Review of the National Ambient Air Quality 

Standards for Ozone:

Policy Assessment of Scientific 

and Technical Information 

 

OAQPS Staff Paper 
EPA-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 Carolina
 DISCLAIMER

 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 EPA. 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 Committee (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 included as an Attachment to this edition (Attachment B). In 

addition, this edition of the Staff Paper includes 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 and the model runs have been redone, generally 

resulting in small increases in the exposure estimates. The corrected results are presented 

in this edition of the Staff Paper and in the revised Exposure Analysis technical support 

document. The lung function risk estimates also have been redone based on the corrected 

exposure estimates and are generally slightly higher 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 figure. Additional minor edits to Chapters 4 and 

5 are listed in the errata. 
 ACKNOWLEDGMENTS 

 This Staff Paper is the product of the Office of Air Quality Planning and Standards 

(OAQPS). For the chapters on ozone-related health effects, exposure, risk, and primary 

standards, the principal authors include Karen Martin, David McKee, Harvey Richmond, Susan 

Lyon Stone, and John Langstaff. For the chapters on ozone-related welfare effects and 

secondary standards, the principal authors include Vicki Sandiford and Jeffrey Herrick. The 

principal authors of the chapter on air quality characterization include Lance McCluney and 

Michael Rizzo. Staff from other EPA offices, including the Office of Research and 

Development, the Office of General Counsel, and 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 available for public comment. This document has 

been informed by the expert advice and comments 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..........................................................................................................1-1 

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 ORGANIZATION OF THE DOCUMENT........... 1-7 

REFERENCES ...................................................................................................................... 1-9 

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

2.1 INTRODUCTION ..................................................................................................... 2-1 

2.2 CHEMICAL AND PHYSICAL PROPERTIES, 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 METHODS AND DATA QUALITY ............................ 2-12 

2.4.1 Effect of Measurement Precision 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.............................................................. 2-35 
ii

2.6 CHARACTERIZATION OF OZONE EPISODES................................................. 2-39 

2.7 POLICY RELEVANT BACKGROUND 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 O3 Exposure.....................................................3-27 

3.3.2.2 Mortality and Long-term O3 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 Relationships and Potential Thresholds.................3-46 

3.4.6 Health Effects of Pollutant Mixtures Containing O3 ..................................... 3-48 

3.5 BIOLOGICAL PLAUSIBILITY AND COHERENCE OF EVIDENCE ............... 3-50 

3.5.1 Animal-to-Human Extrapolation Issues ........................................................ 3-51 

3.5.2 Coherence and Plausibility of Short-term Effects on the Respiratory 

System...........................................................................................................3-55 

3.5.3 Coherence and Plausibility of Effects on the Cardiovascular System........... 3-58 

3.5.4 Coherence and Plausibility of Effects Related to Long-Term O3

Exposure........................................................................................................ 3-60 

3.5.5 Coherence and Plausibility of Short-Term Mortality-Related Health 

Endpoints ...................................................................................................... 3-61 

3.6 OZONE-RELATED IMPACTS ON PUBLIC HEALTH ....................................... 3-62 

3.6.1 Factors that Modify Responsiveness 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........................................................................3-69 
iii

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 Short-term Exposures to Ozone.........................3-85 

3.7.5 Confidence in Various Health Outcomes 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 Microenvironmental 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 in Indoor Microenvironments ................... 4-15 

4.3.4.3 Characterization of Population Demographics and Activity 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 ......................................................................................... 4-24 
iv

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 Factors 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: Representativeness 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 Selected Benchmark Levels.............................. 4-43 

4.7.3 Estimates of Repeated Exposures .................................................................. 4-64 

REFERENCES .................................................................................................................... 4-68 

5. CHARACTERIZATION OF HEALTH RISKS.........................................................5-1 

5.1 INTRODUCTION ..................................................................................................... 5-1 

5.1.1 Overview of Risk Assessment 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 Incidence and Population Estimates................... 5-37 
v

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 Alternative Ozone Standards............................ 5-63 

5.4.3 Sensitivity Analyses................................................................................... 5-81 

5.4.3.1 Impact of Alternative Assumptions About Background........................... 5-80 

5.4.3.2 Impact of Alternative Assumptions About the Shape of ExposureResponse Relationships for Lung Function Decrements ......................... 5-82 

5.4.4 Comparison with Risk Estimates from Prior Review................................ 5-87 

5.4.5 Key Observations....................................................................................... 5-92 

REFERENCES ..................................................................................................................5-100 

6. STAFF CONCLUSIONS AND RECOMMENDATIONS ON THE 

PRIMARY O3 NAAQS.................................................................................................. 6-1 

6.1 INTRODUCTION ..................................................................................................... 6-1 

6.2 APPROACH ..............................................................................................................6-1 

6.3 PRIMARY O3 STANDARD ..................................................................................... 6-4 

6.3.1 Adequacy of Current O3 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 Level of the Standard........................................6-77 

6.3.5 Form............................................................................................................... 6-82 

6.3.6 Summary of Staff Conclusions and Recommendations on the Primary 

O3 NAAQS.................................................................................................... 6-85 

6.4 SUMMARY OF KEY UNCERTAINTIES AND RESEARCH 

RECOMMENDATIONS RELATED TO SETTING A PRIMARY O3

STANDARD............................................................................................................ 6-87 

REFERENCES .................................................................................................................... 6-92 
vi

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 O3 Exposures......................................7-6 

7.3 NATURE OF EFFECTS ON VEGETATION .......................................................... 7-6 

7.3.1 Ozone Sensitive Plants and Their Relationship 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 Vegetation Impact from Ozone Exposure? .... 7-10 

7.4.2 Factors That Modify Functional 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 VEGETATION EXPOSURES TO OZONE............ 7-15 

7.5.1 Key Considerations in Vegetation 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 O3 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 ................................................................................7-65 
vii

7.6.3.4 Uncertainties In the Tree Risk Analyses...................................................7-69 

7.7 QUALITATIVE RISK: ECOSYSTEM 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 O3 NAAQS............................................................................................ 8-1 

8.1 INTRODUCTION ..................................................................................................... 8-1 

8.2 APPROACH ..............................................................................................................8-1 

8.3 SECONDARY O3 STANDARD ............................................................................... 8-4 

8.3.1 Adequacy of Current O3 Standard ...................................................................8-5 

8.3.1.1 Vegetation Evidence-, Exposure- and 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 and Cumulative Seasonal Forms........... 8-19 

8.3.4.2 Comparison of SUM06 and W126 Cumulative, ConcentrationWeighted Forms ....................................................................................... 8-21 

8.3.5 Level of the Standard.....................................................................................8-22 

8.3.6 Summary of Staff Conclusions and Recommendations on the Secondary 

O3 Standard....................................................................................................8-24 

8.4 SUMMARY OF KEY UNCERTAINTIES AND RESEARCH 

RECOMMENDATIONS RELATED TO SETTING A SECONDARY O3

STANDARD............................................................................................................ 8-27 

REFERENCES .................................................................................................................... 8-30 

ATTACHMENT A: Clean Air Scientific Advisory 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 EXPOSURE STUDIES....... 3C-1 

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

APPENDIX 5A.1: OZONE AIR QUALITY INFORMATION 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 ESTIMATES REPORTED IN HUANG ET AL. (2004)....... 5B-11 

APPENDIX 5C: ADDITIONAL HEALTH RISK ASSESSMENT ESTIMATES ................ 5C-1 

APPENDIX 6A: PREDICTED PERCENT OF COUNTIES WITH MONITORS (AND 

PERCENT OF POPULATION IN COUNTIES) NOT LIKELY TO MEET 

ALTERNATIVE OZONE STANDARDS ............................................................................... 6A-1 
ix

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 Physiological and Biochemical Changes in Humans and Animals .... 3-52 

3-2. Gradation of Individual Responses to Short-Term Ozone Exposure in Healthy 

Persons..................................................................................................................... 3-74 

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 equivalent ventilation rates (liters/min-m2)..............................4-2 

4-2. Urban areas and time periods modeled..............................................................................4-19 

4-3. Population coverage of modeled 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 ozone standard scenarios.........................................................................4-29 

4-7. 2002-2004 8-hr ozone design values for the modeled areas .............................................4-29 

4-8. Comparison of APEX 2002 base case simulations: 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. ............................................................... 4-35 

4-9. Comparison of APEX simulations: All CHAD vs. the NHAPS part of CHAD. 

Percent reduction1

 from the 2002 base case to the current standard of the 

number of children at moderate exertion 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 Sacramento, 2002. Numbers of people with at 

least six repeated 8-hour exposures above 0.06, 0.07, and 0.08 ppm-8hr............... 4-36 

4-11. Uncertainty of the estimated percent of children exposed at moderate exertion, 

Boston, 2002............................................................................................................ 4-40 

4-12. Uncertainty of the estimated percent of asthmatic children exposed at moderate 

exertion, Boston, 2002.............................................................................................4-40 

4-13. Uncertainty of the estimated percent reduction, from the 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 Population 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 Data for Lung Function Decrements........................5-19 

5-4. Locations, Health Endpoints, and Epidemiological Studies Included in the O3 Risk 

Assessment .............................................................................................................. 5-36 
x

5-5. Relevant Population Sizes for O3 Risk Assessment Locations ......................................... 5-38 

5-6. Baseline Mortality Rates (per 100,000 Population) Used in the O3 Risk Assessment 

 .................................................................................................................................5-39 

5-7. Baseline Rates for Hospital Admissions Used in the O3 Risk Assessment....................... 5-41 

5-8. Number and Percent of All School Age Children Estimated to Experience Lung 

Function Responses (FEV1 > 15%) Associated with 8-Hour O3 Exposure 

While Engaged in Moderate Exertion for Location-Specific O3 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 School Age Children Estimated to Experience 

Lung Function Responses (FEV1 > 10%) Associated with 8-Hour O3

Exposure While Engaged in Moderate Exertion for Location Specific O3

Seasons .................................................................................................................... 5-52

5-11. Number of Occurrences of Lung 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 Associated with Recent (April - September, 

2004) O3 Concentrations Above Background in Boston, MA ................................ 5-54 

5-13. Estimated Respiratory Symptoms Associated with Recent (April - September, 

2002) O3 Concentrations Above Background in Boston, MA ................................ 5-55 

5-14. Estimated Hospital Admissions Associated with Recent (April - September, 2004) 

O3 Concentrations in NY, NY ................................................................................ 5-56 

5-15. Estimated Hospital Admissions Associated with Recent (April - September, 2002) 

O3 Concentrations in NY, NY ................................................................................ 5-56 

5-16. Estimated Non-Accidental Mortality Associated with Recent (April - September, 

2004) O3 Concentrations......................................................................................... 5-57 

5-17. Estimated Non-Accidental Mortality Associated 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 Function 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 the 
xi

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 Days 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-related 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 Associated 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 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 .......................................... 6-51 

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 ........................................................... 6-66 

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 Severe Asthmatic Children in 

Boston, MA ............................................................................................................. 6-75 

6-10. Risks of Hospital Admissions for Respiratory 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 results with (A) and without (B) a 10% adjustment of hourly 

O3 exposures............................................................................................................ 7-54 

7-4. Percentage and number of counties with visible foliar injury (injured) and without 

injury (not injured) below various standard 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 ppm) and alternative standards are met.....7-66 
xii

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 Monitors from AQS and CASTNET ................................................ 2-11 

2-3. 1-hr Ozone Distributions across 12 Risk Areas, 2002-2004. ............................................ 2-16 

2-4. 8-hr Ozone Distributions across 12 Risk Areas, 2002-2004. ............................................ 2-17 

2-5. 24-hr Ozone Distributions 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 Exposure Index in U.S. Counties, 2001 AQS 

Data. ........................................................................................................................ 2-22 

2-9. Highest 3-month 12-hour W126 Exposure Index in U.S. Counties, 2001 AQS Data.......2-23 

2-10. Highest 3-month 12-hour SUM06 Exposure 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 Exposure Index in U.S. Counties, 2002 AQS and 

CASTNET Data. ..................................................................................................... 2-26 

2-13. Highest 3-month 12-hour W1126 Exposure Index in U.S. Counties, 2002 AQS and 

CASTNET Data. ..................................................................................................... 2-27 

2-14. Highest 3-month 12-hour SUM06 Exposure 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.......................................................................................... 2-49 
xiii

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 FEV1 changes following 6.6-hr exposures to a 

constant concentration of O3 or filtered air. ..............................................................3-7 

3-1 C. Frequency distributions of FEV1 changes following 6.6-hr exposures to a constant 

concentration of O3 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 Changes in Human Airway Epithelial Cells on 

Acute Exposure to Ozone........................................................................................3-54 

4-1. APEX Diagram....................................................................................................................4-8 

4-2. Modeled and measured weekly average personal exposures: means,.................................4-32

 minima, maximum for each week. Upland, CA.

4-3. Modeled and measured weekly average personal exposures: means, minima, maxima

 for each week. Lake Arrowhead, Crestline, and Running Springs,, CA................ 4-32 

4-4. Uncertainty of percent of children with exposures above 0.06 ppm-8hr ......................... 4-38 

4-5. Uncertainty of percent of children with exposures above 0.07 ppm-8hr ......................... 4-39 

4-6. Uncertainty of percent of children with exposures above 0.08 ppm-8hr ......................... 4-39 

4-7. Comparison of exposures for different population groups................................................ 4-44 

4-8. Comparison of exposures for different years .................................................................... 4-44 

4-9. Percent of children with repeated 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 Risk Assessment Based on Controlled Human 

Exposure Studies .....................................................................................................5-17 

5-2. a, b, c. Probabilistic Exposure-Response Relationships for FEV1 Decrement > 

10%, > 15%, and > 20% for 8-Hour Exposures Under Moderate Exertion.......... 5-24 

5-3a, b, c. Probabilistic Exposure-Response Relationships for FEV1 Decrement > 10% 

and > 15% for 8-Hour Exposures Under Moderate Exertion: 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 .....................................................................................................................5-31 

5-6. Estimated Annual Percent of Non-Accidental Mortality Associated with Short-Term 

Exposure to Recent O3 Concentrations Above Background for the Period 
xiv

April – September (Based on Bell et al., 2004) – Total and Contribution of 

24-Hour Average O3 Ranges................................................................................... 5-62 

5-7. Percent of All Children (Ages 5-18) Engaged 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 4th-highest Daily Maximum 8-Hour 

Standards, for Location-Specific O3 Seasons (Based on Adjusting 2002 Air 

Quality.....................................................................................................................5-66 

5-8. Percent of All Children (Ages 5-18) Engaged in Moderate Exertion Estimated to 

Experience At Least One Lung Function Response (Decrement in FEV1 ≥ 15 

%) Associated with Recent Air Quality (2002) and Just Meeting the Current 

and Alternative Average nth Daily Maximum 8-Hour Standards, for 

Location-Specific O3 Seasons (Based on Adjusting 2002 Air Quality)*................ 5-67 

5-9. Percent of Asthmatic Children (Ages 5-18) Engaged in Moderate Exertion 

Estimated to Experience At Least One Lung Function Response (Decrement 

in FEV1 ≥ 10%) Associated with Exposure to O3 Concentrations That Just 

Meet the Current and Alternative Average 4th-highest Daily Maximum 8-

Hour Standards, for Location-Specific O3 Seasons (Based on Adjusting 2002 

Air Quality) .............................................................................................................5-69 

5-10. Percent of Asthmatic Children (Ages 5-18) Engaged in Moderate Exertion 

Estimated to Experience At Least One Lung Function Response (Decrement 

in FEV1 ≥ 10 %) Associated with Recent Air Quality (2002) and Exposure to 

O3 Concentrations That Just Meet the Current and Alternative 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 Associated with Recent (April-September 

2002) O3 Levels and with Levels Just Meeting Alternative Average 4thHighest Daily Maximum 8-Hour Ozone Standards ................................................5-72 

5-12. Estimated Incidence of (Unscheduled) Respiratory Hospital Admissions per 

100,000 Relevant Population in New York Associated with Recent (April – 

September, 2002) O3 Levels and with O3 Levels Just Meeting Alternative 

Average 4th-Highest Daily Maximum 8-Hour Standards....................................... 5-73 

5-13. Estimated Incidence of Non-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. Cities Function), Based on 2002 Ozone Concentrations.......... 5-74 

5-14. Annual Warm Season (April to September) Estimated O3-Related Non-Accidental 

Mortality Associated with Recent (2002) O3 Levels and Levels Just Meeting 

Alternative 8-hr O3 Standards (Using Bell et al., 2004 – 95 U.S. Cities 

Function) .................................................................................................................5-76 

5-15. Estimated Annual Percent of Non-Accidental Mortality Associated with ShortTerm Exposure to O3 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 Contribution of 24-Hour Average O3 Ranges...................... 5-79 
xv

5-16. Sensitivity Analysis of Estimated Percent Change in O3-related Non-Accidental 

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................................................................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 FEV1 >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 FEV1 >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 Asthmatic School Age Children Experiencing at 

Least One Decrement in FEV1 >10% 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.................................... 6-70 

6-4. Percent Changes in Numbers of Asthmatic School Age Children Experiencing at 

Least One Decrement in FEV1 > 10% 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.................................... 6-71 

6-5. Percent Changes in O3-Related Non-Accidental Mortality Incidence 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 (Using Bell et al., 2004 – 95 U.S. Cities) ..............................................6-72 

6-6. Percent Changes in O3-Related Non-Accidental Mortality Incidence 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 (Using Bell et al., 2004 – 95 U.S. Cities) .............................................. 6-73 

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. ................................................................................................................ 7-18 

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.......................................................................................................................... 7-20 
xvi

7-3. Highest 3 month 12-hr W126 values from monitors in National Parks in the 

Mountain West (A) and California (B). ..................................................................7-21 

7-4. Maximum 3-month 12-hr SUM06 plotted against maximum 3-month 12-hr W126. 

Data points are from the AQS and CASTNET O3 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 Exposure – Max 3-months for 2001: Quadratic 

Rollback to just meet 4th-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 Highest 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 Exposure – 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 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. .............................. 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-month 12-hr W126 with 

a 10% downward adjustment of hourly O3 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 O3

exposure (growing period 12-hr W126, July 7 – Sept. 20) ..................................... 7-57
xvii

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 studies referenced in Figure 3-4 was added. 

For Chapter 4:

The following tables and figures were revised 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, continuing onto page 4-2, a redundant sentence was 

removed. 

The footnote on page 4-1 was revised to clarify why the results for active children were 

not presented in the Staff Paper. The corrected exposure modeling, 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 modeled and measured weekly average personal 

exposures) were changed to present the corrected exposure estimates. The discussion of 

these results on pages 4-32 and 4-34 was revised accordingly, and now concludes that the 

exposures predicted by APEX are generally 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 revised 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 Assessment TSD and Risk Assessment TSD were 

updated to reflect the corrected final reports. 

For Chapter 6:

The following tables and figures were revised 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 Chapters 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 (OAQPS), evaluates the policy implications of the 

key studies and scientific information contained in the document, Air Quality Criteria for Ozone 

and Related Photochemical Oxidants (USEPA, 2006; henceforth referred to as the CD), prepared 

by EPA’s National Center for Environmental Assessment (NCEA). This document also presents 

and interprets results from several quantitative analyses (e.g., air quality analyses, human 

exposure analyses, human health risk assessments, 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 (O3), and presents factors relevant 

to the evaluation of current primary and secondary 03 standards. Finally, this document presents 

staff conclusions and recommendations on a range 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 secondary (welfare-based) O3 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 appropriate to retain or revise the NAAQS for O3. 

This policy assessment considers the available scientific evidence and quantitative risk-based 

analyses, together with related limitations and uncertainties, and focuses on the basic elements of 

air quality standards: indicator, averaging times, forms,1

 and levels. These elements, which 

serve to define each standard, must be considered collectively in evaluating the health and 

welfare protection afforded by the O3 standards. Our conclusions and policy recommendations 

on whether, and if so how, to revise these standard 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 informed 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 use to all parties interested in the O3 NAAQS review, 

it is written with an expectation that the reader 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 Administrator 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 air results from numerous or diverse mobile or 

stationary sources” and, if listed, to issue air quality criteria for them. These air quality criteria 

are intended to “accurately reflect the latest scientific 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 pollutants identified under section 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 criteria and allowing an adequate margin of safety, 

are requisite to protect the public health.”3

 A secondary standard, as defined in Section 

109(b)(2), must “specify a level of air quality the attainment and maintenance of which, in the 

judgment of the Administrator, based on such criteria, is requisite to protect the public welfare 

from any known or anticipated adverse effects associated with the presence of [the] pollutant in 

the ambient air.”4

 The requirement that primary standards include an adequate margin of safety was 

intended to address uncertainties associated with inconclusive scientific and technical 

information available at the time of standard setting. It was also intended to provide a reasonable 

degree of protection against hazards that research has not yet identified. 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 representative sample of persons comprising the sensitive group 

rather than to a single person in such a group.” [S. Rep. No. 91-1196, 91st Cong., 2d Sess. 10 (1970)]. 

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, 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.” 
 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 selecting primary standards that include an adequate 

margin of safety, the Administrator is seeking not only to prevent pollution levels that have been 

demonstrated to be harmful but also to prevent 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 considers such factors as the nature and severity 

of the health effects, the size of the sensitive population(s) at risk, and the kind and degree of the 

uncertainties that must be addressed. The selection 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 and 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 the 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 the national ambient air quality standards . . . and shall make 

such revisions in such criteria and standards and promulgate such new standards as may be 

appropriate . . . .” Section 109(d)(2) requires that an independent scientific review committee 

“shall complete a review of the criteria . . . and the national primary and secondary ambient air 

quality standards . . . and shall recommend to the Administrator any new . . . standards and 

revisions of existing criteria and standards as may be appropriate . . . .” Since the early 1980's, 

this independent review function has been performed 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) O3 is formed from biogenic precursor emissions and as a 

result of anthropogenic precursor emissions. Naturally occurring O3 in the troposphere can result 

from biogenic organic precursors reacting with naturally occurring nitrogen oxides (NOx) and by 

stratospheric O3 intrusion into the troposphere. Anthropogenic precursors of O3, specifically 

NOx and volatile organic compounds (VOC), originate from a wide variety of stationary and 

mobile sources. Ambient O3 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 primary 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 first periodic review of the criteria and 

standards for O3 and other photochemical oxidants (44 FR 8202). In that action, EPA made 

significant revisions to the original standard: the level of the primary and secondary NAAQS 

was changed to 0.12 ppm; the indicator was changed to O3; 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 ppm (i.e., attainment of the standard occurs when that number 

is equal to or less than one). 

 On March 9, 1993, EPA concluded its second periodic review of the criteria and 

standards for O3 by deciding that revisions to the O3 NAAQS were not warranted at that time (58 

FR 13008). The timing of this decision was required by a court order issued to resolve a lawsuit 

filed to compel EPA to complete its review of the criteria and standards for O3 in accordance 

with the Act. This decision reflected EPA's review of relevant scientific and other information 

assembled since the last review, as contained in the 1986 O3 CD (U.S. EPA, 1986), its 

Supplement (U.S. EPA, 1992), and the 1989 O3 Staff Paper (U.S. EPA, 1989), although it did not 

take into consideration a large number of studies on the health and welfare effects of O3 

published since the literature was last assessed in the O3 Supplement. The final decision 

emphasized the Administrator's intention to proceed as rapidly as possible with the next periodic 

review of the air quality criteria 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 O3 NAAQS on July 18, 1997, based on the 1996 O3 CD (U.S. EPA, 1996a) 

and 1996 O3 Staff Paper (U.S. EPA, 1996b). EPA revised the primary and secondary O3 

standards on the basis of the then latest scientific evidence linking exposures to ambient O3 to 

adverse health and welfare effects at levels allowed by the 1-hr average standards (62 FR 38856). 

The O3 standards were revised by replacing the existing primary 1-hr average standard with an 8-

hr average O3 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 concentration, averaged over three 

years. The secondary O3 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 O3 NAAQS, petitions for review were filed 

addressing a broad range of issues. On May 14, 1999, in response to those challenges, the U.S. 
 1-5

Court of Appeals for the District of Columbia Circuit (D.C. Circuit Court) remanded the O3

NAAQS to EPA, finding that section 109 of the 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 potential beneficial health effects of O3 pollution in shielding the 

public from the effects of solar ultraviolet (UV) radiation, as well as the adverse health effects. 

 EPA petitioned the U.S. Supreme Court for certiorari 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 O3. 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 case to the D.C. Circuit Court to consider those challenges to 

the O3 NAAQS that had not been addressed by that Court’s earlier decisions.6 On March 26, 

2002, the D.C. Circuit Court issued its final decision, finding the 1997 O3 NAAQS to be “neither 

arbitrary nor capricious,” and denying the remaining petitions for review.7

 

 In response to the D.C. Circuit Court’s remand to consider the potential beneficial health 

effects of O3 pollution in shielding the public from the effects of solar (UV) radiation, on 

November 14, 2001, EPA proposed to leave the 1997 8-hr NAAQS unchanged (66 FR 52768). 

After considering public comment on the proposed decision, EPA reaffirmed the 8-hr O3

NAAQS set in 1997 (68 FR 614). Finally, on April 30, 2004, EPA announced the decision to 

make the 1-hr O3 NAAQS no longer applicable to areas one year after the effective date of the 

designation of those areas for the 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. EPA, 2002) for the preparation of the CD was 

released in November 2002 for CASAC and public review. EPA held a series of workshops in 

mid-2003 on several draft chapters of the CD to obtain broad input from the relevant scientific 

communities. These workshops helped to inform the preparation of the first draft CD (U.S. 

EPA, 2005a), which was released for CASAC 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 draft CD, NCEA revised the planned format of 

the CD described in the 2002 work plan. These revisions were made as part of a collaborative 

effort with OAQPS staff to modify the review process 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 interpretative 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. The modified review process envisions that key 

policy-relevant issues will be identified earlier 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 held on May 4-5, 2005, to review the first draft CD, 

this new format for the CD was met with general approval of CASAC and the public. A second 

draft CD (EPA, 2005b) was released for CASAC 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, CASAC offered additional advice to the Agency concerning Chapter 

8 of the final CD (Integrative Synthesis) to help inform the second draft Staff Paper (Henderson, 

2006b). The second draft Staff Paper was released 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 recommendations from CASAC as 

well as public comments have been taken into account in preparing this 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 plaintiffs representing national environmental 

organizations, alleging that EPA had failed to complete 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 this review, entered by the court on December 16, 

2004, provides that EPA sign for publication notices of proposed and final rulemaking 

concerning its review of the O3 NAAQS no later than March 28, 2007 and December 19, 2007, 

respectively. This consent decree was further 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 dates for signing the publication 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 ORGANIZATION OF THE DOCUMENT 

 The policy assessment in this Staff Paper is based on staff’s evaluation of the policy 

implications of the scientific evidence contained 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 identification of a range of 

options on certain elements of the O3 standards under review. While the CD focuses on new 

scientific information available since the last review, it appropriately integrates that information 

with scientific criteria from previous reviews. The quantitative analyses presented in this Staff 

Paper (and described in more detail in technical support documents) are based on the most 

recently available air quality information, so as to provide current characterizations of O3 air 

quality patterns and estimated health and environmental risks related to exposure to ambient O3

concentrations. 

 Following this introductory chapter, the Staff Paper is organized into three main parts: the 

characterization of ambient O3 air quality data; O3-related health effects and primary O3

NAAQS; and O3-related welfare effects and secondary O3 NAAQS. The content of these parts is 

discussed more fully below. 

The characterization of ambient O3 and related photochemical oxidants is presented in 

Chapter 2 and includes information on O3 properties, current O3 air quality patterns, historic 

trends, and background levels. This chapter provides a frame of reference for subsequent 

discussion of current and alternative O3 NAAQS and alternative forms of O3 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 conclusions from the CD, and an examination of 

issues related to the quantitative assessment of evidence from controlled human exposure and 

epidemiological studies. Chapters 4 and 5 describe the scope and methods used in conducting 

human exposure and health risk assessments and present results from those assessments. 

Chapter 6 includes staff conclusions and policy recommendations on the adequacy of the current 

primary standard and on an appropriate range of alternative primary standards for the 

Administrator’s consideration, together with a discussion 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 O3 welfare effects evidence and discusses the scope and methods 

used in conducting vegetation-related exposure and risk assessments. Chapter 8 includes staff 

conclusions and policy recommendations on the adequacy of the current secondary standard and 

on an appropriate range of alternative secondary standards that for the Administrator’s 
 1-8

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 Primary and Secondary Ambient Air Quality Standards: Revisions to the National 

Ambient Air Quality Standards for Photochemical Oxidants, Final Rule. 40 CFR 50; Federal Register 

44: 8202. 

Federal Register (1993) National Ambient Air Quality Standards 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 Standards 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 and 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) Project 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/recordisplay.cfm?deid=137307
 2-1

2. AIR QUALITY CHARACTERIZATION 

2.1 INTRODUCTION 

 This chapter generally characterizes ambient ozone (O3) and related photochemical 

oxidants in terms of measurement methods, recent concentrations and trends, relationships 

between different air quality indicators, and estimates of policy-relevant background. This 

information is useful for interpreting the available exposure, health, and welfare effects 

information, and for evaluating the adequacy of the current primary and secondary standards for 

O3 and developing options for alternative standards. The information presented in this chapter 

was drawn from the 2006 Criteria Document (CD) and additional analyses of data from various 

O3 monitoring networks. 

 This chapter particularly focuses on 1-hr, 8-hr, and 24-hr average concentrations metrics 

in characterizing urban O3 air quality because these are the metrics 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 Chapter 7 of this Staff Paper, both the current 

secondary standard 8-hr. metric and the cumulative, concentration-weighted metrics, SUM06 

and W126 are used. 

 Although this chapter focuses on 2002-2004 air quality data in order to be consistent with 

the CD, recent observations demonstrates the 2005 O3 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 levels being lower by 5%. Meteorological 

conditions for 2005 were similar to those observed in 2002 which was much hotter than 2004 

and, therefore, more conducive to O3 formation. Furthermore, the O3 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 NOx 

SIP Call1 which occurred in 2002 for many states east of the Mississippi River. 

2.2 CHEMICAL AND PHYSICAL PROPERTIES, FORMATION, AND TRANSPORT 

2.2.1 Properties and Formation 

The atmosphere can be divided into 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 surface to about 8 km above the surface in polar 

 1

 EPA's rule, known as the NOx SIP Call, was designed to reduce regional transport of O3 and O3-forming 

pollutants in the eastern half of the United States by requiring 21 states to reduce O3- season NOx 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 placed on concentrations 

of O3 occurring in the lower troposphere, in particular in the PBL (CD, p.2-1). 

Ozone chemistry in the presence of sunlight, nitrogen oxides (NOx) and volatile organic 

carbon (VOC) is well understood and a central component of modern air quality models. The 

chemical formation of O3 in the troposphere results from the oxidation of nitric oxide (NO) to 

nitrogen dioxide (NO2) by organic (RO2) or hydro-peroxy (HO2) radicals. Photolysis (the 

chemical process of breaking down molecules into smaller units through the absorption of light) 

of NO2 yields NO and a ground-state oxygen atom, O(3

P), which then reacts with molecular 

oxygen to form O3 (CD, p.2-2). 

 Oxidized nitrogen compounds are emitted to the atmosphere mainly as NO, which is 

oxidized to NO2 which subsequently can be reduced back to NO. Consequently, NO and NO2 are 

often grouped together into their own family called NOx (CD, p.2-3). Oxidized nitrogen 

containing compounds are essential to the formation of O3 in the air. There are a large number of 

oxidized nitrogen containing compounds in the atmosphere including NO, NO2, nitrate (NO3), 

nitrous acid (HNO2), nitric acid (HNO3), nitrogen pentoxide (N2O5), pernitric acid (HNO4), 

peroxy acetyl nitrate (PAN) and its homologues, other organic nitrates and particulate nitrate. 

Collectively these species are referred to as NOy. NOx is considered a good surrogate for NOy

and, thus, is commonly monitored and reported (see Table 2-1). 

 In urban areas, both biogenic and anthropogenic VOCs are important for O3 formation. 

Table 2-2 lists a variety of VOC sources (see http://www.epa.gov/airtrends/econemissions.html). The categories in the table are self explanatory with the exception of the fires 

and miscellaneous categories. The fires category includes both wild fires and prescribed burns. 

The miscellaneous category includes mainly structural 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, highway vehicles have been the single 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, solvent use and highway vehicles were the two 

main sources of VOCs with roughly equal contributions to the total emissions. 

In non-urban, vegetated areas, biogenic VOCs emitted from the vegetation tend to be the 

most important. In the remote troposphere, CH4 and CO are the main carbon-containing 

precursors to O3 formation. In coastal environments and other selected environments, atomic Cl 

and Br radicals can also initiate the oxidation of VOCs (CD, p.2-2 and 2-3). 
2-3

Table 2-1. NOx Emission Sources, 1970-2004

Nitrogen Oxides (NOx) 

National Emissions Totals (thousands of tons) 

Source Category 1970 1975 1980 1985 1990 1991 1992 FUEL COMB. ELEC. UTIL. 4,900 5,694 7,024 6,127 6,663 6,519 6,504 FUEL COMB. INDUSTRIAL 4,325 4,007 3,555 3,209 3,035 2,979 3,071 FUEL COMB. OTHER 836 785 741 712 1,196 1,281 1,353 CHEMICAL & ALLIED PRODUCT MFG 271 221 213 262 168 165 163 METALS PROCESSING 77 73 65 87 97 76 81 PETROLEUM & RELATED INDUSTRIES 240 63 72 124 153 121 148 OTHER INDUSTRIAL PROCESSES 187 182 205 327 378 352 361 SOLVENT UTILIZATION 0 0 0 2 1 2 3 STORAGE & TRANSPORT 0 0 0 2 3 6 5 WASTE DISPOSAL & RECYCLING 440 159 111 87 91 95 96 HIGHWAY VEHICLES 12,624 12,061 11,493 10,932 9,592 9,449 9,306 OFF-HIGHWAY 2,652 2,968 3,353 3,576 3,781 3,849 3,915 MISCELLANEOUS 330 165 248 310 369 286 255 MISCELLANEOUS NA NA NA NA NA NA NA TOTAL 26,883 26,377 27,079 25,757 25,529 25,179 25,260 Total without FIRES 26,883 26,377 27,079 25,757 25,167 24,932 25,026 FIRES NA NA NA NA 362 247 234 
2-4

Table 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 FUEL COMB. ELEC. UTIL. 6,384 6164 6276 6232 5721 5330 4917 FUEL COMB. INDUSTRIAL 3,144 3151 3101 3050 2709 2723 2757 FUEL COMB. OTHER 1,298 1197 1177 1101 768 766 779 CHEMICAL & ALLIED PRODUCT MFG 158 125 127 129 102 105 107 METALS PROCESSING 98 83 89 89 86 89 94 PETROLEUM & RELATED INDUSTRIES 110 139 143 143 120 122 124 OTHER INDUSTRIAL PROCESSES 399 433 460 467 451 479 504 SOLVENT UTILIZATION 3 2 3 3 4 4 4 STORAGE & TRANSPORT 6 15 16 16 14 15 16 WASTE DISPOSAL & RECYCLING 99 153 157 163 162 129 130 HIGHWAY VEHICLES 8,876 8733 8792 8619 8371 8394 7774 OFF-HIGHWAY 4,113 4179 4178 4156 4084 4167 4156 MISCELLANEOUS 267 412 187 179 251 276 184 MISCELLANEOUS NA 0 0 0 0 0 0 TOTAL 24,956 24787 24705 24348 22845 22598 21549 FIRES 258 405 179 172 236 263 171 Total without FIRES 24,698 24,382 24,526 24,176 22,609 22,335 21,378 
2-5

Table 2-2. VOC Emission Sources, 1970-2004 

Volatile Organic Compounds (VOC) 

National Totals (thousands of tons) 

Source Category 1970 1975 1980 1985 1990 1991 1992 FUEL COMB. ELEC. UTIL. 30 40 45 32 47 44 44 FUEL COMB. INDUSTRIAL 150 150 157 134 182 196 187 FUEL COMB. OTHER 541 470 848 1,403 776 835 884 CHEMICAL & ALLIED PRODUCT MFG 1,341 1,351 1,595 881 634 710 715 METALS PROCESSING 394 336 273 76 122 123 124 PETROLEUM & RELATED INDUSTRIES 1,194 1,342 1,440 703 611 640 632 OTHER INDUSTRIAL PROCESSES 270 235 237 390 401 391 414 SOLVENT UTILIZATION 7,174 5,651 6,584 5,699 5,750 5,782 5,901 STORAGE & TRANSPORT 1,954 2,181 1,975 1,747 1,490 1,532 1,583 WASTE DISPOSAL & RECYCLING 1,984 984 758 979 986 999 1,010 HIGHWAY VEHICLES 16,910 15,392 13,869 12,354 9,388 8,860 8,332 OFF-HIGHWAY 1,616 1,917 2,192 2,439 2,662 2,709 2,754 MISCELLANEOUS 1,101 716 1,134 566 1,059 756 486 TOTAL 34,659 30,765 31,106 27,404 24,108 23,577 23,066 FIRES 917 587 1,024 465 983 678 407 Total without FIRES 33,742 30,178 30,082 26,939 23,125 22,899 22,659 
2-6

Table 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 FUEL COMB. ELEC. UTIL. 44 50 52 56 54 62 61 FUEL COMB. INDUSTRIAL 206 179 175 174 172 173 176 FUEL COMB. OTHER 823 893 893 889 919 949 950 CHEMICAL & ALLIED PRODUCT MFG 660 388 388 394 251 254 262 METALS PROCESSING 125 73 78 78 66 67 71 PETROLEUM & RELATED INDUSTRIES 642 477 487 485 457 428 441 OTHER INDUSTRIAL PROCESSES 450 435 438 443 438 454 420 SOLVENT UTILIZATION 6,183 5477 5621 5149 5036 4831 5012 STORAGE & TRANSPORT 1,652 1294 1328 1327 1237 1176 1192 WASTE DISPOSAL & RECYCLING 1,067 509 518 535 487 415 420 HIGHWAY VEHICLES 6,749 6221 5985 5859 5681 5325 4952 OFF-HIGHWAY 2,890 2935 2752 2673 2682 2644 2622 MISCELLANEOUS 551 1940 816 718 791 733 532 TOTAL 22,041 20871 19530 18782 18270 17512 17111 FIRES 464 1870 744 645 667 615 412 Total without FIRES 21,577 19001 18786 18136 17603 16898 16699 
 2-7

 The effects of sunlight on O3 formation, aside from the role of solar radiation in 

meteorological processes, depend on its intensity and its spectral distribution. Intensity varies 

diurnally, seasonally, and with latitude, but the effect of latitude is strongest in the winter. 

Ultraviolet radiation from the sun plays a key role in initiating the photochemical processes 

leading to O3 formation and affects individual photolytic reaction steps. However, there is little 

empirical evidence in the literature directly linking day-to-day variations in observed surface UV 

radiation levels with variations in tropospheric O3 levels (CD, p.AX2-90). 

2.2.2 Relationship of Ozone to Photochemical Oxidants 

 The relationship between O3, other oxidants, and oxidation products is complex and 

involves many factors. Most notably, O3 acts as a generator of hydroxyl radicals (OH) 

propagating a variety of integrated and cascading reactions yielding additional oxidizing species 

(e.g., hydroperoxy radical, HO2; organic peroxy radicals, RO2; hydrogen peroxide, H2O2; 

nitrogen dioxide, NO2; many of which are short lived in the atmosphere. These “oxidizing” 

species would be expected, like O3, to interfere with cellular processes leading to adverse health 

effects. Oxidants also drive the formation of particle bound sulfate, nitrate and organic carbon; 

which are principal components of secondarily formed PM2.5; and influence positively the 

formation or reaction of toxic gases such as peroxy acetyl nitrate (PAN), aldehydes (e.g., 

formaldehyde, acetaldehyde, acrolein), organic nitrates and organic amines. Furthermore, 

deposition and subsequent adverse aquatic and terrestrial effects generally are enhanced through 

availability of reactive oxidant species. These “enhanced” deposition impacts include 

acidification, near field deposition of reactive mercury, and other nitrogen-based eutrophication 

effects (See Figure 2-1). Benefits of reducing O3 extend beyond that associated with O3

autonomously, given the role of O3 as an oxidizing agent elevating levels of atmospheric 

components responsible for a broad range of adverse human health and environmental impacts. 

2.2.3 Transport 

 The transport of O3 and other secondary pollutants is determined by meteorological and 

chemical processes extending typically 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 Chameides (2000) suggests that O3 can be transported over a few 

thousand kilometers in the upper boundary layer of the eastern half of the United States during 

specific O3 episodes. Convection is capable of transporting O3 and its precursors vertically 

through the troposphere as shown in Annex AX2.3.2 of the CD. Nocturnal low-level jets (LLJs) 
2-8

Figure 2-1. Atmospheric Processes Affecting the Formation of Photochemical Oxidants and Particulate M

links illustrating relationships across, criteria pollutants and HAPs including mercury, as well as connections acr

secondarily formed species, gases, particulate matter and deposition. Primary emissions are distinguished from species. Note that this diagram is a highly condensed model that does not capture numerous various heterogenecomplex chemical pathways. Key atmospheric species that are involved in many reactions across pollutant categthe hydroxyl radical, OH. Primary PM emissions are not included as they interact marginally with other other at(adopted from NARSTO, 2002). 
 2-9

can also transport pollutants hundreds of kilometers over the mid-Atlantic region, the central 

U.S. and California (Zhang et al., 2001). Turbulence associated with LLJs can bring these 

pollutants to the surface and result in secondary O3 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 Mexico City resulting in a greater frequency and 

duration of days with high O3 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 (AQS) 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 technique 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 fill in the gaps left by a sparse rural monitoring 

network in the western United States. 

Air quality models are often used to simulate the formation, transport, and decay of air 

pollution. The CMAQ modeling system is a comprehensive three-dimensional grid-based 

Eulerian air quality model designed to estimate O3 and particulate concentrations and deposition 

over large spatial scales (Dennis et al., 1996; Byun and Ching, 1999; Byun and Schere, 2006). 

The CMAQ model is a publicly available, widely-used, peer-reviewed, 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 O3, as well as sulfate, nitrate, and organic aerosols. 

2.3.1 Air Quality System (AQS) 

 EPA’s ambient air quality surveillance regulations are found at 40 CFR Part 58. Section 

58.20 requires States to provide for the establishment of air quality surveillance 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 standards have been established in 

40 CFR Part 50. SLAMS, National Air Monitoring Stations (NAMS), which are a subset of 

SLAMS, and Photochemical Assessment Monitoring Stations (PAMS) must meet the 

requirements of 40 CFR Part 58, Appendices A (Quality Assurance Requirements), C (Ambient 

Air Quality Monitoring Methodology), D (Network Design Criteria), 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 which are currently active. Of these, over 3000 

measure and report O3 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, descriptive information about each monitoring station 

(including its geographic location and its operator), and data quality assurance/quality control 

information. The Office of Air Quality Planning 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 Plans for Non-Attainment Areas, perform modeling 

for permit review analysis, and other 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 O3 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 O3

monitors are also included the average upper bounds of bias and precision 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 O3. Operating since 1987, CASTNET is used in conjunction with other national 

monitoring networks to provide information for evaluating 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 operated and funded with the National Park Service. 

In 1986, EPA established the National Dry Deposition Network (NDDN) to obtain field data on 

rural deposition patterns and trends at different locations throughout the United States. The 

network consisted of 50 monitoring sites that derived dry deposition data based on measured air 

pollutant concentrations and modeled dry deposition velocities estimated from meteorology, land 

use, and site characteristic data. In 1990, amendments 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, EPA, in cooperation with the National Oceanic 

Atmospheric Administration (NOAA), 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 and accuracy. Overall, CASTNET O3 monitors are stable showing 

only very small variation (U.S. EPA 2003, p.22). 
2-11

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Figure 2-2. Locations of Ozone Monitors from AQS and CASTNET 
 2-12

2.4 OZONE MONITORING METHODS AND DATA QUALITY 

2.4.1 Ozone Monitoring Methods 

 Ozone monitoring is conducted almost exclusively 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-path UV absorption instrument maintained under 

carefully controlled conditions at the National Institute of Standards and Technology (NIST) 

(CD, p.2-22). Most O3 UV instruments reference the NIST method through a network of 

Standard Reference Photometers (SRPs) that are maintained and operated by EPA. 

 Several reports in the reviewed scientific literature have investigated interferences in O3 

detection via UV radiation absorption and chemiluminescence which is the reference method but 

almost never employed. These include the effects of water vapor, VOC’s, aromatic compounds 

and their oxidation products, and other organic and inorganic compounds. Water vapor had no 

significant impact on UV absorption-based instruments, 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 oxidation products were found to generate a positive but small 

interference in the UV absorption instruments. However, when the results are applied to ambient 

concentrations of toluene and NOx

, 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 O3 in an urban environment (CD, p.2-25). 

 Although not widely used, O3 measurements by differential optical absorption 

spectroscopy (DOAS) at a variety of wavelengths in the UV and visible parts of the spectrum. 

Comparisons of DOAS results to those from 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 O3. 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 O3

concentration (Cox and Camalier, 2006). Daily maximum 8-hr O3 values were simulated using a 

Weibull distribution to yield a “true” three-year averaged O3 design value without the influence 

of measurement error. 

From 2002 to 2004, the average precision in the collected O3 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 O3 monitors for 
 2-13

the 2002 through 2004 O3 seasons, a second set of 8-hr O3 concentrations was generated to 

incorporate the precision data from the O3 monitoring network to account for instrument 

measurement error. The result was a value which reflected the “true” O3 design value plus 

measurement error. The difference between the 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 the differences between the two previously 

described design values were summarized. Table 2-3 shows the results of the analysis. The 

percentiles presented in the table reflect the percentage of sites 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 O3 sites are at or below, the standard deviation of the difference between the 8-hr 

design values is less than 0.001 ppm. 

A second exercise was performed to incorporate systematic bias error which includes the 

instrument drift, noise, precision and calibration error associated with the UV absorption method. 

It was assumed that each 8-hr measurement was subjected to this randomly occurring bias which 

had an average of zero and a standard deviation 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 results 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), which is equivalent to the nearest part per billion 

(ppb).2

 The State of California also reached a similar conclusion regarding the precision of the 

existing ozone monitoring methodology (California Environmental Protection Agency, 2005). 

2.5 CHARACTERIZATION OF GROUND-LEVEL OZONE CONCENTRATIONS 

2.5.1 Metrics 

 This section characterizes ground level O3 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 concentration weighted statistics, SUM06 and W126, 

are summarized to show how O3 varies over space and time. The 1-hr and 8-hr daily maximum 

averaging times reflect the former and current O3 standards, and much of the health effects 

literature for O3 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 National 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 decimal place are truncated would be retained. 
2-14

Table 2-3. Relationship between Precision of 1-hour Ozone Data and Corresponding Standard Deviation 

Values 

Precision of 1- hour 

ozone value (%) 

Nationwide Percentile 

Standard Deviati

Difference in DV's 

1.63 25 0.27 2.22 50 0.34 2.97 75 0.45 3.89 90 0.57 4.52 95 0.63 
 2-15

average has been used for several personal exposure studies (CD, pp.3-72 – 74). The SUM06 

and W126 have been used frequently in the scientific literature and CD in studying and assessing 

the relationship between O3 exposures and adverse effects on vegetation. The daily maximum 8-

hr values are found by first calculating running or moving 8-hr values 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 the 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 summarized. 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 hourly concentrations measured 

from midnight to midnight. 

The maximum, 3 month, 12 hour SUM06 statistic 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 O3 monitoring season, the largest 

consecutive 3-month sum of the daily values is calculated according 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 when 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. The only difference is the weighting function where 

the W126 statistic is a continuous, sigmoidal weighting 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 O3 based on all the metrics discussed 

above. Spatial variability is based on maps displaying county levels of the various metrics. In 

this way different levels of O3 for different areas of the country are displayed. It should be noted 

that county areas can be much larger in the West than in the East, but monitors are not spread 

evenly within a county. As a result, the assigned 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 O3 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 than 
2-16

Ozone Concentration (ppm)

0.000.010.020.030.040.050.060.070.080.090.100.110.120.130.140.150.160.170.180.190.20

City

Figure 2-3. 1-hr Ozone Distributions across 12 Risk Areas, 2002-2004. Box Depicts interquartile range and mdepicts the mean; whiskers depict 10th and 90th percentile; and ‘x’ depicts values outside the 10th and 90th percData Source: AQS 
2-17

Ozone Concentration (ppm)

0.000.010.020.030.040.050.060.070.080.090.100.110.120.130.140.150.16

City

Figure 2-4. 8-hr Ozone Distributions across 12 Risk Areas, 2002-2004. Box Depicts interquartile range and mdepicts the mean; whiskers depict 10th and 90th percentile; and ‘x’ depicts values outside the 10th and 90th percData Source: AQS 
2-18

Ozone Concentration (ppm)

0.000.010.020.030.040.050.060.070.080.090.100.110.12

City

Figure 2-5. 24-hr Ozone Distributions across 12 Risk Areas, 2002-2004. Box Depicts interquartile range and depicts the mean; whiskers depict 10th and 90th percentile; and ‘x’ depicts values outside the 10th and 90th percData Source: AQS 
 2-19

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 concentration distributions, Houston shows a lower 75th

percentile than the other cities with areas like Cleveland, Philadelphia and New York having 

higher distributions. The lower 24 hour concentrations in Houston indicate a wider range 

between the daily O3 minima and maxima unlike an area like Cleveland, which has a higher 

interquartile range. 

2.5.2.2 8-Hour and 1-Hour Statistics 

 High 8-hr average O3 concentrations tend to occur near 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 caused by transport. Higher 8-hr 

O3 levels observed in smaller urban and non-urban areas are most obvious at the end of the 

northeast corridor (the highly urbanized area running from Washington, 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 Concentration-Weighted Statistics 

 The highest SUM06 and W126 levels in 2001 (most of the analyses in Chapter 7 center 

on 2001 data) occurred in most of the agricultural areas of California. When the data were from 

CASTNET sites, more purely rural counties showed higher values (See Figures 2-8 through 2-

11) (Fitz-Simons, et al., 2005). The SUM06 and W126 values experienced a sharp decline in 

2004 when compared to 2002 primarily in the eastern 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 O3 season. However, the eastern half of the 

country was also subject to the emission control requirements implemented under the NOx SIP 

Call which occurred after 2002. The improvements seen in 2004 for the East are most likely due 

to a combination of cooler weather, the emission reductions from the NOx SIP Call, and emission 

reductions from mobile source and other stationary source rules. 
2-20

Concentration PPM X < 0.100; 364 Counties; 63,252,165 People (2000 census)

0.125 <= X; 16 Counties; 26,021,093 People 

0.100 <= X < 0.125; 264 Counties; 100,568,984 People

Figure 2-6. Average 2nd Highest Daily Maximum 1-hour Values in U.S. Counties, 2002-2004 AQS Data.
2-21

Concentration PPM X < 0.074; 140 Counties; 27,502,811 People (2000 census)

0.085 <= X; 210 Counties; 96,172,263 People 

0.074 <= X < 0.085; 294 Counties; 66,167,168 People

Figure 2-7. Average 4th Highest Daily Maximum 8-hour Values in U.S. Counties, 2002-2004 AQS Data. 
2-22

Concentration PPM-Hour SUM06<15 15<=SUM06<25

25<=SUM06<38 38<=SUM06

Figure 2-8. Highest 3-month 12-hour SUM06 Exposure Index in U.S. Counties, 2001 AQS Data. 
2-23

Figure 2-9. Highest 3-month 12-hour W126 Exposure Index in U.S. Counties, 2001 AQS Data.

W126<13 13<=W126<21 21<=W126<31 31<=W126 Concentration PPM-Hour
2-24

Concentration PPM-Hour SUM06<15 15<=SUM06<25

25<=SUM06<38 38<=SUM06

Figure 2-10. Highest 3-month 12-hour SUM06 Exposure Index in U.S. Counties, 2001 CASTNET Data.
2-25

Figure 2-11. Highest 3-month 12-hour W126 Exposure Index in U.S. Counties, 2001 CASTNET Data.

Concentration PPM-Hour W126<13 13<=W126<21 21<=W126<31 31<=W126
2-26

Concentration PPM-Hour SUM06<15 15<=SUM06<25

25<=SUM06<38 38<=SUM06

Figure 2-12. Highest 3-month 12-hour SUM06 Exposure Index in U.S. Counties, 2002 AQS and CASTNET 
2-27

Figure 2-13. Highest 3-month 12-hour W1126 Exposure Index in U.S. Counties, 2002 AQS and CASTNET 

Concentration PPM-Hour W126<13 13<=W126<21 21<=W126<31 31<=W126
2-28

Concentration PPM-Hour SUM06<15 15<=SUM06<25

25<=SUM06<38 38<=SUM06

Figure 2-14. Highest 3-month 12-hour SUM06 Exposure Index in U.S. Counties, 2004 AQS and CASTNET 
2-29

Figure 2-15. Highest 3-month 12-hour W126 Exposure Index in U.S. Counties, 2004 AQS and CASTNET D

Concentration PPM-Hour W126<13 13<=W126<21 21<=W126<31 31<=W126
 2-30

2.5.3 Temporal Variability 

 Temporal variability consists of several time frames when considering characterization of 

ground level air quality data. Multi-year variability characterizes 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 (only 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 month to month variability to demonstrate when in 

the year the highest concentrations occur. Diurnal variability characterizes hour-to-hour changes 

demonstrating when, in the day, the highest concentrations occur (Fitz-Simons, et al., 2005). 

2.5.3.1 Long Term Variability – Trends 

 Long term, nationwide trends for 8-hr O3 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 City. 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 than the urban means; however the largest urban 

concentrations are much higher than the largest rural concentrations (Fitz-Simons, et al., 2005). 

 Long term trends for 1-hr O3 values are presented in Figures 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 rural trends are similar, but urban have more data 

and more variation. The 1-hr means for the urban 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 O3 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-year 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 clearly in the 1990s. In many cases, short term 

variation (3 years or less) is associated with meteorological conditions that are generally more or 

less conducive to O3 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: NOX p.17, U.S. EPA, 2005b) 
2-31

Urban

Ozone Concentration (ppm)

0.000.020.040.060.080.100.120.140.160.180.20

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004

487 505 505 543 545 569 560 592 602 618 633 650 670 670 670

Figure 2-16. 4th Highest Daily Maximum 8-hour Ozone Values 1990-2004 (Urban). Box Depicts interquarti

the dot depicts the mean; whiskers depict 10th and 90th percentile; ‘x’ depicts values outside the 10th and 90th pnumbers above the boxes depicts the number of sites. Data Source: AQS 
2-32

Rural

Ozone Concentration (ppm)

0.000.020.040.060.080.100.120.140.160.180.20

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004

52 55 55 51 52 55 55 66 72 75 75 75 76 77 81

Figure 2-17. 4th Highest Daily Maximum 8-hour Ozone Values 1990-2004 (Rural). Box Depicts interquartithe dot depicts the mean; whiskers depict 10th and 90th percentile; ‘x’ depicts values outside the 10th and 90th pnumbers above the boxes depicts the number of sites. Data Source: CASTNET 
2-33

Urban

Ozone Concentration (ppm)

0.000.020.040.060.080.100.120.140.160.180.200.220.240.260.280.300.32

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004

494 507 513 547 546 572 566 595 604 620 631 650 668 667 671

Figure 2-18. 2nd Highest Daily Maximum 1-hour Ozone Values 1990-2004 (Urban). Box Depicts interquartthe dot depicts the mean; whiskers depict 10th and 90th percentile; ‘x’ depicts values outside the 10th and 90th pnumbers above the boxes depicts the number of sites. Data Source: AQS 
2-34

Rural

Ozone Concentration (ppm)

0.000.020.040.060.080.100.120.140.160.180.200.220.240.260.280.300.32

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004

52 55 55 51 52 55 55 66 72 75 75 75 76 77 80

Figure 2-19. 2nd Highest Daily Maximum 1-hour Ozone Values 1990-2004 (Rural). Box Depicts interquarti

the dot depicts the mean; whiskers depict 10th and 90th percentile; ‘x’ depicts values outside the 10th and 90th pnumbers above the boxes depicts the number of sites. Data Source: CASTNET 
 2-35

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 grouping of two bars represents the number of 

exceedance days for 1-hr, 8-hr averaged and 24-hr averaged O3 concentrations. The 1-hr 

measured concentrations were compared to the previous 1-hr O3 standard of 0.12 ppm, 8 hour 

averaged concentrations were compared to the current O3 standard of 0.08 ppm and the average 

24 hour concentrations were compared to 0.055 ppm which is the 95th percentile for 24 hour O3

concentrations across the United States for 2002 through 2004. The data show that in all sites in 

the Midwest and the East, O3 concentrations were down dramatically in 2004 when compared to 

2002. This is due in part to the fact that 2004 was much cooler than 2002. The reduction in peak 

O3 concentrations also reflects the improvement in air quality due to emission reductions from 

the NOx SIP Call, mobile source and other stationary source rules. The NOx SIP Call provided 

large NOx reductions in the eastern part of the country in 2003 and 2004, thereby reducing peak 

O3 concentrations (U.S. EPA, 2005b). The number 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 averaged 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 seasonal variation in O3

concentrations. However in many areas, monitors are not active during cooler months. As a 

result, data from May through September are the only universally available data for all monitors. 

Although this is a limited characterization of seasonal variability, it is consistent across the entire 

national network. 

 Figure 2-21 shows box-plots of all 2004 data from May through September for the 

second highest daily 1-hr maximums. The center of the distribution shows a slight, steady 

increase from May to September while the extreme values show a more pronounced but more 

variable increase for the same period (Fitz-Simons, et al., 2005). 

Figure 2-22 shows box-plots of all 2004 data from May through September for the fourth 

highest daily 8-hr maximums. The center of the distribution and the extremes 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 activity and the solar phase drive the hour-to-hour daily cycle 

seen in ground level O3 concentrations. The daily 1-hr peak levels generally occur in the 

afternoon with the lowest concentration occurring in the early morning. However, on any given 
2-36

Atlanta

Boston

Chicago Cleveland

Detroit

Houston

Los Angeles

New York

Sacramento Philadelphia

St. Louis

Washington, DC

2002

8-hr 24-hr

2004 2002 2004 2002 2004

1-hr

Figure 2-20. Comparison of 1-hr, 8-hr, and 24-hr Metrics for 2002 and 2004, 12 Risk Areas Data Source: AQS
2-37

Ozone Concentration (ppm)

0.000.020.040.060.080.100.120.140.160.180.200.220.240.260.280.300.32

May June July August September

301 1002 976 913 378

Figure 2-21. 2nd Highest Daily Maximum 1-hour Ozone Values from 2004 by Month. Box Depicts interquamedian; the dot depicts the mean; whiskers depict 10th and 90th percentile; ‘x’ depicts values outside the 10th anand numbers above the boxes depicts the number of sites. Data Source: AQS 
2-38

Ozone Concentration (ppm)

0.000.020.040.060.080.100.120.140.160.180.20

May June July August September

360 1053 940 800 392

Figure 2-22. 4th Highest Daily Maximum 8-hour Ozone Values from 2004 by Month. Box Depicts interquamedian; the dot depicts the mean; whiskers depict 10th and 90th percentile; ‘x’ depicts values outside the 10th anand numbers above the boxes depicts the number of sites. Data Source: AQS 
 2-39

day when conditions are right, this phase can be reversed with the highest values occurring at 

night or early morning. Ozone transport 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-plots 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 that 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 shows a smooth sinusoidal portion 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 average 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 the 1-hr data and the 8-hr data is that the 8-

hr data exhibit a smoother sinusoidal 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 and 8-hr data from CASTNET sites which are 

considered rural. Several differences are noted here. The patterns for the center of the 

distribution are similar to the patterns for the urban sites. The largest 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 smooth 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 distribution (Fitz-Simons, et al., 2005). 

2.6 CHARACTERIZATION OF OZONE EPISODES 

 Major episodes of high O3 concentrations in the United States are associated with slow 

moving, high pressure systems. High pressure systems during the warmer seasons are associated 

with the sinking of air, resulting in warm, generally cloudless skies, with light winds. These 

conditions result in the development of stable air masses near the surface which inhibit the 

vertical mixing of O3 precursors. The combination of inhibited limited vertical mixing and light 

winds minimizes the dispersal of pollutants emitted in urban areas, allowing their concentrations 

to build up. Photochemical activity involving these precursors is also enhanced because of higher 

temperatures and the availability of sunlight. Downward entrainment of overnight transported O3

and precursors trapped aloft begins on the following day as the PBL starts growing. In the 
2-40

22 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

0.0500.1000.1500.200

1 hour ozone (ppm)

hour

Figure 2-23. 1-Hour Diurnal Week Day Pattern for Urban Sites, May through September 2004. Box Depiand median; whiskers depict maximum and minimum values; and ‘+’ depicts the mean. Data Source: AQS 
2-41

22 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 

0

0.0500.1000.1500.200

1 hour ozone (ppm)

hour

Figure 2-24. 1-Hour Diurnal Week End Pattern for Urban Sites, May through September 2004. Box Depi

and median; whiskers depict maximum and minimum values; and ‘+’ depicts the mean. Data Source: AQS 
2-42

22 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 

0.0000.0250.0500.0750.1000.125

8 hour ozone (ppm)

hour

Figure 2-25. 8-Hour Diurnal Week Day Pattern for Urban Sites, May through September 2004. Box Depic

and median; whiskers depict maximum and minimum values; and ‘+’ depicts the mean. Data Source: AQS
2-43

22 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 0

0.0000.0250.0500.0750.1000.125

8 hour ozone (ppm)

hour

Figure 2-26. 8-Hour Diurnal Week End Pattern for Urban Sites, May through September 2004. Box Depiand median; whiskers depict maximum and minimum values; and ‘+’ depicts the mean. Data Source: AQS 
2-44

22 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 

-0.050

0

0.050

0.1000.150

1-hour ozone (ppm)

hour

Figure 2-27 1-Hour Week Day Diurnal Pattern for Rural Sites, May through September 2004. Box Depictand median; whiskers depict maximum and minimum values; and ‘+’ depicts the mean. Data Source: CASTNET 
2-45

22 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 0

-0.050

0

0.050

0.1000.1500.200

1-hour ozone (ppm)

hour

Figure 2-28. 1-Hour Week End Diurnal Pattern for Rural Sites, May through September 2004. Box Depicand median; whiskers depict maximum and minimum values; and ‘+’ depicts the mean. Data Source: CASTNET 
2-46

22 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 

-0.025

0

0.0250.0500.075

0.1000.1250.150

8-hour ozone (ppm)

hour

Figure 2-29. 8-Hour Week Day Diurnal Pattern for Rural Sites, May through September 2004. Box Depicand median; whiskers depict maximum and minimum values; and ‘+’ depicts the mean. Data Source: CASTNET 
2-47

22 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 

-0.025

0

0.0250.0500.075

0.1000.1250.150

8-hour ozone (ppm)

hour

Figure 2-30. 8-Hour Week End Diurnal Pattern for Rural Sites, May through September 2004. Box Depicand median; whiskers depict maximum and minimum values; and ‘+’ depicts the mean. Data Source: CASTNET 
 2-48

eastern United States, high O3 concentrations during an episode can extend over hundreds of 

thousands of square kilometers for several days. 

 Episodes have two main characteristics: the concentration level reached and the length of 

time that this level is reached in consecutive days. The following discussion addresses how these 

characteristics of episodes have varied through both space and time. 

 Numbers of episodes defined by daily maximum 1-hr O3 concentrations reaching a level 

of 0.12 ppm for 1 day generally follow the long term trend of central values (means or medians) 

of the 1-hr O3 data (See Figures 2-18 and 2-31). As the 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 (Fitz-Simons, et al., 2005). From this we conclude 

that control strategies have been reducing peak 1-hr O3 across major urban areas. 

 Numbers of episodes defined by daily maximum 8-hr O3 concentrations reaching a level 

of 0.08 ppm for 1 day generally follow the long term trend of central values of the 8-hr O3 data 

(See Figures 2-16 and 2-32). As the length of these episodes increase, the frequency of these 

episodes decreases. However, some of the longer episodes (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 the most recent years (Fitz-Simons, et al., 2005). 

As episode length and level increase for both 1-hr and 8-hr O3 data the frequency 

decreases (Figure 2-33 and 2-34). The longer periods and higher levels disappear 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 episodes 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 significant indications of 

periodicities. The 1-hr O3 data exhibit much the same lack of periodicity as the 8-hr data (FitzSimons, et al., 2005). 

2.7 POLICY RELEVANT BACKGROUND LEVELS 

 For purposes of this document, background or policy relevant background (PRB) O3 is 

defined as the distribution of O3 concentrations that would be observed in the U.S. in the absence 

of anthropogenic (man-made) emissions of precursor 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 facilitates separating pollution levels that can be controlled by U.S. 
2-49

> 6

6

5

4

3

2

1

episode

length

(days)

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004

year

16 24 15 13 7 6 1 4 2 2

18 16 27 26 10 14 10 1 4 2 1

36 46 41 23 18 19 9 10 23 3 3 8 2

49 71 60 44 36 34 28 10 40 10 3 16 20 6 

134 137 105 84 75 100 71 43 57 25 19 22 48 

317 336 208

9 10 23 3 3 8 2

49 71 60 44 36 34 28 10 40 10 3 16 20 6 

134 137 105 84 75 100 71 43 57 25 19 22 48 

317 336 208 188 189 243 147 154 164 148 99 92 13

1123 1205 891 894 819 1133 667 649 866 822 553 514 

Figure 2-31. Length of Consecutive Day Episodes over 0.12 ppm by Year for 1-hour Ozone Data across all Data Source: AQS
2-50

> 6

6

5

4

3

2

1

episode

length (days)

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004

year

33 43 37 27 25 31 34 39 33 34 24 17 35 25 8

41 61 62 47 43 65 61 47 74 70 46 45 110 44 

78 154 85 93 91 155 104 71 161 202 67 101 269 66 

172 225 131 147 178 371 180 147 313 372 163 274 375 1

396 558 323 358 387 579

45 110 44 

78 154 85 93 91 155 104 71 161 202 67 101 269 66 

172 225 131 147 178 371 180 147 313 372 163 274 375 1

396 558 323 358 387 579 468 390 654 747 422 401 732 

1041 1277 788 958 1085 1270 1063 1153 1644 1640 991 1107 1

3369 3285 2561 3260 3221 3828 3068 3299 4460 4864 3132 3257 

Figure 2-32. Length of Consecutive Day Episodes over 0.08 ppm by Year for 8-hour Ozone Data across all Data Source: AQS
2-51

> 6

6

5

4

3

2

1

episode length (days)

0.09 0.1 0.11 0.12 0.13 0.14 0.15

level

355 95 17 6 3

303 64 10 1 1

597 191 63 13 2

1029 359 131 46 11

2285 952 326 134 29 12 

5433 2655 1168 470 209 

18055 9552 5016 2522 1264 

Figure 2-33. Length of Consecutive Day Episodes over Displayed Levels for 1-hour Ozone Data (2000-2004

Monitors. 

Data Source: AQS 
2-52

> 6

6

5

4

3

2

1

episode length (days)

0.06 0.07 0.08 0.09 0.1 0.11 0.12

level

5861 1423 315 57 13 2

2957 968 263 41 5

4536 1835 539 112 18 4

7381 3031 1038 307 49 4

12223 5527 2092 741 189 35 

22945 11964 4968 1885 626 1

48777 30041 14518 6541 2588 

Figure 2-34. Length of Consecutive Day Episodes over Displayed Levels for 8-hour Ozone Data (2000-2004

Monitors. 

Data Source: AQS 
2-53

FREQUENCY

0

100020003000

gap 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 50

Figure 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 international agreements with neighboring countries) from levels that are 

not generally controllable in this manner. As defined here, PRB includes (1) O3 in the U.S. from 

natural sources of emissions in the U.S., Canada, and Mexico and (2) O3 in the U.S. from the 

transport of O3 or the transport of emissions from both natural and man-made sources, from 

outside of the U.S. and its neighboring countries. As discussed in Chapter 5 of this Staff Paper, 

PRB concentrations enter into the assessments of risk to human health. 

 Contributions to PRB levels of O3 include: photochemical interactions involving natural 

emissions of VOCs, NOX, and CO; the long-range transport of O3 and its precursors from outside 

North America; and stratospheric-tropospheric exchange (STE). Processes involved in STE are 

described in detail in Annex AX2.3 of the CD. Natural sources of O3 precursors include biogenic 

emissions, wildfires, and lightning. Biogenic emissions from agricultural activities are not 

considered in the formation of PRB (CD, p.AX2-145). 

 As a result of long-range transport of O3

 and its precursors from anthropogenic sources 

within North America, estimates of PRB O3 concentrations cannot be derived solely from 

measurements of O3, and must be based on modeling. The global photochemical transport model 

GEOS-CHEM (Fiore et al., 2003) has been applied to estimate PRB O3 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; Fusco 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 detailed evaluations of GEOS-CHEM with O3

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 relevant because sources of the O3 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 predictions of 39 ± 5 ppbv, indicating no significant 

differences between the model predictions and observations for conditions suggestive of PRB. 

The CD further notes that "several other papers have evaluated the GEOS-CHEM simulation for 

surface O3 and its precursors over the United States." Summarizing their assessment of the 

validity of the GEOS-CHEM model, the CD states "in conclusion, we estimate that the PRB O3

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 within 5 ppbv in other regions and 

seasons." These error estimates are based on comparison 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 O3 (cf. Figures 8 and 9 of Fiore et al., (2003) for the SE and 
 2-55

Figure 3 of Fiore et al. (2002) for the NE.) it can be seen that GEOS-CHEM overestimates O3 for 

the SE and underestimates it for the NE. 

The GEOS-CHEM model shows that PRB O3 concentrations are related to season, 

altitude and total surface O3 concentration. PRB O3 concentrations at the surface are generally 

predicted to be in the range of 0.015 to 0.035 ppm in the afternoon, and they tend to decline 

under conditions conducive to high O3

 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 stratospheric intrusions. The stratospheric contribution to 

surface O3 is typically well below 0.020 ppm and only rarely elevates O3 concentrations at lowaltitude sites and only slightly more often elevates them at high-altitude sites (U.S. EPA, 2005a, 

AX3-148). 

In the previous review of the O3 NAAQS, the criteria document and staff paper adopted a 

value of 40 ppb for PRB O3. However, Figure 3-17 in the CD shows that mean daily maximum 

8-h O3 concentrations were less than 40 ppb at over 10 % of U.S. sites. In 2004, the mean daily 

maximum 8-h O3 concentrations were less than 40 ppb at 25 % of U.S. sites. It is highly unlikely 

that this fraction of O3 monitoring sites would be unaffected by O3 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 O3 concentrations at Voyageurs National Park were typically less than 

40 ppb. Simulations of O3 at Voyageurs, the site with the lowest O3 show that there is still a 

substantial regional contribution to O3 (Figure AX2-86). Thus, 40 ppb is likely to be too high for 

the mean PRB O3 concentration. 

 The exposure and health risk analyses described in Chapter 4 and 5 use estimates of PRB 

based on runs of the GEOS-CHEM model applied for the 2001 warm season (i.e., April to 

September). The GEOS-CHEM data consist of hourly gridded values with latitude running from 

12o to 80 o in 2 o steps and longitude 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 O3

season. The PRB estimates from the grid nearest each of the 12 urban areas included in the 

exposure and risk analyses have been used to estimate 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 algorithms 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 Multiscale 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.; Yantosca, 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.; Yantosca, 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.(2005) U.S. EPA Memorandum to File. Subject: Analysis of 2004 Ozone 

Data for the Ozone NAAQS Review, November 7. 

Kasibhatla, P.; Chameides, W. L. (2000) 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 Air 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: 

NOX 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. Rao, B. Doddridge, C.R. Philbrick, 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 O3, alone and in combination with other pollutants 

that are routinely present in ambient air. This assessment focuses specifically on the health 

effects evidence evaluated in Chapters 4 through 7 of the CD with particular emphasis on the 

integrative synthesis presented in Chapter 8. That integrative synthesis focuses on integrating 

newly available scientific information with that available from the last review, as well as 

integrating information from various disciplines, to address a set of issues central to the 

assessment of scientific information upon which this review of the O3 NAAQS is based. This 

chapter also addresses key issues relevant to quantitative assessment of controlled-human 

exposure and epidemiological evidence, to provide a foundation for the quantitative human 

exposure and health risk assessments presented in Chapters 4 and 5. Those quantitative 

assessments, together with this evidence-based assessment, provide the foundation for the 

development of staff conclusions and identification of options for consideration related to 

primary standards for O3 presented in Chapter 6. 

The decision in the last review focused primarily on evidence from short-term and 

prolonged controlled-exposure studies reporting lung function decrements, respiratory 

symptoms, and respiratory inflammation in humans, as well as epidemiology studies reporting 

excess hospital admissions and emergency department (ED) visits for respiratory causes. The 

CD prepared for this review emphasizes a large number of epidemiological studies published 

since the last review with these and additional health endpoints, including the effects of acute 

and chronic exposures to O3 on premature mortality, enhanced respiratory symptoms and lung 

function decrements in asthmatic individuals, and school absences. It also emphasizes important 

new information from toxicology, 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 healthy adults under moderate exertion for 6.6 hr 

exposures to levels as low as 0.04 and 0.06 ppm; however, in a few subjects, 

decrements of >10% were observed. 

• New controlled human-exposure studies offer evidence of increased airway 

responsiveness to allergens in subjects with allergic asthma and allergic rhinitis 

exposed to O3. 

• Numerous controlled human-exposure studies have reported indicators of O3-induced 

inflammatory response in both the upper respiratory tract (URT) and lower respiratory 
3- 2

tract (LRT), while other studies have shown significant changes in host defense 

capability following O3 exposure of healthy young adults. 

• Animal toxicology studies provide new information regarding mechanisms of action, 

increased susceptibility to respiratory infection, and the biological plausibility of acute 

effects and chronic, irreversible respiratory damage. 

• Numerous acute exposure epidemiological studies published during the past decade 

offer added evidence of ambient O3-related lung function decrements and respiratory 

symptoms in physically active healthy subjects and asthmatic subjects, as well as 

evidence on new health endpoints, such as the relationships between ambient O3 

concentrations and school absenteeism and between ambient O3 and cardiac 

physiologic endpoints. 

• Several new studies have been published over the last decade examining the temporal 

associations between O3 exposures and ED visits for respiratory diseases and on 

respiratory-related hospital admissions. 

 Newly available, large multicity studies, designed specifically to examine the effects of 

acute exposure to PM and O3 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. National Morbidity, Mortality Air Pollution 

Study [NMMAPS]) and in 23 European cities (Air Pollution and Health: European 

Approach [APHEA]) reported positive and significant O3 effect estimates for all cause 

(nonaccidental) mortality. 

• 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 threshold level exists for premature mortality. The results indicate that even 

low levels of tropospheric O3 are associated with premature mortality. 

• Three recent meta-analyses evaluated potential sources of heterogeneity in O3-mortality 

associations, and these studies provide evidence of a robust association between 

ambient O3 and mortality, especially for the warm O3 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 O3 exposure or 

associated with exposure to O3, 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 observed associations between health endpoints and 

exposure to O3, and discusses key issues related to quantitative risk assessment based on such 

evidence. Section 3.5 discusses biological plausibility and coherence of evidence for O3-related 

adverse health effects, including short-term respiratory effects, short-term cardiovascular effects, 
3- 3

long-term health effects, and mortality-related health endpoint. Drawing from the CD’s 

integrative synthesis, section 3.6 discusses factors that modify responsiveness to O3; potentially 

susceptible and vulnerable populations groups; and public health impacts of exposure to ambient 

O3. Finally, section 3.7, summarizes key policy-relevant conclusions from the CD about O3-

related health effects, in the context of a discussion of issues related to our confidence in and the 

utility of the underlying evidence. 

3.2 MECHANISMS OF TOXICITY 

 Evidence is covered in Chapters 5 and 6 of the CD on possible mechanisms by which 

exposure to O3 may result in acute and chronic health effects. While most of the available 

evidence addresses mechanisms for O3, we recognize that O3 serves as an indicator for the total 

photochemical oxidant mixture found in the ambient air. Some effects may be caused by one or 

more components in the overall pollutant mix, either separately or in combination with O3. 

Evidence from dosimetry, toxicology, and human exposure studies has contributed to an 

understanding of the mechanisms that help to explain the biological plausibility and coherence of 

evidence for O3-induced respiratory health effects reported in epidemiological studies. In the 

past, however, little information was available to help explain potential biological mechanisms 

which linked O3 exposure to premature mortality or cardiovascular effects. More recently, 

however, an emerging body of animal toxicology evidence is beginning to suggest mechanisms 

that may mediate acute O3 cardiovascular effects. 

 Scientific evidence discussed in the CD (section 5.2) indicates that reactions with lipids 

and antioxidants are the initial step in mediating deleterious health effects of O3. There is 

subsequent activation of a cascade of events starting with inflammation, altered permeability of 

the epithelial barrier, impaired host defense (including clearance mechanisms), and pulmonary 

structural alterations that can potentially exacerbate a preexisting disease status. According to 

the CD, the scientific evidence is still lacking for clearly establishing a role for one or a group of 

mechanistic pathways underlying O3 health effects observed in epidemiological studies. 

Appendix 3A provides a further discussion of mechanisms of toxicity. 

3.3 NATURE OF EFFECTS 

 The CD provides new evidence that notably enhances our understanding of short-term 

exposure effects, including effects on lung function, symptoms, and inflammatory effects 

reported in controlled exposure studies. These studies support and extend the findings of the 

previous CD. There is also a significant body of new epidemiological evidence of associations 

between short-term exposure to O3 and effects such as premature mortality, hospital admissions 
3- 4

and ED visits for respiratory (e.g., asthma) causes. Key epidemiological and human controlled 

exposure studies are summarized in Appendices 3B and 3C, respectively. 

 The following discussions of O3-related health effects are based on scientific evidence 

critically reviewed in chapters 5, 6, and 7 of the CD, as well as the CD’s integration of scientific 

evidence contained in Chapter 8. In addition, these health effects discussions rely on the more 

detailed information and tables presented in the CD’s annexes AX5, AX6, and AX7. 

Conclusions drawn about O3-related health effects depend on the full body of evidence from 

controlled-exposure human, epidemiological and toxicological data contained in the CD. 

Section 3.3.1 focuses on a broad array of morbidity effects, including both acute and chronic 

exposures. Section 3.3.2 focuses on the expanded body of evidence on associations between 

acute O3 exposure and mortality, as well as the more limited evidence on chronic O3 exposures 

and mortality. 

3.3.1 Morbidity 

This section summarizes scientific information contained in the CD on respiratory and 

cardiovascular effects associated with exposure to O3. Evidence of the effects of short-term and 

long-term exposure to O3 on the respiratory system is discussed in sections 3.3.1.1 and 3.3.1.2, 

and evidence of O3-related cardiovascular effects in section 3.3.1.3. 

3.3.1.1Effects on the Respiratory System from Short-term Exposures 

 Short-term exposures to O3 have been reported to induce a wide variety of respiratory 

health effects. These effects include a range of effects, such as morphological changes in the 

respiratory tract, pulmonary function decrements, respiratory symptoms, respiratory 

inflammation, increased airway responsiveness, changes in host defense capability, acute 

morphological effects, increased ED visits and hospital admissions, and effects on exercise 

performance. Short-term O3 exposure has also been associated with increases in restricted 

activity days and school absences but evidence is limited for these effects. 

3.3.1.1.1 Pulmonary Function Decrements, Respiratory Symptoms, and Asthma 

Medication Use 

 A very large literature base of studies published prior to 1996, which investigated the 

health effects on the respiratory system from short-term O3 exposures, was reviewed in the 1986 

and 1996 CDs (U.S. Environmental Protection Agency, 1986, 1996). In the last review, the 

lowest O3 concentration at which statistically significant reductions in forced vital capacity 

(FVC) and forced expiratory volume in 1 second (FEV1) had been reported in sedentary subjects 

was 0.5 ppm (CD, p 6-3). During exercise, spirometric and symptomatic responses were 

observed at much lower O3 exposures. When minute ventilation was considerably increased by 
3- 5

continuous exercise (CE) during O3 exposures lasting 2 hr or less at > 0.12 ppm, healthy subjects 

generally experienced decreases in FEV1, FVC, total lung capacity (TLC), inspiratory capacity 

(IC), mean forced expiratory flow from 25% to 75% of FVC (FEF25-75), and tidal volume (VT); 

increases in specific airway resistance (sRaw), breathing frequency (fB), and airway 

responsiveness; and symptoms such as cough, pain on deep inspiration, shortness of breath, 

throat irritation, and wheezing. When exposures were increased to 4- to 8-hr in duration, 

statistically significant spirometric and symptom responses were reported at O3 concentrations as 

low as 0.08 ppm and at lower minute ventilation (i.e., moderate rather than high level exercise) 

than the shorter duration studies (CD. p. 6-6). 

 The most important observations drawn from studies reviewed in the 1996 CD were that: 

(1) young healthy adults exposed to O3 concentrations > 0.08 ppm develop significant, 

reversible, transient decrements in pulmonary function if minute ventilation or duration of 

exposure is increased sufficiently, (2) children experience similar spirometric responses but 

lesser symptoms from O3 exposure relative to young adults, (3) O3-induced spirometric 

responses are decreased in the elderly relative to young adults, (4) there is a large degree of 

intersubject variability in physiologic and symptomatic responses to O3 but responses tend to be 

reproducible within a given individual over a period of several months, (5) subjects exposed 

repeatedly to O3 for several days show an attenuation of response upon successive exposures; 

this attenuation is lost after about a week without exposure; and (6) acute O3 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 studies 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 duration 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 examined reported changes in FEV1 in 485 white males (ages 18-

36) exposed for 2 hr to O3 concentrations from as low as 0.08 ppm up to 0.40 ppm, at rest or with 

intermittent exercise (IE). Decrements in FEV1 were modeled by sigmoid-shaped curve as a 

function of subject age, O3 concentration, minute ventilation, and duration of exposure. In 

another study, Ultman et al. (2004) found that exposing 60 young, healthy subjects to 0.25 ppm 

O3 for 1 hr with continuous exercise produced considerable intersubject variability in FEV1

decrements ranging from 4% improvement to a 56% decrement, which was consistent with 

findings in the 1996 CD. One third of subjects had FEV1 decrements > 15% and 7% had 

decrements > 40%. Foster et al. (1993, 1997) examined the effects of O3 on ventilation 

distribution and reported results suggesting a prolonged O3 effect on the small airways and 

ventilation distribution (CD, p. 6-5). 
3- 6

 For prolonged exposures (4 to 8 hr) in the range of 0.08 to 0.16 ppm O3 using moderate 

quasi-continuous exercise (QCE; 50 min exercise [minute ventilation of 35 to 40 L/min] and 10 

min rest per hr), several pre- and post-1996 studies (Folinsbee et al., 1988,1994; Horstman et al., 

1990; Adams, 2002, 2003a, 2006) have reported statistically significant spirometric responses 

and increased symptoms in healthy adults with increasing duration of exposure, O3 concentration, 

and minute ventilation. Based on review of several prolonged exposure studies, the CD (p. 6-6) 

concluded that FEV1 decrements are a function of minute ventilation in 6.6 hr exposure studies 

and that data from recent studies do not support the contention that minute ventilation should be 

normalized to body surface area (BSA) for adults. Triangular exposure (i.e., integrated 

exposures that begin at a low level, rise to a peak, and return to a low level during time of 

exposure) studies (Hazucha et al., 1992; Adams 2003a, 2006) suggest that, depending upon the 

profile of the exposure, the triangular exposure, which may reflect the pattern of ambient 

exposures in some locations, can potentially lead to greater FEV1 decrements than square wave 

exposures (i.e., a constant exposure level during time of exposure) when the overall O3 doses are 

equal (CD, p. 6-10), suggesting that peak exposures are important in terms of O3 toxicology. 

 McDonnell (1996) used data from a series of studies to investigate the frequency 

distributions of FEV1 decrements following 6.6 hr exposures and found that average FEV1

responses were relatively small (between 5 and 10 %) at 0.08 ppm O3 (CD, p. 8-17)1. However, 

about 18% of the exposed subjects had moderate functional decrements (10 to 20%), and about 

8% experienced large decrements (>20%). Figure 3-1A,B,C (CD, 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 insignificant, some individuals 

can experience much more significant and severe effects that may be clinically significant. The 

FEV1 responses illustrated in this figure were not corrected for the effect of exercise in clear air. 

When that is done for the Adams (2002, 2006) data, the percentage of subjects experiencing 

>10% FEV1 decrements changes to 7% at O3 exposures of 0.04 ppm, to 7% at O3 exposures of 

 1

 The studies conducted in EPA’s clinical research facility 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. Frequency distributions of FEV1 changes following 6.6-h exposures to 

a constant concentration of O3 or filtered air. Note that the percentage in each panel 

indicates the distributions of % decrement.

Source:Panel A, McDonnell (1996); Panel B, Adams (2002, 2006), pre- and post-FEV1 data for each subject 

provided by author. 

C. 

Figure 3-1C. Frequency distributions of FEV1 changes following 6.6-h exposures to a 

constant concentration of O3 or filtered air. The FEV1 changes following O3 exposures 

have been corrected for filtered air responses, i.e., they are O3-induced FEV1 changes. Note 

that the percentage in each panel indicates the distributions of % decrement. 

Source: Adams (2002, 2006), pre- and post- FEV1 data for each subject provided by author.
3- 8

0.06 ppm, and to 23% at O3 exposures of 0.08 ppm, in studies conducted in California (CD, p. 8-

18). The development of these effects is time-dependent during both exposure and recovery 

periods, with great overlap for development and disappearance of the effects. In healthy human 

subjects exposed to typical ambient O3 levels near 0.12 ppm, spirometric responses largely 

resolve within 4 to 6 hr postexposure, but cellular effects persist for about 24 hr. In these healthy 

subjects, small residual lung function effects are almost completely gone within 24 hr, while in 

hyperresponsive subjects, recovery can take as much as 48 hr to return to baseline. The majority 

of these responses are attenuated after repeated exposure, but such attenuation to O3 is lost one 

week postexposure (CD, p. 8-19). 

 In the Adams (2006) investigation of the effects of square-wave (0.00, 0.06, and 0.08 

ppm O3) and triangular (averaging 0.04, 0.06, and 0.08 ppm O3) exposures for 6.6 hr during 

quasi continuous exercise on pulmonary function in 30 healthy adults, the study was designed to 

compare pulmonary function responses between the six exposure protocols 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 O3 exposures were found to be significantly different from 

the responses observed for the 0.0, 0.04, and 0.06 ppm O3 exposures. The FEV1 responses did 

not differ significantly at 6.6 hr between the two 0.08 ppm O3 exposures (i.e., the square-wave 

vs. the triangular). Another statistically insignificant comparison was between the FEV1

responses at 0.06 ppm O3 and filtered air (0.0 ppm O3) at 6.6 hr. 

 On examination of the group mean FEV1 responses in Figure 1 of Adams (2006), 

however, responses during the 0.06 ppm O3 exposures appear to diverge from responses for 

filtered-air and 0.04 ppm O3 (CD, 8-42). In addition to reducing Type I error, the correction for 

the multiple comparisons by Adams (2006) may have also increased Type II error (falsely 

accepting the null) for the simple evaluation of pre- to postexposure effects of O3 versus filtered 

air on FEV1, as has been commonly assessed by others (e.g., Horstman et al., 1990; McDonnell 

et al., 1991). A cursory evaluation 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 O3

(square-wave), and 0.06 ppm O3 (triangular) exposures, the FEV1 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 postexposure difference in FEV1 responses between filtered air and O3

exposure, the lack of an overlap in the range of responses (i.e., the means±SEs) at 0.06 ppm O3

versus filtered air is suggestive of a significant effect on FEV1. Furthermore, in a prior 

publication (Adams, 2002), the author stated that, “some sensitive subjects experience notable 

 2

 These studies reported O3 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 O3 (in a 

face mask exposure study) had greater than a 10% decrement in FEV1 even though the group 

mean response was not statistically different from the filtered air response. The effects described 

by Adams (2002), along with the cursory evaluation of the Adams (2006) data as described 

above, strongly suggest that exposure to 0.06 ppm O3 causes small group mean FEV1 decrements 

in healthy adults with some individuals having notable effects. 

