Evidence map›Paper›PMID 38227205›Full record

ArticleEnvironmental geochemistry and health2024

Quantitative risk analysis of sediment heavy metals using the positive matrix factorization-based ecological risk index method: a case of the Kuye River, China.

Yaning Zhang, Xijun Wu, Ying Dong, Jing Liu

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Article in Environmental geochemistry and health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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3 · Its place in the literature

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2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Yaning ZhangSchool of Civil Engineering, Yulin University, Yulin, 719000, China.
Xijun WuSchool of Civil Engineering, Yulin University, Yulin, 719000, China. wxj0826@163.com.
Ying DongSchool of Civil Engineering, Yulin University, Yulin, 719000, China.
Jing LiuSchool of Civil Engineering, Yulin University, Yulin, 719000, China.

Funding

National Natural Science Foundation of China 51969031National Natural Science Foundation of China 52169006the Open Fund of State Key Laboratory of Eco-hydraulics in Northwest Arid Region of China 2019KFKT-13the Shaanxi Key Scientific Research Plan of Education Department 22JS045the Shaanxi Science and Technology Innovation Team 2022TD-08the Yulin 'Scientists + Engineers' Team Project YLKG-2022-10Yulin University Scientific Research Project 1517-2021JJJB13Yulin University Scientific Research Project 1517-2021SKJJB19
6 · The paper itself

Abstract

Identifying the sources of heavy metals (HMs) in river sediments is crucial to effectively mitigate sediment HM pollution and control its associated ecological risks in coal-mining areas. In this study, ecological risks resulting from different pollution sources were evaluated using an integrated method combining the positive matrix factorization (PMF) and the potential ecological risk index (RI) model. A total of 59 sediment samples were collected from the Kuye River and analyzed for eight HMs (Zn, Cr, Ni, Cu, Pb, As, Cd, and Hg). The obtained results showed that the sediment HM contents were higher than the corresponding soil background values in Shaanxi Province. The average sediment Hg content was 3.42 times higher than the corresponding background value. The PMF results indicated that HMs in the sediments were mainly derived from industrial, traffic, agricultural, and coal-mining sources. The RI values ranged from 26.15 to 483.70. Hg was the major contributor (75%) to the ecological risk in the vicinity of the Yanjiata Industrial Park. According to the PMF-based RI model, coal-mining activities exhibited the strongest impact on the river ecosystem (48.79%), followed, respectively, by traffic (34.41%), industrial (12.70%), and agricultural (4.10%) activities. These results indicated that the major anthropogenic sources contributing to the HM contents in the sediments are not necessarily those posing the greatest ecological risks. The proposed integrated approach in this study was useful in evaluating the ecological risks associated with different anthropogenic sources in the Kuye River, providing valuable suggestions for reducing sediment HM pollution and effectively protecting river ecosystems.

Indexed as

MercuryMetals, HeavyChinaCoalEcosystemRiversCoalMercuryMetals, HeavyCoal-miningPMF-based RI modelPotential ecological risksSediment pollutionSource apportionment

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.