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Global fine-scale changes in ambient NO 2 during COVID-19 lockdowns.
- Source :
-
Nature [Nature] 2022 Jan; Vol. 601 (7893), pp. 380-387. Date of Electronic Publication: 2022 Jan 19. - Publication Year :
- 2022
-
Abstract
- Nitrogen dioxide (NO <subscript>2</subscript> ) is an important contributor to air pollution and can adversely affect human health <superscript>1-9</superscript> . A decrease in NO <subscript>2</subscript> concentrations has been reported as a result of lockdown measures to reduce the spread of COVID-19 <superscript>10-20</superscript> . Questions remain, however, regarding the relationship of satellite-derived atmospheric column NO <subscript>2</subscript> data with health-relevant ambient ground-level concentrations, and the representativeness of limited ground-based monitoring data for global assessment. Here we derive spatially resolved, global ground-level NO <subscript>2</subscript> concentrations from NO <subscript>2</subscript> column densities observed by the TROPOMI satellite instrument at sufficiently fine resolution (approximately one kilometre) to allow assessment of individual cities during COVID-19 lockdowns in 2020 compared to 2019. We apply these estimates to quantify NO <subscript>2</subscript> changes in more than 200 cities, including 65 cities without available ground monitoring, largely in lower-income regions. Mean country-level population-weighted NO <subscript>2</subscript> concentrations are 29% ± 3% lower in countries with strict lockdown conditions than in those without. Relative to long-term trends, NO <subscript>2</subscript> decreases during COVID-19 lockdowns exceed recent Ozone Monitoring Instrument (OMI)-derived year-to-year decreases from emission controls, comparable to 15 ± 4 years of reductions globally. Our case studies indicate that the sensitivity of NO <subscript>2</subscript> to lockdowns varies by country and emissions sector, demonstrating the critical need for spatially resolved observational information provided by these satellite-derived surface concentration estimates.<br /> (© 2022. The Author(s).)
Details
- Language :
- English
- ISSN :
- 1476-4687
- Volume :
- 601
- Issue :
- 7893
- Database :
- MEDLINE
- Journal :
- Nature
- Publication Type :
- Academic Journal
- Accession number :
- 35046607
- Full Text :
- https://doi.org/10.1038/s41586-021-04229-0