occurrences is significantly underestimated, we have more conf idence that the estimates for total number of occurrences (i.e., person days with exposures greater than 0.06, 0.07, and 0.08 ppm) are not biased. Section 4.6 provides a summary of the exposure modeling uncertainties; the details of this uncertainty analysis are desc ribed in Langstaff (2007). It is im portant to note that there have been significant improvements in several componen ts of the exposure model and in the inputs to the model (e.g., better characterization of the am bient air quality surface across each area, more complete data on air exchange rates, much la rger human activity database) relative to the exposure analysis conducted for the 1997 review. Thus, while we recognize and have considered the kind and degree of uncertain ties associated with the e xposure estimates, we believe, consistent with CASAC’s views (Henderson, 2006c ), that the exposure analysis represents a state-of-the-art modeling approach and the quality of the estimates is such that they are suitable to be used as an input to the decisions on the O 3 standard. As discussed in Chapter 5, uncertainties rela ted to the air quality data affect both the controlled human exposure studies-based and the ep idemiological studies-bas ed parts of the risk
assessment. These include uncertainties associated with the air quality adju stment procedure that was used to simulate just meeting the current and alternative 8-hr standards, and the uncertainties associated with estimating background O 3 concentrations for each lo cation. Based on sensitivity analyses conducted in the prior review, alterna tive air quality adjustment procedures had only a modest impact on the risk estimates. With re spect to uncertainties about estimated background concentrations, as discussed in section 5.4.3, alternativ e assumptions about PRB levels have a variable impact depending on th e location and standard analyzed in terms of the absolute magnitude of the risk estimates. Alternative assumptions about P RB levels have a greater impact
on risk estimates associated with more stringent 8-hr standards. However, the overall pattern of reductions, expressed in terms of percentage reduction relative to the current standard, is generally unaffected by alternativ e assumptions for PRB for most of the standards analyzed. With respect to the lung functi on part of the health risk assessment, key uncertainties
include uncertainties in the e xposure estimates for children engaged in moderate or greater exertion (noted above) and uncertainties associat ed with the shape of the exposure-response relationship, especially at le vels below 0.08 ppm, 8-hr averag e, where only limited data are6-21 available down to 0.04 ppm and there is an ab sence of data below 0.04 ppm. The uncertainty associated with the shape of the exposure-respons e relationship was considered using a Bayesian Markov Chain Monte Carlo approach as r ecommended by members of the CASAC panel (Henderson, 2006c). As discu ssed in section 5.3.2.5, the impact s of changing the functional form of the exposure-response relationship vari ed substantially. Changing from the 90% logistic/10% linear base case to the 80%/20% split generally ha d only a small impact for all school age children, with most risk estimates being within 5% of the base case estimates. The impacts of changing from the base case to th e 50% logistic/50% linear case were generally (although not always) larger. We observed greater changes for all school age children between the 50/50 split and the base case in terms of percent change in risk for two more stringent
alternative standards relative to the current standard. With re spect to the lung function risk estimates for asthmatic children, there were relatively small changes observed between the 50/50 split and the base case in the percent changes as sociated with two more stringent alternative
standards relative to th e current standard. With respect to the part of the health risk assessment based on effects reported in epidemiological studies, an important uncertainty fo r the mortality risk estimates is the extent to
which the associations reported between O 3 and non-accidental and cardi orespiratory mortality actually reflect causal relationshi ps. Other important uncertaintie s for this part of the risk
assessment include uncertainties (1) surrounding estimates of O 3 coefficients in concentrationresponse functions used in the assessment, (2) concerning the specification of the concentrationresponse model (including the shape of the relationship) and whether or not a population threshold or non-linear relationship exists within the range of c oncentrations examined in the studies, (3) related to the extent to which concentration-respon se relationships derived from studies in a given location and time when O 3 levels were higher or behavior and/or housing
conditions were different provide accurate representations of the relationships for the same locations with lower air quality distributions and different behavior and/or housing conditions, and (4) concerning the possible role of co-pollu tants which also may have varied between the time of the studies and the current assessment pe riod. For both parts of the risk assessment, statistical uncertainty due to sampling error has been characterized. As discussed in section 5.4.5, there are additional unquantified uncertainties including model uncertainty noted above. While we and CASAC have recognized the various uncertainties that are inherent in conducting such risk assessments, CASAC found th e health risk assessment to be “well done, balanced, and reasonably communicated” (Henders on, 2006c). We have considered the kind and
extent of uncertainties in the he alth risk estimates, but judge th at these estimates, discussed in Chapter 5 and in this chapter, are appropriate for consideration as an inpu t to the decisions on the

O 3 standard.6-22 The exposure and risk assessments estimated occurrences of exposures of concern and lung function decrements, respectivel y, in school-age children ages 5 to 18. Due to the increased amount of time spent outdoors engaged in relative ly high levels of physical activity, school-age children, as a group, are particular ly at risk for experiencing O 3 -related health effects. We report results for school-age children down to age five , but there is a trend for younger children to attend school. We are not taking these younger ch ildren into account in our analysis due to a
lack of information which would let us characteri ze this group of children. Some states allow 4- year-olds to attend kindergarten, and more than 40 states have preschool programs for children younger than five (Blank and Mitchell, 2001). In 2000, six percent of U.S. children ages 3 to 19 who attend school were younger than five years old (2000 Census Summary File 3, Table QTP19: School Enrollment). Clearly the estimates of exposures of concern and lung function decrements in school-age children would be higher had we been able to include this group of children in the exposure and risk assessments.

Exposure Assessment Results The results of exposure assessments, which provide estimates of the number of people exposed to different levels of ambient O 3 while at prescribed exertion levels, serve two purposes. First, the entire range of modele d personal exposures to ambient O 3 is an essential input to the risk assessments based on exposure-response func tions from controlled human exposure studies. Secondly, estimates of persona l exposures to ambient O 3 levels at and above specific benchmark concentrations provide some pers pective on the public health impacts of health effects that we cannot currently evaluate in quant itative risk assessments that may occur at current air quality levels, and the extent to which such impacts might be reduced by meeting the current and alternative standards. This is especially true when there are exposure leve ls at which we know or can reasonably infer that specific O 3 -related health effects are occu rring. We refer to exposures
at and above these benchmark concentr ations as "exposures of concern." Estimating exposures of concern is important because it provides some indication of the potential public health impacts of a range of O 3 -related health outcomes, such as pulmonary inflammation, increased airway responsiv eness, or changes in host defenses. 4 These particular

4 We note that estimates of the number of people likely to experience exposures of concern can not be directly translated into quantitative estimates of the number of people likely to experience specific health effects, since sufficient information to draw such comparisons is not available -- if such information were available, we would have included these health outcomes in the quantitative risk assessment As discussed in section 3.3.1.1.3, the studies reporting inflammatory responses and markers of lung injury have clearly acknowledged that there is significant variation in responses of subjects exposed, especially to 6.6 hour O 3 exposures at 0.08 and 0.10 ppm. To provide some perspective on th e public health impacts of thes e health effects, we note th at one study (Devlin et al., 1991, Figure 5), for example, showed that roughly 10 to 50% of the 18 young healthy adult subjects in the study experienced notable increases (i.e., > 2 fold increase) in most of the inflammatory and cellular injury indicators6-23 effects have been demonstrated in controlled human exposure stud ies of healthy individuals to occur at levels as low as 0.08 ppm O 3 , but have not been evaluated at lower levels in controlled human exposure studies. We have not estimated these effects in a quant itative risk assessment due to the lack of adequate information on the overall exposure-response relationships. For the exposure analysis in the second dr aft Staff Paper, an exposure of concern was defined the same way as it was in the 1997 review, i. e., an 8-hr average exposure > 0.08 ppm O 3 while engaged in intermittent moderate or greater exertion leve ls (62 FR 38860). However, at the August 2006 CASAC meeting, the CASAC O 3 Panel encouraged staff to also consider exposures of concern at levels lower than 0.08 ppm, e xpressing the view that there is a range of health effects that likely occur below the lowest le vel tested for these effects (U .S. EPA 2006e, p.104-105). There
is no reason to assume that there is a threshold for effects, such as markers of inflammation, at 0.08 ppm O 3 . Moreover, Panel members noted there is evidence of adverse effects that are strongly correlated with pulmonary inflammation, such as ED visits observed in epidemiological studies, at levels we ll below 0.08 ppm. We concur with these views, and note that exposures of concern, a nd the health outcomes they represent, likely oc cur across a range of O 3 exposure levels, such that there is no one exposure level that addresses all relevant public h ealth concerns. Therefore, we have estimated exposures of concern not only at 0.080 ppm O 3 , a level at which there are demonstrated effects, but also at 0.070 and 0.060 ppm O 3 , recognizing that there is no apparent threshold for O 3 health effects and that potentially a dverse lung function decrements have been demonstrated in controlled human exposure studies of healthy individuals at 0.060 + 0.003 ppm O 3 . Moreover, there will be varying degrees of c oncern about exposures at each of these levels, based in part on the population subgroups experiencing them. For exam ple, it is reasonable to conclude that a high degree of protection is warra nted against effects that have been clearly demonstrated in healthy people, not only for the general public, but especially for members of sensitive subgroups, such as children or people with asth ma and other lung diseas es. At levels where
effects have not been demonstrat ed in controlled human exposure studies but there is reason to infer that effects likely occur, or where the evidence is less clear, the appropriate level of protection will depend on the strength of the evidence and the adversity of the effect. At comparable levels of uncertainty in the evidence , it is important to pr ovide stronger protection against effects that are more clear ly adverse. Given that there is clear evidence of inflammation, increased airway responsiveness, and changes in host defenses in healthy people exposed to

0.080 + 0.004 ppm O 3 and reason to infer that such eff ects will continue at lower exposure

analyzed associated with 6.6- hour exposures at 0.08 ppm. We also note that susceptible subpopulations such as those with asthma may be even more affected.6-24 levels, but with increasing uncertainty about the extent to which such effects occur at lower O 3 concentrations, in the following discussion we present information on all three levels of exposures of concern, with a focus on exposures of concern at levels ≥ 0.070 and > 0.060 ppm
O 3
. Exposure estimates for 6 scenarios (i.e., r ecent air quality for each of the three years examined, 2002 to 2004, and just meeting the curren t standard in each of the same three years based on adjusting air quality in this three-year period to determine the amount of adjustment needed) aggregated across 12 urban areas, have been developed for each of these exposure-ofconcern levels. These estimates are shown in Table 6-1. The exposure estimates are for the number and percent of people exposed, in each of the population subgroups, and the number of person-days (occurrences) of exposures, with dail y 8-hr maximum average exposures at or above 0.080 ppm (Table 6-1a), 0.070 ppm (Table 6-1b ), and 0.060 ppm (Table 6-1c), while at intermittent moderate or greater exertion. 5 As shown in Table 6-1, the patterns of exposures in terms of percentages of the population exceeding a given exposure level are ve ry similar for the general population and for all and asthmatic school age (5-18) children, alth ough children are about twice as likely to be exposed, based on the percent of the population e xposed, at any given level. Thus, in the discussion below, we focus on the patterns obser ved for all school age children, which includes asthmatic children, with the recognition that these exposure patterns apply to this other subpopulation. While Table 6-1 shows aggregate resu lts, it is important to note that there is substantial variability in th e percent of the population subg roups estimated to experience exposures of concern across the 12 urban areas. For example, in the case of exposures of

concern ≥ 0.070 ppm O 3 , for 2002 when the current standard is just met, while the aggregate estimate is 18% (Table 6-1b), the estimates of expo sures for all children range from about 1% to more than 35% of the population across the 12 urban areas analyzed (see Figure 4-7). Variability in the degree of health protection offe red across urban areas is an important factor to consider in evaluating the adequacy of the current standard.

5 Information in Table 6-1 is drawn from Appendix 4A.6-25Table 6-1a. Summary of Estimates of Number of People Exposed and Number ofOccurrences1 at Moderate Exertion2Associated with 8-Hour Daily Maximum Ozone Concentrations > 0.080 ppm for 12 Urban Areas in the U.S.General Population(88.5 million people)All Children (5-18 years old)(18.3 million children)Asthmatic Children (5-18 years old)(2.6 million children)Air QualityScenarioPersons(% of population)Person Days[% change fromrecent air quality]Persons(% of population)Person Days[% change fromrecent air quality]Persons(% of population)Person Days[% change fromrecent air quality]2002 Air QualityRecent Air Quality10,790,000(12%)15,030,0004,130,000(23%)6,030,000 630,000(24%)940,000Just MeetingCurrent Standard2,020,000(2%)2,270,000[85% reduction]700,000(4%)800,000[87% reduction]110,000(4%)130,000[86% reduction]2003 Air QualityRecent Air Quality5,970,000(7%)8,320,000 2,430,000(13%)3,500,000 340,000(13%)470,000Just MeetingCurrent Standard470,000(0.5%)480,000[94% reduction]160,000(0.9%)140,000[95% reduction]20,000(1%)30,000[95% reduction]2004 Air QualityRecent Air Quality2,350,000(3%)3,000,000 910,000(5%)1,180,000 130,000(5%)170,000Just MeetingCurrent Standard80,000(0.1%)90,000[97% reduction]30,000(0.1%)30,000[98% reduction]3,000(0.2%)3,000[98% reduction]1Estimates for persons and person days are rounded to the nearest10,000. Percentages greater than or equal to 1 are rounded tothe nearest percent andpercentages less than one arerounded to the nearest tenth.2Moderate exertion is defined as havingan 8-hr average equivalent ventilationrate (EVR) in the range 13-27 l-min/m2.6-26Table 6-1b. Summary of Estimates of Numberof People Exposed and Number of Occurrences1at Moderate Exertion2Associated with 8-Hour DailyMaximum Ozone Concentrations >0.070 ppm for 12 Urban Areas in the U.S.General Population(88.5 million people)All Children (5-18 years old)(18.3 million children)Asthmatic Children (5-18 years old)(2.6 million children)Air QualityScenarioPersons(% of population)Person Days[% change fromrecent air quality]Persons(% of population)Person Days[% change fromrecent air quality]Persons(% of population)Person Days[% change fromrecent air quality]2002 Air QualityRecent Air Quality22,770,000(26%)44,050,0008,550,000(47%)18,500,0001,280,000(50%)2,830,000Just MeetingCurrent Standard8,890,000(10%)12,350,000[72% reduction]3,340,000(18%)4,880,000[74% reduction]520,000(20%)770,000[73% reduction]2003 Air QualityRecent Air Quality14,100,000(16%)24,390,000 5,510,000(30%)10,380,000 790,000(31%)1,430,000Just MeetingCurrent Standard2,480,000(3%)2,710,000[89% reduction]1,000,000(5%)1,090,000[90% reduction]150,000(6%)160,000[89% reduction]2004 Air QualityRecent Air Quality7,660,000(9%)12,040,0003,020,000(17%)5,020,000440,000(17%)710,000Just MeetingCurrent Standard720,000(0.8%)770,000[94% reduction]260,000(1%)270,000[95% reduction]40,000(1%)40,000[95% reduction]1Estimates for persons and person days are rounded to the nearest10,000. Percentages greater than or equal to 1 are rounded tothe nearest percent andpercentages less than one arerounded to the nearest tenth.2Moderate exertion is defined as havingan 8-hr average equivalent ventilationrate (EVR) in the range 13-27 l-min/m2.6-27Table 6-1c. Summary of Estimates of Number of People Exposed and Number of Occurrences1at Moderate Exertion2Associated with 8-Hour DailyMaximum Ozone Concentrations >0.060 ppm for 12 Urban Areas in the U.S.General Population(88.5 million people)All Children (5-18 years old)(18.3 million children)Asthmatic Children (5-18 years old)(2.6 million children)Air QualityScenarioPersons(% of population)Person Days[% change fromrecent air quality]Persons(% of population)Person Days[% change fromrecent air quality]Persons(% of population)Person Days[% change fromrecent air quality]2002 Air QualityRecent Air Quality36,410,000(41%)112,510,000 12,580,000(69%)48,000,000 1,860,000(72%)7,260,000Just MeetingCurrent Standard21,860,000(25%)45,040,000[60% reduction]7,970,000(44%)18,760,000[61% reduction]1,210,000(47%)2,910,000[60% reduction]2003 Air QualityRecent Air Quality27,660,000(31%)68,790,000 10,220,000(56%)29,640,000 1,490,000(58%)4,170,000Just MeetingCurrent Standard10,410,000(12%)14,220,000[79% reduction]4,040,000(22%)5,750,000[81% reduction]610,000(24%)860,000[79% reduction]2004 Air QualityRecent Air Quality19,820,000(22%)44,620,000 7,570,000(41%)19,300,000 1,090,000(42%)2,690,000Just MeetingCurrent Standard4,720,000(5%)5,920,000[87% reduction]1,800,000(10%)2,300,000[88% reduction]270,000(11%)350,000[87% reduction]1Estimates for persons and person days are rounded to the nearest10,000. Percentages greater than or equal to 1 are rounded tothe nearest percent andpercentages less than one arerounded to the nearest tenth.2Moderate exertion is defined as havingan 8-hr average equivalent ventilationrate (EVR) in the range 13-27 l-min/m2.6-28 In addition to city-to-city variability, subs tantial year-to-year va riability in exposure estimates is observed. For example, about 3 million children (17% of all school age children for the 12 urban areas) to more than 8.5 million childr en (47% of all school age children for the 12 urban areas), are estimated to experience one or more exposures of concern (i.e., > 0.070 ppm, while engaged in moderate or greate r exertion) for 2004 and 2002, respectively. 6 When air quality is adjusted to simulate just meeting th e 8-hr standard, the estimated number of children exposed is substantially reduced. Depending on wh ich year is adjusted for just meeting the current standard, approximately 260,000 children (1 % of all school age children) (based on 2004 air quality data) to more than 3.3 million (18% of all school age children) (based on 2002 air quality data) are estimated to experience one or more exposures of concern. These results suggest reductions of approximately 91%, base d on 2004 air quality, to 61%, based on 2002 air quality, in the number of children estimated to experience one or more 8-hr average exposures above 0.070 ppm when the current 8-hr O 3 standard is just met.
We have also examined the extent to which individuals are likely to experience repeated exposures of concern, which is an important as pect to consider when making judgments about the extent to which these exposures can be cons idered adverse to individuals. However, based on the analysis described in section 4.6.4, sta ff concludes that the APEX exposure model significantly underestimates the fr equency of occurrences of indi viduals (adults and children) experiencing repeated 8-hour aver age exposures at the three levels . As discussed in Chapter 4, this underestimation results from the way that people’s activities are modeled in APEX using CHAD, which does not properly account for repeated behavior of adults and children, and may be the greatest source of uncertainty in the exposur e estimates. Thus, it is likely that the number of repeated exposures, which are estimated here to be relatively small, is significantly underestimated. As seen in Table 6-1, for air qual ity just meeting the current standard, in most cases the estimated number of occurrences is only slightly larger than the estimated number of people exposed, indicating that the estimated number of repeated exposures is relatively small. Moreover, due to limitations in the CHAD databa se, the exposure assessment does not include outdoor workers, some proportion of whom are likely to be exposed repeatedly day after day to
elevated ambient O 3 levels while at work.

Risk Assessment Results Turning to risk-based considerations, as disc ussed in Chapter 5, risk estimates have been
calculated and are discussed below for severa l important health e ndpoints, including:

6 Unless otherwise noted, estimates for 2003 fall between the estimates for 2002 and 2004.6-29 • Lung function decrements (i.e., ≥ 15% and ≥ 20% reductions in FEV 1 ) in all school age children for 12 urban areas;

• Lung function decrements (i.e., ≥ 10% and ≥ 20% reductions in FEV 1 ) in asthmatic school age children for 5 urban areas (a subset of the 12 urban areas);

• Respiratory symptoms (i.e., chest tightness, sh ortness of breath, wheeze) in moderate to severe asthmatic children for the Boston area;

• Respiratory-related hospital admissions for 3 urban areas;

• Non-accidental and cardiorespirato ry mortality for 12 urban areas. In the sections on lung functi on decrements in children (all and asthmatic children), we describe the scope of the assessments, the numbe r and percent of childre n experiencing moderate and large lung function decremen ts, the number of occurrences of moderate and large lung function decrements, and what risk is estimated to remain after the current 8-hr standard is met. For effects such as lung function decrements, whic h are transient and reversible, aspects such as
the likelihood that these effects would interfere with normal activities or occur repeatedly are important to consider in making judgments about adversity to individu als and are described below. There are discussions about year-to-year variability in the resu lts and variability in results across the urban areas, which are importa nt for making judgments about public health impacts. These estimates indicate that there are substantial differences in the natural fluctuation of air quality levels from year to year. This can result in significant variability in the number of children affected by moderate or greater lung function decr ements and the number of occurrences they experience during a 3-year period th at is adjusted to just meet the current 8-hr standard. For example, the number of childre n affected, and the number of occurrences, can increase by more than 100% for a year with gene rally poorer air quality compared to a year with better air quality, within a three year period. Other aspects of the risk information presented are important to consider. The first is that there is some degree of consistency in the estimat ed population risk across the 12 urban areas, as indicated by the percen t of the population estimated to be affected, which describes the risk normalized across the urban areas with very differe nt population sizes. In Table 6-2, the percent of all children likely to experience one or more moderate or greater lung function responses ( ≥
15% reduction in FEV 1 ) under recent air quality and when air quality just meets the current 8-hr standard are 7% and 3% (based on 2002 air quality), respectivel y. The range across the 12 urban areas, from Table 5-8 is approximately 5% to 10% under recent (2002) ai r quality, and about 1% to 5% when air quality is adjusted to just meet the current 8-hr standard based on that year. The pattern across the 12 urban areas is similar fo r the risk estimates based on 2004 air quality. The remaining sections on respiratory symp toms in moderate to severe asthmatic children, respiratory related hospital admissions, and non-accid ental and cardiorespiratory6-30 mortality include discussions of the scope of the assessments, provi de estimates of the incidence, incidence per 100,000 and percen t of total incidence of the effect s, and discussion of year-to-year variability in the estimates and the risk that remains after the current standard is met.

Table 6-2. Summary of Number and Percent of All School Age Children (5-18) in 12 Urban Areas Estimated to Experience Lung Function Responses and the Number of Occurrences 1 Associated with 8-Hour Ozone Exposures While Engaged in Moderate Exertion 2 for 2002, 2003, and 2004 Air Quality and Just Meeting the Current 8-Hour Standard 3

FEV 1 > 15% FEV 1 > 20% Air Quality

Scenario Children (% of Children, 5-18) Occurrences [% reduction from recent air quality] Children (% of Children, 5-18) 1 Occurrences [% reduction from recent air quality] Recent Air Quality (2002) 1,330,000 (7%) 6,160,000 530,000 (3%) 1,370,000

Just Meeting Current Standard 610,000 (3%) 3,170,000 [49% reduction] 170,000 (0.9%) 500,000 [64% reduction] Recent Air Quality (2003) 990,000 (5%) 4,540,000 370,000 (2%) 920,000

Just Meeting Current Standard 350,000 (2%) 1,920,000 [58% reduction] 80,000 (0.4%) 230,000 [75% reduction] Recent Air Quality (2004) 620,000 (3%) 3,570,000 190,000 (1%) 570,000

Just Meeting Current Standard 230,000 (1%) 1,620,000 [55% reduction] 40,000 (0.2%) 160,000 [71% reduction]

1 Estimates for persons and person days greater than 10,000 were rounded to the nearest 10,000. Estimates for persons and person days less than 10,000 were rounded to the nearest thousand. Percentages less than 1 are rounded to the nearest tenth, percentages greater than or equal to 1 are rounded to the nearest percent.

2 Moderate exertion is defined as having an 8-hr average equivalent ventilation rate > 13 l-min/m 2

.
3 Estimates are the aggregate results base d on 12 urban areas (Atlanta, Boston, Chicago, Cleveland, Detroit, Houston, Los Angeles, New York, Philadelphia, Sacramento, St. Louis, and Washington, D.C.) based on Tables 5-6 and 5-7 for estimates based on 2002 and 2004 air quality and tables provided in Post (2007) for estimates based on 2003 air quality. Estimates are for the ozone seas on which is all year in Houston, Lo s Angeles and Sacramento and March or April to September or October for the remaining urban areas.

Lung function decrements in all school-age children. Tables 5-6 and 5-7 in Chapter 5 display risk estimates for all school age childr en (ages 5-18) for mode rate or greater lung function decrement responses for the 12 urban areas . As with the exposure estimates, the risk
estimates are associated with three years of recent air qua lity (i.e., 2002, 2003, 2004) and air quality based on adjusting these same three years to simulate just meeting the current 0.08 ppm,
8-hr O 3 standard based on the three-year design va lue. All estimates in both tables reflect6-31 responses associated with exposure to O 3 in excess of exposures associated with policy relevant background (PRB) O 3 concentrations. 7 Table 5-6 shows the number and percent of all school age children estimated to have at least one moderate or grea ter lung function response (i.e., >
15% decrement in FEV 1 ) during the O 3 season. Table 5-7 displa ys the total number of occurrences for the moderate or grea ter lung function responses during the O 3 season. Table 6-2 draws upon the risk estimates for all school age child ren contained in tables in Chapter 5 and the Risk Assessment TSD, and provides the number of children estimated to experience one or more
occurrences of moderate or greater (i.e., > 15% decrement in FEV 1 ) and large or greater (i.e., >
20% decrement in FEV 1 ) lung function responses, and the numb er of total days of occurrences, aggregated across all 12 urban areas. As shown in Table 6-2, for the three r ecent years (2002 - 2004), from 620,000 to over 1.3 million school age children (3 to 7% of all school age children) are estimate d to experience 1 or more moderate lung function responses (i.e., ≥ 15% reduction in FEV 1 ) in the 12 urban areas combined. Similar to the exposure estimates disc ussed above, when air qua lity is adjusted to simulate just meeting the current 8-hr standar d, there are significant reductions in estimated health outcomes. Depending on which year is adju sted to just meet the current 8-hr standard, from about 230,000 to about 610,000 children (1 to 3% of all school age children) are estimated to experience moderate (i.e., ≥ 15% reduction in FEV 1 ) lung function responses in these 12 urban areas combined upon just meeting the current st andard. Among all school age children, these estimates indicate that the percent of children li kely to experience one or more moderate or greater lung function decrements (i.e., ≥ 15% FEV 1 decrement) is reduced by about 54 to 65% when the current standard is just met base d on adjusting for 2002, 2003, and 2004 air quality. The analogous reduction in the number of occurrences of lung function decrements > 15% is 49
to 58%. It is also important to note that many of these children will experience repeated occurrences of moderate or gr eater lung function responses. Th ese results indicate that among all school age children, on average an individual is likely to e xperience 5 to 7 occurrences of moderate or greater lung f unction responses during an O 3 season. 8 However, based on the distribution of exposures estimated from the 1997 review, it is reasonable to expect that many

7 With respect to the impact of uncertainties about estimated background concen trations on the risk estimates presented in Tables 5-6 and 5-7, as discussed in section 5.4.3, alternative assumptions about PRB levels had a variable impact depending on the location and standard analyzed in terms of the absolute magnitude of the risk estimates. However, the overall pattern of reductions, expressed in terms of percentage reduction relative to the current standard, is not impacted by alternative assumpti ons for PRB for most of the a lternative standards analyzed.

8 This number is estimated for example for all children, by dividing the estimated number of children into the estimated number of occurrences, resulting in an average of about 5 to 7 occurrences per child.6-32 children will experience one or just a few modera te or greater lung function responses, while a smaller number of children will experience large numbers of such responses. These ranges of
estimated number of occurrences of moderate or greater lung function decrements in an O 3 season are important in considering the implications for the health status of individuals likely to experience these effects. As discussed in section 3.6.3, for active he althy people, large lung function responses (i.e., > 20% decrement in FEV 1 ), would likely interfere with no rmal activities in many sensitive individuals, therefore single occurrences would be consid ered to be adverse under ATS guidelines, and are the appropriate indicator to consider. As s hown in Table 6-2, for the three recent years (2002 - 2004), there were estimated to be from about 1,370,000 to about 570,000 occurrences of large lung function decrements (i.e., ≥ 20% reduction in FEV 1 ) in school age
children in the 12 urban areas combined. Simila r to the exposure estimates discussed above, when air quality is adjusted to simulate just meeting the current 8-hr standard, there are significant reductions in estimated health outc omes. Depending on which year is considered, upon just meeting the current 8-hr standard, th ere are estimated to be from about 500,000 to about 160,000 occurrences of large lung function decrements (i.e., ≥ 20% reduction in FEV 1 ) in school age children in these 12 urban areas comb ined. Among all school age children, these

estimates indicate that o ccurrences of large lung function decrements (i.e., ≥ 20% FEV 1 decrement) are reduced by about 64 to 75% when the current st andard is just met based on adjusting 2002, 2003, and 2004 air quality. Lung function decrements in asthmatic school age children. As discussed in greater detail in section 3.6.3, FEV 1 decrements > 10% but < 20% have been judged to represent
moderate levels of functional re sponses for active heal thy people and would lik ely interfere with normal activity for relatively few sensitive individuals. However, for persons with lung disease, such as asthma, lung function decrements at th e lower end of the moderate range (i.e., FEV 1 decrements ≥ 10%) would likely interfere with normal activity for many individuals and would likely result in additional and more frequent use of medication. We also note that new evidence
described above indicates that ch ildren with asthma, particularly those with moderate-to-severe asthma, are more likely to have lung function and symptomatic responses, and have bigger responses, from O 3 exposure than children who do not have asthma. Studies discussed in section 3.3.1.1 that show increased lung function respon ses, inflammation, and increased airway responsiveness in asthmatic s indicate that the risk estimates for lung function decrements derived from controlled exposures of healthy adult vo lunteers likely underest imate the percent of asthmatic school age children that would experience decrements in FEV 1 . In this final Staff Paper, we use a ≥ 10% decrease in FEV 1 as a benchmark for modera te functional responses in
asthmatic children. The CASAC endorsed this approach. Thus, as discussed in section 5.4.1,6-33 consistent with the CASAC recommendation (He nderson, 2006c) that for asthmatic children a lung function response defined in terms of FEV 1 decrement ≥ 10% serves as an indicator of potential adverse health effects for this group, risk estimates have been calculated for lung function decrements (i.e., ≥ 10% and ≥ 20% reductions in FEV 1 ) in asthmatic school age
children for 5 urban areas that are a subset of the 12 urban ar eas included for all children. As shown in Table 6-3, for the three r ecent years (2002 - 2004), from about 160,000 to about 250,000 asthmatic school age children (9 to 15% of asthma tic school age children) are estimated to experience 1 or more mo derate lung function responses (i.e., ≥ 10% reduction in

FEV 1 ) in the 5 urban areas combined. Similar to the risk estimates for all school age children discussed above, when air quality is adjusted to simulate just meeting th e current 8-hr standard, there are significant reductions in estimated health outcomes. Depending on which year is adjusted to just meet the current 8-hr standa rd, from about 70,000 to about 130,000 children (4 to 8% of asthmatic school age children) are estimated to experience moderate (i.e., ≥ 10% reduction
in FEV 1 ) lung function responses in these 5 urban areas combined upon just meeting the current standard. Among asthmatic school age children, th ese estimates indicate that the number of children likely to experience one or more mode rate or greater lung function decrements (i.e., ≥
10% FEV 1 decrement) drops by about 50 to 60% when the current standard is just met based on adjusting 2002, 2003, and 2004 air quality. Asthmatic school age children are estimated to experience a greater number of repeated occurrences of moderate or gr eater lung function responses pe r individual responding compared to all school age children. The results in Ta ble 6-3 indicate that among asthmatic school age children, on average an individual is likely to experience 8 to 10 occurrences of moderate or greater lung function re sponses during an O 3 season. As discussed above, the more likely distribution is that many childre n will experience one or only a fe w occurrences of moderate or greater lung function decrements ( ≥ 10% decrement in FEV 1 ), while some may experience a very large number, based on these estimates. Recognizing that nationa lly over 14% of school age children have asthma, these numbers raise concern about the potentia l number of children with asthma who could experience a large number of occurrences of moderate or greater lung function decrements ( ≥ 10% decrement in FEV 1 ) even with air quality ju st meeting the current 8-
hr standard.6-34 Table 6-3. Summary of Number and Percent of Asthmatic School Age Children (5-18) in 5 Urban Areas Estimated to Experience Lung Function Responses and the Number of Occurrences 1 Associated with 8-Hour Ozone Exposures While Engaged in Moderate Exertion 2 for 2002, 2003, and 2004 Air Quality and Just Meeting the Current 8-Hour Standard 3

FEV 1 > 10% FEV 1 > 20% Air Quality Scenario Children (% of Asthmatic

Children in) 1 Occurrences 1 [% reduction from recent air quality] 1 Children (% of Asthmatic Children) 1 Occurrences 1 [% reduction from recent air quality] 1
Recent Air Quality (2002) 250,000 (16%) 1,890,000 50,000 (3%) 120,000

Just Meeting Current Standard 130,000 (8%) 1,040,000 [45% reduction] 10,000 (0.7%) 40,000 [70% reduction] Recent Air Quality (2003) 210,000 (13%) 1,590,000 40,000 (2%) 90,000

Just Meeting Current Standard 90,000 (6%) 760,00 0 [53% reduction] 6,000 (0.4%) 20,000 [79% reduction] Recent Air Quality (2004) 160,000 (10%) 1,390,000 20,000 (1%) 60,000

Just Meeting Current Standard 70,000 (4%) 680,000 [51% reduction] 3,000 (0.2%) 10,000 [76% reduction]

1 Estimates for persons and person days greater than 10,000 were rounded to the nearest 10,000. Estimates for persons and person days less than 10,000 were rounded to the nearest thousand. Percentages less than 1 are rounded to the nearest tenth, percentages greater than or equal to 1 are rounded to the nearest percent.

2 Moderate exertion is defined as having an 8-hr average equivalent ventilation rate > 13 l-min/m 2

3 Estimates are the aggregate results based on 5 urban areas (Atlanta, Chicago, New York, Houston, and Los Angeles) based on Tables 5-8 and 5-9 for estimates based on 2002 and 2004 air quality and Tables 3-8, 3-9, 3-24, 3- 26, and 3-27 in the Risk Assessment TSD for estimates based on 2003 air quality. Estimates are for the ozone season which is all year in Houston, and Los Angeles, and March or April to September or October for the remaining urban areas

.

As discussed in section 3.6.3, for people with asthma, large lung function responses (i.e.,

≥ 20% decrement in FEV 1 ), would likely interfere with nor mal activities for most individuals
and would also increase the likelihood that thes e individuals would use additional medication or seek medical treatment. Single occurrences would be considered to be adve rse to the individuals
and would be cause for concern. As shown in Table 6-3, for the three recent years (2002 - 2004),
there were estimated to be from about 120,000 to about 60,000 occurr ences of large lung function responses (i.e., ≥ 20% reduction in FEV 1 ) in asthmatic school age children in the 5 urban areas combined. When air quality is adjust ed to simulate just meeting the current 8-hr standard, there are significant reductions in estimated health outcomes. Depending on which6-35 year is adjusted to just meet the current 8-hr standard, there are estimated to be from about 30,000 to about 10,000 occurrences of la rge lung function responses (i.e., ≥ 20% reduction in

FEV 1 ) in asthmatic children in these 5 urban areas combined. Among asthmatic school age children, these estimates indicate that occurren ces of large lung function decrements (i.e., ≥ 20%

FEV 1 decrement) in these 5 urban areas are re duced by about 70 to 79% when the current standard is just met based on adjusting 2002, 2003, and 2004 air quality. 9 Respiratory symptoms in moderate to severe asthmatic children. Risk estimates were developed for several respirator y symptoms (i.e., chest tightne ss, shortness of breath, and wheeze) during the O 3 season in children of ag e 0 to 12 years with moderate to severe asthma (as defined by the use of maintenance asthma medications), living in the Boston area. 10 About 40%
of the children with asthma in the Boston area ar e estimated to be on controller medications and
would be considered moderate-to-severe asthmatics. 11 In this population of 25,000 children with moderate-to-severe asthma, as shown in Tabl es 5-10 and 5-11, the es timated incidence of symptom days of chest tightness (across 4 models reflecting 2 different lags and O 3 alone vs.
inclusion of PM 2.5 in the model) ranges from almost 6,900 to 10,800 based on a year (2002) with poorer air quality, and from 5,300 to 8,400 based on a year with better (2004) air quality. As indicated in Figure 5-10, the current stan dard reduces the incidence of symptom days for chest tightness by relatively small and cons istent amounts across the 4 models specified. Risk estimates for the other symptom endpoints, shortness of breath and wheeze, show similar patterns as the risk estimates for chest tightness. The reduction of risks across the 4 models for chest tightness is shown in Table 6-4. Averag ing the median estimates of symptom days indicates that just meeting the current 8-hr sta ndard is estimated to reduce the total number of symptom days for chest tightness in children with moderate to severe asthma by 11% (8,700 to 7,700) based on a year (2002) with generally poorer air quality and by 15% (from 6,700 to 5,700) based on a year (2004) with ge nerally better air quality. The current standard clearly does not provide the same degree of protection against respiratory symptoms in moderate to severe

9 Risk estimates for all and asthmatic children school age children (i.e., ≥ 15% and ≥ 10% reductions in FEV 1 , respectively) are discussed in more detail in Chapter 5 and in the Risk Assessment TSD. Risk estimates for large lung function decrements in all and asthmatic children (i.e., ≥ 20% reductions in FEV 1 ), are included in the Risk Assessment TSD.

10 To minimize uncertainty, this risk assessment was perfor med for the Boston area because that is the urban area nearest to where the epidemiologi cal study was conducted that is the basis for the exposure-response function used in the assessment.

11 The estimated percent of asthmatic children using maintenance medications (40%) was obtained via email 4-05-06 from Jeanne E. Moorman, Survey Statistician, National Center for Environmental Health, CDC. The email communication has been placed in the docket for this review.6-36 asthmatic children as it provides against modera te or greater lung function decrements in all
children. Looking at percent of total incidence of symptom days, even after the current 8-hr standard is met in a year with generally be tter air quality, among children with moderate to severe asthma in the Boston area, as many as one symptom day in 8 during the O 3 season is
estimated to be attributable to O 3 exposure. In a year with ge nerally poorer air quality, as many as one symptom day in 6 is estimated to be attributable to O 3 exposure. These results support the human clinical and epidemiological evidence th at people with asthma are more likely to experience effects related to O 3 exposure than the general popul ation, and provide evidence that
the current 8-hr O 3 standard is not as protec tive for children with moderate to severe asthma in the Boston area as it is for all school age children in the 12 urban areas evaluated. Respiratory-related hospital admissions in New York City. For unscheduled hospital admissions, risk estimates for the New York City area 12 associated with O 3 levels above background for the period from April to Septembe r are shown in Table 6- 5 for recent air quality (2002, 2004), and for just meeting the current 8-hr standard based on adjusting a recent 3-year period (2002-2004). The current 8-hr standard reduces the incidence of respiratory-related hospital admissions by about 16% in a year with poorer air quality (2002) and about 18% in a year with better air quality (2004). The incidenc e of asthma-related hospital admissions (which are a subset of total respiratory hospital admissi ons) were reduced by about the same amount in
each of the two scenarios. This results in an incidence per 100,000 of 4.6 to 6.4 for respiratoryrelated hospital admissions, and 3.9 to 5.5 for as thma-related hospital ad missions, based on two air quality years, after the current standard is met.

12 To minimize uncertainty, this risk assessment was perf ormed for the New York City area because that is where the epidemiological study was co nducted that is the basis for the exposure-response function used in the
assessment.6-37 Table 6-4. Incidence of Respiratory Symptom Days for Chest Tightn ess Associated with Recent (2004, 2002) Air Quality and Just Meets the Current Standard Based on Adjusting 2004 and 2002 Air Quality in Moderate to Severe Asthmatic Children in Boston, MA

Average Incidence of Chest Tightness Associated with Air Quality (range of median estimates) 1,2 [% reduction from recent air quality] Respiratory Symptoms in Moderate to Severe Asthmatic Children on Controller Meds Year

Recent Air Quality Just Meets 0.08 ppm 2002 8,700 (6,900 - 10,800) 7,700 [11% reduction] (6,100 - 9,600) Incidence 2004 6,700 (5,300 - 8,400) 5,700 [15% reduction] (4,500 - 7,200) 2002 34,400 (27,200 - 42,700) 30,600 (24,100 - 38,100) Incidence per 100,000 2004 26,400 (20,700 - 33,100) 22,600 (17,700 - 28,400) 2002 12% - 20% 11% - 17%
Percent of Total
Incidence 2004 9% - 15% 8% - 13%

1 Incidence rounded to nearest 100. Percentages rounded to nearest tenth.

2 Range of median estimates across models using lag 0 and lag 1 day and O 3 only and including PM 2.5 in the model.

Total non-accidental and cardiorespi ratory mortality in 12 urban areas. Table 6-6
summarizes risk estimates for non-accidental mo rtality in 12 urban areas associated with O 3 levels above background for the period from Apr il to September based on the 95-city function reported in Bell et al. (2004) fo r non-accidental mortality. This table includes risks for two recent years of air quality (2002 and 2004) and risks associated with just meeting the current 8-hr standard over a recent 3-year period (2002-2004). 13 We chose to present the multi-city function risk estimates here because they are available for all 12 urban areas, whil e single-city estimates

13 The information presented in Table 6-6 is based on Tables 5-10 and 5-11 in this Staff Paper which summarize the risk estimates for non-accidental mortality in 12 urban ar eas for recent air quality (2002, 2004) and Tables 5C-13 to 5C-16 in Appendix 5C of this Staff Pape r and Tables 4-15 and 4-18 of the Risk Assessment TSD which present risk estimates for just meeting the current 8-hr standard based on adjusting the 3-year period (2002- 2004).6-38 are only available for 7 of the 12 urban areas an d because the multi-city risk estimates are less subject to publication bias. In comparing estim ates between recent air quality and just meeting the current standard, similar patt erns are seen in terms of rela tive reductions regardless of whether single- or multi-city functions are used. 14 Across the 12 urban areas, the estimates of mortality incidence per 100,000 relevant populati on range from 0.4 to 2.8 (for 2002) and from 0.5 to 1.5 (for 2004). Meeting the current standard results in a reduction of the incidence per 100,000 to a range of 0.3 to 2.4 based on adjusting 2002 air quality and a range of 0.3 to 1.2 based on adjusting 2004 air quality. Estimates fo r cardiorespiratory mortality show similar patterns (Tables 5-14, 5-15).

14 Additional risk estimates for cardiorespiratory morta lity are included in the Risk Assessment TSD for 8 of the 12 urban areas based on Huang et al. (2005).6-39Table 6-5. Risks of Respiratory- and Asthma-related Hospital Admissions Associated with Recent (2004, 2002) Air Qualityand Air Quality Adjusted to JustMeets Current Standard Based on Adjusting 2004 and 2002 Air Quality in NewYork City, NYIncidence1(Range)2[% reduction from recent]Incidence per 100,000(Range)2Percent Total Incidence(Range)2UnscheduledHospitalAdmissionsAirQualityScenario2002 2004 2002 2004 2002 2004Recent610(150 – 1070)450(110 – 790)7.6(1.8 - 13.3)5.6(1.4 - 9.8)1.7%(0.4 - 3%)1.3%(0.3 - 2.2%)RespiratoryJust Meets0.08 ppm510(120 – 900)[16% reduction]370(90 - 640)[18 % reduction]6.4(1.5 - 11.3)4.6(1.1 - 8)1.5%(0.4 - 2.6%)1%(0.3 - 1.8%)Recent520(110 – 930)380(80 – 680)6.5(1.4 - 11.6)4.8(1 - 8.5)4%(0.8 - 7.1%)2.9%(0.6 - 5.2%)Asthma(subset ofrespiratory)Just Meets0.08 ppm440(90 - 780)[16% reduction]310(70 - 560)[18% reduction]5.5(1.2 - 9.8)3.9(0.8 - 7)3.3%(0.7 - 6%)2.4%(0.5 - 4.3%)1Incidence rounded to the nearest 10. Incidence per 100,000 and percent of total incidence rounded to the nearest tenth.2Numbers in parentheses are 95% confidence or credible intervals based on statistical uncertainty surrounding the O3coefficient6-40Table 6-6. Risks of Non-accidental Mortality Associated with Recent (2004, 2002) Air Quality and Air Quality Adjusted toJust Meets Current Standard Based on Adjusting 2004 and 2002 Air QualityEstimated Risk of Non-accidental Mortality1,2Incidence(range)3Incidence per 100,000(range)3Percent of Total Incidence(range)3LocationAir QualityScenario2002 2004 2002 2004 2002 2004Recent 17(6 - 29)12(4 - 20)1.2(0.4 - 1.9)0.8(0.3 - 1.4)0.4%(0.1 - 0.6%)0.3%(0.1 - 0.4%)AtlantaJust Meets 0.08 ppm 14(5 - 23)9(3 - 15)0.9(0.3 - 1.6)0.6(0.2 - 1)0.3%(0.1 - 0.5%)0.2%(0.1 - 0.3%)Recent 10(3 - 17)7(2 - 12)1.5(0.5 - 2.5)1.0(0.3 - 1.7)0.4%(0.1 - 0.7%)0.3%(0.1 - 0.5%)BostonJust Meets 0.08 ppm 9(3 - 15)6(2 - 9)1.3(0.4 - 2.1)0.8(0.3 - 1.4)0.3%(0.1 - 0.6%)0.2%(0.1 - 0.4%)Recent 69(23 - 115)49(16 - 81)1.3(0.4 - 2.1)0.9(0.3 - 1.5)0.3%(0.1 - 0.5%)0.2%(0.1 - 0.4%)ChicagoJust Meets 0.08 ppm 55(18 - 91)33(11 - 55)1(0.3 - 1.7)0.6(0.2 - 1)0.3%(0.1 - 0.4%)0.2%(0.1 - 0.3%)Recent 38(13 - 64)17(6 - 28)2.8(0.9 - 4.6)1.2(0.4 - 2)0.5%(0.2 - 0.9%)0.2%(0.1 - 0.4%)ClevelandJust Meets 0.08 ppm 31(10 - 52)12(4 - 20)2.2(0.8 - 3.7)0.9(0.3 - 1.4)0.4%(0.1 - 0.7%)0.2%(0.1 - 0.3%)Recent 29(10 - 48)17(6 - 28)1.4(0.5 - 2.3)0.8(0.3 - 1.4)0.3%(0.1 - 0.5%)0.2%(0.1 - 0.3%)DetroitJust Meets 0.08 ppm 24(8 - 39)12(4 - 20)1.1(0.4 - 1.9)0.6(0.2 - 1)0.3%(0.1 - 0.4%)0.1%(0 - 0.2%)Recent 14(5 - 24)17(6- 28)0.4(0.1 - 0.7)0.5(0.2 - 0.8)0.2%(0.1 - 0.3%)0.2%(0.1 - 0.3%)HoustonJust Meets 0.08 ppm 9(3 - 15)11(4 - 18)0.3(0.1 - 0.4)0.3(0.1 - 0.5)0.1%(0% - 0.2%)0.1%(0% - 0.2%)6-41Estimated Risk of Non-accidental Mortality1,2Incidence(range)3Incidence per 100,000(range)3Percent of Total Incidence(range)3LocationAir QualityScenario2002 2004 2002 2004 2002 2004Recent 110(37 - 184)133(45 - 221)1.2(0.4 - 1.9)1.4(0.5 - 2.3)0.4%(0.1 - 0.7%)0.5%(0.2 - 0.8%)Los AngelesJust Meets 0.08 ppm 52(17 - 86)67(22 - 111)0.5(0.2 - 0.9)0.7(0.2 - 1.2)0.2%(0.1 - 0.3%)0.2%(0.1 - 0.4%)Recent 105(35 - 174)60(20 - 100)1.2(0.4 - 2)0.7(0.2 - 1.1)0.3%(0.1 - 0.6%)0.2%(0.1 - 0.3%)New YorkJust Meets 0.08 ppm 84(28 - 139)43(15 - 72)0.9(0.3 - 1.6)0.5(0.2 - 0.8)0.3%(0.1 - 0.4%)0.2%(0.1 - 0.3%)Recent 37(12 - 62)23(8 - 38)2.4(0.8 - 4.1)1.5(0.5 - 2.5)0.5%(0.2 - 0.8%)0.3%(0.1 - 0.5%)PhiladelphiaJust Meets 0.08 ppm 30(10 - 50)17(6 - 28)2(0.7 - 3.3)1.1(0.4 - 1.8)0.4%(0.1 - 0.6%)0.2%(0.1 - 0.3%)Recent 23(8 - 39)18(6 - 29)1.9(0.6 - 3.2)1.4(0.5 - 2.4)0.6%(0.2 - 0.9%)0.4%(0.1 - 0.7%)SacramentoJust Meets 0.08 ppm 18(6 - 30)12(4 - 21)1.5(0.5 - 2.4)1(0.3 - 1.7)0.4%(0.1 - 0.7%)0.3%(0.1 - 0.5%)Recent 6(2 - 10)3(1 - 5)1.7(0.6 - 2.8)0.9(0.3 - 1.5)0.3%(0.1 - 0.5%)0.2%(0.1 - 0.3%)St. LouisJust meets 0.08 ppm 5(2 - 8)2(1 - 4)1.4(0.5 - 2.3)0.7(0.2 - 1.1)0.2%(0.1% - 0.4%)0.1%(0%- 0.2%)Recent 15(5 - 25)8(3 - 14)2.6(0.9 - 4.4)1.5(0.5 - 2.4)0.6%(0.2 - 0.9%)0.3%(0.1 - 0.5%)Washington, DCJust Meets 0.08 ppm 14(5 - 23)7(2 - 12)2.4(0.8 - 3.9)1.2(0.4 - 2.1)0.5%(0.2 - 0.8%)0.3%(0.1 - 0.4%)1All results are for mortality (among all ages)associated with short-term exposures to O3. All results are based on single-pollutant model from Bell et al. (2004)95-cities model.2Incidence was quantified down to estimated policy relevant background levels. Incidences are rounded to the nearest whole number; incidences per 100,000relevant population and percents are rounded to the nearest tenth.3Note: Numbers in parentheses are 95% confidence or credibleintervals based on statistical uncertainty surrounding the O3coefficient.6-42 6.3.1.3 CASAC and Public Commenters’ Views on the Adequacy of the Current Standard Beyond the evidence- and risk/exposure-based information discussed above, staff has
also taken into account the comments and a dvice of CASAC (Henderson, 2006a, b, c), based on
their review of the CD and earlier drafts of this document and the related technical support documents, as well as comments on earlier draf ts of these documents provided by public

commenters. 15 The range of views summarized here ge nerally reflects differing judgments as to the relative weight to place on various types of evidence, the exposure- and risk-based information, and the associated uncertainties , as well as differing judgments about the importance of various O 3 -related health effects from a public health perspective. In a letter to the Administrator (Attachment 1), the CASAC O 3 Panel, with full endorsement of the chartered CASAC, unanimous ly concluded that ther e is “no scientific justification for retaining” the current primary O 3 standard, and the current standard “needs to be substantially reduced to prot ect human health, particularly in sensitive subpopulations” (Henderson, 2006c, pp. 1-2). 16 The Panel’s rationale for this conclusion is outlined in their letter, beginning with their conclusion that “ new evidence supports and build-upon key, healthrelated conclusions drawn in the 1997 Ozone NAAQS review. ” (id., p. 3). The Panel points to studies discussed in Chapter 3 and Appendix 3B of this document in noting that several new single-city studies and large multi-city studies ha ve provided more evidence for adverse health
effects at concentrations lower than the current standard, and th at these epidemiological studies are backed-up by evidence from controlled huma n exposure studies. The Panel specifically noted evidence from the recent Adams (2006) st udy that reported statistically significant decrements in the lung function of healthy, mode rately exercising adults at a 0.08 ppm exposure level, and importantly, also reported adverse lung function effects in some individuals at 0.06 ppm. In concluding that these results indicate that the current standard “is not sufficiently health-protective with an adequate margin of sa fety,” the Panel noted that that while similar studies in sensitive groups such as asthmatics have yet to be conducted, “people with asthma, and particularly children, have been found to be more sensitive and to experience larger

15 All written comments submitted to the Agency are ava ilable in the docket for this rulemaking, as are transcripts of the public meetings held in conjunction with CASAC’s review of earlier drafts of this document and of draft and final versions of the CD on which this document is based.

16 Comments of individual Panel members are av ailable as Attachment D to the CASAC O 3 Panel letter (Henderson, 2006c); the letter without its attachments is reproduced as Attachment 1 to this document and the attachments to the letter, including individual Panel member comments, can be found in the docket and online at http://www.epa.gov/sab/ pdf/casac-07-001.pdf

.6-43 decrements in lung function in response to ozone exposures than w ould healthy volunteers (Mortimer et al. , 2002).” (Henderson, 2006c, p. 4). The CASAC Panel also highlighted a numbe r of adverse health effects, beyond lung function decrements, that are attributable to low-concentration exposure to ambient O 3, below the level of the current standard, ba sed on a broad range of epidemio logical and controlled exposure studies (id.). These adverse he alth effects include increases in school absenteeism, respiratory hospital emergency department visits among as thmatics and patients with other respiratory diseases, hospitalizations for respiratory illnesse s, symptoms associated with adverse health effects (including chest tightness and medica tion usage, and mortal ity (non-accidental, cardiorespiratory deaths) reported at exposure levels well below the current standard. “ The CASAC considers each of these findings to be an important indicator of adverse health effects .” (id.). The Panel further noted that the risk assessment (discussed above in chapter 5) estimated
that beneficial reductions in some adverse he alth effects would occur upon meeting the lowest standard level (0.064 ppm) considered in the assessment. With regard to the justification discussed in the second draft of this Staff Paper for
consideration of retainin g the current standard, 17 the CASAC Panel felt that more emphasis should be placed on numbers of subjects in controlled human exposure studies with FEV 1 decrements greater than 10%, which can be clinic ally significant, rather than on the relatively small average decrements. The Panel also emphasized significant O 3 -related inflammatory responses and markers of injury to the epithelial li ning of the lung that are independent of spirometric responses. Further, the Panel e xpressed the view that the justification for considering retaining the current standard discussed in the earlier draft of this document did not place enough emphasis on serious morbidity (e.g ., hospital admissions) and mortality observed in epidemiology studies. On the basis of the large amount of recent data evaluating adverse
health effects at levels at and below the current O 3 standard, it was the unanimous opinion of the CASAC that the current primary O 3 standard is not adequate to protect human health, that the
relevant scientific data do not support consideration of retaining the current standard, and that the
current standard needs to be subs tantially reduced to be protectiv e of human health, particularly in sensitive subpopulations (id., pp. 4-5). Further, the CASAC letter noted that “ there is no longer signific ant scientific uncertainty regarding the CASAC’s conclusion that the curr ent 8-hr primary NAAQS must be lowered .” (id., p. 5). The Panel noted that a “large body of da ta clearly demonstrates adverse human health effects at the current level” of the standard, such that “[R]etaining this standard would continue

17 See second draft O 3 Staff Paper (U.S. EPA, 2006c, e.g., p. 6-50) for the justification referred to by CASAC. In the second draft Staff Paper staff concluded th at “consideration could be given” to retaining the current standard, as discussed below in section 6.3.1.4 which presents staff’s final conclusions.6-44 to put large numbers of individua ls at risk for respiratory eff ects and/or significant impact on quality of life including asthma exacerbations, emergency room visits, hospital admissions and mortality” (id.). The Panel also noted that “sci entific uncertainty does exist with regard to the lower level of ozone exposure that would be fully protective of human h ealth,” concluding that “it is possible that there is no threshold for an ozone-induced impact on human health and that some adverse events may occur at policy-relevant background” (id.). Consistent with the advice of CASAC, se veral public commenters supported revising the primary O 3 standard to provide increa sed public health protection. 18 In considering the available evidence as a basis for their views, these commen ters generally noted that the controlled human exposure studies, showing statistically signifi cant declines in lung f unction, increases in respiratory symptoms, airway inflammation a nd airway responsiveness at a 0.08 ppm exposure level, were conducted with healthy adults, not members of sensitive groups including people with asthma and active children generally. Furt her, recognizing the substantial variability in response between subjects, some of these commen ters felt that the number of subjects included
in these studies was too small to ascertain the full range of responses, especially for sensitive groups. Such considerations in part were th e basis for these commen ters’ view that an O 3 standard set at 0.08 ppm is not protective of publ ic health and has no margin of safety for sensitive groups. In considering the results of the human exposur e and health risk assessment, this group of commenters generally expressed th e view that these assessments substantially unde restimate the public health impacts of exposure to O 3 . For example, several commenters noted that the
assessments are done for a limited number of c ities, they do not address risks to important sensitive subpopulations (e.g., outdoor worker s, active people who spend their summers outdoors, children up to 5 years of age), and they do not include many health effects that are important from a public health perspective (e.g., school absences, restricted activity days). Further, some of these commenters e xpressed the view that the primary O 3 standard should be set to protect the most exposed and most vulnerabl e groups, and the fact th at some children are frequently indoors, and thus at lower risk, should not weigh agains t setting a standard to protect
those children who are active outdoors. To th e extent the exposure and risk estimates are considered, some of these commenters felt that primary consideration should be given to the estimates based on 2002 air quality, for wh ich most areas had relatively higher O 3 levels than in 2004, so as to ensure public health protecti on even in years with relatively worse O 3 air quality
levels. Some commenters also felt that the exposure analysis should focus on exposures of

18 This group of commenters included a public health advocacy group, a medical association, a State agency, and a regional State organization.6-45 concern down to at least 60 ppb, the lower end of the range of alternativ e standards advocated by the CASAC Panel during their public meeting in August 2006.
In contrast to the views discussed ab ove, several other public commenters supported retaining the current standards. 19 In considering the available evidence as a basis for their views, these commenters challenged a numbe r of aspects of the interpreta tion of the evidence presented in the CD. For example, some of these commen ters asserted that EPA generally overestimates the magnitude and consistency of the results of short-term exposure epidemiological studies (e.g., for respiratory symptoms, school absences , hospital admissions, mortality), mistakenly links statistical significance and consistency with strength of a ssociations, and underestimates the uncertainties in interpreting the results of such studies. Further, these commenters generally express the view that there is significant uncertain ty related to the reliability of estimates from time-series studies, in that ambient monitors do not provide reliable estimates of personal exposures, such that the small reported morbid ity and mortality risks are unlikely to be attributable to peopl e’s exposures to O 3 . Rather, these commenters variously attribute the reported risks to the inability of time series stud ies to account for key mode l specification factors such as smoothing for time-varying paramete rs, meteorological factors, removal of O 3 by building ventilation systems, and confounding by co- pollutants. In particular, these commenters generally asserted that reported a ssociations between short-term O 3 exposure and mortality are not causal, in that the reported relative risks are too small to provide a basis for inferring causality and the associations are most likel y due to confounding, inappropriately specified statistical models, or publication bias. In considering the results of the human exposur e and health risk assessment, this group of commenters generally expressed the view that these assessments ar e based on a number of
studies that should not be used in quantitative risk assessment. For example, some commenters variously asserted that the results of time-series studies should not be used at all in quantitative risk assessments, that risk estimates from single city time-series studies should not be used since they are highly heterogeneous and influenced by publication bias, and that risk estimates from multi-city studies should not be used in estimati ng risk for individual cities. This group of commenters also generally expressed the view th at the assessments generally overestimate the public health impacts of exposure to O 3 . Noting that the risk assessment used a nonlinear exposure-response function to estimate decreas ed lung function risks, some commenters expressed the view that a nonlinear approach should also be used to assess other acute morbidity effects and mortality. This view was in part based on judgments that it is not possible to determine if thresholds exist using time-series an alyses and that the lack of association of O 3 to

19 This group of commenters included industry associations and corporations.6-46 mortality in the winter season is highly supportive of the likelihood of the existence of an effect threshold. With regard to the risk assessmen t based on controlled human exposure studies of lung function decrements, some commenters expr essed the view that th e assessment should not rely on what they characterized as “outlier ” information to define exposure-response relationships, with reference to the data in the Adams ( 2006) study at the 0.06 and 0.04 ppm exposure levels, but rather shoul d focus on group central tendency response levels. Further, some commenters expressed the vi ew that the air quality rollback algorithm used may result in
overestimates in benefits from emission reduc tions. Some commenters noted that potential
beneficial effects of O 3 in shielding from UV-B radiation ar e not quantified in the assessment,
and that the assessment should di scuss the evidence for both advers e and beneficial effects with the same objectivity. Finally, some of these co mmenters asserted that since estimates of exposures of concern (defined as 0.080 ppm) a nd lung function decremen ts are substantially
below the estimates available when the current O 3 standard was set in 1997 , retaining the current standard is the most appropr iate policy alternative.

