M. Tech. Environmental Health / Particulate Matter (PM) is a complex, heterogeneous mixture of smoke, soot, dust, salt, acids, and metals. Particulate Matter varies in concentration, size, chemical composition, surface area and sources of origin. Given the known ambient particulate pollution problem, the potential health risks posed by PM to the population of eMbalenhle are unknown. eMbalenhle (the study area) is a township located in Mpumalanga Province, about 12 km from Secunda. The area is surrounded by industries, power stations and mines, all of which are recognised emitters of PM. The main aim of this study was to assess the health risks posed by ambient PM10 exposure to the population of eMbalenhle.

The Port of Durban is a resource utilised by a wide range of stakeholders. The water quality of this resource is a prerequisite for sustaining the preferred uses of the bay for future generations. Given the extent of development in the port the abundance of fauna and flora is remarkable. Based on the current literature available the management of the port uses a combination of international and local standards to manage the water resource. An associated problem however is that the local legislation does not address the heart of the pollution problem - the polluter. This is highlighted in all chapters of this thesis, as the South African water quality guidelines are not legally enforceable, and do not take into account the combined use of resources. The uncontrolled nutrient loads and pollution present in the port system could ultimately affect the ecosystem health. This is amplified by apparent inability of officials to protect the receiving environment of the Port of Durban. The subsequent condition of water quality in the port compared with the Department of Water Affairs guidelines indicates that there is less than 5% compliance with the target water quality variables. in comparing the same water quality to international water quality Legislation the compliance percentage increased marginally, however the bacterial contamination and nutrient contamination of the resource is apparent even with more relaxed international comparisons. The noticeable cause was clearly evident when comparing results, indicating extensive unacceptable bacterial and nutrient contamination emanating from stormwater systems from the city of Durban, and highly urbanised river catchments. Based on the water quality results it is highly recommended that sustainable environmental management practices be implemented to protect and address the water resource. The metropolitan authorities need to investigate the origins of the stormwater pollution and dialogue must ensue between Portnet and the City to reach consensus on receiving water quality objectives with the aim of compiling a water management policy. / Thesis (M.A.)-University of Natal, Durban, 2001.

When mining activities in some parts of the Witwatersrand were discontinued in 2000, the defunct workings started to flood. In September 2002 the mine water started to decant from the West Rand Mine Basin (WRB) next to the Tweelopie East Stream. Treated water is currently used in the mine's metallurgical plants and 15Ml per day of treated water is disposed firstly into the Cooke Attenuation Dam and then discharged into the Wonderfonteinspruit. The aim of this study was to find and provide remediation measures as a result of acid mine drainage and other impacting factors on the water quality and volume in the Wonderfonteinspruit. Conductivity and total dissolved solids (TDS) were highest at the point where the tailings dam leached into the Wonderfonteinspruit. Sulphate was very high as was expected due to acid mine drainage. The best way to treat the high sulphate levels is with sulphate-reducing bacteria. To avoid the fatal flaw of many other constructed wetlands, a continuous carbon source is provided to the bacteria in the form of activated sewage from the Flip Human sewage treatment plant. Iron and other heavy metals are being precipitated through oxidation reactions to form oxides and hydroxides from the aerobic cell in the wetland. The wetlands are also known for their ability to reduce nitrate and microbial values with great success. In the remediation, four elements that currently do not comply with the SABS criteria for class 0 water, were chosen for improvement: conductivity, dissolved solids, sulphate and iron. Conductivity falls within class 1 and has a maximum of 178 mS/m @25ºC that should be reduced to under 70 mS/m. Total dissolved solids have a value of 1585 mg/l, which is much higher than the prescribed 450 ml/l, making it class 2 water. The last two problematic elements are both considered as class 2 water: sulphate peaks at 592 mg/l where the preferred value is 200 mg/l, and iron should be 0.01 mg/l, not the staggering 0.3mg/l. iv Alternative mitigation methods were identified and analysed for the impacts of the five major contaminators and ultimately the solution comes down to constructed wetlands. This is not a straightforward solution, however, and a specific design to accommodate all the different pollutants and water quality ranges was proposed. The other mitigation methods include a cut-off trench and pump-back system for the tailings dam, as well as the implementation of a monitoring programme. The sewage works should be optimised and better managed. Both the settlement and agricultural sector need to be educated on their representative impacts on the environment and government assistance should be available. / ENVIRONMENTAL SCIENCES / MSC (ENVIRON MANAGEMENT)

M.Sc. (Environmental Management) / The use of atmospheric dispersion models to predict ground level pollutants concentrations has been on an increase in South Africa in the last decade. At this stage National Department of Environmental Affairs has published a draft document to provide guidelines on the type or use of models. Most Air Quality Specialists in the country make use of the United States Environmental Protection Agency approved atmospheric dispersion models to conduct air quality investigations. These models were developed in the United States of America after having considered the environmental set up and monitoring capabilities. In light of the above, much of the required input data are not readily available and calculations have been conducted to make up for the shortfall. For domestic emissions, quantifying the emissions factors is proving to be a challenge for modellers. They calculate emissions factors using different data sets from variable sources – sometimes the data are not up to date. This variability could potentially compromise the output of the model. This study aim was to model domestic emissions from an isolated rural township, Leandra, in the Mpumalanga Province – located within a nationally declared Highveld air quality management priority area – for two one month periods – in both the winter – July 2008 – and the summer – October 2008. This was achieved by using a United States Environmental Protection Agency approved AERMOD atmospheric dispersion model. Hourly surface measured meteorology data were obtained from the Langverwacht ambient air quality monitoring station and upper air data from the Irene monitoring station. The data were screened for any suspect values, formatted and then pre-processed by AERMET to be used by AERMOD. The study also investigated and compared the modelled time-series and monitored time-series data. This study calculated the effective emissions rate of 0.3 g PM10 s-1 m-2 by using a combination of monitored hourly PM10 concentrations and dispersion modelling time series data, for a typical Highveld township. Furthermore, the study revealed that, during winter when air is stagnant, Leandra was demonstrably isolated from other emissions sources of strength in the region – i.e. power station and domestic emissions were the dominant emissions sources. Under these circumstances, indoor and outdoor emissions were above the acceptable standards – i.e. they constituted unhealthy ambient air conditions. During summer – with the higher average wind speeds – Leandra was under the influence of industrial sources and the argument of isolation was not valid.

MESCH / Department of Hydrology and Water Resources

Thesis (M.Sc. (Zoology) -- University of Limpopo, 2019 / The Olifants River is one of the major river systems in South Africa, providing water for industries, mines, agricultural and domestic activities. Consequently, the river has turned out to be one of the most polluted rivers in South Africa. The Blyde River is an important tributary of the Olifants River, known for its continuous flow and good water quality. However, the recent increase in human activities such as, commercial agricultural and large-scale forestry practices in the catchment may have a negative impact on the quality of the water, which may consequently affect the aquatic biota community structure. The aim of the study was to assess the water and sediment quality of the Blyde River using aquatic macroinvertebrates as bioindicators and the South African Scoring System version 5 (SASS5) protocol was followed. Seven sampling sites were selected at Blyde River and five samples were collected per site. Collected macroinvertebrates were identified to family level and classified according to their tolerance levels to pollution at the University of Limpopo Biodiversity Laboratory. In addition, seasonal readings of the physico-chemical parameters such as, pH, dissolved oxygen (DO), temperature, salinity, total dissolved solutes (TDS) and electrical conductivity (EC) were recorded in situ using YSI Model 554 Datalogger with a 4 m multiprobe and a Mettler Toledo SevenGo™. Most of the physico-chemical parameters recorded at Blyde River were within the South African water quality guidelines for aquatic ecosystems. Metals such as, As, Al, Ba, B, Cd, Cr, Co, Cu, Fe, Pb, Mn, Ni, Se, Ag, Sr, Sn, Ti, V, and Zn were tested from the water column, sediments and macroinvertebrate tissue. Almost all the metals analysed from the water column and sediments were within the quality guidelines. Out of the twenty tested metals, As, Ag, Cu, and Zn exceeded the recommended quality guidelines in the water column at some sites. Only As, Cr and Cu exceeded the recommended quality guidelines in the sediments. The most abundant macroinvertebrates were from the orders Ephemeroptera, Diptera, and Trichoptera at all sites. There was a similar macroinvertebrate community structure across the sites, supported by the positive correlation analysis among the sites (r > 0.4). Wildlife Estate and Wildrivers Estate had the highest and lowest numbers of sensitive macroinvertebrates respectively. The highest percentage of iv sensitive macroinvertebrate taxa was recorded in winter and the highest percentage of tolerant species was recorded in summer. This was also supported by the SASS indices, the SASS score, number of taxa and average score per taxon (ASPT) were highest in winter, followed by autumn, spring and lowest in summer. The overall SASS indices showed that the water quality condition at most of the sites at Blyde River could be considered as good. All the seven sites on average fell under ecological band A and B, except for the Wildrivers Estate, thus, the water quality status of the river could be described as unmodified and largely natural with few modifications. / VLIR

The deteriorating air quality in Cape Town (CT) is a threat to the social and economic development of the city. Although previous studies have shown that most of the pollutants are emitted in the city, it is not clear how the transport of pollutants from neighbouring cities may contribute to the pollution. This thesis studies the transport of atmospheric nitrogen oxides (NOx) and nitric acid (HNO3) pollutants over South Africa and examines the role of pollutant transport from the Mpumalanga Highveld on pollution in CT. The study analysed observation data (2001 - 2008) from the CT air quality network and from regional climate model simulation (2001 - 2004) over South Africa. The model simulations account for the influences of complex topography, atmospheric conditions, and atmospheric chemistry on transport of the pollutants over South Africa. Flux budget analysis was used to examine whether the city is a net source or sink for NOx and HNO3. The results show that north-easterly flow transports pollutants (NOx and HNO3) at low level (i.e., surface to 850 hPa) from the Mpumalanga Highveld towards CT. In April, a tongue of high concentration of HNO3 extends from the Mpumalanga Highveld to CT, along the southern coast. The flux budget analysis shows that CT can be a net sink for NOx and HNO3 during extreme pollution events. The study infers that, apart from the local emission of the pollutants in CT, the accumulation of pollutants transported from other areas may contribute to pollution in the city. / Environmental Sciences / M. Sc. (Environmental Science)

The deteriorating air quality in Cape Town (CT) is a threat to the social and economic development of the city. Although previous studies have shown that most of the pollutants are emitted in the city, it is not clear how the transport of pollutants from neighbouring cities may contribute to the pollution. This thesis studies the transport of atmospheric nitrogen oxides (NOx) and nitric acid (HNO3) pollutants over South Africa and examines the role of pollutant transport from the Mpumalanga Highveld on pollution in CT. The study analysed observation data (2001 - 2008) from the CT air quality network and from regional climate model simulation (2001 - 2004) over South Africa. The model simulations account for the influences of complex topography, atmospheric conditions, and atmospheric chemistry on transport of the pollutants over South Africa. Flux budget analysis was used to examine whether the city is a net source or sink for NOx and HNO3. The results show that north-easterly flow transports pollutants (NOx and HNO3) at low level (i.e., surface to 850 hPa) from the Mpumalanga Highveld towards CT. In April, a tongue of high concentration of HNO3 extends from the Mpumalanga Highveld to CT, along the southern coast. The flux budget analysis shows that CT can be a net sink for NOx and HNO3 during extreme pollution events. The study infers that, apart from the local emission of the pollutants in CT, the accumulation of pollutants transported from other areas may contribute to pollution in the city. / Environmental Sciences / M. Sc. (Environmental Science)

Thesis (MScEng)--University of Stellenbosch, 2000. / ENGLISH ABSTRACT: Air pollution is a major concern III the Cape Metropole. A major contributor to the air pollution problem is road transport. For this reason, a national vehicle emissions study is in progress with the aim of developing a national policy regarding motor vehicle emissions and control. Such a policy could bring about vehicle emission control and regulatory measures, which may have far-reaching social and economic effects. Air pollution models are important tools 10 predicting the effectiveness and the possible secondary effects of such policies. It is therefore essential that these models are fundamentally sound to maintain a high level of prediction accuracy. Complex air pollution models are available, but they require spatial, time-resolved information of emission sources and a vast amount of processing power. It is unlikely that South African cities will have the necessary spatial, time-resolved emission information in the near future. An alternative air pollution model is one that is based on the Gaussian Plume Model. This model, however, relies on gross simplifying assumptions that affect model accuracy. It is proposed that statistical and mathematical analysis techniques will be the most viable approach to modelling air pollution in the Cape Metropole. These techniques make it possible to establish statistical relationships between pollutant emissions, meteorological conditions and pollutant concentrations without gross simplifying assumptions or excessive information requirements. This study investigates two analysis techniques that fall into the aforementioned category, namely, Non-linear Time Series Analysis (specifically, the method of delay co-ordinates) and Singular Spectrum Analysis (SSA). During the past two decades, important progress has been made in the field of Non-linear Time Series Analysis. An entire "toolbox" of methods is available to assist in identifying non-linear determinism and to enable the construction of predictive models. It is argued that the dynamics that govern a pollution system are inherently non-linear due to the strong correlation with weather patterns and the complexity of the chemical reactions and physical transport of the pollutants. In addition to this, a statistical technique (the method of surrogate data) showed that a pollution data set, the oxides of Nitrogen (NOx), displayed a degree of non-linearity, albeit that there was a high degree of noise contamination. This suggested that a pollution data set will be amenable to non-linear analysis and, hence, Non-linear Time Series Analysis was applied to the data set. SSA, on the other hand, is a linear data analysis technique that decomposes the time series into statistically independent components. The basis functions, in terms of which the data is decomposed, are data-adaptive which makes it well suited to the analysis of non-linear systems exhibiting anharmonic oscillations. The statistically independent components, into which the data has been decomposed, have limited harmonic content. Consequently, these components are more amenable to prediction than the time series itself. The fact that SSA's ability has been proven in the analysis of short, noisy non-linear signals prompted the use of this technique. The aim of the study was to establish which of these two techniques is best suited to the modelling of air pollution data. To this end, a univariate model to predict NOx concentrations was constructed using each of the techniques. The prediction ability of the respective model was assumed indicative of the accuracy of the model. It was therefore used as the basis against which the two techniques were evaluated. The procedure used to construct the model and to quantify the model accuracy, for both the Non-linear Time Series Analysis model and the SSA model, was consistent so as to allow for unbiased comparison. In both cases, no noise reduction schemes were applied to the data prior to the construction of the model. The accuracy of a 48-hour step-ahead prediction scheme and a lOO-hour step-ahead prediction scheme was used to compare the two techniques. The accuracy of the SSA model was markedly superior to the Non-linear Time Series model. The paramount reason for the superior accuracy of the SSA model is its adept ability to analyse and cope with noisy data sets such as the NOx data set. This observation provides evidence to suggest that Singular Spectrum Analysis is better suited to the modelling of air pollution data. It should therefore be the analysis technique of choice when more advanced, multivariate modelling of air pollution data is carried out. It is recommended that noise reduction schemes, which decontaminate the data without destroying important higher order dynamics, should be researched. The application of an effective noise reduction scheme could lead to an improvement in model accuracy. In addition to this, the univariate SSA model should be extended to a more complex multivariate model that explicitly encompasses variables such as traffic flow and weather patterns. This will explicitly expose the inter-relationships between the variables and will enable sensitivity studies and the evaluation of a multitude of scenarios. / AFRIKAANSE OPSOMMING: Die hoë vlak van lugbesoedeling in die Kaapse Metropool is kommerwekkend. Voertuie is een van die hoofoorsake, en as gevolg hiervan word 'n landswye ondersoek na voertuigemissie tans onderneem sodat 'n nasionale beleid opgestel kan word ten opsigte van voertuigemissie beheer. Beheermaatreëls van so 'n aard kan verreikende sosiale en ekonomiese uitwerkings tot gevolg hê. Lugbesoedelingsmodelle is van uiterste belang in die voorspelling van die effektiwiteit van moontlike wetgewing. Daarom is dit noodsaaklik dat hierdie modelle akkuraat is om 'n hoë vlak van voorspellingsakkuraatheid te handhaaf. Komplekse modelle is beskikbaar, maar hulle verg tyd-ruimtelike opgeloste inligting van emmissiebronne en baie berekeningsvermoë. Dit is onwaarskynlik dat Suid-Afrika in die nabye toekoms hierdie tydruimtelike inligting van emissiebronne gaan hê. 'n Alternatiewe lugbesoedelingsmodel is dié wat gebaseer is op die "Guassian Plume". Hierdie model berus egter op oorvereenvoudigde veronderstellings wat die akkuraatheid van die model beïnvloed. Daar word voorgestel dat statistiese en wiskundige analises die mees lewensvatbare benadering tot die modellering van lugbesoedeling in die Kaapse Metropool sal wees. Hierdie tegnieke maak dit moontlik om 'n statistiese verwantskap tussen besoedelingsbronne, meteorologiese toestande en besoedeling konsentrasies te bepaal sonder oorvereenvoudigde veronderstellings of oormatige informasie vereistes. Hierdie studie ondersoek twee analise tegnieke wat in die bogenoemde kategorie val, naamlik, Nie-lineêre Tydreeks Analise en Enkelvoudige Spektrale Analise (ESA). Daar is in die afgelope twee dekades belangrike vooruitgang gemaak in die studieveld van Nie-lineêre Tydreeks Analise. 'n Volledige stel metodes is beskikbaar om nie-lineêriteit te identifiseer en voorspellingsmodelle op te stel. Dit word geredeneer dat die dinamika wat 'n besoedelingsisteem beheer nie-lineêr is as gevolg van die sterk verwantskap wat dit toon met weerpatrone asook die kompleksiteit van die chemiese reaksies en die fisiese verplasing van die besoedelingstowwe. Bykomend verskaf 'n statistiese tegniek (die metode van surrogaatdata) bewyse dat 'n lugbesoedelingsdatastel, die okside van Stikstof (NOx), melineêre gedrag toon, alhoewel daar 'n hoë geraasvlak is. Om hierdie rede is die besluit geneem om Nie-lineêre Tydreeks Analise aan te wend tot die datastel. ESA daarenteen, is 'n lineêre data analise tegniek. Dit vereenvoudig die tydreeks tot statistiese onafhanklike komponente. Die basisfunksies, in terme waarvan die data vereenvoudig is, is data-aanpasbaar en dit maak hierdie tegniek gepas vir die analise van nielineêre sisteme. Die statisties onafhanklike komponente het beperkte harmoniese inhoud, met die gevolg dat die komponente aansienlik makliker is om te voorspel as die tydreeks self. ESA se effektiwitiet is ook al bewys in die analise van kort, hoë-graas nie-lineêre seine. Om hierdie redes, is ESA toegepas op die lugbesoedelings data. Die doel van die ondersoek was om vas te stel watter een van die twee tegnieke meer gepas is om lugbesoedelings data te analiseer. Met hierdie doelwit in sig, is 'n enkelvariaat model opgestel om NOx konsentrasies te voorspel met die gebruik van elk van die tegnieke. Die voorspellingsvermoë van die betreklike model is veronderstelom as 'n maatstaf van die model se akkuraatheid te kan dien en dus is dit gebruik om die twee modelle te vergelyk. 'n Konsekwente prosedure is gevolg om beide die modelle te skep om sodoende invloedlose vergelyking te verseker. In albei gevalle was daar geen geraasverminderings-tegnieke toegepas op die data nie. Die akuraatheid van 'n 48-uur voorspellingsmodel en 'n 100-uur voorspellingsmodel was gebruik vir die vergelyking van die twee tegnieke. Daar is bepaal dat die akkuraatheid van die ESA model veel beter as die Nie-lineêre Tydsreeks Analise is. Die hoofrede vir die ESA se hoër akkuraatheid is die model se vermoë om data met hoë geraasvlakke te analiseer. Hierdie ondersoek verskaf oortuigende bewyse dat Enkelvoudige Spektrale Analiese beter gepas is om lugbesoedelingsdata te analiseer en gevolglik moet hierdie tegniek gebruik word as meer gevorderde, multivariaat analises uitgevoer word. Daar word aanbeveel dat geraasverminderings-tegnieke, wat die data kan suiwer sonder om belangrike hoë-orde dinamika uit te wis, ondersoek moet word. Hierdie toepassing van effektiewe geraasverminderings-tegniek sal tot 'n verbetering in model-akkuraatheid lei. Aanvullend hiertoe, moet die enkele ESA model uitgebrei word tot 'n meer komplekse multivariaat model wat veranderlikes soos verkeersvloei en weerpatrone insluit. Dit sal die verhoudings tussen veranderlikes ten toon stel en sal sensitiwiteit-analises en die evaluering van menigte scenarios moontlik maak.

