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Estimating national-scale ground-level PM25 concentration in China using geographically weighted regression based on MODIS and MISR AOD

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Abstract

Taking advantage of the continuous spatial coverage, satellite-derived aerosol optical depth (AOD) products have been widely used to assess the spatial and temporal characteristics of fine particulate matter (PM2.5) on the ground and their effects on human health. However, the national-scale ground-level PM2.5 estimation is still very limited because the lack of ground PM2.5 measurements to calibrate the model in China. In this study, a national-scale geographically weighted regression (GWR) model was developed to estimate ground-level PM2.5 concentration based on satellite AODs, newly released national-wide hourly PM2.5 concentrations, and meteorological parameters. The results showed good agreements between satellite-retrieved and ground-observed PM2.5 concentration at 943 stations in China. The overall cross-validation (CV) R 2 is 0.76 and root mean squared prediction error (RMSE) is 22.26 μg/m3 for MODIS-derived AOD. The MISR-derived AOD also exhibits comparable performance with a CV R 2 and RMSE are 0.81 and 27.46 μg/m3, respectively. Annual PM2.5 concentrations retrieved either by MODIS or MISR AOD indicated that most of the residential community areas exceeded the new annual Chinese PM2.5 National Standard level 2. These results suggest that this approach is useful for estimating large-scale ground-level PM2.5 distributions especially for the regions without PMs monitoring sites.

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Acknowledgments

This research was supported by the National Natural Science Foundation of China under Grant Nos. 41275128, 41375063, and 41206163. MODIS data were obtained from the Atmosphere Archive and Distribution System at NASA/Goddard Space Flight Center.

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Authors and Affiliations

  1. Institute of Meteorology and Oceanography, PLA University of Science and Technology, No.60, Shuanglong Street, Nanjing, 211101, China

    Wei You, Zengliang Zang, Lifeng Zhang, Yi Li & Weiqi Wang

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  1. Wei You
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  2. Zengliang Zang
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  4. Yi Li
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  5. Weiqi Wang
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Correspondence to Zengliang Zang.

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You, W., Zang, Z., Zhang, L. et al. Estimating national-scale ground-level PM25 concentration in China using geographically weighted regression based on MODIS and MISR AOD. Environ Sci Pollut Res 23, 8327–8338 (2016). https://doi.org/10.1007/s11356-015-6027-9

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