Systematic Approach for the selection of monitoring technologies in CO2 geological storage projects. Application of multicriteria decision making

Geologic storage of carbon dioxide (CO2) has been proposed as a viable means for reducing anthropogenic CO2 emissions. Once injection begins, a program for measurement, monitoring, and verification (MMV) of CO2 distribution is required in order to: a) research key features, effects and processes needed for risk assessment; b) manage the injection process; c) delineate and identify leakage risk and surface escape; d) provide early warnings of failure near the reservoir; and f) verify storage for accounting and crediting. The selection of the methodology of monitoring (characterization of site and control and verification in the post-injection phase) is influenced by economic and technological variables. Multiple Criteria Decision Making (MCDM) refers to a methodology developed for making decisions in the presence of multiple criteria. MCDM as a discipline has only a relatively short history of 40 years, and it has been closely related to advancements on computer technology. Evaluation methods and multicriteria decisions include the selection of a set of feasible alternatives, the simultaneous optimization of several objective functions, and a decision-making process and evaluation procedures that must be rational and consistent. The application of a mathematical model of decision-making will help to find the best solution, establishing the mechanisms to facilitate the management of information generated by number of disciplines of knowledge. Those problems in which decision alternatives are finite are called Discrete Multicriteria Decision problems. Such problems are most common in reality and this case scenario will be applied in solving the problem of site selection for storing CO2. Discrete MCDM is used to assess and decide on issues that by nature or design support a finite number of alternative solutions. Recently, Multicriteria Decision Analysis has been applied to hierarchy policy incentives for CCS, to assess the role of CCS, and to select potential areas which could be suitable to store. For those reasons, MCDM have been considered in the monitoring phase of CO2 storage, in order to select suitable technologies which could be techno-economical viable. In this paper, we identify techniques of gas measurements in subsurface which are currently applying in the phase of characterization (pre-injection); MCDM will help decision-makers to hierarchy the most suitable technique which fit the purpose to monitor the specific physic-chemical parameter.

A decision model for it supplier selection

En los últimos años la externalización de TI ha ganado mucha importancia en el mercado y, por ejemplo, el mercado externalización de servicios de TI sigue creciendo cada año. Ahora más que nunca, las organizaciones son cada vez más los compradores de las capacidades necesarias mediante la obtención de productos y servicios de los proveedores, desarrollando cada vez menos estas capacidades dentro de la empresa. La selección de proveedores de TI es un problema de decisión complejo. Los gerentes que enfrentan una decisión sobre la selección de proveedores de TI tienen dificultades en la elaboración de lo que hay que pensar, además en sus discursos. También de acuerdo con un estudio del SEI (Software Engineering Institute) [40], del 20 al 25 por ciento de los grandes proyectos de adquisición de TI fracasan en dos años y el 50 por ciento fracasan dentro de cinco años. La mala gestión, la mala definición de requisitos, la falta de evaluaciones exhaustivas, que pueden ser utilizadas para llegar a los mejores candidatos para la contratación externa, la selección de proveedores y los procesos de contratación inadecuados, la insuficiencia de procedimientos de selección tecnológicos, y los cambios de requisitos no controlados son factores que contribuyen al fracaso del proyecto. La mayoría de los fracasos podrían evitarse si el cliente aprendiese a comprender los problemas de decisión, hacer un mejor análisis de decisiones, y el buen juicio. El objetivo principal de este trabajo es el desarrollo de un modelo de decisión para la selección de proveedores de TI que tratará de reducir la cantidad de fracasos observados en las relaciones entre el cliente y el proveedor. La mayor parte de estos fracasos son causados por una mala selección, por parte del cliente, del proveedor. Además de estos problemas mostrados anteriormente, la motivación para crear este trabajo es la inexistencia de cualquier modelo de decisión basado en un multi modelo (mezcla de modelos adquisición y métodos de decisión) para el problema de la selección de proveedores de TI. En el caso de estudio, nueve empresas españolas fueron analizadas de acuerdo con el modelo de decisión para la selección de proveedores de TI desarrollado en este trabajo. Dos softwares se utilizaron en este estudio de caso: Expert Choice, y D-Sight. ABSTRACT In the past few years IT outsourcing has gained a lot of importance in the market and, for example, the IT services outsourcing market is still growing every year. Now more than ever, organizations are increasingly becoming acquirers of needed capabilities by obtaining products and services from suppliers and developing less and less of these capabilities in-house. IT supplier selection is a complex and opaque decision problem. Managers facing a decision about IT supplier selection have difficulty in framing what needs to be thought about further in their discourses. Also according to a study from SEI (Software Engineering Institute) [40], 20 to 25 percent of large information technology (IT) acquisition projects fail within two years and 50 percent fail within five years. Mismanagement, poor requirements definition, lack of comprehensive evaluations, which can be used to come up with the best candidates for outsourcing, inadequate supplier selection and contracting processes, insufficient technology selection procedures, and uncontrolled requirements changes are factors that contribute to project failure. The majority of project failures could be avoided if the acquirer learns how to understand the decision problems, make better decision analysis, and good judgment. The main objective of this work is the development of a decision model for IT supplier selection that will try to decrease the amount of failures seen in the relationships between the client-supplier. Most of these failures are caused by a not well selection of the supplier. Besides these problems showed above, the motivation to create this work is the inexistence of any decision model based on multi model (mixture of acquisition models and decision methods) for the problem of IT supplier selection. In the case study, nine different Spanish companies were analyzed based on the IT supplier selection decision model developed in this work. Two software products were used in this case study, Expert Choice and D-Sight.

