Spatiotemporal characteristics of PM2.5 and ozone concentrations in Chinese urban clusters

Chuxiong Deng; Si Tian; Zhongwu Li; Ke Li

doi:10.1016/j.chemosphere.2022.133813

Spatiotemporal characteristics of PM_2.5 and ozone concentrations in Chinese urban clusters

Chemosphere. 2022 May:295:133813. doi: 10.1016/j.chemosphere.2022.133813. Epub 2022 Jan 31.

Authors

Chuxiong Deng¹, Si Tian², Zhongwu Li³, Ke Li⁴

Affiliations

¹ School of Geographic Sciences, Hunan Normal University, Changsha, Hunan, 410081, PR China. Electronic address: dcxppd@hunnu.edu.cn.
² School of Geographic Sciences, Hunan Normal University, Changsha, Hunan, 410081, PR China. Electronic address: tiansi1217@163.com.
³ School of Geographic Sciences, Hunan Normal University, Changsha, Hunan, 410081, PR China. Electronic address: lzw17002@hunnu.edu.cn.
⁴ Key Laboratory of Computing and Stochastic Mathematics (Ministry of Education of China), Key Laboratory of Applied Statistics and Data Science, School of Mathematics and Statistics, Hunan Normal University, Changsha, Hunan, 410081, PR China. Electronic address: like@hunnu.edu.cn.

PMID: 35114261
DOI: 10.1016/j.chemosphere.2022.133813

Abstract

Despite China's public commitment to emphasise air pollution investigation and control, trends in PM_2.5 and ozone concentrations in Chinese urban clusters remain unclear. This study quantifies the spatiotemporal variations in PM_2.5 and surface ozone at the scale of Chinese urban clusters by using a long-term integrated dataset from 2015 to 2020. Nonlinear Granger causality testing was used to explore the spatial association patterns of PM_2.5 and ozone pollution in five megacity cluster regions. The results show a significant downward trend in annual mean PM_2.5 concentrations from 2015 to 2020, with a decline rate of 2.8 μg m^-3 yr^-1. By contrast, surface ozone concentrations increased at a rate of 2.1 μg m^-3 yr^-1 over the 6 years. The annual mean PM_2.5 concentrations in urban clusters show significant spatial clustering characteristics, mainly in Beijing-Tianjin-Hebei (BTH), Fenwei Plain (FWP), Northern slope of Tianshan Mountains urban cluster (NSTM), Sichuan Basin urban cluster (SCB), and Yangtze River Delta (YRD). Surface ozone shows severe summertime pollution and distributional variability, with increased ozone pollution in major urban clusters. The highest increases were observed in BTH, Yangtze River midstream urban cluster (YRMR), YRD, and Pearl River Delta (PRD). Nonlinear Granger causality tests showed that PM_2.5 was a nonlinear Granger cause of ozone, further supporting the literature's findings that PM_2.5 reduction promoted photochemical reaction rates and stimulated ozone production. The nonlinear test statistic passed the significance test in magnitude and statistical significance. FWP was an exception, with no significant long-term nonlinear causal link between PM_2.5 and ozone. This study highlights the challenges of compounded air pollution caused primarily by ozone and secondary PM_2.5. These results have implications for the design of synergistic pollution abatement policies for coupled urban clusters.

Keywords: Non-linear granger causality testing; Ozone; PM(2.5); Spatiotemporal characteristics; Urban clusters.

MeSH terms

Air Pollutants* / analysis
Air Pollution* / analysis
Beijing
China
Environmental Monitoring / methods
Ozone* / analysis
Particulate Matter / analysis

Substances

Air Pollutants
Particulate Matter
Ozone