Cao Xin, Liu Xiansheng, Hadiatullah Hadiatullah, Xu Yanning, Zhang Xun, Cyrys Josef, Zimmermann Ralf, Adam Thomas
School of Sport Science, Beijing Sport University, Beijing, 100084, China.
Joint Mass Spectrometry Center, Cooperation Group Comprehensive Molecular Analytics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, Neuherberg, 85764, Germany.
Atmos Pollut Res. 2022 Sep;13(9):101536. doi: 10.1016/j.apr.2022.101536. Epub 2022 Aug 21.
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, NO, O, PM, PM, 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 O, 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, NO, 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. O 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. PM and PM 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.
2020年德国的新冠疫情带来了许多阻碍病毒传播的规定，如封锁措施。因此，在本研究中，我们将2020年奥格斯堡的年度空气污染物（一氧化碳、一氧化氮、二氧化氮、臭氧、细颗粒物、可吸入颗粒物和黑碳）与2010 - 2019年的记录数据进行了比较。2020年的年度空气污染物除臭氧外均显著低于2010 - 2019年（p < 0.001），而臭氧则显著高于2010 - 2019年（p = 0.02）。从深入的角度来看，我们探讨了封锁措施对奥格斯堡空气污染物的影响。我们使用四种不同的模型（即随机森林、K近邻、线性回归和套索回归），根据气象数据、交通密度以及工作日和周末/节假日来模拟空气污染物。根据最佳拟合效果，使用随机森林来预测两个封锁期（2020年3月16日至4月19日，第一次封锁；2020年11月2日至12月31日，第二次封锁）的空气污染物，以探究封锁措施对空气污染物的影响。与预测值相比，在第一次封锁期间，实测的一氧化碳、一氧化氮和黑碳分别显著降低了18.21%、21.75%和48.92%，在第二次封锁期间分别降低了7.67%、32.28%和79.08%。这可能是由于交通和工业活动的减少。臭氧在第一次封锁期间显著增加了15.62%，但在第二次封锁期间下降了40.39%。这可能与一氧化氮滴定效应和光化学效应的波动有关。细颗粒物和可吸入颗粒物在第一次封锁期间分别显著增加了18.23%和10.06%，但在第二次封锁期间分别降低了34.37%和30.62%，这可能归因于它们复杂的生成机制。
