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Premium member Presentation Transcript Air Quality and Human Health2004 Olympic GamesAthens, GreeceKarsten BaumannGeorgia Institute of TechnologySchool of Earth & Atmospheric Sciences: Air Quality and Human Health 2004 Olympic Games Athens, Greece Karsten Baumann Georgia Institute of Technology School of Earth & Atmospheric Sciences Research OpportunitiesAsthma Epidemic: Emergency room visits for treatment of asthma increase by 30-40 % when ambient ozone levels are elevated. The US EPA estimates that more than 110 million people reside in counties where the air is consistently unhealthy due to periodic ozone pollution. Asthma Epidemic The percentage of the US population with the disease has nearly doubled since 1980. In 2000, ~11 million people suffered an asthma attack. Sources: Morbidity & Mortality: 2002 Chart Book on Cardiovascular, Lung, and Blood Diseases; National Institutes of Health, National Heart, Lung, and Blood Institute, 2002. Latest Findings on National Air Quality: 2001 Status and Trends; EPA 454/K-02-001; US EPA Office of Air Quality Planning and Standards (OAQPS); September 2002. Urban Air Pollution: Athens 2004 Air Quality Study, 1997 Moussiopoulos & Papagrigoriou Aristotle University Thessaloniki & Laboratory of Heat Transfer and Environmental Engineering (LHTEE), Thessaloniki, Greece Renewal of the Athenian vehicle fleet Exclusion of most polluting passenger cars Reducing [NOx] from heavy-duty vehicles Minor effects from pedestrian zones Urban Air Pollution IS THIS SUFFICIENT ?Potential US Contributions: Potential US Contributions Comprehensive characterization of air quality Baseline measurements 3 weeks before and 3 weeks after Olympics Indoor and outdoor measurements / modeling All measurements before, during, and after the games Local population and athlete exposure to pollution Relate pollutant levels to human health effects Model / monitor effects of emissions reductions Long-term monitoring to the benefit of AthensThe US Research Team: The US Research TeamAREC Team: AREC Team Baumann, EAS, director, lab & field operations Bergin, EAS/CEE prof, aerosol optical properties Chang, EAS, Sr RS, urban AQ modeling Nenes, EAS prof, heterogeneous modeling Odman, CEE, Sr RE, adaptive grid modeling Russell, CEE head, emissions UAM Weber, EAS, prof, aerosol in situ R&D Zheng, EAS, RS, lab & field operations, CMB AREC Measurements: AREC Measurements Karsten Baumann, kb@eas.gatech.edu Aerosol characterization High-res precurser gases and low-res PM composition Air quality monitoring network in TN and GA Seasonal differences in AQ character {transport & formation} Atmospheric chemistry and aerosol transformation (SOS, SCISSAP, ChinaMAP, FAQS, TexAQS, PERCH) Mobile laboratory for coordinated integrated deployments Vertical gradients utilizing high-rise buildings and towers Diagnostic analyses and collaborative evaluations Source identification, BL transport, photochemical transformation Benefits of Network Measurements: Benefits of Network MeasurementsBenefits of Detailed Measurements: Benefits of Detailed MeasurementsBenefits … Towards SOA: Benefits … Towards SOA Regional Difference: Higher OM/OC and OC/EC at more rural site! Seasonal Difference: Lower OM/OC and higher OC/EC in winter. Baumann et al., JGR in pressBenefits of High-Rise PlatformO3: High-Rise O3 levels are significantly higher early mornings and lower at midday http://www.utexas.edu/research/ceer/texaqs/ Benefits of High-Rise Platform O3Benefits of High-Rise PlatformPM2.5: Benefits of High-Rise Platform PM2.5 Positive vertical [PM2.5] ‘gradients’ favored more often at night than at day http://www.utexas.edu/research/ceer/texaqs/AREC Measurements: AREC Measurements Mike Bergin, mhbergin@ce.gatech.edu Aerosol characterization Linking physical, optical and chemical properties Natural background versus anthropogenic influence Air quality and visibility Track changes in mode and hygroscopicity (ssp vs sap) Link observed changes to air mass history and transport Climate change Less uncertain aerosol parameters for climate models Effects on regional climate, BL stability, photosynthesis Spatial and temporal variations in radiative forcingAerosols Regional to Global Effects: Aerosols