Application of multivariate statistical approach to identify heavy metal sources in bottom soil of the Seyhan River (Adana), Turkey

Yalçın, Mustafa Gürhan; Tümüklü, Ali; Sönmez, Mustafa; Erdag, Dilek Satir

doi:10.1007/s10661-009-0894-9

Cited by 46 publications

(18 citation statements)

References 26 publications

(38 reference statements)

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“…The metal quality indices have been computed to assess the suitability level of water resources for drinking with respect to metals (Ojekunle et al, 2016). Pearson's correlation analysis can be an effective tool for identification of pollution sources, to apportion natural versus anthropogenic or mixed contributions (Yalcin et al, 2010;Manoj et al, 2012).…”

Section: Issn: 2319-7706 Volume 6 Number 12 (2017) Pp 1491-1498mentioning

confidence: 99%

Assessment of Heavy Metal Pollution through Index Analysis for Yamuna Water in Agra Region, India

Pal¹,

Dubey²,

Dubey³

et al. 2017

Int.J.Curr.Microbiol.App.Sci

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Section: Issn: 2319-7706 Volume 6 Number 12 (2017) Pp 1491-1498mentioning

confidence: 99%

Assessment of Heavy Metal Pollution through Index Analysis for Yamuna Water in Agra Region, India

Pal¹,

Dubey²,

Dubey³

et al. 2017

Int.J.Curr.Microbiol.App.Sci

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“…Inter-element relationships of total heavy metal contents not only provide interesting information regarding the sources and pathways of the heavy metals, but can also be applied to explain the behavior and fate of heavy metals effectively and efficiently (Yalcin et al 2008;Yalcin et al 2010).…”

Section: Correlation Analysismentioning

confidence: 99%

Heavy metals in the gold mine soil of the upstream area of a metropolitan drinking water source

Ding

Tang

et al. 2015

Environ Sci Pollut Res

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Pinggu District is adjacent to the county of Miyun, which contains the largest drinking water source of Beijing (Miyun Reservoir). The Wanzhuang gold field and tailing deposits are located in Pinggu, threatening Beijing's drinking water security. In this study, soil samples were collected from the surface of the mining area and the tailings piles and analyzed for physical and chemical properties, as well as heavy metal contents and particle size fraction to study the relationship between degree of pollution degree and particle size. Most metal concentrations in the gold mine soil samples exceeded the background levels in Beijing. The spatial distribution of As, Cd, Cu, Pb, and Zn was the same, while that of Cr and Ni was relatively similar. Trace element concentrations increased in larger particles, decreased in the 50-74 μm size fraction, and were lowest in the <2 μm size fraction. Multivariate analysis showed that Cu, Cd, Zn, and Pb originated from anthropogenic sources, while Cr, Ni, and Sc were of natural origin. The geo-accumulation index indicated serious Pb, As, and Cd pollution, but moderate to no Ni, Cr, and Hg pollution. The Tucker 3 model revealed three factors for particle fractions, metals, and samples. There were two factors in model A and three factors for both the metals and samples (models B and C, respectively). The potential ecological risk index shows that most of the study areas have very high potential ecological risk, a small portion has high potential ecological risk, and only a few sampling points on the perimeter have moderate ecological risk, with higher risk closer to the mining area.

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“…During geochemical studies, factor analysis has long been used for tracing elemental sources (e.g. Cloutier et al 2008;Zhou et al 2008;Yalcin et al 2010). In this study, factor analysis is processed using the major ion concentrations (Na ?…”

Section: Source Of Major Ionsmentioning

confidence: 99%

Hydro-chemical evolution of groundwater and mixing between aquifers: a statistical approach based on major ions

Sun

Gui

2014

Appl Water Sci

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Geochemical analysis is a useful tool in hydrogeological assessment, particularly in constructing a conceptual model of a hydrogeological system. In this study, major ion concentrations of 53 groundwater samples from the coal-bearing aquifer in the Qidong coal mine, northern Anhui Province of China have been processed by statistical analysis for understanding either hydro-chemical characteristics or hydrological evolution, which will be useful for the safety of coal mining. The results suggest that most of the samples are Na-SO 4 and Na-HCO 3 types, and their hydro-chemical compositions are mainly controlled by dissolution of more soluble minerals (e.g. calcite) and weathering of silicate minerals (e.g. plagioclase). Two groups of samples have been subdivided by quantile and scatter plots of factor scores, one is related to different degrees of water-rock interactions and another is related to groundwater mixing. Moreover, four end members have been identified and the mixing calculation suggests that the groundwater samples affected by mixing have 20-100 % contribution from the loose layer aquifer (LA), and therefore, groundwater from the LA in the coal mine should be taken seriously during coal mining. The study demonstrated that statistical analysis is useful for connecting the hydrochemistry of groundwater with hydrological evolution of the aquifer.

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Application of multivariate statistical approach to identify heavy metal sources in bottom soil of the Seyhan River (Adana), Turkey

Cited by 46 publications

References 26 publications

Assessment of Heavy Metal Pollution through Index Analysis for Yamuna Water in Agra Region, India

Assessment of Heavy Metal Pollution through Index Analysis for Yamuna Water in Agra Region, India

Heavy metals in the gold mine soil of the upstream area of a metropolitan drinking water source

Hydro-chemical evolution of groundwater and mixing between aquifers: a statistical approach based on major ions

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