Participatory modelling to support decision making in water management under uncertainty: Two comparative case studies in the Guadiana river basin, Spain.

A participatory modelling process has been conducted in two areas of the Guadiana river (the upper and the middle sub-basins), in Spain, with the aim of providing support for decision making in the water management field. The area has a semi-arid climate where irrigated agriculture plays a key role in the economic development of the region and accounts for around 90% of water use. Following the guidelines of the European Water Framework Directive, we promote stakeholder involvement in water management with the aim to achieve an improved understanding of the water system and to encourage the exchange of knowledge and views between stakeholders in order to help building a shared vision of the system. At the same time, the resulting models, which integrate the different sectors and views, provide some insight of the impacts that different management options and possible future scenarios could have. The methodology is based on a Bayesian network combined with an economic model and, in the middle Guadiana sub-basin, with a crop model. The resulting integrated modelling framework is used to simulate possible water policy, market and climate scenarios to find out the impacts of those scenarios on farm income and on the environment. At the end of the modelling process, an evaluation questionnaire was filled by participants in both sub-basins. Results show that this type of processes are found very helpful by stakeholders to improve the system understanding, to understand each others views and to reduce conflict when it exists. In addition, they found the model an extremely useful tool to support management. The graphical interface, the quantitative output and the explicit representation of uncertainty helped stakeholders to better understand the implications of the scenario tested. Finally, the combination of different types of models was also found very useful, as it allowed exploring in detail specific aspects of the water management problems.

TITIM GIS-tool: A GIS-based decision support system for measuring the territorial impact of transport infrastructures

To achieve sustainability in the area of transport we need to view the decision-making process as a whole and consider all the most important socio-economic and environmental aspects involved. Improvements in transport infrastructures have a positive impact on regional development and significant repercussions on the economy, as well as affecting a large number of ecological processes. This article presents a DSS to assess the territorial effects of new linear transport infrastructures based on the use of GIS. The TITIM ? Transport Infrastructure Territorial Impact Measurement ? GIS tool allows these effects to be calculated by evaluating the improvement in accessibility, loss of landscape connectivity, and the impact on other local territorial variables such as landscape quality, biodiversity and land-use quality. The TITIM GIS tool assesses these variables automatically, simply by entering the required inputs, and thus avoiding the manual reiteration and execution of these multiple processes. TITIM allows researchers to use their own GIS databases as inputs, in contrast with other tools that use official or predefined maps. The TITIM GIS-tool is tested by application to six HSR projects in the Spanish Strategic Transport and Infrastructure Plan 2005?2020 (PEIT). The tool creates all 65 possible combinations of these projects, which will be the real test scenarios. For each one, the tool calculates the accessibility improvement, the landscape connectivity loss, and the impact on the landscape, biodiversity and land-use quality. The results reveal which of the HSR projects causes the greatest benefit to the transport system, any potential synergies that exist, and help define a priority for implementing the infrastructures in the plan

