December 2009 i 

December 2009 

EPA/600/R-08/139F

Integrated Science Assessment for 

Particulate Matter 

Includes Errata Sheet created on 2/10/2010 

National Center for Environmental Assessment-RTP Division 

Office of Research and Development 

U.S. Environmental Protection Agency 

Research Triangle Park, NC 
December 2009 ii 

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. 
December 2009 iii 

Errata Sheet Created 2/10/2010 

for the document titled 

Integrated Science Assessment for Particulate Matter, December 2009, Final 

Table or 

Figure Page Erratum 

 iv-v Table of contents for Chapter 2 updated to correct page numbers. 

xv, xxiii Page numbers for Chapter 2 figures and tables corrected. 

2-9 Replaced reference to “Table 6-14” in the text with “Table 6-15” 

2-10 Replaced reference to “Table 6-14” in the text with “Table 6-15” 

2-11 Replaced reference to “Table 6-14” in the text with “Table 6-15” 

 2-12 Replaced the reference to “Figure 7-8” in the text with “Figure 7-

7” (cited 3 times) 

Figure 2-2 2-15 

Mean concentration for Laden et al. (2006, 087605) corrected 

from 14.8 to 16.4. Deleted “conducted in locations where the 

mean annual PM2.5 concentrations were <17 μg/m3 ” in caption. 

 2-17 Replaced reference to “Table 6-17” in the text with “Table 6-18” 

Figure 6-4 6-72 Figure replaced. Lisabeth et al. (2008, 155939) correctly moved to 

PM2.5 study group. 

Figure 6-15 6-148 Updated HERO ID numbers. 

Figure 7-6 7-85 PM2.5 concentrations for Laden et al. (2006, 087605) corrected 

from 17.6 to 16.4
December 2009 iv 

Table of Contents 

LIST OF TABLES ________________________________________________________ XV

LIST OF FIGURES _______________________________________________________ XXIII

PM ISA PROJECT TEAM _________________________________________________ XLIII

AUTHORS, CONTRIBUTORS, REVIEWERS______________________________________ XLVI

CLEAN AIR SCIENTIFIC ADVISORY COMMITTEE FOR PARTICULATE MATTER NAAQS ______ LII

ACRONYMS AND ABBREVIATIONS ____________________________________________ LIV

CHAPTER 1. INTRODUCTION _______________________________________________ 1-2

1.1. Legislative Requirements _______________________________________________________16958H1-4

1H1.2. History of Reviews of the NAAQS for PM __________________________________________1695H1-5

12H1.3. ISA Development _____________________________________________________________1690H1-9

13H1.4. Document Organization _______________________________________________________169H1-13

14H1.5. EPA Framework for Causal Determination_________________________________________1692H1-14

15H1.5.1. Scientific Evidence Used in Establishing Causality____________________________1693H1-15

16H1.5.2. Association and Causation ______________________________________________1694H1-15

17H1.5.3. Evaluating Evidence for Inferring Causation _________________________________1695H1-15

18H1.5.4. Application of Framework for Causal Determination___________________________169H1-19

19H1.5.5. First Step—Determination of Causality _____________________________________1697H1-20 20H1.5.6. Second Step—Evaluation of Response ____________________________________1698H1-22

21H1.5.6.1. Effects on Human Populations ____________________________________169H1-22

2H1.5.6.2. Effects on Public Welfare ________________________________________16970H1-24

23H1.5.7. Concepts in Evaluating Adversity of Health Effects____________________________1697H1-24

24H1.6. Summary __________________________________________________________________16972H1-24

25HChapter 1 References ____________________________________________________________16973H1-26

26HCHAPTER 2. INTEGRATIVE HEALTH AND WELFARE EFFECTS OVERVIEW _______________ 16974H2-1

27H2.1. Concentrations and Sources of Atmospheric PM_____________________________________16975H2-2

28H2.1.1. Ambient PM Variability and Correlations _____________________________________1697H2-2

29H2.1.1.1. Spatial Variability across the U.S. __________________________________1697H2-2

30H2.1.1.2. Spatial Variability on the Urban and Neighborhood Scales _______________16978H2-3

31H2.1.2. Trends and Temporal Variability ___________________________________________1697H2-3

32H2.1.3. Correlations between Copollutants _________________________________________16980H2-4

3H2.1.4. Measurement Techniques ________________________________________________1698H2-4

34H2.1.5. PM Formation in the Atmosphere and Removal _______________________________16982H2-4 35H2.1.6. Source Contributions to PM ______________________________________________16983H2-5

36H2.1.7. Policy-Relevant Background ______________________________________________16984H2-6

37H2.2. Human Exposure _____________________________________________________________16985H2-6

38H2.2.1. Spatial Scales of PM Exposure Assessment__________________________________1698H2-6

39H2.2.2. Exposure to PM Components and Copollutants _______________________________16987H2-7

40H2.2.3. Implications for Epidemiologic Studies ______________________________________1698H2-7
December 2009 v 

2.3. Health Effects ________________________________________________________________2-8

42H2.3.1. Exposure to PM2.5 ______________________________________________________1690H2-9

43H2.3.1.1. Effects of Short-Term Exposure to PM2.5 _____________________________169H2-9 4H2.3.1.2. Effects of Long-Term Exposure to PM2.5 ____________________________1692H2-11

45H2.3.2. Integration of PM2.5 Health Effects_________________________________________1693H2-13

46H2.3.3. Exposure to PM10-2.5 ___________________________________________________1694H2-18

47H2.3.3.1. Effects of Short-Term Exposure to PM10-2.5 __________________________1695H2-18

48H2.3.4. Integration of PM10-2.5 Effects_____________________________________________169H2-19

49H2.3.5. Exposure to UFPs _____________________________________________________1697H2-21

50H2.3.5.1. Effects of Short-Term Exposure to UFPs____________________________1698H2-21

51H2.3.6. Integration of UFP Effects _______________________________________________169H2-22

52H2.4. Policy Relevant Considerations _________________________________________________170H2-23

53H2.4.1. Potentially Susceptible Populations _______________________________________170H2-23

54H2.4.2. Lag Structure of PM-Morbidity and PM-Mortality Associations ___________________1702H2-24

5H2.4.2.1. PM-Cardiovascular Morbidity Associations __________________________1703H2-24 56H2.4.2.2. PM-Respiratory Morbidity Associations _____________________________1704H2-24 57H2.4.2.3. PM-Mortality Associations _______________________________________1705H2-25

58H2.4.3. PM Concentration-Response Relationship __________________________________1706H2-25

59H2.4.4. PM Sources and Constituents Linked to Health Effects ________________________170H2-26

60H2.5. Welfare Effects ______________________________________________________________1708H2-27

61H2.5.1. Summary of Effects on Visibility __________________________________________1709H2-27

62H2.5.2. Summary of Effects on Climate___________________________________________170H2-28

63H2.5.3. Summary of Ecological Effects of PM ______________________________________170H2-29

64H2.5.4. Summary of Effects on Materials__________________________________________1702H2-30

65H2.6. Summary of Health Effects and Welfare Effects Causal Determinations__________________1703H2-31

6HChapter 2 References ____________________________________________________________1704H2-34

67HCHAPTER 3. SOURCE TO HUMAN EXPOSURE ___________________________________ 1705H3-1

68H3.1. Introduction__________________________________________________________________1706H3-1

69H3.2. Overview of Basic Aerosol Properties _____________________________________________170H3-1

70H3.3. Sources, Emissions and Deposition of Primary and Secondary PM ______________________1708H3-6

71H3.3.1. Emissions of Primary PM and Precursors to Secondary PM _____________________1709H3-8

72H3.3.2. Formation of Secondary PM _____________________________________________1702H3-10

73H3.3.2.1. Formation of Nitrate and Sulfate __________________________________1702H3-10

74H3.3.2.2. Formation of Secondary Organic Aerosol ___________________________1702H3-10 75H3.3.2.3. Formation of New Particles ______________________________________17023H3-12

76H3.3.3. Mobile Source Emissions _______________________________________________17024H3-13

7H3.3.3.1. Emissions from Gasoline Fueled Engines ___________________________17025H3-13

78H3.3.3.2. Emissions from Diesel Fueled Engines _____________________________17026H3-13

79H3.3.4. Deposition of PM ______________________________________________________1702H3-14

80H3.3.4.1. Deposition Forms ______________________________________________17028H3-16

81H3.3.4.2. Methods for Estimating Dry Deposition _____________________________17029H3-17

82H3.3.4.3. Factors Affecting Dry Deposition Rates and Totals ____________________1703H3-18

83H3.4. Monitoring of PM ____________________________________________________________1703H3-20

84H3.4.1. Ambient Measurement Techniques ________________________________________17032H3-20

85H3.4.1.1. PM Mass_____________________________________________________1703H3-20

86H3.4.1.2. PM Speciation ________________________________________________17034H3-23

87H3.4.1.3. Multiple-Component Measurements on Individual Particles _____________17035H3-28

8H3.4.1.4. UFPs: Mass, Surface Area, and Number____________________________17036H3-29

89H3.4.1.5. PM Size Distribution ____________________________________________1703H3-29

90H3.4.1.6. Satellite Measurement __________________________________________17038H3-29

91H3.4.2. Ambient Network Design________________________________________________17039H3-30

92H3.4.2.1. Monitor Siting Requirements _____________________________________1704H3-30

93H3.4.2.2. Spatial and Temporal Coverage___________________________________1704H3-31
December 2009 vi 

94H3.4.2.3. Network Application for Exposure Assessment with Respect to 

Susceptible Populations _________________________________________17042H3-36

95H3.5. Ambient PM Concentrations____________________________________________________17043H3-40

96H3.5.1. Spatial Distribution_____________________________________________________1704H3-41 97H3.5.1.1. Variability across the U.S. _______________________________________17045H3-42

98H3.5.1.2. Urban-Scale Variability__________________________________________17046H3-60

9H3.5.1.3. Neighborhood-Scale Variability ___________________________________1704H3-85

10H3.5.2. Temporal Variability ____________________________________________________17048H3-91

10H3.5.2.1. Regional Trends _______________________________________________17049H3-91

102H3.5.2.2. Seasonal Variations ____________________________________________1705H3-96

103H3.5.2.3. Hourly Variability_______________________________________________1705H3-97

104H3.5.3. Statistical Associations with Copollutants __________________________________17052H3-100

105H3.6. Mathematical Modeling of PM _________________________________________________17053H3-104

106H3.6.1. Estimating Source Contributions to PM Using Receptor Models ________________17054H3-104

107H3.6.1.1. Receptor Models _____________________________________________1705H3-104

108H3.6.2. Chemistry Transport Models ____________________________________________17056H3-109 109H3.6.2.1. Global Scale _________________________________________________1705H3-111

10H3.6.2.2. Regional Scale _______________________________________________17058H3-111

1H3.6.2.3. Local or Neighborhood Scale ____________________________________17059H3-113

12H3.6.3. Air Quality Model Evaluation for Air Concentrations __________________________1706H3-113

13H3.6.3.1. Ground-based Comparisons of Photochemical Dynamics______________1706H3-120

14H3.6.3.2. Predicted Chemistry for Nitrates and Related Compounds _____________17062H3-120

15H3.6.4. Evaluating Concentrations and Deposition of PM Components with CTMs ________17063H3-126

16H3.6.4.1. Global CTM Performance_______________________________________17064H3-126

17H3.6.4.2. Regional CTM Performance_____________________________________17065H3-127

18H3.7. Background PM ____________________________________________________________1706H3-139

19H3.7.1. Contributors to PRB Concentrations of PM_________________________________1706H3-139

120H3.7.1.1. Estimates of PRB Concentrations in Previous Assessments____________17068H3-140

12H3.7.1.2. Chemistry Transport Models for Predicting PRB Concentrations ________17069H3-142

12H3.8. Issues in Exposure Assessment for PM and its Components _________________________170H3-152

123H3.8.1. General Exposure Concepts ____________________________________________170H3-153

124H3.8.2. Personal and Microenvironmental Exposure Monitoring_______________________1702H3-155

125H3.8.2.1. New Developments in Personal Exposure Monitoring Instrumentation____1703H3-155

126H3.8.2.2. New Developments in Microenvironmental Exposure Monitoring 

Instrumentation_______________________________________________1704H3-156

127H3.8.3. Exposure Modeling ___________________________________________________1705H3-157

128H3.8.3.1. Time-Weighted Microenvironmental Models ________________________1706H3-157 129H3.8.3.2. Stochastic Population Exposure Models ___________________________170H3-158

130H3.8.3.3. Dispersion Models ____________________________________________1708H3-160

13H3.8.3.4. Land Use Regression and GIS-Based Models ______________________1709H3-160

132H3.8.4. Exposure Assessment Studies __________________________________________1708H3-162

13H3.8.4.1. Micro-to-Neighborhood Scale Ambient PM Exposure _________________1708H3-162

134H3.8.4.2. Ambient PM Exposure Estimates from Central Site Monitoring Data _____17082H3-165

135H3.8.4.3. Infiltration ___________________________________________________17083H3-168

136H3.8.5. Multicomponent and Multipollutant PM Exposures ___________________________17084H3-170

137H3.8.5.1. Exposure Issues Related to PM Composition _______________________17085H3-170

138H3.8.5.2. Exposure to PM and Copollutants ________________________________17086H3-175

139H3.8.6. Implications of Exposure Assessment Issues for Interpretation of Epidemiologic 

Studies_____________________________________________________________1708H3-176

140H3.8.6.1. Measurement Error____________________________________________1708H3-176

14H3.8.6.2. Model-Related Errors __________________________________________17089H3-177

142H3.8.6.3. Spatial Variability _____________________________________________1709H3-179

143H3.8.6.4. Temporal Variability ___________________________________________1709H3-181

14H3.8.6.5. Use of Surrogates for PM Exposure_______________________________17092H3-183

145H3.8.6.6. Compositional Differences ______________________________________17093H3-184 146H3.8.6.7. Conclusions _________________________________________________17094H3-184
December 2009 vii 

147H3.9. Summary and Conclusions ___________________________________________________17095H3-185

148H3.9.1. Concentrations and Sources of Atmospheric PM ____________________________17096H3-185

149H3.9.1.1. PM Source Characteristics______________________________________1709H3-185 150H3.9.1.2. Measurement Techniques ______________________________________17098H3-185

15H3.9.1.3. Ambient PM Variability and Correlations ___________________________1709H3-186

152H3.9.1.4. Temporal Variability ___________________________________________170H3-187

153H3.9.1.5. Correlations between Copollutants _______________________________170H3-188

154H3.9.1.6. Source Contributions to PM _____________________________________1702H3-188

15H3.9.1.7. Policy-Relevant Background ____________________________________1703H3-189

156H3.9.2. Human Exposure_____________________________________________________1704H3-189

157H3.9.2.1. Characterizing Human Exposure _________________________________1705H3-189

158H3.9.2.2. Spatial Scales of PM Exposure Assessment ________________________1706H3-190

159H3.9.2.3. Multicomponent and Multipollutant PM Exposures ___________________170H3-191

160H3.9.2.4. Implications for Epidemiologic Studies_____________________________1708H3-191

16HChapter 3 References ___________________________________________________________1709H3-193

162HCHAPTER 4. DOSIMETRY __________________________________________________ 170H4-1

163H4.1. Introduction__________________________________________________________________17H4-1

164H4.1.1. Size Characterization of Inhaled Particles____________________________________172H4-2

165H4.1.2. Structure of the Respiratory Tract __________________________________________173H4-3

16H4.2. Particle Deposition ____________________________________________________________174H4-5

167H4.2.1. Mechanisms of Deposition _______________________________________________175H4-6

168H4.2.2. Deposition Patterns _____________________________________________________176H4-7

169H4.2.2.1. Total Respiratory Tract Deposition__________________________________17H4-8

170H4.2.2.2. Extrathoracic Region ____________________________________________178H4-9

17H4.2.2.3. Tracheobronchial and Alveolar Region _____________________________179H4-10 172H4.2.2.4. Localized Deposition Sites _______________________________________1720H4-10

173H4.2.3. Interspecies Patterns of Deposition________________________________________172H4-11

174H4.2.4. Biological Factors Modulating Deposition ___________________________________172H4-11

175H4.2.4.1. Physical Activity _______________________________________________1723H4-12

176H4.2.4.2. Age _________________________________________________________1724H4-13

17H4.2.4.3. Gender ______________________________________________________1725H4-14 178H4.2.4.4. Anatomical Variability ___________________________________________1726H4-14

179H4.2.4.5. Respiratory Tract Disease _______________________________________172H4-15

180H4.2.4.6. Hygroscopicity of Aerosols _______________________________________1728H4-16

18H4.2.5. Summary ____________________________________________________________1729H4-16

182H4.3. Clearance of Poorly Soluble Particles ____________________________________________1730H4-17

183H4.3.1. Clearance Mechanisms and Kinetics ______________________________________173H4-17 184H4.3.1.1. Extrathoracic Region ___________________________________________1732H4-17

185H4.3.1.2. Tracheobronchial Region ________________________________________173H4-18

186H4.3.1.3. Alveolar Region _______________________________________________1734H4-19

187H4.3.2. Interspecies Patterns of Clearance and Retention ____________________________1735H4-19

18H4.3.3. Particle Translocation __________________________________________________1736H4-20

189H4.3.3.1. Alveolar Region _______________________________________________173H4-21

190H4.3.3.2. Olfactory Region_______________________________________________1738H4-22

19H4.3.4. Factors Modulating Clearance ___________________________________________1739H4-23

192H4.3.4.1. Age _________________________________________________________1740H4-23

193H4.3.4.2. Gender ______________________________________________________174H4-24

194H4.3.4.3. Respiratory Tract Disease _______________________________________1742H4-24

195H4.3.4.4. Particle Overload ______________________________________________1743H4-25

196H4.3.5. Summary ____________________________________________________________174H4-25

197H4.4. Clearance of Soluble Materials _________________________________________________1745H4-26

198H4.4.1. Clearance Mechanisms and Kinetics ______________________________________1746H4-26

19H4.4.2. Factors Modulating Clearance ___________________________________________174H4-27

20H4.4.2.1. Age _________________________________________________________1748H4-28
December 2009 viii 

201H4.4.2.2. Physical Activity _______________________________________________1749H4-28

20H4.4.2.3. Disease______________________________________________________1750H4-28

203H4.4.2.4. Concurrent Exposures __________________________________________175H4-29 204H4.4.3. Summary ____________________________________________________________1752H4-29

205HChapter 4 References ____________________________________________________________1753H4-30

206HCHAPTER 5. POSSIBLE PATHWAYS/ MODES OF ACTION ___________________________ 1754H5-1

207H5.1. Pulmonary Effects ____________________________________________________________175H5-1

208H5.1.1. Reactive Oxygen Species ________________________________________________1756H5-1

209H5.1.2. Activation of Cell Signaling Pathways _______________________________________175H5-3

210H5.1.3. Pulmonary Inflammation _________________________________________________1758H5-4

21H5.1.4. Respiratory Tract Barrier Function _________________________________________1759H5-6

21H5.1.5. Antioxidant Defenses and Adaptive Responses _______________________________1760H5-6

213H5.1.6. Pulmonary Function_____________________________________________________176H5-7 214H5.1.7. Allergic Disorders ______________________________________________________1762H5-8

215H5.1.8. Impaired Lung Defense Mechanisms _______________________________________1763H5-8

216H5.1.9. Resolution of Inflammation/Progression or Exacerbation of Disease _______________1764H5-8

217H5.1.9.1. Factors Affecting the Retention of PM _______________________________1765H5-9

218H5.1.9.2. Factors Affecting the Balance of Pro/Anti-Inflammatory Mediators, 

Oxidants/Anti-Oxidants and Proteases/Anti-Proteases __________________176H5-9

219H5.1.9.3. Pre-Existing Disease ___________________________________________176H5-10

20H5.1.10. Pulmonary DNA Damage _______________________________________________1768H5-10

21H5.1.11. Epigenetic Changes ___________________________________________________1769H5-10

2H5.1.12. Lung Development ____________________________________________________170H5-11

23H5.2. Systemic Inflammation ________________________________________________________17H5-12

24H5.2.1. Endothelial Dysfunction and Altered Vasoreactivity ___________________________172H5-13 25H5.2.2. Activation of Coagulation and Acute Phase Response_________________________173H5-14

26H5.2.3. Atherosclerosis _______________________________________________________174H5-15

27H5.3. Activation of the Autonomic Nervous System by Pulmonary Reflexes ___________________175H5-16

28H5.4. Translocation of UFPs or Soluble PM Components__________________________________176H5-17

29H5.5. Disease of the Cardiovascular and Other Organ Systems ____________________________17H5-18

230H5.6. Acute and Chronic Responses__________________________________________________178H5-19

231H5.7. Results of New Inhalation Studies which Contribute to Modes of Action__________________179H5-19

23H5.8. Gaps in Knowledge __________________________________________________________1780H5-22

23HChapter 5 References ____________________________________________________________178H5-23

234HCHAPTER 6. INTEGRATED HEALTH EFFECTS OF SHORT-TERM PM EXPOSURE ___________ 1782H6-1

235H6.1. Introduction__________________________________________________________________1783H6-1

236H6.2. Cardiovascular and Systemic Effects______________________________________________1784H6-2

237H6.2.1. Heart Rate and Heart Rate Variability _______________________________________1785H6-2

238H6.2.1.1. Epidemiologic Studies ___________________________________________1786H6-2

239H6.2.1.2. Controlled Human Exposure Studies ________________________________178H6-8

240H6.2.1.3. Toxicological Studies ___________________________________________178H6-10

241H6.2.2. Arrhythmia ___________________________________________________________1789H6-13

24H6.2.2.1. Epidemiologic Studies __________________________________________1790H6-13 243H6.2.2.2. Toxicological Studies ___________________________________________179H6-18

24H6.2.3. Ischemia ____________________________________________________________1792H6-20

245H6.2.3.1. Epidemiologic Studies __________________________________________1793H6-20 246H6.2.3.2. Controlled Human Exposure Studies _______________________________1794H6-22

247H6.2.3.3. Toxicological Studies ___________________________________________1795H6-23

248H6.2.4. Vasomotor Function____________________________________________________1796H6-24
December 2009 ix 

249H6.2.4.1. Epidemiologic Studies __________________________________________179H6-24

250H6.2.4.2. Controlled Human Exposure Studies _______________________________1798H6-26

251H6.2.4.3. Toxicological Studies ___________________________________________179H6-29 25H6.2.5. Blood Pressure _______________________________________________________1720H6-33

253H6.2.5.1. Epidemiologic Studies __________________________________________1720H6-33

254H6.2.5.2. Controlled Human Exposure Studies _______________________________1720H6-36

25H6.2.5.3. Toxicological Studies ___________________________________________17203H6-37

256H6.2.6. Cardiac Contractility ___________________________________________________17204H6-38

257H6.2.6.1. Toxicological Studies ___________________________________________17205H6-38

258H6.2.7. Systemic Inflammation _________________________________________________17206H6-39

259H6.2.7.1. Epidemiologic Studies __________________________________________1720H6-40

260H6.2.7.2. Controlled Human Exposure Studies _______________________________17208H6-44

261H6.2.7.3. Toxicological Studies ___________________________________________17209H6-46

26H6.2.8. Hemostasis, Thrombosis and Coagulation Factors____________________________1720H6-47

263H6.2.8.1. Epidemiologic Studies __________________________________________172H6-47

264H6.2.8.2. Controlled Human Exposure Studies _______________________________172H6-48 265H6.2.8.3. Toxicological Studies ___________________________________________1723H6-50

26H6.2.9. Systemic and Cardiovascular Oxidative Stress_______________________________1724H6-52

267H6.2.9.1. Epidemiologic Studies __________________________________________1725H6-52

268H6.2.9.2. Controlled Human Exposure Studies _______________________________1726H6-53

269H6.2.9.3. Toxicological Studies ___________________________________________172H6-54

270H6.2.10. Hospital Admissions and Emergency Department Visits________________________1728H6-56 271H6.2.10.1. All Cardiovascular Disease ______________________________________1729H6-60

27H6.2.10.2. Cardiac Diseases ______________________________________________1720H6-64

273H6.2.10.3. Ischemic Heart Disease _________________________________________172H6-64

274H6.2.10.4. Acute Myocardial Infarction ______________________________________172H6-67

275H6.2.10.5. Congestive Heart Failure ________________________________________1723H6-68

276H6.2.10.6. Cardiac Arrhythmias____________________________________________1724H6-69 27H6.2.10.7. Cerebrovascular Disease ________________________________________1725H6-70

278H6.2.10.8. Peripheral Vascular Disease _____________________________________1726H6-72

279H6.2.10.9. Copollutant Models_____________________________________________172H6-72

280H6.2.10.10. Concentration Response _____________________________________1728H6-75

281H6.2.10.11. Out of Hospital Cardiac Arrest _________________________________1729H6-76

28H6.2.11. Cardiovascular Mortality ________________________________________________17230H6-77 283H6.2.12. Summary and Causal Determinations______________________________________1723H6-78

284H6.2.12.1. PM2.5 ________________________________________________________1723H6-78

285H6.2.12.2. PM10-2.5 ______________________________________________________1723H6-81

286H6.2.12.3. UFPs________________________________________________________17234H6-83

287H6.3. Respiratory Effects ___________________________________________________________17235H6-84

28H6.3.1. Respiratory Symptoms and Medication Use _________________________________17236H6-84 289H6.3.1.1. Epidemiologic Studies __________________________________________1723H6-84

290H6.3.1.2. Controlled Human Exposure Studies _______________________________17238H6-93

291H6.3.2. Pulmonary Function____________________________________________________17239H6-94

29H6.3.2.1. Epidemiologic Studies __________________________________________17240H6-95

293H6.3.2.2. Controlled Human Exposure Studies _______________________________1724H6-98

294H6.3.2.3. Toxicological Studies ___________________________________________1724H6-99

295H6.3.3. Pulmonary Inflammation _______________________________________________17243H6-101

296H6.3.3.1. Epidemiologic Studies _________________________________________1724H6-101

297H6.3.3.2. Controlled Human Exposure Studies ______________________________17245H6-104

298H6.3.3.3. Toxicological Studies __________________________________________17246H6-106

29H6.3.4. Pulmonary Oxidative Responses ________________________________________1724H6-110

30H6.3.4.1. Controlled Human Exposure Studies ______________________________17248H6-111

301H6.3.4.2. Toxicological Studies __________________________________________17249H6-112

302H6.3.5. Pulmonary Injury _____________________________________________________17250H6-114

30H6.3.5.1. Epidemiologic Studies _________________________________________1725H6-114

304H6.3.5.2. Controlled Human Exposure Studies ______________________________1725H6-114

305H6.3.5.3. Toxicological Studies __________________________________________17253H6-115

306H6.3.6. Allergic Responses ___________________________________________________17254H6-122
December 2009 x 

307H6.3.6.1. Epidemiologic Studies _________________________________________1725H6-122

308H6.3.6.2. Controlled Human Exposure Studies ______________________________17256H6-122

309H6.3.6.3. Toxicological Studies __________________________________________1725H6-123 310H6.3.7. Host Defense________________________________________________________17258H6-129

31H6.3.7.1. Epidemiologic Studies _________________________________________17259H6-129

312H6.3.7.2. Toxicological Studies __________________________________________17260H6-129

31H6.3.8. Respiratory ED Visits, Hospital Admissions and Physician Visits ________________1726H6-132

314H6.3.8.1. All Respiratory Diseases _______________________________________1726H6-133

315H6.3.8.2. Asthma _____________________________________________________17263H6-137

316H6.3.8.3. Chronic Obstructive Pulmonary Disease ___________________________17264H6-142

317H6.3.8.4. Pneumonia and Respiratory Infections ____________________________17265H6-143

318H6.3.8.5. Copollutant Models____________________________________________1726H6-147

319H6.3.9. Respiratory Mortality __________________________________________________1726H6-149

320H6.3.10. Summary and Causal Determinations_____________________________________17268H6-149

321H6.3.10.1. PM2.5 _______________________________________________________17269H6-149

32H6.3.10.2. PM10-2.5 _____________________________________________________1720H6-152 32H6.3.10.3. UFPs_______________________________________________________172H6-153

324H6.4. Central Nervous System Effects _______________________________________________172H6-154

325H6.4.1. Epidemiologic Studies _________________________________________________1723H6-154

326H6.4.2. Controlled Human Exposure Studies _____________________________________1724H6-155

327H6.4.3. Toxicological Studies __________________________________________________1725H6-155

328H6.4.3.1. Urban Air ___________________________________________________1726H6-155 329H6.4.3.2. CAPs ______________________________________________________172H6-156

30H6.4.3.3. Diesel Exhaust _______________________________________________1728H6-156

31H6.4.3.4. Summary of Toxicological Study Findings of CNS Effects______________1729H6-157

32H6.4.4. Summary and Causal Determination _____________________________________17280H6-157

3H6.5. Mortality __________________________________________________________________1728H6-158

34H6.5.1. Summary of Findings from 2004 PM AQCD ________________________________1728H6-158

