Due to environmental health and nutrient impact concerns, the conventional on-site sewage collection, treatment, and disposal systems are no longer able to meet the nutrient reduction requirements for wastewater effluent and may represent a large fraction of pollutant loads. The loads include not only nitrogen (N) and phosphorus (P), but also pathogens such as fecal coliform and E. coli which indicate the presence of other disease-causing bacteria flowing into aquatic system that adversely affect public health. A subsurface upflow wetland, which is an effective small-scale wastewater treatment system with low energy and maintenance requirements and operational costs, fits the current nutrient and pathogen removal situation having received wide attention throughout the world. Within this research study, a subsurface upflow wetland system (SUW), including four parallel SUW (three planted versus one unplanted), were constructed as a key component of the septic tank system receiving 454 liters per day (120 GPD) influent using the green sorption media along with selected plant species. It was proved effective in removing both nutrients and pathogens. During a one month test run, the planted wetlands achieved a removal efficiency of 84.2%, 97.3 %, 98.93 % and 99.92%, compared to the control wetland, 10.5%, 85.7 %, 99.74 % and 100.0 %, in total nitrogen (TN), total phosphorus (TP), fecal coli and E.Coli, respectively. Denitrification was proved to be the dominant pathway for removing N as evidenced by the mass balance and real-time PCR analyses. A simplified compartmental dynamics simulation model of constructed subsurface upflow wetlands was also developed to provide a dependable reference and tool for design of constructed subsurface upflow wetland.

Drinking water supply insecurity is globally on the rise, and prevalent in most low and middle-income urban areas. Multiple responses have emerged to cope with the lack of a reliable and equitable supply of safe and sufficient drinking water in cities, which presents a wide range of social-ecological implications. Yet, many of the analyses to date are focused on predominantly technological, ecological, and economic perspectives, overlooking broader cultural and political dimensions. What are the elements and the interrelationship between them that sustain the lack of drinking water supply security at an urban scale? The empirical case study is located in Mexico City, the capital city of one of the most drinking water-insecure countries globally and among the world’s five largest metropolitan areas. Qualitative data is elicited from a literature review and semi-structured interviews with key experts and urban stakeholders. The results provide an integrated understanding of the proposed system structure that created and maintain the water supply problem in the long-term. Hindrances include knowledge lock-ins and critical dynamics that inhibit the political support to transition towards a drinking water security scenario. This study shows that drinking water supply crisis in the study area and other cities with similar conditions need to be understood as multi-dimensional and from a system perspective, by challenging underlying assumptions and embracing interconnectedness. Key feedback mechanisms are presented in causal loop diagrams, allowing the exploration of higher-order leverage points to reduce existing path-dependencies as one increasingly important research area, and potentially relevant for decision-makers.

