A contribution to support decision making in energy/water sypply chain optimisation

The seeking of process sustainability forces enterprises to change their operations. Additionally, the industrial globalization implies a very dynamic market that, among other issues, promotes the enterprises competition. Therefore, the efficient control and use of their Key Performance Indicators, including profitability, cost reduction, demand satisfaction and environmental impact associated to the development of new products, is a significant challenge. All the above indicators can be efficiently controlled through the Supply Chain Management. Thus, companies work towards the optimization of their individual operations under competitive environments taking advantage of the flexibility provided by the virtually inexistent world market restrictions. This is achieved by the coordination of the resource flows, across all the entities and echelons belonging to the system network. Nevertheless, such coordination is significantly complicated if considering the presence of uncertainty and even more if seeking for a win-win outcome. The purpose of this thesis is extending the current decision making strategies to expedite these tasks in industrial processes. Such a contribution is based on the development of efficient mathematical models that allows coordinating large amount of information synchronizing the production and distribution tasks in terms of economic, environmental and social criteria. This thesis starts presents an overview of the requirements of sustainable production processes, describing and analyzing the current methods and tools used and identifying the most relevant open issues. All the above is always within the framework of Process System Engineering literature. The second part of this thesis is focused in stressing the current Multi-Objective solution strategies. During this part, first explores how the profitability of the Supply Chain can be enhanced by considering simultaneously multiple objectives under demand uncertainties. Particularly, solution frameworks have been proposed in which different multi-criteria decision making strategies have been combined with stochastic approaches. Furthermore, additional performance indicators (including financial and operational ones) have been included in the same solution framework to evaluate its capabilities. This framework was also applied to decentralized supply chains problems in order to explore its capabilities to produce solution that improves the performances of each one of the SC entities simultaneously. Consequently, a new generalized mathematical formulation which integrates many performance indicators in the production process within a supply chain is efficiently solved. Afterwards, the third part of the thesis extends the proposed solution framework to address the uncertainty management. Particularly, the consideration of different types and sources of uncertainty (e.g. external and internal ones) where considered, through the implementation of preventive approaches. This part also explores the use of solution strategies that efficiently selects the number of scenarios that represent the uncertainty conditions. Finally, the importance and effect of each uncertainty source over the process performance is detailed analyzed through the use of surrogate models that promote the sensitivity analysis of those uncertainties. The third part of this thesis is focused on the integration of the above multi-objective and uncertainty approaches for the optimization of a sustainable Supply Chain. Besides the integration of different solution approaches, this part also considers the integration of hierarchical decision levels, by the exploitation of mathematical models that assess the consequences of considering simultaneously design and planning decisions under centralized and decentralized Supply Chains. Finally, the last part of this thesis provides the final conclusions and further work to be developed.La globalización industrial genera un ambiente dinámico en los mercados que, entre otras cosas, promueve la competencia entre corporaciones. Por lo tanto, el uso eficiente de las los indicadores de rendimiento, incluyendo rentabilidad, satisfacción de la demanda y en general el impacto ambiental, representa un area de oportunidad importante. El control de estos indicadores tiene un efecto positivo si se combinan con la gestión de cadena de suministro. Por lo tanto, las compañías buscan definir sus operaciones para permanecer activas dentro de un ambiente competitivo, tomando en cuenta las restricciones en el mercado mundial. Lo anterior puede ser logrado mediante la coordinación de los flujos de recursos a través de todas las entidades y escalones pertenecientes a la red del sistema. Sin embargo, dicha coordinación se complica significativamente si se quiere considerar la presencia de incertidumbre, y aún más, si se busca exclusivamente un ganar-ganar. El propósito de esta tesis es extender el alcance de las estrategias de toma de decisiones con el fin de facilitar estas tareas dentro de procesos industriales. Estas contribuciones se basan en el desarrollo de modelos matemáticos eficientes que permitan coordinar grandes cantidades de información sincronizando las tareas de producción y distribución en términos económicos, ambientales y sociales. Esta tesis inicia presentando una visión global de los requerimientos de un proceso de producción sostenible, describiendo y analizando los métodos y herramientas actuales así como identificando las áreas de oportunidad más relevantes dentro del marco de ingeniería de procesos La segunda parte se enfoca en enfatizar las capacidades de las estrategias de solución multi-objetivo, durante la cual, se explora el mejoramiento de la rentabilidad de la cadena de suministro considerando múltiples objetivos bajo incertidumbres en la demanda. Particularmente, diferentes marcos de solución han sido propuestos en los que varias estrategias de toma de decisión multi-criterio han sido combinadas con aproximaciones estocásticas. Por otra parte, indicadores de rendimiento (incluyendo financiero y operacional) han sido incluidos en el mismo marco de solución para evaluar sus capacidades. Este marco fue aplicado también a problemas de cadenas de suministro descentralizados con el fin de explorar sus capacidades de producir soluciones que mejoran simultáneamente el rendimiento para cada uno de las entidades dentro de la cadena de suministro. Consecuentemente, una nueva formulación que integra varios indicadores de rendimiento en los procesos de producción fue propuesta y validada. La tercera parte de la tesis extiende el marco de solución propuesto para abordar el manejo de incertidumbres. Particularmente, la consideración de diferentes tipos y fuentes de incertidumbre (p.ej. externos e internos) fueron considerados, mediante la implementación de aproximaciones preventivas. Esta parte también explora el uso de estrategias de solución que elige eficientemente el número de escenarios necesario que representan las condiciones inciertas. Finalmente, la importancia y efecto de cada una de las fuentes de incertidumbre sobre el rendimiento del proceso es analizado en detalle mediante el uso de meta modelos que promueven el análisis de sensibilidad de dichas incertidumbres. La tercera parte de esta tesis se enfoca en la integración de las metodologías de multi-objetivo e incertidumbre anteriormente expuestas para la optimización de cadenas de suministro sostenibles. Además de la integración de diferentes métodos. Esta parte también considera la integración de diferentes niveles jerárquicos de decisión, mediante el aprovechamiento de modelos matemáticos que evalúan lasconsecuencias de considerar simultáneamente las decisiones de diseño y planeación de una cadena de suministro centralizada y descentralizada. La parte final de la tesis detalla las conclusiones y el trabajo a futuro necesario sobre esta línea de investigaciónPostprint (published version

