Response of PM2.5 pollution to meteorological and anthropogenic emissions changes during COVID-19 lockdown in Hunan Province based on WRF-Chem model

Simin Dai; Xuwu Chen; Jie Liang; Xin Li; Shuai Li; Gaojie Chen; Zuo Chen; Juan Bin; Yifan Tang; Xiaodong Li

doi:10.1016/j.envpol.2023.121886

Response of PM_2.5 pollution to meteorological and anthropogenic emissions changes during COVID-19 lockdown in Hunan Province based on WRF-Chem model

Environ Pollut. 2023 Aug 15;331(Pt 2):121886. doi: 10.1016/j.envpol.2023.121886. Epub 2023 May 24.

Authors

Simin Dai¹, Xuwu Chen², Jie Liang¹, Xin Li¹, Shuai Li¹, Gaojie Chen³, Zuo Chen⁴, Juan Bin¹, Yifan Tang¹, Xiaodong Li⁵

Affiliations

¹ College of Environmental Science and Engineering, Hunan University, Changsha, 410082, PR China.
² School of Advanced Interdisciplinary Studies, Hunan University of Technology and Business, Changsha, 410205, PR China.
³ College of Mathematics and Econometrics, Hunan University, Changsha, 410082, PR China.
⁴ College of Information Science and Technology, Hunan University, Changsha, 410082, PR China.
⁵ College of Environmental Science and Engineering, Hunan University, Changsha, 410082, PR China. Electronic address: lxdfox@hnu.edu.cn.

Abstract

In December 2019, the New Crown Pneumonia (the COVID-19) outbroke around the globe, and China imposed a nationwide lockdown starting as early as January 23, 2020. This decision has significantly impacted China's air quality, especially the sharp decrease in PM_2.5 (aerodynamic equivalent diameter of particulate matter less than or equal to 2.5 μm) pollution. Hunan Province is located in the central and eastern part of China, with a "horseshoe basin" topography. The reduction rate of PM_2.5 concentrations in Hunan province during the COVID-19 (24.8%) was significantly higher than the national average (20.3%). Through the analysis of the changing character and pollution sources of haze pollution events in Hunan Province, more scientific countermeasures can be provided for the government. We use the Weather Research and Forecasting with Chemistry (WRF-Chem, V4.0) model to predict and simulate the PM_2.5 concentrations under seven scenarios before the lockdown (2020.1.1-2020.1.22) and during the lockdown (2020.1.23-2020.2.14). Then, the PM_2.5 concentrations under different conditions is compared to differentiate the contribution of meteorological conditions and local human activities to PM_2.5 pollution. The results indicate the most important cause of PM_2.5 pollution reduction is anthropogenic emissions from the residential sector, followed by the industrial sector, while the influence of meteorological factors contribute only 0.5% to PM_2.5. The explanation is that emission reductions from the residential sector contribute the most to the reduction of seven primary contaminants. Finally, we trace the source and transport path of the air mass in Hunan Province through the Concentration Weight Trajectory Analysis (CWT). We found that the external input of PM_2.5 in Hunan Province is mainly from the air mass transported from the northeast, accounting for 28.6%-30.0%. To improve future air quality, there is an urgent need to burn clean energy, improve the industrial structure, rationalize energy use, and strengthen cross-regional air pollution synergy control.

Keywords: Anthropogenic emissions; COVID-19; Hunan province; Meteorological; PM(2.5); Regional transportation.

MeSH terms

Air Pollutants* / analysis
Air Pollution* / analysis
COVID-19*
China / epidemiology
Communicable Disease Control
Humans
Particulate Matter / analysis

Substances

Air Pollutants
Particulate Matter