6.3.1.4 Staff Conclusions on the Adequacy of the Current Standard As discussed above, we have considered new evidence from controlled human exposure, toxicological, and epidemiological studies as well as estimates of O 3 -related exposures of concern and risks upon meeting the current O 3 standard in many urban areas across the U.S., together with associated uncerta inties. As an initial matter, we note that there is general agreement among staff, CASAC, and all interest ed parties who commented on earlier drafts of
this document that this information supports considerati on of a primary O 3 standard that is at least as protective as the curre nt standard, with no one s upporting consideration of an O 3 standard that is any less protective. In considering whether the current standard is adequate or should be revised to provide increased public health protection, we first note that in the second draft of this Staff Paper,
retention of the current standard was included among the policy options that we identified for consideration. At that time, wh ile we recognized that there was substantial evidence that could be interpreted as calling into que stion the adequacy of the current standard, we chose not to exclude the option of retaining th e current standard from the provi sional conclusions presented in
that draft document. We wanted to have th e benefit of receiving CASAC views and public comments on the strength of the av ailable evidence, the results of the exposure/risk assessments, and their interpretation of the evidence with re gard to judging the ad equacy of the current standard before reaching final conclusions. As discussed below, based on the available information and taking into account the view s of CASAC and public comments, we now conclude that the overall body of evidence clearly calls into question the ad equacy of the current6-47 standard in protecting sensitiv e groups, notably incl uding asthmatic children and other people with lung disease, as well as a ll children and older adults, espe cially those active outdoors, and outdoor workers, 20 against an array of adverse health effects that range from decreased lung
function to serious indicators of respiratory morbidity incl uding ED visits and hospital admissions for respiratory causes, and possibly card iovascular effects and mortality. We believe the available information provides str ong support for consideration of an O 3 standard that would provide increased health prot ection for these sensitive groups. In discussing information related to the ade quacy of the current standard, we have noted that evidence of a range of resp iratory-related morbidity effects se en in the last review has been strengthened, both through toxi cological and controlled human exposure (see Chapter 3, e.g., Table 3-1 and Appendix 3C) studies as well as through many new panel and epidemiological studies (see Chapter 3, e.g., Figure 3-4 and Appendi x 3B). In addition, new evidence identifies people with asthma as an important susceptibl e population for which estimates of respiratory effects in the general population may underestimate the magnit ude or importance of the effect. New evidence about mechanisms of toxicity help s to explain the biologi cal plausibility of O 3 - induced respiratory effects and is beginni ng to suggest mechanisms that may link O 3 exposure to cardiovascular effects. Further, there is now re latively strong evidence for associations between

O 3 and total nonaccidental and cardiopulmonary mortality, even after adjustment for the
influence of season and PM. Relative to the in formation that was available to inform the Agency’s 1997 decision to set the current standard, the newly available evidence increases our confidence that a broad array of adverse health effects, especially i ndicators of respiratory morbidity, are causally related to O 3 exposures, and that mortality is likely associated with O 3 exposures during the O 3 season. In examining the entire body of evidence a nd considering CASAC’s views and advice on interpreting the evidence with regard to the adeq uacy of the current stan dard, we conclude that there is important new evidence de monstrating that exposures to O 3 at levels below the level of the current standard cause or are clearly associated with a broad array of adverse health effects in sensitive populations. For example, we note new direct evidence of transient and reversible lung function effects and respiratory symptoms in some healthy individuals at exposure levels below
the level of the current standard. In additi on, there is now epidemiological evidence of statistically significant O 3 -related associations with lung function and resp iratory symptom effects, respiratory-related ED visits and hospital admissions, as well as possibly increased mortality, in areas that likely would have met the current st andard. There are also many

20 In defining sensitive groups this way we are includ ing both groups with greater inherent sensitivity and those more likely to be exposed.6-48 epidemiological studies done in areas that likel y would not have met the current standard but which nonetheless report statistica lly significant associations th at generally extend down to
ambient O 3 concentrations that are well below the leve l of the current standard. Further, there
are a few studies that have examined subsets of data that include onl y days with ambient O 3 concentrations below the level of the curre nt standard, or belo w even much lower O 3 concentrations, and continue to report statistically significan t associations. Our level of confidence in the findings from these studies is not related to whether th ey were done in areas that likely would or would not have met the curren t standard. However, we agree with the views expressed by the CASAC O 3 Panel 21 that uncertainty in epidemiological findings increases at the low end of the ranges of concentrations obser ved in these studies, which are generally well below the level of the current standard, because of limitations in interpreting the results that relate, for example, to poor co rrelations between ambient con centrations and personal exposure and to questions of plausibility that are mo re salient at relatively low concentrations. Based on the strength of the currently avai lable evidence of adverse health effects, especially indicators of respiratory morbidity, an d on the extent to which the evidence indicates that such effects likely result from exposures to ambient O 3 concentrations well below the level of the current standard, we conc lude that the available evidence clearly calls into question the adequacy of the current standard and provides strong support for giving c onsideration to revising the standard to provide increased protection, es pecially for sensitive groups, against a broad array of adverse health effects. As discussed be low, we have also consid ered the results of the exposure and risk assessments conducted for th is review to provide some quantitative perspective on the extent to which sensitive groups are likely to experience exposures of concern and on the risk of experiencing various adverse h ealth effects when air quality is adjusted to simulate meeting the current standard in a number of urban areas in the U.S. In considering the results of the exposure and risk assessments, we first note that the CASAC Panel has expressed the view that the e xposure analysis represents a state of the art modeling approach, that the risk assessment is well-done and bala nced, and that the results of both are appropriate input to the decision on the O 3 NAAQS. Moreover, the additional uncertainty and sensitivity analyses conducted after CASAC review of the second draft Staff Paper have increased our overall confidence in th e results of these assessments. Accordingly, in considering the adequacy of the current standard , we have placed substantial weight on these results, both as direct measures of a limited set of O 3 -related risks to public health and as indicators of the potential for a ra nge of other types of adverse h ealth effects for which currently
available information is too limited to allow for direct estimates of risk.

21 See, for example, the written comments of Dr. Veda l (Henderson, 2006c, Appendix D, p. D-74).6-49 Turning to the results of the exposure assessm ent, we note that estimating exposures of concern provides an important i ndication of the potential magnitude of the incidence of health outcomes that we cannot currently evaluate in a qu antitative risk assessment, such as, increased airway responsiveness, increased pulmonary inflammation, including increased cellular permeability, and decreased pulmonary defense mech anisms. These physiological effects, which
have been demonstrated to o ccur in healthy people at O 3 exposures as low as 0.080 ppm, are associated with aggravation of asthma, increas ed medication use, increased school and work absences, increased suscep tibility to respiratory infection, incr eased visits to doctors’ offices and EDs, increased admissions to hospitals, and pos sibly to cardiovascular system effects and
chronic effects such as chronic bronchitis or l ong-term damage to the lungs that can lead to reduced quality of life. In considering whether the current standard provides a margin of safety against such serious respiratory morbidity effects not just in h ealthy adults but in sensitive groups, such as people with asthma or other lung diseases, children, and older adults, we believe it is appropriate to cons ider the extent to which the curr ent standard reduces exposures of concern not only at and above th e 0.080 ppm benchmark level, but more importantly also at
lower benchmark levels. Therefor e, we have focused on the extent to which the current standard reduces exposures of concern at the 0.070 and 0.060 ppm benchmark levels, noting that 0.060 ppm is the lowest level at which potentially adverse lung function decrements have been observed in healthy people. While we believe that exposures of concern at these lower benchmark levels are an important indicator of th e potential for adverse health effects especially in sensitive groups, as discussed above, we note that due to indi vidual variability in responsiveness only a subset of individuals in these groups with exposures of concern can be expected to experience such adverse health effects. Based on the aggregate estimates summarized above in Table 6-1a-c for the 12 U.S., urban areas included in the exposur e analysis, we first note that th ere is substantial year-to-year variability across the three years included in this analysis, ranging up to an order of magnitude or more, in estimates of the number of people a nd the number of occurrences of exposures of
concern at each of the benchmark levels. We be lieve it is appropriate to consider not just the average estimates across all years, but also to consider public health impacts in years with relatively poorer air quality. In so doing, we note that even when considering the benchmark
level of > 0.080 ppm, an exposure level at which adverse respiratory effects have been demonstrated in healthy adults, approxi mately 100,000 asthmatic children (and over 700,000 total children) in these 12 cities alone are estimated to experience such exposure levels in the worst of the three years when th e current standard is met. In looking at the lower benchmark levels that are more relevant to providing a margin of safety for sensitive groups, over 500,000 (~20%) asthmatic children (and over 3 million total ch ildren) in these 12 cities are estimated to6-50 experience exposures > 0.070 ppm in the worst of the thr ee years; even in the mid-year, approximately 150,000 (~6%) asthmatic children (and approximately one million total children) are estimated to experience such exposures. Th ese estimates are roughly 2 to 4 times higher when considering exposures at the benchmark level of > 0.060 ppm. We also note that there is substantial city-t o-city variability in these estimates, as summarized in Table 6-7, and we believe it is appropriate to consider not just aggregate estimates across all cities, but al so to consider public health impacts in cities that receive relatively less protection from th e current standard. For example, in considering the benchmark
level of > 0.070 ppm, while the aggreg ate percentage of asthmatic children estimated to experience such exposures of con cern across all 12 cities is ~ 6% in the mid-year and ~20% in the worst year when the current standard is met, these estimates range up to 12% and 41%, respectively, in the city with the least degree of protection from the current standard. As seen in Table 6-7, such percentages are substantially higher when considering exposures at the
benchmark level of > 0.060 ppm, ranging up to 38 to 69% in the mid to worst years. Estimates of the percent of all children exposed are gene rally similar or slightly lower than those for
asthmatic children.

Table 6-7. Estimates of Percent of Children Exposed While at Moderate Exertion to 8- Hour Daily Maximum Ozone Concentrations > 0.070 ppm and > 0.060 ppm Combined for 12 Urban Areas in the U.S., and the Range of Estimates for Each of the 12 Cities – Just Meeting Current Standard

Percent of All Children (5-18 yrs old) (18.3 million children) -- Aggregated across 12 cities (Range for each of 12 cities) Percent of Asthmatic Children (5-18 yrs old) (2.6 million children) – Aggregated across 12 cities (Range for each of 12 cities) Exposure of

Concern Benchmark Level 2002 2003 2004 2002 2003 2004

>

0.070 ppm 18 (1 – 38) 5 (1 – 11) 1 (0 – 7) 20 (1 – 41) 6 (1 – 12) 1 (0 – 7)

>

0.060 ppm 44 (7 – 66) 22 (8 – 39) 10 (1 – 26) 47 (7 – 69) 24 (9 – 38) 11 (1 – 28)

With regard to estimates of risks of health effects in sensitive populat ions likely to remain upon meeting the current standard, we note that so me such estimates related to relatively less serious lung function effects are now appreciably lower than in the last review, whereas risk6-51 estimates related to more serious effects, such as hospital admissions, are as high or higher than previously estimated. In additi on, unlike in the last re view, there is now evidence that supports estimating risks for respiratory symptoms in asthmatic children and O 3 -related mortality. Based on Tables 6-2 and 6-3, we note that meeting the current O 3 standard substantially

reduces the estimated risk of mode rate lung function decrements (i.e., ≥ 15% FEV 1 decrement) in all school age children across 12 urban areas . In asthmatic childre n the reduction in the estimated risk of moderate lung function decrements (i.e., ≥ 10% FEV 1 decrement) is not as large, with about 4 to 8% of asthmatic school age children estimated to experience one or more occurrences of moderate lung f unction decrements even when th e current standard is met, resulting in over 1 million occurren ces just in 5 urban areas in a year with relatively poorer air quality (2002). Moreover, the estimated number of occurrences of moderate or greater lung function decrements per child is on average approxi mately 5 to 7 in all children and 8 to 10 in
asthmatic children in an O 3 season, even when the current standard is met. In the 1997 review of
the O 3 standard a general consensus view of the a dversity of such moderate responses emerged as the frequency of occurrences increases, w ith the judgment that re peated occurrences of moderate responses, even in otherwise healthy in dividuals, may be considered adverse since they may well set the stage for more serious illness. Large lung function decrements (i.e., ≥ 20% FEV 1 decrement) would likely interfere with normal activities in many healthy individuals, therefore single occurrences would be considered to be adverse. In people with asth ma, large lung function responses (i.e., ≥ 20% FEV 1 decrement), would likely interfere with normal ac tivities for most individuals and would also
increase the likelihood that thes e individuals would use additiona l medication or seek medical treatment. Not only would singl e occurrences be considered to be adverse to asthmatic individuals under the ATS definition, but they also would be cause for medical concern. While
the current standard reduces the occurrences of large lung function decrements in all children and asthmatic children overall from about 60 to 80%, in a year with relativ ely poorer air quality (2002) there are estimated to be about 500,000 occu rrences in all school children across 12 urban areas, and about 40,000 occurrences in asthmatic ch ildren across just 5 urban areas. As noted above, it is clear that even when the current st andard is met over a three-year period, air quality in each year can vary considerably, as evidenced by relatively large differences between risk estimates based on 2002 to 2004 air quality. We believe it is appropriate to consider this yearly variation in air quality allowed by the current standard in judgi ng the extent to which impacts on members of sensitive groups in a year with relatively poorer air quality remains of concern from a public health perspective. As seen in Tables 6-4 through 6-6, risks of respiratory symptom days in moderate to severe asthmatic children, respiratory-relate d hospital admissions, and non-accidental and6-52 cardiorespiratory mortality, respectively, are not reduced to as great an extent by meeting the current standard as are lung function decrements. For example, just meeting the current standard reduces the estimated average in cidence of chest tightness in m oderate to severe asthmatic children living in the Boston urban area by 11 to 15%, based on adjusting 2002 and 2004 air quality, respectively, resulting in an inciden ce per 100,000 relevant population of approximately 23,000 to 31,000 children, attributable to O 3 exposure (Table 6-4). Th e current standard reduces the estimated incidence of respiratory-related hospital admissions in the New York City urban area by 16 to 18%, based on adjusting 2002 and 2004 air quality, respectivel y, resulting in an incidence per 100,000 population of approximately 4.6 to 6.4, respectively (Table 6-5). Across
the 12 urban areas considered in this assessm ent, the estimates of non-accidental mortality incidence per 100,000 relevant popula tion range from 0.4 to 2.6 (for 2002) and 0.5 to 1.5 (for 2004) (Table 6-6). Meeting the current standard results in a reduction of the estimated incidence per 100,000 population to a range of 0.3 to 2.4 based on adjusting 2002 air quality and a range of 0.3 to 1.2 based on adjusting 2004 air quality. Esti mates for cardiorespiratory mortality show similar patterns. Staff notes that in considering the estimate s of the proportion of population affected and
the number of occurrences of the health effects that are included in the risk assessment, these
limited estimates are indicative of a much broader array of O 3 -related health endpoints that are part of a “pyramid of effects” that include various indicators of morbidity that could not be included in the risk assessment (e.g., school abse nces, increased medication use, ED visits) and which primarily affect members of sensitive groups. While we had sufficient information to
estimate and consider the number of symptom days in children w ith moderate to severe asthma, we recognize that there are many other effects that may be associ ated with symptom days, such as increased medication use, school and work absen ces, or visits to doctors’ offices, that we did
not have sufficient information to estimate but are important to consider in assessing the adequacy of the current standard. The same is tr ue for more serious, but less frequent effects. We estimated hospital admissions, but we did not have sufficient information to estimate ED visits in a quantitative risk assessment. Consid eration of such unquantified risks for this array of health effects, in conjunction with risk estimates for health effects that we did quantify, leads us to conclude that they are indicative of risks to sensitive groups that can reasonably be judged to be important from a public health perspective. These risk-based considerations reinforce our conclusion that consideration should be given to revising the standard so as to provide increased public health protection, especia lly for sensitive groups such as people with asthma or other lung diseases, as well as children a nd older adults, particularly t hose active outdoors, and outdoor
workers.6-53 Taking into account the above evidence- and exposure/risk-based considerations, staff concludes that the body of information that is now available supports co nsideration of revising the current primary O 3 standard so as to afford greater public health protection, especially to sensitive groups, and that it doe s not support retention of the current standard. The following sections on indicator, averaging time, level, and form are intended to help inform consideration of an appropriate range of alternative standards.

6.3.2 Indicator

In the last review EPA focused on a standard for O 3 as the most appropriate surrogate for ambient photochemical oxidants. In this review , while the complex atmospheric chemistry in
which O 3 plays a key role has been highlighted, no alternatives to O 3 have been advanced as being a more appropriate surrogate for ambient photochemical oxidants. It is generally recognized that control of ambient O 3 levels provides the best means of controlling photochemical oxidants of potentia l health concern. Further, among the photochemical oxidants, the acute exposure cham ber, panel and field epidemiological human health database provides evidence only for O 3 at levels of photoche mical oxidants commonly reported in the ambient air, in part because few other photochemical oxidants are routinely measured. However, recent invest igations on copollutantinteractions have used simulated urban photochemical oxidant mixes. Thes e investigations suggest the need for similar studies to help in understanding the biological basis for effects observed in epidemiologi cal studies that are associated with air pollutant mixtures, where O 3 is used as the surrogate for the mix of photochemical oxidants. Meeting the O 3 standard can be expected to provide some degree of protection against potential health effects that may be independently associated with other photochemical oxidants but which ar e not discernable from current ly available studies indexed by O 3 alone. Since the precursor emissions that lead to the formation of O 3 generally also lead to the formation of other photochemical oxidants, m easures leading to redu ctions in population exposures to O 3 can generally be expected to lead to reductions in population exposures to other photochemical oxidants.

6.3.3 Averaging Time

6.3.3.1 Short-Term and Prolonged (1 to 8 Hours) The current 8-hr averaging time for the primary O 3 NAAQS was set in 1997. The decision to revise the averaging time of the primar y standard from 1 to 8 hr was supported by the following key observations and conclusions (62 FR 38861): (1) The 1-hr averaging time of the previ ous NAAQS was originally selected on the basis
of health effects associated with s hort-term (i.e., 1- to 3-hr) exposures.6-54 (2) Substantial health effects informa tion was available for the 1997 review that
demonstrated associations between a wide range of health eff ects (e.g., moderate to large lung function decrements, moderate to severe symp toms and pulmonary inflammation) and prolonged (i.e., 6- to 8-hr) exposures below the level of the NAAQS. (3) Results of the quantitative risk analyses showed that reductions in risks from both short-term and prolonged exposures could be ach ieved through a primary standard with an averaging period of either 1 or 8 hr. (4) The 8-hr averaging time is more directly associated with health effects of concern at
lower O 3 concentrations than the 1-hr averaging time . It was thus the consensus of CASAC “that an 8-hour standard was more appropriate for a human health-based standard than a 1-hour standard.” (Wolff, 1995) In looking at the new information that is discussed in se ction 7.6.2 of the CD, epidemiological studies have used various averaging periods for O 3 concentrations, most commonly 1-hr, 8-hr and 24-hr aver ages. As described more speci fically below, in general the results presented from U.S. and Canadian stud ies (Appendix 3B) show no consistent difference for various averaging times in different studies. Only a few studies presen ted results for different O 3 averaging periods using the same data set. Two of the recent multi-city mortal ity studies reported associations for multiple averaging times (Bell et al., 2004; Gryparis et al., 2004). Both repor ted that the effect estimates for different averaging times we re not statistically different, though the effect estimates for associations with 1-hr daily maximum O 3 concentrations were somewhat larger than those for longer averaging times, especially 24-hr average O 3 . In addition, Gent et al., (2003) reported that
associations for 1-hr and 8-hr average O 3 with respiratory symptoms were not significantly
different. Among the single-city epidemiological studies, Peters et al. (2001) reported positive, but not statistically significant associations between O 3 and the incidence of myocardial infarction (CD, p. 7-55); this study differs fr om most since the short-term O 3 concentration used was the time period preceding the health event, not the hi ghest daily short-term average concentration.
The effect estimate for the association with O 3 averaged over a 2-hr period prior to the myocardial infarction was substan tially larger than that reported for an association with 24-hr average O 3 (Peters et al., 2001). The CD reports results for a number of single-city results that generally reported effect estimate sizes that were larger when compari ng 1-hr or 8-hr daily
maximum O 3 concentrations with the 24-hr concen tration, but the results did not differ statistically (CD, p. 7-120). The CD observes that the various O 3 average concentrations were generally very highly correlated wi th one another, so it is not su rprising that effect estimates6-55 would be similar. The CD concludes that th e epidemiological study results were generally comparable for the three O 3 averaging times (CD, p. 7-120). Because the 8-hr averaging time continues to be more directly associated with health effects of concern from controlled human expos ure studies at lower c oncentrations than do shorter averaging periods, we have not focused on alternative averaging times in this review and have not conducted exposure or risk assessments for standards with averaging times other than 8
hours. In its letter to th e Administrator, the CASAC O 3 Panel supported the continued use of an 8-hr averaging time for the primary O 3 standard (Henderson, 2006c, p. 2), as did many

commenters. Some other commenters expresse d the view that considerati on should be given to setting or reinstating a 1-hr standard, in addition to maintaining the use of an 8-hr averaging time, to protect people in those parts of the country with relatively mo re “peaky” exposure profiles. These commenters point out that when contro lled exposure studies us ing triangular exposure patterns (with relatively higher 1- hr peaks) have been compared to constant exposure patterns with the same aggregate O 3 dose (in terms of concentration x time), “peaky” exposure patterns are seen to lead to higher risks. The California Air Resources Boar d made particular note of this point, expressing the view that a 1-hr standard wo uld more closely represent actual exposures, in that many people spend only 1 to 2 hours a day out doors, and that it would be better matched to

O 3 concentration profiles along the coasts where O 3 levels are typically high for shorter averaging periods than 8 hours. In considering the information discusse d above, CASAC views and public comments on the earlier draft of this Staff Paper, staff concl udes that the 8-hr averaging time remains the most appropriate averaging time for a human health-bas ed standard. This conclusion is based on the observations summarized above, partic ularly: (1) the fact that th e 8-hr averaging time is more directly associated with health effects of concern at lower O 3 concentrations than are averaging times of shorter duration and (2) results from quan titative risk analyses showing that attaining an
8-hr standard reduces the risk of experiencing health effects associ ated with both 8-hr and shorter duration exposures. Furthermore, the CASAC O 3 Panel unanimously agre ed that the healthbased standard should be an 8-hr average in 1995 (Wolff, 1995) and made no comment in 2006 (Henderson, 2006c) to suggest that any averaging time ot her than 8-hr was appropriate for the
health-based standard. In addition to quantitative risk analyses, we conducted an anal ysis of a recent three-year period of air quality data (2002 to 2004) to determine whether th e comparative 1- and 8-hr air quality patterns that were observed in the last review continue to be observed based on more recent air quality data. This updated air quality analysis (McCluney, 2007) is very consistent with the analysis done in the last review in that it indicates that only two urban areas of the U.S.6-56 have such “peaky” air quality patterns that the ratio of 1-hr to 8-hr design values is greater than 1.5. This suggests that based on rece nt air quality data, it is reasona ble to again conclude that an 8-hr average standard at or below the current level would generally be expected to provide protection equal to or greater th an the previous 1-hr standard of 0.12 ppm in almost all urban areas. Thus, staff concludes that setting a standa rd with an 8-hr averaging time can effectively limit both 1- and 8-hr exposures of concern and is appropriate to prov ide adequate and more uniform protection of public health from bot h short-term and prolonged exposures to O 3 in the ambient air. Therefore, we recommend that th e 8-hr averaging time be retained and do not recommend consideration of a separa te 1-hr standard at this time.

6.3.3.2 Long-Term During the last review, there was a large anim al toxicological database for consideration that provided clear evidence of associations be tween long-term (e.g., from several months to years) exposures and lung tissue damage, with additional evidence of reduced lung elasticity and accelerated loss of lung function. However, there was no corresponding evidence for humans, and the state of the science had not progressed su fficiently to allow quantitative extrapolation of the animal study findings to humans. For these reasons, consideration of a separate long-term primary O 3 standard was not judged to be appropriate at that time, rec ognizing that the 8-hr standard would act to limit long- term exposures as well as shor t-term and prolonged exposures. In the current review, long-term animal to xicological studies c ontinue to support the relationship between O 3 exposure and structural alterations in several regions of the respiratory tract and identify the CAR as the most affected region. In addition, animal toxicological studies that utilized exposure regimens to simulate seas onal exposure patterns also report incr eased lung injury compared to conventional long-term, st able exposures. (CD, p. 8-85) Collectively, the
evidence from animal studies strongly suggest that O 3 is capable of damaging the distal airways and proximal alveoli, resulting in lung tissue re modeling leading to apparently irreversible changes. Compromised pulmonary function an d structural changes due to persistent inflammation may exacerbate the progression and development of chronic lung disease (CD, p. 8-70). Recent epidemiological studies observed that reduced lung functio n growth in children was associated with seasonal exposure to O 3 ; however, cohort studies in vestigating the effect of annual or multiyear O 3 exposure observed little clear evid ence for impacts of longer-term, relatively low-level O 3 exposure on lung function development in children. Collectively, the epidemiological studies ar e inconclusive, but sugge stive of respiratory health effects from long-term O 3 exposure. While there continues to be evidence of structural changes in the respiratory tract in animal studies, with some very weak support from epidemiological studies in children, it is highly uncertain as to what long-term patterns of6-57 exposure or O 3 concentrations in humans may be requi red to produce the morphological changes
found in the animal studies and it is not curren tly possible to characteri ze the possible magnitude or severity of any such effects occurr ing in humans in response to ambient O 3 exposures at levels observed in the U.S.. Further, to the extent that meeting an 8-hr O 3 standard in some cases is expected to result in lower long-term average concentrations, the 8-hr standard would provide some protection against effects that may be associated with long-term O 3 exposures. In its letter to the Administrator, the CASAC O 3 Panel offered no views on the long-term exposure evidence, nor did it suggest that consideration of a primary O 3 standard with a longterm averaging time was appropriate (Hende rson, 2006c, p. 2). Similarly, no commenters expressed support for consid ering such a standard.
Staff concludes that a health-based standard with a longer-term averaging time than 8 hours is not warranted at this time. While poten tially more serious health effects have been identified as being associated with longer-ter m exposure studies of laboratory animals and in epidemiology studies, there remains substantial un certainty regarding how these data could be used quantitatively to develop a basis for setting a long-term health standard. Because long-term air quality patterns would be impr oved in areas coming into attainme nt with an 8-hr standard, the potential risk of health effects associated with long-term exposures would be reduced in any area meeting an 8-hr standard. Furthermore, the CASAC O 3 Panel offered no advice either in 1995 (Wolff, 1995) or in 2006 (Henderson, 2006c) that a long-term health-based standard should be considered. Thus, staff does not recommend consid eration of a long-term, health-based standard
at this time.

6.3.4 Level In considering alternative O 3 standard levels that would pr ovide greater protection against the array of O 3 -related adverse health effects than that afforded by the current standard, staff has taken into account both evidence- and exposure/ risk-based considerations, as well as the comments and advice of CASAC and public commenter s’ views. The discussion of alternative levels in this section builds upon the informa tion presented above in the discussion of the adequacy of the current standard (section 6.3.1) to help inform staff’s evaluation of the range of levels that would be appropriate for consideration. As an initial matter, we have considered whet her it is appropriate to continue to specify
the level of the O 3 standard to the nearest hundredth (two decimal places) ppm, or whether the precision with which ambient O 3 concentrations are measured supports specifying the standard level to the nearest thousandth ppm (i.e., to the nearest part pe r billion (ppb)). As discussed above in Chapter 2 (section 2.4.2), staff conducted an analysis to determine the impact of
ambient O 3 measurement error on calculated 8-hr average O 3 design value concentrations, which6-58 are compared to the level of the standard to determine whether the standard is attained (Cox and Camalier, 2006). The results of this analysis sugges t that instrument me asurement error, or possible instrument bias, contribute very little to the uncertainty in design values. More specifically, measurement imprecision was determ ined to contribute less than 1 ppb to design value uncertainty, and a simulati on study indicated that randomly occurring instrument bias could contribute approximately 1 ppb. Staff has inte rpreted this analysis as being supportive of specifying the level of the standard to the ne arest thousandth ppm. This information was provided to the CASAC O 3 Panel and made available to th e public at the August 24-25, 2006 public meeting. The Panel concluded that cu rrent monitoring technology “allows accurate
measurement of O 3 concentrations with a precision of parts per billion ” and recommended that the specification of the level of the O 3 standard should reflect th is degree of precision (Henderson, 2006c). 22 Based on these considerations, sta ff recommends that consideration be given to specifying the level of an alternative 8-hr O 3 standard to the nearest thousandth ppm. If the current standard were to be specified to th is degree of precision, th e current standard would effectively be at a level of 0.084 ppm, reflecting the data rounding conventions that are part of the definition of the current 0.08 ppm 8-hr standard.

6.3.4.1 Evidence-based Considerations In taking into account evidence-based cons iderations, staff has evaluated available evidence from controlled human exposure studie s and epidemiological studies, as well as the
uncertainties and limitations in that evidence. In so doing, we focused primarily but not exclusively on U.S. and Canadian studies. In part icular, we have considered the extent to which controlled human exposure studies provide evidence of lowest-obs erved-effects levels and the extent to which epidemiological studies provide evidence of associations that extend down to the
lower levels of O 3 concentrations observed in the studies or some indication of potential effect thresholds in terms of 8-hr average O 3 concentrations. In considering the available controlled huma n exposure studies, as discussed above in Chapter 3 (section 3.3.1.1), we note that FEV 1 decrements and various measures of respiratory symptoms were observed in some healthy adu lts following a 6.6-hr exposure level of 0.06 ppm (reflecting exposures of 0.060 + 0.003 ppm) during moderate ex ertion. More specifically, Adams (2002) reports that in an earlier study (Adams, 1998) 20% of subjects (6 of 30 subjects) had notable responses (FEV 1 decrements > 10%) at the 0.06 ppm exposure level, and data underlying the Adams (2006) study show that 7% of healthy adult subjects had > 10% FEV 1

22 We also note that the 8-hr O 3 standard adopted by the state of Ca lifornia in 2006 is specified to the nearest thousandth part per million (at a level of 0.070 ppm) ( http://www.arb.ca.gov/research/aaqs/ozone-rs/ozoners.htm ).6-59 decrements at the 0.06 ppm exposure level in that study. Notably, in Adams (2006), total respiratory symptoms (which in cludes pain on deep inspiration, shortness of breath, and cough) following 5.6 and 6.6-hr exposures at 0.06 ppm (during a triangular exposure pattern, that is more representative of those en countered in summer air polluti on episodes than a square-wave exposure pattern) reached statistical significance. In considering the controlled human exposure study results discussed above in the
context of the broader bo dy of controlled human exposure studies, we conclude that these studies provide evidence of a lowest- observed-effects level of 0.060 ppm for potentially adverse lung function decrements and respiratory symptoms in some healthy adults while at prolonged
moderate exertion. We further conclude that since people with asthma, particularly children,
have been found to be more sensitive and to e xperience larger decrements in lung function in response to O 3 exposures than would healthy adults, the 0.060 ppm exposure level also can be interpreted as representing a level likely to cause adverse lung function decrements and respiratory symptoms in children with asthma a nd more generally in people with respiratory
disease. In considering controlled human exposure st udies of pulmonary inflammation, airway responsiveness, and impaired host defense capabi lities, we note that these studies provide
evidence of a lowest-observed-e ffects level for such effects in healthy adults at prolonged moderate exertion of 0.08 ppm (general ly reflecting exposures of 0.080 ppm + 0.004 ppm). As discussed above, these physiologi cal effects have been linked to aggravation of asthma and increased susceptibility to resp iratory infection, potentially lead ing to increased medication use, increased school and work absences, increased vis its to doctors’ offices and EDs, and increased hospital admissions. Further, pulmonary infl ammation is related to increased cellular permeability in the lung, which may be a mechanism by which O 3 exposure can lead to cardiovascular system effects, and to potential ch ronic effects such as ch ronic bronchitis or longterm damage to the lungs that can lead to reduce d quality of life. Thes e are all indicators of
adverse O 3 -related morbidity effects, which are cons istent with and lend plausibility to the adverse morbidity effects and mortality effects observed in epidemiological studies. In considering epidemiological studies, we first recognize that the available evidence neither supports nor refutes th e existence of effect threshol ds at the population level for morbidity and mortality effects. As discussed above, based on a consider ation of studies that have explored the question of poten tial thresholds and of seasonal st udies that show no consistent

O 3 -related effects during the cold season when O 3 concentrations are generally low, we conclude that if a population threshold leve l does exist, it would likely be well below the level of the

current O 3 standard and possibly within the range of background leve ls. More specifically, as discussed above in Chapter 3 (section 3.4.5) and more fully in the CD (Chapter 7, section 7.6.5),6-60 a number of studies reported so me suggestive evidence of possibl e thresholds for morbidity and mortality outcomes in terms of 24-hr, 8-hr, a nd 1-hr averaging times. These results, taken together, provide some indication of possible 8-hr average threshold levels from below about 25 to 35 ppb up to approximately 50 ppb. Other stud ies, however, observe linear concentrationresponse functions suggesting no effect threshold. In considering this information, we conclude that the statistically significant associations between ambient O 3 concentrations and lung function decrements, respiratory symptoms, i ndicators of respirator y morbidity including increased ED visits and hospitals admissions, a nd possibly mortality reported in a large number of studies likely extend down to ambient O 3 concentrations that are well below the level of the
current standard. Toward the lower end of the range of O 3 concentrations observed in such studies, ranging down to background levels, howev er, we conclude that there is increasing uncertainty as to whether the observed associati ons remain plausibly related to exposures to
ambient O 3 , rather than to the broader mix of air po llutants present in the ambient atmosphere.
We have also considered studi es that did subset analyses that include only days with
ambient O 3 concentrations below the level of the current standard, or below even lower O 3 concentrations, and continue to re port statistically significant asso ciations. Notably, as discussed above, Bell et al. (2006) conducted a subset analysis that cont inued to show statistically significant associations even when only days with a maximum 8-hr average O 3 concentration below a value of approximately 61 ppb were included. 23 Also of note is the large multi-city NCICAS (Mortimer et al., 2002) th at reported statistically si gnificant associations between
ambient O 3 concentrations and lung function decrements even when days with 8-hr average O 3 levels greater than 80 ppb were excluded (which consisted of less than 5% of the days in the eight urban areas in the study). Being mindful of the uncertainties and limitati ons inherent in interpreting the available evidence, staff believes that the range of alternative O 3 standards appropriate for consideration in
this review should take into account information on lowest-observed-effects levels in controlled human exposure studies as well as indications of possible effect s thresholds reported in some epidemiological studies and quest ions of biological plausibility in attributing associations observed down to background levels to O 3 exposures alone. Based on the evidence and these considerations, we conclude that the upper end of the range of c onsideration should be somewhat below 0.080 ppm, the lowest-observed-effects leve l for effects such as pulmonary inflammation, increased airway responsiveness and impaired host-de fense capabilities in he althy adults while at prolonged moderate exertion. As discussed above, these physiological effects have been linked

23 Bell et al. (2006) referred to this level as being approximately equivalent to 120 μg/m 3 , daily 8-hr maximum, the World Health Organization guide line and European Commissi on target value for O 3 .6-61 to aggravation of asthma and incr eased susceptibility to respiratory infecti on, potentially leading to increased medication use, increased school and work absences, increased visits to doctors’ offices and EDs, and increased hospital admissions . Further, pulmonary inflammation is related to increased cellular permeability in the lung, which may be a mechanism by which O 3 exposure can lead to cardiovascular system effects, a nd to potential chronic effects such as chronic bronchitis or long-term damage to the lungs that ca n lead to reduced quality of life. These are all
indicators of adverse O 3 -related morbidity effects, which are consistent with and lend plausibility to the adverse morbidity effects and mortalit y effects observed in epidemiological studies reporting statistically significan t associations with ambient O 3 concentrations that range down to levels well below 0.080 ppm. Based on the evidence, we also conclude that the lower end to the range of alternative O 3 standards appropriate for consideratio n should be at least as low as the lowest-observed-effects level for potentially a dverse lung function decrements and respiratory symptoms in healthy adults, 0.060 ppm, which is al so a level likely to ca use adverse effects in sensitive groups, and above the level where th ere is some indicati on of possible effects thresholds in epidemiological studies. In consid ering a lower end of the range for consideration, we also recognize that control stra tegies designed to attain an O 3 standard set at a particular level within an urban area, as measured at the monitor reporting the highest O 3 design value, would
cause the entire di stribution of O 3 concentrations across the area to be reduced, thus lowering not only concentrations above the level of the standard but also those below that level as well. Thus, we believe that it is appropriate to also consid er the results of the exposure and risk assessments that are based on modeling changes in the entire distribution of ambient O 3 concentrations to simulate just meeting alternative standards, di scussed below, in reachi ng conclusions about an appropriate lower end of the range for consideration.

6.3.4.2 Exposure/Risk-based Considerations

In addition to the evidence-based considera tions, staff has also c onsidered quantitative exposures and health risks estimated to occur up on meeting the current a nd alternative standards to help inform judgments about a range of standard levels for cons ideration that could provide an appropriate degree of public he alth protection. In so doing, we are mindful of the important
uncertainties and limitations that are associated with the exposure and risk assessments, as
discussed above in section 6.3.1.2 a nd more fully in Chapters 4 and 5. For example, important uncertainties affecting the exposure estimates are related to modeling human activity patterns

over an O 3 season (especially re petitive exposures), modeling micr oscale variations in ambient concentrations, and modeling buildin g air exchange rates. With regard to the risk assessment, important uncertainties include, for example, t hose related to exposure estimates (for children engaged in moderate or greater exertion), as well as those relate d to estimation of concentration-6-62 response functions, specification of concentra tion-response models, th e possible role of copollutants in interpreting reported associations with O 3 , and inferences of a likely causal relationship between O 3 exposure and non-accidental mortalit y (for risk estimates based on epidemiological studies). As noted above, after considering th e key uncertainties, the CASAC Panel expressed the view that the exposure an alysis represents a st ate of the art modeling approach, that the risk assessment is well-done and balanced, and that the results of both are appropriate input to the decision on the O 3 NAAQS. Beyond these uncertainties, we and CASAC al so recognize important limitations to the exposure and risk analyses. For example, we did not have sufficient information to evaluate all relevant sensitive groups (e.g., outdoor workers) or all O 3 -related health outcomes (e.g., increased medication use, school absences, ED visits), and the scope of our analyses was generally limited to estimating exposures and risk s in 12 urban areas across the U.S., and to only five or just one area for some risk analyses. Thus, it is clear that na tional-scale public health impacts of ambient O 3 exposures are much larger than the quantitative estimates of O 3 -related
incidences of adverse health e ffects and the numbers of childre n likely to experience exposures of concern associated with meeting the current or alternative standards. Taking these limitations into account, the CASAC advised us not to rely solely on the results of the exposure and risk assessments in considering alternative standards, but also to place signifi cant weight on the body
of evidence of O 3 -related health effects in drawing conc lusions about an a ppropriate range of
levels for consideration. We conc ur with this important caveat. Turning to the results of the exposure a ssessment, we examine the extent to which
alternative standard levels be low the current standard are es timated to reduce exposures of concern at the 0.070 and 0.060 ppm benchmark levels , for all and asthmatic school age children
in the 12 urban areas included in the assessment. The alternative standard levels evaluated
include standards set at: 0.080 ppm, 4 th daily maximum (i.e., the 80/4 scenario); 0.074 ppm, 5 th daily maximum (i.e., the 74/5 scenario); 0.074 ppm, 4 th daily maximum (i.e., the 74/4 scenario); 0.074 ppm, 3 rd daily maximum (i.e., the 74/3 scenario); 0.070 ppm, 4 th daily maximum (i.e., the 70/4 scenario); and, 0.064 ppm, 4 th daily maximum (i.e., the 64/4 scenario). 24 Exposure estimates for 14 scenarios are examined (i.e ., meeting 6 alternative standard level/form combinations, based on adjusting 2002 and 2004 air quality for all 6 alternative standards, and

24 The abbreviated notation used to identify the current and alternative standards in the figures showing reductions in risk estimates in this chapter is in terms of ppm and the nth highest daily maximum. For example, the current standard is identified as “0.084/4.” This notation is equivalent to the abbreviated labeling used in Chapters 4 and in the text and tables in this chapter which is in terms of ppb and the nth highest daily maximum (e.g., the current standard is labeled “84/4”).6-63 adjusting 2003 air quality for the 74/4 and 64/4 alternative standards 25 ) at the 0.060 and 0.070 ppm O 3 benchmark levels, for all children and asthma tic children. Individual city estimates of the percent of all children likely to experience ex posures of concern are gi ven in the exhibits in Chapter 4. Estimates of the percent of asthmatic children, the number of a ll children and asthmatic children, and the number of occurrences of exposures of concern, both the aggregate
estimates across the 12 urban areas and the individua l city estimates, are shown in Appendix 4A.
The estimates are for the number and percent of all ch ildren and asthmatic children exposed, and the number of person-days (occurren ces) of exposures, with daily 8-hr maximum exposures at or above the 0.060 ppm and the 0.070 ppm benchmark le vels while at intermittent moderate or greater exertion. For the purpose of this disc ussion, recommending an appropriate range of levels for consideration, we will focus on scen arios with the same form as the current O 3 standard (i.e. the 80/4, 74/4, 70/4 and 64/4 scen arios) and will addr ess consideration of
alternative forms in the next section. As shown in the exhibits in Chapter 4 and Appendix 4A, the percent of population exposed at any given level is very similar for all and asthmatic school ag e children. Substantial year-to-year variability in exposure estimates is observed, ranging to over an order of magnitude at the higher alternative standard levels, in estimat es of the number of chil dren and the number of occurrences of exposures of con cern at both of the benchmark leve ls. For example, for the 80/4 scenario, approximately 2.2 million children (~ 12%) (and 330,000 asthmatic children) based on 2002 air quality, to approximately 100,000 child ren (~0.5%) (and about 10,000 asthmatic children) based on 2004 air quality, are estimated to experience one or more exposures of
concern at the benchmark level of ≥ 0.070 ppm O 3 . For the 74/4 and 64/4 scenarios, we estimated exposures of concern at the two benchmark levels, based on air quality in 2003, which
was intermediate between 2002 and 2004. Estimates of exposures of concern for this year are
between the estimates for 2002 and 2004. Across the alternative standard leve ls, in the year with poorer air quality (2002) estimates of the number of all children exposed one or more times ranges from 2.2 million (80/4 scenario) to 30,000 ( 64/4 scenario); for asthmatic children the range is from 330,000 (80/4 scenario) to about 5,000 (64/4 scenario), at the benchmark level of ≥ 0.070 ppm O 3 . These results suggest reductions of appr oximately 35% (80/4 scenario) to nearly 100% (64/4 scenario) across the rang e of alternative standards in the number of all children and
asthmatic children at this e xposure of concern level. The estimates of exposures of concern are cons iderably larger at the benchmark level of ≥ 0.060 ppm O 3 , and the pattern of year-to-year variabil ity remains. For example, for the 80/4

25 Estimates for exposures of concern for the year 2003 were developed since the second draft of this Staff Paper for only 2 alternative standard levels (i.e., 74/4 and 64/4) due to time constraints.6-64 scenario, approximately 6.7 million children (~ 37%) (> 1,000,000 asthmatic children) based on 2002 air quality, to more than 1,000,000 children (~6%) (and > 100,000 asthmatic children) based on 2004 air quality, are estimated to experi ence one or more exposures of concern at the
benchmark level of ≥ 0.060 ppm O 3 . In the year with poorer air quality (2002), across the alternative standard levels, estimates of the num ber of all children exposed one or more times ranges from 6.7 million (80/4 scenario) to mo re than 900,000 children (64/4 scenario); for asthmatic children the range is more than 1,000,0 00 (80/4 scenario) to more than 100,000 (64/4 scenario) at the benchmark level of ≥ 0.060 ppm O 3 . At this benchmark level, in the year with poorer air quality, these results suggest reductions of about 15% (80/4 scenario) to about 90% (64/4 scenario) in the percent of children estimate d to be exposed across the range of alternative
standards. We also note that there is substantial city -to-city variability in these estimates, as summarized in Table 6-8, and we believe it is ap propriate to consider not just the aggregate estimates across all cities, but also to consider the public health impacts in cities that receive relatively less protection from the alternative standards. For example, in considering the
benchmark level of > 0.070 ppm, for the 74/4 scenario, while the aggregate percentage of all or asthmatic children estimated to experience such e xposures of concern across all 12 cities is about 4% in the worst year, it ranges up to 14% in the c ity with the least degree of protection from that alternative standard. This pattern of city-to-city variability also occurs at the benchmark level of

≥ 0.060 ppm O 3 . While the aggregate percentage of a ll and asthmatic children estimated to experience one or more exposures of concern acro ss all 12 cities, for the 74/4 scenario, is about 25% in the worst year, it ranges up to approximate ly 50% in the city with the least degree of protection from that alternative standard. Turning to the estimates from the risk assessment, Figures 6-1 through 6-6 show the percent reduction in risk estimates from just mee ting the current standard (the 84/4 scenario) to just meeting the same alternative standard s discussed above, based on adjusting 2002 and 2004 air quality data. These figures also provide pers pective on the extent to which the risks in these recent years (i.e., 2002 and 2004) are greater than those estimated to occur upon meeting the current standard (in terms of a negative percent reduction relative to the 84/4 scenario). Figures 6-1 and 6-2 show the percent reduction in the numbers of school age children estimated to experience at least one decrement in FEV 1 ≥ 15% in each of the 12 urban areas for 2002 and 2004, respectively, and Figures 6-3 and 6-4 show the percent reduction in the number of6-65 Table 6-8. Daily Maximum Ozone Concentrations > 0.07 ppm and > 0.06 ppm Combined for 12 Urban Areas in the U.S., and the Range of Estimates for Each of the 12 Cities – Just Meeting Alternative Standards

Percent of All Children (5-18 yrs old) (18.3 million children) -- Aggregated across 12 cities (Range for each of 12 cities) Percent of Asthmatic Children (5-18 yrs old) (2.6 million children) – Aggregated across 12 cities (Range for each of 12 cities) Exposure of Concern Benchmark Level Alternative Standard

Level/ Form

2002 2003 2004 2002 2003 2004 80/4 12 (1 – 28) 1 (0 – 3) 13 (0 – 31) 0 (0 – 3) 74/5 6 (0 – 18) 0 (0 - 1) 7 (0 - 17) 0 (0 - 1) 74/4 4 (0 – 13) 1 (0 - 2) 0 (0 - 1) 5 (0 - 14) 1 (0 - 2) 0 (0 - 1) 74/3 3 (0 - 8) 0 (0 - 1) 3 (0 - 9) 0 (0 - 1) 70/4 1 (0 - 5) 0 (0 - 0) 2 (0 - 6) 0 (0 - 0) >

0.07 ppm

64/4 0 (0 - 1) 0 (0 - 0) 0 (0 - 0) 0 (0 - 1) 0 (0 - 0) 0 (0 - 0)
80/4 37 (4 – 60) 6 (1 – 18) 40 (4 – 63) 6 (0 – 19) 74/5 28 (1 – 52) 3 (0 - 11) 30 (2 - 53) 3 (0 - 11) 74/4 25 (1 – 48) 5 (2 - 14) 2 (0 - 9) 27 (1 - 51) 7 (2 - 14) 2 (0 -9) 74/3 21 (1 - 41) 1 (0 - 8) 23 (1 - 46) 1 (0 - 7) 70/4 16 (1 - 36) 1 (0 - 4) 18 (0 - 41) 1 (0 - 3) >

0.06 ppm

64/4 5 (0 - 17) 0 (0 - 1) 0 (0 - 1) 6 (0 -16) 0 (0 - 1) 0 (0 - 1)6-66 asthmatic school age children estimated to experience at least one decrement in FEV 1 ≥ 10% in only 5 urban areas for 2002 and 2004, respectively. 26 Figures 6-5 and 6-6 show the percent
reduction in risk estimates of non-accidental mortality for the 12 urban areas, for 2002 and 2004, respectively. The legend under each figure li sts the estimated number of cases (and 95% credible intervals) when O 3 concentrations just meet the curr ent standard next to the name of
each location. There were two health outcomes th at we evaluated in one city only, respiratory symptom days in moderate to severe asthmatic children (Boston, Table 6-9) and respiratoryrelated hospital admissions (New York City, Table 6-10), beca use the concentr ation-response functions were developed in these cities and we did not want to introduce additional uncertainties by applying these functions to othe r locations. We believe, however , that it is reasonable to assume that these results would be ge nerally applicable to other locations. As shown in Figures 6-1 and 6-2, we first no te that just meeting the 80/4 scenario is estimated to result in about a 20% reduction in the number of all school age children estimated to experience moderate lung function decrements ( ≥ 15% reduction in FEV 1 ) relative to the current standard. Reducing the level of the standard to the 74/4 scenario results in about a 40 to 50% reduction in the number of all school age childr en estimated to experience moderate lung function decrements, depending on whether 2002 or 2004 air quality is the basis for adjustment. As shown in Figures 6-3 and 6-4, for asthmatic school age children, reduc ing the level of the
standard to the 74/4 scenario results in about a 30 to 45% reduction in estimated risks across the
5 urban areas relative to the curren t standard. An alternative sta ndard set at the 64/4 scenario provides an appreciably greater reduction of about 65 to 80% in the number of all school age children estimated to experience mo derate lung function decrements ( ≥ 15% reduction in FEV 1 )
relative to the current standard (depending on the year adjusted a nd the urban area). This same

64/4 scenario reduces estimates of m oderate lung function decrements ( ≥ 10% reduction in

FEV 1 ) in asthmatic school age children by about 55 to 65% in most of th e areas, with 1 area having reductions of about 75%.

26 The health risk assessment for lung function decrements for asthmatic school age children was conducted for 5 of the 12 urban areas and for a more limited set of alternative standards due to time constraints. The areas were selected to be geographically diverse includi ng urban areas that are not meeting the current O 3 standard in the northeast, southeast, deep south, Midwest, and southern California.6-67 Figure 6-1. Percent Changes in Numbers of Sc hool Age Children Experiencing at Least One Decrement in FEV1 >1 5% when O3 Concentrat ions are Reduced from Those Just Meeting the Current Standard to Those that Would Just Meet Each Alternative Standard, Base d on Adjusting 2002 Data*



### -200% -150% -100%

-50%

0% 50% 100%

2002 air quality 0.084/4 0.084/3 0.080/4 0.074/ 5 0.074/4 0.074/3 0.070/4 0.064/4

Alternative StandardP ercen t C h an g e



### Atlanta: 31 (17 - 47); 3.3% (1.8% - 5%) Boston: 47 (29 - 68); 4.3% (2.6% - 6.2%) Chicago: 67 (37 - 100); 3.4% (1.9% - 5.2%) Cleveland: 27 (17 - 39); 4.6% (2.9% - 6.6%) Detroit: 45 (27 - 66); 4% (2.4% - 5.9%) Houston: 22 (9 - 36); 2% (0.8% - 3.3%) Los Angeles: 35 (8 - 63); 1% (0.2% - 1.7%) New York: 131 (70 - 200); 3.1% (1.7% - 4.8%) Philadelphia: 58 (37 - 83); 4.9% (3.1% - 7%) Sacramento: 9 (4 - 14); 2.2% (1% - 3.5%) St. Louis: 30 (20 - 43); 5.2% (3.4% - 7.4%) Washington, DC: 64 (39 - 93); 4.3% (2.6% - 6.3%)

*The numbers in the box below the figure show for each urban area the number of children estimated to experience moderate lung function decrements (FEV 1 > 15%), in thousands (and 95% credible interval) and the percent of children (and 95% credible in terval) estimated to experience these effects when O 3 concentrations just meet the current 0.084/4 8-hr standard. The 8-hr average standards shown in this figure, denoted m/n, are characterized by a concentration of m ppm and an nth-highest daily maximum form. For example, the current standard is 0.084/4 -- 0.084 ppm, 4 th -highest daily maximum 8-hr average. The figure al so compares the current standard to a recent year of air quality. The percent change from the current standard (0.084/4) to a recent year of air quality was omitted for Los Angeles because it was so large in magnitude (–528% in 2002).6-68 Figure 6-2. Percent Changes in Numbers of Sc hool Age Children Experiencing at Least One Decrement in FEV1 >1 5% when O3 Concentrat ions are Reduced from Those Just Meeting the Current Standard to Those that Would Just Meet Each Alternative Standard, Base d on Adjusting 2004 Data*



### -200% -150% -100%

-50%

0% 50% 100%

2004 air quality 0.084/4 0.084/3 0.080/4 0.074/5 0.074/4 0.074/3 0.070/4 0.064/4

Alternative StandardP ercen t C h an g e



### Atlanta: 18 (6 - 31); 1.9% (0.7% - 3.3%) Boston: 13 (3 - 25); 1.2% (0.3% - 2.3%) Chicago: 14 (0 - 30); 0.7% (0% - 1.5%) Cleveland: 6 (1 - 12); 1% (0.1% - 1.9%) Detroit: 12 (2 - 23); 1.1% (0.2% - 2.1%) Houston: 21 (8 - 35); 1.9% (0.8% - 3.2%) Los Angeles: 33 (5 - 61); 0.9% (0.1% - 1.7%) New York: 39 (4 - 77); 0.9% (0.1% - 1.9%) Philadelphia: 17 (4 - 30); 1.4% (0.3% - 2.5%) Sacramento: 4 (1 - 7); 1% (0.1% - 1.8%) St. Louis: 7 (1 - 13); 1.2% (0.2% - 2.3%) Washington, DC: 24 (8 - 42); 1.6% (0.5% - 2.8%)

* The numbers shown in the box below the figure for each urban area represent the number of children estimated to experience moderate lung function decrements (FEV 1 > 15%), in thousands (and 95% credible interval) and the percent of children (and 95% credible interval ) estimated to experience these effects when O 3 concentrations just meet the current 0.084/4 8-hr standard. The 8-hr aver age standards shown in this figure, denoted m/n, are characterized by a concentra tion of m ppm and an nth-highest daily maximum form. For example, the current standard is 0.084/4 -- 0.084 ppm, 4 th -highest daily maximum 8-hr average. The figure also compares the current standard to a recent year of air quality. The percent change from the current standard (0.084/4) to a recent year of air quality was omitted for Los Angeles because it was so large in magnitude (-553% in 2004).6-69 Figure 6-3. Percent Changes in Numbers of As thmatic School Age Children Experiencing at Least One Decrement in FEV1 >10% when O3 Concentrations are Reduced from Those Just Meeting the Current Sta ndard to Those that Would Just Meet Each Alternative Standard, Based on Adjusting 2002 Data*



### -200% -150% -100%

-50%

0% 50% 100%

2002 air quality 0.084/4 0.074/4 0.064/4

Alternative StandardsPercent Change from CurrentStandard



### Atlanta: 11 (8 - 16); 9.6% (7.2% - 13.9%) Chicago: 26 (20 - 38); 9.4% (7% - 13.5%) Houston: 8 (6 - 13); 6.2% (4.4% - 9.5%) Los Angeles: 16 (11 - 24); 3.4% (2.5% - 5.3%) New York: 58 (43 - 85); 9.1% (6.7% - 13.3%)

*The numbers shown in the box below the figure show for each urban area the number of asthmatic children estimated to experience moderate lung function decrements (FEV 1 > 10%), in thousands (and 95% credible interval) and the percent of asthmatic children (and 95% credible interval) estimated to experi ence these effects when O 3 concentrations just meet the current 0.084/4 8-hr standard. The 8-hr average standards shown in this figure, denoted m/n, are characterized by a concentration of m ppm and an nth-highest daily maximum form. For example, the current standard is 0.084/4 -- 0.084 ppm, 4 th -highest daily maximum 8-hr average. The figure also compares the current standard to a r ecent year of air quality. The percent change fr om the current standard (0.084/4) to a recent year of air quality was omitted for Los Angeles becaus e it was so large in magnitude (-275% in 2002).6-70 Figure 6-4. Percent Changes in Numbers of As thmatic School Age Children Experiencing at Least One Decrement in FEV1 > 10% when O3 Concentrations are Reduced from Those Just Meeting the Current Sta ndard to Those that Would Just Meet Each Alternative Standard, Based on Adjusting 2004 Data*



### -200% -150% -100%

-50%

0% 50% 100%

2004 air quality 0.084/4 0.074/4 0.064/4

Alternative StandardsPercent C hange from C urrentStandard



### Atlanta: 7 (5 - 11); 6.2% (4.2% - 9.8%) Chicago: 8 (5 - 13); 3% (1.7% - 4.8%) Houston: 8 (6 - 13); 6.1% (4.3% - 9.4%) Los Angeles: 16 (11 - 25); 3.4% (2.4% - 5.4%) New York: 24 (14 - 39); 3.7% (2.2% - 6%)

*The numbers in the box below the figure show for each urban area the number of asth matic children estimated to experience moderate lung function decrements (FEV 1 > 10%), in thousands (and 95% credible interval) and the percent of asthmatic children (and 95% credible inte rval) estimated to experi ence these effects when O 3 concentrations just meet the current 0.084/4 8-hr standard. The 8-hr average standards shown in this figure, denoted m/n, are characterized by a concentration of m ppm and an nth-highest daily maximum form. For example, the current standard is 0.084/4 -- 0.084 ppm, 4 th -highest daily maximum 8-hr average. The figure also compares the current standard to a r ecent year of air quality. The percent change fr om the current standard (0.084/4) to a recent year of air quality was omitted for Los Angeles beca use it was so large in magnitude (-281% in 2004).6-71 Figure 6-5. Percent Changes in O3-Related No n-Accidental Mortality Incidence when O3 Concentrations are Reduced from Those Just Meeting the Current Standard to Those that Would Just Meet Each Alt ernative Standard, Based on Adjusting 2002 Data* (Using Bell et al., 2004 – 95 U.S. Cities)

*The numbers in the box below the figure show for each ur ban area the number of cases (and 95% credible interval) and the percent of tota l incidence (and 95% cr edible interval) of O 3 -related non-accidental mortality when O 3 concentrations just meet the current st andard (0.084/4). The 8-hr average standards shown in this figure, denoted m/n, are characterized by a concentration of m ppm and an nth-highest daily maximum form. For example, the current standard is 0.084/4 -- 0.084 ppm, 4 th -highest daily maximum 8-hr average. The figure also compares the current standard to a recent year of air quality

. -120% -100%

-80% -60% -40% -20%

0% 20% 40% 60% 80%

2002 air quality 0.084/4 0.084/3 0.080/4 0.074/5 0.074/4 0.074/3 0.070/4 0.064/4

Alternative StandardPercent Change from Current Standard

Atlanta: 14 (5 - 23); 0.3% (0.1% - 0.5%) Boston: 9 (3 - 15); 0.3% (0.1% - 0.6%) Chicago: 55 (18 - 91); 0.3% (0.1% - 0.4%) Cleveland: 31 (10 - 52); 0.4% (0.1% - 0.7%) Detroit: 24 (8 - 39); 0.3% (0.1% - 0.4%) Houston: 9 (3 - 15); 0.1% (0% - 0.2%) Los Angeles: 52 (17 - 86); 0.2% (0.1% - 0.3%) New York: 84 (28 - 139); 0.3% (0.1% - 0.4%) Philadelphia: 30 (10 - 50); 0.4% (0.1% - 0.6%) Sacramento: 18 (6 - 30); 0.4% (0.1% - 0.7%) St Louis: 5 (2 - 8); 0.2% (0.1% - 0.4%) Washington: 14 (5 - 23); 0.5% (0.2% - 0.8%)6-72 Figure 6-6. Percent Changes in O3-Related No n-Accidental Mortality Incidence When O3 Concentrations are Reduced from Those Just Meeting the Current Standard to Those that Would Just Meet Each Alternative Standard, Ba sed on Adjusting 2004 Data* (Using Bell et al., 2004 – 95 U.S. Cities)

* *The numbers in the box below the figure show for each urban area t he number of cases (and 95% credible interval) and the percent of total incidence (and 95% credible interval) of O 3 -related non-accidental mortality when O 3 concentrations just meet the current standard (0.084/4). The 8-hr average standards shown in this figure, denoted m/n, are characterized by a concentration of m ppm and an nth-highest daily maximum form. For example, the current standard is 0.084/4 -- 0.084 ppm, 4 th -highest daily maximum 8-hr average The figure also compares the current standard to a recent year of air quality. -120% -100%

-80% -60% -40% -20%

0% 20% 40% 60% 80%

2004 air quality 0.084/4 0.084/3 0.080/4 0.074/5 0.074/4 0.074/3 0.070/4 0.064/4

Alternative StandardPercent Change from Current Standard

Atlanta: 9 (3 - 15); 0.2% (0.1% - 0.3%) Boston: 6 (2 - 9); 0.2% (0.1% - 0.4%) Chicago: 33 (11 - 55); 0.2% (0.1% - 0.3%) Cleveland: 12 (4 - 20); 0.2% (0.1% - 0.3%) Detroit: 12 (4 - 20); 0.1% (0% - 0.2%) Houston: 11 (4 - 18); 0.1% (0% - 0.2%) Los Angeles: 67 (22 - 111); 0.2% (0.1% - 0.4%) New York: 43 (15 - 72); 0.1% (0% - 0.2%) Philadelphia: 17 (6 - 28); 0.2% (0.1% - 0.3%) Sacramento: 12 (4 - 21); 0.3% (0.1% - 0.5%) St Louis: 2 (1 - 4); 0.1% (0% - 0.2%) Washington: 7 (2 - 12); 0.3% (0.1% - 0.4%)6-73 As shown in Figures 6-5 and 6-6, we first not e that just meeting the 80/4 scenario is
estimated to result in about a 5 to 15 % reduction in estimated incidences of O 3 -related nonaccidental mortality relative to the current standa rd. Reducing the level of the standard to the
74/4 scenario results in the estimated inciden ces of non-accidental mortality being reduced by about 15 to nearly 40% (depending on the year adjusted and the urban area) relative to the current standard. Just meeting the 64/4 scenar io is estimated to provide appreciably greater
reduction relative to the current st andard in some areas, with an estimated reduction of about 30
to 40% in most areas and about 60 to 70% in tw o areas (depending on the year adjusted and the urban area) in the estimated incidences of O 3 -related non-accidental mortality. With regard to respiratory symptom days fo r chest tightness in moderate to severe
asthmatic children in the Boston area, as shown in Table 6-9, th e alternative standards provide incremental protection beyond that offered by the cu rrent standard. From the 80/4 scenario to the 64/4 scenario, the estimated incidence of resp iratory symptom days is reduced by 5 to 25% in the worst year, and by approximately 7 to 31% in the best year. In the wors t of the two years, the estimated percent of total incidence, or the percent of respiratory-symptom days attributable to

