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H. Tutu, E. M. Cukrowska, V. Dohnal and J. Havel, “Application of Artificial Neural Networks for Classification of Uranium Distribution in the Central Rand Goldfield, South Africa, and Assessment,” Environmental Modelling, Vol. 10, No. 2, 2005, pp. 143-152.

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• TITLE: Environmental Assessment of Acid Mine Drainage Pollution on Surface Water Bodies around Ngwenya Mine, Swaziland

  AUTHORS: A. O. Fadiran, C. L. Dlamini, J. M. Thwala

  KEYWORDS: Acid Mine Drainage; Heavy Metal Pollution; Redox Potential; Physico-Chemical Properties; Iron Speciation

  JOURNAL NAME: Journal of Environmental Protection, Vol.5 No.2, February 28, 2014

  ABSTRACT: Twenty-three water samples and three “yellow boy” samples were obtained from different water bodies located at the foot of the Ngwenya Mountain on top of which the old Ngwenya Iron Ore Mine is located. The samples were analysed for pH, electrical conductivity (EC), redox potential (ORP) and temperature (T). The dominant Fe species was determined using a UV-VIS spectrophotometer. Selected anions namely: halogens (F-, Br-, Cl-), the nutrients (NO2-,NO3-,PO43-) and the best indicator for AMD pollution (SO42-) were analysed using Ion Chromatography (IC) while the selected heavy metals, namely: Cr, Mn, Fe, Ni, Co, Cu, Zn, Pb and Cd were analysed using Flame Atomic Absorption Spectrometry (FAAS). The physico-chemical parameters ranges obtained were pH (6.32 - 8.63), EC (11.00 - 585.33 μS/cm), ORP (-93.67 - 79.33 mV) and T (7.60°C - 18.57°C). The levels of the Fe species (ppm) in the water samples were Fe2+ (0.56 - 3.17) and Fe3+ (0.00 - 0.73). Measured mean anion ranges in ppm were F- (0.00 - 0.15), Cl- (1.5 - 11.19),