Regional to Global EffectsMajor Findings: Major Findings Tasmania—predominance of seasalt aerosol indicative of a true background marine site Wavelength independence, predominance of coarse mode, strongly hygroscopic/deliquescent aerosol, light scattering >> light absorption Portugal and Atlanta—anthropogenic perturbation of aerosol results in factor of 5-10 greater impact on radiative transfer Strong wavelength dependence, predominance of fine mode, suppressed hygroscopic growth, light scattering > light absorption Nepal—strong seasonal cycle with spring-time peak comparable to urban areas and possible monsoon impacts Low concentrations during monsoon, Pre-monsoon “dusty period with evidence of long-range transport of mineral (Saharan?) dustAREC Measurements: AREC Measurements Rodney Weber, rweber@eas.gatech.edu Aerosol chemical characterization (PILS) High-resolution PM2.5 composition at ground & airborne Source apportionment from transient events Mobile versus point sources, biomass burning, dust Aerosol chemistry w/in large field campaigns (SCISSAP, FAQS, TexAQS, ACE-Asia, TRACE-P) Source apportionment in plumes (see transients above) Chemical transformation of transported aerosol (box model) New particle formation (nucleation)Slide17: Transient Events in Atlanta Midday sulfate peaks from downmixed power plant plumes. Morning rush hour EC/OC.Sources for Atlanta Sulfate: Sources for Atlanta Sulfate Most intense during stagnation events. Links to health effects?! (Weber et al., JAWMA in Jan 2003)Slide19: Mixed plumes - near northern coastal areas of China, Korea, and Japan. On average, about 305% of the fine PM mass in the mixed plumes is from BB emissions. K+ is good tracer for BB. Molar ratio of dK+/dSO42- useful to estimate relative influence of BB on PM2.5 mass in mixed plumes. Limitation of the method Dust contribution Check for correlations Ma et al., JGR, submitted 2002 F10 10015% F14 6210% F19 182% TRACE-P Biomass BurningAREC Measurements: AREC Measurements Mei Zheng, mzheng@eas.gatech.edu Aerosol particle-phase organics speciation GC-MS analysis of high-volume samples Field campaigns in SE-US and China (ChinaMAP, PRDS, PERCH, ACE-Asia) Chemical mass balance (CMB) receptor model Source apportionment to PM2.5 and OCSlide21: Detect > 100 POC species n-alkanes, branched alkanes, cycloalkanes n-alkanoic acids, n-alkenoic acids alkanedioic acids PAHs, oxy-PAHs retene steranes hopanes resin acids pimaric acid abietic acid sandaracopimaric acid aromatic acids levoglucosan Ongoing Joint PBS* *) US-DOD funded “Study of Air Quality Impacts Resulting from Prescribed Burning on Military Facilities” 2002. Source Contributions to OC: Source Contributions to OC Zheng et al., ES&T 2002AREC Modeling: AREC Modeling Mike Chang, chang@eas.gatech.edu http://www.cure.gatech.edu/faqs.asp Thanos Nenes, nenes@eas.gatech.edu Inverse modeling Urban Airshed Model (UAM)-AERO successful in LA 1987 SCAQS (Lurmann et al., 1997) SAPRC-90 gas phase mechanism (n=133, R=130) Online aerosol dynamics with inorganic component resolved (H2O, Na, Cl, NO3, NH4,SO4), incl OC/EC Evolution of aerosol described by mass balance ISORROPIA (Nenes et al., 1998)AREC Modeling: AREC Modeling Thanos Nenes, nenes@eas.gatech.edu UAM-AERO (continued) Collaboration with the University of the Aegean applied to simulate the atmospheric conditions in the Athens basin (Sotiropoulou et al., in preparation). CAMx (www.camx.com) “Next-generation” modeling system SAPRC-99 improved from version 90 Parallel processing & nested grid Sotiropoulou et al., in preparation Both can be nested into larger scale modelsAREC Modeling: AREC Modeling Ted Russell, trussell@ce.gatech.edu Talat Odman, talat.odman@ce.gatech.edu http://environmental.gatech.edu/~odman/page2.html Emissions modeling Emissions inventory & inverse modeling Onboard measurements Regional air quality impacts modeling Sensitivities to changes in anthropogenic emissions Advanced adaptive grid modeling Sub-regional pollutants transport & transformationSlide26: Allows measurement of vehicle emissions and engine parameters under real-world conditions Mobile Emissions On-Board Monitoring (A.Unal) Effect of Traffic Congestion on Vehicle Emissions Enables finding relationships between vehicle emissions and