O 3 exposure ranges from about 14% for just meeti ng the current standard to about 10% for the
64/4 scenario. This means that even under the mo st stringent alternative standard evaluated, as many as one symptom day in 10 would be estimated to be attributable to O 3 exposure in the O 3

season. Risk estimates for respiratory-related hospital admissions attributable to O 3 exposure in New York City are shown in Table 6-10. Across th e range of alternative standards from the 80/4
scenario to the 64/4 scenari o, the estimated number of O 3 -related hospital admissions declines by about 6 to 29% in the worst year (2002), and about 7 to 34% in the best y ear (2004). The percent of total respiratory-related hospital admissions attributable to O 3 exposure declines from about
1.5% for the current standard to abou t 1% or less for the 64/4 scenario.6-74 Table 6-9. Risks of Respiratory Symptom Days for Chest Tightness Associated with Just Meeting the Current and Alternative Ozone Standards Based on Adjusting 2002 and 2004 Air Quality in Moderate to Se vere Asthmatic Children in Boston, MA 1

Average Risks of Chest Tightness Associated with Air Quality 2,3 [percent reduction from current standard] Current and Alternative Standards Risk Metric

2002 2004
Incidence 7800 5700 Current Standard (84/4) Percent of Total Incidence 14% 10%

Incidence 7400 [5% reduction] 5400 [7% reduction] 80/4

Percent of Total Incidence 13% 10%

Incidence 6800 [12% reduction] 4900 [15% reduction] 74/4

Percent of Total Incidence 12% 9%

Incidence 6400 [17% reduction] 4500 [22% reduction] 70/4

Percent of Total Incidence 12% 8%

Incidence 5900 [25% reduction] 3900 [31% reduction] 64/4

Percent of Total Incidence 10% 7%

1 It is estimated that there are 25,000 children with moderate to severe asthma in the Boston area.

2 Incidence rounded to nearest 100.
3 Average of median estimates for models using lag 0 and lag 1 day and O 3 only and including PM 2.5 in the model.6-75 Table 6-10. Risks of Hospital Admissions fo r Respiratory Illness Associated with Just Meeting the Current and Alternative Ozone Standards Based on Adjusting 2002 and 2004 Air Quality in New York, NY

Hospital Admissions for Respiratory Illness Associated with Ozone Exposures 1,2 [percent reduction from current standard] Current and Alternative Standards Risk Metric

2002 2004
Incidence 513 366 Current Standard (84/4) Percent of Total Incidence 1.5% 1.0%

Incidence 483 [6% reduction] 341 [7% reduction] 80/4

Percent of Total Incidence 1.4% 1.0%

Incidence 439 [14% reduction] 304 [17% reduction] 74/4

Percent of Total Incidence 1.2% 0.9%

Incidence 410 [20% reduction] 278 [24% reduction] 70/4

Percent of Total Incidence 1.2% 0.8%

Incidence 365 [29% reduction] 241 [34% reduction] 64/4

Percent of Total Incidence 1.0% 0.7%

1 Incidence rounded to nearest whole number.

2 95 % credible intervals based on statistical uncertainty surrounding the O 3 coefficient are presented in tables in Appendix 5C of this Staff Paper.6-76 6.3.4.3 CASAC and Public Commenters’ Views on the Level of the Standard As noted above in section 6.3.1.4, staff recogni zes that the exposur e- and risk-based
information can be considered both in terms of whether the risks estimated to remain upon attaining the current standard are important fr om a public health perspective and/or whether
additional reductions in risk es timated to be associated with alternative, more protective standards are important from a public health pers pective. Judgments abou t the importance of the estimates of exposures and risks need to take in to account the important uncertainties associated with such estimates. We recognize that public health policy judgments, including the weight to place on various types of evidence and how to we igh the importance of estimated risks in a public health perspective, are ultimately decisions left to the Administrator. To help inform those judgments with regard to the level of the primary O 3 standard, the views expressed by CASAC as well as the views of interested partie s who have commented on earlier drafts of this
document are summarized here.
As stated in its letter to the Administrator, “ the CASAC unanimously recommends that the current primary ozone NAAQS be revised and that the level that should be considered for the revised standard be from 0.060 to 0.070 ppm ” (Henderson, 2006c, p. 5). The CASAC coupled this recommended range of levels wi th a range of forms, as discusse d in the next section below.
This recommendation follows from their more general recommendation, discussed above in section 6.3.2, that the current standard of 0.08 pp m needs to be substantially reduced to be protective of human health, particularly in sens itive subpopulations. The lower end of this range reflects CASAC’s views that “[W]h ile data exist that adverse health effects may occur at levels lower than 0.060 ppm, these data are less cert ain and achievable gain s in protecting human health can be accomplished through lowering th e ozone NAAQS to a level between 0.060 and 0.070 ppm.” (id.). The same group of commenters that expre ssed the view that the current primary O 3 standard is not adequate also submitted comm ents that supported revising the level of the primary O 3 standard to within the same or even lower range of levels than the range recommended by CASAC. The basis for these comm enters’ views on the level of the standard is generally reflected in the discussion above on th e basis for their views on the adequacy of the
current standard and in the ra tionale given by CASAC. In a ddition, some of these commenters
also noted that the World Health Organization’s guidelines for O 3 air quality are in the range of 51 to 61 ppb. The other group of commenters who e xpressed the view that the current standard is adequate did not provide any provisional views on alternative le vels that would be appropriate
for consideration should the Administrato r consider revisions to the standard.6-77 6.3.4.4 Staff Conclusions on the Level of the Standard

Staff’s consideration of altern ative levels of the primary O 3 standard builds upon our conclusion, discussed above in se ction 6.3.1, that the overall body of evidence clearly calls into question the adequacy of the current standard in protecting sensitive groups, notably including asthmatic children and other people with lung disease, as well as all children and older adults, especially those active outdoors, and outdoor worker s, against an array of adverse health effects that range from decreased lung f unction to serious indicators of respiratory morbidity including ED visits and hospital admissions for respirator y causes, and possibly ca rdiovascular-related effects and mortality. Thus, we believe that th e available information provides strong support for consideration of a range of standard levels that is below the le vel of the current standard so as to afford increased health protection for these se nsitive groups. We have also concluded, as an initial matter, that it is appropriate to consider specifying the level of the O 3 standard to the nearest thousandth ppm. As discussed above in section 6.3.4.1., based on the evidence, we conclude that it is appropriate to consider a range of levels for the primary O 3 standard from somewhat below 0.080 ppm down to at least as low as 0.060 ppm. Th is evidence-based recommendation takes into
account information on lowest-obser ved-effects levels in controll ed human exposure studies as well as indications of possible e ffects thresholds reported in so me epidemiological studies and questions of biological plausibi lity in attributing associati ons observed down to background
levels to O 3 exposures alone. The upper end of this range is somewhat below the lowestobserved-effects level for effects such as pulmonary inflammation, increased airway responsiveness and impaired host-defense capab ilities in healthy adu lts while at prolonged
moderate exertion. These effects have been li nked to aggravation of asthma and increased susceptibility to respiratory inf ection, potentially leading to incr eased medication use, increased school and work absences, increased visits to doctors’ offices and EDs, and increased hospital admissions, and pulmonary inflammation is also re lated to increased cellular permeability in the lung, which may be a mechanism by which O 3 exposure can lead to cardiovascular system effects, and to potential chronic effects such as chronic bronchitis or long-term damage to the lungs that can lead to reduced quality of life. These indicators of adverse O 3 -related morbidity effects lend plausibility to the adverse morbid ity effects and mortality effects observed in epidemiological studies reporting statistically significant associations with ambient O 3 concentrations that range down to levels well below 0.080 ppm. The lower end of this range
reflects the lowest-observed-effects level for potentially adverse lung function decrements and respiratory symptoms in some healthy adults, 0.0 60 ppm, which is also a level likely to cause these adverse effects in sensitive groups, and is above the level where there is some indication of possible effects thresholds in epidemiological studies.6-78 Having reached this evidence-based conclusi on on an appropriate range of levels for consideration, we have also focused on consideri ng the public health implications of selecting
different levels within this range (< 0.08 to 0.060 ppm O 3 ). In so doing, we have looked to the results of the analyses of exposure and risk for the 74/4 scenario to repr esent the public health impacts of selecting a standard level in the upper pa rt of the range, the results of the analyses of the 70/4 scenario to represent the impacts in the middle part of the range, and the results of the analyses of the 64/4 scenario to re present the lower part of the range. As discussed above in section 6.3.4.2, for each of these alternative standard levels, we have considered exposures of concern at the two benchmark levels discussed above (i.e., 0.070 ppm and 0.060 ppm), that serve as indicators of health outcomes for which there is insufficient information to do quantitative risk assessments . We have also considered the quantitative estimates of risk for moderate lung function decr ements in all and asthmatic children, respiratory symptom days in moderate to severe asthmatic children, respiratory-re lated hospital admissions, and non-accidental mortality. In considering bot h exposures of concern and quantitative risk estimates, we again note that there is substantia l year-to-year variabilityacross the three years included in this analysis (2002 to 2004) in th e estimates of the number of children and the number of occurrences of exposur es of concern at the benchmark levels and in the quantitative
risk estimates. We also note the substantial c ity-to-city variability in these estimates of exposures of concern and quantitative risk. We believe that it is appropr iate and important to consider not just the average estimates across all y ears or all cities included in the analyses, but to consider the public health imp acts in years and locations with relatively poorer air quality and in locations receiving relatively less protection from any alternative standard. We turn now to considering the public health implications of setti ng the standard in the upper, middle and lower parts of the range. A sta ndard set in the upper part of this range (e.g., the 74/4 scenario) would result in an aggregate estimate of about 4% of all school age children 27 (~ 770,000 children in 12 urban areas) likely to experience exposures of concern at the > 0.070 ppm benchmark level in the worst (2002) of the 3 years evaluated, while the estimates range up to 13% of all school age children (~ 150,000 children) in the single c ity with the least degree of protection from this standard. In the mid-year (2003), in aggreg ate about 1% of all school age children (~110,000 children) are estimated to experience exposure s of concern at this level; in the city with the least degree of protection from this standard the estimate is less than 2% of all school age children (~ 26,000 children) . At the benchmark level of > 0.060 ppm, in aggregate in

27 We note that the percent of all school age children and asthmatic school age children estimated to experience exposures of concern (aggregate and individual city estimates) are very similar, and the results for all school age children are presented in the exhibits in Chapter 4, thus for ease of discussion we present results for all school age children here.6-79 the worst year about 25% of all school age ch ildren (~ 4.4 million children) are estimated to experience exposures of concern; this estimate ranges up to about 48% of all school age children (~ 1 million children) in the single city with th e least degree of protection from this standard. Even in the mid-year, in aggregate about 7% of all school age children (~ 1.3 million children) are estimated to experience exposures of concer n, ranging up to 15% of all school age children (~290,000 children) in the single city with the leas t degree of protection from this standard. A
standard set at this level w ould reduce the number of all and asthmatic school age children estimated to experience one or more moderate lung function decrements by about 30 to 50%
relative to the current st andard (Figures 6-1 through 6-4), wi th city-to-city differences accounting for most of the variability in estimates. A sta ndard set at this level would reduce non-accidental mortality by about 10 to 40%, with most of the variab ility occurring across the 12 city estimates (Figures 6-5 and 6-6).
There were two health outcomes that we ev aluated in one city onl y, respiratory symptom days in moderate to severe asthmatic childre n (Boston, Table 6-9) a nd respiratory-related hospital admissions (New York City, Table 6-10). In the worst year, a standard set at this level (the 74/4 scenario) is estimated to reduce the incidence of symptom days in children 28 with
moderate to severe asthma in the Boston area to 6,800 days, a 12% redu ction relative to the
current standard. Even with th is reduction, it is estimated that 1 respiratory symptom day in 8 during the O 3 season would be attributable to O 3 exposure. Estimated incidence of respiratoryrelated hospital admissions was redu ced by 14 to 17% by a standard se t at this level relative to the current standard, in the year with worst and best air quality respectively. A standard set at this level reduces exposur es of concern at the > 0.070 benchmark level much more than exposures of concern at the > 0.06 ppm benchmark level, placing relatively less weight on the evidence from the controlled human exposure st udies showing lung function decrements and respiratory symptoms in some healthy adults at 0.060 ppm O 3 , as well as evidence from epidemiological studies showing an array of respiratory morbidity effects occurring at levels well
below the current standard. It would place relatively more weight on the uncertainties associated with the exposure and risk estimates, sugges ting less importance for the implications of exposures at the 0.060 ppm benchmark level fr om a public health policy perspective. A standard set in the middle part of this ra nge (e.g., the 70/4 scenar io) would result in an aggregate estimate of about 1% of all school ag e children (> 250,000 children in 12 urban areas) likely to experience exposures of concern at the > 0.070 ppm benchmark level even in the worst year (2002); in the c ity with the least prot ection about 5% of all school age children (~ 64,000

28 Since there are estimated to be about 25,000 modera te to severe asthmatic children in the Boston area, this incidence rate is per 25,000 children.6-80 children) are estimated to experience exposures of concern at this level. 29 At the benchmark
level of > 0.060 ppm, in aggregate in the worst year about 16% of all school age children (~ 3 million children) are estimated to experience exposures of concern; this number ranges up to 36% of all school age children (~ 600,000 children) in the single city with the least degree of protection from this standard. A standard set at this level woul d reduce the number of all school age children 30 estimated to experience one or more m oderate lung function decrements by about 50 to 65% over the current standard, with city -to-city differences accounting for most of the variability in estimates. A standard set at th is level would reduce non- accidental mortality by about 20 to 55%, with most of the variability occurring ac ross the 12 city estimates. In the worst year, a standard set at this level is estimated to reduce the incidence of symptom days in children
with moderate to severe asthma in the Boston ar ea only slightly over the standard set at the upper end of the range, to 6,400 days (a 12% reduction). With this reduc tion, it is estimated that about 1 respiratory symptom day in 8 during the O 3 season would be attributable to O 3 exposure. Estimated incidence of respirat ory-related hospital admissions was reduced by about 20 to 24% in the year with worst and best air quality, respectively. A standard set in the middle part of the r ecommended range, as indicated by the estimates for the 70/4 scenario, would reduce the exposures of concern at the 0.070 ppm level substantially over the current standard, even in the worst of the three years and in the city with the least degree of protection. However, it reduces exposures of concern at the 0.060 ppm benchmark level much less so, leaving relatively large percentages of all school age children unprotected in the worst year or the city with the least protection from this standard. It provides incremental additional protection for members of sensitive groups, over the current O 3 standard, against respiratory morbidity effects such as lung function decrem ents, respiratory symptom days and hospital admissions, as well as non-accidental mortality. A standard set in the lower part of this ra nge (e.g., the 64/4 scenario) would result in an aggregate estimate of less than 0.5% of all sc hool age children (~ 30,000 children) likely to experience exposures of concern at the 0.070 ppm benchmark level in the worst year and only 1% of all school age children (9,900 children) in the city with th e least degree of protection from this standard. In the mid-year (2003), estimates of exposures of concern go close to zero, even in the city with the least degree of protection. At the benchmar k level of 0.060 ppm, in aggregate in the worst year about 5% of all school age children (~ 950,000 children) are estimated to experience exposures of concern; this number ranges up to 17% of all school age children

29 Estimates were not developed for the mid-year (2003) for this alternative standard.

30 Estimates for asthmatic children were not developed for this alternative standard.6-81 (~200,000 children) in the city with the least degree of protection from this standard. In the midyear exposures of concern at th is level are reduced substantia lly, resulting in an aggregate estimates of less than 0.5% of all school age children (~ 70,0 00 children), ranging up to only 1% of all school age children (~ 13,000 children) in the city with the least degree of protection from
this standard. A standard set at this level w ould reduce the number of all and asthmatic school age children estimated to expe rience one or more moderate lu ng function decrements by about 50 to 80% over the current standard, and non-accid ental mortality by about 25 to 75%, with most of the variability occurri ng across the 12 city estimates. In the worst year, a standard set at this level is estimated to reduce the incidence of symp tom days in children with moderate to severe asthma in the Boston area to 5,900 days, about a 25% reduction over the cu rrent standard. But even with this reduction, it is estimated that 1 respiratory symptom day in 10 during the O 3 season is attributable to O 3 exposure. Estimated incidence of respiratory-related hospital admissions was reduced by 30 to 35% over the current standard, in the year with worst and best air quality respectively. These results indicate that setting a standa rd in the lower part of the range would essentially eliminate exposures of concern at the benchmark level of 0.070 ppm, even in the worst of the three years and in the city with the least de gree of protection. It would also substantially reduce exposu res of concern at the benchmark le vel of 0.060 ppm, especially in the mid-year of the three years evaluated. It prov ides additional incremental protection for members of sensitive groups over the current O 3 standard and the alternativ e standards at the upper to middle part of the range, against respiratory morb idity effects such as l ung function decrements, respiratory symptom days and hospital admission s, as well as non-accidental mortality. A standard set in the lower part of the range would place relatively more weight on the evidence from the controlled human exposure studies s howing lung function decrements and respiratory symptoms in some hea lthy adults at 0.060 ppm O 3 , as well as evidence from epidemiological studies showing an array of respiratory morbidit y effects occurring at levels below the current standard. It would place relativel y less weight on the uncertaintie s associated with the exposure and risk estimates, and reflect the greater importa nce, from a policy perspective, of the public health implications of exposures at the 0.060 ppm benchmark level. The CASAC recommended a range down to 0.060 ppm for the level of the O 3 standard, noting that “achievable gains in protecting public health” (Henders on 2006c, p. 5) can be accomplished by setting the level of the standard down to 0.060 ppm O 3 . The results of the exposure and risk assessments support this r ecommendation. Staff concludes that important improvements in protecting the health of sensitive groups can be made by setting the level of the

O 3 standard within the range of < 0.080 ppm to 0.060 ppm O 3 . Standard levels within this range considered in staff exposure and risk a ssessments include 0.074, 0.070, and 0.064 ppm, which6-82 are representative of levels with in the upper, middle, and lower pa rts of this range, respectively. Moreover, these assessment results indicate that even in the lo wer end of the range there are
benefits to the health of sensitiv e groups that warrant consideration. To provide some perspective on the implicati ons of alternative 8- hr primary standards (within the range of levels recommended above a nd within the range of forms discussed in the next section below), staff asse ssed (based on 2002 and 2004 air quali ty data) the percentage of counties, and the populations in those counties, that likely w ould not attain various 8-hr O 3 standards. This assessment, shown in Appendix 6B for various forms and levels of the 8-hr standards, was not considered as a basis for the above staff conclusi ons and recommendations.

6.3.5 Form In 1997 the primary O 3 NAAQS was changed from a “1-expected-exceedance” form 31 to a concentration-based statistic, sp ecifically the 3-year average of the annual fourth-highest daily maximum 8-hr concentrations. The principal advant age of the concentration-based form is that it is more directly related to the ambient O 3 concentrations that are associated with the health effects. With a concentration-based form, days on which higher O 3 concentrations occur would weigh proportionally more than days with lower concentrations, since the actual concentrations are used in determining whether th e standard is attained. That is , given that there is a continuum of effects associated with expos ures to varying levels of O 3 , the extent to which public health is affected by exposure to ambient O 3 is related to the act ual magnitude of the O 3 concentration, not just whether the concentration is above a specified level. In evaluating alternative forms for the prim ary standard in conj unction with specific standard levels, staff considers the adequacy of the public health pr otection provided by the
combination of the level and form to be the fo remost consideration. In addition, we recognize that it is important to have a form of the standard that is stable and insu lated from the impacts of extreme meteorological even ts that are conducive to O 3 formation. Such instability can have the effect of reducing public health protection, because frequent shifti ng in and out of attainment due of meteorological conditions can disrupt an area’s ongoing impleme ntation plans and associated control programs. Providing more stability is one of the reasons that EPA moved to a
concentration-based form in 1997. During the 1997 review, consid eration was given to a rang e of alternative forms, including the second-, thir d-, fourth- and fifth-highest daily ma ximum 8-hr concentrations in an

O 3 season, recognizing that the public health risk s associated with exposure to a pollutant

31 The 1-expected-exceedance form essen tially requires that the fourth-highe st air quality value in 3 years, based on adjustments for missing data, be less than or equal to the level of the standard for the standard to be met at an air quality monitoring site.6-83 without a clear, discernable thre shold can be appropriately addr essed through a standard that allows for multiple exceedances to provide increased stability, but that also significantly limits the number of days on which the level may be ex ceeded and the magnitude of such exceedances. Consideration was given to setting a standard with a form that w ould provide a margin of safety against possible, but uncertain chronic effects, and would also provide greater stability to ongoing control programs. The fourth-highest daily maximum was selected because it was
decided that the differences in the degree of protection against pot ential chronic effects afforded by the alternatives within the range were not well enough underst ood to use any such differences as a basis for choosing the most restrictive fo rms. On the other ha nd, the relatively large percentage of sites that would experience O 3 peaks well above 0.08 ppm and the number of days on which the level of the standard may be excee ded even when attaining a fifth-highest 0.08 ppm concentration-based standard, argu ed against choosing that form. In selecting alternative standards to include in our e xposure and risk analyses, we considered two concentration-based forms, the nth-highest maximum concentration and a percentile-based form. A percent ile-based statistic is useful fo r comparing datasets of varying length because it samples approximately the same place in the distribution of air quality values,
whether the dataset is se veral months or several years long. However, a percentile-based form would allow more days with higher air qua lity values in locations with longer O 3 seasons relative to places with shorter O 3 seasons. An nth-highest maximu m concentration form would more effectively ensure that people who liv e in areas with different length O 3 seasons receive the same degree of public health protecti on. For this reason, our exposure and risk analyses were based on a form specified in terms of an nth-highest concentration, with n ranging from 3 to 5. The results of some of these analyses ar e shown in Figures 6-1 through 6-4, discussed above in section 6.3.4.2. These figures illustrate th e estimated percent change in risk estimates for the incidence of moderate or gr eater decrements in lung function ( ≥ 15% FEV 1 ) in all school age children and moderate or gr eater lung function decrements ( ≥ 10% FEV 1 ) in asthmatic school age children, associated with going from meeting the current standard to meeting
alternative standards with alternative forms. Fi gures 6-5 and 6-6 illustrate the estimated percent change in the estimated incide nce of non-accidental mortality, associated with going from meeting the current standard to meeting altern ative standards. These results are generally representative of the patterns found in all of the analyses. The estimated reductions in risk
associated with different forms of the standar d, ranging from third- to fourth-highest daily maximum concentrations at 0.084 ppm, and from third- to fifth-highest daily maximum concentrations at 0.074 ppm, are generally less than the estimated reductions associated with the different levels that were analyzed. As seen in these figures, there is much city-to-city variability, particularly in the percent changes associated with going from a fourth-highest to6-84 third-highest form at the current level of 0.084 ppm, and with estimated reductions associated with the fifth-highest form at a 0.074 ppm level. In most cities, there ar e generally only small
differences in the estimated reductions in risks asso ciated with the third- to fifth-highest forms at a level of 0.074 ppm.
In their letter to the Administ rator, CASAC recommended that “ a range of concentration-based forms from the third- to the fifth-highest daily maximum 8-hr average

concentration” be considered (Henderson, 2006c, p. 5). Further, CASAC recommended that the Agency conduct a broader evaluation of alternat ive concentration-based forms to evaluate the implications of a broader range of alternative fo rms on public health protection and stability (i.e., with respect to yearly variability to ensu re a stable target for control programs). The same group of commenters that expre ssed the view that the current primary O 3 standard is not adequate also submitted comments that supported a more health-protective form of the standard than the current form (e.g., a seco nd- or third-highest dail y maximum form). The other group of commenters who expr essed the view that the current standard is adequate did not provide any provisional views on alternative forms that would be appropriate for consideration
should the Administrator consider revisions to the standard.
Staff notes that there is not a clear health-b ased threshold for sele cting a particular nthhighest daily maximum form of the st andard from among the ones analyzed. 32 We further note that the changes in the form considered in our analyses result in only small differences in the estimated reductions in risks in most cities, a lthough in some cities larger differences are
estimated. Staff concludes that a range of concentrati on-based forms from the third- to the fifthhighest daily maximum 8-hr averag e concentration is appropriate fo r consideration in setting the
standard. Given that there is a continuum of eff ects associated with exposures to varying levels
of O 3 , the extent to which public health is affected by exposure to ambient O 3 is related to the actual magnitude of the O 3 concentration, not just whether the concentration is above a specified level. The principal advantage of a concentration-ba sed form is that it is more directly related to
the ambient O 3 concentrations that are a ssociated with health effects. Robust, concentrationbased forms, in the range of the third- to fifth-highest daily maximum 8-hr average concentration, including the current 4 th -highest daily maximum form, minimize the inherent lack of year-to-year stability of ex ceedance-based forms and provide insulation from the impacts of

32 Staff consideration of an alternative form based on looking at the nth-highest daily maximum 8-hr average concentration over thre e years (specifically the 12 th -highest value in three year s), rather than the current form that is based on the 3-year average of annual nth- highest concentrations, did not identify a specific alternative form that was appreciably more consistent across ar eas than the range of forms previously considered.6-85 extreme meteorological events. Such instability can have the effect of reducing public health protection by disrupting ongoing implementation plans and associated control programs.

6.3.6 Summary of Staff Conclusions and Recommendations on the Primary O 3 NAAQS

Staff conclusions and recommendations on the elements of the primary O 3 standard for
the Administrator’s consideration in making decisions on the primary O 3 standard are summarized below, together wi th supporting conclusions from sections 6.3.1 to 6.3.5 above. These standard elements, including indicator, averaging time, level, and form, collectively determine the public health prot ection afforded by the standard. We recognize that selecting from among alte rnative standards will necessarily reflect consideration of qualitative and quantitative uncertain ties inherent in the relevant evidence and in the assumptions of the quantitative exposure and risk assessments. Any such standard should protect public health against health ef fects associated with exposure to O 3 , alone or in combination with related photochemical oxidants, taking into account both evidence-based and exposure- and risk-based considerations, and th e nature and degree of uncertainties in such information. In recommending these ranges of alte rnative standards for c onsideration, we are mindful that the Act requires standards that, in th e judgment of the Administrator, are requisite to protect public health with an adequate margin of safety. The standards are to be neither more nor less stringent than necessary. Thus, the Act doe s not require that NAAQS be set at zero-risk levels, but rather at levels that reduce risk sufficiently to protect public health with an adequate margin of safety.

(1) It is appropriate to continue to use O 3 as the indicator for a sta ndard that is intended to address effects associated with exposure to O 3 , alone or in combination with related photochemical oxidants. Based on the availa ble information, and consistent with the views of CASAC and public commenters, we concluded that th ere is no basis for considering any alternative indi cator at this time. Staff not es that while the new body of time-series epidemiological evidence cannot resolve questions about the relative contribution of other photochemical oxidant species to the range of morbidity and mortality effects associated with O 3 in these types of studi es, control of ambient O 3 levels is generally understood to provi de the best means of cont rolling photochemical oxidants in general, and thus of protecting against e ffects that may be asso ciated with individual species and/or the broader mix of photoc hemical oxidants, independent of effects specifically related to O 3
.6-86 (2) It is appropriate to continue to us e an 8-hr averaging time for the primary O 3 standard.
We conclude that a standard with an 8-hr averaging time can effectively limit both 1- and 8-hr exposures of concern and that an 8-hr averaging time is a ppropriate to provide adequate and more uniform protection of public health from both short-term (1- to 3-hr) and prolonged (6- to 8-hr) exposures to O 3 in the ambient air. Therefore, we recommend retaining the 8-hr averaging time and do not recommend consideration of a separate 1-hr
standard at this time. We also conclude th at consideration of a standard with a longerterm averaging time (e.g., annual) is not warranted at this time.

(3) We conclude that the overall body of eviden ce clearly calls into que stion the adequacy of the current standard and provides str ong support for consideration of an O 3 standard that would provide increased health protection for sensitive groups, including asthmatic children and other people with lung disease, as well as all children and older adults, especially those active outdoors, and outdoor wo rkers, against an arra y of adverse health effects that range from decreased lung f unction and respiratory symptoms to serious indicators of respiratory morbidity incl uding ED visits and hospital admissions for respiratory causes, and possibl y cardiovascular-rel ated effects and mortality. We also conclude that risks projecte d to remain upon meeting the current standard, based on the exposure and risk assessment, are indicativ e of risks to sensitive groups that can reasonably be judged to be important from a public health perspective, which reinforces our conclusion that consideration should be gi ven to revising the level of the standard so as to provide increased public health protection. (a) We recommend that consider ation be given to a standard level within the range of somewhat below 0.080 ppm to 0.060 ppm, refl ecting our judgment that a standard set within this range coul d provide an appropriate degree of public health protection and would result in important improvements in protecting the health of sensitive groups. Standard levels within this range that were considered in staff analyses of air quality, exposure, and risk include 0.074, 0.070, and 0.064 ppm, representative of levels within the uppe r, middle, and lower parts of this range, respectively. (b) We further recommend that considerati on be given to specifying the level of the primary standard to the n earest thousandth ppm, reflecti ng the degree of precision
with which ambient O 3 concentrations can be measur ed and design values can be
calculated.6-87 (4) We conclude that it is appropr iate to consider a form in th e range of the annual third- to fifth-highest daily maximum 8-hr average co ncentration, which includes the current form of the annual fourth-highest daily maximum 8-hr average concentr ation, averaged over three years. It is appropriate to consider a form within th is range in conjunction with a standard level within the recommended range, so as to provide an a ppropriate degree of increased public health protection.

6.4 SUMMARY OF KEY UNCERTA INTIES AND RESEARCH RECOMMENDATIONS RELATED TO SETTING A PRIMARY O 3 STANDARD We believe it is important to continue to highlight the uncertainties associated with establishing standards for O 3 during and after completion of the NAAQS review process. Research needs go beyond what is necessary to understand health and welf are effects, population exposures, and the risks of exposure for purposes of setting standards. Research can also support the development of more efficien t and effective control strategies. It should be noted, however, that a thorough discussion of research needs related to control strategy development is beyond the scope of this document. Following completion of the 1996 Ozone Staff Paper (U.S. EPA, 1996), the EPA held a research needs workshop and produced a draft document 33 for review by the CASAC at a public meeting held November 16, 1998. Based on our revi ew of scientific information contained in the 2006 CD, we have concluded that O 3 health research needs and priorities have not changed substantially since the above document was written. Key uncer tainties and research needs that continue to be high priority for future revi ews of the health-based primary standards are
identified below:

(1) An important aspect of risk characteriza tion and decision making fo r air quality standard
levels for the O 3 NAAQS is the charact erization of the shap e of exposure-response
functions for O 3 , including the identification of pote ntial population threshold levels. Recent controlled human exposure studies conducted at levels below 0.08 ppm O 3 provide evidence that measurable lung functi on effects occur in some individuals for 6-8 hr exposures in the range of 0.08 to as low as 0.04 ppm. A major limitation of these data is that they were collected in one laboratory located in an area of the U.S. that typically experiences higher ambient air levels of O 3 ; therefore, prior attenuation of subject response may have been a factor in the re sponses observed. Considering the importance of estimating health risks in the range of 0.04 to 0.08 ppm O 3 , additional research is

33 “Ozone Research Needs to Improve Health and Ecological Risk Assessment” (U.S. EPA, 1998).6-88 needed to evaluate responses in healthy and asthmatic individuals in the range of 0.04 to 0.08 ppm for 6-8 hr exposures whil e engaged in moderate exertion.

(2) Similarly, for health endpoints reported in epidemiological studies such as hospital admissions, ED visits, and premature mortality, an important aspect of characterizing risk is the shape of concentra tion-response functions for O 3 , including identification of potential population threshold levels. Most of the recent studies and analyses continue to
show no evidence for a clear threshol d in the relationships between O 3 levels and these health endpoints or have suggest ed that any such thresholds must be at very low levels approaching policy relevant background leve ls. Whether or not exposure errors, misclassification of exposure, or potential im pacts of other copollutants may be obscuring potential population thre sholds is still unknown.

(3) The extent to which the broad mix of phot ochemical oxidants and more generally other copollutants in the ambient air (e.g., PM, NO 2 , SO 2 , etc.) may play a role in modifying or contributing to the observed a ssociations between ambient O 3 and various morbidity effects and mortality continues to be an important research question. Ozone has long
been known as an indicator of health effect s of the entire photochemical oxidant mix in
the ambient air and has served as a surr ogate for control purposes. A better understanding of sources of th e broader pollutant mix, of human exposures, and of how other pollutants may modify or cont ribute to the health effects of O 3 in the ambient air, and vice versa, is needed to bett er inform future NAAQS reviews.

(4) As epidemiological research has become a more important factor in assessing the public health impacts of O 3 , methodological issues in epidem iological studies have received greater visibility and scrutiny. Investigations of questions on the use of generalized additive models in time-series epidemiologi cal studies have raised model specification
issues. There remains a need for further st udy on the selection of appropriate modeling strategies and appropriate methods to cont rol for time-varying factors, such as temperature, and to better understand the role of copollutants in the ambient air.

(5) Limited controlled human exposure and ep idemiology research has provided suggestive
evidence of both direct a nd indirect effects of O 3 on the cardiovascular system, cardiovascular hospital admissions, and cardiov ascular mortality. However, additional work will be needed to examine biologically plausible mechanisms of cardiovascular
effects and to determine the extent to which O 3 is directly implicated or works together6-89 with other pollutants in causing adverse cardio vascular effects in sensitive individuals and in the general population.

(6) Most epidemiological studies of short-term exposure effects have been time-series studies in large populations. Time-series studies re main subject to uncertainty due to use of
ambient fixed-site data servi ng as a surrogate for ambient e xposures, to the difficulty of determining the impact of any single pollutant among the mix of pollutants in the ambient air, to limitations in existing statistical models, or to a combination of all of these factors. Independent variables for ai r pollution have generally be en measurements made at stationary outdoor monitors, but the accuracy with which these measurements actually reflect subjects’ exposure is not yet fully unde rstood. Also, additional research is needed to improve the characterization of the degr ee to which discrepanc y between stationary monitor measurements and actual pollutant exposures introduces error into statistical estimates of pollutant effect s in time-series studies.

(7) Improved understanding of human exposures to ambient O 3 and to related copollutants is an important research need. Populati on-based information on human exposure for healthy adults and children and susceptible or at-risk populations including asthmatics to
ambient O 3 concentrations, including exposure information in various microenvironments, is needed to bett er evaluate current and future O 3 exposure models. Such information is needed for sufficient pe riods to facilitate evaluation of exposure models throughout the O 3 season.

(8) Information is needed to improve input s to current and future population-based O 3 exposure and health risk assessment models. Collection of time-ac tivity data over longer time periods is needed to re duce uncertainty in the modele d exposure distributions that form an important part of the basis for d ecisions regarding air quality standard for O 3 and other air pollutants. Research addressing energy expenditure and associated breathing rates in various population groups, particularly healthy and asthmatic children, in various locations, across the spectrum of physical activity, includi ng sleep to vigorous physical
exertion is needed.

(9) An important consideration in the O 3 NAAQS review is the ch aracterization of policy relevant background levels. There still re main significant uncertainties in the characterization of 8-hr daily maximum O3 background concentrations. Further research to improve the evaluation of the GEOS -CHEM model which has been used to characterize estimates of policy relevant background levels would help reduce6-90 uncertainties in estimating health risks rele vant for standard se tting (i.e., those risks associated with exposure to O 3 in excess of policy relevant background levels) and would aid in the development of a ssociated control programs.6-91 REFERENCES

Abt Associates Inc. (2006). Ozone Health Risk Assessment for Selected Urban Areas: Draft Report. Prepared for Office of Air Quality Planning and Standards, U.S. Environmental Pr otection Agency, Research Triangle Park, NC. June 2006. Available electronically on the internet at: http://www.epa.gov/ttn/naaqs/standards/ozone/s_o3_cr_td.html

. Adams, W.C. (2002). “Comparison of Chamber and Face-Mask 6.6-Hour Exposures to Ozone on Pulmonary Function and Symptoms Responses.” Inhalation Toxicology 14:745-764.

Adams, W.C. (2003). “Comparison of Chamber and Face Mask 6.6-Hour Expo sure to 0.08 ppm Ozone via SquareWave and Triangular Profiles on Pulmonary Responses.” Inhalation Toxicology 15: 265-281.

Adams, W.C. (2006). “Comparison of Chamber 6.6-h Exposures to 0.04-0.08 ppm Ozone via Square-Wave and Triangular Profiles on Pulmonary Responses.” Inhalation Toxicology 18: 127-136.

Bell, M. L.; McDermott, A.; Zeger, S. L.; Samet, J. M.; Dominici, F. (2004) Ozone and short-ter5m mortality in 95 US urban communities, 1987-2000. JAMA J. Am. Med. Assoc. 292: 2372-2378.

Bell, M,A. R.D. Peng, and F. Dominici (2006). “The Exposure-Response Curve for Ozone and Risk of Mortality and the Adequacy of Current Ozone Regulations.” Envi ronmental Health Perspectives. Available online at: http://dx.doi.org/

Blank, H. and Mitchell, A. (2001). The Status of Preschool Policy in the States. Children’s Defense Fund and Early Childhood Policy Research. Available at: www.earlychildhoodfinance.org/handouts/S tatusOfPreschoolPolicyInTheStates.doc

Brauer, M.; Blair, J.; Vedal, S. (1996) Effect of ambient ozone exposure on lung function in farm workers. Am. J. Respir. Crit. Care Med. 154: 981-987.

Burnett, R. T.; Brook, J. R.; Yung, W. T.; Dales, R. E.; Krewski, D. (1997a) Association between ozone and hospitalization for respiratory diseases in 16 Canadian cities. Environ. Res. 72: 24-31.

Burnett, R. T.; Brook, J. R.; Yung, W. T.; Dales, R. E.; Krewski, D. (1997b) Association between ozone and hospitalization for respiratory diseases in 16 Canadian cities. Environ. Res. 72: 24-31.

Burnett, R. T.; Smith-Doiron, M.; Stieb, D.; Raizenne, M. E.; Brook, J. R.; Da les, R. E.; Leech, J. A.; Cakmak, S.; Krewski, D. (2001) Association between ozone and hosp italization for acute respiratory diseases in children less than 2 years of age. Am. J. Epidemiol. 153: 444-452.

Chock, D. P.; Winkler, S. L.; Chen, C. (2000) A study of the association between daily mortality and ambient air pollutant concentrations in Pittsburgh, Pennsylvania. J. Air Waste Manage. Assoc. 50: 1481-1500

. Delfino, R. J.; Murphy-Moulton, A. M.; Burnett, R. T.; Brook, J. R.; Becklake , M. R. (1997) Effects of air pollution on emergency room visits for respiratory illnesses in Mo ntreal, Quebec. Am. J. Respir. Crit. Care Med. 155: 568-576.

Delfino, R.J.; Zeiger, R.S.; Seltzer, J.M.; Street, D.H. ( 1998) Symptoms in pediatric asthmatics and air pollution: differences in effects by symptom se verity, anti-inflammatory medication us e and particulate averaging time. Environ. Health Perspect. 106: 751-761.

Dockery, D. W.; Schwartz, J.; Spengler, J. D. (1992) Air pollution and daily mortality: associations with particulates and acid aerosols. Environ. Res. 59: 362-373.6-92 Fairley, D. (1999) Daily mortality and air pollution in Sa nta Clara County, California: 1989-1996. Environ. Health Perspect. 107: 637-641.

Fairley, D. (2003) Mortality and air pollution for Santa Cl ara County, California, 1989-19 96. In: Revised analyses of time-series studies of air pollution and health. Sp ecial report. Boston, MA: Health Effects Institute; pp. 97-106. Available: http://www.healtheffects. org/Pubs/TimeSeries.pdf [18 October, 2004].

Federal Register (1997) National Ambient Air Quality Standards for Ozone; Final Rule. 40 CFR 50; Federal Register 62: 38856.

Gamble, J. L. (1998) Effects of ambient air pollution on daily mortality: a time series analysis of Dallas, Texas, 1990-1994. Presented at: 91st annual meeting and exhibition of the Air & Waste Management Association; June; San Diego, CA. Pittsburgh, PA: Air & Waste Management Association; paper no. 98-MP26.03.

Gent, J. F.; Triche, E. W.; Holford, T. R.; Belanger, K.; Bracken, M. B.; B eckett, W. S.; Lead erer, B. P. (2003) Association of low-level ozone and fine particles with respiratory symptoms in children with asthma. JAMA

Gryparis, A.; Forsberg, B.; Katsouya nni, K.; Analitis, A.; Touloumi, G.; Sc hwartz, J.; Samoli, E.; Medina, S.; Anderson, H. R.; Niciu, E. M.; Wichmann, H.-E.; Kriz, B.; Kosnik, M.; Skorkovsky, J.; Vonk, J. M.; Dörtbudak, Z. (2004) Acute effects of ozone on mort ality from the "air pollution and health: a European approach" project. Am. J. Respir. Crit. Care Med. 170: 1080-1087.

Henderson, R. (2006a) Letter from CASAC Chairman Rogene Henderson to EPA Administrator Stephen Johnson, February 16, 2006, EPA-CASAC-06-003.

Henderson, R. (2006b) Letter from CASAC Chairman Rogene Henderson to EPA Administrator Stephen Johnson, June 5, 2006, EPA-CASAC-06-007.

Henderson, R. (2006c) Letter from CASAC Chairman Rogene Henderson to EPA Administrator Stephen Johnson, October 24, 2006, EPA-CASAC-07-001.

Huang, Y.; Dominici, F.; Bell, M. L. (2005) Bayesian hierarchical distributed lag models for summer ozone exposure and cardio-respiratory mortality. Environmetrics 16: 547-562.

Ito, K. (2003) Associations of particulate matter components with daily mortality and morbidity in Detroit, Michigan. In: Revised analyses of tim e-series studies of air pollution and health. Special repo rt. Boston, MA: Health Effects Institute; pp. 143-156. Available: http://www.healtheffects. org/Pubs/TimeSeries.pdf [12 May, 2004],

Ito, K.; De Leon, S. F.; Lippmann, M. (2005) Associatio ns between ozone and daily mortality, analysis and metaanalysis. Epidemiology 16: 446-457.

Kinney, P. L.; Ito, K.; Thurston, G. D. (1995) A sensitivity analysis of mortality/PM10 associations in Los Angeles. In: Phalen, R. F.; Bates, D. V., eds. Proceedings of the colloquium on particulate air pollution and human mortality and morbidity; January 1994; Irvine, CA. Inhalation Toxicol. 7: 59-69.

Klemm, R. J.; Lipfert, F. W. ; Wyzga, R. E.; Gust, C. (2004) Daily morta lity and air pollution in Atlanta: two years of data from ARIES. Inhalation Toxicol. 16(suppl. 1): 131-141.

Korrick, S. A.; Neas, L. M.; Dockery, D. W.; Gold, D. R.; Allen, G. A.; Hill, L. B.; Kimbal l, K. D.; Rosner, B. A.; Speizer, F. E. (1998) Effects of ozone and other pollutants on the pulmonary function of adult hikers. Environ. Health Perspect. 106: 93-99.

Langstaff, J. (2007) Analysis of Uncertainty in Ozon e Population Exposure Modeling, Draft Memorandum to the Ozone NAAQS Review Docket (OAR-2005-0172), July 24, 2006.6-93 Levy, J. I.; Chemerynski, S. M.; Sarnat, J. A. (2005) Ozone exposure and mortality, an empiric Bayes metaregression analysis. Epidemiology 16: 458-468.

Linn, W. S.; Shamoo, D. A.; Anderson, K. R.; Peng, R.-C.; Avol, E. L.; Hackney, J. D.; Gong, H., Jr. (1996) Shortterm air pollution exposures and responses in Los Angeles area schoolchildren. J. Exposure Anal. Environ. Epidemiol. 6: 449-472.

Lippmann, M.; Ito, K.; Nádas, A.; Burnett, R. T. (2000) Association of particulate matter components with daily mortality and morbidity in urban populations. Cambridge , MA: Health Effects In stitute; research report no. 95.

Moolgavkar, S. H.; Luebeck, E. G.; Hall, T. A.; Anders on, E. L. (1995) Air pollution and daily mortality in Philadelphia. Epidemiology 6: 476-484.

Mortimer, K. M.; Neas, L. M.; Dockery, D. W.; Redline, S.; Tager, I. B. (2002) The effect of air pollution on innercity children with asthma. Eur. Respir. J. 19: 699-705.

Naeher, L. P.; Holford, T. R. ; Beckett, W. S.; Belanger, K.; Triche, E. W.; Bracken, M. B.; Lead erer, B. P. (1999) Healthy women's PEF variations with ambient summer concentrations of PM 10 , PM 2.5 , SO 4 2- , H + , and O 3 . Am. J. Respir. Crit. Care Med. 160: 117-125.

Neas, L. M.; Dockery, D. W.; Koutrakis, P.; Tollerud, D. J.; Speizer, F. E. (1995) The association of ambient air pollution with twice daily peak expiratory flow rate measurements in children. Am. J. Epidemiol. 141: 111- 122.

Ostro, B. (1995) Fine particulate air pollution and morta lity in two Southern California counties. Environ. Res. 70: 98-104.

Ostro, B.; Lipsett, M.; Mann, J.; Brax ton-Owens, H.; White, M. (2001) Air pollution and exacerbation of asthma in African-American children in Los Angeles. Epidemiology 12: 200-208.

Ostro, B. D.; Broadwin, R.; Lipsett, M. J. (2003) Coarse particles and daily mortality in Coachella Valley, California. In: Revised analyses of time-series studies of air pollution and health. Special report. Boston, MA: Health Effects Institute; pp. 199-204. Available: http://www.healtheffects.org/ Pubs/TimeSeries.pdf [18 October, 2004].

Peters, A.; Dockery, D. W.; Muller, J. E.; Mittleman, M. A. (2001) Increased particulate air pollution and the triggering of myocardial infarction. Circulation 103: 2810-2815.

Post, E. (2007). Memorandum – Subject: Additional Tabl es of Lung Function Risk Estimates Associated with Ozone Exposures Based on 2003 Air Quality Data. January 30. Available at: http://www.epa.gov/ttn/naaqs/standards/ozone/s_o3_cr_td.html

. Ross, M. A.; Persky, V. W.; Scheff, P. A.; Chung, J.; Cu rtis, L.; Ramakrishnan, V.; Wadden, R. A.; Hryhorczuk, D. O. (2002) Effect of ozone and aeroa llergens on the respiratory health of asthmatics. Arch. Environ. Health 57: 568-578.

Schwartz, J. (1996) Air pollution and hospital admissions for respiratory disease. Epidemiology 7: 20-28.

Schwartz, J. (2005) How sensitive is th e association between ozone and daily deaths to control for temperature? Am. J. Respir. Crit. Care Med. 171: 627-631.

Sheppard, L. (2003) Ambient air pollution and nonelderly asthma hospital admissions in Seattle, Washington, 1987- 1994. In: Revised analyses of time-series studies of air pollution and health. Special report. Boston, MA:6-94 Health Effects Institute; pp. 227-230. Available: http://www.healtheffects. org/Pubs/TimeSeries.pdf [18 October, 2004].

U.S. Environmental Protection Agency (1996) Review of the national ambient air quality standards for ozone: assessment of scientific and technical information. OAQ PS staff paper. Research Triangle Park, NC: Office of Air Quality Planning and Standards; EPA report no. EPA–452/R–96–007. Available from: NTIS, Springfield, VA; PB96–203435. http://www.epa.gov/ttn/naaqs/standards/ozone/s_o3_pr_sp.html

U.S. Environmental Protection Agency (1998) Ozone Research Needs to Improve Health and Ecological Risk Assessments (External Review Draft). Research Tria ngle Park, NC: Office of Research and Development; report no. EPA/600/R-98/031. March 31, 1998.

U.S. Environmental Protection Agency (2006a) Air quality criteria for ozone and related photochemical oxidants(Final). Research Triangle Park, NC: National Center for Environmental Assessment; report no. EPA/600R05/004aB-cB, 3v. Available: http://cfpub.epa.gov/ncea/cfm/r ecordisplay.cfm?deid=137307 [March 2006]

U.S. Environmental Protection Agency (2006b) Ozone Population Exposure Analysis for Selected Urban Areas (draft). Office of Air Quality Planning and Standa rds, Research Triangle Park, NC. June. Available electronically on the internet at: http://www.epa.gov/ttn/naaqs/standards/ozone/s_o3_cr_td.html

. U.S. Environmental Protection Agency (2006c) Review of the national ambient air quality standards for ozone: policy assessment of scientific and technical informa tion. OAQPS staff paper – Second draft. Research Triangle Park, NC: Office of Air Qu ality Planning and Standards; EPA report no. EPA–452/D–05–002, July 2006. Available electronically at: http://www.epa.gov/ttn/naaqs/standards/ozone/s_o3_cr_sp.html

. U.S. Environmental Protection Agency (2006d) Transcript of the August 24, 2006 Public Advisory Meeting to Conduct a Peer Review of EPA's 2nd Draft Ozone Staff Paper and Related Draft Technical Support Documents, Science Advisory Board, August. Docket number EPA-HQ-OAR-2005-0172-0044.

U.S. Environmental Protection Agency (2006e) Transcript of the August 25, 2006 Public Advisory Meeting to Conduct a Peer Review of EPA's 2nd Draft Ozone Staff Paper and Related Draft Technical Support Documents, Science Advisory Board, August. Docket number EPA-HQ-OAR-2005-0172-0045.

Vedal, S.; Brauer, M.; White, R.; Petkau, J. (2003) Air pollu tion and daily mortality in a city with low levels of pollution. Environ. Health Perspect. 111: 45-51.

Villeneuve, P.J.; Burnett, R. T.; Shi, Y.; Krewski, D.; Goldberg, M.S.; Hertzman, C.; Chen, Y.; Brook, J. (2003) A time-series study of air pollution, socioeconomic status, and mortality in Vancouver, Canada. J. Exposure Anal. Environ. Epidemiol. 13: 427-435.

Wolff, G.T. (1995) Letter to EPA Administrator Caro l Browner: “CASAC Closure on the Primary Standard Portion of the Staff Paper for Ozone” EPA-SAB-CASAC-LTR-96-002, November 30, 1995.

Yang, Q.; Chen, Y.; Shi, Y.; Burnett, R. T.; McGrail, K. M.; Krewski, D. (2003) Association between ozone and respiratory admissions among children and the elderly in Vancouver, Canada. Inhalation Toxicol. 15: 1297- 1308.

### 7. POLICY-RELEVANT ASSESSMENT OF WELFARE EFFECTS EVIDENCE

7.1 INTRODUCTION This chapter presents information critical to the review of the secondary NAAQS for O 3
. Welfare effects addressed by a secondary NAAQ S 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. Of these welfar e effects categories,
the effects of O 3 on vegetation, including agricultural crops, trees in managed and unmanaged forests, and herbaceous and woody species growing in natural settings are of most concern at concentrations typically occurring in the U.S. As stated in earlier reviews, "of the phytotoxic compounds commonly found in the ambient air, O 3 is the most prevalent, impairing crop production and injuring native vege tation and ecosystems more th an any other air pollutant" (U.S. EPA, 1989, 1996b). Ozone can also affect other ecosystem com ponents such as soils, water, wildlife, and habitat, either directly, or indirectly, through its effects on vegetation. These individual ecosystem components are associated with one or more of six essential ecological attributes (EEAs) recently described in A Framework for Assessing and Reporting on Ecological Condition: an SAB report (Young and Sanzone, 2002) as part of a conceptual framework useful for assessing and reporting on ecological conditi on (see Figure 7-21 and discussion in section 7.7). This framework can be used to link O 3 effects at the species level to potential impacts at higher levels in the hierarchy (e.g., EEAs). Some of these species level impacts have direct, quantifiable economic value, while others are curre ntly not quantifiable, bu t still have societal
value. In the absence of sufficient research to allow quantification of O 3 impacts at the ecosystem level, including impacts on ecosystem goods and services, only a qualitative discussion is included. However, the staff infe rs, based on the linkages described in the SAB framework, that increasing prot ection for vegetation from O 3 related effects would also improve the protection afforded to ecosystems and th eir related public welfare categories.
Other O 3 related welfare effects categories includ e damage to certain manmade materials (e.g., elastomers, textile fibers, dyes, paints, and pigments) and climate interactions. The amount of damage to actual in-use mate rials and the economic consequen ces of that damage are poorly characterized, however, and the scie ntific literature contains ve ry little new information to adequately quantify estimates of materials da mage from photochemical oxidants (U.S. EPA,

7-11996a, b, 2006). Therefore, staff judges that ther e is insufficient information in the materials damage literature to inform secondary standard se tting and so it will not be discussed further. Interested readers are referred to Chapter 11 in the CD (U.S. EPA, 2006). In contrast, the welfare impact of O 3 on local, regional and global climates has received more attention in recent years. Ozone enhances the heat capacity of the atmosphere. The overall body of scientific evidence suggests that hi gh concentrations of O 3 on a regional scale c ould have a discernable influence on climate, leading to surface temper ature and hydrological cycle changes. However, the CD stated that confirming this effect wi ll require further advances in monitoring and improvement in chemical transport and regiona l-scale modeling. Thus, staff concludes that
insufficient information is available at this tim e to quantitatively inform the secondary NAAQS process with regard to this aspect of the O 3 -climate interaction and will not address it further. Another aspect, is the potential m odification of plant response to O 3 under conditions of changing climate, is included in the discussi on of factors that can modify the predicted vegetation responses (see section 7.4.2). To summarize, this chapter includes an inte grated discussion of the key policy relevant science regarding O 3 -related effects on vegetation (sections 7.2 through 7.4) and terrestrial ecosystems (section 7.7), as described in the previ ous CD (U.S. EPA, 1996a ) and reiterated in the current CD (U.S. EPA, 2006). The remaini ng sections (7.5 and 7.6) of this chapter are focused on a discussion of the analyses that ha ve been conducted in support of this current NAAQS review that update and expand upon the exposure, risk and benefits assessments conducted in the last review (U.S. EPA, 1996b). These updated assessments incorporate newer data, models, and approaches, and take into account alternative O 3 air quality scenarios under
consideration. The environmental as sessment technical support document, Technical Report on Ozone Exposure, Risk, and Impac ts Assessments for Vegetation (Abt, 2007) (hereafter cited as “Environmental Assessment TSD”), presents a deta iled description of the exposure, risk and impacts analysis methodology. Results from these assessments, along with key uncertainties and limitations, are also described in sections 7.5 a nd 7.6. This information forms the basis for a discussion in Chapter 8 of staff conclusions and recommendations with respect to the secondary

O 3 NAAQS.

7.2 MECHANISMS GOVERNING PLANT RESPONSE TO OZONE The interpretation of predictions of risk a ssociated with vegetation response at ambient

O 3 exposure levels can be informed by scientific understa nding regarding O 3 impacts at the genetic, physiological, a nd mechanistic levels. In most cases, the mechanisms of response are similar regardless of the degree of sensitivity of the species. The information assessed in the 1996 CD (U.S. EPA 1996a) regarding th e fundamental hypotheses concerning O 3 -induced

7-2changes in physiology continues to be valid. However, during the last decade, understanding of the cellular processes within plants has been fu rther clarified and enhanc ed. Therefore, this section reviews the key scientific conclusions identified in 1996 O 3 CD (U.S. EPA, 1996a), and incorporates new information from the current CD (U.S. EPA, 2006). This section describes: (1) O 3 uptake, (2) cellular to systemic O 3 response, (3) plant compensation and defense mechanisms, (4) O 3 –induced changes to plant metabolism, and (5) plant response to chronic O 3
exposures.

7.2.1 Ozone Uptake: Canopy, Plant and Leaf To cause injury, O 3 must first enter the pl ant through the stomata of the leaves. Leaves
exist in a three dimensional environment calle d the plant canopy, where each leaf has a unique
orientation and receives a diffe rent exposure to ambient air, microclimatological conditions, and sunlight. In addition, a plant may be located within a stand of other plants which further modifies ambient air exchange w ith individual leaves. Not all O 3 entering a plant canopy is absorbed into the leaves, but may be adsorbed to other surfaces e.g., leaf cuticles, stems, and soil (termed non-stomatal deposition) or scavenged by reactions with intra-canopy biogenic VOCs and naturally occurring NOx emi ssions from soils. Because O 3 does not penetrate the leaf’s cuticle, it must reach the stomatal openings in the leaf for absorption to occur. The movement of

O 3 and other gases such as CO 2 into and out of leaves is controlled primarily through the stomata. The aperture of the stomata are contro lled by guard cells, which respond to a variety of internal species-specific factors as well as external site specific environmental factors such as light, humidity, CO 2 concentration, soil fertility and water st atus, and in some cases the presence of other air pollutants, including O 3 (see section 7.4.2). These modifying factors produce stomatal conductances that vary across the diurnal cycle, days and seasons. Once O 3 is inside the leaf, a phytotoxic effect will only occur if sufficient amounts of O 3 reach sensitive cellular sites that are subject to the various physiological and biochemi cal controls within the leaf cells (see
the discussion in section 7.2.3 below – Compensation and Detoxification).
A measure of O 3 flux is attractive because it incor porates both relevant environmental factors and physiological processes, and is cons idered the measure that most closely links exposure to plant response. Unfortunately, m easurement of flux is very complex, making it difficult to extrapolate uptake from an individual leaf to that of a whole plant or canopy. Since the last review, interest has been increasing, pa rticularly in Europe, in using mathematically
tractable flux models for O 3 assessments at the regional and national scale (Emberson et al., 2000a, b). Though significant new research ha s been done with respect to flux model development, it has still not advanced to a point of being generally applicable across a range of

7-3species and environments at a national scale. These topics are discussed in more detail in Appendix 7A of this document and in the current CD (U.S. EPA, 2006).

7.2.2 Cellular to Systemic Response

Once O 3 diffuses into the leaf air spaces it can react with a variety of biochemical compounds that are exposed to the air (path 1) or it can be solubilized in to the water lining the cell wall of the air spaces (path 2). Having entered the aqueous phase, O 3 can be rapidly altered to form oxidative products that can diffuse more readily into and through the cell and react with many biochemical compounds. The initial sites of membrane reactions seem to involve transport properties and, possibly, the ex ternal signal transducer mol ecules (U.S. EPA, 2006). This alteration in plasma membrane function is clearly an early step in a series of O 3 -induced events that leads to leaf injury. Under certain circumstances, O 3 reacts with organic molecules to generate peroxides, including hydrogen peroxide (H 2 O 2 ). The role of hydrogen peroxi de as a signaling molecule in plants is now better underst ood. The primary set of me tabolic reactions that O 3 triggers clearly includes those typical of “wounding” responses generated by cutting of the leaf or by pathogen/insect attack. One aspect of this total res ponse is the production of O 2

 and H 2 O 2 by the cell (Lamb and Dixon, 1997). The presence of higher-than-normal levels of H 2 O 2 within the apoplastic space is a potential tri gger for the normal, well-studied pathogen defense pathway. Ethylene is another compound produced when pl ants are subjected to biotic or abiotic stressors. Increased ethylene production by plants exposed to O 3 stress was identified as a
consistent marker for O 3 exposure decades ago (Tingey et al., 1976). These studies suggested that increased production of stress- ethylene correlated well with th e degree of foliar injury that developed within hours or days after O 3 exposure. Thus, one could postulate that O 3 generates a wounding response with the production of ethylene, which would, in turn, generate a change in stomatal conductance and photosynthesis.

7.2.3 Compensation and Detoxification Ozone injury will not occur if (1) the rate and amount of O 3 uptake is small enough for the plant to detoxify or metabolize O 3 or its metabolites or (2) the plant is able to repair or compensate for the O 3 impacts (Tingey and Taylor, 1982; U. S. EPA, 1996a). Leaves may physically exclude O 3 from sensitive tissues. A few studies have documented a direct stomatal
closure or restriction in re sponse to the presence of O 3 ranging from within minutes to hours or days of exposure (Moldau et al., 1990; Dann a nd Pell, 1989; Weber et al., 1993). However,
exclusion of O 3 also restricts the uptake of CO 2 , thus limiting photosynthesis and growth. In addition, plants can also effectively prot ect tissue against damage by dissipating excess oxidizing power using antioxidants. Since 1996, the role of detoxifi cation in providing a level of

7-4resistance to O 3 has been further investigated. A number of antioxidants, including ascorbate, glutathione peroxidase, and sulf uroxide dimutase, which are highl y reactive, can detoxify the chemicals generated by O 3 . The pattern of changes in these antioxidant proteins varies greatly among different species and conditions. Most recen t reports indicate that ascorbate within the cell wall provides the first significant opportunity for detoxification to occur. The balance
between the total O 3 flux and the detoxification process has been defined as the “effective flux” (Dämmgen et al., 1993; Grünhage and Haenel, 1997; Musselman and Massman, 1999). In spite of the new research, however, it is st ill not clear as to what extent detoxification protects against O 3 injury. Specifically, data are needed on the potential rates of antioxidant production and on the subcellular lo cation of the antioxidants. Potential rates of antioxidant production are needed to assess whether th ey are sufficient to detoxify the O 3 as it enters the cell. Data on the subcellular location(s) are needed to assess whether the antioxidants are in the cell wall or plasmalemma locations that permit contact with the O 3 before it has a chance to damage subcellular systems. In addition, generation of these antioxidants in response to O 3 -induced stress potentially diverts resour ces away from other sinks and e xpends energy. Thus, scientific understanding of the detoxificat ion mechanisms is not yet complete and requires further investigation (U.S. EPA, 2006).

