1. Applications of Satellite Remote Sensing to Inform Air Quality Management Randall Martin with contributions from Aaron van Donkelaar, Brian Boys, Matthew Cooper, Shailesh Kharol, Colin Lee, Sajeev Philip Fall AGU San Francisco 3 Dec 2012 Daven Henze (UC Boulder), Yuxuan Wang (Tsinghua), Qiang Zhang (Tsinghua), Dan Crouse (Health Canada), Rick Burnett (Health Canada), Mike Brauer (UBC), Jeff Brook (Environment Canada), Aaron Cohen (HEI)

2. Vast Regions Have Insufficient Measurements for Exposure Assessment to Fine Particulate Matter (PM 2.5 ) Locations of Publicly-Available Long-Term PM 2.5 Monitoring Sites Previous WHO Global Burden of Disease Project for the Year 2000 Impaired by Insufficient Global Observations of PM 2.5 Cohen et al., 2005

3. General Approach to Estimate Surface Concentration Daily Satellite(MODIS, MISR, SeaWifs, OMI) Column of AOD or NO 2 S → Surface Concentration Ω → Tropospheric column Coincident Model (GEOS-Chem) Profile Altitude Concentration

4. Climatology (2001-2006) of MODIS- and MISR-Derived PM 2.5 van Donkelaar et al., EHP, 2010EHP Paper of the Year Evaluation in North America: r=0.77 slope = 1.07 N=1057 Included in current Global Burden of Disease report Outside Canada/US N = 244 (84 non-EU) r = 0.83 (0.83) Slope = 0.86 (0.91) Bias = 1.15 (-2.64) μg/m 3

5. Significant Association of Long-term PM 2.5 Exposure and Cardiovascular Mortality at Low PM 2.5 Crouse et al., EHP, 2012

6. ΔPM 2.5 [µg m -3 yr -1 ] 2 -2 Coherent PM 2.5 Trends Inferred from MISR and SeaWiFS AOD Uses Coincident AOD/PM 2.5 from GEOS-Chem Boys et al., in prep. 0 1 Tuesday, 5:24 3012 Moscone West MISR 2000 - 2011 SeaWiFS 1998 - 2010

7. SPARTAN: An Emerging Global Network to Evaluate and Enhance Satellite-Based Estimates of PM 2.5 Measures PM 2.5 Mass & Composition at AERONET sites PM 2.5 Sampling Station from Vanderlei Martins (Airphoton) Filter PM 2.5 & PM 10 3-λ Nephelometer AOD from CIMEL Sunphotometer (AERONET) www.spartan-network.org

8. PM 2.5 Nearly as Sensitive to Emissions of NO x as to SO 2 Kharol et al., GRL, in prep GEOS-Chem Calculation of Annual PM 2.5 Response to 10% Change in Emissions Supported by Comparison of GEOS-Chem vs IASI NH 3 ΔNO x Emissions ΔSO 2 Emissions ΔNH 3 Emissions 25% 41% 34% Using NH 3 emissions from Streets et al. (2003) reduced by 30% following Huang et al. (2012) DJF JJA IASI GC (w/AK) IASI - GC ΔPM 2.5 (ug m -3 ) -0.5 0 1 2

9. Change in PM 2.5 Exposure from Local Changes in Emissions Use GEOS-Chem Adjoint & Satellite PM 2.5 Distribution Lee et al., EHP, in prep Change in Global Premature Mortality for 10% change in Emissions Uses relation of exposure and mortality from Global Burden of Disease Project Δ Anthropogenic NO x EmissionsΔ Anthropogenic SO 2 Emissions

10. Observed TOA reflectance a priori AOD a posteriori AOD a priori error observational error Optimal Estimation allows: Error-constrained AOD solution Consistent optical properties Local reflectance information Chemical Transport Model CALIOP Space-borne LIDAR Optimal Estimation AOD CALIOP-adjusted AOD/PM 2.5 MODIS Imaging Spectroradiometer Optimal Estimation constrains AOD retrieval by error: Enhanced Algorithm to Infer PM 2.5 from MODIS van Donkelaar et al., in prep

11. Optimal Estimation Improves Global AOD Retrieval Used to Infer Global PM 2.5 van Donkelaar et al., in prep Western North America Eastern North America Europe Optimal Estimation AOD (Unitless) slope=1.47 r=0.65 slope=0.87 r=0.80 slope=0.55 r=0.53 slope=1.25 r=0.85 slope=0.95 r=0.86 slope=0.70 r=0.72 n = 29,976 n = 15,554 n = 25,497 slope=1.36 r=0.62 slope=1.11 r=0.77 slope=1.23 r=0.77

12. Use CALIOP Observations (2006-2011) to Correct Bias in Simulated Aerosol Extinction van Donkelaar et al., in prep η = PM 2.5 / AOD Southeast US China

13. Optimal Estimation Retrieval Improves Accuracy and Coverage MODIS-Derived PM 2.5 for 2005 van Donkelaar et al., in prep

14. A Satellite-Based Multipollutant Index from PM 2.5 & NO 2 OMI-derived NO 2 Indicator of Combustion Sources Cooper et al., ES&T, 2012 PM 2.5 NO 2 MPI 0 4 8 12 Multipollutant Index Satellite-Based Multipollutant Index (Unitless) Shanghai Beijing Delhi Karachi Seoul Cairo Lima Tehran Los Angeles Berlin Moscow Nairobi 0 1 2 5 7 9 11 13 15 AQG = WHO Air Quality Guideline PM 2.5 [μg/m 3 ] MPI [unitless] Eastern China 150 75 0 15 7.5 0 PM 2.5 [μg/m 3 ] MPI [unitless] Moscow 25 15 5 2.5 1.5 0.5

15. Numerous Opportunities to Inform Air Quality Management through Satellite Remote Sensing and Modeling Acknowledgements: NSERC, Environment Canada, Health Canada, NASA Particulate matter is major risk factor for global mortalityParticulate matter is major risk factor for global mortality Evidence of no lower limit on the health effects of PM 2.5Evidence of no lower limit on the health effects of PM 2.5 Controls on Chinese NO x emissions reduce PM 2.5Controls on Chinese NO x emissions reduce PM 2.5 SPARTAN and CALIOP evaluate AOD/PM 2.5 simulationSPARTAN and CALIOP evaluate AOD/PM 2.5 simulation Asian PM 2.5 increasing by 1-2 ug/m 3 /yrAsian PM 2.5 increasing by 1-2 ug/m 3 /yr Optimal estimation improves retrieval of PM 2.5Optimal estimation improves retrieval of PM 2.5 Satellite-based indicator of air pollution from PM 2.5 and NO 2Satellite-based indicator of air pollution from PM 2.5 and NO 2

16. Optimal Estimation Improves Global AOD Retrieval Used to Infer Global PM 2.5 van Donkelaar et al., in prep East Asia South Asia South America Optimal Estimation AOD (Unitless)