Articles | Volume 12, issue 7
Atmos. Meas. Tech., 12, 3789–3803, 2019
Atmos. Meas. Tech., 12, 3789–3803, 2019

Research article 11 Jul 2019

Research article | 11 Jul 2019

Aerosol-type classification based on AERONET version 3 inversion products

Sung-Kyun Shin et al.

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Cited articles

Aerosol Robotic Network (AERONET): available at:, 9 July 2019. a, b
Bellouin, N., Quaas, J., Morcrette, J.-J., and Boucher, O.: Estimates of aerosol radiative forcing from the MACC re-analysis, Atmos. Chem. Phys., 13, 2045–2062,, 2013. a
Bergstrom, R. W., Russell, P. B., and Hignett, P.: Wavelength dependence of the absorption of black carbon particles: Predictions and results from the TARFOX experiment and implications for the aerosol single scattering albedo, J. Atmos. Sci., 59, 568–578, 2002. a
Bohren, C. and Huffman, D.: Absorbing and scattering of light by small particles, Wiley,, 1983. a, b
Bond, T. C. and Bergstrom, R. W.: Light absorption by carbonaceous particles: An investigative review, Aerosol Sci. Tech., 40, 27–67,, 2006. a
Short summary
This study proposes an aerosol-type classification based on parameters from the AErosol RObotic NETwork (AERONET) version 3 level 2.0 inversion product that describe light depolarization and absorption properties of atmospheric particles. We compare our classification with an earlier method and find that the new approach allows for a refined classification of mineral dust that occurs as a mixture with other absorbing aerosols.