La transition énergétique, en partie caractérisée par le déploiement massif des énergies renouvelables, a relancé un débat de longue date sur les architectures de marché fournissant les meilleures incitations aux investissements dans les marchés libéralisés de l’électricité. Ces incitations sont essentielles pour garantir la sécurité d’approvisionnement à long terme. Pour choisir l’architecture de marché adéquate, les décideurs publics doivent évaluer et comparer les performances économiques des solutions disponibles. La présente thèse complète la littérature sur les incitations aux investissements et la sécurité d’approvisionnement en étudiant trois aspects importants : (i) le comportement des marchés de l'électricité en présence d’acteurs averses au risque, (ii) la compatibilité entre les incitations des acteurs à mettre leurs actifs sous cocon et les objectifs de sécurité d’approvisionnement et (iii) les performances économiques de différentes architectures de marché dans un contexte de forte pénétration des énergies renouvelables. Pour ce faire, une modélisation de type System Dynamics est utilisée pour représenter les dynamiques de long terme résultant des décisions des acteurs dans un marché libéralisé. La thèse est organisée en trois chapitres correspondant à chacun des points mentionnés ci-dessus. Les principaux résultats sont les suivants : Premièrement, les mécanismes de capacité sont nécessaires pour faire face aux effets néfastes de l’aversion au risque des investisseurs. Ce phénomène affecte de manière significative les marchés de l’énergie de type energy-only, qui subissent alors une baisse des investissements et des pénuries plus importantes. Les marchés de capacité résistent mieux à l’aversion au risque des investisseurs. Cependant, cette résilience dépend du plafond des prix dans les enchères de capacité. Pour qu'une telle architecture de marché donne des résultats satisfaisants en termes de sécurité d’approvisionnement, ce plafond de prix doit tenir compte du risque d'investissement supporté par les acteurs. Deuxièmement, si les acteurs du marché en ont la possibilité, leurs décisions de mettre leurs actifs sous cocon peuvent modifier les dynamiques d'investissement et de fermeture à long terme. En outre, dans un monde caractérisé par des actifs indivisibles, cette possibilité augmente le niveau de coordination nécessaire pour assurer la sécurité d’approvisionnement. Cela est particulièrement vrai pour les marchés de type energy-only, dans lesquels la mise sous cocon augmente le niveau des pénuries, au point de contrebalancer les économies de coûts qu’elle génère. En revanche, les marchés de capacité peuvent fournir la coordination nécessaire pour assurer la sécurité d’approvisionnement même lorsque les acteurs ont la possibilité de mettre leurs actifs sous cocon. Troisièmement, parmi les architectures de marché proposées dans la littérature, les marchés de capacité apparaissent comme la meilleure solution du point de vue du surplus social. Néanmoins, du point de vue des investisseurs, et dans certaines conditions liées à une forte pénétration des énergies renouvelables, les marchés de capacité avec des contrats annuels ne suppriment pas entièrement le problème dit de "missing money". Les résultats indiquent que l'attribution de contrats de capacité pluriannuels atténue le problème. / The ongoing energy transition, partly characterized by the massive deployment of renewables, has reignited a long-lasting debate on the best market design options to provide adequate investment incentives and ensure capacity adequacy in liberalised electricity markets. To choose the appropriate market design, policymakers need to assess and compare the economic performances of available solutions in terms of effectiveness and cost-efficiency. This dissertation complements the existing literature on market design for long-term capacity adequacy by focusing on three research topics: (i) understanding how electricity markets perform under different assumptions regarding investors’ risk preferences, (ii) analysing the compatibility of private agents’ incentives to mothball capacity resources with security of supply objectives and (iii) assessing the economic performance of different market designs in a context of a high penetration of renewables. To this end, the System Dynamics modelling framework is applied to represent long-term dynamics resulting from private agents’ decisions in liberalised electricity markets. The dissertation is organised in three chapters corresponding to each of the topics mentioned above. The main results are outlined below. Firstly, capacity remuneration mechanisms are necessary to deal with the detrimental effects of investors’ risk aversion. Energy-only markets are significantly affected by this phenomenon as they experience reduced investment incentives and higher levels of shortages. Capacity markets are more resilient to private investors’ risk aversion. However, this resilience depends on the level of the price cap in the capacity auctions. For such a market design to provide satisfactory outcomes in terms of capacity adequacy, this price cap should account for the investment risk faced by market participants. Secondly, when market participants have the possibility to mothball their capacity resources, these mothballing decisions can potentially modify investment and shutdown dynamics in the long run. Furthermore, in a world with capacity lumpiness (i.e. indivisibilities), mothballing increases the level of coordination needed to ensure capacity adequacy. This is especially true in energy-only markets, where mothballing increases the level of shortages to an extent that seems to overweigh the cost savings it generates at system level. Capacity markets can provide the required coordination to ensure capacity adequacy in a world with mothballing. Thirdly, among proposed market designs in the literature, capacity markets appear as the preferable solution to ensure capacity adequacy from a social welfare point of view. Nevertheless, from a private investor’s perspective and under certain conditions related to high penetration of renewables, capacity markets with annual contracts do not entirely remove the so-called “missing money” problem. The results indicate that granting multiannual capacity contracts alleviates the problem.

Les marchés électriques libéralisés sont supposés assurer la coordination de long terme des investissements afin de garantir sécurité d’approvisionnement, viabilité et compétitivité. Dans le modèle de référence energy-only, la formation des prix par alignement sur le coût variable de l’équipement marginal sur les marchés horaires successifs fournit un signal prix pour les investisseurs. Cependant, en pratique, ce modèle est remis en question quant à sa capacité à déclencher des investissements dans les technologies bas-carbone et en particulier les énergies renouvelables (EnR) et quant à sa capacité à garantir la sécurité d’approvisionnement. Cette thèse cherche d’abord à caractériser ces deux défaillances de marché puis s’intéresse à différentes solutions pour faire face à chacune d’entre elles. Pour cela, la réflexion s’appuie sur un modèle en System Dynamics développé afin de simuler les investissements dans les marchés électriques.D’une part, les résultats montrent que le remplacement des mécanismes de support hors marché par des investissements par le marché avec l’aide d’un prix du carbone apparait comme une solution pour déclencher le développement des EnR à condition d'un engagement politique fort en faveur d’un prix du carbone élevé. D’autre part, il apparait aussi que le marché energy-only avec des prix plafonnés ne parvient pas à assurer l’adéquation de capacité. L’ajout d’un marché de capacité ou la suppression du plafond de prix permettent une amélioration en termes de nombre d’heure de délestage et de bien-être collectif. De plus, le marché de capacité apparaît comme le meilleur choix pour le régulateur parmi les architectures de marché considérées. / In liberalised electricity systems, power markets are expected to ensure the long-term coordination of investments in order to guarantee security of supply, sustainability and competitiveness. In the reference energy-only market, it relies on the ability of power markets — where the hourly price is aligned with the marginal cost of the system — to provide an adequate price-signal for investors. However, in practice, questions have been raised about its ability to trigger investments in low-carbon technologies including in particular Renewable Energy Sources of Electricity (RES-E), and its ability to ensure capacity adequacy. After a characterisation of these market failures, this dissertation tackles the two research topics within a methodological framework based on a System Dynamics model developed to simulate private investment decisions in power markets.First, the results show that substituting out-of-market support mechanisms for RES-E by market-based investments helped by the sole implementation of a carbon price appears as a feasible solution to trigger RES-E development providing that there is a political commitment on a high carbon price. Second, it also appears that the energy-only market with price cap is ineffective to ensure capacity adequacy. Adding a capacity market or removing the price cap both bring benefits in terms of loss of load expectation and social welfare. Moreover, the capacity market is identified as the best option for regulators among the considered market designs.

