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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

The impact of innovative effluent permitting policy on urban wastewater system performance

Meng, Fanlin January 2015 (has links)
This thesis investigates innovative effluent point-source permitting approaches from an integrated urban wastewater system (UWWS) perspective, and demonstrates that three proposed permitting approaches based on optimal operational or control strategies of the wastewater system are effective in delivering multiple and balanced environmental benefits (water quality, GHG emissions) in a cost-efficient manner. Traditional permitting policy and current flexible permitting practices are first reviewed, and opportunities for permitting from an integrated UWWS perspective are identified. An operational strategy-based permitting approach is first developed by a four-step permitting framework. Based on integrated UWWS modelling, operational strategies are optimised with objectives including minimisation of operational cost, variability of treatment efficiency and environmental risk, subject to compliance of environmental water quality standards. As trade-offs exist between the three objectives, the optimal solutions are screened according to the decision-makers’ preference and permits are derived based on the selected solutions. The advantages of this permitting approach over the traditional regulatory method are: a) cost-effectiveness is considered in decision-making, and b) permitting based on operational strategies is more reliable in delivering desirable environmental outcomes. In the studied case, the selected operational strategies achieve over 78% lower environmental risk with at least 7% lower operational cost than the baseline scenario; in comparison, the traditional end-of-pipe limits can lead to expensive solutions with no better environmental water quality. The developed permitting framework facilitates the derivation of sustainable solutions as: a) stakeholders are involved at all points of the decision-making process, so that various impacts of the operation of the UWWS can be considered, and b) multi-objective optimisation algorithm and visual analytics tool are employed to efficiently optimise and select high performance operational solutions. The second proposed permitting approach is based on optimal integrated real time control (RTC) strategies. Permits are developed by a three-step decision-making analysis framework similar to the first approach. An off-line model-based predictive aeration control strategy is investigated for the case study, and further benefits (9% lower environmental risk and 0.6% less cost) are achieved by an optimal RTC strategy exploiting the dynamic assimilation capacity of the environment. A similar permitting approach, but simpler than the first two methods, is developed to derive operational/control strategy-based permits by an integrated cost-risk analysis framework. Less comprehensive modelling and optimisation skills are needed as it couples a dynamic wastewater system model and a stochastic permitting model and uses sensitivity analysis and scenario analysis to optimise operational/control strategies, hence this approach can be a good option to develop risk-based cost-effective permits without intensive resources. Finally, roadmaps for the implementation of the three innovative permitting approaches are discussed. Current performance-based regulations and self-monitoring schemes are used as examples to visualise the new way of permitting. The viability of the proposed methods as alternative regulation approaches are evaluated against the core competencies of modern policy-making.
2

Management of industrial wastewater discharges in river basins through agents'argumentation

Aulinas Masó, Montse 14 October 2009 (has links)
La gestió de l'aigua residual és una tasca complexa. Hi ha moltes substàncies contaminants conegudes però encara moltes per conèixer, i el seu efecte individual o col·lgectiu és difícil de predir. La identificació i avaluació dels impactes ambientals resultants de la interacció entre els sistemes naturals i socials és un assumpte multicriteri. Els gestors ambientals necessiten eines de suport pels seus diagnòstics per tal de solucionar problemes ambientals.Les contribucions d'aquest treball de recerca són dobles: primer, proposar l'ús d'un enfoc basat en la modelització amb agents per tal de conceptualitzar i integrar tots els elements que estan directament o indirectament involucrats en la gestió de l'aigua residual. Segon, proposar un marc basat en l'argumentació amb l'objectiu de permetre als agents raonar efectivament. La tesi conté alguns exemples reals per tal de mostrar com un marc basat amb agents que argumenten pot suportar diferents interessos i diferents perspectives. Conseqüentment, pot ajudar a construir un diàleg més informat i efectiu i per tant descriure millor les interaccions entre els agents. En aquest document es descriu primer el context estudiat, escalant el problema global de la gestió de la conca fluvial a la gestiódel sistema urbà d'aigües residuals, concretament l'escenari dels abocaments industrials. A continuació, s'analitza el sistema mitjançant la descripció d'agents que interaccionen. Finalment, es descriuen alguns prototips capaços de raonar i deliberar, basats en la lògica no monòtona i en un llenguatge declaratiu (answer set programming).És important remarcar que aquesta tesi enllaça dues disciplines: l'enginyeria ambiental (concretament l'àrea de la gestió de les aigües residuals) i les ciències de la computació (concretament l'àrea de la intel·ligència artificial), contribuint així a la multidisciplinarietat requerida per fer front al problema estudiat. L'enginyeria ambiental ens proporciona el coneixement del domini mentre que les ciències de la computació ens permeten estructurar i especificar aquest coneixement. / Wastewater management is a very complex task. There is a high number of known and an increasing number of unknown pollutants whose individual and collective effects are very difficult to predict. Identifying and evaluating the impacts of environmental problems resulting from the interactions between our social system and its natural environment is a multifaceted critical issue. Environmental managers require tools to support their diagnoses for solving these problems. The contributions of this research work are twofold: first, to propose the use of an agent-based modelling approach in order to conceptualize and integrate all elements that are directly or indirectly involved in wastewater management. Second, to propose a framework based on argumentation that allows to reason effectively. The thesis provide some real examples to show that an agent-based argumentation framework can deal with multiple interests and different agents' perspectives and goals. This help to build a more effective and informed dialog in order to better describe the interaction between agents. In this document we first describe the context under study, scaling down the global river basins system to the urban wastewater systems and giving some more details for the specific scenario of industrial wastewater discharges. Then, we analyze the system in describing intelligent agents that interact. Finally, we propose some reasoning and deliberation prototypes by using an argumentation framework founded on non-monotonic logics (i.e. permitting to learn things that were previously not known) and the answer set programming specification language (i.e. a declarative programming language). It is important to remark that this thesis links two disciplines: environmental engineering (specifically the area of wastewater management) and computer science (specifically the area of artificial intelligence), contributing to the required multidsciplinarity needed to confront the complexity of the problem under study. From environmental engineering we obtain the domain knowledge whereas the computer science field permits us to structure and specify this knowledge.

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