Thesis (Ph.D)(Soil Mineralogy) --University of the North, 2004. / This research study focuses on environmental mining impact of soils around the abandoned Kgwakgwe Mn mine in Botswana. The thesis contains five chapters: introduction, methods and analytical techniques, results, interpretation and discussions, and conclusions. The physico-chemical properties, mineralogical identification and characterisation and chemical properties of soils and related geological materials as well as the chemical properties of the soils and leaves of plants around the abandoned mine were investigated in order to determine the mining impact on the surrounding soils. It mentions field research components, which included observation and sampling of surface soils, related geological materials and leaves of plants for different laboratory analyses. Methods, techniques and instrumentation for physico-chemical, mineralogical and chemical analyses are explained. Physico-chemical properties studied on soil samples included particle size distribution (PSD), pH, electrical conductivity (EC), soil colour, and descriptive petrography. Identification of minerals contained in soil samples which included both < 53 μm and < 4 μm size fractions were performed employing X-ray powder diffraction (XRPD) techniques. The < 4 μm size fractions of soil samples were further characterised using the environmental scanning electron microscope (ESEM) to which was fitted with an X-ray energy dispersive spectrometer (EDS). Chemical analyses for iron (Fe) and manganese (Mn) concentration levels in soil and leaf samples were measured with the flame atomic absorption spectrometer (FAAS). Determination of exchangeable bases (Na, K, Ca and Mg), cation echange capacity (CEC) and percent base saturation, viii P, Cl, SO4 and CO3 concentrations were performed only on the soil samples. The exchangeable bases, CEC and percent base saturation were determined using the ammonium acetate method which included flame photometry for K and Na, and AAS for Ca and Mg. The Olsen method was applied to determine P concentrations. Furthermore analyses for Cl and SO4 were done using ion chromatography, whereas the calcimeter was used to determine CO3 concentrations. A Quickbird 2.4 m – 2.8 m resolution with zero cloud cover multispectral standard imagery of the study area was processed to characterise the vegetation cover. The laboratory results were processed using Geographical Information Systems (GIS), and Remote Sensing (RS) techniques with the integrated Land and Water Information System (ILWIS), Geosoft Oasis Montaj and ArcGIS software packages. Microsoft Excel was used for statistical and graphical presentation of data analyses. The particle size distribution of soil samples revealed the average wt % of the soil fractions as follows: the < 4 μm fraction was between o.3 wt % and 30.58 wt %, and the < 53 μm fraction was between 11.05 wt % and slightly above 100 wt %. Soil pH ranged from 2.92 to 7.26 with very acidic soils located close to the mine workings. Electrical conductivity values were significantly low, and the range was from 49.1 μScm- 1 to 123.5 μScm- 1 . Dark brown to reddish brown soil colour was indicative of very high Fe and Mn levels in the soils. Bulk soil samples consisted of quartz, SiO2; haematite, Fe2O3; goethite, Fe+3O(OH); bixbyte, Mn2O3; braunite, Mn+2Mn6 +3SiO12 ramsdellite, MnO2; pyrolusite, MnO2; cryptomelane, K2-xMn8O16; sanidine, K(Si3Al)O8; microcline, KAlSi3O8; whereas the < 4 μm ix fraction was made up of kaolinite, Al2Si2O5(OH)4 illite, KAl2Si3AlO10(OH)2; and muscovite KAl2Si3AlO10(OH)2. The range of concentration levels of Fe in soils was from 1116 μg g-1 to 870766 μg g-1 with a mean of 17593 μg g-1 and for Mn in soils was 35 μg g-1 to 24907 μg g-1 with a mean of 1088 μg g-1. The values for Na concentration in the soil samples ranged from 0.1 cmolckg-1 to 89.1 cmolckg-1, with a mean of 0.44 cmolckg-1, and for K concentration in the soil samples values ranged from 0.1 cmolckg-1 to 163.6.1 cmolckg-1, with a mean of 0.82 cmolckg-1. The values for Ca concentration in the soil samples ranged from 0.3 cmolckg-1 to 1139 cmolckg-1, with a mean of 5.68 cmolckg-1, and values for Mg concentration in the soil samples ranged from 0.3 cmolckg-1 to 1655.3 cmolckg-1, with a mean of 8.26 cmolckg-1. The CEC values in the soil samples from the study area ranged from 1.1 cmolckg-1 to 29.2 cmolckg-1, with a mean of 8.2 cmolckg-1, and values for percent base saturation in the soil samples were from 33.77% to 100 % with a mean of 82.10 % cmolckg-1. Values obtained for P2O5 in some randomly chosen soil samples from the study area were from 0.51 mgkg-1 to 6.02 mgkg-1. The values for Cl concentration in the soil samples ranged from 0.2 mgkg-1 to 11.9 mgkg-1, with a mean of 7.63 mgkg-1, and for SO4 concentration in the soil samples values ranged from 2.1 mgkg-1 to 47.5 mgkg-1, with a mean of19.36 mgkg-1. The values for CO3 concentration (measured in terms of CaCO3 equivalent) in the soil samples ranged from 5.1 gkg-1 to 59.1 gkg-1, with a mean of 40.98 gkg-1. For the leaves, the range of concentration levels of Fe contained in them was from 101.2 μg g-1 to 3758 μg g-1 with a mean of 637 μg g-1 and for Mn in leaves, the range was from 26.2 μg g-1 to 3611.5 μg g-1 with a mean of x 598.4 μg g-1. The TOC values were between 0 wt % to 7.9 wt %. High acidity of soils is reflected by on-going neomineralisation activities which at some places are depicted by the formation of dead zones. Other observable phenomena were stunted growth of plants, and the yellowing of their leaves as a result of high concentrations of Fe and Mn in their organic systems. The gridded soil and vegetation maps for Fe and Mn show anomalies in different parts of the study area. Where Mn is high, the Fe is low and vice versa. Manganese was high at the mine workings and in the northwestern part of the study area. Iron on the other hand is very low in the mine working area and is high on the northern part of the study area. The mineral genesis is explained and a model is advanced for the Mn interplay in the soils and environment around the Kgwakgwe abandoned Mn oxides ore mine. Remediative measures for reclamation of the contaminated soils and appropriate land use of the area have been suggested. It is anticipated that these useful recommendations to stakeholders which have been suggested, and the direction for further research if adhered could bring solution to some of the environmental pollution problems in the study area.

