Evidence map›Paper›PMID 36982005›Full record

ArticleInternational journal of environmental research and public health2023

Pollution Risk Prediction for Cadmium in Soil from an Abandoned Mine Based on Random Forest Model.

Jie Cao, Zhaohui Guo, Yongjun Lv, Man Xu, Chiyue Huang, Huizhi Liang

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Article in International journal of environmental research and public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Article
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

6 authors.

Jie CaoSchool of Metallurgy and Environment, Central South University, Changsha 410083, China.ORCID 0009-0008-9938-5743
Zhaohui GuoSchool of Metallurgy and Environment, Central South University, Changsha 410083, China.
Yongjun LvLinxiang Station of Yueyang Ecology and Environment Monitoring Center, Linxiang 414300, China.
Man XuLinxiang Station of Yueyang Ecology and Environment Monitoring Center, Linxiang 414300, China.
Chiyue HuangSchool of Metallurgy and Environment, Central South University, Changsha 410083, China.
Huizhi LiangSchool of Metallurgy and Environment, Central South University, Changsha 410083, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

It is highly uncertain as to the potential risk of toxic metal(loid)s in abandoned mine soil. In this study, random forest was used to predict the risk of cadmium pollution in the soils of an abandoned lead/zinc mine. The results showed that the random forest model is stable and precise for the pollution risk prediction of toxic metal(loid)s. The mean of Cd, Cu, Tl, Zn, and Pb was 6.02, 1.30, 1.18, 2.03, and 2.08 times higher than the soil background values of China, respectively, and their coefficients of variation were above 30%. As a case study, cadmium in the mine soil had "slope" hazard characteristics while the ore sorting area was the major source area of cadmium. The theoretical values of the random forest model are similar to the practical values for the ore sorting area, metallogenic belt, riparian zone, smelting area, hazardous waste landfill, and mining area. The potential risk of soil Cd in the ore sorting area, metallogenic belt, and riparian zone are extremely high. The tendency of pollution risk migrates significantly both from the ore sorting area to the smelting area and the mining area, and to the hazardous waste landfill. The correlation of soil pollution risk is significant between the mining area, the smelting area, and the riparian zone. The results suggested that the random forest model can effectively evaluate and predict the potential risk of the spatial heterogeneity of toxic metal(loid)s in abandoned mine soils.

Indexed as

Metals, HeavySoil PollutantsCadmiumChinaEnvironmental MonitoringEnvironmental PollutionRandom ForestRisk AssessmentSoilCadmiumMetals, HeavySoilSoil Pollutantsabandoned lead/zinc minecadmiumpotential pollution risksrandom forest modeltoxic metal(loid)s

Identifiers

PMID36982005
PMCPMC10049454

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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.