Introduction Run-off from Johannesburg mine dumps is a source of environmental pollution and a public health concern. This study focussed on assessing and developing remediation strategies for Manuel Street Park (MSP) that has been affected by run-off from the Princess Mine dump. Study objectives were threefold: to use a survey involving residents living around MSP to determine community use and perception of rehabilitation of the Park; to determine the impact of the addition of a preparation known as “Effective Micro-organisms” (EM®) to polluted Park soil and; to prepare a remediation plan for this Park. Methodology A qualitative survey was conducted amongst users of the park as to their use and perceptions of rehabilitation of the park and their understanding of mine-related pollution and acid mine drainage. Controlled greenhouse trials were conducted to determine optimal germination and growth of Pennisetum clandestinum (Kikuyu grass) in Park soil, with and without EM® or compost. A landscaper was consulted to collate research results to facilitate park rehabilitation. Results Survey participants understood the risks of Acid Mine Drainage (AMD) and other mine pollution and gave valuable information which assisted in understanding local issues concerning the park. Tests with soil polluted with AMD showed that it promoted seed germination while treatment of park soil with fertiliser, compost and enhanced microorganisms improved plant development and growth. Practically, it was determined that the use of EM1 at the park would be difficult because of on-going flooding of the park with contaminated water. For this reason, an improved drainage plan was suggested, along with raised walkways. Conclusion A remediation plan can be implemented on site involving installation of French drains, raised walkways, and soil remediation involving EM® / Agriculture, Animal Health and Human Ecology / M. Sc. (Environmental Management Ornamental Horticulture)