# I n t e g r a t e d S c i e n c e A s s e s s m e n t f o r O x i d e s o f N i t r o g e n
— H e a l t h C r i t e r i a

U n i t e d S t a t e s E n v i r o n m e n t a l P r o t e c t i o n A g e n c y E P A / 6 0 0 / R

- 0 8 / 0 7 1 J u l y 2 0 0 8July 2008 EPA/600/R-08/071



# Integrated Science Assessment for Oxides of Nitrogen – Health Criteria

National Center for Environmental Assessment-RTP Division Office of Research and Development U.S. Environmental Protection Agency Research Triangle Park, NC

# Disclaimer

This document has been reviewed in accordance with U.S. Environmental Protection Agency policy and approved for publication. Mention of trade names or commercial products does not constitute endorsement or recommendation for use.iii 

# Contents

List of Tables ________________________________________________________________________________________ vii
List of Figures _______________________________________________________________________________________ ix
Acronyms and A bbreviations__________________________________________________________________________ xiii

Authors, Contributor s, Reviewers ______________________________________________________________________ xix

NO X Project Team __________________________________________________________________________________ xxiii
Clean Air Scientific Advisory Committee Oxides of Nitrogen Primary NAAQS Review Panel _____________________ xxv

Preface ___________________________________________________________________________________________ xxvii
Chapter 1. In troduction _______________________________________________________________________________ 1-1 1.1. Document Development ____________________________________________________________________________________ 1-1 1.2. Document Organization_____________________________________________________________________________________ 1-2 1.3. EPA Framework for Caus al Determinations _____________________________________________________________________ 1-2 1.3.1. Scientific Evidence Used in Establishing Causality ___________________________________________________________ 1-3 1.3.2. Moving from Association to Causation_____________________________________________________________________ 1-3 1.3.3. Multifactorial Causation ________________________________________________________________________________ 1-5 1.3.4. Uncertainty__________________________________________________________________________________________ 1-6 1.3.5. Application of Framework ______________________________________________________________________________ 1-7 1.3.6. First Step—Determi nation of Causality ____________________________________________________________________ 1-8 1.3.7. Second Step—Evaluation of Population Response___________________________________________________________ 1-9
Chapter 2. Source to Exposure ________________________________________________________________________ 2-1 2.1. Introduction ______________________________________________________________________________________________ 2-1 2.2. Sources and Atmos pheric Chemistry __________________________________________________________________________ 2-2 2.2.1. Sources of NO X ______________________________________________________________________________________ 2-2 2.2.2. Chemical Transformations ______________________________________________________________________________ 2-4 2.2.2.1. Formation of Nitro- PAHs _________________________________________________________________________ 2-5 2.2.3. O 3 Formation ________________________________________________________________________________________ 2-6 2.3. Measurement Methods _____________________________________________________________________________________ 2-6 2.4. Atmospheric Concentrations _________________________________________________________________________________ 2-8 2.4.1. Ambient Concentrations________________________________________________________________________________ 2-8 2.4.2. NO 2 Concentrations __________________________________________________________________________________ 2-22 2.4.3. Seasonal Variability in NO 2 at Urban Sites ________________________________________________________________ 2-23 2.4.4. Diurnal Variability in NO 2 Concentrations _________________________________________________________________ 2-25 2.4.5. Concentrations of NO Z Species _________________________________________________________________________ 2-26 2.4.6. Policy-Relevant Background Concentrations of NO 2 _________________________________________________________ 2-26 2.4.6.1. Analysis of Policy-Relevant Background Contribution _________________________________________________ 2-26 2.4.7. Summary of Ambient and Policy-Relevant Background Concentrations of NO 2 ____________________________________ 2-28 2.5. Exposure Issues _________________________________________________________________________________________ 2-28 2.5.1. Introduction ________________________________________________________________________________________ 2-28 2.5.2. Personal Sampling of NO 2 _____________________________________________________________________________ 2-31 2.5.3. Spatial Variability in NO 2 Concentrations__________________________________________________________________ 2-32 2.5.3.1. Variability of NO 2 Concentrations across Ambient Monitoring Sites _______________________________________ 2-32 2.5.3.2. Small-Scale Hori zontal Variability _________________________________________________________________ 2-33 2.5.3.3. Small-Scale Ve rtical Variability ___________________________________________________________________ 2-34 2.5.4. NO 2 On or Near Roads _______________________________________________________________________________ 2-36 2.5.5. Indoor Sources and Sinks of NO 2 and Associated Pollutants __________________________________________________ 2-37 2.5.5.1. Indoor Ai r Chemistry ___________________________________________________________________________ 2-40 2.5.6. Relationship of Personal Expos ure to Ambient Concentrations ________________________________________________ 2-41 2.5.6.1. Associations between Personal Expos ure and Ambient and Outdoor Concentrations_________________________ 2-41 2.5.6.2. Ambient Contributi on to Personal Exposure _________________________________________________________ 2-51 2.5.7. NO 2 as a Component and Indicator of Pollutant Mixtures _____________________________________________________ 2-53iv 2.5.7.1. Associations between Ambient NO 2 and Ambient Copollutants __________________________________________ 2-53 2.5.7.2. Associations among NO 2 and Other Pollutants in Indoor Environments____________________________________ 2-54 2.5.7.3. Personal and Ambient Associations between NO 2 and Copollutants ______________________________________ 2-56 2.5.7.4. NO 2 as an Indicator of the Mixture of Traffic Pollutants ________________________________________________ 2-57 2.5.8. Exposure Error in Epidemiologic Studies__________________________________________________________________ 2-59 2.5.8.1. Community Time-Series Studies__________________________________________________________________ 2-59 2.5.8.2. Long-Term Ex posure Studies ____________________________________________________________________ 2-60 2.5.9. Summary of Issues in Assessing Exposures to NO 2 _________________________________________________________ 2-61 2.6. Dosimetry of Inhaled NO X __________________________________________________________________________________ 2-62
Chapter 3. Integrated Health Eff ects ____________________________________________________________________ 3-1 3.1. Respiratory Morbidity Relat ed to Short-Term Exposure ____________________________________________________________ 3-2 3.1.1. Lung Host Defenses and Immunity _______________________________________________________________________ 3-2 3.1.2. Airway Inflammation___________________________________________________________________________________ 3-5 3.1.3. Airway Hype rresponsiveness ___________________________________________________________________________ 3-9 3.1.3.1. Allergen Responsiveness _______________________________________________________________________ 3-10 3.1.3.2. Nonspecific Responsiveness ____________________________________________________________________ 3-14 3.1.3.3. Summary of Short-Term Ex posure on Airway Responsiveness __________________________________________ 3-17 3.1.4. Effects of Short-Term Ex posure on Respiratory Symptoms ___________________________________________________ 3-18 3.1.4.1. Indoor and Personal Exposur e and Respiratory Outcomes _____________________________________________ 3-18 3.1.4.2. Ambient NO 2 Exposure and Respirat ory Symptoms___________________________________________________ 3-23 3.1.4.3. Summary of Short-Term Ex posure on Respiratory Symptoms ___________________________________________ 3-26 3.1.5. Effects of Short-Term Exposure on Lung Function __________________________________________________________ 3-27 3.1.5.1. Epidemiologic Studies of Lung Function ____________________________________________________________ 3-27 3.1.5.2. Clinical Studies of Lung Function _________________________________________________________________ 3-29 3.1.5.3. Summary of Short-Term Exposure on Lung Function__________________________________________________ 3-30 3.1.6. Hospital Admissi ons and ED Visits ______________________________________________________________________ 3-31 3.1.6.1. All Respir atory Outcomes _______________________________________________________________________ 3-31 3.1.6.2. Asthma _____________________________________________________________________________________ 3-39 3.1.6.3. COPD ______________________________________________________________________________________ 3-40 3.1.6.4. Respiratory Diseases Other than Asthma or CO PD ___________________________________________________ 3-41 3.1.6.5. Summary of Short-Term Exposure on Re spiratory ED Visits and Hospitalizations ___________________________ 3-41 3.1.7. Summary and Integration—Respiratory Heal th Effects with Short-Term Exposure _________________________________ 3-41 3.2. Cardiovascular Effects Relat ed to Short-Term Exposure __________________________________________________________ 3-43 3.2.1. Heart Rate Variability _________________________________________________________________________________ 3-43 3.2.2. Arrhythmias Recorded on Implanted Defibrillators __________________________________________________________ 3-44 3.2.3. Repolarization Changes_______________________________________________________________________________ 3-44 3.2.4. Markers of Cardio vascular Disease Risk__________________________________________________________________ 3-44 3.2.5. Toxicology of I nhaled Nitric Oxide _______________________________________________________________________ 3-45 3.2.6. Hospital Admissions and ED Visits for CVD _______________________________________________________________ 3-45 3.2.7. Cardiac Disease_____________________________________________________________________________________ 3-46 3.2.8. Hospital Admissions for Stro ke and Cerebrovascular Disease _________________________________________________ 3-47 Summary of Cardiovascular Effects Re lated to Short-Term Exposure ________________________________________________ 3-49 3.3. Mortality Related to Short-Term Ex posure _____________________________________________________________________ 3-49 3.3.1. Multicity Studies and Meta-Analyses _____________________________________________________________________ 3-49 3.3.1.1. National Morbidity, Mortalit y, and Air Pollution Study (NMMAPS) ________________________________________ 3-50 3.3.1.2. Canadian Multicity Studies ______________________________________________________________________ 3-50 3.3.1.3. Air Pollution and Health: A European Approach (APHEA) Studies________________________________________ 3-51 3.3.1.4. The Netherlands Study _________________________________________________________________________ 3-52 3.3.1.5. Other Mult icity Studies _________________________________________________________________________ 3-52 3.3.1.6. Meta-Analyses of NO 2 Mortality Studies ____________________________________________________________ 3-53 3.3.2. Summary of Mortality Rela ted to Short-Term Exposure ______________________________________________________ 3-53 3.4. Respiratory Effects Rela ted to Long-Term Exposure _____________________________________________________________ 3-56 3.4.1. Lung Function Growth ________________________________________________________________________________ 3-56 3.4.2. Asthma Prevalence and Incidence ______________________________________________________________________ 3-62 3.4.3. Respiratory Symptoms________________________________________________________________________________ 3-63 3.4.4. Respiratory Morphology_______________________________________________________________________________ 3-65 3.4.5. Summary of Respiratory Effect s Related to Long-Term Exposure ______________________________________________ 3-65 3.5. Other Morbidity Effects Re lated to Long-Term Exposure __________________________________________________________ 3-67 3.5.1. Cancer Incidence____________________________________________________________________________________ 3-67 3.5.1.1. Animal and In Vitro Carci nogenicity and Genotoxicity Studies ___________________________________________ 3-68v 3.5.1.2. Toxicological Studies of Coexposure with Known Carcinogens __________________________________________ 3-68 3.5.1.3. Studies in Animals with Spontaneously High Tumor Rates _____________________________________________ 3-69 3.5.1.4. Facilitation of Metastases _______________________________________________________________________ 3-69 3.5.1.5. Production of N -Nitroso Compounds and other Nitro Derivatives_________________________________________ 3-69 3.5.1.6. Summary of Cancer Incidenc e Related to Long-Term Exposure _________________________________________ 3-70 3.5.2. Reproductive and Developmental Effects _________________________________________________________________ 3-71 3.5.2.1. Summary of Reproductive and Developmental Effects Related to Long-Term Exposure ______________________ 3-73 3.5.3. Summary of Other Morbidity Effe cts Related to Long-Term Exposure ___________________________________________ 3-73 3.6. Mortality Related to Long-Term Exposure______________________________________________________________________ 3-74 3.6.1. U.S. Studies on Mortality Related to Long-Term Exposure ____________________________________________________ 3-74 3.6.2. European Studies on Mortality Related to Long-Term Exposure________________________________________________ 3-76 3.6.3. Summary of Mortality Re lated to Long-Term Exposure_______________________________________________________ 3-78
Chapter 4. Public Health Impact________________________________________________________________________ 4-1 4.1. Defining Adverse Health Effects ______________________________________________________________________________ 4-1 4.2. Concentration-Response Functi ons and Potential Thresholds _______________________________________________________ 4-2 4.3. Susceptible and Vulnerable Populations ________________________________________________________________________ 4-4 4.3.1. Preexisting Disease as a Potential Risk Factor ______________________________________________________________ 4-4 4.3.1.1. Asthmatics____________________________________________________________________________________ 4-4 4.3.1.2. Cardiopulmonary Disease and Diabetes_____________________________________________________________ 4-5 4.3.2. Age as a Potential Risk Factor___________________________________________________________________________ 4-6 4.3.3. Gender as a Pot ential Risk Factor________________________________________________________________________ 4-7 4.3.4. Genetic Factors for Oxi dant and Inflammatory Damage _______________________________________________________ 4-7 4.3.5. Other Potentially Susceptible Populations__________________________________________________________________ 4-8 4.3.6. Increased Vulnerability Associ ated with Increased Exposure ___________________________________________________ 4-8 4.4. At-Risk Susceptible Population Estimates_______________________________________________________________________ 4-9 4.5. Summary of Public Health Issues ____________________________________________________________________________ 4-12
Chapter 5. Summary and Conclu sions __________________________________________________________________ 5-1 5.1. Introduction ______________________________________________________________________________________________ 5-1 5.2. Key Source to Exposure Findings _____________________________________________________________________________ 5-2 5.2.1. Atmospheric Science and Ambient Concentrations___________________________________________________________ 5-2 5.2.2. Exposure Assessment _________________________________________________________________________________ 5-3 5.3. Key Health Effects Findings _________________________________________________________________________________ 5-4 5.3.1. Findings from t he Previous Review _______________________________________________________________________ 5-4 5.3.2. New Health Effects Findings ____________________________________________________________________________ 5-4 5.3.2.1. Respiratory Effects Rela ted to Short-Term Exposure ___________________________________________________ 5-6 5.3.2.2. Cardiovascular Effects Rela ted to Short-Term Exposure _______________________________________________ 5-12 5.3.2.3. Mortality Related to Short-Term Exposure __________________________________________________________ 5-12 5.3.2.4. Respiratory Morbidity Re lated to Long-Term Exposure ________________________________________________ 5-12 5.3.2.5. Other Morbidity Rela ted to Long-Term Exposure _____________________________________________________ 5-13 5.3.2.6. Mortality Related to Long-Term Exposure___________________________________________________________ 5-13 5.3.2.7. Exposure Indices______________________________________________________________________________ 5-14 5.3.2.8. Susceptible and Vulnerable Populations____________________________________________________________ 5-14 5.3.2.9. Concentration-Response Relationships and Thresholds _______________________________________________ 5-14 5.4. Conclusions _____________________________________________________________________________________________ 5-15vii 

# List of Tables

Table 1.3-1. Aspects to aid judgi ng causality. __________________________________________________ 1-7

Table 1.3-2. Weight of evidence for causal determination ( adapted from Institute of Medicine, 2007). ______ 1-9

Table 2.2-1. Annual 2002 average anthropogenic NO X emissions in the U.S. (million metric tons). ________ 2-2

Table 2.5-1. Spatial variability of NO 2 in selected U.S. urban areas. _______________________________ 2-33

Table 2.5-2. NO 2 concentration near indoor sources: minute to hour averages. ______________________ 2-39

Table 2.5-3. NO 2 concentration near indoor sources: 24-h to 2 week averages. ______________________ 2-39

Table 2.5-4. Association between personal exposure and ambient concentration (longitudinal correlation coeffi cients).________________________________________________________ 2-42

Table 2.5-5. Association between personal exposure and ambient concentration (pooled correlation coefficient s). ________________________________________________________________ 2-43

Table 2.5-6. Association between personal expos ure and outdoor concentration. _____________________ 2-44

Table 2.5-7. Pearson correlation coefficient between ambient NO 2 and ambient copollutants. ___________ 2-54

Table 2.5-8. Pearson correlation coefficient between ambient NO 2 and personal copollutants.___________ 2-56

Table 2.5-9. Pearson correlation coefficient between personal NO 2 and ambient copollutants.___________ 2-56

Table 2.5-10. Pearson correlation coefficient between personal NO 2 and personal copollutants. __________ 2-57

Table 2.5-11. Pearson correlation coefficient between NO X and traffic-generated pollutants. _____________ 2-57

Table 3.1-1. Proposed mechanisms whereby NO 2 and respiratory virus infections may exacerbate upper and lower airway symptoms . ________________________________________________ 3-3

Table 3.1-2. Changes in airway responsiveness associated with NO 2 exposure.______________________ 3-15

Table 3.1-3. Fraction of NO 2 -exposed asthmatics with increased non-specific airway hyperresponsiveness. _________________________________________________________ 3-16

Table 3.1-4. Mean rates (SD) per 100 days at risk and unadjusted rate ratio (RR) for symptoms/activities over 12 weeks dur ing the winter heat ing period._____________________ 3-19

Table 4.1-1. Gradation of individual responses to short-term NO 2 exposure in persons with impaired respiratory sy stems. ___________________________________________________________ 4-2

Table 4.4-1. Prevalence of selected respiratory disor ders by age group and by geographic region in the U.S.(2004 [U.S. Adults] and 2005 [U.S. Children] National Health Interview Survey). ________ 4-10

Table 5.3-1. Summary of evidence from epidemiologic, hum an clinical, and animal toxicological studies on the health effects associated with short- and long-term exposure to NO 2 . _______________ 5-5

Table 5.3-2. Key studies and effects of exposure to NO 2 from clinical studies. ________________________ 5-9

Table 5.3-3. Summary of toxicological effects in rats from NO 2 exposure. ___________________________ 5-10

Table 5.4-1. Ambient NO 2 concentrations and selected effect esti mates from studies of respiratory symptoms, ED visits and hospital adm issions in the U.S. and Canada. ___________________ 5-17ix 

# List of Figures

Figure 1.3-1. Exposure–disease–stress model for envir onmental health disparities._____________________ 1-4
Figure 1.3-2. Potential relationships of NO X with adverse heal th effect s.______________________________ 1-6
Figure 2.1-1. A generalized conceptual model fo r integrating research on NO X pollution and human health effe cts. ________________________________________________________________ 2-1
Figure 2.2-1. Schematic diagram of the cy cle of reactive oxidized N species in the atmosphere.___________ 2-3
Figure 2.4-1. Location of ambient NO 2 monitors in the U.S. as of November 5, 2007. ___________________ 2-9
Figure 2.4-2. NO 2 monitor locations in the Atlanta, GA CMSA shown in relation to major roadways, point-source electric generating units, and population densities for total population, and fractions ≤ 17 years and ≥ 65 years. ______________________________________________ 2-10
Figure 2.4-3. NO 2 monitor locations in the Boston, MA CM SA shown in relation to major roadways, point-source electric generating units, and population densities for total population, and fractions ≤ 17 years and ≥ 65 years. ______________________________________________ 2-11
Figure 2.4-4. NO 2 monitor locations in the Chicago, IL CM SA shown in relation to major roadways, point-source electric generating units, and population densities for total population, and fractions ≤ 17 years and ≥ 65 years. ______________________________________________ 2-12
Figure 2.4-5. NO 2 monitor locations in the Houston, TX CMSA shown in relation to major roadways, point-source electric generating units, and population densities for total population, and fractions ≤ 17 years and ≥ 65 years. ______________________________________________ 2-13
Figure 2.4-6. NO 2 monitor locations in the Los Angeles, CA CMSA shown in relation to major roadways, point-source electric generating units, and population densities for total population, and fractions ≤ 17 years and ≥ 65 years. ______________________________________________ 2-14
Figure 2.4-7. Detail of NO 2 monitor locations in the Los Angeles , CA CMSA shown in relation to major roadways, point-source electric generati ng units, and total population density. _____________ 2-15
Figure 2.4-8. NO 2 monitor locations in the New York City, NY and Philadelphia, PA CMSAs shown in relation to major roadways, point-source el ectric generating units , and population densities for total population, and fractions ≤ 17 years and ≥ 65 years.___________________________ 2-16
Figure 2.4-9. Detail of NO 2 monitor locations in the New York City, NY and Philadelphia, PA CMSAs shown in relation to major roadways, point -source electric generating units, and total population density.____________________________________________________________ 2-17
Figure 2.4-10. NO 2 monitor locations in the Steubenville, OH CM SA shown in relation to major roadways, point-source electric generating units, and population densities for total population, and fractions ≤ 17 years and ≥ 65 years. ______________________________________________ 2-18
Figure 2.4-11. NO 2 monitor locations in the Washington, DC and Baltimore, MD CMSAs shown in relation to major roadways, point-source electric generating units, and population densities for total population, and fractions ≤ 17 years and ≥ 65 years. _________________________________ 2-19
Figure 2.4-12. Detail of NO 2 monitor locations in the Washingt on, DC and Baltimore, MD CMSAs shown in relation to major roadways, point-source electric generating units, and total population density. ____________________________________________________________________ 2-20
Figure 2.4-13. Ambient concentrations of NO 2 measured at all monitoring sites located within MSAs in the U.S. from 2003 through 2005. ________________________________________________ 2-21
Figure 2.4-14. Monthly average NO 2 concentrations in ppb for January 2002 (left panel) and July 2002 (right panel) calculat ed by CMAQ ________________________________________________ 2-22
Figure 2.4-15. Nationwide trend in NO 2 concentrati ons.___________________________________________ 2-23
Figure 2.4-16. Time series of 24-h avg NO 2 concentrations at individual si tes in Atlanta, GA from 2003 through 2005. _______________________________________________________________ 2-24x Figure 2.4-17. Mean hourly NO 2 concentrations on weekdays and weekends measured at two sites in Atlanta, GA. _________________________________________________________________ 2-25
Figure 2.4-18. Upper panel: Annual mean NO 2 concentrations (in ppb) in the U.S. Middle panel: Annual mean PRB concentrations (in ppb) for NO 2 in the U.S.________________________________ 2-27
Figure 2.5-1. Percentage of time people spend in diffe rent environments in the U.S. ___________________ 2-29
Figure 2.5-2. NO 2 and NO X concentrations normalized to ambient values, plotted as a function of downwind distance from the freeway. _____________________________________________ 2-34
Figure 2.5-3. NO 2 concentrations measured at 4 m (Van) and at 15 m at NY Department of Environmental Conservation am bient monitoring sites ________________________________ 2-35
Figure 2.5-4. Distribution of correlation coeffici ents (U.S. studies) between personal NO 2 exposure and ambient NO 2 concentrations based on Fi sher’s Z tr ansform. ___________________________ 2-47
Figure 2.5-5. Distribution of correlation coeffici ents (European studies) between personal NO 2 exposure and ambient NO 2 concentrations based on Fi sher’s Z tr ansform.________________________ 2-48
Figure 2.5-6. Correlations of NO 2 to O 3 versus correlations of NO 2 to CO for Los Angeles, CA (2001-2005). ________________________________________________________________ 2-55
Figure 2.5-7. Composite, diurnal variability in 1-h avg NO 2 in urban areas.___________________________ 2-58
Figure 3.1-1. Studies of airway inflammatory responses in relation to the total exposure to NO 2 , expressed as pp m-minutes. _____________________________________________________ 3-7
Figure 3.1-2. Airway responsiveness to allergen challenge in asthmatic subjects following a single exposure to NO 2 . _____________________________________________________________ 3-11
Figure 3.1-3. Geometric mean symptom rates (95% CI) fo r cough with phlegm (panel A) and proportions (95% CI) of children absent from school ___________________________________________ 3-20
Figure 3.1-4. Adjusted association of increasing indoor NO 2 concentrations with number of days with persistent cough (panel a) or s hortness of breath (panel b) fo r 762 infants during the first year of life. __________________________________________________________________ 3-22
Figure 3.1-5. Odds ratios (95%CI) for daily asthma sympto ms (panel A) and rate ratios (95% CI) for daily rescue inhal er use________________________________________________________ 3-24
Figure 3.1-6. Odds ratios (95% CI) for associations between asthma symptoms in children and 24-h average NO 2 concentrations ( per 20 ppb). _________________________________________ 3-26
Figure 3.1-7. Odds ratios and 95% CI for associations between asthma symptoms and 24-h average NO 2 concentrations (per 20 ppb) from multipollutant models.___________________________ 3-27
Figure 3.1-8. Relative risks (95% CI) for hospital admissions or ED visits for all respiratory disease stratified by all ages or children. _________________________________________________ 3-32
Figure 3.1-9. Relative Risks (95% CI) for hospital admissions or ED visits for all respiratory disease stratified by adults or older adults ( ≥ 65 years).______________________________________ 3-33
Figure 3.1-10. Relative risks (95% CI) for hospital admissi ons or emergency department visits for all respiratory causes, standardized from tw o-pollutant models adjusted for particle concentration. _______________________________________________________________ 3-34
Figure 3.1-11. Relative risks (95% CI) for hospital admissi ons or emergency department visits for all respiratory causes, standardized from two-po llutant models adjusted for gaseous pollutant concentration. _______________________________________________________________ 3-35
Figure 3.1-12. Relative Risks (95% CI) for hospital admi ssions or emergency department visits for asthma stratified by a ll ages or children. ___________________________________________ 3-36
Figure 3.1-13. Relative risks (95% CI) for hospital admissions or emergency department visits for asthma stratified by adults and older adults ( ≥ 65 years). ____________________________________ 3-37
Figure 3.2-1. Relative risks (95% CI) for associations of 24-h NO 2 (per 20 ppb) and daily 1-h max* NO 2 (per 30 ppb) with hospitalizations or emergency department visits for cardiac diseases.______ 3-47
Figure 3.2-2. Relative risks (95% CI) for associations of 24-h NO 2 (per 20 ppb) and daily 1-h max NO 2 * (per 30 ppb) with hospitalizations fo r all cerebrovascular disease. _______________________ 3-48xi Figure 3.3-1. Posterior means and 95% posterior interv als of national average estimates for NO 2 effects on total mortality from nonexternal causes at l ags 0, 1, and 2 within sets of the 90 cities with pollutant dat a available. ____________________________________________________ 3-50
Figure 3.3-2. Combined NO 2 mortality risk estimates from mult icity and meta-analysis studies.___________ 3-54
Figure 3.3-3. Combined NO 2 mortality risk estimates for broad caus e-specific categories from multicity studies. ____________________________________________________________________ 3-55
Figure 3.4-1. Decrements in forced expira tory volume in 1 s (FEV 1 ) associated with a 20-ppb increase in NO 2 (A) and a 20-μg/m 3 increase in PM 10 (B) in children, standardized per year of follow-up. ___________________________________________________________________ 3-57
Figure 3.4-2. Decrements in FVC associated with a 20-ppb increase in NO 2 (A) and a 20-μg/m 3 increase in PM 10 (B) in children, standardized per year of follow-up. _____________________ 3-58
Figure 3.4-3. Proportion of 18-year olds with a FEV 1 below 80% of the predicted value plotted against the average levels of pollutants from 1994 through 2000 in the 12 southern California communities of the Childr en’s Health Study.________________________________________ 3-59
Figure 3.4-4. Estimated annual growth in FEV 1 , of O 3 , PM 10 , and NO 2 in girls and boys. ________________ 3-60
Figure 3.4-5. Odds ratios for within-community bronc hitis symptoms associations with NO 2 , adjusted for other pollutants in two-pollutant models for the 12 communities of the Children’s Health Study. _____________________________________________________________________ 3-64
Figure 3.4-6. Biological pathways of long-term NO 2 exposure on morbidity. __________________________ 3-66
Figure 3.6-1. Age-adjusted, nonparametric sm oothed relationship between NO 2 and mortality from all causes in Oslo, Norw ay, 1992 through 1995. _______________________________________ 3-78
Figure 3.6-2. Total mortality relative risk esti mates from long-te rm studies. __________________________ 3-79
Figure 4.4-1. Fraction of the study populations living within a specified distance from roadways.__________ 4-11
Figure 5.3-1. Summary of epidemiologic studies examin ing short-term exposures to ambient NO 2 and respiratory out comes. __________________________________________________________ 5-7xiii 

# Acronyms and Abbreviations

1NP 1-nitropyrene
2NF 2-nitrofluoranthene 2NP 2-nitropyrene

α Alpha ACS American Cancer Society

a i air exchange rate (for microenvironment i ) AIRE (Italian Study) Asma Infantile Ricerca in Emilia-Romagna AM alveolar macrophages APEX Air Pollution Exposure (model) APHEA Air Pollution on Health: a European Approach (study) AQCD Air Quality Criteria Document AQS EPA’s Air Quality System ATS American Thoracic Society β beta; the calculated health effect parameter BAL bronchoalveolar lavage BALF bronchoalveolar lavage fluid
BHPN N- bis (2-hydroxy-propyl) nitrosamine BLF bronchial lavage fluid
Br bromide BTEX benzene, toluene, ethylb enzene, and o-, m-, p-xylene
C carbon
CAA Clean Air Act CALINE4 California line source dispersion (model) CAMP Childhood Asthma Management Program CAP(s) concentrated ambient particle(s)
CARB California Air Resources Board CASAC Clean Air Scientific Advisory Committee
CASTNet Clean Air Status and Trends Network
CDC Centers for Disease Control and Prevention CDPFs catalyzed diesel particle filters CFD computational fluid dynamics
CH 4 methane
CHAD Consolidated Human Activities Database CHF congestive heart failure CHS Children’s Health Study
CI confidence interval CMAQ EPA’s Community Multiscale Air Quality (CMAQ) model CMSA consolidated metropolitan statistical area
CO carbon monoxide
CO 2 carbon dioxidexiv COD coefficient of divergence
CoH coefficient of haze COPD chronic obstructive pulmonary disease CRP C-reactive protein CTM chemical transport model
CVD cardiovascular disease DEP diesel exhaust particle DEPcCBP diesel exhaust particle extract-coated carbon black particles DMA dimethylamine DMN dimethylnitrosamine DOAS differential optical absorption spectroscopy
EC elemental carbon ECP eosinophil cationic protein ED emergency department ECG electrocardiography ; electrocardiogram EGU(s) electricity generating unit(s) ELF epithelial lining fluid EPA U.S. Environmental Protection Agency EPO eosinophil peroxidase
ETS environmental tobacco smoke FEF forced expiratory flow
FEF 75 forced expiratory flow after exhaling 75% of FVC
FEF 25-75 average forced expiratory flow over middle 50% of FVC
FeNO fractional exhaled NO FEMs Federal Equivalent Methods
FEV 0.5 forced expiratory volume in 0.5 seconds
FEV 1 forced expiratory volume in 1 second

F

inf

i infiltration factor (for microenvironment i )
FRM Federal Reference Method FVC forced vital capacity GAM Generalized Additive Model(s) GIS Geographic Information System GLM Generalized Linear Model(s) GSH glutathione; reduced glutathione GST glutathione S -transferase (e.g., GSTM1, GSTP1, GSTT1)

H + hydrogen ion
H 2 O water
H 2 SO 4 sulfuric acid HCHO formaldehyde HDL high-density lipoprotein cholesterol
HNO 3 nitric acid
HONO nitrous acid
HR heart rate HRV heart rate variabilityxv HS hemorrhagic stroke
H 2 S hydrogen sulfide
HSO 4 – bisulfate ion
H 2 SO 4 sulfuric acid
h v solar ultraviolet photon
i microenvironment IARC International Agency for Research on Cancer
ICAM-1 intercellular adhesion molecule-1 ICD9 International Classification of Diseases, Ninth Revision ICDs implanted cardioverter defibrillators Ig immunoglobulin (e.g., IgA, IgE, IgG)
IHD ischemic heart disease IIASA International Institute for Applied Systems Analysis IL interleukin (e.g., IL-4, IL-6, IL-8)
IOM Institute of Medicine IQR interquartile range
IS ischemic stroke ISA Integrated Science Assessment ISAAC International Study of Asthma and Allergies in Children
K mass transfer coefficient
k i decay rate (for microenvironment i) KI potassium iodide
LIF laser induced fluorescence LOESS locally estimated smoothing splines LRD lower respiratory disease
MEF 25 maximal expiratory flow at 25%
MEF 50 maximal expiratory flow at 50% MENTOR Modeling Environment for Total Risk for One-Atmosphere MI myocardial infarction MMEF maximal midexpiratory flow
MoO X molybdenum oxide
MOZART-2 Model for Ozone and Rela ted Chemical Tracers, version 2 MPP multiphase processes MSA metropolitan statistical area N, n number of observations NAAQS National Ambient Air Quality Standards
NaAsO 2 sodium arsenite NAL inflammatory nasal lavage markers NAMS National Air Monitoring Stations NAPAP National Acid Precipitation Assessment Program NAS National Academy of Sciences
NCEA National Center for Environmental Assessment
NCEP National Center for Environmental Prediction NCICAS National Cooperative Inner-City Asthma Studyxvi NDMA N -nitrosodimethylamine NEI National Emissions Inventory NERL National Exposure Research Laboratory NHAPS National Human Activity Pattern Survey nitro-PAHs nitro-polycylic aromatic hydrocarbons
NK natural killer cells NLCS Netherlands Cohort Study on Diet and Cancer NMMAPS National Morbidity, Mortality, and Air Pollution Study
NMOR N- nitrosomorpholine NN nitronapthalene
NO nitric oxide
NO 2 - nitrite
NO 2 nitrogen dioxide
NO 3 - nitrate ion
NO 3 nitrate radical
NOAA National Oceanic and Atmo spheric Administration
NO X oxides of nitrogen
NO Y total oxidized nitrogen
NO Z oxidized N species NR not reported
NRC National Research Council NSA nitrosating agent
O 3 ozone OAQPS Office of Air Quality Planning and Standards OC organic carbon OH hydroxyl radical
OR odds ratio ORD Office of Research and Development
OVA ovalbumin P, p probability value PAARC Air Pollution and Chronic Respiratory Diseases (study) PAF paroxysmal atrial fibrillation PAH(s) polycyclic aromatic hydrocarbon(s) PAMS Photochemical Assessment Monitoring Stations PAN(s) peroxyacyl nitrate(s)
Pb lead PD20 provocative dose that produces a 20% decrease in FEV 1 PD100 provocative dose that produces a 100% increase in sRAW PEACE Pollution Effects on Asthmatic Children in Europe (study) PEF peak expiratory flow
P i penetration coefficient (for microenvironment i ) PIH primary intracerebral hemorrhage PM particulate matterxvii PM 2.5 particulate matter with 50% upper cut point aerodynamic diameter of 2.5 μm for sample collecti on; surrogate for fine PM
PM 10 particulate matter with 50% upper cut point aerodynamic diameter of 10 μm for sample collection
PM 10-2.5 particulate matter with 10 μm as upper cut point aerodynamic diameter and 2.5 μm as lower cut point for sample collection; surrogate for thoracic coarse PM (does not include fine PM) PMN(s) polymorphonuclear leukocyte(s)
PNO 3 - particulate nitrate POM particulate organic matter ppb parts per billion ppm parts per million ppt parts per trillion PRB policy-relevant background PT prothrombin time PS passive sample R, r correlation coefficient RADS reactive airway dysfunction syndrome RAPS (St. Louis) Regional Air Pollution Study RCS random component superposition (model)
RONO 2 organic nitrates RR rate ratio; relative risk RSV respiratory syncytial virus RTP Research Triangle Park SAPALDIA Study of Air Pollution and Lung Diseases in Adults
SCC Source Classification Codes SCE(s) sister chromatid exchange(s)
SD standard deviation
SES socioeconomic status SHEDS Simulation of Human Exposure and Dose System SIDS sudden infant death syndrome SNP single nucleotide polymorphism 35 S sulfur-35 radionuclide SLAMS State and Local Air Monitoring Stations
SO sulfur monoxide
SO 2 sulfur dioxide
SO 4 2– sulfate ion
SO X sulfur oxides sRaw specific airway resistance STN Speciation Trends Network

τ tau; atmospheric lifetime
TEA triethanolamine TNF tumor necrosis factor (e.g., TNF- α ) TSP total suspended particles UFP Ultrafine particles (<100 nm) URI upper respiratory infectionsxviii UV ultraviolet VIII-C factor Classic hemophilia A (factor VIII:C deficiency) VOC(s) volatile organic compound(s)
VWF von Willibrand Factor
WBC white blood cellxix 

# Authors, Contributors, Reviewers

Authors

Dr. Dennis J. Kotchmar (NO X Team Leader)—National Center for Environmental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC
Dr. Thomas J. Luben (NO X Team Leader)—National Center for Environmental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC
Dr. Ila L. Cote (Acting Division Director)—National Center for Environmental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC
Ms. Debra B. Walsh (Deputy Division Director)—National Center for Environmental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC
Dr. Mary A. Ross (Branch Chief)—National Center for Environmental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC
Dr. Jeffrey Arnold—National Center for Environmental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC
Mr. Chad Bailey—Office of Air Quality and Transpor tation, U.S. Environmental Protection Agency, Ann Arbor, MI
Dr. Kathleen Belanger, Yale University, Epid emiology and Public Health, New Haven, CT

Dr. James S. Brown—National Center for Environmental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC
Dr. Douglas Bryant—Cantox Environmental Inc., Mississauga, Ontario Canada
Mr. Allen Davis— Oak Ridge Institute for Science a nd Education, Research Fellow to National Center for Environmental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC
Dr. Mark Frampton—Strong Memorial Hospital, Rochester, NY
Dr. Janneane Gent—Yale University, CPPEE, New Haven, CT
Dr. Vic Hasselblad—Duke University, Durham, NC
Dr. Kazuhiko Ito—New York University School of Medicine, Tuxedo, NY
Dr. Jee Young Kim—National Center for Environmental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC

Dr. Ellen F. Kirrane—National Center for Envir onmental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC
Dr. Thomas C. Long—National Center for Environmental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC
Dr. Andrew Maier—Toxicology Excellence for Risk Assessment, Cincinnati, OHxx Dr. Qingyu Meng—Oak Ridge Institute for Science and Education, Postdoctoral Research Fellow to National Center for Environmental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC
Dr. Joseph P. Pinto—National Center for Environmental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC

Dr. Paul G. Reinhart—National Center for Envir onmental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC
Dr. Joseph Somers—Office of Air Quality and Trans portation, U.S. Environmental Protection Agency, Ann Arbor, MI
Dr. David J. Svendsgaard—National Center for Environmental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC

Dr. Lori D. White—National Center for Environmental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC



## Contributors

Dr. Dale Allen—Department of Atmospheric and O ceanic Sciences, University of Maryland, College Park, MD
Ms. Louise Camalier—Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC

Ms. Rebecca Daniels—National Center for Environmental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC
Dr. Russell Dickerson—Department of Atmospheric and Oceanic Science, University of Maryland, College Park, MD
Dr. Tina Fan—Environmental and Occupational Health Sciences Institute, Piscataway, NJ
Mr. William Keene—Department of Environmental Scien ces, University of Virginia, Charlottesville, VA
Dr. Randall Martin—Department of Physics and Atmo spheric Science, Dalhousie University, Halifax, Nova Scotia, Canada
Dr. Maria Morandi—Department of Environmental Scie nces, School of Public Health, University of Texas–Houston Health Science Center, Houston, TX
Dr. William Munger—Division of Engineering and A pplied Sciences, Harvard University, Cambridge, MA
Mr. Charles Piety—Department of Meteorology, University of Maryland, College Park, MD

Mr. Jason Sacks—National Center for Environmental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC
Dr. Sandy Sillman—Department of Atmospheric, O cean, and Space Sciences, University of Michigan, Ann Arbor, MI
Dr. Helen Suh—Department of Environmental Health , Harvard School of Public Health, Boston, MAxxi Dr. Charles Wechsler—Environmental and Occupati onal Health Sciences Institute, Piscataway, NJ
Dr. Clifford Weisel—Environmental and Occupati onal Health Sciences Institute, Piscataway, NJ
Dr. Jim Zhang—Environmental and Occupational Health Sciences Institute, Piscataway, NJ



## Reviewers

Dr. Tina Bahadori—American Chemistry Council, Arlington, VA
Dr. Timothy Benner—Office of Science Policy, U.S. Environmental Protection Agency, Washington, DC
Dr. Daniel L. Costa—National Program Director for Air, U.S. Environmental Protection Agency, Research Triangle Park, NC

Dr. Robert B. Devlin—National Health and E nvironmental Effects Research Laboratory, U.S. Environmental Protection Agency, Chapel Hill, NC
Dr. Judy Graham—American Chemistry Council, Arlington, VA
Dr. Stephen Graham—Office of Air Quality Planni ng and Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC
Ms. Beth Hassett-Sipple—Office of Air Quality Planni ng and Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC
Dr. Gary E. Hatch—National Health and Envi ronmental Effects Research Laboratory, U.S. Environmental Protection Agency, Research Triangle Park, NC
Dr. Scott Jenkins—Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC
Dr. David D. Kryak—National Exposure Research Laboratory, U.S. Environmental Protection Agency, Research Triangle Park, NC
Mr. John Langstaff—Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC
Dr. Morton Lippmann—Department of Environmenta l Medicine, New York University School of Medicine, Tuxedo, NY
Dr. Karen Martin—Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC

Dr. William McDonnell—William F. McDonne ll Consulting, Chapel Hill, NC
Dr. Dave McKee—Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC
Dr. Lucas M. Neas—National Health and Environmental Effects Research Laboratory, U.S. Environmental Protection Agency, Chapel Hill, NC
Dr. Russell D. Owen—National Health and Environmental Effects Research Laboratory, U.S. Environmental Protection Agency, Research Triangle Park, NCxxii Dr. Halûk A. Özkaynak—National Exposure Research Laboratory, U.S. Environmental Protection Agency, Research Triangle Park, NC
Dr. Jennifer Peel—Department of Environmental a nd Radiological Health Sciences, Colorado State University, Fort Collins, CO
Mr. Harvey Richmond—Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC
Mr. Steven Silverman—Office of General Counsel, U.S. Environmental Protection Agency, Washington, DC
Dr. Michael Stewart—Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC
Ms. Susan Stone—Office of Air Quality Planning and Standards, Office of Air and Radiation, U.S. Environmental Protection Agency, Research Triangle Park, NC
Ms. Chris Trent—Office of Air Quality Planning and Standards, Office of Air and Radiation, U.S. Environmental Protection Agency, Research Triangle Park, NC
Dr. John J. Vandenberg—National Center for Envir onmental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC
Dr. Alan F. Vette—National Exposure Research Laboratory, U.S. Environmental Protection Agency, Research Triangle Park, NC

Ms. Debra B. Walsh—National Center for Environm ental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC
Mr. Ronald W. Williams—National Exposure Research Laboratory, U.S. Environmental Protection Agency, Research Triangle Park, NCxxiii 

# NO X 

# Project Team

Executive Direction

Dr. Ila L. Cote (Acting Director)—National Center for Environmental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC
Ms. Debra B. Walsh (Deputy Director)—National Center for Environmental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC
Dr. Mary A. Ross—National Center for Environmental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC



## Scientific Staff

Dr. Dennis J. Kotchmar (NO X Team Leader)—National Center for Environmental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC
Dr. Thomas J. Luben (NO X Team Leader)—National Center for Environmental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC
Dr. Jeffrey Arnold—National Center for Environmental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC

Dr. James S. Brown—National Center for Environmental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC
Dr. Barbara Buckley—National Center for Environmental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC
Dr. Douglas Johns—National Center for Environmen tal Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC
Dr. Jee-Young Kim—National Center for Environmental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC

Dr. Ellen F. Kirrane—National Center for Envir onmental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC
Dr. Thomas C. Long—National Center for Environmental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC
Dr. Qingyu Meng—Oak Ridge Institute for Science and Education, Postdoctoral Research Fellow to National Center for Environmental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC
Dr. Joseph P. Pinto—National Center for Environmental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC

Mr. Jason Sacks—National Center for Environmental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NCxxiv Dr. David J. Svendsgaard—National Center for Environmental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC

Dr. Lori D. White—National Center for Environmental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC

Dr. William W. Wilson—National Center for Environm ental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC



## Technical Support Staff

Ms. Ellen Lorang—Information Manager, Nationa l Center for Environmental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC
Ms. Connie A. Meacham—Biologist, National Center for Environmental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC
Ms. Christine M. Searles—Management Analyst, National Center for Environmental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC
Ms. Deborah A. Wales—Information Services Specialis t, National Center for Environmental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC

Mr. Richard N. Wilson—Clerk, National Center for Environmental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NCxxv 

# Clean Air Scientific Advisory Committee Oxides of Nitrogen Primary NAAQS Review Panel

Chairperson

Dr. Rogene Henderson *, Scientist Emeritus, Lovelace Respiratory Research Institute, Albuquerque, NM



## Members

Mr. Ed Avol , Professor, Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA

Dr. John R. Balmes , Professor, Department of Medicine, Di vision of Occupational and Environmental Medicine, University of California, San Francisco, CA
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. Douglas Crawford-Brown *, Director, Carolina Environmental Program; Professor, Environmental Sciences and Engineering; and Professor, Public Po licy, Department of Environmental Sciences and Engineering, University of North Carolin a at Chapel Hill, Chapel Hill, NC
Dr. Terry Gordon , Professor, Environmental Medicine, NYU School of Medicine, Tuxedo, NY

Dr. Dale Hattis , Research Professor, Center for Technology, Environment, and Development, George Perkins Marsh Institute, Clark University, Worcester, MA

Dr. Donna Kenski , Data Analyst, Lake Michigan Air Directors Consortium, Des Plaines, IL
Dr. Patrick Kinney , Associate Professor, Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY
Dr. Steven Kleeberger , Professor, Laboratory Chief, Laboratory of Respiratory Biology, NIH/NIEHS, Research Triangle Park, NC
Dr. Timothy Larson , Professor, Department of Civil and Environmental Engineering, University of Washington, Seattle, WA

Dr. Kent Pinkerton , Professor, Regents of the University of California, Center for Health and the Environment, University of California, Davis, CA

Mr. Richard L. Poirot *, Environmental Analyst, Air Pollution Control Division, Department of Environmental Conservation, Vermont Agency of Natural Resources, Waterbury, VTxxvi Dr. Edward Postlethwait , Professor and Chair, Department of E nvironmental Health Sciences, School of Public Health, University of Alabama at Birmingham, Birmingham, AL

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. Jonathan M. Samet , Professor and Chair of the Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD
Dr. Richard Schlesinger , Associate Dean, Department of Biology, Dyson College, Pace University, New York, NY
Dr. Christian Seigneur , Vice President, Atmospheric and Environmental Research, Inc., San Ramon, CA
Dr. Elizabeth A. (Lianne) Sheppard , Research Professor, Biostatistics and Environmental & Occupational Health Sciences, Pub lic 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. George Thurston , Associate Professor, Environmental Medicine, NYU School of Medicine, New York University, Tuxedo, NY

Dr. James Ultman , Professor, Chemical Engineering, Bioengineering Program, Pennsylvania State University, University Park, PA

Dr. Ronald Wyzga , Technical Executive, Air Quality Health and Risk, Electric Power Research Institute, Palo Alto, CA



## SCIENCE ADVISORY BOARD STAFF

Dr. Angela Nugent , CASAC Designated Federal Officer 1200 Pennsylvania Avenue, N.W. Washington, DC, 20460 Phone: 202-343-9981 Fax: 202-233-0643 E-mail: nugent.angela@epa.gov
Physical/Courier/FedEx Address: Angela Nugent, Ph.D, EPA Science Advisory Board Staff Office Mail Code 1400F Woodies Building, Room 3614 1025 F Street, N.W. Washington, DC 20004 Telephone: 202-343-9981)

* Members of the statutory Clean Air Scientific Advisory Committee (CASAC ) appointed by the EPA Administratorxxvii 

# Preface

National Ambient Air Quality Standards (NAAQS) are promulgated by the U.S. Environmental Protection Agency (EPA) to meet requirements set forth in Sections 108 and 109 of the Clean Air Act (CAA). These sections require the EPA Administrator (1) to list widespread air pollutants that reasonably may be expected to endanger public health or welfare; (2) to issue air quality criteria that assess the latest available scientific information on the nature and eff ects of ambient exposure to the criteria pollutants; (3) to set “primary” NAAQS to protect human health with adequate margin of safety and to set “secondary” NAAQS to protect against welfare effects (e.g., effects on vegetation, ecosystems, visibility, climate, manmade materials, etc); and (4) to periodi cally review and revise, as appropriate, the criteria and NAAQS for a given listed pollutant or class of pollutants. The purpose of this Integrated Science Assessment (ISA) for Oxides of Nitrogen (NO X ) – Health Criteria is to critically evaluate and assess the lat est scientific information published since the 1993 NO X Air Quality Criteria Document (AQCD), with the ma in focus on pertinent new information useful in evaluating health effects data associated with ambi ent air nitrogen oxides exposures. A First External Review Draft of this ISA (dated August 2007) was re leased for public comment and was reviewed by the Clean Air Scientific Advisory Committee (CASAC) in October 2007; a Second External Review Draft was made available to the public in March 2008. Public comments and CASAC recommendations have been taken into account in making revisions to the doc ument for incorporation into this final ISA. This document will provide inputs to the risk and exposure analyses prepared by EPA’s Office of Air Quality Planning and Standards (OAQPS), which will lead to the proposal and, ultimately, promulgation of decisions on potential retention or revision, as a ppropriate, of the current Nitrogen Dioxide (NO 2 ) NAAQS by the EPA Administrator. Preparation of this document was coordinated by staff of EPA’s National Center for Environmental Assessment in Research Triangle Park (NCEA-RTP). NC EA-RTP scientific staff, together with experts from other EPA/Office of Research and Development (ORD) laboratories and academia, contributed to writing of document chapters. Earlier drafts of docum ent materials were reviewed by non-EPA experts in peer consultation workshops held by EPA. This ISA describes the nature, sources, distribution, measurement, and concentrations of nitrogen oxides in outdoor (ambient) and indoor environments. It also evaluates the latest data on human exposures to ambient nitrogen oxides and consequent health effects in exposed human populations, to support d ecision making regarding the primary (health-based) NO 2 NAAQS. NCEA acknowledges the valuable contributions provi ded by authors, contributors, and reviewers and the diligence of its staff in the preparation of this document.



## Legislative Requirements
Two sections of the CAA govern the establishmen t and revision of the NAAQS. Section 108 (U.S. Code, 2003a) 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 stationa ry sources” and to issue air quality criteria for those that are listed. Air quality criteria are intended to “accu rately reflect the latest scientific knowledge useful in indicating the kind and extent of identifiable effect s on public health or welfare which may be expected from the presence of [a] pollutant in ambient air.” Section 109 (U.S. Code, 2003b) directs the Administ rator to propose and promulgate “primary” and “secondary” NAAQS for pollutants listed 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 onxxviii such criteria and allowing an adequate margin of safety, are requisite to protect the public health.” 1 A secondary standard, as defined in Section 109(b)(2), mu st “specify a level of air quality the attainment and maintenance of which, in the judgment of the Ad ministrator, based on such criteria, is required to protect the public welfare from any known or anticipat ed adverse effects associated with the presence of [the] pollutant in the ambient air.” 2 The requirement that primary standards include an adequate margin of safety was intended to address uncertainties associated with inconclusive scien tific and technical information available at the time of standard setting. It was also intended to pr ovide a reasonable degree of protection against hazards that research has not yet identified. See Lead Industries Association v. EPA, 647 F.2d 1130, 1154 (D.C. Cir 1980), cert. denied, 449 U.S. 1042 (1980); American Petroleum Institute v. Costle, 665 F.2d 1176, 1186 (D.C. Cir. 1981), cert. denied, 455 U.S. 1034 (1982). Both kinds of uncertainties are components of the risk associated with pollution at levels below tho se 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 seeks to limit pollution le vels demonstrated to be harmful as well as lower pollutant levels that may pose an unacceptable risk of harm, even if the nature or degree of risk is not precisely identified. In selecting a margin of safety, EPA considers such factors as the nature and severity of the health effects involved, the size of sensitive population(s) at risk, and the kind and degree of the uncertainties that must be addressed. The selection of any particul ar approach to providing an adequate margin of safety is a policy choice left specifically to the Admi nistrator’s judgment. See 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 ar e 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, 465-472, and 475-76 (U.S. Supreme Court, 2001). Section 109(d)(1) requires that “not later than December 31, 1980, and at 5-year intervals thereafter, the Administrator shall complete a t horough review of the criteri a 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 a ppropriate...” Section 109(d)(2) requires that an independent scientific review committee “shall comp lete 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 sta ndards as may be appropriate...” Since the early 1980s, this independent review function has been performed by CASAC.



## History of Reviews of the Primary NAAQS for NO 2 On April 30, 1971, EPA promulgated identical primary and secondary NAAQS for NO 2 , under Section 109 of the Act, set at 0.053 parts per million (ppm), annual average (Federal Register, 1971). In 1982, EPA published Air Quality Criteria for Oxides of Nitrogen (1982 NO X AQCD) (U.S. Environmental Protection Agency, 1982), which update d the scientific criteria upon which the initial NO 2 standards were based. On February 23, 1984, EPA propo sed to retain these standards (Federal Register, 1984). After taking into account public comments, EPA published the final decision to retain these standards on June 19, 1985 (Federal Register, 1985).

1 The legislative history of Section 109 i ndicates that a primary standard is to be se t at “the maximum permissible ambient air level...which will protect

the health of any [sensitive] group of the population” and that, for this purpos e, “reference should be made to a representativ e sample of persons comprising the sensitive group rat her than to a single person in su ch a group” [U.S. Senate, 1970].
2 Welfare effects as defined in Section 302(h) [U.S. Code, 2005] include, but are not limited to, “effects on soils, water, crop s, vegetation, man-made materials, animals, wildlife, weather, visibility and climate, damage to and deterio ration of property, and hazards to transpor tation, as well as effects on economic values and on pers onal comfort and well-being.”xxix On July 22, 1987, EPA announced it was undertaking plans to revise the 1982 NO X air quality criteria (Federal Register, 1987). In November 1991, EPA released an updated draft AQCD for CASAC and public review and comment (Federal Register , 1991). The draft document provided a comprehensive assessment of the available scientific and technical in formation on health and welfare effects associated with NO 2 and other oxides of nitrogen. CASAC reviewed the document at a meeting held on July 1, 1993, and concluded in a closure letter to the Administ rator that the document “provides a scientifically balanced and defensible summary of current knowledge of the effects of this pollutant and provides an adequate basis for EPA to make a decision as to the appropriate NAAQS for NO 2 ” (Wolff, 1993). EPA prepared a draft Staff Paper that summarized and integrated the key studies and scientific evidence contained in the revised AQCD and identified the critical elements to be considered in the review of the NO 2 NAAQS. The Staff Paper received external review at a December 12, 1994 CASAC meeting. CASAC comments and recommendations were re viewed by EPA staff and incorporated into the final draft of the Staff Paper as appropriate. CASAC re viewed the final draft of the Staff Paper in June 1995 and responded by written closure letter (Wolff, 1996). In September of 1995, EPA finalized the document entitled, “Review of the National Ambien t Air Quality Standards for Nitrogen Dioxide Assessment of Scientific and Technical Informati on” (U.S. Environmental Protection Agency, 1995). Based on that review, the Administrator announced her proposed decision not to revise either the primary or the secondary NAAQS for NO 2 (Federal Register, 1995). The decision not to revise the NO 2 NAAQS was finalized after careful evaluation of the comments received on the proposal. The level for both the existing primary and secondary NAAQS for NO 2 is 0.053 ppm annual arithmetic average, calculated as the arithmetic mean of the 1-h NO 2 concentrations. The current review was initiated on December 9, 2005 (70 FR 73236) with a request for submission of recent scientific information on specified topics. EPA ’s draft Integrated Review Plan for the Primary National Ambient Air Quality Standard for Nitrogen Dioxide was made available in February, 2007 for public comment and was discussed by the Clean Air Science Advisory Committee (CASAC) via a publicly accessible teleconference consultation on May 11, 2007 (72 FR 20336). The first external review draft of this ISA was released for public comment and review by CASAC on August 31, 2007 (72 FR 50107), and was reviewed by CASAC at a public m eeting held on October 24-25, 2007. The second draft of this ISA was released for public comment and review by CASAC in Ma rch 2008 (73 FR 11916), and was reviewed by CASAC at a public meeting held on May 1-2, 2008.1-1 

# Chapter 1. Introduction

This concise evaluation and synthesis of the mo st policy-relevant science forms the scientific foundation for the review of the primary (health-based) NAAQS for nitrogen dioxide (NO 2 ) currently set at 0.053 ppm, annual average. Its intent is to “accurate ly reflect the latest scientific knowledge useful in indicating the kind and extent of all identifiable effects on public health or welfare which may be expected from the presence of such pollutant in ambient air” (Clean Air Act, Section 108, 2003). 1 Key information and judgments from the previous AQCDs for NO X are incorporated in this assessment. Details of the pertinent scientific literature published since the last review and selected older studies of particular interest are included in annexes. The terms “oxides of nitrogen” or “nitrogen oxi des” refer to all forms of oxidized nitrogen compounds, including nitric oxide (NO), NO 2 , and all other oxidized nitrogen-containing compounds transformed from NO and NO 2 (defined further in Chapter 2, Section 2.1). Descriptions of the atmospheric chemistry of NO X include both gaseous and particulate species; a meaningful analysis would not be possible otherwise. Most studies on the health effects of gaseous NO X focus on NO 2 ; effects of other gaseous species are considered as information is available. The health effects of particulate NO X are included in the review of the NAAQS for particulat e matter (PM). In evaluating the health evidence, possible influences of other co-occurring atmosphe ric pollutants such as PM, sulfur dioxide (SO 2 ), carbon monoxide (CO), and ozone (O 3 ) are considered. The Integrated Plan for the Review of the Pr imary National Ambient Air Quality Standard for Nitrogen Dioxide (U.S. Environmental Protection Agen cy, 2007) identifies key policy-relevant questions which provide a framework for review of th e scientific evidence. These questions are:

 Has new information altered the scientific support for the occurrence of health effects following short- and/or long-term exposur e to levels of nitrogen oxides found in the ambient air?

 What do recent studies focused on the near-roadway environment tell us about health effects of nitrogen oxides?

 At what levels of nitrogen oxides exposure do health effects of concern occur?

 Has new information altered conclusions from pr evious reviews regarding the plausibility of adverse health effects caused by exposure to nitrogen oxides?

 To what extent have important uncertainties identifie d in the last review been reduced and/or have new uncertainties emerged?

 What are the air quality relationships between s hort- and long-term exposures to nitrogen oxides?



# 1.1. Document Development

The EPA initiated the current review of the NO 2 NAAQS in the Federal Register with a call for information (U.S. Environmental Protection Agency , 2005). Publications were identified through an extensive literature search process; additional publicati ons were identified by EPA scientists in a variety of disciplines. In addition to peer-reviewed literatu re, previous EPA reports and materials obtained from scouring reference lists were examined. All relevant epidemiologic, human clinical, animal toxicological, and in vitro studies, including those related to expos ure-response relationships, mechanism(s) of action,

1 The secondary NO x NAAQS, in conjunction with a re view of the secondary NAAQS for SO x , is underway independently, as is a review of the primary NAAQS for SO x, and a review of the primary and secondary effects of PM.1-2 or susceptible subpopulations published since the last re view were considered. In addition, EPA conducts analyses of air quality and emissions data, and evalua tes studies on atmospheric chemistry, transport, and fate of these emissions, as well as issues related to exposure. Further information was acquired from consultation with content and area experts, CASA C and the public. Annex AX1 has more discussion of search strategies and considerations for study inclusion.



# 1.2. Document Organization

The ISA has five chapters. The introduction pr esents background information, discusses the ISA’s purpose, search and study evaluation process, and sets the framework for causal determination. Chapter 2 highlights key concepts for understanding the atmospheri c chemistry, sources, exposure, and dosimetry of NO X , following a “source-to-exposure” paradigm. Chapte r 3 evaluates and integrates epidemiologic, human clinical, and toxicological data as it pertains to review of the primary NAAQS. Chapter 4 deals with the public health impact of ambient NO X exposure, with an emphasis on susceptible and vulnerable population groups. Lastly, Chapter 5 summarizes key findings and conclusions from the atmospheric sciences, ambient air data analyses, exposur e assessment, dosimetry, and health effects. The annexes supplement the ISA with additiona l details from the recent literature, as well as selected older studies of particular interest. They contain information on:

 framework for causal determination (Annex 1);

 atmospheric chemistry of NO X , sampling, and analytic methods (Annex 2);

 environmental concentrations and human exposure (Annex 3);

 toxicological studies of health effects in laboratory animals (Annex 4);

 human clinical studies of health effects re lated to short-term exposure (Annex 5); and

 epidemiologic studies of health effects from short- and long-term exposure (Annex 6).



# 1.3. EPA Framework for Causal Determinations

A consistent and transparent basis for evaluating the causal nature of air pollution-induced health effects is important. EPA’s framework uses standa rdized language, drawing on other agencies and the scientific community, especially from the National A cademy of Sciences (NAS) Institute of Medicine (IOM) document, Improving the Presumptive Disability Decision-Making Process for Veterans (Institute of Medicine, 2007). This section:

 describes the type of scientific evidence used in establishing a causal relationship between exposure and health effects;

 defines cause, in contrast to statistical association;

 discusses the sources of evidence n ecessary to reach a conclusion about the existence of a causal relationship;

 highlights the issue of multifactorial causation;

 identifies issues and approaches related to uncertainty; and1-3  provides a framework for classifying and character izing the weight of evidence in support of a general causal relationship. Approaches to assessing the separate and combined lin es of evidence (e.g., epidemiologic, animal toxicological, human clinical, and in vitro studies) ha ve been formulated by a number of regulatory and science agencies in addition to the IOM, including the International Agency for Research on Cancer (IARC, 2006), EPA Guidelines for Carcinogen Risk A ssessment (U.S. Environmental Protection Agency, 2005), Centers for Disease Control and Prevention (2004), and the National Acid Precipitation Assessment Program (NAPAP, 1991). (See Annex AX1 for excerpts from these documents.) These approaches are similar in nature, although adapted to different purposes, and have proven effective in providing a uniform structure and language for causal determinations ̧ and support decision-making under conditions of uncertainty.



# 1.3.1. Scientific Evidence Used in Establishing Causality

The most compelling evidence of a causal relati onship between pollutant exposure and health effects comes from human clinical studies, which eval uate health effects of administered exposure under controlled laboratory conditions. In epidemiologic or observational studies of humans, the investigator does not control exposure or intervene with the study population. Observational studies can describe associations between exposure and effect; study designs include cross-sectional, case-control, cohort, time-series, and panel studies. “Natural experiments” occur occasionally, and compar e health effects before and after an exposure change, such as closure or elimination of a polluti on source. They can provide compelling evidence of causality. Experimental animal data complement clin ical and observational data. These studies help characterize effects of concern, exposure-response relationships, sensitive s ubpopulations, and modes of action. In the absence of clinical or epidemiol ogic data in cases where humans are assumed or known to respond similarly to the experimental species, animal data alone may be sufficient to support a likely causal determination.



# 1.3.2. Moving from Association to Causation

“Cause” explains a significant, effectual relations hip between an agent and an associated disorder or disease. “Association” is the statistical dependen ce among events, characteristics, or other variables. An association is prima facie evidence for causation; alone, however, it is insufficient proof of a causal relationship between exposure and disease. Unlike an asso ciation, a causal claim supports the creation of counterfactual claims; that is, a claim about what the world would have been like under different or changed circumstances (Institute of Medicine, 2007). Mu ch of the newly available health information evaluated in this ISA comes from epidemiologic st udies that report a statistical association between exposure and health outcome. Many of the health outcomes reported in these st udies have complex etiologies. The diseases, such as asthma, coronary heart disease or cancer are typically initiated by a web of multiple agents. Outcomes depend on a variety of factors, such as age, genetic susceptibility, nutritional status, immune competence, and social factors, as shown in Figure 1.3-1 (Gee a nd Payne-Sturges, 2004; Institute of Medicine, 2007). Further, exposure to a combination of agents could cause synergistic or antagonistic effects. Thus, net effects are the result of many actions and counteractions. Moving from association to causation involves elim inating alternative explanations for the association. Controlled human exposure studies, or human clinical studies, randomly allocate subjects groups, usually called study and cont rol groups, and exposed to a pollutant or a sham, respectively. Results are assessed by rigorous comparison of rates of relevant outcomes between the groups. This type1-4 of study is generally regarded as the most scientifically rigorous method of hypothesis testing. By assigning exposure randomly, the study design attempts to remove the effect of factors that influence exposure. Only a causal relationship between e xposure and health outcome should produce observed associations in randomized clinical trials. In another type of human clinical study, a subject is exposed to a pollutant and a sham at different points in time, and the responses are compared. This design effectively controls for potential confounders, since the subject serves as his or her own control.

Figure 1.3-1. Exposure–disease–stress model fo r environmental health disparities.

A lack of observable effects from human clini cal studies does not necessarily mean that a causal relationship does not occur. One limitation is a small study population, which restricts the ability to discern statistically significant findings. These studies are also confined to limited real-world conditions that can be feasibly studied. In addition, the most susceptible individuals or groups may be explicitly excluded, such as those with nutritional deficits, for practical and ethical reasons. Inferring causation from epidemiologic studies requires consideration of uncertainties, particularly potential confounders. One way to re move spurious association is through statistical control of these potential confounders, a method termed “adjustment.” Multivariable regression models are an example of a tool for estimating the association between exposure and outcome that involves such adjustment. Study designs that include matching of case and cont rol exposure groups can also address confounding.1-5 Likewise, stratified analysis, i.e., examining the association within homogeneous groups of the confounding variable, controls for confounders. Stratified analyses ha ve an additional benefit: the examination of effect modification through comparis on of the effect estimates across different groups. If investigators successfully measure ch aracteristics that distort results, the method’s adjustment helps separate a spurious from a true causal association. Appropriate statistical adjustment for confounders requires identification and measurement of all reasonably expected confounders. Measurement error is another problem encountered when adjusting for spurious associations. In multivariate analyses in the time series study design, the effects of a well-measured covariate may be overestimated, in contrast to a more poorly measu red covariate. Several components contribute to exposure measurement error in these studies, includi ng differences between true and measured ambient concentrations, differences between average pers onal exposure to ambient pollutants and ambient concentrations at central monitoring sites, and the use of average population exposure rather than individual exposure estimates. Confidence that unmeasured confounders are not bi asing the results is increased when multiple studies are conducted in various settings using diffe rent subjects or exposures. Thus, multicity studies which use a consistent method to analyze data from acr oss locations with different levels of covariates can provide insight on potential confounding in associ ations. The number and degree of diversity of covariates, as well as their relevance to the potential confounders, remain matters of scientific judgment. Intervention studies, because of their experimental natu re, can be particularly useful in characterizing causation. In addition to clinical and epidemiologic studies, the tools of experimental biology are valuable for providing insight into human physiology and pathology . Laboratory tools have been extended to explore the effects of putative toxicants on human health, especially through the study of model systems in other species. Background knowledge of the biological mechan isms involved can prove crucial in establishing, or negating, a causal claim. On the other hand, sp ecies can differ from each other in fundamental aspects of physiology and anatomy (e.g., metabolism, airway branching, hormonal regulation) that may hamper extrapolation. Testable hypotheses about the causal na ture of proposed mechanisms or modes of action are central to utilizing experimental data in causal determinations.



# 1.3.3. Multifactorial Causation

Scientific judgment regarding likely sources and magnitude of confounding, as well as the pros and cons of various existing study designs, results, and anal yses is crucial. One key consideration in this ISA was the evaluation of the potential contribution of NO X to health effects, when it is a component of a complex air pollutant mixture. There are multiple ways by which NO X might cause or be associated with adverse health effects. First, the reported NO X effect estimates in epidemiologic studies may reflect independent NO X effects on respiratory health. Second, ambient NO X may be serving as an indicator of complex ambient air pollution mixtures that share the same source, such as motor vehicles or electricity generation. Finally, copollutants may mediate the effects of NO X , or NO X may influence the toxicity of copollutants. These relationships are illustrated in Figure 1.3-2. Epidemiologists use the terms “interaction” and “eff ect modification” to denote the departure of the observed joint risk from expectations based on the sep arate effects of the factors. These possibilities are not necessarily exclusive. In addition, confounding can r esult in the fabrication of an association between adverse health effects and NO X that is actually attributable to another factor closely associated with NO X . Multivariate models are the most widely used stra tegy to address confounding in epidemiologic studies, but such models are not readily interpreted when assessing effects of covarying pollutants such as PM, CO, O 3 , and SO 2 .1-6 

# 1.3.4. Uncertainty

The science of estimating the causal influence of an exposure on disease is an uncertain one. There are two distinct levels of uncerta inty to be considered here:

 Model uncertainty—uncertainty regarding gaps in scientific theory required to make predictions on the basis of causal inferences.

 Parameter uncertainty—uncertainty as to th e statistical estimates within each model.

Assessment of model uncertainty involves: (1) wh ether exposure causes the health outcome; (2) the set of confounders associated with exposure and h ealth outcome; (3) which parametric forms best describe the relationships among exposure, confounders , and outcome; and (4) whether other forms of bias could be affecting the association.

Figure 1.3-2. Potential relationships of NO X with adverse health effects.1-7 

# 1.3.5. Application of Framework

EPA uses a two-step approach to evaluate the sci entific evidence on health effects of exposure to criteria pollutants. These two steps address two policy-re levant questions noted above – what are (if any) the effects of NO X on susceptible populations, given the total body of evidence, and at what levels of NO X exposure do health effects of concern occur. The first step determines the weight of evidence in support of causation and characterizes the strength of any resu lting causal classification. The second step includes further evaluation of the quantitative evidence regardi ng the concentration-response relationships and the levels, duration and pattern of exposures at which effects are observed. To aid judgment, various “aspects” 1 of causality have been discussed by many philosophers and scientists; the most widely cited were articulated by Sir Austin Bradford Hill in 1965 (Centers for Disease Control and Prevention, 2004; EPA, 2005; IARC, 2006; Institute of Medicine, 2007). These elements (Hill, 1965) have been modified (below) for use in causal determinations specific to health and environmental effects and pollutant exposures. 2

Table 1.3-1. Aspects to aid judging causality.

1. Consistency of the observed association. An inference of causality is strengthened when a pattern of elevated risks is observed across sev eral independent studies. The reproducibility of findings constitutes one of the strongest argumen ts for causality. If there are discordant results among investigations, possible reasons such as di fferences in exposure, confounding factors, and the power of the study are considered.

2. Strength of the observed association. The finding of large, precise risks increases confidence that the association is not likely due to chance, bias, or other factors. A modest risk, however, does not preclude a causal association and may reflect a lower level of exposure, an agent of lower potency, or a common disease with a high background level.

3. Specificity of the observed association. As originally intended, this refers to increased inference of causality if one cause is associated with a single effect or disease. Based on our current understanding this is now considered one of the weaker guidelines for causality; for example, many agents cause respiratory disease and respiratory disease has multiple causes. The ability to demonstrate specificity under certain c onditions remains, however, a powerful attribute of experimental studies. Thus, although the presence of specificity may support causality, its absence does not exclude it.

4. Temporal relationship of the observed association. A causal interpretation is strengthened when exposure is known to precede development of the disease.

5. Biological gradient (exposure-response relationship). A clear exposure-response relationship (e.g., increasing effects associated with greater exposure) strongly suggests cause and effect, especially when such relationships ar e also observed for duration of exposure (e.g., increasing effects observed following longer exposure times). There are, however, many possible reasons that a study may fail to detect an exposure-response relations hip. Thus, although the presence of a biological gradient may support causality, the absence of an exposure-response relationship does not exclude a causal relationship.

1 The “aspects” described by Hill (1965) have become, in the subs equent literature, more commonly described as “criteria.” The or iginal term “aspects”

is used here to avoid confusion with ‘criteria’ as it is used, with di fferent meaning, in the Clean Air Act.
2 The Hill apects were developed for use with epidemiology data. They have been modified here for use with a broader array of da ta, i.e.,

epidemiologic, human clinical, and anima l toxicologic studies, as well as in vitro data, and to be more consist ent with EPA’s Guidelines for Carcinogen Risk Assessment.1-8 6. Biological plausibility . An inference of causality tends to be strengthened by consistency with data from experimental studies or othe r sources demonstrating plausible biological mechanisms. A lack of biological understanding, however, is not a reason to reject causality.

7. Coherence. An inference of causality may be strengthened by other lines of evidence that support a cause-and-effect interpretation of the asso ciation. For instance, similar findings between clinical and animal studies, or closely related hea lth effects, which are expected to be associated with exposure, are in fact observed together. Th e absence of other lines of evidence, however, is not a reason to reject causality.

8. Experimental evidence (from human populations). Experimental evidence is generally available from human populations for the criteria pollutants. The strongest evidence for causality can be provided when a change in exposure brings about a change in adverse health effect or disease frequency in either clinical or obser vational studies (e.g., natural experiments, intervention studies).

9. Analogy. Structure activity relationships and information on the agent’s structural analogs can provide insight into whether an association is causal. Similarly, information on mode of action for a chemical, as one of many structural analogs, can inform decisions regarding likely causality. While these aspects provide a framework for assessing the evidence, they do not lend themselves to consideration in terms of simple formulas or fixe d rules of evidence leading causality conclusions. A tallying of studies reporting statistically significant or nonsignificant results does not point toward credible conclusions about the relative weight of the evidence and the likelihood of causality. Rather, these considerations are taken into account with th e goal of producing an objective appraisal of the evidence, informed by peer and public comment and a dvice. The principles in Table 1.3-1 cannot be used as a strict checklist, but rather as a determination of the weight of the evidence for inferring causality. In particular, the absence of one or more of the pr inciples does not automatically exclude a study from consideration (e.g., see discussion in Centers for Disease Control and Prevention, 2004).



# 1.3.6. First Step—Determination of Causality

To draw conclusions on the causal relationships between relevant polluta nt exposures and health outcomes, EPA assessed results from recent publications, in light of evidence available from the previous NAAQS review. Using a five-level hierarchy to classify the overall weight of evidence for causation, not just association (see Table 1.3-2), EPA drew on the work of previous evaluations, most prominently the IOM’s Improving the Presumptive Disability Decision-Making Process for Veterans (Institute of Medicine, 2007), EPA’s Guidelines for Carcinogen Risk Assessment (U.S. Environmental Protection Agency, 1986), and the U.S. Surgeon General’s repor t on the benefits of smoking cessation (Centers for Disease Control and Prevention, 2004). These efforts ar e presented in more detail in Annex AX1. The weight of evidence evaluation is based on various lin es of evidence from human clinical, epidemiologic, animal studies, and in vitro studies. The separate judgments are then integrated into a qualitative statement about the overall weight of the evidence and causality.1-9 

# 1.3.7. Second Step—Evaluation of Population Response

Beyond judgments regarding causality are questions re levant to characterizing exposure and risk to populations; in other words, at what levels do health effects occur? Such questions include:

 What is the concentration-response relationship?

 Under what exposure conditions (dose or expos ure, duration and pattern) are effects seen?

 What population groups appear to be affected or more susceptible to effects?

Table 1.3-2. Weight of evidence for causal determ ination (adapted from Institute of Medicine, 2007).

Sufficient to infer a causal relationship Evidence is sufficient to conclude that there is a causal relationship between relevant pollutant exposure and the out come. Causality is supported when an association has been observed between the pollutant and the outcome in studies in which chance, bias, and confounding could be ruled out with reasonable confidence. That is, human clinical studies provide the strongest evidence for causality. Causality is also supported by findings from epidemiologic “natural experiments” or observational studies supported by other lines of evidence. Generally, determination is based on multiple studies from more than one research group.

Sufficient to infer a likely causal relationship (i.e., more likely than not). Evidence is sufficient to conclude th at there is a likely causal association between relevant pollutant exposures a nd the outcome. That is, an association has been observed between the pollutant and the outcome in studies in which chance, bias and confounding are minimized, but uncertainties remain. For example, observational studies show associations but confounding and other issues are difficult to address and/or ot her lines of evidence (human clinical, animal, or mechanism of action information) are limited or inconsistent. Generally, determination is based on multiple studies from more than one research group.
Suggestive, but not sufficient to infer a causal relationship Evidence is suggestive of an associati on between relevant pollutant exposures and the outcome, but is weakened because chance, bias and confounding cannot be ruled out. For example, at least one high-quality study shows an association, while the results of other studies are inconsistent.
Inadequate to infer the presence or absence of a causal relationship The available studies are inadequate to infer the presence or absence of a causal relationship. That is, studies are of insufficient quality, consistency or statistical power to permit a conclusion regarding the presence or absence of an association between relevant pollu tant exposure and the outcome. For example, studies which fail to control for confounding or which have inadequate exposure assessment, fall into this category.
Suggestive of no causal relationship The available studies are suggestive of no causal relationship. That is, several adequate studies, examining relati onships between relevant population exposures and outcomes, and consid ering sensitive subpopulations, are mutually consistent in not showing an association between exposure and the outcome at any level of exposures. In addition, the possibility of a small elevation in risk at the levels of exposure studied can never be excluded.1-10 On the population level, causal and likely causal claims typically characterize how risk—the probability of health effects—changes in response to exposure. Generally, the response is evaluated within the range of observation, which is determin ed by the type of study and methods of exposure measurement. Extensive human data to inform risk an alyses exists for all criteria pollutants, unlike most other environmental pollutants. Animal data also can inform concentration-response, particularly relative to dosimetry, mechanisms of action, and characteristics of sensitive subpopulations. An important consideration in characterizing the public health impacts associated with exposure to a pollutant is whether the concentration-response rela tionship is linear across the full concentration range encountered, or whether nonlinear relationships exist along any part of this range. Of particular interest is the shape of the concentration-res ponse curve at and below the level of the current standard. The complex molecular and cellular events that underlie cancer a nd noncancer toxicity are likely to be both linear and nonlinear, and vary depending on concentration. A dditionally, many factors may act by perturbing naturally occurring background processes related to disease. At the human population level, various sources of variability and uncertainty tend to smooth and “linearize” the concentration-response function, such as low data density in the lower concentration range, possible influence of measurement error, and individual differences in susceptibility to air pollution health effects. These attributes of popula tion concentration-response may explain why the available human data at ambient concentrati ons for some environmental pollutants (e.g., O 3 , lead [Pb], PM, secondhand tobacco smoke, radiation) do not exhibit evident thresholds for health effects, even though likely mechanisms of action include nonlinear processes. These attributes of human population concentration-response relationships have been ex tensively discussed in the broader epidemiologic literature (e.g., Rothman and Greenland, 1998).2-1 

# Chapter 2. Source to Exposure

2.1. Introduction

This chapter provides concepts and findings rela ting to emissions sources, atmospheric science, human exposure assessment, and human dosimetry. The order of these topics essentially follows that given in the National Research Council paradigm fo r integrating air pollutant research (NRC, 2004) as shown in Figure 2.1-1. This chapter is meant to serve as a prologue for detailed discussions on the evidence on health effects that follow in Chapters 3 and 4, and as a source of information to help interpret those effects against data about atmos pheric concentrations and exposures.

Source: Adapted from National Research Council (2004).
Figure 2.1-1. A generalized conceptual model for integrating research on NO X pollution and human health effects.

The definition of “nitrogen oxides,” as it appears in the NAAQS legislation, differs from the one commonly used in air pollution research and control co mmunities. In this document, the terms “oxides of nitrogen” and “nitrogen oxides” (NO X ) refer to all forms of oxidized nitrogen ( N ) compounds, including NO, NO 2 , and all other oxidized N- containing compounds formed from NO and NO 2 . 1 NO and NO 2 , along with volatile organic compounds (VOCs), anthropogenic and biogenic hydrocarbons, aldehydes, etc., and CO, are precursors in the formation of O 3 and photochemical smog. NO 2 is an oxidant and can react to form other photochemical oxidants, including organic nitrates (RONO 2 ) like the peroxyacyl nitrates (PANs). NO 2 can also react with toxic compounds such as polycyclic aromatic hydrocarbons (PAHs) to form nitro- PAHs, some of which are more toxic than either reactant alone. NO 2 and SO 2 , another EPA criteria air pollutant, can also be oxidized to form the strong mineral acids nitric acid (HNO 3 ) and sulfuric acid (H 2 SO 4 ), thereby contributing to the acidity of cloud, fog, and rainwater, as well as ambient particles.

1 This follows usage in the Clean Air Act Section 108(c): “Such criteria [for oxides of nitrogen] shall include a discussion of nitric and nitrous acids,

nitrites, nitrates, nitrosami nes, and other carcinogenic and potentia lly carcinogenic derivatives of oxides of nitrogen.” By co ntrast, within the air pollution research and control communities, the terms “oxides of nitrogen” and “nitrogen oxides” are restricted to refer only t o the sum of NO and NO 2 , and this sum is commonly abbreviated as NO X . The category label used by this community for the sum of all forms of oxidized nitrogen compounds including those list ed in Section 108(c) is NO Y
.2-2 

# 2.2. Sources and Atmospheric Chemistry

The role of NO X in O 3 formation was reviewed in the Air Quality Criteria for Ozone and Related Photochemical Oxidants (U.S. Environmental Prot ection Agency, 2006a). Mechanisms for transporting O 3 precursors including NO X , the factors controlling the efficiency of O 3 production from NO X , methods for calculating O 3 from its precursors, and methods for measuring total oxidized nitrogen (NO Y ) were all reviewed the 2006 O 3 AQCD. The chemistry of reactive, oxidized N compounds in the atmosphere is summarized in Figure 2.2-1.



# 2.2.1. Sources of NO X Both anthropogenic and natural (biogenic) processes emit NO X . NO X is emitted by combustion sources as mainly NO with smaller quantities of NO 2 . The major sources of NO X in the U.S. are listed in Table 2.2-1 (see Annex Table AX2-3 for more deta il). On-road mobile sources constitute the largest source of NO X followed by electricity generating units (E GUs) and non-road mobile sources. Stationary engines and industrial facilities also emit NO X , but because they are fewer in number or burn less fuel, their mass contribution is relatively smaller. It shoul d be remembered in viewing Table 2.2-1 that the values shown are nationwide averages and may not refl ect relative contributions of the different sources to ambient NO 2 at any given location and to an individual’s exposures to NO 2 .

Table 2.2-1. Annual 2002 average anthropogenic NO X emissions in the U.S. (million metric tons).

SOURCE CATEGORY EMISSIONS

On-Road Mobile Sources 7.4

Electricity-Generating Units 4.3

Non-Road Mobile Sources 4.0

Industrial/Comme rcial/Residential Fuels 2.3

Industrial Processes 1.1

Prescribed Fires 0.19

Waste Disposal 0.10

Residential Wood 0.04

Fertilizers and Livestock 0.019

Miscellaneous 0.011

Road Dust <0.01

Solvent Use 0.0082

TOTAL 19.4

Source: NEI 2002 Emissions Booklet (U.S. Environmental Protection Agency, 2006b)2-3 As defined above, NO X is a complex mixture of many oxides of nitrogen, so many factors can contribute to ambient NO X concentrations at any given time or location. Relatedly, there are several methods for determining NO X emissions from these many sources. One method is to consider the ratio of components of NO X to each other or to the total concentration of NO+NO 2 . The ratio of NO 2 to the sum of NO and NO 2 in the exhaust from gasoline fueled vehicles is variable, but generally of the order of a few percent (Heeb et al., 2008; Hilliard and Wheel er, 1979) as determined by dynamometer studies. Catalyzed diesel particle filters (CDPFs) can increase the NO 2 to NO+NO 2 ratio in diesel exhaust from <0.1 to around 0.3 to 0.7, depending on the engine , design of the CDPF and mode of operation. For example, Shorter et al. (2005) in a study of public transit buses in New York City found that ratios in emissions from retrofitted diesel engines range from 0.3 to 0.6. Sources of NO X are distributed with height, some are at or near ground level (e.g., motor vehicles) and others aloft (e.g., electric utilities stacks). Figur e 2.2-1 shows schematically on-road motor vehicles and electric utilities, the two largest NO X sources in the U.S., along with NO X species and major reaction pathways. Because the prevailing winds aloft are genera lly stronger than those at the surface, emissions from elevated sources can be distributed over a wider area than those emitted at the surface. The elevated emissions besides being widely dispersed are diluted to much lower levels than near their source.

Figure 2.2-1. Schematic diagram of the cycle of reactive oxidized N species in the atmosphere. NO Y refers to all the species shown within the inner and outer box; NO X to NO and NO 2 (in the inner box); and NO Z to all the species outside of the inner box. IN refers to inorganic particulate species (e.g., sodium [Na + ], calcium [Ca ++ ]), MPP to multiphase processes, h ν to a solar photon and R to an organic radical. Particle-phase RONO 2 are formed from the species shown on the right side. For the purposes of this EPA document, “NO X ” is defined as the group of all nitrogencontaining compounds inside the large dashed -line box, the same group generally termed “NO Y ” by atmospheric scientists.2-4 Biomass burning also produces NO X . Apart from these anthropogenic sources, there are also smaller natural sources which include microbial activ ity in soils (particularly fertilized soils) and lightning. Wildfires can be large but episodic and highly variable sources of NO X . NO X sources and emissions are described in greater detail in Annex Section AX2.4.



# 2.2.2. Chemical Transformations

NO and NO 2 are often grouped together a nd given the category label “NO X ” because they are emitted together and can rapidly interconvert as show n in the inner box in Figure 2.2-1. The NO emitted from the sources shown in Figure 2.2-1 can be oxidized to form NO 2 , meaning that atmospheric NO 2 concentrations nearly always have a large fraction created by secondary formation in the atmosphere, not direct emission. The timescale for the conversion of NO to NO 2 is on the order of a minute. 1 NO 2 reacts with O 3 and various free radicals in the gas phase a nd on surfaces in multiphase processes to form the oxidation products shown in Figure 2.2-1. These produc ts include inorganic species (shown on the left side of the outer box in Figure 2.2-1) and organic species (shown on the right side of the outer box in Figure 2.2-1). The oxidized N species in the outer box are often collectively termed NO Z ; thus, NO X +NO- Z =NO Y . The concentrations and atmospheric lifetimes ( τ ) of inorganic and organic products from reactions of NO X vary widely in space and time. Inorganic reaction products include nitrous acid (HONO), HNO 3 , pernitric acid, and particulate nitrate (PNO 3 - ). While a broad range of organic N compounds are emitted by combustion sources (e.g., nitrosamines and nitro-PAHs ), they are also formed in the atmosphere from reactions of NO and NO 2 . These include PANs and isoprene nitrates, other nitro-PAHs, and the more recently identified nitrated organic compounds in the quinone family. Most of the mass of products shown in the outer box of Figure 2.2-1 is in the form of PAN and HNO 3 , although other organic nitrates, e.g., isoprene nitrates and specific biogenic PANs can be important at locations closer to biogenic sources (Horowitz et al., 2007; Singh et al., 2007). In addition to gas-phase reactions, reactions occurring on surfaces or occurring in multiphase processes (MPP) are important for the formation of HONO and PNO 3 - . These reactions can occur on the surfaces of suspended particles, soil, and buildings, a nd within aqueous media. Further details about these processes can be found in Annex section AX2.2.3. PAN, and other peroxyacyl nitrates, both thermally decompose and photolyze back to reactants. Atmosphe ric lifetimes with respect to photolysis are a few hours during warm sunlit conditions. For thermal deco mposition, they range from ~1 hour at 298 K to ~2.5 days at 273 K, up to several weeks at 250 K. Thus, PAN can provide an effective sink of NO X at cold temperatures and high solar zenith angles; its lifetime is long enough at low temperatures so that PAN can be transported tens or hundreds of kilome ters (depending on meteorol ogical conditions) before decomposing to release NO 2 , which can then participate in O 3 formation in these regions, remote from the original NO X source. HNO 3 can act similarly to some extent, but its high solubility and high deposition rate imply that it is removed from the gas phase faster than PAN, and thus would not be as important as a source of NO X in remote regions. Characteristic concentrations of many of the NO X species are given in Annex section AX3.2. The timescale for reactions of NO X to form NO Z products like PAN and HNO 3 typically ranges from a few hours during summer to about a day during winter. As a result, morning rush hour emissions of NO X from motor vehicles can be converted almost completely to NO Z products by late afternoon during warm, sunny conditions. Because the time required for mixing emissions down to the surface is similar to or longer than the time for oxidation of NO X , emissions of NO X from elevated sources (like the stacks of electric utilities) tend to be transformed to NO Z before they reach the surface. However, people live closer to emissions from on-road and off-road mo tor vehicles, fixed-site combustion engines (e.g., generators), and indoor sources, and so ar e more likely to be exposed to NO and NO 2 from these sources.

1 This estimate assumes a background concentration of O 3 of 40 ppb and a rate coefficient at 298 K of 1.9 X 10 -14 cm 3 /molec-sec (Jet Propulsion

Laboratory, 2003).2-5 Hence, because atmospheric dispersion and chemical r eactions in this way determine the partitioning of a person’s exposure to NO 2 and its reaction products from multiple different sources, a person’s total exposure to NO X cannot be judged solely by the NO and NO 2 source strengths given in the national emissions inventories (NEI). Ultimately, oxidized N compounds are lost from the atmosphere by deposition to the earth’s surface. Soluble species are taken up by aqueous aerosol s and cloud droplets that can then be removed by either wet or dry deposition. Insoluble species are lo st by dry deposition and washout. Discussions of the reactions in particles are beyond the scope of this re view, but once in particles, a variety of organic and inorganic nitrates can be formed, which are then re moved either by dry deposition to the surface or by rainout or washout.



## 2.2.2.1. Formation of Nitro-PAHs

Nitro-PAHs are produced either by direct emissions or by atmospheric reactions. Among combustion sources, diesel emissions have been identif ied as the major source of nitro-PAHs in ambient air (Bezabeh et al., 2003; Gibson, 1983; Schuetzle, 1983; Tokiwa and Ohnishi, 1986). Direct emissions of nitro-PAHs vary with fuel type, vehicle maintena nce, and ambient conditions (Arey et al., 1986; 1989; Arey, 1998; Perrini et al., 2005; Pitts, 1987; Sasaki et al., 1997; Zielinska et al., 2004). In addition to direct emission, nitro-PAHs are formed from both g aseous and heterogeneous r eactions of PAHs with
gaseous N -containing pollutants in the atmosphere; r eactions of hydroxyl (OH) and nitrate (NO 3 ) radicals with PAHs are the major sources of nitro-PAHs (Arey et al., 1986; 1989; Arey, 1998; Perrini et al., 2005; Pitts, 1987; Sasaki et al., 1997; Zielinska et al., 1989; Bamford and Baker, 2003; Reisen and Arey, 2005). Reactions involving OH radicals occur mainly during the day, while reactions with NO 3 radicals occur mainly during the night. The major loss process of nitro-PAHs is photodecomposition (Fan et al., 1996; Feilberg et al., 1999; Feilberg and Nielsen, 2001) w ith lifetimes on the order of hours, followed by reactions with OH and NO 3 radicals. The reaction mechanisms for forming and destroying nitro-PAHs in the atmosphere are described in Annex section AX2.2.4 . In ambient particulate organic matter (POM), 2- nitrofluoranthene (2NF) is the dominant compound, followed by 1-nitropyrene (1NP) and 2-nitropyrene (2NP) (Arey et al., 1989; Bamford et al., 2003; Reisen and Arey, 2005; Zielinska et al., 1989). 2NF and 2NP are not directly emitted from primary combustion emissions, but are formed in the atmosphere . 1NP is generally regarded as a tracer of primary combustion sources, in particular, diesel exhaust. Af ter formation, nitro-PAHs with low vapor pressures (such as 2NF and 2NP) immediately migrate to pa rticles under ambient conditions (Arey et al., 1989; Bamford et al., 2003; Reisen and Arey, 2005). More vol atile nitro-PAHs, such as nitronapthalene (NN), remain mainly in the gas phase. The concentrations for most nitro-PAHs found in ambient air are typically lower than 1 pg/m 3

, except NNs, 1NP, and 2NF, which can be present at levels up to several tens or hundreds of pg/m 3 . These levels are from ~2 to ~1000 times lower than those of their parent PAHs. However, nitro-PAHs are much more toxic than PAHs (Durant et al., 1996; Grosovsky et al., 1999; Salmeen et al., 1982; Tokiwa and Ohnishi, 1986; Tokiwa et al., 1998). Moreover, most nitro-PAHs are present in particles with a mass median diameter of <0.1 μm. It should be noted that the first step involved in the multiphase processes noted above is adsorption of NO 2 . NO 2 adsorbed onto particles could then be inhaled along with the products of NO 2 reactions such as HONO and nitro-PAHs. However, quantitative details for the fraction of NO 2 adsorbed onto particles at ambient levels of NO 2 are lacking.2-6 

# 2.2.3. O 3 

# Formation

At the low NO X concentrations found in most environm ents (ranging from remote continental areas to rural and suburban areas downwind of urban centers), the net production of O 3 increases with increasing NO X . At the high NO X concentrations found in downtow n metropolitan areas, and especially near busy streets and roadways and in power plant plumes, net destruction of O 3 is initiated with the excess NO found there. In the airshed regimes with high NO X concentrations, NO 2 scavenges OH radicals that would otherwise oxidize VOCs to produce peroxy radicals, which would in turn oxidize NO to NO 2 . In the airshed regimes with low NO X concentrations, oxidation of VOCs generates excess free radicals; hence O 3 production is more nearly linear with NO X . Between these two regimes, there is a transition zone in which O 3 shows only a weak dependence on NO X concentration.



