Fine particulate matter (PM2.5), one of the major atmospheric pollutants, has a significant impact on human health. However, the determinant power of natural and socioeconomic factors on the spatial-temporal variation of PM2.5 pollution is controversial in China.
In this study, we explored spatial-temporal characteristics and driving factors of PM2.5 through 252 prefecture-level cities in China from 2015 to 2019, based on the spatial autocorrelation and geographically and temporally weighted regression model (GTWR).
PM2.5 concentrations showed a significant downward trend, with a decline rate of 3.58 μg m−3 a−1, and a 26.49% decrease in 2019 compared to 2015, Eastern and Central China were the two regions with the highest PM2.5 concentrations. The driving force of socioeconomic factors on PM2.5 concentrations was slightly higher than that of natural factors. Population density had a positive significant driving effect on PM2.5 concentrations, and precipitation was the negative main driving factor. The two main driving factors (population density and precipitation) showed that the driving capability in northern region was stronger than that in southern China. North China and Central China were the regions of largest decline, and the reason for the PM2.5 decline might be the transition from a high environmental pollution-based industrial economy to a resource-clean high-tech economy since the implementation the Air Pollution Prevention and Control Action Plan in 2013.
We need to fully consider the coordinated development of population size and local environmental carrying capacity in terms of control of PM2.5 concentrations in the future. This research is helpful for policy-makers to understand the distribution characteristics of PM2.5 emission and put forward effective policy to alleviate haze pollution.