Once O 3 injury has occurred in leaf tissue, some plants are able to repair or compensate for the impacts (Tingey and Taylor, 1982). In ge neral, plants have a va riety of compensatory mechanisms for low levels of stress including re allocation of resources, changes in root/shoot ratio, production of new tissue, and/or biochemi cal shifts, such as increased photosynthetic capacity in new foliage and changes in respiratio n rates, indicating possible repair or replacement of damaged membranes or enzymes. Since these mechanisms are genetically determined, not all plants have the same complement or degree of tolerance, nor are all stages of a plant’s development equally sensitive to O 3 . It is not yet known to what degree or how the use of plant resources for repair processes affects th e overall carbohydrate budget or subsequent plant response to O 3 or other stresses (U.S. EPA, 1996a, U.S. EPA, 2006).

7.2.4 Changes to Plant Metabolism Ozone inhibits photosynthesis, the pro cess by which plants produce energy rich compounds (e.g., carbohydrates) in the leaves. This impairment can result from direct impact to chloroplast function and/or O 3 -induced stomatal closure resu lting in reduced uptake of CO 2 . A large body of literature published since 1996 has further elucidated the mechanism of effect of

O 3 within the chloroplast. Pe ll et al. (1997) showed that O 3 exposure results in a loss of Ribulose-1, 5-bisphosphate car boxylase/oxygenase (RuBisCo), the central carboxylating enzyme that plays an important role in the production of carbohydrates. Due to its central importance,

7-5any decrease in RuBisCo may have severe cons equences for the plant’s productivity. Several
recent studies have found that O 3 has a greater effect as leaves ag e, with the greatest impact of

O 3 occurring on the oldest leaves (Fiscus et al ., 1997; Reid and Fiscus, 1998; Noormets et al., 2001; Morgan et al., 2004). The loss of Ru BisCo and its messenger RNA as a function of increasing O 3 exposure is also linked to an early senescence or a speeding up of normal development leading to senescen ce. If total plant photosynthesis is sufficiently reduced, the plant will respond by reallocating the remaining carbohydrate at the level of the whole organism (see section 7.3 below) (U.S. EPA, 1996a, 2006).

7.2.5 Plant Response to Chronic/Long-term O 3 Exposures Many changes that occur with O 3 exposure can be observed within hours, or perhaps days, of the exposure, including those connected with wounding a nd elicitor-induced changes in gene expression. Other effects due to O 3 , however, take longer to occur and tend to become most obvious after long exposures to low-O 3 concentrations. These have been linked to senescence or some other physiological respons e very closely linked to senescence. The understanding of how O 3 affects long-term growth and resi stance to other biotic and abiotic insults in long-lived trees is unclear. Often, the c onditions to which a tree is subjected to in one year will affect, or “carry-over”, the response of that tree into the next year (U.S. EPA, 2006). In other words, a condition in an earlier year sets the stage for a reaction in the next year; thereby giving a “cause-effect” scenario (U.S. EPA, 2006). In perennial plant spec ies, growth affected by a reduction in carbohydrate storage may result in the limitation of growth the following year (Andersen et al., 1997). Carry- over effects have been documen ted in the growth of tree seedlings (Hogsett et al., 1989; Sa sek et al., 1991; Temple et al., 1993; U.S. EPA, 1996a) and in roots (Andersen et al., 1991; U.S. EPA, 1996a). Accumulation of carry- over effects over time will affect survival and reproduction. Understanding of how O 3 interacts with the plant at a cellular level has dramatically improved in recent years. However, additional work remains to more fully elucidate the translation of those cel lular mechanisms into altered cell metabolism, whole plant productivity, and ot her physiological effects.

7.3 NATURE OF EFFECTS ON VEGETATION Studies published since the conclusion of the 1996 review con tinues to support and strengthen key conclusions regarding O 3 effects on vegetation and ecosystems found in the previous CD (U.S. EPA, 1996a) and reiterated in the current CD (U.S. EPA, 2006). For additional detail the reader is referred to Chap ter 9 and Annex 9 in the current CD (U.S. EPA, 2006)

7-67.3.1 Ozone Sensitive Plants and Their Relationship to Public Welfare Of all the plant species growing within the U.S. ( over 43,000 species have been catalogued in the USDA PLANTS database, USDA, NRCS, 2006), only a small percentage have been studied with respect to O 3 sensitivity. Most of the studied species were selected because of their commercial importance or observed O 3 -induced visible foliar injury in the field. Given that

O 3 impacts to vegetation also include less obvious but often more significant impacts, such as reduced annual growth rates and below ground root loss (see following sections), the paucity of information on other species means the true range of both inter- and intra-species O 3 sensitivity that exists within U.S. vegetation is unknown. Even so, plant species /genotypes with known O 3 sensitivity span a broad range of vegetation types and public use categories. These use categories include food production for human an d domestic animal consumption, fiber and materials production, and urban/priv ate landscaping. In addition to these direct uses, a number
of O 3 sensitive species have specific relevance to public welfare based on their aesthetic, medicinal, or habitat value. Table 7J-1 in Appendix 7J presents a list of O 3 sensitive species that occur in Federal Class I areas and Table 7J-2 presents O 3 sensitive species in each state.

7.3.2 Vegetation Effects Endpoints Ozone injury at the cellular level, wh en it has accumulated sufficiently, will be propagated to the level of the whole leaf or plant. These larger scale effects can include: visible foliar injury and premature senescence; re duced carbohydrate producti on and reallocation; reduced growth or reproduction; and reduced pl ant vigor. Much of what is now known about O 3 exposure-plant response relationships, as summar ized below, is based on research that was
available in the last review. Thus, the present discussion is la rgely based on the conclusions of the 1978, 1986, and 1996 CDs (U.S. EPA, 1978; 1986; 1996a). Further, research results published since 1996 have supported earlier EPA conclusions (U.S. EPA, 2006) and in some cases have expanded and strengthened those conclusions. The sections below describe the current understanding of the physiological effects of O 3 on vegetation.

7.3.2.1 Visible Foliar Injury and Premature Senescence Cellular injury can and often does become visible. Acute in jury usually appears within 24 hours after exposure to O 3 and, depending on species, can o ccur under a range of exposures and durations from 0.04 ppm for a period of 4 hours to 0.41 ppm for 0.5 hours for crops and 0.06 ppm for 4 hours to 0.51 ppm for 1 hour for trees and shrubs (J acobson, 1977). Chronic injury may be mild to severe. In some cases, cell deat h or premature leaf senescence may occur. The significance of O 3 injury at the leaf and w hole plant levels depends on how much of the total leaf area of the plant has been affected, as well as the plant’s age, size, developmental stage, and degree of functional redundancy among the existing leaf area. Previous CDs have noted the

7-7difficulty in relating visible foliar injury symptoms to other vegetation effects such as individual tree growth, stand growth, or ecosystem characteristics (U.S. EPA, 1996a) and this difficulty remains to the present day (See discussion in section 7.6.3.2). As a result, it is not presently possible to determine, with consistency across sp ecies and environments, what degree of injury at the leaf level has significance to the vigor of th e whole plant. However, visible foliar injury by itself, can impact the public welfare. The presence of visible symptoms due to O 3 exposures can reduce the market va lue of certain leafy crops (such as spinach, lettuce) and impact the aesthetic value of ornamentals (such as petunia, geranium, and poinsettia) in urban landscapes and scenic vistas in protected natural areas such as national parks and wilderness areas. Though not quantified, there is likely some level of economic impact to
businesses and homeowners from O 3 -related injury on sensitive ornamental species due to the cost associated with more frequent replacemen t and/or increased main tenance (fertilizer or pesticide application). In addition, because O 3 not only results in discoloration of leaves but can lead to more rapid senescence (ear ly shedding of leaves), there is a potential for some lost tourist dollars at sites where fall foliage is less availabl e or attractive. In recent years, field surveys of visibl e foliar injury symptoms have become more common, with greater attention to the standard ization of methods and the use of reliable indicator species (Campbell et al., 2000; Smith et al., 2003). Specifically, the Unites States Forest Service (USFS) through the Forest Hea lth Monitoring Program (FHM) (1990 - 2001) and currently the Forest Inventory and Analysis (FIA ) Program collects data regarding the incidence and severity of visible foliar injury on a variety of O 3 sensitive plant species throughout the U.S. (Coulston et al. 2003, 2004; Smith et al. 2003). Section 7.6.3.2 contains additional information on the use of visible foliar injury inciden ce on bioindicator species as a measure of the occurrence of phytot oxic levels of O 3 in the ambient air. To view pictures of O 3 -induced foliar injury symptoms to selected sensitive species go to the USDA Agricultural Research Service website ( http://www.ars.usda.gov/Main/docs.htm?docid=12463 ) or the USDA Forest Service Ozone Biomonitoring website ( http://www.fiaozone.net/species/index.html ).

7.3.2.2 Carbohydrate Production and Allocation When total plant photosynthesis is su fficiently reduced, the plant will respond by reallocating the remainin g carbohydrate at the level of the w hole organism. Many studies have demonstrated that root grow th is more sensitive to O 3 exposure than stem or leaf growth (U.S. EPA, 2006). When fewer carbohydrates are present in the roots, less energy will be available for
root-related functions such as acquisition of water and nutrients. Mycorrhizal fungi in the soil form a symbiotic relationship with many terrestr ial plants. For host plants, these fungi improve

7-8the uptake of nutrients, protect the roots against pathogens, produce plant growth hormones, and may transport carbohydrates from one plant to another (U.S. EPA, 1996a). Ozone can disrupt the association between mycorrhizal fungi and host plants by inhibiting photosynthesis and the amount of carbohydrates available for transfer to the roots. This effect has recently been documented in the field. Data from a long-st udied pollution gradient in the San Bernardino Mountains of southern California suggest that O 3 substantially reduces ro ot growth in natural stands of ponderosa pine ( Pinus ponderosa ). Root growth in mature trees was decreased at least 87% in a high-pollution site as compared to a low-pollution site (Gru lke et al., 1998), and a similar pattern was found in a separate study with whole-tree harvest along this gradient (Grulke and Balduman, 1999). Though effe cts on other ecosystem components were not examined, a reduction of root growth of this magnitude could have signifi cant implications for the below ground communities at those sites. In contrast , a study in Great Smoky M ountains National Park
in Tennessee found no statistical ly significant effects of O 3 exposure on stem or root biomass for several tree species (Neufeld et al., 2000). The difference in the results from these two studies may reflect the species specific nature of the symbiont-host relationship. Unlike root systems, effects on leaf and needle carbohydrate content under O 3 stress range from a reduction (Barnes et al., 1990; Miller et al., 1989), to no effect (Alscher et al., 1989), to an increase (Luethy-Kr ause and Landolt, 1990). Therefore, studies that examine only above-ground vegetative components may miss important O 3 -induced changes below ground. These below-ground changes could signal a shift in nutrient cycling wi th significance at the ecosystem level (Young and Sanzone, 2002).

7.3.2.3 Growth and Reproduction Studies of the growth response of trees to O 3 have established that individual deciduous trees are generally less sensitive to O 3 than most annual plants, w ith the exception of a few genera such as Populus , which are highly sensitive and in some cases (for instance, quaking aspen and black cherry), are as sensitive to O 3 as annual plants. The O 3 sensitivity of seedlings and mature trees within species and between species varies widel y. In general, mature deciduous trees are likely to be more sensitive to O 3 compared to seedlings, while mature evergreen trees are likely to be less sensitive than seedlings. Based on these results, stomatal conductance, O 3 uptake, and O 3 effects cannot be assumed to be equivale nt in seedlings and mature trees. Depending on exposure durati on, concentrations of O 3 currently in the United States are sufficient to affect the growth of a number of tree species during th e annual growing season. However, these conclusions do not take into acc ount the possibility of “carry over” effects on growth in subsequent years, an important consider ation in the case of long-lived species. Given that multiple-year exposures may cause a cumulativ e effect on the growth of some trees (Hogsett

7-9et al. 1989; Simini et al., 1992; Temple et al., 1993), it is li kely that a number of species currently are being impacted. Other research in the U.S. in the last 10 years has focused on perennial forage crops (U.S. EPA, 2006). Recent results confirm that yields and quality of multiple-year forage crops are reduced at sufficient magnitude to have nutritional and possibly economic implications to their
use as ruminant animal feed at O 3 exposures that occur in some y ears over large areas of the U.S. Ozone may also reduce the quality or nutritive value of annual species.
Recent studies have also further demonstrated O 3 effects on different stages of plant reproduction. Effects of O 3 have been observed on pollen germination, pollen tube growth, fertilization, and abortion of reproductive structures, as reviewed by Black et al. (2000). For seed-bearing plants, reproductive ef fects will culminate in seed produc tion. The recent scientific literature supports the conclusions of the 1996 CD that ambient O 3 concentrations are reducing the yield of major crops in the U.S. For exampl e, the yield reductions fo r soybean are generally similar to those reported previously (U.S. EPA, 2006).

7.3.2.4 Reduced Plant Vigor Though O 3 levels over most of the U.S. are not high enough to kill vegetation directly,
current levels have been shown to reduce the ability of many sensitiv e species and genotypes within species to adapt to or withstand othe r environmental stresses. These may include increased susceptibility to freezi ng temperatures, pest infestati ons and/or root disease, and compromised ability to compete for available reso urces. For example, when different species are grown together, O 3 exposure can increase the growth of O 3 -tolerant species while exacerbating the growth decrease of O 3 -sensitive species. In the long run, the result of this loss in vigor may be plant death.

7.4 IMPACTS ON PUBLIC WELFARE

7.4.1 What Constitutes an Adverse Vegetation Impact from Ozone Exposure? Ozone can cause a variety of effects, begi nning at the level of the individual cell and accumulating up to the level of whole leaves, pl ants, plant populations, communities and whole ecosystems. Not all O 3 -related effects, however, have been classified as “adverse” to public
welfare. Previous reviews have classified O 3 vegetation effects as either “injury” or “damage” to help in determining adversity. Specifically, “injury” is defined as encompassing all plant reactions, such as reversible changes in plant metabolism (e.g., altered photosynt hetic rate), altered plant quality, or reduced growth, that do es not impair the intended use or value of the plant (Guderian, 1977). In contrast, “damage” incl udes those injury effect s that also reduce or impair the intended use or value of the plant. Damage includes reductions in aesthetic values

7-10(e.g., visible foliar injury in ornamental species) as well as losses in terms of weight, number, or size of the plant part that is harvested (yield lo ss). Yield loss also ma y include changes in crop quality, i.e., physical appearance , chemical composition, or the ability to withstand storage. While this construct has proved us eful in the past, it appears mo st useful in the context of evaluating effects on single plants or species grow n in monocultures, such as agricultural crops or managed forests. It is less clear how it might apply to potential eff ects on natural forests or entire ecosystems, such as shifts in species composition or nutrient cy cling where the intended use or value of the system is not specifically quantified. A more recent construct for assessing risks to forests described in Hogsett et al. (1997) suggests that “adverse effects coul d be classified into one or more of the following categories: (1) economic production, (2) ecological structure, (3) genetic resources, and (4 ) cultural values.” This expands the context for evaluating the adversity of O 3 -related effects beyond the species level. In another recent publication, A Framework for Assessing and Reporting on Ecological Condition: an SAB report (Young and Sanzone, 2002), additi onal support is provided for expanding the consideration of adversity by maki ng explicit the linkages be tween stress- related effects (e.g., O 3 exposure) at the species leve l and at higher levels within an ecosystem hierarchy. Staff suggests that consideration of adverse e ffects undertaken within the context of such a broader paradigm is appropriate in the context of this secondary NAAQS review.

7.4.2 Factors That Modify Functional and Growth Response The caveat that must be placed on results from any experimental study on the response of living organisms to a stressor in a specific sett ing is that uncertainty is introduced when attempting to extrapolate or apply those results ou tside that specific setti ng (e.g., to a different set of organisms, scales, or exposur e/growing conditions). The desc ription of plant response to O 3 exposure is no different. Because staff must necessarily rely on experimental data produced under very specific sets of conditions in conducti ng this assessment, it is important to understand the range of factors that can influence plant response to O 3 and the magnitude and direction of that response, in order to bette r assess the likelihood of observi ng the experimentally predicted response in the ambient environment. Plant response to O 3 exposure is a function of the plan t’s ongoing integration of genetic, biological, physical and chemical f actors both within and external to the plant. The corollary is
also true that O 3 exposure can modify the plant’s subs equent integrated response to other environmental factors, both by influencing the plant response directly, and by contributing to altered climatic factors that influence plan t response through its greenhouse gas forcing properties.

7-11The 1996 O 3 CD (U.S. EPA, 1996a) concluded with a statement that our understanding regarding modifying factors was too fragmented to permit draw ing many general conclusions. Unfortunately, in the interval since the 1996 CD , little additional information has become available, thus, this earlier conclusion remain s unchanged. Therefore, only a brief overview of the current understanding from th is research is provided. The r eader is referred to the 1996 CD (U.S. EPA 1996a) and the current 2006 CD (U.S. EPA 2006) for further information.

7.4.2.1 Genetics Plant response to O 3 is determined by genes that are di rectly related to oxidant stress and to an unknown number of genes that are not specifically related to oxida nts but instead control leaf and cell wall thickness, stomat al conductance, and the internal architecture of the air spaces. It is unlikely that single genes are responsible for O 3 tolerance, except in rare cases (Engle and Gabelman, 1966). Recent studies using molecular biological tool s and transgenic plants have begun to positively verify the role of various genes and gene products in O 3 tolerance and are beginning to increase the understanding of O 3 toxicity and differences in O 3 sensitivity. Specifically, O 3 has been shown to trigger the pro duction of a number of compounds (e.g., ethylene) and the signaling of these molecules determines, in some cases, the O 3 susceptibility of plants (U.S. EPA, 2006). Because the genetic code is species specific, species vary greatly in their responsiveness to O 3 . Even within a given species, indi vidual genotypes or populations can also vary significantly with respect to O 3 sensitivity. Thus, cauti on should be taken when ranking species categorically as having an absolute degree of sensitivity to O 3
.

7.4.2.2 Biological Factors The biological factors within the plant’s environment that may directly or indirectly influence its response to O 3 in a positive or negative manner encompass insects, other animal pests, diseases, weeds, and other competing pl ant species. Ozone and other photochemical oxidants may influence the severity of a disease or infestation either by direct effects on the causal species, or indirectly by affecting the host, or both. Li kewise, mutually beneficial relationships or symbioses involvi ng higher plants and bacteria or fungi may also be affected by

O 3 . Ozone can also have indirect e ffects on herbivorous animals due to O 3 -induced changes in feed quality. New evidence with regard to insect pests and diseases has done little to remove the uncertainties noted in the 1996 CD (U.S. EPA 1996a ). Most of the large numbers of such interactions that may affect cr ops, forest trees, and other natu ral vegetation have yet to be studied. With respect to any particular O 3 -plant-insect interaction, it is still not possible to predict its likelihood, or its severity. Th e situation is only a little cleare r with respect to interactions involving facultative necrotrophic plant pathogens, with O 3 generally leading to increased

7-12disease. In contrast, with oblig ate biotrophic fungal, bacterial, and nematode diseases, there are twice as many reports indicating O 3 -induced inhibitions than enhancements. At this time, therefore, although some diseases may become mo re widespread or severe as a result of exposure to O 3 , it is still not possible to predict which di seases are likely to present the greatest risks to crops and forests.
The latest studies on O 3 interactions with root symbiont s present a more complex picture
than was described in the last review. In addition to adverse effects of O 3 on the functioning of tree root symbioses with mycorrh izae (discussed in se ction 7.3.1 above), there is also evidence that the presence of mycorrhizae may help plan ts overcome root diseases stimulated by O 3 and/or encourage the spread of mycorrhizae to the roots of uninfected trees. The few recent studies of the impact of O 3 on intraspecific plant competition have again confirmed that grasses frequently show greater re silience than other types of plants. In grasslegume pastures, the leguminous species suffer gr eater growth inhibition. Separately, the suppression of ponderosa pine seedling growth by blue wild-rye grass was markedly increased by O 3 (Andersen et al. 2001). Due to the limite d number of species studied under competitive situations to date, however, it is still not possible to predict the outcome of O 3 exposure on other specific competitive situations, such as successional plant communities or crop-weed interactions. Clearly, however, O 3 stress creates a selective pr essure in some vegetative
communities that can lead to a shift in community composition. This community change may be undesirable in some settings.

7.4.2.3 Physical Factors The interaction of a plant with its physical environment (e.g., light, temperature, relative humidity, soil moisture and wind speed/turbulence) influences the degree and/or nature of the plant response to O 3 exposure. Light is an essential “resource” whose energy content drives photosynthesis and CO 2 assimilation. It has been suggested that increased light intensity may increase the sensitivity of light-tolerant species to O 3 while decreasing the O 3 sensitivity of shade-tolerant species, but this appears to be an oversimplification with many exceptions. Temperature affects the rates of all physio logical processes based on enzyme-catalysis and diffusion, and each process and overall growth (t he integral of all processes) has a distinct optimal temperature range. Although some recent field studies have indicated that O 3 impact significantly increases with increased ambient te mperature, other studies have revealed little effect of temperature. Temperature is unques tionably an important va riable affecting plant response to O 3 in the presence of the elevated CO 2 levels contributing to global climate change (see below). In contrast, evidence continues to accumulate to indica te that exposure to O 3 sensitizes plants to low temperature stre ss by reducing below-ground carbohydrate reserves,

7-13possibly leading to responses in perennial species ranging from rapi d demise to impaired growth in subsequent seasons. High relative humidity of the ambient air has generally been found to increase the
adverse effects of O 3 by increasing stomatal conduc tance and thereby increasing O 3 flux. Similarly, abundant evidence indicates that the r eady availability of so il moisture results in greater sensitivity to O 3 . The opposite condition, drought, has been observed in field experiments and modeled in computer simulations to provide partial “p rotection” against the
adverse effects of O 3 as would be expected. This is because, in the short-term, drought causes stomates to close and thus, decrease the exposure to O 3 . However, there is also compelling
evidence that O 3 can predispose plants to drought stress. Hence, the response will depend to some extent upon the sequence in which the stresses occur, and the species-sp ecific nature of the response. Regardless of the interaction, howev er, the net result of dr ought on growth in the short-term is negative, although in the case of tree species, othe r responses such as increased water use efficiency could be a benefit to long-term survival. Wind speed and air turbulence affect the thickness of the boundary layers over leaves and canopies and, hence, affects gas exchange rates. These factors can have a significant impact on the relationship between ambient ai r exposures and actual exposure c oncentrations at the leaf or canopy surface.

7.4.2.4 Chemical Factors Mineral nutrients in the soil, other gaseous air pollutants, and agricultural chemicals
constitute chemical factors in the environment. The evidence regarding interactions with specific nutrients is still too contradictory to permit any sw eeping conclusions. Somewhat analogous with temperature, it appears that a ny shift away from the nutritional optimum may lead to greater sensitivity, but the shift would have to be substantia l before a significant effect on response to O 3 was observed.
Interactions of O 3 with other air pollutants have recei ved relatively littl e recent attention.
The situation with SO 2 remains inconsistent, but seems unlik ely to pose any additional risk to
those related to the individual pollutants. With NO and NO 2 , the situation is complicated by
their nutritional value as N sources. In leguminous species, it appears that NO 2 may reduce the impact of O 3 on growth, with the reverse in other speci es, but the nature of the exposure pattern, i.e., sequential or concurrent, also determines th e outcome. Much more investigation is needed before it will be possible will be able to predict the outcomes of different O 3 -NO-NO 2 exposure scenarios. The latest research into O 3 × acid rain interactions has confirmed that, at realistic acidities, significant interactions are unlikel y. A continuing lack of information precludes offering any generalizations a bout interactive effects of O 3 with NH 3 , HF, or heavy metals.

7-14More evidence has been reported that the appl ication of fungicides affords some protective effects against O 3
. Over the last decade, considerable emphasis has been placed on research into O 3 interactions with two com ponents of global climate change: increased atmospheric CO 2 and increased mean global temperature. Most of these studies, however, have tended to regard
increased CO 2 levels and increased mean temperatures as unrelated phenomena, in spite of the crucial role of temperature as a climatic determinant (Monteith and Elston, 1993). Thus, experiments that examine the effects of doubled CO 2 levels at the current mean ambient temperatures are not particularly helpful in tryi ng to assess the impact of climate change on responses to O 3 , since most of the biotic and chemi cal interactions with oxidants may be modified by these climatic changes. T hough it is now known from limited experimental evidence and evidence obtained by computer simula tion that an atmosphere sufficiently enriched
with CO 2 (e.g., 600 + ppm) would more th an offset the impact of O 3 on responses as varied as wheat yield or the growth of young Ponderosa pine trees, the concurrent increase in temperature would reduce, but probably not eliminate, the net gain. Little, if any, experimental evidence exists related to three-way interactions, such as O 3 × CO 2 × disease or O 3 × CO 2 × nutrient availability . Increased use of computer simulations may be important in suggesting outcomes of the many complex interactions of O 3 and various combinations of environmental factors. However, the results obtained will only be as reliable as the input data used for parameterization. Thus, additional data from organized, systematic
studies are needed. It is important to recognize that wide vari ations in net impacts of climate change in different geographic areas are expected. Many regions are pr edicted to expe rience severe, possibly irreversible, adverse e ffects due to climate change. The EPA is currently leading a research effort that uses regional-scale climate models with the goal of identifying changes to O 3 and PM concentrations that may occur in a warming climate. An assessment of the results of this effort is expected to be available for c onsideration in the ne xt review of the O 3 NAAQS.

7.5 CHARACTERIZATION OF VEGETA TION EXPOSURES TO OZONE

7.5.1 Key Considerations in Vegetation Exposure Characterization In the last review, the Administra tor chose to make the secondary O 3 NAAQS equal to the primary standard set as the th ree year average of the annual 4 th -highest daily maximum 8-hr average concentrations at the level of 0.08 ppm. While recognizing this as a reasonable policy choice, she also recognized that “a SUM06 seasonal standard is more biologically relevant and, therefore, ... also appropriate to consider” (62 FR 38877). This conclusion by the Administrator in 1997 is again supported by the recent body of science reviewed in the 2006 O 3 CD (U.S. EPA,

7-152006). Staff, therefore, c ontinues to express hourly O 3 monitoring data in terms of both the 8-hr average and seasonal cumulative index forms for comparison. Staff considers the cumulative, concentration weighted SUM06 and W126 index forms discussed in the 1996 Staff Paper (U.S. EPA, 1996b). Staff rationale for including the W 126 will emerge from the discussions of current patterns of O 3 air quality and of policy-relevant b ackground (PRB) in the remainder of this section. Further, in a letter to the Ad ministrator on October 24, 2006, CASAC indicated a preference for the W126 form (Henderson, 2006c). Below are the definitions of the three index forms considered in this review and how they w ill be referred to in the rest of this document:

• 8-hr average form : 4 th -highest daily maximum 8-hr average over the O 3 season.

• 12-hr SUM06 : 3-month sum of all hourly O 3 concentrations greater than or equal to 0.06 ppm observed during the daily 12-hr period be tween 8 am and 8 pm. The 3 months are the maximum consecutive 3 months during the O 3 season.

• 12-hr W126 : Sigmoidally weighted 3- month sum of all hourly O 3 concentrations observed during the daily 12-hr period between 8 am to 8 pm. The 3 months are the maximum consecutive 3 months during the O 3 season.

More specifically, W126 is defined in Lefohn et al., 1988 as:



## ∑ <

= − + = = = PMi

AMi C C i iC t i i e wandihouratOhourlyCwhereCw W 8

8 126 3 44031 1

, , 126

Staff selected two levels of air quality to evaluate for each of th ese alternative standard forms. Specifically, the levels analyzed were 0.084 and 0.070 ppm, 25 and 15 ppm-hr, and 21 and 13 ppm-hr levels for the 8-hr average, the 12-hr SUM06, and the 12-hr W126 forms, respectively. The current level of the 8-hr average form is 0.084 ppm and the 0.070 ppm level was chosen as a possible alternative. For both the 12-hr SUM06 and 12-hr W126 forms, the two levels were
selected on the basis of the associated levels of crop yield loss protecti on described in the last review. Specifically, both the upper levels of 12-hr SUM06 (25 ppm-hr) and 12-hr W126 (21 ppm-hr) were associated with a level of crop protection of ap proximately no more than 10% yield loss in 50% of crop cases studied in the National Crop Loss Assessment Network (NCLAN) experiments (section 7.6.2.2.). This leve l was proposed for a secondary standard in the 1996 review. Alternatively, the lower leve ls of both SUM06 (15 ppm-hr) and W126 (13 ppm-hr) were associated with a level of crop protection of ap proximately no more than 10% yield loss in 75% of NCLAN cases . Another level to note is the upper level benchmark of W126

7-16The 1997 final rule recognized that “it remained uncertain as to the extent to which air quality improvements designed to reduce 8-hr O 3 concentrations would reduce O 3 exposures measured by a seasonal SUM06 index” (62 FR 38876) . In the last review, staff undertook an analysis to explore the relati onship between the 8-hr average form and the seasonal SUM06 index. Results of that analysis suggested that many areas that were above the proposed SUM06 standard of 25 ppm-hr were al so above the 0.08 primary standa rd. However, considerable uncertainty remained as to the strength of the relationship, especi ally between urban O 3 air quality and distributions that oc cur in non-monitored rural or remote areas. Using recent (2001- 2004) county-level air quality data, staff has performed a similar analysis to compare the degree of overlap between the current le vel of the 8-hr average form a nd exposure levels of concern for vegetation expressed in terms of the 12- hr W126. Figure 7-1 depicts county O 3 air quality in terms of both the current secondary standard 8-hr average form (Y-axis) and the 3-month 12-hr W126 form (X-axis). This graph shows the rela tionship between these two forms averaged over three recent years (2002-2004). Both the 21 a nd 13 ppm-hr levels for the 12-hr W126 are indicated on the graph. For the 3-year aver age of 2002-2004, only a few counties would have a 12-hr W126 higher than a level of 21 ppm-hr while meeting the 0.08 level of the current 8-hr average form. At the lower 12-hr W126 level of 13 ppm-hr, approximately 135 counties would have a 12-hr W126 higher than a level of 13 ppm-h rs while meeting the 0. 08 level of the current 8-hr average form. Based on this comparison, air quality levels associated with adverse Since the conclusion of the last review, improvements in O 3 air quality have occurred in some areas of the U.S. In the eastern U.S., thes e improvements may be attributable in part to the reductions in NOx emissions resulting from the initiation of Phase II of the acid rain program (U.S. EPA, 2004) and the NOx SIP call in 2002 (see Chap ter 2 of this SP). In addition, efforts to attain the current NAAQS have no doubt contri buted to some air quality improvements, including lower hourly maximum values and fewe r occurrences of those maximum values at some sites. One example of this is at the Crestline site in California, where the number of days
with concentrations ≥ 95 ppb has been declining steadily over the last decade, matched by a decline in peak 1-hr concentra tions and 12-hr SUM06 values. These declines match a similar trend in NOx and reactive organic gases (U.S . EPA, 2006, section Annex 9-207, Figure AX9-17) (U.S. EPA 2006; Lee et al 2003). Ho wever, not all areas in the U.S. show this declining trend. of 31 ppm-hr that approximates the upper end of the SUM06 range analyzed in the last review (U.S. EPA, 1996b) and which was associated with up to 17% yield loss in 50% of crop cases. All approximate equivalency calculations be tween the 12-hr W126 and 12-hr SUM06 metrics discussed in Chapter 7 and Chap ter 8 of this document were done based on NCLAN data (See Appendix 7B).

7-17Figure 7-1. The 3-year average (2002-2004) of the 4th-highest maximum 8-hr average (current standard form) versus the 3-year average of the highest 3-month 12-hr W126, by county.Highest 3-month 12-hr W126 (ppm-hrs), 3-year average0 10 20 30 40 50 60 70 80 90

4th Highest Max. 8-hr Aver age (ppm), 3-year average0.000.020.040.060.080.100.120.1412-hr W126 options analyzedCurrent standardAlternative standard7-18vegetation response can occur in some areas th at meet the current 8-hr average secondary NAAQS. The number of counties m eeting the current 8-hr averag e standard and above a 12-hr W126 standard would obviously depend greatly on the level of 12-hr W126 and 8-hr average form selected. In addition, the number of counties also varies depending on the air quality of a particular year or set of years. Figures of the relationship between the current 8-hr average form and 12-hr W126 for 2002 and 2004 are presented in Appendix 7B. These figures demonstrate that the relationship between the current 8-hr average form and 12-hr W126 is not constant and can vary between years. Thus, staff suggests caution should be used in evaluating the likely vegetation impacts associated with a given level of air quality expressed in terms of the 8-hr average form in the absence of parallel 12-hr SUM06 or W126 information. Unfortunately, much of the data published both in this review and in other Agency re ports only depicts trend information in terms of the 8-hr average form. National parks represent areas of nationally recognized ecological and public welfare significance, which are afforded a higher level of protection. Therefore, st aff has also focused on air quality in the subset of national park sites and important natural areas . Two recent reports presented some discussion of O 3 trends in a subset of nationa l parks (See discussion in The Ozone Report: Measuring Progress thr ough 2003 (U.S. EPA, 2004) and 2005 Annual Performance and Progress Report: Air Quality in national parks (NPS, 2005). Unfortunately, much of this information is presented only in term s of the current 8-hr average form. Therefore, staff has selected a subset of national parks and other significant natu ral areas representing 4 general regions of the U.S to analyze available ai r quality data in terms of the 12-hr W126 levels from 2001 to 2005 (Figures 7-2 and 7-3). These graphs show that many national parks and
natural areas have monitored O 3 levels above concentrations that have been shown to decrease plant growth and above the 12-hr W126 levels analy zed in this review. For example, one park in the east and four parks in the we st had more than one year with a 12-hr W126 above 21 ppm-hr. This level of exposure has been estimated to cause a 9% biomass loss in 50% of the 49 tree seedling cases studied (Lee and Hogsett, 1996). Sensitive tree seedling species such as black cherry ( Prunus serotina ) and ponderosa pine ( Pinus ponderosa ) have been reported to have 10%
biomass losses at levels as low as 5 and 11 ppm-hr (Lee and Hogsett, 1996). Impacts on seedlings may potentially affect long-term growth and survival, ultimately affecting the competitiveness of sensitive species and individual trees. Another key aspect of evaluating exposu re levels of concern to vegetation is distinguishing between pollution levels that can be controlled by U.S. regulations (or through international agreements with ne ighboring countries) from levels that are generally considered uncontrollable by the U.S., e.g., policy-relevant-b ackground (PRB). As described in Chapter 2 of this SP, the global photochemical transport m odel GEOS-CHEM (Fiore et al., 2003) was used

7-19Figure 7-2. Highest 3-month 12-hr W126 values from monitors in National Parks and other natural areas in the Southeast (A) and Northeast (B). Monitors designated as GSMNP are found in different areas of the Great Smoky Mountain National Park.

Year 2001 2002 2003 2004 2005Max 3-month 12-hr W126 (ppm-hr)

0 10 20 30 40 50 60 70 80

GSMNP-Purchase Knob GSMNP-Clings. Dome
GSMNP-Look Rock
GSMNP-Cades Cove
Shenandoah NP

Year 2001 2002 2003 2004 2005Max 3-month 12-hr W126 (ppm-hr)

0 10 20 30 40 50 60 70 80

Base Whiteface Mtn,NY Summit,Whiteface Mtn,NY Mt. Washington, NH Mt. Greylock, MA Acadia NP, ME A.

B.

7-20Figure 7-3. Highest 3 month 12-hr W126 values fr om monitors in National Parks in the Mountain West (A) and California (B).

Year 2001 2002 2003 2004 2005Max 3-month 12-hr W126 (ppm-hr)

0 10 20 30 40 50 60 70 80
Rocky Mtn, NP
Yellowstone NP Grand Canyon NP
Glacier NP

Year 2001 2002 2003 2004 2005Max 3-month 12-hr W126 (ppm-hr)

0 10 20 30 40 50 60 70 80

Sequoia NP Yosemite NP 

### A.

B.

7-21to estimate PRB levels. This model shows that PRB O 3 concentrations, which vary as a function
of season, altitude and total surface O 3 concentration, are generally pr edicted to be in the range of 0.015 to 0.035 ppm at the surface in the afte rnoon, and they decline under conditions
conducive to O 3 episodes. They are highest during sp ring and decline into summer. Higher values tend to occur at higher elevations duri ng spring due to contributions from hemispheric pollution and stratospheric intrusions. Th e stratospheric contribution to surface O 3 is typically well below 0.020 ppm and only rarely elevates O 3 concentrations at low-altitude sites and only slightly more often elevates them at high-altitude sites (U .S. EPA, 2006, AX3-148). The modeled range of 0.015 to 0.035 ppm in the 2006 CD is lower than the 0.03 to 0.05 ppm range used as background O 3 in the 1996 O 3 NAAQS review (U.S. EPA, 1996a, 2006). This is significant for the secondary standard review because the highe r end of the range (0.05 ppm) provided an important policy consideratio n for staff in 1996 for selecting the cumulative SUM06 exposure index that did not weight concentrations be low 0.06 ppm. Thus, SUM06 was not influenced by concentrations thought to be at background. Partially on the basis of these lower estimat es of PRB, as well as declining peak O 3 levels at some sites, staff has re-evaluated the usef ulness of using the si gmoidally weighted W126 index to capture more of the vegetation rele vant exposures below 0.06 ppm. Though the W126 index weights all concentrati ons, the concentrations below 0.04 ppm receive substantially smaller weights (3 percent or less) so as not to contribute significantly to the value of the index (Lefohn et al. 1988). Indeed, a constant concen tration of the highest estimated PRB (0.035 ppm) would only add up to a 3-month 12-hr W126 of less than 1 ppm-hr. In addition, because the
W126 form does not contain an absolute threshol d like the SUM06 form, it is more in keeping
with scientific consensus that there is no threshold for exposures that cause effects on vegetation (Heck and Cowling 1997, U.S. EPA 2006). Further, CASAC has indicated a preference for the 12-hr W126 metric (Henderson, 2006c). Therefor e, staff has continued to include the 12-hr W126 in the vegetation risk analyses. Figure 7-4 shows the relationship between 12-hr W126
and SUM06 as measured at O 3 monitors in 2001. The metrics, as calculated at the monitors, are highly correlated. A similar correlation was s een with other years (2002-2004). Because the inflection point of W126 is appr oximately 0.06 ppm, the SUM06 metric is essentially a simple approximation of the sigmoidally weighted W126 form and it is not su rprising that the two
metrics measure O 3 exposures in a very similar way at most monitoring stations (Lee et al. 1989). Finally, the W126 metric should also be easier to model than SU M06 since small errors in prediction of hourly concentrations around 0.06 ppm could cause variations in the SUM06
metric. This issue is avoided in the continuous weighting of the W126.

7-22Figure 7-4. Maximum 3-month 12-hr SUM 06 plotted against maximum 3-month 12-hr W126. Data points are from the AQS and CASTNET O 3 monitors for the year 2001.

3-month 12-hr SUM06 (ppm-hr) 0 10 20 30 40 50 60 70 80 903-month 12-hr W126 (ppm-hr)

0 10 20 30 40 50 60 70 80 90

r 2 = 0.98 proposed1996 SUM06 standard

7-237.5.2 Monitor Networks: National Coverage Hourly O 3 monitoring data are available from two national networks: (1) Air Quality System (AQS; http://www.epa.gov/ttn/airs/airsaqs ) and (2) Clean Air Status and Trends Network (CASTNET; http://www.epa.gov/castnet/ ). The locations of these monitors are presented in Figure 7-5 and are described in sections 2.3.1 a nd 2.3.2 of this document. The AQS monitoring network currently has over 1100 active O 3 monitors which are genera lly sited near population centers. However, this network also includes approximately 36 monitors located in national parks. CASTNET is the nation's primary sour ce for data on dry acidic deposition and rural, ground-level O 3 . It consists of over 80 sites acros s the eastern and western U.S. and is cooperatively operated and funded with the National Park Service. Due to the overall stability in these monitoring networks and standardized, rigo rous QA/QC and data handling protocols, they provide useful information regarding long-term trends in air quality across regions and at specific sites. For more on the AQS protocols, se e section 2.3.1 of this Staff Paper or Code of Federal Regulations, Title 40, Part 58 (40 CFR Part 58). CASTNET, in terms of data quality, achieved 98% to 99% of all precision and accuracy audits being within the ±10% criteria for both precision and accuracy. Overall, CASTNET O 3 monitors are stable and show only very small variation (U.S. EPA 2003b, p.22). Both networks take O 3 measurements on an hourly time step which allows for quick comparisons between different air quality index forms and different averaging times. In spite of the size and quality of these mon itoring networks, however , vast rural areas of the U.S., where important crops and natura l vegetation occur, still do not have O 3 monitor coverage (Figure 7-5). As was the case in the 1996 review, sta ff found it necessary to select a
method that could be used to characterize O 3 air quality over broad geographical areas of concern (see sections 7.5.3 and 7.5.4 below) to support a national scale risk assessment of the
effects of ambient O 3 exposures on vegetation and ecosystems. Staff’s review of the monitoring
data showed that within the five most recen t years available (2000 to 2004), 2001 was a fairly
moderate O 3 year. Based on this information, and becau se it coincided with the most recently available air quality model data (see section 7.5.3. below), 2001 was selected as the initial (base) air quality year for most of the quantitative vegetation risk analyses conducted in this review. In a few cases (e.g., visible foliar injury and tree gr owth modeling), monitoring data from other air quality years were used.

7-24Figure 7-5. Locations of AQS monitors (top) and CASTNET mo nitoring stations (bottom)

7-257.5.3 Community Multi-scale Air Quality Model (CMAQ) Staff investigated the appr opriateness of using the O 3 outputs from the EPA/NOAA Community Multi-scale Air Qu ality (CMAQ) model system ( http://www.epa.gov/asmdnerl/CMAQ , Byun and Ching, 1999; Arnold et al. 2003, Eder and Yu, 2005) to improve spatial interpolations based on the regionally limited and unevenly distributed

O 3 monitoring network in the western U.S. (s ee section 7.5.2). The CMAQ model is a multipollutant, multiscale air quality model that c ontains state-of-the-science techniques for simulating all atmospheric and land processes that affect the transport, transformation, and deposition of atmospheric pollutant s and/or their precursors on both regional and urban scales. It is designed as a science-based modeling tool for handling many major pollutants (including photochemical oxidants/O 3 , particulate matter, and nutrient deposition) holistically. The CMAQ model can generate estimates of hourly O 3 concentrations for the co ntiguous U.S., making it possible to express model outputs in terms of a variety of exposure in dices (e.g., W126, 8-hr average). Due to the significant resources required to run CMAQ, however, model outputs are only available for a limited number of years. For this review, 2001 outputs from CMAQ version
4.5 were the most recent available. This version of CMAQ utilizes the more refined 12 km x 12 km grid for the eastern U.S., while using the 36 km x 36 km grid for the western U.S. The 12 km x 12 km domain covers an area from roughly central Texas, north to North Dakota, east to Maine, and south to central Florida. More detailed information on CMAQ can be found in Appendix 7C. Section 7.5.4 below describes the ve ry limited capacity in which staff used the CMAQ results. As explained below, in the final analysis, staff opted not to use O 3 values calculated from the CMAQ model, but instead only us ed model results to scale interpolations in
the western U.S.

7.5.4 Generation of Potential Oz one Exposure Surfaces (POES) Staff evaluated ten approaches for interpolating O 3 air quality across the U.S. which included (1) use of the CMAQ model alone; (2) us e of only monitoring data with the Voronoi Neighbor Averaging (VNA) techni que; and (3) use of a combin ation of monitoring data and scaling from CMAQ called enhanced Voronoi Neighbor Averaging (eVNA). The evaluations were based on how well the CMAQ model or inter polation techniques were able to predict the 12-hr SUM06, 12-hr W126 and the current 8-hr average form measured at each monitor. For VNA and eVNA evaluations, each monitor was dr opped out sequentially and a value for that monitor was interpolated using th e remaining monitors. At each monitor site, Normalized Mean Bias (NMB), Normalized Mean Error (NME), Absolute Mean Bias (AMB) and Absolute Mean Error (AME) were calculated (Table 7-1). Fo r more details see discussions in section 7.5.5 below and in the Environmental Assessment TSD (Abt, 2007). From the results of these

7-26Figure 7-6 suggests that under the base year (2001) air quality, a large portion of
California had a 12-hr W126 above 31 ppm-hr which has been re ported to produce 14% biomass loss in 50% of tree seedlings st udies by National Health and E nvironmental Effects Research Lab, Western Ecology Division ( NHEERL-WED). Broader multistate regions in the east and west were predicted to have 12-hr W126 above 21 ppm-hr, which is appr oximately equal to the secondary standard proposed in 1996. A 12-hr W126 ppm-hr of 21 is associated with a 9%
biomass loss in 50% of tree seed lings studied (Lee and Hogsett, 1996). Much of the east and To support the vegetation exposure and risk assessments, ambient O 3 exposures were projected using seasonal O 3 air quality for the 2001 base year in terms of the 3-month 12-hr W126 (Figure 7-6) and 12-hr SU M06 exposure indices (Figure 7D-1 in Appendix 7D). The uncertainties of this interpolation are discu ssed below (section 7.5.5). Taking the uncertainties into account and given the absence of more comp lete monitoring data in rural areas, staff finds
the POES serves as a useful tool for identifying areas across the country where O 3 exposure levels would be expected to exceed those known to produce yield loss or biomass loss at given levels for crops and trees, respectively. To generate the POES, a set of geographical locations for which O 3 data would be interpolated was needed. Ideally these loca tions would be regular ly spaced, cover the continental US, and be close enough to each othe r to provide a good spatial resolution. Staff chose to use the regularly spaced grid structure of the CMAQ model as the basis for these locations. Specifically, the center of each grid cell was identified bot h for cells in the 12 km x 12 km grid (which covers only the Eastern U.S.), and the 36 km x 36 km grid (the Western US). This approach produced the de nsest possible non-redundant “com posite” grid of 44432 regularly spaced grid cell center locations throughout the U.S. Using VNA in the eastern U.S. and eVNA in the West, O 3 values were interpolated for each grid cell center in the composite grid (see
Environmental Assessment TSD fo r more details, Abt, 2007). evaluations, the eVNA and VNA performed equa lly well in many cases. The CMAQ model alone did not perform as well as the VNA and e VNA methods. The staff chose to use separate interpolation techniques in the east and the west. The simpler VNA approach was chosen for the
eastern U.S. since it was determined that enha ncing the interpolation with CMAQ did not add much information to the eastern U.S. interpol ation where the monitoring network has greater coverage than in the west (Figure 7-5). In the west, eVNA was chosen because of the sparse monitoring network in those states. Although the VNA and eVNA interpolation approaches are not as complex or sophisticated as some techniques (e.g., Bayesian methods), they have the advantages of relying on readil y available data, being relativelyinexpensive to run, and being able to quickly produce estimates of a ny exposure index, for multiple months or years, and for different air quality scenarios.

7-27Figure 7-6. Estimated 12-hr W126 Ozone Exposure –Max 3-months for 2001: “As Is” scenario7-28The exposure maps generated for the 0.070 ppm level of the 8-hr average form (Figure 7- 8), 12-hr SUM06 of 25 and 15 ppm-hr alternatives (Figures 7-9 and 7-10) and 12-hr W126 of 21 and 15 ppm-hr showed a markedly improved picture of O 3 air quality compared to Figure 7-7. Thus, the staff observes that, except for just m eeting the current form, all other alternative standards, when met at all lo cations, would be expected to provide improved protection of Maps generated for the SUM06 25 and 15 ppm-hr scen arios were nearly identical to the maps of 12-hr W126 levels of 21 and 13 ppm-hr and thus , only maps of the SUM06 25 and 15 ppm-hr scenarios are displayed. When 2001 air quality was rolled back to meeting the level of the current 8-hr standard (0.08 pp m), the overall seasonal 12-hr W126 exposures did not improve very much (Figure 7-7). Under this scenario, so me areas in the east improve, but there are still many areas of the country that have seasonal O 3 levels above 12-hr W126 of 21 ppm-hr. To evaluate changing vegetation exposure s and risks under changing air quality, maps were generated for selected "just meet" scenar ios (Figures 7-7, 7-8, 7- 9, 7-10) by analytically adjusting air quality distributions with the quadra tic method to reflect “just meeting” the level of various alternative standards (see Horst and Duff, 1995; Rizzo, 2005 & 2006). This technique combines both linear and quadratic elements to reduce larger O 3 concentrations more than smaller ones. In this regard, the quadratic method attempts to account for reductions in emissions without greatly affecting lower concentrations near ambient background levels. The following “just meet” air quality scenarios were generated: Arizona and California have seasonal W126 valu es above 13 ppm-, which has been associated with a 7% biomass loss in 25% of tree seedlings studied (Lee and Hogsett, 1996). This indicates that current air quality levels could result in si gnificant impacts to vege tation in some areas. However, these exposures may be uncertain in some cases with respect to vegetation with canopy heights below monitor inlet heights, e.g., crops and tree s eedlings. In the crop and tree seedling risk/benefit assessments, staff inco rporated an adjustment of monitored O 3 to take into account the uncertainty associated with a potential vertical O 3 gradient from the height of the monitoring probe (~4 meters) to the approxima te canopy height of crops and seedlings (see section 7.6.2.3).

• 3-month, 12-hr W126 of 21 ppm-hr and 13 ppm-hr • 3-month, 12-hr SUM06 of 25 ppm-hr (alterna te standard proposed in the 1996 NAAQS review) and 15 ppm-hr • 4 th -highest daily maximum 8-hr average of 0.084 ppm (current EPA standard) and 0.070 ppm

7-29Figure 7-7. Estimated 12-hr W126 Ozone Exposure – Max 3-months for 2001: Quadratic Rollback to just meet 4th-Highest 8-hr Maximum of >0.0847-30Figure 7-8. Estimated 12-hr W126 Ozone Exposure – Max 3-monthsfor 2001: Quadratic Rollback tojust meet 4th Highest 8-hr Maximum of >0.0707-31Figure 7-9. Estimated 12-hr W126 Ozone Exposure – Max 3-monthsfor 2001: Quadratic Rollbackto just meet 12-hr SUM06of 25 ppm-hr, secondary standard proposed in 19967-32Figure 7-10. Estimated 12-hr W126 Ozone Exposure – Max 3-months for 2001: Quadratic Rollback to just meet 12-hrSUM06 of 15 ppm-hr7-33vegetation from seasonal O 3 exposures of concern over the cu rrent standard. As expected, however, the greatest improveme nts in air quality and estima ted exposures to sensitive vegetation were observed when just meeting th e lower 12-hr W126 of 13, 12-hr SUM06 of 15 and 0.07 ppm, 8-hr average scenarios.

7.5.5 Uncertainties in the O 3 Exposure Analysis Staff recognizes there are inhere nt uncertainties in using an interpolation that must rely on sparse data that, for the most part, are repres entative of urban and near-urban areas. This
network could bias th e picture of the O 3 exposure estimate especially in the western U.S. where monitoring sites can be very far apart. Intuitiv ely, it is expected that the eVNA approach with spatial scaling from CMAQ approach would be an improvement over a simple interpolation in the West. However, it is difficult to test for this because of the paucity of monitoring sites in the
western U.S. To quantify the uncertainty associated w ith the exposure surface, each monitoring site was sequentially dropped out of the interpolation and recalculated with the remaining monitoring sites. At each monitoring site, Normalized M ean Bias (NMB), Normalized Mean Error (NME), Absolute Mean Bias (AMB) and Absolute Mean Error (AME) were calculated. These statistics
are defined below:

) *100(

i i i dropoutsi IC actualMETR IC actualMETR ETRIC predictedM average NMB −

= ∈

) *100(

i i i dropoutsi IC actualMETR IC actualMETR ETRIC predictedM average NME −

= ∈

AMB = average i ε dropouts ( predictedMETRIC i – actualMETRIC i )

AME = average i ε dropouts ( | predictedMETRIC i – actualMETRIC i | )

This method of evaluation may resu lt in a slight overestimation of error and bias for the exposure surface since dropping out monitors loses informati on that the interpolation uses in that local area. Summary error and bias metrics are pres ented in Tables 7-1a and b. Using all the monitors, the Eastern U.S. interpolation had an NME of about 26% for the 12-h SUM06 metric (Table 7-1a). Western U.S. interpolation ha d a much higher NME of approximately 62%. However, since SUM06 and W126 values are ofte n low numbers, NME can be calculated to be

7-34Figure 7-11 also depicts predicted W126 valu es, from the sequential drop-out exercise, against the actual W126 values measured at CASTNET monitors and AQS monitors designated as “rural.” This figure gives a grap hical representation of how well the O 3 exposures were predicted in the rural monitors away from urba n areas. A perfect predic tion would result in all points aligning on the black “one-to-one” line. In general, these graphs indicate that the interpolation technique sli ghtly overestimated W126 exposure at the low levels and underestimated W126 exposure at th e high levels. Biologically, the more significant error is at the high exposures, since vegetation responds more at high exposures. Fi gure 7-11 indicates, in general, that the most relevant high exposures were underestimated. This may have implications for the subsequent calculation of crop yield and tree seedling biomass loss, potentially resulting
in an underestimation of risk in some areas. Mo re detailed information from this analysis is presented in the Environmental Assessment TSD (Abt, 2007). large while the absolute difference is small. Fo r example, if a monitor with a W126 of 4 ppm-hr is measured and the interpolation predicts a W1 26 of 6 ppm-hr then the NME would be 50%. Therefore, staff thought it was useful to also report the absolute mean bias and error. In absolute terms, the average bias for SUM06 was slightly low (-1.83 ppm-hr in the East and -2.62 ppm-hr in the West). CASTNET monitors are also pr esented to illustrate how well the interpolation techniques predicted air quality in that rural monitoring network. In general, the interpolations in the East and West under-predicte d the 12-hr SUM06 values. Th is under-prediction is likely a result of the averaging inherent in the interpolation. Similar re sults are seen for the 12-hr W126 (Table 7-1b). However, in almost all cases, th e interpolation was able to predict monitored W126 slightly better than monito red SUM06. The calculation of error and bias metrics for the interpolation represents a notable improvement over the 1996 assessment which did not have an
evaluation of the error and bias asso ciated with the exposure surface.

7-35Table 7-1a. Evaluation statistics for the 3-month 12-hr SUM06interpolations of the Eastern and Western U.S. domains.NMB is Normalized Mean Bias, NME is NormalizedMean Error, AMB is Absolute Mean Bias and AME isAbsolute Mean Error. An explanationof these metrics is given in section 7.5.5.Table 7-1b. Evaluation statistics for the 3-month 12-hr W126 interpolations of the Eastern and Western U.S. domains.RegionMonitorsNMB (%)NME (%)AMB (ppm-hr)AME (ppm-hr)Eastern USAll monitors-0.0425.78-1.834.07Eastern USCASTNET only-8.8420.76-2.954.79Western USAll monitors16.4662.39-2.626.05Western USCASTNET only-6.0342.12-2.157.98RegionMonitorsNMB (%)NME (%)AMB (ppm-hr)AME (ppm-hr)Eastern USAll monitors-1.0621.92-1.212.97Eastern USCASTNET only-8.4317.44-2.003.22Western USAll monitors14.5748.38-1.504.27Western USCASTNET only0.6741.47-0.605.217-36Figure 7-11. Comparison of predicted v ersus observed 12-hr W126 at CASTNET and “rural” AQS monitors. Monitor data was predicted by dropping out each monitor sequentially and interpolated with the all remaining monitors



### .

Observed 3-month 12-hr W126 (ppm-h) 0 5 10 15 20 25 30 35Predicted 3-month 12-hr W126

0 5 10 15 20 25 30 35

Best fit line

Observed 3-month 12-hr W126 (ppm-h) 0 10 20 30 40 50 60 70Predicted 3-month 12-hr W126

0 10 20 30 40 50 60 70

r 2 = 0.74 East

West One-to-one line

One-to-one line r 2 = 0.60

7-377.6 CHARACTERIZATION OF VEGETATION RISKS

7.6.1 Scope of Vegetation Risk Assessment The vegetation impact assessment conducted fo r the current review (see Figure 7-12a-c), consists of exposure, risk and benefits an alyses and improves and builds upon the similar analyses performed in support of the 1996 s econdary NAAQS review (U.S. EPA 1996b). The vegetation exposure assessment wa s discussed above in section 7.5. The organization of this section reflects the remaining risk and benef it components of the asse ssment. The vegetation
risk discussion which follows is divided between the crop and tree analyses. The crop analysis
discussed in section 7.6.2 include s estimates of the risks to crop yields from current and
alternative O 3 exposure conditions and the associated ch ange in economic benefits expected to accrue in the agriculture sector upon meeting the leve ls of various alternative standards. The tree risk analysis described in secti on 7.6.3 includes three dis tinct lines of evidence: (1) estimates of seedling growth loss under current and alternative O 3 exposure conditions; (2) observations of visible foliar injury in the fiel d linked to recent monitored O 3 air quality for the years 2001 - 2004; and (3) simulated mature tr ee growth reductions using the TREGRO model to simulate the effect of meeting alte rnative air quality standards on the predicted annual growth of a single western species (ponderosa pine) and two eastern species (red ma ple and tulip poplar). Both quantitative and qualitative discussions of known s ources and ranges of uncertainties associated with the components of this as sessment are also discussed.

7-38Figure 7-12 (a-c). Major Componen ts of Vegetation Risk Assessment

Ozone monitor

data CMAQ air quality model output Interpolation of regional potential ozone exposure surface

National maps: W126 and SUM06

(‘as is’ and ‘just meet’)

County USDA crop planting data

Economic impact of crop loss AgSIM model Calculation of % yield

loss NCLAN C-R functions

Calculation of seedling growth loss USGS range maps OTC C-R functions

Maps Maps County USFS foliar injury data County ‘As is’ air quality (a) Exposure

(b) Risks

Crop yield Foliar injury Seedling growth

(c) Economic Benefits TREGRO Model for 3 species Tree growth

‘As is’ & ‘just meet’ air quality from east

& west sites

Air quality/injury comparison

7-397.6.2 Characterization of Crop Risks and Associated Economic Benefits

7.6.2.1 Exposure Methodologies Used in Vegetation Research In the 1996 review, O 3 exposure studies were dominated by the use of various versions of the open-top chamber (OTC), first described by H eagle et al. (1973) and Mandl et al. (1973). Hogsett et al. (1985, 1987) described in detail ma ny of the subsequent modifications to the original OTC design. The OTC method continues to be a widely used technique in the U.S. and Europe for exposing plants to varying levels of O 3 (U.S. EPA, 2005b). Chambered systems, including OTCs, have several advantages. For instance, they can provide a range of treatment leve ls including charcoal-filtered (CF), clean-air control, and above
ambient concentrations for O 3 experiments. Depending on experi mental intent, a replicated,
clean-air control treatment is an essential co mponent in many experimental designs. The OTC can provide a consistent, defina ble exposure because of the cons tant wind speed and delivery systems. From a policy perspective, the st atistically robust concen tration-response (C-R) functions developed using such systems are nece ssary for evaluating the implications of various alternative air qua lity scenarios on vegetation response. Nonetheless, there are several characteristi cs of the OTC design and operation that can lead to exposures that might diffe r from those experienced by plants in the field. First, the OTC plants are subjected to constant turbulence, which, by lowering the boundary layer resistance to diffusion, which may result in increased uptake. This may lead to an overestimation of effects in areas with less turbulence (Krupa et al., 1995; Le gge et al., 1995). As with all methods that expose vegetation to modified O 3 concentrations in chambers, OTCs create internal
environments that differ from ambient air. Th is so-called “chamber effect” refers to the modification of microclimatic variables, incl uding reduced and uneven light intensity, uneven rainfall, constant wind speed, reduced dew form ation, and increased air temperatures (Fuhrer, 1994; Manning and Krupa, 1992). Howe ver, staff notes that the uncer tainties associ ated with the influence of other modifying factors occurring in the field such as water and nutrient availability (see discussion above in section 7.4.2 ), are likely to be greater than the uncertainties in the data
due to the influence of OTCs. Because of th e standardized methodology and protocols used in National Crop Loss Assessment Network (NCLAN) and other programs, the database can be assumed to be internally consistent.
While it is clear that OTCs can alter some aspects of the microenvironment and plant growth, the question to be answ ered is whether or not these differences affect the relative response of a plant to O 3 . As noted in the 1996 O 3 CD (U.S. EPA, 1996a), evidence from a number of comparative studies of OTCs and other exposure syst ems suggested that responses were essentially the same regardless of expos ure system used and chamber effects did not

7-40significantly affect response. For example, a study of chamber effects examined the responses of
tolerant and sensitiv e white clover clones ( Trifolium repens ) to ambient O 3 in greenhouse, opentop, and ambient plots (Heagle et al., 1996). The response found in OTCs was the same as in ambient plots. The California Air Res ources Board (CARB), during its recent O 3 standard review, came to a similar conclusion about the usefulness of OTC data. Its review states “there is little scientific ju stification for the categ orical discounting of O 3 yield-response relationships obtained using the OTC t echnology” (CEPA, 2005). In recent years, a few studies have employed a modified Free Air CO 2 Enrichment (FACE) methodology to expose vegetation to elevated O 3 without using chambers. This exposure method was originally developed to ex pose vegetation to elevated levels of CO 2 , but
has been modified to include O 3 exposure in Illinois (SoyFACE) and Wisconsin (AspenFACE) for soybean and deciduous trees, respectively (D ickson et al., 2000; Morgan et al., 2004). The FACE method releases gas (e.g., CO 2 , O 3 ) from a series of orifices placed along the length of the vertical pipes surrounding a circular field plot and uses the prevaili ng wind to distribute it. This exposure method may more closely replicate cond itions in the field and, more importantly for forest research, has the benefit of being able to expand vertically with the growth of the trees, allowing for exposure experiments to span numerous years. The FACE methodology has a different set of li mitations than those of the OTC. Most importantly, it is not possible with FACE to pr oduce a number of replicated treatment levels, including O 3 concentrations below ambient levels that are needed to build the statistically robust C-R functions possible with OTCs. One also must recognize the potential for significant gradients of exposure gas concentrations through out the FACE exposure rings. While the FACE protocols minimize exposure concentration gradie nts, plants near the gas emitters will be exposed to larger concentrations than centrally located plants near the air monitoring point. There is little information on within-plot O 3 concentrations in FACE -type exposures and this issue needs to be addressed more fully to understand O 3 exposure and response data from FACE studies. Despite the differences in these two exposure methods, recent evidence obtained using FACE and OTC systems appear to support the re sults observed in OTC studies used in the 1996 review. For example, a series of studies undertaken at AspenFAC E (Isebrands et al., 2000, 2001) showed that O 3 -symptom expression was generally si milar in OTCs, FACE, and ambientO 3 gradient sites, and supported the previously observed variation among trembling aspen clones ( Populus tremuloides L.) using OTCs (Karnosky et al., 1999). In the SoyFACE experiment in Illinois, s oybean (Pioneer 93B15 cultivar) yield loss data from a two-year study was recently published (M organ et al., 2006). This cultivar is a recent selection and, like most modern cultivars, has been selected with an already high current O 3 . It was found to have average sensitivity to O 3 compared to 22 other cultivars tested at SoyFACE.

