Contributions of various driving factors to air pollution events: Interpretability analysis from Machine learning perspective

Contributions of various driving factors to air pollution events: Interpretability analysis from Machine learning perspective

The air quality in China has been improved substantially, however fine particulate matter (PM2.5) still remain at a high level in many areas. PM2.5 pollution is a complex process that is attributed to gaseous precursors, chemical, and meteorological factors. Quantifying the contribution of each vari...

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Bibliographic Details
Main Authors:	Tianshuai Li, Qingzhu Zhang, Yanbo Peng, Xu Guan, Lei Li, Jiangshan Mu, Xinfeng Wang, Xianwei Yin, Qiao Wang
Format:	Article
Language:	English
Published:	Elsevier 2023-03-01
Series:	Environment International
Subjects:	PM2.5 Air pollution Machine learning Permutation importance PDP SHAP
Online Access:	http://www.sciencedirect.com/science/article/pii/S0160412023001344

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