Communications in Information and Systems

Volume 23 (2023)

Number 2

Quantitative anatomy of characteristics and influencing factors of PM2.5 and O3 in Liaoning province of China

Pages: 185 – 212

DOI: https://dx.doi.org/10.4310/CIS.2023.v23.n2.a2

Authors

Hongmei Yang (Institute for Mathematical Sciences, Renmin University of China, Beijing, China; and School of Mathematics and Data Sciences, Changji University, Xinjiang, China)

Yanqi Liu (Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China)

Xiaoqiu Jiang (International Poverty Reduction Center in China, Beijing, China)

Xinqi Gong (Institute for Mathematical Sciences, Renmin University of China, Beijing, China)

Abstract

Northeast China is an important region in Asia, bordered by Siberia to the north and Bohai Sea and Yellow Sea to the south. Liaoning province is one of the most important industrial and agricultural bases in China. It is located in the south of Northeast China. Due to the unique characteristics of geography, climate and anthropogenic emissions, it is of great significance to explore the air pollution in Liaoning Province. In this paper, spatial association network feature analysis, spatial interpolation, standard deviation ellipse and exploratory spatial data analysis are used to analyze the temporal and spatial evolution characteristics and influencing factors of PM2.5 and O3 in Liaoning Province. The results demonstrate that PM2.5 concentration has a decreasing trend in all cities, while O3 concentration has no obvious decreasing trend. The high concentration of PM2.5 is mainly distributed in central and northern of Liaoning, while high concentration of O3 is in central-western and coastal cities. PM2.5 and O3 show opposite seasonal dynamic characteristic, which is mainly due to their seasonal anthropogenic emissions, meteorological factors conducive to pollutant generation and geographical conditions unfavorable to the diffusion of air pollutants. Moreover, PM2.5 and O3 have certain spatial correlation with economic factors, such as agriculture, industry, tertiary industry and population density. The results of this study enable a more comprehensive understanding of the temporal and spatial distribution characteristics and the relative influencing factors of PM2.5 and O3 in Liaoning Province. This provides a policy basis for regional joint prevention and control and collaborative air pollution control in Northeast China.

Keywords

PM2.5, O3, quantitative anatomy

Received 28 January 2023

Published 7 August 2023