 Although not mentioned in the CD, Adams (2006) reported that total subjective symptom 

scores (TSS) during the triangular 0.06 ppm exposure reached statistical 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 Table 4 of the Adams (2006) publication allow further 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, respectively, 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 

FEV1 changes, the lack of an overlap in the ranges of responses (i.e., the means±SEs) at 0.06 

ppm O3 versus filtered air for those two sympom scores is suggestive of a significant effect on 

respiratory symptoms. 

 A relatively large number of field studies investigating the effects of ambient O3

concentrations, in combination with other air pollutants, on lung function decrements and 

respiratory symptoms have been published 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 FEV1 or peak expiratory flow (PEF), and respiratory 

symptoms in healthy adults and asthmatic children are closely correlated to ambient O3

concentrations. Pre-1996 field studies focused primarily on children attending summer camps 

and found O3-related impacts on measures of lung function, but not respiratory symptoms, in 

healthy children. The newer studies have expanded to evaluate O3-related effects on outdoor 

workers, athletes, the elderly, hikers, school children, and asthmatics. Collectively, these studies 

confirm and extend clinical observations that prolonged exposure periods, combined with 

elevated levels of exertion or exercise, may magnify the effect of O3 on lung function. The most 

representative data come from the hiker study (Korrick et al., 1998), which provided outcome 

measures stratified by several factors (e.g., gender, 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 O3 exposure measurements 

were made. The mean 8-hr average O3 concentration was 40 ppb (SD 12). Decreased lung 

function was associated with O3 exposure, with the greatest effect estimates reported for the 
3-10 

subgroup that reported having asthma or wheezing, and for those who hiked for longer periods of 

time, thus increasing the exposure 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 O3 exposures among asthmatic and healthy 

persons (CD, sections 7.2.3.2 and 8.4.4.1). One large U.S. multicity study (Mortimer et al., 

2002) examined O3-related changes in PEF in 846 asthmatic children from 8 urban areas and 

reported that the incidence of > 10% decrements in morning PEF are associated with a 30 ppb 

increase in 8-hr average O3 for a 5-day cumulative lag, suggesting that O3 exposure may be 

associated with clinically significant changes 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 morning PEF remained statistically significant when days with 8-hr 

O3 concentrations above 80 ppb were excluded (CD, p. 7-46). Two studies (Romieu et al., 1996, 

1997) carried out simultaneously in northern and southwestern Mexico City with mildly 

asthmatic school children reported statistically significant O3-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 O3 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 statistically significant associations between O3

exposure and reduced PEF in asthmatics, other studies (Hiltermann et al., 1998; Delfino et al., 

1997a) did not, possibly due to very low levels of O3. Collectively, however, these studies 

indicate that O3 may be associated with short-term declines in lung function in asthmatic 

individuals and that they occurred at concentrations below those used in chamber studies using 

exercise (CD, p. 7-40 to 7-46). 

 Mortimer et al. (2002) discussed biological mechanisms for delayed effects on pulmonary 

function in asthma, which included increased nonspecific airway responsiveness secondary to 

airway inflammation due to O3 exposure (CD, p. 7-43). Animal toxicological and human 

chamber studies (CD, Chapters 5 and 6) provide supporting evidence that exposure to O3 may 

augment cellular infiltration and cellular activation, enhance release of cytotoxic inflammatory 

mediators, and alter membrane permeability (CD, p.7-44). In most laboratory animals studied, 

biochemical markers of lung injury and associated morphological changes were not found to be 

attenuated, even though at similar exposures pulmonary function changes might be attenuated. 

 Most of the panel studies which have investigated associations between O3 exposure and 

respiratory symptoms or increased use of asthma medication are focused 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 international 
3-11 

studies (Hilterman et al., 1998; Desqueyroux et al., 2002a,b), have reported fairly robust 

associations between ambient O3 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. urban areas to be most strongly associated with 

a cumulative 1- to 4-day lag of O3 concentrations (Mortimer et al., 2002). The NCICAS used 

standard protocols that included instructing caretakers of the subjects to record symptoms in the 

daily diary by observing or asking 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 the incidence of symptoms was 1.35 (95% CI: 1.04, 1.69) per 30 ppb 

increase in 8-hr avg O3 (10 a.m.-6 p.m.). The mean 8-hr avg O3 was 48 ppb across the 8 cities. 

Excluding days when 8-hr avg O3 was greater than 80 ppb (less than 5% of days), the odds ratio 

was 1.37 (95% CI: 1.02, 1.82) for incidence of morning symptoms. 

 Gent and colleagues (2003) followed 271 asthmatic children under age 12 and living in 

southern New England for 6 months (April through September) in a diary study of daily 

symptoms in relation to O3 and PM2.5. Mean 1-hr max O3 and 8-hr max O3 concentrations were 

58.6 ppb (SD 19.0) and 51.3 ppb (SD 15.5), respectively. The data were analyzed for two 

separate groups of subjects, 130 who used maintenance asthma medications during the follow-up 

period and 141 who did not. The need for regular medication was considered to be a proxy for 

more severe asthma. Not taking any medication on a regular basis and not needing to use a 

bronchodilator would suggest the presence of very mild asthma. Effects of 1-day lag O3 were 

observed on a variety of respiratory symptoms only in the medication user group. Both daily 1-

hr max and 8-hr max O3 concentrations were similarly related to symptoms such as chest 

tightness and shortness of breath. Effects of O3, but not PM2.5, remained significant and even 

increased in magnitude in two-pollutant models. Some of the associations were noted at 1-hr 

max O3 levels below 60 ppb. In contrast, no effects 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 O3, and provides supportive 

evidence for effects of O3 independent of PM2.5. Study limitations include 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 Mortimer et al. (2002), which provides an asthmatic population 

most representative of the United States, and several single-city studies indicate a robust 

association of O3 concentrations with respiratory symptoms and increased medication use in 

asthmatics. While there are a number of well-conducted, albeit relatively smaller, studies which 

showed only limited or a lack of evidence for symptom increases associated with O3 exposure, 
3-12 

these studies had less statistical power and/or were conducted in areas with relatively low O3

levels (CD, p. 7-54). The CD (p. 7-55) concludes that the asthma panel studies, as a group, and 

the NCICAS in particular, indicate a positive association between ambient concentrations and 

respiratory symptoms and increased medication use in asthmatics. The evidence has continued 

to expand since 1996 and now is considered to be much stronger than in the previous review of 

the O3 primary standard. 

 The association between school absenteeism and ambient O3 concentrations was assessed 

in two relatively large field studies (CD, section 7.2.6). Chen et al. (2000) examined daily 

school absenteeism in 27,793 elementary school students in Nevada over a 2-year period (after 

adjusting for PM10 and CO concentrations) and found that ambient O3 concentrations were 

associated with 10.41% excess rate of school absences per 40 ppb increase in 1-hr max O3 with a 

distributed lag of 1 to 14 days. Gilliland et al. (2001) studied O3-related absences among 1,933 

4th grade students in 12 southern California communities and found significant associations 

between 30-day distributed lag of 8-hr average O3 concentrations and all absence categories, and 

particularly for respiratory causes. Neither PM10 nor NO2 were associated with any respiratory 

or nonrespiratory illness-related absences in single pollutant models. The CD concludes that 

these studies of school absences suggest that ambient O3 concentrations, accumulated over two 

to four weeks, may be associated with school absenteeism, and particularly illness-related 

absences, but further replication is needed before firm conclusions can be reached regarding the 

effect of O3 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 propensity for the airways to bronchoconstrict due to a variety of stimuli 

(e.g., exposure to cold air, allergens, or exercise) becomes augmented (CD, section 6.8). This 

condition is typically quantified by measuring the decrement in pulmonary function (e.g., 

spirometry or plethysmography) after inhalation exposure to specific (e.g., antigen, allergen) or 

nonspecific (e.g., methacholine, histamine) bronchoconstrictor stimuli. Exposure to O3 causes an 

increase in nonspecific airway responsiveness as indicated by a reduction in the concentration of 

methacholine or histamine required to produce a given reduction in FEV1 or increase in SRaw. 

Increased airway responsiveness is an important consequence of exposure to O3 because its 

presence means that the airways are predisposed to narrowing on inhalation of various stimuli, 

such as specific allergens, cold air or SO2 (CD, p. 8-21). Significant, clinically relevant 

decreases in pulmonary function have been observed in early phase allergen response in subjects 

with rhinitis after consecutive (4-day) exposure to 0.125 ppm O3 (Holz et al., 2002). Similar 

increased airway responsiveness in asthmatics to house dust mite antigen 16 to 18 hrs after 
3-13 

exposure to a single dose of O3 (0.16 ppm for 7.6 hrs) was observed. These observations suggest 

that O3 exposure may be a clinically important factor that can exacerbate the response to ambient 

bronchoconstrictor substances in individuals with preexisting allergic asthma. Further, O3 may 

have an immediate impact on asthmatics as well as contribute to effects that persist for longer 

periods (CD, p. 8-21). 

 An important aspect of increased airway responsiveness after O3 exposure is that it 

represents a plausible link between O3 exposure and increased hospital admissions. Kreit et al. 

(1989) found that O3 can induce increased airway responsiveness in asthmatic subjects to O3, 

who typically have increased airway 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 lesser extent in subjects with allergic rhinitis after exposure to 0.25 

ppm O3 for 3 hrs; other studies (Molfino et al., 1991; Kehrl et al., 1999) reported similar results. 

According to one study (Folinsbee and Hazucha, 2000), changes in airway responsiveness after 

O3 exposure resolve more slowly than changes in FEV1 or respiratory symptoms. Other studies 

of repeated exposure to O3 suggest that changes in airway responsiveness tend to be somewhat 

less affected by attenuation with consecutive exposures than changes in FEV1 (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 effects of acute, long-term, and 

repeated exposure, at rest, to O3 indicates that induction of AHR occurs at relatively high 

(>1ppm) O3 concentrations (p. 8-21). These studies provide clues to the roles of physiological 

and biochemical components involved in this process, but caution should be exercised in 

interpreting these results, as different mechanisms 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 near-ambient concentrations of O3, and attenuation has been 

reported. In addition, dosimetric adjustments potentially could be made to allow better 

estimation of levels that would be relevant to human exposure effect levels. 

 The CD concludes that O3 exposure is linked with increased AHR (CD, section 6.8). 

Both human and animal studies indicate that AHR is not mechanistically associated with 

inflammation, but they do suggest a likely role for neuronal involvement (CD, p. 8-21). Increases 

in AHR do not appear to be strongly 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 previous review, acute inflammatory responses in the lung 

have been observed subsequent to 6.6 hr O3 exposures to the lowest tested level of 0.08 ppm in 

healthy adults engaged in moderately high exercise. Some studies suggest that inflammatory 
3-14 

responses may be detected in some individuals following O3 exposures in the absence of O3-

induced pulmonary decrements in those subjects. Short-term exposures to O3 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 newer findings consistent with the previous review, but also 

there is better characterization of the physiological mechanisms by which O3 causes these 

effects. 

 Lung inflammation and increased permeability, which are distinct events controlled by 

different mechanisms, are two well characterized effects of O3 exposure observed in all species 

studied. Disruption of the lung barrier leads to leakage of serum proteins, influx of 

polymorphonuclear leukocytes (PMNs), release of bioactive mediators, and movement of 

compounds from the airspaces into the blood. 

 In the animal toxicological studies discussed in the CD (Chapter 5), the lowest O3

concentration that induced inflammation in the mouse lung was 0.11 ppm for 24 hr exposures. 

Shorter exposures of 8 hours required concentrations of 0.26 ppm to induce epithelial 

permeability, although there was no effect on inflammation. The lowest O3 concentration that 

affected epithelial permeability or inflammation 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 exposures, the influence of the duration of exposure 

increases as the concentration of O3 increases; however, dosimetric adjustments would need to be 

done before one can compare levels. The exact role of inflammation in causation of lung disease 

is not known; nor is the relationship between inflammation and lung function (CD, p. 5-23). 

 A number of human O3-exposure studies have analyzed bronchoalveolar lavage (BAL) 

and nasal lavage (NL) fluids and cells for markers of inflammation 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 (PMNs) found in BAL fluid in the 

lungs, which has long been accepted as a hallmark of inflammation. It is apparent, however, that 

inflammation within airway tissues 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 O3. In addition to 

their role in inflammation, many of these compounds have bronchoconstrictive properties and 

may be involved in increased airway responsiveness following O3 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 O3 showed significantly increased permeability compared to cells from normal 

persons. This indicates a potentially inherent susceptibility of cells from asthmatic individuals 

for O3-induced permeability. 

 In the 1996 CD, assessment of human exposure studies indicated that a single, acute (1 to 

4 hr) O3 exposure (> 0.08 to 0.1 ppm) of subjects engaged in moderate to heavy exercise could 
3-15 

induce a number of cellular and biochemical changes suggestive of pulmonary inflammation and 

lung permeability (CD, p. 8-22). These changes persisted for at least 18 hrs. Graham and Koren 

(1990) compared inflammatory mediators present in NL and BAL fluids of humans exposed to 

0.4 ppm O3 for 2 hrs and found similar increases in PMNs in both fluids, suggesting 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 O3 for 6.6 hr with exercise, and McBride et al. (1994) reported that 

asthmatic subjects were more sensitive than non-asthmatics to upper airway inflammation for O3

exposures (0.24 ppm, 1.5 hr, with light IE) that did not affect pulmonary function (CD, p. 6-33). 

 The studies reporting inflammatory responses and markers of lung injury have clearly 

acknowledged that there is significant variation in response of subjects exposed, especially to 6.6 

hour O3 exposures at 0.08 and 0.10 ppm. To provide 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 subjects experienced notable increases (i.e., > 2 

fold increase) in most of the inflammatory and cellular injury indicators analyzed, associated 

with 6.6-hour exposures at 0.08 ppm. Similar, although in some cases higher, fractions of the 

population of 10 healthy adults tested saw > 2 fold increases associated 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 impairment 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 information on lung inflammation and epithelial permeability. 

Mudway and Kelly (2004) examined O3-induced inflammatory responses and epithelial 

permeability with a meta-analysis of 21 controlled human exposure studies and showed that 

PMN influx in healthy subjects is associated with total O3 dose ( product of O3 concentration, 

exposure duration, and minute ventilation) (CD, p. 6-34). Results of the analysis suggest that the 

time course for inflammatory responses (including recruitment of neutrophils and other soluble 

mediators) is not clearly established, but differential attenuation 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 provided evidence suggesting that asthmatics show greater 

inflammatory response than healthy subjects when exposed to similar O3 levels (CD, section 

6.9). Markers from BAL fluid following both 2-hr (Devlin et al., 1997) and 4-hr (Christian et al., 

1998; Jorres et al., 2000) O3 exposures repeated up to 5 days indicate that there is ongoing 

cellular damage irrespective of attenuation of some cellular inflammatory responses of the 

airways, pulmonary function, and symptom responses (CD, p. 8-22). 
3-16 

 The CD (p. 8-24) concludes that interaction of O3 with lipid constituents of epithelial 

lining fluid (ELF) and cell membranes and the induction of oxidative stress is implicated in 

injury and inflammation. Alterations in the expression of cytokines, chemokines, and adhesion 

molecules, indicative of an ongoing 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 inflammation. While antioxidants in 

ELF confer some protection, O3 reactivity is not eliminated at environmentally relevant 

exposures. Further, antioxidant reactivity with O3 is both species-specific 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 O3 have 

been shown to impair host defense capabilities in both humans and experimental animals by 

depressing alveolar macrophage (AM) functions and by altering the mucociliary clearance of 

inhaled particles and microbes. Short-term O3 exposures also interfere with the clearance 

process by accelerating clearance for low doses and slowing clearance for high doses. Animal 

toxicological studies have reported that acute O3 exposures suppress alveolar 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 O3

levels as low as 0.08 ppm (CD, p. 8-26). 

Changes in antibacterial defenses are dependent on exposure regimens, species and strain 

of lab animals, species of bacteria, and age of the animals used. Acute O3-induced suppression 

of alveolar phagocytosis and immune function in experimental animals appeared to be transient 

and attenuated with continuous or repeated exposures. Ozone exposure has also been shown to 

interfere with AM-mediated clearance in the respiratory region of the lung and with mucociliary 

clearance of the tracheobronchial airways. These interferences with clearance are dose 

dependent, with low doses accelerating clearance and high doses slowing the process (CD, p. 8-

26). 

 A single controlled human exposure study (Devlin et al., 1991) reviewed in the 1996 CD 

reported that exposure to 0.08 to 0.10 ppm O3 for 6.6 hrs (with moderate exercise) induced 

decrements in the ability of AMs to phagocytose microorganisms (CD, p. 8-26). Integrating the 

recent study results with evidence available in the 1996 CD, the CD concludes that available 

evidence indicates that short-term O3 exposures have the potential to impair host defenses, 

primarily by interfering with AM function. Any impairment in AM function may lead to 

decreased clearance of microorganisms or nonviable particles. Compromised AM functions in 
3-17 

asthmatics may increase their susceptibility to other O3 effects, the effects of particles, and 

respiratory infections (CD, p. 8-26). 

3.3.1.1.5 Morphological Effects 

The 1996 CD found that short-term O3 exposures cause similar alterations in lung 

morphology in all laboratory animal species studied, including primates. Cells in the 

centriacinar region (CAR) of the lung (the segment between the last conducting airway and the 

gas exchange region) have been recognized as a primary target of O3-induced damage (epithelial 

cell necrosis and remodeling of respiratory bronchioles), possibly because epithelium in this 

region receives the greatest dose of O3 delivered to the lower respiratory tract. Following 

chronic O3 exposure, structural changes have been observed in the CAR, the region typically 

affected in most chronic airway diseases 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 O3 exposures can cause epithelial cell 

profileration and fibrolitic changes in the CAR, these changes appear to be transient with 

recovery time after exposure, depending on species and O3 dose. The potential impacts of 

repeated short-term and chronic morphological effects of O3 exposure are discussed later in 

section 3.3.1.2.5. 

 Recent studies continue to show that short-term and sub-chronic exposures to O3 cause 

similar alterations in lung structure in a variety of experimental animal species, at concentrations 

of 0.15 ppm in rats (12 hr/day for 6 weeks) and even lower concentrations 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 nasal epithelia, while exposure to bacterial endotoxin 

can potentiate effects. Ozone-induced fibrotic changes in the CAR are maximal at 3 days of 

exposure and recover 3 days post-exposure with exposures of 0.2 ppm O3 in rodents. One study 

has demonstrated variability of local O3 dose and subsequent injury in the respiratory tract due to 

depletion of glutathione (GSH). The proximal respiratory bronchiole receives the most acute 

epithelial injury from exposures < 1 ppm, while metabolic effects were greatest in the distal 

bronchioles and minor daughter airways (CD, p. 5-38). 

 Based on evidence from animal toxicological studies, short-term and sub-chronic 

exposures to O3 can cause morphological changes in the respiratory 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 hospital admissions as possible outcomes 

following exposure to O3 (CD, section 7.3). The evidence was limited for ED visits, but results 
3-18 

of several studies generally indicated that short-term exposures to O3 were associated with 

respiratory ED visits. The strongest and most consistent evidence, both below and above 0.12 

ppm 1-hr max O3, was found in the group of studies which investigated summertime daily 

hospital admissions for respiratory causes in different eastern North American cities. These 

studies were consistent in demonstrating that ambient O3 levels were associated with increased 

hospital admissions and accounted for about one to three excess respiratory hospital admissions 

per million persons with each 100 ppb increase in 1-hr max O3, with adjustment for possible 

confounding effects of temperature and copollutants. Overall, the 1996 CD concluded that there 

was strong evidence that ambient O3 exposures can cause significant exacerbations of preexisting 

respiratory disease in the general public (CD, p. 7-66). Excess respiratory-related hospital 

admissions associated with O3 exposures for the New York City area (based on Thurston et al., 

1992) were included in the quantitative risk assessment in the prior review and are included in 

the current assessment along with estimates for respiratory-related hospital admissions in 

Cleveland, Detroit, and Los Angeles based on more recent studies (see Chapter 5). Significant 

uncertainties and the difficulty of obtaining reliable baseline incidence numbers resulted in ED 

visits not being used in the quantitative risk assessment conducted in the last O3 NAAQS review. 

 In the past decade, a number of studies have examined the temporal pattern associations 

between O3 exposures and ED visits for respiratory causes (CD, section 7.3.2). These studies are 

summarized in the CD (Table AX7-3, Chapter 7 Annex). Respiratory causes for ED visits 

include asthma, bronchitis, emphysema, pneumonia, and other upper and lower respiratory 

infections, such as influenza, but asthma visits typically dominate the daily incidence counts. 

Among studies with adequate controls for seasonal patterns, many reported at least one 

significant positive association involving O3. These studies examined ED visits for total 

respiratory complaints (Delfino et al., 1997b, 1998b; Hernandez-Garduno 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 ; Tolbert et al., 2000 ; Weisel et al., 2002), and COPD 

(Tenias et al., 2002). 

 Figure 7-8 (CD, p. 7-68) provides effect estimates for associations between ED visits for 

asthma and short-term O3 exposures. In general, O3 effect estimates from summer only analyses 

tended to be positive and larger compared to results from cool season or all year analyses (CD, p. 

7-67). Several of the studies reported significant associations between O3 concentrations and ED 

visits for respiratory causes. However, inconsistencies were observed which were at least 

partially attributable to differences in model specifications and analysis approach among various 

studies. For example, ambient O3 concentrations, length of the study period, and statistical 

methods used to control confounding by seasonal patterns and copollutants appear to affect the 

observed O3 effect on ED visits. Thus, the CD (p. 7-71) has concluded that stratified analyses by 
3-19 

season generally supported a positive association between O3 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 environmental factors, such as high O3 levels. 

Thus, hospital admissions studies focus specifically on unscheduled admissions. Results of a 

fairly large number of these studies published during the past decade are summarized in Table 

AX7-4 (CD, Chapter 7 Annex). As a group, these hospital admissions studies tend to be larger 

geographically and temporally than the ED visit studies and provide results that are generally 

more consistent. The largest and most significant associations of respiratory hospital admissions 

with O3 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, statistically significant associations between ambient O3

concentrations and respiratory hospital admissions in the warm season, including studies with 

98th percentile 8-hr maximum O3 levels as low as about 50 ppb. However, not all studies found 

a statistically significant relationship with O3, possibly because of very low ambient O3 levels. 

Analyses for confounding using multipollutant regression models suggest that copollutants 

generally do not confound the association between O3 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 O3 concentrations and various respiratory disease hospitalization outcomes, when 

focusing particularly on results of warm-season analyses. Recent studies also generally 

supported a positive association between O3 concentrations and ED visits for asthma during the 

warm season (CD, p. 7-175). These observations are strongly supported by the human clinical, 

animal toxicologic, and epidemiologic evidence for lung function decrements, increased 

respiratory symptoms, airway inflammation, and increased airway responsiveness. Taken 

together, the overall evidence supports a causal relationship between acute ambient O3 exposures 

and increased respiratory morbidity outcomes 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 O3 exposure on exercise performance of healthy individuals have been 

investigated in a number of controlled exposure studies (CD, section 6.7). Several studies

discussed in the 1996 CD reported that endurance exercise performance and VO2max may be 

limited by acute exposure to O3. Other studies found that significant reductions in maximal 

endurance exercise performance may occur in well-conditioned athletes while they perform CE 

(VE > 80 L/min) for 1 hr at O3 concentrations > 0.18 ppm. There are no new studies available in 
3-20 

the CD. Thus, as in the 1996 CD, the CD concludes that reports from studies of O3 exposure 

during high-intensity exercise indicate that breathing discomfort associated with maximal 

ventilation may be an important factor in limiting exercise performance in some, but not all, 

subjects (CD, p. 6-30). 

3.3.1.2 Effects on the Respiratory System from Long-term Exposures 

 The 1996 CD concluded that there was insufficient evidence from the limited number of 

studies to determine whether long-term O3 exposures resulted in chronic health effects at 

ambient levels observed in the U.S. However, the aggregate evidence suggested that O3

exposure, along with other environmental factors, could be responsible for health effects in 

exposed populations (CD, section 7.5). Animal toxicological studies carried out in the 1980’s 

and 1990’s demonstrated that long-term exposures can result in a variety of morphological 

effects, including permanent changes in the small airways of the lungs, including remodeling of 

the distal airways and CAR and deposition of collagen, possibly representing fibrotic changes. 

These changes result from the damage and repair processes that occur with repeated exposure. 

Fibrotic changes were also found to persist after months of exposure providing a potential 

pathophysiologic basis for changes in airway function observed in children in some recent 

epidemiological studies. It appears that variable seasonal ambient patterns of exposure may be 

of greater concern than continuous daily exposures. 

This section reviews studies published since 1996 in which health effects were assessed 

for O3 exposures lasting from weeks to several years. Summaries of recent morphological 

effects studies of subchronic and chronic exposures are listed in Table AX5-10 (CD, Annex 

AX5). Summaries of recent morbidity effects epidemiological studies of long-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 human exposure and field studies that daily multihour exposures to O3 produce transient declines in lung function; however, lung function effects 

of repeated exposures to O3 over extended periods are not as well characterized. Several studies 

published since 1996 have investigated lung function changes over seasonal time periods (CD, 

section 7.5.3). One large, three-year study (Frischer et al., 1999) collected repeated lung 

function measurements in 1,150 young, Austrian school children in 9 communities and reported 

that there may be an association between developmental changes in lung function over the 

summer season and seasonal mean O3 levels. Mean summertime 24-hr avg O3 concentrations 

during the three summers was 34.8 ppb (SD 8.7). The number of days with half-hour maximum 

O3 concentrations greater than 60 ppb ranged from 44 to 99 days across the 9 communities. 

Seasonal mean O3 was associated with reduced lung function development. It was cautioned that 
3-21 

it was difficult to attribute the reported effects to O3 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 O3 levels may be related to a negative effect on increases in lung function in 

children. A study (Kopp et al., 2000) of 797 children in Austria and southwestern Germany 

reported smaller increases in lung function in children exposed to higher levels of ambient O3

(mean O3 concentration of 44 to 52 ppb) compared to children living in areas with lower ambient 

O3 levels (25 to 33 ppb). Another Austrian study (Ihorst et al., 2000) of 2,153 young children 

found significantly lower FVC and FEV1 increases associated with higher O3 exposures in the 

summer but not in the winter. A pilot study (Kinney and Lippmann, 2000) of 72 young adult, 

military academy students provided results that are consistent with a seasonal decline in lung 

function that may be due, in part, to O3 exposures. According to the CD (p. 7-114), these studies 

collectively indicate that seasonal O3 exposure is associated with smaller growth-related 

increases in lung function in children than they would have experienced living in clean air and 

that there is some limited evidence that seasonal O3 also may affect lung function in young 

adults, although uncertainty about the role of copollutants makes it difficult to attribute the 

effects to O3 alone. 

3.3.1.2.2 Reduced Baseline Lung Function and Respiratory Symptoms 

 Lung capacity grows during childhood and adolescence as body size increases, reaches a 

maximum during the twenties, and then begins to decline steadily and progressively with age. 

Long-term exposure to air pollution has long been thought to contribute to slower growth in lung 

capacity, diminished maximally attained capacity, and/or more rapid decline in lung capacity 

with age (CD, section 7.5.4). Toxicological findings evaluated in the 1996 CD demonstrated that 

repeated daily exposure of rats to an episodic profile of O3 caused small, but significant, 

decrements in growth-related lung function that were consistent with early indicators of focal 

fibrogenesis in the proximal alveolar region, without overt fibrosis (CD, section 5.2.5.2). 

Because O3 is a strong respiratory irritant and has been shown to cause inflammation and 

restructuring of the respiratory airways, it is plausible that long-term O3 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 O3 exposure. 

 Several epidemiological studies published since 1996 have examined the relationship 

between lung function development and long-term O3 exposure. The most extensive and robust 

study of respiratory effects in relation 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; Gauderman et al., 2000, 2002, 2004a,b; Peters et al., 1999a,b). One 
3-22 

study (Peters et al., 1999a) examined the relationship between long-term O3 exposures and self 

reports of respiratory symptoms and asthma in a cross sectional analysis and found a limited 

relationship between outcomes of current asthma, bronchitis, cough and wheeze and a 40 ppb 

increase in 1-hr max O3 (CD, p. 7-115). Another analysis (Peters et al., 1999b) examined the 

relationship between lung function at baseline and levels of air pollution in the community and 

reported evidence that annual mean O3 levels were associated with decreases in FVC, FEV1, PEF 

and FEF25-75 (the latter two being statistically significant) among females but not males (CD, p. 7-

116). In a separate study (Gauderman et al., 2000) of 4th, 7th, and 10th grade students, a 

longitudinal analysis of lung function development over four years found no association with O3

exposure. Subsequent studies by the same group (Gauderman et al., 2002, 2004a,b) led the 

authors to conclude that results provide little evidence that ambient O3 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). Avol et al. (2001) examined children who had moved from 

participating communities in southern California to other states with improved air quality and 

found, with the exception of FEV1, the O3 effect estimates for all other spirometric parameters 

were negative, but the associations were not as strong as those observed for PM10 (CD, p. 7-116). 

Collectively, the results of these reports from the children’s health cohorts provide little evidence 

for impact of long-term O3 exposures on lung function development (CD, p. 7-122). 

 Evidence for a significant relationship between long-term O3 exposures and decrements 

in maximally attained lung function was reported in a nationwide study of first year Yale 

students (CD, p. 7-120). Males had much larger effect estimates than females, which might 

reflect higher outdoor activity levels and correspondingly higher O3 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 O3 exposures on lung 

function (CD, p. 7-121). In a comparison of students whose city of origin was either Los 

Angeles or San Francisco, long-term O3 exposures were associated with significant changes in 

mid- and end-expiratory flow measures, which could be considered early indicators for 

pathologic changes that might progress to COPD. 

 In summary, recent publications from the southern California children’s cohort study 

provide no evidence for an association between long-term O3 exposure and lung function 

development in children (CD, p. 7-118), while limited evidence available from studies of adults 

and college students suggest that long-term O3 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 effects of long-term O3 exposure on respiratory symptoms or lung function (CD, 

p. 7-175). 
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3.3.1.2.3 Long-term O3 Exposure and Respiratory Inflammation 

 As noted above in section 3.3.1.1.3 and in the CD (Chapter 6), chamber studies of 

exercising humans exposed to O3 for 2 to 6.6 hrs have demonstrated inflammation in the lungs, 

including the alveolar region where gas exchange takes place. The potential long-term 

significance of short-term exposures to O3 is that they can result in the release of reactive 

substances from inflammatory cells that can damage the sensitive cells lining the lungs. Over 

time repeated inflammation can lead to permanent lung damage and restructuring of the small 

airways and alveoli. Also, since inflammation is a hallmark characteristic of asthma, there is the 

possibility that O3-induced inflammation may exacerbate existing asthma or contribute to the 

development of asthma in genetically predisposed individuals (CD, section 7.5.5). 

 For subchronic exposures of animals, permeability changes are transient (and speciesdependent) and return to control levels even with continuing exposure. For long-term O3 

exposures, persistent O3-induced inflammation plays an important role in alterations of lung 

structure and function. Significant remodeling of the epithelium and underlying connective 

tissues in distal airways have been reported in rats exposed to 0.25 ppm O3 (12 hr/day for 6 

weeks) and in monkeys exposed to 0.15 ppm O3 (8 hr/day for 90 days)(CD, p. 8-23). 

 In one epidemiological field 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 damage (CD, p. 7-122). The mean 1-hr max 

concentrations for a 3-month period were 58 ppb (max 110 ppb) in the summer and 32 ppb (max 

64 ppb) in the winter. There was little evidence of an association between O3 and acute 

inflammation in the summer BAL fluids compared to winter, but there was evidence of enhanced 

cell damage. This suggests that even though inflammation may diminish over the summer, cell 

damage may be continuing. A cross-sectional cohort study (Calderon-Garciduenas et al., 1995) 

conducted in Mexico City provides evidence of inflammation and genetic damage to cells in the 

nasal passages of children chronically exposed to O3 and other air pollutants (CD, p. 7-123). In 

Mexico City, the 1-hr avg O3 concentrations exceeded 120 ppb for 4.4 hr/day, on average. 

Significantly higher DNA damage was reported in children living in Mexico City compared to 

nonurban children and in older compared to younger children. Another marker of inflammation, 

urinary eosinophils, was analyzed in an Austrian school children study (Frischer et al., 2001), 

and it was reported that O3 exposure (mean 30 day avg O3 concentration before sample collection 

was 31.6 ppb) was significantly associated with eosinophil inflammation (CD, p. 7-122). 

 In assessing these studies, the CD (p. 7-123) concluded that specific attribution of these 

adverse respiratory and genotoxic effects to O3 is difficult given the complex mixture in ambient 

air, although inflammatory changes like eosinophil levels observed in the Austrian study would 

be consistent with known effects of O3. 
3-24 

3.3.1.2.4 Risk of Asthma Development 

 There have been a few studies investigating associations between long-term O3 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., 1993; McDonnell et al., 1999). 

Subjects were surveyed in 1977, 1987, and 1992. During the ten-year follow-up in 1987, it was 

reported that the incidence of new asthma was 2.1% for males and 2.2% for females (Greer et al., 

1993). A statistically significant relative risk of 3.12 (95% CI: 1.16, 5.85) per 10 ppb increase in 

annual mean O3 was observed in males, compared to a nonsignificant 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 females 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 O3, but there was no evidence of an association in females. The lack of an 

association in females does not necessarily mean there is no effect but may be due to differences 

in time-activity patterns in males and females, which could lead to greater misclassification of 

exposure in females. Consistency of results in the two studies with different follow-up times 

provides supportive evidence of an association between long-term O3 exposure and asthma 

incidence in adult males; however, representativeness of this cohort to the general U.S. 

population may be limited (CD, p. 7-125). 

 In a similar study (McConnell et al., 2002) of incident asthma among children (ages 9 to 

16 at enrollment), annual surveys 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-O3 (75.4 ppb mean 1-hr 

max over four years) and six low-O3 (50.1 ppb, mean 1-hr max) communities were identified 

where the children resided. There were 265 children who reported new-onset asthma during the 

follow-up period. Although asthma risk was no higher for all residents of the six high-O3 

communities versus the six low-O3 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-O3 communities. This association was absent in the communities with lower O3 

concentrations. No other pollutants were found to be associated with new-onset asthma (CD, p. 

7-125). 

 Playing sports may result in extended outdoor activity and exposure occurring during 

periods when O3 levels are higher. The sports activities would cause an increased ventilation 

rate, thus resulting in increased O3 dose. It should be noted, however, that the results of the 

Children’s Health Study (McConnell et al., 2002) were based on a small number (20 in high-O3

areas and 9 in low- O3 areas) of new-onset asthma cases among children who played three or 
3-25 

more sports (CD, p. 7-125). Future replication of these findings in other cohorts would help 

determine whether a causal interpretation is appropriate. 

3.3.1.2.5 Morphological Effects 

 In animal toxicology studies, the progression of morphological effects reported during 

and after a chronic exposure in the range of 0.5 to 1.0 ppm O3 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 changes sometimes persist or 

increase. Epithelial hyperplasia peaks soon after the inflammatory response but is usually 

maintained in both the nose and lungs with continuous 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 effects, with 18 months of daily 

exposure, causing less morphologic damage than exposures on alternating months. This is 

important as environmental O3 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 monkeys exposed to simulated, seasonal O3 (0.5 ppm, 8 hrs/day 

for 5 days, every 14 days for 11 episodes) and demonstrated: 1) remodeling in the distal airways, 

2) abnormalities in tracheal basement membrane; 3) eosinophil accumulation in conducting 

airways; and 4) decrements in airway innervation (CD, p. 5-45). As with other effects, these 

findings advance earlier information regarding possible injury-repair processes occurring with 

long-term O3 exposures suggesting that these processes are only partially reversible and may 

progress following cessation of O3 exposure. Further, these processes may lead to nonreversible 

structural damage to lung tissue; however, there is still too much uncertainty 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 longitudinal studies have examined the effect of 

chronic O3 exposure on respiratory health outcomes. Evidence from recent long-term morbidity 

studies have suggested in some cases that chronic exposure to O3 may be associated with 

seasonal declines in lung function or reduced lung function 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 supportive evidence 

from animal studies involving chronic exposures, large uncertainties still remain as to whether 

current ambient levels and exposure patterns might cause these same effects in human 
3-26 

populations. The CD also concludes that epidemiological studies of new asthma development 

and longer-term lung function declines remain inconclusive at present (CD, p. 7-134). 

3.3.1.3 Effects on the Cardiovascular System 

 At the time of the 1997 review, the possibility of O3-induced cardiovascular effects was a 

largely unrecognized issue. Since then, a very limited body of evidence from animal, controlled 

human exposure and epidemiologic studies has emerged that provides some potential plausible 

mechanisms for how O3 exposures might exert cardiovascular system effects, however much 

needs to be done to substantiate these effects. Possible mechanisms may involve O3-induced 

secretions of vasoconstrictive substances and/or effects on neuronal reflexes that may result in 

increased arterial blood pressure and/or altered electrophysiologic control of heart rate or 

rhythm. Some animal toxicology studies have shown O3-induced decreases in heart rate, mean 

arterial pressure, and core temperature. One controlled human exposure study that evaluated 

effects of O3 exposure on cardiovascular health outcomes found no significant O3-induced 

differences in ECG or blood pressure in healthy or hypertensive subjects but did observe a 

significant O3-induced increase the alveolar-to-arterial PO2 gradient and heart rate in both groups 

resulting in an overall increase in myocardial work and impairment in pulmonary gas exchange 

(Gong et al., 1998). In another controlled human exposure study, inhalation of a mixture of 

PM2.5 and O3 by healthy subjects increased brachial artery tone and reactivity (Brook et al., 

2002). 

 The evidence from a few animal studies also includes potential direct effects such as O3-

induced release from lung epithelial cells of platelet activating factor (PAF) that may contribute 

to blood clot formation that would increase the risk of serious cardiovascular outcomes (e.g., 

heart attack, stroke, mortality). Also, interactions of O3 with surfactant components in epithelial 

lining fluid of the lung may result in production of oxysterols and reactive oxygen species that 

may exhibit PAF-like activity contributing to clotting and also may exert cytotoxic effects on 

lung and heart muscle cells. 

 Epidemiologic panel and field studies that examined associations between O3 and various 

cardiac physiologic endpoints have yielded limited evidence suggestive of a potential association 

between acute O3 exposure and altered heart rate variability, ventricular arrhythmias, and 

incidence of heart attacks. A number of epidemiological studies have also reported associations 

between short-term exposures and hospitalization for cardiovascular diseases. As shown in 

Figure 7-13 of the CD, many of the studies reported negative or inconsistent associations. Some 

other studies, especially those that examined the relationship when O3 exposures were higher, 

have found robust positive associations between O3 and cardiovascular hospital admissions (CD, 

p. 7-82). For example, one study reported a positive association between O3 and cardiovascular 
3-27 

hospital admissions in Toronto, Canada in a summer-only analysis (mean 1-hr max O3 of 41.2 

ppb) (Burnett et al., 1997b). The results were robust to adjustment for various PM indices, 

whereas the PM effects diminished when adjusting for gaseous pollutants. Other studies 

stratified their analysis by temperature, i.e., by warms days (≥ 20°C) versus cool days (< 20°C). 

Several analyses using warms days consistently 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 cardiovascular hospitalizations with warm-season O3 

concentrations. Most of the available European and Australian studies, all of which conducted 

all-year O3 analyses, did not find an association between short-term O3 concentrations and 

cardiovascular hospitalizations. Overall, the currently available evidence is inconclusive 

regarding an association between cardiovascular hospital admissions and ambient O3 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 O3 can directly and/or indirectly contribute to cardiovascular-related morbidity, 

but that much needs to be done to more fully substantiate links between ambient O3 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 O3

and mortality available for review in the 1996 CD. Some studies suggested that mortality was 

associated with short-term exposure to O3, 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 epidemiological evidence was available on potential 

associations between long-term exposure to O3 and mortality. Some recent studies have 

evaluated this relationship and provide limited, if any, evidence for an association between 

chronic O3 exposure and mortality, as described in section 3.3.2.2. 

3.3.2.1 Mortality and Short-term O3 Exposure 

 The 1996 CD concluded that an association between daily mortality and O3 concentration 

for areas with high O3 levels (e.g., Los Angeles) was suggested. However, due to a very limited 

number of studies available at that time, there was insufficient evidence to conclude that the 

observed association was likely causal, and thus the possibility that O3 exposure may be 

associated with mortality was not relied upon in the 1997 decision on the O3 primary standard. 
3-28 

 The 2006 CD includes results from numerous epidemiological analyses of the 

relationship between O3 and mortality. Key findings are available from multi-city time-series 

studies that report associations between O3 and mortality. These studies include analyses using 

data from 90 U.S. cities in the National Mortality, Morbidity and Air Pollution (NMMAPS) 

study (Dominici et al., 2003) and from 95 U.S. communities in an extension to the NMMAPS 

analyses (Bell et al., 2004). The analyses conducted by Huang et al. (2005) used a subset of 19 

U.S. cities and focused primarily on cause-specific mortality associations 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 O3-mortality 

relationship (CD, p. 8-38). Finally, 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 PM10 on mortality. A significant association was reported 

between mortality and 24-hr average O3 concentrations during the warm season, but the 

association was not significant in analyses for the full year (Samet et al., 2000) (CD, Figure 7-21; 

p. 7-98). This is because the estimate using all available data was about half that for the 

summer-only data at a lag of 1-day. 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 associations were reported between O3 and mortality. The effect estimate for 

increased mortality was 0.5% per 24-hr average O3 measured on the same day (20 ppb change; 

95% PI: 0.24, 0.78), and 1.04% per 24-hr average O3 in a 7-day distributed lag model (20 ppb 

change; 95% PI: 0.54, 1.55) (CD, p. 7-88). In analyses using only data from the warm season, 

the results were not significantly different from the full-year results; the effect estimate for 

increased mortality was 0.44% per 24-hr average O3 measured on the same day (20 ppb change; 

95% PI: 0.14, 0.74), and 0.78% per 24-hr average O3 in a 7-day distributed lag model (20 ppb 

change; 95% PI: 0.26, 1.30). The authors also report that O3-mortality associations were robust 

to adjustment for PM (CD, p. 7-100). 

 Using a subset of the NMMAPS data set, Huang et al. (2005) focused on associations 

between cardiopulmonary mortality and O3 exposure (24-hr avg) during the summer season only. 

The authors report a 1.47% increase per 20 ppb change in O3 concentration measured on the 

same day (95% PI: 0.54, 2.39) and a 2.52% increase per 20 ppb change in O3 concentration using 

a 7-day distributed lag model (95% PI: 0.94, 4.10)(CD, p. 7-92). These findings suggest that the 

effect of O3 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 the increased photochemical 
3-29 

activities that are important for O3 formation. Using a case-crossover study design, Schwartz 

(2005) assessed associations between daily maximum concentrations 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 O3 (1-hr max, 95% PI: 0.06, 

1.80) was similar to time-series analysis results with adjustment for temperature (0.76% per 40 

ppb O3, 95% PI, 0.13, 1.40), suggesting that associations between O3 and mortality were robust 

to the different adjustment methods for temperature (CD, p. 7-93). 

 An initial publication from APHEA, a European multi-city study, reported statistically 

significant associations between daily maximum O3 concentrations and mortality, with an effect 

estimate of a 4.5% increase in mortality per 40 ppb O3 (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 significant association was 

found between mortality and 1-hr daily maximum O3 in a full year analysis (CD, p. 7-93). 

Gryparis et al. (2004) noted that there was a considerable seasonal difference in the O3 effect on 

mortality; thus, the small effect for the all-year data might be attributable to inadequate 

adjustment for confounding by seasonality. Focusing on analyses using summer measurements, 

the authors report statistically significant associations with total mortality [1.8% increase per 30 

ppb 8-hr O3 (95% CI: 0.8, 2.9)], cardiovascular mortality [2.7% increase per 30 ppb 8-hr O3

(95% CI: 1.2, 4.3)] and with respiratory mortality (6.8% increase per 30 ppb 8-hr O3, 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 between mortality and 1-hr daily max, 8-hr daily max and 24-hr avg 

O3 concentrations. Effect estimates for associations with 1-hr O3 was slightly larger than that 

reported for 8-hr O3 concentrations, and both were slightly larger than the association with 24-hr 

avg O3, but the effect estimates did not differ statistically. The APHEA study (Gryparis et al., 

2004) also reported effect estimates that were slightly larger with 1-hr than with 8-hr O3

concentrations, but not significantly so. 

 Numerous single-city analyses have also reported associations between mortality and 

short-term O3 exposure, especially for those analyses using warm season data. As shown in 

Figure 7-21 of the CD, the results of recent publications show a pattern of positive, often 

statistically significant associations between short-term O3 exposure and mortality during the 

warm season (CD, p. 7-97). For example, statistically significant associations 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 association was seen in a study conducted in Pittsburgh 
3-30 

(Chock et al., 2000). In considering results from year-round analyses, there remains a pattern of 

positive results but the findings are less consistent. For example, statistically significant 

associations were reported in Philadelphia (Moolgavkar et al., 1995) and Dallas (Gamble et al., 

1998), while positive but not statistically significant associations were reported in Detroit 

(Lippmann et al., 2000, reanalyzed in Ito, 2003), San Jose (Fairley, 1999, reanalyzed Fairley, 

2003), 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. Louis and Eastern 

Tennessee (Dockery et al., 1992). In most single-city analyses, effect estimates were not 

substantially changed with adjustment for PM (CD Figure 7-22, p. 7-101). 

 In addition, several meta-analyses have been conducted on the relationship between O3

and mortality. As described in section 7.4.4 of the CD, these analyses reported fairly consistent 

and positive combined effect estimates ranging from 1.5 to 2.5% increase in mortality for a 

standardized change in O3 (CD, Figure 7-20, p. 7-95). Three recent meta-analyses evaluated 

potential sources of heterogeneity in O3-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 

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 evidence of publication bias, but O3-mortality associations remained after accounting 

for that potential bias. The CD (7-97) concludes that the “positive O3 effects estimates, along 

with the sensitivity analyses in these three meta-analyses, provide evidence of a robust 

association between ambient O3 and mortality.” 

Most of the single-pollutant model estimates from single-city studies range from 0.5 to 

5% excess deaths per standardized increments. Corresponding summary estimates in large U.S. 

multi-city studies ranged between 0.5 to 1% with some studies noting heterogeneity across cities 

and studies (CD, p. 7-110). 

In the CD (p. 7-101), Figure 7-22 shows the O3 risk estimates with and without 

adjustment for PM indices using all-year data in studies that conducted two-pollutant analyses. 

Approximately half of the O3 risk estimates increased slightly, whereas the other half decreased 

slightly with the inclusion of PM in the models. In general, the O3-mortality risk estimates were 

robust to adjustment for PM in the models, with the exception of Los Angeles, CA data with 

PM10 (Kinney et al., 1995) and Mexico City data with TSP (Borja-Aburto et al., 1997). The U.S. 

95 communities study (Bell et al., 2004) examined the sensitivity of acute O3-mortality effects to 

potential confounding by PM10 (CD, 7-100). Restricting analysis to days when both O3 and PM10

data were available, the community-specific O3-mortality effect estimates as well as the national 

average results indicated that O3 was robust to adjustment for PM10 (Bell et al., 2004). 
3-31 

 Several O3-mortality studies examined the effect of confounding by PM indices in 

different seasons (CD, p. 7-102, Figure 7-23). In analyses using all-year data and warm-season 

only data, O3 effect estimates were once again fairly robust to adjustment for PM indices, with 

values showing both slight increases and decreases with the inclusion of PM in the model. In the 

analyses using cool season data only, the O3 effect estimates all increased slightly with the 

adjustment of PM indices, although none reached statistical 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 O3 risk estimates. No substantial influence was observed in 

any of these studies. In the analysis by Bell et al. (2005), the combined estimate without PM 

adjustment was 1.7% (95% PI: 1.10, 2.37) from 41 estimates, and the 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 O3. In the meta-analysis of 15 cities (Ito et al., 2005), the combined 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 O3 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 regression relationships between O3 and 

PM indices (PM10 and PM2.5) with O3-mortality effect estimates for all year and by season. 

Positive slopes, which might indicate potential confounding, were observed for PM2.5 on O3

effect estimates in the summer and all-year periods, but the relationships were weak. The effect 

of one causal variable (i.e., O3) is expected to be overestimated when a second causal variable 

(e.g., PM) is excluded from the analysis, if the two variables are positively correlated and act in 

the same direction. However, the results from these meta-analyses, as well as several single- and 

multiple-city studies, indicate that copollutants generally do not appear to substantially confound 

the association between O3 and mortality (CD, p. 7-103). 

 Finally, from those studies that included assessment of associations with specific causes 

of death, it appears that effect estimates for associations with cardiovascular mortality are larger 

than those for total mortality; effect estimates for respiratory mortality are less consistent in size, 

possibly due to reduced statistical power in this subcategory of mortality (CD, p. 7-108). The 

U.S. 95 communities study (1987-2000) analyzed O3 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-season only data from 40 communities. The 

national average estimate from the constrained distributed lag model was slightly greater for 

cardiopulmonary deaths than deaths 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 O3 in the 

preceding week. 
3-32 

One recent multi-city study (Bell et al., 2006) examined the shape of the concentrationresponse function for the O3-mortality relationship in 98 U.S. urban communities for the period 

1987 to 2000 specifically to evaluate whether a “safe” threshold level exists. Results from 

various analytic methods all indicated that any threshold would exist at very low concentrations, 

far below the level of the current O3 NAAQS and other, lower international O3 standards,3

 and 

nearing background levels. Notably, in a subset analysis using only days that were below the 

level of the current O3 NAAQS, the O3-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 O3 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 maximum 8-hr average concentrations in U.S. 

cities that are within the range of background concentrations. The authors conclude that 

“interventions to further reduce ozone pollution would benefit public health, even in regions that 

meet current regulatory standards and guidelines” (Bell et al., 2006, p. 3). 

A related study (Huang et al., 2005) examined O3 effects on cardiopulmonary mortality 

during the summers (June to September) of 1987 to 1994 in 19 large U.S. cities from the 

NMMAPS database. Figure 7-24 in the CD (p. 7-104), presents the Bayesian city-specific and 

overall average O3 effect estimates for cardiopulmonary mortality per 20 ppb increase in 24-hr 

avg O3 from a constrained 7-day distributed lag model. The O3 effect estimate was 2.52% (95% 

PI: 0.94, 4.10) excess risk in cardiopulmonary mortality per 20 ppb increase in 24-hr avg O3 in 

the preceding week for the combined analysis of all cities. For analyses of summer data, 

confounding of the O3 effect by PM is of concern as daily variations in O3 may be positively 

correlated to PM during the summer months. Huang et al. (2005) observed that when PM10 was 

included in the model, the O3 effect estimate, on average, remained positive and significant. As 

PM10 measurements were available only every 1 to 6 days, only single-day lags were examined. 

At a 0-day lag, O3 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 O3-only model and after 

adjustment for PM10, respectively. The slight sensitivity of the O3 health effects to the inclusion 

of PM10 in the model may indicate a true confounding effect. However, as only the days with 

PM10 data available were included in the analysis, the 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 estimates for associations between O3

and cardiovascular mortality for all-year and warm-season analyses. All studies, with the 

 3

 Other international 8-hr O3 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), showed positive associations between O3 and cardiovascular 

mortality (CD, p. 7-105). As with all-cause mortality, there appears to be heterogeneity in the 

effect estimates across studies. The cardiovascular mortality estimate from one meta-analysis 

(Bell et al., 2005) appears to be close to the mode of the effect 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. This study observed that the posterior 

mean estimate for cardiovascular causes (2.23% excess risk per 20 ppb increase in 24-hr avg O3 

from 25 estimates) was slightly larger than that for total mortality (1.75% excess risk from 41 

estimates). However, since cardiovascular deaths account for the largest fraction (over 40%) of 

total deaths, it is not surprising that the risk estimates for cardiovascular mortality are somewhat 

similar to those from all-cause mortality. Overall, the cardiovascular mortality risk estimates in 

the current literature show consistently positive associations with some heterogeneity (most 

estimates fall within the range of 1 to 8% per 40 ppb increase in 1-hr avg O3 (CD, p. 7-107). 

 Several studies observed that the risk estimates 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 apparent inconsistencies across 

studies may be due in part to the differences in model specifications, but they may also reflect 

the lower statistical power associated with the smaller daily counts of the respiratory category 

(usually accounting for less than 10% of total deaths) compared to the larger daily counts for the 

cardiovascular category (approximately 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 observed positive associations of ambient O3

concentrations with total nonaccidental and cardiopulmonary mortality. The CD finds that the 

results from U.S. multi-city time-series studies provide the strongest evidence to date for O3

effects on acute mortality. Recent meta-analyses also indicate positive risk estimates that are 

unlikely to be confounded by PM; however, future work is needed to better understand the 

influence of model specifications on the risk coefficient (CD, p. 7-175). A meta-analysis that 

examined specific causes of mortality found that the cardiovascular mortality risk estimates were 

higher than those for total mortality. For cardiovascular mortality, the CD (Figure 7-25, p. 7-

106) suggests that effect estimates are consistently 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 less consistent, possibly because of lower statistical power in this 

subcategory of mortality. The CD (p. 8-78) concludes that these findings are highly suggestive 

that short-term O3 exposure directly or indirectly contribute to non-accidental and 

cardiopulmonary-related mortality, but additional research is needed to more fully establish 

underlying mechanisms by which such effects occur. 
3-34 

3.3.2.2 Mortality and Long-term O3 Exposure 

 Little evidence was available in the last review on the potential for associations between 

mortality and long-term exposure to O3. In the Harvard Six City prospective cohort analysis, the 

authors report that mortality was not associated with long-term exposure to O3 (Dockery et al., 

1993). The authors note that the range of O3 concentrations across the six cities was small (19.7 

to 28.0 ppb in average 24-hr concentrations over the 7-year study period), which may have 

limited the power of the study to detect associations between mortality and O3 levels (CD, p. 7-

127). 

 As discussed in section 7.5.8 of the CD, in this review there are results available from 

three prospective cohort studies: the American Cancer Society (ACS) study, the Adventist 

Health and Smog (AHSMOG) study, and the U.S. Veterans Cohort study. In addition, a major 

reanalysis report includes evaluation of data from the Harvard Six City cohort study (Krewski et 

al., 2000). This reanalysis also includes additional evaluation of data from the initial ACS cohort 

study report that had only reported results of associations between mortality and long-term 

exposure to fine particles and sulfates (Pope et al., 1995).4

 In this reanalysis of data from the previous Harvard Six City prospective cohort study, 

the investigators replicated and validated the findings 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 O3 concentrations (8.3 ppb between the highest and lowest 

concentrations in the cities) and mortality was negative and nearly statistically significant 

(relative risk = 0.87, 95% CI: 0.76, 1.00). 

 The ACS study is based on health data from a large prospective cohort 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, for 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 associations with other air pollutants were also 

reported, and the authors report that no significant associations were found between O3 and all 

cause mortality (95% CI: 0.96-1.07). A significant association was reported for 

cardiopulmonary mortality (relative risk=1.08, 95% CI: 1.01, 1.16) (Krewski et al., 2000, p. 

174). For some specifications of O3 exposure in the ACS study, there was an effect in the warm 

quarter, as there was in the reanalysis 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 associations with an extended 

data base; the mortality records for the cohort had been updated to include 16 years of follow-up 

(compared with 8 years in the first report) and more recent air quality data were included in the 

analyses. Results are presented for full-year and summer season analyses, and show no evidence 

for a significant association between long-term exposure to O3 and mortality. As shown in 

Figure 7-27 of the CD, the effect estimates are not statistically significant for associations 

between long-term O3 exposure and all-cause, cardiopulmonary, and lung cancer mortality (CD, 

p. 7-128) in all year analyses. However, in the summer season, marginally significant 

associations were observed for cardiopulmonary mortality. 

 The Adventist Health and Smog (AHSMOG) cohort includes about 6,000 adults living in 

California. In two studies from this cohort, a significant association has been reported between 

long-term O3 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 O3

exposure and mortality from all causes 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 concerns about the plausibility of the reported 

association with lung cancer (CD, p. 7-130). 

 The U.S. Veterans Cohort study (Lipfert et al., 2000b, 2003) of approximately 50,000 

middle-aged males diagnosed with hypertension, reported some positive associations between 

mortality and peak O3 exposures (95th percentile level for several years of data). The study 

included numerous analyses using subsets of exposure and mortality follow-up periods which 

spanned the years 1960 to 1996. In the results of analyses using deaths and O3 exposure 

estimates concurrently across the study period, there were positive, statistically significant 

associations between peak O3 and mortality, with a 9.4% excess risk (95% CI: 0.4, 18.4) per 

mean 95% percentile O3 (CD, p. 7-129). 

 Thus, the results from all-year analyses in the Harvard Six Cities and ACS cohorts 

provide no evidence for associations between long-term O3 exposure and mortality, though the 

warm-season results in the reanalysis of the ACS cohort study suggest a potential association. 

Imprecise and inconclusive associations were reported in analyses for the AHSMOG cohort 

study. Significant associations between long-term O3 exposure and mortality were only reported 

for the Veterans cohort study; however, this study used an indicator of peak O3 concentrations 

and the cohort is also a rather specific subgroup of the U.S. population. Overall, the CD 

concludes that consistent associations have not been reported between long-term O3 exposure 

and all-cause, cardiopulmonary or lung cancer mortality (CD, p. 7-130). 
3-36 

3.3.3 Ozone Effects on UV-B Flux 

The CD (Chapter 10) provides a thorough analysis of the current understanding of the 

relationship between reducing tropospheric O3 concentrations and the potential impact these 

reductions might have on increasing UV-B surface fluxes and indirectly contributing to increased 

UV-B related health effects. It is clear that there are many factors that influence UV-B radiation 

penetration to the earth’s surface, including cloud cover, surface albedo, PM concentration and 

composition, and gas phase pollution. A risk assessment of UV-B related health effects would 

need to take into account human habits, such as outdoor activities, dress and skin care. However, 

little is known about the impact of these factors on individual 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 exposure, 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 producing vitamin D, suggesting that increased risks of human disease 

due to slight excess UV-B exposure may be offset by the benefits of enhanced vitamin D 

production. However, as with other impacts of UV-B on human health, this beneficial effect of 

UV-B radiation has not been studied in sufficient detail to allow for a credible health benefits or 

risk assessment. The CD (p. 10-38) concluded that the effects of changes in surface-level O3

concentrations on UV-induced health effects cannot be critically assessed given the significant 

uncertainties summarized above. 

3.3.4 Summary 

 The CD (Chapters 4-8) summarizes and assesses substantial new evidence which builds 

upon what was previously known about the health effects of O3. The new information supports 

previous findings that short-term O3 is associated with lung function decrements and respiratory 

symptoms, as well as numerous more subtle effects on the respiratory system such as 

morphological changes and altered host defense mechanisms. Short-term O3 exposure has also 

been associated with hospital admissions for respiratory causes in numerous new studies that 

further confirm the findings evaluated in the 1996 CD. The CD reports that warm-season studies 

show evidence for positive and robust associations between ambient O3 concentrations and 

respiratory hospital admissions, asthma ED visits, and respiratory symptoms and lung function 

effects in asthmatic children (CD, p. 7-175). 

 Some new studies have suggested associations between increased incidence of asthma or 

reduced lung function and long-term exposure to elevated ambient O3 levels. The findings of 

this small group of studies are inconsistent, however, and the CD concludes 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 O3 exposure and 

effects on the cardiovascular system, including changes in heart 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 potential effects of O3 on the cardiovascular 

system (CD, p. 8-77). 

 A major area where new information presented in the CD has significantly expanded our 

knowledge on health effects is evidence of an elevated risk of mortality associated with acute 

exposure to O3, especially in the summer or warm season when O3 levels are typically high. 

Results from recent large U.S. multicity time-series studies and meta-analyses provide the 

strongest evidence for associations between short-term O3 exposure and mortality (CD, p. 7-

175). The risk estimates shown are consistent across studies and robust to control for potential 

confounders. This overall body of evidence is highly suggestive that O3 directly or indirectly 

contributes to nonaccidental and cardiopulmonary-related mortality, but additional research is 

needed to more fully establish underlying mechanisms 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, dosimetric and controlled human exposure) and 

epidemiological studies, to make judgments about the extent to which causal inferences can be 

made about observed associations between health endpoints and exposure to O3. Section 8.4.4.3 

of the CD indicates that strength of the O3 effects (including the magnitude and precision of 

reported O3 effect estimates and their statistical significance), robustness of epidemiological 

associations (i.e., stability in the effect estimates after considering a number of factors), and 

consistency of effects associations (looking across results of multiple- and single-city studies 

conducted by different investigators in different places and times) are all important in forming 

judgments as to the likely causal significance of observed associations (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-recognized criteria, including: (1) the strength of reported associations, 

including the magnitude and precision of reported effect estimates and their statistical 

significance; (2) the robustness of reported associations, or stability in the effect estimates after 

considering factors such as alternative models and model specification, potential confounding by 

co-pollutants, and issues related to the consequences of exposure measurement error; and (3) the 

consistency of the effects associations as observed by looking across results of multiple- and 

single-city studies conducted by different investigators in different places and times (CD, p. 8-

40). Integrating more broadly across epidemiological and experimental evidence, the CD also 
3-38 

focuses on the coherence and plausibility of observed O3-related health effects 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 additional advice on some key issues in order to inform 

specifically the preparation of this draft Staff Paper specifically and the review of the O3

NAAQS in general. The issues related to assessment of epidemiological studies are addressed in 

this section and include the general issue of the utility of time-series epidemiological studies in 

assessing the risks from exposure to O3 and other criteria pollutants, as well as related issues 

about exposure measurement error in O3 mortality time-series studies and O3 as a surrogate for 

the broader mix of photochemical oxidant pollution in time-series studies. Implications of these 

issues for staff conclusions about the adequacy of the current O3 NAAQS and the identification 

of options for consideration will be considered in Chapter 6. 

 The following discussion summarizes 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 below in section 3.5. This section 

also addresses issues related to lag periods between O3 ambient exposure levels and health 

outcomes, the nature of O3-health effect concentration-response relationships, and the assessment 

of air pollutant mixtures containing O3 in time-series epidemiological studies. 

3.4.1 Strength of Associations 

 The strength of associations most directly refers to the 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 association 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 statistical power of the study (CDC, 2004). In general, 

when associations are strong in terms 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). With associations that yield small relative risk estimates it is 

especially important to consider potential confounding and other factors in assessing causality. 

Effect estimates between O3 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% increases per 40 ppb increase in 1-hr max O3 or 

equivalent, whereas associations for hospitalization range up to 50% increases per standardized 

O3 increment. The CD particularly notes that there are several multicity studies for associations 

between short-term O3 exposure and mortality or morbidity that, although small in size, have 
3-39 

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 measured by the studies such that many of the 

associations can be distinguished from the null hypothesis with statistical confidence. 

3.4.2 Robustness of Associations 

 Factors considered in assessing robustness include impact of exposure error, potential 

confounding by copollutants, and alternative models and model specifications, 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, concentrations measured at centrally-located 

ambient monitoring stations are generally used to represent a community’s exposure to ambient 

O3. For time-series studies and panel studies that use these ambient concentrations, the emphasis 

is on the temporal (e.g., daily or hourly) changes in ambient O3. 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 O3 and other pollutants. In both types of 

analyses, exposure error is an important consideration, as actual exposures to individuals in the 

population will vary across the community. 

In considering exposure error, it should be noted that total personal exposure can be 

partitioned into two types of sources, ambient and nonambient. As described in the CD, there 

are few sources of O3 exposure for most people other than ambient air; potential indoor sources 

of O3 include office equipment, air cleaners, and small electric motors (CD, p. 7-6). Sheppard 

(2005) notes that nonambient source exposures typically vary across individuals, but the 

community averages do not vary across communities. In addition, nonambient exposures are not 

likely to have strong temporal correlations. In contrast, ambient concentrations across 

individuals should be highly correlated, as they tend to vary over time similarly for everyone 

because of changes in source generation, weather, and season. The independence of ambient and 

non-ambient exposure sources has important implications. Sheppard et al. (2005) observes that 

when ambient and nonambient sources are independent, exposure variation due to nonambient 

source exposures behaves like Berkson measurement error and does not bias the effect estimates. 

Ozone concentrations measured at central ambient monitoring sites may explain, at least 

partially, the variance in individual exposures to ambient O3; however, this relationship is 

influenced by various factors related to building ventilation practices and personal behaviors. 

Further, the pattern of exposure misclassification error and the influence of confounders may 

differ across the outcomes of interest as well as in susceptible populations. As discussed in the 

CD Section 3.9, only a limited number of studies have examined the relationship between 

ambient O3 concentrations and personal exposures to ambient O3. One of the strongest 
3-40 

predictors of the relationship between ambient concentrations and personal exposures appears to 

be time spent outdoors. The strongest relationships were observed in outdoor workers (Brauer 

and Brook, 1995, 1997; O’Neill et al., 2003). For example, Brauer and Brook (1995, 1997) 

observed that in farmers who worked 6-14 hours outdoors each day, the personal to ambient O3

concentration ratio was 0.96, with a Spearman correlation coefficient of 0.64. Statistically 

significant correlations between ambient concentrations and personal exposures were also 

observed for children, who likely spend more time outdoors in the warm season (Linn et al., 

1996; Xue et al., 2005). 

There is some concern about the extent to which ambient concentrations are 

representative of personal O3 exposures of another particularly susceptible group of individuals, 

the debilitated elderly, and what impact that may have on mortality and hospitalization timeseries studies. Those who suffer from chronic cardiovascular or respiratory conditions may tend 

to protect themselves more from environmental threats by reducing their exposure to both O3 and 

its confounders, such as high temperature and PM, than those who are healthy. The correlation 

between ambient concentrations and personal exposure measurements in older adults (mean age 

75 years) has been examined by Sarnat et al. (2001, 2005). These studies by Sarnat et al. also 

included children and COPD patients, and only results for the combined populations are 

reported. The first study conducted 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, found statistically significant associations between ambient O3

concentrations and personal exposures to O3. The regression coefficient 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 the relationship between ambient concentrations and personal 

exposures. Eight of 29 subjects had personal-ambient O3 correlations greater than 0.8 during the 

summer. 

Collectively, these studies observed that the daily averaged personal O3 exposures from 

the population were well correlated with ambient O3 concentrations despite the substantial 

variability that existed among the personal measurements. Averaging likely removes the noise 

associated with other sources of variation. These studies provide supportive evidence that 

ambient O3 concentrations from central monitors may serve as valid surrogate measures for 

mean personal exposures experienced by the population, which is of most relevance for timeseries studies. A better understanding of the relationship between ambient concentrations and 

personal exposures, as well as of the other factors that affect relationship will improve the 

interpretation of concentration-population health response associations observed. 

 The CD discusses the potential influence of exposure error on epidemiologic study results 

in Section 7.1.3.1. Zeger et al. (2000) outlined the three components to exposure measurement 
3-41 

error: (1) the use of average population 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 concentrations (CD, p. 7-7). 

These components are expected to have different effects, with the first and third likely not 

causing bias in a particular direction (“nondifferential error”) but increasing 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). 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 measurements will estimate 

a health risk that is attenuated by that factor. Navidi et al. (1999) used data from a children’s 

cohort study to compare effect estimates from a simulated “true” exposure level to results of 

analyses from O3 exposures determined by several methods. The results indicated that the use of 

O3 exposures from personal sampling or microenvironmental approaches is associated with 

nondifferential error in O3 effect estimates, compared with effect estimates from “true” 

exposures. However, O3 exposures based on the use of ambient monitoring data overestimates 

the individual’s O3 exposure and thus generally results in O3 effect estimates that are biased 

downward (CD, p. 7-8). Similarly, Zidek (1997) observed that a statistical analysis must balance 

bias and imprecision (error variance). For example, in a reanalysis of a study by Burnett et al. 

(1994) on the acute respiratory effects of ambient air pollution, Zidek et al. (1998) reported that 

accounting for measurement, as well as making a few additional changes to the analysis, resulted 

in qualitatively similar conclusions, but the effects estimates were considerably larger in 

magnitude (CD, p. 7-8). 

A simulation study by Sheppard et al. (2005) also considered attenuation of the risk based 

on personal behavior, their microenvironment, 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 exposure that is independent of ambient concentration does not further bias the 

effect estimate. In other words, risk estimates were not further attenuated in time-series studies 

even when the correlations between personal exposures and ambient concentrations were weak. 

In addition to overestimation of exposure and the resulting underestimation of effects, the 

use of ambient O3 concentrations may obscure the presence of thresholds in epidemiologic 

studies (CD p. 7-9). Brauer et al. (2002) concluded that surrogate measures of exposure, such as 

those from centrally located ambient monitors, that were not highly correlated with personal 

exposures obscured the presence of thresholds in epidemiologic studies at the population level, 

even if a common threshold exists for individuals within the population. 

Existing epidemiologic models may not fully take into consideration all of the 

biologically relevant exposure history or reflect the complexities of all of the underlying 
3-42 

biological processes. As discussed in the CD, Section 3.9, using ambient concentrations to 

determine exposure generally overestimates true personal O3 exposures by approximately 2- to 

4-fold in available studies, resulting in attenuated risk estimates. The implication is that the 

effects being estimated occur at fairly low exposures and the potency of O3 is greater than these 

effects estimates indicate. As very few studies evaluating O3 health effects with personal O3

exposure measurements exist in the literature, effect estimates determined from ambient O3

concentrations must be evaluated and used with caution to assess the health risks of O3. Until 

more data on personal O3 exposure becomes available, the use of routinely monitored ambient 

O3 concentrations as a surrogate for personal exposures is not generally expected to change the 

principal conclusions from O3 epidemiologic studies. Therefore, population health risk estimates 

derived using ambient O3 levels from currently available observational studies, with appropriate 

caveats about personal exposure considerations, remain useful. 

The CD recommends caution in the quantitative use of effect estimates calculated using 

ambient O3 concentrations as they may lead to underestimation of the potency of O3. However, 

staff observes that the use of these risk estimates for comparing relative risk reductions between 

alternative ambient O3 standards considered in the risk assessment is less likely to suffer from 

this concern. In addition, as discussed in Chapter 5, staff 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 health 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; epidemiological analyses attempt to 

adjust or control for potential confounders. Copollutants (e.g., PM, CO, SO2 and NO2) can meet 

the criteria for potential confounding in O3-health associations if they are potential risk factors 

for the health effect under study and are correlated with O3. Effect modifiers include variables 

that may influence the health response to the pollutant exposure (e.g., co-pollutants, individual 

susceptibility, smoking or age). Both are important considerations 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, while the emphasis for effect 

modification is on identifying and assessing the effects for different modifiers. 

The CD observes that O3 is generally not highly correlated with other criteria pollutants 

(e.g., PM10, CO, SO2 and NO2), but may be more highly correlated with secondary fine particles, 

especially during the summer months (CD, p. 7-148). In addition, the correlation between O3

and other pollutants may vary across seasons, since O3 concentrations are generally higher in the 
3-43 

summer months. For example, positive associations are observed between O3 and pollutants 

such as fine particles during the warmer months, but negative correlations may be observed 

between O3 and these pollutants during the cooler months (CD, p. 7-17). Thus, the CD pays 

particular attention to the results of season-specific analyses and studies that assess effects of PM 

in potential confounding of O3-health relationships in its discussions in section 7.6.4. 

 Multipollutant models are commonly used to assess potential confounding in 

epidemiological studies. As discussed in the CD, the limitations to the use of multipollutant 

models include the difficulty in interpreting results where the copollutants are highly colinear, or 

where correlations between pollutants change by season (CD, p. 7-150). This is particularly the 

situation where O3 and a copollutant, such as sulfates, are formed under the same atmospheric 

condition; in such cases multipollutant models would produce unstable and possibly misleading 

results (CD, p. 7-152). 

 For mortality, the results from numerous multi-city and single-city studies are shown in 

Figure 7-22 of the CD. These results indicate that O3-mortality associations do not appear to be 

substantially changed in multipollutant models including PM10 or PM2.5 (CD, p. 7-101). 

Focusing on results of warm season analyses, Figure 7-23 of the CD shows effect estimates for 

O3-mortality associations that are fairly robust to adjustment for PM in multipollutant models 

(CD, p. 7-102). In general, based on results from several single- and multiple-city studies, and 

on recent meta-analyses, the CD (p. 7-103) concludes that “copollutants generally do not appear 

to substantially confound the association between O3 and mortality.” 

 Similarly, multipollutant models are presented for associations between short-term O3

exposures and respiratory hospitalization in Figure 7-12 of the CD; the CD concludes that 

copollutants generally do not confound the relationship between O3 and respiratory 

hospitalization (CD, p. 7-79 to 7-80). Multipollutant models were not used as commonly in 

studies of relationships between respiratory symptoms or lung function with O3, but the CD 

reports that results of available analyses indicate that such associations generally were robust to 

adjustment for PM2.5 (CD, p. 7-154). For various co-pollutant models, in a large multicity study 

of asthmatic children (Mortimer et al., 2002), the O3 effect was attenuated, but there was still a 

positive association. In Gent et al. (2003), effects of O3, but not PM2.5, remained statistically 

significant and even increased in magnitude in two-pollutant models (CD, p. 7-53). 

 Considering this body of studies, the CD concludes: “Multipollultant regression analyses 

indicated that O3 risk estimates, in general, were not sensitive to the inclusion of copollutants, 

including PM2.5 and sulfate. These results suggest that the effects of O3 on respiratory health 

outcomes appear to be robust and independent of the effects of other copollutants (CD, p. 7-

154).” We use the results 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) for 
3-44 

purposes of comparing results from different studies. However, we also include the use of multipollutant model results in presenting risk estimates, when available, to more completely 

characterize the quantitative health risks associated with ambient O3 levels.

3.4.2.3 Model Specification 

 The CD observes that one challenge of time-series epidemiological analysis is assessing 

the relationship between O3 and health outcomes while avoiding bias due to confounding by 

other time-varying factors, particularly seasonal trends and weather variables (CD, p. 7-14). 

These variables are of particular interest because O3 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 effects are associated with O3 or with seasonal or 

weather variables in statistical analyses. 

 Section 7.1.3.4 of the CD discusses statistical modeling approaches that have been used 

to adjust for time-varying factors, highlighting a series of analyses that were done in a Health 

Effects Institute-funded reanalysis of numerous time-series studies. While the focus of these 

reanalyses was on associations with PM, a number of investigators also examined the sensitivity 

of O3 coefficients to the extent of adjustment for temporal trends and weather factors. In 

addition, several recent studies, including U.S. multi-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 O3-mortality associations. As discussed in the CD (section 7.6.3.1), these 

studies generally report that associations reported with O3 are not substantially changed with 

alternative modeling strategies 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 O3 effect estimate. 

However, significant confounding can occur when strong seasonal cycles are present, suggesting 

that season-specific results are more generally robust than year-round results in such cases. The 

CD concludes that “seasonal dependence of O3-mortality effects complicates interpretation of O3

risk estimates calculated from year-round data without adequate adjustment of temporal trends” 

(CD, p. 7-99), and that more work is needed in this area to reduce the uncertainty involved in the 

epidemiologic interpretation of O3 effect estimates (CD, p. 7-141). 

 A number of epidemiological studies have conducted season-specific analyses, as 

discussed in section 7.6.3.2 of the CD. As observed above in section 3.3, such studies have 

generally reported stronger and more precise effect estimates for O3 associations in the warm 

season than in analyses conducted in the cool seasons or over the full year. For assessing 

relationships between O3 and health outcomes, the CD highlights several reasons to focus on 

warm season analyses: (1) the seasonal nature of O3 concentrations; (2) the relationship between 
3-45 

O3 formation and temperature; (3) correlations between other pollutants, particularly fine 

particles, and O3 variations across seasons in some areas; and (4) factors affecting exposure to 

ambient O3, such as air conditioning use, varies seasonally in most areas of the U.S.. We have 

therefore focused on epidemiological findings from warm season analyses, where available, for 

qualitative assessments and for the quantitative risk assessment discussed in Chapter 5. 

3.4.3 Consistency 

 Consistency refers to the persistent finding of an association between exposure and 

outcome in multiple studies of adequate power in different persons, places, circumstances and 

times (CDC, 2004). In considering results from multicity studies and single-city studies in 

different areas, the CD observes general consistency in effects of short-term O3 exposure on 

mortality, respiratory hospitalization 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 O3, as well as varying concentrations and composition of copollutants present in 

different regions. Thus, the CD concludes that “consideration of consistency or heterogeneity of 

effects is appropriately understood as an evaluation of the similarity or general concordance of 

results, rather than an expectation of finding quantitative 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 periods between the health outcome and O3 concentration (see 

CD, sections 7.1.3.3). The CD observes that the selection of an appropriate lag period can 

depend on the health outcome under study. For example, if cough is resulting from the irritant 

action of O3, that would be expected to occur with a short lag time; however, exacerbation of 

asthma through an inflammatory response might occur up to several days after initial exposure 

(CD, p. 7-12). For both mortality and respiratory hospital admissions, the CD reports that most 

significant associations between O3 and mortality were observed with O3measured on the same 

day or a 1-day lag period in studies using individual lag periods (CD, p. 7-14). In U.S. multi-city 

studies, larger effect estimate sizes were reported for the O3-mortality relationship with the 

distributed lag structure (CD, p. 7-88). Field studies of lung function or respiratory symptoms 

reported associations with O3 across a range of lag periods from exposure on the same day to 

exposures averaged over several days (CD, sections 7.2.3 and 7.2.4). Cardiovascular effects 

appeared to be associated with O3 at shorter lag periods; cardiovascular health outcomes such as 

changes in cardiac autonomic control were associated with O3 measured on the same day (CD, 

section 7.2.7.1). In addition, Peters et al. (2001) reported a positive but not statistically 
3-46 

significant association between myocardial infarction onset and O3 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 the pattern of results across the series of lag periods. If there is an 

apparent pattern of results across the different lags, then selecting the single-day lag with the 

largest effect from a series of positive associations is still likely to underestimate the overall 

effect size, since single-day lag effect estimates do not fully capture the risk that may be 

distributed over adjacent or other days (CD, p. 7-13). However, if the reported effect estimates 

vary substantially across lag periods, any result for a single day may well be biased (CD, p. 7-

14). If the effect of O3 on health outcomes persists over several days, distributed lag model 

results may provide more accurate effect estimates for quantitative assessment than an effect 

estimate for a single lag period (CD, p. 7-12). Conversely, if the underlying O3-health 

relationship is truly an acute effect, then a distributed lag model would likely result in a reduced 

effect estimate size that may underestimate 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 consideration of multi-day lag effects (CD, p. 7-14). For quantitative 

assessments, we conclude that it is appropriate to use results from lag period analyses 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 availability of results (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 patterns, the use of singleday lag results is not appropriate for inclusion in the quantitative assessment. 

3.4.5 Concentration-Response Relationships and Potential Thresholds 

 It has been recognized that it is reasonable to expect that there likely are biological 

thresholds for different health effects in individuals or groups of individuals with similar innate 

characteristics and health status. For O3 exposure, individual thresholds would presumably vary 

substantially from person to person due to individual differences in genetic susceptibility, preexisting disease conditions and possibly individual risk factors such as diet or exercise levels 

(and could even vary from one time to another for a given 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 unusually sensitive even down to 

very low concentrations (U.S. EPA, 2004, p. 9-43, 9-44). 

 Some studies have tested associations between O3 and health outcomes after removal of 

days with higher O3 levels from the data set; such analyses do not necessarily indicate the 

presence or absence of a threshold, but provide some information on whether the relationship is 
3-47 

found using only lower-concentration data. For example, using data from 95 U.S. cities, Bell et 

al. (2004) found that the effect estimate for an association between short-term O3 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 

O3 concentrations <20 ppb were excluded (CD, p. 8-43). Using data from 8 U.S. cities, 

Mortimer and colleagues (2002) also reported that associations between O3 and both lung 

function and respiratory symptoms remained statistically 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 studies are also summarized in section 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 the upper end of the concentration range are removed. 

 Other time-series epidemiological studies have used statistical modeling approaches to 

evaluate whether thresholds exist in associations between short-term O3 exposure and mortality. 

As discussed in section 7.6.5 of the CD, one European multi-city study included evaluation of 

the shape of the concentration-response curve, and observed no deviation from a linear function 

across the range of O3 measurements from the study (Gryparis et al., 2004; CD p. 7-154). 

Several single-city studies also observed a monotonic increase in associations between O3 and 

morbidity that suggest that no population threshold exists (CD, p. 7-159). 

 On the other hand, a study in Korea used several different modeling approaches and 

reported that a threshold model provided the best fit for the data. The results suggested a 

potential threshold level of about 45 ppb (1-hr maximum concentration; < 35 ppb, 8-hr avg) for 

an association between mortality and short-term O3 exposure during the summer 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 O3-mortality association might be 

underestimated in the non-threshold model. A threshold analysis recently reported by Bell et al. 

(2006) for 98 U.S. communities, including the same 95 communities in Bell et al. (2004), 

indicated that if a population threshold existed for mortality, it would likely fall below a 24-h 

average O3 concentration of 15 ppb (< 25 ppb, 8-hr avg). In addition, Burnett and colleagues 

(1997) plotted the relationships between air pollutant concentrations and both respiratory and 

cardiovascular hospitalization, and it appears in these results that the associations with O3 are 

found in the concentration range above about 30 ppb (1-hr maximum; < 25 ppb, 8-hr avg). 

 Vedal and colleagues (2003) reported a significant association between O3 and mortality 

in British Columbia where O3 concentrations were quite low (mean concentration of 27.3 ppb). 

The authors did not specifically test for threshold levels, but the fact that the association was 

found in an area with such low O3 concentrations suggests that any potential threshold level 

would be quite low in this data set. 
3-48 

 In summary, the CD finds that, taken together, the available evidence from clinical and 

epidemiological studies suggests that no clear conclusion can now be reached with regard to 

possible threshold levels for O3-related effects (CD, p. 8-44). We also recognize that the 

available epidemiological evidence neither supports nor refutes the existence of thresholds at the 

population level for effects such as increased hospital admissions and premature mortality. There 

are limitations in epidemiological studies that make discerning thresholds in populations 

difficult, including low data density in the lower concentration ranges, the possible influence of 

exposure measurement error, and interindividual differences in susceptibility to O3-related 

effects in populations. We recognize, however, the possibility that 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 epidemiological analyses. Based on 

the CD’s conclusions, we judge that there is insufficient evidence to support use of potential 

threshold levels in quantitative risk assessments and that it is appropriate to estimate risks within 

the range of air quality concentrations down to estimated policy-relevant background level. 

3.4.6 Health Effects of Pollutant Mixtures Containing O3

The potential for O3-related enhancements of PM formation, particle uptake, and 

exacerbation of PM-induced cardiovascular effects underscores the importance of considering 

contributions of O3 interactions with other often co-occurring air pollutants to health effects due 

to O3-containing pollutant mixes. Chapters 4, 5, and 6 of the CD provide a discussion of 

experimental studies that evaluate interactions of O3 with other co-occurring pollutants. Some 

examples of important pollutant mixture effects noted there are highlighted below. 

In Chapter 4, the CD noted some important interactive effects of coexposures to O3, and 

NO2 and SO2, two other common gaseous copollutants found in ambient air mixes. A study by 

Rigas et al. (1997) showed that continuous exposure of healthy human adults to SO2 or to NO2 

increased inhaled bolus O3 absorption, while continuous exposure to O3 alone decreased bolus 

absorption of O3. This suggests enhancement of O3 uptake by NO2 or SO2 coexposure in ambient 

air mixes. Another study by Jenkins et al. (1999) showed that asthmatics exhibited enhanced 

airway responsiveness to house dust mite following exposures to O3, NO2, and the combination 

of the two gases (CD, Chapter 6). Spirometric responses, however, were impaired only by O3

and O3+NO2 at higher concentrations. On the other hand, animal toxicology studies (CD, 

Chapter 5) that evaluated exposures to O3 in mixture with NO2, formaldehyde, and PM 

demonstrated additive, synergistic or antagonistic effects, depending on the exposure regimen 

and the specific health endpoints evaluated. 

Several studies have demonstrated the enhancement by O3 exposure of various respiratory 

responses of sensitive individuals to allergens. For example, Peden et al. (1995) showed O3-
3-49 

induced increased response to nasal allergen challenge among allergic asthmatic subjects, and 

Michelson et al. (1999) showed promotion by 0.4 ppm O3 exposure of inflammatory cell influx 

in response to nasal allergen challenge in asymptomatic dust-mite sensitive asthmatics. In 

addition, Jörres et al. (1996) demonstrated enhancement by 0.25 ppm O3 exposure of airway 

responsiveness in mildly allergic asthmatics that was increased in response to an individual’s 

historical allergen (grass and birch pollen, house dust mite, animal dander). These results were 

further extended by Holz et al. (2002) who showed that repeated daily exposure to 0.125 ppm O3

for 4 days exacerbated lung function decrements (e.g., decreased FEV1) in response to bronchial 

allergen challenges among subjects with preexisting allergic airway disease, with or without 

asthma (see Chapter 6 of the CD). This suggests that O3 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. Consistent with and supporting the above findings are animal toxicology 

studies reviewed in detail by Harkema and Wagner (2005), which indicate that (a) O3-induced 

epithelial and inflammatory responses in laboratory rodents are markedly enhanced by 

coexposure to inhaled biogenic substances (e.g., bacterial endotoxin or ovalbumin, an 

experimental aeroallergen) and (b) adverse airway effects of biogenic substances can be 

exacerbated by coexposure to O3. 

Also of much note is a newly emerging literature which indicates that O3 can modify the 

biological potency of certain types 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 O3 for 48 

hr increased the potency (compared to non-exposed or air-exposed diesel PM) to induce 

neutrophil influx, total protein, and 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 O3, suggesting that O3 reaction with organic components of the diesel 

PM were responsible for the observed increased diesel PM effects. 

Potential interaction of O3 with fine PM in aged rats was examined by Kleinman et al. 

(2000). In this study the effects of fine PM containing two common toxic constituents, 

ammonium bisulfate (ABS, 0.3 μm 70 μg/m3) and elemental carbon (C, 0.3 μm 50 μg/m3) and a 

mixture (ABS + C) with 0.2 ppm O3 was evaluated on aged rat lung structure and macrophage 

function. Exposures of O3, elemental carbon or ABS alone did not cause significant lung injury, 

lung tissue collagen content or respiratory burst activity. On the other hand, mixtures (ABS + C 

+ O3) caused significant lung injury as assessed by increased cell proliferation response in lung 

epithelial and interstitial cells, loss of lung tissue collagen and increase in respiratory burst and 

phagocytic activity. 

The majority of toxicological studies discussed in the CD evaluated effects of individual 

pollutants or simple mixtures of the constituents of urban smog mixtures, and these toxicology 
3-50 

studies may not fully explain epidemiologic findings that have increasingly shown ambient O3, 

other gaseous pollutants, and/or PM to be associated with various health effects at relatively low 

concentrations. In a recent report, Sexton et al. (2004) utilized “smog chambers”, i.e., 

environmental irradiation chambers to generate synthetic photochemical oxidants mixtures 

similar to urban smog, and studied the toxicity of such mixtures on the inflammatory response of 

A549 cells in an in vitro exposure system. In this preliminary study, the authors found the 

simulated urban photochemical oxidant mixture generated with the addition of O3 to have 

enhanced toxicity (as assessed by the expression of IL-8 mRNA). Additional toxicology studies 

using similar realistic air pollution smog mixtures in the future may provide more relevant 

biological understanding for the potential interactions that occur in the ambient air among 

various pollutants. 

The body of epidemiological studies discussed in this Staff Paper emphasizes the role of 

O3 acting autonomously, from a statistical sense, in association with a variety of adverse 

respiratory and cardiovascular effects. Despite a variety of plausible mechanisms, there exists a 

general consensus suggesting that O3, either directly or through initiation, interferes with basic 

cellular oxidation processes responsible for inflammation, reduced antioxidant capacity, 

atherosclerosis and other effects. Reasoning that O3 influences cellular chemistry through basic 

oxidative properties (as opposed to a unique chemical interaction), other reactive oxidizing 

species (ROS) in the atmosphere acting either independently or in combination with O3 may also 

contribute to a number of adverse respiratory and cardiovascular health effects. Consequently, 

the role of O3 should be considered more broadly as O3 behaves as a generator of numerous 

oxidizing species in the atmosphere. 

