1. Significantly underestimated traffic-related ammonia emissions in Chinese megacities: Evidence from satellite observations during COVID-19 lockdowns.
- Author
-
Chen P, Wang Q, Shao M, and Liu R
- Subjects
- China, Humans, Particulate Matter analysis, SARS-CoV-2, Beijing, Ammonia analysis, COVID-19 epidemiology, Air Pollutants analysis, Vehicle Emissions analysis, Environmental Monitoring, Air Pollution statistics & numerical data, Cities
- Abstract
Ammonia (NH
3 ) plays an important role in the formation of atmospheric particulate matter, but the contribution of traffic-related emissions remains unclear, particularly in megacities with a large number of vehicles. Taking the opportunity of the stringent COVID-19 lockdowns implemented in Beijing and Shanghai in 2022, this study aims to estimate the traffic-related NH3 emissions in these two megacities based on satellite observations. Differences between urban and suburban areas during the lockdown and non-lockdown periods are compared. It was found that despite different dominating sources, the overall NH3 concentrations in urban and suburban areas were at a similar level, and the lockdown resulted in a more prominent decrease in urban areas, where traffic activities were most heavily affected. The traffic-related contribution to the total emission was estimated to be ∼30% in megacities, and ∼40% in urban areas, which are about 2-10 times higher than that in previous studies. The findings indicate that the traffic-related NH3 emissions have been significantly underestimated in previous studies and may play a more critical role in the formation of air pollution in megacities, especially in winter, when agricultural emissions are relatively low. This study highlights the importance of traffic-related NH3 emissions in Chinese megacities and the need to reassess the emissions and their impacts on air quality., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)- Published
- 2024
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