Evidence map›Paper›PMID 32457428›Full record

ArticleScientific reports2020

Soil heavy metal contamination assessment in the Hun-Taizi River watershed, China.

Wei Zhang, Miao Liu, Chunlin Li

Abstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–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

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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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

3 authors.

Wei ZhangCollege of Land and Environment, Shenyang Agricultural University, Shenyang, 110161, China.
Miao LiuCAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, 110164, China. lium@iae.ac.cn.
Chunlin LiCAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, 110164, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Hun-Taizi River watershed includes the main part of the Liaoning central urban agglomeration, which contains six cities with an 80-year industrial history. A total of 272 samples were collected from different land use areas within the study area to estimate the concentration levels, spatial distributions and potential sources of arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), mercury (Hg), nickel (Ni), lead (Pb) and zinc (Zn) with a geographic information system (GIS), principal component analysis (PCA) and canonical correspondence analysis (CCA). Only the concentration of Cd was over the national standard value (GB 15618-2018). However, the heavy metal concentrations at 24.54%, 71.43%, 63.37%, 85.71, 70.33%, 53.11%, and 72.16% of the sampling points were higher than the local soil background values for As, Cd, Cr, Cu, Hg, Ni, Pb and Zn, respectively, which were used as standard values in this study. The maximal values of Cd (16.61 times higher than the background value) and Hg (12.18 times higher than the background value) had high concentrations, while Cd was present in the study area at higher values than in some other basins in China. Cd was the primary pollutant in the study area due to its concentration and potential ecological risk contribution. The results of the potential ecological risk index (RI) calculation showed that the overall heavy metal pollution level of the soil was considerably high. Three groups of heavy metals with similar distributions and sources were identified through PCA. The results of the CCA showed that the distribution of mines was the strongest factor affecting the distributions of Ni, As, Zn, Pb, and Cd. However, Cu was strongly influenced by the distance to the nearest river. These findings can provide scientific support for critical planning and strategies for soil pollution control and removal to support the sustainable development of the study area.

Identifiers

PMID32457428
PMCPMC7250917

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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.