Exploring the Spatial Variation Characteristics and Influencing Factors of PM2.5 Pollution in China: Evidence from 289 Chinese Cities

Abstract

Haze pollution has become an urgent environmental problem due to its impact on the environment as well as human health. PM2.5 is one of the core pollutants which cause haze pollution in China. Existing studies have rarely taken a comprehensive view of natural environmental conditions and socio-economic factors to figure out the cause and diffusion mechanism of PM2.5 pollution. This paper selected both natural environmental conditions (precipitation (PRE), wind speed (WIN), and terrain relief (TR)) and socio-economic factors (human activity intensity of land surface (HAILS), the secondary industry's proportion (SEC), and the total particulate matter emissions of motor vehicles (VE)) to analyze the effects on the spatial variation of PM2.5 concentrations. Based on the spatial panel data of 289 cities in China in 2015, we used spatial statistical methods to visually describe the spatial distribution characteristics of PM2.5 pollution; secondly, the spatial agglomeration state of PM2.5 pollution was characterized by Moran’s I; finally, several regression models were used to quantitatively analyze the correlation between PM2.5 pollution and the selected explanatory variables. Results from this paper confirm that in 2015, most cities in China suffered from severe PM2.5 pollution, and only 17.6% of the sample cities were up to standard. The spatial agglomeration characteristics of PM2.5 pollution in China were particularly significant in the Beijing–Tianjin–Hebei region. Results from the global regression models suggest that WIN exerts the most significant effects on decreasing PM2.5 concentration (p < 0.01), while VE is the most critical driver of increasing PM2.5 concentration (p < 0.01). Results from the local regression model show reliable evidence that the relation between PM2.5 concentrations and the explanatory variables varied differently over space. VE is the most critical factor that influences PM2.5 concentrations, which means controlling motor vehicle pollutant emissions is an effective measure to reduce PM2.5 pollution in Chinese cities.

A Clustering Framework to Reveal the Structural Effect Mechanisms of Natural and Social Factors on PM2.5 Concentrations in China

“…However, the relationships between population and gas emissions are not constant over space and time. For example, vehicle emissions were regarded as one of the major sources of PM 2.5 pollution in China [41]. Owing to the spatiotemporal difference of consumption levels and habits, the same population increase may cause an increase in different vehicle usage, which leads to the different change of PM 2.5 concentrations in different geographical areas and time periods.…”

Decrease in the chronic health effects from PM2.5 during the 13th Five-Year Plan in China: Impacts of air pollution control policies

“…The reduction from 2015 to 2018 is obvious due to China's APPC-AP, which is consistent with a previous study ( Zhai et al, 2019 ). In particular, cities in the key regions showed greater reduction ( Yu et al, 2020 ; Zhao and Xu, 2019 ) because the government adopted more stringent measures and greater capital investment both in APPC-AP from 2013 to 2017 and TAPFAP from 2018 to 2020.…”

Research on the Effect of an Environmental Protection Tax Policy on Haze Control in China—Empirical Analysis Based on Provincial Panel Data

“…In addition, seven of the ten most serious cities in the world in terms of air pollution are in China. In recent years, China has been plagued by severe PM2.5 pollution [1]. When examining the history of economic development and environmental protection in developed countries, one can see that those countries have gone through hundreds of years of industrialization.…”