Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Este trabalho teve como objetivo descrever o potencial de biossorção de lantânio pelas microalgas Ankistrodesmus sp. e Golenkinia sp. livres e pellets de alginato de cálcio, com e sem as microalgas imobilizadas, a partir de soluções aquosas. Para isso foram realizados estudos em regime batelada e em coluna de leito fixo. Modelos cinéticos de pseudo-primeira ordem e de segunda ordem e isotermas de equilíbrio de Langmuir e de Freundlich foram utilizados para a descrição quantitativa e a previsão do comportamento de adsorção do metal pelas biomassas livres e imobilizadas no sistema descontínuo. Os dados foram mais bem ajustados pelo modelo cinético de segunda ordem, com coeficientes de determinação (r2) maiores que 0,98. Foram obtidos tempos de equilibrio muito curtos, na faixa de 1-30 minutos. A isoterma de Langmuir foi a que melhor se ajustou aos dados experimentais, com valores de r2 maiores que 0,94. Foram observados valores de qmáx, isto é, a quantidade máxima de metal captado pelo biossorvente, entre 0,96 e 10,43 mmol/g. As células livres mostraram-se mais eficientes do que os pellets caracterizados com e sem os micro-organismos. Os pellets mostraram melhor potencial quando contendo microalgas imobilizadas, em comparação com eles puros. No estudo dinâmico, 12 L de solução contendo uma concentração de La (III) de 150 mmol/L ascenderam pela coluna contendo Ankistrodesmus sp. e Golenkinia sp. imobilizadas e pellets de alginato de cálcio puros durante 8 horas. No último minuto, os três biossorventes ainda apresentaram cerca de 80% de eficiência de remoção. Desta forma, o ponto de satuação não foi atingido. A rápida e alta capacidade de adsorção das microalgas revelou que sua aplicação em escala superior é possível em ambos os processos estudados, uma vez que a imobilização desses biomateriais não mudou a sua capacidade de sorção e nem o rápido contato entre o adsorvente e o soluto no processo de biossorção de lantânio / This study aimed to describe the potential of lanthanum biosorption by microalgal Ankistrodesmus sp. and Golenkinia sp. free and calcium alginate pellets with and without immobilized microalgae from aqueous solutions. To study this system in batch and fixed bed column were performed. Kinetic models of pseudo first-order and second order and equilibrium isotherms of Langmuir and Freundlich were used for the quantitative description and prediction of the behavior of metal adsorption by free and immobilized biomass in a batch system. The data were best fitted by a second-order kinetic model, with coefficients of determination (r2) values greater than 0.98. Very short equilibrium times were obtained in the range of 1-30 minutes. The Langmuir isotherm was the best fit to the experimental data, with r2 values greater than 0.94. qmax, that is, the maximum amount of metal captured by the biosorbent, values between 0.96 and 10.43 mmol/g were observed. The free cells were more efficient than with pellets characterized with and without the microorganisms. The pellets showed good potential when containing immobilized microalgae compared to pure them. In the dynamic study, 12 L of solution containing a concentration of La (III) 150 mmol/L reached by the column containing Ankistrodemsus sp. and Golenkinia sp. immobilized and pure calcium alginate pellets for 8 hours. At the end of the run, the three biosorbents still showed about 80% removal efficiency. Thus, the saturation point was not reached. The rapid and high adsorption capacity of microalgae revealed that its application in a higher scale is possible in both cases studied, since the immobilization of these biomaterials has not changed its sorption capacity or the rapid contact between the adsorbent and the solute in the process biosorption of lanthanum

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Este trabalho teve como objetivo descrever o potencial de biossorção de lantânio pelas microalgas Ankistrodesmus sp. e Golenkinia sp. livres e pellets de alginato de cálcio, com e sem as microalgas imobilizadas, a partir de soluções aquosas. Para isso foram realizados estudos em regime batelada e em coluna de leito fixo. Modelos cinéticos de pseudo-primeira ordem e de segunda ordem e isotermas de equilíbrio de Langmuir e de Freundlich foram utilizados para a descrição quantitativa e a previsão do comportamento de adsorção do metal pelas biomassas livres e imobilizadas no sistema descontínuo. Os dados foram mais bem ajustados pelo modelo cinético de segunda ordem, com coeficientes de determinação (r2) maiores que 0,98. Foram obtidos tempos de equilibrio muito curtos, na faixa de 1-30 minutos. A isoterma de Langmuir foi a que melhor se ajustou aos dados experimentais, com valores de r2 maiores que 0,94. Foram observados valores de qmáx, isto é, a quantidade máxima de metal captado pelo biossorvente, entre 0,96 e 10,43 mmol/g. As células livres mostraram-se mais eficientes do que os pellets caracterizados com e sem os micro-organismos. Os pellets mostraram melhor potencial quando contendo microalgas imobilizadas, em comparação com eles puros. No estudo dinâmico, 12 L de solução contendo uma concentração de La (III) de 150 mmol/L ascenderam pela coluna contendo Ankistrodesmus sp. e Golenkinia sp. imobilizadas e pellets de alginato de cálcio puros durante 8 horas. No último minuto, os três biossorventes ainda apresentaram cerca de 80% de eficiência de remoção. Desta forma, o ponto de satuação não foi atingido. A rápida e alta capacidade de adsorção das microalgas revelou que sua aplicação em escala superior é possível em ambos os processos estudados, uma vez que a imobilização desses biomateriais não mudou a sua capacidade de sorção e nem o rápido contato entre o adsorvente e o soluto no processo de biossorção de lantânio / This study aimed to describe the potential of lanthanum biosorption by microalgal Ankistrodesmus sp. and Golenkinia sp. free and calcium alginate pellets with and without immobilized microalgae from aqueous solutions. To study this system in batch and fixed bed column were performed. Kinetic models of pseudo first-order and second order and equilibrium isotherms of Langmuir and Freundlich were used for the quantitative description and prediction of the behavior of metal adsorption by free and immobilized biomass in a batch system. The data were best fitted by a second-order kinetic model, with coefficients of determination (r2) values greater than 0.98. Very short equilibrium times were obtained in the range of 1-30 minutes. The Langmuir isotherm was the best fit to the experimental data, with r2 values greater than 0.94. qmax, that is, the maximum amount of metal captured by the biosorbent, values between 0.96 and 10.43 mmol/g were observed. The free cells were more efficient than with pellets characterized with and without the microorganisms. The pellets showed good potential when containing immobilized microalgae compared to pure them. In the dynamic study, 12 L of solution containing a concentration of La (III) 150 mmol/L reached by the column containing Ankistrodemsus sp. and Golenkinia sp. immobilized and pure calcium alginate pellets for 8 hours. At the end of the run, the three biosorbents still showed about 80% removal efficiency. Thus, the saturation point was not reached. The rapid and high adsorption capacity of microalgae revealed that its application in a higher scale is possible in both cases studied, since the immobilization of these biomaterials has not changed its sorption capacity or the rapid contact between the adsorbent and the solute in the process biosorption of lanthanum

