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

Abstract

Multivariate statistical analysis and geochemical approaches were exploited for the assessment of the level of some heavy metals (Mn, Fe, Ni, Cu, Zn and Pb) 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 µm), two sources (crustal and anthropogenic) were recorded in fine sediment grains (grain-size < 500 µm). 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 in 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.