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Risk sources quantitative identification of heavy metals in coal mining hinterland river sediments, Northern China
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  • Published: 03 February 2026

Risk sources quantitative identification of heavy metals in coal mining hinterland river sediments, Northern China

  • Yaning Zhang1,2,
  • Xinlin He1,
  • Ying Dong1,2,
  • Xijun Wu2,
  • Jing Liu2,
  • Fuchu Zhang1,
  • Yi He2 &
  • …
  • Jian Zhao3 

Scientific Reports , Article number:  (2026) Cite this article

We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Subjects

  • Ecology
  • Environmental sciences
  • Environmental social sciences
  • Risk factors

Abstract

The accumulation of heavy metals (HMs) from coal resource exploitation and coal-related industries poses serious ecological and health risks in the hinterland river sediments of Shenfu coal field in Northern China. Using data from 59 samples, the geo-accumulation index and ecological health risks of HMs were assessed probabilistically using Monte Carlo Simulation. Two coupling models were constructed in this study, integrating both the Positive Matrix Factorization and ecological health risk models to identify the risk levels of pollution sources in the Kuye River. The risk of HMs during the wet season was explored due to the lower concentrations and a broader range of pollution sources compared to the dry season. The Igeo value of Hg was greater than 1 in 69% of the samples, suggesting moderately contaminated sediments. According to the source-oriented coupling models (PMF-RI/HRA), coal-mining sources contributed to the overall ecological risk by 48.79%, primarily due to Hg (98.50%). Industrial sources (51.48%) were the largest contributors to carcinogenic risk, with Ni corresponding to the target HM. This indicated that different HMs originating from distinct pollution sources were responsible for ecological or carcinogenic health risks. The probabilistic health risk evaluation results indicated that children faced higher risks than adults, with over 94.07% of carcinogenic risks exceeding thresholds. Traffic sources followed, contributing 34.41% to ecological and 41.09% to carcinogenic risks. The results highlight the priority sources and target HMs based on specific sources in the mixed ‘mining-industrial-traffic’ areas, providing valuable insights for environmental protection and the development of risk prevention strategies in a typical energy industry area.

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Data availability

The data is available on request from the first corresponding author.

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Funding

This study was supported by the National Natural Science Foundation of China (No. 52169006), Key Research and Development Projects of Shaanxi Province of China (No. 2024SF-YBXM-552), Education Department of Shaanxi Province of China (No. 22JS045), Yulin Science and Technology Bureau Project (No. 2025-CXY-087, 2025-CXY-090), and Yulin University Scientific Research Project (No. 2RCYPJB01012, 2021JJB13, 2022TZRC02).

Author information

Authors and Affiliations

  1. College of Water Conservancy & Architectural Engineering, Shihezi University, Shihezi, 832003, China

    Yaning Zhang, Xinlin He, Ying Dong & Fuchu Zhang

  2. School of Civil Engineering, Yulin University, Yulin, 719000, China

    Yaning Zhang, Ying Dong, Xijun Wu, Jing Liu & Yi He

  3. State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China

    Jian Zhao

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  1. Yaning Zhang
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Contributions

Yaning Zhang: Conceptualization, Writing-original draft, Investigation, Methodology, Writing–review & editing. Xinlin He: Conceptualization, Methodology, Supervision, Writing-review & editing. Ying Dong: Data curation, Investigation, Software, Funding acquisition. Xijun Wu: Conceptualization, Funding acquisition, Writing–review & editing, Supervision, Methodology. Jing Liu: Software, Formal analysis. Fuchu Zhang: Formal analysis, Software. Yi He: Data curation, Software. Jian Zhao: Methodology, Writing–review & editing.

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Correspondence to Xinlin He or Xijun Wu.

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Zhang, Y., He, X., Dong, Y. et al. Risk sources quantitative identification of heavy metals in coal mining hinterland river sediments, Northern China. Sci Rep (2026). https://doi.org/10.1038/s41598-026-37889-x

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  • Received: 29 September 2025

  • Accepted: 27 January 2026

  • Published: 03 February 2026

  • DOI: https://doi.org/10.1038/s41598-026-37889-x

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Keywords

  • Coal field hinterland river
  • Heavy metal pollution
  • Coupling model
  • Priority pollution sources
  • Monte Carlo simulation
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