Rare earth elements redistribution in mine tailings soil: A comparative study of sunlit and shady slopes after in-situ leaching
Date
2024
Authors
Luo, Y.
Zhang, Z.
Lin, J.
Owens, G.
Chen, Z.
Chen, Z.
Editors
Advisors
Journal Title
Journal ISSN
Volume Title
Type:
Journal article
Citation
Journal of Hazardous Materials, 2024; 476
Statement of Responsibility
Conference Name
Abstract
The in-situ leaching of rare earth minerals results in ecological differences between sunlit and shady slopes, which may be related to differences in the distribution REEs in the associated soil matrices. Studies of REEs mine tailings in Southern China indicated higher total concentrations of REEs on sunlit slopes compared to shady ones. Specifically, the exchangeable REEs fraction (F1-REEs) was higher on the shady slopes, whereas the Fe/Mn oxides bound REEs fraction (F3-REEs) was higher on the sunlit slopes. In addition, light REE (LREE) concentrations were lower at lower elevations. With the exception of the Ce fraction which remained stable, this indicated a change in all REEs distributions, moving from F1-REEs towards the residual fraction. Hierarchical cluster and principal component analysis revealed a strong correlation between F3-REEs, organic matter bound REEs (F4-REEs), and LREEs, and a positive association of F3-REEs with sunlight exposure. Partial Least Squares Path Modeling analysis suggested that OM promoted the conversion of LREEs to F3 and F4-REEs in soil driven by sunlight exposure. Additionally, as the Fe<sub>o</sub>/Fe<sub>d</sub> ratio decreased, more LREEs were converted to F3. This study suggests that sunlight and elevation both play a critical role in the geochemical dynamics of REEs in in-situ tailings, advocating for environmental evaluations to be undertaken in order to accurately understand the ecological impacts of rare earth mining.
School/Discipline
Dissertation Note
Provenance
Description
Data source: Supplementary material, https://doi.org/10.1016/j.jhazmat.2024.135095
Access Status
Rights
Copyright 2024 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.