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Air Quality Applications of Satellite Remote Sensing

Air Quality Applications of Satellite Remote Sensing. Randall Martin, Dalhousie and Harvard-Smithsonian Aaron van Donkelaar, Akhila Padmanabhan, Dalhousie University Lok Lamsal, Dalhousie U  NASA Goddard with contributions from Rob Levy, Ralph Kahn, NASA.

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Air Quality Applications of Satellite Remote Sensing

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  1. Air Quality Applications of Satellite Remote Sensing Randall Martin, Dalhousie and Harvard-Smithsonian Aaron van Donkelaar, Akhila Padmanabhan, Dalhousie University Lok Lamsal, Dalhousie U  NASA Goddard with contributions from Rob Levy, Ralph Kahn, NASA 1st Workshop on Satellite Observations for Air Quality Management 9 May 2011

  2. Two Major Air Quality Applications of Satellite Observations of Atmospheric Composition Estimating Pollution Concentrations (regions w/o ground-based obs) (AQHI) Smog Alert Top-down Constraints on Emissions (to improve AQ simulations)

  3. Major Nadir-viewing Space-based Measurements of Tropospheric Trace Gases and Aerosols (Not Exhaustive) Solar Backscatter&Thermal Infrared

  4. Column Observations of Aerosol and NO2 Strongly Influenced by Boundary Layer Concentrations Weak Thermal Contrast Strong Rayleigh Scattering CO CO O3 O3 HCHO Aerosol SO2 NO2 9.6 2.2 4.7 0.52 0.62 0.75 0.30 0.36 0.43 Wavelength (μm) Vertical Profile Affects Boundary-Layer Information in Satellite Obs Normalized GEOS-ChemAnnual Mean Profiles over North America S(z) = shape factor C(z) = concentration Ω = column Aerosol Extinction SO2 NO2 O3 CO HCHO Martin, AE, 2008

  5. Temporal Correlation of AOD vs In Situ PM2.5 Correlation over Aug-Oct 2010

  6. 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

  7. 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

  8. 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

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

  10. 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

  11. Model (GC) CALIPSO (CAL) Evaluate GEOS-Chem Vertical Profile with CALIPSO Observations Altitude [km] • Coincidently sample model and CALIPSO extinction profiles • Jun-Dec 2006 • Compare % within boundary layer Optical depth above altitude z Total column optical depth τa(z)/τa(z=0)

  12. 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

  13. 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

  14. van Donkelaar et al., EHP, 2010

  15. 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 Global mortality from PM2.5 2-8 million deaths/year (Evans et al., EHP, submitted) Used in WHO Global Burden of Disease assessment Significant association of PM2.5 and health at low PM2.5 levels (Crouse et al., EHP, in prep) Population [%] 5 10 15 25 35 50 100 PM2.5 Exposure [μg/m3] van Donkelaar et al., EHP, 2010

  16. 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

  17. Relaxed Cloud Screening Needed for Extreme Events van Donkelaar et al., submitted

  18. Application of Satellite-based Estimates to Moscow Smoke Event During Fires Before Fires MODIS-based In Situ from PM10 In Situ PM2.5 van Donkelaar et al., submitted

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

  20. 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

  21. Ground-Level NO2 Inferred From OMI for 2005 Spatial Correlation vs In Situ for North America = 0.78 Lok Lamsal

  22. Bottom-Up Emission Inventories Take Years to CompileBottom-up Anthropogenic NOx Emission Inventory from Land Sources for 2006 Based on EDGAR (2000), CAC (2005), NEI2005, BRAVO (1999), EMEP (2006), Zhang (2006), scaled to 2006

  23. 1996 - 2002 Changes in Tropospheric NO2 Column Reflect Changes in NOx Emissions Trend in Tropospheric NO2 Column over 1996-2002 from GOME Richter et al., 2005

  24. Application of Satellite Observations for Timely Updates to NOx Emission Inventories Use GEOS-Chem to Calculate Local Sensitivity of Changes in Trace Gas Column to Changes in Emissions Fractional Change in Emissions Fractional Change in Trace Gas Column Local sensitivity of column changes to emissions changes Insensitive to changes in anthropogenic CO and VOCs Walker et al., ACP, 2010 Lamsal et al., GRL, 2011

  25. Evaluate Hindcast Inventory Versus Bottom-upHindcast for 2003 Based on Bottom-up for 2006 and Monthly NO2 for 2003-2006 Bottom-up Hindcast Lamsal et al., GRL, 2011

  26. Forecast Inventory for 2009 Based on Bottom-up for 2006 and Monthly OMI NO2 for 2006-2009 Temporary Dataset Until Bottom-Up Inventory Available 9% increase in global emissions 19% increase in Asian emissions 6% decrease in North American emissions Lamsal et al., GRL, 2011

  27. Emerging Applications of Satellite Remote Sensing of Atmospheric Composition Chemical Transport Model Plays a Valuable Role in Relating Retrieved and Desired Quantity • Ground-level Estimates of PM2.5 & NO2 • Simple Method for Timely Updates to NOx Emission Inventories • Challenge • Continue to develop retrieval capability • Evaluate and improve simulation to relate retrieved and desired quantity • (includes AOD/PM2.5, NO2 / NOx emissions) Acknowledgements: NSERC, Environment Canada, Health Canada, NASA

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