35H6.5.2. Associations of Mortality and Short-Term Exposure to PM _____________________17283H6-159

36H6.5.2.1. PM10 _______________________________________________________17284H6-160

37H6.5.2.2. PM2.5 _______________________________________________________17285H6-174

38H6.5.2.3. Thoracic Coarse Particles (PM10-2.5)_______________________________17286H6-184

39H6.5.2.4. Ultrafine Particles _____________________________________________1728H6-190

340H6.5.2.5. Chemical Components of PM____________________________________1728H6-191

341H6.5.2.6. Source-Apportioned PM Analyses ________________________________17289H6-196

342H6.5.2.7. Investigation of Concentration-Response Relationship ________________17290H6-197

34H6.5.3. Summary and Causal Determinations_____________________________________1729H6-200 34H6.5.3.1. PM2.5 _______________________________________________________1729H6-200

345H6.5.3.2. PM10-2.5 _____________________________________________________17293H6-201

346H6.5.3.3. UFPs_______________________________________________________17294H6-202

347H6.6. Attribution of Ambient PM Health Effects to Specific Constituents or Sources ____________17295H6-202

348H6.6.1. Evaluation Approach __________________________________________________17296H6-202 349H6.6.2. Findings ____________________________________________________________1729H6-203

350H6.6.2.1. Epidemiologic Studies _________________________________________17298H6-203

351H6.6.2.2. Controlled Human Exposure Studies ______________________________1729H6-206

352H6.6.2.3. Toxicological Studies __________________________________________1730H6-206

35H6.6.3. Summary by Health Effects _____________________________________________1730H6-210

354H6.6.4. Conclusion__________________________________________________________17302H6-211

35HChapter 6 References ___________________________________________________________1730H6-213

356HCHAPTER 7. INTEGRATED HEALTH EFFECTS OF LONG-TERM PM EXPOSURE____________ 17304H7-1

357H7.1. Introduction__________________________________________________________________17305H7-1

358H7.2. Cardiovascular and Systemic Effects______________________________________________17306H7-1 359H7.2.1. Atherosclerosis ________________________________________________________1730H7-2

360H7.2.1.1. Epidemiologic Studies ___________________________________________17308H7-2
December 2009 xi 

361H7.2.1.2. Toxicological Studies ____________________________________________17309H7-4

362H7.2.2. Venous Thromboembolism _______________________________________________1730H7-6

36H7.2.2.1. Epidemiologic Studies ___________________________________________173H7-7 364H7.2.3. Metabolic Syndromes ___________________________________________________1732H7-7

365H7.2.3.1. Epidemiologic Studies ___________________________________________173H7-7

36H7.2.3.2. Toxicological Studies ____________________________________________1734H7-7

367H7.2.4. Systemic Inflammation, Immune Function, and Blood Coagulation ________________1735H7-8

368H7.2.4.1. Epidemiologic Studies ___________________________________________1736H7-8

369H7.2.4.2. Toxicological Studies ____________________________________________173H7-8

370H7.2.5. Renal and Vascular Function______________________________________________1738H7-9

371H7.2.5.1. Epidemiologic Studies __________________________________________1739H7-10

372H7.2.5.2. Toxicological Studies ___________________________________________17320H7-11

37H7.2.6. Autonomic Function____________________________________________________1732H7-12

374H7.2.6.1. Toxicological Studies ___________________________________________1732H7-12

375H7.2.7. Cardiac changes ______________________________________________________1732H7-12

376H7.2.7.1. Toxicological studies ___________________________________________17324H7-12 37H7.2.8. Left Ventricular Mass and Function ________________________________________17325H7-13

378H7.2.9. Clinical Outcomes in Epidemiologic Studies _________________________________17326H7-13

379H7.2.10. Cardiovascular Mortality ________________________________________________1732H7-17

380H7.2.11. Summary and Causal Determinations______________________________________17328H7-18

381H7.2.11.1. PM2.5 ________________________________________________________17329H7-18

382H7.2.11.2. PM10-2.5 ______________________________________________________1730H7-19 38H7.2.11.3. UFPs________________________________________________________173H7-19

384H7.3. Respiratory Effects ___________________________________________________________1732H7-20

385H7.3.1. Respiratory Symptoms and Disease Incidence ______________________________173H7-20

386H7.3.1.1. Epidemiologic Studies __________________________________________1734H7-20

387H7.3.2. Pulmonary Function____________________________________________________1735H7-26

38H7.3.2.1. Epidemiologic Studies __________________________________________1736H7-26

389H7.3.2.2. Toxicological Studies ___________________________________________173H7-30

390H7.3.3. Pulmonary Inflammation ________________________________________________1738H7-32

391H7.3.3.1. Epidemiologic Studies __________________________________________1739H7-32

392H7.3.3.2. Toxicological Studies ___________________________________________17340H7-32

39H7.3.4. Pulmonary Oxidative Response __________________________________________1734H7-34

394H7.3.4.1. Toxicological Studies ___________________________________________17342H7-34

395H7.3.5. Pulmonary Injury ______________________________________________________1734H7-35

396H7.3.5.1. Toxicological Studies ___________________________________________1734H7-35

397H7.3.6. Allergic Responses ____________________________________________________17345H7-38 398H7.3.6.1. Epidemiologic Studies __________________________________________17346H7-38

39H7.3.6.2. Toxicological Studies ___________________________________________1734H7-39

40H7.3.7. Host Defense_________________________________________________________17348H7-40 401H7.3.7.1. Epidemiologic Studies __________________________________________17349H7-40

402H7.3.7.2. Toxicological Studies ___________________________________________17350H7-40

403H7.3.8. Respiratory Mortality ___________________________________________________1735H7-41

40H7.3.9. Summary and Causal Determinations______________________________________17352H7-42

405H7.3.9.1. PM2.5 ________________________________________________________1735H7-42

406H7.3.9.2. PM10-2.5 ______________________________________________________17354H7-43

407H7.3.9.3. UFPs________________________________________________________1735H7-44

408H7.4. Reproductive, Developmental, Prenatal and Neonatal Outcomes_______________________17356H7-44

409H7.4.1. Epidemiologic Studies __________________________________________________1735H7-44

410H7.4.1.1. Low Birth Weight ______________________________________________17358H7-45

41H7.4.1.2. Preterm Birth _________________________________________________17359H7-48

412H7.4.1.3. Growth Restriction _____________________________________________17360H7-51

413H7.4.1.4. Birth Defects __________________________________________________1736H7-52

41H7.4.1.5. Infant Mortality ________________________________________________17362H7-53

415H7.4.1.6. Decrements in Sperm Quality ____________________________________1736H7-58

416H7.4.2. Toxicological Studies ___________________________________________________17364H7-58

417H7.4.2.1. Female Reproductive Effects _____________________________________17365H7-59
December 2009 xii 

418H7.4.2.2. Male Reproductive Effects _______________________________________1736H7-60

419H7.4.2.3. Multiple Generation Effects ______________________________________1736H7-62

420H7.4.2.4. Receptor Mediated Effects _______________________________________17368H7-63 421H7.4.2.5. Developmental Effects __________________________________________17369H7-63

42H7.4.3. Summary and Causal Determinations______________________________________1730H7-67

423H7.4.3.1. PM2.5 ________________________________________________________173H7-67

42H7.4.3.2. PM10-2.5 ______________________________________________________1732H7-68

425H7.4.3.3. UFPs________________________________________________________173H7-68

426H7.5. Cancer, Mutagenicity, and Genotoxicity ___________________________________________1734H7-68

427H7.5.1. Epidemiologic Studies __________________________________________________1735H7-69

428H7.5.1.1. Lung Cancer Mortality and Incidence_______________________________1736H7-70

429H7.5.1.2. Other Cancers ________________________________________________173H7-73

430H7.5.1.3. Markers of Exposure or Susceptibility ______________________________1738H7-73

431H7.5.2. Toxicological Studies ___________________________________________________1739H7-75

432H7.5.2.1. Mutagenesis and Genotoxicity ____________________________________17380H7-76 43H7.5.2.2. Carcinogenesis________________________________________________1738H7-79 43H7.5.2.3. Summary of Toxicological Studies _________________________________17382H7-80

435H7.5.3. Epigenetic Studies and Other Heritable DNA mutations ________________________1738H7-80

436H7.5.4. Summary and Causal Determinations______________________________________17384H7-81

437H7.5.4.1. PM2.5 ________________________________________________________17385H7-81

438H7.5.4.2. PM10-2.5 ______________________________________________________17386H7-82

439H7.5.4.3. UFPs________________________________________________________1738H7-82

40H7.6. Mortality ___________________________________________________________________1738H7-82

41H7.6.1. Recent Studies of Long-Term Exposure to PM and Mortality ____________________17389H7-84

42H7.6.2. Composition and Source-Oriented Analyses of PM ___________________________17390H7-89

43H7.6.3. Within-City Effects of PM Exposure________________________________________1739H7-90

4H7.6.4. Effects of Different Long-term Exposure Windows ____________________________17392H7-92

45H7.6.5. Summary and Causal Determinations______________________________________1739H7-95

46H7.6.5.1. PM2.5 ________________________________________________________17394H7-95

47H7.6.5.2. PM10-2.5 ______________________________________________________17395H7-97

48H7.6.5.3. UFPs________________________________________________________17396H7-97

49HChapter 7 References ____________________________________________________________1739H7-98

450HCHAPTER 8. POPULATIONS SUSCEPTIBLE TO PM-RELATED HEALTH EFFECTS ___________ 17398H8-1

451H8.1. Potentially Susceptible Populations _______________________________________________1739H8-3 452H8.1.1. Lifestage _____________________________________________________________1740H8-3

453H8.1.1.1. Older Adults ___________________________________________________1740H8-3

45H8.1.1.2. Children ______________________________________________________17402H8-5 45H8.1.2. Pregnancy and Developmental Effects ______________________________________17403H8-5

456H8.1.3. Gender_______________________________________________________________1740H8-6

457H8.1.4. Race/Ethnicity _________________________________________________________17405H8-7

458H8.1.5. Gene-Environment Interaction ____________________________________________17406H8-7

459H8.1.6. Pre-Existing Disease ____________________________________________________1740H8-9

460H8.1.6.1. Cardiovascular Diseases _________________________________________17408H8-9

461H8.1.6.2. Respiratory Illnesses ___________________________________________17409H8-12

462H8.1.6.3. Respiratory Contributions to Cardiovascular Effects ___________________1740H8-13

463H8.1.6.4. Diabetes and Obesity ___________________________________________174H8-13

46H8.1.7. Socioeconomic Status __________________________________________________1742H8-14

465H8.1.8. Summary ____________________________________________________________1743H8-15

46HChapter 8 References ____________________________________________________________174H8-17

467HCHAPTER 9. WELFARE EFFECTS ____________________________________________ 1745H9-1

468H9.1. Introduction__________________________________________________________________1746H9-1

469H9.2. Effects on Visibility ____________________________________________________________174H9-1
December 2009 xiii 

470H9.2.1. Introduction ___________________________________________________________1748H9-1

471H9.2.2. Background ___________________________________________________________1749H9-2

472H9.2.2.1. Non-PM Visibility Effects _________________________________________17420H9-5 473H9.2.2.2. PM Visibility Effects _____________________________________________1742H9-5

47H9.2.2.3. Direct Optical Measurements ______________________________________1742H9-8

475H9.2.2.4. Value of Good Visual Air Quality __________________________________17423H9-10

476H9.2.3. Monitoring and Assessment _____________________________________________1742H9-10

47H9.2.3.1. Aerosol Properties _____________________________________________17425H9-11

478H9.2.3.2. Spatial Patterns _______________________________________________17426H9-16

479H9.2.3.3. Urban and Regional Patterns _____________________________________1742H9-23

480H9.2.3.4. Temporal Trends ______________________________________________17428H9-31

481H9.2.3.5. Causes of Haze _______________________________________________17429H9-37

482H9.2.4. Urban Visibility Valuation and Preference ___________________________________17430H9-65

483H9.2.4.1. Urban Visibility Preference Studies ________________________________1743H9-67

48H9.2.4.2. Denver, Colorado Urban Visibility Preference Study ___________________17432H9-68

485H9.2.4.3. Phoenix, Arizona Urban Visibility Preference Study ___________________1743H9-69 486H9.2.4.4. British Columbia, Canada Urban Visibility Preference Study_____________1743H9-69

487H9.2.4.5. Washington, DC Urban Visibility Preference Studies___________________17435H9-69

48H9.2.4.6. Urban Visibility Valuation Studies__________________________________17436H9-71

489H9.2.5. Summary of Effects on Visibility __________________________________________1743H9-72

490H9.3. Effects on Climate ___________________________________________________________17438H9-74

491H9.3.1. The Climate Effects of Aerosols __________________________________________17439H9-74 492H9.3.2. Overview of Aerosol Measurement Capabilities ______________________________1740H9-82

493H9.3.2.1. Satellite Remote Sensing ________________________________________174H9-82

49H9.3.2.2. Focused Field Campaigns _______________________________________1742H9-88

495H9.3.2.3. Ground-Based In Situ Measurement Networks _______________________1743H9-89

496H9.3.2.4. In Situ Aerosol Profiling Programs _________________________________174H9-91

497H9.3.2.5. Ground-Based Remote Sensing Measurement Networks _______________1745H9-95

498H9.3.2.6. Synergy of Measurements and Model Simulations ____________________1746H9-96

49H9.3.3. Assessments of Aerosol Characterization and Climate Forcing __________________174H9-99

50H9.3.3.1. The Use of Measured Aerosol Properties to Improve Models ___________1748H9-100

501H9.3.3.2. Intercomparisons of Satellite Measurements and Model Simulation of 

Aerosol Optical Depth _________________________________________1749H9-103

502H9.3.3.3. Satellite-Based Estimates of Aerosol Direct Radiative Forcing __________17450H9-105

503H9.3.3.4. Satellite-Based Estimates of Anthropogenic Component of Aerosol 

Direct Radiative Forcing ________________________________________1745H9-111

504H9.3.3.5. Aerosol-Cloud Interactions and Indirect Forcing _____________________17452H9-112 50H9.3.3.6. Remote Sensing of Aerosol-Cloud Interactions and Indirect Forcing _____17453H9-113

506H9.3.3.7. In Situ Studies of Aerosol-Cloud Interactions________________________1745H9-116

507H9.3.4. Outstanding Issues ___________________________________________________1745H9-117 508H9.3.5. Concluding Remarks __________________________________________________17456H9-120

509H9.3.6. Modeling the Effect of Aerosols on Climate_________________________________1745H9-121

510H9.3.6.1. Introduction__________________________________________________17458H9-121

51H9.3.6.2. Modeling of Atmospheric Aerosols________________________________17459H9-124

512H9.3.6.3. Calculating Aerosol Direct Radiative Forcing________________________17460H9-129

513H9.3.6.4. Calculating Aerosol Indirect Forcing_______________________________1746H9-137

514H9.3.6.5. Aerosol in the Climate Models ___________________________________17462H9-145

51H9.3.6.6. Impacts of Aerosols on Climate Model Simulations ___________________17463H9-153

516H9.3.6.7. Outstanding Issues____________________________________________1746H9-157

517H9.3.6.8. Conclusions _________________________________________________17465H9-158

518H9.3.7. Fire as a Special Source of PM Welfare Effects _____________________________1746H9-159

519H9.3.8. Radiative Effects of Volcanic Aerosols ____________________________________1746H9-160

520H9.3.8.1. Explosive Volcanic Activity ______________________________________17468H9-160

521H9.3.9. Other Special Sources and Effects _______________________________________17469H9-164

52H9.3.9.1. Glaciers and Snowpack ________________________________________1740H9-167

523H9.3.9.2. Radiative Forcing by Anthropogenic Surface Albedo Change: BC in 

Snow and Ice ________________________________________________174H9-169

524H9.3.9.3. Effects on Local and Regional Climate ____________________________1742H9-170
December 2009 xiv 

52H9.3.10. Summary of Effects on Climate__________________________________________1743H9-171

526H9.4. Ecological Effects of PM______________________________________________________174H9-172

527H9.4.1. Introduction _________________________________________________________1745H9-172

528H9.4.1.1. Ecosystem Scale, Function, and Structure _________________________1746H9-173 529H9.4.1.2. Ecosystem Services ___________________________________________174H9-174

530H9.4.2. Deposition of PM _____________________________________________________1748H9-174

531H9.4.2.1. Forms of Deposition ___________________________________________1749H9-175

532H9.4.2.2. Components of PM Deposition___________________________________17480H9-175

53H9.4.2.3. Magnitude of Dry Deposition ____________________________________1748H9-179

534H9.4.3. Direct Effects of PM on Vegetation _______________________________________17482H9-182

53H9.4.3.1. Effects of Coarse-mode Particles_________________________________17483H9-182

536H9.4.4. PM and Altered Radiative Flux __________________________________________1748H9-183

537H9.4.5. Effects of Trace Metals on Ecosystems____________________________________17485H9-183

538H9.4.5.1. Effects on Soil Chemistry _______________________________________17486H9-185

539H9.4.5.2. Effects on Soil Microbes and Plant Uptake via Soil ___________________1748H9-186 540H9.4.5.3. Plant Response to Metals ______________________________________1748H9-189 541H9.4.5.4. Effects on Aquatic Ecosystems __________________________________17489H9-192

542H9.4.5.5. Effects on Animals ____________________________________________17490H9-192

543H9.4.5.6. Biomagnification across Trophic Levels____________________________1749H9-193

54H9.4.5.7. Effects near Smelters and Roadsides _____________________________17492H9-194

54H9.4.5.8. Toxicity to Mosses and Lichens __________________________________17493H9-196

546H9.4.6. Organic Compounds __________________________________________________1749H9-196 547H9.4.7. Summary of Ecological Effects of PM _____________________________________17495H9-199

548H9.5. Effects on Materials _________________________________________________________17496H9-201

549H9.5.1. Effects on Paint ______________________________________________________1749H9-202

50H9.5.2. Effects on Metal Surfaces ______________________________________________17498H9-202

51H9.5.3. Effects on Stone _____________________________________________________1749H9-203

52H9.5.4. Summary of Effects on Materials_________________________________________1750H9-203

53HChapter 9 References ___________________________________________________________1750H9-204

54HANNEX A. ATMOSPHERIC SCIENCE __________________________________________ 17502HA-1

5HAnnex A References ___________________________________________________________ 17503HA-353

56HANNEX B. DOSIMETRY ___________________________________________________ 17504HB-1

57HAnnex B References _____________________________________________________________ 1750HB-7

58HANNEX C. CONTROLLED HUMAN EXPOSURE STUDIES ____________________________ 17506HC-1

59HAnnex C References ____________________________________________________________ 1750HC-14

560HANNEX D. TOXICOLOGICAL STUDIES _________________________________________ 17508HD-1

561HAnnex D References ___________________________________________________________ 17509HD-172

562HANNEX E. EPIDEMIOLOGIC STUDIES _________________________________________ 1750HE-1

563HAnnex E References ___________________________________________________________ 175HE-524

564HANNEX F. SOURCE APPORTIONMENT STUDIES __________________________________ 1752HF-1

56HAnnex F References _____________________________________________________________1753HF-11
December 2009 xv 

List of Tables 

56HTable 1-1. Summary of NAAQS promulgated for PM, 1971-2006. ___________________________________________1754H1-6

567HTable 1-2. Aspects to aid in judging causality.__________________________________________________________175H1-20

568HTable 1-3. Weight of evidence for causal determination.__________________________________________________1756H1-22

569HTable 2-1. Summary of causal determinations for short-term exposure to PM2.5. ________________________________175H2-9

570HTable 2-2. Summary of causal determinations for long-term exposure to PM2.5. _______________________________1758H2-11

571HTable 2-3. Summary of causal determinations for short-term exposure to PM10-2.5. _____________________________1759H2-18

572HTable 2-4. Summary of causal determinations for short-term exposure to UFPs._______________________________17520H2-21

573HTable 2-5. Summary of causality determination for welfare effects. _________________________________________1752H2-27

574HTable 2-6. Summary of PM causal determinations by exposure duration and health outcome. ____________________1752H2-32

57HTable 2-7. Summary of PM causal determinations for welfare effects _______________________________________17523H2-33

576HTable 3-1. Characteristics of ambient fine (ultrafine plus accumulation-mode) and coarse particles._________________17524H3-4

57HTable 3-2. Constituents of atmospheric particles and their major sources._____________________________________1752H3-7

578HTable 3-3. Proximity to PM2.5 and PM10 monitors for total populationa by city.__________________________________17526H3-35

579HTable 3-4. Proximity to PM2.5 and PM10 monitors for children age 0-4 yr, children age 5-17 yr, and 

adults age 65 yr and older.a _______________________________________________________________1752H3-37

580HTable 3-5. Proximity to PM2.5 and PM10 monitors for adults age 65 yr and oldera by city. _________________________17528H3-38

581HTable 3-6. Proximity to PM2.5 and PM10 monitors based on the population identified as white, black, 

Hispanic, or non-Hispanic a. _______________________________________________________________17529H3-39

582HTable 3-7. Proximity to PM2.5 and PM10 monitors based on the population below or above the poverty 

line, population over age 25 with less than high school education, population over 25 with 

high school education, and population over 25 with college education or morea

. ______________________17530H3-40

583HTable 3-8. PM2.5 distributions derived from AQS data (concentration in μg/m3).________________________________1753H3-44

584HTable 3-9. PM10-2.5 distributions derived from AQS data (concentration in μg/m3). ______________________________17532H3-47

58HTable 3-10. PM10 distributions derived from AQS data (concentration in μg/m3). ________________________________1753H3-49

586HTable 3-11. Inter-sampler comparison statistics for each pair of 24-h PM2.5 monitors reporting to AQS 

for Boston, MA._________________________________________________________________________17534H3-63

587HTable 3-12. Inter-sampler comparison statistics for each pair of 24-h PM2.5 monitors reporting to AQS 

for Pittsburgh, PA. ______________________________________________________________________1753H3-67

58HTable 3-13. Inter-sampler comparison statistics for each pair of 24-h PM2.5 monitors reporting to AQS 

for Los Angeles, CA._____________________________________________________________________17536H3-69

589HTable 3-14. Inter-sampler comparison statistics for each pair of 24-h PM10 monitors reporting to AQS for 

Boston, MA. ___________________________________________________________________________1753H3-75

590HTable 3-15. Inter-sampler comparison statistics for each pair of 24-h PM10 monitors reporting to AQS for 

Pittsburgh, PA. _________________________________________________________________________17538H3-78

591HTable 3-16. Inter-sampler comparison statistics for each pair of 24-h PM10 monitors reporting to AQS for 

Los Angeles, CA. _______________________________________________________________________17539H3-81
December 2009 xvi 

592HTable 3-17. Example of emissions factors (ng/km) for trace elements under variable speed and steady 

speed driving conditions for PM emitted by diesel and gasoline engines. ___________________________17540H3-106

593HTable 3-18. Estimates of annual average natural background concentrations of PM2.5 and PM10 (μg/m3) 

from Trijonis et al. (1990, 157058)._________________________________________________________1754H3-140

594HTable 3-19. Annual and quarterly mean PM2.5 concentrations (μg/m3) measured at IMPROVE sites in 

2004.________________________________________________________________________________17542H3-142

59HTable 3-20. Annual and quarterly mean PM2.5 concentrations (μg/m3) for the CMAQ “base case” at 

IMPROVE sites in 2004._________________________________________________________________17543H3-150

596HTable 3-21. Annual and quarterly mean PM2.5 concentrations (μg/m3) for the CMAQ PRB simulations at 

IMPROVE sites in 2004._________________________________________________________________1754H3-151

597HTable 3-22. Annual and quarterly mean of the CMAQ-predicted base case PM2.5 concentrations (μg/m3) 

in the U.S. EPA CONUS regions in 2004. ___________________________________________________1754H3-151

598HTable 3-23. Annual and quarterly mean of the CMAQ-predicted PRB PM2.5 concentrations (μg/m3) in 

the U.S. EPA CONUS regions in 2004. _____________________________________________________17546H3-152

59HTable 3-24. Examples of studies comparing near-road personal exposures with fixed site ambient 

concentrations. ________________________________________________________________________1754H3-164

60HTable 4-1. Breathing patterns with activity level in adult human male. _______________________________________17548H4-12

601HTable 6-1. Characteristics of epidemiologic studies investigating associations between PM and 

changes in HRV._________________________________________________________________________17549H6-6

602HTable 6-2. Epidemiologic studies of ventricular arrhythmia and ambient PM concentration, in patients 

with implantable cardioverter defibrillators. ___________________________________________________1750H6-15

603HTable 6-3. PM Concentrations reported in epidemiologic studies ECG changes suggestive of 

ischemia. _____________________________________________________________________________175H6-22

604HTable 6-4. PM concentrations reported in epidemiologic studies of vasomotor function._________________________1752H6-26

605HTable 6-5. Mean PM concentrations reported in epidemiologic studies of blood pressure. _______________________1753H6-35

60HTable 6-6. PM concentrations reported in epidemiologic studies of inflammation, hemostasis, 

thrombosis, coagulation factors and oxidative stress. ___________________________________________1754H6-42

607HTable 6-7. Description of ICD-9 and ICD-10 codes for diseases of the circulatory system. _______________________175H6-57

608HTable 6-8. Characterization of ambient PM concentrations in epidemiologic studies of hospital 

admission and ED visits for cardiovascular diseases. ___________________________________________1756H6-63

609HTable 6-9. PM concentrations reported in studies of out-of-hospital cardiac arrest. _____________________________175H6-77

610HTable 6-10. Characterization of ambient PM concentrations from epidemiologic studies of respiratory 

morbidity and short-term exposures in asthmatic children and adults. ______________________________1758H6-87

61HTable 6-11. PAMCHAR PM10-2.5 inflammation results with ambient PM.______________________________________1759H6-119

612HTable 6-12. Other ambient PM – in vivo PM10-2.5 studies – BALF results, 18-24 h post-IT exposure.________________17560H6-119

613HTable 6-13. Description of ICD-9 and ICD-10 codes for diseases of the respiratory system. ______________________1756H6-133

614HTable 6-14. PM concentrations in epidemiologic studies of respiratory diseases. ______________________________17562H6-146

615HTable 6-15. Overview of U.S. and Canadian multicity PM studies of mortality analyzed in the 2004 PM 

AQCD and the PM ISAb

._________________________________________________________________17563H6-159

61HTable 6-16. NMMAPS national and regional percentage increase in all-cause, cardio-respiratory, and 

other-cause mortality associated with a 10 μg/m3

 increase in PM10 at lag 1 day for the 

periods 1987-1994, 1995-2000, and 1987-2000. ______________________________________________17564H6-163
December 2009 xvii 

617HTable 6-17. Effect modification of composition on the estimated percent increase in mortality with a 10 

μg/m3

 increase in PM2.5. _________________________________________________________________1756H6-194

618HTable 6-18. Study-specific PM2.5 factor/source categories associated with health effects. ________________________1756H6-207

619HTable 7-1. Characterization of ambient PM concentrations from studies of subclinical measures of 

cardiovascular diseases and long-term exposure. ______________________________________________1756H7-11

620HTable 7-2. Characterization of ambient PM concentrations from studies of clinical cardiovascular 

diseases and long-term exposure. __________________________________________________________17568H7-14

621HTable 7-3. Characterization of ambient PM concentrations from studies of respiratory 

symptoms/disease and long-term exposures. _________________________________________________17569H7-22

62HTable 7-4. Characterization of ambient PM concentrations from studies of FEV1 and long-term 

exposures. ____________________________________________________________________________1750H7-27

623HTable 7-5. Characterization of ambient PM concentrations from studies of reproductive, 

developmental, prenatal and neonatal outcomes and long-term exposure.___________________________175H7-46

624HTable 7-6. Characterization of ambient PM concentrations from recent studies of cancer and long-term 

exposures to PM. _______________________________________________________________________1752H7-70

625HTable 7-7. Associations* between ambient PM concentrations from select studies of lung cancer 

mortality and incidence. __________________________________________________________________1753H7-72

62HTable 7-8. Characterization of ambient PM concentrations from studies of mortality and long-term 

exposures to PM. _______________________________________________________________________1754H7-83

627HTable 7-9. Comparison of results from ACS intra-urban analysis of Los Angeles and New York City 

using kriging or land use regression to estimate exposure. _______________________________________175H7-91

628HTable 7-10. Distribution of the effect of a hypothetical reduction of 10 μg/m3 PM10 in 2000 on all-cause 

mortality 2000-2009 in Switzerland. _________________________________________________________1756H7-94

629HTable 8-1. Definitions of susceptible and vulnerable in the PM literature.______________________________________175H8-2

630HTable 8-2. Susceptibility factors evaluated. _____________________________________________________________1758H8-3

631HTable 8-3. Percent of the U.S. population with respiratory diseases, cardiovascular diseases, and 

diabetes. ______________________________________________________________________________1759H8-11

632HTable 9-1. Regional Planning Organization websites with visibility characterization and source 

attribution assessment information. _________________________________________________________17580H9-17

