Industrial effluents with high concentrations of heavy metals are widespread pollutants of great concerns as they are known to be persistent and non-degradable. Continuous monitoring and treatment of the effluents become pertinent because of their impacts on wastewater treatment plants. The aim of this study is to determine the correlation between heavy metal pollution in water and the location of industries in order to ascertain the effectiveness of the municipal waste water treatment plant. Heavy metal identification and physico-chemical analysis were done using Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES) and multi-parameter probe respectively. Correlation coefficients of the measured values were done to investigate the effect of the industrial effluents on the treatment plants. Heavy metal resistant bacteria were identified and characterised by polymerase chain reaction and sequencing. Leeuwkuil wastewater treatment plants were effective in maintaining temperature, pH, and chemical oxygen demand within South Africa green drop and SAGG Standards whereas the purification plant was effective in maintaining the values of Cu, Zn, Al, temperature, BOD, COD, and TDS within the SANS and WHO standard for potable water. This findings indicated the need for the treatment plants to be reviewed.The industrial wastewater were identified as a point source of heavy metal pollution that influenced Leeuwkuil wastewater treatment plants and the purification plants in Vaal, Vereenining South Africa. Pseudomonas aeruginosa, Serratia marcescens, Bacillus sp. strain and Bacillus toyonensis that showed 100% similarity were found to be resistant to Al, Cu, Pb and Zn. These identified bacteria can be considered for further study in bioremediation. / Environmental Sciences / M. Sc. (Environmental Science)
Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:unisa/oai:uir.unisa.ac.za:10500/25877 |
Date | 07 1900 |
Creators | Iloms, Eunice Chizube |
Contributors | Ololade, O. O., Selvarajan, R. |
Source Sets | South African National ETD Portal |
Language | English |
Detected Language | English |
Type | Dissertation |
Format | 1 online resource (xv, 148 leaves) : color illustrations, color maps, graphs, application/pdf |
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