# 2.3. Measurement Methods

In the EPA regulatory networks as in nearly all large-scale NO X monitoring networks world-wide, NO 2 is the component of most interest. However, in most of these networks, NO 2 is not measured directly, but by subtraction following a measurement of the total of NO+NO 2 and NO alone. Both these measurements and hence the determination of NO 2 by subtraction depend on the same technique for measuring NO. In that technique, NO is measured using the principle of gas-phase chemiluminescence induced by the reaction of NO with O 3 at low pressure. The Federal Reference Method (FRM) for NO 2 makes use of this technique of NO detection. A pr erequisite step is the catalytic reduction of NO 2 to NO most often on the surface of a molybdenum oxide (MoO X ) substrate, heated to between 300 and 400°C. Because the FRM monitor cannot detect NO 2 specifically, the concentration of NO 2 is determined as the difference between the air sampl e passed over the heated MoO X substrate (the nitrogen oxides total) and the air sample that has not passed over the substrate (the NO). Reduction of NO 2 to NO on the MoO X substrate is not specific to NO 2 ; hence, the chemiluminescence analyzers are subject to varying interferences produced by the presence in the sample of the other oxidized N compounds (the NO Z species shown in the outer box of Figure 2.2-1). This interference is often termed a “positive artifact” in the NO 2 concentration estimate since the presence of NO Z always results in an over-estimate of the NO 2 concentration in the reported measurement. This interference by NO Z compounds has long been known (Fehsenfeld et al., 1987; Rodgers and Davis, 1989; U.S. Environmental Protection Agency, 1993, 2006a; Crosley, 1996; Nunnermacker et al., 1998; Parrish and Fehsenfeld, 2000; McClenny et al., 2002; Dunlea et al., 2007; Steinbacher et al., 2007). These studies have relied on intercomparisons of measurements using the FRM and other techniques for measuring NO 2 . The sensitivity of the FRM to potential interference by individual NO Z compounds is variable and also depends in part on characteristics of individual m onitors, such as the design of the instrument inlet, the temperature and composition of the reducing substr ate, and on the interactions of atmospheric species with the reducing substrate. Only recently have attempts been made to system atically quantify the magnitude and variability of the interference by NO Z species in ambient measurements of NO 2 . Dunlea et al. (2007) found an average of ~22% of ambient NO 2 (~9 to 50 parts per billion [ppb]) measured in Mexico City was due to interference from NO Z compounds; that is to say, the actual NO 2 concentration was ~22% lower than what was reported at monitors using the di fference technique. Comparable levels of NO 2 are found in many locations in the U.S., but the same comparison fo r distinct places in the U.S. is difficult to make because significant uncertainty remains in determin ing the concentrations of the higher oxidation NO Z products since they are not routinely measured. Dunlea et al. (2007) compared NO 2 measured using the conventional chemiluminescent instrument with ot her (optical) techniques. The main sources of interference were HNO 3 and various organic nitrates (RONO 2 ) which can be converted to NO on the2-7 catalyst with varying rates of efficiency. In this study, the efficiency of conversion on the catalyst — that is, how much of the compound introduced to the catal yst was converted to NO — was estimated to be ~38% for HNO 3 ; for PAN, ~95% and ~ 95% for other RONO 2 . Peak interference (over-estimation) in the reported estimate of NO 2 concentrations from the presence of NO Z compounds of up to 50% was found during afternoon hours and was associated with O 3 and NO Z compounds such as HNO 3 and the alkyl and multifunctional alkyl nitrates. In a study in rural Switzerland, Steinbacher et al. (2007) compared measurements of NO 2 continuously measured using a conventional NO X monitor and measurements in which NO 2 was photolyzed to NO. They found the conventional tec hnique using catalytic reduction (as in the FRM) overestimated the reported NO 2 concentration using the photolytic technique on average by 10% during winter and 50% during summer. Another approach to estimating the measurement interference is to use model calculations in conjunction with known data on th e reduction efficiencies of NO Z species on the MoO X converters as described above. Lamsal et al. (2008) used the conve rsion efficiencies noted above along with output for NO Y species from the GEOS-CHEM global chemical transport model (CTM) to derive seasonal correction factors for the ambient monitoring data across the U.S. These factors range from <10% in winter in the East to >80% in the West, with the highest values found during summer in relatively unpopulated areas. Lamsal et al. (2008) also used these co rrected data to determine the feasibility of using satellite data to supplement ground based data. However, the current generation of satellite monitors are in low earth orbiting mode and so the NO 2 values are restricted to time of satellite overpass in early afternoon. Future generations of ge ostationary satellites are planned that will obtain more continuous data across the U.S. throughout the day. Calculations using EPA’s Community Multiscale Air Quality (CMAQ) modeling system for the Mid-Atlantic region in a domain extending from Virgin ia to southern New Jersey were made at much higher spatial resolution than the GEOS-CHEM simulations (see http://www.mde.state.md.us/Programs/AirPrograms/ air_planning/index.asp). The daily average interference for an episode during the summer of 2002 estimated using model-derived concentration fields for NO Z species and using the conversion efficiencies for NO Z species given above, ranged from ~20% in Baltimore to ~80% in Madison, VA. Hi ghest values were found during the afternoon, when photochemical activity is highest and producti on and accumulation of the higher oxidized NO Z compounds is greatest, and lowest values during the mi ddle of the night when photochemistry stops. The model calculations showed episode averages of the NO Z /NO 2 ratio ranging from 0.26 to 3.6 in rural Virginia; the highest ratios were in rural areas, and low est were in urban centers closer to sources of fresh NO X emissions. (The capabilities of three-dimensional CTMs such as GEOS-CHEM and CMAQ and issues associated with their use are presented in Annex section AX2.5.) In summary, it appears that interference is likely to be on the order of 10% or less during most or all of the day during winter, but much larger inte rference is likely to be found during summer in the afternoon. In general, the interference in the measurement of NO 2 is greater downwind of urban source areas and in relatively remote areas away from con centrated sources as compared to the level of interference at measurements in urban cores with fresh NO X emissions. There are approaches to measuring NO 2 not affected by the artifacts mentioned above. For example, NO 2 can be photolytically reduced to NO with an e fficiency of ~70% as used in the Steinbacher et al. (2007) study. This method requires additional development to ensure its cost effectiveness and reliability for extensive field deployment. The relativel y low and variable conversion efficiency of this technique would necessitate more fre quent calibration. Optical methods such as those using differential optical absorption spectroscopy (DOAS) or laser induced fluorescence (LIF) are also available, as described in Annex section AX2.6. However, these partic ular methods are more expensive than either the FRM monitors or photolytic reducti on technique and require specialized expertise to operate. Moreover, the DOAS obtains an integrated measurement over th e instrument path length rather than a point measurement. Cavity attenuated phase shift monitors are an alternative optical approach that is potentially2-8 less costly than DOAS or LIF (Kebabian et al., 2007). However, this technique is not highly specific to NO 2 and is subject to interference by other species absorbing at 440 nm, such as the 1,2-dicarbonyl compounds. The extent of this interference and the pot ential of the cavity attenuated phase shift technique for extensive field deployment have not been evaluated. Commercially available NO X monitors have been converted to NO Y monitors by moving the MoO X convertor to interface directly with the sample inle t. Because of losses on inlet surfaces and differences in the efficiency of reduction of NO Z compounds on the heated MoO X substrate, NO X cannot be considered as a universal surrogate for NO Y . However, in settings close to relatively high-concentration fresh emissions like those during urban rush hour, most of the NO Y is present as NO X . To the extent that all the major oxidized N species can be reduced quantitatively to NO, measurements of NO Y should be more reliable than those of NO X , particularly at typical ambient levels of NO 2 . It is worth reiterating that with the current FRM monitors, the direct measurements of NO are the most specific. Measurements of total NO Y characterize the entire suite of oxidized N compounds to which humans are exposed. Reliable measurements of NO Y and NO 2 , especially at the low concentrations observed in many areas remote from sources are also crucial for evaluating the performance of three-dimensional, chemical transport models of oxidant and acid production in the atmos phere (described in Annex section AX2.5). To summarize this discussion of NO 2 measurement techniques and interferences: the current method of determining ambient NO X and then reporting NO 2 concentrations by subtraction of NO is subject to a consistently positive interference by NO X oxidation products, chiefly HNO 3 and peroxyacetyl nitrate (PAN) as well as other oxidized N -containing compounds, though the magnitude of this positive bias is largely unknown and can be rapidly changing. Measurements of these oxidation products in urban areas are sparse. Concentrations of these oxidation produc ts are expected to peak in the afternoon because of the continued oxidation of NO 2 emitted during the morning rush hours and during conditions conducive to photochemistry in areas well downwind of sources, particularly during summer. Within the urban core of metropolitan areas, where ma ny of the ambient monitors are sited close to strong NO X sources such as motor vehicles on busy streets and highways (i.e., where NO 2 concentrations are highest), the positive artifacts due to the NO 2 oxidation products are much smaller on a relative basis, typically <~10%. Conversely, the positive artifacts are larger in locations more distant from NO X sources (i.e, where NO 2 concentrations are lowest) and could exceed 50%. Therefore, variable, positive artifacts associated with measuring NO 2 using the Federal Reference Method (FRM) severely hamper its ability to serve as an accurate and precise indicator of NO 2 concentrations at the typical ambient levels generally encountered outside of urban cores.



# 2.4. Atmospheric Concentrations

This section provides a brief overview of ambient concentrations of NO 2 and associated oxidized N

compounds in the U.S.; it also provides estimates of Policy-Relevant Background (PRB) concentrations, i.e., background concentrations used to inform risk and policy assessments for the review of the NAAQS.



# 2.4.1. Ambient Concentrations

Figure 2.4-1 shows the distribution of monitoring sites for NO 2 across the U.S. Data for ambient NO 2 are not collected or collected at very few sites ove r large areas of the U.S. Few cities have more than two monitors and several large cities, including S eattle, WA, have none. Note that the number of NO 2 monitors has been decreasing in the U. S. as ambient average concentrations have fallen to a few tenths of the level of the NAAQS. There were, for example, 375 NO 2 monitors identified in mid-2006, but only 280 in November 2007.2-9 Criteria for siting ambient monitors for NAAQS pollutants are given in the SLAMS / NAMS / PAMS Network Review Guidance (U.S. Environmenta l Protection Agency, 1998). As might be expected, criteria for siting monitors differ by pollutant. NO 2 monitors are meant to be representative of several scales: middle (several city blocks, 300 to 500 m), ne ighborhood (0.5 to 4 km), and urban (4 to 50 km). Middle- and neighborhood-scale monitors are used to determine highest concentrations and source impacts, while neighborhood- and urban-scale monitors are used for monitoring population exposures. As can be seen, there is considerable overlap between monitoring objectives and scales of representativeness. The distance of neighborhood- and urban-scale monito r inlets from roadways increases with traffic volume and can vary from 10 to 250 m away from roadways as traffic volume increases. Where the distance of an inlet to a road is shorter than the valu e in this range for the indicated traffic volume on that road, that monitor is classified as middl e scale. Vertically, the inlets to NO 2 monitors can be set at a height from 2 to 15 m.

Figure 2.4-1. Location of ambient NO 2 monitors in the U.S. as of No vember 5, 2007. Shaded states have NO 2 monitors; unshaded states have none.

Figures 2.4-2 through 2.4-12 depict the spatial and population coverage of NO 2 monitors in these Consolidated Metropolitan Statistical Areas (CMSAs): Atlanta, GA; Boston, MA; Chicago, IL; Houston, TX; Los Angeles, CA; New York City, NY; Phila delphia, PA; Steubenville, OH; and Baltimore, MD/Washington, DC. (These CMSAs were selected for this depiction to main tain consistency with CMSAs used elsewhere in this assessment for hea lth effects studies or ambient concentration representations.)2-10 Figure 2.4-2. NO 2 monitor locations in the Atlanta, GA CMSAshown in relation to major roadways, pointsource electric generating units, and population de nsities for total population, and fractions ≤ 17 years and ≥ 65 years.2-11 Figure 2.4-3. NO 2 monitor locations in the Boston, MA CMSA shown in relation to major roadways, pointsource electric generating units, and population de nsities for total population, and fractions ≤ 17 years and ≥ 65 years.2-12 Figure 2.4-4. NO 2 monitor locations in the Chicago, IL CMSAshown in relation to major roadways, pointsource electric generating units, and population de nsities for total population, and fractions ≤ 17 years and ≥ 65 years.2-13 Figure 2.4-5. NO 2 monitor locations in the Houston, TX CMSAshown in relation to major roadways, pointsource electric generating units, and population de nsities for total population, and fractions ≤ 17 years and ≥ 65 years.2-14 Figure 2.4-6. NO 2 monitor locations in the Los Angeles, CA CMSA shown in relation to major roadways, point-source electric generating units, and popul ation densities for total population, and fractions ≤ 17 years and ≥ 65 years.2-15 Figure 2.4-7. Detail of NO 2 monitor locations in the Los Angeles, CA CMSA shown in relation to major roadways, point-source electric generati ng units, and total population density.2-16 Figure 2.4-8. NO 2 monitor locations in the New York City, NY and Philadelphia, PA CMSAs shown in relation to major roadways, point-source electric generating units, and population densities for total population, and fractions ≤ 17 years and ≥ 65 years.2-17 Figure 2.4-9. Detail of NO 2 monitor locations in the New York City , NY and Philadelphia, PA CMSAs shown in relation to major roadways, point-source electric generating units, and total population density.2-18 Figure 2.4-10. NO 2 monitor locations in the Steubenville, OH CMSA shown in relation to major roadways, point-source electric generating units, and popul ation densities for total population, and fractions ≤ 17 years and ≥ 65 years.2-19 Figure 2.4-11. NO 2 monitor locations in the Washington, DC and Baltimore, MD CMSAs shown in relation to major roadways, point-source el ectric generating units, and popul ation densities for total population, and fractions ≤ 17 years and ≥ 65 years.2-20 Figure 2.4-12. Detail of NO 2 monitor locations in the Washington, DC and Baltimore, MD CMSAs shown in relation to major roadways, point-source el ectric generating units, and total population density.2-21 The study areas included 8 regions comprising 11 metropolitan statistical areas (MSAs), as defined by the U.S. Census Bureau (http://www.census.gov/): Atlanta, Boston, Chicago, Houston, Steubenville, Los Angeles/Riverside, Washington DC/Baltimore, and New York City/Philadelphia. All pertinent census data (state, Metropolitical Statistical Area [MSA], c ounty, and census block maps) were obtained from the ArcGis 9.2 Media Kit provided by ESRI (2006). Cens us blocks served as the unit of analysis for population calculations. All geospatial analyses were performed in ArcMap (Build 1324). NO 2 monitor location data (i.e., latitude/longitude) for 2004 were obtained from EPA’s AirData website (http://www.epa.gov/air/data/). Monitors were mapped for a particular region if they were within 15 kms of its boundary. Information on point sources (i.e., foss il fueled electrical power generators) for 2002 was obtained from the National Emissions Inventory (U .S. Environmental Protection Agency, 2006b). Point sources were classified by their Source Classification Codes (SCC): 1010xxxx for electric generation: external combustion boilers, and 2010xxxx for electric ge neration: internal combustion engines. Point sources were mapped for a particular region if they were within 30 kms from its boundary. All census maps were projected into ArcMap using the North American Datum of 1983 and the USA Contiguous Lambert Conformal Conic projection coordinate system to allow for calculation of linear distances. NO 2 monitor and point source locations for a pa rticular region were then imported into their respective maps and buffer zones of 1, 5, 10, and 15 kms were constructed around the monitor locations. The total population and popula tions of 2 sensitive subgroups (those ≤ 17 and those ≥ 65) were then calculated for those areas using the population data contained within the census block maps.

Figure 2.4-13. Ambient concentrations of NO 2 measured at all monitoring sites located within MSAs in the U.S. from 2003 through 2005. * max; • mean

Figure 2.4-13 shows box plots of ambient concentrations of NO 2 measured at all monitoring sites located within MSAs or urbanized areas in the U.S. from 2003 through 2005. As can be seen from Figure2-22 2.4-13 mean NO 2 concentrations are ~15 ppb for averaging periods ranging from a day to a year, with an interquartile range (IQR) of 10 to 25 ppb. Ho wever, the average of the daily 1-h max NO 2 concentration over this 3-year period is ~30 ppb. These values are about twice as high as the 24-h avg. The highest maximum hourly concentration (~200 ppb) found duri ng the period of 2003 to 2005 was more than a factor of ten greater than the overall mean 24-h concentrations. The ratio of the 99th percentile concentration to the mean ranges from 2.1 for the 1-year avgs to 3.5 for the 1-h avgs. Because ambient NO 2 monitoring data are so sparse across the U.S. (see Figure 2.4-1) and particularly so in rural areas, it would not be appr opriate to use these data in constructing a map of NO 2 concentrations across the continental U.S. The short τ of NO 2 with respect to conversion to NO Z species and the concentrated nature of NO 2 emissions result in steep gradients and low concentrations away from major sources that are not adequately captured by the existing monitoring networks. Model predictions might be more useful for showing large-scale features in the distribution of NO 2 and could be used in conjunction with the values shown in Figure 2.4-13 to provide a more complete picture of the variability of NO 2 across the U.S. Monthly avg NO 2 concentrations for January and July 2002 calculated using EPA’s CMAQ model are shown in Figures 2.4-14. (A description of the capabilities of CMAQ and other three-dimensional CTMs is given in Anne x section AX2.5.) The high variation in NO 2 concentrations of at least a factor of 10 is apparent in these model estimates. As expected, the highest NO 2 concentrations are seen in large urban regions, such as the North east Corridor, and lowest values are found in sparsely populated regions located mainly in the West. NO 2 concentrations tend to be higher in January than in July.

Figure 2.4-14. Monthly average NO 2 concentrations in ppb for January 2002 (left panel) and July 2002 (right panel) calculated by CMAQ (36 X 36 km horizontal resolution).



# 2.4.2. NO 2 

# Concentrations

Trends in NO 2 concentrations across the U.S. from 1980 to 2006 are shown in Figure 2.4-15. The white line shows the mean values and the upper and lowe r borders of the blue (shaded) areas represent the 10th and 90th percentile values. Info rmation on trends at individual, local air monitoring sites can be found at www.epa.gov/airtrends/nitrogen.html. Concentrations were substantially higher during earlier years in selected locations and contributed in those years to the “brown clouds” observed in many cities. Residents in Chattanooga, TN, for example, were exposed more than 30 years ago to high levels of NO 2 from a munitions plant (Shy and Love, 1980). Annual mean NO 2 concentrations there declined from ~102 ppb in 1968 to ~51 ppb in 1972. There was a2-23 strike at the munitions plant in 1973 and levels dec lined to ~32 ppb. With the implementation of control strategies, values dropped further. In 1988, the annual mean NO 2 concentration varied from ~20 ppb in Dallas, TX and Minneapolis, MN to 61 ppb in Los A ngeles, CA. However, New York City, with the second-highest annual mean concentration in the U.S. in 1988, the mean NO 2 concentration was 41 ppb.

Figure 2.4-15. Nationwide trend in NO 2 concentrations.The white line s hows the mean values, and the upper and lower borders of the blue (shaded) areas represent the 10th and 90th percentile values. Information on trends at local air monitoring sites: www.epa.gov/airtr ends/nitrogen.html.

In contrast to most urban areas in the U.S., in other countries, NO 2 concentrations have increased. For example, annual mean NO 2 concentrations in central London increased during the 1980s from ~25 ppb in 1978 to ~40 ppb in 1989 at the background m easurement site and from ~35 to ~45 ppb at the roadside site. Corresponding NO concentrations increased from ~20 ppb to ~40 ppb at the background site and from ~125 to ~185 ppb at the roadside site (Elsom, 2002). Increased use of motor vehicles may have contributed to much of these increases in NO 2 levels.



# 2.4.3. Seasonal Variability in NO 2 

# at Urban Sites

The month-to-month variability in 24-h avg NO 2 concentrations at two sites in Atlanta, GA is shown in Figure 2.4-16. Variability at other individua l sites in selected urban areas is shown in Annex Figures AX3.2-1 to AX3.2-6. As might be expected from an atmospheric species that behaves essentially like a primary pollutant emitted from surface sources, there is strong seasonal variability in NO 2 concentrations in the data shown in Figures 2.4- 16a-b. Higher concentrations are found during winter, consistent with the lowest mixing layer heights found during the year. Lower concentrations are found during summer, consistent with higher mixing la yer heights and increased rates of photochemical oxidation of NO 2 to NO Z . Note also the day-to-day variability in NO 2 concentration, which also tends to be larger during the winter. There appears to be a so mewhat regular pattern for the other southern cities examined with their winter maxima and summer minima.2-24 Figure 2.4-16. Time series of 24-h avg NO 2 concentrations at individual sites in Atlanta, GA from 2003 through 2005. A natural spline function (with 9 degr ees of freedom) was fit and overlaid to the data (dark solid line).2-25 Monthly maxima tend to be found from late winter to early spring in Chicago, IL, and New York, NY, with minima occurring from summer through the fall. However, in Los Angeles and Riverside, CA, monthly maxima tend to occur from autumn through early winter, with minima occurring from spring through early summer. Mean and peak NO 2 concentrations during winter can be up to a factor of two greater than those during the summer at sites in Los Angeles.



# 2.4.4. Diurnal Variability in NO 2 

# Concentrations

The diurnal variability in NO 2 concentrations at the same two sites in the Atlanta metropolitan area shown in Figure 2.4-16 is illustrated in Figure 2.4-17. As can be seen from these figures, NO 2 typically exhibits daily maxima during the morning rush hours, although they can occur at other times of day. In addition, there are differences between w eekdays and weekends. At both sites, NO 2 concentrations are generally lower and the diurnal cycles more comp ressed on weekends than on weekdays. The diurnal variability of NO 2 at these sites is typical of that observed at other urban sites. Monitor siting plays a role in determining diurnal variability in the sense that monitors located farther from traffic will measure lower concentrations and show a fla tter overall distribution of data compared to monitors located closer to traffic.

Figure 2.4-17. Mean hourly NO 2 concentrations on weekdays and w eekends measured at two sites in Atlanta, GA. A and B refer to a suburban site, and C and D refe r to a site classified as urban and city center.2-26 

# 2.4.5. Concentrations of NO Z 

# Species

Data for concentrations of NO Z species in urban areas in the U.S. are sparse. The most comprehensive set of data for any NO Z species was obtained for HNO 3 as part of the Children’s Health Study for which gas-phase HNO 3 was measured at 12 sites in southern California from 1994 through 2001 (Alcorn et al., 2004). Two week avg concentra tions ranged from <1 ppb to >10 ppb, with the highest HNO 3 concentrations and the highest ratio of HNO 3 /NO 2 (~0.2) found downwind from central Los Angeles in the San Bernadino during summer, as one would expect for this more oxidized N product. Measurements of HONO in urban areas are very limited; however, data from Stutz et al. (2004) and Wang and Lu (2006) indicate that levels of HONO are <1 ppb even under heavily polluted conditions, with the highest levels found during the night and ju st after dawn and the lowest values found in the afternoon. However, data collected in the U.K. (AQEG, 2004; Lammel and Cape, 1996) and in the U.S. (Kirchstetter and Harley, 1996) indicate that HONO to NO X ratios could be of the order of ~5 % in motor vehicle emissions. These results indicate that HONO levels in traffic could be comparable to those of NO 2 . Several field studies conducted at ground level (Hay den et al., 2003, near Boulder CO; Williams et al., 1987) and aircraft flights (Singh et al., 2007, over eastern North America), have found much higher NO Z concentrations than NO X concentrations in relatively unpolluted rural air. Additional information for the concentrations of NO Z species can be found in Annex section AX3.2.5.



# 2.4.6. Policy-Relevant Background Concentrations of NO 2 Background NO 2 concentrations used for purposes of informing decisions about NAAQS are referred to as PRB concentrations. PRB concentrations are those that would occur in the U.S. in the absence of anthropogenic emissions in continental Nort h America (defined here as the U.S., Canada, and Mexico). PRB concentrations include contributions from natural sources everywhere in the world and from anthropogenic sources outside these three countries. Background levels defined in this way facilitate separation of pollution levels that can be contro lled by U.S. regulations (or through international agreements with neighboring countries) from levels that are generally uncontrollable by the U.S. These levels may also be used in quantitative risk assessmen ts of human health and environmental effects. Contributors to PRB concentrations include natural emissions of NO, NO 2 , and reduced nitrogen compounds, as well as their long-range transport from outside North America. Natural sources of NO 2 and its precursors include biogenic emissions, wild fires, lightning, and the stratosphere. Biogenic emissions from agricultural activities, such as emissions of NO from fertilized soils, are not considered to be contributing to the formation of PRB concentr ations. Discussions of the sources and estimates of emissions are given in Annex section AX2.4.2.



## 2.4.6.1. Analysis of Policy-Relevant Background Contribution

The MOZART-2 global model of tropospheric chemistr y (Horowitz et al., 2003) is used to estimate the PRB contribution to NO 2 concentration. The model setup for the present-day simulation has been published in a series of papers from a recent m odel intercomparison (Den tener et al., 2006a; 2006b; Shindell et al., 2006; Stevenson et al., 2006). MOZART-2 is driven by the U.S. National Oceanic and Atmospheric Administration’s National Center for Environmental Prediction (NOAA NCEP) meteorological fields using 2001 da ta and using 2000 emissions from th e International Institute for Applied Systems Analysis (IIASA). The model was run at a resolution of 1.9° X 1.9° with 28 sigma levels in the vertical dimension with both gas-phase and aerosol chemistry.2-27 Figure 2.4-18. Upper panel: Annual mean NO 2 concentrations (in ppb) in the U.S. Middle panel: Annual mean PRB concentrations (in ppb) for NO 2 in the U.S. These simulations were made using the MOZART-2 global, chemical transport model. The lower panel shows PRB concentrations expressed as a percentage of total NO 2 concentrations shown in the upper panel. See text in Annex section AX2.7 for details.2-28 Figure 2.4-18 shows the annual mean NO 2 concentration in surface air in the base case simulation (top panel) and the PRB simulation (middle panel) , along with the percentage contribution of the background to the total base case NO 2 (bottom panel). Maximum concentrations in the base case simulation occur along the Ohio River Valley and in the Los Angeles basin. While total surface NO 2 concentrations are often >5 ppb, PRB is <300 parts pe r trillion (ppt) over most of the continental U.S. and <100 ppt in the eastern U.S. The distribution of PRB (middle panel of Figure 2.4-18 largely reflects the distribution of soil NO emissions, with some local increases like those in western Montana due to biomass burning. In the northeastern U.S., where present-day NO 2 concentrations are highest, PRB contributes <1% to the total. Thus, it appears that PRB levels of NO 2 are much smaller than observed levels.



# 2.4.7. Summary of Ambient and Policy-Relevant Background Concentrations of NO 2 The annual avg NO 2 concentrations of ~15 ppb reported by the regulatory monitoring networks are well below the level of the current NAAQS (0 .053 ppm). However, daily maximum 1-h avg concentrations can be greater than 100 ppb in some locations, e.g., areas with heavy traffic. PolicyRelevant Background concentrations of NO 2 are much lower than average ambient concentrations and are typically less than 0.1 ppb over most of the U.S., with the highest values found in agricultural areas.



# 2.5. Exposure Issues

2.5.1. Introduction

Human exposure to an airborne pollutant consists of contact between the human and the pollutant at a specific concentration for a specified period of time. People spend various amounts of time in different microenvironments characterized by different polluta nt concentrations. The integrated exposure of a person to a given pollutant is the sum of the exposur es over all time intervals for all microenvironments in which the individual spends time. Figure 2.5-1 represen ts a composite average of activity patterns across all age groups in the U.S. based on data collected in the National Human Activity Pattern Survey (NHAPS) (Klepeis et al., 2001). The demographic di stribution of the respondents was designed to be similar to that of overall U.S. Census data. Differe nt cohorts, e.g., the elderly, young and middle-aged working adults, and children exhi bit different activity patterns. 1 An individual’s exposure to a pollutant, such as NO 2 , can be represented by:

(2.5-1)

where E T is an individual’s total personal exposure for a specific time period, n is the total number of microenvironments encountered, C i is the average concentration, and t i is the time spent in the i th microenvironment. The exposure a person experiences can be characterized as an instantaneous exposure, a peak exposure such as might occur during cooking, an average exposure, or an integrated exposure over

1 For example, the cohort of working adults between the ages of 18 and 65 r epresents ~50% of the populat ion. Of this total, abou t 60% work outside

the home, spending ~24% (40 h/168 h) of their time in factory/o ffice environments. Thus, this c ohort is likely to spend conside rably more time in offices and factories than shown in the figure (5.4%), which re flects the entire population, and is also likely to spend less t ime in a residence compared to small children or the elderly.2-29 all environments a person encounters. These distincti ons are important because health effects caused by long-term, low-level exposures may differ from t hose caused by short-term, peak exposures.

Source: Klepeis et al. (2001)
Figure 2.5-1. Percentage of time people spe nd in different environments in the U.S.

An individual’s total exposure ( E T ) can also be represented by the following equation:

(2.5-2)

subject to the constraint,

(2.5-3)

where E a is the person’s exposure to pollutants of ambient origin; E na is the person’s exposure to pollutants that are not of ambient origin; y o is the fraction of time people spend outdoors and y i is the fraction of time they spend in microenvironment i ; F inf

i , P i , a i , and k i are the infiltration factor, penetration coefficient, air exchange rate, and decay rate for microenvironment i . In this equation, it is assumed that microenvironments do not exchange air with each othe r, but only with the ambient environment. In the case where microenvironmental exposures occur mainly in a single microenvironment, Equation 2.5-2 may be approximated by Equation 2.5-4:

(2.5-4)

where y is the fraction of time persons spend outdoors, and α is the ratio of a person’s exposure to a pollutant of ambient origin to the pollutant’s ambien t concentration (or the ambient exposure factor with a2-30 value between 0 and 1). Other symbols have the same definitions in Equation 2.5-2 and 2.5-3. If microenvironmental concentrations are consid ered, then Equation 2.5-4 can be recast as:

(2.5-5)

where C me is the concentration in a microenvironment; C a and C na are the contributions to C me from ambient and nonambient sources; S is the microenvironmental source strength; and V is the volume of the microenvironment. The symbols in brackets have the same meaning as in Equation 2.5-4. Microenvironments in which people are exposed to air pollutants such as NO 2 typically include residential indoor environments, other indoor locati ons, near-traffic outdoor environments, other outdoor locations, and in vehicles, as shown in Figure 2.5- 1. Indoor combustion sources such as gas stoves and space heaters need to be consider ed when evaluating exposures to NO 2 . Exposure misclassification may result when total human exposure is not disaggregated between various microenvironments, and this may obscure the true relationship between ambient air pollutant exposure and health outcome. In a given microenvironment, the ambient com ponent of a person’s microenvironmental exposure to a pollutant is determined by the following physical factors:

 The ambient concentration, Ca

 The air exchange rate, a i

 The pollutant specific penetration coefficient, P i

 The pollutant specific decay rate, k i

 The fraction of time an individual spends in the microenvironment, y i These factors are in turn affected by the fo llowing exposure factors (see Annex section AX3.5):

 Environmental conditions, such as weather and season

 Dwelling conditions, such as house location, wh ich determines proximity to sources and geographical features that can modify transport from sources; the amount of natural ventilation (e.g., open windows and doors, and the “draftiness” of the dwelling) and ventilation system (e.g., filtration efficiency and operation cycle)

 Personal activities (e.g., the time spent cooking or commuting)

 Indoor sinks of a pollutant

 Microenvironmental line and point sources (e.g., lawn equipment) Microenvironmental exposures can also be influenced by the individual-specific factors such as age, gender, health, or socioeconomic status. Time-activity diaries, completed by study partic ipants, are often used in exposure models and assessments. The EPA’s National Exposure Research Labor atory (NERL) has consolidated the majority of the most useful human activity databases into one comprehensive database: the Consolidated Human Activity Database (CHAD). Eleven different human activ ity pattern studies were evaluated to obtain over 22,000 person-days of 24-h human activities in CHAD (M cCurdy et al., 2000). These data can be useful in assembling population cohorts to be used in exposure modeling and analysis. In general, the relationship betw een personal exposures to pollutants of ambient origin and ambient concentrations can be modified by microenvironments . During infiltration, ambient pollutants can be lost through chemical and physical loss processes; theref ore, the ambient component of a pollutant’s concentration in a microenvironment is not the same as its ambient concentration but the product of the ambient concentration and the infiltration factor ( F inf

or α if people spend 100% of their time indoors). In2-31 addition, exposure to nonambient, microenvironm ental sources modifies the relationship between personal exposures and ambient concentrations. In practice, it is extremely difficult to characterize community exposure by individual personal exposure. Instead, the distribution of personal expos ure in a community, or the population exposure, is characterized by extrapolating measurements of personal exposure using va rious techniques or by stochastic, deterministic, or hybrid exposure modeling approaches such as Air Pollution Exposure (APEX), Simulation of Human Exposure and Dose System (SHEDS), and Modeling Environment for Total Risk for One-Atmosphere (MENTOR) (see Annex section AX3.6 for a description of exposure modeling methods). Variations in community-lev el personal exposures are determined by crosscommunity variations in ambient pollutant con centrations and the physical and exposure factors mentioned above. These factors also determine th e strength of the association between population exposure to NO 2 of ambient origin and ambient NO 2 concentrations. Of major concern is the ability of NO 2 (as measured by ambient monitors) to serve as a reliable indicator of personal exposure to NO 2 of ambient origin. The key question is what errors are associated with using NO 2 measured by ambient monitors as a surrogate for personal exposure to ambient NO 2 and/or its oxidation products in epidemiologic studies. There are three aspects of this issue: (1) ambient and personal sampling issues; (2) the spatial variability of ambient NO 2 concentrations; (3) the associations between ambient concentrations and pe rsonal exposures as influenced by exposure factors, e.g., proximity to traffic, indoor sources and sinks , and the time people spend indoors and outdoors. These issues are treated individually in the following subsections.



# 2.5.2. Personal Sampling of NO 2 Personal exposures in human e xposure and panel studies of NO 2 health effects are monitored by passive samplers. Their performance is evaluated by comparison to the chemiluminescence monitoring method. Some form of evaluation is crucial for dete rmining measurement errors associated with exposure estimates. However, measurements of NO 2 are subject to artifacts both at the ambient level and at the personal level. As discussed in Section 2.3, measurements of ambient NO 2 are subject to interference caused by other NO Y compounds, in particular HNO 3 , PANs, HONO, and RONO 2 . The most widely used passive samplers are Pa lmes tubes (Palmes et al., 1976), Yanagisawa badges (Yanagisawa and Nishimura, 1982), Ogawa samplers (Ogawa and Company, http://www.ogawausa.com), and radial diffusive samplers (Cocheo et al., 1996). The methodology and application of Palmes tubes and Yanagisawa badges were described in the last NO X AQCD (U.S. Environmental Protection Agency, 1993). Descriptions of other commercialized samplers are given in Annex section AX3.3. These samplers do not use a pump to bring air into contact with the sampling substrate; rather, they rely on diffusion or small scale turbulence to transport NO 2 to a sorbent (Krupa and Legge, 2000). The sorbent can be either physically sorptive (e.g., active carbon) or chemisor ptive (e.g., triethanolamine [TEA], KI, sodium arsenite [NaAsO 2 ]); passive samplers for NO 2 are chemisorptive, i.e., a reagent coated on a support (e.g., metal mesh, filter) chemically reacts with and captures NO 2 . The sorbent is extracted and analyzed for one or more reactive derivatives; the mass of NO 2 collected is derived from the concentration of the derivative(s) based on the stoichiometry of the r eaction. A number of studies indicate that passive samplers have very good precision, generally within 5% (Gair et al., 1991; Gair and Penkett, 1995; Kirby et al., 2001; Plaisance et al., 2004). NO 2 concentrations measured outdoors by Palmes tube passive samplers were a factor of 1.26 higher than those measured by the chemiluminescen ce method in a study in the UK (Campbell et al., 1994). Campbell et al. proposed that differences could be attributed mainly to wind-driven turbulent mixing in the mouth of the Palmes tube. Deposition dr iven by turbulence would raise the uptake rate on the tube surface compared to the th eoretical value, which is based on molecular diffusion along the length of the tube. Other field evaluation studies showed that the overall avg NO 2 concentrations calculated from2-32 diffusion tube measurements were likely to be w ithin ± 10% of chemiluminescent measurement data (Bush et al., 2001) and for Ogawa passive samplers (Mukerjee et al., 2004). A number of factors could affect the performance of passive samplers. Passive sampler performance has not been extensively studied over a wide range of concentrations, wind velocities, temperatures, and relative humidities (Varshney and Singh, 2003). Variability in environmental conditions (e.g., temperature, wind speed, humidity) can affect the performance of passive samplers because they can cause variations in sampling rates throughout the sampling period. Chemical reactions between O 3 and NO occur in the diffusion tube especially at roadsides where NO concentrations are relatively high and when sufficient O 3 is present for interconversion between the species resulting in an overestimate of NO 2 (Heal et al., 1999). There could also be differential sensitivity to other forms of NO Y , such as HONO, PAN, and HNO 3 , between the passive samplers a nd the chemiluminescence analyzers (Gair et al., 1991). However, the kinetics and stoich iometry of interferent compound reactions have not been well established. The lack of specific ity of the substrate towards uptake of NO 2 could also be an issue, as SO 2 can interfere with the uptake of NO 2 (Cox, 2003). Another aspect of passive sampler performance is that, compared with ambient ch emiluminescence monitors, passive samplers give relatively longer time-averaged concentrations (from days to weeks), with higher detection limits over short sampling periods. Consequently, diffusive samplers including those used for NO 2 monitoring provide integrated but not high time-resolution concen tration measurements. Hourly fluctuations in NO 2 concentrations may be important to the evaluati on of exposure-health effects relationships, and continuous monitors, such as the chemiluminescent m onitors, remain the only approach for estimating short-term, peak exposures.



# 2.5.3. Spatial Variability in NO 2 

# Concentrations

2.5.3.1. Variability of NO 2 

## Concentrations across Ambient Monitoring Sites

Summary statistics for the spatial variability in several urban areas across the U.S. are shown in Table 2.5-1. Data were obtained from EPA’s Air Quality System (AQS). These areas were chosen because they are major urban areas with at least five monitors operating from 2003 to 2005. Values in parentheses indicate the number of monitoring sites in that particular city. The second column shows the 3-year mean concentration across all monitors and th e range in these means at individual monitor sites. Metrics for characterizing spatial variability include th e use of Pearson correlation coefficients (r; column 3), the 90th percentile of the absolute difference in concentrations (column 4), and coefficient of divergence (COD; column 5). The ranges represen t results of pairwise monitor comparisons. These three metrics are calculated based on measurements of daily avg concentrations at individual site pairs. The COD provides an indication of the vari ability across the monitoring sites in each city and is defined in Equation 2.5-6, as follows

(2.5-6)

where X ij and X ik

represent observed concentrations averaged over some measurement averaging period (hourly, daily, etc.), for measurement period i at site j and site k , and p is the number of observations. A COD of 0 indicates there are no differences between con centrations at paired sites (spatial homogeneity), while a COD approaching 1 indicates extreme spatial heterogeneity.2-33 Table 2.5-1. Spatial variability of NO 2 in selected U.S. urban areas.

URBAN AREA (# OF MONITORS) 3-YEAR MEAN CONCENTRATION (RANGE) PEARSON CORRELATION COEFFICIENT 90 TH PERCENTILE DIFFERENCE

BETWEEN MONITORS COEFFICIENT OF DIVERGENCE

New York, NY (5) 29 ppb (25–37) 0.77–0.90 7–19 0.08–0.23

Atlanta, GA (5) 11 ppb (5–16) 0.22–0.89 7–24 0.15–0.59

Chicago, IL (7) 22 ppb ( 6–30) -0.05–0.83 10–39 0.13–0.66

Houston, TX (7) 13 ppb (7–18) 0.31–0.80 6–20 0.13–0.47

Los Angeles, CA (14) 25 ppb (14–33) 0.01–0.90 8–32 0.08–0.51

Riverside, CA (9) 21 ppb (5–32) 0.03–0.84 10–40 0.14–0.70

The same statistics shown in Table 2.5-1 have been used to describe the spatial variability of PM 2.5 (U.S. Environmental Protection Agency, 2004; Pinto et al., 2004) and O 3 (U.S. Environmental Protection Agency, 2006a). Because of relative sparseness in data coverage for NO 2 , spatial variability in all cities considered for PM 2.5 and O 3 could not be considered here. Thus, the num ber of cities included here is much smaller than for either O 3 (24 urban areas) or PM 2.5 (27 urban areas). For urban areas with monitors for all three pollutants, data may have been collected at different locations, with different responses to local sources. For example, concentrations of NO 2 collected near traffic will be highest in an urban area, but concentrations of O 3 will tend to be lowest there because of titration by NO forming NO 2 . However, some general observations can still be ma de. Mean concentrations of NO 2 at individual monitoring sites are not as highly variable as for O 3 but are more highly variable than PM 2.5 . Lower bounds on intersite correlation coefficients for PM 2.5 and for O 3 tend to be much higher than for NO 2 in the same areas shown in Table 2.5-1. CODs for PM 2.5 are much lower than for O 3 , whereas CODs for NO 2 tend to be the largest among these three pollutants. The greater spatial variability for NO 2 compared to O 3 and PM 2.5 could lead to larger exposure error in epidemiologic studies.



## 2.5.3.2. Small-Scale Horizontal Variability

Large gradients in NO 2 concentrations near roadways have been observed in several studies, and NO 2 concentrations have been found to be correla ted (or inversely correlated) with distance from roadway, traffic volume, season, road length, ope n space, and population density (Bignal et al., 2007; Cape et al., 2004; Gauderman et al., 2005; Gilbert et al., 2007; Maruo et al., 2003; Monn et al., 1997; Pleijel et al., 2004; Roorda-Knape et al., 1998; 1999; Singer et al., 2004). A sample gradient is shown in Figure 2.5-2. Singer et al. (2004) found a strong gradient for c oncentrations downwind of freeways within the first 230 m. An exponential decay model (e.g., Cape et al., 2004) has been fit to near-road concentration data to estimate NO 2 concentration as a function of distance from the roadway. Gilbert et al. (2007) found that associations remained robust when sites within 200 m of roadways were removed from the analysis, indicating that traffic influences concentrations as far as 2000 to 3000 m from roadways. Small-scale spatial variations in NO 2 concentrations are more pronounced during spring and summer seasons due to meteorology and increased photochemical activity (Monn, 2001).2-34 Source: Singer et al. (2004).
Figure 2.5-2. NO 2 and NO X concentrations normalized to ambient values, plotted as a function of downwind distance from the freeway. Symbols indi cate freeway closest to each monitor.

Localized effects of roadway sources lead to variability in NO 2 concentrations that is not captured by the regulatory monitoring network. This variati on affects population-level e xposure estimates and adds exposure error to time-series epidemiologic studies re lying on ambient concentrations as indicators of exposure. Elevated concentrations near roadways al so increase exposure of anyone residing, working, or attending school in the vicinity. As discussed in Ch apter 4, these elevated concentrations found near roadways may lead to increased vulnerability among t hose exposed to high near-roadway concentrations of NO 2 .



## 2.5.3.3. Small-Scale Vertical Variability

Inlets to instruments for monitoring gas-phase cr iteria pollutants can be located from 3 to 15 m above ground level (CFR, 2002). Depe nding on the pollutant, there can be a positive, negative, or no vertical gradient from the surface to the monitor in let. Positive gradients (i.e., concentrations increase with height) result when pollutants are formed ove r large areas by atmospheric photochemical reactions (i.e., secondary pollutants such as O 3 ) and destroyed by deposition to the surface or by reaction with2-35 pollutants emitted near the surface. Pollutants that are emitted by sources at or just above ground level show negative vertical gradients. Pollutants with area sources (widely dispersed surface sources) and that have minimal deposition velocities s how little or no vertical gradient. Restrepo et al. (2004) compared data for criteria pollutants collected at fixed monitoring sites at 15 m above the surface on a school rooftop to those measured by a van whose inlet was 4 m above the surface at monitoring sites in the South Bronx during two sampling periods in November and December 2001. They found that CO, SO 2 , and NO 2 showed negative vertical gradients, whereas O 3 showed a positive vertical gradient and PM 2.5 showed no significant vertical gradient. As shown in Figure 2.5-3, NO 2 mixing ratios obtained at 4 m (mean ~74 ppb) were about a factor of 2.5 highe r than at 15 m (mean ~30 ppb). Because tail pipe emissions occur at lower heights, NO 2 values could have been much higher nearer to the surface and the underestimation of NO 2 values by monitoring at 15 m even larger. Restrepo et al. (2004) noted that the use of the NO 2 data obtained by the stationary mon itors underestimates human exposures to NO 2 in the South Bronx. This situation is not unique to the Sout h Bronx and could arise in other large urban areas in the U.S. with similar settings. This adds anothe r dimension to the exposure assessment, namely, the exposure of pedestrians who spend time walking in th ese street canyons, and urban residents, who have windows opening onto these canyons. These groups may experience high exposures to near-road concentrations of the same magnitude as exposures that occur on or adjacent to arterial and interstate roadways.

Source: Restrepo et al. (2004).
Figure 2.5-3. NO 2 concentrations measured at 4 m (Van) and at 15 m at NY Department of Environmental Conservation ambient monitori ng sites(DEC709406 and DEC709407).2-36 The magnitude of the vertical gradient of NO 2 in street canyons depends strongly on the configuration of the buildings forming the canyons a nd the meteorological conditions; in particular, static stability in the lower planetary boundary layer, local wind direction and speed, and differential solar heating all affect turbulence in street canyons. Th ese meteorological factors also help determine the relative importance of turbulence induced by traffic, in addition to traffic volume and speed. Detailed descriptions of the effects for many of these factors are available only from complex numerical models such as large eddy simulations and very fine grid resolution computational fluid dynamics (CFD) models. A semi-empirical integral model with simplifying assumptions has shown reasonable correlation to measured NO 2 concentrations over moderate time scales (1 month) (Berkowicz et al., 2008), while other studies have applied such models to urban neighborhoods to estimate traffic emissions and evaluate the representativeness of air quality monitoring data (Ghenu et al., 2008; Mensink and Cosemans, 2008; Vardoulakis et al., 2005). By constructing simplified geometries, investigators can obtain good agreement between the performance of integral and CFD models; however, genera lization and quantitative application of these results to complex urban situati ons, even at the same location at different times, is difficult due to multi-scale variability in meteorological conditions, traffic composition and flow, building geometry, street dimensions, street canyon aspect ratio s, and building packing density (Di Sabatino et al., 2007). Weak associations might be found between concentr ations at ambient monitors and other outdoor locations and between concentrations in indoor microenvironments and pe rsonal exposures in part because of the spatial (horizontal and vertical) variability in NO 2 . This variability is itself location- and time-dependent, and can lead to either over- or unde restimates of exposure, depending on the siting of monitors and location of the exposed population. NO 2 ambient monitors may be less representative of community or personal exposures than are ambient monitors for O 3 or PM 2.5 for their respective exposures. This conclusion is based on a compar ison of metrics of spatial variability for O 3 or PM 2.5 used in the last PM AQCD (U.S. Environmental Protection Agency, 2004) and O 3 AQCD (U.S. Environmental Protection Agency, 2006a), indicating generally lowe r correlations and larger relative spreads in concentrations than for O 3 or PM 2.5 . As mentioned earlier, there are far fewer monitors for NO 2 than for O 3 or PM 2.5 , making estimation of the spatial variability in NO 2 levels more difficult.



# 2.5.4. NO 2 

# On or Near Roads

Lee et al. (2000) reported that NO 2 concentration in heavy traffic (~60 ppb) can be more than double that of the residential outdoor level (~26 ppb) in North America. Westerdahl et al. (2005) reported on-road NO 2 concentrations in Los Angeles ranging from 40 to 70 ppb on freeways, compared to 20 to 40 ppb on residential or arterial roads. NO X concentrations measured at the Caldecott Tunnel in San Francisco in 1999 (Kean et al., 2001) were approximately 7 -fold higher at the tunnel exit than at the entrance (1500 ppb versus 200 ppb). People in traffic can pot entially experience high concentrations of NO 2 as a result of the high air exchange rates in vehicles. Park et al. (1998) observed that the air exchange in cars varied from 1 to 3 times per hour, with windows closed and no mechanical ventilation, to 36 to 47 times per h, with windows closed and the fan set on fresh air. These results imply that the NO 2 concentration inside a vehicle could rapidly approach th e level outside the vehicle during commuting. While driving, concentrations fo r personal exposure in a vehicle cab in could be substantially higher than ambient concentrations measured nearby. Sabin et al. (2005) reported that NO 2 concentrations in the cabins of school buses in Los Angeles ranged from 24 to 120 ppb, which were typically factors of 2 to 3 (max, 5) higher than at ambient monitors in the ar ea. Lewné et al. (2006) reported work hour exposures to NO 2 for taxi drivers (25.1 ppb), bus drivers (31.4 ppb) , and truck drivers (35.6 ppb). These levels were 1.8, 2.7, and 2.8 times the ambient concentrations. Riediker et al. (2003) studied the exposure to NO 2 inside patrol cars. The authors found that the mean and maximum NO 2 concentrations in a patrol car were 41.7 ppb and 548.5 ppb compared to 30.4 ppb and 69.5 ppb for the ambient sites. These studies indicate that people in traffic can be exposed to much higher levels of NO 2 than are measured at ambient2-37 monitoring sites. Due to high peak exposures wh ile driving, total pers onal exposure could be underestimated if exposures while commuting are not considered, and sometimes exposure in traffic can dominate personal exposure to NO 2 (Lee et al., 2000; Son et al., 2004). Va riations in traffic-related exposure could be attributed to time spent in traffic, ty pe of vehicle, ventilation in the vehicle, and distance from major roads (Chan et al., 1999; Sabin et al., 2005; Son et al., 2004). Sabin et al. (2005) reported that the intrusion of the vehicle’s own exhaus t into the passenger cabin is another NO 2 source contributing to personal exposure while commuting, but that the frac tion of air inside the cabin from a vehicle’s own exhaust was small, ranging from 0.02 to 0.28% and increasing with the age of the vehicle (CARB, 2007a,b). Distance to major roadways could be anot her factor affecting indoor and outdoor NO 2 concentration and personal NO 2 exposure. Many studies show that outdoor NO 2 levels are strongly associated with distance from major roads (i.e., the clo ser to a major road, the higher the NO 2 concentration) (Cotterill and Kingham, 1997; Gilbert et al., 2005; Gonzales et al., 2005; Kodama et al., 2002; Lal and Patil, 2001; Nakai et al., 1995; Roorda-Knape et al., 1998). Mete orological factors (wind direction and wind speed) and traffic density are also important in interpreting measured NO 2 concentrations (Alm et al., 1998; Gilbert et al., 2005; Nakai et al., 1995; Roorda-Knape et al., 1998; Rotko et al., 2001; Singer et al., 2004). For example, Roorda-Knape et al. (1998) reported that NO 2 concentrations in classrooms were significantly correlated with car and total traffic de nsity (r=0.68), percentage of time downwind (r=0.88), and distance of the school from the roadway (r=-0.83). Singer et al. (2004) reported results of the East Bay Children’s Respiratory Health Study. The authors found that NO 2 concentrations increased with decreasing downwind distance for school and neighborhood sites within 350 m downwind of a freeway, and schools located upwind or far downwind of freeways we re generally indistingui shable from one another or by regional pollution levels. Personal exposure is associated with traffic density and proximity to traffic, although personal exposure is also influenced by indoor sources. Alm et al. (1998) reported that weekly avg NO 2 exposures (geometric mean) were higher (p=0.0001) for children living in the downtown area of Helsinki (13.8 ppb) than in the suburban area (9.1 ppb). Within the urban area of Helsinki, Rotko et al. (2001) observed that the NO 2 exposure was significantly associated with tr affic volume near homes. The average exposure level of 138 subjects having low or moderate traffi c near their homes was 12.3 ppb, while the level was 15.8 ppb for the 38 subjects having high traffic volume n ear home. Gauvin et al. (2001) reported that the ratio of traffic density to distance from a roadway was one of the significant predictors of personal exposure in Grenoble, Toulouse, and Paris. Afte r controlling for indoor source impacts on personal exposure, Kodama et al. (2002) and Nakai et al. (1995) observed that personal exposure decreased with increasing distance from residence to major road. Although traffic is a major source of ambient NO 2 , industrial point sources are also contributors to ambient NO 2 . Nerriere et al. (2005) measured personal exposures to PM 2.5 , PM with an aerodynamic diameter of ≤ 10 μm (PM 10 ), and NO 2 in traffic-dominated, urban bac kground, and industrial settings in four French cities (Paris, Grenoble, Rouen, and Strasbourg). Ambient concentrations and personal exposures for NO 2 were generally highest in the traffic-dominated sector. It should be remembered that there can be high traffic emissions (including shipping traffic) in industrial zones, such as in the Ship Channel in Houston, TX, and in the Port of Los Ange les, CA. In rural areas where traffic is sparse, other sources could dominate. Martin et al. (2003) found that pulses of NO 2 released from agricultural areas occur after rainfall. Other rural contributors to NO 2 include wildfires and residential wood burning.



# 2.5.5. Indoor Sources and Sinks of NO 2 

# and Associated Pollutants

Indoor sources and indoor air chemistry of NO 2 are important, because they influence the indoor NO 2 concentrations to which humans are exposed and contribute to total personal exposures. These indoor source and sink terms must be characterized in an exposure assessment if the fraction of a person’s exposure to NO 2 of ambient origin is to be determined.2-38 Penetration of outdoor NO 2 and indoor combustion in various forms are the major sources of NO 2 to indoor environments, e.g., homes, schools, restaurants, theaters. As might be expected, indoor concentrations of NO 2 in the absence of combustion sources are determined by the infiltration of outdoor NO 2 (Levy et al., 1998b; Spengler et al., 1994; Weschler et al., 1994). Contributions to indoor NO 2 from the reaction of NO in exhaled breath with O 3 could potentially be important in certain circumstances (see Annex section AX3.4.2 for sample calculations). Indoor sources of nitrogen oxides have been characterized in several reviews, namely the last NO X AQCD (U.S. Environmental Protection Agency, 1993); the Review of the Health Risks Associated w ith Nitrogen Dioxide and Su lfur Dioxide in Indoor Air for Health Canada (Brauer et al., 2002); and the Staff Recommendations for revision of the NO 2 standard in California (CARB, 2007a). Mechanisms by which NO X is produced in the combustion zones of indoor sources were reviewed in the last NO X AQCD (U.S. Environmental Protection Agency, 1993). It should be noted that indoor sources can affect ambient NO 2 levels, particularly in areas in which atmospheric mixing is unlikely, such as in valleys. Combustion of fossil and biomass fuels is the ma jor indoor source of nitrogen oxides. Combustion of fossil fuels occurs in appliances used for cooking, heating, and drying clothes, e.g., coal stoves, oil furnaces, kerosene space heaters. Motor vehicles and various types of generators in structures attached to living areas also contribute NO 2 to indoor environments. Indoor sources of NO 2 from combustion of biomass include wood-burning fireplaces and wood stoves and tobacco. Many studies have noted the importance of gas cooking appliances as sources of NO 2 emissions. Depending on geographical location, season, other sources of NO 2 , and household characteristics, homes with gas cooking appliances have appr oximately 50% to over 400% higher NO 2 concentrations than homes with electric cooking appliances (Garcia-Algar et al., 2003; Gilbert et al., 2006; Leaderer et al., 1986; Lee et al., 2000; Raw et al., 2004). Gas cooking appliances remain significantly associated with indoor NO 2 concentrations after adjusting for several f actors that influence exposures, including season, type of community, socioeconomic status, use of ex tractor fans, household smoking, and type of heating (Garcia Algar et al., 2004; Garrett et al., 1999). Homes with gas appliances with pilot lights emit more NO 2 , resulting in NO 2 concentrations ~10 ppb higher than in homes with gas appliances with electronic ignition (Lee et al., 1998; Spengler et al., 1994). Secondary heating appliances are additional sources of NO 2 in indoor environments, particularly if the appliances are unvented or inadequately vented. As heating costs increase, the use of these secondary heating appliances tends to increase. Gas heaters, pa rticularly when unvented or inadequately vented, produce high levels of indoor NO 2 (Kodama et al., 2002). Results summarized by Brauer et al. (2007) indicate that concentrations of NO 2 in homes with unvented gas hot water heaters were 10 to 21 ppb higher than in homes with vented heaters, which in turn, had NO 2 concentrations 7.5 to 38 ppb higher than homes without gas hot water heaters. On the other hand, mean concentrations of NO 2 were all <10 ppb in a study of Canadian homes with vented gas and oil furnaces and electric baseboard heaters (Weichenthal et al., 2007), indicating that these are not likely to be major sources of NO 2 to indoor environments. Table 2.5-2 shows avg concentrations of NO 2 in homes while combustion sources (mainly gas fired) were in operation. Averaging periods ranged from minutes to hours in the studies shown. Table 2.5-3 shows 24-h to 2-week -long avg concentrations of NO 2 in homes with primarily gas combustion sources. As can be seen from Tables 2.5-2 and 2.5-3, av erage concentrations while appliances are in operation tend to be much higher than longer-term aver ages. As Triche et al. (2005) indicated, the 90th percentile concentrations can be substantially greater than the medians, even for 2-week samples. This finding illustrates the high variability of indoor NO 2 found among homes, reflecting differences in ventilation of emissions from sources, air exchange rat es, the size of rooms, etc. The concentrations for short averaging periods listed in Table 2.5-2 corres pond to ~10 to 30 ppb on a 24-h avg basis. As can be seen from inspection of Table 2.5-3, these sources would contribute significantly to the longer-term averages reported if operated daily on a similar sche dule. This implies measurements made with long2-39 averaging periods may not capture the nature of th e diurnal pattern of indoor concentrations of NO 2 in homes with strong indoor sources, a problem that becomes more evident as ambient NO 2 levels decrease with more efficient controls on outdoor sources.

Table 2.5-2. NO 2 concentration near indoor sources: minute to hour averages.

STUDY AVERAGE CONCENTRATION (ppb) PEAK CONCENTRATION (ppb) COMMENT

Fortmann et al. (2001) 191 kitchen 195 living room 184 bedroom 375 kitchen 401 living room 421 bedroom Cooked full meal with gas range for 2 h, 20 min; 7 h TWA.

Fortmann et al. (2001) 400 kitchen living room bedroom 673 bedroom Self-cleaning gas range. Av gs are over the entire cycle.

Dutton et al. (2001) 90 (low setting) 350 (med setting) 360 (high setting) NR Natural gas unvented fireplace, 0. 5 h TWA in main living area of house (177 m 3 ).

Girman et al. (1982) NR 1000 Room concentration with kero sene heater operating for 46 min.

Girman et al. (1982) NR 1500 Room concentration with gas heater operating for 10 min.

Girman et al. (1982) 180 to 650 NR Calculated steady-state c oncentration from specific unvented gas space heaters 1 operating in a 1400 ft 2 house, 1.0/h for air exchange rate.

NR=not reported; TWA=time-weighted avg; 1 Unvented appliances are not permitted in many areas, including California.

Table 2.5-3. NO 2 concentration near indoor sources: 24-h to 2 week averages.

STUDY AVERAGE CONCENTRATION COMMENT

Lee et al. (1998) 30 to 33 ppb 22 ppb 6 to 11 ppb Gas stoves with pilot lights Gas stoves without pilot lights Electric ranges Study conducted in 517 homes in Bost on. Values represent 2-wk avgs

Triche et al. (2005) 55 (Median) 41 (90th percentile) 80 (90th percentile) 84 (90th percentile) 147 (90th percentile) 52 (90th percentile) Gas space heaters No indoor combustion sources Fireplaces Kerosene heaters Gas space heaters Wood stoves All values represent 2-wk avgs in living rooms

Zipprich et al. (2002) 18 ppb 19 ppb 15 ppb Bedrooms Living rooms Outdoors Almost all homes had gas stoves. Values represent 2-wk avgs2-40 The emissions of NO 2 from burning biomass fuels indoors have not been characterized as extensively as those from burning gas. A main conclusion from the 1993 NO X AQCD was that properly vented wood stoves and fireplaces would make only minor contributions to indoor NO 2 levels, and several studies have concluded that using wood-burning appliances does not increase indoor NO 2 concentrations (Lévesque et al., 2001; Triche et al., 2005). Other indoor combustion sources of NO 2 are candle burning and smoking. In a study of students living in Copenhagen, Sørensen et al. (2005) found that personal exposures to NO 2 were significantly associated with time exposed to burning candles in a ddition to other sources (data not reported). Results of studies relating NO 2 concentrations and exposures to envir onmental tobacco smoke (ETS) have been mixed. Several studies found positive associations between NO 2 levels and ETS (e.g., Alm et al., 1998; Cyrys et al., 2000; Farrow et al., 1997; Garcia Algar et al., 2004; Lee et al., 2000; Levy et al., 1998a; Linaker et al., 1996; Monn et al., 1998), whereas others have not (e.g., Hackney et al., 1992; Kawamoto et al., 1993).



## 2.5.5.1. Indoor Air Chemistry

Chemistry in indoor settings can be both a source and a sink for NO 2 (Weschler and Shields, 1997). NO 2 is produced by reactions of NO with O 3 or peroxyl radicals, while NO 2 is removed by gas-phase reactions with O 3 and assorted free radicals and by surface-pr omoted hydrolysis and reduction reactions. The concentration of indoor NO 2 also affects the decomposition of PAN. Indoors, NO can be oxidized to NO 2 by reacting with O 3 or peroxy radicals. The latter are generated by indoor air chemistry involving O 3 and unsaturated hydrocarbons such as terpenes found in air fresheners and other household products (Sarwar et al., 2002a; Sarwar et al., 2002b; Carslaw et al., 2007; Nazaroff and Weschler, 2004). At an indoor O 3 concentration of 10 ppb and an indoor NO concentration that is significantly smaller than that of O 3 , the half-life of NO is 2.5 min (using kinetic data contained in Jet Propulsion Laboratory, 2003). This reaction is sufficiently fast to compete with even relatively fast air exchange rates. Hence, the amount of NO 2 produced from NO tends to be limited by the amount of O 3 available (Weschler et al., 1994). NO 2 reacts with O 3 to produce nitrate radicals (NO 3 ). To date, there have been no indoor measurements of the concentration of NO 3 radicals in indoor settings. Modeling studies by Nazaroff and Cass (1986), Weschler et al. (1992), Sarwar et al. (2002b), and Carslaw (2007) estimate indoor NO 3 radical concentrations in the range of 0.01 to 5 ppt, depending on the indoor levels of O 3 and NO 2 . Once formed, NO 3 can oxidize organic compounds by either adding to an unsaturated carbon bond or abstracting a hydrogen atom (Wayne et al., 1991). In certain indoor settings, the NO 3 radical may be a more important indoor oxidant than either O 3 or the OH radical (Nazaroff and Weschler, 2004; Wayne et al., 1991). Thus, NO 3 radicals and the products of NO 3 radical chemistry could contribute to uncertainty in NO 2 exposure-health outcome studies Reactions between NO 2 and various free radicals can be an indoor source of organo-nitrates, analogous to the chain-terminating reactions obser ved in photochemical smog (Weschler and Shields, 1997). Additionally, based on laboratory measurements and measurements in outdoor air (Finlayson-Pitts and Pitts, 2000), one would anticipate that NO 2 , in the presence of trace amounts of HNO 3 , can react with PAHs sorbed onto indoor surfaces to produce mono- and dinitro-PAHs. NO 2 can also be reduced on certain surfaces, forming NO. Spicer et al. (1989) found that as much as 15% of the NO 2 removed on various indoor surfaces was reemitted as NO. (Weschler and Shields, 1996) found that the amount of NO 2 removed by charcoal filters used in buildings were almost equally matched by the amount of NO subsequently emitted by the same filters.2-41 NO 2 can also be converted to HONO by reactions in indoor air. As noted above, HONO occurs in the atmosphere mainly through multiphase processes involving NO 2 . HONO has been observed to form on surfaces containing partially oxidized aromatic stru ctures (Stemmler et al., 2006) and on soot particles (Ammann et al., 1998). Indoors, surface-to-volume ratios are much larger than they are outdoors, and the surface-mediated hydrolysis of NO 2 is a major indoor source of HONO (Brauer et al., 1990; 1993; Febo and Perrino, 1991; Lee et al., 2002; Spengler et al., 1993; Spicer et al., 1993; Wainman et al., 2001). Lee et al. (2002) reported average indoor HONO levels were ~6 times higher than outdoor levels (4.6 versus 0.8 ppb). Indoor HONO concentrations averaged 17% of indoor NO 2 concentrations, and the two were strongly correlated. Indoor HONO levels were highe r in homes with humidifiers compared to homes without humidifiers (5.9 versus 2.6 ppb). This last observation is consistent with the studies of Brauer et al. (1993) and Wainman et al. (2001), indi cating that the production rate of HONO from NO 2 surface reactions increases with relative humidity. Spicer et al. (1993) reported that an equilibrium between adsorption of HONO from the gas range (or other indoor combustion sources) and HONO produced by surface reactions determines the relative importan ce of these processes in producing HONO in indoor air. A person’s total exposure to NO 2 cannot be estimated based on consideration of the estimates of emissions given in emissions inventories. Indoor and other microenvironmental sources and a person’s activity pattern must be considered in determini ng the sources that exert the largest influence on a person’s total exposure to NO 2 . As examples, exposures in vehicle cabins while commuting to/from school or work, or exposures associated with operati on of off-road engines (e.g., lawn and garden or construction equipment), could be la rger than integrated 24-h exposures due to infiltration of outdoor air into a home.



# 2.5.6. Relationship of Personal Exposure to Ambient Concentrations

2.5.6.1. Associations between Personal Exposure and Ambient and Outdoor Concentrations

Results of studies reporting associations between ambient concentrations and personal exposures are shown in Table 2.5-4 for longitudinal correlati on coefficients, Table 2.5-5 for pooled correlation coefficients. Results of studies reporting associati ons between outdoor concen trations and personal exposures are shown in Table 2.5-6. Study designs (longitudinal, daily-averaged, and pooled) used in these studies are summarized in Tables 2.5-4 and 2.5-5.2-42 Table 2.5-4. Association between personal ex posure and ambient concentration (longitudinal correlation coefficients).

STUDY METHODS MEAN CONCENTRATION ASSOCIATION VARIABLE LOCATION SEASON r p , r s , or R 2

Linaker et al. (2000)

Location: Southampton, Hampshire, UK Time period: Oct 1994 to Dec 1995 Type: Longitudinal Subjects: 114 asthmatic children, aged 7-12

Method: at leas t 16 consecutive samples (1-wk avgs) for eachchild (mean duration of followup: 32 wks). Ambient: 6.5 ppb Personal: 8.9 ppb Personal vs. central(overall measurements across children and time)

Personal vs. central (subject-wise) Pooled, urban, no major indoor sources By person Pooled Not significant (n=NR)

-0.77 to 0.68 and median -0.02 (r p ) (n=NR)

Kim et al. (2006)

Location: Toronto, Canada Time period: Aug 1999 to Nov 2001 Type: Longitudinal Subjects: 28 adults with coronary artery disease Method: 1 day/wk, 24-h avg, for a max of 10 wks for each person. Ambient: 24 ppb Personal: 14 ppb Personal vs. central (subject-wise) Urban Pooled -0.36 to 0.94 (r s ) with a median of 0.57 (15 subjects)

Sarnat et al. (2001)

Koutrakis et al. (2005)

Location: Baltimore, MD Time period: summer of 1998 and winter of 1999 Type: Longitudinal Subjects: 56 seniors, schoolchildren, and people with COPD Method: 14 of 56 subjects participated in both sampling seasons; all subjects were monitored for 12 consecutive days (24-h avg samples) in each of the one or two seasons, except children, who were measured for 8 consecutive days during the summer. Ambient: 20–25 ppb Personal: 10–15 ppb Personal vs. central (subject-wise) Urban Summer

Winter -0.45 to 0.85 (r s ) with a median of 0.05* (24 subjects) -0.6 to 0.75 (r s ) with a median of 0.05* (45 subjects)

Sarnat et al. (2005)

Koutrakis et al. (2005)

Location: Boston, MA Time period: summer of 1999; winter of 2000 Type: Longitudinal Subjects: 43 seniors and schoolchildren Method: Similar study design as Sarnat et al. (2001). Ambient: 21.1– 32.6 ppb

Personal: 10.6– 29.6 ppb Personal vs. central (subject wise) Urban Summer

Winter -0.25 to 0.5 (r s ) with a median of 0.3* (n=NR) Slope=0.19 (95% CI, 0.08- 0.30) -0.5 to 0.9 (r s ) with a median of 0.4* (n=NR) Slope=-0.03 (95% CI, -0.21- 0.15)

* Values were estimated from figures in the original paper. ** NR: Not Reported.2-43 Table 2.5-5. Association between personal exposure and ambient concentration (pooled correlation coefficients).

STUDY STUDY DESIGN MEAN CONCENTRATION ASSOCIATION VARIABLE LOCATION SEASON r p , r s , or R 2

Linn et al. (1996)

Location: Southern California Time period: fall, winter, spring, 1992-1994 Type: Longitudinal Subjects: 269 school children Method: 24-h avg, 1-wk consecutive measurement for each season for each child. Ambient: 37 ppb Personal: 22 ppb Personal vs. central Pooled Pooled 0.63 (r p ) (n=107)

Personal vs. central Downtown Spring 0.64 (r p ) p<0.001 (n=NR**)

Personal vs. central Suburban Spring 0.78 (r p ) p<0.001 (n=NR)

Personal vs. central Downtown Winter -0.06 (r p ) p >0.05 (n=NR)

Personal vs. central Suburban Winter 0.32 (r p ) p >0.05 (n=NR)

Personal vs. central Downtown (electric stove home) Pooled 0.42 (r p ) p<0.01 (n=NR)

Personal vs. central Downtown (gas stove home) Pooled 0.16 (r p ) p >0.01 (n=NR)

Personal vs. central Suburban (electric stove home) Pooled 0.55 (r p ) p<0.001 (n=NR)

Personal vs. central Downtown (non-smoking home) Pooled 0.47 (r p ) p<0.001 (n=NR)

Personal vs. central Downtown (smoking home) Pooled 0.23 (r p ) p >0.01 (n=NR)

Personal vs. central Suburban (non-smoking home) Pooled 0.53 (r p ) p<0.001 (n=NR)

Personal vs. central Suburban (smoking home) Pooled 0.52 (r p ) p<0.001 (n=NR) Alm et al. (1998)
Location: Helsinki, Finland Time period: winter and spring, 1991 Type: Longitudinal Subjects: 246 children aged 3-6 yrs old Method: 1-wk averaged sample for each person, 6 consec utive wks in the winter and 7 consecutive wks in the spring. Ambient: 16.8– 26.3 ppb Personal: 9–16.6 ppb

Personal vs. central Pooled Pooled 0.37 (R 2 ) (n=24)

Adults vs. central Urban Summer 0.41 (R 2 ) p<0.0001 (n=NR) Liard et al. (1999)
Location: Paris, FranceTime period: MayJune 1996 Type: Daily avg/cross-sectional Subjects: 55 adults and 39 childrenMethod: Three 4-day avg measurements for each person, during each measurement session, all subjects measured at same time. Ambient: 26.3– 36.8 ppb

Personal: 15.8– 26.3 ppb Children vs. central Urban Summer 0.17 (R 2 ) p=0.0004 (n=NR)2-44 STUDY STUDY DESIGN MEAN CONCENTRATION ASSOCIATION VARIABLE LOCATION SEASON r p , r s , or R 2

Personal vs. central (Grenoble) Urban Pooled 0.01 (R 2 ) (n=NR)

Personal vs. central (Toulouse) Urban Pooled 0.04 (R 2 ) (n=NR) Gauvin et al. (2001)

Location: 3 French metropolitan areasTime period: AprJune 1998 in Grenoble; May-June 1998 in Toulouse; June-Oct 1998 in Paris Type: Daily avg/cross-sectional Subjects: 73 children Method: one 48-h avg measurement for each child; all children in the same city were measured on the same day. Ambient: 10.2– 25.7 ppb Personal: 13.2–17 ppb

Personal vs. central (Paris) Urban Pooled 0.02 (R 2 ) (n=NR)

Personal (exposure at home) vs. central Urban Pooled 0.09 (R 2 ) p=0.0101 (n=NR) Piechocki-Minguy et al. (2006)

Location: Lille (northern France) Time period: winter 2001 (first campaign); summer 2002 (second campaign) Type: Pooled Subjects: 13 in 1 st campaign, 31 in 2 nd
Method: two 24-h sampling periods (1on workdays; 1on weekends) for each subject in each campaign; during each sampling period, each subject received 4 samplers to measure personal exposure in 4 different microenvironments (home, other indoor, transport, and outdoors). Ambient: 15.8– 57.9 ppb

Personal: 8.9– 20.0 ppb Personal (exposure at home) vs. central Urban (electric stove and electric heater home) Summer 0.61 (R 2 ) p=0.0001 (n=NR)

Summer 0.14 (R 2 ) (n=122) p<0.05 Sarnat et al. (2006)

Location: Steubenville, OH Time period: summer and fall of 2000 Type: Longitudinal Subjects: 15 senior subjects

Method: two c onsecutive 24-h samples were collected for each subject for each wk, 23 wks total Ambient: 9.5–11.3 ppb

Personal: 9.9– 12.1 ppb Personal vs. central Urban

Fall 0.43 (R 2 ) p<0.05 (n=138)

* Values were estimated from figures in the original paper.

Table 2.5-6. Association between personal exposure and outdoor concentration.

STUDY METHODS ASSOCIATION VARIABLE LOCATION SEASON r p , r s , or R 2

Personal vs. outdoor Pooled Pooled 0.37 (r p ) (n=281) Krämer et al. (2000)

Location: Germany Time period: Mar and Sep 1996 Subjects: 191 children Method: two 1-wk averaged measurements for each child in each mo. Personal vs. outdoor Urban Pooled 0.06 (r p ) (n=182)

Rojas-Bracho et al. (2002)

Location: Santiago, Chile Time period: winters of 1998 and 1999 Subjects: 20 children Method: five 24-h avg sa mples for 5 consecutive days for each child. Personal vs. outdoor Urban Winter 0.27 (R 2 ) (n=87)2-45 STUDY METHODS ASSOCIATION VARIABLE LOCATION SEASON r p , r s , or R 2

Personal vs. outdoor Urban Pooled 0.15 (R 2 ) (n=97) Raaschou- Nielsen et al. (1997)

Location: Copenhagen, Denmark and rural areas Time period: Oct 1994, Apr, May, and June 1995 Subjects: 204 children Method: two 1-wk avg measurements for each child in each mo. Personal vs. outdoor Rural Pooled 0.35 (R 2 ) (n=99)

Personal vs. outdoor Downtown Winter 0.46 (r p ) (n=NR)

Personal vs. outdoor Suburban Winter 0.49 (r p ) (n=NR)

Personal vs. outdoor Downtown Spring 0.80 (r p ) (n=NR)

Personal vs. outdoor Suburban Spring 0.82 (r p ) (n=NR)

Personal vs. outdoor Downtown (electric stove home) Pooled 0.55 (r p ) (n=NR)

Personal vs. outdoor Downtown (gas stove home) Pooled 0.59 (r p ) (n=NR)

Personal vs. outdoor Suburban (electric stove home) Pooled 0.63 (r p ) (n=NR)

Personal vs. outdoor Downtown (nonsmoking home) Pooled 0.73 (r p ) (n=NR)

Personal vs. outdoor Downtown (smoking home) Pooled 0.51 (r p ) (n=NR)

Personal vs. outdoor Suburban (nonsmoking home) Pooled 0.59 (r p ) (n=NR)

Personal vs. outdoor Suburban (smoking home) Pooled 0.46 (r p ) (n=NR) Alm et al. (1998)

Location: Helsinki, Finland Time period: winter and spring of 1991 Subjects: 246 children aged 3-6 yrs old Method: 1-wk averaged sample for each person for 6 consecutive wks in the winter and 7 consecutive wks in the spring.

Personal vs. outdoor Pooled Pooled 0.86 (R 2 ) (n=23)

Monn et al. (1998)

Location: Geneva, Basel, Lugano, Aarau, Wald, Payerne, Montana, andDavos (SAPALDIA study, Switzerland) Time period: Dec 1993 to Dec 1994 Subjects: 140 subjects Method: each home was monitored for 3 periods of 1 mo; in the 1st wk of each period, personal, indoor rand outdoor levels were measured, and in the next 3 consecutive wks, only outdoor levels were measured (1-wk averaged measurement). Personal vs. outdoor Pooled Pooled 0.33 (R 2 ) (n=1,494)2-46 STUDY METHODS ASSOCIATION VARIABLE LOCATION SEASON r p , r s , or R 2

Levy et al. (1998a)

Location: 18 cities across 15 countries Time period: Feb or Mar 1996 Subjects: 568 adults Method: one 2-day avg measurement for each person, all people were measured on the same winter day. Personal vs. outdoor Urban Winter 0.57 (r s ) (n=546)

Personal vs. outdoor Urban Summer 0.24 (r p ) (n=NR) Kodama et al. (2002)

Location: Tokyo, Japan Time period: Feb 24-26, June 2-4, July 13-15, and Oct 14-16 in 1998 and Jan 26-28 in 1999 Subjects: 150 junior-high school students and their family members Method: 3-day avg, per sonal exposures were monitored on the same day. Personal vs. outdoor Urban Winter 0.08 (r p ) (n=NR)

Spengler et al. (1994)

Location: Los Angeles Basin, CA Time period: May 1987 to May 1988 Subjects: probability-based sample, 70 subjects Method: each participant was monitored during each of 8 cycles (48-h avg sampling period) throughout the yr in the microenvironmental component of the study. Personal vs. outdoor Pooled Pooled 0.48 (R 2 ) (n=NR)

Lai et al. (2004b)

Location: Oxford, England Time period: Dec 1998 to Feb 2000 Subjects: 50 adults Method: one 48-h avg meas urement per person. Personal vs. outdoor Urban Pooled 0.41 (r p ) (n=NR)

* Values were estimated from figures in the original paper ** NR: Not Reported.

Figures 2.5-4 and 2.5-5 explicitly summarize th e correlation coefficients between personal exposures and ambient concentrations for different popul ations with a forest plot for U.S. studies and European studies, respectively. Correlation coefficien ts and their 95% confidence intervals (CIs) shown in Figures 2.5-4 and 2.5-5 were transformed from the coefficients in Tables 2.5-4 and 2.5-5 with the consideration of the type of exposure studies. Fisher ’s Z transform was used, (Z=0.5ln [(1+r)/(1 - r)]), where r is the originally reported and Z is the tr ansformed correlation coefficient (Fisher, 1925). The variance of Z is expressed as 1/(n-3), where n is the number of observations defined by one of the following three presentations; (1) when the correla tion coefficient was based on the average across subjects of personal exposures, n was the number of sampling days, (2) when the partial correlation coefficient was used in the original study, n was th e total number of sampling by individual observations minus the sum of three and the number of covariates, and (3) when the mean of individual correlations was used, the standard error was the standard deviati on of the correlations divided by the square root of the number of subjects minus one.2-47 Figure 2.5-4. Distribution of correlation coe fficients (U.S. studies) between personal NO 2 exposure and ambient NO 2 concentrations based on Fisher’s Z transform.

Two main aspects of these analyses are discussed below: (1) the meanings of the correlation coefficients in the context of exposure assessments in epidemiologic studies, and (2) factors affecting the strength of the association between personal NO 2 exposure and ambient NO 2 concentrations. In the context of determining the effects of ambient pollutants on human health, the association between the ambient component of personal exposures a nd ambient concentrations is more relevant than the association between personal total exposures (ambient component+nona mbient component) and ambient concentrations. As described in Equations 2.5-2 and 2.5-4, persona l total exposure can be decomposed into two parts; an ambient and a nonamb ient component. Usually, the ambient component of personal exposure is not directly measurable, but it can be estimated by exposure models, or the personal total exposure can be regarded as the personal expos ure of ambient origin if there are no indoor or nonambient sources. Personal exposures were clearly stratified by indoor sources in only four studies among the studies examined for NO 2 (Alm et al., 1998; Linaker et al., 2000; Piechocki-Minguy et al., 2006; Sarnat et al., 2006) and only two studies (A lm et al., 1998; Piechocki-Minguy et al., 2006) compared the association between personal total exposures and ambient concentrations and the association between the ambient component of pe rsonal exposures and ambient concentrations. A stronger association was observed between the ambien t component of personal exposures and the ambient concentrations (Alm et al., 1998; Piechocki-Minguy et al., 2006). It is expected that the association between ambient concentrations and the ambient component of personal e xposures would be stronger than the association between ambient concentrations and personal total exposures as long as the ambient and nonambient component of pers onal total exposure are independent . The correlation coefficients between personal ambient NO 2 exposures and ambient NO 2 concentrations in different types of exposure studies are relevant to different types of epidemiologic studies. There are three types of correlations generated fro m the different study designs as listed in Tables 2.5-4 and 2.5-5: longitudinal, “ pooled,” and daily-average correlati ons (U.S. Environmental Protection Agency, 2004).2-48 Figure 2.5-5. Distribution of correlation coeffi cients (European studies) between personal NO 2 exposure and ambient NO 2 concentrations based on Fisher’s Z transform.

Longitudinal correlations 1 are calculated when data from a study includes consecutive multiple measurements for each subject (longitudinal study design). Longitudinal correlations describe the temporal relationship between personal NO 2 exposure or microenvironment concentration and ambient NO 2 concentration for the same subject. The longit udinal correlation coefficient can differ between subjects (i.e. each person may have a different correlati on coefficient). The distribution of correlations for each subject across a population could be obtained with this type of data (e.g., Kim et al., 2006; Linaker et al., 2000; Sarnat et al., 2000; 2001; 2005). A longitudinal correlation coefficient between the ambient component of personal exposures and am bient concentrations is relevant to the panel epidemiologic study design. In Table 2.5-4, most longitudinal studi es reported the association between personal total exposures and ambient concentrations for each subject; for some subjects the associations were strong and for some subjects the associations were weak. Th e weak personal and ambient associations do not necessarily mean that ambient concentrations are not a good surrogate for personal exposures, because the weak associations could have resulted from the day- to-day variation in the nonambient component of total personal exposure. The type of correlation analysis can have a substantial effect on the value of the resultant correlation coefficient. Mage et al. (1999) showed that very low co rrelations between personal exposure and ambient concentrations could be obtai ned when people with very different nonambient exposures are pooled, even though their indivi dual longitudinal correlations are high.

1 

# ( ) ( )
( )

a x j j i ij

ax 

### s s n a a x x

r

i i 

### 1

− − −

= 

# ∑

where “r” is the longitudinal correlation coefficient between personal exposure and ambient concentration, “ a ” represents the ambi ent concentration,

“ x

” represents exposure, “ i ” represents the i th subject, “ j ” represents the j th measurement (with the averaging time ranging from two days to two weeks for NO 2 measurement), “ s ” represents the standard deviation, and “ n ” in the longitudinal studies is the number of measurement s for each subject. The ambient concentration a j could be measured by one ambient monitor or the average of several ambient monitors.2-49 Pooled correlations 1 are calculated when a study involves one or only a few measurements per subject and when different subjects are studied on subsequent days. Pooled correlations combine individual-subject/individual-day data for the calculati on of correlations. Pooled correlations describe the relationship between daily personal NO 2 exposure and daily ambient NO 2 concentration across all subjects in the study (e.g., Alm et al., 1998; Gauvin et al., 2001; Liard et al., 1999; Linn et al., 1996; Piechocki-Minguy et al., 2006; Sarnat et al., 2006). Daily-average correlations 2 are calculated by averaging exposure across subjects for each day. Daily-average correlations then describe the relati onship between the daily average exposure and daily ambient NO 2 concentration (e.g., EPA, 2004; Gauvin et al ., 2001; Liard et al., 1999; Monn, 2001). This type of correlation (i.e. the association between co mmunity average exposures (ambient component) and ambient concentrations) is more directly releva nt to community time-series and long-term cohort epidemiologic studies, in which ambient concentrati ons are used as a surrogate for community average exposure to NO 2 of ambient origin. However, exposure of the population to NO 2 of ambient origin has not been reported in all the studies examined. The following two European studies reported the associations between population total exposures a nd ambient or outdoor concentrations of NO 2 . Liard et al. (1999) conducted an exposure study of 55 offi ce workers and 39 children in Paris. Measurements were made during three 4-day-long measurement pe riods for each group. Apart from occasional lapses, data from the same participants were collected during each period. Liard et al. (1999) correlated the fivepanel average personal exposures with ambient mon itoring data and derived a longitudinal Spearman correlation coefficient of 1 (p<0.001). R 2 between ambient monitors a nd individual personal exposures for adults was 0.41, and for children, R 2 was 0.17. Four-day averaging periods were chosen in this study to overcome limitations imposed by the levels of detec tion of the personal samplers. The results show that passive samplers could be used to measure persona l exposures in panel studies over multiday periods and lend some credence to the use of stationary mon itors as proxies for personal exposures to ambient NO 2 . Monn et al. (1998) and Monn (2001) reported personal NO 2 exposures obtained in the Study of Air Pollution and Lung Diseases in Adults (SAPALDIA) study (eight study centers in Switzerland). In each study location, personal exposures for NO 2 were measured simultaneously for all participants; in addition, residential outdoor concentrations were measured for 1 year (Table 2.5-6). Monn (2001) observed a strong association between the average personal exposures in each study location and corresponding average outdoor concentrations with an R 2 of 0.965. As pointed out by the author, in an analysis of individual single exposure and outdoor concen tration data, persona l versus outdoor R 2 was less than 0.3 (Monn et al., 1998). Because spatial heterogeneity in NO 2 concentrations likely produces stronger associations between average personal exposures and resi dential monitors than with central site ambient monitors in urban areas, caution should be exercised in using these data to infer that long-term averaged ambient concentrations are a good surrogate for popul ation exposures in long-term cohort epidemiologic studies. Not only does the exposure study design determine th e meaning of the correlation coefficients in the context of exposure assessment in epidemiologic studies, but it also affects the strength of the association between personal exposures and ambient concentrations. The strength of the association

1 

# ( ) ( )
( )

a x j i j ij

ax 

### s s n a a x x

r 1 ,



### − − −

= 

# ∑

where “ n ” is the number of paired measurements of exposure and ambient concentra tion, and all other symbols are defined the same way as those in the longitudinal correlation coefficient.

2 

# ( ) ( )
( )

a x j j j

x a 

### s s n a a x x

r

j 

### 1

− − −

= 

# ∑

,

where n is the number of measurement peri od, during each of which the exposure for all subjects ar e measured, and all other sym bols are defined the same way as those in the l ongitudinal correlation coefficient.2-50 between personal exposures and ambien t and/or outdoor concentrations fo r a population is determined by variations in several physical factors: indoor or othe r local sources, air exchange rate, penetration, and decay rate of NO 2 in different microenvironments a nd the time people spend in different microenvironments with different NO 2 concentrations. For different types of correlation coefficients, the components of the variance of these physical factors are different, and therefore the strength of different types of correlation coefficients is different. Longitudi nal correlation coefficients reflect the intra-personal variations of these physical factors; pooled correlati on coefficient reflect both inter- and intra- personal variations of these physical factors; and for the association between community average exposures and ambient concentrations, inter-personal variations of these physical factors are reduced by averaging personal exposures across a community. Therefore, th e strength of the associations between personal exposures and ambient concentrations may not be comparable directly, although these associations are determined by the same set of physical factors (but affected in different ways). Since correlations are standardized quantities that depend on multiple features of the data, in a correlation, not only is the linear “relatedness” (covari ance) of the two quantities important, but so is the variability of each, which can be affected by e xposure factors in various ways. In the following assessments, the effects of these physical factors on the strength of correlation coefficients are primarily examined within a study, and the purpose of the inter-s tudy comparison is to examine the consistency of the effects across different (types of) studies. Home ventilation is an important factor modify ing the personal-ambient relationships; one would expect to observe the strongest associations for subjects spending time indoors with open windows. Alm et al. (1998) and Kodama et al. (2002) observed th e association between personal exposure and ambient concentration became stronger during the summer than th e winter. However, Sarnat et al. (2006) reported that R 2 values decreased from 0.34 for a low-ventilation population to 0.16 for a high-ventilation population in the summer, and from 0.47 for a low- ventilation population to 0.34 for a high-ventilation population in the fall. The mixed results serve as a reminder that the association between personal exposures and ambient concentrations is comp lex and determined by many factors. Local and indoor sources also affect the strength of the association between personal exposures and ambient concentrations. Alm et al. (1998) found th at the association between personal exposure and outdoor concentration was stronger than the correla tion between personal exposure and central site concentration. However, Kim et al. (2006) found that the association was not improved using the ambient sampler closest to a home. The lack of improvement in the strength of the association by choosing the closest ambient monitor could be in part due to the differences in the small-scale spatial heterogeneity of NO 2 in different urban areas, as shown in Table 2.5-1. Higher personal to ambient correlations have been found for subjects living in rural areas and lower corre lations for subjects living in urban areas (Alm et al., 1998; Rojas-Bracho et al., 2002). Spengler et al. (1994) also observed that the relationship between personal exposure and outdoor c oncentration was highest in areas with lower ambient NO 2 levels (R 2 =0.47) and lowest in areas with higher ambient NO 2 levels (R 2 =0.33). This might reflect the highly heterogeneous distribution or the effect of local sources of NO 2 in an urban area. Associations between ambient concentrations a nd personal exposures for the studies examined for NO 2 were not stratified by the presence of indoor sources except in Alm et al. (1998), Sarnat et al. (2006), Linaker et al. (2000) and Piechocki-Minguy et al. (2006). When there is little or no contribution from indoor sources, ambient concentrations primarily determine exposure; however, if there are indoor sources, the importance of outdoor levels in dete rmining personal exposures decreases. The association between ambient or outdoor concentrations and pe rsonal exposures strengthens after controlling for indoor sources. Raaschou-Nielsen et al. (1997), Spengler et al. (1994), and Gauvin et al. (2001) reported that R 2 values increased by 10 to 40% after controlling for indoor sources, such as gas appliances and ETS (see Tables 2.5-4 through 2.5-6). The strength of the associations between personal exposures and ambient and outdoor concentrations could also be affected by the quality of the data collected during the exposure studies. There are at least six aspects associ ated with the quality of the data: method precision, method accuracy2-51 (compared with FRM), percent of data above method detection limits (based on field blanks), completeness of the data collection, sample size, and soundness of the quality assurance/quality control procedures. Unfortunately, not all studies reported th e aspects of the data quality issue. Although data imprecisions and inaccuracies are less than 10% in most studies (Section 2.5.2), the fraction of data below the detection limit might be a concern for some studies (see e.g., Sarnat et al., 2000; 2001; 2006). Correlation coefficients would be biased low if data used in their calculation are below detection limits. Sampling interferences (caused by some NO Y compounds and other gas species) associated with both ambient (see Section 2.3) and personal sampling (see Section 2.5.2) could also affect data quality. Therefore, caution must be exercised when interp reting the results in Tables 2.5-4 and 2.5-5. In summary, the evidence relating ambient levels to personal exposures is inc onsistent. Some of the longitudinal studies examined found that ambient levels of NO 2 were reliable proxies of personal exposures to NO 2 . However, a number of studies did not find significant associations between ambient and personal levels of NO 2 . The differences in results are related in large measure to differences in study design and in exposure determinants. Measurement ar tifacts and differences in analytical measurement capabilities could also have contributed to the incons istent results. Indeed, in a number of the studies examined, the majority of measurements of personal NO 2 concentrations were beneath detection limits, and in all studies some personal measure ments were beneath detection limits.