 All of the above types of interactive effects of O3 with other co-occurring gaseous and 

nongaseous viable and nonviable PM components of ambient air mixes argue for not only being 

concerned about direct effects of O3 acting alone, but also the need for viewing O3 as a surrogate 

indicator for air pollution mixes which may enhance risk of adverse effects due to O3 acting in 

combination with other pollutants. Viewed from this perspective, those epidemiologic findings 

of morbidity and mortality associations, with ambient O3 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 contained in section 8.4.3 and section 8.6 of the CD, 

which integrates epidemiological studies with mechanistic information from controlled human 

exposure studies and animal toxicological studies to draw conclusions regarding the coherence of 

evidence and biological plausibility of O3-related health effects. For its assessment, the CD’s 

discussion draws from epidemiological evidence on a range of relevant health endpoints (from 
3-51 

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 associations (CD, p. 8-45). 

3.5.1 Animal-to-Human Extrapolation Issues 

 Table 3-1 (Table 8-1, CD, p. 8-29) summarizes physiological and biochemical 

observations which represent the knowledge base available from studies in humans and animals 

that support conclusions drawn about biological alterations that cause acute O3-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 environmentally relevant exposure regimens. Although 

most of the acute O3-induced biological alterations are transient and attenuate over time, this 

does not mean that injury at the cellular and tissue level does not continue. Most inflammatory 

markers (e.g., PMN influx) attenuate after 5 days of exposure, but markers of cell damage (e.g., 

LDH enzyme activity) do not attenuate and continue to increase. The time-line for resolution of 

many of the physiological and biological parameters presented in Figure 3-2 (Figure 8-3, CD, p. 

8-30) differ for healthy human subjects and those with underlying cardiopulmonary diseases. 

The CD also notes that alterations in acute O3-induced cellular and molecular changes observed 

in human airway epithelium evolve over time, depicted in Figure 3-3 (Figure 8-4, CD, p. 8-31), 

and that the knowledge of this profile is important in assessing biological plausibility to integrate 

across evidence of various health endpoints. 

The similarities in physiological, biochemical and pathological 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 disease processes across species, 

especially on the acute O3-induced effects in the respiratory tracts of humans and various animal 

species, as depicted in CD Table 3-1 and Figures 3-2 and 3-3. The similarities observed in 

human and rat respiratory system effects (e.g., in measures of lung function, ventilatory 

response, host defense), attenuation, and at higher levels of cellular organization (e.g., 

neutrophilic inflammation, macrophage phagocytosis processes) lend support to animal-tohuman extrapolation. This is particularly important in collecting information that would not be 

possible to gather in human exposure or epidemiological studies but may corroborate data from 

both types of studies. 
Table 3-1. Acute O3-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 FEV1

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: Impairment in arterial O2 transfer

Ventilation-perfusion mismatch

(suggesting potential arterial

vasoconstriction)

8 rate pressure product5

8 myocardial work5

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 O3

 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 vitro studies using cells recovered

 from BALF.

3

 Responses were observed in animal toxicology studies with exposure for a duration of 2 to 72 h with O3

 concentration in the range of 0.1 to 2.0 ppm.

4

 Various species (mice, rat, guinea pigs and rabbit) and strains. 5

 In hypertensive subjects.

3-52 
3-53

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) O3 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)3-4.Acute (1-8 h) O3 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 combination 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 endpoints with sufficient accuracy to be useful in evaluating the 

potential for human health effects. For example, the amount of protein in lavage fluid shows a 

striking relationship when interspecies dosimetric adjustments are applied to the individual 

species and exposure studies. One study (Hatch et al., 1994) of inflammatory markers suggests 

that a 2 ppm O3 exposure in sedentary rats approximates a 0.4 ppm exposure in exercising 

humans (i.e., if one considers the dosimetry, the sensitivities of rats and humans are consistent). 

This supports the use of some animal data collected at higher O3 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) reporting lesions in animals caused by long-term O3

exposures that may analogously occur in humans with long-term (months, years) exposure to 

relatively high levels of O3. However, specific exposure patterns of O3 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 effects that have been associated with short-term exposure to 

O3 include such health endpoints as decrements in lung function, increased airway 

responsiveness, airway inflammation, epithelial injury, immune system effects, ED visits for 

respiratory diseases, and hospitalization due to respiratory illness 

 Recent epidemiological studies have supported evidence available in the previous O3

NAAQS review on associations between ambient O3 exposure and decline in lung function for 

children. Earlier observations that children and asthmatic individuals are particularly susceptible 

to ambient O3 are supported by a meta-analysis (Kinney et al., 1996) of summer camp studies. 

The CD (p. 8-34) concludes that exposure to ambient O3 has a significant effect on lung function 

and is associated with increased respiratory symptoms and medication use, particularly in 

asthmatics. 

 Short-term exposure to O3 has also been associated with more severe morbidity 

endpoints, such as ED visits and hospital admissions for respiratory cases, including specific 

respiratory illness (e.g., asthma) (CD, sections 7.3.2 and 7.3.3). In addition, a few 

epidemiological studies have reported positive associations between short-term O3 exposure and 

respiratory mortality, though the associations are not generally statistically significant (CD, p. 7-

108). 

Considering the evidence from epidemiological studies, the results described above 

provide evidence for coherence in O3-related effects on the respiratory system. Effect estimates 

from U.S. and Canadian studies are shown in Figure 3-4, where it can be seen that 
Respirat

1. Moolgav2. Ito, 200(a=1986-1

3. Vedal e4. Villeneu5. Ostro et 

Respiratory 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 Connecticut

Emergency Department Visits:1. Peel et al., 2005 Atlanta2. Wilson et al., 2005 Portland NH3. Wilson et al., 2005 Manchester NH 4. 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 Montreal 7. 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 Atlanta 

Hospital 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 Montreal 

10. Burnett et al., 1997 16 Canadian cities11. Luginaah et al., 2003 Windsor(a=males; b=females)12. Thurston et al., 1992 Buffalo 13. Thurston et al., 1994 Toronto14. Schwartz et al., 1996 Spokane 15. Burnett et al., 1999 Toronto 16. 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 Detroit

Figure 3-4. Effect estimates (with 95% confidence intervals) for ass

between short-term ozone exposure and respiratory health outcome

Effect estimates expressed as odds ratios for associations with respiratory symptoms and % increasstandardized increments: 20 ppb for 24-hr O3, 30 ppb for 8-hr O3, and 40 ppb for 1-hr O3, presented in 

statistical power from left to right in each category. Dotted line (blue) indicates all year analyses; solwarm season results. LRS=lower respiratory symptoms; COPD=chronic obstructive pulmonary disea

Respiratory Symptoms (Odds Ratios)

0.001.002.00

3.004.005.00

1

2 3

5

(40)

8

7

8

2 3

4a

4b5 5 9 8 8

6

Asthma

symptoms

Wheeze

Shortness

of breath

Medication

use

7

-60-40-20

0

20

40

6080

1

5a

4

2a

COPD

Pneumonia

Respiratory

Asthma Respiratory Asthma

Respiratory Infection

COPD

Pneum

RIn

Respiratory Emergency Department Visits Respiratory Hospital Admissions 

1

1

1 1 3

2

3

2

6

9

5b

5c

7

10

11b

8

13

12

11

1 98

2b

4b

4a

3

7

6

5

6

11a

10

20

19

13

15

14

12 12 15

21

17

18

16

16

21

5 5

% Increase in Risk

Cough

LRS

3-56
3-57 

mostly positive associations have been reported with respiratory effects ranging from respiratory 

symptoms, such as cough or wheeze, to hospitalization for various respiratory diseases, and there 

is suggestive evidence for associations with respiratory mortality. Many of the reported 

associations are statistically significant. 

 Considering also evidence from toxicological, chamber, and field studies, the CD (section 

8.6) discusses biological plausibility and coherence of evidence for acute O3-induced respiratory 

health effects. Inhalation of O3 for several hours while subjects are physically active can elicit 

both acute adverse pathophysiological changes and subjective respiratory tract symptoms (CD, 

section 8.4.2). Acute pulmonary responses observed in healthy humans exposed to O3 at ambient 

concentrations include: decreased inspiratory capacity; mild bronchoconstriction; rapid, shallow 

breathing during exercise; subjective symptoms of tracheobronchial airway irritation, including 

cough and pain on deep inspiration; decreases in measures of lung function (e.g., FVC and 

FEV1); and increased airway resistance (SRaw). The severity of symptoms and magnitude of 

response depends on inhaled dose, individual O3 sensitivity, and the degree of attenuation or 

enhancement of response resulting from previous O3 exposures. Lung function studies of several 

animal species acutely exposed to relatively low O3 levels (0.25 to 0.4 ppm) show responses 

similar to those observed in humans, including increased breathing 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 O3

exposures is similar to those observed in humans. 

Physiological and biochemical alterations investigated in controlled human exposure and 

animal toxicology studies tend to support certain hypotheses of underlying pathological 

mechanisms which lead to the development of respiratory-related effects reported in 

epidemiology studies (e.g., increased hospitalization and medication use). Some of these are: 

(a) decrements in lung function, (b) bronchoconstriction, (c) increased airway responsiveness, (d) 

airway inflammation, (e) epithelial injury, (f) immune system activation, (g) host defense 

impairment, and sensitivity of individuals, 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 depicted in Figures 3-2 and 3-3), 

illustrate the inherent difficulty of interpreting the biological plausibility of O3-induced 

cardiopulmonary health effects (CD, p. 8-48). 

The interaction of O3 with airway epithelial cell membranes and epithelial lining fluid 

(ELF) to form lipid ozonation 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, airway epithelial damage and increased epithelial damage and 

increased alveolar permeability to vascular fluids. Repeated respiratory inflammation can lead to 
3-58 

a chronic inflammatory state with altered lung structure and lung function and may lead to 

chronic respiratory diseases such as fibrosis and emphysema (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 O3 are well documented, and lung injury can become 

apparent within 3 hr after exposure in humans. Ozone-induced lung injury and subsequent 

disruption of the airway epithelial barrier has been implicated in increased mucociliary clearance 

of particles in human subjects. 

Taken together, the CD concludes that the evidence from experimental human and animal 

toxicology studies indicates that acute O3 exposure is causally associated with respiratory system 

effects, including O3-induced pulmonary function decrements, respiratory symptoms, lung 

inflammation, and increased lung permeability, airway hyperresponsiveness, increased uptake of 

nonviable and viable particles, and consequent increased susceptibility to PM-related toxic 

effects and respiratory infections (CD, p. 8-48). 

3.5.3 Coherence and Plausibility of Effects on the Cardiovascular System 

There is very limited experimental evidence of animals and humans that has evaluated 

possible mechanisms or physiological pathways by which acute O3 exposures may induce 

cardiovascular system effects. Ozone induces lung injury, inflammation, 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, the generation of lipid ozonation 

products and reactive oxygen species in lung tissues can influence pulmonary hemodynamics, 

and ultimately the cardiovascular system. 

Other potential mechanisms by which O3 exposure may be associated with cardiovascular 

disease outcomes have been described. Laboratory animals exposed to relatively high O3

concentrations (≥ 0.5 ppm) demonstrate tissue edema in the heart and lungs. Ozone-induced 

changes in heart rate, edema of heart tissue, and increased tissue and serum levels of ANF found 

with 8-h 0.5 ppm O3 exposure in animal toxicology studies (Vesely et al., 1994a,b,c) also raise 

the possibility of potential cardiovascular effects of acute ambient O3 exposures. 

Animal toxicology studies have found both transient and persistent ventilatory responses 

with and without progressive decreases in heart rate (Arito et al., 1997). Observations of O3-

induced vasoconstriction in a controlled human exposure study by Brook et al. (2002) suggests 

another possible mechanism for O3-related exacerbations of preexisting cardiovascular disease. 

One controlled human study (Gong et al., 1998) evaluated potential cardiovascular health effects 

of O3 exposure. The overall results did not indicate acute cardiovascular effects of O3 in either 

the hypertensive or control subjects. The authors observed an increase in rate-pressure product 

and heart rate, a decrement for FEV1, and a >10 mm Hg increase in the alveolar/arterial pressure 
3-59 

difference for O2 following O3 exposure. The mechanism for the decrease in arterial oxygen (O2) 

tension study could be due to an O3-induced ventilation-perfusion mismatch. Foster et al. (1993) 

demonstrated that even in relatively young healthy adults, O3 exposure can cause ventilation to 

shift away from the well-perfused basal lung. This effect of O3 on ventilation distribution may 

persist beyond 24-hr post-exposure (Foster et al., 1997). These findings suggest that O3may 

exert cardiovascular effects indirectly by impairing alveolar-arterial O2 transfer and potentially 

reducing O2 supply to the myocardium. Ozone exposure may increase 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 epidemiological studies have 

reported associations between short-term O3 exposure and effects on the cardiovascular system. 

Among these studies, three were population-based and involved relatively large cohorts. Two 

studies, the ARIC (Liao at al., 2004) and the NAS (Parks et al., 2005) evaluated associations 

between O3 and HRV. The other study, MONICA (Ruidavets et al., 2005) evaluated the 

association between O3 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 O3 exposure and the cardiovascular endpoints studies. 

In other recent studies on incidence of myocardial infarction and some more subtle 

cardiovascular health endpoints, such as changes in heart rate variability or cardiac arrhythmia, 

some but not all studies reported associations with short-term exposure to O3 (CD, section 

7.2.7.1). From these studies, the CD concludes that 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 O3 exposure and 

cardiovascular hospital admissions. As shown in Figure 7-13 and discussed in section 7.3.4 of 

the CD, many reported negative or inconsistent associations, whereas other studies, especially 

those that examined the relationship when O3 exposures were higher, have found positive and 

robust associations between O3 and cardiovascular hospital admissions. The CD finds that the 

overall evidence from these studies remains inconclusive regarding the effect of O3 on 

cardiovascular hospitalizations (CD, p. 7-83). 

 The CD notes that the suggestive positive epidemiologic findings of O3 exposure on 

cardiac autonomic control, including effects on HRV, ventricular arrhythmias and MI, and 

reported associations between O3 exposure and cardiovascular hospitalizations in the warm 

season gain credibility and scientific support from the results of experimental animal toxicology 

and human clinical studies, which are indicative of plausible pathways by which O3 may exert 

cardiovascular effects (CD, Section 8.6.1). 
3-60 

3.5.4 Coherence and Plausibility of Effects Related to Long-Term O3 Exposure 

 Human chamber studies can not evaluate effects of long-term exposures to O3; there is 

some evidence available from toxicological studies. While early animal toxicology studies of 

long-term O3 exposures were conducted using continuous exposures, more recent studies have 

focused on exposures which mimic diurnal and seasonal patterns and more realistic O3 exposure 

levels (CD, p. 8-50). Studies of monkeys that compared these two exposure scenarios found 

increased airway pathology only with the latter design. Persistent and irreversible effects 

reported in chronic animal toxicology studies suggest that additional complementary human data 

are needed from epidemiologic studies (CD, p. 8-50). 

A long-term study of infant rhesus monkeys exposed to simulated seasonal O3 (0.5 ppm , 

8 hr/day for 5 days every 14 days for 11 episodes) reported remodeling of the distal airways, 

abnormalities in tracheal basement membrane, accumulation of eosinophils in conducting 

airways, and decrements in airway innervation. Another long-term exposure study of monkeys 

exposed to 0.61 ppm O3 for a year and studies of rats exposed for 20 months (0.5-1.0 ppm O3 for 

6 hr/day) reported increased deposition of collagen and thickening of the CAR, suggestive of 

irreversible long-term O3 impacts on the lungs. Although some earlier seasonal exposure studies 

of rats reported small, but significant, decrements in lung function consistent with focal 

fibrogenesis in the proximal alveolar region, other chronic exposure studies with exposures of 

0.5 to 1.0 ppm O3 report epithelial hyperplasia that disappears in a few days. 

At this time, there is limited evidence from human studies for long-term O3-induced 

effects on lung function. As discussed 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 O3 exposure. The CD observes that the inconsistency in findings may be due to a lack 

of precise exposure information, the possibility of selection bias, and the difficulty of controlling 

for confounders (CD, p. 8-50). Several new longitudinal epidemiology studies have evaluated 

associations between long-term O3 exposures and morbidity and mortality and suggest that these 

long-term exposures may be related to changes in lung function in children; however, little 

evidence is available to support a relationship between chronic O3 exposure and mortality or lung 

cancer incidence (CD, p. 8-50). 

 The CD (p. 8-51) concludes that evidence from animal toxicology studies strongly 

suggests that chronic O3 exposure is capable of damaging the distal airways and proximal alveoli, 

resulting in lung tissue remodeling leading to apparent irreversible changes. Such structural 

changes and compromised pulmonary function caused by persistent inflammation may 

exacerbate the progression and development of chronic lung disease. Together 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 O3
3-61 

and reduced lung function development in children which have been observed in epidemiologic 

studies (CD, p. 8-51). 

3.5.5 Coherence and Plausibility of Short-Term Mortality-Related Health 

Endpoints 

 An extensive epidemiological literature on air pollution related mortality risk estimates 

from the U.S., Canada, and Europe is discussed in the CD (sections 7.4 and 8.6.3). These singleand multi-city mortality studies coupled with meta-analyses generally indicate associations 

between acute O3 exposure and elevated risk for all-cause mortality, even after adjustment for the 

influence of season and PM. Several single-city studies that specifically evaluated the 

relationship between O3 exposure and cardiopulmonary mortality also reported results suggestive 

of a positive association (CD, p. 8-51). These mortality studies suggest a pattern of effects for 

causality that have biologically plausible explanations, but our knowledge regarding potential 

underlying mechanisms is very limited at this time and requires further research. Most of the 

physiological and biochemical parameters investigated in human and animal studies suggest that 

O3-induced biochemical effects are relatively transient and attenuate over time. The CD (p. 8-

52) hypothesizes a generic pathway of O3-induced lung damage, potentially involving oxidative 

lung damage with subsequent inflammation and/or decline in lung function leading to respiratory 

distress in some sensitive population groups (e.g., asthmatics), or other plausible pathways noted 

below that may lead to O3-related contributions to cardiovascular effects that ultimately increase 

risk of mortality. 

 The third National Health and Nutrition Examination Follow-up data analysis indicates 

that about 20% of the adult population has reduced FEV1 values, suggesting impaired lung 

function in some portion of the population. Most of these individuals have COPD, asthma or 

fibrotic lung disease (Manino et al., 2003), which are associated with persistent low-grade 

inflammation. Furthermore, patients with COPD are at increased risk for cardiovascular disease. 

Also, lung disease with underlying inflammation may be linked to low-grade systemic 

inflammation associated with atherosclerosis, independent of cigarette smoking (CD, p. 8-52). 

Lung function decrements in persons with cardiopulmonary disease have been associated with 

inflammatory markers, such as C-reactive protein (CRP) in the blood. At a population level it 

has been found that individuals with the lowest FEV1 values have the highest levels of CRP, and 

those with the highest FEV1 values have the lowest CRP levels (Manino et al., 2003; Sin and 

Man, 2003). This complex series of physiological and biochemical reactions following O3

exposure may tilt the biological homeostasis mechanisms 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 O3-related increases in cardiovascular 

mortality observed in some epidemiological studies. These include the direct effect of O3 on 

increasing PAF in lung tissue that can then enter the general circulation and possibly contribute 

to increased risk of blood clot formation and the consequent increased risk of MI, 

cerebrovascular events (stroke), or associated cardiovascular-related mortality. Ozone reactions 

with cholesterol in lung surfactant to form epoxides and oxysterols that are cytotoxic to lung and 

heart muscles and that contribute to atherosclerotic plaque formation 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 heart rate, and edema of heart tissue. A few new 

field and panel studies of human adults have reported associations between ambient O3

concentrations and changes in cardiac autonomic control (e.g., HRV, ventricular arrhythmias, 

and MI). These represent plausible pathways that may lead to O3-related contributions to 

cardiovascular effects that ultimately increase the risk of mortality. 

In addition, O3-induced increases in lung permeability allow more ready entry for inhaled 

PM into the blood stream, and O3 exposure may increase the risk of PM-related cardiovascular 

effects. Furthermore, increased ambient O3 levels contribute to ultrafine PM formation in the 

ambient air and indoor environments. Thus, the contributions of elevated ambient O3

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 O3 (CD, p. 8-53). 

3.6 OZONE-RELATED IMPACTS ON PUBLIC HEALTH 

 The following discussion draws from section 8.7 of the CD to characterize factors which 

modify responsiveness to O3, subpopulations potentially at risk for O3-related health effects, and 

potential public health impacts associated with exposure to ambient O3. Providing appropriate 

protection of public health requires 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 effect but also on the population 

group being affected. While some changes in healthy individuals would not be considered 

adverse, similar changes in susceptible individuals would be seen as adverse. In order to 

estimate the potential public health impact, it is important to consider both the susceptible 

subpopulations for O3 exposure and the definition of adversity for O3 health effects. 
3-63 

3.6.1 Factors that Modify Responsiveness to Ozone 

 There are numerous factors that can modify individual responsiveness to O3. These 

include: influence of physical activity; age; gender and hormonal influences; racial, ethnic and 

socioeconomic status (SES) factors; 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 minute ventilation 

and will thus increase the dose of O3 inhaled (CD, section 6.5.4). Increased physical activity 

results in deeper penetration of O3 into more distal regions of the lungs, which are more sensitive 

to acute O3 response and injury. This will result in greater lung function decrements for acute 

exposures of individuals during increased physical activity. Research has shown that respiratory 

effects are observed at lower O3 concentrations if the level of exertion is increased and/or 

duration of exposure and exertion are extended. Predicted O3-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 investigating the influence of age have used lung function decrements 

and symptoms as measures of response. For healthy adults, lung function and symptom 

responses to O3 decline as age increases. The rate of decline in O3 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 large data set, a 5.4% decrement 

in FEV1 was estimated for 20 year old individuals exposed to 0.12 ppm O3, whereas similar 

exposure of 35 year old individuals were estimated to have a 2.6% decrement. While healthy 

children tend not to report respiratory symptoms when exposed to low levels of O3, for subjects 

18 to 36 years old symptom responses induced by O3 tend to decrease with increasing age 

(McDonnell et al., 1999). 

 Limited evidence of gender differences in response to O3 exposure has suggested that 

females may be predisposed to a greater susceptibility to O3. Lower plasma and NL fluid levels 

of the most prevalent antioxidant, uric acid, in females relative to males may be a contributing 

factor (Housley et al., 1996). Consequently, reduced removal of O3 in the upper airways may 

promote deeper penetration. However, most of the evidence on gender differences appears to be 

equivocal, with one study (Hazucha et al., 2003) suggesting that physiological responses of 

young healthy males and females may be comparable (CD, section 6.5.2). 

 A few studies have suggested that ethnic minorities might be more responsive to O3 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 O3. The 

limited data available, which have investigated the influence of race, ethnic or other related 

factors on responsiveness to O3, prevent drawing any clear conclusions at this time. 
3-64 

 Few human studies have examined the potential influence of environmental factors such 

as the sensitivity of individuals who voluntarily smoke tobacco (i.e., smokers) and the effect of 

high temperatures. New controlled human exposure studies have confirmed that smokers are 

less responsive to O3 than nonsmokers; however, time course of development and recovery of 

these effects, as well as reproducibility, was not different from nonsmokers (CD, section 6.5.5). 

Influence of ambient temperature on pulmonary effects induced by O3 has been studied very 

little, but additive effects of heat and O3 exposure have been reported. 

 Antioxidants, which scavenge free radicals and limit lipid peroxidation in the ELF, are 

the first line of defense against oxidative stress. Ozone exposure leads to absorption of O3 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 O3 responsiveness (CD, 

section 6.5.6). Controlled studies of dietary antioxidant supplements have shown some 

protective effects on lung function decrements but not on symptoms and airway inflammatory 

responses. Dietary antioxidant supplements have provided some protection to asthmatics by 

attenuating post-exposure airway hyperresponsiveness. Animal studies 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 O3 have been discussed in the CD, in the sections on clinical studies in Chapter 6, 

epidemiological studies in Chapter 7, and in the integrated assessment in Chapter 8; this section 

will draw on all of these. The characteristics that likely increase susceptibility to O3 are based 

on: (1) activity patterns; (2) lung disease; (3) age; and (4) biological responsiveness to O3. 

Other groups that might have enhanced sensitivity to O3, but for which there is currently very 

little evidence, include: people with heart disease; groups based on race, gender and 

socioeconomic status; and those with nutritional deficiencies. 

3.6.2.1 Active People 

A large group of individuals at risk from O3 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 O3 concentrations tend to be higher. This 

conclusion is based on a large number of controlled-exposure human studies and several 

epidemiologic field/panel studies which have been conducted with healthy children and adults 

and those with preexisting respiratory diseases (CD, sections 6.2 and 6.3). The controlled 

human exposure studies show a clear O3 exposure-response relationship with increasing 

spirometric and symptomatic response as exercise level increases. Furthermore, O3-induced 

response increases as time of exposure increases. Studies of outdoor workers and others who 
3-65 

participate in outdoor activities indicate that extended exposures to O3 at elevated exertion levels 

can produce marked effects on lung function. 

The effects of O3 on the respiratory health of outdoor workers and others who participate 

in outdoor activities have been investigated in several recent epidemiologic studies. These 

individuals may experience increased vulnerability for O3 health effects, because they are 

typically exposed to high doses of O3 as they spend long hours outdoors often at elevated 

exertion levels. In a group of berry pickers in Fraser Valley, Canada, decrements in lung 

function (~5% decrease in FEV1 per 40 ppb increase in 1-hr max O3) were associated with acute 

exposure to relatively low concentrations of O3 (Brauer et al., 1996). The mean ambient 1-hr 

max O3 was 40.3 ppb (SD 15.2) over the study period of June to August 1993. The berry pickers 

worked outdoors for an average of 11 hr at elevated heart rates (on average, 36% higher than 

resting levels). These results indicate that extended exposures to O3 at elevated exertion levels 

can produce marked effects on lung function among outdoor workers. 

Höppe et al. (1995) examined forestry workers for O3-related changes in pulmonary 

function in Munich, Germany. Ventilation rates, estimated from their average activity levels, 

were elevated. When comparisons were made between high O3 days (mean 1⁄2-hr max O3 of 64 

ppb) and low O3 days (mean 1⁄2-hr max O3 of 32 ppb), 59% of the forestry workers experienced a 

notable decrement in lung function (i.e., at least a 20% increase in specific airway resistance or 

at least a 10% decrease in FEV1, FVC, or PEF) on high O3 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 O3 levels and decrements in FEV1 was observed overall, 

a smaller percentage of the athletes (14%) experienced a notable decrement in lung function on 

high O3 days compared to the forestry workers; and 19% of the athletes actually showed an 

improvement. 

A large field study by Korrick et al. (1998) examined the effects of multi-hour O3

exposures (on average, 8 hr) on adults hiking outdoors on Mount Washington, in NH. The mean 

of the hourly O3 concentrations during the hike was 40 ppb (range 21-74). After the hike, all 

subjects combined experienced a relatively small mean decline in FEV1 (1.5% decrease per 30 

ppb increase in mean hourly O3 concentrations) during the hike. Ozone-related changes in lung 

function parameters were estimated. Stratifying the data by hiking duration indicated that 

individuals who hiked 8 to 12 hr experienced a 2-fold greater decline in FEV1 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; Higgins et al., 1990; Raizenne et al., 1987, 1989; Spektor et al., 1988, 
3-66 

1991), which also observed strong associations between acute O3 exposure and decrements in 

lung function among children who spent long hours 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 followed for up to 5 years to identify new-onset asthma 

cases associated with higher long-term ambient O3 concentrations (McConnell et al., 2002). 

Communities were stratified by pollution levels, with six high-O3 communities (mean 1-hr max 

O3 of 75.4 ppb [SD 6.8] over four years) and six low-O3 communities (mean 50.1 ppb 

[SD 11.0]). In the combined analysis using all children, asthma risk was not found to be higher 

for residents of the six high-O3 communities versus those from the six low-O3 communities. 

However, within the high-O3 communities, asthma risk was more than 3 times greater for 

children who played three or more sports versus those who played no sports, an association not 

observed in the low-O3 communities. Therefore, among children repeatedly exposed to higher 

O3 levels, increased exertion outdoors (and resulting increased O3 dose) was associated with 

excess asthma risk. 

These field studies with subjects 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 O3 exposure in subjects performing continuous or 

intermittent exercise for variable periods of time. Significant O3-induced respiratory responses 

have been observed in clinical studies of exercising individuals. The epidemiologic studies 

discussed above also indicate that prolonged exposure periods, combined with elevated levels of 

exertion or exercise, may magnify O3 effects on lung function. Thus, outdoor workers and others 

who participate in higher exertion activities outdoors during the time of day when high peak O3

concentrations occur appear to be particularly vulnerable to O3 effects on respiratory health. 

Although these studies show a wide variability of response and sensitivity among subjects and 

the factors contributing to this variability continue to be incompletely 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 range of other highly reactive 

photochemical oxidants coexisting with O3 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 O3 exposure. Altered physiological, morphological and biochemical states typical of 

respiratory diseases like asthma, COPD and chronic bronchitis may render people sensitive to 

additional oxidative burden induced by O3 exposure. The new results from controlled exposure 

and epidemiologic studies continue to indicate that asthmatics are a sensitive subpopulation for 

O3 health effects. 
3-67 

A number of epidemiological studies have been conducted using asthmatic study 

populations. The majority of epidemiological panel studies that evaluated respiratory symptoms 

and medication use related to O3 exposures focused on children. These studies suggest that O3

exposure may be associated with increased respiratory symptoms and medication use in children 

with asthma. Other reported effects include respiratory symptoms, 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 O3 

exposure may be associated with increased respiratory symptoms and medication use in children 

with asthma. With regard to ambient O3 levels and increased hospital admissions and ED visits 

for asthma and other respiratory causes, strong and consistent evidence establishes a correlation 

between O3 exposure and increased exacerbations of preexisting respiratory disease for 1-hr 

maximum O3 concentrations <0.12 ppm. Several hospital admission and ED visit studies in the 

U.S. (Peel et al., 2005), Canada (Burnett et al., 1997a; Anderson et al., 1997), and Europe 

(Anderson et al., 1997) have reported positive associations between increase in O3 and increased 

risk of ED visits and hospital admissions, especially during the warm season. 

Several clinical studies reviewed in the 1996 CD on atopic and asthmatic subjects had 

suggested but not clearly demonstrated enhanced responsiveness to acute O3 exposure compared 

to healthy subjects. The majority of the newer studies reviewed in Chapter 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 neutrophils, protein, and IL-8 were found to be significantly 

higher in the BAL fluid from asthmatics compared to healthy subjects, suggesting mechanisms 

for the increased sensitivity of asthmatics. Similarly, subjects with allergic asthma exhibited 

increased airway responsiveness to inhaled allergens upon acute O3 exposure. Asthmatics 

present a differential response profile for cellular, molecular, and biochemical parameters (CD, 

Figure 8-1) that are altered in response to acute O3 exposure. Increases in O3-induced 

nonspecific airway responsiveness incidence and 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 cells in the bronchi, narrowing the lumen and decreasing the 

airflow. In asthmatics, these mediators also cause accumulation of eosinophils, followed by 

production of mucus and a late-phase bronchial constriction and reduced airflow. Holz et al. 

(2002) reported an early phase response in subjects with rhinitis after a consecutive 4-day 

exposure to 0.125 ppm O3 that resulted in a clinically relevant (>20%) decrease in FEV1. 

Allergen challenge in mild asthmatics 24 hr before exposure to 0.27 ppm O3 for 2 hr resulted in 
3-68 

significantly increased eosinophil counts in samples of respiratory tract lining fluid, obtained by 

sputum induction, compared to results in healthy subjects (Vagaggini et al., 2002). Epithelial 

cells from mucosal biopsies of allergic asthmatics indicated significant increases in the 

expression of IL-5, IL-8 and GM-CSF, suggesting increased neutrophilic inflammation 

compared to healthy subjects (Bosson et al., 2003). 

Several human exposure studies have shown differences between asthmatics and healthy 

human subjects with regard to PMN influx in BAL fluid. In vitro studies (Schierhorn et al., 

1999) of nasal mucosal biopsies from atopic and nonatopic subjects exposed to 0.1 ppm O3 found 

significant differences in release of IL-4, IL-6, IL-8, and TNF-α. Another study by Schierhorn et 

al. (2002) found significant differences in the O3-induced release of the neuropeptides neurokinin 

A and substance P for allergic patients in comparison to nonallergic controls, suggesting 

increased activation of sensory nerves by O3 in the allergic tissues. Another study by Bayram et 

al. (2002) using in vitro culture of bronchial epithelial cells recovered from atopic and nonatopic 

asthmatics also found significant increases in epithelial permeability in response to O3 exposure. 

In addition, some controlled human O3 exposure studies in asthmatics (Hiltermann et al., 1999; 

Scannell et al., 1996) reported increased secretion of IL-8, suggesting increased neutrophilic 

inflammation. Two studies (Jörres et al., 1996; Holz et al., 2002) observed increased airway 

responsiveness to repeated daily O3 exposure to bronchial allergen challenge in subjects with 

preexisting allergic airway disease. 

Newly available reports from controlled human exposure studies (see Chapter 6 in the 

CD) utilized subjects with preexisting cardiopulmonary diseases such as COPD, asthma, allergic 

rhinitis, and hypertension. The data generated from these studies that evaluated pulmonary 

function changes in spirometry did not find clear differences between filtered air and O3 exposure 

in COPD subjects. However, the new data on airway responsiveness, inflammation, and various 

molecular markers of inflammation and bronchoconstriction indicate that people with atopic 

asthma and allergic rhinitis comprise susceptible groups for O3-induced adverse health 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 expected to have such changes 

based on their age. However, in Section 8.7.1, the CD notes that new epidemiological evidence 

indicates that people with COPD may be more likely to experience other effects, including 

emergency room visits, hospital admissions, or premature mortality. For example, results from 

an analysis of five European cities indicated strong and consistent O3 effects on unscheduled 

respiratory hospital admissions, including COPD (Anderson et al., 1997). Also, an analysis of a 

9-year data set for the whole population of the Netherlands provided risk estimates for more 

specific causes of mortality, including COPD (Hoek et al., 2000, 2001; reanalysis Hoek, 2003); a 
3-69 

positive, but nonsignificant, excess risk of COPD-related mortality was found to be associated 

with short-term O3 concentrations. Moreover, as indicated by Gong et al. (1998), the effects of 

O3 exposure on alveolar-arterial oxygen gradients may be more pronounced in patients with 

preexisting obstructive lung diseases. Relative to healthy elderly subjects, COPD patients have 

reduced gas exchange and low SaO2. Any inflammatory or edematous responses due to O3

delivered to the well-ventilated regions of the COPD lung could further inhibit gas exchange and 

reduce oxygen saturation. In addition, O3-induced vasoconstriction could also acutely induce 

pulmonary hypertension. Inducing pulmonary vasoconstriction and hypertension in these 

patients would perhaps worsen their 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 heterogeneity in the effects of O3 by age. As discussed in 

section 6.5.1 of the CD, children, adolescents, and young adults (<18 yrs of age) appear, on 

average, to have nearly equivalent spirometric responses to O3, but have greater responses than 

middle-aged and older adults when exposed to comparable O3 doses. Symptomatic responses to 

O3 exposure, however, do not appear to occur in healthy children, but are observed in asthmatic 

children, particularly those who use maintenance 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 symptomatic and spirometric responses 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 O3 on the respiratory health of school children. In general, children experienced 

decrements in pulmonary function parameters, including PEF, FEV1, and FVC. Increases in 

respiratory symptoms and asthma medication use were also observed in asthmatic children. In 

one German study, children with and without asthma were found to be particularly susceptible to 

O3 effects on lung function. Approximately 20% of the children, both with and without asthma, 

experienced a greater than 10% change in FEV1, 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 pollutants, including O3. This is in part 

because their lungs are still developing. For example, eighty percent of alveoli are formed after 

birth, and changes in lung development continue through adolescence (Dietert et al., 2000). 

Children are also likely to spend more time outdoors than adults do, which results in increased 

exposure to air pollutants (Wiley et al., 1991a,b). Moreover, children have high minute 
3-70 

ventilation rates and high levels of physical activity which also increases their dose (Plunkett et 

al., 1992). 

 Several mortality studies have investigated age-related differences in O3 effects. Among 

the studies that observed positive associations between O3 and mortality, a comparison of all age 

or younger age (#65 years of age) O3-mortality effect estimates to that of the elderly population 

(>65 years) indicates that, in general, the elderly population is more susceptible to O3 mortality 

effects (Borja-Aburto et al., 1997; Bremner et al., 1999; Gouveia 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 O3-mortality effect by age in Sno Paulo, Brazil. 

Among all ages, O3 was associated with a 0.6% excess risk in all cause mortality per 40 ppb 

increase in 1-hr max O3. In comparison, in the elderly population, the O3-mortality risk estimate 

was nearly threefold greater, at 1.7%. Similarly, a Mexico City study found that O3-mortality 

effect estimates were 1.3% and 2.8% per 20 ppb increase in 24-hr average O3 concentration in all 

ages and the elderly, respectively (O’Neill et al., 2004). 

 The meta-analysis by Bell et al. (2005) found a larger effect estimate for the elderly 

(2.92% per 20 ppb increase in 24-hr average O3) 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 O3, compared to individuals 

less than 65 years and 75 years or greater, 1.00% and 1.04%, respectively, using a constrained 

distributed 7-day lag model. Bell et al. (2004) note that despite similar effects estimates, the 

absolute effect of O3 is substantially greater in the elderly population due to the higher 

underlying mortality rates, which lead to a larger number of extra deaths for the elderly 

compared to the general population. The CD concludes that the elderly population (>65 years of 

age) appear to be at greater risk of O3-related mortality and hospitalizations compared to all ages 

or younger populations (CD, p. 7-177). 

 The CD notes that, collectively, there is supporting evidence of age-related differences in 

susceptibility to O3 lung function effects. The elderly population (>65 years of age) appear to be 

at increased risk of O3-related mortality and hospitalizations, and children (<18 years of age) 

experience other potentially adverse respiratory health outcomes with increased O3 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 O3-

sensitive and resistant strains and illustrated the importance of genetic background in 

determining O3 susceptibility (CD, section 8.7.4). Using subacute low exposure regimen (0.3 

ppm O3, 48h) studies on inbred strains that have been designated as inflammation prone or 
3-71 

resistant, Kleeberger et al., (1997) identified the pro-inflammatory cytokine gene, Tnf-α, as a 

susceptibility gene. Further characterization of this model indicated a role for TNF receptors 

(TNFR1, TNFR2) in O3-induced pulmonary epithelial injury and inflammation (Cho et al., 

2001). Studies on five inbred strains of mouse with differing response to O3 exposure (acute 

high dose or low dose continuous exposure for 3 days), reported a protective role for clara cell 

secretory protein (CCSP) against O3-induced oxidative damage (Broeckaert et al., 2003; Wattiez 

et al., 2003). The role for these genes and/or their orthologs in human susceptibility to O3 

exposure is yet to be examined. 

 Apart from age at the time of exposure, controlled human exposure studies have also 

indicated a high degree of interindividual 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 antioxidant enzymes and genes involved in inflammation to modulate 

pulmonary function and inflammatory responses to O3 exposure. Similar to mouse studies 

referred above, polymorphism in Tnf-α has been implicated in O3-induced lung function changes 

in healthy, mild asthmatics and individuals with rhinitis. These observations suggest a potential 

role for these markers in the innate susceptibility to O3, however, the validity of these markers 

and their relevance in the context of prediction to population studies needs additional 

experimentation. 

 Biochemical and molecular parameters extensively evaluated in these experiments were 

used to identify specific loci on the chromosomes and, in some cases, to relate the differential 

expression of specific genes to biochemical and physiological differences observed among these 

species. Utilizing O3-sensitive and O3-resistant species, it has been possible to identify the 

involvement of AHR and inflammation processes in O3 susceptibility. However, most of these 

studies were carried out using relatively high doses of O3, making the relevance of these studies 

questionable in human health effects assessment. The molecular parameters identified in these 

studies may serve as useful biomarkers with the availability of suitable technologies and, 

ultimately, can likely be integrated with epidemiological studies. Interindividual differences in 

O3 responsiveness have been observed across a spectrum of symptoms and lung function 

responses do not yet allow identification of important 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 O3 exposures 

and a range of effects on the cardiovascular system. Some but not all, epidemiological studies 

have reported associations between short-term O3 exposures and the incidence of myocardial 

infarction and more subtle cardiovascular health endpoints, such as changes in heart rate 
3-72 

variability and cardiac arrhythmia. Others have reported associations with hospitalization or ED 

visits for cardiovascular diseases, although the results across the studies are not consistent. 

Studies also report associations between short-term O3 exposure and mortality from 

cardiovascular or cardiopulmonary causes. The CD concludes that current cardiac physiologic 

effects evidence from some field studies is rather limited but supportive of a potential effect of 

short-term O3 exposure and HRV, cardiac arrhythmia, and MI incidence (CD, p. 7-65). In the 

CD’s evaluation of studies of hospital admissions for cardiovascular disease (CD, section 7.3.4), 

it is concluded that evidence from this growing group of studies is generally inconclusive 

regarding an association with O3 in studies conducted during the warm season (CD, p. 7-83). 

This body of evidence suggests that people with heart disease may be at increased risk from 

short-term exposures to O3; however, more evidence is needed to conclude that people with heart 

disease are a susceptible population. 

Other groups that might have enhanced sensitivity to O3, but for which there is currently 

very little evidence, include groups based on race, gender and socioeconomic status, and those 

with nutritional deficiencies, as discussed in section 3.6.1 which presents factors which modify 

responsiveness to O3. 

3.6.3 What Constitutes an Adverse Health Impact from Ozone Exposure? 

 In making judgments as to when various O3-related effects become regarded as adverse 

to the health of individuals, in previous NAAQS reviews staff has relied upon the guidelines 

published by the American Thoracic Society (ATS) and the advice of CASAC. While 

recognizing that perceptions of “medical significance” and “normal activity” may differ among 

physicians, lung physiologists and experimental subjects, the ATS (1985) defined adverse 

respiratory health effects as “medically significant physiologic changes generally evidenced by 

one or more of the following: (1) interference with the normal activity of the affected person or 

persons, (2) episodic respiratory illness, (3) incapacitating illness, (4) permanent respiratory 

injury, and/or (5) progressive respiratory dysfunction.” 

During the 1997 review, it was concluded that there was evidence of causal associations 

from controlled human exposure studies for effects in the first of these five ATS-defined 

categories, evidence of statistically significant associations from epidemiological studies for 

effects in the second and third categories, and evidence from animal toxicology studies, which 

could be extrapolated to humans only with a significant degree of uncertainty, for the last two 

categories. For the current review, the evidence of O3-related effects is stronger across all the 

categories. For ethical reasons, clear causal evidence from controlled human exposure studies 

still covers only effects in the first category. However, for this review there are results from 

epidemiological studies, upon which to base judgments about adversity, for effects in all of the 
3-73 

categories. Statistically significant 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 require medication (e.g., asthma), but not necessarily hospitalization, 

as well as respiratory hospital admissions and ED visits for respiratory causes. Less conclusive, 

but still positive associations have been reported for school absences and cardiovascular hospital 

admissions. Human health effects for which associations have been suggested through evidence 

from epidemiological and animal toxicology studies, but have not been conclusively 

demonstrated still fall primarily into the last two categories. In the last review of the O3

standard, evidence for these more serious effects came from studies of effects in laboratory 

animals. Evidence from animal studies evaluated in this CD strongly suggests that O3 is capable 

of damaging the distal airways and proximal alveoli, resulting in lung tissue remodeling leading 

to apparently irreversible changes. Recent advancements of dosimetry modeling also provide a 

better basis for extrapolation from animals to humans. Information from epidemiological studies 

provides supporting, but limited evidence of irreversible respiratory effects in humans (as 

described in section 6.3.3.2 below). Moreover, the CD concludes that the findings from singlecity and multi-city time-series epidemiology studies and meta-analyses of these epidemiology 

studies support a likely causal association between short-term O3 exposure and mortality 

particularly in the warm season. 

 While O3 has been associated with effects that are clearly adverse, application of these 

guidelines, in particular to the least serious category of effects related to ambient O3 exposures, 

involves judgments about which medical experts on the CASAC panel and public commenters 

have in the past expressed diverse views. To help frame such judgments, we have defined 

gradations of individual functional responses (e.g., decrements in FEV1 and airway 

responsiveness) and symptomatic responses (e.g., cough, chest pain, wheeze), together with 

judgments as to the potential impact on individuals experiencing varying 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 levels of functional responses (e.g., FEV1

decrements of >10% but < 20%, lasting up to 24 hrs) and/or moderate symptomatic responses 

(e.g., frequent spontaneous cough, marked discomfort on exercise or deep breath, lasting up to 

24 hrs) would likely interfere with normal activity for relatively few sensitive individuals; 

whereas large functional responses (e.g., FEV1 decrements > 20%, lasting longer than 24 hrs) 

and/or severe symptomatic responses (e.g., persistent uncontrollable cough, severe discomfort on 

exercise or deep breath, lasting longer than 24 hrs) would likely interfere with normal activities 
Table 3-2. Gradation of Individual Responses to Short-Term Ozone Exposure in Healthy 

Persons1

Functional Response None Small Moderate Large

FEV1 Within 

normal 

range (±3%) 

Decrements of 

3 to #10% 

Decrements of 

>10 but <20% 

Decrements of 

$20% 

Nonspecific 

airway responsiveness2

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 O3 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 PD20 or PD100. 
Table 3-3. Gradation of Individual Responses to Short-Term Ozone Exposure in Persons 

with Impaired Respiratory Systems3

Functional 

Response

None Small Moderate Large

FEV1 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 change Normal medication as 

needed 

Increased frequency 

of medication use or 

additional medication 

Physician or 

emergency room 

visit 

1 3-75

 

3 This table is reproduced from the 1996 O3 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 PD20 or PD100. 
3-76 

for many sensitive individuals and therefore would be considered adverse under ATS guidelines. 

For the purpose of estimating potentially adverse lung function decrements in active healthy 

people, the CASAC indicated that a focus on the mid to upper end of the range of moderate 

levels of functional responses is most appropriate (e.g., FEV1 decrements ≥ 15% but < 20%)5. 

However, for people with lung disease, even moderate functional (e.g., FEV1 decrements > 10% 

but < 20%, lasting up to 24 hr) or symptomatic 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 normal 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., FEV1 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 accompanied by shortness of breath, lasting longer 

than 24 hrs) would likely interfere with normal activity for most individuals and would increase 

the likelihood that these individuals would seek medical treatment. For the purpose of 

estimating potentially adverse lung function decrements in people with lung disease, the CASAC 

indicated that a focus on the lower end of the range of moderate levels of functional responses is 

most appropriate (e.g., FEV1 decrements ≥ 10%). 

In judging the extent to which these impacts represent effects that should be regarded as 

adverse to the health status of individuals, an additional factor that has been considered in 

previous NAAQS reviews is whether such effects are experienced repeatedly during the course 

of a year or only on a single occasion. While some experts would judge single occurrences of 

moderate responses to be a “nuisance,” especially for healthy individuals, a more general 

consensus view of the adversity of such moderate responses emerges as the frequency of 

occurrence increases. Thus 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 (61 FR 65723). The CASAC panel in the last review expressed 

a consensus view that these “criteria 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 revised guidance was intended to address new investigative 

approaches used to identify the effects of air pollution, and to reflect the concern for the impacts 

of air pollution on specific groups that had been expressed through the environmental justice 

movement. 

 5

 Transcript of CASAC meeting, day 8/24/06, page 149. 
3-77 

 The new guidance builds upon and expands the 1985 definition of adversity in several 

ways. There is an increased focus on quality of life measures as indicators of adversity. There is 

also a more specific consideration of population risk. Exposure to air pollution that increases the 

risk of an adverse effect to the entire population is adverse, even 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 lung function such that no individual has a level associated 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 O3 exposure that have been studied, many would meet the ATS 

definition of adversity. Such effects include, for example, any detectible level of permanent lung 

function loss attributable to air pollution, including both reductions in lung growth or 

acceleration of the age-related decline 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 FEV1 is 

considered to have clinical importance to asthma morbidity (ATS 1991; Lebowitz et al. 1987; 

Lippmann, 1988). This is in line with the view expressed by the CASAC that a focus on the 

lower end of the range of moderate levels of functional responses is most appropriate (e.g., FEV1

decrements ≥ 10%) to estimate the risk of potentially adverse lung function responses in people 

with lung disease. The National Institutes of Health (1997) has stated that a PEF below 80% of a 

person’s personal best indicates a need for continued medication use in asthmatics. In Mortimer 

et al. (2002), O3 was associated with increased incidence of > 10% declines in morning PEF as 

well as morning symptoms, indicating that O3 exposure may have clinically significant effects on 

asthmatic children. 

 Reflecting new investigative approaches, the ATS statement describes the potential 

usefulness of research into the genetic basis for disease, including responses to environmental 

agents that will provide insights 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 defining the point at which a response should be 

equated with an adverse effect. Based on concern for segments of the population that may be 

disproportionately exposed to environmental contaminants, or have other factors that may 
3-78 

increase susceptibility (e.g., genetic or nutritional factors), there was a call for increased research 

in these areas. 

 Overall, the new guidance does not fundamentally change the approach previously taken 

to define adversity, nor does it suggest a need at this time to change 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 People in At-Risk Susceptible Population 

Groups in the United States 

Although O3-related health risk estimates may appear to be numerically small, their 

significance from an overall public health perspective is affected by the large numbers of 

individuals in potential risk groups. Several subpopulations may be identified as having 

increased susceptibility or vulnerability to adverse health effects from O3, including: older adults, 

children, individuals with preexisting pulmonary disease, and those with higher exposure levels, 

such as outdoor workers. 

One consideration in the assessment of potential public health impacts is the size of 

various population groups that may be at increased risk for health effects associated with O3-

related air pollution exposure. Table 8-4 in the CD summarizes information 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). Individuals with preexisting cardiopulmonary disease constitute 

a fairly large proportion of the population, with tens of millions of people included in each 

disease category. Of most concern 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 bronchitis and/or emphysema). Table 8-5 

in the CD provides further information on the number of various specific respiratory conditions 

per 100 persons by age among the U.S. population during the mid-1990s. Asthma prevalence 

tends to be higher in children than adults. 

In addition, subpopulations based on age group also comprise substantial segments of the 

population that may be potentially at risk for O3-related health impacts. Based on U.S. census 

data from 2003, about 26% of the 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. population are included in age groups 

that are considered likely to have increased susceptibility and vulnerability for health effects 

from ambient O3 exposure. 

The health statistics data illustrate what is known 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 respiratory diseases (Kochanek et al., 

2004). For respiratory health diseases, there are nearly 4 million hospital discharges per year 
3-79 

(DeFrances et al., 2005), 14 million ED visits (McCaig and Burt, 2005), 112 million ambulatory 

care visits (Woodwell and Cherry, 2004), and an estimated 700 million restricted activity days 

per year due to respiratory conditions (Adams et al., 1999). Combining small risk estimates with 

relatively large baseline levels of health outcomes can result in quite large public health impacts. 

Thus, even a small percentage reduction in O3 health impacts on cardiopulmonary diseases would 

reflect a large number of avoided cases. 

Another key input for public health impact assessment is the range of concentration 

response functions for various health outcomes. Epidemiologic studies have reported 

associations between short-term exposure to O3 with mortality, hospitalizations for pulmonary 

diseases, ED visits for asthma, reduced lung function, and incidence of respiratory symptoms. 

Effect estimates for morbidity responses to short-term changes in O3 tend to be larger and more 

variable in magnitude than those for mortality. 

 In addition to attribution of risks for various health outcomes related to O3 and other 

copollutants, important considerations in assessing the impact of O3 on public health include the 

size of population groups at risk, as well as the concentration-response relationship and potential 

identification of threshold levels. Taken together, based on the above information, it can be 

concluded that exposure to ambient O3 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 epidemiological evidence assessed in the 1996 

CD, a set of findings and conclusions were drawn regarding potential health effects of O3

exposure as of 1996. These conclusions are integrated into the 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 order to be more easily distinguished from the “1996 CD.” Section 

8.8 of the 2006 CD also has summarized the main conclusions derived from the integrated 

analysis of animal toxicology (2006 CD, Chapter 5), human experimental (2006 CD, Chapter 6) 

and epidemiological (2006 CD, Chapter 7) studies that evaluated evidence of health effects 

associated with short-term, prolonged, and long-term exposures to O3 alone or in combination 

with other pollutants commonly found in the ambient air. This section summarizes conclusions 

drawn from section 8.8 of the 2006 CD with respect to the health effects associated with 

exposure to O3 that are most relevant to our assessment of the adequacy of the current primary 

O3 standard and the identification of options to consider concerning potential alternative 

standards to protect public health with an adequate margin of safety. 
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3.7.1 Respiratory Morbidity Effects of Short-term Exposures to Ozone 

In the 1996 CD, it was concluded from assessment of controlled human exposure studies 

that short-term O3 exposures to O3 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 function and respiratory symptoms in healthy adults and asthmatic 

individuals exposed (2006 CD, p. 8-73). Lung inflammatory responses have been observed in 

healthy human adults following 6.6 hr O3 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 concentration, duration, and level of exertion. Such experimentally 

demonstrated effects were consistent with and helped support the plausibility of epidemiological 

findings assessed in the 1996 CD regarding daily hospital admissions and ED visits for 

respiratory causes. 

 The 1996 CD concluded that group mean data from numerous controlled human exposure 

and field studies of healthy subjects (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 FEV1) occur in subjects exposed: 

• at >0.12 ppm O3 after very heavy exercise (competitive running). 

• at >0.18 ppm O3 after heavy exercise (easy jogging), 

• at >0.30 ppm O3 after moderate exercise (brisk walking), 

• at >0.37 ppm O3 after light exercise (slow walking), and 

• at >0.50 ppm O3 when at rest. 

 Small group mean changes (e.g., <5%) in FEV1 have been observed in healthy young 

adults at levels as low as 0.12 ppm O3 for 1 to 3 hr exposure periods. Also, lung function 

decrements have been observed in children and adolescents at concentrations of 0.12 and 0.14 

ppm O3 with heavy exercise. Some individuals within a study may experience FEV1 decrements 

in excess of 15% under these conditions, even when group mean decrements are less than 5%. 

 For exposures of healthy, young adult subjects performing moderate exercise during 

longer duration exposures (6 to 8 hr), 5% group mean decrements in FEV1 were observed at 

• 0.08 ppm after O3 5.6 hr, 

• 0.10 ppm after O3 4.6 hr, and 

• 0.12 ppm after O3 3 hr. 
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For these same subjects, 10% group mean FEV1 decrements were observed at 0.12 ppm O3 after 

5.6 and 6.6 hr. As in the shorter duration studies, some individuals experience changes larger 

than those represented by group mean changes. 

 The 2006 CD (section 8.8) concludes that newer meta-analyses confirmed interindividual 

differences in lung function decrements reported in the 1996 CD. Age-specific differences in 

lung function responses were also observed. Spirometric responses (i.e., decrements in lung 

function) in healthy adults exposed to near ambient O3 levels typically resolve to near baseline 

within 4-6 hr. Meta-analyses of four controlled human exposure studies (two new and two 

assessed in the 1996 CD) reporting the effects of prolonged (6.6 hr) exposures to 0.08 ppm O3

during moderate exertion on lung function in young healthy adults (M=90, F=30; mean age 23 

years) indicate an absolute FEV1 decrease of 6%, whereas FEV1 increased by 1% following fresh 

air exposures. Newer studies from Adams (2002, 2006), as illustrated earlier in Figure 3-1B, 

demonstrate notable interindividual variability for O3 exposure concentrations of 0.04, 0.06 and 

0.08 ppm. Following a continuous exposure to 0.08 ppm O3 during intermittent, moderate 

exertion, the group mean FEV1 decrement (corrected for filtered air) was 6%, but 23 % of 

subjects had FEV1 decrements of 10% or more. Following exposure to 0.06 ppm O3, the group 

mean FEV1 decrement was less than 3%, but 7% of subjects had greater than 10% FEV1 

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 presented in the Adams (2006) study show a small (< 3%) group 

mean FEV1 decrement following the 6.6-hr exposure at 0.06 ppm, which may be statistically 

significantly different from filtered air responses. 

 A few controlled human exposure studies (Adams, 2003; 2006; Hazucha et al., 1992) 

investigated a triangular exposure pattern at O3 concentrations that had 6.6 to 8-hr averages 

between 0.08 and 0.12 ppm in order to more closely mimic typical ambient O3 exposure patterns. 

Greater overall FEV1 decrements were observed with triangular exposures compared to the 

constant or square-wave exposures. Furthermore, peak FEV1 decrements observed during 

triangular exposures were greater than those observed during square-wave patterns. At a lower 

average O3 concentration of 0.06 ppm, no temporal (i.e., hour by hour responses) differences 

were observed in FEV1 decrements between square-wave and triangular exposure patterns. 

There was, however, a statistically significant effect of the 0.06 ppm triangular 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 suggest the potential for somewhat 

greater effects on lung function in ambient O3 exposure scenarios that typically involve gradually 

increasing daily exposure up to a peak in the late afternoon and a subsequent gradual decline 

(2006 CD, p. 8-19). The quantitative risk assessment, discussed below in Chapter 5, provides 
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estimates of the percentages of school age children likely to experience FEV1 decrements greater 

than or equal to 10, 15, and 20% after 8-hr exposures to O3 while engaged in moderate exertion. 

 Decrements in lung function associated with ambient O3 levels have also been found in 

children attending summer camps in southern Ontario, Canada, in the 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 O3 exposure and the incidence of a >10% decrement in 

morning PEF in asthmatic children. Meta-analyses indicate that a 0.50-mL decrease in FEV1 is 

associated with a 1 ppb increase in O3 concentration. For preadolescent children exposed to 120 

ppb (0.12 ppm) ambient O3, this amounts to an average decrement of 2.4 to 3.0% in FEV1. 

Similar responses are reported for exercising children and adolescents exposed to O3 in ambient 

air or O3 in purified air for 1-2 hours. 

 The 1996 CD concluded that an increase in the incidence of cough has been reported at O3

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 pain on deep inspiration, shortness of breath, and 

lower respiratory scores (i.e., a combination of several symptoms), have been observed at 0.16 

ppm to 0.18 ppm O3, 1-hr average, with heavy and very heavy exertion. Respiratory symptoms 

also have been observed following exposure to 0.08, 0.10 and 0.12 ppm O3 for 6.6 hr with 

moderate exertion levels. Also, increases in nonspecific airway responsiveness 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 O3; 

during very heavy exertion, these increases were observed at concentrations as low as 0.18 ppm 

but not at 0.12 ppm O3. Increases in nonspecific airway responsiveness during the 6.6 hr 

exposures with moderate levels of exertion have been observed at 0.08, 0.10 and 0.12 ppm O3. 

 The majority of asthma panel studies evaluated the associations of ambient O3 with lung 

function and respiratory symptoms in asthmatic children. Results obtained from these studies 

show some inconsistencies, with some indicating significant positive associations and other 

smaller studies not finding such effects. Overall, however, the multicity study by Mortimer et al. 

(2002) and several credible single-city studies (e.g., Gent et al., 2003) indicate a fairly robust 

association between ambient O3 concentrations and increased respiratory symptoms in moderate 

to severe asthmatic children (2006 CD, p. 8-35). 

 The 2006 CD (p. 8-75) concludes that lung inflammatory responses have been observed 

in healthy human adults following 6.6 hr O3 exposures as low as 0.08 ppm. These responses 

have been found even in the absence of O3-induced lung function decrements for some 

individuals. Attenuation of most inflammatory markers occurs with repeated exposures over 

several days, but none of the several markers of lung injury and permeability show attenuation, 

which is indicative of continued lung tissue damage during repeated exposure. Laboratory 

animal studies have reported that 1 to 3 hr O3 exposures as low as 0.1 to 0.5 ppm can cause (1) 
3-83 

lung inflammatory responses (e.g., increased ROS and 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 susceptibility to infectious diseases 

due to modulation of lung host defenses. Consistent with the above results of human and animal 

experimental studies, there is limited epidemiologic evidence of an association between acute 

ambient O3 exposure (1-hr max of about 0.1 ppm) and airway inflammation in children, all of 

which taken together is indicative of a causal role for O3 in inflammatory responses in the 

airways (2006 CD, p. 8-76). See Table 3.4 for a summary of short-term health effects of O3

based on clinical studies assessed in both the 1996 CD and 2006 CD. 

The 1996 CD concluded that increased O3 levels are associated with increased hospital 

admissions and ED visits for respiratory causes. Analyses from data in the northeastern U.S. 

suggested that O3 air pollution is associated with a substantial portion of all summertime 

respiratory hospital visits and admissions. The 2006 CD concludes (CD, p. 8-36) that a large 

multi-city and several single-city studies have indicated a positive association between increased 

O3 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 addressed in the 2006 

CD, is O3-induced cardiovascular effects. Newly available evidence has emerged since 1996 

which provides considerable plausibility for how O3 could exert cardiovascular effects (2006 

CD, p. 8-77). Examples of such O3-induced cardiovascular effects include: (1) O3-induced 

release from lung epithelial cells of PAF that may contribute to blood clot formation that would 

increase the risk of serious cardiovascular outcomes (e.g., heart attack, stroke, mortality); (2) 

interactions of O3 with surfactant components in ELF of the lung resulting in production of 

oxysterols and ROS that may exhibit PAF-like activity contributing to clotting and/or exerting 

cytotoxic effects on lung and heart cells; (3) possible mechanisms that may involve O3-induced 

secretions of vasoconstrictive substances 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 O3 and various cardiac physiologic endpoints suggesting a potential 

relationship between O3 exposure and altered HRV, ventricular arrhythmias, and incidence of 

MI; and (5) positive associations during the warm season only between ambient O3

concentrations and cardiovascular hospitalizations. While the only controlled human exposure 

study that evaluated effects of O3 exposure on the cardiovascular system found no O3-induced 

differences in ECG or blood pressure in healthy or hypertensive subjects, the study did report 

overall increases in myocardial work and heart rate, and impairment in pulmonary gas exchange.
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Table 3-4. Summary of Ozone-Induced Respiratory Health Effects from Clinical Studies6

Health Effect Exercise 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 O3-induced decreases in heart rate, mean 

arterial pressure and core temperature. Overall, the 2006 CD (p. 8-77) concludes that this 

generally limited body of evidence is highly suggestive that O3 directly and/or indirectly 

contributes to cardiovascular-related morbidity, but much remains to be done to more fully 

substantiate links between short-term ambient O3 exposures and adverse cardiovascular effects. 

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

 The 1996 CD concluded that an association between daily mortality and O3 concentration 

for areas with high O3 levels (e.g., Los Angeles) was suggested. However, due to a very limited 

number of studies available at that time, there was insufficient evidence to conclude that the 

observed association was likely causal. 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. 
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studies conducted in the U.S. and Europe, and several single-city studies conducted all over the 

world, as well as from several meta-analyses that have combined information from multiple 

studies. The majority of these studies suggest an elevated risk of total nonaccidental mortality 

associated with acute exposure to O3, especially in the summer or warm season when O3 levels 

are typically high, with somewhat larger effect estimate sizes for associations with 

cardiovascular mortality (2006 CD, p. 7-175). The 2006 CD finds that the results from U.S. 

multicity time-series studies provide the strongest evidence to-date for associations between 

short-term O3 exposure and mortality. These studies, along with recent meta-analyses, showed 

consistent effect estimates that are unlikely to be confounded by PM, though the 2006 CD 

observes that future work is needed to better understand the influence of model specifications on 

the effect estimates (2006 CD, p. 7-175). For cardiovascular mortality, the 2006 CD reports that 

effect estimates are consistently positive, falling in the range of 1 to 8% increases per 40 ppb in 

1-hr max O3 (2006 CD, p. 7-107). Overall, the 2006 CD concludes that the majority of these 

findings suggest an elevated risk of all-cause mortality associated with short-term O3 exposure, 

especially in the summer or warm season when O3 levels are typically high. Slightly greater 

effects were observed for cardiovascular 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 O3 exposures (2006 

CD, p. 8-15). Partial or complete attenuation is observed for some of the O3-induced responses 

after more than 2 days of exposure. After 5 days of exposure, lung function changes return to 

control levels with the greatest changes usually occurring on the second day, but the attenuation 

was reversed after 7 to 10 days without O3 exposure. Most inflammatory markers (e.g., PMN 

influx) attenuate after 5 days of exposure, but markers of cell damage (e.g., LDH enzyme 

activity) do not attenuate and continue to increase. Recovery of some inflammatory markers 

occurred a week to 10 days after exposure ceased, but some responses were not normal after 20 

days. Animal studies suggest underlying cell damage continues throughout the attenuation 

process. Also, attenuation may alter normal distribution of O3 within the lungs, allowing more 

O3 to reach sensitive regions, possibly affecting lung defenses. Newer studies assessed in the 

2006 CD (p. 8-74 and 8-75) supported all of these conclusions in addition to which it was 

concluded that repeated daily, multi-hour exposure to lower concentrations of O3 (0.125 ppm for 

4 days) causes an increased response to bronchial allergen challenge in subjects with preexisting 

allergic airway disease, with or without asthma. In these subjects, changes in airway 

responsiveness after O3 exposure appear to be resolved more slowly than changes in FEV1 or 

respiratory symptoms. 
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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-term exposures to ambient O3 are likely causal, we note that several 

different factors have informed the judgments made in the CD and here. These factors include 

the nature of the evidence (i.e., controlled human exposure, epidemiological, and/or toxicological 

studies) and the weight of evidence, including such considerations as biological plausibility, 

coherence of evidence, strength of association, and consistency of evidence. 

In assessing the health effects data base for O3, it is clear that human studies provide the 

most directly applicable information because they are not limited by the uncertainties of 

dosimetry differences and species sensitivity differences, which would need to be addressed in 

extrapolating animal toxicology data to human health effects. Controlled human exposure 

studies provide dat 

a with the highest level of confidence since they provide human effects data under closely 

monitored conditions and can provide clear exposure-response relationships. Epidemiological 

data provide evidence of associations between ambient O3 levels and more serious acute and 

chronic health effects (e.g., hospital admissions and mortality) that cannot be assessed in 

controlled human exposure studies. For these studies the degree of uncertainty regarding 

potential confounding variables (e.g., other pollutants, temperature) and other factors affects the 

level of confidence that the health effects being investigated are attributable to O3 exposures, 

alone and in combination with other copollutants. 

In using a weight of evidence approach to inform judgments about the degree of 

confidence that various health outcomes are likely to be caused by exposure to O3, confidence 

increases as the number of studies and other factors, such as strength, consistency, and coherence 

of evidence, consistently reporting a particular health endpoint grows. For example, there is a 

very high level of confidence that O3 induces lung function decrements in healthy adults and 

children due in part to the dozens of studies consistently showing that these effects were 

observed. As noted above, the 2006 CD (p. 8-74) states that studies provide clear evidence of 

causality for associations between short-term O3 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 breath) has been observed in controlled human 

exposure studies of short-term O3 exposures, and significant associations between ambient O3

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 supported by human clinical, animal 

toxicologic, and epidemiologic evidence for lung function decrements, respiratory symptoms, 
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airway inflammation, and airway hyperreactivity. Taken together, the 2006 CD (p. 8-77) 

concludes that the overall evidence supports the inference of a causal relationship between acute 

ambient O3 exposures and increased respiratory morbidity outcomes resulting in increased 

asthma ED visits and respiratory hospitalizations during the warm season. Recent epidemiologic 

evidence has been characterized in the CD (p. 8-78) as highly suggestive that O3 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 plausibility, consistency, and coherence of evidence of O3-related health 

effects are drawn from the integration of epidemiological studies with mechanistic information 

from controlled human exposure studies and animal toxicological studies. This type of 

mechanistic linkage has been firmly established for several respiratory endpoints (e.g., lung 

function decrements, lung inflammation) but remains far more equivocal for cardiovascular 

endpoints (e.g., cardiovascular-related hospital admissions). Finally, for epidemiological studies, 

strength of association refers to the magnitude of the association and its statistical strength, 

which includes assessment of both effects estimate size and precision (section 3.4.1). In general, 

when associations yield large relative risk estimates, it is less likely that the association could be 

completely accounted for by a potential confounder or some other bias. Consistency refers to the 

persistent finding of an association between exposure and outcome 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, O3 exposure and mortality. 

Figure 3-5 summarizes our judgments for the various health outcomes discussed above 

concerning the extent to which relationships between various health outcomes and ambient O3

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 nature of the evidence and overall 

weight of the evidence, and are taken into consideration in our quantitative risk assessment, 

presented below in Chapter 5. 

3.7.6 Health Effects of Long-term Exposures to Ozone 

 In the 1996 CD, available data, primarily from animal toxicology studies, indicated that 

exposure to O3 for periods of months to years causes structural 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 meet. This region of the lungs is typically 

affected in most human airway diseases. However, data from epidemiological are limited or 

inconclusive, and data from clinical studies are lacking. Most information on chronic O3 effects 

in the distal lungs continues 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 O3 season

-Cardiorespiratory-related mortality during the O3 season

-Total nonaccidental mortality during the O3 season

-Cardiovascular-related hospital admissions

Characterization Overall Confidence in Causal Relationship With Ambient 

Ozone

Causal

Suggestive

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3-89

What had been viewed previously as an apparent lack of reversibility of O3-induced effects with 

a clean air recovery period has been 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 O3 pattern (0.5 ppm O3 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 findings support and advance the earlier information suggestive of 

injury and repair processes which are caused by seasonal O3 exposures (2006 CD, p.8-79). 

Epidemiological studies investigating chronic effects in humans following long-term exposures 

to O3 have provided only limited suggestive evidence. Further investigation will be necessary 

before we are able to draw firmer conclusions about chronic health effects of O3 in human 

populations. 

3.7.7 Health Effects of Pollutant Mixtures Containing Ozone 

In the 1996 CD, it was recognized that coexposure to O3 and other pollutants, such as 

NO2, SO2, H2SO4, HNO3, or CO, showed additive response for lung spirometry or respiratory 

symptoms (2006 CD, p. 8-82). Since 1996, most animal toxicology studies investigating O3 in a 

mixture with NO2 and H2SO4 have shown that effects can be additive, synergistic, or even 

antagonistic, depending on the exposure regimen and the endpoint studied. Ozone has served for 

a long time as a surrogate or indicator for the overall photochemical oxidant mix. It is well 

recognized that the observed effects may be due to components of that mix alone or in 

combination with O3 and other gases and PM in the ambient air. Although the issue of exposure 

to copollutants was previously described as poorly understood, especially with regard to chronic 

effects, newer information from human and animal studies of binary mixtures containing O3

suggest potential interactions depending on the exposure regimen and pollutant mix (CD, p. 8-

82). Examples of this newer information include: (1) continuous exposure to SO2 and NO2

increased inhaled O3 bolus absorption, while continuous exposure to O3 decreased O3 bolus 

absorption; (2) asthmatics exhibited enhanced airway reactivity to house dust mite allergen 

following exposures to O3, NO2 and the combination of the two gases; however, spirometric 

response was impaired only by O3 and O3+ NO2 at higher concentrations; and (3) animal 

toxicology studies with O3 in mixture with NO2, formaldehyde, and PM demonstrated additive, 

synergistic, or antagonistic effects depending on the exposure regimen and the endpoints 

evaluated. 

 One controlled-exposure study of children, designed to approximate conditions of an 

epidemiological study by matching population and exposure atmosphere (0.1 ppm O3, 0.1 ppm 

SO2, and 101 ug/m2

 H2SO4), failed to support the findings of the epidemiological study. This 
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demonstrates the difficulty of trying to link outcomes of epidemiological studies and controlledexposure studies with pollutant mixtures. 

3.7.8 Populations at Risk/Susceptibility Factors Associated with Ozone Exposure 

 The 1996 CD (2006 CD, p. 8-80) identified several factors that may increase sensitivity 

to O3 of population groups, including: (1) biological variation in responsiveness to O3; (2) 

preexisting lung disease (e.g., asthma); (3) activity patterns (e.g., exertion levels); (4) personal 

exposure history (e.g., time spent indoors v. outdoors); and (5) personal factors (e.g., age, 

nutritional status, gender, smoking history, ethnicity). Based on the information assessed in the 

1996 CD (2006 CD, p. 8-80), population groups that demonstrated increased responsiveness to 

ambient concentrations of O3 consisted of exercising, healthy and asthmatic individuals, 

including children, adolescents, and adults. Since 1996, evidence from controlled-exposure 

human and animal studies, as well as from epidemiological studies, has provided further support 

for these and other susceptibility factors and populations at risk. For example, controlledexposure human studies continue to show differential biological response to O3 based on 

physical activity (exertion) and age. These studies demonstrate a large variation in sensitivity 

and responsiveness to O3, although specific factors that contribute to this intersubject variability 

are yet to be identified. Associations of increased summertime hospital admissions for asthma 

with ambient O3 levels suggest that individuals with these respiratory diseases are populations at 

risk to O3 exposure effects. Also, based on O3-induced differential response in lung 

inflammation and airway responsiveness, asthmatic adults and children appear to have 

potentially increased susceptibility to O3. 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 O3. 

 There is some animal toxicology and limited epidemiologic evidence which has 

demonstrated the importance of genetic background in O3 susceptibility. Genetic and molecular 

characterization studies of experimental animals have identified genetic 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 physical exertion) healthy and asthmatic adults, adolescents, and 

children appear to exhibit increased responsiveness to ambient O3 levels and continue to be 

considered at increased risk of O3-induced health effects. Also, any individual with respiratory 

or cardiovascular disease or any healthy individual who is engaged in vigorous physical activity 

outdoors during periods when O3 levels are high (e.g., active outdoor children) is potentially at 

increased risk to O3-induced health effects. In addition, healthy individuals and those with 
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cardiorespiratory impairment (e.g., those with asthma or cardiovascular disease) who are 

“hyperresponsive” to O3 exposure (i.e., exhibit much higher than normal lung function 

decrements and/or respiratory symptoms) would be considered at greater risk to O3 exposure. 

Finally, individuals who are more likely to be exposed to air pollution while engaged in physical 

activity (e.g., outdoor workers) and those with genetic polymorphisms for antioxidant enzymes 

and inflammatory genes may be at heightened risk of effects of O3 (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 exposure via face mask. Inhalation Toxicol. 

 12: 299-313. 

Adams, W. C. (2000b) Ozone dose-response effects of varied 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 mask 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 pulmonary function decline in asthmatics compared to 

normals. Inhalation Toxicol. 12: 1205-1224. 

American Academy of Pediatrics, Committee on Environmental Health. (2004) Ambient air pollution: health 

hazards to children. Pediatrics 114: 1699-1707. 

American Thoracic Society (1985) Guidelines as to what constitutes an adverse respiratory health effect, with 

special reference to epidemiological studies of air pollution. Am. Rev. Respir. Dis. 131: 666-668. 

American Thoracic Society (1991) Lung function testing: selection of reference values and interpreatative 

strategies. Am. Rev. Respir. Dis. 144: 1202-1218. 

American Thoracic Society (2000) What constitutes an adverse health effect 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.; Bacharova, L.; Schwartz, J.; Katsouyanni, K. (1997) Air pollution and daily 

admissions for chronic obstructive pulmonary 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 O3-induced decreases in FEV1. 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 children 
3-93

attending a southern California summer camp. Presented at: 83rd annual meeting and exhibition of the Air & 

Waste Management Association; June; Pittsburgh, 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. Cambridge, MA: Health Effects Institute; 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 southern Ontario: the acid summer haze 

effect. Environ. Res. 43: 317-331. 

Bates, D. V.; Sizto, R. (1989) The Ontario Air Pollution study: identification of the causative 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-analysis 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 O3-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 health 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-Salazar, G.; Rodríguez-Alcaraz, A.; Gambling, T. M.; García, R.; Osnaya, N.; 

Villarreal-Calderon, A.; Devlin, R. B.; Carson, J. L. (2001) Ultrastructural nasal pathology in children 

chronically and sequentially exposed to air pollutants. Am. J. Respir. Cell Mol. Biol. 24: 132-138. 

Calderón-Garciduenas, L.; Mora-Tiscareno, 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 and 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.; Koutrakis, 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 illnesses 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-inflammatory 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.; House, 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.; Becker, 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 Services, 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.healtheffects.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. Special report. Boston, MA: Health Effects Institute; 

pp. 97-106. Available: http://www.healtheffects.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 function 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 pollution 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.; Bailar, 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 exposure 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. Environ. 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 pollution 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 acidic 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: enhancement 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.; Bromberg, P. A. (2003) Distribution and reproducibility 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) Effects 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) Effect 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.; Steerenberg, 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.; Fischer, 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.; Richter, 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.; Folinsbee, 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 difference 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 mortality. 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.; Villaire, 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 PM10/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 results. 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.; Frischer, T.; Forster, J.; Kuehr, 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 objective test results as responses to air 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 Prevention; 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. (2005) 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.; Miller, 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.; Flanders, 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.; Anderson, 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 effect of ozone on inner-city 

children with asthma: identification of susceptible groups. 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 antioxidant concentrations are not predictive of individual 

responsiveness to ozone: a comparison of healthy and 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 PM10, PN2.5, SO42-, H+, and O3. 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. Cambridge, MA: Health Effects Institute; research report no. 86. 

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. 

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 environmental 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.; Braxton-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]. 

Park, H.; Lee, B.; Ha, E.-H.; Lee, J.-T.; Kim, H.; Hong, Y.-C. (2002) Association of air pollution with school 

absenteeism due to illness. Arch. Pediatr. 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.; Gauderman, 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 with 
3-103

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 Europe. 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 effects of air pollution on health: 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 aeroallergens 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, induces 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 inflammatory 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 competitive 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 Tertre, A.; Piekarksi, T.; 

Ponce de Leon, A.; Pönkä, A.; Rossi, G.; Saez, M.; Schouten, 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, socioeconomic 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.; Antó, 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 Effects 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 Toronto, Ontario: consideration of the role of acid aerosols. Environ. Res. 

65: 271-290. 

Thurston, G. D.; Lippmann, M.; Scott, M. B.; Fine, J. M. (1997) Summertime 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 asthma 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 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. (1996) Air quality criteria for ozone and related photochemical oxidants. 

Research Triangle Park, NC: Office of Research and 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) Research 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.; Bacci, 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 atrial 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.; Montgomery, M. R. (1994c) Ozone increases 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 and 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. (1994) Exacerbations of childhood asthma and ozone pollution 

in Atlanta. Environ. Res. 65: 56-68. 

Wiley, J. A.; Robinson, J. P.; Piazza, T.; Garrett, K.; Cirksena, K.; Cheng, Y.-T.; Martin, 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.; Pladsen, 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 pollution. Environmetrics 16: 481-493. 

Zmirou, D.; Schwartz, J.; Saez, M.; Zanobetti, A.; Wojtyniak, 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 HUMAN EXPOSURE TO OZONE 

4.1 INTRODUCTION 

 As part of the last O3 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 several alternative 8-hr standards. EPA also conducted a health 

risk assessment that produced risk estimates for 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 conducted for the last review (U.S. EPA, 1996a). 

The methodology used to conduct the exposure analysis as well as summary results from the 

exposure analysis are described in this chapter. The exposure analysis technical support 

document, Ozone Population Exposure Analysis for Selected Urban Areas (U.S. EPA, 2007) 

(hereafter cited as “Exposure Analysis TSD”) presents a detailed description of the exposure 

analysis methodology. 

 Population exposures to ambient O3 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 O3 levels in recent years, based on 2002, 2003, and 2004 

ambient air quality measurements. Exposures are also estimated for O3 levels associated with 

just meeting the current 8-hr O3 NAAQS and several potential alternative standards, based on 

adjusting data derived from the ambient monitoring network as described in section 4.5.8. 

Exposures to background levels of O3 are also estimated, based on O3 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 O3 NAAQS review that children are an 

important at-risk group. Two groups at potentially 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 population. Thus, exposure estimates for active children are not 

included in this chapter. 
 4-2 

results are not presented are older adults and outdoor workers. Although older adults are in the 

general population exposure estimates, we did not separately tabulate exposures for older adults 

since we do not have specific exposure-response data for this group. Exposure to outdoor 

workers has not been modeled due to insufficient data to properly characterize 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 model used for this analysis, the 

model input data, and the results of the analysis. The final sections 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 O3 exposure model described in 

this chapter. The uncertainty assessment and a technical description 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 O3 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 O3 include 

studies of people’s activities, work and exercise patterns, physiology, physics and O3-related 

chemistry in microenvironments, atmospheric modeling of O3, chamber studies of atmospheric 

chemistry, and modeling of meteorology. Measurements that have proven to be useful for 

understanding and estimating exposure obtained from personal exposure assessment studies 

include fixed-site ambient concentrations, concentrations in specific indoor and outdoor 

microenvironments, personal exposure levels, personal activity patterns, air exchange rates, 

infiltration rates, deposition and 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 concentration for a specific interval of time,” and 

has units of concentration times time (National Research Council, 1991). For airborne pollutants 

the contact boundary is nasal and 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

[ , ] ( ) 1 2

t

t

E t t C t dt (4-1) 
 4-3 

where E[t1,t2] is the personal exposure during the time period from t1 to t2, 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 breathing rate (ventilation rate) at the time of 

exposure is an important determinant of the dose received by the individual. Although we do not 

estimate dose, we refer to intake as the total amount of O3 inhaled (product of exposure 

concentration, duration, and minute ventilation rate). 

 Personal exposure to O3 can be estimated directly by monitoring the concentration of O3

in the person’s breathing zone (close to the nose/mouth) using a personal exposure monitor. 

Exposure can also be estimated indirectly, by estimating 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 these methods, Equation 4-1 is used to calculate an 

estimate of personal exposure. A key concept in modeling exposure is the microenvironment, a 

term that refers to the immediate surroundings of an individual. A microenvironment is a 

location in which pollutant concentrations are relatively homogeneous for short periods of time. 

Microenvironments can be outdoors or indoors; some examples are outdoors near the home, 

outdoors near the place of work, bedrooms, kitchens, vehicles, stores, restaurants, street-corner 

bus stops, schools, and places of work. A bedroom may be treated as a different 

microenvironment than a kitchen if the concentrations are significantly different in the two 

rooms. The concentrations in a microenvironment typically change over time; for example, O3

concentrations in a kitchen while cooking with a gas stove may be lower than when these 

activities are not being performed, due to scavenging of O3 by nitric oxide (NO) emissions from 

the gas burned. 

 An important factor affecting the concentrations of O3 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 decay rates, and penetration factors. The volumetric 

exchange rate (m3

/hour) is the rate of air exchange between the indoor and outdoor air. The AER

between indoors and outdoors is the number of complete air exchanges per hour and is equal to 

the volumetric exchange rate divided by the volume of the well-mixed indoor air. Indoor 

concentrations of O3 can be decreased by uptake of O3 by surfaces and by chemical reactions. 

The deposition and chemical decay rates are the rates (per hour) at which O3 is removed from 

the air by surface uptake and chemical reactions. Some exposure models employ an infiltration 

factor, which is conceptually useful if distinguishing between the air exchange processes of air 

blowing through open doors and windows and the infiltration 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 O3 exposures and will not be discussed further 

here. Simpler exposure models use a “factor model” approach to estimate indoor O3
 4-4 

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 involve monitoring airborne O3 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 general 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 over a period of hours, days, or weeks. The 

placement of PEMs is important; the desired placement 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 concentrations the individual breathes in. PEMs typically 

report continuously measured O3 concentrations with averaging times ranging from 1 to 24 

hours. 

 The CD reviews O3 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 detection 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 O3 monitors which are part of national, state, and local air monitoring 

networks. In addition to their role of being used to determine which areas are in compliance with 

existing O3 NAAQS, these are also useful for alerting the public to high O3 days, providing air 

quality data in support of photochemical modeling and exposure assessments for a study area, for 

tracking O3 levels and trends, and for studying the representativeness of measurements at these 

monitors for the study area. Existing fixed-site monitors usually report hourly averaged 

concentrations, and are in operation over a period of years. Federal reference and equivalent O3

monitoring methods are required to have a lower detectable limit of 0.01 ppm and precision of 

0.01 ppm for 1-hr average concentrations (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 stationary monitors expressly set up for particular exposure field studies. 

These are used to measure concentrations over time in microenvironments, such as rooms in a 

home, just outside a home, roadsides, and so forth. The stationary monitors which are outdoors 

can provide information about community-scale representativeness 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 collected repeatedly from each individual in the 

study over a period of time, yielding a longitudinal 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 O3. 

 Some studies could be designed 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 studies addressing O3 exposure have not been of random design and the 

measurement averaging times are longer than hourly. They might have specific goals for which 

randomness is not required, or be subject to constraints 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 measuring other parameters that contribute to 

variability in exposure. Typically, microenvironmental measurements include indoor and 

outdoor concentrations of O3 and other pollutants, AERs, infiltration factors, deposition rates, 

decay rates, emissions of O3, NOx, VOCs, and other pollutants, operating characteristics of air 

conditioning systems, and meteorological data such as wind velocity, temperature, and humidity. 

The CD discusses several studies of microenvironments that contribute to our understanding of 

the factors and processes that affect exposure to O3 (CD Appendix AX3, p. 191-216). 

 There is a great deal of variability among individuals 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 O3 indoors can be an important determinant of people’s exposure 

to O3. There are several factors affecting O3 concentrations indoors. The ambient outdoor 

concentration of O3 and the AER are the primary determinants of the indoor concentrations. 

Removal processes are also significant, the most important of which is deposition onto indoor 

surfaces such as carpets, furnishings, and ventilation ductwork. Chemical reactions of O3 with 

other compounds, such as solvents from consumer products or nitric oxide emissions from gas 

stoves, also deplete O3 indoors (Weschler, 2000; Monn, 2001). 

 The primary sources of O3 indoors are O3-generating air cleaners and some photocopiers 

and laser printers. Ozone generators can increase indoor concentrations by more than 0.05 ppm. 

Some older photocopiers, if run continuously in an enclosed area, can increase O3 concentrations 
 4-6 

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 pollutants are typically driven by estimates of 

ambient outdoor concentrations of the pollutants, which vary by time of day as well as by 

location. These outdoor concentration 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 O3 within each urban area, associated with current air 

quality levels and with several potential alternative 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 given population. This section provides a brief 

overview of the model used by EPA to estimate O3 population exposure. Details about the 

application of the model to estimate O3 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 pollutants. 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 O3 NAAQS review (Johnson et al., 1996a; 1996b: 1996c). Since that time 

the model has been restructured, improved, and expanded 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 approach with a probabilistic sampling approach 

focused on individuals, accounting for fatigue and oxygen debt after exercise in the calculation 

of ventilation rates, and a new approach for construction of longitudinal activity patterns for 

simulated persons. Major improvements to data input to the model 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. APEX 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. Figure 4-1 provides a schematic overview of the APEX model. The 

model stochastically generates simulated individuals using census-derived probability 

distributions for demographic characteristics (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 home-to-work commuting flows between tracts.2 

Any number of simulated individuals can be modeled, and collectively they approximate a 

random sampling of people residing 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 the Consolidated Human Activity Database (CHAD) 

(McCurdy et al., 2000; EPA, 2002). The diaries are used to construct a sequence of activity 

events for simulated individuals consistent with their demographic characteristics, day type, and 

season of the year, as defined by ambient temperature regimes (Graham & McCurdy, 2004) 

(Figure 4-1, step 4). The time-location-activity diaries input to APEX contain information 

regarding an individuals’ age, gender, race, employment 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, and temperature as firstorder characteristics. The approach is designed to capture the important attributes contributing to 

an individuals’ behavior, and of particular relevance here, time spent outdoors (Graham and 

McCurdy, 2004). Furthermore, these diary selection criteria give credence to the use of the 

variable data that comprise CHAD (e.g., data collected were from different seasons, different 

states of origin, etc.). APEX calculates the concentration in the microenvironment associated 

with each event in an individual’s activity pattern and sums the event-specific 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 modeling microenvironmental concentrations, where 

the user can define the microenvironments to be modeled and their characteristics. Typical 

indoor microenvironments include residences, schools, and offices. Outdoor microenvironments 

include near roadways, at bus stops, and playgrounds. 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. 
- National

database

- Area-specific

input data

- Intermediate step

or data

- Simulation

step

- Data processor - Output data

Sector location data(latitude, longitude)

Defined study area (sectors within a city radius and with air quality and meteorological data within their radii of influence)

Sector population data 

(age/gender/race)

Population within 

the study area

Commuting flow data

(origin/destination sectors)

Age/gender-specific physiological distribution data (body weight, height, etc)

Distribution functions forprofile variables (e.g, probability of air conditioning)

Locations of air quality and 

meteorological measurements; 

radii of influence

Stochastic 

profile generator

Distribution functions for seasonal and daily varying profile variables (e.g., window status, car speed)

A sfoll• H• W• A• G• Ra• Em• H• H• H• Ca• Ph

(h

2000 Census tract-level data for the entire U.S. (sectors=tracts for the NAAQS ozone exposure application)

Age/gender/tract-speci

employment probabilit

1. Characterize study area 2. Characterize study population 3. Generate N nu

simulated individua

Figure 4-1. Overview of the APEX Model

4-8
Diary events/activities 

and personal information 

(e.g., from CHAD)

Maximum/mean daily

temperature data

Activity diary pools by day 

type/temperature category

Each day in the simulation period is assigned to an activity pool based on day type and temperature category

Selected diary records for each day in the simulation period, resulting in a sequence of events(microenvironments visited, minutes spent, and activity) in the simulation period, for an individual

Stochastic diary 

selector using 

age, gender, and 

employment

Stochastic

calculation of energy

expended per event (adjusted for

physiological limits and EPOC)

and ventilation

rates

Physiological 

parameters from 

profile

Sequence of 

indi

Profile for an 

individual

4. Construct sequence of activity events 

for each simulated individual

Figure 4-1. Overview of the APEX Model, continued

4-9
Hourly air quality 

data for all sectors

Select calculation method for each microenvironment:• Factors• Mass balance

Concentrations for all events 

for each simulated individual

Hourly concentrations and minutes spent in each

microenvironment visited by 

the simulated individual

Average exposuresfor simulated person, stratified by ventilation rate:• Hourly• Daily 1-hour max• Daily 8-hour max• Daily...

