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Cao, X. ; Liu, X.* ; Hadiatullah, H.* ; Xu, Y.* ; Zhang, X.* ; Bendl, J.* ; Cyrys, J.* ; Zimmermann, R. ; Adam, T.

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

Atmos. Pollut. Res. 13:101536 (2022)
DOI PMC
Free by publisher: Verlagsversion online verfügbar 09/2025
The 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.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Korrespondenzautor
Schlagwörter Air Pollution ; Covid-19 ; Lockdown ; Random Forest ; Traffic Volume
e-ISSN 1309-1042
Zeitschrift Atmospheric Pollution Research
Quellenangaben Band: 13, Heft: 9, Seiten: , Artikelnummer: 101536 Supplement: ,
Verlag Elsevier
Verlagsort Buca
Nichtpatentliteratur Publikationen
Begutachtungsstatus Peer reviewed
Institut(e) Cooperation Group Comprehensive Molecular Analytics (CMA)
Förderungen Project of High-level Teachers in Beijing Municipal Universities in the Period of 13th Five-year Plan
National Natural Science Foundation of China
Bundesministerium für Verkehr und Digitale Infrastruktur