63HTable 9-2. Summary of urban visibility preference studies.________________________________________________1758H9-67

634HTable 9-3. Top-of-atmosphere, cloud-free, instantaneous direct aerosol radiative forcing dependence 

on aerosol and surface properties.__________________________________________________________17582H9-81

635HTable 9-4. Summary of major satellite measurements currently available for the tropospheric aerosol 

characterization and radiative forcing research.________________________________________________17583H9-83

63HTable 9-5. List of major intensive field experiments that are relevant to aerosol research in a variety of 

aerosol regimes around the globe conducted in the past two decades. _____________________________17584H9-93

637HTable 9-6. Summary of major U.S. surface in situ and remote sensing networks for the tropospheric 

aerosol characterization and radiative forcing research. _________________________________________1758H9-94

638HTable 9-7. Summary of approaches to estimating the aerosol direct radiative forcing in three 

categories: (1) satellite retrievals; (2) satellite-model integrations; and (3) model 

simulations.___________________________________________________________________________17586H9-106

639HTable 9-8. Summary of seasonal and annual average clear-sky DRF (W/m2) at the TOA and the 

surface (SFC) over global OCEAN derived with different methods and data. ________________________1758H9-109
December 2009 xviii 

640HTable 9-9. Summary of seasonal and annual average clear-sky DRF (W/m2) at the TOA and the 

surface (SFC) over global LAND derived with different methods and data.__________________________1758H9-110

641HTable 9-10. Estimates of anthropogenic components of aerosol optical depth (Tant) and clear-sky DRF 

at the TOA from model simulations. ________________________________________________________17589H9-112

642HTable 9-11. Anthropogenic emissions of aerosols and precursors for 2000 and 1750. __________________________17590H9-126

643HTable 9-12. Summary of statistics of AeroCom Experiment A results from 16 global models. _____________________1759H9-127

64HTable 9-13. SO4

2– mass loading, MEE and AOD at 550 nm, shortwave radiative forcing at the top of the 

atmosphere, and normalized forcing with respect to AOD and mass. ______________________________17592H9-131

645HTable 9-14. Particulate organic matter (POM) and BC mass loading, AOD at 550 nm, shortwave 

radiative forcing at the top of the atmosphere, and normalized forcing with respect to AOD 

and mass. ____________________________________________________________________________17593H9-132

64HTable 9-15. Differences in present day and pre-industrial outgoing solar radiation (W/m2) in the different 

experiments.__________________________________________________________________________17594H9-141

647HTable 9-16. Forcings used in IPCC AR4 simulations of 20th century climate change. ___________________________1759H9-145

648HTable 9-17. Climate forcings (1880-2003) used to drive GISS climate simulations, along with the 

surface air temperature changes obtained for several periods. ___________________________________17596H9-154

649HTable 9-18. Overview of the different aerosol indirect effects and their sign of the net radiative flux 

change at the top of the atmosphere (TOA). _________________________________________________1759H9-166

650HTable 9-19. Overview of the different aerosol indirect effects and their implications for the global mean 

net shortwave radiation of the surface Fsfc (columns 2-4) and for precipitation (columns 

5-7). ________________________________________________________________________________17598H9-166

651HTable 9-20. Recent studies highlighting POP occurrence and fate in the major arctic compartments._______________1759H9-168

652HTable 9-21. Factors potentially important in estimating Hg exposure.________________________________________1760H9-177

653HTable A-1. Summary of integrated and continuous samplers included in the field comparison. ____________________ 1760HA-1

654HTable A-2. Summary of PM2.5 and PM10 FRM and FEM samplers. __________________________________________ 17602HA-5

65HTable A-3. Measurement and analytical specifications for filter analysis of mass, elements, ions, and 

carbon. _______________________________________________________________________________ 17603HA-7

65HTable A-4. Measurement and analytical specifications for filter analysis of organic species. ______________________ 17604HA-9

657HTable A-5. Measurement and analytical specifications for continuous mass and mass surrogate 

instruments. __________________________________________________________________________ 17605HA-11

658HTable A-6. Measurement and analytical specifications for continuous elements. ______________________________ 1760HA-14

659HTable A-7. Measurement and analytical specifications for continuous NO3-. _________________________________ 1760HA-15

60HTable A-8. Measurement and analytical specifications for continuous SO4

2–. _________________________________ 17608HA-17

61HTable A-9. Measurement and analytical specifications for ions other than NO3

–

 and SO4

2–.______________________ 17609HA-19

62HTable A-10. Measurement and analytical specifications for continuous carbon. ________________________________ 1760HA-20

63HTable A-11. Summary of mass measurement comparisons. _______________________________________________ 176HA-23

64HTable A-12. Summary of element and liquid water content measurement comparisons. _________________________ 1762HA-31

65HTable A-13. Summary of PM2.5 NO3

-

 measurement comparisons.___________________________________________ 1763HA-32

6HTable A-14. Summary of PM2.5 SO4

2– measurement comparisons __________________________________________ 1764HA-38

67HTable A-15. Summary of PM2.5 carbon measurement comparisons. _________________________________________ 1765HA-41
December 2009 xix 

68HTable A-16. Summary of particle mass spectrometer measurement comparisons.______________________________ 176HA-48

69HTable A-17. Summary of key parameters for TD-GC/MS and pyrolysis-GC/MS. _______________________________ 176HA-52

670HTable A-18. Relevant Spatial Scales for PM10, PM2.5, and PM10-2.5 Measurement_______________________________ 1768HA-54

671HTable A-19. Major routine operating air monitoring networksa ______________________________________________ 1769HA-56

672HTable A-20. Inter-sampler correlation statistics for each pair of PM2.5 monitors reporting to AQS for 

Atlanta, GA. __________________________________________________________________________ 17620HA-98

673HTable A-21. Inter-sampler correlation statistics for each pair of PM2.5 monitors reporting to AQS for 

Birmingham, AL. ______________________________________________________________________ 1762HA-102

674HTable A-22. Inter-sampler correlation statistics for each pair of PM2.5 monitors reporting to AQS for 

Boston, MA. _________________________________________________________________________ 1762HA-106

675HTable A-23. Inter-sampler correlation statistics for each pair of PM2.5 monitors reporting to AQS for 

Chicago, IL. _________________________________________________________________________ 17623HA-111

67HTable A-24. Inter-sampler correlation statistics for each pair of PM2.5 monitors reporting to AQS for 

Denver, CO. _________________________________________________________________________ 17624HA-116

67HTable A-25. Inter-sampler correlation statistics for each pair of PM2.5 monitors reporting to AQS for 

Detroit, MI. __________________________________________________________________________ 17625HA-120

678HTable A-26. Inter-sampler correlation statistics for each pair of PM2.5 monitors reporting to AQS for 

Houston, TX._________________________________________________________________________ 1762HA-123

679HTable A-27. Inter-sampler correlation statistics for each pair of PM2.5 monitors reporting to AQS for Los 

Angeles, CA._________________________________________________________________________ 1762HA-127

680HTable A-28. Inter-sampler correlation statistics for each pair of PM2.5 monitors reporting to AQS for New 

York, NY. ___________________________________________________________________________ 17628HA-131

681HTable A-29. Inter-sampler correlation statistics for each pair of PM2.5 monitors reporting to AQS for 

Philadelphia, PA. _____________________________________________________________________ 17629HA-136

682HTable A-30. Inter-sampler correlation statistics for each pair of PM2.5 monitors reporting to AQS for 

Phoenix, AZ._________________________________________________________________________ 17630HA-140

683HTable A-31. Inter-sampler correlation statistics for each pair of PM2.5 monitors reporting to AQS for 

Pittsburgh, PA. _______________________________________________________________________ 1763HA-144

684HTable A-32. Inter-sampler correlation statistics for each pair of PM2.5 monitors reporting to AQS for 

Riverside, CA.________________________________________________________________________ 17632HA-148

685HTable A-33. Inter-sampler correlation statistics for each pair of PM2.5 monitors reporting to AQS for 

Seattle, WA. _________________________________________________________________________ 1763HA-152

68HTable A-34. Inter-sampler correlation statistics for each pair of PM2.5 monitors reporting to AQS for St. 

Louis, MO. __________________________________________________________________________ 17634HA-155

687HTable A-35. Inter-sampler correlation statistics for each pair of PM10 monitors reporting to AQS for 

Atlanta, GA. _________________________________________________________________________ 17635HA-159

68HTable A-36. Inter-sampler correlation statistics for each pair of PM10 monitors reporting to AQS for 

Birmingham, AL. ______________________________________________________________________ 1763HA-163

689HTable A-37. Inter-sampler correlation statistics for each pair of PM10 monitors reporting to AQS for 

Boston, MA. _________________________________________________________________________ 1763HA-166

690HTable A-38. Inter-sampler correlation statistics for each pair of PM10 monitors reporting to AQS for 

Chicago, IL. _________________________________________________________________________ 17638HA-170
December 2009 xx 

691HTable A-39. Inter-sampler correlation statistics for each pair of PM10 monitors reporting to AQS for 

Denver, CO. _________________________________________________________________________ 17639HA-174

692HTable A-40. Inter-sampler correlation statistics for each pair of PM10 monitors reporting to AQS for 

Detroit, MI. __________________________________________________________________________ 17640HA-178

693HTable A-41. Inter-sampler correlation statistics for each pair of PM10 monitors reporting to AQS for 

Houston, TX._________________________________________________________________________ 1764HA-181

694HTable A-42. Inter-sampler correlation statistics for each pair of PM10 monitors reporting to AQS for Los 

Angeles, CA._________________________________________________________________________ 17642HA-184

695HTable A-43. Inter-sampler correlation statistics for each pair of PM10 monitors reporting to AQS for New 

York, NY. ___________________________________________________________________________ 17643HA-188

69HTable A-44. Inter-sampler correlation statistics for each pair of PM10 monitors reporting to AQS for 

Philadelphia, PA. _____________________________________________________________________ 1764HA-191

697HTable A-45. Inter-sampler correlation statistics for each pair of PM10 monitors reporting to AQS for 

Phoenix, AZ._________________________________________________________________________ 17645HA-195

698HTable A-46. Inter-sampler correlation statistics for each pair of PM10 monitors reporting to AQS for 

Pittsburgh, PA. _______________________________________________________________________ 1764HA-200

69HTable A-47. Inter-sampler correlation statistics for each pair of PM10 monitors reporting to AQS for 

Riverside, CA.________________________________________________________________________ 1764HA-204

70HTable A-48. Inter-sampler correlation statistics for each pair of PM10 monitors reporting to AQS for 

Seattle, WA. _________________________________________________________________________ 17648HA-207

701HTable A-49. Inter-sampler correlation statistics for each pair of PM10 monitors reporting to AQS for St. 

Louis, MO. __________________________________________________________________________ 17649HA-211

702HTable A-50. Correlation coefficients of hourly and daily average particle number, surface and volume 

concentrations in selected particle size ranges.______________________________________________ 17650HA-212

703HTable A-51. Different receptor models used in the Supersite source apportionment studies: chemical 

mass balance. _______________________________________________________________________ 1765HA-273

704HTable A-52. Different receptor models used in the Supersites source apportionment studies: factor 

analysis. ____________________________________________________________________________ 17652HA-274

705HTable A-53. Different receptor models used in the Supersites source apportionment studies: tracerbased methods. ______________________________________________________________________ 17653HA-278

706HTable A-54. Different receptor models used in the Supersites source apportionment studies: 

meteorology-based methods.____________________________________________________________ 17654HA-280

70HTable A-55. Source Profiles: Part I__________________________________________________________________ 1765HA-286

708HTable A-56. PM2.5 receptor model results (μg/m3) ______________________________________________________ 1765HA-289

709HTable A-57. PM10 receptor model results (mass percent) ________________________________________________ 1765HA-290

710HTable A-58. Exposure Assessment Study Summaries __________________________________________________ 17658HA-291

71HTable A-59. Examples of studies showing developments with UFP sampling methods since the 2004 

PM AQCD. __________________________________________________________________________ 17659HA-317

712HTable A-60. Summary of in-vehicle studies of exposure assessment._______________________________________ 1760HA-318

713HTable A-61. Summary of personal PM exposure studies with no indoor source during 2002-2008. ________________ 176HA-320

714HTable A-62. Summary of PM species exposure studies. _________________________________________________ 1762HA-324

715HTable A-63. Summary of personal PM exposure source apportionment studies. ______________________________ 1763HA-337
December 2009 xxi 

716HTable A-64. Summary of PM infiltration studies. _______________________________________________________ 1764HA-339

71HTable A-65. Summary of PM – copollutant exposure studies. _____________________________________________ 1765HA-350

718HTable B-1. Ultrafine disposition in humans. ____________________________________________________________ 176HB-1

719HTable B- 2. Ultrafine disposition in animals. ____________________________________________________________ 176HB-2

720HTable B- 3. In vitro studies of ultrafine disposition. _______________________________________________________ 1768HB-3

721HTable B-4. Olfactory particle translocation. ____________________________________________________________ 1769HB-3

72HTable B-5. Studies of respiratory tract mucosal and macrophage clearance as a function of age. __________________ 1760HB-5

723HTable C-1. Cardiovascular effects.___________________________________________________________________ 176HC-1

724HTable C-2. Respiratory effects.______________________________________________________________________ 1762HC-9

725HTable C- 3. Central nervous system effects. ___________________________________________________________ 1763HC-13

726HTable D-1. Cardiovascular effects.___________________________________________________________________ 1764HD-1

72HTable D-2. Respiratory effects: in vitro studies. ________________________________________________________ 1765HD-31

728HTable D-3. Respiratory effects: in vivo studies. ________________________________________________________ 176HD-81

729HTable D-4. Effects related to immunity and allergy. ____________________________________________________ 176HD-116

730HTable D-5. Effects of the central nervous system. _____________________________________________________ 1768HD-155

731HTable D-6. Reproductive and developmental effects. __________________________________________________ 1769HD-157

732HTable D-7. Mutagenic/genotoxic effects in bacterial cultures. ____________________________________________ 17680HD-163

73HTable D-8. Mutagenicity and genotoxicity data summary: In vitro and in vivo.________________________________ 1768HD-166

734HTable E-1 Short-term exposure – cardiovascular morbidity outcomes: PM10 __________________________________ 17682HE-1

735HTable E-2. Short-term exposure - cardiovascular morbidity studies: PM10-2.5.__________________________________ 17683HE-19

736HTable E-3. Short-term exposure - cardiovascular morbidity studies: PM2.5 (including PM 

components/sources). __________________________________________________________________ 17684HE-21

73HTable E-4. Short-term exposure-cardiovascular morbidity studies: Other size fractions. ________________________ 17685HE-79

738HTable E-5. Short-term exposure-cardiovascular: ED/HA PM10 ____________________________________________ 1768HE-85

739HTable E-6. Short-term exposure-cardiovascular-ED/HA - PM10-2.5. ________________________________________ 1768HE-104

740HTable E-7. Short-term exposure – cardiovascular: ED/HA PM2.5 (including PM components/sources)_____________ 1768HE-107

741HTable E-8. Short-term exposure-cardiovascular-ED/HA-other size fractions. ________________________________ 17689HE-130

742HTable E-9. Short-term exposure-respiratory morbidity outcomes -PM10. ____________________________________ 17690HE-134

743HTable E-10. Short-term exposure - respiratory morbidity outcomes - PM10-2.5. _________________________________ 1769HE-169

74HTable E-11. Short-term exposure - respiratory morbidity outcomes - PM2.5 (including 

components/sources). _________________________________________________________________ 17692HE-173

745HTable E-12. Short-term exposure-respiratory-ED/HA-PM10._______________________________________________ 17693HE-230

746HTable E-13. Short-term exposure-respiratory-ED/HA-PM10-2.5. _____________________________________________ 17694HE-256

74HTable E-14. Short-term exposure-respiratory-ED/HA-PM2.5 (including PM components/sources). _________________ 17695HE-262

748HTable E-15. Short-term exposure-respiratory-ED/HA-Other Size Fractions. __________________________________ 1769HE-284

749HTable E-16. Short-term exposure-mortality - PM10. _____________________________________________________ 1769HE-293

750HTable E-17. Short-term exposure-mortality - PM10-2.5.____________________________________________________ 17698HE-343
December 2009 xxii 

751HTable E-18. Short-term exposure-mortality - PM2.5 (including PM components/sources).________________________ 1769HE-346

752HTable E-19. Short-term exposure-mortality - other PM size fractions. _______________________________________ 170HE-360

753HTable E-20. Long-term exposure - cardiovascular morbidity outcomes - PM10.________________________________ 170HE-363

754HTable E-21. Long-term effects-cardiovascular- PM2.5 (including PM components/sources). ______________________ 1702HE-372

75HTable E-22. Long-term exposure - respiratory morbidity outcomes - PM10. ___________________________________ 1703HE-383

756HTable E-23. Long-term exposure - respiratory morbidity outcomes - PM10-2.5. _________________________________ 1704HE-407

75HTable E-24. Long-term exposure - respiratory morbidity outcomes - PM2.5 (including PM 

components/sources). _________________________________________________________________ 1705HE-412

758HTable E-25. Long-term exposure - respiratory morbidity outcomes - other PM size fractions. ____________________ 1706HE-432

759HTable E-26. Long-term exposure - cancer outcomes - PM10. ______________________________________________ 170HE-434

760HTable E-27. Long-term exposure - cancer outcomes - PM2.5 (including PM components/sources). ________________ 1708HE-437

761HTable E-28. Long-term exposure - cancer outcomes - other PM size fractions. _______________________________ 1709HE-440

762HTable E-29. Long-term exposure - reproductive outcomes - PM10. _________________________________________ 170HE-441

763HTable E-30. Long-term exposure-mortality - PM10.______________________________________________________ 17HE-491

764HTable E-31. Long-term exposure-mortality - PM10.______________________________________________________ 172HE-498

765HTable E-32. Long-term exposure-mortality - PM10-2.5. ____________________________________________________ 173HE-499

76HTable E-33. Long-term exposure-mortality - PM2.5 (including PM components/sources). ________________________ 174HE-500

76HTable E-34. Long-term exposure - central nervous system outcomes - PM.__________________________________ 175HE-521

768HTable F-1. Epidemiologic studies of ambient PM sources, factors, or constituents______________________________ 176HF-1

769HTable F-2. Human clinical studies of ambient PM sources, factors, or constituents _____________________________ 17HF-6

70HTable F-3. Toxicological studies of ambient PM sources, factors, or constituents ______________________________ 178HF-7
December 2009 xxiii 

List of Figures 

71HFigure 1-1. Identification of studies for inclusion in the ISA. ________________________________________________179H1-11

72HFigure 2-1. Summary of effect estimates (per 10 μg/m3) by increasing concentration from U.S. studies 

examining the association between short-term exposure to PM2.5 and cardiovascular and 

respiratory effects, and mortality ___________________________________________________________1720H2-14

73HFigure 2-2. Summary of effect estimates (per 10 μg/m3) by increasing concentration from U.S. studies 

examining the association between long-term exposure to PM2.5 and cardiovascular and 

respiratory effects, and mortality ___________________________________________________________172H2-15

74HFigure 2-3. Summary of U.S. studies examining the association between short-term exposure to 

PM10-2.5 and cardiovascular morbidity/mortality and respiratory morbidity/mortality_____________________172H2-20

75HFigure 3-1. Particle size distributions by number and volume. _______________________________________________1723H3-2

76HFigure 3-2. X-ray spectra and scanning electron microscopy images of individual particles.________________________1724H3-5

7HFigure 3-3. Detailed source categorization of anthropogenic emissions of primary PM2.5, PM10 and 

gaseous precursor species SO2, NOX, NH3 and VOCs for 2002 in units of million metric 

tons (MMT). ____________________________________________________________________________1725H3-9

78HFigure 3-4. Primary emissions and formation of SOA through gas, cloud and condensed phase 

reactions. _____________________________________________________________________________1726H3-12

79HFigure 3-5. Schematic of the resistance-in-series analogy for atmospheric deposition.___________________________172H3-15

780HFigure 3-6. The relationship between particle diameter and Vd for particles. ___________________________________1728H3-19

781HFigure 3-7. PM2.5 monitor distribution in comparison with population density, Boston CSA. _______________________1729H3-33

782HFigure 3-8. PM10 monitor distribution in comparison with population density, Boston CSA.________________________1730H3-34

783HFigure 3-9. Three-yr avg 24-h PM2.5 concentration by county derived from FRM or FRM-like data, 

2005-2007. ____________________________________________________________________________173H3-43

784HFigure 3-10. Three-yr avg 24-h PM10-2.5 concentration by county derived from co-located low volume 

FRM PM10 and PM2.5 monitors, 2005-2007. ___________________________________________________1732H3-46

785HFigure 3-11. Three-yr avg 24-h PM10 concentration by county derived from FRM or FEM monitors, 

2005-2007. ____________________________________________________________________________173H3-48

786HFigure 3-12. Three-yr avg 24-h PM2.5 OC concentrations measured at CSN sites across the U.S., 2005-

2007._________________________________________________________________________________1734H3-52

78HFigure 3-13. Three-yr avg 24-h PM2.5 EC concentrations measured at CSN sites across the U.S., 2005-

2007._________________________________________________________________________________1735H3-53

78HFigure 3-14. Three-yr avg 24-h PM2.5 SO4

2– concentrations measured at CSN sites across the U.S., 

2005-2007. ____________________________________________________________________________1736H3-54

789HFigure 3-15. Three-yr avg 24-h PM2.5 NO3

–

 concentrations measured at CSN sites across the U.S., 

2005-2007. ____________________________________________________________________________173H3-55

790HFigure 3-16. Three-yr avg 24-h PM2.5 NH4

+

 concentrations measured at CSN sites across the U.S., 

2005-2007. ____________________________________________________________________________1738H3-56

791HFigure 3-18. Seasonally-stratified 3-yr avg PM2.5 speciation estimates for 2005-2007 derived using the 

SANDWICH method. ____________________________________________________________________1739H3-58

792HFigure 3-19. Locations of PM2.5 monitors and major highways, Boston, MA. ____________________________________1740H3-61
December 2009 xxiv 

793HFigure 3-20. Seasonal distribution of 24-h avg PM2.5 concentrations by site for Boston, MA, 2005-2007.______________174H3-62

794HFigure 3-21. Locations of PM2.5 monitors and major highways, Pittsburgh, PA.__________________________________1742H3-65

795HFigure 3-22. Seasonal distribution of 24-h avg PM2.5 concentrations by site for Pittsburgh, PA, 2005-

2007._________________________________________________________________________________1743H3-66

796HFigure 3-23. Locations of PM2.5 monitors and major highways, Los Angeles, CA.________________________________174H3-68

79HFigure 3-24. Seasonal distribution of 24-h avg PM2.5 concentrations by site for Los Angeles, CA, 2005-

2007._________________________________________________________________________________1745H3-69

798HFigure 3-25. Inter-sampler correlations for 24-h PM2.5 as a function of distance between monitors in 

Boston, MA. ___________________________________________________________________________1746H3-71

79HFigure 3-26. Inter-sampler correlations for 24-h PM2.5 as a function of distance between monitors in 

Pittsburgh, PA. _________________________________________________________________________174H3-71

80HFigure 3-27. Inter-sampler correlations for 24-h PM2.5 as a function of distance between monitors in Los 

Angeles, CA.___________________________________________________________________________1748H3-72

801HFigure 3-28. Seasonal distribution of 24-h avg PM10-2.5 concentrations by site __________________________________1749H3-73

802HFigure 3-29. Locations of PM10 monitors and major highways, Boston, MA.____________________________________1750H3-74

803HFigure 3-30. Seasonal distribution of 24-h avg PM10 concentrations by site for Boston, MA, 2005-2007. ______________175H3-75

804HFigure 3-31. Locations of PM10 monitors and major highways, Pittsburgh, PA. __________________________________1752H3-76

805HFigure 3-32. Seasonal distribution of 24-h avg PM10 concentrations by site for Pittsburgh, PA, 2005-

2007._________________________________________________________________________________1753H3-77

806HFigure 3-33. Locations of PM10 monitors and major highways, Los Angeles, CA. ________________________________1754H3-80

807HFigure 3-34. Seasonal distribution of 24-h avg PM10 concentrations by site for Los Angeles, CA, 2005-

2007._________________________________________________________________________________175H3-81

80HFigure 3-35. Inter-sampler correlations for 24-h PM10 as a function of distance between monitors in 

Boston, MA. ___________________________________________________________________________1756H3-82

809HFigure 3-36. Inter-sampler correlations for 24-h PM10 as a function of distance between monitors in 

Pittsburgh, PA. _________________________________________________________________________175H3-83

810HFigure 3-37. Inter-sampler correlations for 24-h PM10 as a function of distance between monitors in Los 

Angeles, CA.___________________________________________________________________________1758H3-83

81HFigure 3-38. Bin-wise Spearman correlation coefficients in aerosol particle number concentrations 

between the Ift (urban background) and the Eisenbahn-strasse (city/urban center) sites in 

Leipzig, Germany. ______________________________________________________________________1759H3-84

812HFigure 3-39. Dimensionless concentration as a function of height at windward and leeward locations and 

street canyon aspect ratios (H/W). __________________________________________________________1760H3-86

813HFigure 3-40. Inter-sampler correlations for 24-h PM2.5 and PM10 as a function of distance between 

monitors for samplers located within 4 km (neighborhood scale). __________________________________176H3-87

814HFigure 3-41. Particle size distributions measured at various distances from the 710 freeway in Los 

Angeles, CA (top), and particle number concentration as a function of distance from the 

710 freeway (bottom).____________________________________________________________________1762H3-88

815HFigure 3-42. Mass distributions for BaP at a high traffic urban center (HTC), high traffic urban periphery 

(HTP), low traffic urban center (LTC), low traffic urban periphery (LTP), and low traffic 

industrial urban periphery (LTIP) in Seville, Spain. _____________________________________________1763H3-90

816HFigure 3-43. Mass distributions for 16 PAHs at a high traffic city center in Seville, Spain.__________________________1764H3-91
December 2009 xxv 

817HFigure 3-44. Ambient 24-h PM2.5 concentrations in the U.S., 1999-2007, showing A) ambient 

concentrations, B) number of trends sites above the 24-h NAAQS and C) trends by U.S. 

EPA Region.___________________________________________________________________________1765H3-92

81HFigure 3-45. Ambient annual PM2.5 concentrations in the U.S., 1999-2007, showing A) ambient 

concentrations, B) number of trends sites above the annual NAAQS and C) trends by U.S. 

EPA Region.___________________________________________________________________________176H3-93

819HFigure 3-46. Ambient 24-h PM10 concentrations in the U.S., 1988-2007, showing A) ambient 

concentrations, B) number of trends sites above the 24-h NAAQS and C) trends by U.S. 

