Paper
8 March 2018 Satellite remote sensing of air quality in winter of Lanzhou
Dawei Wang, Tao Han, Youyan Jiang, Lili Li, Shuyuan Ren
Author Affiliations +
Proceedings Volume 10611, MIPPR 2017: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications; 106110M (2018) https://doi.org/10.1117/12.2288184
Event: Tenth International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2017), 2017, Xiangyang, China
Abstract
Fine particulate matter (aerodynamic diameters of less than 2.5 μm, PM2.5) air pollution has become one of the global environmental problem, endangering the existence of residents living, climate, and public health. Estimation Particulate Matter (aerodynamic diameters of less than 10 μm, PM10) concentration and aerosol absorption was the key point in air quality and climate studies. In this study, we retrieve the Aerosol Optical Depth (AOD) from the Earth Observing System (EOS) and the Moderate Resolution Imaging Spectroradiometer (MODIS), and PM2.5, PM10 in winter on 2014 and 2015, using Extended Dense Dark Vegetation Algorithm and 6S radiation model to analysis the correlation. The result showed that at the condition of non-considering the influence of primary pollutants, the correlation of two Polynomials between aerosol optical depth and PM2.5 and PM10 was poor; taking the influence of the primary pollutants into consideration, the aerosol optical depth has a good correlation with PM2.5 and PM10. The version of PM10 by aerosol optical depth is higher than that of PM2.5, so the model can be used to realize the high precision inversion of winter PM10 in Lanzhou.
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Dawei Wang, Tao Han, Youyan Jiang, Lili Li, and Shuyuan Ren "Satellite remote sensing of air quality in winter of Lanzhou ", Proc. SPIE 10611, MIPPR 2017: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications, 106110M (8 March 2018); https://doi.org/10.1117/12.2288184
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KEYWORDS
Phase modulation

Atmospheric modeling

Aerosols

Remote sensing

Reflectivity

Satellites

Data modeling

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