Evidence map›Paper›PMID 33219420›Full record

ArticleEnvironmental monitoring and assessment2020

Contamination evaluation and source identification of heavy metals in sediments near outlet of Shekou industrial district of Shenzhen City.

Limin Wang, Yang Xu, Haibo Wen, Min Tang, Guangyao Zhao, Qingguo Han, Xu Xu, Ming Ying, Zhangli Hu, Hong Xu

Abstract read
PubMed Publisher
In one paragraph

Article in Environmental monitoring and assessment, 2020. 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
0.5field-weighted citation impact, top 42% 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, 12 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

10 authors at 1 institution in 1 country.

Limin WangShenzhen Key Laboratory of Marine Bioresource and Eco-environmental Science, Shenzhen Engineering Laboratory for Marine Algal Biotechnology, Guangdong Provincial Key Laboratory for Plant Epigenetics, College of Life Sciences and Oceanography, Shenzhen University, Shenzhen, 518060, China.
Yang XuShenzhen Key Laboratory of Marine Bioresource and Eco-environmental Science, Shenzhen Engineering Laboratory for Marine Algal Biotechnology, Guangdong Provincial Key Laboratory for Plant Epigenetics, College of Life Sciences and Oceanography, Shenzhen University, Shenzhen, 518060, China.
Haibo WenShenzhen Key Laboratory of Marine Bioresource and Eco-environmental Science, Shenzhen Engineering Laboratory for Marine Algal Biotechnology, Guangdong Provincial Key Laboratory for Plant Epigenetics, College of Life Sciences and Oceanography, Shenzhen University, Shenzhen, 518060, China.
Min TangShenzhen Key Laboratory of Marine Bioresource and Eco-environmental Science, Shenzhen Engineering Laboratory for Marine Algal Biotechnology, Guangdong Provincial Key Laboratory for Plant Epigenetics, College of Life Sciences and Oceanography, Shenzhen University, Shenzhen, 518060, China.
Guangyao ZhaoShenzhen Key Laboratory of Marine Bioresource and Eco-environmental Science, Shenzhen Engineering Laboratory for Marine Algal Biotechnology, Guangdong Provincial Key Laboratory for Plant Epigenetics, College of Life Sciences and Oceanography, Shenzhen University, Shenzhen, 518060, China.
Qingguo HanShenzhen Key Laboratory of Marine Bioresource and Eco-environmental Science, Shenzhen Engineering Laboratory for Marine Algal Biotechnology, Guangdong Provincial Key Laboratory for Plant Epigenetics, College of Life Sciences and Oceanography, Shenzhen University, Shenzhen, 518060, China.
Xu XuShenzhen Key Laboratory of Marine Bioresource and Eco-environmental Science, Shenzhen Engineering Laboratory for Marine Algal Biotechnology, Guangdong Provincial Key Laboratory for Plant Epigenetics, College of Life Sciences and Oceanography, Shenzhen University, Shenzhen, 518060, China.
Ming YingShenzhen Key Laboratory of Marine Bioresource and Eco-environmental Science, Shenzhen Engineering Laboratory for Marine Algal Biotechnology, Guangdong Provincial Key Laboratory for Plant Epigenetics, College of Life Sciences and Oceanography, Shenzhen University, Shenzhen, 518060, China.
Zhangli HuShenzhen Key Laboratory of Marine Bioresource and Eco-environmental Science, Shenzhen Engineering Laboratory for Marine Algal Biotechnology, Guangdong Provincial Key Laboratory for Plant Epigenetics, College of Life Sciences and Oceanography, Shenzhen University, Shenzhen, 518060, China.
Hong XuShenzhen Key Laboratory of Marine Bioresource and Eco-environmental Science, Shenzhen Engineering Laboratory for Marine Algal Biotechnology, Guangdong Provincial Key Laboratory for Plant Epigenetics, College of Life Sciences and Oceanography, Shenzhen University, Shenzhen, 518060, China. xuhong@szu.edu.cn.ORCID http://orcid.org/0000-0002-4730-9625
Shenzhen University · CN

Funding

National Key Project for Synthetic Biology SQ2018YFA090029National Key R&D Program of China 2018YFD0901106National Natural Science Foundation of China 31540012National Natural Science Foundation of China 31871734National Natural Science Foundation of China 81501213Natural Science Foundation of Guangdong Province 2016A030313051Natural Science Foundation of Guangdong Province 2018A0303130054Science and Technology Planning Project of Guangdong Province 2020B121202014Shenzhen Science and Technology Innovation Commission JCYJ20170818143107733Shenzhen Science and Technology Innovation Commission JCYJ20180305124211995Shenzhen Science and Technology Innovation Commission JCYJ20180305125619343Shenzhen Science and Technology Innovation Commission JCYJ20180507182405562Shenzhen Science and Technology Innovation Commission JSGG20160229120821300
6 · The paper itself

Abstract

Sediment samples in this study were taken from five typical sites near the outlet of Shekou industrial district of Shenzhen City, China. The concentrations of seven elements including Cr, Cu, Cd, Pb, Hg, Zn, and As were determined respectively by atomic absorption spectrometry or atomic fluorescence spectrometry. The pollution degrees of the seven elements were assessed with the contamination factor and potential ecological risk index respectively, and their different sources were identified using multivariate statistical methods. The calculated contamination factors of these elements indicated that the sediments were at least moderately polluted by all the surveyed elements except As. The values of potential ecological risk indexes obtained decreased as the following order: Cd > Hg > Cu > As > Pb > Zn > Cr, and suggested that Cd and Hg were respectively at high and considerable environmental health risks. In addition, multivariate statistical analyses indicated that Cd, Hg, Cu, and Zn were most likely from the waste of electroplating, metal, and battery industries at Shekou industrial district, while Pb and As originated from both natural processes and anthropogenic activities along the bank of Pear River such as coal transportation and combustion, glass manufacturing, and painting, and Cr came mostly from Cr-related industries especially leather tanning within Shenzhen City. This study provided useful reference information about heavy metal contamination in the sediments in the estuarine and coastal areas with rapid urbanization and industrialization, and should be very helpful for the local governments to make relevant policies and strategies of heavy metal contamination control and management in developing countries.

Indexed as

Metals, HeavyWater Pollutants, ChemicalChinaCitiesEnvironmental MonitoringGeologic SedimentsRisk AssessmentRiversMetals, HeavyWater Pollutants, ChemicalHeavy metalSedimentsSource identificationSpatial distributionStatistical analysis

Identifiers

PMID33219420
OpenAlexW3099014066

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.