Microenvironments defined by 

grouping of CHAD location codes

Calculate hourly

concentrations in

microenvironments

visited

Populatioindicator• Total p• Childre• Asthma

Sequence of events for 

each simulated individual

Calculate

concentrations in all

microenvironments

5. Calculate concentrations in 

microenvironments for all events for 

each simulated individual

6. Calculate hourly 

exposures for each 

simulated individual

7. 

popula

s

Figure 4-1. Overview of the APEX Model, concluded

4-10
 4-11 

 Activity-specific simulated breathing rates of individuals are used in APEX to 

characterize intake received from an exposure. These breathing, or ventilation, rates are derived 

from energy expenditure estimates for each activity included in CHAD and are adjusted for ageand gender-specific physiological parameters associated 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 Physical Activities.” METS are a dimensionless 

ratio of the activity-specific energy expenditure rate to the basal or resting energy expenditure 

rate, and the metric is used by exercise physiologists and clinical nutritionists to estimate work 

undertaken by individuals as they 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 microenvironment are estimated using either a massbalance or transfer factors approach, and the user specifies probability distributions for the 

parameters that are used in the microenvironment model that reflect the observed variabilities in 

the parameters. These distributions can depend on the values of other 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 present, which are also stochastic inputs to the 

model, as well as the ambient temperature. The user can choose to keep the value of a stochastic 

parameter constant for the entire simulation (which 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 distributions 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 microenvironment. 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 microenvironment due to deposition, filtration, and 

chemical degradation; and 

• Emissions from sources of a pollutant inside the microenvironment. 
 4-12 

 The transfer factors model is simpler than the mass balance model, however, still most 

parameters are derived from distributions rather than single values, to account for observed 

variability. It does not calculate concentration in a microenvironment from the concentration in 

the previous hour and it has only two parameters, a proximity factor, used to account for 

proximity of the microenvironment to sources or sinks of pollution, or other systematic 

differences between concentrations just outside 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 essentially 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 exposure concentrations that a simulated individual experiences during 

the modeled time period. APEX estimates the exposure using the concentrations calculated for 

each microenvironment and the time spent in each of a sequence of microenvironments visited 

according to the “activity diary” of each individual. The hourly average exposures of each 

simulated individual are time-weighted averages of the within-hour exposures. From hourly 

exposures, APEX calculates the time series of 8-hr and daily average 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 O3 air pollution. 

Factors that are important include the magnitude and duration of exposure, frequency of repeated 

high exposures, and the breathing rate of individuals at the time of exposure. In this analysis, 

exposure indicators include daily maximum 1-hr and 8-hr average O3 exposures, stratified by a 

measure of the level of exertion at the time of exposure. The level of exertion of individuals 

engaged in particular activities is measured by an equivalent ventilation rate (EVR), ventilation 

normalized by body surface area (BSA, in m2), which is calculated as VE/BSA, where VE 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-m2) 

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 general types of exposure estimates: counts of the estimated 

number of people exposed to a specified O3 concentration level and the number of times per O3

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 O3 season 

to the exposure indicator of interest. In the case where the exposure indicator is a benchmark 

concentration level, the model estimates the number of people who are expected to experience 

exposures to that level of air pollution, or higher, at least once during the modeled period. APEX 

also reports counts of individuals with multiple exposures. The person-occurrences measure 

estimates the number of times per season that individuals 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 measures 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 different 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 incorporates several significant algorithmic 

improvements and updates to input data since it’s predecessor, pNEM, was used in the last 

review. In this section we discuss qualitatively some of the general strengths and limitations of 

the application of APEX to model population exposures to O3 pollution. The discussion is 

divided into four fundamental areas: estimation of ambient air quality, estimation of 

concentrations in microenvironments, characterization of population demographics and activity 

patterns, and modeling physiological processes as applicable to this exposure assessment. 
 4-14 

Additional details for advancements made to the model of specific relevance for this ozone 

exposure assessment are given in section 4.5. 

 In general, limitations and uncertainties result from variability not modeled or modeled 

incorrectly, erroneous or uncertain inputs, errors in coding, simplifications 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 Ambient Air Quality 

 For estimating ambient O3 concentrations to use in the exposure model, the urban areas 

modeled here have several monitors measuring hourly O3 concentrations. Having multiple 

monitors in the simulated areas collecting time-resolved 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 contact of individuals with these spatially 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 interpolation of actual data points) and from the method used to estimate 

missing data. In addition, concentrations of O3 near roadways are particularly difficult to 

estimate due to the rapid reaction of O3 with nitric oxide emitted from motor vehicles. 

 We have modeled the O3 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, O3

concentrations were lower in 2004 than previous years, due to a combination of reduced 

emissions of precursors and weather patterns less conducive to the formation of O3. 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 estimating 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 uncertainties involved with modeling historical 

scenarios, the uncertainties of the complex process of projecting to future years air quality, 

population demographics, activity patterns, and other changing parameters. For the purpose of 

estimating population exposure as an input to decisions about the appropriate level of a NAAQS, 

EPA has historically not incorporated any projections 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 on 
 4-15 

population exposure and public health while avoiding 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, restaurants, vehicles) is underscored by the finding that personal 

exposure measurements of O3 are often not well-correlated with ambient measurements (CD, 

pages 3-59 to 3-61). 

 APEX has been designed to better estimate human exposure through use of algorithms 

that attempt to capture the full range of O3 concentrations expected within several important 

microenvironments. Parameters used to estimate the concentrations in microenvironments can 

be highly variable, both between microenvironments (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 variabilities would not result in uncertainties in the 

estimation of the microenvironmental concentrations. Thus, it is the input data used in 

development of the parameters that are the limiting factor, and to date, APEX uses the most 

current available data to develop 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 O3. AERs are highly variable, both within a 

microenvironment over time and between microenvironments 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 probabilistic 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 influencing AER distributions (see Appendix A of the Exposure Analysis 

TSD). 

Removal Processes 

 Concentrations within indoor microenvironments can be reduced due to removal 

processes such as deposition to surfaces and by reaction with other chemicals in the air. The rate 

of deposition of O3 to a surface depends on the surface composition, the humidity, and the 

concentration of O3. The rate of removal of O3 from a microenvironment depends on its 

dimensions, the ratio of surface area to volume, and of course the presence, amount, and type of 
 4-16 

surface coverings and furnishings in the microenvironment. Deposition is modeled 

probabilistically in APEX by a using a distribution of decay rates derived from a study that 

measured decay rates in 26 homes in Southern California (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 variability in decay rates is not anticipated to be a 

large contributor to the uncertainty in the modeling results. There can be additional O3 loss, 

which is not currently modeled, due to the use of HVAC systems, which significantly increase 

the effective surface area as air recirculates through ductwork and filters. 

 Ozone reacts with a number of indoor pollutants, such as nitric oxide from gas stoves and 

VOCs from consumer products. With the exception of nitric oxide, O3 reacts slowly with most 

indoor pollutants, and this is typically a less influential removal process than air exchange and 

surface removal (Weschler, 2000). The lack of a better treatment of indoor air chemistry is not 

considered to be a significant limitation of APEX for modeling O3. 

4.3.4.3 Characterization of Population Demographics and Activity Patterns 

 The approach to reasonably estimating exposure considering a variety of alternative 

scenarios is best done using models that better represent the contact of a human with the 

contaminant of concern. By using actual time-location-activity diaries that capture the duration 

and frequency of occurrence of visitations/activities performed, APEX can simulate expected 

variability in human behavior, both within and between individuals. Fundamentals of energy 

expenditure are then used to estimate relative intensity of activities performed. This, combined 

with microenvironmental concentrations, allows for the reasonable estimation of the magnitude, 

frequency, pattern, and duration of exposures an individual experiences. 

 CHAD is the best source of human activity 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 geographically diverse, containing diaries from individuals 

residing in major cities, suburban and rural areas 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 database, however, many of which are founded in the 

individual studies from which activity patterns were derived (Graham and McCurdy, 2004). A 

few questions remain regarding the representativeness 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 structure differences (i.e., real-time versus recall method 
 4-17 

of data collection). Many of the assumptions about use of these activity patterns in exposure 

modeling are strengthened by the manner in which they are used by APEX, through focusing on 

the most important individual attributes that contribute 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 database provides a balanced representation of 

the population being modeled is likely to vary across areas. Although the algorithm that 

constructs activity sequences accounts to some extent for the effects 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 developed to more appropriately 

assign individual diaries to reflect time-location-activity patterns in simulated individuals 

(discussed further in section 4.5.3). Input distributions 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 application 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 limitations in approximating within-person variance and betweenperson variance for certain variables (e.g., time spent outdoors). Personal activity patterns are 

also likely to be affected by many local factors, 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 exposure and intake of 

O3 is a complicated endeavor, particularly when attempting to capture inter- and intra-personal 

variability in these rates. APEX has a physiological module capable of estimating ventilation 

rates (VE) for every activity performed by an individual, which primarily drives O3 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 energy expenditure and 

oxygen consumption rate, thus both within- and between-person variability in ventilation can be 

addressed through utilization of the unique sequence of events individuals go through each 

simulated day. These activity-specific VE estimates, when normalized by BSA, are then used to 

characterize an individual’s exertion level in compiling the summary exposure tables (Table 

4-1). One of the key determinants of estimated VE is the exertion level of an individual’s 

activity, where exertion levels have units of metabolic equivalents of work (MET), which is the 

ratio of energy expenditure for an activity to the person’s basal, or resting, metabolic rate. 
 4-18 

 There are some limitations in using MET values 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 (or their caregiver if younger than eight years old) would record 

the activity performed with a start and end time, with no information on the associated exertion 

level of the activity. Exertion level (MET) was then inferred by developers of the CHAD 

database (McCurdy et al., 2000) using standard values 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 activity levels fluctuate widely within a single 

activity category; their pattern is often characterized as having bursts of high energy expenditure 

within a longer time frame of less energy expenditure (Freedson, 1989). These fluctuations in 

energy expenditure that occur within an activity (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 takes into consideration 

the location of O3 epidemiological studies, the availability of ambient O3 data, and the desire to 

represent a range of geographic areas, population demographics, and O3 climatology. These 

selection criteria are discussed further in Chapter 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 O3 seasons for which routine hourly O3 monitoring 

data are available. These periods include most of the high-ozone events 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 general population residing in each area 

modeled, as well as for school-age children (ages 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 O3-related health effects. We report results 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 these younger children into account in our analysis 

due to a lack of information which would let us characterize this group of children. 

 The population of asthmatic children is estimated for each city using asthma prevalence 

data from the National Health Interview Survey (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 regions 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 those 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 into account the survey design. A scatter plot smoothing technique 

using the LOESS smoother was applied to smooth the prevalence curves and compute the 

standard errors and confidence intervals for the smoothed prevalence estimates. Logistic 

analysis of the prevalence curves shows statistically significant differences in prevalence by 
 4-20 

gender and by region. Therefore we did not combine the prevalence rates for different genders 

or regions. A detailed description 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 represent 40 percent of the total U.S. urban 

population (approximately 222 million in 2000). Table 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 

children1

(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 and the derivation of input distributions can be 

found in the Exposure Analysis TSD. 

4.5.1 Population Demographics 

 APEX takes population characteristics into account to develop accurate representations of 

study area demographics. Population counts and employment probabilities by age and gender 

are used to develop representative profiles of hypothetical individuals for the simulation. Tractlevel population counts by age in one-year increments, from birth to 99 years, come from the 
 4-21 

2000 Census of Population and Housing Summary File 1. The Summary File 1 contains the 100-

percent data, which is the information compiled from 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 included commuting to and from school. This 

results in the implicit assumption that children attend a school with ambient O3 concentrations 

similar to concentrations near their residence. To the extent that the highest ozone levels are 

generally in the period June through August when most students are not in school, the absence of 

school commuting is less likely to have a significant 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 persons with home-to-work distances up to 120 km are daily 

commuters, and that persons who travel further than 120 km do not commute daily. Therefore 

the list of commuting destinations for each home tract is restricted to only those work tracts that 

are within 120 km of the home tract. 

 APEX allows the user to specify how to handle individuals who commute to destinations 

outside the study area. One option is to drop them from the simulation. If they are included, the 

user specifies values for two additional parameters, called LM and LA (Multiplicative and 

Additive factors for commuters who Leave 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 are inside the study area). Instead, it is assumed to be related to 

the average concentration CAVE (t) over all air districts at the time in question. The ambient 

concentration outside the study area at time t, COUT (t), is estimated as: 

COUT (t) = LM * CAVE (t) + LA (4-2) 
 4-22 

 The microenvironmental concentration (for example, 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 LM and LA were both set to zero for this modeling 

analysis; thus, exposures to individuals 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 ambient concentrations of O3 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 includes data from several surveys covering specific 

time periods at city, state, and national levels, with varying degrees of representativeness. Table 

4-4 summarizes the studies in CHAD used in this modeling analysis, 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 O3-season 

or year-long activity sequences for individuals based on a cross-sectional activity data base of 

24-hour records. The typical subject in the time/activity studies in CHAD provided less than two 

days of diary data. For this reason, the construction 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 approach 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 activities, 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 set to the amount of time an individual spends outdoors each day, 

which is one of the most important determinants of exposure to high levels of O3. 

 The actual diary construction method targets two 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 between-person variance in the key variable. The A

statistic quantifies the lag-one (day-to-day) key variable 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 preserve 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 outdoor 
 4-23 

Table 4-4. Studies in CHAD used in this analysis Study name Geographic 

coverage 

Study time period 

Subjectages 

Diarydays Diary-days (ages 5-18) Diary type and study design Re

Baltimore One building 

in Baltimore 

01/1997-02/1997, 07/1998-08/1998 

72 - 93 292 0 Diary Wi

California Adolescents (CARB) 

California 10/1987-09/1988 12 - 17 181 181 Recall; Random Ro

Wi

California Adults (CARB) 

California 10/1987-09/1988 18 - 94 1,552 36 Recall; Random Ro

Wi

California Children (CARB) 

California 04/1989- 02/1990 <1 - 11 1,200 683 Recall; Random Wi

Cincinnati (EPRI) Cincinnati 

metro. area 

03/1985-04/1985, 08/1985 

<1 - 86 2,587 740 Diary; Random Joh

Denver (EPA) Denver 

metro. area 

11/1982- 02/1983 18 - 70 791 7 Diary; Random Joh

et a

Los Angeles: Elementary School 

Los Angeles 10/1989 10 - 12 51 51 Diary Sp

Los Angeles: High School 

Los Angeles 09/1990-10/1990 13 - 17 42 42 Diary Sp

National: NHAPS-Air National 09/1992-10/1994 <1 - 93 4,326 634 Recall; Random Kle

Ts

National: NHAPSWater National 09/1992-10/1994 <1 - 93 4,332 691 Recall; Random Kl

Ts

Washington, D.C. (EPA) 

Wash., D.C. metro. area 

11/1982-02/1983 18 - 98 639 10 Diary; Random Ha

Ak

Total diary days 15,993 3,075 
 4-24 

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 others outside the study age range, these values are used for all 

ages. This new method for constructing longitudinal diaries from the CHAD data is described in 

detail in the Exposure Analysis TSD. 

4.5.4 Physiological Data 

 APEX requires values for various physiological 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 physiological 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 maximum oxygen consumption potential), body mass, 

resting metabolic rate, and oxygen consumption-to-ventilation rate relationships. 

4.5.5 Microenvironments Modeled 

 In APEX, microenvironments provide the exposure 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 located on a daily and hourly basis. As discussed 

in section 4.3.2 above, the two methods available in APEX for calculating pollutant concentrations 

within microenvironments are a mass balance model and a transfer factor approach. Table 4-5 

lists the 12 microenvironments selected for this analysis and the 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 the 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 clearly demonstrates that the AER distributions vary 

greatly across cities and A/C types and temperatures, so that the selected 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 mean AER for residences without A/C ranges 

from 0.46 for San Francisco on days with temperature between 10 and 20 oC to 2.29 for 
 4-25 

Table 4-5. Microenvironments modeled by APEX 

Microenvironment Calculation Method Parameters1

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 and 25 oC. The need to account for the city as 

well as the A/C type and temperature is illustrated 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 combination 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. Generally, the lognormal distribution was the bestfitting of the four distributions, and so, for consistency, 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 comparisons demonstrate that the AER distributions 

depend upon the city as well as the temperature 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 description 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 final AER distributions used for the exposure 

modeling are given the Exposure Analysis TSD. 
 4-26 

 Some residences, particularly in the Southwest, use evaporative coolers, also known as 

“swamp coolers,” for cooling. We performed an analysis of AER distributions of residences 

without A/C, with and without evaporative coolers, using data from three AER measurement 

studies. This comparison is described in Appendix 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 presence 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-residential, 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; Persily 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 SF6 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 ventilation, in a large number of randomly selected office buildings 

throughout the U.S. This data base consists of a total of 390 AER measurements in 96 large, 

mechanically ventilated offices. AERs were measured both by a volumetric method and by a 

CO2 ratio method, and included their 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 individual measurements, to account for the strong 

dependence of the AER measurements for the same office space over a relatively short period. 

The mean values are similar for the two studies, but the standard deviations are about twice as 

high for the Persily data. The proposed AER distributions were derived from the more recent 

Persily data only. 

 We fitted exponential, lognormal, normal, and 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 distributions for the indoor non-residential 

microenvironments, can be found in the Exposure Analysis TSD. 
 4-27 

4.5.5.3 Proximity and Penetration Factors for Outdoors and In-vehicle 

Microenvironments 

 For the outdoors near-road, public garage/parking lot, and in-vehicle proximity factors, 

and for the in-vehicle penetration factors, we use distributions developed 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 according to an experimental design 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 urban arterial roads (urban), and local 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 vehicle, 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 O3 decay and deposition rates was obtained from the analysis 

of measurements from a study by Lee et al. (1999). This study measured decay rates in the 

living rooms of 43 residences in Southern California. Measurements 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 study, 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 temperatures were obtained from hourly surface 

temperature measurements obtained from the National 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 for indoor microenvironments. 
 4-28 

4.5.7 Ambient Ozone Concentrations 

 APEX requires hourly ambient O3 concentrations at a set of locations in the study area. 

Data from EPA’s AIRS Air Quality Subsystem were used to prepare the ambient air quality 

input files for 2002, 2003, and 2004. The hourly O3 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 described 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 O3 standard of 0.08 

ppm, and considering the previous rounding convention that allowed for concentrations up to 

0.084 ppm. Several alternative standards, reflecting different combinations of standard levels 

and form were also considered. Alternatives examined were intended to reflect improved 

precision in the measurement of the ambient concentrations, 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 4th

daily maximum 8-hr average scenario currently used. For example, a 3rd-highest form (the 

average of the annual 3rd-highest daily maximum 8-hour concentrations averaged over the three 

year period) was considered for 0.084 and 0.074 ppm levels, and a 5th-highest form for the 0.074 

ppm level (the average of the annual 5th-highest daily maximum 8-hour concentrations averaged 

over the three year period). These alternative scenarios are modeled using a quadratic rollback 

approach to adjust the hourly O3 concentrations observed in 2002-2004 to yield a design value 

corresponding to the standard being modeled. Table 4-6 shows the attainment thresholds (to 

which the design values are rolled back), the form of the standard used for each scenario, and the 

notation used in the remainder of this chapter. Design values for the current 8-hr O3 standard are 

calculated as the 3-year averages of the annual 4th-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 concentrations near ambient background levels. The 

quadratic rollback adjustment procedure was considered in a sensitivity analysis during the last 

review of the O3 NAAQS and has been shown to be more realistic than the linear proportional 

rollback method, where all of the ambient measurements 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 3rd-highest form 

4th-highest form 

84/3 

84/4 

0.080 ppm 4th-highest form 80/4 

0.074 ppm 

3rd-highest form 

4th-highest form 

5th-highest form 

74/3 

74/4 

74/5 

0.070 ppm 4th-highest form 70/4 

0.064 ppm 4th-highest form 64/4 

Table 4-7. 2002-2004 8-hr ozone design values for the modeled areas 

Urban Area (CSA) 2002-2004 design 

value1

 (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 model 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 O3

NAAQS, completed in 1997. 

 Second, we report the results of a limited APEX model evaluation, which involves the 

comparison of model exposure estimates to personal 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 model 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 this 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 uncertainties of the exposure modeling was performed, 

and the results of that analysis are described here. At the end of this section, the conclusions 

drawn from the evaluation, sensitivity, and 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 discussed in Section 4.3.1. In the previous review, six urban areas 

were modeled using the pNEM model, Houston, Los Angeles, New York, Philadelphia, St. 

Louis, and Washington (U.S. EPA, 1996a,c). These six cities (as well as six others) are also 

modeled in the current review, although the geographic 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 will be more people exposed, but a smaller 

percentage of the modeled population will be exposed at high levels, if O3 concentrations are 

lower in the extended areas. Typical years, in terms of O3 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 the 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 quantitative comparison of the exposure results is not 

appropriate. 
 4-31 

4.6.2 Comparison of Model Estimates with Measured Personal Exposures 

APEX simulation results were compared to personal O3 concentration measurements 

obtained from the Harvard Southern California Chronic Ozone Exposure Study (Xue et al. 2004, 

Geyh et al. 2000). Although this study was limited 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 

O3 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 O3 concentrations were collected in at least 6 of the 12 months of the study period. 

Passive O3 samplers were used to measure 6-day or 7-day average personal O3 concentrations, as 

well as indoor and outdoor concentrations at participants’ homes, for six days each month. The 

subjects resided in two separate areas of San Bernardino County: urban Upland CA, and the 

small mountain towns of Lake Arrowhead, Crestline, 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 same 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 measurements taken in Sacramento and the inland 

portions of the Los Angeles area: Riverside and San Bernardino Counties. The hourly outdoor 

O3 concentrations were from fixed site monitors located in Upland and Crestline. 

 For each period for which personal measurements 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 concentrations was compared to the corresponding 

distribution of measured values, 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 concentration estimates during the times of exposure, and between the O3

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 Upland and for Lake Arrowhead, Crestline, and 

Running Springs. 

 Variability in exposure is reasonably estimated by APEX across the population, although 

the APEX predictions tend to have a lower variance than the measured values. The mean
 4-32 

Figure 4-2. Modeled and measured weekly average personal exposures: means, minima, 

maxima for each week. Upland, CA. 

Figure 4-3. Modeled and measured weekly average 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 Lake 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 exposures, although the underprediction of variance 

indicates that APEX may be underpredicting 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 described in the Exposure Assessment TSD. 

4.6.3.1 Near-Road Residential Exposures 

 APEX does not take into account the effects of mobile source emissions of NO on the 

concentrations of O3 in residences near roadways; therefore, we conducted a sensitivity analysis 

to assess the potential effect on exposures in residences of the titration of O3 by mobile source 

NO. We performed APEX simulations for the Boston and Houston 2002 base cases for each of 

these three subsets of the population, 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 O3 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 indoors, 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 analysis assessed the effect of 
 4-34 

potential biases in the values used in the APEX exposure modeling. APEX simulations for the 

Boston 2002 base case and current standard scenarios 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 distributions simultaneously by +0.1 and by −0.1. Biases of these 

magnitudes in these parameters turn out to have little effect on the high 8-hour average 

exposures predicted by APEX. For example, changes in the percents of children experiencing 

exposures over 0.06, 0.07, and 0.08 ppm-8hr change by less than one percentage point. 

4.6.3.3 Activity Patterns: Representativeness of CHAD 

 Many of the studies included in the CHAD data base are not national in scope, nor do 

they necessarily correspond to the modeled urban areas, and we conducted an analysis to assess 

how similar the exposure results are when using individual component studies. Strong similarity 

would suggest that extrapolation of activity data gathered 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), and we compared the APEX exposure results 

using all of CHAD with corresponding 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 described in the Exposure Assessment TSD. 

 APEX simulations were performed using only 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 reductions in exposures to children at moderate 

exertion in going from the base case to the current standard is presented in Table 4-9. 

 There is good agreement between the APEX predictions of the reductions in exposures 

from the current base case to the current standard, whether all of CHAD or only the NHAPS 

component of CHAD is used, indicating that these 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: Underestimation of Repeated Exposures 

 Not only is the actual exposure level important 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 repeated exposure results generated by APEX, 
 4-35 

Table 4-8. Comparison of APEX 2002 base case simulations: 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 

reduction1

 from the 2002 base case to the current standard of the number 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 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 exposures estimated by APEX for those urban areas 

was performed. 

Due to data limitations, APEX has not been set 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 the corresponding APEX estimates for all workers 

reveals that APEX significantly underestimates the number of multiple exposures for working 

adults. For example, in Atlanta, APEX estimates 490,000 workers to be exposed at least once to 

levels above 0.07 ppm-8hr in 2002; however, only 220 were estimated 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 estimates 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 outdoor 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 Atlanta 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 workers 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 Sacramento, 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 been 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 similarity of daily activities for a given simulated 

individual in terms of the time spent outdoors, and some simulated individuals tend to spend 
 4-37 

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 simulated individuals representing 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 children 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 analyses addressing different aspects of the overall uncertainty. 

A Monte Carlo analysis was performed which accounts for most of the uncertainties of the 

APEX model inputs. Sensitivity analyses have been conducted to address the potential influence 

of other sources of uncertainty, described in the previous section. This section provides a 

summary of the results of the exposure modeling uncertainty analysis; the details of the 

uncertainty analysis are described in Langstaff (2007). 

 A Monte Carlo approach was selected for a detailed uncertainty analyses. Monte Carlo 

methods for analysis of model uncertainty use statistical sampling techniques to estimate 

statistics which characterize uncertainty. Essentially, a Monte Carlo approach entails performing 

many model runs with model inputs randomly sampled from distributions reflecting the 

uncertainty of the inputs. This propagates the uncertainty of the model inputs through to the 

model results, taking into account input parameter 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 model result as the interval from the 2.5th to the 97.5th percentile of 

the uncertainty distribution for that result. 

 The Monte Carlo uncertainty analysis performed 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 convergence 
 4-38 

 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 the current standard. Uncertainties of model results for other areas 

and years are expected to be similar. 

 Figure 4-4 illustrates the uncertainty distributions for one model result, the percent of 

children with exposures above 0.06 ppm-8hr while at moderate exertion. This distribution 

results from approximately 2000 Monte Carlo APEX 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 estimates of the model inputs, as 

described in Section 4.5. The corresponding result 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 other 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 children

Number of Monte Carlo simulations

Figure 4-4. Uncertainty of percent of children 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 children

Number 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 children

Number of Monte Carlo simulations

Figure 4-5. Uncertainty of percent of children with exposures above 0.07 ppm-8hr (Boston 

2002 base case) 

Figure 4-6. Uncertainty of percent of children 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 children with exposures above different 8-hour 

exposure levels under moderate exertion. The UIs for the estimated reductions in exposures, 

going from the 2002 base case to the current standard, 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 points of the UI endpoints. The 

uncertainties of the exposures to asthmatic children 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 estimated 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 estimated 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 current 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 information and the spatial interpolation of ambient 

concentrations from monitoring sites to other locations. The primary findings of these analysis 

are the following: 

• The Monte Carlo analysis of the uncertainties of the APEX model estimates of exposure 

distributions indicates that the uncertainty is relatively small. The APEX estimates of the 

percent of children or asthmatic children with exposures above 0.06, 0.07, or 0.08 ppm8hr under moderate exertion have 95% uncertainty intervals of at most ±6 percentage 

points. 

• An investigation into the representativeness of the CHAD activity diaries with respect to 

the specific urban areas and time periods modeled indicates uncertainties of only a few 

percent in the APEX estimates of the numbers of children with exposures above 0.06, 

0.07, or 0.08 ppm-8hr under moderate exertion. 

• Although the effect on exposures in residences of the titration of O3 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 frequency of occurrence of individuals 

experiencing repeated 8-hour average exposures greater than 0.06, 0.07, and 0.08 ppm8hr. The reasons for this are understood, and further research will be required to address 

this. 
 4-42 
 4-43 

4.7 EXPOSURE ASSESSMENT RESULTS 

4.7.1 APEX Modeling Results 

 The results of the exposure analysis4

 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 concentrations in the air quality 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. Exposure results are presented 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 Paper 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 for 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 exposures above 0.080, 0.070, and 0.060 ppm-8hr. A 

few notes regarding the exhibits are necessary to mention. Exposure 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 characterized by breathing rates, as described in section 

4.3.3. Results for children exposed to O3 while engaged in moderate exertion are presented in 

each of the subsequent exhibits, however results 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, asthmatic 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 estimates). Exposure estimates for year 2003 

generally fell in between the exposures estimated 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

40

Percent of subgroup with 1 or more 

exposures >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 standard, 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

40

Percent of children with 1 or more 

exposures >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 for the alternative standards is defined in Table 

4-6. Exposures were also estimated using the respective year air quality data without application 

of the rollback procedure, and are presented as the “base” scenario in each exhibit. The numbers 

for the base scenarios are omitted from some of the figures within the exhibits (i.e., the numbers 

of children and person days) since they increased the vertical scale, obscuring the details of 

interest. 

 The patterns of estimated exposures are variable 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 areas 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 O3. 

 Inspection of these exhibits shows marked differences between urban areas in the levels 

of exposures under alternative standards. For example, under the same 0.074 ppm, 4th daily 

maximum 8-hr average alternative standard, it is estimated that 10 percent of the Boston children 

but very few of the Los Angeles children experience 8-hr O3 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 4th-highest concentrations for Boston compared to the rest of its air quality 

distribution, which in general, allowed for retention of higher concentrations within the air 

quality distribution (and therefore exposures) following the rollback of the air quality. In Los 

Angeles, much more of the upper range of the air quality distribution needed to be rolled back to 

allow for the meeting of the alternative standards, thus significantly reducing the frequency of 

occurrence of high ambient concentrations (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 benchmark level selected and year of air quality 

data used. For example in considering the series of 74/x scenarios (74/5, 74/4, 74/3), the impact 

could be a low as a few percent (percent of children with estimated exposures 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 air quality go from, on average, 28% to 21%)
 4-46 

Exhibit 1. Summary of exposure metrics regarding 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 exposure 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%

Chicago 17% 3% 2% 1% 0% 0% 0% 0% 0%

Cleveland 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 Angeles 16% 0% 0% 0% 0% 0% 0% 0% 0%

New York 28% 3% 2% 1% 0% 0% 0% 0% 0%

Philadelphia 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%

Washington 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

40

Percent of children with 1 or more 

exposures >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+5

Number of children with 

exposures >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+5

Number of children person days with 

exposures >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 exposure 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%

Chicago 44% 20% 15% 12% 6% 3% 2% 1% 0%

Cleveland 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 Angeles 36% 1% 1% 0% 0% 0% 0% 0% 0%

New York 54% 16% 13% 9% 2% 3% 2% 1% 0%

Philadelphia 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%

Washington 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

70

Percent of children with 1 or more 

exposures >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+5

Number of children with 

exposures >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+5

Number of children person days with 

exposures >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 exposure 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%

Chicago 69% 53% 48% 44% 37% 28% 23% 17% 3%

Cleveland 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 Angeles 61% 7% 6% 4% 1% 1% 1% 0% 0%

New York 74% 50% 46% 41% 23% 25% 21% 15% 3%

Philadelphia 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%

Washington 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

80

Percent of children with 1 or more 

exposures >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+6

Number of children with 

exposures >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+6

Number of children person days with 

exposures >0.06 ppm-8hr

Alternative

Standard

City

3-C) 

3-D) 
 4-52 

Exhibit 4. Summary of exposure metrics regarding 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 exposure 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%

Chicago 1% 0% . . . 0% . . 0%

Cleveland 11% 1% . . . 0% . . 0%

Detroit 16% 1% . . . 0% . . 0%

Houston 18% 0% . . . 0% . . 0%

Los Angeles 26% 0% . . . 0% . . 0%

New York 13% 1% . . . 0% . . 0%

Philadelphia 14% 3% . . . 0% . . 0%

Sacramento 8% 0% . . . 0% . . 0%

St. Louis 8% 2% . . . 0% . . 0%

Washington 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

30

Percent of children with 1 or more 

exposures >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+4

Number of children with 

exposures >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+4

Number of children person days with 

exposures >0.08 ppm-8hr

Alternative

Standard

City

4-C) 

4-D) 
 4-54 

Exhibit 5. Summary of exposure metrics regarding 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 exposure 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%

Chicago 10% 4% . . . 0% . . 0%

Cleveland 25% 8% . . . 1% . . 0%

Detroit 32% 7% . . . 1% . . 0%

Houston 42% 3% . . . 0% . . 0%

Los Angeles 49% 1% . . . 0% . . 0%

New York 31% 6% . . . 0% . . 0%

Philadelphia 32% 10% . . . 2% . . 0%

Sacramento 28% 2% . . . 0% . . 0%

St. Louis 24% 11% . . . 2% . . 0%

Washington 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

50

Percent of children with 1 or more 

exposures >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+5

Number of children with 

exposures >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+5

Number of children person days with 

exposures >0.07 ppm-8hr

Alternative

Standard

City

5-C) 

5-D) 
 4-56 

Exhibit 6. Summary of exposure metrics regarding 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 exposure 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%

Chicago 37% 26% . . . 7% . . 0%

Cleveland 49% 22% . . . 9% . . 0%

Detroit 56% 26% . . . 10% . . 0%

Houston 67% 19% . . . 4% . . 0%

Los Angeles 71% 8% . . . 2% . . 0%

New York 57% 24% . . . 7% . . 0%

Philadelphia 58% 33% . . . 11% . . 1%

Sacramento 59% 15% . . . 3% . . 0%

St. Louis 54% 39% . . . 15% . . 1%

Washington 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

80

Percent of children with 1 or more 

exposures >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+6

Number of children with 

exposures >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+6

Number of children person days with 

exposures >0.06 ppm-8hr

Alternative

Standard

City

6-C) 

6-D) 
 4-58 

Exhibit 7. Summary of exposure metrics regarding 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 exposure 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%

Chicago 0% 0% 0% 0% 0% 0% 0% 0% 0%

Cleveland 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 Angeles 14% 0% 0% 0% 0% 0% 0% 0% 0%

New York 2% 0% 0% 0% 0% 0% 0% 0% 0%

Philadelphia 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%

Washington 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

15

Percent of children with 1 or more 

exposures >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+4

Number of children with 

exposures >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+4

Number of children person days with 

exposures >0.08 ppm-8hr

Alternative

Standard

City

7-C) 

7-D) 
 4-60 

Exhibit 8. Summary of exposure metrics regarding 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 exposure 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%

Chicago 1% 0% 0% 0% 0% 0% 0% 0% 0%

Cleveland 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 Angeles 38% 0% 0% 0% 0% 0% 0% 0% 0%

New York 11% 0% 0% 0% 0% 0% 0% 0% 0%

Philadelphia 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%

Washington 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

40

Percent of children with 1 or more 

exposures >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+4

Number of children with 

exposures >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+4

Number of children person days with 

exposures >0.07 ppm-8hr

Alternative

Standard

City

8-C) 

8-D) 
 4-62 

Exhibit 9. Summary of exposure metrics regarding 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 exposure 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%

Chicago 12% 1% 0% 0% 0% 0% 0% 0% 0%

Cleveland 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 Angeles 69% 5% 4% 3% 1% 1% 1% 0% 0%

New York 35% 6% 4% 3% 0% 0% 0% 0% 0%

Philadelphia 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%

Washington 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

70

Percent of children with 1 or more 

exposures >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+5

Number of children with 

exposures >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+5

Number of children person days with 

exposures >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 exposures pose a greater health concern than 

single exposures. However, multiple repeated exposures are underestimated by APEX 

(discussed previously in the model evaluation 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 percent of children experiencing 1, 2, and 3 or more 

repeated exposures above 0.080, 0.070, and 0.060 ppm-8hr, respectively, concomitant with 

moderate or greater exertion, for each of the urban areas modeled, based on rollback of 2002 O3

concentrations. When considering the alternative standard scenarios, clear trends are evident. 

The reduction in both the number of those experiencing exposures above a given benchmark 

level and the frequency of occurrence of those exceedances is directly correlated with the 

standard level.
 4-65 

exposur es 12

3 +

ATLA

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 12

3 +

ATLA

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, based on 2002 air quality. 
 4-67 

exposur es 12

3 +

ATLA

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 and 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/O3 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/StatusOfPreschoolPolicyInTheStates.doc 

CARB (2005). Review of the California Ambient Air Quality Standard for Ozone. California 

Environmental Protection Agency Air Resources Board. Available at: 

http://www.arb.ca.gov/research/aaqs/ozone-rs/rev-staff/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 Health Statistics. Vital Health Stat 10(223). 

Available at: http://www.cdc.gov/nchs/data/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 Emission Controls. Presented at the Air and 

Waste Management Annual Meeting, San Diego, CA. June 14-18, 1998. 

Freedson, P. S. (1989). Field monitoring 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: assessing ozone exposure of grade-school-age children in 

two southern California communities. Environ Health Perspect. 108: 265-270. 

Graham, S. E. and McCurdy, T. (2004). Developing 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 Carbon Monoxide Exposure of Residents of 

Washington, DC and Denver, Colorado. Research Triangle Park, NC: U.S. Environmental 

Protection Agency, Office of Research and 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. Environmental Protection Agency, Environmental 

Monitoring Systems Laboratory. EPA-600/4-84-014. 

Johnson, T. (1989). Human Activity Patterns in Cincinnati, 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, Research Triangle Park, North Carolina. 

Johnson, T., Capel, J., McCoy, M. (1996a). Estimation of Ozone Exposures Experienced by 

Urban Residents Using a Probabilistic Version of NEM and 1990 Population Data. 

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. (1996b). Estimation of Ozone Exposures 

Experienced by Outdoor Children in Nine Urban Areas Using 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 Workers in Nine Urban Areas Using a Probabilistic Version of 

NEM. 1996. 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., Pakrasi, A., Wisbeth, A., Meiners, G., Ollison, W. (1995). Ozone exposures Within 

Motor Vehicles – Results of a Field Study in Cincinnati, Ohio. Proceedings 88th 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 Protection Agency, Office of Research and 

Development. EPA/600/R-96/074. 

Langstaff, J. E. (2007). OAQPS Staff Memorandum 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/standards/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. 
 4-70 

Lioy, 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 multi-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 pollutants: 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. Washington, DC: National Academy of Sciences. 

OMB (2005). Update of Statistical 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). Ventilation Design and Performance in U.S. Office 

Buildings. ASHRAE Journal. April 2005, 30-35. 

Richmond H., Palma, T, Langstaff, J., McCurdy, T., Glenn, G., Smith, L. (2002). Further 

Refinements and Testing of APEX (3.0): EPA's population exposure model for criteria and 

air toxic inhalation exposures. Joint meeting of the International 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/standards/ozone/s_o3_cr_td.html

Rizzo, M. (2006). A Distributional Comparison between Different Rollback Methodologies 

Applied to Ambient Ozone Concentrations. May 31, 2006. Available at: 

http://www.epa.gov/ttn/naaqs/standards/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 Implications for Potential Exposure to Pollution. 

California Air Resources Board, Sacramento, CA. CARB-A6-177-33. 

Spier, C. E., Little, D. E., Trim, S. C., Johnson, 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). Descriptive Statistics Tables from a Detailed Analysis 

of the National Human Activity Pattern Survey (NHAPS) Data. U.S. Environmental 

Protection Agency. EPA/600/R-96/148. 

Turk, B. H., Grimsrud, D. T., Brown, J. T., Geisling-Sobotka, K. L., Harrison, J., Prill, R. J. 

(1989). Commercial Building Ventilation Rates and Particle Concentrations. ASHRAE 

No. 3248. 

U.S. Department of Transportation and U.S. Census 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, Environmental Criteria and Assessment Office, 

U.S. Environmental Protection Agency, Research Triangle Park, NC. EPA-600/8-84-

020aF-eF. Available from: NTIS, Springfield, VA., PB87-142949. 

U.S. EPA (1995). Office Equipment: Design, Indoor Air Emissions, and Pollution Prevention 

Opportunities. Office of Research and Development, U.S. Environmental Protection 

Agency, Washington, DC. EPA/600/R-95/045. 

U.S. EPA (1996a). 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, 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 Ozone and Related Photochemical Oxidants. Office 

of Research and Development, National Center for Environmental Assessment, U.S. 

Environmental Protection Agency, Research Triangle 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 Activities Database (CHAD) Users Guide. Database 

and documentation available at: http://www.epa.gov/chadnet1/

U.S. EPA (2006a). Total Risk Integrated Methodology (TRIM) - Air Pollutants 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 Methodology (TRIM) - Air Pollutants Exposure Model 

Documentation (TRIM.Expo / APEX, Version 4) Volume II: Technical Support Document. 

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 (2006c). Air Quality Criteria for Ozone 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=149923
 4-72 

U.S. EPA (2007). Ozone Population Exposure Analysis 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/standards/ozone/s_o3_cr_td.html

Weschler, C. J. (2000). Ozone in indoor environments: concentration and chemistry. Indoor 

Air. 10: 269-288. 

Whitfield, R., Biller, W., Jusko, M., Keisler, J. (1996). A Probabilistic Assessment of Health 

Risks Associated with Short- and Long-Term 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 Residents: Final Report. California Air Resources 

Board, Sacramento, CA. ARB/R93/487. Available from: NTIS, Springfield, VA., PB94-

108719. 

Wiley, J. A., Robinson, J. P., Cheng, Y.-T., Piazza, T., Stork, L., Pladsen, K. (1991b). Study of 

Children's Activity Patterns: Final Report. California 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 matter epidemiology-exposure study: Part 2. 

Personal exposure associated with 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 regarding the results from an updated ozone (O3) health 

risk assessment that builds upon the methodology used in the assessment conducted as part of the 

last O3 NAAQS review. This updated assessment includes estimates of (1) risks of lung function 

decrements in school age children, respiratory symptoms in asthmatic children, respiratoryrelated hospital admissions, and respiratory, non-accidental, and cardiorespiratory mortality 

associated with recent ambient O3 levels; and (2) risk reductions associated with just meeting the 

current and several alternative 8-hr O3 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 O3 risk assessment are: (1) to provide estimates of the potential 

magnitude of mortality and several morbidity effects associated with current O3 levels, and with 

meeting the current 8-hr O3 NAAQS and alternative O3 8-hr standards, in specific urban areas; 

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

risk estimates; and (3) to gain insights into the distribution of risks and patterns of risk reductions 

associated with meeting alternative O3 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 endpoints (e.g., increased lung inflammation, increased airway 

responsiveness, impaired host defenses, increased medications use, increased asthma-elated 

emergency department visits, increased school absences) for which there currently is insufficient 

information to develop quantitative risk estimates. These additional health endpoints are 

discussed qualitatively in Chapter 3 of this Staff Paper. We recognize that while there are many 

sources of uncertainty and variability inherent in the inputs to this assessment, which make the 

specific estimates uncertain, there is sufficient confidence in the direction and general magnitude 

of the estimates provided by the assessment, particularly with respect to relative differences 

between alternative potential standards, for the assessment to serve as a useful input to decisions 

on the adequacy of the O3 standard. While some of these uncertainties have been addressed 

quantitatively in the form of estimated confidence ranges around central risk estimates, other 

uncertainties and the variability in key inputs are not reflected in these confidence ranges, but 

rather are addressed through separate sensitivity analyses or are characterized qualitatively. 

 Following this introductory section, this chapter discusses the scope of the risk 

assessment, including selection of urban areas and health endpoints and the degree of confidence 

associated with the various health outcomes that have been associated with ambient O3
 5-2

exposures; components of the risk model; characterization 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 beyond 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 experiencing lung function and respiratory symptoms 

associated with O3 exposures for 9 urban areas. This portion of the risk assessment was based on 

exposure-response relationships developed from analysis of data from several controlled human 

exposure studies which was combined with exposure estimates developed for children who spent 

more time outdoors and for outdoor workers. The risk assessment for the last review also 

included risk estimates for excess respiratory-related hospital admissions related to O3

concentrations for New York City, based on a concentration-response relationship reported in an 

epidemiological study (Thurston et al., 1992). Risk estimates for lung function decrements, 

respiratory symptoms, and hospital admissions were developed associated 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 methodological approach followed 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; Whitfield, 1997; Whitfield et al., 1998). 

 In the 1997 review of the O3 NAAQS, the risk estimates played a significant role in both 

the staff recommendations and in the proposed and final decisions to revise the O3 standards. 

CASAC stated (Wolff, 1995) in its advice and recommendations to the Administrator on the O3

Staff Paper that “EPA’s risk assessments must play a central role in identifying an appropriate 

level,” while also noting that “because of the myriad of assumptions that are made to estimate 

population exposure and risk, large uncertainties exist in these estimates.” In the 1997 notice (62 

FR 38856) announcing the decision to revise the O3 standards, EPA indicated that the 

Administrator considered the results of the exposure and risk analyses 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 this 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 also is based on the information evaluated in the 
 5-3

final CD. The general approach used in the current 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 which was the subject of a consultation with the 

CASAC O3 Panel on May 5, 2005. The approach used in the current risk assessment reflects 

consideration of the comments offered by CASAC members and the public on the draft Health 

Assessment Plan, comments offered by CASAC members and the public on the first and second 

drafts of the Staff Paper and first and second drafts of the Risk Assessment TSD at and 

subsequent to a consultation with CASAC on December 8, 2005, and at and subsequent to a 

review by CASAC on August 24-25, 2006. CASAC comments reflecting both the Ozone 

Panel’s views and additional comments by individual members were provided to the Agency in 

letters dated February 16, 2006 (Henderson, 2006a), June 5, 2006 (Henderson, 2006b) and 

October 24, 2006 (Henderson, 2006c). This risk assessment chapter indicates where significant 

new information has been added since the second draft Staff Paper. 

 The basic structure of the current risk assessment reflects the two different types of 

human studies on which the O3 health risk assessment is based: controlled human exposure 

studies and epidemiological studies. Controlled human exposure studies involve volunteer 

subjects who are exposed while engaged in different exercise regimens to specified levels of O3

under controlled conditions 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 measure of personal exposure to O3 and 

measures of lung function recorded in the studies. The measure of personal exposure to ambient 

O3 is typically some function of hourly exposures – e.g., 1-hr maximum 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 O3, typically on a 

1-hr or multi-hour basis. Because data on personal hourly exposures to O3 of ambient origin are 

not available, estimates of personal exposures to varying ambient concentrations are derived 

through exposure modeling, as described in Chapter 4. While the quantitative risk assessment 

based on controlled human exposure studies addresses only lung function responses, it is 

important to note that other respiratory responses have been found to be related to O3 exposures 

in these types of studies, including increased lung inflammation, increased 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 O3 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 real world community settings. Ambient O3
 5-4

concentrations, measured as the average of monitor-specific measurements, using populationoriented monitors, are used as a surrogate measure of population exposure. It is important to 

consider that O3 in ambient air is present in a complex mixture of air pollutants, and that some 

other components of the mixture may play an important role in some of the health-related effects 

observed. It is also important to recognize that population health responses included in the 

quantitative risk assessment for O3 (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 O3 exposures. As discussed more fully in Chapter 3, a wide 

variety of respiratory and cardiorespiratory effects have been shown to be related to O3

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 baseline incidence rates and 

population data for the risk assessment locations. 

 The characteristics that are relevant to carrying out a risk assessment based on controlled 

human exposure studies versus one based on epidemiology 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 O3. The relevant 

epidemiological studies in the CD provide concentration-response functions, and, 

therefore, a risk assessment based on these studies requires as input (actual monitored or 

adjusted based on monitored) ambient O3 concentrations, and personal exposures are not 

required as inputs to the assessment. 

• Epidemiological studies are carried 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 studies, carried out in laboratory settings, are generally not 

specific to any particular real world location. A risk assessment based on controlled 

human exposure studies can therefore appropriately be carried 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 exposure studies could appropriately be carried out but a risk 

assessment based on epidemiological studies would involve greater uncertainty. 

• The adequate modeling of hourly personal exposures associated with ambient 

concentrations for use with exposure-response relationships requires more complete 

ambient monitoring data than are necessary to estimate average ambient concentrations 

used to calculate risks based on concentration-response relationships. Therefore, there 

may be some locations in which an epidemiological studies-based risk assessment could 

appropriately be carried out, but a controlled human exposure studies-based risk 

assessment would involve greater uncertainty. 
 5-5

• To derive estimates of risk from concentration-response relationships estimated in 

epidemiological studies, it is usually necessary to have estimates of the baseline 

incidences of the health effects involved. Such baseline incidence estimates are not 

needed in a controlled human exposure studies-based risk assessment. 

 The scope of the current O3 risk assessment is described in the next section along with air 

quality considerations that 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 O3 risk estimates in section 5.4. Both 

parts of the risk assessment were implemented within a new probabilistic version of TRIM.Risk, 

the component of EPA’s Total Risk Integrated Methodology (TRIM) model that estimates 

human health risks. 

5.2 SCOPE OF OZONE HEALTH RISK ASSESSMENT 

 The current O3 health risk assessment estimates risks of various health effects associated 

with exposure to ambient O3 in a number of urban areas selected to illustrate the public health 

impacts of this pollutant. The short-term exposure related health endpoints selected for the O3

risk assessment, discussed in section 5.2.1, include those for which the CD concludes that the 

evidence as a whole supports the general conclusion that O3, acting alone and/or in combination 

with other components in the ambient 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 O3 at ambient levels. As discussed in section 

3.7.5 there is clear evidence of a causal relationship between lung function decrements and O3 

exposures for school age children engaged in moderate exertion for 6 to 8-hours based on the 

numerous controlled human exposure studies 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 respiratory symptoms in moderate to severe asthmatic children 

and O3 exposures. There also is strong evidence of a causal relationship between increased 

respiratory-related hospital admissions and O3 exposure during the warm O3 season, based on 

extensive and fairly consistent epidemiological studies as well as evidence from controlled 

human exposure studies reporting increased lung inflammation and airway responsiveness. 

 The CD concludes that there is strong evidence 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 O3 exposures during the warm O3 season. Our judgment with respect to these health 

outcomes is based on the fairly consistent positive associations found between elevated warm O3

season levels and these mortality outcomes even when the effect of PM is controlled for, and 

supporting evidence about potential mechanisms of effects on the cardiovascular system from 

animal toxicology, human clinical and epidemiological studies. There is certainly greater 

uncertainty about these outcomes than the other effects discussed above. We also recognize, as 

discussed in section 3.7.5, that for some of the effects observed in epidemiological studies, such 

as increased respiratory-related hospital admissions and non-accidental and cardiorespiratory 

mortality, O3 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 O3 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 about the NAAQS than estimates that include risks potentially 

attributable to uncontrollable 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 for both lung function decrements (≥ 10, ≥ 15, and ≥ 20% 

changes in FEV1) and respiratory symptoms in children (age 6 to 18 years old) who spend more 

time outdoors and outdoor workers with 1-hr exposures at moderate and heavy exertion and 8-hr 

exposures at moderate exertion. As discussed in section 3.3.1.1 and Chapter 6 of the CD, there is 

a significant body of controlled human exposure studies reporting lung function decrements and 

respiratory symptoms in adults associated with 1- and 6 to 8-hr exposures to O3, as well as 

similar responses in outdoor workers and others engaged in recreational outdoor activities. 

 Consistent with the approach used in the last review, we judge that it is reasonable to 

estimate exposure-response relationships for lung function decrements associated with O3

exposures in children 5-18 years old based on data from young adult 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 old 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 those observed in healthy adults exposed to O3 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 moderate exertion, and 8-hr moderate exertion 

exposures in children age 5-18 years of age. Since the 8-hr moderate exertion exposure scenario 

in children who spend more time outdoors clearly resulted in the greatest health risks in terms of 

both the magnitude of the lung function decrements and the percent of the population estimated 

to experience these effects, and since no new information published since the last review 

suggests any changes that would impact this conclusion, we have included only the lung function 

decrements (≥ 10, 15, and 20% FEV1) 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 offered by the CASAC emphasizing the importance 

of health effects for this population. 

 While outdoor workers and other adults who 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 O3 concentrations, the exposure and risk assessment 

conducted during the prior review suggested that school age children are 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 recognize that the current risk assessment does not account for all of 

the lung function effects in the general population that would be associated with exposure to O3

under the various air quality scenarios examined. 

Although respiratory symptoms in healthy children were estimated in the last review, we 

have not included this endpoint in the current quantitative risk assessment. This is because 

 

3

Subsequent to completion of the Risk Assessment TSD, 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 included in the exposure 

estimates which are an input to the lung function risk estimates for active children. Thus, the 

lung function risk estimates provided 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 since the last review did not observe respiratory symptoms in 

field studies examining responses in healthy children. The CD concludes that “collectively, 

these studies indicate that there is no consistent evidence of an association between O3 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 exposure studies have reported additional health 

endpoints associated with short-term exposures to O3, including airway hyperresponsiveness, 

inflammation, and immune system effects, there is insufficient exposure-response data at 

different concentrations to develop quantitative risk estimates for these effects. These important 

additional effects are discussed in Chapter 3, and we want to emphasize that the current 

quantitative risk assessment presents only a partial picture of the risks to public health associated 

with short-term O3 exposures. 

As discussed in the CD and Chapter 3, a significant number of epidemiological studies 

examining a variety of health effects associated with ambient O3 concentrations in various 

locations throughout the U.S., Canada, Europe, and other regions of the world have been 

published since the last O3 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 adverse health effect in the population) and endpoint 

categories for which the weight of the evidence supports the inference of a likely causal 

relationship between O3 and the effect category. Certain health 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 associated with short-term exposures to O3 during the 

“warm O3 season” (April 1 to September 30) have been included: 

• Respiratory symptoms in moderate/severe 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 associated with acute exposure to O3. These recent studies provide 

very strong evidence that asthmatic children experience O3-related effects. 
 5-9

Large multi-city studies, as well as many studies from individual cities, have reported an 

association of O3 concentrations with respiratory-related hospital admissions. Studies with data 

restricted to the summer or warm season, in general, indicated positive and robust associations 

between ambient O3 concentrations and respiratory-related hospital admissions. With respect to 

acute O3 effects on mortality, the CD concludes (p.7-175) that, “The majority of the studies 

suggest an elevated risk of all cause mortality associated with acute exposure to O3, especially in 

the summer or warm season when O3 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 O3 exposures. The current 

quantitative risk assessment does not include these additional health endpoints. Emergency 

department visits were excluded from the quantitative 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 O3 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 quantitative risk assessment. Table 5-2 lists some 

of the health effects that have been associated with elevated O3 exposures which were not 

included in the quantitative risk assessment. Chapter 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 O3 risk 

assessment included the following: 

• The overall set of urban locations should represent a range of geographic areas, urban 

population demographics, and climatology and be focused on areas that do not meet the 

current 8-hr O3 NAAQS. 

• The largest areas with major O3 nonattainment problems should be included. 

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

• An area should be the same or close to the location where at least one concentrationresponse function for the health endpoints included in the assessment has been estimated 

by a study that satisfies the study selection criteria (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 Population Groups Addressed in Quantitative 

Risk assessment 

Health Effect Population 

Lung function decrements (FEV1) 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 including accidental) 

-Cardiorespiratory 

All ages 

Table 5-2. Health Endpoints and Associated Population Groups Not Included in the 

Quantitative Risk Assessment* 

Health Effect Population 

Lung function decrements Adults (outdoor 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 have been assessed were preferred to those 

with fewer. 

 Since the exposure-response functions for lung function decrements based on the 

controlled human exposure studies were based on controlled laboratory conditions, the location 

of these studies played no role in selecting urban locations for the risk assessment. 

 Based on the selection criteria and considerations listed above, 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 associated with these population exposure estimates, the 12 urban 

areas have been defined based on consolidated 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 contrast to the risk assessment for lung function 

decrements, for the risk estimates for premature 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 source of the concentration-response functions used 

in this risk assessment. In most cases the epidemiological 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 risk estimates for a recent year of air quality 

(labeled “as is” air quality in the Risk Assessment TSD) and for air quality adjusted so that it 

simulates just meeting the current and several alternative 8-hr O3 NAAQS based on a recent 
 5-12

three-year period (2002-2004). This period was selected to represent the most recent air quality 

data for which complete data were available when the risk assessment was conducted. 

In order to estimate health risks associated with just meeting the current and alternative 8-

hr O3 NAAQS, it is necessary to estimate the distribution of hourly O3 concentrations that would 

occur under any given standard. Since compliance with the current O3 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 O3 concentrations required to meet the current standard. Estimated design values4

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 O3 season or single warm O3 season, depending on the health 

effect, in each of these individual years. As described in section 4.5.6 and in more detail in 

Rizzo (2006), after considering several approaches, we concluded that the Quadratic air quality 

adjustment procedure generally best represented the pattern of reductions across the O3 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 O3 air quality data and 

in a subset of 5 urban areas (Atlanta, Chicago, New York, Houston, and Los Angeles) to the 

2003 O3 air quality data, based on the 3-year period (2002-2004) O3 design values, to generate 

new time series of hourly O3 concentrations for 2002, 2003, and 2004 that reflect air quality 

levels that just meet the current 8-hr O3 standard over this three year period. Risk estimates 

associated with 2003 O3 monitoring data and 2003 air quality adjusted to just meet the current 

and alternative 8-hr standards have been added to the assessment since the second draft Staff 

Paper. 

We note that since compliance with the current standard is based on the 3-year average 

of the 4th-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 estimates 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 O3 over the eastern half of the U.S. and this 

resulted in the highest O3 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. For example, for the current O3 NAAQS, the 3-year average of the annual 4th-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 fact that the lowest O3 levels 

over this same three-year period were observed in this year in most of the urban areas included in 

the assessment. The lower O3 levels observed in 2004 also were lower, in part, as a result of 

reductions in nitrogen oxides (NOx) 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 California 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 occur over a three-year period when alternative 

standards are just met. Daily maximum 1-hr and 8-hr O3 levels in 2003 generally fell 

somewhere between 2002 and 2004 levels in most of the 12 urban areas. 

 As noted earlier, the risk estimates developed for both the recent air quality scenario and 

just meeting the current 8-hr standard represent risks associated with O3 levels in excess of 

estimated background concentrations. The results of the global tropospheric O3 model GEOSCHEM have been used to estimate average background O3 levels for different geographic 

regions across the U.S. These GEOS-CHEM simulations include a background simulation in 

which North American anthropogenic emissions of NOx, non-methane volatile organic 

compounds, and carbon monoxide are set 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 O3 season (See Appendix 2-A of this Staff Paper for plots of these 

estimated background values). The CD and section 2.7 above indicate that background O3

concentrations at the surface are generally predicted to be in the range of 0.015 to 0.035 ppm in 

the afternoon, and they decline under conditions conducive to O3 episodes. They are highest 

during spring and decline into summer. This range 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 summarizes 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 within 5 ppbv in other regions and seasons" (CD, p.3-
 5-14

53 ). These error estimates are based on comparison 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 O3 (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 O3 for the southeast and underestimates it for the northeast. Sensitivity analyses 

examining the impact of alternative estimates for background on lung function 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 risk reductions associated with alternative 

standards relative to just meeting the current standard 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 health risk assessment: one 

based on combining information from controlled human exposure studies with modeled 

population exposure and the other based on combining information from community 

epidemiological studies with either monitored or adjusted ambient concentrations levels. Section 

5.3.1 below discusses the portion of the current risk 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 reported in community epidemiological studies. 

5.3.1 Assessment of Risk Based on Controlled Human Exposure Studies 

5.3.1.1 General Approach 

 The major components of the portion of the health risk assessment based on data from 

controlled human exposure studies are illustrated in Figure 5-1. As shown in Figure 5-1, under 

this portion of the risk assessment, exposure estimates 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 combined with probabilistic exposure-response 

relationships derived from the controlled human exposure studies to develop risk estimates 

associated with recent air quality and just meeting the current and alternative standards in excess 

of background. As discussed above, the health effect included in this portion of the risk 

assessment is lung function decrement, as measured by FEV1 in school aged children engaged in 

moderate exertion for 8 hours. The air quality and exposure analysis components that are 

integral to this portion of the risk assessment are discussed in greater detail in Chapter 4 and in 

the Exposure Assessment TSD. 
 5-15

 Several risk measures were generated for this portion of the risk assessment. In addition 

to the estimates of the number of all and asthmatic school age children experiencing one or more 

occurrences of a lung function decrement >10, >15, and >20% in an O3 season, risk estimates 

have been developed for the total number of occurrences 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 average number of times that a responder would experience the 

specified effect during an O3 season. The population sizes for all and asthmatic school age 

children for each of the 12 urban areas used in this part of the risk assessment are given in Table 

4-3 of this Staff Paper. We note that the asthmatic school age children subpopulation is a subset 

of all school age children, and thus the risk estimates presented for these two groups should not 

be combined. 

 A population risk estimate for a given lung function decrement (e.g., $15% change in 

FEV1) 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 O3 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 O3 concentrations was estimated, (2) expected risk given the 

personal exposures associated with estimated background ambient O3 concentrations was 

estimated, and (3) the latter was subtracted from the former. As shown in Equation 5-1 below, 

the population risk is then calculated by multiplying the resulting expected risk by the number of 

people in the relevant population. See Appendix 5B.2 for additional information concerning 

notation and the derivation of the risk estimate algorithms 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 kth fractile, Rk is: 

 ) ( | ) ( |

1 1

b

k i

N

i

b

k j i

N

j

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

∑ ∑ = =

= − (Equation 5-1) 

where: 

ej = (the midpoint of) the jth category of personal exposure to O3, given recent ambient 

O3 concentrations; 

b

i e = (the midpoint of) the ith category of personal exposure to O3, given background 

ambient O3 concentrations; 
 5-16

Pj = the fraction of the population having personal exposures to O3 concentration of ej

ppm, given recent ambient O3 concentrations; 

b Pi = the fraction of the population having personal exposures to O3 concentration of 

b

i e ppm, given background ambient O3 concentrations; 

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

b

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

N = number of intervals (categories) of O3 personal exposure concentration, given recent 

ambient O3 concentrations; and 

Nb = number of intervals of O3 personal exposure concentration, given background 

ambient O3 concentrations. 

 For example, if the median expected response rate for recent ambient concentrations is 

0.065 (i.e., the median expected fraction of the population responding is 6.5%) and the median 

expected response rate for background ambient concentrations 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 relevant 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 O3 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. 
5-17

Figure 5-1. Major Components of Ozone Health Risk Assessment Based on Controlled Human Exposure 

Ambient 

Monitoring for 

Selected Urban 

Areas

Air Quality 

Adjustment 

Procedures

Current and 

Alternative 

Proposed 

Standards

Health 

Risk 

Model

Controlled Human 

Exposure Studies

Probabilistic 

Exposure -

Response 

Relationships

Exposure-Response

Air Quality

Modeled 

Background 

Concentrations

Recent 

(“As Is”) 

Ambient 

O3 Levels

Exposure 

Model

Exposure Estimates Associated with:•Background 

Concentrations

•Recent Air Quality•Current Standard•Alternative 

Standards

Exposure

Ambient 

Monitoring for 

Selected Urban 

Areas

Air Quality 

Adjustment 

Procedures

Current and 

Alternative 

Proposed 

Standards

Health 

Risk 

Model

Controlled Human 

Exposure Studies

Probabilistic 

Exposure -

Response 

Relationships

Exposure-Response

Air Quality

Modeled 

Background 

Concentrations

Recent 

(“As Is”) 

Ambient 

O3 Levels

Exposure 

Model

Exposure Estimates Associated with:•Background 

Concentrations

•Recent Air Quality•Current Standard•Alternative 

Standards

Exposure
5-18

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 for 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 alternative 8-hr standards, for 2003 air quality and 

2003 air quality adjusted to just meet several potential alternative standards in 5 urban areas, and 

for air quality levels representing background 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 methodology used to estimate population exposure in the 12 urban 

areas. Exposure estimates for all and asthmatic school age children (ages 5 to 18) were 

separately combined with probabilistic exposure-response relationships for lung function 

decrements associated with 8-hr exposure while engaged in moderate exertion. Individuals 

engaged in activities that resulted in an average equivalent ventilation rate (EVR) for the 8-hr 

period at or above 13 l/min-m2

 were included in the exposure estimates for 8-hr moderate or 

greater exertion. This range was selected to match the EVR for the group 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 associated with 8-hr moderate exertion 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 Adams (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 correcting all individual responses for the effect on lung function 

decrements of exercise in clean air. The previously used studies were all conducted in EPA’s 

facility in Chapel Hill, while the Adams studies were 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 function 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. 
5-19

Table 5-3. Study-Specific Exposure-Response Data for Lung Function Decrements 

Change in FEV1>10% Change in FEV1>15% 

Study Protocol Number 

Exposed 

Number 

Responding 

Number 

Exposed 

Number 

Responding 

N

E

0.04 ppm O3Adams (2006) Triangular 30 0 30 0 Adams (2002) Square-wave, face mask 30 2 30 0 0.06 ppm O3Adams (2006) Square-wave 30 2 30 0 

Triangular 30 2 30 2 

0.08 ppm O3Adams (2006) Square-wave 30 7 30 2 

Triangular 30 9 30 3 

Square-wave, chamber 30 6 30 2 Square-wave, face mask 30 9 30 3 Variable levels (0.08 ppm avg), chamber 

30 6 30 1 

Adams (2003) 

Variable levels (0.08 ppm avg), face mask 

30 5 30 3 

Adams (2002) Square-wave, face mask 30 6 30 5 F-H-M* Square-wave 60 18 60 11 0.1 ppm O3F-H-M Square-wave 32 13 32 9 0.12 ppm O3Adams (2002) Square-wave, chamber 30 17 30 12 

Square-wave, face mask 30 21 30 13 

F-H-M Square-wave 30 15 30** 15** 

*F-H-M includes combined data from Folinsbee et al. (1988), Horstman et al. (1990), and McDonnell 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 an outlier aanalysis. 
5-20 

Davis. Data from these controlled human exposure studies were corrected for the effect of 

exercise in clean air to remove any 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 O3-exposed cases. 

 For the risk assessment conducted during the last O3 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. With the addition of data from three more recent 

Adams studies9

 that included 0.04, 0.06, and/or 0.08 ppm, 6.6 hour exposures, the combined data 

set appears to be more S-shaped, although there is still considerable uncertainty about the overall 

functional form, given the limited data at exposure levels below 0.08 ppm. Consistent with 

advice from the CASAC O3 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 estimation 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 O3 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 O3 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 function decrement, we assumed for the base case 

a 90% probability that the exposure-response function has the following 3-parameter logistic 

form:10,11 

 

8

The studies conducted in EPA’s facility in Chapel Hill that are considered in the lung function risk 

assessment measured O3 concentrations to within +/- 5% or +/- 0.004 ppm at the 0.08 ppm exposure level. 9

These studies reported O3 concentrations to be accuate within +/- 0.003 ppm over the range of 

concentrations included in these studies. 10As noted in Whitfield et al., 1996, the response data point associated with 0.12 ppm for the response 

measure FEV1 ≥ 15% appeared to be inconsistent with the other data points (see Whitfield et al., 1996, Table 10, 

footnote c). Because of this, we estimated the probability of a response of FEV1 ≥ 15% at an O3 concentration of 

0.12 ppm by interpolating between the FEV1 ≥ 10% and FEV1 ≥ 20% response rates at that O3 concentration. 
5-21 

(1 )(1 )

* (1 ) ( ; , , ) γ β γ

γ β α

α β γ + + +

− = x

x

e e

e e

y x , (Equation 5-2) 

where x denotes the O3 concentration (in ppm) to which the individual is exposed, y denotes the 

corresponding response (decrement in FEV1 > 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 percent probability that the exposure-response 

function has the following linear (hockeystick) form: 

 

⎩

⎨

⎧

+ <

+ + > = 0, 0

, 0

( ; , ) for x

x for x

y x

α β

α β α β

α β (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 with response probability given by model (5-1) with 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 O3 concentration 

more than once – for example, using a square-wave exposure pattern in one protocol and a 

triangular exposure pattern in another protocol. However, because there were insufficient data to 

estimate subject-specific response probabilities, we assumed a single 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 (logistic and linear), we derived a Bayesian 

posterior distribution using this binomial likelihood function 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 function. 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 (logistic 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 model runs to get a single combined distribution of 

10,000 sets of values reflecting the 90 percent/10 percent assumption stated above. As noted 

 

11The 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 impact on lung function risk estimates of two 

alternative choices are presented in section 5.4.3.2. 

 For any O3 concentration, x, we could then derive the nth 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 logistic model and 1,000 of which were for a linear 

model). The resulting 2.5th percentile, median (50th percentile), and 97.5th percentile exposureresponse functions for changes in FEV1 > 10%, > 15% and > 20% are shown separately in 

Figure 5-2a, b, and c along with the response data to which they were fit. 

 We note that the fraction of the population experiencing FEV1 > 10, 15, and > 20% 

associated with 0.08 ppm O3 exposures was generally lower 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 example, the fraction of the population experiencing 

FEV1 decrements >15% associated with 0.08 ppm O3 exposures ranged from 3.3 to16.7% in the 

three Adams studies compared to 18.3% in the combined data set from the Chapel Hill studies. 

The 0.08 ppm level is the only common level tested in both sets of studies. This observed 

difference may be due to differences in sensitivity of the subjects tested, random variability due 

to the relatively small number of subjects tested, and/or possibly greater attenuation of response 

for subjects living in or near Davis, California (where the Adams studies were conducted) 

compared to subjects living in or near Chapel Hill, NC (where the other studies were conducted). 

Adams notes in his studies that they were conducted over a 6-month period when the 0.09 ppm, 

1-hr California standard was not exceeded in the area where his subjects resided. The difference 

in observed responses between these two sets of studies is an additional uncertainty that should 

be considered. 

 As noted above, the Risk Assessment TSD includes risk estimates for all three measures 

of lung function response (i.e., > 10, 15, and 20% decrements in FEV1). However, we are 

focusing on FEV1 decrements >15% for all school age children and >10% FEV1 decrements for 

asthmatic school age children in this Staff Paper, consistent with the advice from CASAC 

expressed in its October 24, 2006 letter (Henderson, 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 any population health risk assessment is the 

characterization of uncertainty and variability. Uncertainty refers to the lack of knowledge 

regarding both the actual values of model input variables (parameter uncertainty) and the 

physical systems or relationships (model uncertainty – e.g., the shapes of concentration-response 

functions). In any risk assessment, uncertainty is, ideally, reduced to the maximum extent 
5-23 

possible, but significant uncertainty 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 statistical uncertainty surrounding the estimated O3

coefficients in the exposure-response functions is reflected in the credible intervals provided for 

the risk estimates in this chapter 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 draft 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 O3

concentration, x, as described above. Because the exposure estimates were generated at the 

midpoints of 0.01 ppm intervals (i.e., for 0.005 ppm, 0.015 ppm, etc), we derived 2.5th percentile, 

50th percentile (median), and 97.5th percentile response estimates for O3 concentrations at these 

midpoint values. As illustrated in Figure 5-2a, b, and c, for each of the lung function response 

definitions, the 2.5th percentile and 97.5th percentile response estimates comprise the lower and 

upper bounds of the credible interval around each point estimate (median estimate) of response. 

 As noted above, the exposure-response relationships shown in Figures 5-2a, b, and c are 

based on the assumption that the relationship between exposure and response has a logistic form 

with 90 percent probability and a linear (hockeystick) form with 10 percent probability. The 

resulting 2.5th percentile, median (50th percentile), and 97.5th percentile exposure-response 

functions for decrements in FEV1 > 10% and > 15% for the base case and two alternative 

exposure-response functions, based on an 80 percent logistic/20 percent linear split and a 50 

percent logistic/50 percent linear split are shown in Figures 5-3a and b To aid comparison 

between the base case and the two alternative exposure-response functions, Figures 5-4a and b 

show the median exposure-response relationships in the same graph for these same two FEV1

endpoint definitions for the base case and two alternative exposure-response functions. Section 

5.4.4 presents results from a sensitivity analysis that examines the impact of using these two 

alternative exposure-response relationships on the lung function risk estimates for all and 

asthmatic school age children. 

 In addition to uncertainties arising from sampling 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 data, we believe that the observed differences in 

response between the Adams studies and the Chapel Hill studies contribute to additional 

uncertainty about the exact shape of the exposure-response relationship, especially for levels at 
5-24 

Figure 5-2. a, b, c. Probabilistic Exposure-Response Relationships for FEV1 Decrement > 10%, >

15%, and > 20% for 8-Hour Exposures Under Moderate Exertion* 

a) FEV1 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) FEV1 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) FEV1 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). 
5-25 

Figure 5-3a, b, c. Probabilistic Exposure-Response Relationships for FEV1 Decrement > 10% and > 15% for 

Under Moderate Exertion: Comparison of 90% Logistic/10% Linear (Hockeystick) Split anLinear (Hockeystick) and 50% Logistic/50% Linear (Hockeystick) Splits in Assumed RelatiExposure and Response* 

FEV1 Decrement > 10%: 90% Logistic/10% Linear 

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

FEV1 Decrement > 10%: 80% Logistic/20% Linear 

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

FEV1 Decrement 

0%

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

100%

0 0.02 

O

Probability of a Response

FEV1 Decrement > 15%: 90% Logistic/10% Linear 

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

FEV1 Decrement > 15%: 80% Logistic/20% Linear 

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

FEV1 Decrement 

0%

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

100%

0 0.02 

O

Probability of a Response

*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 Functions Using Three Different Combinations of 

Logistic and Linear (Hockeystick) Models 

 

Figure 5-4a. FEV1 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. FEV1 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% linear

 
 5-27 

or below 0.08 ppm. Additional uncertainties with respect to the estimated exposure-response 

relationships are briefly 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 function response appears to level off after 

exposure for 4 to 6 hours. It is unlikely that the exposure-response relationships would 

have been appreciably different had the studies been conducted over an 8-hr period. 

• Extrapolation of exposure-response relationships. It was necessary to estimate responses 

at O3 levels below the lowest exposure levels used in the controlled human studies (i.e., 

0.04 ppm) down to background levels. 

• Reproducibility of O3-induced responses. The risk assessment assumed that the O3-

induced responses for individuals are reproducible. 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 reproducibility of response. 

• Age and lung function response. As in the prior review, exposure-response relationships 

based on controlled human exposure 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 the CD (see section AX6.4) which cites the 

findings of McDonnell et al. (1985a) who reported that children 8-11 years old 

experienced FEV1 responses similar to those observed in adults 18-35 years old when 

both groups were exposed to concentrations of 0.12 ppm at an EVR of 35 L/min/m2

. In 

addition, a number of summer camp studies of school age children exposed in outdoor 

environments in the northeast also showed O3-induced lung function changes similar to 

and in some cases somewhat larger than those observed in controlled human exposure 

studies. 

• Exposure history. The risk assessment assumed that the O3-induced response on any 

given day is independent of previous O3 exposures. As discussed in Chapter 3 and in the 

CD, O3-induced responses can be enhanced on the second day of exposure or attenuated 

after more than 2 consecutive days of exposure. The possible impact of recent exposure 

history on the risk estimates is an additional source of uncertainty that is not quantified in 

this assessment. We note that the three Adams studies which were conducted in Davis, 

California reported a smaller fraction of the subjects experiencing FEV1 decrements >15 

and 20% associated with O3 exposures to 0.08 ppm for 6.6 hours than the 

Folinsbee/Horstman/McDonnell studies conducted in Chapel Hill, NC at this same level 

and exposure period. While Adams indicates in each of these studies that O3 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 

 

12Additional uncertainties with respect to the exposure 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 differences might reflect differential sensitivity among 

the pools of subjects tested. 

• Exposure-response relationships for all and asthmatic school age children. The risk 

assessment used the same O3 exposure-response relationships developed from data on 

“healthy” subjects, for all and asthmatic school age children. Based on evidence from 

epidemiological studies, it is likely that moderate to severe asthmatic children would 

experience greater lung function decrements than other children without 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 asthmatic 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 O3 under moderate exertion may be overstated. This factor would tend to 

lead to overestimates of risks for lung function decrements in the asthmatic school age 

population. 

• Interaction between O3 and other pollutants. Because the controlled human exposure 

studies used in the risk assessment involved only O3 exposures, it was assumed that 

estimates of O3-induced health responses would not be affected by the presence of other 

pollutants (e.g., SO2, PM2.5). Some evidence exists that other pollutants may enhance the 

respiratory effects associated with exposure to O3, but the evidence is not consistent 

across studies. 

Variability refers to the heterogeneity in a population or variable of interest that is 

inherent and cannot be reduced through further research. The current 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 the 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 embedded 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 populations included in the risk assessment across 

different geographic areas is currently 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 the 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., future population levels). 
 5-29 

5.3.2 Assessment of Risk Based on Epidemiological Studies 

 As discussed above, the current quantitative risk assessment based on epidemiological 

studies includes risk estimates for respiratory symptoms in moderate to severe asthmatic 

children, respiratory-related hospital admissions, and total non-accidental and cardiorespiratory 

mortality associated with short-term O3 exposures in selected urban locations in the U.S. We 

want to emphasize that there is considerable evidence that O3 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 characterization presented in Chapter 6. The 

methods used in the epidemiological portion of the quantitative risk assessment are described 

below. 

5.3.2.1 General Approach 

The general approach used in this part of the risk assessment 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 appropriate application of these functions in a risk 

assessment similarly requires the use of ambient air 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 O3 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 O3 levels resulting from just meeting the current or 

alternative 8-hr O3 standards, the following three elements are required: 

• Air quality information including: (1) recent air quality data for O3 from populationoriented monitors in the assessment location, (2) estimates of background O3

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 quality 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 O3 concentrations, preferably derived 

in the assessment location, as use of functions estimated in other locations increases 

uncertainty. 

• Seasonal baseline health effects incidence rate and population. The baseline 

incidence rate provides an estimate of the incidence rate in the assessment location 

corresponding to recent O3 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 O3 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 y Be β = , (Equation 5-4) 

where x is the ambient O3 level, y is the incidence of the health endpoint of interest at O3 level x, 

β is the coefficient of ambient O3 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 O3. The relationship 

between a specified ambient O3 level, x0, for example, and the incidence of a given health 

endpoint associated with that level (denoted as y0) is then 

0

0

x y Be β = . (Equation 5-5) 

Because the log-linear form of concentration-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 x0 denote the baseline (upper) O3 level, and x1 denote the lower O3 level, and y0 

and y1 denote the corresponding incidences of the health effect, we can derive the following 

relationship between the change in x, Δx= (x0- x1), and the corresponding change in y, Δy, from 

equation (5-4)14: 

Δ Δyyy y e x =−= − − ( ) [ ]. 01 0 1 β (Equation 5-6) 

 Alternatively, the difference in health effects incidence can be calculated indirectly using 

relative risk. Relative risk (RR) is a measure commonly used by epidemiologists to characterize 

 

13The derivations of the health impact functions from concentration-response functions for all three 

functional forms found in the epidemiological literature and used in this risk assessment – the log-linear, linear, and 

logistic – are given in section B.2 of Appendix B in the Risk Assessment TSD. 

14If Δx < 0 – i.e., if Δx = (x1- x0) – then the relationship between Δx and Δy can be shown to be 

( ) [ 1] Δ = 1 − 0 = 0 − Δx y y y y e β . If Δx < 0, Δy will similarly be negative. However, the magnitude of Δy will be the 

same whether Δx > 0 or Δx < 0 – i.e., the absolute value of Δy does not depend on which equation is used. 
5-31 

Figure 5-5. Major Components of Ozone Health Risk Assessment Based on Epidemiological Studies

Ambient Monitoring for Selected Urban Areas

Air Quality Adjustment ProceduresCurrent and Alternative Proposed Standards

Changes in Distribution 

of O3 Air 

Quality

Ris

• R

Q

• C

S

• A

S

Health 

Risk 

Model

Estimates of City-specific Baseline Health Effects Incidence Rates and Population DataHuman Epidemiological Studies

Concentration -Response Relationships

Concentration-Response

Air Quality

Modeled Background Concentrations

Recent (“As Is”) Ambient Monitoring for Ambient O3 Levels Selected Urban Areas

Air Quality Adjustment ProceduresCurrent and Alternative Proposed Standards

Changes in Distribution 

of O3 Air 

Quality

Ris

• R

Q

• C

S

• A

S

Health 

Risk 

Model

Estimates of City-specific Baseline Health Effects Incidence Rates and Population DataHuman Epidemiological Studies

Concentration -Response Relationships

Concentration-Response

Air Quality

Modeled Background Concentrations

Recent (“As Is”) Ambient O3 Levels
5-32 

the comparative health effects associated with a particular air quality comparison. The risk of 

mortality at ambient O3 level x0 relative to the risk of mortality at ambient O3 level x1, for 

example, may be characterized by the ratio of the two mortality rates: the mortality rate among 

individuals when the ambient O3 level is x0 and the mortality rate among (otherwise identical) 

individuals when the ambient O3 level is x1. This is the RR for mortality associated with the 

difference between the two ambient O3 levels, x0 and x1. Given a concentration-response 

function of the form shown in equation (5-4) and a particular difference in ambient O3 levels, Δx, 

the RR associated with that difference in ambient O3, denoted as RRΔx, is equal to eβΔx

 . The 

difference in health effects incidence, Δy, corresponding to a given difference in ambient O3

levels, Δx, can then be calculated based on this RRΔx: 

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

Equations (5-6) and (5-7) are simply alternative ways of expressing the relationship between a 

given difference in ambient O3 levels, Δx, and the corresponding difference in health effects 

incidence, Δy. These health impact equations are the key equations that combine air quality 

information, concentration-response function information, and baseline health effects incidence 

information to estimate ambient O3 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 O3 risk assessment includes: (1) recent air quality data for O3 from suitable monitors for each 

selected location, (2) estimates of background concentrations for each selected location, and (3) 

air quality adjustment procedures to modify the recent data to reflect changes in the distribution 

of hourly O3 air quality estimated to occur when an area just meets a given O3 standard. The 

approach used to adjust air quality data to simulate just meeting alternative 8-hr standards is 

discussed in more detail in Chapter 4 and in Rizzo (2005, 2006). 

 We retrieved O3 ambient air quality data for the years 2002 through 2004 from EPA’s Air 

Quality System (AQS). Although the O3 season varies somewhat for different regions of the 

country, for much of the country the season coincides with spring and summer. To allow 

comparison across locations, and because O3 effects observed in epidemiological studies have 

been more clearly and consistently shown for warm season analyses, all analyses for this portion 

of the risk assessment were carried out for the same time period, April through September. 

Because O3 concentrations varied substantially over the 3-year period from 2002 through 2004, 

separate analyses were carried out using air quality data from 2002, in which O3 concentrations 

were relatively higher in most locations over this 3-year period, and air quality data from 2004, 
5-33 

in which O3 concentrations were relatively lower in most 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 Los Angeles, had similar or higher O3 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, Houston, 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 health effect associated with a change in O3

concentrations from recent levels to background levels in an assessment location, two time series 

of O3 concentrations are needed for that location: (1) hourly O3 concentrations from a recent 

year for the period April 1 through September 30, and (2) hourly background O3 concentrations 

for the same time period. In order to be consistent with the approach generally used in the 

epidemiological studies that estimated O3 concentration-response functions, the (spatial) average 

ambient O3 concentration on each hour for which measured data are available is deemed most 

appropriate for the risk assessment. A composite monitor data set was created for each 

assessment location based on averaging each hourly 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 O3 concentrations for these locations. 

Different exposure metrics have been used in epidemiological O3 studies, including the 

24-hr average and the daily 1-hr and 8-hr maximum. Therefore, daily changes at the composite 

monitor in the O3 exposure metric appropriate to a given concentration-response function were 

calculated for use in the risk assessment (see Tables 5A-13 and 5A-14, Appendix 5A.1 for 

summary statistics for the composite monitor O3 concentrations in the 12 urban locations for 

2002, 2003, and 2004). For example, if a concentration-response function related daily mortality 

to daily 1-hr maximum O3 concentrations, the daily changes in 1-hr maximum O3 concentrations 

at the composite monitor were calculated. In the first part of the epidemiology-based risk 

assessment, in which risks associated with the recent levels of O3 above background levels were 

estimated, this required the following steps: 

• Using the monitor-specific input streams of hourly O3 concentrations from a recent year, 

calculate a stream of hourly O3 concentrations at the composite monitor. The recent O3

concentration at the composite monitor for a given hour on a given day is the average of 

the monitor-specific O3 concentrations for that hour on that day. 

• Using this stream of hourly O3 concentrations from a recent year at the composite 

monitor, calculate the 1-hr maximum O3 concentration for each day at the composite 

monitor. 

• Using the monitor-specific input streams of hourly background O3 concentrations, 

calculate a stream of hourly background O3 concentrations at the composite monitor. 
5-34 

• Using this stream of background hourly O3 concentrations at the composite monitor, 

calculate the 1-hr maximum background O3 concentration for each day at the composite 

monitor. 

• For each day, calculate Δx = (the 1-hr maximum O3 concentration for that day at the 

composite monitor) - (the 1-hr maximum background O3 concentration for that day at the 

composite monitor). 

The calculations for the second part of the epidemiology-based risk assessment, in which 

risks associated with estimated O3 levels that just meet the current and potential alternative 8-hr 

standards above background levels, were done analogously. For this case the series of monitorspecific adjusted hourly concentrations were used rather than the series of monitor-specific 

recent monitored hourly concentrations. Similarly, calculations for concentration-response 

functions that used a different exposure metric (e.g., the 8-hr daily maximum 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 key component in the risk model based on 

epidemiological studies is the set of concentration-response functions which provide estimates of 

the relationships between each health endpoint of interest and ambient concentrations. As 

discussed above, the health endpoints that have been included in the O3 risk assessment include 

respiratory symptoms in moderate-to-severe asthmatic children, respiratory-related hospital 

admissions, and premature mortality associated with 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 yield statistically significant 

results. Effect estimates that are not statistically significant are used from studies judged suitable 

for inclusion in this assessment to avoid introducing bias into the estimate of the magnitude of 

the effect. Table 5-4 summarizes the studies included in this part of the risk assessment for each 

of the urban locations. 

 Studies often report more than one estimated concentration-response function for the 

same location and health endpoint. Sometimes models including different sets of co-pollutants 

are estimated in a study; sometimes different lags are estimated. In some cases, two or more 

studies estimated a concentration-response function for O3 and the same health endpoint in the 

same location (this is the case, for example, with O3 and mortality associated with short-term 

exposures). For some health endpoints, there are studies that estimated multi-city and single-city 

O3 concentration-response functions, while other studies estimated only single-city functions. 
5-35 

 All else being equal, a concentration-response function estimated in the assessment 

location is preferable to a function estimated elsewhere, since it avoids uncertainties related to 

potential differences due to geographic location. That is why the urban areas selected this part of 

the O3 risk assessment are, generally, those locations in which concentration-response functions 

have been estimated. There are several advantages, however, to using estimates from multi-city 

studies versus studies carried out in single cities. These advantages include, but are not limited 

to: (1) more precise effect estimates due to larger data sets, reducing the uncertainty around the 

estimated coefficient, (2) greater consistency in data handling and model specification that can 

eliminate city- to-city variation due to study design, and (3) less likelihood of publication bias or 

exclusion of reporting of negative or nonsignificant findings. Multi-city studies are applicable to 

a variety of settings, since they estimate a central 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 been developed for both functions. 

