Abstract

The results of numerical modeling of air pollution using CHIMERE and COSMO-ART chemical transport models are presented. The modeling was performed according to the scenarios of the 50–60% reduction of emissions from anthropogenic sources in the Moscow region during the period of March–July 2020. Scenario calculations of pollutant concentrations were compared with baseline simulations using regionally adapted inventory of anthropogenic pollutant emissions to the atmosphere. The most significant decrease in the concentrations of NO₂ and CO was reproduced by the models when emissions from two sectoral sources (vehicles and nonindustrial plants) were reduced. The PM₁₀ drop was mostly influenced by the reduction of emissions from industrial combustion. With the total reduction of emissions from anthropogenic sources as compared to the baseline calculations, the pollutant concentration decreased by 44–54% for NO₂, by 38–44% for CO, and by 26–39% for PM₁₀. This generally coincides with the quantitative estimates of the pollution level drop obtained by other authors. The greatest effect of reducing pollutant emissions into the atmosphere was found during the episodes of adverse weather conditions for air purification, when the simulated and observed pollution level increases by 3–5 times as compared to the conditions of intense pollutant dispersion.

中文翻译：

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使用 CHIMERE 和 COSMO-ART 化学传输模型模拟 COVID-19 大流行期间减少排放的地表空气污染

摘要

介绍了使用CHIMERE 和COSMO-ART 化学传输模型对空气污染进行数值模拟的结果。该模型是根据 2020 年 3 月至 2020 年 7 月期间莫斯科地区人为源排放量减少 50-60% 的情景进行的。将污染物浓度的情景计算与使用区域适应的人为污染物清单的基线模拟进行比较排放到大气中。 当两个部门来源（车辆和非工业工厂）的排放量减少时，模型再现了NO ₂和 CO浓度的最显着下降。PM ₁₀ 下降主要受工业燃烧排放减少的影响。与基线计算相比，人为源排放总量减少，NO ₂污染物浓度下降了 44-54% ，CO 污染物浓度下降了 38-44%，PM ₁₀污染物浓度下降了 26-39% 。这通常与其他作者获得的污染水平下降的定量估计一致。在空气净化的不利天气条件下，减少污染物排放到大气中的效果最大，当模拟和观察到的污染水平与污染物强烈扩散的条件相比增加 3-5 倍时。