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[Monitoring and Analysis of the Spatio-temporal Change Characteristics of the PM Concentration Over Beijing-Tianjin-Hebei and Its Surrounding Regions Based on Remote Sensing].

Huan Jing Ke Xue; 40(1): 33-43, 2019 Jan 08.
Artigo em Chinês | MEDLINE | ID: mdl-30628257
To analyze the spatial and temporal variation characteristics of PM in Beijing-Tianjin-Hebei and its surrounding regions, a 1 km resolution AOT product was retrieved from MODIS data and the remote sensing inversion of the PM concentration in Beijing-Tianjin-Hebei and its surrounding regions was realized using the geographically weighted regression model. On this basis, the synthesis results of multi-timescale PM concentrations were verified and analyzed. Finally, the spatial and temporal variation characteristics of PM in Beijing-Tianjin-Hebei and its surrounding regions between 2016 and 2017 were compared and analyzed using different time scales. The results show that the verification of the PM concentration products of the average daily, monthly, and annual averages are in general good. The larger the time scale is, the better is the PM effect of the remote sensing estimation. The relative accuracy of the annual average PM products is higher than 80%. However, the precision of the PM remote sensing results for 2016 and 2017 is relatively close (at the same time scales). The PM distribution in Beijing-Tianjin-Hebei and its surrounding regions shows a seasonal variation (winter > autum ≈ spring > summer). The spatial distribution is high in the southern but low in the northern part. Compared with 2016, the average PM concentration decreased by~9.2% in 2017. The area with high values was significantly reduced. High PM concentrations occurred in November and December and low concentrations were observed in August. The PM concentration change between 2017 and 2016 is closely related to the comprehensive control crucial action and specific inspection activities of air pollution in 2017, which indirectly account for the effect of the reduction of the atmospheric pollution.