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