4.7 Article

Combining multivariate analysis and geochemical approaches for assessing heavy metal level in sediments from Sudanese harbors along the Red Sea coast

期刊

MICROCHEMICAL JOURNAL
卷 90, 期 2, 页码 159-163

出版社

ELSEVIER
DOI: 10.1016/j.microc.2008.05.004

关键词

Heavy metals; Multivariate analysis; Principal component analysis; Hierarchical cluster analysis; Enrichment factor; Marine sediment

资金

  1. IAEA

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Multivariate statistical analysis and geochemical approaches were exploited for the assessment of the level of some heavy metals (Mn, Fe, Ni, Cu, Zn and Ph) in sediments from Sudanese harbors along the Red Sea coast. Principal component analysis, as a multivariate statistical analysis approach, was applied to identify contribution Sources by heavy metals in sediments. While a single source (Crustal) Was recorded in the bulk sediments and coarse sediment grains (grain-size 1000-500 mu m), two Sources (crustal and anthropogenic) were recorded in fine sediment grains (grain-size < 500 mu m). Furthermore, enrichment factor (EF), as a geochemical approach, appointed Polluted sites by heavy metals in the Study area. Based upon a previous study addressed the interpretation of EF values, minor to moderate anthropogenic enrichment were recorded in sediments from some sites in the study area. The main anthropogenic activities that believed to be the major Sources Of Pollution by heavy metals ill the Study area are discharges from oil refinery. industry, shipping activity and domestic waste. Hierarchical cluster analysis (HCA), as another multivariate statistical analysis approach, was applied for the concentrations of heavy metals in bulk sediments to group sediments according to their mineralogical composition. The Output of HCA is that sediments from the Port-Sudan harbor can be divided mainly into three areas - east, west and south. For the Sawakin harbor, no apparent trend for the spatial distribution of heavy metals in sediments was recorded. (c) 2008 Elsevier B.V. All rights reserved.

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