An analysis of AERONET aerosol absorption properties and classifications representative of aerosol source regions

Partitioning of mineral dust, pollution, smoke, and mixtures using remote sensing techniques can help improve accuracy of satellite retrievals and assessments of the aerosol radiative impact on climate. Spectral aerosol optical depth (T) and single scattering albedo (omega(o)) from Aerosol Robotic Network (AERONET) measurements are used to form absorption (i.e., omega(o) and absorption angstrom ngstrom exponent (alpha(abs))) and size (i.e., extinction angstrom ngstrom exponent (alpha(ext)) and fine mode fraction of T) relationships to infer dominant aerosol types. Using the long-term AERONET data set (1999-2010), 19 sites are grouped by aerosol type based on known source regions to (1) determine the average omega(o) and alpha(abs) at each site (expanding upon previous work), (2) perform a sensitivity study on alpha(abs) by varying the spectral omega(o), and (3) test the ability of each absorption and size relationship to distinguish aerosol types. The spectral omega(o) averages indicate slightly more aerosol absorption (i.e., a 0.0 < delta omega(o) <= 0.02 decrease) than in previous work, and optical mixtures of pollution and smoke with dust show stronger absorption than dust alone. Frequency distributions of alpha(abs) show significant overlap among aerosol type categories, and at least 10% of the alpha(abs) retrievals in each category are below 1.0. Perturbing the spectral omega(o) by +/- 0.03 induces significant alpha(abs) changes from the unperturbed value by at least similar to +/- 0.6 for Dust, similar to +/- 0.2 for Mixed, and similar to +/- 0.1 for Urban/Industrial and Biomass Burning. The omega(o440nm) and alpha(ext440-870nm) relationship shows the best separation among aerosol type clusters, providing a simple technique for determining aerosol type from surface-and future space-based instrumentation.