traffic parametersSlide27: Direct sensitivity analysis for predicting the air quality impacts of anthropogenic activities. Adaptive Grid Modeling Part of DOD-funded “Study of Air Quality Impacts Resulting from Prescribed Burning on Military Facilities” 2003 Adaptive Grid Air Quality Model: Adaptive Grid Air Quality ModelSuperior O3 Predictions: Superior O3 Predictions Sumner Co., TN Graves Co., KYSensitivity of O3 to NOx Emissions : Sensitivity of O3 to NOx Emissions MINOS Asian Monsoon Plume modeled by MATCH-MPIC: MINOS Asian Monsoon Plume modeled by MATCH-MPIC Additional AREC Contributors => Lawrence et al., Atmos. Chem. Phys. Discuss., 2002: http://www.atmos-chem-phys.org See also Lelieveld et al., Science 298, 2002Additional AREC Contributors: Additional AREC Contributors Judy Curry, EAS Chair, curryja@eas.gatech.edu Robotic Aircraft UAV (Aerosonde, Seascan) Small Size Long Range & Endurance Autonomous Operations Automated Missions Payload 2 to 5 kg Sensor R&D Ample Power > 100 watts Real-Time Full-Motion VideoRobotic Aircraft UAV: Robotic Aircraft UAV Color Video System Pan / Tilt / Zoom Inertial Stabilization Image Processing Eliminate Unwanted Motion Analog Link to 30 Miles Longer Range with Digital CompressionRobotic Aircraft UAV: Robotic Aircraft UAV US Patent 6,264,140 International Patents in Process Skyhook Retrieval System for launch and retrieval over seaProposed GT Measurements: Proposed GT Measurements Complement existing monitoring network Establish comprehensive sites: urban, rural, high-rise, hill-top Identify rural location Top of downtown high-rise best represents urban AQ Olympic Village site if possible Ideally, upgrade existing urban site in collaboration with locals Conduct advanced measurements Evaluate effects of public transportation mediation relate AQ conditions to traffic activities Analyze visibility degradation Poor visibility is noticed by the public and associated with air pollution Sources of degradation will be identified and quantified Information useful in health impact analysisProposed GT Modeling: Proposed GT Modeling Simulate Athens air quality during Olympics Apply model with direct source-impact tool Show impact of specific sources on ozone and PM species (diesel, biogenic, cooking, etc.) Validate emissions inventory Work with health scientists Link emissions sources to air quality to health Model exposure at finer scale than measurementsResearch Topics: Research Topics Measurements Air Quality Indoor Outdoor In Situ Lidar Satellite Meteorology Emissions Surveys Traffic Monitoring Health Monitoring Modeling Air Quality Emissions BL transport Physical-Chemical Transformation Forecasting Meteorology Exposure Health Asthma in Athletes Asthma in Athens Population Relationship of Exposure to Respiratory and Cardiac Disease Epidemiology US Research Team: US Research Team Gary G. Gimmestad – GT/GTRI Senior Faculty Leader in remote sensing technology development Leanne L. West – GT/GTRI Co-Director of Health Science and Technology Research, UV lidar systems Charlene Bayer – GT/GTRI Indoor air quality, asthma triggers, exposure Ted Russell – GT/CEE Air quality modeling, emission inventories, visibility, exposureUS Research Team: US Research Team Karsten Baumann – GT/EAS Field measurements coordinator, BL transport, physical-chemical transformation of atmospheric constituents W. Gerald Teague – Emory Asthma Center Relationship of air quality problems to asthma attacks Michael S. Friedman – CDC Effects of air quality problems on human healthAnticipated Benefits: Anticipated Benefits Better understanding of Athens air quality Demonstration of improvement strategies Improved forecasting Link between sources and health Insight for “Green Olympics” in Beijing 2008 These benefits will help all cities with air quality problems, give insights to improving human health, and will become part of the International Olympics Legacy You do not have the permission to view this presentation. In order to view it, please contact the author of the presentation.