EPA Region.___________________________________________________________________________176H3-94

820HFigure 3-47. Regional and seasonal trends in annual PM2.5 compostion from 2002 to 2007 derived using 

the SANDWICH method. _________________________________________________________________1768H3-95

821HFigure 3-48. UFP size distribution at highway (site A) and background (site B) sites in Los Angeles, CA, 

during summer and winter seasons, with winter broken into day and evening distributions. ______________1769H3-97

82HFigure 3-49. Diel plot generated from hourly FRM-like PM2.5 data (μg/m3) stratified by weekday (left) and 

weekend (right) for Pittsburgh, PA, and Seattle, WA, 2005-2007. __________________________________170H3-98

823HFigure 3-50. Diel plots generated from hourly FEM PM10 data (μg/m3) stratified by weekday (left) and 

weekend (right) for Chicago, IL, and Phoenix, AZ, 2005-2007. ____________________________________17H3-99

824HFigure 3-51. Average diel variation in total particle number (ToN) and total particle volume (ToV) on 

weekdays (left column) and Sundays (right column) from two sites in Denmark: one in a 

busy street canyon (Jagtv) and one measuring urban background (HCØ). __________________________172H3-100

825HFigure 3-52. Distribution of correlations between 24-h avg PM2.5 and co-located 24-h avg PM10, PM10-2.5, 

SO2, NO2 and CO and daily max 8-h avg O3 for the U.S. stratified by season (2005-2007)._____________173H3-101

826HFigure 3-53. Distribution of correlations between 24-h avg PM10 and co-located 24-h avg PM2.5, PM10-2.5, 

SO2, NO2 and CO and daily max 8-h avg O3 for the U.S. stratified by season (2005-2007)._____________174H3-102

827HFigure 3-54. Schematic of organic composition of particulate emissions from gasoline-fueled vehicles. _____________175H3-105

82HFigure 3-55. Source category contributions to PM2.5 at a number of sites in the East derived using PMF. ____________176H3-108

829HFigure 3-56. Pearson correlation coefficients for source category contributions to PM2.5 between the 10 

Regional Air Pollution Study/Regional Air Monitoring System (RAPS/RAMS) monitoring 

sites in St. Louis. ______________________________________________________________________17H3-109

830HFigure 3-57. Pearson correlation coefficients for source contributions to PM10-2.5 between the 10 

Regional Air Pollution Study/Regional Air Monitoring System (RAPS/RAMS) monitoring 

sites in St. Louis. ______________________________________________________________________178H3-109

831HFigure 3-58. Eight km southeast U.S. CMAQ-UCD domain zoomed over Tampa Bay, FL.________________________179H3-115

832HFigure 3-59. Two km southeast U.S. CMAQ-UCD domain zoomed over Tampa Bay, FL. ________________________1780H3-115

83HFigure 3-60. Hourly average CMAQ-UCD predictions and measured observations of NO (top), NO2

(middle), and total NOX (bottom) concentrations for May 1-31, 2002. ______________________________178H3-116

834HFigure 3-61. CMAQ-UCD predictions and measured observations of ethene concentrations at Sydney, 

FL for May 1-31, 2002. __________________________________________________________________1782H3-117

835HFigure 3-62. CMAQ-UCD predictions and measured observations of isoprene concentrations at Sydney, 

FL for May 1-31, 2002. __________________________________________________________________1783H3-118

836HFigure 3-63. CMAQ-UCD predictions and measured observations of PM2.5 concentrations at Sidney, FL 

for May 1-31, 2002. ____________________________________________________________________1784H3-119

837HFigure 3-64. CMAQ-UCD predictions of HNO3

–

 concentrations and corresponding measured 

observations at Sydney, FL, for May 1-31, 2002.______________________________________________1785H3-121
December 2009 xxvi 

83HFigure 3-65. CMAQ-UCD predictions of NH3 concentrations and corresponding measured observations 

at Sydney, FL, for May 1-31, 2002. ________________________________________________________1786H3-122

839HFigure 3-66. CMAQ-UCD predictions of pNO3

–

 concentrations and corresponding measured 

observations at Sydney, FL, for 1-31 May, 2002.______________________________________________178H3-123

840HFigure 3-67. CMAQ-UCD predictions of the ratio of HNO3 to total NO3 and corresponding measured 

observations at Sydney, FL, for May 1-31, 2002.______________________________________________178H3-124

841HFigure 3-68. CMAQ-UCD predicted size and chemical-form fractions of total NO3

–

 for days in May 2002 

with measured observations. _____________________________________________________________1789H3-125

842HFigure 3-69. Scatter plot of total nitrate (HNO3 plus pNO3

–

) wet deposition (mg N/m2/yr) of the model 

mean versus measurements for the North American Deposition Program (NADP) network. ____________1790H3-127

843HFigure 3-70. Scatter plot of total SO4

2– wet deposition (mg S/m2

/yr) of the model mean versus 

measurements for the National Atmospheric Deposition Program (NADP) network. __________________179H3-127

84HFigure 3-71. CMAQ modeling domains for the OAQPS risk and exposure assessments: 36 km outer 

parent domain in black; 12 km western U.S. (WUS) domain in red; 12 km eastern U.S. 

(EUS) domain in blue. __________________________________________________________________1792H3-128

845HFigure 3-72. 12-km EUS Summer sulfate PM. __________________________________________________________1793H3-129

846HFigure 3-73. 12-km EUS Winter nitrate PM. ____________________________________________________________1794H3-130

847HFigure 3-74. 12-km EUS Winter total nitrate (HNO3 + total pNO3

–

). __________________________________________1795H3-131

84HFigure 3-75. 12-km EUS annual sulfate wet deposition.___________________________________________________1796H3-132

849HFigure 3-76. 12-km EUS annual nitrate wet deposition. ___________________________________________________179H3-133

850HFigure 3-77. CMAQ vs. measured air concentrations from east-coast sites in the IMPROVE, CSN 

(labeled STN), and CASTNet sites in the summer of 2002 for sulfate (left) and ammonium 

(right). _______________________________________________________________________________1798H3-134

851HFigure 3-78. Comparison of CMAQ-predicted and NADP-measured NH4

+

 wet deposition ________________________179H3-134

852HFigure 3-79. CMAQ-predicted (red symbols and lines) and 12-h measured (blue symbols and lines) NH3

and SO4

2– surface concentrations at high and low concentration grid cells in North Carolina 

in July 2004. __________________________________________________________________________1780H3-135

853HFigure 3-80. Surface grid cell (layer 1) analysis of the sensitivity of NHX deposition and transport to the 

change in NH3 Vd in CMAQ. ______________________________________________________________1780H3-136

854HFigure 3-81. Total column analysis for NH3 (left) and NHX (right) showing modeled NH3 emissions, 

transformation, and transport throughout the mixed layer and up to the free troposphere. ______________17802H3-136

85HFigure 3-82. Range of influence (where 50% of emitted NH3 deposits) from the high concentration 

Sampson County grid cell in the June 2002 CMAQ simulation of Vd sensitivities._____________________17803H3-137

856HFigure 3-83. Areal extent of the change in NHX range of influence as predicted by CMAQ for the 

Sampson County high concentration grid cell (center of range circles) in June 2002 using 

the base case and sensitivity case Vd. ______________________________________________________17804H3-138

857HFigure 3-84. IMPROVE monitoring site locations. _______________________________________________________17805H3-141

85HFigure 3-85. 12-km EUS Summer SO4

2– PM. ___________________________________________________________17806H3-144

859HFigure 3-86 12-km EUS Winter NO3

-

 PM. _____________________________________________________________1780H3-145

860HFigure 3-87. 12-km EUS Winter total nitrate (HNO3 + total particulate NO3

–

). __________________________________1780H3-145

861HFigure 3-88. Monthly average of PM2.5 concentrations measured at IMPROVE sites in the East and 

Midwest for 2004. ______________________________________________________________________17809H3-146
December 2009 xxvii 

862HFigure 3-89. Monthly average of PM2.5 concentrations measured at IMPROVE sites in the West for 

2004.________________________________________________________________________________1780H3-147

863HFigure 3-90. Distribution of PM2.5 concentrations measured at IMPROVE sites in the East and Midwest 

for 2004. _____________________________________________________________________________178H3-148

864HFigure 3-91. Distribution of PM2.5 concentrations measured at IMPROVE sites in the West for 2004. _______________1782H3-149

865HFigure 3-92. Model of total personal exposure to PM as a function of ambient and nonambient sources. ____________1783H3-154

86HFigure 3-93. Distribution of time sample population spends in various environments, from the National 

Human Activity Pattern Survey. ___________________________________________________________1784H3-159

867HFigure 3-94. Total exposure to SO4

2– as a function of measured ambient SO42– concentration, from the 

Vancouver study. ______________________________________________________________________1785H3-166

86HFigure 3-95. Estimated ambient exposure to PM2.5 as a function of measured ambient PM2.5

concentration, from the Vancouver study____________________________________________________1786H3-166

869HFigure 3-96. Total exposure to PM2.5 as a function of measured ambient PM2.5 concentration, from the 

Vancouver study. ______________________________________________________________________178H3-167

870HFigure 3-97. Finf as a function of particle size.___________________________________________________________178H3-170

871HFigure 3-98. Apportionment of aliphatic carbon, carbonyl, and SO4

2– components of outdoor, indoor, and 

personal PM2.5 samples, for Los Angeles (top), Elizabeth (center), and Houston (bottom). _____________1789H3-172

872HFigure 3-99. Apportionment of infiltrated PM from mechanical generation (top), primary combustion 

(center), and secondary combustion (bottom).________________________________________________17820H3-173

873HFigure 3-100. Results of the positive matrix factorization model showing differences in the mass of 

outdoor PM and PM that has infiltrated indoors based on source category. _________________________1782H3-174

874HFigure 3-101. Grid resolution of the CMAQ model in Philadelphia compared with distribution of census 

tracts in which exposure assessment is performed.____________________________________________1782H3-178

875HFigure 4-1. Diagrammatic representation of respiratory tract regions in humans. ________________________________17823H4-3

876HFigure 4-2. Structure of lower airways with progression from the large airways to the alveolus. _____________________17824H4-4

87HFigure 4-3. Comparison of total and regional deposition results from the ICRP and MPPD models for a 

resting breathing pattern (VT = 625 mL, f = 12 min-1) and corrected for particle inhalability. _______________17825H4-7

87HFigure 4-4. Comparison of total and regional deposition results from the ICRP and MPPD models for a 

light exercise breathing pattern (VT = 1250 mL, f = 20 min-1) and corrected for particle 

inhalability. _____________________________________________________________________________17826H4-8

879HFigure 4-5. Total lung deposition measured in healthy adults (UF, 11 M, 11 F, 31 ± 4 yr; fine and 

coarse, 11 M, 11 F, 25 ± 4 yr) during controlled breathing on a mouthpiece. __________________________1782H4-9

80HFigure 4-6. Total deposition of hygroscopic sodium chloride and hydrophobic aluminosilicate aerosols 

during oral breathing (VT = 1.0 L; f = 15 min-1)._________________________________________________1782H4-16

81HFigure 4-7. Retention of poorly soluble particles (0.5-5 μm) in the alveolar region of the lung over time 

in various mammalian species. ____________________________________________________________17829H4-20

82HFigure 5-1. PM oxidative potential. ____________________________________________________________________17830H5-2

83HFigure 5-2 PM stimulates pulmonary cells to produce ROS/RNS.____________________________________________1783H5-3

84HFigure 5-3. PM activates cell signaling pathways leading to pulmonary inflammation. ____________________________17832H5-5

85HFigure 5-4. Potential pathways for the effects of PM on the respiratory system. _________________________________1783H5-7

86HFigure 5-5. Potential pathways for the effects of PM on the cardiovascular system. _____________________________17834H5-13
December 2009 xxviii 

87HFigure 6-1. Excess risk estimates per 10 μg/m3 increase in 24-h avg PM2.5, PM10- 2.5, and PM10 

concentration for CVD ED visits and HAs. ____________________________________________________17835H6-62

8HFigure 6-2. Excess risk estimates per 10 μg/m3 increase in 24-h avg (unless otherwise noted) PM2.5, 

PM10- 2.5, and PM10 concentration for MI and IHD ED visits and HAs. _______________________________17836H6-66

89HFigure 6-3. Excess risk estimates per 10 μg/m3 increase in 24-h avg PM2.5, PM10- 2.5, and PM10

concentration for CHF ED visits and HAs. ____________________________________________________1783H6-69

890HFigure 6-4. Excess risk estimates per 10 μg/m3 increase in 24-h avg PM2.5 and PM10 concentration for 

CBVD ED visits and HAs._________________________________________________________________1783H6-72

891HFigure 6-5. Excess risk estimates per 10 μg/m3 increase in 24-h avg PM2.5, and PM10-2.5 for 

cardiovascular disease ED visits or HAs, adjusted for co-pollutants.________________________________17839H6-74

892HFigure 6-6. Combined random-effect estimate of the concentration-response relationship between MI 

emergency hospital admissions and PM10, computed by fitting a piecewise linear spline, 

with slope changes at 20 μg/m3

 and 50 μg/m3. ________________________________________________17840H6-76

893HFigure 6-7. Respiratory symptoms and/or medication use among asthmatic children following acute 

exposure to PM. ________________________________________________________________________1784H6-86

894HFigure 6-8. Respiratory symptoms and/or medication use among asthmatic adults following acute 

exposure to particles. ____________________________________________________________________17842H6-92

895HFigure 6-9. Respiratory symptoms following acute exposure to particles and additional criteria 

pollutants. _____________________________________________________________________________17843H6-93

896HFigure 6-10. Excess risk estimates per 10 μg/m3 24-h avg PM2.5, PM10- 2.5, and PM10 concentration for 

ED visits and HAs for respiratory diseases in children. _________________________________________1784H6-134

897HFigure 6-11. Excess risks estimates per 10 μg/m3 increase in 24-h avg PM2.5, PM10- 2.5, and PM10 for ED 

visits and HAs for respiratory diseases among adults.__________________________________________17845H6-138

89HFigure 6-12. Excess risk estimates per 10 μg/m3 increase in 24-h avg PM2.5, PM10- 2.5, and PM10 for 

asthma ED visits and HAs._______________________________________________________________17846H6-140

89HFigure 6-13. Excess risks estimates per 10 μg/m3 increase in 24-h avg PM2.5, PM10- 2.5, and PM10 for 

COPD ED visits and HAs among older adults (65+ yr, unless other age group is noted)._______________1784H6-143

90H Figure 6-14. Excess risks estimates per 10 μg/m3 increase in 24-h avg PM2.5, PM10- 2.5, and PM10 for 

respiratory infection ED visits* and HAs. ____________________________________________________1784H6-145

901HFigure 6-15. Excess risk estimates per 10 μg/m3 increase in 24-h avg PM2.5, and PM10-2.5 for respiratory 

disease ED visits or HAs, adjusted for co-pollutants.___________________________________________17849H6-148

902HFigure 6-16. National and regional estimates of smooth seasonal effects for PM10 at a 1-day lag and 

their sensitivity to the degrees of freedom assigned to the smooth function of time in the 

updated NMMAPS data 1987-2000.________________________________________________________17850H6-162

903HFigure 6-17. Percent increase in the daily number of deaths, for all ages, associated with a 10-μg/m3

increase in PM10: lag 1 (A) and lags 0 and 1 (B) for all three centers. ______________________________1785H6-166

904HFigure 6-18. Effect modification by city characteristics in 20 U.S. cities. ______________________________________17852H6-168

905HFigure 6-19. Percent excess risk in mortality (all-cause [nonaccidental] and cause-specific) per 

10 μg/m3

increase in PM10by individual-level characteristics. _____________________________________17853H6-170

906HFigure 6-20. Percent excess risk in mortality (all-cause [nonaccidental] and cause-specific) per 

10 μg/m3

increase in PM10 by location of death and by season. ___________________________________17854H6-171

907HFigure 6-21. Percent increase in mortality (all-cause [nonaccidental] and cause-specific) per 10 μg/m3

increase in PM10 by contributing causes of death. _____________________________________________1785H6-172
December 2009 xxix 

908HFigure 6-22. Summary of percent increase in all-cause (nonaccidental) mortality from recent multicity 

studies per 10 μg/m3

 increase in PM10. _____________________________________________________17856H6-174

90HFigure 6-23. Percent increase in all-cause (nonaccidental) and cause-specific mortality per 10 μg/m3

increase in the average of 0- and 1-day lagged PM2.5, combined by climatic regions. _________________1785H6-177

910HFigure 6-24. Empirical Bayes-adjusted city-specific percent increase in total (nonaccidental), 

cardiovascular, and respiratory mortality per 10 μg/m3

 increase in the average of 0- and 1-

day lagged PM2.5 by decreasing mean 24-h avg PM2.5 concentrations. _____________________________1785H6-178

91HFigure 6-25. Summary of percent increase in all-cause (nonaccidental) mortality per 10 μg/m3 increase 

in PM2.5 by various effect modifiers. _______________________________________________________17859H6-181

912HFigure 6-26. Summary of percent increase in all-cause (nonaccidental) and cause-specific mortality per 

10 μg/m3

 increase in PM2.5 from recent multicity studies.________________________________________17860H6-183

913HFigure 6-28. Percent increase in all-cause (nonaccidental) and cause-specific mortality per 10 μg/m3

increase in the average of 0- and 1-day lagged PM10-2.5, combined by climatic regions.________________1786H6-186

914HFigure 6-29. Empirical Bayes-adjusted city-specific percent increase in total (nonaccidental), 

cardiovascular, and respiratory mortality per 10 μg/m3

 increase in the average of 0- and 1-

day lagged PM10-2.5 by decreasing 98th percentile of mean 24-h avg PM10-2.5 concentrations. ___________17862H6-187

915HFigure 6-30. Summary of percent increase in total (nonaccidental) and cause-specific mortality per 

10 μg/m3

 increase in PM10-2.5 for all U.S.-, Canadian-, and international-based studies. ________________17863H6-190

916HFigure 6-31. Percent increase in PM10 risk estimates (point estimates and 95% CIs) associated with a 

5th-95th percentile increase in PM2.5 and PM2.5 chemical components. ____________________________17864H6-192

917HFigure 6-32. Sensitivity of the percent increase in PM10 risk estimates (point estimates and 95% CIs) 

associated with an interquartile increase in Ni. _______________________________________________17865H6-193

918HFigure 6-33. Percent excess risk (CI) of total (nonaccidental) mortality per IQR of concentrations. _________________1786H6-196

91HFigure 6-34. Relative risk and CI of cardiovascular mortality associated with estimated PM2.5 source 

contributions. _________________________________________________________________________1786H6-197

920HFigure 6-35. Concentration-response curves (spline model) for all-cause, cardiovascular, respiratory and 

other cause mortality from the 20 NMMAPS cities. ____________________________________________1786H6-198

921HFigure 6-36. Percent increase in the risk of death on days with PM10 concentrations in the ranges of 

15-24, 25-34, 35-44, and 45 μg/m3

 and greater, compared to a reference of days when 

concentrations were below 15 μg/m3

._______________________________________________________17869H6-199

92HFigure 6-37. Combined concentration-response curves (spline model) for all-cause, cardiovascular, and 

respiratory mortality from the 22 APHEA cities. _______________________________________________1780H6-200

923HFigure 7-1. Risk estimates for the associations of clinical outcomes with long-term exposure to ambient 

PM2.5 and PM10. ________________________________________________________________________178H7-15

924HFigure 7-2. Adjusted ORs and 95% Cls of symptoms and respiratory diseases associated with a 

decline of 10 μg/m3

 PM10 levels in Swiss Surveillance Program of Childhood Allergy and 

Respiratory Symptoms. __________________________________________________________________1782H7-23

925HFigure 7-3. Effect of PM2.5 on the association of lung function with asthma. ___________________________________1783H7-24

926HFigure 7-4. Proportion of 18-yr olds with an FEV1 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 Children’s Health Study. __________________________________________________1784H7-28

927HFigure 7-5. Percent increase in postneonatal mortality per 10 μg/m3 in PM10, comparing risk for total 

and respiratory mortality. _________________________________________________________________1785H7-58
December 2009 xxx 

928HFigure 7-6. Mortality risk estimates associated with long-term exposure to PM2.5 from the Harvard Six 

Cities Study (SCS) and the American Cancer Society Study (ACS).________________________________1786H7-85

92HFigure 7-7. Mortality risk estimates, long-term exposure to PM2.5 in recent cohort studies. ________________________178H7-86

930HFigure 7-8. Plots of the relative risk of death from cardiovascular disease from the Women’s Health 

Initiative study displaying the between-city and within-city contributions to the overall 

association between PM2.5 and cardiovascular mortality windows of exposure-effects. _________________178H7-92

931HFigure 7-9. The model-averaged estimated effect of a 10-μg/m3 increase in PM2.5 on all-cause mortality 

at different lags (in years) between exposure and death._________________________________________1789H7-93

932HFigure 7-10. Time course of relative risk of death after a sudden decrease in air pollution exposure 

during the year 2000, assuming a steady state model (solid line) and a dynamic model 

(bold dashed line). ______________________________________________________________________1780H7-94

93HFigure 7-11. Experts’ mean effect estimates and uncertainty distributions for the PM2.5 mortality 

concentration-response coefficient for a 1 μg/m3

 change in annual average PM2.5. ____________________178H7-96

934HFigure 9-1. Important factors involved in seeing a scenic vista are outlined. ____________________________________1782H9-3

935HFigure 9-2. Schematic of remote-area (top) and urban (bottom) nighttime sky visibility showing the 

effects of PM and light pollution._____________________________________________________________1783H9-4

936HFigure 9-3. Effect of relative humidity on light scattering by mixtures of ammonium nitrate and 

ammonium sulfate. _______________________________________________________________________1784H9-6

937HFigure 9-4. Estimated fractions of total particulate nitrate during each field campaign comprised of 

ammonium nitrate, reacted sea salt nitrate (shown as NaNO3), and reacted soil dust nitrate 

(shown as Ca(NO3)2).____________________________________________________________________1785H9-12

938HFigure 9-5. A scatter plot of the original IMPROVE algorithm estimated particle light scattering versus 

measured particle light scattering. __________________________________________________________1786H9-15

93HFigure 9-6. Scatter plot of the revised algorithm estimates of light scattering versus measured light 

scattering._____________________________________________________________________________178H9-15

940HFigure 9-7. IMPROVE network PM species estimated light extinction for 2000 (left) and for 2004 (right). ____________178H9-18

941HFigure 9-8. Mean estimated light extinction from PM speciation measurements for the first (top left), 

second (top right), third (bottom left), and fourth (bottom right) calendar quarters of 2004._______________1789H9-18

942HFigure 9-9. Percent contributions of ammonium nitrate (left column) and ammonium sulfate (right 

column) to particulate light extinction for each calendar quarter of 2004 (first through fourth 

quarter arranged from top to bottom). _______________________________________________________17890H9-20

943HFigure 9-10. Percent contributions of organic mass (left column) and EC (right column) to particulate 

light extinction for each calendar quarter of 2004 (first through fourth quarter arranged from 

top to bottom). _________________________________________________________________________1789H9-21

94HFigure 9-11. Percent contributions of coarse mass (left column) and fine soil (right column) to particulate 

light extinction for each calendar quarter of 2004 (first through fourth quarter arranged from 

top to bottom). _________________________________________________________________________17892H9-22

945HFigure 9-12. IMPROVE Mean PM2.5 mass concentration determined by summing the major components 

for the 2000-2004. ______________________________________________________________________17893H9-24

946HFigure 9-13. IMPROVE and CSN (STN) mean PM2.5 mass concentration determined by summing the 

major components for 2000-2004. __________________________________________________________17894H9-24

947HFigure 9-14. IMPROVE mean ammonium nitrate concentrations for 2000-2004. ________________________________17895H9-25

948HFigure 9-15. IMPROVE and CSN (STN) mean ammonium nitrate concentrations for 2000-2004. ___________________17896H9-25
December 2009 xxxi 

94HFigure 9-16. IMPROVE mean ammonium sulfate concentrations for 2000-2004. ________________________________1789H9-26

950HFigure 9-17. IMPROVE and CSN (STN) mean ammonium sulfate concentrations for 2000-2004. ___________________1789H9-26

951HFigure 9-18. IMPROVE monitored mean organic mass concentrations for 2000-2004.____________________________1789H9-28

952HFigure 9-19. IMPROVE and CSN (STN) mean organic mass concentrations for 2000-2004. _______________________1790H9-28

953HFigure 9-20. IMPROVE mean EC concentrations for 2000-2004. ____________________________________________1790H9-29

954HFigure 9-21. IMPROVE and CSN (STN) mean EC concentrations for 2000-2004. _______________________________17902H9-29

95HFigure 9-22. IMPROVE mean fine soil concentrations for 2000-2004._________________________________________17903H9-30

956HFigure 9-23. IMPROVE and CSN (STN) fine soil concentrations, 2000-2004.___________________________________17904H9-30

957HFigure 9-24. Regional and local contributions to annual average PM2.5 by particulate SO4

2–, nitrate and 

total carbon (i.e., organic plus EC) for select urban areas based on paired IMPROVE and 

CSN monitoring sites.____________________________________________________________________17905H9-32

958HFigure 9-25. IMPROVE mean coarse mass concentrations for 2000-2004._____________________________________17906H9-33

95HFigure 9-26. Ten-year (1995-2004) haze trends for the mean of the 20% best annual haze conditions._______________1790H9-34

960HFigure 9-27. Ten-year (1995-2004) haze trends for the mean of the 20% worst annual haze conditions.______________17908H9-35

961HFigure 9-28. Ten-year trends in the 80th percentile particulate SO4

2– concentration based on IMPROVE 

and CASTNet monitoring and net SO2 emissions from the National Emissions Trends 

(NET) data base by region of the U.S. _______________________________________________________1790H9-36

962HFigure 9-29. Map of 10-yr trends (1994-2003) in haze by particulate nitrate contribution to haze for the 

worst 20% annual haze periods. ___________________________________________________________1790H9-37

963HFigure 9-30. Contributions of the Pacific Coast area to the ammonium sulfate (μg/m3) at 84 remote-area 

monitoring sites in western U.S. based on trajectory regression for all sample periods from 

2000-2002 ____________________________________________________________________________179H9-39

964HFigure 9-31. Shows the IMPROVE monitoring sites in the WRAP region with at least three years of valid 

data and identifies the six sites selected to demonstrate the apportionment tools. _____________________1792H9-41

965HFigure 9-32. Particulate SO4

2– (a) and nitrate (b) source attribution by region using CAMx modeling for 

six western remote area monitoring sites_____________________________________________________1793H9-43

96HFigure 9-33. Monthly averaged model predicted organic mass concentration apportioned into primary 

PM and anthropogenic and biogenic secondary PM categories for the Olympic NP (top) 

and San Gorgonio W (bottom) monitoring sites. _______________________________________________1794H9-44

967HFigure 9-34. Monthly averaged model predicted organic mass concentration apportioned into primary 

PM and anthropogenic and biogenic secondary PM categories for the Yellowstone NP (top) 

and Grand Canyon (Hopi Point) (bottom) monitoring sites. _______________________________________1795H9-45

968HFigure 9-35. Monthly averaged model predicted organic mass concentration apportioned into primary 

PM and anthropogenic and biogenic secondary PM categories for the Badland NP (top) 

and Salt Creek W (bottom) monitoring sites. __________________________________________________1796H9-46

96HFigure 9-36. Comparison of carbon concentrations between Seattle (Puget Sound site) and Mt. Rainer 

(left) and between Phoenix and Tonto (right) showing the background site concentration 

(gray) and the urban excess concentration (black) for total, fossil and contemporary carbon 

during the summer and winter studies._______________________________________________________179H9-47

970HFigure 9-37. Average contemporary fraction of PM2.5 carbon for the summer (top) and winter (bottom), 

estimated from IMPROVE monitoring data (June 2004-February 2006) based on EC/TC 

ratios. ________________________________________________________________________________1798H9-48
December 2009 xxxii 

971HFigure 9-38. Results of the weighted emissions potential tool applied to primary OC emissions (top) and 

EC emissions (bottom) for the baseline and projected 2018 emissions inventories for 

Olympic NP. ___________________________________________________________________________179H9-50

972HFigure 9-39. Results of the weighted emissions potential tool applied to primary OC emissions (top) and 

EC emissions (bottom) for the baseline and projected 2018 emissions inventories for San 

Gorgonio W. ___________________________________________________________________________17920H9-51

973HFigure 9-40. Results of the weighted emissions potential tool applied to primary OC emissions (top) and 

EC emissions (bottom) for the baseline and projected 2018 emissions inventories for 

Yellowstone NP. ________________________________________________________________________1792H9-53

974HFigure 9-41. Results of the weighted emissions potential tool applied to primary OC emissions (top) and 

EC emissions (bottom) for the baseline and projected 2018 emissions inventories for Grand 

Canyon NP. ___________________________________________________________________________1792H9-54

975HFigure 9-42. Results of the weighted emissions potential tool applied to primary OC emissions (top) and 

EC emissions (bottom) for the baseline and projected 2018 emissions inventories for 

Badlands NP. __________________________________________________________________________17923H9-55

976HFigure 9-43. Results of the weighted emissions potential tool applied to primary OC emissions (top) and 

EC emissions (bottom) for the baseline and projected 2018 emissions inventories for Salt 

Creek W.______________________________________________________________________________17924H9-56

97HFigure 9-44. BRAVO study haze contributions for Big Bend NP, TX during a 4-mo period in 1999. __________________17925H9-58

978HFigure 9-45. Maps of spatial patterns for average annual particulate nitrate measurements (top), and for 

ammonia emissions for April 2002 from the WRAP emissions inventory (bottom). _____________________17926H9-59

97HFigure 9-46. Maps of spatial patterns of annual NO (left) and NO2 (right) emissions for 2002 from the 

WRAP emissions inventory. _______________________________________________________________1792H9-60

980HFigure 9-47. Midwest ammonia monitoring network. ______________________________________________________17928H9-61

981HFigure 9-48. Upwind transport probability fields associated with high particulate nitrate concentrations 

measured at Toronto, Canada; Boundary Water Canoe Area, MN; Shenandoah NP, VA; 

Lye Brook, VT; and Great Smoky Mountains NP, TN. ___________________________________________1792H9-62

982HFigure 9-49. Trajectory probability fields for periods with high particulate SO4

2– measured at Underhill, 

VT and Brigantine, NJ (shown as white stars) associated with oil-burning trace components 

(left) and with coal-burning trace components (right). ___________________________________________17930H9-63

983HFigure 9-50. Scatter plots of particulate SO4

2– (left) and particulate SO42– and organic mass (right) 

versus nephelometer measured particle light scattering for Acadia NP, ME. _________________________1793H9-64

984HFigure 9-51. CMAQ air quality modeling projections of visibility responses on the 20% worst haze days 

at Great Smoky Mountains NP, NC (top) and Swanquarter W, NC (bottom) to 30% 

reductions. ____________________________________________________________________________17932H9-65

985HFigure 9-52. Aerosol radiative forcing. _________________________________________________________________1793H9-76

986HFigure 9-53. Global average radiative forcing (RF) estimates and uncertainty ranges in 2005, relative to 

the pre-industrial climate. _________________________________________________________________17934H9-78

987HFigure 9-54. Probability distribution functions (PDFs) for anthropogenic aerosol and GHG RFs. ____________________17935H9-79

