Satellite data and machine learning reveal a significant correlation between NO
Covid-19
Pollution
Remote sensing
Sentinel-5p
Journal
Environmental research
ISSN: 1096-0953
Titre abrégé: Environ Res
Pays: Netherlands
ID NLM: 0147621
Informations de publication
Date de publication:
03 2022
03 2022
Historique:
received:
31
03
2021
revised:
30
07
2021
accepted:
21
08
2021
pubmed:
3
9
2021
medline:
15
12
2021
entrez:
2
9
2021
Statut:
ppublish
Résumé
The Coronavirus disease 2019 (COVID-19) pandemic has officially spread all over the world since the beginning of 2020. Although huge efforts are addressed by scientists to shed light over the several questions raised by the novel SARS-CoV-2 virus, many aspects need to be clarified, yet. In particular, several studies have pointed out significant variations between countries in per-capita mortality. In this work, we investigated the association between COVID-19 mortality with climate variables and air pollution throughout European countries using the satellite remote sensing images provided by the Sentinel-5p mission. We analyzed data collected for two years of observations and extracted the concentrations of several pollutants; we used these measurements to feed a Random Forest regression. We performed a cross-validation analysis to assess the robustness of the model and compared several regression strategies. Our findings reveal a significant statistical association between air pollution (NO
Identifiants
pubmed: 34474031
pii: S0013-9351(21)01265-2
doi: 10.1016/j.envres.2021.111970
pmc: PMC8403556
pii:
doi:
Substances chimiques
Air Pollutants
0
Particulate Matter
0
Nitrogen Dioxide
S7G510RUBH
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
111970Informations de copyright
Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.
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