Coal is a fossil fuel mineral, which is presently a major source of electricity and energy to industries. From past to present, there are many coal reserves around the world and large scale coal mining operates in various areas such as the USA, Russia, China, Australia, India, and Germany, etc. Thailand’s coal resources can be found in many areas; there are lignite mining in the north of Thailand, the currently operational Mae Moh Lignite Mine, and also coal reserves in the south of Thailand, such as Krabi and Songkhla, where mines are not yet operating. The main consumption of coal is in electricity production, which increases annually. In 2019, the Thai Government and Electricity Generating Authority of Thailand (EGAT) plans to run a 800 MW coal power plant at Krabi, which may run on imported coal, despite there being reserves of lignite at Krabi; the use of domestic coal is a last option because of social and environmental concerns about the effects of coal mining. There is a modern trend in mining projects, the responsibility of mining should cover not only the mining activity, but the social and environmental protection and mine closure activities which follow. Thus, the costs and decisions taken on by the mining company are increasingly complicated. To reach a decision on investment in a mining project is not easy; it is a complex process in which all variables are connected. Particularly, the responsibility of coal mining companies to society and the environment is a new topic. Thus, a tool to help to recognize and generate information for decision making is in demand and very important. In this thesis, the system dynamics model of coal mine planning is made by using Vensim Software and specifically designed to encompass many variables during the period of mining activity until the mine closure period. The decisions use economic criteria such as Net Present Value (NPV), Net Cash Flow (NCF), Payback Period (PP), and Internal Rate of Return (IRR), etc. Consequently, the development of the decision support system of coal mine planning as a tool is proposed. The model structure covers the coal mining area from mine reserves to mine closure. It is a fast and flexible tool to perform sensitivity analysis, and to determine an optimum solution. The model results are clear and easily understandable on whether to accept or reject the coal mine project, which helps coal mining companies make the right decisions on their policies, economics, and the planning of new coal mining projects. Furthermore, the model is used to analyse the case study of the Krabi coal-fired power plant in Thailand, which may possibly use the domestic lignite at Krabi. The scenario simulations clearly show some potential for the use of the domestic lignite. However, the detailed analysis of the Krabi Lignite Mine Project case shows the high possible risks of this project, and that this project is currently not feasible. Thus, the model helps to understand and confirm that the use of domestic lignite in Krabi for the Krabi Coal Power Plant Project is not suitable at this time. Therefore, the best choice is imported coal from other countries for supporting the Krabi Coal Power Plant Project. Finally, this tool successfully is a portable application software, which does not need to be installed on a computer, but can run directly in a folder of the existing application. Furthermore, it supports all versions of Windows OS.

