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Satellite Remote Sensing of Global Air Pollution PowerPoint Presentation
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Satellite Remote Sensing of Global Air Pollution

Satellite Remote Sensing of Global Air Pollution

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Satellite Remote Sensing of Global Air Pollution

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  1. Satellite Remote Sensing of Global Air Pollution Randall Martin, Dalhousie and Harvard-Smithsonian Aaron van Donkelaar, Dalhousie University Lok Lamsal, Dalhousie University  NASA Goddard with contributions from Michael Brauer, UBC Rob Levy, Ralph Kahn, NASA Symposium on Air Quality and Health in Atlantic Canada: New Directions and Opportunities 16 February 2011

  2. Large Regions Have Insufficient Measurements for Air Pollution Exposure Assessment Locations of Publicly-Available Long-Term PM2.5 Monitoring Sites Aaron van Donkelaar

  3. Aerosol Remote Sensing: Analogy with Visibility Effects of Aerosol Loading Waterton Lakes/Glacier National Park Pollution haze over East Coast 7.6 ug m-3 22 ug m-3

  4. Combined Aerosol Optical Depth (AOD)from MODIS and MISR Instruments for 2001-2006 Combined MODIS/MISR r = 0.63(vs. in-situ PM2.5) van Donkelaar et al., EHP, 2010

  5. Chemical Transport Model (GEOS-Chem) Simulation of Aerosol Optical Depth Aaron van Donkelaar

  6. Ground-level “Dry” PM2.5 = η·AOD η affected by vertical structure, aerosol properties, relative humidity Obtain η from aerosol-oxidant model (GEOS-Chem) sampled coincidently with satellite obs GEOS-Chem Simulation of η for 2001-2006 van Donkelaar et al., EHP, 2010

  7. Significant Agreement with Coincident In situ Measurements Annual Mean PM2.5 [μg/m3] (2001-2006) Satellite Derived Satellite-Derived [μg/m3] In-situ In-situ PM2.5 [μg/m3] van Donkelaar et al., EHP, 2010

  8. Global Climatology (2001-2006) of PM2.5 Evaluation with measurements outside Canada/US Better than in situ vs model (GEOS-Chem): r=0.52-0.62, slope = 0.63 – 0.71 van Donkelaar et al., EHP, 2010

  9. van Donkelaar et al., EHP, 2010

  10. van Donkelaar et al., EHP, 2010

  11. WHO Guideline & Interim Targets Long-term Exposure to Outdoor Ambient PM2.5 AQG IT-3 IT-2 IT-1 100 90 80 70 60 50 40 30 20 10 0 • 80% of global population exceeds WHO guideline of 10 μg/m3 • 35% of East Asia exposed to >50 μg/m3 in annual mean • Estimate health effects of PM2.5 exposure Population [%] 5 10 15 25 35 50 100 PM2.5 Exposure [μg/m3] van Donkelaar et al., EHP, 2010

  12. Emerging Applications Villeneuve et al., OEM, submitted Canadian non-smokers more likely to live in areas with higher concentrations of ambient PM2.5. Cigarette smoking will act as a negative confounder in epidemiological studies of long-term ambient air pollution and mortality outcomes in Canada Hystad et al., EHP, submitted, Satellite dataset dominant contributor to national PM2.5 model Evans et al. in prep: Estimate global mortality from PM2.5 Brauer et al. in prep; Estimate global burden of disease attributable to air pollution; uses satellite estimates and global model (TM5) Burnett et al., in prep; appears that satellite estimates better than in situ at predicting mortality

  13. Application of Satellite-based Estimates to Moscow Smoke Event During Fires Before Fires MODIS-based In Situ van Donkelaar et al., in prep

  14. In Situ GEOS-Chem General Approach to Estimate Surface NO2 Concentration Method: Solar backscatter NO2 Column Coincident ModelProfile l1 l2 Scattering by Earth surface and atmosphere Idealized NO2 absorption spectrum • S→ Surface Concentration • Ω → Tropospheric column l1 l2

  15. Ground-Level NO2 Inferred From OMI for 2005 Spatial Correlation vs In Situ for North America = 0.78 Lamsal et al., JGR, 2008

  16. Challenges Encouraging Prospects for Satellite Remote Sensing of Air Pollutants Remote Sensing: Improved algorithms to increase accuracy and observe other pollutants Modeling: Develop representation of processes Measurements: More needed for evaluation Health Applications: Close interaction to develop appropriate applications Acknowledgements: Health Canada NSERC NASA