Laboratoire de Météorologie Dynamique (LMD), Ecole Polytechnique, IPSL Research University, Ecole Normale Supérieure, Université Paris-Saclay, Sorbonne Universités, UPMC Univ Paris 06, CNRS, Route de Saclay, 91128 Palaiseau, France.
Laboratoire de Météorologie Dynamique (LMD), Ecole Polytechnique, IPSL Research University, Ecole Normale Supérieure, Université Paris-Saclay, Sorbonne Universités, UPMC Univ Paris 06, CNRS, Route de Saclay, 91128 Palaiseau, France; Now at Citepa, Technical Reference Center for Air Pollution and Climate Change, 42, rue de Paradis, 75010 Paris, France.
Sci Total Environ. 2020 Nov 1;741:140426. doi: 10.1016/j.scitotenv.2020.140426. Epub 2020 Jun 23.
Recent studies based on observations have shown the impact of lockdown measures taken in various European countries to contain the Covid-19 pandemic on air quality. However, these studies are often limited to compare situations without and with lockdown measures, which correspond to different time periods and then under different meteorological conditions. We propose a modelling study with the WRF-CHIMERE modelling suite for March 2020, an approach allowing to compare atmospheric composition with and without lockdown measures without the biases of meteorological conditions. This study shows that the lockdown effect on atmospheric composition, in particular through massive traffic reductions, has been important for several short-lived atmospheric trace species, with a large reduction in NO concentrations, a lower reduction in Particulate Matter (PM) concentrations and a mitigated effect on ozone concentrations due to non-linear chemical effects.
最近的基于观测的研究表明，欧洲各国为控制 COVID-19 大流行而采取的封锁措施对空气质量的影响。然而，这些研究往往仅限于比较没有和有封锁措施的情况，而这些情况对应于不同的时间段，然后是不同的气象条件。我们提出了一项使用 WRF-CHIMERE 建模套件进行的 2020 年 3 月的建模研究，这种方法允许在没有气象条件偏差的情况下比较有和没有封锁措施的大气成分。这项研究表明，封锁措施对大气成分的影响，特别是通过大规模减少交通，对几种短寿命的大气痕量物种非常重要，导致 NO 浓度大幅降低，PM 浓度降低幅度较小，由于非线性化学效应，臭氧浓度的影响得到缓解。
