Lockdown-induced Urban Aerosol Change over Changchun, China During COVID-19 Outbreak with Polarization LiDAR

Abstract

Depending on various government policies, COVID-19 (Corona Virus Disease-19) lockdowns have had diverse impacts on global aerosol concentrations. In 2022, Changchun, a provincial capital city in Northeast China, suffered a severe COVID-19 outbreak and implemented a very strict lockdown that lasted for nearly two months. Using ground-based polarization Light Detection and Ranging (LiDAR), we detected real-time aerosol profile parameters (EC, extinction coefficient; DR, depolarization ratio; AOD, aerosol optical depth), as well as air-quality and meteorological indexes from 1 March to 30 April in 2021 and 2022 to quantify the effects of lockdown on aerosol concentrations. The period in 2022 was divided into three stages: pre-lockdown (1–10 March), strict lockdown (11 March to 10 April), and partial lockdown (11–30 April). The results showed that, during the strict lockdown period, compared with the pre-lockdown period, there were substantial reductions in aerosol parameters (EC and AOD), and this was consistent with the concentrations of the atmospheric pollutants PM 2.5 (particulate matter with an aerodynamic diameter ≤ 2.5 µm) and PM 10 (particulate matter with an aerodynamic diameter ≤ 10 µm), and the O 3 concentration increased by 8.3%. During the strict lockdown, the values of EC within 0–1 km and AOD decreased by 16.0% and 11.2%, respectively, as compared to the corresponding period in 2021. Lockdown reduced the conventional and organized emissions of air pollutants, and it clearly delayed the time of seasonal emissions from agricultural burning; however, it did not decrease the number of farmland fire points. Considering meteorological factors and eliminating the influence of wind-blown dust events, the results showed that reductions from conventional organized emission sources during the strict lockdown contributed to a 30% air-quality improvement and a 22% reduction in near-surface extinction (0–2 km). Aerosols produced by urban epidemic prevention and disinfection can also be identified using the EC. Regarding seasonal sources of agricultural straw burning, the concentrated burning induced by the epidemic led to the occurrence of heavy pollution from increased amounts of atmospheric aerosols, with a contribution rate of 62%. These results indicate that there is great potential to further improve air quality in the local area, and suggest that the comprehensive use of straw accompanied by reasonable planned burning is the best way to achieve this.

Impact of the COVID-19 lockdown on typical ambient air pollutants: Cyclical response to anthropogenic emission reduction

“…Wuhan, the city at the center of the COVID-19 epidemic, has been the subject of numerous studies, so the significance of studying it will not be reiterated here. Based on the number of new infections confirmed daily by the Chinese National Health Commission, the measures taken by the local governments, and relevant studies [ [32] , [33] , [34] , [35] ], we selected Shanghai, Shenzhen, Changchun, and Chengdu in addition. As a result of the differences between these cities regarding social development, climatic conditions, geographical location, and levels of air pollution ( Fig.…”

Vertical Profiles of Aerosols Induced by Dust, Smoke, and Fireworks in the Cold Region of Northeast China

“…Furthermore, understanding the dynamic evolution of aerosol properties lays the foundation for formulating strategies to manage anthropogenic emissions, thereby contributing to improvement in air pollution, which poses risks to human health [4]. Based on remote sensing satellites (e.g., the moderate-resolution imaging spectroradiometer, MODIS; medium-resolution imaging spectrometer, MERIS; and cloud-aerosol LiDAR with orthogonal polarization, CALIOP), multiple datasets, such as the aerosol optical depth (AOD), radiance, and water cloud properties, can be retrieved [5][6][7][8]. Notably, cloud-aerosol LiDAR pathfinder satellite observations (CALIPSO) have provided openly accessible observation data on a global scale since June 2006 [9].…”