Local Analysis of Air Quality Changes in the Community of Madrid before and during the COVID-19 Induced Lockdown

Abstract

This paper examines the effect of the COVID-19 induced lockdown upon six pollutants, CO, NO, NO2, PM10, PM2.5, and O3, in the Spanish community of Madrid. The paper relies on clustering methods and multiple regression techniques to control for a battery of potential confounding factors. The results show that the nationwide lockdown, decreed on 13 March by the Spanish government, exerted a statistically significant effect upon most pollution indicators. The estimates range from approximately −82% (NO and NO2) to −3% (CO). Reversely, the COVID-19 induced lockdown raised O3 levels by an average of 20%. By using data from 43 stations spread out among the region, the paper provides a local level analysis. This analysis reveals substantial differences across areas and across pollutants. This observation indicates that any successful approach to improve air quality in the region must be multidimensional.

Functional Data Analysis for the Detection of Outliers and Study of the Effects of the COVID-19 Pandemic on Air Quality: A Case Study in Gijón, Spain

“…This time frame corresponds to those weeks with the most strict restrictions for the civilian population in Spain. Previous research work has demonstrated the improvements in air quality due to the lockdown of the COVID-19 pandemic [18][19][20][21][22]. All sources agree on a reduction on the levels of NO 2 ; therefore, it can be considered as a verified event able to validate the method presented.…”

“…The behavior of these pollutants during the lockdown of the COVID-19 pandemic has been studied by previous research [18][19][20][21][22]. All sources concur on a reduction of the NO 2 levels.…”

“…All sources concur on a reduction of the NO 2 levels. Nevertheless, the levels of SO 2 vary accordingly to the industrial activity of the area, PM 10 can be influenced by atmospheric events, and the levels of ground level ozone show an increase in most cases due to the reduction of NO 2 [18]. Consequently, the methods tested will be validated on the NO 2 data, and the technique presented will be applied to study the effects of the other three pollutants during this time.…”

“…Local outliers are detected through their contrast with their neighbors, while global outliers are those which deviate significantly from the rest of the dataset. From an environmental point of view, global outliers indicate a significant polluting event or an unusual absence of contamination, such as the levels of certain pollutants during the COVID-19 lockdown [18][19][20][21][22]. Observations considered as local outliers can also contain important information regarding uncommon processes, hidden trends or polluting events of less significance.…”

Effects of the COVID-19 Pandemic on the Air Quality of the Metropolitan Region of São Paulo: Analysis Based on Satellite Data, Monitoring Stations and Records of Annual Average Daily Traffic Volumes on the Main Access Roads to the City

“…In the MRSP, ~90 km of congested roads were estimated every day in 2019. It was expected that the reduction of congestion during COVID-19 months due to confinement measures may affect the air quality significantly [41][42][43][44].…”