The aim of this thesis is to demonstrate how a subsidiary of a multi-national corporation (MNC) achieved a social licence, in a Sub-Saharan host country undergoing agrarian transformation. Several foreign companies lost their land to communities in the wake of land conflicts between the legal owners and surrounding communities. However, this is a case of one of a few big landowners that have survived and continued to operate, without suffering substantial vandalism from communities. The study argues this to be an instrumental case of achieving and maintaining a social licence in a context characterised by heighted resource nationalism sentiments. Extant literature acknowledges that communities’ expectations are rising, rendering a legal licence insufficient. Emphasis is on the need for firms reliant on finite natural resources, such as land, to seek a social licence from communities. Yet, the processes through which such a licence could be achieved and maintained are little understood. The social licence is conceptually and theoretically underdeveloped. Anchoring on legitimacy theory, this study looks across two literatures on social licence and corporate community engagement. It empirically demonstrates how and under what conditions corporate community engagement processes deliver phases of a social licence. An embedded case study is utilised to capture processes from the perspective of both the firm and the community. The study advances theory of social licence by exploring the processes of an instrumental firm in an understudied but critical agriculture industry. The study identified transactional, transitional and transformational engagement processes, as essential in building legitimacy and trust which are the basis of dynamic phases of social licence. The researcher proposes three new constructs: context specific community expectations, engagement legitimacy, and corporate community visibility, to advance scholarship on social licencing processes. The study distinguishes firm legitimacy from engagement legitimacy. This paves way for future studies to further develop these concepts in social licence process research. Managers in agriculture and other extractive firms will use the theory built from this study to understand how they can achieve social licence at various levels, thereby mitigating the high social risk associated with losing a social licence. / Thesis (DPhil)--University of Pretoria, 2020. / Gordon Institute of Business Science (GIBS) / DPhil / Unrestricted

Risk assessment is essential for nuclear power plants (NPPs) due to the complex dynamic nature of such systems-of-systems, as well as the devastating impacts of nuclear accidents on the environment, public health, and economy. Lessons learned from the Fukushima nuclear accident demonstrated the importance of enhancing current risk assessment methodologies and developing efficient early warning decision support tools. Static probabilistic risk assessment (PRA) techniques (e.g., event and fault tree analysis) have been extensively adopted in nuclear applications to ensure NPPs comply with safety regulations. However, numerous studies have highlighted the limitations of static PRA methods such as the lack of considering the dynamic hardware/software/operator interactions inside the NPP and the timing/sequence of events. In response, several dynamic probabilistic risk assessment (DPRA) methodologies have been developed and continuously evolved over the past four decades to overcome the limitations of static PRA methods. DPRA presents a comprehensive approach to assess the risks associated with complex, dynamic systems. However, current DPRA approaches are faced with challenges associated with the intra/interdependence within/between different NPP complex systems and the massive amount of data that needs to be analyzed and rapidly acted upon. In response to these limitations of previous work, the main objective of this dissertation is to develop a physics-based DPRA platform and an intelligent data-driven prediction tool for NPP safety enhancement under normal and abnormal operating conditions. The results of this dissertation demonstrate that the developed DPRA platform is capable of simulating the dynamic interaction between different NPP systems and estimating the temporal probability of core damage under different transients with significant analysis advantages from both the computational time and data storage perspectives. The developed platform can also explicitly account for uncertainties associated with the NPP's physical parameters and operating conditions on the plant's response and probability of its core damage. Furthermore, an intelligent decision support tool, developed based on artificial neural networks (ANN), can significantly improve the safety of NPPs by providing the plant operators with fast and accurate predictions that are specific to such NPP. Such rapid prediction will minimize the need to resort to idealized physics-based simulators to predict the underlying complex physical interactions. Moving forward, the developed ANN model can be trained under plant operational data, plants operating experience database, and data from rare event simulations to consider for example plant ageing with time, operational transients, and rare events in predicting the plant behavior. Such intelligent tool can be key for NPP operators and managers to take rapid and reliable actions under abnormal conditions. / Thesis / Doctor of Philosophy (PhD)