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Advances in Applying Satellite Remote Sensing to the AQHI

Advances in Applying Satellite Remote Sensing to the AQHI. Randall Martin, Dalhousie and Harvard-Smithsonian Aaron van Donkelaar, Akhila Padmanabhan, Dalhousie University Lok Lamsal, Dalhousie U  NASA Goddard. 45 th CMOS Congress, Victoria 7 June 2011.

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Advances in Applying Satellite Remote Sensing to the AQHI

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  1. Advances in Applying Satellite Remote Sensing to the AQHI Randall Martin, Dalhousie and Harvard-Smithsonian Aaron van Donkelaar, Akhila Padmanabhan, Dalhousie University Lok Lamsal, Dalhousie U  NASA Goddard 45th CMOS Congress, Victoria 7 June 2011

  2. Large Regions Have Insufficient Measurements for AQHI Measurement Locations of NAPS Sites Southern Ontario

  3. Major Nadir-viewing Space-based Measurements of AQHI Species Solar Backscatter,Thermal Infrared, Active

  4. In Situ GEOS-Chem General Approach to Estimate Surface Concentrations NO2 Column Model Profile • S→ Surface Concentration • Ω → Tropospheric column

  5. Ground-Level Afternoon NO2 Inferred From OMI for 2005-2007 NO2 [ppbv] Lok Lamsal

  6. Ground-Level NO2 Inferred From OMI for 2005 Works in Near-Real-Time! Values Estimated Using Monthly NO2 Profiles for Different Year (2006) Temporal Correlation with In Situ Over 2005 ×In situ —— OMI Insignificant change in results if profiles are daily coincident values from 2005 Lok Lamsal

  7. Aerosol Most Visible over Dark Targets Pollution haze over East Coast Dust off West Africa

  8. Aerosol Optical Depth (AOD) from MODIS and MISR over 2001-2006 MODIS 1-2 days for global coverage (w/o clouds) AOD retrievals at 10 km x 10 km Requires assumptions about surface reflectivity MODIS r = 0.40 vs. in-situ PM2.5 MISR 6-9 days for global coverage (w/o clouds) AOD retrievals at 18 km x 18 km Simultaneous retrieval of surface reflectance and aerosol optical properties MISR r = 0.54 vs. in-situ PM2.5 0 0.1 0.2 0.3 AOD [unitless] van Donkelaar et al., EHP, 2010

  9. Agreement With AERONET Varies with Surface Type July MODIS MISR 9 surface types, defined by monthly mean surface albedo ratios, evaluation against AERONET AOD van Donkelaar et al., EHP, 2010

  10. Combined AOD from MODIS and MISRRejected Retrievals for Land Types with Monthly Error vs AERONET >0.1 or 20% 0.3 0.25 0.2 0.15 0.1 0.05 0 Combined MODIS/MISR r = 0.63(vs. in-situ PM2.5) AOD [unitless] MODIS r = 0.40 (vs. in-situ PM2.5) MISR r = 0.54 (vs. in-situ PM2.5) van Donkelaar et al., EHP, 2010

  11. Significant Agreement with Coincident In situ MeasurementsUsed GEOS-Chem to CalculateAOD/PM2.5 (η) 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

  12. Error Sources in Satellite-Derived PM2.5 Satellite-Derived [μg/m3] • Model • Affected by aerosol optical properties, concentrations, vertical profile, relative humidity • Most sensitive to vertical profile [van Donkelaar et al., 2006] • Evaluate vs Calipso lidar obs Satellite • Error limited to 0.1 + 20% by AERONET filter • Implication for satellite PM2.5 determined by AOD/PM2.5 In-situ PM2.5 [μg/m3] • Estimate error from bias in profile and AOD ±(1 μg/m3 + 15%) • Contains 68% (1 SD) of North American data van Donkelaar et al., EHP, 2010

  13. USA Today: Hundreds Dead from Heat, Smog, Wildfires in Moscow 9 Aug 2010: “Deaths in Moscow have doubled to an average of 700 people a day as the Russian capital is engulfed by poisonous smog from wildfires and a sweltering heat wave, a top health official said Monday.” MODIS/Aqua: 7 Aug 2010

  14. Spatial and Temporal Variation in Satellite-Based PM2.5 during Moscow 2010 Fires van Donkelaar et al., AE, submitted

  15. Satellite-Based PM2.5 Insensitive to Emission InventoryDaily Meteorology More Important Different Emission Inventories GEOS-Chem Calculation of AOD / PM2.5 van Donkelaar et al., AE, submitted

  16. Application of Satellite-based Estimates to Moscow Smoke Event During Fires Before Fires r2 =0.85, slope=1.06 MODIS-based In Situ from PM10 In Situ PM2.5 van Donkelaar et al., submitted

  17. Growing Confidence in Application of Satellite Remote Sensing for PM2.5 and NO2 • Simple Method for Near-Real-Time Estimates of Ground-Level NO2 • Satellite-based PM2.5 Estimate for Long-Term and Extreme Events • Ongoing Work • Develop daily PM2.5 estimate for Canada • Improve spatial resolution from 10 km to 3 km • Evaluate AOD/PM2.5 ratio Acknowledgements: Environment Canada, Health Canada, NASA

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