7th International Conference on Latest Trends in Engineering & Technology (ICLTET'2015) Nov. 26-27, 2015 Irene, ()

Mapping of Surface Water Quality in the Vicinity of based on Mining Pollutants

Elvis Fosso-Kankeu, Divan P. Van der Berg, Frans Waanders, Alusani Manyatshe, Nico Lemmer, and H. Tutu

 complex process that is driven by physical, biological and Abstract— Surface water is considered as one of South Africa’s chemical factors. In short, AMD is formed when sulphide most limiting natural resources. The reality is that many of our minerals undergo oxidative dissolution [6]. AMD water has a natural water resources are contaminated by various activities. low pH, a high specific conductivity and is high in heavy metal Various water treatment plants, industries and agricultural areas and sulphate concentrations [7; 8; 9]. The occurrence of AMD along the depend on its water. These waters travel is observed in both active and abandoned mines [8; 6]. through mining and urban areas that may contribute to the pollution of the water. This study sampled and tested 35 different points along Agricultural activities may contribute in different ways to the the Mooi River and connected streams in Potchefstroom area. pollution of freshwater resources. These contributions include Contaminants tested for using a Spectro-photometer included effects on water chemistry, biocide leaching, suspended loads sulphate, nitrate, and cyanide. An ICP-OES analyser was used to test from soil erosion, changes in the hydrological system and concentrations of Ag, Al, As, Ca, Cd, Cr, Fe, K, Mg, Mo, Ni, Pb, U, effects of exotic species used [10]. and Zn. Geochemical parameters such as the pH, temperature, ORP, The need and drive to optimize crop yields has led to large electronic conductivity and dissolved oxygen concentrations were quantities of artificial nitrogen being used by the agricultural also tested using a pH-meter. The alkalinity and chloride industry over the past few years [11]. Mining activities in concentrations were tested using titration techniques. Both filtered South Africa are among the largest contributors to the and non-filtered samples were tested. The results showed that several of the samples tested for had contaminant concentrations that pollution of surface water as they produce a large volume of exceeded the maximum allowable concentrations for drinking water, tailings dumps [12], and due to poor management of these set by the South African National Standard (SANS) and the World tailings dumps they increase the level of pollution in surface Health Organization (WHO). These results indicate that areas with water. mining activities tend to have higher concentrations of contaminants The key in protecting and preserving the water resources of than other ‘undisturbed’ areas. South Africa is to develop a water efficient economy with the necessary treatment plans in place [13]. With different Keywords— Surface water, contamination, heavy metals, activities contributing to the water pollution in the West Rand geochemical parameters, Mooiriver, Potchefstroom area, it is important to find the sources of contamination in order to better prevent the contamination [14]. I. INTRODUCTION OR many years water has been considered a vital raw II. METHODOLOGY F material of social development and organization [1].The A. Sampling scarcity of water quality can be exacerbated through The first step in this study was to collect water samples at pollution by effluents from anthropogenic sources such as 35 various geologically determined sites along the Mooi River industrial, mining activities, domestic sewage, wastewater and Orkney areas. These water samples were collected during treatment plant and agricultural land which are directly or summer. The sites of sampling ranged from the Doornfontein indirectly discharged into aquatic environment [2, 3, 4], as mine near Carletonville to Potchefstroom as well as from the well as natural processes such as erosion and weathering of Klerkskraal dam to Potchefstroom. The Potchefstroom dam crustal materials [5]. and Boskop dam were also important points of interest. One of the most significant sources of contamination in The coordinates of these sampling sites were recorded using many countries is Acid Mine Drainage (AMD). AMD is a a GPS system and the sampling bottles were then labelled accordingly. The numbering system was done numerically Elvis Fosso-Kankeu is with the School of Chemical and Minerals from sample 1, which is the furthest upstream to sample 35, Engineering of the North West University, Bult area-Potchefstroom-South downstream. The flow of the numbers is thus a representation Africa. of the flow of the water. The Google Earth map in Figure 1 Frans Waanders is with the School of Chemical and Minerals Engineering shows where all of the points are located. Figure 2 is an image of the North West University, Bult area-Potchefstroom-South Africa Divan Van der Berg is with the School of Chemical and Minerals of the Potchefstroom area. Engineering of the North West University, Bult area-Potchefstroom-South Africa

http://dx.doi.org/10.15242/IIE.E1115014 43 7th International Conference on Latest Trends in Engineering & Technology (ICLTET'2015) Nov. 26-27, 2015 Irene, Pretoria (South Africa)