Utilizing the Internet of Things to promote energy awareness and efficiency at discrete production processes: Practices and methodology

El actual contexto de fabricación, con incrementos en los precios de la energía, una creciente preocupación medioambiental y cambios continuos en los comportamientos de los consumidores, fomenta que los responsables prioricen la fabricación respetuosa con el medioambiente. El paradigma del Internet de las Cosas (IoT) promete incrementar la visibilidad y la atención prestada al consumo de energía gracias tanto a sensores como a medidores inteligentes en los niveles de máquina y de línea de producción. En consecuencia es posible y sencillo obtener datos de consumo de energía en tiempo real proveniente de los procesos de fabricación, pero además es posible analizarlos para incrementar su importancia en la toma de decisiones. Esta tesis pretende investigar cómo utilizar la adopción del Internet de las Cosas en el nivel de planta de producción, en procesos discretos, para incrementar la capacidad de uso de la información proveniente tanto de la energía como de la eficiencia energética. Para alcanzar este objetivo general, la investigación se ha dividido en cuatro sub-objetivos y la misma se ha desarrollado a lo largo de cuatro fases principales (en adelante estudios). El primer estudio de esta tesis, que se apoya sobre una revisión bibliográfica comprehensiva y sobre las aportaciones de expertos, define prácticas de gestión de la producción que son energéticamente eficientes y que se apoyan de un modo preeminente en la tecnología IoT. Este primer estudio también detalla los beneficios esperables al adoptar estas prácticas de gestión. Además, propugna un marco de referencia para permitir la integración de los datos que sobre el consumo energético se obtienen en el marco de las plataformas y sistemas de información de la compañía. Esto se lleva a cabo con el objetivo último de remarcar cómo estos datos pueden ser utilizados para apalancar decisiones en los niveles de procesos tanto tácticos como operativos. Segundo, considerando los precios de la energía como variables en el mercado intradiario y la disponibilidad de información detallada sobre el estado de las máquinas desde el punto de vista de consumo energético, el segundo estudio propone un modelo matemático para minimizar los costes del consumo de energía para la programación de asignaciones de una única máquina que deba atender a varios procesos de producción. Este modelo permite la toma de decisiones en el nivel de máquina para determinar los instantes de lanzamiento de cada trabajo de producción, los tiempos muertos, cuándo la máquina debe ser puesta en un estado de apagada, el momento adecuado para rearrancar, y para pararse, etc. Así, este modelo habilita al responsable de producción de implementar el esquema de producción menos costoso para cada turno de producción. En el tercer estudio esta investigación proporciona una metodología para ayudar a los responsables a implementar IoT en el nivel de los sistemas productivos. Se incluye un análisis del estado en que se encuentran los sistemas de gestión de energía y de producción en la factoría, así como también se proporcionan recomendaciones sobre procedimientos para implementar IoT para capturar y analizar los datos de consumo. Esta metodología ha sido validada en un estudio piloto, donde algunos indicadores clave de rendimiento (KPIs) han sido empleados para determinar la eficiencia energética. En el cuarto estudio el objetivo es introducir una vía para obtener visibilidad y relevancia a diferentes niveles de la energía consumida en los procesos de producción. El método propuesto permite que las factorías con procesos de producción discretos puedan determinar la energía consumida, el CO2 emitido o el coste de la energía consumida ya sea en cualquiera de los niveles: operación, producto o la orden de fabricación completa, siempre considerando las diferentes fuentes de energía y las fluctuaciones en los precios de la misma. Los resultados muestran que decisiones y prácticas de gestión para conseguir sistemas de producción energéticamente eficientes son posibles en virtud del Internet de las Cosas. También, con los resultados de esta tesis los responsables de la gestión energética en las compañías pueden plantearse una aproximación a la utilización del IoT desde un punto de vista de la obtención de beneficios, abordando aquellas prácticas de gestión energética que se encuentran más próximas al nivel de madurez de la factoría, a sus objetivos, al tipo de producción que desarrolla, etc. Así mismo esta tesis muestra que es posible obtener reducciones significativas de coste simplemente evitando los períodos de pico diario en el precio de la misma. Además la tesis permite identificar