Evidence map›Paper›PMID 33797674›Full record

ArticleEnvironmental geochemistry and health2022

Comprehensive source identification and apportionment analysis of five heavy metals in soils in Wenzhou City, China.

Shuai Shao, Bifeng Hu, Yunhan Tao, Qihao You, Mingxiang Huang, Lianqing Zhou, Qiuxiao Chen, Zhou Shi

Abstract read
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Article in Environmental geochemistry and health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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  5. Soil contamination and human health: recent contributions.Environmental geochemistry and health · 2022
    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

8 authors.

Shuai ShaoKey Laboratory of Environment Remediation and Ecological Health, Ministry of Education, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, 310058, China.
Bifeng HuDepartment of Land Resource Management, School of Tourism and Urban Management, Jiangxi University of Finance and Economics, 330013, Nanchang, China.
Yunhan TaoSchool of Earth Sciences, Lanzhou University, Lanzhou, 730030, China.
Qihao YouEco-Environmental Science & Research Institute of Zhejiang Province, Hangzhou, 310012, China.
Mingxiang HuangInformation Center of Ministry of Ecology and Environment, Beijing, 100035, China.
Lianqing ZhouKey Laboratory of Environment Remediation and Ecological Health, Ministry of Education, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, 310058, China.
Qiuxiao ChenDepartment of Regional and Urban Planning, College of Civil Engineering and Architecture, Zhejiang University, Hangzhou, 310058, China. chen_qiuxiao@zju.edu.cn.
Zhou ShiKey Laboratory of Environment Remediation and Ecological Health, Ministry of Education, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, 310058, China.

Funding

National Key Research and Development Program 2018YFC1800201
6 · The paper itself

Abstract

The source identification and apportionment of heavy metals (HMs) is a vital issue for restoring contaminated soil. In this study, qualitative approaches [a finite mixture distribution model (FMDM) and raster-based principal components analysis (RB-PCA)] and a quantitative approach [positive matrix factorization (PMF)] were composed to identify and apportion the sources of five HMs (Cd, Hg, As, Pb, Cr) in Wenzhou City, China, using several crucial auxiliary variables. An initial ecological risk assessment suggested that the ecological risk level in the study area was generally considered low, with the greatest contamination contributions coming from Cd and Hg. The result of the FMDM showed that Cd and Pb fit a single log-normal distribution, Hg fit a double log-normal mixed distribution, and As and Cr presented a triple log-normal distribution. Each element was identified and separated from its natural or anthropogenic sources. A map of RB-PCA combined with an analysis of corresponding auxiliary variables suggested that the three main contribution sources in the entire study area were parental materials, industrial and agricultural mixed pollution, and mining exploration activities. Each element was discussed, using the PMF model, with regard to its quantitative contributions. Parental materials contributed to all elements (Cd, Hg, As, Pb, Cr) at 89.22%, 7.31%, 35.84%, 84.81% and 27.42%, respectively. Industrial emissions and agricultural inputs mixed pollution contributed 2.94%, 80.77%, 15.93%, 4.79%, and 25.63%, respectively. Mining activities contributed 7.84%,11.92%, 48.23%, 10.40% and 46.95%, respectively, to the five HMs. Such result could be used efficiently to generate scientific decisions and strategies in terms of decision-making on regulating HM pollution in soils.

Indexed as

Metals, HeavySoil PollutantsChinaEnvironmental MonitoringRisk AssessmentSoilMetals, HeavySoilSoil PollutantsFMDMHeavy metalsPMFRB-PCASource apportionmentSource identification

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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.