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        Accumulation of heavy metals in surface sediments of Lere Lake, Chad

        Léopold Nga Ekengele,Apelbo Blaise,정명채 한국지질과학협의회 2017 Geosciences Journal Vol.21 No.2

        Thirty surface sediment samples collected from Lere Lake were analyzed for As, Co, Cr, Cd, Cu, Ni, Pb, Sb, Sn, Zn, Fe, pH, Electrical Conductivity (EC) and Organic Matter (OM) in order to assess the current pollution status in sediments of the study area. Sediment pollution assessment was carried out using Enrichment Factor (EF) and Geo-accumulation index (Igeo). The potential ecotoxic effects were evaluated based on sediment quality guidelines. The calculated enrichment factor showed that the sediment was mostly enriched with Sb, Cd, Cu, and Cr. The results of the geo-accumulation index indicated that sediments were unpolluted with Sn, Co, Pb; moderately polluted with As, Cr, Cd, Cu, Ni, Zn, and strongly polluted with Sb. This pollution was attributed to anthropogenic activities caused by the sloping side of Lere Lake including consisting of mainly waste disposal, chemicals used in agriculture, and gold exploitation. Sites that exceeded TEL for Cr and Ni and PEL for Cr are ranked at the highest priority level in terms of potential ecological risk.

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        Metals pollution in freshly deposited sediments from river Mingoa, main tributary to the Municipal lake of Yaounde, Cameroon

        Ekengele Nga Léopold,Myung Chae Jung,Ombolo Auguste,Ngounou Ngatcha,Ekodeck Georges,Mbome Lape 한국지질과학협의회 2008 Geosciences Journal Vol.12 No.4

        Freshly deposited thirty six surface sediments from river Mingoa, main tributary to the Municipal lake of Yaounde in Cameroon, were sampled to determine the degree, sources and distribution of metals contamination. The concentrations of trace elements were measured by ICP-AES for the samples collected at different stations in January 2005. Generally, the concentration of metals (Ca, Mg, Na, K, Fe, Mn, Al, Cr, Co, Cu, Cd, Ni, Pb, Zn, Sr, Ba and Si) in the sediments reflected an anthropogenic inputs. The sediments were characterized by a high amount of organic matter (LOI) with a mean value of 12.44%. Enrichment Factors (EF) and Geoaccumulation Index (Igeo) were calculated and the relative contamination levels were assessed at these sites. With the exception of Ni, the enrichment of toxic metals was high. Descriptive statistics and multivariate analysis (principal factor method) were used to assist the interpretation of elemental data. This allowed the determination of the correlations between the metals and LOI variability in the sediments, and the identification of four main factors loadings controlling by parent rocks, anthropogenic input, organic compounds and weathering of silicate minerals.

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        Impact assessment of heavy metal pollution in the municipal lake water, Yaounde, Cameroon

        권지철,Ekengele Nga Léopold,정명채,Ekodeck Georges Emmanuel,Mbome Lape Israël,김기현 한국지질과학협의회 2012 Geosciences Journal Vol.16 No.2

        The objectives of this study are to evaluate the extent of heavy metal pollution in water at the Municipal Lake of Yaounde, and to find out their variability and origin. Water from fifteen selected sites of the lake and River Mingoa, Cameroon was sampled in August 16th of 2005 and 2006 and in 30th August 2007 during the minor dry season; and subjected to the analyses of physico-chemical parameters and various elements. In addition, multivariate data analysis techniques including principal component analysis (PCA) were utilized to determine the variations in heavy metal content in the Municipal Lake water and their natural or anthropogenic sources. The chemical results indicated that concentrations of Al, Fe, Mn, Cd and Pb in the study area exceeded the drinking water quality and they would pose health risk for users of these waters. This is evidence that River Mingoa, the main tributary to the Municipal Lake is the main collector of pollutants from activities in the sloping side of the Municipal Lake. Based on the multivariate statistical analysis, very high positive correlations were observed between elements, and five factors computed from PCA explained 86.6% of total variance. These factor loadings are mainly controlled by anthropogenic inputs, lithogenic processes during weathering progress of natural parent materials and local geology

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