Air Quality and Human Health 2004 Olympic Games Athens, Greece Karsten Baumann Georgia Institute of Technology School of

1. Research Opportunities Air Quality and Human Health2004 Olympic GamesAthens, GreeceKarsten BaumannGeorgia Institute of TechnologySchool of Earth & Atmospheric Sciences kb@eas.gatech.edu

2. 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. 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. kb@eas.gatech.edu

3. 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 IS THIS SUFFICIENT ? kb@eas.gatech.edu

4. 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 Athens kb@eas.gatech.edu

5. Georgia Institute of Technology Centers for Disease Control Emory University Asthma Clinic Research Institute (GTRI) Air Resources Engineering Center (AREC) • Atmospheric chemistry • Air quality monitoring • Aerosol characterization • Forecasting • Air quality modeling • Emissions from motor vehicles • Emissions modeling • NEXLASER Ozone and aerosol lidar • Indoor air quality monitors The US Research Team kb@eas.gatech.edu

6. 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 kb@eas.gatech.edu

7. 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 kb@eas.gatech.edu

8. May-Sep &Oct-Apr Benefits of Network Measurements kb@eas.gatech.edu

9. Benefits of Detailed Measurements kb@eas.gatech.edu

10. 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 press kb@eas.gatech.edu

11. Benefits of High-Rise PlatformO3 High-Rise O3 levels are significantly higher early mornings and lower at midday http://www.utexas.edu/research/ceer/texaqs/ kb@eas.gatech.edu

12. Benefits of High-Rise PlatformPM2.5 Positive vertical [PM2.5] ‘gradients’ favored more often at night than at day http://www.utexas.edu/research/ceer/texaqs/ kb@eas.gatech.edu

13. 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 forcing kb@eas.gatech.edu

14. Aerosols Regional to Global Effects kb@eas.gatech.edu

15. 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?) dust kb@eas.gatech.edu

16. 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) kb@eas.gatech.edu

17. Transient Events in Atlanta Midday sulfate peaks from downmixed power plant plumes. Morning rush hour EC/OC. kb@eas.gatech.edu

18. Sources for Atlanta Sulfate Most intense during stagnation events. Links to health effects?! (Weber et al., JAWMA in Jan 2003) kb@eas.gatech.edu

19. TRACE-P Biomass Burning • Mixed plumes - near northern coastal areas of China, Korea, and Japan. • On average, about 305% 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 F14 6210% F19 182% F10 10015% kb@eas.gatech.edu

20. 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 OC kb@eas.gatech.edu

21. Ongoing Joint PBS* 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 *) US-DOD funded “Study of Air Quality Impacts Resulting from Prescribed Burning on Military Facilities” 2002. kb@eas.gatech.edu

22. Pensacola, FL October 1999 Diesel exhaust 20% Gasoline exhaust Other organic 3% carbon 30% Vegetative detritus 2% Meat cooking 6% Wood combustion 39% Source Contributions to OC Zheng et al., ES&T 2002 kb@eas.gatech.edu

23. 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) kb@eas.gatech.edu

24. 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 models kb@eas.gatech.edu

25. 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 & transformation kb@eas.gatech.edu

26. Mobile Emissions On-Board Monitoring (A.Unal) Effect of Traffic Congestion on Vehicle Emissions Allows measurement of vehicle emissions and engine parameters under real-world conditions Enables finding relationships between vehicle emissions and traffic parameters kb@eas.gatech.edu

27. Adaptive Grid Sensitivity Analysis Computer Simulation with Air Quality Model Strategy Design Impact to Downwind City Controlled Burning at Military Base Adaptive Grid Modeling Direct sensitivity analysis for predicting the air quality impacts of anthropogenic activities. Part of DOD-funded “Study of Air Quality Impacts Resulting from Prescribed Burning on Military Facilities” 2003 kb@eas.gatech.edu

28. Adaptive Grid Air Quality Model kb@eas.gatech.edu

29. Superior O3 Predictions Sumner Co., TN Graves Co., KY kb@eas.gatech.edu

30. Sensitivity of O3 to NOx Emissions kb@eas.gatech.edu

31. Additional AREC Contributors MINOS Asian Monsoon Plume modeled by MATCH-MPIC => Lawrence et al., Atmos. Chem. Phys. Discuss., 2002: http://www.atmos-chem-phys.org See also Lelieveld et al., Science 298, 2002 kb@eas.gatech.edu

32. 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 Video kb@eas.gatech.edu

33. 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 Compression kb@eas.gatech.edu

34. Robotic Aircraft UAV Skyhook Retrieval System for launch and retrieval over sea US Patent 6,264,140 International Patents in Process kb@eas.gatech.edu

35. 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 analysis kb@eas.gatech.edu

36. 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 measurements kb@eas.gatech.edu

37. 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 kb@eas.gatech.edu

38. 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, exposure kb@eas.gatech.edu

39. 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 health kb@eas.gatech.edu

40. 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 kb@eas.gatech.edu