Quantifying the Impact of the Covid-19 Lockdown Measures on Nitrogen Dioxide Levels throughout Europe

In this paper, the effect of the lockdown measures on nitrogen dioxide (NO2) in Europe is analysed by a statistical model approach based on a generalised additive model (GAM). The GAM is designed to find relationships between various meteorological parameters and temporal metrics (day of week, season, etc.) on the one hand and the level of pollutants on the other. The model is first trained on measurement data from almost 2000 monitoring stations during 2015-2019 and then applied to the same stations in 2020, providing predictions of expected concentrations in the absence of a lockdown. The difference between the modelled levels and the actual measurements from 2020 is used to calculate the impact of the lockdown measures adjusted for confounding effects, such as meteorology and temporal trends. The study is focused on April 2020, the month with the strongest reductions in NO2, as well as on the gradual recovery until the end of July. Significant differences between the countries are identified, with the largest NO2 reductions in Spain, France, Italy, Great Britain and Portugal and the smallest in eastern countries (Poland and Hungary). The model is found to perform best for urban and suburban sites. A comparison between the found relative changes in urban surface NO2 data during the lockdown and the corresponding changes in tropospheric vertical NO2 column density as observed by the TROPOMI instrument on Sentinel-5P revealed good agreement despite substantial differences in the observing method.

Automated summary

This paper analyzed the impact of lockdown measures on nitrogen dioxide (NO2) in Europe using a statistical model approach based on a generalised additive model (GAM). Significant differences between countries were identified, with the largest reductions in NO2 observed in Spain, France, Italy, Great Britain, and Portugal. The model performed best for urban and suburban sites.