Augustin Colette, Jerome Barre, Blandine Raux, Marc Guevara, Florian Couvidat, Rostislav Kouznetsov, Marta Blangiardo, Antonio Gasparrini, Vincent-Henri Peuch, Mario Adani, Oriol Jorba, Rochelle Schneider, Francesco Sera, Joaquim Arteta, John Douros, Pierre Masselot, Ana Maria Vicedo Cabrera, Chiara Forlani, London School of Hygiene and Tropical Medicine (LSHTM), University of Bern, Imperial College London, Royal Netherlands Meteorological Institute (KNMI), Barcelona Supercomputing Centre, Italian National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA), Finnish Meteorological Institute (FMI), Institut National de l'Environnement Industriel et des Risques (INERIS), Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS), European Centre for Medium-Range Weather Forecasts (ECMWF), and International Society for Environmental Epidemiology
International audience; BACKGROUND AND AIM: Previous studies have reported a decrease in air pollution following the enforcement of lockdown measures during the first wave of the COVID-19 pandemic. However, these investigations were mostly based on simple pre-post comparisons using past years as a reference, and did not assess the role of different policy interventions. In this contribution, we quantitatively evaluated the association between various lockdown measures and the decrease in NO2, O3, PM2.5, and PM10 levels across 47 European cities and the associated short-term mortality in the period of February-July 2020. METHODS: We used data from several chemical transport models developed by the Copernicus Atmosphere Monitoring Service (CAMS) to define trends in air pollution under business-as-usual and lockdown scenarios, thus removing differences due to weather conditions and other differences affecting pre-post comparisons. We then applied an advanced spatio-temporal Bayesian non-linear mixed effect model to determine the association with stringency indices of individual policy measures, allowing non-linear relationships and geographical correlations. RESULTS: The findings indicate evidence of non-linear relationships, with a stronger decrease in NO2 and to a lesser extent PMs under very strict lockdown regimes. The effects of lockdown measures vary geographically, with a stronger decline in pollution in Southern and Central Europe. The comparative analysis of separate lockdown policies suggests important differences across interventions. Specifically, actions linked to school/workplace closure, limitations on gatherings, and stay-at-home requirements had strong effects, while restrictions on internal movement and international travels showed little impact. The observed decrease in pollution potentially resulted in hundreds of avoided deaths across the European cities. CONCLUSIONS: This study provides important evidence on the differential impacts of various policies implemented during the COVID-19 pandemic in decreasing the level of pollutants in urban areas across Europe.