Development of longitudinal datasets (2000–2020) with high spatiotemporal resolution for air pollution exposure assessment in CanadaFRDR)

We developed datasets intended to aid and inform, health and epidemiological studies in Canada by providing highly resolved spatiotemporal concentrations for regulated air pollutants (fine particulate matter PM2.5, nitrogen dioxide NO2, and ozone O3) across Canada. Daily estimates were generated at...

Descripció completa

Dades bibliogràfiques

Autors principals:	Anas Alhusban, Yasar Burak Oztaner, Markey Johnson, Mastaneh Rezasefat, Negin Hojjatzadeh, Israa Moussa, Mahsa Soleimani, Saeed Nadi, Shunliu Zhao, Hwashin Shin, Joyce J.Y. Zhang, Amir Hakami
Format:	Artigo
Idioma:	Inglês
Publicat:	Elsevier 2025-08-01
Col·lecció:	Data in Brief
Matèries:	Air quality modelling CMAQ Machine learning Hybrid modelling PM2.5 Ozone
Accés en línia:	http://www.sciencedirect.com/science/article/pii/S2352340925004585
Etiquetes:	Afegir etiqueta Sense etiquetes, Sigues el primer a etiquetar aquest registre!