Global Climatology of Fine Particulate Matter Concentrations Estimated from Remote-Sensed Aerosol Optical Depth Aaron van Donkelaar 1, Randall Martin 1,2,

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Global Climatology of Aerosol Optical Depth

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Global Climatology of Fine Particulate Matter Concentrations Estimated from Remote-Sensed Aerosol Optical Depth Aaron van Donkelaar 1, Randall Martin 1,2, Ralph Kahn 3 and Robert Levy 3 International Aerosol Modeling Algorithms December 9-11, Dalhousie University 2 Harvard-Smithsonian 3 NASA Goddard

We relate satellite-based measurements of aerosol optical depth to PM 2.5 using a global chemical transport model Approach Estimated PM 2.5 = η· τ Combined MODIS/MISR Aerosol Optical Depth GEOS-Chem Following Liu et al., 2004: vertical structure aerosol type meteorological effects meteorology diurnal effects η

MODIS and MISR τ MODIS τ 1-2 days for global coverage Requires assumptions about surface reflectivity MISR τ 6-9 days for global coverage Simultaneous surface reflectance and aerosol retrieval Mean τ at 0.1º x 0.1º τ [unitless] MISR MODIS r = 0.40 vs. in-situ PM 2.5 r = 0.54 vs. in-situ PM 2.5 Submitted to Environmental Health Perspectives

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

Combining MODIS and MISR improves agreement MODIS r = 0.40 (vs. in-situ PM 2.5 ) MISR r = 0.54 (vs. in-situ PM 2.5 ) Combined MODIS/MISR r = 0.63 (vs. in-situ PM 2.5 ) τ [unitless]

Global CTMs can directly relate PM 2.5 to τ 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 GEOS-Chem η [ug/m]

Significant agreement with coincident ground measurements over NA Satellite Derived In-situ Satellite-Derived [ μ g/m3] In-situ PM 2.5 [μg/m 3 ] Annual Mean PM 2.5 [ μ g/m 3 ] ( ) r MODIS τ 0.40 MISR τ 0.54 Combined τ 0.63 Combined PM

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/m 3 Method is globally applicable

Coincident PM 2.5 error has two sources Satellite Error limited to % by AERONET filter Implication for satellite PM 2.5 determined by η Estimated PM 2.5 = η· τ Model Affected by aerosol optical properties, concentrations, vertical profile, relative humidity Most sensitive to vertical profile [van Donkelaar et al., 2006]

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

Profile, τ and sampling define error Vary satellite-derived PM 2.5 by profile and τ biases –One-sigma uncertainty of ±25% Agrees with NA ground measurements –Global population-weight mean uncertainty of 6.7 μg/m 3 Satellite-Derived PM 2.5 [ μ g/m 3 ] In-situ PM 2.5 [μg/m 3 ] PM 2.5 Bias Estimate [%]

Satellite-Derived PM 2.5 [μg/m 3 ] Mean Annual Change [μg/m 3 / year]

Mean Annual Change [μg/m 3 / year] Satellite-Derived PM 2.5 [μg/m 3 ]

Mean Annual Change [μg/m 3 / year] Satellite-Derived PM 2.5 [μg/m 3 ]

Significant global deviations from model 2º x 2.5º r = 0.75 (0.76) slope = 0.59 (0.65) bias = 4.36 (0.85) μg/m 3 2º x 2.5º r = 0.63 (0.71) slope = 0.51 (0.56) bias = 8.51 (2.75) μg/m 3 0.1º x 0.1º r = 0.83 (0.84) slope = 0.86 (0.91) bias = 1.15 (-2.52) μg/m 3

Satellite-PM population map → exposure 80% of world population exceeds WHO guideline of 10 μg/m 3 49% of eastern Asia exceeds 35 μg/m 3 WHO Guideline PM 2.5 Exposure [μg/m 3 ] Population [%] High global PM 2.5 exposure AQG IT-3 IT-2 IT-1