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...

ver descrição completa

Detalhes bibliográficos

Principais autores:	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
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Elsevier 2025-08-01
coleção:	Data in Brief
Assuntos:	Air quality modelling CMAQ Machine learning Hybrid modelling PM2.5 Ozone
Acesso em linha:	http://www.sciencedirect.com/science/article/pii/S2352340925004585
Tags:	Adicionar Tag Sem tags, seja o primeiro a adicionar uma tag!