Forecasting PM10 levels using machine learning models in the Arctic: a comparative study

In this study, we present a statistical forecasting framework and assess its efficacy using a range of established machine learning algorithms for predicting Particulate Matter (PM) concentrations in the Arctic, specifically in Pallas (FI), Reykjavik (IS), and Tromso (NO). Our framework leverages hi...

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Bibliographic Details
Published in:Remote Sensing
Main Authors: FAZZINI Paolo, MONTUORI Marco, PASINI Antonello, CUZZUCOLI Alice, CROTTI Ilaria, CAMPANA Emilio, PETRACCHINI Francesco, DOBRICIC Srdan
Language:English
Published: MDPI 2023
Subjects:
Online Access:https://publications.jrc.ec.europa.eu/repository/handle/JRC134016
https://www.mdpi.com/2072-4292/15/13/3348
https://doi.org/10.3390/rs15133348