Papers
9
Total Citations
274
H-Index
7
About
Sung‐Kyun Shin is a leading atmospheric scientist whose research centers on aerosol classification, optical properties, and the remote sensing of atmospheric particles using ground-based networks. His major contributions include developing a novel aerosol-type classification scheme based on the particle linear depolarization ratio (PLDR) and single-scattering albedo (SSA) from AERONET version 3 inversion products—a framework that has become a reference for distinguishing dust, pollution, and mixed aerosols (94 citations). He has also advanced the understanding of mineral dust’s spectral depolarization and lidar ratio, providing critical reference values for lidar measurements (88 citations). Shin’s work on separating absorption aerosol optical depth (AAOD) components in mixed dust plumes (43 citations) and retrieving black carbon absorption from AERONET data has deepened knowledge of light-absorbing aerosols globally. His studies on East Asian dust plumes, combining lidar and sun–sky radiometer observations, have been instrumental in confirming aerosol types during high-PM10 episodes. With over 270 total citations, Shin’s research is essential for improving aerosol typing, air quality monitoring, and climate modeling.
Research Focus
Key Achievements
Top Papers
- 1Aerosol-type classification based on AERONET version 3 inversion products94 citations · 2019
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