 As discussed in the CD and section 3.3.2.1 of this Staff Paper, O3 epidemiological studies 

have reported relationships based on single pollutant models and/or multi-pollutant models (i.e., 

where PM, NO2, SO2, or CO were entered into the health effects model along with O3. To the 

extent that any of the co-pollutants present in the ambient air may have contributed to the health 

effects attributed to O3 in single pollutant models, risks attributed to O3 might be overestimated 

where concentration-response functions are based on single pollutant models. However, if copollutants are highly correlated with O3, their inclusion in an O3 health effects model can lead to 

misleading conclusions in identifying a specific causal pollutant. When collinearity exists, 

inclusion of multiple pollutants in models often produces unstable and statistically insignificant 

effect estimates for both O3 and the co-pollutants. Given that single and multi-pollutant models 

each have both potential advantages and disadvantages, with neither type clearly 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 effect 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, with some consideration 

of multi-day lag effects (CD, p. 7-11). For quantitative assessments, we conclude that it is 

appropriate to use results from lag period analyses 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 availability of results (CD, p. 8-59). If the effect of O3 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 they are available. Where only 
5-36 

Table 5-4. Locations, Health Endpoints, and Epidemiological Studies Included in the O3

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 focused on single day lag periods of 0-1 days for 

associations with mortality or respiratory hospitalization, depending on availability of effect 

estimates (CD, p. 8-59). 

 In summary: 

• if a single-city concentration-response function was estimated in a risk assessment 

location and a multi-city function which includes 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 available; when a study reported several single 

lag models for a health effect, the initial selection of the appropriate lag structure for the 

health effect was based on the overall assessment in the CD, considering all studies 

reporting concentration-response functions for that health effect. 

 The locations, health endpoints, studies, and concentration-response functions included in 

that portion of the risk assessment based on epidemiological studies are summarized in Tables 

5B-1 through 5B-12 in Appendix 5B.1. 

5.3.2.4 Baseline Health Effects Incidence 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 O3 concentrations ()x) as a percentage of the baseline incidence (y). To accurately 

assess the impact of changes in O3 air quality on health risk in the selected urban areas, 

information on the baseline incidence of health effects in each location is therefore needed. For 

this assessment, baseline incidence is the incidence under recent 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 incidence 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 data dissemination provided by the Centers for Disease Control 

(CDC). The baseline mortality rates for each risk assessment location are provided in Table 5-6 

and are expressed as a rate per 100,000 population. 

 County-specific rates for respiratory hospital discharges, and various subcategories (e.g., 

asthma, pneumonia) have been obtained, where possible, from state, local, and regional health 
5-38 

Table 5-5. Relevant Population Sizes for O3 Risk Assessment Locations* 

City Counties Population (in millions)* 

Total Ages $30 Ages $ 65 

Atlanta Fulton, DeKalb 1.5 --- --- Boston Suffolk 0.7 --- ---Boston Essex, Middlesex, Norfolk, Suffolk, Worcester --- --- --- Chicago Cook 5.4 --- --- Cleveland Cuyahoga 1.4 --- 0.2Detroit Wayne 2.1 --- --- Houston Harris 3.4 --- --- Los Angeles Los Angeles 9.5 --- --- Los Angeles Los Angeles, Riverside, San Bernardino, Orange --- 8.4 --- New York Bronx, Kings, Queens, New York, Richmond, 

Westchester 

8.9 --- --- 

New York Bronx, Kings, Queens, New York, Richmond 8.0 --- --- Philadelphia Philadelphia 1.5 --- --- Sacramento Sacramento 1.2 --- --- St. Louis St. 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 nearest 0.1 m

given in this table are those considered in the studies used in the risk assessment, with the exception of the larger Boston area, which is the study that estimated a concentration-response function in moderate and severe asthmatic children (ages 0 – 12) was conducted in Sp** Population derived as follows: The populations of children <5 and 5 - 12 in the counties listed were multiplied by corresponding pe

age group] in New England with “current asthma” -- 5.1% and 10.7% for the two age groups, respectively (see "The Burden of AsthmAsthma Regional Council. March 2006. Table S-2. www.asthmaregionalcouncil.org ). These estimated numbers of asthmatic childre

the estimated percent of asthmatic children using maintenance medications (40%) (obtained via email 4-05-06 from Jeanne Moorman, summed.
5-39 

 Table 5-6. Baseline Mortality Rates (per 100,000 Population) Used in the O3 Risk Assessment* 

Type of Mortality 

(ICD-9 Codes)

City Counties 

Non-accidental 

 (<800) 

Cardiorespiratory 

 (390-448; 490-496; 

487; 480-486; 507) 

Resp

(460

Atlanta Fulton, DeKalb 623 131 Boston Suffolk 736 --- Chicago Cook 781 189 Cleveland Cuyahoga 1,058 268 Detroit Wayne 913 234 Houston Harris 533 123 Los Angeles Los Angeles 569 155 New York Bronx, Kings, Queens, New 

York, Richmond, Westchester 

704 199 

Philadelphia Philadelphia 1,057 242 Sacramento Sacramento 686 --- St. Louis St. Louis City 1147 --- Washington, D.C. Washington, D.C. 942 --- National --- 790 196 

 *Data for the year 2002 from United States Department of Health and Human Services (US DHHS), Centers for Disease Cont

National Center for Health Statistics (NCHS), Compressed Mortality File (CMF) compiled from CMF 1968-1988, Series 20, N

1998, Series 20, No. 2E 2003 and CMF 1999-2002, Series 20, No. 2H 2004 on CDC WONDER On-line Database. See http:/
5-40

departments and hospital planning 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. (2003). Each symptom rate, the percentage of days 

on which the symptom occurred, was calculated for each subject by dividing the number of days 

of the symptom by the number of days of participation in the study and then multiplying by 100. 

Median symptom rates among maintenance medication 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 uncertainty 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 Risk Assessment TSD. Additional uncertainties have 

been addressed quantitatively through 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 concentration-response functions describing the relation between O3 and 

mortality across urban areas. This variability may be due to differences in population (e.g., age 

distribution), population activities that affect exposure to O3 (e.g., use of air conditioning), levels 

and composition of co-pollutants, and/or other 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 concentration-response 

functions, baseline incidence rates, and air quality 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 extent possible, inputs specific to 

each urban area. Temporal variability is more difficult to address, because the risk assessment 

 

15The 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 O3 Risk Assessment 

Rate per 100,000 Relevant Population* 

Los 

Angeles1

New 

York2 Detroit3

 Cleveland4

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 expressly 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 at that 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 baseline incidence rates (from 2002). However, 

future changes in inputs have not been predicted (e.g., future population levels or possible 

changes in baseline incidence rates). 

 A number of important sources of uncertainty 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 following 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 

O3 indicators and the various health endpoints included in this risk assessment actually 

reflect a causal relationship. Our judgment, drawing on the conclusions in the CD and as 

discussed in more detail in Chapter 3 (section 3.7.5), is that for the health effects included 

in the risk assessment (i.e, increased respiratory symptoms in moderate to severe 

asthmatic children, increased respiratory-related hospital admissions, total non-accidental 

mortality, and cardiorespiratory mortality) there is, at a minimum, a likely causal 

relationship with either short-term O3 exposure itself or with O3 serving as an indicator 

for itself and other components of the photochemical oxidant mix, especially during the 

warm O3 season. 

• Empirically estimated concentration-response relationships. In estimating the 

concentration-response relationships, there are uncertainties: (1) surrounding estimates of 

O3 coefficients in concentration-response functions used in the assessment, (2) 

concerning the specification of the concentration-response model (including the shape of 

the relationship) and whether or not a population threshold or non-linear relationship 

exists within the range of concentrations examined in the studies , (3) related to the extent 

to which concentration-response relationships derived from studies in a given location 

and time when O3 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-pollutants 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 respect to the shape of the function and whether 

or not a population threshold may exist, as discussed 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), results from recent large U.S. multi-city timeseries studies and meta-analyses also show effect estimates that are consistent across 

studies and robust to control for potential confounders. 
5-43

• Adequacy of ambient O3 monitors as surrogate for population exposure. The extent to 

which there are differences in the relationship between spatial variation in ambient O3

concentrations and ambient exposures in the original epidemiology studies compared to 

more recent ambient O3 data introduces additional uncertainty in the risk estimates. We 

recognize that ambient concentrations at central monitors may not provide a good 

representation of personal exposures. The CD identifies the following three components 

to exposure measurement error: (1) the use of average population 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 concentrations (CD, p. 7-7). The CD notes that “these 

components are expected to have different effects, with the first and third likely not 

causing bias in a particular direction (“nondifferential error”) but increasing 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 O3 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 ambient concentrations at monitoring stations provide an unbiased 

estimate of the ambient concentrations to which the population is exposed. A more 

comprehensive discussion of exposure measurement 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 O3 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 quality adjustment procedure provides reasonable 

estimates of the shape of the distribution; however, 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 considerable year-to-year variability in O3

concentrations over a three-year period in many of the urban areas examined. This leads 

to substantial year-to-year variability in risk estimates associated with O3 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 location 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 section 2.7) for all hours 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 the 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 concentrations 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 estimates vary for the year(s) when the actual 
5-44

epidemiological studies were conducted, the recent year of air quality used in this 

assessment, and some unspecified future year when air quality is adjusted to simulate just 

meeting the current or alternative standards and (2) the use of annual or seasonal 

incidence rate data to develop daily health effects incidence data. Spatial variability in 

baseline incidence and population data is taken 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 uncertainty resulting from the statistical uncertainty 

associated with the estimate of the O3 coefficient in the concentration-response function was 

characterized either by confidence 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 O3 coefficient 

involved sampling error. Other uncertainties, such as differences in study location, time period, 

and model uncertainties are not represented by the confidence or credible intervals presented. 

 Two large scale multi-city mortality studies, Bell et al. (2004) and Huang et al. (2004), 

reported both multi-location and single-location 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 data from all locations. The resulting “shrinkage” 

estimates are so called because they “shrink” the location-specific estimates towards the overall 

mean estimate (the mean of the posterior distribution of the multi-location concentrationresponse function coefficient). The greater the uncertainty about the estimate of the locationspecific coefficient relative to the estimate of between-study heterogeneity, the more the 

location-specific estimate is “pulled 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 authors provided the posterior distribution for the 

heterogeneity parameter, τ, for their distributed lag model, shown 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” estimates 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 locations 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 uncertainty surrounding estimates of coefficients in location-specific 

concentration-response functions. 
5-45

With respect to model form, most of the epidemiological studies estimated O3 coefficients 

using log-linear models. However, there still is substantial uncertainty about the correct 

functional form of the relationship between O3 and various health endpoints, especially at the low 

end of the range of observed concentrations. While there are likely biological thresholds in 

individuals for specific health responses, as discussed in section 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 threshold level exists for premature mortality. 

The results suggested that even low levels of tropospheric O3, 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 O3 concentrations may obscure the presence of thresholds in epidemiological 

studies (CD p. 7-158). 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). 

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 exist for reported associations at fairly low levels within the range 

of air quality observed in the studies, but not be detectable as population thresholds in 

epidemiological analyses. Based on the CD’s conclusions, we judge that there is insufficient 

evidence to support use of potential threshold levels in the quantitative risk assessment, but we 

do recognize there is increasing uncertainty about the concentration-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 associated with exposure to O3 must be considered in the light of 

uncertainties about whether or not these O3-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 estimates of mortality associated with short-term 

exposures to O3. We reviewed these meta-analyses for additional information that might be used 

to assist in characterizing the uncertainties associated with concentration-response functions for 

this health outcome. As discussed in Chapter 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 evidence of publication bias, but O3-mortality associations 
5-46

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 confound the association between O3 and mortality. 

 As discussed in Chapter 3, while concluding that O3-health associations are found to be 

generally consistent, the recent O3-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 affect exposure to ambient O3. 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 potential alternative 8-hr standards. In section 5.4.3 

we present and discuss the results of sensitivity analyses examining the influence of alternative 

estimates of background O3 concentrations and alternative assumptions about the shape of the 

exposure-response relationship for lung function decrements in all and asthmatic school age 

children. In section 5.4.4 we discuss and compare the risk estimates developed for the current 

review with the risk estimates developed for the prior O3 NAAQS review completed in July 

1997. Finally, in section 5.4.5 we present key observations from the health risk assessment. 

 Throughout this section the uncertainty surrounding risk estimates resulting from the 

statistical uncertainty of the O3 coefficients in the concentration- and exposure-response 

functions used is characterized by ninety-five percent confidence or credible intervals around 

estimates of incidence, incidence per 100,000 population, and the percent of total incidence that 

is O3-related. In some cases, the lower bound of a confidence or credible interval falls below 

zero. This does not imply that additional exposure to O3 has a beneficial effect, but only that the 

estimated O3 coefficient in the concentration- or exposure-response function was not statistically 

significantly different from zero. Lack of statistical significance could reflect insufficient 

statistical power to detect a relationship that exists or that a relationship does not exist. 

Conversely, the fact that a study reports statistical significant associations does not prove 

causation. The judgments about whether a causal relationship likely exists between O3 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 lung function decrements associated with 1-hr 

heavy exertion, 1-hr moderate exertion, and 8-hr moderate exertion exposures were estimated. 

Since the 8-hr moderate exertion exposure scenario for children clearly resulted in the greatest 

health risks in terms of lung function decrements, we have chosen to include only the 8-hr 

moderate exertion exposures in the current risk assessment for this 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 general population associated with any of the air quality scenarios. 

Thus, some outdoor workers and adults engaged in moderate exertion over multi-hour periods 

(e.g., 6-8 hr exposures) also would be expected to experience similar lung function decrements. 

However, the percentage of each of these other subpopulations expected to experience these 

effects is expected to be smaller than all school age children who tend to spend more hours 

outdoors while active based on the exposure analyses conducted during the prior review. 

 We have included risk estimates for all and asthmatic school age children in this section. 

As noted previously, risk estimates for asthmatic school age children have been added to the 

assessment since the second draft Staff Paper. Risk estimates associated with recent air quality 

(2002 and 2004) for up to 12 urban locations are presented in this section. Additional risk 

estimates developed since the second draft Staff Paper associated with 2003 air quality for a 

subset of five locations (Atlanta, Chicago, Houston, Los Angeles, and New York) are presented 

in the Risk Assessment TSD and for all 12 urban areas in a recent memo (Post, 2007). 

 Tables 5-8 and 5-9 display the risk estimates for all school age children (ages 5-18) 

associated with 2004 and 2002 O3 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 FEV1 decrements > 15% for all school age children since 

this level of response is judged to be an indicator of adverse health 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 O3 in excess of exposures associated with background O3 

concentrations. Table 5-8 shows the number and percent of all school age children estimated to 

have at least 1 lung function response (defined as FEV1 > 15%) during the O3 season. Table 5-9 

displays the total number of occurrences for this same lung function response during the O3

season. As illustrated by the estimates shown in these two tables, a child may experience 

multiple occurrences of a lung function response during the O3 season. For example, in Atlanta 
5-48

the median estimate is that 34,000 school age children experienced an FEV1 decrement > 15% 

during the O3 season with a median estimate of about 191,000 occurrences of this same response 

in this population for 2004 air quality data. Thus, for this example on average each child is 

estimated to have over 5 occurrences of this lung function response during the O3 season. 

 As shown in Table 5-8, across the 12 urban areas, the ranges in median estimates of the 

percent of all school age children estimated to experience at least one FEV1 decrement > 15% 

during the O3 season are 1.4 to 6.0% for 2004 and 5.3 to 9.9% for 2002. In terms of total 

occurrences of FEV1 decrement > 15% during the O3 season, Table 5-9 shows 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 O3 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 associated 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 children. Again, the risk estimates 

associated with just meeting the current 8-hr standard presented in these tables will be discussed 

in the next section. For asthmatic children a lung function response defined in terms of FEV1

decrement > 10% is shown, consistent with CASAC’s advice (Henderson, 2006c) that this level 

of response serves as an indicator 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 FEV1 decrement > 10% during the O3 

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 FEV1 decrement > 10% associated with O3 concentrations during the O3 

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 responses in 2002 for asthmatic school age children 

across the 5 urban areas. Dividing 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 roughly 5 and 10 occurrences of this lung function 

response during the O3 season depending on the urban area and year of air quality analyzed. 
5-49 

Table 5-8. Number and Percent of All School Age Children Estimated to Experience Lung Function Respons

Associated with 8-Hour O3 Exposure While Engaged in Moderate Exertion for Location-Specific 

Number of Children (Ages 5-18) Having at Least 1 Lung Function Response (FEV1 > 15%) Associated wit

Recent Air Quality (2004) 

Just Meeting Current 8-Hour 

Standard (based on adjusting 

2004 air quality) 

Recent Air Quality (2002) 

S

Location 

(O3 Season) 

Number 

(1000s) Percent Number (1000s) Percent Number (1000s) Percent 

34 3.6% 20 2.2% 59 6.3% 

Atlanta 

(19 - 51) (2% - 5.4%) (8 - 34) (0.9% - 3.6%) (40 - 81) (4.2% - 8.6%) 

26 2.4% 15 1.4% 84 7.6% 

Boston 

(12 - 42) (1.1% - 3.8%) (4 - 27) (0.4% - 2.5%) (58 - 112) (5.3% - 10.3%) 

27 1.4% 15 0.8% 123 6.3% 

Chicago (6 - 49) (0.3% - 2.5%) (1 - 31) (0% - 1.6%) (83 - 169) (4.2% - 8.7%) 

12 2% 6 1% 56 9.4% 

Cleveland (5 - 20) (0.8% - 3.3%) (1 - 12) (0.1% - 2%) (40 - 74) (6.7% - 12.4%) 

20 1.8% 12 1.1% 76 6.8% 

Detroit 

(7 - 35) (0.6% - 3.1%) (2 - 24) (0.2% - 2.1%) (51 - 103) (4.6% - 9.3%) 

57 5.2% 23 2.1% 58 5.3% 

Houston 

(37 - 79) (3.4% - 7.3%) (10 - 37) (0.9% - 3.4%) (38 - 80) (3.5% - 7.4%) 

220 6% 34 0.9% 220 6% 

Los Angeles (149 - 298) (4.1% - 8.1%) (5 - 62) (0.1% - 1.7%) (150 - 297) (4.1% - 8.1%) 

112 2.7% 43 1% 346 8.3% 

New York 

(55 - 176) (1.3% - 4.2%) (6 - 84) (0.2% - 2%) (244 - 462) (5.9% - 11.2%) (

38 3.2% 19 1.6% 118 9.9% 

Philadelphia (21 - 59) (1.8% - 4.9%) (5 - 33) (0.4% - 2.8%) (85 - 155) (7.2% - 13.1%) 

11 2.7% 4 1% 24 5.8% 

Sacramento (6 - 17) (1.4% - 4.1%) (1 - 7) (0.2% - 1.8%) (16 - 32) (3.9% - 7.9%) 

10 1.8% 7 1.3% 41 7.1% 

St. Louis (3 - 18) (0.6% - 3.1%) (1 - 14) (0.2% - 2.4%) (28 - 56) (4.8% - 9.6%) 

57 3.8% 28 1.9% 125 8.4% 

Washington, DC (33 - 84) (2.2% - 5.6%) (10 - 48) (0.7% - 3.2%) (88 - 167) (5.9% - 11.2%) *Risks are estimated for exposures in excess 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 stathe O3 coefficient. Numbers are rounded to the nearest 1000. Percents are rounded to the nearest tenth. 
5-50 

Table 5-9. Number of Occurrences of Lung Function Responses (FEV1 > 15%) Among All School Age C

with 8-Hour O3 Exposure While Engaged in Moderate Exertion for Location-Specific O3 Seasons*

*Risks are estimated for exposures in excess of policy relevant background. **Numbers are median (0.5 fractile) numbers of occurrences in thousands. Numbers in parentheses below the median abased on statistical uncertainty surrounding the O3 coefficient. Numbers are rounded to the nearest 1000 

Occurrences of Lung Function Response (FEV1 > 15%) Associated with 8-Hour 

Children (Ages 5-18), in Thousands**

Location 

Recent Air Quality 

(2004) 

Just Meeting Current 8-

Hour Standard (based on 

adjusting 2004 air quality) 

Recent Air Quality 

(2002) 

Ju

Ho

adj

Atlanta 191 131 290 (March-October) (29 - 456) (10 - 344) (88 - 593) Boston 125 86 311 (April-September) (16 - 315) (5 - 238) (115 - 611) Chicago 167 110 511 (April-September) (6 - 460) (1 - 328) (171 - 1015) Cleveland 69 43 259 (April-October) (6 - 179) (1 - 125) (110 - 473) Detroit 111 79 333 (April-September) (8 - 296) (2 - 227) (119 - 649) Houston 230 110 209 (All year) (63 - 465) (13 - 253) (62 - 419) Los Angeles 1470 371 1265 (All year) (393 - 3073) (6 - 1044) (355 - 2642) New York 563 296 1522 (April-September) (77 - 1383) (7 - 851) (585 - 2885) Philadelphia 218 130 570 (April-October) (35 - 509) (6 - 345) (239 - 1037) Sacramento 86 41 145 (All year) (11 - 206) (1 - 114) (39 - 305) St. Louis 69 54 183 (April-October) (4 - 181) (1 - 148) (65 - 356) Washington, DC 268 164 565 (April-October) (50 - 622) (12 - 432) (209 - 1086) 
5-51

The risk estimates associated with 2004 and 2002 O3 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 children for the Boston urban area and in Tables 5-14 

and 5-15 for excess hospital admissions for total respiratory illness and asthma (which is a subset 

of total respiratory illness admissions) for the New York City urban area. Additional hospital 

admission estimates for three other locations are 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 O3 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 maintenance 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 epidemiological 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 O3 levels above background 

for April through September of 2004 and 2002, respectively. The risk estimates are expressed in 

terms of cases, cases per 100,000 relevant population, and percent of total incidence 

 Tables 5-14 and 5-15 show risk estimates of unscheduled hospital admissions for 

respiratory illness in the New York City area associated with O3 levels above background for 

April through September of 2004 and 2002, respectively. The risk estimates are expressed in 

terms of cases, cases per 100,000 relevant population, and percent of total incidence. 

 Tables 5-16 and 5-17 show risk estimates for non-accidental mortality associated with O3

levels above background for April through September of 2004 and 2002, respectively. Similar 

tables for cardiorespiratory mortality are included 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-response functions in a variety of locations, using a Bayesian twostage hierarchical model. Thus, where available, risk estimates are included in Tables 5-16 and 

5-17 based on both single-city and multi-city functions. The ranges shown in these tables are 

based either on the 95 percent confidence intervals around those estimates (if the coefficients 

were estimated using classical statistical techniques) or on the 95 percent credible intervals (if 

the coefficients were estimated using Bayesian statistical techniques). 
5-52 

Table 5-10. Number and Percent of Asthmatic School Age Children Estimated to Experience Lung Funct

> 10%) Associated with 8-Hour O3 Exposure While Engaged in Moderate Exertion for Locatio

Seasons* 

Asthmatic Children (Ages 5-18) Having at Least 1 Lung Function Response (FEV1 >10%) Associated with 8-H

Moderate Exertion** 

Recent Air Quality (2004) 

Just Meeting Current 8-Hour 

Standard (based on adjusting 

2004 air quality) 

Recent Air Quality (2002) 

Ju

Sta

Location (O3

Season) 

Number 

(1000s) Percent Number (1000s) Percent Number (1000s) Percent Nu

(1

Atlanta 12 9.9% 8 6.9% 18 15.2% (MarchOctober (9 - 17) (7.4% - 14.2%) (6 - 12) (4.8% - 10.6%) (14 - 23) (12.2% - 19.8%) (10 Chicago 14 4.9% 9 3.2% 40 14.5% (AprilSeptember) (9 - 22) (3.1% - 7.8%) (5 - 14) (1.8% - 5.1%) (32 - 53) (11.6% - 18.9%) (20 Houston 17 12.6% 9 6.7% 17 12.5% (All year) (14 - 23) (10% - 16.8%) (6 - 14) (4.7% - 10.1%) (13 - 23) (9.9% - 16.7%) (6 

62 13.6% 16 3.5% 61 13.3% 

Los Angeles (All year) (52 - 81) (11.4% - 17.7%) (11 - 25) (2.5% - 5.5%) (51 - 79) (11.1% - 17.2%) (11 New York 51 8% 26 4.1% 118 18.3% (AprilSeptember) (37 - 76) (5.8% - 11.8%) (16 - 42) (2.5% - 6.6%) (97 - 147) (15.1% - 22.9%) (47 *Risks are estimated for exposures in excess 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 ssurrounding the O3 coefficient. Numbers are rounded to the nearest 1000. Percents are rounded to the nearest tenth. 
5-53 

Table 5-11. Number of Occurrences of Lung Function Responses (FEV1 > 10%) Among Asthmatic Schoo

Associated with 8-Hour O3 Exposure While Engaged in Moderate Exertion for Location Specif

Occurrences of Lung Function Response (FEV1 >10%) Associated with 8-Hour O3 Exposure Am

(Ages 5-18) While Engaged in Moderate Exertion, in Thousands** 

Location 

Recent Air Quality 

(2004) 

Just Meeting Current 8-Hour 

Standard (based on adjusting 

2004 air quality) 

Recent Air Quality 

(2002) 

Just M

Standa

Atlanta 109 82 145 (March-October) (38 - 196) (22 - 151) (68 - 244) Chicago 114 80 257 (April-October) (27 - 214) (12 - 154) (125 - 427) Houston 110 61 96 (All year) (51 - 181) (22 - 103) (45 - 158) 

660 219 561 

Los Angeles (All year) (308 - 1108) (49 - 405) (255 - 942) 

399 240 834 

New York (April-September) (131 - 720) (46 - 458) (435 - 1356) *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 intervals bauncertainty surrounding the O3 coefficient. Numbers are rounded to the nearest 1000. 
5-54 

Table 5-12. Estimated Respiratory Symptoms Associated with Recent (April - September, 2004) O3 Conc

Background in Boston, MA 

Health Effects Assoc

Relevant Ba

Health Effects* Study Ages Lag Exposure Metric 

Other 

Pollutants 

in Model Incidence 

Inc

100,0

Po

Respiratory symptoms among asthmatic 0 - 12 1-day lag 1 hr max. none 5300 medication-users -- chest tightness 

Gent et al. (2003) 

 (800 - 9200) (330

Respiratory symptoms among asthmatic 0 - 12 0-day lag 1 hr max. PM2.5 8400 medication-users -- chest tightness 

Gent et al. (2003) 

 (3800 - 12400) (149

Respiratory symptoms among asthmatic 0 - 12 1-day lag 1 hr max. PM2.5 7700 medication-users -- chest tightness 

Gent et al. (2003) 

 (3000 - 11800) (118

Respiratory symptoms among asthmatic 0 - 12 1-day lag 8 hr max. none 5400 medication-users -- chest tightness 

Gent et al. (2003) 

 (1700 - 8700) (690

Respiratory symptoms among asthmatic 0 - 12 1-day lag 1 hr max. none 5700 medication-users -- shortness of breath 

Gent et al. (2003) 

 (700 - 10200) (270

Respiratory symptoms among asthmatic 0 - 12 1-day lag 8 hr max. none 6300 medication-users -- shortness of breath 

Gent et al. (2003) 

 (1200 - 10800) (480

Respiratory symptoms among asthmatic 0 - 12 0-day lag 1 hr max. PM2.5 15400 medication-users -- wheeze 

Gent et al. (2003) 

 (5500 - 24200) (218

*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 sympopulation are rounded to the nearest 100. Percents are rounded to the nearest tenth. Note: Numbers in parentheses are 95% confidence or credible intervals based on statistical uncertainty surrounding the O3 coefficient. 
5-55 

Table 5-13. Estimated Respiratory Symptoms Associated with Recent (April - September, 2002) O3 Conc

Background in Boston, MA 

Health Effects Assoc

Relevant Ba

Health Effects* Study Ages Lag Exposure Metric 

Other 

Pollutants 

in Model Incidence 

Inc

100,0

Po

Respiratory symptoms among asthmatic 0 - 12 1-day lag 1 hr max. none 6900 medication-users -- chest tightness 

Gent et al. (2003) 

 (1100 - 11800) (450

Respiratory symptoms among asthmatic 0 - 12 0-day lag 1 hr max. PM2.5 10800 medication-users -- chest tightness 

Gent et al. (2003) 

 (5000 - 15700) (197

Respiratory symptoms among asthmatic 0 - 12 1-day lag 1 hr max. PM2.5 10000 medication-users -- chest tightness 

Gent et al. (2003) 

 (4000 - 15000) (157

Respiratory symptoms among asthmatic 0 - 12 1-day lag 8 hr max. none 7200 medication-users -- chest tightness 

Gent et al. (2003) 

 (2400 - 11400) (930

Respiratory symptoms among asthmatic 0 - 12 1-day lag 1 hr max. none 7500 medication-users -- shortness of breath 

Gent et al. (2003) 

 (900 - 13200) (370

Respiratory symptoms among asthmatic 0 - 12 1-day lag 8 hr max. none 8300 medication-users -- shortness of breath 

Gent et al. (2003) 

 (1700 - 14000) (660

Respiratory symptoms among asthmatic 0 - 12 0-day lag 1 hr max. PM2.5 20100 medication-users -- wheeze 

Gent et al. (2003) 

 (7400 - 31000) (2900

*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 sympopulation are rounded to the nearest 100. Percents are rounded to the nearest tenth. Note: Numbers in parentheses are 95% credible intervals based on statistical uncertainty surrounding the O3 coefficient. 
5-56 

Table 5-14. Estimated Hospital Admissions Associated with Recent (April - September, 2004) O3 Concent

Health Effects Ass

Relevant 

Health Effects* Study Ages Lag Exposure Metric 

Other 

Pollutants in 

Model Incidence 

Inc

P

Hospital admissions Thurston et al. (1992)*** all 3-day lag 1 hr max. none 447 (unscheduled), respiratory illness (108 - 786) Hospital admissions Thurston et al. (1992)*** all 1-day lag 1 hr max. none 382 (unscheduled), asthma (81 - 683) 

*Incidences are rounded to the nearest whole number; incidences per 100,000 relevant population and percents are rounded to the neare**New York in this study is defined as the five boroughs of New York City. Note: Numbers in parentheses are 95% confidence or credible intervals based on statistical uncertainty surrounding the O3 coefficient. 

Table 5-15. Estimated Hospital Admissions Associated with Recent (April - September, 2002) O3 Concent

Health Effects As

Relevant 

Health Effects Study Ages Lag Exposure Metric 

Other 

Pollutants in 

Model Incidence 

In

Hospital admissions Thurston et al. (1992)*** all 3-day lag 1 hr max. none 608 (unscheduled), respiratory illness (147 - 1068) Hospital admissions Thurston et al. (1992)*** all 1-day lag 1 hr max. none 519 (unscheduled), asthma (110 - 928) 

*Incidences are rounded to the nearest whole number; incidences per 100,000 relevant population and percents are rounded to the neare**New York in this study is defined as the five boroughs of New York City. 

Note: Numbers in parentheses are 95% confidence or credible intervals based on statistical uncertainty surrounding the O3 coefficient. 
5-57 

Table 5-16. Estimated Non-Accidental Mortality Associated with Recent (April - September, 2004) 

Location Study Lag Exposure Metric Non-Accidental Mortality Associated 

Background 

Incidence Incidence pe

Relevant Po

Bell et al. (2004) distributed lag 24 hr avg. 6 0.4 

 (-26 - 38) (-1.8 - 2

distributed lag 24 hr avg. 12 0.8 

Atlanta 

Bell et al. -- 95 US Cities (2004) 

 (4 - 20) (0.3 - 1

distributed lag 24 hr avg. 7 1.0 

Boston Bell et al. -- 95 US Cities (2004) 

 (2 - 12) (0.3 - 1

Bell et al. -- 95 US Cities (2004) distributed lag 24 hr avg. 49 0.9 

 (16 - 81) (0.3 - 1

Schwartz (2004) 0-day lag 1 hr max. 394 7.3 

 (125 - 658) (2.3 - 1

0-day lag 1 hr max. 148 2.8 

Chicago 

Schwartz -- 14 US Cities (2004) 

 (46 - 250) (0.9 - 4

Bell et al. (2004) distributed lag 24 hr avg. 27 1.9 

 (-17 - 69) (-1.2 - 

distributed lag 24 hr avg. 17 1.2 

Cleveland 

Bell et al. -- 95 US Cities (2004) 

 (6 - 28) (0.4 - 

Bell et al. (2004) distributed lag 24 hr avg. 33 1.6  (-11 - 76) (-0.5 - 3Bell et al. -- 95 US Cities (2004) distributed lag 24 hr avg. 17 0.8 

 (6 - 28) (0.3 - 1

Schwartz (2004) 0-day lag 1 hr max. 128 6.2  (-21 - 274) (-1 - 13Schwartz -- 14 US Cities (2004) 0-day lag 1 hr max. 70 3.4 

 (22 - 117) (1.1 - 5

Ito (2003) 0-day lag 24 hr avg. 40 2.0 

Detroit 

 (-37 - 116) (-1.8 - 5

Houston Bell et al. (2004) distributed lag 24 hr avg. 35 1.0 
5-58 

Location Study Lag Exposure Metric Non-Accidental Mortality Associated 

Background 

Incidence Incidence pe

Relevant Po

 (2 - 67) (0.1 - Bell et al. -- 95 US Cities (2004) distributed lag 24 hr avg. 17 0.5 

 (6 - 28) (0.2 - 0

Schwartz (2004) 0-day lag 1 hr max. 93 2.7  (9 - 176) (0.3 - 5Schwartz -- 14 US Cities (2004) 0-day lag 1 hr max. 78 2.3 

 (24 - 130) (0.7 - 3

Bell et al. (2004) distributed lag 24 hr avg. 62 0.6  (-149 - 271) (-1.6 - 2

distributed lag 24 hr avg. 133 1.4 

Los Angeles Bell et al. -- 95 US Cities (2004) 

 (45 - 221) (0.5 - 2

distributed lag 24 hr avg. 60 0.7 

New York Bell et al. -- 95 US Cities (2004) 

 (20 - 100) (0.2 - 1

Bell et al. -- 95 US Cities (2004) distributed lag 24 hr avg. 23 1.5 

 (8 - 38) (0.5 - 2

1-day lag 24 hr avg. 82 5.4 

Philadelphia Moolgavkar et al. (1995) 

 (52 - 112) (3.4 - 7

Bell et al. (2004) distributed lag 24 hr avg. 12 1.0  (-36 - 59) (-3 - 4

distributed lag 24 hr avg. 18 1.4 

Sacramento 

Bell et al. -- 95 US Cities (2004) 

 (6 - 29) (0.5 - 2

Bell et al. (2004) distributed lag 24 hr avg. 3 1.0  (-6 - 13) (-1.7 - 3

distributed lag 24 hr avg. 3 0.9 

St Louis 

Bell et al. -- 95 US Cities (2004) 

 (1 - 5) (0.3 - 1

distributed lag 24 hr avg. 8 1.5 

Washington, D.C. Bell et al. -- 95 US Cities (2004) (3 - 14) (0.5 - 2

*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; incide

population and percents are rounded to the nearest tenth. Note: Numbers in parentheses are 95% confidence or credible intervals based on statistical uncertainty surrounding the O3 coefficient.
5-59 

Table 5-17. Estimated Non-Accidental Mortality Associated with Recent (April - September, 2002) O3 Co

Location Study Lag Exposure Metric 

Non-Accidental Mortality Associated 

Background L

Incidence Incidence per 

Relevant Pop

Bell et al. (2004) distributed lag 24 hr avg. 9 0.6 

 (-37 - 54) (-2.5 - 3.6

distributed lag 24 hr avg. 17 1.2 

Atlanta 

Bell et al. -- 95 US Cities (2004) 

 (6 - 29) (0.4 - 1.9

distributed lag 24 hr avg. 10 1.5 

Boston Bell et al. -- 95 US Cities (2004) 

 (3 - 17) (0.5 - 2.5

Bell et al. -- 95 US Cities (2004) distributed lag 24 hr avg. 69 1.3 

 (23 - 115) (0.4 - 2.1

Schwartz (2004) 0-day lag 1 hr max. 505 9.4 

 (161 - 840) (3 - 15.6

0-day lag 1 hr max. 191 3.6 

Chicago 

Schwartz -- 14 US Cities (2004) 

 (60 - 321) (1.1 - 6) 

Bell et al. (2004) distributed lag 24 hr avg. 61 4.3 

 (-38 - 157) (-2.7 - 11.

distributed lag 24 hr avg. 38 2.8 

Cleveland 

Bell et al. -- 95 US Cities (2004) 

 (13 - 64) (0.9 - 4.6

Bell et al. (2004) distributed lag 24 hr avg. 57 2.8  (-18 - 131) (-0.9 - 6.3Bell et al. -- 95 US Cities (2004) distributed lag 24 hr avg. 29 1.4 

 (10 - 48) (0.5 - 2.3

Schwartz (2004) 0-day lag 1 hr max. 181 8.8  (-30 - 385) (-1.4 - 18.Schwartz -- 14 US Cities (2004) 0-day lag 1 hr max. 99 4.8 

 (31 - 165) (1.5 - 8) 

Ito (2003) 0-day lag 24 hr avg. 69 3.4 

Detroit 

(-64 - 198) (-3.1 - 9.6
5-60 

Location Study Lag Exposure Metric 

Non-Accidental Mortality Associated 

Background L

Incidence Incidence per 

Relevant Pop

Bell et al. (2004) distributed lag 24 hr avg. 29 0.9  (2 - 57) (0.1 - 1.7Bell et al. -- 95 US Cities (2004) distributed lag 24 hr avg. 14 0.4 

 (5 - 24) (0.1 - 0.7

Schwartz (2004) 0-day lag 1 hr max. 85 2.5  (8 - 161) (0.2 - 4.7

0-day lag 1 hr max. 71 2.1 

Houston 

Schwartz -- 14 US Cities (2004) 

 (22 - 119) (0.7 - 3.5

Bell et al. (2004) distributed lag 24 hr avg. 51 0.5  (-124 - 224) (-1.3 - 2.4

distributed lag 24 hr avg. 110 1.2 

Los Angeles Bell et al. -- 95 US Cities (2004) 

 (37 - 184) (0.4 - 1.9

distributed lag 24 hr avg. 105 1.2 

New York Bell et al. -- 95 US Cities (2004) 

 (35 - 174) (0.4 - 2) 

Bell et al. -- 95 US Cities (2004) distributed lag 24 hr avg. 37 2.4 

 (12 - 62) (0.8 - 4.1

1-day lag 24 hr avg. 132 8.7 

Philadelphia Moolgavkar et al. (1995) 

 (83 - 180) (5.5 - 11.

Bell et al. (2004) distributed lag 24 hr avg. 16 1.3  (-48 - 78) (-3.9 - 6.4

distributed lag 24 hr avg. 23 1.9 

Sacramento 

Bell et al. -- 95 US Cities (2004) 

 (8 - 39) (0.6 - 3.2

Bell et al. (2004) distributed lag 24 hr avg. 6 1.9  (-11 - 23) (-3.1 - 6.7

distributed lag 24 hr avg. 6 1.7 

St Louis 

Bell et al. -- 95 US Cities (2004) 

 (2 - 10) (0.6 - 2.8

distributed lag 24 hr avg. 15 2.6 

Washington, D.C. Bell et al. -- 95 US Cities (2004) 

 (5 - 25) (0.9 - 4.4

*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; incide

relevant population and percents are rounded to the nearest tenth. Note: Numbers in parentheses are 95% confidence or credible intervals based on statistical uncertainty surrounding the O3 coefficient.
5-61 

 We observe from Tables 5-16 and 5-17 that estimates of O3-related non-accidental 

mortality reported by Schwartz (2004) for Chicago, 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 O3 concentration in Schwartz 

(2004), rather than the 24-hr average, as the exposure metric. The changes from recent (2004 or 

2002)) 1-hr maximum to background 1-hr maximum O3 concentrations were generally larger in 

the assessment locations than the corresponding changes from recent 24-hr average to 

background 24-hr average O3 concentrations. For example, for 2004 air quality the estimated 

O3-related (non-accidental) mortality in Detroit based on Bell et al. (2004), which used a 24-hr 

average indicator, ranged from 0.2% (based on 95 city model) to 0.4% of total incidence (based 

on single-city model). In contrast, the estimated O3-related (non-accidental) mortality in Detroit 

based on Schwartz (2004), which used a 1-hr maximum O3 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 O3 concentrations within specified ranges for the warm 

O3 season (April 1 to September 30) in two recent years. While the current O3 standard is 

expressed in terms of an 8-hr daily maximum inidicator, the large multicity non-accidental (Bell 

et al. (2004) and cardiorespiratory (Huang et al. (2004) mortality studies reported concentrationresponse relationships for 24-hr average O3 levels. Thus, the intervals shown in this figure are 

for 24-hr average concentrations. To provide some perspective on the 24-hr intervals shown, 

scatter plots comparing 8-hr daily 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 average 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 O3-related non-accidental mortality was associated 

with O3 concentrations less than 0.06 ppm, 24 hr average, and most of that was associated with 

O3 concentrations less than 0.04 ppm, 24-hr average. As shown in Figure 5-6b, in 2002, all O3-

related non-accidental mortality was associated with O3 concentrations less than 0.08 ppm, 24-hr 

average and the great majority was associated with O3 concentrations less than 0.05 ppm, 24-hr 

average. The results for cardiorespiratory mortality 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-Accidental Mortality Associated with Short-

 Term Exposure to Recent O3 Concentrations Above Background for the 

 Period April – September (Based on Bell et al., 2004) – Total and Contribution 

 of 24-Hour Average O3 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 O3 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%

Atlanta

Boston

Chicago

Cleveland

Detroit

Houston

Los

Angeles

New York

PhiladelphiaSacramento

St. Louis

Washington,

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%

Atlanta

Boston

Chicago

Cleveland

Detroit

Houston

Los

Angeles

New York

PhiladelphiaSacramento

St. Louis

Washington,

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 ppm
5-63 

5.4.2 Just Meeting Current and Alternative Ozone Standards 

 As described in Chapter 4 and briefly in section 5.3.2.2, the risk estimates described in 

this section represent the risks for two separate O3 seasons based on adjusting the O3 levels 

observed in 2004 or 2002 to simulate O3 levels associated with just meeting the current 0.08 ppm 

standard and several potential alternative 8-hr standards, using the 3-year design value from the 

2002-2004 time period. To facilitate comparison of risk estimates across the urban areas, figures 

used in this section present summaries of the 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-highest daily maximum 8-hr 

average form of the current standard. We present only limited results for several additional 

alternative standards in this section. Risk estimates for three additional alternative 8-hr standards 

(0.084 and 0.074 ppm, using an average of the annual 3rd-highest daily maximum 8-hr 

concentrations averaged over the three year period, and 0.074 ppm using an average of the 

annual 5th-highest daily maximum 8-hr averages over the three year period are more fully 

presented in tables in the Risk Assessment TSD. Because we had to simulate the profiles of O3 

concentrations that just meet the current and alternative 8-hour daily maximum O3 standards in 

each location, there is additional uncertainty surrounding estimates of the reduced incidence 

associated with O3 concentrations that just meet these O3 standards. 

 This section first discusses the risk estimates for lung function responses in all and 

asthmatic school age children, which are based on exposure-response relationships derived from 

controlled human exposure studies, and then risk estimates are explored for respiratory 

symptoms in asthmatic children, respiratory-related hospital admissions, and premature mortality 

which are based on concentration-response relationships obtained from epidemiological studies 

 The risk estimates for lung function responses are for the O3 season, which is all year in 3 

of the study areas (Houston, Los Angeles, and Sacramento) and which is generally 6-7 months 

long in the other 9 urban study areas (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 urban 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 adjusting 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 age children estimated 

to experience at least one FEV1 decrement > 15% during the O3 season across the 12 urban areas 

for recent air quality (2002) and upon just meeting the current and several alternative 8-hr 

standards. Figure 5C-1 in Appendix 5C of this 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 adjusting 2002 air quality data and 0.8 - 2.2% based 

on adjusting 2004 air quality data. In terms of total occurrences of FEV1 decrement > 15% 

during the O3 season, Table 5-9 shows a range of median estimates from about 72,000 to over 

750,000 responses during the O3 season for all school age children 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 O3 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 FEV1 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 would 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 standards, 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 comparing the estimated number of 

occurrences shown in Tables 5C-5 with the number 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 given response in an O3 season. For example, for Atlanta it is estimated that 

36,000 children would have an FEV1 decrement > 15% and that there would be 196,000 

occurrences of this response in this same population when 2002 air quality is adjusted to just 

meet the current 8-hr standard. Thus, on average it is estimated that there would be about 5 

occurrences per O3 season per responding child for air quality 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 O3 season. 

 Figure 5-8 shows the 95% confidence intervals for the lung function risk estimates for 

each of the 12 urban areas using the FEV1 decrement > 15% health response for recent O3 levels 

(2002) and for 2002 air quality adjusted to just meet the current and alternative 8-hr average nth

daily maximum standards. A comparable figure (Figure 5C-2) using 2004 air quality and 

adjusting 2004 air quality to just meet the current and alternative 8-hr standards 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 FEV1 decrement > 10% during the O3 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 maximum standards. Figure 5C-3 in Appendix 5C of this 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 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 FEV1 decrement > 15% during the O3 season, Table 5-9 shows a 

range of median estimates from about 61,000 to 240,000 responses during the O3 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 nearly 510,000 responses across the 5 urban areas 

associated with adjusting 2002 O3 concentrations to just meeting the current 8-hour standard. 

 Figure 5-10 shows the 95% confidence intervals for the lung function risk estimates for 

asthmatic school age children in each of the 5 urban areas using the FEV1 decrement > 10% 

health response for recent O3 levels (2002) and for 2002 air quality 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 quality and adjusting 2004 air quality to just meet the current and 

alternative 8-hr standards is included in Appendix 5C. 

 Figure 5-11 summarizes respiratory symptom response risk estimates associated with O3

exposures during the April to September period for moderate/severe asthmatic children ages 0 to 

12 in the Boston urban area based on the concentration-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) presents 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 PM2.5. 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 involving chest tightness (using the concentrationresponse relationship with only O3 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 

and these are reduced to 3,100 (based on adjusting 2004 air quality) to 4,600 days upon meeting 

the most stringent alternative examined (0.064 ppm, 4th-highest daily maximum 8-hr average). 

These same ranges correspond to 8 - 11% of total incidence of chest tightness upon meeting the 
5-66 

Figure 5-7. Percent of All Children (Ages 5-18) Engaged 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 4th-highest Daily Maximum 8-Hour 

Standards, for Location-Specific O3 Seasons (Based on Adjusting 2002 Air 

Quality)* 

Recent (2002)

0.084/4

0.080/4

0.074/4

0.070/4

0.064/4

Atlanta

Boston

Chicago

Cleveland

Detroit

Houston

Los Angeles

New York

Philadelphia

Sacramento

St. Louis

Washington, D.C.

0%

1%

2%

3%

4%

5%

6%

7%

8%

9%

10%

Percent All Children Respondin

g

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, 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 

three year period be at or below the specified level (m ppm). 95% credible intervals based on statistical uncertainty 

surrounding the O3 coefficient are presented in Table 5C-2 in Appendix 5C. 
5-67 

Figure 5-8. Percent of All Children (Ages 5-18) Engaged in Moderate Exertion Estimated to Experience At 

Least One Lung Function Response (Decrement in FEV1 ≥ 15 %) Associated with Recent Air 

Quality (2002) and Just Meeting the Current and Alternative Average nth Daily Maximum 8-Hour 

Standards, for Location-Specific O3 Seasons (Based on Adjusting 2002 Air Quality)* 

Atlanta 

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/Standards

Percent All Children 

Responding (and 95% CI)

Boston 

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/Standards

Percent All Children 

Responding (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/Standards

Percent All Children 

Responding (and 95% CI)

Cleveland 

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/Standards

Percent 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/Standards

Percent All Children Responding 

(and 95% CI)

Houston 

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/Standards

Percent All Children Responding 

(and 95% CI)
5-68 

Figure 5-8. (Continued) 

Los Angeles 

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/Standards

Percent All Children Respondin

g

(and 95% CI)

New York 

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/Standards

Percent All Children Respondin

g

(and 95% CI)

Philadelphia 

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/Standards

Percent All Children Respondin

g

(and 95% CI)

Sacramento 

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/Standards

Percent All Children Respondin

g

(and 95% CI)

St. Louis 

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/Standards

Percent All Children Respondin

g

(and 95% CI)

Washington, D.C. 

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/Standards

Percent All Children Respondin

g

(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) percents of children. The bars are 95% credible intervals based on statistical 

uncertainty surrounding the O3 coefficient. 
5-69 

Figure 5-9. Percent of Asthmatic Children (Ages 5-18) Engaged in Moderate Exertion 

Estimated to Experience At Least One Lung Function Response (Decrement in 

FEV1 ≥ 10%) Associated with Exposure to O3 Concentrations That Just Meet 

the Current and Alternative Average 4th-highest Daily Maximum 8-Hour 

Standards, for Location-Specific O3 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 O3 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 Respondin

g

Ozone Conc./

Standards (ppm)

Urban Areas
5-70 

Figure 5-10. Percent of Asthmatic Children (Ages 5-18) Engaged in Moderate Exertion Estimated 

to Experience At Least One Lung Function Response (Decrement in FEV1 ≥ 10 %) 

Associated with Recent Air Quality (2002) and Exposure to O3 Concentrations That 

Just Meet the Current and Alternative 8-Hour Standards, for Location-Specific O3

Seasons: Based on Adjusting 2002 O3 Concentrations* 

Atlanta 

0%

5%

10%

15%

20%

25%

Recent (2002)

0.084/4

0.074/4

0.064/4

Ozone Concentrations/Standards

Percent Asthmatic Children

Responding (and 95% CI)

Chicago 

0%

5%

10%

15%

20%

25%

Recent (2002)

0.084/4

0.074/4

0.064/4

Ozone Concentrations/Standards

Percent Asthmatic Children

Responding (and 95% CI)

Houston 

0%

5%

10%

15%

20%

25%

Recent (2002)

0.084/4

0.074/4

0.064/4

Ozone Concentrations/Standards

Percent Asthmatic Children

Responding (and 95% CI)

Los Angeles 

0%

5%

10%

15%

20%

25%

Recent (2002)

0.084/4

0.074/4

0.064/4

Ozone Concentrations/Standards

Percent Asthmatic Children

Responding (and 95% CI)

New York 

0%

5%

10%

15%

20%

25%

Recent (2002)

0.084/4

0.074/4

0.064/4

Ozone Concentrations/Standards

Percent Asthmatic Children

Responding (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. 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 (e.g., 0.084 ppm). Percents are median (0.5 

fractile) percents of children. The bars are 95% 

credible intervals based on statistical uncertainty 

surrounding the O3 coefficient.
5-71 

current 8-hr standard and to about 5.5 - 8% of total incidence of chest tightness upon meeting a 

0.064 ppm, 4th-highest daily maximum 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 O3

concentration-response relationship that included PM2.5 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 meeting the current 8-hr standard and these 

estimates are reduced to 9,000 (based on adjusting 2004 air quality) to about 13,000 (based on 

adjusting 2002 air quality) upon meeting a 0.064 ppm, 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 shown in Tables 5C-7 through 5C10 (Appendix 5C) based on adjusting 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 O3 concentrations 

in excess of background levels from April through September under recent air quality and when 

the current and alternative 8-hr standards are just met based on adjusting 2004 and 2002 air 

quality data, respectively. For total respiratory illness, Figure 5-12 shows about 6.4 cases per 

100,000 relevant population, which represents 1.5% of total incidence or 513 cases when 2002 

O3 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 population, which represents about 3.3% of total incidence or 438 

cases for this same air quality scenario. For 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 meeting the current 8-hr standard to 4.6 cases 

per 100,000 under the most stringent 8-hr standard (i.e., 0.064 ppm, average 4th-highest daily 

maximum) analyzed. The comparable estimates based on adjusting 2004 air quality are shown 

in Figure 5C-6 (Appendix 5C) and are somewhat higher, but show a similar pattern of gradual 

reduction. Confidence intervals, based on statistical uncertainty reflecting sample size 

considerations for incidence, incidence per 100,000 relevant population, 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 current and potential alternative standards. 

 Additional respiratory-related hospital admission estimates for three other locations are 

provided in the Risk Assessment TSD. We note that the concentration-response functions for 

each of these locations examined different outcomes in different age groups (e.g., > age 30 in 

Los Angeles, >age 64 in Cleveland and Detroit, 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 statistically significant and the median estimates were 
5-72 

Figure 5-11. Estimated Symptom-Days for Chest Tightness Among Moderate/Severe 

Asthmatic Children (Ages 0 – 12) in Boston Associated with Recent (AprilSeptember 2002) O3 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% confidence intervals associated with 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

11,000

Estimated Symptom-Days

Ozone Stds. 

(ppm)

Concentration-Response Model
5-73 

Figure 5-12. Estimated Incidence of (Unscheduled) Respiratory Hospital Admissions per 

100,000 Relevant Population in New York Associated with Recent (April – 

September, 2002) O3 Levels and with O3 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 Category
5-74 

Figure 5-13. Estimated Incidence of Non-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. Cities 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

Atlanta

Boston

Chicago

Cleveland

Detroit

Houston

Los

Angeles

New

York

Philadelphia

Sacramento

St. Louis

Washington, D.C.

0

0.5

1

1.5

2

2.5

3

Incidence per 100,000 Relevant Population

Ozone

Stds.

(ppm)

Urban Areas
5-75 

negative for 0- and 1-day lags and small but positive 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 O3 concentrations above background that just meet the current 

and several potential alternative 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 meeting alternative 8-hr standards based on the O3

coefficients estimated in the studies based on adjusting 2002 air quality data. Ranges reflecting 

the statistical uncertainty, taking into account sample size considerations, based either on the 95 

percent confidence intervals around those estimates (if the coefficients were estimated using 

classical statistical techniques) or on the 95 percent credible intervals (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 mortality. Additional risk 

estimates for cardiorespiratory mortality are included 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) presents the comparable figure for 

2004 air quality and just meeting alternative standards based on adjusting 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 Atlanta is around 0.9% of total incidence and the 

95% credible interval is about 0.3% to about 1.5% of total incidence. While the 95% credible 

intervals get progressively smaller as one considers more stringent standards, as discussed 

previously these credible intervals do not consider overall model uncertainty (e.g., whether or not 

the shape of the concentration-response relationship is best represented by a log linear 

relationship versus a more sigmoidal shape, particularly at lower O3 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 section 5.4.1 for risks associated with recent year O3

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 urban areas between that associated with a recent 

year of air quality and just meeting the current 8-hr standard, the reductions associated with 

progressively more stringent alternative 8-hr standards are more modest. Based on adjusting 
5-76 

Figure 5-14. Annual Warm Season (April to September) Estimated O3-Related Non-Accidental 

Mortality Associated with Recent (2002) O3 Levels and Levels Just Meeting 

Alternative 8-hr O3 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/Standards

Mortality per 100,000 Relevant 

Population (and 95% CI)

Boston 

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/Standards

Mortality per 100,000 Relevant 

Population (and 95% CI)

Chicago 

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/Standards

Mortality per 100,000 Relevant 

Population (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/Standards

Mortality per 100,000 Relevant 

Population (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/Standards

Mortality per 100,000 Relevant 

Population (and 95% CI)

Houston 

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/Standards

Mortality per 100,000 Relevant 

Population (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

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/Standards

Mortality per 100,000 Relevant 

Population (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/Standards

Mortality per 100,000 Relevant 

Population (and 95% CI)

Philadelphia 

0.0

0.6

1.2

1.8

2.4

3.0

3.6

4.2

4.8

Recent (2002)

0.084/4

0.084/3

0.080/4

0.074/5

0.074/4

0.074/3

0.070/4

0.064/4

Ozone Concentrations/Standards

Mortality per 100,000 Relevant 

Population (and 95% CI)

Sacramento 

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/Standards

Mortality per 100,000 Relevant 

Population (and 95% CI)

St. Louis 

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/Standards

Mortality per 100,000 Relevant 

Population (and 95% CI)

Washington, D.C. 

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/Standards

Mortality per 100,000 Relevant 

Population (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 are 95% credible intervals based on statistical uncertainty 

surrounding the O3 coefficient.
5-78 

2002 air quality data, the range of median estimates associated with O3 upon just meeting the 

current standard is about 0.3 to 2.4 cases per hundred thousand relevant population across the 12 

urban areas and this range is reduced to about 0.1 to 1.7 cases per 100,000 relevant population 

upon just meeting the most stringent alternative standard analyzed (0.064 ppm, average 4thhighest daily maximum 8-hr average) We also note that the risk 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 alternative standards based on adjusting 2002 data. 

 As shown in Table 5C-13 through 5C-16 in Appendix 5C of this chapter, estimated O3-

related (non-accidental) mortality 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 those locations in large part because Schwartz 

used the 1-hr maximum O3 concentration, rather than the 24-hr average, as the exposure metric. 

The changes from 1-hr maximum O3 concentrations that just meet the current 8-hr O3 standard to 

background 1-hr maximum O3 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 O3 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 O3 concentrations discussed in section 5.4.1. Using simulated O3 concentrations 

that just meet the current 8-hour standard based on 2004 air quality data, all O3-related non-accidental 

mortality was associated with O3 concentrations less than 0.06 ppm, 24-hr average and most of that 

was associated with O3 concentrations less than 0.04 ppm, 24-hr average. Using simulated O3

concentrations that just meet the current 8-hour standard based on 2002 air quality data, all O3-related 

non-accidental mortality was associated with O3 concentrations less than 0.08 ppm, 24-hr average and 

the great majority was associated with O3 concentrations less than 0.05 ppm, 24-hr average. The 

results for cardiorespiratory mortality follow a similar 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 within an urban area were developed and are included in Appendix 5A.2 

to provide some perspective on the 24-hr intervals shown. These scatter 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 Non-Accidental Mortality Associated with 

Short-Term Exposure to O3 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 Contribution of 24-Hour Average O3 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 O3 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%

Atlanta

Boston

Chicago

Cleveland

Detroit

Houston

Los Angeles

New York

PhiladelphiaSacramento

St. Louis

Washington,

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%

Atlanta

Boston

Chicago

Cleveland

Detroit

Houston

Los Angeles

New York

PhiladelphiaSacramento

St. Louis

Washington,

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 ppm
5-80 

5.4.3 Sensitivity Analyses 

 We have conducted sensitivity analyses examining the influence of alternative 

assumptions about background (i.e., PRB) levels on the lung function and mortality risk 

estimates and the impact of alternative assumptions about the shape of the 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 O3-related risks above 0 ppm) 

associated with alternative standards relative to the total risks associated with just meeting the 

current standard, without subtracting estimated risks 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 O3 were estimated for all days above 0 ppm for two recent years 

of air quality (2002 and 2004), the largest part of the total risk was related to levels between 0 

and our baseline estimated PRB levels. Adopting the approach suggested by CASAC would 

place emphasis on the region of the concentration-response relationship (i.e., at levels below 

0.035 ppm down to 0 ppm) where there is the greatest uncertainty about whether effects occur. 

In addition, the approach suggested by CASAC only addresses risks relative to the current 

standard and does not address the risk remaining upon meeting the current and alternative 

standards, which is an important consideration in setting a NAAQS. For assessing risks 

remaining upon just meeting a standard, EPA has decided 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 standards relative to the current standard and have found that these 

estimates are generally insensitive to alternative assumptions about PRB. Similarly, changes in 

non-accidental mortality risk estimates for just meeting alternative standards relative to the 

current standard also are less sensitive to assumptions about the levels used to represent PRB. 

We recognize that the lung function and non-accidental mortality risk estimates remaining upon 

just meeting the current and alternative standards 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 O3 concentrations discussed in this chapter and in the Risk 

Assessment TSD have been developed– either based on O3 concentrations from a recent year of 
5-81 

air quality or O3 concentrations “rolled back” to just meet a standard – above PRB. We selected 

three locations – Atlanta, 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 O3 exposure for 

all 12 urban areas. For all of the urban areas, except Atlanta, the lower PRB estimates were 

calculated by subtracting 5 ppb from 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 calculated by adding 5 ppb to the original PRB 

estimates.16

 The lung function sensitivity analyses for alternative estimates of PRB were run for all 

school age children, with response defined as a decrement in FEV1 >15%, and for asthmatic 

school age children, with lung function response defined as a decrement in FEV1 >10%. Table 

5C-17 shows the results of this sensitivity analysis for all school age children in terms of the 

number of children estimated to experience a lung function response of concern (i.e., FEV1

>15%) based on adjusting 2002 and 2004 air quality to just meet the current and two alternative 

8-hr standards. Additional tables showing the sensitivity analysis results for total occurrences of 

this lung function response for all children are included in the Risk Assessment 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 higher assumed PRB levels on lung function 

responses in all school age children (with responses defined as a decrement in FEV1 > 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 with a response. In terms of total occurrences of moderate lung 

function responses, different assumptions about PRB had a somewhat larger impact, but the 

impact was still generally less than 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 from the current 8-hr standard based on adjusting 

2002 air quality data in each of the 12 urban areas. One observes that for most, but not all of the 

locations, the general pattern is not significantly impacted by the choice of PRB assumptions. The 

 

16Summarizing its assessment of the validity of the GEOS-CHEM model, the O3 CD 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 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 O3 levels associated with just meeting the alternative standards based on this year of air quality 

data. 

 Results of the PRB sensitivity analysis for non-accidental mortality associated with O3

exposures expressed in terms of absolute estimates are presented in Table 5C-18 for 2002 air 

quality adjusted to just meet the current standard. 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 standards are included in the Risk Assessment TSD (see 

section 4.3 and Appendix I). Table 5C-18 illustrates the impact of alternative assumed PRB 

levels on incidence of O3-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 estimates of non-accidental mortality incidence per 

100,000 that are often 50 to 100% greater than the 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 O3 concentrations just 

meeting the current standard are substantially lower than O3 concentrations observed for the 

recent years of air quality (for most of the urban areas), the change 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 estimate. 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 impacted, in terms of being classified as above or below PRB, by 

the assumptions concerning PRB levels. 

5.4.3.2 Impact of Alternative Assumptions About the Shape of Exposure-Response 

Relationships for Lung Function Decrements 

 As described in section 5.3.1.3, the exposure-response functions used in the primary 

analyses are based on the assumption that the relationship between exposure and response has a 
5-83 

Figure 5-16. Sensitivity Analysis of Estimated Percent Change in O3-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 O3 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 Standards

Percent 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 Standards

Percent 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 Standards

Percent 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 Standards

Percent 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 Standards

Percent 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 Standards

Percent Change from Current Standard

Original PRB Estimates

Lower PRB Estimates

Higher PRB Estimates
5-84 

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 Standards

Percent 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 Standards

Percent 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 Standards

Percent 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 Standards

Percent 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 Standards

Percent 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 Standards

Percent 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, 4th-highest daily 

maximum 8-hr average. The figure also compares the current standard to a recent year of air quality. 
5-85 

Figure 5-16b. Based on Adjusting 2002 O3 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 Standards

Percent 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 Standards

Percent 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 Standards

Percent 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 Standards

Percent 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 Standards

Percent 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 Standards

Percent Change from Current Standard

Original PRB Estimates

Lower PRB Estimates

Higher PRB Estimates
5-86 

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 Standards

Percent 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 Standards

Percent 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 Standards

Percent 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 Standards

Percent 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 Standards

Percent 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 Standards

Percent 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, 4th-highest daily 

maximum 8-hr average. The figure also compares the current standard to a recent year of air quality. 
5-87 

logistic form with 90 percent probability and a linear (hockeystick) form with 10 percent 

probability. We have conducted sensitivity analyses which examine the influence of two 

alternative assumptions about the exposure-response functions for lung function decrements in 

all and asthmatic school age children. These alternative exposure-response functions are based 

on an 80 percent logistic/20 percent linear split and a 50 percent logistic/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 FEV1 ≥ 15% for all school age children for a recent year of air quality as well as when O3

concentrations just meet each of three 4th-highest 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 estimated number of asthmatic school age children experiencing at 

least one lung function response, defined as a change in FEV1 ≥ 10%. 

 Figures 5-17a and b and 5-18a and b show the impacts of alternative estimates of 

exposure-response functions on estimated percent changes in response among all school age 

children and asthmatic school age children, respectively, when O3 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 reflects a reduction in risk relative to just 

meeting the current 8-hr standard. Since the comparisons are with respect 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 logistic/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 estimates. 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 assessment during the prior O3

NAAQS review. We recognize that two of the health endpoints, lung function (FEV1) 

decrements for children and respiratory-related and asthma hospital admissions were included in 
5-88 

Figure 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 FEV1 >15% 

Figure 5-17a. Based on Adjusting 2004 O3 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 Standards

Percent 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 Standards

Percent 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 Standards

Percent 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 Standards

Percent 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 Standards

Percent 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 O3 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 Standards

Percent 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 Standards

Percent 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 Standards

Percent 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 Standards

Percent 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 Standards

Percent 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 Standard in Numbers of Asthmatic Children (Ages 

5-18) Engaged in Moderate Exertion Experiencing at Least One Decrement in FEV1 >10% 

Figure 5-18a. Based on Adjusting 2004 O3 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 Standards

Percent 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 Standards

Percent 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 Standards

Percent 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 Standards

Percent 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 Standards

Percent 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 O3 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 Standards

Percent 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 Standards

Percent 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 Standards

Percent 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 Standards

Percent 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 Standards

Percent 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, and 

50/50 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 asthmatic 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 for the current and prior review are based on 

exposure distributions generated by running O3 exposure models and exposure-response 

relationships developed using the available controlled human exposure studies data. There have 

been significant changes in the exposure model 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 exertion associated with just meeting the current 8-hr 

standard between the past and current reviews. This 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-shaped), and changes in estimates for PRB used in 

the assessments, no direct comparison is being made of the differences in lung function risk 

estimates for children between the current and prior review. 

 We note that the current estimates for O3-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 O3 NAAQS review. Both the prior and current assessments used the 

same concentration-response functions for these health outcomes. The main reason for higher 

estimates in the current assessment is the use of a single value of 0.04 ppm for background in the 

prior review which is higher than the current modeled values for background in the current 

assessment which are in the range of about 0.015 to 0.035 ppm. Thus, under the current risk 

assessment O3 levels above background but below 0.04 ppm are contributing additional 

estimated cases that were not included in the assessment for the prior O3 NAAQS review. 

5.4.5 Key Observations 

 In considering the quantitative estimates from the risk assessment the limitations and 

uncertainties associated with the risk estimates discussed in section 5.3.1.4 for lung function 

decrements and section 5.3.2.5 for respiratory symptoms, hospital admissions, and pre-mature 

mortality should be kept in mind. It is also important to consider the degree of confidence about 

the extent to which O3 is causally related to each of the effects for which risk estimates were 

produced (see section 3.7.5). For example, there is clear and convincing evidence of causality 

for lung function decrements in healthy children under moderate exertion for 8-hr average O3
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exposures. We also judge that there is strong evidence for a causal relationship between 

respiratory symptoms in asthmatic children and O3 exposures and between hospital admissions 

for respiratory causes and ambient O3 exposures. There is greater uncertainty and somewhat less 

confidence about the relationship between O3 and non-accidental and cardiorespiratory mortality, 

although the CD’s overall evaluation is that it is highly suggestive that this relationship exists. 

Recent O3 Air Quality Levels 

Section 5.4.1 has presented risk estimates associated 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 FEV1 decrement > 15% due to 8-hr O3 exposures 

during the O3 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 (based on 2002 air quality). In terms of 

percent of this population the ranges 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 O3 season ranged from 

about 4 to 8 depending on urban area and year. 

• The ranges in median estimates of the number of asthmatic school age children (ages 5-

18) estimated to experience at least one FEV1 decrement >10% due to 8-hr O3 exposures 

during the O3 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 estimates 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 are 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 experience this lung function response, results in each child being 

estimated to have on average between roughly 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. The 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 quality). In terms 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 median 
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estimates for New York are about 380 (based on 2004 air quality) and about 520 (based 

on 2002 air quality) O3-related excess hospital admissions for asthma. For 2004 and 

2002 air quality, these estimates represent about 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 incidence. 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 O3-related non-accidental mortality reported by Schwartz (2004) for 

Chicago, 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 O3 concentration in Schwartz (2004), rather 

than the 24-hr average, as the exposure metric. 

• Examining the contribution of various O3 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 associated with concentrations less than 0.04 ppm 

for 2004 air quality. For 2002, all of the O3-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 O3

air quality relationships between 24-hr average concentrations averaged over the urban 

monitors in an urban area on a given day and the highest daily maximum 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 the highest fixed-site 

monitor within an urban area. 

Meeting the Current and Alternative 8-hr Standards 

 Section 5.4.2 has presented risk estimates associated with just meeting the current and 

several potential alternative 8-hr standards based on adjusting 2004 and 2002 monitoring data 

using design values for the 2002-2004 time period. Presented below are key observations 

resulting from this part of the risk assessment. 

• In comparing risk estimates for alternative standards, uncertainties in quantifying the 

health risks associated ambient O3 concentrations would be expected to remain relatively 

constant in different models. Thus, we have greater confidence in relative comparisons 

in risk estimates between alternative standards than in the absolute magnitude of risk 
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estimates associated with any particular standard. As discussed in section 5.4.3.1, 

differences in risk between alternative standards (e.g., reductions in risk for alternative 

standards relative to the current standard or recent air 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 O3 concentrations combined with the use of a 3-

year design value to determine the amount of air quality adjustment to be applied to each 

year analyzed, results in significant 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 number of school age children (ages 5-18) 

estimated to experience at least one FEV1 decrement > 15% due to 8-hr O3 exposures 

during the O3 season across the 12 urban areas when the 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 are 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 alternative 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 range 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 O3 season ranged from about 4 to 10 for air quality just 

meeting the current standard across the 12 urban areas (based on 2002 air quality). The 

average number of occurrences per child ranged 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 standards 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 number of asthmatic school age children (ages 5-

18) estimated to experience at least one FEV1 decrement > 10% due to 8-hr O3 exposures 

during the O3 season across the five urban areas are 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 meeting 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 O3 season ranged from 
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about 6 to 11 associated with just meeting 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 stringent alternative examined (0.064 ppm, 4th-highest daily 

maximum 8-hr average). The risk estimates associated 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 involving chest tightness 

(using the concentration-response relationship with only O3 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 and these are reduced to 3,100 (based on 

adjusting 2004 air quality) to 4,600 days upon meeting the most stringent alternative 

examined (0.064 ppm, 4th-highest daily maximum 8-hr average). These same ranges 

correspond to 8 to 11% of total 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 maximum 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 locations (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 population, which represents about 2.4% of total incidence or 

313 cases upon just meeting the current standard based on adjusting 2004 air quality data. 

For increasingly more stringent alternative 8-hr standards, a gradual reduction in the 

cases per 100,000 relevant population is observed from 3.9 cases per 100,000 upon just 

meeting the current 8-hr standard 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 current standard. For increasingly more 

stringent alternative 8-hr standards, a gradual 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 incidence for non-accidental mortality (based on Bell 

et al., 2004 – 95 cities concentration-response 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 quality data). Adjusting 2002 air quality data to just meet 

the 0.064 ppm, standard results in a 40 percent reduction in non-accidental mortality 

relative to just meeting the current 8-hr standard . The patterns for cardiorespiratory 

mortality are similar. The aggregate O3-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 O3 concentrations that just meet the current and 
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alternative 8-hour standards based 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-accidental and cardiorespiratory 

mortality upon just meeting the current 8-hr standard is associated with 24-hr O3

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 maximum 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 O3-related incidence of morbidity and 

mortality across the 12 urban areas analyzed for both recent years of air quality and for 

air quality adjusted to simulate just meeting 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 factors including varying activity patterns and air 

exchange rates, differences in baseline incidence rates, and differences in susceptible 

populations and the age distribution across the 12 urban areas. For the lung function part 

of the risk assessment, spatial variability in air quality and population exposure inputs has 

been included in the assessment by use of a location specific exposure analysis and 

location specific input data to that analysis. For the epidemiology-based health 

endpoints, spatial variability in key inputs has been embedded 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 O3

and the health endpoints included in the assessment actually reflect causal relationships. 

For lung function decrements, respiratory symptoms in moderate to severe asthmatic 

children, and respiratory-related hospital admissions there is clear and very strong 

evidence supporting the judgment that the relationships are causal. With respect to nonaccidental and cardiorespiratory mortality, there is greater uncertainty, with the CD 

concluding that the overall body of evidence is highly suggestive that O3 directly or 

indirectly contributes to nonaccidental and cardiopulmonary-related mortality (CD, p. 8-

78). Given the overall evidence, including the strong evidence from the time-series 

studies reporting associations with non-accidental and cardiorespiratory mortality, along 

with information about potential mechanisms and a range of health effects observed in 

controlled human exposure studies (i.e., increased lung inflammation, impacts on host 

defense, and increased airway responsiveness), and strong evidence showing respiratoryrelated hospital admissions and emergency department visits for asthmatics, the staff 

judges that there is a likely causal relationship between O3 exposures and non-accidental 

and cardiorespiratory mortality. 

• Statistical uncertainty in the exposure-response relationships associated with sampling 

error has been characterized in the lung function part of the risk assessment. Other 
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important uncertainties in the exposure-response relationship for the lung function health 

outcomes include: 

- uncertainty associated with the shape of the exposure-response relationship, 

which also has been considered using a Bayesian Markov Chain Monte Carlo 

approach recommended by members of the 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 for subjects engaged in moderate exertion to 

estimate response associated with 8-hr exposures under moderate or greater 

exertion; 

- uncertainty about whether O3-induced responses are reproducible, although this 

is generally supported by other controlled 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 represent 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 comparable 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 O3 exposure; and 

- uncertainty in the estimated exposure-response due to assumption that the 

response would not be affected by the presence of other co-pollutants. 

• Uncertainties related to estimating the concentration-response relationships for the 

epidemiological-based part of the risk assessment include: 

 - statistical uncertainty due to sampling error which is characterized in the 

 assessment; 

 - model uncertainty (i.e., uncertainty about the shape and magnitude of the 

 concentration-response relationship taking into account lags, other 

 pollutants, etc.); and 

 - uncertainty about whether a concentration-response function provides an 

 accurate representation of the relationship in the location of interest 

 because of a) the possible role of associated co-pollutants, b) variations in 

 the relationship of total ambient exposure to ambient monitoring in 

 different location, and c) differences in population characteristics and 

 population behavior patterns across locations 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 and alternative 8-hr standards; and 
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- uncertainties about estimated background concentrations for each location, for 

which sensitivity analyses were conducted 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 concentrations, 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 O3-related non-accidental mortality, alternative assumptions about background 

levels had a greater impact. Estimates of risk remaining upon just meeting the current or 

alternative standards were most affected, with differences of +/-50% or larger observed in many 

of the areas. Alternative assumptions 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 mortality in some areas, particularly for more 

stringent standards, the overall pattern of reductions, 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. 
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References 

Abt Associates Inc. (2005a). Ozone Health Risk Assessment for Selected Urban Areas: Draft Report. Prepared for 

Office of Air Quality Planning and Standards, U.S. Environmental Protection 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 Assessment for Selected Urban Areas. Prepared for 

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

Park, NC. June 2005. Available electronically on the internet at: 

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

Abt Associates Inc. (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 Exposure 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.” Environmental 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 Statistics (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 Models for Meta-Analysis.” Technical Report #27. 

September, 1994. National Institute of Statistical Sciences, P. O. Box 14162, Research 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, trend, 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. Graham, 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.; Bromberg, 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 Hopkins 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 Analyses 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 Population Data. Prepared by International 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., Capel, J., McCoy, M., and Warnasch, J. (1996b). Estimation of Ozone Exposures Experienced by 

Outdoor Children in Nine Urban Areas Using a Probabilistic Version of NEM. Prepared by International 
5-102 

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 surveillance--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. Berhane (2000). “Air pollution and daily hospital admissions in 

metropolitan Los Angeles.” Environmental 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 individual 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 Respiratory Disease 147:804-810. 

Moolgavkar, S. H.; Luebeck, E. G.; Hall, T. A.; Anderson, E. L. (1995). “Air pollution and daily mortality in 

Philadelphia.” Epidemiology 6: 476-484. 

Morgan and Henrion (1990). Uncertainty: A Guide To Dealing with Uncertainty in Qualitative Risk and Policy 

Analysis. Cambridge University Press. 

Mortimer, K.M., L.M. Neas, D.W. Dockery, S. Redline, and I.B. Tager (2002). “The effects on air pollution on 

inner-city children with asthma.” European 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. Krewski, 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 matter,” 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.” Poster 
5-103 

presentation. Joint meeting of the International Society 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/standards/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. Barumamdzadeh, A. le Tertre, T. Piekarksi, 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 metropolitan areas: Results for 1988 and 1989 summers.” J. 

Exposure Anal. Environ. Epidemiol. 2(4):429-450. 

Thurston, G.D. and Ito, K. (2001). “Epidemiological 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.” American Journal of Epidemiology 151(8):798-810. 

U. S. EPA (1996a). Review of National Ambient Air Quality Standards for Ozone: Assessment of Scientific and 

Technical Information - OAQPS Staff Paper. EPA/452/R-96-007. Office of Air Quality Planning and 

Standards, Research Triangle Park, NC. Available 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 Environmental 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 Database 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 Methodology 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. Available 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 Triangle 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 Quality Standards for Particulate Matter: Assessment of 

Scientific and Technical Information - OAQPS Staff Paper. 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 Other Related Photochemical Oxidants. National Center for 

Environmental Assessment, Research Triangle Park, NC. Available electronically on the internet at: 

http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=137307

U. S. EPA (2006b). Ozone Population Exposure Analysis 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 Assessment 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 21st Century: Priority Issues and Policy Elsevier; Amsterdam.
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6. STAFF CONCLUSIONS AND RECOMMENDATIONS ON THE 

PRIMARY O3 NAAQS 

6.1 INTRODUCTION 

 This chapter presents staff conclusions and recommendations for the Administrator to 

consider in deciding whether the existing primary O3 standard should be revised and, if so, what 

revised standard is appropriate. Our conclusions and recommendations are based on the 

assessment and integrative synthesis of information 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 document and related technical 

support documents. 

 In recommending policy options for the Administrator’s consideration, we note that the 

final decision on retaining or revising the current O3 standard is largely a public health policy 

judgment. A final decision should draw upon scientific information and analyses about health 

effects, population exposure and risks, as well as judgments about the appropriate response to the 

range of uncertainties that are inherent 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 reflects 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 response become increasingly uncertain. 

 This approach is consistent with the requirements 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 standards that, in the Administrator's judgment, are 

requisite to protect public health with an adequate margin of safety. In so doing, the 

Administrator seeks to establish standards that are 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 retaining the current primary O3

standard, or whether consideration of revisions is appropriate, we adopted an approach in this 

review that builds upon the general approach used in the last review and reflects the broader 

body of evidence now available. The 1997 final decision notice (62 FR 38856) outlined the key 

factors considered in selecting the elements of a standard for O3 (judged to be the most 
 6-2

appropriate indicator for photochemical oxidants): the averaging time; the level (i.e., an ambient 

O3 concentration); and the form (i.e., the air quality statistic used as a basis for determining 

compliance with the standard). Decisions on these elements were based on an integration of 

information on acute and chronic health effects associated with exposure to ambient O3; expert 

judgments on the adversity of such effects on individuals; and policy judgments as to when the 

standard is requisite to protect public health with an adequate margin of safety, which were 

informed by air quality analysis and quantitative exposure and risk assessments when possible, 

as well as qualitative assessment of public health impacts that could not be quantified. 

 As in the last review, in developing conclusions and recommendations on the primary O3

standard in this review, staff has taken into account both evidence-based and quantitative 

exposure- and risk-based considerations. Evidence-based considerations include the assessment 

of evidence from controlled human exposure, animal toxicological, field, 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 endpoints that the CD has judged to be 

likely causal based on an integrative synthesis of the entire body of evidence, including not only 

all available epidemiological evidence but also 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 possible causal relationships. For the purpose of 

evaluating the level of the O3 standard in this review, we have placed greater weight on U.S. and 

Canadian studies, taking into account the extent to which such studies have reported statistically 

significant associations. This is because findings of U.S. and Canadian studies are more directly 

applicable for quantitative considerations in this review as studies conducted in other countries 

may well reflect quite different populations, 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 specifically, we have considered estimates of the 

magnitude of O3-related exposures and risks associated with recent air quality levels, as well as 

the exposure and risk reductions likely to be associated with just meeting the current 8-hr 

primary O3 NAAQS and potential alternative 8-hr standards. We recognize the uncertainties 

inherent in such estimates, which are discussed in Chapters 4 and 5, in part by providing where 

possible some sense of the direction and/or magnitude of the uncertainties which should be taken 

into account as one considers 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 O3
 6-3

standard. Our review of the adequacy of the current standard in section 6.3.1 begins by 

addressing questions such as the following: 

• To what extent does newly available information reinforce or call into question 

evidence of associations of O3 exposures with effects identified in the last review? 

• To what extent has evidence of new effects and/or sensitive populations become 

available since the last review? 

• To what extent have important uncertainties identified in the last review been reduced 

and have new uncertainties emerged? 

• To what extent does newly available information reinforce or call into question any of 

the basic elements of the current standards? 

To the extent that the available information suggests that revision of the current standard may be 

appropriate to consider, we also explore whether the currently available information supports 

consideration of a standard that is either more or less protective by addressing the following 

questions: 

• Is there evidence that associations, especially likely causal associations, extend to 

ambient O3 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 of concern and health risks estimated to occur in areas upon meeting the 

current standard; are they important from a public health perspective; and what are the 

important uncertainties associated with the estimated risks? 

 To the extent that there is support for consideration 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 for the Administrator to consider 

in making public health policy judgments, based on the currently available information, as to the 

degree of protection that is requisite to protect public health with an adequate margin of safety. 

In so doing, we address the following questions: 

• Does the evidence provide support for considering a different O3 indicator? 

• Does the evidence provide support for considering different averaging times? 

• What ranges of levels and forms of alternative standards are supported by the evidence, 

and what are the uncertainties and limitations in that evidence? 

• To what extent do specific levels and forms of alternative standards reduce the 

estimated exposures of concern and risks attributable to O3 and other photochemical 
 6-4

oxidants, and what are the uncertainties associated with the estimated exposure and risk 

reductions? 

 A summary of staff conclusions and recommendations on policy options for the 

Administrator’s consideration concerning whether and, if so, how to revise the current primary 

O3 standard is presented in section 6.3.6. This chapter concludes with a discussion of key 

uncertainties and recommendations for additional research related to setting a primary O3

standard in section 6.4. 

6.3 PRIMARY O3 STANDARD 

 The current primary O3 standard is an 8-hr standard set at a level of 0.08 ppm, with a 

form of the annual fourth-highest daily maximum 8-hr average concentration, averaged over 

three years, to provide protection to the public, especially children and other at-risk populations, 

against a wide range of O3-induced effects. As an introduction to the discussion in this section of 

the adequacy of the current O3 standard and potential options for alternative standards, 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 standard. 

 In the last review, the key factor 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 O3. The best documented health endpoints in these studies were 

decrements in indices of lung function, such as forced expiratory volume in 1 second (FEV1), 

and respiratory symptoms, such as cough and chest pain on deep inspiration. For short-term 

exposures of 1 to 3 hr, group mean FEV1 decrements were statistically significant for O3

concentrations only at and above 0.12 ppm, and only when subjects engaged in very heavy 

exertion. By contrast, prolonged exposures of 6 to 8 hr produced statistically significant group 

mean FEV1 decrements at the lowest O3 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 evidence led to the conclusion in the 1997 final 

decision that the 8-hr averaging time is more directly associated with health effects of concern at 

lower O3 concentrations than is the 1-hr averaging time. 

 Based on the available evidence of O3-related health effects, the following factors were 

of particular importance in the last review in informing the selection of the level and form of a 

new 8-hr standard: (1) quantitative estimates of O3-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 estimated percentages, total numbers of children, and 
 6-5

number of times they were likely to experience such effects; (3) epidemiological evidence of 

associations between ambient O3 and increased respiratory hospital admissions, and quantitative 

estimates of percentages and total numbers of asthma-related admissions in one example urban 

area that were judged to be indicative of a pyramid of much larger effects, including respiratoryrelated hospital admissions, emergency department (ED) visits, doctor visits, and asthma attacks 

and related increased medication use; (4) quantitative 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 O3-related effects for which 

information is too limited to develop quantitative risk estimates, including increased nonspecific 

bronchial responsiveness (e.g., related to aggravation of asthma), decreased pulmonary defense 

mechanisms (suggestive of increased susceptibility to respiratory infection), and indicators of 

pulmonary inflammation (related to potential aggravation of chronic bronchitis or long-term 

damage to the lungs); (6) the broader public health perspective of the number 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 health effects and the relative degree of certainty in both the 

likelihood that people will experience various health effects and their medical significance; (8) 

the relationship of a standard level to estimated “background” levels associated with 

nonanthropogenic sources of O3; and (9) CASAC advice and recommendations. Additional 

factors that were considered in selecting the form of the standard included the public health 

implications of the expected number of times in an O3 season that the standard level might be 

exceeded in an area that is in attainment with the standard and the year-to-year stability of the air 

quality statistic, so as to avoid disruptions to ongoing control programs which could interrupt 

public health protections. 

In reaching a final decision in the last review, the Administrator was mindful that O3

exhibits a continuum of effects, such that there is no discernible threshold 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 recognition that important uncertainties remained, 

for example with regard to interpreting the role of other pollutants co-occurring with O3 in 

observed associations, understanding biological mechanisms of O3-related health effects, and 

estimating human exposures and quantitative risks to at-risk populations for these health effects. 

6.3.1 Adequacy of Current O3 Standard 

 Overall, the new evidence available in this review generally supports and builds further 

upon key health-related conclusions drawn in the previous review. New human clinical studies 

provide information about lung function and respiratory symptom responses to prolonged 
 6-6

exposures at O3 levels at and below 0.08 ppm. There is an expanded body of evidence about the 

mechanisms of respiratory effects, including important new evidence about increased 

susceptibility of people with asthma and limited new evidence about plausible mechanisms by 

which O3 exposure could induce effects on the cardiovascular system. In this review, there is 

additional epidemiological evidence supporting associations between O3 exposure and 

respiratory symptoms in asthmatic children, ED visits and hospital admissions for respiratory 

causes, and new evidence that links O3 exposure to premature mortality. 

 As discussed in Chapter 3, the CD concludes that, based on the extensive body of human 

clinical, toxicological, and epidemiological evidence, there is a causal relationship between 

short-term O3 exposure and a range of respiratory morbidity effects, including lung function 

decrements, increased respiratory symptoms, airway inflammation, and increased airway 

responsiveness. Aggregate population time-series studies provide evidence that ambient O3

concentrations are positively and robustly associated with respiratory-related hospitalizations and 

ED visits during the warm season. The CD concludes that the overall body of evidence supports 

a causal relationship between acute ambient O3 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 O3 can 

directly or indirectly contribute to cardiovascular-related morbidity, but that much needs to be 

done to more fully substantiate links between ambient O3 exposures and adverse cardiovascular 

outcomes (CD, p. 8-77-78). The CD also finds that, consistent with observed O3-related 

increases in respiratory- and cardiovascular-related morbidity, several newer U.S. multi-city 

time-series studies, single-city studies, and several meta-analyses of these studies, provide 

relatively strong epidemiological evidence for associations between short-term O3 exposure and 

all-cause (non-accidental) mortality, even after adjustment for the influence of season and PM 

(CD, p. 8-78). 

 In considering this evidence as a basis for evaluating the adequacy of the current O3

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 judgments about a NAAQS for an 

individual pollutant such as O3 within a mix of highly correlated pollutants, such as the mix of 

photochemical oxidants, especially at ambient O3 concentrations below levels at which O3-

related effects have been observed in controlled human exposure studies. We also recognize that 

the available epidemiological evidence neither supports nor refutes the existence of thresholds at 

the population level for effects such as increased hospital admissions and premature mortality. 