030117d OlympAQS ECJRC Baumann concept Durante Download Post to : URL : Related Presentations : Share Add to Flag Embed Email Send to Blogs and Networks Add to Channel Uploaded from authorPOINTLite Insert YouTube videos in PowerPont slides with aS Desktop Copy embed code: (To copy code, click on the text box) Embed: URL: Thumbnail: WordPress Embed Customize Embed The presentation is successfully added In Your Favorites. Views: 53 Category: Education License: All Rights Reserved Like it (0) Dislike it (0) Added: May 02, 2008 This Presentation is Public Favorites: 0 Presentation Description No description available. Comments Posting comment... Premium member Presentation Transcript Air Quality and Human Health2004 Olympic GamesAthens, GreeceKarsten BaumannGeorgia Institute of TechnologySchool of Earth & Atmospheric Sciences: Air Quality and Human Health 2004 Olympic Games Athens, Greece Karsten Baumann Georgia Institute of Technology School of Earth & Atmospheric Sciences Research OpportunitiesAsthma Epidemic: Emergency room visits for treatment of asthma increase by 30-40 % when ambient ozone levels are elevated. The US EPA estimates that more than 110 million people reside in counties where the air is consistently unhealthy due to periodic ozone pollution. Asthma Epidemic The percentage of the US population with the disease has nearly doubled since 1980. In 2000, ~11 million people suffered an asthma attack. Sources: Morbidity & Mortality: 2002 Chart Book on Cardiovascular, Lung, and Blood Diseases; National Institutes of Health, National Heart, Lung, and Blood Institute, 2002. Latest Findings on National Air Quality: 2001 Status and Trends; EPA 454/K-02-001; US EPA Office of Air Quality Planning and Standards (OAQPS); September 2002. Urban Air Pollution: Athens 2004 Air Quality Study, 1997 Moussiopoulos & Papagrigoriou Aristotle University Thessaloniki & Laboratory of Heat Transfer and Environmental Engineering (LHTEE), Thessaloniki, Greece Renewal of the Athenian vehicle fleet Exclusion of most polluting passenger cars Reducing [NOx] from heavy-duty vehicles Minor effects from pedestrian zones Urban Air Pollution IS THIS SUFFICIENT ?Potential US Contributions: Potential US Contributions Comprehensive characterization of air quality Baseline measurements 3 weeks before and 3 weeks after Olympics Indoor and outdoor measurements / modeling All measurements before, during, and after the games Local population and athlete exposure to pollution Relate pollutant levels to human health effects Model / monitor effects of emissions reductions Long-term monitoring to the benefit of AthensThe US Research Team: The US Research TeamAREC Team: AREC Team Baumann, EAS, director, lab & field operations Bergin, EAS/CEE prof, aerosol optical properties Chang, EAS, Sr RS, urban AQ modeling Nenes, EAS prof, heterogeneous modeling Odman, CEE, Sr RE, adaptive grid modeling Russell, CEE head, emissions UAM Weber, EAS, prof, aerosol in situ R&D Zheng, EAS, RS, lab & field operations, CMB AREC Measurements: AREC Measurements Karsten Baumann, kb@eas.gatech.edu Aerosol characterization High-res precurser gases and low-res PM composition Air quality monitoring network in TN and GA Seasonal differences in AQ character {transport & formation} Atmospheric chemistry and aerosol transformation (SOS, SCISSAP, ChinaMAP, FAQS, TexAQS, PERCH) Mobile laboratory for coordinated integrated deployments Vertical gradients utilizing high-rise buildings and towers Diagnostic analyses and collaborative evaluations Source identification, BL transport, photochemical transformation Benefits of Network Measurements: Benefits of Network MeasurementsBenefits of Detailed Measurements: Benefits of Detailed MeasurementsBenefits … Towards SOA: Benefits … Towards SOA Regional Difference: Higher OM/OC and OC/EC at more rural site! Seasonal Difference: Lower OM/OC and higher OC/EC in winter. Baumann et al., JGR in pressBenefits of High-Rise PlatformO3: High-Rise O3 levels are significantly higher early mornings and lower at midday http://www.utexas.edu/research/ceer/texaqs/ Benefits of High-Rise Platform O3Benefits of High-Rise PlatformPM2.5: Benefits of High-Rise Platform PM2.5 Positive vertical [PM2.5] ‘gradients’ favored more often at night than at day http://www.utexas.edu/research/ceer/texaqs/AREC Measurements: AREC Measurements Mike Bergin, mhbergin@ce.gatech.edu Aerosol characterization Linking physical, optical and chemical properties Natural background versus anthropogenic influence