MODEL DEVELOPMENT AND SYSTEM OPTIMIZATION TO MINIMIZE GREENHOUSE GAS EMISSIONS FROM WASTEWATER TREATMENT PLANTS

As greenhouse gas emissions (GHG) reduction has drawn considerable attention, various methods have been established to estimate greenhouse gas emissions from wastewater treatment plants (WWTPs). In order to establish a design and operational strategy for GHG mitigation, accurate estimates are essential. However, the existing approaches (e.g. the IPCC protocol and national greenhouse gas inventories) do not cover emissions from all sources in WWTPs and are not sufficient to predict facility-level emissions. The ultimate goal of this research was to improve the quantification of GHG emissions from WWTPs. This was accomplished by creating a new mathematical model based on an existing activated sludge model. The first part of the research proposed a stepwise methodology using elemental balances in order to derive stoichiometry for state variables used in a mass balance based whole-plant wastewater treatment plant model. The two main advantages of the elemental balance method are the inclusion of carbon dioxide (CO2) into the existing model with no mass loss and ease of tracking elemental pathways. The second part of the research developed an integrated model that includes (1) a direct emission model for onsite emissions from treatment processes and (2) an indirect emission model for offsite emissions caused by plant operation. A sensitivity analysis of the proposed model was conducted to identify key input parameters. An uncertainty analysis was also carried out using a Monte Carlo simulation, which provided an estimate of the potential variability in GHG estimations. Finally, in the third part, the research identified an optimal operational strategy that resulted in minimizing operating costs and GHG emission, while simultaneously treating the wastewater at better levels. To do this, an integrated performance index (IPI) was proposed to combine the three criteria. The IPI was then incorporated into an optimization algorithm. The results obtained in this research demonstrated that the variation of GHG emissions is significant across the range of practical operational conditions. With system optimization, however, WWTPs have the potential to reduce GHG emissions without raising operating costs or reducing effluent quality. Further research should include a mechanistic examination of processes that produce methane (CH4) in the wastewater treatment stream and nitrous oxide (N2O) in the sludge treatment stream

Wastewater irrigation and health: assessing and mitigating risk in low-income countries

Wastewater irrigation / Public health / Health hazards / Risk assessment / Epidemiology / Sewage sludge / Excreta / Diseases / Vegetables / Leaf vegetables / Economic impact / Wastewater treatment / Irrigation methods / Developing countries

A decision support system for integrated semi-centralised urban wastewater treatment systems