III. RESULTS AND DISCUSSION A. Fitness of water The fitness of the surface water samples was investigated by comparing the concentrations of the various parameters tested for to the standards set for drinking water by SANS [15] and the WHO [16]. This comparison provides an indication of how far from the drinking water norm/standard these samples deviate and thus also to which extent they are contaminated. In Table 4.1, a summary of the geochemical parameters is shown. Table 4.2 represents the major anion concentrations; values in ‘bold’ indicate that these concentrations were above Fig. II.1: Google Earth image of sampling sites the standards set for drinking water by SANS [15] and the WHO [16]. Tables 4.3 and 4.4 show some of the heavy metal concentrations. The measured and determined values of the geochemical parameters are presented in Table 4.1; as a general trend, there was no major concern with regard to the pH values in all the sampling sites; however, compared to the acceptable range, the alkalinity of the water was mostly very high. The high alkalinities observed can be due to minerals from the soil which dissolve in the water [17]. The Carletonville area is known to be underlain by dolomite rock which certainly contributes to the release of carbonate into the water network flowing down to Potchefstroom, hence the higher alkalinity which is also reported to contribute to an increase of pH [18]. The negative ORP values recorded, correspond with the high Fig. II.2: Google Earth image of Potchefstroom sites pH values observed. Water samples were collected in 500 mL clean plastic Other geochemical parameters tested for were temperature containers which were washed and rinsed three times with the and dissolved oxygen. The temperature of the surface water water from the sampling site to prevent any contamination samples ranged from 14.7 to 27°C. The dissolved oxygen from elsewhere. Three samples in 500 mL plastic containers concentrations ranged from 4.7 to 9.0 mg/L. The low DO were collected per sampling site to ensure that enough sample values found are mainly attributed to slow moving/flowing was available for analysis. At each dam, samples were water at these points, which were from an eye and a slow collected from different depths using a depth-sampler designed moving stream. and manufactured at the North-West University (NWU). From Table 4.3 it is seen that three sampling points had Directly after sampling, the following physico-chemical sulphate concentrations that exceeded the maximum allowable parameters were measured using a pH combined electrode concentrations set by SANS [15] and the WHO [16] for with integrated temperature probe: Temperature (°C), pH, drinking water. The amount of chloride was within the limits Electrical conductivity EC (mS/cm), Dissolved oxygen DO and four samples had nitrate concentrations that exceeded the (mg/L), and Redox potential Eh (mV). The pH-meter was limit. Almost all of the samples had cyanide concentrations calibrated before field work started, using reference buffer that were above the standard. According to the WHO [16], an solutions. The samples were then stored in cooler boxes filled excess of cyanide in drinking water may cause cardiovascular, with ice to ensure that the samples were preserved during respiratory and neuro-electric alterations. The brain is transportation to the laboratory were further analyses were reported to be the organ that is most sensitive to cyanide done. toxicity. Heavy metals finding their way in the water sources may B. Laboratory analyses adversely affect the aquatic flora and fauna, but more - - The alkalinity (as HCO3 and CO3 ) was measured by importantly may be linked to human poisoning if present in titrating with 0.2 N H2SO4 acid. The concentrations of sulphate drinking water. Tables 4.5 and 4.6 show that the majority of 2- - -) (SO4 ), nitrate (NO3 ), free chlorine (Cl) and cyanide (CN samples contained higher concentrations of heavy metals that were measured using a COD and Multiparameter Bench exceeded in some cases the limits set by SANS [15] and the Photometer HI 83099 (Hanna Instruments Inc., USA). The WHO [16] for safe drinking water. The high concentrations of concentration of chloride was measured by titrating with a Ag, Ca, Cd, Fe, Mg, Ni, and Pb, were indicative of the silver nitrate and sodium chloride solution. The heavy metal potential contamination from mining activities in the area. concentrations were analyzed using an inductively coupled plasma optical emission spectrometer (ICP-OES).

