Ecological Indicators (Oct 2021)
Spatio-temporal variation and driving factors analysis of PM2.5 health risks in Chinese cities
Abstract
The high concentration of fine particulate matter (PM2.5) has always been a key indicator affecting Chinese environmental quality and a core factor restricting sustainable development. This article refers to the implementation of Air Pollution Prevention and Control Action Plan, analyzes the spatiotemporal variation characteristics of PM2.5 health risks in 247 cities in China from 2015 to 2017, and divides the cities into four types by the interannual variation differences in health risks: cities with PM2.5 health risks continuously decreased (hereinafter referred to as I type cities), cities with PM2.5 health risks continuously increased (Ⅱ type cities), cities with unknown changes of PM2.5 health risks (IIItype cities), and cities with irregular changes of PM2.5 health risks (Ⅳ type cities). The STIRPAT model and cross-sectional regression method are used to explore the influence and difference in socioeconomic drivers on PM2.5 health risks in types of cities. The results show that (1) Chinese PM2.5 health risks decreased by 3% from 2015 to 2017. According to the change characteristics of health risks, the cities are divided into four types of cities. And the distribution of the four types of cities is regional. (2) From the perspective of drivers, all the cities with PM2.5 health risks are vulnerable to the impact of human activities in built-up areas. I type cities have high per capita GDP and low energy consumption per unit GDP, indicating that the economic development of these cities has low dependence on energy. Ⅱ type cities are easily affected by urbanization rate. The highway mileage has the greatest impact on III type cities. In Ⅳ type cities, the proportion of secondary industry is the smallest, but it is easily affected by the proportion of secondary industry. This study provides theoretical support for the fine control of PM2.5 pollution in each city.
