Global and Geographically and Temporally Weighted Regression Models for Modeling PM(2.5) in Heilongjiang, China from 2015 to 2018

Objective: This study investigated the relationships between PM(2.5) and 5 criteria air pollutants (SO(2), NO(2), PM(10), CO, and O(3)) in Heilongjiang, China, from 2015 to 2018 using global and geographically and temporally weighted regression models. Methods: Ordinary least squares regression (OLS...

Descripción completa

Detalles Bibliográficos
Autores principales: Wei, Qingbin, Zhang, Lianjun, Duan, Wenbiao, Zhen, Zhen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6950195/
https://www.ncbi.nlm.nih.gov/pubmed/31847317
http://dx.doi.org/10.3390/ijerph16245107

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6950195/
https://www.ncbi.nlm.nih.gov/pubmed/31847317
http://dx.doi.org/10.3390/ijerph16245107

Ejemplares similares