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

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...

Full description

Saved in:
Bibliographic Details
Main Authors: 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: Article
Language:English
Published: Elsevier 2025-08-01
Series:Data in Brief
Subjects:
Air quality modelling
CMAQ
Machine learning
Hybrid modelling
PM2.5
Ozone
Online Access:http://www.sciencedirect.com/science/article/pii/S2352340925004585
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

http://www.sciencedirect.com/science/article/pii/S2352340925004585

Similar Items