Differential impact of government lockdown policies on reducing air pollution levels and related mortality in Europe

Abstract

Previous studies have reported a decrease in air pollution levels 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. This study contributes to knowledge by quantifying the association between specific lockdown measures and the decrease in NO₂, O₃, PM_2.5, and PM₁₀ levels across 47 European cities. It also estimated the number of avoided deaths during the period. This paper used new modelled data from the Copernicus Atmosphere Monitoring Service (CAMS) to define business-as-usual and lockdown scenarios of daily air pollution trends. This study applies a spatio-temporal Bayesian non-linear mixed effect model to quantify the changes in pollutant concentrations associated with the stringency indices of individual policy measures. The results indicated non-linear associations with a stronger decrease in NO₂ compared to PM_2.5 and PM₁₀ concentrations at very strict policy levels. Differences across interventions were also identified, specifically the strong effects of actions linked to school/workplace closure, limitations on gatherings, and stay-at-home requirements. Finally, the observed decrease in pollution potentially resulted in hundreds of avoided deaths across Europe.

Figure 1

Pollutant change represented as % (Lockdown–BAU differences). NO₂ and PM are expressed by daily mean and O₃ by daily maximum 8 h-mean. This study includes 47 cities (solid thin light grey lines) and their average (solid thick coloured line) from 1st February to 31st July 2020. Three cities [Stockholm (Sweden), London (United Kingdom), and Milan (Italy)] were displayed with solid thin, dashed, and twodash coloured patterns, repectively. Figure created using R software, version 4.0.3.

Figure 2

Estimated association between the SI score and change (Lockdown–BAU differences) for each pollutant. NO₂ and PM are expressed by daily mean and O₃ by daily maximum 8 h-mean. All 47 cities are represented by thin light grey lines, with the average as the thick coloured line. The coloured shaded area represent the credible intervals of the average effect. Figure created using R software, version 4.0.3.

Figure 3

Change in each pollutant’s concentration estimated at 80% SI score across the 47 cities in Europe. NO₂ and PM are expressed by daily mean and O₃ by daily maximum 8 h-mean. Figure created using R software, version 4.0.3.

Figure 4

The effect of individual policies that compose the SI score on changes in the four pollutants (Lockdown–BAU differences), with 95% credible intervals. Figure created using R software, version 4.0.3.