Version 1
: Received: 9 January 2018 / Approved: 10 January 2018 / Online: 10 January 2018 (03:16:02 CET)
How to cite:
Gao, C.; Zhang, X.; Wang, W.; Xiu, A.; Tong, D. Q.; Chen, W. Spatiotemporal Distribution of Satellite-Retrieved Ground-Level PM2.5 and Near Real-Time Daily Retrieval Algorithm Development in Sichuan Basin, China. Preprints2018, 2018010083. https://doi.org/10.20944/preprints201801.0083.v1
Gao, C.; Zhang, X.; Wang, W.; Xiu, A.; Tong, D. Q.; Chen, W. Spatiotemporal Distribution of Satellite-Retrieved Ground-Level PM2.5 and Near Real-Time Daily Retrieval Algorithm Development in Sichuan Basin, China. Preprints 2018, 2018010083. https://doi.org/10.20944/preprints201801.0083.v1
Gao, C.; Zhang, X.; Wang, W.; Xiu, A.; Tong, D. Q.; Chen, W. Spatiotemporal Distribution of Satellite-Retrieved Ground-Level PM2.5 and Near Real-Time Daily Retrieval Algorithm Development in Sichuan Basin, China. Preprints2018, 2018010083. https://doi.org/10.20944/preprints201801.0083.v1
APA Style
Gao, C., Zhang, X., Wang, W., Xiu, A., Tong, D. Q., & Chen, W. (2018). Spatiotemporal Distribution of Satellite-Retrieved Ground-Level PM<sub>2.5</sub> and Near Real-Time Daily Retrieval Algorithm Development in Sichuan Basin, China. Preprints. https://doi.org/10.20944/preprints201801.0083.v1
Chicago/Turabian Style
Gao, C., Daniel Q. Tong and Weiwei Chen. 2018 "Spatiotemporal Distribution of Satellite-Retrieved Ground-Level PM<sub>2.5</sub> and Near Real-Time Daily Retrieval Algorithm Development in Sichuan Basin, China" Preprints. https://doi.org/10.20944/preprints201801.0083.v1
Abstract
Satellite-based monitoring can retrieve ground-level PM2.5 concentrations with higher-resolution and continuous spatial coverage to assist in making management strategies and estimating health exposures. The Sichuan Basin has a complex terrain and several city clusters that differ from other regions in China: it has an enclosed air basin with a unique planetary boundary layer dynamic which accumulates air pollution. The spatiotemporal distribution of 1-km resolution Aerosol Optical Depth (AOD) in the Sichuan Basin was retrieved using the improved dark pixel method and Moderate Resolution Imaging Spectroradiometer (MODIS) data in this study. The retrieved seasonal AOD reached its highest values in spring and had the lowest values in autumn. The higher correlation (r = 0.84, N = 171) between the ground-based Lidar AOD and 1-km resolution MODIS AOD indicated that the high-resolution MODIS AOD could be used to retrieve the ground-level PM2.5 concentration. The Lidar-measured annual average extinction coefficient increased linearly with the Planetary Boundary Layer Height (PBLH) in the range of 100 ~ 670 m, but exponentially decreased between the heights of 670 ~ 1800 m. Both the correlation and the variation tendency of simulated PBLH from WRF_SHIN/CALMET were closer to the Lidar observation than that of three other Planetary Boundary Layer (PBL) schemes (the Grenier-Bretherton-McCaa (GBM) scheme, the he Total Energy-Mass Flux (TEMF) scheme and the University of Washington (UW) scheme), which suggested that the simulated PBLH could be used in the vertical correction of retrieval PM2.5. Four seasonal fitting functions were also obtained for further humidity correction. The correlation coefficient between the aerosol extinction coefficient and the fitted surface-level PM2.5 concentration at the benchmark station of Southwest Jiao-tong University was enhanced significantly from 0.62 to 0.76 after vertical and humidity corrections during a whole year. During the evaluation of the retrieved ground-level PM2.5 with observed values from three cities, Yibin (YB), Dazhou (DZ), and Deyang (DY), our algorithm performed well, resulting in higher correlation coefficients of 0.78 (N = 177), 0.77 (N = 178), and 0.81 (N = 181), respectively.
Environmental and Earth Sciences, Environmental Science
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.