There are limitations in epidemiological studies that make discerning thresholds in populations 
 6-7

difficult, including low data density in the lower concentration ranges, the possible influence of 

exposure measurement error, and interindividual differences in susceptibility to O3-related 

effects in populations. 

 While there clearly are limitations in interpreting 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 O3 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 excluding days over 0.08 ppm or even lower O3 levels. We note 

that seasonal epidemiological studies show no consistent O3-related effects during the cold 

season when O3 concentrations are generally low, in contrast to a pattern of generally positive 

and statistically significant O3-related effects in the warm season when O3 concentrations are 

generally appreciably higher. In addition to direct consideration of the epidemiological studies, 

the findings from controlled human exposure studies strongly suggest that both lung function 

decrements and respiratory symptoms occur in healthy adult subjects at levels down to at least 

0.060 ppm (+/- 0.003 ppm) with some subjects experiencing notable effects (e.g., >10% FEV1

decrement, pain on deep inspiration). Controlled human exposure studies also found significant 

responses in indicators of lung 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 would 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 infection, potentially leading to increased medication use, increased 

school and work absences, increased visits to doctors’ offices and emergency departments (EDs), 

and increased hospital admissions. These observations provide additional support for the 

conclusion that the associations observed in the epidemiological studies, particularly for 

respiratory-related effects and potentially for cardiovascular effects, extend down to ozone levels 

well below 0.084 ppm. 

 Based on the above considerations and findings 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 O3 exposure and respiratory effects 

observed in the last review and broadens the evidence of O3-related associations to include 

additional respiratory-related endpoints, newly identified cardiovascular-related health 

endpoints, and mortality. Newly available evidence also has identified increased susceptibility in 

people with asthma. While recognizing that important uncertainties and research questions 
 6-8

remain, we also conclude that progress has been made since the last review in advancing the 

understanding of potential mechanisms by which ambient O3, alone and in combination with 

other pollutants, is causally linked to a range of respiratory- and cardiovascular-related health 

endpoints. Thus, we generally find support in the available evidence, including the direction of 

the evidence developed since the last review, for consideration of an O3 standard that is at least 

as protective as the current standard and do not find support for consideration of an O3 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 all interested parties 

who provided comments on the previous draft of this document. While CASAC and some 

commenters supported revising the current standard to provide increased public health 

protection, and other commenters supported retaining the current standard, no one who provided 

comments supported a standard that would be less protective than the current standard. 

Having reached this general conclusion, we discuss in greater detail below the available 

evidence (section 6.3.1.1) and exposure- and risk-based considerations (section 6.3.1.2) to more 

fully inform consideration of the adequacy of the current standard. We also take into account the 

views expressed by CASAC and public commenters (section 6.3.1.3) in reaching staff 

conclusions on the adequacy of the current standard (section 6.3.1.4). 

6.3.1.1 Evidence-based Considerations 

In looking more specifically at the controlled human exposure 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 attributable to acute exposures to O3 per se (CD, p. 8-73). We also note 

that evidence from such human studies, together with animal toxicological studies, help to 

provide biological plausibility for health effects observed in epidemiological studies. In 

considering the available evidence, we have focused on studies that examined health effects that 

have been demonstrated to be caused by exposure to O3 or for which the CD judges associations 

with O3 to be causal or likely causal. In considering 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 from all-year studies. We have considered the 

extent to which such studies provide evidence of associations that extend down to ambient O3

concentrations below the level of the current standard, which would call into question the 

adequacy of the current standard. In so doing, we note, as discussed 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 standard. We have also sought to characterize whether the area in 
 6-9

which a study was conducted likely would or would not have met the current standard during the 

time of the study, although we recognize that the confidence that would appropriately 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 O3 concentrations, is not dependent on this distinction. 

Further, we have considered studies that examined subsets of data that include only days with 

ambient O3 concentrations below the level of the current O3 standard, or below even lower O3

concentrations, and continue to report statistically significant associations. We judge that such 

studies are directly relevant to considering the adequacy of the current standard, particularly in 

light of reported responses to O3 at levels below the current standard found in controlled human 

exposure studies. 

In examining air quality information from the epidemiological studies for the purpose of 

determining whether they were conducted in areas 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 were often shorter than a complete O3 season; Appendix 

3B includes 98th and 99th percentile values as a way to approximate 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 reported in Appendix 3B), 

since an area’s attainment status is determined by the monitor measuring the highest O3

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 O3 exposures include lung function decrements, respiratory symptoms, 

pulmonary inflammation, and increased airway responsiveness. In the last review, these O3-

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 exposure studies, healthy adult volunteers were 

exposed to 6.6-hr average O3 levels down to lower levels (i.e., 0.04 and 0.06 ppm) while engaged 

in moderate exertion. These studies did not report statistically significant changes in the group 

mean FEV1 decrements between lung function decrements 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 O3

season) fourth-highest daily maximum 8-hr average O3 concentration at each monitor in an area. 
 6-10

ppm levels versus the filtered air (i.e., essentially 0 ppm O3) 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 Section 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 FEV1 decrement 

following the 6.6-hr exposure at 0.06 ppm, which may be statistically significantly different from 

filtered air responses. Notably, total respiratory symptoms (which includes pain on deep 

inspiration, shortness of breath, and cough) following 5.6 and 6.6 h exposures at 0.06 ppm 

(during a triangular exposure pattern, that is more representative of those encountered in summer 

air pollution episodes than a square-wave exposure pattern) reached statistical significance. In 

addition to information about group mean decrements, this study also reports that a small 

percentage (7%) of healthy adult subjects experienced moderate lung function decrements (≥

10% FEV1) with exposure to 0.06 and 0.04 ppm O3 when corrected for the effects of exercise in 

clean air. The distribution of individual responses related to lung function decrements (≥ 10, 15, 

and 20% FEV1) 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 O3 relative to healthy individuals 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 physiological basis for increased sensitivity in people with asthma and 

other airway diseases, recognizing that people with asthma present a different response profile 

for cellular, molecular, and biochemical responses than people who do not have asthma. New 

evidence indicates that some people with asthma have increased occurrence and duration of 

nonspecific airway responsiveness, which is an increased bronchoconstrictive response to airway 

irritants. Controlled-human exposure studies also indicate that some people with allergic asthma 

and rhinitis have increased airway responsiveness to allergens following O3 exposure. 

Exposures to O3 exacerbated lung function decrements in people with pre-existing allergic 

airway disease, with and without asthma. Ozone-induced exacerbation of airway responsiveness 

persists longer and attenuates more slowly than O3-induced lung function decrements and 

respiratory symptom responses and can have important clinical implications for asthmatics. 

 Newly available human exposure studies suggest that some people with asthma also have 

increased inflammatory responses, relative to non-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 bronchoconstriction indicate that people with asthma 

and allergic rhinitis (with or without asthma) comprise susceptible groups for O3-induced 
 6-11

adverse effects. This body of evidence qualitatively informs our evaluation of the adequacy of 

the current O3 standard in that it indicates that human clinical and epidemiological panel studies 

of lung function decrements and respiratory symptoms that evaluate only healthy, non-asthmatic 

subjects likely underestimate the effects of O3 exposure on asthmatics and other susceptible 

populations. 

 In addition to the experimental evidence of lung function decrements, respiratory 

symptoms, and other respiratory effects in healthy and asthmatic populations discussed above, 

epidemiological studies have reported associations 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 O3 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 O3 and increased asthma 

medication use. The NCICAS reported statistically significant increases in incidence of > 10% 

declines in morning lung function and respiratory symptoms in asthmatic children for multi-day 

lags in 8-hr average O3 concentrations in single pollutant models. For various co-pollutant 

models, the O3 effect was attenuated, but there was still a positive association. Gent et al. (2003) 

included asthmatic children in the area of southern New England and reported associations 

between various respiratory symptoms and both daily 1-hr maximum and 8-hr maximum O3

levels for asthmatics who used maintenance medications and would be considered moderate to 

severe asthmatics, while not finding an association for mild asthmatics, defined as not using 

maintenance medication. In this study, effects of O3, but not PM2.5, 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 positive association between ambient O3 concentrations and 

increased respiratory symptoms in asthmatics. We recognize, however, that uncertainties remain 

with regard to the relative contribution of O3 and other co-pollutants, some of which show 

moderate correlations during the summer time, for 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 populations (Appendix 3B), we note 

that most such studies that reported positive and often statistically significant associations in the 

warm season were conducted in areas with relevant air quality statistics that 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-city NCICAS (Mortimer et al., 2002), we note that the 98th percentile 
 6-12

8-hr daily maximum O3 concentrations at the monitor reporting the highest O3 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 O3 concentrations exceeding 0.080 

ppm. The authors observed that when days with 8-hr average O3 levels greater than 0.080 ppm 

were excluded, similar effect estimates were seen. 

There also are other studies in which the relevant air quality statistics provide some 

indication that lung function and respiratory symptom effects may be occurring in areas that 

likely would have met the current standard (e.g., Naeher et al., 1999; Ross et al., 2002; Brauer et 

al., 1996). We note that this last group of studies reported associations 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 would 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 O3 and increased respiratory 

hospital admissions and emergency room visits, providing strong evidence for a relationship 

between O3 exposure and increased exacerbations of preexisting lung disease at O3 levels below 

the level of the then current 1-hr standard. Analyses of data from studies conducted in the 

northeastern U.S. indicated that O3 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 evaluated the association 

between short-term exposures to O3 and unscheduled hospital admissions for respiratory causes 

(CD, section 7.3.3). Large multi-city studies, as well as many studies from individual cities have 

reported positive and often statistically significant O3 associations with total respiratory 

hospitalizations as well as asthma- and COPD-related hospitalizations, especially in studies 

analyzing the O3 effect during the summer or warm season. Analyses using multipollutant 

regression models suggest that copollutants generally do not confound the association between 

O3 and respiratory hospitalizations, and that the O3 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 causal relationship between acute O3 exposures and increased 

respiratory-related hospitalizations during the warm season (CD, p. 8-77). 

In looking specifically at U.S. and Canadian respiratory hospitalization studies that 

reported positive and often statistically significant associations (and that either did not use GAM 

or were reanalyzed to address GAM-related problems), we note that many such studies were 

conducted in areas that likely would not have met the current O3 standard, with many providing 

only all-year effect estimates, and with some reporting a statistically significant association in the 

warm season (e.g., Schwartz (1996) – Cleveland). Of the studies that provide some indication 
 6-13

that O3-related respiratory hospitalizations may be occurring 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 statistically 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 cities study (Burnett et al., 

1997a), we observe that while the aggregated 98th percentile O3 concentration was calculated as 

47 ppb (Appendix 3B), the fourth-highest values at the monitors reporting the highest O3

concentrations in each of the cities ranged from approximately 35 to 110 ppb, making it difficult 

to determine the extent to which the reported association 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) studies in Toronto. We observed 

that in one of those studies (Burnett 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 98th 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 available for further examination. 

Based on these observations, we find it difficult to judge the extent to which these studies 

provide evidence of an association with respiratory-related hospitalizations in areas that likely 

would have met the current standard. Nonetheless, as discussed above, we recognize that these 

studies do provide evidence of associations that likely extend down to relatively low ambient O3

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 related 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 O3. However, inconsistencies were observed which were at least partially attributable 

to differences in model specifications and analysis approach among various studies. In general, 

O3 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 studies that reported statistically 

significant effect estimates had calculated 98th percentile O3 concentrations (Appendix 3B), 

averaged across monitors, that are indicative of areas that likely would not have met the current 

standard. The notable exception were two studies in Montreal (Delfino et al., 1997, 1998) that 

reported statistically significant warm-season associations with O3 and ED visits in a population 

of older adults with a calculated 98th percentile value, averaged across several monitors, of 

approximately 60 ppb (and for which individual monitor data were not available for further 
 6-14

examination), although the CD raises questions about the plausibility of this result due to the low 

O3 concentrations and inconsistent results across years and age groups. The CD concluded that 

analyses stratified by season generally supported a positive association between O3

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 O3 concentrations. 

 Mortality 

 The 1996 CD concluded that an association between daily mortality and O3 

concentrations for areas with high O3 levels (e.g., Los Angeles) was suggested. However, due to 

a very limited number of studies available at that time, there was insufficient evidence to 

conclude that the observed association was likely causal, and thus the possibility that O3

exposure may be associated with mortality was not relied upon in the 1997 decision on the O3

primary standard. 

Since the last review, as described above, the body of evidence with regard to O3-related 

health effects has been expanded by animal, human clinical, and epidemiological studies, and 

now includes biologically plausible mechanisms by which O3 may affect the cardiovascular 

system. In addition, there is stronger information linking ozone to serious morbidity outcomes, 

such as hospitalization, that are associated with increased mortality. 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 designed specifically to examine the effect of O3

and other pollutants on mortality have provided much more robust 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 associations were reported 

between O3 and mortality that were robust to adjustment for PM (CD, p. 7-100). Using a subset 

of the NMMAPS data set, Huang et al. (2005) focused on associations between cardiopulmonary 

mortality and O3 exposure (24-hr average) during the summer season only. The authors report 

the increase in mortality per 20 ppb change in O3 concentration using a 7-day distributed lag 

model was greater than the increase in mortality measured on the same day (CD, p. 7-92), 

suggesting that the effect of O3 on mortality is immediate but also persists for several days. 

Using a case-crossover study design, Schwartz (2005) assessed associations between daily 

maximum concentrations and mortality in 14 cities, matching case and control periods by 

temperature, and using data only from the warm season. The reported effect estimate was 

similar to time-series analysis results with adjustment for temperature, suggesting that 

associations between O3 and mortality were robust to the different adjustment methods for 

temperature (CD, p. 7-93). Two of the recent multi-city mortality studies (Bell et al., 2004; 
 6-15

Gryparis et al., 2004) have also reported associations for multiple averaging times (CD, p. 8-38). 

Bell and colleagues (2004) reported an effect estimate for the association with 1-hr O3

concentrations that was slightly larger than that reported for 8-hr O3 concentrations, and both 

were slightly larger than the association with 24-hr average O3, 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 O3-mortality relationship in 98 U.S. urban communities for the period 

1987 to 2000 specifically to evaluate whether a “safe” threshold level exists. Results from 

various analytic methods all indicated that any threshold, if it exists, would likely occur at very 

low concentrations, far below the level of the current O3 NAAQS and other, lower international 

O3 standards,2

 and nearing background levels. Notably, in a subset analysis using only days that 

were below the level of the current O3 NAAQS, the O3-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 O3 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 maximum 8-hr average 

concentrations in U.S. cities that are within the range of background concentrations. The authors 

conclude that “interventions to further reduce ozone pollution would benefit public health, even 

in regions that meet current regulatory standards and guidelines” (Bell et al., 2006, p. 3). 

New data are also available from several single-city studies conducted 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 total non-accidental mortality 

associated with acute exposure to O3, especially in the summer or warm season when O3 levels 

are typically high, with somewhat larger effect estimate sizes for associations with 

cardiovascular mortality (CD, p. 7-175). As shown in Figure 7-21 of the CD, the results of 

recent publications show a pattern of positive, often statistically significant associations between 

short-term O3 exposure and mortality during the warm season (CD, p. 7-97). For example, 

statistically significant associations 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. 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 O3 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, statistically significant associations were reported in Philadelphia 

(Moolgavkar et al., 1995) and Dallas (Gamble et al., 1998), while positive but not statistically 

significant associations were reported in Detroit (Lippmann et al., 2000, reanalyzed in Ito, 2003), 

San Jose (Fairley, 1999, reanalyzed Fairley, 2003), 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. Louis and Eastern Tennessee (Dockery et al., 1992). In most singlecity analyses, effect estimates were not substantially 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 98th percentile O3 concentrations (Appendix 3B) that are indicative of 

O3 levels that likely would not have met the current standard. The notable exception was a study 

in Vancouver (Vedal et al., 2003) that reported a statistically significant warm-season association 

with O3 and total non-accidental mortality that was robust in two-pollutant models, with a 

calculated 98th percentile value, averaged across many monitors, of approximately 53 ppb. Upon 

further examination, the relevant air quality statistics for each individual monitor in this study 

ranged from 57 to 59 ppb. This study provides evidence of an O3-related mortality association in 

the warm season in an area with O3 levels that were well below those that would have met the 

current standard. However, the authors questioned whether O3, 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 over a much longer time period (Villeneuve et 

al., 2003) did not provide evidence of O3-related mortality associations, but only all-year results 

were presented which may be more likely confounded by other pollutants than the warm-season 

results in Vedal et al. (2003). 

 Three recent meta-analyses evaluated potential sources of heterogeneity in O3-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 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 evidence of publication bias, but O3-

mortality associations remained after accounting for that potential bias. The CD (7-97) 

concludes that the “positive O3 effects estimates, along with the sensitivity analyses in these three 

meta-analyses, provide evidence of a robust association between ambient O3 and mortality.” 

 The CD finds that the results from U.S. multi-city time-series studies, along with the 

meta-analyses, provide relatively strong evidence for associations between short-term O3

exposure and all-cause mortality even after adjustment for the influence of season and PM (CD, 
 6-17

p. 8-78). The results of these analyses indicate that copollutants generally do not appear to 

substantially confound the association between O3 and mortality (CD, p. 7-103; Figures 7-22 and 

7-23). In addition, several single-city studies observed positive associations of ambient O3

concentrations with total nonaccidental and cardiopulmonary mortality. Finally, from those 

studies that included assessment of associations with specific causes of death, it appears that 

effect estimates for associations with cardiovascular mortality are larger than those for total 

mortality; effect estimates for respiratory mortality 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 that effect estimates are consistently positive 

and more likely to be larger and statistically significant in warm season analyses. The CD (p. 8-

78) concludes that these findings are highly suggestive that short-term O3 exposure directly or 

indirectly contributes to non-accidental and cardiopulmonary-related mortality, but additional 

research is needed to more fully establish underlying mechanisms by which such effects occur. 

6.3.1.2 Exposure- and Risk-based Considerations 

In addition to the evidence-based considerations, staff has also considered exposures and 

health risks estimated to occur upon meeting the current O3 standard to help inform judgments 

about the extent to which exposure and risk estimates may be judged to be important from a 

public health perspective, taking into account key 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 school age children in 12 urban areas across the 

U.S.3 In this discussion we focus particularly on the exposure estimates for all and asthmatic 

school age children while at moderate or greater exertion levels since these groups are 

particularly at risk for experiencing O3-related health effects due to the greater amount of time 

spent outdoors during the O3 season engaged in relatively high levels of physical activity. With 

regard to the quantitative risk assessment, we have estimated the occurrences of moderate or 

greater lung function decrements in all and asthmatic school age children, respiratory symptoms 

in children with moderate to severe asthma, respiratory-related hospital admissions, and nonaccidental and cardiorespiratory mortality. We have selected these 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 O3-related effects become regarded as adverse 

to the health of individuals, staff has relied upon the guidelines published by the American 

 3

As discussed in Chapter 4, since the proportion of children 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 advice of CASAC. As discussed in Chapter 3, the ATS (1985) 

has defined adverse respiratory health effects as medically significant 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 incapacitating illness. Of the morbidity effects estimated in the 

risk assessment, hospital admissions are clearly adverse to the health of the individual. 

Recognizing that respiratory symptoms in moderate to severe asthmatic children are likely to 

cause increased medication use, interference with normal activities, or increased absences from 

school, occurrences of such symptoms are considered to be adverse. For active healthy people, 

moderate lung function decrements would likely interfere with normal activity for relatively few 

individuals within this group who are particularly responsive to O3 exposures; whereas large 

functional responses would likely interfere with normal activities for a greater proportion of 

individuals within this group, such that even single occurrences of large 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 

O3 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 with 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 activity for most individuals in this group and 

would increase the likelihood that these individuals would seek medical treatment. Thus, 

occurrences of either moderate or large functional responses in people with lung disease would 

be considered to be adverse to the health of individuals experiencing these effects. 

Beyond the health effects discussed above that are included in the risk assessment, 

Chapter 3 discusses a broader array of O3-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, increased medication use, ED visits). Ozone-related 

effects that are judged to be important indicators of this broader 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 increased admissions to hospitals; (2) decreased 

pulmonary defense mechanisms which are suggestive of increased susceptibility 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 absences, increased visits to doctors’ offices and 

EDs, and increased admissions to hospitals; increased cellular permeability associated with 

inflammation may be a mechanism by which O3 exposure can lead to cardiovascular system 

effects; and potential chronic effects such as chronic bronchitis or long-term damage to the lungs 

that can lead to reduced quality of life. Some perspective on the O3-related public health 

impacts of these types of effects are characterized based on the results 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 three 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 exposures and risks, while 2004 was a year with 

generally better air quality in most, 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 presenting these results, we note that the exposure 

analysis and risk assessment discussed in Chapters 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 O3 levels, demographic characteristics, physiological attributes, activity 

patterns, and factors affecting microenvironmental concentrations. In our judgment the most 

important uncertainties affecting the exposure estimates are related to the modeling of activity 

patterns over an O3 season, modeling micro-scale 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., measured in terms of METS - metabolic equivalents of work) for 

children engaged in various activities. As discussed in section 4.3.4.7, the uncertainty in METS 

values carries over to the uncertainty of the modeled 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 complementary analyses addressing these 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 sources of uncertainty: near-road exposures and 

the activity data. The uncertainty of the model structure (as distinct from uncertainty driven by 
 6-20

uncertain model inputs) is judged to be less important than the uncertainties of the model inputs 

and parameters. Based on these analyses, relatively small uncertainties are associated with the 

estimation of ambient concentrations and microenvironment model parameters. Relatively larger 

uncertainties are associated with the representativeness of the CHAD activity diaries with respect 

to the specific cities and time periods modeled. The APEX model 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 confidence 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 described in Langstaff (2007). It is important to note that there have 

been significant improvements in several components of the exposure model and in the inputs to 

the model (e.g., better characterization of the ambient air quality surface across each area, more 

complete data on air exchange rates, much larger 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 uncertainties associated with the exposure 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 O3 standard. 

As discussed in Chapter 5, uncertainties related to the air quality data affect both the 

controlled human exposure studies-based and the epidemiological studies-based parts of the risk 

assessment. These include uncertainties associated with the air quality adjustment procedure that 

was used to simulate just meeting the current and alternative 8-hr standards, and the uncertainties 

associated with estimating background O3 concentrations for each location. Based on sensitivity 

analyses conducted in the prior review, alternative air quality adjustment procedures had only a 

modest impact on the risk estimates. With respect to uncertainties about estimated background 

concentrations, as discussed in section 5.4.3, alternative assumptions about PRB levels have a 

variable impact depending on the location and standard analyzed in terms of the absolute 

magnitude of the risk estimates. Alternative assumptions about PRB 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 alternative assumptions for PRB for most of the standards analyzed. 

With respect to the lung function part of the health risk assessment, key uncertainties 

include uncertainties in the exposure estimates for children engaged in moderate or greater 

exertion (noted above) and uncertainties associated with the shape of the exposure-response 

relationship, especially at levels below 0.08 ppm, 8-hr average, where only limited data are 
 6-21

available down to 0.04 ppm and there is an absence of data below 0.04 ppm. The uncertainty 

associated with the shape of the exposure-response relationship was considered using a Bayesian 

Markov Chain Monte Carlo approach as recommended by members of the CASAC panel 

(Henderson, 2006c). As discussed in section 5.3.2.5, the impacts of changing the functional 

form of the exposure-response relationship varied substantially. Changing from the 90% 

logistic/10% linear base case to the 80%/20% split generally had 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 the 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 respect 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 associated with two more stringent alternative 

standards relative to the current standard. 

With respect to the part of the health risk assessment based on effects reported in 

epidemiological studies, an important uncertainty for the mortality risk estimates is the extent to 

which the associations reported between O3 and non-accidental and cardiorespiratory mortality 

actually reflect causal relationships. Other important uncertainties for this part of the risk 

assessment include uncertainties (1) surrounding estimates of O3 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 concentrations examined in the 

studies, (3) related to the extent to which concentration-response relationships derived from 

studies in a given location and time when O3 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-pollutants which also may have varied between the 

time of the studies and the current assessment period. 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 the health risk assessment to be “well done, 

balanced, and reasonably communicated” (Henderson, 2006c). We have considered the kind and 

extent of uncertainties in the health risk estimates, but judge that these estimates, discussed in 

Chapter 5 and in this chapter, are appropriate for consideration as an input to the decisions on the 

O3 standard. 
 6-22

 The exposure and risk assessments estimated occurrences of exposures of concern and 

lung function decrements, respectively, in school-age children ages 5 to 18. Due to the increased 

amount of time spent outdoors engaged in relatively high levels of physical activity, school-age 

children, as a group, are particularly at risk for experiencing O3-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 children into account in our analysis due to a 

lack of information which would let us characterize 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 O3 while at prescribed exertion levels, serve two purposes. 

First, the entire range of modeled personal exposures to ambient O3 is an essential input to the 

risk assessments based on exposure-response functions from controlled human exposure studies. 

Secondly, estimates of personal exposures to ambient O3 levels at and above specific benchmark 

concentrations provide some perspective on the public health impacts of health effects that we 

cannot currently evaluate in quantitative 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 levels at which we know or 

can reasonably infer that specific O3-related health effects are occurring. We refer to exposures 

at and above these benchmark concentrations 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 O3-related health outcomes, such as pulmonary 

inflammation, increased airway responsiveness, 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 O3 exposures at 0.08 and 0.10 ppm. To 

provide some perspective on the public health impacts of these health effects, we note that 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 indicators 
 6-23

effects have been demonstrated in controlled human exposure studies of healthy individuals to 

occur at levels as low as 0.08 ppm O3, but have not been evaluated at lower levels in controlled 

human exposure studies. We have not estimated these effects in a quantitative risk assessment 

due to the lack of adequate information on the overall exposure-response relationships. For the 

exposure analysis in the second draft 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 O3 while engaged in 

intermittent moderate or greater exertion levels (62 FR 38860). However, at the August 2006 

CASAC meeting, the CASAC O3 Panel encouraged staff to also consider exposures of concern 

at levels lower than 0.08 ppm, expressing the view that there is a range of health effects that 

likely occur below the lowest level 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 O3. 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 well below 0.08 ppm. 

 We concur with these views, and note that exposures of concern, and the health outcomes 

they represent, likely occur across a range of O3 exposure levels, such that there is no one 

exposure level that addresses all relevant public health concerns. Therefore, we have estimated 

exposures of concern not only at 0.080 ppm O3, a level at which there are demonstrated effects, 

but also at 0.070 and 0.060 ppm O3, recognizing that there is no apparent threshold for O3 health 

effects and that potentially adverse lung function decrements have been demonstrated in 

controlled human exposure studies of healthy individuals at 0.060 + 0.003 ppm O3. Moreover, 

there will be varying degrees of concern about exposures at each of these levels, based in part on 

the population subgroups experiencing them. For example, it is reasonable to conclude that a 

high degree of protection is warranted 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 asthma and other lung diseases. At levels where 

effects have not been demonstrated 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 provide stronger protection 

against effects that are more clearly 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 O3 and reason to infer that such effects 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 O3

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 

O3. 

 Exposure estimates for 6 scenarios (i.e., recent air quality for each of the three years 

examined, 2002 to 2004, and just meeting the current 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 daily 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 very similar for the general population and for 

all and asthmatic school age (5-18) children, although children are about twice as likely to be 

exposed, based on the percent of the population exposed, at any given level. Thus, in the 

discussion below, we focus on the patterns observed 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 results, it is important to note that there is 

substantial variability in the percent of the population subgroups estimated to experience 

exposures of concern across the 12 urban areas. For example, in the case of exposures of 

concern ≥ 0.070 ppm O3, for 2002 when the current standard is just met, while the aggregate 

estimate is 18% (Table 6-1b), the estimates of exposures 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 offered 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. 
6-25

Table 6-1a. Summary of Estimates of Number of People Exposed and Number of Occurrences1 at Moder

Associated with 8-Hour Daily Maximum Ozone Concentrations > 0.080 ppm for 12 Urban Are

General Population 

(88.5 million people) 

All Children (5-18 years old) 

(18.3 million children) 

Asthmatic Children (5-1

(2.6 million child

Air Quality 

Scenario Persons

(% of population) 

Person Days

[% change from recent air quality] 

Persons

(% of population) 

Person Days

[% change from recent air quality] 

Persons

(% of population) 

Perso

[% charecent 

2002 Air Quality 

Recent Air Quality 10,790,000 (12%) 15,030,000 4,130,000 (23%) 6,030,000 630,000 (24%) 

Just Meeting 

Current Standard 

2,020,000 

(2%) 

2,270,000 

[85% reduction] 

700,000 

(4%) 

800,000 

[87% reduction] 

110,000 

(4%) 

[86

2003 Air Quality 

Recent Air Quality 5,970,000 (7%) 8,320,000 2,430,000 (13%) 3,500,000 340,000 (13%) 

Just Meeting 

Current Standard 

470,000 

(0.5%) 

480,000 

[94% reduction] 

160,000 

(0.9%) 

140,000 

[95% reduction] 

20,000 

(1%) 

[95

2004 Air Quality 

Recent Air Quality 2,350,000 (3%) 3,000,000 910,000 (5%) 1,180,000 130,000 (5%) 

Just Meeting 

Current Standard 

80,000 

(0.1%) 

90,000 

[97% reduction] 

30,000 

(0.1%) 

30,000 

[98% reduction] 

3,000 

(0.2%) 

[98

1Estimates for persons and person days are rounded to the nearest 10,000. Percentages greater than or equal to 1 are rounded to the nea

percentages less than one are rounded to the nearest tenth.

2Moderate exertion is defined as having an 8-hr average equivalent ventilation rate (EVR) in the range 13-27 l-min/m2. 
6-26

Table 6-1b. Summary of Estimates of Number of People Exposed and Number of Occurrences1 at Modera

Associated with 8-Hour Daily Maximum Ozone Concentrations > 0.070 ppm for 12 Urban Are

General Population 

(88.5 million people) 

All Children (5-18 years old) 

(18.3 million children) 

Asthmatic Children (5-1

(2.6 million child

Air Quality 

Scenario Persons

(% of population) 

Person Days

[% change from recent air quality] 

Persons

(% of population) 

Person Days

[% change from recent air quality] 

Persons

(% of population) 

Perso

[% charecent 

2002 Air Quality 

Recent Air Quality 22,770,000 (26%) 44,050,000 8,550,000 (47%) 18,500,000 1,280,000 (50%) 

Just Meeting 

Current Standard 

8,890,000 

(10%) 

12,350,000 

[72% reduction] 

3,340,000 

(18%) 

4,880,000 

[74% reduction] 

520,000 

(20%) 

[73

2003 Air Quality 

Recent Air Quality 14,100,000 (16%) 24,390,000 5,510,000 (30%) 10,380,000 790,000 (31%) 

Just Meeting 

Current Standard 

2,480,000 

(3%) 

2,710,000 

[89% reduction] 

1,000,000 

(5%) 

1,090,000 

[90% reduction] 

150,000 

(6%) 

[89

2004 Air Quality 

Recent Air Quality 7,660,000 (9%) 12,040,000 3,020,000 (17%) 5,020,000 440,000 (17%) 

Just Meeting 

Current Standard 

720,000 

(0.8%) 

770,000 

[94% reduction] 

260,000 

(1%) 

270,000 

[95% reduction] 

40,000 

(1%) 

[95

1Estimates for persons and person days are rounded to the nearest 10,000. Percentages greater than or equal to 1 are rounded to the nea

percentages less than one are rounded to the nearest tenth.

2Moderate exertion is defined as having an 8-hr average equivalent ventilation rate (EVR) in the range 13-27 l-min/m2. 
6-27

Table 6-1c. Summary of Estimates of Number of People Exposed and Number of Occurrences1 at Modera

Associated with 8-Hour Daily Maximum Ozone Concentrations > 0.060 ppm for 12 Urban Are

General Population 

(88.5 million people) 

All Children (5-18 years old) 

(18.3 million children) 

Asthmatic Children (5-1

(2.6 million child

Air Quality 

Scenario Persons

(% of population) 

Person Days

[% change from recent air quality] 

Persons

(% of population) 

Person Days

[% change from recent air quality] 

Persons

(% of population) 

Perso

[% charecent 

2002 Air Quality 

Recent Air Quality 36,410,000 (41%) 112,510,000 12,580,000 (69%) 48,000,000 1,860,000 (72%) 

Just Meeting 

Current Standard 

21,860,000 

(25%) 

45,040,000 

[60% reduction] 

7,970,000 

(44%) 

18,760,000 

[61% reduction] 

1,210,000 

(47%) 

[60

2003 Air Quality 

Recent Air Quality 27,660,000 (31%) 68,790,000 10,220,000 (56%) 29,640,000 1,490,000 (58%) 

Just Meeting 

Current Standard 

10,410,000 

(12%) 

14,220,000 

[79% reduction] 

4,040,000 

(22%) 

5,750,000 

[81% reduction] 

610,000 

(24%) 

[79

2004 Air Quality 

Recent Air Quality 19,820,000 (22%) 44,620,000 7,570,000 (41%) 19,300,000 1,090,000 (42%) 

Just Meeting 

Current Standard 

4,720,000 

(5%) 

5,920,000 

[87% reduction] 

1,800,000 

(10%) 

2,300,000 

[88% reduction] 

270,000 

(11%) 

[87

1Estimates for persons and person days are rounded to the nearest 10,000. Percentages greater than or equal to 1 are rounded to the nea

percentages less than one are rounded to the nearest tenth.

2Moderate exertion is defined as having an 8-hr average equivalent ventilation rate (EVR) in the range 13-27 l-min/m2.
 6-28

 In addition to city-to-city variability, substantial year-to-year variability 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 children (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 greater exertion) for 2004 and 2002, respectively.6

 When air 

quality is adjusted to simulate just meeting the 8-hr standard, the estimated number of children 

exposed is substantially reduced. Depending on which 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%, based 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 O3 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 aspect to consider when making judgments about 

the extent to which these exposures can be considered adverse to individuals. However, based 

on the analysis described in section 4.6.4, staff concludes that the APEX exposure model 

significantly underestimates the frequency of occurrences of individuals (adults and children) 

experiencing repeated 8-hour average 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 exposure 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 quality 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 database, the exposure assessment does not include 

outdoor workers, some proportion of whom are likely to be exposed repeatedly day after day to 

elevated ambient O3 levels while at work. 

 Risk Assessment Results 

 Turning to risk-based considerations, as discussed in Chapter 5, risk estimates have been 

calculated and are discussed below for several important health endpoints, 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 FEV1) in all school age 

children for 12 urban areas; 

• Lung function decrements (i.e., ≥ 10% and ≥ 20% reductions in FEV1) in asthmatic 

school age children for 5 urban areas (a subset of the 12 urban areas); 

• Respiratory symptoms (i.e., chest tightness, shortness of breath, wheeze) in moderate to 

severe asthmatic children for the Boston area; 

• Respiratory-related hospital admissions for 3 urban areas; 

• Non-accidental and cardiorespiratory mortality for 12 urban areas. 

In the sections on lung function decrements in children (all and asthmatic children), we 

describe the scope of the assessments, the number and percent of children experiencing moderate 

and large lung function decrements, 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, which 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 individuals and are described 

below. There are discussions about year-to-year variability in the results and variability in 

results across the urban areas, which are important 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 decrements and the number of 

occurrences they experience during a 3-year period that is adjusted to just meet the current 8-hr 

standard. For example, the number of children affected, and the number of occurrences, can 

increase by more than 100% for a year with generally 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 estimated population risk across the 12 urban areas, as 

indicated by the percent of the population estimated to be affected, which describes the risk 

normalized across the urban areas with very different 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 FEV1) under recent air quality and when air quality just meets the current 8-hr 

standard are 7% and 3% (based on 2002 air quality), respectively. The range across the 12 urban 

areas, from Table 5-8 is approximately 5% to 10% under recent (2002) air 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 for the risk estimates based on 2004 air quality. 

 The remaining sections on respiratory symptoms in moderate to severe asthmatic 

children, respiratory related hospital admissions, and non-accidental and cardiorespiratory 
 6-30

mortality include discussions of the scope of the assessments, provide estimates of the incidence, 

incidence per 100,000 and percent of total incidence of the effects, 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 Occurrences1 Associated with 8-Hour Ozone Exposures While 

Engaged in Moderate Exertion2

 for 2002, 2003, and 2004 Air Quality and Just 

Meeting the Current 8-Hour Standard3 

FEV1 > 15% FEV1 > 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/m2. 

3

Estimates are the aggregate results based 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 season which is all year in Houston, Los 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 children (ages 5-18) for moderate 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 quality (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 O3 standard based on the three-year design value. All estimates in both tables reflect 
 6-31

responses associated with exposure to O3 in excess of exposures associated with policy relevant 

background (PRB) O3 concentrations.7 Table 5-6 shows the number and percent of all school 

age children estimated to have at least one moderate or greater lung function response (i.e., >

15% decrement in FEV1) during the O3 season. Table 5-7 displays the total number of 

occurrences for the moderate or greater lung function responses during the O3 season. Table 6-2 

draws upon the risk estimates for all school age children 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 FEV1) and large or greater (i.e., >

20% decrement in FEV1) lung function responses, and the number of total days of occurrences, 

aggregated across all 12 urban areas. 

 As shown in Table 6-2, for the three recent years (2002 - 2004), from 620,000 to over 1.3 

million school age children (3 to 7% of all school age children) are estimated to experience 1 or 

more moderate lung function responses (i.e., ≥ 15% reduction in FEV1) in the 12 urban areas 

combined. Similar 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 outcomes. Depending on which year is adjusted 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 FEV1) lung function responses in these 12 urban 

areas combined upon just meeting the current standard. Among all school age children, these 

estimates indicate that the percent of children likely to experience one or more moderate or 

greater lung function decrements (i.e., ≥ 15% FEV1 decrement) is reduced by about 54 to 65% 

when the current standard is just met based 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 greater lung function responses. These results indicate that among 

all school age children, on average an individual is likely to experience 5 to 7 occurrences of 

moderate or greater lung function responses during an O3 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 concentrations 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 assumptions for PRB for most of the alternative 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 moderate 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 O3

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 healthy people, large lung function responses 

(i.e., > 20% decrement in FEV1), would likely interfere with normal activities in many sensitive 

individuals, therefore single occurrences would be considered to be adverse under ATS 

guidelines, and are the appropriate indicator to consider. As shown 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 FEV1) in school age 

children in the 12 urban areas combined. Similar 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 outcomes. Depending on which year is considered, 

upon just meeting the current 8-hr standard, there are estimated to be from about 500,000 to 

about 160,000 occurrences of large lung function decrements (i.e., ≥ 20% reduction in FEV1) in 

school age children in these 12 urban areas combined. Among all school age children, these 

estimates indicate that occurrences of large lung function decrements (i.e., ≥ 20% FEV1

decrement) are reduced by about 64 to 75% when the current standard 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, FEV1 decrements > 10% but < 20% have been judged to represent 

moderate levels of functional responses for active healthy people and would likely interfere with 

normal activity for relatively few sensitive individuals. However, for persons with lung disease, 

such as asthma, lung function decrements at the lower end of the moderate range (i.e., FEV1

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 children with asthma, particularly those with moderate-to-severe 

asthma, are more likely to have lung function and symptomatic responses, and have bigger 

responses, from O3 exposure than children who do not have asthma. Studies discussed in section 

3.3.1.1 that show increased lung function responses, inflammation, and increased airway 

responsiveness in asthmatics indicate that the risk estimates for lung function decrements derived 

from controlled exposures of healthy adult volunteers likely underestimate the percent of 

asthmatic school age children that would experience decrements in FEV1. In this final Staff 

Paper, we use a ≥ 10% decrease in FEV1 as a benchmark for moderate 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 (Henderson, 2006c) that for asthmatic children a 

lung function response defined in terms of FEV1 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 FEV1) in asthmatic school age 

children for 5 urban areas that are a subset of the 12 urban areas included for all children. 

 As shown in Table 6-3, for the three recent years (2002 - 2004), from about 160,000 to 

about 250,000 asthmatic school age children (9 to 15% of asthmatic school age children) are 

estimated to experience 1 or more moderate lung function responses (i.e., ≥ 10% reduction in 

FEV1) 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 the 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 standard, 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 FEV1) lung function responses in these 5 urban areas combined upon just meeting the current 

standard. Among asthmatic school age children, these estimates indicate that the number of 

children likely to experience one or more moderate or greater lung function decrements (i.e., ≥

10% FEV1 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 greater lung function responses per individual responding compared 

to all school age children. The results in Table 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 responses during an O3 season. As discussed above, the more likely 

distribution is that many children will experience one or only a few occurrences of moderate or 

greater lung function decrements (≥ 10% decrement in FEV1), while some may experience a 

very large number, based on these estimates. Recognizing that nationally over 14% of school 

age children have asthma, these numbers raise concern about the potential number of children 

with asthma who could experience a large number of occurrences of moderate or greater lung 

function decrements (≥ 10% decrement in FEV1) even with air quality just 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 Occurrences1

 Associated with 8-Hour Ozone Exposures While 

Engaged in Moderate Exertion2

 for 2002, 2003, and 2004 Air Quality and Just 

Meeting the Current 8-Hour Standard3 

Air Quality FEV1 > 10% FEV1 > 20% 

Scenario Children 

(% of Asthmatic 

Children in)1 

Occurrences1 

[% reduction 

from recent air 

quality]1 

Children 

(% of Asthmatic 

Children)1

Occurrences1 

[% 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/m2 

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 FEV1), would likely interfere with normal activities for most individuals 

and would also increase the likelihood that these individuals would use additional medication or 

seek medical treatment. Single occurrences would be considered to be adverse 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 occurrences of large lung 

function responses (i.e., ≥ 20% reduction in FEV1) in asthmatic school age children in the 5 

urban areas combined. When air quality is adjusted to simulate just meeting the current 8-hr 

standard, there are significant reductions in estimated health outcomes. Depending on which 
 6-35

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 large lung function responses (i.e., ≥ 20% reduction in 

FEV1) in asthmatic children in these 5 urban areas combined. Among asthmatic school age 

children, these estimates indicate that occurrences of large lung function decrements (i.e., ≥ 20% 

FEV1 decrement) in these 5 urban areas are reduced 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 respiratory symptoms (i.e., chest tightness, shortness of breath, and 

wheeze) during the O3 season in children of age 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 are 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 Tables 5-10 and 5-11, the estimated incidence of 

symptom days of chest tightness (across 4 models reflecting 2 different lags and O3 alone vs. 

inclusion of PM2.5 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 standard reduces the incidence of symptom days 

for chest tightness by relatively small and consistent 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. Averaging the median estimates of symptom days 

indicates that just meeting the current 8-hr standard 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 generally 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 

FEV1, 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 FEV1), are included in the 

Risk Assessment TSD. 

10To minimize uncertainty, this risk assessment was performed for the Boston area because that is the urban 

area nearest to where the epidemiological study was conducted that is the basis for the exposure-response function 

used in the assessment. 

11The 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 moderate 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 better air quality, among children with moderate to 

severe asthma in the Boston area, as many as one symptom day in 8 during the O3 season is 

estimated to be attributable to O3 exposure. In a year with generally poorer air quality, as many 

as one symptom day in 6 is estimated to be attributable to O3 exposure. These results support the 

human clinical and epidemiological evidence that people with asthma are more likely to 

experience effects related to O3 exposure than the general population, and provide evidence that 

the current 8-hr O3 standard is not as protective 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 area12 associated with O3 levels above 

background for the period from April to September 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 incidence of asthma-related hospital admissions (which 

are a subset of total respiratory hospital admissions) 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 asthma-related hospital admissions, based on two 

air quality years, after the current standard is met. 

 12To minimize uncertainty, this risk assessment was performed for the New York City area because that is 

where the epidemiological study was conducted 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 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 

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 

Incidence per (24,100 - 38,100) 

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 O3 only and including PM2.5 in the model. 

 Total non-accidental and cardiorespiratory mortality in 12 urban areas. Table 6-6 

summarizes risk estimates for non-accidental mortality in 12 urban areas associated with O3

levels above background for the period from April to September based on the 95-city function 

reported in Bell et al. (2004) for 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, while single-city estimates 

 13The 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 areas for recent air quality (2002, 2004) and 

Tables 5C-13 to 5C-16 in Appendix 5C of this Staff Paper 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 and because the multi-city risk estimates are less 

subject to publication bias. In comparing estimates between recent air quality and just meeting 

the current standard, similar patterns are seen in terms of relative 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 population 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 for cardiorespiratory mortality show similar 

patterns (Tables 5-14, 5-15).

 14Additional risk estimates for cardiorespiratory mortality are included in the Risk Assessment TSD for 8 of 

the 12 urban areas based on Huang et al. (2005). 
6-39

Table 6-5. Risks of Respiratory- and Asthma-related Hospital Admissions Associated with Recent (2004, 2

and Air Quality Adjusted to Just Meets Current Standard Based on Adjusting 2004 and 2002 A

York City, NY 

Incidence1

(Range)2

[% reduction from recent] 

Incidence per 100,000 

(Range)2 

Perc

Unscheduled Hospital Admissions 

Air Quality Scenario 

2002 2004 2002 2004 200

Recent 610 

(150 – 1070) 

450 

(110 – 790) 

7.6 

(1.8 - 13.3) 

5.6 

(1.4 - 9.8) 

1.7

(0.4 - 

Respiratory 

Just Meets 0.08 ppm 

510 

(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

Recent 520 

(110 – 930) 

380 

(80 – 680) 

6.5 

(1.4 - 11.6) 

4.8 

(1 - 8.5) 

4% 

(0.8 - 7

Asthma (subset of respiratory) 

Just Meets 0.08 ppm 

440 

(90 - 780) 

[16% reduction] 

310 

(70 - 560) 

[18% reduction] 

5.5 

(1.2 - 9.8) 

3.9 

(0.8 - 7) 

3.3

(0.7 - 

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 O3 coefficient 
6-40

Table 6-6. Risks of Non-accidental Mortality Associated with Recent (2004, 2002) Air Quality and Air Qu

Just Meets Current Standard Based on Adjusting 2004 and 2002 Air Quality 

Estimated Risk of Non-accidental Mortality1,2

Incidence 

(range)3

Incidence per 100,000 

(range)3

Percen

Location Air Quality 

Scenario 

2002 2004 2002 2004 2002 

Recent 17 

(6 - 29) 

12 

(4 - 20) 

1.2 

(0.4 - 1.9) 

0.8 

(0.3 - 1.4) 

0.4% 

(0.1 - 0.6

Atlanta 

Just 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

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

Boston 

Just 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

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

Chicago 

Just 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

Recent 38 

(13 - 64) 

17 

(6 - 28) 

2.8 

(0.9 - 4.6) 

1.2 

(0.4 - 2) 

0.5% 

(0.2 - 0.9

Cleveland 

Just 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

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

Detroit 

Just 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

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

Houston 

Just 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
6-41

Estimated Risk of Non-accidental Mortality1,2

Incidence 

(range)3

Incidence per 100,000 

(range)3

Percen

Location Air Quality 

Scenario 

2002 2004 2002 2004 2002 

Recent 110 

(37 - 184) 

133 

(45 - 221) 

1.2 

(0.4 - 1.9) 

1.4 

(0.5 - 2.3) 

0.4% 

(0.1 - 0.7

Los Angeles Just 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

Recent 105 

(35 - 174) 

60 

(20 - 100) 

1.2 

(0.4 - 2) 

0.7 

(0.2 - 1.1) 

0.3% 

(0.1 - 0.6

New York 

Just 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

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

Philadelphia Just 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

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

Sacramento 

Just 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

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

St. Louis 

Just 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

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

Washington, DC 

Just 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

1All results are for mortality (among all ages) associated with short-term exposures to O3. All results are based on single-pollutant mod

95-cities model. 

2Incidence was quantified down to estimated policy relevant background levels. Incidences are rounded to the nearest whole number; i

 relevant population and percents are rounded to the nearest tenth. 

3Note: Numbers in parentheses are 95% confidence or credible intervals based on statistical uncertainty surrounding the O3 coefficient
 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 advice 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 drafts of these documents provided by public 

commenters.15 The range of views summarized here generally 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 O3-related health effects from a public health perspective. 

 In a letter to the Administrator (Attachment 1), the CASAC O3 Panel, with full 

endorsement of the chartered CASAC, unanimously concluded that there is “no scientific 

justification for retaining” the current primary O3 standard, and the current standard “needs to be 

substantially reduced to protect 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 have provided more evidence for adverse health 

effects at concentrations lower than the current standard, and that these epidemiological studies 

are backed-up by evidence from controlled human exposure studies. The Panel specifically 

noted evidence from the recent Adams (2006) study that reported statistically significant 

decrements in the lung function of healthy, moderately 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 safety,” 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 

 15All written comments submitted to the Agency are available 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. 

16Comments of individual Panel members are available as Attachment D to the CASAC O3 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 would healthy volunteers 

(Mortimer et al., 2002).” (Henderson, 2006c, p. 4). 

 The CASAC Panel also highlighted a number of adverse health effects, beyond lung 

function decrements, that are attributable to low-concentration exposure to ambient O3, below the 

level of the current standard, based on a broad range of epidemiological and controlled exposure 

studies (id.). These adverse health effects include increases in school absenteeism, respiratory 

hospital emergency department visits among asthmatics and patients with other respiratory 

diseases, hospitalizations for respiratory illnesses, symptoms associated with adverse health 

effects (including chest tightness and medication usage, and mortality (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 health 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 retaining the current standard,17 the CASAC Panel felt that more emphasis 

should be placed on numbers of subjects in controlled human exposure studies with FEV1

decrements greater than 10%, which can be clinically significant, rather than on the relatively 

small average decrements. The Panel also emphasized significant O3-related inflammatory 

responses and markers of injury to the epithelial lining of the lung that are independent of 

spirometric responses. Further, the Panel expressed 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 O3 standard, it was the unanimous opinion of the 

CASAC that the current primary O3 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 substantially reduced to be protective of human health, particularly 

in sensitive subpopulations (id., pp. 4-5). 

Further, the CASAC letter noted that “there is no longer significant scientific uncertainty 

regarding the CASAC’s conclusion that the current 8-hr primary NAAQS must be lowered.” (id., 

p. 5). The Panel noted that a “large body of data clearly demonstrates adverse human health 

effects at the current level” of the standard, such that “[R]etaining this standard would continue 

 17See second draft O3 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 that “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 individuals at risk for respiratory effects and/or significant impact on 

quality of life including asthma exacerbations, emergency room visits, hospital admissions and 

mortality” (id.). The Panel also noted that “scientific uncertainty does exist with regard to the 

lower level of ozone exposure that would be fully protective of human health,” 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, several public commenters supported revising the 

primary O3 standard to provide increased public health protection.18 In considering the available 

evidence as a basis for their views, these commenters generally noted that the controlled human 

exposure studies, showing statistically significant declines in lung function, increases in 

respiratory symptoms, airway inflammation and 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. Further, recognizing the substantial variability in 

response between subjects, some of these commenters 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 the basis for these commenters’ view that an O3

standard set at 0.08 ppm is not protective of public health and has no margin of safety for 

sensitive groups. 

 In considering the results of the human exposure and health risk assessment, this group of 

commenters generally expressed the view that these assessments substantially underestimate the 

public health impacts of exposure to O3. For example, several commenters noted that the 

assessments are done for a limited number of cities, they do not address risks to important 

sensitive subpopulations (e.g., outdoor workers, 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 expressed the view that the primary O3 standard should be set 

to protect the most exposed and most vulnerable groups, and the fact that some children are 

frequently indoors, and thus at lower risk, should not weigh against setting a standard to protect 

those children who are active outdoors. To the 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 which most areas had relatively higher O3 levels than in 

2004, so as to ensure public health protection even in years with relatively worse O3 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 alternative standards advocated by 

the CASAC Panel during their public meeting in August 2006. 

 In contrast to the views discussed above, 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 number of aspects of the interpretation of the evidence presented 

in the CD. For example, some of these commenters 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 associations, and underestimates the 

uncertainties in interpreting the results of such studies. Further, these commenters generally 

express the view that there is significant uncertainty 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 morbidity and mortality risks are unlikely to be 

attributable to people’s exposures to O3. Rather, these commenters variously attribute the 

reported risks to the inability of time series studies to account for key model specification factors 

such as smoothing for time-varying parameters, meteorological factors, removal of O3 by 

building ventilation systems, and confounding by co-pollutants. In particular, these commenters 

generally asserted that reported associations between short-term O3 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 likely due to confounding, inappropriately specified 

statistical models, or publication bias. 

 In considering the results of the human exposure and health risk assessment, this group of 

commenters generally expressed the view that these assessments are 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 estimating risk for individual cities. This group of 

commenters also generally expressed the view that the assessments generally overestimate the 

public health impacts of exposure to O3. Noting that the risk assessment used a nonlinear 

exposure-response function to estimate decreased 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 analyses and that the lack of association of O3 to 

 19This 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 assessment based on controlled human exposure studies of 

lung function decrements, some commenters expressed the view that the 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 should focus on group central tendency response levels. Further, 

some commenters expressed the view that the air quality rollback algorithm used may result in 

overestimates in benefits from emission reductions. Some commenters noted that potential 

beneficial effects of O3 in shielding from UV-B radiation are not quantified in the assessment, 

and that the assessment should discuss the evidence for both adverse and beneficial effects with 

the same objectivity. Finally, some of these commenters asserted that since estimates of 

exposures of concern (defined as 0.080 ppm) and lung function decrements are substantially 

below the estimates available when the current O3 standard was set in 1997, retaining the current 

standard is the most appropriate 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 O3-related exposures of 

concern and risks upon meeting the current O3 standard in many urban areas across the U.S., 

together with associated uncertainties. As an initial matter, we note that there is general 

agreement among staff, CASAC, and all interested parties who commented on earlier drafts of 

this document that this information supports consideration of a primary O3 standard that is at 

least as protective as the current standard, with no one supporting consideration of an O3

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, while we recognized that there was substantial evidence that could 

be interpreted as calling into question the adequacy of the current standard, we chose not to 

exclude the option of retaining the current standard from the provisional conclusions presented in 

that draft document. We wanted to have the benefit of receiving CASAC views and public 

comments on the strength of the available evidence, the results of the exposure/risk assessments, 

and their interpretation of the evidence with regard to judging the adequacy of the current 

standard before reaching final conclusions. As discussed below, based on the available 

information and taking into account the views of CASAC and public comments, we now 

conclude that the overall body of evidence clearly calls into question the adequacy of the current 
 6-47

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 workers,20 against an array of adverse health effects that range from decreased lung 

function to serious indicators of respiratory morbidity including ED visits and hospital 

admissions for respiratory causes, and possibly cardiovascular effects and mortality. We believe 

the available information provides strong support for consideration of an O3 standard that would 

provide increased health protection for these sensitive groups. 

In discussing information related to the adequacy of the current standard, we have noted 

that evidence of a range of respiratory-related morbidity effects seen in the last review has been 

strengthened, both through toxicological 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 Appendix 3B). In addition, new evidence identifies 

people with asthma as an important susceptible population for which estimates of respiratory 

effects in the general population may underestimate the magnitude or importance of the effect. 

New evidence about mechanisms of toxicity helps to explain the biological plausibility of O3-

induced respiratory effects and is beginning to suggest mechanisms that may link O3 exposure to 

cardiovascular effects. Further, there is now relatively strong evidence for associations between 

O3 and total nonaccidental and cardiopulmonary mortality, even after adjustment for the 

influence of season and PM. Relative to the information 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 indicators of respiratory 

morbidity, are causally related to O3 exposures, and that mortality is likely associated with O3

exposures during the O3 season. 

In examining the entire body of evidence and considering CASAC’s views and advice on 

interpreting the evidence with regard to the adequacy of the current standard, we conclude that 

there is important new evidence demonstrating that exposures to O3 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 addition, there is now epidemiological evidence of 

statistically significant O3-related associations with lung function and respiratory symptom 

effects, respiratory-related ED visits and hospital admissions, as well as possibly increased 

mortality, in areas that likely would have met the current standard. There are also many 

 20 In defining sensitive groups this way we are including both groups with greater inherent sensitivity and 

those more likely to be exposed. 
 6-48

epidemiological studies done in areas that likely would not have met the current standard but 

which nonetheless report statistically significant associations that generally extend down to 

ambient O3 concentrations that are well below the level of the current standard. Further, there 

are a few studies that have examined subsets of data that include only days with ambient O3

concentrations below the level of the current standard, or below even much lower O3

concentrations, and continue to report statistically significant associations. Our level of 

confidence in the findings from these studies is not related to whether they were done in areas 

that likely would or would not have met the current standard. However, we agree with the views 

expressed by the CASAC O3 Panel21 that uncertainty in epidemiological findings increases at the 

low end of the ranges of concentrations observed 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 correlations between ambient concentrations and personal exposure 

and to questions of plausibility that are more salient at relatively low concentrations. 

Based on the strength of the currently available evidence of adverse health effects, 

especially indicators of respiratory morbidity, and on the extent to which the evidence indicates 

that such effects likely result from exposures to ambient O3 concentrations well below the level 

of the current standard, we conclude that the available evidence clearly calls into question the 

adequacy of the current standard and provides strong support for giving consideration to revising 

the standard to provide increased protection, especially for sensitive groups, against a broad 

array of adverse health effects. As discussed below, we have also considered the results of the 

exposure and risk assessments conducted for this 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 health 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 exposure analysis represents a state 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 O3 NAAQS. Moreover, the additional 

uncertainty and sensitivity analyses conducted after CASAC review of the second draft Staff 

Paper have increased our overall confidence in the 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 O3-related risks to public health and as 

indicators of the potential for a range of other types of adverse health effects for which currently 

available information is too limited to allow for direct estimates of risk. 

 21See, for example, the written comments of Dr. Vedal (Henderson, 2006c, Appendix D, p. D-74). 
 6-49

Turning to the results of the exposure assessment, we note that estimating exposures of 

concern provides an important indication of the potential magnitude of the incidence of health 

outcomes that we cannot currently evaluate in a quantitative risk assessment, such as, increased 

airway responsiveness, increased pulmonary inflammation, including increased cellular 

permeability, and decreased pulmonary defense mechanisms. These physiological effects, which 

have been demonstrated to occur in healthy people at O3 exposures as low as 0.080 ppm, are 

associated with aggravation of asthma, increased medication use, increased school and work 

absences, increased susceptibility to respiratory infection, increased visits to doctors’ offices and 

EDs, increased admissions to hospitals, and possibly to cardiovascular system effects and 

chronic effects such as chronic bronchitis or long-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 healthy adults but in sensitive 

groups, such as people with asthma or other lung diseases, children, and older adults, we believe 

it is appropriate to consider the extent to which the current standard reduces exposures of 

concern not only at and above the 0.080 ppm benchmark level, but more importantly also at 

lower benchmark levels. Therefore, 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 the potential for adverse health effects especially 

in sensitive groups, as discussed above, we note that due to individual 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 exposure analysis, we first note that there 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 and the number of occurrences of exposures of 

concern at each of the benchmark levels. We believe 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, approximately 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 the 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 children) in these 12 cities are estimated to 
 6-50

experience exposures > 0.070 ppm in the worst of the three years; even in the mid-year, 

approximately 150,000 (~6%) asthmatic children (and approximately one million total children) 

are estimated to experience such exposures. These 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-to-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 also to consider public health impacts in cities that receive 

relatively less protection from the current standard. For example, in considering the benchmark 

level of > 0.070 ppm, while the aggregate percentage of asthmatic children estimated to 

experience such exposures of concern 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 generally 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 populations likely to remain 

upon meeting the current standard, we note that some such estimates related to relatively less 

serious lung function effects are now appreciably lower than in the last review, whereas risk 
 6-51

estimates related to more serious effects, such as hospital admissions, are as high or higher than 

previously estimated. In addition, unlike in the last review, there is now evidence that supports 

estimating risks for respiratory symptoms in asthmatic children and O3-related mortality. 

 Based on Tables 6-2 and 6-3, we note that meeting the current O3 standard substantially 

reduces the estimated risk of moderate lung function decrements (i.e., ≥ 15% FEV1 decrement) 

in all school age children across 12 urban areas. In asthmatic children the reduction in the 

estimated risk of moderate lung function decrements (i.e., ≥ 10% FEV1 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 function decrements even when the current standard is met, 

resulting in over 1 million occurrences 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 approximately 5 to 7 in all children and 8 to 10 in 

asthmatic children in an O3 season, even when the current standard is met. In the 1997 review of 

the O3 standard a general consensus view of the adversity of such moderate responses emerged 

as the frequency of occurrences increases, with the judgment that repeated occurrences of 

moderate responses, even in otherwise healthy individuals, may be considered adverse since they 

may well set the stage for more serious illness. 

Large lung function decrements (i.e., ≥ 20% FEV1 decrement) would likely interfere with 

normal activities in many healthy individuals, therefore single occurrences would be considered 

to be adverse. In people with asthma, large lung function responses (i.e., ≥ 20% FEV1

decrement), would likely interfere with normal activities for most individuals and would also 

increase the likelihood that these individuals would use additional medication or seek medical 

treatment. Not only would single 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 relatively poorer air quality 

(2002) there are estimated to be about 500,000 occurrences in all school children across 12 urban 

areas, and about 40,000 occurrences in asthmatic children across just 5 urban areas. As noted 

above, it is clear that even when the current standard 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 judging 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-related hospital admissions, and non-accidental and 
 6-52

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 incidence of chest tightness in moderate 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 incidence per 100,000 relevant population of approximately 

23,000 to 31,000 children, attributable to O3 exposure (Table 6-4). The 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, respectively, 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 assessment, the estimates of non-accidental mortality 

incidence per 100,000 relevant population 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. Estimates for cardiorespiratory mortality show 

similar patterns. 

 Staff notes that in considering the estimates 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 O3-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 absences, 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 with moderate to severe asthma, 

we recognize that there are many other effects that may be associated with symptom days, such 

as increased medication use, school and work absences, 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 true 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. Consideration 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, especially for sensitive groups such as people with asthma or other lung 

diseases, as well as children and older adults, particularly those 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 consideration of revising 

the current primary O3 standard so as to afford greater public health protection, especially to 

sensitive groups, and that it does 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 O3 as the most appropriate surrogate for 

ambient photochemical oxidants. In this review, while the complex atmospheric chemistry in 

which O3 plays a key role has been highlighted, no alternatives to O3 have been advanced as 

being a more appropriate surrogate for ambient photochemical oxidants. 

It is generally recognized that control of ambient O3 levels provides the best means of 

controlling photochemical oxidants of potential health concern. Further, among the 

photochemical oxidants, the acute exposure chamber, panel and field epidemiological human 

health database provides evidence only for O3 at levels of photochemical oxidants commonly 

reported in the ambient air, in part because few other photochemical oxidants are routinely 

measured. However, recent investigations on copollutant interactions have used simulated urban 

photochemical oxidant mixes. These investigations suggest the need for similar studies to help 

in understanding the biological basis for effects observed in epidemiological studies that are 

associated with air pollutant mixtures, where O3 is used as the surrogate for the mix of 

photochemical oxidants. Meeting the O3 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 are not discernable from currently available studies indexed 

by O3 alone. Since the precursor emissions that lead to the formation of O3 generally also lead to 

the formation of other photochemical oxidants, measures leading to reductions in population 

exposures to O3 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 O3 NAAQS was set in 1997. The 

decision to revise the averaging time of the primary 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 previous NAAQS was originally selected on the basis 

of health effects associated with short-term (i.e., 1- to 3-hr) exposures. 
 6-54

 (2) Substantial health effects information was available for the 1997 review that 

demonstrated associations between a wide range of health effects (e.g., moderate to large lung 

function decrements, moderate to severe symptoms 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 achieved 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 O3 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 section 7.6.2 of the CD, 

epidemiological studies have used various averaging periods for O3 concentrations, most 

commonly 1-hr, 8-hr and 24-hr averages. As described more specifically below, in general the 

results presented from U.S. and Canadian studies (Appendix 3B) show no consistent difference 

for various averaging times in different studies. 

 Only a few studies presented results for different O3 averaging periods using the same 

data set. Two of the recent multi-city mortality studies reported associations for multiple 

averaging times (Bell et al., 2004; Gryparis et al., 2004). Both reported that the effect estimates 

for different averaging times were not statistically different, though the effect estimates for 

associations with 1-hr daily maximum O3 concentrations were somewhat larger than those for 

longer averaging times, especially 24-hr average O3. In addition, Gent et al., (2003) reported that 

associations for 1-hr and 8-hr average O3 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 O3 and the incidence of myocardial infarction 

(CD, p. 7-55); this study differs from most since the short-term O3 concentration used was the 

time period preceding the health event, not the highest daily short-term average concentration. 

The effect estimate for the association with O3 averaged over a 2-hr period prior to the 

myocardial infarction was substantially larger than that reported for an association with 24-hr 

average O3 (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 comparing 1-hr or 8-hr daily 

maximum O3 concentrations with the 24-hr concentration, but the results did not differ 

statistically (CD, p. 7-120). The CD observes that the various O3 average concentrations were 

generally very highly correlated with one another, so it is not surprising that effect estimates 
 6-55

would be similar. The CD concludes that the epidemiological study results were generally 

comparable for the three O3 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 exposure studies at lower concentrations 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 the Administrator, the CASAC O3 Panel supported the continued use of an 

8-hr averaging time for the primary O3 standard (Henderson, 2006c, p. 2), as did many 

commenters. 

 Some other commenters expressed the view that consideration 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 more “peaky” exposure profiles. 

These commenters point out that when controlled exposure studies using triangular exposure 

patterns (with relatively higher 1-hr peaks) have been compared to constant exposure patterns 

with the same aggregate O3 dose (in terms of concentration x time), “peaky” exposure patterns 

are seen to lead to higher risks. The California Air Resources Board made particular note of this 

point, expressing the view that a 1-hr standard would more closely represent actual exposures, in 

that many people spend only 1 to 2 hours a day outdoors, and that it would be better matched to 

O3 concentration profiles along the coasts where O3 levels are typically high for shorter 

averaging periods than 8 hours. 

 In considering the information discussed above, CASAC views and public comments on 

the earlier draft of this Staff Paper, staff concludes that the 8-hr averaging time remains the most 

appropriate averaging time for a human health-based standard. This conclusion is based on the 

observations summarized above, particularly: (1) the fact that the 8-hr averaging time is more 

directly associated with health effects of concern at lower O3 concentrations than are averaging 

times of shorter duration and (2) results from quantitative risk analyses showing that attaining an 

8-hr standard reduces the risk of experiencing health effects associated with both 8-hr and shorter 

duration exposures. Furthermore, the CASAC O3 Panel unanimously agreed 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 other than 8-hr was appropriate for the 

health-based standard. 

 In addition to quantitative risk analyses, we conducted an analysis of a recent three-year 

period of air quality data (2002 to 2004) to determine whether the 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 recent air quality data, it is reasonable 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 than the previous 1-hr standard of 0.12 ppm in almost all urban 

areas. Thus, staff concludes that setting a standard with an 8-hr averaging time can effectively 

limit both 1- and 8-hr exposures of concern and is appropriate to provide adequate and more 

uniform protection of public health from both short-term and prolonged exposures to O3 in the 

ambient air. Therefore, we recommend that the 8-hr averaging time be retained and do not 

recommend consideration of a separate 1-hr standard at this time. 

6.3.3.2 Long-Term 

 During the last review, there was a large animal toxicological database for consideration 

that provided clear evidence of associations between 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 sufficiently to allow quantitative extrapolation of 

the animal study findings to humans. For these reasons, consideration of a separate long-term 

primary O3 standard was not judged to be appropriate at that time, recognizing that the 8-hr 

standard would act to limit long-term exposures as well as short-term and prolonged exposures. 

 In the current review, long-term animal toxicological studies continue to support the 

relationship between O3 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 seasonal exposure patterns also report increased lung 

injury compared to conventional long-term, stable exposures. (CD, p. 8-85) Collectively, the 

evidence from animal studies strongly suggest that O3 is capable of damaging the distal airways 

and proximal alveoli, resulting in lung tissue remodeling leading to apparently irreversible 

changes. Compromised pulmonary function and 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 function growth in children 

was associated with seasonal exposure to O3; however, cohort studies investigating the effect of 

annual or multiyear O3 exposure observed little clear evidence for impacts of longer-term, 

relatively low-level O3 exposure on lung function development in children. 

 Collectively, the epidemiological studies are inconclusive, but suggestive of respiratory 

health effects from long-term O3 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 of 
 6-57

exposure or O3 concentrations in humans may be required to produce the morphological changes 

found in the animal studies and it is not currently possible to characterize the possible magnitude 

or severity of any such effects occurring in humans in response to ambient O3 exposures at levels 

observed in the U.S.. Further, to the extent that meeting an 8-hr O3 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 O3 exposures. 

In its letter to the Administrator, the CASAC O3 Panel offered no views on the long-term 

exposure evidence, nor did it suggest that consideration of a primary O3 standard with a longterm averaging time was appropriate (Henderson, 2006c, p. 2). Similarly, no commenters 

expressed support for considering 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 potentially more serious health effects have been 

identified as being associated with longer-term exposure studies of laboratory animals and in 

epidemiology studies, there remains substantial uncertainty 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 improved in areas coming into attainment 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 O3 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 consideration of a long-term, health-based standard 

at this time. 

6.3.4 Level 

In considering alternative O3 standard levels that would provide greater protection against 

the array of O3-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 commenters’ views. The discussion of alternative 

levels in this section builds upon the information 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 whether it is appropriate to continue to specify 

the level of the O3 standard to the nearest hundredth (two decimal places) ppm, or whether the 

precision with which ambient O3 concentrations are measured supports specifying the standard 

level to the nearest thousandth ppm (i.e., to the nearest part per billion (ppb)). As discussed 

above in Chapter 2 (section 2.4.2), staff conducted an analysis to determine the impact of 

ambient O3 measurement error on calculated 8-hr average O3 design value concentrations, which 
 6-58

are compared to the level of the standard to determine whether the standard is attained (Cox and 

Camalier, 2006). The results of this analysis suggest that instrument measurement error, or 

possible instrument bias, contribute very little to the uncertainty in design values. More 

specifically, measurement imprecision was determined to contribute less than 1 ppb to design 

value uncertainty, and a simulation study indicated that randomly occurring instrument bias 

could contribute approximately 1 ppb. Staff has interpreted this analysis as being supportive of 

specifying the level of the standard to the nearest thousandth ppm. This information was 

provided to the CASAC O3 Panel and made available to the public at the August 24-25, 2006 

public meeting. The Panel concluded that current monitoring technology “allows accurate 

measurement of O3 concentrations with a precision of parts per billion” and recommended that 

the specification of the level of the O3 standard should reflect this degree of precision 

(Henderson, 2006c).22 Based on these considerations, staff recommends that consideration be 

given to specifying the level of an alternative 8-hr O3 standard to the nearest thousandth ppm. If 

the current standard were to be specified to this degree of precision, the 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 considerations, staff has evaluated available 

evidence from controlled human exposure studies 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 particular, we have considered the extent to which 

controlled human exposure studies provide evidence of lowest-observed-effects levels and the 

extent to which epidemiological studies provide evidence of associations that extend down to the 

lower levels of O3 concentrations observed in the studies or some indication of potential effect 

thresholds in terms of 8-hr average O3 concentrations. 

In considering the available controlled human exposure studies, as discussed above in 

Chapter 3 (section 3.3.1.1), we note that FEV1 decrements and various measures of respiratory 

symptoms were observed in some healthy adults following a 6.6-hr exposure level of 0.06 ppm 

(reflecting exposures of 0.060 + 0.003 ppm) during moderate exertion. More specifically, 

Adams (2002) reports that in an earlier study (Adams, 1998) 20% of subjects (6 of 30 subjects) 

had notable responses (FEV1 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% FEV1

 22 We also note that the 8-hr O3 standard adopted by the state of California 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 includes 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 encountered in summer air pollution 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 body 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 experience larger decrements in lung function in 

response to O3 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 and more generally in people with respiratory 

disease. 

In considering controlled human exposure studies of pulmonary inflammation, airway 

responsiveness, and impaired host defense capabilities, we note that these studies provide 

evidence of a lowest-observed-effects level for such effects in healthy adults at prolonged 

moderate exertion of 0.08 ppm (generally reflecting exposures of 0.080 ppm + 0.004 ppm). As 

discussed above, these physiological effects have been linked to aggravation of asthma and 

increased susceptibility to respiratory infection, 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 O3 exposure can lead to 

cardiovascular system effects, and to potential chronic effects such as chronic bronchitis or longterm damage to the lungs that can lead to reduced quality of life. These are all indicators of 

adverse O3-related morbidity effects, which are consistent 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 the existence of effect thresholds at the population level for 

morbidity and mortality effects. As discussed above, based on a consideration of studies that 

have explored the question of potential thresholds and of seasonal studies that show no consistent 

O3-related effects during the cold season when O3 concentrations are generally low, we conclude 

that if a population threshold level does exist, it would likely be well below the level of the 

current O3 standard and possibly within the range of background levels. 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 some suggestive evidence of possible thresholds for morbidity and 

mortality outcomes in terms of 24-hr, 8-hr, and 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 studies, however, observe linear concentrationresponse functions suggesting no effect threshold. In considering this information, we conclude 

that the statistically significant associations between ambient O3 concentrations and lung 

function decrements, respiratory symptoms, indicators of respiratory morbidity including 

increased ED visits and hospitals admissions, and possibly mortality reported in a large number 

of studies likely extend down to ambient O3 concentrations that are well below the level of the 

current standard. Toward the lower end of the range of O3 concentrations observed in such 

studies, ranging down to background levels, however, we conclude that there is increasing 

uncertainty as to whether the observed associations remain plausibly related to exposures to 

ambient O3, rather than to the broader mix of air pollutants present in the ambient atmosphere. 

We have also considered studies that did subset analyses that include only days with 

ambient O3 concentrations below the level of the current standard, or below even lower O3

concentrations, and continue to report statistically significant associations. Notably, as discussed 

above, Bell et al. (2006) conducted a subset analysis that continued to show statistically 

significant associations even when only days with a maximum 8-hr average O3 concentration 

below a value of approximately 61 ppb were included.23 Also of note is the large multi-city 

NCICAS (Mortimer et al., 2002) that reported statistically significant associations between 

ambient O3 concentrations and lung function decrements even when days with 8-hr average O3

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 limitations inherent in interpreting the available 

evidence, staff believes that the range of alternative O3 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 effects thresholds reported in some 

epidemiological studies and questions of biological plausibility in attributing associations 

observed down to background levels to O3 exposures alone. Based on the evidence and these 

considerations, we conclude that the upper end of the range of consideration should be somewhat 

below 0.080 ppm, the lowest-observed-effects level for effects such as pulmonary inflammation, 

increased airway responsiveness and impaired host-defense capabilities in healthy 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/m3

, daily 8-hr 

maximum, the World Health Organization guideline and European Commission target value for O3. 
 6-61

to aggravation of asthma and increased susceptibility to respiratory infection, 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 O3 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 are all 

indicators of adverse O3-related morbidity effects, which are consistent with and lend plausibility 

to the adverse morbidity effects and mortality effects observed in epidemiological studies 

reporting statistically significant associations with ambient O3 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 O3 standards appropriate for consideration should be at least as low as the 

lowest-observed-effects level for potentially adverse lung function decrements and respiratory 

symptoms in healthy adults, 0.060 ppm, which is also a level likely to cause adverse effects in 

sensitive groups, and above the level where there is some indication of possible effects 

thresholds in epidemiological studies. In considering a lower end of the range for consideration, 

we also recognize that control strategies designed to attain an O3 standard set at a particular level 

within an urban area, as measured at the monitor reporting the highest O3 design value, would 

cause the entire distribution of O3 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 consider the results of the exposure and risk assessments 

that are based on modeling changes in the entire distribution of ambient O3 concentrations to 

simulate just meeting alternative standards, discussed below, in reaching 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 considerations, staff has also considered quantitative 

exposures and health risks estimated to occur upon meeting the current and alternative standards 

to help inform judgments about a range of standard levels for consideration that could provide an 

appropriate degree of public health 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 and more fully in Chapters 4 and 5. For example, important 

uncertainties affecting the exposure estimates are related to modeling human activity patterns 

over an O3 season (especially repetitive exposures), modeling microscale variations in ambient 

concentrations, and modeling building air exchange rates. With regard to the risk assessment, 

important uncertainties include, for example, those related to exposure estimates (for children 

engaged in moderate or greater exertion), as well as those related to estimation of concentration-
 6-62

response functions, specification of concentration-response models, the possible role of 

copollutants in interpreting reported associations with O3, and inferences of a likely causal 

relationship between O3 exposure and non-accidental mortality (for risk estimates based on 

epidemiological studies). As noted above, after considering the key uncertainties, the CASAC 

Panel expressed the view that the exposure analysis represents a state 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 O3 NAAQS. 

 Beyond these uncertainties, we and CASAC also 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 O3-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 risks 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 national-scale public health 

impacts of ambient O3 exposures are much larger than the quantitative estimates of O3-related 

incidences of adverse health effects and the numbers of children 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 significant weight on the body 

of evidence of O3-related health effects in drawing conclusions about an appropriate range of 

levels for consideration. We concur with this important caveat. 

 Turning to the results of the exposure assessment, we examine the extent to which 

alternative standard levels below the current standard are estimated 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, 4th daily maximum (i.e., the 80/4 scenario); 0.074 ppm, 5th

daily maximum (i.e., the 74/5 scenario); 0.074 ppm, 4th daily maximum (i.e., the 74/4 scenario); 

0.074 ppm, 3rd daily maximum (i.e., the 74/3 scenario); 0.070 ppm, 4th daily maximum (i.e., the 

70/4 scenario); and, 0.064 ppm, 4th 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 standards25) at the 0.060 and 0.070 

ppm O3 benchmark levels, for all children and asthmatic children. Individual city estimates of 

the percent of all children likely to experience exposures of concern are given in the exhibits in 

Chapter 4. Estimates of the percent of asthmatic children, the number of all children and 

asthmatic children, and the number of occurrences of exposures of concern, both the aggregate 

estimates across the 12 urban areas and the individual city estimates, are shown in Appendix 4A. 

The estimates are for the number and percent of all children and asthmatic children exposed, and 

the number of person-days (occurrences) of exposures, with daily 8-hr maximum exposures at or 

above the 0.060 ppm and the 0.070 ppm benchmark levels while at intermittent moderate or 

greater exertion. For the purpose of this discussion, recommending an appropriate range of 

levels for consideration, we will focus on scenarios with the same form as the current O3

standard (i.e. the 80/4, 74/4, 70/4 and 64/4 scenarios) and will address 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 age 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 estimates of the number of children and the number of 

occurrences of exposures of concern at both of the benchmark levels. 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 children (~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 O3. 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 levels, 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 O3. These results suggest reductions of approximately 35% (80/4 scenario) to nearly 

100% (64/4 scenario) across the range of alternative standards in the number of all children and 

asthmatic children at this exposure of concern level. 

The estimates of exposures of concern are considerably larger at the benchmark level of ≥

0.060 ppm O3, and the pattern of year-to-year variability 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 experience one or more exposures of concern at the 

benchmark level of ≥ 0.060 ppm O3. In the year with poorer air quality (2002), across the 

alternative standard levels, estimates of the number of all children exposed one or more times 

ranges from 6.7 million (80/4 scenario) to more than 900,000 children (64/4 scenario); for 

asthmatic children the range is more than 1,000,000 (80/4 scenario) to more than 100,000 (64/4 

scenario) at the benchmark level of ≥ 0.060 ppm O3. 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 estimated 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 appropriate 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 exposures of concern across all 12 cities is about 

4% in the worst year, it ranges up to 14% in the city 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 O3. While the aggregate percentage of all and asthmatic children estimated to 

experience one or more exposures of concern across all 12 cities, for the 74/4 scenario, is about 

25% in the worst year, it ranges up to approximately 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 meeting the current standard (the 84/4 scenario) to 

just meeting the same alternative standards discussed above, based on adjusting 2002 and 2004 

air quality data. These figures also provide perspective 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 FEV1 ≥ 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 of 
 6-65

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 FEV1 ≥ 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 lists the estimated number of cases (and 95% 

credible intervals) when O3 concentrations just meet the current standard next to the name of 

each location. There were two health outcomes that 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), because the concentration-response 

functions were developed in these cities and we did not want to introduce additional uncertainties 

by applying these functions to other locations. We believe, however, that it is reasonable to 

assume that these results would be generally applicable to other locations. 

 As shown in Figures 6-1 and 6-2, we first note 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 FEV1) 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 children 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, reducing 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 current standard. An alternative standard 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 moderate lung function decrements (≥ 15% reduction in FEV1) 

relative to the current standard (depending on the year adjusted and the urban area). This same 

64/4 scenario reduces estimates of moderate lung function decrements (≥ 10% reduction in 

FEV1) in asthmatic school age children by about 55 to 65% in most of the 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 including urban areas that are not meeting the current O3 standard in the 

northeast, southeast, deep south, Midwest, and southern California. 
 6-67

Figure 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* 

-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 Standard

P 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 (FEV1 > 15%), in thousands (and 95% credible interval) and the percent of 

children (and 95% credible interval) estimated to experience these effects when O3 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, 4th-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 (–528% in 2002). 
 6-68

Figure 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* 

-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 Standard

P 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 (FEV1 > 15%), in thousands (and 95% credible interval) and the 

percent of children (and 95% credible interval) estimated to experience these effects when O3 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, 4th-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 Asthmatic School Age Children Experiencing 

at Least One Decrement in FEV1 >10% 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* 

-200%

-150%

-100%

-50%

0%

50%

100%

2002 air quality 0.084/4 0.074/4 0.064/4

Alternative Standards

Percent Change from Current 

Standard

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 (FEV1 > 10%), in thousands (and 95% credible interval) 

and the percent of asthmatic children (and 95% credible interval) estimated to experience these effects when O3

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, 4th-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 (-275% in 2002). 
 6-70

Figure 6-4. Percent Changes in Numbers of Asthmatic School Age Children Experiencing 

at Least One Decrement in FEV1 > 10% 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* 

-200%

-150%

-100%

-50%

0%

50%

100%

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

Alternative Standards

Percent C hange from C urrent Standard

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 asthmatic children estimated to 

experience moderate lung function decrements (FEV1 > 10%), in thousands (and 95% credible interval) and the 

percent of asthmatic children (and 95% credible interval) estimated to experience these effects when O3

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, 4th-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 (-281% in 2004). 
 6-71

Figure 6-5. Percent Changes in O3-Related Non-Accidental Mortality Incidence 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* (Using Bell et al., 2004 – 95 U.S. Cities) 

*The numbers in the box below the figure show for each urban area the number of cases (and 95% credible interval) 

and the percent of total incidence (and 95% credible interval) of O3-related non-accidental mortality when O3

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, 4th-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 Standard

Percent 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 Non-Accidental Mortality Incidence 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* (Using Bell et 

al., 2004 – 95 U.S. Cities) 

**The numbers in the box below the figure show for each urban area the number of cases (and 95% credible 

interval) and the percent of total incidence (and 95% credible interval) of O3-related non-accidental mortality 

when O3 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, 4th-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 Standard

Percent 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 note that just meeting the 80/4 scenario is 

estimated to result in about a 5 to 15% reduction in estimated incidences of O3-related nonaccidental mortality relative to the current standard. Reducing the level of the standard to the 

74/4 scenario results in the estimated incidences 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 scenario is estimated to provide appreciably greater 

reduction relative to the current standard in some areas, with an estimated reduction of about 30 

to 40% in most areas and about 60 to 70% in two areas (depending on the year adjusted and the 

urban area) in the estimated incidences of O3-related non-accidental mortality.

With regard to respiratory symptom days for chest tightness in moderate to severe 

asthmatic children in the Boston area, as shown in Table 6-9, the alternative standards provide 

incremental protection beyond that offered by the current standard. From the 80/4 scenario to 

the 64/4 scenario, the estimated incidence of respiratory symptom days is reduced by 5 to 25% in 

the worst year, and by approximately 7 to 31% in the best year. In the worst of the two years, the 

estimated percent of total incidence, or the percent of respiratory-symptom days attributable to 

O3 exposure ranges from about 14% for just meeting the current standard to about 10% for the 

64/4 scenario. This means that even under the most stringent alternative standard evaluated, as 

many as one symptom day in 10 would be estimated to be attributable to O3 exposure in the O3

season. 

Risk estimates for respiratory-related hospital admissions attributable to O3 exposure in 

New York City are shown in Table 6-10. Across the range of alternative standards from the 80/4 

scenario to the 64/4 scenario, the estimated number of O3-related hospital admissions declines by 

about 6 to 29% in the worst year (2002), and about 7 to 34% in the best year (2004). The percent 

of total respiratory-related hospital admissions attributable to O3 exposure declines from about 

1.5% for the current standard to about 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 Severe Asthmatic Children in Boston, MA1 

Average Risks of Chest Tightness Associated 

with Air Quality2,3

[percent reduction from current standard] 

Current and 

Alternative 

Standards 

Risk Metric 

2002 2004

Current Incidence 7800 5700 

Standard 

(84/4) Percent of Total 

Incidence 

14% 10% 

Incidence 7400 

[5% reduction] 

5400 

80/4 [7% reduction] 

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 O3 only and including PM2.5 in the 

model. 
 6-75

Table 6-10. Risks of Hospital Admissions for 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 Exposures1,2

[percent reduction from current standard] 

Current and 

Alternative 

Standards 

Risk Metric 

2002 2004

Current Incidence 513 366 

Standard 

(84/4) Percent of Total 

Incidence 

1.5% 1.0% 

Incidence 483 

[6% reduction] 

341 

80/4 [7% reduction] 

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 O3 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 recognizes that the exposure- and risk-based 

information can be considered both in terms of whether the risks estimated to remain upon 

attaining the current standard are important from a public health perspective and/or whether 

additional reductions in risk estimated to be associated with alternative, more protective 

standards are important from a public health perspective. Judgments about the importance of the 

estimates of exposures and risks need to take into 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 weigh 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 O3 standard, the views expressed by 

CASAC as well as the views of interested parties 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 with a range of forms, as discussed 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 ppm needs to be substantially reduced to be 

protective of human health, particularly in sensitive subpopulations. The lower end of this range 

reflects CASAC’s views that “[W]hile 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.” (id.). 

 The same group of commenters that expressed the view that the current primary O3

standard is not adequate also submitted comments that supported revising the level of the 

primary O3 standard to within the same or even lower range of levels than the range 

recommended by CASAC. The basis for these commenters’ views on the level of the standard is 

generally reflected in the discussion above on the basis for their views on the adequacy of the 

current standard and in the rationale given by CASAC. In addition, some of these commenters 

also noted that the World Health Organization’s guidelines for O3 air quality are in the range of 

51 to 61 ppb. The other group of commenters who expressed the view that the current standard 

is adequate did not provide any provisional views on alternative levels that would be appropriate 

for consideration should the Administrator consider revisions to the standard. 
 6-77

6.3.4.4 Staff Conclusions on the Level of the Standard 

 Staff’s consideration of alternative levels of the primary O3 standard builds upon our 

conclusion, discussed above in section 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 workers, against an array of adverse health effects 

that range from decreased lung function to serious indicators of respiratory morbidity including 

ED visits and hospital admissions for respiratory causes, and possibly cardiovascular-related 

effects and mortality. Thus, we believe that the available information provides strong support for 

consideration of a range of standard levels that is below the level of the current standard so as to 

afford increased health protection for these sensitive groups. We have also concluded, as an 

initial matter, that it is appropriate to consider specifying the level of the O3 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 O3 standard from somewhat below 0.080 

ppm down to at least as low as 0.060 ppm. This evidence-based recommendation takes into 

account information on lowest-observed-effects levels in controlled human exposure studies as 

well as indications of possible effects thresholds reported in some epidemiological studies and 

questions of biological plausibility in attributing associations observed down to background 

levels to O3 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 capabilities in healthy adults while at prolonged 

moderate exertion. These effects have been linked to aggravation of asthma and increased 

susceptibility to respiratory infection, potentially leading to increased medication use, increased 

school and work absences, increased visits to doctors’ offices and EDs, and increased hospital 

admissions, and pulmonary inflammation is also related to increased cellular permeability in the 

lung, which may be a mechanism by which O3 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 O3-related morbidity 

effects lend plausibility to the adverse morbidity effects and mortality effects observed in 

epidemiological studies reporting statistically significant associations with ambient O3

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, 0.060 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 conclusion on an appropriate range of levels for 

consideration, we have also focused on considering the public health implications of selecting 

different levels within this range (< 0.08 to 0.060 ppm O3). In so doing, we have looked to the 

results of the analyses of exposure and risk for the 74/4 scenario to represent the public health 

impacts of selecting a standard level in the upper part 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 represent 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 decrements in all and asthmatic children, respiratory 

symptom days in moderate to severe asthmatic children, respiratory-related hospital admissions, 

and non-accidental mortality. In considering both exposures of concern and quantitative risk 

estimates, we again note that there is substantial year-to-year variability across the three years 

included in this analysis (2002 to 2004) in the estimates of the number of children and the 

number of occurrences of exposures of concern at the benchmark levels and in the quantitative 

risk estimates. We also note the substantial city-to-city variability in these estimates of 

exposures of concern and quantitative risk. We believe that it is appropriate and important to 

consider not just the average estimates across all years or all cities included in the analyses, but 

to consider the public health impacts 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 setting the standard in the 

upper, middle and lower parts of the range. A standard 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 children27

(~ 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 city with the least degree of 

protection from this standard. In the mid-year (2003), in aggregate about 1% of all school age 

children (~110,000 children) are estimated to experience exposures 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 children (~ 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 the 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 concern, ranging up to 15% of all school age children 

(~290,000 children) in the single city with the least degree of protection from this standard. A 

standard set at this level would 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 standard (Figures 6-1 through 6-4), with city-to-city differences accounting 

for most of the variability in estimates. A standard set at this level would reduce non-accidental 

mortality by about 10 to 40%, with most of the variability occurring across the 12 city estimates 

(Figures 6-5 and 6-6). 