http://dx.doi.org/10.15242/IIE.E1115014 44 7th International Conference on Latest Trends in Engineering & Technology (ICLTET'2015) Nov. 26-27, 2015 Irene, Pretoria (South Africa)

TABLE III.1 TABLE III.2 GEOCHEMICAL PARAMETERS MAJOR ANIONS CONCENTRATIONS Geochemical Parameters Major Anions Sample pH Eh Ec Alkalinity Carb Alk Sample Sulphate Chloride Nitrate Cyanide Number mV mS/cm mg/l CaCO3 mg/l CaCO3 Number mg/l mg/l mg/l mg/l 1 8.37 -76.00 0.45 880.00 18.57 2 8.39 -78.00 0.43 624.00 14.25 1 0.00 13.33 0.00 3.00 3 9.22 -125.00 1.40 608.00 83.75 2 0.00 10.00 2.50 2.00 4 8.80 -100.00 0.37 836.00 46.12 3 595.00 76.67 0.20 3.00 5 8.03 -58.00 1.11 796.00 7.83 6 7.39 -21.00 0.82 856.00 1.93 4 525.00 73.33 0.00 3.00 7 7.40 -21.00 0.81 1012.00 2.30 5 315.00 66.67 2.40 3.00 8 7.41 -22.00 0.85 938.00 2.20 6 150.00 43.33 18.80 2.00 9 8.15 -69.00 0.72 1136.00 14.28 7 140.00 33.33 8.40 3.00 10 8.31 -69.00 0.74 916.00 16.82 11 8.28 -78.00 0.72 812.00 14.08 8 160.00 43.33 3.10 2.00 12 8.34 -81.00 0.69 848.00 16.78 9 110.00 30.00 4.30 1.00 13 8.40 -83.00 0.70 756.00 17.31 10 110.00 33.33 0.00 2.00 14 8.38 -83.00 0.69 788.00 17.18 11 100.00 36.67 6.30 1.00 15 8.44 -86.00 0.69 724.00 18.21 12 100.00 40.00 0.20 1.00 16 8.32 -72.00 0.68 744.00 14.24 17 8.35 -75.00 0.67 828.00 16.79 13 110.00 36.67 0.80 1.00 18 8.15 -63.00 0.70 832.00 10.72 14 100.00 40.00 0.00 1.00 19 8.19 -66.00 0.71 732.00 10.45 15 110.00 40.00 0.90 1.00 20 8.32 -72.00 0.71 220.00 5.20 16 110.00 33.33 8.50 1.00 21 8.37 -83.00 0.70 1040.00 21.66 22 8.39 -83.00 0.75 1112.00 24.11 17 110.00 33.33 2.00 1.00 23 8.38 -83.00 0.69 992.00 21.21 18 120.00 40.00 0.20 2.00 24 8.40 -83.00 0.72 1120.00 24.83 19 110.00 33.33 1.60 2.00 25 8.45 -87.00 0.70 1016.00 25.38 20 120.00 33.33 4.10 2.00 26 8.47 -79.00 0.71 220.00 6.23 27 8.50 -83.00 0.71 244.00 8.42 21 90.00 36.67 21.60 1.00 28 8.41 -77.00 0.71 216.00 6.29 22 100.00 56.67 5.50 1.00 29 8.29 -67.00 0.77 236.00 5.12 23 110.00 36.67 0.00 1.00 30 8.26 -73.00 0.76 264.00 31.39 24 100.00 36.67 0.00 0.00 31 8.06 -61.00 0.76 228.00 2.96 32 8.15 -63.00 0.82 264.00 4.06 25 110.00 43.33 1.90 0.00 33 8.50 -85.00 0.78 364.00 11.52 26 100.00 36.67 11.20 1.00 34 8.37 -81.00 0.71 220.00 5.82 27 95.00 30.00 2.20 0.03 35 8.43 -87.00 0.72 220.00 6.67 28 100.00 40.00 4.70 1.00

