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Título

Investigation of COVID-19-related lockdowns on the air pollution changes in augsburg in 2020, Germany

AutorCao, Xin; Liu, Xiansheng CSIC ORCID; Hadiatullah, Hadiatullah; Xu, Yanning; Zhang, Xun; Cyrys, Josef; Zimmermann, Ralf; Adam, Thomas
Palabras claveTraffic volume
Air pollution
COVID-19
Lockdown
Random forest
Fecha de publicaciónsep-2022
EditorElsevier
CitaciónAtmospheric Pollution Research 13 (9): 101536 (2022)
ResumenThe COVID-19 pandemic in Germany in 2020 brought many regulations to impede its transmission such as lockdown. Hence, in this study, we compared the annual air pollutants (CO, NO, NO2, O3, PM10, PM2.5, and BC) in Augsburg in 2020 to the record data in 2010-2019. The annual air pollutants in 2020 were significantly (p < 0.001) lower than that in 2010-2019 except O3, which was significantly (p = 0.02) higher than that in 2010-2019. In a depth perspective, we explored how lockdown impacted air pollutants in Augsburg. We simulated air pollutants based on the meteorological data, traffic density, and weekday and weekend/holiday by using four different models (i.e. Random Forest, K-nearest Neighbors, Linear Regression, and Lasso Regression). According to the best fitting effects, Random Forest was used to predict air pollutants during two lockdown periods (16/03/2020-19/04/2020, 1st lockdown and 02/11/2020-31/12/2020, 2nd lockdown) to explore how lockdown measures impacted air pollutants. Compared to the predicted values, the measured CO, NO2, and BC significantly reduced 18.21%, 21.75%, and 48.92% in the 1st lockdown as well as 7.67%, 32.28%, and 79.08% in the 2nd lockdown. It could be owing to the reduction of traffic and industrial activities. O3 significantly increased 15.62% in the 1st lockdown but decreased 40.39% in the 2nd lockdown, which may have relations with the fluctuations the NO titration effect and photochemistry effect. PM10 and PM2.5 were significantly increased 18.23% an 10.06% in the 1st lockdown but reduced 34.37% and 30.62% in the 2nd lockdown, which could be owing to their complex generation mechanisms.
Versión del editorhttps://doi.org/10.1016/j.apr.2022.101536
URIhttp://hdl.handle.net/10261/278597
DOI10.1016/j.apr.2022.101536
ISSN1309-1042
Aparece en las colecciones: (IDAEA) Artículos
(PTI Salud Global) Colección Especial COVID-19

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