Quantitative Interpretation of Satellite and Surface Measurements of Aerosols over North America Aaron van Donkelaar M.Sc. Defense December, 2005.

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Presentation transcript:

Quantitative Interpretation of Satellite and Surface Measurements of Aerosols over North America Aaron van Donkelaar M.Sc. Defense December, 2005

Aerosols – Why do we care? Climate Change –Direct Effect –Indirect Effect Health Effects (PM 2.5 ) –Lung cancers –Pulmonary Inflammation Visibility Image from

Part I – Remote Sensing of Ground-Level PM 2.5 Column Mass Loading: Ground-Level PM 2.5 : ρ – particle mass density r – effective radius τ – aerosol optical depth Q e – Mie extinction efficiency z – Height of regional air mass subscript d denotes dry conditions

Instrumentation MODIS Moderate Resolution Imaging Spectroradiometer 32 channels (7 used for Aerosol Retrieval): 0.47, 0.55, 0.67, 0.87, 1.24, 1.64 um Approx. daily global coverage Requires dark surface for AOD retrieval MISR Multiangle Imaging Spectroradiometer 4 spectral bands at 9 different viewing angles 6-9 days for global coverage No assumption regarding surface reflectivity

GEOS-CHEM 50 Tracers 1º x 1º resolution 30 vertical levels (lowest at ~10, 50, 100, 200, 300 m) GMAO fields: temperature, winds, cloud properties, heat flux and precipitation sulphate, nitrate, mineral dust, fine/coarse seasalt, organic and black carbon Aerosol and oxidant simulations coupled through –formation of sulphate and nitrate –heterogeneous chemistry –aerosol effect of photolysis rates Seasonal average biomass burning

Remote vs. Ground PM 2.5

MODISMISR standard constant vertical structure (τ z /τ) 0.29 constant AOD constant aerosol properties (Q e, r, r d, ρ d ) Scatter Plot Comparison/Table Holding Constants

Temporal Correlation

Global PM 2.5

Part II –Organic Aerosol Sources Primary Sources: –combustion (biomass/biofuel) Secondary Sources: –condensation of gaseous species –not well understood GEOS-CHEM OA Simulation –Seasonally varying biomass burning inventories –Inversion removed –SOA based upon Chung and Seinfeld [2002] Biogenic emissions from MEGAN inventory H x C y + (O 3, OH, NO 3 ) → semi-volatile products

IMPROVE Organic Aerosol

IMPROVE – GEOS-CHEM Organic Aerosol

Isoprene conversion fits within model biases

Large effect from non-OA condensation

Conclusions Remote PM 2.5 –significant correlation (MODIS: R=0.68, MISR:0.54) –dominant factors include AOD and vertical structure –reveals global regions of high PM 2.5 Sources of Organic Aerosol –isoprene conversion reduces model bias –non-OA condensation unclear