29 180.00 46.67 0.60 2.00 B. Potential sources of water contamination 30 120.00 26.67 0.00 2.00 Statistical summaries of the geochemical parameters are 31 120.00 43.33 0.00 1.00 shown in Table 5. In Table 6, statistical summary of the major 2- 32 110.00 53.33 5.80 0.00 anion concentrations are shown, which include sulphate (SO4 - - -) 33 550.00 150.00 6.50 33.00 ), nitrate (NO3 ), chloride (Cl ) and cyanide (CN . Table 7) 34 160.00 40.00 0.00 1.00 represents the statistical summary of the heavy metals. 35 100.00 43.33 28.00 1.00 From Table 5 it is seen that the total alkalinity of samples taken upstream of Potchefstroom was significantly higher than samples collected in the Potchefstroom area. This significant difference may be attributed to the variation in soil from the different areas. The upstream area contains more dolomite rock which increases the alkalinity of the water in contact with it [18]. The pH values in all two areas were very similar and fairly high. The upstream pH values varied between 7.39 and 9.22, while in the Potchefstroom area the pH range was 8.06 to 8.50. Although the mine effluents did not seem to significantly impact the pH, the minimum values were recorded in those areas and it is therefore likely that a chemical imbalance will result into an acidic pH. The slightly lower pH values found upstream, may be due to the Doornfontein mine which pumps its treated waste water into the Mooi River at sampling point 4. The Eh and EC of both areas were very similar.

http://dx.doi.org/10.15242/IIE.E1115014 45 7th International Conference on Latest Trends in Engineering & Technology (ICLTET'2015) Nov. 26-27, 2015 Irene, Pretoria (South Africa)

