Explainable geospatial-artificial intelligence models for the estimation of PM2.5 concentration variation during commuting rush hours in Taiwan

PM2.5 concentrations are higher during rush hours at background stations compared to the average concentration across these stations. Few studies have investigated PM2.5 concentration and its spatial distribution during rush hours using machine learning models. This study employs a geospatial-artifi...

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Veröffentlicht in:	Environmental pollution (1987) 2024-05, Vol.349, p.123974-123974, Article 123974
Hauptverfasser:	Wong, Pei-Yi, Su, Huey-Jen, Candice Lung, Shih-Chun, Liu, Wan-Yu, Tseng, Hsiao-Ting, Adamkiewicz, Gary, Wu, Chih-Da
Format:	Artikel
Sprache:	eng
Schlagworte:	Commuting periods Dusk forests Geo-AI model kriging land use model validation Morning PM2.5 pollution Taiwan
Online-Zugang:	Volltext
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