Spatiotemporal Distribution of Continuous Air Pollution and Its Relationship with Socioeconomic and Natural Factors in China

Abstract

Continuous air pollution (CAP) incidents last even longer and generate greater health hazards relative to conventional air pollution episodes. However, few studies have focused on the spatiotemporal distribution characteristics and driving factors of CAP in China. Drawing on the daily reported ground monitoring data on the ambient air quality in 2019 in China, this paper identifies the spatiotemporal distribution characteristics of CAP across 337 Chinese cities above the prefecture level using descriptive statistics and spatial statistical analysis methods, and further examines the spatial heterogeneity effects of both socioeconomic factors and natural factors on CAP with a Multiscale Geographically Weighted Regression (MGWR) model. The results show that the average proportion of CAP days in 2019 reached 11.50% of the whole year across Chinese cities, a figure equaling to about 65 days, while the average frequency, the maximum amount of days and the average amount of days of CAP were 8.02 times, 7.85 days and 4.20 days, respectively. Furthermore, there was a distinct spatiotemporal distribution disparity in CAP in China. Spatially, the areas with high proportions of CAP days were concentrated in the North China Plain and the Southwestern Xinjiang Autonomous Region in terms of the spatial pattern, while the proportion of CAP days showed a monthly W-shaped change in terms of the temporal pattern. In addition, the types of regions containing major pollutants during the CAP period could be divided into four types, including “Composite pollution”, “O3 + NO2 pollution”, “PM10 + PM2.5 pollution” and “O3 + PM2.5 pollution”, while the region type “PM10 + PM2.5 pollution” covered the highest number of cities. The MGWR model, characterized by multiple spatial scale impacts among the driving factors, outperformed the traditional OLS and GWR model, and both socioeconomic factors and natural factors were found to have a spatial non-stationary relationship with CAP in China. Our findings provide new policy insights for understanding the spatiotemporal distribution characteristics of CAP in urban China and can help the Chinese government make prevention and control measures of CAP incidents.

Incidence and mortality of lung cancer in 2018 and the temporal trends from 2010 to 2018 in Henan province, China: a population-based registry study

“…Additionally, the air quality in Henan province is poor. According to the daily reported Air Quality Index data for 2019 ( 12 ), the continuous air pollution index of Henan province ranks among the top in China, which might be another reason for the higher incidence of lung cancer. Thus, effective tobacco control and air pollution control are urgently needed.…”

Spatiotemporal Variation in Ground Level Ozone and Its Driving Factors: A Comparative Study of Coastal and Inland Cities in Eastern China

“…MGWR has been widely used in the environmental field, such as PM 2.5 , PM 10 , NO 2 , and other air pollutants [ 42 , 43 , 44 ]. Zhan et al (2022) has examined the spatial heterogeneity effects of both socioeconomic factors and natural factors on continuous air pollution with a MGWR [ 45 ]. Thus, we attempted to analyze the underlying drivers affecting the spatial distribution of O 3 and its spatial heterogeneity from socioeconomic aspects using MGWR.…”