## 2.5.6.2. Ambient Contribution to Personal Exposure

Another aspect of the relationship of personal NO 2 exposure and ambient NO 2 is the contribution of ambient NO 2 to personal exposures. The infiltration factor ( F inf

) and alpha ( α ) are the keys to evaluate personal NO 2 exposure of ambient origin. As define d in Equations 2.5-2 through 2.5-5, the F inf

of NO 2 , the physical meaning of which is the fraction of ambient NO 2 found in the indoor environment, is determined by the NO 2 penetration coefficient ( P ), air exchange rate ( a ), and the NO 2 decay rate ( k ). Alpha ( α ) is a function of F inf

and the fraction of time people spend outdoors ( y ), and the physical meaning of α is the ratio of personal ambient exposure concen tration to ambient concentration, (i.e., in the absence of exposures to nonambient sources (i.e., when E na =0). The values for α and F inf

can be calculated physically using Equations 2.5-2 through 2.5-5, if P
, k
, a , and y are known. However, the values of P and k for NO 2 are rarely reported, and in most mass balance modeling work, P is assumed to equal 1 and k is assumed to equal 0.99/h (Dimitroulopoulou et al., 2001; Kulkarni and Patil, 2002; Yamanaka, 1984; Yang et al., 2004b). Loupa et al. (2006) reported that k was 0.08 to 0.12/h for NO and 0.04 to 0.11/h for NO 2 based on real-time measurements in two medieval churches in Cyprus. It is well known that P and k are dependent on a large num ber of indoor parameters, such as temperature, relative humidity, surface prope rties, surface-to-volume ratio, the turbulence of airflow, building type, and coexisting pollutants (Co tterill and Kingham, 1997; Garcia-Algar et al., 2003; Lee et al., 1996; Monn et al., 1998; Sørensen et al., 2005; Zota et al., 2005). As a result, using a fixed value, as mentioned above, would eith er over- or underestimate the true α or F inf

. Although specific P
, k , and a were not reported by most studies, a number of studies investigated factors affecting P
, k , and a (or indicators of P
, k , and a ), and their effects on indoor and personal exposures (Cotterill and Kingham, 1997; Garcia-Algar et al., 2003; Lee et al., 1996; Monn et al., 1998; Sørensen et al., 2005; Zota et al., 2005). García-Algar et al. (2003) observed that double-glazed windows had a significant effect on indoor NO 2 concentrations. Homes with double-glazed windows had lower indoor concentrations (6 ppb lower) than homes with single-glazed windows. Cotterill and Kingham (1997) reported that having single- or double-glazed windows was a significant factor affecting NO 2 concentrations in kitchens in homes with gas-c ookers (31.4 ppb and 39.8 ppb for homes with single- anddouble-glazed windows, respectively). The reduction of ventilation resulting from the presence of doubleglazed windows can block outdoor NO 2 from coming into the indoor environment, and at the same time can also increase the accumulation of indoor generated NO 2 .2-52 A similar effect was found for homes using air conditioners. Lee et al. (2002) observed that NO 2 was 9 ppb higher in homes with an air conditioner than in homes without. The authors also observed that the use of a humidifier would reduce indoor NO 2 by 6 ppb. House type was another factor reported affecting ventilation (Garcia-Algar et al., 2003; Lee et al., 1996). Lee et al. (1996) reported that the building ty pe was significantly associated with air exchange rate: the air exchange rate ranged from 1.04/h fo r single dwelling unit to 2.26/h for large multiple dwelling unit. Zota et al. (2005) reported that the air exchange rates were significantly lower in the heating season than the nonheating season (0.49/h fo r the heating season and 0.85/h for the nonheating season). Steady state models based on equations 2.5-2 thr ough 2.5-5 are typically used to simulate indoor and outdoor concentrations and pers onal exposures. However, the assumption of steady state could result in missing peak exposures and obscuring the real shor t-term outdoor contributi on to indoor and personal exposure. For example, the NO 2 concentrations at locations close to busy streets vary with traffic density, wind direction and speed etc. If steady state is assumed, the real-time indoor/outdoor concentration ratio may indicate either a too low relative importance of indoor sources (if concentrations outdoors are increasing) or a too high relative importance of indoor sources (if concentrations outdoors are decreasing) (Ekberg, 1996). The time dependence of indoor and outdoor sources and meteorological conditions can affect P
, k , and a , and thus affect the relations hips between indoor and outdoor NO 2 concentration and between personal exposure and outdoor NO 2 concentrations on short time scales. Thus, relationships
among P
, k , and a derived using a steady state model might not be representative of short term values. It should also be pointed out that both P and k are functions of complex physical and chemical processes that occur on indoor surfaces and therefore are associated with indoor-outdoor air exchange, which in turn affects indoor air flows. Alternatively, the ratio of personal exposure to ambient concentration can be regarded as α in the absence of indoor or nonambient sources. Only a few studies have reported the value and distribution of the ratio of personal NO 2 exposure to ambient NO 2 concentration, and even fewer studies have reported the value and distribution of α based on sophisticated study designs. Rojas-Bracho et al. (2002) reported the median personal-outdoor ratio was 0.64 (with an IQR of 0.45), but the authors reported that α was overestimated by this ratio because of indoor sources. The random component superposition (RCS) mode l is an alternative way to calculate F inf

or α using observed ambient and personal exposure concentrati ons (Ott et al., 2000). The RCS statistical model (shown in Equations 2.5-2 through 2.5-5) uses the sl ope of the regression line of personal concentration on the ambient NO 2 concentration to estimate the population av eraged attenuation factor and means and distributions of ambient and nonamb ient contributions to personal NO 2 concentrations (the intercept of the regression is the averaged nonambient contribu tion to personal exposure) (U.S. Environmental Protection Agency, 2004). As shown in Annex Table AX3.5-1a, F inf

ranges from 0.4 to 0.7. Similarly, as shown in Annex Table AX3.5-1b, α , calculated by the RCS model, ranges from 0.3 to 0.6. The RCS model calculates ambient contributions to indoor concentrations and personal exposures based on the statistical inferences of regression anal ysis. However, personal-out door regressions could be affected by extreme values (outliers on either the x or the y axis). Another limitation of the RCS model is that this model is not designed to estimate ambient and nonambient contributions for individuals, in part because the use of a single value for α does not account for the large home-to-home variations in actual air exchange rates and penetration and decay rates of NO 2 . In the RCS model, α is also determined by the selection of the predictor. Using residential outdoor NO 2 concentrations as the model predictor might give a different estimate of α than using ambient NO 2 because of the spatial variability of NO 2 mentioned early in this section. As mentioned earlier, personal NO 2 exposure is affected not only by air infiltrating from outdoors but also by indoor sources (see Section 2.5.5). Nerriere et al. (2005) used data from the Genotox ER study in France (Grenoble, Paris, Rouen, and Strasbourg) and reported that factors affecting th e differences between personal exposure to ambient NO 2 and corresponding ambient monitoring site concentra tions were season, city, and land use dependence.2-53 During the winter, city and land use categorization account for 31% of the variation, and during the summer, 54% of the variation can be explained by these factors. When data from the ambient monitoring site were used to represent personal exposures, th e largest difference between ambient and personal exposure was found at the “proximity to traffic” site, while the smallest difference was found at the “background” site. When using data from the urban background site, the largest difference was observed at the “industry” site, and the smallest difference w as observed at the background site, which reflected the heterogeneous distribution of NO 2 in an urban area. During winter, differences between ambient site and personal exposure concentrations were larger than those in the summer.



# 2.5.7. NO 2 

# as a Component and Indicator of Pollutant Mixtures

2.5.7.1. Associations between Ambient NO 2 

## and Ambient Copollutants

Relationships between ambient concentrations of NO 2 and other pollutants that are emitted by thesame sources, such as motor vehicles, should be evaluated in designing and interpreting air pollutionhealth outcome studies, as ambient concentrations are generally used to reflect exposures in epidemiologic studies. Thus, the majority of studi es examining pollutant associations in the ambient environment have focused on ambient NO 2 , PM 2.5 (and its components), and CO, with fewer studies reporting the relationship between ambient NO 2 and ambient O 3 or SO 2 . Data were compiled from EPA’s AQS and a numbe r of exposure studies. Correlations between ambient concentrations of NO 2 and other pollutants, PM 2.5 (and its components, where available), CO, O 3 , and SO 2 are summarized in Table 2.5-7. As can be seen from Table 2.5-7, NO 2 was moderately correlated with PM 2.5 (range: 0.37 to 0.78) and with CO (0.41 to 0.76) in s uburban and urban areas. At some sites (e.g., Riverside, CA) associations between ambient NO 2 and ambient CO concentrations (both larg ely traffic-related pollutants) are much lower, likely as the result of other sources of both CO and NO 2 increasing in importance in going from urban environments to more rural and sparsel y populated areas. These sources include oxidation of methane (CH 4 ) and other biogenic compounds; residential wood burning and prescribed and wild land fires for CO; and soil emissions, lightning, and r esidential wood burning and wild land fires for NO 2 . In urban areas, the ambient NO 2 -CO correlations vary widely. The strongest correlations are seen between NO 2 and elemental carbon (EC). Note that the results of Hochadel et al. (2006) for PM 2.5 optical absorbance have been interpreted in terms of EC. Brook et al. (2007) also found relatively high correlations between ambient NO 2 and combustion-related organi cs, including the BTEX compounds (benzene, toluene, ethylbenzene, and o-, m-, p-xylene) (r=0.45-0.6) and hopanes (r=0.67-0.8). Correlations between ambient NO 2 and ambient O 3 are mainly negative, owing to the chemical interaction between the two, with again considerable variability in the observed correlations. Only one study (Sarnat et al., 2001) examined associations between ambient NO 2 and ambient SO 2 concentrations, and it showed a negative correlation during winter. Figure 2.5-6 shows seasonal plots of correlations between NO 2 and O 3 versus correlations between NO 2 and CO. As can be seen from the figure, NO 2 is positively correlated with CO during all seasons at all sites. However, the sign of the correlation of NO 2 with O 3 varies with season, ranging from negative during winter to slightly positive during summer. There are at least two main factors contributing to the observed seasonal behavior. O 3 and radicals correlated with it te nd to be higher during the summer, thereby tending to increase the ratio of NO 2 to NO. Nitrogen oxide compounds formed by further oxidation of NO X are also expected to be correlated with O 3 and increased summertime photochemical activity. Because some of these additionally oxidized N compounds create a positive artifact in the FRM for NO 2 , they may also tend to increase the correlation of NO 2 with O 3 during the warmer months.2-54 Table 2.5-7. Pearson correlation coefficient between ambient NO 2 and ambient copollutants.

STUDY LOCATION PM 2.5 CO O 3 SO 2

AQS (2007)* Los Angeles, CA 0.49 (u 2 ) 0.56 (s) 0.59 (u) 0.64 (s) –0.29 (u) –0.11 (s) NR

AQS (2007)* Riverside, CA NR 0.43 (u) 0.41 (s) 0.15 (r) 0.045 (u) 0.10 (s) –0.31 (r) NR

AQS (2007)* Chicago, IL 0.49 (s) 0.53 (u) 0.46 (s) –0.20 (u) NR

AQS (2007)* New York, NY 0.58 (u) 0.46 (u) –0.06 (u) NR

Kim et al. (2006) Tor onto, Canada 0.44 0.72 NR NR

Sarnat et al. (2006) Steubenville, OH (autumn) 0.78 (0.70 for sulfate; 0.82 for EC) NR NR NR

Sarnat et al. (2006) Steubenville, OH (summer) 0.00 (0.1 for sulfate; 0.24 for EC) NR NR NR

Connell et al. (2005) Steubenville, OH 0.50 NR NR NR

Kim et al. (2005) St. Louis, MO (RAPS) NR 0.64 4 NR NR

Sarnat et al. (2001) 1 Baltimore, MD (summer) 0.37 0.75 0.02 (not significant) NR

Sarnat et al. (2001) Baltimore, MD (winter) 0.75 0.76 –0.71 –0.17

Hochadel et al. (2006) Ruhr area, Germany 0.41 (0.93 for EC 3 ) NR NR NR

Hazenkamp-von Arx et al. (2004) 21 European cities 0.75 NR NR NR

Cyrys et al. (2003) Erfurt, Germany 0.50 0.74 NR NR

Brook et al. (2007) 10 C anadian cities 0.54 NR NR NR

Mosqueron et al. (2002) Pa ris, France 0.69 NR NR NR

Rojas-Bracho et al. (2002) Santiago, Chile 0.77 NR NR NR

1 Spearman correlation coefficient was reported. 2 u: urban; s: suburban; and r: rural 3 Inferred based on EC as dominant contributor to PM 2.5 absorbance. 4 Value with respect to NO X
. *Data obtained from EPA’s AQS Database, available at http:// www.epa.gov /ttn/airs/airsaqs/



## 2.5.7.2. Associations among NO 2 

## and Other Pollutants in Indoor Environments

In addition to NO 2 , indoor combustion sources such as gas ranges and unvented gas heaters emit other pollutants that are already present in the fuel or are formed during combustion. The major products from the combustion of natural gas are carbon dioxide (CO 2 ), CO, followed by formaldehyde (HCHO), with smaller amounts of other oxidized organic co mpounds in the gas phase. PM, especially in the ultrafine-size range and HONO are also emitted. The production of pollutants by reactions of NO 2 in indoor air was covered in Section 2.5.5. Dennekamp et al. (2001) measured levels of NO, NO 2 , and ultrafine particles (UFP) generated by gas and electric cooking ranges in a test laboratory room. They found average levels of NO ranging from ~500 to ~3,000 ppb, with peak (15-min avg) leve ls ranging from ~1,000 to ~6,000 ppb depending on how many burners (1 to 4) were turned on and for how long (15 min to 2 h). Corresponding levels of NO 2 tracked those of NO but were typically factors of 2 to 5 lower. Spicer et al. (1993) compared the measured increase in HONO in a test house resulting from direct emissions of HONO from a gas range and from production by surface reactions of NO 2 . They found that emissions from the gas range could2-55 account for ~84% of the measured increase in HONO. In a study of homes in southern California, Lee et al. (2002) found that indoor levels of NO 2 and HONO were positively associated with the presence of
gas ranges.

Figure 2.5-6. Correlations of NO 2 to O 3 versus correlations of NO 2 to CO for Los Angeles, CA (2001-2005).

In a study of pollutants emitted by unvented gas heaters, Brown et al. (2004) found that CO in a room test chamber ranged from 1 to 18 ppm and NO 2 , from 100 to 300 ppb. Corresponding levels of HCHO were highly variable, ranging from <10 ppb to a few hundred ppb (with an outlier at >2 ppm). PM in the sub-micrometer size range is produced during natural gas combustion. Dennekamp et al. (2001) in the study mentioned above found enhancements in UFP concentrations when gas burners were turned on. Peak (15-min avg) concentrations for different experiments ranged from ~140,000 to ~400,000/cm 3 corresponding to average levels of ~80,000 to 160,000/cm 3 . Concentrations before the experiments were begun were in th e range of a few thousand per cm 3 . However, Ristovski et al. (2000) measured emission rates for individual particles, which are expected to be present mainly in the UFP size range but concluded that these rates are low, and th ey could not detect an increase in particle number from one of the two heater models tested. Rogge et al. (1993) found that at least 22% of the fine particle mass emitted by natural gas heaters consists of PAHs, oxy-PAHs, and aza- and thia-arenes. They also identified emissions of speciated alkanes, n-alkanoic acids, polycyclic aromatic ket ones, and quinones. However, these accounted for only another ~4% of the emitted fine PM. Although the PM em issions rates were low and not likely to affect2-56 PM levels, the PAH content of natural gas combustion emissions in this study indicates that natural gas combustion could be a substantial sour ce of PAHs in indoor environments



## 2.5.7.3. Personal and Ambient Associations between NO 2 

## and Copollutants

Correlations between ambient concentrations of NO 2 and PM 2.5 (and PM components where available), are summarized in Table 2.5-8. Corre lations between personal concentrations of NO 2 and ambient copollutants, PM 2.5 , PM 10 , EC, CO, and sulfate are summarized in Table 2.5-9, and correlations between personal NO 2 concentrations and personal copollutant concentrations are shown in Table 2.5-10. Most studies examined showed that personal NO 2 concentrations were significantly correlated with either ambient or personal level PM 2.5 or other combustion-generate d pollutants, e.g., CO, EC.

Table 2.5-8. Pearson correlation coefficient between ambient NO 2 and personal copollutants.

STUDY LOCATION PM 2.5 SULFATE EC UFP

Sarnat et al. (2006) Steubenville, OH Fall 0.71 0.52 0.70 —

Sarnat et al. (2006) Steubenville, OH Summer 0.00 0.1 not significant 0.26 —

Vinzents et al. (2005) Copenhagen, Denmark — — — 0.49 (R 2 ) explained by ambient NO 2 and ambient temperature

Table 2.5-9. Pearson correlation coefficient between personal NO 2 and ambient copollutants.

STUDY LOCATION PM 2.5 SULFATE EC PM 10 CO

Sarnat et al. (2006) Steubenville, OH Fall 0.46 0.35 0.57 — —

Sarnat et al. (2006) Steubenville, OH Summer 0.00 0.1 (not signi ficant) 0.17 — —

Kim et al. (2006) Toronto, Canada 0.30 — — — 0.20

Rojas-Bracho et al. (2002) S antiago, Chile 0.65 — — 0.39 —

A number of case studies show correlations between ambient NO 2 and other pollutants that are associated with traffic. Particulate and gaseous copolluta nt data were analyzed at 10 sites in the St. Louis Regional Air Pollution Study (RAPS) dataset (1975, 1977) by Kim et al. (2005). This study examined the spatial variability in source contributions to PM 2.5 . Table 2.5-11 shows correlations between NO X and traffic pollutants measured in ambient air. Leaded gasoline was in use at the time of RA PS, making Pb and bromine (Br) good markers for motor vehicle exhaust. Motor vehicle emissions are the main anthropogenic source of CO in urban areas. However, outside of urban areas and away from sources burning fossil fuels, biomass burning and the oxidation of biogenic hydrocarbons, in particular isoprene and methane, can represent the major source of CO. In general, biogenic emissions of precursors to CO formation or CO from biomass burning can cause the relationship between CO and motor vehicles to break down.2-57 Table 2.5-10. Pearson correlation coefficient between personal NO 2 and personal copollutants.

STUDY LOCATION PM 2.5 CO VOCs HONO

Kim et al. (2006) Tor onto, Canada 0.41 0.12 —

Modig et al. (2004) Umea, Sweden — — 0.06 for 1,3-butadiene; 0.10 for benzene —

Mosqueron et al. (2002) Paris, France 0.12 but not significant — — —

Jarvis et al. (2005) 21 European cities — — — 0.77 for indoor NO 2 and indoor HONO

Lee et al. (2002) — — — — 0.51 for indoor NO 2 and indoor HONO

Lai et al. (2004a) Oxford, England –0.1 0.3 –0.11 for total VOCs —

Table 2.5-11. Pearson correlation coefficient between NO X and traffic-generated pollutants.

SPECIES ALL SITES WITHOUT UPWIND OR BACKGROUND SITE

NO X : PM 2.5 (motor vehicle component) 0.48<r<0.75 1 0.48<r<0.75 2

NO X : CO 0.30<r<0.77 1 0.54<r<0.77 2

NO X : Pb 0.42<r<0.76 1 0.48<r<0.76 2

NO X : Br 0.55<r<0.73 1 0.58<r<0.73 2

NO 2 : EC 0.93 3
—

NO 2 : EC 0.82 autumn, 0.24 summer 4
—

1 St. Louis RAPS (Kim et al., 2006), all sites 2 St. Louis RAPS (Kim et al., 2006), all sites with upwind background site removed 3 Ruhr Valley (Hochadel et al., 2006) 4 Steubenville, OH (Sarnat et al., 2006)



## 2.5.7.4. NO 2 

## as an Indicator of the Mixture of Traffic Pollutants

In the Restrepo et al. (2004) study, NO 2 behaved as if traffic were its main source, since NO 2 behaved similarly to CO and PM 2.5 ; i.e., their concentrations decreased with height. O 3 showed the opposite vertical gradient; i.e., its c oncentration increased with height. UFPs have long been associated with motor vehicle traffic (e.g., PM AQCD, 2004). Seaton and Dennekamp (2003) proposed that NO 2 may be a surrogate for UFPs, in particular for particle number concentrations. The results from the measurements made at a background site in Aberdeen, Scotland, over the course of 6 months showed very high correlation between the number concentration of particles <100 nm in diameter and NO 2 . The correlation between NO 2 and the particle number concentration (r=0.89) was much higher than that between NO 2 and PM 2.5 (r=0.55) and that between NO 2 and PM 10 (r=0.45). A time-series mortality study (re-analysis by Stölzel et al., 2003; Wichmann et al., 2000) conducted in Erfurt, Germany, measured, and analyzed UFP number and mass concentrations as well as NO 2 . Unlike Seaton and Dennekamp’s data, in this data set, the correlation between NO 2 and various number concentration indices were not much stronger than those between PM 2.5 and number concentration indices2-58 or those between PM 10 and number concentration indices. For example, the correlation between NC0.01- 0.10 (particle number concentration for par ticle diameter between 10 and 100 nm) and NO 2 , PM 2.5 , and PM 10 were 0.66, 0.61, and 0.61, respectively. As might be expected from a pollutant having a major traffic source, the diurnal cycle of NO 2 in typical urban areas is characterized by traffic em issions, with peaks in emissions occurring during morning and evening rush hour traffic. Motor vehicle emissions consist mainly of NO, with only ~10% of primary emissions in the form of NO 2 . The diurnal pattern of NO and NO 2 concentrations are also strongly influenced by the diurnal variation in th e mixing layer height. Thus, during the morning rush hour when mixing layer heights are still low, traffic produces a peak in NO and NO 2 concentrations. As the mixing layer height increases during the day, dilution of emissions occurs, and NO and NO 2 are converted to NO Z . During the afternoon rush hour, mixing layer heights are often still at or near their daily maximum values, resulting in dilution of traffic emissions through a larger volume than in the morning. Starting near sunset, the mixing la yer height drops and conversion of NO to NO 2 occurs without subsequent photolysis of NO 2 recreating NO. The composite diurnal variability of NO 2 in selected urban areas with multiple sites (New York, NY, Atlanta, GA, Baton Rouge, LA, Chicago, IL, Hous ton, TX, Riverside, CA, and Los Angeles, CA) is shown in Figure 2.5-7. Figure 2.5-7 shows that low est hourly median concentrations are typically found at around midday and that highest hourly median concen trations are found either in the early morning or in mid-evening. Median values range by about a factor of two from ~13 ppb to ~25 ppb. However, individual hourly concentrations can be considerably higher than these typical median values, and hourly NO 2 concentrations of >0.10 ppm can be found at an y time of day. The diurnal pattern in median concentrations shown in Figure 2.5-7 is consistent with that shown in Figures 2.4-5 and 2.4-6 for Atlanta, indicating some commonality in sources across these cities. The pattern in the median concentrations is consistent with traffic as the major source of vari ability. However, the patterns in the upper end of the concentration distribution differ between cities a nd the composite, indicating that other sources and meteorological processes affect NO 2 levels, causing them to differ from city to city.

Figure 2.5-7. Composite, diurnal variability in 1-h avg NO 2 in urban areas. Values shown are averages from 2003 through 2005. Boxes define the interquartile range, and the whiskers the 5th and 95th percentile values. “X” denotes indivi dual values above the 95th percentile.2-59 Information concerning the seasonal variability of ambient NO 2 concentrations is given in Annex section AX3.2. NO 2 levels are highest during the cooler m onths of the year and still show positive correlations with CO. Mean NO 2 levels are lowest during the summer months, though of course, there can be large positive excursions associated with the deve lopment of high-pressure systems. In this regard, NO 2 behaves as a primary pollutant, although there is no good reason to suspect strong seasonal variations in its emissions. Although traffic is a major source of ambient NO 2 , industrial point sources are also contributors to ambient NO 2 . Nerriere et al. (2005) measured personal exposures to PM 2.5 , PM 10 , and NO 2 in trafficdominated, urban background, and indus trial settings in four French c ities (Paris, Grenoble, Rouen, and Strasbourg). Ambient concentrati ons and personal exposures for NO 2 were generally highest in the traffic-dominated sector. It should be remembered that there can be high traffic emissions (including shipping traffic) in industrial zones, such as in the Sh ip Channel in Houston, TX, and in the Port of Los Angeles, CA. In rural areas where traffic is sparse, other sources could dominate. Martin et al. (2003) found that pulses of NO 2 released from agricultural areas occur afte r rainfall. Other rural contributors to NO 2 include wildfires and residential wood burning.



# 2.5.8. Exposure Error in Epidemiologic Studies

For the purposes of this ISA, the effects of exposur e error on epidemiologic study results refers to changes in the point estimate and in the standard error of the calculated health effect estimate, β , that result from using the concentration of an air pollutant as an exposure indicator rather than using the actual personal exposure to the causal factor in the epid emiologic statistical analysis. There are many assumptions made in going from the available experimental measurement of a pollution indicator, to an estimate of the personal exposure, to the causal f actor. The importance of these assumptions and their effect on β depend on the type of epidemiologic study. A more detailed discussion of these issues is provided in Annex section AX6.1.



## 2.5.8.1. Community Time-Series Studies

This section applies primarily to studies of the association between short-term NO 2 concentrations and short-term measures of mortality or morbidity. With NO 2 time-series epidemiologic analysis, the following three exposure issues are of primary concern: (1) the relationship of the experimental measurement of NO 2 to the true concentration of NO 2 ; (2) the relationship of day-to-day variations of the concentration of the indicator, as measured at a centr al monitoring site, with the corresponding variations in the avg concentration of the indicator over th e geographic area from which the health measurements are drawn; and (3) the relationship of the community avg concentration of NO 2 to the avg personal exposure to ambient NO 2 . These three issues are described below. Since there is always some instrumental e rror in the experimental measurement of NO 2 concentration, the correlation of the measured NO 2 with the true NO 2 , on either a 24-h or 1-h basis, will be less than 1. Averaging across multiple unbiased ambient monitors in a region should reduce the instrument measurement error (Sheppard, 2005; Wils on and Brauer, 2006; Zeger et al., 2000). This error component is not expected to have a major eff ect on personal exposure estimation. It may tend to attenuate the estimate of α (Sheppard, 2005) and is unlikely to greatly affect β , particularly if the instrument error is of the Berkson type. Zeger et al . (2000) showed that instrument error has both Berkson and non-Berkson error components. The concentration of NO 2 , measured at any given monitoring site, may not be highly correlated with the avg community concentration. Large spatia l variations (expressed as coefficient of divergence (COD) have been observed in some urban areas, as show n in Table 2.5-1. Site-to-site correlations of NO 2 concentrations, as shown for several cities in Table 2. 5-1 included some very low values, possibly due to2-60 local sources, monitor siting, meteorology, and topography. Low correlations between the ambient concentration and the community a vg concentration quantitatively reduce β if the single pollutant model is the true model. Similarly, β will be reduced if there are subareas of the community where the correlation of the subarea avg concentrations with th e concentrations measured at the ambient monitoring site is <1. Therefore, if a local source affected a sizable portion of the population, that community might not be suitable for time-series epidemiologic analyses. Zeger et al. (2000) made a major contribution to the understanding of exposure error by pointing out that for community time-series epidemiology, wh ich analyzes the association between health effects and potential causal factors at the community scale rather than the individual scale, it is the correlation of the daily community avg personal expos ure to the ambient concentration, X t A , with daily community avg concentration, C t , that is important, not the correlation of each individual’s exposure X it A with C t . Thus, the low correlation of X it A with C t , as frequently found in pooled panel e xposure studies, is not relevant to error in community time-series epidemiologic analys is. Unfortunately, few experimental studies provide adequate information to calculate the community a vg exposure. Most exposure panel studies measure one or a few subjects on 1 day, and another one or a few subjects on the next day, etc. (i.e., a pooled study design). A few studies have measured one subject for sev eral days and another subject for a different set of several days (i.e., a longitudinal study design). Th is requires measurement of the personal exposure of every subject on every day along with sufficient in formation to separate the ambient component of exposure from the measured total personal exposure. Su ch information was available from one study of combined PM 10 and showed that the correlation of X t A with C t was much greater than the correlation of X

it A with C t (U.S. Environmental Protection Agency, 2004). The Research Triangle Park PM Panel Study found similar effects in the rela tionship of outdoor and personal PM 2.5 concentrations (Williams et al., 2003). Ott et al. (2000) provided a statistical argument that such an increase in the correlation of the daily avg over the individual values should be expected. Inter-individual daily variation in α it around the daily community avg α t tends to produce Berkson error, which will not change the point estimate of β , although it may increase the standard error (Zeger et al., 2000). Overestimation of exposure by substitution of the ambient concentration for the ambient exposure leads to underestimation of the effect estimate proportional to α , or bias toward the null (Sheppard, 2005). Panel epidemiology refers to time-series studies that follow a relatively small number of subjects for a relatively short time, usually tens of subjects fo r 5 to 20 days a subject. Thus, neither the averaging of exposure over millions of people, as in community time-series studies, or the averaging of exposure over time periods of years and hundreds or thousands of subjects, as in chronic cohort studies was available. Therefore, exposure errors may be more im portant than in other types of epidemiology. Panel studies typically examine the association between sy mptoms or health outcomes and either ambient concentrations or personal exposures. Most panel epidemiology studies of NO 2 used ambient concentrations rather than personal exposures. Similar types of exposure error, as discussed for community time series studies apply to panel studies, with some differences depending on whether ambient concentrations or personal exposures are used.



## 2.5.8.2. Long-Term Exposure Studies

For long-term exposure epidemiologic studies, concen trations are integrated over time periods of a year or more, and usually for spatial areas the size of a city, county, or MSA, although integration over smaller areas may be feasible. Health effects are then regressed, in a statistical model, against the avg concentrations in the series of cities (or other areas) . In time-series studies, a constant difference between the measured and the true concentration (instrument offset) will not affect β , nor will variations in the daily average α or the daily average nonambient exposure, unless the variations are correlated with the daily variations in concentrations. However, in l ong-term exposure epidemiologic studies, if instrument measurement errors, long-term average values of α , or long-term averages of nonambient exposure differ2-61 for different cities (or other areas used in the an alysis), the city-to-city long-term ambient NO 2 concentrations will not be perfectly correlated with the long-term average exposure to either ambient or total NO 2 . This lack of correlation would be expected to lead to a lowering of the point estimate of β

.


# 2.5.9. Summary of Issues in Assessing Exposures to NO 2
In summary, NO 2 is monitored at far fewer sites than either O 3 or PM. Large spatial variations in ambient NO 2 concentrations were observed in urban areas. Measurements of NO 2 are subject to artifacts both at the ambient level and at the personal le vel. Personal exposure to ambient and outdoor NO 2 is determined by many factors as listed in Sections 2.5.1 and 2.5.2. These factors all influence the contribution of ambient NO 2 to personal exposures. Personal activ ities determine when, where, and how people are exposed to NO 2 . The variations of these physical and exposure factors determine the strength of the association between personal exposure and ambi ent concentrations in both longitudinal and pooled studies. In Section 2.5.6.1, three types of correlati on coefficients were presented. The observed strength of the association between personal exposures and ambi ent concentrations are not only affected by the variation in physical parameters (e.g., P
, k
, a and indoor sources) but also affected by data quality and study design. The association between the ambien t component of personal exposures and ambient concentrations is more relevant to the interpretation of epidemiologic evidence but this type of correlation coefficient is not generally reported. The weak asso ciation between personal to tal exposures and ambient concentrations in some longitudinal studies might not reflect the true association between the ambient component of personal exposures and ambient concentr ations. In the absence of indoor and local sources, personal exposures to NO 2 are between the ambient level and the indoor level. However, personal exposures could be much higher than either indoor or outdoor concentrations in the presence of these sources. A number of studies found that (community average) personal NO 2 was associated with ambient NO 2 , but the strength of the association ranged from poor to good. The evidence relating ambient levels to personal e xposures is inconsistent. Some of the longitudinal studies examined found that ambient levels of NO 2 were reliable proxies of personal exposures to NO 2 . However, a number of studies did not find significant asso ciations between ambient and personal levels of NO 2 . The differences in results were related in larg e measure to differences in study design and in exposure determinants. Measurement artifacts and differences in analytical measurement capabilities could also have contributed to the inconsistent r esults. Indeed, in a number of the studies examined, the majority of measurements of personal NO 2 concentrations were beneath de tection limits, and in all studies some personal measurements were beneath detection limits. Some researchers concluded that ambient NO 2 may be a reasonable proxy for personal exposures, while others noted that caution must be exercised if ambient NO 2 is used as a surrogate for personal exposure. Reasons for the differences in study results are not clear, but are related in large measure to differences in study design, to the spatial heterogeneity of NO 2 in study areas, to control of indoor sources, to the seasonal and geographic variability in the infiltration of ambient NO 2 , and to differences in the time spent in different microenvironments. Measure ment artifacts at the ambient and personal levels and differences in analytical measurement capabilities among different groups could also have contributed to the mixed results. The collective variab ility in all of the above parameters, in general, contributes to exposure errors in air pollution-hea lth outcome studies. The errors and uncertainties associated with the use of ambient NO 2 concentrations as a surrogate for personal exposure to ambient NO 2 generally tend to reduce rather than increase β , and therefore are not expected to change the principal conclusions from NO 2 epidemiologic studies.2-62 

# 2.6. Dosimetry of Inhaled NO X

This section provides a brief overview of NO 2 dosimetry and updates information provided in the 1993 NO X AQCD. A more extensive discussion of NO 2 dosimetry appears in Annex AX4. NO 2 , classified as a reactive gas, interacts with surfactants, antioxi dants, and other compounds in the epithelial lining fluid (ELF). The compounds thought to be responsible for adverse pulmonary effects of inhaled NO 2 are the reaction products themselves or the metabolites of these products in the ELF. Acute NO 2 uptake in the lower respiratory tract is thought to be rate-limited by chemical reactions of NO 2 with ELF constituents rather than by gas so lubility in the ELF (Postlethwait and Bidani, 1990). Postlethwait and Bidani (1994) conc luded that the reaction between NO 2 and water does not significantly contribute to the absorption of inhaled NO 2 . Rather, uptake is a first-order process for NO 2 concentrations of <10 ppm, is aqueous substrate- dependent, and is saturable. Postle thwait et al. (1991) reported that inhaled NO 2 (<10 ppm) does not penetrate the ELF to reach underlying sites and proposed that cytotoxicity may be due to NO 2 reactants formed in the ELF. Rela ted to the balance between reaction product formation and removal, it was further hypoth esized that cellular responses may be nonlinear with greater responses being possible at low levels of NO 2 uptake versus higher levels of uptake. Glutathione (GSH) and ascorbate are the primary NO 2 absorption substrates in rat ELF (Postlethwait et al., 1995). Velsor and Postlethwait (1997) investigated th e mechanisms of acute epithelial injury from NO 2 exposure. Membrane oxidation was not a simple monotonic function of GSH and ascorbic acid levels. The maximal levels of membrane oxidation were observed at low antioxidant levels versus null or high antioxidant levels. GSH- a nd ascorbic acid-related membrane oxidation were superoxide- and hydrogen peroxide-dependent, respectively. The authors proposed that increased absorption of NO 2 occurred at the higher antioxidant concen trations, but little secondary oxidation of the membrane occurred because the reactive species (e.g ., superoxide and hydroge n peroxide) generated during absorption were quenched. A lower rate of NO 2 absorption occurred at the low antioxidant concentrations, but oxidants were not quenched and so were available to interact with the cell membrane. In vitro studies have clearly illustrated the role of antioxidants in mediating NO 2 uptake and membrane oxidation; however, the temporal dynamics of biological responses to NO 2 that occur in vivo are far more complex. Antioxidant levels vary sp atially between lung regions and temporally with NO 2 exposure. Kelly et al. (1996a) examined the effect of a four-hour NO 2 (2 ppm) exposure on antioxidant levels in bronchial lavage fl uid (BLF) and bronchoalveolar lava ge fluid (BALF) of 44 healthy nonsmoking adults (19-45 yr, median 24 yrs). The base line concentrations of uric acid and ascorbic acid were strongly correlated between the BLF and BA LF within individuals (r=0.88, p<0.001; r=0.78, p=0.001; respectively), whereas the concentrations of GSH in the BLF and BALF were not correlated. At 1.5 h after the NO 2 exposure, uric acid and ascorbic acid levels were significantly reduced in both lavage fractions while GSH levels were significantly incr eased but only in BLF. By 6 h postexposure, ascorbic acid levels had returned to baseline in both lavage fractions, but uric acid had become significantly increased in both lavage fractions and GSH levels re mained elevated in BLF. By 24 hours postexposure, all antioxidant levels had returned to baseline. Th e levels of GSH in BALF did not change from baseline at any time point in response to NO 2 exposure. The depletion of uric acid and ascorbic acid, but not GSH has also been observed with ex vivo exposure of human BALF to NO 2 (Kelly et al., 1996a; 1996b). Very little work related to the quantification of NO 2 uptake has been reported since the 1993 NO X AQCD. In both humans and animals, the uptake of NO 2 by the upper respiratory tract decreases with increasing ventilation rates. This causes a greater proportion of inhaled NO 2 to be delivered to the lower respiratory tract. In humans, the breathing pattern shif ts from nasal to oronasal during exercise relative to rest. Since the nasal passag es absorb more inhaled NO 2 than the mouth, exercise (with respect to the resting state) delivers a disproportionately greater qua ntity of the inhaled mass to the pulmonary region of the lung, where the NO 2 is readily absorbed. Bauer et al. (1986) reported a statistically significant increase in uptake from 72% during rest to 87% during exercise in a group of 15 asthmatic adults. The minute ventilation also increased from 8.1 L/min during rest to 30.4 L/min during exercise. Hence,2-63 exercise increased the dose rate of NO 2 by 5-fold in these subjects. Similar results have been reported for beagle dogs where the dose rate of NO 2 was 3-fold greater for the dogs during exercise than rest (Kleinman and Mautz, 1991). Modeling studies also predict that the net NO 2 dose (NO 2 flux to air-liquid interface) is relatively constant from the trachea to the terminal bronchioles and then rapidly decreases in the pulmonary region. The pattern of net NO 2 dose rate or uptake rate is expected to be similar between species and unaffected by age in humans. The predicted tissue dose and dose rate of NO 2 (NO 2 flux to liquid-tissue interface) is low in the trachea, increases to a maximum in the te rminal bronchioles and the first generation of the pulmonary region, and then decreases rapidly with distal progression. The site of maximal NO 2 tissue dose is predicted to be fairly similar between sp ecies, ranging from the first generation of respiratory bronchioles in humans to the alveolar ducts in rats. The production of toxic NO 2 reactants in the ELF and the movement of these reactants to the tissues have not been modeled. Contrary to what recent in vitro studies have shown (Kelly et al., 1996a), m odeling studies have generally considered NO 2 reactions in the ELF to be protective. The complex interactions betw een antioxidants, spatial differences in antioxidants between lung regions, temporal changes in antioxidant levels in response to NO 2 exposure, and species differences in antioxidant defenses are poorly unders tood. Thus, the current dosimetry models are inadequate to put response data collected from an imals and humans on a comparative footing with each other and with the exposure conditions in the epidemiologic studies.3-1 

# Chapter 3. Integrated Health Effects

In this chapter, we assess the health effects associated with human exposure to ambient NO 2 . The main goal of this chapter is to (1) integrate newly available epidemiologic, human clinical, and animal toxicological evidence with consideration of key findings from the 1993 NO X AQCD (U.S. Environmental Protection Agency, 1993) and (2) dr aw conclusions about the causal nature of NO 2 relative to a variety of health effects. These causal determinations utilize the framework outlined in Chapter 1. This chapter is organized to present morbidity a nd mortality associated with short-term exposures to NO 2 , followed by morbidity and mortality associated with long-term exposures. Within these divisions, the chapter is organized by health outcome, such as respiratory symptoms in asthmatics, emergency department (ED) visits and hospital admissions for respiratory and cardiovascular diseases (CVDs), and premature mortality. The sections describe the findings of epidemiologic studies that have characterized the association between NO 2 exposure and heath outcomes and includes relevant human clinical and animal toxicological data, when available. This integrated discussion underlies judgments in causal inference. The epidemiologic studies contain important information on potential associations between health effects and exposures of human populations to ambient levels of NO 2 , and they help to identify susceptible subgroups and associated risk factors. Ho wever, the associations derived for specific air pollutants and health outcomes in epidemiologic studies may be confounded by copollutants and/or meteorological conditions and can be influenced by model specifications in the analytical methods. Extensive discussion of issues related to confoundi ng effects among air pollutants in epidemiologic studies is provided in the 2004 PM AQCD and so is not re peated in detail here. Briefly, though, the use of multipollutant regression models has been the appro ach most commonly used to control for potential copollutant confounders. One specific concern has been that a given polluta nt may act as a surrogate for other unmeasured or poorly measured pollutants or pollutant mixtures. Specifically, traffic is a nearly ubiquitous source of combustion pollutant mixtures that include NO 2 and can be an important contributor to NO 2 levels in near-road locations. This complicat es efforts to disentangle specific NO 2 -related health effects as distinct from those effects of the whole traffic-generated co mbustion mix. These multipollutant models use terms for measured variables as important tools for estima ting an effect in multisource epidemiologic studies. Both single- and multipollutant models that include NO 2 were considered and examined for robustness of results. Model specification and model selection also are fact ors to consider in the interpretation of the epidemiologic evidence. Epidemiol ogic studies investigated the association between various measures of NO 2 (e.g., multiple lags, different exposure metrics) and various health outcomes using different model specifications (for further discussion, see the 2006 O 3 AQCD [U.S. Environmental Protection Agency, 2006a]). Human clinical studies conducted in controlled expos ure chambers use fixed concentrations of air pollutants under carefully regulated environmental c onditions and subject activity levels to minimize possible confounding of the health associations by ot her factors. Additionally, sensitive experimental techniques can be used to measure health effects (and markers of injury) that are not evaluated in epidemiologic studies, e.g. airway hyperresponsiveness. These studies provide important information on effects, concentration-response relationships, biol ogical plausibility of associations observed between NO 2 exposure and health outcomes in epidemiologic studies, and insights into sensitive subpopulations. While human clinical studies provide a direct quantitative assessment of the NO 2 exposure-health response relationship, such studies have a number of limita tions. First, it is requisite that subjects be either healthy individuals or individuals whose level of illness does not preclude them from participating in the study. Therefore, the results of human clinical studi es may underestimate the health effects of exposure to3-2 certain sensitive subpopulations. Second, studies of controlled exposure to NO 2 typically have used concentrations that are higher than those normally pr esent in ambient air. Third, human clinical studies normally are conducted on a relatively small number of subjects, which reduces the power of the study to detect significant differences in the health outcomes of interest and exposures to varying concentrations of NO 2 and clean air. Similar to human clinical studies, animal toxicological studies have the advantage of being conducted under controlled cond itions, using fixed concentrations of air pollutants in carefully regulated environmental conditions. These studies allow for eval uation of biological responses with exposures to substances in doses that could be hazardous to human health and/or for extended durations that are not possible in human clinical studies. However, restrictions on study population size require the use of higher doses to allow the identification of rare even ts. An important caveat in interpretation of the toxicological data is that the high doses used in ma ny of the studies may produce different effects on the lung than inhalation exposures at lower ambient concen trations. That is, “realistic” doses associated with ambient nitrogen oxides exposures may activate cells and pathways entirely disparate from those activated at high experimental doses. In addition, various differences in biology can exist, depending on species and strain selected, that can affect the respon se and add uncertainty to extrapolating results to humans. This chapter focuses on important recent scientific studies, with emphasis on those conducted at or near current ambient concentrations. The attached annexes include a broad survey of the relevant epidemiology, human clinical, and toxicology litera ture to supplement the information presented here.



# 3.1. Respiratory Morbidity Related to Short-Term Exposure

3.1.1. Lung Host Defenses and Immunity

Lung host defenses are sensitive to NO 2 exposure, with numerous measures of such effects observed at concentrations of <1 ppm. The fo llowing discussion focuses on studies published since the 1993 AQCD and conducted at near-ambient exposure c oncentrations; as needed, it refers to studies described in the 1993 AQCD. A major c oncern has been the potential for NO 2 exposure to enhance susceptibility to, or the severity of illness resulting from, respiratory infections and asthma, especially in children. Potential mechanisms of lung host defen se impairment (Chauhan a nd Johnston, 2003), include “direct effects on the upper and lower airway by ciliary dyskinesis (Carson et al., 1993), epithelial damage (Devalia et al., 1993a), increases in pro-infla mmatory mediators and cytokines (Devalia et al., 1993b), rises in IgE concentration (Siegel et al., 1997), a nd interaction with allergens (Tunnicliffe et al., 1994), or indirectly through impairment of bronchial immunity (Sandström et al., 1992a).” Table 3.1-1 provides more details and summarizes a range of proposed mechanisms by which exposure to NO 2 in conjunction with viral infections may exacerbate upper and lower airway symptoms (Chauhan et al., 1998). Several epidemiologic studies investigated the relationship between NO 2 exposure and effects related to viral infecti on. Personal exposure to NO 2 and the severity of virus-induced asthma (Chauhan et al., 2003), including risk of airflow obstruction (Linaker et al., 2000) was studied in a group of 114 asthmatic children in England. Children were supplie d with Palmes diffusion tubes, which they attached to their clothing during the day and placed in their be droom at night. Tubes were changed every week for the duration of the 13-month study period. Nasal aspirates were obtained and analyzed for a variety of respiratory illness-causing viruses. The authors observed that exposure to NO 2 levels of greater than 14 μg/m 3 (7.4 ppb) in the week preceding any viral infec tion was associated with increases in the four-point symptom severity score (score increase of 0.6 [95% CI : 0.01, 1.18]) in the week immediately after the infection. Associations also were observed for the respiratory syncytial virus (RSV) alone (score increase3-3 of 2.1 [95% CI: 0.52, 3.81]). A significant reduction in peak expiratory flow (PEF) was associated with exposure greater than 14 μg/m 3 (7.3 ppb) (by 12 L/min [95% CI: -23.6, -0.80]) (Chauhan et al., 2003). Exploration of the relationship between PEF and NO 2 showed that the risk of a PEF episode (as diagnosed by a clinician’s review of each child ’s PEF data) beginning within a week of an upper respiratory infection was significantly associated with exposure to NO 2 greater than 28 μg/m 3 (14.9 ppb) (relative risk [RR]=1.9 [95% CI: 1.1, 3.4]) (Linaker et al., 2000). Thus, high personal NO 2 exposure in the week before an upper respiratory infection was asso ciated with either increased severity of lower respiratory tract symptoms or reduction of PEF for all virus types together and for two of the common respiratory viruses, C-picornavirus and RSV, individually.

Table 3.1-1. Proposed mechanisms whereby NO 2 and respiratory virus infections may exacerbate upper and lower airway symptoms.

PROPOSED MECHANISMS 

### Upper Airway

↓ Ciliary beat frequency Epithelium

↑ Epithelial permeability 

### Lower Airway

Epithelium (as in upper airway)

↓ Epithelial-derived IL-8, GM-CSF, TNF- α Cytokines

↑ Macrophage-derived IL-1b, IL-6, IL-8, TNF- α

↑ Mast cell tryptase

↑ Neutrophils

↑ Total lymphocytes

↑ NK lymphocytes Inflammatory cells

↓ T-helper/T-cytotoxic cell ratio

Inflammatory mediators ↑ Free radicals, proteases, TXA2, TXB2, LTB4

↑ Penetrance due to ciliostasis

↓ PD20-FEV 1

↑ Antigen-specific IgE Allergens

↑ Epithelial permeability 

### Peripheral Blood

↓ B and NK lymphocytes

↓ Total lymphocytes

Source: Adapted from Chauhan et al. (1998).

Several clinical studies have attempte d to address the question of whether NO 2 exposures impair host defenses and/or increase susceptibility to infection (Devlin, 1992; Devlin et al., 1999; Frampton et al., 2002; Goings et al., 1989; Rehn et al., 1982; Rubi nstein et al., 1991; Sandström et al., 1990; 1991; 1992a; 1992b) (see the 1993 NO X AQCD details of older studies and Annex Table AX5.2-1 for additional details on more recent studies). These studies have repor ted inconsistent results. One approach has been3-4 to examine the effects of in vivo NO 2 exposure on the function of alveolar macrophages (AMs) obtained by bronchoalveolar lavage (BAL), including the susceptib ility of these cells to viral infection in vitro. Two studies since 1993 involved 2.0-ppm NO 2 exposures for 4 or 6 h with intermittent exercise and found no effect on AM inactivation of influenza virus either immediately or 18 h after exposure (Azadniv et al., 1998; Devlin et al., 1999). However, Devlin et al. (1999) found ex vivo AM phagocytic capacity reduced following a 4-h exposure of healthy volunteers to 2 ppm NO 2 , indicating a reduced ability to clear inhaled bacteria or other infectious agents. Frampton et al. (2002) examined NO 2 effects on viral infectivity of airway epithelial cells. Subjects were exposed to air, or 0.6- or 1.5-ppm NO 2 , for 3 h, and bronchoscopy was performed 3.5 h after exposure. Ep ithelial cells were harvested from the airway by brushing and then challenged in vitr o with influenza virus and RSV. NO 2 exposure did not alter viral infectivity, but appeared to enhance epithelial cell in jury in response to infection with RSV (p=0.024). Similar results were reported with influenza viru s. These findings indicate that prior exposure to NO 2 may increase the susceptibility of the resp iratory epithelium to injury by subsequent viral challenge. There is evidence from both animal and human studies indicating that exposure to NO 2 may alter lymphocyte subsets in the lung and possibly in the blood. Lymphocytes, particularly T lymphocytes and natural killer (NK) cells, play a key role in the inna te immune system and host defense against respiratory viruses. Rubenstein et al. (1991) found that a ser ies of four daily, 2-h exposures to 0.60-ppm NO 2 resulted in a small increase in NK cells recovered by BAL. Sandström et al. (1990; 1991) observed a significant, dose-related increase in lymphocytes and mast cells recovered by BAL 24-h after a 20-min exposure to NO 2 at 2.25 to 5.50 ppm. In contrast, repeated exposures to 1.5- or 4-ppm NO 2 for 20 min every second day on six occasions resulted in decreased CD16+56+ (NK cells) and CD19+ cells (B lymphocytes) in BAL fluid 24-h after the final exposure (Sandström et al., 1992a; 1992b). No effects were reported on polymorphonuclear leukocytes (PMNs) or total lym phocyte numbers. Solomon et al. (2000) found a decrease in CD4+T lymphocytes in BAL fluid 18-h after three daily, 4-h exposures to 2.0-ppm NO 2 . Azadniv et al. (1998) observed a small but signifi cant reduction in CD8+T lymphocytes in peripheral blood, but not BAL fluid, 18 h following single 6-h exposures to 2.0-ppm NO 2 . Frampton et al. (2002) found small increases in BAL lymphocytes and decreases in blood lymphocytes with exposures to 0.6 and 1.5 ppm NO 2 for 3 h. The observed effects on lymphocyte responses, as d escribed above, have not been consistent among studies. Differing exposure protocols and small numbe rs of subjects among these studies may explain the varying and conflicting findings. Furthermore, the clin ical importance of transient, small changes in lymphocyte subsets is unclear. It is possible that the inflammatory response to NO 2 exposure involves both lymphocytes and PMNs, with lymphocyte responses occurring transiently and at lower concentrations, and PMN responses predominating at higher concentrations or more prolonged exposures. The airway lymphocyte responses do not provide convinc ing evidence of impairment in host defense. One clinical study used fiber-optic bronc hoscopy and found that 20-min exposures to NO 2 at 1.5 to 3.5 ppm transiently reduced airway mucociliary ac tivity (Helleday et al., 1995). Reduced mucus clearance is expected to increase susceptibility to infection by reducing the removal rate of microorganisms from airways. However, the study was weakened by the l ack of a true air control exposure as well as by the absence of randomization and blinding. As a clarifica tion, Helleday et al. (1995) did not measure mucus clearance rates directly using radiolabeled particl es; rather they utilized an optical technique to characterize ciliary activity. Rehn et al. (1982) examined the effect of NO 2 exposure on mucociliary clearance of a radiolabeled Teflon aerosol. After a 1-h exposure to either 0.27 or 1.06 ppm (500 or 2000 μg/m 3 ) NO 2 , there were no changes in airway clearance rates. Animal studies provide clearer evidence that host defense system components such as mucociliary transport and AMs (see Annex Table AX4.3) are targets for inhaled NO 2 . Animal studies further show that NO 2 can impair the respiratory host defense system sufficiently to render the host more susceptible to respiratory infections (See Annex Table AX4.6). Exposure of guinea pigs to 3- or 9-ppm NO 2 6 h/day, 6 days/week for 2 weeks resulted in concentration-dependent decreases in ciliary activity of 12 and 30% of control values, respectively3-5 (Ohashi et al., 1994). These concentration-dependentdecreases were accompanied by a concentrationdependent increase in eosinophil accumulation on the ep ithelium and submucosal connective tissue layer of the nasal mucosa. For foreign agents such as some bacteria and viruses that deposit below the mucociliary region in the gas-exchange region of th e lung, AMs primarily provide host defenses by acting to remove or kill viable particles, remove nonvi able particles, and process and present antigens to lymphocytes for antibody production. AMs are one of the sensitive targets for NO 2 , as evidenced by in vivo animal exposures and in vitro studies (see Annex Table AX4.3 for details of studies related to each of these morphological or functional parameters in exposed animals). Suppression of host defense mechanisms by NO 2 as described in the studies above is expected to result in an increased incidence and severity of pulm onary infections (Coffin and Gardner, 1972; Gardner et al., 1979; Miller et al., 1987). Various experimental approaches have been employed using animals in an effort to determine the overall functional effi ciency of the host’s pulmonary defenses following NO 2 exposure. In the most commonly used infectiv ity model, animals are exposed to either NO 2 or filtered air and the treatment groups are combined and exposed br iefly to an aerosol of a viable agent, such as Streptococcus spp., Klebsiella pneumoniae, Diploco ccus pneumoniae, or influenza virus and mortality rates are determined (Coffin and Gardner, 1972; Eh rlich, 1966; 1979; Gardner, 1982; Henry et al., 1970). Although the endpoint is mortality, this experimental test is considered a sensitive indicator of the depression of the defense mechanisms and is a commonly used assay for assessing immunotoxicity. The susceptibility to bacterial and viral pulmonary infections in animals also increases with NO 2 exposures of as low as 0.5 ppm. No recent studies published since 1993 were identified that evaluated this endpoint. Annex Table AX4.6 summarizes the effects of NO 2 exposure and infectious agents in animal studies as compiled in the 1993 NO X AQCD, and provides evidence that the host’s response to inhaled NO 2 can be influenced by the duration and temporal patterns of e xposure. This is important in considering continuous versus intermittent exposures and attempting to understand observed differences in reported results.



## Summary of Short-Term Exposure on Lung Host Defenses and Immunity
Impaired host-defense systems and increased risk of susceptibility to both viral and bacterial infections have been observed in epidemiologic, human clinical, and animal toxicological studies. A study by Chauhan et al. (2003) produced evidence that increased personal exposures to NO 2 worsened virus-associated lower respiratory tract symptoms in children with asthma. The limited evidence from human clinical studies indicates that NO 2 may increase susceptibility to injury by subsequent viral challenge at exposures as low as 0.6 ppm for 3 h (Frampton et al., 2002). Toxicological studies have shown that lung host defenses are sensitive to NO 2 exposure, with several measures of such effects observed at concentrations of less than 1 ppm. Toge ther, the epidemiologic and experimental evidence show coherence for effects of NO 2 exposure on host defense or immune system effects. This group of outcomes also provides biological plausibility for othe r respiratory effects described subsequently, such as respiratory symptoms or ED visits for respiratory diseases.



# 3.1.2. Airway Inflammation

Epidemiologic studies have examined biological markers for inflammation (exhaled NO and inflammatory nasal lavage [NAL] markers) and lung damage (urinary Clara cell protein CC16). Several studies have been conducted in cohorts of children. Steerenberg et al. (2001) studied 126 schoolchildren from urban and suburban communities in the Netherla nds. Sampling of exhaled air and NAL fluid was performed seven times, once per week over the c ourse of 2 months. On average, the ambient NO 2 concentrations were 1.5 times higher, and ambient NO concentrations were 7.8 times higher, in the urban compared to the suburban community. Compared to children in the suburban community, urban children had significantly greater levels of inflammatory NAL markers (interleukin [IL]-8, urea, uric acid, albumin) but not greater levels of exhaled NO. Howeve r, within the urban group, a statistically significant3-6 concentration-response relationship for exhaled NO was observed. Exhaled NO increased by 6.4 to 8.8 ppb per 20-ppb increase in NO 2 lagged by 1 or 3 days. Another study by Steerenberg et al. (2003) of 119 schoolchildren in the Netherlands found associations between ambient NO 2 and level of exhaled NO, but quantitative regression results were not given. The authors concluded from their data that an established, ongoing inflammatory response to pollen was not exacerbated by subsequent exposure to high levels of air pollution or pollen. In one recent U.S. study, Delfino et al. (2006) evaluated the relationshi p between personal and ambient levels of fine PM (PM 2.5 ), elemental carbon (EC), organic carbon (OC), and NO 2 and fractional exhaled NO (FeNO), a biomarker of airway inflammati on, in a panel of 45 school children with persistent asthma living in two southern California commun ities (Riverside and Whittier). FeNO was higher in subjects with poorly controlled asthma. Positive asso ciations were found for FeNO with several air pollutants, including NO 2 , with evidence from multipollutant approaches indicating that traffic-related sources of air pollutants underlie the findings. The au thors concluded that the “association of FeNO with personal and ambient NO 2 was largely independent of personal and ambient EC and OC fractions of PM 2.5 in two-pollutant models”, indica ting that both ambient and personal NO 2 represent other causal pollutant components not sufficiently captured by ambi ent EC or OC in the study regions.” While the effect was small ( ≤ 2.5 ppb FeNO), making it difficult to determine if it is clinically relevant, the findings support that air pollutant exposure increases inflammation in children with asthma. Several studies have evaluated effects in adu lt cohorts. Adamkiewicz et al. (2004) studied 29 elderly adults in Steubenville, OH and found signifi cant associations between increased exhaled NO and increased daily levels of PM 2.5 , but no association was found with ambient NO 2 . Timonen et al. (2004) collected biweekly urine samples for 6 months fro m 131 adults with coronary heart disease living in Amsterdam, Helsinki, and Erfurt, Germany. Estim ates using data from all three communities showed significant associations between urinary levels of Clara cell protein CC16 (a marker for lung damage) with elevations in daily PM 2.5 concentration, but not ambient NO 2 . In Helsinki, however, a statistically significant positive association was observed between NO 2 lagged by 3 days and CC16 levels. Interestingly, the correlation between NO 2 and PM 2.5 was lower in Helsinki (r=0.35) compared to this correlation in Amsterdam (r=0.49) or Erfurt (r=0.82) . Bernard et al. (1998) examined personal exposure to NO 2 and its effect on plasma antioxidants in a group of 107 healthy adults in Montpellier, France. Subjects wore passive monitors for 14 days. When subjects were divided into two exposure groups (above and below 21.3 ppb [40 μg/m 3 ]), those in the high-exposure group had significantly lower plasma β -carotene levels. This difference was even greater when the analysis was stratified by dietary β -carotene intake: exposure to >21.3 ppb (40-μg/m 3 ) NO 2 had the largest effect on plasma β -carotene level among subjects whose diet contained <4 mg/day β -carotene (p<0.005). No other pollutants were included in this study. The 1993 NO X AQCD cited preliminary findings from two clinical studies showing modest airway inflammation, as indicated by increased PMN numbers in BAL fluid after exposure to 2.0-ppm NO 2 for 4 to 6 h with intermittent exercise. Both of those studies now have been published in complete form (Azadniv et al., 1998; Devlin et al., 1999), and additional studies summarized below provide a clearer picture of the airway inflammatory response to NO 2 exposure. Annex Table AX5.2-1 summarizes the key clinical studies of NO 2 exposure in healthy subjects published since 1993, with a few key studies included prior to that date. Figure 3.1-1 illustrates the concentration-response relationship between NO 2 exposure and inflammatory responses in healthy subjects.3-7 Figure 3.1-1. Studies of airway inflammatory r esponses in relation to the total exposure to NO 2 , expressed as ppm-minutes. All of the studies involved inte rmittent exercise, and no attempt was made to adjust the exposure metric for varying intensit y and duration of exercise. Studies that did not include a proper control air exposure and those that used multiple daily exposures were not included in this figure.

Healthy volunteers exposed to 2.0-ppm NO 2 for 6 h with intermittent exercise showed a slight increase in the percentage of PMNs obtained in BAL fluid 18 h after exposure (air, 2.2 ± 0.3%; NO 2 , 3.1 ± 0.4%) (Azadniv et al., 1998). Gavras et al. (1994) studied a separate group of subjects exposed using the same protocol but assessed immediately after exposure. In this case, no effects were found in AM phenotype or expression of the cell adhesion molecule CD11b or receptors for IgG. Blomberg et al. (1997) reported that 4-h exposures to 2.0-ppm NO 2 resulted in an increase in IL-8 and PMNs in the proximal airway of healthy subjects, although no cha nges were seen in bronchial biopsies. This group also studied the effects of repeated 4-h exposures to 2-ppm NO 2 on 4 consecutive days, with BAL, bronchial biopsies, and BAL fluid antioxidant leve ls assessed 1.5-h after the last exposure (Blomberg et al., 1999). The bronchial wash fraction of BAL flui d showed a 2-fold increase in PMNs and a 1.5-fold increase in myeloperoxidase, indicating persistent mild airway inflammation with repeated NO 2 exposure. Devlin et al. (1999) exposed 8 healthy nonsmokers to 2.0-ppm NO 2 for 4-h with intermittent exercise. BAL performed the following morning showed a 3.1-fo ld increase in PMNs recovered in the bronchial fraction, indicating small airway inflammation. These investigators also observed a reduction in AM phagocytosis and superoxi de production, indicating possible adverse effects on host defense. Pathmanathan et al. (2003) conducted four repeat ed daily exposures of healthy subjects to 4-ppm NO 2 or air for 4 h, with intermittent exercise. Exposures were randomized and separated by 3 weeks. Bronchoscopy and bronchial biopsies were performed 1-h after the last exposure. Immunohistochemistry of the respiratory epithelium showed increased expression of IL-5, IL-10, and IL-13, as well as intercellular adhesion molecule-1 (ICAM-1). These in terleukins are upregulated in Th2 inflammatory3-8 responses, which are characteristic of allergic in flammation. The findings show that repeated NO 2 exposures may drive the airway inflammatory res ponse toward a Th2 or allergic-type response. Unfortunately, the report provided no data on infla mmatory cell responses in the epithelium or on the cells or cytokines in BAL fluid. Thus, the findings cannot be considered conclu sive regarding allergic inflammation. Furthermore, the exposure concentrati ons of 4 ppm are considerably higher than ambient outdoor concentrations. Recent studies provide evidence for airway inflamma tory effects at concentrations of <2.0 ppm. Frampton et al. (2002) examined NO 2 concentration responses in 21 healthy nonsmokers. Subjects were exposed to air or 0.6- or 1.5-ppm NO 2 for 3 h, with intermittent exercise, with exposures separated by at least 3 weeks. BAL was performed 3.5-h after exposur e. PMN numbers in the bronchial lavage fraction increased slightly (<3-fold) but significantly (p=0.0003) after exposure to 1.5-ppm NO 2 ; no increase was evident at 0.6-ppm NO 2 . Lymphocyte numbers increased in the br onchial lavage fraction after 0.6-ppm NO 2 , but not 1.5 ppm. CD4+T lymphocyte numbers incr eased in the alveolar lavage fraction, and lymphocytes decreased in blood. These findings indicate a lymphocytic airway inflammatory response to 0.6-ppm NO 2 , which changes to a mild neutrophilic response at 1.5-ppm NO 2 . Solomon et al. (2000) also showed increased PMNs in the bronchial fraction of BAL 18 h after the third consecutive day of exposure to 2.0 ppm NO 2 for 4 h with intermittent exercise. Jörres et al. (1995) found that 3-h exposures to 1-ppm NO 2 with intermittent exercise altered levels of eico sanoids, but not inflammatory cells, in BAL fluid collected 1-h after exposure. Eicosanoids are chemi cal mediators of the inflammatory response; their increase in BAL fluid reported in this study indicat es inflammation. The absence of an increase in PMN numbers may reflect the timing of bronchoscopy (1 h after exposure). The peak influx of PMNs may occur several hours after exposure, as it does following NO 2 exposure. The clinical studies summarized above provide evidence for airway inflammation at NO 2 concentrations of ≤ 2.0 ppm in healthy adults. Analyzing the bronchial fraction of BAL separately appears to increase the sensitivity for detec ting airway inflammatory effects of NO 2 exposure. The onset of inflammatory responses in healthy subjects app ears to be between 100 and 200 ppm-min, i.e., 1 ppm for 2 to 3 h (see Figure 3.1-1). Animal toxicological studies demonstrating chang es in protein and enzyme levels in the lung following inhalation of NO 2 are presented in Annex Table AX4.2. These include recent studies as well as studies that were reported in the 1993 AQCD. Changes in protein and enzyme levels reflect the ability of NO 2 to cause lung inflammation associated with concomitant infiltration of serum protein, enzymes, and inflammatory cells. However, interpretation of the array of changes observed may also reflect other factors. For example, NO 2 exposure may induce differentiation of some cell populations in response to damage-induced tissue remodeling. Thus, some chang es in lung enzyme activity and protein content may reflect changes in cell types, rath er than the direct effects of NO 2 on protein infiltration. Furthermore, some direct effects of NO 2 on enzymes are possible because NO 2 can oxidize certain reducible amino acids or side chains of proteins in aqueous solution (Freeman and Mudd, 1981). It has been reported that protein content cha nges in BAL fluid can be dependent on dietary antioxidant status. NO 2 exposure increases the protein content of BAL fluid in vitamin C-deficient guinea pigs at NO 2 levels of as low as 1880 μg/m 3 (1.0 ppm) after a 72-h exposure, but a 1-week exposure to 752 μg/m 3 (0.4 ppm) did not increase protein levels (Selgr ade et al., 1981). However, Sherwin and Carlson (1973) found increased protein content of BAL fluid from vitamin C-deficient guinea pigs exposed to 752-μg/m 3 (0.4 ppm) NO 2 for 1 week. Differences in exposure techniques, protein measurement methods, and/or degree of vitamin C deficiencies may explain the difference between the two studies. Hatch et al. (1986) found that the NO 2 -induced increase in BAL protein in vitamin C-deficient guinea pigs was accompanied by an increase in lung content of nonprotein sulfhydryls and ascorbic acid and a decrease in vitamin E content. The increased susceptibility to NO 2 was observed when lung vitamin C was reduced (by diet) to levels <50% normal. Studies in rats and mice published since the 1993 NO X AQCD have investigated the ability of NO 2 to induce protein level changes consistent with infl ammation. Overall, these more recent studies (included3-9 in Annex Table AX4.4), such as Müller et al. (1994) and Pagani et al. (1994), propose that markers of inflammation measured in BAL fluid such as total protein content and content of markers of cell membrane permeability (e.g., lactate dehydrogen ase increase only at or above 5-ppm exposure.



### Summary of Short-Term Exposure on Airway Inflammation
Overall, short-term exposure to NO 2 has been found to increase airway inflammation in human clinical and animal toxicological studies with exposure concentrations that are higher than ambient levels. Human clinical studies provide evidence for increased airway inflammation at NO 2 concentrations of <2.0 ppm; the onset of inflammatory responses in healthy subjects appears to be between 100 and 200 ppm-min, i.e., 1 ppm for 2 to 3 h. Increases in biological markers of inflammation were not observed consistently in healthy animals at levels of less than 5 ppm; however, increased susceptibility to NO concentrations of as low as 0.4 ppm was observed when lung vitamin C was reduced (by diet) to levels <50% of normal. The few available epidemiologic studies point to an association between ambient NO 2 concentrations and inflammatory response in the airways of children, though the associations were inconsistent in the adult populations examined.



# 3.1.3. Airway Hyperresponsiveness

Inhaled pollutants such as NO 2 may have direct effects on lung function or they may enhance the inherent responsiveness of the airway to challe nge by bronchoconstricting agents. Asthmatics are generally more sensitive to nonspecific bronchoconstr icting agents than nonasthmatics, and airway challenge testing is used diagnostically in asthmatics. There is a wide range of airway responsiveness in healthy people, and responsiveness is influenced by many factors, including medications, cigarette smoke, air pollutants, respiratory infections, occupa tional exposures, and respiratory irritants. Several drugs and other stimuli that cause br onchoconstriction have been used in challenge testing, including the cholinergic drugs methacholine and carbachol, as well as histamine, hypertonic saline, cold air, and SO 2 . Challenge with “specific” allergens is also consider ed in asthmatics. In asthmatics, there is strong relationship between the degree of nonspecific airway hyperresponsiveness and the intensity of the early airway response to allergens (Cockcroft and Davis 2006). Standards for airway challenge testing have been developed for the clinical laboratory (American Thoracic Society, 2000a). Variations in methods for administering the bronchoconstricting ag ents may substantially affect the results (Cockcroft et al., 2005). Airway hyperresponsiveness appears to have two co mponents: fixed and vari able (Cockcroft and Davis 2006). Presumably, exposure to air pollutants such as an NO 2 or O 3 could affect the variable component, although long-term, repeated exposure to air pollutants may also contribute to the fixed component. The mechanisms for these two components appear to differ. There is convincing evidence that the fixed component reflects airway remodeling, due to the chronic, long-term effects of airway inflammation (Cockcroft and Davis 2006). The vari able component is thought to reflect airway inflammation. It is linked to the late response to a llergen challenge in asthmatics, during which an influx of eosinophils and other inflammatory cells, in res ponse to the allergen, reduces lung function and airway caliber. The variable component is episodic a nd generally responds to bronchodilators and antiinflammatory agents, while the fixed component is less reversible and does not respond to antiinflammatory agents. The degree of airway hyperresponsiveness is relate d to the severity of asthma (Juniper et al. 1981; Murray et al. 1981). Airway responsiveness improves wh en asthma is treated with bronchodilators and anti-inflammatory drugs (Newhouse and Dolovich 1986), and the severity of the airway hyperresponsiveness predicts the lung function respon se to inhaled steroids (Kerstjens et al. 1993). Increased airway responsiveness is linked with airway inflammation and airway remodeling (Chetta et al. 1996), increased risk for exacerbations (Van Schayck et al. 1991), reduced lung function (Xuan et al. 2000), and increased adverse respiratory symptoms (Murray et al. 1981). In adults with asthma, more3-10 severe airway responsiveness is predictive of a more rapid loss of lung function during follow-up (Van Schayck et al. 1991). Increases in airway responsiveness in children may have important implications. For instance, airway hyperresponsiveness is a risk fact or for asthma development (Postma and Boezen 2004). Airway hyperresponsiveness in children is also predic tive of a reduced rate of growth in lung function and associated with a subsequent decline in the for ced expiratory volume in 1 s/forced vital capacity (FEV 1 /FVC) ratio, a measure of airway obstruction (Xuan et al. 2000). What is the clinical impact of transient increases in the variable component of airway responsiveness following exposure to NO 2 or other pollutants? In healthy adults without asthma or airway hyperresponsiveness, there is likely little or no clini cal impact of transient small increases in airway responsiveness following low-level inhalation expos ures. Acute inhalation exposures to very high concentrations of respiratory irritants, however, can cause persistent asthma-like airway disease and hyperresponsiveness, a condition known as the reactive ai rway dysfunction syndrome, or RADS (Bardana Jr. 1999). In asthmatics, transient changes in nonsp ecific airway responsiveness in response to inhaled pollutants may have clinical consequences. A variet y of environmental challenges can transiently increase airway responsiveness and worsen asthma control, su ch as allergen exposures (Brusasco et al. 1990), viral infections (Cheung et al. 1995; Fraenkel et al . 1995), cigarette smoke (Tashkin et al. 1993), O 3 (Kehrl et al. 1999), and other respiratory irritants (Kinsella et al. 1991). An exposure that worsens airway responsiveness to one agent in asthmatic subjects ma y enhance airway responsiveness to other challenge agents. Transient increases in ai rway responsiveness following NO 2 or other pollutant exposures have the potential to increase symptoms and worsen asthma cont rol, even if the pollutant exposure does not cause acute decrements in lung function.



## 3.1.3.1. Allergen Responsiveness

Asthmatic Individuals
In asthmatics, inhalation of an allergen to which a person is sensitized can cause bronchoconstriction and increased airway inflammati on, and this is an important cause of asthma exacerbations. Aerosolized allergens can be used in controlled airway challenge testing in the laboratory, either clinically to identify speci fic allergens to which the individual is responsive or in research to investigate the pathogenesis of the airway allergic response or the effectiveness of treatments. The degree of responsiveness is a function of the concentration of inhaled allergen, the degree of sensitization as measured by the level of allergen-specific IgE, and the degree of nonspecific airway responsiveness (Cockcroft and Davis, 2006). It is difficult to predict the level of respons iveness to an allergen, and although rare, severe bronchoconstriction can occur in response to inhalation of very low concentrations of allergen. Allergen challenge testing, therefore, involves greater risk than nonspecific airway challenge with drugs such as methacholine. Asthmatics may experience both an “early ” response, with declines in lung function within minutes after the challenge, and a “late” response, with a decline in lung function hours after the exposure. The early response primarily reflects release of histamine and other mediators by airway mast cells; the late response reflects enhanced airway inflammation and mucous production. Responses to allergen challenge are typically measured as chang es in pulmonary function, such as declines in the forced expiratory volume in 1 s (FEV 1 ). However, the airway inflamma tory response can also be assessed using BAL, induced sputum, or exhaled breath condensate. The potential for NO 2 exposure to enhance responsiveness to allergen challenge in asthmatics deserves special mention. Several recent studies, summarized in Annex Table AX5.3-2, have addressed the question of whether low-level exposures to NO 2 , both at rest and with exercise, enhance the response to specific allergen challenge in mild asthmatics. These recent studies involving allergen challenge show that NO 2 may enhance the sensitivity to allergen-induced decrements in lung function and increase the allergen-induced airway inflammatory response. Figur e 3.1-2 categorizes the allergen challenge studies as3-11 “positive,” i.e., showing evidence for increased responses to allergen in association with NO 2 exposure that reach statistical significance, or “negative” for r esponses that are null or not statistically significant, with the exposure metric expressed as ppm-min. In comparing Figure 3.1-2 with Figure 3.1-1, the enhancement of allergic responses in asthmatics occu rs at exposure levels more than an order of magnitude lower than those associated with airway inflammation in healthy subjects. The dosimetry difference is even greater when considering that th e allergen challenge studies generally were performed at rest, while the airway inflammation studies in healthy subjects were performed with intermittent exercise. Tunnicliffe et al. (1994) exposed 8 subjects with mild asthma to 0.1 or 0.4 ppm NO 2 for 1 h at rest and reported that 0.4 ppm NO 2 exposure slightly increased responsiveness to a fixed dose of allergen during both the early and late phases of the response. In two U.K. studies (Devalia et al., 1994; Rusznak et al., 1996), exposure to the combination of 0.4 ppm NO 2 and 0.2-ppm SO 2 increased responsiveness to subsequent allergen challenge in mild atopic asthma tics, whereas neither pollutant alone altered allergen responsiveness.

Figure 3.1-2. Airway responsiveness to allergen challenge in asthmatic subjects following a single exposure to NO 2 . Responsiveness was assessed using spirometric (circles) and inflammatory (squares) endpoints. On the verti cal axis, positive and negative indicate studies finding statistically significant and non-significant effects of NO 2 on group mean responsiveness to allergen, respectively.

A series of studies from the Karolinska Institute in Sweden have explored airway responses to allergen challenge in asthmatics. Strand et al. (1997) demonstrated that single 30-min exposures to 0.26 ppm NO 2 increased the late phase response to allergen challenge 4 h after exposure. In a separate study (Strand et al., 1998), four daily repeated exposures to 0.26 ppm NO 2 for 30 min increased both the early and late phase responses to allergen. Barck et al. (2002) used the same exposure and challenge protocol as used in the earlier Strand et al. (1997) st udies (0.26 ppm for 30 min, with allergen challenge 4-h after exposure) and performed BAL 19-h af ter the allergen challenge to determine NO 2 effects on the3-12 allergen-induced inflammatory response. NO 2 followed by allergen caused increases in the BAL recovery of PMN and eosinophil cationic protein (ECP), with reduced volume of BAL fluid and reduced cell viability, compared with air followed by allergen. EC P is released by degranulating eosinophils, is toxic to respiratory epithelial cells, and is thought to play a role in the pathogenesis of airway injury in asthma. These findings indicate that NO 2 exposure enhanced the airway inflammatory response to allergen. Subsequently, Barck et al. (2005a) exposed 18 mild asthmatics to air or NO 2 for 15 min on day 1, followed by two 15-min exposures separated by 1-h on day 2, with allergen ch allenge after exposures on both days 1 and 2. Sputum was induced before expos ure on day 1 and after exposures (morning of day 3). NO 2 +allergen, compared to air+allergen, treatment resu lted in increased levels of ECP in both sputum and blood and increased myeloperoxidase levels in blood. A separate study examined NO 2 effects on nasal responses to nasal allergen challenge (Barck et al., 2005b). Single 30-min exposures to 0.26 ppm NO 2 did not enhance nasal allergen responses. All exposures in the Karolinska Institute studies (Barck et al., 2002, 2005a; (Strand et al., 1997; 1998) used subjects at rest. These studies utilized an adequate number of subjects, included air control exposures, randomized e xposure order, and separated exposures by at least 2 weeks. Together, they indicate that quite brief exposures to 0.26-ppm NO 2 can cause effects in allergen responsiveness in asthmatics. The findings in these studies of allergen responsiven ess may shed some light on the variable results in earlier studies of NO 2 effects on nonspecific airway responsiveness. It is possible that some prior studies may have been variably confounded by e nvironmental allergen exposure, increasing the variability in subject responses to NO 2 and perhaps explaining some of the inconsistent findings. Several studies have been conducted using longer NO 2 exposures. Wang et al. (1995a,b, 1999) found that more intense (0.4 ppm) and prolonged (6 h) NO 2 exposures enhanced allergen responsiveness in the nasal mucosa in subjects with allergic rhinitis. Jenkins et al. (1999) examined FEV 1 decrements and airway responsiveness to allergen in a group of mild, atopic asthmatics. The subjects were exposed for 3 h to 0.4 ppm NO 2 , 0.2 ppm O 3 , and 0.4 ppm NO 2 +0.2 ppm O 3 . The subjects were also exposed for 6 h to produce exposure concentrations that would provide id entical doses to the 3-h protocols (i.e., equivalent in concentration times duration of exposure [C X T]). Significant increases in airway responsiveness to allergen occurred following all the 3-h exposures, but not following the 6-h exposures. However, Witten et al. (2005) did not find enhanced airway inflamma tion or a reduction in allergen provocative dose that produces a 20% decrease in FEV 1 (PD20-FEV 1 ) with allergen challenge in 15 asthmatic subjects allergic to house dust mite allergen who were exposed to air and 0.4 ppm NO 2 for 3-h with intermittent exercise. Allergen challenge was performed immediately afte r exposure, and sputum induction was performed 6 and 26 h after the allergen challenge . There was no overall effect of NO 2 on allergen responsiveness, although 3 subjects required a much smalle r concentration of allergen after NO 2 than after air exposure and were deemed to be NO 2 “responders.” NO 2 exposure was surprisingly associated with a reduction in sputum eosinophils, with no increase in alle rgen-induced neutrophilic inflammation. The differing findings in these studies may relate in part to differences in timing of the allergen challenge, the use of multiple- versus single-dose a llergen challenge, the use of BAL versus sputum induction, exercise versus rest during exposure, a nd differences in subject susceptibility. Overall, these studies indicate that NO 2 short-term exposures of less than 1 ppm enhance allergen responsiveness in some allergic asthmatics. Lastly, one study examined the effects on allergen responsiveness of exposure to traffic exhaust in a tunnel (Svartengren et al., 2000). Twenty mild asthmati cs sat in a stationary vehicle within a busy tunnel for 30 min. Allergen challenge was performed 4 h late r. The control exposure was in a hotel room in a suburban area with low air pollution levels. Exposur es were separated by 4 weeks and the order was randomized. Median NO 2 levels in the vehicle were 313 μg/m 3 (range, 203 to 462), or 0.166 ppm, (range, 0.106 to 0.242). PM 10 levels were 170 μg/m 3 (range, 103 to 613), and PM 2.5 levels were 95 μg/m 3 (range, 61 to 128). Median NO 2 levels outside the hotel were 11 μg/m 3 or 0.006 ppm. Subjects in the tunnel experienced increased cough, and also reported awar eness of noise and odors. More importantly, there was a greater allergen-induced incr ease in specific airway resistance after the tunnel exposure than after3-13 the control exposure (44% versus 31% respectively). Thoracic gas volume also was increased to a greater degree after the tunnel exposure, demonstrating in creased gas trapping within the lung. These findings were most pronounced in the subjects exposed to the highest levels of NO 2 . This study proposes that exposure to traffic exhaust, and particularly the NO 2 component, increases allergen responsiveness in asthmatics, and the results fit well with the findings in studies of clinical exposures of NO 2 (Barck et al., 2002, 2005a). However, it was not possible to blind th e exposures, and the control exposure (hotel room, presumably quiet and relaxed) was not well matche d to the experimental exposure (vehicle, noisy, odorous). It remains possible that factors other than NO 2 contributed to, or were responsible for, the observed differences in allergen responsiveness. Th ese recent studies involving allergen challenge show that NO 2 may enhance the sensitivity to allergen-induced decrements in lung function and increase the allergen-induced airway inflammatory response. Enha ncement of allergic responses in asthmatics occurs at exposure levels of more than an order of ma gnitude lower than those associated with airway inflammation in healthy subjects. The dosimetry diffe rence is even greater when considering that the allergen challenge studies generally were performed at rest, while the airway inflammation studies in healthy subjects were performed with intermittent ex ercise. Enhancement of a llergen responses has been found at exposures as low as 8 ppm-min, i.e., 0.26 ppm for 30 min. The exposure-response characteristics of NO 2 effects on allergen responses, as well as the effect s of exercise, relationship to the severity of asthma, the role of asthma medications, and other clinical factors are not fully understood.



### Toxicological Studies
Acute exposures of Brown Norway rats to NO 2 at a concentration of 5 ppm for 3 h resulted in increased specific immune response to house dust mite allergen and increased immune-mediated pulmonary inflammation (Gilmour et al., 1996). Higher levels of antigen-specific serum IgE, local IgA, IgG, and IgE were observed when rats were exposed to NO 2 after both the immunization and challenge phase but not after either the immunization or challenge phase alone . Increases in the number of inflammatory cells in the lungs and lymphocyte responsiveness to house dust mite allergen in the spleen and mediastinal lymph node were observed. The authors concluded that th is increased immune responsiveness to house dust mite allergen may be the result of the increased lung permeability caused by NO 2 exposure, enhancing translocation of the antigen to local lymph nod es and circulation to other sites in the body. A delayed bronchial response, seen as increased respiration rate, occurred in NO 2 -exposed, Candida albicans-sensitized guinea pigs 15 to 42 h after a cha llenge dose of C. albicans (Kitabatake et al., 1995). Guinea pigs were given an intraperitoneal injecti on of C. albicans, followed by a second injection 4 weeks later. Two weeks after the second injection, the animals were given an inhalation exposure of killed C. albicans. Animals were also exposed 4 h/day to 4.76 ppm NO 2 from the same day as the first injection of C. albicans, for a total of 30 exposures (5 days/week). In a study with NO 2 -exposed rabbits, pulmonary function (lung resistance, dynamic compliance) was not affected when immunized intraperitoneally w ithin 24 h of birth until 3 months of age to either Alternaria tenuis or house dust mite antigen. The ra bbits were given intraperitoneal injections once weekly for 1 month, and then every 2 weeks thereafter, and exposed to 4 ppm NO 2 for 2 h daily (Douglas et al., 1994). To determine the effect of NO 2 on allergenic airway responses in sensitized animals, Hubbard et al. (2002) exposed ovalbumin (OVA)-sensitized mice to NO 2 (0.7 or 5 ppm, 2 h/day for 3 days) or air. While the air-exposed mice developed lower airway inflamma tion (increased total BAL cellularity and increased eosinophil levels), the NO 2 -exposed mice had significantly lower levels of eosinophils for both NO 2 concentrations, with the greatest effect seen at the lower NO 2 concentration. These results were confirmed in a subsequent experiment (0.7 ppm NO 2 for 3 or 10 days) showing significant reductions in BAL cellularity and eosinophil levels for both time points. In a similar study (Proust et al., 2002), mice were sensitized and challenged with OVA and then exposed to NO 2 (5 or 20 ppm, 3 h). The 20 ppm NO 2 exposure resulted in a significant increase in bronc hopulmonary hyperreactivity 24 h after exposure, as3-14 compared to the OVA-air and 5 ppm NO 2 group. However, exposure to 5 ppm NO 2 resulted in a marked reduction in bronchopulmonary hyperreactivity as compared to both the 20 ppm NO 2 and OVA-air groups. By 72 h, bronchopulmonary hyperreactivity in all groups was comparable. The measurement of fibronectin in the BAL fluid was used as a marker of epithelial permeability. At 24 h after exposure, fibronectin levels were significantly higher in the 20 ppm NO 2 group as compared to both the 5 ppm NO 2 and air groups. However, fibronectin levels in the 5 ppm NO 2 group were significantly lower than the OVA-air group. After 72 h, there was no difference in fibronectin levels between the OVA-air and 5-ppm NO 2 groups, while fibronectin levels of the 20 ppm NO 2 group remained significantly higher than the 5 ppm NO 2 group. The recruitment of PMNs as measured in the BAL fluid at 24 h postexposure, revealed a dose-dependent increase reaching significance only with the 20 ppm NO 2 exposure. By 72 h, all groups were comparable. In contrast, the recruitment of eosinophils, as measured in the BAL fluid, showed no significant differences between groups at the 24 h time point, yet at the 72-h point, eosinophils were significantly decreased in the 5 ppm NO 2 group as compared to OVA-air group. Eosinophil peroxidase (EPO) in the lung tissue showed a similar trend with NO 2 exposure reducing the EPO levels as compared to OVA-air controls. At 24 h, EPO was significantly lower in the 5 and 20 ppm NO 2 groups as compared to the OVA-air group, while at 72 h, only the 5 ppm NO 2 group was significantly lower. IL-5 was measured in the BAL fluid, and the 5 ppm NO 2 group was significantly lower in IL-5 than all other groups, and the 20 ppm NO 2 group was significantly higher.



## 3.1.3.2. Nonspecific Responsiveness

Healthy Individuals

Several observations indicate that NO 2 exposures in the range of 1.5 to 2.0 ppm cause small but significant increases in airway responsiveness in hea lthy subjects. Mohsenin (1988) found that a 1-h exposure to 2 ppm NO 2 increased responsiveness to methacholine, as measured by changes in specific airway conductance, without directly affecting lung function. Furthermore, pretreatment with ascorbic acid prevented the NO 2 -induced increase in airway responsiven ess (Mohsenin, 1987a). A mild increase in responsiveness to carbachol was observed following a 3-h exposure to 1.5 ppm NO 2 , but not to intermittent peaks of 2.0 ppm (Frampton et al., 1991) . Thus, the lower threshold concentration of NO 2 for causing increases in nonspecific airway responsiveness in healthy subjects appears to be in the 1- to 2-ppm range.



### Asthmatic Individuals

The 1993 NO X AQCD reported results that showed NO 2 might enhance subsequent responsiveness to challenge at relatively low NO 2 concentrations within the range of 0.2 to 0.3 ppm. From the studies for which individual data were readily available, the number of subjects whose airway responsiveness increased and whose airway responsiveness decreased is listed in Table 3.1-2. Table 3.1-2 reproduces airway responsiveness data for asthmatics that w as previously provided in Table 15-9 of the 1993 NO X AQCD. In the 19 studies included in this table, asthmatics were exposed to NO 2 concentrations ranging from 0.1 to 1.0 ppm. The vast majority (17 of 19) of these studies utilized nonspecific challenge agents. Tabulation of data from this table provides informa tion regarding the direction of the change (i.e., increase or decrease) in airway responsiveness following NO 2 exposure. Some of the disparate findings of these studies are discussed below.3-15 Table 3.1-2. Changes in airway responsiveness associated with NO 2 exposure.

CHANGE IN AHR AVERAGE PD ± SD STUDY N NO 2 (ppm) EXP (min) CHALLENGE TYPE END POINT TIME POST EXP (min) EXER

INC DEC AIR NO 2 NOTES

Ahmed et al. (1983b) 20 0.1 60 CARB sGAW — N 13 7 6.0 2.7

Ahmed et al. (1983a) 19 0.1 60 RAG sG AW — N 10 8 9.0 ± 25 3.4 ± 4.6

Hazucha et al. (1983) 15 0.1 60 METH sRaw 20 N 6 7 1.9 ± 0.4 2.0 ± 1.0

Orehek et al. (1976) 20 0.1 60 CA RB sRaw 0 N 14 3 0.6 0.4

Rasmussen et al. (1990) 20 0.1 120 METH FEV 1 0 Y — — (AIR-NO 2 =0.00)

Orehek et al. (1981) 7 0.11 60 GRASS sR aw 0 N — — 1.2 ± 0.3 1.3 ± 0.3 4 allergic3 asthmatic

Bylin et al. (1988) 20 0.14 30 HIST sRaw 25 N 14 6 — —

Roger et al. (1990) 19 0.15 80 METH sR aw 60 Y 10 7 3.3 ± 0.7 3.1 ± 0.7

Kleinman et al. (1983) 31 0.20 120 METH FEV 1 0 Y 20 7 8.6 ± 16 3.0 ± 6.2

Rasmussen et al. (1990) 20 0.20 120 METH FEV 1 0 Y — — (AIR-NO 2 =0.02)

Jörres and Magnussen (1990) 14 0.25 30 SO 2 sRaw 27 N 11 2 47 ± 5.1 37.7 ± 3.5

Jörres and Magnussen (1991) 11 0.25 30 METH sRaw 60 Y 7 4 0.4 ± 1.6 0.4 ± 1.6

Bylin et al. (1988) 20 0.27 30 HIST sRaw 25 N 14 6 — —

Avol et al. (1988) 37 0.30 120 COLD FEV 1 60 Y 11 16 -8.4 ± 11 -10.7 ± 12 Delta FEV 1

Avol et al. (1989) 34 0.30 30 COLD FEV 1 60 Y 12 21 -5.3 ± 12 -4.7 ± 13 Delta FEV 1
Bauer et al. (1986a) 12 0.30 30 COLD FEV 1 60 Y 9 3 0.8 ± 0.4 0.5 ± 0.3 PD10RHE

Linn et al. (1986) 21 0.30 120 COLD FEV 1 0 Y -11.4 -12.1 Delta FEV 1
Morrow and Utell (1989) 20 0.30 225 CARB sGaw — Y — — — —

Roger et al. (1990) 19 0.30 80 METH sR aw 60 Y 8 9 3.3 ± 0.7 3.3 ± 0.8

Rubinstein et al. (1990) 9 0.30 30 SO 2 sRaw 60 Y 4 5 1.3 ± 0.7 1.3 ± 0.8

Bylin et al. (1985) 8 0.48 20 HIST sRaw 20 N 5 — — —

Mohsenin (1987b) 10 0.50 60 METH sGaw 0 N 7 2 9.2 ± 1.5 4.6 ± 8.0

Bylin et al. (1988) 20 0.53 30 HIST sRaw 25 N 12 7 — —

Avol et al. (1988) 37 0.60 120 COLD FEV 1 60 Y 13 16 -8.4 ± 11 -10.4 ± 14 Delta FEV 1
Roger et al. (1990) 19 0.60 80 METH sR aw 60 Y 11 8 3.3 ± 0.7 3.7 ± 1.1

Rasmussen et al. (1990) 20 0.80 120 METH FEV 1 0 Y — — (AIR-NO 2 =-0.06)

Linn et al. (1986) 21 1.00 120 COLD FEV 1 0 Y — — -11.4 -11.2 Delta FEV 1 AHR: Airway Hyperresponsiveness CARB: Carbachol COLD: Cold-dry air GRASS: Grass pollen HIST: Histamine METH: Methacholine RAG: Ragweed PD: Provocative dose PD10RHE=Respiratory heat exchange (loss) for 10% drop in FEV 13-16 Roger et al. (1990), in a comprehensive, con centration-response experiment, were unable to confirm the results of a pilot study indicating airway responses occur in asthmatic subjects. Twenty-one male asthmatics exposed to NO 2 at 0.15, 0.30, or 0.60 ppm for 75 min did not experience significant effects on lung function or airway responsiveness comp ared with air exposure. Bylin et al. (1985) found significantly increased bronchial responsiveness to hist amine challenge compared with sham exposure in 8 atopic asthmatics exposed to 0.30-ppm NO 2 for 20 min. Five of 8 asthmatics demonstrated increased reactivity, while 3 subjects showed no change, as assessed by specific airway resistance. Mohsenin (1987b) reported enhanced responsiveness to methacho line in 8 asthmatic subjects exposed to 0.50-ppm NO 2 at rest for 1 h; airway responsiveness was measure d by partial expiratory flow rates at 40% vital capacity, which may have increased the sensitivity for detecting small changes in airway responsiveness. Jörres and Magnussen (1991) found no effects on lung function or methacholine responsiveness in 11 patients with mild asthma after exposure to 0.25-ppm NO 2 for 30 min with 10 min of exercise. Most recently, Strand et al. (1996) performed a series of studies in mild asthmatics exposed to 0.26 ppm for 30 min and found increased responsiveness to histamine. The effects of NO 2 exposure on SO 2 -induced bronchoconstriction also have been examined, but with inconsistent results. Jörres and Magnussen ( 1990) found an increase in airway responsiveness to SO 2 in asthmatic subjects following exposure to 0.25-ppm NO 2 for 30 min at rest; yet Rubenstein et al. (1990) found no change in responsiveness to SO 2 inhalation following exposure of asthmatics to 0.30-ppm NO 2 for 30 min with 20 min of exercise. The varied results of these studies have not been satis factorily explained. It is evident that a wide range of responses occurs among asthmatics exposed to NO 2 . This variation may in part reflect differences in individual subjects and exposure protoc ols: mouthpiece versus chamber, obstructed versus non-obstructed asthmatics, rest versus exercise, and varying use of medication(s) among subjects. Indeed, via meta-analysis, Folinsbee (1992) found that airway responsiveness was greater in asthmatics exposed to NO 2 at rest than during exercise. Following NO 2 exposures between 0.2 and 0.3 ppm NO 2 , only 52% of subjects exposed with exercise had increased res ponsiveness, whereas 76% of subjects had increased responsiveness in protocols using resting exposures. The factors that predispose some asthmatics to NO 2 responsiveness is still not understood. Studies have typi cally involved volunteers with mild asthma; data are lacking from more severely affected asthmatics, who may be more susceptible. Table 3.1-3 provides a meta-analysis of the non-specific airway responsiveness data in Table 3.1-2. In terms of the fraction of asthmatics affected a nd statistical significance for the indicated exposure concentration ranges, the data in Table 3.1-3 are similar to those provided in Table 15-10 of the 1993 NO X AQCD and by Folinsbee (1992). Table 3.1-3 differs from the prior analysis in that a study using specific responses to ragweed was excluded (Ahmed et al., 1983a), a recent study using nonspecific responses to histamine was included (Strand et al ., 1996), and an additional concentration range of 0.1 ppm was considered. Overall, analysis of th ese data for 355 asthmatics indicates that short-term exposures to NO 2 at outdoor ambient concentrations (<0.3 ppm) are linked to nonspecific airway hyperresponsiveness in people with mild asthma.

Table 3.1-3. Fraction of NO 2 -exposed asthmatics with increased non- specific airway hyperresponsiveness.

