Evidence map›Paper›PMID 37888679›Full record

ReviewToxics2023

Water Quality Degradation Due to Heavy Metal Contamination: Health Impacts and Eco-Friendly Approaches for Heavy Metal Remediation.

Peng Zhang, Mingjie Yang, Jingjing Lan, Yan Huang, Jinxi Zhang, Shuangshuang Huang, Yashi Yang, Junjie Ru

Open access · goldAbstract readReview
In one paragraph

Review in Toxics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
51citing papers in PubMed, 2 pooled it
19.1field-weighted citation impact, top 1% of its field
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

51 citing papers in PubMed, 2 syntheses or guidelines pooled it, 263 citations in OpenAlex.

  1. Pooled it
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  11. Finite-Element-Informed Pyramid Neural Network With Draco Lizard Optimizer for Accurate and Efficient Water Contamination Classification.Water environment research : a research publication of the Water Environment Federation · 2026
    Article
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  13. ACS applied polymer materials · 2026
    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

8 authors at 2 institutions in 1 country.

Peng ZhangSchool of Hydraulic Engineering, Wanjiang University of Technology, Ma'anshan 243031, China.
Mingjie YangSchool of Hydraulic Engineering, Wanjiang University of Technology, Ma'anshan 243031, China.
Jingjing LanSchool of Hydraulic Engineering, Wanjiang University of Technology, Ma'anshan 243031, China.
Yan HuangSchool of Hydraulic Engineering, Wanjiang University of Technology, Ma'anshan 243031, China.
Jinxi ZhangSchool of Hydraulic Engineering, Wanjiang University of Technology, Ma'anshan 243031, China.
Shuangshuang HuangSchool of Hydraulic Engineering, Wanjiang University of Technology, Ma'anshan 243031, China.
Yashi YangSchool of Hydraulic Engineering, Wanjiang University of Technology, Ma'anshan 243031, China.
Junjie RuSchool of Hydraulic Engineering, Wanjiang University of Technology, Ma'anshan 243031, China.
Anhui University of Technology · CNHohai University · CN

Funding

Maanshan Engineering Technology Research Center for Water Resources Efficient Utilization in Hilly Region),Intelligent algorithm optimizes model validation of neural network water quality prediction in hilly areas CW2019025
6 · The paper itself

Abstract

Water quality depends on its physicochemical and biological parameters. Changes in parameters such as pH, temperature, and essential and non-essential trace metals in water can render it unfit for human use. Moreover, the characteristics of the local environment, geological processes, geochemistry, and hydrological properties of water sources also affect water quality. Generally, groundwater is utilized for drinking purposes all over the globe. The surface is also utilized for human use and industrial purposes. There are several natural and anthropogenic activities responsible for the heavy metal contamination of water. Industrial sources, including coal washery, steel industry, food processing industry, plastic processing, metallic work, leather tanning, etc., are responsible for heavy metal contamination in water. Domestic and agricultural waste is also responsible for hazardous metallic contamination in water. Contaminated water with heavy metal ions like Cr (VI), Cd (II), Pb (II), As (V and III), Hg (II), Ni (II), and Cu (II) is responsible for several health issues in humans, like liver failure, kidney damage, gastric and skin cancer, mental disorders and harmful effects on the reproductive system. Hence, the evaluation of heavy metal contamination in water and its removal is needed. There are several physicochemical methods that are available for the removal of heavy metals from water, but these methods are expensive and generate large amounts of secondary pollutants. Biological methods are considered cost-effective and eco-friendly methods for the remediation of metallic contaminants from water. In this review, we focused on water contamination with toxic heavy metals and their toxicity and eco-friendly bioremediation approaches.

Indexed as

health impacts of heavy metalsheavy metalsheavy metals removalwater contamination

Identifiers

PMID37888679
PMCPMC10611083
OpenAlexW4387265043

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.