Additionally, owing to meteorological factors, the effects differed between inland and coastal regions. Specifically, urban, industrial and highly populated areas of China experienced greater improvements in air quality than rural, residential and less populated areas. The reported reductions in air pollution varied by region and period. We found evidence of a substantial reduction in air pollution immediately after lockdown measures were implemented, with traffic-related NO2 exhibiting the largest decrease. The majority of the eligible studies reported data from central China (e.g., Wuhan and Hubei Province), and the most frequently measured air pollutant was nitrogen dioxide (NO2 51 values in 28 studies), followed by fine particulate matter (PM2.5 49 values in 26 studies). Dalo y michela full#After screening the titles, abstracts and full texts of the retrieved results, two reviewers independently evaluated the relevant data. Following PRISMA guidelines, we used predefined eligibility criteria to search the databases of PubMed, Scopus, Web of Science and EBSCO Host for peer-reviewed published literature that investigated the nexus between COVID-19 and air quality in China. This literature review systematically examines the effect of COVID-19 lockdowns on pollutant concentrations in China by synthesising the reported evidence. As these changes cannot be attributed to a weather effect, it is likely that they are a byproduct of the lockdown measures. 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 an output, we provide a collection of weekly continuous maps, describing the spatial pattern of the NO$_2$ 2019/2020 relative changes. In particular, we focus here on the 2019/2020 relative change in nitrogen dioxide (NO$_2$) concentrations in the north of Italy, for the period of March and April during which the lockdown measure was in force. In this paper we propose a statistical spatio-temporal model as a tool for intervention analysis, able to take into account the effect of weather and other confounding factors, as well as the spatial and temporal correlation existing in the data. 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. 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.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |