published_or_final_version / Biological Sciences / Doctoral / Doctor of Philosophy

With the increased concern as to sustainable development in recent years, there is a need to develop a sustainable transport system as urban transportation plays an important role in cities. Transportation is an important part of daily life as it is related to mobility; and enhanced mobility will contribute to economic development and improve the quality of life. However, the most commonly used transport modes (i.e. motorised transportation) have contributed to heavy air and noise pollution, degrading our environment and affecting people’s quality of life. With this unsustainable urban transport system, there is an urgent need to apply the principles of sustainable development to the development of the transport system. The aim of this study is to revisit the general transport hierarchy, examine how the hierarchy varies according to geographical and trip characteristics, and propose new sustainable transport hierarchies that take local contexts, availability of existing infrastructures, travel distance, and income level into consideration. In this study, Hong Kong is chosen as the focus of the study despite the fact that government has already identified the heavy rail system as the backbone of Hong Kong’s transport system, and 90% of all travel trips in Hong Kong are carried out on public transport, yet there is much room for improvements, for example the high roadside air pollution, the public transport are not fully utilised, non-motorised transport modes are not widely used, and the public transport fares are on the high side. The Travel Characteristics Survey 2001 will be used for examining trip characteristic variations in Hong Kong. The findings suggest that the general transport hierarchies in Hong Kong do not match with the theoretically most sustainable transport hierarchy. Furthermore, the findings suggest that travel distance and income level have an effect on people’s choice of transport modes. The results give a better understanding of the overall sustainability of Hong Kong’s transport system and its local variations so that supportive policy can be formulated to further promote sustainable transportation based on the local characteristics, such as the availability of infrastructure, and the socio-economic and travel characteristics of residents in different districts. / published_or_final_version / Geography / Master / Master of Philosophy

A field study was conducted to determine the applicability of multivariate geostatistical methods to the problem of estimating and simulating pesticide concentrations in groundwater from measured concentrations of nitrate and pesticide, when pesticide is undersampled. Prior to this study, no published attempt had been made to apply multivariate geostatistics to groundwater contamination. The study was divided into two complementary aspects of geostatistics: estimation and simulation. The use of kriging and cokriging to estimate nitrate and the herbicide dimethyl tetrachloroterepthalate (DCPA) contaminant densities is described in Chapter I. Measured concentrations of nitrate and the DCPA were obtained for 42 wells in a shallow unconfined alluvial and basin-fill aquifer in a 16.5 km² agricultural area in eastern Oregon. The correlation coefficient between log(nitrate) and log(DCPA) was 0.74. Isotropic, spherical models were fitted to experimental direct- and cross-semivariograms with correlation ranges and sliding neighborhoods of 4 km. The relative gain for estimates obtained by cokriging ranged from 14 to 34%. Additional sample locations were selected for nitrate and DCPA using the fictitious point method. A simple economic analysis demonstrated that additional nitrate samples would be more beneficial in reducing estimation variances than additional DCPA samples, unless the costs of nitrate and DCPA analysis were identical. These estimates are by definition, the Best Linear Unbiased Estimates (i.e., the estimates with minimized estimation variance), however the requirement of minimized variance smoothes the variability of contaminant values. The application of conditional simulations to groundwater contamination is described in Chapter 11. Conditional simulation allows the degree of fluctuation of nitrate and DCPA between sample points to be assesed. With knowledge of both the 'best' estimates and the of the variability between sample points, nitrate and DCPA groundwater contamination in the study area can be characterized Based on the semivariogram models found in Chapter I, univariate and multivariate conditional simulations of nitrate and DCPA were generated using the turning bands method and the kriging or cokriging system. Kriging was used to condition the univariate simulations, while cokriging was used to cross-correlate and condition the multivariate simulations. The mean of 25 conditional and coconditional simulations at 8 different locations in the study area were generated and compared to kriging and cokriging estimates and 95% confidence intervals. Both conditional and coconditional simulation of the DCPA and nitrate contaminant densities showed large variations when values in different simulations were compared. The fluctuation in values demonstrate the uncertainties in the contaminant distributions when sample sizes are small. As a result of this unkown component, simulated values vary widely. Coconditional simulation displayed the cross-correlation imposed by using the cokriging system to condition the simulations. After 25 simulations, the mean remained unstable indicating that more simulations would be required to enable comparisons with kriging and cokriging estimates. / Graduation date: 1989

As a first step in understanding the chemistry of toxic elements in sludged soil, this thesis presents a comprehensive model of their chemistry in the digester. A review of the literature had shown that heavy metals were likely to be held in 3 pools: as precipitated and detrital mineral phases 'Particulate'; as complexes with the flocculated biomass 'Biofloc'; and as complexes in solution 'Soluble'. A simple pragmatic fractionation procedure has been offered to separate these 3 pools based on their physical properties in water. A mass-balance between the pools showed that the 'Particulate' fraction held only 5-16% of the heavy metals but contained them in the highest concentration. The 'Biofloc' held 82-94% of the heavy metals. The 'Particulate' material was subdivided by density separation and examined by a combination of analytical SEM and XRD. Thirty-four minerals were identified by XRD, many of which were detrital. Secondary precipitates on the surface of detrital minerals were revealed by the SEM; of these only the sulphides were found to contain detectable levels of heavy metals. Eleven minerals were identified in the 'Biofloc', of which most were clays. The fractionation scheme defined 2 fractions that could hold heavy metals by complexation. The 'Soluble' had a CEC of 8.8 meq/gm and the 'Biofloc' 4 meq/gm. Complexation by the heavy metals and a few other important cations was measured. A thermodynamic model was built which describes the possible solution species, mineral phases and complexation by the biomass in terms of a set of 33 primary components. This model was solved by computer for an 'average' sludge based on published analyses, and considered 313 solution species, 42 exchange reactions and 129 possible minerals. The predicted speciation was broadly in line with observations and suggested that the majority of the heavy metals separating with the 'Biofloc' would have been held as fine enmeshed sulphide precipitates. The model may be used with existing programs such as MINEQL and GEOCHEM. Preliminary studies have shown that with a few additions the model may be used to describe the heavy metals in sludged soil.

This problem includes, first, the isolation and identification of microorganisms which utilized the hydrocarbon insecticide as a sole source of carbon and energy; second, a determination of the effect on plants sprayed with the hydrocarbon medium as compared with the effect on plants sprayed with the hydrocarbon medium containing a good growth of hydrocarbon-utilizers; and third, a determination of the ability of laboratory stock cultures of organisms to utilize or remain alive in the hydrocarbon medium.

Call number: LD2668 .T4 1986 V53 / Master of Science / Chemistry

A research report submitted to the Faculty of Humanities University of the Witwatersrand In partial fulfilment of the requirements for the degree of Masters of Arts in Organisational Psychology 2016 / Recent environmental awareness has led to an expanding interest surrounding environmental consciousness and a greater social shift world over towards energy efficiency and the sustainability of technologies and resources. Consequently, there has been the development of sustainable technologies within the automobile industry including that of hybrid electric vehicles (HEVs). With the development of these technologies, it becomes necessary to investigate the factors that underpin the use and adoption of them within our society, so as to ensure their greater diffusion, use and adoption. In this light, this study aimed to investigate the factors that function in predicting the Intention to Adopt the sustainable technology of HEVs. This has been investigated in accordance with the constructs of the Unified Theory of Acceptance and Use of Technology (UTAUT) model. This model comprises the constructs of: Performance Expectancy, Effort Expectancy, Social Influence and Facilitating Conditions. This study also intended to examine these constructs and determine whether they are moderated by the constructs of Pro-Environmental Behaviour and Dispositional Resistance to Change in predicting the Intention to Adopt HEVs. The sample for this study was comprised of 133 final year Law students from the University of the Witwatersrand. The adapted UTAUT Scale, the adapted Dispositional Resistance to Change Scale and the Pro-Environmental Scale were utilised as the measures within this study. Several subscales of the UTAUT Scale as well as the Pro-Environmental Behaviour (PEB) Scale had low Internal Consistency Reliabilities within both the Pilot and Main study. However, the researcher chose to run the analyses taking this into consideration. Several subscales of the UTAUT Scale as well as the Dispositional Resistance to Change (DRC) Scale had acceptable levels of Internal Consistency Reliabilities for use in conducting analyses. Multiple regression equations and moderated multiple regression equations were run in order to investigate the effects of these constructs in predicting the Intention to Adopt HEVs. The results drawn from this study illustrated that there was a positive, significant effect of two questions concerning lifestyle factors and a reduced taxed levy of the construct Facilitating Conditions on Intention to Adopt HEVs. The results also showed that the constructs of PEB and DRC had no direct moderating influence on Intention to Adopt HEVs. / MT2017