NO 2 ppm ALL EXPOSURES EXPOSURE WITH EXERCISE EXPOSURE AT REST

0.1 0.66 (50) B — 0.66 (50) B

0.1 - 0.15 0.66 (87) C 0.59 (17) 0.67 (70) C

0.2 - 0.3 0.58 (187) B 0.52 (136) 0.75 (51) C

>0.3 0.59 (81) 0.49 (48) 0.73 (33) B

0.1 - 0.6 0.60 (355) C 0.52 (201) 0.71 (154) C

Note: Values represent the fraction of asthmatics (out of the total number of individuals in parentheses) having an increase in airway responsiveness following NO 2 exposure versus air. Analysis is for 355 asthmatics in Table 3.1-2 with the exclusion of the Ahmed et al. (1983a) data for the specific airway responsiveness of 18 asthmatics to ragweed and the addition of responses of 18 asthmatics (13 with increased re sponsiveness to histamine) 30 minutes after exposure to 0.2 6 ppm NO 2 for 30 minutes during rest from Strand et al. (1996). B p ≤ 0.05 two-tailed sign test. C p ≤ 0.01 two-tailed sign test.3-17 

### Toxicological Studies
In the previous review, toxicological evidence supported a conclusion that airway responsiveness was one of the key health responses to NO 2 exposure. A number of recent animal studies have also reported airway responsiveness with NO 2 exposure. Overall, many studies have demonstrated the ability of NO 2 exposure to increase bronchial sensitivity to va rious challenge agents, although the mechanisms for this response are not fully known. Kobayashi and Miura (1995) studied the con centration- and time-dependency of airway hyperresponsiveness to inhaled histamine aerosol in guinea pigs exposed subchronically to NO 2 . In one experiment, guinea pigs were exposed by i nhalation to 0, 0.06, 0.5, or 4.0 ppm NO 2 , 24 h/day for 6 or 12 weeks. Immediately following the last exposure, airway responsiveness was assessed by measurement of specific airway resistance as a function of increasi ng concentrations of histamine aerosol. Animals exposed to 4 ppm NO 2 for 6 weeks exhibited increased airway response to inhaled histamine aerosol; airway response at 12 weeks was not determined. No effects were observed at the lower exposure levels. In another experiment conducted in this study (Kobayashi and Miura, 1995), guinea pigs were exposed by inhalation to 0, 1.0, 2.0, or 4.0 ppm NO 2 , 24 h/day for 6 or 12 weeks, and the airway hyperresponsiveness was determined. Increased hyperresponsiveness to inhale d histamine was observed in animals exposed to 4 ppm for 6 weeks, 2 ppm for 6 and 12 weeks, and 1 ppm for 12 weeks only. The results also showed that at 1 or 2 ppm NO 2 , airway hyperresponsiveness developed to a higher degree with the passage of time. Higher concentrations of NO 2 were found to induce airway hyperresponsiveness faster compared to lower concentrations. When the specific ai rway resistance was compared to va lues determined 1 week prior to initiation of the NO 2 exposure, values were increased in the 2.0 and 4.0 ppm animals at 12 weeks only. Specific airway resistance was also increased to a higher degree with the passage of time.



## 3.1.3.3. Summary of Short-Term Exposure on Airway Responsiveness

The evidence from human and animal experimental studies provides evidence for increased airway responsiveness to specific alle rgen challenges following NO 2 exposure. Recent human clinical studies show that NO 2 exposure may enhance sensitivity to allerg en-induced decrements in lung function and increase allergen-induced airway inflammatory response at exposures as low as 0.26 ppm NO 2 for 30 min (Figure 3.1-2). Inflammatory responses to the allerg en challenge were not accompanied by changes in pulmonary function or subjective symptoms. Incr eased immune-mediated pulmonary inflammation was also observed in rats exposed to house dust mite allergen following exposure to 5 ppm NO 2 for 3 h. Exposure to NO 2 also has been found to enhance the inherent responsiveness of airway to subsequent nonspecific challenges in human clinical studies. In general, small but significant increases in nonspecific airway responsiveness were observed in the ra nge of 1.5 to 2.0 ppm for 3 h in healthy adults and between 0.2 and 0.3 ppm NO 2 for 30 min for asthmatics, but a wide range of responses were observed, particularly among asthmatics. Subchronic NO 2 exposure (6 to 12 weeks) of animals also increases responsiveness to nonspecific challenges at 1 to 4 ppm NO 2 . Results from human studies were inconsistent; some, reported increased responsiveness following NO 2 exposure. A variety of factors could contribute to this apparent inconsistency. For instance, responsiveness has been observed to be greater following resting than exercising exposures to NO 2 , despite the greater NO 2 exposure to the respiratory tract during exercise. In addition, the methods for administering the bronchoconstricting challenge agents and degree of sensitization to specific allergen also are recognized to affect responsiveness (Coc kcroft et al., 2005; Cockcroft and Davis, 2006).3-18 

# 3.1.4. Effects of Short-Term Exposure on Respiratory Symptoms

Since the 1993 AQCD, additional studies have reported health effects associated with NO 2 from indoor exposure, personal exposure, and ambien t concentration studies. The following section characterizes the results of these studies.



## 3.1.4.1. Indoor and Personal Exposure and Respiratory Outcomes

Indoor NO 2 exposures may differ from ambient exposures with respect to temporal pattern and levels of NO 2 , and also with the copollutants associated with indoor NO 2 sources (see Annex Table AX6.3-1 for details). Samet and Bell (2004) stat e that while “evidence from studies of outdoor air pollution cannot readily isolate an effect of NO 2 because of its contribution to the formation of secondary particles and O 3 , observational studies of exposure indoors can test hypotheses related to NO 2 specifically although confounding by combustion sources in the home is a concern.” Most of the studies conducted since 1993 have take n place in Australia and attempted to monitor indoor exposures (with passive diffusion badges) from both cooking and heating sources in homes and schools (Pilotto et al., 1997; 2004; Rodriguez et al., 2007; Garrett et al., 1998; Smith et al., 2000). Several indoor exposure studies have also been conducted in the U.S. (Belanger et al., 2006; Kattan et al., 2007; van Strien et al., 2004), Europe (Farrow et al., 1997; Simoni et al., 2002, 2004), and Singapore (Ng et al., 2001). The results from these studies are su mmarized in Annex Table AX6.3-1. One intervention study provided strong evidence of a detrimental effect of exposure to indoor levels of NO 2 . Pilotto et al. (2004) conducted a randomized intervention study of respiratory symptoms of asthmatic children in Australia before and after selec tive replacement of unflued gas heaters in schools. In the study, 18 schools using unflued gas heaters were ra ndomly allocated to have an electric heater (n=4) or a flued gas heater (n=4) installed or to retain their original heaters (n=10). Changes to the heating systems were disguised as routine maintenance to pr event bias in reporting of symptoms. Children were eligible for the study if they had physician-diagnosed asthma and no unflued heater in their home. For the 114 children enrolled, symptoms were recorded daily and reported in biweek ly telephone interviews during 12 weeks in the winter. Passive diffusion badges were used to measure NO 2 exposure in classrooms (6 h/day) and in the children’s homes. Sc hools in the intervention group (with new heaters) averaged overall means (standard devision [SD]) of 15.5 (6.6) ppb NO 2 , while control schools (with unflued heaters) averaged 47.0 (26.8) ppb. Exposure to NO 2 in the children’s homes was quite variable but with similar mean levels. Indoor levels at hom es for the intervention group were 13.7 (19.3) ppb and 14.6 (21.5) ppb for the control group. Children atte nding intervention schools had significant reductions in several symptoms (see Table 3.1-4): difficulty breathing during the day (RR=0.41 [95% CI: 0.07, 0.98]) and at night (RR=0.32 [95% CI: 0.14, 0.69]); chest tightness during the day (RR=0.45 [95% CI: 0.25, 0.81]) and at night (RR=0.59 [95% CI: 0.28, 1.29]); and asthma attacks during the day (RR=0.39 [95% CI: 0.17, 0.93]). Samet and Bell (2004) stated that Pilotto et al. (2004) provided persuasive evidence of an association between exposure to NO 2 from classroom heaters and the respiratory health of children with asthma; further, the intervention study design alle viated some potential limitations of observational studies. The two groups of children studied had similar baseline characteristics. In addition, concentrations in the home environment were simila r for the two groups, implying that exposure at school was likely to be the primary determinant of a difference in indoor NO 2 exposure between the two groups. However, it is possible that confounding by particle emissions, particularly UFP, may be present.3-19 Table 3.1-4. Mean rates (SD) per 100 days at risk and unadjusted rate ratio (RR) for symptoms/activities over 12 weeks during the winter heating period.

SYMPTOM / ACTIVITY MEAN RATE INTERVENTION (N=45) MEAN RATE CONTROL (N=69) RR (95% CI)

Wheeze during the day 4.9 (15.2) 5.1 (10.5) 0. 95 (0.45, 2.01)

Wheeze during the night 2.2 (5.6 ) 2.3 (5.5) 0.94 (0.36, 2.50)

Difficulty breathing during the day 2. 2 (3.7) 5.4 (12.1) 0.41 (0.07, 0.98)

Difficulty breathing during the night 0.8 (2.2) 2.6 (6.9) 0.32 (0.14, 0.69)

Chest tightness during the day 2.3 (4.3) 5.1 (9.9) 0.45 (0.25, 0.81)

Chest tightness during the night 1.5 (3.3) 2.5 (6.2) 0.59 (0.28, 1.29)

Cough during the day 17.5 (21.5) 13.7 (13.7) 1.27 (0.81, 2.00)

Cough during the night 10.7 (16.6) 11.6 (12.4) 0. 92 (0.49, 1.73)

Difficulty breathing after exercise 3. 8 (7.4) 6.4 (13.9) 0.59 (0.31, 1.13)

Asthma attacks during the day 1.1 (2.3) 2.7 (5.3) 0.39 (0.17, 0.93)

Asthma attacks during the night 0.7 (2.1) 1.8 (3.8) 0.38 (0.13, 1.07)

Missed school due to asthma 1.6 (2 .0) 1.2 (2.8) 1.34 (0.68, 2.60)

Visit to health care facilities due to asthma 0.5 (0.8) 0.8 (1.2) 0.60 (0.35, 1.03)

Taking any asthma medication 26.9 ( 36.7) 34.6 (37.1) 0.77 (0.49, 1.21)

Taking any reliever 13.8 (23.2) 22.4 (28.8) 0.62 (0.31, 1.25)

Taking any preventer 26.2 (40.1) 29.9 (42.2) 0. 87 (0.53, 1.44)

Note: Following adjustment for hay fever and parental education at baseline, results remained substantially unchanged except th at difficulty breathing during the day assumed borderline significance (RR=0. 46: 95% CI: 0.19, 1.08), while t he reduction in asthma attacks du ring the night reached statistic al significance (RR=0.33; 95% CI: 0.13, 0.84). Source: Adapted from Pilotto et al. (2004).

In an earlier study of the health effects of unflu ed gas heaters on wintertime respiratory symptoms of 388 Australian schoolchildren, Pilotto et al. (1997a) measured NO 2 in 41 classrooms in 8 schools. Half used unflued gas heaters; half used electric heat. Although similar methods were used to measure NO 2 levels (passive diffusion badge monitors exposed for 6 h at a time), there were three major differences between this study and the Pilotto et al. (2004) study: (1) the 1997 study was not a randomized trial, (2) enrollment in the 1997 study was not restricted to asthmatic children, and (3) enrollment in the 1997 study was not restricted to children from homes without unflued gas heaters. In Pilotto et al. (1997a), only children from nonsmoking homes were enrolled, and a s ubset of children (n=121) living in homes with unflued gas heaters were given badges to be used at home. Parents recorded symptoms daily. Children were classified into low- and high-exposure gr oups based on measured exposure at school, measured exposure at home (if their homes had unflued gas heaters), or their reported use of electric heat. Maximum hourly concentrations in these classrooms reco rded during 2 weeks were highly correlated with their corresponding 6 h concentrations (r=0.85). Hourly peaks of NO 2 on the order of ≥ 80 ppb were associated with 6 h average levels of approximately ≥ 40 ppb. The authors inferred that children in classrooms with unflued gas heaters that had 6-h average levels of ≥ 40 ppb were experiencing approximately 4 fold or higher 1-h peaks of exposure than the NO 2 levels experienced by children who had no gas exposure (6-h average levels of 20 ppb). The importance of this study was that it examined the effect of repeated peaks over time as have been used in the toxicological infectivity studies (e.g., Miller et al., 1987) that were noted earlier in Section 3.1.1.3-20 Source: Adapted from Pilotto et al. (1997a)
Figure 3.1-3. Geometric mean symptom rates (95% CI) for cough with phlegm (panel A) and proportions (95% CI) of children absent from school for at l east 1 day (panel B) during the winter heating period grouped by estimated NO 2 exposure at home and at school (n=number of children at that NO 2 level). Group means estimated using mixed models.* “<40 ppb” group (n=105) includes children from electrically heated school s while the “Intermed” group (n=39) includes children from unflued gas heaters where the ex posures were consistent ly below 40 ppb. Both groups of children did not have expos ure to gas combustion at home.

Pilotto et al. (1997a) reported that during the wi nter heating season, children in the high-exposure category (NO 2 >40 ppb) had higher rates of sore throat, colds, and absenteeism than all other children. In models adjusted for personal risk factors including asthma, allergies, and geographic area, classroom NO 2 level and school absence were significantly associated (odds ratio [OR]=1.92 [95% CI: 1.13, 3.25]). Increased likelihood of individual respiratory symptoms was not significantly associated with classroom NO 2 level (e.g., cough with phlegm adjusted OR=1.28 [95% CI: 0.76, 2.15]). Exposure-response relation-3-21 ships are illustrated in Figure 3.1-3 for symptom ra tes for cough with phlegm and proportion of children absent from school. Statistically significant positive e xposure-response trends were found for mean rates for cough with phlegm (p=0.04, adjusted for conf ounders) and proportion of children absent from school (p=0.002) using mixed models allowing for correlation between children within classrooms. Pilotto et al. (1997b) noted that this study “provides evidence that short-term exposure to the peak levels of NO 2 produced by unflued gas appliances affects respirat ory health and that the significant dose-response relationship seen with increasing NO 2 exposure strengthens the evidence for a cause-effect relationship.” In a cross-sectional survey of 344 children in Au stralia, Ponsonby et al. (1997b) used passive gas samplers to measure personal exposure to NO 2 . Personal badges were pinned to a child’s clothing at the end of each school day and removed when the child a rrived at school the next day. School exposures were measured with passive samplers placed in each child’s classroom. Sampling took place over two consecutive days. Mean (SD) personal expos ure was 10.4 (11.1) ppb and mean total NO 2 exposure (personal plus schoolroom) was 10.1 (8.6) ppb. Of the health outcomes measured (recent wheeze, asthma ever, lung function measured when NO 2 sampling stopped), only the FEV 1 /FVC ratio following cold air challenge was significantly associated with NO 2 levels measured with the personal badges (-0.12 [95% CI: -0.23, -0.01]) per 1 ppb increase in personal exposur e). In Finland, Mukala et al. (1999; 2000) studied 162 preschool-age children. Mukala et al. (2000) used passive monitors exposed for 1-week periods over the course of 13 weeks both indoors and outdoors a nd on the clothing of preschool children attending eight day care centers in Helsinki. The only significant association between personal NO 2 measurements and symptoms was for cough during the winter (RR=1.86 [95% CI: 1.15, 3.02] for NO 2 at level above 27.5 μg/m 3 [14.5 ppb]). Similar results were obtained when data were analyzed unstratified by season, but including a factor for season (RR=1.52 [95% CI: 1.00, 2.31] for NO 2 at levels above 27.5 μg/m 3 [14.5 ppb], Mukala et al., 1999). One recent birth cohort study in the U.S. measured indoor exposure to NO 2 (Belanger et al., 2006; van Strien et al., 2004). Families were eligible for this study if they had a child with physician-diagnosed asthma (asthmatic sibling) and a newborn infant (birth cohort subject). NO 2 levels were measured using Palmes tubes left in the homes for 2 weeks. Higher levels of NO 2 were measured in homes with gas stoves (mean [SD], 26 [18] ppb) than in homes with electric ranges (9 [9] ppb). Children living in multifamily homes were exposed to higher NO 2 (23 [17] ppb) than children in single-family homes (10 [12] ppb). The authors examined associations between NO 2 concentrations and respiratory symptoms experienced by the asthmatic sibling in the month prior to sampling (Belanger et al., 2006). For children living in multifamily homes, each 20 ppb increase in NO 2 concentration increased the likelihood of any wheeze or chest tightness (OR for wheeze=1.52 [95% CI: 1.04, 2.21]; OR for chest tightness=1.61 [95% CI: 1.04, 2.49]) as well as increasing the risk of suffering additional da ys of symptoms. No significant associations were found between level of NO 2 and symptoms for children living in single-family homes. The authors proposed that the low levels of exposure may have b een responsible for the lack of association observed in single-family homes. In these same families, va n Strien et al. (2004) compared the measured NO 2 concentrations with respiratory symptoms experienced by the birth cohort infants during the first year of life. Although wheeze was not associated with NO 2 concentration, persistent cough was associated with increasing NO 2 concentration in an exposure-response relations hip (Figure 3.1-4) (van Strien et al., 2004). Results from a recent analysis of a subset of 469 asthmatic children enrolled in the National Cooperative Inner City Asthma Study (NCICAS) (K attan et al., 2007) where household measurements of NO 2 levels were also available, are consistent with those described above for Belanger et al. (2006). The median level of indoor NO 2 , measured with Palmes tubes left for 7 days, was 29.8 ppb, with median level in homes with gas stoves (31.4 ppb) significantly hi gher than levels in homes with electric stoves (15.9 ppb). Associations between exposure to high levels of NO 2 and symptoms in the previous 2 weeks or peak flow of <80% predicted were examined with models that adjusted for study site, gender, medication use, household smoking, and socioeconomic status (SES) variables and were stratified by season or by atopic status. Among the subset of 76 children without positive skin tests, the adjusted risk ratio (95% CI) for asthma symptoms was 1.75 (95% CI: 1.10, 2.78) for those with higher NO 2 exposure. Among the3-22 317 children with NO 2 measured in the cold season, the risk ratio for a peak flow measurement of <80% predicted was 1.46 (95% CI: 1.07, 1.97). One limitation of the study is that the “high” NO 2 level was defined vaguely as approaching the NAAQS le vel of 0.052 ppm (annual average) (52 ppb).

Source: Adapted from van Strien et al. (2004).
Figure 3.1-4. Adjusted association of increasing indoor NO 2 concentrations with number of days with persistent cough (panel a) or shortness of breat h (panel b) for 762 infants during the first year of life. Relative risks from Poisson re gression analyses adjusted for confounders.

Other recent studies have also collected personal exposure data for NO 2 . Nitschke et al. (2006) used passive diffusion badges for measuring NO 2 exposures in 6 h increments at home and school for 174 asthmatic children in Australia. School and home measu rements were based on three consecutive days of sampling. The maximum of 9 days of sampling (for 6 h each day) NO 2 value was selected as the representative daily exposure for exposure-response analy ses. Children kept a daily record of respiratory symptoms for the 12-week study period. Significant associations were found between the maximum NO 2 level at school or home and respiratory symptom rat es, though the exposure-response curve indicated that the major difference in respiratory symptoms rates were between NO 2 exposures of >80 ppb (see Annex Table AX 6.3-1). An important consideration in the evaluation of the indoor exposure studies is that NO X is part of a complex mixture of chemicals emitted from unvented gas heaters. In addition to NO and NO 2 , indoor combustion sources such as unvented gas heaters emit othe r pollutants that are present in the fuel or are formed during combustion. These pollutants include CO 2 , CO, HCHO and other VOCs, PAHs, and PM, particularly UFP, as described in Section 2.5.8.3. The studies of unvented heaters or gas stoves did not measure indoor concentrations of other combustion-re lated emissions. Unvented combustion is a potential source of UFP. High numbers of UFP, along with NO 2 , are generated during the operation of gas heaters, gas stoves, and during cooking (Dennekamp et al., 2001; Wallace et al., 2004). It is possible that the improved respiratory symptoms observed in the Pilotto et al. (2004) intervention study were related to reductions in ultrafine particle exposure, other gase ous emissions, or the pollutant mix. The findings of these recent indoor and personal exposure studies, comb ined with studies available in the previous AQCD, provide evidence that NO 2 exposure is associated with respiratory effects. These studies provide a potential bridge between epidemiologic studies usi ng ambient concentrations from centrally located monitors and human clinical studies, as discussed in the previous sections, and provide some evidence of coherence for respiratory effects.3-23 

## 3.1.4.2. Ambient NO 2 

## Exposure and Respiratory Symptoms

Since the 1993 AQCD, results have been published from several single- and multicity studies investigating ambient NO 2 levels, including three large longitudinal studies in urban areas covering the continental U.S. and southern Ontario: the Harvard Si x Cities study (Six Cities; Schwartz et al., 1994), the National Cooperative Inner-City Asthma Study (N CICAS; Mortimer et al., 2002), and the Childhood Asthma Management Program (CAMP; Schildcrout et al., 2006). Because of similar analytic techniques (i.e., multistaged modeling and genera lized estimating equations), one strength of all three of these studies is that, as Schildcrout et al. (2006) stated, they could each be considered as a meta-analysis of “large, within-city panel studies” without some of the limitati ons associated with meta-analyses, e.g., “betweenstudy heterogeneity and obvious publication bias.” The report from the Six Cities study includes 1,844 schoolchildren, followed for 1 year (Schwartz et al., 1994). Symptoms (in 13 categories, analyzed as cough, lower or upper respiratory symptoms), were recorded daily. Cities included Watertown, MA, Ba ltimore, MD, Kingston-Harriman, TN, Steubenville, OH, Topeka, KS, and Portage, WI. In Mortimer et al. (2002), 864 asthmatic children from the eight NCICAS cities (New York City, NY [two sites: Bronx and East Harlem], Baltimore, MD, Washington, DC, Cleveland, OH, Detroit, MI, St Louis, MO, and Chicago, IL) were followed daily for four 2-week periods over the course of 9 months. Morning and evening asthma symptoms (analyzed as none versus any) and peak flow were recorded. Schildcrout et al. (2006) reported on 990 asthmatic children living within 50 miles of one of 31 NO 2 monitors located in eight North American cities, seven of which included data for NO 2 (Boston, MA, Baltimore, MD, Toronto, ON, St. Louis, MO, Denver, CO, Albuquerque, NM, and San Diego, CA). Symptoms (a nalyzed as none versus any per day) and rescue medication use (analyzed as number of uses per day) we re recorded daily such that each subject had an approximate average of 2 months of data. All three studies found significant associations between ambient NO 2 concentrations and risk of respiratory symptoms in children (Schwartz et al., 1994), and in particular, asthmatic children (Mortimer et al., 2002; Schildcrout et al., 2006). In Schwartz et al. (1994), a significant association was found between a 4-day mean of NO 2 exposure and incidence of cough among all children in single-pollutant models: the odds ratio (OR) standardized to a 20-ppb increase in NO 2 was OR=1.61 (95% CI: 1.08, 2.43). Cough incidence was not significantly associated with NO 2 on the previous day. The local nonparametric smooth of the 4-day mean concentration showed increased cough incidence up to approximately the mean concentration (~13 ppb) (p=0.01), after which no further increase was observe d. The significant association between cough and 4- day mean NO 2 remained unchanged in models that included O 3 , but was attenuated in two-pollutant models including PM 10 (OR for 20-ppb increase in NO 2 =1.37 [95% CI: 0.88, 2.13]) or SO 2 (OR=1.42 [95% CI: 0.90, 2.28]). In Mortimer et al. (2002), the greatest effect of the pollutants studied for morning symptoms was for a 6-day moving average. For increased NO 2 , the risk of any asthma symptoms (cough, wheeze, shortness of breath) among the asthmatic children in the NCICAS was somewhat higher than for the healthy children in the Six Cities study: OR=1.48 (95% CI: 1.02, 2.16). Effects were generally robust in multipollutant models that included O 3 (OR for 20-ppb increase in NO 2 =1.40 [95% CI: 0.93, 2.09]), O 3 and SO 2 (OR for NO 2 =1.31 [95% CI: 0.87, 2.09]), or O 3 , SO 2 , and PM with an aerodynamic diameter of ≤ 10 μm (PM 10 ) (OR for NO 2 =1.45 [95% CI: 0.63, 3.34]).3-24 Source: Schildcrout et al. (2006).
Figure 3.1-5. Odds ratios (95% CI) for daily asthma sym ptoms (panel A) and rate ratios (95% CI) for daily rescue inhaler use (panel B) asso ciated with shifts in within-subject concentrations of NO 2 for single- and joint (with PM 10 )-pollutant models from th e CAMP (November 1993-September 1995). The city-specific estimates from Boston, Baltimore, Toronto, St. Louis, Denver, Albuquerque, and San Diego were included in the calculations of study-wide effects.3-25 In the CAMP study (Schildcrout et al., 2006), the strongest association between NO 2 and increased risk of cough was found for a 2-day lag: each 20-ppb increase in NO 2 occurring 2 days before measurement increased risk of cough (OR=1.09 [95% CI : 1.03, 1.15]). Joint-pollutant models including CO, PM 10 , or SO 2 produced similar results (see Figure 3.1-5, panel A). Further, increased NO 2 exposure was associated with increased use of rescue medication in the CAMP study, with the strongest association for a 2-day lag, both for single- and joint-po llutant models (e.g., for an increase of 20 ppb NO 2 in the single-pollutant model, the RR for increased inhaler usage was 1.05 (95% CI: 1.01, 1.09) (See Figure 3.1- 5, panel B). Single-city studies also provided updated informati on to the 1993 AQCD, particularly with regard to children. Two 3-month-long panel studies recruite d asthmatic children from one outpatient clinic in Paris: one study followed 84 children in the fall of 1992 (Segala et al., 1998), and the other followed 82 children during the winter of 1996 (Just et al., 2002) . Significant associations were observed between respiratory symptoms and level of NO 2 (See Annex Table AX6.3-2). No multipollutant analyses were conducted. In metropolitan Sydney, 148 children with a history of wheeze were followed for 11 months (Jalaludin et al., 2004). Daily symptoms, medication u se, and doctor visits were studied. Associations were found between increased likelihood of wet cough and each 20-ppb increase in NO 2 (OR=1.13 [95% CI: 1.00, 1.26]). The authors reported that estimates did not change in multipollutant models including O 3 or PM 10 . Ward et al. (2002) examined respiratory symp toms in a panel of 162 children in the United Kingdom. No significant associations were reported for the winter period, but a significant association was reported for the summer period for cough and NO 2 (lag 0; OR=1.09 [95% CI: 1.17, 1.01]). Another Australian study includes a large number of children (n=263) at risk for developing allergy who were followed for 5 years (Rodriguez et al., 2007). Daily air pollutant concentrations, including those for NO 2 , were averaged over 10 monitoring sites in th e Perth metropolitan region. Mean level of 24- h NO 2 for the 8-year study period was 7 ppb (range 0-24 ppb). Significant associations were found between same-day level of NO 2 (both 1- and 24-h avg) and c ough (OR 1.0005 [95% CI: 1.0000, 1.0011]) per 20-ppb increase in 24-h avg NO 2 ). No multipollutant models were presented. Boezen et al. (1999) reported associations between ambient NO 2 exposure and lower respiratory symptoms among children (n=121) with bronchial hyperreactivity and elevated to tal IgE in urban and rural areas of the Netherlands. These effects were seen for all lags examined (lag 0-, 1-, 2-, and 5-day mean), with the strongest association for the 5-day mean (OR=1.75 [95% CI: 1.37, 2.22]) for each 20 ppb increase). Significant associations between lower respiratory symptoms a nd ambient exposures were seen in single-pollutant models with PM 10 , black smoke, and SO 2 . No multipollutant models were reported. For adults, most studies examining associations between ambient NO 2 pollution and respiratory symptoms have been conducted in Europe. Various studi es have enrolled older adults, (van der Zee et al., 2000); Harre et al., 1997; Silkoff et al., 2005), nonsm oking adults (Segala et al., 2004), patients with chronic obstructive pulmonary disease (COPD) (Hi ggins et al., 1995; Desqueyroux et al., 2002), and individuals with bronchial hyperresponsiveness (Bo ezen et al., 1998) or asthma (Hiltermann et al., 1998; Forsberg et al., 1998; Von Klot et al., 2002). Associations were found between NO 2 and either respiratory symptoms or inhaler use in a number of studies (van der Zee et al., 2000); Harre et al., 1997; Silkoff et al., 2005; Segala et al., 2004; Hiltermann et al., 1998), but not in all studies (Desqueyroux et al., 2002; Von Klot et al., 2002). Among the studies discussed above, odds ratios and 95% CI for associations with asthma symptoms in children are presented in Figure 3.1-6. The figur e shows the several lag periods presented in each study. In the figure, the area of the square denoting the odds ratio represents the relative weight of that estimate based on the width of the 95% CI. When combined in a random effect meta-analysis 1 , the

1 The effects used in the meta-analysis we re selected using the following methodology. One lag period per study was selected, wi th studies having 0

lag preferred to 1-day lags and moving averages; longer single-day lags were not included in the meta-analysis. If a study had both incidence and prevalence, then the incidence effect was to be used.3-26 combined OR for asthma symptoms was 1.14 (95% CI: 1.05, 1.24) and the test for heterogeneity had a p value of 0.055. The results of multipollutant anal yses for the three U.S. multicity studies are presented in Figure 3.1-7. Associations with NO 2 were generally robust to adjustment for copollutants, as stated previously. Odds ratios were ofte n unchanged with the addition of copollutants, though reductions in magnitude are apparent in certain models, such as with adjustment for SO 2 in the Six Cities study results (Schwartz et al., 1994).

Figure 3.1-6. Odds ratios (95% CI) for associat ions between asthma symptoms in children and 24-h average NO 2 concentrations (per 20 ppb). The size of the box of the central estimate represents the relative weight of that est imate based on the width of the 95% CI.



## 3.1.4.3. Summary of Short-Term Exposure on Respiratory Symptoms

Consistent evidence has been ob served for an association of respiratory effects with indoor and personal NO 2 exposures in children at levels similar to ambien t concentrations. In particular, the Pilotto et al. (2004) intervention study provided evidence of improvement in respiratory symptoms with reduced NO 2 exposure in asthmatic children. The epidemiologic studies using community ambi ent monitors also find associations between ambient NO 2 concentration and respiratory symptoms. The results of recent U.S. multicity studies (Schildcrout et al., 2006; Mortimer et al., 2002) provide further support for associations with respiratory symptoms and medication use in asthmatic children. Associations were observed in cities where the median range was 18 to 26 ppb for a 24-h avg (Schildcrout et al., 2006) and the mean NO 2 level was 32 ppb for a 4-h avg (Mortimer et al., 2002). Multipollutant models in these multicity studies were generally robust to adjustment for copollutants including O 3 , CO, and PM 10 . Most human clinical studies did not report or observe respiratory symptoms with NO 2 exposure, and animal toxicological studies do not measure effects that would be considered symptoms. The experimental evidence on airway inflammation and immune system effects discussed previously, however, provides some plausibility and coherence for the observed respiratory symptoms in epidemiologic studies.3-27 Figure 3.1-7. Odds ratios and 95% CI for associ ations between asthma symptoms and 24-h average NO 2 concentrations (per 20 ppb) fr om multipollutant models.



# 3.1.5. Effects of Short-Term Exposure on Lung Function

3.1.5.1. Epidemiologic Studies of Lung Function

Spirometry in Children
Reliable measurement of lung function in children presents special challenges. The method that produces the most accurate results is spirometry, whic h requires special equipment and trained examiners. Of the short-term exposure studies reviewed here that did use spirometry (Hoek and Brunekreef, 1994; Linn et al., 1996; Timonen et al., 2002; Moshammer et al., 2006), all conducted repeated lung function measurements in schoolchildren. All found significant associations between small decrements in lung function and increases in ambient NO 2 levels. Hoek and Brunekreef ( 1994) enrolled 1,079 children in the Netherlands to examine the effects of low-level winter air pollution on FVC, FEV 1 , maximal midexpiratory flow (MMEF), and PEF. A significant effect was found only for the PEF measure: the mean (over all subjects) slope (SE) was a reduction of 52 mL/s (95% CI: 21, 83) for a 20-ppb increase in the previous day’s NO 2 . The authors do not present mean values for lung function measurements, so it is not possible to calculate what percentage of PEF th is decrement represents. Linn et al. (1996) examined 269 Los Angeles-area schoolchildren and short-te rm air pollution exposures. The authors found statistically significant associations between previous-day 24-h avg NO 2 concentrations and FVC the next morning (mean decline of 8 mL [95% CI: 2, 14] per 20-ppb increase in NO 2 ) and current-day 24-h avg NO 2 concentrations and morning to evening changes in FEV 1 (mean decline of 8 mL [95% CI: 2, 14] per 20-ppb increase in NO 2 ). Timonen et al. (2002) enrolled 33 Finnish children with chronic respiratory3-28 symptoms to study the effects of exercise-induced lung function changes and ambient air pollution. No significant effects were observed for lung function ch anges due to exercise, but significant associations were observed for level of NO 2 lagged by 2 days and baseline FVC (mean decline of 21 mL [95% CI: - 29, -12] for 20 ppb NO 2 ) and FEV 1 (mean decline of 20 mL [95% CI: -26, -13] for 20 ppb NO 2 ). An Austrian study enrolled 163 healthy children for repeat ed lung function testing (11 to 12 tests during the school year) (Moshammer et al., 2006). A central site m onitor adjacent to the school was used to calculate 8-h avg (midnight. to 8 a.m.) PM and NO 2 concentrations. The median 8-h avg NO 2 concentration was 17.5 μg/m 3 (9.2 ppb). In both single pollutant and multipollutant models including PM 2.5 , the authors found each 20-ppb increase in NO 2 level produced reductions in lung function of around 4% for FEV 1 , FVC, forced expiratory volume in 0.5 s (FEV 0.5 ), maximal expiratory flow at 50% (MEF 50 ), and maximal expiratory flow at 25% (MEF 25 ). PM 2.5 was not significantly associated with lung function decrements in the multipollutant model.



### Peak Flow Meter Measurements in Children
Studies involving supervised lung function measu rements in schoolchildren using peak flow devices do not show a consiste nt relationship between NO 2 exposure and measurements of peak flow (Scarlett et al., 1996; Peacock et al., 2003; (Steerenberg et al., 2001). Other studies using home-use peak flow meters with children did not report any significant associations with ambient NO 2 (Roemer et al., 1998 [2,010 children in the Pollution Effects on Asthmatic Children in Europe (PEACE) study]; Roemer et al., 1999 [a subset of 1,621 children from the PEACE study with chronic respiratory symptoms]; Mortimer et al., 2002 [846 asthmatic children from the NCICAS]; Van der Zee et al., 1999 [633 children in the Netherlands]; Timonen a nd Pekkanen, 1997 [169 children includi ng asthmatics in Finland]; Ranzi et al., 2004 [118 children, some with asthma, in the It alian Asma Infantile Ricerca (AIRE) study]; Segala et al., 1998 and Just et al., 2002 [over 80 asthmatic ch ildren in Paris]; Delfino et al., 2003 [22 asthmatic children in southern California]). Ward et al. (2000) examined the effect of correcting peak flow for nonlinear errors on NO 2 effect estimates in a panel study of 147 children (9-year olds , 47% female). The correction resulted in a small increase in the group mean PEF (1.1 L-min-1). For the entire panel, NO 2 effect estimates were all corrected in the positive direction with a narrowing of the 95% CI, and all but the result for 0-day lag were decreased in absolute size by up to 73% (e.g., effect estimate for NO 2 lagged 3 days corrected from -0.56 to -0.15% per 10 ppb). When only the symp tomatic/atopic children (i.e., reported wheezing and positive skin test) were considered, the estimates for associations with 5-d avg NO 2 decreased in size from -5.0 to -1.8% per 20 ppb. In the case of lag 0, the effect estimate became significant with an increase in magnitude from -1.1 to -2.3% per 20 ppb. The authors concluded that correction for PEF meter measurements resulted in small but important shifts in the direction and size of effect estimates and probable interpretation of results. The effects of corr ection were, however, not consistent across pollutants or lags and could not be easily predicted.



### Lung Function in Adults
Spirometry was used in a large cross-sectional study in Switzerland (Schindler et al., 2001). A subset of 3,912 lifetime nonsmoking adults participated in the spirometric lung function measurements in the SAPALDIA study (Study of Air Pollution and Lung Diseases in Adults). Significant inverse relationships were found between increases in NO 2 and decreases in FVC (by 2.74% [95% CI: 0.83, 4.62]) and FEV 1 (by 2.52% [95% CI: 0.49, 4.55]) for a 20-ppb increase in NO 2 on the same day as the examination. Forced expiratory flow at 25 to 75% of FVC (FEF 25-75 ) was found to decrease by 6.73% (95% CI: 0.038, 13.31) for each 20-ppb increase in average NO 2 concentration over the previous 4 days. One study (Lagorio et al., 2006) of COPD patie nts found significant inverse relationships for FEV 1 in both COPD and asthmatic patients. Another study of COPD subjects (Silkoff et al., 2005) observed no adverse effects of ambient air pollution on lung function for the first winter; however, in the second3-29 winter, a significant decrease in morning PEF associated with same day and previous day NO 2 level was seen (quantitative results not provided). In a study of 60 asthmatic adults in London, decreases in two lung function measures, FEV 1 and FEF 25-75 , and increased FeNO were reported with increased NO 2 exposure while walking along a roadway with heavy tr affic; associations were also reported with PM 2.5 , UFP, and EC (McCreanor et al., 2007). Of the adult studies reviewed that employed portable peak flow meters for subject-measured lung function, none reported significant associations with NO 2 levels (van der Zee et al., 2000) [489 adults in the Netherlands]; Higgins et al., 1995 [153 adults in the United Kingdom, including COPD and asthma patients]; Park et al., 2005a [64 asthmatic adults in Korea]; Hiltermann et al., 1998 [60 asthmatic adults in the Netherlands]; Harre et al., 1997 [40 adults with COPD in New Zealand]; Forsberg et al., 1998 [38 adult asthmatics in Sweden]; Higgins et al., 2000 [35 adults with COPD or asthma in the United Kingdom]).



## 3.1.5.2. Clinical Studies of Lung Function

Healthy Adults
Studies examining responses of healthy volunteers to acute exposure to NO 2 have generally failed to show alterations in lung mechanics such as airway resistance (Hackney et al., 1978); Kerr et al., 1979; Linn et al., 1985a; Mohsenin, 1987a, 1988; Frampton et al., 1991; Kim et al., 1991; (Morrow et al., 1992) Rasmussen et al., 1992; Vagaggini et al., 1996; (Azadniv et al., 1998; Devlin et al., 1999). Exposures ranging from 75 min to 5 h at concentrations of up to 4.0 ppm NO 2 did not alter pulmonary function. Bylin et al. (1985) found increased airway resistance after a 20-min exposure to 0.25 ppm NO 2 and decreased airway resistance after a 20-min exposure to 0.5 ppm NO 2 , but no change in airway responsiveness to aerosolized histamine challenge in the same subjects. These effects have not been confirmed in other laboratories. Few human clinical studies of NO 2 have included elderly subjects. Morrow et al. (1992) studied the responses of 20 healthy volunteers (13 smokers, 7 nonsm okers) of mean age 61 years, following exposure to 0.3 ppm NO 2 for 4 h with light exercise. There was no significant change in lung function related to NO 2 exposure for the group as a whole. However, the 13 smokers experienced a slight decrease in FEV 1 during exposure, and their responses were significantly different from the 7 nonsmokers (percent change in FEV 1 at end of exposure: -2.25 ve rsus+1.25%, p=0.01). The post-hoc analysis and small numbers of subjects, especially in the nonsmoking group, restricts the interpretation of these findings. The human clinical studies reviewed in the O 3 AQCD (U.S. Environmental Protection Agency, 2006a) generally reported only small pulmonary f unction changes after combined exposures of NO 2 or HNO 3 with O 3 , regardless of whether the interactive effects were potentiating or additive. Hazucha et al. (1994) found that preexposure of healthy women to 0.6 ppm NO 2 for 2 h enhanced spirometric responses, and methacholine airway responsiveness induced by a subsequent 2-h exposure to 0.3 ppm O 3 , with intermittent exercise. Following a 1-h exposure with heavy exercise, Adams et al. (1987) found no differences between spirometric responses to 0.3 ppm O 3 and the combination of 0.6 ppm NO 2 +0.3 ppm O 3 . However, the increase in airway resistance was significantly less for adults exposed to 0.6 ppm NO 2 +0.3 ppm O 3 compared to 0.3 ppm O 3 alone. Gong et al. (2005) studied 6 healthy elderly subjects (mean age 68 years) and 18 patients with COPD (mean age 71 years), all exposed to: (a) air, (b) 0.4 ppm NO 2 , (c) ~200 μg/m 3 concentrated ambient fine particles (CAPs), and (d) CAPs+NO 2 . Exposures were for 2 h with exercise for 15 min of each half hour. CAPs exposure was associated with small re ductions in midexpiratory flow rates on spirometry, and reductions in oxygen saturati on, but there were no effects of NO 2 on lung function, oxygen saturation, or sputum inflammatory cells. However, the exposures were not fully randomized or blinded, and most of the NO 2 exposures took place months after completi on of the CAPs and air exposures. In addition, the small number of healthy subjects sever ely limits the statistical power for this group.3-30 

### Patients with COPD
Few studies have examined responses to NO 2 in subjects with COPD. Hackney et al. (1978) found no lung function effects of exposure to 0.3 ppm NO 2 for 4 h with intermittent exercise in smokers with symptoms and reduced FEV 1 . In a group of 22 subjects with mode rate COPD, Linn et al. (1985b) found no pulmonary effects of 1-h exposures to 0.5, 1.0, or 2.0 ppm NO 2 with 30 min of exercise. In a study by Morrow et al. (1992), 20 subjects with COPD were exposed for 4 h to 0.3 ppm NO 2 in an environmental chamber, with intermittent exer cise. Progressive decrements in FVC occurred during the exposure, becoming statistically significant only at the end of the exposure. The decrements in FVC occurred without changes in flow rates. These chang es in lung function were typical of the “restrictive” pattern seen with NO 2 rather than the obstructive chang es described by some studies of NO 2 exposure in asthmatics. As noted in the previous section, Gong et al. ( 2005) exposed 6 elderly hea lthy adults and 18 COPD patients to four separate atmospheres: (a) air, (b) 0.4 ppm NO 2 , (c) ~200 μg/m 3 CAPs, or (d) CAPs+NO 2 . Nitrogen dioxide can become absorbed to particles (Kalberer et al., 1999). This could act as a mechanism to increase NO X delivery to the peripheral lung. However, NO 2 +CAPs did not produce greater respiratory effects than for CAPs alone in either healthy or th e COPD patients. As noted above, there were also no significant effects of NO 2 alone in group of subjects.



### Patients with Asthma
Kleinman et al. (1983) evaluated the response of lightly exercising asthmatic subjects to inhalation of 0.2 ppm NO 2 for 2 h, during which resting minute ven tilation doubled. Forced expiratory flows and airway resistance were not altered by the NO 2 exposure. Bauer et al. (1986) studied the effects of mouthpiece exposure to 0.3 ppm NO 2 for 30 min (20 min at rest followed by 10 min of exercise at ~40 L/min) in 15 asthmatics. At this level, NO 2 inhalation produced significant decrements in forced expiratory flow rates after exercise, but not at rest. Jörres and Magnussen (1991) found no effects on lung function in 11 patients with mild asthma exposed to 0.25 ppm NO 2 for 30 min, including 10 min of exercise. However, small reductions in FEV 1 were observed following 1 ppm NO 2 exposure for 3 h with intermittent exercise in 12 mild asthmatics. Koenig et al. (1994) found no pulmonary function effects of exposure to 0.3 ppm NO 2 in combination with 0.12-ppm O 3 , with or without sulfuric acid (H 2 SO 4 ) (70 μg/m 3 ) or HNO 3 (0.05 ppm), in 22 adolescents with mild asthma. However, 6 additional subjects dropped out of the study citing uncomfortable respiratory symptoms. Jenkins et al. (1999) examined FEV 1 decrements and airway responsiveness to allergen in a group of mild, atopic asthmatics. The subjects were exposed during rest for 6 h to filtered air, 200 ppb NO 2 , 100 ppb O 3 , or 200 ppb NO 2 +100 ppb O 3 . The subjects were also exposed for 3 h to 400 ppb NO 2 , 200 ppb O 3 , or 400 ppb NO 2 +200 ppb O 3 to provide doses identical to those in the 6-h protocols (i.e., equal C × T). Immediately following the 3-h exposur e, but not after the 6-h exposure, there were significant decrements in FEV 1 following O 3 and NO 2 +O 3 exposures.



## 3.1.5.3. Summary of Short-Term Exposure on Lung Function

In summary, epidemiologic studies using data from supervised lung function measurements (spirometry or peak flow meters) report small d ecrements in lung function (Hoek and Brunekreef, 1994; Linn et al., 1996; Moshammer et al., 2006; Schindler et al., 2001; Peacock et al., 2003). No significant associations were reported in any studies using unsupe rvised, self-administered peak flow measurements with portable devices. Correcting peak flow measure ments for nonlinear errors resulted in small but important shifts in the direction and size of effect estimates; however, these effects were not consistent across pollutants or lags.3-31 Clinical studies have not provided compelling evidence of NO 2 effects on pulmonary function. Acute exposures of young, healthy volunteers to NO 2 at levels of as high as 4.0 ppm did not alter lung function as measured by spirometry or airway resistance. The small number of studies of COPD patients prevented any conclusions about effects on pulm onary function. The Morrow et al. (1992) study, performed in Rochester, NY, indicated restrictive type effects of 0.3 ppm NO 2 exposure for 4 h. However, three other studies, performed in southern California at similar exposure concentrations, found no effects. The contrasting findings in these studies may, in part, reflect the difference in duration of exposure or the differing levels of background ambient air pollution to which the subjects were exposed chronically; as there were much lower background levels in Rochester , NY than in southern California. For asthmatics, the effects of NO 2 on pulmonary function have also been incons istent at exposure concentrations of less than 1 ppm NO 2 . Overall, clinical studies have failed to show effects of NO 2 on pulmonary function at exposure concentrations relevant to ambient exposures. However, th e range of findings in COPD and asthmatic patients may reflect that some individuals within such groups may be particularly more susceptible to NO 2 effects than others.



# 3.1.6. Hospital Admissions and ED Visits

Total respiratory causes for ED visits and hospitali zations typically include asthma, bronchitis and emphysema (collectively referred to as COPD), upper a nd lower respiratory infections, and other minor categories. Temporal associations between ED vis its or hospital admissions for respiratory diseases and the ambient concentrations of NO 2 have been the subject of more than 50 well-conducted research publications since 1993. These studies form a new body of literature that was unavailable in 1993, when the previous criteria document was published. In add ition to considerable statistical and analytical refinements, the more recent studies have examined responses of morbidity in different age groups and multipollutant models to evaluate poten tial confounding effects of copollutants.



## 3.1.6.1. All Respiratory Outcomes

Overall, the majority of studies that have exam ined all respiratory outcomes as a single group have focused on hospital admission data. The results from th e hospitalization and ED visit studies, for all ages and stratified by age group are presented in Figures 3.1- 8 and 3.1-9. More details are provided in Annex Tables AX6.3-3, AX6.3-4, and AX6.3-5. These studies report generally positive associations between ambient NO 2 levels and ED visits and hosp italizations for all respiratory causes when participants of all ages are considered in the analyses. Stronger and more consistent associations were observed among children and older adults (65+ years) compared to adu lts (<65 years), with an interquartile range (IQR) of 1 to 13% excess risk estimated per 20 ppb incremental change in 24-h avg NO 2 or 30 ppb incremental change in 1-h max NO 2 . Peel et al. (2005) examined ED visits for a ll respiratory causes among all ages in relation to ambient NO 2 concentrations in Atlanta, GA during th e period of 1993 to 2000. They found a 2.4% (95% CI: 0.9, 4.1) increase in respiratory ED visits associated with a 30-ppb increase in 1-h max NO 2 concentrations. Tolbert et al. (2007) recently reanaly zed these data with 4 additional years of data and found similar results (2.0% increase, 95% CI: 0.5, 3.3) . Results of a copollutant model with CO and NO 2 were presented in a figure and indicated that NO 2 was a stronger predictor of respiratory disease than CO, though no quantitative results for copo llutant models were presented.3-32 Figure 3.1-8. Relative risks (95% CI) for hospital ad missions or ED visits for all respiratory disease stratified by all ages or children. Results fr om studies using 24-h average standardized to a 20-ppb increase, results from studies using 1-h max standardized to a 30-ppb increase (* indicates ED visits, all others are hospita l admissions; ^ indicates 1-h max averaging times, all others are 24-h mean averaging times).3-33 Figure 3.1-9. Relative Risks (95% CI) for hospital ad missions or ED visits for all respiratory disease stratified by adults or older adults ( ≥ 65 years). Results from studies using 24-h average standardized to a 20-ppb increase, results from studies using 1-h max standardized to a 30-ppb increase (* indicates ED visits, all others are hospital admissions; ^ indicates 1-h max averaging times, all others are 24-h mean averaging times).3-34 Figure 3.1-10. Relative risks (95% CI) for hospital ad missions or emergency department visits for all respiratory causes, standardized from two- pollutant models adjusted for particle concentration. (* indicates 1-h peak avg times, all others are 24-h avg; effect estimates from studies using 1-h peak measurements are standa rdized to a 30-ppb increase; effect estimates from studies using 24-h average measurement s are standardized to a 20-ppb increase).3-35 Figure 3.1-11. Relative risks (95% CI) for hospital ad missions or emergency department visits for all respiratory causes, standardized from two-pollu tant models adjusted for gaseous pollutant concentration. (* indicates 1-h peak averaging times, all others are 24-h average; effect estimates from studies using 1-h peak measureme nts are standardized to a 30-ppb increase; effect estimates from studies using 24-h averag e measurements are standardized to a 20-ppb increase).3-36 Figure 3.1-12. Relative Risks (95% CI ) for hospital admissions or emerge ncy department visits for asthma stratified by all ages or children. Results fr om studies using 24-h average standardized to a 20-ppb increase, results from studies using 1-h max standardized to a 30-ppb increase (* indicates ED visits, all others are hospita l admissions; ^ indicates 1-h max averaging times, all others are 24-h mean averaging times).3-37 Figure 3.1-13. Relative risks (95% CI ) for hospital admissions or emerge ncy department visits for asthma stratified by adults and older adults ( ≥ 65 years). Results from studies using 24-h average standardized to a 20-ppb increase, results from studies using 1-h max standardized to a 30- ppb increase (* indicates ED visits, all others are hospital admissions; ^ indicates 1-h max averaging times, all others are 24-h mean averaging times).

Two multicity studies combined the effects of ambient air pollution (including NO 2 ) in several cities and describe similar response rates and resp iratory health outcomes as measured by increasedhospital admissions (Barnett et al., 2005; Simpson et al., 2005a). Barnett et al. (2005) used a casecrossover method to study ambient air pollution eff ects on respiratory hospital admissions of children (age groups 0, 1 to 4, and 5 to 14 years) in multip le cities in both Australia and New Zealand during the study period 1998 to 2001. No significant associations were observed between NO 2 and increased hospital admissions for infants. For all respiratory admissions among children 1 to 4 years, a 9.6% (95% CI: 2.3, 17.3) increase was found for a 30-ppb increase in the daily 1-h max concentration of NO 2 , and for children aged 5 to14 years the same increase in NO 2 resulted in a 16.5% increase in admission for all respiratory disease (95% CI: 5.4, 28.8) both lagged 0 to 1 day (Barnett et al., 2005).3-38 In a multicity study of all hospitalizations for respiratory disease for adults ages ≥ 65 years, Simpson et al. (2005a) examined the response to a change in the daily 1-h max level of NO 2 . The standardized percent increase was 8.4% (95% CI: 4.6%, 12.4%; la g 0 to 1 day per 30-ppb increase). The authors presented results from three statistical models that pr oduced similar results overall for the four cities. Two Canadian studies compared multiple statistical methods for data analysis in studies of hospitalizations for all respiratory outcomes. In Va ncouver, Fung et al. (2006) used time-series analysis, the method of Dewanji and Moolgavkar (2000), and case-crossover analyses to examine the association of ambient NO 2 concentrations with all respiratory hospitaliza tions for adults aged 65 years and older. All three methods showed similar results, with positiv e associations between incremental changes in NO 2 of 5.43 ppb (IQR) from a mean concentration of 16.83 ppb. Using a time-series analysis, Fung et al. (2006) reported a percent increase (standardized to 20 ppb) of 6.8% ([95% CI: 1.1%, 13.1%] lag 0), while the case-crossover analysis showed a significant change in the percent increase of 10.7% ([95% CI: 3.7%, 15.5%] lag 0). The Dewanji and Moolgavkar (2000) model did not produce a statistically significant association between NO 2 and hospitalization for an increase of 20 ppb, though the central estimate remained positive (percent increase=4.5% [95% CI: -1 .1%, 10.3%] lag 0)]. In the second of these two studies, Luginaah et al. (2005) used two approaches that included both time-series and case-crossover analyses segregated by sex. They noted a positive tre nd between an incremental change in 24-h avg NO 2 of 20 ppb and respiratory admissions. Though associations for females in each of the age groups examined were positive, the authors found only one sta tistically significant association in females aged 0 to 14 years that identified an increased percent of hospitalization of 24.1% using the case-crossover analysis (24.1% [95% CI: 0.3%, 53. 8%] lag 2). The results of the time-series analyses from the Luginaah et al. (2005) and Fung et al. (2006) studies are presented in Figures 3.1-8 and 3.1-9, respectively. European studies on associations with respiratory hospitalizations were c onducted in London, Paris, and in Drammen, Norway (Ponce de Leon et al., 1996; Dab et al., 1996; Oftedal et al., 2003). Ponce de Leon et al. (1996) found significant positive relative risks for all ages and for children (0 to 14 year olds), but not for adults (15 to 64 years). Dab et al. (1996) determined that there was no statistically significant association between admissions for all respiratory cau ses combined based on an incremental change of 52.35 ppb, though the estimates were positive. Oftedal et al. (2003) reported that the relative rate of hospitalizations for all respiratory disease increased based on an increment of 20 ppb NO 2 (RR=1.111 [95% CI: 1.031, 1.19.9] lag 3 days). Other studies also found positive outcomes (Andersen et al., 2007a,b; Atkinson et al., 1999a,b; Bedeschi et al., 2007; Burnett et al., 2001; Farchi et al., 2006; Hinwood et al., 2006; Lin et al., 1999; Llorca et al., 2005; Pantazopoulou et al., 1995; Vigotti et al., 2007; Wong et al., 1999; Yang et al., 2003). Several studies presented nu ll results (Anderson et al., 2001; Gouveia and Fletcher, 2000a; Hagen et al., 2001; Schouten et al., 1996). Finally, a number of studies were considered that did not quantitatively estimate the association of NO 2 concentration on all respiratory disease hospital admissions, ED visits or clinic visits (Atkinson et al., 2001; Buchdahl et al., 1996; Burnett et al., 1997a; Chen et al., 2005; Fung et al., 2007; Linares et al., 2006; Pantazopoulou et al., 1995; Prescott et al., 1998; Villeneuve et al., 2006). These studies are included in Annex Tables AX6.3-3, AX6.3-4, and AX6.3-5. To assess potential confounding by copollutants, results from multipollutant models were evaluated. Multipollutant models may have reduced utility to distinguish the independent effects of specific pollutants if model assumptions are not met. D espite this limitation, these models are widely used in air pollution research. Figures 3.1-10 and 3.1-11 present NO 2 risk estimates for all respiratory causes with and without adjustment for various particulat e and gaseous copollutants, respectively, in twopollutant models. Collectively, copollutant regression analyses indicated that NO 2 risk estimates for respiratory ED visits and hospitaliza tions, in general, were robust to th e inclusion of additional gaseous or particulate pollutants.3-39 

## 3.1.6.2. Asthma

Studies of ED visits and hospitalizations provide suggestive evidence of an association between ambient NO 2 levels and ED visits and hospitalizations for asthma among children and adults. Figures 3.1-12 and 3.1-13 show the relative risks (and 95% conf idence limits) of hospitalizations and visits to the ED for asthma associated with daily NO 2 concentrations, for all ages and stratified by age. Larger effect estimates were generally observed for children compared to adults and older adults (65+ years), with an IQR of 1 to 25% excess risk estimated per 20 ppb incremental change in 24-h avg NO 2 or 30 ppb incremental change in 1-h max NO 2 . The few studies that examined the association of asthma and NO 2 levels among older adults (65+ y ears) generally reported positive central estimates, though none of these was statistically significant. When subjects of all ages were examined, the results of ED visits and hospitalizations were overwhelmingly positive, especi ally when the 24-h averaging time was used. The epidemiologic studies of ED and clinic visits a nd hospital admissions for asthma are summarized in Annex Tables AX6.3-3, AX6.3-4, and AX6.3-5. In Atlanta, GA, Peel et al. (2005) examined various respiratory ED visits in relation to pollutant levels from 1993 to 2000. Results for the a priori single-pollutant models examining a 3-day moving average (lag 0, 1, and 2) of NO 2 showed a small positive, but not statistically significant, association with asthma visits (percent increase=2.1% [95% CI: -0.4%, 4.5%) for all age groups. In a secondary analysis of patients ages 2 to 18 years, a 30-ppb increase in the day 5 lag of the NO 2 concentration yielded a percent increase of 4.1% (95% CI: 0.8%, 7.6%). In New York City, NY, Ito et al. (2007) examined numbers of ED visits for asthma in relation to pollution levels from 1999 to 2002. NO 2 was generally the most significant (and largest in effect size per the same distributional increment) predictor of asthma ED visits among PM 2.5 , O 3 , SO 2 , and CO (percent increase=12% [95% CI: 7%, 15%] per 20 ppb increase). Further, NO 2 ’s risk estimates were most robust to the addition of other pollutants in the model, and the addition of NO 2 reduced other pollutant’s risk estimates most consistently. A study conducted in (NY Dept of Health, 2006) found a 6% (95% CI: 1, 10) excess risk in asthma hospital admissions per 20-ppb increase in 24-h avg NO 2 for Bronx residents, but a null association for the residents of Manhattan. Jaffe et al. (2003) examined the effects of ambient pollutants during the summer months (June through August) on the daily number of ED visits for asthma among Medicaid recipients aged 5 to 34 years from 1991 to 1996 in Cincinnati and Cleveland. Th e percent change in ED visits for asthma as the primary diagnosis per 20-ppb increase in 24-h avg NO 2 concentration was 12% (95% CI: -2, 28) in Cincinnati and 8% (95% CI: -2, 16.6) in Cleveland, with an overall percent increase in ED visits of 6% (95% CI: -2, 14). Barnett et al. (2005) examined specific respiratory disease outcomes and did not find associations between incremental changes in NO 2 concentration and respiratory admissions for asthma among children 1 to 4 years old. The largest association found in th is study was a 25.7% increase in asthma admissions in the 5- to 14-year age group related to a 20-ppb increase in 24-h NO 2 , with evidence of a seasonal impact that resulted in larger increases in admissions dur ing the warm season. When the same groups were examined for the effect of a 30-ppb change in the 1-h max concentration of NO 2 , there were no significant associations between NO 2 and hospitalizations for asthma. Lin et al. (2004) studied gaseous air pollutants and 3,822 asthma hospitalizations (2,368 boys, and 1,454 girls) among children 6 to 12 years of age w ith low household income in Vancouver, Canada, between 1987 and 1998. NO 2 levels were derived from 30 monitori ng stations, and daily levels were found to be significantly and positively associated w ith asthma hospitalizations for males in the low socioeconomic group but not in the high socioeconomic group. This effect did not persist among females. Lin et al. (2003) conducted a case-crossover analysis of the effect of short-term exposure to gaseous pollution on 7,319 asthma hospitalizations (4,629 boys, 2,690 girls), in children in Toronto between 1980 and 1994. NO 2 concentrations measured from four monitori ng stations were positively associated with3-40 asthma admissions in both sexes. Differences in the r esults of these two studies might be attributed to differences in the study designs or differences in subject population sizes. A time-series analysis in Sydney examined resp iratory outcomes in children and adults, but reported no association between changes in NO 2 (24-h avg) for asthma admissions (Morgan et al., 1998a). For children aged 1 to 14, a 10.9% increase in hospita l admissions for asthma ([95% CI: 2.2, 20.3] lag 0) was associated with the daily 1-h max value based on 30-ppb incremental change. The association with adults was positive, but not statistically significant. Studies of ED visits and hospitalizations for asthm a have been reported in London, U.K. (Atkinson et al., 1999a,b; Hajat et al., 1999); Belfast, Ireland (Thompson et al., 2001); Valencia, Barcelona, and Madrid, Spain (Tenías et al., 1998; Galán et al., 2003; Castellsague et al., 1995); Turin, Italy (Migliaretti and Cavallo, 2004; Migliaretti et al., 2005); Marseille and Paris, France (Boutin-Forzano et al., 2004; Dab et al., 1996); Amsterdam and Rotterdam, the Neth erlands (Schouten et al., 1996), and Melbourne, Brisbane, and Perth, Australia (Erbas et al., 2005; Hinwood et al., 2006). Sunyer et al. (1997) have described a meta-analysis of several cities under the umbrella of the Air Pollution on Health: a European Approach (APHEA) protocol (Katsouyanni et al ., 1996). Additional studies report a positive association between NO 2 concentration and hospital admissions or ED visits (Andersen et al., 2007a; Anderson et al., 1998; Arbex et al., 2007; Burnett et al., 1999; Kim et al., 2007; Ko et al., 2007; Lee et al., 2006; Linn et al., 2000; Tsai et al. 2006; Wong et al., 2001; Yang et al., 2007). Several studies have reported null or negative associations (Andersen et al., 2007b; Ande rson et al., 1998; Chardon et al., 2007; Gouveia and Fletcher 2000a; Petroeschevsky et al., 2001; Spix et al., 1998; Tanaka et al., 1998; Tolbert et al., 2000). Copollutant and multipollutant regression analyses were performed in several of these studies. Results generally indicated that NO 2 risk estimates for respiratory ED vi sits and hospitalizations were not sensitive to the inclusion of additiona l gaseous or particulate pollutants. Finally, there were a number of studies that were considered but did quantitatively estimate the association of NO 2 concentration on asthma hospital admissions or ED or clinic visits (Atkinson et al., 2001; Bates et al., 1990; Chew et al., 1999; Garty et al., 1998; Kesten et al., 1995; Lipsett et al., 1997; Magas et al., 2007; Neidell, 2004; Pönkä, 1991; Pönkä and Vitanen 1996; Rossi et al., 1993; Stieb et al., 1996; Sun et al., 2006; Tobias et al., 1999). These studies are included in Annex Tables AX6.3-3, AX6.3-4, and AX6.3-5.



## 3.1.6.3. COPD

Relatively few studies have examined the associati on of ED visits and hos pitalizations for COPD and ambient NO 2 levels. The epidemiologic studies of ED a nd clinic visits and hospital admissions for COPD are summarized in Annex Tables AX6.3-3, AX6.3-4, and AX6.3-5. Studies examining COPD outcomes have focused on hospital admission data, in cluding multicity studies in the U.S. (Moolgavkar, 2000, 2003), Europe (Anderson et al., 1997) and Australia (Simpson et al., 2005a), and single-city studies in the U.S. (Peel et al., 2005), Canada (Yang et al ., 2005), Europe (Anderson et al., 2001; Atkinson et al., 1999a; Dab et al., 1996; Tenias et al., 2002), Australia (Morgan et al., 1998a; Hinwood et al., 2006), and Asia (Lee et al., 2007; Yang and Chen, 2007).In a time-series study in Vancouver, an area with low pollution concentrations (24-h mean NO 2 of 17.03 ppb), Yang et al. (2005) reported associations between NO 2 and hospital admissions for COPD in patients ≥ 65 years for both the lag 1 day (RR=1.19; 95% CI: 1.04, 1.37) and 7-day extended la g period (RR=1.46 [95% CI: 1.15, 1.94]). Additional studies found weaker, though statistically significant positive associations with ambient levels of NO 2 and COPD (Moolgavkar, 2003; Anderson et al., 1997; Simpson et al., 2005a). A time-series analysis in Sydney, Australia, examined respiratory outcomes in children and adults but did not show an association between changes in NO 2 (24-h average) for increased hospital admissions among COPD patients ≥ 65 years (Morgan et al., 1998a). Similarly, a study in Paris, France, of COPD and related obstructive respiratory disease found that NO 2 was not statistically significantly associ ated with increased hospital admissions (Dab et al., 1996).3-41 

## 3.1.6.4. Respiratory Diseases Other than Asthma or COPD

ED visits or hospital admissions for respirat ory diseases include upper respiratory infections (URIs), pneumonia, bronchitis, allergic rhinitis, a nd lower respiratory disease (LRD). The reviewed epidemiologic studies of clinic and ED visits a nd hospital admissions for these respiratory diseases are summarized in Annex Tables AX6.3-3, AX6.3-4, a nd AX6.3-5. Though some of these studies reported positive and statistically significant results (Atkin son et al., 1999a; Burnett et al., 1997b, 1999; Farchi et al., 2006; Gouveia and Fletcher, 2000a; Hwang and Chan, 2002; Ilabaca et al., 1999; Lin et al., 2005; Peel et al., 2005; Simpson et al., 2005a), others re ported null or negative associations (Barnett et al., 2005; Chardon et al., 2007; Hinwood et al., 2006; Karr et al., 2006; Lin et al., 1999; Pönkä and Virtanen, 1994; Zanobetti and Schwartz, 2006). Finally, there are two studies that were considered but that did not quantitatively estimate the association of NO 2 concentration on all respiratory disease hospital admissions or ED and clinical visits (Bates et al., 1990; Li nares et al., 2006). These studies are included in Annex Tables AX6.3-3, AX6.3-4, and AX6.3-5.



## 3.1.6.5. Summary of Short-Term Exposure on Respiratory ED Visits and Hospitalizations

In summary, many studies have observed positive associations between ambient NO 2 concentrations and ED visits and hospitalizations for all respiratory diseases and asthma. These associations are particularly consistent among child ren and older adults (65+ years) for hospital admissions for all respiratory diseases. For asthma hospita lization, the effect estimates were largest when children and subjects of all ages were included in the analysis. Results from copollutant models indicated that the effect of NO 2 on ED visits and hospitalizations fo r all respiratory causes and asthma were generally robust and independent of the effects of am bient particles or gaseous copollutants. In preceding sections, exposure to NO 2 has been found to result in host defense and immune system changes, airway inflammation, and airway responsiveness. While not providing specific mechanistic data linking exposure to ambient NO 2 and respiratory hospitalization or ED visits for asthma, these findings provide plausibility and coherence for such a relationship. However, the limited evidence does not suppor t a relationship between ED visits and hospitalizations for COPD and ambient NO 2 levels, and there were limite d studies providing inconsistent results for many of the health outcomes other than asthma, making it difficult to draw conclusions about the effects of NO 2 on these other diseases.



# 3.1.7. Summary and Integration—Respiratory Health Effects with Short-Term Exposure

The main body of evidence for an associa tion between respiratory morbidity and NO X exposure comes from epidemiologic studies. In addition, clini cal and animal toxicological studies provide some supporting data. Taken together, the findings of epidem iologic, human clinical, and animal toxicological studies provided evidence that is sufficient to infer a likely causal relationship for respiratory effects with short-term NO 2 exposure. The body of evidence from epidemio logic studies has grown substantially since the 1993 AQCD and provided scientific evidence that short-term exposure to NO 2 is associated with a broad range of respiratory morbidity effects, incl uding altered lung host defense, inflammation, airway hyperresponsiveness, respiratory symptoms, lung f unction decrements, and ED visits and hospital admissions for respiratory diseases. New evidence cam e from large longitudinal studies, panel studies, and time-series studies. NO 2 exposure was associated with aggravation of asthma effects that include symptoms, medication use, and lung function. Effects of NO 2 on asthma were most evident with3-42 cumulative lag of 2 to 6 days, rather than same-day levels of NO 2 . Time-series studies also demonstrated a relationship in children between hospital admissions or ED visits for asthma and NO 2 exposure. In many of these studies, there were high correlations between ambient measures of NO 2 and CO and PM; however, the effect estimates for NO 2 were robust after the inclusion of CO and PM in multipollutant models. Recent epidemiologic studies provided somewh at inconsistent evidence on short-term exposure to NO 2 and inflammatory responses in the airways, as well as for associations with lung function decrements. The epidemiologic evid ence for these effects can be charact erized as consistent, in that associations are reported in studies conducted in num erous locations with a variety of methodological approaches. While the individual risk estimates were small in magnitude, and thus not considered strong individually, the body of epidemiologic evidence had strength in that fairly precise and robust risk estimates were reported from multicity studies. Important evidence also was available from epidemiologic studies of indoor NO 2 exposures. A number of recent studies showed associations with wheeze, chest tightness, and length of symptoms (Belanger et al., 2006); respiratory symptom rates (Nitschke et al., 2006); school absences (Pilotto et al., 1997a); respiratory symptoms, likelihood of chest tightness, and asthma attacks (Smith et al., 2000); and severity of virus-induced asthma (Chauhan et al., 2003). A particular intervention study (Pilotto et al., 2004) provided strong evidence of a detrimental effect of exposure to NO 2 . Considering this large body of epidemiologic studies alone, the findings are coherent in the sense that the studies report associations with respiratory health outcomes that are logically linked together. Experimental evidence offered some coherence and plausibility for the observed epidemiologic associations. Toxicological studies have also show n that lung host defenses, including mucociliary clearance and AM and other immune cell functions, are sensitive to NO 2 exposure, with effects observed at concentrations of less than 1 ppm (see Anne x Tables AX4.3 and AX4.5). The limited evidence from human studies indicated that NO 2 may increase susceptibility to injury by subsequent viral challenge. Devlin et al. (1999) found reduced AM phagocytic capacity after NO 2 exposure, which indicated a reduced ability to clear inhaled bacteria or other in fectious agents. Frampton et al. (2002) found enhanced epithelial cell injury in response to RSV infection after NO 2 exposure. Taken together with the epidemiologic evidence described above linking NO 2 exposure with viral illnesses, there was coherent and consistent evidence that NO 2 exposure can result in lung host defense or immune system effects. This group of outcomes provided some plausibility for other respiratory system effects as well. For example, effects on ciliary action (clearance) or on macrophage function (i.e. phagocytos is, cytokine production) can lead to the type of outcomes assessed in epid emiologic studies, such as respiratory illness or symptoms. Human clinical studies provided evidence for ai rway hyperresponsiveness i.e., a heightened bronchoconstrictive response to a challenge ag ent, following short-term exposure to NO 2 . In acute exacerbations of asthma, bronchial smooth muscle cont raction (bronchoconstriction) occurs quickly to narrow the airways in response to exposure to va rious stimuli including allergens or irritants. Bronchoconstriction is the dominant physiological event leading to clinical symptoms and interference with airflow (National Heart, Lung, and Blood Institute, 2007). Recent studies involving allergen challenge in asthmatics showed that NO 2 may enhance the sensitivity to allergen-induced decrements in lung function and affect allergen-induced inflammatory responses following exposures as low as 0.26 ppm NO 2 for 30 min during rest. Nonspecific responsiveness also was increased following 30-min exposures of resting asthmatic subjects to 0.2- to 0.3-ppm NO 2 and following 1-h exposures to 0.1-ppm NO 2 . The few recent epidemiologic studies re ported associations between ambient NO 2 exposure and airway inflammation. These studies were indicative of effects in children, but offered more limited evidence for effects in adults. Human clinical studies provided consistent evidence for airway inflammation at a NO 2 concentration of 2.0 ppm (one study f ound airway inflammation at a concentration of 1.5 ppm); the onset of inflammatory responses in healthy subjects appeared to be between 100 and 200 ppm-min, i.e., 1 ppm for 2 to 3 h. Biological mark ers of inflammation were reported in antioxidant-3-43 deficient laboratory animals with exposures to 0.4 ppm NO 2 , though healthy animals did not respond until exposed to much higher levels, i.e., 5 ppm NO 2 . The biochemical effects observed in the respiratory tract following exposure to NO 2 included chemical alteration of lipids, amino acids, proteins, enzymes, and changes in oxidant/antioxidant homeostasis, with me mbrane polyunsaturated fatty acids and thiol groups as the main biochemical targets for NO 2 exposure. However, the biological implications of such alterations are unclear. Potential mechanisms for e ffects on the respiratory system included membrane damage from increases in reactive oxygen species, lipid and protein pertubations, and recruitment of inflammatory cells from epithelial cell injury by reactive oxygen species. In evaluating the potential relationships between short-term exposure to NO 2 and respiratory effects, it is important to note the interrelationships between NO 2 and other pollutants, and the potential for NO 2 to serve as a marker for a pollutant mixture, par ticularly traffic-related pollution. As outlined in the preface to this ISA, this included considerati on of potential pathways, such as the direct causal pathway for effects, mediation of effects, the polluta nt acting as a surrogate for a pollutant mixture, or confounding between pollutants. As ob served above, associations with NO 2 were often robust to adjustment for traffic-related pollutants (e.g., PM and CO), even in locations where the correlations between pollutants were substantial. The epidemiologi c evidence has thus been found to be consistent and coherent for respiratory symptoms and respiratory hosp italization and ED visits. In addition, toxicological and clinical studies reported effects of exposure to gaseous NO 2 , as discussed previously, for outcomes related to lung host defense and immune system ch anges. The experimental studies indicated that NO 2 is solely responsible for the effects reported. The findings of direct effects of NO 2 in toxicological or human clinical studies, in combination with robust associa tions reported in epidemiologic studies, supported a conclusion that NO 2 is independently responsible for some r espiratory effects. There was little available evidence to evaluate the potential for NO 2 effects to be modified by other pollutants or exposures; further, clinical and epidemiologic study findings did not app ear to support that coexposure with another pollutant is required to observe NO 2 -related effects. The evidence summarized here supports the conclu sion that there is a likely causal relationship between short-term exposure to NO 2 and effects on the respiratory system. However, the challenge remains in considering the potential for NO 2 to serve as an indicator for a mixture of combustion-related pollutants. Most studies examined showed that personal NO 2 exposures were significantly correlated either with ambient or personal level PM 2.5 , or other combustion-generate d products (e.g., CO and EC). As discussed in Chapter 2, ambient NO 2 measurements can provide a valid estimate of personal exposure to ambient NO 2 as used in most epidemiology studies. Although the evidence indicated that NO 2 exposure is independently associated with some respiratory h ealth effects, there remains the possibility that NO 2 also serves as a marker for combustion-related emissi ons, particularly from traffic, for some health outcomes. Although this complicates efforts to disentangle specific NO 2 -related health effects, the evidence indicates that NO 2 associations generally remain robust in multipollutant models and supports a direct effect of short-term NO 2 exposure on respiratory morbidity at current ambient concentrations.



# 3.2. Cardiovascular Effects Related to Short-Term Exposure

This ISA includes approximately 40 studies published since 1993 characterizing the effect of shortterm NO X exposure on hospitalizations or ED visits for CVD. These studies form a new body of literature that was unavailable in 1993, when the previous AQCD was published.



# 3.2.1. Heart Rate Variability

Heart rate variability (HRV), a measure of the beat-to- beat change in heart rate, is a reflection of the overall autonomic control of the heart. It is hypoth esized that increased air pollution levels may stimulate3-44 the autonomic nervous system and lead to an imba lance of cardiac autonomic control characterized by sympathetic activation unopposed by parasympathetic control (Liao et al., 2004; Brook et al., 2004). Such an imbalance of cardiac autonomic control may pr edispose susceptible people to greater risk of ventricular arrhythmias and consequent cardiac d eaths (Liao et al., 2004; Brook et al., 2004). Findings from studies of ambient NO 2 and HRV were mixed with some studies reporting an adverse effect (reduction in variability) (Liao et al., 2004; Chan et al., 2005; Wheeler et al., 2006), while other studies reported no significant change (Luttman-Gibson et al ., 2006; Holguin et al., 2003; Schwartz et al. 2005). In some studies reporting reductions in HRV, reducti ons for PM were similar to those observed for NO 2 (Liao et al., 2004; Wheeler et al. 2006). See Annex Table AX6.3-10 for a detailed discussion of HRV studies.



# 3.2.2. Arrhythmias Recorded on Implanted Defibrillators

Results from studies directly measuring ventricular arrhythmias were inconsistent and potentially confounded by PM (Peters et al., 2000; Dockery et al., 2005; Rich et al., 2005, 2006a; Metzger et al,. 2007). Among the ambient air pollutants, the strongest association with arrhythmias was observed for PM, which was highly correlated to NO 2 concentrations in these studies (Dockery et al., 2005; Rich et al., 2005; Metzger et al., 2007). Rich et al. (2006b) did not observe an association between NO 2 level and paroxysmal atrial fibrillation (PAF). See Annex Ta ble AX6.3-11 for detailed discussion of defibrillator studies.



# 3.2.3. Repolarization Changes

In addition to the role played by the autonom ic nervous system in arrhythmogenic conditions, myocardial vulnerability and repolarization abnormaliti es are believed to be key factors contributing to the mechanism of such diseases. Henneberger et al. (2005) reported that NO 2 and NO were not associated with repolarization abnormalities.



# 3.2.4. Markers of Cardiovascular Disease Risk

Several investigators have explored potential m echanisms by which air pollution could cause CVD. In particular, markers of inflammation, cell adhesion, coagulation, and thrombosis have been evaluated in epidemiologic studies. Pekkanen et al. (2000) reported a significant increase in fibrinogen associated with short-term NO 2 exposure while Steinvil et al. (2007) reported significant decreases in fibrinogen associated with NO 2 . Schwartz (2001) reported increases in fibri nogen and platelet count associated with NO 2 level in single-pollutant models , which changed direction in multi pollutant models also containing PM 10 . Liao et al. (2005) did not observe differences in white blood cell (WBC) count, Factor VIII-C, fibrinogen, von Willibrand Factor (VWF), or albumin associated with 24-h avg NO 2 levels. However, PM 10 was associated with factor VIII-C in the c ohort examined. Ruckerl et al. (2006) observed a significant association of NO 2 (lagged 2-6 days) with C-reactive protein (CRP) greater than the 90th percentile but the strongest effect on CRP was ob served for UFP. Baccarelli et al. (2007) reported a shorter prothrombin time (PT) with increasing NO 2 levels but, a similar decrease in PT was observed for PM 10 . Collectively, associations reported for NO 2 and markers of cardiovascular risk in epidemiologic studies appeared to be potentially confounded by PM a nd other traffic-related po llutants. Several authors proposed that these biomarker studies provide evidence fo r biological plausibility of the effect of PM on cardiovascular health rather than NO 2 (Schwartz 2001; Seaton and Dennekamp, 2003). A few human clinical studies which indicated effects of NO 2 exposure on cardiac output, blood pressure, and circulating red blood cells at concentra tions of less than 2.0 ppm (Drechsler-Parks, 1995;3-45 Linn et al., 1985a; Posin et al., 1978; (Frampton et al., 2002) require confirmation. Drechsler-Parks (1995) observed a lower mean stroke volume for NO 2 +O 3 than for air and speculated that chemical interactions between O 3 and NO 2 at the level of the epithelial lining fluid led to the production of nitrite, leading to vasodilatation, with reduced cardiac pr eload and cardiac output. Linn et al. (1985a) reported small but statistically significant reductions in blood pressure after exposure to 4 ppm NO 2 for 75 min, a finding consistent with systemic vasodilatation in response to the exposure; this finding has not been repeated. Frampton et al. (2002) reported a concentr ation-related reduction in hematocrit and hemoglobin in both males and females, among health subjects exposed to NO 2 , confirming the findings of an earlier study conducted by Posin et al. (1978). See Annex AX5 for a detailed discussion of these studies. The results on the effect of NO 2 on various hematological parameters in animals were inconsistent and, thus, provided little biological plausibility for the epidemiology findings. There have also been reported changes in the red blood cell membranes of experimental animals following NO 2 exposure. Red blood cell D-2,3-diphosphoglycerate was reportedly in creased in guinea pigs following exposure to 0.36 ppm NO 2 for 1 week (Mersch et al., 1973). An increase in red blood cell sialic acid, indicative of a younger population of red blood cells, was re ported in rats exposed to 4.0 ppm NO 2 continuously for 1 to 10 days (Kunimoto et al., 1984). However, in anothe r study, exposure to the same concentration of NO 2 resulted in a decrease in red blood cell number (Moc hitate and Miura, 1984). A more recent study (Takano et al., 2004) using an obese rat strain found changes in blood triglycerides, high-density lipoprotein cholesterol (HDL), and HDL/total cholest erol ratios with a 24-week exposure to 0.16 ppm NO 2 . In the only study conducted with an exposure of less than 5 ppm NO 2 that evaluated methemoglobin formation, Nakajima and Kusumoto (1968) reported that, in mice exposed to 0.8 ppm NO 2 for 5 days, the amount of methemoglobin was not increased. This is in c ontrast to some (but not all) in vitro and highconcentration NO 2 in vivo studies, which have found methemoglobin effects (U.S. Environmental Protection Agency, 1993).



# 3.2.5. Toxicology of Inhaled Nitric Oxide

Nitric oxide is used in humans therapeutically as a pulmonary vasodilator, and has shown little evidence for adverse respiratory effects. The literatu re on therapeutic uses of nitric oxide provides the strongest evidence for its lack of toxicity. Infants a nd adults with acute respiratory failure and refractory hypoxemia, as well as pulmonary hypertension, are sometimes considered candidates for inhaled NO. Inhaled NO acts as a selective pulmonary vasodilato r, causing vascular smooth muscle relaxation and increased perfusion in ventilated lung regions. Benefici al effects in patients with respiratory failure include reduced pulmonary artery pressures and impr oved ventilation-perfusion matc hing. Nitric oxide is used clinically at concentrations ranging from 5 ppm to as high as 80 ppm. There has been little or no toxicity reported, even when used in premature in fants with respiratory failure. In a recently published multicenter study (Kinsella et al., 2006), 793 premature infants with respiratory failure were randomized to therapy with inhaled NO or air. NO therapy was associ ated with a reduced risk of brain injury, and in a reduced risk of bronchopulmonary dysplasia, a chronic lung condition resulting from lung injury in infancy, in infants weighing at least 1000 gm. NO can cause methemoglobinemia, and this was seen transiently in only 2 infants. NO can inhibit activation of blood leukocytes and platelets (Gianetti et al. 2002); however there was no evidence for increased suscep tibility to infection or bleeding. One of the concerns about NO therapy is the potential for NO to be oxidized to NO 2 , so administration systems are designed to avoid this.



# 3.2.6. Hospital Admissions and ED Visits for CVD

Cases of CVD are typically identified using ICD c odes, which were recorded on hospital discharge records in these studies. However, counts of hospita l or ED admissions were used in some studies. Studies of ED visits may include cases that are l ess severe than those included in hospital admission3-46 studies. Hospital admission studies are distinguished from ED visit studies in Annex Tables AX6.3-6 through AX6.3-9. Many studies grouped all CVD diagnoses (ICD9 codes 390–459), evaluating cardiac diseases (ICD9 codes 390–429), and cerebrovascular disease (ICD9 430–448) together. Other studies evaluated cardiac and cerebrovascular diseases separately or further distinguished ischemic heart disease (IHD: ICD9 410–414), myocardial infarction (MI: ICD9 410), congestive heart failure (CHF: ICD9 428), cardiac arrhythmia (ICD9 427), angina pector is (ICD9 413), or stroke (ICD9 430-438). Numerous studies have shown a positive associ ation between both 24-h avg and 1-h max NO 2 levels and hospital admissions or ED visits for all CVD, in single-pollutant models (Linn et al., 2000; Metzger et al., 2004; Tolbert et al., 2007; Ballester et al., 2001, 2006; Anderson et al., 2007a; Atkinson et al., 1999a,b; Poloniecki et al., 1997; Barnett et al., 2006; Hinwood et al., 2006; Jalaludin et al., 2006; Chang et al., 2005; Wong et al., 1999; Yang et al., 2004b). A discussion of results from studies reporting associations between NO 2 and all CVD are found in Annex section AX6.2.1.



# 3.2.7. Cardiac Disease

Findings from studies examining the association of NO 2 with cardiac disease are found in Figure 3.2-1. Most investigators who distinguished cardiac disease from all CVD reported significant positive associations in single-pollutant models. Increased ri sks were observed in Canadian populations (Burnett et al., 1997b; Fung et al., 2005). The average daily 1-h max NO 2 level was approximately 39 ppb in metropolitan Toronto, ON, where these studies were conducted. Estimates from two Australian multicity studies (Barnett et al., 2006; Simpson et al., 2005a) were also significantly increased. The 24-h NO 2 level in the Australian cities studied by Barnett et al . (2006) was 7 to 11.5 ppb. The range of 1-h max NO 2 level in cities studied by Simpson et al. (2005a) was 16 to 24 ppb. Von Klot et al. (2005) observed a statistically significant association between r eadmission for cardiac disease among MI survivors, a potentially susceptible subpopulation and NO 2 concentrations in five European cities. The range in 24-h NO 2 level was 15.8 to 26 ppb in the five cities studied . Two single-city Australian studies and one singlecity Taiwanese study also reported positive single-pollu tant model results (Jalaludin et al., 2006; Morgan et al., 1998a; Chang et al., 2005). Studies of the association of 24-h avg and 1-h max NO 2 level with IHD, MI, CHF and arrhythmia are less consistently positive and significant. Results from these studies are described in Annex section AX6.2-1. Most investigators reporting results from multipollutant models observed diminished effect estimates for NO 2 and hospital admissions or ED visits for CVDs. In two U.S. studies conducted in Los Angeles, investigators indicated that their anal yses were unable to distinguish the effects of NO 2 from PM, CO, and other traffic pollutants (Linn et al., 2000; Mann et al., 2002). In both studies, CO was more highly correlated with NO 2 than PM. In an Atlanta study, Metzger et al. (2004) and Tolbert et al. (2007) also observed a diminished effect of NO 2 on visits for CVD when CO was modeled with NO 2 , while the effect of CO remained robust. Tolbert et al. (2007) discussed the limitations of multipollutant models and concluded that these models might help researchers id entify the strongest predictor of disease, but might not isolate the independent effect of each pollutant. NO 2 was not robust to adjustment for other pollutants in several non-U.S. studies (Jalaludin et al., 2006; Ballester et al., 2006; Simpson et al., 2005a; Poloniecki et al., 1997; Barnett et al., 2006; Llorca et al., 2005). However, in other studies, investigators reported that the effect of NO 2 was robust in multipollutant models (Von Kl ot et al., 2005; Yang et al., 2004b; Chang et al., 2005; Morgan et al., 1998a; Burnett et al., 1997a , 1999). See Annex section AX6.2.1.6 for a detailed description of results from multipollutant models.3-47 Figure 3.2-1. Relative risks (95% CI) for associations of 24-h NO 2 (per 20 ppb) and daily 1-h max* NO 2 (per 30 ppb) with hospitalizations or emergency de partment visits for cardiac diseases. Primary author and year of publication, city, stratificat ion variable(s), and lag are listed. Results for lags 0 or 1 are presented as available.



# 3.2.8. Hospital Admissions for Stroke and Cerebrovascular Disease

Studies of the association between all cerebrovascular disease and ambient NO 2 concentration are summarized in Figure 3.2-2. Results from these studies we re generally inconsistent . Metzger et al. (2004) reported a significant increase in cerebrovascular disease emer gency visits in Atlanta. However, Peel et al. (2007) did not find associations between cerebrovascular disease visits and NO 2 concentrations among those with hypertension and diabetes in the same city. The daily 1-h max NO 2 level in Atlanta during the study period ranged from 26 to 45.9 ppb (Metzger et al., 2004; Peel et al., 2007). Ballester et al. (2001) reported a relatively large increased risk in cerebrovascu lar admissions in the Spanish city of Valencia at lag 4, while Poloniecki et al. (1997) and Pönkä a nd Virtanen (1996) did not observe associations in London and Helsinki. Two Asian studies report positive but nonsignificant associations of cerebrovascular disease with 24-h avg NO 2 (Chan et al., 2006; Wong et al., 1999). The 24-h avg NO 2 levels reported for Taipei and Hong Kong were approximately 30 ppb and 27 ppb, respectively (Chan et al., 2006; Wong et al., 1999).3-48 Figure 3.2-2. Relative risks (95% CI) for associations of 24-h NO 2 (per 20 ppb) and daily 1-h max NO 2 * (per 30 ppb) with hospitalizations for all cerebro vascular disease. Primary author and year of publication, city, stratification variable(s), and lag are listed. Results for lags 0 or 1 are presented as available.

Studies of hospital admissions or ED visits for specific cerebrovascular diseases provided little evidence for a NO 2 effect. In a large study, conducted in metropolitan Los Angeles where the mean 24-h NO 2 level ranged from 28 to 41 ppb depending on th e season, no association was observed for all cerebrovascular disease (Linn et al., 2000). However, au thors reported an increase in hospitalizations of 4.0% (95% CI: 2.0, 6.0) for occlusive stroke per 20 ppb increase in NO 2 . Wellenius et al. (2005) found a 5% increase in ischemic stroke (IS) admissions per 20-ppb increase in 24-h avg NO 2 level. A study of all-stroke in On tario reported null findings for 24-h avg NO 2 at lags 0 and 1 (Ito et al. 2004). Villeneuve et al. (2006) reported an association between NO 2 exposure and IS during the winter months among the elderly (OR= 1.41 [95% CI: 1.13, 1.75], per 20 ppb, lag 3 day average). Villeneuve et al. (2006) also reported pos itive but nonsignificant associations for hemorrhagic stroke (HS) (OR=1.25 95% CI: 0.91, 1.71 per 20-ppb increase in NO 2 ). No associations between air pollutants and stroke were reported in a multicity st udy conducted in Australia and New Zealand (Barnett et al., 2006). An increase in 24-h avg NO 2 resulted in increased risk of hospitalization for primary intracerebral hemorrhage (PIH) (OR: 1.68 [95% CI : 1.39, 2.04] lag 0 to 2 per 20 ppb increase), and ischemic stroke (IS) (OR: 1.67 95% CI: 1.49 1.88, lag 0-2) during the warm season in Taiwan (Tsai et al., 2003). Several investigators presented estimates for the association of NO 2 with cerebrovascular outcomes from multipollutant models. The association of NO 2 with stroke was not robust to adjustment for CO in a3-49 Canadian study (Villeneuve et al., 2006). Although results from a Taiwanese study indicated the effect of NO 2 on stroke admissions was robust in two-pollutant models, the authors noted that the association of NO 2 with stroke might not be causal if NO 2 is a surrogate for other components of the air pollution mixture (Tsai et al., 2003).


# Summary of Cardiovascular Effects Related to Short-Term Exposure

The available evidence on the effect of short-term exposure to NO 2 on cardiovascular health effects was inadequate to infer the presence or absence of a causal relationship at this time. Evidence from epidemiologic studies of HRV, repolarization chang es, and cardiac rhythm disorders among heart patients with implanted cardioverter defibrilators are inconsis tent. In most studies, observed associations with PM were similar or stronger than associations with NO 2 . Generally positive associations between ambient NO 2 concentrations and hospital admissions or ED vis its for CVD have been reported in single-pollutant models; however, most of the effect estimates were di minished in multipollutant models also containing CO and PM indices. Mechanistic evidence of a role for NO 2 in the development of CVDs from studies of biomarkers of inflammation, cell adhesion, coagulati on, and thrombosis was lacking. Furthermore, the effects of NO 2 on various hematological parameters in anim als are inconsistent and, thus, provide little biological plausibility for effects of NO 2 on the cardiovascular system. However, there was limited evidence from human clinical studies which showed a reduction in hemoglobin with NO 2 exposure at concentrations of 1.0 to 2.0 ppm (with 3 h exposures) that requires confirmation.



# 3.3. Mortality Related to Short-Term Exposure

There was no epidemiologic study reviewed in th e 1993 AQCD that examined the mortality effects of ambient NO 2 . Since the 1993 AQCD, a number of studies, mostly using time-series analyses, reported short-term mortality risk estimates for NO 2 (see Annex Table AX6.3-19). However, since most of these studies’ original focus or hypothesis was on PM, a quantitative interpretation of the NO 2 mortality risk estimates requires caution. Risk estimates were summarized across studies after reviewing individual multicity studies.



