Volume XLII-3
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 147-153, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-147-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 147-153, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-147-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  30 Apr 2018

30 Apr 2018

RETRIEVAL OF ATMOSPHERIC PARTICULATE MATTER USING SATELLITE DATA OVER CENTRAL AND EASTERN CHINA

G. L. Chen1,3, J. Guang1, Y. Li1,2, Y. H. Che1,2, and S. Q. Gong3 G. L. Chen et al.
  • 1Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China
  • 2University of Chinese Academy of Sciences, Beijing 100049, China
  • 3School of Geography and Remote Sensing, Nanjing University of Information Science & Technology, Nanjing 210044, China

Keywords: Retrieval, Atmospheric Particulate Matter, Satellite, Central and Eastern China

Abstract. Fine particulate matter (PM2.5) is a particle cluster with diameters less than or equal to 2.5 μm. Over the past few decades, regional air pollution composed of PM2.5 has frequently occurred over Central and Eastern China. In order to estimate the concentration, distribution and other properties of PM2.5, the general retrieval models built by establishing the relationship between aerosol optical depth (AOD) and PM2.5 has been widely used in many studies, including experimental models via statistics analysis and physical models with certain physical mechanism. The statistical experimental models can’t be extended to other areas or historical period due to its dependence on the ground-based observations and necessary auxiliary data, which limits its further application. In this paper, a physically based model is applied to estimate the concentration of PM2.5 over Central and Eastern China from 2007 to 2016. The ground-based PM2.5 measurements were used to be as reference data to validate our retrieval results. Then annual variation and distribution of PM2.5 concentration in the Central and Eastern China was analysed. Results shows that the annual average PM2.5 show a trend of gradually increasing and then decreasing during 2007–2016, with the highest value in 2011.