Air quality and visibility Track changes in mode and hygroscopicity (ssp vs sap) Link observed changes to air mass history and transport Climate change Less uncertain aerosol parameters for climate models Effects on regional climate, BL stability, photosynthesis Spatial and temporal variations in radiative forcingAerosols Regional to Global Effects: Aerosols Regional to Global EffectsMajor Findings: Major Findings Tasmania—predominance of seasalt aerosol indicative of a true background marine site Wavelength independence, predominance of coarse mode, strongly hygroscopic/deliquescent aerosol, light scattering >> light absorption Portugal and Atlanta—anthropogenic perturbation of aerosol results in factor of 5-10 greater impact on radiative transfer Strong wavelength dependence, predominance of fine mode, suppressed hygroscopic growth, light scattering > light absorption Nepal—strong seasonal cycle with spring-time peak comparable to urban areas and possible monsoon impacts Low concentrations during monsoon, Pre-monsoon “dusty period with evidence of long-range transport of mineral (Saharan?) dustAREC Measurements: AREC Measurements Rodney Weber, rweber@eas.gatech.edu Aerosol chemical characterization (PILS) High-resolution PM2.5 composition at ground & airborne Source apportionment from transient events Mobile versus point sources, biomass burning, dust Aerosol chemistry w/in large field campaigns (SCISSAP, FAQS, TexAQS, ACE-Asia, TRACE-P) Source apportionment in plumes (see transients above) Chemical transformation of transported aerosol (box model) New particle formation (nucleation)Slide17: Transient Events in Atlanta Midday sulfate peaks from downmixed power plant plumes. Morning rush hour EC/OC.Sources for Atlanta Sulfate: Sources for Atlanta Sulfate Most intense during stagnation events. Links to health effects?! (Weber et al., JAWMA in Jan 2003)Slide19: Mixed plumes - near northern coastal areas of China, Korea, and Japan. On average, about 305% of the fine PM mass in the mixed plumes is from BB emissions. K+ is good tracer for BB. Molar ratio of dK+/dSO42- useful to estimate relative influence of BB on PM2.5 mass in mixed plumes. Limitation of the method Dust contribution Check for correlations Ma et al., JGR, submitted 2002 F10 10015% F14 6210% F19 182% TRACE-P Biomass BurningAREC Measurements: AREC Measurements Mei Zheng, mzheng@eas.gatech.edu Aerosol particle-phase organics speciation GC-MS analysis of high-volume samples Field campaigns in SE-US and China (ChinaMAP, PRDS, PERCH, ACE-Asia) Chemical mass balance (CMB) receptor model Source apportionment to PM2.5 and OCSlide21: Detect > 100 POC species n-alkanes, branched alkanes, cycloalkanes n-alkanoic acids, n-alkenoic acids alkanedioic acids PAHs, oxy-PAHs retene steranes hopanes resin acids pimaric acid abietic acid sandaracopimaric acid aromatic acids levoglucosan Ongoing Joint PBS* *) US-DOD funded “Study of Air Quality Impacts Resulting from Prescribed Burning on Military Facilities” 2002. Source Contributions to OC: Source Contributions to OC Zheng et al., ES&T 2002AREC Modeling: AREC Modeling Mike Chang, chang@eas.gatech.edu http://www.cure.gatech.edu/faqs.asp Thanos Nenes, nenes@eas.gatech.edu Inverse modeling Urban Airshed Model (UAM)-AERO successful in LA 1987 SCAQS (Lurmann et al., 1997) SAPRC-90 gas phase mechanism (n=133, R=130) Online aerosol dynamics with inorganic component resolved (H2O, Na, Cl, NO3, NH4,SO4), incl OC/EC Evolution of aerosol described by mass balance ISORROPIA (Nenes et al., 1998)AREC Modeling: AREC Modeling Thanos Nenes, nenes@eas.gatech.edu UAM-AERO (continued) Collaboration with the University of the Aegean applied to simulate the atmospheric conditions in the Athens basin (Sotiropoulou et al., in preparation). CAMx (www.camx.com) “Next-generation” modeling system SAPRC-99 improved from version 90 Parallel processing & nested grid Sotiropoulou et al., in preparation Both can be nested into larger scale modelsAREC Modeling: AREC Modeling Ted Russell, trussell@ce.gatech.edu Talat Odman, talat.odman@ce.gatech.edu http://environmental.gatech.edu/~odman/page2.html Emissions modeling Emissions inventory & inverse modeling Onboard measurements Regional air quality impacts modeling Sensitivities to changes in