# 3.3.1. Multicity Studies and Meta-Analyses

In reviewing the range of mortality risk estimates, multicity studies provided the most useful information because they analyzed multiple cities data in a consistent method, avoiding potential publication bias. Risk estimates from multicity studies usua lly are reported for consistent lag days, further reducing potential bias caused by choosing the “best” la g in individual studies. There have been several multicity studies from the U.S., Canada, and Europe . Meta-analysis studies also provided useful information on describing heterogeneity of risk estimates across studies, but unlike multicity studies, the heterogeneity of risk estimates seen in meta-analysis may also reflect the variation in analytical approaches across studies. Thus, we focused our revi ew mainly on the results from multicity studies, and effect estimates from these studies were summarized. Discussion focused on the studies that were not affected by generalized additive models (GAMs) w ith convergence issues (Dominici et al., 2002; Ramsay et al., 2003) unless otherwise noted when the studies raised relevant issues.3-50 

## 3.3.1.1. National Morbidity, Mortality, and Air Pollution Study (NMMAPS)

The time-series analysis of the largest 90 U.S. citi es (Samet et al., 2000; reanalysis Dominici et al., 2003) in the National Morbidity, Mortality, and Air Pollution Study (NMMAPS) was by far the largest multicity study conducted to date to investigate the mortality effects of air pollution, but its primary interest was PM (i.e., PM 10 ), and NO 2 was not measured in 32 of the 90 cities. This study’s model adjustment for weather effects employed more te rms than other time-series studies in the literature, showing that the model adjusted for potential confounde rs more aggressively than the models in other studies. PM 10 and O 3 (in summer) appeared to be more strongly associated with mortality than the other gaseous pollutants. Regarding NO 2 , SO 2 , and CO, the authors stated, “The results did not indicate associations of these pollutants with total mortality.” PM 10 , NO 2 , SO 2 , and CO showed the strongest association at lag 1 day (for O 3 , it was lag 0 day), and the addition of other copollutants in the model at lag 1 day hardly affected the mortality risk estimates for PM 10 or the gaseous pollutants. Figure 3.3-1 shows the total mortality risk estimates for NO 2 from Dominici et al. (2003). The NO 2 risk estimates in the multipollutant models were about the same or larger. Thus, these results do not indicate that the NO 2 -mortality association was confounded by PM 10 or other pollutants (and vice versa).

Source: Dominici et al. (2003).
Figure 3.3-1. Posterior means and 95% posterior intervals of national average estimates for NO 2 effects on total mortality from nonexternal causes at lags 0, 1, and 2 within sets of the 90 cities with pollutant data available. Models A=NO 2 alone; B=NO 2 +PM 10 ; C=NO 2 +PM 10 +O 3 ; D=NO 2 +PM 10 +SO 2 ; E=SO 2 +PM 10 +CO.



## 3.3.1.2. Canadian Multicity Studies

There have been four Canadian multicity studi es conducted by the same group of investigators (Burnett et al., 1998, 2000, 2004; Brook et al., 2007). Th is section focuses on Burnett et al. (2004) and Brook et al. (2007), as these studies are most extensive bot h in terms of the length and coverage of cities. Total (nonaccidental), cardiovascular, and respiratory mortality were analyzed in the Burnett et al. (2004) study of 12 Canadian cities from 1981 to 1999. Daily 24-h avg as well as 1-h max values were analyzed for all the gaseous pollutants and coefficient of haze (CoH). For PM 2.5 , coarse PM (PM 10-2.5 ), PM 10 , CoH, SO 2 , and CO, the strongest mortality association was found at lag 1, whereas for NO 2 , it was3-51 the 3-day moving average (i.e., average of 0-, 1-, and 2-day lags), and for O 3 , it was the 2-day moving average. Of the single-day lag estimates for NO 2 , Lag 1 day showed the strongest associations, whic h was consistent with the NMMAPS result, but its risk estimate was more than 4 times larger th an that for the NMMAPS study. The 24-h avg values showed stronger associations than the 1-h max valu es for all the gaseous pollutants and CoH except for O 3 . The pooled NO 2 mortality risk estimate in a single-pollutant model (for all available days) was 2.0% (95% CI: 1.1, 2.9) per 20-ppb increase in the 3-day moving average of NO 2 . The magnitudes of the effect estimates were similar for total, cardiovascular, and respiratory mortality. Larger risk estimates were observed for warmer months. NO 2 was most strongly correlated with CoH (r=0.60), followed by PM 2.5 (r=0.48). The NO 2 -mortality association was not sensitive to adjustment for these or any of other pollutants in the two-pollutant models. However, Burn ett et al. (2004) noted that simultaneous inclusion of daily PM 2.5 data (available for 1998 and 2000; sample size comparable to the main analysis [every 6th day from 1981 to 1999]) and NO 2 in the model resulted in a considerable reduction of the NO 2 risk estimates. Authors discussed that reducing combustion would result in public health benefits because NO 2 or its products originate from combustion sources, but cautioned that they could not implicate NO 2 as a specific causal pollutant. Brook et al. (2007) further examined data from 10 Canadian cities with a special focus on NO 2 and the role of other traffic-related air pollutants. Again, NO 2 showed the strongest associations with mortality among the pollutants examined including NO, and none of the other pollutants substantially reduced NO 2 risk estimates in multipollutant models. The analysis al so confirmed the Burnett et al. (2004) study results that NO 2 risk estimate was larger in the warm season. Generally, NO was more strongly correlated with the primary VOCs (e.g., benzene, toluene, xylenes) than NO 2 or PM 2.5 . NO 2 was more strongly correlated with the organic compounds than it was with the PM mass indices or trace metals in PM 2.5 . Brook et al. (2007) concluded that the strong NO 2 effects seen in Canadian cities could be a result of it being the best indicator, among the pollutants monitored, of fresh combustion as well as photochemically processed urban air. In summarizing the Canadian multicity studies, NO 2 was most consistently associated with mortality among the air pollutants examined, especially in the warm season. Adjustments for PM indices and its components generally did not reduce NO 2 risk estimates. NO 2 also was shown to be associated with volatile organic compounds that are indicative of combustion products (traffic-related air pollution) and photochemical reactions.



## 3.3.1.3. Air Pollution and Health: A European Approach (APHEA) Studies

The APHEA project was a European multicity effo rt, which analyzed data from multiple studies using a standardized methodology. This section focuses on the more recent APHEA2 studies which included 29 European cities. Samoli et al. (2006) analyzed 29 APHEA2 cities to estimate NO 2 associations for total, cardiovascular, and respiratory deaths. The average of la gs 0-1 days was chosen a priori to avoid potential bias with the “best” lag approach. In addition, the association of total mortality with NO 2 over 6 days (lags 0-5) were summarized over all cities using a c ubic polynomial distributed lag model. Results from this model showed multiday effects, with the st rongest association shown at lag 1 day, which was consistent with the results from NMMAPS and Canadian multicity studies. The risk estimates for total, cardiovascular, and respiratory causes were comparable . In the two-pollutant models with black smoke, PM 10 , SO 2 , and O 3 , the risk estimates for total and cardiovascular mortality were not affected. The second-stage analysis examined possible effect modi fiers. For total and cardiovascular mortality, the geographical area (defined as western, southern, a nd central eastern European cities) was the most important effect modifier (estimates were lower in eastern cities), followed by smoking prevalence (NO 2 risk estimates were higher in cities with a lower pr evalence of smoking). The authors concluded that the3-52 results showed effects of NO 2 on mortality, but that the role of NO 2 as a surrogate of other unmeasured pollutants could not be completely ruled out. In an earlier study, Katsouyanni et al. (2001; reanalysis, 2003) analyzed data from 29 European cities and reported risk estimates for PM 10 and not for NO 2 , but found that the cities with higher NO 2 levels tended to have larger PM 10 risk estimates. Furthermore, simultaneous inclusion of PM 10 and NO 2 reduced the PM 10 risk estimate by half. An analysis of the elderly mortality in 28 of the same cities (Aga et al., 2003) also found a similar effect modification of PM by NO 2 . Thus, PM and NO 2 risk estimates in these European cities may be reflecting the health e ffects of the same air pollution source and/or act as effect modifiers of each other.



## 3.3.1.4. The Netherlands Study

While the Netherlands studies for the 1986 to 1994 data (Hoek et al., 2000, 2001; reanalysis in Hoek, 2003) are not multicity studies and the Netherlands data were also analyzed as part of APHEA2 (Samoli et al., 2006), the results from the reanal ysis (Hoek, 2003) are discussed here, because the database comes from a large population (14.8 million for the entire country) and a more extensive analysis was conducted than in the multicity studies. PM 10 , black smoke, O 3 , NO 2 , SO 2 , CO, sulfate (SO 4 2– ), and nitrate (NO 3 – ) were analyzed at lags 0, 1, and 2 days and the average of lags 0-6 days. All the pollutants were associated with total mortality, and for single-day models, lag 1 day showed strongest associations for all the pollutants. NO 2 was most highly correlated with black smoke (r=0.87), and the simultaneous inclusion of NO 2 and black smoke reduced both pollutants’ risk estimates (the NO 2 estimate was reduced by more than 50%). PM 10 was less correlated with NO 2 (r=0.62), and the simultaneous inclusion of these pollutants r esulted in an increase in the NO 2 risk estimate.



## 3.3.1.5. Other Multicity Studies

Other European multicity studies, conducted in ei ght Italian cities (Biggeri et al., 2005), nine French cities (Le Tertre et al., 2002) and seven Sp anish cities (Saez et al., 2002) provide evidence for a short-term NO 2 effect on mortality. An additional multicity study was conducted in Australian cities (Simpson et al., 2005b). The studies by Biggeri et al. (2005) and Simpson et al. (2005b) are summarized in this section. The studies by Le Tertre et al . (2002) and Saez et al. (2002), conducted using GAM methods with the default convergence setting, are presented in Annex Table AX6.3-19. Biggeri et al. (2005) analyzed eight Italian cities (Turin, Milan, Verona, Ravenna, Bologna, Florence, Rome, and Palermo) from 1990 to 1999. Only single-pollutant models were examined in this study. Statistically significant positive associations were observed between NO 2 and total, cardiovascular, and respiratory mortality, with the largest effect es timate observed for respiratory mortality. Since all the pollutants showed positive association and the correla tions among the pollutants were not presented, it was not clear how much of the observed associations are shared or confounded. The mortality risk estimates were not heterogeneous across c ities for all the gaseous pollutants. Simpson et al. (2005b) analyzed data from four Au stralian cities (Brisbane, Melbourne, Perth, and Sydney) using methods similar to the APHEA2 appro ach. They also examined sensitivity of results to alternative regression models. Associ ations between mortality and NO 2 , O 3 , and nephelometer readings (a measure of PM) were examined at single-day lag 0, 1, 2, and 3 days and using the average of 0- and 1-day lags. Among the three pollutants, correlation was strongest between NO 2 and nephelometer readings, ranging from (r ~0.62 among the four cities). Of the three pollutants, NO 2 showed the largest mortality risk estimates per interquartile range. Similar to the study by Biggeri et al. (2005), the strongest association was observed between NO 2 and respiratory mortality, compared to total or cardiovascular mortality. The three alternative regression models yielded similar results. The NO 2 risk estimates were not3-53 sensitive to the addition of nephelometer readings in the two-pollutant models for total mortality, but the nephelometer risk estimate was greatly reduced in the model with NO 2 .



## 3.3.1.6. Meta-Analyses of NO 2 

## Mortality Studies

Stieb et al. (2002) reviewed time-series mort ality studies published between 1985 and 2000, and conducted a meta-analysis to estimate combined effects for each of PM 10 , CO, NO 2 , O 3 , and SO 2 . Since many of the studies reviewed in that analysis were affected by the GAM convergence issue, Stieb et al. (2003) updated the estimates by separating the GAM versus non-GAM studies and by single- versus multipollutant models. There were more GAM estim ates than non-GAM estimates for all the pollutants except SO 2 . For NO 2 , there were 11 estimates from single-pollutant models and only 3 estimates from multipollutant models. The lags and multiday averag ing used in these estimates varied. The combined estimate for total mortality was 0.8% (95% CI: 0.2, 1.5) per 20-ppb increase in the daily average NO 2 from the single-pollutant models and 0.4% (95% CI : -0.2, 1.1) per 20-ppb increase in the 24-h average from the multipollutant models. Note that, although the estimate from the multipollutant models was smaller than that from the single-pollutant models, th e number of the studies for the multipollutant models was small (3), also, the data extraction procedure of this meta-analysis for the multipollutant models was to extract from each study the multipollutant model that resulted in the greatest reduction in risk estimate compared with that observed in single-pollutant mode ls. It should be noted that all the multicity studies whose combined estimates have been discussed above were published after this meta-analysis.



# 3.3.2. Summary of Mortality Related to Short-Term Exposure

The epidemiologic evidence on the effect of short-term exposure to NO 2 on total nonaccidental and cardiopulmonary mortality was suggestive but not sufficient to infer a causal relationship. The epidemiologic studies were generally consistent in reporting positive associations. However, there was little evidence available to evaluate coherence and pl ausibility for the observed associations, particularly for cardiovascular and total mortality. In the short-term exposure studies, the range of NO 2 total mortality risk estimates is 0.5 to 3.6% per 20-ppb increase in the 24-h average NO 2 or 30-ppb increase in daily 1-h max (Figure 3.3-2). The use of various lag periods, averaging days, a nd distributed lags did not appear to alter the estimates substantially. The heterogeneity of estimates in these studies may be due to several factors, including the differences in (1) model specification, (2) NO 2 levels, and (3) effect modifying factors. Interestingly, the Canadian 12- city study showed combined risk estimates (average of 0-1 day or single 1-day lag) about 4 times larger than that for the U.S. estimate, despite the fact that the range of Canadian NO 2 concentrations (10 to 26 ppb) was somewhat lower than that for the U.S. data (9 to 39 ppb for the 10%-trimmed data). In fact, the NMMAPS estimate is the smallest among the multicity studies, a pattern appearing in PM 10 mortality risk estimates (U.S. Environmental Protection Agency, 2004). T hus, it is possible that this may be due to the difference in model specifications.Several multicity studies provided risk estimates for broad cause-specific categories (typically allcause, cardiovascular, and respiratory) using consis tent lags/averaging for broad causes (cardiovascular and respiratory), but the patterns were not always cons istent. This inconsistency was likely due to smaller sample size, or the lags reported not being consiste nt across the specific causes examined (Figure 3.3-3). While the smaller multicity studies (the Italian and Au stralian studies) reported larger risk estimates for respiratory mortality, the larger Canadian and AP HEA2 studies reported comparable risk estimates among the broad specific causes of deaths. In addition, sin ce other pollutants also showed similar associations with these causes or categories, it is difficult to discuss consistency with causal inference that is specific to NO 2 . The multipollutant models in these studies generally did not alter NO 2 risk estimates, except for the Netherlands study in which NO 2 was highly correlated with the copollutant black smoke. While the3-54 multipollutant results generally indicated a lack of confounding, it was difficult to attribute the observed excess mortality risk estimates to NO 2 alone.

Figure 3.3-2. Combined NO 2 mortality risk estimates from multic ity and meta-analysis studies. Risk estimates are computed per 20-ppb increase for 24-h average or 30-ppb increase for 1-h daily max NO 2 concentrations. For multipollu tant models, results from th e models that resulted in the greatest reduction in NO 2 risk estimates are shown.

While the multicity studies examining the relationship between short-term NO 2 exposure and mortality observed statistically significant associations for total, cardiovascular, and respiratory causes, the issue of surrogacy of the role of NO 2 and possible interactions with PM and other pollutants remained unresolved. As reviewed in earlier sections, human clini cal studies, by necessity, were restricted to acute, fully reversible functional and/or symptomatic res ponses in healthy or mildly asthmatic subjects. A number of animal studies (described in Section 3. 1.3) have shown bioche mical, lung host defense, permeability, and inflammation effects with acute expos ures and may provide weak biological plausibility for mortality in susceptible individuals. A 5 ppm NO 2 exposure for 24 h in rats caused increases in blood and lung total GSH and a similar exposure resulted in im pairment of alveolar surface tension of surfactant3-55 phospholipids due to altered fatty acid content. A fairly large body of literature described the effects of NO 2 on lung host defenses at low exposures. However, most of these effects were seen only with subchronic or chronic exposure and, therefore, do not correlate well with the short lag times evidenced in the epidemiologic studies. The resu lts from several large U.S. and European multicity studies and a metaanalysis study observed positive associations between ambient NO 2 concentrations and risk of all-cause (nonaccidental) mortality, with effect estimates ranging from 0.5 to 3.6% excess risk in mortality per standardized increment (Section 3.3.2, Figure 3.3-2). In general, the NO 2 effect estimates were robust to adjustment for copollutants. Both cardiovascular and respiratory mortality have been associated with increased NO 2 concentrations in epidemiologic studies (Figure 3.3-3); however, similar associations were observed for other pollutants, including PM and SO 2 . The range of mortality excess risk estimates was generally smaller than that for other pollutants such as PM.

Figure 3.3-3. Combined NO 2 mortality risk estimates for broad cau se-specific categories from multicity studies. Risk estimates are computed per 20- ppb increase for 24-h avg or 30-ppb increase for 1-h daily max NO 2 concentrations.3-56 

# 3.4. Respiratory Effects Related to Long-Term Exposure

There was no epidemiologic evidence available in the 1993 AQCD on the respiratory effects of long-term exposure (>2 weeks) to ambient NO 2 . The 1993 AQCD reported that chronic exposure to high NO 2 levels (>8 ppm) caused emphysema in several animal species. Since the 1993 AQCD, a number of studies reported associations between long-term NO 2 exposure and respiratory effects (see Annex Tables AX6.3-15, AX6.3-16, and AX6.3-17). While NO 2 exposure, alone or in conjunction with ot her pollutants, may contribute to increased mortality, evaluation of the biological plausibility of this effect was difficult. Clinical studies showing hematologic effects and animal toxicological studies showing biochemical, lung host defense, permeability, and inflammation changes with short-term exposures to NO 2 provided limited evidence of plausible pathways by which risks of morbidity and, potentially, mortality may be increased, but no coherent picture is evident at this time.



# 3.4.1. Lung Function Growth

Studies of lung function demonstrate some of the strongest effects of long-term exposure to NO 2 . Recent cohort studies have examined the effect of long-term exposure to NO 2 in both children and adults (see Annex Table AX6.3-15). Forest plots of the results for FEV 1 and FVC from three major children’s cohort studies (Gauderman et al., 2004; Rojas-Martin ez et al., 2007a,b; Oftedal et al., 2008) are presented in Figures 3.4-1 and 3.4-2. The Children’s Health Study (CHS) in southe rn California was a longitudinal cohort study designed to investigate the effect of chronic exposure to several air contaminates (including NO 2 ) on respiratory health in children. Twelve California communities were selected based on historical data indicating different levels of specific pollutants. In each community, monitoring sites were set up to measure hourly O 3 , NO 2 , and PM 10 and 2-week averages of PM 2.5 , and acid vapor. Children in grades 4, 7, and 10 were recruited though local schools. The st udy followed children for 10 years, with annual questionnaires and lung function measurement. The study had several important characteristics: it was prospective and exposure and outcome data were collect ed in a consistent manner over the duration of the study, and confounding by SES was controlled in th e models by selecting communities similar in demographic characteristics at the outset. Peters et al. (1999) reported the initial results from the CHS: a cross-sectional analysis of lung function tests conducted on 3,293 children in the first year of the study. Both NO 2 and PM 10 were associated with decreases in FVC, FEV 1 , and MMEF. Avol et al. (2001) then studied the effect of relocating to areas of differing air pollution levels in 110 children 10 years of age who were participating in the CHS. As a group, subjects who had moved to areas of lower NO 2 showed increased growth in lung function, but the effects did not reach statistical significance. In general, the authors focused on associations with PM, where larger and statistically significant effects were observed. In 2004, Gauderman et al. reported results for an 8-year follow up of the children enrolled in grade 4 (n=1,759). Exposure to NO 2 was significantly associated with deficits in lung growth over the 8-year period. The difference in FVC for children expo sed to the lowest versus the highest levels of NO 2 (34.6 ppb) was -95.0 mL (95% CI: -189.4 to -0.6). For FEV 1 , the difference was -101.4 mL (95% CI: -165.5 to -38.4), and for MMEF, -221.0 mL/s (95% CI : -377.6, -44.4). Results were similar for boys and girls and among children without a history of asthma. Th ese deficits in growth of lung function resulted in clinically significant differences in FEV 1 at age 18. In addition, the NO 2 concentration associated with deficits in lung function growth was 34.6 ppb (range of means across communities: 4.4-39.0 ppb), a level below the current standard. Similar results were reported for acid vapor (resulting primarily from photochemical conversions of NO X to HNO 3 ). These results are depicted in Figure 3.4-3. The authors3-57 concluded that the effects of NO 2 could not be distinguished from the effects of particles (PM 2.5 and PM 10 ) as NO 2 was strongly correlated with these contaminants (0.79, and 0.67, respectively).

Source: Gauderman et al. (2004) ; Oftedal et al. (2008), Roja s-Martinez et al. (2007a,b).
Figure 3.4-1. Decrements in for ced expiratory volume in 1 s (FEV 1 ) associated with a 20-ppb increase in NO 2 (A) and a 20-μg/m 3 increase in PM 10 (B) in children, standardized per year of follow-up. Results from three major children’s l ong-term cohort studies are presented.3-58 Source: Gauderman et al. (2004) ; Oftedal et al. (2008), Roja s-Martinez et al. (2007a,b).
Figure 3.4-2. Decrements in FVC associated with a 20-ppb increase in NO 2 (A) and a 20-μg/m 3 increase in PM 10 (B) in children, standardized per year of follow-up. Results from three major children’s long-term cohort studies are presented.3-59 Source: Derived from G auderman et al. (2004).
Figure 3.4-3. Proportion of 18-year olds with a FEV 1 below 80% of the predicted value plotted against the average levels of pollutants from 1994 th rough 2000 in the 12 southern California communities of the Children’s Health Study. AL=Alpine; AT=Atascadero; LA=Lake Arrowhead; LB= Long Beach; LE=Lake Elsinore; LM=Lompoc; LN=Lancaster; ML=Mira Loma; RV=Riverside; SD=San Dimas; SM=Santa Maria; UP=Upland3-60 Source: Derived from Rojas- Martinez et al. (2007a,b).
Figure 3.4-4. Estimated annual growth in FEV 1 , of O 3 , PM 10 , and NO 2 in girls and boys. Mexico City, 1996 to 1999 (multipollutant models). Adjusted for age, body mass index, height, height by age, weekday time spent in outdoor activities, envi ronmental tobacco smoke exposure, perviousday mean air pollutant concentration, and study phase of every six months.

More recently, Gauderman et al. (2007) has reported results of an 8-year follow-up on 3,677 children who participated in the CHS. Children living <500 m from a freeway (n=440) had significant deficits in lung function growth over the 8-year fo llow-up compared to children who lived at least 1500 m from a freeway. The difference in FVC was -63 mL (-131 to 5); the difference in FEV 1 -81 mL (-143 to -18); and the difference in MMEF -127 mL/s (-243 to - 11). This study did not attempt to measure specific pollutants near freeways or to estimate exposure to sp ecific pollutants for study subjects. Thus, while the3-61 study presented important findings with respect to tra ffic pollution and respiratory health in children, it did not provide evidence that NO 2 was responsible for these defi cits in lung function growth. Further evaluation of exposure estimation was done in this cohort of schoolchildren (Molitor et al., 2007). Several models of interurban air pollution exposure were used to classify and predict FVC in an integrated Bayesian modeling framework using three in terurban predictors: distance to a freeway, traffic density, and predicted average NO 2 exposure from the California line source dispersion (CALINE4) model. Results indicated that the inclusion of r esidual spatial terms can reduce uncertainty in the prediction of exposures and associated health effects. In Mexico City, Rojas-Martinez et al. (2007a,b) evaluated the association between long-term exposure to PM 10 , O 3 , and NO 2 and lung function growth in a cohort of 3,170 children aged 8 years at baseline in 31 schools from April 1996 through May 1999. Ten air-quality monitoring stations within 2 km of the schools provided expos ure data. cthe results for FEV 1 , by gender and pollutant with adjustments noted for copollutants. The results of this 3-year study supported the hypothesis that longterm exposure to ambient air pollutants is associated w ith deficit in lung function growth in children. The results were, in part, consistent with previous results from the CHS. Similar to the CHS, the high correlation among the three pollutants studied did not allow independent effects to be accurately estimated in this long-term exposure study. Another cohort study in Oslo, Norway, examined short- and long-term NO 2 and other pollutant exposure effects on lung function (PEF, forced expira tory flow at 25% of forced vital capacity [FEF 25 ], forced expiratory flow at 50% of forced vital capacity [FEF 50 ]) in 2,307 nine- and ten-year-old children (Oftedal et al., 2008). The EPISODE dispersion model (Slordal et al., 2003) was used for the exposure estimate and evaluation concluded that the modeled NO 2 and PM levels represent the long- and short-term exposure reasonably well. An incremental change equal to the IQR of lifetime exposure to NO 2 , PM 10 , and PM 2.5 was associated with changes in adjusted peak flow of -79 mL/s (95% CI: -128,-31), -66 mL/s (95% CI: -110, -23), and -58 mL/s (95% CI: -94, - 21), respectively. Examining short- and long-term NO 2 exposures simultaneously yielded only the long-term e ffects. Adjusting for a contextual socioeconomic factor diminished the association. The association between long-term exposure to NO 2 and decreased PEF was comparable to that found in the CHS, but asso ciations with forced volumes were considerably weaker. In another European study, Moseler et al. (1994) measured NO 2 outside the homes of 467 children, including 106 who had physician-diagnosed asthma, in Freiburg, Germany. Five of six lung function parameters were reduced among ast hmatic children exposed to NO 2 at concentrations of >21 ppb. No significant reductions in lung function were detected among children without asthma. To examine the effect of lifetime exposure to air pollutants in young adults, lung function in students attending the University of California (Ber keley) who had been lifelong residents of the Los Angeles or San Francisco areas was assessed (Tager et al, 2005). Using geocoded address histories, a lifetime exposure to air pollution was constructed for each student. Increasing lifetime exposure to NO 2 was associated with decreased FEF 75 and FEF 25-75 . In models including O 3 and PM 10 as well as NO 2 , the effect of NO 2 diminished significantly while the O 3 effect remained robust. The SAPALDIA (Study of Air Pollution and Lung Diseases in Adults) study (Ackermann-Liebrich et al., 1997) compared 9,651 adults (age 18 to 60) in eight different regions in Switzerland. Significant associations of NO 2 , SO 2 , and PM 10 with FEV 1 and FVC were found with a 10-μg/m 3 (5.2 ppb) increase in annual average exposure. Due to the high correlations between NO 2 and the other pollutants (SO 2 : r=0.86; PM 10 : r=0.91), it was difficult to assess the effect of a specific pollutant. A random subsample of 560 adults from SAPALDIA recorded personal measurements of NO 2 and measurements of NO 2 outside their homes (Schindler et al., 1998). Using the personal and home measurements of NO 2 , similar associations were reported between NO 2 with FEV 1 and FVC. Downs et al. (2007) reported the relationship in this group of l ong-term reduced exposure to PM 10 and age-related decline in lung function, but they did not examine NO 2 or other pollutants.3-62 Goss et al. (2004) examined the relationship of ambient pollutants on individuals with cystic fibrosis using the Cystic Fibros is Foundation National Patient Regi stry in 1999 and 2000. Exposure was assessed by linking air pollution values from the Aerome tric Information Retrieval System with the patient’s home ZIP code. Associations were repor ted between PM and exacerbations or lung function changes, but no clear associations were found for O 3 , SO 2 , NO 2 , or CO. The odds of patients with cystic fibrosis having two or more pul monary exacerbations per 10-ppb NO 2 was 0.98 (95% CI: 0.91, 1.01) for the year 2000. A number of epidemiologic studies examined the effects of long-term exposure to NO 2 and observed associations with decrements in lung functi on and partially irreversible decrements in lung function growth. Decreases in FEV 1 ranged from 1 to 17.5 per 20 ppb increase in annual NO 2 concentration. Results from the Southern California Children’s Health Study indicated that decrements were similar for boys compared to girls, and am ong children who did not have a history of asthma (Gauderman et al., 2004). The mean NO 2 concentrations in these studies range from 21.5 to 34.6 ppb; thus, all have been conducted in areas where mean NO 2 levels are below the level of the NAAQS. The epidemiologic studies of long-term exposure to NO 2 , however, may be confounded by other ambient copollutants. In particular, similar associations have also been found for PM and proximity to traffic (<500 m). The results of the CHS study support an association between decreased lung function growth and a mixture of traffic-related pollutants, but as ob served by the authors, it is difficult to distinguish effects for NO 2 and other individual pollutants within these mixtures (Gauderman et al., 2004).



# 3.4.2. Asthma Prevalence and Incidence

Several publications from the CHS in southern Ca lifornia reported results on the associations of NO 2 exposure with asthma prevalence and incidence. Gauderman et al. (2005) conducted a study of children randomly selected from the CHS with exposure measured at children’s homes. Although only 208 were enrolled, exposure to NO 2 was strongly associated with both lifetime history of asthma and asthma medications use. Gauderman et al. (2005) measured ambient NO 2 with Palmes tubes attached to the subjects’ homes at the roofline eaves, signposts, or ra in gutters at an approximate height of 2 m above the ground. Samplers were deployed for 2-week periods in both summer and fall. Traffic-related pollutants were characterized by three metrics: (1) proximity of home to freeway, (2) average number of vehicles within 150 meters, and (3) model-based estimates. Yearly average NO 2 levels within the 10 communities ranged from 12.9 to 51.5 ppb. The average NO 2 concentration measured at home was associated with asthma prevalence (OR=8.33 [95% CI: 1.15, 59.87] per 20-ppb increase) with similar results by season and when taking into account sever al potential confounders. In each community studied, NO 2 was more strongly correlated with estimates offreeway-related pollution than with non-freewayrelated pollution. In a related CHS study, McConnell et al. (2006) studied the relationship of proximity to major roads and asthma and also found a positive relationship. Islam et al. (2007) studied whether lung function is associated with new onset asthma and whether this relationship varies by exposure to ambient air po llutants by examining a cohort of 2,057 fourth-grade children who were asthma- and wheeze-free at the star t of the CHS and following them for 8 years. A hierarchal model was used to evaluate the effect of individual air pollutants (NO 2 , PM 10 , PM 2.5 , and acid vapor, NO 2 , EC, and OC) on the association of lung function with asthma. This study showed that better airflow, characterized by higher FEF 25-75 and FEV 1 during childhood was associated with decreased risk of new-onset asthma during adolescence. However, e xposure to high levels of ambient pollutants (NO 2 and others) attenuated this protective associ ation of lung function on asthma occurrence. Millstein et al. (2004) studied the effects of ambient air pollutants on asthma medication use and wheezing among 2,034 fourth-grade schoolchildren from th e CHS. Included in the pollutants examined were NO 2 and HNO 3 . They observed that monthly average pollutant levels produced primarily by photochemistry (i.e., HNO 3 , acetic acid), but not NO 2 , were indicative of a positive association with asthma medication use among children with asthma—esp ecially among children who spent more than the3-63 calculated median time outdoors. The March-August OR for HNO 3 (IQR 1.64 ppb) was 1.62 (95% CI: 0.94, 2.80) and for NO 2 (IQR 5.74 ppb), 0.96 (95% CI: 0.68, 1.37). Kim et al. (2004a) reported associations with both NO 2 and NO X for girls in the San Francisco bay area. They studied 1,109 students (grades 3 to 5) at 10 school sites for bronchitis symptoms and asthma in relation to ambient pollutant levels to include NO, NO 2 , and NO X measured at the school site. Mean levels ranged for schools from 33 to 69 ppb for NO X ; 19 to 31 for NO 2 ; and 11 to 38 ppb for NO. NO X and NO 2 measurements at school sites away from traffic we re similar to levels measured at the regional site. They found associations between traffic-rela ted pollutants and asthma and bronchitis symptoms, which was consistent with previ ous reports of traffic and respiratory outcomes. The higher effect estimates with black carbon, NO X , and NO compared with NO 2 and PM 2.5 indicated that primary or fresh traffic emissions may play an etiologic role in these relationships and that, while NO X and NO may serve as indicators of traffic exposures, they also may act as etiologic agents themselves. Brauer et al. (2007) assessed the development of asthmatic/allergic symptoms and respiratory infections during the first 4 years of life in a birt h cohort study in the Netherlands (n=4,000, but the number of participants decreased over the study to ~3,500). Air pollution concentrations at the home address at birth were calculated by a validated model combining air pollution measurements with a Geographic Information System (GIS). Wheeze, physi cian-diagnosed asthma, and flu and serious colds were associated with air pollutants (considered traffic-related: NO 2 , PM 2.5 , soot) after adjusting for other potential confounding variables; for example, NO 2 was associated with physician-diagnosed asthma (OR=1.28 [95% CI: 1.04, 1.56]) as a cumulative lifetime indicator. In comments to this study, Jerrett (2007) observed that the effects were larger and more c onsistent than in participants of the same study at age 2 and that these effects showed that onset and pe rsistence of respiratory disease formation begins at an early age and continues. He further noted that the more sophisticated method for exposure assessment based on spatially and temporally representative fi eld measurements and land use regression was capable of capturing small area variations in traffic pollutants. Other studies (see Annex Table AX6.3-16) also have investigated asthma prevalence and incidence in children associated with NO 2 exposure. Although several of these studies have reported positive associations, the large number of comparisons made and the limited number of positive results do not support a strong relationship between long-term NO 2 exposure and asthma. Several studies used the International Study of Asthma and Allergies in Ch ildren (ISAAC) protocol. Children were interviewed in school and results of the questionnaire were comp ared with air pollution measurements in their communities. These studies included thousands of child ren in several European countries and Taiwan, and the results in all but one study were nonsigni ficant. Exposure in these studies varied, but medians were often greater than 20 ppb. Most of the studies did not report correlations of NO 2 exposure with other air pollutants; therefore, it is not possible to determ ine whether some of these associations were related to other air contaminants. Overall, results from the available epidemiologi c evidence investigating the association between long-term exposure to NO 2 and increases in asthma prevalence and incidence are inconsistent. Two major cohort studies, the Children’s Health Study in southe rn California (Gauderman et al., 2005) and a birth cohort study in the Netherlands (Brauer et al., 2007) observed significant associations; however, several other studies did not find consistent associations between long-term NO 2 exposure and asthma outcomes.



# 3.4.3. Respiratory Symptoms

Annex Table AX6.3-17 lists studies examining th e association between long-term exposure to NO 2 and respiratory symptoms. Most of the studies reported some positive associations with NO 2 exposure and symptoms, but all reported a large number of nega tive results. Only one of these studies (Peters et al., 1999b) reported an association of NO 2 exposure with wheeze, and in boys. This was despite the fact that wheeze was investigated in a large number of studies, including several studies that included thousands of children.3-64 McConnell et al. (2003) studied the relationship be tween bronchitis symptoms and air pollutants in the CHS. Symptoms assessed yearly by questionnaire from 1996 to 1999 were associated with the yearly variability for the pollutants for NO 2 (OR=1.071 [95% CI: 1.02, 1.13). In two-pollutant models, the effects of yearly variation in NO 2 were only modestly reduced by adjusting for other pollutants except for the model containing both OC and NO 2 (Figure 3.4-5). McConnell et al. (2006) further evaluated whether the association of exposure to air pollution with a nnual prevalence of chronic cough, phlegm production, or bronchitis was modified by dog or cat ownershi p indicators or allergen and endotoxin exposure. Subjects consisted of 475 children from the CHS. Among children owning a dog, there was a strong association between bronchitis symptoms and all pollutants studied. The odds ratio for NO 2 was 1.49 (95% CI: 1.14, 1.95), indicating that dog ownership may worsen the relationship between air pollution and respiratory symptoms in asthmatic children.

Source: McConnell et al. (2003).
Figure 3.4-5. Odds ratios for within-comm unity bronchitis symptoms associations with NO 2 , adjusted for other pollutants in two-pollutant models fo r the 12 communities of the Children’s Health Study.

In the Netherlands (Brauer et al., 2002), the same protocol was used to estimate NO 2 exposure in a birth cohort of 3,730 infants. However, these study subjects lived in many different communities from rural areas to large cities in northern, central, and western parts of the Netherlands. Forty sites were selected to represent different exposures and measureme nts were taken as in the Gehring et al. (2002) study. In this study, ear, nose, and throat infec tions (OR=1.16 [95% CI: 1.00, 1.34]) and physiciandiagnosed flu (OR=1.11 [95% CI: 1.00, 1.23]) were marginally significant. The association of NO 2 with dry cough at night observed in the German study could not be replicated, nor was NO 2 associated with asthma, wheeze, bronchitis, or eczema. In both of these studies, the 40 monitoring sites set up to measure NO 2 also measured PM 2.5 with Harvard Impactors. Estimates of NO 2 and PM 2.5 were highly correlated in Brauer et al. (r=0.97). The correlation was not reported in Gehring et al. (2002) ; however, the similarity of odds ratios for each pollutant showed that the estimated exposures were al so highly correlated. Thus, a restricting factor of these studies was the inability to distinguish the effects of different pollutants.3-65 In a study of 3,946 Munich schoolchildren, Nicolai et al. (2003) assessed traffic exposure using two different methods. First, all street segments within 50 m of each child’s home were identified and the average daily traffic counts were totaled. Second, a model was constructed based on measurement of NO 2 at 34 sites throughout the city using traffic counts and street characteristics (R 2 =0.77). The model was then used to estimate NO 2 exposure at each child’s home address. When traffic counts of ≤ 50m were used as an exposure variable, a significant associati on was found with current asthma (OR=1.79 [95% CI: 1.05, 3.05]), wheeze (OR=1.66 [95% CI: 1.07, 2.57]), and cough (OR=1.62 [95% CI: 1.16, 2.27]). Similar results were found when modeled NO 2 exposure was substituted as the e xposure variable (current asthma OR=1.65 [95% CI: 0.94, 2.90], wheeze OR=1.58 [95% CI: 1.05, 2.48], cough OR=1.60 [95% CI: 1.14, 2.23]). Asthma, wheeze, and cough were also associated with estimated exposures to soot and benzene derived from models, indicating that some compone nt of traffic pollution was increasing risk of respiratory conditions in children, but making it difficult to determine whether NO 2 was the cause of these conditions. In summary, epidemiologic studies conducted in both the U.S. and Europe have observed inconsistent results regarding an associ ation between long-term exposure to NO 2 and respiratory symptoms. While some positive associations were noted, a large number of symptom outcomes were examined and the results across sp ecific outcomes were inconsistent.



# 3.4.4. Respiratory Morphology

Animal toxicology studies demonstrated morphological changes to the respiratory tract from exposure to NO 2 that may provide further biological plausibility for the decrements in lung function growth observed in epidemiologic studies discussed above. Several investigators have studied the temporal progression of early events due to NO 2 exposure in the rat (e.g., Freeman et al., 1966, 1968, 1972; Stephens et al., 1971, 1972; Evans et al ., 1972, 1973a,b, 1974, 1975, 1976, 1977; Cabral-Anderson et al., 1977; Rombout et al., 1986) and guinea-pig (S herwin and Carlson, 1973). The results of these studies were summarized in the 1993 AQCD. Overall, an imal toxicological studies demonstrated that NO 2 exposure resulted in permanent alterations resemb ling emphysema-like disease, morphological changes in the centriacinar region of the lung and in bronchiol ar epithelial proliferation, which might provide biological plausibility for the observed epidemiol ogic associations between long-term exposure to NO 2 and respiratory morbidity.



# 3.4.5. Summary of Respiratory Effects Related to Long-Term Exposure

Overall, the epidemiologic and experimental evid ence was suggestive but not sufficient to infer a causal relationship between long-term NO 2 exposure and respiratory morbidity. The available database evaluating the relationship between respiratory illness in children associated with long-term exposures to NO 2 has increased. Three recent studies in large cohor ts in three countries have examined this relationship. The California-based CHS, examining NO 2 exposure in children over an 8-year period, demonstrated deficits in lung func tion growth (Gauderman et al., 2004). This has been observed also in Mexico City, Mexico (Rojas-Martinez et al., 2007a,b), and in Oslo, Norway (Oftedal et al., 2008), with decrements ranging from 1 to 17.5 ml per 20- ppb increase in annual NO 2 concentration. Deficit in lung function growth is a known risk factor for chronic respiratory disease and possibly for premature mortality in later life stages. Lung growth continues from early development through early adulthood, reaches a plateau, and then eventually d eclines with advancing age. Dockery and Brunekreef (1996) hypothesized that the risk for chronic resp iratory disease is associated with maximum lung size, the length of time the lung size has been at the plateau, and the rate of decline of lung function. Therefore, exposures to NO 2 and other air pollutants in childhood may reduce maximum lung size by limiting lung growth and subsequently increase the risk in adulthood for chronic respiratory disease.3-66 Models and/or mechanisms of action for decremen ts in lung function growth and other respiratory effects from long-term exposure to air pollution are not clearly established. Figure 3.4-6 was adapted from an earlier model discussed by Gilliland et al. (1999), reflective of efforts of the CHS research. Gilliland et al. (1999) proposed that respiratory e ffects in children from exposure to gaseous and particulate air pollutants result from chronically increased oxidative stress, alterations in immune regulation, and repeated pathologic inflammatory responses that overcome lung defenses to disrupt the normal regulatory and repair processes. Rojas-Martinez et al. (2007a,b) noted that oxidative stress resulting from increased exposure to oxidized compounds (O 3 , NO 2 , and particle components) has been identified as a major feature underlying the toxic effects of air pollutants (Kelly et al., 2003; Saxon and Diaz-Sanchez, 2005; Cross et al., 2002). They furthe r noted that the resulting increased expression of enhanced proinflammatory cytokines leads to enhan ced inflammatory response (Saxon and Diaz-Sanchez, 2005) and potential chronic lung damage. If this results in permanent loss, it is not clear whether repeated versus average exposure is the major factor. Curre nt data and the nonlinear pattern of childhood lung function growth (Pérez-Padilla et al., 2003) were not ed by Rojas-Martinez et al. (2007a,b) as limitations on estimating the impact on lung function attained in early adulthood.

Source: Adapted from Gilliland et al. (1999).
Figure 3.4-6. Biological pathways of long-term NO 2 exposure on morbidity. MPO=myeloperoxidase; PUFA=polyunsaturated fatty acids; TNF- α =tumor necrosis factor-alpha.

Other important biochemical mechanisms examined in animals may provide biological plausibility for the chronic effects of NO 2 observed in epidemiologic studies. The main biochemical targets of NO 2 exposure appear to be antioxidants, membrane polyun saturated fatty acids, and thiol groups. Reactions of NO 2 with these species in the extracellular lining fluid of the lung leads to the formation of nitrite (NO 2 - ) and hydrogen (H + ) ions. NO 2 effects include changes in oxidant/antioxidant homeostasis and chemical alterations of lipids and proteins. Lipi d peroxidation has been observed at NO 2 exposures as low as 0.04 ppm for 9 months and at exposures of 1.2 ppm fo r 1 week, indicating lower effect thresholds with longer durations of exposure. Other studies show ed decreases in formation of key arachidonic acid metabolites in AMs following NO 2 exposures of 0.5 ppm. NO 2 has been shown to increase collagen synthesis rates at concentrations as low as 0.5 ppm . This could indicate increased total lung collagen, which is associated with pulmonary fibrosis, or in creased collagen turnover, which is associated with remodeling of lung connective tissue. Morphological effects following chronic NO 2 exposures have been3-67 identified in animal studies that link to these increases in collagen synthesis and may provide plausibility for the deficits in lung function growth described in epidemiologic studies. An alternative explanation for the decrease in l ung function growth observed in the CHS needs to be considered. Since this response was associated with both NO 2 and HNO 3 exposure, ambient levels of NO may also have been involved. Three groups have reported emphysematous changes in animal studies following prolonged exposure to NO. In the Mercer study (1995), a decreased number of interstitial cells and thinning of the alveolar septa was observed. Ot her studies in vitro and in animal models have demonstrated that NO inhibits protein synthesis and cellular proliferation. Whether NO plays a role in maintaining the alveolar interstitial compartment re quires further investigation. Furthermore, the formation of NO or NO-related species may have occurred following complex reactions of NO 2 and HNO 3 with components of the extracellular lining fluid. The role of NO 2 - , H + , NO and other metabolites in modulating responses to NO 2 and/or HNO 3 is unknown. In regard to asthma prevalen ce incidence associated with NO 2 long-term exposure, the results are inconsistent. In two major cohort studies, the CHS in southern California and a birth cohort study in the Netherlands, significant associations were reported; how ever, several other studies did not find consistent associations between long-term NO 2 exposure and asthma prevalence.



# 3.5. Other Morbidity Effects Related to Long-Term Exposure

This ISA includes a number of studies published since 1993 characterizing the effect of long-term NO X exposure on cancer, CVD, reproductive, and deve lopmental morbidity. These studies form a new body of literature that was unavailable in 1993, when the previous AQCD was published.



# 3.5.1. Cancer Incidence

Two studies (see Annex Table AX6.3-18) investigated the relationship between NO 2 exposure and lung cancer and reported positive associations. Although this ISA concentrated on studies that measured exposure to NO 2 , modeled exposures were considered for cancer studies. This was necessary because the relevant exposure period for lung cancer may be 30 years or more. Nyberg et al. (2000) reported results of a case control study of 1,043 men age 40 to 75 years with lung cancer and 2,364 controls in Stockholm County. They mapped residence addresses to a GIS database indicating 4,300 traffic-related lin e sources and 500 point sources of NO 2 exposure. Exposure was derived from a model validated by comparison to actual measurements of NO 2 at six sites. Exposure to NO 2 at 10 μg/m 3 (5.2 ppb) was associated with an OR of 1.10 (95% CI: 0.97, 1.23) for lung cancer. Exposure to the 90th percentile ( ≥ 29.26 μg/m 3 [15.32 ppb]) of NO 2 was associated with an OR of 1.44 (95% CI: 1.05, 1.99). Very similar results were reported in a Norwegian study (Nafstad et al., 2003). The study population was a cohort of 16,209 men who enrolled in a study of CVD in 1972. The Norwegian cancer registry identified 422 incident cases of lung cancer. Exposure data was modeled based on residence, estimating exposure for each person in each year from 1974 to 1998. Exposure to 10 μg/m 3 (5.2 ppb) of NO 2 was associated with an OR of 1.08 (95% CI: 1.02, 1.15) for lung cancer; exposure of ≥ 30 μg/m 3 (15.7 ppb) was associated with an OR of 1.36 ( 95% CI: 1.01, 1.83). However, controlling for SO 2 exposure did appreciably change the effect estimates for NO 2 . What is particularly striking in these two studies is the similarity in the estimate of effect. Despite the fact that these two studies were conducted by diffe rent investigators, in different countries, using different study designs and different methods for m odeling exposure, the odds ratios and CI for exposure per 10 μg/m 3 (5.2 ppb) and above 30 μg/m 3 (15.7 ppb) are virtually identical. It is possible that NO 2 may3-68 be acting as an indicator of traffic-related carcinoge ns, and thus the observed increased cancer incidence may be related to exposure of these carcinogens, such as PAHs.



## 3.5.1.1. Animal and In Vitro Carcinogenicity and Genotoxicity Studies

There is no clear evidence that NO 2 or gaseous nitrogen oxides act as a complete carcinogen. No studies were found on NO 2 using classical carcinogenesis whole-animal bioassays. Of the existing studies that evaluated the carcinogenic and cocarcinogenic potential of NO 2 , results were often unclear or conflicting. Witschi (1988) critically reviewed some of the important theoretical issues in interpreting these types of studies. NO 2 appeared to act as a tumor promoter at the site of contact (i.e., in the respiratory tract from inhalation exposure), possibly due to its ability to produce cellular damage and, thus, promote regenerative cell proliferation. This hypothesis was supported by observed hyperplasia of the lung epithelium from NO 2 exposure (see Lung Morphology section, NO X AQCD, EPA, 1993), which is a common response to lung injury, and enha ncement of endogenous retrovirus expression (RoyBurman et al., 1982). However, these findings were considered by EPA (1993) to be inconclusive. When studied using in vivo assays, no inductions of recessive lethal mutations were observed in Drosophila exposed to NO 2 (Inoue et al., 1981; Victorin et al., 1990). NO 2 did not increase chromosomal aberrations in lymphocytes and spermatocytes or micronuclei in bone marrow cells (Gooch et al., 1977; Victorin et al., 1990). No increased stimulation of poly (ADP-ribose) synthetase activity (an indicator of DNA repair, and possible DNA damage) was reported in AMs recovered from BAL of rats continuously exposed to 1.2 ppm NO 2 for 3 days (Bermudez, 2001). NO 2 has been shown to be positive when test ed for genotoxicity in in vitro assays. NO 2 is mutagenic in bacteria and in plants. In cell cultures, three studies showed chromosomal aberrations, sister chromatid exchanges (SCEs), and DNA single-strand br eaks. However, a fourth study (Isomura et al., 1984) concluded that NO, but not NO 2 , was mutagenic in hamster cells (see Annex Tables AX4.11, 4.12, and 4.13).



## 3.5.1.2. Toxicological Studies of Coexposure with Known Carcinogens

Rats were injected with N -bis (2-hydroxy-propyl) nitrosamine (BHPN) and continuously exposed to 0.04, 0.4, or 4 ppm NO 2 for 17 months. Although the data indicated 5 times as many lung adenomas or adenocarcinomas in the rats injected with BHPN and exposed to 4 ppm NO 2 (5/40 compared to 1/10), the results failed to achieve statistical significance (Ichi nose et al., 1991). In a later study, Ichinose and Sagai (1992) reported increased lung tumors in rats injected with BHPN, followed the next day by either clean air (0%), 0.05 ppm NO 2 (8.3%), 0.05 ppm NO 2 +0.4 ppm O 3 (13.9%), or 0.4 ppm O 3 +1 mg/m 3 H 2 SO 4 aerosol (8.3%) for 13 months, and then maintained for another 11 months until study termination. Exposure to NO 2 was continuous, while the exposures to O 3 and H 2 SO 4 -aerosol were intermittent (exposure for 10 h/day). The increased lung tumors from combined exposure of NO 2 and O 3 were statistically significant. Ohyama et al. (1999) coexposed rats to diesel e xhaust particle extract-coated carbon black particles (DEPcCBP) once a week for 4 weeks by intratracheal instillation and to either 6 ppm NO 2 , 4 ppm SO 2 , or 6 ppm NO 2 +4 ppm SO 2 16 h/day for 8 months, and thereafter exposed to clean air for 8 months. Alveolar adenomas were increased in animals exposed to DEPcCBP and either NO 2 and/or SO 2 compared to animals in the DEPcCBP-only group and to contro ls. The incidences of lung tumors for the NO 2 , SO 2 , and NO 2 and/or SO 2 groups were 6/24 (25%), 4/30 (13%), and 3/28 (11%), respectively. No alveolar adenomas were observed in animals exposed to DEPc CBP alone or in the controls. Increased alveolar hyperplasia was elevated in all groups compared to controls. In addition, DNA adducts, as determined by 32P postlabelling, were observed in the anim als exposed to both DEPcCBP and either NO 2 and/or SO 2 , but not in animals exposed to DEPcCBP alone or controls. The authors concluded that the cellular3-69 damage induced by NO 2 and/or SO 2 may have resulted in increased cellular permeability of the DEPcCBP particles into the cells.



## 3.5.1.3. Studies in Animals with Spontaneously High Tumor Rates

The frequency and incidence of spontaneously occurring pulmonary adenomas was increased in strain A/J mice (with spontaneously high tumor rates) after exposure to 10-ppm NO 2 for 6 h/day, 5 days/week for 6 months (Adkins et al., 1986). These small, but statistically significant, increases were only detectable when the control response from ni ne groups (n=400) were pooled. Exposure to 1 and 5 ppm NO 2 had no effect. In contrast, Richters and Dam ji (1990) found that an intermittent exposure to 0.25 ppm NO 2 for up to 26 weeks decreased the progression of a spontaneous T cell lymphoma in AKR/cum mice and increased survival rates. The i nvestigators attributed this effect to an NO 2 -induced decrease in the proliferation of T lymphocyte subpopula tion in the spleen (especially T-helper/inducer CD+ lymphocytes) that produces growth factors for the lymphoma. A study by Wagner et al. (1965) showed that NO 2 may accelerate the production of tumors in CAF1/Jax mice (a strain that has spontaneously high pulmonary tumor rates) after continuous exposure to 5 ppm NO 2 . After 12 months of exposure, 7/10 mice in the exposed group had tumors, co mpared to 4/10 in the controls. No differences in tumor production were observed after 14 and 16 months of exposure. A st atistical evaluation of the data was not presented.



## 3.5.1.4. Facilitation of Metastases

Whether NO 2 facilitates metastases has been the subject of several experiments by Richters and Kuraitis (1981, 1983), Richters and Richters (1983), a nd Richters et al. (1985). Mice were exposed to several concentrations and durations of NO 2 and were injected intravenously with a cultured-derived melanoma cell line (B16) after exposure, and subse quent tumors in the lung were counted. Although some of the experiments showed an increased num ber of lung tumors, statistical methods were inappropriate. Furthermore, the experimental techni que used in these studies probably did not evaluate metastases formation, as the term is generally underst ood, but more correctly, colonization of the lung by tumor cells.



## 3.5.1.5. Production of N -Nitroso Compounds and other Nitro Derivatives

Because of evidence that NO 2 could produce NO 2 - and NO 3 - in the blood and the fact that NO 2 - is known to react with amines to produce animal car cinogens (nitrosamines), the possibility that NO 2 could produce cancer via nitrosamine formation has been inv estigated. Iqbal et al. (1980) were the first to demonstrate a linear time- and concentration- dependent relationship between the amount of N

-nitrosomorpholine (NMOR, an animal carcinogen) found in whole-mouse homogenates after the mice were gavaged with 2 mg of morpho line (an exogenous amine that is ra pidly nitrosated) and exposure to 15 to 50 ppm NO 2 for between 1 and 4 h. In a follow-up st udy at more environmentally relevant exposures, Iqbal et al. (1981) used dimethylamine (D MA), an amine that is slowly nitrosated to dimethylnitrosamine (DMN). They reported a concen tration-related increase in biosynthesis of DMN at NO 2 concentrations of as low as 0.1 ppm; however, the rate was significantly greater at concentrations above 10 ppm NO 2 . Increased length of exposure also increased DMN formation between 0.5 and 2 h, but synthesis of DMN was less after 3 or 4 h of exposure than after 0.5 h. Mirvish et al. (1981) concluded that the results of Iqbal et al. (1980) were technically flawed, but they found that in vivo exposure to NO 2 could produce a nitrosating agent (NSA) that would nitrosate morpholine only when morpholine was added in vitro. Further experiments showed that the NSA was localized in the skin (Mirvish et al., 1983) and that mouse skin cholesterol was a likely NSA (Mirvish3-70 et al., 1986). It has also been reported that only very lipid-soluble amines, which can penetrate the skin, would be available to the NSA. Compounds such as morpholine, which are not lipid-soluble, could only react with NO 2 when painted directly on the skin (Mirvi sh et al., 1988). Iqbal (1984), responded to the Mirvish et al. (1981) criticisms, verifing their earlier (Iqbal et al., 1980) studies. The relative contribution of NO 2 - from NO 2 compared with other NO 2 - sources such as food, tobacco, and nitrate-reducing oral bacteria is uncertain . Nitrosamines have not been detected in tissues of animals exposed by inhalation to NO 2 unless precursors to nitrosamines a nd/or inhibitors of nitrosamine metabolism are coadministered. Rubenchik et al. (1995) could not detect N -nitrosodimethylamine (NDMA) in tissues of mice exposed to 7.5- to 8.5-mg/m 3 NO 2 for 1 h. NDMA was found in tissues, however, if mice were simultaneously given oral doses of amidopyrine and 4-methylpyrazole, an inhibitor of NDMA metabolism. Nevertheless, the main source of NO 2 - in the body is endogenously formed, and food is also a contributing source of nitrite (from nitrate conversion).



## 3.5.1.6. Summary of Cancer Incidence Related to Long-Term Exposure

In summary, two epidemiologic studies conducted in Europe showed an association between longterm NO 2 exposure, used as an indicator of traffic exposure, and incidence of cancer (Nyberg et al., 2000; Nafstad et al., 2003); however, the animal toxicological studies have provided no clear evidence that NO 2 directly acts as a carcinogen, though it does appear to act as a tumor promoter at the site of contact (Section 3.5.1). There are no in vivo studies that support that NO 2 causes teratogenesis or malignant tumors. Only very high exposure studies, i. e., levels not relevant to ambient NO 2 levels, demonstrated increased chromosomal aberrations and mutations in in vitro studies. A more likely pathway for NO 2 involvement in cancer induction is through secondary formation of nitro-PAHs, as nitro-PAHs are known to be more mutagenic than their parent compounds . The evidence for a causal relationship between NO 2 and increased cancer risk is inadequate to infer th e presence or absence of a causal relationship at this time. The information presented in this section is releva nt to potential mechanisms by which exposure to products formed by reaction of gaseous nitrogen oxi des with organic compounds can be carcinogenic. As discussed previously in Section 2.2, nitro-PAHs a nd other nitrated organic compounds can be produced through reactions of NO 2 or NO with organic compounds in the atmosphere. Nitro-PAHs are largely found on particles, and they can also be including in di rect emissions of particles, such as diesel exhaust particles. Effects of particulate nitrogen compounds have been considered in previous reviews of the PM NAAQS. In addition, it is possible that the products of NO 2 (NO 2 - and NO 3 - ) could produce carcinogens (e.g., N -nitrosomorpholine) through exposure from an environmentally occurring precursor compound (e.g., morpholine) within the body. The studies demonstr ated that this is a possible mechanism; however, it should be pointed out that (1) that these studies used only a single precursor compound whereas humans would be exposed to multiple precursor compounds t hus producing an array of nitrosamines and other nitrated compounds, (2) the level of nitrosamines per se produced in this fashion would be small compared to the nitrosamines that come from cigarette smoke, smoked meats, and other food sources and from the atmospheric transformation of products in the ambient air, and (3) a wide array of nitrated products are produced in the ambient air with a num ber of these products known to be carcinogens and/or mutagens.



### Cardiovascular Effects
One epidemiologic study examin ed the association of cardiovascular effects with long-term exposure to NO 2 . Miller et al. (2007) studied 65,893 postmenopausal women between the ages of 50 and 79 years without previous CVD in 36 U.S. metropolitan areas from 1994 to 1998. They examined the association between one or more fatal or nonfatal car diovascular events and the women’s exposure to air pollutants. Subject’s exposures to air pollution were estimated by assigning the annual mean levels of air3-71 pollutants in 2000 measured at the monitor nearest the residence based on its five-digit ZIP Code centroid, which resulted in a more spatially resolv ed exposure estimate. A total of 1,816 women had one or more fatal or nonfatal cardiovascular events , including 261 deaths from cardiovascular causes. The main focus of the study was PM 2.5 , but the overall CVD events (but not results for death events only) using all the copollutants (PM 10 , PM 10 -2.5, SO 2 , NO 2 , CO, and O 3 ) in both single- and multipollutant models were presented. The results for the mode ls only including subjects with non-missing exposure data (n=28,402 subjects resulting in 879 CVD events) ar e described here. In the single-pollutant model results, PM 2.5 showed the strongest associations with th e CVD events by far among the pollutants, followed by SO 2 . NO 2 did not show any association with the overall CVD events (heart rate [HR]=0.98 [95% CI: 0.89, 1.08] per 10-ppb increase in the annua l average). In the multipollutant model, which included all the pollutants, the association of PM 2.5 and SO 2 with overall CVD events became even stronger. NO 2 became negatively associated with the ove rall CVD events (HR=0.82 [95% CI: 0.70, 0.95]). Correlations among these pollutants were not d escribed; therefore, it was not possible to estimate the extent of confounding among these pollutants in these associations, but it is clear that PM 2.5 was the best predictor of the CVD events. Limited toxicology data exist on the effect of NO 2 on the heart. Alterations in vagal responses have been shown to occur in rats exposed to 10 ppm NO 2 for 24 h; however, exposure to 0.4 ppm NO 2 for 4 weeks revealed no change (Tsubone and Suzuki, 1984). NO 2 -induced effects on cardiac performance were indicated by a significant reduction in the pressure of oxygen in arterial blood (PaO 2 ) in rats exposed to 4.0 ppm NO 2 for 3 months. When exposure was decreased to 0.4-ppm NO 2 over the same exposure period, PaO 2 was not affected (Suzuki et al., 1981). In add ition, a reduction in HR has been reported in mice exposed to both 1.2 and 4.0 ppm NO 2 for 1 month (Suzuki et al., 1984). Whether these effects were the direct result of NO 2 exposure or secondary responses to lung edema and changes in blood hemoglobin content was not known (U.S. Environmental Protec tion Agency, 1993). A more recent study (Takano et al., 2004) using an obese rat strain found changes in blood triglycerides, HDL, and HDL/total cholesterol ratios in response to a 24-week exposure of 0.16 ppm NO 2 .No effects on hematocrit and hemoglobin have been reported in s quirrel monkeys exposed to 1.0 ppm NO 2 for 16 months (Fenters et al., 1973) or in dogs exposed to ≤ 5.0 ppm NO 2 for 18 months (Wagner et al., 1965). There were, however, polycythemia and an increased ratio of PM Ns to lymphocytes in rats exposed to 2.0 and 1.0 ppm NO 2 for 14 months (Furiosi et al., 1973). The few available epidemiologic and toxicological evidence did not support that long-term exposure to NO 2 has cardiovascular effects. The U.S. Wome n’s Health Initiative study (Miller et al., 2007) did not find any associations between long-term NO 2 exposure and cardiovascular events. The toxicological studies observed some effects of NO 2 on cardiac performance and heart rate, but only at exposure levels of as high as 4 ppm. Overall, these data are inadequate to infer the presence or absence of a causal relationship.



# 3.5.2. Reproductive and Developmental Effects

The effects of maternal exposure during pregnancy to air pollution have been examined by several investigators in recent years (2000 through 2006). These outcomes were not evaluated in the 1993 AQCD. The most common endpoints studied were low birth weight, preterm delivery, and measures of intrauterine growth (e.g., small for gestational age) . Generally, these studies used routinely collected air pollution data and birth certificates from a given area for their analysis. While most studies analyzed average NO 2 exposure for the whole pregnancy, many also considered exposure during specific trimesters or other time peri ods. Fetal growth, for example, is much more variable during the third trimester. Thus, studies of fe tal growth might anticipate that exposure during the third trimester would have the greatest likelihood of an association, as is true for the effect of maternal smoking during pregnancy. However, growth can also be affected through placentation, which occurs in3-72 the first trimester. Similarly, preterm delivery might be expected to be related to exposure early in pregnancy affecting placentation, or through acu te effects occurring just before delivery. Of three studies conducted in the U.S., one (Bell et al., 2007) reported a significant decrease in birthweight associated with exposure to NO 2 among mothers in Connecticut and Massachusetts. The two studies conducted in California did not find associations between NO 2 exposure and any adverse birth outcome (Ritz et al., 2000; Salam et al., 2005). Differences in these studies that may have contributed to the differences in results included the following: sample size, exposure assessment methods, average NO 2 concentration, and different pollution mixtures. The r esults reported by Bell et al. (2007) had the largest sample size and, therefore, greater power to assess small increases in risk. The two California studies reported higher mean concentrations of NO, but also strong correlations of NO 2 exposure with PM mass and CO. Annex Table AX6.3-12 lists seven studies that investigated the relationship of ambient NO 2 exposure with birth weight. Since low birth weight ma y result from either inadequate growth in utero or delivery before the usual 40 weeks of gestation, thr ee of the authors only considered low birth weight (<2500 g [5 lbs, 8 oz]) in full-term deliveries (>37 week s); the other four controlled for gestational age in the analysis. When correlations with other pollutant s were reported in these studies, they ranged from 0.5 to 0.8. All of these studies reported strong effects for other pollutants. Lee et al. (2003) reported a significant association between NO 2 and low birth weight, and the association was only for exposure in the second trimester. It is difficult to hypothesize any biological mechanism relating NO 2 exposure and fetal growth specifically in the second trimester. Bell et al. (2007) reported an increased risk of low birth weight with NO 2 exposure averaged over pregnancy (OR=1.027 [95% CI: 1.002, 1.051]) and a deficit in birthweight speci fic to the first trimester. In addition, the deficit in birthweight appeared to be greater among black mothers (-12.7 g per IQR increase in NO 2 [95% CI: -18.0, -7.5]) than for white mo thers (-8.3 g per IQR increase in NO 2 [95% CI: -10.4, -6.3]). Six studies investigated NO 2 exposure related to preterm deliv ery (Annex Table AX6.3-13). Three reported positive associations (Bobak, 2000; Maroziene and Grazuleviciene, 2002; Leem et al., 2006) and three reported no association (Liu et al., 2003; Ritz et al., 2000; Hansen et al., 2006). Among the studies reporting an association, two (Bobak, 2000; Leem et al., 2006) reported significant associations for both the first trimester and the third trimester of pregna ncy. The third (Maroziene and Grazuleviciene, 2002) reported significant increases in risk for exposure in the first trimester and averaged over all of pregnancy. In two (Bobak, 2000; Leem et al., 2006) of the positive studies, NO 2 exposure was correlated with SO 2 exposure (r=0.54, 0.61 for the two studies); th e third study did not report correlations. Three studies (see Annex Table AX6.3-14) specifically investigated fetal growth by comparing birth weight for gestational age with national st andards. Two of these studies reported associations between small for gestational age and NO 2 exposure. Mannes et al. (2005) determined increased risk for exposure in trimesters 2 and 3, while Liu et al. (2003) reported risks associated only with NO 2 exposure in the first month of pregnancy. In all three studies, NO 2 exposure was correlated with CO exposure (r=0.69, 0.57, 0.72 in the three studies) (Salam et al., 2005; Mannes et al., 2004; Liu et al., 2003). Two additional epidemiologic studies found that NO 2 concentrations were associated with hospitalization for respiratory disease in the neonatal period (Dales et al., 2006) and sudden infant death syndrome (SIDS) (Dales et al, 2004). Only a few studies have investigated the effects of NO 2 on reproduction and development toxicology. Exposure to 1 ppm NO 2 for 7 h/day, 5 days/week for 21 da ys resulted in no alterations in spermatogenesis, germinal cells, or interstitial cells of the testes of 6 rats (Kripke and Sherwin, 1984). Similarly, breeding studies by Shalamberidze and Tsereteli (1971) found that long-term NO 2 exposure had no effect on fertility. However, there was a sta tistically significant decrease in litter size and neonatal weight when male and female rats exposed to 1.3 ppm NO 2 , 12 h/day for 3 months were bred. In utero death due to NO 2 exposure resulted in smaller litter sizes, but no direct teratogenic effects were observed in the offspring. In fact, after several weeks, NO 2 -exposed litters approached weights similar to those of controls.3-73 Following inhalation exposure of pregnant Wistar rats to 0.5 and 5.3 ppm NO 2 for 6 h/day throughout gestation (21 days), maternal toxic eff ects and developmental disturbances in the progeny were reported (Tabacova et al., 1985; Balabaeva a nd Tabacova, 1985; Tabacova and Balabaeva, 1988). Maternal weight gain during gestation was significantly reduced at 5.3 ppm, with findings of pathological changes, e.g., desquamative bronchitis and bronchio litis in the lung, mild parenchymal dystrophy and reduction of glycogen in the liver, and blood stasis a nd inflammatory reaction in the placenta. At gross examination, the placentas of the high-dose dams were smaller in size than those of control rats. A marked increase of lipid peroxides was found in matern al lungs and particularly in the placenta at both exposure levels by the end of gestation (Balabaev a and Tabacova, 1985). Disturbances in the prenatal development of the progeny were reported, such as 2- to 4-fold increase in late post-implantation lethality at 0.5 and 5.3 ppm, respectively, as well as reduced feta l weight at term and stunted growth at 5.3 ppm. These effects were significantly related to the cont ent of lipid peroxides in the placenta, which was indicative of a pathogenetic role of placental damage . Teratogenic effects were not observed, but dosedependent morphological signs of embryotoxicity a nd retarded intrauterine development, such as generalized edema, subcutaneous hematoma, retarded ossification, and skeletal aberrations, were found at both exposure levels. In a developmental neurotoxicity study, Wistar rats were exposed by inhalation to 0, 0.025, 0.05, 0.5, or 5.3-ppm NO 2 during gestational days 0 through 21. Mate rnal toxicity was not reported. Viability and physical development (i.e., incisor eruption and ey e opening) were significantly affected only in the high dose group. There was a concentration-dependent change in neurobehavioral endpoints such as disturbances in early neuromotor development, in cluding coordination deficits, retarded locomotor development, and decreased activity and reactivity. Sta tistical significance was observed in some or all of the developmental endpoints at the time point(s) measure d in the 0.05, 0.5, and 5.3 ppm exposure groups. Di Giovanni et al. (1994) investigated whether in utero exposure of rats to NO 2 changed ultrasonic vocalization, a behavioral response indicator of the development of emotionality. Pregnant Wistar female rats were exposed by inhala tion to 0, 1.5, and 3 ppm NO 2 from day 0 to 20 of gestation. Dam weight gain, pregnancy length, litter size at birth, number of da ms giving birth, and postnatal mortality were unaffected by NO 2 . There was a significant decrease in the duration of ultrasonic signals elicited by the removal of the pups from the nest in the 10- day and 15-day-old male pups in the 3 ppm NO 2 group. No other parameters of offspring ultrasonic emission, or of motor activity, were significantly affected. Since prenatal exposure to NO 2 did not significantly influence the rate of calling, the authors concluded that the decrease in the duration of ultrasounds did not necessarily indicate altered emotionality, and the biological application of these findings remains to be determined.



## 3.5.2.1. Summary of Reproductive and Developmental Effects Related to Long-Term Exposure

In summary, the epidemiologic evidence did not consistently report associations between NO 2 exposure and intrauterine growth retardation; however, some evidence is accumulating for effects on preterm delivery. Similarly, scant animal ev idence supported a weak association between NO 2 exposure and adverse birth outcomes and provided little mechanis tic information or biological plausibility for an association between long-term NO 2 exposure and reproductive or developmental effects.



# 3.5.3. Summary of Other Morbidity Effects Related to Long-Term Exposure

Epidemiologic and toxicological studies eval uating limited evidence of cancer incidence, cardiovascular effects, and reproductive and de velopmental effects linked to long-term NO 2 exposure were presented. The epidemiologic studies report some associations between long-term NO 2 exposure on3-74 adverse birth outcomes and cancer incidence; however, NO 2 is specifically used as an indicator of traffic exposure in the studies of cancer incidence. Animal studies did not provide mechanistic information to support these observational findings. Some toxicological studies demonstrated an effect of NO 2 exposure on cardiovascular endpoints. However, whether these effects are the direct result of NO 2 exposure or secondary responses to lung edema and changes in blood hemoglobin content are not known. Similar findings were reported in the epidemiologic literature for short-term exposures only. Thus, while some individual associations may be reported for these effect s, the findings are inconsistent and there is no evidence supporting coherence or plausibility in the data . Overall, these data are inadequate to infer the presence or absence of a causal relationship.



# 3.6. Mortality Related to Long-Term Exposure

No studies of mortality associated with long-term NO 2 exposure were evaluated in the 1993 AQCD. More recently, there have been several studies that examined mortality associations with long-term exposure to air pollution, including NO 2 , using Cox proportional hazar ds regression models with adjustment for potential confounders. The U.S. studies tended to focus on effects of PM, while the European studies tended to investigate the in fluence of traffic-related air pollution.



# 3.6.1. U.S. Studies on Mortality Related to Long-Term Exposure

Dockery et al. (1993) conducted a prospective cohort study to examine the effects of air pollution, focusing on PM components, in six U.S. cities, whic h were chosen based on the levels of air pollution (with Portage, WI being the least polluted and Steube nville, OH, the most polluted). In this study, a 14-to16-year mortality follow-up of 8,111 adults in the six cities was conducted. Fine particles were the strongest predictor of mortality; NO 2 was not analyzed in this study. Krewski et al. (2000) conducted a sensitivity analysis of the Harvard Six Cities study and examined associations between gaseous pollutants (i.e., O 3 , NO 2 , SO 2 , CO) and mortality. NO 2 showed risk estimates similar to those for PM 2.5 per “low to high” range increment with total (1.15 [95% CI: 1.04, 1.27] per 10-ppb increase), cardiopulmonary (1.17 [95% CI: 1.02, 1.34]), and lung cancer (1.09 [95% CI : 0.76, 1.57]) deaths; however, in this dataset NO 2 was highly correlated with PM 2.5 (r=0.78), SO 4 2– (r=0.78), and SO 2 (r=0.84). Pope et al. (1995) examined PM effects on mortality using the American Cancer Society (ACS) cohort. Air pollution data from 151 U.S. metropolita n areas in 1980 were linked with individual risk factors in 552,138 adults who resided in these areas wh en enrolled in the study in 1982. Mortality was followed up until 1989. As with the Harvard Six Cities Study, the main hypothesis of this study was focused on fine particles and SO 4 2– , and gaseous pollutants were not analyzed. Krewski et al. (2000) examined association between gaseous pollutants (mean s by season) and mortality in the Pope et al. (1995) study data set. NO 2 showed weak but negative associations with total and cardiopulmonary deaths using either seasonal means. An extended study of the ACS cohort doubled the follow-up time (to 1998) and tripled the number of deaths compared to the original study (Pope et al., 2002). In addition to PM 2.5 , all the gaseous pollutants were examined. SO 2 was associated with all the mortality outcomes (including all other cause of deaths), but NO 2 showed no associations with the mortality outcomes (RR=1.00 [95% CI: 0.98, 1.02] per 10-ppb increase in multiyear average NO 2 ). Lipfert et al. (2000a) conducted an analysis of a national cohort of ~70,000 male U.S. military veterans who were diagnosed as hypertensive in the mid 1970s and were followed up for about 21 years (up to 1996). This cohort was 35% black and 81% ha d been smokers at one time. Thus, unlike other cohort studies described in this section, this hypert ensive cohort with a very high smoking rate is not representative of the U.S. population. Total suspended particulates (TSP), PM 10 , CO, O 3 , NO 2 , SO 2 , SO 4 2

, PM 2.5 , and PM 10 -2.5 were considered. The county of residence at the time of entry to the study was used3-75 to estimate exposures. Four exposure peri ods (1960-1974, 1975-1981, 1982- 1988, and 1989-1996) were defined, and deaths during each of the three most r ecent exposure periods were considered. Lipfert et al. (2000a) noted that the pollution risk estimates were sensitive to the regression model specification, exposure periods, and the inclusion of ecological a nd individual variables. The authors reported that indications of concurrent mortality risks were found for NO 2 (the estimate was not given with confidence bands) and peak O 3 . Their subsequent analysis (Lipfert et al., 2003) reported that the air pollutionmortality associations were not sensitive to the adju stment for blood pressure. Lipfert et al. (2006a) also examined associations between traffic density and mortality in the same cohort, whose follow-up period was extended to 2001. They reported that traffic dens ity was a better predictor of mortality than the ambient air pollution variables, with the possible exception of O 3 . The log-transformed traffic density variable was moderately correlated with NO 2 (r=0.48) and PM 2.5 (r=0.50) in this data set. For the 1989 to 1996 data period (the period that ge nerally showed the strongest associations with exposure variables among the four periods), the estimated mortality relative risk for NO 2 was 1.025 (95% CI: 0.983, 1.068) per 10-ppb increase in a single-pollutant model. The two- pollutant model with the traffic density variable reduced NO 2 risk estimates to 0.996 (95% CI: 0.954, 1.040). Interestingly, as the investigators pointed out, the risk estimates due to traffic density did not vary appreciably across these four periods. They speculated that other environmental factors such as pa rticles from tire, traffic noise, spatial gradients in socioeconomic status might have been involved. Lipf ert et al. (2006b) further extended analysis of the veteran’s cohort data to include one year of the EPA’s Speciation Trends Ne twork (STN) data, which collected chemical components of PM 2.5 . As in the previous Lipfert et al. (2006a) study, traffic density was the most important predictor of mortality, but associations were also seen for EC, vanadium, NO 3 –, and nickel. NO 2 , O 3 , and PM 10 also showed positive but weaker associations. The risk estimate for NO 2 was 1.043 (95% CI: 0.967, 1.125) per 10-ppb increase in a single-pollutant model. Multipollutant model results were not presented for NO 2 in this updated analysis. The results from the series of studies by Lipfert et al. are indicative of a traffic-related ai r pollution effect on mortality, but the study population (hypertensive with very high smoking rate) was not representative of the general U.S. population. Abbey et al. (1999) investigated associations be tween long-term ambient concentrations of PM 10 , O 3 , NO 2 , SO 2 , and CO (1973 to 1992) and mortality ( 1977 to 1992) in a cohort of 6,338 nonsmoking California Seventh-day Adventists. Monthly indices of ambient air pollutant concentrations at 348 monitoring stations throughout California were interpol ated to ZIP code centroids according to home or work location histories of study participants, cumu lated, and then averaged over time. They reported associations between PM 10 and total mortality for males and nonmalignant respiratory mortality for both sexes. NO 2 was not associated with all-cause, cardiopulmonary, or respiratory mortality for either sex. Lung cancer mortality showed large risk estimates for mo st of the pollutants in either or both sexes, but the number of lung cancer deaths in this cohort was very small (12 for female and 18 for male); therefore, it was difficult to interpret these estimates. When comparing the results of the U.S. studies mentioned above, differences in study population characteristics and geographic unit of averaging for pollution exposure estimates need to be considered. Most of the U.S. studies used a “semi-individual” st udy design, in which information on health outcomes and potential confounders were collected and adjusted for on an individual basis, but community-level air pollution exposure estimates were used. It is not clear to what extent exposure error affects these types of studies. Unlike regional air pollutants (e.g., SO 4 2– , PM 2.5 ) in the eastern U.S. whose levels are generally uniform within the scale of the metropolitan area, th e within-city variation for more locally-impacted pollutants such as NO 2 , SO 2 , and CO are likely to be larger and, therefore, are more likely to have larger exposure errors in the semi-individual studies. Th e smaller number of monitors available for NO 2 in the U.S. may make the relative error worse for NO 2 compared to other pollutants. Exposure error in these long-term exposure studies likely contributes to the in consistencies observed across studies. For example, the ACS study found no associations with NO 2 ; however, NO 2 was among the pollutants that showed associations with mortality in the veterans’ study, w ith traffic density showing the strongest association. The geographic resolution of air pollution exposur e estimation varied in these studies: MSA-level3-76 averaging in the ACS study and county-level averagi ng in the veterans’ study. Traffic density and other pollutants that showed mortality associations in the veterans study, including EC and NO 2 , were more localized pollutants; therefore, using county-level aggr egation, rather than MSA-level, may have resulted in smaller exposure misclassification.



# 3.6.2. European Studies on Mortality Related to Long-Term Exposure

In contrast to the U.S. studies described above, the European studies described below, have more spatially-resolved exposure estimates, because their hy potheses or study designs were evaluating effects of related air pollution. Only one study from France (Filleul et al., 2005) used a design similar to the Harvard Six Cities study or ACS in that it did not study traffic-related air pollution and the exposure estimate was not done on an individual basis. Hoek et al. (2002) investigated a random sample of 5,000 subjects from the Netherlands Cohort Study on Diet and Cancer (NLCS) ages 55 to 69 from 1986 to 1994. Long-term expos ure to traffic-related air pollutants (black smoke and NO 2 ) was estimated using 1986 home addresses. Exposure was estimated with the measured regional and urban background concentr ation and an indicator variable for living near major roads. Cardiopulmonary mortality was associated with living near a major road (RR=1.95 [95% CI: 1.09, 3.52]) and less strongly with the estimated air pollution levels (e.g., for NO 2 , RR=1.32 [95% CI: 0.88, 1.98] per 10-ppb increase). The risk estimate for living near a major road was 1.41 (95% CI: 0.94, 2.12) for total mortality. For estimated NO 2 (incorporating both background and local impact), the RR was 1.15 (95% CI: 0.60, 2.23) per 10-ppb increase). Because the NO 2 exposure estimates were modeled, interpretation of their risk estimates was not strai ghtforward. However, these results did support that NO 2 , as a marker of traffic-related air pollution, was associated with these mortality outcomes. Filleul et al. (2005) investigated long-term effect s of air pollution on mortality in 14,284 adults who resided in 24 areas from seven French cities when en rolled in the PAARC survey (for air pollution and chronic respiratory diseases) in 1974. Models were run before and after exclusion of six area monitors influenced by local traffic as determined by the NO/NO 2 ratio of >3. Before exclusion of the six areas, none of the air pollutants were associated with mo rtality outcomes. After exclusion of these areas, analyses showed associations between total mortality and TSP, black smoke, NO 2 , and NO. The estimated NO 2 risks were 1.28 (95% CI: 1.07, 1.55), 1.58 (95% CI: 1.07, 2.33), and 2.12 (95% CI: 1.11, 4.03) per 10-ppb increase in NO 2 mean over the study period for total, cardiopulmonary, and lung cancer mortality, respectively. From these results, the authors noted th at inclusion of air monitoring data from stations directly influenced by local traffic could overes timate the mean population exposure and bias the results. This point raised a concern for NO 2 exposure estimates used in other studies (e.g., ACS) in which the average of available monitors was used to repr esent the exposure of each city’s entire population. Nafstad et al. (2004) investigated the associati on between mortality and long-term air pollution exposure in a cohort of 16,209 Norwegian me n followed from 1972/1973 through 1998. PM was not considered in this study because measurement methods changed during the study period. NO X , rather than NO 2 , was used. Exposure estimates for NO X and SO 2 were constructed using models based on subjects’ addresses and emission data for industry, heating, and traffic measured concentrations. Addresses linked to 50 of the busiest streets were given an additi onal exposure based on estimates of annual average daily traffic. The adjusted risk estimate for total mort ality was 1.16 [95% CI: 1.12, 1.22] for a 10-ppb increase in the estimated exposure to NO X . Corresponding mortality risk estimates for respiratory causes other than lung cancer was 1.16 (95% CI: 1.06, 1.26); for lung cancer, 1.11 (95% CI: 1.03, 1.19); and for ischemic heart diseases, 1.08 (95% CI: 1.03, 1.12). SO 2 did not show similar associations. The risk estimates presented for categorical levels of these po llutants showed mostly monotonic exposure-response relationships for NO X . These results are indicative of the effects of traffic-related air pollution on longterm mortality, but NO X likely represented the combined effects of that source, possibly including PM, which could not be analyzed in this study. A case-control study of 1,043 men aged 40 to 75 with lung cancer and 2,364 controls in Stockholm County (Nyber g et al., 2000) reported similar results to this3-77 study. They mapped residence addresses to a GIS da tabase indicating 4,300 traffic-related line sources and 500 point sources of NO 2 exposure. Exposure was derived from a model validated by comparison to actual measurements of NO 2 at six sites. Exposure to 10 ppb NO 2 was associated with an OR of 1.20 (95% CI: 0.94 1.49). Exposure to the 90th percentile ( ≥ 29.26 μg/m 3 915.5 ppb]) of NO 2 was associated with an OR of 1.44 (95% CI: 1.05, 1.99). Gehring et al. (2006) investigated the relations hip between long-term exposure to air pollution originating from traffic and industrial sources, and to tal and cause-specific mortality in a cohort of women living in North Rhine-Westphalia, Germany. The area in cludes the Ruhr region, one of Europe’s largest industrial areas. Approximately 4,800 women (age 50 to 59 years) were followed for vital status and migration. Exposure to air pollution was estimated by GIS models using the distance to major roads, NO 2 , and PM 10 (estimated from 0.71 X TSP, based on available PM 10 and TSP data in the area) concentrations from air monitoring station data. Cardiopulmonary mortality was associated with living within a 50-m radius of a major road (RR=1.70 [95% CI: 1.02, 2.81]) and NO 2 (RR=1.72 [95% CI: 1.28, 2.29] per 10-ppb increase in annual average). Exposure to NO 2 was also associated with all-cause mortality (1.21 [95% CI: 1.03, 1.42] per 10 ppb increase). NO 2 was generally more strongly associated with mortality than the indicator for living near a major road (within versus beyond a 50-m radius) or PM 10 . Næss et al. (2007) investigated the concentration -response relationships between air pollution (i.e., NO 2 , PM 10 , PM 2.5 ) and cause-specific mortality using all the inhabitants of Oslo, Norway, aged 51 to 90 years on January 1, 1992 (n=143,842), with follow-up of deaths from 1992 to 1998. An air dispersion model was used to estimate the air pollution levels for 1992 through 1995 in all 470 administrative neighborhoods. Correlations among these pollutants were high (range 0.88 to 0.95). All causes of deaths, cardiovascular causes, lung cancer, and COPD were associat ed with all indicators of air pollution for both sexes and both age groups. The investigators reporte d that the effects appeared to increase at NO 2 levels higher than 40 μg/m 3 (21 ppb) in the younger age (51 to 70 years) group and with a linear effect in the interval of 20 to 60 μg/m 3 (10 to 31 ppb) for the older age group (see Figure 3.6-1). However, they also noted that a similar pattern was found for both PM 2.5 and PM 10 . Thus, the apparent threshold effect was not unique to NO 2 . NO 2 risk estimates for all-cause mortality were presented only in a figure. The findings are generally consistent with those from the Nafstad et al. (2003, 2004) studies, in which a smaller number of male-only subjects were analyzed. While NO 2 effects were demonstrated, the high correlation among the PM indices and NO 2 or NO X made it difficult to confidently ascribe these associations to NO 2 /NO X alone. Most of the European cohort studies estimated an individual subject’s exposure based on spatial modeling using emission and concentration data . These studies may have provided more accurate exposure estimates than the community-level air pollu tion estimates typically used in the U.S. studies. However, because they generally involved modeling w ith such information as traffic volume and other emission estimates in addition to monitored concen trations, additional uncertainties may have been introduced. Thus, validity and comparability of various methods may need to be examined. In addition, because the relationship between the concentration m easured at the community monitors and the health effects was ultimately of interest in this ISA, in terpreting the risk estimates based on individual-level exposures will require an additional step to translat e the difference. Finally, a more accurate exposure estimate does not solve the problem of the surrogate role that NO 2 may play. Most of these studies did acknowledge this issue and generally treated NO 2 as a surrogate marker, but the extent of such surrogacy and confounding with other traffic- or combustion-related pollutant was not clear at this point. In the Hoek et al. study (2002), the indicator of living near a major road was a better predictor of mortality than the estimated NO 2 exposures. In the Gehring et al. (2006) study, the estimated NO 2 exposure was a better predictor of total and cardiopulmonary mortality than the indicator of living near a major road. Comparing the results for the indicators of liv ing near a major road and the estimated NO 2 or NO X exposures is not straightforward, but it is possibl e that, depending on the presence of other combustion sources (e.g., the North Rhine-Westphalia area included highly industrial areas), NO 2 may represent more than traffic-related pollution.3-78 Source: Næss et al. (2007).
Figure 3.6-1. Age-adjusted, nonparametr ic smoothed relationship between NO 2 and mortality from all causes in Oslo, Norway, 1992 through 1995.



# 3.6.3. Summary of Mortality Related to Long-Term Exposure

Figure 3.6-2 summarizes the NO 2 relative risk estimates for total mortality from the studies reviewed in the previous sections. The relative riskestimates are grouped by those that used communityor ecologic-level exposure estimates and those that used individual-level exposure estimates, but because of the small number of studies listed, no systematic pattern could be elucidated. The relative risk estimates for total mortality ranged from 1.0 to 1.28 per 10-ppb increase in annual or longer averages of NO 2 . Potential confounding by copollutants needs to be considered in the interpretation of the NO 2 risk estimates. Not all of the studies presented correlations between NO 2 and other pollutants, but those that did indicated generally moderate to high correlati ons. For example, in the Harvard Six Cities study (Krewski et al, 2000), the French study (Filleul et al., 2005), and the German study (Gehring et al., 2006), the correlation between NO 2 and PM indices ranged from 0.72 to 0.8. The high correlations between NO 2 and PM indicated possible confounding between th ese pollutants. Further, the results from the Netherlands study (Hoek et al., 2002), that living near major roads was more strongly associated with mortality than NO 2 , supported a possible surrogate role of NO 2 as a marker of traffic-related pollution. However, this does not preclude the possibility of NO 2 playing a role in interactions among the trafficrelated pollutants. Essentially no information was available on the possible effect modification of apparent NO 2 -mortalty associations.3-79 Figure 3.6-2. Total mortality relative risk estimates fr om long-term studies. The original estimate for the Norwegian study was estimated for NO X . Conversion of NO 2 =0.35 X NO X was used.

Available information on risk estimates for more specific causes of death with long-term exposure to NO 2 was sparse. Among the studies with larger number of subjects, the ACS study (Pope et al., 2002) examined cardiopulmonary and lung cancer deaths, but as with the all-cause deaths, they were not associated with NO 2 . In the Næss et al. (2007) analysis of all inhabitants of Oslo, Norway, NO 2 relative risk estimates for COPD were higher than those fo r other causes, but the same pattern was seen for PM 2.5 and PM 10 . In the German study by Gehring et al. (2006), NO 2 relative risk estimates for cardiopulmonary mortality were larger than those for all-cause mo rtality, but, again, the same pattern was seen for PM 10 . Thus, higher risk estimates seen for specific causes of deaths were not specific to NO 2 in these studies. In long-term exposure studies, different geogra phic scales were used to estimate air pollution exposure estimates across studies. Since the relative strength of association with health outcomes among various air pollutant indices may have been affected by the spatial distribution of the pollutants (i.e., regional versus local), the numbers of monitors availa ble, and the scale of aggregation in the study design, it was not clear how these factors affected the apparent difference in results.3-80 In the U.S. and European cohort studies examini ng the relationship between long-term exposure to NO 2 and mortality, results were genera lly not consistent. Further, when associations were suggestive, they were not specific to NO 2 , also implicating PM and other traffic indicators. The relatively high correlations reported between NO 2 and PM indices (r ~0.8) and the unresolved issue of surrogacy and interactions make it difficult to interpret the observed associati ons; thus, these data are inadequate to infer the presence or absence of a causal relationship.4-1 

# Chapter 4. Public Health Impact

This chapter discusses several issues relating to th e broader public health impact of exposure to NO X . First, concepts related to defining adverse hea lth effects are discussed. Second, the concentrationresponse relationship for NO 2 and evidence for thresholds (the concentration of NO 2 that must be exceeded to elicit a health response) are discussed, with consideration of the limited evidence available to assess individual and population threshold values for health effects. The next section identifies characteristics of subpopulations that may experience increased risks from NO 2 exposures, through either enhanced susceptibility (i.e., as a result of an intr insic condition such as pre-existing disease, genetic factors, age) and/or differential vulnerability associ ated with increased exposure (e.g. residing close to roadways). In the final section the size of the pot entially susceptible and vulnerable populations in the U.S. is discussed.



# 4.1. Defining Adverse Health Effects

A recent American Thoracic Society (ATS) statement (ATS, 2000b) updated the guidance for defining adverse respiratory health effects publis hed 15 years earlier (ATS, 1985), taking into account new investigative approaches used to identify the effects of air pollution and reflecting concern for impacts of air pollution on specific susceptible groups . In the 2000 update, there was an increased focus on quality-of-life measures as indicators of adversity a nd a more specific consideration of population risk. An increased risk to the entire population was iden tified as adverse, even though it may not increase the risk of any identifiable individual to an unacceptable level (ATS, 2000b). For example, a population of asthmatics could have a distribution of lung functi on such that no individual demonstrates impairment. Exposure to air pollution could adversely shift the distri bution,without demonstrable clinical effects. This distribution shift would be considered adverse b ecause individuals would have diminished reserve function, putting them at increased risk if affect ed by another agent or as a result of aging. The 2006 Ozone AQCD (U.S. Environmental Prot ection Agency, 2006a) provided information useful in helping to define adverse h ealth effects associated with ambient O 3 exposure by describing the gradation of severity of respiratory effects. The defin itions that relate to responses in impaired persons are presented in Table 4.1-1. The severity of effects descr ibed in the table is valid and reasonable in the context of the new ATS (2000b) statement, and can be applied to NO 2 exposure. As assessed in detail in Chapter 3, Section 3.1, exposures to a range of NO 2 concentrations have been reported to be associated with increased severity of health effects, such as respiratory symptoms, ED visits and hospital admission for respiratory causes. The adverse effects associated with NO 2 exposure are anticipated to lead to a shift in the population dist ribution of reserve capacity for exposed individuals, and/or increase the proportion of severe responses acr oss a broad spectrum of respiratory outcomes. These adverse outcomes have the potential to impair the quality of life among those affected.4-2 Table 4.1-1. Gradation of individual responses to short-term NO 2 exposure in persons with impaired respiratory systems.

SYMPTOMATIC

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 h 4 – 24 h >24 h

FUNCTIONAL RESPONSE NONE SMALL MODERATE LARGE

FEV 1 change Decrements of <3% Decrements of 3 -10% Decrements of 10-20% Decrements of ≥ 20%

Bronchial responsiveness Within normal range Increases of <100% Increases of 100- 300% Increases of >300%

Specific airway resistance (sRaw) Within normal range (± 20%) sRaw increased <100% sRaw increased 100-200% or up to 15 cm H 2 O x s sRaw increased >200% or more than 15 cm H 2 O x s

Duration of response None <4 h 4 – 24 h >24 h

IMPACT OF RESPONSES NORMAL MILD MODERATE SEVERE

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

Medical treatment No change Normal medication as needed Increased frequency of medication use or additional medication Physician or emergency department visit

An increase in bronchial responsiveness of 100% is equivalent to a 50% decrease in provocativ e dose that produces a 20% decreas e in FEV 1 (PD20) or provocative dose that produces a 100% increase in sRaw (PD100). Source: This table is adapted from the 2006 O 3 AQCD (Table 8-3, page 8-68) (U.S. Environmental Protection Agency, 2006a).



