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Predicting heavy metal distribution coefficient in global soil via machine learning: The effect of mineral heterogeneity | Synapse
March 3, 2026
Predicting heavy metal distribution coefficient in global soil via machine learning: The effect of mineral heterogeneity
WZ
Wenping Zuo
HG
Huangling Gu
QL
Qinpeng Liao
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Puntos clave
The analysis predicts the distribution coefficient of heavy metals effectively, enhancing soil assessment methods.
Key metrics indicate that mineral heterogeneity significantly impacts heavy metal distribution, influencing soil quality.
Assessment used machine learning techniques to analyze data from diverse soil samples worldwide, examining various minerals.
Findings may enable better environmental management practices, necessitating further validation across different soil types.
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Zuo et al. (Fri,) studied this question.
synapsesocial.com/papers/69a768adbadf0bb9e87e5908
https://doi.org/https://doi.org/10.1016/j.envres.2026.123957