Spatial clustering of metals in the sediments of the Skagerrak/Kattegat

Danielsson, Åsa; Cato, Ingemar; Carman, Rolf; Rahm, Lars

doi:10.1016/s0883-2927(99)00003-7

Cited by 124 publications

(48 citation statements)

References 39 publications

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“…In clustering, similar objects are grouped into the same class (Danielsson et al 1999). Hierarchical cluster analysis is the most widely applied techniques to detect similar and dissimilar groups between the sampling sites (Shrestha and Kazama 2007).…”

Section: Cluster Analysismentioning

confidence: 99%

Multivariate statistical evaluation of heavy metals in the surface water sources of Jia Bharali river basin, North Brahmaputra plain, India

Khound¹,

Bhattacharyya

2016

Appl Water Sci

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The aim of this study was to assess the quality of surfacewater sources in the Jia Bharali river basin and adjoining areas of the Himalayan foothills with respect to heavy elements viz. (As, Cd, Cr, Cu, Fe, Mn, Ni, Pb and Zn) by hydrochemical and multivariate statistical techniques, such as cluster analysis (CA) and principal component analysis (PCA). This study presents the first ever systematic analysis on toxic elements of water samples collected from 35 different surface water sources in both the dry and wet seasons for a duration of 2 hydrological years (2009)(2010)(2011). Varimax factors extracted by principal component analysis indicates anthropogenic (domestic and agricultural run-off) and geogenic influences on the trace elements. Hierarchical cluster analysis grouped 35 surfacewater sources into three statistically significant clusters based on the similarity of water quality characteristics. This study illustrates the usefulness of multivariate statistical techniques for analysis and interpretation of complex data sets, and in water quality assessment, identification of pollution sources/factors and understanding temporal/spatial variations in water quality for effective surfacewater quality management.

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Section: Cluster Analysismentioning

confidence: 99%

Multivariate statistical evaluation of heavy metals in the surface water sources of Jia Bharali river basin, North Brahmaputra plain, India

Khound¹,

Bhattacharyya

2016

Appl Water Sci

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“…The association of Pb with vehicle emissions can be explained in terms of Pb contamination in crude oil, which may be of the order of 10-15 mg/L (Vassilakos et al, 2007). Vehicle exhaust is also the primary major source for Cr, Cu, Zn, Cd, Sb, Br, Fe and Ba (Danielsson et al, 1999;Shu et al, 2001;Fang et al, 2010). With rapid economic development in China, the number of motor vehicles has dramatically increased in recent years.…”

Section: Introductionmentioning

confidence: 99%

Assessing the Hazardous Risks of Vehicle Inspection Workers’ Exposure to Particulate Heavy Metals in Their Work Places

Kong

Geng

et al. 2013

Aerosol Air Qual. Res.

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Exposure of on-duty vehicle inspection workers to heavy metals in Beijing was investigated from April 18 to May 17, 2011. Particulate samples were collected by personal environmental monitors during vehicle inspectors' work time, and were analyzed by inductively coupled plasma-mass spectroscopy (ICP-MS) for V, Cr, Mn, Co, Ni, Cu, Zn, As, Cd and Pb. The results showed that in three vehicle inspection lines, Zn was the most abundant element, accounting for over 45% of the total metal concentration. Cr and Pb were the next most abundant compositions. The geoaccumulation index and enrichment factor analysis showed that Cr, Zn, As, Cd and Pb exhibited heavy or extreme contamination and significant enrichment, indicating the influence of anthropogenic sources. Mn and Co were mostly non-enriched and were mainly influenced by crustal sources. Ni and V presented moderate or heavy contamination, and were influenced by both crustal materials and anthropogenic sources. Principle component analysis revealed that the major sources were vehicle emissions, re-suspended dust and industrial processes. Cr and Mn could trigger adverse non-cancer health effects. The median values of incremental lifetime cancer risk (ILCR) of inhalation exposure route were estimated to be 2.59 × 10 , respectively for gasoline, bus, and diesel inspection workers, respectively. The ILCR was higher than the acceptable risk level of 10 -6 , indicating an unacceptable potential cancer risk.

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“…This method is commonly used for sediment analysis in terms of spatial distribution of metal and heavy metal pollution (e.g. Danielsson et al, 1999;Simeonov et al, 2000). Former application of this statistical method on rock magnetic data from the Dead Sea sediments revealed that it is particularly suited for grouping sediment samples with similar composition from a set of geophysical and geochemical variables (Frank et al, 2007).…”

Section: Cluster Analysismentioning

confidence: 99%

A 350 ka record of climate change from Lake El'gygytgyn, Far East Russian Arctic: refining the pattern of climate modes by means of cluster analysis

et al. 2013

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Rock magnetic, biochemical and inorganic records of the sediment cores PG1351 and Lz1024 from Lake El'gygytgyn, Chukotka peninsula, Far East Russian Arctic, were subject to a hierarchical agglomerative cluster analysis in order to refine and extend the pattern of climate modes as defined by Melles et al. (2007). Cluster analysis of the data obtained from both cores yielded similar results, differentiating clearly between the four climate modes warm, peak warm, cold and dry, and cold and moist. In addition, two transitional phases were identified, representing the early stages of a cold phase and slightly colder conditions during a warm phase. The statistical approach can thus be used to resolve gradual changes in the sedimentary units as an indicator of available oxygen in the hypolimnion in greater detail. Based upon cluster analyses on core Lz1024, the published succession of climate modes in core PG1351, covering the last 250 ka, was modified and extended back to 350 ka. Comparison to the marine oxygen isotope (δ¹⁸O) stack LR04 (Lisiecki and Raymo, 2005) and the summer insolation at 67.5° N, with the extended Lake El'gygytgyn parameter records of magnetic susceptibility (κ_LF), total organic carbon content (TOC) and the chemical index of alteration (CIA; Minyuk et al., 2007), revealed that all stages back to marine isotope stage (MIS) 10 and most of the substages are clearly reflected in the pattern derived from the cluster analysis

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Spatial clustering of metals in the sediments of the Skagerrak/Kattegat

Cited by 124 publications

References 39 publications

Multivariate statistical evaluation of heavy metals in the surface water sources of Jia Bharali river basin, North Brahmaputra plain, India

Multivariate statistical evaluation of heavy metals in the surface water sources of Jia Bharali river basin, North Brahmaputra plain, India

Assessing the Hazardous Risks of Vehicle Inspection Workers’ Exposure to Particulate Heavy Metals in Their Work Places

A 350 ka record of climate change from Lake El'gygytgyn, Far East Russian Arctic: refining the pattern of climate modes by means of cluster analysis

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