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Estimation of ground-level PM2.5 concentration using MODIS AOD and corrected regression model over Beijing, China

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  • Xinghan Xu
  • Chengkun Zhang

Abstract

To establish a new model for estimating ground-level PM2.5 concentration over Beijing, China, the relationship between aerosol optical depth (AOD) and ground-level PM2.5 concentration was derived and analysed firstly. Boundary layer height (BLH) and relative humidity (RH) were shown to be two major factors influencing the relationship between AOD and ground-level PM2.5 concentration. Thus, they are used to correct MODIS AOD to enhance the correlation between MODIS AOD and PM2.5. When using corrected MODIS AOD for modelling, the correlation between MODIS AOD and PM2.5 was improved significantly. Then, normalized difference vegetation index (NDVI), surface temperature (ST) and surface wind speed (SPD) were introduced as auxiliary variables to further improve the performance of the corrected regression model. The seasonal and annual average distribution of PM2.5 concentration over Beijing from 2014 to 2016 were mapped for intuitively analysing. Those can be regarded as important references for monitoring the ground-level PM2.5 concentration distribution. It is obviously that the PM2.5 concentration distribution over Beijing revealed the trend of “southeast high and northwest low”, and showed a significant decrease in annual average PM2.5 concentration from 2014 to 2016.

Suggested Citation

  • Xinghan Xu & Chengkun Zhang, 2020. "Estimation of ground-level PM2.5 concentration using MODIS AOD and corrected regression model over Beijing, China," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-15, October.
    • Handle: RePEc:plo:pone00:0240430
    DOI: 10.1371/journal.pone.0240430
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