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Spatio-temporal data on the air pollutant nitrogen dioxide derived from Sentinel satellite for France

Monitoring of air pollution is an important task in public health. Availability of data is often hindered by the paucity of the ground monitoring station network. We present here a new spatio-temporal dataset collected and processed from the Sentinel 5P remote sensing platform. As an example applica...

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Detalles Bibliográficos
Autores principales: Omrani, Hichem, Omrani, Bilel, Parmentier, Benoit, Helbich, Marco
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6957866/
https://www.ncbi.nlm.nih.gov/pubmed/31956677
http://dx.doi.org/10.1016/j.dib.2019.105089
Descripción
Sumario:Monitoring of air pollution is an important task in public health. Availability of data is often hindered by the paucity of the ground monitoring station network. We present here a new spatio-temporal dataset collected and processed from the Sentinel 5P remote sensing platform. As an example application, we applied the full workflow to process measurements of nitrogen dioxide (NO(2)) collected over the territory of mainland France from May 2018 to June 2019. The data stack generated is daily measurements at a 4 × 7 km spatial resolution. The supplementary Python code package used to collect and process the data is made publicly available. The dataset provided in this article is of value for policy-makers and health assessment.