Machine learning algorithms for high-resolution prediction of spatiotemporal distribution of air pollution from meteorological and soil parameters

Machine learning algorithms for high-resolution prediction of spatiotemporal distribution of air pollution from meteorological and soil parameters

This study uses machine learning (ML) models for a high-resolution prediction (0.1°×0.1°) of air fine particular matter (PM2.5) concentration, the most harmful to human health, from meteorological and soil data. Iraq was considered the study area to implement the method. Different lags and the chang...

Full description

Bibliographic Details
Published in:Environment International
Main Author: Tao H.; Jawad A.H.; Shather A.H.; Al-Khafaji Z.; Rashid T.A.; Ali M.; Al-Ansari N.; Marhoon H.A.; Shahid S.; Yaseen Z.M.
Format: Article
Language:English
Published: Elsevier Ltd 2023
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85153537218&doi=10.1016%2fj.envint.2023.107931&partnerID=40&md5=91f7aa5b1ffbb13a2eae2389f70ff7ea

Internet

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85153537218&doi=10.1016%2fj.envint.2023.107931&partnerID=40&md5=91f7aa5b1ffbb13a2eae2389f70ff7ea

Similar Items