| Literature DB >> 33523881 |
Zongbo Shi1, Congbo Song1, Bowen Liu2, Gongda Lu3, Jingsha Xu3, Tuan Van Vu4, Robert J R Elliott2, Weijun Li5, William J Bloss3, Roy M Harrison3.
Abstract
The COVID-19 lockdowns led to major reductions in air pollutant emissions. Here, we quantitatively evaluate changes in ambient NO2, O3, and PM2.5 concentrations arising from these emission changes in 11 cities globally by applying a deweathering machine learning technique. Sudden decreases in deweathered NO2 concentrations and increases in O3 were observed in almost all cities. However, the decline in NO2 concentrations attributable to the lockdowns was not as large as expected, at reductions of 10 to 50%. Accordingly, O3 increased by 2 to 30% (except for London), the total gaseous oxidant (O x = NO2 + O3) showed limited change, and PM2.5 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.Entities:
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Year: 2021 PMID: 33523881 PMCID: PMC7806219 DOI: 10.1126/sciadv.abd6696
Source DB: PubMed Journal: Sci Adv ISSN: 2375-2548 Impact factor: 14.136