The importance of adequate water supply and sanitation infrastructure as cornerstones for the development of civilizations is undeniable. Although a strategy based on centralised infrastructure has proven to be successful in the past, in some circumstances such conventional systems are inappropriate for future needs. A Semi-centralised Urban Wastewater Treatment System (SUWWTS) may be considered a viable sustainable urban water management solution to promote water security. A SUWWTS merges regulations of traditional centralised systems with the concepts of close-loop and resource recovery of decentralised systems. However, research on the design and feasibility of implementing semi-centralised systems is in its infancy. This Thesis is a first attempt to articulate the complexity, to systematize and to automatize the design of a SUWWTS. Here we show a novel method, referred to as framework, for the development of SUWWTS with allowance for the socio-economic and geographic context of any urban area. To demonstrate the proposed framework a Decision Support System (DSS) was developed; its output is a recommended design comprised of several wastewater treatment plants, their respective technology, and their associated sewerage and reclaimed water distribution networks. The results demonstrate the capabilities and the usefulness of the DSS; it applies the design engineers’ subjective preferences, such as regional technological inclinations and implementation strategies. The results from a feasibility study on the city of Rio de Janeiro validated and demonstrated how the DSS can be used to assist decision-makers. This Thesis discusses the framework, the DSS and the demonstration case. Overall, it will hopefully help both other researchers and practitioners by contributing to the discussion on how to promote urban water security, to decrease urban areas’ dependency on ecosystem services whilst delivering better social welfare

Water Integration for Squamscott Exeter (WISE): Preliminary Integrated Plan, Final Technical Report

This document introduces the goals, background and primary elements of an Integrated Plan for the Lower Exeter and Squamscott River in the Great Bay estuary in southern New Hampshire. This Plan will support management of point (wastewater treatment plant) and nonpoint sources in the communities of Exeter, Stratham and Newfields. The Plan also identifies and quantifies the advantages of the use of green infrastructure as a critical tool for nitrogen management and describes how collaboration between those communities could form the basis for an integrated plan. The Plan will help communities meet new wastewater and proposed stormwater permit requirements. Critical next steps are need before this Plan will fulfill the 2018 Nitrogen Control Plan requirements for Exeter and proposed draft MS4 requirements for both Stratham and Exeter. These next steps include conducting a financial capability assessment, development of an implementation schedule and development of a detailed implementation plan. The collaborative process used to develop this Plan was designed to provide decision makers at the local, state and federal levels with the knowledge they need to trust the Plan’s findings and recommendations, and to enable discussions between stakeholders to continue the collaborative process. This Plan includes the following information to guide local response to new federal permit requirements for treating and discharging stormwater and wastewater: Sources of annual pollutant load quantified by type and community; Assessment and evaluation of different treatment control strategies for each type of pollutant load; Assessment and evaluation of nutrient control strategies designed to reduce specific types of pollutants; Evaluation of a range of point source controls at the wastewater treatment facility based on regulatory requirements; Costs associated with a range of potential control strategies to achieve reduction of nitrogen and other pollutants of concern; and A preliminary implementation schedule with milestones for target load reductions using specific practices for specific land uses at points in time; Recommendations on how to implement a tracking and accounting program to document implementation; Design tools such as BMP performance curves for crediting the use of structural practices to support nitrogen accounting requirements; and Next Steps for how to complete this Plan

Optimisation-based methodology for the design and operation of sustainable wastewater treatment facilities

The treatment of municipal and industrial wastewaters in conventional wastewater treatment plants (WWTPs) requires a significant amount of energy in order to meet ever more stringent discharge regulations. However, the wastewater treatment industry is undergoing a paradigm shift from a focus on waste-stream treatment and contaminant removal to a proactive interest in energy and resource recovery facilities, driven by both economic and environmental incentives. The main objective of this thesis is the development of a decision-making tool in order to identify improvement opportunities in existing WWTPs and to develop new concepts of sustainable wastewater treatment/recovery facilities. The first part of the thesis presents the application of a model-based methodology based on systematic optimisation for improved understanding of the tight interplay between effluent quality, energy use, and fugitive emissions in existing WWTPs. Plant-wide models are developed and calibrated in an objective to predict the performance of two conventional activated sludge plants owned and operated by Sydney Water, Australia. In the first plant, a simulation-based approach is applied to quantify the effect of key operating variables on the effluent quality, energy use, and fugitive emissions. The results show potential for reduced consumption of energy (up to 10-20%) through operational changes only, without compromising effluent quality. It is also found that nitrate (and hence total nitrogen) discharge could be signficantly reduced from its current level with a small increase in energy consumption. These results are also compared to an upgraded plant with reverse osmosis in terms of energy consumption and greenhouse gas emissions. In the second plant, a systematic model-based optimisation approach is applied to investigate the effect of key discharge constraints on the net power consumption. The results show a potential for reduction of energy (20-25%), without compromising the current effluent quality. The nitrate discharge could be reduced from its current level to less than 15 mg/L with no increase in net power consumption and could be further reduced to <5 mg/L subject to a 18% increase in net power consumption upon the addition of an external carbon source. This improved understanding of the relationship between nutrient removal and energy use for these two plants will feed into discussions with environmental regulators regarding nutrient discharge licensing.The second part of the thesis deals with the application of a systematic, model-based methodology for the development of wastewater treatment/resource recovery systems that are both economically and environmentally sustainable. With the array of available treatment and recovery options growing steadily, a superstructure modeling approach based on rigorous mathematical optimisation provides a natural approach for tackling these problems. The development of reliable, yet simple, performance and cost models is a key issue with this approach in order to allow for a reliable solution based on global optimisation. it is argued that commercial wastewater simulators can be used to derive such models. The superstructure modeling framework is also able to account for wastewater and sludge treatment in an integrated system and to incorporate LCA with multi-objective optimisation to identify the inherent trade-off between multiple economic and environmental objectives. This approach is illustrated with two case studies of resource recovery from industrial and municipal wastewaters. The results establish that the proposed methodology is computationally tractable, thereby supporting its application as a decision support system for selection of promising wastewater treatment/resource recovery systems whose development is worth pursuing. Our analysis also suggests that accounting for LCA considerations early on in the design process may lead to dramatic changes in the configuration of future wastewater treatment/recovery facilities.Open Acces

Invited review: Models for the optimization of regional wastewater treatment systems

European Journal of Operational Research, nº 73 (1994)The problem of the optimization of regional wastewater systems may be generally formulated as follows: to define the transport and treatment system, in a region or water basin, which assure compliance with given pollution control criteria, with minimum cost. In addition, one may try to satisfy other objectives, such as minimum environmental impact, better effluent reuse or adequate phasing. From the optimization point of view, the two main problems that render the solution difficult are the dimensionality and the concavity of cost functions. The matter has been dealt with by many authors, who have produced varied techniques to try to solve this problem. This paper begins with a brief review of the work of those authors who have produced models specifically designed to study the problem. Then, solution strategies are discussed concerning three major items: definition of the objective function and constraints, optimization method and practical aplicability of the models. The paper concludes with the discussion of topics for future research

Reliable, resilient and sustainable urban drainage systems: an analysis of robustness under deep uncertainty (article)

This is the author accepted manuscript. The final version is available from the American Chemical Society via the DOI in this record.The dataset associated with this article is available in ORE at: https://doi.org/10.24378/exe.563Reliability, resilience and sustainability are key goals of any urban drainage system. However, only a few studies have recently focused on measuring, operationalizing and comparing such concepts in a world of deep uncertainty. In this study, these key concepts are defined and quantified for a number of gray, green and hybrid strategies, aimed at improving the capacity issues of an existing integrated urban wastewater system. These interventions are investigated by means of a regret-based approach, which evaluates the robustness (that is the ability to perform well under deep uncertainty conditions) of each strategy in terms of the three qualities through integration of multiple objectives (i.e. sewer flooding, river water quality, combined sewer overflows, river flooding, greenhouse gas emissions, cost and acceptability) across four different future scenarios. The results indicate that strategies found to be robust in terms of sustainability were typically also robust for resilience and reliability across future scenarios. However, strategies found to be robust in terms of their resilience and, in particular, for reliability did not guarantee robustness for sustainability. Conventional gray infrastructure strategies were found to lack robustness in terms of sustainability due to their unbalanced economic, environmental and social performance. Such limitations were overcome, however, by implementing hybrid solutions that combine green retrofits and gray rehabilitation solutions.This study was funded by the UK Engineering and Physical Sciences Research Council through STREAM (EP/G037094/1) with Northumbrian Water Limited, BRIM (EP/N010329/1) and the final author’s fellowship Safe & SuRe (EP/K006924/1)