Long Time-Series Spatial Characterization of PM2.5 Concentration Based on GTWR and GTWRK Models: A Case Study of the Beijing–Tianjin–Hebei Region

As China's urbanization continues to accelerate, the ensuing environmental problems are becoming more and more significant, with an increase in the occurrence of hazy weather. The Beijing–Tianjin–Hebei urban agglomeration is one of the fastest-growing areas of urbanization in China, and air pollution has obvious regional characteristics, making it a typical area of serious urban air pollution in China. In this paper, the Beijing–Tianjin–Hebei region is selected as the study area, and based on the GTWR and GTWRK models, the PM2.5 concentrations in the region are estimated from June 2014 to December 2020. The four models, namely, GWR, GTWR, OK, and GTWRK, are compared and analyzed to validate the accuracies of the GTWR and GTWRK models and the 2014–2020 temporal and spatial characteristics of PM2.5 concentration in the Beijing–Tianjin–Hebei region from 2014 to 2020. The results of the study can provide data support for the development of prevention and control strategies for atmospheric PM2.5 pollution in the Beijing–Tianjin–Hebei region, as well as the assessment of population exposure to pollution and the analysis of health effects. The findings indicate that the variables that affect the fluctuations in the Beijing–Tianjin–Hebei region's level of PM2.5 with high significance are PRE, WS, AOD, NDVI, and POP, and the GTWR model is the most suitable for PM2.5 concentration prediction in the Beijing–Tianjin–Hebei region among the GWR, GWRK, OK, and GTWRK models. PM2.5 pollution in the Beijing–Tianjin–Hebei region is more severe in winter throughout the year and relatively less severe in summer; PM2.5 concentrations in the northern area are much lower than those in the middle and southern regions; PM2.5 pollution deepened in 2015–2016 compared with 2014, while PM2.5 pollution basically showed a yearly decreasing trend after 2016.