When a new environmental policy or a specific intervention is taken in order to improve air quality, it is paramount to assess and quantify—in space and time—the effectiveness of the adopted strategy. The lockdown measures taken worldwide in 2020 to reduce the spread of the SARS-CoV-2 virus can be envisioned as a policy intervention with an indirect effect on air quality. In this paper we propose a statistical spatiotemporal model as a tool for intervention analysis, able to take into account the effect of weather and other confounding factor, as well as the spatial and temporal correlation existing in the data. In particular, we focus here on the 2019/2020 relative change in nitrogen dioxide (NO2${}_2$) concentrations in the north of Italy, for the period of March and April during which the lockdown measure was in force. We found that during March and April 2020 most of the studied area is characterized by negative relative changes (median values around −$-$25%), with the exception of the first week of March and the fourth week of April (median values around 5%). As these changes cannot be attributed to a weather effect, it is likely that they are a byproduct of the lockdown measures. There are two aspects of our research that are equally interesting. First, we provide a unique statistical perspective for calculating the relative change in the NO2${}_2$ by jointly modeling pollutant concentrations time series. Second, as an output we provide a collection of weekly continuous maps, describing the spatial pattern of the NO2${}_2$ 2019/2020 relative changes.

中文翻译：

---

意大利 2020 年 COVID-19 封锁期间二氧化氮浓度的时空分析


当采取新的环境政策或具体干预措施以改善空气质量时，最重要的是在空间和时间上评估和量化所采用策略的有效性。 2020 年全球为减少 SARS-CoV-2 病毒传播而采取的封锁措施可以被视为对空气质量产生间接影响的政策干预措施。在本文中，我们提出了一种统计时空模型作为干预分析的工具，能够考虑天气和其他混杂因素的影响，以及数据中存在的时空相关性。我们在此特别关注 2019/2020 年二氧化氮 (NO2${}_2$
）在封锁措施生效的三月和四月期间，集中在意大利北部。我们发现，在 2020 年 3 月和 4 月期间，大多数研究区域的特点是相对负变化（中值约为−$-$
25%），三月第一周和四月第四周除外（中值约为 5%）。由于这些变化不能归因于天气影响，因此它们很可能是封锁措施的副产品。我们的研究有两个方面同样有趣。首先，我们提供了一个独特的统计视角来计算 NO 的相对变化2${}_2$
通过对污染物浓度时间序列进行联合建模。其次，作为输出，我们提供每周连续地图的集合，描述 NO 的空间模式2${}_2$
2019/2020 相对变化。