Aerosol-type classification based on AERONET version 3 inversion products

• Published in: Atmospheric Measurement Techniques
• Main Authors: Shin, Sung-Kyun, Tesche, Matthias, Mueller, Detlef, Now, Youngmin
• Other Authors: School of Physics, Astronomy and Mathematics, Centre for Atmospheric and Climate Physics Research, SPECS Deans Group
• Language: English
• Published: 2019
• Subjects: Atmospheric Science; Aerosol Robotic Network
• Online Access: http://hdl.handle.net/2299/21430; http://www.scopus.com/inward/record.url?scp=85068817321&partnerID=8YFLogxK

© Author(s) 2019. This work is distributed under the Creative Commons Attribution 4.0 License. This study proposes an aerosol-type classification based on the particle linear depolarization ratio (PLDR) and single-scattering albedo (SSA) provided in the AErosol RObotic NETwork (AERONET) version 3 level 2.0 inversion product. We compare our aerosol-type classification with an earlier method that uses fine-mode fraction (FMF) and SSA. Our new method allows for a refined classification of mineral dust that occurs as a mixture with other absorbing aerosols: pure dust (PD), dust-dominated mixed plume (DDM), and pollutant-dominated mixed plume (PDM). We test the aerosol classification at AERONET sites in East Asia that are frequently affected by mixtures of Asian dust and biomass-burning smoke or anthropogenic pollution. We find that East Asia is strongly affected by pollution particles with high occurrence frequencies of 50 % to 67 %. The distribution and types of pollution particles vary with location and season. The frequency of PD and dusty aerosol mixture (DDM+PDM) is slightly lower (34 % to 49 %) than pollution-dominated mixtures. Pure dust particles have been detected in only 1 % of observations. This suggests that East Asian dust plumes generally exist in a mixture with pollution aerosols rather than in pure form. In this study, we have also considered data from selected AERONET sites that are representative of anthropogenic pollution, biomass-burning smoke, and mineral dust. We find that average aerosol properties obtained for aerosol types in our PLDR–SSA-based classification agree reasonably well with those obtained at AERONET sites representative for different aerosol types. Peer reviewed