anthropogenic emissions Advanced adaptive grid modeling Sub-regional pollutants transport & transformationSlide26: Allows measurement of vehicle emissions and engine parameters under real-world conditions Mobile Emissions On-Board Monitoring (A.Unal) Effect of Traffic Congestion on Vehicle Emissions Enables finding relationships between vehicle emissions and traffic parametersSlide27: Direct sensitivity analysis for predicting the air quality impacts of anthropogenic activities. Adaptive Grid Modeling Part of DOD-funded “Study of Air Quality Impacts Resulting from Prescribed Burning on Military Facilities” 2003 Adaptive Grid Air Quality Model: Adaptive Grid Air Quality ModelSuperior O3 Predictions: Superior O3 Predictions Sumner Co., TN Graves Co., KYSensitivity of O3 to NOx Emissions : Sensitivity of O3 to NOx Emissions MINOS Asian Monsoon Plume modeled by MATCH-MPIC: MINOS Asian Monsoon Plume modeled by MATCH-MPIC Additional AREC Contributors => Lawrence et al., Atmos. Chem. Phys. Discuss., 2002: http://www.atmos-chem-phys.org See also Lelieveld et al., Science 298, 2002Additional AREC Contributors: Additional AREC Contributors Judy Curry, EAS Chair, curryja@eas.gatech.edu Robotic Aircraft UAV (Aerosonde, Seascan) Small Size Long Range & Endurance Autonomous Operations Automated Missions Payload 2 to 5 kg Sensor R&D Ample Power > 100 watts Real-Time Full-Motion VideoRobotic Aircraft UAV: Robotic Aircraft UAV Color Video System Pan / Tilt / Zoom Inertial Stabilization Image Processing Eliminate Unwanted Motion Analog Link to 30 Miles Longer Range with Digital CompressionRobotic Aircraft UAV: Robotic Aircraft UAV US Patent 6,264,140 International Patents in Process Skyhook Retrieval System for launch and retrieval over seaProposed GT Measurements: Proposed GT Measurements Complement existing monitoring network Establish comprehensive sites: urban, rural, high-rise, hill-top Identify rural location Top of downtown high-rise best represents urban AQ Olympic Village site if possible Ideally, upgrade existing urban site in collaboration with locals Conduct advanced measurements Evaluate effects of public transportation mediation relate AQ conditions to traffic activities Analyze visibility degradation Poor visibility is noticed by the public and associated with air pollution Sources of degradation will be identified and quantified Information useful in health impact analysisProposed GT Modeling: Proposed GT Modeling Simulate Athens air quality during Olympics Apply model with direct source-impact tool Show impact of specific sources on ozone and PM species (diesel, biogenic, cooking, etc.) Validate emissions inventory Work with health scientists Link emissions sources to air quality to health Model exposure at finer scale than measurementsResearch Topics: Research Topics Measurements Air Quality Indoor Outdoor In Situ Lidar Satellite Meteorology Emissions Surveys Traffic Monitoring Health Monitoring Modeling Air Quality Emissions BL transport Physical-Chemical Transformation Forecasting Meteorology Exposure Health Asthma in Athletes Asthma in Athens Population Relationship of Exposure to Respiratory and Cardiac Disease Epidemiology US Research Team: US Research Team Gary G. Gimmestad – GT/GTRI Senior Faculty Leader in remote sensing technology development Leanne L. West – GT/GTRI Co-Director of Health Science and Technology Research, UV lidar systems Charlene Bayer – GT/GTRI Indoor air quality, asthma triggers, exposure Ted Russell – GT/CEE Air quality modeling, emission inventories, visibility, exposureUS Research Team: US Research Team Karsten Baumann – GT/EAS Field measurements coordinator, BL transport, physical-chemical transformation of atmospheric constituents W. Gerald Teague – Emory Asthma Center Relationship of air quality problems to asthma attacks Michael S. Friedman – CDC Effects of air quality problems on human healthAnticipated Benefits: Anticipated Benefits Better understanding of Athens air quality Demonstration of improvement strategies Improved forecasting Link between sources and health Insight for “Green Olympics” in Beijing 2008 These benefits will help all cities with air quality problems, give insights to improving human health, and will become part of the International Olympics Legacy