Speciation Characteristics and Risk Assessment of Heavy Metals in Cultivated Soil in Pingshui Village, Zhaoping County, Hezhou City, Guangxi DOI Creative Commons

Yuanxu MA,

Meilan Wen, Panfeng Liu

et al.

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(23), P. 11361 - 11361

Published: Dec. 5, 2024

In order to comprehensively understand the content, source, speciation characteristics, and risk of heavy metals in cultivated soil Pingshui Village, Zhaoping County, Hezhou City, this study conducted measurements on total amounts Cr, Ni, Cu, Zn, As, Cd, Pb, Hg 34 samples within area. Correlation analysis principal component were employed investigate their sources. An improved BCR sequential extraction procedure was utilized analyze occurrence forms eight samples. Ecological risks evaluated using geo-accumulation index (Igeo), potential ecological (RI), assessment code (RAC). The findings revealed that: (1) area exhibited varying degrees enrichment, primarily attributed anthropogenic activities. (2) There no significant difference characteristics each sampling site area, main components all residual fraction, mild acid-soluble fraction Cd Zn accounted for a relatively high proportion individual sites, which should be paid attention to. (3) Through results three methods, it is concluded that metal pollution serious, continuous corresponding prevention measures.

Language: Английский

Machine learning-supported determination for site-specific natural background values of soil heavy metals DOI
Jian Wu, Chengmin Huang

Journal of Hazardous Materials, Journal Year: 2025, Volume and Issue: 487, P. 137276 - 137276

Published: Jan. 18, 2025

Language: Английский

Citations

1
Relationships between heavy metal migration in soils and landslide dynamics under conditions of modern climate change: A case study of Lake Baikal, Olkhon Island DOI
T. Yu. Cherkashina, А. А. Svetlakov, V. A. Pellinen

et al.

The Science of The Total Environment, Journal Year: 2025, Volume and Issue: 975, P. 179285 - 179285

Published: April 2, 2025

Language: Английский

Citations

0
Prediction of Soil Pollution Risk Based on Machine Learning and SHAP Interpretable Models in the Nansi Lake, China DOI Creative Commons
Min Wang, Ruilin Zhang, Beibei Yan

et al.

Toxics, Journal Year: 2025, Volume and Issue: 13(4), P. 278 - 278

Published: April 5, 2025

To assess and predict the Nansi Lake soil pollution risk, we evaluate environmental quality in region using machine learning techniques, combined with SHapley Additive exPlanations (SHAP) model for interpretability. The primary objective was to level of caused by heavy metals, incorporating traditional Pollution Load Index (PLI) Potential Ecological Risk (PERI) methods. Through integration statistical characteristics, PLI, PERI evaluations, a new assessment method created, categorizing into “Class0—no risk”, “Class1—low “Class2—high risk”. Various models, including Support Vector Machine (SVM), Decision Tree Classifier (DT), Random Forest (RF), XGBoost, were employed based on these indices. XGBoost demonstrated highest accuracy, achieving prediction accuracy 93%. SHAP analysis further applied explain determined that accumulation key pollutants such as cadmium (Cd) mercury (Hg) may significantly produce targeted management needs be developed features.

Language: Английский

Citations

0
Identifying spatial drivers of soil heavy metal pollution risk integrating positive matrix factorization, machine learning, and multi-scale geographically weighted regression DOI
Yujie Pan,

Anmeng Sha,

Wenjing Han

et al.

Journal of Hazardous Materials, Journal Year: 2024, Volume and Issue: 485, P. 136841 - 136841

Published: Dec. 10, 2024

Language: Английский

Citations

2
Soil health assessment of dressing and smelting slag field based on heavy metal pollution-buffer-fertility three aspects DOI
Fan Min,

Huili Liang

Journal of Hazardous Materials, Journal Year: 2024, Volume and Issue: 482, P. 136602 - 136602

Published: Nov. 20, 2024

Language: Английский

Citations

1
Speciation Characteristics and Risk Assessment of Heavy Metals in Cultivated Soil in Pingshui Village, Zhaoping County, Hezhou City, Guangxi DOI Creative Commons

Yuanxu MA,

Meilan Wen, Panfeng Liu

et al.

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(23), P. 11361 - 11361

Published: Dec. 5, 2024

In order to comprehensively understand the content, source, speciation characteristics, and risk of heavy metals in cultivated soil Pingshui Village, Zhaoping County, Hezhou City, this study conducted measurements on total amounts Cr, Ni, Cu, Zn, As, Cd, Pb, Hg 34 samples within area. Correlation analysis principal component were employed investigate their sources. An improved BCR sequential extraction procedure was utilized analyze occurrence forms eight samples. Ecological risks evaluated using geo-accumulation index (Igeo), potential ecological (RI), assessment code (RAC). The findings revealed that: (1) area exhibited varying degrees enrichment, primarily attributed anthropogenic activities. (2) There no significant difference characteristics each sampling site area, main components all residual fraction, mild acid-soluble fraction Cd Zn accounted for a relatively high proportion individual sites, which should be paid attention to. (3) Through results three methods, it is concluded that metal pollution serious, continuous corresponding prevention measures.

Language: Английский

Citations

0