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Advancing methodologies for applying machine learning and evaluating spatiotemporal models of fine particulate matter (PM(2.5)) using satellite data over large regions

Reconstructing the distribution of fine particulate matter (PM(2.5)) in space and time, even far from ground monitoring sites, is an important exposure science contribution to epidemiologic analyses of PM(2.5) health impacts. Flexible statistical methods for prediction have demonstrated the integrat...

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Shranjeno v:
Bibliografske podrobnosti
izdano v:Atmos Environ (1994)
Main Authors: Just, Allan C., Arfer, Kodi B., Rush, Johnathan, Dorman, Michael, Shtein, Alex, Lyapustin, Alexei, Kloog, Itai
Format: Artigo
Jezik:Inglês
Izdano: 2020
Teme:
Online dostop:https://ncbi.nlm.nih.gov/pmc/articles/PMC7591135/
https://ncbi.nlm.nih.gov/pubmed/33122961
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.atmosenv.2020.117649
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