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A Short Note on the Potential of Utilization of Spectral AERONET-Derived Depolarization Ratios for Aerosol Classification

Research Institute for Radiation-Satellite, Gangneung-Wonju National University, Gangneung 25457, Korea
School of Physics, Astronomy and Mathematics, University of Hertfordshire, Hatfield AL10 9AB, UK
Author to whom correspondence should be addressed.
Atmosphere 2019, 10(3), 143;
Received: 8 February 2019 / Revised: 9 March 2019 / Accepted: 12 March 2019 / Published: 16 March 2019
(This article belongs to the Special Issue Remote Sensing of Aerosols)
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We herein present the spectral linear particle depolarization ratios (δp) from an Aerosol Robotics NETwork (AERONET) sun/sky radiometer with respect to the aerosol type. AERONET observation sites, which are representative of each aerosol type, were selected for our study. The observation data were filtered using the Ångström exponent (Å), fine-mode fraction (FMF) and single scattering albedo (ω) to ensure that the obtained values of δp were representative of each aerosol condition. We report the spectral δp values provided in the recently released AERONET version 3 inversion product for observation of the following aerosol types: dust, polluted dust, smoke, non-absorbing, moderately-absorbing and high-absorbing pollution. The AERONET-derived δp values were generally within the range of the δp values measured from lidar observations for each aerosol type. In addition, it was found that the spectral variation of δp differed according to the aerosol type. From the obtained results, we concluded that our findings provide potential insight into the identification and classification of aerosol types using remote sensing techniques. View Full-Text
Keywords: AERONET; spectral depolarization ratio; wavelength dependency; aerosol classification AERONET; spectral depolarization ratio; wavelength dependency; aerosol classification

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Zo, I.-S.; Shin, S.-K. A Short Note on the Potential of Utilization of Spectral AERONET-Derived Depolarization Ratios for Aerosol Classification. Atmosphere 2019, 10, 143.

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