98HFigure 9-55. The clear-sky forcing efficiency Eτ, defined as the diurnally averaged aerosol direct 

radiative effect (W/m2

) per unit AOD at 550 nm, calculated at both TOA and the surface, for 

typical aerosol types over different geographical regions. ________________________________________17936H9-80

98HFigure 9-56. A composite of MODIS/Terra observed aerosol optical depth (at 550 nm, green light near 

the peak of human vision) and fine-mode fraction that shows spatial and seasonal 

variations of aerosol types.________________________________________________________________1793H9-87
December 2009 xxxiii 

90HFigure 9-57. Oregon fire on September 4, 2003, as observed by MISR: (a) MISR nadir view of the fire 

plume, with five patch locations numbered and wind-vectors superposed in yellow; (b) 

MISR aerosol optical depth at 558 nm; and (c) MISR stereo height without wind correction 

for the same region. _____________________________________________________________________17938H9-88

91HFigure 9-58. Global maps at 18 km resolution showing monthly average (a) AOD at 865 nm and (b) 

Ångström exponent of AOD over water surfaces only for June, 1997, derived from radiance 

measurements by the POLDER. ___________________________________________________________1793H9-89

92HFigure 9-59. A dust event that originated in the Sahara desert on 17 August 2007 and was transported 

to the Gulf of Mexico. ____________________________________________________________________17940H9-91

93HFigure 9-60. A constellation of five spacecraft that overfly the Equatorat about 1:30 p.m., the so-called 

A-Train, carries sensors having complementary capabilities, offering unprecedented 

opportunities to study aerosols from space in multiple dimensions._________________________________1794H9-92

94HFigure 9-61. Geographical coverage of active AERONET sites in 2006. _______________________________________17942H9-95

95HFigure 9-62. Comparison of the mean concentration (μg/m3) and standard deviation of the modeled 

(STEM) aerosol chemical components with shipboard measurements during INDOEX, 

ACE-Asia, and ICARTT.__________________________________________________________________17943H9-98

96HFigure 9-63. Correlations between one-hour PM2.5 surface measurements in the U.S. and southern 

Canada reported to AIRNOW and MODIS satellite AOD values for the period between 4 

July and 1 September 2009._______________________________________________________________1794H9-99

97HFigure 9-64. Location of aerosol chemical composition measurements with aerosol mass spectrometers. ___________17945H9-101

98HFigure 9-65. Scatterplots of the submicrometer POM measured during NEAQS versus A) acetylene and 

B) iso-propyl nitrate. ____________________________________________________________________17946H9-102

9HFigure 9-66. Comparison of annual mean aerosol optical depth (AOD). ______________________________________1794H9-104

10HFigure 9-67. Percentage contributions of individual aerosol components. _____________________________________17948H9-105

10HFigure 9-68. Geographical patterns of seasonally (MAM) averaged aerosol optical depth at 550 nm (left 

panel) and the diurnally averaged clear-sky aerosol direct radiative (solar spectrum) forcing 

(W/m2

) at the TOA (right panel) derived from satellite (Terra) retrievals. ____________________________1794H9-107

102HFigure 9-69. Summary of observation- and model-based (denoted as OBS and MOD, respectively) 

estimates of clear-sky, annual average DRF at the TOA and at the surface. ________________________17950H9-108

103HFigure 9-70. Scatter plots showing mean cloud drop effective radius (re) versus aerosol extinction 

coefficient (unit: km-1) for various liquid water path (LWP) bands on April 3, 1998 at ARM 

SGP site. ____________________________________________________________________________1795H9-115

104HFigure 9-71. Sampling the Arctic Haze. Pollution and smoke aerosols can travel long distances, from 

mid-latitudes to the Arctic, causing “Arctic Haze.” _____________________________________________17952H9-123

105HFigure 9-72. Global annual averaged AOD (upper panel) and aerosol mass loading (lower panel) with 

their components simulated by 15 models in AeroCom- A (excluding one model which only 

reported mass). _______________________________________________________________________17953H9-130

106HFigure 9-73. Aerosol direct radiative forcing in various climate and aerosol models._____________________________17954H9-134

107HFigure 9-74. Aerosol optical thickness and anthropogenic shortwave all-sky radiative forcing from the 

AeroCom study. _______________________________________________________________________1795H9-135

108HFigure 9-75. Radiative forcing from the cloud albedo effect (1st aerosol indirect effect) in the global 

climate models used from IPCC (2007, 092765), Chapter 2, Figure 2.14, of the IPCC AR4. ____________17956H9-136
December 2009 xxxiv 

109HFigure 9-76. Anthropogenic impact on cloud cover, planetary albedo, radiative flux at the surface (while 

holding sea surface temperatures and sea ice fixed) and surface air temperature change 

from the direct aerosol forcing (top row), the first indirect effect (second row) and the 

second indirect effect (third row). __________________________________________________________1795H9-139

10HFigure 9-77. Global average present-day short wave cloud forcing at TOA (top) and change in whole sky 

net outgoing shortwave radiation (bottom) between the present-day and pre-industrial 

simulations for each model in each experiment. ______________________________________________17958H9-140

10HFigure 9-78. Direct radiative forcing by anthropogenic aerosols in the GISS model (including sulfates, 

BC, OC and nitrates). ___________________________________________________________________1795H9-148

102HFigure 9-79. Percentage of aerosol optical depth in the GISS, left, based on Liu et al. (2006, 190422), 

provided by A. Lacis, GISS, and GFDL, right, from Ginoux et al. (2006, 190582). ____________________17960H9-151

103HFigure 9-80. Most probable aerosol altitude (in pressure, hPa) from the GISS model in January (top) and 

July (bottom). _________________________________________________________________________1796H9-153

104HFigure 9-81. Time dependence of aerosol optical thickness (left) and climate forcing (right). Note that as 

specified, the aerosol trends are all “flat” from 1990-2000. ______________________________________17962H9-155

105HFigure 9-82. Change in global mean ocean temperature (left axis) and ocean heat content (right axis) for 

the top 3000 m due to different forcings in the GFDL model._____________________________________17963H9-156

106HFigure 9-83. Visible (wavelength 0.55 μm) optical depth estimates of stratospheric SO4

2– aerosols 

formed in the aftermath of explosive volcanic eruptions that occurred between 1860 and 

2000.________________________________________________________________________________17964H9-163

107HFigure 9-84. The transfer of POPs between the major abiotic compartments of the Arctic.________________________17965H9-169

108HFigure 9-85. Relationship of plant nutrients and trace metals with vegetation.__________________________________1796H9-185

109HFigure A-1. PM2.5 monitor distribution in comparison with population density, Atlanta, GA. _______________________ 1796HA-59

102HFigure A-2. PM10 monitor distribution in comparison with population density, Atlanta, GA. _______________________ 17968HA-60

102HFigure A-3. PM2.5 monitor distribution in comparison with population density, Birmingham, AL. ___________________ 1796HA-61

102HFigure A-4. PM10 monitor distribution in comparison with population density, Birmingham, AL.____________________ 1790HA-62

1023HFigure A-5. PM2.5 monitor distribution in comparison with population density, Boston, MA. ______________________ 179HA-63

1024HFigure A-6. PM10 monitor distribution in comparison with population density, Boston, MA. _______________________ 1792HA-64

1025HFigure A-7. PM2.5 monitor distribution in comparison with population density, Chicago, IL. _______________________ 1793HA-65

1026HFigure A-8. PM10 monitor distribution in comparison with population density, Chicago, IL. _______________________ 1794HA-66

1027HFigure A-9. PM2.5 monitor distribution in comparison with population density, Denver, CO._______________________ 1795HA-67

1028HFigure A-10. PM10 monitor distribution in comparison with population density, Denver, CO. _______________________ 1796HA-68

1029HFigure A-11. PM2.5 monitor distribution in comparison with population density, Detroit, MI. ________________________ 179HA-69

103HFigure A-12. PM10 monitor distribution in comparison with population density, Detroit, MI. ________________________ 1798HA-70

103HFigure A-13. PM2.5 monitor distribution in comparison with population density, Houston, TX. ______________________ 179HA-71

1032HFigure A-14. PM10 monitor distribution in comparison with population density, Houston, TX. ______________________ 17980HA-72

103HFigure A-15. PM2.5 monitor distribution in comparison with population density, Los Angeles, CA.___________________ 1798HA-73

1034HFigure A-16. PM10 monitor distribution in comparison with population density, Los Angeles, CA. ___________________ 17982HA-74

1035HFigure A-17. PM2.5 monitor distribution in comparison with population density, New York, NY. _____________________ 17983HA-75

1036HFigure A-18. PM10 monitor distribution in comparison with population density, New York, NY. _____________________ 17984HA-76
December 2009 xxxv 

1037HFigure A-19. PM2.5 monitor distribution in comparison with population density, Philadelphia, PA. ___________________ 17985HA-77

1038HFigure A-20. PM10 monitor distribution in comparison with population density, Philadelphia, PA. ___________________ 17986HA-78

1039HFigure A-21. PM2.5 monitor distribution in comparison with population density, Phoenix, AZ. ______________________ 1798HA-79

104HFigure A-22. PM10 monitor distribution in comparison with population density, Phoenix, AZ._______________________ 1798HA-80

104HFigure A-23. PM2.5 monitor distribution in comparison with population density, Pittsburgh, PA._____________________ 1798HA-81

1042HFigure A-24. PM10 monitor distribution in comparison with population density, Pittsburgh, PA. _____________________ 1790HA-82

1043HFigure A-25. PM2.5 monitor distribution in comparison with population density, Riverside, CA. _____________________ 179HA-83

104HFigure A-26. PM10 monitor distribution in comparison with population density, Riverside, CA. _____________________ 1792HA-84

1045HFigure A-27. PM2.5 monitor distribution in comparison with population density, Seattle, WA._______________________ 1793HA-85

1046HFigure A-28. PM10 monitor distribution in comparison with population density, Seattle, WA. _______________________ 1794HA-86

1047HFigure A-29. PM2.5 monitor distribution in comparison with population density, St. Louis, MO. _____________________ 1795HA-87

1048HFigure A-30. PM10 monitor distribution in comparison with population density, St. Louis, MO.______________________ 1796HA-88

1049HFigure A-31. Three-yr avg of 24-h PM2.5 Cu concentrations measured at CSN sites across the U.S., 

2005-2007. ___________________________________________________________________________ 179HA-89

105HFigure A-32. Three-yr avg of 24-h PM2.5 Fe concentrations measured at CSN sites across the U.S., 

2005-2007 ___________________________________________________________________________ 1798HA-90

105HFigure A-33. Three-yr avg of 24-h PM2.5 Ni concentrations measured at CSN sites across the U.S., 

2005-2007 ___________________________________________________________________________ 179HA-91

1052HFigure A-34. Three-yr avg of 24-h PM2.5 Pb concentrations measured at CSN sites across the U.S., 

2005-2007 ___________________________________________________________________________ 180HA-92

1053HFigure A-35. Three-yr avg of 24-h PM2.5 Se concentrations measured at CSN sites across the U.S., 

2005-2007 ___________________________________________________________________________ 180HA-93

1054HFigure A-36. Three-yr avg of 24-h PM2.5 V concentrations measured at CSN sites across the U.S., 2005-

2007 ________________________________________________________________________________ 1802HA-94

105HFigure A-37. PM2.5 monitor distribution and major highways, Atlanta, GA. _____________________________________ 1803HA-96

1056HFigure A-38. Box plots illustrating the seasonal distribution of 24-h avg PM2.5 concentrations for Atlanta, 

GA. _________________________________________________________________________________ 1804HA-97

1057HFigure A-39. PM2.5 inter-sampler correlations as a function of distance between monitors for Atlanta, GA. ___________ 1805HA-99

1058HFigure A-40. PM2.5 monitor distribution and major highways, Birmingham, AL. ________________________________ 1806HA-100

1059HFigure A-41. Box plots illustrating the seasonal distribution of 24-h avg PM2.5 concentrations for 

Birmingham, AL. ______________________________________________________________________ 1807HA-101

106HFigure A-42. PM2.5 inter-sampler correlations as a function of distance between monitors for 

Birmingham, AL. ______________________________________________________________________ 180HA-103

106HFigure A-43. PM2.5 monitor distribution and major highways, Boston, MA.____________________________________ 1809HA-104

1062HFigure A-44. Box plots illustrating the seasonal distribution of 24-h avg PM2.5 concentrations for Boston, 

MA. ________________________________________________________________________________ 180HA-105

1063HFigure A-45. PM2.5 inter-sampler correlations as a function of distance between monitors for Boston, MA. __________ 180HA-107

1064HFigure A-46. PM2.5 monitor distribution and major highways, Chicago, IL. ____________________________________ 1802HA-108

1065HFigure A-47. Box plots illustrating the seasonal distribution of 24-h avg PM2.5 concentrations for Chicago, 

IL. _________________________________________________________________________________ 1803HA-110
December 2009 xxxvi 

106HFigure A-48. PM2.5 inter-sampler correlations as a function of distance between monitors for Chicago, IL.___________ 1804HA-113

1067HFigure A-49. PM2.5 monitor distribution and major highways, Denver, CO.____________________________________ 1805HA-114

1068HFigure A-50. Box plots illustrating the seasonal distribution of 24-h avg PM2.5 concentrations for Denver, 

CO. ________________________________________________________________________________ 1806HA-115

1069HFigure A-51. PM2.5 inter-sampler correlations as a function of distance between monitors for Denver, CO. __________ 1807HA-117

107HFigure A-52. PM2.5 monitor distribution and major highways, Detroit, MI._____________________________________ 180HA-118

107HFigure A-53. Box plots illustrating the seasonal distribution of 24-h avg PM2.5 concentrations for Detroit, 

MI._________________________________________________________________________________ 1809HA-119

1072HFigure A-54. PM2.5 inter-sampler correlations as a function of distance between monitors for Detroit, MI. ___________ 1802HA-121

1073HFigure A-55. PM2.5 monitor distribution and major highways, Houston, TX. ___________________________________ 1802HA-122

1074HFigure A-56. Box plots illustrating the seasonal distribution of 24-h avg PM2.5 concentrations for Houston, 

TX. ________________________________________________________________________________ 1802HA-123

1075HFigure A-57. PM2.5 inter-sampler correlations as a function of distance between monitors for Houston, 

TX. ________________________________________________________________________________ 18023HA-124

1076HFigure A-58. PM2.5 monitor distribution and major highways, Los Angeles, CA.________________________________ 18024HA-125

107HFigure A-59. Box plots illustrating the seasonal distribution of 24-h avg PM2.5 concentrations for Los 

Angeles, CA._________________________________________________________________________ 18025HA-126

1078HFigure A-60. PM2.5 inter-sampler correlations as a function of distance between monitors for Los 

Angeles, CA._________________________________________________________________________ 18026HA-127

1079HFigure A-61. PM2.5 monitor distribution and major highways, New York City, NY. ______________________________ 18027HA-128

108HFigure A-62. Box plots illustrating the seasonal distribution of 24-h avg PM2.5 concentrations for New 

York, NY. ___________________________________________________________________________ 1802HA-130

108HFigure A-63 PM2.5 inter-sampler correlations as a function of distance between monitors for New York, 

NY. ________________________________________________________________________________ 18029HA-133

1082HFigure A-64. PM2.5 monitor distribution and major highways, Philadelphia, PA. ________________________________ 1803HA-134

1083HFigure A-65. Box plots illustrating the seasonal distribution of 24-h avg PM2.5 concentrations for 

Philadelphia, PA. _____________________________________________________________________ 1803HA-135

1084HFigure A-66. PM2.5 inter-sampler correlations as a function of distance between monitors for 

Philadelphia, PA. _____________________________________________________________________ 18032HA-137

1085HFigure A-67. PM2.5 monitor distribution and major highways, Phoenix, AZ. ___________________________________ 1803HA-138

1086HFigure A-68. Box plots illustrating the seasonal distribution of 24-h avg PM2.5 concentrations for Phoenix, 

AZ. ________________________________________________________________________________ 18034HA-139

1087HFigure A-69. PM2.5 inter-sampler correlations as a function of distance between monitors for Phoenix, 

AZ. ________________________________________________________________________________ 18035HA-141

108HFigure A-70. PM2.5 monitor distribution and major highways, Pittsburgh, PA.__________________________________ 18036HA-142

1089HFigure A-71. Box plots illustrating the seasonal distribution of 24-h avg PM2.5 concentrations for 

Pitsburgh, PA.________________________________________________________________________ 18037HA-143

109HFigure A-72. PM2.5 inter-sampler correlations as a function of distance between monitors for Pittsburgh, 

PA. ________________________________________________________________________________ 1803HA-145

109HFigure A-73. PM2.5 monitor distribution and major highways, Riverside, CA. __________________________________ 18039HA-146
December 2009 xxxvii 

1092HFigure A-74. Box plots illustrating the seasonal distribution of 24-h avg PM2.5 concentrations for 

Riverside, CA.________________________________________________________________________ 1804HA-147

1093HFigure A-75. PM2.5 inter-sampler correlations as a function of distance between monitors for Riverside 

CA. ________________________________________________________________________________ 1804HA-149

1094HFigure A-76. PM2.5 monitor distribution and major highways, Seattle, WA.____________________________________ 18042HA-150

1095HFigure A-77. Box plots illustrating the seasonal distribution of 24-h avg PM2.5 concentrations for Seattle, 

WA.________________________________________________________________________________ 18043HA-151

1096HFigure A-78. PM2.5 inter-sampler correlations as a function of distance between monitors for Seattle, WA. __________ 1804HA-152

1097HFigure A-79. PM2.5 monitor distribution and major highways, St. Louis, MO. __________________________________ 18045HA-153

1098HFigure A-80. Box plots illustrating the seasonal distribution of 24-h avg PM2.5 concentrations for St. 

Louis, MO. __________________________________________________________________________ 18046HA-154

109HFigure A-81 PM2.5 inter-sampler correlations as a function of distance between monitors for St. Louis, 

MO.________________________________________________________________________________ 18047HA-156

10HFigure A-82. PM10 monitor distribution and major highways, Atlanta, GA. ____________________________________ 1804HA-157

10HFigure A-83. Box plots illustrating the seasonal distribution of 24-h avg PM10 concentrations for Atlanta, 

GA. ________________________________________________________________________________ 18049HA-158

102HFigure A-84. PM10 inter-sampler correlations as a function of distance between monitors for Atlanta, GA. ___________ 1805HA-160

103HFigure A-85. PM10 monitor distribution and major highways, Birmingham, AL._________________________________ 1805HA-161

104HFigure A-86. Box plots illustrating the seasonal distribution of 24-h avg PM10 concentrations for 

Birmingham, AL. ______________________________________________________________________ 18052HA-162

105HFigure A-87 PM10 inter-sampler correlations as a function of distance between monitors for Birmingham, 

AL. ________________________________________________________________________________ 18053HA-164

106HFigure A-88. PM10 monitor distribution and major highways, Boston, MA. ____________________________________ 18054HA-165

107HFigure A-89. Box plots illustrating the seasonal distribution of 24-h avg PM10 concentrations for Boston, 

MA. ________________________________________________________________________________ 1805HA-166

108HFigure A-90 PM10 inter-sampler correlations as a function of distance between monitors for Boston, MA.___________ 18056HA-167

109HFigure A-91. PM10 monitor distribution and major highways, Chicago, IL. ____________________________________ 18057HA-168

10HFigure A-92. Box plots illustrating the seasonal distribution of 24-h avg PM10 concentrations for Chicago, 

IL. _________________________________________________________________________________ 1805HA-169

1HFigure A-93. PM10 inter-sampler correlations as a function of distance between monitors for Chicago, IL. ___________ 18059HA-171

12HFigure A-94. PM10 monitor distribution and major highways, Denver, CO. ____________________________________ 1806HA-172

13HFigure A-95. Box plots illustrating the seasonal distribution of 24-h avg PM10 concentrations for Denver, 

CO. ________________________________________________________________________________ 1806HA-173

14HFigure A-96. PM10 inter-sampler correlations as a function of distance between monitors for Denver, CO.___________ 18062HA-175

15HFigure A-97. PM10 monitor distribution and major highways, Detroit, MI. _____________________________________ 18063HA-176

16HFigure A-98. Box plots illustrating the seasonal distribution of 24-h avg PM10 concentrations for Detroit, 

MI._________________________________________________________________________________ 18064HA-177

17HFigure A-99. PM10 inter-sampler correlations as a function of distance between monitors for Detroit, MI.____________ 18065HA-178

18HFigure A-100. PM10 monitor distribution and major highways, Houston, TX. ___________________________________ 1806HA-179
December 2009 xxxviii 

19HFigure A-101. Box plots illustrating the seasonal distribution of 24-h avg PM10 concentrations for Houston, 

TX. ________________________________________________________________________________ 18067HA-180

120HFigure A-102. PM10 inter-sampler correlations as a function of distance between monitors for Houston, TX. __________ 1806HA-182

12HFigure A-103. PM10 monitor distribution and major highways, Los Angeles, CA. ________________________________ 18069HA-183

12HFigure A-104. Box plots illustrating the seasonal distribution of 24-h avg PM10 concentrations for Los 

Angeles, CA._________________________________________________________________________ 1807HA-184

123HFigure A-105. PM10 inter-sampler correlations as a function of distance between monitors for Los Angeles, 

CA. ________________________________________________________________________________ 1807HA-185

124HFigure A-106. PM10 monitor distribution and major highways, New York, NY. __________________________________ 18072HA-186

125HFigure A-107. Box plots illustrating the seasonal distribution of 24-h avg PM10 concentrations for New 

York, NY. ___________________________________________________________________________ 18073HA-187

126HFigure A-108. PM10 inter-sampler correlations as a function of distance between monitors for New York, 

NY. ________________________________________________________________________________ 18074HA-188

127HFigure A-109. PM10 monitor distribution and major highways, Philadelphia, PA. ________________________________ 18075HA-189

128HFigure A-110. Box plots illustrating the seasonal distribution of 24-h avg PM10 concentrations for 

Philadelphia, PA. _____________________________________________________________________ 18076HA-190

129HFigure A-111. PM10 inter-sampler correlations as a function of distance between monitors for Philadelphia, 

PA. ________________________________________________________________________________ 1807HA-191

130HFigure A-112. PM10 monitor distribution and major highways, Phoenix, AZ.____________________________________ 1807HA-192

13HFigure A-113. Box plots illustrating the seasonal distribution of 24-h avg PM10 concentrations for Phoenix, 

AZ. ________________________________________________________________________________ 18079HA-194

132HFigure A-114. PM10 inter-sampler correlations as a function of distance between monitors for Phoenix, AZ. __________ 180HA-197

13HFigure A-115. PM10 monitor distribution and major highways, Pittsburgh, PA. __________________________________ 180HA-198

134HFigure A-116. Box plots illustrating the seasonal distribution of 24-h avg PM10 concentrations for 

Pittsburgh, PA. _______________________________________________________________________ 1802HA-199

135HFigure A-117. PM10 inter-sampler correlations as a function of distance between monitors for Pittsburgh, 

PA. ________________________________________________________________________________ 1803HA-201

136HFigure A-118. PM10 monitor distribution and major highways, Riverside, CA. __________________________________ 1804HA-202

137HFigure A-119. Box plots illustrating the seasonal distribution of 24-h avg PM10 concentrations for 

Riverside, CA.________________________________________________________________________ 1805HA-203

138HFigure A-120. PM10 inter-sampler correlations as a function of distance between monitors for Riverside, 

CA. ________________________________________________________________________________ 1806HA-205

139HFigure A-121. PM10 monitor distribution and major highways, Seattle, WA. ____________________________________ 1807HA-206

140HFigure A-122. Box plots illustrating the seasonal distribution of 24-h avg PM10 concentrations for Seattle, 

WA.________________________________________________________________________________ 180HA-207

14HFigure A-123. PM10 inter-sampler correlations as a function of distance between monitors for Seattle, WA.___________ 1809HA-208

142HFigure A-124. PM10 monitor distribution and major highways, St. Louis, MO. __________________________________ 1809HA-209

143HFigure A-125. Box plots illustrating the seasonal distribution of 24-h avg PM10 concentrations for St. Louis, 

MO.________________________________________________________________________________ 1809HA-210

14HFigure A-126. PM10 inter-sampler correlations as a function of distance between monitors for St. Louis, 

MO.________________________________________________________________________________ 18092HA-212
December 2009 xxxix 

145HFigure A-127. Seasonally averaged PM2.5 speciation data for 2005-2007 for a) annual, b) spring, 

c) summer, d) fall and e) winter derived using the SANDWICH method in Atlanta, GA. _______________ 18093HA-213

146HFigure A-128. Seasonally averaged PM2.5 speciation data for 2005-2007 for a) annual, b) spring, 

c) summer, d) fall and e) winter derived using the SANDWICH method in Birmingham, AL.____________ 18094HA-214

147HFigure A-129. Seasonally averaged PM2.5 speciation data for 2005-2007 for a) annual, b) spring, 

c) summer, d) fall and e) winter derived using the SANDWICH method in Boston, MA. _______________ 18095HA-215

148HFigure A-130. Seasonally averaged PM2.5 speciation data for 2005-2007 for a) annual, b) spring, 

c) summer, d) fall and e) winter derived using the SANDWICH method in Chicago, IL. _______________ 18096HA-216

149HFigure A-131. Seasonally averaged PM2.5 speciation data for 2005-2007 for a) annual, b) spring, 

c) summer, d) fall and e) winter, derived using the SANDWICH method in Denver, CO. ______________ 18097HA-217

150HFigure A-132. Seasonally averaged PM2.5 speciation data for 2005-2007 for a) annual, b) spring, 

c) summer, d) fall and e) winter derived using the SANDWICH method in Detroit, MI. ________________ 1809HA-218

15HFigure A-133. Seasonally averaged PM2.5 speciation data for 2005-2007 for a) annual, b) spring, 

c) summer, d) fall and e) winter derived using the SANDWICH method in Houston, TX. ______________ 1809HA-219

152HFigure A-134. Seasonally averaged PM2.5 speciation data for 2005-2007 for a) annual, b) spring, 

c) summer, d) fall and e) winter derived using the SANDWICH method in Los Angeles, CA. ___________ 180HA-220

153HFigure A-135. Seasonally averaged PM2.5 speciation data for 2005-2007 for a) annual, b) spring, 

c) summer, d) fall and e) winter derived using the SANDWICH method in New York, NY. _____________ 180HA-221

154HFigure A-136. Seasonally averaged PM2.5 speciation data for 2005-2007 for a) annual, b) spring, 

c) summer, d) fall and e) winter derived using the SANDWICH method in Philadelphia, PA. ___________ 1802HA-222

15HFigure A-137. Seasonally averaged PM2.5 speciation data for 2005-2007 for a) annual, b) spring, 

c) summer, d) fall and e) winter derived using the SANDWICH method in Phoenix, AZ._______________ 1803HA-223

156HFigure A-138. Seasonally averaged PM2.5 speciation data for 2005-2007 for a) annual, b) spring, 

c) summer, d) fall and e) winter derived using the SANDWICH method in Pittsburgh, PA. _____________ 1804HA-224

157HFigure A-139. Seasonally averaged PM2.5 speciation data for 2005-2007 for a) annual, b) spring, 

c) summer, d) fall and e) winter derived using the SANDWICH method in Riverside, CA. _____________ 1805HA-225

158HFigure A-140. Seasonally averaged PM2.5 speciation data for 2005-2007 for a) annual, b) spring, 

c) summer, d) fall and e) winter derived using the SANDWICH method in Seattle, WA. _______________ 1806HA-226

159HFigure A-141. Seasonally averaged PM2.5 speciation data for 2005-2007 for a) annual, b) spring, 

c) summer, d) fall and e) winter derived using the SANDWICH method in St. Louis, MO. _____________ 1807HA-227

160HFigure A-142. Seasonal patterns in PM2.5 chemical composition from city-wide monthly average values for 

Atlanta, GA, 2005-2007.________________________________________________________________ 180HA-228

16HFigure A-143. Seasonal patterns in PM2.5 chemical composition from city-wide monthly average values for 

Birmingham, AL, 2005-2007. ____________________________________________________________ 1809HA-228

162HFigure A-144. Seasonal patterns in PM2.5 chemical composition from city-wide monthly average values for 

Boston, MA, 2005-2007.________________________________________________________________ 180HA-229

163HFigure A-145. Seasonal patterns in PM2.5 chemical composition from city-wide monthly average values for 

Chicago, IL, 2005-2007. ________________________________________________________________ 18HA-229

164HFigure A-146. Seasonal patterns in PM2.5 chemical composition from city-wide monthly average values for 

Denver, CO, 2005-2007. _______________________________________________________________ 182HA-230

165HFigure A-147. Seasonal patterns in PM2.5 chemical composition from city-wide monthly average values for 

Detroit, MI, 2005-2007._________________________________________________________________ 183HA-230
December 2009 xl 

16HFigure A-148. Seasonal patterns in PM2.5 chemical composition from city-wide monthly average values for 

