Assessing a fossil fuels externality with a new neural networks and image optimisation algorithm: the case of atmospheric pollutants as confounders to COVID-19 lethality

This paper demonstrates how the combustion of fossil fuels for transport purpose might cause health implications. Based on an original case study [i.e. the Hubei province in China, the epicentre of the coronavirus disease-2019 (COVID-19) pandemic], we collected data on atmospheric pollutants (PM(2.5...

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Detalles Bibliográficos
Autores principales: Magazzino, Cosimo, Mele, Marco, Schneider, Nicolas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cambridge University Press 2021
Materias:
Original Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8755550/
https://www.ncbi.nlm.nih.gov/pubmed/34782027
http://dx.doi.org/10.1017/S095026882100248X

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8755550/
https://www.ncbi.nlm.nih.gov/pubmed/34782027
http://dx.doi.org/10.1017/S095026882100248X

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