TABLE III.3 HEAVY METALS CONCENTRATIONS From Table 6, it is seen that the concentrations of sulphate Heavy metals Sample Ag Al As Ca Cd Cr Fe in the upstream were slightly higher than in Potchefstroom Number mg/l mg/l mg/l mg/l mg/l mg/l mg/l areas, indicating the potential source of AMD contamination. 1 0.00 0.00 0.00 38.43 0.00 0.00 0.00 2 0.00 0.00 0.57 37.60 0.17 0.00 0.00 The concentration of sulphate found upstream in the 3 0.00 0.63 5.00 102.92 0.07 0.00 0.00 Doornfontein mine canal was 595 mg/L, and the sulphate 4 0.00 0.14 2.07 102.25 0.09 0.00 0.00 concentration in the Ikageng canal in Potchefstroom was 550 5 0.00 0.30 4.84 78.26 0.05 0.00 0.00 6 0.00 0.00 3.51 71.40 0.15 0.00 0.00 mg/L. Both these sample sites are located near mining 7 0.00 0.00 4.61 68.45 0.09 0.00 0.00 activities, which may suggest that polluted waters from the 8 0.00 0.00 2.30 68.40 0.01 0.00 0.00 9 0.00 0.03 0.84 218.50 0.15 0.00 5.71 respective mines are potentially polluting these points. High 10 0.01 0.05 0.00 216.60 0.11 0.00 0.10 chloride concentrations were found in the Ikageng canal (150 11 0.07 3.85 0.00 217.30 0.14 0.00 11.34 12 0.01 0.05 0.00 213.40 0.09 0.02 0.65 mg/L) which suggests some chloride contamination from this 13 0.00 0.00 0.31 212.50 0.25 0.03 6.90 mine. 14 0.00 0.05 0.26 210.30 0.08 0.00 0.39 15 0.00 0.09 0.95 211.40 0.14 0.00 8.29 The highest concentration of nitrate was found just 16 0.00 0.00 2.20 44.35 0.00 0.06 0.00 downstream of an agricultural college in the Potchefstroom 17 0.00 0.00 2.10 45.48 0.24 0.03 0.00 area, which indicates the potential presence of fertilizers in the 18 0.00 0.00 0.00 48.75 0.03 0.00 0.00 19 0.00 1.60 0.00 52.80 0.14 0.06 9.45 water that are used for agricultural activities. The highest 20 0.04 0.10 2.35 51.22 0.03 0.00 8.47 nitrate concentration upstream was found in an area with a lot 21 0.01 0.30 1.43 208.70 0.15 0.00 0.47 22 0.02 0.40 0.00 208.40 0.15 0.00 0.68 of cattle, which can potentially mean that the cattle dung is 23 0.02 0.06 0.00 210.10 0.09 0.00 0.20 contributing to the high nitrate concentration. Very high 24 0.00 0.11 0.00 210.20 0.08 0.00 0.34 25 0.00 0.14 0.00 212.00 0.13 0.00 0.69 cyanide concentration of 33 mg/L was found in the Ikageng 26 0.12 0.21 4.53 48.43 0.20 0.06 22.00 canal, which indicates potential contamination from this mine 27 0.05 0.16 3.67 48.64 0.70 0.06 36.00 which mostly focuses on gold mining and may therefore use 28 0.59 0.13 2.06 48.73 0.09 0.01 17.80 29 0.00 0.09 2.25 66.15 0.15 0.00 7.69 cyanide as a leaching agent. 30 0.00 0.00 0.97 53.36 0.00 0.02 0.66 There was no statistical significant difference between the 31 0.01 0.43 1.38 49.88 0.21 0.09 6.95 32 0.00 0.00 0.00 38.69 0.00 0.00 0.00 concentrations of heavy metals at the different sampling sites; 33 0.01 0.14 0.00 185.80 0.10 0.03 15.60 however according to the results in Table 7, some elements 34 0.02 0.04 1.76 48.89 0.02 0.00 8.48 were relatively abundant in specific areas. Uranium (U) was 35 0.05 0.04 1.08 49.26 0.20 0.00 14.00 mainly found upstream of Potchefstroom, where mining TABLE III.4 activities are taking place. Co-occurrence of higher HEAVY METALS CONCENTRATIONS concentrations of Ca and Mg was observed upstream of Heavy metals Sample K Mg Mo Ni Pb U Zn Potchefstream, confirming the impact of dolomite rock on the Number mg/l mg/l mg/l mg/l mg/l mg/l mg/l geochemistry of streams that flow across that area. Arsenic 1 1.43 28.39 0.51 0.00 0.72 0.01 0.00 2 9.75 27.67 0.29 0.00 0.32 0.06 0.00 (As) was higher upstream, and its presence in surface water 3 1.22 72.00 0.10 0.00 0.00 0.04 0.16 around Potchefstroom could probably result from 4 5.38 71.00 0.00 0.15 0.00 0.07 0.00 contamination of water flowing through the mining areas 5 5.08 42.02 0.17 0.06 0.21 0.00 0.00 6 20.17 38.25 0.00 0.00 0.25 0.00 0.00 upstream. It was quite surprising to record high concentration 7 13.14 37.33 0.00 0.00 0.22 0.00 0.00 of Fe in Potchefstroom and the source could not be identified. 8 12.79 39.85 0.00 0.00 0.00 0.00 0.00 9 2.38 195.60 1.10 0.00 0.39 0.05 0.30 In general, the heavy metals contamination in the 10 4.93 199.90 0.91 0.00 0.44 0.01 0.07 Potchefstroom area was slightly less than in the upstream area; 11 13.24 202.00 0.88 0.00 0.70 0.03 0.08 12 13.48 199.50 0.62 0.00 1.25 0.00 0.16 as already mentioned, the mining activities could have been 13 13.02 199.20 1.07 0.00 0.73 0.00 0.56 the major source of these pollutants. 14 16.72 198.00 0.35 0.00 0.67 0.00 0.24 15 12.88 198.80 0.65 0.00 0.21 0.00 0.29 16 12.98 41.07 0.14 0.00 0.00 0.01 0.00 17 12.94 42.09 0.25 0.00 0.00 0.00 0.03 18 12.89 39.65 0.00 0.00 0.00 0.00 0.00 19 13.11 43.09 0.00 0.32 0.00 0.05 0.56 20 3.17 36.56 0.58 0.28 0.00 0.01 0.25 21 3.37 188.80 0.65 0.00 0.30 0.00 0.28 22 3.54 191.30 0.60 0.00 1.21 0.00 0.10 23 2.87 195.00 0.38 0.00 0.89 0.00 0.29 24 2.32 199.00 0.54 0.00 0.59 0.00 0.21 25 2.07 199.70 0.69 0.00 1.01 0.04 0.09 26 11.67 40.37 23.50 0.00 5.13 0.00 0.25 27 9.34 39.89 0.41 0.51 0.13 0.00 0.33 28 6.85 39.52 0.13 0.00 0.00 0.00 0.00 29 39.41 50.53 0.38 0.03 0.00 0.03 0.09 30 25.88 20.00 0.13 0.00 1.01 0.00 0.00 31 27.93 40.19 0.31 0.28 0.00 0.00 0.00 32 0.00 28.33 0.80 0.31 0.00 0.00 0.00 33 0.99 124.10 0.99 0.13 0.00 0.00 0.00 34 0.95 35.94 0.17 0.13 0.00 0.00 0.01 35 2.56 35.38 0.04 0.00 0.00 0.00 0.00

