Statistical analysis of spatiotemporal heterogeneity of the distribution of air quality and dominant air pollutants and the effect factors in Qingdao Urban Zones

Abstract

Air pollution has impacted people's lives in urban China, and the analysis of the distribution and driving factors behind air quality has become a current research focus. In this study, the temporal heterogeneity of air quality (AQ) and the dominant air pollutants across the four seasons were analyzed based on the Kruskal-Wallis rank-sum test method. Then, the spatial heterogeneity of AQ and the dominant air pollutants across four sites were analyzed based on theWilcoxon signed-rank test method. Finally, the copula model was introduced to analyze the effect of relative factors on dominant air pollutants. The results show that AQ and dominant air pollutants present significant spatiotemporal heterogeneity in the study area. AQ is worst in winter and best in summer. PM10, O3, and PM2.5 are the dominant air pollutants in spring, summer, and winter, respectively. The average concentration of dominant air pollutants presents significant and diverse daily peaks and troughs across the four sites. The main driving factors are pollutants such as SO2, NO2, and CO, so pollutant emission reduction is the key to improving air quality. Corresponding pollution control measures should account for this heterogeneity in terms of AQ and the dominant air pollutants among different.