Cargando…
A neural network-based method for modeling PM 2.5 measurements obtained from the surface particulate matter network
Air pollution is a global problem; hence, many countries devoted lots of resources towards its study and possible eradication. The major parameter indicator for air quality is the particulate matter (PM). These particles, especially PM(2.5), are injurious to health either under high concentration le...
Autores principales: | Onyeuwaoma, Nnaemeka, Okoh, Daniel, Okere, Bonaventure |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8041022/ https://www.ncbi.nlm.nih.gov/pubmed/33846862 http://dx.doi.org/10.1007/s10661-021-09049-3 |
Ejemplares similares
-
Network Analysis of Fine Particulate Matter (PM(2.5)) Emissions in China
por: Yan, Shaomin, et al.
Publicado: (2016) -
Higher-order Network Analysis of Fine Particulate Matter (PM(2.5)) Transport in China at City Level
por: Wang, Yufang, et al.
Publicado: (2017) -
Effects of Green Network Management of Urban Street Trees on Airborne Particulate Matter (PM(2.5)) Concentration
por: Jeong, Na-Ra, et al.
Publicado: (2023) -
Machine learning methods to predict particulate matter PM
(2.5)
por: Palanichamy, Naveen, et al.
Publicado: (2022) -
Fine particulate matter (PM(2.5)) in China at a city level
por: Zhang, Yan-Lin, et al.
Publicado: (2015)