Enrichment and sources of trace metals in roadside soils in Shanghai, China: A case study of two urban/rural roads

Yan, Geng; Mao, Lingchen; Liu, Shuoxun; Yu, Mengxiao; Ye, Hua; Huang, Tianshu; Li, Feipeng; Chen, Ling

doi:10.1016/j.scitotenv.2018.02.340

Cited by 111 publications

(45 citation statements)

References 67 publications

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“…The maximum EF values of Zn and Sb in Karachi and Zn, Sb, Cr in Shikarpur were higher than 40, which illustrated the relation of metals with anthropogenic sources. The high accumulations of Cu, Pb, Zn, Cd, Ni, Sb, and Cr in the road dust of studied areas of both cities showed their origin from traffic emissions [ 72 ]. The pollution level of Sb in the studied areas of both cities was found significantly higher than other metals, this result connects the elevated concentration of Sb with artificial sources.…”

Section: Resultsmentioning

confidence: 99%

Health Risk Assessment of Heavy Metals Accumulated on PM2.5 Fractioned Road Dust from Two Cities of Pakistan

Moryani

Kong

et al. 2020

IJERPH

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The aim of this study is to identify and investigate levels of toxic heavy metals in PM2.5 fractioned road dust to better understand the associated inhalation risk and potential health impacts. To achieve this aim, concentrations of seven traffic generated heavy metals (Cu, Pb, Zn, Cd, Ni, Sb, and Cr) were determined in the PM2.5 fraction of road dust samples from four different locations (offices, residential, hospital, and school) in two cities (Karachi and Shikarpur) of Pakistan using ICP-MS. The average concentration values of heavy metals in Karachi were as follows: 332.9 mg/kg Cu, 426.6 mg/kg Pb, 4254.4 mg/kg Zn, 62.3 mg/kg Cd, 389.7 mg/kg Ni, 70.4 mg/kg Sb, 148.1 mg/kg Cr, whereas the average concentration values of heavy metals in Shikarpur were 245.8 mg/kg Cu, 538.4 mg/kg Pb, 8351.0 mg/kg Zn, 57.6 mg/kg Cd, 131.7 mg/kg Ni, 314.5 mg/kg Sb, 346.6 mg/kg Cr. The pollution level was assessed through two pollution indices enrichment factor (EF) and geoaccumulation index (Igeo). These indices showed moderate to extreme level pollution in studied areas of both cities. The health risk assessment through inhalation contact was conducted according to the United States Environmental Protection Agency’s (USEPA) model for children and adults. Both non-cancerous and cancerous risks were characterised in the road dust samples for each location. As yet, there is not a single study on the concentrations of heavy metals in PM2.5 fractions of road dust in Karachi and Shikarpur, findings of this research will facilitate researchers for further investigations in current field.

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Section: Resultsmentioning

confidence: 99%

Health Risk Assessment of Heavy Metals Accumulated on PM2.5 Fractioned Road Dust from Two Cities of Pakistan

Moryani

Kong

et al. 2020

IJERPH

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“…All the analyzed HMs such as Cu, Cr, Co and Pb are positively correlated with each other. HMs indicating high correlations may attribute to a similar type of sources [55].…”

Section: Soil Physiochemical Properties and Heavy Metalsmentioning

confidence: 98%

Assessment of pollution in roadside soils by using multivariate statistical techniques and contamination indices

Kumar

Sharma

et al. 2019

SN Appl. Sci.

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Pollution of roadside soils by heavy metals (HMs) presents serious concern throughout the world and, specifically, in India, due to the increasing traffic and anthropogenic activities. Understanding this problematic, policymakers and land managers will be able to design correct and sustainable land plans to avoid human health problems. The current study was conducted in order to determine the sources and levels of contamination by physiochemical parameters and HMs (Cu, Co, Cr and Pb) in roadside soils of Jalandhar, Punjab. A total of 90 samples were collected in triplicates from different sites and analysed for physiochemical and heavy metals. The average values of Cu, Co, Cr and Pb were found less than the permissible limits of Indian soils. Pearson's correlation analysis indicated that HMs are positively correlated with each other, indicating a similar source of their origin. Further results of correlation analysis were supported by cluster analysis and Principal component analysis also indicated that HMs have the same source of origin mainly anthropogenic (agricultural and transportation activities), while soil properties have the same source of origin. The results of contamination factor, geo-accumulation index, potential contamination index, pollution index and ecological risk index showed that soils are moderately contaminated by HMs. In the future, further research would be needed to understand which specific factor (agriculture, industry and urban residues) could be considered as the main driving factor. We conclude that this study can provide the baseline data for policymakers and stakeholders to help the protection of soil ecosystem.