7-41In this experiment, ambient hourly O 3 concentrations were increas ed by approximately 20% and measured yields were decreased by 15% in 2002, as a result of the increased O 3 exposure (Morgan et al., 2006). To comp are these results to chamber studies, Morgan et al. (2006) calculated the expected yield loss from a linear relationship constructed from chamber data using 7-hr seasonal averages (Ashmore, 2002). They cal culated an 8% expected yield loss from the

2002 O 3 exposure which was surprisingly less than th e measured 15% yield loss. Staff believes that the expected yield loss may have been closer if the authors used C-R functions based on the W126 metric. Nonetheless, the re sults from this study suggest th at C-R relations hips developed from chambers are not overestimating response of recently developed soybean cultivars to
elevated O 3 exposure. As more FACE data become av ailable, a more quantitative comparison of findings from the SoyFACE and AspenFACE systems would be useful. Other exposure methods described both in the 1996 and 2006 O 3 CDs (U.S. EPA, 1996a; U.S. EPA 2006) also provided useful information on plant responses to O 3 exposure. For example, Gregg et al. (2003), found significant effects of O 3 on the growth of cottonwood saplings along an ambient O 3 gradient in the New York City area, similar to those reported in OTCs (see section 7.6.3. Other exposure met hods include but are not limited to chemical protectants (e.g., ethylen ediurea [EDU]) and O 3 exclusion. Nonetheless, given a continued policy need for robust C-R functions to evaluate vegetation response under alternative air quality scenarios and the apparent cons istency between plant response s using OTC and other methods,
staff concludes that the robust C-R functions derived using the OTC methodology are currently the most useful in a policy context and we contin ue to rely on them in the following analyses.

7.6.2.2 Basis for C-R Functions The 1996 crop assessment was built upon the NCLAN O 3 C-R functions. Since very few new studies have publishe d C-R functions that would be usef ul in an updated assessment, C-R
functions from NCLAN remain the best data available for a national assessment of crop loss
under various O 3 air quality scenarios. The NCLAN pr otocol was designed to produce crop C-R functions representative of the areas in which the crops were typically grown. The U.S. was divided into 5 regions over whic h a network of field sites was es tablished. In total, 15 crop species (corn, soybean, winter wheat, tobacco, sorghum, cotton, barley, peanuts, dry beans, potato, lettuce, turnip, and hay [alf alfa, clover, and fescue]), were studied. The first 12 of these 15 listed species were analyzed for the 1996 review and included 38 different cultivars studied under a variety of unique combin ations of sites, water regimes, and exposure conditions, producing a total of 54 separate cas es. Figure 7-13 uses the regression equations for each of the 54 cases to graph predicted relati ve yield loss at various exposure levels in terms of a 12-hr W126 (Figures 7E-1, 2, 3 present similar figures w ith the 8-hr average and 12-hr SUM06 forms).

7-42Figures 7-14 (a-d) show composite graphs fo r some individual crops from NCLAN and the variations in sensitivity between important cr ops. According to the most recent USDA National Agricultural Statistical Survey (NASS) da ta, the 12 species analyzed in the last O 3 NAAQS review account for greater than 70% of principal cr ops acreage planted in the U.S. in 2004. 1 Corn, soybean, and winter wheat alone acc ounted for 62% of 2004 principal crop acreage planted. For the economic analysis described in section 7.6.2.4, a reduced list of 9 species (69% of 2004 principal crops) were incl uded (e.g., cotton, field corn, gr ain sorghum, peanut, soybean, winter wheat, lettuce, kidney bean, potato), w ith tobacco, turnip and barley not evaluated. Since the NCLAN studies were performed during the years 1980 to 1988, there is some uncertainty whether the crop cultiv ars tested in NCLAN are representative of crops grown today. In general, new crop varieties are not specifically bred for O 3 tolerance and the cultivars used today were bred from the same very narrow genetic stock available in the 1980’s. Thus, it is not expected that there would be much difference in O 3 tolerance between cultivars used today and
when the NCLAN studies were done. Since the last review, there has been no evidence that crops are becoming more tolerant of O 3 (U.S. EPA, 2006). For cotton, some newer varieties
have been found to have higher yield loss due to O 3 compared to older va rieties (Olszyk et al., 1993, Grantz and McCool, 1992). In a meta-analysi s of 53 studies, Morgan et al. (2003) found
consistent deleterious effects of O 3 exposures on soybean from studies published between 1973 and 2001. Further, early results from the SoyFACE experiment in Illinois i ndicate a lack of any apparent difference in the O 3 tolerance of old and recent cultivars of soybean in a study of 22 soybean varieties (L ong et al., 2002).

1 Principal crops as defined by the USDA include corn, sorghum, oats, barley, winter wheat, rye, Durum wheat, other spring wheat, rice, soybeans, peanuts, sunflower, cotton, dry edible beans, potatoes, sugar beets, canola, proso millet, hay, tobacco, and sugarcane. Acreage data for the principal crops were taken from the USDA NASS 2005 Acreage Report ( http://usda.mannlib.cornell.edu/reports /nassr/field/pcp-bba/acrg0605.pdf ).

7-43Figure 7-13. Median crop yield loss from NCLAN crops characterized with the 12-hr W126

12-hr W126 (ppm-hr)Predicted Relative Yield Loss (%)

0 10 20 30 40 50 60 70 80 90 100

10 20 30 40 50 60 a. 12-hr W126

75th Percentile

50th Percentile

25th Percentile

Distribution of yield loss predictions from Weibull exposure-response models that relate yield to O 3 exposure characterized with the 12-hr W126 statistic using data from 31 crop studies from National Crop Loss Assessment Network (NCLAN). Separa te regressions were calculated for studies with multiple harvests or cultivars, resulting in a total of 54 individual equations from the 31 NCLAN studies. Each equation was used to calculate the predicted relative yield or biomass loss at a 12-hr W126 of 10, 20, 30, 40, 50, and 60 ppm-hr, and the distributions of the resulting loss were plotted. The solid line represents the 50th percentile. Source: U.S. EPA, 1996a; Lee and Hogsett

1995.

7-447-45 Figure 7-14 (A-D). Median soybean (A), wheat (B), cotton (C) and corn (D) yield loss from NCLAN crops charac terized with the 12-hr W126

Distribution of yield loss predictions from Weibull exposure-response models that relate yield to O 3 exposure characterized with the 12-hr W126 statistic using data from 22 soybean, 7 wheat, 9 cotton and 2 corn studies from National Crop Loss Assessment Network (NCLAN). Separate regressions were calculated for studies with multiple harvests or cultivars. Each equation was used to calculate the predicted relative yield loss at a 12-hr W126 of 10, 20, 30, 40, 50, and 60 ppm-hr, and the distributions of the resulting loss were plotted. Source: U. S. EPA, 1996a; Lee and Hogsett 1995. 12-hr W126 (ppm-hr)Predicted Relative Yield Loss (%)

0 10 20 30 40 50 60 70 80 90 100

10 20 30 40 50 60 B. Wheat 75th Percentile

50th Percentile

25th Percentile

12-hr W126 (ppm-hr)Predicted Relative Yield Loss (%)

0 10 20 30 40 50 60 70 80 90 100

10 20 30 40 50 60 A. Soybean

75th Percentile

50th Percentile

25th Percentile

12-hr W126 (ppm-hr)Predicted Relative Yield Loss (%)

0 10 20 30 40 50 60 70 80 90 100

10 20 30 40 50 60 D. Corn

12-hr W126 (ppm-hr)Predicted Relative Yield Loss (%)

0 10 20 30 40 50 60 70 80 90 100

10 20 30 40 50 60 C. Cotton

75th Percentile

50th Percentile

25th Percentile7.6.2.3 Considerations for Exposures at Crop Canopy Height An important consideration when predicting crop yield and/or tree seedling biomass loss using monitored O 3 exposure levels is the potential posit ive exposure bias associated with the height at which the measurement is taken. Ambient monitor inlets are typically at heights of 3 to 5 meters, and thus are located in the inner part of the plan etary boundary layer (U.S. EPA, 2005b). It is well known that within this layer O 3 reacts with vegeta tion, other surfaces and volatile compounds and can create a ve rtical gradient of decreasing O 3 concentration from the inlet height of the monitors to the canopies of short ve getation. The magnitude of the gradient is determined in large part by the intensity of turb ulent mixing in the surface layer. During daytime hours, the vertical O 3 gradient is relatively small becau se turbulent mixing maintains the
downward flux of O 3 . For example, Horvath et al. ( 1995) calculated a 7% decrease in O 3 going from a height of 4 meters down to 0.5 meters above the surface during unstable (or turbulent) conditions in a study over low vegetation in Hungary [see section AX3.3.2. of the 2006 CD (U.S. EPA, 2006)]. This is compared to a 20% decr ease during stable conditio ns, which usually occur during the night. The average de crease for all times measured was 10%. The daytime versus nighttime bias is an important distinction since the assessments outlined below rely heavily on daytime metrics, such as the12-hr SUM06 and W126. Thus, staff selected 10% as a daytime downward adjustment factor to apply to hourly monitor-derived exposures (including interpolated values) prior to estimating crop yi eld and tree seedling biomass loss values. We consider this 10% adjustment at the upper-end of the differences between the monitor height and top of the canopy of low vege tation in the daytime. Staff recognizes that a 10% adjustment to hourly monitoring data across the country is a very simple method to deal with a co mplicated issue. The exchange of O 3 between the atmosphere and vegetation is controlled by complex interactions of meteorological and biological processes. Ideally one should accoun t for the exact height of each monitor, canopy roughness for each vegetation type and the seasonal and diurnal nature of turbulence. This was not possible in our analyses. To bound the unc ertainty associated with applying a 10% adjustment to all monitors and short canopies, staff performed a sensi tivity analysis by also calculating crop and tree seedling assessments without an adjustment. Staff agrees with CASAC comments that these calculations will provide a bracket of responses within which the reality probably lies for the true exposure of O 3 to short vegetation (He nderson, 2006c). For brevity, staff has presented the 10% adjust ed figures in the main body of the Staff Paper and have placed companion figures without the 10% adjustment in the Appendices 7-G and 7-H. However, both
sets of results are disc ussed in this chapter.

7-46The inclusion of a 10% hourly adjustment had a substantial effect on the predicted 12-hr SUM06 and W126 exposures. Reducing each hourly value by 10% over the entire interpolated surface resulted in an average reduction of th e 3-month 12-hr SUM06 by 53% and an average
reduction of 42% in the 3-month 12-hr W126. Th ese large reductions in the SUM06 and W126 exposures are most likely a result of many mon itored hourly concentratio ns occurring near the SUM06 threshold and the inflection point fo r W126 (approximately 0.06 ppm). When these “mid-level” hourly O 3 values are reduced by 10%, many fall below 0.06 ppm, decreasing the amount of hourly values counted in (SUM06) or contributing to (W126) these metrics. Given the somewhat lesser impact of the 10% adjustment on exposures using the W126
and the lack of evidence for a biological threshold for effects at 0.06 ppm, staff considered the W126 index form more appropriate for conducting the crop yield and tree seedling biomass loss risk assessment. Other information that supports this decision includes: 1) studies that document effects on crops and other sensitive vegetation at O 3 concentrations below 0.06 ppm [e.g., exposures as low as a 0.04 ppm 7-hr seasonal aver age (U.S. EPA, 2006)]; and 2) the high degree
of correlation between both form s when describing ambient exposur es (see Figure 7-4) and their similar predictive power of NCLAN crop data results in retrospectiv e analyses (Lee et al., 1989; U.S. EPA, 1996a, 2006).

7.6.2.4 Quantifiable Risk of Yield Loss In Select Commodity, Fruit and Vegetable Crops The 2001 county-level crop planting data were obtained for the 9 commodity crops (corn, soybean, winter wheat, sorghum, cotton, peanuts, kidney bean, potato & lettuce) from USDANASS (National Agricultural Statistics Service; http://www.usda.gov/nass ). The appropriate NCLAN C-R functions (available in the 12-hr W126 format) for each of the nine commodity crops were identified from the analysis done for the 1996 Staff Paper (U.S. EPA 1996b, Table 7F-1). The C-R functions for six fruit and vegetable species (tomatoes-processing, grapes, onions, rice, cantaloupes, Valencia oranges) were identified from the 1996 California fruit and vegetable analysis (Table 7F-2). Staff notes that fruit and vegetable studies were not part of the NCLAN program and C-R functions were available only in terms of seasonal 7 hr or 12-hr mean
index. This index form is considered less e ffective in predicting pl ant response for a given change in air quality than the cumulative form us ed with other crops. Therefore, staff considers the fruit and vegetable C-R functions more uncer tain than those for co mmodity crops. Staff combined the C-R functions with the crop planting information and with projections of 2001 O 3 exposure based on a 12-hr W126 calculated for the 3 months prior to the harvest date for each commodity crop and the appropriate growing season 7-hr or 12-hr average used for some fruits and vegetables. Calendar periods used for comp uting W126, 7-hr and 12-hr exposure statistics,

7-47Some of the results of this risk assessment are presented in Appendix 7F in Table 7F-4. This table depicts the maximum county-level re lative change in crop yi eld loss under air quality scenarios of just meeting various alternative standard options under c onsideration using the median C-R functions. Maps of predicted yield loss for selected major crops are presented in Appendix 7G. Figure 7-15 shows a map of predic ted yield loss for soybean from 2001 using the 10% adjusted “as is” estimated O 3 exposure scenario. Soybean is predicted to have the largest yield loss in southwestern Pennsyl vania, southern New Jersey and east Texas. However, these areas are not places of high soybean production. In a high soybean producing state, such as Illinois, yield loss was predicted to reach a ma ximum range of 1-2% with a 10% adjusted O 3 exposure (Figure 7-15) and 3-4% without a 10% adjusted O 3 exposure (Figure 7G-1 in Appendix 7G). Corn, another major commodity crop, was not predicted to have any loss in 2001. This is
because the two corn cultivars studie d in NCLAN were not sensitive to O 3 . In contrast, cotton, a more sensitive crop, had predicted yield loss ab ove 10% in southern Ca lifornia (see Appendix 7G, Figures 7G-3 & 4). are based on the harvest date and are done on a st ate-specific basis. This allows for geographic
variation and better reflects actual O 3 exposure during the true growi ng period of the crop so that calculated expected yield change for each crop, fruit and vegetable is specific to where they were planted (Abt, 2007).

7-48Figure 7-15. Estimated soybean yield loss based on interpolated 2001 3-month 12-hr W126 with a 10% downward adjustmentof hourly O3concentrations.7-497.6.2.5 Economic Benefits Assessment – AGSIM This section presents results of the quanti tative economic benefits analysis associated with just meeting alternate sta ndards. Adequate data are currently available to assess economic benefits for 9 of the commodity crops studied in the NCLAN pr oject and 6 fruit and vegetable species. Fruits and vegetables were evaluate d in the 1996 review using a separate regional benefits model separate from the national co mmodity crop model (U.S. EPA 1996b). This was due to the fact that only regiona l planting data were available at the time for those fruits and vegetables. In the current bene fits assessment, both commodity cr ops and fruits and vegetables were evaluated together in the same national scale model. Fruit and vegetables are a large part of the U.S. agricultural sector and ma y be especially susceptible to O 3 pollution because much of the production is located in the San Joaquin Vall ey region of California, which has very high
levels of O 3 exposure (CEPA, 2005). Because 6 of fruits and vegetables were not a part of the NCLAN program and the uncertainties inherent in those experiments are less well known, information on fruits and vegetables is presented se parately in this document. Nonetheless, fruits and vegetables are large portion of the U.S. agricultural economy. For example, in 2004, cash
income from California fruit and nut production was worth more than 9.6 billion dollars and over 7.2 billion dollars for vegetabl e crops (California Agricult ural Resource Directory, 2005, http://www.cdfa.ca.gov/). The Agriculture Simulation Model (AGSIM ) (Taylor, 1994; Taylor, 1993) has been utilized recently in ma ny major policy evaluations. 2 AGSIM is an econometric-simulation model used to calculate agricultu ral benefits of changes in O 3 exposure and is based on a large set of statistically estimated demand and suppl y equations for agricultural commodities produced in the U.S. A number of updates to AGSIM were performed before running this analysis: (1) an update of the commodity data for 2001, (2) inco rporation of the most recent version of the official USDA baseline model, (3) an econometri c component added to AGSIM to compute total farm program payments for different levels of farm program parameters, and (4) a farm payment program component was added to the economic su rplus module. The AGSIM model was run to provide benefit estimates for nine major commod ity crops (soybeans, corn, winter wheat, cotton, peanuts, sorghum, potato, lettuce, kidney bean) a nd six fruits and vegetables mainly grown in California (tomatoes-processing, grapes, onions, rice, cantaloupes, Valencia oranges). As

2 For example, AGSIM© has been used in EPA’s prospective study of the benefits derived from the Clean Air Act Amendments of 1990 required by section 812-B of the Clean Air Act, non-road, land-based diesel engine rule, and proposed Clear Skies legislation.

7-50described earlier, hourly O 3 exposures were adjusted downw ard by 10% before calculating the W126, 7-hr or 12-hr exposure metrics. Percent relative yield losses (PRYL) calcula ted as the change in yield occurring between just meeting ‘as is’ air quality and various altern ative standard scenarios were the relevant input parameters to the AGSIM model. The AGSIM model predicted acreage, production, supply and price parameters for each crop for each year, as well as yield-per-har vested acre, based on calculated new yield-per-planted ac re values, as well as on lagged price data, ending stocks from the previous year and other variables. From these results and demand relationships embedded in the model, AGSIM calculated the utilization of each crop (i.e., exports, feed use, other domestic use, etc), as well as change in consumer surplu s, net crop income, defici ency payments and other government support payments. Total undiscounted economic surplus was calculated as the crop income plus consumer surplus. For more de tail on the AGSIM model see Appendix I of the Environmental TSD (Abt, 2007). The AGSIM mode l was run for 14 years for each scenario in order for the model parameters to adjust to the initial change in yield. Annual changes in total undiscounted economic surplus were calculated for each of the 14 years. The annual averages for the 14 years are reported in Tables 7-3A-B. The results from applying the AGSIM model to determine commodity crop and fruit and vegetable benefits based on meeting the level of the current 8-hr average standard and five alternative standards are presented in Tables 7-3A-B . Note that Table 7-3A presents results with the 10% downward hourly adjustment and Table 7- 3B presents results w ithout the adjustment. In summary, this analysis estimated a range of benefits using both the available minimum and maximum yield loss equations for each crop. Re sults are presented in annual 2000 dollars for the commodity crops, fruits and vegetables and tota l agricultural sector. Overall, benefits from the fruit and vegetable species in this analysis accounted for a re latively large porti on of the total agricultural benefits compared with the commodity crops. This is likely because many of the fruits and vegetables are grown in parts of California with high O 3 exposures and any rolling back of air quality produced greater changes in O 3 levels, resulting in hi gher changes in yield. All of the alternative standards analyzed showed positive incremental benefits greater than those associated with just meeting the level of the current 8-hr average sta ndard. Including a 10% downward adjustment the hourly monitoring did not have a large effect on the overall benefits calculated for each standard. Not surprisingl y, not adjusting the hour ly monitoring data downward resulted in slightly hi gher benefits. Meeting the SUM 06 of 25 ppm-hr proposed in the last review and the approximate equivale nt W126 of 21 ppm-hr produced benefits of approximately $140-$260 million for the total agricult ural sector. Of all the scenarios, W126 of 13 ppm-hr, SUM06 of 15 ppm-hr and 8-hr averag e of 0.07 ppm had the largest economic benefit. Meeting the alternative W126 of 13 ppm-hr and approximate e quivalent of SUM06 of 15 ppm-hr

7-51produced benefits of approximate ly $290-$630 million for the total agricultural sector. It is important to note that these resu lts represent a macro-analysis of the U.S. agricultural economy. Farmers in areas that have higher O 3 levels are more adversely affected than farmers that are in
areas with low O 3 levels. These important effects are diffi cult to quantify in a macro-analysis. The current CD reports very few new st udies conducted on the economic effect of O 3 on U.S. agriculture (U.S. EPA, 2006). A study by Murphy et al. (1999) confirmed the general magnitude of economic effects reported by two key studies performed a decade earlier (Adams, 1986; Adams et al., 1985). Specifi cally, Murphy et al. (1999) evalua ted benefits to eight major crops associated with several scenarios con cerning the reduction or elimination of O 3 precursor emissions from motor vehicles in the U.S. Their analysis reported a $2.8 to 5.8 billion (1990 dollars) benefit from complete elimination of O 3 exposures from all sources, i.e., ambient O 3 reduced to a background level assumed to be 0.025 to 0.027 ppm. In comparison, AGSIM calculates $300 million to 2.5 billion (2000 dollars ) in economic benefit for 9 major commodity crops when O 3 levels are reduced to near background. These AGSIM results are without any downward adjustment to the O 3 monitoring data and without s ubtracting out farm payments. With a 10% adjustment and subtracting farm payments, AGSIM calculates substantially lower benefits ($200-800 million) for the same 9 majo r commodity crops. The Murphy et al. (1999) analysis and the current AGSIM analysis are quite difficult to compare for many reasons: different economic models, differe nt air quality years, different treatment of government farm payment programs, dollar value un adjusted for inflation, different assumptions, etc. However, these comparisons point out that initial assumptions about O 3 exposure and crop payments have large implications when calculating agricultural benefits for reducing O 3 to background levels.

7.6.2.6 Uncertainties In the Crop Risk and Benefit Analyses The crop risk assessment utilized the C-R relationships developed in OTC experiments performed between 1980 and1988 in the NCLAN program and in other experiments done on fruits and vegetables. As disc ussed earlier, fruit and vegetable studies were not part of the NCLAN program and C-R functions were availabl e only in terms of a seasonal 7-hr or 12-hr
mean index. This mean index form is considered less effective in predic ting plant response for a given change in air quality than the cumulative form used with other crops. Two of the uncertainties using the OTC C-R functions in th e crop risk assessment are chamber effects (see section 7.6.2.1) and sensitivity of current crops (see secti on 7.6.2.2). Staff qualitatively addressed these uncertainties citing studies with r ecent cultivars and studies not using chambers. However, it was not possible to perform a quan titative assessment of these uncertainties. Therefore, despite support in th e scientific lite rature for the magnitude of yield effects of O 3 exposure on crops from OTCs, st aff cannot quantify how these uncertainties would affect

7-52estimated crop risks and benefits. Staff notes that the predicted yield losses calculated from the OTC studies represent losses for crops that were not being affected by othe r stressors. Stressors such as drought may decrease the yield response to O 3 exposure while insect or disease damage to crops may be exacerbated by O 3 exposure. An additional source of uncertainty not desc ribed or accounted for in the last review is that associated with the pr esence of a decreasing O 3 gradient from the height of the monitor probe down to the canopy heights for most crops. The presence of this gradient makes less certain the predictions of current crop exposures and the associated yield losses based on ambient
monitor data. Staff selected a 10% reduction fact or to represent the maximum gradient believed to occur for daylight hours. However, recogniz ing that the actual dow nward adjustment value varies depending on interactions between numerous plant and site-specific f actors, staff chose to present estimates of yield loss for each crop as a range, with non-adjusted and 10%-adjusted air quality as the upper and lower bounds (see section 7.6.2.3 for a detailed discussion). It is important to restate the uncertaintie s associated with the results of the AGSIM economic analysis presented in section 7.6.2.5. Uncertainties are in troduced by: (1) the interpolation of air quality monito ring data to estimate 2001 national O 3 exposures; (2) the use of
C-R functions from OTC studies to estimate relative yield losses from 2001 exposures; (3) the use of a quadratic rollback method to project the "j ust meet" air quality scen arios without a direct
link to an emissions control strate gy; and (4) the inherent uncertainties associated with use of an economic model such as AGSIM. It is also import ant to note that the rang e of results from this analysis represents impacts associated only w ith available NCLAN experimental data and a limited number of fruits and vegetable studies. Not all crops have been subjected to exposureresponse experiments and effects on those crop s would be missed. Despite the amount of uncertainty, staff concludes that this analysis provides useful insights for comparing the relative
benefits obtained as a result of meeti ng alternative regulat ory scenarios.

7-53Table 7-3 A-B. Agricultural model results wi th (A) and without (B) a 10% adjustment of hourly O 3 exposures.

A. Average Annual Changes in Total Undisc ounted Economic Surplus for the Current 8hr Standard (0.08) and Altern ative Standards (millions $; 2000)

Standard Commodity Crops Fruits & Vegetables Total Ag.

0.08 4 th -highest $10 - 20 $60 - 80 $70 - 100

0.07 4 th -highest $50 - 200 $310 - 360 $360 - 560

W126 = 21 $10 - 40 $130 - 140 $140 - 180

W126 =13 $30 - 140 $260 - 300 $290 - 440

SUM06 = 25 $10 - 50 $160 - 180 $170 - 230

SUM06 = 15 $60 - 200 $290 - 330 $350 - 530

B. Average Annual Changes in Total Undisc ounted Economic Surplus for the Current 8hr Standard (0.08) and Altern ative Standards (millions $; 2000)

Standard Commodity Crops Fruits & Vegetables Total Ag.

0.08 4 th -highest $10 - 30 $70 - 80 $80 - 110

0.07 4 th -highest $70 - 280 $350 - 410 $420 - 690

W126 = 21 $20 – 40 $140 - 160 $160 - 200

W126 =13 $60 - 190 $280 - 340 $340 - 530

SUM06 = 25 $20 - 60 $180 - 200 $200 - 260

SUM06 = 15 $70 - 260 $320 - 370 $390 - 630

7-547.6.3 Tree Risk Assessments In the last review (U.S. EPA, 1996b ), analyses of the effects of O 3 on trees were limited to 11 tree species for which C-R functions for the seedling growth stage had been developed from OTC studies conducted by the National Hea lth and Environmental Effects Research Lab, Western Ecology Division (NHEER L-WED). Figure 7-16A uses the regression equations for each of the 26 studies (49 cases) to graph predicte d relative yield loss at various exposure levels in terms of a 12-hr W126. Figures 7-16B-C show composite graphs for the intensively studied quaking aspen and ponderosa pine. Work done sin ce the 1996 review at the AspenFACE site in Wisconsin (see section 7.6.2.1) on quaking aspen ha s confirmed the detrimental effects of O 3 exposure on tree growth in a field study without chambers (Karnosky et al., 2005). Since the 1996 review, only a few new studies have develo ped C-R functions for additional tree seedling species (U.S. EPA, 2006). One such study of eastern cottonwood ( Populus deltoides ) saplings
was done without chambers or O 3 FACE-type fumigation (Gre gg et al., 2003). Eastern cottonwood is a fast growing tree that is important ecologically along streams and commercially for pulpwood, manufacturing furniture and a possi ble source for energy biomass (Burns and Hankola, 1990). Gregg et al. ( 2003) found that the cottonwood sa plings grown in urban New York City grew faster than saplings grown in more rural areas where O 3 was higher. The secondary nature of the reactions of O 3 formation and NOx titration reactions within the city center resulted in significantly higher cumulative O 3 exposures in the rural sites. After carefully considering many factors, they c oncluded the major explanation for the difference in growth was the gradient of O 3 exposure between urban and rural sites. This explan ation was also confirmed with an OTC study (Gregg et al., 2003). Figur e 7-17 shows the biomass growth of cottonwood plotted against the monitored 12-hr W126 at the s ites the trees were plante d (Gregg et al., 2003). Staff notes that the responses of natural populations of cottonwood to O 3 may vary because of precipitation patterns and differences in native soils. The Gregg et al. (2003) study is important
because it demonstrated th at growth effects of O 3 exposure could be documented in field without chambers or fumigation and the growth decreases were as great as to seen in previous OTC studies. The evidence from the AspenFACE results and Gregg et al. (200 3) provide support for
the continued use of NHEER-WED OTC studies to esti mate risk to seedlings in the U.S. Section 7.6.3.1 describes how staff updated the tree seedling risk analysis performed in the last review. Section 7.6.3.2 discusses the approach for assessing O 3 effects on vegetation in natural settings using visible foliar in jury data. Section 7.6.3.3 discusse s the analysis and results for modeling O 3 impacts on mature trees in the Eastern a nd Western U.S. The tree and/or forest analyses outlined below will enable staff to begin to assess important long-term effects of various secondary standard levels on forest ecosyst em health and services.

7-557-56 Figure 7-16. Median tree seedling biomass loss for all 49 cases (A), quaking aspen (B), and ponderosa pine (C) characterized with the 12-hr W126

12-hr W126 (ppm-hr)Predicted Relative Biomass Loss (%)

0 10 20 30 40 50 60 70 80 90 100

10 20 30 40 50 60 A. All seedlings studied

75th Percentile

50th Percentile

25th Percentile

12-hr W126 (ppm-hr)Predicted Relative Biomass Loss (%)

0 10 20 30 40 50 60 70 80 90 100

10 20 30 40 50 60 C. Ponderosa Pine

75th Percentile 50th Percentile
25th Percentile 12-hr W126 (ppm-hr)Predicted Relative Biomass Loss (%)

0 10 20 30 40 50 60 70 80 90 100

10 20 30 40 50 60 B. Quaking Aspen

75th Percentile

50th Percentile

25th PercentileFigure 7-17. Cottonwood ( Populus deltoides ) shoot biomass (mean ± s.e.) at urban (filled) and rural (open) sites in the vicinity of New York City versus ambient O 3 exposure (growing period 12-hr W126, July 7 – Sept. 20). Squares, circles and triangles represent responses in 1992, 1993 and 1994, respectively. Cottonwood saplings were grown in potting soil under well watered conditions. (Modified from Gregg et al., 2003)

y = -6.1902x + 87.149 R 2 = 0.8622

0 10 20 30 40 50 60 70 80 90

0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 Ozone Exposure (W126, ppm-hrs)Biomass (g) y = -6.1902x + 87.149 R 2 = 0.8622

0 10 20 30 40 50 60 70 80 90

0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 Ozone Exposure (W126, ppm-hrs)Biomass (g)

7-57Figure 7-18 shows an example of the quaking aspen seedling biomass loss with an hourly

O 3 exposures adjusted down by 10%. Figure H-1 in Appendix H shows the quaking aspen without the 10% hourly adjustment . The quaking aspen maps show significant variability in projected seedling biomass loss across its range for 2001. Quaki ng aspen seedling biomass loss (with the10% adjustment) was projected to be greater than 4% over much of its geographic range, though it can reach as high as 12% in some areas. In Appendix 7H, there are additional maps of ponderosa pine and black cherry along with maps of seedling biomass loss with and without a 10% adjustment of the monitoring data. Further, in Chapter 5 of the Environmental TSD, a series of maps are presented showing seed ling biomass gain when various standard levels are met. These biomass gain maps indicate th at substantial improvements in seedling growth may be achieved when the alternative sta ndards are met, especi ally the 0.07 ppm 4 th -highest max., SUM06 of 15 ppm-hr and W126 of 13 ppm-hr. It should be noted that the species mapped are generally sensitive and they are also important tree species in ecosystems across vast areas of the U.S. Though each map shows the geographical range for a species, it does not indicate that an individual of that species will be found at ev ery point within its range . It should also be recognized that the production of these maps incorporates several separate sources of uncertainty, beginning with the C-R functions produced for seedlings in OTCs to the uncertainties associated with the inputs used to generate the POES. Furthermore, percent biomass loss in tree seedlings is not intended to be a surrogate for expected biomass loss in mature trees of the same speci es (see section 7.6.3.3 for modeli ng of mature tree growth). Studies indicate that mature trees can be more or less sensitive than seedlings depending on the species. Further, seedling biomass loss cannot be considered comparable to percent yield loss in agricultural crops. This is because a small biom ass loss per year in a pe rennial tree species, if compounded over multiple years of exposure could have a large effect on the growth of that tree, while yield loss in annual crops is only affected by the O 3 exposure for that year. In summary, In a process similar to that used for cr ops above (7.6.2.4), C-R functions for biomass loss for a subset of seedling tree species taken from the CD (Table 7F-3) and information on tree growing regions derived from the U.S. Department of Agriculture's Atlas of United States Trees (Little, 1971) were combined with projections of air quality based on 2001 POES, to produce estimated biomass loss for each of the seedling tree species individually. Some of the results for the highest areas of risk to tree seedlings are presented in Table 7F-5 in Appendix 7F. In addition, maps depicting these re sults for selected tree seedling species are found in Appendix

7H. 7.6.3.1 Quantifiable Risk of Biomass Lo ss In Select Tree Seedling Species

7-58Figure 7-18. Estimated aspen seedling annual biomass lossbased on interpolated 2001 maximum 3-month 12-hr W126 with a10% downward adjustment of hourly O3concentrations. This map indicates the geographic range for quakingaspen (Populus tremoloides), but it does not necessarily indicate thataspen will be found at every point within itsrange.7-59this analysis indicates that current air qua lity can produce significant seedling biomass loss in the areas which those trees grow. Meeting the level of alternative standards is expected to improve biomass growth in the seedlings analyzed.

7.6.3.2 Visible Foliar Injury Incidence The use of sensitive plants as biological in dicators to detect phytotoxic levels of O 3 is a longstanding and effective methodology (Chappelka and Samuelson, 1998; Manning and Krupa, 1992) . Some well defined bioindicators for ambient O 3 include blackberry, black cherry, green ash, milkweed, quaking aspen, sassafras, yello w poplar, and white ash. Each of these bioindicators exhibits typical O 3 injury symptoms when exposed under appropriate conditions. These symptoms are considered diagnostic as th ey have been verified in exposure-response studies under experimental conditio ns. Typical visible injury symp toms on broad leaved plants include: 1) acute exposure (pigmented lesions (stippling), flecking, su rface bleaching, and/or bifacial necrosis); 2) chroni c exposure (pigmentation (bronz ing), chlorosis or premature senescence). Typical visible injury symptoms for conifers include: 1) chlorotic banding or tipburn (acute exposure); 2) flecking or chlo rotic mottling, premature senescence of needles (chronic exposure). Though common patterns of injury develop within a species, these foliar lesions can vary considerably between and w ithin taxonomic groups. Furthermore, the degree and extent of visible foliar injury development va ries from year to year and site to site, even among co-members of a population exposed to similar O 3 levels, due to the influence of cooccurring environmental and genetic factors. It is important to not e that the visible foliar injury occurs only when sensitive plan ts are exposed to elevated O 3 concentrations in a predisposing environment. Thus, great care must be taken wh en assessing the response of bioindicators to
ambient O 3 (Flagler, 1998). The Unites States Forest Service (USFS) th rough the Forest Health Monitoring Program (FHM) (1990 - 2001) and currently the Forest Inventory and Anal ysis (FIA) Program has been collecting data regarding the inci dence and severity of visible foliar injury on a variety of O 3 sensitive plant species throughout the U.S. (Coul ston et al., 2003, 2004; Smith et al., 2003). The plots where these data are taken are known as bi osites. These biosites are located throughout the country and analysis of visible foliar injury within these sites follows a set of established protocols (for more details see http://fiaozone .net/). Since the conclusion of the 1996 NAAQS review, the FIA monitoring program network and database has cont inued to expand. The visible foliar injury indicator has been id entified as a means to track O 3 exposure stress trends in the nation’s natural plant communities as highlighted in EPA’s most recent Report on the Environment (U.S. EPA, 2003a; http://www.epa.gov/i ndicators/roe). EPA staff also considers it important to assess the degree to which O 3 -induced visible foliar injury observed in situ
,

7-60In an attempt to assess how meeting various O 3 standard levels affected the incidence of visible foliar injury, staff matched up county-level O 3 monitoring data with counties that had US Forest Service biosites. In counties containing multiple O 3 monitors, staff used the monitor measuring the highest O 3 to characterize county air quality. Because visible foliar injury symptoms reflect the O 3 stress of the year in which they are observed, staff looked at yearly Due to a congressional requirement that the USFS protect landowner privacy, FIA cannot publicize the exact locations of the biosites. As a result, all data in this analysis are reported on a county-level. County-level visi ble foliar injury data were av ailable for the years 2001 to 2004 for all areas of the U.S. except the Mountain West region. However, according to the FIA staff,

no O 3 injury was reported at any site in that re gion. Figure 7-19, shows that the incidence of visible foliar injury in 2001 was widespread acro ss the eastern and western U.S. The 2001 data are indicative of the incidence of visible foliar injury in th e years 2001 to 2004. (see Appendix 7I for 2002). This indicates that O 3 levels are above phytotoxic leve ls sufficient to cause adverse effects in natural plant populations in many areas. It is important to note that direct links
between O 3 induced visible foliar injury symptoms and other adverse effects (e.g., biomass loss), are not always found. However, in some cases, visible foliar symptoms have been correlated
with decreased ve getative growth (Karnosky et al., 1996; Peterson et al., 1987; Somers et al., 1998) and with impaired reproductive function (Black et al., 2000; Chappelka, 2002) . Though visible injury is a valuable indicator of the presence of phytotoxic concentrations of O 3 in ambient air it is not always a reli able indicator of damage or othe r injury endpoints. The lack of visible injury does not indicate a lack of phytotoxic concentrations of O 3 or a lack of non-visible

O 3 effects. The major confounding effect for O 3 induced visible foliar inju ry is the amount of soil moisture (local rainfall) available to a plant during the year that the visible foliar injury is being
assessed. This is because lack of soil moistu re decreases stomatal conductance of plants and, therefore, limits the amount of O 3 entering the leaf that can cause injury. Many researchers have shown that dry periods in local ar eas tend to decrease the inciden ce and severity of visible foliar injury caused by O 3 in plants measured by the USFS (Sm ith et al., 2002). Therefore, the incidence of visible foliar injury is no t always higher in years with higher O 3 , especially when there is drought in areas where visible foliar injury is assessed. corresponds with monitored O 3 air quality in recent years. In a collaborative effort with FIA staff, EPA staff conducted an analysis to comp are the incidence of vi sible foliar injury at different levels of air quality (e.g., the cu rrent standard and alternative levels under consideration) by county throughout the U.S. This analysis potentially provides a measure of the effectiveness and degree of protection provided by the current form/level of the secondary
standard for this welfare effect.

7-61Figure 7-19. 2001 County-level incidence of visible foliar injury in the eastern and western U.S. as measured by the US ForestService FIA program.7-62In summary, this analysis indicates that incidence of O 3 induced visible foliar injury is widespread across the eastern and western U.S. Visibl e foliar injury was observed in counties that are meeting the current level of the 8-hr standard and an alternat ive secondary standard option of a SUM06 of 25 ppm-hr proposed in 19 96. Lower standards in the 8-hr average and SUM06 forms would be expected to have lower incidences of visi ble foliar injury. However, the level of protection would depend he avily on local environmental variab le such as soil moisture. Finally, in the consensus workshop held on the secondary O 3 standard, researchers were in agreement that a 3 month 12-hr SUM06 value of 8 to 12 ppm-hr should be considered for protection from visible foliar injury to natu ral ecosystems (Heck and Cowling, 1997). The analysis above supports this recommendation that these levels would reduce the incidence of visible foliar injury to natural ecosystems. publicly available, staff was unable to determine how close the biosites within each county were
to the O 3 monitor selected to represent that county. Air quality was evaluated in terms of both the current 8-hr. average and 12-hr SUM06 forms, using a number of differ ent levels. Table 7-4 shows the percentage and number of counties with and without visible foliar injury at or below various standard levels for the 2001-2004 period. Because the FIA program reorganized the locations of biosites in 2002 and expanded th e number of biosites in 2003 and 2004, the total number of counties containing both an O 3 monitor and an FIA biosite changed each year and it is difficult to interpret changes in the number of counties in different categ ories between years. Therefore, staff found it more info rmative to present resu lts in terms of per cent of total counties with or without injury unde r different levels of air quality. First, this tabl e illustrates that visible foliar injury is occurring in areas that are meeting the current 8-hr average O 3 standard (0.084 ppm). Second, the table illustrates that the seco ndary standard option of a SUM06 of 25 ppm-hr proposed in 1996 did not appear to offer more pr otection from visible fo liar injury than the current 8-hr average standard form. By co mparison, the SUM06 of 15 ppm-hr and the 8-hr average of 0.074 ppm provided more protection ac ross all years than either the 0.084 ppm 8-hr average or SUM06 of 25 ppm-hr standards. At the 0.084 ppm, 8-hr aver age, the percent of counties showing injury ranged from 21% to 39%. Under a SUM06 of 25 ppm-hr, the percent of counties with injury was 26% to 49%. For the tw o lower air quality alternatives (0.074 ppm 8-hr average and SUM06 of 15 ppm-hr), values ranged from 12% injured to 30% and 35%, respectively. snapshots of county-level air quality da ta. Between 235 and 286 counties had EPA O 3 monitoring and at least one USFS FIA biosite surveyed for visibl e foliar injury in the years 2001 – 2004 (see Table 7-4). However, because the sp ecific locations of the USFS biosite are not

7-63Table 7-4. Percentage and number of counties with visible foliar injury (injured)and without injury (not injured) belowvarious standard levels for the years 2001-2004. Each county had an Omonitor and a USDA forest service FIAplot tracking visible foliar injury due to Oexposur33e.Year<0.084*(ppm)<0.074*(ppm)<SUM06 25(ppm-hr)<SUM06 15(ppm-hr)Total Counties withO3monitoring & FIAbiosites# of counties993613448injured39% (39)25% (9)49% (65)23% (11)2001not injured61% (60)75% (27)51% (69)77% (37)235# of counties894312959injured21% (19)12% (5)26% (33)12% (7)2002not injured79% (70)88% (38)74% (96)88% (52)270# of counties18561236135injured28% (52)11% (7)34% (81)25% (34)2003not injured72% (133)89% (54)66% (155)75% (101)285# of counties260159249220injured35% (91)30% (47)37% (91)35% (76)2004not injured65% (169)70% (112)63% (158)65% (144)2867-64*These standard levels represent the annual 4th-highest 8-hr maximum averageStaff collaborated with the EPA NHEERL- WED laboratory to use the TREGRO model to assess growth of Ponderosa pine ( Pinus ponderosa ) in the San Bernardino Mountains of California (Crestline) and th e growth of yellow poplar ( Liriodendron tulipifera ) and red maple ( Acer rubrum ) in the Appalachian mountains of Vi rginia and North Carolina, Shenandoah National Park (Big Meadows) and Linville Gorg e Wilderness Area (Cranberry), respectively. Total tree growth associated with ‘as is’ air qua lity, and air quality adjusted to just meet
alternative O 3 standards was assessed (Table 7-5). Ponde rosa pine is one of the most widely distributed pines in western North America, a major source of timber, important as wildlife TREGRO is a process-based, individual tree growth simulation model (Weinstein et al, 1991) and has been used to evaluate the effects of a variety of O 3 scenarios and linked with
concurrent climate data to account for O 3 and climate/meteorology interactions on several species of trees in different re gions of the U.S. (Tingey et al., 2001; Weinstein et al., 1991; Retzlaff et al., 2000; Laurence et al., 1993; Laurence et al., 2001; Weinstein et al., 2005). The model provides an analytical framework that accounts for the nonlinear relationship between O 3 exposure and response. Th e interactions between O 3 exposure, precipitation and temperature are integrated as they affect vegeta tion, thus providing an internal consistency for comparing effects in trees under different exposure scenarios a nd climatic conditions (see the Environmental Assessment TSD for more details on TREGRO). An earlier assessment of the effectiveness of national ambient air quality standa rds in place since the early 1970s took advantage of 40 years of air quality and climate data for the Crest line site in the San Be rnardino Mountains of
California to simulate Ponderosa pine growth over time with the improving air quality using TREGRO (Tingey et al., 2004). In the 1996 O 3 Staff Paper, evaluations of O 3 impacts on tree growth were limited to the seedling growth stage (U.S. EPA, 1996b). At th at time, robust C-R functions were available only for 11 tree seedlings developed from OTC data. Few studies had been done comparing seedling sensitivity to that of a mature tree of the same species. Recent experiments using the FACE methodology have been able to expose 3 tree species to O 3 beyond the seedling growth stage. However, this methodology has not yielded C-R functions at this time, due to the limited number of exposure regimes used. Findings from FACE publications, however, do show decreased biomass grow th under elevated O 3 in trees beyond the seedling stage (King et al., 2005). In order to better characterize the potential O 3 effects on mature tree growth, staff used a tree growth model (TREGRO) as a tool to evaluate the effect of changing O 3 air quality scenarios from just meeting alternative O 3 standards on the grow th of mature trees. 7.6.3.3 Modeled Mature Tree Growth Response: Eastern and Western Species Case Studies

7-651A rollback was not necessary for theCranberry site for the 0.08 ppm 4th-highest and SUM06 = 25 ppm-hrscenarios since air qualitywas at or below the levels of those scenarios.Table 7-5. Relative increase in total annual tree biomass growth, simulated withthe TREGRO model, if the level of thecurrent (0.08 ppm) and alternative standards are met.3The roll-back to a SUM06 of 25 ppm-hrwas a W126 of approximately 18 ppm-hr atCranberry, Big Meadows and Crestline.Speciesred maplered mapleyellow poplaryellow poplarponderosa pineSiteBig Meadows, VA(1993-1995)Cranberry, NC(1993-1995)Big Meadows, VA(1993-1995)Cranberry, NC(1993-1995)Crestline, CA(1995-2000)0.08 4th-highest0.41%no rollback10.03%no rollback18.63%0.07 1st-highest2.71%2.31%0.38%6.54%10.81%0.07 4th-highest2.24%1.38%0.34%3.91%n.a.2SUM06 = 2530.34%no rollback10.07%no rollback110.33%SUM06 = 1544.49%2.99%0.60%8.26%n.a.24The roll-back to a SUM06 of 15 ppm-hr was a W126 ofapproximately 13 ppm-hr atCranberry and Big Meadows7-662TREGRO was not run for ponderosa pine for the 0.07 ppm 4th-highest scenario.habitat, and valued for aesthetics (Burns and Honkala, 1990). Red maple is one of the most abundant species in the eastern U.S. and is im portant for its brilliant fall foliage and highly desirable wildlife browse food (Burns and Honka la, 1990). Yellow poplar is an abundant species in the southern Appalachian forest. It is 10% of the cove hardw ood stands in southern Appalachians which are widely viewed as some of the country’s most treasured forests because the protected, rich, moist set of conditions permit tr ees to grow the largest in the eastern U.S. The wood has high commercial value because of its versatility and as a substitute for increasingly scarce softwoods in furniture and framing construction. Yellow poplar is also valued as a honey tree, a source of wildlife food, and a shade tree for large areas (Burns and Honkala, 1990). At the western site, staff a nd NHEERL-WED scientists used Crestline, CA air quality and climate data from the years 1995 to 2000 to run TREGRO, while at the eastern sites, staff used Big Meadows, VA and Cranbe rry, NC air quality and climate data from the years 1993 to 1995. These three years were the only year s in the east with readily available O 3 and climate data that could be used in TREGRO. The years chosen to run the TREGRO at each site appear
to have annual O 3 exposures typical of the last 15 years (F igure 7-20). Air quality from each site and year was adjusted using th e quadratic roll-back method to ‘just meet’ the current 8-hr average secondary standard (0.084 ppm) , a 12-hr SUM06 of 25 ppm-hr, and 1 st highest max average of 0.07 ppm. Staff also tested the 4 th -highest 0.07 ppm level on the Cranberry and Big Meadows sites. For the ponderosa pine at Cres tline, TREGRO was run for “as is” and “just meet” air quality conditions in four 3 year increm ents to increase the accountability of climate variability and the annua l average biomass determined from these 4 simulations to yield an annual average biomass change over the 6 years of O 3 exposure. For the yellow poplar and red maple, two sites (Big Meadows, VA and Cra nberry, NC) were chosen to run TREGRO to increase the variability in climate since there were only 3 years of data available at each site. The differences between growth under “just m eet” and “as is” air quality conditions were compared to evaluate the effectiveness of th e current secondary sta ndard and alternative standards in protecting thes e three tree species. Results of the TREGRO simulations are pres ented in Table 7-5. Clearly, the greatest simulated growth benefits in the scenarios are se en in ponderosa pine at the Crestline site in California. As shown in Figure 7-20, O 3 levels are much higher at Crestline than the sites in the eastern US. Meeting the level of the current standard was s imulated to result in an 8.63% increase annual growth and a SUM06 of 25 pp m-hr is expected increase growth 10.33% in ponderosa pine. In the eastern si tes (Cranberry and Big Meadows), O 3 levels are much lower (Figure 7-20) and had less of an effect on the simulated growth of red maple and yellow poplar. In fact, the Cranberry, NC site was below the level of the current 8-hr av erage standard and the

7-67Figure 7-20. Historical O 3 data as measured in the 3-month 12-hr SUM06 and 4 th highest 8-hr metrics for the 3 sites used to r un the TREGRO model. For Big Meadows, VA and Cranberry, NC, climate and O 3 data from 1993 to 1995 was used to run TREGRO and for Crestline, CA, 1995 to 2000 was used. Missing data points in the top panel indicate incomplete data to calculate a SUM06. * indicates which years of data were used in the TREGRO model at each site.3-month 12hr SUM06 (ppm hrs-1)

0 20 40 60 80 100 120 Crestline, CA Big Meadows, VA Cranberry, NC

Year 1988 1990 1992 1994 1996 1998 2000 2002 20044th highest max. 8hr average (ppm)

0.06 0.08 0.10 0.12 0.14 0.16 0.18 0.20
Crestline, CA Big Meadows, VA Cranberry, NC proposed 1996 SUM06 standard

current 8hr standard

*

* * *

*

* *

*

* *

* *

* * * * *

* *

*

*

* * *

7-68SUM06 of 25 ppm-hr scenarios and, therefore, no benefits were ca lculated for those levels. At Big Meadows, VA, the current 8-hr average standa rd and SUM06 scenarios resulted in relatively small growth increases for yellow poplar (0.03 -0.07%) and red maple (0.34-0.41%). This was mostly because the Big Meadows site was clos e to meeting those leve ls in 1993-1995 (Figure 7- 20). Red maple was simulated to have a similar response (~2%) to the 0.07 ppm 1 st and 4 th

highest 8-hr max in Big Meadow s and Cranberry. For the same scenarios, yellow poplar had a very different response to O 3 reduction at Big Meadows (0.3 4-0.38%) compared to Cranberry (3.91-6.54%). The climate at Cranberry is much more ideal for yellow poplar than under the cool temperatures of Big Meadows, making it much more likely that its growth would be suppressed by O 3 and that, conversely, it would respond much more to O 3 reductions. Red maple has a much larger geogra phical distribution, so that the temperature differences between Big Meadows and Cranberry are less likely to affect the growth response. This phenomenon was
reflected in the simulations.
The effect of O 3 on an individual tree may be quite di fferent than the predicted effect on a forest stand after many years. Some research ers have used the ZELIG model, a forest stand simulator, to predict stand gr owth using growth rates of i ndividual species from TREGRO scenarios (Laurence et al., 2001; Weinstein et al., 2005). Small changes in growth of an individual tree over a short period of time have sometimes been simulated to have large changes in basal area as it develops over a long time period. For example, Weinstein et al. (2005) found a
simulated O 3 effect on an individual ponde rosa pine at Crestline to reduce growth by 6.7% in three years under normal precipita tion, yet stand basal area was cal culated to be reduced by 29% after 100 years. Similarly, Laurence et al. (2001) found individual yellow poplar in NC with an

O 3 induced growth loss of 1.7% which was then calculated to reduce basa l area by 14% after 100 years. This suggests that small effects on indivi dual tree growth may resu lt in substantial effects on forest stand growth after many years.

7.6.3.4 Uncertainties In the Tree Risk Analyses It should be recognized the seedling risk assessment incorporates several sources of uncertainty that have been previously discussed. Specifically, uncertainties associated with the development C-R functions using OTCs and uncerta inties associated with the inputs used to generate the POES (see sections 7.6.2.1 and 7.5.5) . As with crops, the potential differences between exposures measured above seedling canop ies and actual exposure at the top of the canopy is an important uncertainty. As explai ned in section 7.6.2.3, it is impossible to fully account for these potential differences throughout the U.S. Therefore, staff calculated risks using a 10% adjustment of hourly exposures and no adjustment of hourly exposures. These

7-69calculations provide a bracket of responses within which the real ity probably lies for the actual

O 3 exposures tree seedling canopies. The visible foliar injury risk assessment cont ains several sources of uncertainty. First, due to the major confounding effect of soil moisture (local rainfall) in determining the level of observed symptom expression, the in cidence and degree of visible foliar injury is not always higher in years with higher O 3 , especially when there is drought in areas where foliar injury is assessed. Second, the lack of visible injury does not indicate a lack of ph ytotoxic concentrations
of O 3 or a lack of non-visible O 3 -induced effects, since it is not always a reliable indicator of
other O 3 -related injury and damage endpoints. Finall y, due to the change in FIA protocols in 2002 and the unavailability of specific biosite loca tions, staff was unable to determine the degree to which county level monitored O 3 values reflect the actual O 3 exposure conditions at the
biosites within those counties.

As with every model, TREGRO has many kno wn and unknown sources of uncertainty. Because TREGRO only models indi vidual trees, the effects of co mpetition are not factored in. There is genetic variability within species so th at the values produced for an individual tree may not reflect the variability within the species as a whole. Only a few species have been parameterized in TREGRO. Due to the limited nu mber of species tested and included in this assessment, it is unclear to what degree these results apply to O 3 impacts on mature trees in general. For further discussion of uncertainties see Appendix J in the Environmental Assessment TSD (Abt, 2007).

7.7 QUALITATIVE RISK: ECOSYSTEM CONDITION, FUNCTION AND SERVICES Ecosystems are comprised of complex assemb lages of organisms that provide distinct ecological attributes, many of which may be adversely affected by O 3 (U.S. EPA, 2006). A new
effort has been initiated within the Agency to identify indicato rs of ecological condition whose responses can be clearly linked to changes in air quality and be used to track improvements in environmental protection attributable to e nvironmental program actions/implementation. Moreover, a recent critique of the secondary NAAQS review process published in the report by the National Academy of Sciences on Air Quality Management in the Un ited States (NRC, 2004) stated that “EPA’s current prac tice for setting secondary standa rds for most criteria pollutants does not appear to be sufficiently protective of sensitive crops and ecosystems...” This report made several specific recommendations fo r improving the secondary NAAQS process and concluded that “There is growi ng evidence that tighter standards to protect sensitive ecosystems
in the United States are neede d...” However, the vast majority of information regarding the
effects of O 3 involves the sensitivity of i ndividual species. Therefore, this section lays out some

7-70examples of our curren t understanding of how O 3 may be affecting ecosystems and identifies
areas of research needed to address this issue. An ecosystem is defined as comprising all of the organisms in a given area interacting with the physical environment, so that a flow of energy lead s to a clearly defined trophic structure, biotic diversity, and cycling of ma terials between living a nd nonliving parts (Odum, 1963). Individuals within a species and populati ons of species are the building blocks from which communities and ecosystems are constructed. Classes of natural ecosystems, e.g., tundra, wetland, deciduous forest, and conifer forest, ar e distinguished by thei r dominant vegetation forms. Ecosystem boundaries are delineated when an integral unit is formed by their physical and biological parts. Defined pathways for mate rial transport and cycling and for the flow of energy are contained within a given integrated unit. Each level of organization within an ecosystem has functional and structural characteristics. At the ecosystem level, functional characteristics include, but are not limited to, energy flow; nutrient, hydrologic, and biogeochemical cycling; a nd maintenance of food chains. The sum of the functions carried out by ecosy stem components provides many benefits to humankind, as in the case of forest ecosystems (Smith, 1992). Some of these benefits include food, fiber production, aesthetics, gene tic diversity, and energy exchange. A conceptual framework for discussing the effects of O 3 on ecosystems was developed by the EPA Science Advisory Board (Young and Sa nzone, 2002). Their six essential ecological attributes (EEAs) include lands cape condition, biotic conditio n, organism condition, ecological processes, hydrological and ge omorphological processes, and na tural disturbance regimes. Figure 7-21 outlines how common anthropoge nic stressors, including tropospheric O 3 , might affect the essential ecological attributes outlined by the SAB. There is evidence that tropospheric O 3 is an important stress or of ecosystems, with documented impacts on the biotic condition, ecological processes, and chemical/physical nature of natural ecosystems (U.S. EPA, 2006). Most of the effects on ecosystems must be inferred
from O 3 exposure to individual plants and proces ses that are scaled up through the ecosystem affecting processes such as ener gy and material flow, inter- and in traspecies competition, and net primary productivity (NPP). Thus, effects on indi vidual keystone species and their associated microflora and fauna, which have been shown experimentally, may cascade through the ecosystem to the landscape level. By affecting water balance, cold hardiness, tolerance to wind and by predisposing plants to insect and disease pests, O 3 may even impact the occurrence and impact of natural disturba nce (e.g., fire, erosion). Another approach to assessing O 3 effects on ecosystems is the identification and use of indicators. For example, the main indicators of phytotoxic O 3 exposures used for forest ecosystems are visible foliar injury (as described in section 7.6.3.2 above) and radial growth of

7-71Figure 7-21. Common anthropogenic stressors a nd the essential ecologi cal attributes they affect. Modified from Young and Sanzone (2002)

7-72trees. Systematic injury surveys demonstrate that foliar injury occurs on O 3 -sensitive species in many regions of the United States. However, th ere is not always a dire ct relationship between the severity of the visible foliar symptoms and gr owth. This essentially means it is difficult to quantify or characterize the degree which EEAs may be impacted when visible foliar injury is found in the field. Investigations of the relations hip between changes in ra dial growth of mature
trees and ambient O 3 , in combination with data from many controlled studies with seedlings, suggest that ambient O 3 is reducing the growth of mature trees in some locations. However, definitively attributing growth losses in the field to O 3 in a wide array of ecosystems is often difficult because of confounding factors with othe r pollutants, climate, insect damage and
disease. The CD (U.S. EPA, 2006) outli nes seven case studies where O 3 effects on ecosystems have either been documented or are suspected. However, in most cas es, only a few components in each of these ecosystems have been examined and characterized for O 3 effects and, therefore, the full extent of ecosystem changes in thes e example ecosystems is not fully understood. Clearly, there is a need for highl y integrated ecosystem studies th at specifically investigate the
effect of O 3 on ecosystem structure and function in orde r to fully determine the extent to which

O 3 is altering ecosystem services.