cómo el nivel de monitorización del consumo energético (es decir al nivel de máquina), el intervalo temporal, y el nivel del análisis de los datos son factores determinantes a la hora de localizar oportunidades para mejorar la eficiencia energética. Adicionalmente, la integración de datos de consumo energético en tiempo real con datos de producción (cuando existen altos niveles de estandarización en los procesos productivos y sus datos) es esencial para permitir que las factorías detallen la energía efectivamente consumida, su coste y CO2 emitido durante la producción de un producto o componente. Esto permite obtener una valiosa información a los gestores en el nivel decisor de la factoría así como a los consumidores y reguladores. ABSTRACT In today‘s manufacturing scenario, rising energy prices, increasing ecological awareness, and changing consumer behaviors are driving decision makers to prioritize green manufacturing. The Internet of Things (IoT) paradigm promises to increase the visibility and awareness of energy consumption, thanks to smart sensors and smart meters at the machine and production line level. Consequently, real-time energy consumption data from the manufacturing processes can be easily collected and then analyzed, to improve energy-aware decision-making. This thesis aims to investigate how to utilize the adoption of the Internet of Things at shop floor level to increase energy–awareness and the energy efficiency of discrete production processes. In order to achieve the main research goal, the research is divided into four sub-objectives, and is accomplished during four main phases (i.e., studies). In the first study, by relying on a comprehensive literature review and on experts‘ insights, the thesis defines energy-efficient production management practices that are enhanced and enabled by IoT technology. The first study also explains the benefits that can be obtained by adopting such management practices. Furthermore, it presents a framework to support the integration of gathered energy data into a company‘s information technology tools and platforms, which is done with the ultimate goal of highlighting how operational and tactical decision-making processes could leverage such data in order to improve energy efficiency. Considering the variable energy prices in one day, along with the availability of detailed machine status energy data, the second study proposes a mathematical model to minimize energy consumption costs for single machine production scheduling during production processes. This model works by making decisions at the machine level to determine the launch times for job processing, idle time, when the machine must be shut down, ―turning on‖ time, and ―turning off‖ time. This model enables the operations manager to implement the least expensive production schedule during a production shift. In the third study, the research provides a methodology to help managers implement the IoT at the production system level; it includes an analysis of current energy management and production systems at the factory, and recommends procedures for implementing the IoT to collect and analyze energy data. The methodology has been validated by a pilot study, where energy KPIs have been used to evaluate energy efficiency. In the fourth study, the goal is to introduce a way to achieve multi-level awareness of the energy consumed during production processes. The proposed method enables discrete factories to specify energy consumption, CO2 emissions, and the cost of the energy consumed at operation, production and order levels, while considering energy sources and fluctuations in energy prices. The results show that energy-efficient production management practices and decisions can be enhanced and enabled by the IoT. With the outcomes of the thesis, energy managers can approach the IoT adoption in a benefit-driven way, by addressing energy management practices that are close to the maturity level of the factory, target, production type, etc. The thesis also shows that significant reductions in energy costs can be achieved by avoiding high-energy price periods in a day. Furthermore, the thesis determines the level of monitoring energy consumption (i.e., machine level), the interval time, and the level of energy data analysis, which are all important factors involved in finding opportunities to improve energy efficiency. Eventually, integrating real-time energy data with production data (when there are high levels of production process standardization data) is essential to enable factories to specify the amount and cost of energy consumed, as well as the CO2 emitted while producing a product, providing valuable information to decision makers at the factory level as well as to consumers and regulators.