Thesis (M. Sc.)--University of Hong Kong, 2005.

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A dissertation submitted to the Faculty of Science, University of the Witwatersrand, Johannesburg, in fulfilment of the requirements for the degree of Master of Science. Johannesburg, 2017. / An Environmental Impact Assessment (EIA) is an instrument used to limit unexpected and negative effects of proposed developments on the environment. Much experience has been gained internationally but the lack of follow-up after the EIA is prepared is one of the major weak spots of the assessments. It is therefore very important to follow up on development projects and observe their effects on the environment after the go-ahead has been given, so that the EIA quality may be improved. There is often a significant difference between predicted impacts and actual impacts. Sometimes the predicted impacts do not occur, or new impacts which were not predicted in the Environmental Impacts Assessment Reports (EIRs) arise. The aim of this study was to assess the accuracy of the impacts predicted in the EIRs compiled for three large-scale Eskom projects currently under execution situated in the Mpumalanga, Limpopo and KwaZulu-Natal provinces by comparing them to the actual impacts that occurred on site. The EIA follow-up process was used to assess the influence that the EIA may have on large-scale projects and ultimately assess the effectiveness of the EIA process as a whole. A procedure developed by Wilson (1998) was used to follow up on the selected projects because the method allowed for comparisons between the actual and predicted impacts to be made and for discrepancies in the EIRs to be identified. Recent audit reports, aerial photographs and interviews were all used to identify actual impact occurrence. Of the impacts which actually occurred, 91% occurred as predicted (OP) and 9% occurred but were not predicted (ONP). The majority of impacts omitted from the reports were hydrological (27%) and air quality impacts (25%). These unexpected impacts were most probably overlooked because they are site-specific, temporary in nature and would not cause any significant environmental damage. Of all the impacts predicted in the reports, 85% were accurately predicted and 15% were not. The impacts inaccurately predicted were hydrological impacts (27%), flora and fauna impacts (7%) and 30% other impacts which included soil pollution, fires and loss of agricultural potential. The inaccuracies could be a result of Environmental Impact Assessment Practitioners (EAPs) predicting a large number of impacts with the hopes of lowering the risk of omitting impacts. However, sometimes the impacts predicted do not occur in reality. Overall it can be concluded that the impact prediction accuracy of the three EIRs compiled for Eskom exceeds previous studies conducted nationally. Eskom EIRs are highly accurate with regards to impact prediction with minor discrepancies which can easily be rectified. Key words: Environmental Impacts Assessment (EIA) Environmental Impacts Assessment Reports (EIRs), Environmental Impact Assessment Practitioners (EAPs), EIA follow-up, discrepancies. / LG2017

Typescript, etc. / Digitized by Kansas Correctional Industries

Thesis (M.A.)--University of Hong Kong, 2001. / Includes bibliographical references (leaves 67-72).