Estimates of PM2.5 concentrations spatiotemporal evolution across China considering aerosol components in the context of the Reform and Opening-up

Su Ding; Zhiwei Wei; Jianhua He; Dianfeng Liu; Rong Zhao

doi:10.1016/j.jenvman.2022.115983

Estimates of PM_2.5 concentrations spatiotemporal evolution across China considering aerosol components in the context of the Reform and Opening-up

J Environ Manage. 2022 Nov 15:322:115983. doi: 10.1016/j.jenvman.2022.115983. Epub 2022 Sep 1.

Authors

Su Ding¹, Zhiwei Wei², Jianhua He³, Dianfeng Liu³, Rong Zhao⁴

Affiliations

¹ State Key Laboratory of Subtropical Silviculture, Zhejiang A & F University, Hangzhou, 311300, China; Key Laboratory of Carbon Cycling in Forest Ecosystems and Carbon Sequestration of Zhejiang Province, Zhejiang A & F University, Hangzhou, 311300, China; School of Environmental and Resources Science, Zhejiang A & F University, Hangzhou 311300, China. Electronic address: suding@whu.edu.cn.
² School of Remote Sensing & Geomatics Engineering, Nanjing University of Information Science and Technology, Nanjing, 210044, China; Key Laboratory of Network Information System Technology (NIST), Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100190, China.
³ School of Resource and Environmental Sciences, Wuhan University, Wuhan, 430079, China; Key Laboratory of Geographic Information System, Ministry of Education, Wuhan University, Wuhan, 430079, China.
⁴ Vanke School of Public Health, Tsinghua University, Beijing 100084, China.

PMID: 36058070
DOI: 10.1016/j.jenvman.2022.115983

Abstract

With astonishing and rapid development in China since the Reform and Opening-up in 1978, serious air pollution has become a great challenge. A better understanding of the response of PM_2.5 pollution to socioeconomic development after the Reform and Opening-up policy is benefit for pollution control. However, heterogeneous influences of biophysical and socioeconomic activities on PM_2.5 pollution pose great challenges in statistical simulation of PM_2.5. Few statistical model regards aerosol species as the explanatory variables for heterogeneous formation mechanism to retrieve PM_2.5 concentration. In this research, monthly PM_2.5 concentration in China during 1980-2020 was reconstructed by a novel statistical strategy considering aerosol components (AC-RF). Three cross-validation (CV) methods, sample-based CV, spatial-based CV and temporal-based CV results indicated satisfactory performance of AC-RF model with correlation coefficient (R) of 0.92, 0.90, 0.86, respectively. A three-stage concluded on PM_2.5 concentration annual variation in China was drawn as followed: Before 2000, PM_2.5 level in China represented smooth evolution and mainly influenced by natural events with polluted region locating in Xinjiang province, North China and Central China. Since 2000, PM_2.5 concentration increased to high level in the context of rapid socioeconomic development. Severe air pollution covered Jing-Jin-Ji agglomeration, Central China and Sichuan Basin. During 2012-2020, PM_2.5 declined and polluted region shrank, which was benefited by the strictest-ever air pollution control measures. Based on aerosol components analysis, sulfate aerosol exhibited the most significant increase trend in recent 40 years and black aerosol variation is the most closely related to PM_2.5 pollution. In conclusion, unsustainable development is the culprit for air quality deterioration. Strict and continuous air pollution control strategies are effective for air quality improvement.

Keywords: Aerosol components; Long-term trend; MERRA-2; PM(2.5) concentration.

MeSH terms

Aerosols / analysis
Air Pollutants* / analysis
China
Environmental Monitoring / methods
Particulate Matter* / analysis
Sulfates / analysis

Substances

Aerosols
Air Pollutants
Particulate Matter
Sulfates