[Socio-economic Factors Influencing the Spatial Distribution of PM_2.5 Concentrations in China: An Exploratory...

In recent years, the PM_2.5 pollution in China has become a top environmental and health concern, involving the characterization of healthy effects over a broad spatial area with uneven geographical distribution. This research aims to explore the influential factors for the PM_2.5 distribution from a socio-economic perspective, based on the observations from China's 1497 monitoring sites in 2015. First, the Moran's I index and the local indicators of spatial association (LISA) were computed to outline the distribution of PM_2.5 on a national scale using provincial-level divisions. Second, the correlation between the spatial distribution of PM_2.5 and socio-economic factors were analyzed by ordinary least squares (OLS) and geo-weighted regression (GWR) models. The results indicated that the GWR model explained the causal relationships better. Generally, Beijing, Tianjin, and Hebei had peak levels of PM_2.5, while Guangxi, Sichuan, and several other southern provinces had the lowest levels. Particularly, forest coverage rate and electricity consumption per capita were negatively correlated with the concentration of PM_2.5. In this study, the vehicle ownership per capita proved to be the most significant factor that positively contributed to the concentration.