Quantitative assessment of changes in surface particulate matter concentrations and precursor emissions over China during the COVID-19 pandemic and their implications for Chinese economic activity

Abstract

Abstract. Sixty days after the lockdown of Hubei Province, where the coronavirus was first reported, China's true recovery from the pandemic remained an outstanding question. This study investigates how human activity changed during this period using observations of surface pollutants. By combining surface data with a three-dimensional chemistry model, the impacts of meteorological variations and variations in yearly emission control are minimized, demonstrating how pollutant levels over China changed before and after the Lunar New Year from 2017 to 2020. The results show that the reduction in NO2 concentrations, an indicator of emissions in the transportation sector, was clearly greater and longer in 2020 than in normal years and started to recover after 15 February. By contrast, PM2.5 emissions had not yet recovered by the end of March, showing a reduction of around 30 % compared with normal years. SO2 emissions were not affected significantly by the pandemic. An additional model study using a top–down emission adjustment still confirms a reduction of around 25 % in unknown surface PM2.5 emissions over the same period, even after realistically updating SO2 and NOx emissions. This evidence suggests that different economic sectors in China may be recovering at different rates, with the fastest recovery in transportation and a slower recovery likely in agriculture. The apparent difference between the recovery timelines of NO2 and PM2.5 implies that monitoring a single pollutant alone (e.g., NOx emissions) is insufficient to draw conclusions on the overall recovery of the Chinese economy.

Impact of the COVID-19 on the vertical distributions of major pollutants from a tower in the Pearl River Delta

“…The reduction in human activities due to the pandemic has greatly decreased primary pollutant emissions, with significant impacts on regional air quality ( Xing et al, 2020 ; Salma et al, 2020 ; Wang et al, 2021 ; Kim et al, 2021 ) and climate ( Gettelman et al, 2021 ), despite differences between regions. In South East Asia, the lockdown led to a notable decrease in aerosol optical depth over the region and in pollution outflow over oceanic areas.…”

Changes in global air pollutant emissions during the COVID-19 pandemic: a dataset for atmospheric modeling

“…The advantage of such a dataset, which provides AFs for assessments of the impact of COVID-19 restrictions on pollutants emitted into the atmosphere, is that it can be applied directly to most global and regional inventories used in chemistry-climate and transport models in a flexible way. The inventories commonly used in these models (Emission Database for Global Atmospheric Research, EDGAR, Crippa et al, 2018; Evaluating the Climate and Air Quality Impacts of Short-Lived Pollutants, ECLIPSE, Klimont et al, 2017; Copernicus Atmosphere Monitoring Service, CAMS, Granier et al, 2019; Multi-resolution Emission Inventory for China, MEIC, Li et al, 2017;etc. ) include the sectors already mentioned (industrial processes, road transportation, power generation, resi- dential, aviation and shipping).…”

Impacts of Lockdown Policy on Air Quality in Chinese Cities on Different Economic Levels during the COVID-19 Pandemic

“…The percentage changes of PM2.5 in all cities is not as large as that of NO2, because the emission sources of PM2.5 may be different from NO2. Unlike NOX emissions, PM2.5 includes direct emissions of particulate matter and gas-to-particle conversion of emission precursors (such as SO2, NOX, NH3, and VOC-volatile organic compounds) mediated by atmospheric chemical conversion (Kim et al, 2021) . Analysis of the sources of PM2.5 shows that the secondary heterogeneous gas-to-particle conversion of nitrate from NOX may be a large source of PM2.5 (Chan et al, 2017;Jiang and Xia, 2017).…”