A Novel Dataset and Benchmark for Surface No2 Prediction from Remote Sensing Data Including Covid Lockdown Measures

NO
2
is an atmospheric trace gas that contributes to global warming as a precursor of greenhouse gases and has adverse effects on human health. Surface NO
2
concentrations are commonly measured through strictly localized networks of air quality stations on the ground. This work presents a novel dataset of surface NO
2
measurements aligned with atmospheric column densities from Sentinel-5P, as well as geographic and meteorological variables and lockdown information
^1
1
Available at https://github.com/HSG-AIML/NO2-dataset. The dataset provides access to data from a variety of sources through a common format and will foster data-driven research into the causes and effects of NO
2
pollution. We showcase the value of the new dataset on the task of surface NO
2
estimation with gradient boosting. The resulting models enable daily estimates and confident identification of EU NO
2
exposure limit breaches. Additionally, we investigate the influence of COVID-19 lockdowns on air quality in Europe and find a significant decrease in NO
2
levels.