Evidence map›Paper›PMID 34642865›Full record

ArticleEnvironmental monitoring and assessment2021

Revealing heavy metal correlations with water quality and tracking its latent factors by canonical correlation analysis and structural equation modeling in Dongjianghu Lake.

Dongping Liu, Huibin Yu, Huijuan Feng, Hongjie Gao, Yanzhong Zhu

Abstract read
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In one paragraph

Article in Environmental monitoring and assessment, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.4field-weighted citation impact, top 37% 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

0 citing papers in PubMed, 8 citations in OpenAlex.

No citing paper in PubMed yet.

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 at 1 institution in 1 country.

Dongping LiuChinese Research Academy of Environmental Science, Beijing, 100012, People's Republic of China.
Huibin YuChinese Research Academy of Environmental Science, Beijing, 100012, People's Republic of China. yhbybx@163.com.ORCID http://orcid.org/0000-0003-2687-9466
Huijuan FengChinese Research Academy of Environmental Science, Beijing, 100012, People's Republic of China.
Hongjie GaoChinese Research Academy of Environmental Science, Beijing, 100012, People's Republic of China. ghjxh@sina.com.
Yanzhong ZhuChinese Research Academy of Environmental Science, Beijing, 100012, People's Republic of China.
Chinese Research Academy of Environmental Sciences · CN

Funding

Environmental Protection Science and Technology Research Project of the Ningxia Hui Autonomous Region of China 2019Major Science and Technology Program for Water Pollution Control and Treatment 2018ZX07111001
6 · The paper itself

Abstract

Decreasing levels of water quality and elevated concentrations of heavy metals in freshwaters can pose global challenges for drinking water sources. Multivariate statistical techniques have been applied on data matrices of water quality and heavy metals for keen characterization of their spatio-temporal variations, exploration of latent factors, and identification of pollution sources. Non-metric multidimensional scaling (nMDS), canonical correlation analysis (CCA), and structural equation modeling (SEM) were employed to process data matrices of the water quality and heavy metals with 14 parameters measured at 13 sampling sites in Dongjianghu Lake in March, June, August, and December 2016. The sampling sites were grouped into three clusters using the nMDS, suggesting that the increasing order of the water quality levels was approximately midstream < downstream < upstream and lake. The CCA of 14 parameters proved that the Escherichia coli, COD

Indexed as

Metals, HeavyWater Pollutants, ChemicalEnvironmental MonitoringEscherichia coliGeologic SedimentsLakesLatent Class AnalysisMultivariate AnalysisWater QualityMetals, HeavyWater Pollutants, ChemicalCanonical correlation analysisHeavy metalsLatent factorStructural equation modelingWater quality

Identifiers

PMID34642865
OpenAlexW3207657241

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.