http://dx.doi.org/10.15242/IIE.E1115014 46 7th International Conference on Latest Trends in Engineering & Technology (ICLTET'2015) Nov. 26-27, 2015 Irene, Pretoria (South Africa)

TABLE III.5 STATISTICAL GEOCHEMICAL PARAMETERS

TABLE III.6 STATISTICAL MAJOR ANIONS

TABLE III.7 STATISTICAL HEAVY METALS

Wonderfontein area. In general though the Boskop and Potchefstroom dams were not significantly contaminated and IV. CONCLUSION can be grouped with the Klerkskraal dam which was the least This study was able to identify some significant points of contaminated point in the system. contamination in the water system of the Mooi River in the vicinity of Potchefstroom. The most contaminated areas ACKNOWLEDGEMENT within the study were found to be those in close proximity to The authors are grateful to the sponsor from the North-West mining activities. Contamination from upstream was University and the National Research Foundation (NRF) in predominantly found near the Doornfontein mine. The mine’s South Africa. The contribution of Dr O. Ntwampe is really canal discharges its water into the Mooi River at sampling appreciated. point 4, which is identified as the source of upstream contamination. The Ikageng canal, flowing from a mine dam, REFERENCES was identified as the largest contributor to contamination in Potchefstroom. The high concentrations of other contaminants [1] Sabhapandit, P., Saikia, P. & Mishra, A.K. 2010. Statistical analysis of heavy metals from water samples of Tezpur sub-division in Sonitpur are linked to contamination from upstream which indicates that district, Assam, India. International Journal of Applied Biology and these contaminants do not totally precipitate in the system, and Pharmaceutical Technology, 1 (3). are transported downstream. [2] Manickum, T., John, W., Terry, S. & Hodgson, K. 2014. Preliminary The upstream and Potchefstroom areas were dominated by study on the radiological and physicochemical quality of the Umgeni Water catchments and drinking water sources in KwaZulu-Natal, South high levels of Ca, Mg, sulphate and alkalinity. The upstream Africa. J Environ Radioact, 137:227-240, Nov. area is underlain by dolomite rock which is certainly the http://dx.doi.org/10.1016/j.jenvrad.2014.07.015 contributing factor to the high alkalinity in the area. The high [3] Fosso-Kankeu E, Mulaba-Bafubiandi A, Mamba BB, Barnard TG. 2009. Mitigation of Ca, Fe, and Mg loads in surface waters around Ca, Mg and sulphate concentrations are linked to the mining areas using indigenous microorganism strains. Journal of Doornfontein mine as well as mining activities from the upper Physics and Chemistry of the Earth, Vol 34, pp 825-829.

