Evidence map›Paper›PMID 35139087›Full record

ArticlePloS one2022

Assessment of heavy metal pollution in surface sediments of the Chishui River Basin, China.

Fanxi Li, Xia Yu, Jiemei Lv, Qixin Wu, Yanling An

Abstract read
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

4 citing papers in PubMed.

  1. Article
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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

5 authors.

Fanxi LiKey Laboratory of Karst Environment and Geohazard Prevention, Guizhou University, Guiyang, Guizhou Province, China.ORCID 0000-0002-4833-8831
Xia YuThe College of Resources and Environmental Engineering, Guizhou Institute of Technology, Guiyang, Guizhou Province, China.
Jiemei LvThe College of Resources and Environmental Engineering, Guizhou Institute of Technology, Guiyang, Guizhou Province, China.
Qixin WuThe College of Resources and Environmental Engineering, Guizhou University, Guiyang, Guizhou Province, China.
Yanling AnThe College of Resources and Environmental Engineering, Guizhou Institute of Technology, Guiyang, Guizhou Province, China.ORCID 0000-0003-2351-615X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accumulated heavy metals in surface sediments are released into the aquatic environment, causing secondary contamination of the hydrosphere, and increasing the risks to human health. To evaluate the pollution characteristics of heavy metals in the sediments of the Chishui River Basin, in the present study, the concentrations of five heavy metals in surface sediments of the Chishui River Basin in China were investigated using the geo-accumulation index, pollution load index, and potential ecological risk indexes. These indexes evaluated the degree of contamination and the influence of human activities on heavy metal levels in the basin. Cu, Zn, Cd, Hg, and As were found at concentrations of 5.12-120.40, 36.01-219.31, 0.03-1.28, 0.01-1.18, and 1.56-11.59 mg kg-1, respectively, with mean values of 37.43, 91.92, 0.25, 0.07, and 5.16 mg kg-1, respectively, in the order Zn > Cu > As > Cd > Hg. The contamination indices revealed Hg as the principal pollutant based on the spatial distribution, while Pearson's correlation coefficients suggested that Cu, Zn, and As originated from a similar source. Hg had a different source from the other metals, whereas Cd originated from a different source compared with that of Zn, As, and Hg. This paper showed a Hg and Cd contamination in the Chishui River Basin.

Indexed as

Environmental MonitoringGeologic SedimentsMetals, HeavyRiversWater Pollutants, ChemicalChinaHumansMetals, HeavyWater Pollutants, Chemical

Identifiers

PMID35139087
PMCPMC8827479

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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.