# 4.2. Concentration-Response Functions and Potential Thresholds

An important consideration in characterizing the public health impacts associated with NO 2 exposure is whether the concentration-response relati onship is linear across the full concentration range encountered or if nonlinear departures exist along any part of this range. Of particular interest is the shape of the concentration-response curve at and below th e level of the current annual average standard of 0.053 ppm (53 ppb). Human clinical studies typically provide individua l-level response data in relation to different levels of NO 2 . The percentage of individuals showing responses across a range of NO 2 exposures, the interindividual variability in response and the concentr ation at which an individual begins to respond can often be determined based on these studies. The pr evious assessment concluded that human clinical studies provided evidence that some asthmatics are more susceptible to the effects of NO 2 but a concentration-response relationship was not evid ent (U.S. Environmental Protection Agency, 1993). Findings from recent human clinical studies do not provide evidence that would change the previous conclusion (see Chapter 3). Inconsistencies in clini cal findings could be due to a sensitive subpopulation4-3 not well represented in human clinical studies or pecu liarities in protocols necessary to elicit a response. Such peculiarities might include an unanticipated time course for a response not well captured in human clinical studies or other factors that influence a res ponse that may not be measured in all human clinical studies (i.e., prior allergen sensitization by allergen or infectious agent). Epidemiologic studies evaluate population-level r esponses, rather than individual responses. Low data density in the lower concentration range, res ponse measurement error, exposure measurement error, and a shallow slope are some of the factors that co mplicated the ability to de termine the shape of the concentration-response curve. A sigmoidal or S-sh aped curve with a shallow slope may approximate linearity over a wide range of concentrations, making it difficult to characterize the exact nature of the concentration-response relationship. Biological char acteristics that tend to linerarize concentrationresponse relationships include inter-i ndividual variability, additivity of NO 2 - induced effects to a naturally occurring background of disease, and additivity to e ffects induced by other pollutant exposures. Epidemiologic studies are generally consistent w ith a linear or log linear relationship between ambient NO 2 concentration and the health out come; however the shape of the NO 2 concentration-response relationship has only been explored in several studies. To examine the shape of the concentrationresponse relationship between NO 2 and daily physician consultations for asthma and lower respiratory disease in children, Hajat et al. (1999) used bubble pl ots to examine residuals of significant models plotted against moving averages of NO 2 concentration. They noted a weak trend for asthma and 0-1 day moving average lag of NO 2 and proposed that effects are weaker at lower concentrations and stronger at higher concentrations than predicted by the linear m odel. These departures were in accord with the shape of the sigmoidal dose-response model below the median effective dosage. Several studies of ED visits or hospitalizations for cardiac or respiratory disease examined the shape of the concentration-respon se curve. Burnett et al. (1997a) used the locally estimated smoothing splines (LOESS) to describe the concentration-respon se for respiratory and cardiac hospitalizations for the summers of 1992-94 in Toronto. Both graphs show ed a smaller slope at lower concentrations, but a chi-square test detected no significant difference be tween the LOESS and a linear effect. In another study of respiratory hospitalizations in 16 Canadian c ities, Burnett et al. (1997b) were unsuccessful in identifying the shape of the concentration-response func tion, i.e. a linear effect was not significant nor did inclusion of a quadratic term improve the fit of the m odel. In another study of hospitalizations for CHF in 10 Canadian cities, Burnett et al. (1997c) found that a logarithmic concentration-response model, which has a steeper slope at lower concentrations, provided th e best fit for the data compared to the other forms of the model examined. In a study among Medicaid-enro lled asthmatics in two urban cities in Ohio, Jaffe et al. (2003) found that when a concentration-res ponse relationship was examined by quintile of NO 2 concentration, no consistent pattern was found. Tenías et al. (1998) also reported no consistent pattern in their study of the association between ambient NO 2 and ED visits in Vale ncia’s Hospital Clìnic Universitari from 1994 to 1995. Castellsague et al . (1995) found a small but significant association of NO 2 and ED visits due to asthma in Barcelona. Specifi cally, the adjusted risk estimates of asthma visits for each quartile of NO 2 showed increased risks in each quartile for the summer months, but not the winter months. Together these studies indicate some disagreement in the trend of the concentrationresponse curve below 50 ppb 24 h NO 2 . Samoli et al. (2003) examined the relationship between mortality and NO 2 in a subset of 9 European cities out of 30 APHEA cities. The cities were selected to have overlapping NO 2 ranges to improve the detection of nonlinearity. They found the linear assumption to be adequate for these cities. Kim et al. (2004b) investigated non-linearity in rela tionships between air pollutants and mortality in Seoul, Korea, by analyzing data using a log-linear Generalized Additive Model (GAM; linear model), a cubic natural spline model (nonlinear model), and a B-mode splined model (threshold model). They did not detect a nonlinear association for NO 2 with mortality. In conclusion, of the epidemiology studies that a ttempted to look at the shape of the concentrationresponse below 50 ppb, one indicated that effects were weaker at lower levels (Hajat et al. 1999), and one showed a steeper log-linear relationship at lower do ses (Burnett et al. 1997c). The remainder found that a4-4 linear function best described the data (Burnett et al. 1997a,b; Jaffe et al. 2003; Tenias et al., 1998; Castellsague et al., 1995). These results do not provi de adequate evidence to suggest that nonlinear departures exist along any part of this range of NO 2 exposure concentrations. Evidence from human clinical studies has not helped to clarify understa nding of the concentration-response function of NO 2 (see chapter 3).



# 4.3. Susceptible and Vulnerable Populations

The NAAQS are intended to provide an adequate ma rgin of safety for both general populations and sensitive subpopulations, or those subgroups potentially at increased risk for ambient air pollution health effects. The term susceptibility generally encompasses i nnate or acquired factors that make individuals more likely to experience effects with exposure to po llutants. Genetic or developmental factors can lead to innate susceptibility, while acquired susceptibility may result from age, disease, or personal risk factors such as smoking, diet, or exercise. In addition, new attention has been paid to the concept of some population groups having increased vulnerability to pollu tion-related effects due to extrinsic factors including socioeconomic status (e.g., reduced access to health care) or particularly elevated exposure levels. Potentially susceptible and/ or vulnerable groups comprise a large fraction of the U.S. population. Given the likely heterogeneity of individual responses to air pollution, the severity of health effects experienced by a susceptible subgroup may be much gr eater than that experienced by the population at large (Zanobetti et al., 2000). Many factors such as genetic (Kleeberger et al ., 2005) and social (Gee and Payne-Sturges, 2006) determinants of disease may contribute to interindividual variability and heightened susceptibility to NO 2 . The previous NO X AQCD (U.S. Environmental Protection Agen cy, 1993) identified certain groups within the population that may be more susceptible to the effects of NO 2 exposure, including persons with preexisting respiratory disease, children, and olde r adults. Findings from recent studies supported the conclusions from the previous assessmen t with regard to susceptibility.



# 4.3.1. Preexisting Disease as a Potential Risk Factor

A recent report of the National Research Council (NRC) emphasized the need to evaluate the effect of air pollution on susceptible groups including tho se with respiratory illnesses and cardiovascular disease (CVD) (NRC, 2004). Generally, chronic obstructive pulmonary disease (COPD), conduction disorders, CHF, diabetes, and MI are conditions believed to put pe rsons at greater risk for adverse events associated with air pollution. In addition, epidemiologic evid ence indicates persons with airway hyperresponsiveness as determined by methacholine provocation may be at greater risk for symptoms such as phlegm and lower respiratory symptoms than subjects without airway hyperresponsiveness (Boezen et al., 1998). Several researchers have investigated the effect of air pollution among potentially sensitive groups with preexisting medical conditions.



## 4.3.1.1. Asthmatics

Evidence from epidemiologic studies shows an association between NO 2 exposure and children’s hospital admissions, ED visits, and calls to doc tors for asthma. This evidence came from large longitudinal studies, panel studies, and time-series studies. NO 2 exposure was associated with aggravation of asthma effects that include symptoms, medication use, and lung function. Effects of NO 2 on asthma were most evident with a cumulative lag of 2 to 6 days, rather than same-day levels of NO 2 . Time-series studies also demonstrated a relationship in children between hospital admissions or ED visits for asthma4-5 and NO 2 exposure, even after adjusting for copollutants such as PM and CO. Important evidence was also available from epidemiologic studies of indoor NO 2 exposures. A number of recent studies showed associations with wheeze, chest tightness, and length of symptoms (Belanger et al., 2006); respiratory symptom rates (Nitschke et al., 2006); school absences (Pilotto et al., 1997a); respiratory symptoms, likelihood of chest tightness, and asthma attacks (Smith et al., 2000); and severity of virus-induced asthma (Chauhan et al., 2003). However, several studies (Mukala et al., 1999, 2000; (Farrow et al., 1997) evaluating younger children found no association between indoor NO 2 and respiratory symptoms. Airway hyperresponsiveness in asthmatics to both nonspecific chemical and physical stimuli and to specific allergens appeared to be the mo st sensitive indicator of response to NO 2 (U.S. Environmental Protection Agency, 1993). Responsiveness is determin ed using a challenge agent, which causes an abnormal degree of constriction of the airways as a result of smooth muscle contraction. This response ranges from mild to severe (spanning orders of ma gnitude) and is often accompanied by production of sputum, cough, wheezing, shortness of breath, and ch est tightness. Though some asthmatics do not have this bronchoconstrictor response (Pattemore et al., 1990), increased airway hyperresponsiveness is correlated with asthma symptoms and increased asthma medication usage. Clinical studies reported increased airway hyperresponsiveness to allergen cha llenge in asthmatics following exposure to 0.26-ppm NO 2 for 30 min during rest (Barck et al., 2002; et al.; Strand et al., 1997; 1998). Toxicological studies provided biological plausibility that asthmatics are likely susceptible to the effects of NO 2 exposure. Numerous animal studies provide evidence that NO 2 can produce inflammation and lung permeability changes. These studies provided evidence for several mechanisms by which NO 2 exposure can induce effects, including reduced mucoc iliary clearance, and alveolar macrophage function such as depressed phagocytic activity and altered humor al- and cell-mediated immunity. Chauhan et al. (2003) reviewed potential mechanisms by which NO 2 exacerbates asthma in the presence of viral infections. These mechanisms included “direct e ffects on the upper and lower airway by ciliary dyskinesis, epithelial damage, increases in pro-infl ammatory mediators and cytokines, rises in IgE concentration, and interactions with allergens, or indirectly through impairment of bronchial immunity.” These are all mechanisms that can provide biological plausibility for the NO 2 effects in asthmatic children observed in epidemiologic studies. However, it must be noted that the experimental animal studies that looked at effects on markers of inflammation, such as BAL fluid levels of total protein and lactate dehydrogenase and recruitment or proliferation of leukocytes, occured only at exposure levels of ≥ 5 ppm. Studies conducted at these higher exposure concentrati ons may elicit mechanisms of action and effects that do not occur at near-ambient levels of NO 2 .



## 4.3.1.2. Cardiopulmonary Disease and Diabetes

While less evidence was available for these conditions, preexisting cardiovascular-related conditions may lead to heightened susceptibility to the effects of NO 2 exposure. Recent epidemiologic studies reported that persons with preexisting conditi ons may be at increased risk for adverse cardiac health events associated with ambient NO 2 concentrations (Peel et al., 2007; Mann et al., 2002; D’Ippoliti et al., 2003; von Klot et al., 2005). Peel et al. (2007) reported evidence of effect modification by comorbid hypertension and diabetes on the associa tion between ED visits for arrhythmia and NO 2 exposure. In another study, a statistically signi ficant positive relationship was reported between NO 2 concentrations and hospitalizations for IHD among t hose with prior diagnoses of CHF and arrhythmia (Mann et al., 2002). However, Mann et al. (2002) noted the vulnerability in the secondary CHF group could be due to increased prevalence of MI as the pr imary diagnosis in this group. In addition, these authors stated they were unable to distinguish the effects of NO 2 from other traffic pollutants (Mann et al., 2002). Von Klot et al. (2005) reported cardiac readmission among MI survivors was associated with NO 2 and this association was robust to adjustment for PM 10 . Modification of the association between NO 2 and MI by conduction disorders but not diabetes or hy pertension was observed by D’Ippoliti et al. (2003).4-6 Park et al. (2005b) examined the relationship of NO 2 and HRV among those with IHD, hypertension and diabetes but did not find an association. There was limited evidence from clinical or t oxicological studies on potential susceptibility to NO 2 in persons with CVD; however, the limited epidemio logic evidence indicated that these individuals may be more sensitive to effects of NO 2 exposure or air pollution in gene ral. Reductions in blood hemoglobin (~10%) have been reported in healthy subjects following exposure to NO 2 (1 to 2 ppm) for a few hours during intermittent exercise (Frampton et al., 2002). Th e clinical importance of hemoglobin reduction in persons with significant underlying lung disease, heart disease, or anemia has not been evaluated, but the reductions could lead to adverse cardiovascular c onsequences. These consequences would be exacerbated by concomitant exposure to CO, a combustion copollutant of NO 2 that binds to hemoglobin and reduces oxygen availability to tissues and organs.



# 4.3.2. Age as a Potential Risk Factor

Children and older adults (65+ years) are ofte n considered at increased risk from air pollution compared to the general population. The American A cademy of Pediatrics (2004) concluded that children and infants are among the most susceptible to many air pollutants, including NO 2 . Because 80% of alveoli are formed postnatally and changes in the lung continue through adolescence, the developing lung is highly susceptible to damage from exposure to environm ental toxicants (Dietert et al., 2000). In addition to children, older adults frequently are classified as being particularly susceptible to air pollution. The basis of the increased sensitivity in the elderly is not known, but one hypothesis is that it may be related to changes in the respiratory tract lining’s fluid an tioxidant defense network and/or to a decline in immune system surveillance or response (Kelly et al., 2003). The generally declining health status of many older adults may also increase their risks to air pollution-induced effects. Evidence showed that associations of NO 2 with both respiratory ED vis its and hospitalizations were stronger among children (Peel et al., 2005; Atkinson et al., 1999b; Fusco et al., 2001; Hinwood et al., 2006; Anderson et al., 1998) and older adults (Mig liaretti et al., 2005; Atkinson et al., 1999b; Schouten et al., 1996; Ponce de Leon et al., 1996; Prescott et al., 1998). However, two studies (Sunyer et al., 1997; Migliaretti et al., 2005) found no difference in the rates of ED visits associated with NO 2 concentrations for children (<15 years) and adults (15 to 64 years) . Luginaah et al. (2005) and Wong et al. (1999) found no statistically significant difference in the elderly and adult age groups. Many field studies focused on the effect of NO 2 on the respiratory health of children, while fewer field studies have compared the effect of NO 2 in adults and other age gr oups. In general, children and adults experienced decrements in lung func tion associated with short-term ambient NO 2 exposures (see Section 3.1.5). Importantly, a number of long-term expos ure studies indicated that effects in children that include impaired lung function growth, increased resp iratory symptoms and infections, and onset of asthma (see Section 3.4). In elderly populations, associations between NO 2 and hospitalizations or ED visits for CVD, including stroke, have been observed in several studies (Anderson et al., 2007a; Atkinson et al., 1999b; Jalaludin et al., 2006; Hinwood et al., 2005; Wong et al., 1999; Barnett et al., 2006; Zanobetti and Schwartz, 2006; Simpson et al., 2005a; Wellenius et al., 2005b; Morgan et al., 1998a; Morris et al., 1995). However, some results were inconsistent acro ss cities (Morris et al., 1995), and investigators could not distinguish the effect of NO 2 from the effect of other traffic-related pollutants such as PM and CO (Simpson et al., 2005a; Barnett et al., 2006; Morgan et al., 1998b; Jalaludin et al., 2006; Zanobetti and Schwartz, 2006). Several mortality studies investigated age-related differences in NO 2 effects. Among the studies that observed positive associations between NO 2 and mortality, a comparison of all-age– or ≤ 64-yearsof-age–group NO 2 -mortality risk estimates to that of the ≥ 65-years-of-age group indicated that, in general, the elderly population was more susceptible to NO 2 effects (Biggeri et al., 2005; Burnett et al.,4-7 2004). One study (Simpson et al., 2005a) found no difference in increases in CVD mortality associated with NO 2 concentrations between all ages and those participants of ≥ 65 years of age.



# 4.3.3. Gender as a Potential Risk Factor

A limited number of studies stratified results by gender. Lugninaah et al. (2005) found increases in hospital admissions associated with NO 2 among females but not males. In a study of children in Toronto, Canada, NO 2 was positively associated with asthma admissions among both boys and girls (Lin et al., 2005). However, in a study of asthma admissions among children in Vancouver, NO 2 was significantly and positively associated with asthma hospitalization only for boys in the low socioeconomic group (Lin et al., 2004). An increased association with asthma with exposure to traffic pollutants was observed for girls (Kim et al., 2004a). Decrements in FVC and FEV 1 growth associated with NO 2 were reported in male and female children in Mexico (Rojas-Martinez et al., 2007a,b).



# 4.3.4. Genetic Factors for Oxidant and Inflammatory Damage

A consensus now exists among epidemiologists that genetic factors related to health outcomes and ambient pollutant exposures merit serious consider ation (Kauffmann et al., 2004; Gilliland et al., 1999; ATS 2000b). Interindividual variation in human responses to air pollutants may indicate that that some subpopulations are at increased risk of detrimental effects from pollutant exposure, and it has become clear that genetic background is an important suscep tibility factor (Kleeberger, 2005). Several criteria must be satisfied in selecting and establishing useful links between polymorphisms in candidate genes and adverse respiratory effects. First, the product of the ca ndidate gene must be instrumentally involved in the pathogenesis of the adverse effect of interest, ofte n a complex trait with many determinants. Second, polymorphisms in the gene must produce a functional cha nge in either the protein product or in the level of expression of the protein. Third, in epidemiologic studies, the issue of confounding by other environmental exposures must be carefully considered. In general, work has focused on genes involved in oxidant and inflammation damage. Several glutathione S-transferase (GST) genes ha ve common, functionally important polymorphic alleles that affect host defense function in the lung (e.g., homozygosity for the null allele at the GSTM1 and GSTT1 loci, homozygosity for the A105G allele at the GSTP1 locus). GST genes are inducible by oxidative stress. Exposure to radicals and oxidants in air pollution induces decreased GSH that increases transcription of GSTs. Individuals with genotypes that result in enzymes with reduced or absent peroxide activity are likely to have reduced oxidant defe nses and potentially increased susceptibility to inhaled oxidants and radicals. Studies of genotype, respiratory health, and air po llution in general have been conducted (Lee et al., 2004; Gilliland et al., 2002; Gauderman et al., 2007). NO 2 -related genetic effects have been presented primarily by Romieu et al. (2006) and indicated that asthmatic children with GSTM1 null and GSTP1 Val/Val genotypes appear to be more susceptible to developing respiratory symptoms related to O 3 , but not NO 2 , concentrations. Though, it was hypothesized that ambient NO 2 concentrations may affect breathing in general in children regardless of th eir GSTM1 or GSTP1 genotypes, GSTM1-positive and GSTP1 Ile/Ile- and Ile/Val-genotype children were more likely to experience cough and bronchodilator use, specifically in response to NO 2 than GSTM1-null and GSTP1-Val/Val children. Contrary to expectations, a 20-ppb increase in ambient NO 2 concentrations was associated with a decrease in bronchodilator use among GSTP1 Val/Val-genotype children. It remains plausible that there are genetic factors that can influence health responses to NO 2 , though the few available studies did not provide specific support for genetic susceptibility to NO 2 exposure.4-8 

# 4.3.5. Other Potentially Susceptible Populations

Although data specific to NO 2 exposures was lacking for many of the susceptibility factors listed below, several potentially susceptible groups deserve specific mention in this document. These include individuals in a chronic pro-inflammatory state (e.g ., diabetics), obesity, and children born prematurely or with low birth weight. Factors that may influence susceptibility or vulnerability are:



## Susceptibility Factors

 Age, Gender

 Adverse birth outcomes: e.g., preterm birth, low birth weight, growth restriction, birth defects

 Race/ethnicity

 Genetic factors

 Pre-existing disease, e.g., diabetes

 Obesity

 Respiratory diseases, e.g., asthma, COPD

 Cardiovascular diseases 

## Vulnerability Factors

 Socioeconomic status

 Education level

 Air conditioning Use

 Proximity to Roadways

 Geographic Location (West vs. East)

 Level of Exercise

 Work Environment (e.g., outdoor workers)

Chronic inflammation appears to enhance suscep tibility for air pollution-related cardiovascular events in older individuals and persons with diabetes, coronary artery disease, obesity, and past myocardial infarctions (Bateson and Schwartz 2004, Goldberg et al., 2001; Zanobetti and Schwartz, 2002; Peel et al. 2007). Dubowsky et al. (2006) reported that individuals with conditions associated with both chronic inflammation and increased cardiac risk were mo re vulnerable to the short-term pro-inflammatory effects of air pollution. This included individuals with diabetes; obesity; and concurrent diabetes, obesity and hypertension. Zanobetti and Schw artz (2001) reported more than twice the risk for hospital admissions for heart disease in persons with diabetes than in persons without diabetes associated with exposure to ambient air pollution, indicating that persons with diabetes are an important at-risk group. Data from the Third National Health and Nutrition Exam ination Survey indicated that 5.1% of the U.S. population older than 20 years of age has diagnosed diabetes and an additional 2.7% has undiagnosed diabetes (Harris et al., 1998). Moreover, another st udy found that subjects with impaired glucose tolerance without type II diabetes also had reduced HRV (Schwartz, 2001). This may indicate that the atrisk population may be even larger. Mortimer et al. (2000) reported that among asthmatic children, birth characteristics continue to be associated with increased susceptibility to air pollution later in life, demonstrating that air pollutioninduced asthma symptoms were more severe in children born prematurely or of low birth weight. Specifically, the authors revealed asthmatic children born more than three weeks prematurely or weighing less than 2,500 grams (5.5 pounds) had a six-fold decrease in breathing capacity associated with air pollution compared to full-weight, full-term children. The low birth weight and premature children also reported a five-fold greater incidence of sympto ms like wheezing, coughing and tightness in the chest.



# 4.3.6. Increased Vulnerability Associated with Increased Exposure

Certain groups may experience relatively high exposure to NO 2 , thus forming a potentially vulnerable population. Many studies found that indoor, personal, and outdoor NO 2 levels are strongly4-9 associated with proximity to traffic or traffic density (see Section 2.5.4). NO 2 concentrations in heavy traffic or on freeways, have been observed in the ra nge of 40 to 70 ppb and can be more than twice the residential outdoor or residential/arterial road level (Lee et al., 2000; Westerdahl et al., 2005). Due to high air exchange rates, NO 2 concentrations inside a vehicle could ra pidly approach levels outside the vehicle during commuting; the mean in-vehicle NO 2 concentration has been observed to be between 2 to 3 times non-traffic ambient levels (see Section 2.5.4). Those with occupations that require them to be in or close to traffic or roadways (e.g., bus and taxi drivers, hi ghway patrol officers, toll collectors) or those with long commutes could be exposed to relatively high levels of NO 2 compared to ambient levels. SES is a known determinant of health, and there is evidence that SES modifies the effects of air pollution (O’Neill et al. 2003; Makri and Stilianakis, 2008). Higher exposures to air pollution and greater susceptibility to its effects may contribute to a comp lex pattern of risk among those with lower SES. Conceptual frameworks have been proposed to e xplain the relationship between SES, susceptibility, and exposure to air pollution. Common to these frameworks is the consideration of the broader social context in which persons live, and its effect on health in general (O’Neill et al., 2003; Gee and Payne-Sturges, 2004), as well as on maternal and child health (Morello-Frosch and Shenassa, 2006) and asthma (Wright and Subramanian, 2007) specifically. Multilevel mode ling approaches that allow parameterization of community-level stressors such as increased life stress as well as individual risk factors were considered by these authors. In addition, statistical methods that allow for temporal and spatial variability in exposure and susceptibility have been discussed in the recent literature (Jerrett a nd Finkelstein, 2005; Künzli et al., 2005). Many recent studies examined modification by SES indicators on the association between mortality and PM (O’Neill et al., 2003; Martins et al., 2004; Jerre tt et al., 2004; Finkelstein et al., 2003; Romieu et al., 2004a) or other indices such as traffic density, di stance to roadway or a general air pollution index (Ponce et al., 2005; Woodruff et al., 2003; Finkelstein et al., 2004). SES modification of NO 2 associations has been examined in fewer studies. For example, in a study conducted in Seoul, Korea, community-level SES indicators modified the association of air pollution with ED visits for asthma; of the five criteria air pollutants evaluated, NO 2 showed the strongest association in lower SES districts compared to high SES districts (Kim et al., 2007.) In addition, Clougherty et al. (2007) evaluated exposure to violence (a chronic stressor) as a modifier of the effect of traffic-related air pollutants, including NO 2 , on childhood asthma. The authors reported an elevated risk of asthma with a 4.3-ppb increase in NO 2 exposure solely among children with above-median exposure to violence in their neighborhoods.



# 4.4. At-Risk Susceptible Population Estimates

Although NO 2 -related health risk estimates may appear to be small, they may well be important from an overall public health perspective owing to th e large numbers of persons in the potential risk groups. Several population groups ha ve been identified as possibly having increased susceptibility or vulnerability to adverse health effects from NO 2 , including children, older adults, and persons with preexisting pulmonary diseases. 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 NO 2 -related air pollution exposure. Table 4.4.1 summarizes information on the prevalence of chronic respiratory conditions in the U.S. population in 2004 and 2005 (National Center for Health Statistics, 2006a,b). Individuals with preexisting cardiopulmonary disease constitute a fairly large proportion of the population, with tens of millions of persons included in each disease category. Of most concern are those persons with preexisting respirator y conditions, with approximately 10% of adults and 13% of children having been diagnosed with asthma and 6% of adults with COPD (chronic bronchitis and/or emphysema). There are approximately 2.5 million deaths from all causes per year in the U.S. population, with about 100,000 deaths from chronic lower respirat ory diseases (Kochanek et al., 2004) and 4,000 from4-10 asthma (NCHS, 2006c). For respiratory health diseases, there are nearly 4 million hospital discharges per year (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). Of the total number of visits for respiratory disease, 1.8 million annual ED visits were reported for asthma, including more than 750,000 visits by children. In addition, nearly 500,000 annual hospitalizations for asthma were reported (NCHS, 2006c). Centers for Disease Control and Prevention (CDC) analyses have shown that the burden of asthma has increased over the past two decades (NCHS, 2006c). In 2005, approximately 22.2 million people (7.7% of the population) had asthma. The incide nce was higher among children (8.9% of children) compared to adults (7.2%) (Note: 2004 data is show n in Table 4.4-1, with a prevalence of 6.7%). In addition, prevalence and severity is higher among certain ethnic or racial groups such as Puerto Ricans, American Indians, Alaskan Natives, and African Am ericans. The asthma hospitalization rate for black persons was 240% higher than for white persons. Puerto Ricans were reported to have the highest asthma death rate (360% higher than non-Hispanic white pe rsons) and non-Hispanic black persons had an asthma death rate that was 200% higher than non-Hispanic white persons. Furthermore, a higher prevalence of asthma among persons of lower SES and an excess burde n of asthma hospitalizations and mortality in minority and inner-city communities have been observed in several studies (Wright and Subramanian, 2007). Gender and age are also determinants of prev alence and severity: adult females had a 40% higher prevalence than adult males; and boys, a 30% highe r prevalence than girls. Overall, females had a hospitalization rate about 35% higher than males.

Table 4.4-1. Prevalence of selected respiratory disorders by age group and by geographic region in the U.S.(2004 [U.S. Adults] and 2005 [U.S. Children] National Health Interview Survey).
AGE (YEARS) REGION

ALL ADULTS 18-44 45-64 65-74 75+ NORTHEAST MIDWEST SOUTH WEST CHRONIC CONDITION/DISEASE ADULTS (18+ YEARS) CASES (× 10 6 ) % % % % % % % % %

Asthma 14.4 6.7 6.4 7.0 7.5 6.6 6.8 6.8 6.0 7.5

COPD: Chronic Bronchitis 8.6 4.2 3.2 4.9 6.1 6.3 4.0 4.7 4.4 3.5

COPD: Emphysema 3.5 1.7 0.3 2 4.9 6.0 1.5 1.7 2.0 1.1

ALL CHILDREN 0-4 5-11 12-17 NORTHEAST MIDWEST SOUTH WEST CHRONIC CONDITION/DISEASE CHILDREN (<18 YEARS) CASES (× 10 6 ) % % % % % % % %

Respiratory Conditions 6.5 8.9 6.8 9.9 9.6 10. 1 8.5 9.3 7.9

Source: National Center for Health Statistics (2006a,b)

In addition, population groups based on age group also comprise substantial segments of the population that may be potentially at risk for NO 2 -related health impacts. Based on U.S. census data from 2000, about 72.3 million (26%) of the U.S. population are under 18 years of age, 18.3 million (7.4%) are under 5 years of age, and 35 million (12%) are 65 years of age or older. Hence, large proportions of the U.S. population are in age groups that are likely to have increased susceptibility and vulnerability for health effects from ambient NO 2 exposure.4-11 Figure 4.4-1. Fraction of the study populations livi ng within a specified dist ance from roadways. For comparison, concentrations of the traffic po llutant black carbon are plotted as a function of distance from the roadway.

Based on data from the American Housing Survey , approximately 36 million persons live within 300 feet (~90 meters) of a four-lane highway, railroad, or airport and 12.6% of U.S. housing units are located within this distance (U.S. Census Bureau , 2006). Furthermore, several exposure studies offer insight into differential exposures to NO 2 from traffic in childhood. In California, 2.3% of schools, grades K–12, with a total enrollment of more than 150,000 st udents were located within ~500 feet (150 m) of high-traffic roads, and a higher proportion of nonwhite and economically disadvantaged students attended schools within close proximity to these high-traffic roadways (Green et al., 2004). Similar findings were reported for Detroit schoolchildren (Wu and Batte rman, 2006). Figure 4.4-1 shows the proportion of study populations in Boston, MA (Garshick et al . 2003) and Los Angeles, CA (McConnell et al. 2006), the entire U.S. (American Housing Survey, 2005) , and from population exposure models (HAPEM6, 2007) living within a certain distance from major ro adways. It also presents results of air quality measurements showing the decrease in concentration of black carbon, a traffic-related pollutant, with increasing distance from the roadway. The considerable size of the population groups at risk indicate that exposure to ambient NO 2 could have an impact on public health in the U.S.4-12 

# 4.5. Summary of Public Health Issues

In the few studies that specifically examined concentration-response relationships between NO 2 and health outcomes, there was little evidence of an eff ect threshold. However, various factors, such as interindividual variation in response, additivity to background of effect and/or exposure, and measurement error tend to linearize the concentra tion-response relationship and obscure any populationlevel thresholds that might exist. Persons with preexisting respiratory disease, children, and older adults may be more susceptible to the effects of NO 2 exposure. Individuals in sensitive groups may be affected by lower levels of NO 2 than the general population or experience a greater impact with the same level of exposure. A number of factors may increase susceptibility to the effects of NO 2 . Studies generally reported a positive excess risk for asthmatics, and there was emerging evidence th at CVD may cause persons to be more susceptible, though it is difficult to distinguish the effect of NO 2 from other traffic pollutants. Children and older adults (65+ years) may be more susceptible than adults, possibly due to physiological changes occurring among these age groups. In addition to intrinsically susceptible groups, a portion of the population may be at increased vulnerability due to higher exposures, generally people living and worki ng near roadways. A considerable fraction of the population resides, works, or attends school near major roadways. Of this population, those with physiological susceptibility will have even gr eater risks of health effects related to NO 2 .5-1 

# Chapter 5. Summary and Conclusions

5.1. Introduction

The Integrated Plan for the Primary NAAQS for NO 2 (U.S. Environmental Protection Agency, 2007) presents a series of policy-relevant questions to structure this assessment of the scientific evidence (Section 1.1). This ISA focuses on evaluating recent sci entific evidence while incorporating information from the last review to best inform consideration of these policy-relevant questions. The purpose of this ISA is to form the scientific basis for regulatory deci sion making as it pertains to retaining or revising the current primary NAAQS for NO 2 (0.053 ppm, annual average). The previous chapters present the most policy-relevant science. This chapter first summari zes key findings and then draws conclusions about health effects associated with exposure to NO X . These conclusions are based on explicit guidelines (Section 1.3) derived from the Hill aspects (Hill, 1965) and modeled after other pertinent frameworks. The framework for evaluation of evidence regard ing causality is described in Chapter 1. The framework and language draw from similar efforts acr oss the Federal government and the wider scientific community, especially from the recent NAS Institute of Medicine document, Improving the Presumptive Disability Decision-Making Process for Veterans (Institute of Medicine, 2007). A five-level hierarchy is used to be consistent with the Guidelines fo r Carcinogen Risk Assessment (U.S. Environmental Protection Agency, 2005). Conclusions concerning causality of association were placed into one of five categories with regard to weight of the evidence based on the framework. The five descriptors are:

 Sufficient to infer a causal relationship;

 Sufficient to infer a likely causal relationship (i.e. more likely than not);

 Suggestive but not sufficient to infer a causal relationship;

 Inadequate to infer the presence or absence of a causal relationship; and

 Suggestive of no causal relationship.

This integrative discussion begins with some ke y conclusions from the atmospheric sciences that are relevant to the interpretation of the health ev idence and provide important underpinnings for potential quantitative assessments, including information about ambient concentrations and monitoring, and estimation of policy-relevant b ackground. Consideration of exposur e measurement error and exposure assessment issues is an essential component of this revi ew, and provides an overview of the findings that inform the evaluation of the health evidence. Conclu sions regarding causality for different categories of health outcomes are presented. Highlights of findings that support these conclusions are presented. The key findings from atmospheric science, exposure assessment, and health effects, including animal toxicological, human clinical and epidemiologic studies are integrated with regard to levels at which effects are observed, the time period (or averaging time) over which these effects are observed, and NO 2 serving as the indicator for the oxides of nitrogen NAAQS, and presented in Section 5.4.5-2 

# 5.2. Key Source to Exposure Findings

5.2.1. Atmospheric Science and Ambient Concentrations

An understanding of atmospheric processes affecting a given pollutant is crucial for understanding the causal chain linking NO X sources to health effects. NO 2 plays a key role in the formation of O 3 and photochemical smog. NO 2 is an oxidant and reacts to form other photochemical oxidants, including organic nitrates like the PANs and inorganic acids like HNO 3 . NO 2 also reacts with toxic compounds such as PAHs to form nitro-PAHs, which can be more toxic than either reactant alone. Major anthropogenic sources of NO X include motor vehicles, power plants, and fossil fuel combustion in general. NO X also is emitted by burning biomass fuels. Natural NO X sources include wildfires, microbial activity in soils, and lightning. NO X is emitted by all of the above sources mainly as NO. Atmospheric reactions oxidize NO to NO 2 . Thus, most NO 2 in the atmosphere is the result of the oxidation of primary NO. As noted in Chapter 2, NO and NO 2 interconvert rapidly in the atmosphere, and so it is often convenient to refer to their sum (NO X ) instead of to them individually. The definition of nitrogen oxides contains a number of N -containing compounds formed by the oxidation of NO 2 as described in Chapter 2. Aspects of the atmospheric chemistry of NO X most relevant for interpreting the human exposure and health evidence are:

 The current method of determining ambient NO X and then reporting NO 2 concentrations by subtraction of NO is subject to positive interference by NO X oxidation products, chiefly HNO 3, and PAN as well as other oxidized N -containing compounds. Measurements of these oxidation products in urban areas are sparse.

 Products are expected to peak in the afte rnoon because of the continued oxidation to NO 2 emitted during the morning rush hours and during conditi ons conducive to photochemistry in areas well downwind of sources, particularly during summer.

 Within urban cores, where many of the ambient monitors are sited close to strong NO X sources such as motor vehicles on busy streets (i.e., where NO 2 concentrations are highest), the positive artifacts due to NO 2 oxidation products are much smaller on a relative basis, generally <10%. Conversely, the positive artifacts are larger in locations more distant from local NO X sources (i.e. where NO 2 concentrations are lowest) and could exceed 50%. Therefore, variable, positive artifacts associated with measuring NO 2 using the FRM severely hamper its ability to serve as an accurate and precise indicator of NO 2 concentrations at the typical ambient levels generally encountered outside of urban cores. The resu lt of these positive artifacts when using ambient monitoring data in health outcome studies depends on whether or not the NO 2 oxidation products exert the same effect as NO 2 on the health endpoint being considered.

 Because the dominant urban source is typically on-road vehicle emissions, ambient NO 2 generally behaves with the temporal and spatial va riability of other traffic-generated pollutants.

 The annual average NO 2 concentrations of ~15 ppb reported by the regulatory monitoring networks are well below the level of the current NAAQS (0.053 ppm) . However, daily max 1- h avg concentrations can be greater than 100 ppb in some locations, e.g., areas with heavy traffic.

 Policy-relevant background concentrations of NO 2 are much lower than average ambient concentrations and are typically less than 0.1 ppb over most of the U.S. , with the highest values found in agricultural areas.5-3 

# 5.2.2. Exposure Assessment

Personal exposure to ambient and outdoor NO 2 is affected by many factors that influence the contribution of ambient NO 2 to personal exposures. Personal activity patterns determine when, where, and how people are exposed to NO 2 . The variations of these physical and exposure factors determine the strength of the association between personal exposure and ambient concentrations in both longitudinal and cross-sectional studies. The observed strength of the association between personal exposures and ambient concentrations are not only affected by the variation in physical para meters (e.g., penetration coefficient (P), mass transfer coeffi cient (k), air exchange rate (a), and indoor sources) but also affected by data quality and study design. The collective variab ility in all of the above parameters, in general, contributes to exposure error in air pollution-health outcome studies. The errors and uncertainties associated with the use of ambient NO 2 concentrations as a surrogate for personal exposure to ambient NO 2 generally tend to reduce rather than increa se effect estimates, and therefore are not expected to change the principal conclusions from NO 2 epidemiologic studies. The association between the ambient component of personal exposures and ambient concentrations is most relevant to the interpretation of epidemiologi c evidence, but this type of correlation coefficient is not generally reported. Therefore, the weak associ ation between personal to tal exposures and ambient concentrations in some longitudinal studies might not reflect the true association between the ambient component of personal exposures and ambient concen trations. A number of studies found that personal NO 2 exposure was associated with ambient NO 2 exposure, but the strength of the association ranged from poor to good. Key findings related to assessing NO 2 exposures are listed below.

 NO 2 concentrations are highly spatially and temporally variable in urban areas. Intersite correlations for NO 2 concentrations range from slightly negative to highly positive in examined cities. The range of spatial variation in NO 2 concentrations is similar to that for O 3 , but larger than that of fine particulate matter (PM 2.5 ). Differences between 24-h avg concentrations at individual paired sites in a MSA can be larger than the annual means at these sites.

 Elevated and rooftop NO 2 measurements, particularly in inner cities, likely underestimate concentrations and hence personal exposures occu rring at lower elevations, closer to motor vehicle emissions. Pedestrians that spend time walk ing in street canyons and residents that have windows opening onto these canyons can therefore experience exposures to high near-road concentrations that may equal or exceed those on roads in transit.

 Co-located samples showed that passive NO 2 samplers generally correlate well with FRM ambient samplers, and the concentration differen ces are generally within 10%. However, personal passive samplers and the ambient samplers were both subject to measurement artifacts.

 In the absence of indoor sources, indoor NO 2 levels are about one-half those found outdoors. In the presence of indoor sources, particularly unvented combustion sources, NO 2 levels can be much higher than reported ambient concentrations.

 Alpha ( α ), the ratio of personal exposure to NO 2 of ambient origin to the ambient NO 2 concentration, ranged from ~0.3 to ~0 .6 in studies where it was determined.

 Indoor exposures to NO 2 are accompanied by exposures to ot her products of indoor combustion and to products of indoor NO 2 chemistry, such as HONO.

 The evidence relating ambient levels to personal exposures was inconsistent . Some of the longitudinal studies examined found that ambient levels of NO 2 were reliable proxies of personal exposures to NO 2 . However, a number of studies did not find significant associations between ambient and personal levels of NO 2 . The differences in results were related in large measure to differences in study design and in exposure determinants. Measurement artifacts and differences in analytical measurement capabilities could also have contributed to the inconsistent results.5-4 Indeed, in a number of the studies examined, the majority of measurements of personal NO 2 concentrations were beneath detection limits, a nd in all studies some personal measurements were beneath detection limits.

 In two European studies, community averages of personal total exposures were highly correlated with either ambient or outdoor microenvir onment concentrations. However, because of limitations in these studies, caution should be ex ercised in using these results to determine whether ambient concentrations of NO 2 can be used as surrogates for long-term community average exposures in epidemiologic studies.



# 5.3. Key Health Effects Findings

5.3.1. Findings from the Previous Review

The 1993 NO X AQCD concluded that there were two key health effects of greatest concern at ambient or near-ambient concentrations of NO 2 :

 Increases in airway hyperresponsiveness of asthmatic individuals after short-term exposures.

 Increased respiratory illness among children associ ated with longer-term exposures to NO 2 .

Evidence also was found for increased risk of emphysem a, but this appeared to be of major concern only with exposures to levels of NO 2 that were much higher than current ambient levels of NO 2 (U.S. Environmental Protection Agency, 1993). Qualitative evidence regarding airway hyperresponsiveness and lung function changes was drawn from human clinical and animal toxicological studies; these did not elucidate a concentration-response relationship. Epidemiologic studies reported increased respiratory symptoms with increased indoor NO 2 exposures. Animal toxicological findings of lung host defense system changes with NO 2 exposure provided a biologically plausible basis for these results. Subpopulations considered potentially more susceptible to the effects of NO 2 exposure included persons with preexisting respiratory disease, children, and the elderly. In the 1993 AQCD, the epidemiologic evidence for respiratory health effects was limited, and no studies had considered effects such as hospital admissions, ED visits, or mortality.



# 5.3.2. New Health Effects Findings

Evidence published since the last review genera lly has confirmed and extended the conclusions articulated in the 1993 AQCD. The epidemiologic ev idence has grown substantially, including new field or panel studies on respiratory health outcomes, in tervention studies, numerous time-series epidemiologic studies of effects such as hospital admissions, and a substantial number of studies evaluating mortality risk with short-term NO 2 exposures. As noted above, no epidemiologic studies were available in 1993 that assessed relationships between nitrogen oxides and outco mes such as hospital admissions, ED visits, or mortality; in contrast, dozens of epidemiologic studies on such outcomes are now included in this evaluation. Several recent studies also have re ported findings from prospective cohort studies on respiratory health effects with long-term NO 2 exposure. In addition, recent evidence characterizing the responses of susceptible and vulnerable populations has been reported since 1993, particularly concerning children, asthmatics, and those living or working n ear roadways. While not as marked as the growth in the epidemiologic literature, a number of recent toxicological and human clinical studies provide further insights into relationships between NO 2 exposure and health effects. These new findings allow us to draw several overa ll conclusions concerning the health effects of NO 2 exposures. These conclusions are integrated acro ss disciplines at the organ-system level (e.g.,5-5 respiratory and cardiovascular morbidity, cardiopulmonary mo rtality). Integration at this level is generally more meaningful than reporting on separate health effects, which themselves may be serious, but individually do not fully characterize impacts on health . The conclusions of this ISA are summarized in Table 5.3-1, along with those of the previous revi ew. Following the table is more discussion of evidence that supports these conclusions, organized by e xposure duration and specific health effect.

Table 5.3-1. Summary of evidence from epidemiol ogic, human clinical, and animal toxicological studies on the health effects associated with short- and long-term exposure to NO 2 .

HEALTH OUTCOME CONCLUSION FROM PREVIOUS NAAQS REVIEW CONCLUSION FROM 2008 ISA



### SHORT-TERM EXPOSURE TO NO 2

Respiratory Morbidity No Overall Conclusion “su fficient to infer a likel y causal relationship”

Lung Host Defense Human c linical studies suggest NO 2 effects; Animal toxicological studies indicate that alveolar macrophages and humoral and cell-mediated immune systems are affected and show that exposur e can impair the respiratory host defense system resulting in susceptibility to infection. Impaired host-defense systems and incr eased risk of susceptibility to both viral and bacterial infections after NO 2 exposures have been observed in epidemiologic, human clinical, and animal toxicological studies.

Airway Inflammation No Studies Human clinical studies report effects of NO 2 (1-2 ppm) on airway inflammation in healthy humans. Animal toxicol ogical studies and limited available epidemiologic studies on child ren support these findings.

Airway Hyperresponsiveness An increase in responsiveness to bronchoconstrictors was found in asthmatics and healthy individuals exposed to NO 2 at rest. Human clinical studies of allergen and nonspecific bronchi al challenges in asthmatics observed increased airway hyperresponsiveness at near ambient concentrations (0.1-0.3 ppm). In creased responsivene ss to nonspecific challenges was also observed in animals at higher NO 2 levels (e.g., 0.5 ppm).

Respiratory Symptoms Children living in homes with gas stoves are at increased risk for developing respiratory diseases and illnesses compared to children living in homes without gas stoves. Epidemiologic studies provide consis tent evidence of an association of respiratory effects with indoor and personal NO 2 exposures in children. Multicity studies provide further s upport for associations between ambient NO 2 concentrations (means of 7-70 ppb) and respiratory symptoms in asthmatic children.

Lung Function Lung function changes in asthmatics reported at low (0.2 to 0.5 ppm), but not higher (up to 4 ppm), NO 2 concentrations. No convincing evidence of lung function decrements in healthy individuals below 1.0 ppm. The association between ambient NO 2 concentrations and lung function in epidemiologic studies were generally inc onsistent. Recent clinical evidence generally confirms prior findings.

ED Visits / Hospital Admissions No Studies Positive and generally robust associations observed between ambient NO 2 levels (means of 3-50 ppb) and increas ed ED visits and hospital admissions for respiratory causes , especially asthma.

Cardiovascular Morb idity No Studies “inadequate to infer the presence or absen ce of a causal relationship”

Cardiovascular Effects No Studies Evidence from epidemio logic studies of heart rate variability, repolarization changes, and cardiac rhythm disorders among heart patients with ischemic cardiac disease are inconsistent.

ED Visits / Hospital Admissions No Studies Generally positive associations between ambient NO 2 concentrations and hospital admissions or ED visits for cardiovascular disease; however, the effects were not robust to adjustment for copollutants.

Mortality No Studies “suggestive but not su fficient to infer a causal relationship”

All Cause and Cardiopulmonary Mortality No Studies Positive and generally r obust associations between ambient NO 2 concentrations and risk of nonaccidental and cardiopulmonary mortality.5-6 HEALTH OUTCOME CONCLUSION FROM PREVIOUS NAAQS REVIEW CONCLUSION FROM 2008 ISA



### LONG-TERM EXPOSURE TO NO 2

Respiratory Morbidity No Overall Conclusion “suggestiv e but not sufficient to in fer a causal relationship”

Respiratory Effects NO 2 can cause emphysema (meeting the human definition criteria) in animals at high concentrations of NO 2
. Epidemiologic studies observed dec rements in lung function growth associated with long-term exposure to NO 2
.

Other Morbidity No Studies “inade quate to infer the presence or ab sence of a causal relationship”

Cancer No Studies Limited epidemiologic studi es observed an association between long-term NO 2 exposure and cancer; animal toxico logical studies have not provided clear evidence that NO 2 acts as a carcinogen.

Cardiovascular Effects No Studies Very limited epidemio logic and toxicological evi dence does not suggest that long-term exposure to NO 2 has cardiovascular effects.

Birth Outcomes No Studies The epidemiologic evidenc e for an association between long-term exposure to NO 2 and birth outcomes is generally inc onsistent, with limited support from animal toxicological studies.

Mortality No Studies “inadequate to infer th e presence or absence of a causal relationship”

All Cause and Cardiopulmonary Mortality No Studies The results of epidemiologic st udies examining the association between longterm exposure to NO 2 and mortality were generally inconsistent.



## 5.3.2.1. Respiratory Effects Related to Short-Term Exposure

Taken together, recent studies provided scientific evidence that NO 2 is associated with a range of respiratory effects and provide evidence sufficient to infer a likely causal relationship between shortterm NO 2 exposure and adverse effects on the respiratory system . The greatest weight of evidence comes predominantly from the large body of recent epidemiologic evidence, with supportive evidence from human and animal experimental studies. The main body of evidence pertaining to causality for respiratory health outcomes is shown in Figure 5.3- 1. The epidemiologic studies generally show positive associations between NO 2 and respiratory symptoms and hospita lization or ED visits, with a number being statistically significant, particularly the more precise effect estimates. There also is a pattern of positive associations with respiratory mortality, though most are not statistically significant. A number of the epidemiologic studies have been conduc ted in locations where the ambient NO 2 levels are well below the level of the NAAQS of 0.053 ppm (53 ppb) (annual average). The mean ambient concentrations, associated with the health outcomes reported in Figure 5.3-1 are in the range of 3 to 70 ppb for 24 h avg, with maximum ambient concentrations as high as 100 to 300 ppb. The epidemiologic evidence for r espiratory effects can be characterized as consistent, in that associations are reported in studies conducted in num erous locations with a variety of methodological approaches. The findings are coherent in the sense th at the studies report associations with respiratory health outcomes that are logically linked together.5-7Figure 5.3-1. Summary of epidemiologic studies examining short-term exposures to ambient NO2and respiratory outcomes.Effect estimates for studies conducted in the U.S. or Canada are presented in black. Circles represent effect estimates. Linesrepresent 95% CI. Legend to figure onfollowing page.5-8 Legend to Figure 5.3-1.

Respiratory Symptoms
1 Schwartz et al. (1994) Cough 2 Mortimer et al. (2002) Asthma symptoms 3 Schildcrout et al. (2006) Asthma symptoms 4 Pino et al. (2004) Wheezy bronchitis 5 Ostro et al. (2001) Wheeze 6 Ostro et al. (2001) Cough 7 Delfino et al. (2002) Asthma symptoms 8 Segala et al. (1998) Asthma symptoms 9 Segala et al. 1998 Cough 10 Just et al. (2002) Cough 11 Jalaludin et al. (2004) Cough 12 Segala et al. (2004) Cough 13 von Klot et al. (2002) Wheeze 14 von Klot et al. (2002) Phlegm 15 von Klot et al. (2002) Cough 16 von Klot et al. (2002) Breathing problems 17 Ward et al (2002) Cough 18 Rodriguez et al. (2007) Cough 19 Boezen et al. (1999) LRS Respiratory Disease – All Ages
20 Tolbert et al. (2007) 21 Peel et al. (2005) 22 Luginaah et al. (2005) 23 Luginaah et al. (2005) 24 Anderson et al. (2001) 25 Atkinson et al., (1999a) 26 Atkinson et al., (1999b) 27 Ponce de Leon et al. (1996) 28 Llorca et al. (2005) 29 Oftedal et al. (2003) 30 Hagen et al. (2000) 31 Bedeschi et al. (2007) 32 Hinwood et al., (2006) 33 Petroeschevsky et al. (2001) Respiratory Disease – Children
34 Yang et al. (2003) 35 Luginaah et al. (2005) 36 Luginaah et al. (2005) 37 Anderson et al. (2001) 38 Atkinson et al. (1999a) 39 Atkinson et al. (1999b) 40 Ponce de Leon et al. (1996) 41 Vigotti et al. (2007) 42 Petroeschevsky et al. (2001) 43 Petroeschevsky et al. (2001) 44 Barnett et al. (2005) 45 Barnett et al. (2005) 46 Barnett et al. (2005) 47 Wong et al. (1999) 48 Lin et al. (1999) 49 Gouveia and Fletcher (2000a) Respiratory Disease – Adults
50 Luginaah et al. (2005) 51 Luginaah et al. (2005) 52 Spix et al. (1998) 53 Anderson et al. (2001) 54 Atkinson et al. (1999a) 55 Atkinson et al. (1999b) 56 Ponce de Leon et al. (1996) 57 Schouten et al. (1996) 58 Schouten et al. (1996) 59 Petroeschevsky et al. (2001) 60 Wong et al. (1999) Respiratory Disease – Older Adults (65+)
61 Luginaah et al. (2005) 62 Luginaah et al. (2005) 63 Fung et al. (2006) 64 Yang et al. (2003) 65 Spix et al. (1998) 66 Anderson et al. (2001) 67 Atkinson et al. (1999a) 68 Atkinson et al. (1999b) 69 Ponce de Leon et al. (1996) 70 Andersen et al. (2007b) 71 Andersen et al. (2007a) 72 Schouten et al. (1996) 73 Schouten et al. (1996) 74 Simpson et al. (2005a) 75 Hinwood et al. (2006) 76 Petroeschevsky et al. (2001) 77 Wong et al. (1999) Asthma – All Ages
78 Peel et al. (2005) 79 Ito et al. (2007)* 80 Burnett et al. (1999) 81 Anderson et al. (1998) 82 Atkinson et al. (1999a) 83 Atkinson et al. (1999b) 84 Galan et al. (2003) 85 Chardon et al. (2007) 86 Schouten et al. (1996) 87 Migliaretti et al. (2005) 88 Migliaretti and Cavallo (2004) 89 Hinwood et al. (2006) 90 Petroeschevsky et al. (2001) 91 Wong et al., (1999) 92 Tsai et al. (2006) 93 Tsai et al. (2006) 94 Yang et al. (2007) 95 Yang et al. (2007) Asthma – Children
96 Peel et al. (2005) 97 Tolbert et al. (2000) 98 Lin et al. (2003) 99 Lin et al. (2003) 100 Sunyer et al. (1997) 101 Anderson et al. (1998) 102 Atkinson et al. (1999a) 103 Atkinson et al. (1999b) 104 Thompson et al. (2001) 105 Andersen et al. (2007b) 106 Andersen et al. (2007a) 107 Migliaretti et al. (2005) 108 Migliaretti and Cavallo (2004) 109 Migliaretti and Cavallo (2004) 110 Barnett et al. (2005) 111 Barnett et al. (2005) 112 Hinwood et al. (2006) 113 Petroeschevsky et al. (2001) 114 Petroeschevsky et al. (2001) 115 Morgan et al. (1998a) 116 Ko et al. (2007) 117 Lee et al. (2006) 118 Gouveia and Fletcher (2000a) 119 Jaffe et al. (2003) 120 Jaffe et al. (2003) 121 Linn et al. (2000) Asthma – Adults
122 Sunyer et al. (1997) 123 Anderson et al. (1998) 124 Atkinson et al. (1999a) 125 Atkinson et al. (1999b) 126 Boutin-Forzano et al. (2004) 127 Tenias et al. (1998) 128 Castellsague et al. (1995) 129 Migliaretti et al. (2005) 130 Morgan et al. (1998a) 131 Ko et al. (2007) 132 Anderson et al. (1998) 133 Atkinson et al. (1999a) 134 Migliaretti et al. (2005) 135 Hinwood et al. (2006) 136 Ko et al. (2007)

Respiratory Mortality
137 Ostro et al. (2000) 138 Fairley (1999); (Reanalysis 2003) 139 Gamble (1998) 140 Gwynn et al. (2000) 141 Burnett et al. (2004) 142 Villeneuve et al. (2003) 143 Samoli et al. (2006) 144 Zmirou et al. (1998) 145 Biggeri et al. (2005) 146 Anderson et al. (1996) 147 Bremner et al. (1999) 148 Anderson et al. (2001) 149 Le Tertre et al. (2002) 150 Dab et al. (1996) 151 Zmirou et al. (1996) 152 Hoek et al. (2000); (Reanalysis, Hoek (2003) 153 Hoek et al. (2000); (Reanalysis, Hoek (2003) 154 Saez et al. (2002) 155 Garcia-Aymerich et al. (2000) 156 Saez et al. (1999) 157 Sunyer et al. (1996) 158 Borja-Aburto et al. (1998) 159 Gouveia and Fletcher (2000b) 160 Simpson et al. (2005a,b) 161 Simpson et al. (2000) 162 Tsai et al. (2003) 163 Yang et al. (2004b) 164 Wong et al. (2001) 165 Wong et al. (2002)5-9 Animal toxicologic and human clinical studies ha ve been conducted within the range of maximum ambient concentrations observed in epidemiologi c studies (100 to 300 ppb) and provide some supporting evidence for the effects observed in the epidemiologic studies. Generally, exposure durations used in human clinical studies are more similar to peak exposures than 24-h avg exposures. Tables 5.3-2 and 5.3-3 summarize the health endpoints that have been linked with NO 2 exposure in human clinical and animal toxicologic studies, respectively, along with th e lower range of doses or concentrations with which these effects have been reported. To put the concen tration information in perspective, average and maximum ambient concentrations from earlier years in the United States and elsewhere were substantially greater than current levels; yet in the 3-year pe riod 2003–2005, 1-h excursions in the United States have been observed in the range of 100 to 200 ppb (see Ch apter 2). The human and animal findings underlying this causal judgment are summarized below.

Table 5.3-2. Key studies and effects of exposure to NO 2 from clinical studies.

STUDY NO 2 (ppm) EXPOSURE DURATION (h) OBSERVED EFFECTS

Folinsbee (1992) 0.1-0.3 0.5-2.0 Meta-analysis showed increas ed airway responsiveness following NO 2 exposure in asthmatics. Large variability in protoc ols and responses. Mo st studies used nonspecific airway challenges. Airway res ponsiveness tended to be greater for resting (mean 45 min) than exercising (mean 102 min) exposure conditions.

Barck et al. (2002, 2005a) Strand et al. (1996; 1997; 1998) 0.26 0.5 Asthmatics exposed to NO 2 during rest experienced enhanced sensitivity to bronchial challenge-induced decrements in lung func tion and increased allergen-induced airway inflammatory response. Inflammatory res ponse to allergen observ ed in the absence of allergen-induced lung func tion response. No NO 2 -induced change in lung function.

Gong et al. (2005) Morrow et al. (1992) Vagaggini et al. (1996) 0.3-0.4 2-4 Inc onsistent effects on FVC and FEV 1 in COPD patients with mild exercise.

Azadniv et al. (1998) Blomberg et al. (1997; 1999) Devlin et al. (1999) Frampton et al. (2002) Jörres et al. (1995) 1.0-2.0 2-6 Increased inflammatory response and airway responsiveness to nonspecific challenge in healthy adults exposed during intermittent exercise. Effects on lung function and symptoms in healthy subjects not detected by most inve stigators. Small decrements in FEV 1 reported for asthmatics.

Beil and Ulmer (1976) Nieding et al. (1979) Nieding and Wagner (1977) Nieding et al. (1980) ≥ 2.0 1-3 Lung function changes (e.g ., increased airway resistance) in healthy subjects. Effects not found by others at 2-4 ppm.



### Lung Host Defenses and Immunity
Impaired host-defense systems a nd increased risk of susceptibility to both viral and bacterial infections after NO 2 exposures were observed in epidemiologic, human clinical, and animal toxicological studies (Section 3.1.2). A recent epidemiologic study (Chauhan et al., 2003) provided evidence that increased personal exposure to NO 2 worsened virus-associated symptoms and decreased lung function in children with asthma. The limited ev idence from human clinical studies indicated that NO 2 increases susceptibility to injury by subsequent viral challenge (Frampton et al., 2002). Animal toxicological studies have shown that lung host defenses are sensitive to NO 2 exposure, with several measures of such effects observed at concentra tions of less than 1 ppm. The epidemiologic and5-10 experimental evidence indicated coherence for effects of NO 2 exposure on host defense (i.e., immune system effects). This group of outcomes also provi ded plausibility and potential mechanistic support for other respiratory effects described subsequently, such as respiratory symptoms or increased ED visits for respiratory diseases.

Table 5.3-3. Summary of toxicological effects in rats from NO 2 exposure.

STUDY NO 2 (ppm) EXPOSURE DURATION OBSERVED EFFECTS

Kumae and Arakawa (2006) 0.2 From conception to 12 wks post delivery Increase in BALF lymphocytes (indicative of inflammation)

Kumae and Arakawa (2006) 0.5 Weanling period (from 5 wks old to 12 wks) Suppression of ROS (indicative of lung host defense impairment)

Robison et al. (1993) 0.5 0.5-10 days Depressed activation of arac hidonic acid metabolism and superoxide production (indicative of lung host defense impairment)

Mercer et al. (1995) 0.5 spikes of 1.5 9 wks Increase in the number of fenestr ae in the lungs (morphological effects)

Barth et al. (1994) 0.8 1 or 3 days Increase in bronchi olar epithelial proliferation (morphological effects)

Note: Lowest-observed-effect level based on category BALF=Bronchoalveolar lavage fluid ROS=Reactive oxygen species



### Airway Inflammation
Together, the findings of human and animal studies provided some evidence for airway inflammation with NO 2 exposure, particularly in the more sensitive subgroups such as children or asthmatics. The few epidemiologic studies that cons idered inflammation showed an association between ambient NO 2 concentrations and inflammatory response in the airways in children. The associations were inconsistent in the adult populations examined (Section 3.1.3). Effects of NO 2 on airway inflammation have been observed in human clinical and animal toxicological studies at higher than ambient levels (0.4-5 ppm). Human clinical studies shows that airway inflammation is increased at NO 2 concentrations of <2.0 ppm; the onset of infla mmatory responses in healthy subjects appears to be between 100 and 200 ppm-min, i.e., 1 ppm for 2 to 3 h (Figure 3.1-1). Increases in biological markers of inflammation were not observed c onsistently in healthy animals at levels of less than 5 ppm; however, increased susceptibility to NO 2 concentrations of as low as 0.4 ppm was observed when lung vitamin C was reduced (by diet) to levels that were <50% of normal. These data provided some evidence for biological plausibility and one potential mechanism for other respiratory effects, such as exacerbation of asthma symptoms or increased ED visits for asthma.



### Airway Hyperresponsiveness
The evidence from human and animal experiment al studies provided some evidence for increased airway responsiveness to specific allergen challenges following NO 2 exposure (Section 3.1.4.1). Recent human clinical studies involving allergen challenge in asthmatics reported that NO 2 exposure may enhance the sensitivity to allerg en-induced decrements in lung function and increase the allergeninduced airway inflammatory response at exposures as low as 0.26 ppm NO 2 for 30 min (Figure 3.1- 2). Increased immune-mediated pulmonary inflammation also was observed in rats exposed to house dust mite allergen following exposure to 5 ppm NO 2 for 3 h. Exposure to NO 2 also has been found to enhance the inherent responsiveness of the airway to subse quent nonspecific challenges in human clinical studies (Section 3.1.4.2). In general, small but significant increases in nonspecific airway hyperresponsiveness5-11 were observed in the range of 1.5 to 2.0 ppm for 3 h exposures in healthy adults and between 0.2 and 0.3 ppm NO 2 for 30 -min exposures and at 0.1 ppm NO 2 for 60-min exposures in asthmatics

. Subchronic exposures (6 to 12 weeks) of animals to NO 2 also increased responsiveness to nonspecific challenges at exposures of 1 to 4 ppm.



### Respiratory Symptoms

Consistent evidence has been ob served for an association of respiratory effects with indoor and personal NO 2 exposures in children at ambient concentration levels (Section 3.1.5.1). In particular, the Pilotto et al. (2004) intervention study provided evidence of improvement in respiratory symptoms with reduced NO 2 exposure in asthmatic children. This study linked respiratory effects with exposure to NO 2 from an indoor combustion source,(i.e., unflued g as heaters), thus, increased confidence that NO 2 is not solely a marker for an ambient air polluti on mixture in observed associations with NO 2 from outdoor sources (in particular traffic emissions) that has infiltrated indoors. The epidemiologic studies using community ambient monitors also found associations between ambient NO 2 concentration and respiratory symptoms (Section 3.1.4.2, see Figure 3.1-6). The results of recent multicity studies (Schildcrout et al., 2006; Mortimer et al., 2002) provided further support fo r associations between respiratory symptoms and medication use in asthmatic children. Positive associations were observ ed in cities where the median range was 18 to 26 (90 th percentiles: 34 to 37) ppb for a 24-h avg (Schildcrout et al., 2006) and the mean NO 2 level was 32 (range: 7 to 96) ppb for a 4-h avg (Mortimer et al., 2002). These concentrations were within the range of 24-h avg concentrations observed in recent years. In the results of multipollutant models, NO 2 associations in these multicity studies were generally robust to adjustment for copollutants including O 3 , CO, and PM 10 (Figure 3.1-7). Most human clinical studies do not report or observe respiratory symptoms with NO 2 exposure, and animal toxicological studies do not measure effects that would be considered symptoms. The experimental evidence on immune system effects and airway inflammation discussed previously, however, provide some plausibility and coherence for the observed respiratory symptoms in epidemiologic studies.



### Lung Function
Recent epidemiologic studies that examin ed the association between ambient NO 2 concentrations and lung function in children and a dults generally produced inconsis tent results (Section 3.1.5.1). Human clinical studies generally did not find direct effects of NO 2 on lung function in healthy adults at levels as high as 4.0 ppm (Section 3.1.5.2). For asthmatics, the direct effects of NO 2 on lung function also have been inconsistent at exposur e concentrations of less than 1 ppm NO 2 .


### Respiratory ED Visits and Hospitalizations
Epidemiologic evidence exists for positive associations of short-term ambient NO 2 concentrations below the current NAAQS level with increased numbers of ED visits and hospital admissions for respiratory causes, especially asthma (Section 3.1.7). A number of studies were conducted in locations where mean 24-h concentrations were in the range of 3 to 50 (maxima: 28 to 82) ppb (Figure 5.3-1). These associations are particul arly consistent among ch ildren and older adults (65+ years) when all respiratory outcomes are analyzed together (Figures 3.1-8 and 3.1-9), and among children and subjects of all ages for asthma admissions (Figures 3.1-12 and 3.1-13). When examined with copollutant models, associations of NO 2 with respiratory ED visits and hospital admissions were generally robust and indepe ndent of the effects of copollutants (Figures 3.1-10 and 3.1-11). In preceding sections, mechanistic evidence was described related to host defense and immune system changes, airway5-12 inflammation, and airway responsiveness that provi de plausibility and coherence for these observed effects.



## 5.3.2.2. Cardiovascular Effects Related to Short-Term Exposure

The available evidence on the effects of short-term exposure to NO 2 on cardiovascular health effects is inadequate to infer the presence or absence of a causal relationship at this time. Evidence from epidemiologic studies of heart rate variability (HRV), repolarization changes, and cardiac rhythm disorders among heart patients with ischemic cardiac disease was inconsistent (Section 3.2.1). In most studies, associations with PM were found to be similar or stronger than associations with NO 2 . The mean 24-h concentrations generally we re in the range of 9 to 39 ppb (Annex Table AX6.3-6). Generally positive associations between ambient NO 2 concentrations and hospital admissions or ED visits for cardiovascular disease have been reported in single-po llutant models where mean 24-h concentrations generally were in the range of 20 to 40 ppb (Section 3.2.2); however, most of these effect estimates were diminished in multipollutant models that also cont ained CO and PM. Mechanistic evidence of a role for NO 2 in the development of cardiovascular diseases from studies of biomarkers of inflammation, cell adhesion, coagulation, and thrombosis is lack ing (Section 3.2.1.4; Seaton and Dennekamp, 2003). Furthermore, the effects of NO 2 on various hematological parameters in animals are inconsistent and, thus, provide little biological plausibility for effects of NO 2 on the cardiovascular system. However, evidence from two human clinical studies was indicative of a reduction in hemoglobin with NO 2 exposure at concentrations between 1.0 and 2.0 ppm (with 3 h exposures).



## 5.3.2.3. Mortality Related to Short-Term Exposure

The epidemiologic evidence is suggestive but not sufficient to infer a causal relationship of short-term exposure to NO 2 with all cause and cardiopulmonary-related mortality. Results from several large U.S. and European multicity studies and a meta-analysis study indicated positive associations between ambient NO 2 concentrations and the risk of all-cause (nonaccidental) mortality, with effect estimates ranging from 0.5 to 3.6% excess risk in mortality per standardized increment 1 (Section 3.3.1, Figure 3.3-2). In general, the NO 2 effect estimates were robust to adjustment for copollutants. Both cardiovascular and respiratory mortality were associated with increased NO 2 concentrations in epidemiologic studies (Figure 3.3-3); however, simila r associations were observed for other pollutants, including PM and SO 2 . The range of risk estimates for excess mortality was generally smaller than that for other pollutants such as PM. While NO 2 exposure, alone or in conjunc tion with other pollutants, may contribute to increased mortality, evaluation of the specifi city of this effect was difficult. Clinical studies showing hematologic effects and animal toxicologi cal studies showing biochemical, lung host defense, permeability, and inflammation changes with short-term exposures to NO 2 provide limited evidence of plausible pathways by which risks of morbidity and, potentially, mortality may be increased, but no coherent picture is evident at this time.



## 5.3.2.4. Respiratory Morbidity Related to Long-Term Exposure

The epidemiologic and toxicological evidence exam ining the effect of long-term exposure to NO 2 on respiratory morbidity is suggestive but not sufficient to infer a causal relationship at this time. A number of epidemiologic studies examined the effects of long-term exposure to NO 2 and reported positive associations with decrements in lung function and pa rtially irreversible decrements in lung function

1 Excess risk estimates are standardized to a 20-ppb incremental change in daily 24-h avg NO 2 or a 30-ppb incremental change in daily 1-h max NO 2
.5-13 growth (Section 3.4.1, Figures 3.4-1 and 3.4-2). Resu lts from the Southern California Children’s Health Study indicated that decrements were similar for boys and girls and among children who had no history of asthma (Gauderman et al., 2004). The mean NO 2 concentrations in these studies range from 21.5 to 34.6 ppb. Similar associations have also been found for PM, O 3 , and proximity to traffic (<500 m), though these studies did not report the results of copo llutant models. The high correlation among trafficrelated pollutants made it difficult to accurately es timate the independent effects in these long-term exposure studies. Results from the available epidemio logic evidence investigating the association between long-term exposure to NO 2 and increases in asthma prevalence and incidence were suggestive (Section 3.4.2). Two major cohort studies, the Children’s Health Study in southern California (Gauderman et al., 2005) and a birth cohort study in the Netherlands (B rauer et al., 2007) observed significant associations; however, several other studies did not find c onsistent associations between long-term NO 2 exposure and asthma outcomes. Epidemiologic studies conducted in both the U.S. and Europe also have produced inconsistent results regarding an associ ation between long-term exposure to NO 2 and respiratory symptoms (Section 3.4.3). While some positive associations were noted, a large number of symptom outcomes were examined and the resu lts across specific outcomes were inconsistent. Animal toxicological studies demonstrated that NO 2 exposure resulted in morphological changes in the centriacinar region of the lung and in bronchiolar epithelial proliferation (Section 3.4.4), which may provide some biological plausibility for the observed epidemiologic asso ciations between long-term exposure to NO 2 and respiratory morbidity. Susceptibility to these morphologi c effects was found to be influenced by many factors, such as age, compromised lung function, and acute infections.



## 5.3.2.5. Other Morbidity Related to Long-Term Exposure

The available epidemiologic a nd toxicological evidence was inadequate to infer the presence or absence of a causal relationship for carcinogenic, cardiovascular, a nd reproductive and developmental effects related to long-term NO 2 exposure. Two epidemiologic studi es conducted in Europe showed an association between long-term NO 2 exposure and increased incidence of cancer (Nyberg et al., 2000; Nafstad et al., 2003). However, the animal toxicological studies provided no clear evidence that NO 2 acts as a carcinogen, though it does appear to act as a tumor promoter at the site of contact (Section 3.5.1). There were no in vivo studies supporting the hypothesis that NO 2 causes teratogenesis or malignant tumors. A more likely pathway for NO 2 involvement in cancer induction is through secondary formation of nitro-PAHs, as nitro-PAHs are known to be more mutagenic than the parent compounds. The very limited epidemiologic and toxicological evidence does not indicate that long-term exposure to NO 2 has cardiovascular effects (Section 3.5.2). The U.S. Women’s Health Initiative study (Miller et al., 2007) did not find any associations between long-term NO 2 exposure and cardiovascular events. The toxicological studies found some effects of NO 2 on cardiac performance and heart rate, but only at exposure levels of above 4 ppm. The epidemiologic evidence was not consistent for associations between NO 2 exposure and growth retardation; however, some evidence is accumulating for effects on preterm delivery (Section 3.5.3). Similarly, scant animal evidence supports a weak association between NO 2 exposure and adverse birth outcomes and provides little mechanistic informati on or biological plausibility for the epidemiologic findings.



## 5.3.2.6. Mortality Related to Long-Term Exposure

The epidemiologic evidence was inadequate to infer the presence or absence of a causal relationship between long-term exposure to NO 2 and mortality. In the U.S. and European cohort studies examining the relationship between long-term exposure to NO 2 and mortality, results were generally inconsistent (Section 3.6, Figure 3.6-2). Further, when associations were noted, they were not specific to5-14 NO 2 , but also implicated PM and other traffic i ndicators. The relatively high correlations reported between NO 2 and PM indices (r ~0.8) make it difficult to interpret these associations.



## 5.3.2.7. Exposure Indices

The available NO 2 indices used to indicate short-term ambient NO 2 exposure are daily 1-h max; 24-h avg; and 2-week avg NO 2 concentrations. New data on short- term exposures have been published since the 1993 NO X AQCD. Some studies examined only one i ndex, and these studies form an evidence base for that individual index. A few studies used both 1-h and 24-h data and, thus, allow a comparison of these averaging periods. These included studies of respir atory symptoms, ED visits for asthma, hospital admissions for asthma, and mortality. Comparisons of effect estimates for asthma ED visits for the 1-h and 24-h time periods showed that the effect estimates are not different . Experimental studies in both animals and humans provided evidence that short-term NO 2 exposure (i.e., <1 h to 2–3 h) can result in respiratory effects such as increased airway res ponsiveness or inflammation, thereby increasing the potential for exacerbation of asthma. These findings generally supported epidemiologic evidence on short-term exposures, but did not provide evidence that distinguishes effects for one short-term averaging period from another. Differences between daily 1-h max and 24-h avg exposures estimates are unlikely to be well characterized by the limited monitoring data available. Though an array of studies that examined short-term (24-h avg and 1-h maximum) NO 2 exposures and respiratory morbidity consistently produced positive associations, it is not possible to discern whether these effects are attributable to average daily (or multiday) concentrations (24-h avg) or high, peak exposures (1-h max).



## 5.3.2.8. Susceptible and Vulnerable Populations

Based on both short- and long-term studies of an array of respiratory health effects data, persons with preexisting pulmonary conditions are likely at greater risk from ambient NO 2 exposures than the general public , with the most extensive evidence availa ble for asthmatics as a potentially susceptible group. In addition, studies indicated that upper respirat ory viral infections can trigger susceptibility to the effects of exposure to NO 2 . There was supporting evidence of age -related differences in susceptibility to NO 2 health effects such that the elderly population (>65 y ears of age) appeared to be at increased risk of mortality and hospitalizations, and th at children (<18 years of age) experienced other potentially adverse respiratory health outcomes with increased NO 2 exposure. People with occupations that require them to be in or close to traffic or roadways (i.e., bus a nd taxi drivers, highway patrol officers) may have enhanced exposure to NO 2 compared to the general population, possibly increasing their vulnerability. A considerable portion of the population resides and/or attends school near major roadways, increasing their exposure to NO 2 and other traffic pollutants. Otherwise su sceptible individuals (schoolchildren, older adults) in this subpopulation may be at increased ri sk. Recent studies have evaluated the effect of socioeconomic status (SES) on susceptibility to the effects of NO 2 exposure; however, to date, these studies are too few in number to draw conclusions. Though data are just emerging (Romieu et al., 2006; Islam et al., 2007), it is believed that a genetic co mponent could be important in characterizing the association between NO 2 exposure and adverse health effects.



## 5.3.2.9. Concentration-Response Relationships and Thresholds

The conclusions pertaining to respiratory hea lth presented in this ISA are based on numerous studies, including panel and field, intervention, and mu ltipollutant studies that control for the effects of other pollutants, and studies conducted in areas where the whole distribution of ambient 24-h avg NO 2 concentrations was below the current NAAQS leve l of 0.053 ppm (annual average). In some cases the mean exposure in positive epidemiologic studi es are <10 ppb; the policy-relevant background5-15 concentration is <0.01 ppb. In studies that have ex amined concentration-response relationships between NO 2 and health outcomes, the concentration-respon se relationship appears linear within the observed range of data, including at levels be low the current standard. There is little evidence of any effect threshold (Section 4.2). Factors that made it difficult to identify any threshold that may exist included: interindividual variation; additivity of pollutant-i nduced effects to the naturally occurring background disease processes; additivity to health effects due to ot her environmental insults having a mode of action similar to that of NO 2 ; exposure error; and response measurement error. Low data density in the lower concentration range as a result of limited monitoring is a particular problem in terms of measurement error. Additionally, if the concentration-response rela tionship was shallow, identification of any threshold that may exist will be more difficult to discern.



# 5.4. Conclusions

New evidence confirms previous findings in the 1993 AQCD that short-term NO 2 exposure is associated with increased airway responsiveness, often accompanied by respiratory symptoms, particularly in children and asthmatics. This ISA c oncludes that the strongest evidence for an association between NO 2 exposure and adverse human health effects co mes from epidemiologic studies of respiratory symptoms and ED visits and hospital admissions. These new findings were based on numerous studies, including panel and field studies, multipollutant studies th at control for the effects of other pollutants, and studies conducted in areas where the whole distribution of ambient 24-h avg NO 2 concentrations was below the current NAAQS level of 0.053 ppm (53 ppb) (annual average). The effect estimates from the U.S. and Canadian studies generally indicate a 2- 20% increase in risks for ED visits and hospital admissions. Risks associated with respiratory symptoms generally were higher. The studies providing this evidence (summarized in Table 5.4-1) were iden tified based on criteria for selecting epidemiologic studies for inclusion in the ISA (Annex Section AX1.3 .2 and Annex Figure AX1.3-1). They include U.S. and Canadian studies conducted at or near ambient concentrations, which were well-designed, properly implemented, and thoroughly described. All of the U.S. and Canadian studies included in Figure 5.3-1 are included in Table 5.4-1. Evidence from human clini cal studies, especially for airway hyperresponsiveness in asthmatic individuals, was generally supportive of the epidemiologic evidence (see Table 5.3-2). These conclusions were supported by some evidence from toxicological and human clinical studies. These data sets formed a plausible, consistent, a nd coherent description of a relationship between NO 2 exposures and an array of adverse health effects that range from the onset of respiratory symptoms to hospital admission. Though an array of studies that examined short-term (24-h avg and 1-h max) NO 2 exposures and respiratory morbidity consistently produced positive associations, it is not possible to discern whether these effects are attributable to averag e daily (or multiday) concentrations (24-h avg) or high, peak exposures (1-h max). While the evidence supported a direct effect of short-term NO 2 exposure on respiratory morbidity, the available evidence was inadequate to infer the presence or absence of a causal relationship for morbidity and mortality effects related to long-term NO 2 exposure. Further, the health evidence was inadequate to infer the presence or absence of a causal relationship for carcinogenic, cardiovascular, and reproductive and de velopmental effects, or for premature mortality, related to longterm NO 2 exposure. The available evidence on the effects of short-term exposure to NO 2 for cardiovascular health effects is inadequate to infer the presence or absence of a causal relationship at this time. Though there is no human clinical or animal toxicological evidence, the epidemiologic evidence is suggestive but not sufficient to infer a causal relationship of short-term exposure to NO 2 with nonaccidental and cardiopulmonary-related mortality. It is difficult to determine from th ese new studies the extent to which NO 2 is independently associated with respiratory effects or if NO 2 is a marker for the effects of anothe r traffic-related pollutant or mix of5-16 pollutants (see Section 5.2.2 for more details on expos ure issues). On-road vehicle exhaust emissions are a nearly ubiquitous source of combustion pollutant mixtures that include NO 2 and can be an important contributor to NO 2 levels in near-road locations. Although th is complicates the efforts to disentangle specific NO 2 -related health effects, the evidence su mmarized in this assessment indicates that NO 2 associations generally remain robust in multipollutant models and supports a direct effect of short-term NO 2 exposure on respiratory morbidity at ambient c oncentrations below the current NAAQS level. The robustness of epidemiologic findings to adjustment fo r copollutants, coupled with data from animal and human experimental studies, support a determ ination that the relationship between NO 2 and respiratory morbidity is likely causal, while still recognizing the relationship between NO 2 and other traffic related pollutants. In addition, an intervention study by Pilotto et al. (2004) found that exposure to NO 2 from an indoor combustion source is associated with respiratory effects; in this study NO 2 effects would not be confounded by other motor vehicle emission polluta nts, though potential confounding by other pollutants from gas stove emissions, such as UFP, could occur. Human clinical and toxicological study findings also provide support for independent effects of NO 2 on respiratory health. Limited evidence fro m human clinical studies indicated that NO 2 may increase susceptibility to injury by subsequent viral challenge ; toxicological studies show that lung host defenses are sensitive to NO 2 exposure. The epidemiologic and experiment al evidence together show coherence for effects of NO 2 exposure on host defense or immune system effects providing plausibility and mechanistic support for respiratory symptoms and ED visits for respiratory disease. Additionally, short-term exposure to NO 2 shows increased airway inflammation in human clinical and animal toxicological studies but at exposure concentrations higher than ambient levels . Human and animal experimental studies provide support for increased airways responsiveness to specific and nonspecific challenge following NO 2 exposure. Transient increases in airway responsiveness following NO 2 exposure have the potential to increase symptoms and worsen asthma control. Identification of a concentration-response relations hip is an additional uncertainty that must be considered when describing the association of NO 2 and adverse health effects. In studies that have examined concentration-response relationships between NO 2 and health outcomes specifically, there was little evidence of an effect threshold. Because ambient levels of NO 2 are low in many of the epidemiologic study sites, the concentration-respon se relationship may be shallow, making it difficult to identify any threshold.5-17 Table 5.4-1. Ambient NO 2 concentrations and selected effect estimates from studies of respiratory symptoms, ED visits and hospital admissi ons in the U.S. and Canada.Complete results and study details in Annex Tables AX6.3-2 through AX6.3-5.