7.7.1 Evidence of Potential Ozone Altera tion of Ecosystem Structure and Function

The seven case studies listed in the 2006 CD demonstrate the potential for O 3 to alter ecosystem structure and function (U.S. EPA, 2006 ). The oldest and clearest example involves the San Bernardino Mountain forest ecosystem. In this example, O 3 appeared to be a predisposing factor leading to increased drought stress, windthrow, rootdiseases, and insect infestation (Takemoto et al., 2001). Increased mo rtality of susceptible tree species, including ponderosa and Jeffrey pine, resulting from th ese combined stresses has shifted community composition towards white fir and incense cedar and has altered forest sta nd structure (Miller et al., 1989). A shift of community composition towa rds white fir may make this ecosystem more susceptible to fire. Although the role of O 3 was extremely difficult to separate from other confounding factors, such as high N deposition, th ere is evidence that this shift in species composition has altered trophic structure and f ood web dynamics (Pronos et al., 1999) and C and N cycling (Arbaugh et al., 2003). Ongoing research in this important ecosystem will reveal the extent to which ecosystem services have been affected.
One of the best-documented studies of population and community response to O 3 effects are the long-term studies of common plantain ( Plantago major ) in native plant communities in the United Kingdom (Davison and Reiling, 1995; Lyons et al., 1997; Reiling and Davison,

7-731992c). Elevated O 3 significantly decreased the growth of sensitive populations of common plantain (Pearson et al., 1996; Re iling and Davison, 1992a, b; Whitf ield et al., 1997) and reduced fitness as determined by decreased reproducti ve success (Pearson et al., 1996; Reiling and Davison, 1992a). While spatial compar isons of population responses to O 3 are complicated by other environmental factors, rapid changes in O 3 resistance were imposed by ambient levels and
variations in O 3 exposure (Davison and Reiling, 1995). At th e site of plantain seed collection, the highest correlations occurred between O 3 resistance and ambient O 3 concentrations (Lyons et al., 1997). In this case study, it appeared that O 3 -sensitive individuals are being removed by O 3 stress and the genetic variation represented in the population could be declining. If genetic diversity and variation is lost in ecosystems, there may be in creased vulnerability of the system to other biotic and abiotic stressors, and ultimat ely a change in the services provided by those
ecosystems. Reconstructed ecosystems in artificial e xposure experiments have also provided new insight into how O 3 may be altering ecosystem structur e and function (Karnosky et al., 2005). For example, the Aspen Free-Air CO 2 Enrichment facility was desi gned to examine the effects of
both elevated CO 2 and O 3 on aspen ( Populus tremuloides ), birch ( Betula papyrifera ), and sugar maple ( Acer saccharum ) in a simple reconstructed planta tion characteristic of Great Lakes aspen-dominated forests (Karnosky et al., 2003; Karnosky et al., 1999). They found evidence that the effects on above- and below-ground grow th and physiological processes have cascaded through the ecosystem, even affecting microbial communities (Larson et al., 2002; Phillips et al., 2002). This study also confirme d earlier observations of O 3 -induced changes in trophic interactions involving keystone tr ee species, as well as important insect pests a nd their natural enemies (Awmack et al., 2004; Holton et al., 2003; Percy et al., 2002). Collectively these examples suggest that O 3 is an important stressor in natural ecosystems, but it is difficult to quantify the contribution of O 3 due to the combination of stresses present in ecosystems. Continued research, employing new approaches, will be necessary to fully understand the extent to which O 3 is affecting ecosystem services.

7.7.2 Effects on Ecosystem Services and Carbon Sequestration

Since it has been established that O 3 affects photosynthesis and growth of plants, O 3 is most likely affecting the productivi ty of forest ecosystems. Therefore, it is desirable to link effects on growth and productivity to essential ecosystem services. However, it is very difficult to quantify ecosystem-level productivity losses b ecause of the amount of complexity in scaling from the leaf-level or individual plant to the ecosystem level, and because not all organisms in an ecosystem are equally affected by O 3
.

7-74Terrestrial ecosystems are important in the Earth's carbon (C) balance and could help
offset emissions of CO 2 by humans if anthropogenic C is se questered in vegetation and soils. The annual increase in atmospheric CO 2 is less than the total input s from fossil fuel burning and land use changes (Prentice et al., 2001) and much of this discrepancy is th ought to be attributable

to CO 2 uptake by plant photosynthesis (Tans & White, 1998). Temperate forests of the northern hemisphere have been estimated to be a net si nk of 0.6 to 0.7 Pg of C pe r year (Goodale et al. 2002). Ozone interferes with photos ynthesis, causes some plants to senesce leaves prematurely and in some cases, reduces allocation to stem and root tissue. Thus, O 3 decreases the potential for C sequestration. For the purposes of this di scussion, we define C sequestration as the net exchange of carbon by the terrestrial biosphere. However, long-term storage in the soil organic matter is considered to be the most stable form of C storage in ecosystems. In a study including all ecosystem types, Felz er et al. (2004), estimated that U.S. net primary production (net flux of C into an eco system) was decreased by 2.6-6.8% due to O 3 pollution in the late 1980's to early 1990's. Oz one not only reduces C se questration in existing forests, it can also affect refo restation projects (Beedlow et al. 2004). This effect, in turn, has been found to ultimately inhibit C sequestration in forest soils wh ich act as long-term C storage (Loya et al., 2003; Beedlow et al. 20 04). The interaction of rising O 3 pollution and rising CO 2 concentrations in the coming decades complicates predictions of future sequestration potential. Models generally predict that, in the future, C sequestration will increase with increasing CO 2 , but often do not account for the d ecrease in productivity due to the local effects of tropospheric
O 3 . In the presence of high O 3 levels, the stimulatory effect of rising CO 2 concentrations on forest productivity has been estimated to be reduced by more that 20% (Tingey et al., 2001; Ollinger et al. 2002; Karnosky et al., 2003). In summary, it would be anticipated that meeting lower O 3 standards would increase the
amount of CO 2 uptake by many ecosystems in the U.S. However, the amount of this improvement would be heavily dependent on th e species composition of those ecosystems. Many ecosystems in the U.S. do have O 3 sensitive plants. For, example forest ecosystems with dominant species such as aspen or ponderosa pine would be expected to increase CO 2 uptake
more with lower O 3 than forests with more O 3 tolerant species.

7-75REFERENCES

Abt Associates, Inc. (1995). Ozone NAAQS benefits analysis: Californi a crops. Report to U.S. EPA, July.

Abt Associates Inc. (2007). Techni cal Report on Ozone Exposure, Risk, an d Impacts Assessments for Vegetation: Final Report. Prepared for Office of Air Quality Pl anning and Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC. January 2007. Available electronically on the internet at: http://www.epa.gov/ttn/naaqs/standards/ozone/s_o3_cr_td.html.

Adams, R. M.; Hamilton, S. A.; McCarl, B. A. (1985) An assessment of the economic effects of ozone on U.S. agriculture. J. Air Pollut. Control Assoc. 35: 938-943.

Adams, R. M.; Hamilton, S. A.; McCarl, B. A. (1986) The benefits of pollution control: the case of ozone and U.S. agriculture. Am. J. Agric. Econ. 68: 886-893.

Alscher, R. G.; Amundson, R. G.; Cumming, J. R.; Fellows, S.; Fincher, J.; Rubin, G.; van Leuken, P.; Weinstein, L. H. (1989) Seasonal changes in the pigments, carbohydrat es and growth of red spru ce as affected by ozone. New Phytol. 113: 211-223.

Amar, P., D. Chock, A. Hansen, M. Moran, A. Russell, D. Steyn, and W. Stockwell, (2005): Final Report: Second Peer Review of the CMAQ Model. Report submitted to Community Modeling and Analysis System Center, University of North Carolina at Chapel Hill, May, 28 pp. ( http://www.cmascenter.org/PDF/CMAQ_Scd_Peer_Rev_July_5.pdf )

Amar, P., R. Bornstein, H. Feldman, H. Jeffries, D. St eyn, R. Yamartino, and Y. Zhang, (2004): Final Report: December 2003 Peer Review of the CMAQ Model. Report submitted to Community Modeling and Analysis System Center, University of No rth Carolina at Chapel Hill, July, 24 pp.

Andersen, C. P.; Hogsett, W. E.; Wessling, R.; Plocher, M. (1991) Ozone decreases spring root growth and root carbohydrate content in ponderosa pine the year following exposure. Can. J. For. Res. 21: 1288-1291.

Andersen, C. P.; Wilson, R.; Plocher, M.; Hogsett, W. E. (1997) Carry-over effects of ozone on root growth and carbohydrate concentrations of ponderosa pine seedlings. Tree Physiol. 17: 805-811.

Andersen, C. P.; Hogsett, W. E.; Plocher, M.; Rodecap, K.; Lee, E. H. (2001) Blue wild-rye grass competition increases the effect of ozone on ponderosa pine seedlings. Tree Physiol. 21: 319-327.

Andersen, C. P. (2003) Source-sink balance and carbon a llocation below ground in plants exposed to ozone. New Phytol. 157: 213-228.

Appel, K.W.; A. Gilliland; B. Eder (2005) An Operati onal Evaluation of the 2005 Release of Models-3 CMAQ Version 4.5. National Oceanic and Atmospheric Administration – Air Resources Laboratory, Atmospheric Sciences Modeling Division; In partnership with the National Exposure Research Laboratory, U.S. Environmental Protection Agency, Research Triangle Park, NC

Arbaugh, M.; Bytnerowicz, A.; Grulke , N.; Fenn, M.; Poth, M.; Temple, P.; Miller, P. (2003) Photochemical smog effects in mixed conifer forests along a natural gradient of ozone and nitrogen deposition in the San Bernardino Mountains. Environ. Int . 29: 401-406.

Arnold J.R.; R. L. Dennis; G. S. Tonnesen, (2003) Diag nostic evaluation of numerical air quality models with specialized ambient observations: testing the Community Multiscale Air Quality modeling system (CMAQ) at selected SOS 95 ground sites, Atmospheric Environment 37: 1185-1198.

Ashmore M.R. (2002). Effects of oxidants at the whole plant and community level. In: Bell JNB, Treshow M, eds. Air pollution and plants. London, UK: J Wiley, 89–118.

7-76Ashmore, M.; Emberson, L.; Karlsson, P. E.; Pleijel, H. (2004) New directions: a new generation of ozone critical levels for the protection of vegetation in Europe (correspondence). Atmos. Environ. 38: 2213-2214

Awmack, C. S.; Harrington, R.; Lindroth, R. L. (2004) Aphid individual performance may not predict population responses to elevated CO2 or O 3 . Global Change Biol. 10: 1414-1423.

Ball, G. R.; Benton, J.; Palmer-Brown, D.; Fuhrer, J.; Skär by, L.; Gimeno, B. S.; Mills, G. (1998) Identifying factors which modify the effects of ambient ozone on white clover (Trifolium repens) in Europe. Environ. Pollut. 103: 7-16.

Barnes, J. D.; Eamus, D.; Brown, K. A. (1990) The influence of ozone, acid mist and soilnutrient status on Norway spruce [Picea abies (L.) Karst.]: II. photosynthesis, dark respiration and soluble carbohydrates of trees during late autumn. New Phytol. 115: 149-156.

Beedlow P.A., Tingey D.T., Phillips D.L., Hogsett W.E. & Olszyk D.M. (2004) Rising atmospheric CO2 and carbon sequestration in forests. Frontiers in Ecology and the Environment 2, 315–322.

Bichele, I.; Moldau, H.; Padu , E. (2000) Estimation of plasmalemma conduc tivity to ascorbic acid in intact leaves exposed to ozone. Physiol. Plant. 108: 405-412.

Black, V. J.; Black, C. R.; Roberts, J. A.; Stewart, C. A. (2000) Impact of ozone on the reproductive development of plants. New Phytol. 147: 421-447.

Booker, F. L.; Reid, C. D.; Brunsc hon-Harti, S.; Fiscus, E. L.; Miller, J. E. (1997) Photosynthesis and photorespiration in soybean [Glycine max (L) Merr] chronically exposed to elevated carbon dioxide and ozone. J. Exp. Bot. 48: 1843-1852.

Booker, F. L.; Fiscus, E. L.; Miller, J. E. (2004) Combin ed effects of elevated atmospheric carbon dioxide and ozone on soybean whole-plant water use. Environ. Manage. 33: S355-S362.

Booker, F. L.; Miller, J. E.; Fiscus, E. L.; Pursley, W. A.; Stefanski, L. A. (2005) Comparative responses of container- versus ground-gro wn soybean to elevated CO 2 and O 3 . Crop Sci. 45: 883-895.

Burkey, K. O. (1999) Effects of ozone on apoplast/cytopl asm partitioning of ascorbic acid in snap bean. Physiol. Plant. 107: 188-193.

Burns, R. M., B. H. Honkala, tech. coords. (1990). Silvics of North America: 1. Conifers; 2. Hardwoods. Agriculture Handbook 654. U.S. Department of Agriculture, Forest Service, Washington, DC. vol.2, 877 p.

Byun, D.W., Ching, J.K.S. (Eds.), 1999. Science Algo rithms of the EPA Models-3 Community Multiscale Air Quality Model (CMAQ) Modeling System. EPA/600/ R-99/030, US Environmental Protection Agency, Office of Research and Development, Washington, DC 20460.

Campbell, S.; Temple, P.; Pronos, J.; Roch efort, R.; Andersen, C. (2000) Monito ring for ozone injury in west coast (Oregon, Washington, California) forests in 1998. Por tland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station; gene ral technical report no. PNW-GTR-495. Available: http://www.fs.fed.us/pnw/gtr s.htm [11 April, 2003].

Castillo, F. J.; Heath, R. L. (1990) CA 2+ transport in membrane vesicles from pinto bean leaves and its alteration after ozone exposure. Plant Physiol. 94: 788-795.

Castillo, F. J.; Miller, P. R.; Greppin, H. (1987) Extracellular biochemical markers of photochemical oxidant air pollution damage to Norway spruce. Experientia (Basel) 43: 111-115.

7-77CEPA. (2005) Review of the California Ambient Air Quality Standard for Ozone. Staff Report: Initial Statement of Reasons for Proposed Rulemaking. California Environmental Protection Agency, Air Resources Board

Chappelka, A. H.; Samuelson, L. J. (1998) Ambient ozon e effects on forest trees of the eastern United States: a review. New Phytol. 139: 91-108.

Chappelka, A. H. (2002) Reproductive development of blackberry (Rubus cuneifolius) as influenced by ozone. New Phytol. 155: 249-255.

Cooley, D. R.; Manning, W. J. (1987) The impact of ozone on assimilate partitioning in plants: a review. Environ. Pollut. 47: 95-113.

Coulston, J. W., Smith, G. C. and Smith, W. D. (2003). “Regional assessment of ozone sensitive tree species using bioindicator plants.” Environmental Monitoring and Assessment 83: 113–127.

Coulston, J.W., K. H. Riitters and G. C. Smith (2004). A Preliminary Assessment of the Montréal Process Indicators of Air Pollution for the United States. Environmental Monitoring and Assessment 95: 57–74.

Dämmgen, U.; Grünhage, L.; Haenel, H. D.; Jäger, H. J. (1993) Climate and stress in ecotoxicology: a coherent system of definitions and terms. Angew Bot. 67: 157-162.

Dann, M. S.; Pell, E. J. (1989) Decline of activity and quantity of ribulose bisphosphatecarboxylase/oxygenase and net photosynthesis in ozone-treated potato foliage. PlantPhysiol. 91: 427-432.

Davison, A. W.; Barnes, J. D. (1998) Effects of ozone on wild plants. New Phytol. 139: 135-151.

Davison, A. W.; Reiling, K. (1995) A rapid change in ozone resistance of Plantago major after summers with high ozone concentrations. New Phytol . 131: 337-344.

DeCaria, A. J.; Pickering, K. E.; Stench ikov, G. L.; Scala, J. R.; Stith, J. L.; Dye, J. E.; Ridley, B. A.; Laroche, P. (2000) A cloud-scale model study of lightning-generate NOx in an individual thunderstorm during STERAO-A.J. Geophys. Res. [Atmos. ] 105: 11,601-11,616.

Dickson, R.E., Lewin K.F., Isebrands J.G., Coleman M.D., Heilman W.E., Riemenschneider D.E., Sober J., Host G.E., Zak D.F., Hendrey G.R., Pregitzer K.S. and Karnosky D.F. (2000) Forest atmosphere carbon transfer storage-II (FACTS II) – The aspen free-air CO 2 and O 3 enrichment (FACE) project in an overview. USDA Forest Service North Central Research Sta tion. General Tech. Rep. NC-214. 68pp.

Dominy, P. J.; Heath, R. L. (1985) Inhibition of the K+-s timulated ATpase of the plasmalemma of pinto bean leaves by ozone. Plant Physiol. 77: 43-45.

Eder, B. and S. Yu, 2005: A pe rformance evaluation of the 2004 release of Models-3 CMAQ, Atmos. Environ. , in
press

Eder, B.K., Davis, J.M. and Bloomfield, P. (1993). A characterization of the spatiotemporal variability of non-urban ozone concentrations over the eastern United States. Atmospheri c Environment 27A: 2645–2668

Eder BK, Davis JM, Bloomfield P (1994) An automated classification scheme designed to better elucidate the dependence of ozone on meteorology. J Appl Meteorol 33: 1182–1199

Elkiey, T.; Ormrod, D. P. (1979) Leaf diffusion resistance responses of three petunia cultivars to ozone and/or sulfur dioxide. J. Air Pollut. Control Assoc. 29: 622-625.

Emberson, L.; Ashmore, M. R.; Cambridge, H. M.; Simpson, D.; Tuovinen, J. P. (2000a) Modelling stomatal ozone flux across Europe. Environ. Pollut. 109: 403-413.

7-78Emberson, L. D.; Wieser, G.; Ashmore, M. R. (2000b) Modelling of stomatal conductance and ozone flux of Norway spruce: comparison with field data. Environ. Pollut. 109: 393-402.

Engle, R. L.; Gabelman, W. H. (1966) Inheritance and m echanism for resistance to ozone damage in onion, Allium cepa L. Proc. Am. Soc. Hortic. Sci. 89: 423-430.

Farage, P. K.; Long, S. P. (1999) The effects of O 3 fumigation during leaf development on photosynthesis of wheat and pea: an in vivo analysis. Photosynth. Res. 59: 1-7.

Farage, P. K.; Long, S. P.; Lechner, E. G.; Baker, N. R. (1991) The sequence of changes within the photosynthetic apparatus of wheat following short-term exposure to ozone. Plant Physiol. 95: 529-535.

Federal Register (1996) National Ambient Air Quality Sta ndards for Ozone, Proposed Decision. 40 CFR 50; Federal Register 61: 65716.

Federal Register (1997) National Ambient Air Quality Standards for Ozone; Final Rule. 40 CFR 50; Federal Register 62: 38856.

Felzer, B.; Kickligher, D.; Melillo, J.; Wang, C.; Zhuang, Q.; Prinn, R. (2004) Effects of ozone on net primary production and carbon sequestration in the conterminous United States using a biogeochemistry model. Tellus B 56 (3), 230-248.

Finnan, J. M.; Burke, J. L.; Jones, M. B. (1997) An evaluation of indices that describe the impact of ozone on the yield of spring wheat (Triticum aestivum L). Atmos. Environ. 31: 2685-2693.

Fiore, A. M.; Jacob, D. J.; Mathur, R.; Martin, R. V. (2003) Application of empirical orthogonal functions to evaluate ozone simulations with regional and global models. J. Geophys. Res. (Atmos.) 108(D14): 10.1029/2002JD003151.

Fiscus, E. L.; Reid, C. D.; Miller, J. E.; Heagle, A. S. (1997) Elevated CO 2 reduces O 3 flux and O 3 -induced yield losses in soybeans: possible im plications for elevated CO 2 studies. J. Exp. Bot. 48: 307-313.

Fiscus, E. L.; Miller, J. E.; Booker, F. L.; Heagle, A. S.; Reid, C. D. (2002) The impact of ozone and other limitations on the crop productivity response to CO 2 . Technology 8: 181-192.

Fiscus, E. L.; Booker, F. L.; Burkey, K. O. (2005) Crop responses to ozone: uptake, modes of action, carbon assimilation and partitioning. Plant Cell Environ.: in press.

Flagler, R. B. (1998) Recognition of air pollution injury to vegetation: A pictorial atlas; second edition. Pittsburgh, PA: Air & Waste Management Association.

Fuentes, M and Raftery, AE (2005). Model evaluation an d spatial interpolation by Bayesian combination of observations with outputs from numerical models. Biometrics , 61, 36-45

. Fuentes, J. D.; Hayden, B. P.; Garsta ng, M.; Lerdau, M.; Fitzjarrald, D.; Ba ldocchi, D. D.; Monson, R.; Lamb, B.; Geron, C. (2001) New directions: VOCs and biosphere-atmosphere feedbacks. Atmos. Environ. 35: 189- 191.

Fuhrer, J. H. (1994) Effects of ozone on managed pasture. 1. Effects of open-top chambers on microclimate, ozone flux and plant growth. Environ. Pollut. 86: 297-305.

Gates, D. M. (1968) Transpirati on and leaf temperature. Annu. Rev. Plant Physiol. 19: 211-238.

7-79Goodale, C. L., Apps, M. J., Birdsey, R. A., Field, C. B., Heath, L. S., Houghton, R. A. , Jenkins, J. C., Kohlmaier, G. H., Kurz, W., Liu, S., Nabuurs, G.-J., Nilsson, S. an d Shvidenko, A. Z. (2002) Forest carbon sinks in the northern hemisphere. Ecol. Appl. 12, 891–899.

Grantz, D.A., McCool, P.H. (1992) Effect of ozone on Pima and Acala cottons in the San Joaquin Valley. In: Herber, D.J., Richter, D.A. (Eds.), Proceedings 1 992 Beltwide Cotton Conferences, vol 3.National Cotton Council of America, Memphis, TN, pp. 1082–1084.

Grantz, D. A.; Farrar, J. F. (2000) Ozone inhibits phloem loading from a transport pool: compartmental efflux analysis in Pima cotton. Aust. J. Plant Physiol. 27: 859-868.

Grantz, D. A.; Yang, S. (2000) Ozone impacts on allome try and root hydraulic conductance are not mediated by source limitation nor developmental age. J. Exp. Bot. 51: 919-927.

Gregg, J. W., C.G. Jones and T.E. Dawson (2003). “Urbanization effects on tree growth in the vicinity of New York City.” Nature 424: 183-187.

Grünhage, L.; Jäger, H. J. (1994) Influence of the atmospheric conductivity on the ozone exposure of plants under ambient conditions: considerations for establishing ozone standards to protect vegetation. Environ. Pollut. 85: 125-129.

Grünhage, L.; Haenel, H. D. (1997) PLATIN (PLant-ATmosphere-INteraction) I: a model of plant-atmosphere interaction for estimating absorbed doses of gaseous air pollutants. Environ. Pollut. 98: 37-50.

Grünhage, L.; Krupa, S. V.; Legge, A. H.; Jäger, H. J. (2004) Ambient flux-based critical values of ozone for protecting vegetation: differing spatial scales and un certainties in risk assessment. Atmos. Environ. 38: 2433-2437.

Grulke, N. E.; Andersen, C. P.; Fenn, M. E.; Miller, P. R. (1998) Ozone exposure and nitrogen deposition lowers root biomass of ponderosa pine in the San Bernardino Mountains, California. Environ. Pollut. 103: 63-73.

Grulke, N. E.; Balduman, L. (1999) Deciduous conifers: high N deposition and O 3 exposure effects on growth and biomass allocation in ponderosa pine. Water Air Soil Pollut. 116: 235-248.

Grulke, N. E.; Alonso, R.; Nguyen, T.; Cascio, C.; Dobrowolski, W. (2004) Stomata open at night in pole-sized and mature ponderosa pine: implications for O 3 exposure metrics. Tree Physiol. 24: 1001-1010.

Grulke, N. E.; Preisler, H. K.; Rose, C.; Kirsch, J.; Balduman, L. (2002) O 3 uptake and drought stress effects on carbon acquisition of ponderosa pine in natural stands. New Phytol. 154: 621-631.

Guderian, R. (1977) Discussion of the suitability of plant responses as a basis for air pollution control measures. In: Billings, W. D.; Golley, F.; Lange, O. L.; Olson, J. S. , eds. Air pollution: phytotoxicity of acidic gases and its significance in air pollution control. Berlin, Federa l Republic of Germany: Springer Verlag; pp. 75-97.

Hanson, P., Samuelson, L., Wullschleger, S., Tabberer, T. and Edwards, G. (1994) “Seasonal patterns of lightsaturated photosynthesis and leaf conductance for mature and seedling Quercus rubra L. foliage: differential sensitivity to ozone exposure.” Tree Physiology 14:1351-1366.

Heagle, A. S.; Body, D. E.; Heck, W. W. (1973) An open-t op field chamber to assess th e impact of air pollution on plants. J. Environ. Qual. 2: 365-368.

Heagle, A. S.; Letchworth, M. B.; Mitche ll, C. A. (1983) Effects of growth me dium and fertilizer rate on the yield response of soybeans exposed to chronic doses of ozone. Phytopathology 73: 134-139.

Heagle, A.S., L.W. Kress, P.J. Temple, R.J. Kohut, J.E. Miller, H.E. Hegg estad (1988) “Factors influencing ozone dose-yield response relationships in open-top field chamber studies.” In: W.W. Heck, O.C. Taylor, D.T.

7-80Tingey eds. Assessment of crop loss from air polluta nts: proceedings of an international conference; October, 1987; Raleigh, NC. New York, NY: Elsevier Applied Science; pp. 141-179.

Heagle, A. S.; Reinert, R. A. ; Miller, J. E. (1996) Response of white cl over to ozone in different environments. J. Environ. Qual. 25: 273-278.

Heagle, A. S.; Miller, J. E.; Pursley, W. A. (1998) Influence of ozone st ress on soybean response to carbon dioxide enrichment: III Yield and seed quality. Crop Sci. 38: 128-134.

Heath, R. L. (1987) The biochemistry of ozone attack on the plasma membrane of plant cells. Recent Adv. Phytochem. 21: 29-54.

Heath, R. L. (1988) Biochemical mechan isms of pollutant stress. In: Heck, W. W. ; Taylor, O. C. ; Tingey, D. T. , eds. Assessment of crop loss from air pollutants: proceedings of an international conference; October, 1987; Raleigh, NC. London, United Kingdom: Elsevier Applied Science; pp. 259-286.

Heath, R. L. (1994a) Alterations of plant metabolism by ozone exposure. In: Alscher, R. G.; Wellburn, A. R., eds. Plant Responses to the Gaseous Envi ronment: molecular, metabolic, and physiological aspects. molecular, metabolic, and physiological aspects. London, United Kingdom: Chapman & Hall; pp. 121-146.

Heath, R. L. (1994b) Possible mechanisms for the inhibition of photosynthesis by ozone. Photosynt. Res. 39: 439451.

Heck, W. W.; Cowling, E. B. (1997) The need for a long term cumulative secondary ozone standard - an ecological perspective. EM (January): 23-33

Heck, W. W.; Furiness, C. S.; Cowling, E. B.; Sims, C. K. (1998) Effects of ozone on crop, forest, and natural ecosystems: assessment of research needs. EM (October): 11-22.

Henderson, R. (2006c) Letter from CASAC Chairman Rogene Henderson to EPA Administrator Stephen Johnson, October 24, 2006, EPA-CASAC-07-001.

Herstrom, A., W. Hogsett, D. Tingey, E. Lee, and D. Phillips (1995). Using a geographical information system to estimate ozone exposure over fo rests across the United States

Holton, M. K.; Lindroth, R. L.; Nordheim, E. V. (2003) Foliar quality influences tree-herbivore-parisitoid interactions: effects of elevated CO2, O 3 , and plant genotype. Oecologia 137: 233-244.

Horst, R.; Duff, M. (1995). Concentr ation data transformation and the quadratic rollback methodology (Round 2, Revised). Unpublished memorandum to R. Rodríguez, U.S. EPA, June 8.

Hogsett, W. E.; Tingey, D. T.; Holman, S. R. (1985) A programmable exposure control system for determination of the effects of pollutant exposure regimes on plant growth. Atmos. Environ. 19: 1135-1145.

Hogsett, W. E.; Olszyk, D.; Ormrod, D. P.; Taylor, G. E., Jr.; Tingey, D. T. (1987) Air pollution exposure systems and experimental protocols: volume 1: a review and evaluation of performa nce. Corvallis, OR: U.S. Environmental Protection Agency, Environmental Research Laboratory; EPA report no. EPA/600/3- 87/037a. Available from: NTIS, Springfield, VA; PB88-181680.

Hogsett, W. E., Weber, J. E ., Tingey, D., Herstrom, A., Lee, E. H., Laurence, J. A. (1 997) “Environmental auditing: an approach for characterizing tro pospheric ozone risk to forests.” Environ. Manage . 21: 105-120

Hogsett, W. E.; Tingey, D. T.; Hendric ks, C.; Rossi, D. (1989) Sensitivity of western conifers to SO2 and seasonal interaction of acid fog and ozone. In: Olson, R. K.; Le fohn, A. S., eds. Effects of air pollution on western forests [an A&WMA symposium; June; Anaheim, CA]. Air Pollution Control Association; pp. 469-491 (APCA transactions series: no. 16).

7-81Horváth, L.; Nagy, Z.; Weidinger, T.; Artz, R.; Luke, W. T.; Valigura, R.; Pinto, J. P.; Womack, J. (1995) Measurement of fluxes of trace gases (O 3 , NOx, SO 2 , CO 2 , HNO 3 ), particulate sulfate and nitrate, water vapour over short vegetation by gradient and eddy correlation techniques in Hungary. EGS XX. General Assembly; April; Hamburg, Germany. Ann. Geophys. 13(suppl. 2): C490.

Isebrands, J. G.; Dickson, R. E.; Rebbeck, J.; Karnosky, D. F. (2000) Interacting effects of multiple stresses on growth and physiological processes in northern forest trees. In: Mickler, R. A.; Birsdey, R. A.; Hom, J., eds. Responses of northern U.S. forests to environmental change. New York, NY: Springer-Verlag; pp. 149-180. (Ecological studies: v. 139).

Isebrands, J. G.; McDonald, E. P.; Kruger, E.; Hendrey, G. ; Percy, K.; Pregitzer, K.; Sober, J.; Karnosky, D. F. (2001) Growth responses of Populus tremuloides clones to interacting carbon dioxide and tropospheric ozone. Environ. Pollut. 115: 359-371.

Jacobson, J. S. (1977) The effects of photochemical oxidants on vegetation. In: Ozon und Begleitsubstanzen im photochemischen Smog: das Kolloquium [Ozone and related substances in photochemical smog: the colloquium]; September 1976; Dusseldorf, Federal Republic of Germany. Dusseldorf, Federal Republic of Germany: VDI-Verlag GmbH; pp. 163-173. (VDI-Berichte nr. 270).

Jans, U.; Hoigne, J. (2000) Atmospheric water: transformation of ozone into OH-radicals by sensitized photoreactions or black carbon. Atmos. Environ. 34: 1069-1085.

Johnson, T. (1997). “Sensitivity of Exposure Estimates to Air Quality Adjustment Procedure,” Letter to Harvey Richmond, Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina.

Kolb, T. E.; Matyssek, R. (2001) Limitations and perspectiv es about scaling ozone impact s in trees. Environ. Pollut. 115: 373-393.

Karnosky, D.F., B. Mankovska, K. Perc y, R.E. Dickson, G.K. Podila, J. Sober, A. Noormets, G. Hendrey, M.D. Coleman, M. Kubiske, K.S. Pregitzer, and J.G. Isebrands (1999). “Effects of tropospheric O 3 on trembling aspen and interaction with CO 2 : Results from an O 3 -gradient and a FACE experiment.” J. Water, Air and Soil Pollut. 116: 311-322.

Karnosky, D. F., Z.E.Gagnon, R.E. Dickson, M.D. Coleman, E.H. Lee, J.G. Isebrands, (1996) “Changes in growth, leaf abscission, biomass associated with seasonal tropospheric ozone exposures of Populus tremuloides clones and seedlings.” Can. J. For. Res. 26: 23-37.

Karnosky, D. F.; Zak, D. R.; Pregitzer, K. S.; Awmack, C. S.; Bockheim, J. G.; Dickson, R. E.; Hendrey, G. R.; Host, G. E.; King, J. S.; Kopper, B. J.; Kruger, E. L.; Kubiske, M. E.; Lindrot h, R. L.; Mattson, W. J.; McDonald, E. P. (2003) Tropospheric O 3 moderates responses of temperat e hardwood forests to elevated CO2: A synthesis of molecular to ecosystem results from the Aspen FACE project. Funct. Ecol. 17: 289- 304.

Karnosky, D.F., Pregitzer, K.S., Zak, D.R., Kubiske, M.E., Hendrey, G.R., Weinstein, D., Nosal, M. & Percy, K.E. 2005 Scaling ozone responses of forest trees to th e ecosystem level in a changing climate. Plant Cell Environ.28, 965–981

Kats, G.; Thompson, C. R.; Kuby, W. C. (1976) Improved ventilation of open top greenhouses. J. Air Pollut. Control Assoc. 26: 1089-1090.

Kats, G.; Olszyk, D. M.; Thompson, C. R. (1985) Open top experimental chambers for trees. J. Air Pollut. Control Assoc. 35: 1298-1301.

7-82King, J.S., M. E. Kubiske, K. S. Pregitzer, G. R. Hendrey, E. P. McDonald, C. P. Giardina, V. S. Quinn, D. F. Karnosky. (2005) Tropospheric O 3 compromises net primary production in young stands of trembling aspen, paper birch and sugar maple in response to elevated atmospheric CO 2 . New Phytologist. 168:623– 636.

Kraft, M.; Weigel, H. J.; Mejer, G. J. ; Brandes, F. (1996) Reflectance measurem ents of leaves for detecting visible and non-visible ozone damage to crops. J. Plant Physiol. 148: 148-154.

Kerstiens, G.; Lendzian, K. J. (1989) Interaction between ozone and plant cuticles: I ozone deposition and permeability. New Phytol. 112: 13-19.

Krupa, S. V.; Grunhage, L.; Jager, H. J.; Nosal, M.; Manning, W. J.; Legge, A. H.; Hanewald, K. (1995) Ambient ozone (O 3 ) and adverse crop response: a unified view of cause and effect. Environ. Pollut. 87: 119-126.

Laisk, A.; Kull, O.; Moldau, H. (1989) Ozone concentration in leaf intercellula r air spaces is close to zero. Plant Physiol. 90: 1163-1167.

Lamb, C.; Dixon, R. A. (1997) The oxidative burst in plan t disease resistance. Ann. Rev. Plant Physiol. Mol. Biol. 48: 251-275.

Langebartels, C.; Kerner, K.; Leonardi, S.; Schraudner, M.; Trost, M.; Heller, W.; Sandermann, H., Jr. (1991) Biochemical plant responses to ozone: I differential induction of polyamine and ethylene biosynthesis in tobacco. Plant Physiol. 95: 882-889.

Larson, J. L.; Zak, D. R.; Sinsabaugh, R. L. (2002) Ex tracellular enzyme activity beneath temperate trees growing under elevated carbon dioxide and ozone. Soil Sci. Soc. Am. J. 66: 1848-1856.

Laurence, J.A.,Kohut, R.J., Amundson, R.G., (1993). Use of TREGRO to simulate the effects of ozone on the growth of red spruce seedlings. Forest Science. 39: 453-464.

Laurence, J. A.; Retzlaff, W. A.; Kern, J. S.; Lee, E. H.; Hogsett, W. E.; We instein, D. A. ( 2001) Predicting the regional impact of ozone and precipitation on the growth of loblolly pine and yellow poplar using linked TREGRO and ZELG models. For. Ecol. Manage. 146: 247-263.

Laurence, J. A.; Andersen, C. P. (2003) Ozone and natural systems: understanding exposure, response, and risk. Environ. Int. 29: 155-160.

Lee, E. H.; Tingey, D. T.; Hogsett, W. E.; Laurence, J. A. (2003) History of tropospheric ozone for the San Bernardino Mountains of southern California, 1963-1999. Atmos. Environ. 37: 2705-2717.

Lee, E. H.; Hogsett, W. E (2001) In terpolation of temperature and non-urban ozone exposure at high spatial resolution over the western United St ates. Climate Research. 18:163–179

Lee, E. H.; Hogsett, W. E. (1996) Methodology for calculating inputs for ozone secondary standard benefits analysis: part II. Report prepared for Office of Air Qu ality Planning and Standards, Air Quality Strategies and Standards Division, U.S. Environmental Protectio n Agency, Research Triangle Park, N.C., March.

Lee, E. H.; Hogsett, W. E. (1999) Role of concentrations and time of day in developing ozone exposure indices for a secondary standard. J. Air Waste Manage. Assoc. 49: 669-681

Lee, E. H.; Tingey, D. T.; Hogsett, W. E. (1989) Interrelation of experimental exposure and ambient air quality data for comparison of ozone exposure indices and es timating agricultural losses. Corvallis, OR: U.S. Environmental Protection Agen cy, Environmental Research Laboratory; EPA report no. EPA-600/3-89-047. Available from: NTIS, Springfield, VA; PB89-195036.

7-83Lefohn, A. S.; Laurence, J. A.; Kohut, R. J. (1988) A comp arison of indices that describe the relationship between exposure to ozone and reduction in the yield of agricultural crops. Atmos. Environ. 22: 1229-1240.

Legge, A. H.; Grunhage, L.; Nosal, M.; Jager, H. J.; Krupa, S. V. (1995) Ambient ozone and adverse crop response: an evaluation of North American and European data as they relate to exposure indices and critical levels. Angew. Bot. 69: 192-205.

Leitao, L.; Goulas, P.; Biolley, J. P. (2003) Time-course of Rubisco oxidation in beans (Phaseolus vulgaris L) subjected to a long-term ozone stress. Plant Sci. 165: 613-620.

Little, E. L., Jr. (1971) Atlas of United States Trees. U.S. Department of Agriculture, Forest Service; Miscellaneous Publication No. 1146.

Long, S., Nelson, R.L., Ainsworth, L., Ho llis, K., Mies, T., Morgan, P., Naidu, S., Ort, D.R., Webster, R., Zhu, X. Adapting Soybean To Curren t And Future Change In Atmospheric Composition. Do We Need More Than Field Selection Under Current Conditions?. Cellular And Molecular Biology Of Soybean Biennial Conference. 2002. P. 401. http://www.ars.usda.gov/rese arch/publications/publications.htm?SEQ_NO_115=142752

Loya W.M., Pregitzer K.S., Karberg N.J., King J.S. & Giardina C.P. (2003) Reduction of soil carbon formation by tropospheric ozone under elevated carbon dioxide. Nature 425, 705–707.

Luethy-Krause, B.; Landolt, W. (1990 ) Effects of ozone on starch accumula tion in Norway spruce (Picea abies). Trees 4: 107-110.

Luwe, M. W. F.; Takahama, U.; Heber, U. (1993) Role of ascorbate in detoxifying ozone in the apoplast of spinach (Spinacia oleracea L) leaves. Plant Physiol. 101: 969-976.

Lyons, T. M.; Barnes, J. D.; Davison, A. W. (1997) Relationships between ozone resistance and climate in European populations of Plantago major. New Phytol. 136: 503-510.

Mandl, R. H.; Weinstein, L. H.; McCune, D. C.; Keveny, M. (1973) A cylindrical, open-top chamber for the exposure of plants to air pollutants in the field. J. Environ. Qual. 2: 371-376.

Mandl, R. H.; Laurence, J. A.; Kohut, R. J. (1989) Development and testing of open-top chambers for exposing large, perennial plants to air pollutants. J. Environ. Qual. 18: 534-540.

Manning, W. J.; Krupa, S. V. (1992) Experimental methodology for studying the effects of ozone on crops and trees. In: Lefohn, A. S., ed . Surface level ozone exposures and their ef fects on vegetation. Chelsea, MI: Lewis Publishers, Inc.; pp. 93-156.

Massman, W. J.; Musselman, R. C.; Lefohn, A. S. (2000) A conceptual ozone dose-response model to develop a standard to protect vegetation. Atmos. Environ. 34: 745-759.

Massman, W. J. (2004) Toward an ozone standard to protect vegetation based on effective dose: a review of deposition resistance and a possible metric. Atmos. Environ. In press.

Matters, G. L.; Scandalios, J. G. (1987) Synthesis of isozymes of superoxide dismutase in maize leaves in response to O 3 , SO2, and elevated O2. J. Exp. Bot. 38: 842-852.

Matyssek, R.; Gunthardt-Goerg, M. S. ; Maurer, S.; Keller, T. (1995) Ni ghttime exposure to ozone reduces wholeplant production in Betula pendula. Tree Physiol. 15: 159-165.

McAinsh, M. R.; Evans, N. G.; Montgomery, L. T. (2002) Calcium signalling in stomatal responses to pollutants. New Phytol. 153: 441-447.

7-84McLaughlin, S. B.; McConathy. (1983) Effects of SO2 and O 3 on alocation of 14C-labeled photosynthate in Phaseolus vulgaris. Plant Physiol. 73: 630-635.

Mehlhorn, H.; O'Shea, J. M.; Wellburn, A. R. (1991) Atmosp heric ozone interacts with stress ethylene formation by plants to cause visible plant injury. J. Exp. Bot. 42: 17-24.

Miller, P. R.; McBride, J. R.; Schilling, S. L.; Gomez, A. P. (1989) Trend of ozone damage to conifer forests between 1974 and 1988 in the San Bernardino Mountains of southern California. In: Olson, R. K.; Lefohn, S., eds. Effects of air pollution on western forests [an A&WMA symposium; June; Anaheim, CA]. Air and Waste Management Association; pp. 309-323. (APCA transactions series, no. 16).

Moldau, H.; Söber, J.; Söber, A. (1990 ) Differential sensitivity of stomata and mesophyll tosudden exposure of bean shoots to ozone. Photosynthetica 24: 446-458.

Moldau, H. (1998) Hierarchy of ozone scavenging reactions in the plant cell wall. Phys iol. Plant. 104: 617-622.

Moldau, H.; Bichele, I. ( 2002) Plasmalemma protection by the apopla st as assessed from above zero ozone concentration in leaf intercellula r air spaces. Planta 214: 484-487.

Monteith, J. L.; Elston, J. (1993) Climatic constraints on crop production. In: Fowden, L.; Mansfield, T.; Stoddart, J., eds. Plant adaptation to environmental stress. London, United Kingdom: Chapman and Hall; pp. 3-18.

Morgan, P. B.; Ainsworth, E. A.; Long, S. P. (2003) How does elevated ozone impact soybean? A meta-analysis of photosynthesis, growth and yield. Plant Cell Environ. 26: 1317-1328.

Morgan, P.B., Bernacchi, C.J., Ort, D.R., Long, S.P. (2004). An in vivo analysis of the effect of season-long openair elevation of ozone to anticipated 2050 levels on photosynthesis in soybean. Plant Physiology 135: 2348- 2357.

Morgan, P.B, Mies T.A., Bollero G.A., Nelson R.L., Long, S.P. (2006) Season-long elevation of ozone concentration to projected 2050 levels under fully ope n-air conditions substantially decreases the growth and production of soybean. New Phytologist 2006 170: 333-343.

Murphy, J. J.; Deluki, M. A.; McCubbin, D. R.; Kim, H. J. (1999) The cost of crop damage caused by ozone air pollution from motor vehicles. J. Environ. Manage. 55: 273-289.

Musselman, R. C.; Massman, W. J. (1999) Ozone flux to vegetation and its relationship to plant response and ambient air quality standards. Atmos. Environ. 33: 65-73.

Musselman, R. C.; Minnick, T. J. (2000) Nocturnal stomatal conductance and ambient air quality standards for ozone. Atmos. Environ. 34: 719-733.

Neufeld, H. S.; Lee, E. H.; Renfro, J. R.; Hacker, W. D. (2000) Seedling insensitivity to ozone for three conifer species native to Great Smoky Mountains National Park. Environ. Pollut. 108: 141-151.

Noormets, A.; Sober, A.; Pell, E. J.; Di ckson, R. E.; Posila, G. K.; Sober, J. ; Isebrands, J. G.; Karnosky, D. F. (2001) Stomatal and non-stomatal limitation to photosynthesis in two trembling aspen (Populus tremuloides Michx) clones exposed to elevated CO2 and/or O 3 . Plant Cell Environ. 24: 327-336.

NPS (2005) 2005 Annual Performance & Progress Report: Air Quality in National Parks. National Park Service. http://www2.nature.nps.gov/air/Pubs/pdf/gp ra/Gpra2005_Report_03202006_Final.pdf

NRC (2004). Air quality management—United States. I. National Research Council (U.S.). Committee on Air Quality Management in the United States. TD883.2.A64325 2004 363.739 ′ 25 ′ 0973—dc222004014594 http://www.nap.edu/openbook/0309089328/html/

7-85Odum, E. P. (1963) Ecology. New York, NY: Holt, Rinehart and Winston. (Modern biology series).

Ollinger, S. V., Aber, J. D., Reich, P. B. and Freuder, R. J. (2002) Inter active effects of nitrogen deposition, tropospheric ozone, elevated CO2 and land use history on the carbon dynamics of northern hardwood forests. Glob. Change Biol. 8(6), 545–562.

Olszyk, D., Bytnerowlez, A., Kats, G., Reagan, C., Hake, S., Kerby, T., Millhouse, D., Roberts, B., Anderson, C., Lee, H. (1993) Cotton yield losses and ambient ozone concentrations in California’s San Joaquin Valley. Journal of Environmental Quality 22, 602–611.

Overmyer, K.; Tuominen, H.; Kettunen, R.; Betz, C.; Lange bartels, C.; Sandermann, H., Jr.; Kangasjarvi, J. (2000) Ozone-sensitive Arabidopsis rcd1 mutant reveals opposite roles for ethylene and jasmonate signaling pathways in regulating superoxide-dependent cell death. Plant Cell 12: 1849-1862.

Pauls, K. P.; Thompson, J. E. (1980) In vitro simula tion of senescence-related membrane damage by ozoneinduced lipid peroxidation. Nature (London) 283: 504-506.

Panek, J. A.; Baldocchi, D. D.; Goldstein, A. H. ( 2003) The need for spatially and functionally integrated models of ozone deposition to Sierra Nevada forests. In: Bytnerowicz, A.; Arbaugh, M. J.; Alonso, R., eds. Ozone Air Pollution in the Si erra Nevada: Distribution and Effects on Forests. Distribution and Effects on Forests. New York, NY: Elsevier; pp. 325-357.

Pearson, S.; Davison, A. W.; Reiling, K.; Ashenden, T.; Ollerenshaw, J. H. (1996) The effects of different ozone exposures on three contrasting populations of Plantago major . New Phytol. 132: 493-502.

Pel, Z. M.; Murata, Y.; Benning, G.; Thomine, S.; Klusener, B.; Allen, G. J.; Grill, E.; Schroeder, J. I. (2000) Calcium channels activated by hydrogen peroxide mediate abscisic acid signalling in guard cells. Nature (London) 406: 731-734.

Pell, E. J.; Schlagnhaufer, C. D.; Ar teca, R. N. (1997) Ozone-induced oxida tive stress: mechanisms of action and reaction. Physiol. Plant. 100: 264-273.

Percy, K. E.; Awmack, C. S.; Lindroth, R. L.; Kubiske, M. E.; Kopper, B. J.; Isebrand s, J. G.; Pregitzer, K. S.; Hendry, G. R.; Dickson, R. E.; Zak, D. R.; Oksanen, E.; Sober, J.; Harrington, R.; Karnosky, D. F. (2002) Altered performance of forest pests under atmospheres enriched with CO2 and O 3 . Nature (London) 420: 403-407.

Peterson, D. L.; Arbaugh, M. J.; Wakefield, V. A.; M iller, P. R. (1987) Evidence ofgrowth reduction in ozoneinjured Jeffrey pine (Pinus jeffreyi Grev and Balf) in Sequoia and Kings Canyon National Parks. JAPCA 37: 906-912.

Phillips, R. L.; Zak, D. R.; Holmes, W. E.; White, D. C. (2002) Microbial community composition and function beneath temperate trees exposed to elevated atmos pheric carbon dioxide and ozone. Oecologia 131: 236- 244.

Pleijel, H.; Wallin, G.; Karlsson, P.; Skarby, L.; Sellden, G. (1995) Gradients of ozone at a forest site and over a field crop - consequences for the AOT4O concept of critical level. Water Air Soil Pollut. 85: 2033-2038.

Pleijel, H.; Karlsson, G. P.; Sild, E.; Danielsson, H.; Skarby, L.; Sellden, G. (1996) Exposure of a grass-clover mixture to ozone in open-top chambers--effects on yield, quality and botanical composition. Agric. Ecosyst. Environ. 59: 55-62.

Pronos, J.; Merrill, L.; Dahlsten, D. (1999) Insects and pat hogens in a pollution-stressed forest. In: Miller, P. R.; McBride, J. R., eds. Oxidant air pollution impacts in the montane forests of southern California. Springer, pp. 317-337.

7-86Pitelka, L. F. (1988) Evolutionary responses of plants to anthropogenic pollutants. Trends in Ecology and Evolution 3: 233-236.

Prentice IC, Farquhar GD, Fasham MJR, et al. (2001) The Carbon Cycle an d Atmospheric Carbon Dioxide. In Climate Change 2001: The Scientific Basis. Cont ribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change. (ed J. T. Houghton YD, D. J. Griggs, M. Noguer, P. J. van der Linder, X. Dai, K. Maskell, and C. A. Johnson), pp. 241-280. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.

Rao, M. V.; Davis, K. R. (2001) The physiology of ozone induced cell death. Planta 213: 682-690.

Rao, M. V.; Lee, H. I.; Davis, K. R. (2002) Ozone-induced ethylene production is dependent on salicylic acid, and both salicylic acid and ethylene act in concert to re gulate ozone-induced cell death. Plant J. 32: 447-456.

Regener, V.H. (1957). Vertical flux of atmospheric ozone. J. Geophys. Res. 62: 221-228.

Reid, C. D.; Fiscus, E. L. (1998) E ffects of elevated [CO2] an d/or ozone on limitations to CO2 assimilation in soybean (Glycine max). J. Exp. Bot. 49: 885-895.

Reich, P. B.; Lassoie, J. P. (1984) Effects of low level O 3 exposure on leaf diffusive conductance and water-use efficiency in hybrid poplar. Plant Cell Environ. 7: 661-668.

Reiling, K.; Davison, A. W. (1992a) Effects of a short ozone exposure given at different stages in the development of Plantago major L. New Phytol. 121: 643-647.

Reiling, K.; Davison, A. W. (1992b) The response of native, herbaceous species to ozone: growth and fluorescence screening. New Phytol. 120: 29-37.

Reiling, K.; Davison, A. W. (1992c) Spatial variation in ozone resistance of British populations of Plantago major L. New Phytol. 122: 699-708.

Retzlaff, W. A.; Arthur, M. A.; Grulke, N. E.; Weinstein, D. A.; Gollands, B. (2000) Use of a single-tree simulation model to predict effects of ozone and drought on growth of a white fir tree. Tree Physiol. 20: 195-202.

Rizzo, M (2005). Evaluation of a quadratic approach for adjusting distributions of hourly ozone concentrations to meet air quality standards. November 7, 2005.

Rizzo, M. (2006). A distributional comparison between different rollback methodologies applied to ambient ozone concentrations. May 31, 2006

Roitsch, T. (1999) Source-sink regulation by sugar and stress. Curr. Opin. Plant Biol. 2: 198-206.

Samuelson, L.; Kelly, J. M. (2001) Scaling ozone effects from seedlings to forest trees Tansley review no 21. New Phytol. 149: 21-41.

Sandermann, H., Jr. (1998) Ozone: an air pollutant actin g as a plant-signaling molecule. Naturwissenschaften 85: 369-375.

Sandermann, H., Jr. (2000) Ozone/biotic disease interactions: molecular biomarkers as a new experimental tool. Environ. Pollut. 108: 327-332.

Sasek, T. W.; Richardson, C. J.; Fendick, E. A.; Bevington, S. R.; Kress, L. W. (1991) Carryover effects of acid rain and ozone on the physiology of multiple flushes of loblolly pine seedlings. For. Sci. 37: 1078-1098.

7-87Schraudner, M.; Moeder, W.; Wiese, C.; Van Camp, W.; Inze, D.; Lange bartels, C.; Sandermann, H., Jr. (1998) Ozone-induced oxidative burst in the ozone biomonitor plant, tobacco Bel W3. Plant J. 16: 235-245.

Simini, M.; Skelly, J. M.; Davis, D. D.; Savage, J. E.; Comr ie, A. C. (1992) Sensitivity of four hardwood species to ambient ozone in north central Pennsylvania. Can. J. For. Res. 22: 1789-1799.

Smith, W. H. (1992) Air pollution effects on ecosystem proce sses. In: Barker, J. R.; Tingey, D. T., eds. Air pollution effects on biodiversity. Van Nostrand Reinhold; pp. 234-260.

Smith, G., Coulston J., Jepsen, J. and Prichard, T. (2003) “A national ozone biomonitoring program: Results from field surveys of ozone sensitive plants in northeastern forest (1994–2000)” Environmental Monitoring and Assessment 87(3): 271

− 291.

Somers, G. L.; Chappelka, A. H.; Rosseau, P.; Renfro, J. R. (1998) Empirical evidence of growth decline related to visible ozone injury. For. Ecol. Manage. 104: 129-137.

Stitt, M. (1996) Plasmodesmata play an essential role in su crose export from leaves: a step towards an integration of metabolic biochemistry and cell biology. Plant Cell 8: 565-571.

Takemoto, B. K.; Bytnerowicz, A.; Fenn, M. E. (2001) Current and future effects of ozone and atmospheric nitrogen deposition on California's mixed conifer forests. For. Ecol. Manage . 144: 159-173.

Tans PP, White JWC (1998) In balance, with a little help from the plants. Science, 281, 183-184.

Taylor R. (1994) “Deterministic versus stochastic eval uation of the aggregate economi c effects of price support programs” Agricultural Systems 44: 461-473.

Taylor, C.R. “AGSIM: Model Description and Documentati on.” Agricultural Sector Models for the United States. C.R. Taylor, K.H. Reichelderfer, and S.R. Johnson, eds. Ames IA: Iowa State University Press, (1993).

Temple, P. J.; Riechers, G. H.; Miller, P. R.; Lennox, R. W. (1993) Growth responses of ponderosa pine to longterm exposure to ozone, wet and dry acidic deposition, and drought. Can. J. For. Res. 23: 59-66.

Tingey, D. T.; Fites, R. C.; Wickliff, C. (1975) Activity changes in selected enzymes from soybean leaves following ozone exposure. Physiol. Plant. 33: 316-320.

Tingey, D. T.; Standley, C.; Field, R. W. (1976) Stress ethylene evolution: a measure of ozone effects on plants. Atmos. Environ. 10: 969-974.

Tingey, D. T.; Taylor, G. E., Jr. (1982) Variation in plant response to ozone: a conceptual model of physiological events. In: Unsworth, M. H.; Ormrod , D. P., eds. Effects of gaseou s air pollution in agriculture and horticulture. London, United Kingdom: Butterworth Scientific; pp. 113-138.

Tingey, D. T.; Laurence, J. A.; Weber, J. A.; Greene, J.; Ho gsett, W. E.; Brown, S.; Lee, E. H. (2001) Elevated CO2 and temperature alter the response of Pinus ponderosa to ozone: A simulation analysis. Ecol. Appl

. 11: 1412-1424.

Tingey, D. T.; Hogsett, W. E.; Lee, E. H.; Laurence, J. A. (2004) Stricter ozone ambient air quality standard has beneficial effect on Ponderosa pine in California. Environ. Manage . 34: 397-405.

Unsworth, M. H.; Heagle, A. S.; Heck, W. W. (1984a) Ga s exchange in open-top field chambers - I measurement and analysis of atmospheric resistances to gas exchange. Atmos. Environ . 18: 373-380.

Unsworth, M. H.; Heagle, A. S.; Heck, W. W. (1984b) Gas exchange in open-top field chambers - II resistances to ozone uptake by soybeans. Atmos. Environ . 18: 381-385.

7-88Urban, D.L., G.B. Bonan, T.M. Smith, H.H. Shugart (1991). “Spatial applications of gap models.” For. Ecol. Mgmt. 42: 95-110.

USDA, NRCS. 2006. The PLANTS Database (http://plants.usda .gov, December 2006). National Plant Data Center, Baton Rouge, LA 70874-4490 USA.

U.S. Environmental Protection Agency (1978) Air quality criteria for ozone and other photochemical oxidants. Research Triangle Park, NC: Office of Health and Environmental Assessment, Environmental Criteria and Assessment Office; report no. EPA-600/8-78-004. Available from: NTIS, Springfield, VA; PB80-124753.

U.S. Environmental Protection Agency (1986) Air quality criteria for ozone and other photochemical oxidants. Research Triangle Park, NC: Office of Health and Environmental Assessment, Environmental Criteria and Assessment Office; report nos. EPA-600/8-84-020aF-eF. 5v. Available from: NTIS, Springfield, VA; PB87-142949.

U.S. Environmental Protection Agency (1989). Review of National Ambient Air Quality Standards for Ozone: Assessment of Scientific and Technical Information - OAQPS Staff Paper. Office of Air Quality Planning and Standards, Research Triangle Park, NC.

U.S. Environmental Protection Agency (1996a). Air Quality Criteria for Ozone and Related Photochemical Oxidants. EPA/600/P-93/004aF-cF. Office of Research and Development, National Center for Environmental Assessment, Research Triangle Park, NC.

U.S. Environmental Protection Agency (1996b). Review of National Ambient Air Quality Standards for Ozone: Assessment of Scientific and Techni cal Information - OAQPS Staff Paper. EPA/452/R-96-007. Office of Air Quality Planning and Standard s, Research Triangle Park, NC.

U.S. Environmental Protection Agency (2003a). Ozone Injury to Forest Trees. In: EPA's Draft Report on the Environment Technical Document. EPA-600-R-03-050. U.S. EPA, ORD, Washington, DC, page 5-19

U.S. Environmental Protection Agency (2003b).Clean Ai r Status and Trends Network (CASTNet) 2001 Quality Assurance Report; Research Triangle Park, NC: Office of Air Quality Planning and Standards. Report from EPA Contract No. 68-D-98-112.

U.S. Environmental Protection Agency (2004). The Ozon e Report: Measuring Progress through 2003. EPA/454/K04-001. Office of Air Quality Planning an d Standards, Research Triangle Park, NC.

U.S. Environmental Protection Agency (2005a). Plan for Review of the National Ambient Air Quality Standards for Ozone. Office of Air Quality Planning and Standa rds, Research Triangle Park, NC. March. Available electronically on the internet at http ://www.epa.gov/ttn/naaqs/standards/ozone/s_O 3 _cr_pd.html.

U.S. Environmental Protection Agency (2005b). Technical Support Document for the Final Clean Air Interstate Rule: Air Quality Modeling. Office of Air Quality Pl anning and Standards, Research Triangle Park, NC.

U.S. Environmental Protection Agency (2006) Air Quality Criteria for Ozone and Related Photochemical Oxidants (Final). Office of Research and Development, National Center for Environmental Assessment, Research Triangle Park, NC. EPA/600/R-05/004aF-cF, 2006.

USDA Forest Service: 1999, ‘Forest Health Monitoring 1999 Field Methods Guide. USDA Forest Service’, National Forest Health Monitoring Program, Research Triangle Park, NC.

Vahala, J.; Ruonala, R.; Keinanen, M.; Tuominen, H.; Ka ngasjarvi, J. (2003) Ethylene insensitivity modulates ozone-induced cell death in birch. Plant Physiol. 132: 185-195.

Walcek, C. J.; Yuan, H. H.; Stockwell, W. R. (1997) The influence of aqueous-phase chemical reactions on ozone formation in polluted and nonpolluted clouds. Atmos. Environ. 31: 1221-1237.

7-89Weber, J. A.; Clark, C. S.; Hogsett, W. E. (1993) Analysis of the relationship(s) among O 3 uptake, conductance, and photosynthesis in needles of Pinus ponderosa. Tree Physiol. 13: 157-172.

Weinstein, D.A., Beloin, R.M., R.D. Yanai (1991). “Mode ling changes in red spruce ca rbon balance and allocation in response to interacting ozone and nutrient stress.” Tree Physiology 9: 127-146.

Weinstein, D.A., J.A. Laurence, W.A. Retzlaff, J.S. Kern, E.H. Lee, W.E. Hogsett, J. Weber (2005). Predicting the effects of tropospheric ozone on regional productivity of ponderosa pine and white fir. Forest Ecology and Management 205: 73-89.

Wellburn, A. R. (1990) Why are atmospheric oxides of nitr ogen usually phytotoxic and not alternative fertilizers? New Phytol. 115: 395-429.

Whitfield, C. P.; Davison, A. W.; Ashenden, T. W. (1997) Artificial selection and heritability of ozone resistance in two populations of Plantago major. New Phytol. 137: 645-655.

Winner, W. E.; Lefohn, A. S.; Cotter, I. S.; Greitner, C. S.; Nellessen, J.; McEvoy , L. R., Jr.; Olson, R. L.; Atkinson, C. J.; Moore, L. D. (1989) Plant re sponses to elevational gradients of O 3 exposures in Virginia. Proc. Natl. Acad. Sci. U. S. A. 86: 8828-8832.

Winner, W. E.; Coleman, J. S.; Gillespie, C.; Mooney, H. A.; Pell, E. J. (1991) Conseq uences of evolving reistance to air pollutants. In: Taylor, G. E.; Pitelka, L. F.; Clegg, M. T., eds. Ecological genetics and air pollution. Springer-Verlag; pp. 177-202.