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http://dx.doi.org/10.1016/j.pce.2009.07.005 [4] Fosso-Kankeu E, Mulaba-Bafubiandi AF, Mamba BB and Barnard TG. 2011. Prediction of metal-adsorption behaviour in the remediation of water contamination using indigenous microorganisms. Journal of Environmental Management, 92 (10), pp 2786-2793. http://dx.doi.org/10.1016/j.jenvman.2011.06.025 [5] Simeonov, V., Stratis, J.A., Samara, C., Zachariadis, G., Voutsa, D., Anthemidis, A., et al. 2003. Assessment of the surface water quality in Northern Greece. Water Res, 37 (17):4119-4124. http://dx.doi.org/10.1016/S0043-1354(03)00398-1 [6] Simate, G.S. & Ndlovu, S. 2014. Acid mine drainage: Challenges and opportunities. Journal of Environmental Chemical Engineering, 2 (3). http://dx.doi.org/10.1016/j.jece.2014.07.021 [7] Akcil, A. & Koldas, S. 2006. Acid Mine Drainage (AMD): causes, treatment and case studies. Journal of Cleaner Production, 14 (12- 13):1139-1145. http://dx.doi.org/10.1016/j.jclepro.2004.09.006 [8] Anawar, H.M. 2013. Impact of climate change on acid mine drainage generation and contaminant transport in water ecosystems of semi-arid and arid mining areas. Physics and Chemistry of the Earth, Parts A/B/C, 58-60:13-21. http://dx.doi.org/10.1016/j.pce.2013.04.002 [9] Nyquist, J. & Greger, M. 2009. A field study of constructed wetlands for preventing and treating acid mine drainage. Ecological Engineering, 35 (5). http://dx.doi.org/10.1016/j.ecoleng.2008.10.018 [10] Moss, B. 2008. Water pollution by agriculture. Philos Trans R Soc Lond B Biol Sci, 363 (1491):659-666, Feb 12. [11] Zhang, Y., Li, F., Zhang, Q., Li, J. & Liu, Q. 2014b. Tracing nitrate pollution sources and transformation in surface- and ground-waters using environmental isotopes. Sci Total Environ, 490:213-222, Aug 15. [12] Rosner, T. & van Schalkwyk, A. 1999. The environmental impact of gold mine tailings footprints in the Johannesburg region, South Africa. Engineering and Environmental Geology, 59:137-148. [13] Ntengwe, F.W. 2005. An overview of industrial wastewater treatment and analysis as means of preventing pollution of surface and underground water bodies—the case of Nkana Mine in Zambia. Physics and Chemistry of the Earth, Parts A/B/C, 30 (11-16):726-734. http://dx.doi.org/10.1016/j.pce.2005.08.014 [14] Opperman, I. 2008. The Remediation of surface water comtamination: . 1. University of South Africa. [15] SANS. 2005. South African National Standard Drinking water. Standards South Africa, http://apps.who.int/iris/bitstream/10665/44584/1/9789241548151_eng. pdf Date of access 20 May 2015. [16] WHO. 2011. Guidelines for drinking water quality, fourth edition. World Health Organization, http://apps.who.int/iris/bitstream/10665/44584/1/9789241548151_eng. pdf Date of access 20 May 2015. [17] Bajpai, R. 2012. Comparative analyses of physicochemical parameters of Hasdeo river barrage & Arpa River water samples of Bilaspur region. International Journal of Scientific and Reasearch Publications, 2 (9):2250-3153. [18] Malan, J.D. 2002. The impact of the gold mining industry on the water quality of the Kromdraai catchment. Geography and Environmental Management: University of Johannesburg. https://ujdigispace.uj.ac.za Date of access 19 Oct. 2015.

The corresponding author is currently a Senior Lecturer in the School of Chemical and Minerals Engineering at the North-West University (Potchefstroom). He is an NRF rated researcher who has published journal articles, book chapters and book. Dr Elvis Fosso-Kankeu has been the recipient of several merit awards.

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