To analyze the spatial and temporal variation characteristics of PM2.5 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 PM2.5 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 PM2.5 concentrations were verified and analyzed. Finally, the spatial and temporal variation characteristics of PM2.5 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 PM2.5 concentration products of the average daily, monthly, and annual averages are in general good. The larger the time scale is, the better is the PM2.5 effect of the remote sensing estimation. The relative accuracy of the annual average PM2.5 products is higher than 80%. However, the precision of the PM2.5 remote sensing results for 2016 and 2017 is relatively close (at the same time scales). The PM2.5 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 PM2.5 concentration decreased by~9.2% in 2017. The area with high values was significantly reduced. High PM2.5 concentrations occurred in November and December and low concentrations were observed in August. The PM2.5 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.
Keywords: Beijing-Tianjin-Hebei and its surrounding regions; PM2.5; multiscale verification; remote sensing; spatiotemporal change.