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Estimation of Ground-Level PM2.5 Concentrations in the Major Urban Areas of Chongqing by Using FY-3C/MERSI

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Air pollution is becoming increasingly serious with rapid economic development in China, and the primary pollutant has converted from PM10 to PM2.5, which is associated with more adverse impacts on… Click to show full abstract

Air pollution is becoming increasingly serious with rapid economic development in China, and the primary pollutant has converted from PM10 to PM2.5, which is associated with more adverse impacts on human health. Satellite remote sensing, with help of its quantitative observations over large spatial and temporal extent, has become a significant supplement to the in situ measurements. This study exploits the aerosol optical depth (AOD) product retrieved from the Medium Resolution Spectrum Imager (MERSI) onboard Fengyun-3C satellite to estimate PM2.5 estimation over the major urban areas of Chongqing, a metropolitan city in the Southwestern China. A semi-empirical model and the linear mixed effect (LME) model are combined based on in situ observations from local air quality and meteorological networks from May 2014 to May 2015. This combined model is able to explain about 90% of the variation of the estimated PM2.5, and performs better than LME model by achieving higher correlation and smaller deviations between the satellites estimated PM2.5 and in situ measurements. Benefiting from the high resolution of 1 km × 1 km, MERSI AOD achieves much more detailed spatial distribution of ground-level PM2.5 over the major urban areas of Chongqing, compared to most of concurrent satellite products, such as the MODIS L2 AOD. According to the estimation, PM2.5 concentration is higher in cold seasons than in warm seasons in Chongqing. Peak levels of PM2.5 is found in Yuzhong District, the center of Chongqing urban area, while the concentration gradually decreases in surrounding areas, indicating that air pollution in Chongqing is highly contributed by local anthropogenic emissions.

Keywords: pm2; urban areas; estimation; ground level; major urban; areas chongqing

Journal Title: Atmosphere
Year Published: 2017

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