Winner, W. E.; Lefohn, A. S.; Cotter, I. S.; Greitner, C. S.; Nellessen, J.; McEvoy , L. R., Jr.; Olson, R. L.; Atkinson, C. J.; Moore, L. D. (1989) Plant re sponses to elevational gradients of O 3 exposures in Virginia. Proc. Natl. Acad. Sci. U. S. A. 86: 8828-8832.

Young, T. F.; Sanzone, S., eds. (2002) A framework for assessing and reporting on ecological condition: an SABreport. Washington, DC: U.S. Environmental Protection Agency, Science Advisory Board; report no. EPASAB-EPEC-02-009. Available: h ttp://www.epa.gov/sab/ pdf/epec02009.pdf [9 December, 2003].

7-908-1 

### 8. STAFF CONCLUSIONS AND RE COMMENDATIONS ON THE SECONDARY O 3 

### NAAQS

8.1 INTRODUCTION This chapter presents staff conclusions and recommendations rega rding an appropriate range of options for the Administ rator to consider in selecting a pollutant indicator, averaging time, form, and level for the secondary O 3 standard. In so doing, this chapter describes the
results and conclusions of staff assessments of sc ientific evidence presented in the CD and of air quality, exposure, and risk analyses presented in Chapters 2 and 7 herei n. Comments and advice
received from CASAC in their review of earlier drafts of this document, as well as comments on earlier drafts submitted by interested parties, that have significantly informed the development of staff’s views, are also discussed. In presenting policy options fo r the Administrator’s consider ation, we note that the final decision on retaining or revi sing the current secondary O 3 standard is larg ely a public welfare policy judgment. A final decisi on should draw upon scientific in formation and analyses about welfare effects, exposure and risks, as well as judgments about the appropriate response to the range of uncertainties that are i nherent in the scientific evidence and analyses. Our approach to informing these judgments, discussed more fully be low, is consistent with the requirements of the NAAQS provisions of the Act a nd with how EPA and the courts have historically interpreted the Act. These provisions require the Administrato r to establish secondary standards that, in the Administrator’s judgment, are re quisite to protect public welfar e from any known or anticipated adverse environmental effect. In so doing, the Ad ministrator seeks to esta blish standards that are neither more nor less stringent th an necessary for this purpose.

8.2 APPROACH Welfare effects, as defined in section 302( h) (42 U.S.C. 7602(h)) of the Clean Air Act include, but are not limited to, ‘‘ effects on soils, water, crops, vegetation, manmade 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.” As in the last review, this review has focused on vegetation and crops, since effects on these public welfare categories are well-studied and currently known to be of most concern at

O 3 concentrations typically occu rring in the U.S. Further, by adversely affecting natural vegetation and commercial crops, O 3 may also indirectly adversely affect natural ecosystems and their components (e.g., soils, water, animals, and wildlife). Therefore, these important but less
well-studied indirect effects will be qualitatively discussed. As discussed above in Chapter 7, for8-2 other welfare effects categories, insufficient new information was available to inform the selection of an indicator, form, averaging time or level for a distinct secondary standard and they are not discussed further, except in terms of research needs. In evaluating whether the current seconda ry standard is adequate or whether consideration of revisions is appr opriate, we adopted an approach in this review that builds upon the general approach used in the last revi ew and reflects the broader body of evidence now available. In developing conc lusions and recommendations for the Administrator to consider in this review, staff presents eff ects-, exposure- and risk-based c onsiderations. We have expanded and modified the exposure and risk assessments to reflect the availabi lity of new tools, assessment methods, and a larger and more divers e body of evidence. We have taken a weight of evidence approach that evaluates information across the variety of vegetation-related research areas described in the CD (e.g., seedling and matu re forest tree species and commodity, fruit, vegetable and forage crop species), and incl udes assessments of air quality, exposures, and qualitative and quantitative risks associated with alternative air quality scenarios. With respect to vegetation effects informa tion, we have evaluated the conclusions drawn
at the end of the last review in light of more recent evidence from chamber, free air, gradient,
model and field-based observation studies for a variety of vegetation e ffects endpoints. We place greater weight on U.S. studies due to the often species-, site -, and climate-specific nature
of O 3 -related vegetation response. With respect to quantitative exposure- and risk-based considerations, we have relied on both monitored and interpolated O 3 exposures as described in section 7.5. of Chapter 7. Several alternative air quality scenarios were selected for evaluation to reflect a range of alternative standards under cons ideration. These scenarios include current “as is” air quality (2001), as well as six “just meet” scenarios for wh ich interpolated O 3 air quality is adjusted using a rollback method to simulate ju st meeting a range of alternative standards. Uncertainties associated with the exposure a nd risk assessments are also discussed, including, where possible, some sense of the direction and/or magnitude of the uncertainties that should be
taken into account as one consid ers these estimates. With rega rd to the use of the TREGRO model for estimating mature tree risks, staff acknowledges the presence of unknown and unquantifiable sources of uncertainty, as is typical with all such models. In this review, a series of general questions frames our approach to informing conclusions
and the identification of an appropriate range of policy op tions for consideration by the Administrator regarding the current secondary O 3 standard. Our consideration of the adequacy of the current standard begins in section 8.3.1 by addressing questions such as the following:

• To what extent does newly available info rmation reinforce or call into question evidence of associations with effects identified in the last review?8-3 • To what extent does newly available informa tion reinforce or call into question any of the basic elements of the current standards?

• To what extent have important uncertainties identified in th e last review been reduced and have new uncertainties emerged?

To the extent that the available information s uggests that revision of th e current standards may be appropriate to consider, we explore whethe r the currently availabl e information supports
consideration of a standard that is either mo re or less protective by addressing the following questions:

• Is there evidence that vegetation effects extend to ambient O 3 concentration levels that are as low as or lower than had previously been observed, and what are the important uncertainties associated with that evidence?

• Are exposures and vegetation risks of concern estimated to occur in areas that meet the current standard; are they important from a public welfare perspective; and what are the important uncertainties associated with the estimated risks? To the extent that there is support for considerati on of revised standards, we then identify a range of alternative standards (in te rms of an indicator for photoche mical oxidants, averaging time, level, and form in sections 8.3.2 through 8.3.5 below, respectively) that sta ff feels are appropriate
for the Administrator to consider and that refl ect staff conclusions a nd recommendations on the science, taking into account ot her public welfare policy consid erations. In so doing, staff addresses the following questions:

• Does the evidence provide support for considering a different O 3 indicator?

• Does the evidence provide support for c onsidering different averaging times?

• What ranges of levels and forms of alternat ive standards are supported by the evidence, and what are the uncertainties and limitations in that evidence?

• To what extent do specific levels and fo rms of alternative standards reduce the estimated exposures of concern and risks attributable to O 3 and other photochemical oxidants, and what are the un certainties in the es timated exposure and risk reductions? A summary of staff conclu sions and recommendations regarding a range of policy options identified for the Administrator’s cons ideration, as well as key CASAC and public commenter views concerning whether, and if so how, to revise th e current secondary O 3 standard is presented in section 8.3.6 below. This chapter concludes with a discussion of key uncertainties and recommendations for additional research related to setting a secondary O 3 NAAQS in section 8.4.8-4 8.3 SECONDARY O 3 STANDARD The current secondary standard is a 3-year average of the annual 4 th -highest maximum 8- hr average set at a level of 0.08 ppm. This standard was select ed to provide protection to the public welfare, especially agricu ltural crops and other at-risk sens itive plant species, against a wide range of O 3 -induced effects. As an introduction to our discussion in this section of the adequacy of the current O 3 standard, it is useful to summarize the key factors that formed the
basis of the decision in the last review to revise the averaging time, level and form of the then current 1-hr secondary standard. In the 1996 proposal notice (61 FR 65716), th e Administrator proposed to replace the then existing 1-hr O 3 secondary NAAQS with one of two altern ative new standards: a standard identical to the proposed 0.08 ppm, 8-hr primary standard (describ ed above), or alternatively, a new seasonal standard expressed as a sum of hourly concentrations greate r than or equal to 0.06 ppm, cumulated over 12 hours per day duri ng the maximum 3-month period during the O 3 monitoring season (SUM06), set at a level of 25 ppm-hr. At the time, this latter standard was considered to be an annual standard. This pr oposal was based on a thorough review of the latest
scientific information available and described in the 1996 O 3 CD, as well as (1) staff assessments of the policy-relevant information in the 1996 O 3 CD presented in the 1996 O 3 Staff Paper including air quality, vegetation exposure and risk , and economic values; (2 ) consideration of the degree of protection to vegetati on potentially afforded by the pr oposed 0.08 ppm, 8-hr primary standard; (3) CASAC advi ce and recommendations; and (4) public comments.
In the final rule for the O 3 NAAQS published in July 1997 (62 FR 38877), the Administrator decided to replace the then current 1-hr, 0.12-ppm se condary NAAQS with a
standard that was identical in every way to the new revised primary standard of an 0.08 ppm
annual 4 th -highest maximum 8-hr average standard averaged over 3 years. Her decision was based on her judgment that: (1) the then existi ng secondary standard did not provide adequate protection for vegetation against th e adverse welfare effects of O 3 ; (2) reflected CASAC advice “that a secondary NAAQS, more st ringent than the present primar y standard, was necessary to protect vegetation from O 3 ” (Wolff, 1996); (3) the new 8-hr average standard would provide substantially improved protec tion for vegetation from O 3 -related adverse effects as compared to the level of protection provided by the then cu rrent 1-hr, 0.12-ppm secondary standard; (4) significant uncertainties remained with respect to exposure dynamics, ai r quality relationships, and the exposure, risk, and monetized valuation analyses presented in the proposal, resulting in only rough estimates of the increased public welf are likely to be afforded by each of the proposed alternative standards; (5) there was va lue in allowing more time to obtain additional
information to better characterize O 3 -related vegetation effects under field conditions from
additional research and to deve lop a more complete rural monitoring network and air quality8-5 database from which to evaluate the elements of an appropriate seasonal secondary standard; and (6) there was value in allowing more time to eval uate more specifically the improvement in rural air quality and in O 3 –related vegetation effects resulting fr om measures designed to attain the new primary standard (62 FR 38877-78). The Administrator further concluded (62 FR 38877-78) that continued research on the
effects of O 3 on vegetation under field conditions and on better characterizing the relationship
between O 3 exposure dynamics and plant response w ould be important in the next review
because:

• The available biological data base highlighted the importa nce of cumulative, seasonal exposures as a primary determinant of plant responses.

• The association between daily maximum 8-hr O 3 concentrations and plant responses had not been specifically examined in field tests.

• The impacts of attaining an 8-hr, 0.08 ppm primary standard in upwind urban areas on rural air quality distributions could not be ch aracterized with confidence due to limited monitoring data and air quality mo deling in rural and remote areas.

8.3.1 Adequacy of Current O 3 Standard

The new evidence available in this review continues to support and strengthen key policy-relevant conclusions drawn in the previous review (U.S. EPA, 2006). Based on this new evidence, the current CD once more concl udes that: (1) a plant’s response to O 3 depends upon the cumulative nature of ambient exposure (e.g., concentration times duration) as well as the temporal dynamics of those concen trations; (2) current ambient c oncentrations in many areas of the country are sufficient to impair growth of numerous common and economically valuable plant and tree species; (3) the entrance of O 3 into the leaf through the stomata is the critical step
in O 3 effects; (4) effects can occur with only a fe w hourly concentrations above 80 ppb; (5) other
environmental biotic and abiotic factors are also influential to the overall impact of O 3 on plants and trees; and (6) a high degree of uncertainty remains in our abil ity to assess the impact of O 3 on ecosystem services. The effects-based evidence described in the CD underlying the
reaffirmation of these conclusions will be discussed in more detail in the sections that follow. Based on the above policy-relevant findings from the CD, and wh ile recognizing that important uncertainties and research questi ons remain, we also conclude th at progress has been made since the last review and thus, we generally find s upport in the available e ffects-based evidence for
consideration of an O 3 standard that is at least as protec tive as the current standard and do not find support for consideration of an O 3 standard that is less protectiv e than the current standard. This general conclusion is consistent with th e advice and recommendations of CASAC and with8-6 the views expressed by all the in terested parties who provided co mment on the previous draft of
this document. Having reached this general conclusion, we th en evaluated the adequacy of the current standard by considering to what degree risks to vegetation and eco systems would be expected to occur after just meeting the current as well as a range of alternative secondary standards. As discussed in Chapter 7 and in gr eater detail below, staff conclu sions regarding the adequacy of
the current standard are based on the available vegetation effects, exposure and risk-based evidence (section 8.3.1.1) and CASAC and pub lic commenter views (section 8.3.1.2) in conjunction with the additional policy-relevant c onsiderations presented under the discussions on indicator, averaging time, form, and level (sections 8.3.2 through 8.3.5). In evaluating the strength of this information, staff has taken in to account the uncertainties and limitations in the scientific evidence and analyses as well as cons idered the views of CASA C and other interested parties provided on the sec ond draft of this document.

8.3.1.1 Vegetation Evidence-, Exposure- and Risk-Based Considerations In the last review, crop yield and seedli ng biomass loss open-top chamber (OTC) data provided the basis for staff analyses, conclu sions, and recommendations (U.S. EPA, 1996b). Since then, several additional lines of evidence ha ve progressed sufficiently to provide staff with a more complete and coherent picture of the scope of O 3 -related vegetation risks, especially those currently faced by seedling, sapling and mature tree species growing in field settings, and indirectly, forested ecosystems. Specifically, new research re flects an increased emphasis on field-based exposure methods (e.g., free air expos ure and ambient gradient), improved field survey biomonitoring techniques, and mechanisti c tree process models. Findings from each of
these research areas are discusse d separately below. However, in reaching conclusions regarding the adequacy of the current standard, staff has considered the combined information from all these areas together, using an integrat ed, weight of evidence approach. In evaluating the degree to which the cu rrent standard is adequate in protecting vegetation at the national scale, staff has relied on both meas ured and modeled air quality information. For some effects, like visible fo liar injury and modeled mature tree growth response, only monitored air quality informati on was used. For other effects categories (e.g., crop yield and tree seedling growth), staff relied on interpolated O 3 exposures. Staff recognizes that exposures predicted by this interpolation method are more uncertain. The uncertainties associated with this approach are discussed under the exposure assessment discussion below. Additional sources of uncertainty associated with the risk assessm ent are described in the section preceding the discussion of seedling and ma ture tree biomass-loss risk results.8-7 Visible Foliar Injury Evidence Recent systematic injury surveys continue to document visible foliar injury symptoms diagnostic of phytotoxic O 3 exposures on sensitive bioindicator plants. These surveys produce more expansive evidence than that available at the time of the last review that visible foliar injury is occurring in many areas of the U.S. under current ambient conditions. Staff performed an assessment combining recent U.S. Forest Service Forest Inventory and Analysis (FIA) biomonitoring site data with the county level ai r quality data for thos e counties containing the FIA biomonitoring sites. This assessment showed that incidence of visi ble foliar injury ranged from 21 to 39% during the four-year period ( 2001-2004) across all count ies with air quality
levels at or below that of the current 8

- hr standard. The magnitude of these percentages suggests that phytotoxic exposures sufficient to induce visi ble foliar injury would still occur in many areas after meeting the level of the current secondary standard. Additionally, the data show that visible foliar injury occurrence is geographically widespread and is o ccurring on a variety of plant species in forested and other natural sy stems (see Figure 7-19 in section 7.6.3.2). Linking visible foliar injury to other plant effects is st ill problematic. However, its presence indicates
that other O 3 –related vegetation effects c ould also be present. The presence of visible foliar injury can adversely impact the public welfare. For example, visible foliar injury in national pa rks and wilderness areas can impact the aesthetic experience for both outdoor enthusiasts and the o ccasional park visitor. In addition, because these areas are afforded a higher de gree of protection, the presence of O 3 -induced vegetation effects, including visible foliar in jury, can take on increased signi ficance. Specifically, federal land managers (FLMs) “...have determined th at given the high ecol ogical, aesthetic, and intrinsic value of federal lands, all native species are significant and warrant protection” (NPS, 2000). As a result, FLMs have identified visible foliar injury, along with other O 3 -induced vegetation effects, as air quality related values (AQRV) of co ncern (NPS, 2000). As shown in Appendix 7J, numerous O 3 sensitive species are found on Class I federal lands. In addition, the presence of visible foliar injury also has the po tential to economically impact for those who rely on healthy looking vegetation for th eir livelihood (e.g., horticulturali sts, farmers of leafy crops, landscapers, Christmas tree growers). Many ornamental species have been listed as sensitive to

O 3 (Abt, 1993). Similarly, early senescence of fall fo liage could also diminish the time available for viewing fall foliage, important in some regions of the country in drawing tourists. Although data are not available to allow the quantification of these impacts, the potential for their existence
should not be overlooked.

Exposure-Based Considerations As described in Chapter 7, due to the paucity of rural O 3 monitoring data, it was necessary to select an interpolation met hod that could be used to characterize O 3 air quality over8-8 broad geographic areas. Staff rec ognizes there are inherent uncertain ties in the interpolation that must rely on sparse data that, fo r the most part, are representative of urban and near-urban areas. The interpolation method used for the western U. S. contains additional sources of uncertainty associated with the use of CMAQ model outputs to develop scali ng factors for the interpolation. See section 7.5 of chapter 7 for details on how th e interpolation was cons tructed and how staff quantified the uncertain ties (error and bias) associated with the interpolation. This quantification of exposure uncertainty for th e interpolation represents a notable improvement over the 1996
assessment which did not have an evaluation of the exposure surface. In general, this interpolation method under-predi cts higher 12-hr W126 exposures . Due to the important influence of higher exposures in determining risk s to plants, this feature of the interpolated surface could result in an under-estimation of risks to vegetation in some areas. Taking these uncertainties into account, and given the absen ce of more complete rura l monitoring data, staff judged that this approach was appropriate to us e in developing national vegetation exposure and risk assessments that estimate relative change s in risk for the various alternative standards analyzed. To evaluate changing vegetation exposu res and risks under selected "just meet" scenarios, staff analytically adjusted 2001 base year air quality distribut ions with a rollback method (Horst and Duff, 1995; Rizzo, 2005 & 2006) to reflect “just meeti ng” the current and alternative secondary standard options. This technique combines both linear and quadratic elements to reduce higher O 3 concentrations more than lower one s. In this regard, the rollback method attempts to account for reductions in emissions without greatly affecting lower concentrations near ambient background levels. The following “just meet ” air quality scenarios were generated along with maps for severa l scenarios (see Figures 7-7, 7-8, 7-9, 7-10):

• 4 th -highest daily maximum 8-hr average: 0.084 ppm (the effective level of the current standard) and 0.070 ppm levels

• 3-month, 12-hr. SUM06: 25 ppm-hr (pr oposed in the 1996 review) and 15 ppm-hr levels

• 3-month, 12-hr. W126: 21 ppm- hr and 13 ppm-hr levels Staff’s rationale for selecting these six alternative standards for evaluation is presented here and in section 7.5.1 of Chapter 7. The two 8-hr average levels were chosen as possible
alternatives of the current form for comparison with the cumulativ e seasonal alternative forms. For both the SUM06 and W126 forms, the two levels were selected on the basis of the associated levels of crop yield loss protec tion described in the last revi ew. Specifically, both the upper levels of SUM06 (25 ppm-hr) and W126 (21 ppm- hr) were associated with a level of crop protection of approximately no more than 10% yi eld loss in 50% of crop cases studied in the8-9 National Crop Loss Assessment Network (NCLAN) experiments (section 7.6.2.2.). Alternatively, the lower levels of both SU M06 (15 ppm-hr) and W126 (13 ppm-hr) were associated with a level of crop protection of a pproximately no more than 10% yield loss in 75%
of NCLAN cases. Another level to note is the upper level benchmar k of W126 of 31 ppm-hr that approximates the upper end of the SUM06 range an alyzed in the last review (U.S. EPA, 1996b) and which was associated with no more than 17% yi eld loss in 50% of crop cases as described in
the last review. The above levels have also been associated with varying levels of tree seedling biomass loss protection based on a similar set of tree seedling studies performed by scientists in
the National Health and Environmental Eff ects Research Lab, Western Ecology Division (NHEERL-WED). Under the base year (2001) air quality, a large portion of California had 12-hr W126 above 31 ppm-hr, which has been reported to produce approximately 14% biomass loss in 50% of NHEERL-WED tree seedling studies. Broader multi-state regions in the east and west are predicted to have levels of air quality above the W126 level of 21 ppm-hr, which is approximately equal to the secondary standard proposed in 1996 and is associated with approximately 9% biomass loss in 50% of tree se edlings studied. Much of the east and Arizona
and California have 12-hr W126 values above 13 ppm-hr which has been reported to allow approximately 7% biomass loss in 25% of tree se edlings studied. Althoug h there is appreciable uncertainty associated with these exposure estimates, the results of the exposure assessment indicates that current air quality levels could result in significan t impacts to vegetation in some

areas. When 2001 air quality is rolled back to just meet the curren t 8-hr secondary standard, the overall 3-month 12-hr W126 expos ures do not improve by much (Figure 7-7). Under this scenario, there are still many areas of the country that have seasonal O 3 levels above the 12-hr W126 level of 21 ppm-hr. The exposure maps generated for the 0.070 ppm, 4 th -highest maximum 8-hr average alternative standard, th e SUM06 alternatives of 25 and 15 ppm-hr, and the W126 alternatives of 21 and 13 ppm-hr (Fig ures 7-8, 7-9, 7-10), all showed a markedly improved picture of O 3 air quality compared to the current standard (Figure 7-7). Thus, the staff
observes that all other alternativ e standards, when met at all lo cations, would be expected to provide improved protection of vegetation from seasonal O 3 exposures of concern over the current standard. As expected, however, the grea test improvements in air quality and estimated exposures to sensitive vegetation were observed when just meeting the lower W126 alternative of 13 ppm-hr, the SUM06 alternat ive of 15 ppm-hr, and the 0.07 pp m, 8-hr alternative standard.

Risk-Based Considerations This review continues to rely upon the con centration-response (C-R) functions developed
from OTC exposure systems (also relied upon in the 1996 review). Due to what has been8-10 described in the scientific literature as the “cham ber effect,” some continue to express concern as to the appropriateness of applying OTC generated C-R functions to non-chambered
environments. A shift toward the use of more fi eld-based approaches (e.g., free air exposure and ambient gradient) in recent research has occu rred, providing information in the peer-reviewed literature that at least qualitativ ely informs how one might weigh this concern. These new fieldbased studies, conducted on a limited number of crop and tree seedling species to date, demonstrate plant growth and visible foliar injury responses similar in nature and magnitude to those observed previously under OTC exposure conditions. These findi ngs lend qualitative support to the conclusion that OTC conditions do not fundamentally alte r the nature of the O 3 - plant response. A related concer n with respect to the use of the OTC C-R functions for crops is the concern that the crop vari eties grown today may have O 3 sensitivities significantly different than those used to derive the NCLAN crop and OTC tree seedling C-R func tions which are relied upon in this review. Nothing in the recen t literature, however, suggests that the O 3 sensitivity of crop or tree species studied in th e last review and for which C- R functions were developed has changed significantly in the intervening period. Indeed, in the few recent studies where this is examined, O 3 sensitivities are found to be as great or greater than those observed in the last review. As a result, staff conti nues to rely on the C-R functions av ailable in the last review for predicting relative crop yield a nd tree seedling biomass loss potenti als across a range of possible
ambient O 3 exposures. An additional source of uncertainty not desc ribed or accounted for in the last review is that associated with the pr esence of a decreasing O 3 gradient from the height of the monitor probe down to the lower plant canopy heights for most crop and seedling trees. The presence of this gradient makes less certain the predictions of current crop and tree seedling exposures and the associated yield and biomass losses, respec tively, based on ambien t monitor data. Staff selected a 10% reduction factor to represent the ma ximum gradient believed to occur for daylight hours. However, recognizing th at the actual downward adjustme nt value varies depending on interactions between numerous plan t and site-specific factors, staff chose to present estimates ofyield and biomass loss for each crop and tree seedling species, respectively, as a range, with nonadjusted and 10%-adjusted air quality as the upper and lower bounds (See Chapter 7, section 7.6.2.3 for a detailed discussion). Seedling and Mature Tree Biomass Loss

. Biomass loss in sensitive tree seedlings is predicted to occur under O 3 exposures that just meet the level of the current secondary standard (see Table 7F-5 in Appendix 7F). For instance, black cherry, ponderosa pi ne, eastern white pine, and aspen had estimated median seedling bi omass losses as high as 24, 11, 6, and 6%, respectively, when air quality was rolled back to just meet the current 8-hr standard with the 10% adjustment applied. Staff notes that these results are for tree seedlings and that mature trees of8-11 the same species may have more or less of a response to O 3 exposure. Due to the potential for compounding effects over multiple years, a consensus workshop on O 3 effects reported that a biomass loss greater than 2% annually can be significant (Heck and Cowling, 1997). Decreased seedling root growth and survivability could a ffect overall stand health and composition in the long term. Our analysis using modeled mature tree growth response under different air quality scenarios for a western species (ponderosa pine) and two eastern species (red maple and tulip poplar) projected that just meeting the curren t standard would likely continue to allow O 3 -related reductions in annual net biomass gain in these species (see Table 7-5 in Chapter 7). This judgment is based, in part, on model outputs that estimate that as O 3 levels are reduced below those of the current standard, si gnificant improvements in growth would occur. For instance, estimated growth in red maple increased by 4% and 3% at Big Meadows and Cranberry sites, respectively, when air quality was rolled b ack to just met a SUM06 value of 15 ppm-hr (approximately equivalent to a W126 value of 13 ppm-hr). Yellow poplar was projected to have a growth increase between 0.6 and 8% under the same scenarios at the two sites. Though there is significant uncertainty associat ed with this analysis, we judge that this information should be given careful consideration in light of seve ral other pieces of evidence. Specifically, limited evidence from experimental studies that goes beyond the seedling growth stage continues to show decr eased growth under elevated O 3 (King et al. 2005). Some mature
trees such as red oak have shown an even greater sensitivity of photosynthesis to O 3 than seedlings of the same species (Hanson et al., 1994). As indicated above, smaller growth loss increments may be significant for perennial spec ies. The potential for cumulative “carry over” effects as well as compounding must be consider ed. The accumulation of such “carry-over” effects over time may affect long-term survival and reproduction of individuals and ultimately
the abundance of sensitive tree species in forest stands. Crop Yield Loss. Staff exposure and risk assessme nts estimate that just meeting the
current 8-hr standard would still allow O 3 –related yield loss to o ccur in several fruit and vegetable species and major commodity crop species currently grown in the U.S. (see Table 7F-4 in Appendix 7F). These estimates are substantially lower than thos e estimated in the last review
as a result of several factors. First, O 3 air quality has improved in many areas of the country
since the last review. Secondl y, staff has factored in an O 3 adjustment for the height gradient, as described above, and will present results for bot h non-adjusted and adjusted exposure levels to approximate upper and lower bounds of predicted yield loss. Several sources of uncertainty should be taken into account when evaluating the significance of these findings. Fi rst, yield loss estimates were generated using the median C-R
function when more than one function was availa ble for a given species. For some species,8-12 however, only one C-R function was av ailable. In this latter cas e, there is more uncertainty regarding the range of variability in O 3 sensitivity within each crop. Secondly, six of the fruit and vegetable species were not part of the NC LAN program and C-R func tions were available only in terms of seasonal 7-hr or 12-hr mean indi ces. These indices are considered less effective in predicting plant response for a given change in air quality than cumulative forms used with other crops. Therefore, staff places less weight on the fruit and vegetable yield loss numbers than those for commodity crops, even though the ma gnitude of the fruit and vegetable effect was much greater. Finally, staff recognize that agricultural systems are heavily managed and vulnerable to adverse impacts from a variety of other factors (e.g., weather, insects, disease), which can overshadow the magnitude of yield impacts predicted for a given O 3 exposure. However, it should also be recognized that, in some experimental cases, exposure to O 3 has made plants more sensitive or vulnerabl e to other important stressors such as disease, insect pests, and harsh weather (U.S. EPA, 2006). Due to the signif icant impact these othe r stressors can have on crop production in some areas, staff recommends that additional research be done to better understand the nature and significance of these interactive effects of O 3 with other plant

stressors. Keeping these uncertainties in mind, the result s of the risk assessment show that when air quality is rolled back to just meet the current standard, yield loss is still estimated to occur in several fruit and vegetable speci es and major commodity crop species currently grown in the U.S. (see 7.6.2.4 of Chapter 7). For example, based on median C-R function response, in counties with the highest O 3 levels, potatoes and cotton had es timated yield losses of 9-15% and 5-10%, respectively, when ai r quality just met the level of the current standard. Estimated yield improved in these counties when the alternative SUM06 and W126 standard levels were met. The very important soybean crop had generally small yield losses thr oughout the country under current air quality (0-6%) and just m eeting the current standard (0-4%). Another group of crops, multiple year forage crops, have also received additional study since the last review. Based on these new studies, the yields and quality of multiple-year forage crops have also been shown to be sufficientl y reduced as to have nutritional and possibly economic implications for their use as ruminant animal feed at O 3 exposures that occur in some years over large areas of the U.S. However, it is not clear at th is time to what degree they are impacted at lower levels of air quality, since the studies were not desi gned to address this question.

Summary In summary, O 3 levels that would be expected to remain after meeting the level of the current secondary standard are sufficient to caus e visible foliar injury, seedling and mature tree growth, and reduce cr op yields. Other O 3 -induced effects described in the literature include an8-13 impaired ability of many sensitive species and ge notypes within species to adapt to or withstand other environmental stresses such as freezing temperat ures, pest infestations and/or root disease, and reduced ability to compete for available re sources. In the long run, the result of these impairments (e.g., loss in vigor) may be prem ature plant death. Though effects on other ecosystem components have not been examined, ex cept in isolated cases, effects such as those described above could have significant implicatio ns for plant community and associated species biodiversity and the structure and function of whole ecosyst ems (Young and Sanzone, 2002).

8.3.1.2 CASAC and Public Commenter Views on the Adequacy of the Current Standard Staff recognizes that the expos ure-and risk-based informati on can be considered both in
terms of whether the risks estimated to remain upon attaining the current standard are important from a public welfare perspective and/or whether additional reductions in risk estimated to be associated with alternative, more protective st andards are also important from a public welfare perspective. Judgments about th e importance of the estimates of exposure and risks need to take into account the important uncertainties associated with such estimates. There is general recognition among staff, CA SAC, and all interested parties that public welfare policy judgments, includi ng the weight to place on various types of evidence and how to weigh the importance of estimated risks in a public welfare perspective, are ultimately decisions left to the Administrator. To help inform thos e judgments with regard to the adequacy of the current secondary O 3 standard, the views expressed by CA SAC as well as the views of other interested parties who have commented on earlier dr afts of this document are summarized here. The range of views generally refl ects differing judgments as to th e relative weight to place on various types of exposure- and risk-based inform ation, and the associated uncertainties, as well as differing judgments about th e importance of various O 3 -related vegetation effects from a public welfare perspective.
In a letter to the Administra tor (Henderson, 2006c), the CASAC O 3 Panel, with full endorsement of the chartered CASAC, unanimous ly concluded that “despite limited recent research, it has become clear since the last re view that adverse effect s on a wide range of vegetation including visible foliar injury are to be expected and have been observed in areas that
are below the level of th e current 8-hour primary and seconda ry ozone standards...” Therefore, “based on the Ozone Panel’s review of Chapters 7 and 8, the CASAC unanimously agrees that it is not appropriate to try to pr otect vegetation from the substan tial, known or anticipated, direct and/or indirect, adverse effects of ambient ozone by continuing to promulgate identical primary and secondary standards for ozone. Moreover, th e members of the Committee and a substantial8-14 majority of the Ozone Panel agrees with EPA staff conclusions and encourages the
Administrator to establish an al ternative cumulative secondary standard for ozone and related photochemical oxidants that is dis tinctly different in averaging time, form and level from the currently existing or potentially revised 8-hour primar y standard” (Henderson, 2006c).
In contrast to the views of CASAC disc ussed above, others submitted comments that supported retaining the current standards. 1 In considering the available evidence as a basis for their views, these commenters iden tified a number of key concerns that, in their view, make it inappropriate to revise the secondary standard at this time. For ex ample, they assert: 1) The key uncertainties cited by the Administrator in the 1997 review as reasons for deciding it was not appropriate to move forward with a seasonal seco ndary, (e.g., uncertainties in the exposure, risk and valuation analyses and the lack of air quality data in rura l and remote areas), have not been materially reduced in this curre nt review; and 2) The exposure assessment is inaccurate and too
uncertain due to the use of low estimates of policy-relevant background (PRB), an arbitrary rollback method that is uninformed by atmos pheric chemistry from photochemical models, and the use of the CMAQ model in the west, whose biases and uncertainties are insufficiently
characterized and evaluated.

8.3.1.3 Staff Conclusions on the Adequacy of the Current Standard On the basis of the vegetation effects that have been observed to still occur under current ambient exposure conditions and those predicted to occur under the scenario of just meeting the current secondary NAAQS, staff co ncludes that the current seconda ry NAAQS is inadequate to protect the public welfare from known and anticipated adverse we lfare effects. As discussed above, this conclusion derives from several lines of evidence. First, visible foliar injury observation s for the years 2001 to 2004 at USDA FIA biomonitoring sites show widespread O 3 –induced effects occurring in the field, including in forested ecosystems. For a few studied species, it has been further shown that the presence of visible foliar injury is linked to the presen ce of other vegetation e ffects (e.g., reduced plant growth and impaired below ground root deve lopment) (U.S. EPA, 2006), though for most species, making this linkage remains problematic. Nevertheless, when visible foliar injury is present, the possibility that other O 3 -induced vegetation effects coul d also be present should be considered. Staff recogni zes that it is not possibl e at this time to quant itatively assess the degree of visible foliar injury that should be judged adverse in all se ttings and across all species, and
that other environmental factors can mitigate or exacerbate the degree of O 3 -induced visible foliar injury expressed at a ny given concentration of O 3 . However, recognizi ng that the presence

1 This group of commenters included industry associations, corporations, and individuals.8-15 of visible foliar injury alone can be adverse to the public welfare (see foliar injury discussion in 8.3.1.1), and on the basis of the above considerations , staff concludes that the current standard continues to allow levels of visible foliar inju ry that could reasonably be considered to be adverse from a public welfare perspective. Second, a recent ambient gradient study and a free air O 3 enrichment (FACE) experiment have supported earlier findings from O 3 experiments conducted in OT C. Studies conducted at the AspenFACE site in Wisconsin (see secti on 7.6.2.1 of chapter 7) on quaking aspen has
confirmed the detrimental effects of O 3 exposure on tree growth in a field study without chambers (Isebrands et al., 2000, 2001). The rece nt ambient gradient study (Gregg et al, 2003) evaluated biomass loss in cottonwood along an ur ban-to-rural gradient at several locations. Study results found that conditions in the field were sufficient to produce substantial biomass loss in cottonwood, with larger impacts observed in downwind rural areas due to the presence of higher O 3 concentrations (See Sectio n 7.6.3). Staff’s inclusion a nd emphasis on these two fieldbased lines of evidence is consistent with the Ad ministrator’s conclusion at the end of the last review (62 FR 38877-78), that contin ued research on the effects of O 3 on vegetation under field conditions would be important in this next review. Staff feel s that the expanded field-based evidence provides qualitative s upport for the conti nued usefulness of findings obtained from
chamber studies. Staff’s conclusion is further strengthene d by evidence of remaining impacts on tree seedling biomass loss when the current 8-hr standa rd is met. Staff estimated annual biomass loss up to 6-24% for some sensitive species in areas of high O 3 exposure. Because of the potential for indirect effects on plant vigo r from even small incremental biomass or growth reductions in the field, staff observes that these levels of tr ee seedling growth reduction are well above the 1- 2% range of concern identified by the 1997 c onsensus workshop (Heck and Cowling, 1997).
Staff also took into account modeled mature tr ee growth loss estimates and commodity crop and fruit and vegetable yield loss in arriving at these conclusions. Li nkages across ecosystem hierarchies (Young and Sanzone, 2002) make indire ct impacts to ecosystems another welfare effects category of concern even after a ttaining the current secondary standard.

8.3.2 Pollutant Indicator

The staff concludes that O 3 remains the appropriate pollu tant indicator for use in a secondary NAAQS that provide s protection for public welfare from exposure to all photochemical oxidants. This conclusion is ba sed on the same rationale presented in the previous Staff Paper (U.S. EPA, 1996b), which recognizes that among the other photochemical oxidants, the database for vegeta tion effects only raises concern at levels found in the ambient air8-16 for O 3 and, therefore, control of ambient O 3 levels provides the best means of controlling other photochemical oxidants of pot ential welfare concern.

8.3.3 Averaging Times Plants, unlike people, are exposed to ambien t air 24 hours a day, every day for their entire life. For annual species, this is for only a peri od within one year; for pe rennials, exposures are for multiple years, decades or centuries. Regardless of plant type, it has been well established in
the literature that O 3 effects are cumulative, and that l onger exposure durations have a greater impact than shorter durations, all else being e qual (U.S. EPA, 2006). Air quality indices that account for the exposure duration overall do a better job predicting plant response than short- or long-term averages. However, O 3 levels are not continuously elev ated and plants are not equally
sensitive to O 3 over the course of a day, season or lif etime. Thus, it becomes necessary to identify periods of exposure that have the most relevance for plant response.

8.3.3.1 Seasonal Window Many recent studies described in the 2006 CD have specifically selected exposure indices that take into account the cumulative, concentration-weighted impact of O 3 -induced effects throughout the growing season when measuring grow th and yield impacts and have substantiated the 1996 CD and 1996 Staff Paper conclusions on the importance of cumulative, seasonal exposures (U.S. EPA, 2006). A nnual crops are typically grown for periods of two to three months before being harvested. In contrast, perennial species may be photosynthetically active longer (up to 12 months each year for a few sp ecies) depending on the species and where it is grown. In general, the period of maximum physiological activity and thus, potential O 3 uptake for annual crops, herbaceous species, and deciduous trees and shrubs coinci des with some or all of the intra-annual period defined as the O 3 season, which varies on a state-by-state basis. This is because the high temperature and high light conditions that promote the formation of tropospheric O 3 also promote physiologica l activity in vegetation. In the 1996 Staff Paper and proposal notice, we noted that the selection of any single averaging time for a national standard would represent a compromise, given the significant variability in growth patterns and lengths of growing seasons among the wide range of vegetation species that may experience adverse effects associated with O 3 exposure. However, we concluded, based on the information available at that time, that selection of the maximum consecutive 3-month period within the O 3 season was reasonable, and in most cases, would most likely coincide with the periods of greatest plant sens itivity on an annual basis. Based on the information assessed in the current CD (U.S . EPA, 2006) and Chapter 7 above, we again
conclude the maximum consecutive 3-month period within the O 3 season is a reasonable averaging time for vegetation.8-17 8.3.3.2 Diurnal Window Stomata are the entry points for O 3 into plant leaves. Over the course of a day, plant stomatal conductance varies along wi th light level, soil moisture a nd other factors. In general, stomata are most open during daylight hours in order to allow sufficient CO 2 uptake for use in carbohydrate production through the light driven process of phot osynthesis. At most locations,

O 3 concentrations are also highest during the daytime, potentially co inciding with maximum stomatal uptake. Ozone uptake during daylight hours impairs the li ght-driven process of photosynthesis, which can then lead to im pacts on carbohydrate production, plant growth, reproduction (yield) and root functio n. Thus, in the last review, st aff selected the 12-hr daylight window (8 am to 8 pm) to capture the diurnal wi ndow with most relevan ce to the photosynthetic process. Since that time, some limited work has been done by Musselman and Minnick (2000) to more fully characterize O 3 uptake at night and its potential contribution to total plant uptake and response

. This work reports that some species do take up O 3 at night, but that the degree of nocturnal stomatal conductance varies widely between species and its relevance to overall O 3 - induced vegetation effects remain unclear. We c onclude that such inform ation continues to be preliminary and not generalizable at this time (s ee also Appendix 7A of Chapter 7). Staff, therefore, again concludes that the daytime 12-hr window is th e most appropriate period over
which to cumulate diurnal O 3 exposures, specifically those most relevant to plant growth and yield responses.

8.3.3.3 Alternative Views and Staff Conclusions The CASAC expressed views in agreement w ith staff with respect to both seasonal and diurnal averaging times. Specifi cally, CASAC states “the suggest ed approach to the secondary standard is a cumulative seasonal growing st andard such as the indices SUM06 or W126 aggregated over at least the three summer months exhibiting the highest cumulative ozone levels and includes the ozone exposures fr om at least 12 daylight hours.” In contrast, some commenters pointed to new information on nocturnal conductance as
evidence for the need for a 24-hour diurnal windo w. Specifically, they state “an extensive review of the literature reported that a large num ber of species had varying degrees of nocturnal
stomatal conductance.” Based on this review , Musselman and Minnick (2000) recommend that any O 3 exposure index used to rela te air quality to plant response should use the 24-hour cumulative exposure period. No commenters a ddressed the adequacy of the three month seasonal window. In examining the availabl e information on nocturnal conductance (See Appendix 7A), staff concludes that it remains unclear to what exte nt nocturnal upta ke contributes to the vegetation effects of yiel d loss, biomass loss or visible foliar injury. Due to the many species- and site-specific variables that influenc e the potential for and significance of nocturnal8-18 uptake, staff concludes that additio nal research needs to be done before consideri ng whether this component of vegetation exposur e should be addressed with a different averaging time. Based on these considerations, as well as in formation assessed in the current CD (U.S. EPA, 2006) and Chapter 7 above, we again conclude that a 12-hr (8:00 am to 8:00 pm) diurnal window remains appropriate for a secondary NAAQS designed to protect a wide range of vegetation growing in environmen tal conditions found across the U.S

.

8.3.4 Form of the Standard

The 2006 O 3 CD states, “In the 1996 O 3 CD..., it was concluded, based on the best available data, that those O 3 exposure indices that cumulated differentially weighted hourly
concentrations were the best candidates for re lating exposure to plant growth response.... The
few studies that have been published since the 1996 O 3 CD continue to support the earlier conclusions...” (U.S. EPA, 2006, pg. 9-12). The following selections taken from the 1996 CD (see U.S. EPA, 1996a, pgs. 5-88/89, 5-95/96), further elucidate the depth a nd strength of these
conclusions. “When O 3 effects are the primary cause of vari ation in plant response, plants from replicate studies of varying durat ion showed greater reductions in yield or growth when exposed for the longer duration.” “The mean exposure index of unspecified duration could not account for the year-to-year variation in response.” “Because the mean exposure index treats all concentrations equally and doe s not specifically include an exposure duration component, the use of a mean exposure index for characterizi ng plant exposures appears inappropriate for relating exposure with vegetation effects” Though the scientific ju stification for a cumulative, seas onal form was generally accepted in the last review, an analys is undertaken by EPA at that ti me had showed that there was considerable overlap between areas that would be expected not to meet the range of alternative 8-hr standards being considered for the primar y NAAQS and those expect ed not to meet the range of values (expressed in terms of the seas onal SUM06 index) of concern for vegetation. This result suggested that improve ments in national air quality exp ected to result from attaining an 8-hr primary standard within the recommended range of levels would also be expected to reduce levels below those of concern for vegetati on in those same areas. Thus, in the proposal notice, the Administrator proposed two alternatives for consider ation: one alternative was to make the secondary standard equal in ever y way to the proposed 8-hr, 0.08 ppm primary standard; and the second was to establish a 3- month, 12-hr SUM06 seasonal secondary standard (set at a level of 25 ppm-hr) as also appropr iate to protect public welfare from known or anticipated adverse effects given the available scientific knowledge and that such a seasonal standard “...is more biologically relevant...” (61 FR 65716). In the 1997 final rule, the decision was made to make the secondary identical to the primary standard. It acknowledged, however,8-19 that “it remained uncertain as to the extent to which air quality improvements designed to reduce 8-hr average O 3 concentrations averaged over a 3-year period would reduce O 3 exposures measured by a seasonal SUM06 index.” (62 FR 38876) In other words, it was uncertain as to whether the 8-hr average form would, in prac tice, provide sufficient protection for vegetation from the seasonal, cumulative and concentration-we ighted exposures descri bed in the scientific
literature as of concern. On the basis of that history, Chapters 2 and 7 of this Staff Paper revisited the issue of the appropriateness of using an 8-hr average standard form to pr ovide the requisite protection required for vegetation.

8.3.4.1 Comparison of 8-Hour Average and Cumulative Seasonal Forms Staff performed an analysis to evaluate the extent to which there appears to be a relationship between county level air quality measured in terms of the current 8-hr average form
and that measured in terms of an alternative cumulative, seasonal form (e.g. 12-hr W126). Staff determined it was most useful to begin by compar ing the 3-year averages of each form, since the current 8-hr average secondary form is a 3-year average. However, in recognition that some vegetation effects (e.g. crop yield and folia r injury) are driven solely by annual O 3 exposures, and that typically the cumulative forms are defi ned in terms of the a nnual growing season, staff also performed a comparison of the current 8-hr form to the annual W126 air quality values for both 2002 and 2004 (see Appendix 7B). Staff performed this analysis using recen t (2002-2004) county-level air quality data from AQS sites and the subset of CASTNET sites having the highest O 3 levels for the counties in which they are located. Due to the lack of more complete monitor coverage in many rural areas, staff acknowledges that this analysis may not be an accurate reflection of the situation in nonmonitored, rural counties. Results of the 3-year average comparison showed that after meeting the current 3-year average form of the 0.08-ppm, 8-hr average standard, only a few counties showed 3-year average W126 values above the upper level (21 ppm-hr) evaluated (see Figure 7- 1). This result, taken alone, might suggest that areas that met the current level and form would typically overlap with the areas that met the an alyzed alternative cumulative level and form. However, at the lower W126 leve l of 13 ppm-hr (see discussion on level in section 8.3.5 below), many more counties that meet th e current 8-hr standard level and form no longer meet the
alternative W126 form at this level. When individual ye ars are compared, this lack of a relationship becomes clearer. For example, the relatively high 2002 air quality year, showed a greater degree of overlap between those areas that would meet the levels analyzed for the current
8-hr and alternative W126 forms than did the relatively low 2004 air quality year (See Appendix 7B). It is clear from this analysis that the degree to which the current 8-hr standard form and8-20 level would overlap with areas of concern for vegetation expressed in terms of the 12-hr W126
standard is inconsistent and w ould depend greatly on the level of the 12-hr W126 and 8-hr forms selected and the distribution of hourly O 3 concentrations within the a nnual and/or 3 year average period. It is not clear how this relationship would change due to the change in O 3 patterns resulting from control strategies put in place to attain different levels of standards.
This view is consistent with those of CASAC who unanimously ag ree that it is not appropriate to try to protect vege tation from the substantial, know n or anticipated, direct and/or indirect, adverse effects of ambient ozone by c ontinuing to promulgate identical primary and secondary standards for ozone. Moreover, the me mbers of CASAC and a s ubstantial majority of
the CASAC O 3 Panel agree with staff conclusions and encourage the Administrator to establish an alternative cumulative secondary standard fo r ozone and related photo chemical oxidants that is distinctly different in averag ing time, form, and level from the currently existing or potentially revised 8-hour primary standard. The suggested approach to the sec ondary standard is a cumulative seasonal growing standard such as the indices SUM06 or W126 aggregated over at
least the three summer months e xhibiting the highest cumulative O 3 levels and includes the O 3 exposures from at least 12 day light hours (Henderson, 2006c). Some other public commenters agreed that “directionally a cumulative form of the standard may better match the underlying data.” Ho wever, they believe further work is needed to determine whether a cumulative exposure index for the form of the secondary standard is needed. Specifically, a few co mmenters were of the view that a W126 (or SUM06) was not
sufficient in and of itself but s hould be combined with a measure of the number of peaks above 100 ppb (N100). Some of these same commenter s also felt a 24-hr averaging time was supported by the data on noctu rnal stomatal conductance. Staff recognizes that th e relationship between O 3 exposure and plant response is more complex than described by the single component indices and supports the need for further research into improvements on such indices to be tter capture factors that influence flux. Staff also recognizes that meeting the current 8-hr st andard would result in air quality improvements that could potentially benefit vegetation in some areas. However, at this time, based on the weight of evidence in the scientific literature demonstrating the cumulative nature of O 3 -induced plant effects and the need to give greater weight to higher concentrations, the advice of CASAC consistent with this view, and the results of the above analysis, staff again concludes that a secondary standard should, at a minimum, be defi ned in terms of a form that reflects the two components of exposure known to influence plant response, i.e. differen tially weighted peak concentrations and cumulative seasonal exposures . Further, staff sugge sts caution should be used in evaluating the likely vegetation impacts associated with a given level of air quality expressed in terms of the 8-hr form in the ab sence of parallel SUM06 or W126 information.8-21 Selecting a more biologically-r elevant secondary standard form would also: 1) be directly responsive to the recommendation of the 2004 National Research Counc il’s report titled Air Quality Management in the United States (NRC, 2004) which encourages the Agency to evaluate its historic practice of setting the secondary NAAQS equal to the primary; 2) provide support to important new Agency initiatives to enha nce ecosystem-related program tracking and accountability; and 3) potentially spur more polic y relevant vegetation effects research in the
future.

8.3.4.2 Comparison of SUM06 and W126 Cumu lative, Concentration-Weighted Forms In addition to evaluating the 8-hr average fo rm, we evaluated the appropriateness of the SUM06 alternative proposed in the last revi ew by comparing it to another cumulative, concentration-weighted form discussed in th e 1996 Staff Paper, the W126 index. In the 1996 Staff Paper, the preference for the SUM06 over other cumulative forms was based on the following science and policy considerations:

• All cumulative, peak-weighted exposure indices considered, including W126 and SUM06, were about equally good as exposure measures to predict exposure-response relationships reported in the NCLAN crop studies.

• The SUM06 form would not be influenced by PRB O 3 concentrations (defined at the time as 0.03 to 0.05 ppm) under many typi cal air quality distributions. In the current review, we have reconsider ed whether the SUM06 form should still be judged the most appropriate cumulative form fo r a secondary NAAQS pr otective of vegetation and ecosystems, based on the following:

• Model predictions of PRB in the range of 0.015 to 0.035 ppm for the current review are below the PRB range of 0.03 to 0.05 ppm de scribed in the 1996 review, making PRB contributions much less of a factor influenc ing the choice of an appropriate cumulative index.

• There is no evidence in the extensive vegetation effects literature of a biological exposure threshold applicable across the broad array of O 3 -sensitive species found growing in the U.S. The SUM06 index, with a threshold set at 0.06 ppm, artificially truncates exposures that have been show n to produce vegetation effects of concern given sufficient duration. The W126 i ndex, on the other hand, cumulates all O 3 concentrations. However, because concentrations below 0.04 ppm, receive substantially smaller weights (3 percent or less), those con centrations within the range of PRB levels would not contribute signi ficantly to the value of the index.

The CASAC Ozone Panel also views the 3-month growing season W126 index “...as a potentially more biologically -relevant index than the 3-m onth growing season SUM06 index.
This is because the W126 index has no absolu te minimum ozone concentration threshold and8-22 only lightly weights the lower ozone concentrat ions. Therefore, a three-month seasonal W126 range that is the approximate equivalent of th e SUM06 range of 10 to 20 ppm-hr is preferred” (Henderson, 2006c). On the basis of the information highlighted above, staff concludes that the W126 form is a more appropriate biologically based and polic y-relevant cumulative, concentration-weighted
form and recommends the Administrator consider the W126 as a more appropriate form for the secondary standard. This recomm endation is consistent with th e views of CASAC. Given the legitimate policy interest in having a more stable standard form, the Administrator may want to give consideration to using a 3-year average of the 12-hr W126, in addition to consideration of
an annual form.

8.3.5 Level of the Standard The level at which a secondary standard s hould be set depends on a blending of science and policy judgments by the Administ rator as to the level of air quality which is requisite to protect the public welfare from any known or anticipated advers e effects associated with the pollutant in the ambient air. The exposure and risk assessments conducted in Chapter 7 and summarized briefly above, provide information regarding the effects associated with a number of different welfare endpoints at diffe rent levels of air quality, ofte n expressed in terms of both the current 8-hr average form and the W126 (or SUM06) seasonal form(s). At the end of the last review, we identifie d a range for a 3-month, 12-hr SUM06 standard form of 25 to 38 ppm-hr, for the Administrator’s consideration. These leve ls were estimated to allow 10% to 20% yield loss, respectively, to oc cur in no more than 50% of the studied NCLAN agricultural crop cases. These levels were also estimated to provide an increased level of protection for other categories of vegetation such as tree seedlings and mature trees in commercial, Class I, and other forested areas in urban, rural, and remote environments. It was recognized, however, that a standard set within this range would not protect the most sensitive species or individuals within a species from all potential effects related to O 3 exposures. The Administrator proposed the lower end of the range (e.g., 25 ppm-h r) as necessary to provide a requisite level of protection for vegeta tion against the adverse effects of O 3 . Staff believes that this level is an appropriate uppe r bound for a range of levels recommended for consideration in this review, as it would continue to provide a level of crop and tree protection judged requisite by
the Administrator in the last re view. In addition, this level derives from the extensive and quantitative historic and recent cr op effects database, as well as current staff exposure and risk analyses. In identifying a lower bound for the range of alternative standard levels appropriate for consideration, staff concludes th at several lines of evidence po int to the need for greater8-23 protection for tree seedlings, mature trees, and asso ciated forested ecosystems. Tree growth is an important endpoint to consider becau se it can be related to other as pects of societal welfare such as sustainable production of timber and related goods, recreat ion, and carbon (CO 2 ) sequestration. Equally important, impacts on tr ee growth can also affect ecosystems through shifts in species composition and the loss of genetic diversity due to the loss of O 3 sensitive individuals or species. To help inform staff judgment about an a ppropriate level of protection to consider for trees, staff consider ed the results of a consensus- building workshop on the need for a long-term cumulative secondary O 3 standard. At this workshop, expert scientists expressed their judgments on what standard form(s) and le vel(s) would provide ve getation with adequate protection from O 3 -related adverse effects. Consensus wa s reached with respect to selecting appropriate ranges of levels in terms of a 3- month, 12-hr SUM06 standard for a number of vegetation effects endpoints. Th ese ranges are identifie d below, with the es timated approximate equivalent W126 shown in pare ntheses (See Appendix 7B for explanation of SUM06 to W126 equivalents). For yield reductions in agricultural crops – a range of 15 to 20 (13 to 17) ppm-hr; for growth effects to tree seedlings in natural fore st stands – a range of 10 to 15 (7 to 13) ppm-hr; for growth effects to tree seedlings and saplings in plantations – a range of 12 to 16 (9 to 14) ppm-hr; and for visible foliar injury to natural ecosys tems – a SUM06 range of 8 to 12 (5 to 9) ppm-hr (Heck and Cowling, 1997). In the 1997 final rule, the Admi nistrator had pointed to the results of this workshop as providing important support to her view that the then current secondary standard was not adequately protective of vegetation, contributing to her rationale that revision of the secondary standard was needed (62 FR 38877) In its October 24, 2006 letter to the Administ rator, CASAC expresse d its view regarding the appropriate form and range of levels fo r the Administrator to consider. The CASAC preferred a seasonal 3-month W126 st andard in a range that is the approximate equivalent of the SUM06 at 10 to 20 ppm-hrs. Staff has determin ed that the approximate equivalent 3-month W126 range is 7 to 17 ppm-hrs. The lower end of this range (7 ppm-hr) is the same as the lower end of the range identified in the 1997 Consensu s Workshop as protective of tree seedlings in natural forest stands from grow th effects (Heck and Cowling, 1997).
Staff believes that O 3 -related effects on forest tree speci es are an important public welfare
effect of concern. Therefore st aff concludes that it is appropri ate to include as the lower bound of the recommended range, the lower end of the approximate range recommended by CASAC (Henderson, 2006c). Based on our analyses of risks of tree seedling biomass loss and mature tree growth reductions and on the ba sis of the scientific effects lit erature, we anticipate that the lower end of the range identified for the Admi nistrator’s consideration would substantially
decrease the adverse effects of O 3 on forested ecosystems. Additionally, it is anticipated that the lower end of this range would pr ovide increased protection from the more subtle impacts of O 38-24 acting in synergy with other natu ral and man-made stressors to a dversely affect individual plants, populations and whole systems. By disrupti ng the photosynthetic process, decreasing carbon storage in the roots, increasing early senescence of leaves and affecting water use efficiency in trees, O 3 exposure could potentially disr upt or change the nutrient and water flow of an entire system. Weakened trees can become more suscep tible to other environmental stresses such as pest and pathogen outbreaks or harsh weather co nditions. Though it is not possible to quantify all the ecological and societal benefits associated with va rying levels of a lternative secondary standards, we conclude that th is information should be weighed in considering the extent to which a secondary standard should be precautionary in nature in protecting against effects that have not yet been adequately studied and evaluated. Based on all the above considerations, sta ff concludes that a 3-month, 12-hr W126 range of 21-7 ppm-hr is appr opriate for consideration, with th e upper bound equivalent to that proposed in the last review and with the lower bound being that recommended by CASAC. In the absence of any informa tion regarding a threshold of O 3 exposures for vegetation, staff recognizes that the level selected is largel y a policy judgment as to the requisite level of protection needed. In determining the requisite level of protection for crops and trees, the Administrator will need to weigh the importance of the predicted risks of these effects in the overall context of public welfar e protection, along with a determ ination as to the appropriate weight to place on the associated uncertainti es and limitations of this information.

8.3.6 Summary of Staff Conclusions and Recommendations on the Secondary O 3 Standard

Staff conclusions and recommendations on the elements of the secondary O 3 standard for
the Administrator’s consideration in making decisions on the secondary O 3 standard are summarized below, together with supporting conclusions from s ections 8.3.3 to 8.3.5 above. We recognize that selecting from among alternat ive policy options will necessarily reflect consideration of qualitative and quantitative uncertain ties inherent in the relevant evidence and in the assumptions of the quantitative exposure and risk assessments. Any such standard should protect public welfare from any known or antici pated adverse effects associated with the presence of the pollutant in th e ambient air. In recommending these options for consideration, we are mindful that the Act requi res standards that, in the judgme nt of the Administrator, are requisite to protect public welfare. The standards are to be neither more nor less stringent than

necessary. In the last review, the Admi nistrator took into account the following in reaching her final decision: 1) the varying degrees of protection afforded by the alternative primary standards recommended; 2) the incremental protection asso ciated with alternativ e cumulative, seasonal8-25 secondary standards under consideration; 3) th e value of establishing a seasonal form for the secondary standard that is more representative of biologically relevant exposures; and 4) the extent to which a secondary standard should be precautionary in nature, given the possibility of

O 3 impacts acting in synergy with other natura l and manmade stressors to impact climate and other environmental endpoints, pa rticularly given the potential si gnificance at a regional scale
and in Class I areas. Staff notes that since the last review, se veral additional policy-relevant developments have occurred that may also warrant considera tion by the Administrator when making decisions about what is requisite to protect public welfare. First, the Agency has undertaken a number of activities geared toward improving ecosystem-related program tracking and accountability and is currently engaged in efforts to identify releva nt indicators for that pu rpose. Having a more biologically-relevant air quality index would allow the Agency to better track improvements in vegetation protection on the ground w ith specific program actions aimed at accomplishing that end. Second, the NRC report (described above) stat es: “Whatever the reason that led EPA to use identical primary and secondary NAAQS in the past , it is becoming increasingly evident that a new approach will be needed in the future. Ther e is growing evidence that the current forms of the NAAQS are not providing adequate protectio n to sensitive ecosystems and crops” (NRC, 2004). The following secondary standard recomme ndations encompass the breadth of policyrelevant considerations described above:

(1) It is appropriate to continue to use O 3 as the indicator for a sta ndard that is intended to address effects associated with exposure to O 3, alone or in combination with related photochemical oxidants. Based on the available information, we conclude that there is no basis for considering any altern ative indicator at this time.

(2) It is not appropriate to continue to use an 8-hr aver aging time for the secondary O 3 standard. The 8-hr average form should be replaced with a cumulative, seasonal, concentration weighted form. Given the reasons stated in earlier di scussions herein, staff concludes that the W126 form is more appr opriate than the SUM06 form recommended
in the last review.

(3) It is appropriate to consider the ma ximum consecutive 3 month period within the O 3 season as the seasonal averaging tim e over which to cumulate hourly O 3 exposures for the daily 12-hr daylight (8 am to 8 pm ) window. Though the length of time in the growing season varies significantly between sp ecies, staff concludes that the 3-month8-26 period of maximum O 3 exposure generally coincides w ith maximum biological activity for most plants. Staff notes th at for certain welfare effects of concern (e.g ., foliar injury, yield loss for annual crops, growth effects on other annual vegetation and potentially tree seedlings), an annual standard form may be more appropriate, while for other welfare effects (e.g., mature tree biomass loss), a 3-ye ar average form may be more appropriate. Staff concludes it is appropriate to consider both the annual and 3-year average forms.