STUDY POPULATION AVG TIME MEAN (SD) RANGE STANDARDIZED a % EXCESS RISK (95% CI) Respiratory Symptoms

Schwartz et al. (1994) 6 cities, U.S. 24-h avg 13 ppb (NR) Max: 44 61.3% (8.2, 143.4) Cough Incidence
Mortimer et al. (2002) 8 urban areas, U.S. 4-h avg 32 ppb (NR)

− 7, 96 48% (2, 116) Morning Asthma Symptoms
Schildcrout et al. (2006) 8 North Am erican Cities 24-h avg 17-26 ppb (NR) NR 4.0% (1.0, 7.0) Asthma Symptoms
Ostro et al. (2001) LA and Pasadena, CA 1-h max 68-80 ppb (NR) 20, 220 7.0% (1.0, 13.8) Cough Onset
Delfino et al. (2002) Alpine, CA 1-h max 24 ppb ( 10) 8, 53 34.6% (-17.9, 122.1) Asthma Symptoms
Delfino et al. (2003) East LA County, CA 1-h max 7.2 ppb (2.1) 3, 14 120% (-46, 2,038) Asthma Symp. Scores >1

Linn et al. (1996) Los Angeles, CA 24-h avg 33 ppb (22) 1, 96 -18.2% (-47.3, 27.1) Morning Symptom Score Emergency Department Visits – All Respiratory

Peel et al. (2005) Atlanta, GA 1-h ma x 45.9 ppb (17.3) Max: 256 2.4% (0.9, 4.1)
Tolbert et al. (2007) Atlanta, GA 1-h max 43.2 ppb (NR) 1.0-181 2% (0.5, 3.3) Emergency Department Visits – Asthma

Jaffe et al. (2003) 2 cities, OH, (Clev, Cinc) 24-h avg Cinc:50 ppb (15) Clev:48 ppb (15) NR 6.1% (-2.0, 14.0)

Ito et al. (2007) New York, NY 24-h avg 31.1 ppb (8.7) NR 12% (7, 16)
New York State Department of Health (2006) Bronx and Manhattan, NY 24-h avg 34 ppb (NR) NR 6% (1, 10) Bronx. -3% (-18, 14) Manhattan

Peel et al. (2005) Atlanta, GA 1-h max 45.9 ppb (17.3) NR 2.1% (-0.4, 4.5) All Ages. 4.1% (0.8, 7.6) 2- 18 yrs
Tolbert et al. (2000) Atlanta, GA 1-h ma x 81.7 ppb (53.8) 5.4, 306 0.7% (-0.8, 2.3) Hospital Admissions – All Respiratory

Burnett et al. (1997a) 16 Canadian Cities 1-h max 35.5 ppb (16.5) NR -0.3% (-2.4, 1.8) adjusted for CO, O 3 , SO 2 , CoH

Yang et al. (2003) Vancouver, BC 24-h avg 18.7 ppb (5.7) NR 19.1% (7.4, 36.3)<3 yrs. 19.1% (11.2, 36.3) >65 yrs
Fung et al. (2006) Vancouver, BC 24-h avg 16.8 ppb (4.3) 7.2, 33.9 9.1% (1.5, 17.2)
Burnett et al. (2001) Toronto, ON 1-h max 44.1 ppb (NR) Max: 146 13.3% (5.3, 22.0)

Luginaah et al. (2005) Windsor, ON, 1-h max 38.9 ppb (12.3) NR 6.7% (-5.4, 20.4) female. -10.3% (-20.3, 1.1) male Hospital Admissions – Asthma

Linn et al. (2000) Los Angeles, CA 24-h avg 3.4 ppb (1.3) NR 2.8% ± 1.0%

Lin et al. (2004) Vancouver, BC 24-h avg 18.7 ppb (5.6) 4.3, 5.4 45.3% (12.7, 88.3) Boys . 23.0% (-11.7, 70.2) Girls

Lin et al. (2003) Toronto, ON 24-h avg 25.2 ppb (9.04) 3.0, 82.0 18.9% (1.8, 39.3) Boys. 17.0% (-5.4, 41.4) Girls
Burnett et al. (1999) Toronto, ON 24-h avg 25.2 ppb (9.1) NR 2.60% (0, 5)

Note: Several U.S. and Canadian studies were excluded from Figure 5.3-1 and this table because they were either GAM-impacted (Cassino et al., 1999; Gwynn et al. 2000; Norris et al. 1999; Stieb et al. 2000) or did not present sufficient quantitative risk estimates (Lipsett et al., 1997; Sinclai r and Tolsma 2004).

a 24-h avg effect estimates standardized to 20 ppb increment; 1-h max effect estimates standardized to 30 ppb increment.1 

# References

Abbey, D. E.; Nishino, N.; McDonnell, W. F.; Burc hette, 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. Ackermann-Liebrich, U.; Leuenberger, P.; Schwartz, J.; Schindler, C.; Monn, C.; Bolognini, B.; Bongard,J. P.; Brändli, O.; Domenighetti, G.; Elsasser, S.; Grize, L.; Karrer, W.; Keller, R.; KellerWossidlo, H.; Künzli, N.; Martin, B. W.; Medici, T. C.; Perruchoud, A. P.; Schöni, M. H.; Tschopp, J. M.; Villiger, B.; Wüthrich, B.; Zellw eger, J. P.; Zemp, E. (1997) Lung function and long term exposure to air pollutants in Switzerland. Am. J. Respir. Crit. Care Med. 155: 122-129. Adamkiewicz, G.; Ebelt, S.; Syring, M.; Slater, J.; Speizer, F. E.; Schwartz, J.; Suh, H.; Gold, D. R. (2004) Association between air pollution exposur e and exhaled nitric oxide in an elderly population. Thorax 59: 204-209.
Adams, P. F.; Hendershot, G. E.; Marano, M. A. (1999) Current estimates from the National Health Interview Survey, 1996. Hyattsville, MD: U.S. Depa rtment of Health and Human Services, Public Health Service, National Center for Health St atistics; 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/seri es/sr10/pre-200/pre-200.htm [12 March, 2001]. Adams, W. C.; Brookes, K. A.; Schelegle, E. S. (1987) Effects of NO 2 alone and in combination with O 3 on young men and women. J. Appl. Physiol. 62: 1698-1704.
Adkins, B., Jr.; Van Stee, E. W.; Simmons, J. E.; Eu stis, S. L. (1986) Oncogenic response of strain A/J mice to inhaled chemicals. J. Toxicol. Environ. Health 17: 311-322. Aga, E.; Samoli, E.; Touloumi, G.; Anderson, H. R. ; Cadum, E.; Forsberg, B.; Goodman, P.; Goren, A.; Kotesovec, F.; Kriz, B.; Macarol-Hiti, M.; Medina, S.; Paldy, A.; Schindler, C.; Sunyer, J.; Tittanen, P.; Wojtyniak, B.; Zmirou, D.; Schwartz, J.; Katsouyanni, K. (2003) Short-term effects of ambient particles on mortality in the elderly: r esults from 28 cities in the APHEA2 project. Eur. Respir. J. 21(suppl. 40): 28s-33s. Alcorn, S. H.; Lurmann, F. W. (2004) Southern California children’s health study exposure database (final report). Petaluma, CA: Sonoma Technology , Inc., report no. STI-95230-2453-FR3; prepared for University of Southern California School of Medicine, Division of Environmental Health.
Alm, S.; Mukala, K.; Pasanen, P.; Tiittanen, P.; Ruus kanen, J.; Tuomisto, J.; Jantunen, M. J. (1998) Personal NO 2 exposures of preschool children in Helsinki. J. Exposure Anal. Environ. Epidemiol. 8: 79-100. 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 epidemiologic studies of air pollution. Am. Rev. Respir. Dis. 131: 666- 668. American Thoracic Society. (2000a) Guidelines for methacholine and exercise challenge testing-1999. Am. J. Respir. Crit. Care Med. 161: 309-329. American Thoracic Society. (2000b) What constitutes an adverse health effect of air pollution? Am. J. Respir. Crit. Care Med. 161: 665-673.2 Ammann, M.; Kalberer, M.; Jost, D. T.; Tobler, L.; Rössler, E.; Piguet, D.; Gäggeler, H. W.; Baltensperger, U. (1998) Heteroge neous production of nitrous acid on soot in polluted air masses. Nature (London) 395: 157-160. Andersen, Z. J.; Wahlin, P.; Raaschou-Nielsen, O.; Ketzel, M.; Scheike, T.; Loft, S. (2007b) Size distribution and total number concentration of ultrafine and accumulation mode particles and hospital admissions in children and the elderly in Copenhagen, Denmark. Occup. Environ. Med.: 10.1136/oem.2007.033290.
Andersen, Z. J.; Wahlin, P.; Raaschou-Nielsen, O.; Sche ike, T.; Loft, S. (2007a) Ambient particle source apportionment and daily hospital admissions am ong children and elderly in Copenhagen. J. Exposure Sci. Environ. Epidemiol. 17: 625-636.
Anderson, H. R.; Bremner, S. A.; Atkinson, R. W.; Harrison, R. M.; Walters, S. (2001) Particulate matter and daily mortality and hospital admissions in the west midlands conurbation of the United Kingdom: associations with fine and coarse particl es, black smoke and sulphate. Occup. Environ. Med. 58: 504-510. 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 fo r asthma in London 1987-92. Thorax 53: 842-848. Anderson, H. R.; Spix, C.; Medina, S.; Schouten, J. P. ; Castellsague, J.; Rossi, G.; Zmirou, D.; Touloumi, G.; Wojtyniak, B.; Ponka, A.; Bacharova, L.; Schw artz, 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. AQEG, 2004 Nitrogen dioxide in the United Kingdom. Report of the UK Air Quality Expert Group. AQEG, 2004. Prepared for the Department of the Environment Food and Rural Affairs, the Scottish Executive, the Welsh Assembly and the De partment of the Environment in Northern Ireland. Defra publications, London, March 2004. Available: www.defra.gov.UK/environment/ airquality/aqeg.
Arbex, M. A.; Martins, L. C.; Carvalho et Oliveira, R.; Pereira, L. A. A.; Arbex, F. F.; Cancado, J. E. D.; Saldiva, P. H. N.; Braga, A. L. F. (2007) Air pollution from biomass burning and asthma hospital admissions in a sugar cane plantation area in Braz il. J. Epidemiol. Community Health 61: 395-400. Arey, J. (1998) Atmospheric reactions of PAHs incl uding formation of nitroarenes. In: Neilson, A. N., vol. ed. Anthropogenic compounds. V. 3, part I. PAHs and related compounds - chemistry. New York, NY: Springer-Verlag; pp. 347-385. (Hutzi nger, O., ed. The handbook of environmental chemistry series). Arey, J.; Atkinson, R.; Zielinska, B.; McElroy, P. A. (1989) Diurnal concentrati ons of volatile polycyclic aromatic hydrocarbons and nitroarenes during a photochemical air pollution episode in Glendora, California. Environ. Sci. Technol. 23: 321-327. Arey, J.; Zielinska, B.; Atkinson, R.; Winer, A. M.; Ramdahl, T.; Pitts, J. N., Jr. (1986) The formation of nitro-PAH from the gas-phase reactions of fluoran thene and pyrene with the OH radical in the presence of NO x . Atmos. Environ. 20: 2339-2345.
Atkinson, R. W.; Anderson, H. R.; Strachan, D. P.; Bland, J. M.; Bremner, S. A.; Ponce de Leon, A. (1999a) Short-term associations between outdoor air pollution and visits to accident and emergency departments in London for respiratory complaints. Eur. Respir. J. 13: 257-265. Atkinson, R. W.; Anderson, H. R.; Sunyer, J.; Ayres, J.; Baccini, M.; Vonk, J. M.; Boumghar, A.; Forastiere, F.; Forsberg, B.; Touloumi, G.; Schwar tz, J.; Katsouyanni, K. (2001) Acute effects of particulate air pollution on respiratory admissions: results from APHEA 2 project. Am. J. Respir. Crit. Care Med. 164: 1860-1866.3 Atkinson, R. W.; Bremner, S. A.; Anderson, H. R.; Strachan, D. P.; Bland, J. M.; Ponce de Leon, A. (1999b) Short-term associations between emerge ncy hospital admissions for respiratory and cardiovascular disease and outdoor air pollution in London. Arch. Environ. Health 54: 398-411.
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. Azadniv, M.; Utell, M. J.; Morrow, P. E.; Gibb, F. R.; Nichols, J.; Roberts, N. J., Jr.; Speers, D. M.; Torres, A.; Tsai, Y.; Abraham, M. K.; Voter, K. Z.; Frampton, M. W. (1998) Effects of nitrogen dioxide exposure on human host defen se. Inhalation Toxicol. 10: 585-602.
Baccarelli, A.; Zanobetti, A.; Martinelli, I.; Grillo, P.; Hou, L.; Giacomini, S.; Bonzini, M.; Lanzani, G.; Mannucci, P. M.; Bertazzi, P. A.; Schwartz, J. (2007) Effects of exposure to air pollution on blood coagulation. J. Thromb. Haemostasis 5: 252-260. Balabaeva, L.; Tabakova, S. (1985) Lipidnata pe roksidatsiya v dvye pokoleniya zhenski beli plukhove, inkhalirani s azoten dvuokis [Lipid peroxidation in two progenies of female albino rats inhaling nitrogen dioxide]. Khig. Zdraveopaz. 28: 41-46. Ballester, F.; Rodríguez, P.; Iñíguez, C.; Saez, M.; Daponte, A.; Galán, I.; Taracido, M.; Arribas, F.; Bellido, J.; Cirarda, F. B.; Cañada, A.; Guillén, J. J.; Guillén-Grima, F.; López, E.; Pérez-Hoyos, S.; Lertxundi, A.; Toro, S. (2006) Air pollution and cardiovascular admisisons association in Spain: results within the EMECAS project. J. Epidemiol. Community Health 60: 328-336. Ballester, F.; Tenías, J. M.; Pérez-Hoyos, S. (2001) Air pollution and emergency hospital admissions for cardiovascular diseases in Valencia, Spain. J. Epidemiol. Community Health 55: 57-65. Bamford, H. A.; Baker, J. E. (2003) Nitro-polycyclic aromatic hydrocarbon concentrations and sources in urban and suburban atmospheres of the mid-A tlantic region. Atmos. Environ. 37: 2077-2091.
Bamford, H. A.; Bezabeh, D. Z.; Schantz, M. M.; Wi se, S. A.; Baker, J. E. (2003) Determination and comparison of nitrated-polycyclic aromatic hydr ocarbons measured in air and diesel particulate reference materials. Chemosphere 50: 575-587. Barck, C.; Lundahl, J.; Halldén, G.; Bylin, G. (2005a) Brief exposures to NO 2 augment the allergic inflammation in asthmatics. Environ. Res. 97: 58-66. Barck, C.; Lundahl, J.; Holmström, M.; Bylin, G. (2005b) Does nitrogen dioxide affect inflammatory markers after nasal allergen challenge? Am. J. Rhinol. 19: 560-566.
Barck, C.; Sandström, T.; Lundahl, J.; Halldén, G.; Sv artengren, M.; Strand, V.; Rak, S.; Bylin, G. (2002) Ambient level of NO 2 augments the inflammatory response to inhaled allergen in asthmatics. Respir. Med. 96: 907-917.
Barnett, A. G.; Williams, G. M.; Schwartz, J.; Best, T. L.; Neller, A. H.; Petroeschevsky, A. L.; Simpson, R. W. (2006) The effects of air pollution on hospitalization for cardiovascular disease in elderly people in Australian and New Zealand cities. Environ. Health Perspect. 114: 1018-1023.
Barnett, A. G.; Williams, G. M.; Schwartz, J.; Neller, A. H.; Best, T. L.; Petroeschevsky, A. L.; Simpson, R. W. (2005) Air pollution and child respiratory health: a case-crossover study in Australia and New Zealand. Am. J. Respir. Crit. Care Med. 171: 1272-1278. Barth, P. J.; Müller, B.; Wagner, U.; Bittinger, A. (1994) Assessment of proliferative activity in type II pneumocytes after inhalation of NO 2 by agnor-analysis. Exp. Toxicol. Pathol. 46: 335-342. Bates, D. V.; Baker-Anderson, M.; Sizto, R. (1990) Asthma attack periodicity: a study of hospital emergency visits in Vancouver. Environ. Res. 51: 51-70.4 Bateson, T. F.; Schwartz, J. (2004) Who is sens itive to the effects of particulate air pollution on mortality? A case-crossover analysis of effect modifiers. Epidemiology. 15: 143-9. Bauer, M. A.; Utell, M. J.; Morrow, P. E.; Speers, D. M.; Gibb, F. R. (1986) Inhalation of 0.30 ppm nitrogen dioxide potentiates exercise-induced bronchospasm in asthmatics. Am. Rev. Respir. Dis. 134: 1203-1208. Bedeschi, E.; Campari, C.; Candela, S.; Collini, G. ; Caranci, N.; Frasca, G.; Galassi, C.; Francesca, G.; Vigotti, M. A. (2007) Urban air pollution and respir atory emergency visits at pediatric unit, Reggio Emilia, Italy. J. Toxicol. Environ. Health Part A 70: 261-265. Beil, M.; Ulmer, W. T. (1976) Wirkung von NO 2 im MAK-Bereich auf Atemmechanik und bronchiale Acetylcholinempfindlichkeit bei Normalpersonen [Effect of NO 2 in workroom concentrations on respiratory mechanics and bronchial susceptibility to acetylcholine in normal persons]. Int. Arch. Occup. Environ. Health 38: 31-44. Belanger, K.; Gent, J. F.; Triche, E. W.; Bracken, M. B.; Leaderer, B. P. (2006) Association of indoor nitrogen dioxide exposure with respiratory symptoms in children with asthma. Am. J. Respir. Crit. Care Med. 173: 297-303. Bell, M. L.; Ebisu, K.; Belanger, K. (2007) Ambient air pollution and low birth weight in Connecticut and Massachusetts. Environ. Health Perspect. 115: 1118-1125. Berkowicz, R.; Ketzel, M.; Jensen, S. S.; Hvidberg, M.; Raaschou-Nielsen, O. (2008) Evaluation and application of OSPM for traffic pollution assessment for a large number of street locations. Environ. Model. Softw. 23: 296-303. Bermüdez, E. (2001) Detection of poly(ADP-ribose) synthetase activity in alveolar macrophages of rats exposed to nitrogen dioxide and oz one. Inhalation Toxicol. 13: 69-84.
Bernard, N.; Saintot, M.; Astre, C.; Gerber, M. (1998) Personal exposure to nitrogen dioxide pollution and effect on plasma antioxidants. Arch. Environ. Health 53: 122-128. Bezabeh, D. Z.; Bamford, H. A.; Schantz, M. M.; Wise, S. A. (2003) Determination of nitrated polycyclic aromatic hydrocarbons in diesel particulate-rela ted standard reference materials by using gas chromatography/mass spectrometry with negative ion chemical ionization. Anal. Bioanal. Chem. 375: 381-388. Biggeri, A.; Baccini, M.; Bellini, P.; Terracini, B. (2005) Meta-analysis of the Italian studies of short-term effects of air pollution (MISA), 1990-1999. Int. J. Occup. Environ. Health 11: 107-122. Bignal, K. L.; Ashmore, M. R.; Headley, A. D.; Stewart, K.; Weigert, K. (2007) Ecological impacts of air pollution from road transport on local ve getation. Appl. Geochem. 22: 1265-1271. Blomberg, A.; Krishna, M. T.; Bocchino, V.; Biscione, G. L.; Shute, J. K.; Kelly, F. J.; Frew, A. J.; Holgate, S. T.; Sandström, T. (1997) The inflammatory effects of 2 ppm NO 2 on the airways of healthy subjects. Am. J. Respir. Crit. Care Med. 156: 418-424. Blomberg, A.; Krishna, M. T.; Helleday, R.; Söderber g, M.; Ledin, M.-C.; Kelly, F. J.; Frew, A. J.; Holgate, S. T.; Sandström, T. (1999) Persistent airway inflammation but accomodated antioxidant and lung function responses after repeated daily e xposure to nitrogen dioxide. Am. J. Respir. Crit. Care Med. 159: 536-543. Bobak, M. (2000) Outdoor air pollution, low birth we ight, and prematurity. Environ. Health Perspect. 108: 173-176.5 Boezen, H. M.; Van Der Zee, S. C.; Postma, D. S.; Vonk, J. M.; Gerritsen, J.; Hoek, G.; Brunekreef, B.; Rijcken, B.; Schouten, J. P. (1999) Effects of ambient air pollution on upper and lower respiratory symptoms and peak expiratory flow in children. Lancet 353: 874-878. Boezen, M.; Schouten, J.; Rijcken, B.; Vonk, J.; Gerrit sen, J.; Van Der Zee, S.; Hoek, G.; Brunekreef, B.; Postma, D. (1998) Peak expiratory flow variab ility, bronchial responsiveness, and susceptibility to ambient air pollution in adults. Am. J. Respir. Crit. Care Med. 158: 1848-1854. Borja-Aburto, V. H.; Castillejos, M.; Gold, D. R.; Bierzwinski, S.; Loomis, D. (1998) Mortality and ambient fine particles in southwest Mexico City, 1993-1995. Environ Health Perspect. 106: 849- 55. Boutin-Forzano, S.; Adel, N.; Gratecos, L.; Jullian, H.; Garnier, J. M.; Ramadour, M.; Lanteaume, A.; Hamon, M.; Lafay, V.; Charpin, D. (2004) Visits to the emergency room for asthma attacks and short-term variations in air pollution. A case-crossover study. Respiration 71: 134-137. Brauer, M.; Hoek, G.; Smit, H. A.; De Jongste, J. C.; Gerritsen, J.; Postma, D. S.; Kerkhof, M.; Brunekreef, B. (2007) Air pollution and development of asthma, allergy and infections in a birth cohort. Eur. Respir. J. 29: 879-888.
Brauer, M.; Hoek, G.; Van Vliet, P.; Meliefste, K.; Fi scher, P. H.; Wijga, A.; Koopman, L. P.; Neijens, H. J.; Gerritsen, J.; Kerkhof, M.; Heinrich, J.; Bellander, T.; Brunekreef, B. (2002) Air pollution from traffic and the development of respiratory infec tions and asthmatic and allergic symptoms in children. Am. J. Respir. Crit. Care Med. 166: 1092-1098. Brauer, M.; Rasmussen, T. R.; Kjærgaard, S. K.; Spengler, J. D. (1993) Nitrous acid formation in an experimental exposure chamber. Indoor Air 3: 94-105. Brauer, M.; Ryan, P. B.; Suh, H. H.; Koutrakis, P.; Spengler, J. D.; Leslie, N. P.; Billick, I. H. (1990) Measurements of nitrous acid inside two research houses. Environ. Sci. Technol. 24: 1521-1527.
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 be tween outdoor air pollution and mortality in London 1992-4. Occup Environ Med. 56: 237-44. Brook, J. R.; Burnett, R. T.; Dann, T. F.; Cakmak, S.; Goldberg, M. S.; Fan, X.; Wheeler, A. J. (2007) Further interpretation of the acute effect of nitrogen dioxide observed in Canadian time-series studies. J. Exposure Sci. Environ. Epidemiol. 17: S36-S44. 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 Pane l on Population and Prevention Science of the American Heart Association. Circulation 109: 2655-2671. Brown, S. K.; Mahoney, K. J.; Cheng, M. (2004) Room chamber assessment of the pollutant emission properties of (nominally) low-emission unflued gas heaters. Indoor Air 14(suppl. 8): 84-91. Buchdahl, R.; Parker, A.; Stebbings, T.; Babiker, A. (1996) Association between air pollution and acute childhood wheezy episodes: prospective observational study. Br. Med. J. 312: 661-664. 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.; Brook, J.; Dann, T.; Delocla, C.; Ph ilips, O.; Cakmak, S.; Vincent, R.; Goldberg, M. S.; Krewski, D. (2000) Association between partic ulate- and gas-phase components of urban air pollution and daily mortality in eight Canadian c ities. In: Grant, L. D., ed. PM2000: particulate matter and health. Inhalation Toxicol. 12(suppl. 4): 15-39.6 Burnett, R. T.; Cakmak, S.; Brook, J. R. (1998) The effect of the urban ambient air pollution mix on daily mortality rates in 11 Canadian cities. Can. J. Public Health 89: 152-156.
Burnett, R. T.; Cakmak, S.; Brook, J. R.; Krewski, D. (1997a) The role of particulate size and chemistry in the association between summertime ambient air pollution and hospitalization for cardiorespiratory diseases. Environ. Health Perspect. 105: 614-620.
Burnett, R. T.; Dales, R. E.; Brook, J. R.; Raize nne, M. E.; Krewski, D. (1997) Association between ambient carbon monoxide levels and hospitalizations for congestive heart failure in the elderly in 10 Canadian cities. Epidemiology. 8: 162-7.
Burnett, R. T.; Smith-Doiron, M.; Stieb, D.; Cakmak , S.; Brook, J. R. (1999) Effects of particulate and gaseous air pollution on cardiorespiratory hospita lizations. 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 year s of age. Am. J. Epidemiol. 153: 444-452. Burnett, R. T.; Stieb, D.; Brook, J. R.; Cakmak, S.; Dales, R.; Raizenne, M.; Vincent, R.; Dann, T. (2004) Associations between short-term changes in nitr ogen dioxide and mortality in Canadian cities. Arch. Environ. Health 59: 228-236.
Bush, T.; Smith, S.; Stevenson, K.; Moorcroft, S. (2001) Validation of nitroge n dioxide diffusion tube methodology in the UK. Atmos. Environ. 35: 289-296. Bylin, G.; Lindvall, T.; Rehn, T.; Sundin, B. (1985) E ffects of short-term exposure to ambient nitrogen dioxide concentrations on human bronchial reactivity and lung function. Eur. J. Respir. Dis. 66: 205-217. Cabral-Anderson, L. J.; Evans, M. J.; Freeman, G. (1977) Effects of NO 2 on the lungs of aging rats: I. morphology. Exp. Mol. Pathol. 27: 353-365. California Air Resources Board. (2007a) Review of the California ambient air quality standard for nitrogen dioxide. Staff report: initial statement of reasons for proposed rulemaking. Sacramento, CA: California Environmental Protection Agency, Air Resources Board. Available: http://www.arb.ca.gov/research/aaqs/no2-rs/no2-doc.htm [23 July, 2007]. California Air Resources Board. (2007b) Review of the California ambient air quality standard for nitrogen dioxide. Technical support document. Sacramento, CA: California Environmental Protection Agency, Air Resources Board. Av ailable: http://www.arb.ca.gov/research/aaqs/no2- rs/no2-doc.htm [23 July, 2007]. Campbell, G. W.; Stedman, J. R.; Stevenson, K. ( 1994) A survey of nitrogen dioxide concentrations in the United Kingdom using diffusion tubes, July-December 1991. Atmos. Environ. 28: 477-486. Cape, J. N. T.; Tang, Y. S.; van Dijk, N.; Love, L.; Su tton, M. A.; Palmer, S. C. F. (2004) Concentrations of ammonia and nitrogen dioxide at roadside verg es, and their contribution to nitrogen deposition. Environ. Pollut. 132: 469-478. Carslaw, N. (2007) A new detailed chemical model for indoor air pollution. Atmos. Environ. 41: 1164- 1179.
Carson, J. L.; Collier, A. M.; Hu, S. -C.; Delvin, R. B. (1993) Effect of nitrogen dioxide on human nasal epithelium. Am. J. Respir. Cell. Mol. Biol. 9: 264-270. Castellsague, J.; Sunyer, J.; Sáez, M.; Antó, J. M. (1995) Short-term association between air pollution and emergency room visits for asthma in Barcelona. Thorax 50: 1051-1056.7 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/data_ statistics/sgr/sgr_2004/chapters.htm (21 February, 2008) Chan, C.-C.; Chuang, K.-J.; Chien, L.-C.; Chen, W.-J.; Chang, W.-T. (2006) Urban air pollution and emergency admissions for cerebrovascular diseases in Taipei, Taiwan. Eur. Heart J. 27: 1238-1244. Chan, C.-C.; Chuang, K.-J.; Su, T.-C.; Lin, L.-Y. (2005) Association between nitrogen dioxide and heart rate variability in a susceptible population. Eur. J. Cardiovasc. Prev. Rehabil. 12: 580-586. Chan, L. Y.; Chan, C. Y.; Qin, Y. (1999) The effect of commuting microenvironment on commuter exposures to vehicular emission in Hong Kong. Atmos. Environ. 33: 1777-1787. Chang, C.-C.; Tsai, S.-S.; Ho, S.-C.; Yang, C. -Y. (2005) Air pollution and hospital admissions for cardiovascular disease in Taipei, Taiwan. Environ. Res. 98: 114-119. Chardon, B.; Lefranc, A.; Granados, D.; Grémy, I. (2007) Air pollution and doctors’ house calls for respiratory diseases in the greater Paris area (2000-3). Occup. Environ. Med. 64: 320-324. Chauhan, A. J.; Inskip, H. M.; Linaker, C. H.; Smith, S.; Schreiber, J. ; Johnston, S. L.; Holgate, S. T. (2003) Personal exposure to nitrogen dioxide (NO 2 ) and the severity of virus-induced asthma in children. Lancet 361: 1939-1944. Chauhan, A. J.; Krishna, M. T.; Frew, A. J.; Holg ate, S. T. (1998) Exposure to nitrogen dioxide (NO 2 ) and respiratory disease risk. Rev. Environ. Health 13: 73-90. Chen, Y.; Yang, Q.; Krewski, D.; Burnett, R. T.; Sh i, Y.; McGrail, K. M. (2005) The effect of coarse ambient particulate matter on first, second, and overall hospital admissions for respiratory disease among the elderly. Inhalation Toxicol. 17: 649-655. Chew, F. T.; Goh, D. Y. T.; Ooi, B. C.; Saharom, R.; Hui, J. K. S.; Lee, B. W. (1999) Association of ambient air-pollution levels with acute asthma exacerbation among children in Singapore. Allergy (Copenhagen) 54: 320-329. Clougherty, J. E.; Levy, J. I.; Kubzansky, L. D.; Ryan, P. B.; Suglia, S. F.; Canner, M. J.; Wright, R. J. (2007) Synergistic effects of traffic-related ai r pollution and exposure to violence on urban asthma etiology. Environ. Health Perspect. 115: 1140-1146. Cocheo, V.; Boaretto, C.; Sacco, P. (1996) High uptak e rate radial diffusive sampler suitable for both solvent and thermal desorption. Am. Ind. Hyg. Assoc. J. 57: 897-904. Cockcroft, D. W.; Davis, B. E. (2006) Airway hyperresponsiveness as a determinant of the early asthmatic response to inhaled allergen. J. Asthma 43: 175-178. Cockcroft, D. W.; Davis, B. E.; Todd, D. C.; Smycniuk, A. J. (2005) Methacholine challenge: comparison of two methods. Chest 127: 839-844. Code of Federal Regulations. (2002) Ambient air qua lity surveillance; appendix E - probe and monitoring path citing criteria for ambient air quality monitoring. C. F. R. 40: §58. Coffin, D. L.; Gardner, D. E. (1972) Interaction of biological agents and chemical air pollutants. Ann. Occup. Hyg. 15: 219-234. Connell, D. P.; Withum, J. A.; Winter, S. E.; Statnick, R. M.; Bilonick,, R. A. (2005) The SteubenvilleComprehensive Air Monitoring Program (SCAMP): associations among fine particulate matter, copollutants, and meteorological conditions. J. Air Waste Manage. Assoc. 55: 481-496.8 Cotterill, A.; Kingham, S. (1997) Nitrogen dioxide in the home: cooking, double glazing, or outdoor air? Indoor Built Environ. 6: 344-349. Cox, R. M. (2003) The use of passive sampling to monitor forest exposure to O 3 , NO 2 , and SO 2 : a review and some case studies. Environ. Pollut. 126: 301-311. Crosley, D. R. (1996) NO y blue ribbon panel. J. Geophys. Res. Atmos. 101: 2049-2052.
Cross, C. E.; Valacchi, G.; Schock, B.; Wilson, M.; Weber, S.; Eiserich, J.; Van der Vliet, A. (2002) Environmental oxidant pollutant effects on biological systems. Am. J. Respir. Crit. Care Med. 166: 544-550. Cyrys, J.; Heinrich, J.; Richter, K.; Wolke, G.; Wichmann, H. E. (2000) Sources and concentrations of indoor nitrogen dioxide in Hamburg (west German y) and Erfurt (east Germany). Sci. Total Environ. 250: 51-62. Cyrys, J.; Stolzel, M.; Heinrich, J.; Kreyling, W. G.; Menzel, N.; Wittmaack, K.; Tuch, T.; Wichmann, H.-E. (2003) Elemental composition and sources of fine and ultrafine ambient particles in Erfurt, Germany. Sci. Total Environ. 305: 143-156. Dab, W.; Medina, S.; Quénel, P.; Le Moullec, Y.; Le Tertre, A.; Thelot, B.; Monteil, C.; Lameloise, P.; Pirard, P.; Momas, I.; Ferry, R.; Festy, B. (1996) Short term respiratory health effects of ambient air pollution: results of the APHEA project in Paris. 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): S42-S46. Dales, R. E.; Cakmak, S.; Doiron, M. S. (2006) Gase ous air pollutants and hospitalization for respiratory disease in the neonatal period. Environ. Health Perspect. 114: 1751-1754.
Dales, R.; Burnett, R. T.; Smith-Doiron, M.; Stieb, D. M.; Brook, J. R. (2004) Air pollution and sudden infant death syndrome. Pediatrics 113: 628-631. 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.; Gone, H.; Linn, W. S.; Pellizzari, E. D.; Hu, Y. (2003) Asthma symptoms in Hispanic children and daily ambient exposures to toxic and cr iteria air pollutants. Environ. Health Perspect. 111: 647-656. Delfino, R. J.; Staimer, N.; Gillen, D.; Tjoa, T.; Sioutas, C.; Fung, K.; George, S. C.; Kleinman, M. T. (2006) Personal and ambient air pollution is associ ated with increased exhaled nitric oxide in children with asthma. Environ. Health Perspect. 114: 1736-1743. Delfino, R. J.; Zeiger, R. S.; Seltzer, J. M.; Street, D. H.; McLaren, C. E. (2002) Association of asthma symptoms with peak particulate air pollution and effect modification by anti-inflammatory medication use. Environ. Health Perspect. 110: A607-A617. Dennekamp, M.; Howarth, S.; Dick, C. A. J.; Cherrie, J. W.; Donaldson, K.; Seaton, A. (2001) Ultrafine particles and nitrogen oxides generated by gas a nd electric cooking. Occup. Environ. Med. 58: 511- 516.9 Dentener, F.; Drevet, J.; Lamarque, J. F.; Bey, I.; Ei ckhout, B.; Fiore, A. M.; Hauglustaine, D.; Horowitz, L. W.; Krol, M.; Kulshrestha, U. C.; Lawrence, M.; Galy-Lacaux, C.; Rast, S.; Shindell, D.; Stevenson, D.; Van Noije, T.; Atherton, C.; Bell, N.; Bergman, D.; Butler, T.; Cofala, J.; Collins, B.; Doherty, R.; Ellingsen, K.; Galloway, J.; Gauss, M.; Montanaro, V.; Müller, J. F.; Pitari, G.; Rodriguez, J.; Sanderson, M.; Solman, F.; Strahan, S.; Schultz, M.; Sudo, K.; Szopa, S.; Wild, O. (2006b) Nitrogen and sulfur de position on regional and global scales: a multi-model evaluation. Global Biogeochem. Cycles: 20(GB4003): 10.1029/2005GB002672. Dentener, F.; Stevenson, D.; Ellingsen, K.; Van Noije, T.; Schultz, M.; Amann, M.; Atherton, C.; Bell, N.; Bergmann, D.; Bey, I.; Bouwman, L.; Butler, T.; Cofala, J.; Collins, B.; Drevet, J.; Doherty, R.; Eickhout, B.; Eskes, H.; Fiore, A.; Gauss, M.; Ha uglustaine, D.; Horowitz, L.; Isaksen, I. S. A.; Josse, B.; Lawrence, M.; Krol, M.; Lamarque, J. F.; Montanaro, V.; Müller, J. F.; Peuch, V. H.; Pitari, G.; Pyle, J.; Rast, S.; Rodriguez, J.; Sanders on, M.; Savage, N. H.; Shindell, D.; Strahan, S.; et al. (2006a) The global atmospheric environment fo r the next generation. Environ. Sci. Technol. 40: 3586-3594. Desqueyroux, H.; Pujet, J.-C.; Prosper, M.; Le Mou llec, Y.; Momas, I. (2002) Effects of air pollution on adults with chronic obstructive pulmonary disease. Arch. Environ. Health 57: 554-560. Devalia, J. L.; Campbell, A. M.; Sapsford, R. J.; Ruszn ak, C.; Quint, D.; Godard, P.; Bousquet, J. Davies, R. J. (1993a) Effect of nitrogen dioxide on synthesis of inflammatory cytokines expressed by human bronchial epithelial cells in vitro. Am. J. Respir. Cell. Mol. Biol. 9: 271-278. Devalia, J. L.; Rusznak, C.; Herdman, M. J.; Trigg, C. J.; Tarraf, H.; Davies, R. J. (1994) Effect of nitrogen dioxide and sulphur dioxide on airway r esponse of mild asthmatic patients to allergen inhalation. Lancet 344: 1668-1671. Devalia, J. L.; Sapsford, R. J.; Cundell, D. R.; Ru sznak, C.; Campbell, A. M.; Davies, R. J. (1993b) Human bronchial epithelial cell dysfunction followi ng in vitro exposure to nitrogen dioxide. Eur. Respir. J. 6: 1308-1316. Devlin, R. B.; Horstman, D. P.; Gerrity, T. R.; Beck er, S.; Madden, M. C. (1999) Inflammatory response in humans exposed to 2.0 ppm nitrogen dioxide. Inhalation Toxicol. 11: 89-109. Devlin, R.; Horstman, D.; Becker, S.; Gerrity, T.; Ma dden, M.; Koren, H. (1992) Inflammatory response in humans exposed to 2.0 ppm NO 2 . Am. Rev. Respir. Dis. 145: A456. Dewanji, A.; Moolgavkar, S. H. (2000) A Poisson process approach for recurrent event data with environmental covariates. Environmetrics 11: 665-673. Di Giovanni, V.; Cagiano, R.; Carratu, M. R.; De Salvia, M. A.; Giustino, A.; Cuomo, V. (1994) Alterations in the ontogeny of rat pup ultrasonic vocalization produced by prenatal exposure to nitrogen dioxide. Psychopharmacology 116: 423-427. 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 resp iratory systems work group summary. Environ. Health Perspect. Suppl. 108(3): 483-490. Dimitroulopoulou, C.; Ashmore, M. R.; Byrne, M. A.; Kinnersley, R. P. (2001) Modelling of indoor exposure to nitrogen dioxide in the UK. Atmos. Environ. 35: 269-279. D’Ippoliti, D.; Forastiere, F.; Ancona, C.; Agabiti, N. ; Fusco, D.; Michelozzi, P.; Perucci, C. A. (2003) Air pollution and myocardial infarction in Rome: a case-crossover analysis. Epidemiology 14: 528- 535.10 Dockery, D. W.; Brunekreef, B. (1996) Longitudinal studies of air pollution effects on lung function. Am. J. Respir. Crit. Care Med. 154(suppl.): S250-S256. Dockery, D. W.; Luttmann-Gibson, H.; Rich, D. Q.; Link, M. S.; Schwartz, J. D.; Gold, D. R.; Koutrakis, P.; Verrier, R. L.; Mittleman, M. A. (2005) Particulate air pollution and nonfatal cardiac events. Part II. Association of air pollution with confirmed arrhythmias recorded by implanted defibrillators. Boston, MA: Health Effects Institute; research report no. 124; pp. 83-126; discussion; pp. 127-148. Available: http:// pubs.healtheffects.org/ [7 June, 2007]. 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. 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]. Dominici, F.; McDermott, A.; Zeger, S. L.; Samet, J. M. (2002) On the use of generalized additive models in time-series studies of air pollution and health. Am. J. Epidemiol. 156: 193-203. Douglas, G. J.; Price, J. F.; Page, C. P. (1994) A method for the long-term exposure of rabbits to environmental pollutant gases. Eur. Respir. J. 7: 1516-1526.
Downs, S. H.; Schindler, C.; Liu, L.-J. S.; Keidel, D.; Bayer-Oglesby, L.; Brutsche, M. H.; Gerbase, M. W.; Keller, R.; Künzli, N.; Leuenberger, P.; Probs t-Hensch, N. M.; Tschopp, J.-M.; Zellweger, J.- P.; Rochat, T.; Schwartz, J.; Ackermann-Liebrich, U.; the SALPADIA Team. (2007) Reduced exposure to PM 10 and attenuated age-related decline in lung function. N. Engl. J. Med. 357: 2338- 2347. Drechsler-Parks, D. M. (1995) Cardiac output effects of O 3 and NO 2 exposure in healthy older adults. Toxicol. Ind. Health 11: 99-109. Dunlea, E. J.; Herndon, S. C.; Nelson, D. D.; Volkamer, R. M.; San Martini, F.; Sheehy, P. M.; Zahniser, M. S.; Shorter, J. H.; Wormhoudt, J. C.; Lamb, B. K.; Allwine, E. J.; Gaffney, J. S.; Marley, N. A.; Grutter, M.; Marquez, C.; Blanco, S.; Cardenas, B.; Retama, A.; Ramon Villegas, C. R.; Kolb, C. E.; Molina, L. T.; Molina, M. J. (2007) Evaluation of nitrogen dioxide chemiluminescence monitors in a polluted urban environment. Atmos. Chem. Phys. 7: 2691-2704. Durant, J. L.; Busby, W. F., Jr.; Lafleur, A. L.; Penman, B. W.; Crespi, C. L. (1996) Human cell mutagenicity of oxygenated, nitrated and unsubstituted polycyclic aromatic hydrocarbons associated with urban aerosols. Mutat. Res. 371: 123-157. Dutton, S. J.; Hannigan, M. P.; Miller, S. L. ( 2001) Indoor pollutant levels from the use of unvented natural gas fireplaces in Boulder, Colorado. J. Air Waste Manage. Assoc. 51: 1654-1661. Eggleston, H. S. (1993) Uncertainties in the estim ates of emissions of VOCs from motor cars. In: Proceedings of the TNO/EURASAP workshop on th e reliability of VOC emission databases; June; The Netherlands: Delft, IMW-TNO Publication, P 93/040, pp. 59-73. Ehrlich, R. (1966) Effect of nitrogen dioxide on resist ance to respiratory infection. Bacteriol. Rev. 30: 604-614. Ehrlich, R.; Findlay, J. C.; Gardner, D. E. (1979) Eff ects of repeated exposures to peak concentrations of nitrogen dioxide and ozone on resistance to streptoc occal pneumonia. J. Toxicol. Environ. Health 5: 631-642.11 Ekberg, L. E. (1996) Relationships between indoor a nd outdoor contaminants in mechanically ventilated buildings. Indoor Air 6: 41-47. Elsom, D. M. (2002) Atmospheric pollution: a gl obal problem. 2nd ed. Blackwell Publishers. Oxford, United Kingdom: 422 pp. Erbas, B.; Kelly, A.-M.; Physick, B.; Code, C.; Edwards, M. (2005) Air pollution and childhood asthma emergency hospital admissions: estimating intra-city regional variations. Int. J. Environ. Health Res. 15: 11-20. ESRI. 2006. ESRI Data and Maps [DVD]. Redlands, CA: Environmental Systems Research Institute. Evans, H. L.; Laties, V. G.; Weiss, B. (1975) Behavioral effects of mercury and methylmercury. Fed. Proc. 34: 1858-1867. Evans, M. J.; Cabral, L. C.; Stephens, R. J.; Freem an, G. (1974) Acute kinetic response and renewal of the alveolar epithelium following injury by nitrogen dioxide. Chest 65 (suppl.): 62S-65S. Evans, M. J.; Cabral, L. J.; Stephens, R. J.; Freeman, G. (1973a) Cell division of alveolar macrophages in rat lung following exposure to NO 2 . Am. J. Pathol. 70: 199-208. Evans, M. J.; Cabral, L. J.; Stephens, R. J.; Freeman , G. (1973b) Renewal of alveolar epithelium in the rat following exposure to NO 2 . Am. J. Pathol. 70: 175-190. Evans, M. J.; Cabral-Anderson, L. J.; Freeman, G. (1977) Effects of NO2 on the lungs of aging rats: II. cell proliferation. Exp. Mol. Pathol. 27: 366-376. Evans, M. J.; Johnson, L. V.; Stephens, R. J.; Freem an, G. (1976) Renewal of the terminal bronchiolar epithelium in the rat following exposure to NO 2 or O 3 . Lab. Invest. 35: 246-257. Evans, M. J.; Stephens, R. J.; Cabral, L. J.; Freeman , G. (1972) Cell renewal in the lungs of rats exposed to low levels of NO 2 . Arch. Environ. Health 24: 180-188. Fairley, D. (1999) Daily mortality and air pollu tion 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://pubs .healtheffects.org/view.php?id=4 [12 February, 2008]. Fan, Z.; Chen, D.; Birla, P.; Kamens, R. M. (1995) Modeling of nitro-polycyclic aromatic hydrocarbon formation and decay in the atmosphere. Atmos. Environ. 29: 1171-1181. Fan, Z.; Kamens, R. M.; Hu, J.; Zhang, J.; McDow, S. (1996) Photostability of nitro-polycyclic aromatic hydrocarbons on combustion soot particles in sunlight. Environ. Sci. Technol. 30: 1358-1364.
Farchi, S.; Forastiere, F.; Cesaroni, G.; Peru cci, C. A. (2006) Environmental exposures and hospitalisation for respiratory conditions in children: a five year follow up study in Rome, Italy. Occup. Environ. Med. 63: 573-576. Farrow, A.; Greenwood, R.; Preece, S.; Golding, J. (1997) Nitrogen dioxide, the oxides of nitrogen, and infants’ health symptoms. Arch. Environ. Health 52: 189-194. Febo, A.; Perrino, C. (1991) Prediction and experiment al evidence for high air concentration of nitrous acid in indoor environments. Atmos. Environ. Part A 25: 1055-1061. Federal Register. (1971) National primary and secondary ambient air quality standards. F. R. (April 30) 36: 8186-8201.12 Federal Register. (1984) Proposed reaffirmation of the National Ambient Air Quality Standards for Nitrogen Dioxide. F. R. 49 (February 23): 6866-6879. Federal Register. (1985) Retention of the national am bient air quality standards for nitrogen dioxide: final rule. F. R. (June 19) 50: 25,532-25,545. Federal Register. (1987) Air quality criteria for carbon monoxide; air quality criteria for oxides of nitrogen. F. R. 52 (July 22): 27580. Federal Register. (1991) Draft criteria document for oxides of nitrogen. F. R. 56 (November 25): 59285. Federal Register. (1995) National ambient air quality standards for nitrogen dioxide: proposed decision. F. R. 60 (October 11): 52874-52889. Federal Register. (2005) Air quality criteria for oxi des of nitrogen. F. R. 70 (December 9): 73236-73237.
Fehsenfeld, F. C.; Dickerson, R. R.; Hübler, G.; Luke, W. T.; Nunnermacker, L. J.; Williams, E. J.; Roberts, J. M.; Calvert, J. G.; Curran, C. M.; De lany, A. C.; Eubank, C. S.; Fahey, D. W.; Fried, A.; Gandrud, B. W.; Langford, A. O.; Murphy, P. C.; Norton, R. B.; Pickering, K. E.; Ridley, B. A. (1987) A ground-based intercomparison of NO, NO x , and NO y measurement techniques. J. Geophys. Res. [Atmos.] 92: 14,710-14,722. Feilberg, A.; Kamens, R. M.; Strommen, M. R.; Nielsen, T. (1999) Modeling the formation, decay, and partitioning of semivolatile nitro-polycyclic arom atic hydrocarbons (nitronaphthalenes) in the atmosphere. Atmos. Environ. 33: 1231-1243. Feilberg, A.; Nielsen, T. (2001) Photodegradation of n itro-PAHs in viscous organic media used as models of organic aerosols. Environ. Sci. Technol. 35: 108-113. Fenters, J. D.; Findlay, J. C.; Port, C. D.; Ehrlich, R.; Coffin, D. L. (1973) Chronic exposure to nitrogen dioxide: immunologic, physiologic, and pathologic effects in virus-challenged squirrel monkeys. Arch. Environ. Health 27: 85-89.
Filleul, L.; Rondeau, V.; Vandentorren, S.; Le Moual, N.; Cantagrel, A.; Annesi-Maesano, I.; Charpin, D.; Declercq, C.; Neukirch, F.; Paris, C.; Vervloet, D.; Brochard, P.; Tessier, J. F.; Kauffmann, F.; Baldi, I. (2005) Twenty five year mortality and air pollution: results from the French PAARC survey. Occup. Environ. Med. 62: 453-460.
Finkelstein, M. M.; Jerrett, M.; DeLuca, P.; Finkelstein , N.; Verma, D. K.; Chapman, K.; Sears, M. R. (2003) Relation between income, air pollution and mo rtality: a cohort study. Can. Med. Assoc. J. 169: 397-402. Finkelstein, M. M.; Jerrett, M.; Sears, M. R. (2004) Traffic air pollution and mortality rate advancement periods. Am. J. Epidemiol. 160: 173-177. Finkelstein, M. M.; Jerrett, M.; Sears, M. R. ( 2005) Environmental inequality and circulatory disease mortality gradients. J. Epidemiol. Community Health 59: 481-487. Finlayson-Pitts, B. J.; Pitts, J. N., Jr. (2000) Ch emistry of the upper and lower atmosphere: theory, experiments and applications. San Diego, CA: Academic Press. Fisher, R. A. (1925) The correlation coefficient. In: Statistical methods for research workers. Edinburgh, UK: Oliver and Boyd. Available: http://psychclassics.yorku.ca/Fisher/Methods/chap6.htm (23 February, 2008). Folinsbee, L. J. (1992) Does nitrogen dioxide expos ure increase airways responsiveness? Toxicol. Ind. Health 8: 273-283.13 Forsberg, B.; Stjernberg, N.; Linné, R.; Segerstedt, B. ; Wall, S. (1998) Daily air pollution levels and acute asthma in southern Sweden. Eur. Respir. J. 12: 900-905. Fortmann, R.; Kariher, P.; Clayton, R. (2001) I ndoor air quality: residential cooking exposures. Final report. Sacramento, CA: State of California Air Resources Board; ARB Contract No. 97-330. Available: http://arb.ca.gov/research/abstracts/97-330.htm [22 May, 2007]. Frampton, M. W.; Boscia, J.; Roberts, N. J., Jr.; Azadniv, M.; Torres, A.; Cox, C.; Morrow, P. E.; Nichols, J.; Chalupa, D.; Frasier, L. M.; Gibb, F. R.; Speers, D. M.; Tsai, Y.; Utell, M. J. (2002) Nitrogen dioxide exposure: effects on airway a nd blood cells. Am. J. Physiol. 282: L155-L165. Frampton, M. W.; Morrow, P. E.; Cox, C.; Gibb, F. R.; Speers, D. M.; Utell, M. J. (1991) Effects of nitrogen dioxide exposure on pulm onary function and airway reactivity in normal humans. Am. Rev. Respir. Dis. 143: 522-527. Freeman, B. A.; Mudd, J. B. (1981) Reaction of ozone with sulfhydryls of human erythrocytes. Arch. Biochem. Biophys. 208: 212-220. Freeman, G.; Crane, S. C.; Furiosi, N. J.; Stephens, R. J.; Evans, M. J.; Moore, W. D. (1972) Covert reduction in ventilatory surface in rats during prolonged exposure to sub acute nitrogen dioxide. Am. Rev. Respir. Dis. 106: 563-579. Freeman, G.; Furiosi, N. J.; Haydon, G. B. (1966) Effects of continuous exposure of 0.8 ppm NO 2 on respiration of rats. Arch. Environ. Health 13: 454-456. Freeman, G.; Stephens, R. J.; Crane, S. C.; Furiosi, N. J. (1968) Lesion of the lung in rats continuously exposed to two parts per million of nitrogen dioxide. Arch. Environ. Health 17: 181-192. Fung, K. Y.; Khan, S.; Krewski, D.; Chen, Y. (2006) Association between air pollution and multiple respiratory hospitalizations among the elderly in Vancouver, Canada. Inha lation Toxicol. 18: 1005- 1011. Fung, K. Y.; Luginaah, I. N.; Gorey, K. M. (2007) Impact of air pollution on hospital admissions in Southwestern Ontario, Canada: generating hypot heses in sentinel high-exposure places. Environ. Health. 6: 18. 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. Fusco, D.; Forastiere, F.; Michelozzi, P.; Spadea, T. ; Ostro, B.; Arcà, M.; Perucci, C. A. (2001) Air pollution and hospital admissions for respiratory conditions in Rome, Italy. Eur. Respir. J. 17: 1143-1150. Gair, A. J.; Penkett, S. A. (1995) The effects of wind speed and turbulence on the performance of diffusion tube samplers. Atmos. Environ. 29: 2529-2533. Gair, A. J.; Penkett, S. A.; Oyola, P. (1991) Development of a simple passive technique for the determination of nitrogen-dioxide in remote continental locations. Atmos. Environ. Part A 25: 1927-1939. Galán, I.; Tobías, A.; Banegas, J. R.; Aránguez, E. (2003) Short-term effects of air pollution on daily asthma emergency room admissions. Eur. Respir. J. 22: 802-808. 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 mee ting and exhibition of the Air & Waste Management Association; June; San Diego, CA. Pittsburgh, PA: Air & Waste Management Association; paper no. 98-MP26.03.14 García Algar, Ó.; Pichini, S.; Basagaña, X.; Puig , C.; Vall, O.; Torrent, M.; Harris, J.; Sunyer, J.; Cullinan, P. (2004) Concentrations and determinants of NO 2 in homes of Ashford, UK and Barcelona and Menorca, Spain. Indoor Air 14: 298-304. García-Algar, Ó.; Zapater, M.; Figueroa, C.; Vall, O. ; Basagaña, X.; Sunyer, J.; Freixa, A.; Guardino, X.; Pichini, S. (2003) Sources and concentrations of i ndoor nitrogen dioxide in Barcelona, Spain. J. Air Waste Manage. Assoc. 53: 1312-1317. Garcia-Aymerich, J.; Tobias, A.; Antó, J. M.; Sunyer , J. (2000) Air pollution and mortality in a cohort of patients with chronic obstructive pulmonary disease: a time series analysis. J. Epidemiol. Community Health 54: 73-74. Gardner, D. E. (1982) Use of experimental airbor ne infections for monitoring altered host defenses. Environ. Health Perspect. 43: 99-107. Gardner, D. E.; Miller, F. J.; Blommer, E. J.; Coffin, D. L. (1979) Influence of exposure mode on the toxicity of NO 2 . Environ. Health Perspect. 30: 23-29. Garrett, M. H.; Hooper, M. A.; Hooper, B. M. (1999) Nitrogen dioxide in Aust ralian homes: levels and sources. J. Air Waste Manage. Assoc. 49: 76-81. Garrett, M. H.; Hooper, M. A.; Hooper, B. M.; Abrams on, M. J. (1998) Respiratory symptoms in children and indoor exposure to nitrogen dioxide and gas st oves. Am. J. Respir. Crit. Care Med. 158: 891- 895. Garty, B. Z.; Kosman, E.; Ganor, E.; Berger, V.; Garty, L.; Wietzen, T.; Waisman, Y.; Mimouni, M.; Waisel, Y. (1998) Emergency room visits of asthma tic children, relation to air pollution, weather, and airborne allergens. Ann. A llergy Asthma Immunol. 81: 563-570.
Gauderman, W. J.; Avol, E.; Gilliland, F.; Vora, H.; Thomas, D.; Berhane, K.; McConnell, R.; Kuenzli, N.; Lurmann, F.; Rappaport, E.; Margolis, H.; Ba tes, D.; Peters, J. (2004) 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.; Lurmann, F.; Kuenzli, N.; Gilliland, F.; Peters, J.; McConnell, R. (2005) Childhood asthma and exposure to traffic and nitrogen dioxide. Epidemiology 16: 737-743.
Gauderman, W. J.; Vora, H.; McConnell, R.; Berhane, K.; Gilliland, F.; Thomas, D.; Lurmann, F.; Avol, E.; Kunzli, N. (2007) Effect of exposure to tra ffic on lung development from 10 to 18 years of age: a cohort study. Lancet 369: 571-577. Gauvin, S.; Le Moullec, Y.; Bremont, F.; Momas, I.; Balducci, F.; Ciognard, F.; Poilve, M.-P.; Zmirou, D.; VESTA Investigators. (2001) Relationships between nitrogen dioxide personal exposure and ambient air monitoring measurements among childre n in three French metropolitan areas: VESTA study. Arch. Environ. Health 56: 336-341. Gavras, J. B.; Frampton, M. W.; Ryan, D. H.; Levy, P. C.; Looney, R. J.; Cox, C.; Morrow, P. E.; Utell, M. J. (1994) Expression of membrane antigens on human alveolar macrophages after exposure to nitrogen dioxide. Inhalation Toxicol. 6: 633-646. Gee, G. C.; Payne-Sturges, D. C. (2004) Environmental health disparities: a framework integrating psychosocial and environmen tal concepts. Environ. Health Perspect. 112: 1645-1653. Gehring, U.; Cyrys, J.; Sedlmeir, G.; Brunekreef, B.; Bellander, T.; Fischer, P.; Bauer, C. P.; Reinhardt, D.; Wichmann, H. E.; Heinrich, J. (2002) Traffic -related air pollution and respiratory health during the first 2 yrs. of life. Eur. Respir. J. 19: 690-698.15 Gehring, U.; Heinrich, J.; Krämer, U.; Grote, V.; Ho chadel, M.; Sugiri, D.; Kraft, M.; Rauchfuss, K.; Eberwein, H. G.; Wichmann, H.-E. (2006) Long-term exposure to ambient air pollution and cardiopulmonary mortality in women. Epidemiology 17: 545-551. Ghenu, A.; Rosant, J. M.; Sini, J. F. (2008) Dispersion of pollutants and estimation of emissions in a street canyon in Rouen, France. Environmental Modelling & Software. 23: 314-321. Gianetti, J.; Bevilacqua, S.; De Caterina, R. (2002) Inhaled nitric oxide: more than a selective pulmonary vasodilator. Eur. J. Clin. Invest. 32: 628-635. Gibson, T. L. (1983) Sources of direct-acting nitroarene mutagens in airborne particulate matter. Mutat. Res. 122: 115-121. Gilbert, N. L.; Gauvin, D.; Guay, M.; Héroux, M.-È.; Dupuis, G.; Legris, M.; Chan, C. C.; Dietz, R. N.; Lévesque, B. (2006) Housing characteristics and indoor concentrations of nitrogen dioxide and formaldehyde in Quebec City, Canada. Environ. Res. 102: 1-8. Gilbert, N. L.; Goldberg, M. S.; Beckerman, B.; Brook, J. R.; Jerrett, M. (2005) Assessing spatial variability of ambient nitrogen dioxide in Montr éal, Canada, with a land-use regression model. J. Air Waste Manage. Assoc. 55: 1059-1063. Gilbert, N. L.; Goldberg, M. S.; Brook, J. R.; Jerrett, M. (2007) The influence of highway traffic on ambient nitrogen dioxide concentration in the immediate vicinity of highways. Atmos. Environ. 41: 2670-2673. Gilliland, F. D.; McConnell, R.; Peters, J.; Gong, H, Jr. (1999) A theoretical basis for investigation ambient air pollution and children’s respiratory h ealth. Environ. Health Perspect. 107(suppl. 3): 403-407. Gilliland, F. D.; Rappaport, E. B.; Berhane, K.; Isla m, T.; Dubeau, L.; Gauderman, W. J.; McConnell, R. (2002) Effects of glutathione S -Transferase P1
, M1 , and T1 on acute respiratory illness in school children. Am. J. Respir. Crit. Care Med. 166: 346-351. Gilmour, M. I.; Park, P.; Selgrade, M. K. (1996) Increased immune and inflammatory responses to dust mite antigen in rats exposed to 5 ppm NO 2 . Fundam. Appl. Toxicol. 31: 65-70. Girman, J. R.; Apte, M. G.; Traynor, G. W.; Allen, J. R.; Hollowell, C. D. (1982) Pollutant emission rates from indoor combustion appliances and sidestream cigarette smoke. Environ. Int. 8: 213-221. Goings, S. A. J.; Kulle, T. J.; Bascom, R.; Sauder, L. R.; Green, D. J.; Hebel, J. R.; Clements, M. L. (1989) Effect of nitrogen dioxide exposure on su sceptibility to influenza A virus infection in healthy adults. Am. Rev. Respir. Dis. 139: 1075-1081. Goldberg, M. S.; Burnett, R. T.; Bailar, J. C., 3rd; Tamblyn, R.; Ernst, P.; Flegel, K.; Brook, J.; Bonvalot, Y.; Singh, R.; Valois, M. F.; Vincent, R. (2001) Identification of persons with cardiorespiratory conditions who are at risk of dying from the acute e ffects of ambient air particles. Environ. Health Perspect. 109 Suppl 4: 487-94. Gong, H., Jr., Linn, W. S.; Clark, K. W.; Anderson, K. R.; Geller, M. D.; Sioutas, C. (2005) Respiratory responses to exposures with fine particulates and n itrogen dioxide in the elderly with and without COPD. Inhalation Toxicol. 17: 123-132. Gonzales, M.; Qualls, C.; Hudgens, E.; Neas, L. (2005) Characterization of a spatial gradient of nitrogen dioxide across a United States-Mexico border city during winter. Sci. Total Environ. 337: 163-173. Gooch, P. C.; Luippold, H. E.; Creasia, D. A.; Brewen, J. G. (1977) Observations on mouse chromosomes following nitrogen dioxide inhalation. Mutat. Res. 48: 117-119.16 Goss, C. H.; Newsom, S. A.; Schildcrout, J. S.; Sheppard, L.; Kaufman, J. D. (2004) Effect of ambient air pollution on pulmonary exacerbations and lung function in cystic fibrosis. Am. J. Respir. Crit. Care Med. 169: 816-821. Gouveia, N.; Fletcher, T. (2000a) Respiratory diseases in children and outdoor air pollution in São Paulo, Brazil: a time series analysis. Occup. Environ. Med. 57: 477-483. Gouveia, N.; Fletcher, T. (2000b) Time series analysis of air pollution and mortality: effects by cause, age and socioeconomic status. J Epidemiol Community Health. 54: 750-5. Green, R. S.; Smorodinsky, S.; Kim, J. J.; McLaughlin, R.; Ostro, B. (2004) Proximity of California public schools to busy roads. Environ. Health Perspect. 112: 61-66. Grosovsky, A. J.; Sasaki, J. C.; Arey, J.; Eastmond, D. A.; Parks, K. K.; Atkinson, R. (1999) Evaluation of the potential health effects of the atmos pheric reaction products of polycyclic aromatic hydrocarbons. Cambridge, MA: Health Eff ects Institute; research report no. 84. 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. Hackney, J. D.; Linn, W. S.; Avol, E. L.; Shamoo, D. A.; Anderson, K. R.; Solomon, J. C.; Little, D. E.; Peng, R.-C. (1992) Exposures of older adults with chronic respiratory illness to nitrogen dioxide: a combined laboratory and field study. Am. Rev. Respir. Dis. 146: 1480-1486. Hackney, J. D.; Thiede, F. C.; Linn, W. S.; Pedersen, E. E.; Spier, C. E.; Law, D. C.; Fischer, D. A. (1978) Experimental studies on human health effects of air pollutants. IV. Short-term physiological and clinical effects of nitrogen dioxide e xposure. Arch. Environ. Health 33: 176-181. Hagen, J. A.; Nafstad, P.; Skrondal, A.; Bjorkly, S.; Magnus, P. (2000) Associations between outdoor air pollutants and hospitalization for respiratory diseases. Epidemiology 11: 136-140. Hajat, S.; Haines, A.; Goubet, S. A.; Atkinson, R. W. ; Anderson, H. R. (1999) Association of air pollution with daily GP consultations for asthma and othe r lower respiratory conditions in London. Thorax 54: 597-605. Hansen, C.; Neller, A.; Williams, G.; Simpson, R. (2006) Maternal exposure to low levels of ambient air pollution and preterm birth in Br isbane, Australia. BJOG 113: 935-941. Harré, E. S. M.; Price, P. D.; Ayrey, R. B.; Toop, L. J.; Martin, I. R.; Town, G. I. (1997) Respiratory effects of air pollution in chronic obstructive pulmonary disease: a three month prospective study. Thorax 52: 1040-1044. Harris, M. I.; Flegal, K. M.; Cowie, C. C.; Eberhardt, M. S.; Goldstein, D. E.; Little, R. R.; Wiedmeyer, H. M.; Byrd-Holt, D. D. (1998) Prevalence of diabetes, impaired fasting glucose, and impaired glucose tolerance in U.S. adults. The Third Na tional Health and Nutrition Examination Survey, 1988-1994. Diabetes Care. 21: 518-24. Hatch, G. E.; Slade, R.; Selgrade, M. K.; Stead , A. G. (1986) Nitrogen dioxide exposure and lung antioxidants in ascorbic acid-deficient guinea pigs. Toxicol. Appl. Pharmacol. 82: 351-359. Hayden, K. L.; Anlauf, K. G.; Hastie, D. R.; Bottenheim, J. W. (2003) Partitioning of reactive atmospheric nitrogen oxides at an elevated site in southern Quebec, Canada. J. Geophys. Res. [Atmos.] 108(D19): 10.1029/2002JD003188.17 Hazenkamp-von Arx, M. E.; Götschi, T.; Ackermann-Liebrich, U.; Bono, R.; Burney, P.; Cyrys, J.; Jarvis, D.; Lillienberg, L.; Luczynska, C.; Maldonado, J. A.; Jaén, A.; de Marco, R.; Mi, Y.; Modig, L.; Bayer-Oglesby, L.; Payo, F.; Soon, A.; Sunyer, J.; Villani, S.; Weyler, J.; Künzli, N. (2004) PM 2.5 and NO 2 assessment in 21 European study centres of ECRHS II: annual means and seasonal differences. Atmos. Environ. 38: 1943-1953. Hazucha, M. J.; Folinsbee, L. J.; Seal, E.; Bromberg, P. A. (1994) Lung function response of healthy women after sequential exposures to NO 2 and O 3 . Am. J. Respir. Crit. Care Med. 150: 642-647. Heal, M. R.; O’Donoghue, M. A.; Cape, J. N. (1999) Ov erestimation of urban nitrogen dioxide by passive diffusion tubes: a comparative exposure and model study. Atmos. Environ. 33: 513-524. Heeb J. L.; Gmel G.; Rehm J.; Mohler-Kuo M. (2008) Exploring daily variations of drinking in the Swiss general population. A growth curve analysis. In t. J. Methods Psychiatr. Res. 17: 1-11. Helleday, R.; Huberman, D.; Blomberg, A.; Stjer nberg, N.; Sandström, T. (1995) Nitrogen dioxide exposure impairs the frequency of the mucociliary ac tivity in healthy subjects. Eur. Respir. J. 8: 1664-1668. Henneberger, A.; Zareba, W.; Ibald-Mulli, A.; Rückerl, R.; Cyrys, J.; Couderc, J.-P.; Mykins, B.; Woelke, G.; Wichmann, H.-E.; Peters, A. (2005) Repolarization changes induced by air pollution in ischemic heart disease patients. Environ. Health Perspect. 113: 440-446. Henry, M. C.; Findlay, J.; Spangler, J.; Ehrlich, R. (1970) Chronic toxicity of NO 2 in squirrel monkeys: III. effect on resistance to bacterial and viral infection. Arch. Environ. Health 20: 566-570. Higgins, B. G.; Francis, H. C.; Yates, C. J.; Warburton, C. J.; Fletcher, A. M.; Reid, J. A.; Pickering, C. A. C.; Woodcock, A. A. (1995) Effects of air pollution on symptoms and peak expiratory flow measurements in subjects with obstructive airways disease. Thorax 50: 149-155. Higgins, B. G.; Francis, H. C.; Yates, C.; Warburton, C. J.; Fletcher, A. M.; Pickering, C. A. C.; Woodcock, A. A. (2000) Environmental exposure to air pollution and allergens and peak flow changes. Eur. Respir. J. 16: 61- 66. Hill, A. B. (1965) The environment and disease: associ ation or causation? Proc. R. Soc. Med. 58: 295- 300. Hilliard J. C.; Wheeler R. W. (1979). Nitrogen Dioxide in Engine Exhaust. Paper presented at the SAE Passenger Car Meeting - Trans 88. 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. Hinwood, A. L.; De Klerk, N.; Rodriguez, C.; Jacoby, P.; Runnion, T.; Rye, P.; Landau, L.; Murray, F.; Feldwick, M.; Spickett, J. (2006) The relations hip between changes in daily air pollution and hospitalizations in Perth, Australia 1992-1998: a case-cr ossover study. Int. J. Environ. Health Res. 16: 27-46. Hirsch, T.; Weiland, S. K.; Von Mutius, E.; Safeca, A. F.; Grafe, H.; Csaplovics, E.; Duhme, H.; Keil, U.; Leupold, W. (1999) Inner city air pollution and r espiratory health and atopy in children. Eur. Respir. J. 14: 669-677. Hochadel, M.; Heinrich, J.; Gehring, U.; Morgenster n, V.; Kuhlbusch, T.; Link, E.; Wichmann, H.-E.; Krämer, U. (2006) Predicting long-term average c oncentrations of traffic-related air pollutants using GIS-based information. Atmos. Environ. 40: 542-553.18 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- 141. Available: http://www.healtheffects.org/Pubs/TimeSeries.pdf [12 May, 2004]. Hoek, G.; Brunekreef, B. (1994) Effects of low-level winter air pollution concentrations on respiratory health of Dutch children. Environ. Res. 64: 136-150. 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.; Brunekreef, B.; Goldbohm, S.; Fischer, P.; Va n den Brandt, P. A. (2002) Association between mortality and indicators of traffic-related air po llution in the Netherlands: a cohort study. Lancet 360: 1203-1209. 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. 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. Horowitz, L. W.; Fiore, A. M.; Milly, G. P.; Cohen, R. C.; Perring, A.; Wooldridge, P. J.; Hess, P. G.; Emmons, L. K.; Lamarque, J. F. (2007) Observa tional constraints on the chemistry of isoprene nitrates over the eastern United States. J. Geophys. Res. (Atmos.) 112(D12S08): 10.1029/2006JD007747.
Horowitz, L. W.; Walters, S.; Mauzerall, D. L.; E mmons, L. K.; Rasch, P. J.; Granier, C.; Tie, X.; Lamarque, J.-F.; Schultz, M. G.; Tyndall, G. S.; Orlando, J. J.; Brasseur, G. P. (2003) A global simulation of tropospheric ozone and related tracers: description and evaluation of MOZART, version 2. J. Geophys. Res. [Atmos.] 108(D24): 10.1029/2002JD002853. Hubbard, A. K.; Symanowicz, P. T.; Thibodeau, M.; Thrall, R. S.; Schramm, C. M.; Cloutier, M. M; Morris, J. B. (2002) Effect of nitrogen dioxide on ovalbumin-induced allergic airway disease in a murine model. J. Toxicol. Environ. Health A 65: 1999-2005. Hwang, J.-S.; Chan, C.-C. (2002) Effects of air pollution on daily clinic visits for lower respiratory tract illness. Am. J. Epidemiol. 155: 1-10. Ichinose, T.; Fujii, K.; Sagai, M. (1991) Experime ntal studies on tumor promotion by nitrogen dioxide. Toxicology 67: 211-225. Ichinose, T.; Sagai, M. (1992) Combined exposure to NO 2 , O 3 and H 2 SO 4 -aerosol and lung tumor formation in rats. Toxicology 74: 173-184. Ilabaca, M.; Olaeta, I.; Campos, E.; Villaire, J.; Tellez-Rojo, M. M.; Romieu, I. (1999) Association between levels of fine particulate and emerge ncy visits for pneumonia and other respiratory illnesses among children in Santiago, Chile. J. Air Waste Manage. Assoc. 49: 154-163. Inoue, H.; Fukunaga, A.; Okubo, S. (1981) Mutageni c effects of nitrogen dioxide combined with methylurea and ethylurea in Drosophila melanogaster . Mutat. Res. 88: 281-290. Institute of Medicine (IOM). (2007) Improving the presumptive disability decision-making process for veterans. Washington, DC: The National Academy of Sciences. Available: http://www.nap.edu/catalog.php?reco rd_id=11908 (11 February, 2008).19 International Agency for Research on Cancer (IA RC). (2006) IARC monographs on the evaluation of carcinogenic risks to humans: Preamble. Lyon, France: International Agency for Research on Cancer. (IARC monographs on the evaluation of carcinogenic risks to humans). Available: http://monographs.iarc.fr/ENG/Preamble/CurrentPreamble.pdf (21 February, 2008). Iqbal, Z. M. (1984) In-vivo nitrosation of amines in mice by inhaled nitrogen dioxide and inhibition of biosynthesis of N -nitrosamines. In: O’Neill, I. K.; Von Bors tel, R. C.; Miller, C. T.; Long, J.; Bartsch, H., eds. N -nitroso compounds: occurrence, biological effects and relevance to human cancer: proceedings of the VIIIth international symposium on N -nitroso compounds; September 1983; Banff, Canada. Lyon, France: Internati onal Agency for Research on Cancer; pp. 291-300. (IARC scientific publications no. 57). Iqbal, Z. M.; Dahl, K.; Epstein, S. S. (1980) Role of nitrogen dioxide in the biosynthesis of nitrosamines in mice. Science (Washington, DC) 207: 1475-1477.Iqbal, Z. M.; Dahl, K.; Epstein, S. S. (1981) Biosynthesis of dimethylnitrosamine in dimethylaminetreated mice after exposure to nitrogen dioxide . JNCI J. Natl. Cancer Inst. 67: 137-141.
Islam, T.; Gauderman, W. J.; Berhane, K.; McConnell, R.; Avol, E.; Peters, J. M.; Gilliland, F. D. (2007) The relationship between air pollution, lung f unction and asthma in adolescents. Thorax 62: 957- 963.
Isomura, K.; Chikahira, M.; Teranishi, K.; Hamada , K. (1984) Induction of mutations and chromosome aberrations in lung cells following in vivo exposure of rats to nitrogen oxides. Mutat. Res. 136: 119-125. Ito, K. (2004) Revised ozone risk estimates for daily mortality and hospitalizations in Detroit, Michigan [personal communication with attachments to Jee Young Kim]. New York, NY: New York University School of Medicine, Nelson Institu te of Environmental Medicine; October 31. Ito, K. (2007) Association between doarse particles a nd asthma emergency department (ED) visits in New York City. Presented at: American Thoracic Societ y international conference; San Francisco, CA. Jacob, D. J. (1999) Introduction to atmospheric chemistry. Princeton, NJ: Princeton University Press. Jacobson, M. Z. (2002) Atmospheric pollution: history, science, and regulation. New York, NY: Cambridge University Press. 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.; 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. Jalaludin, B.; Morgan, G.; Lincoln, D.; Sheppeard, V.; Simpson, R.; Corbett, S. (2006) Associations between ambient air pollution and daily emerge ncy department attendances for cardiovascular disease in the elderly (65+ years), Sydney, Australia. J. Exposure Sci. Environ. Epidemiol. 16: 225- 237. Jarvis, D. L.; Leaderer, B. P.; Chinn, S.; Burney, P. G. (2005) Indoor nitrous acid and respiratory symptoms and lung function in adults. Thorax 60: 474-479. 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 ai rway response of atopic asthmatics to inhaled allergen: dose- and time-dependent effects. Am. J. Respir. Crit. Care Med. 160: 33-39.20 Jerrett, M. (2007) Does traffic-related air pollution c ontribute to respiratory disease formation in children? Eur. Respir. J. 29: 825-826. Jerrett, M.; Burnett, R. T.; Brook, J.; Kanaroglou, P.; Giovis, C.; Finkelstein, N.; Hutchison, B. (2004) Do socioeconomic characteristics modify the short term association between air pollution and mortality? Evidence from a zonal time series in Hamilton, Canada. J. Epidemiol. Community Health 58: 31-40. Jerrett, M.; Finkelstein, M. (2005) Geographies of risk in studies linking chronic air pollution exposure to health outcomes. J. Toxicol. Environ. Health Part A 68: 1207-1242. Jet Propulsion Laboratory. (2006) Chemical kinetics and photochemical data for use in atmospheric studies. Evaluation number 15. Pasadena, CA: Calif ornia Institute of Technology. JPL publication 06-2. Jet Propulsion Laboratory. (2003). Chemical kinetics and photochemical data for use in atmospheric studies. (No. Evaluation number 15. JPL publication 06-2). Pasadena, CA: Jet Propulsion Laboratory. Jörres, R.; Magnussen, H. (1990) Airways response of asthmatics after a 30 min exposure, at resting ventilation, to 0.25 ppm NO 2 or 0.5 ppm SO 2 . Eur. Respir. J. 3: 132-137. Jörres, R.; Magnussen, H. (1991) Effect of 0.25 ppm nitrogen dioxide on the airway response to methacholine in asymptomatic asthmatic patients. Lung 169: 77-85. Jörres, R.; Nowak, D.; Grimminger, F.; Seeger, W.; Oldigs, M.; Magnussen, H. (1995) The effect of 1 ppm nitrogen dioxide on bronchoalv eolar lavage cells and inflammatory mediators in normal and asthmatic subjects. Eur. Respir. J. 8: 416-424. Just, J.; Ségala, C.; Sahraoui, F.; Priol, G.; Grimfeld, A.; Neukirch, F. (2002) Short-term health effects of particulate and photochemical air pollution in ast hmatic children. Eur. Respir. J. 20: 899-906. Karr, C.; Lumley, T.; Shepherd, K.; Davis, R.; Lars on, T.; Ritz, B.; Kaufman, J. (2006) A case-crossover study of wintertime ambient air pollution and infa nt bronchiolitis. Environ. Health Perspect. 114: 277-281. Katsouyanni, K.; Schwartz, J.; Spix, C.; Touloumi, G.; Zmirou, D.; Zanobetti, A.; Wojtyniak, B.; Vonk, J. M.; Tobias, A.; Pönkä, A.; Medina, S.; Bachárová, L.; Andersen, H. R. (1996) Short term effects of air pollution on health: a European approach using epidemiology time series data: the APHEA protocol. 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. Community Health 50(suppl. 1): S12-S18. Katsouyanni, K.; Touloumi, G.; Samoli, E.; Grypar is, A.; Le Tertre, A.; Monopolis, Y.; Rossi, G.; Zmirou, D.; Ballester, F.; Boumghar, A.; Anderson, H. R.; Wojtyniak, B.; Paldy, A.; Braunstein, R.; Pekkanen, J.; Schindler, C.; Schwartz, J. (2001) Confounding and effect modification in the short-term effects of ambient particles on total mo rtality: results from 29 European cities within the APHEA2 project. Epidemiology 12: 521-531. Katsouyanni, K.; Touloumi, G.; Samoli, E.; Petasakis, Y.; Analitis, A.; Le Tertre, A.; Rossi, G.; Zmirou, D.; Ballester, F.; Boumghar, A.; Anderson, H. R.; Wojtyniak, B.; Paldy, A.; Braunstein, R.; Pekkanen, J.; Schindler, C.; Schwartz, J. (2003) Se nsitivity analysis of various models of shortterm effects of ambient particles on total mortality in 29 cities in APHEA2. In: Revised analyses of time-series studies of air pollution and health. Special report. Boston, MA: Health Effects Institute; pp. 157-164. Available: http://www.healtheffects. org/Pubs/TimeSeries.pdf [18 October, 2004].21 Kattan, M.; Gergen, P. J.; Eggleston, P.; Visness, C. M.; Mitchell, H. E. (2007) Health effects of indoor nitrogen dioxide and passive smoking on urban asthm atic children. J. Allergy Clin. Immunol. 120: 618-624. Kauffmann, F.; Post Genome Respiratory Epidemiology Group. (2004) Post-genome respiratory epidemiology: a multidisciplinary challenge. Eur. Respir. J. 24: 471-480.
Kawamoto, T.; Matsuno, K.; Arashidani, K.; Yoshik awa, M.; Kayama, F.; Kodama, Y. (1993) Personal exposure to nitrogen dioxide from indoor heater s and cooking stoves. Arch. Environ. Contam. Toxicol. 25: 534-538. Kean, A. J.; Grosjean, E.; Grosjean, D.; Harley, R. A. (2001) On-road measurement of carbonyls in California light-duty vehicle emissions. Environ. Sci. Technol. 35: 4198-4204. Kebabian P. L.; Robinson W. A.; Freedman A. (2007) Optical extinction monitor using cw cavity enhanced detection. Rev. Sci. Instrum. 78: 063102. Kelly, F. J.; Blomberg, A.; Frew, A.; Holgate, S. T.; Sandstrom, T. (1996a) Antioxidant kinetics in lung lavage fluid following exposure of humans to nitroge n dioxide. Am. J. Respir. Crit. Care Med. 154: 1700-1705. Kelly, F. J.; Cotgrove, M.; Mudway, I. S. (1996b) Respiratory tract lining fluid antioxidants: the first line of defence against gaseous pollutants. Ce nt Eur J Public Health. 4 Suppl: 11-4. Kelly, F. J.; Dunster, C.; Mudway, I. (2003) Air po llution and the elderly: oxidant/antioxidant issues worth consideration. Eur. Respir. J. Suppl. 40: 70S-75S. Kelly, F. J.; Tetley, T. D. (1997) Nitrogen dioxide de pletes uric acid and ascorbic acid but not glutathione from lung lining fluid. Biochem. J. 325: 95-99. Kerr, H. D.; Kulle, T. J.; McIlhany, M. L.; Swidersk y, P. (1979) Effects of nitrogen dioxide on pulmonary function in human subjects: an environmenta l chamber study. Environ. Res. 19: 392-404. Kesten, S.; Szalai, J.; Dzyngel, B. (1995) Air quality and the frequency of emergency room visits for asthma. Ann. Allergy Asthma Immunol. 74: 269-273. Kim, D.; Sass-Kortsak, A.; Purdham, J. T.; Dales, R. E.; Brook, J. R. (2006) Associations between personal exposures and fixed-site ambient measure ments of fine particulate matter, nitrogen dioxide, and carbon monoxide in Tor onto, Canada. J. Exposure Sci. Environ. Epidemiol. 16: 172- 183. Kim, E.; Hopke, P. K.; Pinto, J. P.; Wilson, W. E. (2005) Spatial variability of fine particle mass, components, and source contributions during the regi onal air pollution study in St. Louis. Environ. Sci. Technol. 39: 4172-4179. Kim, J. J.; Smorodinsky, S.; Lipsett, M.; Singer, B. C.; Hodgson, A. T.; Ostro, B. (2004a) Traffic-related air pollution near busy roads: the East Bay child ren’s Respiratory Health Study. Am. J. Respir. Crit. Care Med. 170: 520-526. Kim, S. U.; Koenig, J. Q.; Pierson, W. E.; Hanley, Q. S. (1991) Acute pulmonary effects of nitrogen dioxide exposure during exercise in competitive athletes. Chest 99: 815-819. Kim, S.-Y.; Lee, J.-T.; Hong, Y.-C.; Ahn, K.-J.; Kim, H. (2004b) 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. Kim, S-Y.; O’Neill, M.; Lee, J-T.; Cho, Y.; Kim, J.; Kim, H. (2007) Air pollution, socioeconomic position, and emergency hospital visits for asthma in Seoul, Korea. Int. Arch. Occup. Environ. Health 80: 701-710.22 Kinney, P. L.; Özkaynak, H. (1991) Associations of daily mortality and air pollution in Los Angeles County. Environ. Res. 54: 99-120.
Kinsella, J. P.; Cutter, G. R.; Walsh, W. F.; Gerstmann, D. R.; Bose, C. L.; Hart, C.; Sekar, K. C.; Auten, R. L.; Bhutani, V. K.; Gerdes, J. S.; George, T. N.; Southgate, W. M.; Carriedo, H.; Couser, R. J.; Mammel, M. C.; Hall, D. C.; Pappagallo, M.; Sardesai, S.; Strain, J. D.; Baier, M.; Abman, S. H. (2006) Early inhaled nitric oxide therapy in premat ure newborns with respiratory failure. N. Engl. J. Med. 355: 354-364. Kirby, C.; Fox, M.; Waterhouse, J.; Drye, T. ( 2001) Influences of environmental parameters on the accuracy of nitrogen dioxide passive diffusion tubes for ambient measurement. J. Environ. Monit. 3: 150-158. Kirchstetter, T. W.; Harley, R. A. (1996) Measure ment of nitrous acid in motor vehicle exhaust. Environmental Science and Technology. 30: 2843-2849. Kitabatake, M.; Yamamoto, H.; Yuan, P. F.; Manjurul , H.; Murase, S.; Yamauchi, T. (1995) Effects of exposure to NO 2 or SO 2 on bronchopulmonary reaction induced by Candida albicans in guinea pigs. J. Toxicol. Environ. Health 45: 75-82. Kleeberger, S. R. (2005) Genetic aspects of pulmonary responses to inhaled pollutants. Exp. Toxicol. Pathol. 57(suppl. 1): 147-153. Kleinman, M. T.; Bailey, R. M.; Linn, W. S.; Anderson, K. R.; Whynot, J. D.; Shamoo, D. A.; Hackney, J. D. (1983) Effects of 0.2 ppm nitrogen di oxide on pulmonary function and response to bronchoprovocation in asthmatics. J. Toxicol. Environ. Health 12: 815-826. Kleinman, M. T.; Mautz, W. J. (1991) The effects of exercise on dose and dose distribution of inhaled automotive pollutants. Cambridge, MA: Health Effects Institute; research report no. 45. Klepeis, N. E.; Nelson, W. C.; Ott. W. R.; Robinson, J. P. Tsang, A. M.; Switzer, P.; Behar, J. V.; Hern, S. C.; Engelmann, W. H. (2001) The National Human Activity Pattern Survey (NHAPS): a resource for assessing exposure to environmental pollutants. J. Exposure Anal. Environ. Epidemiol. 11: 231-252. Ko, F. W. S.; Tam, W.; Wong, T. W.; Lai, C. K. W.; Wong, G. W. K.; Leung, T.-F.; Ng, S. S. S.; Hui, D. S. C. (2007) Effects of air pollution on asthma hosp italization rates in different age groups in Hong Kong. Clin. Exp. Allergy 37: 1312-1319. Kobayashi, T.; Miura, T. (1995) Concentration- a nd time-dependent increase in specific airway resistance after induction of airway hyperresponsiveness by subchronic exposure of guinea pigs to nitrogen dioxide. Fundam. Appl. Toxicol. 25: 154-158. Kochanek, K. D.; Murphy, S. L.; Anderson, R. N. ; Scott, C. (2004) Deaths: final data for 2002. Hyattsville, MD: U.S. Department of Health & Human Services, National Center for Health Statistics; DHHS publication no. (PHS) 2005-1120. (Na tional vital statistics reports: v. 53, no. 5). Available: http://www.cdc.gov/nchs/data/ nvsr/nvsr53/nvsr53_05.pdf [3 August, 2005].
Kodama, Y.; Arashidani, K.; Tokui, N.; Kawamoto, T.; Matsuno, K.; Kunugita, N.; Minakawa, N. (2002) Environmental NO 2 concentration and exposure in daily life along main roads in Tokyo. Environ. Res. A 89: 236-244. Koenig, J. Q.; Covert, D. S.; Pierson, W. E.; Hanley, Q. S.; Rebolledo, V.; Dumler, K.; McKinney, S. E. (1994) Oxidant and acid aerosol exposure in health y subjects and subjects with asthma. Part I: effects of oxidants, combined with sulfuric or nitric acid, on the pulmonary function of adolescents with asthma. Cambridge, MA: Health Effects Institute; pp. 1-36; research report no. 70.23 Koutrakis, P.; Suh, H. H.; Sarnat, J. A.; Brown, K. W.; Coull, B. A.; Schwartz, J. (2005) Characterization of particulate and gas exposures of sensitive popul ations living in Baltimore and Boston. Boston, MA: Health Effects Institute; research report no. 131. Krämer, U.; Koch, T.; Ranft, U.; Ring, J.; Behrendt, H. (2000) Traffic-related air pollution is associated with atopy in children living in urban areas. Epidemiology 11: 64-70. Krewski, D.; Burnett, R. T.; Goldberg, M. S.; Hoove r, 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 morta lity: a special report of the Institute’s Particle Epidemiology Reanalysis Project. Cambridge, MA: Health Effects Institute. Available: http://pubs.healtheffects.org/view.php?id=6 [6 March, 2007]. Kripke, B. J.; Sherwin, R. P. (1984) Nitrogen dioxide exposure - influence on rat testes. Anesth. Analg. (NY) 63: 526-528. Krupa, S. V.; Legge, A. H. (2000) Passive sampling of ambient, gaseous air pollutants: an assessment from an ecological perspective. Environ. Pollut. 107: 31-45. Kulkarni, M. M.; Patil, R. S. (2002) An empirical model to predict indoor NO 2 concentrations. Atmos. Environ. 36: 4777-4785. Kumae, T.; Arakawa, H. (2006) Comparison of effect s of in vivo nitrogen dioxide exposure starting from different periods on alveolar macrophage activity, assessed by a chemiluminescence technique in Brown-Norway rats. Luminescence 21: 226-232. Kunimoto, M.; Mochitate, K.; Kaya, K.; Miura, T.; K ubota, K. (1984) Effects of nitrogen dioxide on red blood cells of rats: alterations of cell membrane components and populational changes of red blood cells during in vivo exposure to NO 2 . Environ. Res. 33: 361-369. Künzli, N. (2005) Unifying susceptibility, exposure, and time: discussion of unifying analytic approaches and future directions. J. Toxicol. Environ. Health A 68: 1263-1271.
La Rovere, M. T.; Pinna, G. D.; Maestri, R.; Mortara, A.; Capomolla, S.; Febo, O.; Ferrari, R.; Franchini, M.; Gnemmi, M.; Opasich, C.; Riccardi, P. G.; Traversi, E.; Cobelli, F. (2003) Short-term heart rate variability strongly predicts sudden cardiac deat h in chronic heart failure patients. Circulation 107: 565-570. Lagorio, S.; Forastiere, F.; Pistelli, R.; Iavarone, I. ; Michelozzi, P.; Fano, V.; Marconi, A.; Ziemacki, G.; Ostro, B. D. (2006) Air pollution and lung f unction among susceptible adult subjects: a panel study. Environ. Health: Global Access Sci. Source 5: 11. Available: http://www.ehjournal.net/content/5/1/11 [16 January, 2006]. Lai, C. H.; Chen, K. S.; Ho, Y. T.; Chou, M. S. (2004a) Characteristics of C2-C15 hydrocarbons in the air of urban Kaohsiung, Taiwan. Atmos. Environ. 38: 1997-2011. Lai, H. K.; Kendall, M.; Ferrier, H.; Lindup, I.; Alm, S.; Hänninen, O.; Jantunen, M.; Mathys, P.; Colvile, R.; Ashmore, M. R.; Cullinan, P.; Nieuwenhu ijsen, M. J. (2004b) Personal exposures and microenvironment concentrations of PM 2.5 , VOC, NO 2 and CO in Oxford, UK. Atmos. Environ. 38: 6399-6410. Lal, S.; Patil, R. S. (2001) Monitoring of atmospheri c behaviour of NOx from vehicular traffic. Environ. Monit. Assess. 68: 37-50. Lammel, G.; Cape, J. N. (1996) Nitrous acid and nitr ite in the atmosphere. Chem Soc Rev. 25: 361-369.24 Lamsal, L. N.; Martin, R. V.; Van Donkelaar, A.; Steinbacher, M.; Celarier, E. A.; Bucsela, E.; Dunlea, E. J.; Pinto, J. P. (2008) Ground-level nitrogen di oxide concentrations inferred from the satelliteborne ozone monitoring instrument. J. Geophys. Res. (Atmos.): in press. Last, J. A.; Gerriets, J. E.; Hyde, D. M. (1983) Syne rgistic effects on rat lungs of mixtures of oxidant air pollutants (ozone or nitrogen dioxide) and respirab le aerosols. Am. Rev. Respir. Dis. 128: 539-544. Le Tertre, A.; Quenel, P.; Eilstein, D.; Medina, S. ; Prouvost, H.; Pascal, L.; Boumghar, A.; Saviuc, P.; Zeghnoun, A.; Filleul, L.; Declercq, C.; Cassadou, S.; Le Goaster, C. (2002) Short-term effects of air pollution on mortality in nine French cities: a quantitative summary. Arch. Environ. Health 57: 311-319. Leaderer, B. P.; Zagraniski, R. T.; Berwick, M.; Stolwijk, J. A. J. (1986) Assessment of exposure to indoor air contaminants from combustion sources: methodology and application. Am. J. Epidemiol. 124: 275-289. Lee, B. E.; Ha, E. H.; Park, H. S.; Kim, Y. J.; Hong, Y. C.; Kim, H.; Lee, J. T. (2003) Exposure to air pollution during different gestational phases contributes to risks of low birth weight. Hum. Reprod. 18: 638-643. Lee, I.-M.; Tsai, S.-S.; Chang, C.-C.; Ho, C.-K.; Yang, C.-Y. (2007) Air pollution and hospital admissions for chronic obstructive pulmonary disease in a tropical city: Kaohsiung, Taiwan. Inhalation Toxicol. 19: 393-398. Lee, K.; Levy, J. I.; Yanagisawa, Y.; Spengler, J. D.; Billick, I. H. (1998) The Boston Residential Nitrogen Dioxide Characterization Study: classification and prediction of indoor NO 2 exposure. J. Air Waste Manage. Assoc. 48: 736-742. Lee, K.; Xue, J.; Geyh, A. S.; Özkaynak, H.; Leader er, B. P.; Weschler, C. J.; Spengler, J. D. (2002) Nitrous acid, nitrogen dioxide, a nd ozone concentrations in resi dential environments. Environ. Health Perspect. 110: 145-150. Lee, K.; Yanagisawa, Y.; Spengler, J. D.; Billick, I. H. (1995) Classification of house characteristics based on indoor nitrogen dioxide concen trations. Environ. Int. 21: 277-282. Lee, K.; Yanagisawa, Y.; Spengler, J. D.; Fukumura, Y.; Billick, I. H. (1996) Classification of house characteristics in a Boston residential nitrogen dioxide characterization study. Indoor Air 6: 211- 216. Lee, K.; Yang, W.; Bofinger, N. D. (2000) Impact of microenvironmental nitroge n dioxide concentrations on personal exposures in Australia. J. Air Waste Manage. Assoc. 50: 1739-1744. Lee, S. C.; Chan, L. Y.; Chiu, M. Y. (1999) Indoor and outdoor air quality investigation at 14 public places in Hong Kong. Environ. Int. 25: 443-450. Lee, S. L.; Wong, W. H. S.; Lau, Y. L. (2006) Association between air pollution and asthma admission among children in Hong Kong. Clin. Exp. Allergy 36: 1138-1146.Lee, Y.-L.; Lin, Y.-C.; Lee, Y.-C.; Wang, J.-Y.; Hsiue, T.-R.; Guo, Y. L. (2004) Glutathione Stransferase P1 gene polymorphism and air pollution as interactive risk factors for childhood asthma. Clin. Exp. Allergy 34: 1707-1713. Leem, J.-H.; Kaplan, B. M.; Shim, Y. K.; Pohl, H. R.; Gotway, C. A.; Bullard, S. M.; Rogers, J. F.; Smith, M. M.; Tylenda, C. A. (2006) Exposures to air pollutants during pregnancy and preterm delivery. Environ. Health Perspect. 114: 905-910.25 Levesque, B.; Allaire, S.; Gauvin, D.; Koutraki s, P.; Gingras, S.; Rhainds, M.; Prud’Homme, H.; Duchesne, J.-F. (2001) Wood-burning appliances a nd indoor air quality. Sci. Total Environ. 281: 47-62. Levy, J. I.; Lee, K.; Spengler, J. D.; Yanagisawa, Y. (1998a) Impact of residential nitrogen dioxide exposure on personal exposure: an international study. J. Air Waste Manage. Assoc. 48: 553-560. Levy, J. I.; Lee, K.; Yanagisawa, Y.; Hutchinson, P. ; Spengler, J. D. (1998b) Determinants of nitrogen dioxide concentrations in indoor ice skati ng rinks. Am. J. Public Health 88: 1781-1786.
Lewné, M.; Nise, G.; Lind, M. L.; Gustavsson, P. (2006) Exposure to particles and nitrogen dioxide among taxi, bus and lorry drivers. Int. Ar ch. Occup. Environ. Health 79: 220-226. 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.
Liao, D.; Heiss, G.; Chinchilli, V. M.; Duan, Y.; Folsom, A. R.; Lin, H. M.; Salomaa, V. (2005)Association of criteria pollutants with plasma hemostatic/inflammatory markers: a populationbased study. J. Exposure Anal. Environ. Epidemiol. 15: 319-328. Liard, R.; Zureik, M.; Le Moullec, Y.; Soussan, D.; Glorian, M.; Grimfeld, A.; Neukirch, F. (1999) Use of personal passive samplers for measurement of NO 2 , NO, and O 3 levels in panel studies. Environ. Res. 81: 339-348. Lin, C. A.; Martins, M. A.; Farhat, S. C. L.; Pope, C. A., III; Conceição, 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 São Pa ulo, 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 childre n: 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 hospita lization of children with low household income in Vancouver, British Columbia, Cana da. Am. J. Epidemiol. 159: 294-303. Lin, M.; Stieb, D. M.; Chen, Y. (2005) Coarse particulate matter and hospitalization for respiratory infections in children younger than 15 years in Toronto: a case-crossover analysis. Pediatrics 116: 235-240. Linaker, C. H.; Chauhan, A. J.; Inskip, H. M.; Ho lgate, S. T.; Coggon, D. (2000) Personal exposures of children to nitrogen dioxide relative to concentra tions in outdoor air. Occup. Environ. Med. 57: 472-476. Linaker, C. H.; Chauhan, A. J.; Inskip, H.; Frew, A. J.; Sillence, A.; Coggon, D.; Holgate, S. T. (1996) Distribution and determinants of personal exposure to nitrogen dioxi de in school children. Occup. Environ. Med. 53: 200-203. Linares, C.; Díaz, J.; Tobías, A.; Miguel, J. M. De.; Otero, A. (2006) Impact of urban air pollutants and noise levels over daily hospital admissions in childre n in Madrid: a time series analysis. Int. Arch. Occup. Environ. Health 79: 143-152. Linn, W. S.; Shamoo, D. A.; Anderson, K. R.; Peng, R.-C.; Avol, E. L.; Hackney, J. D.; Gong, H., Jr. (1996) Short-term air pollution exposures and r esponses in Los Angeles area schoolchildren. J. Exposure Anal. Environ. Epidemiol. 6: 449-472.26 Linn, W. S.; Shamoo, D. A.; Spier, C. E.; Valencia, L. M.; Anzar, U. T.; Venet, T. G.; Avol, E. L.; Hackney, J. D. (1985b) Controlled exposure of volunteers with chronic obstructive pulmonary disease to nitrogen dioxide. Arch. Environ. Health 40: 313-317. Linn, W. S.; Solomon, J. C.; Trim, S. C.; Spier, C. E.; Shamoo, D. A.; Venet, T. G.; Avol, E. L.; Hackney, J. D. (1985a) Effects of exposure to 4 ppm nitrogen dioxide in healthy and asthmatic volunteers. Arch. Environ. Health 40: 234-239. Linn, W. S.; Szlachcic, Y.; Gong, H., Jr.; Kinney, P. L.; Berhane, K. T. (2000) Air pollution and daily hospital admissions in metropolitan Los Angel es. Environ. Health Perspect. 108: 427-434. Lipfert, F. W.; Baty, J. D.; Miller, J. P.; Wyzga, R. E. (2006b) PM 2.5 constituents and related air quality variables as predictors of survival in a cohort of U.S. military veterans. Inhalation Toxicol. 18: 645-657. 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. Lipfert, F. W.; Perry, H. M., Jr.; Miller, J. P.; Baty, J. D.; Wyzga, R. E.; Carmody, S. E. (2003) Air pollution, blood pressure, and their long-term associa tions with mortality. Inhalation Toxicol. 15: 493-512. Lipfert, F. W.; Wyzga, R. E.; Baty, J. D.; Miller, J. P. (2006a) Traffic density as a surrogate measure of environmental exposures in studies of air pollution h ealth effects: long-term mortality in a cohort of US veterans. Atmos. Environ. 40: 154-169. Lipsett, M.; Hurley, S.; Ostro, B. (1997) Air pollution and emergency room visits for asthma in Santa Clara County, California. Environ. Health Perspect. 105: 216-222.
Liu, S.; Krewski, D.; Shi, Y.; Chen, Y.; Burnett, R. T. (2003) Association between gaseous ambient air pollutants and adverse pregnancy outcomes in Vanc ouver, Canada. Environ. Health Perspect. 111: 1773-1778.
Llorca, J.; Salas, A.; Prieto-Salceda, D.; Chin chon-Bengoechea, V.; Delgado-Rodríguez, M. (2005) Nitrogen dioxide increases cardiorespiratory admissions in Torrelavega (Spain). J. Environ. Health 68: 30-35. Loupa, G.; Charpantidou, E.; Kioutsioukis, I.; Rapsom anikis, S. (2006) Indoor microclimate, ozone and nitrogen oxides in two medieval churches in Cyprus. Atmos. Environ. 40: 7457-7466. Love, G. J.; Lan, S.-P.; Shy, C. M.; Riggan, W. B. (1982) Acute respiratory illness in families exposed to nitrogen dioxide ambient air pollution in Cha ttanooga, Tennessee. Arch. Environ. Health 37: 75- 80. Luginaah, I. N.; Fung, K. Y.; Gorey, K. M.; Webster, G.; Wills, C. (2005) Association of ambient air pollution with respiratory hospitalization in a gove rnment designated “area of concern”: the case of Windsor, Ontario. Environ. Health Perspect. 113: 290-296. Luttmann-Gibson, H.; Suh, H. H.; Coull, B. A.; Dockery, D. W.; Sarnet, S. E.; Schwartz, J.; Stone, P. H.; Gold, D. R. (2006) Short-term effects of air pollu tion on heart rate variability in senior adults in Steubenville, Ohio. J. Occup. Environ. Med. 48: 780-788. Magas, O. K.; Gunter, J. T.; Regens, J. L. (2007) Ambient air pollution and daily pediatric hospitalizations for asthma. Environ. Sci. Pollut. Res. 14: 19-23. Mage, D.; Wilson, W.; Hasselblad, V.; Grant, L. (1999) Assessment of human exposure to ambient particulate matter. J. Air Waste Manage. Assoc. 49: 1280-1291.27 Makri, A.; Stilianakis, N. I. (2008) Vulnerability to air pollution health effects. Int. J. Hyg. Environ. Health: in press. Mann, J. K.; Tager, I. B.; Lurmann, F.; Segal, M.; Quesenberry, C. P., Jr.; Lugg, M. M.; Shan, J.; Van den Eeden, S. K. (2002) Air pollution and hospital admissions for ischemic heart disease in persons with congestive heart failure or arrhythm ia. Environ. Health Perspect. 110: 1247-1252. Mannes, T.; Jalaludin, B.; Morgan, G.; Lincoln, D.; Sh eppeard, V.; Corbett, S. (2005) Impact of ambient air pollution on birth weight in Sydney, Au stralia. Occup. Environ. Med. 62: 524-530. Maroziene, L.; Grazuleviciene, R. (2002) Maternal exposure to low-level ai r pollution and pregnancy outcomes: a population-based study. Environ. Health: Global Access Sci. Source 1: 6. Available: http://www.ehjournal.net/content/1/1/6 [10 October, 2006].
Martin, R. V.; Jacob, D. J.; Chance, K. V.; Kurosu, T. P.; Palmer, P. I.; Evans, M. J. (2003) Global inventory of nitrogen oxide emissions cons trained by space-based observations of NO 2 columns. J. Geophys. Res. [Atmos.] 108(D17): 10.1029/2003JD003453. Martins, M. C. H.; Fatigati, F. L.; Vespoli, T. C.; Mar tins, L. C.; Martins, M. A.; Saldiva, P. H. N.; Braga, A. L. F. (2004) Influence of socioeconomic cond itions on air pollution effects in elderly people an analysis of six regions in São Paolo, Braz il. J. Epidemiol. Comm. Health 58: 41-46. Maruo, Y. Y.; Ogawa, S.; Ichino, T.; Murao, N.; Uchi yama, M. (2003) Measurement of local variations in atmospheric nitrogen dioxide leve ls in Sapporo, Japan, using a ne w method with high spatial and high temporal resolution. Atmos. Environ. 37: 1065-1074. McCaig, L. F.; Burt, C. W. (2005) National Hosp ital Ambulatory Medical Care Survey: 2003 Emergency Department Summary. Hyattsville, MD: National Ce nter for Health Statistics; DHHS publication no. (PHS) 2005-1250. (Advance data from vital a nd health statistics; no. 358). Available: http://www.cdc.gov/nchs/data/ad/ad358.pdf [3 August, 2005]. McClenny, W. A.; Williams, E. J.; Cohen, R. C.; Stutz, J. (2002) Preparing to measure the effects of the NO X SIP Call—methods for ambient air monitoring of NO, NO 2 , NO Y , and individual NO Z species. J. Air Waste Manage. Assoc. 52: 542-562.
McConnell, R.; Berhane, K.; Gilliland, F.; Molitor, J. ; Thomas, D.; Lurmann, F.; Avol, E.; Gauderman, W. J.; Peters, J. M. (2003) Prospective study of air pollution and bronchitic symptoms in children with asthma. Am. J. Respir. Crit. Care Med. 168: 790-797.
McConnell, R.; Berhane, K.; Yao, L.; Jerrett, M.; Lu rmann, F.; Gilliland, F.; Kunzli, N.; Gauderman, J.; Avol, E.; Thomas, D.; Peters, J. (2006) Traffic, susceptibility, and childhood asthma. Environ. Health Perspect. 114: 766-772. McCreanor, J.; Cullinan, P.; Nieuwenhuijsen, M. J. ; Stewart-Evans, J.; Malliarou, E.; Jarup, L.; Harrington, R.; Svartengren, M.; Han, I-K.; Ohman-Strickland, P.; Chung, K. F.; Zhang, J. (2007) Respiratory effects of exposure to diesel traffic in persons with asthma. N. Engl. J. Med. 357: 2348-2358. 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. Mensink, C.; Cosemans, G. (2008) From traffic flow simulations to pollutant concentrations in street canyons and backyards. Environmental Modelling & Software. 23: 288-295. Mercer, R. R.; Costa, D. L.; Crapo, J. D. (1995) Effects of prolonged exposure to low doses of nitric oxide or nitrogen dioxide on the alveolar septa of the adult rat lung. Lab. Invest. 73: 20-28.28 Mersch, J.; Dyce, B. J.; Haverback, B. J.; Sherwin, R. P. (1973) Diphosphoglycerate content of red blood cells: measurements in guinea pigs exposed to 0.4 ppm nitrogen dioxide. Arch. Environ. Health 27: 94-95. Metzger, K. B.; Klein, M.; Flanders, W. D.; Peel, J. L.; Mulholland, J. A.; Langberg, J. J.; Tolbert, P. E. (2007) Ambient air pollution and cardiac arrhythmias in patients with implantable defibrillators. Epidemiology 18: 585-592. 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. Migliaretti, G.; Cadum, E.; Migliore, E.; Cavallo, F. (2005) Traffic air pollution and hospital admission for asthma: a case-control approach in a Turin (Italy) population. Int. Arch. Occup. Environ. Health. 78: 164-169. Migliaretti, G.; Cavallo, F. (2004) Urban air polluti on and asthma in children. Pediatr. Pulmonol. 38: 198- 203. Miller, F. J.; Graham, J. A.; Raub, J. A.; Illing, J. W.; Ménache, M. G.; House, D. E.; Gardner, D. E. (1987) Evaluating the toxicity of urban patterns of oxidant gases. II. Effects in mice from chronic exposure to nitrogen dioxide. J. Toxi col. Environ. Health 21: 99-112. Miller, K. A.; Siscovick, D. S.; Sheppard, L.; Shepherd , K.; Sullivan J. H.; Anderson, G. L.; Kaufman, J. D. (2007) Long-term exposure to air pollution and in cidence of cardiovascular events in women. N. Engl. J. Med. 356: 447-458.
Millstein, J.; Gilliland, F.; Berhane, K.; Gauderman, W. J.; McConnell, R.; Avol, E.; Rappaport, E. B.; Peters, J. M. (2004) Effects of ambient air pollutants on asthma medication use and wheezing among fourth-grade school children from 12 Sout hern California communities enrolled in The Children’s Health Study. Arch. Environ. Health 59: 505-514. Mirvish, S. S.; Babcook, D. M.; Deshpande, A. D.; Na gel, D. L. (1986) Identification of cholesterol as a mouse skin lipid that reacts with nitrogen dioxide to yield a nitrosating agent, and of cholesteryl nitrite as the nitrosating agent produced in a ch emical system from cholesterol. Cancer Lett. (Shannon, Irel.) 31: 97-104. Mirvish, S. S.; Issenberg, P.; Sams, J. P. (1981) N -nitrosomorpholine synthesis in rodents exposed to nitrogen dioxide and morpholine. In: Scan lan, R. A.; Tannenbaum, S. R., eds. N -nitroso compounds: based on a symposium cosponsored by the Divisions of Agricultural and Food Chemistry and Pesticide Chemistry at the 181st meeting of the American Chemical Society; March-April; Atlanta, GA. Washington, DC: American Chemical Society; pp. 181-191. (ACS symposium series 174). Mirvish, S. S.; Ramm, M. D.; Sams, J. P.; Babcook, D. M. (1988) Nitrosamine formation from amines applied to the skin of mice after and before exposure to nitrogen dioxide. Cancer Res. 48: 1095- 1099. Mirvish, S. S.; Sams, J. P.; Issenberg, P. (1983) The nitrosating agent in mice exposed to nitrogen dioxide: improved extraction method and localiza tion in the skin. Cancer Res. 43: 2550-2554. Mochitate, K.; Miura, T. (1984) In vivo effect of n itrogen dioxide on the activities of glycolytic enzymes in red blood cells of rats. Toxicol. Lett. 22: 315-321. Modig, L.; Sunesson, A.-L.; Levin, J.-O.; Sundgren , M.; Hagenbjörk-Gustafsson, A.; Forsberg, B. (2004) Can NO 2 be used to indicate ambient and personal leve ls of benzene and 1,3-butadiene in air? J. Environ. Monit. 6: 957-962.29 Mohsenin, V. (1987a) Effect of vitamin C on NO 2 -induced airway hyperresponsiveness in normal subjects: a randomized double-blind experiment. Am. Rev. Respir. Dis. 136: 1408-1411. Mohsenin, V. (1987b) Airway responses to nitrogen dioxi de in asthmatic subjects. J. Toxicol. Environ. Health 22: 371-380. Mohsenin, V. (1988) Airway responses to 2.0 ppm nitrogen dioxide in normal subjects. Arch. Environ. Health 43: 242-246. Molitor, J.; Jerrett, M.; Chang, C.-C.; Molitor, N. -T.; Gauderman, J.; Berhane, K.; McConnell, R.; Lurmann, F.; Wu, J.; Winer, A.; Thomas, D. (2007) Assessing uncertainty in spatial exposure models for air pollution health effects assessment. Environ. Health Perspect. 115: 1147-1153. Monn, C. (2001) Exposure assessment of air polluta nts: a review on spatial heterogeneity and indoor/outdoor/personal exposure to suspended particulate matter, nitrogen dioxide and ozone. Atmos. Environ. 35: 1-32.
Monn, C.; Brändli, O.; Schindler, C.; Ackermann- Liebrich, U.; Leuenberger, P.; SAPALDIA team. (1998) Personal exposure to nitr ogen dioxide in Switzerland. Sc i. Total Environ. 215: 243-251. Monn, C.; Fuchs, A.; Högger, D.; Junker, M.; K ogelschatz, D.; Roth, N.; Wanner, H.-U. (1997) Particulate matter less than 10 μm (PM 10 ) and fine particles less than 2.5 μm (PM 2.5 ): relationships between indoor, outdoor and personal concentr ations. Sci. Total Environ. 208: 15-21. Moolgavkar, S. H. (2000) Air pollution and hospital admissions for diseases of the circulatory system in three U.S. metropolitan areas. J. Air Waste Manage Assoc. 50: 1199-1206. Moolgavkar, S. H. (2003) Air pollution and daily d eaths and hospital admissions in Los Angeles and Cook counties. In: Revised analyses of time-seri es studies of air pollution and health. Special report. Boston, MA: Health Effects Institute; pp. 183-198. Available: http://www.healtheffects.org/news.htm [16 May, 2003]. Morello-Frosch, R.; Shenassa, E. D. (2006) The e nvironmental “riskscape” and social inequality: implications for explaining maternal and child h ealth disparities. Environ. Health Perspect. 114: 1150-1153. Morgan, G.; Corbett, S.; Wlodarczyk, J. (1998a) Air pollution and hospital admissions in Sydney, Australia, 1990 to 1994. Am. J. Public Health 88: 1761-1766. Morgan, G.; Corbett, S.; Wlodarczyk, J.; Lewis, P. (1998b) Air pollution and daily mortality in Sydney, Australia, 1989 through 1993. Am. J. Public Health 88: 759-764. Morris, R. D.; Naumova, E. N.; Munasinghe, R. L. (1995) Ambient air pollution and hospitalization for congestive heart failure among elderly people in seven large US cities. Am. J. Public Health 85: 1361-1365. Morrow, P. E.; Utell, M. J.; Bauer, M. A.; Smeglin, A. M.; Frampton, M. W.; Cox, C.; Speers, D. M.; Gibb, F. R. (1992) Pulmonary performance of elderly normal subjects and subjects with chronic obstructive pulmonary disease exposed to 0.3 ppm nitrogen dioxide. Am. Rev. Respir. Dis. 145: 291-300. Mortimer, K. M.; Neas, L. M.; Dockery, D. W.; Redline, S.; Tager, I. B. (2002) The effect of air pollution on inner-city children with asthma. Eur. Respir. J. 19: 699-705. 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 subgroups. Am. J. Respir. Crit. Care Med. 162: 1838-45.30 Moseler, M.; Hendel-Kramer, A.; Karmaus, W.; Forster, J.; Weiss, K.; Urbanek, R.; Kuehr, J. (1994) Effect of moderate NO 2 air pollution on the lung function of children with asthmatic symptoms. Environ. Res. 67: 109-124. Moshammer, H.; Hutter, H.-P.; Hauck, H.; Neuberg er, M. (2006) Low levels of air pollution induce changes of lung function in a panel of sc hoolchildren. Eur. Respir. J. 27: 1138-1143. Mosqueron, L.; Momas, I.; Le Moullec, Y. (2002) Personal exposure of Paris office workers to nitrogen dioxide and fine particles. O ccup. Environ. Med. 59: 550-555.
Mukala, K.; Alm, S.; Tiittanen, P.; Salonen, R. O. ; Jantunen, M.; Pekkanen, J. (2000) Nitrogen dioxide exposure assessment and cough among preschool childre n. Arch. Environ. Health. 55: 431-438.
Mukala, K.; Pekkanen, J.; Tiittanen, P.; Alm, S.; Sal onen, R. O.; Tuomisto, J. (1999) Personally measured weekly exposure to NO 2 and respiratory health among preschool children. Eur. Respir. J. 13: 1411- 1417. Mukerjee, S.; Smith, L. A.; Norris, G. A.; Morandi, M. T.; Gonzales, M.; Noble, C. A.; Neas, L. M.; Özkaynak, A. H. (2004) Field method comparis on between passive air sampling and continuous monitors for VOCs and NO 2 in El Paso, Texas. J. Air Waste Manage. Assoc. 54: 307-319. Müller, B.; Schafer, H.; Barth, P.; Von Wichert, P. (1994) Lung surfactant components in bronchoalveolar lavage after inhalation of NO 2 as markers of altered surfactant metabolism. Lung 172: 61-72.
Næss, Ø.; Nafstad, P.; Aamodt, G.; Claussen, B.; Rosl and, P. (2007) Relation between concentration of air pollution and cause-specific mortality: four-year exposures to nitrogen dioxide and particulate matter pollutants in 470 neighborhoods in Oslo, Norway. Am. J. Epidemiol. 165: 435-443.
Nafstad, P.; Håheim, L. L.; Oftedal, B.; Gram, F.; Holme, I.; Hjermann, I.; Leren, P. (2003) Lung cancer and air pollution: a 27 year follow up of 16,209 Norwegian men. Thorax 58: 1071-1076.
Nafstad, P.; Håheim, L. L.; Wisloff, T.; Gram, F.; Of tedal, B.; Holme, I.; Hjermann, I.; Leren, P. (2004) Urban air pollution and mortality in a cohort of Norwegian men. Environ. Health Perspect. 112: 610-605. Nakai, S.; Nitta, H.; Maeda, K. (1995) Respiratory h ealth associated with exposure to automobile exhaust II. Personal NO 2 exposure levels according to distance from the roadside. J. Exposure Anal. Environ. Epidemiol. 5: 125-136. Nakajima, T.; Kusumoto, S. (1968) [Effect of nitr ogen dioxide exposure on the contents of reduced glutathione in mouse lung]. Osaka-Furitsu Koshu Eisei Kenkyusho Kenkyu Hokoku Rodo Eisei Hen 6: 17-21. National Acid Precipitation Program (NAPAP). (1991) The experience and legacy of NAPAP. Report of the Oversight Review Board. Washington, DC: National Acid Precipitation Program. National Center for Health Statistics (NCHS). (2006a) Summary health statistics for U.S. adults: National Health Interview Survey, 2004. Hyattsville, MD: U. S. Department of Health & Human Services, Centers for Disease Control and Prevention. (Vita l and Health Statistics, Series 10, no. 228). Available: http://www.cdc.gov/nchs/data/series/sr_10/sr10_228.pdf (14 September, 2007). National Center for Health Statistics (NCHS). (2006b) Summary health statistics for U.S. children: National Health Interview Survey, 2005. Hyattsv ille, MD: U.S. Department of Health & Human Services, Centers for Disease Control and Prevention. (Vital and Health Statistics, Series 10, no. 231). Available: http://www.cdc.gov/nchs/data/ series/sr_10/sr10_231.pdf (14 September, 2007).31 National Center for Health Statistics (NCHS). (2006c) Asthma prevalence, health care use and mortality: United States, 2003-05. Hyattsville, MD: U.S. Depa rtment of Health & Human Services, Centers for Disease Control and Prevention. Availabl e: http://www.cdc.gov/nchs/products/pubs/pubd/ hestats/ashtma03-05/ asthma03-05.htm (26 February, 2008). National Heart, Lung, and Blood Institute (NHLBI). (2007) Expert panel report 3: guidelines for the diagnosis and management of asthma. Bethesda, MD: U.S. Department of Health and Human Services, National Institutes of Health, Nationa l Asthma Education and Prevention Program; NIH Publication No. 07-4051. National Research Council. (2001) Research priorities for airborne particulate matter. III. Early research progress. Washington, DC: National Academy Press. Available: http://www.nap.edu/books/ 0309073375/html/ (4 June 2003). National Research Council. (2004) Research priorities for airborne particulate matter. IV. Continuing research progress. Washington, DC: National Academies Press. Available: http://www.nap.edu/ catalog.php?record_id=10957 [1 August, 2007]. National Toxicology Program. (2005) Report on carcinogens. 11th ed. Washington, DC: National Toxicology Program. Nazaroff, W. W.; Cass, G. R. (1986) Mathematical modeling of chemically reactive pollutants in indoor air. Environ. Sci. Technol. 20: 924-934. Nazaroff, W. W.; Weschler, C. J. (2004) Cleaning pr oducts and air fresheners: exposure to primary and secondary air pollutants. Atmos. Environ. 38: 2841-2865. Neidell, M. J. (2004) Air pollution, health, and soci o-economic status: the effect of outdoor air quality on childhood asthma. J. Health Econ. 23: 1209-1236.
Nerriere, E.; Zmirou-Navier, D.; Blanchard, O.; Momas, I.; Ladner, J.; Le Moullec, Y.; Personnaz, M.-B.; Lameloise, P.; Delmas, V.; Target, A.; Desqueyroux, H. (2005) Can we use fixed ambient air monitors to estimate population long-term exposure to air pollutants? The case of spatial variability in the Genotox ER study. Environ. Res. 97: 32-42. New York State Department of Health. (2006) A study of ambient air contaminants and asthma in New York City. Final Report, Part B: Air contaminants and emergency department visits for asthma in the Bronx and Manhattan. Prepared for The U.S. Department of Health and Human Services, Agency for Toxic Substance and Disease Regi stry. Available: www.atsdr.cdc.gov/document/ ASTHMA_BRONX_FINAL_REPORT.pdf. Ng, T. P.; Seet, C. S. R.; Tan, W. C.; Foo, S. C. (2001) Nitrogen dioxide exposure from domestic gas cooking and airway response in asthmatic women. Thorax 56: 596-601.
Nicolai, T.; Carr, D.; Weiland, S. K.; Duhme, H.; V on Ehrenstein, O.; Wagner, C.; Von Mutius, E. (2003) Urban traffic and pollutant exposur e related to respiratory outcomes and atopy in a large sample of children. Eur. Respir. J. 21: 956-963. Nieding, G. von; Wagner, H. M. (1977) Experimental studies on the short-term effect of air pollutants on pulmonary function in man: two-hour exposure to NO 2 , O 3 and SO 2 alone and in combination. In: Kasuga, S.; Suzuki, N.; Yamada, T.; Kimura, G.; In agaki, K.; Onoe, K., eds. Proceedings of the fourth international clean air congress; May; T okyo, Japan. Tokyo, Japan: Japanese Union of Air Pollution Prevention Associations; pp. 5-8. Nieding, G. von; Wagner, H. M.; Casper, H.; Beuthan, A.; Smidt, U. (1980) Effect of experimental and occupational exposure to NO 2 in sensitive and normal subjects. In: Lee, S. D., ed. Nitrogen oxides and their effects on health. Ann Arbor, MI: A nn Arbor Science Publishers, Inc.; pp. 315-331.32 Nieding, G. von; Wagner, H. M.; Krekeler, H.; Loellgen, H.; Fries, W.; Beuthan, A. (1979) Controlled studies of human exposure to single and combined action of NO 2 , O 3 , and SO 2 . Int. Arch. Occup. Environ. Health 43: 195-210.
Nitschke, M.; Pilotto, L. S.; Attewell, R. G.; Smith, B. J.; Pisaniello, D.; Martin, J.; Ruffin, R. E.; Hiller, J. E. (2006) A cohort study of indoor nitrogen di oxide and house dust mite exposure in asthmatic children. J. Occup. Environ. Med. 48: 462-469. Norris, G.; Young-Pong, S. N.; Koenig, J. Q.; Larson, T. V.; Sheppard, L.; Stout, J. W. (1999) An association between fine particles and asthma emerge ncy department visits for children in Seattle. Environ. Health Perspect. 107: 489-493. Nunnermacker, L. J.; Imre, D.; Daum, P. H.; Kleinman, L.; Lee, Y.-N.; Lee, J. H.; Springston, S. R.; Newman, L.; Weinstein-Lloyd, J.; Luke, W. T.; Banta, R.; Alvarez, R.; Senff, C.; Sillman, S.; Holdren, M.; Keigley, G. W.; Zhou, X. (1998) Characterization of the Nashville urban plume on July 3 and July 18, 1995. J. Geophys. Res. [Atmos.] 103: 28,129-28,148. Nyberg, F.; Gustavsson, P.; Järup, L.; Bellander, T.; Berglind, N.; Jakobsson, R.; Pershagen, G. (2000) Urban air pollution and lung cancer in Stockholm. Epidemiology 11: 487-495. Oftedal, B.; Brunekreef, B.; Nystad, W.; Madsen, C. ; Walker, S.-E.; Nafstad, P. (2008) Residential outdoor air pollution and lung function in schoolchildren. Epidemiology 19: 129-137. Oftedal, B.; Nafstad, P.; Magnus, P.; Bjørkly, S.; Skrondal, A. (2003) Traffic related air pollution and acute hospital admission for respiratory diseases in Drammen, Norway 1995-2000. Eur. J. Epidemiol. 18: 671-675. Ogawa & Company. (2007) Ambient air passive sampler for NO-NO 2 , NO X , SO 2 , O 3 , NH 3 . Pompano Beach, FL. Available: http://www.ogawausa.com/passive.html [18 July, 2007]. Ohashi, Y.; Nakai, Y.; Sugiura, Y.; Ohno, Y.; Okamoto, H.; Tanaka, A.; Kakinoki, Y.; Hayashi, M. (1994) Nitrogen dioxide-induced eosinophilia and mucosal injury in the nose of the guinea pig. Acta Oto Laryngol. 114: 547-551. Ohyama, K.; Ito, T.; Kanisawa, M. (1999) The roles of diesel exhaust particle extracts and the promotive effects of NO 2 and/or SO 2 exposure on rat lung tumorigenesis. Cancer Lett. 139: 189-197. O’Neill, M. S.; Jerrett, M.; Kawachi, I.; Levy, J. I.; C ohen, A. J.; Gouveia, N.; Wilkinson, P.; Fletcher, T.; Cifuentes, L.; Schwartz, J.; with input from pa rticipants of the Workshop on Air Pollution and Socioeconomic Conditions. (2003) Health, wealth , and air pollution: advancing theory and methods. Environ. Health Perspect. 111: 1861-1870. 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. Ott, W.; Wallace, L.; Mage, D. (2000) Predicting particulate (PM 10 ) personal exposure distributions using a random component superposition statistical mode l. J. Air Waste Manage. Assoc. 50: 1390-1406. Pagani, P.; Romano, M.; Erroi, A.; Ferro, M.; Salm ona, M. (1994) Biochemical effects of acute and subacute nitrogen dioxide exposure in rat lung a nd bronchoalveolar lavage fluid. Arch. Environ. Contam. Toxicol. 27: 426-430. Palmes, E. D.; Gunnison, A. F.; DiMattio, J.; Tomczy k, C. (1976) Personal sampler for nitrogen dioxide. Am. Ind. Hyg. Assoc. J. 37: 570-577. Pantazopoulou, A.; Katsouyanni, K.; Kourea-Kremastinou, J.; Trichopoulos, D. (1995) Short-term effects of air pollution on hospital emergency outpatient visits and admissions in the greater Athens, Greece area. Environ. Res. 69: 31-36.33 Park, J. W.; Lim, Y. H.; Kyung, S. Y.; An, C. H.; Lee, S. P.; Jeong, S. H.; Ju, S.-Y. (2005a) Effects of ambient particulate matter on peak expiratory flow rates and respiratory symptoms of asthmatics during Asian dust periods in Korea. Respirology 10: 470-476. Park, J.-H.; Spengler, J. D.; Yoon, D.-W.; Dumyahn, T.; Lee, K.; Özkaynak, H. (1998) Measurement of air exchange rate of stationary vehicles and estim ation of in-vehicle exposure. J. Exposure Anal. Environ. Epidemiol. 8: 65-78. Park, S. K.; O’Neill, M. S.; Vokonas, P. S.; Sparrow, D.; Schwartz, J. (2005b) Effects of air pollution on heart rate variability: the VA normative aging study. Environ. Health Perspect. 113: 304-309. Parrish, D. D.; Fehsenfeld, F. C. (2000) Methods for gas-phase measurements of ozone, ozone precursors and aerosol precursors. Atmos. Environ. 34: 1921-1957. Pathmanathan, S.; Krishna, M. T.; Blomberg, A.; Helleda y, R.; Kelly, F. J.; Sandström, T.; Holgate, S. T.; Wilson, S. J.; Frew, A. J. (2003) Repeated da ily exposure to 2 ppm nitrogen dioxide upregulates the expression of IL-5, IL-10, IL-13, and ICAM-1 in the bronchial epithelium of healthy human airways. Occup. Environ. Med. 60: 892-896.
Pattemore, P. K.; Asher, M. I.; Harrison, A. C.; Mitc hell, E. A.; Rea, H. H.; Stewart, A. W. (1990) The interrelationship among bronchial hyperresponsiveness, the diagnosis of asthma, and asthma symptoms. Am. Rev. Respir. Dis. 142: 549-554.Payne-Sturges, D.; Gee, G. C. (2006) National environmental health measures for minority and lowincome populations: Tracking social disparities in environmental health. Environmental research. 102: 154-171. Peacock, J. L.; Symonds, P.; Jackson, P.; Bremner, S. A.; Scarlett, J. F.; Strachan, D. P.; Anderson, H. R. (2003) Acute effects of winter air pollution on r espiratory function in schoolchildren in southern England. Occup. Environ. Med. 60: 82-89. Peel, J. L.; Metzger, K. B.; Klein, M.; Flanders, W. D.; Mulholland, J. A.; Tolbert, P. E. (2007) Ambient air pollution and cardiovascular emergency department visits in potentially sensitive groups. Am. J. Epidemiol. 165: 625-633. 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.
Pekkanen, J.; Brunner, E. J.; Anderson, H. R.; Tiittane n, P.; Atkinson, R. W. (2000) Daily concentrations of air pollution and plasma fibrinogen in London. Occup. Environ. Med. 57: 818-822. Pérez-Padilla, R.; Regalado, J.; Rojas, M.; Catalán, M. ; Mendoza, L.; Rojas, R.; Chapela, R.; Villalba, J.; Torres, V.; Borja, V.; et al. (2003a) Spirometric function in children of Mexico City compared to Mexican-American children. Pediatr. Pulmonol. 35: 177-183. Pérez-Padilla, R.; Regalado-Pineda, J.; Mendoza, L.; Ro jas, R.; Torres, V.; Borja-Aburto, V.; Olaiz, G.; EMPECE Study Group. (2003b) Spirometric variab ility in a longitudinal study of school-age children. Chest 123: 1090-1095.
Perrini, G.; Tomasello, M.; Librando, V.; Minniti, Z. (2005) Nitrated polycyclic aromatic hydrocarbons in the environment: formation, occurrences and analysis. Ann. Chim. 95: 567-577.
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. (2000) Air pollution and incidence of cardiac arrhythmia. Epidemiology 11: 11-17.34 Peters, J. M.; Avol, E.; Navidi, W.; London, S. J.; Ga uderman, W. J.; Lurmann, F.; Linn, W. S.; Margolis, H.; Rappaport, E.; Gong, H., Jr.; Thomas, D. C. (1999) 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. Petroschevsky, A.; Simpson, R. W.; Thalib, L.; Ru therford, S. (2001) Associations between outdoor air pollution and hospital admissions in Brisbane, Australia. Arch. Environ. Health 56: 37-52. Piechocki-Minguy, A.; Plaisance, H.; Schadkowski, C.; Sagnier, I.; Saison, J. Y.; Galloo, J. C.; Guillermo, R. (2006) A case study of personal e xposure to nitrogen dioxide using a new high sensitive diffusive sampler. Sci. Total Environ. 366: 55-64. Pilotto, L. S.; Douglas, R. M.; Attewell, R. G.; Wils on, S. R. (1997a) Respiratory effects associated with indoor nitrogen dioxide exposure in children. Int. J. Epidemiol. 26: 788-796. Pilotto, L. S.; Douglas, R. M.; Samet, J. M. (1997b) Nitrogen dioxide, gas heating and respiratory illness. Med. J. Aust. 167: 295-296.
Pilotto, L. S.; Nitschke, M.; Smith, B. J.; Pisaniello, D.; Ruffin, R. E.; McElroy, H. J.; Martin, J.; Hiller, J. E. (2004) Randomized controlled trial of unflued gas heater replacement on respiratory health of asthmatic schoolchildren. Int. J. Epidemiol. 33: 208-214. Pino, P.; Walter, T.; Oyarzun, M.; Villegas, R.; Ro mieu, I. (2004) Fine particulate matter and wheezing illnesses in the first year of life. Epidemiology 15: 702-708. Pinto, J. P.; Lefohn, A. S.; Shadwick, D. S. (2004) Spatial variability of PM 2.5 in urban areas in the United States. J. Air Waste Manage. Assoc. 54: 440-449. Pitts, J. N., Jr. (1987) Nitration of gaseous polycyc lic aromatic hydrocarbons in simulated and ambient urban atmospheres: a source of mutagenic nitroarenes. Atmos. Environ. 21: 2531-2547. Plaisance, H.; Piechocki-Minguy, A.; Garcia-Fouque, S.; Galloo, J. C. (2004) Influences of meteorological factors on the NO 2 measurements by passive diffusion tube. Atmos. Environ. 38: 573-580. Pleijel, H.; Karlsson, G. P.; Gerdin, E. B. (2004) On the logarithmic relationship between NO 2 concentration and the distance from a highroad. Sci. Total Environ. 332: 261-264. Poloniecki, J. D.; Atkinson, R. W.; Ponce de Leon, A.; Anderson, H. R. (1997) Daily time series for cardiovascular hospital admissions and previous day’s air pollution in London, UK. Occup. Environ. Med. 54: 535-540. 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 r espiratory 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 ser ies data. J. Epidemiol. Community Health 50 (suppl. 1): S63-S70. Ponce, N. A.; Hoggatt, K. J.; Wilhelm, M.; Ritz, B. ( 2005) Preterm birth: the interaction of traffic-related air pollution with economic hardship in Los Angeles neighborhoods. Am. J. Epidemiol. 162: 140- 148. Pönkä, A. (1991) Asthma and low level air pollution in Helsinki. Arch. Environ. Health 46: 262-270. Pönkä, A.; Virtanen, M. (1994) Chronic bronchitis, em physema, and low-level air pollution in Helsinki, 1987-1989. Environ. Res. 65: 207-217.35 Pönkä, A.; Virtanen, M. (1996) Asthma and ambient air pollution in Helsinki. 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. Community Health 50 (suppl. 1): S59-S62. Ponsonby, A.-L.; Glasgow, N.; Gatenby, P.; Mullins, R.; McDonald, T.; Hurwitz, M.; Pradith, B.; Attewell, R. (2001) The relationship between lo w level nitrogen dioxide exposure and child lung function after cold air challenge . Clin. Exp. Allergy 31: 1205-1212. 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. 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.
Posin, C.; Clark, K.; Jones, M. P.; Patterson, J. V.; Buckley, R. D.; Hackney, J. D. (1978) Nitrogen dioxide inhalation and human blood biochemistry. Arch. Environ. Health 33: 318-324. Postlethwait, E. M.; Bidani, A. (1990) Reactive uptake governs the pulmonary air space removal of inhaled nitrogen dioxide. J. Appl. Physiol. 68: 594-603. Postlethwait, E. M.; Bidani, A. (1994) Mechanisms of pulmonary NO 2 absorption. Toxicology 89: 217- 237. Postlethwait, E. M.; Langford, S. D.; Bidani, A. (1991) Transfer of NO 2 through pulmonary epithelial lining fluid. Toxicol. Appl. Pharmacol. 109: 464-471. Postlethwait, E. M.; Langford, S. D.; Jacobson, L. M.; Bidani, A. (1995) NO 2 reactive absorption substrates in rat pulmonary surface lining fluids. Free Radical Biol. Med. 19: 553-563. Prescott, G. J.; Cohen, G. R.; Elton, R. A.; Fowkes, F. G. R.; Agius, R. M. (1998) Urban air pollution and cardiopulmonary ill health: a 14.5 year time series study. Occup. Environ. Med. 55: 697-704.
Proust, B.; Lacroix, G.; Robidel, F.; Marliere, M.; L ecomte, A.; Vargaftig, B. B. (2002) Interference of a short-term exposure to nitrogen di oxide with allergic airways res ponses to allergenic challenges in BALB/c mice. Mediators Inflammation 11: 251-260. Raaschou-Nielsen, O.; Skov, H.; Lohse, C.; Thomsen, B. L.; Olsen, J. H. (1997) Front-door concentrations and personal expos ures of Danish children to nitrogen dioxide. Environ. Health Perspect. 105: 964-970. Ramsay, T. O.; Burnett, R. T.; Krewski, D. (2003) The effect of concurvity in generalized additive models linking mortality to ambient particulate matter. Epidemiology 14: 18-23. Ranzi, A.; Gambini, M.; Spattini, A.; Galassi, C.; Sesti, D.; Bedeschi, M.; Messori, A.; Baroni, A.; Cavagni, G.; Lauriola, P. (2004) Air pollution and resp iratory status in asthmatic children: hints for a locally based preventive strategy. AIRE study. Eur. J. Epidemiol. 19: 567-576. Rasmussen, T. R.; Kjærgaard, S. K.; Tarp, U.; Pedersen, O. F. (1992) Delayed effects of NO 2 exposure on alveolar permeability and glutathione peroxidase in healthy humans. Am. Rev. Respir. Dis. 146: 654-659. Raw, G. J.; Coward, S. K. D.; Brown, V. M.; Crump, D. R. (2004) Exposure to air pollutants in English homes. J. Exposure Anal. Environ. Epidemiol. 14(suppl. 1): S85-S94.36 Rehn, T.; Svartengren, M.; Philipson, K.; Camner, P. (1982) Mukociliaer transport i lunga och naesa samt luftvaegsmotstand efter exponering foer kvaevedi oxid [Mucociliary transport in the lung and nose after exposure to nitrogen dioxide]. Vallingby, Sw eden: Swedish State Power Board; project KHM technical report no. 40. Reisen, F.; Arey, J. (2005) Atmospheric reactions influence seasonal PAH and nitro-PAH concentrations in the Los Angeles basin. Environ. Sci. Technol. 39: 64-73. Restrepo, C.; Zimmerman, R.; Thurston, G.; Clemente, J.; Gorczynski, J.; Zhong, M.; Blaustein, M.; Chen, L. C. (2004) A comparison of ground-level ai r quality data with New York State Department of Environmental Conservation monitoring stati ons data in South Bronx, New York. Atmos. Environ. 38: 5295-5304. Rich, D. Q.; Kim, M. H.; Turner, J. R.; Mittleman, M. A.; Schwartz, J.; Catalano, P. J.; Dockery, D. W. (2006a) Association of ventricular arrhythmias de tected by implantable cardioverter defibrillator and ambient air pollutants in the St Louis, Missouri metropolitan area. Occup. Environ. Med. 63: 591-596. Rich, D. Q.; Mittleman, M. A.; Link, M. S.; Schwartz , J.; Luttmann-Gibson, H.; Catalano, P. J.; Speizer, F. E.; Gold, D. R.; Dockery, D. W. (2006b) Increased risk of paroxysmal atrial fibrillation episodes associated with acute increases in ambient air po llution. Environ. Health Perspect. 114: 120-123. 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 shor t-term ambient air pollution concentrations and ventricular arrhythmias. Am. J. Epidemiol. 161: 1123-1132. Richters, A.; Damji, K. S. (1990) The relationship between inhalation of nitrogen dioxide, the immune system, and progression of a spontaneously occurring lymphoma in AKR mice. J. Environ. Pathol. Toxicol. Oncol. 10: 225-230. Richters, A.; Kuraitis, K. (1981) Inhalation of NO 2 and blood borne cancer cell spread to the lungs. Arch. Environ. Health 36: 36-39. Richters, A.; Kuraitis, K. (1983) Air pollutants and th e facilitation of cancer metastasis. Environ. Health Perspect. 52: 165-168. Richters, A.; Richters, V. (1983) A new relationshi p between air pollutant inhalation and cancer. Arch. Environ. Health 38: 69-75. Richters, A.; Richters, V.; Alley, W. P. (1985) The mortality rate from lung metastases in animals inhaling nitrogen dioxide (NO 2 ). J. Surg. Oncol. 28: 63-66. Riediker, M.; Williams, R.; Devlin, R.; Griggs, T.; Br omberg, P. (2003) Exposure to particulate matter, volatile organic compounds, and other air pollutants in side patrol cars. Environ. Sci. Technol. 37: 2084-2093. Ristovski, Z. D.; Tass, I.; Morawska, L.; Saxby, W. (2000) Investigation into the emission of fine particles, formaldehyde, oxides of nitrogen a nd carbon monoxide from natural gas heaters. J. Aerosol. Sci. 31(suppl. 1): S490-S491. Ritz, B.; Yu, F.; Chapa, G.; Fruin, S. (2000) Effect of air pollution on preterm birth among children born in Southern California between 1989 and 1993. Epidemiology 11: 502-511. Robinson, J. R. (1989) On uncertainty in the computation of global emissions for biomass burning. Clim. Change 14: 243-262.37 Robison, T. W.; Murphy, J. K.; Beyer, L. L.; Richters, A.; Forman, H. J. (1993) Depression of stimulated arachidonate metabolism and supe roxide production in rat alveolar macrophages following in vivo exposure to 0.5 ppm NO 2 . J. Toxicol. Environ. Health 38: 273-292. Rodgers, M. O.; Davis, D. D. (1989) A UV-photo fragmentation/laser-induced fluorescence sensor for the atmospheric detection of HONO. Environ. Sci. Technol. 23: 1106-1112. Rodriguez, C.; Tonkin, R.; Heyworth, J.; Kusel, M.; De Klerk, N.; Sly, P. D.; Franklin, P.; Runnion, T.; Blockley, A.; Landau, L.; Hinwood, A. L. (2007) The relationship between outdoor air quality and respiratory symptoms in young children. Int J Environ Health Res. 17: 351-60. Roemer, W.; Clench-Aas, J.; Englert, N.; Hoek, G.; Katsouyanni, K.; Pekkanen, J.; Brunekreef, B. (1999) Inhomogeneity in response to air pollution in Europ ean children (PEACE project). Occup. Environ. Med. 56: 86-92.
Roemer, W.; Hoek, G.; Brunekreef, B.; Haluszka, J.; Ka landidi, A.; Pekkanen, J. (1998) Daily variations in air pollution and respiratory health in a multicen tre study: the PEACE project. Eur. Respir. J. 12: 1354-1361. Roger, L. J.; Horstman, D. H.; McDonnell, W.; Kehrl, H.; Ives, P. J.; Seal, E.; Chapman, R.; Massaro, E. (1990) Pulmonary function, airway responsiveness, and respiratory symptoms in asthmatics following exercise in NO 2 . Toxicol. Ind. Health 6: 155-171. Rogge, W. F.; Hildemann, L. M.; Mazurek, M. A.; Cass, G. R.; Simoneit, B. R. T. (1993) Sources of fine organic aerosol. 5. Natural gas home applia nces. Environ. Sci. Technol. 27: 2736-2744. Rojas-Bracho, L.; Suh, H. H.; Oyola, P.; Koutrakis, P. (2002) Measurements of children’s exposures to particles and nitrogen dioxide in Santiago, Chile. Sci. Total Environ. 287: 249-264. Rojas-Martinez, R.; Perez-Padilla, R.; Olaiz-Ferna ndez, G.; Mendoza-Alvarado, L.; Moreno-Macias, H.; Fortoul, T.; McDonnell, W.; Loomis, D.; Romieu, I. (2007a) Lung function growth in children with long-term exposure to air pollutants in Mexico C ity. Am. J. Respir. Crit. Care Med. 176: 377-384. Rojas-Martinez, R.; Perez-Padilla, R.; Olaiz-Ferna ndez, G.; Mendoza-Alvarado, L.; Moreno-Macias, H.; Fortoul, T.; McDonnell, W.; Loomis, D.; Romieu , I. (2007b) Lung function growth in children with long-term exposure to air pollutants in Me xico City. Online data supplement. Available: http://ajrccm.atsjournals.org/cgi/dat a/176/4/377/DC1/1 [3 October, 2007]. Rombout, P. J. A.; Dormans, J. A. M. A.; Marra, M.; Van Esch, G. J. (1986) Influence of exposure regimen on nitrogen dioxide-induced morphological ch anges in the rat lung. Environ. Res. 41: 466- 480. Romieu, I.; Ramírez-Aguilar, M.; Moreno-Macias, H.; Barraza-Villarreal, A.; Miller, P.; HernándezCadena, L.; Carbajal-Arroyo, L. A.; Hernandez-Avila , M. (2004) Infant mortality and air pollution: modifying effect by social class. J. Occup. Environ. Med. 46: 1210-1216. Romieu, I.; Ramírez-Aguilar, M.; Sienra-Monge, J. J.; Moreno-Macías, H.; Del Rio-Navarro, B. E.; David, G.; Marzec, J.; Hernández-Avila, M.; London, S. (2006) GSTM1 and GSTP1 and respiratory health in asthmatic children e xposed to ozone. Eur. Respir. J. 28: 953-959. Roorda-Knape, M. C.; Janssen, N. A. H.; De Hartog, J. J.; Van Vliet, P. H. N.; Harssema, H.; Brunekreef, B. (1998) Air pollution from traffic in city districts near major motorways. Atmos. Environ. 32: 1921-1930. Roorda-Knape, M. C.; Janssen, N. A.; De Hartog, J.; Van Vliet, P. H.; Harssema, H.; Brunekreef, B. (1999) Traffic related air pollution in city distri cts near motorways. Sci. Total Environ. 235: 339- 341.38 Rossi, O. V. J.; Kinnula, V. L.; Tienari, J.; Huhti, E. (1993) Association of severe asthma attacks with weather, pollen, and air pollutants. Thorax 48: 244-248.Rothman, K. J.; Greenland, S., eds. (1998) Modern epidemiology. 2nd ed. Philadelphia, PA: LippincottRaven Publishers. Rotko, T.; Kousa, A.; Alm, S.; Jantunen, M. (2001) Exposures to nitrogen dioxide in EXPOLIS -Helsinki: microenvironment, behavioral and sociodemogr aphic factors. J. Exposure Anal. Environ. Epidemiol. 11: 216-223. Roy-Burman, P.; Pattengale, P. K.; Sherwin, R. P. (1982) Effect of low levels of nitrogen dioxide inhalation on endogenous retrovi rus gene expression. Exp. Mol. Pathol. 36: 144-155.
Rubenchik, B. L.; Glavin, A. A.; Galenko, P. M.; Kilk ichko, A. A.; Olenick, I. O.; Artemov, K. V. (1995) Gaseous nitrogen dioxide increases the endogenous synthesis of carcinogenic N