Selecting crop models for decision making in wheat insurance

In crop insurance, the accuracy with which the insurer quantifies the actual risk is highly dependent on the availability on actual yield data. Crop models might be valuable tools to generate data on expected yields for risk assessment when no historical records are available. However, selecting a crop model for a specific objective, location and implementation scale is a difficult task. A look inside the different crop and soil modules to understand how outputs are obtained might facilitate model choice. The objectives of this paper were (i) to assess the usefulness of crop models to be used within a crop insurance analysis and design and (ii) to select the most suitable crop model for drought risk assessment in semi-arid regions in Spain. For that purpose first, a pre-selection of crop models simulating wheat yield under rainfed growing conditions at the field scale was made, and second, four selected models (Aquacrop, CERES- Wheat, CropSyst and WOFOST) were compared in terms of modelling approaches, process descriptions and model outputs. Outputs of the four models for the simulation of winter wheat growth are comparable when water is not limiting, but differences are larger when simulating yields under rainfed conditions. These differences in rainfed yields are mainly related to the dissimilar simulated soil water availability and the assumed linkages with dry matter formation. We concluded that for the simulation of winter wheat growth at field scale in such semi-arid conditions, CERES-Wheat and CropSyst are preferred. WOFOST is a satisfactory compromise between data availability and complexity when detail data on soil is limited. Aquacrop integrates physiological processes in some representative parameters, thus diminishing the number of input parameters, what is seen as an advantage when observed data is scarce. However, the high sensitivity of this model to low water availability limits its use in the region considered. Contrary to the use of ensembles of crop models, we endorse that efforts be concentrated on selecting or rebuilding a model that includes approaches that better describe the agronomic conditions of the regions in which they will be applied. The use of such complex methodologies as crop models is associated with numerous sources of uncertainty, although these models are the best tools available to get insight in these complex agronomic systems.

Proceso metodológico para optimizar la toma de decisiones en el proyecto de envolventes arquitectónicas multicapa = Methodological process for the optimization of the decision making in multilayer building envelope projects

