1 / 16

Satellite Remote Sensing of Global Air Pollution

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.

hateya
Download Presentation

Satellite Remote Sensing of Global Air Pollution

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  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

More Related