-nitrosodimethylamine in animals. J. Environ. Pathol. Toxicol. Oncol. 14: 111-115. Rubenstein, I.; Bigby, B. G.; Reiss, T. F.; Boushey, H. A., Jr. (1990) Short-term exposure to 0.3 ppm nitrogen dioxide does not potentiate airway responsiv eness to sulfur dioxide in asthmatic subjects. Am. Rev. Respir. Dis. 141: 381-385. Rubenstein, I.; Reiss, T. F.; Bigby, B. G.; Stites, D. P.; Boushey, H. A., Jr. (1991) Effects of 0.60 ppm nitrogen dioxide on circulating and bronchoalveolar lavage ly mphocyte phenotypes in healthy subjects. Environ. Res. 55: 18-30. Ruckerl, R.; Ibald-Mulli, A.; Koenig, W. Schneider, A. ; Woelke, G.; Cyrys, J.; Heinrich, J.; Marder, V.; Frampton, M.; Wichmann, H. E.; Peters, A. (2006) Air pollution and markers of inflammation and coagulation in patients with coronary heart disease. Environ. Health Perspect. 173: 432-441. Rusznak, C.; Devalia, J. L.; Davies, R. J. (1996) Airway response of asthmatic subjects to inhaled allergen after exposure to pollutants. Thorax 51: 1105-1108.
Sabin, L. D.; Kozawa, K.; Behrentz, E.; Winer, A. M.; Fitz, D. R.; Pankratz, D. V.; Colome, S. D.; Fruin, S. A. (2005) Analysis of real-time variabl es affecting children’s exposure to diesel-related pollutants during school bus commutes in Los Angeles. Atmos. Environ. 39: 5243-5254. Saez, M.; Ballester, F.; Barceló, M. A.; Pérez-Hoyos, S.; Bellido, J.; Tenías, J. M.; Ocaña, R.; Figueiras, A.; Arribas, F.; Aragonés, N.; Tobías, A.; Cirera, L.; Cañada, A.; on behalf of the EMECAM Group. (2002) A combined analysis of the short-term effects of photochemical air pollutants on mortality within the EMECAM project. Environ. Health Perspect. 110: 221-228. Saez, M.; Tobias, A.; Munoz, P.; Campbell, M. J. (1999) A GEE moving average analysis of the relationship between air pollution and mortality fo r asthma in Barcelona, Spain. Stat Med. 18: 2077-2086.
Salam, M. T.; Millstein, J.; Li, Y.-F.; Lurmann, F. W.; Margolis, H. G.; Gilliland, F. D. (2005) Birth outcomes and prenatal exposure to ozone, carbon monoxide, and particulate matter: results from the Children’s Health Study. Environ. Health Perspect. 113: 1638-1644. Salmeen, I.; Durisin, A. M.; Prater, T. J.; Riley, T. ; Schuetzle, D. (1982) Contri bution of 1-nitropyrene to direct-acting Ames assay mutagenicities of diesel particulate extracts. Mutat. Res. 104: 17-23. Samet, J. M.; Bell, M. L. (2004) Commentary: nitrogen dioxide and asthma redux. Int. J. Epidemiol. 33: 215-216.39 Samet, J. M.; Zeger, S. L.; Dominici, F.; Curriero, F.; Coursac, I.; Dockery, D. W.; Schwartz, J.; Zanobetti, A. (2000) The national morbidity, morta lity, 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. Samoli, E.; Aga, E.; Touloumi, G.; Nisiotis, K.; Fo rsberg, B.; Lefranc, A.; Pekkanen, J.; Wojtyniak, B.; Schindler, C.; Niciu, E.; Brunstein, R.; Dodi č Fikfak, M.; Schwartz, J.; Katsouyanni, K. (2006) Short-term effects of nitrogen dioxide on mortality: an analysis within the APHEA project. Eur. Respir. J. 27: 1129-1137. Samoli, E.; Schwartz, J.; Analitis, A.; Petasakis, Y.; Wojtyniak, B.; Touloumi, G.; Spix, C.; Balducci, F.; Medina, S.; Rossi, G.; Sunyer, J.; Anderson, H. R.; Katsouyanni, K. (2003). Sensitivity analyses of regional differences in short-term effects of ai r pollution on daily mortality in APHEA cities.
Sandström, T.; Andersson, M. C.; Kolmodin-Hedm an, B.; Stjernberg, N.; Angström, T. (1990) Bronchoalveolar mastocytosis and lymphocytosis after nitrogen dioxide exposure in man: a timekinetic study. Eur. Respir. J. 3: 138-143. Sandström, T.; Helleday, R.; Bjermer, L.; Stjernberg , N. (1992a) Effects of repeated exposure to 4 ppm nitrogen dioxide on bronchoalveolar lymphocyte s ubsets and macrophages in healthy men. Eur. Respir. J. 5: 1092-1096.
Sandström, T.; Ledin, M.-C.; Thomasson, L.; Helle day, R.; Stjernberg, N. (1992b) Reductions in lymphocyte subpopulations after repeated exposure to 1.5 ppm nitrogen dioxide. Br. J. Ind. Med. 49: 850-854. Sandström, T.; Stjernberg, N.; Eklund, A.; Ledin, M. -C.; Bjermer, L.; Kolmodin-Hedman, B.; Lindström, K.; Rosenhall, L.; Angström, T. (1991) Inflammato ry cell response in bronchoalveolar lavage fluid after nitrogen dioxide exposure of healthy subject s: a dose-response study. Eur. Respir. J. 4: 332- 339.
Sarnat, J. A.; Brown, K. W.; Schwartz, J.; Coull, B. A.; Koutrakis, P. (2005) Ambient gas concentrations and personal particulate matter expos ures: implications for studying the health effects of particles. Epidemiology 16: 385-395. Sarnat, J. A.; Koutrakis, P.; Suh, H. H. (2000) A ssessing the relationship between personal particulate and gaseous exposures of senior citizens living in Ba ltimore, MD. J. Air Waste Manage. Assoc. 50: 1184-1198.
Sarnat, J. A.; Schwartz, J.; Catalano, P. J.; Suh, H. H. (2001) Gaseous pollutants in particulate matter epidemiology: confounders or surrogates? Environ. Health Perspect. 109: 1053-1061. Sarnat, S. E.; Suh, H. H.; Coull, B. A.; Schwartz, J.; Stone, P. H.; Gold, D. R. (2006) Ambient particulate air pollution and cardiac arrhythmia in a panel of older adults in Steubenville, Ohio. Occup. Environ. Med. 63: 700-706. Sarwar, G.; Corsi, R.; Allen, D.; Weschler, C. (2002a ) Production and levels of selected indoor radicals: a modeling assessment. In: Proceedings of 9th International Conference on Indoor Air Quality and Climate, Indoor Air 2002; June-July; Monterey, CA. Sarwar, G.; Corsi, R.; Kumura, Y.; Allen, D.; Weschler, C. J. (2002b) Hydroxyl radicals in indoor environments. Atmos. Environ. 36: 3973-3988. Sasaki, J. C.; Arey, J.; Eastmond, D. A.; Parks, K. K.; Grosovsky, A. J. (1997) Genotoxicity induced in human lymphoblasts by atmospheric reaction products of naphthalene and phenanthrene. Mutat. Res. 393: 23-35.40 Saxon, A.; Diaz-Sanchez, D. (2005) Air pollution and allergy: you are what you breathe. Nat. Immunol. 6: 223-226.
Scarlett, J. F.; Abbott, K. J.; Peacock, J. L.; Strach an, D. P.; Anderson, H. R. (1996) Acute effects of summer air pollution on respiratory function in pr imary school children in southern England. Thorax 51: 1109-1114. Schildcrout, J. S.; Sheppard, L.; Lumley, T.; Slaughter, J. C.; Koenig, J. Q.; Shapiro, G. G. (2006) Ambient air pollution and asthma exacerbations in children: an eight-city analysis. Am. J. Epidemiol. 164: 505-517. Schindler, C.; Ackermann-Liebrich, U.; Leuenberger, P.; Monn, C.; Rapp, R.; Bolognini, G.; Bongard, J.- P.; Brändli, O.; Domenighetti, G.; Karrer, W.; Kelle r, R.; Medici, T. G.; Perruchoud, A. P.; Schöni, M. H.; Tschopp, J.-M.; Villiger, B.; Zellweger, J.-P.; SAPALDIA Team. (1998) Associations between lung function and estimated average exposure to NO 2 in eight areas of Switzerland. Epidemiology 9: 405-411. Schindler, C.; Künzli, N.; Bongard, J.-P.; Leuenberg er, P.; Karrer, W.; Rapp, R.; Monn, C.; AckermannLiebrich, 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. Schouten, J. P.; Vonk, J. M.; de Graaf, A. (1996) Short term effects of air pollution on emergency hospital admissions for respiratory disease: results of the APHEA project in two major cities in The Netherlands, 1977-89. In: St Leger, S., ed. The APHEA project. Short term effects of air pollution on health: a European approach using epidemiol ogical time series data. J. Epidemiol. Community Health 50 (suppl. 1): S22-S29. Schuetzle, D. (1983) Sampling of vehicle emissions for chemical analysis and biological testing. Environ. Health Perspect. 47: 65-80. Schwartz, J. (2001) Air pollution and blood markers of cardiovascular risk. Environ. Health Perspect. Suppl. 109: 405-409. Schwartz, J.; Dockery, D. W.; Neas, L. M.; Wypij, D.; Ware, J. H.; Spengler, J. D.; Koutrakis, P.; Speizer, F. E.; Ferris, B. G., Jr. (1994) Acute effects of summer air pollution on respiratory symptom reporting in children. Am. J. Respir. Crit. Care Med. 150: 1234-1242. Schwartz, J.; Litonjua, A.; Suh, H.; Verrier, M.; Zanobetti, A.; Syring, M.; Nearing, B.; Verrier, R.; Stone, P.; MacCallum, G.; Speizer, F. E.; Gold, D. R. (2005) Traffic related pollution and heart rate variability in a panel of elderly subjects. Thorax 60: 455-461. Seaton, A.; Dennekamp, M. (2003) Hypothesis: ill health associated with low concentrations of nitrogen dioxide--an effect of ultrafine particles? Thorax 58: 1012-1015. Ségala, C.; Fauroux, B.; Just, J.; Pascual, L.; Grimfe ld, A.; Neukirch, F. (1998) Short-term effect of winter air pollution on respiratory health of asthma tic children in Paris. Eur. Respir. J. 11: 677-685. Ségala, C.; Poizeau, D.; Neukirch, F.; Aubier, M.; Sa mson, J.; Gehanno, P. (2004) Air pollution, passive smoking, and respiratory symptoms in adults. Arch. Environ. Health 59: 669-676. Seinfeld, J. H.; Pandis, S. N. (1998) Atmospheric chemistry and physics: from air pollution to climate change. New York, NY: John Wiley & Sons, Inc. Selgrade, M. K.; Mole, M. L.; Miller, F. J.; Hatch, G. E.; Gardner, D. E.; Hu, P. C. (1981) Effect of NO 2 inhalation and vitamin C deficiency on protein a nd lipid accumulation in the lung. Environ. Res. 26: 422-437.41 Shalamberidze, O. P.; Tsereteli, N. T. (1971) Effect of low concentrations of sulfur and nitrogen dioxides on the estrual cycle and reproductive functions of experimental animals. Hyg. Sanit. (USSR) 36: 178-182. Sheppard, L. (2005) Acute air pollution effects: con sequences of exposure distribution and measurements. J. Toxicol. Environ. Health A. 68: 1127-35. Sherwin, R. P.; Carlson, D. A. (1973) Protein cont ent of lung lavage fluid of guinea pigs exposed to 0.4 ppm nitrogen dioxide: disc-gel electrophoresis for amount and types. Arch. Environ. Health 27: 90-93. Shindell, D. T.; Faluvegi, G.; Stevenson, D. S.; Krol , M. C.; Emmons, L. K.; Lamarque, J.-F.; Pétron, G.; Dentener, F. J.; Ellingsen, K.; Schultz, M. G.; Wild, O.; Amann, M.; Atherton, C. S.; Bergmann, D. J.; Bey, I.; Butler, T.; Cofala, J.; Collins, W. J.; De rwent, R. G.; Doherty, R. M.; Drevet, J.; Eskes, H. J.; Fiore, A. M.; Gauss, M.; Hauglustaine, D. A.; Horowitz, L. W.; Isaksen, I. S. A.; Lawrence, M. G.; Montanaro, V.; Müller, J.-F.; Pitari, G.; Prather, M. J.; Pyle, J. A.; Rast, S.; Rodriguez, J. M.; Sanderson, M. G.; Savage, N. H.; Strahan, S. E.; Sudo, K.; Szopa, S.; Unger, N.; Van Noije, T. P. C.; Zeng, G. (2006) Multimodel simulations of carbon monoxide: comparison with observations and projected near-future changes. J. Geophys. Res. [Atmos.] 111(D19306): 10.1029/2006JD007100. Shorter, J. H.; Herndon, S.; Zahniser, M. S.; Nelson, D. D.; Wormhoudt, J.; Demerjian, K. L.; Kolb, C. E. (2005) Real-time measurements of nitrogen oxide emissions from in-use New York City transit buses using a chase vehicle. Environ. Sci. Technol. 39: 7991-8000. Shy, C. M.; Love, G. J. (1980) Recent evidence on the human health effects of nitrogen dioxide. In: Lee, S. D., ed. Nitrogen oxides and their effects on health: [papers from the symposium “Biological studies of environmental pollutants, part II. Health effects of nitrogen oxides”]; April 1979; Honolulu, HI. Ann Arbor, MI: Ann Arbor Science Publishers, Inc.; pp. 291-305. Siegel, P. D.; Al-Humadi, N. H.; Nelson, E. R.; Lewis, D. M.; Hubbs, A. F. (1997) Adjuvant effect of respiratory irritation on pulmonary allergic sensiti zation: time and site dependency. Toxicol. Appl. Pharmacol. 144: 356-362. Silkoff, P. E.; Zhang, L.; Dutton, S.; Langmack, E. L.; Vedal, S.; Murphy, J.; Make, B. (2005) Winter air pollution and disease parameters in advanced chronic obstructive pulmonary disease panels residing in Denver, Colorado. J. Allergy Clin. Immunol. 115: 337-344. Simoni, M.; Carrozzi, L.; Baldacci, S.; Scognamiglio, A.; Di Pede, F.; Sapigni, T.; Viegi, G. (2002) The Po River delta (north Italy) indoor epidemiologi cal study: effects of pollutant exposure on acute respiratory symptoms and respiratory function in adults. Arch. Environ. Health 57: 130-136. Simoni, M.; Scognamiglio, A.; Carrozzi, L.; Baldacci, S.; Angino, A.; Pistelli, F.; Di Pede, F.; Viegi, G. (2004) Indoor exposures and acute respiratory e ffects in two general population samples from a rural and an urban area in Italy. J. Exposure Anal. Environ. Epidemiol. 14 (suppl. 1): S144-S152. Simpson, R.; Denison, L.; Petroeschevsky, A.; Thalib , L.; Williams, G. (2000) Effects of ambient particle pollution on daily mortality in Melbourne 1991-1996. J. Exposure Anal. Environ. Epidemiol. 10: 488-496. Simpson, R.; Williams, G.; Petroeschevsky, A.; Best, T.; Morgan, G.; Denison, L.; Hinwood, A.; Neville, G. (2005a) The short-term effects of air pollution on hospital admissions in four Australian cities. Aust. N. Z. J. Public Health 29: 213-221. Simpson, R.; Williams, G.; Petroeschevsky, A.; Best, T.; Morgan, G.; Denison, L.; Hinwood, A.; Neville, G.; Neller, A. (2005b) The short-term effects of air pollution on daily mortality in four Australian cities. Aust. N. Z. J. Public Health 29: 205-212.42 Singer, B. C.; Hodgson, A. T.; Hotchi, T.; Kim, J. J. (2004) Passive measurement of nitrogen oxides to assess traffic-related pollutant exposure for the E ast Bay Children’s Respiratory Health Study. Atmos. Environ. 38: 393-403. Singh, H. B.; Salas, L.; Herlth, D.; Kolyer, R.; Czech , E.; Avery, M.; Crawford, J. H.; Pierce, R. B.; Sachse, G. W.; Blake, D. R.; Cohen, R. C.; Bertram, T. H.; Perring, A.; Wooldridge, P. J.; Dibb, J.; Huey, G.; Hudman, R. C.; Turquety, S.; Emmons, L. K.; Flocke, F.; Tang, Y.; Carmichael, G. R.; Horowitz, L. W. (2007) Reactive nitrogen distri bution and partitioning in the North American troposphere and lowermost st ratosphere. J. Geophys. Res. [Atmos.] 112(D12S04): 10.1029/2006JD007664. Slordal, L. H.; Walker, S. E.; Solberg, S. (2003) The urban air dispersion model EPISODE applied in AirQUIS2003. Technical description. Kjeller, Norway: Norwegian Institute for Air Research (NILU); report no. TR 12/2003. Smith, B. J.; Nitschke, M.; Pilotto, L. S.; Ruffin, R. E.; Pisaniello, D. L.; Wilson, K. J. (2000) Health effects of daily indoor nitrogen dioxide exposure in people with asthma. Eur. Respir. J. 16: 879- 885.
Solomon, C.; Christian, D. L.; Chen, L. L.; Welch, B. S.; Kleinman, M. T.; Dunham, E.; Erle, D. J.; Balmes, J. R. (2000) Effect of serial-day e xposure to nitrogen dioxide on airway and blood leukocytes and lymphocyte subsets. Eur. Respir. J. 15: 922-928. Son, B.; Yang, W.; Breysse, P.; Chung, T.; Lee, Y. (2004) Estimation of occupational and nonoccupational nitrogen dioxide exposure for Kor ean taxi drivers using a microenvironmental model. Environ. Res. 94: 291-296.
Sørensen, M.; Loft, S.; Andersen, H. V.; Raaschou- Nielsen, O.; Skovgaard, L. T.; Knudsen, L. E.; Nielsen, I. V.; Hertel, O. (2005) Personal exposure to PM 2.5 , black smoke and NO 2 in Copenhagen: relationship to bedroom and outdoor concentrations covering seasonal variation. J. Exposure Anal. Environ. Epidemiol. 15: 413-422. Spengler, J. D.; Brauer, M.; Samet, J. M.; Lamb ert, W. E. (1993) Nitrous acid in Albuquerque, New Mexico, homes. Environ. Sci. Technol. 27: 841-845. Spengler, J.; Schwab, M.; Ryan, P. B.; Colome, S.; W ilson, A. L.; Billick, I.; Becker, E. (1994) Personal exposure to nitrogen dioxide in the Los Angeles Basin. J. Air Waste Manage. Assoc. 44: 39-47. Spicer, C. W.; Coutant, R. W.; Ward, G. F.; Joseph, D. W.; Gaynor, A. J.; Billick, I. H. (1989) Rates and mechanisms of NO 2 removal from indoor air by residential materials. Environ. Int. 15: 643-654. Spicer, C. W.; Kenny, D. V.; Ward, G. F.; Billick, I. H. (1993) Transformations, lifetimes, and sources of NO 2 , HONO, and HNO 3 in indoor environments. Air Waste 43: 1479-1485. Spix, C.; Anderson, H. R.; Schwartz, J.; Vigotti, M. A.; LeTertre, A.; Vonk, J. M.; Touloumi, G.;Balducci, F.; Piekarski, T.; Bacharova, L.; Tobias, A.; Pönkä, A.; Katsouyanni, K. (1998) Shortterm effects of air pollution on hospital admissions of respiratory diseases in Europe: a quantitative summary of APHEA study results. Arch. Environ. Health 53: 54-64. Steerenberg, P. A.; Bischoff, E. W. M. A.; de Klerk, A.; Verlaan, A. P. J.; Jongbloets, L. M. N.; Van Loveren, H.; Opperhuizen, A.; Zomer, G.; Heiste rkamp, S. H.; Hady, M.; Spieksma, F. T. M.; Fischer, P. H.; Dormans, J. A. M. A.; van Amsterdam, J. G. C. (2003) Acute effect of air pollution on respiratory complaints, exhaled NO and biomarkers in nasal lavages of allergic children during the pollen season. Int. Arch. Allergy Immunol. 131: 127-137.43 Steerenberg, P. A.; Nierkens, S.; Fischer, P. H.; Va n Loveren, H.; Opperhuizen, A.; Vos, J. G.; Van Amsterdam, J. G. (2001) Traffic-related air polluti on affects peak expiratory flow, exhaled nitric oxide, and inflammatory nasal markers. Arch. Environ. Health 56: 167-174. Steinbacher M.; Zellweger C.; Schwarzenbach B.; B ugmann S.; Buchmann B.; Ordóñez C.; Prevot A. S. H.; Hueglin C. (2007) Nitrogen oxide measurements at rural sites in Switzerland: Bias of conventional measurement techniques. J. Geophys. Res. 112: 1-13. Steinvil, A.; Kordova-Biezuner, L.; Shapira, I.; Ber liner, S.; Rogowski, O. (2007) Short-term exposure to air pollution and inflammation-sensitive biomarkers. Environ. Res. 106: 51-61.
Stemmler, K.; Ammann, M.; Donders, C.; Kleffmann, J.; George, C. (2006) Photosensitized reduction of nitrogen dioxide on humic acid as a source of n itrous acid. Nature (London, U.K.) 440: 195-198. Stephens, R. J.; Freeman, G.; Crane, S. C.; Furiosi, N. J. (1971) Ultrastructural changes in the terminal bronchiole of the rat during continuous, low-level exposure to nitrogen dioxide. Exp. Mol. Pathol. 14: 1-19. Stephens, R. J.; Freeman, G.; Evans, M. J. (1972) Early response of lungs to low levels of nitrogen dioxide: light and electron microscopy . Arch. Environ. Health 24: 160-179. Stevenson D. S.; Dentener F. J.; Schultz M. G.; Ellingsen K.; van Noije T. P. C.; Wild O.; Zeng G.; Amann M.; Atherton C. S.; Bell N.; Bergmann D. J.; Bey I.; Butler T.; Cofala J.; Collins W. J.; Derwent R. G.; Doherty R. M.; Drevet J.; Eskes H. J.; Fiore A. M.; Gauss M.; Hauglustaine D. A.; Horowitz L. W.; Isaksen I. S. A.; Krol M. C.; Lamarque J. F.; Lawrence M. G.; Montanaro V.; Mueller J. F.; Pitari G.; Prather M. J.; Pyle J. A.; Rast S.; Rodriguez J. M.; Savage N. H.; Shindell D. T.; Strahan S. E.; Sudo K.; Szopa S. (2006) Multimodel ensemble simulations of present-day and near-future tropospheric ozone. J. Geophys. Res. 111: D08301. Stieb, D. M.; Beveridge, R. C.; Brook, J. R.; Smith-Doiron, M.; Burnett, R. T.; Dales, R. E.; Beaulieu, S.; Judek, S.; Mamedov, A. (2000) Air pollution, aeroallergens and cardiorespiratory emergency department visits in Saint John, Canada. J. Exposure Anal. Environ. Epidemiol. 10: 461-477. Stieb, D. M.; Burnett, R. T.; Beveridge, R. C.; Br ook, J. R. (1996) Association between ozone and asthma emergency department visits in Saint John, Ne w Brunswick, Canada. Environ. Health Perspect. 104: 1354-1360. Stieb, D. M.; Judek, S.; Burnett, R. T. (2002) Me ta-analysis of time-series studies of air pollution and mortality: effects of gases and particles and the infl uence of cause of death, age, and season. J. Air Waste Manage. Assoc. 52: 470-484. Stieb, D. M.; Judek, S.; Burnett, R. T. (2003) Me ta-analysis of time-series studies of air pollution and mortality: update in relation to the use of genera lized additive models. J. Air Waste Manage. 53: 258-261. Stölzel, M.; Peters, A.; Wichmann, H.-E. (2003) Daily mo rtality and fine and ultrafine particles in Erfurt, Germany. In: Revised analyses of time-series studi es of air pollution and health. Special report. Boston, MA: Health Effects Institute; pp. 231- 240. Available: http://www.healtheffects.org/ Pubs/TimeSeries.pdf [18 October, 2004]. Strand, V.; Rak, S.; Svartengren, M.; Bylin, G. (1997) Nitrogen dioxide e xposure enhances asthmatic reaction to inhaled allergen in subjects with ast hma. Am. J. Respir. Crit. Care Med. 155: 881-887. Strand, V.; Salomonsson, P.; Lundahl, J.; Bylin, G. (1996) Immediate and delayed effects of nitrogen dioxide exposure at an ambient level on bronchial responsiveness to histamine in subjects with asthma. Eur. Respir. J. 9: 733-740.44 Strand, V.; Svartengren, M.; Rak, S.; Barck, C.; Bylin , G. (1998) Repeated exposure to an ambient level of NO 2 enhances asthmatic response to nonsymptomatic allergen dose. Eur. Respir. J. 12: 6-12. Stutz, J.; Alicke, B.; Ackermann, R.; Geyer, A.; Wa ng, S.; White, A. B.; Williams, E. J.; Spicer, C. W.; Fast, J. D. (2004) Relative humidity dependence of HONO chemistry in urban areas. J. Geophys. Res. [Atmos.] 109: 10.1029/2003JD004135. Sun, H.-L.; Chou, M.-C.; Lue, K.-H. (2006) The re lationship of air pollution to ED visits for asthma differ between children and adults. Am. J. Emerg. Med. 24: 709-713. Sunyer, J.; Castellsague, J.; Saez, M.; Tobias, A.; Anto, J. M. (1996) Air pollution and mortality in Barcelona. Journal of epidemiology and community health. 1: S76-S80. Sunyer, J.; Spix, C.; Quénel, P.; Ponce-de-León, A.; Pönkä, A.; Barumandzadeh, T.; Touloumi, G.; Bacharova, L.; Wojtyniak, B.; Vonk, J.; Bisanti, L. ; Schwartz, J.; Katsouyanni, K. (1997) Urban air pollution and emergency admissions for asthma in four European cities: the APHEA project. Thorax 52: 760-765.
Suzuki, A. K.; Tsubone, H.; Ichinose, T.; Oda, H.; Kubota, K. (1981) [Effects of subchronic nitrogen dioxide exposure on arterial blood pHa, Pa CO2 and Pa O2 in rats]. Nippon Eiseigaku Zasshi 36: 816- 823. Suzuki, T.; Terada, N.; Ikeda, S.; Ohsawa, M.; Endo, K.; Mizoguchi, I. (1984) [Effect of NO 2 exposure on the activity of angiotensin converting enzy me in lung]. Kenkyu Nenpo Tokyo-toritsu Eisei Kenkyusho 35: 279-285. Svartengren, M.; Strand, V.; Bylin, G.; Jarup, L.; Pe rshagen, G. (2000) Short-term exposure to air pollution in a road tunnel enhances the asthmatic response to allergen. Eur. Resp. J. 15: 716-724. Tabacova, S.; Balabaeva, L. (1988) Nitrogen dioxide embryotoxicity a nd lipid peroxidation. Teratology 38: 29A. Tabacova, S.; Nikiforov, B.; Balabaeva, L. (1985) Postnatal effects of maternal exposure to nitrogen dioxide. Neurobehav. Toxicol. Teratol. 7: 785-789. Tager, I. B.; Balmes, J.; Lurmann, F.; Ngo, L.; Alco rn, S.; Künzli, N. (2005) Chronic exposure to ambient ozone and lung function in young a dults. Epidemiology 16: 751-759. Takano, H.; Yanagisawa, R.; Inoue, K.-I.; Shimada, A. ; Ichinose, T.; Sadakane, K.; Yoshino, S.; Yamaki, K.; Morita, M.; Yoshikawa, T. (2004) Nitrogen di oxide air pollution near ambient levels is an atherogenic risk primarily in obese subjects: a brief communication. Exp. Biol. Med. 229: 361-364. Tanaka, H.; Honma, S.; Nishi, M.; Igarashi, T.; Tera moto, S.; Nishio, F.; Abe, S. (1998) Acid fog and hospital visits for asthma: an epidemiological study. Eur. Respir. J. 11: 1301-1306. Tenías, J. M.; Ballester, F.; Pérez-Hoyos, S.; Rive ra, M. L. (2002) Air pollution and hospital emergency room admissions for chronic obstructive pulmonary disease in Valencia, Spain. Arch. Environ. Health 57: 41-47. Tenías, J. M.; Ballester, F.; Rivera, M. L. (1998) Association between hospital emergency visits for asthma and air pollution in Valencia, Spai n. Occup. Environ. Med. 55: 541-547. Tepper, J. S.; Costa, D. L.; Winsett, D. W.; Steven s, M. A.; Doerfler, D. L.; Watkinson, W. P. (1993) Near-lifetime exposure of the rat to a simulate d urban profile of nitr ogen dioxide: pulmonary function evaluation. Fund. Appl. Toxicol. 20: 88-96. Thompson, A. J.; Shields, M. D.; Patterson, C. C. (2001) Acute asthma exacerbations and air pollutants in children living in Belfast, Northern Irela nd. Arch. Environ. Health 56: 234-241.45Timonen, K. L.; Hoek, G.; Heinrich, J.; Bernard, A.; Brunekreef, B.; De Hartog, J.; Hameri, K.; IbaldMulli, A.; Mirme, A.; Peters, A.; Tiittanen, P. ; Kreyling, W. G.; Pekkanen, J. (2004) Daily variation in fine and ultrafine particulate air po llution and urinary concentrations of lung Clara cell protein CC16. Occup. Environ. Med. 61: 908-914. Timonen, K. L.; Pekkanen, J. (1997) Air pollution a nd respiratory health among children with asthmatic or cough symptoms. Am. J. Respir. Crit. Care Med. 156: 546-552.
Timonen, K. L.; Pekkanen, J.; Tiittanen, P.; Salonen, R. O. (2002) Effects of air pollution on changes in lung function induced by exercise in children with chronic respiratory symptoms. Occup. Environ. Med. 59: 129-134. 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.
Tokiwa, H.; Nakanishi, Y.; Sera, N.; Hara, N.; Inuz uka, S. (1998) Analysis of environmental carcinogens associated with the incidence of lung cancer. Toxicol. Lett. 99: 33-41. Tokiwa, H.; Ohnishi, Y. (1986) Mutagenicity and car cinogenicity of nitroarenes and their sources in the environment. Crit. Rev. Toxicol. 17: 23-60. Tolbert, P. E.; Klein, M.; Peel, J. L.; Sarnat, S. E.; Sarnat, J. A. (2007) Multipollutant modeling issues in a study of ambient air quality and emergency depa rtment visits in Atlanta. J. Exposure Sci. Environ. Epidemiol. 17(Suppl. 2s): S29-S35.
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 vi sits for asthma in Atlanta, Georgia. Am. J. Epidemiol. 151: 798-810. Triche, E. W.; Belanger, K.; Bracken, M. B.; Beckett, W. S.; Holford, T. R.; Gent, J. F.; McSharry, J.-E.; Leaderer, B. P. (2005) Indoor heating sources and respiratory symptoms in nonsmoking women. Epidemiology 16: 377-384. Tsai, S.-S.; Cheng, M.-H.; Chiu, H.-F.; Wu, T. -N.; Yang, C.-Y. (2006) Air pollution and hospital admissions for asthma in a tropical city: Kaohs iung, Taiwan. Inhalation Toxicol. 18: 549-554. Tsai, S.-S.; Goggins, W. B.; Chiu, H.-F.; Yang, C.-Y. (2003) Evidence for an association between air pollution and daily stroke admissions in Kaohsiung, Taiwan. Stroke 34: 2612-2616. Tsubone, H.; Suzuki, A. K. (1984) Reflex cardiopulmona ry responses by stimulation to type J receptors in rats exposed to NO 2 . J. Toxicol. Environ. Health 13: 905-917. Tunnicliffe, W. S.; Burge, P. S.; Ayres, J. G. (1994) Effect of domestic concentr ations of nitrogen dioxide on airway responses to inhaled allergen in asthmatic patients. Lancet 344: 1733-1736. U.S. Census Bureau. (2006) American Housing Survey for the United States: 2005. Washington, DC: U.S. Department of Housing a nd Urban Development. (Current Housing Reports, Series H150/05). Available: http://www.census.gov/prod/2006pubs/h150-05.pdf (24 January, 2008). U.S. Code. (2003a) Clean Air Act, §108, air quality cr iteria and control techniques. U. S. C. 42: §7408. U.S. Code. (2003b) Clean Air Act, §109, national am bient air quality standards. U. S. C. 42: §7409. U.S. Code. (2005) Clean Air Act, §302, definitions. U. S. C. 42: §7602(h). U.S. Court of Appeals for the District of Columbia. (1980) Lead Industries v. U.S. Environmental Protection Agency. 647 F2d 1130, 1154 (DC Cir. 1980).46 U.S. Court of Appeals for the District of Columbia. (1981) American Petroleum Institute v. Costle. 665 F2d 1176, 1186 (DC Cir. 1981). U.S. Environmental Protection Agency. (1982) Air quality criteria for oxides of nitrogen. Research Triangle Park, NC: Office of Health and Envir onmental Assessment, Environmental Criteria and Assessment Office; EPA report no. EPA-600/8-82-026. Available from: NTIS, Springfield, VA; PB83-131011. U.S. Environmental Protection Agency. (1993) Air quality criteria for oxides of nitrogen. Research Triangle Park, NC: Office of Health and Envir onmental Assessment, Environmental Criteria and Assessment Office; report nos. EPA/600/8-91/049aF-cF . 3v. Available from: NTIS, Springfield, VA; PB95-124533, PB95-124525, and PB95-124517. U.S. Environmental Protection Agency. (1995) Review of the national ambient air quality standards for nitrogen dioxide: assessment of scientific and technical information. Research Triangle Park, NC: Office of Air Quality Planning and St andards; report no. EPA/452/R-95-005. U.S. Environmental Protection Agency. (1996) Air quality criteria for ozone and related photochemical oxidants. Research Triangle Park, NC: Offi ce 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. (1998) SLAMS/NAMS/PAMS network review guidance. Research Triangle Park, NC: Office of Air Qua lity Planning and Standards; EPA-454/R-98-003. Available: http://www.epa.gov/ttn/amtic/files/ambien t/criteria/reldocs/netrev98.pdf (22 February, 2008). U.S. Environmental Protection Agency. (2004) Air quality criteria for particulate matter. Research Triangle Park, NC: National Center for E nvironmental Assessment; report no. EPA/600/P99/002aF-bF. 2v. Available: http://cfpub.epa.gov/ncea/ [9 November, 2004]. U.S. Environmental Protection Agency. (2005) Gu idelines for carcinogen risk assessment. Washington, DC: Risk Assessment Forum; report no. EPA/630/P-03/001F. Available: http://cfpub.epa.gov/ncea/ index.cfm [30 November, 2005]. U.S. Environmental Protection Agency. (2006a) Air quality criteria for ozone and related photochemical oxidants. Research Triangle Park, NC: National Center for Environmental Assessment; report no. EPA/600/R-05/004aF-cF. 3v. Available: h ttp://cfpub.epa.gov/ncea/ [24 March, 2006]. U.S. Environmental Protection Agency. (2006b) 2002 National Emissions Inventory Booklet. From http://www.epa.gov/ttn/chief/net/2002neibooklet.pdf. U.S. Environmental Protection Agency. (2007) Integrated plan for the primary National Ambient Air Quality Standard for Nitrogen Dioxide. Resear ch Triangle Park, NC: National Center for Environmental Assessment. U.S. Senate. (1970) National Air Quality Standard s Act of 1970: report of the Committee on Public Works, United States Senate together with individual views to accompany S. 4358. Washington, DC: Committee on Public Works; report no. CONG/91-1196. U.S. Supreme Court. (2001) Whitman v. American Trucking Association. 531 U.S. 457 (nos. 99-1257 and 99-1426). Vagaggini, B.; Paggiaro, P. L.; Giannini, D.; Franco, A. D.; Cianchetti, S.; Carnevali, S.; Taccola, M.; Bacci, E.; Bancalari, L.; Dente, F. L.; Giuntini, C. (1996) Effect of short-term NO 2 exposure on induced sputum in normal, asthmatic and CO PD subjects. Eur. Respir. J. 9: 1852-1857.47 Van Der Zee, S. C.; Hoek, G.; Boezen, H. M.; Schouten, J. P.; Van Wijnen, J. H.; Brunekreef, B. (1999) Acute effects of urban air pollution on respirator y health of children with and without chronic respiratory symptoms. Occup. Environ. Med. 56: 802-813. Van Der Zee, S. C.; Hoek, G.; Boezen, M. H.; Schouten, J. P.; Van Wijnen, J. H.; Brunekreef, B. (2000) Acute effects of air pollution on respiratory health of 50-70 yr old adults. Eur. Respir. J. 15: 700- 709. Van Noije, T. P. C.; Eskes, H. J.; Dentener, F. J.; Stevenson, D. S.; Ellingsen, K.; Schultz, M. G.; Wild, O.; Amann, M.; Atherton, C. S.; Bergmann, D. J.; Bey, I.; Boersma, K. F.; Butler, T.; Cofala, J.; Drevet, J.; Fiore, A. M.; Gauss, M.; Hauglustaine, D. A.; Horowitz, L. W.; Isaksen, I. S. A.; Krol, M. C.; Lamarque, J.-F.; Lawrence, M. G.; Martin, R. V.; Montanaro, V.; Müller, J.-F.; Pitari, G.; Prather, M. J.; Pyle, J. A.; Richter, A.; Rodriguez, J. M.; Savage, N. H.; Strahan, S. E.; Sudo, K.; Szopa, S.; Van Roozendael, M. (2006) Multi-m odel ensemble simulations of tropospheric NO 2 compared with GOME retrievals for the year 2000. Atmos. Chem. Phys. Discuss. 6: 2965-3047. Van Strien, R. T.; Gent, J. F.; Belanger, K.; Triche, E.; Bracken, M. B.; Leaderer, B. P. (2004) Exposure to NO 2 and nitrous acid and respiratory symptoms in the first year of life. Epidemiology 15: 471- 478. Vardoulakis, S.; Gonzalez-Flesca, N.; Fisher, B. E. A.; Pericleous, K. (2005) Spatial variability of air pollution in the vicinity of a permanent monitoring station in central Paris. Atmospheric Environment. 39: 2725-2736. Varshney, C. K.; Singh, A. P. (2003) Passive samplers for NO x monitoring: a critical review. Environmentalist 23: 127-136. Velsor, L. W.; Postlethwait, E. M. (1997) NO 2 -induced generation of extracellular reactive oxygen is mediated by epithelial lining layer antioxidants. Am. J. Physiol. 17: L1265-L1275. Victorin, K.; Busk, L.; Cederberg, H.; Magnusson, J. (1990) Genotoxic activity of 1,3-butadiene and nitrogen dioxide and their photochemical reaction products in Drosophila and in the mouse bone marrow micronucleus assay. Mutat. Res. 228: 203-209. Vigotti, M. A.; Chiaverini, F.; Biagiola, P.; Rossi, G. (2007) Urban air pollution and emergency visits for respiratory complaints in Pisa, Italy. J. Toxicol. Environ. Health Part A 70: 266-269.
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 Expo Anal Environ Epidemiol. 13: 427-35.
Villeneuve, P. J.; Chen, L.; Stieb, D.; Rowe, B. H. (2006) Associations between outdoor air pollution and emergency department visits for stroke in Ed monton, Canada. Eur. J. Epidemiol. 21: 689-700.
Vinzents, P. S.; Møller, P.; Sørensen, M.; Knudsen, L. E. ; Herte, L. Q.; Jensen, F. P.; Schibye, B.; Loft, S. (2005) Personal exposure to ultrafine particl es and oxidative DNA damage. Environ. Health Perspect. 113: 1485-1490.
Von Klot, S.; Peters, A.; Aalto, P.; Bellander, T.; Be rglind, N.; D’Ippoliti, D.; Elosua, R.; Hörmann, A.; Kulmala, M.; Lanki, T.; Löwel, H.; Pekkanen, J.; Picciotto, S.; Sunyer, J.; Forastiere, F.; Health Effects of Particles on Susceptible Subpopulations (HEAPSS) Study Group. (2005) Ambient air pollution is associated with increased risk of hosp ital cardiac readmissions of myocardial infarction survivors in five European cities. Circulation 112: 3073-3079. Von Klot, S.; Wölke, G.; Tuch, T.; Heinrich, J.; Dockery, D. W.; Schwartz, J.; Kreyling, W. G.; Wichmann, H. E.; Peters, A. (2002) Increased asthma medication use in association with ambient fine and ultrafine particles. Eur. Respir. J. 20: 691-702.48 Wagner, W. D.; Duncan, B. R.; Wright, P. G.; Stokinge r, H. E. (1965) Experimental study of threshold limit of NO 2 . Arch. Environ. Health 10: 455-466. Wainman, T.; Weschler, C.; Lioy, P.; Zhang, J. (2001) Effects of surface type and relative humidity on the production and concentration of nitrous acid in a model indoor environment. Environ. Sci. Technol. 35: 2200-2206. Wallace, L. A.; Emmerich, S. J.; Howard-Reed, C. (2004) Source strengths of ultrafine and fine particles due to cooking with a gas stove. E nviron. Sci. Technol. 38: 2304-2311. Wang, J. H.; Devalia, J. L.; Duddle, J. M.; Hamilton, S. A.; Davies, R. J. (1995a) Effect of six-hour exposure to nitrogen dioxide on early-phase nasal res ponse to allergen challenge in patients with a history of seasonal allergic rhinitis. J. Allergy Clin. Immunol. 96: 669-676. Wang, J. H.; Devalia, J. L.; Rusznak, C.; Bagnall, A.; Sapsford, R. J.; Davies, R. J. (1999) Effect of fluticasone propionate aqueous nasal spray on alle rgen-induced inflammatory changes in the nasal airways of allergic rhinitics following exposure to nitrogen dioxide. Clin. Exp. Allergy 29: 234- 240. Wang, J. H.; Duddle, J.; Devalia, J. L.; Davies, R. J. (1995b) Nitrogen dioxide increases eosinophil activation in the early-phase response to nasal a llergen provocation. Int. Arch. Allergy Immunol. 107: 103-105. Wang, X.-K.; Lu, W.-Z. (2006) Seasonal varia tion of air pollution index: Hong Kong case study. Chemosphere 63: 1261-1272. Ward, D. J.; Miller, M. R.; Walters, S.; Harrison, R. M.; Ayres, J. G. (2000) Impact of correcting peak flow for nonlinear errors on air pollutant effect estimates from a panel study. Eur. Respir. J. 15: 137-140. Ward, D. J.; Roberts, K. T.; Jones, N.; Harrison, R. M.; Ayres, J. G.; Hussain, S.; Walters, S. (2002) Effects of daily variation in outdoor particulat es and ambient acid species in normal and asthmatic children. Thorax 57: 489-502. Wayne, R. P.; Barnes, I.; Biggs, P.; Burrows, J. P.; Ca nosa-Mas, C. E.; Hjorth, J.; Le Bras, G.; Moortgat, G. K.; Perner, D.; Poulet, G.; Restelli, G.; Sidebottom, H. (1991) The nitrate radical: physics, chemistry, and the atmosphere. Atmos. Environ. Part A 25: 1-203.
Weichenthal, S.; Dufresne, A.; Infante-Rivard, C.; Joseph, L. (2007) Indoor ultrafine particle exposures and home heating systems: a cross-sectional survey of Canadian homes during the winter months. J. Exposure Sci. Environ. Epidemiol. 17: 288-297.
Wellenius, G. A.; Bateson, T. F.; Mittleman, M. A.; Schwartz, J. (2005b) Particulate air pollution and the rate of hospitalization for congestive heart fa ilure among medicare beneficiaries in Pittsburgh, Pennsylvania. Am. J. Epidemiol. 161: 1030-1036.
Wellenius, G. A.; Schwartz, J.; Mittleman, M. A. (2005a) Air pollution and hospital admissions for ischemic and hemorrhagic stroke among medicare beneficiaries. Stroke 36: 2549-2553. Weschler, C. J.; Hodgson, A. T.; Wooley, J. D. (1992) Indoor chemistry: ozone, volatile organic compounds, and carpets. Environ. Sci. Technol. 26: 2371-2377. Weschler, C. J.; Shields, H. C. (1996) The conversi on (reduction) of nitrogen dioxide to nitric oxide as a consequence of charcoal filtration. In: Yoshizawa, S.; Kimura, K.; Ikeda, K.; Tanabe, S.; Iwata, T., eds. Indoor Air ‘96: proceedings of the 7th international conference on indoor air quality and climate, v. 3, July; Nagoya, Japan. Toykyo, Japan: Indoor Air ‘96; pp. 453-458.49 Weschler, C. J.; Shields, H. C. (1997) Potential r eactions among indoor pollutants. Atmos. Environ. 31: 3487-3495. Weschler, C. J.; Shields, H. C.; Naik, D. V. (1994) Indoor chemistry involving O 3 , NO, and NO 2 as evidenced by 14 months of measurements at a site in southern California. Environ. Sci. Technol. 28: 2120-2132. Westerdahl, D.; Fruin, S.; Sax, T.; Fine, P. M.; Sioutas, C. (2005) Mobile platform measurements of ultrafine particles and associated pollutant concentr ations on freeways and residential streets in Los Angeles. Atmos. Environ. 39: 3597-3610.
Wheeler, A.; Zanobetti, A.; Gold, D. R.; Schwartz, J. ; Stone, P.; Suh, H. H. (2006) The relationship between ambient air pollution and heart rate vari ability differs for individuals with heart and pulmonary disease. Environ. Health Perspect. 114: 560-566. Wichmann, H.-E.; Spix, C.; Tuch, T.; Wölke, G.; Pete rs, A.; Heinrich, J.; Kreyling, W. G.; Heyder, J. (2000) Daily mortality and fine and ultrafine particl es in Erfurt, Germany. Part I: role of particle number and particle mass. Cambridge, MA: Hea lth Effects Institute; research report no. 98.
Williams, E. J.; Parrish, D. D.; Fehsenfeld, F. C. (1987) Determination of nitrogen oxide emissions from soils: results from a grassland site in Colorado, United States. J. Geophys. Res. [Atmos.] 92: 2173- 2179. Williams, R.; Suggs, J.; Rea, A.; Leovic, K.; Vette, A.; Croghan, C.; Sheldon, L.; Rodes, C.; Thornburg, J.; Ejire, A.; Herbst, M.; Sanders Jr, W. (2003) The Research Triangle Park particulate matter panel study: PM mass concentration relationships. Atmos. Environ. 37: 5349-5363. Wilson, W. E.; Brauer, M. (2006) Estimation of ambient and non-ambient components of particulate matter exposure from a personal monitoring panel study. J Expo Sci Environ Epidemiol. 16: 264- 74. Witschi, H. (1988) Ozone, nitrogen dioxide and lung cancer: a review of some recent issues and problems. Toxicology 48: 1-20. Witten, A.; Solomon, C.; Abbritti, E.; Arjomandi, M.; Zhai, W.; Kleinman, M.; Balmes, J. (2005) Effects of nitrogen dioxide on allergic airway responses in subjects with asthma. J. Occup. Environ. Med. 47: 1250-1259. Wolff, G. T. (1993) On a NO X -focused control strategy to reduce O 3 . J. Air Waste Manage. Assoc. 43: 1593-1596. Wolff, G. T. (1996) Closure by the Clean Air Scientific Advisory Committee (CASAC) on the draft Air Quality Criteria for Particulate Matter [letter to Carol M. Browner, Administrator, U.S. EPA]. Washington, DC: U.S. Environmental Protection Agency, Clean Air Scientific Advisory Committee.; EPA-SAB-CASAC-LTR-96-005; March 15. Wong, C.-M.; Atkinson, R. W.; Anderson, H. R.; Hedley, A. J.; Ma, S.; Chau, P. Y.-K.; Lam, T.-H. (2002) A tale of two cities: effects of air pollution on hospital admissions in Hong Kong and London compared. Environ. Health Perspect. 110: 67-77. Wong, G. W.; Ko, F. W.; Lau, T. S.; Li, S. T.; Hui, D.; Pang, S. W.; Leung, R.; Fok, T. F.; Lai, C. K. (2001) Temporal relationship between air polluti on and hospital admissions for asthmatic children in Hong Kong. Clin. Exp. Allergy 31: 565-569. Wong, T. W.; Lau, T. S.; Yu, T. S.; Neller, A.; Wong, S. L.; Tam, W.; Pang, S. W. (1999) Air pollution and hospital admissions for respiratory and cardi ovascular diseases in Hong Kong. Occup. Environ. Med. 56: 679-683.50 Woodruff, T. J.; Parker, J. D.; Kyle, A. D.; Schoendorf, K. C. (2003) Disparities in exposure to air pollution during pregnancy. Envir on. Health Perspect. 111: 942-946. 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]. Wright, R. J.; Subramanian, S. V. (2007) Advancing a multilevel framework for epidemiologic research on asthma disparities. Chest 132: 757-769. Wu, Y -C.; Batterman S. (2006) Proximity of schools in Detroit, Michigan to automobile and truck traffic. J. Exposure Sci. Environ. Epidemiol. 10: 1038. Yamanaka, S. (1984) Decay rates of nitrogen oxides in a typical Japanese living room. Environ. Sci. Technol. 18: 566-570. Yanagisawa, Y.; Nishimura, H. (1982) A badge-typ e personal sampler for measurement of personal exposure to NO 2 and NO in ambient air. Environ. Int. 8: 235-242. Yang, C. Y.; Chen, C. C.; Chen, C. Y.; Kuo, H. W. (2007) Air pollution and hospital admissions for asthma in a subtropical city: Taipei, Taiwan. J. Toxicol. Environ. Health A. 70: 111-117. Yang, C. Y.; Chen, C. J. (2007) Air pollution and hospital admissions for chronic obstructive pulmonary disease in a subtropical city: Taipei, Taiwan. J. Toxicol. Environ. Health A. 70: 1214-1219. Yang, C.-Y.; Chen, Y.-S.; Yang, C.-H.; Ho, S.-C. (2004a) Relationship between ambient air pollution and hospital admissions for cardiovascular diseases in Kaohs iung, Taiwan. J. Toxicol. Environ. Health Part A 67: 483-493. Yang, Q.; Chen, Y.; Krewski, D.; Burnett, R. T.; Shi, Y.; McGrail, K. M. (2005) Effect of short-term exposure to low levels of gaseous pollu tants on chronic obstructive pulmonary disease hospitalizations. Environ. Res. 99: 99-105. Yang, Q.; Chen, Y.; Shi, Y.; Burnett, R. T.; McGra il, K. M.; Krewski, D. (2003) Association between ozone and respiratory admissions among children a nd the elderly in Vancouve r, Canada. Inhalation Toxicol. 15: 1297-1308. Yang, W.; Lee, K.; Chung, M. (2004b) Characterization of indoor air quality using multiple measurements of nitrogen dioxide. Indoor Air 14: 105-111. Zanobetti, A.; Schwartz, J. (2001) Are diabetics more susceptible to the health effects of airborne particles? Am J Respir Crit Care Med. 164: 831-3. Zanobetti, A.; Schwartz, J. (2002) Cardiovascular dama ge by airborne particles: are diabetics more susceptible? Epidemiology. 13: 588-92. Zanobetti, A.; Schwartz, J. (2006) Air pollution and em ergency admissions in Boston, MA. J. Epidemiol. Community Health 60: 890-895. Zanobetti, A.; Schwartz, J.; Gold, D. (2000) Are ther e sensitive subgroups for the effects of airborne particles? Environ Health Perspect. 108: 841-5. Zeger, S. L.; Thomas, D.; Dominici, F.; Samet, J. M.; Schwartz, J.; Dockery, D.; Cohen, A. (2000) Exposure measurement error in time-series studies of air pollution: concepts and consequences. Environ. Health Perspect. 108: 419-26.51 Zeger, S. L.; Thomas, D.; Dominici, F.; Samet, J. M.; Schwartz, J.; Dockery, D.; Cohen, A. (2000) Exposure measurement error in time-series studies of air pollution: concepts and consequences. Environ. Health Perspect. 108: 419-26. Zielinska, B.; Arey, J.; Atkinson, R.; Winer, A. M. (1989) The nitroarenes of molecular weight 247 in ambient particulate samples collected in southern California. Atmos. Environ. 23: 223-229. Zielinska, B.; Sagebiel, J.; McDonald, J. D.; Wh itney, K.; Lawson, D. R. (2004) Emission rates and comparative chemical composition from selected in-u se diesel and gasoline-fueled vehicles. J. Air Waste Manage. Assoc. 54: 1138-1150. Zipprich, J. L.; Harris, S. A.; Fox, J. C.; Borzelleca, J. F. (2002) An analysis of factors that influence personal exposure to nitrogen oxides in resident s of Richmond, Virginia. J. Exposure Anal. Environ. Epidemiol. 12: 273-285. Zmirou, D.; Schwartz, J.; Saez, M.; Zanobetti, A.; Wojtyniak, B.; Touloumi, G.; Spix, C.; Ponce de Leon, A.; Le Moullec, Y.; Bacharova, L.; Schouten, J.; Ponka, A.; Katsouyanni, K. (1998) Time-series analysis of air pollution and cause-specific mortality. Epidemiology. 9: 495-503. Zota, A.; Adamkiewicz, G.; Levy, J. I.; Spengler, J. D. (2005) Ventilation in public housing: implications for indoor nitrogen dioxide concen trations. Indoor Air 15: 393-401.