An improved algorithm for retrieving the fine-mode fraction of aerosol optical thickness, part 1: Algorithm development

REMOTE SENSING OF ENVIRONMENT

卷:192

Article

Yan, Xing^1,2,3  Li, Zhanqing^2,3,4,5  Shi, Wenzhong¹  Luo, Nana⁶  Wu, Taixia⁷  Zhao, Wenji⁸ 

[1] Hong Kong Polytech Univ, Dept Land Surveying & Geoinformat, Hong Kong, Hong Kong, Peoples R China

[2] Univ Maryland, Dept Atmospher & Ocean Sci, College Pk, MD 20742 USA

[3] Univ Maryland, Earth Syst Sci Interdisciplinary Ctr, College Pk, MD 20742 USA

[4] Beijing Normal Univ, State Key Lab Earth Surface Proc & Resource Ecol, Beijing, Peoples R China

[5] Beijing Normal Univ, Coll Global Change & Earth Syst Sci, Beijing, Peoples R China

[6] San Diego State Univ, Dept Geog, San Diego, CA 92182 USA

[7] Hohai Univ, Sch Earth Sci & Engn, Nanjing, Jiangsu, Peoples R China

[8] Capital Normal Univ, Coll Resource Environm & Tourism, Beijing, Peoples R China

关键词: Aerosol fine-mode fraction;    MODIS;    AOT;    PM2.5;   

DOI  :  10.1016/j.rse.2017.02.005

来源: Elsevier

【 摘 要 】

The fine-mode fraction (FMF) can be a useful tool to separate natural aerosols from man-made aerosols and to assist in estimating surface concentrations of particulate matter with a diameter < 2.5 mu m. A LookUp Table-based Spectral Deconvolution Algorithm (LUT-SDA) was developed here for satellite-based applications using data such as MODerate resolution Imaging Spectroradiometer (MODIS) measurements. This method was validated against ground-based FMF retrievals from the Aerosol Robotic Network (AERONET). The LUT-SDA was then applied to two MODIS-retrieved aerosol optical thickness (AOT) products for the period of December 2013 to July 2015: the MODIS Collection 6 (C6) Dark Target (DT) AOT product and the simplified high-resolution MODIS Aerosol Retrieval Algorithm (SARA) AOT product. In comparison with the MODIS C6 FMF product in three study areas (Beijing, Hong Kong, and Osaka), FMFs estimated by the LUT-SDA agreed more closely with those retrieved from the AERONET with a very low bias. Eighty percent of the FMF values fell within the expected error range of +/- 0.4. The root mean square error (RMSE) was 0.168 with few anomalous values, whereas the RMSE for the MODIS FMF was 0.340 with more anomalous values. The LUT-SDA FMF estimated using SARA AOT data conveys more detailed information on urban pollution than that from MODIS C6 DT AOT data. As a demonstration, the seasonally-averaged spatial distribution of the FMF in Beijing was obtained from the LUT-SDA applied to SARA AOT data and compared with that of the AERONET-retrieved FMF. Their seasonal trends agreed well. (C) 2017 Elsevier Inc. All rights reserved.

【 授权许可】

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