Evidence map›Paper›PMID 34395088›Full record

ArticlePeerJ2021

Distribution, source, water quality and health risk assessment of dissolved heavy metals in major rivers in Wuhan, China.

Xingyong Zhang, Qixin Wu, Shilin Gao, Zhuhong Wang, Shouyang He

Abstract read
In one paragraph

Article in PeerJ, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

5 authors.

Xingyong ZhangKey Laboratory of Karst Geological Resources and Environment, Ministry of Education, Guizhou University, Guiyang, Guizhou, China.
Qixin WuKey Laboratory of Karst Geological Resources and Environment, Ministry of Education, Guizhou University, Guiyang, Guizhou, China.
Shilin GaoKey Laboratory of Karst Geological Resources and Environment, Ministry of Education, Guizhou University, Guiyang, Guizhou, China.ORCID 0000-0002-6878-1451
Zhuhong WangSchool of Public Health, Key Laboratory of Environmental Pollution and Disease Monitoring of Ministry of Education, Guizhou Medical University, Guiyang, Guizhou, China.
Shouyang HeKey Laboratory of Karst Geological Resources and Environment, Ministry of Education, Guizhou University, Guiyang, Guizhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Heavy metals are released into the water system through various natural processes and anthropogenic activities, thus indirectly or directly endangering human health. The distribution, source, water quality and health risk assessment of dissolved heavy metals (V, Mn, Fe, Co, Ni, Zn, As, Mo, Sb) in major rivers in Wuhan were analyzed by correlation analysis (CA), principal component analysis (PCA), heavy metal pollution index (HPI), hazard index (HI) and carcinogenic risk (CR). The results showed that the spatial variability of heavy metal contents was pronounced. PCA and CA results indicated that natural sources controlled Mn, Fe, Co, Ni and Mo, and industrial emissions were the dominant factor for V, Zn and Sb, while As was mainly from the mixed input of urban and agricultural activities. According to the heavy metal pollution index (HPI, ranging from 23.74 to 184.0) analysis, it should be noted that As and Sb contribute most of the HPI values. The health risk assessment using HI and CR showed that V and Sb might have a potential non-carcinogenic risk and As might have a potential carcinogenic risk to adults and children in the study area (CR value exceeded target risk 10

Indexed as

Health risk assessmentHeavy metal pollution indexHeavy metalsSourceWuhan

Identifiers

PMID34395088
PMCPMC8323599

What OpenQuestion holds

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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.