 There were two health outcomes that we evaluated in one city only, respiratory symptom 

days in moderate to severe asthmatic children (Boston, Table 6-9) and 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 children28 with 

moderate to severe asthma in the Boston area to 6,800 days, a 12% reduction relative to the 

current standard. Even with this reduction, it is estimated that 1 respiratory symptom day in 8 

during the O3 season would be attributable to O3 exposure. Estimated incidence of respiratoryrelated hospital admissions was reduced by 14 to 17% by a standard set 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 exposures 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 studies showing lung function decrements and 

respiratory symptoms in some healthy adults at 0.060 ppm O3, 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, suggesting less importance for the implications of 

exposures at the 0.060 ppm benchmark level from a public health policy perspective. 

 A standard set in the middle part of this range (e.g., the 70/4 scenario) would result in an 

aggregate estimate of about 1% of all school age 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 city with the least protection about 5% of all school age children (~ 64,000 

 28 Since there are estimated to be about 25,000 moderate 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 would reduce the number of all school 

age children30 estimated to experience one or more moderate 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 this level would reduce non-accidental mortality by 

about 20 to 55%, with most of the variability occurring across 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 area only slightly over the standard set at the upper 

end of the range, to 6,400 days (a 12% reduction). With this reduction, it is estimated that about 

1 respiratory symptom day in 8 during the O3 season would be attributable to O3 exposure. 

Estimated incidence of respiratory-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 recommended 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 O3 standard, against respiratory 

morbidity effects such as lung function decrements, respiratory symptom days and hospital 

admissions, as well as non-accidental mortality. 

 A standard set in the lower part of this range (e.g., the 64/4 scenario) would result in an 

aggregate estimate of less than 0.5% of all school 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 the 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 benchmark 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 this level are reduced substantially, resulting in an aggregate 

estimates of less than 0.5% of all school age children (~ 70,000 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 would reduce the number of all and asthmatic school 

age children estimated to experience one or more moderate lung function decrements by about 

50 to 80% over the current standard, and non-accidental mortality by about 25 to 75%, with most 

of the variability occurring across 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 area to 5,900 days, about a 25% reduction over the current standard. But 

even with this reduction, it is estimated that 1 respiratory symptom day in 10 during the O3

season is attributable to O3 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 standard 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 degree of protection. It would also 

substantially reduce exposures of concern at the benchmark level of 0.060 ppm, especially in the 

mid-year of the three years evaluated. It provides additional incremental protection for members 

of sensitive groups over the current O3 standard and the alternative standards at the upper to 

middle part of the range, against respiratory morbidity effects such as lung function decrements, 

respiratory symptom days and hospital admissions, 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 showing lung function decrements and respiratory 

symptoms in some healthy adults at 0.060 ppm O3, as well as evidence from epidemiological 

studies showing an array of respiratory morbidity effects occurring at levels below the current 

standard. It would place relatively less weight on the uncertainties associated with the exposure 

and risk estimates, and reflect the greater importance, 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 O3 standard, 

noting that “achievable gains in protecting public health” (Henderson 2006c, p. 5) can be 

accomplished by setting the level of the standard down to 0.060 ppm O3. The results of the 

exposure and risk assessments support this recommendation. Staff concludes that important 

improvements in protecting the health of sensitive groups can be made by setting the level of the 

O3 standard within the range of < 0.080 ppm to 0.060 ppm O3. Standard levels within this range 

considered in staff exposure and risk assessments include 0.074, 0.070, and 0.064 ppm, which 
 6-82

are representative of levels within the upper, middle, and lower parts of this range, respectively. 

Moreover, these assessment results indicate that even in the lower end of the range there are 

benefits to the health of sensitive groups that warrant consideration. 

To provide some perspective on the implications of alternative 8-hr primary standards 

(within the range of levels recommended above and within the range of forms discussed in the 

next section below), staff assessed (based on 2002 and 2004 air quality data) the percentage of 

counties, and the populations in those counties, that likely would not attain various 8-hr O3

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 conclusions and recommendations. 

6.3.5 Form 

 In 1997 the primary O3 NAAQS was changed from a “1-expected-exceedance” form31 to 

a concentration-based statistic, specifically the 3-year average of the annual fourth-highest daily 

maximum 8-hr concentrations. The principal advantage of the concentration-based form is that it 

is more directly related to the ambient O3 concentrations that are associated with the health 

effects. With a concentration-based form, days on which higher O3 concentrations occur would 

weigh proportionally more than days with lower concentrations, since the actual concentrations 

are used in determining whether the standard is attained. That is, given that there is a continuum 

of effects associated with exposures to varying levels of O3, the extent to which public health is 

affected by exposure to ambient O3 is related to the actual magnitude of the O3 concentration, not 

just whether the concentration is above a specified level. 

 In evaluating alternative forms for the primary standard in conjunction with specific 

standard levels, staff considers the adequacy of the public health protection provided by the 

combination of the level and form to be the foremost consideration. In addition, we recognize 

that it is important to have a form of the standard that is stable and insulated from the impacts of 

extreme meteorological events that are conducive to O3 formation. Such instability can have the 

effect of reducing public health protection, because frequent shifting in and out of attainment due 

of meteorological conditions can disrupt an area’s ongoing implementation 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, consideration was given to a range of alternative forms, 

including the second-, third-, fourth- and fifth-highest daily maximum 8-hr concentrations in an 

O3 season, recognizing that the public health risks associated with exposure to a pollutant 

 31The 1-expected-exceedance form essentially requires that the fourth-highest 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 threshold can be appropriately addressed 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 exceeded and the magnitude of such exceedances. 

Consideration was given to setting a standard with a form that would 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 potential chronic effects afforded 

by the alternatives within the range were not well enough understood to use any such differences 

as a basis for choosing the most restrictive forms. On the other hand, the relatively large 

percentage of sites that would experience O3 peaks well above 0.08 ppm and the number of days 

on which the level of the standard may be exceeded even when attaining a fifth-highest 0.08 ppm 

concentration-based standard, argued against choosing that form. 

 In selecting alternative standards to include in our exposure and risk analyses, we 

considered two concentration-based forms, the nth-highest maximum concentration and a 

percentile-based form. A percentile-based statistic is useful for comparing datasets of varying 

length because it samples approximately the same place in the distribution of air quality values, 

whether the dataset is several months or several years long. However, a percentile-based form 

would allow more days with higher air quality values in locations with longer O3 seasons relative 

to places with shorter O3 seasons. An nth-highest maximum concentration form would more 

effectively ensure that people who live in areas with different length O3 seasons receive the same 

degree of public health protection. 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 are shown in Figures 6-1 through 6-4, discussed 

above in section 6.3.4.2. These figures illustrate the estimated percent change in risk estimates 

for the incidence of moderate or greater decrements in lung function (≥ 15% FEV1) in all school 

age children and moderate or greater lung function decrements (≥ 10% FEV1) in asthmatic 

school age children, associated with going from meeting the current standard to meeting 

alternative standards with alternative forms. Figures 6-5 and 6-6 illustrate the estimated percent 

change in the estimated incidence of non-accidental mortality, associated with going from 

meeting the current standard to meeting alternative 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 standard, 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 to 
 6-84

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 are generally only small 

differences in the estimated reductions in risks associated with the third- to fifth-highest forms at 

a level of 0.074 ppm. 

In their letter to the Administrator, 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 alternative concentration-based forms to evaluate the 

implications of a broader range of alternative forms on public health protection and stability (i.e., 

with respect to yearly variability to ensure a stable target for control programs). 

The same group of commenters that expressed the view that the current primary O3

standard is not adequate also submitted comments that supported a more health-protective form 

of the standard than the current form (e.g., a second- or third-highest daily maximum form). The 

other group of commenters who expressed 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-based threshold for selecting a particular nthhighest daily maximum form of the standard 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, although in some cities larger differences are 

estimated. 

Staff concludes that a range of concentration-based forms from the third- to the fifthhighest daily maximum 8-hr average concentration is appropriate for consideration in setting the 

standard. Given that there is a continuum of effects associated with exposures to varying levels 

of O3, the extent to which public health is affected by exposure to ambient O3 is related to the 

actual magnitude of the O3 concentration, not just whether the concentration is above a specified 

level. The principal advantage of a concentration-based form is that it is more directly related to 

the ambient O3 concentrations that are associated with health effects. Robust, concentrationbased forms, in the range of the third- to fifth-highest daily maximum 8-hr average 

concentration, including the current 4th-highest daily maximum form, minimize the inherent lack 

of year-to-year stability of exceedance-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 three years (specifically the 12th-highest value in three years), 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 areas 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 O3

NAAQS 

Staff conclusions and recommendations on the elements of the primary O3 standard for 

the Administrator’s consideration in making decisions on the primary O3 standard are 

summarized below, together with 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 protection afforded by the standard. 

We recognize that selecting from among alternative standards will necessarily reflect 

consideration of qualitative and quantitative uncertainties 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 effects associated with exposure to O3, alone or in 

combination with related photochemical oxidants, taking into account both evidence-based and 

exposure- and risk-based considerations, and the nature and degree of uncertainties in such 

information. In recommending these ranges of alternative standards for consideration, we are 

mindful that the Act requires standards that, in the 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 does 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 O3 as the indicator for a standard that is intended to 

address effects associated with exposure to O3, alone or in combination with related 

photochemical oxidants. Based on the available information, and consistent with the 

views of CASAC and public commenters, we concluded that there is no basis for 

considering any alternative indicator at this time. Staff notes 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 O3 in these types of studies, control of ambient O3 levels 

is generally understood to provide the best means of controlling photochemical oxidants 

in general, and thus of protecting against effects that may be associated with individual 

species and/or the broader mix of photochemical oxidants, independent of effects 

specifically related to O3. 
 6-86

(2) It is appropriate to continue to use an 8-hr averaging time for the primary O3 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 appropriate 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 O3 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 that 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 evidence clearly calls into question the adequacy of 

the current standard and provides strong support for consideration of an O3 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 workers, against an array of adverse health 

effects that range from decreased lung function and respiratory symptoms to serious 

indicators of respiratory morbidity including ED visits and hospital admissions for 

respiratory causes, and possibly cardiovascular-related effects and mortality. We also 

conclude that risks projected to remain upon meeting the current standard, based on the 

exposure and risk assessment, are indicative 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 given to revising the level of the standard so 

as to provide increased public health protection. 

(a) We recommend that consideration be given to a standard level within the range of 

somewhat below 0.080 ppm to 0.060 ppm, reflecting our judgment that a standard 

set within this range could 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 upper, middle, and lower parts of this range, 

respectively. 

(b) We further recommend that consideration be given to specifying the level of the 

primary standard to the nearest thousandth ppm, reflecting the degree of precision 

with which ambient O3 concentrations can be measured and design values can be 

calculated. 
 6-87

(4) We conclude that it is appropriate to consider a form in the range of the annual third- to 

fifth-highest daily maximum 8-hr average concentration, which includes the current form 

of the annual fourth-highest daily maximum 8-hr average concentration, averaged over 

three years. It is appropriate to consider a form within this range in conjunction with a 

standard level within the recommended range, so as to provide an appropriate degree of 

increased public health protection. 

6.4 SUMMARY OF KEY UNCERTAINTIES AND RESEARCH 

RECOMMENDATIONS RELATED TO SETTING A PRIMARY O3 STANDARD 

We believe it is important to continue to highlight the uncertainties associated with 

establishing standards for O3 during and after completion of the NAAQS review process. 

Research needs go beyond what is necessary to understand health and welfare effects, population 

exposures, and the risks of exposure for purposes of setting standards. Research can also support 

the development of more efficient 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 document33 for review by the CASAC at a public 

meeting held November 16, 1998. Based on our review of scientific information contained in 

the 2006 CD, we have concluded that O3 health research needs and priorities have not changed 

substantially since the above document was written. Key uncertainties and research needs that 

continue to be high priority for future reviews of the health-based primary standards are 

identified below: 

(1) An important aspect of risk characterization and decision making for air quality standard 

levels for the O3 NAAQS is the characterization of the shape of exposure-response 

functions for O3, including the identification of potential population threshold levels. 

Recent controlled human exposure studies conducted at levels below 0.08 ppm O3 

provide evidence that measurable lung function 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 O3; therefore, prior attenuation of subject 

response may have been a factor in the responses observed. Considering the importance 

of estimating health risks in the range of 0.04 to 0.08 ppm O3, 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 while 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 concentration-response functions for O3, including identification of 

potential population threshold levels. Most of the recent studies and analyses continue to 

show no evidence for a clear threshold in the relationships between O3 levels and these 

health endpoints or have suggested that any such thresholds must be at very low levels 

approaching policy relevant background levels. Whether or not exposure errors, 

misclassification of exposure, or potential impacts of other copollutants may be obscuring 

potential population thresholds is still unknown. 

(3) The extent to which the broad mix of photochemical oxidants and more generally other 

copollutants in the ambient air (e.g., PM, NO2, SO2, etc.) may play a role in modifying or 

contributing to the observed associations between ambient O3 and various morbidity 

effects and mortality continues to be an important research question. Ozone has long 

been known as an indicator of health effects of the entire photochemical oxidant mix in 

the ambient air and has served as a surrogate for control purposes. A better 

understanding of sources of the broader pollutant mix, of human exposures, and of how 

other pollutants may modify or contribute to the health effects of O3 in the ambient air, 

and vice versa, is needed to better inform future NAAQS reviews. 

(4) As epidemiological research has become a more important factor in assessing the public 

health impacts of O3, methodological issues in epidemiological studies have received 

greater visibility and scrutiny. Investigations of questions on the use of generalized 

additive models in time-series epidemiological studies have raised model specification 

issues. There remains a need for further study on the selection of appropriate modeling 

strategies and appropriate methods to control 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 epidemiology research has provided suggestive 

evidence of both direct and indirect effects of O3 on the cardiovascular system, 

cardiovascular hospital admissions, and cardiovascular mortality. However, additional 

work will be needed to examine biologically plausible mechanisms of cardiovascular 

effects and to determine the extent to which O3 is directly implicated or works together 
 6-89

with other pollutants in causing adverse cardiovascular 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 remain subject to uncertainty due to use of 

ambient fixed-site data serving as a surrogate for ambient exposures, 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 air pollution have generally been measurements made at 

stationary outdoor monitors, but the accuracy with which these measurements actually 

reflect subjects’ exposure is not yet fully understood. Also, additional research is needed 

to improve the characterization of the degree to which discrepancy between stationary 

monitor measurements and actual pollutant exposures introduces error into statistical 

estimates of pollutant effects in time-series studies. 

(7) Improved understanding of human exposures to ambient O3 and to related copollutants is 

an important research need. Population-based information on human exposure for 

healthy adults and children and susceptible or at-risk populations including asthmatics to 

ambient O3 concentrations, including exposure information in various 

microenvironments, is needed to better evaluate current and future O3 exposure models. 

Such information is needed for sufficient periods to facilitate evaluation of exposure 

models throughout the O3 season. 

(8) Information is needed to improve inputs to current and future population-based O3

exposure and health risk assessment models. Collection of time-activity data over longer 

time periods is needed to reduce uncertainty in the modeled exposure distributions that 

form an important part of the basis for decisions regarding air quality standard for O3 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, including sleep to vigorous physical 

exertion is needed. 

(9) An important consideration in the O3 NAAQS review is the characterization of policy 

relevant background levels. There still remain 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 reduce 
 6-90

uncertainties in estimating health risks relevant for standard setting (i.e., those risks 

associated with exposure to O3 in excess of policy relevant background levels) and would 

aid in the development of associated 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 Protection 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 Exposure 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.” Environmental 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/StatusOfPreschoolPolicyInTheStates.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.; 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. 

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 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-inflammatory medication use 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 Santa Clara County, California: 1989-1996. Environ. Health 

Perspect. 107: 637-641. 

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. Special 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.; Beckett, W. S.; Leaderer, B. P. (2003) 

Association of low-level ozone and fine particles with respiratory symptoms in children with asthma. JAMA 

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. 

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 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. 

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 mortality 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.; 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. 

Langstaff, J. (2007) Analysis of Uncertainty in Ozone 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 Institute; research report 

no. 95. 

Moolgavkar, S. H.; Luebeck, E. G.; Hall, T. A.; Anderson, 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.; Leaderer, B. P. (1999) 

Healthy women's PEF variations with ambient summer concentrations of PM10, PM2.5, SO4

2-, H+

, and O3. 

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 mortality in two Southern California counties. Environ. Res. 

70: 98-104. 

Ostro, B.; Lipsett, M.; Mann, J.; Braxton-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 Tables 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.; Curtis, L.; Ramakrishnan, V.; Wadden, R. A.; Hryhorczuk, 

D. O. (2002) Effect of ozone and aeroallergens 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 the 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. OAQPS 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 Triangle 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/recordisplay.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 Standards, 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 information. OAQPS staff paper – Second draft. Research 

Triangle Park, NC: Office of Air Quality 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 pollution 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 Carol 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 O3. 

Welfare effects addressed by a secondary NAAQS 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 welfare effects categories, 

the effects of O3 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, O3 is the most prevalent, impairing crop 

production and injuring native vegetation and ecosystems more than any other air pollutant" 

(U.S. EPA, 1989, 1996b). 

 Ozone can also affect other ecosystem components 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 condition (see Figure 7-21 and discussion in section 

7.7). This framework can be used to link O3 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 currently not quantifiable, but still have societal 

value. In the absence of sufficient research to allow quantification of O3 impacts at the 

ecosystem level, including impacts on ecosystem goods and services, only a qualitative 

discussion is included. However, the staff infers, based on the linkages described in the SAB 

framework, that increasing protection for vegetation from O3 related effects would also improve 

the protection afforded to ecosystems and their related public welfare categories. 

 Other O3 related welfare effects categories include 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 materials and the economic consequences of that damage are poorly 

characterized, however, and the scientific literature contains very little new information to 

adequately quantify estimates of materials damage from photochemical oxidants (U.S. EPA, 

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1996a, b, 2006). Therefore, staff judges that there is insufficient information in the materials 

damage literature to inform secondary standard setting 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 O3 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 high concentrations of O3 on a regional scale could have a discernable 

influence on climate, leading to surface temperature and hydrological cycle changes. However, 

the CD stated that confirming this effect will require further advances in monitoring and 

improvement in chemical transport and regional-scale modeling. Thus, staff concludes that 

insufficient information is available at this time to quantitatively inform the secondary NAAQS 

process with regard to this aspect of the O3-climate interaction and will not address it further. 

Another aspect, is the potential modification of plant response to O3 under conditions of 

changing climate, is included in the discussion of factors that can modify the predicted 

vegetation responses (see section 7.4.2). 

 To summarize, this chapter includes an integrated discussion of the key policy relevant 

science regarding O3-related effects on vegetation (sections 7.2 through 7.4) and terrestrial 

ecosystems (section 7.7), as described in the previous CD (U.S. EPA, 1996a ) and reiterated in 

the current CD (U.S. EPA, 2006). The remaining sections (7.5 and 7.6) of this chapter are 

focused on a discussion of the analyses that have 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 O3 air quality scenarios under 

consideration. The environmental assessment technical support document, Technical Report on 

Ozone Exposure, Risk, and Impacts Assessments for Vegetation (Abt, 2007) (hereafter cited as 

“Environmental Assessment TSD”), presents a detailed 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 and 7.6. This information forms the basis for a 

discussion in Chapter 8 of staff conclusions and recommendations with respect to the secondary 

O3 NAAQS. 

7.2 MECHANISMS GOVERNING PLANT RESPONSE TO OZONE 

 The interpretation of predictions of risk associated with vegetation response at ambient 

O3 exposure levels can be informed by scientific understanding regarding O3 impacts at the 

genetic, physiological, and 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 the fundamental hypotheses concerning O3-induced 

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changes in physiology continues to be valid. However, during the last decade, understanding of 

the cellular processes within plants has been further clarified and enhanced. Therefore, this 

section reviews the key scientific conclusions identified in 1996 O3 CD (U.S. EPA, 1996a), and 

incorporates new information from the current CD (U.S. EPA, 2006). This section describes: 

(1) O3 uptake, (2) cellular to systemic O3 response, (3) plant compensation and defense 

mechanisms, (4) O3–induced changes to plant metabolism, and (5) plant response to chronic O3

exposures. 

7.2.1 Ozone Uptake: Canopy, Plant and Leaf 

 To cause injury, O3 must first enter the plant through the stomata of the leaves. Leaves 

exist in a three dimensional environment called the plant canopy, where each leaf has a unique 

orientation and receives a different 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 with individual leaves. Not all O3 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 emissions from soils. Because O3 does not penetrate the leaf’s 

cuticle, it must reach the stomatal openings in the leaf for absorption to occur. The movement of 

O3 and other gases such as CO2 into and out of leaves is controlled primarily through the 

stomata. The aperture of the stomata are controlled 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, CO2 concentration, soil fertility and water status, and in some cases the presence 

of other air pollutants, including O3 (see section 7.4.2). These modifying factors produce 

stomatal conductances that vary across the diurnal cycle, days and seasons. Once O3 is inside the 

leaf, a phytotoxic effect will only occur if sufficient amounts of O3 reach sensitive cellular sites 

that are subject to the various physiological and biochemical controls within the leaf cells (see 

the discussion in section 7.2.3 below – Compensation and Detoxification). 

 A measure of O3 flux is attractive because it incorporates both relevant environmental 

factors and physiological processes, and is considered the measure that most closely links 

exposure to plant response. Unfortunately, measurement 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, particularly in Europe, in using mathematically 

tractable flux models for O3 assessments at the regional and national scale (Emberson et al., 

2000a, b). Though significant new research has been done with respect to flux model 

development, it has still not advanced to a point of being generally applicable across a range of 

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species 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 O3 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 into the water lining the 

cell wall of the air spaces (path 2). Having entered the aqueous phase, O3 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 external signal transducer molecules (U.S. EPA, 2006). This 

alteration in plasma membrane function is clearly an early step in a series of O3-induced events 

that leads to leaf injury. 

 Under certain circumstances, O3 reacts with organic molecules to generate peroxides, 

including hydrogen peroxide (H2O2). The role of hydrogen peroxide as a signaling molecule in 

plants is now better understood. The primary set of metabolic reactions that O3 triggers clearly 

includes those typical of “wounding” responses generated by cutting of the leaf or by 

pathogen/insect attack. One aspect of this total response is the production of O2 and H2O2 by the 

cell (Lamb and Dixon, 1997). The presence of higher-than-normal levels of H2O2 within the 

apoplastic space is a potential trigger for the normal, well-studied pathogen defense pathway. 

 Ethylene is another compound produced when plants are subjected to biotic or abiotic 

stressors. Increased ethylene production by plants exposed to O3 stress was identified as a 

consistent marker for O3 exposure decades ago (Tingey et al., 1976). These studies suggested 

that increased production of stress-ethylene correlated well with the degree of foliar injury that 

developed within hours or days after O3 exposure. Thus, one could postulate that O3 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 O3 uptake is small enough for 

the plant to detoxify or metabolize O3 or its metabolites or (2) the plant is able to repair or 

compensate for the O3 impacts (Tingey and Taylor, 1982; U.S. EPA, 1996a). Leaves may 

physically exclude O3 from sensitive tissues. A few studies have documented a direct stomatal 

closure or restriction in response to the presence of O3 ranging from within minutes to hours or 

days of exposure (Moldau et al., 1990; Dann and Pell, 1989; Weber et al., 1993). However, 

exclusion of O3 also restricts the uptake of CO2, thus limiting photosynthesis and growth. 

 In addition, plants can also effectively protect tissue against damage by dissipating excess 

oxidizing power using antioxidants. Since 1996, the role of detoxification in providing a level of 

7-4
resistance to O3 has been further investigated. A number of antioxidants, including ascorbate, 

glutathione peroxidase, and sulfuroxide dimutase, which are highly reactive, can detoxify the 

chemicals generated by O3. The pattern of changes in these antioxidant proteins varies greatly 

among different species and conditions. Most recent reports indicate that ascorbate within the 

cell wall provides the first significant opportunity for detoxification to occur. The balance 

between the total O3 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 still not clear as to what extent detoxification 

protects against O3 injury. Specifically, data are needed on the potential rates of antioxidant 

production and on the subcellular location of the antioxidants. Potential rates of antioxidant 

production are needed to assess whether they are sufficient to detoxify the O3 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 O3 before it has a chance to damage 

subcellular systems. In addition, generation of these antioxidants in response to O3-induced 

stress potentially diverts resources away from other sinks and expends energy. Thus, scientific 

understanding of the detoxification mechanisms is not yet complete and requires further 

investigation (U.S. EPA, 2006). 

 Once O3 injury has occurred in leaf tissue, some plants are able to repair or compensate 

for the impacts (Tingey and Taylor, 1982). In general, plants have a variety of compensatory 

mechanisms for low levels of stress including reallocation of resources, changes in root/shoot 

ratio, production of new tissue, and/or biochemical shifts, such as increased photosynthetic 

capacity in new foliage and changes in respiration 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 O3. It is not yet known to what degree or how the use of plant 

resources for repair processes affects the overall carbohydrate budget or subsequent plant 

response to O3 or other stresses (U.S. EPA, 1996a, U.S. EPA, 2006). 

7.2.4 Changes to Plant Metabolism 

 Ozone inhibits photosynthesis, the process 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 O3-induced stomatal closure resulting in reduced uptake of CO2. A 

large body of literature published since 1996 has further elucidated the mechanism of effect of 

O3 within the chloroplast. Pell et al. (1997) showed that O3 exposure results in a loss of 

Ribulose-1, 5-bisphosphate carboxylase/oxygenase (RuBisCo), the central carboxylating enzyme 

that plays an important role in the production of carbohydrates. Due to its central importance, 

7-5
any decrease in RuBisCo may have severe consequences for the plant’s productivity. Several 

recent studies have found that O3 has a greater effect as leaves age, with the greatest impact of 

O3 occurring on the oldest leaves (Fiscus et al., 1997; Reid and Fiscus, 1998; Noormets et al., 

2001; Morgan et al., 2004). The loss of RuBisCo and its messenger RNA as a function of 

increasing O3 exposure is also linked to an early senescence or a speeding up of normal 

development leading to senescence. 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 O3 Exposures 

 Many changes that occur with O3 exposure can be observed within hours, or perhaps 

days, of the exposure, including those connected with wounding and elicitor-induced changes in 

gene expression. Other effects due to O3, however, take longer to occur and tend to become 

most obvious after long exposures to low-O3 concentrations. These have been linked to 

senescence or some other physiological response very closely linked to senescence. The 

understanding of how O3 affects long-term growth and resistance to other biotic and abiotic 

insults in long-lived trees is unclear. Often, the conditions 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 species, 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 documented in the growth of tree 

seedlings (Hogsett et al., 1989; Sasek 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 O3 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 cellular mechanisms into altered cell metabolism, 

whole plant productivity, and other physiological effects. 

7.3 NATURE OF EFFECTS ON VEGETATION 

 Studies published since the conclusion of the 1996 review continues to support and 

strengthen key conclusions regarding O3 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 Chapter 9 and Annex 9 in the current CD (U.S. EPA, 

2006) 

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7.3.1 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 O3 sensitivity. Most of the studied species were selected because of 

their commercial importance or observed O3-induced visible foliar injury in the field. Given that 

O3 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 O3 sensitivity 

that exists within U.S. vegetation is unknown. Even so, plant species/genotypes with known O3

sensitivity span a broad range of vegetation types and public use categories. These use 

categories include food production for human and domestic animal consumption, fiber and 

materials production, and urban/private landscaping. In addition to these direct uses, a number 

of O3 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 O3 sensitive species that 

occur in Federal Class I areas and Table 7J-2 presents O3 sensitive species in each state. 

7.3.2 Vegetation Effects Endpoints 

 Ozone injury at the cellular level, when 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; reduced carbohydrate production and reallocation; 

reduced growth or reproduction; and reduced plant vigor. Much of what is now known about O3

exposure-plant response relationships, as summarized below, is based on research that was 

available in the last review. Thus, the present discussion is largely 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 O3 on vegetation. 

7.3.2.1 Visible Foliar Injury and Premature Senescence 

 Cellular injury can and often does become visible. Acute injury usually appears within 

24 hours after exposure to O3 and, depending on species, can occur 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 (Jacobson, 1977). Chronic injury 

may be mild to severe. In some cases, cell death or premature leaf senescence may occur. The 

significance of O3 injury at the leaf and whole 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 

7-7
difficulty 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 species and environments, what degree of injury 

at the leaf level has significance to the vigor of the whole plant. 

 However, visible foliar injury by itself, can impact the public welfare. The presence of 

visible symptoms due to O3 exposures can reduce the market value 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 O3-related injury on sensitive ornamental species due to the 

cost associated with more frequent replacement and/or increased maintenance (fertilizer or 

pesticide application). In addition, because O3 not only results in discoloration of leaves but can 

lead to more rapid senescence (early shedding of leaves), there is a potential for some lost tourist 

dollars at sites where fall foliage is less available or attractive. 

 In recent years, field surveys of visible foliar injury symptoms have become more 

common, with greater attention to the standardization 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 Health 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 O3 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 incidence on bioindicator species as a measure of the 

occurrence of phytotoxic levels of O3 in the ambient air. 

 To view pictures of O3-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 sufficiently reduced, the plant will respond by 

reallocating the remaining carbohydrate at the level of the whole organism. Many studies have 

demonstrated that root growth is more sensitive to O3 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 terrestrial plants. For host plants, these fungi improve 

7-8
the 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-studied pollution gradient in the San Bernardino 

Mountains of southern California suggest that O3 substantially reduces root 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 (Grulke 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 effects on other ecosystem components were not examined, a 

reduction of root growth of this magnitude could have significant implications for the below 

ground communities at those sites. In contrast, a study in Great Smoky Mountains National Park 

in Tennessee found no statistically significant effects of O3 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 O3 stress 

range from a reduction (Barnes et al., 1990; Miller et al., 1989), to no effect (Alscher et al., 

1989), to an increase (Luethy-Krause and Landolt, 1990). Therefore, studies that examine only 

above-ground vegetative components may miss important O3-induced changes below ground. 

These below-ground changes could signal a shift in nutrient cycling with significance at the 

ecosystem level (Young and Sanzone, 2002). 

7.3.2.3 Growth and Reproduction 

 Studies of the growth response of trees to O3 have established that individual deciduous 

trees are generally less sensitive to O3 than most annual plants, with 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 O3 as annual plants. The O3 sensitivity of seedlings 

and mature trees within species and between species varies widely. In general, mature deciduous 

trees are likely to be more sensitive to O3 compared to seedlings, while mature evergreen trees 

are likely to be less sensitive than seedlings. Based on these results, stomatal conductance, O3

uptake, and O3 effects cannot be assumed to be equivalent in seedlings and mature trees. 

 Depending on exposure duration, concentrations of O3 currently in the United States are 

sufficient to affect the growth of a number of tree species during the annual growing season. 

However, these conclusions do not take into account the possibility of “carry over” effects on 

growth in subsequent years, an important consideration in the case of long-lived species. Given 

that multiple-year exposures may cause a cumulative effect on the growth of some trees (Hogsett 

7-9
et al. 1989; Simini et al., 1992; Temple et al., 1993), it is likely 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 O3 exposures that occur in some years 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 O3 effects on different stages of plant 

reproduction. Effects of O3 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 effects will culminate in seed production. The recent scientific 

literature supports the conclusions of the 1996 CD that ambient O3 concentrations are reducing 

the yield of major crops in the U.S. For example, the yield reductions for soybean are generally 

similar to those reported previously (U.S. EPA, 2006). 

7.3.2.4 Reduced Plant Vigor 

 Though O3 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 sensitive species and genotypes 

within species to adapt to or withstand other environmental stresses. These may include 

increased susceptibility to freezing temperatures, pest infestations and/or root disease, and 

compromised ability to compete for available resources. For example, when different species are 

grown together, O3 exposure can increase the growth of O3-tolerant species while exacerbating 

the growth decrease of O3-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, beginning at the level of the individual cell and 

accumulating up to the level of whole leaves, plants, plant populations, communities and whole 

ecosystems. Not all O3-related effects, however, have been classified as “adverse” to public 

welfare. Previous reviews have classified O3 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 photosynthetic rate), 

altered plant quality, or reduced growth, that does not impair the intended use or value of the 

plant (Guderian, 1977). In contrast, “damage” includes those injury effects 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 loss). Yield loss also may include changes in crop 

quality, i.e., physical appearance, chemical composition, or the ability to withstand storage. 

While this construct has proved useful in the past, it appears most useful in the context of 

evaluating effects on single plants or species grown in monocultures, such as agricultural crops 

or managed forests. It is less clear how it might apply to potential effects on natural forests or 

entire ecosystems, such as shifts in species composition or nutrient cycling 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 could 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 O3-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), additional support is provided for 

expanding the consideration of adversity by making explicit the linkages between stress- related 

effects (e.g., O3 exposure) at the species level and at higher levels within an ecosystem hierarchy. 

Staff suggests that consideration of adverse effects 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 setting is that uncertainty is introduced when 

attempting to extrapolate or apply those results outside that specific setting (e.g., to a different set 

of organisms, scales, or exposure/growing conditions). The description of plant response to O3

exposure is no different. Because staff must necessarily rely on experimental data produced 

under very specific sets of conditions in conducting this assessment, it is important to understand 

the range of factors that can influence plant response to O3 and the magnitude and direction of 

that response, in order to better assess the likelihood of observing the experimentally predicted 

response in the ambient environment. 

 Plant response to O3 exposure is a function of the plant’s ongoing integration of genetic, 

biological, physical and chemical factors both within and external to the plant. The corollary is 

also true that O3 exposure can modify the plant’s subsequent integrated response to other 

environmental factors, both by influencing the plant response directly, and by contributing to 

altered climatic factors that influence plant response through its greenhouse gas forcing 

properties. 

7-11
 The 1996 O3 CD (U.S. EPA, 1996a) concluded with a statement that our understanding 

regarding modifying factors was too fragmented to permit drawing many general conclusions. 

Unfortunately, in the interval since the 1996 CD, little additional information has become 

available, thus, this earlier conclusion remains unchanged. Therefore, only a brief overview of 

the current understanding from this research is provided. The reader 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 O3 is determined by genes that are directly related to oxidant stress and 

to an unknown number of genes that are not specifically related to oxidants but instead control 

leaf and cell wall thickness, stomatal conductance, and the internal architecture of the air spaces. 

It is unlikely that single genes are responsible for O3 tolerance, except in rare cases (Engle and 

Gabelman, 1966). Recent studies using molecular biological tools and transgenic plants have 

begun to positively verify the role of various genes and gene products in O3 tolerance and are 

beginning to increase the understanding of O3 toxicity and differences in O3 sensitivity. 

Specifically, O3 has been shown to trigger the production of a number of compounds (e.g., 

ethylene) and the signaling of these molecules determines, in some cases, the O3 susceptibility of 

plants (U.S. EPA, 2006). Because the genetic code is species specific, species vary greatly in 

their responsiveness to O3. Even within a given species, individual genotypes or populations can 

also vary significantly with respect to O3 sensitivity. Thus, caution should be taken when 

ranking species categorically as having an absolute degree of sensitivity to O3. 

7.4.2.2 Biological Factors 

 The biological factors within the plant’s environment that may directly or indirectly 

influence its response to O3 in a positive or negative manner encompass insects, other animal 

pests, diseases, weeds, and other competing plant 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. Likewise, mutually beneficial 

relationships or symbioses involving higher plants and bacteria or fungi may also be affected by 

O3. Ozone can also have indirect effects on herbivorous animals due to O3-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 crops, forest trees, and other natural vegetation have yet to be 

studied. With respect to any particular O3-plant-insect interaction, it is still not possible to predict 

its likelihood, or its severity. The situation is only a little clearer with respect to interactions 

involving facultative necrotrophic plant pathogens, with O3 generally leading to increased 

7-12
disease. In contrast, with obligate biotrophic fungal, bacterial, and nematode diseases, there are 

twice as many reports indicating O3-induced inhibitions than enhancements. At this time, 

therefore, although some diseases may become more widespread or severe as a result of 

exposure to O3, it is still not possible to predict which diseases are likely to present the greatest 

risks to crops and forests. 

 The latest studies on O3 interactions with root symbionts present a more complex picture 

than was described in the last review. In addition to adverse effects of O3 on the functioning of 

tree root symbioses with mycorrhizae (discussed in section 7.3.1 above), there is also evidence 

that the presence of mycorrhizae may help plants overcome root diseases stimulated by O3 and/or 

encourage the spread of mycorrhizae to the roots of uninfected trees. 

 The few recent studies of the impact of O3 on intraspecific plant competition have again 

confirmed that grasses frequently show greater resilience than other types of plants. In grasslegume pastures, the leguminous species suffer greater growth inhibition. Separately, the 

suppression of ponderosa pine seedling growth by blue wild-rye grass was markedly increased 

by O3 (Andersen et al. 2001). Due to the limited number of species studied under competitive 

situations to date, however, it is still not possible to predict the outcome of O3 exposure on other 

specific competitive situations, such as successional plant communities or crop-weed 

interactions. Clearly, however, O3 stress creates a selective pressure 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 O3 exposure. Light is an essential “resource” whose energy content drives 

photosynthesis and CO2 assimilation. It has been suggested that increased light intensity may 

increase the sensitivity of light-tolerant species to O3 while decreasing the O3 sensitivity of 

shade-tolerant species, but this appears to be an oversimplification with many exceptions. 

 Temperature affects the rates of all physiological processes based on enzyme-catalysis 

and diffusion, and each process and overall growth (the integral of all processes) has a distinct 

optimal temperature range. Although some recent field studies have indicated that O3 impact 

significantly increases with increased ambient temperature, other studies have revealed little 

effect of temperature. Temperature is unquestionably an important variable affecting plant 

response to O3 in the presence of the elevated CO2 levels contributing to global climate change 

(see below). In contrast, evidence continues to accumulate to indicate that exposure to O3

sensitizes plants to low temperature stress by reducing below-ground carbohydrate reserves, 

7-13
possibly leading to responses in perennial species ranging from rapid demise to impaired growth 

in subsequent seasons. 

 High relative humidity of the ambient air has generally been found to increase the 

adverse effects of O3 by increasing stomatal conductance and thereby increasing O3 flux. 

Similarly, abundant evidence indicates that the ready availability of soil moisture results in 

greater sensitivity to O3. The opposite condition, drought, has been observed in field 

experiments and modeled in computer simulations to provide partial “protection” against the 

adverse effects of O3 as would be expected. This is because, in the short-term, drought causes 

stomates to close and thus, decrease the exposure to O3. However, there is also compelling 

evidence that O3 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-specific nature of the 

response. Regardless of the interaction, however, the net result of drought on growth in the 

short-term is negative, although in the case of tree species, other 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 air exposures and actual exposure concentrations 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 sweeping conclusions. Somewhat 

analogous with temperature, it appears that any shift away from the nutritional optimum may 

lead to greater sensitivity, but the shift would have to be substantial before a significant effect on 

response to O3 was observed. 

 Interactions of O3 with other air pollutants have received relatively little recent attention. 

The situation with SO2 remains inconsistent, but seems unlikely to pose any additional risk to 

those related to the individual pollutants. With NO and NO2, the situation is complicated by 

their nutritional value as N sources. In leguminous species, it appears that NO2 may reduce the 

impact of O3 on growth, with the reverse in other species, but the nature of the exposure pattern, 

i.e., sequential or concurrent, also determines the outcome. Much more investigation is needed 

before it will be possible will be able to predict the outcomes of different O3-NO-NO2 exposure 

scenarios. The latest research into O3 × acid rain interactions has confirmed that, at realistic 

acidities, significant interactions are unlikely. A continuing lack of information precludes 

offering any generalizations about interactive effects of O3 with NH3, HF, or heavy metals. 

7-14
More evidence has been reported that the application of fungicides affords some protective 

effects against O3. 

 Over the last decade, considerable emphasis has been placed on research into O3

interactions with two components of global climate change: increased atmospheric CO2 and 

increased mean global temperature. Most of these studies, however, have tended to regard 

increased CO2 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 CO2 levels at the current mean ambient 

temperatures are not particularly helpful in trying to assess the impact of climate change on 

responses to O3, since most of the biotic and chemical interactions with oxidants may be 

modified by these climatic changes. Though it is now known from limited experimental 

evidence and evidence obtained by computer simulation that an atmosphere sufficiently enriched 

with CO2 (e.g., 600 + ppm) would more than offset the impact of O3 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 O3 × 

CO2 × disease or O3 × CO2 × nutrient availability. Increased use of computer simulations may 

be important in suggesting outcomes of the many complex interactions of O3 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 variations in net impacts of climate change in 

different geographic areas are expected. Many regions are predicted to experience severe, 

possibly irreversible, adverse effects 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 O3

and PM concentrations that may occur in a warming climate. An assessment of the results of this 

effort is expected to be available for consideration in the next review of the O3 NAAQS. 

7.5 CHARACTERIZATION OF VEGETATION EXPOSURES TO OZONE 

7.5.1 Key Considerations in Vegetation Exposure Characterization 

 In the last review, the Administrator chose to make the secondary O3 NAAQS equal to 

the primary standard set as the three year average of the annual 4th-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 O3 CD (U.S. EPA, 

7-15
2006). Staff, therefore, continues to express hourly O3 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 W126 will emerge from the discussions of current 

patterns of O3 air quality and of policy-relevant background (PRB) in the remainder of this 

section. Further, in a letter to the Administrator 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 will be referred to in the rest of this document: 

• 8-hr average form: 4th-highest daily maximum 8-hr average over the O3 season. 

• 12-hr SUM06: 3-month sum of all hourly O3 concentrations greater than or equal to 0.06 

ppm observed during the daily 12-hr period between 8 am and 8 pm. The 3 months are 

the maximum consecutive 3 months during the O3 season. 

• 12-hr W126: Sigmoidally weighted 3-month sum of all hourly O3 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 O3 season. 

More specifically, W126 is defined in Lefohn et al., 1988 as: 

∑

<

=

− + = = =

PMi

AMi

iC i C Ct i i

e

W wandihouratOhourlyCwhereCw

8

8

3 126 44031

1 126 , ,

Staff selected two levels of air quality to evaluate for each of these 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 protection 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 approximately 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 level was proposed for a secondary standard in 

the 1996 review. Alternatively, the lower levels of both SUM06 (15 ppm-hr) and W126 (13 

ppm-hr) were associated with a level of crop protection of approximately no more than 10% 

yield loss in 75% of NCLAN cases. Another level to note is the upper level benchmark of W126 

7-16
 The 1997 final rule recognized that “it remained uncertain as to the extent to which air 

quality improvements designed to reduce 8-hr O3 concentrations would reduce O3 exposures 

measured by a seasonal SUM06 index” (62 FR 38876). In the last review, staff undertook an 

analysis to explore the relationship 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 also above the 0.08 primary standard. However, considerable 

uncertainty remained as to the strength of the relationship, especially between urban O3 air 

quality and distributions that occur 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 level of the 8-hr average form and exposure levels of concern for 

vegetation expressed in terms of the 12-hr W126. Figure 7-1 depicts county O3 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 relationship between these two forms averaged over 

three recent years (2002-2004). Both the 21 and 13 ppm-hr levels for the 12-hr W126 are 

indicated on the graph. For the 3-year average 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-hrs 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 O3 air quality have occurred in 

some areas of the U.S. In the eastern U.S., these 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 Chapter 2 of this SP). In addition, efforts to 

attain the current NAAQS have no doubt contributed to some air quality improvements, 

including lower hourly maximum values and fewer 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 concentrations 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). However, 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 between the 12-hr W126 and 12-hr SUM06 metrics 

discussed in Chapter 7 and Chapter 8 of this document were done based on NCLAN data (See 

Appendix 7B). 

7-17
Figure 7-1. The 3-year average (2002-2004) of the 4th-highest maximum 8-hr average (current standard fo

year average of the highest 3-month 12-hr W126, by county. 

Highest 3-month 12-hr W126 (ppm-hrs), 3-year average

4th Highest Max. 8-hr Aver 0 10 20 30 40 50 60 70 80 90age (ppm), 3-year average 

0.000.020.040.060.080.100.120.14

12-hr W126 options analyzed

Current standard

Alternative standard

7-18
vegetation response can occur in some areas that meet the current 8-hr average secondary 

NAAQS. The number of counties meeting the current 8-hr average 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 reports 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, staff has also focused on 

air quality in the subset of national park sites and important natural areas. Two recent reports 

presented some discussion of O3 trends in a subset of national parks (See discussion in The 

Ozone Report: Measuring Progress through 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 terms of the current 8-hr average form. Therefore, 

staff has selected a subset of national parks and other significant natural areas representing 4 

general regions of the U.S to analyze available air 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 O3 levels above concentrations that have been shown to decrease 

plant growth and above the 12-hr W126 levels analyzed in this review. For example, one park in 

the east and four parks in the west 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 exposure levels of concern to vegetation is 

distinguishing between pollution levels that can be controlled by U.S. regulations (or through 

international agreements with neighboring countries) from levels that are generally considered 

uncontrollable by the U.S., e.g., policy-relevant-background (PRB). As described in Chapter 2 

of this SP, the global photochemical transport model GEOS-CHEM (Fiore et al., 2003) was used 

7-19
Figure 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 2005

Max 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 2005

Max 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.

7-20
Figure 7-3. Highest 3 month 12-hr W126 values from monitors in National Parks in the 

Mountain West (A) and California (B). 

Year

2001 2002 2003 2004 2005

Max 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 2005

Max 3-month 12-hr W126 (ppm-hr)

0

10

20

30

40

50

60

70

80

Sequoia NP

Yosemite NP

A.

B.

7-21
to estimate PRB levels. This model shows that PRB O3 concentrations, which vary as a function 

of season, altitude and total surface O3 concentration, are generally predicted to be in the range 

of 0.015 to 0.035 ppm at the surface in the afternoon, and they decline under conditions 

conducive to O3 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 stratospheric intrusions. The stratospheric contribution to surface O3 is typically 

well below 0.020 ppm and only rarely elevates O3 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 O3 in the 1996 O3 NAAQS review (U.S. EPA, 1996a, 2006). 

This is significant for the secondary standard review because the higher end of the range (0.05 

ppm) provided an important policy consideration for staff in 1996 for selecting the cumulative 

SUM06 exposure index that did not weight concentrations below 0.06 ppm. Thus, SUM06 was 

not influenced by concentrations thought to be at background. 

 Partially on the basis of these lower estimates of PRB, as well as declining peak O3 levels 

at some sites, staff has re-evaluated the usefulness of using the sigmoidally weighted W126 

index to capture more of the vegetation relevant exposures below 0.06 ppm. Though the W126 

index weights all concentrations, 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 concentration 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 threshold 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). Therefore, 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 O3 monitors in 2001. The metrics, as calculated at the monitors, are 

highly correlated. A similar correlation was seen with other years (2002-2004). Because the 

inflection point of W126 is approximately 0.06 ppm, the SUM06 metric is essentially a simple 

approximation of the sigmoidally weighted W126 form and it is not surprising that the two 

metrics measure O3 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 SUM06 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. 

7-22
Figure 7-4. Maximum 3-month 12-hr SUM06 plotted against maximum 3-month 12-hr 

W126. Data points are from the AQS and CASTNET O3 monitors for the year 

2001. 

3-month 12-hr SUM06 (ppm-hr)

0 10 20 30 40 50 60 70 80 90

3-month 12-hr W126 (ppm-hr)

0

10

20

30

40

50

60

70

80

90

r

2

 = 0.98

proposed1996 SUM06 standard

7-23
7.5.2 Monitor Networks: National Coverage 

Hourly O3 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 and 2.3.2 of this document. The AQS monitoring 

network currently has over 1100 active O3 monitors which are generally sited near population 

centers. However, this network also includes approximately 36 monitors located in national 

parks. CASTNET is the nation's primary source for data on dry acidic deposition and rural, 

ground-level O3. It consists of over 80 sites across 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, rigorous 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, see 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 O3 monitors are stable and show only very 

small variation (U.S. EPA 2003b, p.22). Both networks take O3 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 monitoring networks, however, vast rural areas of 

the U.S., where important crops and natural vegetation occur, still do not have O3 monitor 

coverage (Figure 7-5). As was the case in the 1996 review, staff found it necessary to select a 

method that could be used to characterize O3 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 O3 exposures on vegetation and ecosystems. Staff’s review of the monitoring 

data showed that within the five most recent years available (2000 to 2004), 2001 was a fairly 

moderate O3 year. Based on this information, and because 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 growth modeling), monitoring data from other air 

quality years were used. 

7-24
Figure 7-5. Locations of AQS monitors (top) and CASTNET monitoring stations (bottom) 

7-25
7.5.3 Community Multi-scale Air Quality Model (CMAQ) 

 Staff investigated the appropriateness of using the O3 outputs from the EPA/NOAA 

Community Multi-scale Air Quality (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 

O3 monitoring network in the western U.S. (see section 7.5.2). The CMAQ model is a multipollutant, multiscale air quality model that contains state-of-the-science techniques for 

simulating all atmospheric and land processes that affect the transport, transformation, and 

deposition of atmospheric pollutants 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/O3, particulate matter, and nutrient deposition) holistically. The CMAQ 

model can generate estimates of hourly O3 concentrations for the contiguous U.S., making it 

possible to express model outputs in terms of a variety of exposure indices (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 very limited capacity in which staff used the 

CMAQ results. As explained below, in the final analysis, staff opted not to use O3 values 

calculated from the CMAQ model, but instead only used model results to scale interpolations in 

the western U.S. 

7.5.4 Generation of Potential Ozone Exposure Surfaces (POES) 

 Staff evaluated ten approaches for interpolating O3 air quality across the U.S. which 

included (1) use of the CMAQ model alone; (2) use of only monitoring data with the Voronoi 

Neighbor Averaging (VNA) technique; and (3) use of a combination of monitoring data and 

scaling from CMAQ called enhanced Voronoi Neighbor Averaging (eVNA). The evaluations 

were based on how well the CMAQ model or interpolation 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 dropped out sequentially and a value for that 

monitor was interpolated using the 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). For more details see discussions in section 7.5.5 

below and in the Environmental Assessment TSD (Abt, 2007). From the results of these 

7-26
 Figure 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 reported to produce 14% biomass 

loss in 50% of tree seedlings studies by National Health and Environmental 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 approximately 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 seedlings studied (Lee and Hogsett, 1996). Much of the east and 

 To support the vegetation exposure and risk assessments, ambient O3 exposures were 

projected using seasonal O3 air quality for the 2001 base year in terms of the 3-month 12-hr 

W126 (Figure 7-6) and 12-hr SUM06 exposure indices (Figure 7D-1 in Appendix 7D). The 

uncertainties of this interpolation are discussed below (section 7.5.5). Taking the uncertainties 

into account and given the absence of more complete monitoring data in rural areas, staff finds 

the POES serves as a useful tool for identifying areas across the country where O3 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 O3 data would be 

interpolated was needed. Ideally these locations would be regularly spaced, cover the 

continental US, and be close enough to each other 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 both 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 densest possible non-redundant “composite” 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, O3 values were interpolated for each grid cell center in the composite grid (see 

Environmental Assessment TSD for more details, Abt, 2007). 

evaluations, the eVNA and VNA performed equally well in many cases. The CMAQ model 

alone did not perform as well as the VNA and eVNA 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 enhancing the interpolation with CMAQ did not add 

much information to the eastern U.S. interpolation 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 readily available data, being relatively inexpensive to run, and being 

able to quickly produce estimates of any exposure index, for multiple months or years, and for 

different air quality scenarios. 

7-27
Figure 7-6. Estimated 12-hr W126 Ozone Exposure – Max 3-months for 2001: “As Is” scenario 

7-28
 The 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 O3 air quality compared to Figure 7-7. 

Thus, the staff observes that, except for just meeting the current form, all other alternative 

standards, when met at all locations, would be expected to provide improved protection of 

Maps generated for the SUM06 25 and 15 ppm-hr scenarios 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 ppm), the overall seasonal 12-hr W126 exposures did not improve 

very much (Figure 7-7). Under this scenario, some areas in the east improve, but there are still 

many areas of the country that have seasonal O3 levels above 12-hr W126 of 21 ppm-hr. 

 To evaluate changing vegetation exposures and risks under changing air quality, maps 

were generated for selected "just meet" scenarios (Figures 7-7, 7-8, 7-9, 7-10) by analytically 

adjusting air quality distributions with the quadratic 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 O3 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 values 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 significant impacts to vegetation 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 seedlings. In the crop and tree 

seedling risk/benefit assessments, staff incorporated an adjustment of monitored O3 to take into 

account the uncertainty associated with a potential vertical O3 gradient from the height of the 

monitoring probe (~4 meters) to the approximate 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 (alternate standard proposed in the 1996 NAAQS 

review) and 15 ppm-hr 

• 4th-highest daily maximum 8-hr average of 0.084 ppm (current EPA standard) and 

0.070 ppm 

7-29
Figure 7-7. Estimated 12-hr W126 Ozone Exposure – Max 3-months for 2001: Quadratic Rollback to just 

hr Maximum of >0.084 

7-30
Figure 7-8. Estimated 12-hr W126 Ozone Exposure – Max 3-months for 2001: Quadratic Rollback to jus

hr Maximum of >0.070 

7-31
Figure 7-9. Estimated 12-hr W126 Ozone Exposure – Max 3-months for 2001: Quadratic Rollback to jus

of 25 ppm-hr, secondary standard proposed in 1996 

7-32
Figure 7-10. Estimated 12-hr W126 Ozone Exposure – Max 3-months for 2001: Quadratic Rollback to ju

SUM06 of 15 ppm-hr 

7-33
vegetation from seasonal O3 exposures of concern over the current standard. As expected, 

however, the greatest improvements in air quality and estimated exposures to sensitive 

vegetation were observed when just meeting the 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 O3 Exposure Analysis 

 Staff recognizes there are inherent uncertainties in using an interpolation that must rely 

on sparse data that, for the most part, are representative of urban and near-urban areas. This 

network could bias the picture of the O3 exposure estimate especially in the western U.S. where 

monitoring sites can be very far apart. Intuitively, 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 with 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 Mean 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 actualMETRIC

predictedMETRIC actualMETRIC NMB average − = ∈

 *100( )

i

i i

dropoutsi actualMETRIC

predictedMETRIC actualMETRIC

NME average − = ∈

 AMB = averageiεdropouts(predictedMETRICi – actualMETRICi)

 AME = averageiεdropouts(|predictedMETRICi – actualMETRICi|) 

This method of evaluation may result in a slight overestimation of error and bias for the exposure 

surface since dropping out monitors loses information that the interpolation uses in that local 

area. Summary error and bias metrics are presented 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 had a much higher NME of approximately 62%. 

However, since SUM06 and W126 values are often low numbers, NME can be calculated to be 

7-34
 Figure 7-11 also depicts predicted W126 values, 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 graphical representation of how well the O3 exposures were 

predicted in the rural monitors away from urban areas. A perfect prediction would result in all 

points aligning on the black “one-to-one” line. In general, these graphs indicate that the 

interpolation technique slightly overestimated W126 exposure at the low levels and 

underestimated W126 exposure at the high levels. Biologically, the more significant error is at 

the high exposures, since vegetation responds more at high exposures. Figure 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. More detailed information from this analysis is 

presented in the Environmental Assessment TSD (Abt, 2007). 

large while the absolute difference is small. For example, if a monitor with a W126 of 4 ppm-hr 

is measured and the interpolation predicts a W126 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 presented 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-predicted the 12-hr SUM06 values. This under-prediction is likely a 

result of the averaging inherent in the interpolation. Similar results are seen for the 12-hr W126 

(Table 7-1b). However, in almost all cases, the interpolation was able to predict monitored 

W126 slightly better than monitored 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 associated with the exposure surface. 

7-35
Table 7-1a. Evaluation statistics for the 3-month 12-hr SUM06 interpolations of the Eastern and Western 

NMB is Normalized Mean Bias, NME is Normalized Mean Error, AMB is Absolute Mean Bias Absolute Mean Error. An explanation of 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

Region Monitors NMB (%) NME (%) AMB (ppm-hr) AME (ppm

Eastern US All monitors -0.04 25.78 -1.83 4.07 Eastern US CASTNET only -8.84 20.76 -2.95 4.79 

Western US All monitors 16.46 62.39 -2.62 6.05 Western US CASTNET only -6.03 42.12 -2.15 7.98 

Region Monitors NMB (%) NME (%) AMB (ppm-hr) AME (ppm

Eastern US All monitors -1.06 21.92 -1.21 2.97 Eastern US CASTNET only -8.43 17.44 -2.00 3.22 

Western US All monitors 14.57 48.38 -1.50 4.27 Western US CASTNET only 0.67 41.47 -0.60 5.21 

7-36
Figure 7-11. Comparison of predicted versus 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 35

Predicted 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 70

Predicted 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

7-37
7.6 CHARACTERIZATION OF VEGETATION RISKS 

7.6.1 Scope of Vegetation Risk Assessment 

 The vegetation impact assessment conducted for the current review (see Figure 7-12a-c), 

consists of exposure, risk and benefits analyses and improves and builds upon the similar 

analyses performed in support of the 1996 secondary NAAQS review (U.S. EPA 1996b). The 

vegetation exposure assessment was discussed above in section 7.5. The organization of this 

section reflects the remaining risk and benefit components of the assessment. The vegetation 

risk discussion which follows is divided between the crop and tree analyses. The crop analysis 

discussed in section 7.6.2 includes estimates of the risks to crop yields from current and 

alternative O3 exposure conditions and the associated change in economic benefits expected to 

accrue in the agriculture sector upon meeting the levels of various alternative standards. The tree 

risk analysis described in section 7.6.3 includes three distinct lines of evidence: (1) estimates of 

seedling growth loss under current and alternative O3 exposure conditions; (2) observations of 

visible foliar injury in the field linked to recent monitored O3 air quality for the years 2001 - 

2004; and (3) simulated mature tree growth reductions using the TREGRO model to simulate the 

effect of meeting alternative air quality standards on the predicted annual growth of a single 

western species (ponderosa pine) and two eastern species (red maple and tulip poplar). Both 

quantitative and qualitative discussions of known sources and ranges of uncertainties associated 

with the components of this assessment are also discussed.

7-38
Figure 7-12 (a-c). Major Components 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 Seedling growth Foliar injury

(c) Economic Benefits

TREGRO

Model for 

3 species

Tree growth

‘As is’ & 

‘just meet’

air quality 

from east 

& west 

sites

Air 

quality/injury 

comparison

7-39
7.6.2 Characterization of Crop Risks and Associated Economic Benefits 

7.6.2.1 Exposure Methodologies Used in Vegetation Research 

 In the 1996 review, O3 exposure studies were dominated by the use of various versions of 

the open-top chamber (OTC), first described by Heagle et al. (1973) and Mandl et al. (1973). 

Hogsett et al. (1985, 1987) described in detail many 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 O3 (U.S. EPA, 2005b). 

 Chambered systems, including OTCs, have several advantages. For instance, they can 

provide a range of treatment levels including charcoal-filtered (CF), clean-air control, and above 

ambient concentrations for O3 experiments. Depending on experimental intent, a replicated, 

clean-air control treatment is an essential component in many experimental designs. The OTC 

can provide a consistent, definable exposure because of the constant wind speed and delivery 

systems. From a policy perspective, the statistically robust concentration-response (C-R) 

functions developed using such systems are necessary for evaluating the implications of various 

alternative air quality scenarios on vegetation response. 

 Nonetheless, there are several characteristics of the OTC design and operation that can 

lead to exposures that might differ 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; Legge et al., 1995). As with all methods that 

expose vegetation to modified O3 concentrations in chambers, OTCs create internal 

environments that differ from ambient air. This so-called “chamber effect” refers to the 

modification of microclimatic variables, including reduced and uneven light intensity, uneven 

rainfall, constant wind speed, reduced dew formation, and increased air temperatures (Fuhrer, 

1994; Manning and Krupa, 1992). However, staff notes that the uncertainties associated 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 the 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 answered is whether or not these differences affect the relative 

response of a plant to O3. As noted in the 1996 O3 CD (U.S. EPA, 1996a), evidence from a 

number of comparative studies of OTCs and other exposure systems suggested that responses 

were essentially the same regardless of exposure system used and chamber effects did not 

7-40
significantly affect response. For example, a study of chamber effects examined the responses of 

tolerant and sensitive white clover clones (Trifolium repens) to ambient O3 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 Resources Board (CARB), during its recent O3 standard 

review, came to a similar conclusion about the usefulness of OTC data. Its review states “there 

is little scientific justification for the categorical discounting of O3 yield-response relationships 

obtained using the OTC technology” (CEPA, 2005). 

 In recent years, a few studies have employed a modified Free Air CO2 Enrichment 

(FACE) methodology to expose vegetation to elevated O3 without using chambers. This 

exposure method was originally developed to expose vegetation to elevated levels of CO2, but 

has been modified to include O3 exposure in Illinois (SoyFACE) and Wisconsin (AspenFACE) 

for soybean and deciduous trees, respectively (Dickson et al., 2000; Morgan et al., 2004). The 

FACE method releases gas (e.g., CO2, O3) from a series of orifices placed along the length of the 

vertical pipes surrounding a circular field plot and uses the prevailing wind to distribute it. This 

exposure method may more closely replicate conditions 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 limitations than those of the OTC. Most 

importantly, it is not possible with FACE to produce a number of replicated treatment levels, 

including O3 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 throughout the FACE exposure rings. While the FACE 

protocols minimize exposure concentration gradients, 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 O3 concentrations in FACE-type exposures and this 

issue needs to be addressed more fully to understand O3 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 results observed in OTC studies used in the 1996 

review. For example, a series of studies undertaken at AspenFACE (Isebrands et al., 2000, 

2001) showed that O3-symptom expression was generally similar in OTCs, FACE, and ambientO3 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, soybean (Pioneer 93B15 cultivar) yield loss data 

from a two-year study was recently published (Morgan et al., 2006). This cultivar is a recent 

selection and, like most modern cultivars, has been selected with an already high current O3. It 

was found to have average sensitivity to O3 compared to 22 other cultivars tested at SoyFACE. 

7-41
In this experiment, ambient hourly O3 concentrations were increased by approximately 20% and 

measured yields were decreased by 15% in 2002, as a result of the increased O3 exposure 

(Morgan et al., 2006). To compare 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 calculated an 8% expected yield loss from the 

2002 O3 exposure which was surprisingly less than the 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 results from this study suggest that C-R relationships developed 

from chambers are not overestimating response of recently developed soybean cultivars to 

elevated O3 exposure. As more FACE data become available, 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 O3 CDs (U.S. EPA, 1996a; 

U.S. EPA 2006) also provided useful information on plant responses to O3 exposure. For 

example, Gregg et al. (2003), found significant effects of O3 on the growth of cottonwood 

saplings along an ambient O3 gradient in the New York City area, similar to those reported in 

OTCs (see section 7.6.3. Other exposure methods include but are not limited to chemical 

protectants (e.g., ethylenediurea [EDU]) and O3 exclusion. Nonetheless, given a continued 

policy need for robust C-R functions to evaluate vegetation response under alternative air quality 

scenarios and the apparent consistency between plant responses 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 continue 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 O3 C-R functions. Since very few 

new studies have published C-R functions that would be useful in an updated assessment, C-R 

functions from NCLAN remain the best data available for a national assessment of crop loss 

under various O3 air quality scenarios. The NCLAN protocol 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 which a network of field sites was established. In total, 15 crop 

species (corn, soybean, winter wheat, tobacco, sorghum, cotton, barley, peanuts, dry beans, 

potato, lettuce, turnip, and hay [alfalfa, 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 combinations of sites, water regimes, and exposure conditions, 

producing a total of 54 separate cases. Figure 7-13 uses the regression equations for each of the 

54 cases to graph predicted relative yield loss at various exposure levels in terms of a 12-hr 

W126 (Figures 7E-1, 2, 3 present similar figures with the 8-hr average and 12-hr SUM06 forms). 

7-42
Figures 7-14 (a-d) show composite graphs for some individual crops from NCLAN and the 

variations in sensitivity between important crops. According to the most recent USDA National 

Agricultural Statistical Survey (NASS) data, the 12 species analyzed in the last O3 NAAQS 

review account for greater than 70% of principal crops acreage planted in the U.S. in 2004.1 

Corn, soybean, and winter wheat alone accounted 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 included (e.g., cotton, field corn, grain sorghum, peanut, soybean, 

winter wheat, lettuce, kidney bean, potato), with 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 cultivars tested in NCLAN are representative of crops grown today. 

In general, new crop varieties are not specifically bred for O3 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 O3 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 O3 (U.S. EPA, 2006). For cotton, some newer varieties 

have been found to have higher yield loss due to O3 compared to older varieties (Olszyk et al., 

1993, Grantz and McCool, 1992). In a meta-analysis of 53 studies, Morgan et al. (2003) found 

consistent deleterious effects of O3 exposures on soybean from studies published between 1973 

and 2001. Further, early results from the SoyFACE experiment in Illinois indicate a lack of any 

apparent difference in the O3 tolerance of old and recent cultivars of soybean in a study of 22 

soybean varieties (Long 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 ). 

7-43
Figure 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 O3 exposure 

characterized with the 12-hr W126 statistic using data from 31 crop studies from National Crop Loss Assessment 

Network (NCLAN). Separate 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. 

7-44
7-45 

Figure 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 

Distribution of yield loss predictions from Weibull exposure-response models that relate yield to O3

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 Percentile
7.6.2.3 Considerations for Exposures at Crop Canopy Height 

An important consideration when predicting crop yield and/or tree seedling biomass loss 

using monitored O3 exposure levels is the potential positive 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 planetary boundary layer (U.S. EPA, 

2005b). It is well known that within this layer O3 reacts with vegetation, other surfaces and 

volatile compounds and can create a vertical gradient of decreasing O3 concentration from the 

inlet height of the monitors to the canopies of short vegetation. The magnitude of the gradient is 

determined in large part by the intensity of turbulent mixing in the surface layer. During daytime 

hours, the vertical O3 gradient is relatively small because turbulent mixing maintains the 

downward flux of O3. For example, Horvath et al. (1995) calculated a 7% decrease in O3 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% decrease during stable conditions, which usually occur 

during the night. The average decrease 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 yield 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 vegetation 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 complicated issue. The exchange of O3 between the 

atmosphere and vegetation is controlled by complex interactions of meteorological and 

biological processes. Ideally one should account 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 uncertainty associated with applying a 10% 

adjustment to all monitors and short canopies, staff performed a sensitivity 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 O3 to short vegetation (Henderson, 2006c). For brevity, 

staff has presented the 10% adjusted 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 discussed in this chapter. 

7-46
 The 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 the 3-month 12-hr SUM06 by 53% and an average 

reduction of 42% in the 3-month 12-hr W126. These large reductions in the SUM06 and W126 

exposures are most likely a result of many monitored hourly concentrations occurring near the 

SUM06 threshold and the inflection point for W126 (approximately 0.06 ppm). When these 

“mid-level” hourly O3 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 O3 concentrations below 0.06 ppm [e.g., 

exposures as low as a 0.04 ppm 7-hr seasonal average (U.S. EPA, 2006)]; and 2) the high degree 

of correlation between both forms when describing ambient exposures (see Figure 7-4) and their 

similar predictive power of NCLAN crop data results in retrospective 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 effective in predicting plant response for a given 

change in air quality than the cumulative form used with other crops. Therefore, staff considers 

the fruit and vegetable C-R functions more uncertain than those for commodity crops. Staff 

combined the C-R functions with the crop planting information and with projections of 2001 O3

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 computing W126, 7-hr and 12-hr exposure statistics, 

7-47
 Some of the results of this risk assessment are presented in Appendix 7F in Table 7F-4. 

This table depicts the maximum county-level relative change in crop yield loss under air quality 

scenarios of just meeting various alternative standard options under consideration 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 predicted yield loss for soybean from 2001 using the 

10% adjusted “as is” estimated O3 exposure scenario. Soybean is predicted to have the largest 

yield loss in southwestern Pennsylvania, 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 maximum range of 1-2% with a 10% adjusted O3

exposure (Figure 7-15) and 3-4% without a 10% adjusted O3 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 studied in NCLAN were not sensitive to O3. In contrast, cotton, a 

more sensitive crop, had predicted yield loss above 10% in southern California (see Appendix 

7G, Figures 7G-3 & 4). 

are based on the harvest date and are done on a state-specific basis. This allows for geographic 

variation and better reflects actual O3 exposure during the true growing 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). 

7-48
Figure 7-15. Estimated soybean yield loss based on interpolated 2001 3-month 12-hr W126 with a 10% do

of hourly O3 concentrations. 

7-49
7.6.2.5 Economic Benefits Assessment – AGSIM 

 This section presents results of the quantitative economic benefits analysis associated 

with just meeting alternate standards. Adequate data are currently available to assess economic 

benefits for 9 of the commodity crops studied in the NCLAN project and 6 fruit and vegetable 

species. Fruits and vegetables were evaluated in the 1996 review using a separate regional 

benefits model separate from the national commodity crop model (U.S. EPA 1996b). This was 

due to the fact that only regional planting data were available at the time for those fruits and 

vegetables. In the current benefits assessment, both commodity crops 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 may be especially susceptible to O3 pollution because much of 

the production is located in the San Joaquin Valley region of California, which has very high 

levels of O3 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 separately 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 vegetable crops (California Agricultural Resource Directory, 2005, 

http://www.cdfa.ca.gov/). 

 The Agriculture Simulation Model (AGSIM) (Taylor, 1994; Taylor, 1993) has been 

utilized recently in many major policy evaluations.2

 AGSIM is an econometric-simulation 

model used to calculate agricultural benefits of changes in O3 exposure and is based on a large 

set of statistically estimated demand and supply 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) incorporation of the most recent version of the 

official USDA baseline model, (3) an econometric 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 surplus module. The AGSIM model was run to 

provide benefit estimates for nine major commodity crops (soybeans, corn, winter wheat, cotton, 

peanuts, sorghum, potato, lettuce, kidney bean) and 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. 

7-50
described earlier, hourly O3 exposures were adjusted downward by 10% before calculating the 

W126, 7-hr or 12-hr exposure metrics. 

 Percent relative yield losses (PRYL) calculated as the change in yield occurring between 

just meeting ‘as is’ air quality and various alternative 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-harvested acre, based on 

calculated new yield-per-planted acre 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 surplus, net crop income, deficiency payments and other 

government support payments. Total undiscounted economic surplus was calculated as the crop 

income plus consumer surplus. For more detail on the AGSIM model see Appendix I of the 

Environmental TSD (Abt, 2007). The AGSIM model 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 without the adjustment. 

In summary, this analysis estimated a range of benefits using both the available minimum and 

maximum yield loss equations for each crop. Results are presented in annual 2000 dollars for 

the commodity crops, fruits and vegetables and total agricultural sector. Overall, benefits from 

the fruit and vegetable species in this analysis accounted for a relatively large portion 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 O3 exposures and any rolling 

back of air quality produced greater changes in O3 levels, resulting in higher 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 standard. Including a 10% 

downward adjustment the hourly monitoring did not have a large effect on the overall benefits 

calculated for each standard. Not surprisingly, not adjusting the hourly monitoring data 

downward resulted in slightly higher benefits. Meeting the SUM06 of 25 ppm-hr proposed in 

the last review and the approximate equivalent W126 of 21 ppm-hr produced benefits of 

approximately $140-$260 million for the total agricultural sector. Of all the scenarios, W126 of 

13 ppm-hr, SUM06 of 15 ppm-hr and 8-hr average of 0.07 ppm had the largest economic benefit. 

Meeting the alternative W126 of 13 ppm-hr and approximate equivalent of SUM06 of 15 ppm-hr 

7-51
produced benefits of approximately $290-$630 million for the total agricultural sector. It is 

important to note that these results represent a macro-analysis of the U.S. agricultural economy. 

Farmers in areas that have higher O3 levels are more adversely affected than farmers that are in 

areas with low O3 levels. These important effects are difficult to quantify in a macro-analysis. 

 The current CD reports very few new studies conducted on the economic effect of O3 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). Specifically, Murphy et al. (1999) evaluated benefits to eight major 

crops associated with several scenarios concerning the reduction or elimination of O3 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 O3 exposures from all sources, i.e., ambient O3

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 O3 levels are reduced to near background. These AGSIM results are without any 

downward adjustment to the O3 monitoring data and without subtracting out farm payments. 

With a 10% adjustment and subtracting farm payments, AGSIM calculates substantially lower 

benefits ($200-800 million) for the same 9 major commodity crops. The Murphy et al. (1999) 

analysis and the current AGSIM analysis are quite difficult to compare for many reasons: 

different economic models, different air quality years, different treatment of government farm 

payment programs, dollar value unadjusted for inflation, different assumptions, etc. However, 

these comparisons point out that initial assumptions about O3 exposure and crop payments have 

large implications when calculating agricultural benefits for reducing O3 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 discussed earlier, fruit and vegetable studies were not part of the 

NCLAN program and C-R functions were available only in terms of a seasonal 7-hr or 12-hr 

mean index. This mean index form is considered less effective in predicting 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 the crop risk assessment are chamber effects (see 

section 7.6.2.1) and sensitivity of current crops (see section 7.6.2.2). Staff qualitatively 

addressed these uncertainties citing studies with recent cultivars and studies not using chambers. 

However, it was not possible to perform a quantitative assessment of these uncertainties. 

Therefore, despite support in the scientific literature for the magnitude of yield effects of O3

exposure on crops from OTCs, staff cannot quantify how these uncertainties would affect 

7-52
estimated 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 other stressors. Stressors 

such as drought may decrease the yield response to O3 exposure while insect or disease damage 

to crops may be exacerbated by O3 exposure. 

 An additional source of uncertainty not described or accounted for in the last review is 

that associated with the presence of a decreasing O3 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 factor to represent the maximum gradient believed 

to occur for daylight hours. However, recognizing that the actual downward adjustment value 

varies depending on interactions between numerous plant and site-specific factors, 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 uncertainties associated with the results of the AGSIM 

economic analysis presented in section 7.6.2.5. Uncertainties are introduced by: (1) the 

interpolation of air quality monitoring data to estimate 2001 national O3 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 "just meet" air quality scenarios without a direct 

link to an emissions control strategy; and (4) the inherent uncertainties associated with use of an 

economic model such as AGSIM. It is also important to note that the range of results from this 

analysis represents impacts associated only with 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 crops 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 meeting alternative regulatory scenarios. 

7-53
Table 7-3 A-B. Agricultural model results with (A) and without (B) a 10% adjustment of 

hourly O3 exposures. 

A. 

Average Annual Changes in Total Undiscounted Economic Surplus for the 

Current 8hr Standard (0.08) and Alternative Standards (millions $; 2000) 

Standard Commodity Crops Fruits & Vegetables Total Ag. 

0.08 4th-highest $10 - 20 $60 - 80 $70 - 100 

0.07 4th-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 Undiscounted Economic Surplus for the 

Current 8hr Standard (0.08) and Alternative Standards (millions $; 2000) 

Standard Commodity Crops Fruits & Vegetables Total Ag. 

0.08 4th-highest $10 - 30 $70 - 80 $80 - 110 

0.07 4th-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 

7-54
7.6.3 Tree Risk Assessments 

 In the last review (U.S. EPA, 1996b), analyses of the effects of O3 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 Health and Environmental Effects Research Lab, 

Western Ecology Division (NHEERL-WED). Figure 7-16A uses the regression equations for 

each of the 26 studies (49 cases) to graph predicted 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 since the 1996 review at the AspenFACE site in 

Wisconsin (see section 7.6.2.1) on quaking aspen has confirmed the detrimental effects of O3

exposure on tree growth in a field study without chambers (Karnosky et al., 2005). Since the 

1996 review, only a few new studies have developed 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 O3 FACE-type fumigation (Gregg et al., 2003). Eastern 

cottonwood is a fast growing tree that is important ecologically along streams and commercially 

for pulpwood, manufacturing furniture and a possible source for energy biomass (Burns and 

Hankola, 1990). Gregg et al. (2003) found that the cottonwood saplings grown in urban New 

York City grew faster than saplings grown in more rural areas where O3 was higher. The 

secondary nature of the reactions of O3 formation and NOx titration reactions within the city 

center resulted in significantly higher cumulative O3 exposures in the rural sites. After carefully 

considering many factors, they concluded the major explanation for the difference in growth was 

the gradient of O3 exposure between urban and rural sites. This explanation was also confirmed 

with an OTC study (Gregg et al., 2003). Figure 7-17 shows the biomass growth of cottonwood 

plotted against the monitored 12-hr W126 at the sites the trees were planted (Gregg et al., 2003). 

Staff notes that the responses of natural populations of cottonwood to O3 may vary because of 

precipitation patterns and differences in native soils. The Gregg et al. (2003) study is important 

because it demonstrated that growth effects of O3 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. (2003) provide support for 

the continued use of NHEER-WED OTC studies to estimate 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 O3 effects on vegetation in natural 

settings using visible foliar injury data. Section 7.6.3.3 discusses the analysis and results for 

modeling O3 impacts on mature trees in the Eastern and 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 ecosystem health and services. 

7-55
7-56 

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 Percentile
Figure 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 O3

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 R2 = 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 R2 = 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)

7-57
 Figure 7-18 shows an example of the quaking aspen seedling biomass loss with an hourly 

O3 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. Quaking 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 seedling biomass gain when various standard levels 

are met. These biomass gain maps indicate that substantial improvements in seedling growth 

may be achieved when the alternative standards are met, especially the 0.07 ppm 4th-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 every 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 species (see section 7.6.3.3 for modeling 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 biomass loss per year in a perennial 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 O3 exposure for that year. In summary,

 In a process similar to that used for crops 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 results for selected tree seedling species are found in Appendix 

7H. 

7.6.3.1 Quantifiable Risk of Biomass Loss In Select Tree Seedling Species 

7-58
Figure 7-18. Estimated aspen seedling annual biomass loss based on interpolated 2001 maximum 3-month 

10% downward adjustment of hourly O3 concentrations. This map indicates the geographic ra

aspen (Populus tremoloides), but it does not necessarily indicate that aspen will be found at everrange. 

7-59
 this analysis indicates that current air quality 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 indicators to detect phytotoxic levels of O3 is a 

longstanding and effective methodology (Chappelka and Samuelson, 1998; Manning and Krupa, 

1992). Some well defined bioindicators for ambient O3 include blackberry, black cherry, green 

ash, milkweed, quaking aspen, sassafras, yellow poplar, and white ash. Each of these 

bioindicators exhibits typical O3 injury symptoms when exposed under appropriate conditions. 

These symptoms are considered diagnostic as they have been verified in exposure-response 

studies under experimental conditions. Typical visible injury symptoms on broad leaved plants 

include: 1) acute exposure (pigmented lesions (stippling), flecking, surface bleaching, and/or 

bifacial necrosis); 2) chronic exposure (pigmentation (bronzing), chlorosis or premature 

senescence). Typical visible injury symptoms for conifers include: 1) chlorotic banding or 

tipburn (acute exposure); 2) flecking or chlorotic mottling, premature senescence of needles 

(chronic exposure). Though common patterns of injury develop within a species, these foliar 

lesions can vary considerably between and within taxonomic groups. Furthermore, the degree 

and extent of visible foliar injury development varies from year to year and site to site, even 

among co-members of a population exposed to similar O3 levels, due to the influence of cooccurring environmental and genetic factors. It is important to note that the visible foliar injury 

occurs only when sensitive plants are exposed to elevated O3 concentrations in a predisposing 

environment. Thus, great care must be taken when assessing the response of bioindicators to 

ambient O3 (Flagler, 1998). 

 The Unites States Forest Service (USFS) through the Forest Health Monitoring Program 

(FHM) (1990 - 2001) and currently the Forest Inventory and Analysis (FIA) Program has been 

collecting data regarding the incidence and severity of visible foliar injury on a variety of O3

sensitive plant species throughout the U.S. (Coulston et al., 2003, 2004; Smith et al., 2003). The 

plots where these data are taken are known as biosites. 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 continued to expand. The visible 

foliar injury indicator has been identified as a means to track O3 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/indicators/roe). EPA staff also considers it 

important to assess the degree to which O3-induced visible foliar injury observed in situ, 

7-60
 In an attempt to assess how meeting various O3 standard levels affected the incidence of 

visible foliar injury, staff matched up county-level O3 monitoring data with counties that had US 

Forest Service biosites. In counties containing multiple O3 monitors, staff used the monitor 

measuring the highest O3 to characterize county air quality. Because visible foliar injury 

symptoms reflect the O3 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 visible foliar injury data were available 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 O3 injury was reported at any site in that region. Figure 7-19, shows that the incidence of 

visible foliar injury in 2001 was widespread across the eastern and western U.S. The 2001 data 

are indicative of the incidence of visible foliar injury in the years 2001 to 2004. (see Appendix 

7I for 2002). This indicates that O3 levels are above phytotoxic levels sufficient to cause adverse 

effects in natural plant populations in many areas. It is important to note that direct links 

between O3 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 vegetative 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 O3 in 

ambient air it is not always a reliable indicator of damage or other injury endpoints. The lack of 

visible injury does not indicate a lack of phytotoxic concentrations of O3 or a lack of non-visible 

O3 effects. 

 The major confounding effect for O3 induced visible foliar injury 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 moisture decreases stomatal conductance of plants and, 

therefore, limits the amount of O3 entering the leaf that can cause injury. Many researchers have 

shown that dry periods in local areas tend to decrease the incidence and severity of visible foliar 

injury caused by O3 in plants measured by the USFS (Smith et al., 2002). Therefore, the 

incidence of visible foliar injury is not always higher in years with higher O3, especially when 

there is drought in areas where visible foliar injury is assessed. 

corresponds with monitored O3 air quality in recent years. In a collaborative effort with FIA 

staff, EPA staff conducted an analysis to compare the incidence of visible foliar injury at 

different levels of air quality (e.g., the current 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. 

7-61
Figure 7-19. 2001 County-level incidence of visible foliar injury in the eastern and western U.S. as measur

Service FIA program. 

7-62
 In summary, this analysis indicates that incidence of O3 induced visible foliar injury is 

widespread across the eastern and western U.S. Visible foliar injury was observed in counties 

that are meeting the current level of the 8-hr standard and an alternative secondary standard 

option of a SUM06 of 25 ppm-hr proposed in 1996. Lower standards in the 8-hr average and 

SUM06 forms would be expected to have lower incidences of visible foliar injury. However, the 

level of protection would depend heavily on local environmental variable such as soil moisture. 

Finally, in the consensus workshop held on the secondary O3 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 natural 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 O3 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 different 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 the number of biosites in 2003 and 2004, the total 

number of counties containing both an O3 monitor and an FIA biosite changed each year and it is 

difficult to interpret changes in the number of counties in different categories between years. 

Therefore, staff found it more informative to present results in terms of percent of total counties 

with or without injury under different levels of air quality. First, this table illustrates that visible 

foliar injury is occurring in areas that are meeting the current 8-hr average O3 standard (0.084 

ppm). Second, the table illustrates that the secondary standard option of a SUM06 of 25 ppm-hr 

proposed in 1996 did not appear to offer more protection from visible foliar injury than the 

current 8-hr average standard form. By comparison, the SUM06 of 15 ppm-hr and the 8-hr 

average of 0.074 ppm provided more protection across 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 average, 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 two 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 data. Between 235 and 286 counties had EPA O3

monitoring and at least one USFS FIA biosite surveyed for visible foliar injury in the years 2001 

– 2004 (see Table 7-4). However, because the specific locations of the USFS biosite are not 

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Table 7-4. Percentage and number of counties with visible foliar injury (injured) and without injury (not 

various standard levels for the years 2001-2004. Each county had an O monitor and a USDA fplot tracking visible foliar injury due to O exposur

3

3 e. 

Year 

<0.084* 

(ppm) 

<0.074* 

(ppm) 

<SUM06 25 

(ppm-hr) 

<SUM06 15 

(ppm-hr) 

Total Counties with 

O3 monitoring & FIA 

biosites

# of counties 99 36 134 48 

2001 injured 39% (39) 25% (9) 49% (65) 23% (11) 

not injured 61% (60) 75% (27) 51% (69) 77% (37) 

235 

# of counties 89 43 129 59 

2002 injured 21% (19) 12% (5) 26% (33) 12% (7) 

not injured 79% (70) 88% (38) 74% (96) 88% (52) 

270 

# of counties 185 61 236 135 

2003 injured 28% (52) 11% (7) 34% (81) 25% (34) 

not injured 72% (133) 89% (54) 66% (155) 75% (101) 

285 

# of counties 260 159 249 220 

2004 injured 35% (91) 30% (47) 37% (91) 35% (76) 

not injured 65% (169) 70% (112) 63% (158) 65% (144) 

286 

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*These standard levels represent the annual 4th-highest 8-hr maximum average 
 Staff 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 the growth of yellow poplar (Liriodendron tulipifera) and red maple 

(Acer rubrum) in the Appalachian mountains of Virginia and North Carolina, Shenandoah 

National Park (Big Meadows) and Linville Gorge Wilderness Area (Cranberry), respectively. 

Total tree growth associated with ‘as is’ air quality, and air quality adjusted to just meet 

alternative O3 standards was assessed (Table 7-5). Ponderosa 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 O3 scenarios and linked with 

concurrent climate data to account for O3 and climate/meteorology interactions on several 

species of trees in different regions 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 O3

exposure and response. The interactions between O3 exposure, precipitation and temperature are 

integrated as they affect vegetation, thus providing an internal consistency for comparing effects 

in trees under different exposure scenarios and climatic conditions (see the Environmental 

Assessment TSD for more details on TREGRO). An earlier assessment of the effectiveness of 

national ambient air quality standards in place since the early 1970s took advantage of 40 years 

of air quality and climate data for the Crestline site in the San Bernardino Mountains of 

California to simulate Ponderosa pine growth over time with the improving air quality using 

TREGRO (Tingey et al., 2004). 

In the 1996 O3 Staff Paper, evaluations of O3 impacts on tree growth were limited to the 

seedling growth stage (U.S. EPA, 1996b). At that 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 O3 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 growth under elevated O3 in trees beyond the seedling stage (King et al., 

2005). In order to better characterize the potential O3 effects on mature tree growth, staff used a 

tree growth model (TREGRO) as a tool to evaluate the effect of changing O3 air quality 

scenarios from just meeting alternative O3 standards on the growth of mature trees. 

7.6.3.3 Modeled Mature Tree Growth Response: Eastern and Western Species 

Case Studies 

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1A rollback was not necessary for the Cranberry site for the 0.08 ppm 4th-highest and SUM06 = 25 ppm-hr scena

was at or below the levels of those scenarios. 

Table 7-5. Relative increase in total annual tree biomass growth, simulated with the TREGRO model, if th

current (0.08 ppm) and alternative standards are met. 

