Publications by authors named "N'Guessan Louis Berenger Kouassi"

Nutrient contamination assessments in the three West African tropical Comoé, Bandama, and Bia Rivers (Côte d'Ivoire) were performed from March 2016 to March 2018. Five stations per river were sampled. Nutrients spatio-temporal distributions were mapped and showed nitrogen concentrations (nitrite 0.

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The impact of uncontrolled municipal dumping sites on metal contamination in the surrounding waters, sediments, and soils are of great concern in many developing countries. Total concentrations of trace metals Cd, Zn, Cu, Pb, Ni, and Co were measured in 33 sediments collected in the vicinity of the Akouedo dumpsite (Abidjan, Cote d'Ivoire) and in a baseline station. The Cu, Zn, Cd, and Pb concentrations in surface sediments around the dumpsite were at least three times higher than those at the reference station, suggesting that the Akouedo dumping site is a significant contamination source of these metals to the surrounding sediments.

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This study examined the concentrations of arsenic (As), cadmium (Cd), and mercury (Hg) in rice grains grown in wetlands associated with gold mining in central-southern of Côte d'Ivoire to evaluate potential health risks exposure via rice consumption. In total, 30 rice grains were sampled around Agbaou and Bonikro gold mines. Arsenic and cadmium concentrations were determined using an inductively coupled plasma-optical emission spectrometer (ICP-OES), while atomic absorption spectrometry (AAS) was used for mercury.

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This data article is issued from the research article ''Distribution trends and ecological risks of arsenic and trace metals in wetland sediments around gold mining activities in central-southern and southeastern Côte d'Ivoire'' [1]. It presents arsenic and trace metal Cd, Pb, Cu, Zn, Cr, Co, Fe, Al, Mn, and Ni loadings in surface sediments collected from industrial mining, artisanal and small scale mining, and non-mining areas (West Africa). Are also provided, hierarchical dendrograms and factor loadings derived from the Hierarchical Clustering Analysis (HCA) and the principal component analysis (PCA), respectively.

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