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THE STATE OF SCIENCE ON SEVERE AIR POLLUTION EPISODES: QUANTITATIVE AND QUALITATIVE ANALYSIS

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dc.contributor.author Morawska, Lidia
dc.contributor.author Zhu, Tong
dc.contributor.author Liu, Nairui
dc.contributor.author Amouei Torkmahalleh, Mehdi
dc.contributor.author de Fatima Andrade, Maria
dc.contributor.author Barratt, Benjamin
dc.contributor.author Broomandi, Parya
dc.contributor.author Buonanno, Giorgio
dc.contributor.author Carlos Belalcazar Ceron, Luis
dc.contributor.author Chen, Jianmin
dc.contributor.author Cheng, Yan
dc.contributor.author Evans, Greg
dc.contributor.author Gavidia, Mario
dc.contributor.author Guo, Hai
dc.contributor.author Hanigan, Ivan
dc.contributor.author Hu, Min
dc.contributor.author Jeong, Cheol H.
dc.contributor.author Kelly, Frank
dc.contributor.author Gallardo, Laura
dc.contributor.author Kumar, Prashant
dc.contributor.author Lyu, Xiaopu
dc.contributor.author Mullins, Benjamin J.
dc.contributor.author Nordstrøm, Claus
dc.contributor.author Pereira, Gavin
dc.contributor.author Querol, Xavier
dc.contributor.author Roa, Nestor Yezid Rojas
dc.contributor.author Russell, Armistead
dc.contributor.author Thompson, Helen
dc.contributor.author Wang, Hao
dc.contributor.author Wang, Lina
dc.contributor.author Wang, Tao
dc.contributor.author Wierzbicka, Aneta
dc.contributor.author Xue, Tao
dc.contributor.author Ye, Celine
dc.date.accessioned 2021-08-06T04:45:45Z
dc.date.available 2021-08-06T04:45:45Z
dc.date.issued 2021-06-21
dc.identifier.citation Morawska, L., Zhu, T., Liu, N., Amouei Torkmahalleh, M., de Fatima Andrade, M., Barratt, B., Broomandi, P., Buonanno, G., Carlos Belalcazar Ceron, L., Chen, J., Cheng, Y., Evans, G., Gavidia, M., Guo, H., Hanigan, I., Hu, M., Jeong, C. H., Kelly, F., Gallardo, L., … Ye, C. (2021). The state of science on severe air pollution episodes: Quantitative and qualitative analysis. Environment International, 156, 106732. https://doi.org/10.1016/j.envint.2021.106732 en_US
dc.identifier.issn 0160-4120
dc.identifier.uri https://www.sciencedirect.com/science/article/pii/S0160412021003573?via%3Dihub#!
dc.identifier.uri https://doi.org/10.1016/j.envint.2021.106732
dc.identifier.uri http://nur.nu.edu.kz/handle/123456789/5659
dc.description.abstract Severe episodic air pollution blankets entire cities and regions and have a profound impact on humans and their activities. We compiled daily fine particle (PM2.5) data from 100 cities in five continents, investigated the trends of number, frequency, and duration of pollution episodes, and compared these with the baseline trend in air pollution. We showed that the factors contributing to these events are complex; however, long-term measures to abate emissions from all anthropogenic sources at all times is also the most efficient way to reduce the occurrence of severe air pollution events. In the short term, accurate forecasting systems of such events based on the meteorological conditions favouring their occurrence, together with effective emergency mitigation of anthropogenic sources, may lessen their magnitude and/or duration. However, there is no clear way of preventing events caused by natural sources affected by climate change, such as wildfires and desert dust outbreaks. en_US
dc.language.iso en en_US
dc.publisher Elsevier Ltd en_US
dc.relation.ispartofseries Environment International;Volume 156, November 2021, 106732
dc.rights Attribution-NonCommercial-ShareAlike 3.0 United States *
dc.rights.uri http://creativecommons.org/licenses/by-nc-sa/3.0/us/ *
dc.subject Type of access: Open Access en_US
dc.subject Research Subject Categories::TECHNOLOGY en_US
dc.subject Formation of secondary pollutants en_US
dc.subject Mitigating air pollutants en_US
dc.subject Pollution emissions en_US
dc.subject Pollution episodes en_US
dc.subject Severe air pollution events en_US
dc.subject Urban air pollution en_US
dc.title THE STATE OF SCIENCE ON SEVERE AIR POLLUTION EPISODES: QUANTITATIVE AND QUALITATIVE ANALYSIS en_US
dc.type Article en_US
workflow.import.source science


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Attribution-NonCommercial-ShareAlike 3.0 United States Except where otherwise noted, this item's license is described as Attribution-NonCommercial-ShareAlike 3.0 United States