A study on identifying synergistic prevention and control regions for PM2.5 and O3 and exploring their spatiotemporal dynamic in China

Haojie Wu; Bin Guo; Tengyue Guo; Lin Pei; Peiqing Jing; Yan Wang; Xuying Ma; Haorui Bai; Zheng Wang; Tingting Xie; Miaoyi Chen

doi:10.1016/j.envpol.2023.122880

A study on identifying synergistic prevention and control regions for PM_2.5 and O₃ and exploring their spatiotemporal dynamic in China

Environ Pollut. 2024 Jan 15:341:122880. doi: 10.1016/j.envpol.2023.122880. Epub 2023 Nov 7.

Authors

Haojie Wu¹, Bin Guo², Tengyue Guo³, Lin Pei⁴, Peiqing Jing⁵, Yan Wang⁶, Xuying Ma⁷, Haorui Bai⁷, Zheng Wang⁷, Tingting Xie⁷, Miaoyi Chen⁷

Affiliations

¹ College of Geomatics, Xi'an University of Science and Technology, Xi'an, Shaanxi, 710054, China; Shaanxi Key Laboratory of Environmental Monitoring and Forewarning of Trace Pollutants, Xi'an, Shaanxi, 710043, China.
² College of Geomatics, Xi'an University of Science and Technology, Xi'an, Shaanxi, 710054, China. Electronic address: guobin12@xust.edu.cn.
³ Department of Geological Engineering, Qinghai University, Xining, Qinghai, 810016, China.
⁴ School of Exercise and Health Sciences, Xi'an Physical Education University, Xi'an, Shaanxi, 710068, China.
⁵ State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, Hubei, 430072, China.
⁶ School of Geography and Tourism, Shaanxi Normal University, Xi'an, Shaanxi, 710119, China.
⁷ College of Geomatics, Xi'an University of Science and Technology, Xi'an, Shaanxi, 710054, China.

PMID: 37944886
DOI: 10.1016/j.envpol.2023.122880

Abstract

Air pollutants, notably ozone (O₃) and fine particulate matter (PM_2.5) give rise to evident adverse impacts on public health and the ecotope, prompting extensive global apprehension. Though PM_2.5 has been effectively mitigated in China, O₃ has been emerging as a primary pollutant, especially in summer. Currently, alleviating PM_2.5 and O₃ synergistically faces huge challenges. The synergistic prevention and control (SPC) regions of PM_2.5 and O₃ and their spatiotemporal patterns were still unclear. To address the above issues, this study utilized ground monitoring station data, meteorological data, and auxiliary data to predict the China High-Resolution O₃ Dataset (CHROD) via a two-stage model. Furthermore, SPC regions were identified based on a spatial overlay analysis using a Geographic Information System (GIS). The standard deviation ellipse was employed to investigate the spatiotemporal dynamic characteristics of SPC regions. Some outcomes were obtained. The two-stage model significantly improved the accuracy of O₃ concentration prediction with acceptable R² (0.86), and our CHROD presented higher spatiotemporal resolution compared with existing products. SPC regions exhibited significant spatiotemporal variations during the Blue Sky Protection Campaign (BSPC) in China. SPC regions were dominant in spring and autumn, and O₃-controlled and PM_2.5-dominated zones were detected in summer and winter, respectively. SPC regions were primarily located in the northwest, north, east, and central regions of China, specifically in the Beijing-Tianjin-Hebei urban agglomeration (BTH), Shanxi, Shaanxi, Shandong, Henan, Jiangsu, Xinjiang, and Anhui provinces. The gravity center of SPC regions was distributed in the BTH in winter, and in Xinjiang during spring, summer, and autumn. This study can supply scientific references for the collaborative management of PM_2.5 and O₃.

Keywords: Cross-validation; Multiple scales; O(3); PM(2.5); Synergistic prevention and control; Two-stage model.

MeSH terms

Air Pollutants* / analysis
Air Pollution* / analysis
Air Pollution* / prevention & control
China
Environmental Monitoring
Particulate Matter / analysis

Substances

Air Pollutants
Particulate Matter