Evidence map›Paper›PMID 33738740›Full record

ArticleEnvironmental science and pollution research international2021

Metals pollution from textile production wastewater in Chinese southeastern coastal area: occurrence, source identification, and associated risk assessment.

Fang Li, Zhehui Zhong, Chunjie Gu, Chensi Shen, Chunyan Ma, Yanbiao Liu, Shanshan Yin, Chenye Xu

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Article in Environmental science and pollution research international, 2021. 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.

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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.

Fang LiCollege of Environmental Science and Engineering, Donghua University, Shanghai, 201620, China.
Zhehui ZhongCollege of Environmental Science and Engineering, Donghua University, Shanghai, 201620, China.
Chunjie GuCollege of Environmental Science and Engineering, Donghua University, Shanghai, 201620, China.
Chensi ShenCollege of Environmental Science and Engineering, Donghua University, Shanghai, 201620, China.
Chunyan MaCollege of Environmental Science and Engineering, Donghua University, Shanghai, 201620, China.
Yanbiao LiuCollege of Environmental Science and Engineering, Donghua University, Shanghai, 201620, China.
Shanshan YinMinistry of Education Key Laboratory of Environmental Remediation and Ecosystem Health, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, 310058, China.
Chenye XuCollege of Environmental Science and Engineering, Donghua University, Shanghai, 201620, China. xcy0714@dhu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The metals used in textile wet processing are of significant concern for the environment and human health. However, our understanding of metals released by the Chinese textile industry and their potential risks to ecology is limited. This work quantified the concentrations of seven metals in 199 wastewater samples from 77 textile enterprises in the southeastern coastal area of China. In the water discharged after end-of-pipe treatment, the mean concentrations of Sb, Hg, Fe, Mn, Zn, Cr, and As were 0.289, 0.009, 0.579, 0.277, 0.035, 0.016, and 0.013 mg/L, respectively. Alkali deweighting effluents, dyeing effluents, and influents into regulation tanks were observed to be "hotspots" for metal distributions. Among the seven target metals, only Sb was found to be significantly correlated with COD, NH

Indexed as

Metals, HeavyWater Pollutants, ChemicalChinaEnvironmental MonitoringHumansRisk AssessmentTextilesWastewaterMetals, HeavyWastewaterWater Pollutants, ChemicalMetalsRisk assessmentSource analysisTextile industry

Identifiers

PMID33738740

What OpenQuestion holds

Textmetadata
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.