Item Type |
Conference or Workshop Item
(Paper)
|
Abstract |
NO2 is an atmospheric trace gas that contributes to global warming as a precursor of greenhouse gases and has adverse effects on human health. Surface NO2 concentrations are commonly measured through strictly localized networks of air quality stations on the ground. This work presents a novel dataset of surface NO2 measurements aligned with atmospheric column densities from Sentinel-5P, as well as geographic and meteorological variables and lockdown information. 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 NO2 pollution. We showcase the value of the new dataset on the task of surface NO2 estimation with gradient boosting. The resulting models enable daily estimates and confident identification of EU NO2 exposure limit breaches. Additionally, we investigate the influence of COVID-19 lockdowns on air quality in Europe and find a significant decrease in NO2 levels. |
Authors |
Scheibenreif, Linus Mathias; Mommert, Michael & Borth, Damian |
Research Team |
AIML Lab |
Language |
English |
Subjects |
computer science |
HSG Classification |
contribution to scientific community |
Date |
16 July 2021 |
Publisher |
IEEE |
Place of Publication |
IEEE International Geoscience and Remote Sensing Symposium (IGARSS) 2021 |
Event Title |
IEEE International Geoscience and Remote Sensing Symposium (IGARSS) 2021 |
Event Location |
Brussels, Belgium (virtual) |
Event Dates |
11-16 July 2021 |
Publisher DOI |
https://doi.org/10.1109/IGARSS47720.2021.9554037 |
Official URL |
https://igarss2021.com/view_paper.php?PaperNum=363... |
Contact Email Address |
linus.scheibenreif@unisg.ch |
Depositing User |
Linus Mathias Scheibenreif
|
Date Deposited |
22 Oct 2021 08:27 |
Last Modified |
20 Jul 2022 17:46 |
URI: |
https://www.alexandria.unisg.ch/publications/264664 |