3The roll-back to a SUM06 of 25 ppm-hr was a W126 of approximately 18 ppm-hr at Cranberry, Big Meadows aSpecies red maple red maple yellow poplar yellow poplar ponderosa pine Site Big Meadows, VA

(1993-1995) 

Cranberry, NC (1993-1995) 

Big Meadows, VA (1993-1995) 

Cranberry, NC (1993-1995) 

Crestline, CA (1995-2000) 

0.08 4th-highest 0.41% no rollback1 0.03% no rollback1 8.63% 0.07 1st-highest 2.71% 2.31% 0.38% 6.54% 10.81% 0.07 4th-highest 2.24% 1.38% 0.34% 3.91% n.a. 2SUM06 = 253 0.34% no rollback1 0.07% no rollback1 10.33% SUM06 = 154 4.49% 2.99% 0.60% 8.26% n.a. 24The roll-back to a SUM06 of 15 ppm-hr was a W126 of approximately 13 ppm-hr at Cranberry and Big Meadow

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2 TREGRO 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 important for its brilliant fall foliage and highly 

desirable wildlife browse food (Burns and Honkala, 1990). Yellow poplar is an abundant species 

in the southern Appalachian forest. It is 10% of the cove hardwood 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 trees 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 and 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 Cranberry, NC air quality and climate data from the years 1993 to 

1995. These three years were the only years in the east with readily available O3 and climate 

data that could be used in TREGRO. The years chosen to run the TREGRO at each site appear 

to have annual O3 exposures typical of the last 15 years (Figure 7-20). Air quality from each site 

and year was adjusted using the 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 1st highest max 

average of 0.07 ppm. Staff also tested the 4th-highest 0.07 ppm level on the Cranberry and Big 

Meadows sites. For the ponderosa pine at Crestline, TREGRO was run for “as is” and “just 

meet” air quality conditions in four 3 year increments to increase the accountability of climate 

variability and the annual average biomass determined from these 4 simulations to yield an 

annual average biomass change over the 6 years of O3 exposure. For the yellow poplar and red 

maple, two sites (Big Meadows, VA and Cranberry, 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 meet” and “as is” air quality conditions were 

compared to evaluate the effectiveness of the current secondary standard and alternative 

standards in protecting these three tree species. 

 Results of the TREGRO simulations are presented in Table 7-5. Clearly, the greatest 

simulated growth benefits in the scenarios are seen in ponderosa pine at the Crestline site in 

California. As shown in Figure 7-20, O3 levels are much higher at Crestline than the sites in the 

eastern US. Meeting the level of the current standard was simulated to result in an 8.63% 

increase annual growth and a SUM06 of 25 ppm-hr is expected increase growth 10.33% in 

ponderosa pine. In the eastern sites (Cranberry and Big Meadows), O3 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 average standard and the 

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Figure 7-20. Historical O3 data as measured in the 3-month 12-hr SUM06 and 4th highest 

8-hr metrics for the 3 sites used to run the TREGRO model. For Big Meadows, 

VA and Cranberry, NC, climate and O3 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 2004

4th 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

*

* *

*

*

*

*

*

*

*

* *

*

*

*

*

*

*

*

*

*

* * *

7-68
SUM06 of 25 ppm-hr scenarios and, therefore, no benefits were calculated for those levels. At 

Big Meadows, VA, the current 8-hr average standard 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 close to meeting those levels in 1993-1995 (Figure 7-

20). Red maple was simulated to have a similar response (~2%) to the 0.07 ppm 1st and 4thhighest 8-hr max in Big Meadows and Cranberry. For the same scenarios, yellow poplar had a 

very different response to O3 reduction at Big Meadows (0.34-0.38%) 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 O3 and that, conversely, it would respond much more to O3 reductions. Red 

maple has a much larger geographical 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 O3 on an individual tree may be quite different than the predicted effect on a 

forest stand after many years. Some researchers have used the ZELIG model, a forest stand 

simulator, to predict stand growth using growth rates of individual 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 O3 effect on an individual ponderosa pine at Crestline to reduce growth by 6.7% in 

three years under normal precipitation, yet stand basal area was calculated to be reduced by 29% 

after 100 years. Similarly, Laurence et al. (2001) found individual yellow poplar in NC with an 

O3 induced growth loss of 1.7% which was then calculated to reduce basal area by 14% after 100 

years. This suggests that small effects on individual tree growth may result 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 uncertainties 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 canopies and actual exposure at the top of the 

canopy is an important uncertainty. As explained 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 

7-69
calculations provide a bracket of responses within which the reality probably lies for the actual 

O3 exposures tree seedling canopies. 

 The visible foliar injury risk assessment contains 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 incidence and degree of visible foliar injury is not always 

higher in years with higher O3, especially when there is drought in areas where foliar injury is 

assessed. Second, the lack of visible injury does not indicate a lack of phytotoxic concentrations 

of O3 or a lack of non-visible O3-induced effects, since it is not always a reliable indicator of 

other O3-related injury and damage endpoints. Finally, due to the change in FIA protocols in 

2002 and the unavailability of specific biosite locations, staff was unable to determine the degree 

to which county level monitored O3 values reflect the actual O3 exposure conditions at the 

biosites within those counties. 

As with every model, TREGRO has many known and unknown sources of uncertainty. 

Because TREGRO only models individual trees, the effects of competition are not factored in. 

There is genetic variability within species so that 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 number of species tested and included in this 

assessment, it is unclear to what degree these results apply to O3 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 assemblages of organisms that provide distinct 

ecological attributes, many of which may be adversely affected by O3 (U.S. EPA, 2006). A new 

effort has been initiated within the Agency to identify indicators 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 environmental 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 United States (NRC, 2004) 

stated that “EPA’s current practice for setting secondary standards for most criteria pollutants 

does not appear to be sufficiently protective of sensitive crops and ecosystems...” This report 

made several specific recommendations for improving the secondary NAAQS process and 

concluded that “There is growing evidence that tighter standards to protect sensitive ecosystems 

in the United States are needed...” However, the vast majority of information regarding the 

effects of O3 involves the sensitivity of individual species. Therefore, this section lays out some 

7-70
examples of our current understanding of how O3 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 leads to a clearly defined trophic 

structure, biotic diversity, and cycling of materials between living and nonliving parts (Odum, 

1963). Individuals within a species and populations 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, are distinguished by their dominant vegetation 

forms. Ecosystem boundaries are delineated when an integral unit is formed by their physical 

and biological parts. Defined pathways for material 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; and maintenance of food chains. 

The sum of the functions carried out by ecosystem components provides many benefits to 

humankind, as in the case of forest ecosystems (Smith, 1992). Some of these benefits include 

food, fiber production, aesthetics, genetic diversity, and energy exchange. 

 A conceptual framework for discussing the effects of O3 on ecosystems was developed 

by the EPA Science Advisory Board (Young and Sanzone, 2002). Their six essential ecological 

attributes (EEAs) include landscape condition, biotic condition, organism condition, ecological 

processes, hydrological and geomorphological processes, and natural disturbance regimes. 

Figure 7-21 outlines how common anthropogenic stressors, including tropospheric O3, might 

affect the essential ecological attributes outlined by the SAB. 

 There is evidence that tropospheric O3 is an important stressor 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 O3 exposure to individual plants and processes that are scaled up through the ecosystem 

affecting processes such as energy and material flow, inter- and intraspecies competition, and net 

primary productivity (NPP). Thus, effects on individual 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, O3 may even impact the occurrence and 

impact of natural disturbance (e.g., fire, erosion). 

 Another approach to assessing O3 effects on ecosystems is the identification and use of 

indicators. For example, the main indicators of phytotoxic O3 exposures used for forest 

ecosystems are visible foliar injury (as described in section 7.6.3.2 above) and radial growth of 

7-71
Figure 7-21. Common anthropogenic stressors and the essential ecological attributes they 

affect. Modified from Young and Sanzone (2002) 

7-72
trees. Systematic injury surveys demonstrate that foliar injury occurs on O3-sensitive species in 

many regions of the United States. However, there is not always a direct relationship between 

the severity of the visible foliar symptoms and growth. 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 relationship between changes in radial growth of mature 

trees and ambient O3, in combination with data from many controlled studies with seedlings, 

suggest that ambient O3 is reducing the growth of mature trees in some locations. However, 

definitively attributing growth losses in the field to O3 in a wide array of ecosystems is often 

difficult because of confounding factors with other pollutants, climate, insect damage and 

disease. 

 The CD (U.S. EPA, 2006) outlines seven case studies where O3 effects on ecosystems 

have either been documented or are suspected. However, in most cases, only a few components 

in each of these ecosystems have been examined and characterized for O3 effects and, therefore, 

the full extent of ecosystem changes in these example ecosystems is not fully understood. 

Clearly, there is a need for highly integrated ecosystem studies that specifically investigate the 

effect of O3 on ecosystem structure and function in order to fully determine the extent to which 

O3 is altering ecosystem services. 

7.7.1 Evidence of Potential Ozone Alteration of Ecosystem Structure and 

Function 

The seven case studies listed in the 2006 CD demonstrate the potential for O3 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, O3 appeared to be a 

predisposing factor leading to increased drought stress, windthrow, root diseases, and insect 

infestation (Takemoto et al., 2001). Increased mortality of susceptible tree species, including 

ponderosa and Jeffrey pine, resulting from these combined stresses has shifted community 

composition towards white fir and incense cedar and has altered forest stand structure (Miller et 

al., 1989). A shift of community composition towards white fir may make this ecosystem more 

susceptible to fire. Although the role of O3 was extremely difficult to separate from other 

confounding factors, such as high N deposition, there is evidence that this shift in species 

composition has altered trophic structure and food 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 O3 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, 

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1992c). Elevated O3 significantly decreased the growth of sensitive populations of common 

plantain (Pearson et al., 1996; Reiling and Davison, 1992a, b; Whitfield et al., 1997) and reduced 

fitness as determined by decreased reproductive success (Pearson et al., 1996; Reiling and 

Davison, 1992a). While spatial comparisons of population responses to O3 are complicated by 

other environmental factors, rapid changes in O3 resistance were imposed by ambient levels and 

variations in O3 exposure (Davison and Reiling, 1995). At the site of plantain seed collection, 

the highest correlations occurred between O3 resistance and ambient O3 concentrations (Lyons et 

al., 1997). In this case study, it appeared that O3-sensitive individuals are being removed by O3

stress and the genetic variation represented in the population could be declining. If genetic 

diversity and variation is lost in ecosystems, there may be increased vulnerability of the system 

to other biotic and abiotic stressors, and ultimately a change in the services provided by those 

ecosystems. 

 Reconstructed ecosystems in artificial exposure experiments have also provided new 

insight into how O3 may be altering ecosystem structure and function (Karnosky et al., 2005). 

For example, the Aspen Free-Air CO2 Enrichment facility was designed to examine the effects of 

both elevated CO2 and O3 on aspen (Populus tremuloides), birch (Betula papyrifera), and sugar 

maple (Acer saccharum) in a simple reconstructed plantation 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 growth and physiological processes have cascaded 

through the ecosystem, even affecting microbial communities (Larson et al., 2002; Phillips et al., 

2002). This study also confirmed earlier observations of O3-induced changes in trophic 

interactions involving keystone tree species, as well as important insect pests and their natural 

enemies (Awmack et al., 2004; Holton et al., 2003; Percy et al., 2002). 

 Collectively these examples suggest that O3 is an important stressor in natural 

ecosystems, but it is difficult to quantify the contribution of O3 due to the combination of stresses 

present in ecosystems. Continued research, employing new approaches, will be necessary to 

fully understand the extent to which O3 is affecting ecosystem services. 

7.7.2 Effects on Ecosystem Services and Carbon Sequestration 

 Since it has been established that O3 affects photosynthesis and growth of plants, O3 is 

most likely affecting the productivity 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 because 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 O3. 

7-74
 Terrestrial ecosystems are important in the Earth's carbon (C) balance and could help 

offset emissions of CO2 by humans if anthropogenic C is sequestered in vegetation and soils. 

The annual increase in atmospheric CO2 is less than the total inputs from fossil fuel burning and 

land use changes (Prentice et al., 2001) and much of this discrepancy is thought to be attributable 

to CO2 uptake by plant photosynthesis (Tans & White, 1998). Temperate forests of the northern 

hemisphere have been estimated to be a net sink of 0.6 to 0.7 Pg of C per year (Goodale et al. 

2002). Ozone interferes with photosynthesis, causes some plants to senesce leaves prematurely 

and in some cases, reduces allocation to stem and root tissue. Thus, O3 decreases the potential 

for C sequestration. For the purposes of this discussion, 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, Felzer et al. (2004), estimated that U.S. net 

primary production (net flux of C into an ecosystem) was decreased by 2.6-6.8% due to O3

pollution in the late 1980's to early 1990's. Ozone not only reduces C sequestration in existing 

forests, it can also affect reforestation projects (Beedlow et al. 2004). This effect, in turn, has 

been found to ultimately inhibit C sequestration in forest soils which act as long-term C storage 

(Loya et al., 2003; Beedlow et al. 2004). The interaction of rising O3 pollution and rising CO2

concentrations in the coming decades complicates predictions of future sequestration potential. 

Models generally predict that, in the future, C sequestration will increase with increasing CO2, 

but often do not account for the decrease in productivity due to the local effects of tropospheric 

O3. In the presence of high O3 levels, the stimulatory effect of rising CO2 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 O3 standards would increase the 

amount of CO2 uptake by many ecosystems in the U.S. However, the amount of this 

improvement would be heavily dependent on the species composition of those ecosystems. 

Many ecosystems in the U.S. do have O3 sensitive plants. For, example forest ecosystems with 

dominant species such as aspen or ponderosa pine would be expected to increase CO2 uptake 

more with lower O3 than forests with more O3 tolerant species. 

7-75
REFERENCES 

Abt Associates, Inc. (1995). Ozone NAAQS benefits analysis: California crops. Report to U.S. EPA, July. 

Abt Associates Inc. (2007). Technical Report on Ozone Exposure, Risk, and Impacts Assessments for Vegetation: 

Final Report. Prepared for Office of Air Quality Planning 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, carbohydrates and growth of red spruce 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. Steyn, 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 North 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 allocation below ground in plants exposed to ozone. New 

Phytol. 157: 213-228. 

Appel, K.W.; A. Gilliland; B. Eder (2005) An Operational 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) Diagnostic 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. 

7-76
Ashmore, 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 O3. Global Change Biol. 10: 1414-1423. 

Ball, G. R.; Benton, J.; Palmer-Brown, D.; Fuhrer, J.; Skärby, 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 conductivity 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.; Brunschon-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) Combined 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-grown soybean to elevated CO2 and O3. Crop Sci. 45: 883-895. 

Burkey, K. O. (1999) Effects of ozone on apoplast/cytoplasm 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 Algorithms 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.; Rochefort, R.; Andersen, C. (2000) Monitoring for ozone injury in west coast 

(Oregon, Washington, California) forests in 1998. Portland, OR: U.S. Department of Agriculture, Forest 

Service, Pacific Northwest Research Station; general technical report no. PNW-GTR-495. Available: 

http://www.fs.fed.us/pnw/gtrs.htm [11 April, 2003]. 

Castillo, F. J.; Heath, R. L. (1990) CA2+ 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. 

7-77
CEPA. (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 ozone 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.; Stenchikov, 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 CO2 and O3 enrichment (FACE) project in an overview. USDA 

Forest Service North Central Research Station. General Tech. Rep. NC-214. 68pp. 

Dominy, P. J.; Heath, R. L. (1985) Inhibition of the K+-stimulated ATpase of the plasmalemma of pinto bean leaves 

by ozone. Plant Physiol. 77: 43-45. 

Eder, B. and S. Yu, 2005: A performance 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. Atmospheric 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. 

7-78
Emberson, 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 mechanism 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 O3 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 Standards 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 CO2 reduces O3 flux and O3-induced yield 

losses in soybeans: possible implications for elevated CO2 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 CO2. 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 and spatial interpolation by Bayesian combination of 

observations with outputs from numerical models. Biometrics, 61, 36-45.

Fuentes, J. D.; Hayden, B. P.; Garstang, M.; Lerdau, M.; Fitzjarrald, D.; Baldocchi, 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) Transpiration and leaf temperature. Annu. Rev. Plant Physiol. 19: 211-238. 

7-79
Goodale, 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. and 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 1992 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 allometry 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 uncertainties 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 O3 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 O3 exposure metrics. Tree Physiol. 24: 1001-1010. 

Grulke, N. E.; Preisler, H. K.; Rose, C.; Kirsch, J.; Balduman, L. (2002) O3 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, Federal 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-top field chamber to assess the impact of air pollution on 

plants. J. Environ. Qual. 2: 365-368. 

Heagle, A. S.; Letchworth, M. B.; Mitchell, C. A. (1983) Effects of growth medium 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. Heggestad (1988) “Factors influencing ozone 

dose-yield response relationships in open-top field chamber studies.” In: W.W. Heck, O.C. Taylor, D.T. 

7-80
Tingey eds. Assessment of crop loss from air pollutants: 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 clover to ozone in different environments. J. 

Environ. Qual. 25: 273-278. 

Heagle, A. S.; Miller, J. E.; Pursley, W. A. (1998) Influence of ozone stress 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 mechanisms 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 Environment: 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 forests 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, O3, and plant genotype. Oecologia 137: 233-244. 

Horst, R.; Duff, M. (1995). Concentration 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 performance. 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. (1997) “Environmental auditing: 

an approach for characterizing tropospheric ozone risk to forests.” Environ. Manage. 21: 105-120 

Hogsett, W. E.; Tingey, D. T.; Hendricks, C.; Rossi, D. (1989) Sensitivity of western conifers to SO2 and seasonal 

interaction of acid fog and ozone. In: Olson, R. K.; Lefohn, 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). 

7-81
Horváth, L.; Nagy, Z.; Weidinger, T.; Artz, R.; Luke, W. T.; Valigura, R.; Pinto, J. P.; Womack, J. (1995) 

Measurement of fluxes of trace gases (O3, NOx, SO2, CO2, HNO3), 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 perspectives about scaling ozone impacts in trees. Environ. Pollut. 

115: 373-393. 

Karnosky, D.F., B. Mankovska, K. Percy, 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 O3 on trembling 

aspen and interaction with CO2: Results from an O3-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.; Lindroth, R. L.; Mattson, W. J.; 

McDonald, E. P. (2003) Tropospheric O3 moderates responses of temperate 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 the 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. 

7-82
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. 

Kraft, M.; Weigel, H. J.; Mejer, G. J.; Brandes, F. (1996) Reflectance measurements 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 (O3) 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 intercellular air spaces is close to zero. Plant 

Physiol. 90: 1163-1167. 

Lamb, C.; Dixon, R. A. (1997) The oxidative burst in plant 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) Extracellular 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.; Weinstein, 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) Interpolation of temperature and non-urban ozone exposure at high spatial 

resolution over the western United States. 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 Quality Planning and Standards, Air Quality Strategies 

and Standards Division, U.S. Environmental Protection 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 estimating agricultural losses. Corvallis, OR: U.S. 

Environmental Protection Agency, Environmental Research Laboratory; EPA report no. 

EPA-600/3-89-047. Available from: NTIS, Springfield, VA; PB89-195036. 

7-83
Lefohn, A. S.; Laurence, J. A.; Kohut, R. J. (1988) A comparison 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., Hollis, K., Mies, T., Morgan, P., Naidu, S., Ort, D.R., Webster, R., Zhu, X. 

Adapting Soybean To Current 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/research/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 accumulation 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 effects 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 O3, SO2, and elevated O2. J. Exp. Bot. 38: 842-852. 

Matyssek, R.; Gunthardt-Goerg, M. S.; Maurer, S.; Keller, T. (1995) Nighttime 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. 

7-84
McLaughlin, S. B.; McConathy. (1983) Effects of SO2 and O3 on alocation of 14C-labeled photosynthate in 

Phaseolus vulgaris. Plant Physiol. 73: 630-635. 

Mehlhorn, H.; O'Shea, J. M.; Wellburn, A. R. (1991) Atmospheric 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. Physiol. Plant. 104: 617-622. 

Moldau, H.; Bichele, I. (2002) Plasmalemma protection by the apoplast as assessed from above zero ozone 

concentration in leaf intercellular 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 open-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.; Dickson, 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 O3. 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/gpra/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/ 

7-85
Odum, 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) Interactive 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.; Langebartels, 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 simulation 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 Sierra 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.; Arteca, R. N. (1997) Ozone-induced oxidative 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.; Isebrands, 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 O3. Nature (London) 420: 

403-407. 

Peterson, D. L.; Arbaugh, M. J.; Wakefield, V. A.; Miller, P. R. (1987) Evidence of growth 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 atmospheric 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 pathogens 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. 

7-86
Pitelka, 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 and Atmospheric Carbon Dioxide. In 

Climate Change 2001: The Scientific Basis. Contribution 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 regulate 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) Effects of elevated [CO2] and/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 O3 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 acting 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. 

7-87
Schraudner, M.; Moeder, W.; Wiese, C.; Van Camp, W.; Inze, D.; Langebartels, 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.; Comrie, 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 processes. 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 sucrose 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 evaluation of the aggregate economic effects of price support 

programs” Agricultural Systems 44: 461-473. 

Taylor, C.R. “AGSIM: Model Description and Documentation.” 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 gaseous 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.; Hogsett, 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) Gas 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. 

7-88
Urban, 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 Technical Information - OAQPS Staff Paper. EPA/452/R-96-007. Office of 

Air Quality Planning and Standards, 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 Air 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 Ozone Report: Measuring Progress through 2003. EPA/454/K04-001. Office of Air Quality Planning and 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 Standards, Research Triangle Park, NC. March. Available 

electronically on the internet at http://www.epa.gov/ttn/naaqs/standards/ozone/s_O3_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 Planning 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.; Kangasjarvi, 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. 

7-89
Weber, J. A.; Clark, C. S.; Hogsett, W. E. (1993) Analysis of the relationship(s) among O3 uptake, conductance, and 

photosynthesis in needles of Pinus ponderosa. Tree Physiol. 13: 157-172. 

Weinstein, D.A., Beloin, R.M., R.D. Yanai (1991). “Modeling changes in red spruce carbon 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 nitrogen 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 responses to elevational gradients of O3 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) Consequences 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 responses to elevational gradients of O3 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 SAB 

report. Washington, DC: U.S. Environmental Protection Agency, Science Advisory Board; report no. EPASAB-EPEC-02-009. Available: http://www.epa.gov/sab/pdf/epec02009.pdf [9 December, 2003]. 

7-90
 8-1

8. STAFF CONCLUSIONS AND RECOMMENDATIONS ON THE 

SECONDARY O3 NAAQS 

8.1 INTRODUCTION 

 This chapter presents staff conclusions and recommendations regarding an appropriate 

range of options for the Administrator to consider in selecting a pollutant indicator, averaging 

time, form, and level for the secondary O3 standard. In so doing, this chapter describes the 

results and conclusions of staff assessments of scientific evidence presented in the CD and of air 

quality, exposure, and risk analyses presented in Chapters 2 and 7 herein. 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 for the Administrator’s consideration, we note that the final 

decision on retaining or revising the current secondary O3 standard is largely a public welfare 

policy judgment. A final decision should draw upon scientific information and analyses about 

welfare effects, exposure and risks, as well as judgments about the appropriate response to the 

range of uncertainties that are inherent in the scientific evidence and analyses. Our approach to 

informing these judgments, discussed more fully below, is consistent with the requirements 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 secondary standards that, in the 

Administrator’s judgment, are requisite to protect public welfare from any known or anticipated 

adverse environmental effect. In so doing, the Administrator seeks to establish standards that are 

neither more nor less stringent than 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 

O3 concentrations typically occurring in the U.S. Further, by adversely affecting natural 

vegetation and commercial crops, O3 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, for 
 8-2

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 secondary standard is adequate or whether 

consideration of revisions is appropriate, we adopted an approach in this review that builds upon 

the general approach used in the last review and reflects the broader body of evidence now 

available. In developing conclusions and recommendations for the Administrator to consider in 

this review, staff presents effects-, exposure- and risk-based considerations. We have expanded 

and modified the exposure and risk assessments to reflect the availability of new tools, 

assessment methods, and a larger and more diverse 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 mature forest tree species and commodity, fruit, 

vegetable and forage crop species), and includes assessments of air quality, exposures, and 

qualitative and quantitative risks associated with alternative air quality scenarios. 

 With respect to vegetation effects information, 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 effects endpoints. We 

place greater weight on U.S. studies due to the often species-, site-, and climate-specific nature 

of O3-related vegetation response. With respect to quantitative exposure- and risk-based 

considerations, we have relied on both monitored and interpolated O3 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 consideration. These scenarios include current “as 

is” air quality (2001), as well as six “just meet” scenarios for which interpolated O3 air quality is 

adjusted using a rollback method to simulate just meeting a range of alternative standards. 

Uncertainties associated with the exposure and 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 considers these estimates. With regard 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 options for consideration by the 

Administrator regarding the current secondary O3 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 information reinforce or call into question 

evidence of associations with effects identified in the last review? 
 8-3

• To what extent does newly available information reinforce or call into question any of 

the basic elements of the current standards? 

• To what extent have important uncertainties identified in the last review been reduced 

and have new uncertainties emerged? 

To the extent that the available information suggests that revision of the current standards may 

be appropriate to consider, we explore whether the currently available information supports 

consideration of a standard that is either more or less protective by addressing the following 

questions: 

• Is there evidence that vegetation effects extend to ambient O3 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 consideration of revised standards, we then identify a range 

of alternative standards (in terms of an indicator for photochemical oxidants, averaging time, 

level, and form in sections 8.3.2 through 8.3.5 below, respectively) that staff feels are appropriate 

for the Administrator to consider and that reflect staff conclusions and recommendations on the 

science, taking into account other public welfare policy considerations. In so doing, staff 

addresses the following questions: 

• Does the evidence provide support for considering a different O3 indicator? 

• Does the evidence provide support for considering different averaging times? 

• What ranges of levels and forms of alternative standards are supported by the evidence, 

and what are the uncertainties and limitations in that evidence? 

• To what extent do specific levels and forms of alternative standards reduce the 

estimated exposures of concern and risks attributable to O3 and other photochemical 

oxidants, and what are the uncertainties in the estimated exposure and risk reductions? 

 A summary of staff conclusions and recommendations regarding a range of policy 

options identified for the Administrator’s consideration, as well as key CASAC and public 

commenter views concerning whether, and if so how, to revise the current secondary O3 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 O3 

NAAQS in section 8.4.

 
 8-4

8.3 SECONDARY O3 STANDARD 

 The current secondary standard is a 3-year average of the annual 4th-highest maximum 8-

hr average set at a level of 0.08 ppm. This standard was selected to provide protection to the 

public welfare, especially agricultural crops and other at-risk sensitive plant species, against a 

wide range of O3-induced effects. As an introduction to our discussion in this section of the 

adequacy of the current O3 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), the Administrator proposed to replace the 

then existing 1-hr O3 secondary NAAQS with one of two alternative new standards: a standard 

identical to the proposed 0.08 ppm, 8-hr primary standard (described above), or alternatively, a 

new seasonal standard expressed as a sum of hourly concentrations greater than or equal to 0.06 

ppm, cumulated over 12 hours per day during the maximum 3-month period during the O3 

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 proposal was based on a thorough review of the latest 

scientific information available and described in the 1996 O3 CD, as well as (1) staff assessments 

of the policy-relevant information in the 1996 O3 CD presented in the 1996 O3 Staff Paper 

including air quality, vegetation exposure and risk, and economic values; (2) consideration of the 

degree of protection to vegetation potentially afforded by the proposed 0.08 ppm, 8-hr primary 

standard; (3) CASAC advice and recommendations; and (4) public comments. 

 In the final rule for the O3 NAAQS published in July 1997 (62 FR 38877), the 

Administrator decided to replace the then current 1-hr, 0.12-ppm secondary NAAQS with a 

standard that was identical in every way to the new revised primary standard of an 0.08 ppm 

annual 4th-highest maximum 8-hr average standard averaged over 3 years. Her decision was 

based on her judgment that: (1) the then existing secondary standard did not provide adequate 

protection for vegetation against the adverse welfare effects of O3; (2) reflected CASAC advice 

“that a secondary NAAQS, more stringent than the present primary standard, was necessary to 

protect vegetation from O3” (Wolff, 1996); (3) the new 8-hr average standard would provide 

substantially improved protection for vegetation from O3-related adverse effects as compared to 

the level of protection provided by the then current 1-hr, 0.12-ppm secondary standard; (4) 

significant uncertainties remained with respect to exposure dynamics, air quality relationships, 

and the exposure, risk, and monetized valuation analyses presented in the proposal, resulting in 

only rough estimates of the increased public welfare likely to be afforded by each of the 

proposed alternative standards; (5) there was value in allowing more time to obtain additional 

information to better characterize O3-related vegetation effects under field conditions from 

additional research and to develop a more complete rural monitoring network and air quality 
 8-5

database from which to evaluate the elements of an appropriate seasonal secondary standard; and 

(6) there was value in allowing more time to evaluate more specifically the improvement in rural 

air quality and in O3–related vegetation effects resulting from 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 O3 on vegetation under field conditions and on better characterizing the relationship 

between O3 exposure dynamics and plant response would be important in the next review 

because: 

• The available biological database highlighted the importance of cumulative, seasonal 

exposures as a primary determinant of plant responses. 

• The association between daily maximum 8-hr O3 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 characterized with confidence due to limited 

monitoring data and air quality modeling in rural and remote areas. 

8.3.1 Adequacy of Current O3 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 concludes that: (1) a plant’s response to O3 depends upon 

the cumulative nature of ambient exposure (e.g., concentration times duration) as well as the 

temporal dynamics of those concentrations; (2) current ambient concentrations 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 O3 into the leaf through the stomata is the critical step 

in O3 effects; (4) effects can occur with only a few hourly concentrations above 80 ppb; (5) other 

environmental biotic and abiotic factors are also influential to the overall impact of O3 on plants 

and trees; and (6) a high degree of uncertainty remains in our ability to assess the impact of O3

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 while recognizing that important 

uncertainties and research questions remain, we also conclude that progress has been made since 

the last review and thus, we generally find support in the available effects-based evidence for 

consideration of an O3 standard that is at least as protective as the current standard and do not 

find support for consideration of an O3 standard that is less protective than the current standard. 

This general conclusion is consistent with the advice and recommendations of CASAC and with 
 8-6

the views expressed by all the interested parties who provided comment on the previous draft of 

this document. 

 Having reached this general conclusion, we then evaluated the adequacy of the current 

standard by considering to what degree risks to vegetation and ecosystems 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 greater detail below, staff conclusions 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 public commenter views (section 8.3.1.2) in 

conjunction with the additional policy-relevant considerations 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 into account the uncertainties and limitations in the 

scientific evidence and analyses as well as considered the views of CASAC and other interested 

parties provided on the second draft of this document. 

8.3.1.1 Vegetation Evidence-, Exposure- and Risk-Based Considerations 

 In the last review, crop yield and seedling biomass loss open-top chamber (OTC) data 

provided the basis for staff analyses, conclusions, and recommendations (U.S. EPA, 1996b). 

Since then, several additional lines of evidence have progressed sufficiently to provide staff with 

a more complete and coherent picture of the scope of O3-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 reflects an increased emphasis on 

field-based exposure methods (e.g., free air exposure and ambient gradient), improved field 

survey biomonitoring techniques, and mechanistic tree process models. Findings from each of 

these research areas are discussed 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 integrated, weight of evidence approach. 

 In evaluating the degree to which the current standard is adequate in protecting 

vegetation at the national scale, staff has relied on both measured and modeled air quality 

information. For some effects, like visible foliar injury and modeled mature tree growth 

response, only monitored air quality information was used. For other effects categories (e.g., 

crop yield and tree seedling growth), staff relied on interpolated O3 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 assessment are described in the section 

preceding the discussion of seedling and mature 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 O3 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 air quality data for those counties containing the 

FIA biomonitoring sites. This assessment showed that incidence of visible foliar injury ranged 

from 21 to 39% during the four-year period (2001-2004) across all counties 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 visible 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 occurring on a variety of 

plant species in forested and other natural systems (see Figure 7-19 in section 7.6.3.2). Linking 

visible foliar injury to other plant effects is still problematic. However, its presence indicates 

that other O3–related vegetation effects could also be present. 

 The presence of visible foliar injury can adversely impact the public welfare. For 

example, visible foliar injury in national parks and wilderness areas can impact the aesthetic 

experience for both outdoor enthusiasts and the occasional park visitor. In addition, because 

these areas are afforded a higher degree of protection, the presence of O3-induced vegetation 

effects, including visible foliar injury, can take on increased significance. Specifically, federal 

land managers (FLMs) “...have determined that given the high ecological, 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 O3-induced 

vegetation effects, as air quality related values (AQRV) of concern (NPS, 2000). As shown in 

Appendix 7J, numerous O3 sensitive species are found on Class I federal lands. In addition, the 

presence of visible foliar injury also has the potential to economically impact for those who rely 

on healthy looking vegetation for their livelihood (e.g., horticulturalists, farmers of leafy crops, 

landscapers, Christmas tree growers). Many ornamental species have been listed as sensitive to 

O3 (Abt, 1993). Similarly, early senescence of fall foliage 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 O3 monitoring data, it was 

necessary to select an interpolation method that could be used to characterize O3 air quality over 
 8-8

broad geographic areas. Staff recognizes there are inherent uncertainties in the interpolation that 

must rely on sparse data that, for 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 scaling factors for the interpolation. 

See section 7.5 of chapter 7 for details on how the interpolation was constructed and how staff 

quantified the uncertainties (error and bias) associated with the interpolation. This quantification 

of exposure uncertainty for the 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-predicts higher 12-hr W126 exposures. Due to the important 

influence of higher exposures in determining risks 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 absence of more complete rural monitoring data, staff 

judged that this approach was appropriate to use in developing national vegetation exposure and 

risk assessments that estimate relative changes in risk for the various alternative standards 

analyzed. 

 To evaluate changing vegetation exposures and risks under selected "just meet" 

scenarios, staff analytically adjusted 2001 base year air quality distributions with a rollback 

method (Horst and Duff, 1995; Rizzo, 2005 & 2006) to reflect “just meeting” the current and 

alternative secondary standard options. This technique combines both linear and quadratic 

elements to reduce higher O3 concentrations more than lower ones. 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 several scenarios (see Figures 7-7, 7-8, 7-9, 7-10): 

• 4th-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 (proposed 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 cumulative 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 protection described in the last review. 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% yield loss in 50% of crop cases studied in the 
 8-9

National Crop Loss Assessment Network (NCLAN) experiments (section 7.6.2.2.). 

Alternatively, the lower levels of both SUM06 (15 ppm-hr) and W126 (13 ppm-hr) were 

associated with a level of crop protection of approximately no more than 10% yield loss in 75% 

of NCLAN cases. Another level to note is the upper level benchmark of W126 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 no more than 17% yield 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 Effects 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 seedlings 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 seedlings studied. Although there is appreciable 

uncertainty associated with these exposure estimates, the results of the exposure assessment 

indicates that current air quality levels could result in significant impacts to vegetation in some 

areas. 

 When 2001 air quality is rolled back to just meet the current 8-hr secondary standard, the 

overall 3-month 12-hr W126 exposures do not improve by much (Figure 7-7). Under this 

scenario, there are still many areas of the country that have seasonal O3 levels above the 12-hr 

W126 level of 21 ppm-hr. The exposure maps generated for the 0.070 ppm, 4th-highest 

maximum 8-hr average alternative standard, the SUM06 alternatives of 25 and 15 ppm-hr, and 

the W126 alternatives of 21 and 13 ppm-hr (Figures 7-8, 7-9, 7-10), all showed a markedly 

improved picture of O3 air quality compared to the current standard (Figure 7-7). Thus, the staff 

observes that all other alternative standards, when met at all locations, would be expected to 

provide improved protection of vegetation from seasonal O3 exposures of concern over the 

current standard. As expected, however, the greatest 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 alternative of 15 ppm-hr, and the 0.07 ppm, 8-hr alternative standard. 

Risk-Based Considerations 

This review continues to rely upon the concentration-response (C-R) functions developed 

from OTC exposure systems (also relied upon in the 1996 review). Due to what has been 
 8-10

described in the scientific literature as the “chamber 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 field-based approaches (e.g., free air exposure and 

ambient gradient) in recent research has occurred, providing information in the peer-reviewed 

literature that at least qualitatively 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 findings lend qualitative 

support to the conclusion that OTC conditions do not fundamentally alter the nature of the O3-

plant response. A related concern with respect to the use of the OTC C-R functions for crops is 

the concern that the crop varieties grown today may have O3 sensitivities significantly different 

than those used to derive the NCLAN crop and OTC tree seedling C-R functions which are relied 

upon in this review. Nothing in the recent literature, however, suggests that the O3 sensitivity of 

crop or tree species studied in the 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, O3 sensitivities are found to be as great or greater than those observed in the last 

review. As a result, staff continues to rely on the C-R functions available in the last review for 

predicting relative crop yield and tree seedling biomass loss potentials across a range of possible 

ambient O3 exposures. 

 An additional source of uncertainty not described or accounted for in the last review is 

that associated with the presence of a decreasing O3 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, respectively, based on ambient monitor data. Staff 

selected a 10% reduction factor to represent the maximum gradient believed to occur for daylight 

hours. However, recognizing that the actual downward adjustment value varies depending on 

interactions between numerous plant and site-specific factors, staff chose to present estimates of 

yield 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 O3 exposures that just meet the level of the current secondary standard 

(see Table 7F-5 in Appendix 7F). For instance, black cherry, ponderosa pine, eastern white pine, 

and aspen had estimated median seedling biomass 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 of 
 8-11

the same species may have more or less of a response to O3 exposure. Due to the potential for 

compounding effects over multiple years, a consensus workshop on O3 effects reported that a 

biomass loss greater than 2% annually can be significant (Heck and Cowling, 1997). Decreased 

seedling root growth and survivability could affect 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 current standard would likely continue to allow O3-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 O3 levels are reduced below 

those of the current standard, significant 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 back 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 associated with this analysis, we judge that this 

information should be given careful consideration in light of several other pieces of evidence. 

Specifically, limited evidence from experimental studies that goes beyond the seedling growth 

stage continues to show decreased growth under elevated O3 (King et al. 2005). Some mature 

trees such as red oak have shown an even greater sensitivity of photosynthesis to O3 than 

seedlings of the same species (Hanson et al., 1994). As indicated above, smaller growth loss 

increments may be significant for perennial species. The potential for cumulative “carry over” 

effects as well as compounding must be considered. 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 assessments estimate that just meeting the 

current 8-hr standard would still allow O3–related yield loss to occur 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 those estimated in the last review 

as a result of several factors. First, O3 air quality has improved in many areas of the country 

since the last review. Secondly, staff has factored in an O3 adjustment for the height gradient, as 

described above, and will present results for both 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. First, yield loss estimates were generated using the median C-R 

function when more than one function was available for a given species. For some species, 
 8-12

however, only one C-R function was available. In this latter case, there is more uncertainty 

regarding the range of variability in O3 sensitivity within each crop. Secondly, six of the fruit 

and vegetable species were not part of the NCLAN program and C-R functions were available 

only in terms of seasonal 7-hr or 12-hr mean indices. 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 magnitude 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 O3 exposure. 

However, it should also be recognized that, in some experimental cases, exposure to O3 has made 

plants more sensitive or vulnerable to other important stressors such as disease, insect pests, and 

harsh weather (U.S. EPA, 2006). Due to the significant impact these other 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 O3 with other plant 

stressors. 

 Keeping these uncertainties in mind, the results 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 species 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 O3 levels, potatoes and cotton had estimated yield losses of 9-15% and 

5-10%, respectively, when air 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 throughout the country under 

current air quality (0-6%) and just meeting 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 sufficiently reduced as to have nutritional and possibly 

economic implications for their use as ruminant animal feed at O3 exposures that occur in some 

years over large areas of the U.S. However, it is not clear at this time to what degree they are 

impacted at lower levels of air quality, since the studies were not designed to address this 

question. 

Summary 

 In summary, O3 levels that would be expected to remain after meeting the level of the 

current secondary standard are sufficient to cause visible foliar injury, seedling and mature tree 

growth, and reduce crop yields. Other O3-induced effects described in the literature include an 
 8-13

impaired ability of many sensitive species and genotypes within species to adapt to or withstand 

other environmental stresses such as freezing temperatures, pest infestations and/or root disease, 

and reduced ability to compete for available resources. In the long run, the result of these 

impairments (e.g., loss in vigor) may be premature plant death. Though effects on other 

ecosystem components have not been examined, except in isolated cases, effects such as those 

described above could have significant implications for plant community and associated species 

biodiversity and the structure and function of whole ecosystems (Young and Sanzone, 2002). 

8.3.1.2 CASAC and Public Commenter Views on the Adequacy of the Current 

Standard 

 Staff recognizes that the exposure-and risk-based information 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 standards are also important from a public welfare 

perspective. Judgments about the 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, CASAC, and all interested parties that public 

welfare policy judgments, including 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 those judgments with regard to the adequacy of the 

current secondary O3 standard, the views expressed by CASAC as well as the views of other 

interested parties who have commented on earlier drafts of this document are summarized here. 

The range of views generally reflects differing judgments as to the relative weight to place on 

various types of exposure- and risk-based information, and the associated uncertainties, as well 

as differing judgments about the importance of various O3-related vegetation effects from a 

public welfare perspective. 

 In a letter to the Administrator (Henderson, 2006c), the CASAC O3 Panel, with full 

endorsement of the chartered CASAC, unanimously concluded that “despite limited recent 

research, it has become clear since the last review that adverse effects 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 the current 8-hour primary and secondary 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 protect vegetation from the substantial, known or anticipated, direct 

and/or indirect, adverse effects of ambient ozone by continuing to promulgate identical primary 

and secondary standards for ozone. Moreover, the members of the Committee and a substantial 
 8-14

majority of the Ozone Panel agrees with EPA staff conclusions and encourages the 

Administrator to establish an alternative cumulative secondary standard for ozone and related 

photochemical oxidants that is distinctly different in averaging time, form and level from the 

currently existing or potentially revised 8-hour primary standard” (Henderson, 2006c). 

 In contrast to the views of CASAC discussed above, others submitted comments that 

supported retaining the current standards.1

 In considering the available evidence as a basis for 

their views, these commenters identified a number of key concerns that, in their view, make it 

inappropriate to revise the secondary standard at this time. For example, 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 secondary, (e.g., uncertainties in the exposure, risk 

and valuation analyses and the lack of air quality data in rural and remote areas), have not been 

materially reduced in this current 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 atmospheric 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 concludes that the current secondary NAAQS is inadequate to 

protect the public welfare from known and anticipated adverse welfare effects. As discussed 

above, this conclusion derives from several lines of evidence. 

First, visible foliar injury observations for the years 2001 to 2004 at USDA FIA 

biomonitoring sites show widespread O3–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 presence of other vegetation effects (e.g., reduced plant 

growth and impaired below ground root development) (U.S. EPA, 2006), though for most 

species, making this linkage remains problematic. Nevertheless, when visible foliar injury is 

present, the possibility that other O3-induced vegetation effects could also be present should be 

considered. Staff recognizes that it is not possible at this time to quantitatively assess the degree 

of visible foliar injury that should be judged adverse in all settings and across all species, and 

that other environmental factors can mitigate or exacerbate the degree of O3-induced visible 

foliar injury expressed at any given concentration of O3. However, recognizing 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 injury that could reasonably be considered to be 

adverse from a public welfare perspective. 

 Second, a recent ambient gradient study and a free air O3 enrichment (FACE) experiment 

have supported earlier findings from O3 experiments conducted in OTC. Studies conducted at 

the AspenFACE site in Wisconsin (see section 7.6.2.1 of chapter 7) on quaking aspen has 

confirmed the detrimental effects of O3 exposure on tree growth in a field study without 

chambers (Isebrands et al., 2000, 2001). The recent ambient gradient study (Gregg et al, 2003) 

evaluated biomass loss in cottonwood along an urban-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 O3 concentrations (See Section 7.6.3). Staff’s inclusion and emphasis on these two fieldbased lines of evidence is consistent with the Administrator’s conclusion at the end of the last 

review (62 FR 38877-78), that continued research on the effects of O3 on vegetation under field 

conditions would be important in this next review. Staff feels that the expanded field-based 

evidence provides qualitative support for the continued usefulness of findings obtained from 

chamber studies. 

 Staff’s conclusion is further strengthened by evidence of remaining impacts on tree 

seedling biomass loss when the current 8-hr standard is met. Staff estimated annual biomass loss 

up to 6-24% for some sensitive species in areas of high O3 exposure. Because of the potential 

for indirect effects on plant vigor from even small incremental biomass or growth reductions in 

the field, staff observes that these levels of tree seedling growth reduction are well above the 1-

2% range of concern identified by the 1997 consensus workshop (Heck and Cowling, 1997). 

Staff also took into account modeled mature tree growth loss estimates and commodity crop and 

fruit and vegetable yield loss in arriving at these conclusions. Linkages across ecosystem 

hierarchies (Young and Sanzone, 2002) make indirect impacts to ecosystems another welfare 

effects category of concern even after attaining the current secondary standard. 

8.3.2 Pollutant Indicator 

 The staff concludes that O3 remains the appropriate pollutant indicator for use in a 

secondary NAAQS that provides protection for public welfare from exposure to all 

photochemical oxidants. This conclusion is based 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 vegetation effects only raises concern at levels found in the ambient air 
 8-16

for O3 and, therefore, control of ambient O3 levels provides the best means of controlling other 

photochemical oxidants of potential welfare concern. 

8.3.3 Averaging Times 

 Plants, unlike people, are exposed to ambient air 24 hours a day, every day for their entire 

life. For annual species, this is for only a period within one year; for perennials, exposures are 

for multiple years, decades or centuries. Regardless of plant type, it has been well established in 

the literature that O3 effects are cumulative, and that longer exposure durations have a greater 

impact than shorter durations, all else being equal (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, O3 levels are not continuously elevated and plants are not equally 

sensitive to O3 over the course of a day, season or lifetime. 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 O3-induced effects 

throughout the growing season when measuring growth 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). Annual 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 species) depending on the species and where it is 

grown. In general, the period of maximum physiological activity and thus, potential O3 uptake 

for annual crops, herbaceous species, and deciduous trees and shrubs coincides with some or all 

of the intra-annual period defined as the O3 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 O3 also promote physiological 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 O3 exposure. However, 

we concluded, based on the information available at that time, that selection of the maximum 

consecutive 3-month period within the O3 season was reasonable, and in most cases, would most 

likely coincide with the periods of greatest plant sensitivity 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 O3 season is a reasonable 

averaging time for vegetation. 
 8-17

8.3.3.2 Diurnal Window 

 Stomata are the entry points for O3 into plant leaves. Over the course of a day, plant 

stomatal conductance varies along with light level, soil moisture and other factors. In general, 

stomata are most open during daylight hours in order to allow sufficient CO2 uptake for use in 

carbohydrate production through the light driven process of photosynthesis. At most locations, 

O3 concentrations are also highest during the daytime, potentially coinciding with maximum 

stomatal uptake. Ozone uptake during daylight hours impairs the light-driven process of 

photosynthesis, which can then lead to impacts on carbohydrate production, plant growth, 

reproduction (yield) and root function. Thus, in the last review, staff selected the 12-hr daylight 

window (8 am to 8 pm) to capture the diurnal window with most relevance to the photosynthetic 

process. Since that time, some limited work has been done by Musselman and Minnick (2000) 

to more fully characterize O3 uptake at night and its potential contribution to total plant uptake 

and response. This work reports that some species do take up O3 at night, but that the degree of 

nocturnal stomatal conductance varies widely between species and its relevance to overall O3-

induced vegetation effects remain unclear. We conclude that such information continues to be 

preliminary and not generalizable at this time (see also Appendix 7A of Chapter 7). Staff, 

therefore, again concludes that the daytime 12-hr window is the most appropriate period over 

which to cumulate diurnal O3 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 with staff with respect to both seasonal and 

diurnal averaging times. Specifically, CASAC states “the suggested approach to the secondary 

standard is a cumulative seasonal growing 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.” 

 In contrast, some commenters pointed to new information on nocturnal conductance as 

evidence for the need for a 24-hour diurnal window. Specifically, they state “an extensive 

review of the literature reported that a large number of species had varying degrees of nocturnal 

stomatal conductance.” Based on this review, Musselman and Minnick (2000) recommend that 

any O3 exposure index used to relate air quality to plant response should use the 24-hour 

cumulative exposure period. No commenters addressed the adequacy of the three month 

seasonal window. In examining the available information on nocturnal conductance (See 

Appendix 7A), staff concludes that it remains unclear to what extent nocturnal uptake contributes 

to the vegetation effects of yield loss, biomass loss or visible foliar injury. Due to the many 

species- and site-specific variables that influence the potential for and significance of nocturnal 
 8-18

uptake, staff concludes that additional research needs to be done before considering whether this 

component of vegetation exposure should be addressed with a different averaging time. 

 Based on these considerations, as well as information 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 environmental conditions found across the U.S. 

8.3.4 Form of the Standard 

 The 2006 O3 CD states, “In the 1996 O3 CD..., it was concluded, based on the best 

available data, that those O3 exposure indices that cumulated differentially weighted hourly 

concentrations were the best candidates for relating exposure to plant growth response.... The 

few studies that have been published since the 1996 O3 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 and strength of these 

conclusions. “When O3 effects are the primary cause of variation in plant response, plants from 

replicate studies of varying duration 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 does not specifically include an exposure duration component, the 

use of a mean exposure index for characterizing plant exposures appears inappropriate for 

relating exposure with vegetation effects” 

 Though the scientific justification for a cumulative, seasonal form was generally accepted 

in the last review, an analysis undertaken by EPA at that time 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 primary NAAQS and those expected not to meet the 

range of values (expressed in terms of the seasonal SUM06 index) of concern for vegetation. 

This result suggested that improvements in national air quality expected 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 vegetation in those same areas. Thus, in the proposal 

notice, the Administrator proposed two alternatives for consideration: one alternative was to 

make the secondary standard equal in every 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 appropriate 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 O3 concentrations averaged over a 3-year period would reduce O3 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 practice, provide sufficient protection for vegetation 

from the seasonal, cumulative and concentration-weighted exposures described 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 provide 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 comparing 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 foliar injury) are driven solely by annual O3 exposures, 

and that typically the cumulative forms are defined in terms of the annual 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 recent (2002-2004) county-level air quality data from 

AQS sites and the subset of CASTNET sites having the highest O3 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 analyzed alternative cumulative level and form. 

However, at the lower W126 level of 13 ppm-hr (see discussion on level in section 8.3.5 below), 

many more counties that meet the current 8-hr standard level and form no longer meet the 

alternative W126 form at this level. When individual years 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 and 
 8-20

level would overlap with areas of concern for vegetation expressed in terms of the 12-hr W126 

standard is inconsistent and would depend greatly on the level of the 12-hr W126 and 8-hr forms 

selected and the distribution of hourly O3 concentrations within the annual and/or 3 year average 

period. It is not clear how this relationship would change due to the change in O3 patterns 

resulting from control strategies put in place to attain different levels of standards. 

 This view is consistent with those of CASAC who unanimously agree that it is not 

appropriate to try to protect vegetation from the substantial, known or anticipated, direct and/or 

indirect, adverse effects of ambient ozone by continuing to promulgate identical primary and 

secondary standards for ozone. Moreover, the members of CASAC and a substantial majority of 

the CASAC O3 Panel agree with staff conclusions and encourage the Administrator to establish 

an alternative cumulative secondary standard for ozone and related photochemical oxidants that 

is distinctly 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 growing standard such as the indices SUM06 or W126 aggregated over at 

least the three summer months exhibiting the highest cumulative O3 levels and includes the O3

exposures from at least 12 daylight hours (Henderson, 2006c). 

 Some other public commenters agreed that “directionally a cumulative form of the 

standard may better match the underlying data.” However, 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 commenters were of the view that a W126 (or SUM06) was not 

sufficient in and of itself but should be combined with a measure of the number of peaks above 

100 ppb (N100). Some of these same commenters also felt a 24-hr averaging time was 

supported by the data on nocturnal stomatal conductance. 

 Staff recognizes that the relationship between O3 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 better capture factors that influence flux. Staff 

also recognizes that meeting the current 8-hr standard 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 O3-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 defined in terms of a form that reflects the two 

components of exposure known to influence plant response, i.e. differentially weighted peak 

concentrations and cumulative seasonal exposures. Further, 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 form in the absence of parallel SUM06 or W126 information. 
 8-21

 Selecting a more biologically-relevant secondary standard form would also: 1) be directly 

responsive to the recommendation of the 2004 National Research Council’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 enhance ecosystem-related program tracking and 

accountability; and 3) potentially spur more policy relevant vegetation effects research in the 

future. 

8.3.4.2 Comparison of SUM06 and W126 Cumulative, Concentration-Weighted 

Forms 

 In addition to evaluating the 8-hr average form, we evaluated the appropriateness of the 

SUM06 alternative proposed in the last review by comparing it to another cumulative, 

concentration-weighted form discussed in the 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 O3 concentrations (defined at the 

time as 0.03 to 0.05 ppm) under many typical air quality distributions. 

 In the current review, we have reconsidered whether the SUM06 form should still be 

judged the most appropriate cumulative form for a secondary NAAQS protective 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 described in the 1996 review, making PRB 

contributions much less of a factor influencing 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 O3-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 shown to produce vegetation effects of concern 

given sufficient duration. The W126 index, on the other hand, cumulates all O3

concentrations. However, because concentrations below 0.04 ppm, receive 

substantially smaller weights (3 percent or less), those concentrations within the range 

of PRB levels would not contribute significantly 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-month growing season SUM06 index. 

This is because the W126 index has no absolute minimum ozone concentration threshold and 
 8-22

only lightly weights the lower ozone concentrations. Therefore, a three-month seasonal W126 

range that is the approximate equivalent of the 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 policy-relevant cumulative, concentration-weighted 

form and recommends the Administrator consider the W126 as a more appropriate form for the 

secondary standard. This recommendation is consistent with the 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 should be set depends on a blending of science 

and policy judgments by the Administrator as to the level of air quality which is requisite to 

protect the public welfare from any known or anticipated adverse 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 different levels of air quality, often 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 identified a range for a 3-month, 12-hr SUM06 standard 

form of 25 to 38 ppm-hr, for the Administrator’s consideration. These levels were estimated to 

allow 10% to 20% yield loss, respectively, to occur 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 O3 exposures. The 

Administrator proposed the lower end of the range (e.g., 25 ppm-hr) as necessary to provide a 

requisite level of protection for vegetation against the adverse effects of O3. Staff believes that 

this level is an appropriate upper 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 review. In addition, this level derives from the extensive and 

quantitative historic and recent crop 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 that several lines of evidence point to the need for greater 
 8-23

protection for tree seedlings, mature trees, and associated forested ecosystems. Tree growth is an 

important endpoint to consider because it can be related to other aspects of societal welfare such 

as sustainable production of timber and related goods, recreation, and carbon (CO2) 

sequestration. Equally important, impacts on tree growth can also affect ecosystems through 

shifts in species composition and the loss of genetic diversity due to the loss of O3 sensitive 

individuals or species. To help inform staff judgment about an appropriate level of protection to 

consider for trees, staff considered the results of a consensus-building workshop on the need for 

a long-term cumulative secondary O3 standard. At this workshop, expert scientists expressed 

their judgments on what standard form(s) and level(s) would provide vegetation with adequate 

protection from O3-related adverse effects. Consensus was 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. These ranges are identified below, with the estimated approximate 

equivalent W126 shown in parentheses (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 forest 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 ecosystems – a SUM06 range of 8 to 12 (5 to 9) 

ppm-hr (Heck and Cowling, 1997). In the 1997 final rule, the Administrator 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 Administrator, CASAC expressed its view regarding 

the appropriate form and range of levels for the Administrator to consider. The CASAC 

preferred a seasonal 3-month W126 standard in a range that is the approximate equivalent of the 

SUM06 at 10 to 20 ppm-hrs. Staff has determined 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 Consensus Workshop as protective of tree seedlings in 

natural forest stands from growth effects (Heck and Cowling, 1997). 

 Staff believes that O3-related effects on forest tree species are an important public welfare 

effect of concern. Therefore staff concludes that it is appropriate 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 basis of the scientific effects literature, we anticipate that the 

lower end of the range identified for the Administrator’s consideration would substantially 

decrease the adverse effects of O3 on forested ecosystems. Additionally, it is anticipated that the 

lower end of this range would provide increased protection from the more subtle impacts of O3
 8-24

acting in synergy with other natural and man-made stressors to adversely affect individual plants, 

populations and whole systems. By disrupting the photosynthetic process, decreasing carbon 

storage in the roots, increasing early senescence of leaves and affecting water use efficiency in 

trees, O3 exposure could potentially disrupt or change the nutrient and water flow of an entire 

system. Weakened trees can become more susceptible to other environmental stresses such as 

pest and pathogen outbreaks or harsh weather conditions. Though it is not possible to quantify 

all the ecological and societal benefits associated with varying levels of alternative secondary 

standards, we conclude that this 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, staff concludes that a 3-month, 12-hr W126 range 

of 21-7 ppm-hr is appropriate for consideration, with the 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 information regarding a threshold of O3 exposures for vegetation, 

staff recognizes that the level selected is largely 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 welfare protection, along with a determination as to the appropriate 

weight to place on the associated uncertainties and limitations of this information. 

8.3.6 Summary of Staff Conclusions and Recommendations on the Secondary O3

Standard 

 Staff conclusions and recommendations on the elements of the secondary O3 standard for 

the Administrator’s consideration in making decisions on the secondary O3 standard are 

summarized below, together with supporting conclusions from sections 8.3.3 to 8.3.5 above. We 

recognize that selecting from among alternative policy options will necessarily reflect 

consideration of qualitative and quantitative uncertainties 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 anticipated adverse effects associated with the 

presence of the pollutant in the ambient air. In recommending these options for consideration, 

we are mindful that the Act requires standards that, in the judgment 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 Administrator 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 associated with alternative cumulative, seasonal 
 8-25

secondary standards under consideration; 3) the 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 

O3 impacts acting in synergy with other natural and manmade stressors to impact climate and 

other environmental endpoints, particularly given the potential significance at a regional scale 

and in Class I areas. 

 Staff notes that since the last review, several additional policy-relevant developments 

have occurred that may also warrant consideration 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 relevant indicators for that purpose. Having a more 

biologically-relevant air quality index would allow the Agency to better track improvements in 

vegetation protection on the ground with specific program actions aimed at accomplishing that 

end. Second, the NRC report (described above) states: “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. There is growing evidence that the current forms of 

the NAAQS are not providing adequate protection to sensitive ecosystems and crops” (NRC, 

2004). 

 The following secondary standard recommendations encompass the breadth of policyrelevant considerations described above: 

(1) It is appropriate to continue to use O3 as the indicator for a standard that is intended to 

address effects associated with exposure to O3, alone or in combination with related 

photochemical oxidants. Based on the available information, we conclude that there is no 

basis for considering any alternative indicator at this time. 

(2) It is not appropriate to continue to use an 8-hr averaging time for the secondary O3 

standard. The 8-hr average form should be replaced with a cumulative, seasonal, 

concentration weighted form. Given the reasons stated in earlier discussions herein, staff 

concludes that the W126 form is more appropriate than the SUM06 form recommended 

in the last review. 

(3) It is appropriate to consider the maximum consecutive 3 month period within the O3

season as the seasonal averaging time over which to cumulate hourly O3 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 species, staff concludes that the 3-month 
 8-26

period of maximum O3 exposure generally coincides with maximum biological activity 

for most plants. Staff notes that 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-year 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 consider a range of levels when making a determination regarding 

what is requisite public welfare protection. Staff concludes that an appropriate upper 

bound of this range is 21 ppm-hrs, expressed in terms of the W126 index, which is 

roughly equivalent to that proposed by the Administrator in the last review as able to 

provide a requisite level of protection to vegetation. Our analyses indicate that this level 

will provide protection against O3-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 protection against annual crop yield loss. 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 vulnerable 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 productivity resulting from elevated O3 exposures. On the 

other hand, O3 can also more subtly impact crop and forage nutritive quality and 

indirectly exacerbate the severity of the impact from other stressors. These latter effects 

cannot currently be quantified and deserve further study. Taking all of the above 

considerations into account, staff concludes that from a public welfare perspective, 

greater concern should be placed on the impacts of O3 exposures on vegetation in less 

heavily managed and unmanaged ecosystems such 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 selecting an appropriate level for a 

secondary standard. These include 1) the fact that O3 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 annual crops and the importance of protecting 
 8-27

against small percentages of biomass loss on an annual basis has been expressed by some 

within the scientific community; 3) visible foliar injury impacts can occur within a 

growing season at very low levels of O3 exposure; and 4) the extent to which a secondary 

standard should be precautionary in nature, given the possibility of O3 impacts acting in 

synergy with other natural and manmade stressors. Should a 3-year average of a 12-hr 

W126 be selected, the level chosen should reflect the fact that annual impacts are still a 

concern for visible foliar injury, tree seedling biomass loss, and crop yield loss, so that a 

potentially lower level might be considered to reduce the potential of adverse impact 

from the single high O3 year that could still occur while attaining a 3-year average. 

8.4 SUMMARY OF KEY UNCERTAINTIES AND RESEARCH 

RECOMMENDATIONS RELATED TO SETTING A SECONDARY O3

STANDARD 

 Staff has identified the following key uncertainties 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 standards. The first set of key uncertainties and research 

recommendations discussed below is that associated with the extrapolation to plant species and 

environments outside of specific experimental or field study conditions. The second set of key 

uncertainties and research recommendations pertain to our ability to assess the impact of O3 on 

other welfare effects categories such as climate, ecosystem components such as wildlife, and 

whole ecosystem structure and function. Third, we identify research recommendations related to 

the development of approaches, tools, or methodologies useful in characterizing the relationship 

between O3 and public welfare in a policy context. These three areas are described below. 

(1) Plant Species-Level Research Needs: 

• To reduce uncertainties associated with extrapolating plant response for a given level 

of O3 using composite response functions across differing regions and climates, studies 

using large numbers of plant species across regions where those species are indigenous 

are recommended. In addition, to better understand the full range of response of plant 

species to O3, research on more species is recommended. 

• To reduce uncertainty associated with estimating the risk to vegetation of differing 

amounts of O3-induced visible foliar injury over the plant’s leaf area, research to 

explore the relationship between visible foliar injury and other O3-related effects is 

recommended. 

• To reduce uncertainty associated with the impact of differing levels of O3 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 O3 flux into plants, including the 

genetic determinants of O3 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 O3 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 O3 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 extrapolating individual plant response spatially or to higher 

levels of biological organization, including ecosystems, research that explores and 

better quantifies the nature of the relationship between O3, plant response and multiple 

biotic and abiotic stressors, including those associated with climate change, is 

recommended. 

(2) Ecosystem Level Impacts: 

• To reduce uncertainties associated with projections of the effects of O3 on the 

ecosystem processes of water, carbon, and nutrient cycling, particularly at the stand 

and community levels, research is needed on the effects on below ground ecosystem 

processes in response to O3 exposure alone and in combination with other stressors. 

These below ground processes include interactions of roots with the soil or 

microorganisms, effects of O3 on structural or functional components of soil food webs 

and potential impacts on plant species diversity, changes in the water use of sensitive 

trees, and if the sensitive tree species is dominant, potential changes to the hydrologic 

cycle at the watershed and landscape level. 

• To conclusively show whether O3 affects biodiversity or genetic diversity, research on 

competitive interactions under elevated O3 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 

O3 and O3 precursor (e.g., volatile organic carbons) production, atmospheric processes, 

and climate change variables, research is recommended to evaluate whether O3 will 

negate the positive effects of an elevated CO2 environment on plant carbon and water 

balance, whether the likelihood of various biotic stressors such as pest epidemics and 

insect outbreaks would be expected to increase in the future 

• To reduce uncertainties associated with scaling O3 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 ecosystems, community and ecosystem studies 
 8-29

along natural O3 gradients, and extensive modeling efforts to project landscape-level, 

regional, national and international impacts of O3. 

• To fill the data gaps regarding O3 impacts to other non-plant welfare effects categories 

such as climate, as well as potential direct impacts of O3 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 O3 air quality, research is needed on methodologies to 

determine the values associated with important services and benefits derived from 

natural ecosystems such that these could be used in comprehensive risk and benefits 

assessments for O3 effects on natural ecosystems. 

• To reduce uncertainties associated with evaluating the performance of different 

exposure indices given different patterns of O3 exposures, experiments would need to 

be designed to specifically test the performance of different indices in predicting plant 

response under different exposure regimes. 

• To reduce uncertainties associated with the generation of rural O3 exposures, improved 

model capabilities are needed, including a more refined spatial grid for the western 

U.S., better handling of O3 movement in complex terrain and predicting nocturnal 

concentrations. Further, research is needed 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). Technical Report on Ozone Exposure, Risk, and Impacts Assessments for Vegetation: 

Final Report. Prepared for Office of Air Quality Planning 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). Concentration 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 Technical Information - OAQPS Staff Paper. EPA/452/R-96-007. Office of 

Air Quality Planning 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. 

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 SAB 

report. Washington, DC: U.S. Environmental Protection Agency, Science Advisory Board; report no. EPASAB-EPEC-02-009. Available: http://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 2nd Draft Ozone Staff Paper 

Dear Administrator Johnson: 

EPA is in the process of reviewing the national ambient air quality standards (NAAQS) 

for ozone (O3) and related photochemical oxidants, which 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 2nd Draft Ozone Staff Paper, entitled, Review of 

the National Ambient Air Quality Standards for Ozone: Policy Assessment of Scientific and 

Technical Information (July 2006). At the request of the Agency, EPA’s Clean Air Scientific 

Advisory Committee (CASAC or Committee), supplemented by subject-matter-expert panelists 

— collectively referred to as the CASAC Ozone Review Panel (Ozone 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 draft technical support documents. 

In its summary of EPA staff conclusions on the primary (health-related) ozone NAAQS 

found in Chapter 6 of the 2nd Draft Ozone Staff Paper, OAQPS set-forth two options with regard 

to revising the level and the form of the standard: (1) retain the current primary eight-hour (8-hr) 

NAAQS of 0.08 parts per million (ppm); or (2) consider a reduction in the level of the primary 

O3 NAAQS within the range of alternative 8-hr standards included in Staff’s exposure and risk 

assessments (which included a range from 0.064 to 0.084 ppm) with primary focus on an O3 

level of 0.07 ppm with a range of forms from third- through fifth-highest daily maximum. The 

Ozone Panel unanimously concludes that: 

1. There is no scientific justification for retaining the current primary 8-hr NAAQS of 0.08 

parts per million (ppm), and 

1 
2. The primary 8-hr NAAQS needs to be substantially reduced to protect 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 secondary (welfare-related) ozone NAAQS, the 

Ozone Panel is in strong agreement with the scientific and technical evidence presented in the 

summary of EPA staff conclusions on the secondary ozone NAAQS found in Chapter 8 of the 

draft Staff Paper in support of the alternative secondary 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 Committee fully endorses the Panel’s letter and hereby 

forwards it to you as the Committee’s consensus report on this subject. A discussion of each 

chapter in the 2nd Draft Ozone Staff Paper follows this letter, and the comments of individual 

Panel members on the 2nd Draft Ozone Staff Paper and three 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” air 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 2nd 

Draft Ozone Staff Paper as part of this activity. In February 2006, the Agency’s National Center 

for Environmental Assessment, Research Triangle Park, NC (NCEA-RTP), within the Agency’s 

Office of Research and Development (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 implications 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” between the scientific review contained in the Ozone AQCD and 

the public health and welfare policy judgments required of the EPA 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 1st Draft Ozone Staff Paper and two related technical support documents. However, 

given that the OAQPS’ first draft Staff Paper did not contain Agency staff conclusions about 

whether to retain or revise the existing primary 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. 

2
2. CASAC Ozone Review Panel’s Peer Review of the 2nd Draft Ozone Staff Paper and 

Related Technical Support Documents 

The Ozone Panel reviewed the 2nd Draft Ozone Staff Paper 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 that 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 immediately below. Following a detailed discussion on 

the primary and secondary NAAQS are the Panel’s major, chapter-specific comments. Finally, 

the individual written comments of Ozone Panel members on the 2nd Draft Ozone Staff Paper 

and the three related draft technical support documents are attached in Appendix D. Panelists’ 

responses to the Agency’s charge questions are included in these 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 2nd Draft Ozone Staff Paper, EPA staff themselves arrived 

at this same conclusion: 

“Based on the above considerations and findings from the [Final Ozone AQCD], while being 

mindful of important remaining uncertainties, staff concludes that the newly available 

information generally reinforces our judgments about causal relationships between O3 exposure 

and respiratory effects observed in the last review and broadens the evidence of O3 -related 

associations 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 progress has been made since the last review in 

advancing our understanding of potential mechanisms by which ambient O3, alone and in 

combination with other pollutants, is causally linked 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 concentrations 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 backed-up by evidence from controlled 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 (Adams, 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 some individuals at 0.06 ppm (Adams, 2006). These 

3
results indicate that the current ozone standard of 0.08 ppm is not sufficiently health-protective 

with an adequate margin of safety. It should be noted these findings were observed in healthy 

volunteers; similar studies in sensitive groups such as asthmatics 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 function 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 the current primary 8-hour NAAQS) found in the 

broad range of epidemiologic and controlled exposure studies cited above include: an increase in 

school absenteeism; increases in respiratory hospital emergency department visits among 

asthmatics and patients with other respiratory diseases; an increase in hospitalizations for 

respiratory illnesses; an increase in symptoms associated with adverse health effects, including 

chest tightness and medication usage; and an increase in mortality (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. 

As demonstrated in Chapter 5 of the 2nd Draft Ozone Staff Paper (specifically, Figures 5.5, 5.7, 

5.8, and 5.9), a significant decrease in adverse effects due to ozone exposures can be achieved by 

lowering the exposure concentrations below the current standard, which is effectively 0.084 

ppm. Beneficial effects in terms of reduction of adverse health effects were calculated to occur 

at the lowest concentration considered (i.e., 0.064 ppm). (See also Figure 3-4, “Effect estimates 

(with 95% confidence intervals) for associations between short-term ozone exposure and 

respiratory health outcomes,” on page 3-53.) 

The justification provided in the 2nd Draft Ozone Staff Paper for retaining the current 

level of the primary ozone standard as an option for the Administrator was based on results of 

controlled human exposure studies measuring modest declines in FEV1 after exposures to 0.08 

ppm ozone. However, as stated in the Staff Paper (page 3-6), while average decrements in the 

FEV1 were relatively small, 26% of the subjects had greater than 10% decrements, which can be 

clinically significant. Also, while measures of FEV1 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 independent 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 NAAQS 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 scientific data; and that the current primary 8-hr 

4
standard 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 scientific uncertainty regarding 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 the 8-hr primary ozone 

standard. Retaining this standard would continue to put large numbers of individuals at risk for 

respiratory effects and/or significant impact on quality of life including asthma exacerbations, 

emergency room visits, hospital admissions and mortality. (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 threshold 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 considered. The analysis found in the 2nd 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. Therefore, the CASAC recommends that the Agency 

conduct a broader evaluation of alternative concentration-based forms of the primary 8-hr ozone 

standard and the implications of those alternative forms on public-health protection and stability 

(i.e., with respect to yearly variability to ensure a stable target for control programs). 

The CASAC further recommends that the ozone NAAQS should reflect the capability of 

current monitoring technology, which allows accurate measurement of ozone concentrations 

with a precision of parts per billion, or equivalently to the third 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 level that should be considered for 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 the course of the entire growing season 

(defined to be a minimum of at least three months). Therefore, there is a clear need for a 

5
secondary standard which is distinctly different from the primary standard in averaging time, 

level and form. Developing a biologically-relevant ozone air quality index would be directly 

responsive to the 2004 National Research Council (NRC) recommendations on Air Quality 

Management in the United States (NAS, 1994) and will help support important new Agency 

initiatives to enhance ecosystem-related program tracking 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 candidates for a secondary standard. The Administrator 

considered a three-month, 12-hr SUM06 secondary standard at a level of 25 ppm-hr as an 

appropriate, biologically-relevant secondary standard, but ultimately rejected this option in favor 

of simply setting the secondary standard equal to the primary. It was rationalized that efforts to 

attain the new 8-hr primary standard would also 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 concentrations. Additionally, it was assumed that future 

ozone/vegetation effects research over the coming years would clarify the very uncertain 

quantitative relationships between ozone exposures and vegetation/ecological responses under 

ambient field conditions. 

Unfortunately, however, the Agency has supported very little new vegetation/ecological 

ozone effects research over the past decade. The net result is that the quantitative evidence 

linking specific ozone concentrations 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 surprising that substantial research needs remain, as indicated both in 

Chapter 8 and in individual reviewer comments. The quantitative evidence linking specific 

ozone concentrations to specific vegetation effects — especially at the complex ecosystem level 

2

— must continue to be characterized 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 and function, interactions among biotic and abiotic 

stressors and stimuli, variability among species and genotype, detoxification and compensatory 

mechanisms, etc. Nevertheless, the compelling weight of evidence provided in Chapter 7 of the 

nd Draft Ozone Staff Paper results from the convergence of results from many various and 

disparate assessment methods including chamber 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 vegetation including visible foliar injury are to be expected and have 

been observed in areas that are below the level 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 SUM06 secondary standard suggested in the 1996 

review and the upper end of the range suggested in Chapter 8 of the 2nd Draft Ozone Staff 

Paper). Seasonal SUM06 (or equivalent W126) ranges well below 25 ppm-hr were 

recommended for protecting various managed and unmanaged crops and tree seedlings in the 

1997 workshop on secondary ozone standards (Heck and Cowling, 1997). The absence of clear6
cut lower effects thresholds for sensitive vegetation combined with the lower recent estimates of 

policy-relevant background (typical 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 substantial, known or anticipated, 

direct and/or indirect, adverse effects of ambient 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 cumulative secondary standard for ozone and related 

photochemical oxidants that is distinctly 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 growing 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-month growing season SUM06 index for agricultural 

crops rather than the 15-25 ppm-hours proposed in Chapter 8. 

However, the Ozone Panel views the three-month growing season W126 index as a 

potentially more biologically-relevant index than the 3-month growing season SUM06 index. 

This is because the W126 index has no absolute minimum ozone concentration threshold and 

only lightly weights the lower ozone concentrations. Therefore, a three-month seasonal W126 

that is the approximate equivalent of the SUM06 at 10 to 20 ppm-hr is preferred. As shown by 

the references cited at the end of Chapter 8, the consensus view 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 standard that is not cumulative in form and does not include the whole 

growing season. 

In conclusion, the Clean Air Scientific Advisory Committee is pleased to provide its 

scientific advice and recommendations to the Agency on the primary and secondary ozone 

NAAQS. We recognize that our 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 statutory 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 Panel’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 February 2007 for the members of the Ozone Panel to 

review — and, prospectively, to offer additional, unsolicited advice to the Agency concerning — 

Chapter 6 (Staff Conclusions on Primary O3 NAAQS) and Chapter 8 (Staff Conclusions on 

Secondary O3 NAAQS) in that final Agency document. The purpose of such advice would be to 

7
inform EPA’s efforts as it develops the forthcoming, proposed rule for ozone and related 

photochemical oxidants. As always, the CASAC wishes EPA well in this important endeavor. 

 Sincerely,

 /Signed/ 

Dr. Rogene Henderson, Chair 

 Clean Air Scientific Advisory Committee 

Appendix A – Clean Air Scientific Advisory 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 Individual CASAC Ozone Review Panel Members 

8
CASAC Chapter-Specific Discussion Comments on 

EPA’s 2nd Draft Ozone Staff Paper 

Sub-groups of the CASAC Ozone Review Panel 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 behavior 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 SO2, NOX, and volatile organic compounds 

(VOCs) as well as gas phase irritants (formaldehyde, 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 the 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 and indoor environment), as provided 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 comparison of different models and measurements, it does 

not adequately address the uncertainties of the global GEOS-CHEM model, and how these 

uncertainties are reflected in the health risk analysis. Since ozone health effects are observed 

down to concentrations of the order of 0.04–0.05 ppm, it is important to know how the PRB is 

related to the considered primary ozone standard and what uncertainties 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 draft. Efforts to respond to some of the earlier 

concerns expressed by the CASAC are 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 might be, but this use is inconsistent across the chapter, and there 

are instances where EPA staff appear to be stretching to infer that data support their statement. 

While the individual comments of Ozone Panel members attached to this letter provide specifics 

on these points, some of the Panel’s more significant concerns are discussed briefly below. 

Discussion of measurement error is convoluted, confusing, and contains some mistakes. 

The primary issue in the use of central ambient monitors for ozone in time-series 

epidemiological studies is whether they provide any information at all that reflects daily personal 

ozone exposure in susceptible populations. The discussion on p. 3-37 of the impact of various 

types of exposure measurement error is incorrect; the difference between true and measured 

ambient concentrations is an example of classical measurement error that results in bias of effect 

9
estimates to the null, not just an increase in standard error. Claiming that the difference between 

average personal exposure and ambient concentrations results in “attenuation of risk” is not 

appropriate. 

The Ozone Panel does not completely agree with staff’s conclusion that “the use of 

routinely monitored ambient ozone concentrations as a surrogate for personal exposures is not 

generally expected to change the principal conclusions from ozone epidemiological studies.” 

Indeed, Panel members have little insight as to what we would find if we had actual exposure 

measurements. Personal exposures most likely correlate 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 outdoor 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 discussed in the chapter. Individuals with chronic 

obstructive pulmonary disease (COPD) and cardiovascular 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 who are at greatest risk of O3-induced health effects has not 

been confirmed. A more appropriate conclusion would be that individuals with COPD and CVD 

are at increased risk of O3-induced health effects. 

The discussion of the ranges for changes in FEV1 that are considered to be small, 

moderate, or large for persons with impaired respiratory systems is not consistent. While EPA 

staff state that the table values for the ranges do not need to be changed, staff indirectly 

acknowledge that a 10% reduction in this variable in asthmatics 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 low-level exposures used in the controlled human 

studies by Adams and colleagues is technically correct that no statistically significant changes 

were found in FEV1 for ozone at 40 to 60 ppb compared to filtered air, there were clearly a few 

individuals who experienced declines in lung function at these lower concentrations. These were 

healthy subjects, so the percentage of asthmatic subjects, if they 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 mortality. Coherence of respiratory 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 power when assessing PM risks, so consistency is 

needed here relative to ozone effect 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 and 6) as “inconclusive” or “inconsistent.” This 

should be corrected. 

10
Chapter 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 see 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 and alternative more stringent standards. This 

would be analogous to the way estimated effects are displayed in Chapter 5 (Figures 5-5 to 5-9 

[pp.5-58 to 5-65]). 

On the whole, Chapter 4 provides a clear “road map” for what was done to characterize 

available knowledge about human exposure to ozone in the framework of generally accepted 

modeling approaches of appropriately selected populations in 12 urban areas of the U.S. Much 

of the text reads like a basic textbook on human exposure assessment using state-of-the-art 

modeling approaches, such as the Air Pollutants Exposure Model (APEX), including adjustments 

for lung ventilation of delivered ozone dose. This extension, beyond exposure characterization, 

is particularly important for ozone where the extent 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 limitations of the APEX model in terms of 

variability and the quality of the input data, which is appropriate and fine as far as it goes. There 

are good reasons presented for selection of urban 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 the 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 modeling results, but 

was deficient it its discussion of seemingly counterintuitive results, 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 exposures above 0.07 ppm (8-hr) than in most other 

cities with lower ozone concentrations and fewer children. This was likely due to the greater 

within-day and sampler-to-sampler variations in concentration 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 air conditioning, especially in Houston. Whatever the reasons, there 

should have been some discussion of the causes. The quadratic rollback methodology should 

have been better described since this strategy has important consequences for the modeled 

results. 

The second issue that was presented, but left hanging without an adequate discussion is at 

the bottom of page 4-47, where it was simply stated 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 model, 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 measured and modeled concentrations depicted in 

Figure 4-22 is certainly worthy of further analysis and discussion. 

Chapter 5 (Characterization of Health Risks): Generally the panel found Chapter 5 

and its accompanying risk assessment to be well done, balanced and reasonably communicated. 

Additional text is needed at the beginning and 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 expanded in section 5.3.2.5. Although a 

number of issues are raised, their 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 FEV1 be evaluated. Although the 

3 parameter logistic (3PL) model emulates 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, although the problem of model 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 response probabilities would 

likely increase to better reflect that uncertainty. In addition, a suggestion to deal with the 

uncertainties surrounding estimation of PRB, particularly 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 expected 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 function expressed as percent change in FEV1 in children 

is a fair indicator of an adverse 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 significant respiratory morbidity, particularly in 

asthmatic children, are not adequately discussed. In addition, some added discussion is 

necessary to indicate that these measures are generally taken in areas with relatively high 

background levels of ozone exposure, and that the role that tolerance may play in minimizing the 

degree of adverse effect observed needs to be considered. 

From the perspective of the epidemiological 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 other endpoints should be discussed qualitatively to 

support the findings that these endpoints indicate that significant adverse effects are occurring at 

exposure concentrations well below the current standard. Other endpoints deemed worthy of 

additional discussion included respiratory emergency department visits among asthmatics and 

patients with other respiratory diseases, increased medication usage, and increased 

12
symptomatology 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 calculations (see Table 5-5 and 5-11) is that they 

are based on computations of the form Rx – RPRB, where Rx is the risk at a given concentration x 

of O3 and RPRB is the corresponding risk at policy-relevant background (PRB) for O3. As 

discussed at the Ozone Panel’s August meeting, the PRB is highly-problematic to calculate and 

is, in some sense, “unknowable.” One can avoid this problem by calculating the ∆ = R0.8 – Rx 

for various concentrations x. This form would allow focus on the question, “What is the 

difference in the expected number of health effects that will occur at various concentrations of 

O3, 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 uncertainties surrounding estimation of PRB. 

Chapter 6 (Staff Conclusions on Primary O3 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 way 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 O3 NAAQS): Chapter 7 is a well-developed and persuasively 

presented assessment of the welfare 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 propagation of error/uncertainty in the underlying technical 

documentation draws into question the conclusions drawn by EPA Staff. As observed in the 

Agency’s 1989 and 1996 Ozone Staff Papers, ozone 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 effects on sensitive vegetation are eliminated. See 

the additional discussion on Chapter 8 found in the main portion of the letter above. 

13
UNITED 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 Committee’s (CASAC) Review of the Agency’s 

Final Ozone Staff Paper 

Dear Administrator Johnson: 

The Clean Air Scientific Advisory Committee (CASAC or Committee), augmented by 

subject-matter-expert Panelists — collectively referred to as the CASAC Ozone Review Panel 

(Ozone Panel) — completed its review of the Agency’s 2nd Draft Ozone Staff Paper in October 

2006 (EPA-CASAC-07-001). In that letter, dated October 24, 2006, the CASAC indicated it 

would review the Agency’s Final Ozone Staff Paper and offer additional, unsolicited advice to 

the Agency on the chapters concerned with setting the primary and secondary National Ambient 

Air Quality Standards (NAAQS) for ozone. 

On March 5, 2007, the Ozone Panel met via a public teleconference to review EPA’s 

Final Review of the National Ambient Air Quality Standards for Ozone: Policy Assessment of 

Scientific and Technical Information (Final Ozone Staff Paper, January 2007). The Panel 

focused on Chapter 6 (The Primary O3 NAAQS) and Chapter 8 (The Secondary O3 NAAQS). 

The CASAC roster is attached as found in Appendix A, the Ozone Panel roster is provided as 

Appendix B, and Ozone Panel members’ individual review comments are found in Appendix C. 

Members of the CASAC Ozone Review Panel were pleased to review EPA’s Final 

Ozone Staff Paper. The members of CASAC and the Ozone Panel 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 recognizes that the Ozone Staff Paper is a final 

document, the Committee offers the following advice to aid the Administrator and Agency staff 

in developing EPA’s proposed rule for ozone and related photochemical oxidants, to be 

published in June 2007. 

1 
Primary 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 ppm, representative of levels within 

the upper, middle, and lower parts of this range, respectively.” Reiterating what was 

stated in the CASAC’s previous letter to you on this review (EPA-CASAC-07-001), 

Ozone Panel members were unanimous in recommending 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 October 24, 2006), in addition to EPA’s own 

findings in the Final Ozone Air Quality Criteria Document (AQCD) and the Final Ozone 

Staff Paper, provide overwhelming scientific evidence for this recommendation. 

Furthermore, the Ozone Panel recommends that the NAAQS should be specified to the 

third decimal place of the ppm scale to avoid any rounding issues — as indicated by the 

standard levels that the Agency itself considered 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 appropriate 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 primary ozone standard. 

• There is an underestimation of the affected population when one considers only twelve 

urban “Metropolitan Statistical Areas” (MSAs). The CASAC acknowledges that EPA 

may have intended to illustrate a range of impacts 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 research on the effects on sensitive subpopulations 

of low levels of the photochemical oxidant mixture for which ozone is used as a surrogate. In addition to the three field studies pointing to higher 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 oxidant mixtures on public health is essential to inform the 

future decision-making process. 

• Finally, with respect to policy-relevant background (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 

2
controllable by EPA. It would require international cooperation beyond the bounds of 

North America. A better scientific understanding of the PRB and its relationship to 

intercontinental transport of air pollutants could 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) ozone 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 are either linear, or indistinguishable from linear. Thus, 

PRB is irrelevant to the discussion of where along the concentration-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 members were unanimous in supporting the 

recommendation in the Final Ozone Staff Paper that protection of managed agricultural 

crops and natural terrestrial ecosystems requires 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 ozone standard is the (sigmoidally-weighted) 

W126 index, accumulated over at least the 12 “daylight” hours and over at least the three 

maximum ozone months of the summer “growing season.” 

• The Ozone Panel agrees with EPA Staff recommendations that the lowest bound of the 

range within which a seasonal 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 approximately 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 standard than for a primary standard based on 

maximum eight-hour concentrations. If multi-year averaging is employed to increase the 

stability of the secondary standard, the level of the standard should 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 occurring plant species has and will take place 

over time along with modification of levels and distribution of ambient ozone exposures. 

Therefore, future refinements of the secondary Ozone NAAQS will require both: (1) a 

significant future investment in effects research to ensure that data for plant response to 

ozone are representative of the species and genetic composition of current crop and forest 

3
species utilized by society; and (2) a clear understanding of the sources and propagation 

of uncertainty in the results of that research. 

Additional details on the general 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 using 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-related staff papers, the Committee will continue to 

provide you with scientific advice related to setting criteria air pollutant standards protective of 

the public health and public welfare under EPA’s revised NAAQS review 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 Individual CASAC Ozone Review Panel Members 

References 

1. Spector, D.M., Lippmann, M., Lioy, P.J., Thurston, 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. Effects 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., and 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 respiratory 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 Advisory Committee (CASAC) 

CHAIR 

Dr. Rogene Henderson, Scientist Emeritus, Lovelace Respiratory Research Institute, 

Albuquerque, NM 

MEMBERS 

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 Medicine, National Jewish Medical and 

Research Center, Denver, CO 

Dr. Frederick J. Miller, Consultant, Cary, NC 

Mr. Richard L. Poirot, Environmental Analyst, Air Pollution 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 Atmospheric 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. Butterfield, 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 Advisory 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 Francisco, 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 Medicine, National Jewish Medical and 

Research Center, Denver, CO 

Dr. William (Jim) Gauderman, Associate Professor, Preventive Medicine, Medicine, 

University of Southern California, Los Angeles, CA 

Dr. Henry Gong, Professor of Medicine and Preventive Medicine, Medicine and Preventive 

Medicine, Keck School of Medicine, University of Southern California, Downey, CA 

Dr. Paul J. Hanson, Senior Research and Development Scientist, Environmental Sciences 

Division, Oak Ridge National Laboratory (ORNL), Oak Ridge, TN 

Dr. Jack Harkema, Professor, Department of Pathobiology, College of Veterinary Medicine, 

Michigan State University, East Lansing, MI 

Dr. Philip Hopke, Bayard D. Clarkson Distinguished Professor, Department of Chemical 

Engineering, Clarkson University, Potsdam, NY 

Dr. Michael T. Kleinman, Professor, Department of Community & Environmental Medicine, 

University of California – Irvine, Irvine, CA 

Dr. Allan Legge, President, Biosphere Solutions, Calgary, Alberta, Canada 

B-1 
Dr. 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 Environmental 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 Anatomy, Physiology and Cell Biology, School 

of Veterinary Medicine, University of California – Davis, Davis, California 

Mr. Richard L. Poirot*, Environmental Analyst, Air Pollution 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 Medicine, 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 Atmospheric 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-2 
United States 

Environmental Protection Agency 

Office of Air Quality Planning and Standards 

Air Quality Strategies and Standards Division 

Research Triangle Park, NC 

Publication N