La presente tesis doctoral se enmarca dentro del concepto de la sistematización del conocimiento en arquitectura, más concretamente en el campo de las construcciones arquitectónicas y la toma de decisiones en la fase de proyecto de envolventes arquitectónicas multicapa. Por tanto, el objetivo principal es el establecimiento de las bases para una toma de decisiones informadas durante el proyecto de una envolvente multicapa con el fin de colaborar en su optimización. Del mismo modo que la historia de la arquitectura está relacionada con la historia de la innovación en construcción, la construcción está sujeta a cambios como respuesta a los fracasos anteriores. En base a esto, se identifica la toma de decisiones en la fase de proyecto como el estadio inicial para establecer un punto estratégico de reflexión y de control sobre los procesos constructivos. La presente investigación, conceptualmente, define los parámetros intervinientes en el proyecto de envolventes arquitectónicas multicapa a partir de una clasificación y sistematización de todos los componentes (elementos, unidades y sistemas constructivos) utilizados en las fachadas multicapa. Dicha sistematización se materializa en una hoja matriz de datos en la que, dentro de una organización a modo de árbol, se puede acceder a la consulta de cada componente y de su caracterización. Dicha matriz permite la incorporación futura de cualquier componente o sistema nuevo que aparezca en el mercado, relacionándolo con aquellos con los que comparta ubicación, tipo de material, etc. Con base en esa matriz de datos, se diseña la sistematización de la toma de decisiones en la fase de proyecto de una envolvente arquitectónica, en concreto, en el caso de una fachada. Operativamente, el resultado se presenta como una herramienta que permite al arquitecto o proyectista reflexionar y seleccionar el sistema constructivo más adecuado, al enfrentarse con las distintas decisiones o elecciones posibles. La herramienta se basa en las elecciones iniciales tomadas por el proyectista y se estructura, a continuación y sucesivamente, en distintas aproximaciones, criterios, subcriterios y posibilidades que responden a los distintos avances en la definición del sistema constructivo. Se proponen una serie de fichas operativas de comprobación que informan sobre el estadio de decisión y de definición de proyecto alcanzados en cada caso. Asimismo, el sistema permite la conexión con otros sistemas de revisión de proyectos para fomentar la reflexión sobre la normalización de los riesgos asociados tanto al proprio sistema como a su proceso constructivo y comportamiento futuros. La herramienta proporciona un sistema de ayuda para ser utilizado en el proceso de toma de decisiones en la fase de diseño de una fachada multicapa, minimizando la arbitrariedad y ofreciendo una cualificación previa a la cuantificación que supondrá la elaboración del detalle constructivo y de su medición en las sucesivas fases del proyecto. Al mismo tiempo, la sistematización de dicha toma de decisiones en la fase del proyecto puede constituirse como un sistema de comprobación en las diferentes fases del proceso de decisión proyectual y de definición de la envolvente de un edificio. ABSTRACT The central issue of this doctoral Thesis is founded on the framework of the concept of the systematization of knowledge in architecture, in particular, in respect of the field of building construction and the decision making in the design stage of multilayer building envelope projects. Therefore, the main objective is to establish the bases for knowledgeable decision making during a multilayer building envelope design process, in order to collaborate with its optimization. Just as the history of architecture is connected to the history of innovation in construction, construction itself is subject to changes as a response to previous failures. On this basis, the decisions made during the project design phase are identified as the initial state to establish an strategic point for reflection and control, referred to the constructive processes. Conceptually, this research defines the parameters involving the multilayer building envelope projects, on the basis of a classification and systematization for all the components (elements, constructive units and constructive systems) used in multilayer façades. The mentioned systematization is materialized into a data matrix sheet in which, following a tree‐like organization, the access to every single component and its characterization is possible. The above data matrix allows the future inclusion of any new component or system that may appear in the construction market. That new component or system can be put into a relationship with another, which it shares location, type of material,… with. Based on the data matrix, the systematization of the decision making process for a building envelope design stage is designed, more particularly in the case of a façade. Putting this into practice, it is represented as a tool which allows the architect or the designer, to reflect and to select the appropriate building system when facing the different elections or the different options. The tool is based on the initial elections taken by the designer. Then and successively, it is shaped on the form of different operative steps, criteria, sub‐criteria and possibilities which respond to a different progress in the definition of the building construction system. In order to inform about the stage of the decision and the definition reached by the project in every particular case, a range of operative sheets are proposed. Additionally, the system allows the connection with other reviewing methods for building projects. The aim of this last possibility is to encourage the reflection on standardization of the associated risks to the building system itself and its future performance. The tool provides a helping system to be used during the decision making process for a multilayer façade design. It minimizes the arbitrariness and offers a qualification previous to the quantification that will be done with the development of the construction details and their bill of quantities, that in subsequent project stages will be executed. At the same time, the systematization of the mentioned decision making during the design phase, can be found as a checking system in the different stages of the decision making design process and in the different stages of the building envelope definition.

Instruments for analysing urban conflicts in the Global South: The case of urban transformation processes in Dakar

Physical and social transformation processes that take place in urban contexts with strong spatial growth and hardly any economic development frequently have significant adverse impacts for the affected people, which tend to be made invisible. This paper presents an analytical framework to explore different ways to approach urban transformation processes (supply side), their impacts on the set of needs of the community (demand side) and their consequences on the urban environment as a whole (context). The proposed method has been used to assess three actions related to the physical and social transformation of the largest self-made settlement in the city of Dakar, Senegal, during the 2005–2012 period. Research findings show how exogenous interests are privileged over the common good when the affected citizens are not effectively involved in decision-making processes.