Abstract

According to economics and medical science literature, health issues are connected to airborne pollutants. However, the complex natural processes underlying this phenomenon are often a drawback for policymakers in designing and implementing interventions aimed at reducing air pollution in urban areas (e.g. traffic restrictions). The complete lockdown which followed the COVID-19 outburst in Italy – during which both people movements and the economy were almost frozen – provides a unique natural experiment to assess the relations existing between local air pollution and different emission sources. This study used machine learning methods to estimate the change in concentrations for major pollutants induced by the lockdown in Lombardy and shows that the lockdown reduced concentrations of nitrogen oxides (NOx), but not fine particulate matter (PM 2.5). This is consistent with the reduction in road traffic, but small changes in emission from building heating. Authors then computed the estimated life-years saved due to the improved air quality.

Speaker: Francesco Granella, RFF-CMCC, European Institute on Economics and the Environment (EIEE)
Discussant: Guido Lanzani, ARPA Lombardia
Moderator: Lara Aleluia, RFF-CMCC European Institute on Economics and the Environment (EIEE)