Abrupt but smaller than expected changes in surface air quality attributable to COVID-19 lockdowns

• Published in: Science advances Vol. 7; no. 3
• Main Authors: Shi, Zongbo, Song, Congbo, Liu, Bowen, Lu, Gongda, Xu, Jingsha, Van Vu, Tuan, Elliott, Robert J R, Li, Weijun, Bloss, William J, Harrison, Roy M
• Format: Journal Article
• Language: English
• Published: United States American Association for the Advancement of Science 01.01.2021
• Subjects: Air Pollutants - analysis; Air Pollution; Atmospheric Science; Cities; Coronavirus; COVID-19 - epidemiology; Environmental Monitoring - methods; Environmental Studies; Gases - analysis; Humans; London; Machine Learning; Nitrogen Dioxide - analysis; Ozone - analysis; Paris; Particulate Matter; SciAdv r-articles; Temperature; London; Paris; Cities
• ISSN: 2375-2548; 2375-2548
• DOI: 10.1126/sciadv.abd6696

The COVID-19 lockdowns led to major reductions in air pollutant emissions. Here, we quantitatively evaluate changes in ambient NO , O , and PM concentrations arising from these emission changes in 11 cities globally by applying a deweathering machine learning technique. Sudden decreases in deweathered NO concentrations and increases in O were observed in almost all cities. However, the decline in NO concentrations attributable to the lockdowns was not as large as expected, at reductions of 10 to 50%. Accordingly, O increased by 2 to 30% (except for London), the total gaseous oxidant (O = NO + O ) showed limited change, and PM concentrations decreased in most cities studied but increased in London and Paris. Our results demonstrate the need for a sophisticated analysis to quantify air quality impacts of interventions and indicate that true air quality improvements were notably more limited than some earlier reports or observational data suggested.