Houston, TX, 2005-2007. _______________________________________________________________ 184HA-231

167HFigure A-149. Seasonal patterns in PM2.5 chemical composition from city-wide monthly average values for 

Los Angeles, CA, 2005-2007.____________________________________________________________ 185HA-231

168HFigure A-150. Seasonal patterns in PM2.5 chemical composition from city-wide monthly average values for 

New York, NY, 2005-2007.______________________________________________________________ 186HA-232

169HFigure A-151. Seasonal patterns in PM2.5 chemical composition from city-wide monthly average values for 

Philadelphia, PA, 2005-2007.____________________________________________________________ 187HA-232

170HFigure A-152. Seasonal patterns in PM2.5 chemical composition from city-wide monthly average values for 

Phoenix, AZ, 2005-2007. _______________________________________________________________ 18HA-233

17HFigure A-153. Seasonal patterns in PM2.5 chemical composition from city-wide monthly average values for 

Pittsburgh, PA, 2005-2007. _____________________________________________________________ 189HA-233

172HFigure A-154. Seasonal patterns in PM2.5 chemical composition from city-wide monthly average values for 

Riverside, CA, 2005-2007. ______________________________________________________________ 1820HA-234

173HFigure A-155. Seasonal patterns in PM2.5 chemical composition from city-wide monthly average values for 

Seattle, WA, 2005-2007. _______________________________________________________________ 182HA-234

174HFigure A-156. Seasonal patterns in PM2.5 chemical composition from city-wide monthly average values for 

St. Louis, MO, 2005-2007. ______________________________________________________________ 182HA-235

175HFigure A-157. Diel plots generated from all available hourly FRM-like PM2.5 data, stratified by weekday 

(left) and weekend (right), in Atlanta, GA. __________________________________________________ 1823HA-235

176HFigure A-158. Diel plots generated from all available hourly FRM-like PM2.5 data, stratified by weekday 

(left) and weekend (right), in Chicago, IL.___________________________________________________ 1824HA-236

17HFigure A-159. Diel plots generated from all available hourly FRM-like PM2.5 data, stratified by weekday 

(left) and weekend (right), in Houston, TX.__________________________________________________ 1825HA-236

178HFigure A-160. Diel plots generated from all available hourly FRM-like PM2.5 data, stratified by weekday 

(left) and weekend (right), in New York, NY. ________________________________________________ 1826HA-237

179HFigure A-161. Diel plots generated from all available hourly FRM-like PM2.5 data, stratified by weekday 

(left) and weekend (right), in Pittsburgh, PA. ________________________________________________ 1827HA-237

180HFigure A-162. Diel plots generated from all available hourly FRM-like PM2.5 data, stratified by weekday 

(left) and weekend (right), in Seattle, WA. __________________________________________________ 182HA-238

18HFigure A-163. Diel plots generated from all available hourly FRM-like PM2.5 data, stratified by weekday 

(left) and weekend (right), in St. Louis, MO._________________________________________________ 1829HA-238

182HFigure A-164. Diel plot generated from all available hourly FRM/FEM PM10 data, stratified by weekday 

(left) and weekend (right), in Atlanta, GA. __________________________________________________ 1830HA-239

183HFigure A-165. Diel plot generated from all available hourly FRM/FEM PM10 data, stratified by weekday 

(left) and weekend (right), in Chicago, IL.___________________________________________________ 183HA-239

184HFigure A-166. Diel plot generated from all available hourly FRM/FEM PM10 data, stratified by weekday 

(left) and weekend (right), in Denver, CO. __________________________________________________ 1832HA-240

185HFigure A-167. Diel plot generated from all available hourly FRM/FEM PM10 data, stratified by weekday 

(left) and weekend (right), in Detroit, MI. ___________________________________________________ 183HA-240

186HFigure A-168. Diel plot generated from all available hourly FRM/FEM PM10 data, stratified by weekday 

(left) and weekend (right), in Los Angeles, CA. ______________________________________________ 1834HA-241
December 2009 xli 

187HFigure A-169. Diel plot generated from all available hourly FRM/FEM PM10 data, stratified by weekday 

(left) and weekend (right), in Philadelphia, PA. ______________________________________________ 1835HA-241

18HFigure A-170. Diel plot generated from all available hourly FRM/FEM PM10 data, stratified by weekday 

(left) and weekend (right), in Phoenix, AZ. __________________________________________________ 1836HA-242

189HFigure A-171. Diel plot generated from all available hourly FRM/FEM PM10 data, stratified by weekday 

(left) and weekend (right), in Pittsburgh, PA. ________________________________________________ 1837HA-242

190HFigure A-172. Diel plot generated from all available hourly FRM/FEM PM10 data, stratified by weekday 

(left) and weekend (right), in Riverside, CA._________________________________________________ 183HA-243

19HFigure A-173. Diel plot generated from all available hourly FRM/FEM PM10 data, stratified by weekday 

(left) and weekend (right), in Seattle, WA. __________________________________________________ 1839HA-243

192HFigure A-174. Diel plot generated from all available hourly FRM/FEM PM10 data, stratified by weekday 

(left) and weekend (right), in St. Louis, MO._________________________________________________ 1840HA-244

193HFigure A-175. Correlations between 24-h PM2.5 and co-located 24-h avg PM10, PM10-2.5, SO2, NO2 and CO 

and daily maximum 8-h avg O3 for Atlanta, GA, stratified by season (2005-2007). ___________________ 184HA-245

194HFigure A-176. Correlations between 24-h PM2.5 and co-located 24-h avg PM10, PM10-2.5, SO2, NO2 and CO 

and daily maximum 8-h avg O3 for Birmingham, AL, stratified by season (2005-2007). _______________ 1842HA-246

195HFigure A-177. Correlations between 24-h PM2.5 and co-located 24-h avg PM10, PM10-2.5, SO2, NO2 and CO 

and daily maximum 8-h avg O3 for Boston, MA, stratified by season (2005-2007).___________________ 1843HA-247

196HFigure A-178. Correlations between 24-h PM2.5 and co-located 24-h avg PM10, PM10-2.5, SO2, NO2 and CO 

and daily maximum 8-h avg O3 for Chicago, IL, stratified by season (2005-2007). ___________________ 184HA-248

197HFigure A-179. Correlations between 24-h PM2.5 and co-located 24-h avg PM10, PM10-2.5, SO2, NO2 and CO 

and daily maximum 8-h avg O3 for Denver, CO, stratified by season (2005-2007).___________________ 1845HA-249

198HFigure A-180. Correlations between 24-h PM2.5 and co-located 24-h avg PM10, PM10-2.5, SO2, NO2 and CO 

and daily maximum 8-h avg O3 for Detroit, MI, stratified by season (2005-2007). ____________________ 1846HA-250

19HFigure A-181. Correlations between 24-h PM2.5 and co-located 24-h avg PM10, PM10-2.5, SO2, NO2 and CO 

and daily maximum 8-h avg O3 for Houston, TX, stratified by season (2005-2007). __________________ 1847HA-251

120HFigure A-182. Correlations between 24-h PM2.5 and co-located 24-h avg PM10, PM10-2.5, SO2, NO2 and CO 

and daily maximum 8-h avg O3 for Los Angeles, CA, stratified by season (2005-2007)._______________ 184HA-252

120HFigure A-183. Correlations between 24-h PM2.5 and co-located 24-h avg PM10, PM10-2.5, SO2, NO2 and CO 

and daily maximum 8-h avg O3 for New York, NY, stratified by season (2005-2007). _________________ 1849HA-253

120HFigure A-184. Correlations between 24-h PM2.5 and co-located 24-h avg PM10, PM10-2.5, SO2, NO2 and CO 

and daily maximum 8-h avg O3 for Philadelphia, PA, stratified by season (2005-2007). _______________ 1850HA-254

1203HFigure A-185. Correlations between 24-h PM2.5 and co-located 24-h avg PM10, PM10-2.5, SO2, NO2 and CO 

and daily maximum 8-h avg O3 for Phoenix, AZ, stratified by season (2005-2007). __________________ 185HA-255

1204HFigure A-186. Correlations between 24-h PM2.5 and co-located 24-h avg PM10, PM10-2.5, SO2, NO2 and CO 

and daily maximum 8-h avg O3 for Pittsburgh, PA, stratified by season (2005-2007)._________________ 1852HA-256

1205HFigure A-187. Correlations between 24-h PM2.5 and co-located 24-h avg PM10, PM10-2.5, SO2, NO2 and CO 

and daily maximum 8-h avg O3 for Riverside, CA, stratified by season (2005-2007). _________________ 1853HA-257

1206HFigure A-188. Correlations between 24-h PM2.5 and co-located 24-h avg PM10, PM10-2.5, SO2, NO2 and CO 

and daily maximum 8-h avg O3 for St. Louis, MO, stratified by season (2005-2007). _________________ 1854HA-258

1207HFigure A-189. Correlations between 24-h PM10 and co-located 24-h avg PM2.5, PM10-2.5, SO2, NO2 and CO 

and daily maximum 8-h avg O3 for Atlanta, GA, stratified by season (2005-2007). ___________________ 185HA-259
December 2009 xlii 

1208HFigure A-190. Correlations between 24-h PM10 and co-located 24-h avg PM2.5, PM10-2.5, SO2, NO2 and CO 

and daily maximum 8-h avg O3 for Birmingham, AL, stratified by season (2005-2007). _______________ 1856HA-260

1209HFigure A-191. Correlations between 24-h PM10 and co-located 24-h avg PM2.5, PM10-2.5, SO2, NO2 and CO 

and daily maximum 8-h avg O3 for Boston, MA, stratified by season (2005-2007).___________________ 1857HA-261

120HFigure A-192. Correlations between 24-h PM10 and co-located 24-h avg PM2.5, PM10-2.5, SO2, NO2 and CO 

and daily maximum 8-h avg O3 for Chicago, IL, stratified by season (2005-2007). ___________________ 185HA-262

12HFigure A-193. Correlations between 24-h PM10 and co-located 24-h avg PM2.5, PM10-2.5, SO2, NO2 and CO 

and daily maximum 8-h avg O3 for Denver, CO, stratified by season (2005-2007).___________________ 1859HA-263

12HFigure A-194. Correlations between 24-h PM10 and co-located 24-h avg PM2.5, PM10-2.5, SO2, NO2 and CO 

and daily maximum 8-h avg O3 for Detroit, MI, stratified by season (2005-2007).____________________ 1860HA-264

123HFigure A-195. Correlations between 24-h PM10 and co-located 24-h avg PM2.5, PM10-2.5, SO2, NO2 and CO 

and daily maximum 8-h avg O3 for Houston, TX, stratified by season (2005-2007). __________________ 186HA-265

124HFigure A-196. Correlations between 24-h PM10 and co-located 24-h avg PM2.5, PM10-2.5, SO2, NO2 and CO 

and daily maximum 8-h avg O3 for Los Angeles, CA, stratified by season (2005-2007)._______________ 1862HA-266

125HFigure A-197. Correlations between 24-h PM10 and co-located 24-h avg PM2.5, PM10-2.5, SO2, NO2 and CO 

and daily maximum 8-h avg O3 for New York, NY, stratified by season (2005-2007)._________________ 1863HA-267

126HFigure A-198. Correlations between 24-h PM10 and co-located 24-h avg PM2.5, PM10-2.5, SO2, NO2 and CO 

and daily maximum 8-h avg O3 for Philadelphia, PA, stratified by season (2005-2007). _______________ 1864HA-268

127HFigure A-199. Correlations between 24-h PM10 and co-located 24-h avg PM2.5, PM10-2.5, SO2, NO2 and CO 

and daily maximum 8-h avg O3 for Phoenix, AZ, stratified by season (2005-2007). __________________ 1865HA-269

128HFigure A-200. Correlations between 24-h PM10 and co-located 24-h avg PM2.5, PM10-2.5, SO2, NO2 and CO 

and daily maximum 8-h avg O3 for Pittsburgh, PA, stratified by season (2005-2007)._________________ 186HA-270

129HFigure A-201. Correlations between 24-h PM10 and co-located 24-h avg PM2.5, PM10-2.5, SO2, NO2 and CO 

and daily maximum 8-h avg O3 for Riverside, CA, stratified by season (2005-2007). _________________ 1867HA-271

120HFigure A-202. Correlations between 24-h PM10 and co-located 24-h avg PM2.5, PM10-2.5, SO2, NO2 and CO 

and daily maximum 8-h avg O3 for St. Louis, MO, stratified by season (2005-2007). _________________ 186HA-272
December 2009 xliii 

PM ISA Project Team 

Executive Direction 

Dr. John Vandenberg (Director)—National Center for Environmental Assessment-RTP Division, U.S. 

Environmental Protection Agency, Research Triangle Park, NC 

Ms. Debra Walsh (Deputy Director)—National Center for Environmental Assessment-RTP Division, U.S. 

Environmental Protection Agency, Research Triangle Park, NC 

Dr. Mary Ross (Branch Chief)—National Center for Environmental Assessment, U.S. Environmental 

Protection Agency, Research Triangle Park, NC

Scientific Staff 

Dr. Lindsay Wichers Stanek (PM 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 (now at Institute for Water Resources, U.S. Army Corps of 

Engineers, Washington, D.C.) 

Dr. Christal Bowman—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 

Mr. Allen Davis—National Center for Environmental Assessment, U.S. Environmental Protection 

Agency, Research Triangle Park, NC 

Dr. Jean-Jacques Dubois—National Center for Environmental Assessment, U.S. Environmental 

Protection Agency, Research Triangle Park, NC 

Dr. Steven J. Dutton—National Center for Environmental Assessment, U.S. Environmental Protection 

Agency, Research Triangle Park, NC 

Dr. Erin Hines—National Center for Environmental Assessment, U.S. Environmental Protection Agency, 

Research Triangle Park, NC 

Dr. Douglas Johns—National Center for Environmental Assessment, U.S. Environmental Protection 

Agency, Research Triangle Park, NC 

Dr. Ellen Kirrane—National Center for Environmental Assessment, U.S. Environmental Protection 

Agency, Research Triangle Park, NC 

Dr. Dennis Kotchmar—National Center for Environmental Assessment, U.S. Environmental Protection 

Agency, Research Triangle Park, NC 

Dr. Thomas Long—National Center for Environmental Assessment, U.S. Environmental Protection 

Agency, Research Triangle Park, NC 
December 2009 xliv 

Dr. Thomas Luben—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. Kristopher Novak—National Center for Environmental Assessment, U.S. Environmental Protection 

Agency, Research Triangle Park, NC 

Dr. Joseph Pinto—National Center for Environmental Assessment, U.S. Environmental Protection 

Agency, Research Triangle Park, NC 

Dr. Jennifer Richmond-Bryant—National Center for Environmental Assessment, U.S. Environmental 

Protection Agency, Research Triangle Park, NC 

Dr. Mary Ross—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, NC 

Dr. David Svendsgaard—National Center for Environmental Assessment, U.S. Environmental Protection 

Agency, Research Triangle Park, NC 

Dr. Lisa Vinikoor—National Center for Environmental Assessment, U.S. Environmental Protection 

Agency, Research Triangle Park, NC 

Dr. William Wilson—National Center for Environmental Assessment, U.S. Environmental Protection 

Agency, Research Triangle Park, NC 

Dr. Lori White—National Center for Environmental Assessment, U.S. Environmental Protection Agency, 

Research Triangle Park, NC (now at National Institute for Environmental Health Sciences, Research 

Triangle Park, NC) 

Technical Support Staff 

Mattie Arnold—Senior Environmental Employee Program, National Center for Environmental 

Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC 

Laeda Baston—Senior Environmental Employee Program, National Center for Environmental 

Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC 

Kimberly Branch—Student Services Contractor, National Center for Environmental Assessment, U.S. 

Environmental Protection Agency, Research Triangle Park, NC 

Ken Breito—Senior Environmental Employee Program, National Center for Environmental Assessment, 

U.S. Environmental Protection Agency, Research Triangle Park, NC 

Eleanor Jamison—Senior Environmental Employee Program, National Center for Environmental 

Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC 

Ryan Jones—Oak Ridge Institute for Science and Education, at National Center for Environmental 

Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC 

Erica Lee—Oak Ridge Institute for Science and Education, at National Center for Environmental 

Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC 

Barbara Liljequist—Senior Environmental Employee Program, National Center for Environmental 

Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC 
December 2009 xlv 

Ellen Lorang—National Center for Environmental Assessment, U.S. Environmental Protection Agency, 

Research Triangle Park, NC 

Kelsey Matson—Student Services Contractor, National Center for Environmental Assessment, U.S. 

Environmental Protection Agency, Research Triangle Park, NC 

Sandy Pham—Student Services Contractor, National Center for Environmental Assessment, U.S. 

Environmental Protection Agency, Research Triangle Park, NC 

Olivia Phillpott—Senior Environmental Employee Program, National Center for Environmental 

Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC 

Deborah Wales—National Center for Environmental Assessment, U.S. Environmental Protection Agency, 

Research Triangle Park, NC 

Erica Wilson—Oak Ridge Institute for Science and Education, at National Center for Environmental 

Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC 

Richard Wilson—National Center for Environmental Assessment, U.S. Environmental Protection Agency, 

Research Triangle Park, NC 

Barbara Wright—Senior Environmental Employee Program, National Center for Environmental 

Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC 
December 2009 xlvi 

Authors, Contributors, Reviewers 

AUTHORS 

Dr. Lindsay Wichers Stanek (PM 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 (now at Institute for Water Resources, U.S. Army Corps of 

Engineers, Washington, D.C) 

Dr. Christal Bowman—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 

Mr. Allen Davis—National Center for Environmental Assessment, U.S. Environmental Protection 

Agency, Research Triangle Park, NC 

Dr. Jean-Jacques Dubois—National Center for Environmental Assessment, U.S. Environmental 

Protection Agency, Research Triangle Park, NC 

Dr. Steven J. Dutton—National Center for Environmental Assessment, U.S. Environmental Protection 

Agency, Research Triangle Park, NC 

Dr. Tara Greaver—National Center for Environmental Assessment, U.S. Environmental Protection 

Agency, Research Triangle Park, NC 

Dr. Erin Hines—National Center for Environmental Assessment, U.S. Environmental Protection Agency, 

Research Triangle Park, NC 

Dr. Douglas Johns—National Center for Environmental Assessment, U.S. Environmental Protection 

Agency, Research Triangle Park, NC 

Dr. Ellen Kirrane—National Center for Environmental Assessment, U.S. Environmental Protection 

Agency, Research Triangle Park, NC 

Dr. Dennis Kotchmar—National Center for Environmental Assessment, U.S. Environmental Protection 

Agency, Research Triangle Park, NC 

Dr. Thomas Long—National Center for Environmental Assessment, U.S. Environmental Protection 

Agency, Research Triangle Park, NC 

Dr. Thomas Luben—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. Kristopher Novak—National Center for Environmental Assessment, U.S. Environmental Protection 

Agency, Research Triangle Park, NC 

Dr. Joseph Pinto—National Center for Environmental Assessment, U.S. Environmental Protection 

Agency, Research Triangle Park, NC 
December 2009 xlvii 

Dr. Jennifer Richmond-Bryant—National Center for Environmental Assessment, U.S. Environmental 

Protection Agency, Research Triangle Park, NC 

Dr. Mary Ross—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, NC 

Dr. Timothy J. Sullivan—E&S Environmental Chemistry, Inc., Corvallis, OR 

Dr. David Svendsgaard—National Center for Environmental Assessment, U.S. Environmental Protection 

Agency, Research Triangle Park, NC 

Dr. Lisa Vinikoor—National Center for Environmental Assessment, U.S. Environmental Protection 

Agency, Research Triangle Park, NC 

Dr. William Wilson—National Center for Environmental Assessment, U.S. Environmental Protection 

Agency, Research Triangle Park, NC 

Dr. Lori White— National Center for Environmental Assessment, U.S. Environmental Protection Agency, 

Research Triangle Park, NC (now at National Institute for Environmental Health Sciences, Research 

Triangle Park, NC) 

Dr. Christy Avery—University of North Carolina, Chapel Hill, NC 

Dr. Kathleen Belanger —Center for Perinatal, Pediatric and Environmental Epidemiology, Yale 

University, New Haven, CT 

Dr. Michelle Bell—School of Forestry & Environmental Studies, Yale University, New Haven, CT 

Dr. William D. Bennett—Center for Environmental Medicine, Asthma and Lung Biology, University of 

North Carolina, Chapel Hill, NC 

Dr. Matthew J. Campen—Lovelace Respiratory Research Institute, Albuquerque, NM 

Dr. Leland B. Deck— Stratus Consulting, Inc., Washington, DC 

Dr. Janneane F. Gent—Center for Perinatal, Pediatric and Environmental Epidemiology, Yale University, 

New Haven, CT 

Dr. Yuh-Chin Tony Huang—Department of Medicine, Division of Pulmonary Medicine, Duke University 

Medical Center, Durham, NC 

Dr. Kazuhiko Ito—Nelson Institute of Environmental Medicine, NYU School of Medicine, Tuxedo, NY 

Mr. Marc Jackson—Integrated Laboratory Systems, Inc., Research Triangle Park, NC 

Dr. Michael Kleinman—Department of Community and Environmental Medicine, University of 

California, Irvine 

Dr. Sergey Napelenok—National Exposure Research Laboratory, U.S. Environmental Protection Agency, 

Research Triangle Park, NC 

Dr. Marc Pitchford—National Oceanic and Atmospheric Administration, Las Vegas, NV 

Dr. Les Recio—Genetic Toxicology Division, Integrated Laboratory Systems, Inc., Research Triangle 

Park, NC 

Dr. David Quincy Rich—Department of Epidemiology, University of Medicine and Dentistry of New 

Jersey, Piscataway, NJ 

Dr. Timothy Sullivan— E&S Environmental Chemistry, Inc., Corvallis, OR 

Dr. George Thurston—Department of Environmental Medicine, NYU, Tuxedo, NY 
December 2009 xlviii 

Dr. Gregory Wellenius—Cardiovascular Epidemiology Research Unit, Beth Israel Deaconess Medical 

Center, Boston, MA 

Dr. Eric Whitsel—Departments of Epidemiology and Medicine, University of North Carolina, Chapel 

Hill, NC

CONTRIBUTORS 

Dr. Philip Bromberg—Department of Medicine, University of North Carolina, Chapel Hill, NC 

Mr. Michael Burr—National Center for Environmental Assessment, U.S. Environmental Protection 

Agency, Research Triangle Park, NC 

Mr. Turhan Carroll—Student Services Contractor, National Center for Environmental Assessment, U.S. 

Environmental Protection Agency, Research Triangle Park, NC 

Ms. Rosana Datti—Student Services Contractor, National Center for Environmental Assessment, U.S. 

Environmental Protection Agency, Research Triangle Park, NC 

Mr. Neil Frank—Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, 

Research Triangle Park, NC 

Mr. Jonathan Krug—Student Services Contractor, National Center for Environmental Assessment, U.S. 

Environmental Protection Agency, Research Triangle Park, NC 

Ms. Katie Lane—Student Services Contractor, National Center for Environmental Assessment, U.S. 

Environmental Protection Agency, Research Triangle Park, NC 

Mr. Phil Lorang—Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, 

Research Triangle Park, NC 

Ms. Christina Miller—National Center for Environmental Assessment, U.S. Environmental Protection 

Agency, Research Triangle Park, NC 

Ms. Irina Mordukhovich—Oak Ridge Institute for Science and Education, at National Center for 

Environmental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC 

Dr. Elizabeth Oesterling Owens—National Center for Environmental Assessment, U.S. Environmental 

Protection Agency, Research Triangle Park, NC 

Dr. Adam Reff—Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, 

Research Triangle Park, NC 

Ms. Victoria Sandiford— Office of Air Quality Planning and Standards, U.S. Environmental Protection 

Agency, Research Triangle Park, NC 

Dr. Mark Schmidt—Office of Air Quality Planning and Standards, U.S. Environmental Protection 

Agency, Research Triangle Park, NC 

Ms. Angelina Schultz—Student Services Contractor, National Center for Environmental Assessment, U.S. 

Environmental Protection Agency, Research Triangle Park, NC 

Ms. Kirsten Simmons—Student Services Contractor, National Center for Environmental Assessment, 

U.S. Environmental Protection Agency, Research Triangle Park, NC 

Ms. Genee Smith—Oak Ridge Institute for Science and Education, at National Center for Environmental 

Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC 

Mr. Kurt Susdorf—Student Services Contractor, National Center for Environmental Assessment, U.S. 

Environmental Protection Agency, Research Triangle Park, NC 

Dr. Barbara Turpin—Department of Environmental Sciences, Rutgers University, New Brunswick, NJ 
December 2009 xlix 

Ms. Lauren Tuttle—Student Services Contractor, National Center for Environmental Assessment, U.S. 

Environmental Protection Agency, Research Triangle Park, NC 

Ms. Rebecca Yang—Student Services Contractor, National Center for Environmental Assessment, U.S. 

Environmental Protection Agency, Research Triangle Park, NC

PEER REVIEWERS 

Dr. Sara Dubowsky Adar, Department of Epidemiology, University of Washington, Seattle, WA 

Mr. Chad Bailey, Office of Transportation and Air Quality, Ann Arbor, MI 

Mr. Richard Baldauf, Office of Transportation and Air Quality, Ann Arbor, MI 

Dr. Prakash Bhave, National Exposure Research Laboratory, U.S. Environmental Protection Agency, 

Research Triangle Park, NC 

Mr. George Bowker, Office of Atmospheric Programs, U.S. Environmental Protection Agency, 

Washington, D.C. 

Dr. Judith Chow, Division of Atmospheric Sciences, Desert Research Institute, Reno, NV 

Dr. Dan Costa, U.S. Environmental Protection Agency, Research Triangle Park, NC 

Dr. Ila Cote, National Center for Environmental Assessment, U.S. Environmental Protection Agency, 

Research Triangle Park, NC 

Dr. Robert Devlin, National Health and Environmental Effects Research Laboratory, U.S. Environmental 

Protection Agency, Research Triangle Park, NC 

Dr. David DeMarini, National Health and Environmental Effects Research Laboratory, U.S. 

Environmental Protection Agency, Research Triangle Park, NC 

Dr. Neil Donahue, Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA 

Dr. Aimen Farraj, National Health and Environmental Effects Research Laboratory, U.S. Environmental 

Protection Agency, Research Triangle Park, NC 

Dr. Mark Frampton, Department of Environmental Medicine, University of Rochester Medical Center, 

Rochester, NY 

Mr. Neil Frank, Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, 

Research Triangle Park, NC 

Mr. Tyler Fox, Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, 

Research Triangle Park, NC 

Dr. Jim Gauderman, Department of Environmental Medicine, Department of Preventive Medicine, 

University of Southern California, Los Angeles, CA 

Dr. Barbara Glenn, National Center for Environmental Research, U.S. Environmental Protection Agency, 

Washington, D.C. 

Dr. Terry Gordon, School of Medicine, New York University, Tuxedo, NY 

Mr. Tim Hanley, Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, 

Research Triangle Park, NC 

Dr. Jack Harkema, Department of Pathobiology and Diagnostic Investigation, Michigan State University, 

East Lansing, MI 

Ms. Beth Hassett-Sipple, Office of Air Quality Planning and Standards, U.S. Environmental Protection 

Agency, Research Triangle Park, NC 
December 2009 l 

Dr. Amy Herring, Department of Biostatistics, University of North Carolina, Chapel Hill, NC 

Dr. Israel Jirak, Department of Meteorology, Embry-Riddle Aeronautical University, Prescott, AZ 

Dr. Mike Kleeman, Department of Civil and Environmental Engineering, University of California, Davis, 

CA 

Dr. Petros Koutrakis, Exposure, Epidemiology and Risk Program, Harvard School of Public Health, 

Boston, MA 

Dr. Sagar Krupa, Department of Plant Pathology, University of Minnesota, St. Paul, MN 

Mr. John Langstaff, Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, 

Research Triangle Park, NC 

Dr. Meredith Lassiter, Office of Air Quality Planning and Standards, U.S. Environmental Protection 

Agency, Research Triangle Park, NC 

Mr. Phil Lorang, Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, 

Research Triangle Park, NC 

Dr. Karen Martin, Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, 

Research Triangle Park, NC 

Ms. Connie Meacham, National Center for Environmental Assessment, U.S. Environmental Protection 

Agency, Research Triangle Park, NC 

Mr. Tom Pace, Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, 

Research Triangle Park, NC 

Dr. Jennifer Peel, Department of Environmental and Radiological Health Sciences, College of Veterinary 

Medicine and Biomedical Sciences, Colorado State University, Fort Collins, CO 

Dr. Zackary Pekar, Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, 

Research Triangle Park, NC 

Mr. Rob Pinder, National Exposure Research Laboratory, U.S. Environmental Protection Agency, 

Research Triangle Park, NC 

Mr. Norm Possiel, Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, 

Research Triangle Park, NC 

Dr. Sanjay Rajagopalan, Division of Cardiovascular Medicine, Ohio State University, Columbus, OH 

Dr. Pradeep Rajan, Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, 

Research Triangle Park, NC 

Mr. Venkatesh Rao, Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, 

Research Triangle Park, NC 

Ms. Joann Rice, Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, 

Research Triangle Park, NC 

Mr. Harvey Richmond, Office of Air Quality Planning and Standards, U.S. Environmental Protection 

Agency, Research Triangle Park, NC 

Ms. Victoria Sandiford, Office of Air Quality Planning and Standards, U.S. Environmental Protection 

Agency, Research Triangle Park, NC 

Dr. Stefanie Sarnat, Department of Environmental and Occupational Health, Emory University, Atlanta, 

GA 

Dr. Frances Silverman, Gage Occupational and Environmental Health, University of Toronto, Toronto, 

ON 
December 2009 li 

Mr. Steven Silverman, Office of General Council, U.S. Environmental Protection Agency, Washington, 

D.C. 

