Evidence map›Paper›PMID 42026544›Full record

ArticleBMC public health2026

Integrated assessment and forecasting of heavy metal contamination in soils affected by Pb-Zn mining in Guizhou, China.

Tianzhu Shi, Jingyi Huang, Shihuang Chen, Huawei Chen, Huajie Xu, Ju Guo, Xiangui Wang, Qiong Li, Qulai Tang, Feng Xie and 1 more

Abstract read
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Article in BMC public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Tianzhu ShiSchool of Brewing Engineering, Moutai Institute, Renhuai, GuiZhou, 564500, China.
Jingyi HuangSchool of Brewing Engineering, Moutai Institute, Renhuai, GuiZhou, 564500, China.
Shihuang ChenSchool of Brewing Engineering, Moutai Institute, Renhuai, GuiZhou, 564500, China.
Huawei ChenSchool of Brewing Engineering, Moutai Institute, Renhuai, GuiZhou, 564500, China.
Huajie XuSchool of Brewing Engineering, Moutai Institute, Renhuai, GuiZhou, 564500, China. xuhuajie@mtxy.edu.cn.
Ju GuoSchool of Brewing Engineering, Moutai Institute, Renhuai, GuiZhou, 564500, China. guoju@mtxy.edu.cn.
Xiangui WangSchool of Brewing Engineering, Moutai Institute, Renhuai, GuiZhou, 564500, China.
Qiong LiSchool of Brewing Engineering, Moutai Institute, Renhuai, GuiZhou, 564500, China.
Qulai TangSchool of Brewing Engineering, Moutai Institute, Renhuai, GuiZhou, 564500, China.
Feng XieSchool of Food Engineering, Moutai Institute, Renhuai, GuiZhou, 564500, China.
Guanglin SongGuizhou Academy of Testing and Analysis, Guiyang, Guizhou, 550002, China.

Funding

A Project on Characteristic Key Laboratory of Guizhou Ordinary Colleges and Universities by Department of Education of Guizhou Province grant No: Qian Jiao He KY Zi [2018] 003Guizhou Engineering Research Center for Comprehensive Utilization of Distillers' Grains;Youth Guidance Project of Guizhou Province Basic Research Program (Natural Sciences) in 2024 Qiankehe Jichu [2024] Qingnian 203Guizhou Province Distillers Grain and Agricultural Waste Resource Utilization Engineering Research Center Grant No. 04500052Modern Baijiu Brewing Technology Engineering Research Center of Guizhou Universities Qianjiaoji (2023) No. 028Moutai institute Joint Science and Technology Research and Development Project ZunShiJiaoHe HZ Zi (2021) 322Research Foundation for Scientific Scholars of Moutai Institute Grant No. mygccrc[2022]007, mygccrc[2022]097, mygccrc[2022]022, mygccrc[2022]020, mygccrc[2022]056, mygccrc[2022]045 and mygccrc[2022]031Zunyi Outstanding Youth Science and technology innovation talents training project ZunYouQingKe (2021) 7Zunyi Science and Technology Bureau of Guizhou Province and Moutai Institute Joint Science and Technology Cooperation Fund Project Zunyi Ke (2023) No. 114
6 · The paper itself

Abstract

Heavy metal contamination in soils surrounding Pb–Zn mining areas poses persistent ecological and public health risks in Guizhou Province, China. However, ecological risk transfer among ecosystem compartments and the future decline in soil environmental capacity remain poorly understood. This study investigated heavy metals in surface soil (0–20 cm) and subsoil (20–60 cm) around a Pb–Zn mining area in Shuicheng District, Liupanshui City, by integrating the geo-accumulation index (Igeo), pollution load index (PLI), potential ecological risk index (PERI), network environ analysis (NEA), Monte Carlo health-risk assessment, and dynamic environmental-capacity forecasting. This framework characterized contamination levels and human-health risks, traced the redistribution of ecological risk among trophic components, and evaluated the future decline of residual soil buffering capacity under continued pollution pressure. The results revealed severe contamination by Pb, Cd, and Zn in both surface and subsurface soils, with Pb showing the highest pollution intensity. PERI classified most sampling sites as moderate to high ecological risk. The NEA model further showed that Pb, Zn, and Cd generated the highest ecological pressures across trophic levels and that soil microorganisms were the major ecological risk sink, accounting for 66.4% of integrated ecosystem risk, followed by vegetation, herbivores, and carnivores. Health risk assessment indicated markedly higher non-carcinogenic and carcinogenic risks for children than adults, primarily due to Pb and As exposure. Dynamic capacity forecasting suggested a rapid reduction in the residual soil environmental capacity over the next 10 years, especially for Hg. These findings support remediation planning, land-use management, and exposure reduction in mining-affected areas.

Indexed as

LeadMetals, HeavyMiningSoil PollutantsZincChinaEnvironmental MonitoringForecastingHumansRisk AssessmentLeadMetals, HeavySoil PollutantsZincEcological riskGuizhou ProvinceHealth risk assessmentHeavy metalsLead–zinc miningSoil pollution

Identifiers

PMID42026544
PMCPMC13245013

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LicenceCC BY-NC-ND
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Registered trials

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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.