Evidence map›Paper›PMID 31090008›Full record

ArticleEnvironmental science and pollution research international2019

Identifying effects of pipe material, hydraulic condition, and water composition on elemental accumulation in pipe corrosion scales.

Manjie Li, Zhaowei Liu, Yongcan Chen, Mingdong Zhang

Abstract read
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Article in Environmental science and pollution research international, 2019. 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

4 authors.

Manjie LiState Key Laboratory Hydroscience and Engineering, Tsinghua University, Beijing, 100084, China.
Zhaowei LiuState Key Laboratory Hydroscience and Engineering, Tsinghua University, Beijing, 100084, China. liuzhw@tsinghua.edu.cn.ORCID http://orcid.org/0000-0003-4536-2091
Yongcan ChenState Key Laboratory Hydroscience and Engineering, Tsinghua University, Beijing, 100084, China.
Mingdong ZhangSchool of Software, Tsinghua University, Beijing, 100084, China.

Funding

National Key Research and Development Program of China 2016YFC0502204National Natural Science Foundation of China 51579130, 91647116
6 · The paper itself

Abstract

Identification of the accumulation mechanism of major elements on pipe surface is essential to investigate the development of corrosion scales and co-occurrence of trace inorganic contaminants. In this study, corrosion scale samples were collected from old, corroded iron pipes made of different materials and exposed to different water qualities and operation conditions. Elemental composition of these scales was determined by energy dispersive X-ray spectroscopy (EDS). Cumulative occurrence analysis, Q-style hierarchical cluster analysis (CA), and principal component analysis (PCA) were conducted to ascertain major elements typical for corrosion scales and to estimate the dominant influencing factor to each elemental constituent. The major elements in the examined scales are Fe, C, Zn, Si, Ca, Al, and S in the descending prevalence. Their occurrences are influenced by an interactive effect. Pipe material imposes a significant effect on the accumulation of Fe, Zn, and Ca in corrosion scales; water composition can account for the presence of Si, Al, and S in this study; hydraulic condition is identified as the primary factor influencing the occurrence of C and Ca. Q-style CA and PCA are verified practicable for data interpretation and identification of dominant factors influencing scale characteristics.

Indexed as

CorrosionWater SupplyIronWaterWater Pollutants, ChemicalIronWaterWater Pollutants, ChemicalCluster analysisCorrosion scalesElemental accumulationHydraulic conditionPipe materialPrincipal component analysisWater composition

Identifiers

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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.