Dr. Barbara Turpin, Department of Environmental Sciences, Rutgers University, New Brunswick, NJ 

Dr. Robert Vanderpool, National Exposure Research Laboratory, U.S. Environmental Protection Agency, 

Research Triangle Park, NC 

Dr. John Vandenberg (Director)—National Center for Environmental Assessment-RTP Division, U.S. 

Environmental Protection Agency, Research Triangle Park, NC 

Dr. Alan Vette, National Exposure Research Laboratory, U.S. Environmental Protection Agency, Research 

Triangle Park, NC 

Ms. Debra Walsh (Deputy Director)—National Center for Environmental Assessment-RTP Division, U.S. 

Environmental Protection Agency, Research Triangle Park, NC 

Mr. Tim Watkins, National Exposure Research Laboratory, U.S. Environmental Protection Agency, 

Research Triangle Park, NC 

Dr. Christopher Weaver, National Center for Environmental Assessment, U.S. Environmental Protection 

Agency, Research Triangle Park, NC 

Mr. Lewis Weinstock, Office of Air Quality Planning and Standards, U.S. Environmental Protection 

Agency, Research Triangle Park, NC 

Ms. Karen Wesson, Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, 

Research Triangle Park, NC 

Dr. Jason West, Department of Environmental Sciences and Engineering, University of North Carolina, 

Chapel Hill, NC 

Mr. Ronald Williams, National Exposure Research Laboratory, U.S. Environmental Protection Agency, 

Research Triangle Park, NC 

Dr. George Woodall, National Center for Environmental Assessment, U.S. Environmental Protection 

Agency, Research Triangle Park, NC 

Dr. Antonella Zanobetti, Department of Environmental Health, Harvard School of Public Health, Boston, 

MA 
December 2009 lii 

Clean Air Scientific Advisory Committee 

for Particulate Matter NAAQS 

CHAIRPERSON 

Dr. Jonathan Samet, Department of Preventive Medicine, Keck School of Medicine, University of 

Southern California, Los Angeles, CA 

MEMBERS

Dr. Lowell Ashbaugh, Crocker Nuclear Lab, University of California, Davis, CA 

Dr. Ed Avol, Department of Preventive Medicine, Keck School of Medicine, University of Southern 

California, Los Angeles, CA 

Dr. Joseph Brain*, Department of Environmental Health, Harvard School of Public Health, Harvard 

University, Boston, MA 

Dr. Wayne Cascio, Brody School of Medicine, East Carolina University, Greenville, NC 

Dr. Ellis B. Cowling*, Colleges of Natural Resources and Agriculture and Life Sciences, North Carolina 

State University, Raleigh, NC 

Dr. James Crapo*, Department of Medicine, National Jewish Medical and Research Center, Denver, CO 

Dr. Douglas Crawford-Brown, Department of Environmental Sciences and Engineering, University of 

North Carolina at Chapel Hill, Chapel Hill, NC 

Dr. H. Christopher Frey*, Department of Civil, Construction and Environmental Engineering, College of 

Engineering, North Carolina State University, Raleigh, NC 

Dr. David Grantz, Botany and Plant Sciences and Air Pollution Research Center, Riverside Campus and 

Kearney Agricultural Center, University of California, Parlier, CA 

Dr. Joseph Helble, Thayer School of Engineering, Dartmouth College, Hanover, NH 

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

Dr. Philip Hopke, Department of Chemical Engineering, Clarkson University, Potsdam, NY 

Dr. Donna Kenski*, Lake Michigan Air Directors Consortium, Rosemont, IL 

Dr. Morton Lippmann, Nelson Institute of Environmental Medicine, New York University School of 

Medicine, Tuxedo, NY 

Dr. Helen Suh MacIntosh, Environmental Health, School of Public Health, Harvard University, Boston, 

MA 

Dr. William Malm, National Park Service Air Resources Division, Cooperative Institute for Research in 

the Atmosphere, Colorado State University, Fort Collins, CO 

Mr. Charles Thomas (Tom) Moore, Jr., Western Regional Air Partnership, Western Governors’ 

Association, Fort Collins, CO 
December 2009 liii 

Dr. Robert F. Phalen, Center for Occupation & Environment Health, College of Medicine, Department of 

Community and Environmental Medicine, Air Pollution Health Effects Laboratory, University of 

California Irvine, Irvine, CA 

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

Mr. Richard L. Poirot, Air Pollution Control Division, Department of Environmental Conservation, 

Vermont Agency of Natural Resources, Waterbury, VT 

Dr. Armistead (Ted) Russell*, Department of Civil and Environmental Engineering, Georgia Institute of 

Technology, Atlanta, GA 

Dr. Frank Speizer, Channing Laboratory, Harvard Medical School, Boston, MA 

Dr. Sverre Vedal, Department of Environmental and Occupational Health Sciences, School of Public 

Health and Community Medicine, University of Washington, Seattle, WA 

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

Administrator. 

**As immediate past CASAC Chair, Dr. Henderson is invited to participate in CASAC advisory activities 

for FY 2009. 

SCIENCE ADVISORY BOARD STAFF 

Dr. Holly Stallworth, Economist and Designated Federal Officer, Clean Air Scientific Advisory 

Committee, Environmental Economics Advisory Committee, Washington, D.C. 
December 2009 liv 

Acronyms and Abbreviations 

α alpha, ambient exposure factor 

α-HCH alpha-hexachlorocyclohexane 

Å Ångström 

A surface albedo 

AAC abdominal aortic calcium 

AAS atomic absorption spectrophotometry 

AB Alcian Blue stain 

ABC Asian Brown Cloud 

ABI ankle-arm or resting blood pressure index 

AC air conditioning 

Ace acenaphthene 

ACE-1 angiotensin converting enzyme-1 

ACEAsia (Asian Pacific Regional) Aerosol Characterization Experiment 

ACGIH American Conference of Governmental Industrial Hygienists 

ACh acetylcholine 

Acl acenaphthylene 

ACP accumulation mode particle 

ACS American Cancer Society 

Ad4BP adrenal-4-binding protein 

ADEOS-1 Advanced Earth Observing Satellite-1 

A-DEP automobile diesel exhaust particles 

ADM angular distribution model(s), angular dependence model 

ADMA asymmetric dimethylarginine 

AD-Net Asian Dust Network 

Ae AERONET 

AeroCom Aerosol Comparisons between Observations and Models 

AERONET NASA AERosol RObotic NETwork 

AF atrial fibrillation 

AGA appropriate for gestational age 

AGE advanced glycation end product 

AHR airway hyperresponsiveness, airway hyperreactivity 

AhR arylhydrocarbon receptor 
December 2009 lv 

AHSMOG California Seventh Day Adventist study 

AI aerosol index 

AIC Akaike’s information criterion 

AIM ambient ion monitor 

AIOP 2003 Aerosol Intensive Operating Period 

AIRS Aerometric Information Retrieval System 

Al aluminum 

ALI air liquid interface 

AM alveolar macrophage(s) 

AM, AMF arbuscular mycorrhizal 

AMAP Arctic Monitoring and Assessment Programme 

AMDP annual maximum of daily precipitation 

AMI acute myocardial infarction 

AMS aerosol mass spectrometry 

Ang II angiotensin II 

ANOVA analysis of variance 

ANP atrial natriuretic peptide 

ANS autonomic nervous system 

Ant anthracene 

AOD aerosol optical depth 

AP-1 activator protein 1 

APC antigen presenting cell(s) 

APCS Absolute Principal Components Scores 

APEX Air Pollutants Exposure Model 

APHEA Air pollution and Health: a European Approach 

APO apocynin 

ApoE apolipoprotein E 

APS aerodynamic particle sizer, aerosol polarimetry sensor 

aPTT activated partial thromboplastin time 

AQCD Air Quality Criteria Document 

AQI Air Quality Index 

AQM air quality model 

AQS U.S. EPA Air Quality System database 

Aqua NASA satellite 

AR4 Fourth Assessment Report (AR4) from the IPCC 
December 2009 lvi 

ARCTAS Arctic Research of the Composition of the Troposphere from Aircraft 

and Satellites 

ARD Air Resources Division 

ARDS adult respiratory distress syndrome 

ARI acute respiratory infection 

ARIC Atherosclerosis Risk in Communities study 

ARIES Aerosol Research and Inhalation Epidemiology Study 

ARM Atmospheric Radiation Measurement program 

ARQM Air Quality Research Branch (Meteorological Service of Canada 

Toronto) 

ARS Air Resource Specialists 

As arsenic 

ASDNN5 mean of the standard deviation in all 5-min segments of a EKG 24 h 

recording 

ASOS Automated Surface Observing System 

ATOFMS aerosol time-of-flight mass spectrometry 

ATP adenosine triphosphate 

A-Train a group of 5 afternoon overpass satellites (Aura, PARASOL, 

CALIPSO, CloudSat, Aqua) 

ATS American Thoracic Society 

AURA NASA satellite 

avg average 

AVHRR Advanced Very High Resolution Radiometer 

ß beta, beta coefficient, slope 

β-HCH beta-hexachlorocyclohexane(s) 

3βHSD 3β-hydroxysteroid dehydrogenase 

βTGF β transforming growth factor 

bag absorption by gases coefficient 

bap absorption by particles coefficient 

bext light extinction coefficient 

bsg scattering by gases coefficient 

bsp sum of light scattering by (aerosol) particles coefficient 

Ba barium 

BaA benz[a]anthracene 

BAD bronchial artery diameter 

BAL bronchoalveolar lavage 

BALB/c albino inbred mouse strain 
December 2009 lvii 

BALF bronchoalveolar lavage fluid 

BALT bronchus-associated lymphoid tissues 

BAM beta attenuation monitor 

BaP benzo[a]pyrene 

BASIC Brain Attack Surveillance in Corpus Christi 

BASE-A Burning Airborne and Spaceborne Experiment - Amazon and Brazil 

BbF benzo[b]fluoranthene 

BC black carbon 

BCC-CMI Beijing Climate Center – Carbon Mitigation Initiative 

BCCR Bjerknes Centre for Climate Research 

BeP benz[e]pyrene 

BghiP, BpPe benzo[g,h,i]perylene 

BGT beta-gauge technique 

BH4 tetrahydrobiopterin 

bhp brake horsepower 

BkF benzo[k]fluoranthene 

BMI body mass index 

BMP bone morphogenetic protein 

BN/BR Brown Norway rat strain 

BNP brain natriuretic peptide, B-type natriuretic peptide 

BOSS BYU Organic Sampling System 

BP blood pressure 

BPM blowing PM2.5

BpPe benzo[ghi]perylene 

BPQ benz(ayrene (BaP)-quinone 

Br bromine 

BRAVO Big Bend Regional Aerosol and Visibility Observational (Study) 

BrdU bromodeoxyuridine 

BS black smoke 

BUC bucillamine (N-[2-mercapto-2-methylpropionyl]-L-cysteine) 

BVAIT B-Vitamin Atherosclerosis Intervention Trial 

BYU Brigham Young University 

C carbon 

C4 Center of Clouds, Chemistry and Climate 

12C carbon-12 
December 2009 lviii 

13C carbon-13 

14C carbon-14 

C60(OH)24 water-soluble fullerene 

Ca calcium 

CAA Clean Air Act 

CAAA 1977 Clean Air Act Amendments 

CAAM continuous ambient mass monitor 

CAC coronary artery calcification 

CaCO3 calcium carbonate 

CAD coronary artery disease 

CALINE California Line Source Dispersion Model 

CALIOP Cloud and Aerosol Lidar with Orthogonal Polarization 

CALIPSO Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations 

CAM Community Atmosphere Model 

CAMM continuous ambient mass monitor 

CAMP Childhood Asthma Management Program 

CAMx comprehensive air quality model with extensions 

Ca(NO3)2 calcium nitrate 

CAP concentrated ambient particle 

CAPMoN Canadian Air and Precipitation Monitoring Network 

CASAC Clean Air Scientific Advisory Committee 

CaSO4 calcium sulfate 

CASTNet Clean Air Status and Trends Network 

CATS cumulative air toxics surface 

CB carbon black, chronic bronchitis 

CB-Fe carbon black particles artificially coated with Fe(II) salt. 

CB(P) carbon black (particles) 

CBSA Core-Based Statistical Area 

CB-V carbon black particles artificially coated with a targeted concentration 

of Vanadium (IV) salt 

CBVD cerebrovascular disease 

CC16 Clara cell protein, Clara cell 16 protein 

CCCma Canadian Centre for Climate Modeling and Analysis 

CCM3 Community Climate Model 

CCN cloud condensation nuclei 

CCPM continuous coarse particle monitor 
December 2009 lix 

CCSM3 Community climate system model, version 3 

CCSP Climate Change Science Program 

Cd cadmium 

CDC Centers for Disease Control and Prevention 

CDE conjugated diene 

CDNC cloud droplet number concentration 

CDPHE Colorado Department of Public Health and Environment 

Ce cerium 

CEN European Committee for Standardization 

CenRAP Central Regional Air Planning Association 

CERES Clouds and the Earth’s Radiant Energy System 

CERFACS European Centre for Research and Advanced Training in Scientific 

Computation 

CF coronary flow, cystic fibrosis 

CFA coal fly ash 

CFD cystic fibrosis disease 

CFR Code of Federal Regulations 

CGCM3.1 Coupled global climate model 

cGMP cyclic guanosine monophosphate 

CH2Cl2 methylene chloride 

CH2O formaldehyde 

CH4 methane 

CHAD Consolidated Human Activity Database 

CHD chronic heart disease 

CHF congestive heart failure 

CHL crown heel length 

CHO Chinese hamster ovary cells 

Chr chrysene 

CHS Children’s Health Study 

CI confidence interval 

CIF carbon-impregnated charcoal filter 

CIIT Chemical Industry Institute of Toxicology 

CIMT carotid intimal-medial thickness 

Cl chlorine 

CL chemiluminescence 

CLAMS Chesapeake Lighthouse and Aircraft Measurements for Satellites 
December 2009 lx 

CM conditioned medium, cell culture medium 

CMAQ Community Multi-scale Air Quality modeling system 

CMAR CSIRO Marine and Atmospheric Research 

CMB chemical mass balance 

CMD count median diameter 

CNES Centre National d''Etudes Spatiales 

CNP carbon nano particle 

CNRM Centre National de Recherches Meteorologiques 

CNRM Center National Weather Research 

CNS central nervous system 

Co cobalt 

CO carbon monoxide 

CO2 carbon dioxide 

COD coefficient of divergence 

COH, CoH coefficient of haze 

CONUS continental United States 

COO-

 carboxyl group 

COPD chronic obstructive pulmonary disease 

CoPP cobalt protoporphyrin 

COX-2 cyclooxygenase 2 enzyme 

CPC condensation particle counter 

CPZ capsazepine 

Cr chromium 

C-R concentration-response (relationship) 

CRP C-reactive protein 

Cs cesium 

137Cs cesium-137 

CS cigarette smoke 

CSA Combined Statistical Area 

CSC cigarette smoke condensates 

CSE cigarette smoke extract 

cSHMT cytosolic serine hydroxymethyltransferase 

CSIRO Commonwealth Scientific and Industrial Research Organization 

CSN Chemical Speciation Network 

CTM chemistry-transport model, chemical transport model 
December 2009 lxi 

Cu copper 

CuSO4 copper sulfate 

Cu/Zn SOD Cu/Zn superoxide dismutase 

CUP Current Use Pesticide 

CV cardiovascular, coefficient of variation 

CVD cardiovascular disease(s) 

CVM contingent valuation method 

CYP cytochrome P450 

CYP 1A1 cytochrome P450 1A1 

Δ delta, change, difference 

ΔFEV1 change in forced expiratory volume in one second 

d50 50 percent cut point or 50 percent diameter 

dae aerodynamic diameter of a particle 

D diameter 

Da Dalton 

DAAC Distributed Active Archive Center 

DAASS Dry Ambient Aerosol Size Spectrometer 

DABEX Dust and Biomass-burning Experiment (in West Africa) 

DAR denuded aortic ring 

DAX-1 x-chromosome gene-1 

DBA dibenzo(a,hnthracene 

DBP diastolic blood pressure 

DC dendritic cell 

DC diesel exhaust particles + cigarette smoke condensates 

DC8 Douglas aircraft 

DCF direct climate forcing, 2',7'-dichlorofluorescin 

DDT dichlorodiphenyltrichloroethane 

DE diesel exhaust 

DEE diesel exhaust extract 

DEP diesel exhaust particle 

DEPAL diesel exhaust particles aliphatic (extract) 

DEPAR diesel exhaust particles aromatic (extract) 

DEPE diesel exhaust particles extract 

DEPM diesel exhaust particles methanol (extract) 

DEPME diesel exhaust particles methylene chloride extract 
December 2009 lxii 

DEPPO diesel exhaust particles polar (extract) 

Dex dexamethasone 

dFld change fold, unit change in property 

DFO desferrioxamine (Desferral) an iron chelator 

DFX deferasirox (Exjade) an oral iron chelator 

DHR dihydrorhodamine 123 

DLCO carbon monoxide diffusing capacity 

DMEM Dulbecco’s modified Eagle’s medium (culture medium) 

DMSO dimethyl sulfoxide 

DMT1 divalent metal transporter-1 protein 

DMTU dimethylthiourea 

DNA deoxyribonucleic acid 

DOE U.S. Department of Energy 

dpc days post conception 

DPC dodecylphosphocholine 

DPCC 1,2-dipalmitoyl-SN-glycero-3-phosphocholine 

DPI diphenyleneiodonium 

DPM diesel particulate matter 

DPPC dipalmitoylphosphatidylcholine 

DRE direct radiative effects 

DRF direct radiative forcing 

DRUM Davis Rotating Uniform size-cut Monitor 

DS diffusion screens 

DSP daily sperm production 

DTMA Dynamic mechanical thermal analysis 

DTPA diethylene triamine pentaacetic acid 

DU dust 

dv deciview(s) 

DVT deep vein thrombosis 

EAD electrical aerosol detector 

EANET Acid Deposition Monitoring Network in East Asia 

EARLINET European Aerosol Research Lidar Network 

EarthCARE Earth Clouds, Aerosols and Radiation Explorer 

EAST-AIRE East Asian Study for Tropospheric Aerosols 

EBCT electron beam computed tomography 
December 2009 lxiii 

EC elemental carbon 

ECE-1 endothelin converting enzyme-1 

ECG, EKG electrocardiogram 

ECHAM5 European Centre Hamburg with Hamburg Aerosol Module 

ECHO-G (ECHAM4 + HOPE-G): 

ECRHS European Community Respiratory Health Survey 

EC/TC ratio of elemental carbon to total carbon 

ED emergency room, emergency department 

EDGAR Emissions Database for Global Atmospheric Research 

EDTA ethylenediaminetetraacetic acid 

ED-XRF energy dispersive X-ray fluorescence 

EGM electrogram 

EGU electricity-generating unit 

EHC-93 Ottawa dust; urban air particulate matter PM10, collected in 1993 in 

Ottawa, Canada 

EKG, ECG electrocardiogram 

ELISA enzyme-linked immunosorbent assay 

EMECAS Spanish Multi-centric Study on the Relation between Air Pollution 

and Health 

EMEP European Monitoring and Evaluation Programme 

eNO exhaled nitric oxide 

eNOS endothelial nitric oxide synthase 

EOS Earth Observing System 

EPA U.S. Environmental Protection Agency 

ER estrogen receptor 

ERBS Earth Radiation Budget Satellite 

ERK1/2 ERK-1 (MAPK p42) and ERK-2 (MAPK p44) 

ESRL Earth System Research Laboratory 

ESTR expanded simple tandem repeat 

ET forcing efficiency 

ET extrathoracic region 

ET endothelin 

ETA endothelin A receptor subtype 

ETB endothelin B receptor subtype 

ETS environmental tobacco smoke 

EU endotoxin units 
December 2009 lxiv 

F breathing frequency 

f the ratio of ambient aerosol mass (wet) to dry aerosol mass M. 

fσsp(RH) total light scattering coefficient at given relative humidity(RH) values 

faf anthropogenic fraction of fine-mode fraction 

ff fine mode fraction 

f(RH) the unitless water growth term that depends on relative humidity 

F fine particles 

F344 Fisher 344 strain of rats 

Fa adjusted forcings 

FA filtered air 

FAC ferric ammonium citrate 

FBI Federal Bureau of Investigation 

FBS fetal bovine serum 

FCS fetal calf serum 

FDMS Filter Dynamics Measurement System 

FDMS-TEOM Filter Dynamics Measurement System - Tapered Element Oscillating 

Microbalance 

Fe effective (Fe) forcings 

Fe iron 

Fe2(SO4)3 ferric sulfate 

FeCl3 ferric chloride 

FEF forced expiratory flow 

FEF25-75 mean forced expiratory flow over the middle half of the forced vital 

capacity 

FEF50% mid-expiratory flow 

FEM Federal Equivalent Method 

FeNO fractional exhaled nitric oxide 

FERA Fire and Environmental Research Applications (Team) 

FEV1 forced expiratory volume in one second 

FGA one fibrinogen alpha chain 

FGB one fibrinogen beta chain 

FGOALS-g1.0 Flexible Global Ocean-Atmosphere-Land System Model 

Fi instantaneous forcing 

FID flame ionization detection 

FIMS fast integrated mobility scanners 

Finf infiltration factors 
December 2009 lxv 

FKHR Proapoptotic Factor FOXO1 

Fle fluorine 

Flu fluoranthene 

FMD flow-mediated dilation 

FPG formamidopyrimidine-DNA glycosylase 

f-PM, FPM fine particulate matter 

FR Federal Register 

FRM Federal Reference Method 

FROSTFIRE The landscape-scale prescribed research burn in the boreal forest of 

interior Alaska, July 1999; conducted by FERA. 

Fs SST forcing(s), forcing driven by sea surface temperature (SST) 

Fsfc mean net solar flux at the (Earth) surface 

FT free troposphere 

FTIR Fourier transform infrared spectrometry 

F/UFP mix of fine and ultrafine particles, all < 2.5 μm 

FVC forced vital capacity 

γGCS gamma glutamylcysteine sythetase 

Ga gallium 

GAM generalized additive model 

GATOR Gas, Aerosol, Transport, and Radiation model 

GATORG Gas, Aerosol, Transport, Radiation, and General circulation model 

GAW Global Atmospheric Watch network 

GBS group B streptococcus 

GC gas chromatography 

GCM(s) general circulation model(s), global climate model 

GCMOM General Circulation, Mesoscale and Ocean Model 

GC/MS gas chromatography/mass spectrometry 

GCS gamma glutamylcysteine sythetase 

GD gestational day 

GDF growth differentiation factor (e.g., GDF-9) 

GEE generalized estimating equations, gasoline engine exhaust 

GEIA Global Emissions Inventory Activity 

GEM gaseous elemental mercury 

GEOS-Chem Goddard Earth Observing System-CHEMistry 

GFAAS graphite furnace atomic absorption spectrometry 

GFAP glial fibrillatory acidic protein 
December 2009 lxvi 

GFDL Geophysical Fluid Dynamics Laboratory 

GFDL-CM2.x GFDL Climate Models 

GFED Global Fire Emission Database 

GGT gamma-glutamyltranspeptidase 

GHG greenhouse gas 

GIS Geographic Information System 

GISS Goddard Institute for Space Studies 

GISS-AOM GISS Atmosphere-Ocean Model climate prediction model 

GISS-EH GISS AOM for sea ice model 

GISS-ER GISS AOM for liquid sea model 

GLAS Geoscience Laser Altimeter System 

GLM generalized linear models 

GM geometric mean 

GM-CSF granulocyte macrophage colony-stimulating factor 

GMD Global Monitoring Division 

GMS Greater Mekong Subregion 

GOCART Goddard Chemistry Aerosol Radiation and Transport 

GOES Geostationary Operational Environmental Satellite 

GoMACCS Gulf of Mexico Atmospheric Composition and Climate Study 

GPS Global Positioning System 

GSD geometric standard deviation 

GSFC NASA Goddard Space Flight Center 

GSH glutathione 

GSH:GSSG ratio of reduced glutathione to glutathione disulfide (oxidized 

glutathione) 

GSO, GSNO S-Nitrosoglutathione 

GSSG glutathione disulfide; oxidized glutathione 

GST glutathione-S-transferase 

GSTM1 glutathione S-transferase polymorphism M1 

GSTP1 glutathione-S-transferase polymorphism P1 

GSTT1 glutathione-S-transferase polymorphism T1 

GWP global warming potential 

h hour 

H atomic hydrogen, hydrogen radical, height, heart rate, high dose, high 

exposure 

H+

 hydrogen ion 
December 2009 lxvii 

HR heart rate 

H2 molecular hydrogen 

H2CO formaldehyde 

H2O water 

H2O2 hydrogen peroxide 

H2S hydrogen sulfide 

H2SO4 sulfuric acid 

H9c2 rat embryonic cardiomyocytes cell line 

HA hospital admission 

HAEC Human Aortic Endothelial Cell 

HAPC Harvard ambient particle concentrator 

HBE, HBEC Human Bronchial Epithelial cells 

HC hydrocarbon(s); head circumference 

HCB hexachlorobenzene 

HCH hexachlorocyclohexane(s) (e.g. α-HCH, β-HCH) 

HDL high density lipoprotein 

HEAPSS Health Effects of Air Pollution among Susceptible Subpopulations 

study 

HEI Health Effects Institute 

HEPA high efficiency particle air (filter) 

HERO Health and Environmental Research Online, NCEA Database System 

HF heart failure, high frequency (HRV parameter), high (dose/exposure) 

filtered 

HFCD High-Fat Chow Diet 

HFE HFE gene, HFE protein 

Hg mercury 

Hg(0) gaseous elemental mercury 

Hg(II) gaseous divalent (oxidized) mercury 

HH hereditary hemochromatosis 

HNRS Hans Nixdorf Recall Study 

HO-1 heme oxygenase-1 

hOGG1 8-hydroxyguanine DNA-glycosylase 

HOPE-G Hamburg Atmosphere-Ocean Coupled Circulation Model 

hPA hectopascal 

hPAEC human pulmonary artery endothelial cells 

hPBMC human peripheral blood mononuclear cells 
December 2009 lxviii 

HPLC high pressure liquid chromatography 

HPMF high particulate matter filtered 

hPMVEC human pulmonary microvascular endothelial cells 

HR heart rate, hazard ratio, high level DE 

HRV heart rate variability 

HSD 17β-hydroxysteroid dehydrogenase 

HSP-70 heat shock protein 

HSPH Harvard School of Public Health 

HSRL High Spectral Resolution Lidar 

HUVEC human umbilical vein endothelial cells 

hν photon 

HWS hardwood smoke 

Hz hertz 

IC ion chromatography 

ICAM-1 intercellular adhesion molecule-1 

ICARTT International Consortium for Atmospheric Research on Transport and 

Transformation 

ICAS Inner-City Asthma Study 

ICD implantable/implanted cardioverter defibrillator 

ICD-9 International Classification of Disease 9th revision 

ICD-10 International Classification of Disease 10th revision 

ICESat Ice, Cloud and land Elevation Satellite 

ICP-AES inductively coupled plasma-atomic emission spectroscopy 

ICP-MS inductively-coupled plasma-mass spectrometry 

ICR imprinting control region, mouse strain 

ICRP International Commission on Radiological Protection 

IDP indeno[1,2,3-c,d]pyrene 

IFN-γ interferon-gamma 

IFS Integrated Forest Study 

Ig immunoglobulin (e.g., IgE) 

