Bayesian multivariate receptor model and convolutional neural network to identify quantitative sources and spatial distributions of potentially toxic elements in soils: A case study in Qingzhou City, China

Determining sources and spatial distributions of potentially toxic elements (PTEs) is a crucial issue of soil pollution survey. However, uncertainty estimation for source contributions remains lack, and accurate spatial prediction is still challenging. Robust Bayesian multivariate receptor model (RB...

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Veröffentlicht in:	Journal of hazardous materials 2024-09, Vol.476, p.135184, Article 135184
Hauptverfasser:	Kong, Xiangyi, Liu, Yang, Duan, Zongqi, Lv, Jianshu
Format:	Artikel
Sprache:	eng
Schlagworte:	Bayesian receptor model Convolutional neural network Potentially toxic elements Source apportionment Spatial distribution
Online-Zugang:	Volltext
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