Characterization and source apportionment of heavy metal contamination in agricultural soils in the complex genesis region of western Yunnan

The genesis of heavy metal contamination in arable soils is complex, and scientifically identifying risks and precisely analyzing contamination sources are essential for safely using contaminated arable land. In this study, we systematically evaluated the pollution characteristics of Cu, Zn, As, Hg, Cd, Pb, Ni, and Cr in soil, and then applied the APCS-MLR and PMF models to jointly analyze pollution sources and their contributions. The results showed that the concentrations of the eight heavy metals were significantly higher than the background values for soils in Yunnan Province, exhibiting clear spatial heterogeneity. The overall pollution level ranged from mild to severe, with Cd and Pb being the most critical contaminants. Four major pollution sources (industrial transportation, parent material, agriculture, and mining) were identified through the dual modeling approach. The results of both models corroborated each other, and the accuracy of the analysis was significantly improved compared to using a single method. This study not only provides a scientific basis for the safe utilization of contaminated arable land in western Yunnan, an area with a complex genesis of soil contamination, but also offers a generalized framework for source analysis in areas affected by geological-anthropogenic composite pollution.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2025-09-01
DOI
https://doi.org/10.1038/s41598-025-16520-5
Citations
8
Primary Topic
Heavy metals in environment
Type
article
Field-Weighted Citation Impact
4.03

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Characterization and source apportionment of heavy metal contamination in agricultural soils in the complex genesis region of western Yunnan

Sheng Wang, Wen Chen, Naiming Zhang, Xiaoyan Shang et al.
8 citations
Scientific Reports
Heavy metals in environment
4.03
article

Characterization and source apportionment of heavy metal contamination in agricultural soils in the complex genesis region of western Yunnan

Sheng Wang, Wen Chen, Naiming Zhang, Xiaoyan Shang, Bao Li, Jianyang He, Yingmei Li, Xiangmei Zhao, Hongyin Zhou, Lijuan Wang
article en
8 citations

Abstract

The genesis of heavy metal contamination in arable soils is complex, and scientifically identifying risks and precisely analyzing contamination sources are essential for safely using contaminated arable land. In this study, we systematically evaluated the pollution characteristics of Cu, Zn, As, Hg, Cd, Pb, Ni, and Cr in soil, and then applied the APCS-MLR and PMF models to jointly analyze pollution sources and their contributions. The results showed that the concentrations of the eight heavy metals were significantly higher than the background values for soils in Yunnan Province, exhibiting clear spatial heterogeneity. The overall pollution level ranged from mild to severe, with Cd and Pb being the most critical contaminants. Four major pollution sources (industrial transportation, parent material, agriculture, and mining) were identified through the dual modeling approach. The results of both models corroborated each other, and the accuracy of the analysis was significantly improved compared to using a single method. This study not only provides a scientific basis for the safe utilization of contaminated arable land in western Yunnan, an area with a complex genesis of soil contamination, but also offers a generalized framework for source analysis in areas affected by geological-anthropogenic composite pollution.

Scientific ReportsVol. 15(1)
Yunnan Agricultural University (CN), Zhaotong University (CN), Puer University (CN), Chuxiong Normal University (CN)
Yunnan Provincial Department of Education
Openalex Percentile: Top 6%
Heavy metals in environment
4.03
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.