Prediction of daily mean and one-hour maximum PM(2.5) concentrations and applications in Central Mexico using satellite-based machine-learning models

BACKGROUND: Machine-learning algorithms are becoming popular techniques to predict ambient air PM(2.5) concentrations at high spatial resolutions (1 × 1 km) using satellite-based aerosol optical depth (AOD). Most machine-learning models have aimed to predict 24 h-averaged PM(2.5) concentrations (mea...

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Detalles Bibliográficos
Autores principales: Gutiérrez-Avila, Iván, Arfer, Kodi B., Carrión, Daniel, Rush, Johnathan, Kloog, Itai, Naeger, Aaron R., Grutter, Michel, Páramo-Figueroa, Víctor Hugo, Riojas-Rodríguez, Horacio, Just, Allan C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group US 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9731899/
https://www.ncbi.nlm.nih.gov/pubmed/36088418
http://dx.doi.org/10.1038/s41370-022-00471-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9731899/
https://www.ncbi.nlm.nih.gov/pubmed/36088418
http://dx.doi.org/10.1038/s41370-022-00471-4

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