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“…The EF coefficient is used to estimate the enrichment of the surface layer of sediments with HMs. EF allows to eliminate the potential impact of differences in grain size sediments of the surface layer and sediments of a geochemical background (Buat-Menard and Chesselet 1979;Hakanson 1980;Håkanson 1984;Kowalska et al 2018;Likuku et al 2013;Weissmannová and Pavlovský 2017;Yan et al 2018). EF was calculated according to formula (1):…”

Section: Enrichment Factormentioning

confidence: 99%

“…HM pollution of soils and sediments in relation to mining and other industrial sites is often reported (Weissmannová et al 2015;Guo et al 2005;Hansen et al 2012;Ji et al 2018;Jinmei and Xueping 2014;Nazeer et al 2016;Qing et al 2015;Wu et al 2017;Yan et al 2018). The problem with hazardous elements occurs in both high and low income countries (Kanda et al 2018).…”

Section: Introductionmentioning

confidence: 99%

“…The measures of site contamination with HMs usually incorporate a variety of pollution or enrichment indices-just to mention a few of them: pollution load index (PLI) (Buat-Menard and Chesselet 1979;Hakanson 1980;Håkanson 1984;Kowalska et al 2018;Likuku et al 2013;Weissmannová and Pavlovský 2017), enrichment factor (EF) (Buat- Menard and Chesselet 1979;Hakanson 1980;Håkanson 1984;Kowalska et al 2018;Likuku et al 2013;Weissmannová and Pavlovský 2017;Yan et al 2018), anthropogenic factor (AF) (Hakanson 1980;Kowalska et al 2018;Likuku et al 2013;Weissmannová and Pavlovský 2017), and modified contamination degree (mCd) (Abrahim and Parker 2008;Likuku et al 2013). The assessment of HM distribution in sediments and contamination levels provides the basis for consideration of sediments remediation techniques and evaluation of the potential release of HMs into water and transportation downstream.…”

Section: Introductionmentioning

confidence: 99%

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Spatial and vertical distribution analysis of heavy metals in urban retention tanks sediments: a case study of Strzyza Stream

Nawrot

Wojciechowska

Matej-Łukowicz

et al. 2019

Environ Geochem Health

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Concentrations of seven heavy metals (HMs): Zn, Cu, Pb, Cd, Ni, Cr, and Fe in core samples of bottom sediments from four retention tanks (RTs) located along the Strzyza Stream in northern Poland (Gdansk) were measured to obtain a general view of sediment quality. The recognition of contamination and potential environmental impacts is the main aim of this paper. A total of 96 sediment samples were collected from eight sampling sites at depths of 0-2 cm, 8-10 cm, 16-18 cm, 24-26 cm. Concentrations of Cu, Zn, Pb, Fe, Ni, and Cr were measured with AAS while Cd concentration was measured with ICP-MS. Granulometric analyses with normalized sieve apertures were carried out. Geochemical indices: enrichment factor, anthropogenic factor, and modified degree of contamination (mCd) were used to assess the contamination level. Concentrations of HMs in sediments changed in the range: Cu (3.24-119 mg/kg d.w.), Zn (12.5-584 mg/kg d.w.), Pb (4.91-309 mg/ kg d.w.), Cd (0.003-0.716 mg/kg d.w.), Ni (1.57-25.8 mg/kg d.w.), Cr (2.45-74.5 mg/kg d.w.), and Fe (3993-63817 mg/kg d.w.). The sequential extraction verified the bonding of HMs with nonmobile fractions. Geochemical indices showed widespread pollution by Cu, Pb, Cd, and Zn. Cluster and factor analysis distinguished three related subgroups of HMs: Pb, Ni-Cr, and Fe-Cd-Cu-Zn, suggesting possible common source of each subgroup. Strongly contaminated sediments were distinguished in sediment cores in two middle stream RTs characterized by intense urbanization in their direct catchments.

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Enrichment and sources of trace metals in roadside soils in Shanghai, China: A case study of two urban/rural roads

Cited by 111 publications

References 67 publications

Health Risk Assessment of Heavy Metals Accumulated on PM2.5 Fractioned Road Dust from Two Cities of Pakistan

Health Risk Assessment of Heavy Metals Accumulated on PM2.5 Fractioned Road Dust from Two Cities of Pakistan

Assessment of pollution in roadside soils by using multivariate statistical techniques and contamination indices

Spatial and vertical distribution analysis of heavy metals in urban retention tanks sediments: a case study of Strzyza Stream

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