Coal is a fossil fuel mineral, which is presently a major source of electricity and energy to industries. From past to present, there are many coal reserves around the world and large scale coal mining operates in various areas such as the USA, Russia, China, Australia, India, and Germany, etc. Thailand’s coal resources can be found in many areas; there are lignite mining in the north of Thailand, the currently operational Mae Moh Lignite Mine, and also coal reserves in the south of Thailand, such as Krabi and Songkhla, where mines are not yet operating. The main consumption of coal is in electricity production, which increases annually. In 2019, the Thai Government and Electricity Generating Authority of Thailand (EGAT) plans to run a 800 MW coal power plant at Krabi, which may run on imported coal, despite there being reserves of lignite at Krabi; the use of domestic coal is a last option because of social and environmental concerns about the effects of coal mining. There is a modern trend in mining projects, the responsibility of mining should cover not only the mining activity, but the social and environmental protection and mine closure activities which follow. Thus, the costs and decisions taken on by the mining company are increasingly complicated. To reach a decision on investment in a mining project is not easy; it is a complex process in which all variables are connected. Particularly, the responsibility of coal mining companies to society and the environment is a new topic. Thus, a tool to help to recognize and generate information for decision making is in demand and very important. In this thesis, the system dynamics model of coal mine planning is made by using Vensim Software and specifically designed to encompass many variables during the period of mining activity until the mine closure period. The decisions use economic criteria such as Net Present Value (NPV), Net Cash Flow (NCF), Payback Period (PP), and Internal Rate of Return (IRR), etc. Consequently, the development of the decision support system of coal mine planning as a tool is proposed. The model structure covers the coal mining area from mine reserves to mine closure. It is a fast and flexible tool to perform sensitivity analysis, and to determine an optimum solution. The model results are clear and easily understandable on whether to accept or reject the coal mine project, which helps coal mining companies make the right decisions on their policies, economics, and the planning of new coal mining projects. Furthermore, the model is used to analyse the case study of the Krabi coal-fired power plant in Thailand, which may possibly use the domestic lignite at Krabi. The scenario simulations clearly show some potential for the use of the domestic lignite. However, the detailed analysis of the Krabi Lignite Mine Project case shows the high possible risks of this project, and that this project is currently not feasible. Thus, the model helps to understand and confirm that the use of domestic lignite in Krabi for the Krabi Coal Power Plant Project is not suitable at this time. Therefore, the best choice is imported coal from other countries for supporting the Krabi Coal Power Plant Project. Finally, this tool successfully is a portable application software, which does not need to be installed on a computer, but can run directly in a folder of the existing application. Furthermore, it supports all versions of Windows OS.

System dynamics modelling has been used for around 40 years to address complex, systemic, dynamic problems, those often described as wicked. But, system dynamics modelling is not an exact science and arguments about the most suitable techniques to use in which circumstances, continues. The nature of these wicked problems is investigated through a series of case studies where poor situational awareness among stakeholders was identified. This was found to be an underlying cause for management failure, suggesting need for better ways of recognising and managing wicked problem situations. Human cognition is considered both as a limitation and enabler to decision-making in wicked problem environments. Naturalistic and deliberate decision-making are reviewed. The thesis identifies the need for integration of qualitative and quantitative techniques. Case study results and a review of the literature led to identification of a set of principles of method to be applied in an integrated framework, the aim being to develop an improved way of addressing wicked problems. These principles were applied to a series of cases in an action research setting. However, organisational and political barriers were encountered. This limited the exploitation and investigation of cases to varying degrees. In response to a need identified in the literature review and the case studies, a tool is designed to facilitate analysis of multi-factorial, non-linear causality. This unique tool and its use to assist in problem conceptualisation, and as an aid to testing alternate strategies, are demonstrated. Further investigation is needed in relation to the veracity of combining causal influences using this tool and system dynamics, broadly. System dynamics modelling was found to have utility needed to support analysis of wicked problems. However, failure in a particular modelling project occurred when it was found necessary to rely on human judgement in estimating values to be input into the models. This was found to be problematic and unacceptably risky for sponsors of the modelling effort. Finally, this work has also identified that further study is required into: the use of human judgement in decision-making and the validity of system dynamics models that rely on the quantification of human judgement.

System dynamics modelling has been used for around 40 years to address complex, systemic, dynamic problems, those often described as wicked. But, system dynamics modelling is not an exact science and arguments about the most suitable techniques to use in which circumstances, continues. The nature of these wicked problems is investigated through a series of case studies where poor situational awareness among stakeholders was identified. This was found to be an underlying cause for management failure, suggesting need for better ways of recognising and managing wicked problem situations. Human cognition is considered both as a limitation and enabler to decision-making in wicked problem environments. Naturalistic and deliberate decision-making are reviewed. The thesis identifies the need for integration of qualitative and quantitative techniques. Case study results and a review of the literature led to identification of a set of principles of method to be applied in an integrated framework, the aim being to develop an improved way of addressing wicked problems. These principles were applied to a series of cases in an action research setting. However, organisational and political barriers were encountered. This limited the exploitation and investigation of cases to varying degrees. In response to a need identified in the literature review and the case studies, a tool is designed to facilitate analysis of multi-factorial, non-linear causality. This unique tool and its use to assist in problem conceptualisation, and as an aid to testing alternate strategies, are demonstrated. Further investigation is needed in relation to the veracity of combining causal influences using this tool and system dynamics, broadly. System dynamics modelling was found to have utility needed to support analysis of wicked problems. However, failure in a particular modelling project occurred when it was found necessary to rely on human judgement in estimating values to be input into the models. This was found to be problematic and unacceptably risky for sponsors of the modelling effort. Finally, this work has also identified that further study is required into: the use of human judgement in decision-making and the validity of system dynamics models that rely on the quantification of human judgement.