Abstract

Abstract. The COVID-19 pandemic lockdowns led to a sharp drop in socio-economic activities in China in 2020, including reductions in fossil fuel use, industry productions, and traffic volumes. The short-term impacts of lockdowns on China's air quality have been measured and reported, however, the changes in anthropogenic emissions have not yet been assessed quantitatively, which hinders our understanding of the causes of the air quality changes during COVID-19. Here, for the first time, we report the anthropogenic air pollutant emissions from mainland China by using a bottom-up approach based on the near-real-time data in 2020 and use the estimated emissions to simulate air quality changes with a chemical transport model. The COVID-19 lockdown was estimated to have reduced China's anthropogenic emissions substantially between January and March in 2020, with the largest reductions in February. Emissions of SO2, NOx, CO, non-methane volatile organic compounds (NMVOCs), and primary PM2.5 were estimated to have decreased by 27 %, 36 %, 28 %, 31 %, and 24 %, respectively, in February 2020 compared to the same month in 2019. The reductions in anthropogenic emissions were dominated by the industry sector for SO2 and PM2.5 and were contributed to approximately equally by the industry and transportation sectors for NOx, CO, and NMVOCs. With the spread of coronavirus controlled, China's anthropogenic emissions rebounded in April and since then returned to the comparable levels of 2019 in the second half of 2020. The provinces in China have presented nearly synchronous decline and rebound in anthropogenic emissions, while Hubei and the provinces surrounding Beijing recovered more slowly due to the extension of lockdown measures. The ambient air pollution presented much lower concentrations during the first 3 months in 2020 than in 2019 while rapidly returning to comparable levels afterward, which have been reproduced by the air quality model simulation driven by our estimated emissions. China's monthly anthropogenic emissions in 2020 can be accessed from https://doi.org/10.6084/m9.figshare.c.5214920.v2 (Zheng et al., 2021) by species, month, sector, and province.

Highlights

  • The world witnessed the outbreak and spread of the coronavirus disease COVID-19 in the first half of 2020

  • Unlike the air quality index that is monitored in real time, the conventional datasets of energy use and air pollutant emissions are only available after 1 or 2 years of latency, which hampers our understanding of the energy–emission–air quality cascade in a fast-evolving event such as COVID-19

  • The air pollutant emissions were estimated to decline by 19 %–36 % compared to those in February 2019, with nitrogen oxide (NOx) illustrating the largest reductions among the air pollutants

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Summary

Introduction

The world witnessed the outbreak and spread of the coronavirus disease COVID-19 in the first half of 2020. Unlike the air quality index that is monitored in real time, the conventional datasets of energy use and air pollutant emissions are only available after 1 or 2 years of latency, which hampers our understanding of the energy–emission–air quality cascade in a fast-evolving event such as COVID-19. Pioneer studies started to explore the new concept of near-real-time emission tracking to assess the influence of COVID-19 lockdowns on climate and air quality. These new approaches extrapolated the emission inventories of a baseline year to the current time in 2020 based on observational constraints or relevant activity indicators. Since few near-real-time proxies are available at present, several common datasets have to be used to approximate the emission changes of different source sectors

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