A research report submitted to the Faculty of Science, University of the Witwatersrand, Johannesburg, in partial fulfillment of the requirement for the degree of Master of Science (Environmental Sciences) at the School of Geography, Archaeology & Environmental Studies March 2017 / Accurate estimates and mapping of grass quality is important for effective rangeland management. The purpose of this research was to map different grass species as well as nutrient Phosphorus (P) and Sodium (Na) concentration across grass communities using Sentinel-2 imagery in Telperion game reserve. The main objectives of the study were to: map the most common grass communities at the Telperion game reserve using Sentinel-2 imagery using artificial neural network (ANN) classifier and to evaluate the use of Sentinel-2 (MSI) in quantifying grass phosphorus and sodium concentration across different grass communities. Grass phosphorus and sodium concentrations were estimated using Random Forest (RF) regression algorithm, normalized difference vegetation index (NDVI) and the simple ratios (SR) which were calculated from all two possible band combination of Sentinel-2 data. Results obtained demonstrated woody vegetation as the dominant vegetation and Aristida congesta as the most common grass species. The overall classification accuracy = 81%; kappa =0.78 and error rate=0.18 was achieved using the ANN classifier. Regression model for leaf phosphorus concentration prediction both NDVI and SR data sets yielded similar results (R2 =0.363; RMSE=0.017%) and (R2 =0.36 2; RMSE=0.0174%). Regression model for leaf sodium using NDVI and SR data sets yielded dissimilar results (R2 =0.23; RMSE=16.74 mg/kg) and (R2 =0.15; RMSE =34.08 mg/kg). The overall outcomes of this study demonstrate the capability of Sentinel 2 imagery in mapping vegetation quality (phosphorus and sodium) and quantity. The study recommends the mapping of grass communities and both phosphorus and sodium concentrations across different seasons to fully understand the distribution of different species across the game reserve as well as variations in foliar concentration of the elements. Such information will guide the reserve managers on resource use and conservation strategies to implement within the reserve. Furthermore, the information will enable conservation managers to understand wildlife distribution and feeding patterns. This will allow integration of effective conservation strategies into decisions on stocking capacity. / MT 2017

A thesis submitted to the Faculty of Science, University of the Witwatersrand, Johannesburg, in fulfilment of the requirements for the degree of Doctor of Philosophy in Chemistry. Johannesburg, 2013 / Unable to load abstract.

A research report submitted to the Faculty of Science, University of the Witwatersrand, Johannesburg, in partial fulfilment of the requirements for the degree of Master of Science. 5 June 2017 in Johannesburg / Global climate change and its related actual and potential impacts to society has called for studies that look to the past to better understand historical climate trends and how they may inform future climate trends. Specific in this area of research is environmental histories, wherein information on historical climate events and disasters are retrieved from historical documentary sources, i.e. archives, in order to study the potential causes and effects of these occurrences, as well as levels of vulnerability and resilience through the analysis of coping and adaptation strategies of societies. / MT 2017