IGS International Genetic Standard 

IHD ischemic heart disease 

IIASA International Institute for Applied Systems Analysis 

IL interleukin 

iMDDC immature monocyte-derived dendritic cells 
December 2009 lxix 

IMPACT Interactive Modeling Project for Atmospheric Chemistry and 

Transport 

IMPROVE Interagency Monitoring of Protected Visual Environment 

IN ice nuclei 

INAA instrumental neutron activation analysis 

INCA Interactions between Chemistry and Aerosol 

INDOEX Indian Ocean Experiment 

INGV-SXG Istituto Nazionale di Geofisica e Vulcanologia coupled to SINTEX-G 

INM-CM3.0 Institute of Numerical Mathematics climate model 

iNOS inducible nitric oxide synthase 

INTEX Intercontinental Chemical Transport Experiment 

I/O indoor-outdoor ratio 

IOM Institute of Medicine 

i.p. intraperitoneal 

IP inhalable particle 

IPCC Intergovernmental Panel on Climate Change 

IPSL-CM4 Institut Pierre Simon Laplace climate model 

IQR interquartile range 

Ir iridium 

IR incidence rate, infrared radiation 

IRE iron responsive element 

IRMS isotope ratio mass spectrometer 

ISA Integrated Science Assessment 

ISO International Standards Organization 

ISO isoprene, 2-methyl analog of 1,3-butadiene 

IT intratracheal, intratracheally 

IUGG International Union of Geodesy and Geophysics 

IUGR intrauterine growth restriction, intrauterine growth retardation 

i.v. intravenous 

JNK c-jun N-terminal kinase 

κB kappa B 

K potassium 

KC local neutrophil chemoattractant protein 

kHz kilohertz 

kJ kilojoules 

KLH keyhole limpet hemocyanin 
December 2009 lxx 

km kilometer 

km-1 inverse kilometer 

Kow octanol-water partition coefficient 

L, dL, mL, μL Liter, deciLiter, milliLiter, microLiter 

L low 

La lanthanum 

LAC light-absorbing carbon 

LACE98 Lindenberg Aerosol Characterization Experiment 1998 

LBA-SMOCC Large-Scale Atmosphere-Biosphere Experiment in Amazon 

LBW low birth weight 

LC lethal concentration 

LC50 median lethal concentration 

LDH lactate dehydrogenase 

LDL low-density lipoprotein 

LDLR low-density lipoprotein receptor 

LDVP left developing ventricular pressure 

LES large eddy simulations model 

LF low frequency an HRV parameter 

LF/HF ratio of LF to HF an HRV parameter 

LIBS laser induced breakdown spectroscopy 

LIF leukemia inhibitory factor 

LITE Lidar In-space Technology Experiment 

LMD Laboratoire de Meteorologie Dynamique 

LMDz LMD with Zoom 

LMDZ-INCA LMDZ INteractive Chemistry and Aerosols model 

LMDZ-LOA LMDZ with Laboratoire d'Optique Atmosphérique model 

L-NAME arginine analog; N(G)-nitro-L- arginine methyl ester 

L-NMMA N(G)-mono-methyl-L-arginine 

LnRMSSD natural log of RMSSD; measure of HRV 

lnSDNN natural log of the standard deviation of NN intervals in an EKG 

LOA Laboratoire d’Optique Atmospherique 

LOESS locally weighted scatterplot smoothing 

LOSU level of scientific understanding 

Lpm liters per minute (L/min) 

LPMF low particulate matter filtered 
December 2009 lxxi 

LPO plasma lipid peroxides 

LPS lipopolysaccharide 

LRAT long range atmospheric transport 

LROT long range oceanic transport 

LSCE Laboratoire des Sciences du Climat et de l’Environnement 

LSDF low-sulfur diesel fuel 

LTB4 leukotriene B4

LTE4 leukotriene E4

LUA NRW The North Rhine-Westphalia State Environment Agency 

LUDEP LUng Dose Evaluation Program 

LUR land use regression 

LV left ventricle 

LVEDP left-ventricular end-diastolic pressure, 

LVSP left-ventricular systolic pressure, left ventricular developed pressure 

L/W ratio of lumen to wall 

LWC liquid water content 

LWDE Low Whole Diesel Exhaust 

LWP liquid water path 

μg microgram 

μg/m3 micrograms per cubic meter 

μm micrometer, micron 

m, cm, μm, nm meter(s), centimeter(s), micrometer(s), nanometer(s) 

M, mM, μM, nM, pM Molar, milliMolar, microMolar, nanoMolar, picoMolar 

M dry aerosol mass, medium dose/exposure 

ma moving average 

MAM March-April-May 

MAN Maritime Aerosol Network 

MANE-VU Mid-Atlantic/Northeast Visibility Union 

MAP mitogen-activated protein, mean arterial pressure 

MAPK mitogen-activated protein kinase(s), MAP kinase 

MARAMA Mid Atlantic Regional Air Management Association 

MATCH Model of Atmospheric Transport and Chemistry 

max maximum 

MBP major basic protein 

MCAPS Medicare Air Pollution Study 
December 2009 lxxii 

Mch methacholine 

MCN mixed carbon nanoparticle 

MCP-1 monocyte chemoattractant protein 1 

MCV mean corpuscular volume 

MD mineral dust 

MDA malondialdehyde 

MDCT multidetector computed tomography 

ME Multilinear Engine 

MEE mass extinction efficiency 

MEF maximal expiratory flow 

MEF50 maximum expiratory flow rate at 50% of vital capacity 

MeHg methyl mercury 

MENTOR Modeling Environment for Total Risk Studies 

MEP motorcycle exhaust particulate(s) 

MEPE motorcycle exhaust particulate extract (particle-free) 

MESA Multi-Ethnic Study of Atherosclerosis 

MFFSR multifilter rotating shadowband radiometer 

mg/m3 milligrams per cubic meter 

Mg magnesium 

MI myocardial infarction 

MIROC3.x Model for Interdisciplinary Research on Climate 

MILAGRO Megacity Initiative: Local and Global Research Observations, study 

of air pollution in Mexico City 

min minute(s), minimum 

MINOS MPI Mediterranean INtensive Oxidant Study 

MIP-2 macrophage inflammatory protein-2 

MIRAGE Megacities Impact on Regional and Global Environment program 

MIS mullerian inhibiting substance 

MISR Multi-angle Imaging SpectroRadiometer 

Mm megameter 

Mm-1 inverse megameter 

MM monocyte-derived macrophages 

MM5 mesoscale model 

MMAD mass median aerodynamic diameter 

MMD mass median diameter 

MMEF maximal mid-expiratory flow 
December 2009 lxxiii 

mmHg millimeters of mercury 

MMP mitochondria membrane potential 

MMP(2,9) matrix metalloproteinase (2, or 9) 

MMT million metric tons 

Mn manganese 

MN micronuclei 

MnSO4 manganese sulfate 

MnSOD manganese superoxide dismutase 

MnTBAP manganese tetrakis (4-benzoic acid) porphyrin 

mo month 

MOA mode(s) of action 

MODIS MODerate resolution Imaging Spectroradiometer 

MOUDI Micro-Orifice Uniform Deposit Impactor 

MOZART MOdel for Ozone and Related chemical Tracers 

MP mid polar, myelopeptide 

MPC mean platelet component 

MPF median power frequency 

MPG N-(2-mercaptopropionyl) glycine 

MPI Max Planck Institute for Meteorology 

MPLNET Micro-Pulse Lidar Network 

MPO myeloperoxidase 

MPPD Multiple-Path Particle Dosimetry model 

MPV mean platelet volume 

MRI Meteorological Research Institute 

MRI-CGCM MRI coupled general circulation model 

mRNA messenger RNA 

MRPO Midwest Regional Planning Organization 

ms millisecond 

MSA metropolitan statistical area 

MSH melanocyte stimulating hormone 

MSHA Mount St. Helen ash 

MSU monosodium urate crystals 

MT metric ton 

MTHFR methylenetetrahydrofolate reductase 

MTT methyl thiazol tetrazolium 
December 2009 lxxiv 

MV motor vehicle 

MWNT multiplewall nanotube

M/Z mass-to-charge ratio 

N nitrogen 

N2O nitrous oxide 

Na sodium 

Na2SO4 sodium sulfate 

NAAQS National Ambient Air Quality Standards 

NAC N-acetylcysteine, a thiol antioxidant 

NaCl sodium chloride 

NADPH reduced form of nicotinamide adenine dinucleotide phosphate 

NAG N-acetyl-β-D-glucosaminidase 

Na,K-ATPase sodium-potassium adenosine triphosphatase 

NAMS National Ambient Monitoring Stations 

NaN3 sodium azide 

NaNO3 sodium nitrate 

nano-BAM low pressure-drop ultrafine particle impactor coupled with a Beta 

Attenuation Monitor 

NAPAP National Acid Precipitation Assessment Program 

NAPCA National Air Pollution Control Administration 

NAS National Academy of Sciences 

NASA U.S. National Aeronautics and Space Administration 

NASDA National Space Development Agency, Japan 

NATA U.S. EPA’s National Air Toxics Assessment 

2-NB 2-nitrobenzanthrone 

NC total (particle) number concentration 

NCAR National Center for Atmospheric Research 

NCC-MPSP negatively charged carboxylate-modified polystyrene particle(s) 

NCD Normal Chow Diet 

NCEA National Center for Environmental Assessment 

NCHS National Center for Health Statistics 

NCICAS National Cooperative Inner-City Asthma Study 

NCore National Core 

Nd drop number concentration 

Nd:YAG neodymium-doped yttrium aluminum garnet laser 

NDDN National Dry Deposition Network 
December 2009 lxxv 

NEAQS NOAA New England Air Quality Study 

NEI National Emissions Inventory 

NESCAUM Northeast States for Coordinated Air Use Management 

NET National Emissions Trends database 

NFκB nuclear factor kappa-B 

NG neutrophil granulocytes 

NH northern hemisphere 

NH3 ammonia 

NH4

+

 ammonium ion 

NH4NO3 ammonium nitrate 

(NH4)2SO4 ammonium sulfate 

NHANES National Health and Nutrition Examination Survey 

NHBE(C) normal human bronchial epithelial cells 

NHPAE normal human pulmonary artery endothelial cells 

NHS Nurses’ Health Study 

Ni nickel 

NIOSH National Institute for Occupational Safety and Health 

NIST National Institute of Standards and Technology 

NMHC non-methane volatile hydrocarbon 

NMMAPS U.S. National Morbidity, Mortality, and Air Pollution Study 

NO nitric oxide 

NO2, NO2

·

 nitrogen dioxide, nitrogen dioxide radical 

NO3

–

 nitrate 

NOAA National Oceanic and Atmospheric Administration 

NOAEL no observed adverse effect level 

NOS nitric oxide synthase 

NOS3 nitric oxide synthase 3 

NOx nitrogen oxides, oxides of nitrogen (NO + NO2) 

NP National Park 

NPM non-blowing PM2.5

NPOESS National Polar-orbiting Operational Environment Satellite System 

NPS National Park Service, U.S. Department of the Interior 

NR not reported 

NR5A1 nuclear receptor subfamily 5, group A, member 1 

NRC National Research Council 
December 2009 lxxvi 

NRPB National Radiological Protection Board 

NSA North Slope Alaska 

NT neurotrophin, nitrotyrosine 

NWS National Weather Service 

NYHA New York Heart Association 

O oxygen 

O2 molecular oxygen 

O3 ozone 

OAQPS Office of Air Quality Planning and Standards 

OC organic carbon 

OCM organic carbon mass 

OE organic extracts 

OGG1 8 oxo-guanine repair enzyme 

OH, OH• hydroxyl group, hydroxyl radical 

8-OHdG 8-hydroxydeoxyguanosine 

OM organic matter 

OMI Ozone Monitoring Instrument 

OMM organic molecular marker 

OR odds ratio(s) 

OSM oncostatin M, a cytokine 

OSPM Operational Street Pollution Model 

OVA ovalbumin 

oxLDL oxidation of LDL, marker of oxidative stress 

8-oxodG 8-oxo-7-hydrodeoxyguanosine 

ox-PAPC oxidized 1-palmitoyl-2-arachidonoyl-sn-glycero-3-phosphorylcholine 

P450 cytochrome P450 

P450c17 cytochrome P450 17-α-hydroxylase 

P450scc cytochrome P450 cholesterol side chain cleavage enzyme 

P90 90th percentile; Printex 90 

p probability value 

P phosphorus 

PA photoacoustic analyzer, physical activity, plasminogen activator, 

pulmonary arterial, alveolar pressure 

PAF platelet-activating factor 

PAH polycyclic aromatic hydrocarbon(s) 

PAI plasminogen activator inhibitor, (e.g. PAI-1) 
December 2009 lxxvii 

PALMS NOAA Particle Analysis by Laser Mass Spectrometry instrument 

PAMCHAR Chemical and Biological Characterisation of Ambient Air Coarse, 

Fine, and Ultrafine Particles for Human Health Risk Assessment in 

Europe 

PAMS Photochemical Assessment Monitoring Stations network 

PAR photosynthetically active radiation 

PAR(s) Pulmonary Artery Rings 

PARASOL Polarization and Directionality of the Earth’s Reflectances, coupled 

with observations from a Lidar, a CNES satellite 

PARP poly(ADP-ribose) polymerase 

PAS Periodic Acid Schiff stain 

Pb lead 

207Pb lead-207 

PBDE polybrominated diphenyl ether 

PBL planetary boundary layer 

PBMC peripheral blood mononuclear cell 

PBMM peripheral blood monocyte-derived macrophages 

PBP primary biological particle(s) 

PBS phosphate buffered saline 

PC synthetic carboxylate-modified particles 

PCA principal component analysis 

PCA-MPSP positively-charged amine modified polystyrene particle 

PCB polychlorinated biphenyl(s) 

PCDD polychlorinated dibenzo-p-dioxin 

PCIS Personal Cascade Impactor Sampler 

PCM NCAR Parallel Climate Model 

PCPSP positively charged polystyrene particle 

PCR polymerase chain reaction 

PDF probability distribution functions 

pDR personal DataRam 

PE post exposure, post exercise, phenylephrine 

PEACE Pollution Effects on Asthmatic Children in Europe study 

PEC particulate elemental carbon 

PECAM-1 platelet endothelial cell adhesion molecule 1 

PEF peak expiratory flow (L/min) 

PEFR peak expiratory flow rate 
December 2009 lxxviii 

PEFT time to peak flow 

PEM personal exposure monitor 

PEM-West NASA Pacific Exploratory Missions in the western Pacific 

Penh enhanced pause 

Per perylene 

PESA particle elastic scattering analysis 

PFDE particle free diesel exhaust 

PGE2 prostaglandin E2

PGI2 prostacyclin 

Phe phenanthrene 

PI post instillation, posterior interval, pulmonary inflammation 

PICT pollution-induced community tolerance 

PILS Particle Into Liquid Sampler 

PILS-IC Particle Into Liquid Sampler-Ion Chromatography 

PIXE Particle Induced X-ray Emission 

PKA protein kinase A 

PLS partial least squares, projection to latent structures 

PM particulate matter 

PMx particulate matter of a specific size range. X refers to the diameter at 

which the sampler collects 50% of the particles and rejects 50% of the 

particles. Collection efficiency increases for particles with smaller 

diameters and decreases for particles with larger diameters. The 

variation of collection efficiency with size is given by a collection 

efficiency curve. The definition of PMx is frequently abbreviated as 

“particles with a nominal mean aerodynamic diameter less than or 

equal to x μm. 

PMx-y particulate matter with a nominal mean diameter greater than x μm 

and less than y μm where x and y are the numeric mean aerodynamic 

or mobility diameters (μm). 

PM0.1 particulate matter with a nominal mean mobility diameter less than or 

equal to 0.1 μm (referred to as ultrafine PM) 

PM2.5 particulate matter with a nominal mean aerodynamic diameter less 

than or equal to 2.5 μm (referred to as fine PM) 

PM10 particulate matter with a nominal mean aerodynamic diameter less 

than or equal to 10 μm 

PM10-2.5 particulate matter with a nominal mean aerodynamic diameter greater 

than 2.5 μm and less than or equal to 10 μm (referred to as thoracic 

coarse particulate matter or the course fraction of PM10) 

Concentration may be measured with a dichotomous sampler or 

calculated as the difference between measured PM10 and measured 

PM2.5 concentrations. 

PMA phorbol 12-myristate 13-acetate 

PMF particulate matter filtrate, positive matrix factorization 
December 2009 lxxix 

PM-HD particulate matter at high concentration 

PM-LD particulate matter at low concentration 

PMN polymorphonuclear leukocytes 

PN particle number 

PNC particle number concentration, particle number count 

PND, pnd post-natal day 

PNMD particle number median diameter 

PNN proportion of interval differences of successive normal-beat intervals 

in EKG 

pNN50 proportion of interval differences of successive normal-beat intervals 

greater than 50 ms in an EKG 

PNNL Pacific Northwest National Laboratory 

pNO3 particulate nitrate 

POA primary organic aerosol 

POC particulate organic carbon 

POLDER POLarization and Directionality of the Earth's Reflectance 

POM particulate organic matter 

POP persistent organic pollutant 

Pp particle density 

PP pulse pressure 

ppb parts per billion 

PPFL percent predicted lung function 

ppm parts per million 

ppt parts per trillion 

PRB policy-relevant background 

PRE AeroCom Experiment 

PRELC Primary Rat Epithelial Lung Cells 

PRIDE Puerto RIco Dust Experiment 

PS public school 

PSAS The French National Program on Air Pollution Health Effects 

PSO Public Service Company of Oklahoma 

pSO4 particulate sulfate 

PSS physiologic saline solution 

PSU Pennsylvania State University 

PT prothrombin time 

PTT partial thomboplastin time 
December 2009 lxxx 

PTV programmable temperature vaporization 

PVD peripheral vascular disease 

Pyr pyrene 

Q cardiac output 

Q coronary flow of the heart 

QAI QA interval 

QBQ backup quartz-fiber filter behind a quartz-fiber filter 

QEEG quantitative electroencephalography 

Qext the extinction coefficient (a function of particle size distribution and 

refractive index) 

r correlation coefficient 

R2

 coefficient of determination 

RAIN Regional Aerosol Intensive Network 

RAMS real-time total ambient mass sampler 

RANTES regulated upon activation, normal T cell expressed and secreted 

RAPS/RAMS Regional Air Pollution Study / Regional Air Monitoring Study 

RAR rapidly activating receptor(s) 

RASMC rat aortic smooth muscle cells 

RAW 264.7 mouse macrophage cell line 

RBC red blood cell 

RD respiratory disease 

REALM Regional East Atmospheric Lidar Mesonet 

RF radiative forcing(s) 

reff particle effective radius 

RFL Fetal Lung Fibroblasts 

RH relative humidity 

RHMVE rat heart micro-vessel endothelial cell 

RHR Regional Haze Rule 

RLF rat lung fibroblasts 

RMC rat cardiomyocyte(s) 

RME rapeseed oil methyl ester 

RMSSD root mean squared differences of successive normal-beat to normalbeat (NN or RR) time intervals between each QRS complex in the 

EKG 

RMV respiratory minute volume 

RNA ribonucleic acid 
December 2009 lxxxi 

RNS reactive nitrogen species 

RO residual oil 

ROCK rho associated kinase 

ROFA residual oil fly ash (particles) 

ROFA-L residual oil fly ash leachate 

ROI reactive oxygen intermediates 

ROS reactive oxygen species 

RPO Regional Planning Organizations 

RR risk ratio, relative risk, normal-to-normal (NN or RR) time interval 

between each QRS complex in the EKG 

RS resuspended soil 

RSV respiratory syncytial virus 

RTI respiratory tract infection 

RTM Radiative Transfer Model 

RTP Research Triangle Park, North Carolina 

RV right ventricular 

RVCFB right ventricular cardio fibroblasts 

RVCM right ventricular cardiomyopathy, rat ventricular cardiomyocytes, 

reduced volume culture medium 

σ sigma, standard deviation 

1σ one sigma; one standard deviation 

σg sigma-g; geometric standard deviation 

s second 

S sulfur 

SAB (EPA) Science Advisory Board 

SAFARI South African Fire-Atmosphere Research Initiative 

SAGE Stratospheric Aerosol and Gas Experiment 

SALIA German study on the Influence of Air Pollution on Lung Function, 

Inflammation, and Aging 

SAM Stratospheric Aerosol Measurement 

SAMUM Saharan Mineral Dust Experiment 

SAP2.3 Synthesis and Assessment Product 2.3

Sb antimony 

SB strand breaks 

SBL stable boundary layer 

SBP systolic blood pressure 
December 2009 lxxxii 

Sc scandium 

SC summer curbside particles 

SCAB California South Coast Air Basin 

SCAR Smoke/Sulfates, Clouds and Radiation 

SCARPOL Swiss Study on Childhood Allergy and Respiratory Symptoms with 

Respect to Air Pollution 

sCD40L soluble CD40 ligand 

SCE sister chromatid exchange 

SCS Harvard Six Cities Study 

SD standard deviation; Sprague-Dawley rat 

SDANN5 standard deviation of the average of normal to normal (N:N) intervals 

in all 5-min intervals in a 24-h period 

SDNN standard deviation normal-to-normal (NN or RR) time interval 

between each QRS complex in the EKG 

SDNN24HR standard deviation of the average of all normal to normal intervals in 

a 24-h period 

Se selenium 

se standard error 

SEARCH Southeastern Aerosol Research and Characterization 

sem standard error of mean 

SEM scanning electron microscopy 

SES socioeconomic status, sample equilibration system 

SF-1 steroidogenic factor -1 

SF-UFID suspension, particle free ultrafine industrial exhaust 

SGA small for gestational age 

sGC soluble guanylate cyclase 

SGP Southern Great Plains 

-SH sulfhydryl group 

SH Mount Saint Helen’s ash 

SH, SHR spontaneously hypertensive disease model rat 

SHADE Saharan Dust Experiment 

SHEDS Stochastic Human Exposure and Dose Simulation model 

Si silicon 

sICAM-1 soluble intercellular adhesion molecule 

SIDS sudden infant death syndrome 

SiO2 silicone dioxide 

SIPS State Implementation Plan 
December 2009 lxxxiii 

SJV San Joaquin Valley 

SLAMS State and Local Air Monitoring Stations 

SME soybean oil methyl ester 

SMOCC Smoke Aerosols, Clouds, Rainfall and Climate 

SMOKE Spare-Matrix Operator Kernel Emissions system 

SMPS scanning mobility particle sizer 

SMPS-APS scanning mobility particle sizer– aerodynamic particle sizer 

SMRA small mesenteric rat arteries 

SNP single-nucleotide polymorphism, sodium nitroprusside 

SNS sympathetic nervous system 

SO2 sulfur dioxide 

SO3 sulfur trioxide 

SO4

2– sulfate 

SOA secondary organic aerosol 

SOC semi-volatile organic compound 

SOD superoxide dismutase 

SOPHIA Study of Particulates and Health in Atlanta 

SOX sulfur oxides, oxides of sulfur 

SP surfactant protein (e.g., SPA, SPD) 

SPA surfactant protein A 

SPD surfactant protein D 

SPEW Speciated Pollutant Emission Wizard 

SPG Southern Great Plains site 

SPM suspended particulate matter 

SPRINTARS Spectral Radiation-Transport Model for Aerosol Species 

SRM-154b NIST standard reference material 154b; (TiO2 Titanium dioxide) 

SRM1648 NIST standard reference material 1648; (urban particulate matter) 

SRM-1649 NIST standard reference material 1649 (Washington, D.C. urban air 

particulate matter, urban dust) 

SRM-1650 NIST standard reference material 1650 (diesel exhaust particulate 

matter) 

SRM-1879 NIST standard reference material 1859; (silicone dioxide, respirable 

cristobalite [respirable crystalline silica]) 

SRM-2975 NIST standard reference material 2975 (diesel exhaust particulate 

matter) 

s-ROFA soluble portion of residual oil fly ash 

SS secondary sulfate, sea salt 
December 2009 lxxxiv 

SSA single-scattering albedo 

SSR standardized sex ratio 

SST sea surface temperature 

STEM Sulfur / Sulfate Transport Eulerian Model 

STN EPA Speciation Trend Network 

STP standard temperature and pressure 

STZ Streptozotocin 

SUB summer urban background particles 

SURFRAD NOAA GMD Surface Radiation network 

SVA supraventricular arrhythmia 

sVCAM-1 soluble vascular adhesion molecule 1 

SVEB supraventricular ectopic beats 

SWNT singlewalled nanotube 

SXRF Synchroton X-ray fluorescence 

SZA solar zenith angle 

τ photochemical lifetime 

T body temperature 

TAR IPCC 3rd Assessment Report 

TARC thymus and activation-regulated chemokine 

TARFOX Tropospheric Aerosol Radiative Forcing Observational Experiment 

TAT thrombin-anti-thrombin complexes 

TB tracheobronchial 

TBA thiobarbituric acid 

TBAP tetrakis(4-benzoic acid) porphyrin 

TBARS thiobarbituric acid reactive substances 

TBQ backup quartz-fiber filter behind a Teflon-membrane filter 

99mTc Technetium-99m 

99mTc-DMTA 99MTc Dynamic mechanical thermal analysis 

99MTc-DTPA 99MTc-diethylenetriaminepentaacetic acid 

Tco core temperature 

TD thermal desorption, tire debris extracted in methanol 

TD-GC/MS thermal desorption-gas chromatography/mass spectrometry 

TEAC Trolox Equivalent Antioxidant Capacity assay 

TEOM Tapered Element Oscillating Microbalance 

TexAQS Texas Air Quality Field Study 
December 2009 lxxxv 

TF tissue factor 

TFPI tissue factor pathway inhibitor 

Tg teragram 

TG terminal ganglion (neurons) 

TGF transforming growth factor 

TGF β β transforming growth factor 

Th thorium 

Th1 T helper cell type 1 

Th2 T helper cell type 2 

tHcy total homocysteine 

Ti titanium 

TIA transient ischemic attack 

TiFe iron-loaded fine titanium oxide 

TIMP-2 tissue inhibitor of MMP 

TiO2 titanium dioxide 

TK thymidine kinase 

TM transition metals 

TM5 Thematic Mapper, a sensor on Landsat5 satellite 

TMTU tetramethylthiourea 

TNF-α tumor necrosis factor alpha 

TOA top of the atmosphere 

TOF-SIMS time-of-flight - secondary ion mass spectrometry 

TOMS Total Ozone Mapping Spectrometer 

TOT/GC thermal optical transmission analyzer coupled with gas 

chromatography 

TOVS TIROS-N Operational Vertical Sounder 

tPA, t-PA tissue plasminogen activator 

TRACE Transition Region and Coronal Explorer 

TRP transient receptor potential 

TRPV1 transient receptor potential vanilloid-1 receptor 

TR-XRF total reflection X-ray fluorescence 

TSA trichostatin A 

TSP total suspended particulate 

TSS WRAP Technical Support System website 

TVOC total VOC 

TWP Tropical West Pacific island 
December 2009 lxxxvi 

TXB2 thromboxane B-2 

U uranium 

UACR urinary albumin / creatinine ratio 

UAE2 United Arab Emirates Unified Aerosol Experiment 

UAP urban ambient particle 

UF ultrafine, uncertainty factor 

UFAA ultrafine ambient air 

UFC ultrafine carbon 

UfCB ultrafine carbon black 

UFDG ultrafine diesel engine exhaust 

UFID ultrafine industrial exhaust 

UFP ultrafine particle 

UFPM ultrafine particulate matter 

UFTiO2 ultrafine titanium dioxide 

UIO University of Oslo 

U.K. United Kingdom 

UKMO United Kingdom Meteorological Office 

ULAQ University of lL’Aquila. 

ULTRA Exposure and Risk Assessment for Fine and Ultrafine Particles in 

Ambient Air 

UMI University of Michigan 

UNEP United Nations Environmental Programme 

UP urban particle 

UPM ultrafine particulate matter 

UPSP unmodified polystyrene particle(s) 

URI upper respiratory infection 

URS upper respiratory symptoms 

U.S. United States of America 

U.S.C. U.S. Code 

UV ultraviolet radiation 

V vanadium 

V, mV, μV volt, millivolt, microvolt 

VAQ visual air quality 

VCAM-1 vascular adhesion molecule 1 

Vd deposition velocity 

VEAPS Vitamin E Atherosclerosis Progression Study 
December 2009 lxxxvii 

VEGF vascular endothelial growth factor 

VIEWS Visibility Information Exchange Web Site 

VISTAS Visibility Improvement State and Tribal Association of the Southeast 

VOC volatile organic compound 

VOSO4 vanadyl sulfate 

VPB ventricular premature beat 

VR visual range 

VR1 vanilloid receptor 1 

VSCC very sharp cut cyclone 

VSMC Vascular Smooth Muscle Cells 

VT tidal volume 

vWF von Willebrand factor 

W Wilderness 

WACAP Western Airborne Contaminates Assessment Project 

WBC white blood cell(s) 

WC winter curbside particles 

WHI Women’s Health Initiative 

WHI OS Women’s Health Initiative Observational Study 

wk week(s) 

WKY Wistar-Kyoto rat strain 

W/m2

, W m-2 watts per square meter 

WMO World Meteorological Organization 

Wnt wingless gene family 

WRAP Western Regional Air Partnership 

WRF Weather Research and Forecasting model 

WS wood smoke 

WSOC water soluble organic carbon 

WUB winter urban background particles 

XAD polystyrene-divinyl benzene 

XPS X-ray photoelectron spectroscopy 

Y yttrium 

yr year 

Z radar reflectivity (measured in dBZ [decibels of Z, where Z represents 

the energy reflected back to the radar.]) 

Zn zinc 

ZnO zinc oxide 
December 2009 lxxxviii 

ZnS zinc sulfide 

ZnSO4 zinc sulfate 

Zr zirconium