(4) It is appropriate to cons ider a range of levels when making a determination regarding what is requisite public welf are protection. Staff concludes that an appropriate upper bound of this range is 21 ppm-hrs, expre ssed in terms of the W126 index, which is roughly equivalent to that proposed by the Admi nistrator in the last review as able to provide a requisite level of prot ection to vegetation. Our analys es indicate that this level will provide protection against O 3 -related adverse impacts on vegetation such as tree growth and crop yield beyond that afforded by the current 8-hr standard. In large part, the basis for selecting the level in the last review was a judgment as to what was an appropriate level of protecti on against annual crop yield lo ss. Though crop data are still useful as a potential indicator of risk to other sensitive annual herbaceous plants, staff recognizes that agricultural systems are heavily managed. In addition, the annual productivity of agricultural systems is vulne rable to disruption from many other stressors (e.g., weather, insects, disease), whose impact in any given year can greatly outweigh the direct reduction in annual productiv ity resulting from elevated O 3 exposures. On the other hand, O 3 can also more subtly impact cr op and forage nutritive quality and indirectly exacerbate the severi ty of the impact from other stressors. These latter effects cannot currently be quantifie d and deserve further study. Taking all of the above considerations into account, staff conclude s that from a public welfare perspective, greater concern should be placed on the impacts of O 3 exposures on vegetation in less heavily managed and unmanaged ecosystems su ch as tree seedlings, mature trees, and forested ecosystems in general. Thus, staff concludes that the lower end of the range should incorporate the lower end of the range expressed by CASAC of a 3-month 12-hr W126 approximately equal to 7 ppm-hrs. This lower level will increase protection for the most sensitive tree species and the ecosystems where they are found.

Several additional factors should be considered when selecti ng an appropriate level for a secondary standard. These include 1) the fact that O 3 effects are cumulative and have been shown to have carry over effects from one year to the next; 2) some seedling tree species have sensitivities as great as a nnual crops and the importance of protecting8-27 against small percentages of biomass loss on an annual basis has been expressed by some within the scientific community; 3) visibl e foliar injury impact s can occur within a growing season at very low levels of O 3 exposure; and 4) the exte nt to which a secondary standard should be precautionary in nature, given the possibility of O 3 impacts acting in synergy with other natural and manmade stre ssors. Should a 3-year average of a 12-hr W126 be selected, the level chosen should refl ect the fact that annua l impacts are still a concern for visible foliar injur y, tree seedling biomass loss, a nd crop yield loss, so that a potentially lower level might be considered to reduce the potentia l of adverse impact from the single high O 3 year that could still occur wh ile attaining a 3-year average.

8.4 SUMMARY OF KEY UNCERTA INTIES AND RESEARCH RECOMMENDATIONS RELATED TO SETTING A SECONDARY O 3 STANDARD Staff has identified the following key uncertain ties and research questions that have been highlighted in Chapter 9 of the CD and Chapter 7 herein, associated with this review of the welfare-based secondary standa rds. The first set of ke y uncertainties and research
recommendations discussed below is that associat ed with the extrapolati on to plant species and environments outside of specific experimental or field study conditions. The second set of key uncertainties and research recommendations pertai n to our ability to a ssess the impact of O 3 on other welfare effects categories such as climate, ecosystem co mponents such as wildlife, and whole ecosystem structure and function. Third, we identify research reco mmendations related to the development of approaches, tools, or methodol ogies useful in charac terizing the relationship
between O 3 and public welfare in a policy context. These three areas are described below.

(1) Plant Species-Level Research Needs:

• To reduce uncertainties associated with ex trapolating plant response for a given level of O 3 using composite response functions acros s differing regions and climates, studies using large numbers of plant species across regions where those species are indigenous are recommended. In addition, to better unders tand the full range of response of plant species to O 3 , research on more species is recommended.

• To reduce uncertainty associated with estim ating the risk to vegetation of differing amounts of O 3 -induced visible foliar injury over th e plant’s leaf area, research to explore the relationship between vi sible foliar injury and other O 3 -related effects is recommended.

• To reduce uncertainty associated with the impact of differing levels of O 3 on the nutritive quality of forage and other crops, additional research is needed.8-28 • To reduce uncertainty associated with estimated or modeled flux into plants, research is recommended to evaluate the factors that affect O 3 flux into plants, including the genetic determinants of O 3 sensitivity and the range of variability among species with respect to detoxification/compensation and nocturnal uptake and response. Research that explores the relative importance of flux rate versus total cumulative flux or dose, and that leads to a database of O 3 flux-response relationships for vegetation; similar to the extensive concentration-response database that currently exists is recommended to further reduce existing uncertainties.

• To reduce uncertainties in extrapolating from O 3 effects on juvenile to mature trees and from trees grown in the open versus those in a closed forest canopy in a competitive environment, additional research is recommended.

• To reduce uncertainties in extr apolating individual plant resp onse spatially or to higher levels of biological organization, including ecosystems, research that explores and better quantifies the nature of the relationship between O 3 , plant response and multiple biotic and abiotic stressors, including t hose associated with climate change, is recommended.

(2) Ecosystem Level Impacts:

• To reduce uncertainties associated w ith projections of the effects of O 3 on the ecosystem processes of water, carbon, and nutrient cycling, particularly at the stand and community levels, research is need ed on the effects on below ground ecosystem processes in response to O 3 exposure alone and in combination with other stressors. These below ground processes include inte ractions of roots with the soil or microorganisms, effects of O 3 on structural or functional components of soil food webs and potential impacts on plant species divers ity, changes in the water use of sensitive trees, and if the sensitive tr ee species is dominant, potenti al changes to the hydrologic cycle at the watershe d and landscape level.

• To conclusively show whether O 3 affects biodiversity or gene tic diversity, research on competitive interacti ons under elevated O 3 levels are recommended. This research could be strengthened by modern molecular methods to quantify impacts on diversity.

• To fill the data gaps regarding interactions and potential feedback mechanisms between O 3 and O 3 precursor (e.g., volatile organic carb ons) production, atmospheric processes, and climate change variables, research is recommended to evaluate whether O 3 will negate the positive effects of an elevated CO 2 environment on plant carbon and water balance, whether the likelihood of various biot ic stressors such as pest epidemics and insect outbreaks would be expected to increase in the future

• To reduce uncertainties associated with scaling O 3 effects up from the responses of single or a few plants to effects on communities and ecosystems, additional research is recommended. Because these uncertainties are multiple and significant due to the complex interactions involved, new research will likely require a combination of manipulative experiments with model ecosy stems, community and ecosystem studies8-29 along natural O 3 gradients, and extensive modeling e fforts to project landscape-level, regional, national and international impacts of O 3
.

• To fill the data gaps regarding O 3 impacts to other non-plant we lfare effects categories such as climate, as well as potential direct impacts of O 3 on some sensitive species of animals and wildlife, more research is needed.

(3) Approaches, Tools, Methodologies:

• To reduce uncertainties associated with valuing improved vegetation and ecosystem function from improved O 3 air quality, research is needed on methodologies to determine the values associated with impor tant services and benefits derived from natural ecosystems such that these could be used in comprehensive risk and benefits assessments for O 3 effects on natural ecosystems.

• To reduce uncertainties associated with evaluating the performance of different exposure indices given di fferent patterns of O 3 exposures, experiments would need to be designed to specifically te st the performance of different indices in predicting plant response under different exposure regimes.

• To reduce uncertainties associated with the generation of rural O 3 exposures, improved model capabilities are needed, including a mo re refined spatial grid for the western U.S., better handling of O 3 movement in complex terrain and predicting nocturnal concentrations. Further, research is need ed regarding whether strategic placement of passive or mobile monitors might benefit the estimation of impact to particular resources of concern.8-30 REFERENCES

Abt Associates, Inc. (1993) Urban ornamental plants: sensitivity to ozone and potential economic losses. Report to U.S. EPA, December

Abt Associates Inc. (2007). Techni cal Report on Ozone Exposure, Risk, an d Impacts Assessments for Vegetation: Final Report. Prepared for Office of Air Quality Pl anning and Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC. January 2007. Available electronically on the internet at: http://www.epa.gov/ttn/naaqs/standards/ozone/s_o3_cr_td.html

. Federal Register (1996) National Ambient Air Quality Standards for Ozone; Proposed Rule. 40 CFR 50; Federal Register 61: 65716.

Federal Register (1997) National Ambient Air Quality Standards for Ozone; Final Rule. 40 CFR 50; Federal Register 62: 38856.

Gregg, J. W., Jones, C.G., Dawson, T.E. (2003). “Urbanization effects on tree growth in the vicinity of New York City.” Nature 424: 183-187.

Hanson, P., Samuelson, L., Wullschleger, S., Tabberer, T. and Edwards, G. (1994) “Seasonal patterns of lightsaturated photosynthesis and leaf conductance for mature and seedling Quercus rubra L. foliage: differential sensitivity to ozone exposure.” Tree Physiology 14:1351-1366.

Heck, W. W. and Cowling, E. B. (1997) The need for a long term cumulative secondary ozone standard - an ecological perspective. EM (January): 23-33

Henderson, R. (2006c) Letter from CASAC Chairman Rogene Henderson to EPA Administrator Stephen Johnson, October 24, 2006, EPA-CASAC-07-001.

Horst, R.; Duff, M. (1995). Concentr ation data transformation and the quadratic rollback methodology (Round 2, Revised). Unpublished memorandum to R. Rodríguez, U.S. EPA, June 8.

Isebrands, J. G.; Dickson, R. E.; Rebbeck, J.; Karnosky, D. F. (2000) Interacting effects of multiple stresses on growth and physiological processes in northern forest trees. In: Mickler, R. A.; Birsdey, R. A.; Hom, J., eds. Responses of northern U.S. forests to environmental change. New York, NY: Springer-Verlag; pp. 149-180. (Ecological studies: v. 139).

Isebrands, J. G.; McDonald, E. P.; Kruger, E.; Hendrey, G. ; Percy, K.; Pregitzer, K.; Sober, J.; Karnosky, D. F. (2001) Growth responses of Populus tremuloides clones to interacting carbon dioxide and tropospheric ozone. Environ. Pollut. 115: 359-371.

King, J.S., M. E. Kubiske, K. S. Pregitzer, G. R. Hendrey, E. P. McDonald, C. P. Giardina, V. S. Quinn, D. F. Karnosky. (2005) Tropospheric O3 compromises net primary production in young stands of trembling aspen, paper birch and sugar maple in response to elevated atmospheric CO2. New Phytologist. 168:623–636.

Musselman, R. C.; Minnick, T. J. (2000) Nocturnal stomatal conductance and ambient air quality standards for ozone. Atmos. Environ. 34: 719-733.

NRC (2004). Air quality management—United States. I. National Research Council (U.S.). Committee on Air Quality Management in the United States. TD883.2.A64325 2004 363.739 ′ 25 ′ 0973—dc222004014594 http://www.nap.edu/openbook/0309089328/html/

National Park Service (2000). Federal Land Managers' Air Quality Related Values Workgroup (FLAG) Phase I Report. (http://www2.nature.nps.gov/air /Pubs/pdf/flag/FlagFinal.pdf).8-31 Rizzo, M (2005). Evaluation of a quadratic approach for adjusting distributions of hourly ozone concentrations to meet air quality standards. November 7, 2005.

Rizzo, M. (2006). A distributional comparison between different rollback methodologies applied to ambient ozone concentrations. May 31, 2006

U.S. Environmental Protection Agency (1996a). Air Quality Criteria for Ozone and Related Photochemical Oxidants. EPA/600/P-93/004aF-cF. Office of Research and Development, National Center for Environmental Assessment, Research Triangle Park, NC.

U.S. Environmental Protection Agency (1996b). Review of National Ambient Air Quality Standards for Ozone: Assessment of Scientific and Techni cal Information - OAQPS Staff Paper. EPA/452/R-96-007. Office of Air Quality Planning and Standard s, Research Triangle Park, NC.

U.S. Environmental Protection Agency (2006) Air Quality Criteria for Ozone and Related Photochemical Oxidants (Final). Office of Research and Development, National Center for Environmental Assessment, Research Triangle Park, NC. EPA/600/R-05/004aF-cF, 2006.

Wolff, G.T. (1996) Letter from Chairman of Clean Air Scientific Advisory Committee to the EPA Administrator, dated April 4, 1996. EPA-SAB-CASAC-LTR-96-006.

Young, T. F.; Sanzone, S., eds. (2002) A framework for assessing and reporting on ecological condition: an SABreport. Washington, DC: U.S. Environmental Protection Agency, Science Advisory Board; report no. EPASAB-EPEC-02-009. Available: h ttp://www.epa.gov/sab/ pdf/epec02009.pdf [9 December, 2003].UNITED STATES ENVIRONMENTAL PROTECTION AGENCY WASHINGTON D.C. 20460

OFFICE OF THE ADMINISTRATOR SCIENCE ADVISORY BOARD

October 24, 2006

EPA-CASAC-07-001

Honorable Stephen L. Johnson Administrator U.S. Environmental Protection Agency 1200 Pennsylvania Avenue, NW Washington, DC 20460

Subject: Clean Air Scientific Advisory Committee’s (CASAC) Peer Review of the Agency’s 2 nd Draft Ozone Staff Paper

Dear Administrator Johnson:

EPA is in the process of re viewing the national ambient ai r quality standards (NAAQS) for ozone (O 3 ) and related photochemical oxidants, whic h the Agency most recently revised in July 1997. As part of its ongoing review of the ozone NAAQS, EPA’s Office of Air Quality Planning and Standards (OAQPS) developed a 2 nd Draft Ozone Staff Paper, entitled, Review of the National Ambient Air Quality Standards fo r Ozone: Policy Assessmen t of Scientific and Technical Information (July 2006). At the request of the Agency, EPA’s Clean Air Scientific Advisory Committee (CASAC or Committee), s upplemented by subject-matter-expert panelists

— collectively referred to as the CASAC Ozone Review Panel (O zone Panel) — met in a public meeting in Durham, NC, on August 24-25, 2006, to conduct a peer review of this draft Ozone Staff Paper and three related draf t technical support documents.

In its summary of EPA staff conclusions on the primary (health-related) ozone NAAQS found in Chapter 6 of the 2 nd Draft Ozone Staff Paper, OAQPS se t-forth two options with regard to revising the level and the form of the standard: (1) retain the current pr imary eight-hour (8-hr) NAAQS of 0.08 parts per million (ppm); or (2) cons ider a reduction in the level of the primary O 3 NAAQS within the range of alternative 8-hr standards incl uded in Staff’s exposure and risk assessments (which included a range from 0.064 to 0.084 ppm) with primary focus on an O 3 level of 0.07 ppm with a range of forms from third- through fift h-highest daily maximum. The Ozone Panel unanimously concludes that:

1. There is no scientific justification for reta ining the current primar y 8-hr NAAQS of 0.08 parts per million (ppm), and

12. The primary 8-hr NAAQS needs to be substa ntially reduced to pr otect human health, particularly in sensitive subpopulations.

Therefore, the CASAC unanimously recommends a range of 0.060 to 0.070 ppm for the primary ozone NAAQS . With regard to the secondar y (welfare-related) ozone NAAQS, t he Ozone Panel is in strong agreement with the scientific and technical evidence presented in the summary of EPA staff conclusions on the sec ondary ozone NAAQS found in Chapter 8 of the draft Staff Paper in support of the alternative secondar y standard of cumulative form that extends over an entire growing season.

The Ozone Panel members agree that this letter adequately represents their views. The chartered Clean Air Scientific Advisory Committ ee fully endorses the Pa nel’s letter and hereby forwards it to you as the Committee’s consensus report on this subject. A discussion of each chapter in the 2 nd Draft Ozone Staff Paper follows this letter, and the comme nts of individual Panel members on the 2 nd Draft Ozone Staff Paper and thr ee related draft technical support documents are attached as Appendix D.

1. Background

2 Section 109(d)(1) of the CAA requires that the Agency periodically review and revise, as appropriate, the air quality criteria and the NAAQS for the “criteria” ai r pollutants, including ambient ozone. Pursuant to sections 108 and 109 of the Act, EPA is in the process of reviewing the ozone NAAQS. OAQPS, within the Office of Air and Radiation (OAR), developed the 2 nd Draft Ozone Staff Paper as part of this activity. In February 2006, the Ag ency’s National Center for Environmental Assessment, Research Triangle Park, NC (NCEA-RTP), within the Agency’s Office of Research and Developm ent (ORD), released its final Air Quality Criteria for Ozone and Related Photochemical Oxidants

, Volumes I, II, and III , (EPA/600/R-05/004aF-cF, Final Ozone Air Quality Criteria Document) for this current review cycle for the ozone NAAQS. The

nd Draft Ozone Staff Paper evaluates the policy imp lications of the key scientific and technical information contained in the Final Ozone AQCD and identifies critical elements that the Agency believes should be considered in its review of the ozone NAAQS. The Ozone Staff Paper is intended to “bridge the gap” be tween the scientific review c ontained in the Ozone AQCD and the public health and welfare pol icy judgments required of the EP A Administrator in reviewing the ozone NAAQS.

The Ozone Panel met in a public meeting on December 8, 2005 to conduct a consultation on EPA’s 1 st Draft Ozone Staff Paper and two related technical support documents. However, given that the OAQPS’ first draft Staff Paper di d not contain Agency st aff conclusions about whether to retain or revise the existing prim ary and secondary Ozone standards, the CASAC’s activity only amounted to a technical assessment of that document. The Committee’s letter to you from that meeting (EPA-CASAC-CON-06-003), dated February 16, 2006, is posted at URL: http://www.epa.gov/sab/pdf/casac_con_06_003.pdf

.

22. CASAC Ozone Review Pane l’s Peer Review of the 2 nd Draft Ozone Staff Paper and Related Technical Support Documents

The Ozone Panel reviewed the 2 nd Draft Ozone Staff Pape r and found it improved over the earlier version that had been reviewed as part of a consultation process. However, the Panel did not agree with the EPA staff conclusions t hat it was appropriate to consider retaining the current NAAQS as an option that would be protective of public health and welfare. The Ozone Panel’s recommendations for reducing the level of the primary ozone standard, and its rationale for these recommendations, are provided immedi ately below. Following a detailed discussion on the primary and secondary NAAQS ar e the Panel’s major, chapter-specific comments. Finally, the individual written comments of Ozone Panel members on the 2 nd Draft Ozone Staff Paper and the three related draft technical support documen ts are attached in Appendix D. Panelists’ responses to the Agency’s charge questions are included in thes e individual review comments.

Primary Ozone NAAQS

New evidence supports and build-upon key, health-related conclusions drawn in the 1997 Ozone NAAQS review. Indeed, in the 2 nd Draft Ozone Staff Paper, EP A staff themselves arrived at this same conclusion:

“Based on the above considerations and findi ngs from the [Final Ozone AQCD], while being mindful of important remaining uncertainties, staff concludes that the newly available information generally reinforces our judgme nts about causal relationships between O 3 exposure and respiratory effects observed in the lastreview and broadens the evidence of O 3 -relatedassociations to include additional respiratory-related endpoints, newly identified cardiovascularrelated health endpoints, and mortality. Newly available evidence also has identified increased susceptibility in people with asthma. While recognizing that important uncertainties and research questions remain, we also conclude that progr ess has been made since the last review in advancing our understanding of potentia l mechanisms by which ambient O 3 , alone and in combination with other pollutants, is causally li nked to a range of respiratory- and cardiovascularrelated health endpoints.” (Pages 6-6 and 6-7)

2 Several new single-city studies and large multi-city studies designed specifically to examine the effects of ozone and other pollutants on both morbidity and mortality have provided more evidence for adverse health effects at concen trations lower than the current standard. (See the numerous ozone epidemiological single-city studies shown in Figure 3-4 on page 3-53 of the

nd Draft Staff Paper and, in addition, Appendix 3B of the staff paper, which contains the summary of effect estimates and air quality data for these studies and multi-city epidemiological studies.) These studies are b acked-up by evidence from contro lled human exposure studies that also suggest that the current primary ozone NAAQS is not adequate to protect human health (Adams, 2002; McDonnell, 1996).

Furthermore, we have evidence from recently reported controlled clinical studies of healthy adult human volunteers exposed for 6.6 hours to 0.08, 0.06, or 0.04 ppm ozone, or to filtered air alone during moderate exercise (Ada ms, 2006). Statistically-significant decrements in lung function were observed at the 0.08 ppm exposure level. Importantly, adverse lung function effects were also observed in so me individuals at 0.06 ppm (Adams, 2006). These

3results indicate that the current ozone standard of 0.08 ppm is not sufficie ntly health -protective with an adequate margin of safety. It should be noted these findi ngs were observed in healthy volunteers; similar studies in se nsitive groups such as asthmatic s have yet to be conducted. However, people with asthma, and particularly children, have been found to be more sensitive and to experience larger decrements in lung func tion in response to ozone exposures than would healthy volunteers (Mortimer et al. , 2002).

Going beyond spirometric decrements, adverse health effects due to low-concentration exposure to ambient ozone (that is, below th e current primary 8-hour NAAQS) found in the broad range of epidemiologic and controlled expo sure studies cited above include: an increase in school absenteeism; increases in respiratory hospital emergency department visits among asthmatics and patients with othe r respiratory diseases; an increase in hospitalizations for respiratory illnesses; an increase in symptoms a ssociated with adverse health effects, including chest tightness and medication usage; and an increase in mortal ity (non-accidental, cardiorespiratory deaths) reported at exposure levels well below the current standard. The CASAC considers each of these findings to be an important indicator of ad verse health effects. As demonstrated in Chapter 5 of the 2 nd Draft Ozone Staff Paper (specifically, Figures 5.5, 5.7, 5.8, and 5.9), a significant decrease in adverse eff ects due to ozone exposures can be achieved by lowering the exposure concentrations below th e current standard, which is effectively 0.084 ppm. Beneficial effects in term s of reduction of adverse health e ffects were calculated to occur at the lowest concentration considered ( i.e. , 0.064 ppm). (See also Fi gure 3-4, “Effect estimates (with 95% confidence intervals) for associa tions between short-term ozone exposure and respiratory health outcomes,” on page 3-53.)

The justification provided in the 2 nd Draft Ozone Staff Paper for retaining the current level of the primary ozone standa rd as an option for the Admini strator was based on results of controlled human exposure studies m easuring modest declines in FEV 1 after exposures to 0.08 ppm ozone. However, as stated in the Staff Paper (page 3-6), while average decrements in the FEV 1 were relatively small, 26% of the subjects had greater than 10% decrements, which can be clinically significant. Also, while measures of FEV 1 are quantitative and readily obtainable in humans, they are not the only measures — and perhaps not the most sensitive measures — of the adverse health effects induced by ozone exposure. As stated on page 6-32 of the Final Ozone AQCD, “Spirometric responses to ozone are i ndependent from inflammatory responses and markers of epithelial injury (Balmes et al. , 1996; Bloomberg et al. , 1999; Hazucha et al. , 1996; Torres et al. , 1997). Significant inflammatory responses to ozone exposures that did not elicit significant spirometric responses have been reported (Holz et al. , 2005; McBride et al. , 1994).” Agency staff’s analyses placed most emphasis on spirometric evidence and not enough emphasis on serious morbidity ( e.g. , hospital admissions) and mortality observed in epidemiology studies (see page 6-44).

Therefore, on the basis of the large amount of recent data evaluating adverse health effects at levels at and below the current N AAQS for ozone, it is the unanimous opinion of the CASAC that the current primary ozone NAAQS is not adequate to protect human health. Furthermore, the Ozone Panel is in complete agreement both that: the EPA staff conclusion in Section 6.3.6 arguing that “consideration could be given to retaining the current 8-hr ozone standard” is not supported by the relevant scien tific data; and that the current primary 8-hr

4standard of 0.08 ppm needs to be substantially reduced to be protective of human health, particularly in sensitive subpopulations.

Additionally, we note that the understanding of the associated science has progressed to the point that there is no longer significant scienti fic uncertainty regar ding the CASAC’s conclusion that the current 8-hr primary NAAQS must be lowered. A large body of data clearly demonstrates adverse human health effects at the current level of th e 8-hr primary ozone standard. Retaining this standard would continue to put large numb ers of individuals at risk for respiratory effects and/or significant impact on quality of life including asthma exacerbations, emergency room visits, hospital admissions and mort ality. (Scientific uncertainty does exist with regard to the lower level of ozone exposure that would be fully-protective of human health. The Ozone Panel concludes that it is possible that there is no thres hold for an ozone-induced impact on human health and that some adverse events may occur at policy-relevant background.)

Moreover, EPA staff concluded that changes in the concentration- based form of the standard ( i.e. , whether to use the third-, fourth-, or fifth-highest daily maximum 8-hr average concentration) should also be consid ered. The analysis found in the 2 nd Draft Ozone Staff Paper indicates that modest changes in the form of the standard can have substantial impacts on the frequency of adverse health effects. Theref ore, the CASAC recommends that the Agency conduct a broader evaluation of alternative concen tration-based forms of the primary 8-hr ozone standard and the implications of those alternat ive forms on public-health protection and stability ( i.e. , with respect to yearly variability to ensu re a stable target for control programs).

The CASAC further recommends that the ozone NAAQS should reflect the capability of current monitoring technology, which allows accu rate measurement of ozone concentrations with a precision of parts per billion , or equivalently to the thir d decimal place on the parts-permillion scale. In addition, given that setting a level of the ozone standard to only two decimal places inherently reflects upward or downward “rounding,” e.g. , 0.07 ppm includes actual measurements from 0.0651 ppm to 0.0749 ppm, the CASAC chooses to express its recommended level, immediately below, to the third decimal place.

Accordingly, the CASAC unanimously recommends that the current primary ozone NAAQS be revised and that the leve l that should be considered fo r the revised standard be from 0.060 to 0.070 ppm, with a range of concentration- based forms from the third- to the fifthhighest daily maximum 8-hr average concentration. While data exist that adverse health effects may occur at levels lower than 0.060 ppm, these data are less certain and achievable gains in protecting human health can be accomplished through lowering the ozone NAAQS to a level between 0.060 and 0.070 ppm.

Secondary Ozone NAAQS

An important difference between the effects of acute exposures to ozone on human health and the effects of ozone exposures on welfare is that vegetation effects are more dependent on the cumulative exposure to, and uptake of, ozone over th e course of the en tire growing season (defined to be a minimum of at least three months). Therefore, there is a clear need for a

5secondary standard which is distinctly different from the primary standar d in averaging time, level and form. Developing a biologically-relevant ozone air quality index would be directly responsive to the 2004 National Research C ouncil (NRC) recommendations on Air Quality Management in the United States (NAS, 1994) and will help support important new Agency initiatives to enhance ecosystem-rela ted program tracki ng and accountability.

In its 1996 review of the ozone NAAQS, EPA staff proposed several cumulative seasonal ozone exposure indices, including SUM06, the concentration-weighted metric ( i.e. , the seasonal sum of all hourly average concentrations > 0.06 ppm), and W126, the integrated exposure index with a sigmoidal weighting function, as candidate s for a secondary standard. The Administrator considered a three-month, 12-hr SUM06 secondar y standard at a level of 25 ppm-hr as an appropriate, biologically-relevant s econdary standard, but ultimately rejected this option in favor of simply setting the secondary stan dard equal to the primary. It was rationalized that efforts to attain the new 8-hr primary standard would al so eliminate most adverse effects on vegetation, and at that time there were uncertainties in how cumulative seasonal exposures would change with efforts to reduce peak 8-hour concentratio ns. Additionally, it was assumed that future ozone/vegetation effects research over the co ming years would clarif y the very uncertain quantitative relationships betw een ozone exposures and vegeta tion/ecological responses under ambient field conditions.

Unfortunately, however, the Agency has supporte d very little new vegetation/ecological ozone effects research over the past decade. The net result is that the quantitative evidence linking specific ozone con centrations to specific vegetation/ecological effects must continue to be characterized as having high uncertainties due to the lack of data for verification of those relationships. It is not surprisi ng that substantial research need s remain, as indicated both in Chapter 8 and in individual re viewer comments. The quantitative evidence linking specific ozone concentrations to specific vegetation effects — especially at the complex ecosystem level

2 — must continue to be characte rized as having high uncertainties due to the lack of data for verification of those relationships . To a large extent, this is an unavoidable consequence of the inherent complexities of ecosystem structure an d function, interactions among biotic and abiotic stressors and stimuli, variabili ty among species and genotype, de toxification and compensatory mechanisms, etc. Nevertheless, the compelling weight of evidence provided in Chapter 7 of the nd Draft Ozone Staff Paper results from the c onvergence of results from many various and disparate assessment methods including chambe r and free air exposure, crop yield and tree seedling biomass experimental studies, foliar injury data from biomonitoring plots, and modeled mature tree growth.

Despite limited recent research, it has become clear since the last review that adverse effects on a wide range of vegeta tion including visible foliar injury are to be expected and have been observed in areas that are below the leve l of the current 8-hour primary and secondary ozone standards. Such effects are observed in areas with seasonal 12-hr SUM06 levels below 25 ppm-hr (the lower end of the range of a SU M06 secondary standard suggested in the 1996 review and the upper end of the rang e suggested in Chapter 8 of the 2 nd Draft Ozone Staff Paper). Seasonal SUM06 (or equivalent W126) ranges well below 25 ppm-hr were recommended for protecting various managed an d unmanaged crops and tree seedlings in the1997 workshop on secondary ozone standards (Heck and Cowling, 1997). The absence of clear6cut lower effects thresholds for sensitive vegeta tion combined with the lower recent estimates of policy-relevant background (typi cal range of 0.015 to 0.035 ppm ) emphasizes the importance of efforts to reduce low- to mid-range environmental exposures below 0.060 ppm.

Based on the Ozone Panel’s review of Chapters 7 and 8, the CASAC unanimously agrees that it is not appropriate to try to protect vegetation from the substan tial, known or anticipated, direct and/or indirect, adverse effects of ambi ent ozone by continuing to promulgate identical primary and secondary standards for ozone. Moreover, the members of the Committee and a substantial majority of the Ozone Panel agrees with EPA staff conclusions and encourages the Administrator to establish an alternative cu mulative secondary standard for ozone and related photochemical oxidants that is di stinctly different in averaging time, form and level from the currently existing or potentially revised 8-hour primary standard. The suggested approach to the secondary standard is a cumulative seasonal grow ing standard such as the indices SUM06 or W126 aggregated over at least the three summer months exhibiting the highest cumulative ozone levels and includes the ozone exposures from at least 12 daylight hours. The CASAC suggests a range of 10 to 20 ppm-hours for the three-mont h growing season SUM06 index for agricultural crops rather than the 15-25 ppm- hours proposed in Chapter 8.

However, the Ozone Panel views the thre e-month growing season W126 index as a potentially more biologically-r elevant index than the 3-mont h growing season SUM06 index. This is because the W126 index has no absolu te minimum ozone concentration threshold and only lightly weights the lower oz one concentrations. Therefore, a three-month seasonal W126 that is the approximate equivalent of the SUM 06 at 10 to 20 ppm-hr is preferred. As shown by the references cited at the e nd of Chapter 8, the consensus vi ew among expert persons in the ecological communities of both this country and elsewhere around the world is that a secondary standard of cumulative form and extending over an entire growing season will be far more effective than a secondary standar d that is not cumulative in fo rm and does not include the whole growing season.

In conclusion, the Clean Air Scientific A dvisory Committee is pl eased to provide its scientific advice and recommendations to th e Agency on the primary and secondary ozone NAAQS. We recognize that ou r recommendation of lowering of the current primary ozone standard would likely result in a large portion of the U.S. being in non-attainment. Nevertheless, we take very seriously the statut ory mandate in the Clean Air Act not only for the Administrator to establish, but also for the CASAC to recommend to the Administrator, a primary standard that provides for an “adequate margin of safety ... requisite to protect the public health.”

Finally, as announced during the Ozone Pa nel’s August meeting, once the Agency releases the Final Ozone Staff Paper in early January 2007, the CASAC intends to hold a public teleconference in late January or early Februa ry 2007 for the members of the Ozone Panel to review — and, prospectively, to offer additional, unsolicited advi ce to the Agency concerning — Chapter 6 (Staff Conclusions on Primary O 3 NAAQS) and Chapter 8 (Staff Conclusions on Secondary O 3 NAAQS) in that final Agency document. The purpose of such advice would be to

7inform EPA’s efforts as it develops the fort hcoming, proposed rule for ozone and related photochemical oxidants. As always, the CASAC wishes EPA well in this important endeavor.

Sincerely,

/ S igned/

Dr. Rogene Henderson, Chair Clean Air Scientific Advisory Committee

Appendix A – Clean Air Scientific A dvisory Committee Roster (FY 2006) Appendix B – CASAC Ozone Review Panel Roster Appendix C – Charge to the CASAC Ozone Review Panel Appendix D – Review Comments from Indivi dual CASAC Ozone Review Panel Members

8

### CASAC Chapter-Specific Di scussion Comments on EPA’s 2 nd 

### Draft Ozone Staff Paper

Sub-groups of the CASAC Ozone Review Pane l who led the discussion on individual chapters of the Staff Paper summarized their comments in the following paragraphs:

Chapter 2 (Air Quality Characterization): A better introduction to the central role of photochemical oxidation reactions as the key reactions governing the behavi or of air pollutants in the atmosphere would improve this chapter. Ozone is the key indicator of the extent of oxidative chemistry and serves to integrate multiple pollutants. Oxidation in the atmosphere leads to the formation of particulate matter from SO 2 , NO X , and volatile organic compounds (VOCs) as well as gas phase irritants (formalde hyde, acrolein, etc). Thus, although ozone itself has direct effects on human health and ecosystems, it can also be considered as indicator of the mixture of photochemical oxidants and of the oxidizing potency of the atmosphere. Section 2.2.6 only briefly covers the relationship of ozone to other photochemical oxidants. It would be beneficial to add a short paragraph outlining th e role of ozone and other photochemical oxidants in the atmospheric transformation processes that may results in the formation of more toxic products (both in an outdoor a nd indoor environment), as prov ided in the individual comments appended to this letter.

The section on policy-relevant background (2.7) continues to have problems. Although the section briefly cites the results of comparis on of different models and measurements, it does not adequately address the un certainties of the global GE OS-CHEM model, and how these uncertainties are reflected in the health risk an alysis. Since ozone health effects are observed down to concentrations of the order of 0.04–0.05 ppm, it is impor tant to know how the PRB is related to the considered primar y ozone standard and what uncerta inties there are in the risk attributed to controllable sources.

Chapter 3 (Policy-Relevant Assessment of Health Effects Evidence): The latest draft of Chapter 3 is much improved over the previous dr aft. Efforts to respond to some of the earlier concerns expressed by the CASAC ar e appreciated. While in general this chapter is well written, and is a credible basis for the risk analyses that follow, there are inconsistencies and inaccuracies that still need to be addressed. Typically, there is appropriate use of cautionary phrases when the data are not as strong as they mi ght be, but this use is inconsiste nt across the chapter, and there are instances where EPA staff appear to be stretching to infer that data support their statement. While the individual comment s of Ozone Panel members attached to this letter provide specifics on these points, some of the Panel’s more signi ficant concerns are discussed briefly below.

Discussion of measurement error is convoluted , confusing, and contains some mistakes. The primary issue in the use of central am bient monitors for ozone in time-series epidemiological studies is whethe r they provide any information at all that reflects daily personal ozone exposure in susceptible populations. The di scussion on p. 3-37 of the impact of various types of exposure measurement error is incorre ct; the difference between true and measured ambient concentrations is an example of classical measurement error that results in bias of effect

9estimates to the null, not just an increase in standard error. Cl aiming that the difference between average personal exposure and ambient concentra tions results in “attenua tion of risk” is not appropriate.

The Ozone Panel does not completely agree wi th staff’s conclusion that “the use of routinely monitored ambient ozon e concentrations as a surrogat e for personal exposures is not generally expected to change th e principal conclusions from oz one epidemiological studies.” Indeed, Panel members have little insight as to what we would find if we had actual exposure measurements. Personal exposures most likely correla te better with central site values for those subpopulations that spend a good deal of time outdoors, which coincides, for example, with children actively engaged in out door activities, and which happens to be a group that the ozone risk assessment focuses upon.

Some statements about which individuals are at greatest risk of ozone -induced effects are not adequately supported by the information discusse d in the chapter. Individuals with chronic obstructive pulmonary disease (COPD) and cardiova scular disease (CVD) are likely to be at increased risk, but the hypothesis that such “ hyper-responsiveness” can be used to identify individuals with COPD or CVD wh o are at greatest risk of O 3 -induced health effects has not been confirmed. A more appropria te conclusion would be that individuals with COPD and CVD are at increased risk of O 3 -induced health effects.

The discussion of the ranges for changes in FEV 1 that are considered to be small, moderate, or large for persons with impaired resp iratory systems is not consistent. While EPA staff state that the table values for the range s do not need to be ch anged, staff indirectly acknowledge that a 10% reducti on in this variable in as thmatics could have serious consequences, an interpretation that is used in Chapters 4-6.

The 30 subjects studied by Adams had a great influence on the analyses presented in Chapters 5 and 6. While the discussion of the lo w-level exposures used in the controlled human studies by Adams and colleagues is technically co rrect that no statistically significant changes were found in FEV 1 for ozone at 40 to 60 ppb compared to filtered air, there were clearly a few individuals who experienced declines in lung func tion at these lower concentrations. These were healthy subjects, so the percenta ge of asthmatic subjects, if th ey had been studied, would most likely be considerably greater.

The lack of statistical power is consistently offered in Chapter 3 for why there appears to be an inconsistent effect seen for COPD morta lity. Coherence of respir atory effects for ozone suffers from neither no more nor no less power considerations that do those for particulate matter (PM). Yet the Agency did not argue a lack of po wer when assessing PM risks, so consistency is needed here relative to ozone eff ect estimates for COPD mortality.

The relatively strong and relatively consistent effect of ozone on emergency department visits for respiratory disease, especially asthma, as evidenced in Figure 3-4 is misrepresented in several places in the Chapter (and in Chapters 5 a nd 6) as “inconclusive” or “inconsistent.” This should be corrected.

10Chapter 4 (Characterization of Human Exposure to Ozone): The second draft of Chapter 4 has responded to many of the comments made on the first draft, and is thus clearer than before. The panel was pleased to s ee the reanalysis for 2002 in addition to 2004.

It would be helpful to have the estimated exposures for current (2002 and 2004) levels displayed in Tables 4-8 & 4-9 ( p. 4-32) and Figures 4-4 to 4-21 ( pp. 4-33 to 4-41), in addition to only those for just meeting the current standard a nd alternative more stringent standards. This would be analogous to the way estimated effects ar e displayed in Chapter 5 (Figures 5-5 to 5-9 [pp.5-58 to 5-65]).

On the whole, Chapter 4 provides a clear “roa d map” for what was done to characterize available knowledge about human exposure to oz one in the framework of generally accepted modeling approaches of appropriate ly selected populations in 12 urban areas of the U.S. Much of the text reads lik e a basic textbook on human exposure as sessment using state-of-the-art modeling approaches, such as the Air Pollutant s Exposure Model (APEX), including adjustments for lung ventilation of delivered ozone dose. This extension, beyond e xposure characterization, is particularly important for ozone where the ex tent of measurable human responses is very sensitive to the amount of ozone inhaled and to where it deposits along the respiratory tract. Further extension of the methodology to estimate dose would have important implications and should be discussed.

There is an explicit discussion of the lim itations of the APEX model in terms of variability and the quality of the i nput data, which is appropriate and fine as far as it goes. There are good reasons presented for selection of urba n areas and the time periods to be modeled. However, there was inadequate consideration of the populations selected for modeling. Those selected were appropriate, but the omission of th e elderly, the population most at risk for ozoneassociated premature daily mortality, was notable and not even mentioned in terms of why it was not considered.

The chapter was very good at exposition and clear presentation of mode ling results, but was deficient it its discussion of seemingly counterintuitive resu lts, and of a potentially large influence of measurement biases. As an example of the first of these issues, the children in LA & Houston are estimated to have far fewer expos ures above 0.07 ppm (8-hr) than in most other cities with lower ozone concentr ations and fewer children. This was likely due to the greater within-day and sampler-to-sampler variations in c oncentration within these two cities than in the others, the fact that the entire year was modeled while for other sites the winter was not included and/or the greater extent of ai r conditioning, especially in Houst on. Whatever the reasons, there should have been some discussion of the cause s. The quadratic ro llback methodology should have been better described sin ce this strategy has important consequences for the modeled results.

The second issue that was presented, but left ha nging without an adequa te discussion is at the bottom of page 4-47, where it was simply stat ed that “in general, APEX systematically under-predicts the measured values by 0.001 to 0.02 ppm (zero to 50 percent).” If this is so, is it due to a really serious failure of the APEX m odel, or to unreliable measurements? The measurements at issue were six-day average concentrations based on the use of passive

11(diffusion) samplers, which are known to be subject to significant errors when the air velocity across the inlet is variable. The comparison of m easured and modeled concen trations depicted in Figure 4-22 is certainly worthy of furt her analysis and discussion.

Chapter 5 (Characterizati on of Health Risks): Generally the panel found Chapter 5 and its accompanying risk assessment to be we ll done, balanced and reasonably communicated. Additional text is needed at the beginning a nd end of the chapter to put the limited risk assessment into the context of the much larger body of evidence of ozone health effects. The discussion of uncertainty in these risk estimates is expa nded in section 5.3.2.5. Although a number of issues are raised, th eir impacts on the estimates have not been thoroughly explored. Additional sensitivity analyses seem warranted. In particular, it is essential that the sensitivity of the risk assessment to the shape of the dose-response curve for FEV 1 be evaluated. Although the 3 parameter logistic (3PL) model em ulates the pattern seen in the five “data points,” these points are aggregates of the original data, and may give a misleadingly optimistic picture of the quality of the fit. More importantly, a lthough the problem of m odel uncertainty is noted it has not been addressed even though methods exist for doing so. Even if only the linear and logistic models were included in the analysis, the error bands around the estimated res ponse probabilities would likely increase to better reflect that uncertaint y. In addition, a sugges tion to deal with the uncertainties surrounding estimation of PRB, pa rticularly as related to Table 5.5 (for lung function) and Table 5.11 (mortality), would be to change the form of the analyses to assess the impact of the concentration change in the expe cted number of health effects relative to the current standard. The key advantage of estimating the effect of concentration change is that it does not depend on the choice of the PRB.

With regard to the controlled human exposure studies, Ozone Panel members believe that the selection of changes in pulmonary func tion expressed as percent change in FEV 1 in children is a fair indicator of an advers e effect at 15% change in all active children; and, in asthmatic children, a 10% change is indicative of adverse effects. However, the presentation of the figures showing these effects needs to be revised to indicate the uncertainties in the results used, particularly at the lower levels of exposure. The potential mechanisms whereby these changes are a reflection of both pain on breathing, partial inflammation of smaller airways, other effects on airways, and potentially triggers for more si gnificant respiratory morbidity, particularly in asthmatic children, are not adequately discu ssed. In addition, some added discussion is necessary to indicate that these measures ar e generally taken in areas with relatively high background levels of ozone exposure, and that the role that tolera nce may play in minimizing the degree of adverse effect observe d needs to be considered.

From the perspective of the epidemiologica l data, the Ozone Panel judged the selection of: respiratory symptoms in moderate/severe asthmatic children (ages zero [birth] to 12); hospital admissions for respiratory illness among asthmatic children; and premature total non-accidental and cardiorespiratory mortality for inclusion in the quantitative risk assessment to be appropriate. However, the CASAC believes that several othe r endpoints should be disc ussed qualitatively to support the findings that these endpo ints indicate that significant adverse effects are occurring at exposure concentrations well below the current standard. Other endpoints deemed worthy of additional discussion included respiratory emer gency department visits among asthmatics and patients with other respiratory diseases, increased medication usage, and increased

12symptomatology reported at exposure levels well below the current standard. Taken together, members of the Ozone Panel felt strongly that these findings preclude including the current standard as a scientifically defensible option for the Administrator (see discussion about Chapter 6 found in the main portion of the letter above).

Another problem in the health effects calcula tions (see Table 5-5 and 5-11) is that they are based on computations of the form R x – R PRB , where R x is the risk at a given concentration x of O 3 and R PRB is the corresponding risk at pol icy-relevant background (PRB) for O 3 . As discussed at the Ozone Panel’s August meeting, the PRB is highl y-problematic to calculate and is, in some sense, “unknowable.” One can avoid this problem by calculating the ∆ = R 0.8 – R x for various concentrations x. This form woul d allow focus on the question, “What is the difference in the expected number of health effects that will occu r at various concentrations of O 3 , relative to the current standard of 0.08?” A key advantage of ∆ is that it does not depend on the choice of PRB, and thus is free of the un certainties surrounding estimation of PRB.

Chapter 6 (Staff Conclusions on Primary O 3 NAAQS): See the discussion on Chapter 6 found in the main portion of the letter above. It would also be helpful to have the estimated exposures for current (2002 and 2004) levels displayed in figures 6-1 to 6-6 (pp. 6-34 to 6-39), in addition to only those for just meeting the current standard and alternative more stringent standards. This would be analogous to the wa y estimated effects are displayed in Chapter 5 (Figures 5-5 to 5-9 [pp.5-58 to 5-65]).

Chapters 7 (Policy-Relevant Assessment of Welfare Effects Evidence) and 8 (Staff Conclusions on Secondary O 3 NAAQS): Chapter 7 is a well-developed and persuasively presented assessment of the welf are effects of ozone on vegetation, which forms the technical basis for the range of secondary standards recommended in Chapter 8. That having been said, the potential for significant pr opagation of error/uncertainty in the underlying technical documentation draws into question the conclusion s drawn by EPA Staff. As observed in the Agency’s 1989 and 1996 Ozone Staff Papers, oz one remains the most prevalent phytotoxic compound in the ambient air “impairing crop production and injuring native vegetation and ecosystems more than any other air pollutant” (USEPA 1989, 1996). Furthermore, as has been noted in the current assessment of human health effects, there also appears to be no safe threshold concentration below which ozone effect s on sensitive vegetation are eliminated. See the additional discussion on Chapter 8 found in the main portion of the letter above.

13UNITED STATES ENVIRONMENTAL PROTECTION AGENCY WASHINGTON D.C. 20460

OFFICE OF THE ADMINISTRATOR SCIENCE ADVISORY BOARD

March 26, 2007

EPA-CASAC-07-002

Honorable Stephen L. Johnson Administrator U.S. Environmental Protection Agency 1200 Pennsylvania Avenue, NW Washington, DC 20460

Subject: Clean Air Scientific Advisory Co mmittee’s (CASAC) Review of the Agency’s Final Ozone Staff Paper

Dear Administrator Johnson:

The Clean Air Scientific Advisory Comm ittee (CASAC or Committee), augmented by subject-matter-expert Panelists — collectively re ferred to as the CASA C Ozone Review Panel (Ozone Panel) — completed its review of the Agency’s 2 nd Draft Ozone Staff Paper in October 2006 (EPA-CASAC-07-001). In that letter, da ted October 24, 2006, the CASAC indicated it would review the Agency’s Final Ozone Staff Pa per and offer additional, unsolicited advice to the Agency on the chapters concerned with set ting the primary and secondary National Ambient Air Quality Standards (NAAQS) for ozone.

On March 5, 2007, the Ozone Panel met via a public teleconferen ce to review EPA’s Final Review of the National Ambient Air Quality Standards for Ozone: Policy Assessment of Scientific and Tec hnical Information (Final Ozone Staff Paper, January 2007). The Panel focused on Chapter 6 (The Primary O 3 NAAQS) and Chapter 8 (The Secondary O 3 NAAQS). The CASAC roster is attached as found in Appendi x A, the Ozone Panel roster is provided as Appendix B, and Ozone Panel memb ers’ individual re view comments are f ound in Appendix C.

Members of the CASAC Ozone Review Pane l were pleased to review EPA’s Final Ozone Staff Paper. The memb ers of CASAC and the Ozone Pa nel were unanimous in their praise of both the responsiveness of the Agency to our previous recommendations and of the clarity of this document. While the CASAC r ecognizes that the Ozone Staff Paper is a final document, the Committee offers the following advi ce to aid the Administrator and Agency staff in developing EPA’s proposed rule for ozone and related photochemi cal oxidants, to be published in June 2007.

1Primary Standard

• The CASAC Ozone Review Panel agreed with the choice of indicator, statistical form and averaging time for the primary Ozone NAAQS suggested by Agency staff.

• The Final Ozone Staff Paper recommended that “consideration be given to a standard level within the range of somewhat below 0.080 ppm to 0.060 ppm,” adding that “[s]tandard levels within this range that were considered in staff analyses of air quality, exposure, and risk include 0.074, 0.070, and 0.064 pp m, representative of levels within the upper, middle, and lower parts of this range, respectively.” Reiterating what was stated in the CASAC’s prev ious letter to you on this review (EPA-CASAC-07-001), Ozone Panel members were unanimous in reco mmending that the level of the current primary ozone standard should be lowered from 0.08 ppm to no greater than 0.070 ppm. The above-referenced CASAC letter (from Oc tober 24, 2006), in addition to EPA’s own findings in the Final Ozone Air Quality Crite ria Document (AQCD) and the Final Ozone Staff Paper, provide overwhelming scient ific evidence for this recommendation. Furthermore, the Ozone Panel recommends t hat the NAAQS should be specified to the third decimal place of the ppm sc ale to avoid any rounding issues — as indicated by the standard levels that the Agency itself c onsidered in the Final Ozone Staff Paper.

• Pursuant to the Clean Air Act, the primary NAAQS for criteria air pollutants must be set to protect the public health with an adequate margin of safety. Significantly, the Final Ozone Staff Paper does not address the issue of a margin of safety. (On page 6-86, the authors conclude that the proposed standard would “...provide an a ppropriate degree of public health protection...;” however, there is no explicit mention of a margin of safety,
per se .) Such a discussion should be added to the document and taken into consideration in setting the prim ary ozone standard.

• There is an underestimation of the affected population when one considers only twelve urban “Metropolitan Statis tical Areas” (MSAs). The CASAC acknowledges that EPA may have intended to illustrate a range of im pacts rather than be comprehensive in their analyses. However, it must be recognized that ozone is a regional pollutant that will affect people living outside these 12 MSAs, as well as inside and outside other urban

areas.

• There is an urgent need to fund more resear ch on the effects on sensitive subpopulations of low levels of the photochem ical oxidant mixture for whic h ozone is used as a surrogate. In addition to the three fi eld studies pointing to highe r responses to the oxidant mixtures than to pure ozone that the Agency has already referenced in the Final Ozone AQCD (1–3), three other such studies are referenced below (4–6). More information on the effects of low levels of oxi dant mixtures on public health is essential to inform the future decision-making process.

• Finally, with respect to policy-relevant b ackground (PRB), the Ozone Panel wishes to point out that the Final Ozone Staff Paper does not provide a sufficient base of evidence from the peer-reviewed literature to suggest that the current approach to determining a PRB is the best method to make this estimation. One reason is that part of the PRB is not

2controllable by EPA. It would require international coopera tion beyond the bounds of North America. A better scientific unders tanding of the PRB and its relationship to intercontinental transport of air pollutants c ould serve as the basis for a more concerted effort to control its growth and preserve the gains in air quality achieved by control efforts within the U.S. In any case, there is no apparent need to define PRP in the context of establishing a health-based (primary) oz one NAAQS. The effects of inhaled ozone on decreases in respiratory function have been seen in healthy children exposed to ozone within ambient air mixtures in summer camps (1–6). Furthermore, the concentrationresponse functions above 40 ppb ar e either linear, or indistin guishable from linear. Thus, PRB is irrelevant to the disc ussion of where along the con centration-response function a NAAQS with an 8-hour averaging time that provides enhanced public health protection should be.

Secondary Standard

• The CASAC Ozone Review Panel memb ers were unanimous in supporting the recommendation in the Final Ozone Staff Pape r that protection of managed agricultural crops and natural terrestrial ecosystems re quires a secondary Ozone NAAQS that is substantially different from the primary ozone standard in averaging time, level and form.

• The recommended metric for the secondary ozon e standard is the (s igmoidally-weighted) W126 index, accumulated over at least the 12 “d aylight” hours and over at least the three maximum ozone months of the summer “growing season.”

• The Ozone Panel agrees with EPA Staff r ecommendations that the lowest bound of the range within which a seasona l W126 welfare-based (secondary ) ozone standard should be considered is 7.5 ppm-hrs; however, it does not agree with Staff’s recommendations that the upper bound of the range should be as high as 21 ppm-hours. Rather, the Panel recommends that the upper bound of the range considered should be no higher than 15 ppm-hour, which the Panel estimates is approxi mately equivalent to a seasonal 12-hour SUM06 level of 20 ppm-hours.

• Multi-year averaging to promote a “stable” secondary Ozone NAAQS is less appropriate for a cumulative, seasonal secondary standa rd than for a primary standard based on maximum eight-hour concentrations. If multi-ye ar averaging is employed to increase the stability of the secondary standard, the leve l of the standard shoul d be revised downward to assure that the desired threshold is not exceeded in individual years.

• There was an effective, Federally-funded program of ozone environmental effects research during the 1970s and 1980s, but such research support has been neglected in recent years. It is reasonable to conclude that changes in the distribution and genetic makeup of crop cultivars and naturally occurr ing plant species has and will take place over time along with modification of levels a nd distribution of ambient ozone exposures. Therefore, future refinements of the sec ondary Ozone NAAQS will require both: (1) a significant future investment in effects research to ensure th at data for plant response to ozone are representative of th e species and genetic composition of current crop and forest

3species utilized by society; and (2) a clea r understanding of the s ources and propagation of uncertainty in the re sults of that research.

Additional details on the ge neral recommendations listed above are provided in the comments of the individual members of the Ozone Panel that are included in Appendix C.

The CASAC appreciate this opportunity to work with the Agency is us ing science to help inform the setting of primary and secondary NAAQS to protect public health. While this is the last of a long series of Agency NAAQS-relate d staff papers, the Committee will continue to provide you with scientific advice related to setting crit eria air pollutant standards protective of the public health and public we lfare under EPA’s revised NAAQS re view process. As always, the CASAC wishes the Agency well in this important endeavor.

Sincerely,

/Signed/

Dr. Rogene Henderson, Chair Clean Air Scientific Advisory Committee

Appendix A – Roster of the Clean Air Scientific Advisory Committee Appendix B – Roster of the CASAC Ozone Review Panel Appendix C – Review Comments from Indivi dual CASAC Ozone Review Panel Members

References

1. Spector, D.M., Lippmann, M., Lioy, P.J., Thurst on, G.D., Citak, K., James, D.J., Bock, N., Speizer, F.E., and Hayes, C. Effects of ambient ozone on respiratory function in active normal children. Am. Rev. Respir. Dis. 137:313-320 (1988).

2. Spektor, D.M., Lippmann, M., Thurston, G.D., Lioy, P.J., Stecko, J., O'Connor, G., Garshick, E., Speizer, F.E., and Hayes, C. E ffects of ambient ozone on respiratory function in healthy adults exercising outdoors. Am. Rev. Respir. Dis. 138:821-828 (1988).

3. Thurston, G.D., Lippmann, M., Scott, M.B., a nd Fine, J.M. Summertime haze air pollution and children with asthma. Am. J. Respir. Crit. Care Med. 155:654-660 (1997).

4. Lippmann, M. Health effects of ozone: A critical review. JAPCA 39:672-695 (1989).

5. Spektor, D.M., Thurston, G.D., Mao, J., He, D ., Hayes, C., and Lippmann, M. Effects of single and multi-day ozone exposures on respir atory function in active normal children. Environ. Res. 55:107-122 (1991).

6. Lippmann, M. Health effects of tropospheric ozone: Implications of recent research findings to ambient air quality standards. J. Exposure Anal. Environ. Epidemiol. 3:103-129 (1993).

4

### Appendix A – Clean Air Scientific Advisory Committee Roster (FY 2006)

U.S. Environmental Protection Agency Science Advisory Board (SAB) Staff Office Clean Air Scientific Advi sory Committee (CASAC)

CHAIR Dr. Rogene Henderson , Scientist Emeritus, Lovelace Re spiratory Research Institute, Albuquerque, NM

MEMBERS Dr. Ellis Cowling , University Distinguished Professo r-at-Large, North Carolina State University, Colleges of Natural Resources and Agriculture and Life Sciences, North Carolina State University, Raleigh, NC

Dr. James D. Crapo , Professor, Department of Medi cine, National Jewish Medical and Research Center, Denver, CO

Dr. Frederick J. Miller , Consultant, Cary, NC

Mr. Richard L. Poirot , Environmental Analyst, Air Pollutio n Control Division, Department of Environmental Conservation, Vermont Agency of Natural Resources, Waterbury, VT

Dr. Frank Speizer , Edward Kass Professor of Medicine, Channing Laboratory, Harvard Medical School, Boston, MA

Dr. Barbara Zielinska , Research Professor, Division of At mospheric Science, Desert Research Institute, Reno, NV

SCIENCE ADVISORY BOARD STAFF
Mr. Fred Butterfield , CASAC Designated Federal Officer , 1200 Pennsylvania Avenue, N.W., Washington, DC, 20460, Phone : 202-343-9994, Fax: 202-233-0643 ( butterfield.fred@epa.gov ) (Physical/Courier/FedEx Address: Fred A. Butterf ield, III, EPA Science Advisory Board Staff Office (Mail Code 1400F), Woodies Building, 1025 F Street, N.W., Room 3604, Washington, DC 20004, Telephone: 202-343-9994)

A-1

### Appendix B – CASAC Ozone Review Panel Roster

U.S. Environmental Protection Agency Science Advisory Board (SAB) Staff Office Clean Air Scientific Advi sory Committee (CASAC) CASAC Ozone Review Panel

CHAIR Dr. Rogene Henderson *, Scientist Emeritus, Lovelace Respiratory Research Institute, Albuquerque, NM

MEMBERS
Dr. John Balmes , Professor, Department of Medicine, University of California San Francisco, University of California – San Fr ancisco, San Francisco, California

Dr. Ellis Cowling *, University Distinguished Professor-at-Large, North Carolina State University, Colleges of Natural Resources and Agriculture and Life Sciences, North Carolina State University, Raleigh, NC

Dr. James D. Crapo *, Professor, Department of Medi cine, National Jewish Medical and Research Center, Denver, CO

Dr. William (Jim) Gauderman , Associate Professor, Prev entive Medicine, Medicine, University of Southern California, Los Angeles, CA

Dr. Henry Gong , Professor of Medicine and Preventiv e Medicine, Medicine and Preventive Medicine, Keck School of Medi cine, University of Southe rn California, Downey, CA

Dr. Paul J. Hanson , Senior Research and Development Scientist, Environmental Sciences Division, Oak Ridge National Labor atory (ORNL), Oak Ridge, TN

Dr. Jack Harkema , Professor, Department of Pathobiol ogy, College of Veterinary Medicine, Michigan State University, East Lansing, MI

Dr. Philip Hopke , Bayard D. Clarkson Distinguished Pr ofessor, Department of Chemical Engineering, Clarkson University, Potsdam, NY

Dr. Michael T. Kleinman , Professor, Department of Commu nity & Environmental Medicine, University of Californi a – Irvine, Irvine, CA

Dr. Allan Legge , President, Biosphere Soluti ons, Calgary, Alberta, Canada

B-1Dr. Morton Lippmann , Professor, Nelson Institute of Environmental Medicine, New York University School of Medicine, Tuxedo, NY

Dr. Frederick J. Miller *, Consultant, Cary, NC

Dr. Maria Morandi , Assistant Professor of Environmen tal Science & Occupational Health, Department of Environmental Sciences, School of Public Health, University of Texas – Houston Health Science Center, Houston, TX

Dr. Charles Plopper , Professor, Department of Anatom y, Physiology and Cell Biology, School of Veterinary Medicine, University of California – Davis, Davis, California

Mr. Richard L. Poirot *, Environmental Analyst, Air Pollut ion Control Division, Department of Environmental Conservation, Vermont Agency of Natural Resources, Waterbury, VT

Dr. Armistead (Ted) Russell , Georgia Power Distinguished Professor of Environmental Engineering, Environmental Engineering Group, School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA

Dr. Elizabeth A. (Lianne) Sheppard , Research Professor, Biostatistics and Environmental & Occupational Health Sciences, Public Health and Community Medici ne, University of Washington, Seattle, WA

Dr. Frank Speizer *, Edward Kass Professor of Medicine, Channing Laboratory, Harvard Medical School, Boston, MA

Dr. James Ultman , Professor, Chemical Engineering, Bioengineering Program, Pennsylvania State University, University Park, PA

Dr. Sverre Vedal , Professor of Medicine, Department of Environmental and Occupational Health Sciences, School of Public Health and Community Medicine, University of Washington, Seattle, WA

Dr. James (Jim) Zidek , Professor, Statistics, Science, University of British Columbia, Vancouver, BC, Canada

Dr. Barbara Zielinska *, Research Professor, Division of A tmospheric Science, Desert Research Institute, Reno, NV

SCIENCE ADVISORY BOARD STAFF
Mr. Fred Butterfield , CASAC Designated Federal Officer , 1200 Pennsylvania Avenue, N.W., Washington, DC, 20460, Phone : 202-343-9994, Fax: 202-233-0643 ( butterfield.fred@epa.gov )

* Members of the statutory Clean Air Scientific Advisory Committee (CASAC) appointed by the EPA

Administrator (FY 2006)

B-2United StatesEnvironmental ProtectionAgencyOffice of Air Quality Planning and StandardsAir Quality Strategiesand Standards DivisionResearch Triangle Park, NCPublication No. EPA 452/R-07-007July 2007