Functional ANOVA approaches for detecting changes in air pollution during the COVID-19 pandemic

Christian Acal,Ana M Aguilera,Annalina Sarra,Sergio Palermi,Tonio Di Battista,Adelia Evangelista

doi:10.1007/s00477-021-02071-4

Abstract

Faced with novel coronavirus outbreak, the most hard-hit countries adopted a lockdown strategy to contrast the spread of virus. Many studies have already documented that the COVID-19 control actions have resulted in improved air quality locally and around the world. Following these lines of research, we focus on air quality changes in the urban territory of Chieti-Pescara (Central Italy), identified as an area of criticality in terms of air pollution. Concentrations of hbox {NO}_{{2}}, hbox {PM}_{{10}}, hbox {PM}_{2.5} and benzene are used to evaluate air pollution changes in this Region. Data were measured by several monitoring stations over two specific periods: from 1st February to 10 th March 2020 (before lockdown period) and from 11st March 2020 to 18 th April 2020 (during lockdown period). The impact of lockdown on air quality is assessed through functional data analysis. Our work makes an important contribution to the analysis of variance for functional data (FANOVA). Specifically, a novel approach based on multivariate functional principal component analysis is introduced to tackle the multivariate FANOVA problem for independent measures, which is reduced to test multivariate homogeneity on the vectors of the most explicative principal components scores. Results of the present study suggest that the level of each pollutant changed during the confinement. Additionally, the differences in the mean functions of all pollutants according to the location and type of monitoring stations (background vs traffic), are ascribable to the hbox {PM}_{{10}} and benzene concentrations for pre-lockdown and during-lockdown tenure, respectively. FANOVA has proven to be beneficial to monitoring the evolution of air quality in both periods of time. This can help environmental protection agencies in drawing a more holistic picture of air quality status in the area of interest.

Highlights

After the discovery of the first case in Wuhan (China) in December 2019, the current outbreak of COVID-19, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has dramatically affected all the countries (Wang et al 2020)
Recent studies suggested that lockdown measures, adopted by the most hard-hit countries around the world in the Spring of 2020 to prevent the spread of COVID-19, have had a positive significant impact on air quality
Being a powerful approach to modelling temporal observations, which is complementary to the usual time series techniques, functional data analysis (FDA) allowed us to reconstruct the temporal profiles of the studied pollutants for the lockdown and unlock phases in each measuring station

Summary

Introduction

After the discovery of the first case in Wuhan (China) in December 2019, the current outbreak of COVID-19, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has dramatically affected all the countries (Wang et al 2020). Coronavirus pandemic has forced nations under partial or complete lockdowns, resulting in prohibition of unnecessary commercial activities in people’s daily lives; prohibition of any types of gathering by residents; restrictions on private (vehicle) and public transportation. In many cities where lockdown measures have been implemented, the decline in economic activities, the nonfunctioning of industries, the drop in road transport, have contributed to mitigate air pollution. Bherwani et al (2020) monetarily quantified the overall benefit due to pollution reduction over the potential economic loss sustained by local governments, as an outcome of lockdown In many cities where lockdown measures have been implemented, the decline in economic activities, the nonfunctioning of industries, the drop in road transport, have contributed to mitigate air pollution. Bherwani et al (2020) monetarily quantified the overall benefit due to pollution reduction over the potential economic loss sustained by local governments, as an outcome of lockdown

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