[Analysis of Spatiotemporal Changes and Multi-scale Socio-economic Driving Factors of PM_2.5 and Ozone in Beijing-Tianjin-Hebei and Its Surroundings].

Based on PM_2.5 and O₃ remote sensing concentration data in Beijing-Tianjin-Hebei and its surrounding areas from 2015 to 2020, we used trend analysis, geographic detectors, and a geographically and temporally weighted regression model to explore the spatiotemporal characteristics and key driving socio-economic factors of multi-scale PM_2.5 and O₃ concentrations. The results indicated that： ① The changing slope of PM_2.5 concentration ranged from -12.93 to 0.43 μg·（m³·a）^-1, and the changing slope of O₃ concentration ranged from 0.70 to 14.90 μg·（m³·a）^-1. The decreasing slope of PM_2.5 concentration was the largest in winter, and the increasing slope of O₃ concentration was the largest in summer. ② The concentrations of PM_2.5 and O₃ were spatially correlated, and the H-H concentrations of PM_2.5 were located in the southern Hebei Province and the northern Henan Province. The spatial clustering pattern of O₃ changed greatly. ③ From the perspective of urban agglomeration, the GDP, population density, and civilian car ownership had a strong explanatory power for PM_2.5, while GDP, urbanization rate, and civilian car ownership had a strong explanatory power for O₃. The dominant interaction factors of 2016 and 2020 were the population density∩the proportion of the secondary industry and urbanization rate∩road network density, respectively. ④ From the perspective of single city, population density, industrial nitrogen oxide emissions, and electricity consumption had mainly positive effects on PM_2.5 and O₃ pollution and became the socio-economic driving factors that need to be focused on to control PM_2.5 and O₃ co-pollution.