Aaron van Donkelaar 1 , Randall Martin 1,2 , Ralph Kahn 3 and Robert Levy 3

1. Global Climatology of Fine Particulate Matter Concentrations Estimated from Remote-Sensed Aerosol Optical Depth Aaron van Donkelaar1, Randall Martin1,2, Ralph Kahn3 and Robert Levy3 International Aerosol Modeling Algorithms December 9-11, 2009 1Dalhousie University 2Harvard-Smithsonian 3NASA Goddard

2. Approach • vertical structure • aerosol type • meteorological effects • meteorology • diurnal effects η We relate satellite-based measurements of aerosol optical depth to PM2.5 using a global chemical transport model Following Liu et al., 2004: Estimated PM2.5 = η· τ Combined MODIS/MISR Aerosol Optical Depth GEOS-Chem

3. MODIS and MISR τ Mean τ2001-2006 at 0.1º x 0.1º MODIS τ • 1-2 days for global coverage • Requires assumptions about surface reflectivity MODIS r = 0.40 vs. in-situ PM2.5 MISR τ • 6-9 days for global coverage • Simultaneous surface reflectance and aerosol retrieval MISR r = 0.54 vs. in-situ PM2.5 0 0.1 0.2 0.3 τ [unitless] Submitted to Environmental Health Perspectives

4. Agreement varies with surface type July MODIS MISR 9 surface types, defined by monthly mean surface albedo ratios, evaluation against AERONET AOD

5. Combining MODIS and MISR improves agreement 0.3 0.25 0.2 0.15 0.1 0.05 0 τ[unitless] Combined MODIS/MISR r = 0.63 (vs. in-situ PM2.5) MODIS r = 0.40 (vs. in-situ PM2.5) MISR r = 0.54 (vs. in-situ PM2.5)

6. Global CTMs can directly relate PM2.5 to τ GEOS-Chem • Detailed aerosol-oxidant model • 2º x 2.5º • 54 tracers, 100’s reactions • Assimilated meteorology • Year-specific emissions • Dust, sea salt, sulfate-ammonium-nitrate system, organic carbon, black carbon, SOA η [ug/m]

7. Significant agreement with coincident ground measurements over NA Annual Mean PM2.5 [μg/m3] (2001-2006) Satellite Derived Satellite-Derived [μg/m3] In-situ In-situ PM2.5 [μg/m3]

8. Method is globally applicable • Annual mean measurements • Outside Canada/US • 244 sites (84 non-EU) • r = 0.83 (0.91) • slope = 0.86 (0.84) • bias = 1.15 (-2.52) μg/m3

9. Coincident PM2.5 error has two sources Estimated PM2.5 = η· τ Model • Affected by aerosol optical properties, concentrations, vertical profile, relative humidity • Most sensitive to vertical profile [van Donkelaar et al., 2006] Satellite • Error limited to 0.1 + 20% by AERONET filter • Implication for satellite PM2.5 determined by η

10. Model (GC) CALIPSO (CAL) Altitude [km] CALIPSO allows profile evaluation • Coincidently sample model and CALIPSO extinction profiles • Jun-Dec 2006 • Compare % within boundary layer Optical Depth from TOA Optical Depth at surface τ(z)/τsurface

11. Profile, τ and sampling define error Satellite-Derived PM2.5 [μg/m3] • Vary satellite-derived PM2.5 by profile and τ biases • One-sigma uncertainty of ±25% • Agrees with NA ground measurements • Global population-weight mean uncertainty of 6.7 μg/m3 In-situ PM2.5 [μg/m3] PM2.5 Bias Estimate [%]

12. -3 -2 -1 0 2 4 6 8 10 Mean Annual Change [μg/m3 / year] 0 2 4 6 8 10 12 14 16 18 Satellite-Derived PM2.5 [μg/m3]

13. -3 -2 -1 0 2 4 6 8 10 Mean Annual Change [μg/m3 / year] 0 5 10 15 20 25 35 Satellite-Derived PM2.5 [μg/m3]

14. -3 -2 -1 0 2 4 6 8 10 Mean Annual Change [μg/m3 / year] 0 5 10 15 45 70 100 Satellite-Derived PM2.5 [μg/m3]

15. Significant global deviations from model 0.1º x 0.1º r = 0.83 (0.84) slope = 0.86 (0.91) bias = 1.15 (-2.52) μg/m3 2º x 2.5º r = 0.75 (0.76) slope = 0.59 (0.65) bias = 4.36 (0.85) μg/m3 2º x 2.5º r = 0.63 (0.71) slope = 0.51 (0.56) bias = 8.51 (2.75) μg/m3

16. High global PM2.5 exposure WHO Guideline AQG IT-3 IT-2 IT-1 100 90 80 70 60 50 40 30 20 10 0 • Satellite-PM2.5 + population map → exposure • 80% of world population exceeds WHO guideline of 10 μg/m3 • 49% of eastern Asia exceeds 35 μg/m3 Population [%] 5 10 15 25 35 50 100 PM2.5 Exposure [μg/m3]