PM(2.5) Exposure and Health Risk Assessment Using Remote Sensing Data and GIS

Assessing personal exposure risk from PM(2.5) air pollution poses challenges due to the limited availability of high spatial resolution data for PM(2.5) and population density. This study introduced a seasonal spatial-temporal method of modeling PM(2.5) distribution characteristics at a 1-km grid le...

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Detalles Bibliográficos
Autores principales: Xu, Dan, Lin, Wenpeng, Gao, Jun, Jiang, Yue, Li, Lubing, Gao, Fei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9141174/
https://www.ncbi.nlm.nih.gov/pubmed/35627689
http://dx.doi.org/10.3390/ijerph19106154

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9141174/
https://www.ncbi.nlm.nih.gov/pubmed/35627689
http://dx.doi.org/10.3390/ijerph19106154

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